Biology subjects

Mitra, R.

Publications and source records attributed to Mitra, R..

31 records · Page 2Linked to original sources

bioRxiv2024

SIRT6 loss causes intervertebral disc degeneration in mice by promoting senescence and SASP status

Intervertebral disc degeneration is a major risk factor contributing to chronic low back and neck pain. While the etiological factors for disc degeneration vary, age is still one of the most important risk factors. Recent studies have shown the promising role of SIRT6 in mammalian aging and skeletal tissue health, however its role in the intervertebral disc health remains unexplored. We investigated the contribution of SIRT6 to disc health by studying the age-dependent spinal phenotype of mice with conditional deletion of Sirt6 in the disc (AcanCreERT2; Sirt6fl/fl). Histological studies showed a degenerative phenotype in knockout mice compared to Sirt6fl/fl control mice at 12 months which became pronounced at 24 months. RNA-Seq analysis of NP and AF tissues, quantitative histone analysis, and in vitro multiomics employing RNA-seq with ATAC-seq revealed that SIRT6-loss resulted in changes in acetylation and methylation status of specific Histone 3 lysine residues, thereby affecting DNA accessibility and transcriptomic landscape. A decrease in autophagy and an increase in DNA damage were also noted in Sirt6-deficient cells. Further mechanistic insights revealed that loss of SIRT6 increased senescence and SASP burden in the disc characterized by increased p21, {gamma}H2AX, IL-6, and TGF-{beta} abundance. Taken together our study highlights the contribution of SIRT6 in modulating DNA damage, autophagy and cell senescence, and its importance in maintaining disc health during aging thereby underscoring it as a potential therapeutic target to treat intervertebral disc degeneration.

molecular biology↗

bioRxiv2024

Molecular insights into the interaction between a disordered protein and a folded RNA

Intrinsically disordered protein regions (IDRs) are well-established as contributors to intermolecular interactions and the formation of biomolecular condensates. In particular, RNA-binding proteins (RBPs) often harbor IDRs in addition to folded RNA-binding domains that contribute to RBP function. To understand the dynamic interactions of an IDR-RNA complex, we characterized the RNA-binding features of a small (68 residues), positively charged IDR-containing protein, SERF. At high concentrations, SERF and RNA undergo charge-driven associative phase separation to form a protein- and RNA-rich dense phase. A key advantage of this model system is that this threshold for demixing is sufficiently high that we could use solution-state biophysical methods to interrogate the stoichiometric complexes of SERF with RNA in the one-phase regime. Herein, we describe our comprehensive characterization of SERF alone and in complex with a small fragment of the HIV-1 TAR RNA (TAR) with complementary biophysical methods and molecular simulations. We find that this binding event is not accompanied by the acquisition of structure by either molecule; however, we see evidence for a modest global compaction of the SERF ensemble when bound to RNA. This behavior likely reflects attenuated charge repulsion within SERF via binding to the polyanionic RNA and provides a rationale for the higher-order assembly of SERF in the context of RNA. We envision that the SERF-RNA system will lower the barrier to accessing the details that support IDR-RNA interactions and likewise deepen our understanding of the role of IDR-RNA contacts in complex formation and liquid-liquid phase separation. SIGNIFICANCESubcellular organization through the formation of biomolecular condensates has emerged as an important contributor to myriad cellular functions, with implications in homeostasis, stress response, and disease. To understand the general and specific principles that support condensate formation, we must interrogate the interactions and assembly of their constituent biomolecules. To this end, this study introduces a simple model system comprised of a small, disordered protein and small RNA that undergo charge-driven, associative phase separation. In addition to extensive biophysical characterization of these molecules and their complex, we also generate new insights into mode of interaction and assembly between an unstructured protein and a structured RNA.

biochemistry↗

bioRxiv2024

PNAbind: Structure-based prediction of protein-nucleic acid binding using graph neural networks

The recognition and binding of nucleic acids (NAs) by proteins depends upon complementary chemical, electrostatic and geometric properties of the protein-NA binding interface. Structural models of protein-NA complexes provide insights into these properties but are scarce relative to models of unbound proteins. We present a deep learning approach for predicting protein-NA binding given the apo structure of a protein (PNAbind). Our method utilizes graph neural networks to encode spatial distributions of physicochemical and geometric properties of the protein molecular surface that are predictive of NA binding. Using global physicochemical encodings, our models predict the overall binding function of a protein and can discriminate between specificity for DNA or RNA binding. We show that such predictions made on protein structures modeled with AlphaFold2 can be used to gain mechanistic understanding of chemical and structural features that determine NA recognition. Using local encodings, our models predict the location of NA binding sites at the level of individual binding residues. Binding site predictions were validated against benchmark datasets, achieving AUROC scores in the range of 0.92-0.95. We applied our models to the HIV-1 restriction factor APOBEC3G and show that our predictions are consistent with experimental RNA binding data.

bioinformatics↗

bioRxiv2023

DeepPBS: Geometric deep learning for interpretable prediction of protein-DNA binding specificity

Predicting specificity in protein-DNA interactions is a challenging yet essential task for understanding gene regulation. Here, we present Deep Predictor of Binding Specificity (DeepPBS), a geometric deep-learning model designed to predict binding specificity across protein families based on protein-DNA structures. The DeepPBS architecture allows investigation of different family-specific recognition patterns. DeepPBS can be applied to predicted structures, and can aid in the modeling of protein-DNA complexes. DeepPBS is interpretable and can be used to calculate protein heavy atom-level importance scores, demonstrated as a case-study on p53-DNA interface. When aggregated at the protein residue level, these scores conform well with alanine scanning mutagenesis experimental data. The inference time for DeepPBS is sufficiently fast for analyzing simulation trajectories, as demonstrated on a molecular-dynamics simulation of a Drosophila Hox-DNA tertiary complex with its cofactor. DeepPBS and its corresponding data resources offer a foundation for machine-aided protein-DNA interaction studies, guiding experimental choices and complex design, as well as advancing our understanding of molecular interactions.

bioinformatics↗

bioRxiv2023

Orai mediated Calcium entry sets the excitability threshold of central dopaminergic neurons by regulation of gene expression

Maturation and fine-tuning of neural circuits frequently requires neuromodulatory signals that set the excitability threshold, neuronal connectivity and synaptic strength. Here we present a mechanistic study of how neuromodulator stimulated intracellular Ca2+ signals, through the store - operated Ca2+ channel Orai, regulate intrinsic neuronal properties by control of developmental gene expression in flight promoting central dopaminergic neurons (fpDANs). The fpDANs receive cholinergic inputs for release of dopamine at a central brain tripartite synapse that sustains flight (Sharma and Hasan, 2020). Cholinergic inputs act on the muscarinic acetylcholine receptor to stimulate intracellular Ca2+ release through the endoplasmic reticulum (ER) localised inositol 1,4,5-trisphosphate receptor followed by ER-store depletion and Orai mediated store-operated Ca2+ entry (SOCE). Analysis of gene expression in fpDANs followed by genetic, cellular and molecular studies identified Orai-mediated Ca2+ entry as a key regulator of excitability in fpDANs during circuit maturation. SOCE activates the transcription factor Trithorax-like (Trl) which in turn drives expression of a set of genes including Set2, that encodes a histone 3 Lysine 36 methyltransferase (H3K36me3). Set2 function establishes a positive feedback loop, essential for receiving neuromodulatory cholinergic inputs and sustaining SOCE. Chromatin modifying activity of Set2 changes the epigenetic status of fpDANs and drives expression of key ion channel and signaling genes that determine fpDAN activity. Loss of activity reduces the axonal arborisation of fpDANS within the MB lobe, and prevents dopamine release required for maintenance of long flight. HighlightsO_LIStore-operated Ca2+ entry (SOCE) through Orai is required in a set of flight-promoting central dopaminergic neurons (fpDANs) during late pupae and early adults to establish their gene expression profile. C_LIO_LISOCE activates a homeobox transcription factor, Trithorax-like and thus regulates expression of histone modifiers Set2 and E(z) to generate a balance between opposing epigenetic signatures of H3K36me3 and H3K27me3 on downstream genes. C_LIO_LISOCE drives a transcriptional feedback loop to ensure expression of key genes required for neuronal function including the muscarinic acetylcholine receptor (mAChR) and the inositol 1,4,5-trisphosphate receptor (itpr). C_LIO_LIThe transcriptional program downstream of SOCE is key to functional maturation of the dopaminergic neurons, enabling their neuronal excitability, axonal arborization and synaptic transmission required for adult flight. C_LI

neuroscience↗

bioRxiv2022

Systematic lncRNA mapping to genome-wide co-essential pathways uncovers cancer dependency on uncharacterized lncRNAs

Quantification of gene dependency across hundreds of cell lines using genome-scale CRISPR screens have revealed co-essential pathways/modules and critical functions of uncharacterized genes. In contrast to protein-coding genes, robust CRISPR-based loss-of-function screens are lacking for long non-coding RNAs (lncRNAs), which are key regulators of many cellular process, leaving many essential lncRNAs unidentified and uninvestigated. Integrating copy- number, epigenetic, and transcriptomic data of >800 cancer cell lines with CRISPR-derived co-essential pathways, our method recapitulates known essential lncRNAs and predicts proliferation/growth dependency of 289 poorly characterized lncRNAs. Analyzing lncRNA dependencies across ten cancer types and their expression alteration by diverse growth- inhibitors across cell types, we prioritize 30 high-confidence pan-cancer proliferation/growth- regulating lncRNAs. Further evaluating two previously uncharacterized top proliferation-suppressive lncRNAs (PSLR-1, PSLR-2) showed they are transcriptionally regulated by p53, induced by multiple cancer treatments, and significantly correlate to increased cancer patient survival. These lncRNAs modulate G2 cell cycle-regulating genes within the FOXM1 transcriptional network, inducing a G2 arrest and inhibiting proliferation and colony formation. Collectively, our results serve as a powerful resource for exploring lncRNA-mediated regulation of cellular fitness in cancer, circumventing current limitations in lncRNA research.

bioinformatics↗

bioRxiv2021

Bergamottin a CYP3A inhibitor found in grapefruit juice inhibits prostate cancer cell growth by downregulating androgen receptor signaling causing cell cycle block and apoptosis

Prostate cancer is the second leading cause of cancer related death in American men. Several therapies have been developed to treat advanced prostate cancer, but these therapies often have severe side effects. To improve the outcome with fewer side effects we focused on the furanocoumarin bergamottin, a natural product found in grapefruit juice and a potent CYP3A inhibitor. Our recent studies have shown that CYP3A5 inhibition can block androgen receptor (AR) signaling, critical for prostate cancer growth. We observed that bergamottin reduces prostate cancer (PC) cell growth by decreasing both total and nuclear AR (AR activation) reducing downstream AR signaling. Bergamottins role in reducing AR activation was confirmed by confocal microscopy studies and reduction in PSA levels. Further studies revealed that bergamottin promotes cell cycle block and accumulates G0/G1 cells. The cell cycle block was accompanied with reduction in cyclin D, cyclin B, CDK4, P-cdc2 (Y15) and P-wee1 (S642). We also observed that bergamottin triggers apoptosis in prostate cancer cell lines as evident by TUNEL staining and PARP cleavage. Our data suggest that bergamottin may be used as an adjunctive nutritional supplement to suppress prostate cancer growth and is of relevance to AA patients carrying wild type CYP3A5 often presenting aggressive disease.

cancer biology↗

bioRxiv2020

IP3/Ca2+ signals regulate larval to pupal transition under nutrient stress through the H3K36 methyltransferase dSET2

Persistent loss of dietary protein usually signals a shutdown of key metabolic pathways. In Drosophila larvae, that have crossed "critical weight" and can pupariate to form viable adults, such a metabolic shut-down would needlessly lead to death. IP3/Ca2+ signals in certain interneurons (vGlutVGN6341) allow Drosophila larvae to pupariate on a protein-deficient diet by partially circumventing this shutdown through upregulation of neuropeptide signaling and the expression of ecdysone synthesis genes. Here we show that IP3/Ca2+ signals in vGlutVGN6341 neurons drive expression of dSET2, a Drosophila Histone 3 Lysine 36 methyltransferase. Further, dSET2 expression is required for larvae to pupariate in the absence of dietary protein. IP3/Ca2+ signal-driven dSET2 expression upregulates key Ca2+ signaling genes through a novel positive feedback loop. Transcriptomic studies coupled with analysis of existing ChIP-seq datasets identified genes from larval and pupal stages, that normally exhibit robust H3K36 trimethyl marks on their gene bodies and concomitantly undergo stronger downregulation by knockdown of either an intracellular Ca2+ release channel the IP3R or dSET2. IP3/Ca2+ signals thus regulate gene expression through dSET2 mediated H3K36 marks on select neuronal genes for the larval to pupal transition.

developmental biology↗

bioRxiv2020

RVAgene: Generative modeling of gene expression time series data

Methods to model dynamic changes in gene expression at a genome-wide level are not currently sufficient for large (temporally rich or single-cell) datasets. Variational autoencoders offer means to characterize large datasets and have been used effectively to characterize features of single-cell datasets. Here we extend these methods for use with gene expression time series data. We present RVAgene: a recurrent variational autoencoder to model gene expression dynamics. RVAgene learns to accurately and efficiently reconstruct temporal gene profiles. It also learns a low dimensional representation of the data via a recurrent encoder network that can be used for biological feature discovery, and can generate new gene expression data by sampling from the latent space. We test RVAgene on simulated and real biological datasets, including embryonic stem cell differentiation and kidney injury response dynamics. In all cases, RVAgene accurately reconstructed complex gene expression temporal profiles. Via cross validation, we show that a low-error latent space representation can be learnt using only a fraction of the data. Through clustering and gene ontology term enrichment analysis on the latent space, we demonstrate the potential of RVAgene for unsupervised discovery. In particular, RVAgene identifies new programs of shared gene regulation of Lox family genes in response to kidney injury.

systems biology↗

bioRxiv2020

Reverse regression increases power for detecting trans-eQTLs

Trans-acting expression quantitative trait loci (trans-eQTLs) are genetic variants affecting the expression of distant genes. They account for [≥]70% expression heritability and could therefore facilitate uncovering mechansisms underlying the origination of complex diseases. However, unlike cis-eQTLs, identifying trans-eQTLs is challenging because of small effect sizes, tissue-specificity, and the severe multiple-testing burden. Trans-eQTLs affect multiple target genes, but aggregating evidence over individual SNP-gene associations is hampered by strong gene expression correlations resulting in correlated p-values. Our method Tejaas predicts trans-eQTLs by performing L2-regularized reverse multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel non-linear, unsupervised k-nearest-neighbor method to remove confounders, Tejaas predicted 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms. Tejaas is available under GPL at https://github.com/soedinglab/tejaas.

genetics↗

bioRxiv2020

Role of CYP3A5 in modulating androgen receptor signaling and its relevance to African American men with prostate cancer

BackgroundAndrogen receptor signaling is crucial for prostate cancer growth and is regulated by intratumoral CYP3A5. As African American (AA) men often carry the wild type CYP3A5 and express high level of CYP3A5 protein, we tested the effect of blocking the wild type CYP3A5 in prostate cancer cells from AA men on androgen receptor signaling. CYP3A5 processes several commonly prescribed drugs and many of these are CYP3A5 inducers (e.g. phenytoin and rifampicin) or inhibitors (e.g. ritonavir and amiodarone). In this study, we test the effect of these commonly prescribed CYP3A5 inducers/inhibitors on AR signaling in prostate cancer cells. MethodsCell fractionation and immunofluorescence studies were performed to study AR nuclear localization and activation process using CYP3A5 siRNA and CYP3A5 inducers and inhibitors. A qPCR based array was employed to examine expression of AR downstream regulated genes after blocking CYP3A5 expression using a pool of CYP3A5 siRNA. Cell growth was monitored using MTS based assays. Since AAs tend to carry wild type CYP3A5 and non-Hispanic White Americans (NHWA) carry mutated CYP3A5 two cell lines one of AA origin (MDAPCA2b) carrying wt CYP3A5 and the other of NHWA origin (LNCaP) carrying mutant CYP3A5 were used for above experiments. ResultsSimilar to that observed in LNCaP (mutant CYP3A5) earlier, CYP3A5 siRNA treated MDACPA2b (AA, wild type CYP3A5) cells showed decreased AR nuclear translocation and PSA production. q-PCR based profiler assay identified several AR regulated genes which were downregulated with CYP3A5 siRNA pool treatment performed with cDNA from CYP3A5 siRNA pool and NT treated MDAPCA2b cells. These downregulated genes include SCL45A3, FKBP5, NCAPD3, MYC, MME, ELL2, PIK3R3, HPRT1 and SPDEF with p-value of [≤]0.005. These genes are known to regulate AR nuclear translocation, cell cycle progression and cell growth. SCL45A3, FKBP5, MYC, and ELL2 also showed decreased protein levels after CYP3A5 siRNA treatment. Commonly prescribed drugs which are either CYP3A5 inhibitors (amiodarone, ritonavir) or inducers (phenytoin, rifampicin) were tested for their ability to alter AR signaling in both LNCaP and MDAPCa2b cells. The results show that the CYP3A5 inducers promoted AR nuclear translocation and downstream signaling whereas CYP3A5 inhibitors abrogated them. The increased nuclear AR observed with phenytoin and rifampicin (CYP3A inducers) treatment is abrogated in CYP3A5 siRNA treated MDAPCa2b cells, confirming that the activation of AR activity is specific to changes in CYP3A5 activity. Both the inducers tested demonstrated increased cell growth of prostate cancer cells, whereas the inhibitors showed reduced cell growth. The difference in growth is more pronounced in MDAPCa2b cells which carries a wild type CYP3A5 as compared to LNCaP with the exception of ritonavir which also downregulates total AR levels. ConclusionsConcomitantly prescribed CYP3A5 modulating drugs may alter downstream AR signaling, cell growth and ADT efficacy in men, more so in AAs expressing wild type CYP3A5. Further, characterization and utilization of this observation how CYP3A5 inducers and inhibitors can alter AR signaling may provide guidance to physicians co-prescribing CYP3A5 modulating drugs to treat comorbidities in elderly patients undergoing ADT, particularly AA.

cancer biology↗

bioRxiv2019

MAPPING TRANSCRIPTION FACTOR NETWORKS BY COMPARING TF BINDING LOCATIONS TO TF PERTURBATION RESPONSES

BackgroundA transcription-factor (TF) network map indicates the direct, functional targets of each TF -- the genes it regulates by binding to their cis-regulatory DNA. Data on the genomic binding locations of each TF and the transcriptional responses to perturbations of its activity, such as overexpressing it, could support TF network mapping. Systematic data sets of both types exist for yeast and for human K562 and HEK293 cells.\n\nResultsIn previous data, most TF binding sites appear to be non-functional, so one cannot take the genes in whose promoters a TF binds as its direct, functional (DF) targets. Taking the genes that are both bound by a TF and responsive to a perturbation of it as its DF targets (intersection algorithm) is also not safe, as we show by deriving a new lower bound on the expected false discovery rate of the intersection algorithm. When there are many non-functional binding sites and many indirect targets, non-functional sites are expected to occur in the cis-regulatory DNA of indirect targets by chance. Dual threshold optimization, a new method for setting significance thresholds on binding and response data, improves the intersection algorithm, as does post-processing perturbation-response data with NetProphet 2.0. A comprehensive new data set measuring the transcriptional response shortly after inducing overexpression of a TF also helps, as does transposon calling cards, a new method for identifying TF binding locations.\n\nConclusionsThe combination of dual threshold optimization and NetProphet greatly expands the high-confidence TF network map in both yeast and human. In yeast, measuring the response shortly after inducing TF overexpression and measuring binding locations by using transposon calling cards improve the network synergistically.

genomics↗

bioRxiv2017

Differential Brd4-bound enhancers drive critical sex differences in glioblastoma

Sex can be an important determinant of cancer phenotype, and exploring sex-biased tumor biology holds promise for identifying novel therapeutic targets and new approaches to cancer treatment. In an established isogenic murine model of glioblastoma, we discovered correlated transcriptome-wide sex differences in gene expression, H3K27ac marks, large Brd4-bound enhancer usage, and Brd4 localization to Myc and p53 genomic binding sites. These sex-biased gene expression patterns were also evident in human glioblastoma stem cells (GSCs). These observations led us to hypothesize that Brd4-bound enhancers might underlie sex differences in stem cell function and tumorigenicity in GBM. We found that male and female GBM cells exhibited opposing responses to pharmacological or genetic inhibition of Brd4. Brd4 knockdown or pharmacologic inhibition decreased male GBM cell clonogenicity and in vivo tumorigenesis, while increasing both in female GBM cells. These results were validated in male and female patient-derived GBM cell lines. Furthermore, analysis of the Cancer Therapeutic Response Portal of human GBM samples segregated by sex revealed that male GBM cells are significantly more sensitive to BET inhibitors than are female cells. Thus, for the first time, Brd4 activity is revealed to drive a sex differences in stem cell and tumorigenic phenotype, resulting in diametrically opposite responses to BET inhibition in male and female GBM cells. This has important implications for the clinical evaluation and use of BET inhibitors. SignificanceConsistent sex differences in incidence and outcome have been reported in numerous cancers including brain tumors. GBM, the most common and aggressive primary brain tumor, occurs with higher incidence and shorter survival in males compared to females. Brd4 is essential for regulating transcriptome-wide gene expression and specifying cell identity, including that of GBM. We report that sex-biased Brd4 activity drive sex differences in GBM and render male and female tumor cells differentially sensitive to BET inhibitors. The observed sex differences in BETi treatment strongly indicate that sex differences in disease biology translate into sex differences in therapeutic responses. This has critical implications for clinical use of BET inhibitors further affirming the importance of inclusion of sex as a biological variable.

genomics↗