Publications

Visceral Leishmaniasis, caused by Leishmania infantum, is a tropical neglected disease and the most dangerous form of Leishmaniasis. It occurs zoonotically, with domestic transmission posing risks to humans as dogs have high susceptibility and are natural reservoirs of the parasite. Given their epidemiological role, improvements are needed in diagnosing Canine Visceral Leishmaniasis (CVL). Thus, we mapped linear epitopes from the rLiNTPDase2 antigen through peptide microarray and identified six positive epitopes. Validation through peptide ELISA revealed three promising peptides with accuracies of 78.6%, 85.92%, and 79.59%. Their combination yielded 97.58% accuracy. Negative epitopes were also found, which interacted with CVL-negative and Chagas Disease positive samples. Their removal from the rLiNTPDase2 sequence resulted in the rNT2.neg, which obtained enhanced specificity over rLiNTPDase2. The rNT2.neg validation achieved 87.50% sensitivity, 90.55% specificity, and 93.5% accuracy within 127 CVL-positive and 96 CVL-negative samples. Therefore, three peptides and rNT2.neg show significant promise for CVL diagnosis.

Introduction: Immunoinformatic tools can be used to predict schistosome-specific B-cell epitopes with little sequence identity to human proteins and antigens other than the target. This study reports an approach for identifying schistosome peptides mimicking linear B-cell epitopes using in-silico tools and peptide microarray immunoassay validation. Method: Firstly, a comprehensive literature search was conducted to obtain published schistosome-specific peptides and recombinant proteins with the best overall diagnostic performances. For novel peptides, linear B-cell epitopes were predicted from target recombinant proteins using ABCpred, Bcepred and BepiPred 2.0 in-silico tools. Together with the published peptides, predicted peptides with the highest probability of being B-cell epitopes and the lowest sequence identity with proteins from human and other pathogens were selected. Antibodies against the peptides were measured in sera, using peptide microarray immunoassays. Area under the ROC curve was calculated to assess the overall diagnostic performances of the peptides. Results: Peptide AA81008-19-30 had excellent and acceptable diagnostic performances for discriminating S. mansoni and S. haematobium positives from healthy controls, with AUC values of 0.8043 and 0.7326 respectively for IgG. Peptides MS3_10186-123-131, MS3_10385-339-354, SmSPI-177-193, SmSPI-379-388, MS3-10186-40-49 and SmS-197-214 had acceptable diagnostic performances for discriminating S. mansoni positives from healthy controls with AUC values ranging from 0.7098 to 0.7763 for IgG. Peptides SmSPI-359-372, Smp126160-438-452 and MS3 10186-25-41 had acceptable diagnostic performances for discriminating S. mansoni positives from S. mansoni negatives with AUC values of 0.7124, 0.7156 and 0.7115 respectively for IgG. Peptide MS3-10186-40-49 had an acceptable diagnostic performance for discriminating S. mansoni positives from healthy controls, with an AUC value of 0.7413 for IgM. Conclusion: One peptide with a good diagnostic performance and nine peptides with acceptable diagnostic performances were identified using the immunoinformatic approach and peptide microarray validation. There is need for evaluation of the peptides with true negatives and a good standard positive reference.

Malaria is still a global challenge with significant morbidity and mortality, especially in the African, South-East Asian, and Latin American regions. Malaria diagnosis is a crucial pillar in the control and elimination efforts, often accomplished by the administration of mass-scale Rapid diagnostic tests (RDTs). The inherent limitations of RDTs- insensitivity in scenarios of low transmission settings and deletion of one of the target proteins- Histidine rich protein 2/3 (HRP-2/3) are evident from multiple reports, thus necessitating the need to explore novel diagnostic tools/targets. The present study used peptide microarray to screen potential epitopes from 13 antigenic proteins (CSP, EXP1, LSA1, TRAP, AARP, AMA1, GLURP, MSP1, MSP2, MSP3, MSP4, P48/45, HAP2) of P. falciparum. Three cyclic constrained immunoreactive peptides- C6 (EXP1), A8 (MSP2), B7 (GLURP) were identified from 5458 cyclic constrained peptides (in duplicate) against P. falciparum-infected sera. Peptides (C6, A8, B7- cyclic constrained) and (G11, DSQ, NQN- corresponding linear peptides) were fairly immunoreactive towards P. falciparum-infected sera in dot-blot assay. Using direct ELISA, cyclic constrained peptides (C6 and B7) were found to be specific to P. falciparum-infected sera. A substantial number of samples were tested and the peptides successfully differentiated the P. falciparum positive and negative samples with high confidence. In conclusion, the study identified 3 cyclic constrained immunoreactive peptides (C6, B7, and A8) from P. falciparum secretory/surface proteins and further validated for diagnostic potential of 2 peptides (C6 and B7) with field-collected P. falciparum-infected sera samples.

Yellow Fever disease is caused by the Yellow Fever virus (YFV), an arbovirus from the Flaviviridae family. The re-emergence of Yellow Fever (YF) was facilitated by the increasing urbanization of sylvatic areas, the wide distribution of the mosquito vector, and the low percentage of people immunized in the Americas, which caused severe outbreaks in recent years, with a high mortality rate. Therefore, serological approaches capable of discerning antibodies generated from the wild-type (YFV-WT) strain between the vaccinal strain (YFV-17DD) could facilitate vaccine coverage surveillance, enabling the development of strategies to avoid new outbreaks. In this study, peptides were designed and subjected to microarray procedures with sera collected from individuals infected by WT-YFV and 17DD–YFV of YFV during the Brazilian outbreak of YFV in 2017/2018. From 222 screened peptides, around ten could potentially integrate serological approaches aiming to differentiate vaccinated individuals from naturally infected individuals. Among those peptides, one was synthesized and validated through ELISA.

INTRODUCTION: The challenges posed by emergent strains of SARS-CoV-2 need to be tackled by contemporary scientific approaches, with proteomics playing a significant role. AREAS COVERED: In this review, we provide a brief synthesis of the impact of proteomics technologies in elucidating disease pathogenesis and classifiers for the prognosis of COVID-19 and propose proteomics methodologies that could play a crucial role in understanding emerging variants and their altered disease pathology. From aiding the design of novel drug candidates to facilitating the identification of T cell vaccine targets, we have discussed the impact of proteomics methods in COVID-19 research. Techniques varied as mass spectrometry, single-cell proteomics, multiplexed ELISA arrays, high-density proteome arrays, surface plasmon resonance, immunopeptidomics, and in silico docking studies that have helped augment the fight against existing diseases were useful in preparing us to tackle SARS-CoV-2 variants. We also propose an action plan for a pipeline to combat emerging pandemics using proteomics technology by adopting uniform standard operating procedures and unified data analysis paradigms. EXPERT OPINION: The knowledge about the use of diverse proteomics approaches for COVID-19 investigation will provide a framework for future basic research, better infectious disease prevention strategies, improved diagnostics, and targeted therapeutics.