Biology subjects

Banerjee, A.

Publications and source records attributed to Banerjee, A..

11 recordsLinked to original sources

bioRxiv2018

Supply and consumption of glucose 6-phosphate in the chloroplast stroma

Fructose 6-phosphate is an intermediate in the Calvin-Benson cycle and can be acted on by phosphoglucoisomerase to make glucose 6-phosphate (G6P) for starch synthesis. A high concentration of G6P is favorable for starch synthesis but can also stimulate G6P dehydrogenase initiating the glucose-6-phosphate shunt an alternative pathway around the Calvin-Benson cycle. A low concentration of glucose 6-phosphate will limit this futile cycle. In order to understand the biochemical regulation of plastidic glucose 6-phosphate supply and consumption, we characterized biochemical parameters of two key enzymes, phosphoglucoisomerase (PGI) and G6P dehydrogenase (G6PDH). We have found that the plastidic PGI in has a higher Km for G6P compared to that for fructose 6-phosphate. The Km of G6PDH isoform 1 is increased under reducing conditions. The other two isoforms exhibit less redox regulation; isoform 2 is the most inhibited by NADPH. Our results support the conclusion that PGI restricts stromal G6P synthesis limiting futile cycling via G6PDH. It also acts like a one-way valve, allowing carbon to leave the Calvin-Benson cycle but not reenter. We found flexible redox regulation of G6PDH that could regulate the glucose-6-phosphate shunt.\n\nHighlightGlucose 6-phosphate stimulates glucose-6-phosphate dehydrogenase. This enzyme is less active during the day but retains significant activity that is very sensitive to the concentration of glucose 6-phopshate.

biochemistry↗

bioRxiv2018

Performance evaluation of inverse methods for identification and characterization of oscillatory brain sources: Ground truth validation & empirical evidences

Oscillatory brain electromagnetic activity is an established tool to study neurophysiological mechanisms of human behavior using electro-encephalogram (EEG) and magneto-encephalogram (MEG) techniques. Often, to extract source level information in the cortex, researchers have to rely on inverse techniques that generate probabilistic estimation of the cortical activation underlying EEG/ MEG data from sensors located outside the body. State of the art source localization methods using current density estimates such as exact low resolution electromagnetic tomography (eLORETA) and minimum norm estimates (MNE) as well as beamformers such as Dynamic Imaging of Coherent Sources (DICS) and Linearly Constrained Minimum Variance (LCMV) have over the years been established as the prominent techniques of choice. However, these algorithms produce a distributed map of brain activity underlying sustained and transient responses during neuroimaging studies of behavior. Furthermore, the volume conduction effects, phase lags between sources and noise of the environment play a considerable role in adding uncertainty to source localization. There are very few comparative analyses that evaluates the \"ground truth detection\" capabilities of these methods and evaluates their efficacies based on sources in temporal cortex relevant for auditory processing as well as mesial temporal lobe epilepsies. In this Methods article, we compare the aforementioned techniques to estimate sources of spectral event generators in the cortex using a two-pronged approach. First, we simulated EEG data with point dipole (single and two-point), as well as, distributed dipole modelling techniques to validate the accuracy and sensitivity of each one of these methods of source localization. The abilities of the techniques were tested by comparing the localization error, focal width, false positive ratios while detecting already known location of neural activity generators under varying signal to noise ratios and depths of sources from cortical surface. Secondly, we performed source localization on empricial EEG data collected from human participants while they listened to rhythmic tone stimuli binaurally. Importantly, we found a less-distributed activation map is generated by LCMV and DICS when compared to eLORETA. However, control of false positives is much superior in eLORETA especially while using realistic distributed dipole scenarios. We also highlight the strengths and drawbacks of eLORETA, LCMV and DICS following a comprehensive analysis of simulated and empirical EEG data.

neuroscience↗

bioRxiv2018

Multiscale dynamic mean field (MDMF) model to relate resting state brain dynamics with local cortical excitatory-inhibitory neurotransmitter homeostasis in health and disease.

Previous neuro-computational studies have established the connection of spontaneous resting-state brain activity with "large-scale" neuronal ensembles using dynamic mean field approach and showed the impact of local excitatory-inhibitory (E-I) balance in sculpting dynamical patterns. Here, we argue that whole brain models that link multiple scales of physiological organization namely brain metabolism that governs synaptic concentrations of gamma-aminobutyric acid (GABA) and glutamate on one hand and neural field dynamics that operate on the macroscopic scale. The multiscale dynamic mean field (MDMF) model captures the synaptic gating dynamics over a cortical macrocolumn as a function of neurotransmitter kinetics. Multiple MDMF units were placed in brain locations guided by an anatomical parcellation and connected by tractography data from diffusion tensor imaging. The resulting whole-brain model generates the resting-state functional connectivity and also reveal that optimal configurations of glutamate and GABA captures the dynamic working point of the brain, that is the state of maximum metsatability as observed in BOLD signals. To demonstrate test-retest reliability we validate the observation that healthy resting brain dynamics is governed by optimal glutamate-GABA configurations using two different brain parcellations for model set-up. Furthermore, graph theoretical measures of segregation (modularity and clustering coefficient) and integration (global efficiency and characteristic path length) on the functional connectivity generated from healthy and pathological brain network studies could be explained by the MDMF model. In conclusion, the MDMF model could relate the various scales of observations from neurotransmitter concentrations to dynamics of synaptic gating to whole-brain resting-state network topology in health and disease.

neuroscience↗

bioRxiv2018

Kipoi: accelerating the community exchange and reuse of predictive models for genomics

Advanced machine learning models applied to large-scale genomics datasets hold the promise to be major drivers for genome science. Once trained, such models can serve as a tool to probe the relationships between data modalities, including the effect of genetic variants on phenotype. However, lack of standardization and limited accessibility of trained models have hampered their impact in practice. To address this, we present Kipoi, a collaborative initiative to define standards and to foster reuse of trained models in genomics. Already, the Kipoi repository contains over 2,000 trained models that cover canonical prediction tasks in transcriptional and post-transcriptional gene regulation. The Kipoi model standard grants automated software installation and provides unified interfaces to apply and interpret models. We illustrate Kipoi through canonical use cases, including model benchmarking, transfer learning, variant effect prediction, and building new models from existing ones. By providing a unified framework to archive, share, access, use, and build on models developed by the community, Kipoi will foster the dissemination and use of machine learning models in genomics.

bioinformatics↗

bioRxiv2018

Quantitative assessment of cell population diversity in single-cell landscapes

Single-cell RNA-sequencing (scRNA-seq) has become a powerful tool for the systematic investigation of cellular diversity. As a number of computational tools have been developed to identify and visualize cell populations within a single scRNA-seq dataset, there is a need for methods to quantitatively and statistically define proportional shifts in cell population structures across datasets, such expansion or shrinkage, or emergence or disappearance of cell populations. Here we present sc-UniFrac, a framework to statistically quantify compositional diversity in cell populations between single-cell transcriptome landscapes. sc-UniFrac enables sensitive and robust quantification in simulated and experimental datasets in terms of both population identity and quantity. We have demonstrated the utility of sc-UniFrac in multiple applications, including assessment of biological and technical replicates, classification of tissue phenotypes, identification and definition of altered cell populations, and benchmarking batch correction tools. sc-UniFrac provides a framework for quantifying diversity or alterations in cell populations across conditions, and has broad utility for gaining insight on how cell populations respond to perturbations.

bioinformatics↗

bioRxiv2018

Identification and design of vinyl sulfone inhibitors against Cryptopain1, which is a cysteine protease from cryptosporidiosis causingCryptosporidium parvum

Cryptosporidiosis, a disease marked by diarrhea in adults and stunted growth in children, is associated with the unicellular protozoan pathogen Cryptosporidium; often the species parvum. Cryptopain-1, a cysteine protease characterized in the genome of Cryptosporidium parvum, had been earlier shown to be inhibited by a vinyl sulfone compound called K11777 (or K-777). Cysteine proteases have long been established as valid drug targets, which can be covalently and selectively inhibited by vinyl sulfones. This computational study was initiated to identify purchasable vinyl sulfone compounds, which could possibly inhibit cryptopain-1 with higher efficacy than K11777. Docking simulations screened a number of such possibly better inhibitors. The work was furthered to probe the enzymatic pocket of cryptopain-1, through in-silico mutations, to derive a map of receptor-ligand interactions in the docked complexes. The idea was to provide crucial clues to aid the design of inhibitors, which would be able to bind the protease well by making favorable interactions with important residues of the enzyme. The analyses dictated placement of ligands towards the front of the enzymatic cleft, and disfavored interactions deep within. The S1 and S2 subsites of the enzyme preferred to remain occupied by polar ligand subgroups. Reasonably distanced ring systems and polar backbones of ligands were desired across the cleft. Large as well as inflexible subgroups were not tolerated. Double ringed systems such as substituted napthalene, especially in S1, were exceptions though. The S2 subsite, which is typically a specificity determinant in papain (C1) family cysteine proteases such as cathepsin L-like cryptopain-1, can possibly accommodate polar and hydrophobic ligand subgroups alike.

bioinformatics↗

bioRxiv2018

Japanese Encephalitis Virus Infected Microglial Cells Secrete Exosomes Containing let-7a/b that Facilitate Neuronal Damage via Caspase Activation

Extracellular microRNAs (miRNAs) are essential for the cell to cell communication in the healthy and diseased brain. MicroRNAs released from the activated microglia upon neurotropic virus infection may exacerbate CNS damage. Here, we identified let-7a and let-7b (let-7a/b) as the overexpressed miRNAs in Japanese Encephalitis virus (JEV) infected microglia and assessed their role in JEV pathogenesis. We measured the let-7a/b expressions in JEV infected post-mortem human brains, mice brains and in mouse microglial N9 cells by the qRT-PCR and in situ hybridization assay. The interaction between let-7a/b and NOTCH signaling pathway further examined in Toll-like receptor 7 knockdown (TLR7 KD) mice to assess the functions. Exosomes released from JEV infected or let-7a/b mimic transfected N9, and HEK-293 cells were isolated and evaluated their function. We observed an upregulation of let-7a/b in the infected brains as well as in microglia. Knockdown of TLR7 or Inhibition of let-7a/b suppressed the JEV induced NOTCH activation possibly via NF-{kappa}B dependent manner and subsequently, attenuated JEV induced TNF production in microglial cells. Further, exosomes secreted from JEV-infected microglial cells specifically contained let-7a/b. Exosomes overexpressed with let-7a/b were injected into BALB/c mice as well as co-incubated with mouse neuronal (Neuro2a) cells, or primary cortical neuron resulted in caspase activation leading to neuronal damage in the brain. Thus, our results provide evidence for the multifaceted role of let-7a/b miRNAs and unravel the exosomes mediated mechanism for JEV induced pathogenesis.

neuroscience↗

bioRxiv2018

Neurodynamic explanation of inter-individual and inter-trial variability in cross-modal perception

A widely used experimental design in multisensory integration is the McGurk paradigm that entail illusory (cross-modal) perception of speech sounds when presented with incongruent audio-visual (AV) stimuli. However, the distribution of responses across trials and individuals is heterogeneous and not necessarily everyone in a given group of individuals perceives the effect. Nonetheless, existing studies in the field primarily focus on addressing the correlation between subjective behavior and cortical activations to reveal the neuronal mechanisms underlying the perception of McGurk effect, typically in the \"frequent perceivers\". Additionally, a solely neuroimaging approach does not provide mechanistic explanation for the observed inter-trial or inter-individual heterogeneity. In the current study we employ high density electroencephalogram (EEG) recordings in a group of 25 human subjects that allow us to distinguish \"frequent perceivers\" from \"rare perceivers\" using behavioral responses as well as from the perspective of large-scale brain functional connectivity (FC). Using global coherence as a measure of large-scale FC, we find that alpha band coherence, a distinctive feature in frequent perceivers is absent in the rare perceivers. Secondly, a decrease in alpha band coherence and increase in gamma band coherence occur during illusory perception trials in both frequent and rare perceivers. Source analysis followed up with source time series reconstructions reveals a large scale network of brain areas involving frontal, temporal and parietal areas that are involved in network level processing of cross-modal perception. Finally, we demonstrate that how a biophysically realistic computational model representing the interaction among key neuronal systems (visual, auditory and multisensory cortical regions) can explain the empirical observations. Each system involves a group of excitatory and inhibitory Hindmarsh Rose neurons that are coupled amongst each other. Large-scale FC between areas is conceptualized using coupling functions and the identity of a specific system, e.g., visual/ auditory/ multisensory is chosen using empirical estimates of the time-scale of information processing in these systems. The model predicts that the disappearance of alpha band coherence observed in rare perceivers stems from a negligible direct A-V (audio-visual) coupling however, an increase in indirect interaction via multisensory node leads to enhanced gamma band and reduced alpha band coherences observed during illusory perception. Overall, we establish the mechanistic basis of large-scale FC patterns underlying cross-modal perception.

neuroscience↗

bioRxiv2017

A Synthetic Microbial Operational Amplifier

Synthetic biology has created oscillators, latches, logic gates, logarithmically linear circuits, and load drivers that have electronic analogs in living cells. The ubiquitous operational amplifier, which allows circuits to operate robustly and precisely has not been built with bio-molecular parts. As in electronics, a biological operational-amplifier could greatly improve the predictability of circuits despite noise and variability, a problem that all cellular circuits face. Here, we show how to create a synthetic 3-stage inducer-input operational amplifier with a differential transcription-factor stage, a CRISPR-based push-pull stage, and an enzymatic output stage with just 5 proteins including dCas9. Our Bio-OpAmp expands the toolkit of fundamental circuits available to bioengineers or biologists, and may shed insight into biological systems that require robust and precise molecular homeostasis and regulation.\n\nOne Sentence SummaryA synthetic bio-molecular operational amplifier that can enable robust, precise, and programmable homeostasis and regulation in living cells with just 5 protein parts is described.

synthetic biology↗

bioRxiv2017

Ectopic activation of the Spindle Assembly Checkpoint reveals its biochemical design and physiological operation

Switch-like activation of the Spindle Assembly Checkpoint (SAC) is critical for accurate chromosome segregation during cell division. To determine the mechanisms that implement it, we engineered an ectopic, kinetochore-independent SAC activator, the \"eSAC\". The eSAC stimulates the SAC signaling cascade by artificially dimerizing the Mps1 kinase domain and a cytosolic KNL1 phosphodomain, the signaling scaffold in the kinetochore. Quantitative analyses and mathematical modeling of the eSAC reveal that the recruitment of multiple SAC proteins by the KNL1 phosphodomain stimulates synergistic signaling, which enables a small number of KNL1 molecules produce a disproportionately strong anaphase-inhibitory signal. However, when multiple KNL1 molecules signal concurrently, they compete for a limited cellular pool of SAC proteins. This frustrates synergistic signaling and modulates signal output. Together, these mechanisms institute automatic gain control - inverse, non-linear scaling between the signal output per kinetochore and the unattached kinetochore number, and thus enact the SAC switch.

cell biology↗

bioRxiv2017

Cysteine Proteases Of Hookworm Necator Americanus As Virulence Factors And Implications For Future Drug Design: A Bioinformatics-Based Study

Human hookworm Necator Americanus (NA) causes iron deficiency anemia, as the parasite ingests blood from the gastrointestinal tract of its human host. This bioinformatics-based study focuses on eight of the cathepsin B-like cysteine proteases (CPs) of the worm to explore their pathogenic potential. CP1 - CP6, which harbored the active site cysteine residue for enzymatic activity, were relevantly observed to have N-terminal signal peptide for extracellular localization. The secretory CPs could be releasing indigenous worm heparin at the host-pathogen interface for anticoagulation purposes. CP2 and CP3 showed a novel hemoglobinase motif that could be a prerequisite for hemoglobin degradation. CP1 and CP6 shared similar enzymatic-pocket features with cathepsin B and cruzain that cleave high molecular weight kininogen for blood-thinning activity. CP1, CP2, CP3, CP5 and CP6 were predicted to bind heparin, at their C terminal domain, like human cathepsin B and cruzain non-covalently bind heparin to enhance their activity. NA CPs action in concert with heparin, have implications for anti-heparin and heparin analog design against hookworm infection.

bioinformatics↗