Biology subjects

Verma, P.

Publications and source records attributed to Verma, P..

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bioRxiv2022

Altered excitatory and inhibitory neuronal subpopulation parameters are distinctly associated with tau and amyloid in Alzheimer's disease

BackgroundNeuronal and circuit level abnormalities of excitation and inhibition are shown to be associated with tau and amyloid-beta (A{beta}) in preclinical models of Alzheimers disease (AD). These relationships remain poorly understood in patients with AD. MethodsUsing empirical spectra from magnetoencephalography (MEG) and computational modeling (neural mass model; NMM) we examined excitatory and inhibitory parameters of neuronal subpopulations and investigated their specific associations to regional tau and A{beta}, measured by positron emission tomography (PET), in patients with AD. ResultsPatients with AD showed abnormal excitatory and inhibitory time-constants and neural gains compared to age-matched controls. Increased excitatory time-constants distinctly correlated with higher tau depositions while increased inhibitory time-constants distinctly correlated with higher A{beta} depositions. ConclusionsOur results provide critical insights about potential mechanistic links between abnormal neural oscillations and cellular correlates of impaired excitatory and inhibitory synaptic functions associated with tau and A{beta} in patients with AD. FundingThis study was supported by the National Institutes of Health grants: K08AG058749 (KGR), F32AG050434-01A1 (KGR), K23 AG038357 (KAV), P50 AG023501, P01 AG19724 (BLM), P50-AG023501 (BLM & GDR), R01 AG045611 (GDR); AG034570, AG062542 (WJ); NS100440 (SSN), DC176960 (SSN), DC017091 (SSN), AG062196 (SSN); a grant from John Douglas French Alzheimers Foundation (KAV); grants from Larry L. Hillblom Foundation: 2015-A-034-FEL and (KGR); 2019-A-013-SUP (KGR); a grant from the Alzheimers Association: (PCTRB-13-288476) (KAV), and made possible by Part the CloudTM, (ETAC-09-133596); a grant from Tau Consortium (GDR & WJJ), and a gift from the S. D. Bechtel Jr. Foundation.

neuroscience↗

bioRxiv2021

Stability and dynamics of a spectral graph model of brain oscillations

We explore the stability and dynamic properties of a hierarchical, linearized, and analytic spectral graph model for neural oscillations that integrates the structuring wiring of the brain. Previously we have shown that this model can accurately capture the frequency spectra and the spatial patterns of the alpha and beta frequency bands obtained from magnetoencephalography recordings without regionally varying parameters. Here, we show that this macroscopic model based on long-range excitatory connections exhibits dynamic oscillations with a frequency in the alpha band even without any oscillations implemented at the mesoscopic level. We show that depending on the parameters, the model can exhibit combinations of damped oscillations, limit cycles, or unstable oscillations. We determined bounds on model parameters that ensure stability of the oscillations simulated by the model. Finally, we estimated time-varying model parameters to capture the temporal fluctuations in magnetoencephalography activity. We show that a dynamic spectral graph modeling framework with a parsimonious set of biophysically interpretable model parameters can thereby be employed to capture oscillatory fluctuations observed in electrophysiological data in various brain states and diseases.

neuroscience↗

bioRxiv2021

Spectral graph theory of brain oscillations -- revisited and improved

Mathematical modeling of the relationship between the functional activity and the structural wiring of the brain has largely been undertaken using non-linear and biophysically detailed mathematical models with regionally varying parameters. While this approach provides us a rich repertoire of multistable dynamics that can be displayed by the brain, it is computationally demanding. Moreover, although neuronal dynamics at the microscopic level are nonlinear and chaotic, it is unclear if such detailed nonlinear models are required to capture the emergent meso- (regional population ensemble) and macroscale (whole brain) behavior, which is largely deterministic and reproducible across individuals. Indeed, recent modeling effort based on spectral graph theory has shown that an analytical model without regionally varying parameters can capture the empirical magnetoencephalography frequency spectra and the spatial patterns of the alpha and beta frequency bands accurately. In this work, we demonstrate an improved hierarchical, linearized, and analytic spectral graph theorybased model that can capture the frequency spectra obtained from magnetoencephalography recordings of resting healthy subjects. We reformulated the spectral graph theory model in line with classical neural mass models, therefore providing more biologically interpretable parameters, especially at the local scale. We demonstrated that this model performs better than the original model when comparing the spectral correlation of modeled frequency spectra and that obtained from the magnetoencephalography recordings. This model also performs equally well in predicting the spatial patterns of the empirical alpha and beta frequency bands. HighlightsO_LIWe show an improved hierarchical, linearized, and analytic spectral graph theory-based model that can capture the frequency spectra obtained from magnetoencephalography recordings C_LIO_LIThis model also accurately captures the spatial patterns of the empirical alpha and beta frequency bands, requiring only 5-10 graph eigenmodes to do so C_LI

neuroscience↗

bioRxiv2021

The effect of mating complexity on gene drive dynamics

Gene drive technology promises to deliver on some of the global challenges humanity faces to-day in healthcare, agriculture and conservation. However, there is a limited understanding of the consequences of releasing self-perpetuating transgenic organisms into the wild populations under complex ecological conditions. In this study, we analyze the impact of three such complexities, mate-choice, mating systems and spatial mating network, on the population dynamics for two distinct classes of modification gene drive systems. All three factors had a high impact on the modelling outcome. First, we demonstrate that distortion based gene drives appear to be more robust against the mate-choice than viability-based gene drives. Second, we find that gene drive spread is much faster for higher degrees of polygamy. Including a fitness cost, the drive is fastest for intermediate levels of polygamy. Finally, the spread of gene drive is faster and more effective when the individuals have fewer connections in a spatial mating network. Our results highlight the need to include mating complexities while modelling the properties of gene drives such as release thresholds, timescales and population-level consequences. This inclusion will enable a more confident prediction of the dynamics of engineered gene drives and possibly even inform on the origin and evolution of natural gene drives.

evolutionary biology↗

bioRxiv2021

CaProDH2-mediated modulation of proline metabolism confers tolerance to Ascochyta in chickpea under drought

Drought and leaf blight caused by the fungus Ascochyta rabiei often co-occur in chickpea (Cicer arietinum)-producing areas. While the responses of chickpea to either drought or A. rabiei infection have been extensively studied, their combined effect on plant defense mechanisms is unknown. Fine modulation of stress-induced signaling pathways under combined stress is an important stress adaptation mechanism that warrants a better understanding. Here we show that drought facilitates resistance against A. rabiei infection in chickpea. The analysis of proline levels and gene expression profiling of its biosynthetic pathway under combined drought and A. rabiei infection revealed the gene encoding proline dehydrogenase (CaProDH2) as a strong candidate conferring resistance to A. rabiei infection. Transcript levels of CaProDH2, pyrroline-5-carboxylate (P5C) quantification, and measurement of mitochondrial reactive oxygen species (ROS) production showed that fine modulation of the proline-P5C cycle determines the observed resistance. In addition, CaProDH2-silenced plants lost basal resistance to A. rabiei infection induced by drought, while overexpression of the gene conferred higher resistance to the fungus. We suggest that the drought-induced accumulation of proline in the cytosol helps maintain cell turgor and raises mitochondrial P5C contents by a CaProDH2-mediated step, which results in ROS production that boosts plant defense responses and confers resistance to A. rabiei infection. Our findings indicate that manipulating the proline-P5C pathway may be a possible strategy for improving stress tolerance in plants suffering from combined drought and A. rabiei infection.

plant biology↗

bioRxiv2021

Emergence of directional bias in tau deposition from axonal transport dynamics

Defects in axonal transport may partly underpin the differences between the observed pathophysiology of Alzheimers disease (AD) and that of other non-amyloidogenic tauopathies. Particularly, pathological tau variants may have molecular properties that dysregulate motor proteins responsible for the anterograde-directed transport of tau in a disease-specific fashion. Here we develop the first computational model of tau-modified axonal transport that produces directional biases in the spread of tau pathology. We simulated the spatiotemporal profiles of soluble and insoluble tau species in a multicompartment, two-neuron system using biologically plausible parameters and time scales. Changes in the balance of tau transport feedback parameters can elicit anterograde and retrograde biases in the distributions of soluble and insoluble tau between compartments in the system. Aggregation and fragmentation parameters can also perturb this balance, suggesting a complex interplay between these distinct molecular processes. Critically, we show that the model faithfully recreates the characteristic network spread biases in both AD-like and non-AD-like mouse tauopathy models. Tau transport feedback may therefore help link microscopic differences in tau conformational states and the resulting variety in clinical presentations. Author SummaryThe misfolding and spread of the axonal protein tau is a hallmark of the pathology of many neurodegenerative disorders, including Alzheimers disease and frontotemporal lobar dementia. How tau misfolding causes disorders with distinct neuropathology and clinical presentations is the subject of ongoing research. Although current evidence suggests that the specific conformations tau adopts affect where it spreads throughout the brain, a mechanistic explanation has remained elusive. Here we propose that the conformer-specific dysregulation of axonal transport can lead to directionally biased spread, and we employ a mathematical model to explore how tau spreads between neurons in the context of this transport feedback mechanism. We find that conformation-specific feedback is flexible enough to explain bias in either direction and thoroughly explore how this bias emerges as a function of the models key parameters. Further, the model reproduces the temporal evolution of directionality observed in two classes of in vivo tauopathy models, demonstrating that transport feedback is sufficient to explain differential tau spread as a function of conformation.

neuroscience↗

bioRxiv2020

ALC1 links chromatin accessibility to PARP inhibitor response in homologous recombination deficient cells

The response to Poly (ADP-ribose) polymerase inhibitors (PARPi) is dictated by homologous recombination (HR) DNA repair mechanisms and the abundance of lesions that trap PARP enzymes on chromatin. It remains unclear, however, if the established role of PARP in promoting chromatin accessibility impacts viability in these settings. Using a CRISPR based screen, we identify the PAR-binding Snf2-like ATPase, ALC1/CHD1L, as a key determinant of PARPi toxicity in HR-deficient cells. ALC1 loss reduced viability of BRCA mutant cells and enhanced their sensitivity to PARPi by up to 250-fold, while overcoming several known resistance mechanisms. ALC1 loss was not epistatic to other repair pathways that execute the PARPi response. Instead, ALC1 deficiency reduced chromatin accessibility concomitant with a decrease in the association of repair factors. This resulted in an accumulation of replication associated DNA damage and a reliance on HR. These findings establish PAR-dependent chromatin remodeling as a mechanistically distinct aspect of PARPi responses, implicating ALC1 inhibition as a new approach to overcome therapeutic resistance in HR-deficient cancers.

cancer biology↗

bioRxiv2020

Control of feeding by Piezo-mediated gut mechanosensation in Drosophila

Across animal species, meals are terminated after ingestion of large food volumes, yet underlying mechanosensory receptors have so far remained elusive. Here, we identify an essential role for Drosophila Piezo in volume-based control of meal size. We discover a rare population of fly neurons that express Piezo, innervate the anterior gut and crop (a food reservoir organ), and respond to tissue distension in a Piezo-dependent manner. Activating Piezo neurons decreases appetite, while Piezo knockout and Piezo neuron silencing cause gut bloating and increase both food consumption and body weight. These studies reveal that disrupting gut distension receptors changes feeding patterns, and identify a key role for Drosophila Piezo in internal organ mechanosensation.

neuroscience↗

bioRxiv2020

Multiple Wnts act synergistically to induce Chk1/Grapes expression and mediate G2 arrest in Drosophila tracheoblasts

Larval tracheae of Drosophila harbor progenitors of the adult tracheal system (tracheoblasts). Thoracic tracheoblasts are arrested in the G2 phase of the cell cycle in an ATR (mei-41)-Checkpoint Kinase1 (grapes, Chk1) dependent manner prior to mitotic re-entry. Here we investigate developmental regulation of Chk1 activation. We report that Wnt signaling is high in tracheoblasts and is necessary for high levels of activated (phosphorylated) Chk1. We find that canonical Wnt signaling facilitates this by transcriptional upregulation of Chk1 expression in cells that have ATR kinase activity. Wnt signalling is dependent on four Wnts (Wg, Wnt5, 6,10) that are expressed at high levels in arrested tracheoblasts and downregulated at mitotic re-entry. Interestingly, none of the Wnts are dispensable and act synergistically to induce Chk1. Finally, we show that downregulation of Wnt signalling and Chk1 expression leads to mitotic re-entry and the concomitant upregulation of Dpp signalling, driving tracheoblast proliferation.

developmental biology↗

bioRxiv2020

How strategy environment and wealth shape altruistic behaviour: Cooperation rules affecting wealth distribution in dynamic networks

Societies rely on individual contributions to sustain public goods that benefit the entire community. Several mechanisms, that specify how individuals change their decisions based on past experiences, have been proposed to explain how altruists are not outcompeted by selfish counterparts. A key aspect of such strategy updates involves a comparison of an individuals latest payoff with that of a random neighbour. In reality, both the economic and social milieu often shapes cooperative behaviour. We propose a new decision heuristic, where the propensity of an individual to cooperate depends on the local strategy environment in which she is embedded as well as her wealth relative to that of her neighbours. Our decision-making model allows cooperation to be sustained and also explains the results of recent experiments on social dilemmas in dynamic networks. Final cooperation levels depend only on the extent to which the strategy environment influences altruistic behaviour but are largely unaffected by network restructuring. However, the extent of wealth inequality in the community is affected by a subtle interplay between the environmental influence on a persons decision to contribute and the likelihood of reshaping social ties, with wealth-inequality levels rising with increasing likelihood of network restructuring in some situations.

animal behavior and cognition↗

bioRxiv2020

A mathematical investigation of chemotherapy-induced peripheral neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a prevalent, painful side effect which arises due to a number of chemotherapy agents. CIPN can have a prolonged effect on quality of life. Chemotherapy treatment is often reduced or stopped altogether because of the severe pain. Currently, there are no FDA-approved treatments for CIPN partially due to its complex pathogenesis in multiple pathways involving a variety of channels, specifically, voltage-gated ion channels. A surrogate of neuropathic pain in an in vitro setting is hyperexcitability in dorsal root ganglia (DRG) peripheral sensory neurons. Our study employs bifurcation theory to investigate the role of voltage-gated ion channels in inducing hyperexcitability as a consequence of spontaneous firing, due to the common chemotherapy agent paclitaxel. Our mathematical investigation suggests that the sodium channel Nav1.8 and the delayed rectifier potassium channel conductances are the most critical for hyperexcitability in normal firing small DRG neurons. Introducing paclitaxel into the model, our bifurcation analysis predicts that hyperexcitability is extreme for a medium dose of paclitaxel, which is validated by multi-electrode array recordings. Our findings using multi-electrode array experiments reveal that the Nav1.8 blocker A-803467 and the delayed rectifier potassium enhancer L-alpha-phosphatidyl-D-myo-inositol 4,5-diphosphate, dioctanoyl (PIP2) have a protective effect on the firing rate of DRG when administered separately together with paclitaxel as suggested by our bifurcation analysis.

neuroscience↗

bioRxiv2020

A unifying approach to gene drive

Synthetic gene drive technologies aim to spread transgenic constructs into wild populations even when they impose organismal fitness disadvantages. The extraordinary diversity of plausible drive mechanisms and the range of selective parameters they may encounter makes it very difficult to convey their relative predicted properties, particularly where multiple approaches are combined. The sheer number of published manuscripts in this field, experimental and theoretical, the numerous techniques resulting in an explosion in the gene drive vocabulary hinder the regulators point of view. We address this concern by defining a simplified parameter based language of synthetic drives. Employing the classical population dynamics approach, we show that different drive construct (replacement) mechanisms can be condensed and evaluated on an equal footing even where they incorporate multiple replacement drives approaches. Using a common language, it is then possible to compare various model properties, a task desired by regulators and policymakers. The generalization allows us to extend the study of the invasion dynamics of replacement drives analytically and, in a spatial setting, the resilience of the released drive constructs. The derived framework is available as a standalone tool. Besides comparing available drive constructs, our tool is also useful for educational purpose. Users can also explore the evolutionary dynamics of future hypothetical combination drive scenarios. Thus, our results appraise the properties and robustness of drives and provide an intuitive and objective way for risk assessment, informing policies, and enhancing public engagement with proposed and future gene drive approaches.

evolutionary biology↗

bioRxiv2019

Using Bifurcation Theory for Exploring Pain

Pain is a common sensation which inescapably arises due to injuries, as well as, various diseases and disorders. However, for the same intensity of disturbance arising due to the forgoing causes, the threshold for pain sensation and perception varies among individuals. Here, we present a computational approach using bifurcation theory to understand how the pain sensation threshold varies and how it can be controlled, the threshold being quantified by the electrical activity of a pain-sensing neuron. To this end, we explored the bifurcations arising from a mathematical model representing the dynamics of this neuron. Our findings indicate that the bifurcation points are sensitive to specific model parameters. This demonstrates that the pain sensation threshold can change as shown in experimental studies found in literature. Further investigation using our bifurcation approach coupled with experimental studies can facilitate rigorous understanding of pain response mechanism and provide strategies to control the pain sensation threshold.

neuroscience↗

bioRxiv2018

The Evolution of Antibiotic Production Rate in a Spatial Model of Bacterial Competition

We consider competition between antibiotic producing bacteria, non-producers (or cheaters), and sensitive cells in a two-dimensional lattice model. Previous work has shown that these three cell types can survive in spatial models due to the presence of spatial patterns, whereas coexistence is not possible in a well-mixed system. We extend this to consider the evolution of the antibiotic production rate, assuming that the cost of antibiotic production leads to a reduction in growth rate of the producers. We find that coexistence occurs for an intermediate range of antibiotic production rate. If production rate is too high or too low, only sensitive cells survive. When evolution of production rate is allowed, a mixture of cell types arises in which there is a dominant producer strain that produces sufficient to limit the growth of sensitive cells and which is able to withstand the presence of cheaters in its own species. The mixture includes a range of low-rate producers and non-producers, none of which could survive without the presence of the dominant producer strain. We also consider the case of evolution of antibiotic resistance within the sensitive species. In order for the resistant cells to survive, they must grow faster than both the non-producers and the producers. However, if the resistant cells grow too rapidly, the producing species is eliminated, after which the resistance mutation is no longer useful, and sensitive cells take over the system. We show that there is a range of growth rates of the resistant cells where the two species coexist, and where the production mechanism is maintained as a polymorphism in the producing species and the resistance mechanism is maintained as a polymorphism in the sensitive species.\n\nAuthor SummaryNatural environments such as the soil contain many species of antibiotic producing bacteria. Antibiotics prevent the growth of sensitive species that would otherwise outcompete the more-slowly-growing antibiotic producers. The producers are also vulnerable to competition from non-producing \"cheats\" arising by mutations within the producing species that avoid the metabolic cost of antibiotic production. We consider multiple strains of producers that differ in production rate in the presence of sensitive cells of a different species. We show, in 2d simulations, that the system evolves towards a state with a dominant producer strain that is able to outcompete the sensitive cells, plus a range of low-rate producers and non-producers that can survive in the presence of the dominant producer, but not on their own. This system remains stable, despite the short-term selective advantage to reducing production rate. When resistant mutants are added to the sensitive species, we show that there is a range of growth rate of the resistant cells in which producers, non-producers, sensitive and resistant cells can all coexist - as we see in nature. Our model shows the balance of factors required to maintain resistance mechanisms and production mechanisms together within the mixture of species.

evolutionary biology↗