Evidence map›Paper›PMID 36991496›Full record

ArticleEnvironmental microbiome2023

Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods.

Julie A Shay, Laura S E Haniford, Ashley Cooper, Catherine D Carrillo, Burton W Blais, Calvin Ho-Fung Lau

Open access · goldAbstract read
In one paragraph

Article in Environmental microbiome, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
8.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 42 citations in OpenAlex.

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  8. Antibiotic Resistance Genes and Microbiota inJournal of agricultural and food chemistry · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Julie A Shay *Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada.
Laura S E Haniford *Ottawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada.
Ashley CooperOttawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada.
Catherine D CarrilloOttawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada.
Burton W BlaisOttawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada.
Calvin Ho-Fung LauOttawa Laboratory (Carling), Canadian Food Inspection Agency, Ottawa, ON, Canada. calvin.lau@inspection.gc.ca.
Canadian Food Inspection Agency · CA

Funding

Canadian Food Inspection Agency,Canada N-000166Government of Canada Genomic Research and Development Initiatives GRDI-AMR
6 · The paper itself

Abstract

backgroundWith the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample's metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods.

resultA targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition.

conclusionsFor metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR.

Indexed as

AMR surveillanceFoodborne microbial hazardsMetagenomicsMethod developmentMicrobiomeResistomeTarget-capture sequencing

Identifiers

PMID36991496
PMCPMC10052294
OpenAlexW4361197586

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.