Evidence map›Paper›PMID 39500537›Full record

ArticleGenome research2024

Factors impacting target-enriched long-read sequencing of resistomes and mobilomes.

Ilya B Slizovskiy, Nathalie Bonin, Jonathan E Bravo, Peter M Ferm, Jacob Singer, Christina Boucher, Noelle R Noyes

Abstract read
In one paragraph

Article in Genome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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

7 authors.

Ilya B SlizovskiyFood-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota 55108, USA.ORCID 0000-0002-0758-5510
Nathalie BoninDepartment of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, Florida 32611, USA.ORCID 0009-0000-7936-8630
Jonathan E BravoDepartment of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, Florida 32611, USA.ORCID 0000-0002-4481-8766
Peter M FermFood-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota 55108, USA.ORCID 0009-0008-8873-0185
Jacob SingerFood-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota 55108, USA.ORCID 0009-0001-0890-2733
Christina BoucherDepartment of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, Florida 32611, USA.ORCID 0000-0001-9509-9725
Noelle R NoyesFood-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota 55108, USA; nnoyes@umn.edu.ORCID 0000-0001-6149-1008

Funding

Triple-enriched metagenomics for robust resistome analysisR01AI173928 · NIAID · UNIVERSITY OF MINNESOTA · PI Noelle Noyes · 2024 to 2026
$2.2M
Developing Computational Methods for Surveillance of Antimicrobial Resistant AgentsR01AI141810 · NIAID · UNIVERSITY OF FLORIDA · PI BOUCHER, CHRISTINA, PROSPERI, MATTIA · 2019 to 2023
$2.1M
NIAID NIH HHS R01 AI141810NIAID NIH HHS R01 AI173928
6 · The paper itself

Abstract

We investigated the efficiency of target-enriched long-read sequencing (TELSeq) for detecting antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) within complex matrices. We aimed to overcome limitations associated with traditional antimicrobial resistance (AMR) detection methods, including short-read shotgun metagenomics, which can lack sensitivity, specificity, and the ability to provide detailed genomic context. By combining biotinylated probe-based enrichment with long-read sequencing, we facilitated the amplification and sequencing of ARGs, eliminating the need for bioinformatic reconstruction. Our experimental design included replicates of human fecal microbiota transplant material, bovine feces, pristine prairie soil, and a mock human gut microbial community, allowing us to examine variables including genomic DNA input and probe set composition. Our findings demonstrated that TELSeq markedly improves the detection rates of ARGs and MGEs compared to traditional sequencing methods, underlining its potential for accurate AMR monitoring. A key insight from our research is the importance of incorporating mobilome profiles to better predict the transferability of ARGs within microbial communities, prompting a recommendation for the use of combined ARG-MGE probe sets for future studies. We also reveal limitations for ARG detection from low-input workflows, and describe the next steps for ongoing protocol refinement to minimize technical variability and expand utility in clinical and public health settings. This effort is part of our broader commitment to advancing methodologies that address the global challenge of AMR.

Indexed as

MetagenomicsAnimalsBacteriaCattleDrug Resistance, BacterialFecesGastrointestinal MicrobiomeHigh-Throughput Nucleotide SequencingHumansInterspersed Repetitive SequencesMetagenomeSequence Analysis, DNASoil Microbiology

Identifiers

PMID39500537
PMCPMC11610571

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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.