Evidence map›Paper›PMID 41068594›Full record

ArticleBMC microbiology2025

A new approach for establishing multilocus sequence typing scheme: Staphylococcus capitis as an example.

Zhengan Wang, Lu Sun, Junxiong Zhang, Lingfang Di, Junxin Zhou, Huangdu Hu, Hemu Zhuang, Qiucheng Shi, Xueqing Wu, Feng Zhao and 10 more

Abstract read
In one paragraph

Article in BMC microbiology, 2025. 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

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

20 authors.

Zhengan WangDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Lu SunDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Junxiong ZhangKey Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China.
Lingfang DiKey Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, China.
Junxin ZhouDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Huangdu HuDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Hemu ZhuangDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Qiucheng ShiDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xueqing WuDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Feng ZhaoDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang province, China.
Dandan WuDepartment of Infectious Diseases, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Shengnan JiangDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Chao GuDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Haiping WangDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Feiteng ZhuDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yiyi ChenDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Mengzhen ChenDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Shiqi CaiDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yunsong YuDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China. yvys119@zju.edu.cn.
Yan ChenDepartment of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China. chenyan@zju.edu.cn.

Funding

medical and health science and technology projects of Zhejiang Province 2019KY427
6 · The paper itself

Abstract

Reliable and efficient typing methods for Staphylococcus capitis, an opportunistic pathogen of growing clinical and epidemiological concern, are urgently needed to support microbial epidemiological studies. In the study, we present a novel workflow for developing a multilocus sequence typing (MLST) scheme tailored to S. capitis. Core genome analysis of 603 high-quality S. capitis genomes revealed 2,065 core genes. A hierarchical filtering strategy, including gene, fragment, and combination filters, was applied to select loci that balance discriminatory power and cluster specificity. The final MLST scheme comprised fragments from seven genes: mntC, phoA, atpB_2, hisS, rluB, carB, and clpP. Using this approach, we assigned 39 sequence types (STs) and defined five clonal complexes. The MLST typing results were highly concordant with phylogenetic analysis and demonstrated considerable discriminatory power. Notably, the globally prevalent NRCS-A clone and the linezolid-resistant L clone were designated as ST1 and ST6, respectively. Overall, we developed a reliable, high-resolution MLST scheme for S. capitis that enables accurate characterization of its population structure and facilitates monitoring of multidrug-resistant lineages.

Indexed as

Multilocus Sequence TypingStaphylococcus capitisDNA, BacterialGenome, BacterialHumansPhylogenyStaphylococcal InfectionsDNA, BacterialDrug-resistance.EpidemiologyMicrobiologyMLST

Identifiers

PMID41068594
PMCPMC12513078

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.