Biology subjects

Bose, B.

Publications and source records attributed to Bose, B..

13 recordsLinked to original sources

bioRxiv2025

Unveiling Differential Epigenetic Regulation of ABC Transporter Genes in Wild and Domestic Rice in Response to Heavy Metal Stress

Plants are continually subjected to heavy metal (HM) stress, which impairs critical physiological and metabolic processes. ATP-binding cassette (ABC) transporters play an important role in heavy metal detoxification, their epigenetic regulation under heavy metal stress remains poorly understood. Epigenetic changes, such as DNA methylation (5mC) and N6-methyladenine (6mA), are emerging as important regulators of stress-responsive genes. We studied the epigenetic regulation of ABC transporter genes in three Oryza species Oryza sativa indica, Oryza rufipogon, and Oryza glaberrima by analysing promoter methylation patterns. Our data show that 5mC is abundant in CHG motifs, whereas 6mA is mostly found at AHCA motifs, indicating sequence-specific methylation preferences across different rice species. Notably, indica rice exhibited higher promoter methylation levels compared to O. rufipogon and O. glaberrima, suggesting a potential link between increased DNA methylation and reduced ABC transporter expression, which may contribute to heightened HM sensitivity in cultivated rice. Phylogenetic analysis further highlighted species-specific variations in methylation patterns, supporting the role of epigenetics in shaping HM stress adaptation. These results provide new insights into the regulatory mechanisms governing heavy metal tolerance in rice and open avenues for epigenetic-based crop improvement strategies.

plant biology↗

bioRxiv2025

Hematopoietic stem cell conditioned media induces excessive mitochondrial fission via Drp-1 to target colorectal cancer

Mitochondria, often referred to as the "powerhouses of the cell," are particularly crucial in cancer cells due to their high energy demands. Mitochondrial fusion-fission dynamics play a critical role in regulating signaling pathways and metabolic activities in colorectal cancer (CRC) cells. Increased mitochondrial fission drives metabolic reprogramming, enabling CRCs to proliferate, metastasize, and resist chemotherapy. Paradoxically, excessive fission induces mitochondria-mediated apoptosis. Our previous studies have shown that hematopoietic stem cell-derived conditioned media (CM) modulate the apoptosis pathway and mitochondrial bioenergetics of cancer stem cells by altering the cancer microenvironment. In this study, We found that HSCs-CM facilitates excessive fission in colorectal cancer cells by modulating Drp-1 and concurrently activating the PINK1-Parkin mitophagy pathway and intrinsic apoptosis, leading to loss of viability of these cells. Moreover, proteomics data showed that HSCs-CM dysregulated the electron transport chain complexes, with an exceptionally high degree of dysregulation of complexes III and IV. Metabolomics revealed dysregulation of critical metabolites, RNA sequencing revealed dysregulation of transcripts, and proteomics revealed dysregulation of proteins, involved in mitochondrial bioenergetics and the autophagy pathway in CRCs treated with CM. Taken together, our studies reveal the therapeutic potential of HSC-conditioned media for treating colorectal cancer. HighlightsO_LIHematopoietic stem cell-derived conditioned media (HSC-CM) induces excessive mitochondrial fission in colorectal cancer (CRC) cells by upregulating Drp-1, thereby activating the intrinsic apoptotic pathway. C_LIO_LIExcessive fission and bioenergetic dysfunction caused by HSC-CM result in loss of mitochondrial membrane potential and elevated reactive oxygen species production. C_LIO_LIHSC-CM severely disrupts the electron transport chain in CRC cells, precipitating an energy crisis and engaging the PINK1-mediated mitophagy pathway. C_LI SummaryHematopoietic stem cell-derived conditioned media (HSC-CM) compromises mitochondrial dynamics by inducing excessive fission in colorectal cancer (CRC) cells through upregulation of Drp-1 and its associated protein complex. The resulting hyperfission leads to severe mitochondrial dysfunction, characterised by a loss of mitochondrial membrane potential, decreased ATP production, and disrupted electron transport chain complexes. This bioenergetic crisis and overproduction of reactive oxygen species ultimately trigger intrinsic apoptosis and engage the mitophagy pathway, leading to loss of CRC cell viability.

cancer biology↗

bioRxiv2025

A network model for patient-derived drug response in breast cancer integrating multi-omics datasets.

The widespread availability of multi-omics tumor profiling has enabled detailed molecular characterization of individual tumors, paving the way for more effective, less toxic, and patient-specific therapies. However, widespread compound screens in human patients are constrained by ethical and logistical challenges, underscoring the need for computational models capable of predicting in vivo drug response. Here, we introduce PDDRNet-MH, a multiplex heterogeneous network-based framework that integrates genomic, transcriptomic, and epigenomic tumor profiles with drug chemical structures, pharmacological activity, and side-effect data to infer personalized drug responses. PDDRNet-MH constructs an integrated network connecting patients, cell lines, drugs, and genes, with each component represented by four biologically and pharmacologically informed similarity layers. This design enables the systematic propagation of drug-biomarker associations across modalities. We applied PDDRNet-MH to breast cancer patient data from The Cancer Genome Atlas and benchmarked its predictive performance against state-of-the-art methods on eleven FDA-approved breast cancer drugs. PDDRNet-MH achieved consistently high accuracy, with perfect prediction scores for gemcitabine and vinorelbine (Area Under the Receiver Operating Characteristic Curve [AUC-ROC] = 1.00; Area Under the Precision-Recall Curve [AUC-PR] = 1.00) and near-perfect scores for methotrexate and zoledronate (AUC-ROC = 0.95; AUC-PR = 0.99), demonstrating its ability to robustly distinguish sensitive from resistant patients. Biologically, PDDRNet-MH accurately prioritized established clinical biomarkers, including HER2 (ERBB2) for lapatinib and BRCA1/2 for doxorubicin and cyclophosphamide. Beyond known associations, the model identified additional genes within the HER2 amplicon on chromosome 17q12, including STARD3, MIEN1, and PPP1R1B, whose amplification was significantly associated with elevated drug response scores, suggesting potential roles in HER2-targeted therapy. These findings highlight the ability of PDDRNet-MH to recover and extend clinically relevant drug-biomarker associations, supporting its utility in guiding precision oncology.

cancer biology↗

bioRxiv2025

Hematopoietic Stem Cells Modulate Tumor Immune-Environment to Target Triple-Negative Breast Cancer via Altering Mitochondrial Bioenergetics

Ontogenic development of Hematopoietic stem cells (HSCs) takes place at diverse anatomical niches. Moreover, during embryonic development, HSCs migrate from the aorta-gonad mesonephros (AGM) to the fetal liver and finally to the bone marrow immediately after childbirth. Hence, the primary residence of adult HSCs in the bone marrow continues replenishing the hematopoietic lineage pool. In vivo, the HSC niche is significant and might be harnessed in regenerative medicine. HSCs in various niches have exhibited their respective tropism and proliferations based on the growth factors secreted by the niche. Accordingly, in this work, we hypothesized HSCs tropism towards cancer and stem cell niche of triple-negative breast cancer (TNBC) and HER2+, having a high relapse rate for possible cell therapy development. Our results indicate that HSC exclusive tropism towards breast cancer stem cells (CSC) and interaction with the cancer milieu lead to HSC differentiation into T-lymphocyte cells (CD4 & CD8). Moreover, the single-cell type proteomics of the migrated HSCs towards TNBC-CSCs and HER2+ cells indicated upregulation of IL-7 and Notch protein and several other upregulated proteins primarily involved in T cell activation and migration-related pathways. Likewise, the metabolomics from HSCs-derived conditioned media-treated CSCs, and HER2+ cells showed the capability of HSC-CM in arresting the growth and cell cycle of TNBC-CSC via altered mitochondrial bioenergetics. Hence, this study paves the way toward harnessing the potential of both HSCs and HSC-CM for personalized medicine against TNBC CSCs. HighlightsO_LIHematopoietic stem cells exhibited tumor tropism towards triple negative breast cancer stem cells and HER2+ cancer cells. C_LIO_LIUpon migration in the tumor milieu, HSCs differentiated into T cells, targeted CSCs, and modulated the upregulation of interleukin-7 and notch proteins. C_LIO_LIHSCs-CM inhibited the cell cycle in TNBC-CSCs by downregulating CDK1, disrupting mitochondrial bioenergetics via upregulated Drp1, and inducing CSC apoptosis. C_LIO_LIParacrine signaling from HSCs via conditioned media induced metabolic stress and disrupted key metabolic pathways in TNBC-CSCs. C_LI SummaryHematopoietic stem cells (HSCs) are known for their regenerative potential in the blood system. This study reveals the novel therapeutic potential of hematopoietic stem cells (HSCs) in combating triple-negative breast cancer stem cells (TNBC-CSCs). HSCs exhibited tropism towards TNBC-CSCs, themselves differentiated into T cells within the tumor microenvironment, leading to targeted cell killing of TNBC-CSCs. In addition, paracrine signaling from HSC-conditioned media (CM) induced metabolic stress in TNBC-CSCs and disrupted key metabolic pathways. HSC-CM also disrupted mitochondrial dynamics and function, leading to DNA damage and apoptosis. Critically, HSC-CM impaired TNBC-CSC stemness by downregulating stemness genes, leading to the inhibition of 3D spheroid formation. Hence, our study highlights HSCs as a promising therapeutic strategy for targeting TNBC-CSCs via disrupted metabolic homeostasis and self-renewal.

cancer biology↗

bioRxiv2023

Differential expression of miRNAs between Young-Onset and Late-Onset Indian colorectal carcinoma patients

Early-Onset Colorectal Carcinoma (EOCRC) is a growing concern as reports indicate a worldwide increase in the incidence of CRC among young adults (<50 years old). In an effort to understand the different mode of pathogenesis in young-onset CRC, we performed a pilot study wherein we looked at colorectal tumors from both young (< 50 years old) and old patients (>55 years old) and screened them to eliminate tumors positive for Microsatellite Instability (MSI) and showing activation of the Wnt pathway, known canonical factors in CRC pathogenesis. RNA isolated from EOCRC and Late-Onset (LOCRC) tumors and paired normal tissues without MSI, nuclear {beta}-catenin and APC mutations were sent for small RNA seq to identify miRNA alterations between the two subsets. Comparative analysis revealed differential expression of 23 miRNAs specific to EOCRC and 11 miRNAs specific to LOCRC. We validated the top 10 EOCRC DEMs in TCGA-COAD cohorts followed by validation in additional EOCRC and LOCRC cohorts. Our integrated analysis revealed upregulation of hsa-miR-1247-3p, hsa-miR-148a-3p and hsa-miR-27a-5p and downregulation of hsa-miR-326 between the two subsets. Experimentally validated targets of the above miRNAs were compared with differentially expressed genes in the TCGA dataset to identify targets with physiological significance in EOCRC development. Our analysis revealed downregulation of epithelial gene expression and intercellular junction proteins potentially leading to dissolution of epithelial intercellular junctions in EOCRC development and EMT progression. Upregulated targets included genes whose expression have been reported to correlate with CRC tumor invasion, liver metastasis, disease recurrence and poor prognosis.

cancer biology↗

bioRxiv2022

Finding the best cell lines across pan-cancer to use in pre-clinical research as a proxy for patient tumor samples considering immune cells, multi-omics, and cancer pathways

In pre-clinical trials of anti-cancer drugs, cell lines are utilized as a model for patient tumor samples to understand the response of drugs. However, in vitro culture of cell lines, in general, alters the biology of the cell lines and likely gives rise to systematic differences from the tumor samples genomic profiles; hence the drug response of cell lines may deviate from actual patients drug response. In this study, we computed a similarity score for the selection of cell lines depicting the close and far resemblance to patient tumor samples in twenty-two different cancer types at genetic, genomic, and epigenetic levels integrating multi-omics datasets. We also considered the presence of immune cells in tumor samples and cancer-related biological pathways in this score which aids personalized medicine research in cancer. We showed that based on these similarity scores cell lines were able to recapitulate the drug response of patient tumor samples for several FDA-approved cancer drugs in multiple cancer types. Based on these scores, several of the high-rank cell lines were shown to have a close likeness to the corresponding tumor type in previously reported in vitro experiments.

bioinformatics↗

bioRxiv2021

Identification of distinct characteristics of antibiofilm peptides and prospection of diverse sources for efficacious sequences

A majority of microbial infections are associated with biofilms. Targeting biofilms is considered an effective strategy to limit microbial virulence while minimizing the development of antibiotic resistance. Towards this need, antibiofilm peptides are an attractive arsenal since they are bestowed with properties orthogonal to small molecule drugs. In this work, we developed machine learning models to identify the distinguishing characteristics of known antibiofilm peptides, and to mine peptide databases from diverse habitats to classify new peptides with potential antibiofilm activities. Additionally, we used the reported minimum inhibitory/eradication concentration (MBIC/MBEC) of the antibiofilm peptides to create a regression model on top of the classification model to predict the effectiveness of new antibiofilm peptides. We used a positive dataset containing 242 antibiofilm peptides, and a negative dataset which, unlike previous datasets, contains peptides that are likely to promote biofilm formation. Our model achieved a classification accuracy greater than 98% and harmonic mean of precision-recall (F1) and Matthews correlation coefficient (MCC) scores greater than 0.90; the regression model achieved an MCC score greater than 0.81. We utilized our classification-regression pipeline to evaluate 135,015 peptides from diverse sources and identified antibiofilm peptide candidates that are efficacious against preformed biofilms at micromolar concentrations. Structural analysis of the top 37 hits revealed a larger distribution of helices and coils than sheets. Sequence alignment of these hits with known antibiofilm peptides revealed that, while some of the hits showed relatively high sequence similarity with known peptides, some others did not indicate the presence of antibiofilm activity in novel sources or sequences. Further, some of the hits had previously recognized therapeutic properties or host defense traits suggestive of drug repurposing applications. Taken together, this work demonstrates a new in silicio approach to predicting antibiofilm efficacy, and identifies promising new candidates for biofilm eradication.

microbiology↗

bioRxiv2021

Significance of Oct-4 transcription factor as a pivotal therapeutic target for CD44+/24- mammary tumour initiating cells; aiming at the root of the recurrence

Breast cancer (BC) remains one of the deadliest and frequently diagnosed metastatic cancers worldwide. Cancer stem cells (CSCs) are the cell population within the tumour niche, having an epithelial to mesenchymal (EMT) transition phenotype, high self-renewal, vigorous metastatic capacity, drug resistance, and tumour relapse. Identification of targets for induction of apoptosis is essential to provide novel therapeutic approaches in BC. Our earlier studies showed that Vitamin C induces apoptotic cell death by losing redox balance in TNBC CSCs. In this study, we have attempted to identify previously unrecognized CSC survival factors that can be used as druggable targets for bCSCs apoptosis regulators isolated from the TNBC line, MDA MB 468. After a thorough literature review, Oct-4 was identified as the most promising marker for its unique abundance in cancer and absence in normal cells and the contribution of Oct-4 to the sustenance of cancer cells. We then validated a very high expression of Oct-4 in the MDA MB 468 bCSCs population using flow-cytometry. The loss of Oct-4 was carried out using siRNA-mediated knockdown in the bCSCs, followed by assessing for cellular apoptosis. Our results indicated that Oct-4 knockdown induced cell death, changes in cellular morphology, inhibited mammosphere formation, and positive for Annexin-V expression, thereby indicating the role of Oct-4 in bCSC survival. Moreover, our findings also suggest the direct interaction between Oct-4 and Vitamin C using in silico docking. This data, hence, contributes towards novel information about Oct-4 highlighting this molecule as a novel survival factor in bCSCs.

cancer biology↗

bioRxiv2020

Sca1+ cells as direct isolate (ex vivo) versus in vitro cultured exhibit differential proteomic signatures in murine skeletal muscle

Stem cell antigen-1 (Sca-1) is a glycosyl-phosphatidylinositol-anchored membrane protein that is expressed in a sub-population of muscle stem and progenitor cell types. Reportedly, Sca-1 regulates the myogenic property of myoblasts and Sca-1-/- mice exhibited defective muscle regeneration. Although the role of Sca-1 in muscle development and maintenance is well-acknowledged, molecular composition of muscle derived Sca-1+ cells is not characterized. Here, we applied a high-resolution mass spectrometry-based workflow to characterize the proteomic landscape of mouse hindlimb skeletal muscle derived Sca-1+ cells. Furthermore, we characterized the impact of the cellular microenvironments on the proteomes of Sca-1+ cells. The proteome component of freshly isolated (ex vivo) Sca-1+ cells was compared with that of Sca-1+ cells expanded in cell culture (in vitro). The analysis revealed significant differences in the protein abundances in the two conditions reflective of their functional variations. The identified proteins were enriched in various biological pathways. Notably, we identified proteins related to myotube differentiation, myotube cell development and myoblast fusion. We also identified a panel of cell surface marker proteins that can be leveraged in future to enrich Sca-1+ cells using combinatorial strategies. Comparative analysis implicated the activation of various pathways leading to increased protein synthesis under in vitro condition. We report here the most comprehensive proteome map of Sca-1+ cells that provides insights into the molecular networks operative in Sca-1+ cells. Importantly, through our work we generated the proteomic blueprint of protein abundances significantly altered in Sca-1+ cells under ex vivo and in vitro conditions.

systems biology↗

bioRxiv2020

CTDPathSim: Cell line-tumor deconvoluted pathway-based similarity in the context of precision medicine in cancer

In cancer research and drug development, human tumor-derived cell lines are used as popular model for cancer patients to evaluate the biological functions of genes, drug efficacy, side-effects, and drug metabolism. Using these cell lines, the functional relationship between genes and drug response and prediction of drug response based on genomic and chemical features have been studied. Knowing the drug response on the real patients, however, is a more important and challenging task. To tackle this challenge, some studies integrate data from primary tumors and cancer cell lines to find associations between cell lines and tumors. These studies, however, do not integrate multi-omics datasets to their full extent. Also, several studies rely on a genome-wide correlation-based approach between cell lines and bulk tumor samples without considering the heterogeneous cell population in bulk tumors. To address these gaps, we developed a computational pipeline, CTDPathSim, a pathway activity-based approach to compute similarity between primary tumor samples and cell lines at genetic, genomic, and epigenetic levels integrating multi-omics datasets. We utilized a deconvolution method to get cell type-specific DNA methylation and gene expression profiles and computed deconvoluted methylation and expression profiles of tumor samples. We assessed CTDPathSim by applying on breast and ovarian cancer data in The Cancer Genome Atlas (TCGA) and cancer cell lines data in the Cancer Cell Line Encyclopedia (CCLE) databases. Our results showed that highly similar sample-cell line pairs have similar drug response compared to lowly similar pairs in several FDA-approved cancer drugs, such as Paclitaxel, Vinorelbine and Mitomycin-c. CTDPathSim outperformed state-of-the-art methods in recapitulating the known drug responses between samples and cell lines. Also, CTDPathSim selected higher number of significant cell lines belonging to the same cancer types than other methods. Furthermore, our aligned cell lines to samples were found to be clinical biomarkers for patients survival whereas unaligned cell lines were not. Our method could guide the selection of appropriate cell lines to be more intently serve as proxy of patient tumors and could direct the pre-clinical translation of drug testing into clinical platform towards the personalized therapies. Furthermore, this study could guide the new uses for old drugs and benefits the development of new drugs in cancer treatments. CCS CONCEPTSO_LIComputational biology C_LIO_LIGenomics C_LIO_LISystems biology C_LIO_LIBioinformatics C_LIO_LIGenetics C_LI ACM Reference formatBanabithi Bose, Serdar Bozdag. 2020. CTDPathSim: Cell line-tumor deconvoluted pathway-based similarity in the context of precision medicine in cancer.

bioinformatics↗

bioRxiv2020

DEBay: a computational tool for deconvolution of quantitative PCR data for estimation of cell type-specifc gene expression in a mixed population

The expression of a gene is commonly estimated by quantitative PCR (qPCR) using RNA isolated from a large number of pooled cells. Such pooled samples often have subpopulations of cells with different levels of expression of the target gene. Estimation of gene expression from an ensemble of cells obscures the pattern of expression in different subpopulations. Physical separation of various subpopulations is a demanding task. We have developed a computational tool, Deconvolution of Ensemble through Bayes-approach (DEBay), to estimate cell type-specific gene expression from qPCR data of a mixed population. DEBay estimates Normalized Gene Expression Coefficient (NGEC), which is a relative measure of the expression of the target gene in each cell type in a population. NGEC has a direct algebraic correspondence with the normalized fold change in gene expression measured by qPCR. DEBay can deconvolute both time-dependent and -independent gene expression profiles. It uses the Bayesian method of model selection and parameter estimation. We have evaluated DEBay using synthetic and real experimental data. DEBay is implemented in Python. A GUI of DEBay and its source code are available for download at SourceForge (https://sourceforge.net/projects/debay).

bioinformatics↗

bioRxiv2019

miRDriver: A Tool to Infer Copy Number Derived miRNA-Gene Networks in Cancer

Copy number aberration events such as amplifications and deletions in chromosomal regions are prevalent in cancer patients. Frequently aberrated copy number regions include regulators such as microRNAs (miRNAs), which regulate downstream target genes that involve in the important biological processes in tumorigenesis and proliferation. Many previous studies explored the miRNA-gene interaction networks but copy number-derived miRNA regulations are limited. Identifying copy number-derived miRNA-target gene regulatory interactions in cancer could shed some light on biological mechanisms in tumor initiation and progression. In the present study, we developed a computational pipeline, called miRDriver which is based on the hypothesis that copy number data from cancer patients can be utilized to discover driver miRNAs of cancer. miRDriver integrates copy number aberration, DNA methylation, gene and miRNA expression datasets to compute copy number-derived miRNA-gene interactions in cancer. We tested miRDriver on breast cancer and ovarian cancer data from the Cancer Genome Atlas (TCGA) database. miRDriver discovered some of the known miRNAs, such as miR-125b, mir-320d, let-7g, and miR-21, which are known to be in copy number aberrated regions in breast cancer. We also discovered some potentially novel miRNA-gene interactions. Also, several miRNAs such as miR-127, miR-139 and let-7b were found to be associated with tumor survival and progression based on Cox proportional hazard model. We compared the enrichment of known miRNA-gene interactions computed by miRDriver with the enrichment of interactions computed by the state-of-the-art methods and miRDriver outperformed all the other methods.\n\nCCS CONCEPTSO_LIBioinformatics\nC_LIO_LIComputational Genomics\nC_LIO_LIBiological Networks\nC_LI

bioinformatics↗

bioRxiv2017

A Negative Feedback Regulates The Flow Of Signal Through Akt/mTORC1/S6K1 Pathway

AbstractSeveral growth factors, cytokines, hormones activate PI3K/Akt pathway. Akt is a key node in this pathway and activates different downstream paths. One such path is Akt/mTORC1/S6K1 that controls protein synthesis, cell survival, and proliferation. Here we show that a negative feedback controls activation of S6K1 through this pathway. Due to this negative feedback, a sustained phospho-Akt signal generates a transient pulse of phospho-S6K1. We have created a mathematical model for this circuit. Analysis of this model shows that the negative feedback acts as a filter and preferentially allows a signal, with sharp and faster rise of phospho-Akt, to induce pronounced activation of S6K1. It blocks an input with a fast oscillation of phospho-Akt to flow through this path. We show that this negative feedback leads to differential activation of S6K1 by Insulin and Insulin-like Growth Factor 1. Such differential effect may explain the difference in the mitogenic effect of these two molecules.

systems biology↗