Immunoproteomic Analysis Reveals Novel Candidate Antigens for the Diagnosis of Paracoccidioidomycosis Due to Paracoccidioides lutzii

Autor: André Teixeira-Ferreira, Breno Gonçalves Pinheiro, Rosane Christine Hahn, Paula H. Kubitschek-Barreira, Anderson Messias Rodrigues, Zoilo Pires de Camargo
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Fungi, Vol 6, Iss 357, p 357 (2020)
Journal of Fungi
Volume 6
Issue 4
Popis: Paracoccidioidomycosis (PCM) is a life-threatening systemic infection caused by the fungal pathogen Paracoccidioides brasiliensis and related species. Whole-genome sequencing and stage-specific proteomic analysis of Paracoccidioides offer the opportunity to profile humoral immune responses against P. lutzii and P. brasiliensis s. str. infection using innovative screening approaches. Here, an immunoproteomic approach was used to identify PCM-associated antigens that elicit immune responses by combining 2-D electrophoresis of P. lutzii and P. brasiliensis proteomes, immunological detection using a gold-standard serum, and mass spectrometry analysis. A total of 16 and 25 highly immunoreactive proteins were identified in P. lutzii and P. brasiliensis, respectively, and 29 were shown to be the novel antigens for Paracoccidioides species, including seven uncharacterized proteins. Among the panel of proteins identified, most are involved in metabolic pathways, carbon metabolism, and biosynthesis of secondary metabolites in both immunoproteomes. Remarkably, six isoforms of the surface-associated enolase in the range of 54 kDa were identified as the major antigens in human PCM due to P. lutzii. These novel immunoproteomes of Paracoccidioides will be employed to develop a sensitive and affordable point-of-care diagnostic assay and an effective vaccine to identify infected hosts and prevent infection and development of human PCM. These findings provide a unique opportunity for the refinement of diagnostic tools of this important neglected systemic mycosis, which is usually associated with poverty.
Databáze: OpenAIRE