Evidence map›Paper›PMID 40677719›Full record

ArticleFrontiers in immunology2025

PepSeq as a highly multiplexed platform for melioidosis antigen discovery and vaccine development.

Evan A Elko, Charles H D Williamson, Heather R Green, Marcellene A Gates-Hollingsworth, Georgia A Nelson, Sujata G Pandit, Heather L Mead, Christopher Allender, Celeste Woerle, Mark Mayo and 6 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Evan A ElkoThe Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, United States.
Charles H D WilliamsonThe Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, United States.
Heather R GreenDepartment of Microbiology and Immunology, University of Nevada, Reno School of Medicine, Reno, NV, United States.
Marcellene A Gates-HollingsworthDepartment of Microbiology and Immunology, University of Nevada, Reno School of Medicine, Reno, NV, United States.
Georgia A NelsonThe Translational Genomics Research Institute, Flagstaff, AZ, United States.
Sujata G PanditDepartment of Microbiology and Immunology, University of Nevada, Reno School of Medicine, Reno, NV, United States.
Heather L MeadThe Translational Genomics Research Institute, Flagstaff, AZ, United States.
Christopher AllenderThe Translational Genomics Research Institute, Flagstaff, AZ, United States.
Celeste WoerleGlobal and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia.
Mark MayoGlobal and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia.
Bart J CurrieGlobal and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia.
David P AuCoinDepartment of Microbiology and Immunology, University of Nevada, Reno School of Medicine, Reno, NV, United States.
John A AltinThe Translational Genomics Research Institute, Flagstaff, AZ, United States.
Paul KeimThe Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, United States.
Erik W SettlesThe Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, United States.
Jason T LadnerThe Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, United States.

Funding

A scalable platform for highly-multiplexed analysis of antibody reactivity from <1uL of bloodU24AI152172 · NIAID · TRANSLATIONAL GENOMICS RESEARCH INST · PI ALTIN, JOHN · 2020 to 2024
$3.3M
NIAID NIH HHS U24 AI152172
6 · The paper itself

Abstract

Introduction: Vaccination aims to prevent or mitigate disease by priming the immune system prior to infection. While historical vaccine development relied mostly on trial-and-error, modern approaches have become more directed. By leveraging our growing understanding of pathogen biology and immune correlates of protection, we can design vaccines in ways that promote protective responses. However, the complexity of many pathogens (e.g., bacteria and fungi), as well as our immune responses against them, continue to present important challenges for vaccine development. Aim: Here, we demonstrate the utility of the PepSeq platform for highly multiplexed serology to both broadly and finely characterize antibody responses against complex pathogens, using the bacterium, Methods: We designed and synthesized three diverse pools of DNA-barcoded peptides (i.e., PepSeq libraries) and used them to characterize antibodies against a variety of Results: Epitope-resolved antibody binding profiles were generated for 85 individuals with culture-confirmed melioidosis, 89 US blood bank controls, and 6 monoclonal antibodies. Using these data, we identify novel B cell antigens/epitopes and finely characterize the epitopes of three monoclonal antibodies against the Conclusion: Highly multiplexed serology platforms, like PepSeq, enable more comprehensive characterization of antibodies, both polyclonal and monoclonal, which can aid in the development of vaccines, diagnostics and therapeutics, even for pathogens with large, complex genomes.

Indexed as

Antigens, BacterialBacterial VaccinesBurkholderia pseudomalleiMelioidosisVaccine DevelopmentAntibodies, BacterialHumansPeptide LibraryAntibodies, BacterialAntigens, BacterialBacterial VaccinesPeptide LibraryBurkholderia pseudomalleiepitopeGroELhighly multiplexed serologymelioidosisPepSeqvaccine

Identifiers

PMID40677719
PMCPMC12267161

What OpenQuestion holds

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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.