Biology subjects

Hughes, L. E.

Publications and source records attributed to Hughes, L. E..

6 recordsLinked to original sources

bioRxiv2026

From group-level neurophysiological biomarkers to individual-level phenotyping to identify mechanisms of neurodegenerative disease

Precision medicine approaches require physiological effects to be informative when translated to the individual. Reliable group differences may have limited individual value when distributions overlap, mechanisms are heterogeneous, or patients differ in phenotype. A feature can differ between group means and still overlap heavily across individuals Moreover, combinations of physiological abnormalities may reveal subject-level structure that is not captured by any single marker at the group level. We evaluate the translation between group- and individual-level features derived from resting-state magnetoencephalography (MEG) using behavioural-variant frontotemporal dementia (bvFTD) and progressive supranuclear palsy (PSP) as demonstrator conditions. These illnesses have distinct molecular pathology but share the pressing need for therapeutic development and have partially overlapping clinical and physiological features. We combine clinical phenotype, power spectral density (PSD), and latent network mechanisms inferred by dynamic causal modelling (DCM) to compare groups and to access their individuals mapping translations. We used classification as an exploratory probe of how group-defined physiological features from 74 healthy controls, 45 participants with bvFTD and 55 participants with PSP support individual assignment. Clinical scores showed strong individual-level translation, consistent with clinical diagnostic definitions (e.g, controls-vs-PSP accuracy 0.94; bvFTD-vs-PSP accuracy 0.83). MEG spectra feature classified individuals weakly (accuracy ~0.6), despite group level re-organization (e.g., reduced beta-band and increased fronto-insular alpha-phase/beta-amplitude coupling in bvFTD). Inferred biophysical parameters gave intermediate performance (e.g. PSP-vs-control accuracy 0.70; bvFTD-vs-PSP accuracy 0.74) while retaining mechanistic interpretability. Using this approach, experimental medicine studies of neurological disease can formally trade between mechanistic insight and classification performance, in using biomarkers that can account for individual heterogeneity within and between diagnostic groups.

bioengineering↗

bioRxiv2025

Apathy as a Loss of Prior Precision on Action Outcomes

Apathy is common in neurological disease, associated with poor prognosis and limited treatments. Current models posit that goal-directed actions are reduced because costs or effort outweigh the expected reward. We highlight an alternative account of apathy, based on the reduction in precision of prior beliefs about action outcomes. In this preregistered study, we test the hypothesis that precision is encoded in the GABAergic gain of prefrontal superficial pyramidal neurons. Fifty healthy adults undertook a goal-directed task during magnetoencephalography. Estimates of synaptic efficacy or gain were obtained by dynamic causal modelling of induced responses. There was strong evidence of a negative correlation between prior precision and apathy (Bayes Factor=12, p<0.01), and that prior precision was associated with gain in prefrontal and premotor neuronal populations (Posterior probability>0.99). The importance of prior precision and GABAergic gain for goal-directed actions opens new avenues to advance the understanding and treatment of apathy.

neuroscience↗

bioRxiv2024

Investigating Novel Streptomyces Bacteriophage Endolysins as Potential Antimicrobial Agents

BackgroundAs antibiotic resistance has become a major global threat; the World Health Organization (WHO) has urgently called for alternative strategies for control of bacterial infections. Endolysin, a phage-encoded protein, can degrade bacterial peptidoglycan (PG) and disrupt bacterial growth. According to the WHO, there are only three endolysin products currently in clinical phase development. In this study we explore novel endolysins from Streptomyces phages as only a few of them have been experimentally characterized. Using several bioinformatics tools, we identified nine different functional domain combinations from 250 Streptomyces phages putative endolysins. LazerLemon gp35 (CHAP; LL35lys), Nabi gp26 (amidase; Nb26lys), and Tribute gp42 (PGRP/amidase; Tb42lys) were selected for experimental studies. We hypothesized that (1) the proteins of interest will have the ability to degrade purified PG, and (2) the proteins will have potential antimicrobial activity against bacteria from families of importance in antibiotic resistance, such as ESKAPE safe relatives (Enterococcus raffinosus, Staphylococcus epidermidis, Klebsiella aerogenes, Acinetobacter baylyi, Pseudomonas putida, and Escherichia coli). ResultsLL35lys, Nb26lys, and Tb42lys exhibit PG-degrading activity on zymography and hydrolysis assay. The enzymes (100 {micro}g/mL) can reduce PG turbidity to 32-40%. The killing assay suggests that Tb42lys has a broader range (E. coli, P. putida, A. baylyi and K. aerogenes). While Nb26lys better attacks Gram-negative than Gram-positive bacteria, LL35lys can only reduce the growth of the Gram-positive ESKAPE strains but does so effectively with a low MIC90 of 2 {micro}g/mL. A higher concentration ([≥]300 {micro}g/mL) of Nb26lys is needed to inhibit P. putida and K. aerogenes. ConclusionFrom 250 putative endolysins, bioinformatic methods were used to select three putative endolysins for cloning and study: LL35lys, Nb26lys, and Tb42lys. All have shown PG-degrading activity, a critical function of endolysin. With a low MIC, LL35lys shows activity for the Gram-positive ESKAPE strains, while Nb26lys and Tb42lys are active against the Gram-negatives. Therefore, endolysins from Streptomyces phage have potential as possible antimicrobial agents against ESKAPE bacteria.

microbiology↗

bioRxiv2020

Dimerization of a membrane transporter is driven by differential energetics of lipid solvation of dissociated and associated states

Over two-thirds of integral membrane proteins of known structure assemble into oligomers. Yet, the forces that drive the association of these proteins remain to be delineated, as the lipid bilayer is a solvent environment that is both structurally and chemically complex. In this study we reveal how the lipid solvent defines the dimerization equilibrium of the CLC-ec1 Cl-/H+ antiporter. Integrating experimental and computational approaches, we show that monomers associate to avoid a thinned-membrane defect caused by their exposed dimerization interfaces. In this defect, lipids are strongly tilted and less densely packed than in the bulk, with a larger degree of entanglement between opposing leaflets and greater water penetration into the bilayer interior. Dimerization restores the membrane to a near-native state and therefore, appears to be driven by the larger free-energy cost of lipid solvation of the dissociated protomers. Supporting this theory, we demonstrate that addition of short-chain lipids strongly shifts the dimerization equilibrium towards the monomeric state, and show that the cause of this effect is that these lipids preferentially solvate the defect. Importantly, we show that this shift requires only minimal quantities of short-chain lipids, with no measurable impact on either the macroscopic physical state of the membrane or the proteins biological function. Based on these observations, we posit that free-energy differentials for local lipid solvation define membrane-protein association equilibria. With this, we argue that preferential lipid solvation is a plausible cellular mechanism for lipid regulation of oligomerization processes, as it can occur at low concentrations and does not require global changes in membrane properties. IMPACT STATEMENTDifferences in the lipid solvation energetics of associated and dissociated states is a primary driving force for membrane protein oligomerization, presenting a molecular mechanism for lipid regulation in biology.

biophysics↗

bioRxiv2019

GABA-ergic dynamics in human frontotemporal networks confirmed by pharmaco-magnetoencephalography.

To bridge the gap between preclinical cellular models of disease and in vivo imaging of human cognitive network dynamics, there is a pressing need for informative biophysical models. Here we assess dynamic causal models (DCM) of cortical network responses, inverted to magnetoencephalographic observations during an auditory oddball roving paradigm in healthy adults. This paradigm induces robust perturbations that permeate frontotemporal networks, including an evoked mismatch negativity response and transiently induced oscillations. Here, we probe GABAergic influences of the networks using double-blind placebo-controlled randomised-crossover administration of the GABA re-uptake inhibitor, tiagabine (oral, 10mg) in healthy older adults. We demonstrate the facility of conductance-based neural mass mean-field models, incorporating local synaptic connectivity, to investigate laminar-specific and GABAergic mechanisms of the auditory response. The neuronal model accurately recapitulated the observed magnetoencephalographic data. Using parametric empirical Bayes for optimal model inversion across both sessions, we identify the effect of tiagabine on GABAergic modulation of deep pyramidal and interneuronal cell populations. Moreover, in keeping with the hierarchical coding of beliefs and sensory evidence, we found a transition of the main GABAergic drug effects from auditory cortex in standard trials to prefrontal cortex in deviant trials. The successful integration of pharmaco-magnetoencephalography with dynamic causal models of frontotemporal networks provides a potential platform on which to evaluate the effects of disease and pharmacological interventions.\n\nSignificance StatementUnderstanding human brain function and developing new treatments require good models of brain function. We tested a detailed generative model of cortical microcircuits that accurately reproduced human magnetoencephalography, to quantify network dynamics and connectivity in frontotemporal cortex. This approach correctly identified the effect of a test drug (tiagabine) on neuronal function (GABA-ergic dynamics), opening the way for psychopharmacological studies in health and disease with the mechanistic precision afforded by generative models of the brain.

neuroscience↗

bioRxiv2018

In vivo assay of cortical microcircuitry in frontotemporal dementia: a platform for experimental medicine studies

The analysis of neural circuits can provide critical insights into the mechanisms of neurodegeneration and dementias, and offer potential quantitative biological tools to assess novel therapeutics. Here we use behavioural variant frontotemporal dementia (bvFTD) as a model disease. We demonstrate that inversion of canonical microcircuit models to non-invasive human magnetoecphalography can identify the regional- and laminar-specificity of bvFTD pathophysiology, and their parameters can accurately differentiate patients from matched healthy controls. Using such models, we show that changes in local coupling in frontotemporal dementia underlie the failure to adequately establish sensory predictions, leading to altered prediction error responses in a cortical information-processing hierarchy. Using machine learning, this model-based approach provided greater case-control classification accuracy than conventional evoked cortical responses. We suggest that this approach provides an in vivo platform for testing mechanistic hypotheses about disease progression and pharmacotherapeutics.

neuroscience↗