Biology subjects

Thomas, P. J.

Publications and source records attributed to Thomas, P. J..

10 recordsLinked to original sources

bioRxiv2025

Neuromechanical Simulation with NEURON and MuJoCo

In computational neuroscience, simulation platforms generally do not have adequate tools to model the brain, body and environment simultaneously. We demonstrate a method for simulating neuromechanical models using a novel combination of widely used software platforms: NEURON and MuJoCo. Different neural models are used to control a realistic musculoskeletal model in both open-loop and closed-loop configurations. Three models are presented: (1) an open-loop model using simple spiking neurons from the NEURON model library; (2) an open-loop model using realistic, spiking motoneurons; and (3) a closed-loop central pattern generator with feedback from the physics engine.

neuroscience↗

bioRxiv2024

Asymmetric neuromodulation in the respiratory network contributes to rhythm and pattern generation

Like other brain circuits, the brainstem respiratory network is continually modulated by neurotransmitters that activate slow metabotropic receptors. In many cases, activation of these receptors only subtly modulates the respiratory motor pattern. However, activation of some receptor types evokes the arrest of the respiratory motor pattern as can occur following the activation of {micro}-opioid receptors. We propose that the varied effects of neuromodulation on the respiratory motor pattern depend on the pattern of neuromodulator receptor expression and their influence on the excitability of their post-synaptic targets. Because a comprehensive characterization of these cellular properties across the respiratory network remains challenging, we test our hypothesis by combining computational modelling with ensemble electrophysiologic recording in the pre-Botzinger complex (pre-BotC) using high-density multi-electrode arrays (MEA). Our computational model encapsulates the hypothesis that neuromodulatory transmission is organized asymmetrically across the respiratory network to promote rhythm and pattern generation. To test this hypothesis, we increased the strength of neuromodulatory connections in the model and used selective agonists in situ while monitoring pre-BotC ensemble activities. The model predictions of increasing slow inhibition were consistent with experiments examining the effect of systemic administration of the 5HT1aR agonist 8-OH-DPAT. Similarly, the predicted effects of increasing slow excitation in the model were experimentally confirmed in pre-BotC ensemble activities before and after systemic administration of the {micro}-opioid receptor agonist fentanyl. We conclude that asymmetric neuromodulation can contribute to respiratory rhythm and pattern generation and accounts for its varied effects on breathing.

neuroscience↗

bioRxiv2023

In Vitro Modulator Responsiveness of 655 CFTR Variants Found in People With CF

BackgroundIn 2017, the US Food and Drug Administration initiated expansion of drug labels for the treatment of cystic fibrosis (CF) to include CF transmembrane conductance regulator (CFTR) gene variants based on in vitro functional studies. This study aims to identify CFTR variants that result in increased chloride (Cl-) transport function by the CFTR protein after treatment with the CFTR-modulator combination elexacaftor/tezacaftor/ivacaftor (ELX/TEZ/IVA). These data may benefit people with CF (pwCF) who are not currently eligible for modulator therapies. MethodsPlasmid DNA encoding 655 CFTR variants and wild-type (WT) CFTR were transfected into Fisher Rat Thyroid cells that do not natively express CFTR. After 24 hours of incubation with control or TEZ and ELX, and acute addition of IVA, CFTR function was assessed using the transepithelial current clamp conductance assay. Each variants baseline activity, responsiveness to IVA alone, and responsiveness to the TEZ/ELX/IVA combination were measured in three different laboratories. Western blots were conducted to evaluate CFTR protein maturation and complement the functional data. Results and Conclusions253 variants not currently approved for CFTR modulator therapy showed low baseline activity (<10% of normal CFTR Cl- transport activity). For 152 of these variants, treatment with ELX/TEZ/IVA improved the Cl- transport activity by [≥]10% of normal CFTR function, which is suggestive of clinical benefit. ELX/TEZ/IVA increased CFTR function by [≥]10 percentage points for an additional 140 unapproved variants with [≥]10% but <50% of normal CFTR function at baseline. These findings significantly expand the number of rare CFTR variants for which ELX/TEZ/IVA treatment should result in clinical benefit.

pharmacology and toxicology↗

bioRxiv2023

COVID-19 and silent hypoxemia in a minimal closed-loop model of the respiratory rhythm generator

Silent hypoxemia, or happy hypoxia, is a puzzling phenomenon in which patients who have contracted COVID-19 exhibit very low oxygen saturation (SaO2 < 80%) but do not experience discomfort in breathing. The mechanism by which this blunted response to hypoxia occurs is unknown. We have previously shown that a computational model (Diekman et al., 2017, J. Neurophysiol) of the respiratory neural network can be used to test hypotheses focused on changes in chemosensory inputs to the central pattern generator (CPG). We hypothesize that altered chemosensory function at the level of the carotid bodies and/or the nucleus tractus solitarii are responsible for the blunted response to hypoxia. Here, we use our model to explore this hypothesis by altering the properties of the gain function representing oxygen sensing inputs to the CPG. We then vary other parameters in the model and show that oxygen carrying capacity is the most salient factor for producing silent hypoxemia. We call for clinicians to measure hematocrit as a clinical index of altered physiology in response to COVID-19 infection.

physiology↗

bioRxiv2022

Variational and phase response analysis for limit cycles with hard boundaries, with applications to neuromechanical control problems

Motor systems show an overall robustness, but because they are highly nonlinear, understanding how they achieve robustness is difficult. In many rhythmic systems, robustness against perturbations involves response of both the shape and the timing of the trajectory. This makes the study of robustness even more challenging. To understand how a motor system produces robust behaviors in a variable environment, we consider a neuromechanical model of motor patterns in the feeding apparatus of the marine mollusk Aplysia californica (Shaw et al., 2015; Lyttle et al., 2017). We established in (Wang et al., 2021) the tools for studying combined shape and timing responses of limit cycle systems under sustained perturbations and here apply them to study robustness of the neuromechanical model against increased mechanical load during swallowing. Interestingly, we discover that nonlinear biomechanical properties confer resilience by immediately increasing resistance to applied loads. In contrast, the effect of changed sensory feedback signal is significantly delayed by the firing rates hard boundary properties. Our analysis suggests that sensory feedback contributes to robustness in swallowing primarily by shifting the timing of neural activation involved in the power stroke of the motor cycle (retraction). This effect enables the system to generate stronger retractor muscle forces to compensate for the increased load, and hence achieve strong robustness. The approaches that we are applying to understanding a neuromechanical model in Aplysia, and the results that we have obtained, are likely to provide insights into the function of other motor systems that encounter changing mechanical loads and hard boundaries, both due to mechanical and neuronal firing properties.

neuroscience↗

bioRxiv2022

Inferring Density-Dependent Population Dynamics Mechanisms through Rate Disambiguation for Logistic Birth-Death Processes

Density dependence is important in the ecology and evolution of microbial and cancer cells. Typically, we can only measure net growth rates, but the underlying density-dependent mechanisms that give rise to the observed dynamics can manifest in birth processes, death processes, or both. Therefore, we utilize the mean and variance of cell number fluctuations to separately identify birth and death rates from time series that follow stochastic birth-death processes with logistic growth. Our method provides a novel perspective on stochastic parameter identifiability, which we validate by analyzing the accuracy in terms of the discretization bin size. We apply our method to the scenario where a homogeneous cell population goes through three stages: (1) grows naturally to its carrying capacity, (2) is treated with a drug that reduces its carrying capacity, and (3) overcomes the drug effect to restore its original carrying capacity. In each stage, we disambiguate whether it happens through the birth process, death process, or some combination of the two, which contributes to understanding drug resistance mechanisms. In the case of limited data sets, we provide an alternative method based on maximum likelihood and solve a constrained nonlinear optimization problem to identify the most likely density dependence parameter for a given cell number time series. Our methods can be applied to other biological systems at different scales to disambiguate density-dependent mechanisms underlying the same net growth rate. Mathematics Subject Classifications60J27 {middle dot} 92D25 {middle dot} 62M10 {middle dot} 60J25

ecology↗

bioRxiv2022

Noise source importance in linear stochastic models of biological systems that grow, shrink, wander, or persist

While noise is an important factor in biology, biological processes often involve multiple noise sources, whose relative importance can be unclear. Here we develop tools that quantify the importance of noise sources in a network based on their contributions to variability in a quantity of interest. We generalize the edge importance measures proposed by Schmidt and Thomas [1] for first-order reaction networks whose steady-state variance is a linear combination of variance produced by each directed edge. We show that the same additive property extends to a general family of stochastic processes subject to a set of linearity assumptions, whether in discrete or continuous state or time. Our analysis applies to both expanding and contracting populations, as well as populations obeying a martingale ("wandering") at long times. We show that the original Schmidt-Thomas edge importance measure is a special case of our more general measure, and is recovered when the model satisfies a conservation constraint ("persists"). In the growing and wandering cases we show that the choice of observables (measurements) used to monitor the process does not influence which noise sources are important at long times. In contrast, in the shrinking or persisting case, which noise sources are important depends on what is measured. We also generalize our measures to admit models with affine moment update equations, which admit additional limiting scenarios, and arise naturally after linearization. We illustrate our results using examples from cell biology and ecology: (i) a model for the dynamics of the inositol trisphospate receptor, (ii) a model for an endangered population of white-tailed eagles, and (iii) a model for wood frog dispersal. Author summaryBiological processes are frequently subject to an ensemble of independent noise sources. Noise sources produce fluctuations that propagate through the system, driving fluctuations in quantities of interest such as population size or ion channel configuration. We introduce a measure that quantifies how much variability each noise source contributes to any given quantity of interest. Using these methods, we identify which binding events contribute significantly to fluctuations in the state of a molecular signalling channel, which life history events contribute the most variability to an eagle population before and after a successful conservation effort rescued the population from the brink of extinction, and which dispersal events, at what times, matter most to variability in the recolonization of a series of ponds by wood frogs after a drought.

ecology↗

bioRxiv2021

A Comparison of Weighted Stochastic Simulation Methods

1Rare events are of particular interest in biology because rare biochemical events may be catastrophic to a biological system. To estimate the probability of rare events, several weighted stochastic simulation methods have been developed. Unfortunately, the robustness of these methods is questionable. Here, an analysis of weighted stochastic simulation methods is presented. The methods considered here fail to accomplish the task of rare event simulation, in general, suggesting that new methods are necessary to adequately study rare biological events.

systems biology↗

bioRxiv2021

Cheater suppression and spite through quorum sensing

The evolutionary consequences of quorum sensing in regulating bacterial cooperation are not fully understood. In this study, we reveal unexpected consequences of regulating public good production through quorum sensing on bacterial population dynamics, showing that quorum sensing can be a collectively harmful alternative to unregulated production. We analyze a birth-death model of bacterial population dynamics accounting for public good production and the presence of non-producing cheaters. Our model demonstrates that when demographic noise is a factor, the consequences of controlling public good production according to quorum sensing depend on the cost of public good production and the presence of non-public fitness benefits. When public good production is inexpensive, quorum sensing is a destructive alternative to unconditional production, in terms of the mean population extinction time. When costs are higher, quorum sensing becomes a constructive strategy for the producing strain, both stabilizing cooperation and decreasing the risk of population extinction.

biophysics↗

bioRxiv2021

Role of transmembrane spanning domain 1 in cystic fibrosis transmembrane conductance regulator folding

Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) protein that disrupt its folding pathway. The most common mutation causing CF is a deletion of phenylalanine at position 508 ({Delta}F508). CFTR contains five domains that each form cotranslational structures that interact with other domains as they are produced and folded. CFTR is comprised of two transmembrane spanning domains (TMDs), two nucleotide binding domains (NBDs) and a unique regulatory region (R). The first domain translated, TMD1, forms interdomain interactions with the other domains in CFTR. In TMD1, long intracellular loops extend into the cytoplasm and interact with both NBDs via coupling helices and with TMD2 via transmembrane spans (TMs). We examined mutations in TMD1 to determine the impact on individual domain and multidomain constructs. We found that mutations in a TM span or in the cytosolic ICLs interfere with specific steps in the hierarchical folding of CFTR. TM1 CF-causing mutants, G85E and G91R, directly affect TMD1, whereas most ICL1 and ICL2 mutant effects become apparent in the presence of TMD2. A single mutant in ICL2 worsened CFTR trafficking in the presence of NBD2, supporting its role in the ICL2-NBD2 interface. Mutation of hydrophobic residues in ICL coupling helices tended to increased levels of pre-TMD2 biogenic intermediates but caused ER accumulation in the presence of TMD2. This suggests a tradeoff between transient stability during translation and final structure. NBD2 increased the efficiency of mutant trafficking from the ER, consistent with stabilization of the full-length constructs. While the G85E and G91R mutants in TM1 have immediately detectable effects, most of the studied mutant effects and the {Delta}F508 mutant are apparent after production of TMD2, supporting this intermediate as a major point of recognition by protein quality control.

molecular biology↗