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.

Multiple microbial guilds mediate soil methane cycling along a wetland salinity gradient

Estuarine wetlands harbor considerable carbon stocks, but rising sea levels could affect their ability to sequester soil carbon as well as their potential to emit methane (CH4). While sulfate loading from seawater intrusion may reduce CH4 production due to the higher energy yield of microbial sulfate reduction, existing studies suggest other factors are likely at play. Our study of 11 wetland complexes spanning a natural salinity and productivity gradient across the San Francisco Bay and Delta found that while CH4 fluxes generally declined with salinity, they were highest in oligohaline wetlands (ca. 3-ppt salinity). Methanogens and methanogenesis genes were weakly correlated with CH4 fluxes but alone did not explain the highest rates observed. Taxonomic and functional gene data suggested that other microbial guilds that influence carbon and nitrogen cycling need to be accounted for to better predict CH4 fluxes at landscape scales. Higher methane production occurring near the freshwater boundary with slight salinization (and sulfate incursion) might result from increased sulfate-reducing fermenter and syntrophic populations, which can produce substrates used by methanogens. Moreover, higher salinities can solubilize ionically bound ammonium abundant in the lower salinity wetland soils examined here, which could inhibit methanotrophs and potentially contribute to greater CH4 fluxes observed in oligohaline sediments.IMPORTANCELow-level salinity intrusion could increase CH4 flux in tidal freshwater wetlands, while higher levels of salinization might instead decrease CH4 fluxes. High CH4 emissions in oligohaline sites are concerning because seawater intrusion will cause tidal freshwater wetlands to become oligohaline. Methanogenesis genes alone did not account for landscape patterns of CH4 fluxes, suggesting mechanisms altering methanogenesis, methanotrophy, nitrogen cycling, and ammonium release, and increasing decomposition and syntrophic bacterial populations could contribute to increases in net CH4 flux at oligohaline salinities. Improved understanding of these influences on net CH4 emissions could improve restoration efforts and accounting of carbon sequestration in estuarine wetlands. More pristine reference sites may have older and more abundant organic matter with higher carbon:nitrogen compared to wetlands impacted by agricultural activity and may present different interactions between salinity and CH4. This distinction might be critical for modeling efforts to scale up biogeochemical process interactions in estuarine wetlands.

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.

Comparative genomics reveals electron transfer and syntrophic mechanisms differentiating methanotrophic and methanogenic archaea

The anaerobic oxidation of methane coupled to sulfate reduction is a microbially mediated process requiring a syntrophic partnership between anaerobic methanotrophic (ANME) archaea and sulfate-reducing bacteria (SRB). Based on genome taxonomy, ANME lineages are polyphyletic within the phylum Halobacterota, none of which have been isolated in pure culture. Here, we reconstruct 28 ANME genomes from environmental metagenomes and flow sorted syntrophic consortia. Together with a reanalysis of previously published datasets, these genomes enable a comparative analysis of all marine ANME clades. We review the genomic features that separate ANME from their methanogenic relatives and identify what differentiates ANME clades. Large multiheme cytochromes and bioenergetic complexes predicted to be involved in novel electron bifurcation reactions are well distributed and conserved in the ANME archaea, while significant variations in the anabolic C1 pathways exists between clades. Our analysis raises the possibility that methylotrophic methanogenesis may have evolved from a methanotrophic ancestor.

A comparative genomics study of anaerobic methanotrophic (ANME) archaea reveals the genetic "parts list" associated with the repeated evolutionary transition between methanogenic and methanotrophic metabolism in the archaeal domain of life.

Discovery and Development of Promiscuous O-Glycan Hydrolases for Removal of Intact Sialyl T-Antigen

Mucin-type O-glycosylation (O-glycosylation) is a common post-translational modification that confers distinct biophysical properties to proteins and plays crucial roles in intercellular signaling. Yet, despite the importance of O-glycans, relatively few tools exist for their analysis and modification. In particular, there is a need for enzymes that can cleave the wide range of O-glycan structures found on protein surfaces, to facilitate glycan profiling and editing. Through functional metagenomic screening of the human gut microbiome, we discovered endo-O-glycan hydrolases from CAZy family GH101 that are capable of slowly cleaving the intact sialyl T-antigen trisaccharide (a ubiquitous O-glycan structure in humans) in addition to their primary activity against the T-antigen disaccharide. We then further explored this sequence space through phylogenetic profiling and analysis of representative enzymes, revealing large differences in the levels of this promiscuous activity between enzymes within the family. Through structural and sequence analysis, we identified active site residues that modulate specificity. Through subsequent rational protein engineering, we improved the activity of an enzyme identified by phylogenetic profiling sufficiently that substantial removal of the intact sialyl T-antigen from proteins could be readily achieved. Our best sialyl T-antigen hydrolase mutant, SpGH101 Q868G, is further shown to function on a number of proteins, tissues, and cells. Access to this enzyme opens up improved methodologies for unraveling the glycan code.

TreeSAPP: the Tree-based Sensitive and Accurate Phylogenetic Profiler

Motivation

Microbial communities drive matter and energy transformations integral to global biogeochemical cycles, yet many taxonomic groups facilitating these processes remain poorly represented in biological sequence databases. Due to this missing information, taxonomic assignment of sequences from environmental genomes remains inaccurate.

Results

We present the Tree-based Sensitive and Accurate Phylogenetic Profiler (TreeSAPP) software for functionally and taxonomically classifying genes, reactions and pathways from genomes of cultivated and uncultivated microorganisms using reference packages representing coding sequences mediating multiple globally relevant biogeochemical cycles. TreeSAPP uses linear regression of evolutionary distance on taxonomic rank to improve classifications, assigning both closely related and divergent query sequences at the appropriate taxonomic rank. TreeSAPP is able to provide quantitative functional and taxonomic classifications for both assembled and unassembled sequences and files supporting interactive tree of life visualizations.

Availability and implementation

TreeSAPP was developed in Python 3 as an open-source Python package and is available on GitHub at https://github.com/hallamlab/TreeSAPP.

Supplementary information

Supplementary data are available at Bioinformatics online.

Prospecting for microbial α-N-acetylgalactosaminidases yields a new class of GH31 O-glycanase

α-Linked GalNAc (α-GalNAc) is most notably found at the nonreducing terminus of the blood type-determining A-antigen and as the initial point of attachment to the peptide backbone in mucin-type O-glycans. However, despite their ubiquity in saccharolytic microbe-rich environments such as the human gut, relatively few α-N-acetylgalactosaminidases are known. Here, to discover and characterize novel microbial enzymes that hydrolyze α-GalNAc, we screened small-insert libraries containing metagenomic DNA from the human gut microbiome. Using a simple fluorogenic glycoside substrate, we identified and characterized a glycoside hydrolase 109 (GH109) that is active on blood type A-antigen, along with a new subfamily of glycoside hydrolase 31 (GH31) that specifically cleaves the initial α-GalNAc from mucin-type O-glycans. This represents a new activity in this GH family and a potentially useful new enzyme class for analysis or modification of O-glycans on protein or cell surfaces.

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.

Recovering cellular biomass from fluids using chemical flocculation

We developed an efficient, scalable and inexpensive method for recovering cellular biomass from complex fluid matrices that cannot be processed using conventional filtration methods. The method uses chemical flocculation with iron oxyhydroxides, is capable of recovering greater than 90% of cellular biomass from fluids with more than 10³ cells ml^-1 , and was validated using both mock communities and field samples. High quality DNA can be readily extracted from iron flocs using standard soil extraction kits. We applied chemical flocculation to fracing fluids from British Columbia, Canada and recovered a diversity of microbial taxa including abundant members of the Epsilon- and Deltaproteobacteria previously recovered from shale gas operations in the United States. Application of chemical flocculation presents new opportunities for scalable time-series monitoring and experimentation on complex fluid matrices including microbial community profiling and shotgun metagenomics over gas production well completion cycles.

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.

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

Summary: Next-generation sequencing is producing vast amounts of sequence information from natural and engineered ecosystems. Although this data deluge has an enormous potential to transform our lives, knowledge creation and translation need software applications that scale with increasing data processing and analysis requirements. Here, we present improvements to MetaPathways, an annotation and analysis pipeline for environmental sequence information that expedites this transformation. We specifically address pathway prediction hazards through integration of a weighted taxonomic distance and enable quantitative comparison of assembled annotations through a normalized read-mapping measure. Additionally, we improve LAST homology searches through BLAST-equivalent E-values and output formats that are natively compatible with prevailing software applications. Finally, an updated graphical user interface allows for keyword annotation query and projection onto user-defined functional gene hierarchies, including the Carbohydrate-Active Enzyme database.

Availability and implementation: MetaPathways v2.5 is available on GitHub: http://github.com/hallamlab/metapathways2.

Contact:shallam@mail.ubc.ca

Supplementary information:Supplementary data are available at Bioinformatics online.