Biology subjects

Hari, K.

Publications and source records attributed to Hari, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Regulatory stochasticity drives opposing phenotypic outcomes in cell-fate decision networks

Gene regulatory network models treat interaction parameters as fixed, although regulatory efficacy fluctuates. We asked how temporal fluctuations in interaction strength reshape phenotype occupancy in cell-fate decision GRN motifs. Across large parameter ensembles, anchored fluctuations largely preserved deterministic occupancies. Additive fluctuations increased occupancy of all-high co-expression states, particularly where high expression was accessible. In contrast, multiplicative fluctuations biased inhibitory interactions toward stronger repression and favored single-high states in a topology-dependent manner. Deterministic controls sampled from noise-induced parameter distributions did not fully reproduce these effects. A Boolean-limit analysis revealed an intrinsic upward bias: loss of repression increased expression regardless of regulator state, whereas stronger repression acted only when the regulator was present. Analyses of epithelial-mesenchymal plasticity and gonadal-fate networks showed increased occupancy of hybrid team-expression states under additive fluctuations. Thus, regulatory noise can reshape the developmental landscape in opposing directions, pushing cell-fate systems toward either progenitor-like or terminally differentiated states.

systems biology↗

bioRxiv2026

Activity-dependent structural plasticity of myelinated axons tunes their excitability

Myelinated axons are classically viewed as stable cables of fixed geometry. We show here that a brief subthreshold stimulation of single nodes in mouse dorsal column axons drives a rapid, lasting structural change: the stimulated axons shrink locally along the internode segments adjacent to the node, to about 70% of their diameter within a few seconds, while neighbouring glia swell to fill the space, sparing the node, paranode and more distant internodes. The thinned axon becomes markedly more excitable for hours, by an amount cable theory predicts from its shorter internodal length constant rather than from active currents that tend to decay over long periods. Using a grease-gap signal that reports the axial-conductance change, we find the axon thinning requires under-myelin Kv1 channels, Na/K-ATPase pumps, bicarbonate, and altered pH, consistent with a regenerative periaxonal potassium build-up that osmotically compresses the axon and swells glia, as previously proposed for physiological high-frequency firing. We present evidence that this mechanism may contribute to the long-lasting clinical benefits of spinal cord stimulation. Axonal GABAA receptor activation reproduces and occludes the plasticity induced by stimulation, indicating that they share a common underlying mechanism. Activity-dependent axon thinning thus enables potent physiologically relevant long term control of conduction, with potential clinical applications.

neuroscience↗

bioRxiv2026

Systems-level analysis identifies IRF6 as an inhibitor of epithelial-mesenchymal transition

BackgroundEpithelial-mesenchymal transition (EMT) and its reverse process Mesenchymal-Epithelial Transition (MET) are crucial during metastasis and therapy resistance. While the dynamics and master regulators of EMT are well-studied, the transcription factors that can prevent EMT or promote MET are relatively less understood. ResultsHere, by integrating bulk and spatial transcriptomic data analysis from cell lines and patient samples, with mechanism-based dynamical modelling, we identify IRF6 as a factor that strongly associates with an epithelial phenotype and is often inhibited during EMT. In vitro experiments in multiple cancer cell lines demonstrate the progression to a mesenchymal phenotype upon IRF6 knock-down, suggesting a role as an inhibitor of EMT. Finally, we observe that IRF6 expression levels correlates with worse patient survival in a subset of solid tumour types. ConclusionOur integrated computational-experimental systems-level analysis suggests that IRF6 is frequently downregulated during EMT and can also prevent the progression towards a complete EMT, underscoring its role as an MET stabilizing factor.

systems biology↗

bioRxiv2026

Reduced GABAB receptor activation and post activation depression of proprioceptive afferents after spinal cord injury.

Despite a long history of studying presynaptic inhibition of the Ia afferent synapse that produces the monosynaptic EPSP on motoneurons, recent evidence has upset the conventional idea that GABAA receptors mediate this inhibition and instead suggests that there are mainly GABAB receptors at this synapse. However, without targeted access to the GABAergic neurons that activate these receptors, quantifying their functional contribution to presynaptic inhibition has proven difficult. We demonstrate here that focal optogenetic activation of terminals of a subpopulation of GAD2+ GABAergic neurons that exclusively project ventrally to Ia afferent synapses produce long-lasting presynaptic inhibition that is entirely mediated by GABAB receptors and simultaneously produces a characteristic brief GABAA receptor-mediated IPSP on the motoneurons. These ventral GAD2 neurons are recurrently activated by Ia afferents, contributing to post-activation depression with repeated afferent reflex testing, with a similar long time-course to post-activation depression of the H-reflex induced in humans from either repetitive activation of the same Ia afferents or from antagonist nerve conditioning. In contrast, focal activation of dorsally projecting GAD2 neurons does not directly cause presynaptic inhibition or postsynaptic IPSPs but does produce primary afferent depolarization. Following chronic spinal cord injury (SCI), the expression of GABAB receptors on the Ia terminal is halved, and in mice and humans, is associated with a similar decrease of GABAB receptor-mediated post-activation depression of Ia-EPSPs transmission, which is reversed by the GABAB receptor agonist baclofen. In summary, GABAB receptors mediate presynaptic inhibition, but are down regulated with SCI, contributing to reflex hyperexcitability associated with spasticity. Key Points SummaryO_LIPresynaptic inhibition of Ia afferents is mediated by the recurrent activation of terminal GABAB receptors by a subpopulation of ventrally projecting GAD2+ interneurons. C_LIO_LIIn contrast, dorsally projecting GAD2+ interneurons activate GABAA receptors on Ia afferent nodes to facilitate action potential conduction through branchpoints. C_LIO_LIRepetitive activation of Ia afferents at rates of every 10 s or faster produces post-activation depression via neurotransmitter depletion and from activation of terminal GABAB receptors. C_LIO_LIThese ventrally projecting GAD2+ interneurons can also be activated by other afferents that then produce PAD-evoked spikes to produce post-activation depression from conditioning nerve stimulation. C_LIO_LIThe reduction of GABAB receptors on the Ia terminal in spinal cord injury results in reduced presynaptic inhibition and post-activation depression, contributing to reflex hyperexcitability. C_LI O_FIG O_LINKSMALLFIG WIDTH=189 HEIGHT=200 SRC="FIGDIR/small/700955v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@17abd51org.highwire.dtl.DTLVardef@12316baorg.highwire.dtl.DTLVardef@a92168org.highwire.dtl.DTLVardef@1d06ca0_HPS_FORMAT_FIGEXP M_FIG Abstract legend: Schematic of GABAergic circuit producing presynaptic inhibition and primary afferent depolarization (PAD) in proprioceptive Ia afferents. We propose two populations of GAD2+ GABAergic interneurons, one with dorsal projections (purple) that activate GABAA receptors on the nodes of Ia afferents to produce PAD and subsequent facilitation of Ia afferent conduction, and another ventrally projecting population (pink) that activates GABAB receptors on the Ia afferent terminal to produce presynaptic inhibition via inhibition of VCa2+ channels and reduction of neurotransmitter release and replenishment. Both are activated by first order interneurons (grey). Repetitive activation of Ia afferents (green extensor) recurrently activates twhe ventrally projecting GAD2+ neurons to activate terminal GABAB receptors and long-lasting post-activation depression of Ia EPSPs and reflexes as measured from ventral root recordings. Strong conditioning stimulation of other afferents (blue flexor) activates dorsal GAD2+ neurons that can produce PAD-evoked spikes in extensor afferents that orthodromically activate motoneurons to set up post-activation depression of subsequent extensor reflexes. Here, PAD is also evoked in other afferents (flexor) by dorsally projecting GAD2+ neurons (light pink branch) but without activation of the ventrally projecting GAD2+ neurons or presynaptic inhibition. C_FIG

neuroscience↗

bioRxiv2025

Multi-team conflict resolution is ineffective for stable decision making

Competition between distinct groups is fundamental to complex systems, from political coalitions and economic markets to gene regulatory networks (GRNs) controlling cell fate. Strikingly, cell-fate decision systems predominantly employ binary competition between two mutually inhibitory teams of genes, despite multi-team competition being common in social and ecological contexts. This raises a fundamental question: does binary decision-making offer functional advantages over multi-team systems? We systematically analyzed multi-team competitive networks using Boolean dynamics on signed directed graphs, extending well-characterized two-team GRN architectures to systems with three or more mutually inhibitory teams. Three-team networks produced significantly less stable outcomes than two-team systems, with steady states showing higher structural frustration and increased sensitivity to perturbations. Multi-team systems exhibited unpredictable transitions even under controlled perturbations, especially at lower densities typical of real networks. Networks with four or more teams failed to maintain distinct stable states entirely. Using spectral analysis, we show that team structure can be predicted from network eigenproperties, extending structural balance theory to directed signed networks. Our findings explain why binary decisions dominate biology and provide insights into coalition instability in social systems, market dynamics, and organizational structures. This work establishes fundamental stability principles for competitive networks across disciplines.

systems biology↗

bioRxiv2025

Impacts of competition and phenotypic plasticity on the viability of adaptive therapy

Cancer is heterogeneous and variability in drug sensitivity is widely documented across cancer types. Adaptive therapy is an emerging modality of cancer treatment that leverages this drug resistance heterogeneity to improve therapeutic outcomes. Current standard treatments typically eliminate a large fraction of drug-sensitive cells, leading to drug-resistant relapse due to competitive release. Adaptive therapy aims to retain some drug-sensitive cells, thereby limiting resistant cell growth by ecological competition. While early clinical trials of such a strategy have shown promise, optimisation of adaptive therapy is a subject of active study. Current methods largely assume cell phenotypes to remain constant, even though cell-state transitions could permit drug-sensitive and -resistant phenotypes to interchange and thus escape therapy. We address this gap using a deterministic model of population growth, in which sensitive and resistant cells grow under competition and undergo cell-state transitions. Based on the models steady-state behaviour and temporal dynamics, we identify distinct balances of competition and phenotypic transitions that are suitable for effective adaptive versus constant dose therapy. Our data indicate that under adaptive therapy, models with cell-state transitions show a higher frequency of fluctuations than those without, suggesting that the balance between ecological competition and phenotypic transitions could determine population-level dynamical properties. Our analyses also identify key limitations of applying phenomenological models in clinical practice for therapy design and implementation, particularly when cell-state transitions are involved. These findings provide an overall perspective on the relevance of phenotypic plasticity for emerging cancer treatment strategies using population dynamics as an investigation framework. Significance StatementDrug-sensitive and -resistant cancer cells can compete with each other within the same tumour, and adaptive therapy exploits this competition to control overall tumour growth. The fact that sensitive and resistant cell types can switch phenotypes complicates the implementation of adaptive therapy. Our ODE-based theoretical ecology framework shows that asymmetric competition favouring sensitive cells generally benefits therapy outcomes, while phenotypic plasticity is usually detrimental. Our model also provides cell population-level indicators that can help predict the underlying balance between competition and plasticity. Phenomenological models are limited by whether their parameters can be reliably identified given scarce data, and our study illuminates the scope of such models in understanding cancer population dynamics and the need for mechanistic modelling.

systems biology↗

bioRxiv2025

Emergent dynamics of cellular decision making in multi-node mutually repressive regulatory networks

Stem cell differentiation during development is governed by the dynamics of the underlying gene regulatory networks (GRNs). Mutually inhibiting nodes/collection of nodes encompass the GRNs that govern differentiation to two distinct fates. But the properties of GRNs that can allow differentiation into n-terminal phenotypes are not understood. In this study, we examine toggle-n networks, encompassing mutual inhibitions among multiple transcription factors, to derive generalized conclusions regarding the dynamics underlying differentiation into n-terminal phenotypes. We show that in steady-state distributions of gene expression, multiple cell state-specific transcription factors are co-expressed, indicating an obligatory multi-step process of multi-lineage differentiation. Furthermore, we show that cytokine signaling and specific asymmetry of regulatory links can lead to directed differentiation towards a particular cell state. Our findings provide valuable insights into the mechanistic aspects of directed differentiation of stem cells.

systems biology↗

bioRxiv2025

Critical assessment of the ability of Boolean threshold models to describe gene regulatory network dynamics.

The inference of gene regulatory networks (GRNs) from high-throughput data constitutes a fundamental and challenging task in systems biology. Boolean networks are a popular modeling framework to understand the dynamic nature of GRNs. In the absence of reliable methods to infer the regulatory logic of Boolean GRN models, researchers frequently assume threshold logic as a default. Using the largest repository of published expert-curated Boolean GRN models as best proxy of reality, we systematically compare the ability of two popular threshold formalisms, the Ising and the 01 formalism, to truthfully recover biological functions and biological system dynamics. While Ising rules match fewer biological functions exactly than 01 rules, they yield a better average agreement. In general, more complex regulatory logic proves harder to be represented by either threshold formalism. Informed by these results and a meta-analysis of regulatory logic, we propose modified versions for both formalisms, which provide a better function-level and dynamic agreement with biological GRN models than the usual threshold formalisms. For small biological GRN models with low connectivity, corresponding threshold networks exhibit similar dynamics. However, they generally fail to recover the dynamics of large networks or highly-connected networks. In conclusion, this study provides new insights into an important question in computational systems biology: how truthfully do Boolean threshold networks capture the dynamics of GRNs? Significance statementGene regulatory networks (GRNs) describe the complex interactions between genes. GRNs control biological processes, respond to environmental changes, and contribute to diseases. An accurate understanding of the dynamics of GRNs is therefore crucial. Given insufficient data, researchers frequently employ Boolean network models with default threshold logic to study the dynamics of GRNs. We systematically assess the ability of two commonly-used types of threshold networks to recover the true regulatory logic and the dynamics of published expert-curated Boolean GRN models. Inspired by biological insights, we further propose modifications to each threshold formalism that improve their match with biological networks.

systems biology↗

bioRxiv2025

Topological conditions of gene regulatory networks enabling robust binary cell-fate decision-making

Phenotypic plasticity--the reversible switching of cell-states--is a central tenet of development, regeneration, and cancer progression. These transitions are governed by gene regulatory networks (GRNs), whose topological features strongly influence their dynamics. While toggle switches (mutually inhibitory feedback loops between two transcription factors) are a common motif observed for binary cell-fate decisions, GRNs across diverse contexts often exhibit a more general structure: two mutually inhibiting teams of nodes. Here, we investigate the teams of nodes as a potential topological design principle of GRNs. We first analyze GRNs from the Cell Collective database and introduce a metric, impurity, which quantifies the fraction of edges inconsistent with an idealized two-team architecture. Impurity correlates strongly with statistical properties of GRN phenotypic landscapes, highlighting its predictive value. To further probe this relationship, we simulate artificial two-team networks (TTNs) using both continuous (RACIPE) and discrete (Boolean) formalisms across varying impurity, density, and network size values. TTNs exhibit toggle-switch-like robustness under perturbations and enable accurate prediction of dynamical features such as inter-team correlations and steady-state entropy. Together, our findings establish the teams paradigm as a unifying principle linking GRN topology to dynamics, with broad implications for inferring coarse-grained network properties from high-throughput sequencing data.

systems biology↗

bioRxiv2024

A multi-level formalism to capture the characteristics of hybrid phenotypes in Epithelial-Mesenchymal Plasticity

Epithelial-mesenchymal plasticity (EMP) is a cell-fate switching program that enables cells to adopt a spectrum of phenotypes ranging from epithelial (E) to mesenchymal (M), including intermediate hybrid E/M states. Hybrid E/M phenotypes are conducive to cancer metastasis, as they are associated with metastatic initiation, cancer stemness, drug resistance, and collective migration. Boolean models of the gene regulatory networks (GRNs) underlying EMP have yielded valuable insights into the dynamics of E and M phenotypes. However, these models are limited in their ability to capture hybrid phenotypes effectively, as they restrict gene expression to binary states. In contrast, hybrid E/M cells often exhibit partial expression of epithelial and mesenchymal markers. To overcome this limitation, we modified a threshold-based Boolean formalism to incorporate intermediate gene expression levels. The resulting multilevel model reveals novel hybrid steady-states characterized by partial expression of both E and M genes, thereby expanding the phenotypic landscape beyond that represented by traditional Boolean approaches. Notably, these hybrid states exhibit lower frustration compared to their counterparts in classical Boolean models. Furthermore, by resolving dynamical degeneracy, we demonstrate that the hybrid states identified by the multilevel model are more stable. These findings suggest that introducing minimal additional complexity into Boolean models can uncover previously hidden qualitative features of phenotypic landscapes governed by GRNs. Significance StatementHybrid epithelial-mesenchymal phenotypes drive metastasis through collective migration, stemness, and drug resistance. However, traditional Boolean models of epithelial-mesenchymal plasticity (EMP) networks cannot capture the partial gene expression characteristic of these biologically crucial hybrid states. We developed a multilevel Boolean formalism that extends classical binary models to include intermediate expression levels. This approach successfully captures hybrid states with partial expression of both epithelial and mesenchymal genes, exhibiting lower frustration and greater stability than traditional Boolean hybrid phenotypes. While conventional Boolean hybrid states depend on modeling artifacts, multilevel hybrid states emerge independently of such uncertainties. Critically, plasticity experiments revealed that multilevel hybrid states show significantly higher transition probabilities to other hybrid states compared to traditional models, creating a stable "hybrid cloud" that maintains metastatic properties while allowing adaptive responses to environmental stress. This multilevel framework provides a biologically meaningful characterization of hybrid phenotypes essential for understanding metastasis.

systems biology↗

bioRxiv2024

Widespread innervation of motoneurons by spinal V3 neurons globally amplifies locomotor output in mice.

While considerable progress has been made in understanding the neuronal circuits that underlie the patterning of locomotor behaviours such as walking, less is known about the circuits that amplify motoneuron output to enable adaptable increases in muscle force across different locomotor intensities. Here, we demonstrate that an excitatory propriospinal neuron population (V3 neurons, Sim1+) forms a large part of the total excitatory interneuron input to motoneurons ([~]20%) across all hindlimb muscles. Additionally, V3 neurons make extensive connections among themselves and with other excitatory premotor neurons (such as V2a neurons). These circuits allow local activation of V3 neurons at just one segment (via optogenetics) to rapidly depolarize and amplify locomotor-related motoneuron output at all lumbar segments in both the in vitro spinal cord and the awake adult mouse. Interestingly, despite similar innervation from V3 neurons to flexor and extensor motoneuron pools, functionally, V3 neurons exhibit a pronounced bias towards activating extensor muscles. Furthermore, the V3 neurons appear essential to extensor activity during locomotion because genetically silencing them leads to slower and weaker mice with a poor ability to increase force with locomotor intensity, without much change in the timing of locomotion. Overall, V3 neurons increase the excitability of motoneurons and premotor neurons, thereby serving as global command neurons that amplify the locomotion intensity.

neuroscience↗

bioRxiv2024

Multistability and predominant double-positive states in a four node mutually repressive network: a case study of Th1/Th2/Th17/T-reg differentiation

Elucidating the emergent dynamics of complex regulatory networks enabling cellular differentiation is crucial to understand embryonic development and suggest strategies for synthetic circuit design. A well-studied network motif often driving cellular decisions is a toggle switch - a set of two mutually inhibitory lineage-specific transcription factors A and B. A toggle switch often enables two possible mutually exclusive states - (high A, low B) and (low A, high B) - from a common progenitor cell. However, the dynamics of networks enabling differentiation of more than two cell types from a progenitor cell is not well-studied. Here, we investigate the dynamics of four master regulators A, B, C and D inhibiting each other, thus forming a toggle tetrahedron. Our simulations show that a toggle tetrahedron predominantly allows for co-existence of six double positive or hybrid states where two of the nodes are expressed relatively high as compared to the remaining two - (high A, high B, low C, low D), (high A, low B, high C, low D), (high A, low B, low C, high D), (low A, high B, high C, low D), (low A, low B, high C, high D) and (low A, high B, low C, high D). Stochastic simulations showed state-switching among these phenotypes, indicating phenotypic plasticity. Finally, we apply our results to understand the differentiation of naive CD4+ T cells into Th1, Th2, Th17 and Treg subsets, suggesting Th1/Th2/Th17/Treg decision-making to be a two-step process. Our results reveal multistable dynamics and establish the stable co-existence of hybrid cell-states, offering a potential explanation for simultaneous differentiation of multipotent naive CD4+ T cells.

systems biology↗

bioRxiv2023

GABA Increases Sensory Transmission In Monkeys

Sensory input flow is central to voluntary movements. For almost a century, GABA was believed to modulate this flow by inhibiting sensory axons in the spinal cord to sculpt neural inputs into skilled motor output. Instead, here we show that GABA can also facilitate sensory transmission in monkeys and consequently increase spinal and cortical neural responses to sensory inputs challenging our understanding of generation and perception of movement.

neuroscience↗

bioRxiv2023

Public engagement with biomedical science: An analysis of Black, Hispanic, and General Population adults in the United States

The COVID-19 pandemic has highlighted the need to better understand public engagement with biomedical science across groups-especially those that have been historically marginalized by the medical science community. However, common approaches to studying group differences in science attitudes are often limited by small sample sizes or by categorizing individuals based on demographic variables, which may obscure meaningful variability within a given population. We recruited three probability-based samples of Black (N = 963), General Population (N = 957), and Hispanic (N = 964) adults living in the U.S. (October 21 - November 5, 2021). Employing a novel application of a non-negative matrix factorization model to conduct an attitudinal-based segmentation that categorized individuals based on distinct orientations toward biomedical science, our analysis revealed 10 unique mindsets across the three surveyed populations. Overall, our work underscores the value of recruiting independent samples from underserved and marginalized communities by revealing underexplored variation in how different publics orient toward biomedical science. TeaserUsing a values-based segmentation approach, we uncover 10 unique biomedical mindsets in the general, Black, and Hispanic adult populations in the U.S.

scientific communication and education↗

bioRxiv2023

Low dimensionality of phenotypic space as an emergent property of coordinated teams in biological regulatory networks

Biological networks driving cell-fate decisions involve complex interactions, but they often give rise to only a few phenotypes, thus exhibiting low-dimensional dynamics. The network design principles that govern such cell-fate canalization remain unclear. Here, we investigate networks across diverse biological contexts- Epithelial-Mesenchymal Transition, Small Cell Lung Cancer, and Gonadal cell-fate determination - to reveal that the presence of two mutually antagonistic, well-coordinated teams of nodes leads to low-dimensional phenotypic space such that the first principal component (PC1) axis can capture most of the variance. Further analysis of artificial team-based networks and random counterparts of biological networks reveals that the principal component decomposition is determined by the team strength within these networks, demonstrating how the underlying network structure governs PC1 variance. The presence of low dimensionality in corresponding transcriptomic data confirms the applicability of our observations. We propose that team-based topology in biological networks are critical for generating a cell-fate canalization landscape.

systems biology↗

bioRxiv2023

Collective heterogeneity of mitochondrial potential in contact inhibition of proliferation

In the epithelium, cell density and cell proliferation are closely connected to each other through contact inhibition of proliferation (CIP). Depending on cell density, CIP proceeds through three distinct stages, namely the free-growing stage at low density, the pre-epithelial transition stage at medium density, and the post-epithelial transition stage at high density. Previous studies have elucidated how cell morphology, motion, and mechanics vary in these stages. However, it remains unknown whether cellular metabolism also has a density-dependent behavior. By measuring the mitochondrial membrane potential at different cell densities, here we reveal a heterogeneous landscape of metabolism in the epithelium, which appears qualitatively distinct in three stages of CIP. Moreover, it did not follow the trend of other CIP-associated parameters, which increase or decrease monotonically with increasing cell density. Importantly, epithelial cells established a collective heterogeneity in mitochondrial potential exclusively in the pre-epithelial transition stage, where the multicellular clusters of high and low-potential cells emerged. However, in the post-epithelial transition stage, the potential field became relatively homogeneous. The collective metabolic heterogeneity in the pre-epithelial transition stage was independent of the mitochondrial content and spatially correlated with the local cell density. Next, to study the underlying dynamics, we constructed a system-biological model, which predicted the role of cell proliferation in metabolic potential towards establishing collective heterogeneity. Further experiments revealed that the metabolic pattern indeed spatially correlated with the proliferative capacity of cells, as measured by the nuclear localization of a pro-proliferation protein, YAP. Finally, experiments perturbing the actomyosin contractility revealed that while metabolic heterogeneity was maintained in absence of actomyosin contractility, its ab initio emergence depended on the latter. Taken together, our results revealed a density-dependent collective heterogeneity in the metabolic field of a pre-epitheli al transition stage epithelial monolayer, which may have significant implications for epithelial form and function. STATEMENT OF SIGNIFICANCEEpithelial contact inhibition of proliferation (CIP) plays a key role in tissue homeostasis, morphogenesis, and development. The biochemical changes in cells during different stages of CIP are not as well-documented as the biophysical changes. We unveil a heterogeneous landscape of metabolism which appears distinct in different stages of CIP. Importantly, in the pre-epithelial transition stage, the epithelial cells establish a collective metabolic heterogeneity wherein multicellular clusters of high and low-potential cells emerge, despite the uniform genetic and nutrient conditions for the cells. The collective heterogeneity is correlated to the local fluctuations in geometrical parameters and the proliferative capacity of cells. Finally, we demonstrate the role of cell mechanics in the establishment of collective heterogeneity.

biophysics↗

bioRxiv2022

Assessing biological network dynamics: Comparing numerical simulations with analytical decomposition of parameter space

Mathematical modeling of the emergent dynamics of gene regulatory networks (GRN) faces a double challenge of (a) dependence of model dynamics on parameters, and (b) lack of reliable experimentally determined parameters. In this paper we compare two complementary approaches for describing GRN dynamics across unknown parameters: (1) parameter sampling and resulting ensemble statistics used by RACIPE (RAndom CIrcuit PErturbation), and (2) use of rigorous analysis of combinatorial approximation of the ODE models by DSGRN (Dynamic Signatures Generated by Regulatory Networks). We find a very good agreement between RACIPE simulation and DSGRN predictions for four different 2- and 3-node networks typically observed in cellular decision making. This observation is remarkable since the DSGRN approach assumes that the Hill coefficients of the models are very high while RACIPE assumes the values in the range 1-6. Thus DSGRN parameter domains, explicitly defined by inequalities between systems parameters, are highly predictive of ODE model dynamics within a biologically reasonable range of parameters.

systems biology↗

bioRxiv2022

Locomotor-related propriospinal V3 neurons produce primary afferent depolarization and modulate sensory transmission to motoneurons

When a muscle is stretched it not only responds with a reflex, but the sensory afferent feedback also depolarizes many afferents throughout the spinal cord (termed primary afferent depolarization, PAD), readying the whole limb for further disturbances. This sensory-evoked PAD is thought to be caused by a trisynaptic circuit, where sensory input activates first order excitatory neurons that activate GABAergic neurons that in turn activate GABAA receptors on afferents to cause PAD, though the identity of these first order neurons is unclear. Here we show that these first order neurons are propriospinal V3 neurons, since they receive extensive sensory input and in turn innervate GABAergic neurons that cause PAD, because optogenetic activation or inhibition of V3 neurons in mice mimics or inhibits sensory-evoked PAD, respectively. Furthermore, persistent inward sodium currents (Na PICs) intrinsic to V3 neurons enable them to respond to transient inputs with long-lasting responses, explaining the long time-course of PAD. Also, local optogenetic activation of V3 neurons at one segment causes PAD in other segments, due to the long propriospinal tracts of these neurons, explaining the widespread radiation of PAD across the spinal cord. This in turn facilitates monosynaptic reflex transmission to motoneurons across the spinal cord. Additionally, we find that V3 neurons directly innervate proprioceptive afferents, causing a glutamate receptor mediated PAD (glutamate PAD). Finally, we show that increasing the spinal cord excitability with either GABAA receptor blockers or chronic spinal cord injury causes an increase in the glutamate PAD, perhaps contributing to spasms after SCI. Overall, we show the V3 neuron has a prominent role in modulating sensory transmission, in addition to its previously described role in locomotion.

neuroscience↗