Evidence map›Paper›PMID 34100643›Full record

ArticlemSystems2021

Whole-Genome Sequencing and Machine Learning Analysis of Staphylococcus aureus from Multiple Heterogeneous Sources in China Reveals Common Genetic Traits of Antimicrobial Resistance.

Wei Wang, Michelle Baker, Yue Hu, Jin Xu, Dajin Yang, Alexandre Maciel-Guerra, Ning Xue, Hui Li, Shaofei Yan, Menghan Li and 6 more

Open access · goldAbstract read
In one paragraph

Article in mSystems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 14% of its field
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Genomic and clinical characteristics ofMicrobiology spectrum · 2026
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Investigating genomic diversity ofFrontiers in microbiology · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. The Plasmidomic Landscape of Clinical Methicillin-ResistantAntibiotics (Basel, Switzerland) · 2023
    Article
  19. A food poisoning caused by ST7Frontiers in microbiology · 2023
    Article
  20. Whole-Genome Analysis ofFoods (Basel, Switzerland) · 2022
    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

16 authors at 2 institutions in 2 countries.

Wei WangNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Michelle BakerSchool of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington, Leicestershire, United Kingdom.
Yue HuSchool of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington, Leicestershire, United Kingdom.
Jin XuNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Dajin YangNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Alexandre Maciel-GuerraSchool of Computer Science, University of Nottingham, Nottingham, United Kingdom.
Ning XueSchool of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington, Leicestershire, United Kingdom.
Hui LiNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Shaofei YanNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Menghan LiNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Yao BaiNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Yinping DongNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Zixin PengNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Jinjing MaNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Fengqin LiNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Tania DottoriniSchool of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington, Leicestershire, United Kingdom.
China National Center for Food Safety Risk Assessment · CNUniversity of Nottingham · GB

Funding

Ministry of Science and Technology of the People's Republic of China (MOST) 2018YFE0101500UK Research and Innovation (UKRI) 104986
6 · The paper itself

Abstract

Staphylococcus aureus is a worldwide leading cause of numerous diseases ranging from food-poisoning to lethal infections. Methicillin-resistant S. aureus (MRSA) has been found capable of acquiring resistance to most antimicrobials. MRSA is ubiquitous and diverse even in terms of antimicrobial resistance (AMR) profiles, posing a challenge for treatment. Here, we present a comprehensive study of S. aureus in China, addressing epidemiology, phylogenetic reconstruction, genomic characterization, and identification of AMR profiles. The study analyzes 673 S. aureus isolates from food as well as from hospitalized and healthy individuals. The isolates have been collected over a 9-year period, between 2010 and 2018, from 27 provinces across China. By whole-genome sequencing, Bayesian divergence analysis, and supervised machine learning, we reconstructed the phylogeny of the isolates and compared them to references from other countries. We identified 72 sequence types (STs), of which, 29 were novel. We found 81 MRSA lineages by multilocus sequence type (MLST),

Indexed as

antimicrobial resistanceBayesian divergence analysisfoodborne pathogenmethicillin-resistant Staphylococcus aureus (MRSA)Staphylococcus aureussupervised machine learningwhole-genome sequencing

Identifiers

PMID34100643
PMCPMC8579812
OpenAlexW3166070247

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.