Francesca Romana Massacci

Mustapha Berri

Gaetan Lemonnier

Elodie Guettier

Fany Blanc

Deborah Jardet

Marie Noelle Rossignol

Marie-José Mercat

Joël Doré

Patricia Lepage

Claire Rogel-Gaillard

Jordi Estellé

Late weaning is associated with increased microbial diversity and Faecalibacterium prausnitzii abundance in the fecal microbiota of piglets

Keywords: piglet, gut microbiota, age, weaning, diversity, F. prausnitzii

Background

In pig production systems, weaning is a crucial period characterized by nutritional, environmental, and social stresses. Piglets transition from a milk-based diet to a solid, more complex plant-based diet, and their gut physiology must adapt accordingly. It is well established that piglets weaned later display improved health, better wean-to-finish growth performance, and lower mortality rates. The aim of this study was to evaluate the impact of weaning age on fecal microbiota diversity and composition in piglets. Forty-eight Large White piglets were divided into 4 groups of 12 animals that were weaned at different ages: 14 days (early weaning), 21 days (a common weaning age in intensive pig farming), 28 days (idem), and 42 days (late weaning). Microbiota composition was assessed in each group by sequencing the 16S rRNA gene using fecal samples taken on the day of weaning, 7 days later, and at 60 days of age.

Results

In each group, there were significant differences in fecal microbiota composition before and after weaning (p < 0.05), confirming that weaning can drastically change the gut microbiota. Microbiota diversity was positively correlated with weaning age: microbial alpha diversity and richness were higher in piglets weaned at 42 days of age both on the day of weaning and 7 days later. The abundance of Faecalibacterium prausnitzii operational taxonomic units (OTUs) was also higher in piglets weaned at 42 days of age.

Conclusions

Overall, these results show that late weaning increased gut microbiota diversity and the abundance of F. prausnitzii, a microorganism with positive effects in humans. Piglets might thus derive a competitive advantage from later weaning because they have more time to accumulate a higher diversity of potentially beneficial microbes prior to the stressful and risky weaning period.

ABSTRACT

In pig production systems, weaning is a crucial period characterized by nutritional, environmental and social stress. During this process, piglets are susceptible to diarrhoea and the gut ecosystem needs to adapt to dietary changes, from a milk-based diet to a solid and more complex cereal-based feed, and to environmental pathogen pressure. One of the most important etiological agent of the post-weaning diarrhoea (PWD) is the Enterotoxigenic Escherichia coli (ETEC) able to cause severe outcomes and considerable economic losses to farmers worldwide. A role of host genetics in infection appearance is well-established, the SNPs located on the Mucine 4 (MUC4) and Fucosyltransferase 1 (FUT1) genes being associated with the susceptibility to ETEC F4 and ETEC F18, respectively. To investigate aspects related to weaning diarrhoea, two studies have been performed. The aim of the first study was to evaluate the impact of weaning age on gut microbiota diversification in piglets comparing animals at different weaning ages. Forty-eight Large White piglets were divided into four groups of 12 animals weaned at 14 days old (early weaning), 21 or 28 days old (main weaning ages in pig intensive farming) and 42 days old (late weaning). In each group, faecal bacteria composition was assessed by sequencing the 16S rRNA gene of faecal DNA on the weaning day, 7 days post-weaning and at 60 days of age. Our results showed that late weaning increases the gut microbiota diversity including a higher abundance of Faecalibacterium prausnitzii, reported as beneficial in humans. Our results suggest than the pre-weaning gut microbiota composition conferred by a late weaning at 42 days of age could enhance gut health in piglets. This would provide a competitive advantage to piglets accumulating a higher diversity of potentially beneficial microbes prior to the stressful and risky weaning transition. The aim of the second study was to evaluate the effects of the hostgenotype and different routes of amoxicillin administration on the presence of diarrhoea and the microbiota composition, during a natural infection by multi-resistant ETEC strains in weaned piglets. For this purpose, seventy-one piglets were divided into three groups: two groups differing by amoxicillin administration routesparenteral (P) or oral (O) and a control group without antibiotics (C). Our results confirmed the MUC4 and FUT1 as host genetic markers for the susceptibility to ETEC infections. Moreover, our data highlighted that amoxicillin treatment may produce adverse outcomes on pig health in course of multi-resistant ETEC infection and this effect is stronger when the antibiotic is orally administered than parenterally. Both studies highlighted the importance of alternative control measures related to farm management in controlling weaning related diarrhoea. With a need to limit the use of antibiotics, selection of resistant genotypes, nextgeneration probiotics supplementation in feed, and correct procedures of weaning age, should be considered in farm management practices in order to preserve a balanced and stable gut microbiota and consequently reduce occurrence of diarrhoea at weaning.

RIASSUNTO

Lo svezzamento rappresenta un momento cruciale nell'allevamento suinicolo ed è caratterizzato da stress nutrizionale, ambientale e sociale. In questa fase, i suinetti risultano a maggior rischio di insorgenza di diarrea in quanto la microflora intestinale deve adattarsi ai cambiamenti alimentari legati al passaggio da una dieta a base lattea ad un alimento solido a base di cereali e più complesso e all'elevata pressione infettiva ambientale. Uno dei più importanti agenti eziologici responsabili della diarrea postsvezzamento (PWD) è Escherichia coli Enterotossigeno (ETEC) in grado di provocare gravi quadri clinici nonché ingenti perdite economiche per gli allevatori. Che ci sia una componente genetica nell'evoluzione di queste infezioni è stato ben definito attraverso l'individuazione degli SNP situati sui geni Mucine 4 (MUC4) e Fucosyltransferase 1 (FUT1) associati rispettivamente alla suscettibilità nei confronti di ETEC F4 e ETEC F18. Nella presente tesi sono illustrati due studi che hanno avuto l'obiettivo di approfondire alcuni aspetti legati alla comparsa di diarrea durante lo svezzamento. Lo scopo del primo studio è stato quello di valutare l'impatto dell'età di svezzamento sulla diversità del microbiota intestinale, confrontandone la composizione in suinetti svezzati a diverse età. Quarantotto suinetti di razza Large-White sono stati suddivisi in quattro gruppi da 12 soggetti, svezzati rispettivamente a 14 giorni di età (svezzamento precoce), a 21 o 28 giorni (età di svezzamento principale nell'allevamento intensivo) e a 42 giorni (svezzamento tardivo). In ogni gruppo è stata valutata la composizione batterica fecale il giorno dello svezzamento, 7 giorni post-svezzamento e a 60 giorni di età, sequenziando il gene 16S rRNA dal DNA batterico fecale. I risultati ottenuti hanno evidenziato come lo svezzamento tardivo aumenti il grado di diversificazione del microbiota intestinale, aumentando l'abbondanza di Faecalibacterium prausnitzii, già considerato benefico per l'uomo. Emerge, inoltre, come la composizione del microbiota intestinale nel presvezzamento associata allo svezzamento tardivo incrementi il livello di salute intestinale nei suinetti. Tale condizione, comporterebbe un notevole vantaggio per gli animali che acquisiscono una maggiore differenziazione del microbiota intestinale, incrementando l'abbondanza di batteri beneficiali prima di affrontare lo stress dello svezzamento. Lo scopo del secondo studio è stato quello di valutare gli effetti del genotipo dell'ospite e le vie di somministrazione dell'amoxicillina sulla comparsa della diarrea e sulla composizione del microbiota intestinale, durante un'infezione naturale causata da ETEC multi-resistente, in suinetti svezzati. A tale scopo, settantuno suinetti sono stati divisi in tre gruppi: due gruppi diversificati dalla via di somministrazione dell'amoxicillinaparenterale (P) o orale (O), e un terzo gruppo di controllo in cui non sono stati somministrati antibiotici (C). I risultati ottenuti hanno confermato il ruolo di MUC4 e FUT1 quali marcatori genetici di suscettibilità alle infezioni da ETEC. Inoltre, i nostri dati hanno evidenziato come la somministrazione di amoxicillina possa influenzare negativamente lo stato di salute dei suini in corso di infezione da ETEC, effetti ancora più evidenti quando la somministrazione antibiotica avviene per via orale. Entrambi gli studi hanno sottolineato l'importanza di adottare misure alternative legate al management aziendale per il controllo della diarrea post-svezzamento. Nell'ottica di limitare l'utilizzo di antibiotici, azioni quali la selezione di genotipi resistenti, l'integrazione di probiotici di nuova generazione nei mangimi ed una corretta gestione dell'età di svezzamento, dovrebbero essere prese in considerazione nelle pratiche gestionali aziendali al fine di preservare un microbiota intestinale equilibrato e stabile e di conseguenza ridurre l'insorgenza di diarrea allo svezzamento.

RÉSUMÉ

En élevage porcin, le sevrage est une période critique caractérisée par un stress nutritionnel, environnemental et social, avec une forte sensibilité des animaux à la diarrhée. Le microbiote intestinal doit s'adapter à un changement alimentaire, avec le passage d'une alimentation lactée à un aliment plus complexe à base de céréales, et les animaux sont soumis à la pression exercée par les agents infectieux environnementaux. Les bactéries entérotoxiques Escherichia coli (ETEC) sont les principaux agents pathogènes responsables de la diarrhée post-sevrage et peuvent entrainer des pertes économiques considérables. Le rôle de la génétique de l'hôte dans la sensibilité à l'infection est bien établi, le polymorphisme des gènes Mucine 4 (MUC4) et Fucosyltransférase 1 (FUT1) étant associé à la sensibilité à ETEC F4 et F18, respectivement. Nous avons réalisé deux études afin d'analyser l'effet de facteurs pouvant influer sur la sensibilité des porcelets à la diarrhée au sevrage. Dans une première étude, nous avons évalué l'impact de l'âge au sevrage sur la diversification du microbiote intestinal, par comparaison du microbiote d'animaux sevrés à différents âges. Quarante-huit porcelets de race Large White ont été répartis en quatre groupes de 12 animaux sevrés à 14 jours (sevrage précoce), 21 ou 28 jours (âge au sevrage courant en élevage intensif) et 42 jours (sevrage tardif). La composition bactérienne du microbiote a été établie par séquençage du gène de l'ARNr 16S d'ADN fécal extrait de selles prélevées le jour du sevrage, sept jours après et à l'âge de 60 jours. Nous avons montré que le sevrage tardif augmente la diversité du microbiote, avec une plus grande abondance de Faecalibacterium prausnitzii identifiée comme bénéfique chez l'homme. Ces résultats suggèrent que la composition du microbiote intestinal pré-sevrage conférée par un sevrage à 42 jours pourrait améliorer la santé intestinale des porcelets, en leur permettant d'acquérir un microbiote plus diversifié avec des bactéries potentiellement bénéfiques lors du sevrage. La seconde étude a eu comme objectif d'évaluer, chez des porcelets sevrés, les effets du génotype des gènes MUC4 et FUT1 et des voies d'administration de l'amoxicilline sur la présence de diarrhée et la composition du microbiote fécal, lors d'une infection naturelle par des souches d'ETEC multirésistantes. Soixante et onze porcelets ont été répartis en trois groupes: deux groupes se différenciant par la voie d'administration de l'amoxicilline, parentérale (P) ou orale (O), et un groupe témoin sans antibiotiques (C). Nous avons confirmé que MUC4 et FUT1 sont des marqueurs génétiques de l'hôte pour la sensibilité aux infections à ETEC et montré que le traitement à l'amoxicilline pouvait avoir des effets néfastes sur la santé du porc au cours d'une infection à ETEC multirésistante, accentués lors d'une administration par voie orale. Les deux études ont mis en évidence l'importance de considérer des méthodes alternatives de conduite d'élevage. Avec la nécessité de limiter l'utilisation d'antibiotiques, la sélection de génotypes résistants, la supplémentation en next-generation probiotics dans l'alimentation et une meilleure optimisation de l'âge au sevrage devraient être prises en compte dans les pratiques, afin de favoriser un microbiote intestinal diversifié, capable de réduire les diarrhées au sevrage.

GRAPHICAL ABSTRACT GENERAL INTRODUCTION Section I

In the present section, an overview of the topics covered in this thesis will be provided.

The first part will present essential knowledge needed to understand the economic importance of pig production, from data on pork consumption to the different pig production systems. Moreover, the use and the amount of antimicrobials in pig herds will be described.

The second part will provide the biological background to understand one of the main objectives of this study, the gut microbiota and its interactions with the host for gut health. The present state of the art of gut microbiota in pigs, both in healthy and in disease status, will be reviewed.

The third part will provide a global overview of the main diseases in pigs, focusing mainly on the enteric diseases caused by bacterial pathogen.

Moreover, a description of the ETEC infection occurring in weaners will carried out.

Pig production

With the increase in worldwide demand for meat, fast-growing species with efficient feed conversion rates, as pigs, are likely to account for a major share in the growth of the livestock subsector. The increase in animal numbers is not spread evenly around the World: Asia leads the trend, whereas pig numbers in North America and Europe are increasing more slowly or holding steady (FAO, 2017).

a. Pig data in the World

Recent reports state that the expansion in global pork production will decelerate over the next decade, but China's production growth is expected to provide nearly half of the additional global output (OECD-FAO, 2018).

The total global volume will remain in line with the demand recovery, which is significantly lower relative to the past decade. Strong production growth rates over the outlook period (2018)(2019)(2020)(2021)(2022)(2023)(2024)(2025)(2026)(2027) are also expected in Brazil, Mexico, Philippines, the Russian Federation, the United States and Vietnam (OECD-FAO, 2018). In March 2018, China was home to the largest number of pigs of any country with 440.6 million pigs (STATISTA, 2018). European Union and United States were second and third in the list, with over 150 and 73.2 million heads, respectively (STATISTA, 2018). In recent months, a severe outbreak of African swine fever decimated the 50% of China's pig population and it continues to spread with new cases mainly reported in South China, having a strong impact on the pig production in this country [START_REF] Mallapaty | Spread of deadly pig virus in China hastens vaccine work[END_REF].

Australia, Central and Eastern Europe have been reported to register cases of African swine fever (https://www.promedmail.org/ and https://www.gov.uk/government/publications/african-swine-fever-inpigs-in-poland-lithuania-and-latvia). Globally, the virulent strain of African swine fever could potentially kill up to 25% of the world's pig population (https://www.theguardian.com/world/2019/oct/13/africanswine-fever-the-deadly-virus-at-australias-doorstep). (FAO, 2017).

c. Pig production systems

Animal welfare is of increasing interest worldwide and it is becoming a mandatory issue to face consumer's demand. Public opinion often has a favourable perception of some alternative production systems, like outdoor or organic rearing, considering it more respectful of animal welfare, sustainable and environmentally friendly. Changes in animal agriculture over the last half of the 20 th century have drastically altered farming practices and management (HSI, 2014).

Very few traditional forms of pig husbandry survive in the developed world. Along with new niche markets such as organic pig farming, they demonstrate the feasibility of alternative production systemsusually mixed farming linked to local markets instead of landless production aiming at global trade. In developing countries, half of the current pig population is still bred in traditional small-scale subsistence-driven production systems in which pigs provide a potential economic benefit.

Less intensive pig production systems are dissimilar worldwide and often connected to tradition. Therefore, they often differ by pig breeds, environmental conditions, and other natural resources. Outdoor pig farming is defined as a system that allows the pigs to have outside access including contact with soil and growing plants, with which animals can express their natural behaviour (Park et al., 2017). From one side, this system is considered to be beneficial for welfare as animals are kept at low stocking density and are able to express better their natural behaviour.

From the other side, outdoor systems could also present negative aspects, such increased exposure to pathogens and in some cases even the access to water and feed, and the protection against climate episode are limited.

Moreover, possible attacks from wildlife and infections carried out by parasites are more frequent than in intensive herds. Moreover, it should be considered that outdoor farms have also biosecurity measures such as fences, reducing the potential contact with external animals (except for birds). The use of outdoor systems is often associated with pig husbandry of local breeds. One of the most representative local pig breed is the Iberian raised in the southwest of the Iberian Peninsula, but there are many other breeds reared in European countries (Muñoz et al., 2018). These breeds are in general characterized by a good adaptation to specific environments, high potential for fat deposition and characteristic meat quality, mostly related to high intramuscular or intramuscular fat content, which are associated with high quality pork productions. As regards for the Iberian breed, outdoor pigs are fed exclusively with acorns present in the field, and this is a request for the production of specific products becoming to local breeds, such as the Jamón ibérico de bellota.

Recently, the swine industry has focused on a sustainable intensification of the pig farming systems, which maximizes value over production costs and represents a shift away from antimicrobial usage. However, free range pigs seldom grow as fast as intensively farmed pigs because they expend more energy to walk around while feeding, may lose more weight due to inclement weather, and do not eat a concentrated ration.

In this scenario, there is an urgent need not only for a correct combination of sustainability and efficiency to meet consumer expectations, but also for the development of new phenotypes related to host robustness (Merks et al., 2012).

d. Antibiotic practises in pig herds and the antibiotic resistance issue

The indiscriminate use of antibiotics in livestock has raised concerns that the selective pressure on the bacteria population promotes antibiotic resistance. In fact, the use of antibiotics is common not only for treatment, but also for controlling the spread of infection (metaphylaxis), preventing infection (prophylaxis) particularly in periods of stress and vulnerability to infections [START_REF] References Aarestrup | Veterinary drug usage and antimicrobial resistance in bacteria of animal origin[END_REF].

However, many classes of antibiotic used for humans are also prescribed in food producing animals. For this reason, the WHO produces a list of all antimicrobials grouped into 3 categories based on their importance in treating human infections (WHO, 2017). The classes of drugs included in the list of CIA for human medicine contain the last-resort antibiotics to treat severe infections caused by MDR. The CIA list of Highest Priority

Critically Important Antimicrobial includes quinolones, 3 rd and higher generation cephalosporins, macrolides and polymixins, an antibiotic class which includes colistin (WHO, 2017).

Despite the difficulties in demonstrating the transmission of resistant bacteria from animals to humans, many studies involving zoonotic pathogens, showed evidence of human infection from resistant bacteria in animals (Angeles et al., 2017;Guevarra et al., 2019;Marshall and Levy, 2011;Nhung et al., 2016;Van Den Bogaard and Stobberingh, 2000). One of the most recent concern about the AMR is the discovery of plasmidmediated colistin resistant genes (mcr-1, mcr-2, mcr-3, mcr-4, mcr-5 ) in commensal Escherichia coli from pigs (Borowiak et al., 2017;Carattoli et al., 2017;Liu et al., 2016;Xavier et al., 2016;Yin et al., 2017). Before EMA recommandations on limiting the use of colistin in animals, colistin was used for over to treat infections caused by Enterobacteriaceae in farm animals, such as colibacillosis in piglets (EMA, 2016a). Nowadays, colistin is considered a last resort antibiotic as it is one of the only antibiotics active in severe infections caused by hospital acquired pathogens such as Pseudomonas aeruginosa, Acinetobacter baumannii and Enterobacteriaceae (Lekagul et al., 2019).

Because of the selective pressure exerted by antibiotics and the spread of difficult-to-treat MDR pathogens observed during the last two decades, their use in human and veterinary medicine started to be considered an important issue. Though the transfer of AMR from livestock to humans may occur via several pathways, a considerable evidence suggests that the food route is the most relevant one (Murphy et al., 2017). In France, the Ecoantibio plan has been developed from 2012 in order to limit the use of antibiotics in livestock (https://agriculture.gouv.fr/plan-ecoantibio-2012-2017-lutte-contre-lantibioresistance).

In EU, recent data have been estimated that resistance to antibiotics led to 25,000 deaths per year and 700,000 worldwide, while the ACDC estimated that among the USA population, 2 million people become infected with bacteria that are resistant to antibiotics (ECDC and EFSA, 2017) 1.

Either in Italy or in France, the oral solution is the most used pharmaceutical form of used antibiotics [START_REF] Ema | Sales of veterinary antimicrobial agents in 31 European countries in 2017[END_REF].

The gut microbiota

The microbial communities that inhabit the GIT are well known to play a fundamental role in many host processes, and understanding of these complex communities continues to advance at a rapid pace.

Some definitions are necessary to better understand the whole scenario:

-Microbiota: "microbial ecosystems living with plants and animals" (Berg, 1996);

-Microbiome: "the totality of the microbes, their genetic elements, and the environmental interactions in a particular environment" (Elzinga et al., 2019;Whipps et al., 1988);

-Superorganism: "the host and the microorganisms inhabiting it" (Elzinga et al., 2019;Thursby and Juge, 2017);

-Holobiont: "hybrid consortia of body cells and microbial communities that together, synergistically and cooperatively, regulate health and disease" (Coleman et al., 2018).

The number of microorganisms inhabiting the human GIT has been estimated to exceed 10 14 , which encompasses ∼10 times more bacterial cells than the number of human cells and over 100 times the amount of genomic content (microbiome) as the human genome (Ley et al., 2005;Luckey, 1972;Savage, 1977). However, a recently revised estimate has suggested that the ratio of human:bacterial cells is actually close to 1:1 (Sender et al., 2016a(Sender et al., , 2016b)). This ratio has been changed replacing the old 10:1 or 100:1 values because the number of human and bacterial cells has been recently recalculated (Sender et al., 2016a(Sender et al., , 2016b)).

Indeed, microbiota and its effects on host phenotypes have emerged as major factors to be considered in animal science (Estellé, 2019).

Understanding the complexity of superorganisms as dynamic ecosystems is essential for interpreting data from pathogen challenge studies of humans and laboratory animals (Foster et al., 2018).

The microbes residing in the gut harvest energy from the food, train our immune system, break down xenobiotics and other foreign products, and release metabolites and hormones important for regulating our physiology (Duvallet et al., 2017;Turnbaugh et al., 2006). Chemical signals from the microbiota can act locally within the gut, and can also have larger systemic effects, such as the case of the "gut-brain axis" (Carabotti et al., 2015;Cryan and O'Mahony, 2011;Duvallet et al., 2017;Mayer et al., 2015;Osadchiy et al., 2019). Due to the physiological interplay between humans and microbial communities, many diseases are hypothesized to be associated with shifts away from a "healthy" gut microbiome. These include metabolic disorders (Dominguez-Bello et al., 2019;Mohammadkhah et al., 2018;Zimmermann et al., 2019), inflammatory and auto-immune diseases (De Luca and Shoenfeld, 2019;Li et al., 2018;Opazo et al., 2018), neurological conditions (Destrez et al., 2019;Griffiths and Mazmanian, 2018;Ma et al., 2019) and cancer (Garrett, 2019(Garrett, , 2017;;Helmink et al., 2019;Vivarelli et al., 2019;Wong et al., 2019), among others (Rinninella et al., 2019;Turnbaugh et al., 2006;Wang et al., 2017).

Certain gut-related conditions (e.g., obesity and IBD) have been extensively studied in human cohorts and in animal trials, where significant and sometimes causal microbial associations have been shown (Forbes et al., 2018;Zuo and Ng, 2018). In this scenario, the GIT microbiota of mammals has been recognized to take part in the reduction in the incidence of infectious, inflammatory, and other immune diseases (Ding et al., 2019;Round and Mazmanian, 2014;Shreiner et al., 2016;Valdes, 2018;Wang et al., 2017). While the inherited host genome remains almost stable during lifetime, the microbiome is extremely dynamic and can be influenced by a number of factors, among which, age, diet, hormonal cycles, travel, therapies and illness (Argenio and Salvatore, 2015;Fouhy et al., 2019;Kers et al., 2018;Kim et al., 2019;Yieh et al., 2018). Moreover, the gut microbiota varies qualitatively and quantitatively according with the chemical and nutrient gradients, and with the physiological and immune compartmentalisation, from the proximal to the distal part of the GIT, establishing the densest communities in caecum and colon (Figure 2). Furthermore, the differences over the intestinal crosssection axis determine compartments between mucosal folds and also between lumen and intestinal wall, which can represent microhabitats with peculiar microbial communities (Crespo-Piazuelo et al., 2018;[START_REF] Donaldson | Gut biogeography of the bacterial microbiota[END_REF].

Figure 2:

Microbial habitats in the human lower gastrointestinal tract [START_REF] Donaldson | Gut biogeography of the bacterial microbiota[END_REF]. The dominant bacterial phyla in the gut are Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria and Verrucomicrobia. The dominant bacterial families of the small intestine and colon reflect physiological differences along the length of the gut. For example, a gradient of oxygen, antimicrobial peptides (including bile acids, secreted by the bile duct) and pH limits the bacterial density in the small intestinal community, whereas the colon carries high bacterial loads.

In the small intestine, the families Lactobacillaceae and Enterobacteriaceae dominate, whereas the colon is characterized by the presence of species from the families Bacteroidaceae, Prevotellaceae, Rikenellaceae, Lachnospiraceae and Ruminococcaceae (colours correspond with the relevant phyla). A cross-section of the colon shows the digesta, which is dominated by Bacteroidaceae, Prevotellaceae and Rikenellaceae, and the inter-fold regions of the lumen, which are dominated by Lachnospiraceae and Ruminococcaceae.

a. The gut microbiota in pigs Large-scale studies have investigated the swine gut microbiome. In the faecal metagenome of 287 pigs from France, Denmark, and China 7,685,872 non-redundant genes, representing 719 metagenomic species were identified and constituted a first gene catalogue of the pig gut microbiota (Xiao et al., 2016). Interestingly, 96% of the functional pathways found in the human gene catalogue are present in the swine gut microbiome gene catalogue, confirming the importance of pigs as human biomedical models (Xiao et al., 2016). These data give an idea of the complexity of the gut ecosystem, and intuitively, the plethora of possible functions the gut microbiota can have (Canibe et al., 2019).

The pig gut microbiota imparts specific function in host nutrient metabolism, xenobiotic and drug metabolism, maintenance of structural integrity of the gut mucosal barrier, immunomodulation, and enhance resistance against pathogenic bacteria (Bum and Isaacson, 2015;Guevarra et al., 2019;Jandhyala et al., 2015;Mohajeri et al., 2018). The swine microbial ecosystem is composed of rich and diverse populations that harbour thousands of different microbial species (aerobic, facultative anaerobic, and strictly anaerobic), dwelling in different anatomical biogeographic locations (Crespo-Piazuelo et al., 2018;Holman et al., 2017). Alteration of the swine microbial environment may detrimentally influence the host's health status and inhibit the pathogen colonization and consequently the gut microbiota of animals (Marchesi et al., 2016). The initial colonising bacteria in suckling and weaner piglets largely drive microbiome establishment and development. However, the microbiome is a dynamic system that is changing and influenced by a variety of factors at weaning (Figure 3). Some of these factors include antibiotic use, stress, diet, age, and the rearing environment (Mach et al., 2015;Nowland et al., 2019). Moreover, several studies have been conducted to evaluate the effect of antibiotics on the pig gut microbiota (Gresse et al., 2017;Luppi, 2017;Schokker et al., 2014;Soler et al., 2018). These studies demonstrate how antibiotics may shape the intestinal microbiota of pigs during the suckling period, and strongly suggest a link between antibiotic supplementation and gut microbiota disruption in early life of pigs (Gresse et al., 2017;Luppi, 2017;Schokker et al., 2014;Soler et al., 2018).

Previous studies in humans have suggested that the most important period for microbial establishment is the first years of life since it is during this time that the microbiome is more dynamic and susceptible to diversification (Koenig et al., 2011;Lallés et al., 2007;Sordillo et al., 2019). Such as for humans, also in pigs, disruption of the gut microbiota during the weaning period results in disease (Dou et al., 2017;Gresse et al., 2017). Thereafter, the microbiome changes toward a more adult-like state where it becomes more stable and resistant to change (Koenig et al., 2011;Sordillo et al., 2019). A definition of a healthy gut microbiota in an eubiotic status is still not completely defined. Globally, a healthy gut microbiota is associated with the concept that the microbial community is mainly composed by potentially beneficial species, while pathogenic bacteria are present with a percentage too low to be infectious (Iebba et al., 2016). Moreover, a homogeneous, richer and balanced gut microbiota is widely acknowledged to be beneficial (Rinninella et al., 2019).

In pigs, the "core-healthy" gut microbiota among all gastrointestinal sites is mainly constituted by Firmicutes and Bacteroidetes phyla, accounted for nearly 85%, and Proteobacteria represent the third more abundant phylum (Holman et al., 2017;Rinninella et al., 2019). The genera Alloprevotella, Blautia, Clostridium, Lactobacillus, Prevotella, Roseburia and Ruminococcus are widely recognised to constitute a healthy core microbiota in pigs (Crespo-Piazuelo et al., 2018;Holman et al., 2017).

A healthy host-microorganism balance must be respected in order to optimally perform metabolic and immune functions and prevent disease development. Indeed, disturbances to the delicate host-microbe relationship may negatively affect the development of the immune system, which may in turn result in diseases susceptibility (Patterson et al., 2019).

i.

Eubiosis, dysbiosis and symbiosis

The intestinal microbial ecosystem balance, called eubiosis, is a fundamental concept. As early as 400 B.C., Hippocrates said: "death is in the bowels" and "poor digestion is the origin of all evil". Ali Metchnikoff, who lived from 1845 to 1916, suggested that most diseases begin in the digestive tract when the "good" bacteria are no longer able to control the "bad" ones. He called this condition dysbiosis, meaning an ecosystem where bacteria no longer live together in mutual harmony (Iebba et al., 2016). In case of dysbiosis, "good bacteria" no longer control the "bad bacteria" which take over (Zhang et al., 2015).

The importance of maintaining an eubiotic condition in the intestinal microbial ecosystem is quickly highlighted when we look at some of the deleterious sequelae after antibiotic treatment or pathogenic status (Iebba et al., 2016;Quigley, 2013;Sekirov et al., 2010;Yoon and Yoon, 2018).

Additionally, it should be highlighted that the host response to exogenous infectious agents amplifies/promotes a dysbiosis status. The host responses include inflammation induction, leading to an alteration of the intestinal nutritional environment, and often to a secretory diarrhoea, having strong effects on the microbiota ecosystem. Under an inflammatory condition, we can observe an unexpected decrease in the vitality of the intestinal microbiota, enhancing the availability of ecological niches for pathogen colonization (Iebba et al., 2016;Shreiner et al., 2016).

Historically among scientists, there has been disagreement on the proper use and definition of the term symbiosis, which is derived from the Greek "syn" meaning together and "bios" meaning life ("Symbiosis| Origin and Meaning of Symbiosis by Online Etymology Dictionary," 2017). While

Heinrich Anton de Bary is credited with popularizing the term in 1879, it was first used in 1877 by Albert Bernhard Frank in reference to the coexistence of different species (Tipton et al., 2019). Both Frank and de Bary used the term "symbiosis" to refer to all types of interactions between species ranging from parasitism, where one partner benefits without any measurable effect to the other(s), to mutualismwhere all partners benefit (Sapp, 2004).

However, the use of the term among microbiome researchers has retained the connotation of mutualism. This extreme mutualism is sometimes simplified as "cross-feeding" but can also take the form of individuals "cheating" mutualisms through adaptive gene loss, as proposed in the "Black Queen Hypothesis" (Morris et al., 2012). Future studies of microbiome will continue to inform and refine our understanding of the breadth of biotic interactions, and may lead to reconsiderations of what constitutes a symbiosis (Tipton et al., 2019).

ii.

Probiotics, Prebiotics and Synbiotics

As already said in previous sections, the gut microbiota composition plays an important role in the health of pigs and modulating the population of bacteria in the gut may improve the health of the animals and decrease the risk of diseases (Liu et al., 2018;Patel and Dupont, 2015;Roselli et al., 2017;Tossou et al., 2016;Tran et al., 2018;Van Der Aar et al., 2017).

In fact, during the last years, research has moved on towards the bacteriotherapy that includes 3 different agents (Patel and Dupont, 2015):

probiotics, prebiotics and synbiotics, defined as it follows.

-Probiotics: "live microorganisms that, when administered in adequate amounts, confer health benefits to the host" (Hill et al., 2014;WHO-FAO, 2001) -Prebiotics: "a selectively fermented ingredient that allows specific changes, both in the composition or activity in the gastrointestinal microflora that confer benefits upon host well-being and health" (Roberfroid, 2007) -Synbiotics: "combination of probiotics and prebiotics" (Yang et al., 2015) Over the past few decades, probiotics and prebiotics or their combination, have been the subject of many research studies because of their potential therapeutic and preventive health benefits to animals [START_REF] Yang | The Use of Lactic Acid Bacteria as a Probiotic in Swine Diets[END_REF].

Previous reports have shown that probiotics and prebiotics have a broad range of beneficial effects in pigs, including fortification of the intestinal barrier function (Barba-Vidal et al., 2017;Wang et al., 2018a), reduction of diarrhoea duration and severity (Hancox et al., 2015;Inatomi et al., 2017;Liao and Nyachoti, 2017), inhibition of pathogenic bacteria (Barba-Vidal et al., 2017;Tran et al., 2018) and immunological development (Barba-Vidal et al., 2017;Wang et al., 2018b).

As regards to probiotics, there are three general mechanisms by which probiotics appear to exert their beneficial effects:

i. antimicrobial effects

ii. enhancement of mucosal barrier integrity

iii. immune modulation Probiotic strains alter the luminal environment, decrease adhesion and cellular invasion, and can produce antibacterial products (e.g., bacteriocins, hydrogen peroxide, and organic acids) that can inhibit the growth of pathogens. This is the case of the genus Lactobacillus responsible for producing bacteriocins. The inhibitory action of these bacteriocins varies from inhibiting other lactobacilli to directly inhibiting a wider range of gram-positive, gram-negative bacteria, viruses, and certain fungi (Gaspar et al., 2018;Kenny et al., 2011). Moreover, hydrolytic enzymes produced by some probiotics contribute to the increase of lactic acid, propionic acid, butyric acid, and other SCFAs in the intestinal lumen, reducing the luminal pH. Maintaining a lower pH creates a physiologically restrictive environment that can inhibit the growth and colonization by pathogenic bacteria (Holman and Chénier, 2015;Smiricky-Tjardes et al., 2003). Furthermore, intestinal barrier function is maintained by mucus production, chloride and water secretion, and tight junctions, which bind the apical portions of epithelial cells. Disruption of the epithelial barrier is seen in several conditions including infectious diarrhoea (Luppi, 2017), IBD (Edwards, 2017;Mohajeri et al., 2018;Rooks et al., 2014), and autoimmune diseases (De Luca and Shoenfeld, 2019;Li et al., 2018). Enhancement of the mucosal barrier may be a crucial mechanism by which probiotic bacteria benefit to the host in these diseases. Moreover, probiotics can alter mucosal immunity considerably as they are able to affect many host cell types involved in the local and systemic immune responses (Roselli et al., 2017;Zhang et al., 2007).

Prebiotics are non-digestible oligosaccharides, such as fructooligosaccharides, galactooligosaccharides, lactulose, and inulin, which have the potential to stimulate growth of selective and beneficial gut bacteria, particularly genera of Lactobacillus and Bifidobacterium (Bouhnik et al., 2004;Samanta et al., 2013). Because of their composition, prebiotics cannot be digested until they reach the large intestine , where they can be fermented by a specific microbe into SCFAs and lactate (Bouhnik et al., 2004). Recent evidence shows that prebiotics are able to increase the production of SCFAs, which in turn modulate cytokine production within the gut mucosa by altering the gut microbiota composition (Baxter et al., 2019;Beek et al., 2018;Poeker et al., 2018).

The quite recent concept of synbiotics is to combine a probiotic and a prebiotic to facilitate the survival and activity of proven probiotics in vivo, as well as stimulating indigenous anaerobic bacteria. Probiotics and prebiotics work synergistically to provide a combined benefit. Several studies have shown positive synergistic effects of synbiotics in humans (İşlek et al., 2014;Markowiak and Śliżewska, 2018;Min et al., 2016).

iii.

Next-generation probiotics from microbiota studies: the example of Faecalibacterium prausnitzii Most of the currently commercialized probiotics used to treat and prevent medical conditions are mainly limited to the Lactobacillus and Bifidobacterium strains (George et al., 2018).

With the development of improved bacterial culturing methodologies, more affordable genome and metagenome sequencing (massive parallel sequencing), and powerful tools able to edit and modify bacterial genomes, we are entering a new era in probiotic research that allows us to develop probiotics that address specific needs and issues for both humans and animals. Information gained from several studies are helping to set a rationale for selection of NGPs such as Faecalibacterium prausnitzii (Martín et al., 2017), Akkermansia muciniphila (Cani and De Vos, 2017),

Bacteroides uniformis and Bacteroides fragilis (Hage et al., 2017). These NGPs were evaluated in preclinical trials and yielded positive outcomes for inflammatory and metabolic disorders in humans (Patel and Dupont, 2015).

One of the most abundant species to be found in the large intestine of humans is Faecalibacterium prausnitzii, which has been reported to be depleted in individuals with IBD (Martín et al., 2017). Therefore, it seems reasonable that if there was a causal link between disease status and the absence of this microorganism, then by simply feeding it to the individual its health promoting features should be restored (Martín et al., 2017).

However, there is no evidence, since now, for this bacterium efficacy as a probiotic to be able to reverse the symptoms of IBD when fed to humans.

In mice, evidence is available and feeding animals with F. prausnitzii does lead to or associate with induction of anti-inflammatory cytokines or reduction of pro-inflammatory cytokines in induced models of colitis/IBD (Martín et al., 2017;Rossi et al., 2015;Sokol et al., 2008;Zhang et al., 2014). The presence of the anti-inflammatory properties of F. prausnitzii also opens the possibility to test them in other animal models to determine further their beneficial effects before testing them in human clinical trials.

Health and disease

The term "health" is defined as a state of complete physical, mental and social well-being that allows the pig to exploit its genetic potential for maximising productivity, reproductive performance and lean meat production (Muirhead and Alexander, 2012) The term "disease" means an unhealthy disorder of body and mind, sometimes with pain and unease that is likely to prevent the pig from exploiting its genetic potential resulting in lowered production efficiency and consequently productivity (Muirhead and Alexander, 2012).

Disease can be clinical (i.e. the affected pig shows clinical signs) or subclinical (the affected pig shows no obvious clinical signs). Any physical or psychological disturbance of immunity may render the pig susceptible to opportunistic pathogens. Good husbandry, meaning good housing, good nutrition and good management, aims to avoid such disturbances in herds (Zimmerman et al., 2012). Good husbandry is the most important factor in preventing disease and maximising health and production.

A recent concept in animal health is the resilience. Resilience takes on different meanings, depending on the context and the field in which it is used. In animal science, it is defined as follows:

Resilience: "the capacity of animals to cope with short-term perturbations in their environment and return rapidly to their prechallenge status" (Colditz and Hine, 2016).

a. Diseases in pig production

According to Koch's postulate, the classical concept involves the relationship 'one microorganismone disease'. However, after determining that the number of microorganisms (viruses, eukaryotes and bacteria) colonizing animals is extremely large, this concept was shown to be an oversimplification, and that it cannot explain the aetiology of a disease.

The main causes of disease are considered under five infectious and five non-infectious main headings (Muirhead and Alexander, 2012): The complete list of the main viral and bacterial diseases of pigs and their main clinical signs are shown in Table 2.

Infectious

b. Weaning enteric diseases

Enteric infections are gastrointestinal disorders among the most common and economically significant diseases affecting swine production worldwide (Zimmerman et al., 2012). Clinical signs of these infections include diarrhoea, reduced growth rates, weight loss, and death of pre-and post-weaned piglets. The most common causes include bacterial and viral etiological agents, such as Enterotoxigenic Escherichia coli, Salmonella spp., type A Clostridium perfringens, Coronavirus (responsible of PED)

and Rotavirus (Argüello et al., 2019(Argüello et al., , 2018a;;[START_REF] Theuns | Porcine group a rotaviruses with heterogeneous VP7 and VP4 genotype combinations can be found together with enteric bacteria on Belgian swine farms[END_REF]Zimmerman et al., 2012).

Control measures for enteric diseases should focus on elimination of environmental risk factors through cleaning and improved biosecurity.

Moving medicated animals to a clean, segregated environment is often successful in elimination efforts. Extensive environmental clean-up with removal of all contaminated faecal material is essential for infected facilities, and a protocol of pressure washing, disinfection, and application of concentrated lime solution to environmental surfaces has been reported to be effective (Muirhead and Alexander, 2012).

i. The Enterotoxigenic Escherichia coli infection in piglets

During weaning, maternal separation, change of environment, mixing with non-litter mates, transportation, change in temperature, new sources of feed and water, handling and administration of vaccines can all coincide and put piglets under considerable stress. This is important because stress at weaning has been shown to reduce growth rates, and even cause dysfunction in the intestines that often open the way to pathogen colonization, such as the colibacillosis infections (Gresse et al., 2017).

Accumulating evidence suggests that a strong shift in the microbial state may be mainly attributed to the transition from a primarily liquid milk diet to one that relies on solid food (Lallés et al., 2007).

Therefore, during the weaning, piglets are subjected to the ETEC infection and the microbiota may have an important effect on the development of the disease. In Italy and in France, ETEC are among the main enteric pathogen affecting the piglets during the weaning [START_REF] Anses | Résapath, le réseau d'épidémiosurveillance de l'antibiorésistance des bactéries pathogènes animales[END_REF]Bin et al., 2018;Gresse et al., 2017;Luppi, 2017;Murphy et al., 2017;Trevisi et al., 2015). Escherichia coli is a gram negative peritrichously flagellated bacteria belonging to the family Enterobacteriaceae and is the etiological agent of a wide range of diseases in pigs, including neonatal diarrhoea and PWD, which are important causes of death occurring worldwide in suckling and weaned pigs respectively (Fairbrother and Gyles, 2012). Two main pathotypes are involved in enteric colibacillosis: ETEC and EPEC.

Between those, ETEC is the most important pathotype in swine (Fairbrother and Gyles, 2012). The ETEC strains possess fimbrial adhesins, identified as F4 or F18, that mediate microbial attachment to the intestinal epithelium (Luppi, 2017). Briefly, pathogenic bacteria contaminating the environment are ingested by susceptible animals and enter the intestinal tract. The fimbriae allow the ETEC to adhere to specific receptors on the brush borders of the small intestine enterocytes (Fairbrother and Gyles, 2012). Resulting bacterial colonization is found mostly on the jejunal and or ileal mucosa. The adherent bacteria produce enterotoxins, which stimulate water and electrolyte loss into the intestinal lumen, leading to dehydration and possibly death, and a decreased weight gain in surviving animals (Figure 4) [START_REF] Sun | Intestinal challenge with enterotoxigenic Escherichia coli in pigs , and nutritional intervention to prevent postweaning diarrhoea[END_REF]. The degree of colonization and proliferation determines whether the disease results from an infection. PWD is commonly observed 2-3 weeks after weaning and although not exceptionally, it can be recorded at 6-8 weeks after weaning (Luppi, 2017). The cases of post-weaning colibacillosis due to ETEC are usually characterized by yellowish, grey or slightly pink watery diarrhoea with a characteristic smell, generally lasting one week (Figure 5). The effect of diarrhoea in piglets affected by enteric colibacillosis is a loss of liquids, consequently animals become dehydrated and die rapidly (Luppi, 2017). Zinc oxide and antimicrobials are the main choices in the treatment of PWD. Feed containing between 2400 and 3000 ppm of zinc oxide reduce diarrhoea, mortality and improve growth (Roselli et al., 2003).

Antimicrobial therapy is required in many cases of enteric colibacillosis, besides using approaches to avoid infectious agents and clinical diseases.

Antimicrobial therapy must be selected which reaches therapeutic concentrations in the intestinal lumen, as observed for different classes of antibiotics: βlactam antibiotics, cephalosporins, aminoglucosides, aminocyclitols, sulphonamide combined with trimethoprim, fluorochinolones, quinolones and polymyxins (Fairbrother and Gyles, 2012;Giguère and Prescott, 2013). Antimicrobial resistance to several antibiotics such as apramycin, neomycin, trimethoprim-sulphametoxazole and colistin has been increasingly observed in ETEC strains causing PWD (Magistrali et al., 2018;Zhang, 2014). The development of resistance to a wide range of antimicrobial drugs, as well as the demonstrated trend of resistance in ETEC strains to the antibiotics used for the treatment of colibacillosis in pigs, is nowadays a concern (Aarestrup et al., 2008).

Among the physiological and GIT factors impacted by the weaning transition, microbiota disruption in the GIT has likely a key influence leading to PWD. Most studies conducted during the weaning transition have reported a decrease in bacteria of the Lactobacillus spp. group and a loss of microbial diversity, whereas Clostridium spp., Prevotella spp. or facultative anaerobes such as Proteobacteriaceae, including E. coli, were increased (Dou et al., 2017;Gresse et al., 2017). Furthermore, in-feed and (or) in-water antibiotics also cause differences in the GIT microbiota at weaning due to their wide spectrum of activity and thus their potential ability to kill or prevent the growth of both pathogenic and beneficial microbes (Gresse et al., 2017).

ii. The MUC4 and FUT1 candidate genes in piglets According to their genetics, piglets are not equally susceptible to ETEC infection. Susceptibility to ETEC F4 has been associated to a single nucleotide polymorphism (SNP) located in intron 7 (g.13:8227C>G) of the Mucin 4 gene (MUC4) (Jørgensen et al., 2004;Luise et al., 2019;Rampoldi et al., 2011). Piglets with MUC4 G-genotypes express the F4

receptor and are considered susceptible to ETEC F4 infection, while piglets with MUC4 CC genotype are associated with the resistant phenotype (Jorgensen et al., 2003).

The susceptibility to the ETEC F18 infection appears to be dependent on the activity of the alpha-fucosyltransferase-1 (FUT1) gene, which is the candidate gene for the adhesion to F18 receptor. The g.6:54079560T>C SNP located on FUT1 gene has been associated with the susceptibility to ETEC F18 infection; piglets with FUT1 C-genotypes appear susceptible to ETEC F18 while piglets with FUT1 TT genotype are resistant to the infection (Meijerink et al., 1997;Muñoz et al., 2018;Vogeli et al., 1997;Wang et al., 2012).

55

The global objective of this thesis was to increase the knowledge on determinants affecting the post-weaning diarrhoea and the faecal microbiota in piglets, through the study of management and husbandry practises, the ETEC infection and host genetics.

This global objective was addressed with the following specific objectives of the two studies performed:

1. To characterize the gut microbiota dynamics in antibiotic-free piglets weaned at different ages and describe the faecal microbiota differences between early and late weaning (Section III-Paper I);

57

SCIENTIFIC PAPERS

Section III

Introduction

Weaning is one of the most important life transitions experienced by pigs raised for commercial meat production, and piglets go through postweaning transient anorexia, which results in undernutrition and weight loss (Lallés et al., 2007). Indeed, it has been estimated that only 50% of piglets consume their first meal within 24 hours of weaning, and 10% still have not eaten 48 hours later [START_REF] Brooks | NLiquid feeding for the young piglet[END_REF]. However, piglets generally return to their pre-weaning level of energy intake 8-14 days after weaning [START_REF] Le Dividich | Effects of underfeeding during the weaning period on growth, metabolism, and hormonal adjustments in the piglet[END_REF]. In modern pig production systems, weaning usually occurs between the third and fourth week of life [START_REF] Colson | Consequences of weaning piglets at 21 and 28 days on growth, behaviour and hormonal responses[END_REF], and piglets are forced to switch from a highly digestible milk-based diet to a more complex, less digestible, and solid plant-based diet (Lallés et al., 2007). During this period, piglets may be afflicted with diarrhea due to gut dysbiosis and/or the colonization of the gut by enteric pathogens (Gresse et al., 2017;Lallés et al., 2007). In addition, piglets experience social stresses, such as being moved to the post-weaning building, being separated from their mothers, and being forced to live with piglets that are not their littermates [START_REF] Colson | Influence of housing and social changes on growth, behaviour and cortisol in piglets at weaning[END_REF]Lallés et al., 2007).

The swine gut microbiota comprises a large and diverse community of bacteria that play a significant role in pig health. Many recent studies have used high-throughput sequencing of the 16S rRNA gene to characterize the composition and structure of this community. In pigs, as in other mammals, the microbiota establishment begins at birth (Katouli et al., 1997;Thompson et al., 2008). From birth until weaning and then during the post-weaning period, the gut microbiota is dynamic and undergoes major compositional changes driven by age, exposure to microbes, environmental conditions, and diet (Mach et al., 2015). Pigs bred under free-range conditions have been reported to wean between 11 and 12.5 weeks of age [START_REF] Bøe | The process of weaning in pigs: when the sow decides[END_REF][START_REF] Stolba | The identification of behavioural key features and their incorporation into a housing design for pigs[END_REF] and in some cases even later (i.e., after 17 weeks [START_REF] Jensen | When to wean -Observations from Free-Ranging Domestic Pigs[END_REF]). Studies comparing piglet weaning ages have found that later weaning can improve health, boost wean-to-finish growth performance, and reduce mortality during the post-weaning period [START_REF] Davis | Effect of weaning age and commingling after the nursery phase of pigs in a wean-to-finish facility on growth, and humoral and behavioral indicators of well-being[END_REF][START_REF] Main | Increasing weaning age improves pig performance in a multisite production system[END_REF].

Delaying the age at weaning in production farms has been proposed as a possible strategy for modulating and limiting the effects of weaningassociated problems (Früh, 2011). However, few studies have examined how weaning age affects the early-life establishment of the pig gut microbiota and individual susceptibility to weaning-related health issues.

Hence, the overall aim of this study was to characterize gut microbiota dynamics in piglets fed antibiotic-free diets and weaned at different ages.

Results

Effect of weaning age on piglet weight and occurrence of diarrhea

Forty-eight Large White piglets (23 females and 25 males) were divided into four groups of 12 animals that were weaned at different ages: 14 days (W14), 21 days (W21), 28 days (W29), and 42 days (W42). These groups are hereafter referred to as the weaning groups. Animals presenting diarrhea were unevenly distributed across groups, with a strong reduction in the proportion of affected animals in the groups W28 and W42: 3/10 (30%) in the W14 group, 5/12 (41%) in the W21 group, 1/12 (8%) in the W28 group and 0/11 (0%) in the W42 group. A Chi-square test confirmed that these differences were significant (p<0.05).

To characterize piglet growth, we monitored the weight of pigs in each weaning group from birth (day 0) to 62 days of age (weight was measured at 5,12,20,27,33,48,55, and 62 days of age). Using ANOVAs, we found that the weaning groups differed in weight across time and that patterns of differences varied (Table S1). In general, after weaning, the mean weight for the W14 group was consistently lower than the mean weights for the other groups (Figure 1). In addition, piglets in the groups W14 (at day 20), W21 (at day 27), and W28 (at day 33) lost weight immediately after weaning. Indeed, three animals from the W14 group were euthanized because they were lethargic and failed to grow (decision made in accordance with the project's established ethical guidelines). On day 62, the mean weights for the groups W21, W28, and W42 were statistically similar to each other, and they all differed from the weight for the W14 group (p<0.05).

Figure 1:

Growth curves for piglets weaned at 14 days of age (W14), 21 days of age (W21), 28 days of age (W28), and 42 days of age (W42). The solid and dashed lines show each group's mean and standard deviation, respectively. The initial sample sizes for each group were as follows: W14: 10 animals, W21: 12 animals, W28: 12 animals, and W42: 10 animals. The samples sizes for each group after weaning were as follows: W14: 4 animals, W21: 6 animals, W28: 6 animals, and W42: 5 animals. Any statistical differences between groups are indicated by different letters in each time point, and further details can be found in Table S1.

Fecal microbiota sequencing, OTU identification and annotation

The piglets' fecal microbiota were analysed by sequencing the bacterial 16S rRNA gene using an Illumina MiSeq Sequencer. Samples with fewer than 10,000 reads following quality control procedures were removed from the analysis, resulting in sample sizes of Other phyla were also represented, but they were less common (e.g., Proteobacteria: 5%, Spirochaetes: 0.45%, Fusobacteria: 0.45%, Actinobacteria: 0.35%, Deferribacteres: 0.27%, and Tenericutes: 0.01%; Figure 2A). At the phylum (Figure 2A) and genus (Figure 2B) levels, the overall abundance of diverse OTUs varied based on weaning age and among sampling points within weaning groups (see the following sections). When we examined the 75% most prevalent taxa in each group at the three sampling points, we found that, out of the

Effect of weaning age on fecal microbiota diversity and composition before and after weaning

Alpha diversity, beta diversity, and richness were calculated using the rarefied OTU counts for each group and then compared among weaning groups and sampling points (Figure 3). ANOVAs and Tukey's honest significant difference (HSD) tests were used to assess any resulting differences (Table S2). Overall, there were significant differences (p<0.05) in alpha diversity and richness among sampling points within all the weaning groups except W42. In the W42 group, only beta diversity differed significantly among sampling points. The results for alpha diversity and richness reflect the diversification that takes place in the gut microbiota during and after weaning. The results for beta diversity fit with the idea that microbiota heterogeneity declines as animals grow older. The Tukey's HSD tests highlighted that the significant differences mainly originated from differences in diversity and richness between the pre-and post-weaning sampling points. Moreover, we observed that beta diversity declined between 7 days post weaning and 60 days of age, except in the W14 group (Figure 3B).

Non-metric multidimensional scaling (NMDS) analyses were carried out using Bray-Curtis dissimilarity values quantifying overall differences in gut microbiota composition between samples collected before weaning, 7 days after weaning, and at 60 days of age for piglets in each weaning group (Figure 4). For the groups W14, W21, and W28, there were clear differences between the results for the three sampling points. For the group W42, in contrast, the centroid for the pre-weaning data was distinct from the centroids for the data from 7 days post weaning and 60 days of age, which overlapped.

We used the metagenomeSeq package in R to identify differentially abundant (DA) OTUs within the full dataset (1,121 OTUs) for each weaning group; we specifically compared the pre-weaning data and the data obtained 7 days after weaning. In the W14 group, there were 224 DA OTUs (Table S3). In the W21 group, this number increased to 484 (Table S4). In W28 and W42, there were 395 DA OTUs (Table S5) and 461 OTUs (Table S6), respectively. There was some degree of overlap among the DA OTUs (Figure S1), although there were unique OTUs in all the weaning groups (W14: 44, W21: 106, W28: 71, and W42: 107). Overall, Bacteroides, Ruminococcus, Oscillospira, and Clostridium were more abundant before weaning and Succinivibrio, Prevotella, and

Campylobacter were more abundant 7 days after weaning. Interestingly, Faecalibacterium prausnitzii was found to be highly abundant after weaning in all the weaning groups.

Effect of weaning age on F. prausnitzii abundance before and after weaning

In the full dataset, three OTUs were annotated as F. prausnitzii (OTU IDs 851865, 350121, and 525215). Since at least one of these OTUs was DA in most comparisons, we decided to explore the overall abundance of F.

prausnitzii by summing the abundances of the three OTUs for each sample.

We had previously normalized these data by log scaling the cumulative sum scaling (CSS) values obtained in metagenomeSeq. For each weaning group, there was a clear increase in F. prausnitzii abundance over time, and the highest abundances were observed in the W42 group (Figure 5). In the groups W14 and W21, there was a marked increase in abundance between weaning and 60 days of age; in the groups W28 and W42, abundance tended to be more stable 7 days post weaning. At weaning, F.

prausnitzii was most abundant in the W42 group, equivalently abundant at lower levels in the W21 and W28 groups, and least abundant in the W14 group. There were significant differences among the four weaning groups (ANOVA: p<0.05), and F. prausnitzii was more abundant before weaning in piglets weaned at a later age (Table S7). Indeed, piglets weaned at 14 days of age had the lowest abundance of F. prausnitzii before weaning, a pattern that persisted until 60 days of age. Post-hoc analysis found differences in the abundance of F. prausnitzii between the groups W14 and W42 before weaning and between various combinations of the weaning groups at 7 days post weaning and 60 days of age (Table S8).

Effect of weaning age on fecal microbiota diversity and composition before weaning

Before weaning, alpha diversity was significantly higher in the W42 group than in the other three groups (Tukey's HSD: p<0.05) (Table S9; W42 versus W14, W42 versus W21, and W42 versus W28). The same pattern was seen for richness, with an additional significant difference between the groups W14 and W28 (Table S9). Beta diversity was only significantly different between the W42 group and the groups W14 and W21 (Table S9). In the NMDS analysis, there were significant associations with litter and weaning group (p<0.05) (Figure S2A).

Furthermore, before weaning, there were 165 DA OTUs for the four weaning groups combined (Table S10). These OTUs belonged to the phyla Firmicutes, Bacteroidetes, and Proteobacteria and the genera Bacteroides, Ruminococcus, and Prevotella. There was some overlap among groups: 44 of the DA OTUs were shared (Figure S3).

Among the weaning groups, there was differential abundance of the phyla Tenericutes, Spirochaetes, Deferribacteres, and Fusobacteria (Table S11) S12).

and

Effect of weaning age on fecal microbiota diversity and composition at seven days post weaning

Seven days after weaning, there was no difference in alpha diversity and richness among the four weaning groups (Table S9). Beta diversity was significantly higher in the W14 group than in the other three groups, and the W42 group had the lowest beta diversity. The NMDS analysis found no differences among the groups (Figure S2B). There were a total of 165 DA OTUs (Table S13) that mainly belonged to the phyla Firmicutes, Bacteroidetes, and Proteobacteria and the genera Prevotella, Ruminococcus, Bacteroides, and Oscillospira. One of the F. prausnitzii

OTUs was more abundant in the groups W28 and W42. The weaning groups shared 25 OTUs (Figure S4), which were more heterogeneous than the OTUs shared by the groups prior to weaning; they belonged to the orders Clostridiales and Bacteroidales. In the analyses at the phylum and genus levels, only the genera Actinobacillus, Peptostreptococcus, and Klebsiella were differently abundant among the weaning groups (Table S14).

Effect of weaning age on fecal microbiota diversity and composition at 60 days of age

When the piglets were 60 days old, alpha diversity was significantly different between the groups W21 and W42 (p<0.05); richness and beta diversity did not vary based on weaning age (Table S9). Similarly, the NMDS analysis found no differences among weaning groups (Figure S2C). There were 54 DA OTUs (Table S15) that belonged to phyla Firmicutes, Bacteroidetes and Proteobacteria and, for the most part, the genera Prevotella, Ruminococcus, and Bacteroides.

Discussion

To the best of our knowledge, this study presents the first thorough comparison of fecal microbiota composition in piglets weaned at different ages, from 14 days (very early weaning) to 42 days (organic-like weaning).

We characterized patterns of microbiota diversity and composition from just before weaning to 60 days of age and showed that piglets weaned later had time to accumulate more diverse microbial communities, which contained higher abundances of potentially beneficial bacteria like F.

prausnitzii, before facing the difficult transition that is weaning.

Indeed, the F. prausnitzii OTUs were present in all the groups, regardless of weaning age, and they were significantly more abundant after weaning, when the gut microbiota diversified and matured. The abundance of the F.

prausnitzii OTUs tracked overall alpha diversity and richness. The W14 group had the lowest abundance of F. prausnitzii at all the sampling points, and the W28 and W42 groups had the highest abundance after weaning.

The W42 group also had the highest abundance of F. prausnitzii before weaning. Since we saw no signs of diarrhea in the W42 group after weaning, it might be hypothesized that F. prausnitzii contributes to the resilience of weaned piglets. Indeed, based on the results for the preweaning period, it appeared that the later-weaned piglets (W42) had a higher abundance of F. prausnitzii than did earlier-weaned piglets (W14).

The W14 group still had the lowest levels of F. prausnitzii at 60 days of age, indicating that very early weaning could have long-term effects on the abundance of this potentially beneficial species. Indeed, F. prausnitzii is considered to be one of the most promising next-generation probiotics (NGP) in humans because it improves gut health, notably by helping to treat inflammation-related diseases (Sokol et al., 2008). It has also been proposed that F. prausnitzii serves as an indicator of human intestinal health (Miquel et al., 2013) because declines in its abundance have been correlated with various diseases and disorders resulting from dysbiosis (Cao et al., 2014;Dave et al., 2011;Lopez-Siles et al., 2018;Martín et al., 2017;Miquel et al., 2016Miquel et al., , 2013;;Sitkin and Pokrotnieks, 2018). Levels of F. prausnitzii are lower in patients suffering from intestinal and metabolic disorders such as inflammatory bowel disease, irritable bowel syndrome, colorectal cancer, obesity, and celiac disease, among others [START_REF] Balamurugan | Real-time polymerase chain reaction quantification of specific butyrateproducing bacteria, Desulfovibrio and Enterococcus faecalis in the feces of patients with colorectal cancer[END_REF][START_REF] Furet | Differential adaptation of human gut microbiota to bariatric surgery-induced weight loss: links with metabolic and low-grade inflammation markers[END_REF][START_REF] Neish | Microbes in gastrointestinal health and disease[END_REF]Sokol et al., 2008). F.

prausnitzii has also been shown to have anti-inflammatory and protective effects in preclinical models of colitis (Martín et al., 2015). Overall, these findings agree with the hypothesis that piglets could benefit from having a higher abundance of F. prausnitzii in their gut microbiota prior to weaning because it could provide protection against post-weaning dysbiosis and help the gut microbiota transition to a new state of gut homeostasis. To confirm this hypothesis, it will be necessary to conduct further research where sample sizes are larger at each sampling point, and also to examine a broader diversity of environmental conditions and production systems.

In addition, because there are limitations associated with 16S rRNA gene sequencing and OTU assignments might not always be precise, it would be fruitful to use qPCR to quantify absolute levels of F. prausnitzii as well as to perform whole-metagenome sequencing to identify individual species strains.

Expanding our focus beyond F. prausnitzii, it has generally been shown that gut microbiota diversity and richness is positively correlated with gut health. In humans and pigs, enteric diseases, poor intestinal health, and intestinal inflammation are often associated with lower bacterial richness in the gut (Chang et al., 2008;Dou et al., 2017;Lozupone et al., 2013;[START_REF] Mccann | The diversity-stability debate[END_REF]Willing et al., 2010). Interestingly, our results showed that piglets in the W42 group had higher alpha diversity before weaning than did piglets in the other groups, and they also had higher alpha diversity at 60 days of age than did piglets in the W14 group. Such diversity might help additionally protect gut homeostasis at weaning. Beta diversity was the lowest in the W42 group before weaning, after weaning, and at 60 days of age, meaning that piglets in this group had more homogenous gut microbiota, even early on.

Our results confirm findings from previous studies that compared the gut microbiota of piglets before and after weaning [START_REF] Clemente | The impact of the gut microbiota on human health: an integrative view[END_REF][START_REF] Costa | Characterization of the fecal microbiota of pigs before and after inoculation with "Brachyspira hampsonii[END_REF][START_REF] Faith | The long-term stability of the human gut microbiota[END_REF][START_REF] Kim | Longitudinal investigation of the age-related bacterial diversity in the feces of commercial pigs[END_REF]Mach et al., 2015;Schokker et al., 2014;Turnbaugh et al., 2006). Notably, we also observed that the phyla Bacteroidetes and Firmicutes were dominant in the fecal microbiota of weaning pigs. These two taxa accounted for more than 90% of all the sequences obtained, like in prior studies examining the ileal, cecal, and fecal microbiota of weaning and weaned pigs [START_REF] Kim | Longitudinal investigation of the age-related bacterial diversity in the feces of commercial pigs[END_REF]Mach et al., 2015;[START_REF] Mccormack | Exploring a possible link between the intestinal microbiota and feed efficiency in pigs[END_REF]Schokker et al., 2014;[START_REF] Yang | Structure and Function of the Fecal Microbiota in Diarrheic Neonatal Piglets[END_REF]. In piglets, the gut microbiota diversifies after weaning, and a new equilibrium of the microbiota ecosystem is established that is based on rich and stable microbial communities (Katouli et al., 1997;Thompson et al., 2008). The NMDS analysis confirmed that piglets differed in their fecal microbiota before and after weaning, which concurs with results from past research showing that weaning is associated with drastic changes in the gut microbiota that have a general impact on the intestinal ecosystem (Dou et al., 2017;Mach et al., 2015).

We analyzed growth performance in the four weaning groups. Although there was an initial imbalance in mean birth weights among groups (animals were heavier in the W14 group), we found that weaning age affected growth: piglets in the groups W14, W21, and W28 lost weight after weaning. Post-weaning weights for the W42 group were not obtained until day 48, but its overall growth curve declined less dramatically than did the curves for the other three groups. Our results concur with those of previous studies in which weight loss was seen immediately after weaning (Al et al., 2017;[START_REF] Han | Evaluating the association between body weight and the intestinal microbiota of weaned piglets via 16S rRNA sequencing[END_REF]. Our study showed that, even at 60 days of age, piglets in the W14 group had lower body weight than piglets in the other groups, suggesting very early weaning might have long-term effects on growth performance. In addition, the W14 group (but not the other groups) displayed morbidity after weaning, resulting in the euthanasia of three animals in accordance with the study's ethical guidelines. Piglets in the W21, W28, and W42 groups all had more similar weights at 60 days of age, highlighting that the impact of weaning age on growth seems to be more limited after 21 days of age. Moreover, studies comparing two different weaning ages (14 days and 21 days) found that weaning age affected growth performance in a wean-to-finish facility, as well as behavioural and immunological responses to weaning and new social conditions after the nursery phase [START_REF] Davis | Effect of weaning age and commingling after the nursery phase of pigs in a wean-to-finish facility on growth, and humoral and behavioral indicators of well-being[END_REF]. In our study, some piglets in all the groups except W42 had diarrhea, confirming that late weaning could provide protection against intestinal issues. We thus confirmed that piglets appear to be more sensitive to diarrhea when they are weaned at an earlier age (Gresse et al., 2017;Lallés et al., 2007), and our results also sustain organic farming practices that promote late weaning to reduce the incidence of diarrhea [START_REF] Jensen | When to wean -Observations from Free-Ranging Domestic Pigs[END_REF][START_REF] Stolba | The identification of behavioural key features and their incorporation into a housing design for pigs[END_REF].

Conclusions

In conclusion, our results suggest that piglet gut health could be enhanced by late weaning (i.e., at 42 days of age), as it would give the gut microbiota more time to diversity prior to weaning. Even though we looked at a relatively small number of animals from a single farm, our results fit with what has been seen in response to organic farming practices, where piglets are weaned at older ages [START_REF] Bøe | The process of weaning in pigs: when the sow decides[END_REF][START_REF] Jensen | When to wean -Observations from Free-Ranging Domestic Pigs[END_REF][START_REF] Stolba | The identification of behavioural key features and their incorporation into a housing design for pigs[END_REF]. Implementing late weaning in conventional production systems would be challenging since pig farms are structured to wean animals at 21 or 28 days of age. However, it may be possible to obtain the benefits of late weaning by using nutritional strategies and/or probiotics to increase microbial diversity before weaning. Indeed, our results indicate that F. prausnitzii could be a promising probiotic for preventing health issues related to weaning dysbiosis, and the economic loss associated to a reduced growth yield. Our results also underscore that weaning piglets are a valuable model for studying how F. prausnitzii might affect intestinal health in humans.

Methods

Study animals and phenotypes

In (https://www.bioinformatics.babraham.ac.uk/projects/fastqc); the files were then analyzed using QIIME software (v. 1.9.1) (Caporaso et al., 2010) by using the subsampled open-reference OTU picking approach (Rideout et al., 2014). Singleton OTUs and OTUs representing less than 0.005% of the total number of sequences were removed from the dataset as suggested by the software developers (Bokulich et al., 2012). Chimeric sequences were identified using the BLAST algorithm and removed using QIIME. Samples with fewer than 10,000 reads after quality control procedures were eliminated from the study. On the day of weaning, 7 days after weaning, and at 60 days of age, the sample sizes were (respectively)

as follows: W14: 8, 8, and 3 animals; W21: 11, 11, and 6 animals; W28:

12, 12, and 5 animals; and W42: 11, 11, and 6 animals.

Biostatistical analyses

All our statistical analyses were performed in R (v. package [START_REF] Oksanen | Multivariate analysis of ecological communities in R: vegan tutorial[END_REF] was used to perform rarefaction analyses of the OTUs in each weaning group at each taxonomic level. Richness and diversity analyses were performed at the OTU level. Alpha diversity and beta diversity were calculated using the Shannon index and Whittaker's index, respectively. Richness was defined as the total number of OTUs present in each sample. Alpha diversity, beta diversity, and logtransformed richness were then analyzed using ANOVAs (aov function); post-hoc comparisons were performed with Tukey's HSD tests. We also used the vegan package to perform non-metric multidimensional scaling (NMDS): we calculated Bray-Curtis dissimilarity values and used the metaMDS function, which standardizes scaling, to assess differences in the overall diversity of fecal microbiota among samples. The env_fit function was used evaluate the statistical significance of the study variables within NMDS ordination space. These variables were sex, litter ID, piglet ID, and sampling point or weaning group. In addition, permutational multivariate analyses of variance were performed using distance matrices and the adonis function. The alpha level was p < 0.05.

OTU differential abundance testing was carried out with the metagenomeSeq package (Paulson et al., 2013). OTU counts were normalized using the cumulative sum scaling (CSS) method, and a zeroinflated Gaussian distribution mixture model (fitZig function) was employed to assess differences in relative OTU abundance; the significance level was set to a false discovery rate (FDR) lower than 0.05.

The model accounted for the different sampling points for each weaning group, and litter effect was included as a cofactor. The overall abundance of F. prausnitzii was estimated by summing the log-scaled CSS normalized abundances of the three F. prausnitzii OTUs (OTU IDs 851865, 350121 and 525215) for each sample. Differences in abundance were then evaluated using ANOVAs (aov function) and post-hoc comparisons were performed with Tukey's HSD tests.

Declarations

of JE. FRM interpreted the results and wrote the first draft of the manuscript under the supervision of CRG and JE. All authors read and approved the final manuscript.

Abstract

Enterotoxigenic Escherichia coli (ETEC) is the etiological agent of postweaning diarrhoea (PWD) in piglets. The SNPs located on the Mucine 4 (MUC4) and Fucosyltransferase 1 (FUT1) genes have been associated with the susceptibility to ETEC F4 and ETEC F18, respectively. The interplay between the MUC4 and FUT1genotypes to ETEC infection and the use of amoxicillin in modifying the intestinal microbiota during a natural infection by multi-resistant ETEC strains have never been investigated. The aim of this study was to evaluate the effects of the MUC4 and FUT1 genotypes and the administration of amoxicillin through different routes on the presence of diarrhoea and the faecal microbiota composition in piglets naturally infected with ETEC. Seventy-one piglets were divided into three groups: two groups differing by amoxicillin administration routesparenteral (P) or oral (O) and a control group without antibiotics (C). Faecal scores, body weight, presence of ETEC F4 and F18 were investigated 4 days after the arrival in the facility (T0), at the end of the amoxicillin administration (T1) and after the withdrawal period (T2). The faecal bacteria composition was assessed by sequencing the 16S rRNA gene. We described that MUC4 and FUT1 genotypes were associated with the presence of ETEC F4 and ETEC F18. The faecal microbiota was influenced by the MUC4 genotypes at T0. We found the oral administration to be associated with the presence of diarrhoea at T1 and T2. Furthermore, the exposure to amoxicillin resulted in significant alterations of the faecal microbiota. Overall, the MUC4 and FUT1 were confirmed as genetic markers for the susceptibility to ETEC infections in pigs. Moreover, our data highlight that group amoxicillin treatment may produce adverse outcomes on pig health in course of multi-resistant ETEC infection. Therefore, alternative control measures, able to maintain a healthy faecal microbiota in weaners are recommended.

Keywords: Antibiotic-resistance, Escherichia coli, FUT1, gut microbiota, MUC4, swine.

Introduction

Weaning is considered the main critical period for pigs raised in intensive farms (Lallés et al., 2007). This phase may be associated with the onset of gastrointestinal disorders with post-weaning diarrhoea (PWD), caused by Enterotoxigenic Escherichia coli (ETEC) that play a major role (Baker et al., 1997;Luppi, 2017). PWD leads to pig morbidity and mortality causing considerable economic losses to farmers worldwide (Fairbrother and Gyles, 2012).The ETEC strains possess fimbrial adhesins, identified as F4 or F18, that mediate microbial attachment to the intestinal epithelium (Luppi, 2017). These fimbriae allow ETEC to adhere to specific receptors on the brush border membrane of the small intestine enterocytes (Fairbrother and Gyles, 2012). Beside adhesion, ETEC strains secrete enterotoxins able to impair enterocyte functions by increasing cell cation exchanges and reducing water absorption [START_REF] Sun | Intestinal challenge with enterotoxigenic Escherichia coli in pigs , and nutritional intervention to prevent postweaning diarrhoea[END_REF], finally resulting in a severe diarrhoea.

Piglets are not equally susceptible to ETEC infection. Susceptibility to ETEC F4 has been associated to a single nucleotide polymorphism (SNP) located in intron 7 (g.13:8227C>G) of the Mucin 4 gene (MUC4) (Jørgensen et al., 2004;Luise et al., 2019;Rampoldi et al., 2011). Piglets with MUC4 G-genotypes express the F4 receptor and are considered susceptible to ETEC F4 infection, while piglets with MUC4 CC genotype are associated with the resistant phenotype (Jorgensen et al., 2003). On the other hand, susceptibility to the ETEC F18 infection appears to be dependent on the activity of the alpha-fucosyltransferase-1 (FUT1) gene, which is the candidate gene for the adhesion to F18 receptor. The g.6:54079560T>C SNP located on FUT1 gene has been associated with the susceptibility to ETEC F18 infection; piglets with FUT1 C-genotypes appear susceptible to ETEC F18 while piglets with FUT1 TT genotype are resistant to the infection (Meijerink et al., 1997;Muñoz et al., 2018;Vogeli et al., 1997;Wang et al., 2012).

At weaning, the gut microbiota of piglets is characterized by a severe compositional changes (Mach et al., 2015), which might impair the barrier effect exerted by symbiotic bacteria towards enteric pathogens (Konstantinov et al., 2006). Notably, the abrupt decrease of Lactobacillus spp. at weaning could increase the risk of enteritis, since bacteria belonging to this genus play a major role in disease prevention (Konstantinov et al., 2006). Moreover, the gut microbiota composition of piglets at weaning is also influenced by the host genetic background and by ETEC F4 and ETEC F18 infections (Bin et al., 2018;[START_REF] Messori | Effect of susceptibility to enterotoxigenic Escherichia coli F4 and of dietary tryptophan on gut microbiota diversity observed in healthy young pigs[END_REF][START_REF] Poulsen | Effects of alpha-(1,2)-fucosyltransferase genotype variants on plasma metabolome , immune responses and gastrointestinal bacterial enumeration of pigs pre-and post-weaning[END_REF]. Finally, the administration of antibiotics, which is often recorded in this production phase, impacts the microorganism abundance and may cause a severe disruption of the gut microbiota ecosystem [START_REF] Blaser | Antibiotic use and its consequences for the normal microbiome[END_REF][START_REF] Mulder | Environmentally-acquired bacteria influence microbial diversity and natural innate immune responses at gut surfaces[END_REF]Schokker et al., 2014;Soler et al., 2018;[START_REF] Zhang | Changes in the diversity and composition of gut microbiota of weaned piglets after oral administration of Lactobacillus or an antibiotic[END_REF].

In European farms, amoxicillin is the main antimicrobial molecule used at weaning, mainly to control ETEC and Streptococcus suis infections (Burch and Sperling, 2018). This antibiotic is currently used for therapeutic or metaphylactic purposes and it can be administered either by the parenteral or oral route, for animal group treatment. However, concerns have been expressed for the use of oral formulations, since they exert a selective pressure on the gut microbiota [START_REF] Kim | The intestinal microbiota: Antibiotics, colonization resistance, and enteric pathogens[END_REF][START_REF] Stanisavljevi | Oral neonatal antibiotic treatment perturbs gut microbiota and aggravates central nervous system autoimmunity in Dark Agouti rats[END_REF]Zhang et al., 2013). Consequently, antibiotic-resistant bacteria or resistance determinants may increase in the gut microbiota, making it a potential reservoir of antibiotic resistance. Strikingly, the oral administration of amoxicillin has been associated with an increase of extended-spectrum beta-lactamase (ESBL) E. coli in pigs [START_REF] Cameron-Veas | Impact of the Use of beta-Lactam Antimicrobials on the Emergence of Escherichia coli Isolates Resistant to Cephalosporins under Standard Pig-Rearing Conditions[END_REF]. Of greater concern is the spread of multi-drug resistant ETEC strains in European pig herds (Magistrali et al., 2018;Rosager et al., 2017;Smith et al., 2010). In this scenario, a full understanding of the impact of group antimicrobial treatments on gut health in field conditions is long overdue.

The interplay between the resistance/susceptibility genotypes to ETEC infection and the use of amoxicillin in modifying the intestinal microbiota during a natural outbreak of PWD has never been investigated.

The hypothesis of this study was that the host genotypes for MUC4 and FUT1 and the route of administration of amoxicillin could affect the development of PWD and the faecal microbiota composition in weaning piglets naturally infected by ETEC.

Materials and Methods

Animal experimental design

Animals until the end of the experiment (d16). The composition of the diet is shown in Table S1.

Animals arrived in the facility the day of weaning (d31, N=36 and d38, N=35). Animals were evaluated 4 days after their arrival (T0), following a 4-day period for acclimatization, at the end of the amoxicillin administration (T1) and again 7 days corresponding to the withdrawal period of the antibiotic (T2).

Individual faecal samples were collected and faecal consistency scores were individually evaluated at each time point. Faecal scores were categorized after visual observation of the certified veterinarian supervising the experiment as follows: 0= normal stools; 1= loose stools;

2= watery diarrhoea. The individual body weight was also recorded at each time point.

Microbiological culture, antimicrobial susceptibility testing

To evaluate the susceptibility profiles to antibiotics of the ETEC strains, standard bacteriological tests at each time point were performed.

Briefly, the primary isolation from individual faecal samples was carried out on blood agar plates (Blood Agar Base, Biolife Italiana Srl, Milan, Italy), supplemented with 5% sheep red blood cells. Plates were incubated at 37°C overnight. Haemolytic E. coli isolates were identified using standard biochemical procedures (RapidAPI32E, bioMérieux Italia Spa, Bagno a Ripoli, FI, Italia), followed by species-specific PCR as described in the following section "ETEC PCR for adhesin detection". The isolates resulting positive for the fimbriae factors F4 and F18 were tested for antimicrobial susceptibility using the agar diffusion method on Muller

Blood sample collection and DNA analysis from blood samples

Blood samples were collected by venepuncture of v. jugularis on all piglets at T0. Genomic DNA was extracted from blood samples following the procedure of the kit NucleoSpin Blood (Macherey Nagel-740951.250).

The Nanodrop instrument was used to assess the quality and quantity of the extracted DNA.

Genotyping of the g.13:8227C>G SNP located on the MUC4 gene and the g.6:54079560T>C SNP located on FUT1 gene was carried by using the PACE™ Genotyping approach (https://3crbio.com/wpcontent/uploads/2019/01/PACE-IR-User-Guide-v1.5.pdf).

To assess the genotype of the MUC4 gene, the following primers were

Faecal sample collection and DNA analysis from faecal samples

Faecal samples were collected from the piglet rectum at three different time points: at T0, at T1 and at T2. All faecal samples were directly frozen in liquid nitrogen and further stored at -80°C until use. Genomic DNA of each faecal sample was extracted the Qiagen QIAamp DNA stool kit, following the modified protocol of [START_REF] Dore | IHMS_SOP 06 V1: Standard operating procedure for faecal samples DNA extraction[END_REF].

The DNA extracted from faecal samples was analysed by PCR endpoint in order to assess the presence/absence of the genes encoding adhesins F4 and F18 (Casey and Bosworth, 2009).

Microbial profiling was performed using high-throughput sequencing of the V3-V4 hypervariable region of the 16S rRNA gene (2x250 bp pairedend reads) on an Illumina MiSeq platform following the standard Illumina sequencing protocol and by using primers PCR1F_343 (5'-CTTTCCCTACACGACGCTCTTCCGATCTACGGRAGGCAGCAG-3') and PCR1R_784

(5'-GGAGTTCAGACGTGTGCTCTTCCGATCTTACCAGGGTATCTAA TCCT-3'). The generated FastQ files were first quality checked though the FastQC software (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and then analysed using the Quantitative Insights Into Microbial Ecology (QIIME) v1.9.1 package (Caporaso et al., 2010) by following the open-reference sub-sampled OTU calling strategy (Rideout et al., 2014). Singleton

Operational Taxonomical Units (OTUs) and OTUs with a number of sequences less than 0.005% of the total number of sequences were removed from the dataset (Bokulich et al., 2012). Chimeric sequences were removed using QIIME and by using the BLAST algorithm. All samples with less than 10,000 post-quality control reads were removed from the analysis, which resulted in eliminating only one sample (pig number 622 sampled at T2).

Biostatistical analysis

Basic statistics for the analysis of pig weight were estimated in R v. 3.6.0 (TeamCore, 2018) by performing ANOVA analyses with the "aov" function. The Fisher test was used to correlate the MUC4 and FUT1

genotypes with the excretion of ETEC F4 and ETEC F18 and the faecal scores. Moreover, the Fisher test was carried out to evaluate the links between the presence of ETEC F4 and ETEC F18 with the faecal scores.

In our analyses, the faecal categories 0 and 1 were considered as "negative" and the score 2 as "positive" for the presence of diarrhoea.

Regarding the MUC4 and FUT1 genes, we have considered as "resistant" the animals MUC4CC and FUT1TT and "susceptible" the animals harbouring MUC4CG, MUC4GG, FUT1CT and FUT1CC genotypes.

Differences among the pig weight and the sex, age, litter of origin, administration routes, MUC4 and FUT1 genotypes, susceptibility to ETEC F4 and ETEC F18, and presence/absence of diarrhoea were assessed using hoc test using the Tukey's Honest Significant Differences (HSD) test.

For the analysis of microbiota composition, the biom OTU table was imported into R with Phyloseq package (v.1.28.0) (McMurdie and Holmes, 2013). Vegan v2.5-5 package [START_REF] Oksanen | vegan: Community Ecology Package[END_REF] was used for the rarefaction on the OTU level of each experimental group. Richness and diversity analyses were performed at the OTU level. Alpha diversity was calculated with Shannon index, beta diversity through the Whittaker's index and richness was evaluated as the total number of OTUs present in each sample. To assess the diversities, the ANOVA was performed on α and β diversity and on log10 richness using the "aov" procedure in R. The Tukey's HSD was also calculated. Vegan's Non-Metric Multidimensional Scaling (NMDS), using the Bray-Curtis distance and with the "metaMDS" function that standardizes the scaling in the result, was used to represent the global diversity of faecal microbiota composition between samples.

The function "envfit" in Vegan was used to fit environmental factors onto the NMDS ordination to compare the groups and evaluate the statistical significance. The permutational Multivariate Analysis of variance (PERMANOVA) using the Bray-Curtis distance was performed using the "adonis" function in order to assess the community differences between groups. The significance threshold was set at p< 0.05.

The differential abundance analysis was performed using the function "fitZig" in the metagenomeSeq (v.1.26.0) package at the OTU level (Paulson et al., 2013). The MUC4 genotype and the age at T0, the antimicrobial treatment at T1, the faecal score (categories: 0, 1, 2) and the antimicrobial treatment at T2 were taken into account in the model as cofactors. In order to make a pairwise comparison of differentially abundant OTUs between the experimental groups (C vs. P, C vs. O, P vs. O), we performed the differential abundance analysis at T1 and at T2, using "fitZig" function. The resulting differentially abundant (DA) OTUs have been plotted in Venn diagrams using Venny 2.1 [START_REF] Oliveros | Venny. An interactive tool for comparing lists with Venn's diagrams[END_REF].

Results

Microbiological culture and antimicrobial susceptibility testing

Results showed that the piglet groups were naturally infected by ETEC F4

(N =50) and F18 (N =20) at T0, while only F18 (N =61) was still detected at T1. Few animals were positive for ETEC F4 (N =3) and F18 (N =8) at T2 (Figure S2; Table S2). In particular, at T0 43 animals tested positive for ETEC F4 and negative for ETEC F18 while 7 piglets were positive for both; 8 animals were negative for both ETEC F4 and F18 and 13 animals were negative for ETEC F4 and positive for ETEC 18. Regarding the susceptibility testing, both the ETEC F4 and ETEC F18 isolates were classified as multi-resistant, showing resistance to beta-lactams (ampicillin and amoxicillin/clavulanic acid), phenicols (chloramphenicol), quinolones (ciprofloxacin and nalidixic acid), sulphonamides (sulphonamides and sulphamethoxazole/ trimethoprim) and tetracycline. The ETEC F4 isolates, differently from the ETEC F18 ones, were also resistant to streptomycin. Both ETEC F4 and ETEC F18 showed susceptibility to cephalosporins (cefazolin and cefotaxime), gentamicin and kanamycin.

Animal genotypes for MUC4 and FUT1

For MUC4, 19 pigs had MUC4 CC resistant genotype for ETEC F4 and 52 had the susceptible genotype for ETEC F4 (36 MUC4 CG and 16 MUC4 GG ).

As regards to FUT1, 13 FUT1 TT for ETEC F18 resistant pigs and 58 for ETEC F18 susceptible pigs (25 FUT1 CC and 33 FUT1 CT ) were observed (Figure S2). Overall, 52 and 58 pigs had a genotype susceptible to ETEC F4 and F18, respectively.

Forty-one pigs were susceptible to both ETECs (6 were MUC4 GG , FUT1 CC ; 6 were MUC4 GG , FUT1 CT ; 9 were MUC4 CG , FUT1 CC and 20 were MUC4 CG , FUT1 CT ). Nine pigs were susceptible for ETEC F4 while being resistant for F18 (two had MUC4 GG , FUT1 TT and 7 had MUC4 CG , FUT1 TT ). In addition, 17 pigs were resistant for ETEC F4 and susceptible for ETEC F18 (7 pigs were MUC4 CC , FUT1 CT and 10 pigs were MUC4 CC , FUT1 CC ). Two pigs were resistant to both ETECs, showing the variants MUC4 CC and FUT1 TT . The composition of the experimental groups according to the pigs' genotypes is reported in Table S3.

Animal phenotypes and correlation with genotypes

All phenotypic traits are summarized in table S2.

ANOVA tests on the individual body weights did not show significant differences among the groups at any of the three time points (p >0.05).

Moreover, the sex of the animals and the presence/absence of diarrhoea did not affect the weight of the animals (p >0.05). Using the ANOVA analysis, the weight was different between the two ages of the piglets at the three time points (T0, p=0.003; T1, p=0.0005; T2, p=0.0004) and consequently by litter of origin (T0, p=0.002; T1, p=0.0001; T2, p=0.0003). The younger piglets (d31) weighted less than the older piglets (d38) at weaning; however, animals were balanced in all the three groups.

At T0, MUC4 and FUT1 genotypes, presence of ETEC F4 and ETEC F18

did not affect the weight of animals.

At T1, ANOVA showed differences in the piglets body weight according to the FUT1 gene (ANOVA, p=0.01). The post-hoc test showed differences between FUT1CC and FUT1CT genotypes (Tukey's HSD, p= 0.01), but did not show differences between the comparison of FUT1CC vs. FUT1 TT and between FUT1 CT vs. FUT1 TT (Tukey's HSD, p>0.05).

MUC4 genotypes and the presence of ETEC F18 did not affect the weight of animals (p >0.05).

Moreover, at T2 we described that the weight was influenced by the FUT1 gene (ANOVA, p=0.02) which were referred to FUT1 CC and FUT1 CT (Tukey's HSD, p= 0.04) and not to FUT1 CC vs. FUT1 TT or FUT1 CT vs.

FUT1 TT (Tukey's HSD, p>0.05). MUC4 genotypes, the presence of ETEC F4 and ETEC F18 did not affect the weight of animals (p >0.05).

The faecal scores were recorded and the results at each time points are reported in Figure S2. At T0, we described 43, 11 and 17 animals with 0, 1 and 2 category of faecal score, respectively; at T1 we observed a higher number of animals with diarrhoea (faecal score 2; N=25) than without diarrhoea (faecal score 0, N=17; faecal score 1, N=29). At T2, the faecal consistencies of piglets fell in categories 0 (N=34) and 1 (N=27), with only 10 animals presenting diarrhoea.

At T0, Fisher tests showed that susceptible MUC4 genotypes were significantly associated with the presence of ETEC F4 (p=0.003) and the occurrence of diarrhoea (categories 0, 1= negative for diarrhoea; category 2= positive for diarrhoea) (p=0.01). However, the MUC4 resistant genotype was associated with an ETEC F4 negative status but also with a higher diarrhoea score. In this case, 9/19 animals with a MUC4 resistant genotype and 8/52 animals with a MUC4 susceptible genotype showed diarrhoea (Figure S2, Table 1). At T1, no ETEC F4 was detected. We found that FUT1 genotypes were significantly associated with the presence of ETEC F18 (p=0.01) but not with the faecal scores (p>0.05) at T1; however, the cases of diarrhoea were more frequent in susceptible FUT1 animals than in the resistant FUT1 piglets. At T2, we did not describe any effect taking into account the MUC4 and FUT1 genotypes associated with either the ETEC F4 and ETEC F18 infections or the faecal scores (Figure S2, Table 1). No association was found between the faecal score and the presence of ETEC F4 or F18 (p>0.05) at each time point.

Correlation between the antibiotic administration routes and the ETEC status

Antibiotic administration did not influence the ETEC F4 status of the animals at the three time points (p>0.05). Conversely, antibiotic administration showed a significant association with the status of ETEC 104 F18 at T1 (p=0.017), with the group P having less ETEC F18 positive pigs (N=17) than the other two groups (Group O, N=24 and Group C, N=20).

At T2 a difference in the number of ETEC F18 positive pigs was observed in the three groups (p=0.004): seven animals were ETEC F18 positive in the group treated orally, while only one ETEC F18 positive piglet was found in the group C and none in the group P. Moreover, the antibiotic treatments were associated with the faecal score at T1 (p=0.009) and at T2 (p=0.02), with more animals showing diarrhoea in the group O compared to the other two groups (Figure S2, Table 2). S3). The effect of the time resulted to be significant between time points, showing clusters in the NMDS plot (envfit test, p=0.004; Figure S4).

Differences in the faecal microbiota at T0 in piglets

The overall composition of the microbiota at T0 (NMDS, Figure 1 Since the presence of diarrhoea was correlated with the MUC4 gene, the MUC4 genotype and the age at T0 were used in the model of the differential analysis at the OTUs level, describing 68 DA OTUs (Table S5; S6; Figure S6B). Among them, 71 DA OTUs were more abundant in animals without diarrhoea and 82 OTUs were overabundant in piglets with diarrhoea. OTUs more abundant in pigs without diarrhoea belonged mainly to Ruminococcaceae and Christensenellaceae families.

Bacteroides, Parabacteroides, Fusobacterium genera and Pasteurellaceae family were predominant among the OTUs more abundant in the diarrhoeal animals.

Differences in the faecal microbiota at T1 in piglets

The overall composition of the microbiota at T1 (NMDS, Figure 2A) was mainly driven by the antibiotic treatment (Adonis test, p = 0.0009), whereas MUC4 and FUT1 genotypes, ages, faecal score and the status of ETEC F4 and ETEC F18 had no influence (Adonis test, p>0.05). The beta diversity was not different between the antimicrobial treatment groups (ANOVA test, p>0.05; Figure 2B). In the NMDS plot, the centroids of the group O appeared separated from the other two groups, resulting in a significant value (envfit test, p=0.02; Figure 2A). The alpha diversity at OTU level was different between the antimicrobial groups (ANOVA test, p=0.03; Figure 2B), showing a lower alpha diversity in the group O.

Nevertheless, the observed microbial richness did not show differences between the antimicrobial treatment groups (ANOVA test, p>0.05; Figure 2B).

The antibiotic administration groups had 187 DA OTUs (Table S7; Figure S6C) in metagenomeSeq analyses. There were several OTUs annotated as Lactobacillus spp. in the whole dataset. Since at least one OTU was found DA in most comparisons between experimental groups, we decided to further explore the global abundance of Lactobacillus spp. by adding the abundances of the OTUs in the whole dataset at T1 (OTUs 292057, 24271, 725198, 536754, 588197, 549756, 553352, 302975, 703741, 807795).

Normalized global abundance of Lactobacillus in each group clearly showed an increase of abundance in the group C and in the group P comparing to the group O (Figure 3A). Accordingly, ANOVA analyses showed significant differences (p=8.56 x 10-5) among the three groups at the OTUs level. In addition, the post-hoc test showed differences between the O vs. C group (Tukey's HSD, p=0.0001), P vs. O group (Tukey's HSD, Abundances were calculated as the addition of normalized for OTUs annotated as Lactobacillus spp. in the whole dataset (MetagenomeSeq R package). The notched boxplots displays the confidence interval around the median. If two boxes' notches do not overlap there is 'strong evidence' (95% confidence) their medians differ and consequently the difference is described as "statistically significant at the .05 level".

overlapping DA OTUs among the different comparisons are showed (Figure 4C). In the DA OTUs belonging to the O vs. C comparison, we have described Prevotella copri, Ruminococcus and Lactobacillus to be more abundant in the C than in the O group.

Discussion

The present study investigates a common situation occurring in commercial pig herds during the weaning period, when animals are naturally infected by ETEC strains and simultaneously treated with antibiotics. The post-weaning period is associated with multiple stressors, causing a faecal microbiota dysbiosis, which is among the leading causes of post-weaning diarrhoea in piglets. The study was focused on the interactions among the host genetics, the phenotype traits and the faecal microbiota composition in field conditions.

In our study, the weight gain was not affected by the genotypes of animals:

this finding is in accordance with other reports [START_REF] Casini | Oral challenge with E . coli K88 as a tool to assess growth and health performance in feeding trials of-weaned pigs to assess growth and health performance[END_REF][START_REF] Poulsen | Effects of alpha-(1,2)-fucosyltransferase genotype variants on plasma metabolome , immune responses and gastrointestinal bacterial enumeration of pigs pre-and post-weaning[END_REF]. We found an association between a susceptible genotype for MUC4 gene and the shedding of ETEC F4, confirming the role of this gene in the host susceptibility to the infection. Similarly, we showed an association between the susceptible FUT1 genotype and the presence of ETEC F18. The association of the MUC4 and FUT1 genes with diarrhoea have been largely described in literature [START_REF] Casini | Oral challenge with E . coli K88 as a tool to assess growth and health performance in feeding trials of-weaned pigs to assess growth and health performance[END_REF]Jørgensen et al., 2004;Luise et al., 2019;Meijerink et al., 1997;[START_REF] Poulsen | Effects of alpha-(1,2)-fucosyltransferase genotype variants on plasma metabolome , immune responses and gastrointestinal bacterial enumeration of pigs pre-and post-weaning[END_REF]Vogeli et al., 1997;[START_REF] Zhang | Oral Administration of a Select Mixture of Bacillus Probiotics Affects the Gut Microbiota and Goblet Cell Function following Escherichia coli Challenge in Newly Weaned Pigs of Genotype MUC4 That Are Supposed To Be Enterotoxigenic E. coli F4ab/ac Receptor[END_REF]. However, the MUC4 resistant genotype was characterized by a higher diarrhoea score, which is in contrast with a previous study (Luise et al., 2019). It should be noted that a small percentage of animals with the resistant genotype could show susceptible phenotypes (Joller et al., 2009) and this may explain our findings. Likewise, the susceptible FUT1 genotype was not associated with the presence of diarrhoea. In this experiment, we decided to use naturally infected piglets, therefore the infectious load was not homogeneous in the animals and this has to be considered as a possible source of bias in our study. In addition, dysbiosis, which is associated with diarrhoea, is commonly reported in this phase and may have confounded our results (Gresse et al., 2017;Lallés et al., 2007). Taking together, our results confirm the role of host genotype on the susceptibility to ETEC infection, but our data suggest that other factors may play a role in determining the presence of diarrhoea in field conditions.

The investigation on the faecal microbiota composition showed that in animals without antimicrobial treatments during weaning, the intestinal microbiota is mainly influenced by the MUC4 genotypes, as reported in previous studies (Luise et al., 2019;[START_REF] Messori | Effect of susceptibility to enterotoxigenic Escherichia coli F4 and of dietary tryptophan on gut microbiota diversity observed in healthy young pigs[END_REF]. We associated Actinobacillus porcinus to the MUC4 resistant group. Interestingly, Actinobacillus porcinus has been described in weaned piglets with a high weight gain (Nowland et al., 2019), thus confirming its beneficial role in porcine gut health. Contrary to what reported by [START_REF] Messori | Effect of susceptibility to enterotoxigenic Escherichia coli F4 and of dietary tryptophan on gut microbiota diversity observed in healthy young pigs[END_REF], we did not described Clostridium barlettii in the resistant MUC4 piglets, in accordance to the recent study of Luise et al., (2019). Furthermore, the Oscillospira genus was also more abundant in the resistant MUC4 animals:

this is not surprising since this genus belong to the Ruminococcaceae family which usually increases after weaning and it is associated with a non-dysbiotic gut [START_REF] Frese | Diet shapes the gut microbiome of pigs during nursing and weaning[END_REF][START_REF] Huang | Dynamic Change of Gut Microbiota During Porcine Epidemic Diarrhoea Virus Infection in Suckling Piglets[END_REF]Mach et al., 2015).

Moreover, we described a different composition of the faecal microbiota in diarrhoeic animals compared to non-diarrhoeic animals, confirming the role of dysbiosis in the development of diarrhoea. DA OTUs showed that in the piglets with diarrhoea the Bacteroides, Parabacteroides, Fusobacterium genera and the bacteria belonging to the Pasteurellaceae family dominated. Our results about Fusobacterium is in accordance with what already reported in literature, where a higher abundance of this genus in dysbiotic animals than in healthy piglets is described [START_REF] Huang | Dynamic Change of Gut Microbiota During Porcine Epidemic Diarrhoea Virus Infection in Suckling Piglets[END_REF].

Finally, we confirmed the role of age at weaning as a major influencer of the intestinal microbiota in piglets, as reported in previous papers [START_REF] Bian | Age, introduction of solid feed and weaning are more important determinants of gut bacterial succession in piglets than breed and nursing mother as revealed by a reciprocal cross-fostering model[END_REF]Massacci et al., Submitted;Soler et al., 2018). In our study, we described a more homogeneous and richer microbiota composition in the oldest piglets compared to the younger ones, which is in accordance with other finding produced by the same group (Massacci et al., Submitted).

Besides the genotype, the antibiotic treatment seems to have an effect on the presence of diarrhoea at T1 and T2. Pigs administered with amoxicillin were at higher risk for diarrhoea when compared to non-treated piglets.

Likewise, the risk of shedding ETEC F18 was higher in piglets treated with amoxicillin by the oral route than in not-treated animals or piglets with parenteral administration route. Amoxicillin could not exert an antibacterial effect on the ETEC strains, since both the ETEC F4 and ETEC F18 were resistant to this antibiotic.

On the contrary, the amoxicillin treatment affected the faecal microbiota of piglets, at T1 and T2. The amoxicillin exposure resulted in significant alterations of the faecal microbiota population evaluated immediately after the end of the treatment, showing a lower alpha diversity in the orally administered group and thus confirming a more direct effect on the microbiota composition. The shifts were different according to the two administration routes. In the group that received amoxicillin orally, we described a decreased abundance of the commensal Lactobacillus. This finding is in accordance with what was reported in a previous study (Connelly et al., 2018), where a lower abundance of Lactobacillus was associated with the administration of amoxicillin through the oral route. This is consistent with the clinical activity of amoxicillin (Burch and Sperling, 2018), which may affect the abundance of Gram-positive commensals, such as Lactobacillus species. Moreover, it has been described that the abrupt decrease of Lactobacillus spp. at weaning could increase the risk of enteritis, since bacteria belonging to this genus play a major role in disease prevention (Konstantinov et al., 2006). Our data suggest that the oral administration of amoxicillin can deeply modify the faecal microbiota, therefore reducing its barrier effect towards ETEC infection and finally resulting in an increased colonization by the pathogen. The same effect was not recorded after a parenteral administration, since the faecal microbiota of piglets in the group treated by the parenteral route were close to the one of the control group. After the withdrawal period of amoxicillin, the control group showed a higher abundance of OTUs belonging to the Lactobacillus genus compared to both groups administered with amoxicillin, demonstrating that even the parenteral administration had a long-term effect on the abundance of Lactobacillus in piglets gut.

However, the differential analysis after the withdrawal period confirmed the parenteral administration of amoxicillin had a lower impact on the faecal microbiota composition compared to the oral administration. In fact, taking the control group as a reference, the number of differentially abundant OTUs was higher in the group receiving amoxicillin by the oral route than in the one receiving amoxicillin by the parenteral route. In our investigation, we have described that the control and the parenteral administered group had a higher abundance of Prevotella copri, Ruminococcus and Lactobacillus species compared to the oral administered group, in accordance with previous studies (Connelly et al., 2018;Konstantinov et al., 2006). These results highlight that the microbiota composition of the intestine of piglets is highly affected by the antimicrobial administrations by the oral route.

It has to be noted that in commercial pig herds, amoxicillin is mainly administered through feed or water as a metaphylactic treatment to control

Streptococcosis and PWD (Burch and Sperling, 2018;Haas and Grenier, 2016;Waack and Nicholson, 2018). Amoxicillin is currently considered an extremely valuable antimicrobial in both human and animal medicine and remains in the critically important category of antibiotics by the World Health Organization (WHO, 2017). In our study, the ETEC F4 and ETEC F18 were multi-drug resistant which is a common feature of ETEC strains in Europe (Magistrali et al., 2018). When amoxicillin is used in group treatment, there is the risk of creating a selective pressure favourable to amoxicillin-resistant ETEC strains, thus making colonization easier. Since pathogenic bacteria are becoming increasingly resistant to antimicrobials, new practises, aimed to limit the administration of antimicrobials, should be encouraged.

In our study, we confirm that the MUC4 and FUT1 genotypes are associated with the susceptibility to ETEC F4 and F18 infection, respectively. The association between diarrhoea and the piglets' FUT1 genotype was not shown, probably due to the presence of multiple variables at the same time. Overall, the MUC4 and FUT1 were confirmed as genetic markers for the susceptibility to ETEC infections in pigs.

Moreover, our data highlight that group amoxicillin treatment may produce adverse outcomes on pig health in course of multi-resistant ETEC infection and this effect is stronger when the antibiotic is orally administered than parenterally. Alternative control measures, such as selection of resistant genotypes or vaccination, should be included in farm management practices to preserve a balanced and stable gut microbiota in weaners. (H) Bar plot of ETEC F4 represented in each of the MUC4 genotypes identified as resistant (R) and susceptible (S). For each MUC4 genotype, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T1: negative (green) and positive (red); (I) Bar plot of ETEC F4 represented in each of the MUC4 genotypes identified as resistant (R) and susceptible (S). For each MUC4 genotype, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T2: negative (green) and positive (red); (L) Bar plot of ETEC F18 represented in each of the FUT1 genotypes identified as resistant (R) and susceptible (S). For each FUT1 genotype, the bar plot represents the number of individuals ascribed to each ETEC F18 status at T0: negative (green) and positive (red); (M) Bar plot of ETEC F18 represented in each of the FUT1 genotypes identified as resistant (R) and susceptible (S). For each FUT1 genotype, the bar plot represents the number of individuals ascribed to each ETEC F18 status at T1: negative (green) and positive (red); (N) Bar plot of ETEC F18 represented in each of the FUT1 genotypes identified as resistant (R) and susceptible (S). For each FUT1 genotype, the bar plot represents the number of individuals ascribed to each ETEC F18 status at T2: negative (green) and positive (red); (O) Bar plot of diarrhoea status represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each diarrhoea status at T0: score 0 (green), score 1 (orange) and positive (red); (P) Bar plot of diarrhoea status represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each diarrhoea status at T1: score 0 (green), score 1 (orange) and positive (red); (Q) Bar plot of diarrhoea status represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each diarrhoea status at T2: score 0 (green), score 1 (orange) and positive (red). 2).

Declarations

Acknowledgements

Table S9: Differentially abundant (DA) OTUs when comparing O (oral administrated) vs. C (control) group at T1.DA OTUs were used to be plotted in the Venn diagram (Figure 2).

Table S10: Differentially abundant (DA) OTUs when comparing P (parenteral administrated) vs. O (oral administrated) group at T1. DA OTUs were used to be plotted in the Venn diagram (Figure 2).

Table S11: Differentially abundant OTUs when comparing the experimental groups at T2.

Table S12: Differentially abundant (DA) OTUs when comparing P (parenteral administrated) vs. C (control) group at T2. DA OTUs were used to be plotted in the Venn diagram (Figure 4).

Table S13: Differentially abundant (DA) OTUs when comparing O (oral administrated) vs. C (control) group at T2. DA OTUs were used to be plotted in the Venn diagram (Figure 4).

Table S14: Differentially abundant (DA) OTUs when comparing P (parenteral administrated) vs. O (oral administrated) group at T2. DA OTUs were used to be plotted in the Venn diagram (Figure 4).

Weaning can be considered as the period that causes stress to the pigs during rearing. Among the stresses, it includes a sudden shift from the milk diet to a cereal-based diet, the abrupt separation from the sows, and other environmental changes like the mixing of several litters in a single production slot [START_REF] Pluske | Gastrointestinal tract ( gut ) health in the young pig[END_REF][START_REF] Pluske | A modification to the isotope-dilution technique for estimating milk intake of pigs using pig serum[END_REF]. All this occurs when the immune system is still not mature and the thermoregulation and the digestive capacity are not well managed by the young piglets. Beyond this, the gut microbiota composition suffers also from drastic shifts that can result in an increased risk to pathologies, especially to enteric diseases.

In the present thesis, enteric disorders in piglets throughout the weaning period have been investigated, analysing the gut microbiota modifications related to different weaning ages and amoxicillin administrations during the colibacillosis. In this section, the main results of the PhD project will be discussed from biological and technical perspectives and, then a summary of challenges and opportunities for the prevention of piglet weaning diarrhoea will be proposed.

On microbiota's role in the post-weaning diarrhoea of piglets

In intensive farming systems, piglets are weaned much earlier than in a natural environment and several studies comparing different weaning strategies have shown that increasing weaning age improved both health and growth. Delaying the age at weaning in production farms has been proposed as a possible strategy to modulate and decrease the weaningassociated problems (Früh, 2011), as a measure to cope with the future necessary parsimonious use of antibiotics. However, only few studies have been performed investigating how early life management affects the early-life establishment of the pig gut microbiota together with the occurrence of enteric disorders.

In our first study, different practises of weaning have been investigated, describing the gut microbiota composition in piglets weaned at different ages (Figure 6), ranging from ultra-early weaning (14 days old), main weaning ages in pig intensive farms (21 and 28 days old) and to organiclike weaning (42 days of age). This study was carried out in antibiotic-free and pathogen-free conditions, allowing us to study the interaction of the gut microbiota composition and the weaning ages without other affecting determinants. In contrast, in our second study, we investigated antibiotic treatment alternatives in a context of natural infection with Enterotoxigenic E. coli. Interestingly, the study comparing different weaning ages showed that animals weaned late (at 42 days of age) presented no diarrhoea and an increased gut microbiota diversity. These results could suggest that late weaning provides a competitive advantage to piglets accumulating a higher diversity of potentially beneficial microbes prior to the stressful and risky weaning transition. Since no diarrhoea was observed for the piglets weaned at 42 days of age, we assumed that weaning at early age constitutes a risk factor for having animals less robust against enteric disorders. Since our study was carried out on a small number of animals, a wider investigation evaluating if a late weaning could be protective to pathogen colonization, could represent an excellent starting point to confirm our findings and provide to the farmers consistent data on possible health benefits deriving from a modulation of existing weaning practices.

Rethinking the age at weaning should be considered in the design of new intensive herds as a "good practice" to improve robustness and health status of animals, even if it could be a difficult issue to overstep by farmers having existing facilities, as it will be analysed later in the discussion.

Late-weaned animals were characterized by higher richness at preweaning, enhancing a protective effect on the gut homeostasis. In fact, several studies stated that a stable gut microbiota composition is correlated with a higher richness compared to enteric diseases and unhealthy or inflammatory states often related with a lower richness of bacteria (Chang et al., 2008;Dou et al., 2017;Lozupone et al., 2013;Willing et al., 2010).

The most practically relevant finding obtained in the study was the detection of an increase of F. prausnitzii relative abundance in the piglets weaned at 28 and 42 days old. We hypothesize that F. prausnitzii and the absence of diarrhoea status in this group of animals could represent a key factor for the increase of piglets' resilience. F. prausnitzii abundance is correlated with the establishment of primo-colonizing bacteria that create an adequate environment in a strictly anaerobic condition [START_REF] Hopkins | Characterisation of intestinal bacteria in infant stools using real-time PCR and northern hybridisation analyses[END_REF]. Moreover, it should be taken into account that the presence of F.

prausnitzii along the GIT may also result from a combination of environmental factors such as other commensal species, redox mediators, oxygen concentration, mucus layer as well as bile salt concentrations and pH [START_REF] Lopez-Siles | Cultured representatives of two major phylogroups of human colonic Faecalibacterium prausnitzii can utilize pectin, uronic acids, and host-derived substrates for growth[END_REF].

In literature, indeed, it is well-established that F. prausnitzii plays an important role in GIT homeostasis and appears as less abundant in enteric pathological status, which makes it a gut health biomarker (Miquel et al., 2013). In fact, F. prausnitzii depletion is correlated with CD, IBD, CRC and IBS (Cao et al., 2014;Dave et al., 2011;Lopez-Siles et al., 2018, 2017, 2015, 2014;Martín et al., 2017Martín et al., , 2015;;Miquel et al., 2016Miquel et al., , 2013;;Sitkin and Pokrotnieks, 2018;[START_REF] Sokol | Low counts of Faecalibacterium prausnitzii in colitis microbiota[END_REF]Sokol et al., , 2008)).

Considering their beneficial effects on GIT, F. prausnitzii together with Akkermansia municiphila, Bacteroides spp. and Clostridium butyricum are now being studied as NGP, both in animals and humans [START_REF] Chang | Next generation probiotics in disease amelioration[END_REF][START_REF] Langella | Editorial : Next-Generation Probiotics : From Commensal Bacteria to Novel Drugs and Food Supplements[END_REF]. While most used probiotics are generally recognised as safe and some of them show beneficial effects in the homeostasis of gut microbiota, results obtained about the prevention or even the treatment of specific diseases remain marginal [START_REF] Chang | Next generation probiotics in disease amelioration[END_REF]. Based on these findings, identification and characterization of novel and disease-specific NGP are urgently needed [START_REF] Chang | Next generation probiotics in disease amelioration[END_REF].

However, it has to be considered that the inclusion in the Qualified Presumption of Safety (QPS) Microorganisms list of EFSA, for NGPs, will be a crucial stage and it might be difficult considering the lack of data about their safety if used in both animal and humans [START_REF] Brodmann | Safety of novel microbes for human consumption: Practical examples of assessment in the European Union[END_REF][START_REF] Saarela | Safety aspects of next generation probiotics[END_REF]. Overall, while technical and bureaucratic issues are being tackled, it would be interesting to perform new studies aiming at evaluating the use of F. prausnitzii as a tool for enhancing the gut health of livestock and whether it is able to prevent the outcomes of enteric diseases. Application at large scale of new probiotic strategies promoting gut eubiosis could represent a valuable approach even to achieve the reduction of drug use in farms, fighting antimicrobial resistance and costs for farmers.

In a complementary approach, our second article investigated a common situation occurring in commercial pig herds during the weaning period:

antibiotic administration and colibacillosis caused by MDR ETEC strains at weaning (Figure 7). PWD is mainly caused by ETEC F4 and ETEC F18 (Baker et al., 1997;Luppi, 2017) being responsible of pig morbidity and mortality, causing considerable economic losses to farmers worldwide (Fairbrother and Gyles, 2012). Different questions were investigated: i) the host genotype versus ETEC F4 and ETEC F18 infection ii) the outbreak of colibacillosis against which antibiotics are usually administered to weaning piglets and iii) the recent spread of MDR bacteria focused the attention on antibiotic resistance, one of the world's most pressing public health issue. Highly Important; iii)

Important. Antibiotics belonging to the first category are not allowed for the veterinary usage. In June 2017, the EU Commission adopted the new One Health Action Plan against Antimicrobial Resistance and the theme 'reduce, replace and re-think' has been created by the EMA and EFSA for a new responsible antibiotic usage in livestock production (Murphy et al., 2017).

The main aims of these plans are: i) reduce antimicrobial consumption; ii)

reduce the usage of antimicrobials in animals with alternative measures; iii) use critically important antimicrobials for human medicine in animals only as a last resort; iv) re-think the livestock system implementing farming practices to prevent the introduction and spread of disease. All these measures are essential for the future of animal and public health.

For this reason, management practises should be implemented at farm levels to limit the spread of MDR bacteria and infections when the use of antibiotic is still essential. Thus, in the second study, we decided to include amoxicillin administration, one of the most prescribed antibiotic in commercial pig herds at weaning for treatment and control of severe and systemic infections (Burch and Sperling, 2018;Haas and Grenier, 2016;Waack and Nicholson, 2018). Since amoxicillin is not included in the CIA list, it remains available for veterinary medicine. Nevertheless, it is recommended that its use takes place under responsible use considerations, such as after laboratory diagnosis, culture and sensitivity testing (WHO, 2017). Oral administration is by far the most common route of administration for antimicrobials in pigs [START_REF] Callens | Associations between a decreased veterinary antimicrobial use and resistance in commensal Escherichia coli from Belgian livestock species ( 2011 -2015 )[END_REF][START_REF] Callens | Prophylactic and metaphylactic antimicrobial use in Belgian fattening pig herds[END_REF][START_REF] Merle | Monitoring of antibiotic consumption in livestock : A German feasibility study[END_REF]. Several studies reported that oral administration of antimicrobials increases the risk of AMR [START_REF] Burow | Oral antimicrobials increase antimicrobial resistance in porcine E . coli -A systematic review[END_REF]Zhang et al., 2013). The oral route is usually associated with a suboptimal administration, meaning a non-correct usage and dosage of the molecule, often resulting in an overuse of antibiotics in healthy pigs. In fact, sick animals usually do not assume the normal ratio of daily feed and, when the medication is supplied in pig feed, it is more difficult to achieve the correct dose of antibiotics.

In intensive herds, amoxicillin is mainly prescribed to treat streptococcosis by oral route, but it is common to find in the same herd two contemporary infections in which streptococcosis coexists with colibacillosis.

Considering what is described above, the second article is based on a common situation frequently occurring in commercial pig herds during the weaning period: when animals are naturally infected by ETEC strains and treated with amoxicillin. Since amoxicillin is administrated by oral route, our hypothesis was that a different administration route, such as the parenteral one, could differently affect the enteric disorders during a natural infection of ETEC. Different studies have been carried out on laboratory animals investigating different amoxicillin administration routes [START_REF] Aguilar | Effects of Amoxicillin Subinhibitory Concentrations on the Cross-Protection Developed by Pneumococcal Antibodies in Mouse Sepsis Caused by an Amoxicillin-Resistant Serotype 6B Streptococcus pneumoniae Strain[END_REF][START_REF] Marx | Antibiotic Administration in the Drinking Water of Mice[END_REF]Zhang et al., 2013).

To the best of our knowledge, this is the first paper in pigs, in which the oral antibiotic treatment was compared with the parenteral administration.

The results showed a major impact on the health status of animals, with oral antibiotics being correlated with a higher risk of diarrhoea and a higher shedding of ETEC F18, if compared to parenteral administration (note that the ETEC strains present in the animals were resistant to amoxicillin).

Moreover, the alpha diversity, which weighs both microbial community richness (number of different species) and evenness (equitability), was found significantly lower in animals treated by oral route by comparison to the parenteral administration and the control group. This finding is coherent with the direct effect on the gut microbiota composition exerted by the oral administration. Alike, a decreased abundance of the commensal Lactobacillus was described in the group treated by oral route. This finding is in accordance with a previous study (Connelly et al., 2018) in which a lower abundance of Lactobacillus was associated with the oral administration of amoxicillin, even though parental administration was not included for comparison. Amoxicillin, according to its pharmacological activity, affects the abundance of Gram-positive commensal bacteria (Burch and Sperling, 2018) and this effect is thus positively effective when the disease is caused by a Gram-positive bacterium. However, different Gram-positive bacteria, such as the Lactobacillus genus, are considered essential bacteria for maintaining the intestinal eubiosis and play a major role in disease prevention. The decrease of Lactobacillus spp. is frequently associated with an increased risk of enteritis at weaning (Konstantinov et al., 2006). The same trend of the oral treatment was not recorded after a parenteral administration and the faecal microbiota of parenteral administrated piglets was comparable to the control group. After the withdrawal period of amoxicillin (7 days), the control group showed a higher abundance of OTUs belonging to the Lactobacillus genus compared to both amoxicillin treated groups, proving that even the parenteral administration exerts a long-term effect on the abundance gut bacteria.

Beyond Lactobacillus, comparing the gut microbiota compositions among groups, we described how control and parenteral administered group showed a higher abundance of Prevotella copri and Ruminococcus spp. compared to the orally treated group, in accordance with previous published data (Connelly et al., 2018;Konstantinov et al., 2006). Globally, our results highlight that the faecal microbiota composition of piglets is highly affected by the oral administration of the amoxicillin.

It is important to consider that even in absence of an antimicrobial administration other factors can influence microbiota diversification.

Enteric disorders, also caused by colibacillosis, are differently affected by the host genotype, and it is known that animals are not equally susceptible to this infection. For these reasons, the interactions among the host genetics, the phenotype traits, such as the presence of diarrhoea and the faecal microbiota composition in animals naturally infected with ETEC F4 and ETEC F18, were also investigated. Genetic difference exists for susceptibility to ETEC F4 and ETEC F18 infection in piglets and MUC4 and FUT1 represent the best generally accepted marker genes (Jørgensen et al., 2004;Luise et al., 2019;Muñoz et al., 2018;Rampoldi et al., 2011;Wang et al., 2012). In our study, the association of the MUC4 and FUT1 genes with the shedding of ETEC F4 and ETEC F18 agreed with reported studies (Joller et al., 2009;Jørgensen et al., 2004;Luise et al., 2019;Muñoz et al., 2018;Rampoldi et al., 2011;Wang et al., 2012).

Nevertheless, in contrast to data reported in literature, we described an association among the MUC4 resistant genotype and the presence of diarrhoea. Jørgensen et al., (2004) reported the possibility to have resistant genotypes with susceptible phenotypes, which would explain our findings.

Likewise, the presence of diarrhoea was not associated with the susceptible FUT1 genotype, contrary to previous results (Luise et al., 2019;Wang et al., 2012). We hypothesize that in our case the fact of concomitant ETEC F4 and F8 infections, plus the resistance to amoxicillin showed by these strains, could interfere to the expected results. In addition, the variability of gut microbiota composition before the infection could have had a role in the outcome of diarrhoea and infection susceptibility. Despite the lack of results of ETEC in the literature, in the case of Salmonella (Argüello et al., 2019(Argüello et al., , 2018b;;E Barba-Vidal et al., 2017;[START_REF] Drumo | Salmonella enterica Serovar Typhimurium Exploits Inflammation to Modify Swine Intestinal Microbiota[END_REF] and Clostridium difficile [START_REF] Grzeskowiak | Developing Gut Microbiota Exerts Colonisation Resistance to Clostridium ( syn . Clostridioides ) difficile in Piglets[END_REF][START_REF] Grzeskowiak | Formula Feeding Predisposes Neonatal Piglets to Clostridium difficile Gut Infection[END_REF][START_REF] Jurburg | Successional Dynamics in the Gut Microbiome Determine the Success of Clostridium difficile Infection in Adult Pig Models[END_REF] infections, the correlation between the infection and the gut microbiota composition is well defined.

In this experiment, we enrolled animals, which were naturally affected by ETEC infection, meaning that bacterial load was not homogeneous among piglets. This is a limit of our investigation, since it may have increased the variation of the parameters within the experimental groups, thus reducing the power of our study. At the same time, compared to an experimental infection, the enrollment of naturally infected piglets better reflects the conditions occurring on the field during weaning. In our study, both ETEC F4 and ETEC F18 were classified as MDR which is a common feature of ETEC strains Worldwide [START_REF] Hedegaard | Purified natural pig immunoglobulins can substitute dietary zinc in reducing piglet post weaning diarrhoea[END_REF][START_REF] Jiang | Genotypes and Antimicrobial Susceptibility Profiles of Hemolytic Escherichia coli from Diarrheic Piglets[END_REF][START_REF] Luppi | Antimicrobial Resistance of F4 + Escherichia Coli Isolated from Swine in Italy[END_REF]Magistrali et al., 2018;Rosager et al., 2017;Smith et al., 2010). In this scenario, the use of amoxicillin could take over the ecological niche and exert a selective pressure on the resistant pathogen strains. Administering amoxicillin through oral route could exert a selective pressure amending the gut microbiota and open the gate to a higher risk of pathogen colonization. Consistently with the previous study, even in the second study, animals were weaned at different ages and the beneficial role of a late weaning age was confirmed. A more homogeneous and richer microbiota composition in the late weaned piglets was described.

On technical choices for the study of gut microbiota in our work

For a better understanding of the results obtained in the two trials performed in this PhD project, it is useful to take into account the two approaches to metagenomic analysis of microbial communities that are available nowadays: i) Whole (meta-)Genome Sequencing (WGS) and ii)

16S rRNA gene fragment analysis.

We applied the 16S amplicon approach, the most commonly employed method to analyse gut microbiomes, and that presents several important advantages [START_REF] Ranjan | Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing[END_REF]:

i. it is cost effective; ii. data analysis can be performed by established pipelines without using large computing infrastructures; iii. there is a large body of archived data for reference. Indeed, considering that the 16S technique is the most used by livestock researchers, it allows to compare results more effectively.

However, there are multiple substantial advantages of the WGS approach such as the accuracy of taxa at the species level and a direct access to the global microbial genes present in the sample. The biggest disadvantage remains still that WGS is more expensive, requires more specialized and extensive data analysis and may be necessary to sequence the microbial genomes with high coverage and increased cost for studying low-abundant microbes [START_REF] Sims | Sequencing depth and coverage: key considerations in genomic analyses[END_REF]. In our case, the 16S rRNA sequencing remained the first choice to analyse the microbiota composition, essentially due to a cost-effectiveness issue.

Another important issue to be considered is that intestinal microbiota can be deeply modified across the different intestinal tracts, both in terms of composition and abundance (Crespo-Piazuelo et al., 2018;Dieterich et al., 2018;Zhao et al., 2015). Moreover, other factors could influence the biogeography of bacteria within the gut, including diet, antimicrobials, mucus, adherence and the host immune system [START_REF] Donaldson | Gut biogeography of the bacterial microbiota[END_REF].

In our investigations, we only considered the modification occurring at the faecal microbiota level to ensure consistency between experimental trials in environmentally controlled facilities and in field studies. This allow us to sample the same animals at different time points. Nevertheless, it would be interesting to confirm that the observed results are coherent with the microbial composition at different intestine sections.

Summary of challenges and opportunities for the prevention of diarrhoea at weaning

In commercial herds, a robust, balanced and already well-diversified and gut microbiota able to limit the occurrence of enteric disorders should be expected in piglets at weaning. In our studies, we achieved a good correlation between relevant phenotypic traits and abundance of beneficial microbes on late weaned animals, and about the impact of antibiotics on the gut microbiota composition during a natural ETEC infection. From a practical point of view, once the results are confirmed on a larger scale, it will be interesting to disseminate these scientific results to farmers. In fact, applied science as intended in this PhD thesis should be carried out with a continuous focus on its practical effectiveness in herds. For a long time, several studies have been carried out in order to prevent the problem of diarrhoea at weaning improving managing practises in herds (Zimmerman et al., 2012). In previous years, studies were mainly based on phenotypical data collection, histological analysis, vaccination and feed supplementation [START_REF] Alexa | Combined parenteral and oral immunization against enterotoxigenic Escherichia coli diarrhea in weaned piglets[END_REF][START_REF] Baranyiova | The effects of diarrhoea on food intake in piglets weaned on the day of birth[END_REF][START_REF] Boudry | Diet-related adaptation of the small intestine at weaning in pigs is functional rather than structural[END_REF][START_REF] Ciosek | The effectiveness of inactivated vaccines applied parenterally to sows to control Escherichia coli diarrhea in piglets in an industrial fattening farm[END_REF][START_REF] Driesen | Studies on preweaning piglet diarrhoea[END_REF][START_REF] Hampson | Pre-weaning supplementary feed and porcine post-weaning diarrhoea[END_REF][START_REF] Kyriakis | The efficacy of enrofloxacin in-feed medication, by applying different programmes for the control of post weaning diarrhoea syndrome of piglets[END_REF][START_REF] Lecce | Dietary regimen, rotavirus, and hemolytic enteropathogenic Escherichia coli in weanling diarrhea of pigs[END_REF][START_REF] Melin | Weaning of piglets. Effects of an exposure to a pathogenic strain of Escherichia coli[END_REF][START_REF] Nabuurs | Clinical experience in the use of an adjuvant in the prevention of edema disease/post-weaning diarrhea in piglets[END_REF][START_REF] Nabuurs | Weaning piglets as a model for studying pathophysiology of diarrhea[END_REF][START_REF] Schone | The performance of weaned piglets after a five week weaning period in relation to the weaning weight, the feed composition and the use of an effective ergotropic[END_REF][START_REF] Shu | Probiotic treatment using Bifidobacterium lactis HN019 reduces weanling diarrhea associated with rotavirus and Escherichia coli infection in a piglet model[END_REF][START_REF] Svensmark | Epidemiological studies of piglet diarrhoea in intensively managed Danish sow herds. II. Post-weaning diarrhoea[END_REF]. Nonetheless, thanks to the invention of new techniques like highthroughput sequencing, new studies focusing on the prevention of diarrhoea should allow achieving new results and make closer the possibility of interventions. In my view, the coupling of the gut microbiota analysis with the modern 'omics technologies, such as transcriptomics and metabolomics in addition with managing practises, could help on finding feasible alternatives for fighting the diarrhoea at weaning in production herds.

At the production farm level, and in order to optimize production efficiency and animal welfare, producers should be aware of economic consequences of different protocols for preventing diarrhoea and be able to choose the solution that fits into their productive reality. A cost-benefit analysis should be applied to estimate the strengths and weaknesses of alternative control measures for limiting diarrhoea at weaning. However, literature delineating the economic costs associated with this critical period is relatively scarce. A European study carried out in 504 herds over a 3-year period (2014-2016), reported that E. coli was the cause of PWD in 83.3%, of which 45.8% were ETEC F4 and 37.5% ETEC F18 [START_REF] Vangroenweghe | Prevalence of virulence factors of Escherichia coli isolated from piglets with post-weaning diarrhoea in Belgium and The Netherlands, in: ECMIS -E. Coli and the Mucosal Immune System[END_REF]. This relevant result showed a high prevalence of infected farms. Moreover, depending on the severity of the disease, the cost of PWD was estimated to range from €40 to €314 per sow per year [START_REF] Sjölund | Financial impact on pig production: III Gastrointestinal disorders[END_REF]. Likewise, farmers should add to these estimations the cost of antibiotics usage at weaning, although it could be negligible given the low price of some antibiotic formulations.

Since the antibiotic molecules are becoming less and less effective due to the increase of antibiotic resistances, the incidence of diseases is not decreasing. For this reason, alternative molecules with an antimicrobial effect should be taken into consideration. This is the case of the Zinc oxide;

in fact, after the recent restriction use of colistin (EMA, 2016b), Zinc oxide became the first choice for treatment of colibacillosis and it is common used in a therapeutic dosage for the prevention of PWD [START_REF] Hedegaard | Purified natural pig immunoglobulins can substitute dietary zinc in reducing piglet post weaning diarrhoea[END_REF][START_REF] Heo | Gastrointestinal health and function in weaned pigs: A review of feeding strategies to control post-weaning diarrhoea without using in-feed antimicrobial compounds[END_REF][START_REF] Pluske | Feed-and feed additives-related aspects of gut health and development in weanling pigs[END_REF]W. Wang et al., 2019).

The use of pharmacological dose of Zinc can prevents diarrhoea and colibacillosis, doses of Zinc oxide in piglet weaning diets stabilises intestinal microbiota and prevents adhesion of pathogenic bacteria to the intestinal villi, which prevent many problems associated with postweaning diarrhoea (Roselli et al., 2003;W. Wang et al., 2019). However, recent findings highlighted its negative effects. A study conducted in 2015, suggested that the use of high doses of dietary zinc beyond 2 weeks after weaning should be avoided in pigs due to the possible increase of antibiotic resistance in Gram-negative bacteria [START_REF] Vahjen | High dietary zinc supplementation increases the occurrence of tetracycline and sulfonamide resistance genes in the intestine of weaned pigs[END_REF]. The Agency's Committee for Medicinal Products for Veterinary Use (CVMP) concluded that the benefits of zinc oxide for the prevention of diarrhoea in pigs do not outweigh the risks for the environment (EMA, 2017). The committee recommended a refusal on future authorisations for medicinal products containing Zinc, and a withdrawal of approvals for existing products. From 21 June 2017, the EU gave all its member states up to five years to phase out ZnO at medicinal levels in piglet feeds [START_REF] Ema | Questions and answers on veterinary medicinal products containing zinc oxide to be administered orally to food-producing species. Outcome of a referral procedure under Article 35 of Directive[END_REF].

Another important point to take into account is that, though still a niche in the food market especially in the US and Europe, increasing consumer awareness is paving the way for a growing market in organic and/or antibiotic-free foods. In fact, in a survey carried out in 2008 in the US, consumers already displayed a strong attitude against the use of antibiotics in animal husbandry [START_REF] Brewer | Consumer Attitudes Toward Food Safety Issues[END_REF]. Interestingly, about one third of the respondents declared that they were unwilling to purchase food from antibiotic-treated animals and almost one quarter claimed that they had reduced the intake of meat for the same reason [START_REF] Brewer | Consumer Attitudes Toward Food Safety Issues[END_REF]. This attitude increased over the last ten years, with 43% of the respondents in a consumer survey declaring that they often or always look for meat with a 'raised without antibiotics' claim (Consumer reports, 2018). To face consumers demand for a healthier and welfare friendly food, farmers raise animals that are not only highly productive and healthy but also treated without antibiotics or following the organic system.

A recently published estimation stated that more that 10 million people would be expected to die every year by antibiotic-resistant infections [START_REF] O'neill | Antimicrobial Resistance : Tackling a crisis for the health and wealth of nations[END_REF]. This type of studies has contributed to an increased awareness of the consumers, which reacts by asking for organic or antibiotic free farms and for better health and welfare conditions of animals. Specific national and international guidelines are available to discriminate these two production systems. It is important to highlight that the organic philosophy grown and matured in Europe from the 1920s and the establishment of international groups, such as the International Federation of Organic Agriculture Movements (IFOAM) occurred in the 1970s. Key requirements for organic poultry, cattle and pigs are (IFOAM and FiBL, 2019):

i) Must be raised organically on certified organic land; ii) Must be fed certified organic feed; iii) No added growth hormones are allowed; iv) Only one cycle of antibiotic treatment is allowed throughout the productive cycle of animals; v) Must have outdoor access. The animals' organic feed cannot contain animal by-products, antibiotics or genetically engineered grains and cannot be grown using persistent pesticides or chemical fertilizers. However, according to the welfare rules, animals on an organic farm can be treated with antibiotics if they are sick but must be clearly identified and sold separately into the non-organic market.

In the last 4-5 years, the label "Raised without Antibiotics" is being found more frequently on packaging. This indicates that the animals were grown without any antibiotics used for animal health maintenance, treatment or prevention of diseases. This definition may be misleading since meat should be always free of antibiotic residues, and then be defined as "antibiotic-free." In fact, the withdrawal period ensures that there is enough time for the animal's body to clear the antibiotic and the related residues from tissues and organs before slaughter.

Supermarkets and private companies have started to develop policies and positions on the use of antibiotics in meat-producing animals. Some are already offering organic or antibiotic-free meat to customers; others possess clear position statements while others are discussing internally on this rising issue. The consumption of organic food is reported to increase 10.5% each year [START_REF] Ifoam | The World of organic agriculture -STATISTICS & EMERGING TRENDS[END_REF]. However, both the consumer and the health industry have directed the evolution of antibiotic-free and organic pork production. Over the last 20 years, discussions on antibiotic -resistant organisms in human medicine have evolved into the livestock industry to help control potential bacterial resistance over time across all species. In addition, the consumers requesting to eat products of animals raised in organic or antibiotic-free productive systems are motivated by personal health, taste, quality and environmental concerns.

In that scenario, according to our results, the enteric disorders occurring at the weaning moment could be potentially limited and prevented by applying different measures on management practices at the farm levels.

A global list of the main procedures to apply at the farm level in order to prevent the diarrhoea at weaning are shown in Figure 8.

In my view, farmers, who need to face the enteric disorders and the colibacillosis at weaning without using antimicrobials, should consider the benefits of late weaning in terms of diarrhoea prevention and an associated richness and composition of the gut microbiota. Furthermore, even during a colibacillosis infection, the strong effect exerted by amoxicillin treatment on the gut microbiota, in a context where the use of antibiotics and Zinc oxide will be limited should pave the way for the introduction of alternative control measures. However, a multi-disciplinary approach, evaluating fattening and finishing periods of pig herds weaned at different ages should be performed in order to have a widen view of performances, health conditions and meat quality, achieving the consumer demand for an healthier and welfare friendly food. Meanwhile, enforcing biosecurity management practises, selecting resistant genotypes to ETEC infection and making available the inclusion of next-generation probiotics supplementation in feed, should be considered in a holistic strategy aimed at containing enteric disorders in weaners. In this last scenario, our results highlighting F. prausnitzii as a relevant candidate to be considered in porcine production need to be confirmed by performing specific probiotic trials in controlled environment and, when legislation makes it possible, in real-life production farms. Thus, late weaning could be involved in an enhancement of gut health in piglets by promoting a more mature gut microbial ecosystem.

II. An increased relative abundance of F. prausnitzii concomitant with the overall increased microbial richness was described in the group weaned at 42 days old. Since F. prausnitzii is considered a nextgeneration probiotic and it is positively correlated in stable and balanced guts, it could be an important probiotic to consider for the prevention of disorders linked to weaning dysbiosis in pigs. III. Studying the impact of the host genotype during a natural outbreak of colibacillosis, we confirmed that the MUC4 and FUT1 genotypes as genetic markers for the susceptibility to ETEC F4 and F18 infection, respectively.

IV. Amoxicillin, commonly used at weaning for the treatment of streptococcosis occurring in the same timeframe as colibacillosis, showed adverse outcomes on pig gut health during a multi-resistant ETEC infection and this effect was stronger through the oral compared to the parenteral route. Résumé: En élevage porcin, le sevrage est une période critique caractérisée par un stress nutritionnel, environnemental et social, avec une forte sensibilité des animaux à la diarrhée. Le microbiote intestinal doit s'adapter à un changement alimentaire, avec le passage d'une alimentation lactée à un aliment plus complexe à base de céréales, et les animaux sont soumis à la pression exercée par les agents infectieux environnementaux. Les bactéries entérotoxiques Escherichia coli (ETEC) sont les principaux agents pathogènes responsables de la diarrhée post-sevrage et peuvent entrainer des pertes économiques considérables. Le rôle de la génétique de l'hôte dans la sensibilité à l'infection est bien établi, le polymorphisme des gènes Mucine 4 (MUC4) et Fucosyltransférase 1 (FUT1) étant associé à la sensibilité à ETEC F4 et F18, respectivement. Nous avons réalisé deux études afin d'analyser l'effet de facteurs pouvant influer sur la sensibilité des porcelets à la diarrhée au sevrage. Dans une première étude, nous avons évalué l'impact de l'âge au sevrage sur la diversification du microbiote intestinal, par comparaison du microbiote d'animaux sevrés à différents âges. Quarante-huit porcelets de race Large White ont été répartis en quatre groupes de 12 animaux sevrés à 14 jours (sevrage précoce), 21 ou 28 jours (âge au sevrage courant en élevage intensif) et 42 jours (sevrage tardif). La composition bactérienne du microbiote a été établie par séquençage du gène de l'ARNr 16S d'ADN fécal extrait de selles prélevées le jour du sevrage, sept jours après et à l'âge de 60 jours. Nous avons montré que le sevrage tardif augmente la diversité du microbiote, avec une plus grande abondance de Faecalibacterium prausnitzii identifiée comme bénéfique chez l'homme.

Ces résultats suggèrent que la composition du microbiote intestinal pré-sevrage conférée par un sevrage à 42 jours pourrait améliorer la santé intestinale des porcelets, en leur permettant d'acquérir un microbiote plus diversifié avec des bactéries potentiellement bénéfiques lors du sevrage. La seconde étude a eu comme objectif d'évaluer, chez des porcelets sevrés, les effets du génotype des gènes MUC4 et FUT1 et des voies d'administration de l'amoxicilline sur la présence de diarrhée et la composition du microbiote fécal, lors d'une infection naturelle par des souches d'ETEC multirésistantes. Soixante et onze porcelets ont été répartis en trois groupes: deux groupes se différenciant par la voie d'administration de l'amoxicilline, parentérale (P) ou orale (O), et un groupe témoin sans antibiotiques (C). Nous avons confirmé que MUC4 et FUT1 sont des marqueurs génétiques de l'hôte pour la sensibilité aux infections à ETEC et montré que le traitement à l'amoxicilline pouvait avoir des effets néfastes sur la santé du porc au cours d'une infection à ETEC multirésistante, accentués lors d'une administration par voie orale. Les deux études ont mis en évidence l'importance de considérer des méthodes alternatives de conduite d'élevage. Avec la nécessité de limiter l'utilisation d'antibiotiques, la sélection de génotypes résistants, la supplémentation en next-generation probiotics dans l'alimentation et une meilleure optimisation de l'âge au sevrage devraient être prises en compte dans les pratiques, afin de favoriser un microbiote intestinal diversifié, capable de réduire les diarrhées au sevrage. Abstract : In pig production systems, weaning is a crucial period characterized by nutritional, environmental and social stress. During this process, piglets are susceptible to diarrhoea and the gut ecosystem needs to adapt to dietary changes, from a milk-based diet to a solid and more complex cereal-based feed, and to environmental pathogen pressure. One of the most important etiological agent of the post-weaning diarrhoea (PWD) is the Enterotoxigenic Escherichia coli (ETEC) able to cause severe outcomes and considerable economic losses to farmers worldwide. A role of host genetics in infection appearance is well-established, the SNPs located on the Mucine 4 (MUC4) and Fucosyltransferase 1 (FUT1) genes being associated with the susceptibility to ETEC F4 and ETEC F18, respectively. To investigate aspects related to weaning diarrhoea, two studies have been performed. The aim of the first study was to evaluate the impact of weaning age on gut microbiota diversification in piglets comparing animals at different weaning ages. Forty-eight Large White piglets were divided into four groups of 12 animals weaned at 14 days old (early weaning), 21 or 28 days old (main weaning ages in pig intensive farming) and 42 days old (late weaning). In each group, faecal bacteria composition was assessed by sequencing the 16S rRNA gene of faecal DNA on the weaning day, 7 days postweaning and at 60 days of age. Our results showed that late weaning increases the gut microbiota diversity including a higher abundance of Faecalibacterium prausnitzii, reported as beneficial in humans.

Université Paris-Saclay

Our results suggest than the pre-weaning gut microbiota composition conferred by a late weaning at 42 days of age could enhance gut health in piglets. This would provide a competitive advantage to piglets accumulating a higher diversity of potentially beneficial microbes prior to the stressful and risky weaning transition. The aim of the second study was to evaluate the effects of the host-genotype and different routes of amoxicillin administration on the presence of diarrhoea and the microbiota composition, during a natural infection by multi-resistant ETEC strains in weaned piglets. For this purpose, seventyone piglets were divided into three groups: two groups differing by amoxicillin administration routesparenteral (P) or oral (O) and a control group without antibiotics (C). Our results confirmed the MUC4 and FUT1 as host genetic markers for the susceptibility to ETEC infections. Moreover, our data highlighted that amoxicillin treatment may produce adverse outcomes on pig health in course of multi-resistant ETEC infection and this effect is stronger when the antibiotic is orally administered than parenterally. Both studies highlighted the importance of alternative control measures related to farm management in controlling weaning related diarrhoea. With a need to limit the use of antibiotics, selection of resistant genotypes, next-generation probiotics supplementation in feed, and correct procedures of weaning age, should be considered in farm management practices in order to preserve a balanced and stable gut microbiota and consequently reduce occurrence of diarrhoea at weaning.

Université Paris-Saclay

Espace Technologique / Immeuble Discovery Route de l'Orme aux Merisiers RD 128 / 91190 Saint-Aubin, France

Figure 1 :

 1 Figure 1: sales of veterinary antimicrobial agents for food-producing animals, stratified into pharmaceutical forms, by country (EMA, 2019).

Figure 3 :

 3 Figure 3: factors affecting the gut microbiota in piglets at weaning (adapted fromGuevarra et al., 2019; Muirhead and Alexander, 2012; Wang et al., 2019).

Figure 4 :

 4 Figure 4: pathogenesis of ETEC infection in piglets (adapted from Rhouma et al., 2017).

Figure 5 :

 5 Figure 5: post-weaned piglets in intensive herd (A). Intestine of a piglet affected by post-weaning diarrhoea. The picture shows dilatation of the small intestine and colon filled with liquid intestinal content (B).

2 .

 2 To explore the effect of the host genotypes for MUC4 and FUT1 and different routes of amoxicillin administration on the development of post-weaning diarrhoea and the faecal microbiota composition in weaned piglets during a natural infection by Enterotoxigenic Escherichia coli (Section III-Paper II).

Figure 2 :

 2 Figure 2: Relative abundance of the different microbial phyla (A) and genera (B) at each sampling point for every individual pig in each weaning group. Only genera present in at least 20% of the piglets are shown.

Figure 3 :

 3 Figure 3: Boxplots for alpha diversity (A), beta diversity (B) and richness (C) for each sampling time point in animals weaned groups at 14 days of age (W14), 21 days of age (W21), 28 days of age (W28) and 42 days of age (W42). Statistical differences are included in the figure. Significative values are reported as follows: * (p<0.05); ** (p<0.01); *** (p<0.001).

Figure 4 :

 4 Figure 4: NMDS ordination for microbiota composition at each time point for every weaned group (A: piglets weaned at 14 days of age; B: piglets weaned at 21 days of age; C: piglets weaned at 28 days of age; D: piglets weaned at 42 days of age).

Figure 5 :

 5 Figure 5: Abundance of F. prausnitzii at each sampling point for piglets weaned at 14 days of age (W14), 21 days of age (W21), 28 days of age (W28), and 42 days of age (W42). The normalized abundances of the three OTUs annotated as F. prausnitzii (OTU IDs 851865, 350121, and 25215) were summed for each individual sample.

  our study, we used 48 Large White piglets (23 females and 25 males) from 6 different litters that were bred on INRAE's experimental farm at the PAO Experimental Unit in Nouzilly (France). The piglets were randomly assigned to four groups that were weaned at different ages: 14 days (W14), 21 days (W21), 28 days (W28), and 42 days (W42). Each group included animals from two different litters to minimize block effects. At weaning, piglets were transferred into four different pens based on their litter of origin; the pens had fully slatted floors, used a flat deck system, and were temperature controlled. Six piglets from each group were euthanized seven days after weaning to take tissue samples for a complementary study, while the others were followed until they reached 62 days of age. The quality of environmental conditions, and housing conditions were monitored throughout the study. Animals were kept in the same pen during the entire post-weaning period, and no new piglets were introduced. After weaning, piglets were fed an ad libitum standard diet of grain-based pellets, which was formulated to exceed the animals' nutritional requirements. None of the piglets were treated with antibiotics during the experiment. Pigs were free of major pathogens and of enterotoxigenic E. coli, whose presence/absence was tested via PCR(Casey and Bosworth, 2009) performed on the fecal samples.The piglets were weighed at birthand at 5, 12, 20, 27, 33, 48, 55, and 62days of age. At the beginning of the experiment, sample sizes for each group were as follows: W14: 10 animals, W21: 12 animals; W28: 12 animals, and W42: 10 animals. After weaning, three animals in the W14 group were lethargic and failed to grow; they were therefore euthanized in accordance with the study's ethical guidelines. Furthermore, half of the animals in each group were euthanized seven days after weaning to collect tissues for a complementary study. On day 60, the sample sizes for each group were as follows: W14: 4 animals, W21: 6 animals, W28: 6 animals, and W42: 5 animals. During the period from weaning to seven days after weaning, we visually scored the animals' feces for the presence/absence of diarrhea (0 = normal feces; 1 = liquid diarrhea) (W14: 3 cases of diarrhea out of 18 observations; W21: 6/33; W28: 1/15; and W42: 0/19).Fecal DNA extraction and quality controlFecal samples were collected directly from the piglets' rectums at three different sampling points: the day of weaning, 7 days after weaning (day 21 for W14; day 28 for W28; day 35 for W28; and day 49 for W42), and at 60 days of age. Samples could only be collected from half of the animals at 60 days of age because of the earlier tissue sampling. Furthermore, in the W14 group, three piglets had been euthanized, leaving just 3 piglets to reach the age of 60 days. All the fecal samples were directly frozen in liquid nitrogen and further stored at -80°C until use.A modified version of the protocol developed by[START_REF] Godon | Molecular Microbial Diversity of an Anaerobic Digestor as Determined by Small-Subunit rDNA Sequence Analysis[END_REF] was used for DNA extraction. The method was adapted as follows to be compatible with the chemagic STAR nucleic acid workstation (Hamilton, Perkin Elmer, USA). For each sample, 200 mg of frozen fecal matter was placed in a tube and suspended in a mixture of 250 µl of guanidine thiocyanate buffer (4 M guanidine thiocyanate-0.1 M Tris [pH 7.5]), 40 µl of 10% N-lauroyl sarcosine-0.1 M phosphate buffer (pH 8.0), and 500 µl of 5% N-lauroyl sarcosine. These samples were then incubated at 70°C for 1 h. Afterwards, a 750-µl volume of 0.1-mmdiameter silica beads (Sigma-Aldrich, Germany) was added, and the samples were shaken for 10 minutes at 25 agitations per second in a MM301 Mixer Mill (Retsch, Germany). The samples were subsequently centrifuged at 14,000 rpm and 4°C for 5 min, the supernatant was collected, and 30 µl of Proteinase K (chemagic STAR DNA BTS Kit, Perkin Elmer, USA) was added. The samples were then incubated with shaking (MultiTherm Vortexer, Benchmark Scientific, USA) at 250 rpm and 70°C; there was a final 5-min heating step at 95°C for enzyme inactivation. Finally, the samples were again centrifuged at 14,000 rpm and 4°C for 5 min, and the supernatant was transferred into deep-well plates for further extraction using the chemagic STAR DNA BTS Kit (Perkin Elmer, USA), in accordance with the manufacturer's instructions (starting at the Protease K incubation step). A NanoDrop spectrophotometer (Thermo Scientific, USA) was used to assess the quality of the DNA extracts.Fecal DNA sequencing and bioinformatic data processingMicrobial profiling was performed via the high-throughput sequencing of the V3-V4 hypervariable region of the 16S rRNA gene (2x250 bp pairedend reads) using an Illumina MiSeq Sequencer (Illumina, USA). We employed the standard Illumina protocol and the primers PCR1F_343 (5

  were allocated at the animal experimental facility of the Istituto Zooprofilattico Sperimentale dell' Umbria e delle Marche "Togo Rosati" (Perugia, Italy) and were left to acclimatize 4 days before the onset of the experiment. The experiment was authorized by the Italian Ministry of Health (Authorization n°68/2018-PR of 31-01-2018), according to the Italian and European regulations (Directive 2010/63/EU, D.L. 26/2014), and was carried out under the supervision of certified veterinarians.Seventy-two animals were purchased from an Italian herd, positive for ETEC infection, neither piglets nor sows were vaccinated against ETEC and piglets never received antibiotic before entering in the experimental facilities. One piglet was removed from the study, because the animal died within the first week of the experiment. A diagnosis of colibacillosis was made based on lesions and the isolation of ETEC F4 from the gut, according toLuppi (2017).Seventy-one piglets (35 females and 36 males) were divided into three groups (P, O and C) balanced for litter of origin, sex, age at weaning, and weight (FigureS1).Group P (23 piglets) received parenteral administration of amoxicillin (Longocillina L.A.; CEVA), group O (24 piglets) was administrated with oral amoxicillin (Amoxione; Vetoquinol) and group C (24 piglets) received a placebo made with water and was considered the control group.Each pig of group P received the antibiotic via intramuscular injection with the recommended dosage of 15 mg/kg bodyweight two administrations at 48 hours interval. The group O received 12-20 mg/kg bodyweight of the suspension orally twice a day, approximately 7:00 am and 7:00 pm for 5 days. Animals were fed with a starter diet from the day of the arrival (d0)

  used in the genotyping assay. After thermal cycling was complete, the fluorescent signal was detected by reading the plate in the QuantStudio 12k Flex instrument (Applied BioSystems, ThermoFisher Scientific).

  Figure S5B).

Figure

  Figure S6A). Globally, OTU belonging to Oscillospira genera and the Actinobacillus porcinus were more abundant in the resistant MUC4 genotype. Moreover, the same differential analysis was carried out taking into account in the model only the diarrhoea phenotype (faecal scores 0 and 1= negative; faecal score 2= positive) and we identified 153 DA OTUs (TableS6; FigureS6B). Among them, 71 DA OTUs were more abundant

Figure 1 :

 1 Figure 1: Plots include only the samples obtained from T0. Dissimilarities in gut microbiota composition represented by the non-metric multidimensional scaling (NMDS) ordination plot, with Bray-Curtis dissimilarity index calculated on unscaled OTU abundances. The centroids of each group are features as the group name on the graph ("envfit"; Vegan R package). Samples are coloured by MUC4 gene (A): resistant (R, red) and susceptible (S, pink) genotypes; by age (B): 31 days-old (31d, light blue) and 38 daysold (38d, blue) and by faecal score (C): category 0 (green), 1 (orange) and 2 (red).

p=0. 01 )

 01 and did not show a significant p-value among C vs. P group (Tukey's HSD, p>0.05). When comparing two groups, we have described 144 DA OTUs in the comparison P vs. O, 127 O vs. C and 65 by comparing P vs. C (TablesS8, S9and S10, respectively). In the Venn diagram, the overlapping DA OTUs between the two by two groups comparison is showed (Figure2C).

Figure 2 :

 2 Figure 2: Plots include only the samples obtained from T1. (A) Dissimilarities in gut microbiota composition represented by the non-metric multidimensional scaling (NMDS) ordination plot, with Bray-Curtis dissimilarity index calculated on unscaled OTU abundances. Samples are coloured by experimental groups: control (C, blue), amoxicillin oral-administered (O, orange) and amoxicillin parenteral-administered (P, purple). (B) Box plot graph representation of the alpha diversity (Shannon index), beta diversity (Whittaker's index) and richness (total number of OTUs present in each sample) using the rarefied OTU table for each group and time point. Samples are coloured by experimental groups: control (C, blue), amoxicillin oral-administered (O, orange) and amoxicillin parenteral-administered (P, purple). (C) Venn diagram representing the overlaps of differentially abundant OTUs more abundant belonging to the comparison of two experimental groups (C vs. P, C vs. O, P vs. O) ("fitZig"; MetagenomeSeq R package). Group are coloured by comparisons: control vs. amoxicillin parenteral-administered (C vs. P, yellow), control vs. amoxicillin oral-administered (C vs. O, blue) and amoxicillin oral-administered vs. amoxicillin parenteral-administered (O vs. P, green).

Figure 3 :

 3 Figure 3: Abundances of Lactobacillus spp. at T1 (A) and T2 (B) among the experimental groups. Samples are coloured by experimental groups: control (C, blue), amoxicillin oraladministered (O, orange) and amoxicillin parenteral-administered (P, purple).Abundances were calculated as the addition of normalized for OTUs annotated as Lactobacillus spp. in the whole dataset (MetagenomeSeq R package). The notched boxplots displays the confidence interval around the median. If two boxes' notches do not overlap there is 'strong evidence' (95% confidence) their medians differ and consequently the difference is described as "statistically significant at the .05 level".

Figure 4 :

 4 Figure 4: Plots include only the samples obtained from T2. (A) Dissimilarities in gut microbiota composition represented by the non-metric multidimensional scaling (NMDS) ordination plot, with Bray-Curtis dissimilarity index calculated on unscaled OTU abundances. Samples are coloured by experimental groups: control (C, blue), amoxicillin oral-administered (O, orange) and amoxicillin parenteral-administered (P, purple). (B) Box plot graph representation of the alpha diversity (Shannon index), beta diversity (Whittaker's index) and richness (total number of OTUs present in each sample) using the rarefied OTU table for each group and time point. Samples are coloured by experimental groups: control (C, blue), amoxicillin oral-administered (O, orange) and amoxicillin parenteral-administered (P, purple). (C) Venn diagram representing the overlaps of differentially abundant OTUs more abundant belonging to the comparison of two experimental groups (C vs. P, C vs. O, P vs. O) ("fitZig"; MetagenomeSeq R package). Group are coloured by comparisons: control vs. amoxicillin parenteral-administered (C vs. P, yellow), control vs. amoxicillin oral-administered (C vs. O, blue) and amoxicillin oral-administered vs. amoxicillin parenteral-administered (O vs. P, green).

Figure S3 :

 S3 Figure S3: Relative abundance of the Phyla (A) and Genera (B) in each time point for every individual belonging to each experimental group (C=control, P= parenteral

Figure 6 :

 6 Figure 6: summary of the design of the study (Paper I)

Figure 7 :

 7 Figure 7: summary of the design of the study (Paper II)

Figure 8 :

 8 Figure 8: procedures to apply at the farm level in order to prevent the diarrhoea and the enteric dysbiosis in piglets at weaning.

  Désordres entériques au sevrage: âge, administration d'amoxicilline et infection par Escherichia coli entérotoxigénique influençant le microbiote intestinal des porcelets Mots clés : porcelets, microbiote, maladies infectieuses

  Espace Technologique / Immeuble Discovery Route de l'Orme aux Merisiers RD 128 / 91190 Saint-Aubin, France 200 Enteric disorders at weaning: age, amoxicillin administration and Enterotoxigenic Escherichia coli infection affecting the gut microbiota of piglets Keywords: piglets, microbiota, infectious disease

  b. Data on pig production in Europe, Italy and France With respectively 59.4 million and 47.7 million pigs slaughtered in 2016,

Germany (23% of the EU total) and Spain (19%) were by far the two largest pork meat producers in the EU. They are followed by France (23.8 million, 9%), Poland (21.8 million, 8%), Denmark (18.2 million, 7%), the Netherlands (15.4 million, 6%), Italy (11.8 million, 5%), Belgium (11.2 million, 4%) and the United Kingdom (11.0 million, 4%)

(EUROSTAT, 2017)

. It was reported that 12,301,293 and 8,570,807 pigs were produced in 2017 in France and in Italy, respectively

Table 1 :

 1 Distribution of overall sales, in tonnes of active ingredient, split into tablets (used in companion animals) and all other pharmaceutical forms (used in food-producing animals)(EMA, 2019).

	Country	Tonnes	Tablets % of overall sales	All other pharmaceutical forms % of overall Tonnes sales	Total tonnes
	Austria	0.6	1.4	44.6	98.6	45.2
	Belgium	1.9	0.8	221.0	99.2	222.8
	Bulgaria	0.2	0.3	49.6	99.7	49.7
	Croatia	0.1	0.5	21.1	99.5	21.2
	Cyprus	0.05	0.1	45.4	99.9	45.5
	Czech Republic	1.0	2.3	44.1	97.7	45.1
	Denmark	0.8	0.9	94.4	99.1	95.2
	Estonia	0.1	2.1	6.3	97.9	6.4
	Finland	1.2	11.0	9.8	89.0	11.0
	France	15.2	3.0	482.9	97.0	498.1
	Germany	8.6	1.1	766.6	98.9	775.2
	Greece	0.1	0.1	116.7	99.9	116.8
	Hungary	0.3	0.2	147.2	99.8	147.5
	Iceland	0.04	7.1	0.6	92.9	0.6
	Ireland	1.2	1.2	98.5	98.8	99.7
	Italy	9.9	0.9	1057.8	99.1	1067.7
	Latvia	0.1	1.7	5.9	98.3	6.0
	Lithuania	0.1	0.8	11.6	99.2	11.7
	Luxemburg	0.1	4.9	1.9	95.1	2.0
	Malta	0.2	12.1	1.8	87.9	2.0
	Netherlands	2.8	1.5	188.0	98.5	190.9
	Norway	0.5	7.3	5.7	92.7	6.2
	Poland	1.9	0.3	749.6	99.7	751.6
	Portugal	0.8	0.6	135.1	99.4	135.9
	Romania	3.3	1.2	262.9	98.8	266.1
	Slovakia	0.2	1.7	13.9	98.3	14.1
	Slovenia	0.4	6.1	6.7	93.9	7.2
	Spain	0.9	0.1	1769.5	99.9	1770.4
	Sweden	0.8	7.7	9.5	92.3	10.3
	Switzerland	0.7	2.2	31.9	97.8	32.6
	United Kindom	14.3	5.8	233.9	94.2	242.2
	Total 31 countries	68.6	1.0	6634.4	99.9	6703.0

  . Another important definition is animal welfare, which means how an animal is coping with the conditions in which it lives. An animal is in a good state of welfare if (as indicated by scientific evidence) it is healthy, comfortable, well nourished,

safe, able to express innate behaviour, and if it is not suffering from unpleasant states such as pain, fear, and distress

(OIE, 2010)

. Good animal welfare requires disease prevention and veterinary treatment, appropriate shelter, management, nutrition, humane handling and humane slaughter/killing. Animal welfare refers to the state of the animal; the treatment that an animal receives is covered by other terms such as animal care, animal husbandry, and humane treatment

Table 2 :

 2 main viral and bacterial diseases and their main clinical signs in pigs (adapted fromMuirhead and Alexander, 2012).

					Clinical signs
	Diseases	Pathogen	Lameness	Diarrhoea	Respiratory	Nervous	Infertility	Misc.**

  .trend.test function). To examine microbiota diversity and composition, the biom OTU table was imported into R using the Phyloseq package (v.1.24.2) (McMurdie and Holmes, 2013). The vegan(v. 2.5-2)

3.5.1)

[START_REF] Teamcore | R: A language and environment for statistical computing[END_REF]

. We analyzed piglet weight using ANOVAs (aov function), and we assessed the frequency of piglets with diarrhea using a Chi-square test (prop

Table 1 :

 1 Distribution of animal status for the presence of diarrhoea according to the MUC4 and FUT1 genotypes at T0, T1 and T2. Statistical differences calculated using the Fisher exact test in the different comparisons and the p-values are reported.

	Time point	Gene	Susceptibility (S) Resistance (R)	Individual diarrhoea status Negative Positive	Fisher test (p-value)
	T0	MUC4 FUT1	S R S R	44 10 45 9	8 9 13 4	0.01 0.49
	T1	MUC4 FUT1	S R S R	34 12 38 8	18 7 20 5	1 0.94
	T2	MUC4 FUT1	S R S R	45 16 49 12	7 3 9 1	1 0.76

Table 2 :

 2 Distribution of animals status for the presence of diarrhoea according to the experimental groups (C=control, P= parenteral administrated, O=oral administrated) at T0, T1 and T2. Statistical differences calculated using the Fisher exact test in the different comparisons and the p-values are reported.

	Time point	Group	Presence of diarrhoea Negative Positive	Fisher test (p-value)
		P	17	6
	T0	O	17	7	0.61
		C	20	4
		P	11	10
	T1	O	14	10	0.009
		C	21	3
		P	19	4
	T2	O	18	6	0.02
		C	24	0
	Faecal microbiota sequencing, identification and annotation of OTUs
	After quality control, a mean of 36706 reads were available for each
	sample. OTU counts per sample and OTU taxonomical assignments are
	available in supplementary Table S4. Sequences across the whole sample
	sets were successfully clustered into 1080 OTUs and only (10/1080)
	0.92% of the OTUs could not be assigned to any phylum. Globally, 553

  Marcello Mari and Luigi Molinari are thanked for excellent technical assistance. This article is based upon work from COST Action (FA1401 PiGutNet), supported by COST (European Cooperation in Science and Technology). COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. (www.cost.eu). Description of health status of our cohort. Distribution of animals in the experimental groups (C=control, P= parenteral administrated, O=oral administrated). (A) Bar plot of ETEC F4 represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T0: negative (green) and positive (red); (B) Bar plot of ETEC F4 represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T1: negative (green) and positive (red); (C) Bar plot of ETEC F4 represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T2: negative (green) and positive (red); (D) Bar plot of ETEC F18 represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T0: negative (green) and positive (red); (E) Bar plot of ETEC F18 represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T1: negative (green) and positive (red); (F) Bar plot of ETEC F18 represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T2: negative (green) and positive (red); (G) Bar plot of ETEC F4 represented in each of the MUC4 genotypes identified as resistant (R) and susceptible (S). For each MUC4 genotype, the bar plot represents the number of individuals ascribed to each ETEC F4 status at T0: negative (green) and positive (red);

	Availability of data and materials
	The raw sequencing data has been submitted to NCBI's Sequence Read
	Archive (SRA) repository (BioProject: PRJNA543556; Biosample:
	SUB5638166, accessions 11771978 to 11772198).

Figure S2:

Table S5 :

 S5 Differentially abundant OTUs when comparing the MUC4 genotypes and the age categories at T0.

Table S6 :

 S6 Differentially abundant OTUs when comparing the non-diarrhoeic and diarrhoeic animals at T0.

Table S7 :

 S7 Differentially abundant OTUs when comparing the experimental groups at T1.

Table S8 :

 S8 Differentially abundant (DA) OTUs when comparing P (parenteral administrated) vs. C (control) group at T1. DA OTUs were used to be plotted in the Venn diagram (Figure

GENERAL DISCUSSIONSection IV

Acknowledgements

We are grateful to all members of the PIGLETBIOTA consortium that support this project, and which include DELTAVIT (CCPA group), InVivo-NSA (InVivo group), LALLEMAND, SANDERS (AVRIL group), and TECHNA companies and the ALLIANCE R&D association (AXIOM, CHOICE GENETICS, NUCLEUS and IFIP). We are also grateful to the Valorial competitiveness cluster for its support to the project. We are grateful to the personnel at UE PAO farm at INRAE's Tours Centre for their implication for the generation of animals and sampling and to Michel Olivier and members of porcine Mucosal Immunology team of INRAE-Tours for their support. We are grateful to the INRAE MIGALE bioinformatics platform (http://migale.jouy.INRAE.fr) for providing computational resources for the bioinformatics data analysis.

This thesis was based upon work from Action FA1401-PiGutNet, supported by COST (European Cooperation in Science and Technology), a funding agency for research and innovation networks. These COST Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers (www.cost.eu). Francesca Romana Massacci was supported by a PhD grant from the Department of Agricultural and Food Sciences (DISTAL) of Bologna University (Italy) and by the Vinci 2018 fellowship (n. C2-723) of the Université Franco-Italienne. The PhD work was funded by the French National Agency (project PIGLETBIOTA, ANR-14-CE18-0004) and by the Italian Ministry of Health (Progetto di Ricerca Corrente IZSUM RC 006/2016).

Funding

Experiments were funded by the PIGLETBIOTA project by the French Agence Nationale de Recherche (ANR; project: ANR-14-CE18-0004). F.R. Massacci was supported by a PhD grant from the Department of Agricultural and Food Sciences (DISTAL) of Bologna University (Italy). Funding This study was funded by the Italian Ministry of Health (Progetto di Ricerca Corrente IZSUM RC 006/2016), by INRAE (Animal Genetics division) and by France Génomique National infrastructure, funded as part of "Investissement d'avenir" program managed by Agence Nationale pour la Recherche (contract ANR-10-INBS-09). F.R. Massacci was supported by a PhD grant from the Department of Agricultural and Food Sciences (DISTAL) of Bologna University (Italy).

LIST OF PUBLICATIONS

The present thesis is based on the work contained in the list of scientific papers below:

OBJECTIVES Section II

Ethics approval and consent to participate

All animal procedures were performed according to the guidelines for the care and use of experimental animals established by INRAE and the French authorities (Ability for animal experimentation to E. Guettier: R-45GRETA-F1-04; agreement for experimentation of INRAE's Experimental Unit of Animal Physiology of Orfrasiere: F37-175-2; protocol approved by the French Ministry of Research with authorization ID APAFIS#328-2015031616056915 v5 after the review of ethics committee nº019).

Consent for publication

All authors accepted the final version of the manuscript.

Availability of data and materials

The raw sequencing data has been submitted to NCBI's Sequence Read Archive (SRA) repository (BioProject: PRJNA540598; accessions SAMN11547623 to SAMN11547734).

Competing interests

The authors declare that they have no competing interests. Authors' contributions JE, MB, MJM, JD, PL and CRG designed the research. EG and MB were responsible of the animal production and phenotyping at INRAE's UE PAO farm. GL and JE sampled microbiota and FB managed sampling processing. DJ and FRM did faecal DNA extractions and MNR performed the 16S rRNA sequencing. FRM analysed all data under the supervision

Supplementary information

Additional supporting information accompanies this paper at the following link https://doi.org/10.1186/s42523-020-0020-4

Supplementary figures

Supplementary tables

Table S1: Differences in mean weight among weaning groups and sampling points. General differences were determined using ANOVAs, and Tukey's HSD tests were employed for post-hoc comparisons. Significant p-values are in bold.

Table S2: Differences in alpha diversity, beta diversity, and richness among sampling points for each weaning group. General differences within each group were determined using ANOVAs, and Tukey's HSD tests were employed to carry out post-hoc comparisons between sampling points. Significant p-values are in bold.

Table S3: Differentially abundant OTUs before and after weaning in the W14 group.

Table S4: Differentially abundant OTUs before and after weaning in the W21 group.

Table S5: Differentially abundant OTUs before and after weaning in the W28 group.

Table S6: Differentially abundant OTUs before and after weaning in the W42 group.

Table S7: Differences in normalized F. prausnitzii abundances among weaning groups across all sampling points. The existence of a general difference among the groups was determined using an ANOVA, and Tukey's HSD tests were employed to carry out posthoc comparisons between all the groups at all the sampling points. Significant p-values are in bold.

Table S8: Differences in normalized F. prausnitzii abundances among sampling points for the four weaning groups. General differences were determined using ANOVAs, and Tukey's HSD tests were employed to compare F. prausnitzii abundances between weaning groups for each sampling point: before weaning, after weaning, and at 60 days of age. Significant p-values are in bold.

Table S9: Differences in alpha diversity, beta diversity, and richness among sampling points. General differences were determined using ANOVAs, and Tukey's HSD tests were employed for the post-hoc comparisons. Significant p-values are in bold.

Table S10: Differentially abundant OTUs before weaning for the weaning groups.

Table S11: Differentially abundant phyla before weaning for the weaning groups.

Table S12: Differentially abundant genera before weaning for the weaning groups.

Table S13: Differentially abundant OTUs after weaning for the weaning groups.

Table S14: Differentially abundant genera after weaning for the weaning groups.

Differences in the faecal microbiota at T2 in piglets

The overall composition of the microbiota at T2 (NMDS, Figure 4) was mainly linked to the antibiotic treatment (Adonis test, p = 0.0001) and the faecal score (Adonis test, p = 0.0002), whereas MUC4, FUT1 genotypes, the age and the presence of ETEC F4 and ETEC F18 had no influence (Adonis test, p>0.05). The beta diversity was not significantly different across the antimicrobial treatment groups (ANOVA test, p>0.05). In the NMDS plot, the centroids of the group O appeared separated from the P and the C group, resulting in a significant value (envfit test, p=0.03; Figure 4A). The alpha diversity at OTU level and the observed microbial richness did not show differences among the groups (ANOVA test, p>0.05; Figure 4B). Moreover, the antibiotic administration differential analysis at the OTUs level identified 124 DA OTUs (Table S11; Figure S6D). Since at least one OTU was found DA in most comparisons between experimental groups, we decided to further explore the global abundance of Lactobacillus spp. by adding the abundances of the OTUs in the whole dataset at T2 (OTUs 292057, 24271, 725198, 536754, 588197, 581474, 549756, 553352, 302975, 703741, 807795). We described that Lactobacillus spp. was more abundant in the group C (Figure 3B).

ANOVA analyses showed significant differences (p=0.001) between the experimental groups. In addition, the post-hoc test showed significant differences between P vs. C group (Tukey's HSD, p= 0.0009) and a significant trend between the O vs. C group (Tukey's HSD, p= 0.055). No differences were described between O and P group (Tukey's HSD, p>0.05). When comparing two groups, we have described 162 DA OTUs in the comparison O vs. C, 61 P vs. O and 51 when comparing P vs. C (Tables S12, S13 and S14, respectively). In the Venn diagram, the

Conflict of Interest Statement

The authors declared that they had no conflict of interests with respect to their authorship on the publication of this article.

Supplementary information

Additional supporting information may be found online in the Supporting Information section at the end of the article.

(https://onlinelibrary.wiley.com/doi/10.1111/jbg.12432)

Supplementary figures

Figure S1: Description of our cohort. Distribution of animals in the experimental groups (C=control, P= parenteral administrated, O=oral administrated). (A) Bar plot of sex represented in each of the experimental groups. For each group, the bar plot represents the number of individuals ascribed to each sex: female (pink), and male (blue); (B) Bar plot of age at weaning represented in each experimental group. For each group, the bar plot represents the number of individuals ascribed to each age: 31 days-old (31d, orange) and 38 days-old (38d, grey); (C) Bar plot of litter of origin represented in each experimental group. For each group, the bar plot represents the number of individuals ascribed to each litter number: 14N178 (red), 153 (blue), 156 (green), 159159 (purple), 169099 (orange), 16T115 (yellow), 174 (brown) and 177053 (pink); (D) Bar plot of MUC4 genotypes represented in each experimental group. For group, the bar plot represents the number of individuals ascribed to each MUC4 genotypes: MUC4 CC (red), MUC4 CG (grey) and MUC4 GG (beige); (E) Bar plot of FUT1 genotypes represented in each experimental group. For group, the bar plot represents the number of individuals ascribed to each FUT1 genotypes: FUT1 CC (red), FUT1 CT (grey) and FUT1 TT (beige). administrated, O=oral administrated). Only Genera present in at least 20% of the individuals are shown.

Figure S4:

Plots include all the samples obtained at T0, T1 and T2. Dissimilarities in gut microbiota composition represented by the non-metric multidimensional scaling (NMDS) ordination plot, with Bray-Curtis dissimilarity index calculated on unscaled OTU abundances. The centroids of each group are features as the group name on the graph ("envfit"; Vegan R package). Samples are coloured by time point: T0 (blue), T1 (purple) and T2 (yellow).

Figure S5:

Box plots include only the samples obtained from T0. (A) Box plot graph representation of the alpha diversity (Shannon index), beta diversity (Whittaker's index) and richness (total number of OTUs present in each sample) using the rarefied OTU table for each MUC4 genotype. Samples are coloured by MUC4 genotypes: MUC4 CC (red), MUC4 CG (grey) and MUC4 GG (beige); (B) Box plot graph representation of the alpha diversity (Shannon index), beta diversity (Whittaker's index) and richness (total number of OTUs present in each sample) using the rarefied OTU table for each age at weaning. Samples are coloured by age: 31 days-old (31d, light blue) and 38 days-old (38d, blue); (C) Box plot graph representation of the alpha diversity (Shannon index), beta diversity (Whittaker's index) and richness (total number of OTUs present in each sample) using the rarefied OTU table for each faecal score. Samples are coloured by diarrhoea status: score 0 (green), score 1 (orange) and positive (red).

Supplementary tables

Table S1: Ingredient and chemical composition of the concentrates of post-weaning pigs.

Table S2: Table summarizing the phenotypic traits and genotypes of piglets.

Table S3: Number of pigs belonging to the experimental groups (C=control, P= parenteral administrated, O=oral administrated) along their distribution on the genotypes for MUC4 and FUT1.