Biology subjects

Bandyopadhyay, A.

Publications and source records attributed to Bandyopadhyay, A..

33 records · Page 2Linked to original sources

bioRxiv2022

Amount of antigen, T follicular helper cells and quality of seeder cells shape the diversity of germinal center B cells

A variety of B cell clones seed the germinal centers, where a selection stringency expands the fitter clones to generate higher affinity antibodies. However, recent experiments suggest that germinal centers often retain a diverse set of B cell clones with a range of affinities and concurrently carry out affinity maturation. Amid a tendency to flourish germinal centers with fitter clones, how several B cell clones with differing affinities can be concurrently selected remains poorly understood. Such a permissive selection may allow non-immunodominant clones, which are often rare and of low-affinity, to somatically hypermutate and result in a broad and diverse B cell response. How the constituent elements of germinal centers, their quantity and kinetics may modulate diversity of B cells, has not been addressed well. By implementing a state-of-the-art agent-based model of germinal center, here, we study how these factors impact temporal evolution of B cell clonal diversity and its underlying balance with affinity maturation. While we find that the extent of selection stringency dictates clonal dominance, limited antigen availability on follicular dendritic cells is shown to expedite the loss of diversity of B cells as germinal centers mature. Intriguingly, the emergence of a diverse set of germinal center B cells depends on high affinity founder cells. Our analysis also reveals a substantial number of T follicular helper cells to be essential in balancing affinity maturation with clonal diversity, as a low number of T follicular helper cells impedes affinity maturation and also contracts the scope for a diverse B cell response. Our results have implications for eliciting antibody responses to non-immunodominant specificities of the pathogens by controlling the regulators of the germinal center reaction, thereby pivoting a way for vaccine development to generate broadly protective antibodies.

immunology↗

bioRxiv2022

Arsenic induced alteration of neuroregulatory gene expression in Macrobrachium lamarrei: a neurotoxicological approach to grooming behaviour

Arsenic is a highly active neuromodulator which can induce neurological disorders in invertebrates. The present study is a neurotoxicological approach to assess the toxicity of arsenic trioxide, where grooming behaviour is considered as a behavioural biomarker of arsenic induced stress in the prawns. Non-lethal exposure to arsenic trioxide, manipulates the expression pattern of neuroregulatory marker genes in a freshwater prawn, Macrobrachium lamarrei and induces symptoms of autism spectrum disorders (ASDs) in a short time.

pharmacology and toxicology↗

bioRxiv2021

Antenna modification leads to enhanced nitrogenase activity in a high light tolerant cyanobacterium

Biological nitrogen fixation is an energy intensive process that contributes significantly towards supporting life on this planet. Among nitrogen-fixing organisms, cyanobacteria remain unrivaled in their ability to fuel the energetically expensive nitrogenase reaction with photosynthetically harnessed solar energy. In heterocystous cyanobacteria light-driven, photosystem I (PSI)-mediated ATP synthesis plays a key role in propelling the nitrogenase reaction. Efficient light transfer to the photosystems rely on phycobilisomes (PBS), the major antenna protein complexes. PBS undergo degradation as a natural response to nitrogen starvation. Upon nitrogen availability, these proteins are resynthesized back to normal levels in vegetative cells, but their occurrence and function in heterocysts remains inconclusive. Anabaena 33047 is a heterocystous cyanobacterium that thrives under high light, harbors higher amounts of PBS in its heterocysts and fixes nitrogen at higher rates compared to other heterocystous cyanobacteria. To assess the relationship between PBS in heterocysts and nitrogenase function, we engineered a strain that retains high amounts of the antenna proteins in its heterocysts. Intriguingly, under high light intensities the engineered strain exhibited unusually high rates of nitrogenase activity compared to the wild type. Spectroscopic analysis revealed altered PSI kinetics in the mutant, with increased cyclic electron flow around PSI, a route that contributes to ATP generation and nitrogenase activity in heterocysts. Retaining higher levels of PBS in heterocysts appears to be an effective strategy to enhance nitrogenase function in cyanobacteria that are equipped with the machinery to operate under high light intensities. ImportanceThe function of phycobilisomes, the large antenna protein complexes in heterocysts has long been debated. This study provides direct evidence of the involvement of these proteins in supporting nitrogenase activity in Anabaena 33047, a heterocystous cyanobacterium that has affinity for very high light intensities. This strain was previously known to be recalcitrant to genetic manipulation and hence despite its many appealing traits, remained largely unexplored. We developed a genetic modification system for this strain and generated a {Delta}nblA mutant that exhibited resistance to phycobilisome degradation upon nitrogen starvation. Physiological characterization of the strain indicated that PBS degradation is not essential for acclimation to nitrogen deficiency and retention of PBS is advantageous for nitrogenase function.

microbiology↗

bioRxiv2021

smBEVO: A computer vision approach to rapid baseline correction of single-molecule time series

Single-molecule time series inform on the dynamics of molecular mechanisms that are occluded in ensemble-averaged measures. Amplitude-based methods and hidden Markov models (HMMs) frequently used for interpreting these time series require removal of low frequency drift that can be difficult to completely avoid in real world experiments. Current approaches for drift correction primarily involve either tedious manual assignment of the baseline or unsupervised frameworks such as infinite HMMs coupled with baseline nodes that are computationally expensive and unreliable. Here, we develop an image-based method for baseline correction using techniques from computer vision such as lane detection and active contours. The approach is remarkably accurate and efficient, allowing for rapid analysis of single-molecule time series contaminated with nearly any type of slow baseline drift.

bioinformatics↗

bioRxiv2021

Mean field approximation of network of biophysical neurons driven by conductance-based ion exchange dynamics

Whole-brain simulations are a valuable tool for gaining insight into the multiscale processes that regulate brain activity. Due to the complexity of the brain, it is impractical to include all microscopic details in a simulation. Hence, researchers often simulate the brain as a network of coupled neural masses, each described by a mean-field model. These models capture the essential features of neuronal populations while approximating most biophysical details. However, it may be important to include certain parameters that significantly impact brain function. The concentration of ions in the extracellular space is one key factor to consider, as its fluctuations can be associated with healthy and pathological brain states. In this paper, we develop a new mean-field model of a population of Hodgkin-Huxley-type neurons, retaining a microscopic perspective on the ion-exchange mechanisms driving neuronal activity. This allows us to maintain biophysical interpretability while bridging the gap between micro- and macro-scale mechanisms. Our model is able to reproduce a wide range of activity patterns, also observed in large neural network simulations. Specifically, slow-changing ion concentrations modulate the fast neuroelectric activity, a feature of our model that we validated through in vitro experiments. By studying how changes in extracellular ionic conditions can affect whole-brain dynamics, this model serves as a foundation to measure biomarkers of pathological activity and provide potential therapeutic targets in cases of brain dysfunctions like epilepsy.

neuroscience↗

bioRxiv2021

Defining function of wild-type and patient specific TP53 mutations in a zebrafish model of embryonal rhabdomyosarcoma

In embryonal rhabdomyosarcoma (ERMS) and generally in sarcomas, the role of wild-type and loss or gain of function TP53 mutations remains largely undefined. Eliminating mutant or restoring wild-type p53 is challenging; nevertheless, understanding TP53 effects on tumorigenesis remains central to realizing better treatment outcomes. In ERMS, >70% of patients retain wild-type TP53, yet TP53 mutations when present in tumors are associated with poor prognosis. Employing a kRASG12D-driven ERMS tumor model and newly generated tp53 null (tp53-/-) zebrafish, we define both wild-type and patient-specific TP53 mutant effects on tumorigenesis. We demonstrate that tp53 is a major suppressor of tumor initiation, where tp53 loss expands tumors initiation from <35% to >97% of animals. Next, characterizing three patient-specific mutants finds that TP53C176F partially retains wild-type p53 apoptotic activity that can be exploited, while the TP53P153{Delta} and TP53Y220C mutants define two structural mutations that predispose to head musculature ERMS.

cancer biology↗

bioRxiv2021

BMP signaling is necessary and sufficient for osteoarthritis and a target for disease modifying therapy

ObjectiveTo investigate the role of BMP signaling in osteoarthritis' pathogenesis and propose a disease-modifying therapy for OA. MethodsC57BL6/J mouse line was used to perform ACLT surgery at P120 to study the expression pattern of the BMP signaling readout pSMAD1/5/9. To investigate whether activation of BMP signaling is sufficient and necessary to induce osteoarthritis, we have used conditional GOF and LOF mouse lines in which BMP signaling can be activated or depleted, respectively, upon intra-peritoneal injection of tamoxifen. Finally, we locally inhibited BMP signaling through intra-articular injection of LDN-193189 pre- and post-onset surgically induced OA. Most of the analysis has been done through immunohistochemistry, histopathological staining, and micro-CT to evaluate the status of the pathogenesis of the disease. ResultsWe observed concomitant activation of BMP signaling, as judged by pSMAD1/5/9 immunoreactivity in the articular cartilage, upon induction of osteoarthritis with simultaneous depletion of SMURF1, an intra-cellular BMP signaling inhibitor in articular cartilage. Even without surgical induction of osteoarthritis, only BMP gain-of-function mutation induces OA in mouse articular cartilage. Also, genetic, or pharmacological inhibition of BMP signaling offered significant protection against OA pathogenesis. Interestingly, post-onset of the disease, inhibition of BMP signaling by intra-articular injection of LDN-193189 retarded OA progression with a significant reduction in inflammatory markers. ConclusionOur study demonstrated that BMP signaling plays an essential role in the pathogenesis of OA and that local BMP inhibition can be an effective therapeutic strategy to mitigate osteoarthritis.

developmental biology↗

bioRxiv2021

Unsupervised selection of optimal single-molecule time series idealization criterion

Single-molecule (SM) approaches have provided valuable mechanistic information on many biophysical systems. As technological advances lead to ever-larger datasets, tools for rapid analysis and identification of molecules exhibiting the behavior of interest are increasingly important. In many cases the underlying mechanism is unknown, making unsupervised techniques desirable. The Divisive Segmentation and Clustering (DISC) algorithm is one such unsupervised method that idealizes noisy SM time series much faster than computationally intensive approaches without sacrificing accuracy. However, DISC relies on a user selected objective criterion (OC) to guide its estimation of the ideal time series. Here, we explore how different OCs affect DISCs performance for data typical of SM fluorescence imaging experiments. We find that OCs differing in their penalty for model complexity each optimize DISCs performance for time series with different properties such as signal-to-noise and number of sample points. Using a machine learning approach, we generate a decision boundary that allows unsupervised selection of OC based on the input time series to maximize performance for different types of data. This is particularly relevant for SM fluorescence datasets which often have signal-to-noise near the derived decision boundary and include time series of nonuniform length due to stochastic bleaching. Our approach allows unsupervised per-molecule optimization of DISC, which will substantially assist rapid analysis of high-throughput single-molecule datasets with noisy samples and nonuniform time windows.

bioinformatics↗

bioRxiv2020

A novel mode of photoprotection mediated by a cysteine residue in the chlorophyll protein IsiA

Oxygenic photosynthetic organisms have evolved multitude mechanisms for protection against high light stress. IsiA, a chlorophyll a-binding cyanobacterial protein serves as an accessory antenna complex for photosystem I. Intriguingly, IsiA can also function as an independent pigment protein complex in the thylakoid membrane and facilitate dissipation of excess energy, providing photoprotection. The molecular basis of IsiA-mediated excitation quenching mechanism remains poorly understood. In this study, we demonstrate that IsiA uses a novel cysteine-mediated process to quench excitation energy. The single cysteine in IsiA in the cyanobacterium Synechocystis 6803 was converted to a valine. Ultrafast fluorescence spectroscopic analysis showed that this single change abolishes the excitation energy quenching ability of IsiA, thus providing direct evidence of the crucial role of this cysteine residue in the energy dissipation from excited chlorophylls. Under stress condition, the mutant cells exhibited enhanced light sensitivity, indicating that the cysteine-mediated quenching process is critically important for photoprotection.

biochemistry↗

bioRxiv2020

Structural studies on M. tuberculosis decaprenyl phosphoryl-β-D-ribose epimerase-2 enzyme involved in cell wall biogenesis

The Mycobacterium DprE2 is a NADH-dependent enzyme and converts the decaprenylphosphoryl-{beta}-D-ribose (DPX) to decaprenylphosphoryl-{beta}-D-arabinofuranose (DPA). The FAD-containing oxidoreductase MtbDprE1 and NADH-dependent reductase MtbDprE2 enzymes catalyses together the epimerization reaction, which coverts DPR to DPA. Here, MtbDprE2 enzyme was purified and structurally characterized using circular dichroism, molecular modelling and dynamics simulation techniques. The MtbDprE2 was purified, which eluted as oligomer from size exclusion column. The circular dichroism analysis yielded ~ 47.6% -helix, ~ 19.8% {beta}-sheet and ~ 32.6% random coil structures in MtbDprE2 enzyme and showed highly thermostability. The molecular modelling of MtbDprE2 and its complex with NADH showed that it contains two domains (i) the large domain consists of central twisted seven {beta}-sheets decorated by eight -helices and (ii) a small domain contains two short -helices connect by loop. Overall, the MtbDprE2 adopts a typical short-chain dehydrogenase rossmann fold and NADH binds to Asp69, Ser147, Tyr160, Lys164 of catalytic triad and Gly16, Ser19, Glu20, Ile21 of Gly-rich motif of MtbDprE2. 1 ns dynamics simulation was performed on apo and NADH bound MtbDprE2, which indicated the small conformational change in ligand binding site, which resulted more closed pocket than open pocket observed in apo enzyme. Small conformational changes were observed in active site residues and orientation between large and small domains of MtbDprE2 upon NADH binding. Current knowledge of MtbDprE2 structure and its NADH binding mechanism will contribute significantly in development of specific inhibitors against M. tuberculosis.

bioinformatics↗

bioRxiv2020

Membrane composition and lipid to protein ratio modulate amyloid kinetics of yeast prion protein

Understanding of prion aggregation in membrane environment may help to ameliorate neurodegenerative complications caused by the amyloid forms of prions. Here, we investigated the membrane binding induced aggregation of yeast prion protein Sup35. Using the combination of fluorescence correlation spectroscopy (FCS) at single molecule resolution and other biophysical studies, we establish that lipid composition and lipid/protein ratio are key modulators of the aggregation kinetics of Sup35. In the presence of zwitterionic membrane, Sup35 exhibited a novel biphasic aggregation kinetics at lipid/protein ratio ranging between 20:1 and 70:1 (termed here as the Optimum Lipid Concentration, OLC). In ratios below (Low Lipid Concentration, LLC) and above (ELC, Excess Lipid Concentration) that range, the aggregation was found to be monophasic. In contrast, in the presence of negatively charged membrane, we did not observe any bi-phasic aggregation kinetics in the entire range of protein to lipid ratios. The toxicity of the aggregates formed within OLC range was found to be greater. Our results provide a mechanistic description of the role that membrane-concentration/composition-modulated-aggregation may play in neurodegenerative diseases.

biophysics↗

bioRxiv2020

Rapid and sensitive direct detection and identification of poliovirus from stool and environmental surveillance samples using nanopore sequencing

Global poliovirus surveillance involves virus isolation from stool and environmental samples, intratypic differential (ITD) by PCR and sequencing of the VP1 region to distinguish vaccine (Sabin), vaccine-derived and wild-type polioviruses and ensure an appropriate response. This cell-culture algorithm takes 2-3 weeks on average between sample receipt and sequencing. Direct detection of viral RNA using PCR allows faster detection but has traditionally faced challenges related to poor sensitivity and difficulties in sequencing common samples containing poliovirus and enterovirus mixtures. We present a nested PCR and nanopore sequencing protocol that allows rapid (<3 days) and sensitive direct detection and sequencing of polioviruses in stool and environmental samples. We developed barcoded primers and a real-time analysis platform that generate accurate VP1 consensus sequences from multiplexed samples. The sensitivity and specificity compared with cell-culture were 90.9% (95% Confidence Interval: 75.7-98.1%) and 99.2% (95.5-100.0%) for wild-type 1 poliovirus, 92.5% (79.6-98.4%) and 98.7% (95.4-99.8%) for vaccine and vaccine-derived serotype 2 poliovirus, and 88.3% (81.2-93.5%) and 93.2% (88.6-96.3%) for Sabin 1 and 3 poliovirus alone or in mixtures when tested on 155 stool samples in Pakistan. Variant analysis of sequencing reads also allowed identification of polioviruses and enteroviruses in artificial mixtures and was able to distinguish complex mixtures of polioviruses in environmental samples. The median identity of consensus nanopore sequences with Sanger or Illumina sequences from the same samples was >99.9%. This novel method shows promise as a faster and safer alternative to cell-culture for the detection and real-time sequencing of polioviruses in stool and environmental samples.

microbiology↗

bioRxiv2020

Criticality in the conformational phase transition among self-similar groups in intrinsically disordered proteins: probed by salt-bridge dynamics

Intrinsically disordered proteins (IDP) serve as one of the key components in the global proteome. In contrast to the dominant class of cytosolic globular proteins, they harbor an enormous amount of physical flexibility and structural plasticity enforcing them to be retained in conformational ensembles rather than well defined stable folds. Previous studies in an aligned direction have revealed the importance of transient dynamical phenomena like that of saltbridge formation in IDPs to support their physical flexibility and have further highlighted their functional relevance. For this characteristic flexibility, IDPs remain amenable and accessible to different ordered binding partners, supporting their potential multi-functionality. The current study further addresses this complex structure-functional interplay in IDPs using phase transition dynamics to conceptualize the underlying (avalanche type) mechanism of their being distributed across and hopping around degenerate structural states (conformational ensembles). For this purpose, extensive molecular dynamics simulations have been done and the data analyzed from a statistical physics perspective. Investigation of the plausible scope selforganized criticality (SOC) to fit into the complex dynamics of IDPs was found to be assertive, relating the conformational degeneracy of these proteins to their multi-functionality. In accordance with the transient nature of salt-bridge dynamics, the study further uses it as a probe to explain the structural basis of the proposed criticality in the conformational phase transition among self-similar groups in IDPs. The analysis reveal scale-invariant self-similar fractal geometries in structural conformations of different IDPs. Also, as discussed in the conclusion, the study has the potential to benefit structural tinkering of bio-medically relevant IDPs in the design of biotherapeutics against them.

bioinformatics↗

bioRxiv2018

Lineage space and the propensity of bacterial cells to undergo growth transitions

The molecular makeup of the offspring of a dividing cell gradually becomes phenotypically decorrelated from the parent cell by noise and regulatory mechanisms that amplify phenotypic heterogeneity. Such regulatory mechanisms form networks that contain thresholds between phenotypes. Populations of cells can be poised near the threshold so that a subset of the population probabilistically undergoes the phenotypic transition. We sought to characterize the diversity of bacterial populations around a growth-modulating threshold via analysis of the effect of non-genetic inheritance, similar to conditions that create antibiotictolerant persister cells and other examples of bet hedging. Using simulations and experimental lineage data in Escherichia coli, we present evidence that regulation of growth amplifies the dependence of growth arrest on cellular lineage, causing clusters of related cells undergo growth arrest in certain conditions. Our simulations predict that lineage correlations and the sensitivity of growth to changes in toxin levels coincide in a critical regime. Below the critical regime, the sizes of related growth arrested clusters are distributed exponentially, while in the critical regime clusters sizes are more likely to become large. Furthermore, phenotypic diversity can be nearly as high as possible near the critical regime, but for most parameter values it falls far below the theoretical limit. We conclude that lineage information is indispensable for understanding regulation of cellular growth.\n\nAuthor SummaryOne of the most important characteristics of a cell is whether it is growing. Actively growing cells can multiply exponentially. In the case of infections and cancer, growth causes problems for the host organism. On the other hand, cells that have stopped growing can allocate cellular resources toward different activities, such as bacteria surviving antibiotics and tissues in multicellular organisms performing their physiological roles. Observing small bacterial colonies in a microscope over time, we have found that cells closely related to each other often have similar growth state. We were curious if lineage dependence was an intrinsic property of growth regulation or if other factors were needed to explain this effect. We therefore built a computational model of a growing and dividing cellular colony with an encoded growth regulation network. We found that regulation of growth is sufficient for lineage dependence to emerge. We next asked if lineage dependence constrains how diverse the cellular population can become. We found that cellular diversity can reach a peak that is nearly as high as possible near the conditions that have the highest lineage dependence, but that most conditions do not permit such high diversity. We conclude that lineage is an important constraint and discuss how the growth arrest transition is in some ways like a phase transition from physics, and in some ways strikingly different, making it a unique phenomenon.

systems biology↗

bioRxiv2017

BMP signalling is critical for maintaining homeostasis of hair follicles and intestine in adult mice

BMP signalling play critical roles during embryonic development, however, its roles have not been extensively studied in the maintenance of adult tissue homeostasis. In this study we have used temporal knock out of Bmp2 and Bmp4 to uncover the role of BMP signalling in adult mice. We observed rapid changes in the adult hair follicles and the intestine within two days of depleting BMP signalling, which demonstrates the critical and acute requirement of BMP signalling in maintaining homeostasis in these tissues. In addition, our study demonstrates that while BMP signalling is required for maintenance of quiescence in telogen hair follicles, it is needed for survival and proliferation in late anagen hair follicles. Our study also reveals differential requirement of BMP signalling in differentiation of distinct intestinal cell types. In addition, Loss of BMP signalling rapidly promotes early neoplastic transformations in mouse intestine.

developmental biology↗