Challenges in Serologic Diagnostics of Neglected Human Systemic Mycoses: An Overview on Characterization of New Targets

Abstract

Systemic mycoses have been viewed as neglected diseases and they are responsible for deaths and disabilities around the world. Rapid, low-cost, simple, highly-specific and sensitive diagnostic tests are critical components of patient care, disease control and active surveillance. However, the diagnosis of fungal infections represents a great challenge because of the decline in the expertise needed for identifying fungi, and a reduced number of instruments and assays specific to fungal identification. Unfortunately, time of diagnosis is one of the most important risk factors for mortality rates from many of the systemic mycoses. In addition, phenotypic and biochemical identification methods are often time-consuming, which has created an increasing demand for new methods of fungal identification. In this review, we discuss the current context of the diagnosis of the main systemic mycoses and propose alternative approaches for the identification of new targets for fungal pathogens, which can help in the development of new diagnostic tests.

Keywords: diagnosis; experimental approaches; in silico approaches; new targets; systemic mycoses.

Figure 1

Workflow of epitope prediction for diagnostic development. Obtaining fungal protein or proteomes (FungiDB). Secretome prediction by SignalP, THMHMM, TargetP, Worlf Psort and SecretomeP. The B-cell epitope prediction—Linear Epitope: BCPreds, ABcpred, LBtope and BepiPred; Conformational Epitope: CBTOPE, DiscoTope and ElliPro. The antigenicity evaluation by VaxiJen. Investigation of new target information in literature.

Figure 2

Workflow of Location Prediction. UniProt and FungiDB for protein sequence obtention; SignalP/Phobius (for signal peptide prediction), TMHMM, (transmembrane helices), TargetP (mitochondria), ProtComp9.0/WoLF PSORT/BUSCA (cell localization) and SecretomeP/OutCyte (non-classical secretion) and FragAnchor and PredGPI (GPI anchor).

Figure 3

Workflow of functional characterization of hypothetical proteins. Searching for homologous proteins by Blast and PSI-Blast. Investigation of GO in homologous sequence by Blast2GO, NaviGO, AmiGO, REVIGO, DeepGO and DeepTex2GO for homologous proteins in database. For non-homologous proteins in database: Location prediction; Searching functional domains on InterPro; Construction of the 3D model protein by I-TASSER/SWISS-MODEL and comparing protein models on PDB and/or investigation of protein–protein interaction by STRING.