Publications

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.

Rapid design, screening, and characterization of biorecognition elements (BREs) is essential for the development of diagnostic tests and antiviral therapeutics needed to combat the spread of viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To address this need, we developed a high-throughput pipeline combining in silico design of a peptide library specific for SARS-CoV-2 spike (S) protein and microarray screening to identify binding sequences. Our optimized microarray platform allowed the simultaneous screening of ~ 2.5 k peptides and rapid identification of binding sequences resulting in selection of four peptides with nanomolar affinity to the SARS-CoV-2 S protein. Finally, we demonstrated the successful integration of one of the top peptides into an electrochemical sensor with a clinically relevant limit of detection for S protein in spiked saliva. Our results demonstrate the utility of this novel pipeline for the selection of peptide BREs in response to the SARS-CoV-2 pandemic, and the broader application of such a platform in response to future viral threats.

The identification of specific biomarkers for Zika infection and its clinical complications is fundamental to mitigate the infection spread, which has been associated with a broad range of neurological sequelae. , The identification of specific biomarkers for Zika infection and its clinical complications is fundamental to mitigate the infection spread, which has been associated with a broad range of neurological sequelae. We present the characterization of antibody responses in serum samples from individuals infected with Zika, presenting non-severe (classical) and severe (neurological disease) phenotypes, with high-density peptide arrays comprising the Zika NS1 and NS2B proteins. The data pinpoints one strongly IgG-targeted NS2B epitope in non-severe infections, which is absent in Zika patients, where infection progressed to the severe phenotype. This differential IgG profile between the studied groups was confirmed by multivariate data analysis. Molecular dynamics simulations and circular dichroism have shown that the peptide in solution presents itself in a sub-optimal conformation for antibody recognition, which led us to computationally engineer an artificial protein able to stabilize the NS2B epitope structure. The engineered protein was used to interrogate paired samples from mothers and their babies presenting Zika-associated microcephaly and confirmed the absence of NS2B IgG response in those samples. These findings suggest that the assessment of antibody responses to the herein identified NS2B epitope is a strong candidate biomarker for the diagnosis and prognosis of Zika-associated neurological disease.