Annotated metagenome-assembled genomes recovered from rumen samples from cows

  

Protozoa comprise a major fraction of the microbial biomass in the rumen microbiome, of which the

entodiniomorphs (order: Entodiniomorphida) and holotrichs (order: Vestibuliferida) are consistently

observed to be dominant across a diverse genetic and geographical range of ruminant hosts. Despite

the apparent core role that protozoal species exert, their major biological and metabolic contributions to rumen function remain largely undescribed in vivo. Here, we have leveraged (meta)genome

centric metaproteomes from rumen fluid samples originating from both cattle and goats fed diets with varying inclusion levels of lipids and starch, to detail the specific metabolic niches that protozoa

occupy in the context of their microbial co-habitants. Initial proteome estimations via total protein counts and label-free quantification highlight that entodiniomorph species Entodinium and Epidinium as well as the holotrichs Dasytricha and Isotricha comprises an extensive fraction of the total rumen

metaproteome. Proteomic detection of protozoal metabolism such as hydrogenases (Dasytricha,  Isotricha, Epidinium, Enoploplastron), carbohydrate-active enzymes (Epidinium, Diplodinium, Enoploplastron, Polyplastron), microbial predation (Entodinium) and volatile fatty acid production (Entodinium and Epidinium) was observed at increased levels in high methane-emitting animals.

Despite certain protozoal species having well-established reputations for digesting starch, they were

unexpectedly less detectable in low methane emitting- 37 animals fed high starch diets, which were

instead dominated by propionate/succinate-producing bacterial populations suspected of being

resistant to predation irrespective of host. Finally, we reaffirmed our abovementioned observations

in geographically independent datasets, thus illuminating the substantial metabolic influence that under-explored eukaryotic populations have in the rumen, with greater implications for both digestion

and methane metabolism.The experimental procedures were approved by 104 the Auvergne-Rhône-Alpes Ethics Committee for Experiments on Animals (France; DGRI agreement APAFIS#3277–2015121411432527 v5) and

complied with the European Union Directive 2010/63/EU guidelines. Experiments were performed at

the animal experimental facilities of HerbiPôle site de Theix at the Institut National de la Recherche

pour l’Agriculture, l’Alimentation l’Environnement (INRAE, Saint-Genès-Champanelle, France) from

February to July 2016. Experimental design, animals and diets were as described elsewhere5,23. Briefly,

four Holstein cows and four Alpine goats, all lactating, were enrolled in respectively two 4 x 4 Latin

square design trials to study the effects of 4 diets over four 28-d experimental periods

The original study included four different experimental grassland hay basal diets with

concentrates supplemented with various lipid sources; control diet with no added lipids (CTL), diet

supplemented with corn oil and wheat starch (COS), diet supplemented with marine algae powder

(MAP) and diet supplemented with hydrogenated palm oil (HPO). In the

present study, we focused on the CTL and COS diets, which were associated with the most extreme

methane (CH4) emission profiles in both ruminant species. The CTL diet composed of grass hay ad

libitum with concentrates containing no additional lipid, whereas COS contained corn oil (5.0% total

dry matter intake (DMI)) and wheat starch -5.0 % of total DMI (COS). Corn oil (Olvea, Saint

Léonard, France) was added to the concentrate, at 5% of total DMI and contained (g/kg of total FA):

16:0 (114), 18:0 (16.4), cis-9 18:1 (297), cis-11 18:1 (6.30), 18:2n-6 (535), 18:3n-3 (7.57), 20:0 (3.48),

22:0 (1.0), 24:0 (1.5), and total FA (1000 g/kg). Detailed diet composition is available in Martin et al.

Each experimental period lasted for 28 days. Diets were offered as two equal meals at 0830 and 1600h.

Animals had access to a constant supply of freshwater ad libitum. Concentrate and hay refusals were

weighed daily. The amounts of feed offered the following day was adjusted regarding to refusals to

maintain the targeted the dietary 45 % dry matter (DM) forage and 55 % DM concentrate ratio. We

acknowledge that by only including one sampling point for rumen fluid we are reducing the power

that the original experimental Latin square design gives regarding minimizing individual error between

the animals. Rumen fluid was collected through stomach-tubing before the morning feeding on day 27 of each experimental period. The stomach tube consisted of a flexible 23 mm external diameter PVC hose fitted to a 10 cm-strainer at the head of the probe for cows, and a flexible 15 mm PVC hose with a 12 cm-strainer for goats. The first 200 ml of rumen fluid was discarded from to minimize contamination from saliva. Samples were filtered through a polyester monofilament fabric (280 μm pore size), dispatched in 2-ml screw-cap tubes, centrifuged at 15000 x g for 10 mins and the pellet snap-frozen

in liquid nitrogen. Samples were stored at -80°C until DNA extraction using the Yu and Morrison bead

beating procedure. In total, 32 rumen fluid samples (four cattle and four goats fed four diets included in the original study) were sent to the Norwegian University of Life Sciences (NMBU) for

metagenomic and metaproteomic analysis. Respiration chambers were used to measure methane

emissions over a 5-day period, while VFA and NH3 concentrations were determined by gas

chromatography using a flame ionization detector. Protozoa were counted by microscopy and

categorized as either small entodiniomorphs (<100 μm), large entodiniomorphs (>100 μm) or as

holotrichs Dasytricha and Isotricha9. Further specifics about diets and measurements can be found in

Martin et al. and VFA and methane measurements are summarized in Table 1.

Metagenomic shotgun sequencing was performed at the Norwegian Sequencing Centre on two lanes

of the HiSeq 3/4000 (Illumina) generating 150 bp paired-end reads in both lanes. Sequencing libraries

were prepared using the TruSeq DNA PCR-Free High Throughput Library Prep Kit (Illumina) prior to

sequencing. All 32 samples (4 cattle and 4 goats fed four diets included in the original study) were

run on both lanes to prevent potential lane-to-lane sequencing bias. FASTQ files were quality filtered

and Illumina adapters removed using Trimmomatic (v. 0.36) with parameters -phred33 for base

quality encoding, leading and trailing base threshold set to 20. Sequences with an average quality

score below 15 in a 4-base sliding window were trimmed and the minimum length of reads was set to

36 bp. MEGAHIT (v.1.2.9) was used to co-assemble reads originating from samples collected from

cow and goats separately, with options –kmin-1pass, --k-list 27,37,47,57,67,77,87, --min-contig-len 1000 in accordance with previous studies. Bowtie2 (v. 2.3.4.1) was used to map reads back to the assemblies and SAMtools (v. 1.3.1) was used to convert SAM files to BAM format and index sorted BAM files.

The two co-assemblies (one from the samples originating from cattle and the other originating from

the samples of goats) were binned using Maxbin2, MetaBAT2 and CONCOCT. MetaBAT2 (v. 2.12.1) was run using parameters –minContig 2000 and –numThreads 4, Maxbin2 (v. 2.2.7) ran with

default parameters and -thread 4, min_contig_length 2000, and CONCOCT (v. 1.1.0) ran with default

parameters and –length_threshold 2000. Further, bins were filtered, dereplicated and aggregated using DASTool39(v. 1.1.2 ) with the parameters –write_bins 1, --threads 2 and BLAST as search engine. This resulted in a total of 244 dereplicated MAGs across the two host species (104 originating from cow and 140 from goat). CheckM43(v. 1.1.3) lineage workflow was used to calculate completeness and contamination of each MAG, with parameters –threads 8, --extension fa, and CoverM (v. 0.5.0) (https://github.com/wwood/CoverM) was used to calculate relative abundance of each MAG, while GTDB-tk (v. 1.3.0) was used for taxonomic annotation. Approximately 90% (219 of 244) of the

recovered MAGs were considered high or medium quality MAGs according to MIMAGs threshold for

completeness and contamination for genome reporting standards. Gene

calling and functional annotation of the final MAGs were performed using the DRAM pipeline with

the databases dbCAN, Pfam, Uniref90, Merops, VOGdb and KOfam.