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Characterizing the gut microbiota in terms of their capacity to interfere with drug metabolism is necessary to achieve drug efficacy and safety. Although examples of drug-microbiome interactions are well-documented, little has been reported about a computational pipeline for systematically identifying and characterizing bacterial enzymes that process particular classes of drugs. The goal of our study is to develop a computational approach that compiles drugs whose metabolism may be influenced by a particular class of microbial enzymes and that quantifies the variability in the collective level of those enzymes among individuals. The present paper describes this approach, with microbial β-glucuronidases as an example, which break down drug-glucuronide conjugates and reactivate the drugs or their metabolites. We identified 100 medications that may be metabolized by β-glucuronidases from the gut microbiome. These medications included morphine, estrogen, ibuprofen, midazolam, and their structural analogues. The analysis of metagenomic data available through the Sequence Read Archive (SRA) showed that the level of β-glucuronidase in the gut metagenomes was higher in males than in females, which provides a potential explanation for the sex-based differences in efficacy and toxicity for several drugs, reported in previous studies. Our analysis also showed that infant gut metagenomes at birth and 12 months of age have higher levels of β-glucuronidase than the metagenomes of their mothers and the implication of this observed variability was discussed in the context of breastfeeding as well as infant hyperbilirubinemia. Overall, despite important limitations discussed in this paper, our analysis provided useful insights on the role of the human gut metagenome in the variability in drug response among individuals. Importantly, this approach exploits drug and metagenome data available in public databases as well as open-source cheminformatics and bioinformatics tools to predict drug-metagenome interactions.
The aim of this paper is to obtain a systems-level understanding of the interactions between Dehalococcoides and corrinoid-supplying microorganisms by analyzing community structures and functional compositions, activities, and dynamics in trichloroethene (TCE)-dechlorinating enrichments. Metagenomes and metatranscriptomes of the dechlorinating enrichments with and without exogenous cobalamin were compared. Seven putative draft genomes were binned from the metagenomes. At an early stage (2 days), more transcripts of genes in the Veillonellaceae bin-genome were detected in the metatranscriptome of the enrichment without exogenous cobalamin than in the one with the addition of cobalamin. Among these genes, sporulation-related genes exhibited the highest differential expression when cobalamin was not added, suggesting a possible release route of corrinoids from corrinoid producers. Other differentially expressed genes include those involved in energy conservation and nutrient transport (including cobalt transport). The most highly expressed corrinoid de novo biosynthesis pathway was also assigned to the Veillonellaceae bin-genome. Targeted quantitative PCR (qPCR) analyses confirmed higher transcript abundances of those corrinoid biosynthesis genes in the enrichment without exogenous cobalamin than in the enrichment with cobalamin. Furthermore, the corrinoid salvaging and modification pathway of Dehalococcoides was upregulated in response to the cobalamin stress. Finally, this study provides important insights into the microbial interactions and roles played by members of dechlorinating communities under cobalamin-limited conditions.
Patrick Chain of DOE JGI at LANL, Co-Chair of the Metagenome-specific Assembly session, on Metagenome Assembly at the DOE JGIat the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
DOE JGI's Tanja Woyke, chair of the Single Cells and Metagenomes session, delivers an introduction, followed by Bigelow Laboratory's Ramunas Stepanauskas on "Single Cell and Metagenomic Assemblies: Biology Drives Technical Choices and Goals" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
Soil microorganisms carry out important processes, including support of plant growth and cycling of carbon and other nutrients. However, the majority of soil microbes have not yet been isolated and their functions are largely unknown. Although metagenomic sequencing reveals microbial identities and functional gene information, it includes DNA from microbes with vastly varying physiological states. Therefore, metagenomics is only predictive of community functional potential. We posit that the next frontier lies in understanding the metaphenome, the product of the combined genetic potential of the microbiome and available resources. Here we describe examples of opportunities towards gaining understanding of the soil metaphenome.
Aeration is a major cost at biological nutrient removal (BNR) plants. We report on microbial communities in a pilot-scale BNR system before and after a dissolved oxygen transition from 2.5 to 0.2 mg/L implemented over 18 months. Four PacBio metagenomes and 316 metagenome-assembled genomes are announced.
Operating biological nutrient removal (BNR) wastewater treatment plants with low dissolved oxygen (DO) conditions can reduce energy costs. We report on five metagenomes and 492 metagenome-assembled genomes (MAGs) obtained from samples collected at the Pomona water reclamation plant before and after a DO reduction from 3.5 to 0.7 mg/L.
DOE JGI's Alex Sczyrba on "Evaluation of the Cow Rumen Metagenome" and "Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
Keio University's Yasumbumi Sakakibara on "MetaVelvet: An Extension of Velvet Assembler to de novo Metagenome Assembly from Short Sequence Reads" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
University of Maryland's Sergey Koren on "denovo Metagenomic Assembly" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
San Diego Supercomputer Center's Weizhong Li on "Effective Analysis of NGS Metagenomic Data with Ultra-fast Clustering Algorithms" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
JCVI's Johannes Goll on Using Solr/Lucene for Large-Scale Metagenomics Data Retrieval and Analysis at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
DOE JGI's Zhong Wang, chair of the High-performance Computing session, gives a brief introduction before Berkeley Lab's Shane Canon talks about "Exploiting HPC Platforms for Metagenomics: Challenges and Opportunities" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.
Annotation of metagenomes involves comparing the individual sequence reads with a database of known sequences and assigning a unique function to each read. This is a time-consuming task that is computationally intensive (though not computationally complex). Here we present a novel approach to annotate metagenomes using unique k-mer oligopeptide sequences from 7 to 12 amino acids long. We demonstrate that k-mer-based annotations are faster and approach the sensitivity and precision of blastx-based annotations without loosing accuracy. A last-common ancestor approach was also developed to describe the members of the community.
Genomes reveal nutrient stress patterns Within the surface ocean, nitrogen, iron, and phosphorous can all be limiting nutrients for phytoplankton depending on location. Ustick et al. used the prevalence of Prochlorococcus genes involved in nutrient acquisition to develop maps of inferred nutrient stress across the global ocean (see the Perspective by Coleman). They found broad patterns of limitation consistent with an Earth system model and nutrient addition experiments. Leveraging metagenomic data in this manner is an appealing approach that will help to expand our understanding of the biogeochemistry in the vast open ocean. Science , this issue p. 287 ; see also p. 239
Here, we present 36 metagenomes, 59 metatranscriptomes, and 373 metagenome-assembled genomes (MAGs) from Chesapeake and Delaware Bay water samples. This data set will be useful for studying microbial biogeochemical cycling in estuaries.