Biology subjects

Chowdhury, D.

Publications and source records attributed to Chowdhury, D..

At least 19 recordsLinked to original sources

bioRxiv2026

The TIRR–53BP1 axis controls PLK1 spatiotemporal regulation during mitosis

p53-binding protein 1 (53BP1) is a key mediator of the DNA damage response and genome stability. While its interphase function is well-characterized, its mitotic role remains less understood. Here we show that aberrant activation of 53BP1 through the loss of its negative regulator, TIRR, leads to mitotic abnormalities including altered spindle geometry, kinetochore-microtubule (k-MT) attachment errors and whole chromosome missegregation. We demonstrate that loss of TIRR results in excess interaction between 53BP1 and the key mitotic kinase Polo-like kinase 1 (PLK1), altering PLK1s activation, spatial distribution, and its interaction with known PLK1 substrates at multiple mitotic stages. Moreover, due to PLK1s established role in CENP-A loading, hyperactivation of 53BP1 compromises CENP-A loading, triggers gradual loss of CENP-A from centromeres and generates severe kinetochore assembly defects. These findings uncover a non-canonical mitotic function of 53BP1 as a key regulator of PLK1 activity and chromosome segregation fidelity.

Cell Biology↗

bioRxiv2026

H3K27M-driven hypertranscription leads to a new targetable dependency in diffuse midline gliomas

Diffuse midline gliomas (DMGs) are driven by the H3K27M oncohistone--a challenging therapeutic target. However, conventional therapeutic modalities are never curative. Against this backdrop, we address an important unresolved question--are there H3K27M-induced oncogenic vulnerabilities that can be exploited for therapeutic benefit. We show that H3K27M induces hypertranscription, thus identifying hypertranscription as a new molecular feature of H3K27M-driven DMGs. We demonstrate this finding in genetic mouse models, human DMG cells, and primary tumor specimens. We further demonstrate that H3K27M-induced hypertranscription perturbs replication, heightens basal replication stress, and enhances sensitivity to ATR inhibition. In exploring therapeutic implications of these findings, we document brain penetrance, target engagement, and therapeutic efficacy of a clinical-stage ATR inhibitor (alnodesertib) in vitro and in intracranial DMG xenografts. We further demonstrate synergistic activity of alnodesertib with radiotherapy--the current standard of care for DMGs. These findings provide the mechanistic underpinning and preclinical rationale for including alnodesertib as monotherapy and in combination with radiation in clinical trials for children with H3K27M DMGs. The broad implications of our studies highlight ATR inhibition as a therapy for aggressive human cancers displaying hypertranscription.

cancer biology↗

bioRxiv2025

Human CDK5-cyclin B1 structures uncover a conserved mitotic CDK activation mechanism

Cyclin-dependent kinase 5 (CDK5), long considered atypical and activated by non-cyclin cofactors in neurons, also functions in mitosis. To resolve its activation mechanism during mitosis, we determined the first high-resolution crystal structures of CDK5-cyclin B1 in apo and nucleotide-bound states. Contrary to AlphaFold predictions, we find CDK5 structures unexpectedly mirrors CDK1-cyclin B1 assembly and activation, establishing CDK5 as a bona fide mitotic kinase acting in parallel with CDK1.

biochemistry↗

bioRxiv2025

Chromatin Perturbation Promotes Susceptibility to Hypomethylating Agents

Cancer-directed drugs are often clinically deployed without definitive understanding of their molecular mechanisms of action (MOA). Hypomethylating agents (HMAs), which result in the degradation of the DNA methyltransferase 1 (DNMT1), have been deployed for decades in the treatment of haematological malignancies1,2. The precise mechanism of action of these drugs, however, has been debated, rendering the design of rational combination therapies challenging. Here, we identified the deubiquitinating enzyme USP48 as a crucial regulator of posttranslational histone modification in the context of DNA demethylation. USP48 loss selectively enhances response to DNMT1 inhibition, leading to a rapid induction of cell death. We demonstrate that USP48 is localized at sites of DNA damage and deubiquitinates H2A variants and proteins important for DNA damage repair. Functionally, loss of USP48 triggers an increase in chromatin accessibility upon HMA treatment, rendering AML cells more susceptible to DNA damage. Our results support USP48 as a posttranslational histone modifier for chromatin stability and DNA damage in response to HMA-related DNA demethylation. These findings propose USP48 as a new target for combination therapy with HMAs for acute myeloid leukaemia (AML).

cancer biology↗

bioRxiv2025

Future flooding tolerant rice germplasm: resilience afforded beyond Sub1A gene

Developing high-yielding, flood-tolerant rice varieties is essential for enhancing productivity and livelihoods in flood-prone ecologies. We explored genetic avenues beyond the well-known SUB1A gene to improve flood resilience in rice. We screened a collection of 6,274 elite genotypes from IRRIs germplasm repository for submergence and stagnant flooding tolerance over multiple seasons and years. This rigorous screening identified 89 outstanding elite genotypes, among which thirty-seven exhibited high submergence tolerance, surpassing the survival rate of SUB1A introgression genotypes by 40-50%. Thirty-five genotypes showed significant tolerance to stagnant flooding, and 17 demonstrated dual tolerance capabilities, highlighting their adaptability to varying flood conditions. The genotypes identified have a broader genetic diversity and harbor 86 key QTLs and genes related to traits such as grain quality, grain yield, herbicide resistance, and various biotic and abiotic traits, highlighting the richness of the identified elite collection. Besides germplasm, we introduce an innovative breeding approach called Transition from Trait to Environment (TTE). TTE leverages a parental pool of high-performing genotypes with complete submergence tolerance to drive population improvement and enable genomic selection in the flood breeding program. Our approach of TTE achieved a remarkable 65% increase in genetic gain for submergence tolerance, with the resulting fixed breeding genotypes demonstrating exceptional performance in flood-prone environments of India and Bangladesh. The elite genotypes identified herein represent invaluable genetic resources for the global rice research community. By adopting the TTE approach, which is trait agonistic, we establish a robust framework for developing more resilient genotypes using advanced breeding tools. Plain Language SummaryTo address climate challenges, an urgent focus is necessary to identify and develop flood-tolerant rice varieties, particularly for flood-prone ecosystems across Asia and Africa. We screened 6,274 elite genotypes from IRRIs germplasm and identified 89 promising lines with improved tolerance to submergence and stagnant flooding. Among these, 37 demonstrated 40-50% greater submergence tolerance than SUB1A introgression lines, 35 exhibited stagnant flooding tolerance, and 17 showed dual tolerance. These genotypes contain 86 key QTLs and genes associated with yield, grain quality, and biotic and abiotic tolerance traits. A new breeding strategy, the Transition from Trait to Environment (TTE) approach, was developed. We achieved a genetic gain of 65% for submergence tolerance in rice using this method. The newly identified germplasm provides invaluable genetic resources for the global rice research community to develop flood-tolerant rice genotypes. Core ideas The SUB1A gene, enabling rice to survive underwater for 14 days, marked a significant breakthrough. We have identified elite genotypes with submergence tolerance significantly surpassing the SUB1A gene-mediated tolerance. The diverse elite genotypes identified harbor 86 key genes and QTLs that affect various traits positively. Developed a unique breeding strategy for implementing population improvement in challenging environments. The new breeding strategy demonstrated a genetic gain of 65% for submergence tolerance.

plant biology↗

bioRxiv2024

Comprehensive Enumeration of Cancer Stem-like Cell Heterogeneity Using Deep Neural Network

Cancer stem cells (CSCs), a distinct subpopulation within tumors, are pivotal in driving treatment resistance and tumor recurrence, posing substantial challenges to conventional therapeutic strategies. Precise quantification and profiling of these cells are essential for improving cancer treatment outcomes. We present ACSCeND, an advanced deep neural network model accompanied by a robust workflow, specifically developed to quantify cellular compositions from bulk RNA-seq data, enabling accurate CSC profiling. By integrating bulk RNA-seq data with insights derived from single-cell RNA-seq datasets, ACSCeND effectively captures the diversity and hierarchical organization of tumor-resident cell states, alongside cell-specific gene expression profiles (GEPs). Compared to current tissue deconvolution models, ACSCeND exhibits superior performance, achieving significantly higher Concordance Correlation Coefficient (CCC) values and lower Root Mean Square Error (RMSE) across various pseudobulk and real-world bulk tissue samples. Application of ACSCeND to TCGA and PRECOG datasets reveals a strong association between CSC abundance and poorer disease-free survival outcomes, underscoring the clinical relevance of CSCs in cancer progression. Furthermore, cell-specific GEPs for distinct CSC states unveil novel molecular signatures and illuminate the origins of CSC-driven tumor heterogeneity. In summary, ACSCeND provides a powerful, scalable platform for high-throughput quantification of cellular compositions and distinct potency states within normal tissues as well as highly heterogeneous tissues, such as tumors.

genomics↗

bioRxiv2023

A compendium of Amplification-Related Gain Of Sensitivity (ARGOS) genes in human cancer

Chromosomal gains are among the most frequent somatic genetic alterations occurring in cancer. While the effect of sustained oncogene expression has been characterized, the impact of copy-number gains affecting collaterally-amplified "bystander" genes on cellular fitness remains less understood. To investigate this, we built a comprehensive map of dosage compensations across human cancers by integrating expression and copy number profiles from over 8,000 TCGA tumors and CCLE cell lines. Further, we analyzed the effect of gene overexpression across 17 human cancer ORF screens to provide an overview of genes that prove toxic to cancer cells when overexpressed. Combining these two independent approaches we propose a class of Amplification-Related Gain Of Sensitivity (ARGOS) genes. These genes are located in commonly amplified regions of the genome, have lower expression levels than expected by their copy-number status, and are toxic to cancer cells when overexpressed. We experimentally validated CDKN1A and RBM14 as high-confidence pan-cancer ARGOS genes in lung and breast cancer cell line models. We additionally suggest that RBM14s mechanism of toxicity involves altered DNA damage response and innate immune signaling processes following gene overexpression. Finally, we provide a comprehensive catalog of compensated, toxic, and ARGOS genes as a community resource.

cancer biology↗

bioRxiv2023

Next-Gen Profiling of Tumor-resident Stem Cells using Machine learning

Tumor-resident stem cells, also known as cancer stem cells (CSCs), constitute a subgroup within tumors, play a crucial role in fostering resistance to treatment and the recurrence of tumors, and pose significant challenges for conventional therapeutic methods. Existing approaches for identifying CSCs face notable hurdles related to scalability, reproducibility, and technical consistency across different cancer types due to the adaptable nature of CSCs. In this context, we introduce OSCORP, an innovative machine-learning-driven approach. This methodology quantifies and identifies CSCs, achieving almost 99% accuracy using biopsy bulk RNAseq data. OSCORP leverages genetic similarities between normal and cancer stem cells. By categorizing CSCs into four distinct yet dynamic potency states, this approach provides insights into the differentiation landscape of CSCs, unveiling previously undisclosed facets of tumor heterogeneity. In evaluations conducted on patient samples across 22 cancer types, OSCORP revealed clinical, transcriptomic, and immunological signatures associated with each CSC state. It has emerged as a comprehensive tool for understanding and addressing the complexities of cancer stem cells. Ultimately, OSCORP opens up new possibilities for more effective personalized cancer therapies and holds the potential to serve as a clinical tool for monitoring patient-specific CSC changes during treatment or follow-up care.

cancer biology↗

bioRxiv2023

An autoinhibited state of 53BP1 revealed by chemical probes and protein engineering

The recruitment of 53BP1 to chromatin, mediated by its recognition of histone H4 dimethylated at lysine 20 (H4K20me2), is important for DNA double-strand break repair. Using a series of small molecule antagonists, we demonstrate a conformational equilibrium between an open and a pre-existing lowly populated closed state of 53BP1 in which the H4K20me2 binding surface is buried at the interface between two interacting 53BP1 molecules. In cells, these antagonists inhibit the chromatin recruitment of wild type 53BP1, but do not affect 53BP1 variants unable to access the closed conformation despite preservation of the H4K20me2 binding site. Thus, this inhibition operates by shifting the conformational equilibrium toward the closed state. Our work therefore identifies an auto-associated form of 53BP1 -- autoinhibited for chromatin binding -- that can be stabilized by small molecule ligands encapsulated between two 53BP1 protomers. Such ligands are valuable research tools to study the function of 53BP1 and have the potential to facilitate the development of new drugs for cancer therapy.

biochemistry↗

bioRxiv2023

Methotrexate-modulated talin-dynamics drives cellular mechanical phenotypes via YAP signalling

Methotrexate is a well-known antineoplastic drug used to prevent cancer aggravation. Despite being a targeted therapeutic approach, its administration comes with the risk of cancer recurrence, plausibly through its proven off-target effect on focal adhesions. Since FA dynamics is dependent on force transmission through its constituent proteins, including talin, methotrexate might affect the mechanical activity of these proteins. Here we have combined single-molecule studies, computational dynamics, cell-based assays, and genomic analysis to unveil the focal adhesion-regulating role of methotrexate central to its effect on talin dynamics and downstream pathways. Interestingly, our single-molecule force spectroscopic study shows that methotrexate modulates the bimodal force distribution of talin in a concentration-dependent manner. Steered molecular dynamics reveal that methotrexate-talin interactions alter talin mechanical stability exposing their vinculin binding sites. Finally, we found that methotrexate-regulated talin-dynamics remodel cancer cell mechanical phenotypes like cell polarity, adhesion, and migration by regulating talin-vinculin association-mediated YAP signaling. These results further correlate with genomic analysis of methotrexate-treated patients, demonstrating its clinical importance. Taken together, these findings disseminate the effects of methotrexate-modulated mechanosensitivity of adhesion proteins on cellular events.

cell biology↗

bioRxiv2023

Dynamics of the DYNLL1/MRE11 complex regulates DNA end resection and recruitment of the Shieldin complex to DSBs

Extent and efficacy of DNA end resection at DNA double strand break (DSB)s determines the choice of repair pathway. Here we describe how the 53BP1 associated protein DYNLL1 works in tandem with Shieldin and the CST complex to protect DNA ends. DYNLL1 is recruited to DSBs by 53BP1 where it limits end resection by binding and disrupting the MRE11 dimer. The Shieldin complex is recruited to a fraction of 53BP1-positive DSBs hours after DYNLL1 predominantly in the G1 cells. Shieldin localization to DSBs is dependent on MRE11 activity and is regulated by the interaction of DYNLL1 with MRE11. BRCA1-deficient cells rendered resistant to PARP inhibitors by the loss of Shieldin proteins can be re-sensitized by the constitutive association of DYNLL1 with MRE11. These results define the temporal and functional dynamics of the 53BP1-centric DNA end resection factors in cells.

molecular biology↗

bioRxiv2023

Force-regulated chaperone activity of BiP/ERdj3 is opposite to their homologs DnaK/DnaJ: explained by strain energy

Polypeptide chains experiences mechanical tension while translocating through cellular tunnel. In this scenario, interaction of tunnel-associated chaperones with the emerging polypeptide occurs under force; however, this force-regulated chaperone behaviour is not fully understood. We studied the mechanical chaperone activity of two tunnel-associated chaperones BiP and ERdj3 both in the absence and presence of force; and compared to their respective cytoplasmic homologs DnaK and DnaJ. We found that BiP/ERdj3 shows strong foldase activity under force; whereas their cytoplasmic homolog DnaK/DnaJ behave as holdase. Importantly, these tunnel-associated chaperones (BiP/ERdj3) revert to holdase in the absence of force, suggesting that mechanical chaperone activity differs depending on the presence or absence of force. This tunnel-associated chaperone-driven folding event generates additional mechanical energy of up to 54 zJ that could help protein translocation. The mechanical-chaperone behaviour can be explained by strain theory: chaperones with higher intrinsic deformability function as mechanical foldase (BiP, ERdj3), while chaperones with lower intrinsic deformability act as holdase (DnaK and DnaJ). Our study thus unveils the underlying mechanism of mechanically regulated chaperoning activity and provides a novel mechanism of co-translocational protein folding. SignificanceThe mechanical-activity of chaperones, located at the edge of a tunnel, could be different from their cytoplasmic homologs. Translocating substrates within the tunnel are known to experience mechanical constraints, whereas the cytosolic substrates interact with the chaperones in the absence of force. To understand this phenomenon, we investigated two tunnel-associated chaperones BiP/ERdj3 and their cytosolic homologs-DnaK/DnaJ. We observed that BiP/ERdj3 possess strong foldase activity while their substrates are under force; whereas DnaK/DnaJ possess holdase function. Notably all these chaperones function as holdase in the absence of force, which suggest that mechanical chaperone activity is different with and without force. We explained this mechanical behaviour using strain theory, providing a physical mechanism of chaperone-assisted co-translocational protein folding.

biophysics↗

bioRxiv2023

An explainable artificial intelligence-based typification of chronic inflammatory responses enhances glioma prognosis

Glioma is one of the most aggressive solid brain tumors with a poor prognosis. A chronic tumor inflammatory microenvironment drives glioma promotion and progression. The neutrophil-to-lymphocyte ratio and other clinicopathological variables usually serve as prognostic glioma markers. However, they are not ubiquitous prognostic markers for glioma as they fail to reveal the intricacy between the glioma-specific tumor inflammatory microenvironment and the systemic inflammatory responses, especially those chronic inflammatory responses, which vary among individuals fabricating diverse prognostic outcomes. Here, we introduced an explainable artificial intelligence model to typify chronic inflammatory responses as prognostic markers for glioma using 694-patients data from The Cancer Genome Atlas. We characterized the glioma-specific personalized inflammatory mediators using multi-layered regulators such as transcriptional networks, cellular infiltration markers, and cellular senescence markers, which identified five unique chronic inflammatory responses (p-value<0.0001). We defined its prognostic significance using overall survival analyses. The chronic inflammatory responses were positively correlated with poor overall survival in glioma. The patients with higher chronic inflammatory responses showed significantly shorter overall survival than those with lower chronic inflammatory responses. Interestingly, optimizing those chronic inflammatory responses improved the overall survival of glioma patients. We identified the effector genes within the personalized inflammatory mediators networks, indicating them as the targets for optimizing individualized chronic inflammatory response profiles through co-drug intervention. SignificanceExplainable artificial intelligence-based typification of chronic inflammatory responses accelerates glioma prognosis and supports co-drug discovery to modulate inflammatory responses alongside cancer therapy, suggested by 694-glioma patients data analysis.

systems biology↗

bioRxiv2022

Pan-cancer Analysis Predicts Kindlin-associated Global Mechanochemical Perturbation

Kindlins are mechanosensitive adapter proteins that connect extracellular mechanical cues to intracellular chemical events. Any alterations in these proteins thus alter cellular signaling, which could result in cancer progression. However, their involvement in global mechanochemical signals remains elusive in cancers. Here we analyze pan-cancer samples to decipher how kindlin alterations aid cancer progression. We show that kindlin alterations, at both the genetic and mRNA level, dysregulates cellular behavior which significantly correlate with poor survival. We find that while these alterations are cancer-specific, they are prevalent in advanced tumor stages and metastatic onset. We observe that kindlins co-alter with a substantial fraction of human mechanochemical proteome in various tumors. Our analysis suggests how kindlin alterations aid tumor-promoting signals with a synergistic effect from alterations of cancer-hallmark genes. Notably, we demonstrate a consistent alteration of epithelial-mesenchymal-transition markers with kindlin activity. Overall, our study highlights how kindlin alterations could affect metabolism, genomic instability, and signal disruption via their interactome network, causing cancer and suggests targeting them as a therapeutic strategy.

cancer biology↗

bioRxiv2022

OmicSelector: automatic feature selection and deep learning modeling for omic experiments.

A crucial phase of modern biomarker discovery studies is selecting the most promising features from high-throughput screening assays. Here, we present the OmicSelector - Docker-based web application and R package that facilitates the analysis of such experiments. OmicSelector provides a consistent and overfitting-resilient pipeline that integrates 94 feature selection approaches based on 25 distinct variable selection methods. It identifies and then ranks the best feature sets using 11 modeling techniques with hyperparameter optimization in hold-out or cross-validation. OmicSelector provides classification performance metrics for proposed feature sets, allowing researchers to choose the overfitting-resistant biomarker set with the highest diagnostic potential. Finally, it performs GPU-accelerated development, validation, and implementation of deep learning feedforward neural networks (up to 3 hidden layers, with or without autoencoders) on selected signatures. The application performs an extensive grid search of hyperparameters, including balancing and preprocessing of next-generation sequencing (e.g. RNA-seq, miRNA-seq) oraz qPCR data. The pipeline is applicable for determining candidate circulating or tissue miRNAs, gene expression data and methylomic, metabolomic or proteomic analyses. As a case study, we use OmicSelector to develop a diagnostic test for pancreatic and biliary tract cancer based on serum small RNA next-generation sequencing (miRNA-seq) data. The tool is open-source and available at https://biostat.umed.pl/OmicSelector/

bioinformatics↗

bioRxiv2022

Trimethylamine N-oxide (TMAO) enhances substrate mechanical stability probed by single molecule magnetic tweezers

Trimethylamine N-oxide (TMAO) is a well-known osmolyte to stabilize the folded proteins through a variety of mechanisms. Since mechanical strength of proteins is a critical determinant of its stabilization, TMAO might play a relevant role by favoring its folding dynamics or by enhancing its mechanical stability. To address this question, we have performed the single-molecule magnetic tweezers experiment to explore the TMAO effect on two structurally distinct substrates-protein L and talin. We observed that TMAO increases the mechanical stability of these proteins through increasing their unfolding force. Additionally, we are able to demonstrate that TMAO retards the unfolding kinetics, while accelerating the refolding kinetics under force; which eventually tilts the energy landscape towards the folded state. Interestingly, this TMAO-enhanced protein folding generates mechanical work output upto [~]67 zJ, allowing the protein folding under higher force regime. Overall this TMAO-enhanced mechanical stability provides a significant implication to folding-induced structural stability of proteins.

biophysics↗

bioRxiv2022

ReDisX: a Continuous Max Flow-based framework to redefine the diagnosis of diseases based on identified patterns of genomic signatures

Diseases originate at the molecular-genetic layer, manifest through altered biochemical homeostasis, and develop symptoms later. Hence symptomatic diagnosis is inadequate to explain the underlying molecular-genetic abnormality and individual genomic disparities. The current trends include molecular-genetic information relying on algorithms to recognize the disease subtypes through gene expressions. Despite their disposition toward disease-specific heterogeneity and cross-disease homogeneity, a gap still exists to describe the extent of homogeneity within the heterogeneous subpopulation of different diseases. They are limited to obtaining the holistic sense of the whole genome-based diagnosis resulting in inaccurate diagnosis and subsequent management. To fill those gaps, we proposed ReDisX framework, a scalable machine learning algorithm that uniquely classifies patients based on their genomic signatures. It was deployed to re-categorizes the patients with rheumatoid arthritis and coronary artery disease. It reveals heterogeneous subpopulations within a disease and homogenous subpopulations across different diseases. Besides, it identifies GZMB as a subpopulation-differentiation marker that plausibly serves as a prominent indicator for GZMB-targeted drug repurposing. The ReDisX framework offers a novel strategy to redefine disease diagnosis through characterizing personalized genomic signatures. It may rejuvenate the landscape of precision and personalized diagnosis, and a clue to drug repurposing.

bioinformatics↗

bioRxiv2022

Talin-drug interaction reveals a key molecular determinant for biphasic mechanical effect: studied under single-molecule resolution

Talin as an adhesion protein, exhibits a strong force-dependent structure-function dynamics. Being a mechanosensitive focal adhesion (FA) protein, talin might interact to several FA targeting drugs; however, the molecular mechanism of talin-drug interactions remains elusive. Here we combined magnetic tweezers and molecular dynamics (MD) simulation to explore mechanical stability of talin with three drugs based on their talin specificity. Interestingly, our study revealed that talin displays a bimodal force distribution with a low and high unfolding force population. We observed that talin nonspecific drugs (tamoxifen and letrozole) display biphasic effect: increase talin mechanical stability upto optimum concentration, followed by a decrease in stability with further concentration increase. By contrast, talin-specific cyanidin 3-O-glucoside promotes a steady increase to talin mechanical stability with its concentration. We reconciled our observation from the simulation study: tamoxifen enters into talin hydrophobic core, eventually destabilizing the protein; whereas cyanidin 3-O-glucoside stabilizes the protein core by maintaining the inter-helix distance. Finally, we observed a strong correlation among hydrophobicity and cavity analysis, illustrating a detailed mechanistic analysis of drug effect on the mechanosensitive protein. Overall this study presents a novel perspective for drug designing against mechanosensitive proteins and studying off-target effects of already known drugs.

biophysics↗