Evidence map›Paper›PMID 41428748›Full record

ArticlePLoS neglected tropical diseases2025

K-mer-based approach for serodiagnostic antigen discovery in Chagas disease using unassembled sequencing reads.

Nathan Ravi Medeiros Honorato, Laila Viana de Almeida, João Luís Reis-Cunha, Vanêssa Gomes Fraga, Daniel Menezes Souza, Ramon Vieira Nunes, Fátima Ribeiro-Dias, Edward Valencia Ayala, Jeffery A Noble, Alexandre Ferreira Marques and 3 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. Not yet cited in PubMed.

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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

13 authors.

Nathan Ravi Medeiros HonoratoDepartamento de Parasitologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Laila Viana de AlmeidaDepartamento de Parasitologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
João Luís Reis-CunhaDepartment of Biology, University of York, York, Yorkshire, United Kingdom.
Vanêssa Gomes FragaDepartamento de Parasitologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Daniel Menezes SouzaDepartamento de Patologia Clínica, COLTEC, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Ramon Vieira NunesDepartamento de Parasitologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Fátima Ribeiro-DiasLaboratório de Imunidade Natural (LIN), Instituto de Patologia Tropical e Saúde Pública, Universidade Federal de Goiás, Goiânia, Goiás, Brazil.
Edward Valencia AyalaLaboratorio de Parasitología Molecular y Celular, Facultad de Ciencias Biológicas, Universidad Nacional Mayor de San Marcos, Lima, Peru.
Jeffery A NobleSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
Alexandre Ferreira MarquesSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
M G FinnSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
Lúcia Maria da Cunha GalvãoDepartamento de Análises Clínicas e Toxicológicas, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
Daniella C BartholomeuDepartamento de Parasitologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.ORCID 0000-0003-0974-7357

Funding

Conselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de Minas GeraisInstituto Nacional de Ciência e Tecnologia de VacinasPró-reitoria de Pesquisa, Universidade Federal de Minas Gerais
6 · The paper itself

Abstract

Trypanosoma cruzi, the causative agent of Chagas disease (CD), exhibits remarkable genetic diversity, classified into six discrete typing units (DTUs), and one additional DTU, TcBat, primarily associated with bats. These DTUs are distributed differentially across CD-endemic regions, posing significant challenges for molecular and serological diagnosis, as test performance often varies geographically. Identifying conserved genomic regions shared among parasites circulating in distinct endemic areas is therefore essential. However, complete or semi-complete genome assemblies are available for only a limited number of strains, insufficiently capturing intra- and inter-DTU variability, particularly within repetitive multigene families. A wealth of raw T. cruzi genomic reads is publicly available, offering an opportunity to investigate highly repetitive, high-copy number sequences that are difficult to assemble but potentially valuable for improving diagnostic sensitivity. In this study, we applied a read-based bioinformatics pipeline to analyze data from six DTUs (TcI-TcVI), generating 80-mer fragments and clustering them to identify conserved sequences. Consensus sequences from conserved clusters were used to design synthetic peptides, which were evaluated serologically with samples from chronically infected individuals from Brazil, Bolivia, and Peru. Four peptides from the conserved C-terminal region of mucin family proteins demonstrated robust diagnostic performance (AUC: 0.8783-0.9353), with particularly high values obtained with sera from Brazilian and Bolivian patients. Overall, our results demonstrate that k-mer-based, assembly-free approaches can successfully identify conserved antigens across genetically diverse T. cruzi populations, underscoring their value as discovery tools for potential serological markers. While the peptides identified here represent promising candidates, validation in larger and more geographically diverse cohorts will be essential to establish their broader diagnostic applicability. Importantly, similar genome-informed strategies may also be leveraged to guide the discovery of diagnostic targets for other infectious diseases.

Indexed as

Antigens, ProtozoanChagas DiseaseSerologic TestsTrypanosoma cruziComputational BiologyGenetic VariationHumansSequence Analysis, DNAAntigens, Protozoan

Identifiers

PMID41428748
PMCPMC12747435

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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.