Trypanosoma evansi secretome carries potential biomarkers for Surra diagnosis.

Trypanosoma evansi is a parasite that is phylogenetically close to Trypanosoma brucei and is the causative agent of a disease known as surra. Surra is responsible for a high mortality rate in livestock and large economic losses in the Americas, Africa, and Asia. This work aimed to analyze in vitro secreted proteins from T. evansi and identify potential treatment and diagnostic biomarkers for surra diagnosis. Two groups were used. In one group the parasites were purified using a DEAE-Cellulose column and maintained in a secretion medium while in the other group the parasites were not purified. Each group was further divided to be maintained at either 37 °C or 27 °C. We identified 246 proteins through mass spectrometry and found that the temperature appears to modulate protein secretion. We found minimal variations in the protein pools from pure and non-purified sets. We observed an emphasis on proteins associated to vesicles, glycolysis, and cellular homeostasis through the enrichment of GO. Also, we found that most secretome proteins share homologous proteins with T. b. brucei, T. b. gambiense, T. vivax, T. equiperdum, and T. b. rhodesiense secretome but unique T. evansi epitopes with potential biomarkers for surra diagnosis were detected. SIGNIFICANCE: Trypanosoma evansi is a parasite of African origin that is phylogenetically close to Trypanosoma brucei. As with other trypanosomatids and blood parasites, its infection causes non-pathognomonic symptoms, which makes its diagnosis difficult. One great problem is the fact that no diagnostic test differentiates between Trypanosoma equiperdum and T. evansi, which is a problem in South America and Asia, and Africa. Thus, it is urgent to study the biochemistry of the parasite to discover proteins that can be used for differential diagnosis or be possible therapeutic targets. In addition, the study of the secretome can point out proteins that are used by the parasite in its interactions with the host, helping to understand the progression of the disease.

EpiBuilder: A Tool for Assembling, Searching, and Classifying B-Cell Epitopes.

Epitopes are portions of a protein that are recognized by antibodies. These small amino acid sequences represent a significant breakthrough in a branch of bioinformatics called immunoinformatics. Various software are available for linear B-cell epitope (BCE) prediction such as ABCPred, SVMTrip, EpiDope, and EpitopeVec; a well-known BCE predictor is BepiPred-2.0. However, despite the prediction, there are several essential steps, such as epitope assembly, evaluation, and searching for epitopes in other proteomes. Here, we present EpiBuilder (https://epibuilder.sourceforge.io), a user friendly software that assists in epitope assembly, classifying and searching using input results of BepiPred-2.0. EpiBuilder generates several output results from these data and supports a proteome-wide processing approach. In addition, this software provides the following features: Chou & Fasman beta-turn prediction, Emini surface accessibility prediction, Karplus and Schulz flexibility prediction, Kolaskar and Tongaonkar antigenicity, Parker hydrophilicity prediction, N-glycosylation domains, and hydropathy. These information generate a unique topology for each epitope, visually demonstrating its characteristics. The software can search the entire epitope sequence in various FASTA files, and it allows to use BLASTP to identify epitopes that eventually have sequence variations. As an EpiBuilder application, we developed a epitope dataset from the protozoan Trypanosoma brucei gambiense, the gram-positive bacterium Clostridioides difficile, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Serum proteomic signature of Trypanosoma evansi -infected mice for identification of potential biomarkers.

Trypanosoma evansi is the agent of "surra," a trypanosomosis endemic in many areas worldwide. Trypanosoma proteins released/secreted during infection are attractive biomarkers for disease detection and monitoring. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), we performed a comprehensive analysis of the serum proteome of mice infected with T.evansi and detected changes in the abundance of parasite and host serum proteins during infection. Following bioinformatics analysis, 30 T. evansi proteins were identified in the mice serum including known targets such as pyruvate kinase 1, ß-tubulin, actin A, heat shock protein 70, and cyclophilin A. We also identified two exclusive VSG epitopes which are novel putative biomarker targets. In addition, upregulation of 31 mouse proteins, including chitinase-like protein 3 and monocyte differentiation antigen CD14, were observed. Identification of parasite-specific biomarkers in the host serum is critical for the development of reliable serological/ assays for differential diagnosis.