Development of pathophysiologically relevant models of sickle cell disease and ß-thalassemia for therapeutic studies.

Ex vivo cellular system that accurately replicates sickle cell disease and ß-thalassemia characteristics is a highly sought-after goal in the field of erythroid biology. In this study, we present the generation of erythroid progenitor lines with sickle cell disease and ß-thalassemia mutation using CRISPR/Cas9. The disease cellular models exhibit similar differentiation profiles, globin expression and proteome dynamics as patient-derived hematopoietic stem/progenitor cells. Additionally, these cellular models recapitulate pathological conditions associated with both the diseases. Hydroxyurea and pomalidomide treatment enhanced fetal hemoglobin levels. Notably, we introduce a therapeutic strategy for the above diseases by recapitulating the HPFH3 genotype, which reactivates fetal hemoglobin levels and rescues the disease phenotypes, thus making these lines a valuable platform for studying and developing new therapeutic strategies. Altogether, we demonstrate our disease cellular systems are physiologically relevant and could prove to be indispensable tools for disease modeling, drug screenings and cell and gene therapy-based applications.

Leptospira and Leptospirosis: New Systems Science Insights on Proteome, Posttranslational Modifications, and Pathogen-Host Interaction.

Leptospirosis is one of the most important zoonotic diseases for planetary health. It is caused by Leptospira spp., which poses a formidable challenge in both rural and urban geographies. Discovery of molecular targets is crucial for developing interventions, including vaccines, against leptospirosis. We report here novel systems science insights on Leptospira proteome, posttranslational modifications (PTMs), and pathogen-host interactions, with an eye to bacterial pathophysiology from a functional standpoint. A systematic reanalysis of unassigned spectra from our previous total proteome identification was used for a multi-PTM search. Notably, we identified 3693 unique high-confidence PTM sites corresponding to 1266 proteins (PTM-profiling probability cutoff value ≥75%). The majority of the phosphorylated peptides were found to be GroEL molecular chaperones. Notably, the molecular docking of PTM-GroEL with STAT3, an important signaling protein in cytokine production, resulted in the prediction of druggable "hotspots." These energetically significant smaller subsets of amino acids (hotspot residues) offer promise for practical applications in planetary health, rational drug design, and peptide engineering. Furthermore, the prediction strategies described here could serve as a starting point for narrowing down the more extensive interface in protein-protein interactions that currently exist. Going forward, systems science approaches and the new insights reported here offer veritable prospects for innovation in preventing and treating leptospirosis.

Novel Post-Translational Modifications and Molecular Substrates in Glioma Identified by Bioinformatics.

Glioma is the most common type of brain cancer that originates from the glial cells. It constitutes about one-third of all brain cancers. Recently, transcriptomics, proteomics, and multiomics approaches have been harnessed to discover potential biomarkers and therapeutic targets in glioma. Moreover, post-translational modifications (PTMs) of proteins play a major role in cell biology and function and offer new avenues of research in cancer. Using unbiased multi-PTM bioinformatics analyses of two proteomic datasets of glioma available in the public domain, we identified 866 proteins with common PTMs from both studies. Out of these 866 proteins, 19 proteins were identified with the common PTMs, with the same site modifications pertaining to glioma. Importantly, the identified PTMs belonged to proteins involved in integrin PI3K/Akt/mTOR, JAK/STAT, and Ras/Raf/MAPK pathways. These pathways are essential for cell proliferation in tumor cells and thus involved in glioma progression. Taken together, these findings call for validation in larger datasets in glioma and brain cancers and with an eye to future drug discovery and diagnostic innovation. Bioinformatics-guided discovery of novel PTMs from the publicly available proteomic data can offer new avenues for innovation in cancer research.