Recommendations for the use of metagenomics for routine monitoring of antibiotic resistance in wastewater and impacted aquatic environments-Reference-Cited by-同舟云学术

Recommendations for the use of metagenomics for routine monitoring of antibiotic resistance in wastewater and impacted aquatic environments

Published:2023-03-01 Issue:19 Volume:53 Page:1731-1756
ISSN:1064-3389
Container-title:Critical Reviews in Environmental Science and Technology
language:en
Short-container-title:Critical Reviews in Environmental Science and Technology

Author:

Davis Benjamin C.¹^ORCID,Brown Connor²^ORCID,Gupta Suraj²,Calarco Jeannette³,Liguori Krista¹^ORCID,Milligan Erin¹^ORCID,Harwood Valerie J.³^ORCID,Pruden Amy¹^ORCID,Keenum Ishi¹^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA

2. Department of Genetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, VA, USA

3. Department of Integrative Biology, University of South Florida, Tampa, FL, USA

Funder

Water Research Foundation

Publisher

Informa UK Limited

Subject

Pollution,Waste Management and Disposal,Water Science and Technology,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10643389.2023.2181620

Reference141 articles.

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2. Inhibition of histone deacetylase 1 (HDAC1) and HDAC2 enhances CRISPR/Cas9 genome editing

3. Andrews, S. (2010). FastQC: A quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/

4. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data

5. MetaStorm: A Public Resource for Customizable Metagenomics Annotation

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