Evidence map›Paper›PMID 39521944›Full record

ArticleFEMS microbiology ecology2024

MetaCompare 2.0: differential ranking of ecological and human health resistome risks.

Monjura Afrin Rumi, Min Oh, Benjamin C Davis, Connor L Brown, Adheesh Juvekar, Peter J Vikesland, Amy Pruden, Liqing Zhang

Abstract read
In one paragraph

Article in FEMS microbiology ecology, 2024. 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
–field-weighted citation impact
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.

  1. Soil management practices shape the abundance, diversity, and spread of antimicrobial resistance.Proceedings of the National Academy of Sciences of the United States of America · 2026
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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

8 authors.

Monjura Afrin RumiDepartment of Computer Science, Virginia Tech, Blacksburg, VA 24060, USA.ORCID 0009-0002-7353-8058
Min OhDepartment of Computer Science, Virginia Tech, Blacksburg, VA 24060, USA.
Benjamin C DavisOffice of Research and Development, US Environmental Protection Agency, Cincinnati, OH 45268, USA.
Connor L BrownDepartment of Civil & Environmental Engineering, Virginia Tech, Blacksburg, VA 24060,  USA.
Adheesh JuvekarDepartment of Computer Science, Virginia Tech, Blacksburg, VA 24060, USA.
Peter J VikeslandDepartment of Civil & Environmental Engineering, Virginia Tech, Blacksburg, VA 24060,  USA.
Amy PrudenDepartment of Civil & Environmental Engineering, Virginia Tech, Blacksburg, VA 24060,  USA.
Liqing ZhangDepartment of Computer Science, Virginia Tech, Blacksburg, VA 24060, USA.

Funding

National Science Foundation #2004751Water Research Foundation 4813
6 · The paper itself

Abstract

While numerous environmental factors contribute to the spread of antibiotic resistance genes (ARGs), quantifying their relative contributions remains a fundamental challenge. Similarly, it is important to differentiate acute human health risks from environmental exposure, versus broader ecological risk of ARG evolution and spread across microbial taxa. Recent studies have proposed various methods for achieving such aims. Here, we introduce MetaCompare 2.0, which improves upon original MetaCompare pipeline by differentiating indicators of human health resistome risk (potential for human pathogens of acute resistance concern to acquire ARGs) from ecological resistome risk (overall mobility of ARGs and potential for pathogen acquisition). The updated pipeline's sensitivity was demonstrated by analyzing diverse publicly-available metagenomes from wastewater, surface water, soil, sediment, human gut, and synthetic microbial communities. MetaCompare 2.0 provided distinct rankings of the metagenomes according to both human health resistome risk and ecological resistome risk, with both scores trending higher when influenced by anthropogenic impact or other stress. We evaluated the robustness of the pipeline to sequence assembly methods, sequencing depth, contig count, and metagenomic library coverage bias. The risk scores were remarkably consistent despite variations in these technological aspects. We packaged the improved pipeline into a publicly-available web service (http://metacompare.cs.vt.edu/) that provides an easy-to-use interface for computing resistome risk scores and visualizing results.

Indexed as

BacteriaDrug Resistance, BacterialEnvironmental MicrobiologySoftwareBacterial InfectionsEcologyEpidemiological MonitoringHumansMetagenomeRisk Factorsantibiotic resistance geneassembly methodecological resistome riskhuman health resistome riskresistome risksequencing depth

Identifiers

PMID39521944
PMCPMC12116288

What OpenQuestion holds

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LicenceCC BY-NC
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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.