Evidence map›Paper›PMID 41678533›Full record

ArticlePLoS pathogens2026

Identification of multiple Acinetobacter baumannii protein antigens as targets for potential immunotherapies using a novel protein microarray screening approach.

Samantha Palethorpe, Giuseppe Ercoli, Elisa Ramos-Sevillano, Gathoni Kamuyu, Joe Campo, Samuel Willcocks, Rie Nakajima, Philip Felgner, Brendan Wren, Ganjana Lertmemongkolchai and 2 more

Abstract read
In one paragraph

Article in PLoS pathogens, 2026. 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

12 authors.

Samantha PalethorpeUCL Respiratory, University College London, London, United Kingdom.
Giuseppe ErcoliUCL Respiratory, University College London, London, United Kingdom.
Elisa Ramos-SevillanoUCL Respiratory, University College London, London, United Kingdom.
Gathoni KamuyuUCL Respiratory, University College London, London, United Kingdom.
Joe CampoAntigen Discovery Inc., Irvine, California, United States of America.
Samuel WillcocksDepartment of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Rie NakajimaVaccine Research and Development Center, Department of Physiology and Biophysics, University of California Irvine, Irvine, California, United States of America.
Philip FelgnerVaccine Research and Development Center, Department of Physiology and Biophysics, University of California Irvine, Irvine, California, United States of America.
Brendan WrenDepartment of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Ganjana LertmemongkolchaiCellular and Molecular Immunology Unit, Centre for Research and Development of Medical Diagnostic Laboratories (CMDL), Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen, Thailand.
Richard StablerDepartment of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Jeremy BrownUCL Respiratory, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-5650-5361

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The World Health Organisation has identified Acinetobacter baumannii as a critical priority antimicrobial resistant (AMR) pathogen for which new therapeutics are needed. Despite this, currently there are no antibody or vaccine candidates in advanced clinical development for A. baumannii. To help address this, we designed a protein microarray approach to identify multiple A. baumannii protein antigens for further investigation as potential targets for vaccination or an antibody therapy. An 868-protein microarray was constructed containing mainly highly conserved A. baumannii proteins, and was enriched for those predicted to be surface localised and for which the corresponding gene is highly expressed during culture in ex vivo human serum. Probing the protein microarray with sera obtained from mice after non-lethal infection with multiple different A. baumannii strains identified IgG responses to 66 proteins. Four proteins (three previously poorly described outer membrane proteins and BamA, a known protective vaccine antigen selected as a positive control) were selected for further investigation. Polyclonal rabbit IgG to all four protein antigens recognised multiple clinical AMR A. baumannii strains, and for selected strains promoted opsonisation with IgG and complement, improved neutrophil phagocytosis, and increased membrane attack complex formation. Passive immunisation with polyclonal IgG to each antigen partially protected mice against A. baumannii sepsis, and a combination of polyclonal to two antigens completely protected against A. baumannii murine sepsis. Repeating passive immunisation experiments in mice depleted of complement, neutrophils or tissue macrophages demonstrated protection against systemic infection was dependent on complement and neutrophils but not macrophages. Overall, the data demonstrate that our protein microarray is a novel approach that can rapidly identify multiple new protein antigens as potential antibody targets for preventing or treating AMR bacterial infections.

Indexed as

Acinetobacter baumanniiAcinetobacter InfectionsAntigens, BacterialBacterial ProteinsImmunotherapyProtein Array AnalysisAnimalsAntibodies, BacterialBacterial VaccinesFemaleHumansImmunoglobulin GMiceMice, Inbred C57BLRabbitsAntibodies, BacterialAntigens, BacterialBacterial ProteinsBacterial VaccinesImmunoglobulin G

Identifiers

PMID41678533
PMCPMC12919932

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.