Search NASA⌕ Search

SEARCH · Search NASA

Results for “Genome stability”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Radiation-induced genomic instability

Quantitative assessment of the heritable somatic effects of ionizing radiation exposures has relied upon the assumption that radiation-induced lesions were 'fixed' in the DNA prior to the first postirradiation mitosis. Lesion conversion was thought to occur during the initial round of DNA replication or as a consequence of error-prone enzymatic processing of lesions. The standard experimental protocols for the assessment of a variety of radiation-induced endpoints (cell death, specific locus mutations, neoplastic transformation and chromosome aberrations) evaluate these various endpoints at a single snapshot in time. In contrast with the aforementioned approaches, some studies have specifically assessed radiation effects as a function of time following exposure. Evidence has accumulated in support of the hypothesis that radiation exposure induces a persistent destabilization of the genome. This instability has been observed as a delayed expression of lethal mutations, as an enhanced rate of accumulation of non-lethal heritable alterations, and as a progressive intraclonal chromosomal heterogeneity. The genetic controls and biochemical mechanisms underlying radiation-induced genomic instability have not yet been delineated. The aim is to integrate the accumulated evidence that suggests that radiation exposure has a persistent effect on the stability of the mammalian genome.

NASA Discipline Radiation Health↗
DOE OSTI2020

The fate of 35S rRNA genes in the allotetraploid grass Brachypodium hybridum

Nucleolar dominance (ND) consists of the reversible silencing of 35S/45S rDNA loci inherited from one of the ancestors of an allopolyploid. The molecular mechanisms by which one ancestral rDNA set is selected for silencing remain unclear. We applied a combination of molecular (Southern blot hybridization and reverse-transcription cleaved amplified polymorphic sequence analysis), genomic (analysis of variants) and cytogenetic (fluorescence in situ hybridization) approaches to study the structure, expression and epigenetic landscape of 35S rDNA in an allotetraploid grass that exhibits ND, Brachypodium hybridum (genome composition DDSS), and its putative progenitors, Brachypodium distachyon (DD) and Brachypodium stacei (SS). In progenitor genomes, B. stacei showed a higher intragenomic heterogeneity of rDNA compared with B. distachyon. In all studied accessions of B. hybridum, there was a reduction in the copy number of S homoeologues, which was accompanied by their inactive transcriptional status. The involvement of DNA methylation in CG and CHG contexts in the silencing of the S-genome rDNA loci was revealed. In the B. hybridum allotetraploid, ND is stabilized towards the D-genome units, irrespective of the polyphyletic origin of the species, and does not seem to be influenced by homoeologous 35S rDNA ratios and developmental stage.

35S rDNA evolution↗
DOE OSTI2021

A Genomic Catalog of Stress Response Genes in Anaerobic Fungi for Applications in Bioproduction

Anaerobic fungi are a potential biotechnology platform to produce biomass-degrading enzymes. Unlike model fungi such as yeasts, stress responses that are relevant during bioprocessing have not yet been established for anaerobic fungi. In this work, we characterize both the heat shock and unfolded protein responses of four strains of anaerobic fungi ( Anaeromyces robustus, Caecomyces churrovis, Neocallimastix californiae , and Piromyces finnis ). The inositol-requiring 1 (Ire1) stress sensor, which typically initiates the fungal UPR, was conserved in all four genomes. However, these genomes also encode putative transmembrane kinases with catalytic domains that are similar to the metazoan stress-sensing enzyme PKR-like endoplasmic reticulum kinase (PERK), although whether they function in the UPR of anaerobic fungi remains unclear. Furthermore, we characterized the global transcriptional responses of Anaeromyces robustus and Neocallimastix californiae to a transient heat shock. Both fungi exhibited the hallmarks of ER stress, including upregulation of genes with functions in protein folding, ER-associated degradation, and intracellular protein trafficking. Relative to other fungi, the genomes of Neocallimastigomycetes contained the greatest gene percentage of HSP20 and HSP70 chaperones, which may serve to stabilize their asparagine-rich genomes. Taken together, these results delineate the unique stress response of anaerobic fungi, which is an important step toward their development as a biotechnology platform to produce enzymes and valuable biomolecules.

Swift, Candice L.↗
NASA NTRS2011

Stress-Driven Selection of Novel Phenotypes

A process has been developed that can confer novel properties, such as metal resistance, to a host bacterium. This same process can also be used to produce RNAs and peptides that have novel properties, such as the ability to bind particular compounds. It is inherent in the method that the peptide or RNA will behave as expected in the target organism. Plasmid-born mini-gene libraries coding for either a population of combinatorial peptides or stable, artificial RNAs carrying random inserts are produced. These libraries, which have no bias towards any biological function, are used to transform the organism of interest and to serve as an initial source of genetic variation for stress-driven evolution. The transformed bacteria are propagated under selective pressure in order to obtain variants with the desired properties. The process is highly distinct from in vitro methods because the variants are selected in the context of the cell while it is experiencing stress. Hence, the selected peptide or RNA will, by definition, work as expected in the target cell as the cell adapts to its presence during the selection process. Once the novel gene, which produces the sought phenotype, is obtained, it can be transferred to the main genome to increase the genetic stability in the organism. Alternatively, the cell line can be used to produce novel RNAs or peptides with selectable properties in large quantity for separate purposes. The system allows for easy, large-scale purification of the RNAs or peptide products. The process has been reduced to practice by imposing sub-inhibitory concentrations of NiCl2 on cells of the bacterium Escherichia coli that were transformed separately with the peptide library and RNA library. The evolved resistant clones were isolated, and sequences of the selected mini-gene variants were established. Clones resistant to NiCl2 were found to carry identical plasmid variants with a functional mini-gene that specifically conferred significant nickel tolerance on the host cells. Sequencing of the selected mini-gene revealed a propensity of the encoded peptide to bind transient metal ions. Expression of the mini-gene markedly improved growth parameters of the evolved clones at sub-inhibitory concentrations of NiCl2 while being slightly detrimental in the absence of stress. Similar results have been obtained with the RNA libraries. Overall, the results demonstrate a very natural outcome of the selection experiments in which the mini-genes were expected to be either successfully integrated into bacterial genetic networks, or rejected depending upon their effect on host fitness. This described approach can be useful as a laboratory model to study the dynamics of bacterial adaptive evolution on the molecular level. It can also provide a strategy for screening expressed DNA libraries in search of novel genes with desirable properties.

Fox, George E.↗
DOE OSTI2023

Combinatorial gene inactivation of aldehyde dehydrogenases mitigates aldehyde oxidation catalyzed by E. coli resting cells

Aldehydes are attractive chemical targets both as end products in the flavors and fragrances industry and as synthetic intermediates due to their propensity for C–C bond formation. Here, in this study, we identify and address unexpected oxidation of a model collection of aromatic aldehydes, including many that originate from biomass degradation. When diverse aldehydes are supplemented to E. coli cells grown under aerobic conditions, as expected they are either reduced by the wild-type MG1655 strain or stabilized by a strain engineered for reduced aromatic aldehyde reduction (the E. coli RARE strain). Surprisingly, when these same aldehydes are supplemented to resting cell preparations of either E. coli strain, under many conditions we observe substantial oxidation. By performing combinatorial inactivation of six candidate aldehyde dehydrogenase genes in the E. coli genome using multiplexed automatable genome engineering (MAGE), we demonstrate that this oxidation can be substantially slowed, with greater than 50% retention of 6 out of 8 aldehydes when assayed 4 h after their addition. Given that our newly engineered strain exhibits reduced oxidation and reduction of aromatic aldehydes, we dubbed it the E. coli ROAR strain. We applied the new strain to resting cell biocatalysis for two kinds of reactions – the reduction of 2-furoic acid to furfural and the condensation of 3-hydroxybenzaldehyde and glycine to form a non-standard β-hydroxy-α-amino acid. In each case, we observed substantial improvements in product titer 20 h after reaction initiation (9-fold and 10-fold, respectively). Moving forward, the use of this strain to generate resting cells should allow aldehyde product isolation, further enzymatic conversion, or chemical reactivity under cellular contexts that better accommodate aldehyde toxicity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Multi-omics profiling of the cold tolerant Monoraphidium minutum 26B-AM in response to abiotic stress

Microalgae that are of interest for biofuel production must be able to tolerate environmental changes that occur in outdoor cultivation systems. While algal cultures may experience daily temperature fluctuations and seasonal environmental changes, the underlying mechanisms that control and regulate physiological responses and adaptation to environmental pressures are largely unknown. Systems-level characterization enabled by functional genomics can help identify biochemical pathways that promote stability and productivity of algae in various environmental conditions. Monoraphidium minutum 26B-AM, a freshwater green microalga, was identified as a top performer in biomass production in winter season screens. We sequenced the genome of M. minutum 26B-AM and applied our multi-omics pipeline to profile this high potential strain under high salt and cold temperature perturbations. Through comparative analysis, including other green algae in the class Chlorophyceae, we identified gene families unique to the genus Monoraphidium, including a desaturase that has been linked to cold tolerance in plants. We observed that osmolytes, such as trehalose, proline and betaine, accumulate under salt stress, coinciding with upregulation of genes involved in biosynthesis of these metabolites. From the genome annotation, we reconstructed a metabolic model to provide a detailed map of the metabolic pathways and can be used to simulate growth and reaction fluxes. This multi-omics analysis provides a foundation to explore algal strain potential for biofuel applications, guides strain engineering, and expands our understanding of metabolic and regulatory mechanisms of algae in applied systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Incorporation of Viral RNA Elements for Increased mRNA Stability Within Mammalian Cells to Prolong Nanobody Production

The development of protein-based pharmaceuticals has taken place for years, often finding roadblocks relevant to in vitro biomanufacturing, drug delivery, and drug half-life. Industrial and national laboratory focus has now shifted to messenger RNA (mRNA)-based pharmaceuticals, as mRNA can be manufactured and delivered more easily, and can lead to direct intracellular protein production. Artificial stabilization of the naturally transient mRNA is needed to prolong protein production by recipient cells. Incorporation of viral genome elements known as exoribonuclease-resistant RNA (xrRNA) should allow for this stabilization. To evaluate the effects of xrRNA on mRNA stability, fluorescent proteins are encoded within the mRNA of interest for easier detection through immunocytochemistry, microplate reader screening, and high-content confocal microscopy. As seen with the Pfizer and Moderna COVID 19 vaccines, mRNA-based medical countermeasures can be powerful tools in service of public health and biodefense, and our work to improve mRNA stability should further enhance this promising new approach to medicine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew↗
DOE OSTI2024

Structure of an RNA G-quadruplex from the West Nile virus genome

Potential G-quadruplex sites have been identified in the genomes of DNA and RNA viruses and proposed as regulatory elements. The genus Orthoflavivirus contains arthropod-transmitted, positive-sense, single-stranded RNA viruses that cause significant human disease globally. Computational studies have identified multiple potential G-quadruplex sites that are conserved across members of this genus. Subsequent biophysical studies established that some G-quadruplexes predicted in Zika and tickborne encephalitis virus genomes can form and known quadruplex binders reduced viral yields from cells infected with these viruses. The susceptibility of RNA to degradation and the variability of loop regions have made structure determination challenging. Despite these difficulties, we report a high-resolution structure of the NS5-B quadruplex from the West Nile virus genome. Analysis reveals two stacked tetrads that are further stabilized by a stacked triad and transient noncanonical base pairing. This structure expands the landscape of solved RNA quadruplex structures and demonstrates the diversity and complexity of biological quadruplexes. We anticipate that the availability of this structure will assist in solving further viral RNA quadruplexes and provides a model for a conserved antiviral target in Orthoflavivirus genomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream

Although river ecosystems constitute a small fraction of Earth’s total area, they are critical modulators of microbially and virally orchestrated global biogeochemical cycles. However, most studies either use data that is not spatially resolved or is collected at timepoints that do not reflect the short life cycles of microorganisms. To address this gap, we assessed how viral and microbial communities change over a 48-hour period by sampling surface water and pore water compartments of the wastewater-impacted River Erpe in Germany. We sampled every 3 hours resulting in 32 samples for which we obtained metagenomes along with geochemical and metabolite measurements. From our metagenomes, we identified 6,500 viral and 1,033 microbial metagenome assembled genomes (MAGs) and found distinct community membership and abundance associated with each river compartment (e.g., Competibacteraceae in surfacewater and Sulfurimonadaceae in pore water). We show that 17% of our viral MAGs clustered to viruses from other ecosystems like wastewater treatment plants and rivers. Our results also indicated that 70% of the viral community was persistent in surface waters, whereas only 13% were persistent in the pore waters taken from the hyporheic zone. Finally, we predicted linkages between 73 viral genomes and 38 microbial genomes. These putatively linked hosts included members of the Competibacteraceae, which we suggest are potential contributors to river carbon and nitrogen cycling via denitrification and nitrogen fixation. Together, these findings demonstrate that members of the surface water microbiome from this urban river are stable over multiple diurnal cycles. These temporal insights raise important considerations for ecosystem models attempting to constrain dynamics of river biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Eight Metagenome-Assembled Genomes Provide Evidence for Microbial Adaptation in 20,000- to 1,000,000-Year-Old Siberian Permafrost

Permafrost microbes may be metabolically active in microscopic layers of liquid brines, even in ancient soil. Metagenomics can help discern whether permafrost microbes show adaptations to this environment. Thirty-three metagenome-assembled genomes (MAGs) were obtained from six depths (3.5 m to 20 m) of freshly cored permafrost from the Siberian Kolyma-Indigirka Lowland region. These soils have been continuously frozen for ~20,000 to 1,000,000 years. Eight of these MAGs were ≥80% complete with <10% contamination and were taxonomically identified as Aminicenantes, Atribacteria, Chloroflexi, and Actinobacteria within bacteria and Thermoprofundales within archaea. MAGs from these taxa have been obtained previously from nonpermafrost environments and have been suggested to show adaptations to long-term energy starvation, but they have never been explored in ancient permafrost. The permafrost MAGs had greater proportions in the Clusters of Orthologous Groups (COGs) categories of energy production and conversion and carbohydrate transport and metabolism than did their nonpermafrost counterparts. They also contained genes for trehalose synthesis, thymine metabolism, mevalonate biosynthesis, and cellulose degradation, which were less prevalent in nonpermafrost genomes. Furthermore, many of these genes are involved in membrane stabilization and osmotic stress responses, consistent with adaptation to the anoxic, high-ionic-strength, cold environments of permafrost brine films. Our results suggest that this ancient permafrost contains DNA of high enough quality to assemble MAGs from microorganisms with adaptations to survive long-term freezing in this extreme environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Veridical data science

Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data science life cycle. The PCS workflow uses predictability as a reality check and considers the importance of computation in data collection/storage and algorithm design. It augments predictability and computability with an overarching stability principle. Stability expands on statistical uncertainty considerations to assess how human judgment calls impact data results through data and model/algorithm perturbations. As part of the PCS workflow, we develop PCS inference procedures, namely PCS perturbation intervals and PCS hypothesis testing, to investigate the stability of data results relative to problem formulation, data cleaning, modeling decisions, and interpretations. We illustrate PCS inference through neuroscience and genomics projects of our own and others. Moreover, we demonstrate its favorable performance over existing methods in terms of receiver operating characteristic (ROC) curves in high-dimensional, sparse linear model simulations, including a wide range of misspecified models. Finally, we propose PCS documentation based on R Markdown or Jupyter Notebook, with publicly available, reproducible codes and narratives to back up human choices made throughout an analysis. The PCS workflow and documentation are demonstrated in a genomics case study available on Zenodo.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Genomic factors shaping codon usage across the Saccharomycotina subphylum

Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. It has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces. We characterized codon usage across 1,154 strains from 1,051 species from the fungal subphylum Saccharomycotina to gain insight into the biases, molecular mechanisms, evolution, and genomic features contributing to codon usage patterns. We found a general preference for A/T-ending codons and correlations between codon usage bias, GC content, and tRNA-ome size. Codon usage bias is distinct between the 12 orders to such a degree that yeasts can be classified with an accuracy >90% using a machine learning algorithm. We also characterized the degree to which codon usage bias is impacted by translational selection. We found it was influenced by a combination of features, including the number of coding sequences, BUSCO count, and genome length. Our analysis also revealed an extreme bias in codon usage in the Saccharomycodales associated with a lack of predicted arginine tRNAs that decode CGN codons, leaving only the AGN codons to encode arginine. Analysis of Saccharomycodales gene expression, tRNA sequences, and codon evolution suggests that avoidance of the CGN codons is associated with a decline in arginine tRNA function. Consistent with previous findings, codon usage bias within the Saccharomycotina is shaped by genomic features and GC bias. However, we find cases of extreme codon usage preference and avoidance along yeast lineages, suggesting additional forces may be shaping the evolution of specific codons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

GENTANGLE: integrated computational design of gene entanglements

The design of two overlapping genes in a microbial genome is an emerging technique for adding more reliable control mechanisms in engineered organisms for increased stability. The design of functional overlapping gene pairs is a challenging procedure, and computational design tools are used to improve the efficiency to deploy successful designs in genetically engineered systems. GENTANGLE (Gene Tuples ArraNGed in overLapping Elements) is a high-performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome. This new software package can be used to design and test gene entanglements for microbial engineering projects using arbitrary sets of user-specified gene pairs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Morphological Characters Can Strongly Influence Early Animal Relationships Inferred from Phylogenomic Data Sets

There are considerable phylogenetic incongruencies between morphological and phylogenomic data for the deep evolution of animals. This has contributed to a heated debate over the earliest-branching lineage of the animal kingdom: the sister to all other Metazoa (SOM). Here, we use published phylogenomic data sets ($\sim $45,000–400,000 characters in size with $\sim $15–100 taxa) that focus on early metazoan phylogeny to evaluate the impact of incorporating morphological data sets ($\sim $15–275 characters). We additionally use small exemplar data sets to quantify how increased taxon sampling can help stabilize phylogenetic inferences. We apply a plethora of common methods, that is, likelihood models and their “equivalent” under parsimony: character weighting schemes. Our results are at odds with the typical view of phylogenomics, that is, that genomic-scale data sets will swamp out inferences from morphological data. Instead, weighting morphological data 2–10$\times $ in both likelihood and parsimony can in some cases “flip” which phylum is inferred to be the SOM. This typically results in the molecular hypothesis of Ctenophora as the SOM flipping to Porifera (or occasionally Placozoa). However, greater taxon sampling improves phylogenetic stability, with some of the larger molecular data sets ($>$200,000 characters and up to $\sim $100 taxa) showing node stability even with $\geqq100\times $ upweighting of morphological data. Accordingly, our analyses have three strong messages. 1) The assumption that genomic data will automatically “swamp out” morphological data is not always true for the SOM question. Morphological data have a strong influence in our analyses of combined data sets, even when outnumbered thousands of times by molecular data. Morphology therefore should not be counted out a priori. 2) We here quantify for the first time how the stability of the SOM node improves for several genomic data sets when the taxon sampling is increased. 3) The patterns of “flipping points” (i.e., the weighting of morphological data it takes to change the inferred SOM) carry information about the phylogenetic stability of matrices. The weighting space is an innovative way to assess comparability of data sets that could be developed into a new sensitivity analysis tool.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Genomic and functional analyses of fungal and bacterial consortia that enable lignocellulose breakdown in goat gut microbiomes

Abstract The herbivore digestive tract is home to a complex community of anaerobic microbes that work together to break down lignocellulose. These microbiota are an untapped resource of strains, pathways and enzymes that could be applied to convert plant waste into sugar substrates for green biotechnology. We carried out more than 400 parallel enrichment experiments from goat faeces to determine how substrate and antibiotic selection influence membership, activity, stability and chemical productivity of herbivore gut communities. We assembled 719 high-quality metagenome-assembled genomes (MAGs) that are unique at the species level. More than 90% of these MAGs are from previously unidentified herbivore gut microorganisms. Microbial consortia dominated by anaerobic fungi outperformed bacterially dominated consortia in terms of both methane production and extent of cellulose degradation, which indicates that fungi have an important role in methane release. Metabolic pathway reconstructions from MAGs of 737 bacteria, archaea and fungi suggest that cross-domain partnerships between fungi and methanogens enabled production of acetate, formate and methane, whereas bacterially dominated consortia mainly produced short-chain fatty acids, including propionate and butyrate. Analyses of carbohydrate-active enzyme domains present in each anaerobic consortium suggest that anaerobic bacteria and fungi employ mostly complementary hydrolytic strategies. The division of labour among herbivore anaerobes to degrade plant biomass could be harnessed for industrial bioprocessing.

59 BASIC BIOLOGICAL SCIENCES↗