Evidence map›Paper›PMID 30886350›Full record

ReviewNature reviews. Genetics2019

Sequencing-based methods and resources to study antimicrobial resistance.

Manish Boolchandani, Alaric W D'Souza, Gautam Dantas

Registry-linked trialAbstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06566898 (Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients), which is not on this map. Cited by 267 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
267citing papers in PubMed, 3 pooled it
–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.

NCT06566898 recruitingnot on this mapstarted 2024, after this paper: background citation

Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients: a Genomic Epidemiology Study

TypeobservationalSponsorShanghai General Hospital, ChinaRan2024 to 2026Enrolled800ConditionsPneumonia, Next-generation Sequencing, Microbiome, Antimicrobial Resistance
3 · Its place in the literature

Who cites it

267 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Review
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  11. Genomic diversity of multidrug-resistantApplied and environmental microbiology · 2026
    Article
  12. Article
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  15. Metabolism-Based Biomarkers for Rapid Phenotypic Antibiotic Susceptibility Testing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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  17. Review
  18. Review
  19. Article
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207 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Manish BoolchandaniThe Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID http://orcid.org/0000-0001-6038-8957
Alaric W D'SouzaThe Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.ORCID http://orcid.org/0000-0002-8744-8136
Gautam DantasThe Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA. dantas@wustl.edu.ORCID http://orcid.org/0000-0003-0455-8370

Funding

STRUCTURAL, MECHANISTIC, & EVOLUTIONARY CHARACTERIZATION OF TETRACYCLINE DESTRUCTASESU01AI123394 · NIAID · WASHINGTON UNIVERSITY · PI DANTAS, GAUTAM, WENCEWICZ, TIMOTHY ADAM · 2020 to 2025
$4.1M
Tunable therapeutic modulation of the gut microbiome by engineered probioticsR01AT009741 · NCCIH · WASHINGTON UNIVERSITY · PI DANTAS, GAUTAM, MOON, TAE SEOK · 2018 to 2022
$3.5M
PHYLOGENOMIC, TRANSCRIPTOMIC, VIROMIC, AND IMMUNOPROTEOMIC DETERMINANTS OF NECROTIZING ENTEROCOLITISR01HD092414 · NICHD · WASHINGTON UNIVERSITY · PI DANTAS, GAUTAM, TARR, PHILLIP I · 2017 to 2021
$3.0M
STRUCTURAL, MECHANISTIC, & EVOLUTIONARY CHARACTERIZATION OF TETRACYCLINE DESTRUCTASESR01AI123394 · NIAID · WASHINGTON UNIVERSITY · PI DANTAS, GAUTAM, WENCEWICZ, TIMOTHY ADAM · 2016 to 2019
$2.7M
NCCIH NIH HHS R01 AT009741NIAID NIH HHS R01 AI123394NIAID NIH HHS U01 AI123394NICHD NIH HHS R01 HD092414
6 · The paper itself

Abstract

Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies.

Indexed as

Genome, BacterialAnti-Bacterial AgentsBacteriaBacterial InfectionsBase SequenceDrug Resistance, Multiple, BacterialHigh-Throughput Nucleotide SequencingHumansMachine LearningMetagenomicsSequence Analysis, DNAWhole Genome SequencingAnti-Bacterial Agents

Identifiers

PMID30886350
PMCPMC6525649

What OpenQuestion holds

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Registered trials

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.