Literature DB >> 33747038

Toward Accurate and Robust Environmental Surveillance Using Metagenomics.

Jiaxian Shen1, Alexander G McFarland1, Vincent B Young2, Mary K Hayden3, Erica M Hartmann1.   

Abstract

Environmental surveillance is a critical tool for combatting public health threats represented by the global COVID-19 pandemic and the continuous increase of antibiotic resistance in pathogens. With its power to detect entire microbial communities, metagenomics-based methods stand out in addressing the need. However, several hurdles remain to be overcome in order to generate actionable interpretations from metagenomic sequencing data for infection prevention. Conceptually and technically, we focus on viability assessment, taxonomic resolution, and quantitative metagenomics, and discuss their current advancements, necessary precautions and directions to further development. We highlight the importance of building solid conceptual frameworks and identifying rational limits to facilitate the application of techniques. We also propose the usage of internal standards as a promising approach to overcome analytical bottlenecks introduced by low biomass samples and the inherent lack of quantitation in metagenomics. Taken together, we hope this perspective will contribute to bringing accurate and consistent metagenomics-based environmental surveillance to the ground.
Copyright © 2021 Shen, McFarland, Young, Hayden and Hartmann.

Entities:  

Keywords:  environmental surveillance; limit of detection; metagenomics; quantitative metagenomics; taxonomic resolution; viability

Year:  2021        PMID: 33747038      PMCID: PMC7973286          DOI: 10.3389/fgene.2021.600111

Source DB:  PubMed          Journal:  Front Genet        ISSN: 1664-8021            Impact factor:   4.599


  59 in total

1.  Quantitative metagenomic analyses based on average genome size normalization.

Authors:  Jeremy A Frank; Søren J Sørensen
Journal:  Appl Environ Microbiol       Date:  2011-02-11       Impact factor: 4.792

2.  Use of synthetic DNA spike-in controls (sequins) for human genome sequencing.

Authors:  James Blackburn; Ted Wong; Bindu Swapna Madala; Chris Barker; Simon A Hardwick; Andre L M Reis; Ira W Deveson; Tim R Mercer
Journal:  Nat Protoc       Date:  2019-06-19       Impact factor: 13.491

Review 3.  Benchmarking Metagenomics Tools for Taxonomic Classification.

Authors:  Simon H Ye; Katherine J Siddle; Daniel J Park; Pardis C Sabeti
Journal:  Cell       Date:  2019-08-08       Impact factor: 41.582

4.  Estimating the total exposure to air pollutants for different population age groups in Hong Kong.

Authors:  C K Chau; E Y Tu; D W T Chan; J Burnett
Journal:  Environ Int       Date:  2002-03       Impact factor: 9.621

5.  Relationship between chlorhexidine gluconate skin concentration and microbial density on the skin of critically ill patients bathed daily with chlorhexidine gluconate.

Authors:  Kyle J Popovich; Rosie Lyles; Robert Hayes; Bala Hota; William Trick; Robert A Weinstein; Mary K Hayden
Journal:  Infect Control Hosp Epidemiol       Date:  2012-07-23       Impact factor: 3.254

6.  Consistent and correctable bias in metagenomic sequencing experiments.

Authors:  Michael R McLaren; Amy D Willis; Benjamin J Callahan
Journal:  Elife       Date:  2019-09-10       Impact factor: 8.140

7.  Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data.

Authors:  Nicole M Davis; Diana M Proctor; Susan P Holmes; David A Relman; Benjamin J Callahan
Journal:  Microbiome       Date:  2018-12-17       Impact factor: 14.650

8.  Whole microbial community viability is not quantitatively reflected by propidium monoazide sequencing approach.

Authors:  Ya Wang; Yan Yan; Kelsey N Thompson; Sena Bae; Emma K Accorsi; Yancong Zhang; Jiaxian Shen; Hera Vlamakis; Erica M Hartmann; Curtis Huttenhower
Journal:  Microbiome       Date:  2021-01-21       Impact factor: 14.650

9.  Evaluating the Information Content of Shallow Shotgun Metagenomics.

Authors:  Benjamin Hillmann; Gabriel A Al-Ghalith; Robin R Shields-Cutler; Qiyun Zhu; Daryl M Gohl; Kenneth B Beckman; Rob Knight; Dan Knights
Journal:  mSystems       Date:  2018-11-13       Impact factor: 6.496

10.  Sensitivity of shotgun metagenomics to host DNA: abundance estimates depend on bioinformatic tools and contamination is the main issue.

Authors:  Andrew J McArdle; Myrsini Kaforou
Journal:  Access Microbiol       Date:  2020-02-17
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  1 in total

1.  Shotgun-metagenomics based prediction of antibiotic resistance and virulence determinants in Staphylococcus aureus from periprosthetic tissue on blood culture bottles.

Authors:  Adriana Maria Sanabria; Jessin Janice; Erik Hjerde; Gunnar Skov Simonsen; Anne-Merethe Hanssen
Journal:  Sci Rep       Date:  2021-10-21       Impact factor: 4.379

  1 in total

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