Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. It automatically forms hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat.

MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities

We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.

/pdf/minimum-information-about-a-single-amplified-genome-misag-1jusa368s7.pdf

Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea

Reference genomes are required to understand the diverse roles of microorganisms in ecology, evolution, human and animal health, but most species remain uncultured. Here we present a sequence composition-independent approach to recover high-quality microbial genomes from deeply sequenced metagenomes. Multiple metagenomes of the same community, which differ in relative population abundances, were used to assemble 31 bacterial genomes, including rare (<1% relative abundance) species, from an activated sludge bioreactor. Twelve genomes were assembled into complete or near-complete chromosomes. Four belong to the candidate bacterial phylum TM7 and represent the most complete genomes for this phylum to date (relative abundances, 0.06-1.58%). Reanalysis of published metagenomes reveals that differential coverage binning facilitates recovery of more complete and higher fidelity genome bins than other currently used methods, which are primarily based on sequence composition. This approach will be an important addition to the standard metagenome toolbox and greatly improve access to genomes of uncultured microorganisms.

Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types.

/pdf/species-level-functional-profiling-of-metagenomes-and-2hqzackk6l.pdf

Species-level functional profiling of metagenomes and metatranscriptomes.

The study of microbiomes using whole-metagenome shotgun sequencing enables the analysis of uncultivated microbial populations that may have important roles in their environments. Extracting individual draft genomes (bins) facilitates metagenomic analysis at the single genome level. Software and pipelines for such analysis have become diverse and sophisticated, resulting in a significant burden for biologists to access and use them. Furthermore, while bin extraction algorithms are rapidly improving, there is still a lack of tools for their evaluation and visualization. To address these challenges, we present metaWRAP, a modular pipeline software for shotgun metagenomic data analysis. MetaWRAP deploys state-of-the-art software to handle metagenomic data processing starting from raw sequencing reads and ending in metagenomic bins and their analysis. MetaWRAP is flexible enough to give investigators control over the analysis, while still being easy-to-install and easy-to-use. It includes hybrid algorithms that leverage the strengths of a variety of software to extract and refine high-quality bins from metagenomic data through bin consolidation and reassembly. MetaWRAP’s hybrid bin extraction algorithm outperforms individual binning approaches and other bin consolidation programs in both synthetic and real data sets. Finally, metaWRAP comes with numerous modules for the analysis of metagenomic bins, including taxonomy assignment, abundance estimation, functional annotation, and visualization. MetaWRAP is an easy-to-use modular pipeline that automates the core tasks in metagenomic analysis, while contributing significant improvements to the extraction and interpretation of high-quality metagenomic bins. The bin refinement and reassembly modules of metaWRAP consistently outperform other binning approaches. Each module of metaWRAP is also a standalone component, making it a flexible and versatile tool for tackling metagenomic shotgun sequencing data. MetaWRAP is open-source software available at https://github.com/bxlab/metaWRAP
 .

/pdf/metawrap-a-flexible-pipeline-for-genome-resolved-metagenomic-6the619027.pdf

MetaWRAP-a flexible pipeline for genome-resolved metagenomic data analysis.

The gut microbial community (Gut microbiota) is known to impact metabolic functions as well as immune responses in our body Diet plays an important role in determining the composition of the gut microbiota Gut microbes help in assimilating dietary nutrients which are indigestible by humans The metabolites produced by them not only modulate gastro-intestinal immunity, but also impact distal organs like lung and brain Micro-aspiration of gut bacteria or movement of sensitized immune cells through lymph or bloodstream can also influence immune response of other organs Dysbiosis in gut microbiota has been implicated in several lung diseases, including allergy, asthma and cystic fibrosis The bi-directional cross-talk between gut and lung (termed as Gut-Lung axis) is best exemplified by intestinal disturbances observed in lung diseases Some of the existing probiotics show beneficial effects on lung health A deeper understanding of the gut microbiome which comprises of all the genetic material within the gut microbiota and its role in respiratory disorders is likely to help in designing appropriate probiotic cocktails for therapeutic applications

/pdf/diet-microbiota-and-gut-lung-connection-3im2wdn07g.pdf

Diet, Microbiota and Gut-Lung Connection

Characterizing the taxonomic diversity of microbial communities is one of the primary objectives of metagenomic studies. Taxonomic analysis of microbial communities, a process referred to as binning, is challenging for the following reasons. Primarily, query sequences originating from the genomes of most microbes in an environmental sample lack taxonomically related sequences in existing reference databases. This absence of a taxonomic context makes binning a very challenging task. Limitations of current sequencing platforms, with respect to short read lengths and sequencing errors/artifacts, are also key factors that determine the overall binning efficiency. Furthermore, the sheer volume of metagenomic datasets also demands highly efficient algorithms that can operate within reasonable requirements of compute power. This review discusses the premise, methodologies, advantages, limitations and challenges of various methods available for binning of metagenomic datasets obtained using the shotgun sequencing approach. Various parameters as well as strategies used for evaluating binning efficiency are then reviewed.

/pdf/classification-of-metagenomic-sequences-methods-and-tw3rp7x8u2.pdf

Classification of metagenomic sequences: methods and challenges.

A new secretion system, called the Type VI Secretion system (T6SS), was recently reported in Vibrio cholerae, Pseudomonas aeruginosa and Burkholderia mallei. A total of 18 genes have been identified to be belonging to this secretion system in V. cholerae. Here we attempt to identify presence of T6SS in other bacterial genomes. This includes identification of orthologous sequences, conserved motifs, domains, families, 3D folds, genomic islands containing T6SS components, phylogenetic profiles and protein-protein association of these components. Our analysis indicates presence of T6SS in 42 bacteria and its absence in most of their non-pathogenic species, suggesting the role of T6SS in imparting pathogenicity to an organism. Analysis of genomic regions containing T6SS components, phylogenetic profiles and protein-protein association of T6SS components indicate few additional genes which could be involved in this secretion system. Based on our studies, functional annotations were assigned to most of the components. Except one of the genes, we could group all the other genes of T6SS into those belonging to the puncturing device, and those located in the outer membrane, transmembrane and inner membrane. Based on our analysis, we have proposed a model of T6SS and have compared the same with the other bacterial secretion systems.

Identification and Functional Characterization of Gene Components of Type VI Secretion System in Bacterial Genomes

The link between gut microbiome and brain is being slowly acknowledged due to the speculated role of resident gut microbial community in altering the functions of gut-brain axis (GBA). Recently, a number of microbial metabolites (referred to as neuro-active metabolites) produced through tryptophan metabolism have been suggested to influence the GBA. In view of this, the current study focuses on microbial tryptophan metabolism pathways which produce neuro-active metabolites. An in silico analysis was performed on bacterial genomes as well as publicly available gut microbiome data. The results provide a comprehensive catalog of the analyzed pathways across bacteria. The analysis indicates an enrichment of tryptophan metabolism pathways in five gut-associated phyla, namely, Actinobacteria, Firmicutes, Bacteroidetes, Proteobacteria, and Fusobacteria. Further, five genera, namely, Clostridium, Burkholderia, Streptomyces, Pseudomonas, and Bacillus have been predicted to be enriched in terms of number of the analyzed tryptophan metabolism pathways, suggesting a higher potential of these bacterial groups to metabolize tryptophan in gut. Analysis of available microbiome data corresponding to gut samples from patients of neurological diseases and healthy individuals suggests probable association of different sets of tryptophan metabolizing bacterial pathways with the etiology of different diseases. The insights obtained from the present study are expected to provide directions toward designing of microbiome based diagnostic and therapeutic approaches for neurological diseases/disorders.

Tryptophan Metabolism by Gut Microbiome and Gut-Brain-Axis: An in silico Analysis.

Background 
Malnutrition is a global health problem affecting more than 300 million pre-school children worldwide. It is one of the major health concerns in India since around 50% of children below the age of two suffer from various forms of malnutrition. The gut microbiome plays an important role in nutrient pre-processing, assimilation and energy harvest from food. Consequently, dysbiosis of the gut microbiota has been implicated in malnutrition.


Methodology/Principal Findings 
Metagenomics approach was adopted to investigate the gut microbiome sampled from 20 rural Indian children with varying nutritional status. The changes in the abundances of various taxonomic and functional groups were investigated across these gut microbiomes. A core set of 23 genera were observed across samples, with some showing differential abundances with varying nutritional status. One of the findings of the current study is the positive/negative associations of specific taxonomic and functional groups with the nutritional status of the children. Notable alterations in the architecture of the inter-microbial co-occurrence networks were also observed with changes in nutritional status. A key example is the clustering of potentially pathogenic groups into a distinct hub in severely malnourished gut. Our data does not demonstrate causality with the microbiome patterns that we observed, rather a description of some interesting patterns, whose underlying mechanism remains to be uncovered.


Conclusions 
The present study envisioned interrelationships between the pattern of gut microbiome and the nutritional status of children. The cause of this pattern needs to be explored. However, insights obtained from the present study form the basis for further metagenomic investigations on larger population of children. Results of such studies will be useful in identifying the key microbial groups that can be utilized for targeted therapeutic interventions for managing severe acute malnutrition.

Sharmila S. Mande

Papers

Diet, Microbiota and Gut-Lung Connection

Classification of metagenomic sequences: methods and challenges.

Identification and Functional Characterization of Gene Components of Type VI Secretion System in Bacterial Genomes

Tryptophan Metabolism by Gut Microbiome and Gut-Brain-Axis: An in silico Analysis.

Gut Microbiomes of Indian Children of Varying Nutritional Status