NAJUMU SAQIB

• Cell culture: Growth and maintenance of Aml-12 and HepG-2 cells. MTT cytotoxic assay, kit-based triglyceride accumulation assay, cellular lipotoxic induction in liver cells, western blot, and siRNA transfection.
• Confocal Microscopy: Nile Red Assay, colocalization studies, and LC3 puncta visualization in mammalian cell lines and PBMCs, Y-H2Ax accumulation, and visualization of the nuclear envelope in yeast cells.
• Immunoprecipitations: Interaction studies by co-immunoprecipitation, DNA-protein interaction by chromatin immunoprecipitations (ChIP), and dual crosslinker ChIP.
• Yeast Biology: Using the homologous recombination technique to develop deletion/tagging in both Schizosaccharomyces pombe and Saccharomyces cerevisiae strains, and Flag affinity protein purification from S. pombe. Site-directed mutagenesis (SDM) in S. cerevisiae.
• 3D Genome Organization: HiC and Micro-C XL: Yeast cells crosslinking, sphaeroplast isolation, Dpn-II fragmentation (in HiC), MNase digestion (in Micro-C XL), nuclei isolation, reverse cross-linking, DNA purification, and proximity ligation.
• NGS library preparation: size selection, biotinylation, end repair, and A-tailing, ligation of adapters, Ampure selection, and final amplification.

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• NGS Bioinformatics:
• RNA-seq pipeline: FastQC, trimming (Trimmomatic), alignment (Bowtie 2, STAR, HISAT), quantification of counts (HTSeq, featureCounts), differential expression (DESeq2, Limma), pathway enrichment.
• ChIP-seq pipeline: FastQC, trimming (Trimmomatic), alignment (Bowtie 2), ChIP-seq QC, Peak Calling (MACS2, HOMER), Peak Annotation, Motif Analysis, and Differential Binding.
• Data analysis tools: Python (NumPy, Seaborn, Pandas, CoolTools, Matplotlib, Biopython, Cooler, HiCExplorer, PyGenomeTracks). R program (dplyr, ggplot), Linux.

• Cloning, expression, and purification of two pairs of Toxin-Antitoxin Mtb (Mycobacterium tuberculosis) membrane proteins in the E. coli expression system.
• Understanding inflammatory and anti-inflammatory responses by the measurement of ROS (Reactive Oxygen Species) , iNOS (inducible Nitric Oxide Synthase), and cytokines (IL-6, IL-12, TNF-α).
• Identifying the immune response pathway by sorting the cell population using FACS based on their surface markers, such as CD88, CD86, and MHC-II.
• Measurement of apoptosis induced by the proteins within the macrophage cell lines, by sorting the cell populations with the apoptosis-specific markers.
• Delineating the signaling pathways by measuring the expression of key inflammatory proteins (NFkB, p-MEK, iNOS) using the Western blot technique.
• Development of a database (MycoTRAP-DB) that consists of the non-synonymous mutations in the genes related to drug resistance acquired from the clinical isolates of Mtb patients, updated until December 2020. Bioinformatics: The mutations were characterized and sorted on the basis of their capacity to disrupt the interaction between the well-known Mtb drugs and their target proteins by utilizing the Schrodinger Suite for Glide -Docking and MD simulations.
• Bioinformatics: Molecular docking studies and MD simulations were used to identify a range of FDA-approved drugs against the ThyX protein of Mtb.

• Cloning, expression, and purification of Mycobacterium tuberculosis toxin-antitoxin protein in the E. coli expression system.
• The immunological response of these proteins was measured over the macrophage RAW 264.7 cells to understand their role in the virulence of M. tuberculosis.
• Cytokine ELISA, MTT Assay