Biology subjects

Payne, A.

Publications and source records attributed to Payne, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Higher cortical beta oscillatory power before balance perturbations is associated with worse balance in older adults with Parkinson's Disease, but not in age-matched older adults

Elevated beta activity is hypothesized to reflect reduced flexibility in updating motor and sensory states, which may impair the rapid integration of sensory information required for balance. Therefore, we predicted that higher cortical beta power immediately before balance perturbations would be associated with poorer clinical balance performance, particularly in individuals with Parkinson's Disease (PD). Seventeen individuals with PD (median Hoehn & Yahr = 2) and eighteen neurotypical older adults stood on a translating platform while 32-channel electroencephalography was recorded. For each participant, the cortical component contributing most strongly to the perturbation-evoked N1 response, a balance-related cortical response localized to the supplementary motor area, was identified. Oscillatory beta power (13-30 Hz) during the one-second period immediately preceding perturbation onset was extracted from this N1-related cortical source and parameterized using Fitting Oscillations and One-Over-F (FOOOF). Balance ability was assessed using the Mini-Balance Evaluation Systems Test (Mini-BESTest). Beta power derived from this N1-related source did not differ between groups; however, within individuals with PD, higher pre-perturbation beta power was associated with lower Mini-BESTest scores, a relationship not observed in neurotypical older adults. A subset of older adults exhibited an additional, higher-frequency beta peak absent in PD, suggesting heterogeneity in cortical beta dynamics with aging. These findings suggest that elevated cortical beta oscillations immediately preceding balance perturbations are linked to clinically meaningful balance impairment in PD, supporting beta activity as a potential cortical biomarker of balance dysfunction in this population.

neuroscience↗

bioRxiv2026

A Scalable Cross-Modal Workflow for Linking In Vivo Neural Activity to Neuronal Cell Types via Spatial Gene Profiling

A central challenge in systems neuroscience research is to elucidate how distinct neuronal cell types coordinate to produce complex behaviors: an endeavor that requires linking their molecular identity, connectivity and activity patterns in behaving animals. Recent advances in single-cell RNA sequencing and spatial transcriptomics have revealed remarkable molecular diversity among neurons. However, most functional recording techniques, including in vivo two-photon calcium imaging, do not reveal the molecular cell identities of recorded cells. Although manual one-to-one matching between functional imaging and post hoc molecular profiling has been achieved for dozens to a few hundred neurons, these approaches are typically labor-intensive, difficult to scale, and capture only a limited fraction of cell types. Integrating these two modalities at large scale remains challenging, limiting our ability to fully understand the general logic of neural computation. Here we present a cross-modal workflow that integrates in vivo two-photon calcium imaging in behaving mice with Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH), a thick-tissue spatial transcriptomic approach. As a proof of concept, we apply this workflow to the mouse dorsal hippocampus, a brain region with high neuronal density and small cell size where manual cell matching is impractical, making it a stringent test for the accuracy and scalability of this method. Using our approach, we achieved highly accurate alignment between in vivo neural activity and ex vivo molecular cell-type identity across hundreds to thousands of neurons, enabling direct mapping of neural dynamics to molecularly defined neuronal populations. We showed that longitudinal neural recordings followed by molecular mapping reveal distinct neural activity patterns that emerge as animals learn a spatial navigation task. By linking activity patterns to molecularly defined cell types, this method provides a framework for testing whether neural representations are organized through cell-type-specific coding or distributed population activity, offering insight into the computational logic by which neural circuits generate complex behaviors.

neuroscience↗

bioRxiv2026

Modeling steady state thermoregulation of near-term human fetus

Maternal thermal strain is associated with adverse pregnancy outcomes, yet fetal temperatures cannot currently be directly measured, limiting quantification of fetal thermal strain. Here, we develop two steady-state models for estimating internal temperatures in a near-term fetus. First, we improve the only previously published human fetal thermoregulation model, deriving a closed-form solution within its simplified uniform-cylinder representation. Second, we introduce a multilayer, anatomically segmented model that resolves tissue-specific temperatures. Both couple the fetal body to central blood pool and amniotic fluid compartments and incorporate a new placenta-umbilical cord heat-exchanger representation. Predictions agree with available intrauterine scalp measurements, with fetal core and head-center temperatures approximately 0.5{degrees}C and 0.8{degrees}C above maternal core, respectively. Physiologically plausible changes in umbilical cord heat-exchanger effectiveness or blood flow increased fetal temperatures by approximately 0.3{degrees}C. These models enable estimation of otherwise inaccessible temperatures, while the multilayer formulation lays a foundation for transient, coupled maternal-fetal thermoregulation modeling.

biophysics↗

bioRxiv2026

Integrating multi-host modelling with empirical wildlife-livestock contacts reveals an essential population in a pathogen reservoir

Infections at the animal-human or wildlife-livestock interfaces have severe health and socio-economic consequences. Combined with empirical data, mathematical models can contribute to a better understanding of the reservoirs of these infections, which is a priority for mitigating their impact by using appropriate management interventions. Taking brucellosis in the Bargy massif (French Alps) as an example of a zoonosis at the wildlife-livestock interface, we developed and calibrated a multi-host model integrating data on direct and environment-mediated cross-species contacts from field observations. Estimates of the basic reproduction number (R0) allowed to identify the population of Alpine ibex (Capra ibex) and its environment as an essential host in the reservoir, driving both pathogen maintenance (within-species R0[≥]1: 1.66, 95% credible interval: 1.42-2.03) and its transmission to livestock (between-species R0>0: 0.035, 0.01-0.05). Our approach can be adapted to other multi-host pathogens, which will contribute to improve the understanding and management of these complex systems.

ecology↗

bioRxiv2026

NPAS4 refines spatial and temporal firing in CA1 pyramidal neurons

NPAS4 is an activity-dependent transcription factor that, in CA1 of the hippocampus, regulates inhibitory synapses made onto the active pyramidal neuron. In principle, NPAS4 thereby allows the past activity of a neuron to influence how it encodes information, although this has not yet been demonstrated. Here, we generated a sparse, CA1-specific knockout (KO) of NPAS4 in the mouse hippocampus and used optogenetic tagging to identify KO neurons in vivo. Recordings from intermingled wild-type (WT) and KO neurons in awake behaving animals revealed that NPAS4 deletion degrades spatial representations and temporal precision of spiking: KO neurons exhibited larger place fields with reduced in-field firing and increased out-of-field firing, less stable place fields, reduced coupling to local field potential theta oscillations, and diminished phase precession. These findings demonstrate that NPAS4 plays a crucial role in refining the spatial and temporal properties of CA1 pyramidal neuron spikes, which themselves are thought to be fundamental building blocks of more complex processes such as learning and memory.

neuroscience↗

bioRxiv2026

Translational control of CAK and Cdk T-loop phosphorylation in response to growth in yeast

Cyclin-dependent kinases (Cdks) require activating T-loop phosphorylation, a modification that is considered constitutive. Here, we examined the regulation of the Cdk-activating kinase, Cak1, in budding yeast. We measured Cak1 levels and the activating T169 phosphorylation of Cdc28 (the budding yeast Cdk) across various nutrient environments. We found that the abundance of Cak1 and the T169 phosphorylation is significantly reduced in cells that are proliferating very slowly or have entered quiescence. A small upstream open reading frame (uORF) in the CAK1 transcript represses Cak1 synthesis, especially in poor growth conditions. Eliminating the uORF increased Cak1 levels but did not alter proliferation kinetics under most laboratory contexts. Instead, it reduced the viability of quiescent cells and the fitness of slowly proliferating chemostat cultures. In cells lacking several type 2C protein phosphatases, which remove the T169 phosphorylation, there was a pronounced acceleration of initiation of cell division in the absence of the uORF in CAK1. Our results suggest an unexpected layer of control, impinging on the activating phosphorylation of the Cdk. The uORF-mediated repression of Cak1 synthesis directly couples protein synthesis to the activity of the core cell cycle machinery. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/702203v1_ufig1.gif" ALT="Figure 1"> View larger version (12K): org.highwire.dtl.DTLVardef@6da10org.highwire.dtl.DTLVardef@1d657a1org.highwire.dtl.DTLVardef@1133e3corg.highwire.dtl.DTLVardef@5adbd8_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2024

Lessons learned during the journey of data: from experiment to model for predicting kinase affinity, selectivity, polypharmacology, and resistance

Recent advances in machine learning (ML) are reshaping drug discovery. Structure-based ML methods use physically-inspired models to predict binding affinities from protein:ligand complexes. These methods promise to enable the integration of data for many related targets, which addresses issues related to data scarcity for single targets and could enable generalizable predictions for a broad range of targets, including mutants. In this work, we report our experiences in building KinoML, a novel framework for ML in target-based small molecule drug discovery with an emphasis on structure-enabled methods. KinoML focuses currently on kinases as the relative structural conservation of this protein superfamily, particularly in the kinase domain, means it is possible to leverage data from the entire superfamily to make structure-informed predictions about binding affinities, selectivities, and drug resistance. Some key lessons learned in building KinoML include: the importance of reproducible data collection and deposition, the harmonization of molecular data and featurization, and the choice of the right data format to ensure reusability and reproducibility of ML models. As a result, KinoML allows users to easily achieve three tasks: accessing and curating molecular data; featurizing this data with representations suitable for ML applications; and running reproducible ML experiments that require access to ligand, protein, and assay information to predict ligand affinity. Despite KinoML focusing on kinases, this framework can be applied to other proteins. The lessons reported here can help guide the development of platforms for structure-enabled ML in other areas of drug discovery.

biophysics↗

bioRxiv2023

Development of an MR-guided focused ultrasound (MRgFUS) lesioning approach for small and deep structures in the rat brain

ObjectiveHigh-intensity magnetic resonance-guided focused ultrasound (MRgFUS) is a noninvasive therapy to lesion brain tissue, used clinically in patients and preclinically in several animal models. Challenges with focused ablation in rodent brains can include skull and near-field heating and accurately targeting small and deep brain structures. We overcame these challenges by creating a novel method consisting of a craniectomy skull preparation, a high-frequency transducer (3 MHz) with a small ultrasound focal spot, a transducer positioning system with an added manual adjustment of [~]0.1 mm targeting accuracy, and MR acoustic radiation force imaging for confirmation of focal spot placement. MethodsThe study consisted of two main parts. First, two skull preparation approaches were compared. A skull thinning approach (n=7 lesions) was compared to a craniectomy approach (n=22 lesions), which confirmed a craniectomy was necessary to decrease skull and near-field heating. Second, the two transducer positioning systems were compared with the fornix chosen as a subcortical ablation target. We evaluated the accuracy of targeting using a high-frequency transducer with a small ultrasound focal spot and MR acoustic radiation force imaging. ResultsComparing a motorized adjustment system ([~]1 mm precision, n=17 lesions) to the motorized system with an added micromanipulator ([~]0.1 mm precision, n=14 lesions), we saw an increase in the accuracy of targeting the fornix by 133%. The described work allows for repeatable and accurate targeting of small and deep structures in the rodent brain, such as the fornix, enabling the investigation of neurological disorders in chronic disease models.

bioengineering↗

bioRxiv2023

Precise cortical contributions to feedback sensorimotor control during reactive balance

The role of the cortex in shaping automatic whole-body motor behaviors such as walking and balance is poorly understood. Gait and balance are typically mediated through subcortical circuits, with the cortex becoming engaged as needed on an individual basis by task difficulty and complexity. However, we lack a mechanistic understanding of how increased cortical contribution to whole-body movements shapes motor output. Here we use reactive balance recovery as a paradigm to identify relationships between hierarchical control mechanisms and their engagement across balance tasks of increasing difficulty in young adults. We hypothesize that parallel sensorimotor feedback loops engaging subcortical and cortical circuits contribute to balance-correcting muscle activity, and that the involvement of cortical circuits increases with balance challenge. We decomposed balance-correcting muscle activity based on hypothesized subcortically- and cortically-mediated feedback components driven by similar sensory information, but with different loop delays. The initial balance-correcting muscle activity was engaged at all levels of balance difficulty. Its onset latency was consistent with subcortical sensorimotor loops observed in the lower limb. An even later, presumed, cortically-mediated burst of muscle activity became additionally engaged as balance task difficulty increased, at latencies consistent with longer transcortical sensorimotor loops. We further demonstrate that evoked cortical activity in central midline areas measured using electroencephalography (EEG) can be explained by a similar sensory transformation as muscle activity but at a delay consistent with its role in a transcortical loop driving later cortical contributions to balance-correcting muscle activity. These results demonstrate that a neuromechanical model of muscle activity can be used to infer cortical contributions to muscle activity without recording brain activity. Our model may provide a useful framework for evaluating changes in cortical contributions to balance that are associated with falls in older adults and in neurological disorders such as Parkinsons disease.

neuroscience↗

bioRxiv2023

Assessing the dynamics of Mycobacterium bovis infection in three French badger populations

The Sylvatub system is a national surveillance program established in 2011 in France to monitor infections caused by Mycobacterium bovis, the main etiologic agent of bovine tuberculosis, in wild species. This participatory program, involving both national and local stakeholders, allowed us to monitor the progression of the infection in three badger populations in clusters covering between 3222 km2 and 7698 km2 from 2013 to 2019. In each cluster, badgers were trapped and tested for M. bovis. Our first aim was to describe the dynamics of the infection in these clusters. We developed a Bayesian model of prevalence accounting for the spatial structure of the cases, the imperfect and variable sensitivity of the diagnostic tests, and the correlation of the infection status of badgers in the same commune caused by local factors (e.g., social structure and proximity to infected farms). This model revealed that the prevalence increased with time in one cluster (Dordogne/Charentes), decreased in the second cluster (Burgundy), and remained stable in the third cluster (Bearn). In all the clusters, the infection was strongly spatially structured, whereas the mean correlation between the infection status of the animals trapped in the same commune was negligible. Our second aim was to develop indicators for monitoring M. bovis infection by stakeholders of the program. We used the model to estimate, in each cluster, (i) the mean prevalence level at mid-period, and (ii) the proportion of the badger population that became infected in one year. We then derived two indicators of these two key quantities from a much simpler regression model, and we showed how these two indicators could be easily used to monitor the infection in the three clusters. We showed with simulations that these two simpler indicators were good approximations of these key quantities.

ecology↗

bioRxiv2023

Icarust, a real-time simulator for Oxford Nanopore adaptive sampling.

1SummaryOxford Nanopore Technologies (ONT) sequencers enable real-time generation of sequence data, which allows for concurrent analysis during a run. Adaptive sampling leverages this real-time capability in extremis, rejecting or accepting reads for sequencing based on assessment of the sequence from the start of each read. This functionality is provided by ONTs software, MinKNOW (https://community.nanoporetech.com/downloads). Designing and developing software to take advantage of adaptive sampling can be expensive due to the cost of using real sequencing consumables, using precious samples and preparing sequencing libraries. MinKNOW addresses this issue in part by providing the ability to replay previously sequenced runs for testing, using its playback functionality. However, as we have illustrated here, the sequencing output only partially changes in response to adaptive sampling instructions. Here we present Icarust, a tool enabling more accurate approximations of sequencing runs. Icarust recreates all the required endpoints of MinKNOW to perform adaptive sampling and writes output compatible with current base-callers and analysis pipelines. Icarust is capable of serving nanopore signal to simulate a MinION or PromethION flow cell experiment from any reference genome using either R9 or R10 pore signal. We show that simulating sequencing runs with Icarust provides a realistic testing and development environment for software exploiting the real-time nature of Nanopore sequencing. Availability and ImplementationAll code is open source and freely available here - https://github.com/LooseLab/Icarust. Icarust is implemented in Rust, with an easy to install and use docker container available. Supplementary InformationSupplementary information is available here - https://github.com/Adoni5/Icarust_paper.

genomics↗

bioRxiv2022

The Nanog epigenetic remodeling complex was essential to vertebrate mesoderm evolution

Pluripotency defines the unlimited potential of cells in the primitive ectoderm of vertebrate embryos, from which all adult somatic cells and germ cells are derived. Understanding how the programing of pluripotency evolved has been obscured by the study of early development in models from lower vertebrates in which pluripotency is not conserved. Here we investigated how the axolotl ortholog of the mammalian core pluripotency factor NANOG, programs pluripotency during axolotl development to model the tetrapod ancestor from which terrestrial vertebrates evolved. We show that in axolotl primitive ectoderm (animal caps; AC) NANOG synergizes with NODAL activity and the epigenetic modifying enzyme DPY30 to direct the deposition of H3K4me3 in chromatin prior to the waves of transcription required for lineage commitment and developmental progression. We show that the interaction of NANOG and NODAL with DPY30 is required to direct development downstream of pluripotency and this is conserved in axolotls and human. These data demonstrate that the interaction of NANOG and NODAL signaling represents the basal state of vertebrate pluripotency.

developmental biology↗

bioRxiv2021

Barcode aware adaptive sampling for Oxford Nanopore sequencers.

Adaptive sampling enables selection of individual DNA molecules from sequencing libraries, a unique property of nanopore sequencing. Here we develop our adaptive sampling tool readfish to become "barcode-aware" enabling selection of different targets within barcoded samples or filtering out individual barcodes. We show that multiple human genomes can be assessed for copy number and structural variation on a single sequencing flow cell using sample specific customised target panels on both GridION and PromethION devices.

genomics↗

bioRxiv2021

Real-time monitoring and analysis of SARS-CoV-2 nanopore sequencing with minoTour.

MotivationThe ongoing SARS-CoV-2 pandemic has demonstrated the utility of real-time analysis of sequencing data, with a wide range of databases and resources for analysis now available. Here we show how the real-time nature of Oxford Nanopore Technologies sequencers can accelerate consensus generation, lineage and variant status assignment. We exploit the fact that multiplexed viral sequencing libraries quickly generate sufficient data for the majority of samples, with diminishing returns on remaining samples as the sequencing run progresses. We demonstrate methods to determine when a sequencing run has passed this point in order to reduce the time required and cost of sequencing. ResultsWe extended MinoTour, our real-time analysis and monitoring platform for nanopore sequencers, to provide SARS-CoV2 analysis using ARTIC network pipelines. We additionally developed an algorithm to predict which samples will achieve sufficient coverage, automatically running the ARTIC medaka informatics pipeline once specific coverage thresholds have been reached on these samples. After testing on run data, we find significant run time savings are possible, enabling flow cells to be used more efficiently and enabling higher throughput data analysis. The resultant consensus genomes are assigned both PANGO lineage and variant status as defined by Public Health England. Samples from within individual runs are used to generate phylogenetic trees incorporating optional background samples as well as summaries of individual SNPs. As minoTour uses ARTIC pipelines, new primer schemes and pathogens can be added to allow minoTour to aid in real-time analysis of pathogens in the future. Availability and ImplementationSource code and documentation is available at https://github.com/LooseLab/minotourapp. Supplementary informationSupplementary data are available from https://github.com/LooseLab/artic_minotour_analyses.

bioinformatics↗

bioRxiv2021

MinoTour, real-time monitoring and analysis for Nanopore Sequencers.

SummaryMinoTour offers a LIMS system for Oxford Nanopore Technology (ONT) sequencers, with real-time metrics and analysis available permanently for review. Integration of unique real-time automated analysis can reduce the time required to answer biological questions, including mapping and classification of sequence whilst a run is in progress. Real-time sequence data requires new methods of analysis which do not wait for the completion of a run and MinoTour provides a framework to allow users to exploit these features. Availability and ImplementationSource code and documentation are available at https://github.com/LooseLab/minotourcli and https://github.com/LooseLab/minotourapp. Docker images are available from https://hub.docker.com/r/adoni5/, and can be installed using a preconfigured docker-compose script at https://github.com/LooseLab/minotour-docker. An example server is available at http://137.44.59.170.

bioinformatics↗

bioRxiv2021

Lower cognitive set shifting ability is associated with stiffer balance recovery behavior and larger perturbation-evoked cortical responses in older adults

1.The mechanisms underlying associations between cognitive set shifting impairments and balance dysfunction are unclear. Cognitive set shifting refers to the ability to flexibly adjust behavior to changes in task rules or contexts, which could be involved in flexibly adjusting balance recovery behavior to different contexts, such as the direction the body is falling. Prior studies found associations between cognitive set shifting impairments and severe balance dysfunction in populations experiencing frequent falls. The objective of this study was to test whether cognitive set shifting ability is expressed in successful balance recovery behavior in older adults with high clinical balance ability (N=19, 71 {+/-} 7 years, 6 female). We measured cognitive set shifting ability using the Trail Making Test and clinical balance ability using the miniBESTest. For most participants, cognitive set shifting performance (Trail Making Test B-A = 37 {+/-} 20s) was faster than normative averages (46s for comparable age and education levels), and balance ability scores (miniBESTest = 25 {+/-} 2 / 28) were above the threshold for fall risk (23 for people between 70-80 years). Reactive balance recovery in response to support-surface translations in anterior and posterior directions was assessed in terms of body motion, muscle activity, and brain activity. Across participants, lower cognitive set shifting ability was associated with smaller peak center of mass displacement during balance recovery, lower directional specificity of late phase balance-correcting muscle activity (i.e., greater antagonist muscle activity 200-300ms after perturbation onset), and larger cortical N1 responses (100-200ms). None of these measures were associated with clinical balance ability. Our results suggest that cognitive set shifting ability is expressed in balance recovery behavior even in the absence of profound clinical balance disability. Specifically, our results suggest that lower flexibility in cognitive task performance is associated with lower ability to incorporate the directional context into the cortically-mediated later phase of the motor response. The resulting antagonist activity and stiffer balance behavior may help explain associations between cognitive set shifting impairments and frequent falls.

neuroscience↗

bioRxiv2020

Making the invisible enemy visible

During the COVID-19 pandemic, structural biologists rushed to solve the structures of the 28 proteins encoded by the SARS-CoV-2 genome in order to understand the viral life cycle and enable structure-based drug design. In addition to the 204 previously solved structures from SARS-CoV-1, 548 structures covering 16 of the SARS-CoV-2 viral proteins have been released in a span of only 6 months. These structural models serve as the basis for research to understand how the virus hijacks human cells, for structure-based drug design, and to aid in the development of vaccines. However, errors often occur in even the most careful structure determination - and may be even more common among these structures, which were solved quickly and under immense pressure. The Coronavirus Structural Task Force has responded to this challenge by rapidly categorizing, evaluating and reviewing all of these experimental protein structures in order to help downstream users and original authors. In addition, the Task Force provided improved models for key structures online, which have been used by Folding@Home, OpenPandemics, the EU JEDI COVID-19 challenge and others.

molecular biology↗

bioRxiv2020

A multi-omic integrative scheme characterizes tissues of action at loci associated with type 2 diabetes

Resolving the molecular processes that mediate genetic risk remains a challenge as most disease-associated variants are non-coding and functional and bioinformatic characterization of these signals requires knowledge of the specific tissues and cell-types in which they operate. To address this challenge, we developed a framework for integrating tissue-specific gene expression and epigenomic maps (primarily from tissues involved in insulin secretion and action) to obtain tissue-of-action (TOA) scores for each association signal by systematically partitioning posterior probabilities from Bayesian fine-mapping. We applied this scheme to credible set variants for 380 association signals from a recent GWAS meta-analysis of type 2 diabetes (T2D) in Europeans. The resulting tissue profiles underscored a predominant role for pancreatic islets and, to a lesser extent, subcutaneous adipose and liver, that was largely attributable to enhancer elements and transcribed regions, particularly among signals with greater fine-mapping resolution. We incorporated resulting TOA scores into a rule-based classifier, and validated the tissue assignments through comparison with data from cis-eQTL enrichment, functional fine-mapping, RNA co-expression, and patterns of physiological association. In addition to implicating signals with a single tissue-of-action, we also found evidence for signals with shared effects in multiple tissues as well as distinct tissue profiles between independent signals within heterogeneous loci. Lastly, we demonstrated that TOA scores can be directly coupled with eQTL colocalization to further resolve effector transcripts at T2D signals. This framework guides mechanistic inference by directing functional validation studies to the most relevant tissues and can gain power as fine-mapping resolution and cell-specific annotations become richer. This method is generalizable to all complex traits with relevant annotation data and is made available as an R package.

genetics↗