Biology subjects

Banerjee, A.

Publications and source records attributed to Banerjee, A..

At least 127 records · Page 7Linked to original sources

bioRxiv2022

Ancient midbrain inhibitory neurons control selective spatial attention

To behave adaptively in complex environments, animals must selectively process the most important information in space while ignoring distractors. Contrary to the dominant cortico-centric view, we report that an evolutionarily old group of inhibitory neurons in the brainstem, called PLTi, is critical for this function of selective spatial attention. In freely behaving mice performing a human-like spatial attention task, we found that bilateral silencing of PLTi severely disrupted target selection without causing perceptual or motor impairments. PLTis effects depended necessarily on goal-relevant, rather than just physical salience-based signals, together revealing it as a dedicated brain site for priority-driven attentional target selection. PLTis core computational function is its explicit implementation of the abstract cognitive decision boundary separating target from distracters: it controlled the accuracy and categorical precision of this decision boundary, doing so by shaping neural representations of competing stimuli in the superior colliculus, a major sensorimotor hub. PLTi may, therefore, be a conserved brainstem engine across vertebrates for winner-take-all-like spatial decisions in goal-driven behavior.

neuroscience↗

bioRxiv2022

Antisense, but not sense, repeat expanded RNAs activate PKR/eIF2α-dependent integrated stress response in C9orf72 FTD/ALS

GGGGCC (G4C2) hexanucleotide repeat expansion in the C9orf72 gene is the most common genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). The repeat is bidirectionally transcribed and confers gain of toxicity. However, the underlying toxic species is debated, and it is not clear whether antisense CCCCGG (C4G2) repeat expanded RNAs contribute to disease pathogenesis. Our study shows that C9orf72 (C4G2) antisense repeat expanded RNAs trigger the activation of the PKR/eIF2-dependent integrated stress response independent of dipeptide repeat proteins that are produced through repeat-associated non-AUG initiated translation, leading to global translation inhibition and stress granule formation. Increased phosphorylation of PKR/eIF2 is also observed in the frontal cortex of C9orf72 FTD/ALS patients. Finally, only antisense (C4G2), but not sense (G4C2), repeat expanded RNAs can activate the PKR/eIF2 pathway. These results provide a mechanism by which antisense repeat expanded RNAs elicit neuronal toxicity in FTD/ALS caused by C9orf72 repeat expansions.

neuroscience↗

bioRxiv2022

A novel approach to single cell analysis to reveal intrinsic differences in immune marker expression in unstimulated macrophages from BALB/c and C57BL/6 mouse strains

Macrophages are cells of the innate immune system that provide the first line of defense against pathogens. Their functional and morphological heterogeneity is well known, though the origin of this heterogeneity is still debated. Furthermore, while mouse strains differ in the type of immune responses that they mount to individual pathogens, the range of gene expression variation among their macrophages in the absence of a specific stimulus is not known. By applying single cell RNA sequencing we here reveal the gene expression variation in pre-stimulation macrophage populations from specific pathogen-free BALB/c and C57BL/6 mice, two mouse strains that give prototypical Th2 and Th1-biased immune responses, directed towards extracellular or intracellular pathogens, respectively. We show that intrinsic differences between the macrophages of these two strains are detectable before any specific stimulation and we place the gene expression profile of these cells within the range of variation that is measured upon in vitro stimulation with pro-inflammatory lipopolysaccharide (LPS) and interferon {gamma} (IFN), or anti-inflammatory IL-4. We find that C57BL/6 mice show stronger evidence of macrophage polarization than BALB/c mice, which could explain their resistance to pathogens such as Leishmania. Our computational methods for analyzing single cell RNA sequencing data, controlling for common sources of stochastic variation, can be more generally adopted to uncover biological variation between cell populations.

systems biology↗

bioRxiv2022

Evolution of Delta variant by non-Spike signature co-appearing mutations: trailblazer of COVID-19 disease outcome

The high transmissibility and infectivity of a SARS-CoV-2 variant is usually ascribed to the Spike mutations, while emerging non-spike mutations might be a serious threat to the current Spike-recombinant vaccines. In addition to mutations in structural Spike glycoprotein, rapid accumulation of mutations across non-structural genes is leading to continuous virus evolution, altering its pathogenicity. We performed whole genome sequencing of SARS-CoV-2 positive samples collected from different clinical groups from eastern India, during the second pandemic wave (April-May, 2021). In addition to the several common spike mutations in Delta variant, two mutually explicit signature constellations of non-spike co-appearing mutations were identified, driving symptomatic and asymptomatic infections. We attempted to correlate these unique signatures of non-Spike co-appearing mutations to COVID-19 disease outcome. Results revealed that the Delta strains harboring a unique constellation of 9 non-spike co-appearing mutations could be the wheeler and dealer of symptomatic infection, even post vaccination. The strains predominantly driving asymptomatic infection possessed 7 non-spike co-appearing mutations, which were mutually exclusive in contrast to the set of mutations causing symptomatic disease. Phylodynamic analysis depicted high probability of emergence of these unique sub-clusters within India, with subsequent spread worldwide. Interestingly, some mutations of this signature were selected in Omicron and IHU variants, which suggest that gradual accumulation of such co-existing mutations may lead to emergence of more "vaccine-evading variants" in future. Hence, unfaltering genome sequencing and tracking of non-Spike mutations might be significant in formulation of any future vaccines against emerging SARS-CoV-2 variants that might evade the current vaccine-induced immunity.

genomics↗

bioRxiv2022

Concurrent separation of phase-locked and non-phase-locked activity

Brain dynamics recorded via electroencephalography (EEG) is conceptualized as a sum of two components, "phase-locked" and "non-phase-locked" to the stimulus. Both activities are understood to be stemming from different neuronal mechanisms and hence accurately characterizing them is of immense importance in neuroscientific studies. Here, we discuss the drawbacks of currently used methods to separate the phase-locked and non-phase-locked activity and propose a new method that decomposes the two components simultaneously. First, we demonstrate that single-trial separation of phase-locked and non-phase-locked power is an ill-posed problem. Second, using simulations where ground truth validation is possible, we elucidate the drawbacks of the widely used averaging method and efficacy of the proposed concurrent phaser method (CPM). Using two experimental datasets, audio oddball EEG data and auditory steady-state responses (ASSR) we show how the empirical signal-to-noise estimates warrant the usage of CPM to separate phase-locked and non-phase-locked activity.

neuroscience↗

bioRxiv2022

Genome-wide analysis of PTR/POT transporters in Candida species and their functional characterization in the newly emerged pathogen Candida auris

The PTR or proton-dependent oligopeptide transporter (POT) family exploits the inwardly directed proton motive force to facilitate the cellular uptake of di- and tripeptides. Interestingly, representatives from the family have shown efficacy in delivering peptide-based antifungal derivatives in certain Candida species. Given the increased incidences of fungal infections by Candida species and the associated escalating orders of resistance against frontline antifungals, peptide derivatives are attractive therapeutic options. In that direction, the identification and characterization of PTR transporters serve as an essential first step in the translation of peptide-based antifungals as next-gen therapeutics. Herein, we present a genome-wide inventory of the PTR transporters in five prominent Candida species. Our study identifies 2 PTR transporters each in C. albicans and C. dubliniensis, 1 in C. glabrata, 4 in C. parapsilosis, and 3 in C. auris. Notably, despite all representatives retaining the conserved features seen in the PTR family, there exist two distinct classes of PTR transporters that differ in terms of their sequence identities and membrane topology. Further, we also evaluated the contribution of each PTR protein of the newly emerged multidrug-resistant C. auris in di-/tripeptide uptake. Notably, deletion of the PTR transporters encoded by BNJ08_003830 and BNJ08_005124 led to a marked reduction in the transport capabilities of several tested di-/tripeptides. Besides, BNJ08_005124 deletion also resulted in increased resistance towards the peptide-nucleoside drug Nikkomycin Z, pointing towards its predominant role in the uptake mechanism. Altogether, the study provides an important template for future structure-function investigations of PTR transporters in Candida species.

microbiology↗

bioRxiv2022

Structural basis for ultrapotent neutralization of human metapneumovirus

Human metapneumovirus (hMPV) is a leading cause of morbidity and hospitalization among children worldwide, however, no vaccines or therapeutics are currently available for hMPV disease prevention and treatment. The hMPV fusion (F) protein is the sole target of neutralizing antibodies. To map the immunodominant epitopes on the hMPV F protein, we isolated a panel of human monoclonal antibodies (mAbs), and the mAbs were assessed for binding avidity, neutralization potency, and epitope specificity. We found the majority of the mAbs target diverse epitopes on the hMPV F protein, and we discovered multiple mAb binding approaches for antigenic site III. The most potent mAb, MPV467, which had picomolar potency, was examined in prophylactic and therapeutic mouse challenge studies, and MPV467 limited virus replication in mouse lungs when administered 24 hrs before or 72 hrs after viral infection. We determined the structure of MPV467 in complex with the hMPV F protein using cryo-electron microscopy to a resolution of 3.3 [A], which revealed a complex novel prefusion-specific epitope overlapping antigenic sites II and V on a single protomer. Overall, our data reveal new insights into the immunodominant antigenic epitopes on the hMPV F protein, identify a new mAb therapy for hMPV F disease prevention and treatment, and provide the discovery of a unique pre-fusion-specific epitope on the hMPV F protein.

immunology↗

bioRxiv2022

Genomic landscape of the DHA1 family in the newly emerged pathogen Candida auris and mapping substrate repertoire of the prominent member CauMdr1

The last decade has witnessed the rise of extremely threatening healthcare-associated multidrug resistant non-albicans Candida (NAC) species, Candida auris. Thus, understanding the molecular basis of antifungal resistance has emerged as the single most important goal amongst the research community. Since besides target alterations, efflux mechanisms contribute maximally to antifungal resistance, it is imperative to investigate their contributions in this pathogen. Of note, within the Major Facilitator Superfamily (MFS) of efflux pumps, Drug/H+ antiporter family 1 (DHA1) has been established as a predominant contributor towards xenobiotic efflux. Our study provides a complete landscape of DHA1 transporters encoded in the genome of C. auris. This study identifies 14 DHA1 transporters encoded in the genome of the pathogen. We also construct deletion and heterologous overexpression strains for the most important DHA1 drug transporter, viz., CauMdr1 to map the spectrum of its substrates. While the knockout strain did not show any significant changes in the resistance patterns against the majority of the tested substrates, the ortholog when overexpressed in a minimal background S. cerevisiae strain, AD1-8u-, showed significant enhancement in the Minimum inhibitory concentrations (MICs) against a large panel of antifungal molecules. Altogether, the present study provides a comprehensive template for investigating the role of DHA1 members of C. auris in antifungal resistance mechanisms.

microbiology↗

bioRxiv2022

Potent Neutralization of Omicron and other SARS-CoV-2 Variants of Concern by Biparatopic Human VH Domains

The emergence of SARS-CoV-2 variants of concern (VOCs) requires the development of next-generation biologics that are effective against a variety of strains of the virus. Herein, we characterize a human VH domain, F6, which we generated by sequentially panning large phage displayed VH libraries against receptor binding domains (RBDs) containing VOC mutations. Cryo-EM analyses reveal that F6 has a unique binding mode that spans a broad surface of the RBD and involves the antibody framework region. Attachment of an Fc region to a fusion of F6 and ab8, a previously characterized VH domain, resulted in a construct (F6-ab8-Fc) that neutralized Omicron pseudoviruses with a half-maximal neutralizing concentration (IC50) of 4.8 nM in vitro. Additionally, prophylactic treatment using F6-ab8-Fc reduced live Beta (B.1.351) variant viral titers in the lungs of a mouse model. Our results provide a new potential therapeutic against SARS-CoV-2 VOCs - including the recently emerged Omicron variant - and highlight a vulnerable epitope within the spike protein RBD that may be exploited to achieve broad protection against circulating variants.

immunology↗

bioRxiv2022

Prediction error processing speeds up in presence of multisensory contexts

Prediction errors in the brain are indexed by two event-related potentials - MMN and P300, which are elicited upon violation of regularity in the occurrence of repetitive stimuli. While MMN reflects the brains ability to perform automatic comparisons between consecutive stimuli and provides an electrophysiological index of sensory error detection, P300 is associated with cognitive processes such as update in working memory. Till date, there has been extensive research on the roles of MMN and P300 individually, because of their potential to be used as clinical markers of consciousness and attention, respectively. However, the relationship between these two ERPs, specifically in terms of their underlying cortical generators, in context of prediction error propagation along the hierarchical brain across multiple modalities is an open question. Our objective in this article is two-fold. First, we reconfirm previous reports regarding the generators of MMN and P300 in sensor space through source-space analysis using an accurate individual subject level co-registration of MRI and EEG data collected from healthy humans. We demonstrate that in multisensory environments, MMN and P300 markers represent "modality-specific" and "modality-independent" information processing, respectively. Advancing an earlier understanding that multisensory contexts speed up early sensory processing, our study reveals that this temporal facilitation extends to even the later components of prediction error processing, using custom-designed experiments that allow comparisons across different modality combinations. Such knowledge can be of immense value in clinical research for determining the stages of various treatments in aging, schizophrenia and depression, and their efficacy on cognitive function.

neuroscience↗

bioRxiv2022

Human orbitofrontal cortex signals decision outcomes to sensory cortex during behavioural adaptations

The ability to respond flexibly to an ever-changing environment relies on the orbitofrontal cortex (OFC). How the OFC associates sensory information with predicted outcomes to enable flexible sensory learning in humans remains elusive. Here, we combine a probabilistic tactile reversal learning task with functional magnetic resonance imaging (fMRI) to investigate how lateral OFC (lOFC) interacts with the primary somatosensory cortex (S1) to guide flexible tactile learning in humans. fMRI results reveal that lOFC and S1 exhibit distinct task-dependent engagement: while the lOFC responds transiently to unexpected outcomes immediately following reversals, S1 is persistently engaged during re-learning. Unlike the contralateral stimulus-responsive S1, activity in ipsilateral S1 mirrors the outcomes of behavior during re-learning, which is closely related to top-down signals from lOFC. These findings suggest that lOFC contributes to teaching signals to dynamically update representations in sensory areas, which implements computations critical for adaptive behavior.

neuroscience↗

bioRxiv2022

Characterizing Variability of Audiovisual Speech Perception Based on Periodic and Aperiodic Features of Prestimulus Brain Activity

Studies have reported that prestimulus brain oscillations guide perceptual experiences during AV speech perception. However, what features of these prestimulus activity drives perception remains unknown. In this electroencephalography (EEG) study, we investigated the relationship between prestimulus periodic oscillations and aperiodic components with subsequent perception of the McGurk illusion at single-trial levels. Using logistic mixed-effect models, we determined which spectral features from different sensor regions predicted response to the illusory perception. We found that lower alpha (8-12 Hz) and beta (15-30 Hz) band oscillations over parieto-occipital sensors predicted illusion perception. We also found lower aperiodic offset values over parieto-temporal sensors, and lower global effect of exponent over the scalp, that predicted the response to McGurk illusion. We conclude that the predominant source of the prestimulus oscillatory state is aperiodic background activity, and that variations in these arrhythmic components account for inter-trial and inter-individual variability in perception of the McGurk illusion.

neuroscience↗

bioRxiv2022

Immunogenicity of convalescent and vaccinated sera against clinical isolates of ancestral SARS-CoV-2, beta, delta, and omicron variants

The omicron variant of concern (VOC) of SARS-CoV-2 was first reported in November 2021 in Botswana and South Africa. Omicron has evolved multiple mutations within the spike protein and the receptor binding domain (RBD), raising concerns of increased antibody evasion. Here, we isolated infectious omicron from a clinical specimen obtained in Canada. The neutralizing activity of sera from 65 coronavirus disease (COVID-19) vaccine recipients and convalescent individuals against clinical isolates of ancestral SARS-CoV-2, beta, delta, and omicron VOCs was assessed. Convalescent sera from unvaccinated individuals infected by the ancestral virus during the first wave of COVID-19 in Canada (July, 2020) demonstrated reduced neutralization against beta and omicron VOCs. Convalescent sera from unvaccinated individuals infected by the delta variant (May-June, 2021) neutralized omicron to significantly lower levels compared to the delta variant. Sera from individuals that received three doses of the Pfizer or Moderna vaccines demonstrated reduced neutralization of the omicron variant relative to ancestral SARS-CoV-2. Sera from individuals that were naturally infected with ancestral SARS-CoV-2 and subsequently received two doses of the Pfizer vaccine induced significantly higher neutralizing antibody levels against ancestral virus and all VOCs. Importantly, infection alone, either with ancestral SARS-CoV-2 or the delta variant was not sufficient to induce high neutralizing antibody titers against omicron. This data will inform current booster vaccination strategies, and we highlight the need for additional studies to identify longevity of immunity against SARS-CoV-2 and optimal neutralizing antibody levels that are necessary to prevent infection and/or severe COVID-19.

immunology↗

bioRxiv2022

RG203KR mutations in SARS-CoV-2 Nucleocapsid: Assessing the impact using Virus-like particle model system

The emergence and evolution of SARS-CoV-2 is characterized by the occurrence of diverse sets of mutations that affect virus characteristics, including transmissibility and antigenicity. Recent studies have focused mostly on Spike protein mutations; however, SARS-CoV-2 variants of interest (VoI) or concern (VoC) contain significant mutations in the nucleocapsid protein as well. To study the relevance of the mutations at the virion level, recombinant baculovirus expression system based VLPs were generated for the prototype Wuhan sequence along with Spike mutants like D614G, G1124V and the significant RG203KR mutation in Nucleocapsid. All the four structural proteins assembled in a particle wherein the morphology and size of the particle confirmed by TEM closely resembles the native virion. The VLP harbouring RG203KR mutations in nucleocapsid exhibited augmentation of humoral immune responses and enhanced neutralization by the immunized mice sera. Results demonstrate a non-infectious platform to quickly assess the implication of mutations in structural proteins of the emerging variant.

microbiology↗

bioRxiv2021

Emotion Dynamics as Hierarchical Bayesian Inference in Time

What fundamental property of our environment would be most valuable and optimal in characterizing the emotional dynamics we experience in our daily life? Empirical work has shown that an accurate estimation of uncertainty is necessary for our optimal perception, learning, and decision-making. However, the role of this uncertainty in governing our affective dynamics remains unexplored. Using Bayesian encoding, decoding and computational modelling, we show that emotional experiences naturally arise due to ongoing uncertainty estimations in a hierarchical neural architecture. This hierarchical organization involves a number of prefrontal sub-regions, with the lateral orbitofrontal cortex having the highest representational complexity of uncertainty. Crucially, this representational complexity, was sensitive to temporal fluctuations in uncertainty and was predictive of participants predisposition to anxiety. Furthermore, the temporal dynamics of uncertainty revealed a distinct functional double dissociation within the OFC. Specifically, the medial OFC showed higher connectivity with the DMN, while the lateral OFC with that of the FPN in response to the evolving affect. Finally, we uncovered a temporally predictive code updating individuals beliefs swiftly in the face of fluctuating uncertainty in the lateral OFC. A biologically relevant and computationally crucial parameter in theories of brain function, we extend uncertainty to be a defining component of complex emotions.

neuroscience↗

bioRxiv2021

How synchrony and metastable network dynamics are affected in fast and slow timescales with aging: Implication for Cognition

Both healthy and pathological aging exhibits gradual deterioration of structure but in-terestingly in healthy aging adults often maintains a high level of cognitive performance in a variety of cognitively demanding task till late age. What are the relevant network measures that could possibly track these dynamic changes which may be critically relevant for maintenance of cognitive functions through lifespan and how does these measures affected by the specific alterations in underlying anatomical connectivity till day remains an open question. In this work, we propose that whole-brain computational models are required to test the hypothesis that aging affects the brain network dynamics through two highly relevant network measures synchrony and metastability. Since aging entails complex processes involving multiple timescales we test the additional hypothesis that whether these two network measures remain invariant or exhibit different behavior in the fast and slow timescales respectively. The altered global synchrony and metastability with aging can be related to shifts in the dynamic working point of the system based on biophysical parameters e.g., time delay, and inter-areal coupling constrained by the underlying structural connectivity matrix.Using diffusion tensor imaging (DTI) data, we estimate structural connectivity (SC) of individual group of participants and obtain network level synchrony, metastability indexing network dynamics from resting state functional MRI data for both young and elderly participants in the age range of 18-89 years. Subsequently, we simulate a whole-brain Kuramoto model of coupled oscillators with appropriate conduction delay and interareal coupling strength to test the hypothesis of shifting of dynamic working point with age-associated alteration in network dynamics in both neural and ultraslow BOLD signal time scales. Specifically, we investigate the age-associated difference in metastable brain dynamics across large-scale neurocognitive brain networks e.g., salience network (SN), default mode network (DMN), and central executive network (CEN) to test spatio-temporal changes in default to executive coupling hypothesis with age. Interestingly, we find that the metastability of the SN increases substantially with age, whereas the metastability of the CEN and DMN networks do not substantially vary with age suggesting a clear role of conduction delay and global coupling in mediating altered dynamics in these networks. Moreover, our finding suggests that the metastability changes from slow to fast timescales confirming previous findings that variability of brain signals relates differently in slower and faster time scales with aging. However, synchrony remains invariant network measure across timescales and agnostic to the filtering of fast signals. Finally, we demonstrate both numerically and analytically longrange anatomical connections as oppose to shot-range or mid-range connection alterations is responsible for the overall neural difference in large-scale brain network dynamics captured by the network measure metastability. In summary, we propose a theoretical framework providing a systematic account of tracking age-associated variability and synchrony at multiple time scales across lifespan which may pave the way for developing dynamical theories of cognitive aging.

neuroscience↗

bioRxiv2021

A scale-invariant perturbative approach to study information communication in dynamic brain networks

How communication among neuronal ensembles shapes functional brain dynamics at the large scale is a question of fundamental importance to Neuroscience. To date, researchers have primarily relied on two alternative ways to address this issue 1) in-silico neurodynamical modelling of functional brain dynamics by choosing biophysically inspired non-linear systems, interacting via a connection topology driven by empirical data; and 2) identifying topological measures to quantify network structure and studying them in tandem with functional metrics of interest, e.g. co-variation of time series in brain regions from fast (EEG/ MEG) and slow (fMRI) timescales. While the modelling approaches are limited in scope to only scales of the nervous system for which dynamical models are well defined, the latter approach does not take into account how the network architecture and intrinsic regional node dynamics contribute together to inter-regional communication in the brain. Thus, developing a generalized scale-invariant measure of interaction between network topology and constituent regional dynamics can potentially resolve how transmission of perturbations in brain networks alter function e.g. by neuropathologies, or the intervention strategies designed to mitigate them. In this work, we introduce a recently developed theoretical perturbative framework in network science into a neuroscientific framework, to conceptualize the interaction of regional dynamics and network architecture in a quantifiable manner. This framework further provides insights into the information communication contributions of putative regions and sub-networks in the brain, irrespective of the observational scale of the phenomenon (firing rates to BOLD fMRI time series). The proposed approach can directly quantify network-dynamical interactions without reliance on a specific class of models or response characteristics: linear/nonlinear. By simply gauging the asymmetries in responses to perturbations, we obtain insights into the significance of regions in communication and their influence over the rest of the network. Moreover, coupling perturbations with functional lesions can also answer which regions contribute the most to information spread: a quantity termed Flow. The simplicity of the proposed technique allows translation to an experimental setting where the response asymmetries and flow can inversely act as a window into the dynamics of regions. For proof-of-concept, we apply the perturbative approach on in-silico data generated for human resting state network dynamics, using different established dynamical models that mimic empirical observations. We also apply the perturbation approach at the level of large scale Resting State Networks (RSNs) to gauge the range of network-dynamical interactions in mediating information flow across brain regions.

neuroscience↗

bioRxiv2021

Preservation of neural synchrony at peak alpha frequency via global synaptic scaling compensates for white matter structural decline over adult lifespan

We propose that preservation of functional integration, estimated from measures of neural synchrony, is a key neurocompensatory mechanism associated with healthy human ageing. To support this proposal, we demonstrate how phase-locking at peak alpha frequency from Magnetoencephalography (MEG) data is invariant over lifespan in a large cohort of human participants, aged 18-88 years. Using empirically derived connection topologies from diffusion tensor imaging (DTI) data, we create an in-silico model of whole-brain alpha dynamics. We show that enhancing inter-areal coupling can cancel the effect of increased axonal transmission delay associated with age-related degeneration of white matter tracts and thus, preserve neural synchrony. Together with analytical solutions for non-biological all-to-all connection scenarios, our model establishes the theoretical principles by which frequency slowing with age, frequently observed in the alpha band in diverse populations, can be viewed as an epiphenomenon of the underlying neurocompensatory mechanisms.

neuroscience↗