Biology subjects

Sarkar, A.

Publications and source records attributed to Sarkar, A..

10 recordsLinked to original sources

bioRxiv2018

Understanding visual attention with RAGNAROC: A Reflexive Attention Gradient through Neural AttRactOr Competition

A quintessential challenge for any perceptual system is the need to focus on task-relevant information without being blindsided by unexpected, yet important information. The human visual system incorporates several solutions to this challenge, one of which is a reflexive covert attention system that is rapidly responsive to both the physical salience and the task-relevance of new information. This paper presents a model that simulates behavioral and neural correlates of reflexive attention as the product of brief neural attractor states that are formed across the visual hierarchy when attention is engaged. Such attractors emerge from an attentional gradient distributed over a population of topographically organized neurons and serve to focus processing at one or more locations in the visual field, while inhibiting the processing of lower priority information. The model moves towards a resolution of key debates about the nature of reflexive attention, such as whether it is parallel or serial, and whether suppression effects are distributed in a spatial surround, or selectively at the location of distractors. Most importantly, the model develops a framework for understanding the neural mechanisms of visual attention as a spatiotopic decision process within a hierarchy and links them to observable correlates such as accuracy, reaction time, and the N2pc and PD components of the EEG. This last contribution is the most crucial for repairing the disconnect that exists between our understanding of behavioral and neural correlates of attention.

neuroscience↗

bioRxiv2018

Emergence of Multidrug-Resistant Uropathogens harboring ESBL, Carbapenem, Aminoglycosides and AmpC resistant genes from Northern India

Extended-spectrum {beta}-lactamase (ESBL) producing bacteria acts as a serious threat, and its co-existence with other antibiotic resistant gene makes the clinical scenario worse nowadays. Therefore in this study, we investigated the occurrence of ESBL genes coexisting with carbapenem, AmpC and aminoglycoside resistance gene in uropathogens. Out of 1516 urine samples, 454 showed significant bacteriuria with a prevalence rate of 29.94 %. Escherichia coli (n=340) were found to be the most predominant uropathogen followed by Klebsiella pneumoniae (n=92), Pseudomonas aeruginosa (n=10) and Proteus mirabilis (n=9). Among the total uropathogens, sixty-three ESBL-producers were identified which included blaCTX-M-15 (n=32), followed by blaCTX-M-15 + blaOXA-2 (n=15), blaCTX-M-15 + blaOXA-2 + blaTEM (n=6), blaOXA-2 (n=5), bla OXA-2 + bla SHV-76 (n=1), bla TEM+SHV-76 (n= 1) and bla TEM (n=1). All ESBL genes were found on plasmid incompatibility types: HI1, I1, FIA+FIB, FIA and Y and were horizontally transferable. Among 63 ESBL-producers, 59 isolates harboured carbapenem-resistant genes which included blaNDM-5 (n=48), blaNDM-5 + blaOXA-48 (n=5), blaNDM-5 + blaIMP (n=5) and blaNDM-5 + blaIMP + blaVIM (n=1). The ESBL producing uropathogens also harbored 16S rRNA methylase genes which included rmtB (n=9), rmtA (n=4), rmtC (n=1) and ArmA (n=1) followed by AmpC genes which includes CIT (n=8) and DHA-1 (n=1) genes. Imipenem and gentamicin were found to be more effective. We speculating, this is the first report showing the prevalence of multidrug-resistant uropathogens in this area demanding regular surveillance for such resistance mechanisms which will be useful for health personnel to treat ESBL infection and its co-existence with another antibiotic resistance gene.

microbiology↗

bioRxiv2018

Speed breeding in growth chambers and glasshouses for crop breeding and model plant research

1.To meet the challenge of feeding a growing population, breeders and scientists are continuously looking for ways to increase genetic gain in crop breeding. One way this can be achieved is through \"speed breeding\" (SB), which shortens the breeding cycle and accelerates research studies through rapid generation advancement. The SB method can be carried out in a number of ways, one of which involves extending the duration of a plants daily exposure to light (photoperiod) combined with early seed harvest in order to cycle quickly from seed to seed, thereby reducing the generation times for some long-day (LD) or day-neutral crops. Here we present glasshouse and growth chamber-based SB protocols with supporting data from experimentation with several crop species. These protocols describe the growing conditions, including soil media composition, lighting, temperature and spacing, which promote rapid growth of spring and winter bread wheat, durum wheat, barley, oat, various members of the Brassica family, chickpea, pea, grasspea, quinoa and the model grass Brachypodium distachyon. Points of flexibility within the protocols are highlighted, including how plant density can be increased to efficiently scale-up plant numbers for single seed descent (SSD) purposes. Conversely, instructions on how to perform SB on a small-scale by creating a benchtop SB growth cabinet that enables optimization of parameters at a low cost are provided. We also outline the procedure for harvesting and germinating premature wheat, barley and pea seed to reduce generation time. Finally, we provide troubleshooting suggestions to avoid potential pitfalls.

plant biology↗

bioRxiv2018

HIV-1 vaccine design through minimizing envelope metastability

Overcoming envelope metastability is crucial to trimer-based HIV-1 vaccine design. Here, we present a coherent vaccine strategy by minimizing metastability. For ten strains across five clades, we demonstrate that gp41 ectodomain (gp41ECTO) is the main source of envelope metastability by replacing wild-type gp41ECTO with BG505 gp41ECTO of the uncleaved prefusion-optimized (UFO) design. These gp41ECTO-swapped trimers can be produced in CHO cells with high yield and high purity. Crystal structure of a gp41ECTO-swapped trimer elucidates how a neutralization-resistant tier 3 virus evades antibody recognition of the V2 apex. UFO trimers of transmitted/founder (T/F) viruses and UFO trimers containing a consensus-based ancestral gp41ECTO suggest an evolutionary root of the metastability. Gp41ECTO-stabilized trimers can be readily displayed on 24- and 60-meric nanoparticles, with incorporation of additional T cell help illustrated for a hyperstable 60-mer. In mice and rabbits, gp140 nanoparticles induced more effective tier 2 neutralizing antibody response than trimers with statistical significance.\n\nHIGHLIGHTSO_LIgp41 is the main source of HIV-1 envelope metastability\nC_LIO_LIBG505 gp41 of the UFO design stabilizes gp140 trimers of diverse subtypes\nC_LIO_LIgp41 stabilization facilitates gp140 nanoparticle assembly and improves production\nC_LIO_LINanoparticles elicit tier 2 neutralizing antibodies more effectively than trimers\nC_LI

microbiology↗

bioRxiv2018

Elucidating the active interaction mechanism of phytochemicals withanolide and withanoside derivatives with human serum albumin

Withania somnifera (Ashwagandha) is an efficient plant known in Ayurveda and Chinese medicine since ancient times, whose extracts are consumed orally as food supplement or as a health tonic owing to its several restorative properties for various CNS disorders, inflammation, tumour, stress and rheumatism. In this study, we have analyzed the binding interaction of four derivatives of Withania somnifera (Withanolide A, Withanolide B, Withanoside IV and Withanoside V) with HSA because of their important pharmacological properties. To unravel the binding between derivatives of Withania somnifera and HSA, fluorescence spectroscopy was used. Binding studies were further studied by molecular docking and dynamics studies and results confirmed greater stability upon binding of derivatives with HSA. Circular dichroism data illustrated change in the secondary structure of protein upon interaction with these derivatives, particularly the helical structure was increased and {beta}-sheets and random coils were decreased. Furthermore, morphological and topological changes were observed using AFM and TEM upon binding of ligands with HSA indicating that HSA-withnoside/withanolide complexes were formed. All the results cumulatively demonstrate strong binding of withanosides and withanolides derivatives with serum albumin, which should further be explored to study the pharmacokinetics and pharmacodynamics of these derivatives.

biophysics↗

bioRxiv2018

The RASSF6 tumor suppressor protein regulates apoptosis and cell cycle progression via Retinoblastoma protein.

RASSF6 is a member of the tumor suppressor Ras-association domain family (RASSF) proteins. RASSF6 is frequently suppressed in human cancers and its low expression is associated with poor prognosis. RASSF6 regulates cell cycle arrest and apoptosis and plays a tumor suppressor role. Mechanistically, RASSF6 blocks MDM2-mediated p53 degradation and enhances p53 expression. However, RASSF6 also induces cell cycle arrest and apoptosis in the p53-negative background, which implies that the tumor suppressor function of RASSF6 does not depend solely on p53. In this study, we have revealed that RASSF6 mediates cell cycle arrest and apoptosis via pRb. RASSF6 enhances the interaction between pRb and protein phosphatase. RASSF6 also enhances P16INK4A and P14ARF expression through suppressing BMI1. In this way, RASSF6 increases unphosphorylated pRb and augments the interaction between pRb and E2F1. Moreover, RASSF6 induces TP73-target genes via pRb and E2F1 in the p53-negative background. Finally, we confirmed that RASSF6 depletion induces polypoid cells in p53-negative HCT116 cells. In conclusion, RASSF6 behaves as a tumor suppressor in cancers with the loss-of-function of p53, and pRb is implicated in this function of RASSF6.

molecular biology↗

bioRxiv2018

Identification of co-evolving temporal networks

MotivationBiological networks describes the mechanisms which govern cellular functions. Temporal networks show how these networks evolve over time. Studying the temporal progression of network topologies is of utmost importance since it uncovers how a network evolves and how it resists to external stimuli and internal variations. Two temporal networks have co-evolving subnetworks if the topologies of these subnetworks remain similar to each other as the network topology evolves over a period of time. In this paper, we consider the problem of identifying co-evolving pair of temporal networks, which aim to capture the evolution of molecules and their interactions over time. Although this problem shares some characteristics of the well-known network alignment problems, it differs from existing network alignment formulations as it seeks a mapping of the two network topologies that is invariant to temporal evolution of the given networks. This is a computationally challenging problem as it requires capturing not only similar topologies between two networks but also their similar evolution patterns.\n\nResultsWe present an efficient algorithm, Tempo, for solving identifying coevolving subnetworks with two given temporal networks. We formally prove the correctness of our method. We experimentally demonstrate that Tempo scales efficiently with the size of network as well as the number of time points, and generates statistically significant alignments--even when evolution rates of given networks are high. Our results on a human aging dataset demonstrate that Tempo identifies novel genes contributing to the progression of Alzheimers, Huntingtons and Type II diabetes, while existing methods fail to do so.\n\nAvailabilitySoftware is available online (https://www.cise.ufi.edu/[~]relhesha/temporal.zip).\n\nContactrelhesha@ufi.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2018

Is IκBζ constitutively expressed in mammalian airway epithelium?

I{kappa}B{zeta} is a transcriptional factor induced primarily in immune cells upon Toll-like receptor (TLR) activation that drives important cytokine responses. Recent studies have demonstrated constitutive I{kappa}B{zeta} expression in the epithelial cells of mouse skin and eyes, possibly reflecting the activation of TLRs by pathogen-associated molecular patterns (PAMPs). In this context, another mucosal surface, the lung epithelium, may not be as actively exposed to the external environment as the skin and the conjunctiva, especially since the lower lung airways are typically conceived to be sterile. Whether I{kappa}B{zeta} expression in the lungs is constitutive or induced remains largely unexplored. This is especially important since I{kappa}B{zeta} has been shown to promote the expression of protective cytokine and antimicrobial peptide responses, supporting a role for I{kappa}B{zeta} in lung host defense. We hence evaluated I{kappa}B{zeta} expression in airway epithelia of both humans and mice using immunostaining with antiserum raised against recombinant I{kappa}B{zeta} in our laboratory. We observed positive signal in the nuclei of ciliated epithelial cells lining the central airways. Airway cells of gnotobiotic mice also stained positive, suggesting that I{kappa}B{zeta} expression does not require induction by bacterial PAMPs. Unexpectedly, we also observed staining in the lung epithelia of I{kappa}B{zeta} knockout mice, indicating possible false positive signals from our immunohistochemistry experiments. In this context, 2D gel analysis followed by mass spectrometry revealed that our I{kappa}B{zeta} antiserum also detected a nuclear protein lamin B1. Nevertheless, immunoblotting tissue homogenates from gnotobiotic mouse lungs and primary human airway epithelial cells showed the appropriate 86 kDa band for I{kappa}B{zeta}. Together, these results demonstrate constitutive I{kappa}B{zeta} expression in airway epithelium, suggesting that lung epithelial cells may depend upon I{kappa}B{zeta} expression for airway protection.

immunology↗

bioRxiv2017

Causal gene inference by multivariate mediation analysis in Alzheimer's disease

Characterizing the intermediate phenotypes, such as gene expression, that mediate genetic effects on complex diseases is a fundamental problem in human genetics. Existing methods utilize genotypic data and summary statistics to identify putative disease genes, but cannot distinguish pleiotropy from causal mediation and are limited by overly strong assumptions about the data. To overcome these limitations, we develop Causal Multivariate Mediation within Extended Linkage disequilibrium (CaMMEL), a novel Bayesian inference framework to jointly model multiple mediated and unmediated effects relying only on summary statistics. We show in simulation that CaMMEL accurately distinguishes between mediating and pleiotropic genes unlike existing methods. We applied CaMMEL to Alzheimers disease (AD) and found 206 causal genes in sub-threshold loci (p < 10-4). We prioritized 21 genes which mediate at least 5% of local genetic variance, disrupting innate immune pathways in AD.

genetics↗

bioRxiv2017

Modeling prediction error improves power of transcriptome-wide association studies

1Transcriptome-wide association studies (TWAS) test for associations between imputed gene expression levels and phenotypes in GWAS cohorts using models of transcriptional regulation learned from reference transcriptomes. However, current methods for TWAS only use point estimates of imputed expression and ignore uncertainty in the prediction. We develop a novel two-stage Bayesian regression method which incorporates uncertainty in imputed gene expression and achieves higher power to detect TWAS genes than existing TWAS methods as well as standard methods based on missing value and measurement error theory. We apply our method to GTEx whole blood transcriptomes and GWAS cohorts for seven diseases from the Wellcome Trust Case Control Consortium and find 45 TWAS genes, of which 17 do not overlap previously reported case-control GWAS or differential expression associations. Surprisingly, we replicate only 2 of 40 previously reported TWAS genes after accounting for uncertainty in the prediction.

genetics↗