Román Desirée

Michael Naranjo

Anne Callanan

Olivia Thierry

Mcauliffe

Desirée Román Naranjo

Michael Callanan

Anne Thierry

Olivia Mcauliffe
email: olivia.mcauliffe@teagasc.ie

Evaluation of Environmental Lactococcus lactis Strains Reveals Their Potential for Biotransformation of Lignocellulosic Feedstocks

Keywords: lignocellulose, biotransformation, L. lactis, environmental isolates, pentoses, cellulolytic, plant biomass, waste streams

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Introduction

As climate change records indicate, global CO2 emissions derived from fossil fuels have risen for three consecutive years, with all economic indicators suggesting this growing trend to continue in the future [START_REF] Jackson | Persistent Fossil Fuel Growth Threatens the Paris Agreement and Planetary Health[END_REF]. As the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) states, the global surface temperature will continue to increase, exceeding 2 °C, unless deep reductions in CO2 levels and other greenhouse gas emissions take place [START_REF] Masson-Delmotte; Zhai | Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF]. Moreover, the energy demand is constantly increasing, with estimates of a 28% increase of total energy consumption worldwide by 2040 [START_REF]Annual Energy Outlook 2019 with Projections to 2050[END_REF]. The deteriorating climate change situation and increasing energy demands, together with the depletion of fossil fuels, makes the search for other renewable sources for fuel production an urgent one. Biofuel, derived from the conversion of biomass, is one of the most promising renewable alternatives to fossil fuels [START_REF] Ahmed | Microbial Degradation of Lignocellulosic Biomass: Discovery of Novel Natural Lignocellulolytic Bacteria[END_REF].

Lignocellulose, a polymer that is the most abundant biomaterial on Earth and one of the most abundant renewable feedstocks, comprises on average 23% lignin, 40% cellulose, and 33% hemicellulose by dry weight [START_REF] Zhang | High-Titer Lactic Acid Production by Pediococcus Acidilactici PA204 from Corn Stover through Fed-Batch Simultaneous Saccharification and Fermentation[END_REF][START_REF] Zhu | Industrial Enzymes[END_REF]. Lignocellulose is the main component of forestry, agricultural, and agro-industrial wastes. This agro-industrial waste source has been reported as having potential as an inexpensive, abundant, and renewable energy source.

Lignocellulose biomass can be hydrolyzed using physical, chemical, and biological methods. Biological treatments, such as microbial biotransformation, offer several advantages including high specificity, low energy consumption, no chemical requirement, and mild environmental conditions avoiding sugar degradation [START_REF] Mussatto | Lignocellulose as Raw Material in Fermentation Processes[END_REF]. Nonetheless, biological treatments also have some disadvantages such as a low hydrolysis rate [START_REF] Mussatto | Lignocellulose as Raw Material in Fermentation Processes[END_REF].

Lignocellulose is composed of closely associated polymers such as cellulose, hemicellulose, and lignin, which form a complex cellular matrix in the vegetal biomass. However, the amount of each polymer is different between the plant species [START_REF] Mussatto | Lignocellulose as Raw Material in Fermentation Processes[END_REF][START_REF] Carr | Assessment of Alternative Uses for Lignocellulosic Waste Products[END_REF]. Cellulose can be converted into fermentable sugars with an appropriate cellulolytic system involving the production of cellulase enzyme systems by many cellulolytic bacterial genera such as Clostridium, Cellulomonas, Bacillus, and Actinomycetes [START_REF] Liang | Isolation, Screening, and Identification of Cellulolytic Bacteria from Natural Reserves in the Subtropical Region of China and Optimization of Cellulase Production by Paenibacillus Terrae ME27-1[END_REF][START_REF] Gupta | Isolation of Cellulose-Degrading Bacteria and Determination of Their Cellulolytic Potential[END_REF]. These cellulolytic systems have been applied to many industrial processes including biofuel production, or agricultural and plant waste management [START_REF] Gupta | Isolation of Cellulose-Degrading Bacteria and Determination of Their Cellulolytic Potential[END_REF]. Cellulolytic enzymatic systems comprise three main cellulase groups: endoglucanases, exoglucanases, and β-glucosidases, depending on where in the molecule the cleavage takes place [START_REF] Maki | Characterization of Some Efficient Cellulase Producing Bacteria Isolated from Paper Mill Sludges and Organic Fertilizers[END_REF]. Hemicelluloses are a family of complex biopolymers that can be degraded by specific hemicellulase-producing microorganisms. These hemicellulases include the enzymes xylanase and manannase, produced mostly by fungal species due to their complex natures. Lignin is the second most abundant renewable polymer after cellulose. It is also the most structurally complex lignocellulose component (highly cross-linked phenylpropanoid units), which makes it resistant to its use by microorganisms to produce monomers [START_REF] Umashankar | Isolation and Screening of Lignin Degrading Bacteria from Different Natural and Organic Sources[END_REF][START_REF] Taylor | Isolation of Bacterial Strains Able to Metabolize Lignin from Screening of Environmental Samples[END_REF].

Previous studies have found that certain lactic acid bacteria species possess the capability to ferment several cheap waste streams whose main component is lignocellulose, resulting in the generation value-added products, primarily lactic acid, but also ethanol, butanol, or polylactic acid. Pediococcus acidilactici DSM 20284 and Pediococcus pentosaceus ATCC 25745 were found to ferment common pentose sugars found in lignocellulose, such as xylose and arabinose [START_REF] Boguta | Screening of Lactic Acid Bacteria for Their Potential as Microbial Cell Factories for Bioconversion of Lignocellulosic Feedstocks[END_REF]. Other examples include the production of L-lactic acid from sugarcane bagasse by Lactiplantibacillus delbrueckii NCIM 2025 [START_REF] John | Solid-State Fermentation for L -Lactic Acid Production from Agro Wastes Using Lactobacillus Delbrueckii[END_REF], from wheat straw hemicellulose hydrolysate by Lactiplantibacillus pentosus CHCC 2355 and Levilactobacillus brevis CHCC 2097 [START_REF] Garde | Lactic Acid Production from Wheat Straw Hemicellulose Hydrolysate by Lactobacillus Pentosus and Lactobacillus Brevis[END_REF], or from lignocellulosic hydrolysates by Lactiplantibacillus sp. RKY2 KCTC 10353BP [START_REF] Wee | Lactic Acid Production by Lactobacillus Sp. RKY2 in a Cell-Recycle Continuous Fermentation Using Lignocellulosic Hydrolyzates as Inexpensive Raw Materials[END_REF]. Moreover, the co-cultures of Levilactobacillus brevis and Lactiplantibacillus plantarum were able to produce lactic acid from biomass-derived sugars co-fermentation [START_REF] Zhang | Lactic Acid Production from Biomass-Derived Sugars via Co-Fermentation of Lactobacillus Brevis and Lactobacillus Plantarum[END_REF].

It has previously been shown that Lactococcus lactis strains isolated from environmental sources, including plant material, have more diverse metabolic capabilities compared to their dairy counterparts, in terms of lipolytic activity [START_REF] Naranjo | Superior Esterolytic Activity in Environmental Lactococcus Lactis Strains Is Linked to the Presence of the SGNH Hydrolase Family of Esterases[END_REF] or volatile compound production [START_REF] Alemayehu | Characterization of Plant-Derived Lactococci on the Basis of Their Volatile Compounds Profile When Grown in Milk[END_REF][START_REF] Cavanagh | Evaluation of Lactococcus Lactis Isolates from Nondairy Sources with Potential Dairy Applications Reveals Extensive Phenotype-Genotype Disparity and Implications for a Revised Species[END_REF]. To date, studies on the lignocellulose metabolization capabilities of L. lactis have mostly focused on the ability of genetically engineered L. lactis strains to ferment lignocellulose [START_REF] Shinkawa | Improved Homo L-Lactic Acid Fermentation from Xylose by Abolishment of the Phosphoketolase Pathway and Enhancement of the Pentose Phosphate Pathway in Genetically Modified Xylose-Assimilating Lactococcus Lactis[END_REF][START_REF] Petersen | Transforming Lactococcus Lactis into a Microbial Cell Factory[END_REF][START_REF] Liu | Enhancement of Lignocellulosic Degradation in High-Moisture Alfalfa via Anaerobic Bioprocess of Engineered Lactococcus Lactis with the Function of Secreting Cellulase[END_REF]. However, very few studies focus on the natural ability of L. lactis environmental isolates to biotransform this complex carbon source, and those studies only focus on the strain L. lactis IO-1, which was found to be capable of fermenting xylose [START_REF] Kato | Complete Genome Sequence of Lactococcus Lactis IO-1, a Lactic Acid Bacterium That Utilizes Xylose and Produces High Levels of l-Lactic Acid[END_REF][START_REF] Machii | Chemically Defined Media and Auxotrophy of the Prolific L-Lactic Acid Producer Lactococcus Lactis IO-1[END_REF]. Even though the mutant L. lactis strain IL 1403 produced 50.1 g L -1 of L-lactic acid from xylose [START_REF] Shinkawa | Improved Homo L-Lactic Acid Fermentation from Xylose by Abolishment of the Phosphoketolase Pathway and Enhancement of the Pentose Phosphate Pathway in Genetically Modified Xylose-Assimilating Lactococcus Lactis[END_REF], the wild strain L. lactis IO-1 produced a maximum concentration of 33.26 g L -1 of lactic acid from xylose [START_REF] Tanaka | Two Different Pathways for D-Xylose Metabolism and the Effect of Xylose Concentration on the Yield Coefficient of L-Lactate in Mixed-Acid Fermentation by the Lactic Acid Bacterium Lactococcus Lactis IO-1[END_REF]; this shows the potential of non-engineered L. lactis to metabolize this complex carbon source and to generate compounds of interest. Furthermore, most studies focus on the presence of genes related to these activities from a genomic perspective [START_REF] Siezen | Genome-Scale Genotype-Phenotype Matching of Two Lactococcus Lactis Isolates from Plants Identifies Mechanisms of Adaptation to the Plant Niche[END_REF][START_REF] Siezen | Genome-Scale Diversity and Niche Adaptation Analysis of Lactococcus Lactis by Comparative Genome Hybridization Using Multi-Strain Arrays[END_REF]. The main difference between the physiological and the genomic perspective is the lack of correlation between the presence of specific genes and the phenotypic activity assigned to those genes, which happens sometimes, mainly due to gene inactivation [START_REF] Siezen | Genome-Scale Genotype-Phenotype Matching of Two Lactococcus Lactis Isolates from Plants Identifies Mechanisms of Adaptation to the Plant Niche[END_REF]. For example, the presence of a xylose utilization gene cluster in strain L. lactis subsp. lactis IL-1403 did not correlate with the ability of this strain to utilize xylose. In this study, the objective was to evaluate a collection of L. lactis strains derived from grass, vegetable, and other environmental sources for potential lignocellulose biotransformation from a physiological point of view.

Materials and Methods

Bacterial Strains and Culture Conditions

Details of the strains used in this study are listed in Table 1. Pediococcus acidilactici DSM 20284 was purchased from DSMZ and was used as a positive control for the pentose utilization test. The strains are maintained in the DPC Culture Collection (Teagasc Food Research Centre, Moorepark, Ireland) or were purchased from the German Collection of Microorganisms and Cell Cultures (DSMZ, Braunschweig, Germany). L. lactis strains were cultured in M17 media (Oxoid, Hamphsire, England) supplemented with 5 g L -1 D (+)glucose monohydrate (G-M17) (VWR, Leuven, Belgium). Lactiplantibacillus and Levilactobacillus strains were grown in MRS medium (Oxoid, Hamphsire, England). All the strains were incubated aerobically at 30 °C.

Pentose Utilization Agar Test

The preliminary qualitative ability to utilize xylose and arabinose was tested through spotting onto modified 10% MRS agar medium (mMRS). The basal composition of the 10% mMRS agar medium was (per liter) (all supplied by Merck): 1 g casein peptone (tryptic digest), 15 g agar, 0.8 g meat extract, 0.4 g yeast extract, 1 mL Tween 80, 2 g K2HPO4, 5 g sodium acetate, 2 g diammonium citrate, 0.2 g MgSO4 • 7H2O and 0.05 g MnSO4 • H2O; and 20 g of carbon source: glucose or galactose (hexoses), and xylose or arabinose (pentoses), as described by Boguta et al., 2014 [14]. A 5 μL aliquot of an overnight culture in the appropriate broth was spotted onto the agar plates. Following incubation at 30 °C for 48 h, the growth of the strains was evaluated as good growth (+), moderate (/), and no growth (-), using as a reference the growth of the same strain on 10% mMRS + glucose agar plates. All of the strains were tested in triplicate for each sugar.

Pentose Utilization Growth Curves

Strains that were positive in the pentose utilization agar test (for both pentose sugars) were further tested in modified 10% mMRS broth + 20 g of carbon source: glucose or galactose (hexoses), and xylose or arabinose (pentoses). The media composition was as described above, but excluding the agar. The assay was performed in a transparent 96-well plate (Sarstedt Ltd., Leicester, UK). The reaction mixture included 200 μL of 10% modified mMRS + glucose, galactose, arabinose or xylose, and 2 μL of overnight culture of the selected strains. The mixture was incubated at 30 °C for 48 h, and the absorbance at 600 nm (A600) was measured with Epoch 2 Microplate Spectrophotometer (BioTek, Winooski, VT, USA) every hour during the 48 h. All the assays were performed in triplicate.

In order to compare the growth between the different strains and sugars, the growth rates were calculated for each strain/sugar combination. Raw data were gathered in Microsoft Office Excel 2013 and the statistical software R 4.0.1. The growthcurver package was used to fit the growth data [START_REF] Sprouffske | An R Package for Obtaining Interpretable Metrics from Microbial Growth Curves[END_REF][START_REF] Yeh | Community-Level Physiological Profiling for Microbial Community Function in Broiler Ceca[END_REF]. The growth rate was calculated with the Spline model for the best performing strains, with inclusion of the lag (λ) parameter, meaning that the exponential growth of the biomass of the bacteria is only calculated at a given OD.

Qualitative Cellulolytic Screening

Carboxymethyl cellulose agar (CMC agar) was used to identify the presence or absence of endo-cellulolytic activity. The CMC agar composition was as follows: 11.28 g L -1 M9 minimal medium salts (MP Biomedicals, Eschwege, Germany), 5 g L -1 carboxymethyl cellulose (Merck, Arklow, Ireland), and 15 g L -1 agar (Merck). A 5 μL aliquot of 2% (v/v) of an overnight culture was spotted onto the CMC agar and incubated for 2 days at 30 °C. Following incubation, the agar plates were flooded with Gram's iodine solution (Merck) for 3 min to visualize the cellulolytic activity [START_REF] Maki | Characterization of Some Efficient Cellulase Producing Bacteria Isolated from Paper Mill Sludges and Organic Fertilizers[END_REF].

Cellulolytic Activity Assay

Reducing sugars were measured by following a modified 3,5-dinitrosalicylic acid (DNS) assay as described in [START_REF] Wood | Methods for Measuring Cellulase Activities[END_REF].

Cell-free extracts (CFE) containing crude enzymes were prepared fresh prior to use on the same day of the assays. A total of 2% (v/v) of a 24 h culture (with an average OD600 = 0.812) was inoculated in 10 mL of the corresponding broth for each bacterial strain and incubated for 24 h at 30 °C. In order to obtain the cell-free-extract (CFE) containing crude enzymes, cells were centrifuged at 10,000× g for 20 min at 4 °C and kept on ice until further use.

The reaction mixture consisted of 100 μL of 1% (w/v) carboxymethyl cellulose (CMC, Merck) dissolved in 0.05 mol L -1 glycine/NaOH buffer (pH = 9, Merck) (substrate of the assay) and 20 μL of CFE in a final volume of 120 μL. The reaction mixture was incubated for 30 min at 37 °C, and the enzymatic reaction was halted by placing the reactions on ice. A total of 360 μL of DNS solution was added to the reaction mixture, which was then placed in a boiling water bath for 5 min and subsequently placed on ice to stop the reaction. Samples were then diluted appropriately with sterile water (1:2), vortexed, and 200 μL was pipetted into a 96-well plate. Absorbance was read at 550 nm wavelength using an Epoch 2 Microplate spectrophotometer (Agilent BioTek, Winooski, VT, USA) in triplicates.

The DNS solution was prepared as follows: 3,5-dinitrosalicylic acid (10 g L -1 , Merck), NaOH (20 g L -1 , Merck), sodium sulfite anhydrous (0.5 g L -1 , Fisher Scientific, Dublin, Ireland), potassium sodium tartrate tetrahydrate (200 g L -1 , Merck), and phenol (2 g L -1 , Merck). The 3,5-dinitrosalicylic acid and NaOH solution were dissolved separately and added to the mixed solution of sodium sulfite anhydrous and potassium sodium tartrate tetrahydrate, and finally, phenol was added to the solution.

A glucose standard curve was generated to quantify the amount of reducing sugar in the reaction mixture. One cellulolytic unit was defined as the enzymatic activity that liberates one microgram of glucose per min per mL CFS. A stock solution of glucose (3 mg mL -1 , Merck) was used to prepare the glucose solutions with different concentrations ranging from 0 to 0.9 mg mL -1 .

Results

L. lactis Strains Derived from Green Peas, Grass, and Corn Can Metabolize Arabinose and Xylose

Results for all the strains tested are included in Tables S1 andS2. A preliminary qualitative test was performed on the L. lactis strain collection to evaluate the ability of the environmental L. lactis strains to utilize the pentose sugars xylose and arabinose. Overnight cultures of each strain were spotted onto modified 10% mMRS agar medium containing the sugar of interest, and bacterial growth was indicated as good (+) where clear visible bacterial growth was observed, moderate (/) where faint bacterial growth was observed, and no growth (-) where no growth was observed, in comparison with 10% mMRS + glucose. P. acidilactici DSM 20284 served as the positive control, as this strain has previously been shown to utilize the pentose sugars under investigation in this study [START_REF] Boguta | Screening of Lactic Acid Bacteria for Their Potential as Microbial Cell Factories for Bioconversion of Lignocellulosic Feedstocks[END_REF]. Examples of the plate assays can be observed in Figure 1. While all of the 21 environmental L. lactis strains tested were capable of growth on the hexose sugars glucose and galactose, only 11 strains exhibited growth in the presence of the pentose sugars arabinose and xylose as the sole sugar source. These included strains derived from green peas (DPC 6754, DPC 6755, DPC 6756, DPC 6758, and DPC 6759), grass (DPC 6760, DPC 6763, DPC 6764, and DPC 6765), baby corn (DPC 6762), and mung bean sprouts (KF147). For comparison, we included a number of species in our assay that had previously been shown to have the potential to metabolize lignocellulose. These included Lactiplantibacillus pentosus, Levilactobacillus brevis, and Lactiplantibacillus plantarum [START_REF] Garde | Lactic Acid Production from Wheat Straw Hemicellulose Hydrolysate by Lactobacillus Pentosus and Lactobacillus Brevis[END_REF][START_REF] Zhang | Lactic Acid Production from Biomass-Derived Sugars via Co-Fermentation of Lactobacillus Brevis and Lactobacillus Plantarum[END_REF]. Of the 15 L. pentosus strains tested, five strains-DPC 6616, DPC 6619, and DPC 6620, isolated from silage; and DPC 6622 and DPC 6623, isolated from olives-were also able to grow on arabinose and xylose. The two L. brevis strains tested-DPC 6427, isolated from silage, and DPC 6730, isolated from Japanese pickles-were able to grow on arabinose and xylose. Of the nine L. plantarum strains tested, only one strain-DPC 6429, isolated from hand rinse-was able to grow on arabinose and xylose.

The 11 strains that were determined to exhibit good growth (+) in the qualitative agarbased assay were further tested in liquid media, and growth rates were calculated. Growth rates were highly variable, so mean growth rates were calculated using the Spline growth model (Table 2).

Table 2. Growth rates of test strains on hexoses and pentoses (Spline model). The mean of the maximum growth rate (OD600 μmax (h -1 )) and standard deviation (SD) for every strain/sugar combination is given. Generally, most of the environmental L. lactis tested shown in Table 2 were able to ferment arabinose and xylose as the sole carbon source, with comparable μmax values by Lactiplantibacillus pentosus and Levilactobacillus brevis strains, which were previously shown to grow in these sugars. Most strains had higher growth rates on arabinose rather than xylose, and only two strains had higher growth rates in xylose compared to arabinose: DPC6765 and DPC6730. L. lactis strains DPC6758 and DPC6762, isolated from green peas and baby corn, had comparable growth rates of 0.081 and 0.078 growing in arabinose, respectively. These growth rates are comparable to the four strains with the highest μmax (0.085-0.097) growing in arabinose, which were all Lactiplantibacillus pentosus strains (DPC 6622, DPC 6619, DPC 6623, and DPC 6620). With regards to xylose, the four strains with the highest μmax (0.056-0.077) were Levilactobacillus brevis strain DPC 6427 and Lactiplantibacillus pentosus strains DPC 6619, DPC 6622, and DPC 6623. The environmental L. lactis strain DPC 6764 showed with a comparable growth rate of 0.046, and all the rest of the environmental L. lactis strains had μmax values ranging from 0.018 to 0.035. It was of interest that the best performing strains could grow as well on arabinose and xylose as galactose, which is released during the fermentation of the major milk sugar, lactose.

Environmental L. lactis Strains Exhibit Cellulolytic Activity

The preliminary qualitative cellulolytic assay (CMC agar) allowed for the identification of putative positive strains based on the appearance of a halo on the cell culture after flooding the agar plate with Gram's iodine (Figure 2). The strains that showed the halo were classified as positive (+) strains (Figure 3). All the positive strains are L. lactis, isolated from environmental sources such as green peas and grass. None of the other species tested (Lactiplantibacillus pentosus, Levilactobacillus brevis and Lactiplantibacillus plantarum) showed cellulolytic activity. Strains that tested positive on the agar assay were selected for further quantification of cellulolytic activity degradation (DNS-based enzymatic assay), by calculating the cellulolytic activity (mg mL -1 min -1 ).

Figure 3. Cellulolytic activity (mg mL -1 min -1 ) in the quantitative DNS assay for all the environmental L. lactis isolates that were positive on CMC agar. The values represent the average of triplicates (mean), the error bars, and the standard deviation (SD).

As reported in Figure 3, all 10 strains are L. lactis environmental isolates, of the 21 environmental isolates tested. These positive strains include five isolates derived from grass, (DPC 6760, DPC 6761, DPC 6855, DPC 6858, and DPC 6860), four isolates derived from green peas, (DPC 6754, DPC 6755, DPC 6756, and DPC 6758), and one isolate derived from mung bean sprouts, KF147. Those strains were further tested in a quantitative assay. The strains with the highest cellulolytic activity (mg mL -1 min -1 ) were DPC 6761 (Lactococcus lactis isolated from grass), and DPC 6760 (Lactococcus lactis isolated from grass), with a value of 0.839 and 0.755 mg mL -1 min -1 , respectively (Figure 3). This proves the previously unexplored capability of L. lactis environmental isolates to metabolize cellulose and potentially contribute to lignocellulose degradation.

In order to facilitate the visualization of all the strains used in this study and all the phenotypic tests performed, a Supplementary Table is provided (Table S3). Overall, only six environmental L. lactis strains were able to both metabolize pentoses and showed cellulolytic activity-green peas isolates DPC 6754, DCP 6755, DPC 6756, and DPC 6758, grass isolate DPC 6760, and mung bean sprouts isolate KF147 (Table S3). Some strains that were able to metabolize arabinose and xylose did not show cellulolytic activity-DPC 6759, isolated from green peas, DPC 6762, isolated from baby corn and DPC 6763, DPC 6764, and DPC 6765, isolated from grass. On the other hand, some L. lactis environmental isolates with cellulolytic activity could not metabolize arabinose and xylose-DPC 6761, DPC 6855, DPC 6858, and DPC 6860-all isolated from grass. This shows that these two abilities (cellulolytic activity and pentose sugars fermentation) do not appear to be correlated.

Discussion

In this study, the ability of six L. lactis strains isolated from diverse, primarily plantbased environments to potentially metabolize plant biomass (whose main component is lignocellulose) was demonstrated, by proving their ability to metabolize pentoses commonly derived from lignocellulose (arabinose and xylose), and by showing cellulolytic activity. Initially, their ability to grow on the main fermentable pentoses released after lignocellulose breakdown (arabinose and xylose) was demonstrated. Out of the 21 L. lactis strains, 11 were able to grow in the presence of arabinose and xylose as the sole sugar source. Those strains were isolated from green peas, grass, baby corn, and mung bean sprouts. L. lactis DPC 6758 and DPC 6762, isolated from green peas and baby corn, had Cellulolytic activity (mg/ml/min) Strains comparable growth rates to the highest μmax values of Lactiplantibacillus pentosus and Levilactobacillus brevis strains growing in arabinose. Moreover, environmental L. lactis strains also showed μmax values comparable to the highest values of Levilactobacillus brevis and Lactiplantibacillus pentosus strains growing in xylose as the sole sugar source. This proves the ability of certain environmentally derived L. lactis strains to metabolize the pentose sugars released after lignocellulose breakdown: arabinose and xylose. Ten L. lactis strains out of the 21 tested showed cellulolytic activity in the qualitative agar-based assay and were further tested to determine the extent of cellulolytic activity. Out of the 21 strains, six environmental L. lactis strains were able to both metabolize the pentose sugars and had cellulolytic activity, proving our hypothesis about their potential to metabolize lignocellulosic feedstocks.

The diverse metabolic capabilities and lifestyle adaptations of wild type 'non-dairy' (here referred to as 'environmental' [START_REF] Passerini | Genes but Not Genomes Reveal Bacterial Domestication of Lactococcus Lactis[END_REF]) L. lactis strains have previously been shown. One of those capabilities is related to their ability to metabolize a wide variety of sugars. Previous studies have revealed how some plant isolates (in contrast to their dairy counterparts) were able to grow on sugars like arabinose and xylose [START_REF] Siezen | Genome-Scale Genotype-Phenotype Matching of Two Lactococcus Lactis Isolates from Plants Identifies Mechanisms of Adaptation to the Plant Niche[END_REF]Passerini et al., 2013). One of these strains was L. lactis KF147, used in this study as a positive control, which proved the same capabilities to metabolize those pentose sugars. However, very few other environmental L. lactis strains had been tested on those pentoses sugars to prove this theory. This study supports that hypothesis. Moreover, previous studies have shown the presence of genes involved in the breakdown of plant polymers in a diverse group of environmental L. lactis strains through comparative genome hybridization [START_REF] Siezen | Genome-Scale Diversity and Niche Adaptation Analysis of Lactococcus Lactis by Comparative Genome Hybridization Using Multi-Strain Arrays[END_REF]. These genes include those involved in the arabinose metabolism, such as the complete arabinose gene cluster araADBTFPR, and xylose metabolism, such as genes xynA, xynP, xynQ, and xynS. A preliminary analysis of the available genomes from our strain collection (L. lactis ssp. lactis KF147, L. lactis ssp. lactis DPC 6756, L. lactis ssp. lactis DPC 6853, L. lactis ssp. cremoris DPC 6856, L. lactis ssp. cremoris DPC 6855, and L. lactis ssp. cremoris DPC 6860) using Scoary [START_REF] Brynildsrud | Rapid Scoring of Genes in Microbial Pan-Genome-Wide Association Studies with Scoary[END_REF] did not clearly show a genotype-phenotype correlation with regard to the metabolism of these sugars. Further whole genome sequencing is underway in order to understand the genetic basis for the sugar metabolism demonstrated here.

This study proves the diverse capabilities of certain environmental L. lactis strains to ferment plant-related sugars such as arabinose and xylose. Apart from more diversity in sugar metabolization, other diverse capabilities have been reported in environmental L. lactis isolates, such as the presence of gene clusters for exopolysaccharide production [START_REF] Siezen | Genome-Scale Genotype-Phenotype Matching of Two Lactococcus Lactis Isolates from Plants Identifies Mechanisms of Adaptation to the Plant Niche[END_REF], and the esterolytic activity of the environmental strains [START_REF] Naranjo | Superior Esterolytic Activity in Environmental Lactococcus Lactis Strains Is Linked to the Presence of the SGNH Hydrolase Family of Esterases[END_REF]. In terms of cellulolytic activity, little is known about the ability of wild-type L. lactis to metabolize cellulose. Previous studies have constructed engineered L. lactis strains with genes coding for a GH6 cellulase, endoglucanase, cellobiohydrolase, and β-glucosidase, in order to be able to metabolize cellulose into lactic acid [START_REF] Liu | Enhancement of Lignocellulosic Degradation in High-Moisture Alfalfa via Anaerobic Bioprocess of Engineered Lactococcus Lactis with the Function of Secreting Cellulase[END_REF][START_REF] Singhvi | D-(-)-Lactic Acid Production from Cellobiose and Cellulose by Lactobacillus Lactis Mutant RM2-24[END_REF][START_REF] Liu | Effects of Cellulolytic Lactic Acid Bacteria on the Lignocellulose Degradation, Sugar Profile and Lactic Acid Fermentation of High-Moisture Alfalfa Ensiled in Low-Temperature Seasons[END_REF]. In this study, the untapped cellulolytic activity of wild environmental L. lactis was revealed. In fact, no native cellulolytic L. lactis has ever been identified before [START_REF] Tarraran | Alternative Strategies for Lignocellulose Fermentation through Lactic Acid Bacteria: The State of the Art and Perspectives[END_REF].

One of the main challenges of lignocellulosic feedstocks metabolization via LAB is the need for physical, and/or chemical, and/or enzymatic pre-treatment(s) of biomass, which in turn releases inhibitory compounds to the media, as well as an inefficient saccharification of biomass [START_REF] Tarraran | Alternative Strategies for Lignocellulose Fermentation through Lactic Acid Bacteria: The State of the Art and Perspectives[END_REF]. The resistance to such inhibitory compounds should be tested in future studies with those strains that were both able to metabolize cellulose and pentoses sugars. In the past, LAB have been co-cultivated with native cellulolytic microorganisms in order to replace the saccharification of lignocellulosic biomass via exogenously supplemented cellulases. Several studies have successfully converted cellulolytic biomass to products like butanol or ethanol using this co-cultivation approach [START_REF] Brethauer | Consolidated Bioprocessing of Lignocellulose by a Microbial Consortium[END_REF][START_REF] Wen | Artificial Symbiosis for Acetone-Butanol-Ethanol (ABE) Fermentation from Alkali Extracted Deshelled Corn Cobs by Co-Culture of Clostridium Beijerinckii and Clostridium Cellulovorans[END_REF]. These limitations have added to the high cost of the added cellulases [START_REF] Okano | Biotechnological Production of Enantiomeric Pure Lactic Acid from Renewable Resources: Recent Achievements, Perspectives, and Limits[END_REF], and could be overcome with the use of native cellulolytic LAB strains, like the ones reported in this study. However, further phenotypic research is needed in order to evaluate the capability of those environmental L. lactis strains screened in a real-life plant biomass derived from a plant-based waste stream. Even though the most well-studied commercial product for the Lactiplantibacillus genus from lignocellulose bioconversion is lactic acid [START_REF] Cubas-Cano | Biotechnological Advances in Lactic Acid Production by Lactic Acid Bacteria: Lignocellulose as Novel Substrate. Biofuels Bioprod[END_REF], other industrially relevant compounds, such as biofuel, could be also explored [START_REF] Jiang | State of the Art Review of Biofuels Production from Lignocellulose by Thermophilic Bacteria[END_REF].

The L. lactis strains used in this study were compared to the species Lactiplantibacillus pentosus, Lactiplantibacillus plantarum, and Levilactobacillus brevis. Lactiplantibacillus is the widest and most diverse genus of lactic acid bacteria [START_REF] Castillo Martinez | Lactic Acid Properties, Applications and Production: A Review[END_REF]. Even though LAB are commonly found in dairy environments, previous research has shown the niche adaptation of lactobacilli strains isolated from other environments, such as meat, plant, and sourdough [START_REF] Stefanovic | A Genomic Perspective on Niche Adaptability in Lactobacillus[END_REF]. In this study, L. lactis strains did not only show their ability to metabolize specific pentose sugars, but also the growth rates in the pentoses arabinose and xylose were very comparable to the best-performing lactobacilli. The high of other species such as Lactiplantibacillus pentosus, Lactiplantibacillus plantarum, and Levilactobacillus brevis was expected, since they had previously shown their ability to utilize the pentose sugars [START_REF] Boguta | Screening of Lactic Acid Bacteria for Their Potential as Microbial Cell Factories for Bioconversion of Lignocellulosic Feedstocks[END_REF][START_REF] Garde | Lactic Acid Production from Wheat Straw Hemicellulose Hydrolysate by Lactobacillus Pentosus and Lactobacillus Brevis[END_REF][START_REF] Zhang | Lactic Acid Production from Biomass-Derived Sugars via Co-Fermentation of Lactobacillus Brevis and Lactobacillus Plantarum[END_REF]. However, only some of the L. lactis strains showed cellulolytic activity, and none of the other three species evaluated in this study (in the preliminary qualitative assay) showed cellulolytic activity. This is interesting, since even though most studies rely on the addition of external cellulolytic enzymes for the bioconversion of lignocellulosic material by L. pentosus and L. plantarum [START_REF] Hu | High-Titer Lactic Acid Production by Lactobacillus Pentosus FL0421 from Corn Stover Using Fed-Batch Simultaneous Saccharification and Fermentation[END_REF][START_REF] Shi | Nutrient Value of Fish Manure Waste on Lactic Acid Fermentation by Lactobacillus Pentosus[END_REF], some recent studies have found strains like L. plantarum RI 11 with the ability to produce extracellular cellulolytic enzymes, such as endoglucanase, exoglucanase, and β-glucosidase, without the addition of external enzymes [START_REF] Zabidi | Enhancement of Versatile Extracellular Cellulolytic and Hemicellulolytic Enzyme Productions by Lactobacillus Plantarum RI 11 Isolated from Malaysian Food Using Renewable Natural Polymers[END_REF]. However, the L. plantarum screened in this study were not able to grow on cellulose. Nonetheless, we understand recent concerns about the use and the accuracy of a DNS assay for the reducing sugars, since other carbonyl groups could potentially react with the DNS, leading to incorrect yields of reducing sugars [START_REF] Deshavath | Pitfalls in the 3, 5-Dinitrosalicylic Acid (DNS) Assay for the Reducing Sugars: Interference of Furfural and 5-Hydroxymethylfurfural[END_REF]. These results are in accordance to those found in previous studies, where it was found that even though L. plantarum contains 55 genes encoding 18 glycoside hydrolases, none of them are strict cellulases [START_REF] Moraïs | Establishment of a Simple Lactobacillus Plantarum Cell Consortium for Cellulase-Xylanase Synergistic Interactions[END_REF]. Therefore, L. plantarum strains may lack the inherent ability to metabolize cellulose, while some L. lactis strains tested in this study may have acquired the ability to metabolize cellulose in response to niche specialization.

These findings highlight that wild environmental Lactococcus lactis have the potential to become platforms for second-generation bioconversion processes. Further work is required in order to test the biotransformation potential of these strains in a cellulosic waste stream substrate. The significance of this study relies on the possibility for potentially using these environmental strains to biotransform plant biomass into products such as biofuel and organic chemicals [START_REF] Kumar | Bioconversion of Lignocellulosic Biomass: Biochemical and Molecular Perspectives[END_REF], helping to cope with the increasing energy demand, increasing temperatures, and becoming a renewable alternative to fossil fuels.

Supplementary Materials:

The following supporting information can be downloaded at: www.mdpi.com/article/10.3390/applmicrobiol2040061/s1. Table S1: Bacterial growth on the four different sugars, indicated as good (+) where clear visible bacterial growth was observed, moderate (/) where faint bacterial growth was observed, and no growth (-) where no growth was observed, in comparison with 10% mMRS + glucose, for the Study group: non-engineered environmental L. lactis strains used in this study. Table S2: Bacterial growth on the four different sugars, indicated as good (+) where clear visible bacterial growth was observed, moderate (/) where faint bacterial growth was observed, and no growth (-) where no growth was observed, in comparison with 10% mMRS + glucose for other species/subspecies with proven lignocellulose metabolization potential used in this study for comparison to our study group. Table S3: All the bacterial strains used in this study, including their isolation source and the main tests performed in this study. Pentose utilization test refers to (+) when the strain was able to grow in all four sugars (glucose, galactose, arabinose, and xylose). mMRS + Glucose, mMRS + Galactose, mMRS + Arabinose, and mMRS + Xylose refers to the mean of the growth rates (OD600 μmax (h -1 )). Cellulolytic activity refers to the mean of the DNS-based assay (mg mL -1 min).

Figure 1 .

 1 Figure 1. Pentose utilization agar test, with 16 strains (out of the 47 strains tested) after 48 h of incubation at 30 °C. The same strains across all plates are: (1) Lactiplantibacillus pentosus DPC 6627, (2) P.

  .

Figure 2 .

 2 Figure 2. CMC agar test showing 5 cellulolytic positive strains (halo zone after flooding with Gram's iodine) and a negative strain (C-). The appearance of a halo on the cell culture indicates cellulose metabolization in the positive strains. Strains shown are: (1) L. lactis ssp. lactis KF147, (2) L. lactis ssp. lactis DPC 6760, (3) L. lactis ssp. lactis DPC 6761, (4) L. lactis ssp. lactis DPC 6754, (5) L. lactis ssp. lactis DPC 6755, and (C-) L. brevis DPC 6427.

  Author Contributions: Conceptualization, D.R.N. and O.M.; methodology, D.R.N. and O.M.; formal analysis, D.R.N.; writing-original draft preparation, D.R.N.; writing-review and editing, O.M. and M.C.; supervision, A.T.; project administration, O.M.; funding acquisition, O.M. All authors have read and agreed to the published version of the manuscript.

Table 1 .

 1 Bacterial strains used in this study. DPC CC is the Teagasc DPC Culture Collection housed at the Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland.

	Strain Number Species/Subspecies (ssp)	Isolation Source	Source or Reference
	DSM 20284	Pediococcus acidilactici	Barley	[30]
	KF147	Lactococcus lactis	Mung bean sprouts [31], DPC CC 1
	DPC 6754	Lactococcus lactis ssp. lactis	Green peas	[20], DPC CC
	DPC 6755	Lactococcus lactis ssp. lactis	Green peas	[20], DPC CC
	DPC 6756	Lactococcus lactis ssp. lactis	Green peas	[20], DPC CC
	DPC 6757	Lactococcus lactis ssp. lactis	Green peas	[20], DPC CC
	DPC 6758	Lactococcus lactis ssp. lactis	Green peas	[20], DPC CC
	DPC 6759	Lactococcus lactis ssp. lactis	Green peas	[20], DPC CC
	DPC 6760	Lactococcus lactis ssp. lactis	Grass	[20], DPC CC
	DPC 6761	Lactococcus lactis ssp. lactis	Grass	[20], DPC CC
	DPC 6762	Lactococcus lactis ssp. lactis	Baby corn	[20], DPC CC
	DPC 6763	Lactococcus lactis ssp. lactis	Grass	[20], DPC CC
	DPC 6764	Lactococcus lactis ssp. cremoris	Grass	[20], DPC CC
	DPC 6765	Lactococcus lactis ssp. cremoris	Grass	[20], DPC CC
	DPC 6853	Lactococcus lactis ssp. lactis	Corn	[21], DPC CC
	DPC 6854	Lactococcus lactis ssp. cremoris	Grass	[21], DPC CC
	DPC 6855	Lactococcus lactis ssp. cremoris	Grass	[21], DPC CC
	DPC 6856	Lactococcus lactis ssp. cremoris	Rumen	[21], DPC CC
	DPC 6857	Lactococcus lactis ssp. cremoris	Grass	[21], DPC CC
	DPC 6858	Lactococcus lactis ssp. cremoris	Grass	[21], DPC CC
	DPC 6859	Lactococcus lactis ssp. cremoris	Grass	[21], DPC CC
	DPC 6860	Lactococcus lactis ssp. cremoris	Grass	[21], DPC CC
	DPC 6417	Lactiplantibacillus plantarum	Teat rinse	DPC CC
	DPC 6421	Lactiplantibacillus plantarum	Bovine feces	DPC CC
	DPC 6427	Levilactobacillus brevis	Silage	DPC CC
	DPC 6428	Lactiplantibacillus plantarum	Silage	DPC CC
	DPC 6429	Lactiplantibacillus plantarum	Hand rinse	DPC CC
	DPC 6430	Lactiplantibacillus plantarum	Water milking yard DPC CC
	DPC 6606	Lactiplantibacillus pentosus	Olives	DPC CC
	DPC 6607	Lactiplantibacillus pentosus	Olives	DPC CC
	DPC 6608	Lactiplantibacillus pentosus	Olives	DPC CC
	DPC 6609	Lactiplantibacillus pentosus	Olives	DPC CC
	DPC 6616	Lactiplantibacillus pentosus	Silage	DPC CC
	DPC 6617	Lactiplantibacillus pentosus	Silage	DPC CC
	DPC 6618	Lactiplantibacillus pentosus	Silage	DPC CC
	DPC 6619	Lactiplantibacillus pentosus	Silage	DPC CC
	DPC 6620	Lactiplantibacillus pentosus	Olives	DPC CC
	DPC 6622	Lactiplantibacillus pentosus	Olives	DPC CC
	DPC 6623	Lactiplantibacillus pentosus	Olives	DPC CC
	DPC 6624	Lactiplantibacillus pentosus	Olives	DPC CC
	DPC 6625	Lactiplantibacillus pentosus	Olives	DPC CC

DPC CC is the Teagasc DPC Culture Collection housed at the Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland.

Acknowledgments:

The authors would like to thank Peter Myintzaw (Munster Technological University) for assistance with Growthcurver.

Funding: This research was funded by TEAGASC (project ref. MDBY0402). D. Román Naranjo is supported by a Teagasc Walsh Scholarship (ref. 2018036). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.

Data Availability Statement: Not applicable.

Conflicts of Interest:

The authors declare no conflicts of interest.


Sarah Djeddi

David Reiss

Alexia Menuet

Sébastien Freismuth

Juliana De

Carvalho Neves

Sarah Djerroud

Xènia Massana Munoz

Anne-Sophie Sosson

Christine Kretz

Wolfgang Raffelsberger

Juliana De Carvalho Neves

Xènia Massana-Muñoz

Céline Keime

Olivier M Dorchies

Julie Thompson

Jocelyn Laporte

Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategies

Keywords: genetic disease, congenital myopathy, centronuclear myopathy, myotubular myopathy, XLMTM, MTM1, myotubularin, omics, biomarker, myostatin, RNA interference Background

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Mtm1 /y knockout mouse develops a progressive myopathy with a histopathology mimicking patient hallmarks 23 . Additional Mtm1 knockout lines were generated and showed a similar phenotype, while the Mtm1 RC/y knock-in led to a milder phenotype [24][25][26] . Concerning Dnm2, knock-in mice for the most common mutations in the mildest form (Arg465Trp ; Dnm2 RW/+ ) or the severe neonatal form (Ser619Leu ; Dnm2 SL/+ ) were generated and reproduce a mild or severe muscle weakness, respectively, with CNM-like histopathology without centralized nuclei 27,28 . For Bin1, full loss of BIN1 in mice is perinatally lethal, preventing the comparison with the other CNM models 29,30 . We recently created a mouse model with a skeletal muscle specific Bin1 deletion that is viable and faithfully reproduces the decreased muscle force and most histopathological hallmarks of CNM ( ). Here, we focus on omics analysis of Mtm1 /y , Dnm2 SL/+ mice, since they represent faithful models for the three canonical CNM forms and the mice share a similar skeletal muscle organization with patients.

Several therapeutic proof-of-concepts were recently validated in different CNM models, including the three CNM mice investigated here 17 . Adeno-associated virus (AAV) transduction of MTM1 or its closer homolog MTMR2 rescued the Mtm1 /y mouse, and AAV-MTM1 was further validated in the MTM1

Labrador model and recently injected in patients in a clinical trial [31][32][33] . Downregulation of DNM2 level were found increased at least in Mtm1 /y mice and MTM1 patients, whereas normalization of DNM2 level rescued the Mtm1 /y mouse, the and Dnm2 RW/+ Dnm2 SL/+ mice 28, 34-36 . DNM2 was reduced through three methods : genetic cross with a Dnm2 +/- TgBIN1 mouse or AAV-BIN1 expressing human BIN1 rescued Mtm1 /y and mice 39 .

Mtm1 /y
mouse, potentially representing a drug repurposing strategy 40,41 . Additional potential therapies have been tested in mice and other CNM models, and include Dnm2 allele-specific silencing or trans-splicing, Pik3c2b downregulation, mTOR or acetylcholine esterase inhibitors 17 .

Mtm1 /y , Dnm2 SL/+ mice either developing the disease or treated with 3 different therapies including two methodological approaches for one of the targets. We identified disease and therapeutic molecular signatures common to the three main forms of CNM.

Results

Animal models, treatments and omics strategies Mtm1 /y mice Dnm2 SL/+ mice Mtm1 /y mice Mtm1 /y mice (

Mtm1 /y mice Mtm1 /y TgBIN1
Dnm2 +/-mice (Mtm1 /y Dnm2 +/- Dnm2 SL/+ mice and compared to injection of PBS or control ASO. All these treated cohorts were analyzed by RNAseq in TA at 7 w and compared to the above untreated mice. In addition, RNAseq and mass spectrometry of TA from Mtm1 /y Dnm2 +/-mice was performed at

Influence of the genetic and environment backgrounds

Mtm1 /y mouse line Mtm1 /y mouse Mtm1 /y mice through disease progression Mtm1 /y mice at pre-symptomatic age (E18.5), early (2 w) and late (7 w) disease stages (Figure 1a). We used the cohort MTM1-a, including untreated Mtm1 /y mice, Mtm1 /y mice rescued by Dnm2 genetic downregulation, treated and healthy Mtm1 /y Dnm2 +/-mice, and their WT littermates (Table S1).

Table S7)

Mtm1 /y mice compared to WT disease signature and a common therapy signature indicating potential therapeutic targets and biomarkers to follow disease severity or progression and therapy efficacy.

Discussion

We performed a multi-omics meta-analysis of centronuclear myopathies through the comparison of mouse models for the three main CNM forms and the comparison of three therapies with different targets.

We identified disease signatures for MTM1-CNM conserved in different genetic and environmental backgrounds and in different species (mouse, dog, human). Longitudinal transcriptome and proteome analysis of Mtm1 /y mice suggested early causal pathomechanisms and late compensatory adjustments.

A disease signature common to the three CNM forms was defined, suggesting a common pathomechanism for CNM independent of the mutated genes. Comparison of the molecular effect of the different therapies revealed a correlation between the molecular normalization and the phenotypic rescue.

In addition, novel potential therapeutic targets were suggested. Further molecular and biochemical investigations identified several biomarkers for disease state and therapy efficacy in muscle (RNA, proteins) and in plasma.

Pathomechanism of centronuclear myopathies

We compared the muscle transcriptomes of the Mtm1 /y , Bin1 mck-/-and Dnm2 SL/+ mice faithfully reproducing the muscle weakness and histological hallmarks of the three main CNM forms 28,49 . The overall transcriptomes easily distinguished the CNM models from their WT littermates.

For MTM1-CNM, to identify the specific disease signature independent from the genetic backgrounds or environment, we increased data heterogeneity by characterizing several Mtm1 /y groups on 129Pas, C57BL/6J or mixed backgrounds bred in different animal houses, and then focused on the common transcriptome dysregulation. Next, this signature was compared to available transcriptome data from one MTM1 canine model and to a partial microarray analysis (4200 genes) of patient muscle biopsies 45,46 .

Our conclusions were supported by previous findings. Dysregulation of NMJ components (CHRNA1, CHRND, CHRNG) were recently reported in the MTM1 dog and alteration of NMJ function was suggested in a mtm1 knockdown zebrafish and in Mtm1 mouse models 46,50,51 . We found a high increase in Sln expression in the three CNM mouse models, and upregulation of Sln was previously reported following microarray analysis of the Mtm1 /y mouse 49 . In addition, longitudinal analyses of the muscle transcriptome and proteome of Mtm1 /y mice at pre-symptomatic (E18.5), early (2 w) and late (7 w) disease stages highlighted the same dysregulated pathways, although the same dysregulated genes/proteins were not necessarily found (Figures 3,4). These ages were chosen to potentially distinguish between early causes of the disease and late consequences or compensatory mechanisms.

Further functional investigations are needed to confirm their causality. In addition, the proteome analysis only covered the most abundant proteins. For example, BIN1 and DNM2 were not detected in the muscle proteomes. However, BIN1 and DNM2 proteins were both increased in Mtm1 /y mice using specific antibodies by western blot (Table 3) 34,39 . Interestingly, we recently showed that the Mtm1 /y mice can be rescued by either decreasing DNM2 or increasing BIN1 37,39 , strongly supporting the idea that DNM2 increase is a disease cause while BIN1 increase is a compensatory mechanism.

The comparison of the Mtm1 /y , Bin1 mck-/-and Dnm2 SL/+ muscle transcriptomes revealed a common disease signature, encompassing sarcomere organization, muscle contraction, muscle development and cell adhesion. All these pathways were already the main ones found dysregulated at 2 w in Mtm1 /y mice, supporting the hypothesis that their dysregulation represents the main pathomechanism for all CNM forms (Figures 3, 4, 5). In addition to these pathways, inflammation activation (transcriptome) and ribosomal biogenesis (proteome) were found only at 7 w suggesting that their dysregulation is a consequence or a response to the disease state. Based on these data and on the knowledge that the three CNM proteins regulate membrane remodeling, we propose a model for the pathomechanism of CNM.

Alteration of the triad membrane structure would lead to impaired calcium signaling and defective muscle contraction, explaining the strong muscle weakness and hypotonia seen in patients. The myofiber hypotrophy seen in patients and mouse models correlates with alteration of muscle development and regeneration RNA markers, and may be related to dysregulation of IGF modulators as IGFBP2 or/and to the reported decrease in satellite cells in patients 52 . The strong myofiber hypotrophy would then trigger a later adaptation on protein homeostasis, as underlined by the increase of the ribosome biogenesis genes found only at 7 w. Indeed, defects of protein homeostasis correlate with the alteration of autophagy and the ubiquitin-proteasome pathways found in Mtm1 /y mice 25,53,54 . In parallel, a primary defect in cell adhesion would impact the basement membrane and mechanotransduction and may explain defects in muscle contraction and also the altered fiber shape found in patients and mice. This is in agreement with the accumulation of integrins in Mtm1 /y mouse and patient myofibers, and with the proposed link between MTM1 and beta integrin recycling 39,55,56 . The observed increased in interfiber space, together with the alteration of muscle regeneration, would cause the late increase in genes implicated in inflammation activation. As we detected a significant increase in RNA markers of inflammatory cells while performing whole tissue RNAseq, we conclude there is a significant infiltration of inflammatory cells that was confirmed by immunofluorescence labelling and quantification (Figure 5d-e). An inflammatory component was not previously reported for CNM but is common in dystrophies 57 .

Furthermore, the dysregulated pathways found here were barely underlined previously in the other CNM forms linked to BIN1 or DNM. Overall, although some of these pathways were previously found altered in MTM1-CNM, these omics analyses allowed to obtain a more complete and detailed overview of the pathomechanisms and extend it to several other CNMs. The GO term analysis of the common disease signature identified here for different CNM forms mostly reflects general muscle dysfunction and compensatory mechanisms put in place by the myofibers to cope with these defects, and thus highlights pathways also dysregulated in a large number of muscle diseases. However, differences appear when looking at the gene level that may reveal plasticity to impact or compensate the main muscle pathways depending on the sub-class of myopathies and on the primary genetic defect.

To a greater extent, we found several genes mutated in different neuromuscular diseases in the common CNM disease signature. Notably, LMNA is mutated in Emery-Dreifuss muscular dystrophy and the encoded protein lamin A/C regulates nuclear envelope stability (MIM#181350, 616516) 58 . Of note, lamin A/C and BIN1 both bind the LINC complex that regulates nuclear shape and positioning and BIN1-CNM patients have an altered nuclear envelope structure 59 . KLHL40 is mutated in another congenital myopathy and is a substrate adaptor for the E3-ubiquitin ligase Cullin-3 (MIM#615348) 60,61 . Similarly, MTM1 binds the Cullin-3 partner UBQLN2 and MTM1-CNM is linked to defects in the ubiquitinproteasome pathway 54 . Several dysregulated genes in all CNM models are mutated in cardiomyopathy :

SCN5A (MIM#601154), TNNT2 (MIM#601494) and MYL4 (MIM#617280). In addition, MYH2 and TNNC1 found upregulated in the proteome of 2 w Mtm1 /y mice are also mutated in a proximal myopathy (MIM#605637) or a cardiomyopathy (MIM#611879), respectively. Such findings are commonly observed in myopathies where upregulation of genes usually expressed in embryonic muscle or adult cardiac muscle are re-expressed in the affected skeletal muscle. Finally, CHRNA1 (MIM#601462) and CHRND (MIM#616322) are mutated in congenital myasthenic syndromes, correlating with the defect in NMJ found in MTM1-CNM models 50,51,62 .

Common therapeutic targets for centronuclear myopathies

We compared here three therapies involving three different targets in MTM1-CNM models, BIN1 overexpression, tamoxifen treatment and DNM2 regulation, and two methodologies for the latter target.

For the first time, this allows a molecular comparison of the different therapies for CNM. BIN1 overexpression appears to be the most efficient therapy to normalize the molecular defects. The percentage of rescued genes varies greatly with 96% for BIN1 overexpression, 36% for DNM2 downregulation and 0.5% for tamoxifen in the MTM1-CNM mouse model. In the AAV-MTM1 treated dogs, the percentage of rescued genes was 52% and 43% depending on the muscles analyzed 46 . These findings highlight a correlation between the phenotypic and molecular rescue, as modulations of either MTM1, BIN1 or DNM2 improved the lifespan, locomotor and histological phenotypes very efficiently, while tamoxifen treatment resulted in a partial increase in lifespan and a significant amelioration of the histopathology, although to a lesser extent than with genetic crosses 17,31,34,37,[39][40][41] . As a potential explanation to the different rescue efficiency of the transcriptome dysregulation, BIN1 may directly modulate the general transcription program in a disease context, while MTM1 and DNM2 may directly impact on the cellular (proteins, membrane) defects. Indeed, BIN1 binds the transcription factor MYC and can shuttle between the cytoplasm and the nucleus in muscle cells [63][64][65] . Of note, BIN1 overexpression was achieved through genetic cross and is thus chronic from embryogenesis, while AAV-MTM1 and tamoxifen treatments are postnatal. However, transcriptomes comparison between chronic (Dnm2 +/- genetic cross for MTM1-a) and acute DNM2 downregulation (ASO Dnm2 injection for DNM2 and BIN1 cohorts) showed similar percentages of rescued genes: 36% in MTM1-a, 43% in DNM2 and 47% in BIN1 cohorts (Figure 6). The rescuing effect of tamoxifen treatment is not based on transcriptome remodeling but might directly involve membrane and protein functions.

We evaluated the toxicity of the different therapies used in this study by comparing the WT treated versus WT mice. Treatment of WT mice did not show a strong impact on the transcriptomes, while it was not reported in AAV-MTM1 treated dogs. For example, injection of ASO Dnm2 decreased Dnm2 expression but had few off-targets. No detectable phenotypic toxicity were observed in the treated WT mice.

However, in human, even if the same gene will be targeted (either BIN1 or DNM2), the therapeutic compound and formulation may differ and the delivery method and corresponding dose will change.

Here, for BIN1 overexpression we used the human cDNA while for DNM2 downregulation we used antisense oligonucleotides specific to the mouse Dnm2 gene. We also detected the expected overexpression of the human BIN1 gene in the MTM1-b cohort. BIN1 overexpression only changed the expression of three genes in the treated WT mice (Figure S9), while rescuing most transcriptome dysregulation in the Mtm1 /y mice, suggesting this therapy modulates the transcriptome mainly in a disease context (i.e. normalization).

The present data revealed several potential targets that were not directly targeted in the experiments (i.e. not MTM1, BIN1 nor DNM2). Genes of interest are expected to be dysregulated in disease and normalized upon efficient therapies, i.e. part of the therapy signature. In addition, known drugs targeting these gene products may be an asset, as it will allow drug repurposing and a faster clinical development.

Several genes coding for subunits of the acetylcholine receptor are dysregulated. In particular acetylcholine esterase inhibitors used in clinical trial to treat myasthenic syndromes were tested with some success in different CNM forms 62 . Scn5a is also found upregulated in the disease signature and normalized in the therapy signature, and encodes a subunit of the sodium channel that can be inhibited by quinidine, a stereoisomer of quinine. Mstn encoding the myokine myostatin, an inhibitor of muscle growth, is significantly decreased in disease models of all cohorts except the Bin1 mck-/-mouse (Log2FC = -0.6 while our threshold was -1). Inhibitors of myostatin are being tested in the clinic for other muscle diseases, and one of them (ActRIIB-mFc) showed only a very mild amelioration of the Mtm1 RC/y knockin mouse 66 . The mild amelioration can be explained by the fact that myostatin is already strongly decreased in the disease state and thus could hardly be better suppressed 67 . Sln encoding the calcium regulator sarcolipin is strongly upregulated in disease models of all cohorts except the MTM1-c cohort.

Reducing sarcolipin expression through genetic cross or shRNA improved Duchenne muscular dystrophy phenotypes in mice 68 . As a last example, myosins and troponins also meet these criteria and are targeted by several pharmacological regulators that may improve the muscle contraction defects of CNM. Indeed, all discussed modulations should be first validated in laboratory models, as it is unclear if dysregulation of some pathways are disease causing or compensatory.

Potential biomarkers for disease progression and therapy efficacy

We developed a strategy to identify potential biomarkers, combining RNAseq, RT-qPCR and western blotting in muscle with mass spectrometry and ELISA assays in blood, supported by database and literature mining. The validity of these biomarkers for monitoring disease progression and therapy efficacy has to be confirmed in human samples. This will require muscle and blood sampling of untreated and treated patients with different CNM forms together with adequate aged-matched controls. We found that Mstn RNA level is strongly decreased in Mtm1 /y and Dnm2 SL/+ mice and to a lesser extent in Bin1 mck- /-(Log2FC=-0.6), and was normalized upon modulation of MTM1, BIN1 and Dnm2 (Figures S5, S9, S10, S11) 46 . In agreement, MSTN was recently found decreased in plasma from MTM1-and DNM2-CNM patients and responded to ASO Dnm2 treatment in Mtm1 /y mice 69 . In addition, MSTN plasma level was also normalized upon BIN1 overexpression (Figure 7c). ANXA2 is a calcium-dependent phospholipidbinding protein that has a role in muscle repair 70 , and was validated here as a muscle biomarker for all the CNM forms that we have tested. ANXA2 was detected in plasma, increased in the Bin1 mck-/-mouse model, and normalized upon ASO Dnm2 injection. Moreover, several reports cited ANXA2 to be a valuable biomarker in different cancers 71,72 .

In particular, these potential biomarkers could be used in clinical trials to monitor the progression/reversion of the disease or/and efficacy of the therapy. Currently, there are two clinical trials ongoing to treat CNM. Firstly, the clinical trial (NCT03199469) for X-linked myotubular/centronuclear myopathy in patient under 5 years old based on MTM1 gene replacement using AAV. Secondly, a clinical trial based on the decrease/normalization of DNM2 with ASO (DYN101) is ongoing in patients with mutations in MTM1 and DNM2 over 16 years old (NCT04033159) and is planned for patients between 2 and 17 years old (NCT04743557).

Conclusions

Here, we report the first multi-omics analysis of animal models for several CNM forms, and of the effect of different therapies allowing to reveal a common disease signature and a common therapy signature.

We determined the global pathological mechanism and deciphered the molecular impact of therapies.

Longitudinal analyses of the treated and untreated MTM1-CNM model highlight potential causes and consequences of the pathology. In addition, we identified several novel biomarkers detectable in muscle and/or plasma through different validated methodologies. These findings and the associated data should be an asset to the community for further investigations. More generally, this study validates the concept of using omics to identify molecular signatures common to different disease forms or to several therapeutic strategies.

Materials and Methods

Animals

In this study we used different cohorts of mice. The sample size is given in Table S1. The cohort MTM1a (WT, Dnm2 +/-, Mtm1 /y , and Mtm1 /y Dnm2 +/-) was previously phenotyped on a 129Pas genetic

RNA extraction and RNAseq

Transcriptome analysis

Table S17

Liquid digestion Disease signature refers to the common dysregulated genes in the three mouse models compared to WT littermates, while the therapy signature refers to the common genes rescued following the different treatments. mouse models at 7 w. Protein levels are represented as the fold difference from the average of the WT Table S9. List of the 155 common differentially expressed genes for the MTM1-a, MTM1-b, MTM1-c, DNM2 and BIN1 cohorts.

LC-MS/MS Analysis

Table S10. List of DEGs in cohort MTM1-b.

Table S11. List of DEGs in cohort MTM1-c.

Table S12. List of DEGs in cohort DNM2.

Table S13. List of DEGs in cohort BIN1.

Table S14. List of the specific dysregulated genes expressed in MTM1, DNM2 and BIN1 cohorts (Fig 5b).

Table S15. List of the 42 common differentially expressed genes for the MTM1-a, MTM1-b, DNM2 and BIN1 cohorts.

Table S16. List of proteins retrieved by mass spectrometry in serum of WT mice at 8 w.

Table S17. List of primers used for RT-qPCR. Figure S3. GO enrichment analysis for biological processes (BP), cellular component (CC) and molecular function (MF) of the differentially expressed genes in Mtm1 -/y vs WT mice (N =1175 genes) at (a) 2 w and (b) at 7 w (N=1981 genes). GO terms with highest ratio and lowest q-value are represented.

The ratio represents the number of genes dysregulated divided by the total number of genes in the

• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • 2.7
2.8 2.9

3.0 3.1 E18.5 2w 7w log(normalized expression)

• • WT Mtm1 -/ y TNNC1 • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • 2.7
2.8 2.9

3.0 3.1 E18.5 2w 7w log(normalized expression)

• • WT Mtm1 -/ y RPL3 • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • 2.8
• • • • • • • • • • • • • • • • • • • •

background 34 .

 34 The cohort MTM1-b (WT, TgBIN1, Mtm1 /y , and Mtm1 /y TgBIN1) was previously phenotyped on a 50% 129Pas and 50% C57BL/6N genetic background 39 . Both cohorts MTM1-a and MTM1-b were bred in IGBMC animal house in France. The cohort MTM1-c (WT, WT + tamoxifen, Mtm1 /y , and Mtm1 /y + tamoxifen) was previously treated and phenotyped on a 129Pas genetic background40 . Tamoxifen was administered via supplement pellets of diet (30mg/kg of tamoxifen). This cohort was bred in the animal house of the School of Pharmaceutical Sciences of the University of Geneva, Switzerland. The cohort DNM2 (WT + ASO Ctrl, WT + ASO Dnm2, Dnm2 SL/+ + ASO Ctrl, Dnm2 SL/+ + ASO Dnm2) was previously treated and phenotyped on a C57BL/6N genetic background 28 .The cohort BIN1 (WT + PBS, WT + ASO Dnm2, Bin1 mck/-+ PBS, Bin1 mck-/-+ ASO Dnm2) was previously treated and phenotyped on a C57BL/6N genetic background (unpublished). Both DNM2 and BIN1 cohorts were bred in IGBMC animal house in France. DNM2 and BIN1 cohorts were treated weekly from 3 to 7 weeks of age with intraperitoneal injections of 25mg/kg of ASO (IONIS Pharmaceuticals) targeting Dnm2. Only males were analyzed in this study as only Mtm1 /y males but not Mtm1 +/-females are affected. TA muscles were dissected at E18.5, 2w or 7w and obtained from the previous studies. Data from MTM1-d cohort (WT, Mtm1 /y ) was retrieved from Maani et al.41 . This cohort was analyzed on a C57BL/6J genetic background and bred in University of Toronto animal house in Canada. Quadriceps muscle from 5 w old animals were considered.

Figure 1 .

 1 Figure 1. Experimental design. (a) Timeline of the different steps occurring during muscle development

Figure 2 .

 2 Figure 2. MTM1-CNM signature in different species. (a) Venn diagram illustrating the shared dysregulated genes based on the Mtm1 /y vs WT comparison of four mouse cohorts. The percentages of

Figure 3 .

 3 Figure 3. Longitudinal mRNA profiling of Mtm1 -/y mice. (a) Principal component analysis of RNAseq

Figure 4 .

 4 Figure 4. Longitudinal protein profiling of Mtm1 -/y mice. (a) Principal component analysis of mass

Figure 5 .

 5 Figure 5. CNM disease signature in mouse. (a) PCA on RNAseq data on the 155 genes commonly

Figure 6 .

 6 Figure 6. Common therapy signature in CNM mice treated with different therapies. (a) PCA on RNAseq

Figure 7 .

 7 Figure 7. Muscle and circulating biomarkers for disease and rescue states. (a) Venn diagram illustrating

Figure

  Figure S1. (a)Venn diagram illustrating the common dysregulated genes based on the MTM1 vs controls

Figure S2 .

 S2 Figure S2. PCA related to Fig 5b. (a) PC1 and PC2 and (b) PC1 and PC3 are represented.

Figure S9 .

 S9 Figure S9. Number of dysregulated genes and the associated PCA for each cohort for four comparisons

Figure S10 .

 S10 Figure S10. mRNA expression levels of genes of interest in diseased, rescued and control mice in the

Figure S14 .

 S14 Figure S14. Blot related to Fig 7b.

Figure

  Figure S15. (a) Histogram displaying the proportion of genes according to their status and the metric per

  copper ion positive regulation of macrophage cytokine production cellular response to oxidised low-density lipoprotein particle stimulus atrial cardiac muscle cell membrane repolarization anterograde axonal protein transport protein localization to presynapse cellular response to zinc ion autocrine signaling spermine metabolic process response to inactivity response to muscle inactivity response to muscle inactivity involved in regulation of muscle adaptation response to denervation involved in regulation of muscle adaptation regulation of atrial cardiac muscle cell membrane repolarization detoxification of inorganic compound stress response to metal ion regulation of response to macrophage colony-stimulating factor regulation of cellular response to macrophage colony-stimulating factor stimulus detoxification of copper ion stress response to copper ion sarcomere basement membrane acetylcholine-gated channel complex Rho GTPase binding Rac GTPase binding fibroblast growth factor binding acetylcholine-gated cation-selective channel activity RAGE

Acknowledgements

We thank Luc Negroni, Bastien Morlet, Kirsley Chennen, Matthieu Jung for help in experiments and analyses, Genomeast for RNAseq, IGBMC platforms of proteomics and animal housing.

Data availability

The R script used to process the data has been deposited in GitLab and is freely available at http://git.lbgi.fr/djeddi/Myomics. RNA-sequencing data were deposited in NCBI GEO with the accession code GSE160084. The mass spectrometry proteomics data have been deposited to the

Proteome analysis

Data representation and statistical analyses

ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD021725.

The mass spectrometry proteomics data from the circulating proteins in serum, have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD021765. Table 2: List of the most dysregulated genes in MTM1-CNM mice.

Abbreviations

Table 3: RNA and protein levels of Mtm1 (MTM1), Bin1 (BIN1) and Dnm2 (DNM2) in Mtm1 /y , Bin1 mck-/-, Dnm2 SL/+ and Dnm2 RW/+ mice.

Supplementary information:

Table S1. Number of mice included in the different cohorts for transcriptomic and proteomic experiments.

Table S2. List of the 287 genes commonly differentially expressed in MTM1-CNM cohorts (Fig 2a).

Table S3. List of the 632 genes differentially expressed in common for MTM1-a, MTM1-b and MTM1c cohorts.

Table S4. List of the specific dysregulated genes expressed in MTM1-CNM cohorts (Fig 2c).

Table S5. List of the 68 differentially expressed genes common between mice (Tibialis anterior) and dogs (Vastus Lateralis).

Table S6. List of the 53 differentially expressed genes common between mice (Tibialis anterior) and dogs (Biceps Femoris).

Table S7. List of DEGs in cohort MTM1-a.

Table S8.

-a)

category. The color scale is based on the q-value, dark colors indicate most significantly over-represented terms, while lighter colors indicate the least significant terms.