Farmed ruminants are the largest source of anthropogenic methane emissions globally. The methanogenic archaea responsible for these emissions use molecular hydrogen (H2), produced during bacterial and eukaryotic carbohydrate fermentation, as their primary energy source. In this work, we used comparative genomic, metatranscriptomic and co-culture-based approaches to gain a system-wide understanding of the organisms and pathways responsible for ruminal H2 metabolism. Two-thirds of sequenced rumen bacterial and archaeal genomes encode enzymes that catalyse H2 production or consumption, including 26 distinct hydrogenase subgroups. Metatranscriptomic analysis confirmed that these hydrogenases are differentially expressed in sheep rumen. Electron-bifurcating [FeFe]-hydrogenases from carbohydrate-fermenting Clostridia (e.g., Ruminococcus) accounted for half of all hydrogenase transcripts. Various H2 uptake pathways were also expressed, including methanogenesis (Methanobrevibacter), fumarate and nitrite reduction (Selenomonas), and acetogenesis (Blautia). Whereas methanogenesis-related transcripts predominated in high methane yield sheep, alternative uptake pathways were significantly upregulated in low methane yield sheep. Complementing these findings, we observed significant differential expression and activity of the hydrogenases of the hydrogenogenic cellulose fermenter Ruminococcus albus and the hydrogenotrophic fumarate reducer Wolinella succinogenes in co-culture compared with pure culture. We conclude that H2 metabolism is a more complex and widespread trait among rumen microorganisms than previously recognised. There is evidence that alternative hydrogenotrophs, including acetogenic and respiratory bacteria, can prosper in the rumen and effectively compete with methanogens for H2. These findings may help to inform ongoing strategies to mitigate methane emissions by increasing flux through alternative H2 uptake pathways, including through animal selection, dietary supplementation and methanogenesis inhibitors.
Methane production by livestock accounts for over 5% of global greenhouse gas emissions annually . These emissions mostly originate from the activity of methanogens within ruminants, which generate methane as an obligate end-product of their energy metabolism . Several lineages of methanogenic archaea are core members of the microbiome of the ruminant foregut [3,4,5]. Of these, hydrogenotrophic methanogens are dominant in terms of both methane emissions and community composition [6, 7], with global surveys indicating that Methanobrevibacter gottschalkii and Methanobrevibacter ruminantium comprise 74% of the rumen methanogen community . These organisms use molecular hydrogen (H2) to reduce carbon dioxide (CO2) to methane through the Wolfe cycle of methanogenesis [8, 9]. Rumen methanogens have also been identified that use formate, acetate, methyl compounds and ethanol as substrates, but usually do so in conjunction with H2 [5, 10,11,12]. Given their major contribution to greenhouse gas emissions, multiple programs are underway to mitigate ruminant methane production [13, 14]. To date, most strategies have focused on direct inhibition of methanogens using chemical compounds or vaccines [15,16,17,18]. A promising alternative strategy is to modulate the supply of substrates to methanogens, such as H2, for example, through dietary or probiotic interventions [14, 19, 20]. To achieve this, while maintaining health and productivity of the host animal, requires an understanding of the processes that mediate substrate supply to methanogens within the rumen.
H2, the main substrate supporting ruminal methanogenesis, is primarily produced through fermentation processes . Various carbohydrate fermentation pathways lead to the production of H2 as an end-product, together with volatile fatty acids and CO2 [21,22,23]. This process is supported by hydrogenases, which reoxidise cofactors reduced during carbohydrate fermentation and dispose of the derived electrons by producing H2. Although it is unclear which rumen microorganisms mediate H2 production in situ, a range of isolates have been shown to produce H2 in vitro [24,25,26,27,28]. For example, the model rumen bacterium R. albus 7 reoxidises the reduced ferredoxin and NADH formed during glucose fermentation by using two different [FeFe]-hydrogenases depending on environmental conditions . In addition, it is well-established that some rumen fungi and ciliates produce H2 via hydrogenosomes [30, 31]. A debated source is the nitrogenase reaction, which produces H2 while fixing N2; whereas numerous rumen microorganisms encode putative nitrogenases , in situ data indicate that N2 fixation occurs at negligible rates in the rumen [32, 33]. A large proportion of the H2 produced by hydrogenogenic fermenters is directly transferred to hydrogenotrophic methanogens, in an ecological process known as interspecies hydrogen transfer [25, 34]. Particularly remarkable are the endosymbiotic and ectosymbiotic associations of methanogens, such as M. ruminantium, with rumen ciliates [35,36,37]. In addition to providing a continual substrate supply for methanogens, such symbioses benefit fermenters by maintaining H2 at sufficiently low concentrations for fermentation to remain thermodynamically favourable .
Various hydrogenotrophic bacteria are thought to compete with methanogens for the rumen H2 supply. Most attention has focused on acetogens, which mediate conversion of H2/CO2 to acetate using [FeFe]-hydrogenases . Several genera of acetogens have been isolated from the rumen, including Eubacterium , Blautia  and Acetitomaculum . However, molecular surveys indicate their abundance is generally lower than hydrogenotrophic methanogens [43,44,45]. This is thought to reflect that methanogens outcompete acetogens owing to the higher free energy yield of their metabolic processes, as well as their higher affinity for H2. The dissolved H2 concentration fluctuates in the rumen depending on diet, time of feeding and rumen turnover rates, but is generally at concentrations between 400 and 3400 nm ; these concentrations are typically always above the threshold concentrations required for methanogens (< 75 nm) but often below those of acetogens (< 700 nm) . Despite this, it has been proposed that stimulation of acetogens may be an effective strategy for methane mitigation in methanogen-inhibited scenarios [14, 20, 48, 49]. Various microorganisms have also been isolated from cows and sheep that support anaerobic hydrogenotrophic respiration, including dissimilatory sulfate reduction (e.g., Desulfovibrio desulfuricans) [50, 51], fumarate and nitrate reduction (e.g., Selenomonas ruminantium, Wolinella succinogenes) [52,53,54,55,56,57,58,– 59] and trimethylamine N-oxide reduction (e.g., Denitrobacterium detoxificans) . The first described and most comprehensively studied of these hydrogen oxidisers is W. succinogenes, which mediates interspecies hydrogen transfer with R. albus . In all cases, respiratory electron transfer via membrane-bound [NiFe]-hydrogenases and terminal reductases generates a proton-motive force that supports oxidative phosphorylation . It is generally assumed that these pathways are minor ones and are limited by the availability of oxidants. Promisingly, it has been observed that dietary supplementation with fumarate, sulfate, or nitrate can significantly reduce methane production in cattle, likely by stimulating alternative pathways of H2 consumption [62, 63].
We postulate that mitigating methane emissions, while maintaining animal productivity, depends on understanding and controlling H2 utilisation by methanogens. This requires a system-wide perspective of the schemes for production and concomitant utilisation of H2 in the rumen. To facilitate this, we determined which organisms and enzymes are primarily responsible for H2 production and consumption in rumen. First, we screened genome, metagenome and metatranscriptome data sets [21, 64, 65] to identify microbial genera, metabolic pathways and hydrogenase classes [66, 67] that mediate H2 metabolism. We demonstrate that ruminants harbour a diverse community of hydrogenogenic fermenters and hydrogenotrophic methanogens, acetogens and sulfate, fumarate and nitrate reducers. Second, we used the model system of the H2-producing carbohydrate fermenter R. albus 7 and the H2-utilising fumarate-reducing syntrophic partner Wolinella succinogenes DSM 1740 [25, 54, 55, 68] to gain a deeper mechanistic understanding of how and why ruminant bacteria regulate H2 metabolism. We observed significant differences in the growth, transcriptome and metabolite profiles of these bacteria in co-culture compared with pure culture. Finally, we compared gene expression profiles associated with H2 metabolism between low versus high methane yield sheep . It was recently proposed, on the basis of community structure analysis, that fewer H2-producing bacteria inhabit low methane yield sheep . In this work, we provide evidence for an alternative explanation: H2 uptake through non-methanogenic pathways accounts for these differences. Whereas the enzymes mediating fermentative H2 production are expressed at similar levels, those supporting H2 uptake through acetogenesis, fumarate reduction and nitrate ammonification pathways are highly upregulated in low methane yield sheep. In turn, these findings support that strategies to promote alternative H2 uptake pathways, including through dietary modulation, may significantly reduce methane emissions.
Materials and methods
Comparative genomic analysis
The protein sequences of the 501 genomes of cultured rumen bacteria (410 from Hungate Collection , 91 from other sources) were retrieved from the Joint Genome Institute (JGI) genome portal. These sequences were then screened against local protein databases for the catalytic subunits of the three classes of hydrogenases (NiFe-hydrogenases, FeFe-hydrogenases, Fe-hydrogenases), nitrogenases (NifH), methyl-CoM reductases (McrA), acetyl-CoA synthases (AcsB), adenylylsulfate reductases (AprA), dissimilatory sulfite reductases (DsrA), alternative sulfite reductases (AsrA), fumarate reductases (FrdA), dissimilatory nitrate reductases (NarG), periplasmic nitrate reductases (NapA), ammonia-forming nitrite reductases (NrfA), DMSO/TMAO reductases (DmsA) and cytochrome bd oxidases (CydA). Hydrogenases were screened using the HydDB data set [66, 67], targeted searches were used to screen six protein families (AprA, AsrA, NarG, NapA, NrfA, DmsA, CydA) and comprehensive custom databases were constructed to screen five other protein families (NifH, McrA, AcsB, DsrA, FrdA) based on their total reported genetic diversity [70,71,72,73,74]. A custom Python script incorporating the Biopython package  was designed to produce and parse BLAST results (https://github.com/woodlaur189/get_flanks_blast/releases). This script was used to batch-submit the protein sequences of the 501 downloaded genomes as queries for BLAST searches against the local databases. Specifically, hits were initially called for alignments with an e-value threshold of 1e-50 and the resultant XML files were parsed. Alignments producing hits were further filtered for those with coverage values exceeding 90% and percent identity values of 30–70%, depending on the target, and hits were subsequently manually curated. Table S1 and S2 provide the FASTA protein sequences, alignment details and distribution summaries of the filtered hits. For hydrogenases, the protein sequences flanking the hydrogenase large subunits were also retrieved; these sequences were used to classify group A [FeFe]-hydrogenases into subtypes (A1–A4), as previously described , and retrieve diaphorase sequences (HydB) associated with the A3 subtype. Partial [FeFe]-hydrogenase protein sequences from six incompletely sequenced rumen ciliates and fungi genomes were retrieved through targeted blastP searches  in NCBI.
Metagenomic and metatranscriptomic analysis
We analysed previously published data sets of 20 paired metagenomes and metatranscriptomes of sheep rumen contents . All profiles were derived from the rumen contents of age-matched, pelleted lucerne-fed rams that were collected 4 h after morning feeding and subject to paired-end sequencing on the HiSeq2000 platform . The samples were taken from 10 rams at two different sampling dates based on their measured methane yields [64, 77]; four rams were consistently low yield, four were consistently high yield, and two others switched in methane yield between the sampling dates (Table S3). The metagenome and metatranscriptome data sets analysed are accessible at the NCBI Sequence Read Archive (SRA; http://www.ncbi.nlm.nih.gov/sra) accession numbers SRA075938, and SRX1079958—SRX1079985 under bioproject number PRJNA202380. Each metagenome and metatranscriptome was subsampled to an equal depth of five million reads using seqtk (https://github.com/lh3/seqtk) seeded with parameter -s100. Subsampled data sets were then screened in DIAMOND (default settings, one maximum target sequence per query)  using the protein sequences retrieved from the 507 rumen microbial genomes (NiFe-hydrogenases, FeFe-hydrogenases, Fe-hydrogenases, HydB, NifH, McrA, AcsB, AprA, DsrA, AsrA, FrdA, NarG, NapA, NrfA, DmsA, CydA). Results were then filtered (length of amino acid > 40 residues, sequence identity > 65%). Subgroup classification and taxonomic assignment of the hydrogenase reads was based on their closest match to the hydrogenase data set derived from the 507 genomes at either 65 or 85% identity. The full pipeline used is provided on GitHub (https://github.com/Cecilia-Wang/Diamond_line_reader_pipeline). The hits obtained are shown in Table S4 and S5. The number of reads with the rumen-specific hydrogenase data set (15,464 metagenome hits, 40,485 metatranscriptome hits) exceeded those obtained by screening with the generic data set from HydDB  (12,599 metagenome reads, 31,155 metatranscriptome reads), verifying that the rumen data set comprehensively captures hydrogenase diversity. For each data set, read count was normalised to account for the average length of each gene using the following formula: Normalised Read Count = Actual Read Count × (1000/average gene length). Independent two-group Wilcoxon rank-sum tests were used to determine whether there were significant differences in the targets analysed between low and high methane yield sheep. Separate analyses were performed based on gene abundance, transcript abundance and RNA/DNA ratio.
Bacterial growth conditions
The bovine rumen isolates R. albus 7  and Wolinella succinogenes DSM 1740  were cultured anaerobically at 37 °C in modified Balch medium  (Table S6). Pre-cultures were grown in Balch tubes (18 × 150 mm; Chemglass Life Sciences, Vineland, NJ) containing 20% v/v culture medium and sealed with butyl rubber stoppers crimped with aluminium caps. Cultures were grown in Pyrex side-arm flanks (Corning Inc., Corning, NY) containing 118 mL modified Balch medium. Two pre-cultures were grown before final inoculation, and all inoculum transfers were 5% (v/v). The headspace consisted of 20% CO2 and 80% N2 for R. albus pure cultures and the co-cultures, and 20% CO2 and 80% H2 for W. succinogenes pure cultures. Cultures were periodically sampled at 0, 3, 5, 7, 9 and 11 h for metabolite analysis and bacterial quantification. Each culture was also sampled at 0 and 24 h to analyse H2 mixing ratios. Culture samples were immediately centrifuged (16,000 × g, 10 min) in a bench-top centrifuge (Eppendorf, Hamburg, Germany). For metabolite analysis, the supernatant was collected and further centrifuged (16,000 × g, 10 min) before high-performance liquid chromatography analysis.
Quantitative PCR was used to quantify the copy numbers of R. albus and W. succinogenes under pure culture and co-culture. DNA was extracted from each pellet using the Fungal/Bacterial DNA MiniPrep kit according to the manufacturer’s instructions (Zymo Research, Irvine, CA). Primers were designed to specifically amplify Rumal_2867 (R. albus glucokinase gene; FW: CTGGGATTCCTGAACTTTCC; RV: ATGCATACTGCGTTAG) and WS0498 (W. succinogenes flgL gene; FW: CAGACTATACCGATGCAACTAC; RV: GAGCGGAGGAGATCTTTAATC). For quantification, amplicons of each gene were cloned into pGEM-T Easy vectors (Promega, Madison, WI). Vector inserts were sequenced to confirm proper insertion. Standard curves extended from 102 to 1010 copies mL−1. DNA was amplified with iTaq Universal SYBR Green (Bio-Rad) on a LightCycler 480 (Roche Holding AG, Basel, Switzerland). The amplification conditions were as follows: initial denaturation for 5 min at 95 °C, 40 amplification cycles (15 s at 95 °C, 20 s at 60 °C, 10 s at 68 °C) and final extension for 5 min at 68 °C. Fluorescence was read during the extension phase of each cycle. The linear regression of the standard curve resulted in an R2 > 0.99, efficiencies were between 97.8–98.5%, and primers were confirmed to not cross-react. Two-tailed tests were done on sample data using SAS Studio (SAS Institute Inc., Cary, NC) to compare growth rates between single and co-cultures. All populations were normally and independently distributed with equal variances.
Liquid and gas metabolite analysis
The concentrations of acetate, ethanol, fumarate, succinate and formate in the culture supernatants were analysed using an Ultra-Fast Liquid Chromatograph (UFLC; Shimadzu, Kyoto, Japan). The UFLC consisted of a DGU-20A5 degasser, a SIL-20ACHT autosampler, an LC-20AT solvent delivery unit, an RID-10A refractive index detector, a CBM-20A system controller, and a CTO-20AC column oven. The mobile phase was 5 mm H2SO4 passed through an Aminex HPX-87H ion exclusion column (Bio-Rad, Hercules, CA) at a flow rate of 0.4 mL min−1, 25 °C. Percentage mixing ratios of H2 were measured using a gas chromatograph (GC; Gow-Mac Series 580 Thermal Conductivity Gas Chromatograph, Gow-Mac Instrument Co., Bethlehem, PA). Samples were withdrawn directly from the culture tube in a gas-tight syringe and 0.5 mL was injected into GC for analysis using N2 as the carrier gas. The flow rate was 60 mL min−1, the detector was set to 80 °C, the injector was set to 80 °C and the oven was set to 75 °C. For both liquid and gas analyses, peak retention times and peak area were compared to standards of known concentration.
RNA extraction and sequencing
Each pure culture and co-culture used for transcriptome analysis was grown in duplicate in Balch tubes. Growth was monitored until the cultures were in mid-exponential phase; the change in OD600 at this phase was 0.14 for W. succinogenes, 0.20 for R. albus and 0.35 for the co-culture. At mid-exponential phase, 5 mL cultures were harvested by centrifugation (13,000 × g, 4 °C). Cell pellets were resuspended in 400 μL fresh lysis buffer (5 mm EDTA, 0.5% SDS, 25 mm lysozyme, 250 U mL−1 mutanolysin and 150 μg mL−1 proteinase K in 25 mm sodium phosphate buffer, pH 7.0) and incubated under oxic conditions for 30 min at 55 °C with periodic vortexing. RNA was subsequently extracted under oxic conditions using an RNeasy Mini Kit following the manufacturer’s protocol, including all optional steps (Qiagen, Hilden, Germany), and eluted with 50 μL ultra-pure DEPC-treated water (Invitrogen, Carlsbad, CA). RNA quantity, quality and integrity were confirmed by Qubit Fluorometry (Invitrogen, Carlsbad, CA), Nanodrop UV-Vis Spectrophotometry (Thermo Fisher Scientific, model 2300c), and agarose gel electrophoresis respectively. Bacterial rRNA was removed from 1 μg of total RNA with the MicrobExpress Kit (Life Technologies, Carlsbad, CA). Libraries were prepared on the enriched mRNA fraction using the Stranded RNA Sample Prep Kit (Illumina, San Diego, CA). The barcoded libraries were pooled in equimolar concentration and sequenced on one lane for 101 cycles on a HiSeq2000 using a TruSeq SBS Sequencing Kit (Version 3). Fastq files were generated and demultiplexed with the bc12fastq Conversion Software (Illumina, version 1.8.4). The RNA-seq data were analysed using CLC Genomics Workbench version 5.5.1 (CLC Bio, Cambridge, MA). RNA-seq reads were mapped onto the reference genome sequences of R. albus 7  and Wolinella succinogenes DSM 1740  (Table S7 & S8). The RNA-seq output files were analysed for statistical significance as described  and q values were generated using the q value package in R . Predicted subsystems and functions were downloaded and aligned to the RNA-seq transcriptional data using the RAST Server .
H2 metabolism is a common and diverse trait among rumen bacteria, archaea and eukaryotes
We searched the 501 reference genome sequences of rumen bacteria and archaea  for genes encoding the catalytic subunits of H2-consuming and H2-producing enzymes (Table S1 & S2). Of these, 65% encoded the capacity to metabolise H2 via [FeFe]-hydrogenases (42%), [NiFe]-hydrogenases (31%), [Fe]-hydrogenases (2.4%) and/or nitrogenases (23%). This suggests that H2 metabolism is a widespread trait among rumen microorganisms. We also identified multiple partial sequences of group A1 [FeFe]-hydrogenases in the incomplete genomes of six rumen fungi and ciliates. This is consistent with the known ability of these microorganisms to produce H2 during cellulose fermentation . The 329 hydrogenase- and nitrogenase-positive genomes spanned 108 genera, 26 orders, 18 classes and 11 phyla (Fig. 1; Figure S1; Table S1 & S2).
We then classified the hydrogenases identified into subgroups. To do so, we used the phylogeny-based, functionally-predictive classification scheme of HydDB , which has been used to understand H2 metabolism in a range of organisms and ecosystems [85,86,87,88,89]. In total, 273 strains encoded hydrogenases from classes that primarily evolve H2 under physiological conditions (Table S2). These include group A1 and B [FeFe]-hydrogenases and group 4e [NiFe]-hydrogenases that couple ferredoxin oxidation to H2 production in anaerobic bacteria [90,91,92]. However, the most widespread hydrogenases are the group A3 [FeFe]-hydrogenases, which were encoded in 43 genera, among them well-characterised carbohydrate fermenters such as Ruminococcus, Lachnoclostridium and Bacteroides. These hydrogenases form heterotrimeric complexes, together with diaphorase subunits, that mediate the recently-discovered process of electron-confurcation: coupling co-oxidation of NADH and ferredoxin produced during fermentative carbon degradation to production of H2 [29, 93]. This reversible complex can also support hydrogenotrophic acetogenesis . By retrieving the genes immediately upstream and downstream, we verified that the diaphorase subunits (HydB) of this complex were co-encoded with the retrieved hydrogenase subunits (Fig. 1; Table S2).
In addition, multiple organisms encoded hydrogenases and terminal reductases known to support hydrogenotrophic growth (Fig. 1). All 21 methanogen genomes surveyed harboured [NiFe]-hydrogenases together with the signature gene of methanogenesis (mcrA) (Fig. 1; Table S2). These include 14 Methanobrevibacter strains, which encoded a complete set of enzymes for mediating hydrogenotrophic methanogenesis through the Wolfe cycle , including the [Fe]-hydrogenase and the groups 3a, 3c, 4h and 4i [NiFe]-hydrogenases. Seven genomes encoded both [FeFe]-hydrogenases (A2, A3) and the marker gene for acetogenesis (acsB) (Table S2), including known hydrogenotrophic acetogens Blautia schinkii  and Acetitomaculum ruminis . Several subgroups of the group 1 [NiFe]-hydrogenases, all membrane-bound enzymes known to support hydrogenotrophic respiration [66, 95], were also detected. Most notably, various Selenomonas, Mitsuokella and Wolinella strains encoded such hydrogenases together with the signature genes for fumarate reduction (frdA) and nitrate ammonification (narG, napA, nrfA). As anticipated, the group 1b [NiFe]-hydrogenase and dsrA gene characteristic of hydrogenotrophic sulfate reduction were also encoded in the three genomes of ruminal Desulfovibrio isolates (Fig. 1; Table S2).
H2 is mainly produced in sheep by clostridial electron-bifurcating [FeFe]-hydrogenases and consumed by [NiFe]-hydrogenases of methanogens and selenomonads
We then investigated the relative abundance and expression levels of the retrieved hydrogenases in rumen communities. To do so, we used 20 pairs of metagenomes and metatranscriptomes that were previously sequenced from the rumen contents of age- and diet-matched farmed sheep  (Table S3). Screening these data sets with hydrogenases retrieved from the rumen microbial reference genomes yielded 15,464 metagenome hits (0.015% of all reads) and 40,485 metatranscriptome hits (0.040%) (Table S4). Across the metagenomes, the dominant hydrogenase reads originated from eleven subgroups (A1, A2, A3, B, 3a, 3c, 4e, 4g, 4h, 4i, Fe) (Fig. 2a & S2a) and three taxonomic orders (Clostridiales, Methanobacteriales, Selenomonadales) (Fig. 2c & S3a); this is concordant with the hydrogenase content in the genomes of the dominant community members [64, 65] (Table S2). Metatranscriptome analysis indicated these genes were differentially expressed: whereas A3, 1d, 3a, 3c and 4g genes were highly expressed (RNA/DNA expression ratio > 4), others were expressed at moderate (A1, A2, Fe; ratio 1.5–2.5) or low levels (B, 4e, 4h, 4i; ratio < 1.5) (Figure S2 & S3; Table S1). Though putative nitrogenase genes (nifH) were detected, expression ratios were low (av. 0.45), suggesting nitrogen fixation is not a significant H2 source in sheep (Figure S4). This is consistent with previous reports that nitrogenase activity in ovine rumen contents is low [33, 96].
Accounting for 54% of hydrogenase transcripts detected (Figs. 2b, 3a, S2), group A3 [FeFe]-hydrogenases appear to be the primary catalysts of H2 production in ruminants. We assigned the retrieved transcripts to taxa based on their closest hits to the rumen genome hydrogenase data set (Table S4). Clostridia accounted for the majority of the hits (Fig. 2d), including Ruminococcus (22%), Saccharofermentans (9.2%) and Lachnoclostridium (7.4%) species known to fermentatively produce H2 [29, 34, 97] (Figure S5 & S6). Transcripts from the characterised fermentative genera Bacteroides, Butyrivibrio, Clostridium and Sarcina were also moderately abundant. A further 21% of group A3 [FeFe]-hydrogenase hits were assigned to three uncharacterised cultured lineages within the Clostridia: Clostridiales R-7, Ruminococcaceae P7 and Lachnospiraceae YSB2008 (Figure S5 & S6). This is compatible with our previous studies showing unclassified microorganisms, especially from R-7 group, are abundant in rumen . H2-evolving hydrogenases from the A1 and B subgroups were also detected, but their RNA/DNA expression ratios were threefold lower than the A3 hydrogenases. Rumen ciliates such as Epidinium dominated A1 reads (Fig. 2d & S5), but it is likely that their abundance in the data sets is underestimated owing to the minimal genome coverage of these organisms to date. The expression of formate hydrogenlyases and other formate-dependent hydrogenases were extremely low in metatranscriptome data sets (Fig. 3c), indicating formate-dependent H2 production is not a major pathway in situ.
The metatranscriptome data sets indicate that multiple H2 uptake pathways operate in ruminants (Figs. 2 and 3). In agreement with historical paradigms , hydrogenotrophic methanogenesis appears to be the largest sink of H2; methanogens accounted for 5.3% of normalised hydrogenase reads (Fig. 2d) and methyl-CoM reductase (mcrA) is the most expressed of the reductases surveyed (Fig. 3c). Consistent with their central roles in the CO2-reducing pathway of methanogenesis , the F420-reducing [NiFe]-hydrogenase (3a)  and the heterodisulfide reductase-associated [NiFe]-hydrogenase (3c)  of Methanobrevibacter species were among the most transcribed of all H2 uptake enzymes (Fig. 3a and S5). In contrast, the Eha-type (4h), Ehb-type (4i) and [Fe]-hydrogenases were expressed at lower levels (Fig. 3a and S5), reflecting their secondary roles in the physiology of methanogens [100,101,102]. There was also strong evidence that hydrogenotrophic acetogenesis may be a more significant ruminal H2 sink than previously recognised. Across the data set, acetyl-CoA synthases (acsB; 1135 normalised reads) were expressed at a quarter of the level of methyl-CoM reductases (mcrA; 5246 normalised reads) (Fig. 3c). For 74% of the reads, the closest matches were to predicted hydrogenotrophic acetogens isolated from rumen, including Blautia, Acetitomaculum and Oxobacter (Figure S7 & Table S5). Consistently, genes encoding close homologues of the group A2 and group A3 [FeFe]-hydrogenases from these genera were moderately expressed in the metatranscriptomes (3.7%) (Figure S5). The other acsB reads likely originate from acetogens that use other electron donors, such as formate. No acsB hits from methanogens were detected.
Surprisingly, however, the most highly expressed H2 uptake hydrogenase overall is the group 1d [NiFe]-hydrogenase of Selenomonadales (4.1%) (Figs. 3a, b and S5). This enzyme is likely to mediate the long-known capacity of Selenomonas species to grow by hydrogenotrophic fumarate reduction and nitrate ammonification [52, 53, 58]. Consistently, fumarate reductases (frdA), nitrate reductases (narG) and ammonia-forming nitrite reductases (nrfA) homologous to those in S. ruminantium were expressed in the metatranscriptomes (Fig. 3c). Normalised nrfA expression was fivefold higher than narG, indicating selenomonads may preferentially use external nitrite, although further studies are required to determine the source of nitrite, this compound is known to accumulate in the rumen depending on nitrate content of feed . Reads corresponding to the group 1b [NiFe]-hydrogenase, periplasmic nitrate reductase (napA), nrfA and frdA from Wolinella was also detected, but at low levels (Table S4 & S5; Figure S5). Several other pathways in low abundance in the metagenome were also highly expressed, notably group 1b [NiFe]-hydrogenases and dsrA genes from Desulfovibrio species, as well as group 1i [NiFe]-hydrogenases from metabolically flexible Coriobacteriia (e.g., Slackia, Denitrobacterium) (Figure S4 & S5). The expression levels of the group 1b and 1d [NiFe]-hydrogenases, together with the functionally unresolved group 4g [NiFe]-hydrogenases, were the highest of all hydrogenases in data sets (RNA/DNA ratio > 10) (Figure S3). Though these findings need to be validated by activity-based studies in situ, they suggest that respiratory hydrogenotrophs are highly active and quantitatively significant H2 sinks in the rumen despite often being detected in low abundance .
Culture-based studies demonstrate that hydrogenases mediating H2 production and uptake are differentially regulated in response to hydrogen levels
In order to better understand how rumen bacteria regulate H2 metabolism, we performed a culture-based study using R. albus 7 and Wolinella succinogenes DSM 1740. This system was chosen given it is the best-studied example of rumen microorganisms that participate in interspecies hydrogen transfer  and is relevant to H2 transactions in the rumen, given Ruminococcus electron-bifurcating hydrogenases are the most abundant in the sheep metatranscriptome data sets (Figure S5). We compared the growth, transcriptome and extracellular metabolite profiles of these strains in either pure culture or co-culture when grown on modified fumarate-supplemented Balch medium (Table S6). The concentrations of the metabolites consumed and produced by the strains varied between the conditions (Table S1; Figure S8) in a manner consistent with previous reports [24, 25, 29, 54] and the transcriptomic results (Fig. 4). Based on the ratios of the products observed, R. albus fermentatively degraded cellobiose to H2, acetate and ethanol in pure culture (glucose + 3.3 ADP + 3.3 Pi → 2.6 H2 + 1.3 acetate + 0.7 ethanol + 2 CO2 + 3.3 ATP ) and H2 and acetate in co-culture (glucose + 4 ADP + 4 Pi → 4 H2 + 2 acetate + 2 CO2 + 4 ATP ) (Fig. 4a–c). W. succinogenes grew by hydrogenotrophic fumarate respiration under both conditions by using exogenously supplied H2 in pure culture and syntrophically-produced H2 in co-culture (Fig. 4–f). Hence, R. albus channels fermentation through the pathway that yields stoichiometrically more ATP, H2 and acetate, provided that H2 concentrations are kept sufficiently low through interspecies hydrogen transfer for this to be thermodynamically favourable (see Zheng et al.  for stoichiometric and thermodynamic considerations).
Transcriptome profiling revealed that R. albus tightly regulates the expression of its three hydrogenases (Fig. 4a, b). Overall, 133 genes were differentially expressed (fold change > 2, q value < 0.05) in co-culture compared with pure culture (Table S7). Of these, the greatest fold change was the 111-fold downregulation of a putative eight-gene cluster encoding the ferredoxin-only hydrogenase (group A1 [FeFe]-hydrogenase), a bifunctional alcohol and aldehyde dehydrogenase, and regulatory elements including a putative sensory hydrogenase (group C [FeFe]-hydrogenase) (Fig. 4a, b). By suppressing expression of these enzymes, R. albus can divert carbon flux from ethanol production to the more energetically efficient pathway of acetate production; acetate fermentation produces equimolar levels of NADH and reduced ferredoxin, which can be simultaneously reoxidised by the electron-bifurcating hydrogenase (group A3 [FeFe]-hydrogenase) (Fig. 4c). Glycolysis enzymes and the phosphate acetyltransferase, acetate kinase and electron-bifurcating hydrogenase of the acetate production pathway were expressed at similarly high levels under both conditions (Fig. 4a, b). However, there was a significant increase in the biosynthesis of thiamine pyrophosphate, a cofactor for pyruvate dehydrogenase complex, in co-culture (Fig. 4a).
The fermentation stoichiometries of R. albus 7 measured in pure culture compared with co-culture (Table 1) were the same as we previously reported for the bacterium at high vs low concentrations of H2 . This suggests that the differences in regulation are primarily determined by H2 levels, rather than by direct interactions with syntrophic partners. This regulation may be achieved through direct sensing of H2 by the putative sensory group C [FeFe]-hydrogenase co-transcribed with the ferredoxin-only hydrogenase and alcohol dehydrogenase (Fig. 4e). In common with other enzymes of this class [66, 104, 105], this enzyme contains a subunit containing a H-cluster for H2 binding and a PAS domain for signal transfer, as well as a putative serine or threonine phosphatase subunit that may modify downstream regulators. Thus, analogous to the well-studied regulatory hydrogenases of aerobic bacteria [106, 107], this enzyme may directly sense H2 levels and induce expression of the alcohol/aldehyde dehydrogenase and ferredoxin-only hydrogenase when H2 concentrations are high through a feedback loop. H2 sensing may be a general mechanism regulating hydrogenase expression in ruminants, given group C [FeFe]-hydrogenases are abundant in ruminant genome (Fig. 1), metagenome (Fig. 2a), and metatranscriptome data sets (Fig. 2b and 3a).
The transcriptome results also clarified understanding of hydrogenotrophic fumarate respiration by W. succinogenes (Fig. 4d). In both pure culture and co-culture, the group 1b [NiFe]-hydrogenase, fumarate reductase and F1Fo-ATPase that mediate this process were expressed at high levels (Table S7; Fig. 4f). A periplasmic asparaginase, aspartate ammonia-lyase and dicarboxylate-binding proteins were also highly expressed; this suggests that the organism can efficiently produce and import additional fumarate from amino acid sources (Table S7). In total, 352 genes were significantly differentially regulated in co-culture (fold change > 2, q value < 0.05). The respiratory hydrogenase was among the upregulated genes (Fig. 4e), which may reflect the strain’s faster growth rate in co-culture (Table 1). The periplasmic nitrate reductase and ammonia-forming nitrite reductase (Fig. 4f) were also induced, indicating some plasticity in electron acceptor usage, in line with the metatranscriptomic findings. Two formate dehydrogenases and a formate hydrogenlyase (group 4a [NiFe]-hydrogenase) were highly expressed in co-culture (Fig. 4d, e), indicating the bacterium can potentially use formate transferred from R. albus as a supplemental electron donor to H2 (Fig. 4a); consistently, R. albus is known to produce through formate pyruvate lyase activity and this enzyme was highly expressed in both pure culture and co-culture (Table S7), though any formate produced was below detection limits (1 mm) (Table 1).
Hydrogenotrophic acetogenesis, fumarate reduction and nitrate reduction pathways are significantly upregulated in low methane yield sheep
Finally, we tested whether the abundance and expression of hydrogenases and H2 uptake pathways differed between high and low methane yield sheep. A current leading hypothesis, proposed on the basis of community composition , asserts that H2 production levels account for differences in methane yield between sheep. To the contrary, the expression levels of the dominant H2-evolving hydrogenases (e.g., group A3 [FeFe]-hydrogenases) and taxonomic orders (e.g., Clostridiales) were in fact extremely similar between the groups (Fig. 3a, b; Table S9 & S10).
We therefore tested an alternative hypothesis: H2 utilisation through non-methanogenic pathways can reduce methane yield. In line with this hypothesis, the expression levels of the five methanogen hydrogenases and methyl-CoM reductase are significantly reduced in low methane yield sheep (Fig. 3a, c; Table S9 & S11), confirming a strong correlation with methane yield (Table S3). Concurrent increases in the gene expression for two major alternative H2 sinks were detected, namely acetogenesis (acsB; p < 0.0001) and fumarate reduction (frdA; p = 0.002) (Fig. 3c; Table S10), concomitant with significant increases in the expression levels of Blautia and Selenomonas hydrogenases (Figure S5). Expression levels of nrfA were also on average 1.8-fold higher in low methane yield sheep, though there was much inter-sample variation in the read count for this gene. Whereas there are more transcripts of mcrA than other terminal reductases combined in high methane yield sheep, the transcript levels of acsB and nrfA together exceed those of mcrA in low methane yield sheep. Depending to what extent expression levels predict activity, hydrogenotrophic acetogens and selenomonads may therefore be more active than methanogens in low methane yield sheep and may significantly limit substrate supply for methanogenesis. Two other potential H2 sinks are also upregulated in the low methane yield sheep: the putative group 1i [NiFe]-hydrogenase of Coriobacteriia and, consistent with previous observations , the functionally unresolved group A2 [FeFe]-hydrogenase of Sharpea, Olsenella and Oribacterium (Fig. 3a, b, S5).
To summarise, H2 metabolism is a more widespread and complex process in ruminants than previously realised. Together, the genomic, metagenomic and metatranscriptomic surveys suggest that multiple orders of bacteria, archaea and eukaryotes encode and express enzymes mediating H2 production and consumption in the rumen. We infer that fermentative Clostridia are the main source of H2 in the rumen, which largely agrees with findings from activity-based and culture-based studies [6, 25, 26, 29], and that a range of methanogenic, acetogenic and respiratory hydrogenotrophs are present. Although this manuscript provides a relatively comprehensive understanding of H2 transactions in the rumen, it is probable that other uncharacterised organisms and genes also contribute to this process. A more-detailed perspective of which taxa mediate H2 cycling in the rumen would be possible by profiling the thousands of metagenome-assembled genomes recently recovered from ruminants [23, 108] and also better accounting for the role of the largely unsequenced rumen ciliates and fungi, which to date are underrepresented in genomic data sets. Further studies are also necessary to extend findings to other ruminants, such as bovines, and investigate how H2 cycling responds to environmental factors such as diet.
One of the most-important findings of this work is that the recently characterised electron-bifurcating hydrogenases appear to primarily mediate ruminal H2 production. These enzymes are highly upregulated compared with ferredoxin-only hydrogenases in situ and constitute over half of hydrogenase reads in these metatranscriptomes. We provide a rationale for this finding by showing that R. albus, a dominant H2 producer within the rumen, expresses its electron-bifurcating hydrogenase and suppresses its ferredoxin-only hydrogenase when grown syntrophically with Wolinella succinogenes. In this condition, H2 concentrations remain sufficiently low that the fermentation pathway producing higher levels of ATP, H2 and acetate remains thermodynamically favourable. In the rumen, where tight coupling of hydrogenogenic and hydrogenotrophic processes usually keeps H2 at sub-micromolar concentrations , Clostridia will also preferentially oxidise carbohydrates through higher ATP-yielding pathways and reoxidise the NAD and ferredoxin reduced using the electron-bifurcating hydrogenase . It is likely that the ferredoxin-only hydrogenases are preferentially upregulated during the transient periods where H2 levels are high, for example immediately after feeding . Based on these findings and previously published results [29, 66, 104, 105], we propose that the hydrogenases and fermentation pathways are differentially regulated as a result of direct H2 sensing by putative sensory [FeFe]-hydrogenases. A further surprising finding is that uncharacterised lineages within the Clostridia account for a large proportion of the electron-bifurcating hydrogenase reads, emphasising the need for physiological and bacteriological characterisation of these organisms.
The other major finding of this work is that there are multiple highly active H2 sinks in the rumen. We provide evidence, based on transcript levels of their hydrogenases and terminal reductases, that acetogens (Blautia, Acetitomaculum), fumarate and nitrate reducers (Selenomonas, Wolinella) and sulfate reducers (Desulfovibrio) are quantitatively significant H2 sinks in sheep. In support of these findings, our culture-based study confirmed that the enzymes mediating hydrogenotrophic fumarate reduction and potentially nitrate ammonification are highly expressed by W. succinogenes in co-culture with R. albus. Although alternative H2 uptake pathways have been previously detected in vitro [41, 42, 50,51,52,53, 57, 58], it has generally been assumed that they are quantitatively insignificant compared to hydrogenotrophic methanogenesis [5, 6, 46]. To the contrary, hydrogenase and terminal reductase transcripts from alternative H2 uptake pathways are more numerous than those of methanogens in low methane yield sheep, and hence these pathways may collectively serve as a larger H2 sink than methanogenesis under some circumstances. These findings justify activity-based studies to quantify H2 flux within ruminants between methanogenic and non-methanogenic pathways. There is also evidence of other novel pathways operating in the rumen, mediated by the functionally unresolved group 1i [NiFe]-hydrogenases (Slackia, Denitrobacterium), group 4g [NiFe]-hydrogenase (Clostridium) and group A2 [FeFe]-hydrogenases (Sharpea, Oribacterium, Olsenella).
These findings also provide some insight into the basis of variation in methane emissions between ruminants. Methane yield in ruminants is a quantitative heritable trait [64, 77], to some extent, and there is much interest in developing host or microbiome markers to enable selection of animals with low methane yield traits . Our study compared the abundance and expression of key functional genes in the rumen microbial communities of sheep that differed by an average of 28% in methane yield. In low methane yield sheep, there was significantly decreased expression of methyl-CoM reductase, increased expression of acetyl-CoA synthase and fumarate reductase and multiple changes in hydrogenase profiles. However, we detected few significant differences at the gene level. The similar metagenome profiles, combined with the metatranscriptome profiles of the phenotype-switching sheep, therefore suggest that alternative H2 uptake pathways are partly inducible. Further studies with larger sample sizes are needed to assess whether transcripts of these functional genes can predict methane yield and, if so, whether they can be adopted as biomarkers to facilitate animal selection or evaluate methane mitigation strategies. Our findings, in conjunction with other studies , indicate that the methyl-CoM reductase and hydrogenases of methanogens may be particularly promising and relevant biomarkers.
The strong correlation between H2 uptake pathways and methane yield phenotypes nevertheless supports that modulating H2 metabolism may be an effective methane mitigation strategy. One strategy is to develop inhibitors that redirect electron flux from H2 production towards volatile fatty acid production. However, given the central role of H2 metabolism in the physiology and ecology of most rumen microorganisms, this would be challenging to achieve without compromising rumen function and consequently ruminant nutrition. Furthermore, such strategies may have a converse effect on methane production, given lower H2 concentrations restrict acetogens more than methanogens . Instead, our metatranscriptome analyses support the concept that a more promising approach may be to stimulate alternative H2 pathways such as fumarate, nitrate and sulfate respiration. One solution may be to supplement animal feeds with electron acceptors, such as fumarate, nitrate, or sulfate, that stimulate the dominant respiratory hydrogenotrophs. Such approaches have shown some promise in mitigating methane production both in vitro [110,111,112] and in field trials [62, 63, 113, 114]. These strategies may complement methanogenesis inhibitors [16, 17] by facilitating the redirection of H2 flux from methanogens to other pathways. Although further studies are required, there is also growing evidence that redirecting H2 flux can favour animal production by enabling recovery of energy that would otherwise be lost through methane emissions .
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This study was funded by the New Zealand Government to support the objectives of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases via a grant from the New Zealand Fund for Global Partnerships in Livestock Emissions Research (SOW14-GPLER4-AGR-SP6; awarded to G.T.A., S.C.L., W.J.K., R.M., S.K. and G.M.C.). Transcriptomic and metabolic research on the co-cultures was supported by the Agriculture and Food Research Initiative competitive grant 2012-67015-19451 from the USDA National Institute of Food and Agriculture (awarded to R.I.M. and I.C.). The study was also supported by an ARC DECRA Fellowship (DE170100310; awarded to C.G.), an ARC Future Fellowship (FT170100441; awarded to M.J.M.) and a PhD scholarship awarded by Monash University (L.C.W.).
Conflict of interest
The authors declare that they have no conflict of interest.
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