Metagenomic analysis of antimicrobial resistance

Antimicrobial resistance genes were detected using ABRicate v0.9.9⁵⁹, using the following databases (Jan 2020): NCBI AMRFinder Plus, Resfinder, and Comprehensive Antibiotic Resistance Database (CARD). Each gene was filtered by coverage (≥ 70%) and identity (≥ 80%). Filtered ARGs were manually classified by type of antibiotic and resistance mechanism (Supplementary Data 2). To determine the abundance of ARGs in the microbiome, htseq-count v0.12.4^{60 (link)} was used with a manually curated ARG list, in which one gene ID was selected for genes with multiple synonyms (Supplementary Data 10–12). Taxonomic profiling of contigs was performed with Kraken2 v.2.08^{61 (link)} and Bracken v2.6.0^{62 (link)} using contigs against the Kraken ‘standard’ database (build date 23 April 2020)⁶³. Insertion sequences were identified from filtered contigs using Prokka v.1.14.5^{64 (link)} and annotated using ISFinder database^{65 (link)} (update 2019-09-25). Functional profiling of contigs was performed using HUMAnN2 v2.8.2^{66 (link)}, with functional pathways in each sample classified against UniRef90 and chocophlan databases. Values reported are normalised as counts per million (CPM).

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Sukumar S., Wang F., Simpson C.A., Willet C.E., Chew T., Hughes T.E., Bockmann M.R., Sadsad R., Martin F.E., Lydecker H.W., Browne G.V., Davis K.M., Bui M., Martinez E, & Adler C.J. (2023). Development of the oral resistome during the first decade of life. Nature Communications, 14, 1291.

Publication 2023

Antibiotic Antibiotic resistance Antimicrobial Genes Insertion sequences Microbiome

Corresponding Organization : University of Sydney

Other organizations : University of California, Los Angeles, University of Adelaide, Westmead Institute, University of Melbourne, New South Wales Department of Health

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Variable analysis

independent variables

Antimicrobial resistance genes detection using ABRicate v0.9.9
Databases used: NCBI AMRFinder Plus, Resfinder, and Comprehensive Antibiotic Resistance Database (CARD)
Filtering criteria: coverage (≥ 70%) and identity (≥ 80%)
Manual classification of filtered ARGs by type of antibiotic and resistance mechanism

dependent variables

Abundance of ARGs in the microbiome
Taxonomic profiling of contigs using Kraken2 v.2.08 and Bracken v2.6.0
Identification of insertion sequences from filtered contigs using Prokka v.1.14.5 and ISFinder database
Functional profiling of contigs using HUMAnN2 v2.8.2

control variables

Manually curated ARG list, in which one gene ID was selected for genes with multiple synonyms

positive controls

No positive controls were explicitly mentioned.

negative controls

No negative controls were explicitly mentioned.

Annotations

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