Evidence map›Paper›PMID 40991631›Full record

ArticlePLoS neglected tropical diseases2025

Proteomic-based identification of novel EV-derived protein antibodies biomarkers for melioidosis diagnosis.

Nini Luo, Jun Tan, Xuemiao Li, Yanshuang Wang, Ting Zhang, Chen Chen, Lin Liu, Xinyi Song, Hua Pei, Bo Wang and 5 more

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 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. Review
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

15 authors.

Nini LuoNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Jun TanNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Xuemiao LiNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Yanshuang WangThe Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
Ting ZhangNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Chen ChenNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Lin LiuNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Xinyi SongNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Hua PeiThe Second Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
Bo WangCentral Laboratory, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, PR China.
Qi LiThe First Affiliated Hospital, Hainan Medical University, Haikou, Hainan, China.
Shen TianNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Nan ZhangNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.
Wei ChengThe Center for Clinical Molecular Medical Detection, The First Affiliated Hospital of Chongqing Medical University, Chongqing, P.R. China.
Qianfeng XiaNHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan, China.ORCID 0000-0001-5521-5664

Funding

Major Science and Technology Program of Hainan ProvinceNational Natural Science Foundation of ChinaState Key Research Development Program of China
6 · The paper itself

Abstract

Melioidosis, caused by Burkholderia pseudomallei (Bp), is a life-threatening disease characterized by diverse clinical manifestations and limited diagnostic capabilities. Extracellular vesicles (EVs) have emerged as critical carriers of novel antibody targets for serodiagnosis. In this study, we established a Bp-infected BEAS-2B cell model (Bp/BEAS-2B) and isolated EV from both Bp and Bp/BEAS-2B cells to generate EV proteome, identifying potential antigenic biomarkers for melioidosis diagnosis. Bioinformatics analysis identified PPEP and POMCR proteins as candidate antigens, with BLF1 and omp A serving as positive controls. Using a self-developed IgM-ELISA, serum samples from 43 melioidosis patients and 47 healthy volunteers were analyzed to detect antibodies against these antigens. Anti-POMCR IgM demonstrated exceptional diagnostic performance, with an AUC of 0.9872 (95% CI: 0.9713-1.003), sensitivity of 93.02% and specificity of 97.92% at a cutoff value of OD450 = 0.118. Similarly, IgM against PPEP, BLF1, and omp A also showed high diagnostic accuracy, with AUC values of 0.969, 0.9621, and 0.976, respectively. The accuracy of anti-POMCR and anti-PPEP were 96.43% and 95.54%, respectively, equivalent to anti-omp A (93.75%) and anti-BLF1 (91.96%). Antibodies to EV-derived proteins effectively differentiated melioidosis patients from other bacterial infections and healthy volunteers, highlighting their clinical potential as diagnostic tools for melioidosis.

Indexed as

Antibodies, BacterialBurkholderia pseudomalleiExtracellular VesiclesMelioidosisAdultAntigens, BacterialBacterial ProteinsBiomarkersCell LineEnzyme-Linked Immunosorbent AssayFemaleHumansImmunoglobulin MMaleMiddle AgedProteomeAntibodies, BacterialAntigens, BacterialBacterial ProteinsBiomarkersImmunoglobulin MProteome

Identifiers

PMID40991631
PMCPMC12459824

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.