Strain-resolved community genomic analysis of gut microbial colonization in a premature infant

Department of Surgery, University of Chicago Pritzker School of Medicine, Chicago, IL 60637, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 01/2011; 108(3):1128-33. DOI: 10.1073/pnas.1010992108
Source: PubMed


The intestinal microbiome is a critical determinant of human health. Alterations in its composition have been correlated with chronic disorders, such as obesity and inflammatory bowel disease in adults, and may be associated with neonatal necrotizing enterocolitis in premature infants. Increasing evidence suggests that strain-level genomic variation may underpin distinct ecological trajectories within mixed populations, yet there have been few strain-resolved analyses of genotype-phenotype connections in the context of the human ecosystem. Here, we document strain-level genomic divergence during the first 3 wk of life within the fecal microbiota of an infant born at 28-wk gestation. We observed three compositional phases during colonization, and reconstructed and intensively curated population genomic datasets from the third phase. The relative abundance of two Citrobacter strains sharing ~99% nucleotide identity changed significantly over time within a community dominated by a nearly clonal Serratia population and harboring a lower abundance Enterococcus population and multiple plasmids and bacteriophage. Modeling of Citrobacter strain abundance suggests differences in growth rates and host colonization patterns. We identified genotypic variation potentially responsible for divergent strain ecologies, including hotspots of sequence variation in regulatory genes and intergenic regions, and in genes involved in transport, flagellar biosynthesis, substrate metabolism, and host colonization, as well as differences in the complements of these genes. Our results demonstrate that a community genomic approach can elucidate gut microbial colonization at the resolution required to discern medically relevant strain and species population dynamics, and hence improve our ability to diagnose and treat microbial community-mediated disorders.

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Available from: Valeriy A Poroyko, Jun 20, 2014
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    • "14/29 Other investigators have utilized single bp changes to compare different variants of the same species based on reference genomes (Zhang et al., 2006; Morelli et al., 2010). While less frequent, identification of single bp changes has also been used to characterize heterogeneity in naturally occurring microbial populations through metagenomics (Simmons et al., 2008; Morowitz et al., 2011; Tyson et al., 2004). However, recovering detailed reports of single bp change patterns has not been straightforward due to the lack of adequate algorithms that can automatically identify and report nucleotide positions of highvariability inferred from multiple samples using contigs constructed de novo as reference for metagenomic short reads. "
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    ABSTRACT: Advances in high-throughput sequencing and ‘omics technologies are revolutionizing studies of naturally occurring microbial communities. Comprehensive investigations of microbial lifestyles require the ability to interactively organize and visualize genetic information and to incorporate subtle differences that enable greater resolution of complex data. Here we introduce anvi’o, an advanced analysis and visualization platform that offers automated and human-guided characterization of microbial genomes in metagenomic assemblies, with interactive interfaces that can link ‘omics data from multiple sources into a single, intuitive display. Its extensible visualization approach distills multiple dimensions of information about each contig, offering a dynamic and unified work environment for data exploration, manipulation, and reporting. Using anvi’o, we re-analyzed publicly available datasets and explored temporal genomic changes within naturally occurring microbial populations through de novo characterization of single nucleotide variations, and linked cultivar and single-cell genomes with metagenomic and metatranscriptomic data. Anvi’o is an open-source platform that empowers researchers without extensive bioinformatics skills to perform and communicate in-depth analyses on large ‘omics datasets.
    PeerJ 10/2015; 3(358):e1319. DOI:10.7717/peerj.1319 · 2.11 Impact Factor
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    • "Moreover, 16S sequencing does not provide any functional input about the community, since the sequence is not strain-specific. Gene contents may differ between bacterial strains with identical 16S rRNA gene sequence and underlie their functional difference related to genes responsible for toxicity and pathogenesis [78]. WGS of the microbiota (e.g., Human Microbiome Project Consortium, 2012) is preferred over 16S rRNA-based analysis to elucidate taxonomic classification and bacterial diversity within members of the microbial community. "
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    ABSTRACT: Gut microbiota of higher vertebrates is host-specific. The number and diversity of the organisms residing within the gut ecosystem are defined by physiological and environmental factors, such as host genotype, habitat, and diet. Recently, culture-independent sequencing techniques have added a new dimension to the study of gut microbiota and the challenge to analyze the large volume of sequencing data is increasingly addressed by the development of novel computational tools and methods. Interestingly, gut microbiota maintains a constant relative abundance at operational taxonomic unit (OTU) levels and altered bacterial abundance has been associated with complex diseases such as symptomatic atherosclerosis, type 2 diabetes, obesity, and colorectal cancer. Therefore, the study of gut microbial population has emerged as an important field of research in order to ultimately achieve better health. In addition, there is a spontaneous, non-linear, and dynamic interaction among different bacterial species residing in the gut. Thus, predicting the influence of perturbed microbe-microbe interaction network on health can aid in developing novel therapeutics. Here, we summarize the population abundance of gut microbiota and its variation in different clinical states, computational tools available to analyze the pyrosequencing data, and gut microbe-microbe interaction networks. Copyright © 2015. Production and hosting by Elsevier Ltd.
    07/2015; 13(3). DOI:10.1016/j.gpb.2015.02.005
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    • "The two UC1CITs strains share an approximate 98 . 96 and 99 . 23% nucleotide and amino acid identity between their orthologs , respectively . Read mapping data confirms genome abundances previously published ( Morowitz et al . , 2010 ) , with a drop in the minor strain population around DOL 18 ( Figure 1 ) ."
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    ABSTRACT: While there has been growing interest in the gut microbiome in recent years, it remains unclear whether closely related species and strains have similar or distinct functional roles and if organisms capable of both aerobic and anaerobic growth do so simultaneously. To investigate these questions, we implemented a high-throughput mass spectrometry-based proteomics approach to identify proteins in fecal samples collected on days of life 13-21 from an infant born at 28 weeks gestation. No prior studies have coupled strain-resolved community metagenomics to proteomics for such a purpose. Sequences were manually curated to resolve the genomes of two strains of Citrobacter that were present during the later stage of colonization. Proteome extracts from fecal samples were processed via a nano-2D-LC-MS/MS and peptides were identified based on information predicted from the genome sequences for the dominant organisms, Serratia and the two Citrobacter strains. These organisms are facultative anaerobes, and proteomic information indicates the utilization of both aerobic and anaerobic metabolisms throughout the time series. This may indicate growth in distinct niches within the gastrointestinal tract. We uncovered differences in the physiology of coexisting Citrobacter strains, including differences in motility and chemotaxis functions. Additionally, for both Citrobacter strains we resolved a community-essential role in vitamin metabolism and a predominant role in propionate production. Finally, in this case study we detected differences between genome abundance and activity levels for the dominant populations. This underlines the value in layering proteomic information over genetic potential.
    Frontiers in Microbiology 07/2015; 6:654. DOI:10.3389/fmicb.2015.00654 · 3.99 Impact Factor
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