MetaPathways v2.5: quantitative functional, taxonomic and usability improvements

Deficient butyrate metabolism in the intestinal microbiome is a potential risk factor for recurrent kidney stone disease

Intestinal microbiome dysbiosis is a known risk factor for recurrent kidney stone disease (KSD) with prior data suggesting a role for dysfunctional metabolic pathways other than those directly utilizing oxalate. To identify alternative mechanisms, the current study analyzed differences in the metabolic potential of intestinal microbiomes of patients (n = 17) and live-in controls (n = 17) and determined their relevance to increased risk for KSD using shotgun metagenomic sequencing. We found no differences in the abundance of genes associated with known oxalate degradation pathways, supporting the notion that dysfunction in other metabolic pathways plays a role in KSD. Further analysis showed decreased abundance of key enzymes involved in butyrate biosynthesis in patient intestinal microbiomes. Furthermore, de novo construction of microbial genomes showed that the majority of genes significantly enriched in non-stone formers are affiliated with Faecalibacterium prausnitzii, a major butyrate producer. Specifically pertaining to butyrate metabolism, the majority of abundant genes mapped back to F. prausnitzii, Alistipes spp., and Akkermansia muciniphila. No differences were observed in ascorbate or glyoxylate metabolic pathways. Collectively, these data suggest that impaired bacterial-associated butyrate metabolism may be an oxalate-independent mechanism that contributes to an increased risk for recurrent KSD. This indicates that the role of the intestinal microbiome in recurrent KSD is multi-factorial, which is representative of the highly intertwined metabolic nature of this complex environment. Future bacteria-based treatments must not be restricted to targeting only oxalate metabolism.

Multi-label classification with XGBoost for metabolic pathway prediction

BACKGROUND

Metabolic pathway prediction is one possible approach to address the problem in system biology of reconstructing an organism's metabolic network from its genome sequence. Recently there have been developments in machine learning-based pathway prediction methods that conclude that machine learning-based approaches are similar in performance to the most used method, PathoLogic which is a rule-based method. One issue is that previous studies evaluated PathoLogic without taxonomic pruning which decreases its performance.

RESULTS

In this study, we update the evaluation results from previous studies to demonstrate that PathoLogic with taxonomic pruning outperforms previous machine learning-based approaches and that further improvements in performance need to be made for them to be competitive. Furthermore, we introduce mlXGPR, a XGBoost-based metabolic pathway prediction method based on the multi-label classification pathway prediction framework introduced from mlLGPR. We also improve on this multi-label framework by utilizing correlations between labels using classifier chains. We propose a ranking method that determines the order of the chain so that lower performing classifiers are placed later in the chain to utilize the correlations between labels more. We evaluate mlXGPR with and without classifier chains on single-organism and multi-organism benchmarks. Our results indicate that mlXGPR outperform other previous pathway prediction methods including PathoLogic with taxonomic pruning in terms of hamming loss, precision and F1 score on single organism benchmarks.

CONCLUSIONS

The results from our study indicate that the performance of machine learning-based pathway prediction methods can be substantially improved and can even outperform PathoLogic with taxonomic pruning.

A compendium of bacterial and archaeal single-cell amplified genomes from oxygen deficient marine waters

Oxygen-deficient marine waters referred to as oxygen minimum zones (OMZs) or anoxic marine zones (AMZs) are common oceanographic features. They host both cosmopolitan and endemic microorganisms adapted to low oxygen conditions. Microbial metabolic interactions within OMZs and AMZs drive coupled biogeochemical cycles resulting in nitrogen loss and climate active trace gas production and consumption. Global warming is causing oxygen-deficient waters to expand and intensify. Therefore, studies focused on microbial communities inhabiting oxygen-deficient regions are necessary to both monitor and model the impacts of climate change on marine ecosystem functions and services. Here we present a compendium of 5,129 single-cell amplified genomes (SAGs) from marine environments encompassing representative OMZ and AMZ geochemical profiles. Of these, 3,570 SAGs have been sequenced to different levels of completion, providing a strain-resolved perspective on the genomic content and potential metabolic interactions within OMZ and AMZ microbiomes. Hierarchical clustering confirmed that samples from similar oxygen concentrations and geographic regions also had analogous taxonomic compositions, providing a coherent framework for comparative community analysis.

A Guide to Gene-Centric Analysis Using TreeSAPP

Gene-centric analysis is commonly used to chart the structure, function, and activity of microbial communities in natural and engineered environments. A common approach is to create custom ad hoc reference marker gene sets, but these come with the typical disadvantages of inaccuracy and limited utility beyond assigning query sequences taxonomic labels. The Tree-based Sensitive and Accurate Phylogenetic Profiler (TreeSAPP) software package standardizes analysis of phylogenetic and functional marker genes and improves predictive performance using a classification algorithm that leverages information-rich reference packages consisting of a multiple sequence alignment, a profile hidden Markov model, taxonomic lineage information, and a phylogenetic tree. Here, we provide a set of protocols that link the various analysis modules in TreeSAPP into a coherent process that both informs and directs the user experience. This workflow, initiated from a collection of candidate reference sequences, progresses through construction and refinement of a reference package to marker identification and normalized relative abundance calculations for homologous sequences in metagenomic and metatranscriptomic datasets. The alpha subunit of methyl-coenzyme M reductase (McrA) involved in biological methane cycling is presented as a use case given its dual role as a phylogenetic and functional marker gene driving an ecologically relevant process. These protocols fill several gaps in prior TreeSAPP documentation and provide best practices for reference package construction and refinement, including manual curation steps from trusted sources in support of reproducible gene-centric analysis. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating reference packages Support Protocol 1: Installing TreeSAPP Support Protocol 2: Annotating traits within a phylogenetic context Basic Protocol 2: Updating reference packages Basic Protocol 3: Calculating relative abundance of genes in metagenomic and metatranscriptomic datasets.

Metagenome-Assembled Genome of a Putative Chemoheterotroph from Volcanic Terrain in Hawaii

Here, we present the draft genome for a new putative species, Gaiellasilicea maunaloa, most closely related to Gaiella occulta, within the phylum Actinobacteria. This group contains Gram-negative, aerobic mesophilic species. This metagenome-assembled genome (MAG) contributes to knowledge of life in volcanic environments and may inform investigations of life beyond Earth.

Basaltic Lava Tube Hosts a Putative Novel Genus in the Family Solirubrobacteraceae

We report the draft genome sequence of a putative new genus and species, Siliceabacter maunaloa, in the family Solirubrobacteraceae. The members of this family of Actinobacteria are generally Gram positive and mesophilic. Found within a Hawaiian lava tube, this microbe illuminates the types of prokaryotes inhabiting secondary minerals in subsurface basaltic environments.

Survival strategies of an anoxic microbial ecosystem in Lake Untersee, a potential analog for Enceladus

Lake Untersee located in Eastern Antarctica, is a perennially ice-covered lake. At the bottom of its southern basin lies 20 m of anoxic, methane rich, stratified water, making it a good analog for Enceladus, a moon of Saturn. Here we present the first metagenomic study of this basin and detail the community composition and functional potential of the microbial communities at 92 m, 99 m depths and within the anoxic sediment. A diverse and well-populated microbial community was found, presenting the potential for Enceladus to have a diverse and abundant community. We also explored methanogenesis, sulfur metabolism, and nitrogen metabolism, given the potential presence of these compounds on Enceladus. We found an abundance of these pathways offering a variety of metabolic strategies. Additionally, the extreme conditions of the anoxic basin make it optimal for testing spaceflight technology and life detection methods for future Enceladus exploration.

Functional redundancy imparts process stability to acidic Fe(II)-oxidizing microbial reactors

In previous work, lab-scale reactors designed to study microbial Fe(II) oxidation rates at low pH were found to have stable rates under a wide range of pH and Fe(II) concentrations. Since the stirred reactor environment eliminates many of the temporal and spatial variations that promote high diversity among microbial populations in nature, we were surprised that the reactors supported multiple taxa presumed to be autotrophic Fe(II) oxidizers based on their phylogeny. Metagenomic analyses of the reactor communities revealed differences in the metabolic potential of these taxa with respect to Fe(II) oxidation and carbon fixation pathways, acquisition of potentially growth-limiting substrates and the ability to form biofilms. Our findings support the hypothesis that the long-term co-existence of multiple autotrophic Fe(II)-oxidizing populations in the reactors are due to distinct metabolic potential that supports differential growth in response to limiting resources such as nitrogen, phosphorus and oxygen. Our data also highlight the role of biofilms in creating spatially distinct geochemical niches that enable the co-existence of multiple taxa that occupy the same apparent metabolic niche when the system is viewed in bulk. The distribution of key metabolic functions across different co-existing taxa supported functional redundancy and imparted process stability to these reactors.

Metabolic pathway inference using multi-label classification with rich pathway features

Metabolic inference from genomic sequence information is a necessary step in determining the capacity of cells to make a living in the world at different levels of biological organization. A common method for determining the metabolic potential encoded in genomes is to map conceptually translated open reading frames onto a database containing known product descriptions. Such gene-centric methods are limited in their capacity to predict pathway presence or absence and do not support standardized rule sets for automated and reproducible research. Pathway-centric methods based on defined rule sets or machine learning algorithms provide an adjunct or alternative inference method that supports hypothesis generation and testing of metabolic relationships within and between cells. Here, we present mlLGPR, multi-label based on logistic regression for pathway prediction, a software package that uses supervised multi-label classification and rich pathway features to infer metabolic networks in organismal and multi-organismal datasets. We evaluated mlLGPR performance using a corpora of 12 experimental datasets manifesting diverse multi-label properties, including manually curated organismal genomes, synthetic microbial communities and low complexity microbial communities. Resulting performance metrics equaled or exceeded previous reports for organismal genomes and identify specific challenges associated with features engineering and training data for community-level metabolic inference.

Medium-Chain Fatty Acid Synthesis by "Candidatus Weimeria bifida" gen. nov., sp. nov., and "Candidatus Pseudoramibacter fermentans" sp. nov

Chain elongation by medium-chain fatty acid (MCFA)-producing microbiomes offers an opportunity to produce valuable chemicals from organic streams that would otherwise be considered waste. However, the physiology and energetics of chain elongation are only beginning to be studied, and many of these organisms remain uncultured. We analyzed MCFA production by two uncultured organisms that were identified as the main MCFA producers in a microbial community enriched from an anaerobic digester; this characterization, which is based on meta-multi-omic analysis, complements the knowledge that has been acquired from pure-culture studies. The analysis revealed previously unreported features of the metabolism of MCFA-producing organisms.

Chain elongation is emerging as a bioprocess to produce valuable medium-chain fatty acids (MCFA; 6 to 8 carbons in length) from organic waste streams by harnessing the metabolism of anaerobic microbiomes. Although our understanding of chain elongation physiology is still evolving, the reverse β-oxidation pathway has been identified as a key metabolic function to elongate the intermediate products of fermentation to MCFA. Here, we describe two uncultured chain-elongating microorganisms that were enriched in an anaerobic microbiome transforming the residues from a lignocellulosic biorefining process. Based on a multi-omic analysis, we describe “Candidatus Weimeria bifida” gen. nov., sp. nov., and “Candidatus Pseudoramibacter fermentans” sp. nov., both predicted to produce MCFA but using different substrates. The analysis of a time series metatranscriptomic data set suggests that “Ca. Weimeria bifida” is an effective xylose utilizer since both the pentose phosphate pathway and the bifid shunt are active. Furthermore, the metatranscriptomic data suggest that energy conservation during MCFA production in this organism is essential and occurs via the creation of an ion motive force using both the RNF complex and an energy-conserving hydrogenase. For “Ca. Pseudoramibacter fermentans,” predicted to produce MCFA from lactate, the metatranscriptomic analysis reveals the activity of an electron-confurcating lactate dehydrogenase, energy conservation via the RNF complex, H₂ production for redox balance, and glycerol utilization. A thermodynamic analysis also suggests the possibility of glycerol being a substrate for MCFA production by “Ca. Pseudoramibacter fermentans.” In total, this work reveals unknown characteristics of MCFA production in two novel organisms.

IMPORTANCE Chain elongation by medium-chain fatty acid (MCFA)-producing microbiomes offers an opportunity to produce valuable chemicals from organic streams that would otherwise be considered waste. However, the physiology and energetics of chain elongation are only beginning to be studied, and many of these organisms remain uncultured. We analyzed MCFA production by two uncultured organisms that were identified as the main MCFA producers in a microbial community enriched from an anaerobic digester; this characterization, which is based on meta-multi-omic analysis, complements the knowledge that has been acquired from pure-culture studies. The analysis revealed previously unreported features of the metabolism of MCFA-producing organisms.

Metaphenomic Responses of a Native Prairie Soil Microbiome to Moisture Perturbations

Climate change is causing shifts in precipitation patterns in the central grasslands of the United States, with largely unknown consequences on the collective physiological responses of the soil microbial community, i.e., the metaphenome. Here, we used an untargeted omics approach to determine the soil microbial community's metaphenomic response to soil moisture and to define specific metabolic signatures of the response. Specifically, we aimed to develop the technical approaches and metabolic mapping framework necessary for future systematic ecological studies. We collected soil from three locations at the Konza Long-Term Ecological Research (LTER) field station in Kansas, and the soils were incubated for 15 days under dry or wet conditions and compared to field-moist controls. The microbiome response to wetting or drying was determined by 16S rRNA amplicon sequencing, metatranscriptomics, and metabolomics, and the resulting shifts in taxa, gene expression, and metabolites were assessed. Soil drying resulted in significant shifts in both the composition and function of the soil microbiome. In contrast, there were few changes following wetting. The combined metabolic and metatranscriptomic data were used to generate reaction networks to determine the metaphenomic response to soil moisture transitions. Site location was a strong determinant of the response of the soil microbiome to moisture perturbations. However, some specific metabolic pathways changed consistently across sites, including an increase in pathways and metabolites for production of sugars and other osmolytes as a response to drying. Using this approach, we demonstrate that despite the high complexity of the soil habitat, it is possible to generate insight into the effect of environmental change on the soil microbiome and its physiology and functions, thus laying the groundwork for future, targeted studies.IMPORTANCE Climate change is predicted to result in increased drought extent and intensity in the highly productive, former tallgrass prairie region of the continental United States. These soils store large reserves of carbon. The decrease in soil moisture due to drought has largely unknown consequences on soil carbon cycling and other key biogeochemical cycles carried out by soil microbiomes. In this study, we found that soil drying had a significant impact on the structure and function of soil microbial communities, including shifts in expression of specific metabolic pathways, such as those leading toward production of osmoprotectant compounds. This study demonstrates the application of an untargeted multi-omics approach to decipher details of the soil microbial community's metaphenotypic response to environmental perturbations and should be applicable to studies of other complex microbial systems as well.

High-Throughput Recovery and Characterization of Metagenome-Derived Glycoside Hydrolase-Containing Clones as a Resource for Biocatalyst Development

The generation of new biocatalysts for plant biomass degradation and glycan synthesis has typically relied on the characterization and investigation of one or a few enzymes at a time. By coupling functional metagenomic screening and high-throughput functional characterization, we can progress beyond the current scale of catalyst discovery and provide rapid annotation of catalyst function. By functionally screening environmental DNA from many diverse sources, we have generated a suite of active glycoside hydrolase-containing clones and demonstrated their reaction parameters. We then demonstrated the utility of this collection through the generation of a new catalyst for the formation of azido-modified glycans. Further interrogation of this collection of clones will expand our biocatalytic toolbox, with potential application to biomass deconstruction and synthesis of glycans.

Functional metagenomics is a powerful tool for both the discovery and development of biocatalysts. This study presents the high-throughput functional screening of 22 large-insert fosmid libraries containing over 300,000 clones sourced from natural and engineered ecosystems, characterization of active clones, and a demonstration of the utility of recovered genes or gene cassettes in the development of novel biocatalysts. Screening was performed in a 384-well-plate format with the fluorogenic substrate 4-methylumbelliferyl cellobioside, which releases a fluorescent molecule when cleaved by β-glucosidases or cellulases. The resulting set of 164 active clones was subsequently interrogated for substrate preference, reaction mechanism, thermal stability, and optimal pH. The environmental DNA harbored within each active clone was sequenced, and functional annotation revealed a cornucopia of carbohydrate-degrading enzymes. Evaluation of genomic-context information revealed both synteny and polymer-targeting loci within a number of sequenced clones. The utility of these fosmids was then demonstrated by identifying clones encoding activity on an unnatural glycoside (4-methylumbelliferyl 6-azido-6-deoxy-β-d-galactoside) and transforming one of the identified enzymes into a glycosynthase capable of forming taggable disaccharides.

IMPORTANCE The generation of new biocatalysts for plant biomass degradation and glycan synthesis has typically relied on the characterization and investigation of one or a few enzymes at a time. By coupling functional metagenomic screening and high-throughput functional characterization, we can progress beyond the current scale of catalyst discovery and provide rapid annotation of catalyst function. By functionally screening environmental DNA from many diverse sources, we have generated a suite of active glycoside hydrolase-containing clones and demonstrated their reaction parameters. We then demonstrated the utility of this collection through the generation of a new catalyst for the formation of azido-modified glycans. Further interrogation of this collection of clones will expand our biocatalytic toolbox, with potential application to biomass deconstruction and synthesis of glycans.

Development and Application of a High-Throughput Functional Metagenomic Screen for Glycoside Phosphorylases

Glycoside phosphorylases (GPs) catalyze the reversible phosphorolysis of glycosidic bonds, releasing sugar 1-phosphates. To identify a greater range of these under-appreciated enzymes, we have developed a high-throughput functional screening method based on molybdenum blue formation. In a proof-of-principle screen focused on cellulose-degrading GPs we interrogated ∼23,000 large insert (fosmid) clones sourced from microbial communities inhabiting two separate environments and identified seven novel GPs from carbohydrate active enzyme family GH94 and one from GH149. Characterization identified cellobiose phosphorylases, cellodextrin phosphorylases, laminaribiose phosphorylases, and a β-1,3-glucan phosphorylase. To demonstrate the versatility of the screening method, varying substrate combinations were used to identify GP activity from families GH13, GH65, GH112, and GH130 in addition to GH94 and GH149. These pilot screen and substrate versatility results provide a screening paradigm platform for recovering diverse GPs from uncultivated microbial communities acting on different substrates with considerable potential to unravel previously unknown degradative pathways within microbiomes.

Metatranscriptomic and Thermodynamic Insights into Medium-Chain Fatty Acid Production Using an Anaerobic Microbiome

Mixed communities of microbes play important roles in health, the environment, agriculture, and biotechnology. While tapping the combined activities of organisms within microbiomes may allow the utilization of a wider range of substrates in preference to the use of pure cultures for biomanufacturing, harnessing the metabolism of these mixed cultures remains a major challenge. Here, we predicted metabolic functions of bacteria in a microbiome that produces medium-chain fatty acids from a renewable feedstock. Our findings lay the foundation for efforts to begin addressing how to engineer and control microbiomes for improved biomanufacturing, how to build synthetic mixtures of microbes that produce valuable chemicals from renewable resources, and how to better understand the microbial communities that contribute to health, agriculture, and the environment.

Biomanufacturing from renewable feedstocks can offset fossil fuel-based chemical production. One potential biomanufacturing strategy is production of medium-chain fatty acids (MCFA) from organic feedstocks using either pure cultures or microbiomes. While the set of microbes in a microbiome can often metabolize organic materials of greater diversity than a single species can and while the role of specific species may be known, knowledge of the carbon and energy flow within and between organisms in MCFA-producing microbiomes is only now starting to emerge. Here, we integrated metagenomic, metatranscriptomic, and thermodynamic analyses to predict and characterize the metabolic network of an anaerobic microbiome producing MCFA from organic matter derived from lignocellulosic ethanol fermentation conversion residue. A total of 37 high-quality (>80% complete, <10% contamination) metagenome-assembled genomes (MAGs) were recovered from the microbiome, and metabolic reconstruction of the 10 most abundant MAGs was performed. Metabolic reconstruction combined with metatranscriptomic analysis predicted that organisms affiliated with Lactobacillus and Coriobacteriaceae would degrade carbohydrates and ferment sugars to lactate and acetate. Lachnospiraceae- and Eubacteriaceae-affiliated organisms were predicted to transform these fermentation products to MCFA. Thermodynamic analyses identified conditions under which H₂ is expected to be either produced or consumed, suggesting a potential role of H₂ partial pressure in MCFA production. From an integrated systems analysis perspective, we propose that MCFA production could be improved if microbiomes were engineered to use homofermentative instead of heterofermentative Lactobacillus and if MCFA-producing organisms were engineered to preferentially use a thioesterase instead of a coenzyme A (CoA) transferase as the terminal enzyme in reverse β-oxidation.

IMPORTANCE Mixed communities of microbes play important roles in health, the environment, agriculture, and biotechnology. While tapping the combined activities of organisms within microbiomes may allow the utilization of a wider range of substrates in preference to the use of pure cultures for biomanufacturing, harnessing the metabolism of these mixed cultures remains a major challenge. Here, we predicted metabolic functions of bacteria in a microbiome that produces medium-chain fatty acids from a renewable feedstock. Our findings lay the foundation for efforts to begin addressing how to engineer and control microbiomes for improved biomanufacturing, how to build synthetic mixtures of microbes that produce valuable chemicals from renewable resources, and how to better understand the microbial communities that contribute to health, agriculture, and the environment.

Author Video: An author video summary of this article is available.

Diverse Bacteria Utilize Alginate Within the Microbiome of the Giant Kelp Macrocystis pyrifera

Bacteria are integral to marine carbon cycling. They transfer organic carbon to higher trophic levels and remineralise it into inorganic forms. Kelp forests are among the most productive ecosystems within the global oceans, yet the diversity and metabolic capacity of bacteria that transform kelp carbon is poorly understood. Here, we use 16S amplicon and metagenomic shotgun sequencing to survey bacterial communities associated with the surfaces of the giant kelp Macrocystis pyrifera and assess the capacity of these bacteria for carbohydrate metabolism. We find that Macrocystis-associated communities are distinct from the water column, and that they become more diverse and shift in composition with blade depth, which is a proxy for tissue age. These patterns are also observed in metagenomic functional profiles, though the broader functional groups—carbohydrate active enzyme families—are largely consistent across samples and depths. Additionally, we assayed more than 250 isolates cultured from Macrocystis blades and the surrounding water column for the ability to utilize alginate, the primary polysaccharide in Macrocystis tissue. The majority of cultured bacteria (66%) demonstrated this capacity; we find that alginate utilization is patchily distributed across diverse genera in the Bacteroidetes and Proteobacteria, yet can also vary between isolates with identical 16S rRNA sequences. The genes encoding enzymes involved in alginate metabolism were detected in metagenomic data across taxonomically diverse bacterial communities, further indicating this capacity is likely widespread amongst bacteria in kelp forests. Overall, the M. pyrifera epibiota shifts across a depth gradient, demonstrating a connection between bacterial assemblage and host tissue state.

Metagenomics reveals functional synergy and novel polysaccharide utilization loci in the Castor canadensis fecal microbiome

The North American beaver (Castor canadensis) has long been considered an engineering marvel, transforming landscapes and shaping biological diversity through its dam building behavior. While the beaver possesses conspicuous morphological features uniquely adapted for the use of woody plants as construction materials and dietary staples, relatively little is known about the specialized microorganisms inhabiting the beaver gastrointestinal tract and their functional roles in determining host nutrition. Here we use a combination of shotgun metagenomics, functional screening and carbohydrate biochemistry to chart the community structure and metabolic power of the beaver fecal microbiome. We relate this information to the metabolic capacity of other wood feeding and hindgut fermenting organisms and profile the functional repertoire of glycoside hydrolase (GH) families distributed among and between population genome bins. Metagenomic screening revealed novel mechanisms of xylan oligomer degradation involving GH43 enzymes from uncharacterized subfamilies and divergent polysaccharide utilization loci, indicating the potential for synergistic biomass deconstruction. Together, these results open a functional metagenomic window on less conspicuous adaptations enabling the beaver microbiome to efficiently convert woody plants into host nutrition and point toward rational design of enhanced enzyme mixtures for biorefining process streams.

Short-term microbial effects of a large-scale mine-tailing storage facility collapse on the local natural environment

We investigated the impacts of the Mount Polley tailings impoundment failure on chemical, physical, and microbial properties of substrates within the affected watershed, comprised of 70 hectares of riparian wetlands and 40 km of stream and lake shore. We established a biomonitoring network in October of 2014, two months following the disturbance, and evaluated riparian and wetland substrates for microbial community composition and function via 16S and full metagenome sequencing. A total of 234 samples were collected from substrates at 3 depths and 1,650,752 sequences were recorded in a geodatabase framework. These data revealed a wealth of information regarding watershed-scale distribution of microbial community members, as well as community composition, structure, and response to disturbance. Substrates associated with the impact zone were distinct chemically as indicated by elevated pH, nitrate, and sulphate. The microbial community exhibited elevated metabolic capacity for selenate and sulfate reduction and an abundance of chemolithoautotrophs in the Thiobacillus thiophilus/T. denitrificans/T. thioparus clade that may contribute to nitrate attenuation within the affected watershed. The most impacted area (a 6 km stream connecting two lakes) exhibited 30% lower microbial diversity relative to the remaining sites. The tailings impoundment failure at Mount Polley Mine has provided a unique opportunity to evaluate functional and compositional diversity soon after a major catastrophic disturbance to assess metabolic potential for ecosystem recovery.

Insights into the metabolic functioning of a multipartner ciliate symbiosis from oxygen-depleted sediments

Symbioses between anaerobic or microaerophilic protists and prokaryotes are common in anoxic and oxygen-depleted habitats ranging from marine sediments to gastrointestinal tracts. Nevertheless, little is known about the mechanisms of metabolic interaction between partners. In these putatively syntrophic associations, consumption of fermentative end products (e.g., hydrogen) by the prokaryotic symbionts is thought to facilitate protistan anaerobic metabolism. Here, we employed metagenomic and metatranscriptomic sequencing of a microaerophilic or anaerobic karyorelictid ciliate and its prokaryotic symbionts from oxygen-depleted Santa Barbara Basin (CA, USA) sediments to assess metabolic coupling within this consortium. This sequencing confirmed the predominance of deltaproteobacterial symbionts from the Families Desulfobacteraceae and Desulfobulbaceae and suggested active symbiont reduction of host-provided sulphate, transfer of small organic molecules from host to symbionts and hydrogen cycling among the symbionts. In addition, patterns of gene expression indicated active cell division by the symbionts, their growth via autotrophic processes and nitrogen exchange with the ciliate host. Altogether, this research underscores the importance of symbiont metabolism to host fermentative metabolism and, thus, likely its success in anoxic and low-oxygen habitats, but also suggests ciliate-associated prokaryotes play a role in important biogeochemical processes.

Structural and mechanistic analysis of a β-glycoside phosphorylase identified by screening a metagenomic library

Glycoside phosphorylases have considerable potential as catalysts for the assembly of useful glycans for products ranging from functional foods and prebiotics to novel materials. However, the substrate diversity of currently identified phosphorylases is relatively small, limiting their practical applications. To address this limitation, we developed a high-throughput screening approach using the activated substrate 2,4-dinitrophenyl β-d-glucoside (DNPGlc) and inorganic phosphate for identifying glycoside phosphorylase activity and used it to screen a large insert metagenomic library. The initial screen, based on release of 2,4-dinitrophenyl from DNPGlc in the presence of phosphate, identified the gene bglP, encoding a retaining β-glycoside phosphorylase from the CAZy GH3 family. Kinetic and mechanistic analysis of the gene product, BglP, confirmed a double displacement ping-pong mechanism involving a covalent glycosyl-enzyme intermediate. X-ray crystallographic analysis provided insights into the phosphate-binding mode and identified a key glutamine residue in the active site important for substrate recognition. Substituting this glutamine for a serine swapped the substrate specificity from glucoside to N-acetylglucosaminide. In summary, we present a high-throughput screening approach for identifying β-glycoside phosphorylases, which was robust, simple to implement, and useful in identifying active clones within a metagenomics library. Implementation of this screen enabled discovery of a new glycoside phosphorylase class and has paved the way to devising simple ways in which enzyme specificity can be encoded and swapped, which has implications for biotechnological applications.

Diverse Marinimicrobia bacteria may mediate coupled biogeochemical cycles along eco-thermodynamic gradients

Microbial communities drive biogeochemical cycles through networks of metabolite exchange that are structured along energetic gradients. As energy yields become limiting, these networks favor co-metabolic interactions to maximize energy disequilibria. Here we apply single-cell genomics, metagenomics, and metatranscriptomics to study bacterial populations of the abundant "microbial dark matter" phylum Marinimicrobia along defined energy gradients. We show that evolutionary diversification of major Marinimicrobia clades appears to be closely related to energy yields, with increased co-metabolic interactions in more deeply branching clades. Several of these clades appear to participate in the biogeochemical cycling of sulfur and nitrogen, filling previously unassigned niches in the ocean. Notably, two Marinimicrobia clades, occupying different energetic niches, express nitrous oxide reductase, potentially acting as a global sink for the greenhouse gas nitrous oxide.

Nutrient Acquisition and the Metabolic Potential of Photoferrotrophic Chlorobi

Anoxygenic photosynthesis evolved prior to oxygenic photosynthesis and harnessed energy from sunlight to support biomass production on the early Earth. Models that consider the availability of electron donors predict that anoxygenic photosynthesis using Fe(II), known as photoferrotrophy, would have supported most global primary production before the proliferation of oxygenic phototrophs at approximately 2.3 billion years ago. These photoferrotrophs have also been implicated in the deposition of banded iron formations, the world's largest sedimentary iron ore deposits that formed mostly in late Archean and early Proterozoic Eons. In this work we present new data and analyses that illuminate the metabolic capacity of photoferrotrophy in the phylum Chlorobi. Our laboratory growth experiments and biochemical analyses demonstrate that photoferrotrophic Chlorobi are capable of assimilatory sulfate reduction and nitrogen fixation under sulfate and nitrogen limiting conditions, respectively. Furthermore, the evolutionary histories of key enzymes in both sulfur (CysH and CysD) and nitrogen fixation (NifDKH) pathways are convoluted; protein phylogenies, however, suggest that early Chlorobi could have had the capacity to assimilate sulfur and fix nitrogen. We argue, then, that the capacity for photoferrotrophic Chlorobi to acquire these key nutrients enabled them to support primary production and underpin global biogeochemical cycles in the Precambrian.

Functional structure of the bromeliad tank microbiome is strongly shaped by local geochemical conditions

Phytotelmata in tank-forming Bromeliaceae plants are regarded as potential miniature models for aquatic ecology, but detailed investigations of their microbial communities are rare. Hence, the biogeochemistry in bromeliad tanks remains poorly understood. Here we investigate the structure of bacterial and archaeal communities inhabiting the detritus within the tanks of two bromeliad species, Aechmea nudicaulis and Neoregelia cruenta, from a Brazilian sand dune forest. We used metagenomic sequencing for functional community profiling and 16S sequencing for taxonomic profiling. We estimated the correlation between functional groups and various environmental variables, and compared communities between bromeliad species. In all bromeliads, microbial communities spanned a metabolic network adapted to oxygen-limited conditions, including all denitrification steps, ammonification, sulfate respiration, methanogenesis, reductive acetogenesis and anoxygenic phototrophy. Overall, CO2 reducers dominated in abundance over sulfate reducers, and anoxygenic phototrophs largely outnumbered oxygenic photoautotrophs. Functional community structure correlated strongly with environmental variables, between and within a single bromeliad species. Methanogens and reductive acetogens correlated with detrital volume and canopy coverage, and exhibited higher relative abundances in N. cruenta. A comparison of bromeliads to freshwater lake sediments and soil from around the world, revealed stark differences in terms of taxonomic as well as functional microbial community structure.

Metabolic network analysis reveals microbial community interactions in anammox granules

Microbial communities mediating anaerobic ammonium oxidation (anammox) represent one of the most energy-efficient environmental biotechnologies for nitrogen removal from wastewater. However, little is known about the functional role heterotrophic bacteria play in anammox granules. Here, we use genome-centric metagenomics to recover 17 draft genomes of anammox and heterotrophic bacteria from a laboratory-scale anammox bioreactor. We combine metabolic network reconstruction with metatranscriptomics to examine the gene expression of anammox and heterotrophic bacteria and to identify their potential interactions. We find that Chlorobi-affiliated bacteria may be highly active protein degraders, catabolizing extracellular peptides while recycling nitrate to nitrite. Other heterotrophs may also contribute to scavenging of detritus and peptides produced by anammox bacteria, and potentially use alternative electron donors, such as H2, acetate and formate. Our findings improve the understanding of metabolic activities and interactions between anammox and heterotrophic bacteria and offer the first transcriptional insights on ecosystem function in anammox granules.

A geographically-diverse collection of 418 human gut microbiome pathway genome databases

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn's disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools.

High taxonomic variability despite stable functional structure across microbial communities

Understanding the processes that are driving variation of natural microbial communities across space or time is a major challenge for ecologists. Environmental conditions strongly shape the metabolic function of microbial communities; however, other processes such as biotic interactions, random demographic drift or dispersal limitation may also influence community dynamics. The relative importance of these processes and their effects on community function remain largely unknown. To address this uncertainty, here we examined bacterial and archaeal communities in replicate 'miniature' aquatic ecosystems contained within the foliage of wild bromeliads. We used marker gene sequencing to infer the taxonomic composition within nine metabolic functional groups, and shotgun environmental DNA sequencing to estimate the relative abundances of these groups. We found that all of the bromeliads exhibited remarkably similar functional community structures, but that the taxonomic composition within individual functional groups was highly variable. Furthermore, using statistical analyses, we found that non-neutral processes, including environmental filtering and potentially biotic interactions, at least partly shaped the composition within functional groups and were more important than spatial dispersal limitation and demographic drift. Hence both the functional structure and taxonomic composition within functional groups of natural microbial communities may be shaped by non-neutral and roughly separate processes.

LCA*: an entropy-based measure for taxonomic assignment within assembled metagenomes

Motivation: A perennial problem in the analysis of environmental sequence information is the assignment of reads or assembled sequences, e.g. contigs or scaffolds, to discrete taxonomic bins. In the absence of reference genomes for most environmental microorganisms, the use of intrinsic nucleotide patterns and phylogenetic anchors can improve assembly-dependent binning needed for more accurate taxonomic and functional annotation in communities of microorganisms, and assist in identifying mobile genetic elements or lateral gene transfer events.

Results: Here, we present a statistic called LCA* inspired by Information and Voting theories that uses the NCBI Taxonomic Database hierarchy to assign taxonomy to contigs assembled from environmental sequence information. The LCA* algorithm identifies a sufficiently strong majority on the hierarchy while minimizing entropy changes to the observed taxonomic distribution resulting in improved statistical properties. Moreover, we apply results from the order-statistic literature to formulate a likelihood-ratio hypothesis test and P-value for testing the supremacy of the assigned LCA* taxonomy. Using simulated and real-world datasets, we empirically demonstrate that voting-based methods, majority vote and LCA*, in the presence of known reference annotations, are consistently more accurate in identifying contig taxonomy than the lowest common ancestor algorithm popularized by MEGAN, and that LCA* taxonomy strikes a balance between specificity and confidence to provide an estimate appropriate to the available information in the data.

Availability and Implementation: The LCA* has been implemented as a stand-alone Python library compatible with the MetaPathways pipeline; both of which are available on GitHub with installation instructions and use-cases (http://www.github.com/hallamlab/LCAStar/).

Contact:shallam@mail.ubc.ca

Supplementary information:Supplementary data are available at Bioinformatics online.

Fungal and Prokaryotic Activities in the Marine Subsurface Biosphere at Peru Margin and Canterbury Basin Inferred from RNA-Based Analyses and Microscopy

The deep sedimentary biosphere, extending 100s of meters below the seafloor harbors unexpected diversity of Bacteria, Archaea, and microbial eukaryotes. Far less is known about microbial eukaryotes in subsurface habitats, albeit several studies have indicated that fungi dominate microbial eukaryotic communities and fungal molecular signatures (of both yeasts and filamentous forms) have been detected in samples as deep as 1740 mbsf. Here, we compare and contrast fungal ribosomal RNA gene signatures and whole community metatranscriptomes present in sediment core samples from 6 and 95 mbsf from Peru Margin site 1229A and from samples from 12 and 345 mbsf from Canterbury Basin site U1352. The metatranscriptome analyses reveal higher relative expression of amino acid and peptide transporters in the less nutrient rich Canterbury Basin sediments compared to the nutrient rich Peru Margin, and higher expression of motility genes in the Peru Margin samples. Higher expression of genes associated with metals transporters and antibiotic resistance and production was detected in Canterbury Basin sediments. A poly-A focused metatranscriptome produced for the Canterbury Basin sample from 345 mbsf provides further evidence for active fungal communities in the subsurface in the form of fungal-associated transcripts for metabolic and cellular processes, cell and membrane functions, and catalytic activities. Fungal communities at comparable depths at the two geographically separated locations appear dominated by distinct taxa. Differences in taxonomic composition and expression of genes associated with particular metabolic activities may be a function of sediment organic content as well as oceanic province. Microscopic analysis of Canterbury Basin sediment samples from 4 and 403 mbsf produced visualizations of septate fungal filaments, branching fungi, conidiogenesis, and spores. These images provide another important line of evidence supporting the occurrence and activity of fungi in the deep subseafloor biosphere.

Gene expression profiling of microbial activities and interactions in sediments under haloclines of E. Mediterranean deep hypersaline anoxic basins

Deep-sea hypersaline anoxic basins (DHABs) in the Eastern Mediterranean Sea are considered some of the most polyextreme habitats on Earth. In comparison to microbial activities occurring within the haloclines and brines of these unusual water column habitats near the Mediterranean seafloor, relatively little is known about microbial metabolic activities in the underlying sediments. In addition, it is not known whether activities are shaped by the unique chemistries of the different DHAB brines and whether evidence exists for active microbial eukaryotes in those sediments. Metatranscriptome analysis was applied to sediment samples collected using ROV Jason from underneath the haloclines of Urania, Discovery and L'Atalante DHABs and a control site. We report on expression of genes associated with sulfur and nitrogen cycling, putative osmolyte biosynthetic pathways and ion transporters, trace metal detoxification, selected eukaryotic activities (particularly of fungi), microbe-microbe interactions, and motility in sediments underlying the haloclines of three DHABs. Relative to our control sediment sample collected outside of Urania Basin, microbial communities (including eukaryotes) in the Urania and Discovery DHAB sediments showed upregulation of expressed genes associated with nitrogen transformations, osmolyte biosynthesis, heavy metals resistance and metabolism, eukaryotic organelle functions, and cell-cell interactions. Sediments underlying DHAB haloclines that have cumulative physico-chemical stressors within the limits of tolerance for microoorganisms can therefore be hotspots of activity in the deep Mediterranean Sea.