Biology subjects

Das, S.

Publications and source records attributed to Das, S..

33 records · Page 2Linked to original sources

bioRxiv2018

nPIST: A Novel Actin Binding Protein of trans-Golgi Network

npist is the neuronal isoform of PIST, a trans-golgi associated protein involved in major modulation of vesicular trafficking. nPIST interacts with glutamate delta2 receptor (GluR{delta}2) in Purkinje cells. Our study shows nPIST as a novel actin binding protein. Our structure based sequence analysis shows nPIST contains one WH2-like domain. Further our experimental analysis illustrates that fragment of nPIST consisting of WH2-like domain binds to actin. Moreover it was found that nPIST contains several regions involved in interaction with actin. The binding of nPIST to actin through multiple actin binding regions facilitated actin filament stabilization in vitro. In vivo, nPIST localized actin in perinuclear region as a blotch when ectopically expressed.

cell biology↗

bioRxiv2018

Influenza A Virus Negative Strand RNA is Translated for CD8+ T Cell Immunosurveillance

To probe the limits of CD8+ T cell immunosurveillance, we inserted the model peptide SIINFEKL into influenza A virus (IAV) negative strand gene segments. Although IAV genomic RNA is widely considered as non-coding, there is a conserved, relatively long open reading frame present in the genomic strand of segment eight, encoding a potential protein termed NEG8. The biosynthesis of NEG8 from IAV has yet to be demonstrated. While we failed to detect NEG8 protein expression in IAV infected cells, cell surface Kb-SIINFEKL complexes are generated when SIINFEKL is genetically appended to the predicted COOH-terminus of NEG8, as shown by activation of OT-I T cells in vitro and in vivo. Moreover, recombinant IAV encoding SIINFEKL embedded in the negative strand of the NA-stalk coding sequence also activates OT-I T cells in vivo. Together, our findings demonstrate both the translation of sequences on the negative strand of a single stranded RNA virus and its relevance anti-viral immunosurveillance.\n\nSignificanceEvery gene encodes complementary information on the opposite strand that can potentially be used for immunosurveillance. In this study, we show that the influenza A virus \"non-coding\" strand translated into polypeptides during a viral infection of either cultured cells or mice that can be recognized by CD8+ T cells. Our findings raise the possibility that influenza virus uses its negative strand to generate proteins useful to the virus. More generally, it adds to a growing literature showing that immunosurveillance extends to gene sequences generally thought not to be converted into proteins. The relevance of translating this \"dark\" information extends from viral immunity to cancer immunotherapy and autoimmunity.

immunology↗

bioRxiv2018

Functional wiring of the human medial temporal lobe

The medial temporal lobe (MTL) is a locus of episodic memory in the human brain. It is comprised of cytologically distinct subregions that, in concert, give rise to successful encoding and retrieval of context-dependent memories. However, the functional connections between these subregions are poorly understood. To determine functional connectivity among MTL subregions, we had 126 subjects fitted with indwelling electrodes perform a verbal memory task, and asked how encoding or retrieval correlated with interregional synchronization. Using phase-based measures of connectivity, we found that synchronous theta (4-8 Hz) activity underlies successful episodic memory, whereas high-frequencies exhibit desynchronization. Moreover, theta functional connectivity during encoding aligned with key anatomic connections, including critical links between the entorhinal cortex, dentate gyrus, and CA1 of the hippocampus. Retrieval-associated networks demonstrated enhanced involvement of the subiculum, reflecting a substantial reorganization of the encoding-associated network. We posit that coherent theta activity within the MTL marks periods of successful memory, but distinct patterns of connectivity dissociate key stages of memory processing.\n\nSignificance StatementThe brain functions through the interaction of its distinct parts, but little is known about how such connectivity dynamics relate to learning and memory. We used a large dataset of 126 human subjects with intracranial electrodes to assess patterns of electrical connectivity within the medial temporal lobe - a key region for memory processing - as they performed a memory task. We discovered that unique networks of time-varying, low-frequency interactions correlate with memory encoding and retrieval, specifically in the theta band. Simultaneously, we observed elevated spectral power at high frequencies in these same regions. The result is a complete map of physiological dynamics within the MTL, highlighting how a reorganization of theta networks support distinct memory operations.

neuroscience↗

bioRxiv2018

High precision automated detection of labelednuclei in terabyte-scale whole-brain volumetricimage data of mouse

There is a need in modern neuroscience for accurate and automated image processing techniques for analyzing the large volume of neuroanatomical data. For e.g., the use of light microscopy to image whole mouse brains in a mesoscopic scale produces individual neuroanatomical data volumes in the TerraByte range.. A fundamental task involves the detection and quantification of objects of a given type, e.g. neuronal nuclei or somata, in whole mouse brains. Traditionally this quantification is performed by human visual inspection with high accuracy, that is not scalable.. When state-of-the-art CNN and SVM-based methods are used to solve this classification problem, they achieve accuracy levels between 85 - 92%. However, higher rates of precision and recall, close to that of humans are necessary. In this paper, we describe an unsupervised, iterative algorithm, which provides a high close to human performance for a specific problem of broad interest, i.e. detection of Green Fluorescent Protein labeled nuclei in whole mouse brains. The algorithm judiciously combines classical computer vision (CV) techniques and is focused on the complex problem of decomposing strong overlapped objects (nuclei). Our proposed iterative method uses features detected on ridge lines over distance transformation and an arc based iterative spatial-filling method to solve the problem. We demonstrate our results on two whole mouse brain data sets of Gigabyte resolution and compare it with manual annotation of the brains. Our results show that an aptly designed CV algorithm with classical feature extractors when tailored to this problem of interest achieves near-ideal human-like performance. Quantitative analysis, when compared with the manually annotated ground truth, reveals that our approach performs better on whole mouse brain scans than general purpose machine learning (including deep CNN) methods.

neuroscience↗

bioRxiv2018

Extensive genomic diversity among Mycobacterium marinum strains revealed by whole genome sequencing

Mycobacterium marinum is the causative agent for the tuberculosis-like disease mycobacteriosis in fish and skin lesions in humans. Ubiquitous in its geographical distribution, M. marinum is known to occupy diverse fish as hosts. However, information about its genomic diversity is limited. Here, we provide the genome sequences for 15 M. marinum strains isolated from infected humans and fish. Comparative genomic analysis of these and four available genomes of the M. marinum strains M, E11, MB2 and Europe reveal high genomic diversity among the strains, leading to the conclusion that M. marinum should be divided into two different clusters, the \"M\"- and the \"Aronson\"-type. We suggest that these two clusters should be considered, if not two separate species, at least two M. marinum subspecies. Our data also show that the M. marinum pan-genome for both groups is open and expanding and we provide data showing high number of mutational hotspots in M. marinum relative to other mycobacteria such as Mycobacterium tuberculosis. This high genomic diversity might be related to that M. marinum occupy different ecological niches.

genomics↗

bioRxiv2017

Physical properties characterization of Natural Protein Fibre Peacock Feather Barbs

In the present study, the barbs of peacock feather were subjected to its physio-mechanical characterisation. Various properties of barbs viz., bundle strength, diameter, moisture regain, thermal stability, X-ray diffraction, colour intensity and FTIR was studied according standard analytical methods. The surface morphology of the barbs was examined using SEM images. The results indicate that the barb is a hollow vertical structure made up of protein. The average length and diameter of the barb was found to be 45 mm and 82 m respectively. The FTIR study confirms the presence of characteristic peaks for protein, related to the keratinous material. The barbs seem to be semi-crystalline in nature, as indicated by X-ray study.

zoology↗

bioRxiv2017

Identification and characterization of siderophore producing arsenic tolerant Staphylococcus sp. TA6 and its possible involvement in arsenic geocycle

The presence of arsenic in sediments, carbonaceous rocks are geogenic, while its entry into the aquifers is mediated by several factors including microorganisms. It is well known that the microorganisms play a crucial role in the biogeochemical cycle of different elements. However, the precise role of bacteria in regulating the concentration of arsenic in Brahmaputra valley has not been investigated in detail. In this paper, we report the isolation of arsenic resistant bacterium TA6 with active arsenate reduction efficiency. The isolate was able to grow in arsenate concentration (250 mM) and arsenite (30 mM). Along with resistance to inorganic arsenic, it showed cross-tolerance to other heavy metals like Hg+2, Cd+2, Co+2, Ni+2, Cr+2. The bacterium also had a high siderophore activity (78.7 {+/-} 0.004 mol), which is positively correlated with the resistance aptitude. The biochemical test showed the TA6, a gram-positive bacterium which can hydrolyze starch and casein, produce catalase enzyme and utilizes citrate as a metabolic trait. Molecular and chemotaxonomic identification of TA6 based on 16S rRNA and FMAE analysis showed similarity with members of Staphylococcus genus with significant difference in sequence similarity and fatty acid composition. Based on 16S rRNA and FAME analysis it was identified as Staphylococcus sp. TA6. Rate of biotransformation showed bacterium could reduce ~88.2% of initial 2mM As(V) into As(III). The characterization of arsenate reductase enzyme with NADPH coupled assay showed the highest activity at pH 5.5 and temperature 50{degrees}C.

microbiology↗

bioRxiv2017

The medial temporal lobe organizes memory across time and space: Causal evidence from brain stimulation

The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects abilities to remember items using view-independent (allocentric) navigation strategies. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred.\n\nSignificance StatementNumerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory.

neuroscience↗

bioRxiv2017

Narrow-sense heritability estimation of complex traits using identity-by-descent information.

Heritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly-tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). IBD-based heritability estimates were unbiased when using unrelated individuals, even for traits with extremely rare CVs, but stratification led to strong biases in IBD-based heritability estimates with poor precision. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied successfully to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in this real data that were not predicted from our simulation, suggesting that more work may be required to understand factors that influence IBD-based estimates.

genetics↗

bioRxiv2017

Genetic architecture of early childhood growth phenotypes gives insights into their link with later obesity

Early childhood growth patterns are associated with adult metabolic health, but the underlying mechanisms are unclear. We performed genome-wide meta-analyses and follow-up in up to 22,769 European children for six early growth phenotypes derived from longitudinal data: peak height and weight velocities, age and body mass index (BMI) at adiposity peak (AP ~9 months) and rebound (AR ~5-6 years). We identified four associated loci (P< 5x10-8): LEPR/LEPROT with BMI at AP, FTO and TFAP2B with Age at AR and GNPDA2 with BMI at AR. The observed AR-associated SNPs at FTO, TFAP2B and GNPDA2 represent known adult BMI-associated variants. The common BMI at AP associated variant at LEPR/LEPROT was not associated with adult BMI but was associated with LEPROT gene expression levels, especially in subcutaneous fat (P<2x10-51). We identify strong positive genetic correlations between early growth and later adiposity traits, and analysis of the full discovery stage results for Age at AR revealed enrichment for insulin-like growth factor 1 (IGF-1) signaling and apolipoprotein pathways. This genome-wide association study suggests mechanistic links between early childhood growth and adiposity in later childhood and adulthood, highlighting these early growth phenotypes as potential targets for the prevention of obesity.

genomics↗

bioRxiv2017

Chaperone Network Based On Cellular Response Reveals The Non-Optimal Response To Perturbed Proteostasis

The proteostasis network (PN) comprises a plethora of proteins that are dedicated to aid in protein folding; some with over-lapping functions. Despite this, there are multiple pathophysiological states associated with depletion of chaperones. This is counter-intuitive assuming cells have the ability to re-program transcriptional outputs in accordance with its proteostasic limitations. To this effect, we have used S. cerevisiae to understand the route a cell takes as a response when challenged with different proteostasis impairments. Using 14 single deletion strains of genes of Protein Quality Control (PQC) system, we quantify their proteostasis impairment and the transcriptional response. In most cases cellular response was incapable of restoring proteostasis. The response did not activate proteostasis components or pathways that could complement the function of the missing PQC gene. Over-expression of alternate machineries, could restore part of the proteostasis defect in deletion strains. We posit that epistasis guided synthetic biology approaches may be helpful in realizing the true potential of the cellular chaperone machinery.

genetics↗

bioRxiv2017

Molecular Noise Accelerates Cell Division And Death Under Antibiotic Treatment

It is well known that microbial cell populations can exhibit sustained exponential growth. More surprising is the fact that at high antibiotic levels, cell populations exhibit sustained exponential decay over several orders of magnitude. The boundary between growth and decay occurs at the Minimal Inhibitory Concentration (MIC) of the antibiotic, where the density of living cells remains constant over time. These observations suggest that positive (growth) or negative (decay) exponents arise as a difference of cell division and death rates obeying first-order kinetics. Thus for antibiotic concentrations below MIC, division dominates; for concentrations above MIC, death dominates; while MIC itself is a dynamic steady state of balanced division and death, rather than cell stasis. To measure these rates we separately tracked living and dead cells in Escherichia coli populations treated with the ribosome-targeting antibiotic kanamycin. We found that cells divide rapidly even at MIC: inferred division and death rates at MIC are 0.6 times the antibiotic-free division rate. A stochastic model of cells as collections of self-replicating units we term \"widgets\" reproduces both steady-state and transient features of our experiments, and explains first-order exponential kinetics. In this model cell division and death rates at MIC can be tuned from low to high values by amplifying molecular noise in the synthesis, degradation and partitioning of the widgets. At extremely low noise, cells approach the classic bacteriostatic limit at MIC: neither dividing nor dying. Noise-induced division and death of cells following antibiotic treatment could increase the likelihood of sepsis and antibiotic resistance.

microbiology↗

bioRxiv2017

Maternal and fetal genetic contribution to gestational weight gain

BackgroundClinical recommendations to limit gestational weight gain (GWG) imply high GWG is causally related to adverse outcomes in mother or offspring, but GWG is the sum of several inter-related complex phenotypes (maternal fat deposition and vascular expansion, placenta, amniotic fluid and fetal growth). Understanding the genetic contribution to GWG could help clarify the potential effect of its different components on maternal and offspring health. Here we explore the genetic contribution to total, early and late GWG.\n\nParticipants and MethodsA genome-wide association study was used to identify maternal and fetal variants contributing to GWG in up to 10,543 mothers and up to 16,317 offspring of European origin, with replication in 10,660 mothers and 7,561 offspring. Additional analyses determined the proportion of variability in GWG from maternal and fetal common genetic variants and the overlap of established genome-wide significant variants for phenotypes relevant to GWG (e.g. maternal BMI and glucose, birthweight).\n\nResultsWe found that approximately 20% of the variability in GWG was tagged by common maternal genetic variants, and that the fetal genome made a surprisingly minor contribution to explaining variation in GWG. We were unable to identify any genetic variants that reached genome-wide levels of significance (P<5x10-8) and replicated. Some established maternal variants associated with increased BMI, fasting glucose and type 2 diabetes were associated with lower early, and higher later GWG. Maternal variants related to higher systolic blood pressure were related to lower late GWG. Established maternal and fetal birthweight variants were largely unrelated to GWG.\n\nConclusionWe found a modest contribution of maternal common variants to GWG and some overlap of maternal BMI, glucose and type 2 diabetes variants with GWG. These findings suggest that associations between GWG and later offspring/maternal outcomes may be due to the relationship of maternal BMI and diabetes with GWG.

genetics↗

bioRxiv2017

Comparison of methods that use whole genome data to estimate the heritability and genetic architecture of complex traits.

Heritability, h2, is a foundational concept in genetics, critical to understanding the genetic basis of complex traits. Recently-developed methods that estimate heritability from genotyped SNPs, h2 SNP, explain substantially more genetic variance than genome-wide significant loci, but less than classical estimates from twins and families. However, h2SNP estimates have yet to be comprehensively compared under a range of genetic architectures, making it difficult to draw conclusions from sometimes conflicting published estimates. Here, we used thousands of real whole genome sequences to simulate realistic phenotypes under a variety of genetic architectures, including those from very rare causal variants. We compared the performance of ten methods across different types of genotypic data (commercial SNP array positions, whole genome sequence variants, and imputed variants) and under differing causal variant frequencies, levels of stratification, and relatedness thresholds. These results provide guidance in interpreting past results and choosing optimal approaches for future studies. We then chose two methods (GREML-MS and GREML-LDMS) that best estimated overall h2SNP and the causal variant frequency spectra to six phenotypes in the UK Biobank using imputed genome-wide variants. Our results suggest that as imputation reference panels become larger and more diverse, estimates of the frequency distribution of causal variants will become increasingly unbiased and the vast majority of trait narrow-sense heritability will be accounted for.

genetics↗

bioRxiv2016

Viral Quasispecies Reconstruction via Correlation Clustering

RNA viruses are characterized by high mutation rates that give rise to populations of closely related viral genomes, the so-called viral quasispecies. The underlying genetic heterogeneity occurring as a result of natural mutation-selection process enables the virus to adapt and proliferate in face of changing conditions over the course of an infection. Determining genetic diversity (i.e., inferring viral haplotypes and their proportions in the population) of an RNA virus is essential for the understanding of its origin and mutation patterns, and the development of effective drug treatments. In this paper we present QSdpR, a novel correlation clustering formulation of the quasispecies reconstruction problem which relies on semidefinite programming to accurately estimate the sub-species and their frequencies in a mixed population. Extensive comparisons with existing methods are presented on both synthetic and real data, demonstrating efficacy and superior performance of QSdpR.

bioinformatics↗