Literature DB >> 33531401

Metagenomic Quantification of Genes with Internal Standards.

Emily Crossette1, Jordan Gumm2, Kathryn Langenfeld1, Lutgarde Raskin1, Melissa Duhaime3, Krista Wigginton4.   

Abstract

We demonstrate that an assembly-independent and spike-in facilitated metagenomic quantification approach can be used to screen and quantify over 2,000 genes simultaneously, while delivering absolute gene concentrations comparable to those for quantitative PCR (qPCR). DNA extracted from dairy manure slurry, digestate, and compost was spiked with genomic DNA from a marine bacterium and sequenced using the Illumina HiSeq4000. We compared gene copy concentrations, in gene copies per mass of sample, of five antimicrobial resistance genes (ARGs) generated with (i) our quantitative metagenomic approach, (ii) targeted qPCR, and (iii) a hybrid quantification approach involving metagenomics and qPCR-based 16S rRNA gene quantification. Although qPCR achieved lower quantification limits, the metagenomic method avoided biases caused by primer specificity inherent to qPCR-based methods and was able to detect orders of magnitude more genes than is possible with qPCR assays. We used the approach to simultaneously quantify ARGs in the Comprehensive Antimicrobial Resistance Database (CARD). We observed that the total abundance of tetracycline resistance genes was consistent across different stages of manure treatment on three farms, but different samples were dominated by different tetracycline resistance gene families.IMPORTANCE qPCR and metagenomics are central molecular techniques that have offered insights into biological processes for decades, from monitoring spatial and temporal gene dynamics to tracking ARGs or pathogens. Still needed is a tool that can quantify thousands of relevant genes in a sample as gene copies per sample mass or volume. We compare a quantitative metagenomic approach with traditional qPCR approaches in the quantification of ARG targets in dairy manure samples. By leveraging the benefits of nontargeted community genomics, we demonstrate high-throughput absolute gene quantification of all known ARG sequences in environmental samples.
Copyright © 2021 Crossette et al.

Entities:  

Keywords:  antimicrobial resistance; gene quantification; metagenomics

Year:  2021        PMID: 33531401      PMCID: PMC7858063          DOI: 10.1128/mBio.03173-20

Source DB:  PubMed          Journal:  mBio            Impact factor:   7.867


  46 in total

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Authors:  Mads Albertsen; Lea Benedicte Skov Hansen; Aaron Marc Saunders; Per Halkjær Nielsen; Kåre Lehmann Nielsen
Journal:  ISME J       Date:  2011-12-15       Impact factor: 10.302

2.  ARGs-OAP v2.0 with an expanded SARG database and Hidden Markov Models for enhancement characterization and quantification of antibiotic resistance genes in environmental metagenomes.

Authors:  Xiaole Yin; Xiao-Tao Jiang; Benli Chai; Liguan Li; Ying Yang; James R Cole; James M Tiedje; Tong Zhang
Journal:  Bioinformatics       Date:  2018-07-01       Impact factor: 6.937

3.  Prevalence of antibiotic resistance genes in soils after continually applied with different manure for 30 years.

Authors:  Shuang Peng; Youzhi Feng; Yiming Wang; Xisheng Guo; Haiyan Chu; Xiangui Lin
Journal:  J Hazard Mater       Date:  2017-06-27       Impact factor: 10.588

4.  Absolute quantification of microbial taxon abundances.

Authors:  Ruben Props; Frederiek-Maarten Kerckhof; Peter Rubbens; Jo De Vrieze; Emma Hernandez Sanabria; Willem Waegeman; Pieter Monsieurs; Frederik Hammes; Nico Boon
Journal:  ISME J       Date:  2016-09-09       Impact factor: 10.302

5.  Benchmarking of methods for identification of antimicrobial resistance genes in bacterial whole genome data.

Authors:  Philip T L C Clausen; Ea Zankari; Frank M Aarestrup; Ole Lund
Journal:  J Antimicrob Chemother       Date:  2016-06-30       Impact factor: 5.790

6.  Antibiotic resistance gene abundances associated with antibiotics and heavy metals in animal manures and agricultural soils adjacent to feedlots in Shanghai; China.

Authors:  Xiuling Ji; Qunhui Shen; Fang Liu; Jing Ma; Gang Xu; Yuanlong Wang; Minghong Wu
Journal:  J Hazard Mater       Date:  2012-07-25       Impact factor: 10.588

7.  Metagenomic profiling of historic Colorado Front Range flood impact on distribution of riverine antibiotic resistance genes.

Authors:  Emily Garner; Joshua S Wallace; Gustavo Arango Argoty; Caitlin Wilkinson; Nicole Fahrenfeld; Lenwood S Heath; Liqing Zhang; Mazdak Arabi; Diana S Aga; Amy Pruden
Journal:  Sci Rep       Date:  2016-12-05       Impact factor: 4.379

8.  Fishing in the Soup - Pathogen Detection in Food Safety Using Metabarcoding and Metagenomic Sequencing.

Authors:  Josephine Grützke; Burkhard Malorny; Jens Andre Hammerl; Anne Busch; Simon H Tausch; Herbert Tomaso; Carlus Deneke
Journal:  Front Microbiol       Date:  2019-08-06       Impact factor: 5.640

9.  Metagenomics Reveals the Impact of Wastewater Treatment Plants on the Dispersal of Microorganisms and Genes in Aquatic Sediments.

Authors:  Binh T T Chu; Morgan L Petrovich; Adit Chaudhary; Dorothy Wright; Brian Murphy; George Wells; Rachel Poretsky
Journal:  Appl Environ Microbiol       Date:  2018-02-14       Impact factor: 4.792

10.  CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database.

Authors:  Brian P Alcock; Amogelang R Raphenya; Tammy T Y Lau; Kara K Tsang; Mégane Bouchard; Arman Edalatmand; William Huynh; Anna-Lisa V Nguyen; Annie A Cheng; Sihan Liu; Sally Y Min; Anatoly Miroshnichenko; Hiu-Ki Tran; Rafik E Werfalli; Jalees A Nasir; Martins Oloni; David J Speicher; Alexandra Florescu; Bhavya Singh; Mateusz Faltyn; Anastasia Hernandez-Koutoucheva; Arjun N Sharma; Emily Bordeleau; Andrew C Pawlowski; Haley L Zubyk; Damion Dooley; Emma Griffiths; Finlay Maguire; Geoff L Winsor; Robert G Beiko; Fiona S L Brinkman; William W L Hsiao; Gary V Domselaar; Andrew G McArthur
Journal:  Nucleic Acids Res       Date:  2020-01-08       Impact factor: 16.971

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  6 in total

Review 1.  Antimicrobial Resistance Monitoring of Water Environments: A Framework for Standardized Methods and Quality Control.

Authors:  Krista Liguori; Ishi Keenum; Benjamin C Davis; Jeanette Calarco; Erin Milligan; Valerie J Harwood; Amy Pruden
Journal:  Environ Sci Technol       Date:  2022-06-22       Impact factor: 11.357

2.  A Metagenomic Approach for Characterizing Antibiotic Resistance Genes in Specific Bacterial Populations: Demonstration with Escherichia coli in Cattle Manure.

Authors:  Bo Li; Xu Li; Bing Wang; Tao Yan
Journal:  Appl Environ Microbiol       Date:  2022-03-14       Impact factor: 5.005

3.  A Quantitative Metagenomic Sequencing Approach for High-Throughput Gene Quantification and Demonstration with Antibiotic Resistance Genes.

Authors:  Bo Li; Xu Li; Tao Yan
Journal:  Appl Environ Microbiol       Date:  2021-07-27       Impact factor: 4.792

4.  Multi-Omics Study of Keystone Species in a Cystic Fibrosis Microbiome.

Authors:  Cynthia B Silveira; Ana G Cobián-Güemes; Carla Uranga; Jonathon L Baker; Anna Edlund; Forest Rohwer; Douglas Conrad
Journal:  Int J Mol Sci       Date:  2021-11-07       Impact factor: 5.923

5.  Gut microbiome, enteric infections and child growth across a rural-urban gradient: protocol for the ECoMiD prospective cohort study.

Authors:  Gwenyth O Lee; Joseph N S Eisenberg; Jessica Uruchima; Gabriela Vasco; Shanon M Smith; Amanda Van Engen; Courtney Victor; Elise Reynolds; Rebecca MacKay; Kelsey J Jesser; Nancy Castro; Manuel Calvopiña; Konstantinos T Konstantinidis; William Cevallos; Gabriel Trueba; Karen Levy
Journal:  BMJ Open       Date:  2021-10-22       Impact factor: 2.692

6.  Diel investments in metabolite production and consumption in a model microbial system.

Authors:  Mario Uchimiya; William Schroer; Malin Olofsson; Arthur S Edison; Mary Ann Moran
Journal:  ISME J       Date:  2021-12-17       Impact factor: 11.217

  6 in total

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