Biology subjects

Kundal, K.

Publications and source records attributed to Kundal, K..

4 recordsLinked to original sources

bioRxiv2024

Altered Expression of microRNAs Implicated in Hematopoietic Dysfunction in the Extracellular Vesicles of Bone Marrow-Mesenchymal Stromal Cells in Aplastic Anemia

Recently, we have reported that extracellular vesicles (EVs) from the bone marrow mesenchymal stromal cells (BM-MSC) of aplastic anemia (AA) patients inhibit hematopoietic stem and progenitor cell (HSPC) proliferative and colony-forming ability and promote apoptosis. One mechanism by which AA BM-MSC EVs might contribute to these altered HSPC functions is through microRNAs (miRNAs) encapsulated in EVs. However, little is known about the role of BM-MSC EVs derived miRNAs in regulating HSPC functions in AA. Therefore, we performed miRNA profiling of EVs from BM-MSC of AA (n=6) and normal controls (NC) (n=6), to identify differentially expressed miRNAs carried in AA BM-MSC EVs. DEseq2 analysis identified 34 significantly altered mature miRNAs in AA BM-MSC EVs. Analysis of transcriptome dataset of AA HSPC genes identified that 235 differentially expressed HSPC genes were targeted by these 34 EV miRNAs. The pathway enrichment analysis of 235 HSPC genes revealed their involvement in pathways associated with cell cycle, proliferation, apoptosis, and hematopoiesis regulation, thus highlighting that AA BM-MSC EV miRNAs could potentially contribute to impaired HSPC functions in AA.

molecular biology↗

bioRxiv2023

MyeloDB: A multi-omics resource for Multiple Myeloma

Multiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all haematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 15 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes i.e., CBFB, MANF, MBNL1, SEPHS2 and UFM1 as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB is freely accessible at: (https://project.iith.ac.in/cgntlab/myelodb/)

genomics↗

bioRxiv2023

AMLdb: A comprehensive multi-omics platform to understand the pathogenesis and discover biomarkers for acute myeloid leukemia

Acute myeloid leukemia (AML) is one of the leading leukemic malignancies in adults. The heterogeneity of the disease makes the diagnosis and treatment extremely difficult. Despite the significant developments and the rapid advancements in finding new medication targets, the treatment for AML remains a challenge. With the advent of next-generation sequencing (NGS) technologies, exploration at the molecular level for the identification of biomarkers and drug targets has been the main focus for the researchers to come up with novel therapies for better prognosis and survival outcomes of AML patients. However, the massive amounts of data generated from the NGS platforms demands the necessity to create a comprehensive platform on AML to save the time invested in mining literature. To facilitate this, we developed AMLdb, an interactive multi-omics platform that allows users to query, visualize, retrieve and analyze AML-related multi-omics data. It provides a diverse collection of data resourced from various repositories allowing for a more comprehensive analysis. AMLdb contains 86 datasets for gene expression profiles, 15 datasets for methylation profiles, CRISPR-Cas9 knockout screens of 26 AML cell lines, sensitivity of 26 AML cell lines to 288 drugs, mutations in 41 unique genes in 23 AML cell lines and information on 27 experimentally validated biomarkers. The data provided can be used for deriving conclusions on potential targets for therapies, sensitivity of these targets towards the drugs, patient classification, prediction of treatment strategies and outcomes, chances of relapse etc. In this study, we have reported five genes i.e., CBFB, ENO1, IMPDH2, SEPHS2 and MYH9 identified via our analysis using AMLdb as potential targets. Amongst this, CBFB, IMPDH2, SEPHS2 and MYH9 have been previously validated as targets by experimental studies which is in par with our results. However, ENO1 is a novel target identified using AMLdb which needs further investigation. We anticipates that, AMLdb can be a valuable resource to aid the research community accelerate the development of effective therapies for AML. AMLdb is freely accessible at https://project.iith.ac.in/cgntlab/amldb/ without any restrictions.

genomics↗

bioRxiv2022

In silico identification of novel peptides as potential modulators of Aβ42 Amyloidogenesis

Alzheimers Disease is a neurodegenerative disease for which no cure is available at present. The presence of amyloid plaques in the extracellular space of neural cells is the key feature of this fatal disease. Amyloid-Beta (A{beta}) is a 40-42 amino acid peptide and the main component of amyloid plaques. This peptide is produced by the proteolysis of Amyloid Precursor Protein by presenilin. Deposition of 42 residual A{beta} peptides forms fibrils structure, leading to disruption of neuron synaptic transmission, inducing neural cell toxicity, ultimately leading to neuron death. To modulate the amyloidosis of A{beta} peptides, various novel peptides have been investigated via molecular docking and molecular dynamic simulation studies. The sequence-based peptides were designed and investigated for their interaction with A{beta}42 monomer and fibril using the molecular docking method, and their influence on the structural stability of target proteins was studied using molecular simulations. According to the docking results, amongst all the synthetic peptides, the peptide YRIGY (P6) has the highest binding affinity with A{beta}42 fibril, and the peptide DKAPFF (P12) shows better binding with A{beta}42 monomer. Moreover, simulation results also suggest that the higher the binding affinity, the better the inhibitory action. From these findings, it is suggested that both the peptides can modulate the amyloidogenesis, but peptide (P6) has better potential for the disaggregation of the fibrils, whereas peptide P12 stabilizes the native structure of the A{beta}42 monomer more effectively and hence can serve as a potential amyloid inhibitor. Thus, these peptides can be explored as therapeutic agents against Alzheimers Disease.

bioinformatics↗