Evidence map›Paper›PMID 40360786›Full record

ArticleCommunications biology2025

Genetic landscape and evolution of Acinetobacter pittii, an underestimated emerging nosocomial pathogen.

Shengke Wang, Yan Zhou, Yuezhuo Wang, Keshu Tang, Danqi Wang, Jiawen Hong, Pengcheng Wang, Sheng Ye, Jie Yan, Shengkai Li and 2 more

Abstract read
In one paragraph

Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. mSphere · 2026
    Article
  3. Article
  4. Genomic Characterization of a Carbapenem-ResistantPathogens (Basel, Switzerland) · 2025
    Article
  5. Threat and Control ofFoods (Basel, Switzerland) · 2025
    Review
  6. 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

12 authors.

Shengke Wang *Wenzhou Key Laboratory of Sanitary Microbiology, Department of Microbiology and Immunology, School of Laboratory Medicine, Institute of One Health, Wenzhou Medical University, Wenzhou, China.
Yan Zhou *School of Medicine, Zhejiang University, Hangzhou, China.
Yuezhuo WangKey Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China.
Keshu TangWenzhou Key Laboratory of Sanitary Microbiology, Department of Microbiology and Immunology, School of Laboratory Medicine, Institute of One Health, Wenzhou Medical University, Wenzhou, China.
Danqi WangWenzhou Key Laboratory of Sanitary Microbiology, Department of Microbiology and Immunology, School of Laboratory Medicine, Institute of One Health, Wenzhou Medical University, Wenzhou, China.
Jiawen HongWenzhou Key Laboratory of Sanitary Microbiology, Department of Microbiology and Immunology, School of Laboratory Medicine, Institute of One Health, Wenzhou Medical University, Wenzhou, China.
Pengcheng WangWenzhou Key Laboratory of Sanitary Microbiology, Department of Microbiology and Immunology, School of Laboratory Medicine, Institute of One Health, Wenzhou Medical University, Wenzhou, China.
Sheng YeWenzhou Key Laboratory of Sanitary Microbiology, Department of Microbiology and Immunology, School of Laboratory Medicine, Institute of One Health, Wenzhou Medical University, Wenzhou, China.
Jie YanSchool of Medicine, Zhejiang University, Hangzhou, China. med_bp@zju.edu.cn.ORCID http://orcid.org/0000-0003-2054-6986
Shengkai LiKey Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China. Zxzzzhu@Gmail.com.ORCID http://orcid.org/0000-0002-7865-697X
Zhemin ZhouKey Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China. zmzhou@suda.edu.cn.ORCID http://orcid.org/0000-0001-9783-0366
Jimei DuWenzhou Key Laboratory of Sanitary Microbiology, Department of Microbiology and Immunology, School of Laboratory Medicine, Institute of One Health, Wenzhou Medical University, Wenzhou, China. djm@wmu.edu.cn.ORCID http://orcid.org/0000-0002-6553-210X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a member of Acinetobacter calcoaceticus-baumannii complex, Acinetobacter pittii has been an emerging concern in nosocomial infection due to its increasing prevalence and multidrug resistance (MDR). However, its population structure remains broadly unknown, hampering efficient tracing of its transmission and evolution. In this study, we developed a distributed core genome multilocus sequence typing (dcgMLST) for A. pittii based on 750 genomes and employed it to map the genetic landscape and evolution of A. pittii. The results demonstrated that two hierarchical clustering (HC) levels effectively correspond to genetic diversity from species (HC1100) to natural populations (HC450), as well as that a predominant lineage, HC1100_4, accounts for 33.9% of A. pittii strains. Subsequent analysis revealed that specific gene gain and loss events within HC1100_4 are linked to adaptations to environmental stress. Moreover, we identified a cluster of multidrug-resistant plasmids PT_712 responsible for the dissemination of bla

Indexed as

AcinetobacterAcinetobacter InfectionsCross InfectionEvolution, MolecularDrug Resistance, Multiple, BacterialGenetic VariationGenome, BacterialHumansMultilocus Sequence TypingPhylogeny

Identifiers

PMID40360786
PMCPMC12075791

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.