Evidence map›Paper›PMID 28943406›Full record

ReviewInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2018

Microbial sequence typing in the genomic era.

Marcos Pérez-Losada, Miguel Arenas, Eduardo Castro-Nallar

Abstract readReview
In one paragraph

Review in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 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.

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

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Molecular typing ofApplied and environmental microbiology · 2026
    Article
  3. Article
  4. Typing ofMicroorganisms · 2025
    Article
  5. Article
  6. Genomic diversity and tracing ofMicrobial genomics · 2025
    Article
  7. Article
  8. Laboratory Methods for Culture and Identification.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  9. Contamination of Plant Foods withMicroorganisms · 2023
    Article
  10. Article
  11. Article
  12. Genetic analysis of plasmid-encodedJAC-antimicrobial resistance · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Antibiotic resistance: Time of synthesis in a post-genomic age.Computational and structural biotechnology journal · 2021
    Review
  20. 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

3 authors.

Marcos Pérez-LosadaComputational Biology Institute, Milken Institute School of Public Health, George Washington University, Ashburn, VA 20147, USA; CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, Vairão 4485-661, Portugal; Children's National Medical Center, Washington, DC 20010, USA. Electronic address: mlosada@gwu.edu.
Miguel ArenasDepartment of Biochemistry, Genetics and Immunology, University of Vigo, Vigo, Spain.
Eduardo Castro-NallarUniversidad Andrés Bello, Center for Bioinformatics and Integrative Biology, Facultad de Ciencias Biológicas, Santiago 8370146, Chile.

Funding

SWG 2: Cure Research Scientific Working GroupP30AI117970 · NIAID · GEORGE WASHINGTON UNIVERSITY · PI Italo Mocchetti · 2015 to 2026
$29.6M
The District of Columbia Developmental Center for AIDS Research (DC D-CFAR)P30AI087714 · NIAID · GEORGE WASHINGTON UNIVERSITY · PI MILLER, VERONICA · 2010 to 2014
$8.4M
K12 Career Development Program: Omics of Pediatric Lung Diseases in DCK12HL119994 · NHLBI · CHILDREN'S RESEARCH INSTITUTE · PI FREISHTAT, ROBERT J · 2013 to 2017
$1.3M
NHLBI NIH HHS K12 HL119994NIAID NIH HHS P30 AI087714NIAID NIH HHS P30 AI117970
6 · The paper itself

Abstract

Next-generation sequencing (NGS), also known as high-throughput sequencing, is changing the field of microbial genomics research. NGS allows for a more comprehensive analysis of the diversity, structure and composition of microbial genes and genomes compared to the traditional automated Sanger capillary sequencing at a lower cost. NGS strategies have expanded the versatility of standard and widely used typing approaches based on nucleotide variation in several hundred DNA sequences and a few gene fragments (MLST, MLVA, rMLST and cgMLST). NGS can now accommodate variation in thousands or millions of sequences from selected amplicons to full genomes (WGS, NGMLST and HiMLST). To extract signals from high-dimensional NGS data and make valid statistical inferences, novel analytic and statistical techniques are needed. In this review, we describe standard and new approaches for microbial sequence typing at gene and genome levels and guidelines for subsequent analysis, including methods and computational frameworks. We also present several applications of these approaches to some disciplines, namely genotyping, phylogenetics and molecular epidemiology.

Indexed as

Bacterial Typing TechniquesGenome, BacterialAllelesBacterial InfectionsClone CellsGram-Negative BacteriaGram-Positive BacteriaGuidelines as TopicHigh-Throughput Nucleotide SequencingHumansMinisatellite RepeatsMolecular EpidemiologyMultilocus Sequence TypingPhylogenyPolymorphism, Single NucleotideSequence Analysis, DNABacteriaEpidemiologyMLSTPathogenTypingWGS

Identifiers

PMID28943406
PMCPMC5908768

What OpenQuestion holds

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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.