Biology subjects

Talwar, S.

Publications and source records attributed to Talwar, S..

11 recordsLinked to original sources

bioRxiv2025

Cholesterol-mediated activation of VapC12 toxin modulates growth and drug susceptibility in Mycobacterium tuberculosis

Tuberculosis eradication efforts are severely hampered by antimicrobial resistance (AMR). We have previously reported that VapBC12 TA system in Mycobacterium tuberculosis (M. tuberculosis) regulates both disease and antibiotic persistence in tuberculosis. In this study, we developed a mechanistic understanding of the VapBC12-dependent modulation of growth and antibiotic susceptibility in M. tuberculosis. We identified a unique Cholesterol Recognition Amino acid Consensus (CRAC) motif in VapC12 toxin and demonstrated that its heterologous expression induces toxicity in M. smegmatis. We have solved the crystal structure of VapB12 antitoxin at a 1.6A0 wavelength and using molecular modeling predicted the structure of TA complex. Structure-function analysis revealed specific residues critical for the assembly and activity of the VapBC12 TA system. Our study suggests that cholesterol activates the VapC12 toxin by competitively displacing its cognate antitoxin at the CRAC motif which consequently restricts the growth of M. tuberculosis. Finally, we demonstrated that chemical inhibition of VapC12 prevents growth restriction and potentiates activity of anti-TB drugs.

microbiology↗

bioRxiv2025

Two senses, one rhythm: Pre- and post-stimulus neural states predict perceived audio-visual synchrony

How does the brain integrate or segregate multiple sensory inputs? In our study, we used magnetoencephalography to comprehensively investigate local and network dynamics before and after the presentation of sequences of beeps and flashes that are sometimes perceived as synchronous or asynchronous. Frequency-tagging and spectral analysis revealed that under identical physical conditions, subjective perceptual fusion of multisensory signals elicits stronger evoked sensory responses in both visual and auditory cortices. Crucially, perceptual fusion is preceded by locally reduced pre-stimulus alpha activity, as well as enhanced functional connectivity between auditory and visual cortices within the pre-stimulus gamma activity. We also show that pre-stimulus neuronal states in the occipital cortex predict post-stimulus sensory responses to auditory sequences in the temporal cortex, but not the opposite. The current findings provide evidence that the perceptual fusion of multisensory events relate to a complex interplay between local and inter-sensory neuronal states before and after stimulus presentation. Significance StatementHow does the brain blend information from multiple sensory systems into one holistic perception? We developed a novel frequency-tagging paradigm in Magnetoencephalography (MEG) to robustly estimate the sensory responses to a series of flashes and beeps in early sensory areas, and to demonstrate how these responses are shaped by ongoing fluctuations in local, and long-range network activity. By combining the steady-state method with spectral, and functional connectivity analysis of ongoing oscillations in source space, the current study provides novel insights into the relationship between internal brain states and the way we perceive multisensory events.

neuroscience↗

bioRxiv2024

Modulation of all-trans retinoic acid by light and dopamine in the murine eye

PurposeAmbient light exposure is linked to myopia development in children and affects myopia susceptibility in animal models. Currently, it is unclear which signals mediate the effects of light on myopia. All-trans retinoic acid (atRA) and dopamine (DA) oppositely influence experimental myopia and may be involved in the retino-scleral signaling cascade underlying myopic eye growth. However, how ocular atRA responds to different lighting and whether atRA and DA interact remains unknown. MethodsDark-adapted C57BL/6J mice (29-31 days old) were exposed to Dim (1 lux), Mid (59 lux), or Bright (12,000 lux) ambient lighting for 5-60 minutes. Some mice were also systemically administered the DA precursor, LDOPA, or atRA prior to light exposure. After exposure, the retina and the back-of-the-eye (BOE) were collected and analyzed for levels of atRA, DA, and the DA metabolite, DOPAC. ResultsDA turnover (DOPAC/DA ratio) in the retina increased in magnitude after only five minutes of exposure to higher ambient luminance but was minimal in the BOE. In contrast, atRA levels in the retina and BOE significantly decreased with higher ambient luminance and longer duration exposure. Intriguingly, LDOPA-treated mice had a transient reduction in retinal atRA compared to saline-treated mice, whereas atRA treatment had no effect on ocular DA. ConclusionsOcular atRA was affected by the duration of exposure to different ambient lighting and retinal atRA levels decreased with increased DA. Overall, these data suggest specific interactions between ambient lighting, atRA, and DA that could have implications for the retino-scleral signaling cascade underlying myopic eye growth.

systems biology↗

bioRxiv2023

Hypothetical gene Rv0495c regulates redox homeostasis in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) has evolved sophisticated surveillance mechanisms to regulate and neutralize redox imbalances and associated lethal consequences. Failing this, the accumulated ROS induces toxicity by oxidizing a variety of biological molecules including proteins, nucleic acids and lipids. In the present study we identified Mtbs Rv0495c gene as an important regulator of oxidized cytosolic environment. Compared to wild type Mtb strain lacking the Rv0495c gene, {Delta}Rv0495c, had increased ROS and NAD+/NADH ratio creating a highly oxidized intracellular environment. {Delta}Rv0495c strain demonstrated slow growth phenotype under in vitro and ex-vivo growth conditions and demonstrated enhanced susceptibility to drugs, oxidative, nitrosative and hypoxic growth conditions. In addition, the increase in the superoxide radicals triggered a Fenton-like reaction rendering the {Delta}Rv0495c susceptible to free iron. The increase in the intracellular ROS levels of the {Delta}Rv0495c was further corroborated by an increase in the expression of proteins involved in antioxidant defense and enhanced ROS-mediated oxidation and degradation of mycobacterial lipids. This superoxide-induced lipid degradation resulted in altered colony morphology and loss of membrane integrity in the {Delta}Rv0495c. Surprisingly, despite showing a growth defect phenotype in an ex-vivo macrophage infection model, the absence of the Rv0495c gene in Mtb enhanced the pathogenicity and augmented the ability of the Mtb to grow inside the host. Gene expression analysis revealed a Rv0495c mediated immunomodulation of the host controls inflammation and helps creates a favorable niche for long-term survival of Mtb inside the host. In summary, the current study underscores the fact that the truce in the war between the host and the pathogen favors long-term disease persistence in tuberculosis. We believe targeting Rv0495c could potentially be explored as a strategy to potentiate the current anti-TB regimen.

microbiology↗

bioRxiv2022

Automatic brain categorization of discrete auditory emotion expressions

Seamlessly extracting emotional information from voices is crucial for efficient interpersonal communication. However, it remains unclear how the brain categorizes vocal expressions of emotion beyond the processing of their acoustic features. In our study, we developed a new approach combining electroencephalographic recordings (EEG) in humans with an oddball frequency tagging paradigm to automatically tag neural responses to specific emotion expressions. Participants were presented with a periodic stream of heterogeneous non-verbal emotional vocalizations belonging to five emotion categories (Anger, Disgust, Fear, Happiness, Sadness) at 2.5 Hz. Importantly, unbeknown to the participant, a specific emotion category appeared at an oddball presentation rate at 0.83 Hz that would elicit an additional response in the EEG spectrum only if the brain discriminates the target emotion category from other emotion categories and generalizes across heterogeneous exemplars of the target emotion category. Stimuli were matched across emotion categories for harmonicity-to-noise ratio, spectral center of gravity, pitch, envelope, and early auditory peripheral processing via the simulated output of the cochlea. Additionally, participants were presented with a scrambled version of the stimuli with identical spectral content and periodicity but disrupted intelligibility. We observed that in addition to the responses at the general presentation frequency (2.5 Hz) in both intact and scrambled sequences, a peak in the EEG spectrum at the oddball emotion presentation rate (0.83 Hz) and its harmonics emerged in the intact sequence only. The absence of response at the oddball frequency in the scrambled sequence in conjunction to our stimuli matching procedure suggests that the categorical brain response elicited by a specific emotion is at least partially independent from low-level acoustic features of the sounds. Further, different topographies were observed when fearful or happy sounds were presented as an oddball that supports the idea of different representations of distinct discrete emotions in the brain. Our paradigm revealed the ability of the brain to automatically categorize non-verbal vocal emotion expressions objectively (behavior-free), rapidly (in few minutes of recording time) and robustly (high signal-to-noise ratio), making it a useful tool to study vocal emotion processing and auditory categorization in general in populations where brain recordings are more challenging.

neuroscience↗

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↗

bioRxiv2021

A robust voice-selective response in the human brain as revealed by electrophysiological recordings and fast periodic auditory stimulation

Voices are arguably among the most relevant sounds in humans everyday life, and several studies have suggested the existence of voice-selective regions in the human brain. Despite two decades of research, defining the human brain regions supporting voice recognition remains challenging. Moreover, whether neural selectivity to voices is merely driven by acoustic properties specific to human voices (e.g. spectrogram, harmonicity), or whether it also reflects a higher-level categorization response is still under debate. Here, we objectively measured rapid automatic categorization responses to human voices with Fast Periodic Auditory Stimulation (FPAS) combined with electroencephalography (EEG). Participants were tested with stimulation sequences containing heterogeneous non-vocal sounds from different categories presented at 4 Hz (i.e., 4 stimuli/second), with vocal sounds appearing every 3 stimuli (1.333 Hz). A few minutes of stimulation are sufficient to elicit robust 1.333 Hz voice-selective focal brain responses over superior temporal regions of individual participants. This response is virtually absent for sequences using frequency-scrambled sounds, but is clearly observed when voices are presented among sounds from musical instruments matched for pitch and harmonicity-to-noise ratio. Overall, our FPAS paradigm demonstrates that the human brain seamlessly categorizes human voices when compared to other sounds including matched musical instruments and that voice-selective responses are at least partially independent from low-level acoustic features, making it a powerful and versatile tool to understand human auditory categorization in general. Significance statementVoices are arguably among the most relevant sounds we hear in our everyday life, and several studies have corroborated the existence of regions in the human brain that respond preferentially to voices. However, whether this preference is driven by specific acoustic properties of voices or if it rather reflects a higher-level categorization response to voices is still under debate. We propose a new approach to objectively identify rapid automatic voice-selective responses with frequency tagging and electroencephalographic recordings. In four minutes of recording only, we recorded robust voice-selective responses independent from low-level acoustic cues, making this approach highly promising for studying auditory perception in children and clinical populations.

neuroscience↗

bioRxiv2019

Host cholesterol dependent activation of VapC12 toxin enriches persister population during Mycobacterium tuberculosis infection

A worldwide increase in the frequency of multidrug-resistant and extensively drug-resistant cases of tuberculosis is mainly due to therapeutic noncompliance associated with a lengthy treatment regimen. Depending on the drug susceptibility profile, the treatment duration can extend from 6 months to 2 years. This protracted regimen is attributed to a supposedly non-replicating and metabolically inert subset of the Mycobacterium tuberculosis (Mtb) population, called persisters. The mechanism underlying stochastic generation and enrichment of persisters is not fully known. We have previously reported that the utilization of host cholesterol is essential for mycobacterial persistence. In this study, we have demonstrated that cholesterol-induced activation of a ribonuclease toxin (VapC12) inhibits translation by targeting proT tRNA in Mtb. This results in cholesterol-specific growth modulation that increases the frequency of the generation of persisters in a heterogeneous Mtb population. Also, a null mutant strain of this toxin ({Delta}vapC12) failed to persist and demonstrated an enhanced growth phenotype in a guinea pig model of Mtb infection. Thus, we have identified a novel strategy through which cholesterol-specific activation of a toxin-antitoxin (TA) module in Mtb enhances persister formation during infection. In addition to identifying the mechanism, the study provides opportunity for targeting persisters, a new paradigm facilitating tuberculosis drug development.

microbiology↗

bioRxiv2019

Biophysical mechanisms to relate large-scale brain network dynamics to individual-specific variability of perception

Perception necessitates interaction amongst neuronal ensembles, the dynamics of which can be conceptualized as the emergent behavior of coupled dynamical systems. Here, we propose a detailed neurobiologically realistic model that captures the neural mechanisms of inter-individual variability observed in cross-modal speech perception. From raw EEG signals recorded from human participants when they were presented with speech vocalizations of McGurk-incongruent and congruent audio-visual (AV) stimuli, we computed the global coherence metric to capture the neural variability of large-scale networks. We identified that participants McGurk susceptibility was negatively correlated to their alpha-band global coherence. The proposed biophysical model conceptualized the global coherence dynamics emerge from coupling between the interacting neural masses - representing the sensory specific auditory/visual areas and modality non-specific associative/integrative regions. Subsequently, we could predict that an extremely weak direct AV coupling result in a decrease in alpha band global coherence - mimicking the cortical dynamics of participants with higher McGurk susceptibility. Source connectivity analysis also showed decreased connectivity between sensory specific regions in participants more susceptible to McGurk effect, thus establishing an empirical validation to the prediction. Overall, our study provides an outline to link variability in structural and functional connectivity metrics to variability of performance that can be useful for several perception & action task paradigms.

neuroscience↗

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

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↗