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Datta, A.

Publications and source records attributed to Datta, A..

At least 55 records · Page 3Linked to original sources
bioRxiv2024

A Cell-Permeable Fluorescent Probe Reveals Temporally Diverse PI(4,5)P2 Dynamics Evoked by Distinct GPCR Agonists in Neurons

Lipids, key constituents of cell-membranes, are the first responders to cell signals. At the crux of spatiotemporal dynamics of lipid-signaling response are phosphoinositides. Indeed, phosphoinositides like phosphatidylinositol-(4,5)-bisphosphate (PI(4,5)P2), present in the inner-leaflet of eukaryotic cell-membranes, form the link between signal reception and downstream signal-transmission. In this backdrop, reversible fluorescent probes that can track live PI(4,5)P2 dynamics on a seconds time-scale will afford key insights into lipid-mediated signaling. However, realizing cell-permeable PI(4,5)P2-selective sensors for imaging dynamics remains a challenge due to the presence of structurally similar lipids and low levels of PI(4,5)P2. We report a computationally-designed, rapid-response, reversible, photo-stable, fluorescent sensor that permeates living cells, neurons, and a multicellular organism within few min of direct incubation and distinctly visualizes PI(4,5)P2 pools. We used the sensor to interrogate the role of PI(4,5)P2 in driving heterogeneity of signaling responses and contrasting behavioral effects that ensue upon binding of distinct ligands to the same G protein-coupled receptor. Specifically, we asked whether probing PI(4,5)P2 dynamics using our novel sensor could uncover the earliest of signaling differences evoked by hallucinogenic versus non-hallucinogenic ligands at the serotonin2A (5-HT2A) receptor. Our results reveal that a hallucinogenic ligand at the 5-HT2A receptor leads to a slower rate of PI(4,5)P2-depletion when compared to a non-hallucinogenic ligand, within the initial seconds of ligand addition, but has a sustained effect. The ability of our designer chemical probe in timing early seconds-minute timescale lipid-dynamics in living cells opens avenues for tracking early time-point molecular events in neuronal response to chemical and physical stimuli.

biochemistry↗
bioRxiv2024

Using machine learning to dissect host kinases required for Leishmania internalization and development

The Leishmania life cycle alternates between promastigotes, found in the sandfly, and amastigotes, found in mammals. When an infected sandfly bites a host, promastigotes are engulfed by phagocytes (i.e., neutrophils, dendritic cells, and macrophages) to establish infection. When these phagocytes die or break down, amastigotes must be re-internalized to survive within the acidic phagolysosome and establish disease. To define host kinase regulators of Leishmania promastigote and amastigote uptake and survival within macrophages, we performed an image-based kinase regression screen using a panel of 38 kinase inhibitors with unique yet overlapping kinase targets. We also targeted inert beads to complement receptor 3 (CR3) or Fc{gamma} receptors (FcR) as controls by coating them with complement/C3bi or IgG respectively. Through this approach, we identified several putative host kinases that regulate receptor-mediated phagocytosis and/or the uptake of L. amazonensis. Findings included kinases previously implicated in Leishmania uptake (such as Src family kinases (SFK), Abl family kinases (ABL1/c-Abl, ABL2/Arg), and spleen tyrosine kinase (SYK)), but we also uncovered many novel kinases. Our methods also predicted host kinases necessary for promastigotes to convert to amastigotes or for amastigotes to survive within macrophages. Overall, our results suggest that the concerted action of multiple interconnected networks of host kinases are needed over the course of Leishmania infection, and that the kinases required for the parasites life cycle may differ substantially depending on which receptors are bound and the life cycle stage that is internalized. In addition, using our screen, we identified kinases that appear to preferentially regulate the uptake of parasites over beads, indicating that the methods required for Leishmania to be internalized by macrophages may differ significantly from generalized phagocytic mechanisms. Our findings are intended to be used as a hypothesis generation resource for the broader scientific community studying the roles of kinases in host-pathogen interactions.

microbiology↗
bioRxiv2024

Pooled screening for CAR function identifies novel IL13Rα2-targeted CARs for treatment of glioblastoma

Chimeric antigen receptor therapies have demonstrated potent efficacy in treating B cell malignancies, but have yet to meaningfully translate to solid tumors. Here, we utilize our pooled screening platform, CARPOOL, to expedite the discovery of CARs with anti-tumor functions necessary for solid tumor efficacy. We performed selections in primary human T cells expressing a library of 1.3x106 3rd generation CARs targeting IL13R2, a cancer testis antigen commonly expressed in glioblastoma. Selections were performed for cytotoxicity, proliferation, memory formation, and persistence upon repeated antigen challenge. Each enriched CAR robustly produced the phenotype for which it was selected, and one enriched CAR triggered potent cytotoxicity and long-term proliferation upon in vitro tumor rechallenge. It also showed significantly improved persistence and comparable antigen-specific tumor control in a microphysiological human in vitro model and a xenograft model of human glioblastoma. Taken together, this work demonstrates the utility of extending CARPOOL to diseases beyond hematological malignancies and represents the largest exploration of signaling combinations in human primary cells to date.

immunology↗
bioRxiv2024

The Candida auris Hog1 MAP kinase is essential for the colonization of murine skin and intradermal persistence

Candida auris, a multidrug-resistant human fungal pathogen, was first identified in 2009 in Japan. Since then, systemic C. auris infections have now been reported in more than 50 countries, with mortality rates of 30-60%. A major contributing factor to its high inter- and intrahospital clonal transmission is that C. auris, unlike most Candida species, displays unique skin tropism and can stay on human skin for a prolonged period. However, the molecular mechanisms responsible for C. auris skin colonization, intradermal persistence, and systemic virulence are poorly understood. Here, we report that C. auris Hog1 mitogen-activated protein kinase (MAPK) is essential for efficient skin colonization, intradermal persistence, as well as systemic virulence. RNA-seq analysis of wildtype parental and hog1{Delta} mutant strains revealed marked down-regulation of genes involved in processes such as cell adhesion, cell-wall rearrangement, and pathogenesis in hog1{Delta} mutant compared to the wildtype parent. Consistent with these data, we found a prominent role for Hog1 in maintaining cell-wall architecture, as the hog1{Delta} mutant demonstrated a significant increase in cell-surface {beta}-glucan exposure and a concomitant reduction in chitin content. Additionally, we observed that Hog1 was required for biofilm formation in vitro and fungal survival when challenged with primary murine macrophages and neutrophils ex vivo. Collectively, these findings have important implications for understanding the C. auris skin adherence mechanisms and penetration of skin epithelial layers preceding bloodstream infections. ImportanceCandida auris is a World Health Organization (WHO) fungal priority pathogen and an urgent public health threat recognized by the Centers for Disease Control and Prevention (CDC). C. auris has a unique ability to colonize human skin. It also persists on abiotic surfaces in healthcare environments for an extended period of time. These attributes facilitate the inter- and intrahospital clonal transmission of C. auris. Therefore, understanding C. auris skin colonization mechanisms are critical for infection control, especially in hospitals and nursing homes. However, despite its profound clinical relevance, the molecular and genetic basis of C. auris skin colonization mechanisms are poorly understood. Herein, we present data on the identification of the Hog1 MAP kinase as a key regulator of C. auris skin colonization. These findings lay foundation for further characterization of unique mechanisms that promote fungal persistence on human skin.

microbiology↗
bioRxiv2023

Effects of sampling methodology on phenology indices: insights from sites across India and modelling

Plant phenology is the study of timing and extent of leaf, flower, and fruit production. Phenology data are used to study drivers of cyclicity and seasonality of plant life-history stages, interactions with organisms such as pollinators, and effects of global change factors. Indices such as timing of phenological events, proportion of individuals in a particular phenophase, seasonality, and synchrony have often been used to summarise plant phenology data. However, these indices have specific utilities and limitations and may be sensitive to sampling methodology, making cross-site comparisons challenging, particularly when data collection methods vary in terms of sample size, observation frequency, and the resolution at which phenophase intensity scores/values are recorded. We use fruiting phenology data from tropical trees across five sites in India to study the effects of sampling methodology on two indices: an index of population-level synchrony (overlap), and an index of seasonality. We supplement these results with simulations of fast- and slow-changing phenologies to test for the effects of sampling methodology on these indices. We found that the overlap index is sensitive to the phenophase intensity measurement resolution--with coarser intensity measures leading to overestimation of the overlap index. The seasonality index, on the other hand, was not affected by intensity resolution. Simulations indicated that finer intensity resolution is more important than frequency of observation to accurately estimate population synchrony and seasonality for fast- and slow-changing phenophases. Based on our findings, we provide recommendations for study design of future tropical tree phenology research, particularly for long-term or cross-site studies.

ecology↗
bioRxiv2023

memerna: Sparse RNA Folding Including Coaxial Stacking

AO_SCPLOWBSTRACTC_SCPLOWDetermining RNA secondary structure is a core problem in computational biology. Fast algorithms for predicting secondary structure are fundamental to this task. We describe a modified formulation of the Zuker-Stiegler algorithm with coaxial stacking, a stabilizing interaction in which the ends of multi-loops are stacked. In particular, optimal coaxial stacking is computed as part of the dynamic programming state, rather than inline. We introduce a new notion of sparsity, which we call replaceability. The modified formulation along with replaceability allows sparsification to be applied to coaxial stacking as well, which increases the speed of the algorithm. We implemented this algorithm in software we call memerna, which we show to have the fastest exact RNA folding implementation out of several popular RNA folding packages supporting coaxial stacking. We also introduce a new notation for secondary structure which includes coaxial stacking, terminal mismatches, and dangles (CTDs) information.

bioinformatics↗
bioRxiv2023

CDK12/CDK13 inhibition disrupts a transcriptional program critical for glioblastoma survival

Glioblastoma is the most prevalent and aggressive malignant tumor of the central nervous system. With a median overall survival of only one year, glioblastoma patients have a particularly poor prognosis, highlighting a clear need for novel therapeutic strategies to target this disease. Transcriptional cyclin-dependent kinases (tCDK), which phosphorylate key residues of RNA polymerase II (RNAPII) c-terminal domain (CTD), play a major role in sustaining aberrant transcriptional programs that are key to development and maintenance of cancer cells. Here, we show that either pharmacological inhibition or genetic ablation of the tCDKs, CDK12 and CDK13, markedly reduces both the proliferation and migratory capacity of glioma cells and patient-derived organoids. Using a xenograft mouse model, we demonstrate that CDK12/13 inhibition not only reduces glioma growth in vivo. Mechanistically, inhibition of CDK12/CDK13 leads to a genome-wide abrogation of RNAPII CTD phosphorylation, which in turn disrupts transcription and cell cycle progression in glioma cells. In summary, the results provide proof-of-concept for the potential of CDK12 and CDK13 as therapeutic targets for glioblastoma. Significance statementGlioblastoma is a common, aggressive, and invasive type of brain tumor that is usually fatal. The standard treatment for glioblastoma patients is surgical resection, radiotherapy, and chemotherapy with DNA-alkylating agents, and unfortunately current treatments only extend overall survival by a few months. It is therefore critical to identify and target additional biological processes in this disease. Here, we reveal that targeting a specific transcriptional addiction for glioma cells by inhibition of CDK12/CDK13 disrupts glioma-specific transcription and cell cycle progression and has potential to provide a new therapeutic strategy for glioblastoma.

cancer biology↗
bioRxiv2023

Drug Target Identification in Triple Negative Breast Cancer Stem Cell Pathways: a computational study of gene regulatory pathways using Boolean networks

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer associated with an early age of onset, greater propensity towards metastasis, and poorer clinical outcomes. It accounts for 10% to 20% of newly diagnosed breast cancer cases and disproportionately affects individuals from the African American race. While TNBC is sensitive to chemotherapy, it is also prone to relapse. This is because chemotherapy successfully targets the primary TNBC tumor cell but often fails to target the subpopulation of TNBC stem cells. TNBC stem cells display cancerous traits such as cell cycle progression, survival, proliferation, apoptosis inhibition, and epithelial-mesenchymal transition. To study the cancer initiating behavior of the TNBC stem cells, we studied their underlying signaling pathways using Boolean networks(BN). BNs are effective in capturing the causal interactions taking place in signaling pathways. We built the BN from the pathway literature and used it to evaluate the efficacies of eleven targeted inhibitory drugs in suppressing cancer-promoting genes. We simulated the BN when the pathways had single or multiple mutations, with a maximum of three mutations at a time. Our findings indicated that STAT3, GLI, and NF-{kappa}B are the most optimal targets for inhibition. These genes are known regulators of the cancer-promoting genes in the pathway,hence our model agrees with the existing biological literature. Therefore inhibiting these three genes has the potential to prevent TNBC relapse. Additionally, our studies found that drug efficacies decreased as mutations increased in the pathway. Furthermore, we noticed that combinations of drugs performed better than single drugs.

systems biology↗
bioRxiv2023

A Scalable Framework for Closed-Loop Neuromodulation with Deep Learning

Closed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and error-based triggering) and stimulation-type application. We present and verify a novel deep learning framework for designing and deploying flexible, data-driven, automated closed-loop neuromodulation that is scalable using diverse datasets, agnostic to stimulation technology (supporting multi-modal stimulation: tACS, tDCS, tFUS, TMS), and without the need for personalized ground-truth performance data. Our approach is based on identified periods of responsiveness - detected states that result in a change in performance when stimulation is applied compared to no stimulation. To demonstrate our framework, we acquire, analyze, and apply a data-driven approach to our open sourced GX dataset, which includes concurrent physiological (ECG, EOG) and neuronal (EEG) measures, paired with continuous vigilance/attention-fatigue tracking, and High-Definition transcranial electrical stimulation (HD-tES). Our frameworks decision process for intervention application identified 88.26% of trials as correct applications, showed potential improvement with varying stimulation types, or missed opportunities to stimulate, whereas 11.25% of trials were predicted to stimulate at inopportune times. With emerging datasets and stimulation technologies, our unifying and integrative framework; leveraging deep learning (Convolutional Neural Networks - CNNs); demonstrates the adaptability and feasibility of automated multimodal neuromodulation for both clinical and nonclinical applications.

neuroscience↗
bioRxiv2022

ERK1/2 Activation in Macrophages Promotes Leishmania Internalization and Pathogenesis

The obligate intracellular protozoan parasite Leishmania binds several host cell receptors to trigger its uptake by phagocytic cells, ultimately resulting in visceral or cutaneous leishmaniasis. After Leishmania engages receptors on macrophages and other phagocytes, a series of signaling pathways in the host cell are activated during its internalization, which are critical for establishment and persistence of Leishmania infection. Thus, preventing Leishmania internalization by phagocytes could be a novel therapeutic strategy for leishmaniasis. However, the host cellular machinery that mediates promastigote and amastigote uptake is not well understood. Here, using small molecule inhibitors of Mitogen-activated protein kinases/Extracellular signal regulated kinases (MAPK/ERK), we demonstrate that ERK1/2 mediates Leishmania amazonensis uptake and (to a lesser extent) phagocytosis of beads by macrophages. We find that inhibition of MEK1/2 or ERK1/2 leads to inefficient amastigote uptake by macrophages. Moreover, using inhibitors and primary macrophages lacking spleen tyrosine kinase (SYK) or Abl family kinases, we show that SYK and Abl family kinases mediate Raf, MEK, and ERK1/2 activity and are necessary for efficient uptake. Finally, we demonstrate that trametinib, a MEK1/2 inhibitor used clinically to treat certain cancers, significantly reduces disease severity and parasite burden in Leishmania-infected mice, even if it is started significantly after lesions develop. Our results show that maximal Leishmania infection requires MAPK/ERK and highlight the potential for MAPK/ERK-mediated signaling pathways to be novel therapeutic targets for leishmaniasis. Lay summaryLeishmania is a single-celled parasite that causes skin ulcers or a disseminated disease in humans. Our goal is to identify new drugs to treat Leishmania infection. Leishmania must live inside human immune cells to cause disease. If Leishmania is not able to enter human immune cells, it dies. Our studies demonstrate how Leishmania infection permits a set of proteins called MAP kinases to pass signals from one protein to the next within mammalian immune cells. The resulting signals allow Leishmania to enter into these immune cells and survive within its host. Importantly, trametinib, a drug that prevents these signals from MAP kinases, decreases the development of skin ulcers when it is given to mice that are infected with Leishmania. Our findings suggest that leishmaniasis could be treated with drugs that act on kinases found in humans rather than the parasites themselves. One sentence summaryAn Abl2-SYK-Raf-MEK-ERK pathway facilitates Leishmania uptake by phagocytic cells and promotes disease severity in Leishmania-infected mice.

microbiology↗
bioRxiv2022

Multisite Thalamic Recordings to Characterize Seizure Propagation in the Human Brain

Neuromodulation of the anterior nuclei of the thalamus (ANT) has shown to be efficacious in patients with refractory focal epilepsy, but it is not uniformly effective. One important uncertainty is to what extent thalamic subregions other than the ANT are recruited earlier and more prominently in the propagation of seizures in patients with presumed temporal lobe epilepsy (TLE). To address this unknown, we studied 11 patients with clinical manifestations of TLE planned to undergo invasive stereo-encephalography (sEEG) monitoring. We extended cortical electrodes to reach thalamic nuclear subdivisions in the anterior (ANT), middle (mediodorsal) and or posterior (pulvinar) sites. This multisite thalamic sampling was without any adverse events. Intracranial EEG (iEEG) recordings confirmed seizure-onset in medial temporal lobe, insula, orbitofrontal and temporal neocortical sites - highlighting the importance of iEEG for more accurate localization of seizure foci. Visual review of EEGs documented early and prominent involvement of specific thalamic sites. Seizures originating from the same brain origin produced a stereotyped thalamic EEG signature. Visual review of EEGs, validated with singlepulse corticothalamic evoked potentials, documented early and prominent involvement of thalamic sites that would have not been predicted given the anatomy of seizure onset zones. Pulvinar was involved earlier and more prominently than other sampled nuclear subgroups in 60% of patients, even though all patients had a presumed diagnosis of TLE prior to invasive monitoring. Our findings document the feasibility and safety of multisite sampling from the human thalamus and suggest that the anatomy of thalamic involvement may not be entirely predictable on the basis of clinical information or lobar localization of seizures. Future clinical trials can establish whether offering more personalized targets for thalamic neuromodulation will lead to greater meaningful improvements in outcome.

neuroscience↗
bioRxiv2022

The Src and Abl family kinases activate the Spleen Tyrosine Kinase to maximize phagocytosis and Leishmania infection

Leishmania spp. are obligate intracellular parasites that must be internalized by phagocytic cells to evade immune responses and cause disease. The uptake of both Leishmania promastigotes (insect-stage parasites) and amastigotes (proliferative stage parasites in humans and mice) by phagocytes is thought to be mainly host cell-driven, not parasite-driven. Our previous work indicates that host Src and Abl family kinases facilitate Leishmania entry into macrophages and pathogenesis in murine cutaneous leishmaniasis. Here we demonstrate that host spleen tyrosine kinase (SYK) is required for efficient uptake of Leishmania promastigotes and amastigotes. A Src family kinase-Abl family kinase-SYK signaling cascade induces Leishmania amastigote internalization. Finally, lesion size and parasite burden during Leishmania infection is significantly decreased in mice lacking SYK in monocytes or by treatment with the SYK inhibitor entospletinib. In summary, SYK is required for maximal Leishmania uptake by macrophages and disease in mice. Our results suggest potential for treating leishmaniasis using host cell-directed agents. SUMMARY STATEMENTActivation of Spleen Tyrosine Kinase by Src and Abl family kinases is required for maximal Leishmania uptake by macrophages and disease in a mouse model of cutaneous leishmaniasis.

microbiology↗
bioRxiv2022

Impact of galvanic vestibular stimulation electrode current density on brain current flow patterns: Does electrode size matter?

BackgroundGalvanic vestibular stimulation (GVS) uses at least one electrode placed on the mastoid process with one or multiple placed over other head areas to stimulate the vestibular system. The exact electrode size used is not given much importance in the literature and has not been reported in several studies. In a previous study, we compared the clinical effects of using different electrode sizes (3 cm2 and 35 cm2) with placebo but with the same injected current, on postural control. We observed significant improvement using the smaller size electrode but not with the bigger size electrode. The goal of this study was to simulate the current flow patterns with the intent to shed light and potentially explain the experimental outcome. MethodsWe used an ultra-high-resolution structural dataset and developed a model to simulate the application of different electrode sizes. We considered current flow in the brain and in the vestibular labyrinth. ResultsOur simulation results verified the focality increase using smaller electrodes that we postulated as the main reason for our clinical effect. The use of smaller size electrodes in combination with the montage employed also result in higher induced electric field (E-field) in the brain. ConclusionsElectrode size and related current density is a critical parameter to characterize any GVS administration as the choice impacts the induced E-field. It is evident that the higher induced E-field likely contributed to the clinical outcome reported in our prior study.

bioengineering↗
bioRxiv2022

nnSVG: scalable identification of spatially variable genes using nearest-neighbor Gaussian processes

Feature selection to identify spatially variable genes or other biologically informative genes is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose nnSVG, a scalable approach to identify spatially variable genes based on nearest-neighbor Gaussian processes. Our method (i) identifies genes that vary in expression continuously across the entire tissue or within a priori defined spatial domains, (ii) uses gene-specific estimates of length scale parameters within the Gaussian process models, and (iii) scales linearly with the number of spatial locations. We demonstrate the performance of our method using experimental data from several technological platforms and simulations. A software implementation is available at https://bioconductor.org/packages/nnSVG.

genomics↗
bioRxiv2022

Deep learning models for RNA secondary structure prediction (probably) do not generalise across families

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSThe secondary structure of RNA is of importance to its function. Over the last few years, several papers attempted to use machine learning to improve de novo RNA secondary structure prediction. Many of these papers report impressive results for intra-family predictions, but seldom address the much more difficult (and practical) inter-family problem. ResultsWe demonstrate it is nearly trivial with convolutional neural networks to generate pseudo-free energy changes, modeled after structure mapping data, that improve the accuracy of structure prediction for intra-family cases. We propose a more rigorous method for inter-family cross-validation that can be used to assess the performance of learning-based models. Using this method, we further demonstrate that intra-family performance is insufficient proof of generalisation despite the widespread assumption in the literature, and provide strong evidence that many existing learning-based models have not generalised inter-family. AvailabilitySource code and data is available at https://github.com/marcellszi/dl-rna.

bioinformatics↗
bioRxiv2021

How to Assemble a Scale-Invariant Gradient

Intracellular protein gradients serve a variety of functions, such as the establishment of cell polarity and to provide positional information for gene expression in developing embryos. Given that cell size in a population can vary considerably, for the protein gradients to work properly they often have to be scaled to the size of the cell. Here we examine a model of protein gradient formation within a cell that relies on cytoplasmic diffusion and cortical transport of proteins toward a cell pole. We show that the shape of the protein gradient is determined solely by the cell geometry. Furthermore, we show that the length scale over which the protein concentration in the gradient varies is determined by the linear dimensions of the cell, independent of the diffusion constant or the transport speed. This gradient provides scale-invariant positional information within a cell, which can be used for assembly of intracellular structures whose size is scaled to the linear dimensions of the cell, as was recently reported for the cytokinetic ring and actin cables in budding yeast cells.

biophysics↗
bioRxiv2021

Rapid Estimation of SNP Heritability using Predictive Process approximation in Large scale Cohort Studies

With the advent of high throughput genetic data, there have been attempts to estimate heritability from genome-wide SNP data on a cohort of distantly related individuals using linear mixed model (LMM). Fitting such an LMM in a large scale cohort study, however, is tremendously challenging due to its high dimensional linear algebraic operations. In this paper, we propose a new method named PredLMM approximating the aforementioned LMM motivated by the concepts of genetic coalescence and gaussian predictive process. PredLMM has substantially better computational complexity than most of the existing LMM based methods and thus, provides a fast alternative for estimating heritability in large scale cohort studies. Theoretically, we show that under a model of genetic coalescence, the limiting form of our approximation is the celebrated predictive process approximation of large gaussian process likelihoods that has well-established accuracy standards. We illustrate our approach with extensive simulation studies and use it to estimate the heritability of multiple quantitative traits from the UK Biobank cohort.

bioinformatics↗