Rumen Protozoa Play a Significant Role in Fungal Predation and Plant Carbohydrate Breakdown

The rumen protozoa, alongside fungi, comprise the eukaryotic portion of the rumen microbiome. Rumen protozoa may account for up to 50% of biomass, yet their role in this ecosystem remains unclear. Early experiments inferred a role in carbohydrate and protein metabolism, but due to their close association with bacteria, definitively attributing these functions to the protozoa was challenging. The advent of ‘omic technologies has created opportunities to broaden our understanding of the rumen protozoa. This study aimed to utilise these methods to further our understanding of the role that protozoa play in the rumen in terms of their metabolic capacities, and in doing so, contribute valuable sequence data to reduce the chance of mis or under-representation of the rumen protozoa in meta’omic datasets. Rumen protozoa were isolated and purified using glucose-based sedimentation and differential centrifugation, extracted RNA was Poly(A) fraction enriched and DNase treated before use in a phage-based, cDNA metatranscriptomic library. Biochemical activity testing of the phage library showed 6 putatively positive plaques in response to carboxymethyl cellulose agar (indicative of cellulose activity), and no positive results for tributyrin (indicative of esterase/lipase activity) or egg yolk agar (indicative of proteolysis). Direct sequencing of the cDNA was also conducted using the Illumina HiSeq 2500. The metatranscriptome identified a wealth of carbohydrate-active enzymes which accounted for 8% of total reads. The most highly expressed carbohydrate-active enzymes were glycosyl hydrolases 5 and 11, polysaccharide lyases and deacetylases, xylanases and enzymes active against pectin, mannan and chitin; the latter likely used to digest rumen fungi which contain a chitin-rich cell membrane. Codon usage analysis of expressed genes also showed evidence of horizontal gene transfer, suggesting that many of these enzymes were acquired from the rumen bacteria in an evolutionary response to the carbohydrate-rich environment of the rumen. This study provides evidence of the significant contribution that the protozoa make to carbohydrate breakdown in the rumen, potentially using horizontally acquired genes, and highlights their predatory capacity

STRING 8—a global view on proteins and their functional interactions in 630 organisms

Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures. Version 8.0 of STRING covers about 2.5 million proteins from 630 organisms, providing the most comprehensive view on protein-protein interactions currently available. STRING can be reached at http://string-db.or

eggNOG v4.0: nested orthology inference across 3686 organisms

With the increasing availability of various ‘omics data, high-quality orthology assignment is crucial for evolutionary and functional genomics studies. We here present the fourth version of the eggNOG database (available at http://eggnog.embl.de) that derives nonsupervised orthologous groups (NOGs) from complete genomes, and then applies a comprehensive characterization and analysis pipeline to the resulting gene families. Compared with the previous version, we have more than tripled the underlying species set to cover 3686 organisms, keeping track with genome project completions while prioritizing the inclusion of high-quality genomes to minimize error propagation from incomplete proteome sets. Major technological advances include (i) a robust and scalable procedure for the identification and inclusion of high-quality genomes, (ii) provision of orthologous groups for 107 different taxonomic levels compared with 41 in eggNOGv3, (iii) identification and annotation of particularly closely related orthologous groups, facilitating analysis of related gene families, (iv) improvements of the clustering and functional annotation approach, (v) adoption of a revised tree building procedure based on the multiple alignments generated during the process and (vi) implementation of quality control procedures throughout the entire pipeline. As in previous versions, eggNOGv4 provides multiple sequence alignments and maximum-likelihood trees, as well as broad functional annotation. Users can access the complete database of orthologous groups via a web interface, as well as through bulk downloa

Consistent mutational paths predict eukaryotic thermostability

peer-reviewedBackground: Proteomes of thermophilic prokaryotes have been instrumental in structural biology and successfully exploited in biotechnology, however many proteins required for eukaryotic cell function are absent from bacteria or archaea. With Chaetomium thermophilum, Thielavia terrestris and Thielavia heterothallica three genome sequences of thermophilic eukaryotes have been published. Results: Studying the genomes and proteomes of these thermophilic fungi, we found common strategies of thermal adaptation across the different kingdoms of Life, including amino acid biases and a reduced genome size. A phylogenetics-guided comparison of thermophilic proteomes with those of other, mesophilic Sordariomycetes revealed consistent amino acid substitutions associated to thermophily that were also present in an independent lineage of thermophilic fungi. The most consistent pattern is the substitution of lysine by arginine, which we could find in almost all lineages but has not been extensively used in protein stability engineering. By exploiting mutational paths towards the thermophiles, we could predict particular amino acid residues in individual proteins that contribute to thermostability and validated some of them experimentally. By determining the three-dimensional structure of an exemplar protein from C. thermophilum (Arx1), we could also characterise the molecular consequences of some of these mutations. Conclusions: The comparative analysis of these three genomes not only enhances our understanding of the evolution of thermophily, but also provides new ways to engineer protein stability

eggNOG v4.0:Nested orthology inference across 3686 organisms

With the increasing availability of various 'omics data, high-quality orthology assignment is crucial for evolutionary and functional genomics studies. We here present the fourth version of the eggNOG database (available at http://eggnog.embl.de) that derives nonsupervised orthologous groups (NOGs) from complete genomes, and then applies a comprehensive characterization and analysis pipeline to the resulting gene families. Compared with the previous version, we have more than tripled the underlying species set to cover 3686 organisms, keeping track with genome project completions while prioritizing the inclusion of high-quality genomes to minimize error propagation from incomplete proteome sets. Major technological advances include (i) a robust and scalable procedure for the identification and inclusion of high-quality genomes, (ii) provision of orthologous groups for 107 different taxonomic levels compared with 41 in eggNOGv3, (iii) identification and annotation of particularly closely related orthologous groups, facilitating analysis of related gene families, (iv) improvements of the clustering and functional annotation approach, (v) adoption of a revised tree building procedure based on the multiple alignments generated during the process and (vi) implementation of quality control procedures throughout the entire pipeline. As in previous versions, eggNOGv4 provides multiple sequence alignments and maximum-likelihood trees, as well as broad functional annotation. Users can access the complete database of orthologous groups via a web interface, as well as through bulk download

Resistome analysis of global livestock and soil microbiomes

Publication history: Accepted - 24 May 2022: Published online - 7 July 2022Antimicrobial resistance (AMR) is a serious threat to public health globally; it is estimated that AMR bacteria caused 1.27 million deaths in 2019, and this is set to rise to 10 million deaths annually. Agricultural and soil environments act as antimicrobial resistance gene (ARG) reservoirs, operating as a link between different ecosystems and enabling the mixing and dissemination of resistance genes. Due to the close interactions between humans and agricultural environments, these AMR gene reservoirs are a major risk to both human and animal health. In this study, we aimed to identify the resistance gene reservoirs present in four microbiomes: poultry, ruminant, swine gastrointestinal (GI) tracts coupled with those from soil. This large study brings together every poultry, swine, ruminant, and soil shotgun metagenomic sequence available on the NCBI sequence read archive for the first time. We use the ResFinder database to identify acquired antimicrobial resistance genes in over 5,800 metagenomes. ARGs were diverse and widespread within the metagenomes, with 235, 101, 167, and 182 different resistance genes identified in the poultry, ruminant, swine, and soil microbiomes, respectively. The tetracycline resistance genes were the most widespread in the livestock GI microbiomes, including tet(W)_1, tet(Q)_1, tet(O)_1, and tet(44)_1. The tet(W)_1 resistance gene was found in 99% of livestock GI tract microbiomes, while tet(Q)_1 was identified in 93%, tet(O)_1 in 82%, and finally tet(44)_1 in 69%. Metatranscriptomic analysis confirmed these genes were “real” and expressed in one or more of the livestock GI tract microbiomes, with tet(40)_1 and tet(O)_1 expressed in all three livestock microbiomes. In soil, the most abundant ARG was the oleandomycin resistance gene, ole(B)_1. A total of 55 resistance genes were shared by the four microbiomes, with 11 ARGs actively expressed in two or more microbiomes. By using all available metagenomes we were able to mine a large number of samples and describe resistomes in 37 countries. This study provides a global insight into the diverse and abundant antimicrobial resistance gene reservoirs present in both livestock and soil microbiomes.This work was supported by the Northern Irish Department of Agriculture, Environment and Rural Affairs

Cultivation and sequencing of rumen microbiome members from the Hungate1000 Collection

Productivity of ruminant livestock depends on the rumen microbiota, which ferment indigestible plant polysaccharides into nutrients used for growth. Understanding the functions carried out by the rumen microbiota is important for reducing greenhouse gas production by ruminants and for developing biofuels from lignocellulose. We present 410 cultured bacteria and archaea, together with their reference genomes, representing every cultivated rumen-associated archaeal and bacterial family. We evaluate polysaccharide degradation, short-chain fatty acid production and methanogenesis pathways, and assign specific taxa to functions. A total of 336 organisms were present in available rumen metagenomic data sets, and 134 were present in human gut microbiome data sets. Comparison with the human microbiome revealed rumen-specific enrichment for genes encoding de novo synthesis of vitamin B12, ongoing evolution by gene loss and potential vertical inheritance of the rumen microbiome based on underrepresentation of markers of environmental stress. We estimate that our Hungate genome resource represents ?75% of the genus-level bacterial and archaeal taxa present in the rumen.publishersversionPeer reviewe

Addressing global ruminant agricultural challenges through understanding the rumen microbiome::Past, present and future

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges