Biology subjects

Kothari, J.

Publications and source records attributed to Kothari, J..

3 recordsLinked to original sources

bioRxiv2025

Sub-phenotypes of pneumonia defined by pulmonary histopathological features

Establishing sub-phenotypes of pneumonia based on distinct host processes will be a step towards using host-directed therapies (to complement microbe-directed therapies) more rationally and precisely. Although pneumonia is a pulmonary pathophysiology, histological changes within the lungs have not been leveraged for sub-phenotyping. We addressed this by scoring 18 histopathology features (e.g., type 2 cell hyperplasia or necrosis) across rapid autopsy lung samples from 276 elderly subjects with pneumonia. Machine learning algorithms segregated subjects into seven different sub-phenotypes of pneumonia with distinct histopathology signatures. Quantitative immunofluorescence demonstrated associations of macrophages, neutrophils, T cells, and B cells with select histology features and pulmonary pathology sub-phenotypes. Mouse models revealed corollary sub-phenotypes, although some histology features observed in human lungs were never observed in mice. By illuminating this spectrum of histopathologies and discriminating discrete sub-phenotypes of pneumonia, a foundational framework emerges for developing and using host-directed therapies for subsets of pneumonia patients.

immunology↗

bioRxiv2020

Novel antiproliferative tripeptides block AP-1 transcriptional complex by in silico approach

BACKGROUNDThe complexity and heterogeneity at genetic, epigenetic and microenvironment levels are key attributes of tumors. Genetic heterogeneity encompasses one of key factors at transcriptional gene regulation that promote abnormal proliferation, invasiveness and metastasis. Among various key pro-tumor transcriptional complexes, activating protein-1 (AP-1) transcriptional complex controls the transcriptional expression of key oncogenes in cancer cells. Therefore, an avenue to search for a chemical inhibition approach of the AP-1 transcriptional complex is warranted in cancer therapeutics. METHODSTo achieve chemical inhibition of AP-1 transcriptional complex, we report novel tripeptides identified from the goat urine DMSO fraction as potential agents that bind to AP-1 responsive TPA element and heterodimer c-Jun:c-Fos. Novel tripeptides enriched GUDF were tested against DNA substrates to assess DNA metabolizing activity. Further, Novel tripeptides enriched GUDF were treated upon HCT-116 cells to estimate the nature of tripeptides entered into the intracellular compartment of HCT-116 cells. Here, we report on a novel methodology that employ VTGE assisted intracellular metabolite purification and is analyzed with the help of LC-HRMS technique. Post purification of intracellular metabolites that included tripeptides of GUDF, these tripeptides from DMSO and GUDF treated HCT-116 cells were subjected to molecular docking and ligand-DNA:AP-1 (PDB ID: 1FOS) interaction study by using bioinformatics tools AutoDock Vina and PyMol. RESULTSGUDF enriched with tripeptides and other metabolites show appreciable instability of DNA substrates plasmid and genomic DNA to an extent of 90%. Interestingly, LC-HRMS analysis of intracellular metabolite profiling of GUDF treated HCT-116 cells reveal the appreciable abundance of tripeptides Glu-Glu-Arg, Gly-Arg-Pro, Gln-Lys-Arg, Glu-Glu-Lys, Trp-Trp-Val. On the other hand, DMSO treated HCT-116 cells show the presence of Ser-Trp-Lys, Glu-Glu-Gln, Glu-Glu-Lys, Ser-Leu-Ser. Interestingly, GUDF treated HCT-116 cells show inhibition of proliferation by more than 70%. Among the identified intracellular tripeptides, Glu-Glu-Arg (9.1 Kcal/Mol), Gly-Arg-Pro (8.8 Kcal/Mol), and Gln-Lys-Arg (6.8) show a precise and strong binding to heptameric TPA response element 5 TGAGTCA 3 and key amino acid residue within the AP-1 transcriptional complex. CONCLUSIONIn summary, this study suggests the potential of novel tripeptides, those are reported from GUDF intracellularly in HCT-116 cells to destabilize the AP-1 transcriptional complex. Data indicate that cellular arrest in HCT-116 cells treated by GUDF is well supported by the molecular docking observations that destabilization of AP-1 complex is linked to reduced growth and proliferation.

cancer biology↗

bioRxiv2019

Detection of urinary metabolites of metabolic pathway disorders by using VTGE and LC-HRMS techniques

BackgroundIn recent, various human health disorders including cancer, diabetes, neurodegenerative and metabolic diseases are noticed among human populations. Currently, genetic and proteomic approaches are highly reported to detect metabolic disorders that also include inborn error of metabolisms. These existing detection methods are faced with cost issue and time consuming factors. Therefore, metabolites as biomarkers are one of potential avenues to detect metabolic disorders. Further, exploitation of urine as potential source of metabolite biomarkers, there are limitation in this area of research due to abundance of non-metabolite components such as proteins and nucleic acids. Hence, methods and processes are required to precisely fractionate metabolites from urine of inborn error of metabolism patients and then identified by analytical tools such as LC-HRMS and GC-MS.\n\nMethodsSterile filtered urine samples (750 {micro}l) mixed with (250 {micro}l) loading buffer were electrophoresed on VTGE that uses acrylamide gel (acrylamide:bisacrylamide, 30:1) as matrix of 15%. Further, vertical tube gel electrophoresis (VTGE) technique combined with LC-HR-MS to identify metabolites that are known as the biomarkers of metabolic disorders was carried out.\n\nResults and DiscussionThe authors provide evidence on the use of novel VTGE coupled with LC-HRMS to detect metabolites among metabolic disorders. Data suggest the applicability of VTGE coupled with LC-HRMS technique to detect metabolites such as 2-methyluridine, 2-Methylglutaric acid, 2-Methyl citric acid, 2-Hydroxyglutaric acid in case of metabolic disorders.\n\nConclusionThis preliminary work is suggested to be extended to large clinical samples to validate application of this method to detect metabolic disorders including inborn error of metabolisms.

biochemistry↗