Keywords: composé phénolique, accepteur d'électrons, dihydrogène, méthane, production animale, microbiote du rumen III phenolic compound, electron acceptor, dihydrogen, methane, animal production, rumen microbiota

I RÉSUMÉ Le secteur de l'élevage est une source majeure de méthane d'origine anthropique, un facteur du réchauffement climatique. Tandis que les stratégies disponibles peuvent réduire les émissions de méthane d'environ 25 %, la diminution de la méthanogenèse ne profite pas facilement à l'animal hôte car l'énergie de l'aliment correspondant au méthane perdu n'est pas récupérée à des fins productives. Dans le rumen, les micro-organismes fermentent les glucides, produisant des acides gras volatils (AGV) ainsi que des équivalents réducteurs, principalement sous forme de dihydrogène. Les méthanogènes du rumen utilisent le CO2 comme principal accepteur d'électrons, qui réagit avec le dihydrogène pour générer du méthane. D'autres voies métaboliques hydrogénotrophes existent également. Nous avons postulé que si la méthanogenèse est inhibée, la supplémentation en un accepteur d'électrons externe pourrait encourager des voies hydrogénotrophes générant des nutriments tels que les AGV, améliorant ainsi la production animale. Cette thèse visait à explorer le potentiel des composés phénoliques en tant qu'accepteurs d'électrons et leur aptitude à optimiser la production animale lorsque la méthanogenèse est inhibée. Nous avons évalué divers composés phénoliques comme accepteurs d'hydrogène in vitro et avons examiné les effets d'un composé phénolique sélectionné chez les vaches laitières. Nos résultats indiquent que l'acide gallique et le phloroglucinol étaient les plus efficaces en tant qu'accepteurs d'hydrogène in vitro, augmentant la production d'acétate et de gaz total lorsque la méthanogenèse était II inhibée par du 2-bromoéthanesulfonate de sodium (BES) ou par l'algue rouge Asparagopsis taxiformis. De plus, le phloroglucinol a réduit l'accumulation de dihydrogène, la production de méthane et la présence de méthanogènes tout en augmentant celle des bactéries dégradant potentiellement le phénolique, quand la méthanogenèse était inhibée par le BES. Pour des raisons pratiques et réglementaires, dans l'expérience in vivo réalisée sur 28 vaches laitières, l'acide gallique et l'inhibiteur de méthanogenèse Asparagopsis armata ont été utilisés. Contrairement aux résultats in vitro, l'acide gallique n'a pas réduit les émissions de dihydrogène et de méthane ni augmenté les proportions d'acétate et de propionate. Toutefois, la supplémentation en acide gallique a mitigé l'effet négatif de l'Asparagopsis armata sur la production laitière et l'association acide gallique et Asparagopsis armata a eu un effet d'interaction positive sur la production laitière dans cette étude. Nos découvertes suggèrent que l'acide gallique et le phloroglucinol ont le potentiel pour agir comme accepteurs d'hydrogène dans l'écosystème du rumen. Toutefois, dans l'expérimentation in vivo, l'acide gallique combiné avec Asparagopsis armata n'a pas eu d'effet d'interaction sur l'émission de dihydrogène. Des études supplémentaires sur les animaux sont nécessaires pour validation car le manque d'effet observé pourrait être attribuable aux niveaux d'inclusion de l'acide gallique. Les recherches futures devraient aussi examiner l'impact de l'acide gallique, seul ou en combinaison avec un inhibiteur de méthanogenèse, sur la production laitière.

LIST OF FIGURES

LIST OF TABLES

Table 1 The quantitative relationship between the production of 1 mole of acetate, butyrate, and propionate and the availability of reducing equivalents, ATP, and dihydrogen 1 ......... 12 Table 2 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, and gallic acid or formic acid at 6 mM on 24-h in vitro ruminal fermentation from dairy cows (n= 4). . Table 4 Effect of phloroglucinol with or without BES as methanogenesis inhibitor using a sequential batch culture incubation method and rumen fluid from dairy cows (n=8). ....... 77 Table S3 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, gallic acid, and formic acid at 6 mM when combined with A.taxiformis at 1.5% DM on in

Table S4

Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, gallic acid and formic acid at 6 mM when combined with BES at 3 μM on in vitro ruminal fermentation from dairy cows (n=4). ..................................................................................

Table S5

Effect of phloroglucinol with or without BES as methanogenesis inhibitor using a sequential batch culture incubation method and rumen fluid from dairy cows (n=8, fifth sequential batch).. Emilio Ungerfeld for their wonderful collaboration. I would like to thank Prof. Chris Creevey for the 5-month exchange in his lab at Queen's University Belfast. Prof. Creevey trained me for bioinformatic analysis. I am very appreciating his time and kindness. Also, I would like to thank CreeveyLab members for their warmhearted, friendship, and help.

Studying abroad is the treasure experience for me. Let me have the chance to experience the diversity of different societies, explore different cultures, educate under different systems. Especially, in France, one of the most culturally fulfilled countries. In the future, I will try my best to pursue the "liberté" "égalité" "fraternité" and facilitate the communications between different people from different background.

Without friends, I can't be here. I would like to thank the friendship and accompany of Dr. Maguy EUGUNE. During the pandemic lockdown period, the walk with her in the city center helps me to relax. And I had great time with her for having beers and watching soccer games. I would like to thank Dr. Mathieu Silberberg's concerns during my challenging time. I am very enjoying the coffee break time and after work drinking with the following friends: Karla, Sébastien, Dr. Jun Su, Ranran, Benchu, Yiming, Peter, Abimael, Alyce, Seoyoung, Maria, Blandine, Lauriane, Lumena, Ezequiel, and Carlos.

Their accompany and friendship let my life become more joyful. Chaoyong who is my old friend, I would like to thank him for his listening and advice. I have a great time staying at

François and Lili's home. I am gratefully for their kindness, help, and more importantly, their friendship. I had great time eating meals with them, having happy holidays in their mountain cabin, and the exciting bicycling trip.

XVII

Family is always my strongest support and the source of strength. I would like to give my deepest thank to my parents, sister, brother, and especially, my lovely nephew and niece. I did not visit my family for 3 years and 7 months. It is their support to let me have the courage to finish this journey.

Looking back on this Ph.D. journey, it was full of challenges. I am very glad that I went through all of these barriers. I hope I have the courage to face and embrace the upcoming journey.

CHAPTER 1

Literature review

The generation and transformation of reducing equivalents in the rumen metabolisms: part Ⅰ

Introduction

Ruminants differ from other animals in that they have four stomachs: the rumen, reticulum, omasum, and abomasum before the small intestine. This unique digestive tract gives ruminants having the ability to digest structural carbohydrates. In the rumen, the interactions between microbes, and between microbes and the host animal allow ruminants to digest plant material that is non-utilizable to monogastric animal including humans. In the highly anaerobic environment of the rumen, bacteria, protozoa, and fungi ferment structural and non-structural carbohydrates to volatile fatty acids (VFAs), carbon dioxide, and reducing equivalents. Methanogens use the reducing equivalents (e.g., dihydrogen, formate) and carbon dioxide as precursors to synthesize methane. However, enteric methane emissions contribute to climate change, and waste feed energy.

Methane production from the livestock sector accounts for 6% of anthropogenic greenhouse gas emissions (Gerber et al., 2013), and represents 2 to 12% of the gross energy intake in cattle (Johnson and Johnson, 1995).

Over last fifty years, researchers have developed many strategies to decrease methane emissions from ruminant (Beauchemin et al., 2020). Among them, feed additives such as 3-nitrooxypropanol and red seaweed show the greatest potential to decrease methane emissions. However, the energy saved by decreasing methane emissions is not correspondingly used to increase animal production (Ungerfeld, 2018, Melgar et al., 2020). Researchers believe that electron flow in the rumen is the key link to improving animal production when using methanogenesis inhibitors (Ungerfeld, 2018, Leahy et al., 2022). A few papers have reviewed rumen electron flow [START_REF] Hegarty | Hydrogen production and transfer in the rumen[END_REF], Ungerfeld, 2020, Leahy et al., 2022), however the information is not detailed enough. Therefore, this literature review detailed 1) the nutrients fermentation couple with reducing equivalents generation; 2) the electron transfer between different reducing equivalents; 3) dihydrogen and formate generation. All this information can give us with an insight into the electron flow in the rumen and possible methods to redirect the electron flow.

Reducing equivalents generation in the rumen

Reducing equivalents are electron donors in redox reactions. Rumen microbes ferment carbohydrates, amino acids, and lipids by several pathways that couple reducing equivalents, including the reduced nicotinamide adenine dinucleotide (NADH), reduced nicotinamide adenine dinucleotide phosphate (NADPH), reduced ferredoxin (Fdred), dihydrogen, formate, and small amounts of reduced flavin adenine dinucleotide (FADH2), generation. These reducing equivalents have different redox potentials and can provide different numbers of electrons in the redox reaction. For example, per mol of NADH, NADPH, FADH2, dihydrogen, and formate can provide 2 moles of electrons, while per mole of Fdred can only provide 1 mole of electron.

Carbohydrate metabolism couples with reducing equivalents generation

Carbohydrates account for 60 -70% of total diet, which are the major energy source for ruminants (National Research Council, 2001). Approximately 75% of the digestible carbohydrate energy is converted to VFA, which provides up to 75% of the metabolizable energy for the host animal [START_REF] Bergman | Energy contributions of volatile fatty acids from the gastrointestinal tract in various species[END_REF]. Dietary carbohydrates include cellulose, hemicellulose, starch, pectin, oligosaccharides, disaccharides (e.g., sucrose, and fructans), monosaccharides (e.g., glucose, and fructose), and organic acid (e.g., lactate).

Cellulose, hemicellulose, and pectin are the major components of the plant cell wall.

Starch is mainly found in the concentrate feed. Sucrose and fructans are the major nonstructural carbohydrates of forages and lactate is abundant in silage (National Research Council, 2001). Glycosidases hydrolyze cellulose, hemicellulose, starch, sucrose, and fructans to different monomers: cellulose to glucose; hemicellulose to fucose, galactose, arabinose, xylose, and rhamnose [START_REF] Solden | New roles in hemicellulosic sugar fermentation for the uncultivated Bacteroidetes family BS11[END_REF]; starch to glucose; sucrose to glucose and fructose; fructans to fructose; and pectin mainly to galacturonate [START_REF] Marounek | Metabolism of pectin in rumen bacteria Butyrivibrio fibrisolvens and Prevotella ruminicola[END_REF]. Except glucose, other monosaccharides participate in glucose metabolism pathways by converting themselves into the intermediate products of the glucose metabolism pathways.

Glycolysis pathway

Glycolysis pathway is the core pathway of the carbohydrate metabolic, linking carbohydrate, amino acid, and lipid metabolism. Figure 1 shows the major intermediates and the end products of this pathway. In this pathway, glyceraldehyde-3-phosphate oxidation is the only reaction coupled to NADH generation. One mole of glucose can be converted into 2 moles of glyceraldehyde-3-phosphates; thus 1 mole of glucose can generate 2 moles of NADH via this pathway. It should be noted that oxidized nicotinamide adenine dinucleotide (NAD + ) is not the only cofactor for glyceraldehyde-3phosphate oxidation. Some microbes also use oxidized nicotinamide adenine dinucleotide phosphate (NADP + ) or oxidized ferredoxin (Fdox) as the cofactor [START_REF] Spaans | NADPHgenerating systems in bacteria and archaea[END_REF], although these microbes unlikely to dominate VFA production in the rumen.

Pentose phosphate pathway

The pentose phosphate pathway includes both oxidative and non-oxidative reactions. Figure 1 shows only the oxidative reaction because the reducing equivalents are generated only in the oxidative reaction. The oxidation of glucose-6-phosphate and 6phosphogluconate produce NADPH. The end products of the pentose phosphate pathway are glyceraldehyde-3-phosphate and fructose 6-phosphate which both are the intermediates of the glycolysis pathway. One moles of glucose can be converted to 1 moles of ribulose 5-phosphates and 2 moles of NADPH in the oxidative reaction, then 1 moles of ribulose 5-phosphates can be converted to 1/3 mole of glyceraldehyde-3phosphate and 2/3 moles of fructose 6-phosphate in the non-oxidative reaction.

The pentose phosphate pathway primarily produces NADPH rather than NADH, which is the main source of NADPH used for biosynthesis [START_REF] Spaans | NADPHgenerating systems in bacteria and archaea[END_REF]. The intermediate metabolite ribulose-5-phosphate is the precursor of nucleotides. Therefore, this pathway is very important for rumen microbes because rumen microbes, especially bacteria, have a short generation time.

Entner-Doudoroff pathway

The Entner-Doudoroff pathway is another carbohydrate metabolic pathway (Figure 1). There are two types of Entner-Doudoroff pathways, the classical Entner-Doudoroff pathway and the modified Entner-Doudoroff pathway. The modified Entner-Doudoroff pathway comprises of a semi-phosphorylated Entner-Doudoroff pathway and a nonphosphorylated Entner-Doudoroff pathway [START_REF] Ahmed | The semi-phosphorylative Entner-Doudoroff pathway in hyperthermophilic archaea: a re-evaluation[END_REF]. Both the classical and the modified Entner-Doudoroff pathways use 1 mole of glucose to produce 2 moles of pyruvate, 1 mole of NADPH, and 1 mole of NADH [START_REF] Ettema | The nonphosphorylating glyceraldehyde-3-phosphate dehydrogenase (GAPN) of Sulfolobus solfataricus: a key-enzyme of the semi-phosphorylative branch of the Entner-Doudoroff pathway[END_REF][START_REF] Spaans | NADPHgenerating systems in bacteria and archaea[END_REF]. The classical Entner-Doudoroff pathway is mainly found in prokaryotes [START_REF] Fabris | The metabolic blueprint of Phaeodactylum tricornutum reveals a eukaryotic Entner-Doudoroff glycolytic pathway[END_REF], while the modified Entner-Doudoroff pathway is mainly found in several Clostridium species such as Halobacterium saccharocorum, and extreme thermoacidophiles [START_REF] Conway | The Entner-Doudoroff pathway: history, physiology and molecular biology[END_REF]. Similar to the pentose phosphate pathway, NADP + is the preferred electron acceptor in the Entner-Doudoroff pathway [START_REF] Spaans | NADPHgenerating systems in bacteria and archaea[END_REF].

Methylglyoxal pathway

Some rumen bacteria lack the genes encoding for enolase; therefore, the glycolysis pathway is incomplete for these bacteria as enolase catalyzes the dehydration of 2phospho-D-glycerate to produce phosphoenolpyruvate. [START_REF] Seshadri | Cultivation and sequencing of rumen microbiome members from the Hungate1000 Collection[END_REF] reported that ruminal isolates belonging to the genera Butyrivibrio, Prevotella, and uncharacterized members of the family Lachnospiraceae have a high proportion of enolase-negative strains (approximately 50% for Butyrivibrio). Therefore, the methylglyoxal pathway has been proposed for these microbes [START_REF] Kelly | The glycobiome of the rumen bacterium Butyrivibrio proteoclasticus B316T highlights adaptation to a polysaccharide-rich environment[END_REF] (Figure 1). In the methylglyoxal pathway, glyceraldehyde-3-phosphate is converted to dihydroxyacetone-phosphate, and then dihydroxyacetone-phosphate is converted to pyruvate through intermediate metabolites including methylglyoxal and lactate. However, this metabolic pathway has not been confirmed. Also, some enolase-negative Butyrivibrio strains do not produce lactate and they lack the gene for L-lactate dehydrogenase [START_REF] Seshadri | Cultivation and sequencing of rumen microbiome members from the Hungate1000 Collection[END_REF]. Furthermore, [START_REF] Hackmann | Genomes of rumen bacteria encode atypical pathways for fermenting hexoses to short-chain fatty acids[END_REF] did not find the genes encoding the methylglyoxal pathway in enolase-negative rumen bacteria through genome analysis. Therefore, the methylglyoxal pathway is probably not widespread in rumen bacteria. Further studies are needed to investigate carbohydrate metabolism in these enolase-negative microbes.

Phosphoketolase pathway

Phosphoketolase is a promiscuous enzyme that catalyzes three different reactions [START_REF] Valk | A novel d-galacturonate fermentation pathway in Lactobacillus suebicus links initial reactions of the galacturonate-isomerase route with the phosphoketolase pathway[END_REF]). Here we focus on only one of the three reactions, xylulose 5phosphate cleavage to acetyl-phosphate and glyceraldehyde-3-phosphate (Figure 1), as there is little information on the other two reactions for rumen microbes. Some rumen microbes such as Prevotella ruminicola B14 (this microbe has now been assigned to the genus Xylanibacter [START_REF] Hitch | A taxonomic note on the genus Prevotella: Description of four novel genera and emended description of the genera Hallella and Xylanibacter[END_REF]) and Fibrobacter succinogenes S85 showed significant phosphoketolase activity [START_REF] Matte | Enzymes associated with metabolism of xylose and other pentoses by Prevotella (Bacteroides) ruminicola strains, Selenomonas ruminantium D, and Fibrobacter succinogenes S85[END_REF]. [START_REF] Valk | A novel d-galacturonate fermentation pathway in Lactobacillus suebicus links initial reactions of the galacturonate-isomerase route with the phosphoketolase pathway[END_REF] identified the gene of phosphoketolase by whole-genome analysis and found the phosphoketolase by proteomic analysis of the rumen bacterium Lactobacillus suebicus. However, the incubation pH (pH = 4) and temperature (30 ℃) used in this study were very different from the rumen environment. For some rumen microbes, such as Butyrivibrio fibrisolvens 787, Prevotella ruminicola AR29, and Butyrivibrio fibrisolvens ATCC 19171, researchers did not find the phosphoketolase activity in pure culture (Marounek and[START_REF] Marounek | Fermentation of glucose and xylose in ruminal strains of Butyrivibrio fibrisolvens[END_REF][START_REF] Marounek | Metabolism of pectin in rumen bacteria Butyrivibrio fibrisolvens and Prevotella ruminicola[END_REF]. More research is needed to investigate the importance of the phosphoketolase pathway in rumen carbohydrate metabolism.

All of the above carbohydrate metabolic pathways are related to VFA production as the end products of these pathways are either pyruvate or can be converted to pyruvate, which is the precursor of acetate, propionate, and butyrate. However, their importance in VFA production varies. Glucose metabolism via the pentose phosphate pathway or the phosphoketolase pathway produces more reducing equivalents but less pyruvate and ATP. For example, 1 mole of glucose can produce 2 moles of NADH, 2 moles of pyruvate, and 2 moles of ATP through the glycolysis pathway; whereas 1 mole of glucose can produce 2 moles of NADPH, 5/3 moles of NADH, 5/3 moles of pyruvate, and 5/3 moles of ATP through the pentose phosphate pathway; 1 mole of glucose can produce 2 moles of NADPH, 1 mole of NADH, 1 mole of pyruvate, 1 mole of acetate, and 2 moles of ATP via the phosphoketolase pathway (Figure 1). Therefore, the pentose phosphate and phosphoketolase pathways are probably not preferred for VFA production as these two pathways produce less VFA precursor pyruvate, and less ATP. Another reason why these two pathways are not preferred is that they produce more reducing equivalents, however the rumen environment is in a very high reducing potential state. The glycolysis and methylglyoxal pathways produce the same amount of pyruvate and reducing equivalents; however, the methylglyoxal pathway consumes ATP. The glycolysis and Entner-Doudoroff pathways also produce the same amount of reducing equivalents and pyruvate (Figure 1). The glycolysis pathway uses NAD + as its electron acceptor, whereas the Entner-Doudoroff pathway uses NADP + and NAD + as its electron acceptor. In addition, the glycolysis pathway produces more ATP than the Entner-Doudoroff pathway. For example, 1 mole of glucose is metabolized to 2 moles of pyruvate and produces 2 moles of ATP by the glycolysis pathway, whereas 1 mole of glucose is metabolized to 2 moles of pyruvate and produces only 1 mole of ATP by the Entner-Doudoroff pathway (Figure 1).

Considering the above factors mentioned, the glycolysis pathway is likely to be the core pathway for VFA production in the rumen.

Volatile fatty acid production couples with reducing equivalents generation

Pyruvate is the major end product of different monosaccharides via different carbohydrate metabolic pathways (Figure 1). It is also the main precursor for VFA production (Figure 2). Pyruvate can be converted to acetyl-CoA via three different pathways: 1) pyruvate dehydrogenase (PDH) catalyzes pyruvate to acetyl-CoA using NAD + as electron acceptor; 2) pyruvate-ferredoxin oxidoreductase (PFOR) catalyzes pyruvate to acetyl-CoA using Fdox as the electron acceptor; 3) and pyruvate formatelyase (PFL) catalyzes pyruvate to acetyl-CoA and produces formate (detailed in the following section). Pyruvate-ferredoxin oxidoreductase and PFL catalyze reversible reactions, whereas PDH catalyzes irreversible reaction. Therefore, acetyl-CoA production by PFOR and PFL is likely to be inhibited when dihydrogen accumulates in the rumen caused by the methanogenesis inhibitor. Certainly, the use of a methanogenesis inhibitor generally decrease acetate proportion.

Pyruvate-ferredoxin oxidoreductase has been found in methanogens such as

Methanosarcina barkeri [START_REF] Bock | The iron-sulfur centers of the pyruvate: ferredoxin oxidoreductase from Methanosarcina barkeri (Fusaro)[END_REF], most anaerobic bacteria [START_REF] Chabrière | Crystal structures of the key anaerobic enzyme pyruvate: ferredoxin oxidoreductase, free and in complex with pyruvate[END_REF], and rumen protozoa [START_REF] Yarlett | Hydrogenosomes in the rumen protozoon Dasytricha ruminantium Schuberg[END_REF]. This enzyme is important because it catalyzes Fdred generation instead of NADH. The negative redox potential of Fdred is higher than that of NADH, allowing Fdred to be used in reactions that require stronger reductants than NADH such as dihydrogen formation or formate formation [START_REF] Ragsdale | Pyruvate ferredoxin oxidoreductase and its radical intermediate[END_REF]. Under anaerobic conditions, PFOR was thought to be one of the main pathways for acetyl-CoA generation [START_REF] Kerscher | Pyruvate: ferredoxin oxidoreductase-new findings on an ancient enzyme[END_REF]. Acetyl-CoA is the precursor for the acetate production. Acetyl-CoA synthetase catalyzes acetyl-CoA to generate acetate and ATP. Acetyl-CoA is also the precursor for the generation of butyrate. Figure 2 shows that 2 moles of acetyl-CoA consume 3 moles of NADH to generate 1 mole of butyrate and 2 moles of Fdred (Hackmann and Firkins, 2015). There are three different pathways for propionate formation: 1) phosphoenolpyruvate conversion via intermediates such as malate, fumarate, and succinate; 2) pyruvate conversion via the same intermediates such as malate, fumarate, and succinate; 3) pyruvate conversion via lactate [START_REF] Hackmann | Genomes of rumen bacteria encode atypical pathways for fermenting hexoses to short-chain fatty acids[END_REF]. Propionate generation via phosphoenolpyruvate or pyruvate metabolism consumes reducing equivalents (Figure 2). Valerate, caproate, isobutyrate, and isovalerate generation are not discussed here because their concentrations in the rumen fluid are low. From Figure 1 and Figure 2, we can calculate the number of moles of dihydrogen generated when 1 mole of acetate, or propionate, or butyrate is produced via glycolysis pathway (Table 1). It is noteworthy that acetate and butyrate production generates the same amount of dihydrogen, while propionate production consumes dihydrogen.

Although converting more carbohydrates to propionate may theoretically allow the animal to retain more feed energy, rumen microbes do not appear to adapt to this strategy because dihydrogen is mainly used to produce methane instead of more propionate. The reasons might because different VFA have different physiological functions. For example, acetate and butyrate mainly used to synthesis milk fat in dairy cow [START_REF] Bauman | Nutritional regulation of milk fat synthesis[END_REF], and propionate is mainly used to produce glucose in the liver [START_REF] Bergman | Energy contributions of volatile fatty acids from the gastrointestinal tract in various species[END_REF].

Additionally, acetate and butyrate production generate more ATP than propionate production (Table 1), which can support microbial growth to maintain rumen functions.

Further research is required to understand why propionate production is not the primary pathway for dihydrogen consumption by ruminal microbes.

Protein metabolism couples with reducing equivalents generation

The rumen digestibility of proteins from different feedstuff varies, with plant protein degradation rates ranging from 28 to 56% after 12-h of rumen incubation [START_REF] Taghizadeh | Digestion of feed amino acids in the rumen and intestine of steers measured using a mobile nylon bag technique[END_REF]. Bacteria, protozoa, and anaerobic fungi in the rumen generate various proteases, peptidases, and deaminases to digest feed protein. Among the rumen microbes, bacteria are considered the principal proteolytic microorganisms because of their high abundance and up to 40% of cultured bacteria have proteolytic activity (National Research Council , 2001). In the rumen, the digestible feed proteins are hydrolyzed to peptides and amino acids, which are mainly used to synthesize microbial protein [START_REF] Wu | Amino acids: biochemistry and nutrition. 1st Edition[END_REF]. Amino acid is also undergoing deamination to ammonia and αketoacids, which are involved in metabolic pathways including amino acid, fatty acid, and VFA synthesis [START_REF] Bach | Nitrogen metabolism in the rumen[END_REF]. The deamination of amino acids can generate NAD(P)H via dehydrogenases or FADH2 via oxidases (Figure 3) [START_REF] Wu | Amino acids: biochemistry and nutrition. 1st Edition[END_REF].

Additionally, the synthesis of amino acids using α-ketoacids and ammonia, as well as the synthesis of glutamate from glutamine, consume NAD(P)H. The metabolism of αketoacid via carbohydrate metabolism pathway also linked to NAD(P)H generation or consumption.

Figure 3 Reducing equivalents generation and consumption by amino acids metabolism: example of glutamate and glutamine which is in the central status in amino acids synthesis in the rumen. (Modified from [START_REF] Wu | Amino acids: biochemistry and nutrition. 1st Edition[END_REF] 2.4 Lipid metabolism couples with reducing equivalents generation Microbial lipases extensively hydrolyze esterified lipids from the diet in the rumen, yielding free fatty acids and glycerol. Glycerol can be absorbed by the rumen epithelium [START_REF] Werner Omazic | The fate of glycerol entering the rumen of dairy cows and sheep[END_REF] or metabolized by rumen microbes to produce mainly propionate and butyrate via the intermediate glyceraldehyde-3-phosphate [START_REF] Rémond | In vitro and in vivo fermentation of glycerol by rumen microbes[END_REF], Wang et al., 2009). The conversion of 1 mole of glycerol to 1 mole of propionate consumes 1 mole of NADH, while the conversion of 2 moles of glycerol to 1 mole of butyrate generates 6 moles of Fdred and consumes 1 mole of NADH. Meanwhile, free fatty acid can undergo degradation via the β-oxidation pathway by rumen microbes, using FAD and NAD + as electron acceptors. However, the rumen's capacity to degrade long-chain fatty acids is limited, with less than 1% being degraded [START_REF] Jenkins | Lipid metabolism in the rumen[END_REF]. As a result, the generation of FADH2 and NADH from β-oxidation of long-chain free fatty acids is negligible.

Electron transfer occurs among NAD(H), NADP(H), and ferredoxin

NAD + , NADP + , and Fdox are the electron acceptors for anaerobic dehydrogenase reactions. Different anaerobic dehydrogenases exhibit varying preferences for these electron acceptors, likely due to the difference in the structure and the difference in reduction potential of these electron acceptors. For example, PFOR and flavoprotein/butyryl-CoA dehydrogenases (EtfAB-Bcd) more commonly utilize Fdox as the electron acceptor. In physiological conditions, the reduction potential of these electron acceptors follows the order of NAD + > NADP + > Fdox. Although the reduction potential of these electron acceptors is different, the electrons can transfer between each other under certain conditions.

Mutual transformation between NAD(H) and NADP(H)

NADH and NADPH are commonly used as reducing equivalents in microbes. As mentioned above, NADH is primarily generated via the glycolysis pathway, while NADPH is primarily generated via the pentose phosphate and Entner-Doudoroff pathways. Under standard physiological conditions, NADP + /NADPH and NAD + /NADH have identical redox potential (E′0: -320mV). However, in bacterial cells, the NADP + /NADPH ratio is lower than the NAD + /NADH ratio [START_REF] Bennett | Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli[END_REF][START_REF] Amador-Noguez | Metabolome remodeling during the acidogenic-solventogenic transition in Clostridium acetobutylicum[END_REF], which makes NADP + /NADPH having a higher reducing capacity than NAD + /NADH. The functions of NADPH and NADH are also different: NADPH is used for anabolic redox reactions including lipid, cholesterol, nucleic acid, and amino acid synthesis, whereas NADH is used for oxidation reactions [START_REF] Spaans | NADPHgenerating systems in bacteria and archaea[END_REF]. The varying metabolic functions of NADPH and NDAH may arise from the specificity of enzymes that utilize these reducing equivalents [START_REF] Cracan | A genetically encoded tool for manipulation of NADP+/NADPH in living cells[END_REF].

There are two pathways for NAD(H) biosynthesis: the de novo pathway and the salvage pathway [START_REF] Begley | The biosynthesis of nicotinamide adenine dinucleotides in bacteria[END_REF]. However, NAD(H) kinase is the only enzyme responsible for NADP(H) de novo biosynthesis, which phosphorylates NAD + to NADP + and NADH to NADPH [START_REF] Spaans | NADPHgenerating systems in bacteria and archaea[END_REF] (Figure 4). While, NADP(H) phosphatase hydrolyzes NADP + to NAD + and NADPH to NADH (Figure 4). NAD(H) kinase together with NADP(H) phosphatase regulate the intracellular balance of NAD(H) and NADP(H) [START_REF] Kawai | Structure and function of NAD kinase and NADP phosphatase: key enzymes that regulate the intracellular balance of NAD (H) and NADP (H)[END_REF]. Energy-independent soluble transhydrogenase (STH) is the enzyme that catalyzes electron transfer between NAD(H) and NADP(H) (Figure 4).

Energy-independent soluble transhydrogenase is found in Gammaproteobacteria, such as Pseudomonas fluorescens, and catalyzes a reversible reaction [START_REF] French | Cloning, sequence, and properties of the soluble pyridine nucleotide transhydrogenase of Pseudomonas fluorescens[END_REF].

Membrane-bound pyridine nucleotide transhydrogenase (PntAB) is an energy-dependent or proton-translocating dependent transhydrogenase that facilitates electron transfer between NAD(H) and NADP(H) (Figure 4). NADPH formation is coupled with H + flow from extracellular to intracellular, which provides energy for this reaction. Membranebound pyridine nucleotide transhydrogenase is widely distributed in the mitochondria of eukaryotes and certain bacteria but is rare in archaea [START_REF] Jackson | A review of the binding-change mechanism for proton-translocating transhydrogenase[END_REF]. Although STH and PntAB catalyze reversible reactions, STH favors NADH generation [START_REF] Reddy | Metabolic Engineering an ATPneutral EMP pathway in Corynebacterium glutamicum: adaptive point mutation in NADH dehydrogenase restores growth[END_REF], while PntAB favors NADPH generation [START_REF] Pedersen | Proton-translocating transhydrogenase: an update of unsolved and controversial issues[END_REF] under physiological conditions.

Electron transfer between NAD(H) and ferredoxin

NADH transfer electrons to Fdox occurs in the butyrate generation pathway.

Specifically, EtfAB-Bcd complex reduces crotonyl-CoA to butyryl-CoA with NADH and generates Fdred (Buckel and Thauer, 2018a) (Figure 4). This reaction is called electron bifurcation which couples exergonic and endergonic redox reactions to simultaneously generate low-and high-potential electron carriers (Garcia [START_REF] Costas | Defining electron bifurcation in the electron-transferring flavoprotein family[END_REF]. In this reaction, 1 mole of NADH transfers 2 moles of electrons to 1 mole of crotonyl-Co A to generate 1 mole of butyryl-CoA, and 1 mole of NADH transfers 2 moles of electrons to 2 moles of Fdox to generate 2 moles of Fdred. Reduced ferredoxin generation requires energy which is provided by butyryl-CoA generation (Garcia [START_REF] Costas | Defining electron bifurcation in the electron-transferring flavoprotein family[END_REF].

Therefore, chemical energy is saved in this reaction. Electron bifurcation is recognized as the third energy conservation reaction in biology (the others are substrate-level phosphorylation and oxidative phosphorylation). Additionally, EtfAB-Bcd catalyzes irreversible reaction in microorganisms (Buckel and Thauer, 2018b).

The Rhodobacter nitrogen fixation (Rnf) complex is a membrane-associated electron-transport protein that also couples electron transfer between ferredoxin and NAD(H) with proton or sodium ion translocation (Figure 4) (Buckel and Thauer, 2018b).

The Rnf complex is found in strict anaerobes, including most of butyrivibrios (Hackmann and Firkins, 2015), acetogenic bacteria [START_REF] Tremblay | The Rnf complex of Clostridium ljungdahlii is a proton-translocating ferredoxin: NAD+ oxidoreductase essential for autotrophic growth[END_REF], acetoclactic methanogens [START_REF] Schlegel | Electron transport during aceticlastic methanogenesis by M ethanosarcina acetivorans involves a sodiumtranslocating R nf complex[END_REF], methanotrophic archaea [START_REF] Wang | Methanotrophic archaea possessing diverging methane-oxidizing and electron-transporting pathways[END_REF], and sulfate reducers [START_REF] Pereira | A comparative genomic analysis of energy metabolism in sulfate reducing bacteria and archaea[END_REF]. This reaction couples with 2 moles of H + /Na + translocation out the cell when NADH is generated by oxidation of Fdred. Oxidation of Fdred is an exergonic process because Fdred has a higher reducing potential than NADH, and the energy is saved by the translocation of H + /Na + out the cell. When H + /Na + is transported from the extracellular to intracellular the through ATP synthase, ATP is generated.

Electron transfer between NADP(H) and ferredoxin

Ferredoxin: NADP + oxidoreductases (FNRs) are flavoenzymes that typically feature a non-covalently bound flavin. They catalyze a reversible reaction that involves electron transfer between the one-electron carrier reduced ferredoxin and the two-electron carrier NADPH (Figure 3). These enzymes play a crucial role in photosynthesis. However, in contrast to photosynthetic cells, FNRs in microbes tend to favor the generation of Fdred [START_REF] Spaans | NADPHgenerating systems in bacteria and archaea[END_REF]. Generating Fdred via the reduction of NADPH requires energy because Fdred has a lower reduction potential. Thus, it is unlikely that this reaction is prevalent among rumen microorganisms. Additionally, there is another type of FNR NADH-dependent reduced ferredoxin: NADP+ oxidoreductase (NfnAB), which couples the exergonic reduction of NADP + with Fdred and the endergonic reduction of NADP + with NADH (Figure 4) [START_REF] Spaans | NADPHgenerating systems in bacteria and archaea[END_REF]. This reaction is known as electron confurcation, which is the reverse reaction of electron bifurcation. Genome analysis has shown that NfnAB gene is present in many anaerobic bacteria and archaea (Huang et al., 2012, Buckel andThauer, 2018b).

Interspecies electron transfer

Interspecies electron transfer occurs in the rumen. Rumen bacteria, protozoa, and fungi break down carbohydrates to produce VFA and reducing equivalents such as dihydrogen and formate. These reducing equivalents then diffuse to methanogens, which utilize them to synthesize methane (Leng, 2014). This process has a dual effect: on one hand, the consumption of dihydrogen and formate by methanogens accelerates VFA production, while on the other hand, methanogens obtain energy via methane production.

Dihydrogen generation

Hydrogenases are a diverse group of metalloenzymes that reversibly transfer electrons to protons to generate dihydrogen. Depending on the metal ion composition in the active site, hydrogenases can be classified into [NiFe], [FeFe], and [Fe] groups (Lubitz et al., 2014). Both [NiFe] and [FeFe] hydrogenases have proton channel, hydrophobic gas channels for dihydrogen, and an electron transfer chain consisting of three [FeS] clusters, while [Fe] hydrogenase uses methenyltetrahydromethanopterin as an electron transfer chain component (Lubitz et al., 2014). Although hydrogenases catalyze a reversible reaction, [NiFe] hydrogenases favor dihydrogen oxidation, and

[FeFe] hydrogenases favor dihydrogen generation. In the rumen microbes, hydrogenases present widespread traits. [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF] ,3a,3c,4e,4g,4h,4i,and [Fe] subgroup, which are mainly found in Clostridiales, Methanobacteriales, and Selenomonadales [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF].

Moreover, the authors found that A3, 1d, 3a, 3c, and 4g genes were highly expressed (RNA/DNA expression ratio > 4), with A3 accounted for 54% of hydrogenase transcripts [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF]. Hydrogenase A3 belongs to the [FeFe] group, which utilizes Fdred and NADH as stoichiometric electron donors to produce dihydrogen (Figure 5). The oxidation of reduced ferredoxin is an exergonic reaction, coupled with endergonic reaction of NADH oxidation, thereby conserving energy through electron confurcation.

The hydrogenase A3 complex comprises three components: HydA, HydB, and HydC.

HydA possesses the proton and dihydrogen gas channel, HydB contains an FMN subunit that transfers electrons from NADH, and HydC is an iron-sulfur protein responsible for electron transfer from Fdred (Buckel and Thauer, 2018b). As a result, the hydrogenase A3 complex is also referred to as the HydABC complex (or MvhAGD complex). Reduced Fd, primarily produced by the EtfAB-Bcd and PFOR enzymes, serves as the electron donor for hydrogenase A3. This efficient utilization of Fdred likely explains why hydrogenase A3

is the predominant hydrogenase in anaerobic fermenting microbes. Furthermore, it should be noted that this reaction is reversible and the reverse reaction has been observed in certain hydrogenotrophic acetogens [START_REF] Schuchmann | A bacterial electron-bifurcating hydrogenase[END_REF]. Ech, ferredoxin-dependent and membrane-associated hydrogenase.

Ferredoxin-dependent hydrogenase

Hydrogenases A1, A2, B, and C are the most abundant ferredoxin-dependent

[FeFe]-hydrogenases, and both metagenomic and metatranscriptomic analyses showed that these hydrogenase genes are abundant and highly expressed in the rumen microorganisms of sheep [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF]. Hydrogenases A1, A2, and B catalyze the dihydrogen generation by using Fdred as the electron donor (Figure 5), while hydrogenase C works as dihydrogen concentration sensor [START_REF] Søndergaard | HydDB: a web tool for hydrogenase classification and analysis[END_REF].

Hydrogenases A1, A2, and B are mainly found in fermentative bacteria such as Clostridia, Negativicutes, and Bacteroidia, while hydrogenase C is mainly found in Clostridia [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF]. When dihydrogen accumulated in the rumen,

Ruminococcus albus downregulated the genes expression of hydrogenases C and A1

both by 111 folds, thus total dihydrogen production by A1 likely decreased [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF]. A similar phenomenon was observed in another study by [START_REF] Zheng | Hydrogen formation and its regulation in Ruminococcus albus: involvement of an electronbifurcating [FeFe]-hydrogenase, of a non-electron-bifurcating [FeFe]-hydrogenase, and of a putative hydrogen-sensing [FeFe]-hydrogenase[END_REF].

Hydrogenase 4e, also known as the Ech complex, is a ferredoxin-dependent and membrane-associated [NiFe]-hydrogenase that catalyzes dihydrogen formation through Fdred oxidation and H + /Na + translocation from intracellular to extracellular (Figure 5) (Buckel and Thauer, 2018b), thereby conserving energy. This enzyme is abundant and highly expressed in sheep rumen microorganisms, and is dominant in Clostridia [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF]. Meanwhile, the functions of highly expressed hydrogenase 4g in Clostridia remains unclear [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF].

Formate generation

Rumen microbes have different pathways to generate formate. Pyruvate formatelyase catalyzes pyruvate to acetyl-CoA and formate, which is thought to be the main source of formate production in the rumen fluid (Figure 5) [START_REF] Asanuma | Formate metabolism by ruminal microorganisms in relation to methanogenesis[END_REF]. The genes of hydrogenases 4f, formate hydrogenlyase 4a, and formate dehydrogenase A4 are dominant in Clostridia, Gammaproteobacteria, and Negativicutes, respectively [START_REF] Greening | Diverse hydrogen production and consumption pathways influence methane production in ruminants[END_REF]. Transportation of formate out of the cell is inefficient [START_REF] Stams | Electron transfer in syntrophic communities of anaerobic bacteria and archaea[END_REF], therefore 4f, 4a, and A4 likely catalyze formate oxidation to H2 evolution [START_REF] Greening | Genomic and metagenomic surveys of hydrogenase distribution indicate H2 is a widely utilised energy source for microbial growth and survival[END_REF][START_REF] Søndergaard | HydDB: a web tool for hydrogenase classification and analysis[END_REF]. Moreover, dihydrogen production via hydrogenase A3 is more efficient than pyruvate formatelyase. Considering the factors mentioned above, formate is likely not as important as dihydrogen in interspecies electron transfer under physiologic rumen conditions. According to Hungate et al. (1970), utilizing formate as electron donor produces 18% methane, while using dihydrogen produces 82% methane.

Rumen methanogenesis, methanogenesis inhibition methods, knowledge gaps and objectives of this study: part Ⅱ

Rumen microbiota

The rumen microbiota comprises of a diverse range of microbes, including bacteria, fungi, archaea, protozoa, and phage, which interact with each other and the host animal to facilitate the feed digestion. The host animal provides a habitat with an anaerobic environment, steady temperature, and abundant nutrients to the microbes, and in return, the microbes provide nutrients such as VFA and microbial protein to the host animal. The rumen bacteria, fungi, and protozoa digest feed nutrients (mainly carbohydrates) to VFA and dihydrogen. Rumen wall absorbs VFA as the primarily energy source of the ruminant, and archaea use the diffused dihydrogen with carbon dioxide to produce methane. On one hand, archaea obtain energy (ATP) through methanogenesis. On the other hand, dihydrogen consumption promotes VFA production. Here we give a detailed description of the rumen archaea because of their role in methane production.

Rumen archaea

Archaea are present in the rumen at low abundance (10 4 / mL rumen fluid), with 16s rRNA gene sequencing indicating that they account for only 0.3%~3.3% of total rumen prokaryotes [START_REF] Janssen | Structure of the archaeal community of the rumen[END_REF]. Methanogenic archaea (methanogens) are the dominant component, which use carbon dioxide and dihydrogen to produce methane as the end product (Patra et al., 2017) (Patra et al., 2017). Meanwhile, methanogens inhabit rumen fluid, attach to the feed and rumen epithelium, and even have an endosymbiotic relationship with rumen protozoa (Patra et al., 2017). The abundance and diversity of methanogens differ between rumen fluid, solid, and epithelium [START_REF] Pei | Diversity, abundance and novel 16S rRNA gene sequences of methanogens in rumen liquid, solid and epithelium fractions of Jinnan cattle[END_REF].

Methanogens can be classified into three categories based on the substrates used to produce methane: hydrogenotrophic methanogens, methylotrophic methanogens, and acetotrophic methanogens (Morgavi et al., 2010). Most rumen methanogens are hydrogenotrophic methanogens that use dihydrogen and carbon dioxide as substrates to produce methane. Members of the genus Methanobrevibacter belong to this category;

Methylotrophic methanogens use methyl compounds as carbon sources and are classified as Methanosarcinales, Methanosphaera, and Methanomassiliicoccaceae;

Acetotrophic methanogens including Methanosarcinales using acetate to produce methane and carbon dioxide [START_REF] Huws | Addressing global ruminant agricultural challenges through understanding the rumen microbiome: Past, present, and future[END_REF].

Implications of enteric methane emissions

According to the United Nations, the world population is expected to reach 9.7 billion by 2050 and 11.1 billion by 2100 [START_REF] Abel | Meeting the Sustainable Development Goals leads to lower world population growth[END_REF]. As a results, there will be a greater need for animal products, especially milk and meat, to meet the growing demand for nutrition. Moreover, the requirement for animal protein is significantly increasing with the economic improvement in low-and medium-developed countries. However, the animal industry is one of the main sources of greenhouse gas (e.g., carbon dioxide, methane, and nitrous oxide). In fact, livestock sector produces 7.1 gigatonnes CO2-eq per annum, representing 14.5% of human-induced greenhouse gas emissions (Gerber et al., 2013).

In addition, methane emissions from ruminants also results in feed energy waste.

About 2 ~ 12% of feed energy is lost because of methane production (Johnson and Johnson, 1995). Thus, decreasing methane production could potentially save feed energy and produce more animal products. Decreasing enteric methane emissions, while simultaneously improving animal productivity is one of the most effective ways to meet the increasing demand for animal protein and the challenge of climate change. Also, if decreasing enteric methane emissions leads to increase animal productivity, farmers will have the motivation to use methanogenesis inhibitors in practice.

Methane metrics and methane measurement techniques

To evaluate the effectiveness of mitigation strategies, reliable tools to measure methane and express methane emissions are mandatory. The methane metrics used to describe methane production by ruminants have been standardized to methane production, methane yield, and methane intensity. The term "methane production" refers to the amount of methane produced per day (g of CH4 /d); "methane yield" refers to the amount of methane produced per kg dry matter intake (g of CH4/kg DMI), and "methane intensity" refers to the amount of methane produced per kg animal products (e.g., g of CH4/kg animal products) (Melgar et al, 2020). Residual methane emissions, primarily used in breeding, refers to the discrepancy between an animal's actual methane production and its expected production based on its feed intake and body weight [START_REF] Herd | Measures of methane production and their phenotypic relationships with dry matter intake, growth, and body composition traits in beef cattle[END_REF].

Measuring animal methane emissions is essential for the fundamental understanding of methanogenesis and evaluating any mitigation strategies. The accuracy, precision, repeatability, and cost-effectiveness are the key factors for the methane measurement methods [START_REF] Patra | Recent advances in measurement and dietary mitigation of enteric methane emissions in ruminants[END_REF]. With around 50 years of work in this area, many enteric methane measurement methods have been evaluated. In general, those methods can be classified into two categories: direct methods that directly measure methane emissions from animal, and indirect methods that estimate methane emissions based on other parameters such as feed intake and digestibility.

3.1 Direct methods

Respiration Chamber

The respiration chamber, which can be classified as either open-circuit chamber or closed-circuit chamber, is considered the "gold standard" for animal enteric methane measurement, because it provides highly accurate and repeatable results [START_REF] Tedeschi | Quantification of methane emitted by ruminants: A review of methods[END_REF]. Animals are confined in the chamber for several successive days (usually 3-5 days), and gas samples are collected at a given frequency (for instance, 15 min) and analyzed for composition, while the outlet airflow is recorded. To prevent potential internal gas leaks, the respiration chamber maintains a slightly negative atmospheric pressure (Zhao et al., 2020).

Compared to other methane measurement methods, the respiration chamber can measure enteric methane produced from the rumen and the hindgut, and it can be used to study feed digestibility and energy metabolism, which are directly related to methane production. Additionally, the respiration chamber can continuously monitor methane and dihydrogen production in a 24-h cycle, which is important because ruminant enteric gas emissions, especially methane and dihydrogen emissions, are not evenly distributed throughout the day (van Gastelen et al., 2020).

However, the respiration chamber is costly and requires intensive labor, which limits the number of animals that can be included in each trial. Furthermore, animal behavior may be disturbed while they are confined in the chamber, potentially affecting their performances, even if the animals are acclimated to the chamber prior to the experiment.

Milking, cleaning, sampling, and feeding operations may also interrupt methane and dihydrogen measurement, however a recent study had suggested that these impacts can be negligible (van Gastelen et al., 2020).

Greenfeed

Greenfeed is designed by C-Lock incorporation (Rapid City, SD, USA) to measure methane, dihydrogen, carbon dioxide emissions, and oxygen consumption by ruminants.

It is an automated head-chamber system equipped with a radio-frequency identification system, a bait feed delivery system, a head position sensor, an airflow meter, and gas sensors. The radio-frequency identification system can recognize the animal, and the bait feed delivery system can allure animal to visit this device and control the interval time of the adjacent visiting. For each measurement, it takes 7 mins on average. We can use Greenfeed in grazing system because it is portable and automatic. Although the bait feed and environmental conditions such as wind speed may introduce variances to the measurement, the Greenfeed is a reliable method to measure methane and dihydrogen emissions when the number of animals and visiting frequency are appropriate [START_REF] Coppa | Repeatability and ranking of long-term enteric methane emissions measurement on dairy cows across diets and time using GreenFeed system in farmconditions[END_REF].

Other methods

The sulfur hexafluoride (SF6) tracer technique is a minimally invasive and specific method for measuring methane emission in both stall feeding and grazing systems. A small brass permeation tube filled with liquid SF6 is orally dosed into the rumen, after which the liquid SF6 gasifies at a constant rate. Gas samples are collected from the ruminant's mouth and nose using tubes [START_REF] Arbre | Repeatability of enteric methane determinations from cattle using either the SF6 tracer technique or the GreenFeed system[END_REF]. Methane emission per day can be calculated according to the SF6 release rate and the concentration ratio of methane to SF6 in the collected gas sample. The key assumption of this method is that the rumen's methane production rate is constant throughout the day. However, it is well established that rumen methane production rate fluctuates mainly depending on feeding [START_REF] Van Gastelen | Predicting enteric methane emission of dairy cows with milk Fourier-transform infrared spectra and gas chromatography-based milk fatty acid profiles[END_REF]. Also, this method requires a well-trained technician to operate to minimize error. There are other direct measurement methods, including the sniffer technique, ventilated hood, and facial mask, however these methods are not widely used due to issues related to accuracy, cost, and/or difficulty of operation. Further information about these methods can be found in review papers [START_REF] Hammond | Review of current in vivo measurement techniques for quantifying enteric methane emission from ruminants[END_REF], Zhao et al., 2020[START_REF] Tedeschi | Quantification of methane emitted by ruminants: A review of methods[END_REF].

Indirect methods

While the methods of respiration chamber, Greenfeed, and SF6 tracer technique for measuring ruminant methane emissions are well-established, their intensive labor and high expenditure requirements limit their application. To address this issues, indirect methane emission measurement methods have been developed. For example, the in vitro technique is used to predict the methane production of ruminants. However, this method only reflects relative methane emission among different treatment groups under in vitro conditions. Recently, researchers have sought to identify biomarkers to predict rumen methane emission. [START_REF] Chilliard | Milk fatty acids in dairy cows fed whole crude linseed, extruded linseed, or linseed oil, and their relationship with methane output[END_REF] found that milk-saturated fatty acids of C6:0 to 16:0 and C10:1 have correlation coefficients of 0.87 and 0.91, respectively, with methane emission; and some unsaturated fatty acids have a negative correlation with methane emission. A meta-analysis also found that milk fatty acid is a good indicator to predict dairy methane emission [START_REF] Bougouin | Individual milk fatty acids are potential predictors of enteric methane emissions from dairy cows fed a wide range of diets: Approach by meta-analysis[END_REF]. Van Gastelen et. al. (2018) further compared the different milk fatty acid analysis methods, gas chromatography and Fourier-transform infrared spectroscopy, to calculate the correlation coefficients of milk fatty acid and methane emission. They found that the correlation coefficient is 0.77 for milk fatty acid analyzed by gas chromatography and 0.72 for milk fatty acid analyzed by Fourier-transform infrared spectroscopy. And the cross-validation results indicate that both fatty acid measurement methods were robust to predict methane emission. However, the authors thought that these methods are not yet ready to use in practice. Additionally, researchers have identified some blood discriminant metabolites [START_REF] Yanibada | Review: Fifty years of research on rumen methanogenesis: Lessons learned and future challenges for mitigation[END_REF] and milk discriminant metabolites (Yanibada et al., 2021) that have the potential to predict methane emission.

Methanogenesis mitigation strategies

Methane is a potent greenhouse gas that has a global warming potential equivalent to 28 times than that of carbon dioxide over a period of 100 years [START_REF] Tian | The terrestrial biosphere as a net source of greenhouse gases to the atmosphere[END_REF], however, methane has a shorter lifespan than carbon dioxide. Therefore, decreasing methane emissions could have a rapid and significant effect on decreasing global warming [START_REF] Tian | The terrestrial biosphere as a net source of greenhouse gases to the atmosphere[END_REF].

To date, researchers have developed various methods to mitigate ruminant methane emissions, including the use of feed additives (e.g., 3-nitrooxypropanol, seaweed, lipid, secondary plant compounds, nitrate, and phenolic compounds) (Li et al., 2016, Martinez-Fernandez et al., 2017[START_REF] Doreau | Linseed plus nitrate in the diet for fattening bulls: effects on methane emission, animal health and residues in offal[END_REF], diet formulation (e.g., high-quality forage, increase the ratio of concentrate) [START_REF] Eugène | Methane mitigating options with forages fed to ruminants[END_REF], management intervention (e.g., improve feed efficiency), breeding, immunization, and defaunation (Beauchemin et al., 2020).

Recently, studies have shown that algae have a high ability to mitigate ruminal methane emissions in vitro and in vivo [START_REF] Machado | Effects of marine and freshwater macroalgae on in vitro total gas and methane production[END_REF], Li et al., 2016). Algae is a natural animal feed source in many countries [START_REF] Tiwari | Seaweed sustainability-food and nonfood applications[END_REF], making it a potential methanogenesis inhibitor in ruminants. Additionally, electron acceptors such as nitrate and phenolic compounds are effective methanogenesis inhibitors by completing available dihydrogen with methanogens [START_REF] Doreau | Linseed plus nitrate in the diet for fattening bulls: effects on methane emission, animal health and residues in offal[END_REF][START_REF] Rongcai | Phloroglucinol reduced methane production and hydrogen accumulation in vitro[END_REF]. In this review, we discuss the use of algae and electron acceptors as methanogenesis inhibitors in the ruminant sector.

Algae

Algae can be categorized as either macroalgae (seaweed) or microalgae. Seaweed can be further categorized into three main groups based on their pigmentation: green seaweeds (Chlorophyta), red seaweeds (Rhodophyta), and brown seaweeds (Ochrophyta Phaeophyceae) [START_REF] Hashim | Biosorption of cadmium by brown, green, and red seaweeds[END_REF]. The nutrient composition of algae is highly variable and depends on the factors such as species, habitat, and collection time. Algae are known to contain various bioactive compounds, including steroids and unsaturated fatty acids [START_REF] Harwood | The versatility of algae and their lipid metabolism[END_REF]. Additionally, red and brown seaweeds are known to contain halogenated compounds, and some brown seaweeds (such as Sargassum Fucus, and Ascophyllum nodosum) possess antioxidant activity due to the presence of phenolic compounds [START_REF] Holdt | Bioactive compounds in seaweed: functional food applications and legislation[END_REF].

The history of using algae as methanogenesis inhibitor and the related bioactive compounds

The use of algae as potential methanogenesis inhibitor started in the mid-2000 based on the amount and composition of their lipids because the role of lipids in decreasing methane production in ruminants was already known [START_REF] Swift | The effect of dietary fat on utilization of the energy and protein of rations by sheep[END_REF]. [START_REF] Ungerfeld | Effects of two lipids on in vitro ruminal methane production[END_REF] found that hexadecatrienoic acid extracted from the Hawaiian Chaetoceros (microalgae) inhibited methane production in vitro batch fermentation. Later, [START_REF] Wang | Effects of phlorotannins from Ascophyllum nodosum (brown seaweed) on in vitro ruminal digestion of mixed forage or barley grain[END_REF] reported that phlorotannins extracted from Ascophyllum nodosum (brown seaweed) inhibited methane production in 24-h fermentation. Subsequently, [START_REF] Bozic | Effects of the methane-inhibitors nitrate, nitroethane, lauric acid, Lauricidin® and the Hawaiian marine algae Chaetoceros on ruminal fermentation in vitro[END_REF] investigated the use of whole Chaetoceros (microalgae) powder as a feed additive to inhibit rumen methane production. They found that adding Chaetoceros greatly reduced methane production, hypothesizing that the bioactive compound was hexadecatrienoic acid.

A few years later, [START_REF] Machado | Effects of marine and freshwater macroalgae on in vitro total gas and methane production[END_REF] evaluated the effect of 20 different seaweeds (including green, brown, and red seaweeds) on rumen methane production in vitro. They found that all seaweeds decreased methane production, with Dictyota bartayresii (brown seaweed) and A. taxiformis (red seaweed) exhibiting the greatest inhibitory effects, decreasing methane production by 92% and 99%, respectively. The authors suggested that the secondary metabolites, in particular isoprenoids for Dictyota bartayresii and volatile halogen compounds for A. taxiformis, were responsible for the decrease in methane production [START_REF] Machado | Effects of marine and freshwater macroalgae on in vitro total gas and methane production[END_REF]. It was reported that bromoform was the most abundant volatile halogenated compound, accounting for 80% of the essential oil extracted from A. taxiformis [START_REF] Burreson | Volatile halogen compounds in the alga Asparagopsis taxiformis (Rhodophyta)[END_REF]. Moreover, researchers found that bromoform concentration was 109-fold higher than the second abundant halogenated compound (dibromochloromethane) in A. taxiformis (Machado et al., 2016). Paul et al. (2006) reported that bromoform extracted from A. armata had anti-bacterial properties. More recently, it has been confirmed that A. taxiformis effectively inhibits methane production primarily due to its high concentration of bromoform (Machado et al., 2016). And Glasson et al. (2022) reported that bromoform acts both on the coenzyme M methyltransferase and the methyl-coenzyme M reductase to decrease methane production.

Seaweed inhibits methanogenesis in vitro

In vitro work showed that red seaweed, especially the red seaweed from the genus Asparagopsis, has been shown to be more effective than green and brown seaweeds in decreasing methane production [START_REF] Machado | Effects of marine and freshwater macroalgae on in vitro total gas and methane production[END_REF][START_REF] Maia | The potential role of seaweeds in the natural manipulation of rumen fermentation and methane production[END_REF][START_REF] Brooke | Methane Reduction Potential of Two Pacific Coast Macroalgae During in vitro Ruminant Fermentation[END_REF], Choi et al., 2021a, Choi et al., 2021b). This is likely because the high concentration of bromoform in Asparagopsis species [START_REF] Brooke | Methane Reduction Potential of Two Pacific Coast Macroalgae During in vitro Ruminant Fermentation[END_REF][START_REF] Nørskov | Targeted and untargeted metabolic profiling to discover bioactive compounds in seaweeds and hemp using gas and liquid chromatography-mass spectrometry[END_REF]. [START_REF] Machado | Effects of marine and freshwater macroalgae on in vitro total gas and methane production[END_REF] reported that including 16.7% of A. taxiformis (based on OM) decreased methane production by 99%, but also decreased total gas production by 62%, and total VFA concentration by 47%. To determine the optimal inclusion dose, a lower dose-response experiment was conducted with ten levels of inclusion (0, 0.07, 0.125, 0.25, 0.5, 1, 2, 5, 10, and 16.7 %, based on OM) (Machado et al., 2016). They found that 1% inclusion level of A. taxiformis decreased methane production by 85% with a 17% decrease in total VFA and a 32% decrease in total gas production. Later, Kinley et. al. (2016) found that 2% inclusion level of A. taxiformis (based on OM) eliminated methane production without negatively effecting total VFA concentration or feed digestion.

However, these three in vitro studies did not measure the bromoform concentration in the A. taxiformis. Thus, we still do not know the optimal inclusion level of A. taxiformis in in vitro fermentation. Later, Machado et al. (2016) measured the bromoform concentration

(1.7 mg/g bromoform based on DM) in A. taxiformis and found that 2% of A. taxiformis (based on OM) decreased methane production by 95%, with TGP decreased by 25% without negatively affecting total VFA production and organic matter digestion. Therefore, 2% inclusion level of A. taxiformis was recommended as the highest inclusion level when the bromoform concentration is 1.7 mg/g as it has minimal negative effects on in vitro fermentation (Machado et al., 2016).

In addition, 2% inclusion of A. taxiformis (based on OM) altered the community structure of methanogens by decreasing the abundance of Methanobacteriales, Methanomassiliicoccales, and Methanomicrobiales [START_REF] Machado | In vitro response of rumen microbiota to the antimethanogenic red macroalga Asparagopsis taxiformis[END_REF]. Roque et. al.

(2019a) also reported that 5% inclusion level of A. taxiformis altered the relative abundance of methanogens and changed the bacterial community structure by betadiversity analysis.

Seaweed inhibits methanogenesis in vivo

Li et. al. (2016) first reported that A. taxiformis decreased methane production in sheep in a dose-dependent manner, with inhibition rate from 53% to 81% when the A.

taxiformis (based on OM, lower than 0.4 g/kg halogenated compounds on DM basis) was included at levels between 0.5% and 3%. Total VFA concentration, dry matter intake (DMI), and live weight were not affected when inclusion of 0.5% A. taxiformis (Li et al., 2016). In another study, Roque et al. (2019b) found that inclusion of 0.5% and 1% A.

armata (based on OM, bromoform concentration was 1.3 mg/g based on DM) decreased methane yield by 20.3% and 42.7%, respectively, but also decreased DMI by 10.8% and 38%, respectively. Moreover, milk yield decreased by 11.6% at the 1% inclusion level (Roque et al., 2019b). The effects of Asparagopsis on methane inhibition rate and DMI differ in these two studies despite the similar Asparagopsis inclusion level. These discrepancies could be explained by the factors such as bromoform concentration in Asparagopsis, animal species, diet, and the inclusion method of Asparagopsis. Kinley et al. (2020) investigated the effects of A. taxiformis with a high concentration of bromoform (6.6 g/kg DM) at inclusion levels of 0.1% and 0.2% (based on OM). They found that these low inclusion levels decreased methane yield by 38% and 98%, respectively, while increasing weight gain by 53% and 42%, respectively. Importantly, these inclusion levels did not negatively impact DMI or total VFA concentration. In another study, which used A.

taxiformis with a high concentration of bromoform (based on OM, bromoform concentration was 7.8 g/kg based on the DM), the authors found that inclusion of 0.25%

A. taxiformis decreased steer methane production by 36%, 51%, and 72% when fed high (60%), medium (40%), and low (11%) forage diets, respectively. Moreover, this inclusion level in different diets did not have negative effects on DMI, average daily gain, and feed conversion efficiency (Roque et al., 2021).

Overall, these studies suggest that using high-bromoform-containing Asparagopsis allows for decreased inclusion levels, which may minimize negative effects on DMI and animal performance. However, more research is needed to fully understand the effects of Asparagopsis on methane production and DMI, particularly when using low inclusion levels and high-bromoform-containing seaweed.

Factors affecting the antimethanogenesis ability of seaweed

The efficacy of Asparagopsis in inhibiting methanogenesis is directly related to the concentration of the bioactive compound bromoform. Any factors that decrease the concentration of bromoform in Asparagopsis will decrease its inhibitory efficacy. Stefenoni et. al. (2021) observed that the methane-inhibition power of A. taxiformis was not stable in a four-month duration study, with high efficiency in the first two months that decreased thereafter. They have confirmed that bromoform concentration in the A.

taxiformis linearly decreases during storage, while exposure to light accelerates the decrease process but storage temperature does not have a significant effect on bromoform concentration (Stefenoni et al., 2021). Additionally, the processing method of A. taxiformis is another key factor in preserving bromoform concentration. Vucko et. al.

(2017) examined the effect of processing factors including rinsing (unrinsed/dip rinsed/submerged), freezing (frozen/not frozen), and drying (freeze-dried/ kiln-dried/ dehydrated) on bromoform concentration in the A. taxiformis, and found that unrinsed, frozen, and subsequently freeze-dried were the most effective processing method to maintain bromoform concentration. Other factors such as harvest time, growth phase, habitat, and bromide concentration in the sea may also influence bromoform concentration in A. taxiformis (Paul et al., 2006[START_REF] Félix | The biotechnological potential of Asparagopsis Armata: What is known of its chemical composition, bioactivities and current market?[END_REF].

Animal health and animal products safety concerns when using seaweed as a methanogenesis inhibitor

The use of seaweed as a feed additive may raise concerns about animal health and safety of animal products. Li et. al. (2016) first reported that inclusion of A. taxiformis led to ruminal mucosa granulomatosis and keratosis. These findings were confirmed by Muizelaar et. al. (2021), who observed rumen wall inflammation and the absence of rumen papillae. However, these observations were based on a small number of animals, thus, further experiments with a larger sample size are necessary to verify these results.

In addition, both Li et. al. (2016) and Stefenoni et. al. (2021) reported that A. taxiformis decreased alanine transaminase (ALT) concentration in plasma, which is an indicator of liver cell damage.

A. taxiformis has a high concentration of bromide (mainly bromoform) and iodine, which may transfer into milk and meat when used it as feed additive. Stefenoni et. al.

(2021) reported that inclusion of 0.5% A. taxiformis (based on the DM) for 112 d did not increase bromoform concentration in the milk or alter the milk sensory properties, while it significantly increased milk bromide and iodine concentrations. In contrast, Roque et. al.

(2019b) reported that the inclusion of 1% A. armata (based on OM) for 63 d numerically increased milk bromoform concentration, although this concentration is much lower than the allowed bromoform concentration in drinking water. For meet, bromoform was not detected in the muscle and adipose fat of sheep when inclusion of 3% A. taxiformis (based on OM) in the diet for 72 d (Li et al., 2016). Similarly, Kinley et. al. (2020) observed that the meat quality of steers was not affected by inclusion of 0.2% A.

taxiformis (based on OM) for 90 d and bromoform was not detected in the fat, meat, and kidney tissues. Roque et. al. (2021) found that bromoform was not detected in meat and liver tissues, and the quality of the meat was not affected by inclusion of A. taxiformis for 147 d, however, the iodine concentration in strip loin was significantly increased by A.

taxiformis supplementation, although this concentration is below the tolerable upper intake level for human consumption of foods specified by the US Food and Nutrition Board of the National Academy of Sciences (Roque et al., 2021).

Electron acceptors

An electron acceptor is a chemical compound that can accept electrons in redox reactions. In the rumen, fumarate and carbon dioxide are the primarily electron acceptors (Ungerfeld, 2020). The mechanism by which electron acceptors decrease methane production is by competing with hydrogenotrophic methanogens for available dihydrogen.

Meanwhile, some electron acceptors, such as nitrate, could also directly inhibit methanogens (Guyader et al., 2015b).

Several compounds have been tested as electron acceptors to reduce ruminal methane production, including nitrate [START_REF] Van Zijderveld | Nitrate and sulfate: effective alternative hydrogen sinks for mitigation of ruminal methane production in sheep[END_REF][START_REF] Doreau | Linseed plus nitrate in the diet for fattening bulls: effects on methane emission, animal health and residues in offal[END_REF], sulfate [START_REF] Judy | Reducing methane production with corn oil and calcium sulfate: Responses on whole-animal energy and nitrogen balance in dairy cattle[END_REF], fumarate [START_REF] Asanuma | Effect of the addition of fumarate on methane production by ruminal microorganisms in vitro[END_REF], and phenolic compound such as phloroglucinol (Martinez-Fernandez et al., 2017). Calcium nitrate has been shown to decrease methane production in nonlactating cows (Guyader et al., 2015a, Guyader et al., 2015b). However, high nitrate inclusion levels may result in side effects such as a decrease in milk protein yield, an increase in blood methemoglobin level, and a decrease in hemoglobin level [START_REF] Van Zijderveld | Persistency of methane mitigation by dietary nitrate supplementation in dairy cows[END_REF]. Therefore, Beauchemin et al. (2020) recommended that the inclusion level of nitrate should not be exceed 2% (based on DM).

Inclusion of 0.93% calcium sulfate (based on DM) has been shown to decrease methane yield by 11.2%, and to decrease apparent organic matter digestibility, but did not have adverse effects on DMI or milk yield [START_REF] Judy | Reducing methane production with corn oil and calcium sulfate: Responses on whole-animal energy and nitrogen balance in dairy cattle[END_REF]. However, sulfate is less effective than nitrate and can be toxic to animals when included at high level [START_REF] Hegarty | Mechanisms for competitively reducing ruminal methanogenesis[END_REF].

phenolic compounds

Phenolic compounds, including flavonoids, phenolic acids, and tannins, share a common chemical structure that includes at least one aromatic ring with one or more hydroxyl substituents [START_REF] Ayad | Phytochemistry and biological activities of algerian Centaurea and related genera[END_REF]. This literature review focuses on gallic acid, which is the subunit of hydrolysable tannins. Tannins are plant secondary metabolites present in legumes, cereals, grains, and other feedstuffs [START_REF] Roca-Fernández | Ruminal fermentation and enteric methane production of legumes containing condensed tannins fed in continuous culture[END_REF]. There are two classes of tannins in plants: hydrolysable tannins and condensed tannins. Hydrolysable tannins can be broken down into phenolic constituents, mainly gallic acid, by the ruminal microbiota. The ruminal microbiota then converts gallic acid into pyrogallol, which is further converted into phloroglucinol or resorcinol (McSweeney et al., 2001). Phloroglucinol degradation requires NADPH, this is the mechanism by which phenolic compounds have the potential to work as electron acceptors.

Several researchers have isolated rumen bacteria that can degrade phloroglucinol.

Tsai and Jones (Tsai and Jones, 1975) isolated 8 strains of phloroglucinol-degradation bacteria from rumen, 5 of them belong to Streptococcus bovis and the other belong to

Coprococcus. Later, [START_REF] Patel | Catabolism of phloroglucinol by the rumen anaerobe Coprococcus[END_REF] purified phloroglucinol reductase from

Coprococcus sp. Pe15 and found that it was NADPH-dependent reductase. Meanwhile, other researchers isolated another phloroglucinol-degradation bacterium Eubacterium oxidoreducens sp. nov. from rumen (Krumholz and Bryant, 1986). Tsai et. al. (1976) speculated that Coprococcus sp. Pe15 decomposes 1 molecule of phloroglucinol to produce 2 molecules of carbon dioxide, and 2 molecules of acetate according to the end products and their ratios in pure culture. Evans (1977)

Knowledge gap

In the rumen, methanogens use dihydrogen and carbon dioxide to produce methane.

To date, we can achieve around a 25% methanogenesis inhibition rate without negatively affecting ruminants' health and productivity. When methane production is inhibited, dihydrogen accumulates in the rumen; though alternative hydrogenotrophic pathways are present, all the dihydrogen is not consumed, and just a small proportion erupts. Our current knowledge of the dihydrogen economy in rumen is incomplete, and an improved understanding of microbial pathways involved in dihydrogen metabolism is required.

Hypotheses and objectives

Evidence suggests that alternative hydrogenotrophs can prosper in the rumen and uptake dihydrogen when methanogenesis is inhibited. We hypothesized that adding alternative electron acceptors to the rumen could enhance these pathways and redirect the excessive dihydrogen toward nutritionally beneficial sinks. The objective of the work presented in this manuscript was to evaluate the potential of phenolic compounds to serve as alternative hydrogen acceptors; as phenolic compounds are metabolized to VFA, we aimed at assessing the effects on ruminant production. To achieve this aim, we performed an in vitro experiment to test a range of phenolic compounds as hydrogen acceptors and investigate their effects on rumen microbiota when methanogenesis was inhibited. We also performed an in vivo experiment to build a methanogenesis-inhibited model in cows and test the impact of the selected phenolic compound on animal performance, gas emissions, rumen microbiota, and blood metabolites.

Introduction

In this in vitro experiment, we screened a range of phenolic compounds as dihydrogen acceptors and selected the best candidate for the in vivo experiment. We hypothesized that when methanogenesis is inhibited, the addition of phenolic compounds may enhance the rumen phenolic-degrading bacteria to capture the excessive dihydrogen and generate nutrients. The objective of this chapter is to find the best phenolic compounds as dihydrogen acceptor by screening a range of phenolic compounds in vitro.

Experiment design

Exp.1 Supplementation of phloroglucinol also increased total volatile fatty acid (VFA), acetate, butyrate, and total gas production, and decreased ammonia concentration. This study indicates that some phenolic compounds, particularly phloroglucinol, which are naturally found in plants, could improve cow's VFA production, decrease H2 accumulation and synergistically decrease CH4 production in the presence of antimethanogenic compounds.

Key words: phloroglucinol; methane inhibitor; dihydrogen accumulation; rumen fermentation; volatile fatty acid

Implications

Antimethanogenic additives can decrease the environmental hoofprint of ruminants.

However, inhibition of methane production increases H2 accumulation in the rumen and does not result in the production of useful end products for the host ruminant. This work evaluated the capacity of seven phenolic compounds to decrease rumen H2 build-up and improve fermentation when methane production was inhibited in vitro. Phloroglucinol and also gallic acid decreased H2 accumulation, archaeal abundance, and increased total volatile fatty acids, notably through acetate production. This study shows that H2 acceptors like phloroglucinol have the potential to improve fermentation when methane inhibitors are used in the diet.

Introduction

Methane (CH4) production in livestock sector accounting for 6% of anthropogenic greenhouse gas emissions and ~40% of total greenhouse gas emissions in livestock sector (Gerber et al., 2013). Reducing enteric CH4 emissions is important for the sustainability of the ruminant sector, and several approaches are being investigated (Beauchemin et al., 2020). One of the most effective strategies is the inhibition of methanogenesis using feed additives. The macroalgae A. taxiformis and the synthetic compound 3-nitrooxypropanol are effective feed additives showing a consistent reduction in enteric CH4 emissions (Li et al., 2016, Dijkstra et al., 2018, Roque et al., 2021).

Methane production also results in dietary energy losses of between 2 and 12% for ruminants (Johnson and Johnson, 1995b). Theoretically, it may be expected that the feed energy saved by decreasing CH4 production would improve the energy balance of the host animal. However, animal productivity does not increase correspondingly (Ungerfeld, 2018). For example, no differences in milk production were observed in a dairy cow study where CH4 production was decreased 26% by 3-nitrooxypropanol (Melgar et al., 2020), although the authors estimated an additional 0.4 kg/d of milk could have potentially been produced. In another study on sheep, a decrease of up to 80% in CH4 yield induced by AT inclusion did not improve liveweight gain (Li et al., 2016). This lack of concordance between energy saved by decreasing enteric CH4 production and theoretical increases in animal performance remains largely unexplained (Ungerfeld, 2018). Dihydrogen (H2) is the main substrate for rumen methanogens to produce CH4 (Morgavi et al., 2010b), and it accumulates in the rumen when methanogenesis is inhibited (Janssen, 2010, Ungerfeld, 2020). In theory, H2 accumulation could limit the regeneration of reduced cofactors (NADH, Fdred), decreasing nutrient catabolism [START_REF] Wolin | Microbe-microbe interactions. The rumen microbial ecosystem[END_REF]. However, in situ [START_REF] Nolan | Effects of dietary nitrate on fermentation, methane production and digesta kinetics in sheep[END_REF][START_REF] Martínez-Fernández | Effects of ethyl-3-nitrooxy propionate and 3-nitrooxypropanol on ruminal fermentation, microbial abundance, and methane emissions in sheep[END_REF], Zhang et al., 2020) and in vivo total tract [START_REF] Jayanegara | Use of 3-nitrooxypropanol as feed additive for mitigating enteric methane emissions from ruminants: A meta-analysis[END_REF], Ungerfeld, 2018[START_REF] Kim | The effects of dietary supplementation with 3-nitrooxypropanol on enteric methane emissions, rumen fermentation, and production performance in ruminants: A meta-analysis[END_REF] apparent digestibility was not negatively affected by increased H2 concentrations. Also, volatile fatty acid (VFA) concentrations were unaffected when adjusted by changes in dry matter intake, although effects on VFA production have not been fully characterised. Feed energy lost via H2 eructation resulting from the inhibition of methanogenesis is relatively minor, although variable and dependent on the extent of methanogenesis inhibition (Ungerfeld et al., 2022). It is of interest to investigate if, when methanogenesis is inhibited, the rumen microbiota could use H2 (otherwise expelled) to retain its energy in useful end products for the host animal, and if this could result in improved feed efficiency and productivity.

Rumen microbes can use H2 or formate to catabolize phenolic compounds such as gallate, pyrogallol, and phloroglucinol to generate VFA (Evans, 1977, Krumholz andBryant, 1986b). It was reported that phloroglucinol decreased the ratio mol H2/mol CH4, increased acetate concentration, and improved weight gain in beef cattle when methanogenesis was inhibited by chloroform (Martinez-Fernandez et al., 2017). In this study, we screened a range of phenolic compounds for their potential as H2 acceptors in rumen fluid from dairy cows. We hypothesized that when methanogenesis is inhibited in the rumen, phenolic compounds can act as H2 acceptors to capture excess H2 and produce useful end products. This study used rumen fluid from lactating dairy cows to investigate in in vitro incubations: 1) the dose responses of various phenolic compounds on fermentation; 2) the effects of combining phenolic compound with a methanogenesis inhibitor; 3) the effects of a selected phenolic compound combined with a methanogenesis inhibitor in a longer incubation using sequential batch incubations. This work is part of a larger study in which these experiments were replicated using goats as rumen fluid donors (Romero et al., companion paper). These two ruminant species develop different rumen microbial communities as a result of their production system and host control (Henderson et al., 2015a, Corral-Jara et al., 2022b). In addition, goats and cows have shown different response to the presence of phenolic compounds in the diet [START_REF] Robbins | Role of tannins in defending plants against ruminants: Reduction in dry matter digestion?[END_REF], which could result in distinct responses to the treatments evaluated in this study.

Material and methods

Holstein dairy cows used as rumen fluid donors were housed at the INRAE UE1414 Herbipôle Unit (Saint-Genès Champanelle, France; https://doi.org/10.15454/1.5572318050509348E12). The study consisted of three in vitro experiments: dose responses of pre-selected phenolic compounds (Exp.1), individual phenolic compounds at 6 mM combined with a methanogenesis inhibitor (AT at 1.5% or 2.5% of substrate on a DM basis or 3 μM 2-bromoethanesulfonic sodium (BES)) (Exp.2), and longer-term effects of phloroglucinol combined with a methanogenesis inhibitor (Exp.3).

Substrates and methanogenesis inhibitors preparation

Alfalfa hay and barley grain ground through a 1-mm sieve were used as substrates for incubation. A. taxiformis, a red macroalgae, and BES were chosen as methanogenesis inhibitors in this study. A. taxiformis was obtained from SeaExpert (Faial, Portugal) and its bromoform concentration was 6 mg/g DM. It was freeze-dried and ground using a laboratory mill (IKA All analytical mill, Staufen, Germany). Two milling cycles (30s) were performed, cooling down the mill with liquid nitrogen between cycles to preserve AT chemical integrity. The milled AT was filtered through a polyester monofilament fabric (1 mm aperture) and stored at 4 °C in a glass bottle sealed with a rubber stopper. 2-Bromoethanesulfonate was obtained from Sigma-Aldrich (Darmstadt, Germany), and a 10 mM stock solution was prepared and stored at 4 °C.

Experiment 1: Dose-responses of phenolic compounds

This experiment focused on selecting the highest inclusion concentration of phenolic compounds without negatively affecting fermentation. Seven phenolic compounds were pre-selected based on their theoretical capacity to incorporate H2 during their degradation process. The phenolic compounds used in this study were phenol, catechol, resorcinol, hydroquinone, pyrogallol, phloroglucinol, and gallic acid. Also, formic acid, a fermentation intermediate, which releases H2 and thus acts as an electron donor in the rumen (Leng, 2014b), was used as a positive control. All phenolic compounds were obtained from Sigma-Aldrich (Darmstadt, Germany). Phenolic compounds were dissolved in ethanol to prepare stock solutions at a concentration of 1 mol/L for phenol, catechol, resorcinol, hydroquinone and pyrogallol, and 0.5 mol/L for phloroglucinol and gallic acid. The stock solutions were stored in amber glass bottles at 4 °C. We tested four concentrations (0, 2, 4, and 6 mM in the fermentation fluid) of each phenolic compound based on published work [START_REF] Murray | Effect of simple phenolic compounds of heather (calluna vulgaris) on rumen microbial activity in vitro[END_REF][START_REF] Getachew | Influence of tannic acid application on alfalfa hay: In vitro rumen fermentation, serum metabolites and nitrogen balance in sheep[END_REF]Sarwono et al., 2019). The 0 mM concentration contained only the mixed alfalfa hay and barley grain substrate as a control. The required amount of each stock solution was added into a 125-mL serum bottle used for the incubation, and the ethanol was evaporated under a stream of O2-free CO2 before adding the substrates. Formic acid was directly added to the bottle after inoculation.

Four rumen-cannulated lactating Holstein cows were used as rumen inoculum donors. The cows were fed ad libitum a ration containing 67% forage (corn silage and grass silage) and 33% of concentrate (corn and soybean meal) on a DM basis, twice per day. Cows had free access to water and mineral salt blocks. Rumen contents were collected through the rumen cannula before the morning feeding, placed into pre-heated 1-L thermal flasks and immediately transported to the laboratory. The rumen content from each animal was processed separately by straining through a polyester monofilament fabric (250 µm aperture) to obtain individual rumen fluids. The rumen fluid from each cow was subsequently mixed with warm (39 °C) anaerobic buffer solution at a 1:2 (volume to volume) ratio under a stream of O2-free CO2 [START_REF] Mould | A review and simplification of the in vitro incubation medium[END_REF], Yáñez-Ruiz et al., 2016). A 50 mL rumen fluid-buffer mixture was anaerobically dispensed into 125-mL serum bottles containing 500 mg of substrates composed of alfalfa hay and barley grain (70% and 30% in DM, respectively). Each batch incubation included a blank consisting of rumen fluid-buffer mixture from each cow with no substrate. The bottles were incubated in a water bath at 39 °C for 24 h. At 6 and 24 h incubation, gas pressure was measured using a pressure transducer (GE Sensing, Druck), and a 5-mL gas sample was collected with a syringe followed by the release of excess gas until the pressure in the headspace equalized to the atmospheric pressure. Following gas sampling at 24 h incubation, fermentation liquid was collected for VFA and ammonia analysis as described below. The total number of experimental units was [8 treatments (seven phenolic compounds and formic acid) × 3 concentrations (2, 4, and 6 mM) + 1 control (substrate alone without treatment)] × 4 (cows) = 100 that were used in the statistical analysis (see below). Rumen inocula from individual cows were considered biological replicates (n= 4).

Experiment 2: Effect of phenolic compounds when methanogenesis was inhibited

This experiment was designed to assess the effects of phenolic compounds under methanogenesis inhibition in a 24-h incubation period. Based on Exp. 1 results', phenolic compounds were used at a concentration of 6 mM. A preliminary dose-response study with both AT and BES (performed under the same conditions and using the same donor cows) was used to obtain three distinct methanogenesis inhibition rates. These two different anti-methanogenic additives were chosen to verify that the effect of phenolic compounds, as H2 acceptors, was not limited to a specific inhibitor. A low inhibition rate (~20%) was achieved with 1.5% AT, a medium inhibition rate (~50%) with 3 μM BES, and a high inhibition rate (~75%) with 2.5% AT. An independent run was performed with 10 treatments for each methanogenesis inhibitor: substrate alone, substrate + methanogenesis inhibitor (control), and substrate + methanogenesis inhibitor + individual phenolic compounds or formic acid. Incubation procedures and sample collection were as Exp.1. The total number of experimental units were 10 treatments × 3 (inhibitors) × 4 cows = 120 observations that were used in the statistical analysis (see below). Rumen inocula from individual cows were considered biological replicates (n= 4).

Experiment 3: Sequential batch incubation with phloroglucinol combined with 2-bromoethanesulfonate

This experiment used sequential batch incubation to evaluate the effect of phloroglucinol on fermentation in the presence or absence of BES over a longer incubation period (Figure 6). Phloroglucinol was chosen because it was the most promising compound in the previous experiment among all seven tested phenolic compounds, whereas BES was chosen for practical reasons as it was easier to dose in the sequential batch incubations. We conducted three sequential 24-h incubations for stabilizing and adapting the rumen microbes to phloroglucinol, followed by a fourth 24-h incubation and a fifth 72-h incubation with or without BES, in addition to the phloroglucinol treatment. There were two treatments in the first, second, and third incubations: control and 36 mM phloroglucinol. The concentration of phloroglucinol was based on the absence of negative effects on fermentations that was tested in preliminary experiments using the same conditions (not shown), and it was similar to the estimated concentration used in steers by Martinez-Fernandez et al. (2017). At the end of the third incubation (day 4), control flasks were split into control (as in previous batches) and 3 μM BES treatments, whereas phloroglucinol flasks were split into phloroglucinol (as in previous batches) and 3 μM BES + 36 mM phloroglucinol treatments. We used 8 lactating Holstein cows as rumen fluid donors; cows were fed the same diets as described for Exp. 1 and 2. The first inoculation was performed as in Exp. 1 and for the subsequent batches, one third of incubation fluid from the previous batch bottle was mixed with two-thirds of anaerobic buffer and used to inoculate the next corresponding serum bottle containing fresh substrate. After 6 and 24 h incubation of the first and second incubations, gas pressure was measured, followed by the release of excessive gas. For the third to fifth incubations, gas samples for gas composition analysis and liquid samples for VFA and ammonia analysis were collected as in Exp. 1. Additionally, 1 mL of incubation fluid was collected and centrifuged at 16 000 g for 15 min at 4 °C. After the centrifugation, the supernatant was discarded, and the pellet was stored at -20 °C until gDNA extraction. For phloroglucinol analysis, 5 mL of fermentation fluid were collected and stored at -20 °C.

Sample analysis

The nutrient composition of the substrate was analysed as described in Arco-Pérez et al. (2017). Chemical composition (in g/kg DM) of the alfalfa hay was 901 organic matter, 27.9 nitrogen, 428 NDF, 303 ADF, 63 ADL and 13.7 ether extract, while barley grain contained 975 organic matter, 21.5 nitrogen, 285 NDF, 67.8 ADF, 8.7 ADL and 20.1 ether extract.

Gas composition (CH4, H2, and CO2) was analysed within 12 h after sample collection using micro gas chromatography (Micro GC Fusion, INFICON). The micro-GC was calibrated using a certified gas standard mixture (Messer, France) containing CH4, O2, H2, CO2, and N2 [START_REF] Muñoz-Tamayo | Hydrogenotrophic methanogens of the mammalian gut: Functionally similar, thermodynamically different-a modelling approach[END_REF]. For VFA analysis, 0.8 mL of filtrate was mixed with 0.5 mL of 4 mg/mL crotonic acid and 20 mg/mL metaphosphoric acid in 0.5 M HCl and analysed by gas chromatography (PerkinElmer Clarus 580, Waltham, USA) as described [START_REF] Rira | Potential of tannin-rich plants for modulating ruminal microbes and ruminal fermentation in sheep[END_REF]. For ammonia, 1 mL fermentation fluid was mixed with 5% orthophosphate solution (0.1 mL) and measured according to the phenolhypochlorite reaction (Weatherburn, 1967b). Total gas production (TGP) in mL was calculated using the Ideal Gas Law under standard atmospheric pressure and 39 °C.

Microbial gDNA was extracted using DNeasy PowerSoil Pro Kit (Qiagen, Germany) according to the manufacturer's instruction. Quantitative polymerase chain reaction (qPCR) was used to quantify the copies of the 16S rRNA gene for bacteria, mcrA gene for archaea, 18S rRNA genes for protozoa, and the region between 18S rRNA gene and ITS1 for anaerobic fungi. Primers and qPCR conditions were previously reported [START_REF] Palma-Hidalgo | Inoculation with rumen fluid in early life accelerates the rumen microbial development and favours the weaning process in goats[END_REF]. Ethyl acetate was used to extract residual phloroglucinol [START_REF] Kim | Determination of phloroglucinol in human plasma by high-performance liquid chromatography-mass spectrometry[END_REF], and HPLC (LC1260, Agilent, Les Ulis, France) was used to determine phloroglucinol as described [START_REF] Maxin | Carotenoid, tocopherol, and phenolic compound content and composition in cover crops used as forage[END_REF]. The stochiometric metabolic hydrogen recovery was calculated from fermentation products VFA, CH4 and H2 production (adapted from [START_REF] Demeyer | Quantitative aspects of microbial metabolism in the rumen and hindgut. Rumen microbial metabolism and ruminant digestion[END_REF] and was used as an indirect indicator of the reduction of phenolic compounds.

Statistical analysis

All data were checked for normality using the UNIVARIATE procedure of SAS (version 9.4, SAS Institute Inc., Cary, NC) before statistical analysis. Non-normally distributed data (gene copy counts) were log10-transformed before statistical analysis. For all experiments, the following model was run using the PROC MIXED procedure of SAS:

Yij =𝜇 + Pi + Aj + eij
Where Yij represents a dependent, continuous variable, µ is the overall population mean, Pi represents the fixed effect of treatment, Aj represents the random effect of the cow donor of rumen fluid, and eij is the residual error. The degree of freedom was calculated using the Satterth statement. The PDIFF statement was used to make multiple comparisons, P values were adjusted using the Dunnett statement for comparisons against the control in Exp.1 and Exp.2, and by the Tukey statement to account for multiple pair-wise comparisons for Exp. 3. Differences were considered significant at P < 0.05, trends were discussed at P ≤ 0.10.

Results

Dose-response effects of phenolic compounds (Exp. 1)

There was no negative effect of phenolic compounds or formic acid on ruminal fermentation and VFA concentration for any dose used (2, 4 and 6 mM). Table 2 shows the effect of phenolic compounds or formic acid at a concentration of 6 mM on fermentation parameters compared to the control (substrate alone) treatment. After 24 h incubation, 6 mM phloroglucinol and gallic acid increased (P = 0.017 and P < 0.001 respectively) TGP by 4% and 7%, respectively. Phloroglucinol increased (P < 0.001) TGP in the 6-24 h incubation period, while gallic acid increased TGP in the 0-6 h and 6-24 h periods (P = 0.001 and P = 0.007, respectively). Phloroglucinol also increased (P = 0.027) total VFA concentration by 20%, with a 10% increase (P < 0.001) in acetate proportion; additionally, propionate proportion decreased by 22% resulting in an increase (P < 0.001) in the acetate: propionate ratio. The electron donor formic acid was the only compound that influenced CH4 production, which increased (P < 0.001) by 14% between 0 and 6 h of incubation. None of the compounds affected H2 accumulation. Metabolic hydrogen recovery rate was ~76% under the assay conditions and was not affected by the phenolic compounds except for phloroglucinol and pyrogallol that showed lower values (P < 0.001 and P = 0.020, respectively). Supplementary Tables S1 andS2 show gas production values for 2-and 4-mM doses across treatments, respectively. These lower concentrations were not used in subsequent experiments. Abbreviations: TGP = total gas production; VFA = volatile fatty acid; A:P= acetate: propionate ratio.

1 Control: substrate alone with no phenolic compound or formic acid added.

2 Dunnett-Hsu was used to adjust P-value.

* Indicates P < 0.05, compared to control containing substrate alone and no phenolic compound added.

3.2 Effect of phenolic compounds when methanogenesis was inhibited (Exp. 2)

Methane production was decreased by 22, 51 and 75% by 1.5% AT, 3 μM BES, and 2.5% AT, respectively, compared to controls (Table 3 and supplementary Tables S3 andS4). Table 2 shows the effects of phenolic compounds combined with 2.5% AT. The effects of phenolic compounds combined with 1.5% AT, which induced a low-medium inhibition rate (22%), and with 3 μM BES, which induced a medium inhibition rate (51%),

were similar to that of 2.5% AT and are shown in supplementary Tables S3 andS4, respectively. Dihydrogen accumulation in the gas headspace after 6-h incubation was 1 Substrate alone in the first column (mean ± SE) is provided for information.

2 Dunnett-Hsu was used to adjust P-value.

* Indicates P < 0.05, compared to AT containing substrate and AT but no phenolic compound added.

3.3 Longer-term effect of phloroglucinol on in vitro incubation (Exp.

3)

The sequential batch incubation technique evaluated the effect of phloroglucinol supplementation on fermentation parameters and microbial abundance over several incubation days. Table 4 shows the results with and without addition of the methanogenesis inhibitor BES after three 24-h sequential incubations used to adapt rumen cultures to phloroglucinol. Phloroglucinol treatment nominally increased (P = 0.074) TGP and inhibited (P < 0.001) CH4 production in comparison with the control.

Interestingly, although CH4 production was inhibited, phloroglucinol increased H2 accumulation only nominally (P = 0.37) compared to the control. Phloroglucinol increased (P < 0.001) total VFA concentration by 59%, with increments in acetate (P < 0.001) and butyrate (P < 0.001) proportion of 29% and 58%, respectively, compared to the control. In contrast, phloroglucinol decreased propionate proportion (P < 0.001) and ammonia concentration (P < 0.001). Thus, phloroglucinol sharply increased (P < 0.001) the acetate: propionate ratio. Also, phloroglucinol decreased archaeal (P < 0.001) and fungal (P = 0.079) abundances, whereas it increased bacterial (P = 0.002), and had no effect on protozoal (P = 0.80) abundance, compared to the control. Abbreviations: BES = 2-bromoethanesulfonic sodium; PHL = phloroglucinol; TGP = total gas production; VFA = volatile fatty acid; A:P = acetate: propionate ratio.

1 Control: Substrate alone, no chemical compound added.

a,b,c,d Values within a row with different superscripts differ significantly at P < 0.05.

Adding BES decreased (P < 0.001) CH4 production by 70% and increased (P < 0.001) H2 accumulation tenfold, compared to control. Phloroglucinol + BES increased (P < 0.001) TGP and suppressed (P < 0.001) CH4 production, compared to BES treatment.

Interestingly, the combination of phloroglucinol + BES decreased (P = 0.001) H2

accumulation by 72% compared to BES alone. Phloroglucinol + BES increased (P < 0.001) total VFA concentration by 77%, with increments in acetate (P < 0.001) and butyrate (P = 0.001) proportions of 42% and 22%, respectively, compared to the BES treatment. In contrast, phloroglucinol + BES decreased (P < 0.001) propionate proportion, and consequently, markedly increased (P < 0.001) the acetate: propionate ratio. Phloroglucinol + BES treated cultures had lower (P < 0.001) ammonia concentration, lower archaeal (P < 0.001), and higher bacterial abundance (P = 0.013) than BES alone. In contrast, abundance of protozoa (P = 0.90) and anaerobic fungi (P = 0.93) were similar across treatments. Data from HPLC analysis at the third 24-h incubation show a reduction of phloroglucinol of more than 80% from the initial concentration. Similar results on fermentation parameters and on microbial abundance were found in the fifth sequential incubation (supplementary Table S5).

Discussion

Inhibiting methanogenesis in the rumen is accompanied by an increase in accumulated H2 in vitro and expelled H2 in vivo (Janssen, 2010). We speculated that the extra H2 released could be used by rumen microbes to produce useful compounds for the host ruminant provided the presence of enough concentration of phenolic compounds that could incorporate H2 in their reductive pathways. Phenolic compounds were considered suitable H2 acceptor alternatives because they are naturally present in plants containing hydrolysable tannins, mainly gallic acid, which is further converted to pyrogallol, phloroglucinol or resorcinol by the ruminal microbiota (McSweeney et al., 2001b). In addition, it was reported that Eubacterium oxidoreducens sp. nov. and

Coprococcus sp. Pe15 isolated from the rumen reduce some phenolic compounds using H2 or formate as electron donors to produce VFAs and/or CO2 (Tsai et al., 1976, Krumholz et al., 1987b). Eubacterium oxidoreducens degrades phloroglucinol to acetate and butyrate, whereas Coprococcus sp. degrade phloroglucinol to acetate (Conradt et al., 2016).

The seven phenolic compounds examined did not negatively affect in vitro fermentation at the doses used. Instead, 6 mM phloroglucinol increased total gas and VFA concentration, and in particular acetate proportion. The latter is in accordance with the expected end product of phloroglucinol degradation (Krumholz and Bryant, 1986b). In contrast, Sarwono et al. (2019) reported that adding 6 mM phloroglucinol decreased gas production, ammonia concentration, and CH4 production. Our results agree with [START_REF] Wei | Effects of gallic acid on in vitro rumen fermentation and methane production using rumen simulation (rusitec) and batch-culture techniques[END_REF], who found that up to 4.8 mM gallic acid did not affect total VFA, ammonia concentration, or CH4 production but increased TGP. We also observed that formic acid increased (P < 0.001) CH4 production after 6-h incubation. This was expected as formic acid is a substrate for rumen methanogens (Hungate et al., 1970b).

When CH4 production was inhibited, we observed, as anticipated, H2 accumulation in the headspace at 6 h of incubation. However, none of the phenolic compounds modified the concentration of H2. Despite this result, phloroglucinol in particular increased the proportion of acetate by up to 41% with a concomitant decrease in the extent of H2 recovery. The low hydrogen recovery suggests the reduction of these phenolic compounds to acetate. Likewise, gallic acid increased acetate proportion by 23%. In the rumen, gallic acid can be transformed by decarboxylation to pyrogallol that can be further converted to phloroglucinol or resorcinol. Phloroglucinol can then be reduced to dihydrophloroglucinol using H2 or formate as electron donor, and the ring cleavage of the dihydrophloroglucinol molecule can produce acetate and CO2 (Tsai et al., 1976[START_REF] Lotfi | A commentary on methodological aspects of hydrolysable tannins metabolism in ruminant: A perspective view[END_REF]. In contrast, the other phenolic compounds examined in this study did not increase acetate, likely because they were not used by the rumen microbiota in the conditions of the study.

A possible reason to explain why we did not observe any decrease in H2 could be due to the incorporation by phenolic compounds of other electron donors such as formate (Krumholz et al., 1987), although we did not determine formate concentration so as to understand the extent of formate utilisation in the reduction of phenolic compounds.

However, it is likely that the abundance of the rumen microbes capable of degrading phenolic compounds is low in the non-adapted rumen. In the rumen. Streptococcus bovis have the ability to catabolize phloroglucinol (Tsai and Jones, 1975b), but this bacterium is a minor member of the normal rumen microbiota [START_REF] Petri | Characterization of the core rumen microbiome in cattle during transition from forage to concentrate as well as during and after an acidotic challenge[END_REF]. Other more specialized bacteria known to utilize phloroglucinol as substrate, such as Coprococcus spp and Eubacterium oxidoreducens are also not predominant in the rumen.

Because of the expected low abundance of the bacteria able to degrade phenolic compounds and the low phloroglucinol concentration (lower than 5 μg/mL) in the donor cows' rumen fluid, we hypothesized that populations of rumen microbes that can metabolize phloroglucinol needed longer incubation times to grow to metabolize phenolic compounds. In this regard, it is known that diets containing tannins favour the overgrowth of resistant microbes able to degrade hydrolysable tannins [START_REF] Nelson | Isolation and characterization of an anaerobic ruminal bacterium capable of degrading hydrolyzable tannins[END_REF][START_REF] Krause | Tolerance mechanisms of streptococci to hydrolysable and condensed tannins[END_REF]. In order to examine this hypothesis, we performed a sequential batch incubation experiment using phloroglucinol as H2 acceptor and BES as the CH4 inhibitor.

Prolonged incubation with phloroglucinol increased total gas, total VFA, and acetate production, and decreased metabolic hydrogen recovery corroborating the results obtained with shorter 24-h incubations (Exp.2). Interestingly, we found that prolonged phloroglucinol treatment decreased CH4 production to undetectable concentrations, while only minimally increased H2 accumulation compared to the control. The phloroglucinol + BES treatment decreased H2 accumulation by 72% and almost totally inhibited CH4 production compared to BES alone. These results indicate that prolonged incubation could favour microbial communities able to utilize phloroglucinol as a H2 acceptor reducing H2 accumulation. Additionally, phloroglucinol without BES also increased butyrate proportion, which may be explained by the increase in acetate that can be converted to butyrate (Hackmann and Firkins, 2015). Butyrate production from acetate consumes metabolic hydrogen, which may also contribute to explain why phloroglucinol decreased H2 accumulation. Moreover, butyrate may also be a product of phloroglucinol degradation (Conradt et al., 2016).

The phloroglucinol concentration used in Exp.3 is similar to a previous study in steers (Martinez-Fernandez et al., 2017). Similar to our results, Martinez-Fernandez et al.

(2017) reported that when CH4 production was inhibited phloroglucinol decreased the amount of H2 expelled and increased rumen acetate proportion. In addition, we found that phloroglucinol alone decreased H2 accumulation and CH4 production. This latter disparity between the two studies may be due to differences between in vitro and in vivo methods and, eventually the types of diet and animals (dairy vs beef cattle).

The addition of phloroglucinol, decreased archaeal abundance and increased bacterial abundance, but had no negative effect on protozoal and fungal abundance (Table 4). It is noted that protozoa were not expected to survive in the sequential batch incubations. Abundance of protozoal 18S rRNA was low and may be the remnants of dead cells transferred in successive inocula. Abundance of fungi was also low, whereas the results of methanogens suggest a toxic effect of phloroglucinol on this community.

Similar effects were reported in anaerobic digestors of pig manure where the use of phenolic compounds such as pyrogallol decreased methanogenesis when incubated at comparable concentrations to our study [START_REF] Kayembe | Inhibitory effects of phenolic monomers on methanogenesis in anaerobic digestion[END_REF]. Further research is needed to clarify the mechanism of action of phenolic compounds on methanogens.

Phloroglucinol, as well as hydroquinone and pyrogallol strongly decreased ammonia concentration in vitro. It is known that dietary proteins bind to the hydroxyl moieties of phenolic compounds and this complex is more resistant to microbial degradation (McSweeney et al., 2001b). This phenomenon can decrease emissions of nitrous oxide, another potent greenhouse gas, from ruminant production systems. Low ammonia concentration in the rumen have been associated to decreases in urinary N excretion resulting in decreased emissions of nitrous oxide [START_REF] Carulla | Supplementation of acacia mearnsii tannins decreases methanogenesis and urinary nitrogen in forage-fed sheep[END_REF][START_REF] Dijkstra | Diet effects on urine composition of cattle and n2o emissions[END_REF]. Consistent with the lower ammonia concentration findings, we also observed that supplementation of phloroglucinol, with or without BES, decreased isobutyrate and isovalerate proportion, which originate from deamination of branched-chain amino acids and serve as a carbon skeleton in the synthesis of branched-chain amino acids [START_REF] Chen | Fermentation of peptides and amino acids by a monensinsensitive ruminal peptostreptococcus[END_REF]. Low branched-chain amino acid degradation or greater synthesis in the rumen may increase their availability for productive functions in the small intestine of the host ruminant.

The results presented here using the rumen fluid from lactating dairy cows as inocula are similar to those obtained with rumen fluid from goats (Romero et al., companion paper). However, the sensitivity to methane inhibitors was different as the same batch of AT that was used in both studies almost totally inhibited methane production from goat's rumen fluid at a concentration of 2%, whereas, a 2.5% AT concentration in cow's rumen fluid decreased methane production by 75%. As far as the effect of phenolic compounds, they were comparable in both animal species indicating that, at least for this parameter, the results can be extrapolated to different ruminant species.

Conclusion

We evaluated the effect of seven phenolic compounds on rumen fermentation of dairy cows when methanogenesis was inhibited in vitro and found that phloroglucinol and gallic acid, increased the proportion of acetate, a nutritionally important metabolite for the host animal. The decrease in H2 accumulation indicates that these compounds were successfully used as H2 acceptors. Phloroglucinol, probably because of its position at the end of the biotransformation of phenolic compounds into VFA was more effective at incorporating accumulated H2 and at generating acetate than gallic acid. Moreover, phloroglucinol alone also affected methanogenesis by decreasing methanogens' abundance. The dual effect of phloroglucinol as a H2 acceptor and methanogenesis inhibitor in dairy cows needs to be verified by further studies.

Ethics approval

The use of experimental animals followed the French Ministry of Agriculture guidelines and other applicable guidelines and regulations for animal experimentation in the European Union. Procedures for collecting rumen fluid were approved by the French Ministry of Education and Research (APAFIS #8218-20161151782412). Abbreviations: BES = 2-bromoethanesulfonic sodium; Phe = phenol; Cat = catechol; Res = resorcinol; Hyd = hydroquinone; Phl = phloroglucinol; Pyr = pyrogallol; GA = gallic acid; FA = formic acid; TGP = total gas production; VFA = volatile fatty acids; A:P = acetate: propionate ratio.

Supplemental material

1 Substrate alone in the first column (mean ± SE) is provided for information.

2 Dunnett-Hsu was used to adjust P-value.

* Indicates P < 0.05, compared to AT containing substrate and AT but no phenolic compound added.

Table S5 Effect of phloroglucinol with or without BES as methanogenesis inhibitor using a sequential batch culture incubation method and rumen fluid from dairy cows (n=8, fifth sequential batch).

Introduction

The samples used in this trial were from the longer-term incubation described in chapter 2 and the longer-term incubation from our Spanish co-operators (detailed in M&M). In the longer-term incubation, we observed that phloroglucinol and pyrogallol increased acetate production and decreased dihydrogen accumulation. We hypothesized that changes in fermentation parameters were due to changes in rumen microbiota. The objectives of this study were to identify the microbes responsible for the phloroglucinol and pyrogallol degradation and to compare the responses of cow and goat's rumen microbiota to phenolic compounds when using methanogenesis inhibitor.

Experiment design

Cow inocula experiment: using rumen fluid from cows  After three 24-h adaptation, there were four treatments: CTL, (control), BES (3 μM 2-bromoethanesulfonate), PHL (36 mM phloroglucinol), and BES+PHL (3 μM BES + 36 mM PHL) Goat inocula experiment: using rumen fluid from goats  After three 24-h adaptation, there were six treatments: CTL (control), AT (2% A.taxiformis), AT+PHL1 (2% AT + 6 mM phloroglucinol), AT+PHL2 (2% AT + 36 mM PHL); AT+PYR1 (2% AT + 6 mM pyrogallol), and AT+PYR2 (2% AT+ 36 mM PYR)

Main finding



In both experiments, PHL and PYR at 36 mM decreased bacterial α-diversity  Most bacteria taxa in cow and goat inocula experiments with increased abundances (including Lactobacillaceae, Bifidobacteriaceae, and Lachnospiraceae) were known with the phenolic compounds utilization, while the abundance of cellulolytic bacteria (including Fibrobacteraceae, Ruminococcaceae, and Succinivibrionaceae) decreased with this supplementation

Conclusion

The same microbial taxa were prompted in both experiments, attesting that 1) phenolic-degradating bacteria are naturally present in the two ruminant species and 2) their growth can be enhanced when methanogens are inhibited and phenolic compounds supplemented.

Phenolic compounds increased phenolic utilization bacteria abundance when methanogenesis was inhibited in vitro

Abstract

Two previous in vitro studies found that phloroglucinol and pyrogallol decreased ruminal dihydrogen accumulation and increased volatile fatty acid production when methanogenesis was inhibited. The present work builds upon the previous study describing the effects of these phenolic compounds on the bacterial community when methanogenesis was inhibited with rumen inoculum from cows and goats. There were four treatments in the cow inocula experiment: CTL, (control), BES (3 μM 2bromoethanesulfonate), PHL (36 mM phloroglucinol), and BES+PHL (3 μM BES + 36 mM PHL). There were six treatments in the goat inocula experiment: CTL (control), AT (2% A.

taxiformis), AT+PHL1 (2% AT + 6 mM phloroglucinol), AT+PHL2 (2% AT + 36 mM PHL); AT+PYR1 (2% AT + 6 mM pyrogallol), and AT+PYR2 (2% AT+ 36 mM PYR). In both experiments, PHL and PYR at 36 mM decreased bacterial alpha-diversity. Most bacteria taxa with increased abundances (including Lactobacillaceae, Bifidobacteriaceae, and Lachnospiraceae) were known with the phenolic compound utilization, while the abundance of cellulolytic bacteria (including Fibrobacteraceae, Ruminococcaceae, and Succinivibrionaceae) decreased with this supplementation. Although the structure of rumen bacterial community differed between cows and goats, about half of the bacterial clades whose abundance was affected by 36 mM PHL in the cow innocula experiment were equally affected by 36 mM PHL and PYR in the goat innocula experiment. These findings suggest that nutritional supplementation with phenolic compounds could modify the rumen bacterial community towards a more efficient rumen dihydrogen metabolism and ultimately as a methane mitigation strategy.

Introduction

The livestock sector plays an important role in climate change because it is one of the main anthropogenic methane sources (Gerber et al., 2013). Also, methane production in cattle wastes 2 to 12% of gross energy intake (Johnson and Johnson, 1995). In the rumen, bacteria, fungi, and protozoa ferment carbohydrates to volatile fatty acid (VFA) and reducing equivalents. The VFA is the primary energy source, while the reducing equivalents are used by hydrogenase to synthesize dihydrogen. Methanogens then use the dihydrogen and carbon dioxide to synthesize methane (Morgavi et al., 2010).

While current methane mitigation strategies can decrease methane production by approximately 25%, the saved feed energy resulting from decreased methane emissions is often not utilized to increase animal production (Ungerfeld, 2018). The key factor in improving animal production lies in the metabolism of dihydrogen when a methanogenesis inhibitor is used (Ungerfeld, 2020, Leahy et al., 2022). Therefore, different chemical compounds are used to redirect dihydrogen metabolism when methanogenesis is inhibited. For example, our previous works used nitrate as hydrogen acceptor (Guyader et al., 2015, Popova et al., 2017).

Additionally, in our previous in vitro works (Romero et at., 2023; Chapter 2), we observed that combing phloroglucinol with 2-bromoethanesulfonate (BES), and combing phloroglucinol or pyrogallol with A. taxiformis, decreased dihydrogen accumulation and further decreased methane production. Moreover, combing either phloroglucinol or pyrogallol with a methanogenesis inhibitor increased total VFA production. As both methane and VFA are produced by rumen microbes, we hypothesized that the changes in rumen fermentation were due to changes in the rumen microbes. Indeed, previous research has shown that bulls receiving a diet supplemented with phloroglucinol and the methanogenesis inhibitor chloroform had an increased abundance of Prevotella,

Coprococcus, Ruminococcus, Fibrobacter, CF231, and YRC22 (Martinez-Fernandez et al., 2017). The objectives of the present study were to identify the microbes in cows and goats involved in phloroglucinol and pyrogallol degradation and to compare the responses of rumen microbiota from small and big ruminants (goat and cow) to hydrogen acceptor when using methanogenesis inhibitor. 2.1 Cow inocula experiment: sequential batch incubation using rumen fluid from cows.

Materials and Methods

The inocula media preparation were described in Chapter 2 Exp.3. Briefly, rumen fluid were collected from 8 lactating Holstein cows what were fed ad libitum a diet consisting of 67% forage (corn silage and grass silage) and 33% of concentrate (corn and soybean meal) on a DM basis, twice per day. The cows had free access to water and mineral salt blocks. Rumen fluid was collected via esophageal tubing before morning feeding and transferred to preheated 1-L thermal flasks, which was transported to the laboratory without delay. Each animal's rumen fluid was processed separately, mixed with a warmed (39 °C) anaerobic buffer solution at 1:2 (volume to volume) ratio under a stream of O2-free CO2 (Yáñez-Ruiz et al., 2016). A 50 mL rumen fluid buffer mixture was anaerobically dispensed into 125 mL serum bottles containing 500 mg of substrates composed of alfalfa hay and barley grain (70% and 30% in DM, respectively).

We conducted three sequential 24-h incubations to stabilize and adapt the rumen microbes to phloroglucinol, followed by a fourth 24-h incubation combing phloroglucinol with BES as methanogenesis inhibitor. The first, second, and third incubations had two treatments: control and 36 mM phloroglucinol, the concentration of which was determined based on the absence of negative effects on fermentations from our preliminary trial. At the end of the third incubation, control flasks were split into control (CTL, as in previous batches) and 3 μM BES (BES) treatments, whereas phloroglucinol flasks were split into phloroglucinol (PHL, as in previous batches) and 3 μM BES + 36 mM phloroglucinol (BES+PHL) treatments. In the second through fourth batches, one-third of the incubation fluid from the previous batch bottle was mixed with two-thirds of the anaerobic buffer and used to inoculate the next corresponding serum bottle with fresh substrates. At the end of the fourth incubation, 1 mL of incubation fluid was collected, centrifuged at 16 000 g for 15 min at 4 °C, and the supernatant was discarded. The pellet was stored at -20 °C until DNA extraction.

Goat inocula experiment: sequential batch incubation using rumen fluid from goats

Rumen fluid were obtained from four rumen-fistulized adult Murciano-Granadina goats (n=4) that had been adapted to the experimental diet for more than 3 weeks. The substrates and the inoculation media were prepared as Chapter 2. The in vitro experiment consisted of four sequential batch incubations using 125-mL serum bottles according to the following design: 6 mM or 36 mM phloroglucinol, 6 mM or 36 mM pyrogallol, 2% A. taxiformis (based on DM, A. taxiformis was added in the fourth incubation), and control treatments (n=4 for each treatment) for the first, second, and third incubations. In the fourth incubation, 2% A. taxiformis was added to each bottle except for the control treatment, resulting in six treatments: Control (CTL), 2% A. taxiformis (AT), 2% A. taxiformis + 6 mM phloroglucinol (AT+PHL1), 2% A. taxiformis + 36 mM phloroglucinol (AT+PHL2), 2% A. taxiformis + 6 mM pyrogallol (AT+PYR1), and comparisons using the PairwiseAdonis package (Martinez Arbizu, 2017), with P-value adjusted by Bonferroni statement. Microbial significant associations were analyzed by R package Masslin2 [START_REF] Mallick | Multivariable association discovery in population-scale meta-omics studies[END_REF]. UpSetR plots were generated using the R package UpSetR [START_REF] Conway | UpSetR: an R package for the visualization of intersecting sets and their properties[END_REF], and modified according to our previous publication (Popova et al., 2022). We also performed distance-based redundancy analysis using R package ggvegan.

Results and discussion

In our previous work (Romero et al., 2023; Chapter 2), we found that phloroglucinol and pyrogallol decreased dihydrogen accumulation and increased total VFA production by promoting acetate production when methanogenesis was inhibited. In this study, we used a metataxonomic approach to gain insight into the potential changes in the rumen microbiota induced by phloroglucinol and pyrogallol alone or in combination with a methanogenesis inhibitor. We used rumen fluid as inocula from two ruminant species, dairy cows and goats, and amplified both the bacterial and archaeal communities with universal primers. However, we observed an extremely low number of amplicon sequence variants (ASVs) assigned as archaea in high-concentration phloroglucinol and pyrogallol groups, rendering further analysis infeasible. This low number of archaea ASVs was consistent with qPCR results, which showed a sharp reduction in archaea abundance in response to high phloroglucinol and pyrogallol supplementation, as compared to the control group (Romero et al., 2023; Chapter 2). a,b Values within a row with different superscripts differ significantly at P < 0.05.

Rumen bacterial diversity was affected by phenolic compounds but not by methanogenesis inhibitors

The methane inhibitors used in this study, BES and A. taxiformis, did not affect alpha diversity indicators (Shannon index, Simpson index, and Faith's phylogenetic, Tables 5 and6). BES is the structural analogue of CoM that competes with methyl-CoM for binding to methyl-coenzyme M reductase, effectively inhibiting the reduction of methyl group into methane in the last step of the methanogenic pathway (Patra et al., 2017).

Meanwhile, A. taxiformis contains bromoform, which acts on both coenzyme M methyltransferase and methyl-coenzyme M reductase to inhibit methanogenesis (Glasson et al., 2022). Both BES and bromoform are specific inhibitors that target the methanogenesis pathway, which is unique to methanogenic organisms. This likely explains why neither of these inhibitors affected bacterial alpha diversity.

In contrast, phenolic compounds phloroglucinol and pyrogallol, at a concentration of 36 mM significantly decreased alpha diversity indicators, except the Simpson index (Tables 5 and6). However, at a lower concentration of 6 mM, these phenolic compounds did not affect alpha-diversity indicators. Notably, the results from the 36 mM phloroglucinol treatment alone are inconsistent with previous in vivo work, which reported no effect of a similar concentration (around 40 mM) of phloroglucinol on alpha diversity (Martinez-Fernandez et al., 2017). The inconsistent results may be due to the differences between the in vitro and in vivo methods used in the studies. Likewise, beta diversity analysis revealed differences in bacterial community structure in both fermentation fluid using inocula from cows and goats (Figure 7). In the cow inocula experiment, samples exposed to 36 mM phloroglucinol with and without BES clustered together and separated from the samples from control and BES treatments (Figure 7,A). Pairwise Adonis statistical analysis showed a significant difference between the control and PHL groups (P = 0.012), and a trend difference between BES and BES+PHL groups (P = 0.060), while there was no difference between the control and BES groups (P = 1) or between the PHL and BES+PHL groups (P = 1). In the goat inocula experiment, Pairwise Adonis statistical analysis showed no difference between groups, although samples from AT+PHL2 and AT+PYR2 groups were separated from other samples (Figure 7,B). The results of beta diversity of the cow inocula experiment are inconsistent with those of Martinez-Fernandez et al. (2017), who found that phloroglucinol (~40 mM) did not affect beta diversity. The differences between our study and Martinez-Fernandez et al. (2017) could be due to the in vitro versus in vivo approach, the actual concentration and exposure time of the microbiota to phloroglucinol.

The in vivo concentration was calculated based on the dose and steers' live weight (Martinez-Fernandez et al., 2017), with possible dilution due to passage rate out of the rumen and the assess pharmacokinetics.

We also investigated the effect of fermentation factors, including VFAs, NH3, and pH, on the microbiota structure of cow inocula and goat inocula experiments (Figure S1 and S2). In the cow inocula experiment, we found that acetate, butyrate, and caproate contributed to the samples from the PHL and BES+PHL groups, while isovalerate contributed to the samples from the control and BES groups. Previous studies have shown that phloroglucinol degradation can increase acetate and butyrate production (Conradt et al., 2016), and that inhibition of methane production can increase caproate production (Ungerfeld, 2015). Phloroglucinol supplementation can also decrease protein digestion in the rumen, thus indirectly decreasing isovalerate production (McSweeney et al., 2001). This could explain why isovalerate contributed to the samples from the control and BES groups. In goat inocula experiment, we found that samples from control, AT, AT+PHL1, and AT+PYR1 groups clustered based on pH value, isobutyrate, isovalerate, NH3, and propionate. Interestingly, the AT+PHL2 group and the AT+PYR2 group were separated, with butyrate contributing to the AT+PHL2 grouping and lactate contributing to the AT+PYR2 grouping.

Bacterial community responses to phloroglucinol supplementation in cow inocula experiment

Hydrolysable tannins are secondary plant metabolites commonly found in leguminous forages [START_REF] Reed | Nutritional toxicology of tannins and related polyphenols in forage legumes[END_REF]. Previous studies reported that some rumen microbes have a tolerance to tannins by dihydrogen to break down tannins [START_REF] Patra | Dietary tannins on microbial ecology of the gastrointestinal tract in ruminants[END_REF].

Figure 8A shows the top 50 bacteria that showed significant associations (positive or negative) compared to the control group in the cow inocula experiment. The effects of treatments PHL and BES+PHL on the top 50 bacteria (Figure 8A)

were similar, indicating that phloroglucinol is the key driver for changes in bacterial structure. Phloroglucinol supplementation significantly increased the abundance of several bacterial families, including Lactobacillaceae, Prevotellaceae, Lachnospiraceae, Atopobiaceae, Eggerthellaceae, Veillonellaceae, Bifidobacteriaceae, Acholeplasmataceae, Erysipelatoclostridiaceae, Bacterioidia Class, RF39, Muribaculaceae, and Fusobacteriaceae. Some of these bacteria have been reported to utilize phloroglucinol or have their abundance increased by phloroglucinol supplementation. For example, Coprococcus, a genus from the family Lachnospiraceae that was isolated from rumen fluid, degraded 80% phloroglucinol after two days of pure culture (Tsai and Jones, 1975). Martinez-Fernandez et al. (2017) reported that phloroglucinol increased the proportion and the absolute abundance of Coprococcus when methane production was inhibited by chloroform; Sarwono et al. (2019b) also found that 10 mM phloroglucinol increased the proportion of Coprococcus by twofold, compared to the control group. The abundance of Prevotella, the genus from the family Prevotellaceae, was also increased by phloroglucinol when methane production was inhibited by chloroform (Martinez-Fernandez et al., 2017). These results suggest that

Coprococcus plays an important role in phloroglucinol degradation, and that Prevotella has the potential ability to utilize phloroglucinol.

Phloroglucinol supplementation increased the abundance of other bacteria that are also involved in phenolic compound metabolism. Regression analysis has shown that the enrichment of Lactobacillaceae in the gut of Drosophila melanogaster was associated with the content of phenolic compounds [START_REF] Garcia-Lozano | Effect of pepper-containing diets on the diversity and composition of gut microbiome of drosophila melanogaster[END_REF], and the abundance of Lactobacillaceae was fourfold higher in the group with high concentration of phenolic compound [START_REF] Nissen | Roasting and frying modulate the phenolic profile of dark purple eggplant and differently change the colon microbiota and phenolic metabolites after in vitro digestion and fermentation in a gut model[END_REF]. Another possible reason for the observed increase in Lactobacillaceae abundance is that they are known lactate producers. As phloroglucinol supplementation inhibited methane production and resulted reducing equivalents such as dihydrogen accumulation (Chapter 2), lactate production increased because it consumes reducing equivalents (Ungerfeld, 2020). This could also explain the increase in the abundance of Veillonellaceae because members of this family are lactate utilizers [START_REF] Daly | Alterations in microbiota and fermentation products in equine large intestine in response to dietary variation and intestinal disease[END_REF]. Fusobacteriaceae, and Atopobiaceae are butyrate producers (Van den [START_REF] Van Den Abbeele | Yeast-derived formulations are differentially fermented by the canine and feline microbiome as assessed in a novel in vitro colonic fermentation model[END_REF][START_REF] Kynkäänniemi | Gut microbiota can utilize prebiotic birch glucuronoxylan in production of short-chain fatty acids in rats[END_REF]. Butyrate production also consumes bacteria, especially cellulolytic bacteria cannot grow at low pH values [START_REF] Russell | Effect of pH on the efficiency of growth by pure cultures of rumen bacteria in continuous culture[END_REF][START_REF] Russell | Why are ruminal cellulolytic bacteria unable to digest cellulose at low pH?[END_REF]. The families Spirochaetaceae [START_REF] Shivani | Characterisation of a newly isolated member of a candidatus lineage, Marispirochaeta aestuarii gen. nov., sp[END_REF], Oscillospiraceae [START_REF] Fei | Woodchip-sulfur based mixotrophic biotechnology for hexavalent chromium detoxification in the groundwater[END_REF], Fibrobacteraceae [START_REF] Ozbayram | Comparison of rumen and manure microbiomes and implications for the inoculation of anaerobic digesters[END_REF],

Ruminococcaceae, and unclassified Ruminococcaceae UCG-010 [START_REF] Wang | Metagenomic insights into the carbohydrate-active enzymes carried by the microorganisms adhering to solid digesta in the rumen of cows[END_REF], Guo et al., 2019) are known to be cellulose-degrading bacteria. Christensenellaceae and Hungateiclostridiaceae belong to the class Clostridia, which has a high cellulosedegrading ability [START_REF] Fontes | Cellulosomes: highly efficient nanomachines designed to deconstruct plant cell wall complex carbohydrates[END_REF]Gilbert, 2010, Zhang et al., 2018). Although Bacteroidales RF16 group is unclassified, its abundance was significantly higher in the forage group than in the concentrate group in rumen of yak [START_REF] Liu | Dynamic alterations in yak rumen bacteria community and metabolome characteristics in response to feed type[END_REF], suggesting that is might be a cellulose-degrading bacteria. The role of the Bacteroidetes, unclassified family F082 and p-251-o5 remain unclear [START_REF] Chiariotti | Increasing the sustainability of maize grain production by using arbuscular mycorrhizal fungi does not affect the rumen of dairy cattle (Bos taurus) and buffalo (Bubalus bubalis)[END_REF]. Another possible reason for the decrease in bacterial abundance is that phenolic compounds may be toxic to some bacteria. [START_REF] Hierholtzer | The impact and mode of action of phenolic compounds extracted from brown seaweed on mixed anaerobic microbial cultures[END_REF] reported that phloroglucinol (5.6 mM) can affect the membrane permeability of anaerobic bacteria.

Figure 8 also shows that the effects of BES (A) and A. taxiformis (B) on these 50 bacteria was small. These results are in line with the alpha and beta diversity results. The small impact of BES and A. taxiformis on these bacteria likely because BES and A.

taxiformis are specific inhibitor to methanogens.

Bacterial community responses to phloroglucinol supplementation in goat inocula experiment and the comparison between cow and goat inocula experiments

Figure 8B shows the top 50 bacteria that showed significant associations (positive or negative), compared to the control group. When phloroglucinol and pyrogallol were combined with A. taxiformis at the same concentration, they displayed a highly similar impact on the bacteria structure (Figure 8B and Table S7). The similarity in effect could be attributed to the involvement of both phloroglucinol and pyrogallol in the metabolic pathway of gallic acid, as reported in various studies (Evans, 1977, Bhat et al., 1998;McSweeney et al., 2001;Conradt et al., 2016).

Interestingly, approximately 50% of the bacterial that displayed a positive association with phloroglucinol supplementation in the cow inocula experiment were also positively associated with 36 mM phloroglucinol and pyrogallol supplementation in the goat inocula experiment. This finding suggests that the metabolic effects of phloroglucinol and pyrogallol on these bacteria may be conserved across ruminant species. Additionally, in goat inocula experiment, we observed a significant increase in butyrate and lactate production following treatment with AT+PHL2 (Romero et al., 2023), which provides further support for the hypothesis that the increased abundance of Lactobacillaceae, Veillonellaceae, Fusobacteriaceae, and Atopobiaceae were responsible for the observed effects. Interestingly, in cow inocula experiment, approximately 60% of the bacteria that displayed a negative relationship with phloroglucinol supplementation were also negatively associated with 36 mM phloroglucinol and pyrogallol supplementation in the goat inocula experiment. Consistent with these findings, we observed a significant decrease in pH value in the goat inocula experiment (Romero et al., 2023).

The abundance of Eubacteriaceae, Streptococcaceae, Chloroplast, Erysipelotrichaceae, Mitochondria, Pseudomonadaceae, Selenomonadaceae, and Weeksellaceae increased only in the AT+PHL2 and AT+PYR2 groups in the goat inocula experiment, while no such increase in the cow inocula experiment for the PHL and BES+PHL groups. This difference is likely due to the variations in rumen microbiota between goats and cows, despite the presence of the same core microbes (Henderson et al., 2015, Corral-Jara et al., 2022).

Eubacterium oxidoreducens sp. nov. from the family Eubacteriaceae (Krumholz and Bryant, 1986;Krumholz et al., 1987) and Streptococcus from the family Streptococcaceae (Tsai and Jones, 1975) were isolated from steer rumen fluid, and studies have demonstrated that these two bacteria can utilize phloroglucinol and/or pyrogallol with reducing equivalents such as dihydrogen. However, it is unclear why

Eubacteriaceae was not detected and why Streptococcaceae abundance was lower in PHL or BES+PHL group in the cow inocula experiment (Table S6).

Erysipelotrichaceae has been found to have a positive association with phenolic compounds in plant-based foods [START_REF] Calderón-Pérez | Interplay between dietary phenolic compound intake and the human gut microbiome in hypertension: A crosssectional study[END_REF]. Pseudomonas sp. from the family Pseudomonadaceae has been reported to be involved in phenol degradation [START_REF] Lack | Evidence that phenol phosphorylation to phenylphosphate is the first step in anaerobic phenol metabolism in a denitrifying Pseudomonas sp[END_REF]. However, we did not find any publications that reported the involvement of Selenomonadaceae and Weeksellaceae in phenolic compound metabolism or reducing equivalent consumption.

Different treatments combination have different unique bacteria

We used UpSetR analysis to identify core ASVs that were present in all treatments and treatment-specific ASVs (Figure 9). In the cow inocula experiment (Figure 9 A), we identified 35 core ASVs, with Prevotella (16%), Streptococcus (11%), and Megasphaera (10%) being the dominant ASV. Prevotella was the dominant ASV, which is consistent with its prevalence in the rumen microbial ecosystem [START_REF] Stevenson | Dominance of Prevotella and low abundance 123 of classical ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR[END_REF]. In the PHL group, we identified 2 unique ASVs, with the highest abundance ASV being Erysipelotrichaceae UCG 006. In the BES+PHL group, we identified 1 unique ASV, which was Agathobacter. Like Coprococcus, Agathobacter belongs to the family Lachnospiraceae. We found 8 unique ASVs that were present in both the PHL and BES+PHL groups, with Ligilactobacillus (68%), Dialister (18%), and Limosilactobacillus (5%) being the top three ASVs. Most of these ASVs belonged to the family Lactobacillaceae and Veillonellaceae. In the control and BES groups, we identified 75 unique ASVs, with Succinivibrio (24%), Treponema (15%), and F082 (8%) being the top three abundant ASVs. Additionally, we identified 18 unique ASVs in the control group and 4 unique ASVs in the BES group. In the goat inocula experiment (Figure 9B), we identified 45 core ASVs, with top three most abundant ASVs affiliated with Treponema (19%), Streptococcus (15%), and Succinivibrionaceae UCG-002 (7%). Streptococcus was the second most abundant core ASV in cow inocula experiment. However, Treponema was not found in cow inocula experiment core ASVs, it was the second abundant ASV in control and BES groups.

Also, the abundance of Succinivibrionaceae UCG-002 in cow inocula experiment of core ASVs was much lower (0.2%). The observed difference in core ASVs between cow inocula and goat inocula experiments could due to the varying bacteria composition in the original cow and goat's rumen fluid and the pyrogallol supplementation in the goat inocula experiment. Indeed, we found different ASVs in the control group from cow inocula experiment and the control group from goat inocula experiment.

In the AT+PHL2 group, we identified 4 unique ASVs including Succinatimonas (61%), Erysipelotrichaceae_UCG-007 (22%), uncultured (12%), and Family Myxococcaceae (5%). Meanwhile in the BES+PHL group, there was only 1 unique ASV, which was Agathobacter. In the AT+PYR2 group, we identified 8 unique ASVs, with the top three most abundant ASVs affiliated with Eubacterium ventriosum group (53%), Actinomyces (14%), and uncultured (14%). We did not find any unique ASVs in both AT+PHL1 and AT+PHL2 groups, or in AT+PYR1 and AT+PYR2 groups.

Conclusion

This study aimed to explore the potential of rumen bacteria to degrade phloroglucinol and pyrogallol using dihydrogen. We observed that the responses of cow and goat rumen bacteria to phloroglucinol and pyrogallol were similar, with approximately 50% of the same bacterial showing increased or decreased abundance when supplemented with 36 mM phloroglucinol and/or pyrogallol in both experiments. Phloroglucinol and pyrogallol have a very similar and large effect on rumen bacteria structure, while methane inhibitors A. taxiformis and BES had a limited effects on rumen bacteria structure. Our findings also suggest that certain bacteria present in cow and goat rumen fluid possess the ability to utilize phloroglucinol and pyrogallol, although further studies, such as pure culture and genomic analysis, are necessary to confirm these findings. a,b,c Values within a row with different superscripts differ significantly at P < 0.05.

Supplemental materials

Introduction

In this trial, we used gallic acid for an in vivo supplementation, as this compound is the subunit of hydrolysable tannins and its ability to act as dihydrogen acceptor was demonstrated in vitro in Chapter 2. We hypothesized that combining methanogenesis inhibitor with gallic acid would stimulate phenolic-degrading rumen bacteria to uptake dihydrogen and produce more VFA, thus improving animal production. The objective of this study was to investigate the effects of gallic acid, acting as a dihydrogen acceptor, on milk production, gas emissions, and rumen fermentation when using methanogenesis inhibitor.

Experimental design

Main finding  0.25% AT alone decreased methane yield, increased dihydrogen emissions  0.8% GA alone did not affect methane or dihydrogen emissions, nor acetate or propionate molar proportions  Feed intake decreased by 10% in the AT group with a consequent decrease in milk yield by 18%



In the MIX group, feed intake was also decreased (8%), but the drop in milk yield was less severe (11%), compared to AT group

Conclusion

This study confirmed the antimethanogenic effect of A. armata but also shows a negative effect on feed intake and milk yield. Although there was no interaction effect of gallic acid and A. armata on dihydrogen and methane emission or acetate and butyrate proportion, they have a positive interaction on milk yield.

Gallic Acid alleviates the negative effect of A. armata on milk yield without affecting methanogenesis inhibition in dairy cows

Abstract

We have shown that when ruminal methanogenesis was inhibited in vitro, gallic acted as a hydrogen acceptor improved ruminal fermentation. In this work, we tested the effect of gallic acid and the methanogenesis inhibitor A. armata on dihydrogen emissions and milk production in dairy cows. Lactating Holstein cows (n=28) were separated into four treatment groups as follow: CON, basal diet; AT, basal diet with 0.25% A. armata;

GA, basal diet with 0.8% gallic acid; and MIX, basal diet with 0.25% A. armata and 0.8% gallic acid. This study used a randomized complete block design with 6 weeks of covariate period, 2 weeks of adaptation period, and 3 weeks of experimental period. The AT treatment decreased methane yield by 25%, increased dihydrogen emissions threefold, and reduced the acetate to propionate ratio in the rumen. In contrast, gallic acid did not affect methane or dihydrogen emissions, nor acetate or propionate molar proportions. Feed intake decreased by 10% in the AT group with a consequent decrease in milk yield of 18%. In the MIX group, feed intake was also decreased (8%), but the drop in milk yield was less severe (11%). This study confirmed the antimethanogenic effect of A. armata but also shows a negative effect on feed intake and milk yield. While gallic acid alleviated the negative effect of A. armata on milk production and gallic acid combined with A. armata had positive effects on milk yield, given the conditions in this study.

Introduction

The livestock sector contributes 14.5% of anthropogenic greenhouse gas emissions, and enteric methane emissions accounting for almost half of total enteric greenhouse gas emissions (Gerber et al., 2013). Effective strategies for decreasing methane emissions in the rumen exist, but they are not readily adopted by farmers. Recently, research focused on decreasing methane emissions without altering the fermentation process; the actual challenge is simultaneously reducing methane emissions and improving fermentation efficiency.

This challenge could be met by considering the pivotal place of dihydrogen in the rumen metabolism. Thermodynamic conditions in the rumen give an advantage to methanogenic archaea, makes them the main consumers (Morgavi et al., 2010).

However, alternative dihydrogen consumers are still present and could redirect dihydrogen toward metabolic pathways providing the host animal with extra energy. For instance, some phenolic compounds such as gallic acid and phloroglucinol can capture dihydrogen and generate acetate and butyrate (Tsai et al., 1976, Krumholz et al., 1987).

To develop alternative hydrogenotrophic pathways, two conditions should be met: methanogenic archaea need to be inhibited and an alternative hydrogen acceptor should be available. One effective methanogen-specific inhibitor is the red seaweed A. taxiformis (Li et al., 2016), which bioactive compound bromoform can inhibit methanogenesis (Machado et al., 2016). Glasson et al. (2022) reported that bromoform acts both on the coenzyme M methyltransferase and the methyl-coenzyme M reductase to decrease methane production.

Several compounds have been evaluated as hydrogen acceptors in previous studies, including nitrate (Popova et al., 2017), and phloroglucinol when methanogenesis was inhibited (Martinez-Fernandez et al., 2017). Our in vitro studies also showed the potential of phenolic compounds gallic acid, phloroglucinol, and pyrogallol to capture excessive dihydrogen, and to increase VFA production when methane production was inhibited (Chapter 2). These results from our in vitro study are positive as consuming excessive dihydrogen would improve rumen fermentation and more VFA production would provide more energy for the host animal.

While our in vitro studies have provided promising results, it remains unclear how these phenolic compounds might impact animal productivity and the rumen microbiota with a methanogenesis inhibitor in vivo. To address this gap in knowledge, we conducted an animal study, in which we tested the interaction effects of A. armata1 as a methanogenesis inhibitor with gallic acid as a hydrogen acceptor on lactating dairy cows.

We hypothesized that gallic acid can improve animal productivity by redirecting excessive dihydrogen metabolism and modify rumen microbiota when methanogenesis is inhibited by A. armata. In this study, we investigated the effects of gallic acid alone, A. armata alone, and the combination of gallic acid with A. armata on animal production, rumen fermentation, gas emissions, rumen microbial structure and gene expression, blood metabolism, and cow's health.

counties. A. armata (Volta Greentech, Solna, Sweden) and gallic acid (Acros organics, China) were added to the pellets. The pelleting duration and temperature were controlled to minimize the loss of bioactive compound in the A. armata, the highest temperature was 54 °C during the pelleting. Three different pellets were made: the pellet without A.

armata and gallic acid, the pellet containing 3% A. armata, and the pellet containing 6% gallic acid. The ingredients and nutrient composition of mixed forage and pellets are shown in Table 7. In the AT group, the pellet containing 3% A. armata was mixed with the pellet without A. armata and gallic acid to create a mixed pellet with 1% A. armata. In the GA group, the pellet containing 6% gallic acid was mixed with the pellet without A. armata and gallic acid to create a mixed pellet with 3% gallic acid. In the MIX group, the pellet containing 3% A. armata, the pellet containing 6% gallic acid, and the pellet without A.

armata and gallic acid were mixed to create a mixed pellet with 1% A. armata and 3% gallic acid.

During the covariate period, the supply of concentrate was adjusted so that the average forage intake to concentrate intake ratio was 75:25. Based on this ratio, the A.

armata inclusion level based on DMI was 0.25%, and the gallic acid inclusion level based on DMI was 0.8%. The cows were housed in a free-stall barn and fed ad libitum with free access to drinking water. The mixed forage was prepared with a double screw mixer (Solomix 2 VLH-B, Trioliet, Oldenzaal, Netherlands) and provided once daily in the morning at 08h30. The mixed forage and the mixed pellet were provided by different automatic feeding systems that could record the feed intake of individual cows.

In the first week of the adaption period (week 7), the inclusion level of A. armata Abbreviations: CON = pellet without A. armata and gallic acid; AT = pellet with 3% A. armata; GA = pellet with 6% gallic acid; OM = organic matter; CP =crude protein; NDF = neutral detergent fiber; ADF = acid detergent fiber; GE = gross energy.

1 1% commercial mineral-vitamin premix (Galaphos, CCPA, France).

Sampling and measurement

During the experiment, we recorded the feed intake of each cow using automatic feeding systems to measure daily feed intake. To calculate dry matter intake (DMI), we collected pellets and mixed forage twice weekly and dried them at 60 °C for 72 h in a forced-air oven to determine their dry matter contents. Additionally, we collected the mixed forage, the refusal of mixed forage, and the three different pellets weekly and stored them at -20 °C. After the experiment, we composited the sample of the mixed forage, refusal of mixed forage, and the different three pellets into one sample, respectively, for each period. The composited sample was then dried at 60 °C for 72 h in a forced-air oven. The mixed forage and refusal of mixed forage were ground through a 1-mm sieve using a mill (BJL8500-2, Boisson Jean-Luc, Lusignan, France), while the mixed pellet was ground through a 1-mm sieve using a Foss mill (Cyclotec CT193, Hilleroed, Denmark).

We used the ground samples for chemical composition analysis, following the methods previously described by Guyader et al. (2015b). Briefly, we determined the dry matter (DM) content by drying at 104 °C for 4 h. We determined organic matter (OM) and ash content by ignition at 550 °C for 6 h (Method 942.05;AOAC, 2005). We determined total N content by combustion using the Dumas method (Method 968.06; AOAC, 2005), and calculated the crude protein (CP) content as N × 6.25. We determined neutral detergent fiber (NDF) and acid detergent fiber (ADF) following the method described by [START_REF] Van Soest | Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition[END_REF]. We determined starch content using an enzymatic method [START_REF] Faisant | Resistant starch determination adapted to products containing high level of resistant starch[END_REF], and determined gross energy (GE) by isoperibolic calorimetry (model C200, IKA, Staufen, Germany).

Before the experiment, we collected A. armata powder for bromoform analysis.

During the adaption and experimental period, we collected the 3 % A. armata containing pellet once in week 7 (the beginning of the adaption period), week 9 (the beginning of the experimental period), and week 11 (the end of the experimental period) and stored them intensity (g/kg milk yield or g/kg energy corrected milk yield) during the covariate and experimental periods.

2.4 Milk production, composition, body weight, and body condition score

The milk production data were recorded for each cow at every milking event. Milk samples were collected for 2 consecutive days weekly both in the morning and afternoon, to determine milk fat, milk true protein, milk lactate, milk urea concentration, and somatic cell count (SCC) using a Foss MilkoScan FT6000 (Foss Electric, Hillerød, Denmark). To obtain each milk sample, 30 mL of milk was collected and preserved with 0.02% bronopol at 4°C. Milk composition data were weighted according to the corresponding milk yield during each sampling event.

On Tuesday during week 11 in the experimental period, 10 mL milk from each cow in CON, AT, and MIX groups was collected twice in the morning and evening, and stored at -20 °C. After the experiment, equal amounts of these milk samples from the same group were pooled to obtain one sample for bromoform analysis, as previously described. The weight of each animal was manually recorded every other week, and their body condition score was assessed every other week by parallel-trained staff.

Rumen fluid and blood

Rumen fluid samples were collected on Thursday in week 3 and on Tuesday in week 4 during the covariate period, and on Tuesday and Thursday in week11 during the experimental period, using oesophageal tubing 5 h after the morning feeding (Popova et al., 2022). The collected rumen fluid was filtered through a polyester monofilament fabric (250 μm pore size), and the resulting filtrate was subsampled for VFA, ammonia, pH, protozoa counting, DNA extraction, and RNA extraction as described before (Chapter 3).

Briefly, for VFA analysis, 0.8 mL of filtrate was mixed with 0.5 mL of 4 mg/mL crotonic acid and 20 mg/mL metaphosphoric acid in 0.5 M HCl, and then analyzed by gas chromatography (PerkinElmer Clarus 580, Waltham, USA). For ammonia analysis, 1 mL filtrate was mixed with 0.1mL of 5% orthophosphate solution and analyzed according to the phenol-hypochlorite reaction (Weatherburn, 1967). For protozoa counting, 1 mL of filtrate was mixed with 1 mL of methyl green-formalin solution, and stored away from direct light until counting. The pH value was measured directly by pH meter (pH 538, WTW). The rumen fluid samples from Tuesday and Thursday were incorporated for VFA, ammonia analysis, and protozoa counting during the covariate and experimental periods, respectively.

For total rumen microbes DNA extraction, 1 mL of filtrate was collected and centrifuged at 16 000 g for 10 min at 4 °C. The supernatant was discarded, and the pellet was stored at -20 °C until DNA extraction using DNeasy PowerSoil Pro Kit (Qiagen, Germany) following the manufacturer's instructions. Additionally, around 10 mL filtrate was collected, cooled in liquid nitrogen immediately, and stored at -80 °C until total rumen microbes RNA extraction using the RNeasy Mini kit (Qiagen, Germany) following the manufacturer's instructions. Turbo DNA-free kit (Thermo Fisher, Ambion, USA) was used to digest residual DNA, and RNA Clean & Concentrate kit (Zymo Research, Orange, CA, USA) was used to purify the digested total RNA. The rumen microbes DNA samples were and hexoses were measured by flow injection analysis-tandem mass spectrometry (FIA-MS/MS) using a Xevo TQ XS (Waters, Vienna, Austria) with an electrospray ionization source, and small molecules were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS) using a 5500 QTRAP (AB Sciex, Darmstadt, Germany). In total, 630 metabolites from 26 biochemical classes were detected.

Statistical analysis

The raw data from the metabolomic analysis were analyzed by software SIMCA 14.1 (Göttingen, Germany). The primers used were 515F and 806R for V4 region of 16S rRNA gene amplification. The resulting amplicons were sequenced on an Illumina MiSeq platform using a MiSeq 2x250 pair-end sequencing kit at University of Illinois at Urbana-Champaign (Illinois, America). Downstream processing was performed using QIIME 2 (Bolyen et al., 2019). Specifically, demultiplexing was performed using Qiime demux emp-paired plugin; while denoising, quality control, and ASV generation were performed using the DATA2 plugin. Representative sequences from all ASVs were aligned against SILVA 138.1. The following analysis were performed by software R (Version R 4.2.2). For the analysis of alpha diversity, the Kruskal-Wallis test was performed to obtain P-values associated with treatment variations, while the Pairwise Wilcoxon test was performed to facilitate multiple comparisons between treatments. For beta-diversity analysis, permutational multivariate ANOVA was performed using the Adonis test (with 9999 permutations) to obtain P-values associated with treatment variations, and the Pairwise Adonis2 test was performed to enable multiple comparisons among treatments, also employing 9999 permutations.

To analyze the data, normality of all datasets except sequencing and blood metabolomic data was assessed for normality by the UNIVARIATE procedure (version 9.4, SAS Institute Inc., Cary, NC.). The MIXED procedure of SAS then used for statistical analysis. The statistical analysis of SCC and protozoa counting data were log10transformed prior to statistical analysis. The statistical model included Asparagopsis (AT and MIX versus CON and GA), gallic acid (GA and MIX versus CON and AT), block, treatment x block interaction, Asparagopsis x gallic acid interaction, and covariate response. Block and treatment x block interaction were considered as random effects;

Asparagopsis, gallic acid, and Asparagopsis x gallic acid interaction were considered as fixed effects.

Methane, dihydrogen, and carbon dioxide, milk yield, body weight, and body condition score data were averaged by a cow during covariate and experimental periods, respectively. And the average values were used for statistical analysis. The data of DMI, milk composition, milk composition production, energy corrected milk production (ECM), feed efficiency, ECM feed efficiency, and SSC were first averaged by week for covariate and experimental period, respectively. The ECM was calculated as described [START_REF] Sjaunja | A Nordic proposal for an energy corrected milk (ECM) formula[END_REF]. Data of pH value was averaged by Tuesday and Thursday for covariate and experimental periods, respectively. The degree of freedom was calculated by the Satterth statement, the P value was calculated by PDIFF and adjusted by the Turkey statement.

Differences were considered significant at P ≤ 0.05 and a trend at 0.05 < P ≤ 0.10.

Results

Enteric gas emissions

A. armata decreased methane production (P = 0.0121), methane yield (P = 0.0010), methane intensity (g/kg milk yield) (P = 0.0068), accompanied by a corresponding increase in dihydrogen emission (g/d) (P < 0.0001). Specifically, the AT group demonstrated a 13% decrease in methane production, a 25% decrease in methane yield, and a 16% decrease in methane intensity (g/kg milk yield), along with a fourfold increase in dihydrogen emission (g/d), compared to the CON group (Table 8).

Gallic acid did not have a significant effect on either methane or dihydrogen emissions. Furthermore, there was no interaction effect between gallic acid and A.

armata on methane and dihydrogen (g/d) emissions. Carbon dioxide emissions were not affected by A. armata or gallic acid, however, an interaction effect between A. armata and gallic acid on carbon dioxide emission was observed. 1 Asparagopsis represents the main effect of A. armata (CON and GA versus AT and MIX); Gallic represents the main effect of gallic acid (CON and AT versus GA and MIX); AsparagopsisxGallic represents the interaction between main effects of A.

armata and gallic acid.

Rumen fermentation

A. armata decreased (P = 0.0259) total VFA concentration, acetate proportion (P = 0.0010), while it increased (P = 0.0163) propionate and butyrate proportion, thus acetate to propionate (A/P) ratio was decreased (P = 0.0003) (Table 9). Specifically, in AT group, total VFA concentration was decreased by 11%, acetate proportion was decreased by 6%, while propionate and butyrate proportion were increased by 8% and 18, respectively, thus A/P ratio was decreased, compared to the CON group (Table 9).

Gallic acid did not affect total VFA concentration or VFA profile, and there was no interaction effect of A. armata and gallic acid on total VFA concentration and VFA profile.

There were no A. armata or gallic acid effects or their interaction effects on pH value and ammonia concentration. Furthermore, there were no A. armata or gallic acid effects or their interaction effects on total protozoa counting or different rumen protozoa species counting, with the exception of an increased number of Dasytricha by A. armata (P = 0.0317) (Table 10). Abbreviations: CON = control diet; AT = 0.25% A. armata in the basal diet; GA = 0.8% gallic acid in the basal diet; MIX = 0.25% A. armata and 0.8% gallic acid in the basal diet.

1 Asparagopsis represents the main effect of A. armata (CON and GA versus AT and MIX); Gallic represents the main effect of gallic acid (CON and AT versus GA and MIX); AsparagopsisxGallic represents the interaction between main effects of A.

armata and gallic acid.

Effect of A. armata and gallic acid on animal performance

Table 11 summarizes the effect of A. armata, gallic acid, and their interaction effects on animal performance. Body condition score was not affected by A. armata and gallic acid, but A. armata significantly (P = 0.0187) decreased body weight. AT group decreased body weight by 3%, compared to the CON group. A. armata also decreased forage intake (P = 0.0252), concentrate intake (P = 0.0067), and total feed intake (P = 0.0175). AT group decreased forage intake, concentrate intake, and total feed intake by 11%, 12%, and 10%, respectively, compared to the CON group. In contrast, gallic acid did not affect feed intake and there was no interaction effect of A. armata and gallic acid on feed intake.

Milk yield decreased (P < 0.0001) by A. armata, however it was slightly increased (P = 0.0320) by gallic acid. AT group decreased milk yield by 18% and the GA group increased milk yield by 0.5%, compared to the CON group. There was an interaction effect of A. armata and gallic acid (P = 0.0156) on milk yield. In the MIX group, milk yield 1 Asparagopsis represents the main effect of A. armata (CON and GA versus AT and MIX); Gallic represents the main effect of gallic acid (CON and AT versus GA and MIX); AsparagopsisxGallic represents the interaction between the main effects of A. armata and gallic acid.

2 Feed efficiency = milk yield / total feed intake.

3 ECM feed efficiency = energy-corrected milk yield / total feed intake.

Blood biochemistry

A. armata and gallic acid did not affect blood biochemistry, except gallic acid decreased GGT and ALP concentration (P = 0.0288 and P = 0.0008, respectively) (Table 12). The interaction effects of A. armata and gallic acid were observed on AST, ALP, and ALT (P = 0.0429, P = 0.0425, and P = 0.0302, respectively). 1 Asparagopsis represents the main effect of A. armata (CON and GA versus AT and MIX); Gallic represents the main effect of gallic acid (CON and AT versus GA and MIX); AsparagopsisxGallic represents the interaction between main effects of A.

armata and gallic acid.

Metabolomic and metataxonomic analysis

The kit MxP® Quant 500 kit, capable of detecting a total of 630 metabolites, was used for metabolomic analysis. For the data analysis, only metabolites with a detection rate exceeding 50% in the 24 cows (only 24 samples were used) were retained.

Consequently, 421 metabolites, representing 67% of the total detectable metabolites, were utilized for data analysis. Principal component analysis revealed that the first component accounted for 50% variance (Figure 9). Notably, samples from the CON treatment distinctly separated from samples from the AT treatment along component 1.

Similarly, samples from the CON treatment also appeared to diverge from those samples from the GA treatment along the same component. We subsequently performed orthogonal partial least squares-discriminant analysis between the CON and AT treatments (Figure 10), identifying discriminant metabolites (Table 13). There were 148 differential metabolites identified (P < 0.05) and the concentrations of all these metabolites in the CON treatment were higher than that of the AT treatment. The majority of these metabolites belong to the classes of phosphatidyl-cholines, cholesteryl esters, amino acid and amino acid related, dihexosylceramides, and triglycerides. An attempt at orthogonal partial least squares-discriminant analysis between CON and GA treatments was unsuccessful, with the model not achieving significance (P = 0.17743). 2 Fold change = average (AT) / average (CON).

Abbreviations: CON = basal diet; AT = 0.25% A. armata in the basal diet.

For the rumen metataxonomic analysis, Figure 11 displays the alpha-diversity across treatments throughout the experimental period. The AT treatment significantly decreased alpha-diversity indexes compared to the CON treatment, and the MIX treatment significantly decreased alpha-diversity indexes compared to the GA treatment. Figure 12 displays the beta-diversity across treatments and sampling day throughout the experimental period. There was a significant difference between different treatments. 0.25% of A. armata. It should be noted that we added A. armata in the pellet, and the pelleting process may have resulted in bromoform loss, as bromoform is known to be unstable (Vucko et al., 2017). From week 5 to week 7, both the pelleting process and days of storage were identified as factors contributing to the decrease in bromoform.

From week 7 to week 11, days of storage was the only factor contributing to the decrease in bromoform, and we found that days of storage associated with a linear decrease in bromoform, consistent with previous study (Stefenoni et al., 2021). According to the data from week 7 to week 11, we were able to calculate the rate of bromoform decrease by days of storage (Figure 10). Accordingly, we estimated that about 18% of the bromoform decrease observed from week 5 to week 7 was attributable to pelleting. Pellet was made in week 5 and the bromoform concentration in week 5 (solid line) was calculated based on the inclusion level of A. armata in the pellet (3%), the bromoform concentration in the A. armata (15.5 mg/g DM), and assumed that there is no bromoform loss during pelleting. The bromoform concentration in week 5 (dashed line) was based on the linear relationship from week 7 to week 11.

In the MIX group, methane yield decreased by 34%, while in the AT group, methane yields only decreased by 25%, compared to the CON group. Thus, more dihydrogen emission (g/kg DMI) is expected in the MIX group, compared to the AT group. However, dihydrogen emission (g/kg DMI) in the AT group and MIX group were similar (0.22 vs. 0.26). Although dihydrogen emission (g/kg DMI) in the MIX group did not decrease, compared to AT group, it is possible that gallic acid still acts as a hydrogen acceptor due to the expected higher dihydrogen production the MIX group. The reason for the lower methane yield in the MIX group is not fully understood, particularly considering that both the AT and MIX treatments had the same concentrate intake (5.0 vs 5.0) and similar total feed intake (19.7 vs 20.3). Our previous work (Chapter 2) reported that phloroglucinol decreased methane production by decreasing the abundance of methanogens. Certainly, gallic acid can be converted into phloroglucinol in the rumen (McSweeney et al., 2001). However, methane yield was not decreased (P = 0.1389) by gallic acid in this study. Thus, the substantial decrease in methane yield observed in the MIX group cannot be attributed to gallic acid when compared to the AT group. Interestingly, the effect of gallic acid on methane yield contradicts findings from a previous publication. Aboagye et al. (2019) reported that gallic acid decreased methane yield, although it did not decrease dissolved dihydrogen concentration in the rumen fluid. The disparity in results between these two studies could be due to the difference in gallic acid inclusion level, with 0.8% used in the current study and 1.5% in the study of Aboagye et al (2019).

A. armata decreased total VFA concentration is likely attributed to the reduced DMI. A.

armata decreased acetate proportion, and increased propionate, butyrate, and valerate proportions. This is consistent with the fact that propionate, butyrate, and valerate production consumes dihydrogen compared to acetate production [START_REF] Marty | The effect of inhibitors of methane production of fermentation pattern and stoichiometry in vitro using rumen contents from sheep given molasses[END_REF]Ungerfeld, 2020) In the rumen, gallic acid is supposed to be degraded to acetate and/or butyrate (Bhat et al., 1998;Conradt et al., 2016). However, the proportions of acetate and butyrate did not change by gallic acid supplementation. Our previous in vitro study reported that 6 mM gallic acid increased acetate proportion when methane production was inhibited by BES (Chapter 2), and an in vivo study reported that 1% gallic acid increased both total VFA concentration and butyrate proportion in preweaning dairy calves [START_REF] Xu | Growth performance, digestibility, blood metabolites, ruminal fermentation, and bacterial communities in response to the inclusion of gallic acid in the starter feed of preweaning dairy calves[END_REF]. Nevertheless, our results were consistent with the findings of Aboagye et al. (2019), who reported that acetate and butyrate proportions did not increase with 1.5% gallic acid, despite observing an increase in total VFA concentration in their study.

A. armata resulted in decreased forage intake, concentrate intake, and total feed intake.

Several studies have reported a decrease in DMI with A. taxiformis supplementation (Muizelaar et al., 2021;Roque et al., 2021;Stefenoni et al., 2021). It has been speculated that the decrease in DMI might be attributed to the palatability of A. taxiformis, particularly due to its high ash content (Roque et al., 2019). However, it is worth noting that A. taxiformis also decreased forage intake when it was only mixed with concentrate and when forage and concentrate were offered separately, as observed in the current study and in another study [START_REF] Alvarez-Hess | Twice daily feeding of canola oil steeped with Asparagopsis armata reduced methane emissions of lactating dairy cows[END_REF].

While some studies have reported no decrease in DMI with A. taxiformis supplementation (Li et al., 2016;Kinley et al., 2020).

Alvarez-Hess et al. ( 2023) speculated that the discrepancy in DMI response could be due to differences in the adaptation period. They suggested that a longer adaptation period, up to 30 days, may be necessary to minimize any potential negative effects on DMI with A. taxiformis supplementation. However, the studies reporting decreased DMI with Asparagopsis did include adaptation periods, such as 21 days in the study by Stefenoni et al. (2021), 13 days in the study by [START_REF] Nyløy | Inclusion of Red Macroalgae (Asparagopsis taxiformis) in Dairy Cow Diets Modulates Feed Intake, Chewing Activity and Estimated Saliva Secretion[END_REF] In the present study, gallic acid supplementation slightly increased milk yield, and there was a positive interaction effect of gallic acid and A. Armata on milk production. Gallic acid mitigated the negative effect of A. Armata on milk production, in the MIX group, milk production increased by 9%, compared to the AT group.

Gallic acid supplementation resulted in a decrease in MUN concentration, while it had no significant effect on ruminal ammonia concentration (Table 9) or plasma urea concentration (Table 12). To the best of our knowledge, studies investigating the effects of gallic acid on lactating dairy cows are scarce, therefore we are unable to directly compare our findings to those of other researchers. Bromoform concentration in the milk were below the limit of detection (0.001 mg/g) in the CON, AT, and MIX groups. Although bromoform has been detected in other studies, no significant differences were observed between the control and the Asparagopsis supplementation groups (Roque et al., 2019, Stefenoni et al., 2021). In study where bromoform concentration in milk was significantly increased with Asparagopsis supplementation, the concentration remained well below the safety limit [START_REF] Alvarez-Hess | Twice daily feeding of canola oil steeped with Asparagopsis armata reduced methane emissions of lactating dairy cows[END_REF].

Enzymes such as ALT, AST, ALP, and GGT are primarily found in the liver and are used as indicators to access liver cell damage. In our study, there was a noticeable trend towards a decrease (P = 0.0510) in ALT concentration in the plasmas with A. Armata supplementation, which was in line with Stefenoni et al. (2021) study. They also reported a decrease in ALT concentration in the plasma with 0.5% A. taxiformis supplementation. However, the specific mechanism behind the decrease in ALT concentration with Asparagopsis supplementation was not elucidated in either study. Furthermore, gallic acid supplementation resulted in a decrease in GGT (P = 0.0288) and ALT (P = 0.0008) concentration. This may be attributed to the antioxidant properties of gallic acid, as suggested in previous research by [START_REF] Xu | Growth performance, digestibility, blood metabolites, ruminal fermentation, and bacterial communities in response to the inclusion of gallic acid in the starter feed of preweaning dairy calves[END_REF]. The exact mechanism by which gallic acid influences these enzyme concentrations requires further investigation.

The metabolomic analysis revealed the alterations in the blood metabolites of the AT treatment when compared to the CON treatment. Specifically, amino acids, amino acid-related, and lipid-related metabolites concentrations were higher in the CON treatments. This could be explained by less concentrate and less forage intake in the AT treatment. Less nutrients intake might decrease their concentration in the blood; however, this result is inconsistent with a previous publication (Guo et al., 2019). Guo et al. (2019) reported that feed intake restriction increased lipid related metabolites and some amino acid concentrations due to the energy negative balance. However, in our study the cows in the AT treatments were not in energy negative balance status because the B-OH and NEFA concentrations were not increased.

Previous studies suggested that Asparagopsis supplementation induce rumen inflammation (Li et al., 2016;Muizelaar et al., 2021). Although we could not collect rumen tissue samples in this study, there were metabolites measured in the blood that are known inflammation indicators. For example, dihexosylceramides whose concentration was reported to increase with inflammation [START_REF] Mousa | Lipidomic profiling reveals early-stage metabolic dysfunction in overweight or obese humans[END_REF]. However, in our study, we did not observe an increase in blood dihexosylceramide concentrations in cows subjected to the AT treatment. The effect of Asparagopsis on rumen inflammation needs more exploration. Currently, we are analyzing the pathways of the differential metabolites involved, anticipating that this exploration will yield further insights.

The AT and MIX treatments decreased microbial alpha diversity compared to CON treatment and also changed the beta-diversity. These results are in line with our in vitro study (Chapter 3).

However, the results of the current study are inconsistent with those reported by [START_REF] Belanche | A metagenomics approach to evaluate the impact of dietary supplementation with Ascophyllum nodosum or Laminaria digitata on rumen function in rusitec fermenters[END_REF], who found that seaweeds did not affect the biodiversity indices of rumen microbes. The discrepancy between the two studies may arise from the utilization of different classes of seaweed; while red seaweed was employed in the present study, [START_REF] Belanche | A metagenomics approach to evaluate the impact of dietary supplementation with Ascophyllum nodosum or Laminaria digitata on rumen function in rusitec fermenters[END_REF] used brown seaweeds. We are currently further analyzing the metataxonomic, metagenomic, and metatranscriptomic data. In subsequent analysis, we will integrate this sequencing data with the data of rumen fermentation, gas emissions, and animal performance. These comprehensive approach aims to deeper our understanding of the effects of A. armata and gallic acid, both individually and in combination, on rumen microbiota and animal physiology.

Conclusion

Inclusion of 0.25% A. Armata in the diet of lactating dairy cows decreased methane yield and correspondingly increased dihydrogen emission. However, this inclusion level of A. Armata also decreased DMI, milk yield, and milk component production. Although there was no interaction effect of gallic acid and A. armata on dihydrogen and methane emission or acetate and butyrate proportion, they have a positive interaction effect on milk yield.

CHAPTER 5

General discussion and conclusions

Methane emissions from the ruminant sector not only contribute to the greenhouse effect but also represent a loss of digestible feed energy. By using feed additives, it's now feasible to reduce methane production by 25% or more [START_REF] Morgavi | Reducing enteric methane emissions improves energy metabolism in livestock: is the tenet right?[END_REF]. Theoretically, the feed energy not wasted by methane production could be used to improve animal production; however, milk production was not increased when methane production was inhibited in dairy cows (Ungerfeld, 2018). Improving milk production is important when using methanogenesis inhibitors. This is because it could motivate farmers to purchase and implement methanogenesis inhibitors in their practice, leading to reduced greenhouse emissions from the ruminant sector. Also, it could help to improve feed utilization and address the challenges posed by a growing global population.

Methane production plays a crucial role as a primary dihydrogen sink in the rumen.

Simultaneously, other hydrogenotrophic pathways, including propionate production, are naturally present (Ungerfeld, 2020). When methanogenesis is inhibited, dihydrogen released in the rumen increases. However, propionate production only utilizes a fraction of this excess dihydrogen, with a small amount being expelled by the animal (van Gastelen et al., 2020). In light of this, we hypothesized that supplementation with a hydrogen acceptor could enhance the capacity of other dihydrogen consuming pathways. This would allow to process the surplus dihydrogen more efficiently, converting it into valuable nutrients like VFA. Such a conversion could enhance rumen fermentation, providing additional energy to the host animal and thereby potentially boosting animal production.

In this thesis, we investigated the potential of selected phenolic compounds, some identified from previous publications (Tsai and Jones, 1975, Tsai et al., 1976, Krumholz and Bryant, 1986, Krumholz et al., 1987), and others based on their chemical structure, to act as hydrogen acceptors in vitro. Subsequently, based on our in vitro results, we selected an optimal phenolic compound from these candidates and evaluated its efficacy in capturing dihydrogen and However, it's important to recognize that the concentration of gallic acid in rumen fluid can be influenced by factors such as feed intake and passage rate. Notwithstanding, the inclusion levels in vitro and in vivo are difficult to compare because the systems, among other differences, have contrasting liquid to solid ratios. The inclusion methods for gallic acid and methanogenesis inhibitor in vitro and in vivo were also different. We added gallic acid and A. taxiformis directly into the fermentation bottle, while we added gallic acid and A. armata in the pellet. Moreover, the substrates for in vitro and the diet for in vivo were different. The in vitro experiment used 70% alfalfa hay as forage and 30% barley grain, while the in vivo experiment used around 75% mixed forage and 25% concentrate pellet (Table 7, Chapter 4).

Regarding VFA parameters, distinctions exist between the two experimental settings. In the in vitro experiment, VFA profiles reflect the production of different individual VFAs. On the other hand, in the in vivo experiment, the VFA profiles reflect the production and absorption by the rumen wall of different individual VFA [START_REF] Dijkstra | Production and absorption of volatile fatty acids in the rumen[END_REF]. Also, factors such as the rumen microbiota, and pressure in rumen and the bottle headspace are also a source of variation between the in vitro and in vivo experiments.

The methods used to measure dihydrogen and methane between in vitro and in vivo experiments were different. In the in vitro experiment, we used micro GC to measure dihydrogen and methane, while in the in vivo experiment, we used Greenfeed to measure dihydrogen and methane. The limit of quantitation for the micro GC is lower than 1 ppm (Micro GC Fusion, INFICON), while the limit of quantitation for the Greenfeed is 20 ppm for methane and lower than 1 ppm for dihydrogen [START_REF] Hristov | The use of an automated system (GreenFeed) to monitor enteric methane and carbon dioxide emissions from ruminant animals[END_REF][START_REF]Hydrogen sensor[END_REF]. Also, the in vitro experiment measured the concentration of dihydrogen and methane in the accumulated gas, conversely, the in vivo experiment measured the concentration of dihydrogen and methane in the breath of cow. During the in vivo experiment, cows were allowed to use the Greenfeed 6 times maximum per day with at least 4 hours between the consecutive visits.

We observed that 36 mM phloroglucinol supplementation increased in the abundance of bacteria potentially involved in phenolic compound degradation in cow and goat's sequential incubation experiments. These findings are in line with our fermentation results, phloroglucinol supplementation increased acetate proportion and total VFA production. In the in vivo experiment, we collected rumen fluid samples for microbiota DNA and RNA sequencing. The sequencing data are currently undergoing metataxonomic, metagenomic, and metatranscriptomic analyses. The comprehensive omics data will provide insights into the response of the rumen microbiota to gallic acid and A. armata supplementation and the divergent results obtained from the in vitro and in vivo experiments. In this thesis, we only reported the preliminary results of the metataxonomic analysis.

While the role of gallic acid as a hydrogen acceptor in the in vivo experiment remains unknown, we observed that gallic acid supplementation alleviated the negative effect of A. armata on milk production. Moreover, there was a positive interaction effect between gallic acid and A.

armata on milk production, given the conditions in this study. For future research, we recommend considering the following aspects:

• Using different methods to measure dihydrogen

As we discussed before, Greenfeed system measures methane and dihydrogen through spot sampling. Other methane and dihydrogen measurement devices such as respiration chambers might be more adequate. Respiration chambers continuously measure methane and dihydrogen emissions over a 24-hour period, accurately reflecting the emissions within a daily cycle.

Nevertheless, the respiration chamber is costly, demands a significant workload, and has limitations regarding the number of animals used in the trial. The amount of dihydrogen erupted from rumen accounts for only 23% of the stoichiometric amount involved with the decrease in methane production (van Gastelen et al., 2020). The metabolic pathways of the remaining 77% dihydrogen are not fully understood. Research indicated that inhibiting methanogenesis leads to increases in dissolved dihydrogen (Janssen, 2010), propionate proportion (Janssen, 2010), formate concentration (Ungerfeld, 2015), and lactate concentration (Ungerfeld, 2015). Therefore, it is likely that these dihydrogen "metabolic pathways" could also be affected by supplementation of an external hydrogen acceptor. And we suggest to measure these parameters in future studies where feasible.

• Using different methanogenesis inhibitor

In our in vivo study, we employed A. armata as a methanogenesis inhibitor. We observed a 25% reduction in methane yield and a 200% increase in dihydrogen yield in the AT treatment compared to the CON treatment. These findings suggest that A. armata effectively inhibited methanogenesis, corroborating the results of a previous study by Roque et al. (2019). We also found that gallic acid combined with A. armata had positive interaction effect on milk production.

However, the effect of external hydrogen acceptors combined with other methanogenesis inhibitors on gas emissions and animal performance is not well known. Therefore, we suggest to test the effect of different methanogenesis inhibitor combined with hydrogen acceptor on milk production in future animal studies because this could accelerate the application of this technology. For example, 3-nitrooxypropanol was frequently reported that it could decrease methane production by around 30% without negative effects on DMI, feed digestion, animal production, and animal health [START_REF] Thiel | 3-NOP: mutagenicity and genotoxicity assessment[END_REF], van Gastelen et al., 2020). Moreover, this product is allowed to be used in many countries with large ruminant populations including the European Union and Brazil.

• To test the effects of different inclusion levels of gallic acid supplementation on milk production Studies using gallic acid as feed additive are scarce. [START_REF] Xu | Growth performance, digestibility, blood metabolites, ruminal fermentation, and bacterial communities in response to the inclusion of gallic acid in the starter feed of preweaning dairy calves[END_REF] reported that gallic acid supplementation improved preweaning dairy calves daily weight gain, increased their rumen total VFA concentration, and improved their antioxidant ability. In line with this, Aboagye et al. (2019) demonstrated that gallic acid supplementation not only increased total VFA concentration but also reduced the proportion of urea nitrogen in urinary nitrogen and decreased methane yield in beef cattle. A similar decrease the proportion of urea nitrogen in urinary nitrogen in beef cattle following gallic acid supplementation was reported by [START_REF] Wei | Effect of dietary supplementation of gallic acid on nitrogen balance, nitrogen excretion pattern and urinary nitrogenous constituents in beef as hydrogen acceptors when ruminal methanogenesis is inhibited in vitro-Part 1[END_REF]. In our in vivo experiment, we found that gallic acid alleviated the negative effect of A. armata on milk production. To the best of our knowledge, our study is the first to report that gallic acid had this positive effect. Given this initial finding, we believe further research is warranted to delve deeper into the impact of varying gallic acid inclusion levels on milk production and to elucidate the underlying mechanisms.

• To test the effect of different inclusion levels of hydrogen acceptor combined with methanogenesis inhibitor on gas emissions and milk production Our in vivo experiment observed that gallic acid combined with A. armata had a positive interaction effect on milk production, given the conditions of this study. These results indicate that using a methanogenesis inhibitor can improve animal production if combined with a hydrogen acceptor as feed additive. Nevertheless, there are several aspects for further research that we believe are crucial: 1) to find the optimal inclusion level of gallic acid to combine with methanogenesis inhibitor. Understanding the precise amounts can maximize the benefits while minimizing potential negative effects. 2) to study the diet effects on the interaction effect of gallic acid combined with A. armata. In our in vivo experiment, the forage to concentrate ratio is around 75 to 25. The interactions between gallic acid and A. armata could be influenced by the composition of the diet, especially since the efficacy of methanogenesis inhibitors like 3nitrooxypropanol has been observed to vary with NDF concentration [START_REF] Kebreab | A meta-analysis of effects of 3-nitrooxypropanol on methane production, yield, and intensity in dairy cattle[END_REF]. 3) to study the methods used to add gallic acid and A. armata in the diet. In our in vivo experiment, we added gallic acid and A. armata in the concentrate, which was subsequently pelleted.

Investigating different modes of inclusion, such as direct addition to the total mixed ration, is vital.

The method of introduction might alter the interaction effect between gallic acid and A. armata on milk production.

• To test different hydrogen acceptor

Our in vitro experiment showed that gallic acid and phloroglucinol served as hydrogen acceptors, while we chose gallic acid for the in vivo experiment because it is in the feed additive list. However, we believe that phloroglucinol should also be tested in vivo. This belief is particularly strengthened by our findings in the sequential incubation experiment (Chapter 2), where phloroglucinol demonstrated a significant reduction in dihydrogen accumulation. Moreover, we could also test hydrolysable tannin-enriched by products as hydrogen acceptor due to hydrolysable tannin can be transferred into phenolic compound in the rumen.

In summary, our study provides evidence suggesting that both gallic acid and phloroglucinol have the potential to act as hydrogen acceptors within the rumen ecosystem. In the in vitro experiment, we observed that gallic acid and phloroglucinol acted as hydrogen acceptors, promoting alternative hydrogenotrophic pathways when methanogenesis was inhibited. Both gallic acid and phloroglucinol increased acetate proportion and total gas production. Importantly, after an adaptation phase, the supplementation of phloroglucinol with BES effectively reduced dihydrogen accumulation, methane production, and methanogen abundance. Furthermore, this treatment increased proportions of acetate and butyrate. The combined supplementation of phloroglucinol or pyrogallol with a methanogenesis inhibitor also induced changes in the rumen microbiota of cows and goats, with an increase in the abundance of phenolic compounddegrading bacteria in vitro. In our in vivo experiment, although gallic acid had no effect and gallic acid combined with A. armata had no interaction effect on dihydrogen and methane emissions or VFA profiles, gallic acid supplementation alleviated the negative effect of A. armata on milk production, and gallic acid combined with A. armata had positive interaction effect on milk production. Our findings could accelerate the application of methanogenesis inhibitor in practice, aiming to decrease greenhouse gas emission from the ruminant sector. Also, they could help to address the challenge of world population growth by improving animal production.

Curriculum Vita

Email Address: huangrcai@foxmail.com

EDUCATION

1

  Introduction ................................................................................................................... 2 Material and Methods ................................................................................................... 2.1 Animals, Experimental Design, and Diets ................................................................. 2.2 Sampling and measurement ...................................................................................... 2.3 Gas measurement ..................................................................................................... 2.4 Milk production, composition, body weight, and body condition score .................. 2.5 Rumen fluid and blood ............................................................................................... 2.6 Statistical analysis ..................................................................................................... 3 Results .......................................................................................................................... 3.1 Enteric gas emissions ................................................................................................ 3.2 Rumen fermentation .................................................................................................. 3.3 Effect of A. armata and gallic acid on animal performance ....................................... 3.4 Blood biochemistry .................................................................................................... 3.5 Metabolomic and metataxonomic analysis ............................................................... 4 Discussion ..................................................................................................................... 5 Conclusion .................................................................................................................... References ....................................................................................................................... CHAPTER 5 ..................................................................................................................... General discussion and conclusions ............................................................................... Reference ........................................................................................................................ Appendix ......................................................................................................................... 1 Publications ................................................................................................................... 2 Poster presentation ....................................................................................................... 3 Curriculum Vitae ...........................................................................................................

Figure 1 5 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14

 15234567891011121314 Figure 1 Carbohydrate metabolism pathways. ................................................................... 5 Figure 2 Acetate, propionate, and butyrate generation in the rumen. Solid and dashed arrows represent single and lumped Enzymatic reactions, respectively. .......................... 10 Figure 3 Reducing equivalents generation and consumption by amino acids metabolism: example of glutamate and glutamine which is in the central status in amino acids synthesis in the rumen. (Modified from Wu, 2013) ............................................................................ 14 Figure 4 Electron transfer occurs among NAD(H), NADP(H), and ferredoxin. ................ 18 Figure 5 Common hydrogenases and the bifurcation reaction in Wolfe cycle. ................ 23 Figure 6 Experimental design of the sequential batch incubation that used rumen fluid inocula from dairy cows (n=8). ........................................................................................... 68 Figure 7 Beta diversity of ruminal bacteria from cow inocula (A) and goat inocula (B) experiment. ...................................................................................................................... 107 Figure 8 Top 50 features with significant associations of ruminal bacteria from cow inocula (A) and goat inocula (B) experiments compared to control, respectively. ....................... 110 Figure 9 An UpSetR plot of unique ASVs across different treatments in cow inocula (A) and goat inocula (B) experiments. ................................................................................... 117 Figure 10 Score plots of principal component analysis of blood metabolites. ............... 155 Figure 11 Orthogonal partial least squares-discriminant analysis between CON and AT treatments. ....................................................................................................................... 155 Figure 12 Alpha-diversity among treatments during the experimental period. .............. 161 Figure 13 Beta-diversity among treatments during the experimental period. ................ 161 Figure 14 Effect of storage time and pelleting on concentration of bromoform (CHBr3) in 3% A.armata containing pellet. ........................................................................................ 164

  ...................................................................................................................................... 73Table 3 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, gallic acid, and formic acid at 6 mM when combined with A.taxiformis at 2.5% DM on in vitro rumen fermentation from dairy cows (n= 4). .............................................................. 75

  armata, gallic acid, and their combination on enteric gas emissions in lactating dairy cows. ........................................................................................................ 147 Table 9 Effect of A. armata, gallic acid, and their combination on rumen fermentation in lactating dairy cows. ........................................................................................................ 149 Table 10 Effect of A. armata, gallic acid, and their combination on protozoa counting in lactating dairy cows. ........................................................................................................ 150 Table 11 Effects of A. armata, gallic acid, and their combination on lactating dairy cows' performance. .................................................................................................................... 152 Table 12 Effect of A. armata, gallic acid, and their combination on blood biochemistry in lactating dairy cows. ........................................................................................................ 153 Table 13 Differential metabolites between CON and AT treatments. ............................. 156 Table S1 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, and gallic acid or formic acid at 2 mM on 24-h in vitro ruminal fermentation from dairy cows (n=4). .................................................................................................................................. 91 Table S2 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, and gallic acid or formic acid at 4 mM on 24-h in vitro ruminal fermentation from dairy cows (n=4). .................................................................................................................................. 92

XII

  vitro ruminal fermentation from dairy cows (n=4). .............................................................

  .............................................................................................................. Table S6 Bacterial abundance from cow inocula experiment. ........................................

  let my experiment performed smoothly. I would like to thank my defense committee members: Dr. Christiane FORESTIER, Dr. Christophe CHASSARD, Dr. Eva RAMOS-MORALES, and Dr. Gabriel DE LA FUENTE OLIVER. Your comments and suggestions were very helpful to improve the quality of my thesis. And especially thanks to Dr. Eva RAMOS-MORALES, and Dr. Gabriel DE LA FUENTE OLIVER for reviewing my dissertation. I would like to thank the DINAMIC team, the administration team of UMRH, the doctoral school of Institut Sciences de la vie, Santé, Agronomie, Environnement of Université Clermont Auvergne, and the Herbipôle team. I got invaluable help and training from these team members. I would like to thank Dr. Jérémy Tournayre for his assistance with sequencing data analysis. I would like to express my gratitude to Sarah FESCHET and Karim FAWAZ for their valuable assistance in analyzing the samples, as well as for Sarah's thoughtful gift. I am grateful to the China Scholarship Council-Agreenium joint scholarship for providing financial support for my Ph.D. study. I would like to thank Dr. Jean-Paul Lallès and Dr. Rafael MUNOZ-TAMAYO for their introduction. I would like to thank my collaborators Dr. David R Yáñez-Ruiz, Dr. Alejandro BELANCHE, Pedro Romero, and Dr.

Figure 1

 1 Figure 1 Carbohydrate metabolism pathways. Blue area represents the glycolysis pathway; pink area represents the oxidation reactions of pentose phosphate pathway; gray area represents the Entner-Doudoroff pathway; green area represents the methylglyoxal pathway; and the yellow area represents the phosphoketolase pathway. Solid and dashed arrows represent single and lumped enzymatic reaction, respectively.

Figure 2

 2 Figure 2 Acetate, propionate, and butyrate generation in the rumen. Solid and dashed arrows represent single and lumped Enzymatic reactions, respectively.

Figure 4

 4 Figure 4 Electron transfer occurs among NAD(H), NADP(H), and ferredoxin. STH, energy-independent soluble transhydrogenase; PntAB, membrane-bound pyridine nucleotide transhydrogenase; EtfAB-Bcd, electron transferring flavoprotein/butyryl-CoA dehydrogenase; FNRs, ferredoxin: NADP + oxidoreductases; NfnAB, NADH-dependent reduced ferredoxin: NADP + oxidoreductase; Rnf, rhodobacter nitrogen fixation.

Figure 5

 5 Figure 5 Common hydrogenases and the bifurcation reaction in Wolfe cycle. HydABC, electron-bifurcating Fd-and NAD-dependent [FeFe]-hydrogenase; MtrA-H, energy-conserving methyltransferase;

  speculated that Rhodopseudomonas gelatinosa decomposes 1 molecule of phloroglucinol to produce 3 molecules of acetate and consumes 1 molecule NAD(P)H, whileKrumholz et. al. (1987) speculated that Eubacterium oxidoreducens decomposes 1 molecule of phloroglucinol to produce 3 molecules of acetate and consumes 0 molecules of NAD(P)H or to produce 1 molecule of acetate, 1 molecule of butyrate, and consumes 2 molecules of NAD(P)H based on the enzymes isolated from the pure culture. The pathways of phloroglucinol degradation mentioned above only represent the specific bacteria and they have not been confirmed. However, an in vivo study has been observed that phloroglucinol decreased dihydrogen expelled (g/kg DMI) and decreased formate concentration in the rumen fluid when methanogenesis was inhibited(Martinez- Fernandez et al., 2017).



  Treatment: 2, 4, and 6 mM of each phenolic compounds, control  Incubation time: 24 h Exp.2  Treatment: 6 mM of each phenolic compounds + 3 μM BES  Incubation time: 24 h Exp.3 (sequential incubation) Sample collection: gas and fermentation fluid were collected at end of the fourth and fifth incubations. Main finding  6 mM phenolic compound alone didn't have negative effect on fermentation  6 mM phloroglucinol and gallic acid combined with BES increased acetate proportion  After adaptation, 36 mM phloroglucinol combined with BES decreased dihydrogen accumulation  Supplementation with 36 mM phloroglucinol decreased methanogens abundance Conclusion Phloroglucinol and the gallic acid have the potential to serve as dihydrogen acceptors in vitro. In addition, phloroglucinol supplementation likely have the negative effect on methanogens abundance. Evaluating the effect of phenolic compounds as hydrogen acceptors when ruminal methanogenesis is inhibited in vitro-Part 1. Dairy cows R. Huang a , P. Romero b , A. Belanche b, c , E. M. Ungerfeld d , D. Yanez-Ruiz b , D. P. Morgavi a , M. Popova a a Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genes-Champanelle, France. b Estación Experimental del Zaidín (CSIC), Profesor Albareda, 1, 18008, Granada, Spain. c Departamento de Producción Animal y Ciencia de los Alimentos, Universidad de Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain. d Centro Regional de Investigación Carillanca, Instituto de Investigaciones Agropecuarias INIA, Temuco 4880000, Chile Corresponding author: Diego Morgavi. E-mail address: diego.morgavi@inrae.fr Note: This chapter was published on animal. (https://doi.org/10.1016/j.animal.2023.100788).

Figure 6

 6 Figure 6 Experimental design of the sequential batch incubation that used rumen fluid inocula from dairy cows (n=8). Abbreviations: A = Substrate only; B = Substrate + 2-bromoethanesulfonic sodium; C = Substrate + phloroglucinol; D = Substrate + phloroglucinol + 2-bromoethanesulfonic sodium. The number next to the capital letter indicates the sequential of incubation. The inclusion levels of phloroglucinol and 2-bromoethanesulfonic sodium are 36 mM and 3 μM, respectively.

  Abbreviations: AT = A. taxiformis; Phe = phenol; Cat = catechol; Res = resorcinol; Hyd = hydroquinone; Phl = phloroglucinol; Pyr = pyrogallol; GA = gallic acid; FA = formic

Figure 7

 7 Figure 7 Beta diversity of ruminal bacteria from cow inocula (A) and goat inocula (B) experiment. CTL = control; BES = 3 μM 2-bromoethanesulfonic sodium; PHL = 36 mM phloroglucinol; BES+PHL = 3 μM 2bromoethanesulfonic sodium + 36 mM phloroglucinol; AT = 2% A. taxiformis; AT+PHL1 = 2% A. taxiformis + 6 mM phloroglucinol; PHL2 = 2% A. taxiformis + 36 mM phloroglucinol; AT+PYR1 = 2% A. taxiformis + 6 mM pyrogallol; AT+PYR2 = 2% A. taxiformis + 36 mM pyrogallol.

Figure 8

 8 Figure 8 Top 50 features with significant associations of ruminal bacteria from cow inocula (A) and goat inocula (B) experiments compared to control, respectively. BES = 3 μM 2-bromoethanesulfonic sodium; PHL = 36 mM phloroglucinol; BES+PHL = 3 μM 2-bromoethanesulfonic sodium + 36 mM phloroglucinol; AT = 2% A. taxiformis; AT+PHL1 = 2% A. taxiformis + 6 mM phloroglucinol; PHL2 = 2% A. taxiformis + 36 mM phloroglucinol; AT+PYR1 = 2% A. taxiformis + 6 mM pyrogallol; AT+PYR2 = 2% A. taxiformis + 36 mM pyrogallol.

Figure 9

 9 Figure 9 An UpSetR plot of unique ASVs across different treatments in cow inocula (A) and goat inocula (B) experiments. The number of ASV for each treatment is plotted on the left of the Upset plots of cows and goats, respectively. Dark circles indicate samples containing accessions and their counts are shown by the figures at the top of the charts. Connecting bars indicate overlap between multiple samples. CTL = control; BES = 3 μM 2-bromoethanesulfonic sodium; PHL = 36 mM phloroglucinol; BES+PHL = 3 μM 2-bromoethanesulfonic sodium + 36 mM phloroglucinol; AT = 2% A. taxiformis; AT+PHL1 = 2% A. taxiformis + 6 mM phloroglucinol; PHL2 = 2% A. taxiformis + 36 mM phloroglucinol; AT+PYR1 = 2% A. taxiformis + 6 mM pyrogallol; AT+PYR2 = 2% A. taxiformis + 36 mM pyrogallol.

Figure

  Figure S1 Distance-based redundancy analysis for cow inocula experiment. CTL = control; BES = 3 μM 2-bromoethanesulfonic sodium; PHL = 36 mM phloroglucinol; BES+PHL = 3 μM 2bromoethanesulfonic sodium + 36 mM phloroglucinol.

Figure 10

 10 Figure 10 Score plots of principal component analysis of blood metabolites. R 2 X[1] and R 2 X[2] represent component 1 (t[1]) and 2 (t[2]), respectively. Abbreviations: CON = basal diet; AT = 0.25% A. armata in the basal diet; GA = 0.8% gallic acid in the basal diet; MIX = 0.25% A. armata and 0.8% gallic acid in the basal diet.

Figure 11

 11 Figure 11 Orthogonal partial least squares-discriminant analysis between CON and AT treatments. R2X[1] and R2Xo[1] represent predictive component (t[1]) and orthogonal component (to[1]), respectively. Components=1+0+0, R 2 (cum)=0.817, Q 2 (cum)=0.765, P-value=0.00147. Abbreviations: CON = basal diet; AT = 0.25% A. armata in the basal diet.

Figure 12

 12 Figure 12Alpha-diversity among treatments during the experimental period.

Figure 13

 13 Figure 13 Beta-diversity among treatments during the experimental period. P-value = 0.0001 for treatments, P-vaule = 0.006 for CON vs GA, P-value = 0.001 for CON vs MIX, P-value = 0.001 for CON vs AT, P-value = 0.001 for GA vs MIX, P-value = 0.013 for MIX vs AT. Abbreviations: CON = basal diet; AT = 0.25% A. armata in the basal diet; GA = 0.8% gallic acid in the basal diet; MIX = 0.25% A. armata and 0.8% gallic acid in the basal diet; Tret = treatment; TUE = Tuesday; THU = Thursday; NMDS = non-metric multidimensional scaling.

Figure 14

 14 Figure 14Effect of storage time and pelleting on concentration of bromoform (CHBr3) in 3% A. armata containing pellet. Pellet was made in week 5 and the bromoform concentration in week 5 (solid line) was calculated based on the inclusion level of A. armata in the pellet (3%), the bromoform concentration in the A. armata (15.5 mg/g DM), and assumed that there is no bromoform loss during pelleting. The bromoform concentration in week 5 (dashed line) was based on the linear relationship from week 7 to week 11.

AWARDSoo

  Recipient of China Scholarship Council and Agreenium joint scholarship. o European scholarship Erasmus+ and local region scholarship CAP 20-25. o Recognized as an outstanding researcher by CSC-Seminar in Germany and France committee. (2021) PUBLICATIONS o Huang, R., P. Romero, A. Belanche, E. Ungerfeld, D. Yanez-Ruiz, D. Morgavi, and M. Popova. 2023. Evaluating the effect of phenolic compounds o Poster presentation at the 8 th International Greenhouse Gas and Animal Agriculture Conference in 2022. Poster title: Synergistic effects of natural hydrogen acceptors and a methanogenesis inhibitor on in vitro rumen fermentation. Presentation at Journee des Doctorants et Post-Doctorants de L'UMRH INRAE in 2022. Presentation title: combined effects of natural hydrogen acceptors and a methanogenesis inhibitor on rumen microbiota, rumen fermentation, gas emissions, and production in lactating dairy cow. o Presentation at JEDs 2022 Université Clermont Auvergne in 2022. Presentation title: Synergistic effects of natural hydrogen acceptors and a methanogenesis inhibitor on in vitro. o Poster presentation at Journee des Doctorants et Post-Doctorants de L'UMRH INRAE in 2021. Poster title: Phloroglucinol reduced methane production and hydrogen accumulation in vitro. o Presentation at CSC-Seminar in Germany and France in 2021. Presentation title: Capture Excessive Hydrogen Generated from Methanogenesis Inhibition to Improve Animal Production.

Table 5

 5 Alpha diversity metrics of ruminal bacteria from cow inocula experiment. ........ 104

Table 6

 6 Alpha diversity metrics of ruminal bacteria from goat inocula experiment. ........ 105

Table 7

 7 Ingredients and chemical composition of the experimental diets. ..................... 138

Table 8

 8 Effects of A.

Table S7

 S7 Bacterial abundance from goat inocula experiment. .......................................

	Milk urea nitrogen	ABBREVIATIONS	MUN
	NADH-dependent reduced ferredoxin: NADP+ oxidoreductase	NfnAB
	Alkaline phosphatase Neutral detergent fiber	ALP NDF
	Acetate:propionate ratio Non-esterified fatty acids	A:P NEFA
	Acid detergent fiber Organic matter		ADF OM
	Acid detergent lignin Oxidized nicotinamide adenine dinucleotide	ADL NAD +
	Adenosine triphosphate Oxidized nicotinamide adenine dinucleotide	ATP NADP +
	Alanine transaminase Oxidized nicotinamide adenine dinucleotide phosphate	ALT Fdox
	Asparagopsis armata Pyruvate dehydrogenase	A. armata PDH
	Asparagopsis taxiformis Pyruvate formate-lyase	A. taxiformis PFL
	Aspartate aminotransferase Pyruvate-ferredoxin oxidoreductase	AST PFOR
	Beta-hydroxybutyrate Quantitative polymerase chain reaction	BHB qPCR
	Crude protein		CP
	Dihydrogen		H2
	Dry matter		DM
	Dry matter intake		DMI
	Electron transferring flavoprotein/butyryl-CoA dehydrogenase	EtfAB-Bcd
	Energy corrected milk production	ECM
	Energy-conserving methyltransferase	MtrA-H
	Energy-independent soluble transhydrogenase	STH
	Erredoxin-dependent and membrane-associated Hydrogenase	Ech
	Ferredoxin: NADP+ Oxidoreductase	FNRs
	Gamma-glutamyl transferase	GGT
	Gross energy		GE
	Hydrogenase/heterodisulfide reductase complex	HdrABC
	Membrane-bound pyridine nucleotide transhydrogenase	PntAB
	Methane		CH4

Table 1

 1 The quantitative relationship between the production of 1 mole of acetate, butyrate, and propionate and the availability of reducing equivalents, ATP, and dihydrogen 1 . We assume that pyruvate is the precursor for acetate, butyrate, and propionate production, and the pyruvate is generated by glucose via glycolysis pathway.

	VFA	NADH	Fdred -1	ATP	H2
	Acetate	1	2	2	2
	Butyrate	-1	6	3	2
	Propionate	-1	0	1	-1
	1

  P.Morgavi, and H. Boudra. 2021. Milk metabolome reveals variations on enteric methane emissions from dairy cows fed a specific inhibitor of the methanogenesis pathway. Journal of dairy science. 104:12553-12566. Yanibada, B. n. d., U. Hohenester, M. Pétéra, C. Canlet, S. Durand, F. Jourdan, J. Boccard, C. Martin, M. Eugène, and D. P. Morgavi. 2020. Inhibition of enteric methanogenesis in dairy cows induces changes in plasma metabolome highlighting metabolic shifts and potential markers of emission. Scientific reports. 10:1-14.

	Zhao, Y., X. Nan, L. Yang, S. Zheng, L. Jiang, and B. Xiong. 2020. A Review of Enteric
	Methane Emission Measurement Techniques in Ruminants. Animals. 10:1-15.

Table 2

 2 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, and gallic acid or formic acid at 6 mM on 24-h in vitro ruminal fermentation from dairy cows (n= 4).

	Item	Control 1	Phenol	Catechol	Resorcinol	Treatment Hydroquinone	Phloroglucinol	Pyrogallol	Gallic acid	Formic acid	SEM	P-value 2
	Gas production
	(mL)
	TGP / 0-6 h	58.7	58.0	58.2	57.9	60.7	58.1	58.5	62.6*	62.2*	10.08	<0.0001
	TGP / 6-24 h	65.9	64.5	65.9	65.6	67.2	71.9*	66.6	70.4*	66.4	8.59	<0.0001
	TGP / 0-24 h	124.6	122.5	124.1	123.4	127.9	129.9*	125.2	133.0*	128.7	18.64	<0.0001
	CH4 / 0-6 h	13.3	13.3	13.0	13.3	14.1	13.4	13.6	14.1	15.2*	1.79	<0.0001
	CH4 / 6-24 h	17.2	16.7	17.2	16.9	17.8	16.0	16.7	18.0	16.6	2.29	0.028
	CH4 / 0-24 h	30.4	30.0	30.3	30.2	31.9	29.4	30.3	32.1	31.7	4.06	0.004
	H2 / 0-6 h	0.06	0.03	0.13	0.12	0.13	0.04	0.10	0.07	0.00	0.038	0.034
	Metabolic	75.8	74.6	76.6	75.7	76.7	56.7*	66.3*	72.8	78.2	2.25	<0.0001
	hydrogen
	recovery (%)
	NH3-N (mg/100	31.9	35.3	28.4	27.6	38.3	23.6	32.3	31.9	35.3	4.63	0.061
	mL)
	pH	6.72	6.26*	6.18*	6.25*	6.19*	6.98	7.02	6.66	6.72	0.120	<0.001
	Total VFA (mM)	105.8	105.3	104.6	105.1	109.2	126.6*	123.6	112.5	106.7	15.56	0.013
	VFA, mol/100
	mol
	Acetate	59.8	59.7	58.9	59.5	59.6	65.5*	61.4	61.6	59.3	2.28	<0.0001
	Propionate	16.5	16.3	16.3	16.6	15.4*	12.8*	15.3*	14.8*	16.8	0.55	<0.0001
	Isobutyrate	2.0	2.0	2.2	2.1	2.0	1.7*	1.9	1.9	2.0	0.07	<0.0001
	Butyrate	13.0	13.2	13.2	13.0	12.7	12.0	12.5	12.4	13.2	1.23	0.024
	Isovalerate	4.2	4.1	4.6	4.3	4.8*	3.8	4.2	4.3	4.2	0.39	0.005
	Valerate	3.7	3.7	3.8	3.6	3.9	3.0*	3.5	3.5	3.7	0.12	0.002
	A:P	3.6	3.7	3.6	3.6	3.8	5.1*	4.0	4.2*	3.6	0.23	0.001

Table 3

 3 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, gallic acid, and formic acid at 6 mM when combined with A. taxiformis at 2.5% DM on in vitro rumen fermentation from dairy cows (n= 4).

							Treatment
	Item	Substrate	AT	AT+Phe	AT+Cat	AT+Res	AT+Hyd	AT+Phl	AT+Pyr	AT+GA	AT+FA	SEM	P-value 2
		alone 1
	Gas
	production
	(mL)
	TGP / 0-6	56.06.4	46.6	46.9	47.4	48.8	49.1	50.0	47.9	50.9*	53.0*	2.12	0.002
	h
	TGP / 6-24	55.13.8	49.4	50.7	48.8	49.3	49.3	53.7	49.9	52.7	49.8	3.56	0.206
	h
	TGP / 0-24	111.14.5	96.0	97.6	96.2	98.1	98.4	103.6*	97.8	103.6*	102.8*	4.19	0.001
	h
	CH4 / 0-6 h	12.81.0	2.3	4.1	3.6	3.1	2.1	1.0	2.5	2.6	1.2	1.15	0.034
	CH4 / 6-24	14.32.1	4.3	8.4	6.5	5.3	3.5	0.7	3.2	3.7	0.5	2.91	0.164
	h
	CH4 / 0-24	27.02.4	6.6	12.5	10.1	8.4	5.6	1.7	5.6	6.2	1.7	4.02	0.107
	h
	H2 / 0-6 h	0.0	5.41	3.42	3.97	5.10	6.26	5.95	5.28	5.58	8.94*	1.220	0.002
	Metabolic	60.35.9	48.2	56.4	49.2	48.3	46.5	26.8*	42.0	39.8	42.4	5.42	0.002
	hydrogen
	recovery
	(%)
	NH3-N,	45.06.0	39.9	37.6	37.7	30.4	26.9*	29.6	34.6	37.7	32.7	3.77	0.031
	(mg/100
	mL)
	Total VFA	120.05.5	93.4	93.1	98.7	96.4	92.3	110.2*	95.3	99.2	93.4	3.18	0.014
	(mM)
	VFA,
	mol/100
	mol
	Acetate	64.04.1	43.7	46.3	51.2	49.3	45.4	61.6*	48.2	53.7	45.0	3.08	0.035
	Propionate	18.32.5	24.7	23.4	23.6	24.2	24.7	18.7*	23.7	22.5	26.1	1.84	<0.0001
	Isobutyrate	2.10.9	1.8	1.8	1.6	1.6	1.5	1.3	1.7	1.5	1.2	0.185	0.416
	Butyrate	9.21.2	17.5	16.2	15.1	15.3	16.5	17.4	16.1	14.9	17.0	1.58	0.158
	Isovalerate	3.31.3	3.9	3.9	3.1	3.2	3.1	2.5*	3.2	2.9	2.6	0.26	0.008
	Valerate	2.70.7	4.7	4.4	4.2	4.0	4.4	3.8	4.2	4.0	4.4	0.30	0.200
	A:P	3.60.6	1.9	2.2	2.3	2.2	2.1	3.2*	2.2	2.5	1.9	0.30	0.002

Table 4

 4 Effect of phloroglucinol with or without BES as methanogenesis inhibitor using a sequential batch culture incubation method and rumen fluid from dairy cows (n=8).

	Item	Control 1	BES	Treatment	PHL	PHL + BES	SEM	P-value
	TGP (mL)	92.4 c	84.1 d		95.3 abc	97.9 a	1.03	<0.0001
	CH4 (mL)	9.71 a	2.90 b		0.03 c	0.00 c	0.290	<0.0001
	H2 (mL)	0.29 b	2.99 a		1.13 b	0.84 b	0.363	<0.0001
	Metabolic hydrogen recovery	29.7 a	33.1 a		5.6 b	4.3 b	4.10	<0.0001
	(%)
	NH3-N (mg/100 mL)	40.6 a	40.4 a		17.4 b	16.8 b	0.60	<0.0001
	Total VFA (mM)	113.2 b	106.9 b		180.5 a	189.6 a	5.52	<0.0001
	VFA, mol/100 mol
	Acetate	60.0 b	56.0 b		77.3 a	79.4 a	1.34	<0.0001
	Propionate	21 2 a	22.7 a		3.4 b	3.1 b	0.48	<0.0001
	Isobutyrate	1.6 a	1.6 a		0.7 b	0.6 b	0.05	<0.0001
	Butyrate	10.4 b	12.3 bc		16.4 a	15.0 ac	0.99	<0.0001
	Isovalerate	2.3 a	2.3 a		1.0 b	1.0 b	0.09	<0.0001
	Valerate	4.0 a	4.7 b		0.5 c	0.4 c	0.15	<0.0001
	A:P	2.9 b	2.3 b		20.5 a	19.6 a	1.16	<0.0001
	Microbe (log10 copies / mL)
	Bacteria	10.03 b	10.06 b		10.34 a	10.31 a	0.054	0.001
	Protozoa	1.37	1.42		1.70	1.68	0.304	0.732
	Archaea	6.04 a	5.42 b		3.65 c	3.50 c	0.162	<0.0001
	Fungi	2.61	1.95		1.11	1.61	0.550	0.092

Table S1

 S1 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, and gallic acid or formic acid at 2 mM on 24-h in vitro ruminal fermentation from dairy cows (n=4).

	Item	Treatment Control 1	Phenol	Catechol	Resorcinol	Hydroquinone	Phloroglucinol	Pyrogallol	Gallic acid	Formic acid	SEM	P-value 2
	Gas
	production
	(mL)
	TGP / 0-6 h	58.68	56.58	57.71	57.30	58.42	60.27	58.92	59.94	59.19	10.43	0.21
	TGP / 6-24 h	65.90	61.79	65.10	65.87	66.98	68.84	65.88	66.91	65.85	8.44	0.13
	TGP / 0-24 h	124.58	118.79	122.81	123.17	125.41	129.11	124.81	126.85	125.04	18.89	0.13
	CH4 / 0-6 h	13.30	12.47	12.25	13.14	13.48	13.50	13.48	13.74	14.00	1.87	0.35
	CH4 / 6-24 h	17.15	16.15	16.68	16.90	17.36	16.94	16.61	16.49	16.35	2.35	0.50
	CH4 / 0-24 h	30.45	28.65	28.93	30.04	30.83	30.44	30.09	30.22	30.34	4.21	0.64
	H2 / 0-6 h	0.06	0.07	0.34	0.14	0.10	0.03	0.07	0.06	0.02	0.09	0.29
	Abbreviations: TGP = total gas production.

Table S2

 S2 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, and gallic acid or formic acid at 4 mM on 24-h in vitro ruminal fermentation from dairy cows (n=4).

	Item	Treatment Control 1	Phenol	Catechol	Resorcinol	Hydroquinone	Phloroglucinol	Pyrogallol	Gallic acid	Formic acid	SEM	P-value 2
	Gas
	production
	(mL)
	TGP / 0-6	58.68	58.98	58.83	58.64	58.31	59.07	60.34	60.94	60.47	9.86	0.25
	h
	TGP / 6-	65.90	65.48	65.84	65.84	65.45	69.95*	67.86	66.78	66.74	9.07	<0.01
	24 h
	TGP / 0-	124.58	124.46	124.66	124.28	123.76	129.03*	128.20	127.71	127.20	18.91	<0.01
	24 h
	CH4 / 0-6	13.30	13.47	13.18	13.82	13.62	13.57	14.30	13.80	14.12	1.81	0.19
	h
	CH4 / 6-24	17.15	16.81	17.04	16.68	17.15	16.17*	16.70	16.56	17.15	2.48	0.05
	h
	CH4 / 0-24	30.45	30.28	30.22	30.50	30.77	29.74	31.01	30.36	31.27	4.27	0.20
	h
	H2 / 0-6 h	0.06	0.03	0.08	0.02	0.06	0.06	0.06	0.07	0.00	0.03	0.76
	Abbreviations: TGP = total gas production.

Table S3

 S3 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, gallic acid, and formic acid at 6 mM when combined with A. taxiformis at 1.5% DM on in vitro ruminal fermentation from dairy cows (n=4).

	Item	alone 1 Substrate	AT	AT+Phe	AT+Cat	AT+Res	Treatment AT+Hyd	AT+Phl	AT+Pyr	AT+GA	AT+FA	SEM	P-value 2
	Gas production
	(mL)
	TGP / 0-6 h	56.046.40	49.39	48.41	50.49	49.64	48.54	54.41	48.88	51.92	51.70	3.06	0.39
	TGP / 6-24 h	55.073.75	55.69	55.62	56.23	58.38	55.92	64.00*	56.98	56.88	56.17	2.23	0.01
	TGP / 0-24 h	111.114.48	105.08	104.04	106.73	108.02	104.50	118.41*	105.86	108.80	107.87	4.41	0.09
	CH4 / 0-6 h	12.760.99	7.49	8.87	8.94	8.70	7.82	6.64	8.12	7.35	7.71	1.66	0.02
	CH4 / 6-24 h	14.262.09	13.68	14.08	14.44	14.85	14.28	10.07	12.92	12.16	13.31	1.86	0.09
	CH4 / 0-24 h	27.022.40	21.17	22.94	23.39	23.55	22.10	16.70	21.04	19.50	21.02	3.42	0.06
	H2 / 0-6 h	0.000.00	1.04	0.24	0.41	0.34	0.69	2.60	0.89	1.24	1.54	1.04	0.49
	Metabolic H	60.275.85	62.08	72.02	69.99	67.45	63.52	45.04*	59.15	56.30	64.86	4.32	<0.01
	recovery (%)
	NH3-N (mg/100	45.006.02	42.10	43.20	40.98	38.76	36.61	34.33	33.97*	38.24	40.84	3.53	0.02
	mL)
	Total VFA (mM)	120.05.50	109.0	95.6	101.0	104.7	106.6	127.3*	110.5	109.7	105.2	3.69	<0.01
	VFA, mol/100
	mol
	Acetate	64.04.14	55.7	56.4	56.3	57.2	57.4	59.8	57.6	57.0	54.5	3.20	0.74
	Propionate	18.32.46	20.5	19.9	19.8	19.9	20.2	18.2	19.1	19.2	21.5	1.90	0.25
	Isobutyrate	2.090.861	1.90	1.92	1.94	1.88	1.80	1.32	1.81	1.85	1.89	0.174	0.06
	Butyrate	9.171.238	13.2	13.0	13.0	12.6	12.5	14.2	13.0	13.3	13.7	1.70	0.92
	Isovalerate	3.331.335	3.96	4.00	4.43	3.96	3.95	2.85	4.19	4.16	3.92	0.336	0.09
	Valerate	2.720.690	3.91	3.89	3.79	3.68	3.52	3.13	3.60	3.77	3.96	0.373	0.17
	A:P	3.550.60	2.80	2.87	2.88	2.90	2.91	3.77	3.10	3.11	2.69	0.46	0.24

Abbreviations: AT = A. taxiformis; Phe = phenol; Cat = catechol; Res = resorcinol; Hyd = hydroquinone; Phl = phloroglucinol; Pyr = pyrogallol; GA = gallic acid; FA = formic acid; TGP = total gas production; VFA = volatile fatty acids; A:P = acetate: propionate ratio.

Table S4

 S4 Effect of phenol, catechol, resorcinol, hydroquinone, phloroglucinol, pyrogallol, gallic acid and formic acid at 6 mM when combined with BES at 3 μM on in vitro ruminal fermentation from dairy cows (n=4).

							Treatment						P-
	Item	Substrate	BES	BES+Ph	BES+Ca	BES+Re	BES+Hy	BES+Ph	BES+Py	BES+G	BES+F	SEM	value
		alone 1		e	t	s	d	l	r	A	A		2
	Gas
	production
	(mL)
	TGP / 0-6	52.996.22	49.59	47.67	47.83	49.02	46.98	47.73	47.90	51.47	51.24	1.99	0.06
	h
	TGP / 6-	56.755.83	51.25	50.70	50.90	50.02	50.20	59.05*	53.78	55.95*	52.10	2.63	<0.01
	24 h
	TGP / 0-	109.747.4	100.8	99.04	98.73	99.05	97.19	106.88*	101.67	107.42*	103.33	3.42	<0.01
	24 h	8	4
	CH4 / 0-6	11.820.88	2.93	4.36	4.39	5.05	4.81	5.88*	4.72	4.96	5.24	0.60	0.12
	h
	CH4 / 6-24	14.752.47	10.14	9.00	9.50	9.39	9.94	9.06	9.46	9.43	10.80	1.05	0.46
	h
	CH4 / 0-24	26.573.24	13.07	13.54	13.89	14.44	14.74	14.35	14.18	14.39	16.04*	1.23	0.10
	h
	H2 / 0-6 h	0.090.08	5.25	4.50	4.24	5.36	3.60	3.37	4.02	3.71	4.27	0.89	0.56
	Metabolic	79.362.46	65.06	54.11	60.02	58.97	60.01	44.06*	49.95*	48.92*	65.47	3.03	<0.01
	H
	recovery
	/ %
	NH3-N	35.4610.2	36.35	29.15	24.99	29.13	24.25	23.98	23.30	26.10	31.73	4.37	0.47
	(mg/100	0
	mL)
	Total VFA	93.012.14	95.0	88.3	86.3	91.7	88.5	105.0	99.0	105.4	88.7	6.03	<0.01
	(mM)
	VFA,
	mol/100
	mol
	Acetate	59.88.16	44.2	56.7*	54.0*	55.6*	53.5*	59.5*	58.8*	55.8*	52.0	3.94	<0.01
	Propionat	18.74.91	24.8	20.6	21.6	20.9	20.8	16.5*	18.9*	18.7*	21.2	2.12	<0.01
	e
	Isobutyrat	1.990.315	2.20	1.64	1.83	1.79	1.92	1.55*	1.57*	1.78	1.94	0.16	0.03
	e											4
	Butyrate	11.61.09	15.8	13.4	14.5	13.4	14.5	15.0	13.4	15.5	15.0	0.91	0.48
												7
	Isovalerat	3.710.990	6.12	3.53*	3.73*	3.79*	4.38*	3.39*	3.24*	3.43*	4.62*	0.76	<0.01
	e											6
	Valerate	3.681.310	5.69	3.44*	3.80*	3.94*	4.16*	3.44*	3.58*	4.10*	4.44	0.48	<0.01
												6
	A:P	3.431.19	1.87	2.88*	2.56	2.88*	2.70	3.77*	3.27*	3.04*	2.63	0.45	<0.01

Table 5

 5 Alpha diversity metrics of ruminal bacteria from cow inocula experiment. ,b Values within a row with different superscripts differ significantly at P < 0.05

		Treatment
	Item					SEM	P-value
		CTL	BES	PHL	BES+PHL
	Observed ASVs	246 a	224 a	71 b	83 b	9.5	<0.0001
	Shannon index	4.41 a	4.37 a	3.60 b	3.48 b	0.080	<0.0001
	Simpson index	0.96	0.97	0.96	0.95	0.004	0.0375
	Faith's phylogenetic diversity	11.04 a	10.48 a	3.90 b	3.85 b	0.244	<0.0001
	Abbreviations: CTL = control; BES = 3 μM 2-bromoethanesulfonic sodium; PHL = 36 mM phloroglucinol; BES+PHL = 3 μM 2-
	bromoethanesulfonic sodium + 36 mM phloroglucinol.

a

Table 6

 6 Alpha diversity metrics of ruminal bacteria from goat inocula experiment.

	Treatment
	Item

Table S6

 S6 Bacterial abundance from cow inocula experiment.

	Monoglobaceae	0.09a	0.07ab	0.00b	0.00b	0.021	0.0047
	MVP-15	0.02a	0.02a	0.00b	0.00b	0.006	0.0051
	Streptococcaceae	11.84a	10.96ab	5.46ab	4.87b	2.077	0.0056
	Bacteroidales_UCG-001	0.07ab	0.08a	0.00b	0.00b	0.022	0.006
	Enterococcaceae	Treatment (Relative abundance, %) 0.05ab 0.06a 0.00b	0.00b	0.02	0.0067
	Bacteria family					SEM	P-value
	Candidatus_Kerfeldbacteria	CTL 0.00b	BES 0.02a	PHL 0.00b	BES+PHL 0.00b	0.005	0.0075
	Bacteroidales_BS11_gut_group Synergistaceae	0.15a 0.20ab	0.00b 0.22a	0.00b 0.00b	0.00b 0.00b	0.014 0.068	<0.0001 0.01
	p-251-o5 Erysipelotrichaceae	0.51a 0.52ab	0.77a 0.41b	0.00b 0.95a	0.00b 0.64ab	0.067 0.139	<0.0001 0.0228
	Eggerthellaceae Tannerellaceae	0.24b 0.00	0.22b 0.04	0.78a 0.00	0.74a 0.00	0.087 0.011	<0.0001 0.0239
	Christensenellaceae Clostridiaceae	0.76a 0.13	0.47a 0.36	0.00b 0.00	0.00b 0.00	0.093 0.108	<0.0001 0.0341
	Acidaminococcaceae Clostridia_UCG-014	2.61a 0.25	2.38a 0.26	0.13b 0.00	0.10b 0.00	0.110 0.100	<0.0001 0.0367
	uncultured WCHB1-41	0.47a 0.04	0.53a 0.02	0.00b 0.00	0.00b 0.00	0.035 0.011	<0.0001 0.0544
	Spirochaetaceae Sutterellaceae	4.33a 0.30	5.45a 0.29	0.00b 0.26	0.00b 0.09	0.703 0.074	<0.0001 0.0614
	Fibrobacteraceae Saccharimonadaceae	1.36a 0.05	1.88a 0.05	0.00b 0.00	0.00b 0.00	0.282 0.023	<0.0001 0.0664
	UCG-010 UCG-011	0.30a 0.06	0.11b 0.00	0.00c 0.00	0.00c 0.00	0.017 0.020	<0.0001 0.0675
	Bacteroidales_RF16_group RF39	0.30a 0.02	0.29a 0.02	0.00b 0.00	0.00b 0.00	0.030 0.009	<0.0001 0.0678
	Bifidobacteriaceae Gastranaerophilales	0.19b 0.02	0.26b 0.00	4.65a 0.00	4.16a 0.00	0.475 0.007	<0.0001 0.0751
	Succinivibrionaceae Pirellulaceae	10.90a 0.02	11.26a 0.00	0.16b 0.00	0.18b 0.00	1.244 0.007	<0.0001 0.0773
	Selenomonadaceae Anaerolineaceae	1.72a 0.01	1.92a 0.00	0.14b 0.00	0.13b 0.00	0.141 0.004	<0.0001 0.0835
	Desulfovibrionaceae uncultured	0.18a 0.01	0.19a 0.00	0.00b 0.00	0.00b 0.00	0.020 0.029	<0.0001 0.088
	Rikenellaceae uncultured	13.51a 0.13	13.54a 0.08	0.45b 0.07	0.23b 0.05	0.699 0.031	<0.0001 0.1034
	Bacteroidales Order Izemoplasmataceae	0.14a 0.00	0.14a 0.01	0.00b 0.00	0.00b 0.00	0.015 0.004	<0.0001 0.1166
	Oscillospiraceae Fusobacteriaceae	1.18a 0.03	0.95a 0.02	0.00b 0.00	0.00b 0.00	0.119 0.013	<0.0001 0.1624
	Acholeplasmataceae Muribaculaceae	1.12b 0.01	1.36b 0.02	5.65a 0.00	5.33a 0.00	0.762 0.010	<0.0001 0.2108
	Hungateiclostridiaceae Erysipelatoclostridiaceae	0.150a 7.71	0.111a 7.94	0.00b 8.94	0.00b 10.71	0.019 1.898	<0.0001 0.4414
	F082 Clostridia_vadinBB60_group	3.63a 0.28	1.36b 0.28	0.00c 0.40	0.00c 0.17	0.146 0.141	<0.0001 0.4674
	Lachnospiraceae Anaerovoracaceae	12.56b 0.42	11.82b 0.33	18.51a 0.49	21.20a 0.86	0.998 0.309	<0.0001 0.6017
	Bacteroidaceae	0.12a	0.17a	0.00b	0.00b	0.029	<0.0001
	Abbreviations: CTL = control; BES = 3 μM 2-bromoethanesulfonic sodium; PHL = 36 mM phloroglucinol; BES+PHL = 3 μM 2-
	Prevotellaceae	10.62b	12.43b	28.50a	29.54a	0.860	<0.0001
	Eubacteriaceae bromoethanesulfonic sodium + 36 mM phloroglucinol; AT = 2% A. taxiformis; AT+PHL1 = 2% A. taxiformis + 6 mM 0.08a 0.05a 0.00b 0.00b 0.011 <0.0001
	Ruminococcaceae phloroglucinol; PHL2 = 2% A. taxiformis + 36 mM phloroglucinol; AT+PYR1 = 2% A. taxiformis + 6 mM pyrogallol; AT+PYR2 1.50a 1.19a 0.01b 0.02b 0.180 <0.0001
	Lactobacillaceae = 2% A. taxiformis + 36 mM pyrogallol. 0.02b	0.00b	10.18a	8.82a	1.43	<0.0001
	Atopobiaceae	1.30b	1.62b	3.17a	2.66a	0.368	0.0001
	Bacteroidia Class	0.01b	0.05a	0.00b	0.00b	0.009	0.001
	Izemoplasmatales	0.04a	0.00b	0.00b	0.00b	0.007	0.0013
	Veillonellaceae	7.16b	7.41b	11.10a	9.51ab	0.736	0.0015
	Butyricicoccaceae	0.45a	0.42a	0.00b	0.00b	0.116	0.0016
	Enterobacteriaceae	0.04ab	0.04a	0.00b	0.00b	0.012	0.0032

Table S7

 S7 Bacterial abundance from goat inocula experiment.

	Acholeplasmataceae	4.96a b	2.18b	2.03b	2.76b	3.44b	9.70a	1.16	0.002 5
	Bacteria family Veillonellaceae Erysipelatoclostridiaceae Bacteroidetes_BD2-2 Rikenellaceae Bifidobacteriaceae Desulfovibrionaceae [Eubacterium]_coprostanoligenes _group Prevotellaceae Sutterellaceae Acidaminococcaceae F082 Ruminococcaceae vadinBE97 Bradymonadales Pseudomonadaceae Streptococcaceae Marinifilaceae Atopobiaceae Bacteroidales Order Spirochaetaceae uncultured Succinivibrionaceae Saccharimonadaceae RF39 Bacteroidales_BS11_gut_group Actinomycetaceae	Treatment (Relative abundance, %) CTL SW SW+PH L1 SW+PH L2 2.80b 2.27c 3.63ab 7.53ab 1.38b 0.74b 1.12b 3.98a 0.27a b 0.53a 0.26ab 0.00b 5.58a 7.46a 7.52a 0.62b 0.28b 0.29b 0.28b 1.25b 0.22a 0.10b cd 0.14ab 0.02cd 0.49a 0.22a b 0.10ab 0.00b 10.60 b 13.90 b 14.88b 32.04a 0.04b 0.06b 0.03b 1.88a 0.82a 0.73a 0.76a 0.03a 2.94a 0.78a b 1.60ab 0.04b 0.75a 0.32b c 0.33bc 0.02c 0.14a 0.00b 0.00b 0.00b 0.39a 0.03b 0.02b 0.00b 0.00 0.00 0.00 0.02 5.74b 6.95b 7.71b 14.04b 0.01a b 0.04a 0.01ab 0.00b 0.24c 0.27c 0.27c 3.25a 1.09 1.78 1.54 0.00 24.84 a 22.35 a 20.80a 4.99b 0.26a 0.23a 0.18ab 0.14ab 14.20 a 13.58 a 10.23a 0.15b 0.91a 0.42a b 0.42ab 0.00b 0.34a 0.28a 0.24a 0.03b 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00	SW+PY R1 5.07ab 0.60b 0.28ab 6.18a 0.28b 0.13ab 0.43ab 15.64b 0.13b 0.49a 1.71ab 0.53ab 0.01b 0.02b 0.00 10.85b 0.00b 0.64bc 0.30 21.01a 0.14ab 7.80ab 0.10ab 0.28a 0.01 0.00	7.98a SW+PY R2 1.70b 0.00b 0.78b 2.88a 0.00d 0.00b 17.39b 0.00b 2.08b 0.11b 0.02c 0.00b 0.00b 0.02 27.70a 0.00b 0.86b 0.00 1.29b 0.02b 0.19b 0.00b 0.01b 0.03 0.04	SEM 0.976 6 0.316 0.082 0.542 0.552 0.032 0.111 1.579 0.339 0.223 0.507 0.087 0.026 0.036 0.005 2.11 0.006 0.281 0.469 7 1.728 0.055 1.815 0.194 0.059 0.043 0.01	P-value 0.002 7 0.003 2 <0.00 01 0.004 4 <0.00 01 0.005 6 <0.00 01 0.007 6 <0.00 01 0.008 3 <0.00 01 0.009 6 <0.00 01 0.010 3 <0.00 01 0.012 1 <0.00 01 0.014 6 <0.00 01 0.016 1 <0.00 01 0.017 8 <0.00 01 0.035 2 <0.00 01 0.046
	Bacteroidales_RF16_group Anaerovoracaceae	0.33b c 0.10	0.85a b 0.04	0.83ab 0.08	0.00c 0.13	1.24a 0.06	0.04c 0.00	0.154 0.028	<0.00 01 0.055 8
	Bacteroidales_UCG-001 Erysipelotrichaceae	0.71a 0.06	0.42b 0.12	0.28b 0.17	0.00c 1.08	0.22bc 0.30	0.00c 2.57	0.057 0.207	<0.00 01 0.057 0
	WCHB1-41 Clostridia_vadinBB60_group	0.80a 1.55	0.21b c 1.20	0.38b 1.24	0.00c 0.00	0.08c 1.61	0.00c 0.12	0.07 0.256	<0.00 01 0.066 1
	Eubacteriaceae Muribaculaceae	0.00b 0.14	0.00b 0.10	0.02b 0.13	0.23a 0.17	0.01b 0.12	0.04b 0.09	0.025 0.059	<0.00 01 0.084 4
	Lachnospiraceae Bacteroidia Class	6.42b 0.12	5.66b 0.21	7.58b 0.16	22.64a 0.00	7.93b 0.00	18.33a 0.00	1.384 0.074	<0.00 01 0.102 7
	Christensenellaceae Hungateiclostridiaceae	0.54a c 0.01	0.59a 0.00	0.64a 0.01	0.00b 0.00	0.67a 0.03	0.13bc 0.00	0.104 5 0.001	0.000 1 0.106 6
	uncultured Pedosphaeraceae	0.33a bc 0.05	0.44a bc 0.03	0.66a 0.02	0.30bc 0.00	0.44ab 0.01	0.02c 0.00	0.079 0.017 0.1119 0.000 5
	UCG-010 uncultured Lactobacillaceae Selenomonadaceae p-251-o5 Weeksellaceae Oscillospiraceae Elusimicrobiaceae Izemoplasmatales Synergistaceae Defluviitaleaceae MVP-15	0.18a 0.17 0.14b 0.82 3.92a 0.00 1.52a 0.10 0.34a 0.09 0.00b 0.02	0.08a b 0.07 0.13b 0.73 6.73a 0.01 0.94a b 0.01 0.02b 0.06 0.01b 0.00	0.07ab 0.04 0.16b 0.84 6.91a 0.02 0.74ab 0.00 0.05b 0.06 0.00b 0.00	0.00b 0.00 1.56ab 0.94 0.00b 0.00 0.02b 0.00 0.00b 0.00 0.00b 0.00	0.08ab 0.14 0.18b 0.90 4.74a 0.00 0.62ab 0.00 0.02b 0.06 0.02b 0.00	0.00b 0.01 3.33a 1.60 0.01b 0.00 0.14b 0.01 0.00b 0.00 0.27a 0.00	0.000 0.048 0.1131 0.026 6 0.454 0.000 0.132 0.284 0 6 1.202 0.000 0.132 0.005 0 8 0.242 0.000 0.133 0.028 6 8 0.049 0.000 0.151 0.031 7 9 0.04 0.0011 0.162 0.007 5
	Puniceicoccaceae 0319-6G20	0.02a b 0.02	0.03a b 0.00	0.00b 0.00	0.00b 0.00	0.05a 0.00	0.00b 0.00	0.009 0.005	0.001 6 0.223 2
	Endomicrobiaceae Mitochondria	0.19a 0.01	0.04b 0.01	0.08ab 0.02	0.00b 0.06	0.01b 0.01	0.00b 0.08	0.033 0.028	0.001 6 0.235 0
	Fibrobacteraceae Izemoplasmataceae	1.64a b 0.02	5.50a 0.00	4.58ab 0.00	0.00b 0.00	4.23ab 0.00	0.00b 0.00	1.031 0.007	0.001 9 0.279 9

Table 7

 7 Ingredients and chemical composition of the experimental diets.

	Mixed forage
	Ingredient of forage, % of DM
	Silage	46	46	46	46
	Hay	43	43	43	43
	Beet pulp	10	10	10	10
	Premix 1	1	1	1	1
	Chemical composition of the
	Forage, % of DM
	OM	89.5	89.5	89.5	89.5
	CP	11.1	11.1	11.1	11.1
	NDF	59.6	59.6	59.6	59.6
	ADF	32.1	32.1	32.1	32.1
	GE, MJ/kg of DM	17.8	17.8	17.8	17.8
	Pellet	CON pellet	3% AT pellet	6 GA pellet
	Ingredient of concentrate, % of DM
	Corn	20	22	21	-
	Wheat	19	19	19	-
	Barley	15	15	15	-
	Wheat bran	11	10	9	-
	Sunflower cake	18	14	14	-
	Rapeseed	12	12	11	-
	Calcium carbonate	1	1	1	-
	Premixer	1.5	1.5	1.5	-
	Salt	0.5	0.5	0.5	-
	A. armata	0	3	0	-
	Gallic acid	0	0	6	-
	Molasses	2	2	2	-
	Chemical composition of the
	Concentrate, % of DM
	OM	92.8	92.4	93.2	-
	CP	19.1	19.0	16.7	-
	NDF	21.6	21.6	20.0	-
	ADF	10.1	9.3	8.7	-
	Starch	31.5	31.9	34.4	-
	GE, MJ/kg of DM	17.8	17.6	17.6	-

Table 8

 8 Effects of A. armata, gallic acid, and their combination on enteric gas emissions in lactating dairy cows.

	Item	CON	Treatment AT GA	MIX	SEM	Asparagopsis	P-Value 1 Gallic	AsparagopsisxGallic
	CH4, g/d	432	375	421	340	21.4	0.0121	0.4333	0.3152
	CH4, g/DMI	24.0	17.9	21.3	15.9	1.34	0.0010	0.1389	0.7290
	CH4, g/MY	24.0	20.1	22.8	17.1	1.49	0.0068	0.1898	0.5528
	CH4, g/ECM	27.9	23.6	27.0	21.8	1.40	0.0059	0.4846	0.5006
	H2, g/d	1.29	4.86	1.17	5.27	0.442	<0.0001	0.7685	0.3947
	H2, g/kg DMI	0.07	0.22	0.06	0.26	0.021	<0.0001	0.6974	0.0851
	H2, g/kg MY	0.08	0.25	0.06	0.29	0.024	0.0005	0.3625	<0.0001
	H2, g/kg ECM	0.08	0.30	0.03	0.33	0.027	0.0012	0.6750	0.4061
	CO2, g/d	11425	10663	11210	11276	183.2	0.0681	0.2970	0.0388
	Abbreviations: CON = basal diet; AT = 0.25% A. armata in the basal diet; GA = 0.8% gallic acid in the basal diet; MIX =
	0.25% A. armata and 0.8% gallic acid in the basal diet; DMI = dry matter intake; MY = milk yield; ECM = energy corrected
	milk yield.

Table 9

 9 Effect of A. armata, gallic acid, and their combination on rumen fermentation in lactating dairy cows. Asparagopsis represents the main effect of A. armata (CON and GA versus AT and MIX); Gallic represents the main effect of gallic acid (CON and AT versus GA and MIX); AsparagopsisxGallic represents the interaction between main effects of A.

	Item	CON	Treatment AT GA	MIX	SEM	Asparagopsis	P-Value 1 Gallic AsparagopsisxGallic
	pH	6.81	6.88	6.80	6.86	0.100	0.7755	0.4958	0.9088
	NH3, 100 mg/dL	2.26	2.92	3.19	3.42	0.667	0.5331	0.2118	0.6813
	Total VFA, mmol/L	157.88 140.59 152.01 136.88 7.219	0.0259	0.3331	0.8355
	VFA composition,
	mol/100 mol
	Acetate	69.70	65.28	69.29	63.05	1.40	0.0010	0.3434	0.5163
	Propionate	17.73	19.20	17.77	21.34	0.779	0.0163	0.2029	0.2114
	Butyrate	10.09	11.94	10.48	11.77	0.469	0.0018	0.7947	0.4808
	Iso butyrate	0.61	0.78	0.60	0.74	0.042	0.0072	0.4719	0.6081
	Valerate	0.79	1.11	0.78	1.17	0.154	0.0314	0.8747	0.8118
	Iso valerate	0.61	1.07	0.64	1.73	0.228	0.0046	0.1739	0.1728
	Caproate	0.29	0.65	0.27	0.49	0.091	0.0026	0.2933	0.4244
	A/P	3.94	3.48	3.92	3.02	0.161	0.0003	0.1330	0.1646
	Abbreviations: CON = control diet; AT = 0.25% A. armata in the basal diet; GA = 0.8% gallic acid in the basal diet; MIX =
	0.25% A. armata and 0.8% gallic acid in the basal diet; A/P = acetate/propionate.

1 armata and gallic acid.

Table 10

 10 Effect of A. armata, gallic acid, and their combination on protozoa counting in lactating dairy cows.

	Item	CON	Treatment AT GA	MIX	SEM	Asparagopsis	P-Value 1 Gallic AsparagopsisxGallic
	Total protozoa, log10 / mL	5.01	4.99 5.03 5.22 0.078	0.2700	0.1263	0.2029
	Entodiniomorphs, log10 / mL
	Small (< 100 μm)	4.97	4.93 4.97 5.16 0.080	0.3374	0.1468	0.1620
	Large (> 100 μm)	3.64	4.25 3.92 3.86 0.210	0.1395	0.7604	0.0933
	Holotrichs, log10 / mL
	Dasytricha (< 100 μm)	3.11	3.26 2.86 3.49 0.170	0.0317	0.9361	0.1307
	Isotricha (> 100 μm)	3.08	3.14 3.04 3.24 0.182	0.4772	0.8874	0.6986

Table 11

 11 Effects of A. armata, gallic acid, and their combination on lactating dairy cows' performance.

	Item	CON	Treatment AT GA	MIX	SEM	P-Value 1 Asparagopsis Gallic AsparagopsisxGallic
	Forage intake, kg/d	16.4	14.6 16.4 15.2	0.51	0.0252	0.5927	0.6284
	Concentrate intake, kg/d	5.7	5.0	5.6	5.0	0.19	0.0067	0.9624	0.9600
	Total feed intake, kg/d	22.0	19.7 22.0 20.3	0.52	0.0175	0.4534	0.4528
	Milk yield, kg/d	20.7	17.0 20.8 18.5	0.33	<0.0001	0.0302	0.0156
	Feed efficiency 2 , kg/kg	0.92	0.95 0.98 0.93 0.028	0.6736	0.5074	0.2127
	Milk fat, %	3.64	3.48 3.62 3.35 0.077	0.0116	0.3357	0.4461
	Milk fat, kg/d	0.75	0.58 0.76 0.62 0.020	<0.0001	0.2989	0.5518
	Milk true protein, %	3.09	2.90 3.08 2.97 0.045	0.0007	0.6395	0.1575
	Milk true protein, kg/d	0.64	0.49 0.64 0.55 0.015	<0.0001	0.1963	0.0398
	Lactose, %	4.81	4.81 4.73 4.78 0.078	0.7595	0.5212	0.7755
	Lactose, kg/d	1.00	0.82 0.99 0.89 0.024	<0.0001	0.3162	0.0879
	ECM, kg/d	16.0	15.6 15.9 15.5	0.13	0.0025	0.5226	0.7177
	ECM feed efficiency 3 , kg/kg	0.75	0.82 0.73 0.77 0.026	0.0718	0.1959	0.4352
	MUN, mg/L	70	76	67	62	3.8	0.8918	0.0437	0.1716
	SCC	4.94	5.18 4.82 5.10 0.147	0.1253	0.4026	0.7848
	BW, kg	652	630	656	640	7.2	0.0187	0.3809	0.6636
	BCS	1.62	1.57 1.63 1.62 0.043	0.4378	0.6191	0.6093
	Abbreviations: CON = basal diet; AT = 0.25% A. armata in the basal diet; GA = 0.8% gallic acid in the basal diet; MIX =
	0.25% A. armata and 0.8% gallic acid in the basal diet; ECM = energy corrected milk yield; MUN = milk urea nitrogen; SCC =
	somatic cell count; BW = body weight; BCS = body condition score.

Table 12

 12 Effect of A. armata, gallic acid, and their combination on blood biochemistry in lactating dairy cows.

	Item	Con	Treatment AT GA	MIX	SEM	Asparagopsis	P-Value 1 Gallic	AsparagopsisxGallic
	Glucose, g/L	0.50	0.50	0.39	0.52	0.039	0.1092	0.2637	0.1008
	NEFA, mmol/L	0.10	0.08	0.04	0.05	0.030	0.9674	0.1489	0.6438
	B-OH, mmol/L	0.45	0.43	0.38	0.48	0.032	0.3028	0.8951	0.0640
	Urea, g/L	0.09	0.10	0.08	0.10	0.012	0.1573	0.6190	0.8121
	AST, UI/L	66.2	53.7	49.0	54.4	6.62	0.4157	0.2637	0.0429
	GGT, UI/L	21.3	18.0	15.3	16.8	2.26	0.6293	0.0288	0.1542
	ALP, UI/L	59.9	47.9	38.3	41.3	5.38	0.2105	0.0008	0.0425
	ALT, UI/L	24.5	16.4	17.7	17.8	2.56	0.0510	0.4431	0.0302
	Abbreviations: CON = control diet; AT = 0.25% A. armata in the basal diet; GA = 0.8% gallic acid in the basal diet; MIX =
	0.25% A. armata and 0.8% gallic acid in the basal diet; NEFA = non-esterified fatty acids; B-OH = beta-hydroxybutyrate; AST
	= aspartate transferase; GGT = gamma-glutamyl transferase; ALP = alkaline phosphatase; ALT = alanine transaminase.

  . Additionally, A. Armata led to an increase in isobutyrate, isovalerate, and caproate proportion, although only the increased proportion of isovalerate was reported (canola oil steeped with A. Armata with and without A. Armata biomass) (Alvarez-Hess et al., 2023).

  , and 14 days in the present study. Additionally, A. taxiformis was found to affect cows' eating behaviors. Cows in the A. taxiformis group exhibited sorting behavior and showed increased rumination time, chewing time, and chew counts, as reported by[START_REF] Nyløy | Inclusion of Red Macroalgae (Asparagopsis taxiformis) in Dairy Cow Diets Modulates Feed Intake, Chewing Activity and Estimated Saliva Secretion[END_REF]. Thus, it is likely that other factors contribute to the decrease in DMI observed with Asparagopsis. For example, halogenated compounds, primarily bromoform, present in Asparagopsis could be associated with the reduced DMI as these compounds are volatile and have a strong flavor. Studies have reported that canola oil containing bromoform decreased concentrate intake compared to the canola oil group, and there was no difference in concentrate intake between canola oil containing bromoform and canola oil containing both bromoform and A.

armata biomass treatments

[START_REF] Alvarez-Hess | Twice daily feeding of canola oil steeped with Asparagopsis armata reduced methane emissions of lactating dairy cows[END_REF]

. Notably, forage, concentrate, and total feed intake were not affected by gallic acid, which was consistent with previous findings

(Aboagye et al., 2019)

.

The milk yield in the AT group showed a decrease, likely due to the lower feed intake observed in this group. This reduction in milk yield, accompanied by a decrease in milk fat and milk true protein concentrations, resulted in a decrease in milk fat, milk true protein, and milk lactose production in the AT group. These findings align with the study conducted by

Stefenoni et al. (2021)

using a 0.5% A. taxiformis. However,

Stefenoni et al. (2021)

did not observe any significant effects on milk fat and milk true protein concentrations, although they reported a decrease in milk lactose concentration in the 0.5% A. taxiformis group. Similar results were reported by

[START_REF] Alvarez-Hess | Twice daily feeding of canola oil steeped with Asparagopsis armata reduced methane emissions of lactating dairy cows[END_REF]

, who also observed a decrease in milk component production with A. armata supplementation.

o

  Ph.D. degree in Microbiology, UMR Herbivores INRAE and Université Clermont Auvergne, 2023. o Master degree in Animal Nutrition and feed Science, Chinese Academy of Agricultural Sciences, 2019. o Bachelor degree in Animal Nutrition and feed Science, South China Agricultural University, 2016.

ACADEMIC EXPERIENCES

o Visiting student in Pro. Chris Creevey's lab at Queen's University Belfast (December 2022 to April 2023).

Control: substrate alone with no phenolic compound or formic acid added.

Dunnett-Hsu was used to adjust P-value. * Indicates P < 0.05 compared to control containing substrate alone and no phenolic compound added.

Substrate alone in the first column (mean ± SE) is provided for information.

Dunnett-Hsu was used to adjust P-value. * Indicates P < 0.05, compared to AT containing substrate but no phenolic compound added.

Control: Substrate alone, no chemical compound added.a,b,c Values within a row with different superscripts differ significantly at P < 0.05.

Asparagopsis armata, red seaweed, is similar to A.taxiformis. In this trial, we used Asparagopsis armata as it was the only available variety in our provider.

th International Gut Microbiology Symposium 2021

ACKNOWLEDGMENTS

Firstly, I would like to thank my supervisors, Dr. Diego MORGAVI and Dr. Milka POPOVA for their supervision, patience, and chances provided to me. I would like to thank my Ph.D. committee members, Dr. Evelyne FORANO, Dr. Cecile MARTIN, Dr.

Rafael MUNOZ-TAMAYO, and Dr. Alejandro BELANCHE. Your advice for my experiment

Acknowledgements

The authors wish to thank Florence Fournier and personnel at the Herbipole for animal care, and Dominique Graviou, Agnès Cornu, Angélique Torrent, Frederic Anglard, and Aline Le Morvan for laboratory technical support.

Financial support statement

This work was supported by the EU Horizon 2020 research and innovation program under grant agreement No 818368 (MASTER). RH was supported by the China Scholarship Council. AB has a Ramón y Cajal Research Contract (RYC 2019-027764-I) funded by the Spanish Research Agency (AEI: 10.13039/501100011033).

Data and model availability statement

The raw data generated for this study are available at https://doi.org/10.57745/H3QJTU.

CHAPTER 2

Evaluating the effect of phenolic compounds as hydrogen acceptors when ruminal methanogenesis is inhibited in vitro-Part 1. Dairy cows

Abstract

Some antimethanogenic feed additives for ruminants promote rumen dihydrogen (H2) accumulation potentially affecting the optimal fermentation of diets. We hypothesized that combining a H2 acceptor with a methanogenesis inhibitor can decrease rumen H2 build-up and improve the production of metabolites that can be useful for the host ruminant. We performed three in vitro incubation experiments using rumen fluid from lactating Holstein cows: Experiment 1 examined the effect of phenolic compounds (phenol, catechol, resorcinol, hydroquinone, pyrogallol, phloroglucinol, and gallic acid) at 0, 2, 4, and 6 mM on ruminal fermentation for 24 h; Experiment 2 examined the combined effect of each phenolic compound from Experiment 1 at 6 mM with two different methanogenesis inhibitors (A. taxiformis or 2-bromoethanesulfonate (BES)) for 24 h incubation; Experiment 3 examined the effect of a selected phenolic compound, phloroglucinol, with or without BES over a longer term using sequential incubations for seven days. Results from Experiment 1 showed that phenolic compounds, independently of the dose, did not negatively affect rumen fermentation. Whereas, results from Experiment 2 showed that phenolic compounds did not decrease H2 accumulation or modify CH4 production when methanogenesis was decreased by up to 75% by inhibitors.

In experiment 3, after three sequential incubations, phloroglucinol combined with BES decreased H2 accumulation by 72% and further inhibited CH4 production, compared to BES alone. Interestingly, supplementation with phloroglucinol (alone or in combination with the CH4 inhibitor) decreased CH4 production by 99% and the abundance of methanogenic archaea, with just a nominal increase in H2 accumulation. negligible in the substrate-only group, whereas it was readily detected when CH4 production was inhibited by 2.5% AT. Table 2 shows that none of the phenolic compounds decreased H2 accumulation or CH4 production. In contrast, formic acid increased (P = 0.016) H2 accumulation. Phloroglucinol (P = 0.003), gallic acid (P = 0.004), and formic acid (P = 0.010) increased TGP by ~8% after 24 h incubation. The addition of phloroglucinol decreased (P = 0.005) metabolic hydrogen recovery, whereas it increased (P = 0.006) total VFA concentration by 18%, mainly due to a 41% increase (P = 0.007) in acetate proportion. Similarly, with phloroglucinol, gallic acid increased (P = 0.050) acetate proportion by 23%. Most phenolic compounds had no effect on ammonia concentration except hydroquinone and phloroglucinol, which decreased (P = 0.018 and P = 0.047, respectively) ammonia concentration by 32% and 26%, respectively.

Author ORCIDs

Declaration of interest

None.

CHAPTER 3

Phenolic compounds increased phenolic utilization bacteria abundance when methanogenesis was inhibited in vitro

2% A. taxiformis + 36 mM pyrogallol (AT+PYR2). At the end of the fourth incubation, 1 mL of incubation fluid was collected, centrifuged at 16 000 g for 15 min at 4 °C, and the supernatant was discarded. The pellet was stored at -20 °C until DNA extraction.

Amplicon sequencing

Microbial DNA was extracted using the DNeasy PowerSoil Pro Kit (Qiagen, Germany) following the manufacturer's instructions. The rumen fluid DNA was submitted to Spanish National Research Council for DNA library preparation, which involved amplification of the V3-V4 hypervariable region of the 16S rRNA gene using Fluidigm primers pairs Miseq_F and Miseq_R targeting both archaea and bacteria, as previously described [START_REF] Palma-Hidalgo | Multi-Omics Study of The Salivary Modulation of The Rumen Microbiome[END_REF]. The resulting amplicons were sequenced on an Illumina MiSeq platform using a MiSeq 300-cycle sequencing kit. Downstream processing was performed using QIIME 2 (Bolyen et al., 2019). Specifically, demultiplexing was performed using Qiime demux emp-paired plugin; while denoising, quality control, and amplicon sequence variant (ASV) generation were performed using the DATA2 plugin. Finally, representative sequences from all ASVs were aligned against SILVA 138.1.

Statistical analysis

Alpha diversity and relative abundance of the rumen bacteria of ASVs were analyzed by the GLMMIX process considering treatment as a fixed effect, animal as a random effect, and P-value was adjusted by Bonferroni statement. Beta diversity was analyzed by R (Version R 4.2.2) Phyloseq package, and performed permanova multiple reducing equivalents compared to acetate production. This agrees with our previous findings of phloroglucinol supplementation enhanced butyrate production (Chapter 2). Supplementation with jabuticaba peel, which has a high concentration of total phenolic compounds (8220 mg/100g), significantly increased the abundance of Eggerthellaceae and Muribaculaceae in the gut [START_REF] Loubet Filho | Gut microbiota modulation by jabuticaba peel and its effect on glucose metabolism via inflammatory signaling[END_REF].

Bifidobacteriaceae abundance increased threefold in a high concentration of phenolic compound group [START_REF] Nissen | Roasting and frying modulate the phenolic profile of dark purple eggplant and differently change the colon microbiota and phenolic metabolites after in vitro digestion and fermentation in a gut model[END_REF]. Flavobacterium, from the class Bacterioidia, has been shown to efficiently degrade phenol (Wirth et al., 2015). However, little information is available about the functions of RF39, and Acholeplasmataceae as these bacteria they are either uncultured or their metabolic activities have not been well-established (Wang et al., 2020[START_REF] Casar | Rock-hosted subsurface biofilms: mineral selectivity drives hotspots for intraterrestrial life[END_REF]. Table S6 presents the results of the multiple comparisons of the bacterial abundance between the four groups.

Whereas phloroglucinol supplementation significantly decreased the abundance of F082, Spirochaetaceae, Oscillospiraceae, p-251-o5, Bacteroidales RF16 group, Fibrobacteraceae, Christensenellaceae, unclassified Ruminococcaceae UCG-010, Ruminococcaceae, and Hungateiclostridiaceae. Similar results were reported by Sarwono et al. (2019a), who found that 10 mM phloroglucinol decreased the abundance of Ruminococcus flaveciens and Fibrobacter succinogenes when using a high forage ratio as a substrate. There are two possible reasons for the observed decrease in abundance of these bacteria with high phloroglucinol concentration.

High concentration of phloroglucinol led to massive increase in total VFA production (Romero et al., 2023; Chapter 2), which likely resulted in a low pH value. However, some Values within a row with different superscripts differ significantly at P < 0.05.

CHAPTER 4

Gallic Acid alleviates the negative effect of A. armata on milk yield without affecting methanogenesis inhibition in dairy cows

2 Material and Methods

Animals, Experimental Design, and Diets

The study involved 28 multiparous Holstein cows with an average body weight of 642  59 kg and daily milk production of 19  2.5 kg. The experiment used a randomized complete block design with three periods: a covariate period of 6 weeks, an adaptation period of 2 weeks, and an experimental period of 3 weeks. During the covariate period, dry matter intake (DMI), milk yield, and methane production were recorded and these data were used for the blocking. The cows were blocked into 7 blocks with 4 animals each, based on parity, calving date, DMI, milk yield, and methane production during the covariate period. Within each block, cows were randomly assigned to one of the four treatments: CON (Control, basal diet), AT (0.25% A. armata on a DM basis), GA (0.8% gallic acid on a DM basis), and MIX (0.25% A. armata + 0.8% gallic acid on a DM basis).

A partial mixed ration feeding strategy was used, as it is common in European gradually increased to 0.5% and the gallic acid inclusion level gradually increased to 0.8%. However, the concentrate intake of 3 cows in the AT group and 4 cows in the MIX group sharply decreased in the second week of the adaption period (week 8). Therefore, the A. armata inclusion level was adjusted to 0.25% in the AT and MIX groups for the trial period. The cows were milked twice daily at 07h30 and 16h30.

at -20 °C for bromoform analysis. We sent these samples to Bigelow Laboratory for Ocean Sciences (East Boothbay, USA) for bromoform analysis by GC/MS (QP2010 Ultra, Shimadzu), following the method described by Paul et al. (2006).

Gas measurement

We used two Greenfeed systems (C-Lock Inc., Rapid City, SD) to measure methane, dihydrogen, and carbon dioxide production of cows. The Greenfeed systems were installed in the stall, and cows had free access to the system during the experiment. The Greenfeed system dispensed 4 drops of pellets to each visiting cow, with 40 g of pellet in each drop and 45 s intervals between adjacent drops. Each cow was allowed up to 6 visits per day, with at least 4 h between adjacent visits. Pellet consumption from the Greenfeed system was included in the calculation of DMI.

Before the experiment, cows were trained to use the Greenfeed system for two weeks. The Greenfeed system was calibrated once a day by injecting a calibration gas mixture with certificated concentrations of methane and carbon dioxide. Additionally, the carbon dioxide recovery rate of the system was measured once a month.

The raw gas emission data was processed by C-Lock, Inc. (Rapid City, USA)

following their established protocols. Methane, dihydrogen, and carbon dioxide emissions (g/day) were determined based on the concentrations of these gases, the airflow in the collection pipe, the concentration of these gases in the ambient air, the rate of air capture, and the air temperature. C-Lock was not informed of the treatment of each animal. We calculated methane production (g/d), methane yield (g/kg DMI), and methane used for metataxonomic and metagenomic analysis, while the rumen microbes total RNA samples were used for metatranscriptomic analysis. In this thesis, we only reported the preliminary results from the metataxonomic analysis as the sequencing data are currently under analyzing.

Blood samples were collected from the jugular vein of each animal on Monday in week 4 during the covariate period, and on Wednesday in week 11 during the experimental period. Blood (9 mL) were sampled into a heparinized (BD vacutainer, Plymouth, UK) and an EDTA vacutainer (BD vacutainer, Plymouth, UK), respectively.

After sampling, the heparinized and EDTA vacutainers were centrifuged at 3 000 g for 15 min at 4 °C. Plasma sample (1.2 mL) from the EDTA vacutainer was collected into a 2 mL Eppendorf tube. Then the tubes were cooled by liquid nitrogen immediately, and stored at -20 °C for subsequent analysis of urea, non-esterified fatty acids (NEFA), betahydroxybutyrate (BHB), and glucose using biochemical analyser (Arene 20XT, Thermo Scientific). Plasma samples (1.2 mL X 2) from the heparinized vacutainer were collected into two 2 mL Eppendorf tubes, respectively. Then the tubes were cooled by liquid nitrogen immediately. One sample was stored at -20 °C for subsequent analysis of aspartate aminotransferase (AST), alanine transaminase (ALT), gamma-glutamyl transferase (GGT), and alkaline phosphatase (ALP) using biochemical analyser (Arene 20XT, Thermo Scientific). The other sample was stored at -80 °C for metabolomic analysis.

To perform the metabolomic analysis, plasma samples were analysed by two analytical platforms using the MxP® Quant 500 kit (Biocrates, Innsbruck, Austria): Lipids increased by 9%, compared to AT group.

A. armata decreased milk fat concentration (P = 0.0116), milk fat production (P < 0.0001), milk true protein concentration (P = 0.0007), milk true protein production (P < 0.0001), and lactose production (P < 0.0001). However, gallic acid did not affect milk fat, milk true protein, and lactose concentration or production. Also, there was no interaction effect of A. armata and gallic acid on milk fat, milk true protein, and milk lactose concentration or production, except for milk true protein production (P = 0.0398). Milk true protein production increased by 12% in the MIX group, compared to AT group.

There was no effect on feed efficiency for A. armata or gallic acid, or their interaction, although ECM feed efficiency trended towards an increase (P = 0.0718) by A. armata.

There was no treatment effect or interaction effect on milk urea nitrogen concentration (MUN) or SCC. However, gallic acid decreased (P = 0.0437) MUN concentration. In the GA group, MUN concentration decreased by 4%, compared to the CON group. Milk from CON, AT, and MIX groups did not contain bromoform. The bromoform concentration in the 3% A. armata containing pellet was 0.312 mg/g DM at week 7, 0.240 mg/g DM at week 9, and 0.171 mg/g DM at week 11 (Figure 10).

Discussion

Methanogenesis inhibition in the rumen results in dihydrogen accumulation. If we can capture this excessive dihydrogen use feed additives and convert it into nutrients such as VFA for the host animal, we could potentially improve animal production. In our previous in vitro experiments (Romero et at., 2023; Chapter 2), we tested 7 selected phenolic compounds as hydrogen acceptors and found that gallic acid and phloroglucinol were the most promising candidates (Romero et at., 2023;Chapter 2). In this study, we tested gallic acid as a hydrogen acceptor when methanogenesis was inhibited by A.

armata in vivo. We chose gallic acid because it is the subunit of hydrolysable tannins which are present in common feedstuff, and it also in the feed additive list; A. armata is kinds of red seaweeds, which are potent methanogenesis inhibitors. We chose A. armata over A. taxiformis because our supplier was only providing A. armata at that time.

The AT group decreased methane yield by 25%, and increased dihydrogen emission (g/d) fourfold, compared to the CON group. These results suggest that A. armata is a promising model for inhibiting methanogenesis in dairy cows. Previous research has shown that the antimethanogenic activity of A. taxiformis was due to halogenated compounds, primarily bromoform (Machado et al., 2016). In this study, the concentration of bromoform in the A. armata was 15.5 mg/g DM, which is much higher than the concentration in reported in Asparagopsis by other researchers (Kinley et al., 2020;Roque et al., 2021). The high concentration of bromoform in A. armata likely accounts for the decrease methane yield by 25% observed in our study at a low inclusion level of enhancing milk production in dairy cows.

The in vitro findings showed that gallic acid and phloroglucinol were promising hydrogen acceptors, whereas the in vivo experiment did not yield the same conclusion. Gallic acid or phloroglucinol degradation using dihydrogen produces VFA and carbon dioxide by rumen microbes in pure culture (Krumholz et al., 1987) In the in vitro experiment, the results of gas emissions also suggested that phloroglucinol worked as hydrogen acceptor, while the results of gas emissions did not lead to the same conclusion for the in vivo experiment. Specifically, in the in vitro experiment, after adaptation, 36 mM phloroglucinol combined with BES decreased dihydrogen accumulation by 72%. This combination further decreased methane production, accompanied by a decrease in the abundance of methanogens in the sequential incubation. However, in the in vivo experiment, 0.8% gallic acid did not affect dihydrogen or methane emissions. Also, there were no interaction effects of gallic acid combined with A. armata on dihydrogen or methane emissions. The discrepancies observed between the in vitro and in vivo experiments could be attributed to the difference in the inclusion levels of phenolic compounds used in each study and the inherent variations between the two experimental methods.

In the in vitro experiment, the inclusion level of gallic acid was 6 mM, equivalent to 1.7% based on DM, while the in vivo experiment utilized gallic acid at a level of approximately 0.8% based on DM. From another perspective, 0.8% gallic acid inclusion level in vivo equivalent to 7 mM in the rumen fluid, assuming a total of 85 L of rumen volume and 15% dry matter content.