Biology subjects

Bandyopadhyay, S.

Publications and source records attributed to Bandyopadhyay, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2021

Decade-long remissions of leukemia sustained by the persistence of activated CD4+ CAR T-cells

The adoptive transfer of T lymphocytes reprogrammed to target tumor cells has demonstrated significant potential in various malignancies. However, little is known about the long-term potential and the clonal stability of the infused cells. Here, we studied the longest persisting CD19-redirected chimeric antigen receptor (CAR) T cells to date in two chronic lymphocytic leukemia (CLL) patients who achieved a complete remission in 2010. CAR T-cells were still detectable up to 10+ years post-infusion, with sustained remission in both patients. Surprisingly, a prominent, highly activated CD4+ population developed in both patients during the years post-infusion, dominating the CAR T-cell population at the late time points. This transition was reflected in the stabilization of the clonal make-up of CAR T-cells with a repertoire dominated by few clones. Single cell multi-omics profiling via Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) with TCR sequencing of CAR T-cells obtained 9.3 years post-infusion demonstrated that these long-persisting CD4+ CAR T-cells exhibited cytotoxic characteristics along with strong evidence of ongoing functional activation and proliferation. Our data provide novel insight into the CAR T-cell characteristics associated with long-term remission in leukemia.

immunology↗

bioRxiv2021

Generating realistic cell samples for gene selection in scRNA-seq data: A novel generative framework

High dimensional, small sample size (HDSS) scRNA-seq data presents a challenge to the gene selection task in single cell. Conventional gene selection techniques are unstable and less reliable due to the fewer number of available samples which affects cell clustering and annotation. Here, we present an improved version of generative adversarial network (GAN) called LSH-GAN to address this issue by producing new realistic samples and combining this with the original scRNA-seq data. We update the training procedure of the generator of GAN using locality sensitive hashing which speeds up the sample generation, thus maintains the feasibility of applying gene selection procedures in high dimension scRNA-seq data. Experimental results show a significant improvement in the performance of benchmark feature (gene) selection techniques on generated samples of one synthetic and four HDSS scRNA-seq data. Comprehensive simulation study ensures the applicability of the model in the feature (gene) selection domain of HDSS scRNA-seq data. AvailabilityThe corresponding software is available at https://github.com/Snehalikalall/LSH-GAN

bioinformatics↗

bioRxiv2021

Separate functional subnetworks of excitatory neurons show preference to periodic and random sound structures

Auditory cortex (ACX) neurons are sensitive to spectro-temporal sound patterns and violations in patterns induced by rare stimuli embedded within streams of sounds. We investigate the auditory cortical representation of repeated presentations of sequences of sounds with standard stimuli (common) with an embedded deviant (rare) stimulus in two conditions - Periodic (Fixed deviant position) or Random (Random deviant position), using extracellular single-unit and 2-photon Ca+2 imaging recordings in Layer 2/3 neurons of the mouse ACX. In the population average, responses increased over repetitions in the Random-condition and were suppressed or did not change in the Periodic-condition, showing irregularity preference. A subset of neurons also showed the opposite behavior, indicating regularity preference. Pairwise noise correlations were higher in Random-condition over Periodic-condition, suggesting the role of recurrent connections. 2-photon Ca+2 imaging of excitatory (EX) and parvalbumin-positive (PV) and somatostatin-positive (SOM) inhibitory neurons, showed different categories of adaptation or change in response over repetitions (categorized by the sign of the slope of change) as observed with single units. However, the examination of functional connectivity between pairs of neurons of different categories showed that EX-PV connections behaved opposite to the EX-EX and EX-SOM pairs that show more functional connections outside category in Random-condition than Periodic-condition. Finally considering Regularity preference, Irregularity preference and no preference categories, showed that EX-EX and EX-SOM connections to be in largely separate functional subnetworks with the different preferences, while EX-PV connections were more spread. Thus separate subnetworks could underly the coding of periodic and random sound sequences. Significance StatementStudying how the ACX neurons respond to streams of sound sequences help us understand the importance of changes in dynamic acoustic noisy scenes around us. Humans and animals are sensitive to regularity and its violations in sound sequences. Psychophysical tasks in humans show that auditory brain differentially responds to periodic and random structures, independent of the listeners attentional states. Here we show that mouse ACX L2/3 neurons detect a change and respond differentially to changing patterns over long-time scales. The differential functional connectivity profile obtained in response to two different sound contexts, suggest the stronger role of recurrent connections in the auditory cortical network. Furthermore, the excitatory-inhibitory neuronal interactions can contribute to detecting the changing sound patterns.

neuroscience↗

bioRxiv2021

Modulation of auditory responses by visual inputs in the mouse auditory cortex

So far, our understanding on the role of the auditory cortex (ACX) in processing visual information has been limited to infragranular layers of the ACX, which have been shown to respond to visual stimulation. Here, we investigate the neurons in supragranular layers of the mouse ACX using 2-photon calcium imaging. Contrary to previous reports, here we show that more than 20% of responding neurons in layer2/3 of the ACX respond to full-field visual stimulation. These responses occur by both excitation and hyperpolarization. The primary ACX (A1) has a greater proportion of visual responses by hyperpolarization compared to excitation likely driven by inhibitory neurons of the infragranular layers of the ACX rather than local layer 2/3 inhibitory neurons. Further, we found that more than 60% of neurons in the layer 2/3 of A1 are multisensory in nature. We also show the presence of multisensory neurons in close proximity to exclusive auditory neurons and that there is a reduction in the noise correlations of the recorded neurons during multisensory presentation. This is evidence in favour of deep and intricate visual influence over auditory processing. The results have strong implications for decoding visual influences over the early auditory cortical regions. Significance statementTo understand, what features of our visual world are processed in the auditory cortex (ACX), understanding response properties of auditory cortical neurons to visual stimuli is important. Here, we show the presence of visual and multisensory responses in the supragranular layers of the ACX. Hyperpolarization to visual stimulation is more commonly observed in the primary ACX. Multisensory stimulation results in suppression of responses compared to unisensory stimulation and an overall decrease in noise correlation in the primary ACX. The close-knit architecture of these neurons with auditory specific neurons suggests the influence of non-auditory stimuli on the auditory processing.

neuroscience↗

bioRxiv2021

Trans-channel fluorescence learning improves high-content screening for Alzheimer's disease therapeutics

In microscopy-based drug screens, fluorescent markers carry critical information on how compounds affect different biological processes. However, practical considerations may hinder the use of certain fluorescent markers. Here, we present a deep learning method for overcoming this limitation. We accurately generated predicted fluorescent signals from other related markers and validated this new machine learning (ML) method on two biologically distinct datasets. We used the ML method to improve the selection of biologically active compounds for Alzheimers disease (AD) from high-content high-throughput screening (HCS). The ML method identified novel compounds that effectively blocked tau aggregation, which would have been missed by traditional screening approaches unguided by ML. The method improved triaging efficiency of compound rankings over conventional rankings by raw image channels. We reproduced this ML pipeline on a biologically independent cancer-based dataset, demonstrating its generalizability. The approach is disease-agnostic and applicable across diverse fluorescence microscopy datasets.

pharmacology and toxicology↗

bioRxiv2020

RgCop-A regularized copula based method for gene selection in single cell rna-seq data

Gene selection in unannotated large single cell RNA sequencing (scRNA-seq) data is important and crucial step in the preliminary step of downstream analysis. The existing approaches are primarily based on high variation (highly variable genes) or significant high expression (highly expressed genes) failed to provide stable and predictive feature set due to technical noise present in the data. Here, we propose RgCop, a novel regularized copula based method for gene selection from large single cell RNA-seq data. RgCop utilizes copula correlation (Ccor), a robust equitable dependence measure that captures multivariate dependency among a set of genes in single cell expression data. We raise an objective function by adding a l1 regularization term with Ccor to penalizes the redundant co-efficient of features/genes, resulting non-redundant effective features/genes set. Results show a significant improvement in the clustering/classification performance of real life scRNA-seq data over the other state-of-the-art. RgCop performs extremely well in capturing dependence among the features of noisy data due to the scale invariant property of copula, thereby improving the stability of the method. Moreover, the differentially expressed (DE) genes identified from the clusters of scRNA-seq data are found to provide an accurate annotation of cells. Finally, the features/genes obtained from RgCop can able to annotate the unknown cells with high accuracy. AvailabilityCorresponding software is available in: https://github.com/Snehalikalall/RgCop Contactsumanta.ray@cwi.nl

bioinformatics↗

bioRxiv2020

UDP-glucose pyrophosphorylase 2, a regulator of glycosylation and glycogen, is essential for pancreatic cancer growth

Pancreatic ductal adenocarcinomas (PDACs) have enhanced nutrient uptake requirements and rapid metabolic processing. The enzyme UDP-glucose pyrophosphorylase 2 (UGP2) rests at the convergence of multiple metabolic pathways, however the role of UGP2 in tumor maintenance and cancer metabolism remains unclear. Here, we identify an essential role for UGP2 in the maintenance of PDAC growth in both in vitro and in vivo tumor models. Transcription of UGP2 is directly regulated by the YAP/TEAD complex. Loss of UGP2 leads to decreased intracellular glycogen and defects in N-glycosylation targets important for cell growth including epidermal growth factor receptor (EGFR). In murine xenograft models, knockdown of UGP2 halted tumor growth and repressed expression of EGFR. The critical roles of UGP2 in cancer maintenance, metabolism, and protein glycosylation may offer new avenues of therapy for otherwise intractable PDACs. Impact StatementConvergent findings reveal that UDP-glucose pyrophosphorylase 2 has a central role in growth and metabolism of pancreatic ductal adenocarcinomas, highlighting novel therapeutic possibilities for this deadly cancer.

cancer biology↗

bioRxiv2020

sc-REnF: An entropy guided robust feature selection for clustering of single-cell rna-seq data

Many single-cell typing methods require pure clustering of cells, which is susceptible towards the technical noise, and heavily dependent on high quality informative genes selected in the preliminary steps of downstream analysis. Techniques for gene selection in single-cell RNA sequencing (scRNA-seq) data are seemingly simple which casts problems with respect to the resolution of (sub-)types detection, marker selection and ultimately impacts towards cell annotation. We introduce sc-REnF, a novel and robust entropy based feature (gene) selection method, which leverages the landmark advantage of Renyi and Tsallis entropy achieved in their original application, in single cell clustering. Thereby, gene selection is robust and less sensitive towards the technical noise present in the data, producing a pure clustering of cells, beyond classifying independent and unknown sample with utmost accuracy. The corresponding software is available at: https://github.com/Snehalikalall/sc-REnF

bioinformatics↗

bioRxiv2020

Motif Analysis in k-mer Networks: An Approach towards Understanding SARS-CoV-2 Geographical Shifts

With an increasing number of SARS-CoV-2 sequences available day by day, new genomic information is getting revealed to us. As SARS-CoV-2 sequences highlight wide changes across the samples, we aim to explore whether these changes reveal the geographical origin of the corresponding samples. The k-mer distributions, denoting normalized frequency counts of all possible combinations of nucleotide of size upto k, are often helpful to explore sequence level patterns. Given the SARS-CoV-2 sequences are highly imbalanced by its geographical origin (relatively with a higher number samples collected from the USA), we observe that with proper under-sampling k-mer distributions in the SARS-CoV-2 sequences predict its geographical origin with more than 90% accuracy. The experiments are performed on the samples collected from six countries with maximum number of sequences available till July 07, 2020. This comprises SARS-CoV-2 sequences from Australia, USA, China, India, Greece and France. Moreover, we demonstrate that the changes of genomic sequences characterize the continents as a whole. We also highlight that the network motifs present in the sequence similarity networks have a significant difference across the said countries. This, as a whole, is capable of predicting the geographical shift of SARS-CoV-2.

bioinformatics↗

bioRxiv2020

A tyrosine kinase protein interaction map reveals targetable EGFR network oncogenesis in lung cancer

SUMMARYSignaling networks balance the activities of many physically interacting proteins and perturbations to this network influence downstream signaling, potentially leading to oncogenic states. Using affinity purification-mass spectrometry we defined this network for all 90 human tyrosine kinases revealing 1,463 mostly novel interactions between these key cancer proteins and diverse molecular complexes. Modulation of interactor levels altered growth phenotypes associated with corresponding tyrosine kinase partners suggesting that tumors may alter the stoichiometries of interactors to maximize oncogenic signaling. We show that the levels of EGFR interactors delineates this form of network oncogenesis in 19% of EGFR wild-type lung cancer patients which were mostly otherwise oncogene negative, predicting sensitivity to EGFR inhibitors in vitro and in vivo. EGFR network oncogenesis occurs through mechanistically distinct network alleles often in cooperation with weak oncogenes in the MAPK pathway. Network oncogenesis may be a common and targetable convergent mechanism of oncogenic pathway activation in cancer.HIGHLIGHTSA human tyrosine kinome protein interaction map reveals novel physical and functional associations.Dependence on oncogenic tyrosine kinases is modulated through perturbation of their interactors.EGFR network oncogenesis in up to 19% of EGFR wild-type lung cancers is targetable.EGFR network oncogenesis cooperates with weak oncogenes in the MAPK pathway.Competing Interest StatementS.L.W. is an employee of Pfizer. D.C., I.S., E.M., are employees of Champions oncology. S.B. has received funding from Clovis Oncology, Pfizer, Revolution Medicines and Ideaya Biosciences.View Full Text

cancer biology↗

bioRxiv2020

Tracing Back the Temporal Change of SARS-Cov-2 with Genomic Signatures

The coronavirus disease (COVID-19) outbreak starting from China at the end of 2019 and its subsequent spread in many countries have given rise to thousands of coronavirus samples being collected and sequenced till date. To trace back the initial temporal change of SARS-CoV-2, the coronavirus implicated in COVID-19, we study the limited genomic sequences that were available within the first couple of months of its spread. These samples were collected under varying circumstances and highlight wide variations in their genomic compositions. In this paper, we explore whether these variations characterize the initial temporal change of SARS-CoV-2 sequences. We observe that n-mer distributions in the SARS-CoV-2 samples, which were collected at an earlier period of time, predict its collection timeline with approximately 78% accuracy. However, such a distinctive pattern disappears with the inclusion of samples collected at a later time. We further observe that isolation sources (e.g., oronasopharynx, saliva, feces, etc.) could not be predicted by the n-mer patterns in these sequences. Finally, the phylogenetic and protein-alignment analyses highlight interesting associations between SARS-CoV-2 and other coronaviruses.

bioinformatics↗

bioRxiv2020

Temporal Dysbiosis of Infant Nasal Microbiota Relative to Respiratory Syncytial Virus Infection

RationaleRespiratory Syncytial Virus (RSV) infection is a leading cause of infant respiratory disease and hospitalization. Infant airway microbiota occupying the nasopharynx have been associated with respiratory disease risk and severity. The extent to which interactions between RSV and microbiota occur in the airway, and their impact on respiratory disease severity and infection susceptibility, are not well understood. ObjectivesTo characterize associations between the nasal microbiota and RSV infection before, during, and after infants first respiratory illness. MethodsNasal 16S rRNA microbial community profiling of two cohorts of infants in the first year of life: 1) a cross-sectional cohort of 89 RSV infected infants sampled during illness and 102 population matched healthy controls, and 2) an individually matched longitudinal cohort of 12 infants who developed RSV infection and 12 who did not, sampled at time points before, during, and after infection. Measurements and Main ResultsWe identified 12 taxa significantly associated with RSV infection. All 12 were differentially abundant during infection, with seven differentially abundant prior to infection, and eight differentially abundant after infection. Eight of these taxa were associated with disease severity. Nasal microbiota composition was more discriminative of healthy vs. infected than of disease severity. ConclusionsOur findings elucidate the chronology of nasal microbiota dysbiosis and suggest an altered developmental trajectory associated with first-time RSV infection. Microbial temporal dynamics reveal indicators of disease risk, correlates of illness and severity, and the impact of RSV infection on microbiota composition. Identified taxa represent appealing targets for additional translationally-oriented research.

microbiology↗

bioRxiv2020

Comprehensive analysis of fungal G1 cyclin docking motif sequences that control CDK regulatory potency in vivo

Cyclin-dependent kinases (CDKs) control the ordered series of events during eukaryotic cell division. The stage at which individual CDK substrates are phosphorylated can be dictated by cyclin-specific docking motifs. In budding yeast, substrates with Leu/Pro-rich (LP) docking motifs are recognized by Cln1/2 cyclins in late G1 phase, yet the key sequence features of these motifs and the conservation of this mechanism were unknown. Here we comprehensively analyzed LP motif requirements in vivo by combining a competitive growth assay with mutational scanning and deep sequencing. We quantified the impact of all single-residue replacements in five different LP motifs, using six distinct G1 cyclins from diverse fungi including medical and agricultural pathogens. The results reveal the basis for variations in potency among wild-type motifs, and allow derivation of a quantitative matrix that predicts the potency of other candidate motifs. In one protein, Whi5, we found overlapping LP and phosphorylation motifs with partly redundant effects. In another protein, the CDK inhibitor Sic1, we found that its LP motif is inherently weak due to unfavorable residues at key positions, and this imposes a beneficial delay in its phosphorylation and degradation. The overall results provide a general method for surveying viable docking motif sequences and quantifying their potency in vivo, and they reveal how variations in LP motif potency can tune the strength and timing of CDK regulation.

molecular biology↗

bioRxiv2020

Parallel lemniscal and non-lemniscal sources control auditory responses in the orbitofrontal cortex (OFC)

The orbitofrontal cortex (OFC), controls flexible behavior through stimulus value updating based on stimulus outcome associations, allowing seamless navigation in dynamic sensory environments with changing contingencies. Sensory cue driven responses, primarily studied through behavior, exist in the OFC. However, OFC neurons sensory response properties, particularly auditory, are unknown, in the mouse, a genetically tractable animal. We show that mouse OFC single neurons have unique auditory response properties showing pure deviance detection and long timescales of adaptation resulting in stimulus-history dependence. Further, we show that OFC auditory responses are shaped by two parallel sources in the auditory thalamus, lemniscal and non-lemniscal. The latter underlies a large component of the observed deviance detection and additionally controls persistent activity in the OFC through the amygdala. The deviant selectivity can serve as a signal for important changes in the auditory environment. Such signals if coupled with persistent activity, obtained by disinhibitory control from the non-lemniscal auditory thalamus or the amygdala, will allow for associations with a delayed outcome related signal, like reward prediction error, and potentially forms the basis of updating stimulus outcome associations in the OFC. Thus the baseline sensory responses allow the behavioral requirement based response modification through relevant inputs from other structures related to reward, punishment, or memory. Thus, alterations in these responses in neurological disorders can lead to behavioral deficits.

neuroscience↗

bioRxiv2019

Earliest experience of rare but not frequent sounds causes long term changes in the adult auditory cortex

Sensory experience during a critical period alters sensory cortical responses and organization. We find that the earliest sound driven activity in the mouse auditory cortex (ACX) starts before ear-canal opening (ECO). Effects of auditory experience before ECO on ACX development are unknown. We find that mouse ACX subplate neurons (SPNs), crucial in thalamocortical maturation, respond to sounds before ECO showing oddball selectivity. Before ECO, SPNs are more selective to oddball sounds in auditory streams than thalamo-recipient layer 4 (L4) neurons and not after ECO. We hypothesize that SPNs oddball selectivity can direct development of L4 responses before ECO. Exposing mice before ECO with a rarely occurring tone in a stream of another tone occurring frequently leads to the strengthening of the adult cortical representation of the rare tone, but not that of the frequent tone. Results of control exposure experiments at multiple developmental windows and also with only a single tone corroborate the observations. A computational network model of known thalamic inputs to SPNs and L4 explains the observed developmental plasticity. Information-theoretic analysis with sparse coding assumptions also predicts the observations. Thus, salient low probability sounds in the earliest auditory environment cause long term changes in the ACX.

neuroscience↗

bioRxiv2019

Differential rapid plasticity in auditory and visual responses in the primarily multisensory orbitofrontal cortex

In a dynamic environment with rapidly changing contingencies, the orbitofrontal cortex (OFC) guides flexible behavior through coding of stimulus value. Although stimulus-evoked responses in the OFC are known to convey outcome, baseline sensory response properties in the mouse OFC are poorly understood. To understand mechanisms involved in stimulus value/outcome encoding it is important to know the response properties of single neurons in the mouse OFC, purely from a sensory perspective. Ruling out effects of behavioral state, memory and others, we studied the anesthetized mouse OFC responses to auditory, visual and audiovisual/multisensory stimuli, multisensory associations and sensory-driven input organization to the OFC. Almost all, OFC single neurons were found to be multisensory in nature, with sublinear to supralinear integration of the component unisensory stimuli. With a novel multisensory oddball stimulus set, we show that the OFC receives both unisensory as well as multisensory inputs, further corroborated by retrograde tracers showing labeling in secondary auditory and visual cortices, which we find to also have similar multisensory integration and responses. With long audiovisual pairing/association, we show rapid plasticity in OFC single neurons, with a strong visual bias, leading to a strong depression of auditory responses and effective enhancement of visual responses. Such rapid multisensory association driven plasticity is absent in the auditory and visual cortices, suggesting its emergence in the OFC. Based on the above results we propose a hypothetical local circuit model in the OFC that integrates auditory and visual information which participates in computing stimulus value in dynamic multisensory environments. Significance StatementProperties and modification of sensory responses of neurons in the orbitofrontal cortex (OFC) involved in flexible behavior through stimulus value/outcome encoding are poorly understood. Such responses are critical in providing the framework for the encoding of stimulus value based on behavioral context while also directing plastic changes in sensory regions. The mouse OFC is found to be primarily multisensory with varied nonlinear interactions, explained by unisensory and multisensory inputs. Audio-visual associations cause rapid plastic changes in the OFC, which bias visual responses while suppressing auditory responses. Similar plasticity was absent in the sensory cortex. Thus the observed intrinsic visual bias in the OFC weighs visual stimuli more than associated auditory stimuli in value encoding in a dynamic multisensory environment.

neuroscience↗

bioRxiv2019

Non-affine displacements encode collective conformational fluctuations in proteins

Identifying subtle conformational fluctuations underlying the dynamics of bio macro-molecules is crucial for resolving their free energy landscape. We show that a collective variable, originally proposed for crystalline solids, is able to filter out essential macro-molecular motions more efficiently than other approaches. While homogenous or affine deformations of the biopolymer are trivial, biopolymer conformations are complicated by the occurrence of in-homogenous or non-affine displacements of atoms relative to their positions in the native structure. We show that these displacements encode functionally relevant conformations of macromolecule and, in combination with a formalism based upon time-structured independent component analysis, quantitatively resolve the free energy landscape of a number of macromolecules of hierarchical complexity. The kinetics of conformational transitions among the basins can now be mapped within the framework of a Markov state model. The non-affine modes, obtained by projecting out homogenous fluctuations from the local displacements, are found to be responsible for local structural changes required for transitioning between pairs of macro states.

biophysics↗

bioRxiv2019

S-conLSH: Alignment-free gapped mapping of noisy long reads

MotivationThe advancement of SMRT technology has unfolded new opportunities of genome analysis with its longer read length and low GC bias. Alignment of the reads to their appropriate positions in the respective reference genome is the first but costliest step of any analysis pipeline based on SMRT sequencing. However, the state-of-the-art aligners often fail to identify distant homologies due to lack of conserved regions, caused by frequent genetic duplication and recombination. Therefore, we developed a novel alignment-free method of sequence mapping that is fast and accurate. ResultsWe present a new mapper called S-conLSH that uses Spaced context based Locality Sensitive Hashing. With multiple spaced patterns, S-conLSH facilitates a gapped mapping of noisy long reads to the corresponding target locations of a reference genome. We have examined the performance of the proposed method on 5 different real and simulated datasets. S-conLSH is at least 2 times faster than the state-of-the-art alignment-based methods. It achieves a sensitivity of 99%, without using any traditional base-to-base alignment, on human simulated sequence data. By default, S-conLSH provides an alignment-free mapping in PAF format. However, it has an option of generating aligned output as SAM-file, if it is required for any downstream processing. AvailabilityThe source code of our software is freely available at https://github.com/anganachakraborty/S-conLSH

bioinformatics↗