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

The metagenomic and metabolomic profile of the gut microbes in Chinese full-term and late preterm infants treated with Clostridium butyricum

The present study investigated the composition, abundance, and diversity of gut microbes in full-term and late-preterm infants from a medical center in eastern China. A total of 144 genomes of stool samples were captured for 16S rRNA metagenomic analyses. A high abundance of commensal intestinal bacteria was detected in these samples such as Phocaeicola vulgatus, Escherichia coli, and Faecalibacterium prausnitzii, indicating a relatively consistent diversity of gut microbes in the present full-term infants aged 38-40 weeks. However, late preterm infants (n = 50) with mandatory antimicrobials feeding exhibited lower diversity but a higher composition of opportunistic pathogens such as Enterococcus species. Centralized on the situation, we explored the regulatory effect of Clostridium butyricum as probiotics on these late preterm infants. The consumption of C. butyricum did not restore the composition of gut microbes altered by antimicrobials to normal levels, although several opportunistic pathogens decreased significantly after probiotic therapy including Staphylococcus aureus, Sphingomonas echinoides, and Pseudomonas putida. We also compared the effects of day-fed versus night-fed probiotics. Intriguingly, the nighttime feeding showed a higher proportion of C. butyricum compared with probiotic day-feeding. Finally, fecal metabolome and metabolites were analyzed in late preterm infants with (n = 20) or without probiotic therapy (n = 20). The KEGG enrichment analysis demonstrated that vitamin digestion and absorption, synaptic vesicle cycle, and biotin metabolism were significantly increased in the probiotic-treated group, while MSEA indicated that a series of metabolism were significantly enriched in probiotic-treated infants including glycerolipid, biotin, and lysine, indicating the complex effects of probiotic therapy on glutathione metabolism and nutrients digestion and absorption in late preterm infants. Overall, this study provided metagenomic and metabolomic profile of the gut microbes in full-term newborns and late preterm infants in eastern China. Further studies are needed to support and elucidate the role of probiotic feeding in late preterm infants with mandatory antimicrobial treatment.

Inclusion of database outgroups reduces false positives in fungal metabarcoding taxonomic assignments

Metabarcoding studies of fungal communities rely on curated databases for assigning taxonomy. Any host or other nonfungal environmental sequences that are amplified during polymerase chain reaction (PCR) are inherently assigned taxonomy by these same databases, possibly leading to ambiguous nonfungal amplicons being assigned to fungal taxa. Here, we investigated the effects of including nonfungal outgroups in a fungal taxonomic database to aid in detecting and removing these nontarget amplicons. We processed 15 publicly available fungal metabarcode data sets and discovered that roughly 40% of the reads from these studies were not fungal, although they were assigned as Fungus sp. when using a database without nonfungal outgroups. We discuss implications for metabarcoding studies and recommend assigning taxonomy using a database with outgroups to better detect these nonfungal amplicons.

Propagation, detection and correction of errors using the sequence database network

Nucleotide and protein sequences stored in public databases are the cornerstone of many bioinformatics analyses. The records containing these sequences are prone to a wide range of errors, including incorrect functional annotation, sequence contamination and taxonomic misclassification. One source of information that can help to detect errors are the strong interdependency between records. Novel sequences in one database draw their annotations from existing records, may generate new records in multiple other locations and will have varying degrees of similarity with existing records across a range of attributes. A network perspective of these relationships between sequence records, within and across databases, offers new opportunities to detect-or even correct-erroneous entries and more broadly to make inferences about record quality. Here, we describe this novel perspective of sequence database records as a rich network, which we call the sequence database network, and illustrate the opportunities this perspective offers for quantification of database quality and detection of spurious entries. We provide an overview of the relevant databases and describe how the interdependencies between sequence records across these databases can be exploited by network analyses. We review the process of sequence annotation and provide a classification of sources of error, highlighting propagation as a major source. We illustrate the value of a network perspective through three case studies that use network analysis to detect errors, and explore the quality and quantity of critical relationships that would inform such network analyses. This systematic description of a network perspective of sequence database records provides a novel direction to combat the proliferation of errors within these critical bioinformatics resources.

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.

Ethylmalonyl-CoA pathway involved in polyhydroxyvalerate synthesis in Candidatus Contendobacter

Here a stable glycogen accumulating organisms (GAOs) system was operated by anaerobic–aerobic mode in the sequencing batch reactor. We focused on the metabolic mechanisms of PHAs storage from GAOs. Our system showed the classic characteristic of glycogen accumulating metabolism (GAM). Glycogen consumption was followed by acetic acid uptake to synthesize poly-β-hydroxyalkanoates (PHAs) during the anaerobic period, and glycogen was synthesized by PHAs degradation in the aerobic stage. Microbial community structure indicated that Candidatus Contendobacter was the most prevalent GAOs. We found that the ethylmalonyl-CoA (EMC) pathway was the crucial pathway supplying the core substance propionyl-CoA for poly-β-hydroxyvalerate (PHV) synthesis in Candidatus Contendobacter. All genes in EMC pathway were mainly located in Candidatus Contendobacter by gene source analysis. The key genes expression of EMC pathway increased with Candidatus Contendobacter enrichment, further validating that propionyl-CoA was synthesized by Candidatus Contendobacter predominantly via EMC pathway. Our work revealed the novel mechanisms underlying PHV synthesis through EMC pathway and further improved the intercellular storage metabolism of GAOs.

We observed GAM characteristic in the GAOs enrichment system.

Metagenome-based analysis revealed that Candidatus Contendobacter was the dominant GAOs.

The EMC pathway was a novel propionyl-CoA synthesis pathway for PHV in Candidatus Contendobacter.

BugSplit enables genome-resolved metagenomics through highly accurate taxonomic binning of metagenomic assemblies

A large gap remains between sequencing a microbial community and characterizing all of the organisms inside of it. Here we develop a novel method to taxonomically bin metagenomic assemblies through alignment of contigs against a reference database. We show that this workflow, BugSplit, bins metagenome-assembled contigs to species with a 33% absolute improvement in F1-score when compared to alternative tools. We perform nanopore mNGS on patients with COVID-19, and using a reference database predating COVID-19, demonstrate that BugSplit’s taxonomic binning enables sensitive and specific detection of a novel coronavirus not possible with other approaches. When applied to nanopore mNGS data from cases of Klebsiella pneumoniae and Neisseria gonorrhoeae infection, BugSplit’s taxonomic binning accurately separates pathogen sequences from those of the host and microbiota, and unlocks the possibility of sequence typing, in silico serotyping, and antimicrobial resistance prediction of each organism within a sample. BugSplit is available at https://bugseq.com/academic.

A new computational method, BugSplit, teases out individual species’ genomes from metagenomic samples. The authors show that BugSplit is able to identify the presence of a novel coronavirus in COVID-19 patients using a database from 2019 predating the pandemic and can separate host and pathogen sequences in other clinical samples with much higher specificity and accuracy than competing tools.

Music of metagenomics-a review of its applications, analysis pipeline, and associated tools

This humble effort highlights the intricate details of metagenomics in a simple, poetic, and rhythmic way. The paper enforces the significance of the research area, provides details about major analytical methods, examines the taxonomy and assembly of genomes, emphasizes some tools, and concludes by celebrating the richness of the ecosystem populated by the "metagenome."

Large-scale k-mer-based analysis of the informational properties of genomes, comparative genomics and taxonomy

Information theoretic approaches are ubiquitous and effective in a wide variety of bioinformatics applications. In comparative genomics, alignment-free methods, based on short DNA words, or k-mers, are particularly powerful. We evaluated the utility of varying k-mer lengths for genome comparisons by analyzing their sequence space coverage of 5805 genomes in the KEGG GENOME database. In subsequent analyses on four k-mer lengths spanning the relevant range (11, 21, 31, 41), hierarchical clustering of 1634 genus-level representative genomes using pairwise 21- and 31-mer Jaccard similarities best recapitulated a phylogenetic/taxonomic tree of life with clear boundaries for superkingdom domains and high subtree similarity for named taxons at lower levels (family through phylum). By analyzing ~14.2M prokaryotic genome comparisons by their lowest-common-ancestor taxon levels, we detected many potential misclassification errors in a curated database, further demonstrating the need for wide-scale adoption of quantitative taxonomic classifications based on whole-genome similarity.

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.

Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics

Amplicon metabarcoding is an established technique to analyse the taxonomic composition of communities of organisms using high-throughput DNA sequencing, but there are doubts about its ability to quantify the relative proportions of the species, as opposed to the species list. Here, we bypass the enrichment step and avoid the PCR-bias, by directly sequencing the extracted DNA using shotgun metagenomics. This approach is common practice in prokaryotes, but not in eukaryotes, because of the low number of sequenced genomes of eukaryotic species. We tested the metagenomics approach using insect species whose genome is already sequenced and assembled to an advanced degree. We shotgun-sequenced, at low-coverage, 18 species of insects in 22 single-species and 6 mixed-species libraries and mapped the reads against 110 reference genomes of insects. We used the single-species libraries to calibrate the process of assignation of reads to species and the libraries created from species mixtures to evaluate the ability of the method to quantify the relative species abundance. Our results showed that the shotgun metagenomic method is easily able to set apart closely-related insect species, like four species of Drosophila included in the artificial libraries. However, to avoid the counting of rare misclassified reads in samples, it was necessary to use a rather stringent detection limit of 0.001, so species with a lower relative abundance are ignored. We also identified that approximately half the raw reads were informative for taxonomic purposes. Finally, using the mixed-species libraries, we showed that it was feasible to quantify with confidence the relative abundance of individual species in the mixtures.

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.

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.

Disentangling the drivers of functional complexity at the metagenomic level in Shark Bay microbial mat microbiomes

The functional metagenomic potential of Shark Bay microbial mats was examined for the first time at a millimeter scale, employing shotgun sequencing of communities via the Illumina NextSeq 500 platform in conjunction with defined chemical analyses. A detailed functional metagenomic profile has elucidated key pathways and facilitated inference of critical microbial interactions. In addition, 87 medium-to-high-quality metagenome-assembled genomes (MAG) were assembled, including potentially novel bins under the deep-branching archaeal Asgard group (Thorarchaetoa and Lokiarchaeota). A range of pathways involved in carbon, nitrogen, sulfur, and phosphorus cycles were identified in mat metagenomes, with the Wood-Ljungdahl pathway over-represented and inferred as a major carbon fixation mode. The top five sets of genes were affiliated to sulfate assimilation (cysNC cysNCD, sat), methanogenesis (hdrABC), Wood-Ljungdahl pathways (cooS, coxSML), phosphate transport (pstB), and copper efflux (copA). Polyhydroxyalkanoate (PHA) synthase genes were over-represented at the surface, with PHA serving as a potential storage of fixed carbon. Sulfur metabolism genes were highly represented, in particular complete sets of genes responsible for both assimilatory and dissimilatory sulfate reduction. Pathways of environmental adaptation (UV, hypersalinity, oxidative stress, and heavy metal resistance) were also delineated, as well as putative viral defensive mechanisms (core genes of the CRISPR, BREX, and DISARM systems). This study provides new metagenome-based models of how biogeochemical cycles and adaptive responses may be partitioned in the microbial mats of Shark Bay.

Serpentinization-Influenced Groundwater Harbors Extremely Low Diversity Microbial Communities Adapted to High pH

Serpentinization is a widespread geochemical process associated with aqueous alteration of ultramafic rocks that produces abundant reductants (H₂ and CH₄) for life to exploit, but also potentially challenging conditions, including high pH, limited availability of terminal electron acceptors, and low concentrations of inorganic carbon. As a consequence, past studies of serpentinites have reported low cellular abundances and limited microbial diversity. Establishment of the Coast Range Ophiolite Microbial Observatory (California, U.S.A.) allowed a comparison of microbial communities and physicochemical parameters directly within serpentinization-influenced subsurface aquifers. Samples collected from seven wells were subjected to a range of analyses, including solute and gas chemistry, microbial diversity by 16S rRNA gene sequencing, and metabolic potential by shotgun metagenomics, in an attempt to elucidate what factors drive microbial activities in serpentinite habitats. This study describes the first comprehensive interdisciplinary analysis of microbial communities in hyperalkaline groundwater directly accessed by boreholes into serpentinite rocks. Several environmental factors, including pH, methane, and carbon monoxide, were strongly associated with the predominant subsurface microbial communities. A single operational taxonomic unit (OTU) of Betaproteobacteria and a few OTUs of Clostridia were the almost exclusive inhabitants of fluids exhibiting the most serpentinized character. Metagenomes from these extreme samples contained abundant sequences encoding proteins associated with hydrogen metabolism, carbon monoxide oxidation, carbon fixation, and acetogenesis. Metabolic pathways encoded by Clostridia and Betaproteobacteria, in particular, are likely to play important roles in the ecosystems of serpentinizing groundwater. These data provide a basis for further biogeochemical studies of key processes in serpentinite subsurface environments.