Asma Zened

Sylvie Combes

Laurent Cauquil

Je ´ro ˆme Mariette

Christophe Klopp

Olivier Bouchez

Annabelle Troegeler-Meynadier

Francis Enjalbert

Microbial ecology of the rumen evaluated by 454 GS FLX pyrosequencing is affected by starch and oil supplementation of diets

Keywords: rumen bacteria, diversity, dietary starch, dietary oil, 454 pyrosequencing, taxonomy

To provide a comprehensive examination of the bacterial diversity in the rumen content of cows fed different diets, high-throughput 16S rRNA genebased pyrosequencing was used. Four rumen fistulated nonlactating Holstein cows received 12 kg of dry matter per day of four diets based on maize silage during four periods: the low-starch diet (22% starch, 3% fat); the high-starch diet, supplemented with wheat plus barley (35% starch, 3% fat); the low-starch plus oil diet, supplemented with 5% of sunflower oil (20% starch, 7.6% fat) and the high-starch plus oil diet (33% starch, 7.3% fat). Samples were taken after 12 days of adaptation, 5 h postfeeding. Whatever the diet, bacterial community of sieved rumen contents was dominated by Firmicutes and Bacteroidetes. Lachnospiraceae, Ruminococcaceae, Prevotellaceae, and Rikenellaceae families were highly present and were clearly affected by cow diet. The highest abundance of Prevotellaceae and the lowest abundance of Ruminococcaceae and Rikenellaceae were found with the high-starch plus oil diet. Dietary starch increased the relative abundance of only three genera: Barnesiella, Oribacterium and Olsenella, but decreased the relative abundances of several genera, with very significant effects for Rikenellaceae_RC9 and Butyrivibrio-Pseudobutyrivibrio. Oil alone had a limited effect, but interestingly, starch plus oil addition differently affected the bacterial populations compared to starch addition without oil.

Introduction

The rumen is the major site of digestion in ruminants, due to a complex microbial community including bacteria, archaea, protozoa and fungi. The main functions of this microbiota are degradation of dietary polysaccharides to volatile fatty acids, which are the main energetic fuels of ruminants, degradation of a major part of dietary proteins, synthesis of microbial protein, lipolysis of glycerides and hydrogenation of dietary unsaturated fatty acids. Because of the complexity of the microbial community in the rumen, changing the diet has a cascading effect on rumen metabolism, which can impact both quantity and quality of animal production.

The equilibrium of ruminal microbiota is dependent on the diet, which carries fermentation substrates, and the efficiency of ruminal microbiota can be strongly affected by dietary changes. High-starch diets serve as an energy source for the animal and are often offered to dairy cows, whose energy requirements are very high. However, they lead to a decreased efficiency of fiber digestion, associated with a decreased number of some fibrolytic bacteria, i.e. Ruminococcus flavefasciens [START_REF] Tajima | Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR[END_REF], Fibrobacter succinogenes [START_REF] Tajima | Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR[END_REF] silage occurred showing no variation of nutrient composition. Cows were housed in individual stalls and received 12.5 kg of dry matter daily, in two equal meals at 08:00 and 17:00 hours and were allowed ad libitum access to water. Periods were divided into weeks of washout subperiod during which all cows received the control diet, and 2 weeks of treatment subperiod, during which each cow received one of the four experimental diets. To avoid carry-over effects, treatment orders were different among cows: [high-starch + oil (HSO), low-starch + oil (LSO), high starch (HS) and low starch (LS) for cow 1; LSO, LS, HSO, HS for cow 2; LS, HS, LSO, HSO for cow 3; HS, HSO, LS, LSO for cow 4]. One liter of rumen fluid was taken from the ventral sac of each cow 5 h postfeeding on day 12 of the treatment subperiod, strained through a metal sieve (1.6-mm mesh) and then 200 lL of filtrate were precisely weighed and stored in a 2-mL sterile Eppendorf tube at À80 °C.

DNA extraction and 16S rRNA gene amplicon pyrosequencing

Total DNA was extracted from 0.2 g of ruminal sample, combining a mechanic lysis with a FastPrep instrument (MP Biomedicals, Illkirch, France) and the QIAamp DNA stool minikit (Qiagen GmbH, Hilden, Germany) according to the manufacturer's instructions. A NanoDrop ND-1000 spectrophotometer (Nano-Drop Technologies, Wilmington, DE) was used to quantify DNA.

Amplicons from the V3 to V4 regions of 16S rRNA genes (460 bp on E. coli, GenBank number J01695) of day 12 samples were amplified with bacterial forward 343F (TACGGRAGGCAGCAG; [START_REF] Liu | Short pyrosequencing reads suffice for accurate microbial community analysis[END_REF] and reverse 784R (TACCAGGGTATCTAATCCT; [START_REF] Andersson | Comparative analysis of human gut microbiota by barcoded pyrosequencing[END_REF] primers. Each primer had a barcode sequence of ten nucleotides on 5′ which was unique for

*LS = low-starch diet, LSO = low-starch + oil diet, HS = high-starch diet, HSO = high-starch + oil diet.
Effects of dietary starch and oil on ruminal microbiota [START_REF] Brown | Adaptation of beef cattle to high-concentrate diets: performance and ruminal metabolism[END_REF][START_REF] Fernando | Rumen microbial population dynamics during adaptation to a high grain diet[END_REF] and Butyrivibrio fibrisolvens [START_REF] Fernando | Rumen microbial population dynamics during adaptation to a high grain diet[END_REF], and a shift toward more lactate producers like lactobacilli [START_REF] Brown | Adaptation of beef cattle to high-concentrate diets: performance and ruminal metabolism[END_REF]. Similarly, enrichment of diets with unsaturated fat is interesting in dairy cows both for increasing dietary energy supply and to improve the profile of milk fatty acids. However, it is also known to negatively affect the fibrolytic activity of ruminal microbiota [START_REF] Brooks | Effect of some steroid compounds on ovine rumen function[END_REF]. B. fibrisolvens, a fibrolytic bacterium, is usually assumed as being the main biohydrogenating bacterium in the rumen [START_REF] Enjalbert | Biosynthesis of trans fatty acids in ruminants[END_REF], so that a reduction in the relative abundance of this species could reduce ruminal biohydrogenation and enhance the transfer of unsaturated fatty acids to tissues and milk.

Recent data indicate that this biohydrogenation is a detoxification process necessary to prevent the bacteriostatic effect of polyunsaturated fatty acids [START_REF] Maia | Toxicity of unsaturated fatty acids to the biohydrogenating ruminal bacterium, Butyrivibrio fibrisolvens[END_REF]. Dietary unsaturated fatty acids have been shown to inhibit the growth of numerous bacteria in in vitro pure cultures [START_REF] Maczulak | Effects of long-chain fatty acids on growth of rumen bacteria[END_REF], including B. fibrisolvens [START_REF] Maia | Metabolism of polyunsaturated fatty acids and their toxicity to the microflora of the rumen[END_REF], but in vivo experiments showed more variable and limited effects [START_REF] Yang | Soybean oil and linseed oil supplementation affect profiles of ruminal microorganisms in dairy cows[END_REF][START_REF] Belenguer | Changes in the rumen bacterial community in response to sunflower oil and fish oil supplements in the diet of dairy sheep[END_REF][START_REF] Huws | Forage type and fish oil cause shifts in rumen bacterial diversity[END_REF]. Most of these studies regarding the effects of dietary changes that can disturb the microbiota have focused on bacterial species with known metabolic functions, as assessed by in vitro studies. However, as outlined by [START_REF] Kelly | The glycobiome of the rumen bacterium Butyrivibrio proteoclasticus B316(T) highlights adaptation to a polysaccharide-rich environment[END_REF], direct amplification and sequencing of 16S ribosomal RNA gene indicate that, in the rumen, the majority of sequences are derived from organisms that are phylogenetically distinct from currently cultivated species. Such molecular methods have already been used to approach the effects of changes of dietary forage [START_REF] Pitta | Rumen bacterial diversity dynamics associated with changing from bermudagrass hay to grazed winter wheat diets[END_REF] or concentrates [START_REF] Khafipour | Rumen microbiome composition determined using two nutritional models of subacute ruminal acidosis[END_REF][START_REF] Callaway | Evaluation of bacterial diversity in the rumen and feces of cattle fed different levels of dried distillers grains plus solubles using bacterial tag-encoded FLX amplicon pyrosequencing[END_REF]. The objective of this study was to assess the effects of starch and/or oil addition to the diet on the rumen bacterial community of dairy cows, using FLX amplicon pyrosequencing.

Materials and methods

Experimental design

Four dry ruminally fistulated Holstein cows were assigned to a 4 9 4 Latin square design with four different diets (Table 1) based on maize silage and soybean meal during four periods. Chemical composition of feed was determined according to the Association of Official Analytical Chemists (Association of Official Analytical Chemists, 1998) procedures; Neutral Detergent Fibre was determined according to the procedure of [START_REF] Van Soest | Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition[END_REF]. To ensure the same quality of dietary components, we used the same batch of concentrate over the duration of the experiment during which analysis of the each sample. PCRs were performed in a total volume of 100 lL containing 1X PCR buffer, 200 lM of dNTP, 1U Isis TM DNA polymerase (MP Biomedicals), 0.5 lM of forward and reverse primers, and 0.5-3 ng of DNA template. The amplification program consisted of an initial denaturation step at 94 °C for 2 min; 32 cycles of denaturation at 94 °C for 30 s, annealing at 60 °C for 30 s, and elongation at 72 °C for 30 s; and a final extension step at 72 °C for 7 min. PCR of products were purified with the QIAquick PCR Purification kit (Qiagen) followed by DNA yield quantification and quality estimation using a Nano-Drop ND-1000 spectrophotometer (Nano-Drop Technologies). The size of the PCR products was confirmed by gel electrophoresis. The purified PCR products were quantified using Quant-iT PicoGreen ds DNA Assay kit (Invitogen, Saint Aubin, France) on a ABI Prism 7900HT sequence detection system (Life technologies-Invitrogen-A-BIOSYSTEM, Villebon-sur-Yvette, France) and then mixed in equimolar amounts to a final DNA concentration of 1000 ng lL À1 for each library. The pooled amplicons were pyrosequenced using an on 454 FLX Titanium (454 Life Sciencesa Roche Company, Branford, CT) sequencer at the GeT (Genomic and Transcriptomic) platform of Toulouse. Sequencing occurred on a picotiter plate, of which a half space was available for samples included in this study. To facilitate pyrosequencing using titanium chemistry, each forward primer was appended with the titanium sequencing adaptor A and the reverse primer carried the titanium adaptor B at the 5′ end.

Pyrotag handling and analysis

A total of 138 764 16S rRNA gene sequences (also referred to as 16S pyrotags) were obtained from 454 Titanium pyrosequencing run for the 16 samples. The mean quality score for the base between position 1 and 500 pb was 32.8 ± 4.5 (mean ± SD, max = 38.9; min = 18.0). The 16S pyrotags were sorted based on their respective barcodes to form a total of 16 pyrotag library representing the 16 collected ruminal samples. Sequences were sequentially filtered using a Python script developed by the bioinformatic platform of Toulouse, removing first sequences with a short sequencing length (less than 150 nt; 7768 sequences removed); those with at least one ambiguous base (12 345 sequences removed) or with a long homopolymer (> 9; four sequences); those that did not match the proximal PCR primer sequences (with two mismatches allowed; 2241 sequences removed) and finally those having both primers but with a length shorter than 350 pb (227 sequences removed). A total of 116 183 sequences were retained corresponding to 7088 ± 1258 sequences per samples. The average read length was of 393 ± 81 nucleotides after trimming the barcodes.

Taxonomical classification and statistical analysis

After cleaning, sequences were analyzed using MOTHUR software (v 1.24; [START_REF] Schloss | Introducing mothur: open-source, platform-independent, communitysupported software for describing and comparing microbial communities[END_REF]. Reads were aligned over SILVA alignment database provided by MOTHUR software (14 956 sequences corresponding to the unique sequences in the SSU REF database v102) [START_REF] Pruesse | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB[END_REF] and an alignment quality was calculated using the SILVA secondary structure map file (1072 bad aligned sequences were removed). After calculating a pairwise distance between aligned sequences, they were clustered into Operational Taxonomic Unit (OTU, cutoff 0.05 using a furthest neighbor clustering). Taxonomic assignment was performed with a bootstrap of 60%. Finally, all unclassified bacteria at the phylum level were considered as chimera and were removed from statistical analysis (1692 sequences). Rarefaction curves, Abundance-based coverage estimator (ACE) and Chao1 richness were calculated using the relevant Ribosomal Database Project modules (Cole et al., 2008), including Rarefaction and Chao1 Estimator. Shannon a-diversity index was calculated according to [START_REF] Hayek | Surveying Natural Populations[END_REF].

Sequences corresponding to Butyrivibrio genus which were not identified at species level in SILVA database were compared with deposited sequences in NCBI database using BLAST (http://blast.ncbi.nlm.nih.gov/Blast.cgi). This procedure did not allow discrimination between Butyrivibrio proteoclasticus and Butyrivibrio hungatei.

Statistical analysis

The relative abundances of bacteria in the rumen fluids were analyzed by ANOVA, using the General Linear Model of SYSTAT (version 9, SPSS Inc., Chicago, IL), according to the following model:

Y = l + C + P + S + O + S 9 O + e,
where l is the mean, C, P, S and O are the effects of cow, period, dietary starch level and sunflower oil addition, respectively, and e the residual error. Significant differences among treatments were declared at P < 0.05 and trends at P < 0.10. Genera under 0.1% of relative abundance for the four studied diets were excluded from the analysis.

Results

Microbial community in the rumen of dairy cows

Diversity within the different samples was estimated by the calculation of the number of OTUs and the measure of richness estimators. Of the overall 16 samples, the number of OTUs with a cutoff of 0.05 was 2297 ± 665 with coverage on average of 81.1 ± 6.3%. The Chao1 and ACE estimators were on 4412 ± 1551; 6369 ± 2494 and 6.7 ± 0.7, respectively.

Within the bacterial population, 13 phyla were found across all samples. Firmicutes and Bacteroidetes together represented more than 80% of total sequences: 49.6% and 40.2% of total sequences on average, respectively, but with high variations (residual SEM = 4.5 and 4.7 respectively for mean values presented on Fig. 1a). Rumen bacterial populations had Firmicutes and Bacteroidetes in varying relative abundances, ranging from 24.1% to 67.2% and from 11.5% to 62.9% of the total microbial community, respectively. The remaining rumen microbiota was composed of low relative abundance phyla (< 20% of total microbial community). Proteobacteria and Actinobacteria represented around 4.3% and 5.1% of total sequences on average, respectively. Other phyla (< 0.5% of total microbial community), such as Fibrobacteres, Spirochaetes, Lentisphaerae or Fusobacteria, were not consistently present in all the different host populations.

Evaluation at finer taxonomical levels was carried out to determine the distribution of the different bacteria. When sequences were analyzed at the class level (Fig. 1b), Firmicutes were dominated by Clostridia (48.6% on average of the total sequences) and Bacteroidia class made a significant contribution (39.2% on average of the total sequences) in the Bacteroidetes phylum. Using a minimal bootstrap of 60%, 83.3% and 52.6% of sequences were assigned to family and genus levels, respectively. On the totality of samples, 45 orders and 98 families were detected. Further evaluation of the two major classes showed that Clostridia were mainly composed of the families Lachnospiraceae and Ruminococcaceae (26.1% and 17.2% on average of the total sequences, respectively), belonging to the Clostridiales order. Predominant bacterial families in the Bacteroidia class were Prevotellaceae and Rikenellaceae (17.1% and 5.9% on average of the total sequences, respectively), belonging to the Bacteroidales order. Regarding Actinobacteria phylum, the major class was Actinobacteria represented mainly by Bifidobacteriaceae family (4.0% of total sequences on average).

Over the totality of samples, 219 genera were detected (Supporting information, Table S1a indicates the relative abundances of genera representing more than 0.3% of total sequences). Among these genera, 11.3% of the sequences belonged to the genus Prevotella followed by more than 5% of the genera Ruminococcaceae Incer-tae_Sedis (5.7%) and RC9 (5.6%). The most common uncultured and unclassified bacteria are presented in Table S1b: 11.9% of total sequences belonged to the Lachnospiraceae family, 9.2% to unclassified families of the Bacteroidales order and 7.9% to the Ruminococcaceae family. Uncultured genera were also found such as Lachnospiraceae at 5% of total sequences.

Clustering differences in bacterial community and their relative abundances

After 12 days of experimental diet, the comparison of the bacterial communities by PCA (Fig. 2) showed that cows fed HS and HSO diets were separated from those receiving low-starch diets, but LS and LSO diets were very close in the plot. Importantly, the efficiency of the washout carried out in this study was verified: the structure of bacterial communities (tested by Capillary Electrophoresis -Single Strand Conformation Polymorphism) of ruminal samples taken on the last day of the washout did not differ according to the diet of the previous period (data not shown).

Effect of diet on the relative abundance and diversity of bacterial groups

Starch addition reduced Chao1 richness, ACE and Shannon diversity indexes (Table 2). At the phylum level, both starch and oil additions negatively affected (P < 0.05) Fibrobacteres and Spirochaetes phyla, and starch addition resulted (P = 0.05) in high Actinobacteria relative abundance, but the major phyla were not significantly affected (data not shown).

The dietary starch level and/or the addition of sunflower oil had a number of effects on bacteria encompassing Clostridia and Bacteroidia. For example, among Clostridia, in rumen fluids of cows fed HSO diet, the rel-ative abundance of Ruminococcaceae was 2.4 times lower than with the other diets due to an interaction between starch and oil additions (Table 3). Oil addition had a positive effect on the abundance of Clostridiales Family_XIII Incertae_Sedis (Table 3). In the Bacteroidia class, the relative abundances of BS11 and Rikenellaceae were lower and that of Porphyromonadaceae was higher in ruminal microbiota of cows fed high-starch diets compared to cows fed low-starch diets (Table 3). In addition to the effect of starch, the abundances of Rikenellaceae and RF16 families were negatively affected by the addition of sunflower oil (Table 3), resulting in a very low abundance (0.74% and 0.07% of total sequences, respectively) with HSO diet compared to the other diets (7.57% and 0.65% on average of total sequences). Prevotellaceae relative abundance was numerically higher with HSO diet due to a trend (P = 0.06) toward an interaction between starch level and oil addition (Table 3). The relative abundance of Clostridiales unclassified was significantly lowered with high-starch diets (Table 3). Among Actinobacteria, Bifidobacteriaceae relative abundance tended (P = 0.08) to be affected by an interaction between starch level and oil addition leading to the highest value with HS diet.

Taxonomic evaluation of bacterial genus of the ruminal fluids (LS, LSO, HS and HSO) showed that the relative abundances of some genera were affected by the addition of starch and oil to the diet (Table 4). Single effect of starch addition increased the relative abundance of only three genera: Barnesiella, Oribacterium and Olsenella, but decreased the relative abundance of several genera, with very significant effects (P < 0.001) for Rikenellaceae_RC9 and Butyrivibrio-Pseudobutyrivibrio. Oil addition decreased the relative abundance of Rikenellaceae_RC9 and Acetitomaculum (Table 4). As a consequence of an additive effect of oil and starch additions, Rikenellaceae_RC9 abundance was lowest with HSO diet.

Significant interactions between starch level and oil addition were observed on some genera. Starch addition PC1 (41.5%) PC2 (24.6%) Fig. 2. Principal component analysis (PCA) of bacterial 16S rRNA gene sequence tags generated from 454 pyrosequencing run of 5 h postfeeding ruminal contents taken on day 12, corresponding to the last day of the treatment subperiod. The marks relate to the diets of donor cows: low-starch diet (•), low-starch + oil diet (▲), high-starch diet (□) and high-starch + oil diet (■). diversity than could be provided by other molecular diversity techniques (fingerprints, cloning…). Our 16S rRNA gene pyrosequencing revealed that, at the phylum level, the microbial community of the cows, regardless of individual and diet, was dominated by Firmicutes and Bacteroidetes. This microbial distribution of major phyla is similar to those found with culture-based or molecular approaches [START_REF] Stewart | The rumen bacteria[END_REF][START_REF] Kim | Status of the phylogenetic diversity census of ruminal microbiomes[END_REF] suggesting that Firmicutes and Bacteroidetes play important roles in the ruminal metabolism [START_REF] Turnbaugh | An obesity-associated gut microbiome with increased capacity for energy harvest[END_REF][START_REF] Turnbaugh | Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome[END_REF]. Similarly, the most abundant classes observed in this study were Clostridia and Bacteroidia. At the family level, common features between this study and other rumen 16S rRNA gene studies [START_REF] Koike | Phylogenetic analysis of fiber-associated rumen bacterial community and PCR detection of uncultured bacteria[END_REF][START_REF] Edwards | 16S rDNA library-based analysis of ruminal bacterial diversity[END_REF][START_REF] Kong | Composition, spatial distribution, and diversity of the bacterial communities in the rumen of cows fed different forages[END_REF] included the dominance of Lachnospiraceae, Ruminococcaceae and Prevotellaceae. The fourth prevalent family was Bacteroidales unclassified, which fits with the results of [START_REF] Kong | Composition, spatial distribution, and diversity of the bacterial communities in the rumen of cows fed different forages[END_REF].

Our study, using short-length pyrosequencing, was not able to identify the bacterial groups at species level, but allowed identification of numerous genera, part of them being uncultured or unclassified (Table S2). Our observed predominance of Prevotella (Table S2) is in accordance with literature showing that Prevotella was the major ruminal genus, representing up to 52% of total bacteria of rumen content [START_REF] Pitta | Rumen bacterial diversity dynamics associated with changing from bermudagrass hay to grazed winter wheat diets[END_REF]. High abundance of Rikenellalike bacteria was noticed, in which Rikenellaceae_RC9 was Effects: O = effect of oil addition, S = high-starch vs. low-starch diets, O 9 S = effect of interaction of starch by oil additions.

lowered the relative abundances of Prevotella and Lachno-spiraceae_Incertae_Sedis when diets did not contain oil but increased these abundances with oil supplemented diets, so that the highest abundances were observed with the HSO diet. The slope of the effect of starch addition on relative abundance was positive without oil addition and negative with oil addition for Ruminococcaceae_Incer-tae_Sedis, Acetitomaculum and Bifidobacterium, which exhibited very high percentages only with the HS diet. Butyrivibrio genus relative abundance tended to be decreased by starch addition: in particular B. proteoclasticus or B. hungatei was significantly decreased by starch; B. fibrisolvens was present at low level and a trend toward an interaction between starch and oil addition led to the lowest value with HSO diet. Many of the affected genera were unclassified or uncultured (Table S2). In particular, unclassified and uncultured Ruminoccaceae and uncultured Lachnospiraceae presented lowest abundances with HSO diet.

Discussion

Average microbial community

In this study, high-throughput sequencing approach proved to be a powerful tool to reveal bacterial diversity of sieved rumen contents, and effects of diet on that diversity. It also gave much greater coverage of bacterial among the most abundant ruminal bacteria genera. Similar results were found by [START_REF] Pitta | Rumen bacterial diversity dynamics associated with changing from bermudagrass hay to grazed winter wheat diets[END_REF] but minor abundance of Rikenella was observed in the study of de [START_REF] De Menezes | Microbiome analysis of dairy cows fed pasture or total mixed ration diets[END_REF]. We also found high relative abundances of Ruminocaccaceae genera and Lachnospiraceae genera, including Butyrivibrio, Acetitomaculum, Incertae-Sedis, Moriella and Syntrophococcus.

Fibrobacter and Ruminoccocus species are major cellulolytic bacteria in the rumen. In our study, the Ruminococcus genus represented 0.92% of total bacteria in ruminal content of cows receiving LS diet. These results contrast with those of [START_REF] Palmonari | pH dynamics and bacterial community composition in the rumen of lactating dairy cows[END_REF], who found that Ruminococcus albus represented more than 10% of total 16S rRNA gene. However, in our study, a Ruminococcaceae Incertae-sedis represented about 6% of total bacteria. Similarly, [START_REF] Kong | Composition, spatial distribution, and diversity of the bacterial communities in the rumen of cows fed different forages[END_REF] found a much higher abundance of Ruminococcaceae unclassified than Ruminococcus.

In our study, the relative abundance of Fibrobacteraceae was only 0.34% on average of total bacterial community in LS diet but it accounted for almost 10% of the sequences in the study of [START_REF] De Menezes | Microbiome analysis of dairy cows fed pasture or total mixed ration diets[END_REF]. These authors showed that Fibrobacteres were considerably more prevalent in the solid phase than in the liquid phase which could partly explain the discrepancy between their results and ours. However, in our study, the ruminal samples were strained and sieved through a 1.6 mm mesh so that particles were not completely removed. Similar to our results, [START_REF] Pitta | Rumen bacterial diversity dynamics associated with changing from bermudagrass hay to grazed winter wheat diets[END_REF] found a low abundance of Fibrobacter in the rumen of cows. As the four diets tested in our study contained starch, the growth or the activity of fibrolytic bacteria could have been negatively affected [START_REF] Klieve | Establishing populations of Megasphaera elsdenii YE 34 and Butyrivibrio fibrisolvens YE 44 in the rumen of cattle fed high grain diets[END_REF]. Moreover, Fibrobacter DNA is known to be difficult to amplify [START_REF] Tajima | Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR[END_REF], so that the difference between results of the different experiments could reflect PCR bias. Besides, comparison between results must be done with caution because studies targeting specific bacteria are different from pyrosequencing approach which poses no such restrictions.

Effects of diets

In our study, the washout subperiod was successful in restoring a microbiota that did not depend on the experimental diet given during the previous period (data not shown). Sequencing analysis revealed that diets affected bacterial communities, which could relate to diet being used as a growth substrate for ruminal bacteria, and/or from diet potentially resulting in toxic or inhibiting effects on the ruminal bacteria, due to dietary components or results of diet fermentation. Our deep sequencing enabled quantitative study of the effects of diet on gut microbiota.

As outlined in Fig. 2, dietary starch affected the ruminal bacterial community, which was clearly separated from that of cows fed low-starch diets. Interestingly, the combination of starch and oil supplementations modified the composition of the bacterial community, which was Effects: O = effect of oil addition, S = high-starch vs. low-starch diets, O 9 S = effect of interaction of starch by oil additions.

including B. proteoclasticus or B. hungatei. In our study, B. fibrisolvens was not affected by the single effect of starch addition, as opposed to the results of [START_REF] Fernando | Rumen microbial population dynamics during adaptation to a high grain diet[END_REF]. However, in this latter study, the reference values were obtained when animals received a diet containing only hay, progressively changed to a diet containing 80% grain, which represents a much greater dietary change that our switch from 20% to 35% starch.

Besides these observed differences in the Firmicutes phylum, we also observed differences due to dietary starch level in the relative abundances of the quantitatively minor phyla Fibrobacteres and Spirochaetes, whose relative abundances were decreased by more than two times when the dietary starch level increased. A decreased abundance of Spirochaetes has already been described by de [START_REF] De Menezes | Microbiome analysis of dairy cows fed pasture or total mixed ration diets[END_REF] when switching from 100% to 36% forage in the diet, and increasing dietary starch resulted in a strong decrease of F. succinogenes in the experiment of [START_REF] Tajima | Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR[END_REF]. On the contrary, de [START_REF] De Menezes | Microbiome analysis of dairy cows fed pasture or total mixed ration diets[END_REF] observed that a concentrate diet resulted in a higher abundance of Fibrobacteraceae than a forage diet, and explained this paradoxical effect by the presence of straw in their concentrate diet. In our experiment, the high-starch diets had less fibrous material than the low-starch diets, so this paradoxical effect was not observed. In the Bacteroidetes phylum, Barnesiella, which has recently been identified in the ruminal content [START_REF] Kim | Status of the phylogenetic diversity census of ruminal microbiomes[END_REF], was strongly and positively affected by starch addition. In the Actinobacteria phylum, Bifidobacteriaceae were strongly represented (15.0% relative abundance in average) in ruminal samples of cows receiving HS diet. This bacterial family was not found by [START_REF] Pitta | Rumen bacterial diversity dynamics associated with changing from bermudagrass hay to grazed winter wheat diets[END_REF] in cattle receiving forage diets or by [START_REF] Callaway | Evaluation of bacterial diversity in the rumen and feces of cattle fed different levels of dried distillers grains plus solubles using bacterial tag-encoded FLX amplicon pyrosequencing[END_REF] in cattle receiving very high concentrate diets, but was found in the study of [START_REF] Boguhn | Effects of concentrate proportion in the diet with or without Fusarium toxincontaminated triticale on ruminal fermentation and the structural diversity of rumen microbial communities in vitro[END_REF] in the rumen of dairy cows with diets that were similar to ours. The addition of starch increased the abundance of Bifidobacterium and Olsenella genera but decreased that of Atopobium genus. Information about these genera is not commonly found in the literature except Bifidobacterium genus which seems to be implicated in the production of conjugated linoleic and conjugated linolenic acids isomers [START_REF] Gorissen | Production of conjugated linoleic acid and conjugated linolenic acid isomers by Bifidobacterium species[END_REF][START_REF] Park | Production of conjugated linoleic acid (CLA) by Bifidobacterium breve LMC520 and its compatibility with CLA-producing rumen bacteria[END_REF]. Bifidobacterium spp. have been identified in animals receiving diets rich in starch, which implies a role for these microorganisms in the hydrolysis of this carbohydrate; hence, they can ferment starch to produce acetic and lactic acids [START_REF] Stewart | The rumen bacteria[END_REF]. The genera Olsenella, Atopobium and Bifidobacterium constitute a group of bacteria that ferments carbohydrates to lactic acid [START_REF] Kraatz | Olsenella umbonata sp. nov., a microaerotolerant anaerobic lactic acid bacterium from the sheep rumen and pig jejunum, and emended descriptions of Olsenella, Olsenella uli and Olsenella profusa[END_REF]. Uncultured or unclassified bacteria were also negatively affected by starch addition (Table S2), the three most abundant affected genera being Clostridiales. different from that induced by starch addition alone. Quantitative methods evaluating richness and diversity such as the Shannon index measure the evenness of the a-diversity. In our study, Shannon index was negatively affected by the addition of starch, which suggested a reduced ruminal bacterial diversity.

Most effects of starch addition were observed at the genus level. Starch addition increased the relative abundance of one genus belonging to Firmicutes (Table 4), Oribacterium which has recently been identified in the rumen of cows fed forage based diets [START_REF] Kong | Composition, spatial distribution, and diversity of the bacterial communities in the rumen of cows fed different forages[END_REF][START_REF] Kenters | Isolation of previously uncultured rumen bacteria by dilution to extinction using a new liquid culture medium[END_REF], and whose functions in the rumen are not known. To our knowledge, effects of diet on the abundance of this genus have not been published. Starch addition tended (P = 0.066) to increase the abundance of Selenomonas, a starch utilizing bacteria, but in a much more narrow range than observed by [START_REF] Tajima | Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR[END_REF], whose dietary changes from a low-grain to a high-grain diet were much greater than ours. Previous studies, investigating the effects of dietary starch addition on ruminal bacteria, showed variable effects on Streptococcus bovis [START_REF] Tajima | Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR[END_REF][START_REF] Fernando | Rumen microbial population dynamics during adaptation to a high grain diet[END_REF][START_REF] Palmonari | pH dynamics and bacterial community composition in the rumen of lactating dairy cows[END_REF], another amylolytic bacteria, involved in ruminal acidosis. The relative abundance of Streptococcus exhibited a wide variability in our data set, so that the effect of starch addition was not statistically significant (P = 0.28). Similarly, the relative abundance of Lactobacillus was 0.04%, and the diet did not affect this genus, consistent with [START_REF] Brown | Adaptation of beef cattle to high-concentrate diets: performance and ruminal metabolism[END_REF], who reported increases of this genus only when the diets contained 71% of concentrates.

Starch addition to the diet also decreased the relative abundance of Ruminococcaceae family, including Ruminococcus, a major cellulolytic genus [START_REF] Bryant | Bacterial species of the rumen[END_REF]. R. flavefaciens has already been shown to be highly depressed when switching from hay to grain diet [START_REF] Tajima | Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR[END_REF]. In our study, the genera most affected by starch addition were Rikenellaceae_RC9 and Butyrivibrio-Pseudobutyrivibrio. Rikenellaceae_RC9 has not been extensively studied in the rumen, but [START_REF] Pitta | Rumen bacterial diversity dynamics associated with changing from bermudagrass hay to grazed winter wheat diets[END_REF] already reported effects of diet on a Rikenella-like genus, whose abundance was much lower in both solid and liquid fractions of rumen contents in cows receiving bermudagrass hay than in cows receiving wheat pasture diets. They underlined that, in the liquid fraction of hay fed cows, this genus clustered with other genera including Fibrobacter, and suggested that this bacterium is involved in structural carbohydrates degradation. The genus Butyrivibrio-Pseudobutyrivibrio also contains fibrolytic bacteria, including P. ruminis and P. xylanivorans [START_REF] Kopec ˇny | Butyrivibrio hungatei sp. nov. and Pseudobutyrivibrio xylanivorans sp. nov., butyrate producing bacteria from the rumen[END_REF], which could explain the negative effect of starch addition to the diet. Other Lachnospiraceae were also negatively affected by the high-starch diets, Oil addition had only a positive effect on two unclassified taxa (Firmicutes;unclassified and Clostridiales;Family_ XIII_Incertae_Sedis;unclassified). Oil addition negatively affected some minor or poorly known genera, but had no significant effect on B. proteoclasticus or B. hungatei, and interacted with the effects of starch addition for B. fibrisolvens, whose lowest relative abundance was observed with the HSO diet. These three Butyrivibrio species are known to be able to biohydrogenate unsaturated fatty acids. Contrary to our results, [START_REF] Maia | Metabolism of polyunsaturated fatty acids and their toxicity to the microflora of the rumen[END_REF] showed in pure cultures that many bacteria, including B. hungatei, B. proteoclasticus, together with cellulolytic bacteria belonging to the Ruminococcus and Fibrobacter genera, have increased lag phases during growth when the medium contains linoleic acid. In our experiment, the limited effect of sunflower oil on these bacteria could be due to linoleic acid being in an esterified form, or to differences between in vivo and in vitro studies, for example due to interactions with other bacterial species or substrates. In vivo, [START_REF] Belenguer | Changes in the rumen bacterial community in response to sunflower oil and fish oil supplements in the diet of dairy sheep[END_REF] did not find any effect of 2% sunflower oil in the diet of ewes on the abundance of Butyrivibrio involved in ruminal biohydrogenation. Similarly, in the bovine rumen, [START_REF] Yang | Soybean oil and linseed oil supplementation affect profiles of ruminal microorganisms in dairy cows[END_REF] did not determine any effect of dietary addition of 4% of soybean oil, another high linoleic acid fat, on the amount of B. fibrisolvens, and showed a negative effect on F. succinogenes and R. albus but not R. flavefaciens. In the rumen, R. flavefaciens abundance is 100 times that of R. albus [START_REF] Yang | Soybean oil and linseed oil supplementation affect profiles of ruminal microorganisms in dairy cows[END_REF], which explains the lack of effect of dietary oil on the Ruminococcus genus in our study.

The Prevotella genus comprises a wide range of species, the best known in the rumen being P. ruminicola and P. bryantii, who have important roles in the utilization of polysaccharides of plant origin, including xylans, pectins, and starch [START_REF] Avgus ˇtin | Phenotypic diversity among ruminal isolates of Prevotella ruminicola: proposal of Prevotella brevis sp. nov., Prevotella byantii sp. nov., and Prevotella albensis sp. nov. and redefinition of Prevotella ruminicola[END_REF]. However, most rumen Prevotella do not belong to these two main species [START_REF] Bekele | Genetic diversity and diet specicity of ruminal Prevotella revealed by16S rRNAgene-basedanalysis[END_REF]. In the present experiment, the relative abundance of this genus was not affected by single effects of starch or oil addition. Literature data on the effects of starch diets on this genus are not consistent: switching from a hay to a starch diet, [START_REF] Tajima | Diet-dependent shifts in the bacterial population of the rumen revealed with real-time PCR[END_REF] showed a decrease of P. ruminicola but an increase of P. bryantii whereas [START_REF] Bekele | Genetic diversity and diet specicity of ruminal Prevotella revealed by16S rRNAgene-basedanalysis[END_REF] found an increase of both genera. As far as we are aware, limited knowledge is available regarding the relationship between Prevotella and dietary fat: these bacteria have a low in vitro sensitivity to linoleic acid [START_REF] Maia | Metabolism of polyunsaturated fatty acids and their toxicity to the microflora of the rumen[END_REF], are not affected in vivo by fish oil [START_REF] Huws | Forage type and fish oil cause shifts in rumen bacterial diversity[END_REF], and a strain of Prevotella is linked to rumen biohydrogenation of fatty acids [START_REF] Huws | As yet uncultured bacteria phylogenetically classified as Prevotella, Lachnospiraceae incertae sedis and unclassified Bacteroidales, Clostridiales and Ruminococcaceae may play a predominant role in ruminal biohydrogenation[END_REF]. In our study, Prevotella relative abundance was affected by an interaction between starch and oil additions: switching from LS to HS diet slightly decreased their relative abundance whereas switching from LSO to HSO diet resulted in a twofold increase of relative abundance. This high relative abundance of Prevotella with the HSO diet could be related to their ability to degrade a wide variety of substrates and their resistance to unsaturated fatty acids. However, due to the limited knowledge on the relationship between this genus and dietary lipids, understanding this interaction will require further research on the metabolic characteristics of this genus. Moreover, an accurate study of rumen Prevotellaceae should take into account that liquid and solid rumen fractions have abundances that are different and are differently affected by dietary changes [START_REF] De Menezes | Microbiome analysis of dairy cows fed pasture or total mixed ration diets[END_REF].

Such interaction, resulting in highest relative abundances with the HSO diet, was also observed on Lachnospiraceae Incertae_Sedis. An opposite interaction between starch and oil, with the lowest relative abundance being found with the HSO diet, was observed for B. fibrisolvens, Acetitomaculum (Table 4), Ruminococcaceae Incertae_ Sedis, Ruminococcaceae unclassified, Ruminococcaceae uncultured, Lachnospiraceae uncultured and Firmicutes unclassified (Table S2). Interestingly, bacteria involved in interactions between starch and oil in our experiment in part fit with the results of [START_REF] Huws | As yet uncultured bacteria phylogenetically classified as Prevotella, Lachnospiraceae incertae sedis and unclassified Bacteroidales, Clostridiales and Ruminococcaceae may play a predominant role in ruminal biohydrogenation[END_REF]. These authors found that putative taxonomic identification of many terminal restriction fragments associated with trans-11 18 : 1 and cis-9,trans-11 CLA, intermediates of ruminal biohydrogenation of dietary unsaturated fatty acids, revealed that more than 60% of the predicted phylotypes belonged to the genera Prevotella, Lachnospiraceae Incertae-Sedis and unclassified Bacteroidales, Clostridia, Ruminococcaceae and Lachnospiraceae.

In conclusion, this study, based on 16S rRNA gene pyrosequencing of ruminal microbiota sampled from cows fed different diets, provides a detailed account of the microbial community inhabiting the rumen and the effects of four diets on the relative abundances of some bacterial groups. The diets had significant effects in shaping the microbial community in the rumen of dairy cows, in particular starch and starch plus oil addition. Bacterial profile was primarily predominated by Firmicutes and Bacteroidetes, and a large portion of the bacteria genera were not identified because they are as yet uncultured. With a better understanding of the bacterial diversity in dairy cows, future studies would aim to investigate their relationship with digestion products and efficiency to elucidate their functional roles. Such a study should be of great interest for researchers investigating rumen microbial ecology and bacteria involved in rumen digestion.

Fig. 1 .

 1 Fig. 1. Percentage contribution of sequences (%) evaluated at the phylum (a) and class (b) levels to the total number of sequences in the database (LS = low-starch diet, LSO = low-starch + oil diet, HS diet = high-starch diet, HSO = high-starch + oil diet).

Table 1 .

 1 Ingredients and chemical composition of donor cow diets

	Diets*	LS	LSO	HS	HSO
	Ingredients (% of dry matter)
	Maize silage	68.7	63.2	37.7	32.3
	Alfalfa hay	14.3	14.3	0.0	0.0
	Wheat and barley mix	0.0	0.0	48.5	48.5
	Soybean meal	15.5	16.2	12.4	13.1
	Sunflower oil	0.0	4.8	0.0	4.7
	Minerals and vitamins	1.5	1.5	1.5	1.5
	Composition (% of dry matter)
	Crude protein	14.6	14.6	14.2	14.2
	Neutral detergent fiber	39.7	37.3	30.9	28.6
	Starch	21.5	19.8	34.8	33.1
	Crude fat	2.9	7.6	2.7	7.3

Table 2 .

 2 Estimators of diversity within cow's ruminal fluids on day 12

	Diets †	LS	LSO	HS	HSO	SEM ‡	Effects §
	Number of operational taxonomic units	2939	2467	2055	1729	166.28
	Chao1 estimated	5886	4826	3876	3060	387.87	S*
	richness
	ACE	8713	6976	5599	4188	623.50	S*
	Shannon diversity index	7.33	7.14	6.37	6.16	0.15	S**
	*P < 0.05.

**P < 0.01. † LS, low-starch diet; LSO, low-starch + oil diet; HS, high-starch diet; HSO, high-starch + oil diet. ‡ Residual standard error of the mean. § Effects: S = high-starch vs. low-starch diet.

Table 3 .

 3 Bacterial families affected by dietary changes on day 12, ranked by class and average relative abundance order (% of total sequences) LS, low-starch diet; LSO, low-starch + oil diet; HS, high-starch diet; HSO, high-starch + oil diet.

							Significance
	Diets †	LS	LSO	HS	HSO	SEM ‡	of effects §
	Clostridia class
	Lachnospiraceae	26.02	29.92	20.51	27.81	2.69	O	°Ruminococcaceae
		17.10	21.31	23.05	7.28	3.67	O 9 S*
	Family_XIII_Incertae_Sedis	1.55	2.24	0.86	1.74	0.30	O*, S	°Veillonellaceae
		0.08	0.23	0.56	1.36	0.35	S	°Clostridiales
	unclassified	2.81	4.60	2.36	2.46	0.46	O °, S*
	Bacteroidia class
	Prevotellaceae	17.17	14.38	12.22	24.73	3.33	O 9 S °Rikenellaceae
		11.78	7.39	3.54	0.74	0.96	O*, S***
	BS11	4.40	4.10	1.85	0.16	0.57	S**
	Porphyromonadaceae	1.36	1.77	3.93	4.63	0.98	S*
	RF16	1.18	0.34	0.42	0.07	0.17	O*, S*
	Actinobacteria class
	Bifidobacteriaceae	0.45	0.33	15.03	0.38	3.47	O 9 S	°Corionobacteraceae
		0.73	0.77	1.13	2.64	0.54	S	°°P
	< 0.10.
	*P < 0.05.
	**P < 0.01.
	***P < 0.001.
	†

‡

Residual standard error of the mean. §

Table 4 .

 4 Bacterial genera and selected species ( # ) affected by dietary changes on day 12, ranked by family and genus or species average relative abundance order (% of total sequences) LS, low-starch diet; LSO, low-starch + oil diet; HS, high-starch diet; HSO, high-starch + oil diet. ‡ Residual standard error of the mean. §

	Diets †	LS	LSO	HS	HSO	SEM ‡	Effects §
	Clostridia class
	Lachnospiraceae
	Acetitomaculum	1.36	2.08	3.09	1.19	0.19	O*, S °, O 9 S***
	Incertae_Sedis	1.84	1.50	0.53	2.89	0.51	O °, O 9 S*
	Butyrivibrio	2.45	2.68	1.60	1.85	0.33	S	°B.
	proteoclasticus or	0.86	0.67	0.45	0.24	0.17	S*
	B. hungatei #
	B. fibrisolvens #	0.07	0.12	0.09	0.05	0.01	O 9 S °Butyrivibrio-
		0.72	0.61	0.15	0.17	0.07	S***
	Pseudobutyrivibrio
	Blautia	0.29	0.64	0.11	0.16	0.10	O °, S*
	Lachnospira	0.58	0.12	0.03	0.49	0.19	O 9 S °Catabacter
		0.11	0.15	0.02	0.01	0.03	S**
	Oribacterium	0.01	0.03	0.06	0.15	0.03	S*
	Ruminococcaceae
	Incertae_Sedis	4.12	5.22	11.95	1.45	2.43	O 9 S °Ruminococcus
		0.93	0.59	0.44	0.41	0.14	S	°Fastidiosipila
		0.62	0.67	0.34	0.03	0.14	S*
	Oscillibacter	0.47	0.48	0.24	0.02	0.09	S*
	Papillibacter	0.16	0.13	0.07	0.02	0.03	S*
	Veillonellaceae
	Selenomonas	0.01	0.04	0.16	0.10	0.04	S	°Bacteroidia
	class
	Prevotellaceae
	Prevotella	10.99	9.12	7.85	17.22	2.77	O 9 S °Rikenellaceae
	RC9	11.26	7.03	3.40	0.56	0.98	O*, S***
	Porphyromonadaceae
	Barnesiella	0.98	1.35	3.17	4.10	0.95	S*
	Actinobacteria class
	Bifidobacteraceae
	Bifidobacterium	0.37	0.24	14.48	0.38	3.40	O °, S °, O 9 S	°Corionobacteraceae
	Olsenella	0.18	0.13	0.70	2.48	0.56	S*
	Atopobium	0.15	0.18	0.08	0.05	0.03	S**
	Spirochaetes class
	Spirochaetaceae
	Termite_Treponema_	0.18	0.06	0.07	0.05	0.02	O °°P
	cluster
	< 0.10.
	*P < 0.05.
	**P < 0.01.
	***P < 0.001.
	†

Acknowledgements

The authors thank the staff at the experimental station (UMR1289 Tandem). We would also like to thank Lluch J (INRA, Plateforme Ge ´nomique, Ge ´nopole Toulouse/ Midi-pyre ´ne ´es, Castanet-Tolosan, France).

Supporting Information

Additional Supporting Information may be found in the online version of this article: Table S1a. Most common bacteria genera on day 12 ranked by average relative abundance order (% of total sequences). Table S1b. Most common uncultured or unclassified bacteria genera on day 12 ranked by average relative abundance order (% of total sequences). Table S2. Unclassified or uncultured bacterial genera affected by diet at day 12, ranked by average relative abundance order (% of total sequences).

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