Biology subjects

Walker, S. M.

Publications and source records attributed to Walker, S. M..

9 recordsLinked to original sources

bioRxiv2026

Nitric oxide synthase inhibition and biological sex define different cardiac responses to cardiometabolic stress in older mice.

Background: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome associated with ageing, obesity and impaired nitric oxide signalling. Preclinical models often do not capture the sex-specific and cardiometabolic features observed in patients. We hypothesised that biological sex and the degree of nitric oxide synthase (NOS) inhibition would influence development of HFpEF-like versus HFrEF-like phenotypes. Methods and Results: Male and female C57BL/6J mice (>24 weeks) were exposed to a high-fat diet (HFD) combined with low-dose (0.3 g/L; female only) or high-dose (0.5 g/L; male and female) NOS inhibition using N({omega})-nitro-L-arginine methyl ester (L-NAME) for 15 weeks. Female mice receiving low-dose L-NAME+HFD developed a HFpEF-like phenotype characterised by impaired diastolic function, exercise intolerance and preserved systolic function. Increasing NOS inhibition did not worsen diastolic dysfunction but induced inflammatory and stress-associated transcriptional pathways in female hearts. In contrast, male mice given high-dose L-NAME+HFD developed hypertension, elevated ventricular pressures and impaired systolic function, consistent with a HFrEF-like phenotype. Despite different cardiac phenotypes, circulating lipidomic profiling revealed broadly conserved sphingolipid and phospholipid remodelling, with sex-specific regulation of phosphatidylinositol and lysophosphatidylcholine species. Transcriptomic analyses identified shared regulation of extracellular matrix, calcium-handling and metabolic pathways, whereas greater NOS inhibition was associated with transcriptional signatures related to inflammatory signalling, cellular stress responses and mitochondrial homeostasis. Conclusions: Cardiometabolic stress does not produce a uniform HF phenotype. Instead, biological sex and the degree of NOS inhibition direct distinct functional and molecular remodelling trajectories, identifying HFpEF-like dysfunction as one of several potential cardiac responses to cardiometabolic injury.

pathology↗

bioRxiv2026

Substrate and target selectivity of 4'-fluoroadenosine against viral and host polymerases

Developing safe and effective treatments against emerging RNA viruses is an important goal in pandemic preparedness efforts. 4'-fluorouridine (4'-FlU) is a broad-spectrum antiviral that was shown to inhibit viral RNA-dependent RNA polymerases (RdRps). Given its notable range of antiviral activity, this class of nucleoside analogs warrants further investigation. Here, we studied the antiviral activity and underlying mechanism of inhibition of 4'-fluoroadenosine (4'-FlA). Like 4'-FlU, 4'-FlA demonstrates a broad-spectrum of antiviral activity against eight prototypic viruses representing diverse families. Enzyme kinetics show that the triphosphate (4'-FlA-TP) is efficiently incorporated by viral RdRps. A cryo-EM structure of RdRp of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in complex with double-stranded RNA and the incorporated monophosphate (4'-FlA-MP) characterizes interactions at the active site. The incorporated analog elicits heterogeneous inhibition patterns in primer extension reactions. In contrast, templates with embedded 4'-FlA-MP inhibit incorporation of complementary UTP across the viral RdRps. However, incorporation of 4'-FIA-TP is not limited to viral polymerases and likewise includes human mitochondrial RNA polymerase. These results demonstrate the general potential for 4'-fluorinated nucleotides as antiviral drugs and guide the development of more selective derivatives for medical use in appropriate settings.

microbiology↗

bioRxiv2024

Mechanosensory representation of wing deformations

Locomotor control is facilitated by mechanosensory inputs that report how the body interacts with a physical medium. Effective representation of compliant wing deformations is particularly challenging due to the many degrees of freedom. Structural configurations can constrain the stimulus space, and strategic placement of sensors can simplify computation. Here, we measured and modelled wing displacement fields and characterized spatiotemporal encoding of the wing mechanosensors. Our data show how dragonfly wing architecture prescribes deformation modes consistent across models and measurements. We found that the wings state under normal flapping conditions is detected by the spike timing of few sensors, with additional sensors recruited under perturbation. The functional integration of wing biomechanics and sensor placement enables a straightforward solution for information transfer. Significance StatementMany systems in nature precisely control highly deformable structures, yet monitoring structural deformations has posed a significant challenge for biologists and engineers. By measuring and modelling the intricate structure of compliant dragonfly wings, we demonstrate an elegant solution for mechanosensory representation. We show that the functional integration of natural wing biomechanics and sensor placement provides a straightforward solution for information transfer. Wing morphology passively constrains the range of natural deformations, producing strain patterns that align with sensor locations, allowing them to monitor the wing using a simple timing-dependent encoding strategy. The way insects monitor aerodynamic and inertial forces via wing deformations during flight could apply to many sensory systems in nature and inspire artificial neural networks for controlling diverse dynamic systems.

neuroscience↗

bioRxiv2024

Mechanism and spectrum of inhibition of a 4'-cyano modified nucleotide analog against diverse RNA polymerases of prototypic respiratory RNA viruses

The development of safe and effective broad-spectrum antivirals that target the replication machinery of respiratory viruses is of high priority in pandemic preparedness programs. Here, we studied the mechanism of action of a newly discovered nucleotide analog against diverse RNA-dependent RNA polymerases (RdRp) of prototypic respiratory viruses. GS-646939 is the active 5'-triphosphate (TP) metabolite of a 4'-cyano modified C-adenosine analog phosphoramidate prodrug GS-7682. Enzyme kinetics show that the RdRps of human rhinovirus type 16 (HRV-16) and enterovirus 71 (EV-71) incorporate GS-646939 with unprecedented selectivity; GS-646939 is incorporated 20-50-fold more efficiently than its natural ATP counterpart. The RdRp complex of respiratory syncytial virus (RSV) and human metapneumovirus (HMPV) incorporate GS-646939 and ATP with similar efficiency. In contrast, influenza B RdRp shows a clear preference for ATP and human mitochondrial RNA polymerase (h-mtRNAP) does not show significant incorporation of GS-646939. Once incorporated into the nascent RNA strand, GS-646939 acts as a chain-terminator although higher NTP concentrations can partially overcome inhibition for some polymerases. Modeling and biochemical data suggest that the 4'-modification inhibits RdRp translocation. Comparative studies with GS-443902, the active triphosphate form of the 1'-cyano modified prodrugs remdesivir and obeldesivir, reveal not only different mechanisms of inhibition, but also differences in the spectrum of inhibition of viral polymerases. In conclusion, 1'-cyano and 4'-cyano modifications of nucleotide analogs provide complementary strategies to target the polymerase of several families of respiratory RNA viruses.

biochemistry↗

bioRxiv2024

Motion vision is tuned to maximize sensorimotor energy transfer in blowfly flight

Insects achieve agile flight using a sensor-rich control architecture whose embodiment eliminates the need for complex computation. For example, their visual systems are tuned to detect the optic flow associated with specific self-motions, but what functional principle does this tuning embed and how does it facilitate motor control? Here we test the hypothesis that evolution co-tunes physics and physiology by aligning an insects sensors to its dynamically-significant modes of self-motion. Specifically, we show that the tuning of the blowfly motion vision system maximizes the flow of signal energy from gust disturbances and control inputs to sensor outputs, jointly optimizing observability and controllability. This evolutionary principle differs from the conventional engineering-design paradigm of optimizing state estimation, with implications for novel robotic systems combining high performance with low power-consumption.

neuroscience↗

bioRxiv2023

Oligosaccharide production and signaling correlate with delayed flowering in an Arabidopsis genotype grown and selected in high

Since industrialization began, atmospheric CO2 ([CO2]) has increased from 270 to 415 ppm and is projected to reach 800-1000 ppm this century. Some Arabidopsis ecotypes delayed flowering in elevated [CO2] relative to current [CO2], while others showed no change or accelerations. To predict genotype-specific flowering behaviors, we must understand the mechanisms driving flowering response to rising [CO2]. [CO2] changes alter photosynthesis and carbohydrates in C3 plants. Plants sense carbohydrate levels and exogenous carbohydrate application influences flowering time and flowering transcript levels. We asked how organismal changes in carbohydrates and transcription correlate with changes in flowering time under elevated [CO2]. We used a genotype (SG) of Arabidopsis that was selected for high fitness at elevated [CO2] (700 ppm). SG delays flowering under elevated [CO2] (700 ppm) relative to current [CO2] (400 ppm). We compared SG to a closely related control genotype (CG) that shows no [CO2]- induced flowering change. We compared metabolomic and transcriptomic profiles in these genotypes at current and elevated [CO2] to assess correlations with flowering in these conditions. While both genotypes altered carbohydrates in response to elevated [CO2], SG had higher levels of sucrose than CG and showed a stronger increase in glucose and fructose in elevated [CO2]. Both genotypes demonstrated transcriptional changes, with CG increasing genes related to fructose 1,6-bisphosphate breakdown, amino acid synthesis, and secondary metabolites; and SG decreasing genes related to starch and sugar metabolism, but increasing genes involved in oligosaccharide production and sugar modifications. Genes associated with flowering regulation within the photoperiod, vernalization, and meristem identity pathways were altered in these genotypes. Elevated [CO2] may act through carbohydrate changes to influence transcription in both genotypes and delayed flowering in SG. Changes in the oligosaccharide pool may contribute to delayed flowering in SG. This work extends the literature exploring genotypic-specific flowering responses to elevated [CO2].

plant biology↗

bioRxiv2020

A semi-empirical aerodynamic model of insect flight forces

Blade element modelling provides a quick analytical method for estimating the aerodynamic forces produced during insect flight, but such models have yet to be tested rigorously using kinematic data recorded from free-flying insects. This is largely because of the paucity of detailed free-flight kinematic data, but also because analytical limitations in existing blade element models mean that they cannot incorporate the complex three-dimensional movements of the wings and body that occur during insect flight. Here, we present a blade element model with empirically-fitted aerodynamic force coefficients that incorporates the full three-dimensional wing kinematics of manoeuvring Eristalis hoverflies, including torsional deformation of their wings. The two free parameters were fitted to a large free-flight dataset comprising N = 26, 541 wingbeats, and the fitted model captured approximately 80% of the variation in the stroke-averaged forces in the sagittal plane. We tested the robustness of the model by subsampling the data, and found little variation in the parameter estimates across subsamples comprising 10% of the flight sequences. The simplicity and generality of the model that we present is such that it can be readily applied to kinematic datasets from other insects, and also used for the study of insect flight dynamics.

biophysics↗

bioRxiv2019

Motor output and control input in flapping flight: a compact model of the deforming wing kinematics of manoeuvring hoverflies

Insects are conventionally modelled as controlling flight by varying a few summary kinematic parameters that are defined on a per-wingbeat basis, such as the stroke amplitude, mean stroke angle, and mean wing pitch angle. Nevertheless, as insects have tens of flight muscles and vary their kinematics continuously, the true dimension of their control input subspace is likely to be much higher. Here we present a compact description of the deforming wing kinematics of 36 manoeuvring Eristalis hoverflies, applying functional principal components analysis to Fourier series fits of the wingtip position and wing twist measured over 26,541 wingbeats. This analysis offers a high degree of data reduction, in addition to insight into the natural kinematic couplings. We used statistical resampling techniques to verify that the principal components were repeatable features of the data, and analysed their coefficient vectors to provide insight into the form of these natural couplings. Conceptually, the dominant principal components provide a natural set of control input variables that span the control input subspace of this species, but they can also be thought of as output states of the flight motor. This functional description of the wing kinematics is appropriate to modelling insect flight as a form of limit cycle control.

animal behavior and cognition↗

bioRxiv2019

Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning

Image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data. Here we predict consensus molecular subtypes (CMS) of colorectal cancer (CRC) from standard H&E sections using deep learning. Domain adversarial training of a neural classification network was performed using 1,553 tissue sections with comprehensive multi- omic data from three independent datasets. Image-based consensus molecular subtyping (imCMS) accurately classified CRC whole-slide images and preoperative biopsies, spatially resolved intratumoural heterogeneity and provided accurate secondary calls with higher discriminatory power than bioinformatic prediction. In all three cohorts imCMS established sensible classification in CMS unclassified samples, reproduced expected correlations with (epi)genomic alterations and effectively stratified patients into prognostic subgroups. Leveraging artificial intelligence for the development of novel biomarkers extracted from histological slides with molecular and biological interpretability has remarkable potential for clinical translation.

cancer biology↗