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      Long-term ecological and evolutionary dynamics in the gut microbiomes of carbapenemase-producing Enterobacteriaceae colonized subjects

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          Abstract

          Long-term colonization of the gut microbiome by carbapenemase-producing Enterobacteriaceae (CPE) is a growing area of public health concern as it can lead to community transmission and rapid increase in cases of life-threatening CPE infections. Here, leveraging the observation that many subjects are decolonized without interventions within a year, we used longitudinal shotgun metagenomics (up to 12 timepoints) for detailed characterization of ecological and evolutionary dynamics in the gut microbiome of a cohort of CPE-colonized subjects and family members ( n = 46; 361 samples). Subjects who underwent decolonization exhibited a distinct ecological shift marked by recovery of microbial diversity, key commensals and anti-inflammatory pathways. In addition, colonization was marked by elevated but unstable Enterobacteriaceae abundances, which exhibited distinct strain-level dynamics for different species ( Escherichia coli and Klebsiella pneumoniae). Finally, comparative analysis with whole-genome sequencing data from CPE isolates ( n = 159) helped identify substrain variation in key functional genes and the presence of highly similar E. coli and K. pneumoniae strains with variable resistance profiles and plasmid sharing. These results provide an enhanced view into how colonization by multi-drug-resistant bacteria associates with altered gut ecology and can enable transfer of resistance genes, even in the absence of overt infection and antibiotic usage.

          Abstract

          Longitudinal shotgun metagenomics reveal changes in the gut microbial ecology upon carbapenemase-producing Enterobacteriaceae colonization and decolonization of adult subjects.

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          Most cited references76

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          Metagenomic biomarker discovery and explanation

          This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.
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            A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3.

            We describe a new computer program, SnpEff, for rapidly categorizing the effects of variants in genome sequences. Once a genome is sequenced, SnpEff annotates variants based on their genomic locations and predicts coding effects. Annotated genomic locations include intronic, untranslated region, upstream, downstream, splice site, or intergenic regions. Coding effects such as synonymous or non-synonymous amino acid replacement, start codon gains or losses, stop codon gains or losses, or frame shifts can be predicted. Here the use of SnpEff is illustrated by annotating ~356,660 candidate SNPs in ~117 Mb unique sequences, representing a substitution rate of ~1/305 nucleotides, between the Drosophila melanogaster w(1118); iso-2; iso-3 strain and the reference y(1); cn(1) bw(1) sp(1) strain. We show that ~15,842 SNPs are synonymous and ~4,467 SNPs are non-synonymous (N/S ~0.28). The remaining SNPs are in other categories, such as stop codon gains (38 SNPs), stop codon losses (8 SNPs), and start codon gains (297 SNPs) in the 5'UTR. We found, as expected, that the SNP frequency is proportional to the recombination frequency (i.e., highest in the middle of chromosome arms). We also found that start-gain or stop-lost SNPs in Drosophila melanogaster often result in additions of N-terminal or C-terminal amino acids that are conserved in other Drosophila species. It appears that the 5' and 3' UTRs are reservoirs for genetic variations that changes the termini of proteins during evolution of the Drosophila genus. As genome sequencing is becoming inexpensive and routine, SnpEff enables rapid analyses of whole-genome sequencing data to be performed by an individual laboratory.
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              CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database

              Abstract The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD’s Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.
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                Author and article information

                Contributors
                nagarajann@gis.a-star.edu.sg
                Journal
                Nat Microbiol
                Nat Microbiol
                Nature Microbiology
                Nature Publishing Group UK (London )
                2058-5276
                15 September 2022
                15 September 2022
                2022
                : 7
                : 10
                : 1516-1524
                Affiliations
                [1 ]GRID grid.418377.e, ISNI 0000 0004 0620 715X, Genome Institute of Singapore, ; Singapore, Singapore
                [2 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Yong Loo Lin School of Medicine, , National University of Singapore, ; Singapore, Singapore
                [3 ]GRID grid.240988.f, ISNI 0000 0001 0298 8161, Institute of Infectious Diseases and Epidemiology, , Tan Tock Seng Hospital, ; Singapore, Singapore
                Author information
                http://orcid.org/0000-0003-0850-5604
                Article
                1221
                10.1038/s41564-022-01221-w
                9519440
                36109646
                09e2cc34-cc6c-4bc8-839d-48fcbdb8ba8b
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 September 2021
                : 29 July 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001348, Agency for Science, Technology and Research (A*STAR);
                Award ID: IAF311018
                Award ID: IAF311018
                Award ID: IAF311018
                Award ID: IAF311018
                Award ID: IAF311018
                Award ID: IAF311018
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001349, MOH | National Medical Research Council (NMRC);
                Award ID: NMRC CGAug16C005
                Award ID: CIRG18nov-0034
                Award ID: NMRC CGAug16C005
                Award ID: NMRC/CSA-INV/0002/2016
                Award Recipient :
                Categories
                Letter
                Custom metadata
                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                antimicrobial resistance,microbiome,microbial genetics,microbial ecology,genome informatics

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