Identification and production of novel potential pathogen-specific biomarkers for diagnosis of histoplasmosis

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Resumen

Immunological assays based on the detection of circulating fungal biomarkers are helpful in clinical practice for diagnosing invasive fungal infections.
Some of these targeting antigenic components are common to several different fungi. Histoplasmosis is a mycosis caused by the dimorphic fungus Histoplasma capsulatum, which in recent years has gained significant relevance due to the increase in the population susceptible to developing severe clinical forms, including those living with HIV/AIDS. Immunological tests that detect cell wall polysaccharide antigens are among the most used laboratory techniques for diagnosing this mycosis. However, none have shown adequate performance, and cross-reactivity with other fungal pathogens may be
observed. Considering that there is a real need to improve the sensitivity and specificity of current diagnostic methods, we explored a novel strategy for the identification of H. capsulatum-specific antigens (Hc_Ags) that could be detected in clinical samples during infection based on a computational analysis model that included the application of bioinformatics tools and the analysis of experimental data from transcriptomics and proteomics. The Hc_Ags identified were expressed and purified by eukaryotic and prokaryotic systems. First, the Hc_Ags were used in an in-house immunization model in mice (BALB/c) to obtain Hc_Ag-specific polyclonal antibodies (Hc_Ag_PAb). Then, the presence of these antigens in H. capsulatum-yeast culture extracts and the specificity of Hc_Ag_PAb against culture extracts of Candida albicans, Aspergillus fumigatus, Cryptococcus neoformans, Fusarium spp., and Paracoccidioides brasiliensis were confirmed. Finally, we demonstrated the immunoreactivity of these Hc_Ag-specific polyclonal antibodies with urine samples from patients previously diagnosed with histoplasmosis.
Idioma originalInglés
Páginas (desde-hasta)e0093923
PublicaciónMicrobiology spectrum
Fecha en línea anticipada26 oct. 2023
DOI
EstadoPublicada - 26 oct. 2023

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  • Artículos de investigación con calidad A1 / Q1

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