Proteome specialization of anaerobic fungi during ruminal degradation of recalcitrant plant fiber

Abstract

The rumen harbors a complex microbial mixture of archaea, bacteria, protozoa, and fungi that efficiently breakdown plant biomass and its complex dietary carbohydrates into soluble sugars that can be fermented and subsequently converted into metabolites and nutrients utilized by the host animal. While rumen bacterial populations have been well documented, only a fraction of the rumen eukarya are taxonomically and functionally characterized, despite the recognition that they contribute to the cellulolytic phenotype of the rumen microbiota. To investigate how anaerobic fungi actively engage in digestion of recalcitrant fiber that is resistant to degradation, we resolved genome-centric metaproteome and metatranscriptome datasets generated from switchgrass samples incubated for 48 h in nylon bags within the rumen of cannulated dairy cows. Across a gene catalog covering anaerobic rumen bacteria, fungi and viruses, a significant portion of the detected proteins originated from fungal populations. Intriguingly, the carbohydrate-active enzyme (CAZyme) profile suggested a domain-specific functional specialization, with bacterial populations primarily engaged in the degradation of hemicelluloses, whereas fungi were inferred to target recalcitrant cellulose structures via the detection of a number of endo- and exo-acting enzymes belonging to the glycoside hydrolase (GH) family 5, 6, 8, and 48. Notably, members of the GH48 family were amongst the highest abundant CAZymes and detected representatives from this family also included dockerin domains that are associated with fungal cellulosomes. A eukaryote-selected metatranscriptome further reinforced the contribution of uncultured fungi in the ruminal degradation of recalcitrant fibers. These findings elucidate the intricate networks of in situ recalcitrant fiber deconstruction, and importantly, suggest that the anaerobic rumen fungi contribute a specific set of CAZymes that complement the enzyme repertoire provided by the specialized plant cell wall degrading rumen bacteria.

Fig. 1. Concatenated ribosomal protein tree of the genomes and metagenome-assembled genomes (MAGs) included in RUS-refDB.

Phylum-level groups are colored in shades of gray (bacteria), red (archaea) and green (fungi), and labeled inside the circle (Spiroc. Spirochaetes, Verruc. Verrucomicrobia, Elus. Elusimicrobia). MAGs/clades with uncertain taxa have white background. Circles centered on the nodes indicates a bootstrap support >70, out of 100 bootstraps. Circles at the end of each node are color coded by the metagenome dataset or genome collection each MAG/genome in RUS-refDB originated from, as indicated in the top left legend. The number of different proteins detected from the samples in the switchgrass fiber fraction (dark green) and rumen fluid (light green) are specified by bars surrounding the tree. In cases where a protein group consisted of two or more homologues protein identifications, each protein match is considered. The viral scaffolds, not included in the tree, had 56 and 62 proteins detected in switchgrass fiber and rumen fluid respectively (Fig. S1). Numerical protein detection can be found in Table S1. A complete version of this tree is available in Newick format as Supplementary Data S1.

Fig. 2. CAZyme profile from each predicted source organism in RUS-refDB, displaying the detected proteins associated with the milled switchgrass.

Here, we focused only on CAZymes detected in both animals to achieve high confidence detection of the active key populations. CAZy families that might possess activity against cellulose and hemicellulose are indicated with an asterisk. The colors in the heat map indicates the protein detection levels of each protein group reported as the average Log₂(LFQ)-scores for the biological replicates, where a light blue color is low detection while darker is high protein detection. Some of the source organisms encompassed more than one detected variant of GH1, GH3, GH43, and CE1. For these cases, the protein detection is reported as the average Log₂(LFQ)-score and number of variants are indicated within the heat map. A corresponding figure showing the detection level for all variants separately, as well as the detection in the rumen fluid microhabitat is provided in Supplementary Fig. S3.

Fig. 3. Visualization of the number of predicted genes annotated to specific GH families in MT-eukDB (left) and those detected when searching MT-eukDB against the metaproteome (right).

Only CAZymes detected in both animals in at least one of the microhabitats are included to achieve high confidence detection. The colors of the squares in the right panel indicates the protein detection level for each individual protein, reported as the average log₂(LFQ) of the biological replicates, where light green represents low detection level while darker green is high protein detection level. While this figure only shows those detected in the milled switchgrass, a comprehensive table of all CAZymes detected in both switchgrass and rumen fluid can be found in Supplementary Data S3. This also includes details regarding proteins with multiple CAZyme modules (indicated with an ‘M’).

Fig. 4. Metabolic reconstruction of key players intermediate rumen fermentation as determined in this study.

The heat map shows the detection of proteins associated to main metabolic pathways (listed as pfam IDs) found in the most active genomes/MAGs (indicated on the top: Anasp Anaeromyces robustus, Pirfi Piromyces finnis, PirE2 Piromyces sp. E2, Neosp Neocallimastix californiae, Orpsp Orpinomyces sp.) in RUS-refDB. The colors in the heat map indicates the protein detection levels reported as the average log₂(LFQ)-scores for each biological replicate, where light blue represent lower detection levels while darker blue is high protein detection. Only the proteins from the switchgrass are included in the current figure, while a corresponding figure including protein detection from both switchgrass and rumen fluid is available in Supplementary Fig. S4. A comprehensive table including proteins detected in all MAGs/genomes included in RUS-refDB, proteins associated to the rumen fluid and the functional categorization of the pfam IDs can be found in Supplementary Data S2.