Evidence map›Paper›PMID 38746293›Full record

ArticleResearch square2024

Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID pipeline.

Charles Langelier, Dan Lu, Katrina Kalantar, Victoria Chu, Abigail Glascock, Estella Guerrero, Nina Bernick, Xochitl Butcher, Kirsty Ewing, Elizabeth Fahsbender and 14 more

Abstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors.

Charles LangelierUniversity of California, San Francisco.ORCID 0000-0002-6708-4646
Dan LuChan Zuckerberg Initiative.
Katrina KalantarChan Zuckerberg Initiative.
Victoria ChuUCSF.
Abigail GlascockChan Zuckerberg Biohub.
Estella GuerreroNova Southeastern University.
Nina BernickChan Zuckerberg Initiative.
Xochitl ButcherChan Zuckerberg Initiative.
Kirsty EwingChan Zuckerberg Initiative.
Elizabeth FahsbenderChan Zuckerberg Initiative.
Olivia HolmesChan Zuckerberg Initiative.
Erin HoopsChan Zuckerberg Initiative.
Ann JonesChan Zuckerberg Initiative.ORCID 0000-0003-1148-7275
Ryan LimChan Zuckerberg Initiative.
Suzette McCannyChan Zuckerberg Initiative.
Lucia ReynosoChan Zuckerberg Initiative.
Karyna RosarioChan Zuckerberg Initiative.
Jennifer TangChan Zuckerberg Initiative.
Omar ValenzuelaChan Zuckerberg Initiative.
Peter MouraniArkansas Children's.ORCID 0000-0002-1829-3775
Amy PickeringUC Berkeley.
Amogelang RaphenyaMcMaster University.
Brian AlcockMcMaster University.
Andrew McArthurMcMaster University.ORCID 0000-0002-1142-3063

Funding

The Microbiome, Virome and Host Responses Preceding Ventilator-Associated PneumonR01HL124103 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI MOURANI, PETER M, SONTAG, MARCI K · 2014 to 2017
$2.7M
Integrated Host/Microbe Metagenomics to Improve Lower Respiratory Tract Infection Diagnosis in Critically Ill ChildrenR01HL155418 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LANGELIER, CHARLES · 2021 to 2024
$1.6M
Integrated Host/Microbe (IHM) Metagenomics of the Lower Airway to Diagnose PediatricRespiratory Infections, Identify Etiologic Pathogens, and Predict OutcomesR01AI182308 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Charles Langelier, Peter Michael Mourani · 2025 to 2026
$1.6M
NHLBI NIH HHS R01 HL124103NHLBI NIH HHS R01 HL155418NIAID NIH HHS R01 AI182308
6 · The paper itself

Abstract

Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the CZ ID AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.

Identifiers

PMID38746293
PMCPMC11092797

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LicenceCC BY
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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.