Biology subjects

Chamberlain, S. R.

Publications and source records attributed to Chamberlain, S. R..

6 recordsLinked to original sources

bioRxiv2026

Ultrafast X-Rays Capture Retinal Traversing Conical Intersection in Rhodopsin

G-protein-coupled receptors of the Rhodopsin family are crucial medicinal targets, transmitting signals across biomembranes. While light absorption by visual rhodopsin is well studied, its activation via retinal cofactor dynamics remains unclear. Here we use a free-electron laser to show that time-resolved X-ray solution scattering captures the retinal cis-trans isomerization as it passes the conical intersection of excited and ground-state photoproduct energy surfaces. Femtosecond-scale nuclear changes occur due to resonant photon absorption, with all-atom simulations revealing ultrafast amino acid movements that initiate transmembrane helix shifts. Ligand-free opsin measurements confirm that light activation is unaffected by non-resonant processes, showing the photonic energy is directly transmitted within the protein. Our method unveils how cofactor dynamics activate rhodopsin, free of constraints from crystal lattice packing or cryotrapping photointermediates.

biophysics↗

bioRxiv2023

Fitting high-resolution electron density maps from atomic models to solution scattering data

Solution scattering techniques, such as small and wide-angle X-ray scattering (SWAXS), provide valuable insights into the structure and dynamics of biological macromolecules in solution. In this study, we present an approach to accurately predict solution X-ray scattering profiles at wide angles from atomic models by generating high-resolution electron density maps. Our method accounts for the excluded volume of bulk solvent by calculating unique adjusted atomic volumes directly from the atomic coordinates. This approach eliminates the need for a free fitting parameter commonly used in existing algorithms, resulting in improved accuracy of the calculated SWAXS profile. An implicit model of the hydration shell is generated which uses the form factor of water. Two parameters, namely the bulk solvent density and the mean hydration shell contrast, are adjusted to best fit the data. Results using eight publicly available SWAXS profiles show high quality fits to the data. In each case, the optimized parameter values show small adjustments demonstrating that the default values are close to the true solution. Disabling parameter optimization results in a significant improvement of the calculated scattering profiles compared to the leading software. The algorithm is computationally efficient, showing more than tenfold reduction in execution time compared to the leading software. The algorithm is encoded in a command line script called denss.pdb2mrc.py and is available open source as part of the DENSS v1.7.0 software package (https://github.com/tdgrant1/denss). In addition to improving the ability to compare atomic models to experimental SWAXS data, these developments pave the way for increasing the accuracy of modeling algorithms utilizing SWAXS data while decreasing the risk of overfitting. Statement of SignificanceAccurate calculation of small and wide-angle scattering (SWAXS) profiles from atomic models is useful for studying the solution state and conformational dynamics of biological macromolecules in solution. Here we present a new approach to calculating SWAXS profiles from atomic models using high resolution real space density maps. This approach includes novel calculations of solvent contributions that remove a significant fitting parameter. The algorithm is tested on multiple high quality experimental SWAXS datasets, showing improved accuracy compared to leading software. The algorithm is computationally efficient and robust to overfitting, paving the way for increasing the accuracy and resolution of modeling algorithms utilizing experimental SWAXS data.

biophysics↗

bioRxiv2021

Cortical dopamine reduces the impact of motivational biases governing automated behaviour

Motivations shape our behaviour: the promise of reward invigorates, while in the face of punishment, we hold back. Abnormalities of motivational processing are implicated in clinical disorders characterised by excessive habits and loss of top-down control, notably substance and behavioural addictions. Striatal and frontal dopamine have been hypothesised to play complementary roles in the respective generation and control of these motivational biases. However, while dopaminergic interventions have indeed been found to modulate motivational biases, these previous pharmacological studies used regionally non-selective pharmacological agents. Here, we tested the hypothesis that frontal dopamine controls the balance between Pavlovian, bias-driven automated responding and instrumentally learned action values. Specifically, we examined whether selective enhancement of cortical dopamine either (i) enables adaptive suppression of Pavlovian control when biases are maladaptive; or (ii) non-specifically modulates the degree of bias-driven automated responding. Healthy individuals (n=35) received the catechol-o-methyltransferase (COMT) inhibitor tolcapone in a randomized, double-blind, placebo-controlled cross-over design, and completed a motivational Go NoGo task known to elicit motivational biases. In support of hypothesis (ii), tolcapone globally decreased motivational bias. Specifically, tolcapone improved performance on trials where the bias was unhelpful, but impaired performance in bias-congruent conditions. These results indicate a non-selective role for cortical dopamine in the regulation of motivational processes underpinning top-down control over automated behaviour. The findings have direct relevance to understanding neurobiological mechanisms underpinning addiction and obsessive-compulsive disorders, as well as highlighting a potential trans-diagnostic novel mechanism to address such symptoms.

neuroscience↗

bioRxiv2019

Fractionation of impulsive and compulsive trans-diagnostic phenotypes and their longitudinal associations

ObjectiveYoung adulthood is a crucial neurodevelopmental period during which impulsive and compulsive problem behaviours commonly emerge. While traditionally considered diametrically opposed, impulsive and compulsive symptoms tend to co-occur. The objectives of this study were: (i) to identify the optimal trans-diagnostic structural framework for measuring impulsive and compulsive problem behaviours; and (ii) to use this optimal framework to identify common/distinct antecedents of these latent phenotypes.\n\nMethods654 young adults were recruited as part of the Neuroscience in Psychiatry Network (NSPN), a population-based cohort in the United Kingdom. The optimal trans-diagnostic structural model capturing 33 types of impulsive and compulsive problem behaviours was identified. Baseline predictors of subsequent impulsive and compulsive trans-diagnostic phenotypes were characterised, along with cross-sectional associations, using Partial Least Squares (PLS).\n\nResultsCurrent problem behaviours were optimally explained by a bi-factor model, which yielded dissociable measures of impulsivity and compulsivity, as well as a general disinhibition factor. Impulsive problem behaviours were significantly explained by prior antisocial and impulsive personality traits, male gender, general distress, perceived dysfunctional parenting, and teasing/arguments within friendships. Compulsive problem behaviours were significantly explained by prior compulsive traits, and female gender.\n\nConclusionsThis study demonstrates that trans-diagnostic phenotypes of 33 impulsive and compulsive problem behaviours are identifiable in young adults, utilizing a bi-factor model based on responses to a single questionnaire. Furthermore, these phenotypes have different antecedents. The findings yield a new framework for fractionating impulsivity and compulsivity; and suggest different early intervention targets to avert emergence of problem behaviours. This framework may be useful for future biological and clinical dissection of impulsivity and compulsivity.

neuroscience↗

bioRxiv2018

Transdiagnostic variations in impulsivity and compulsivity in obsessive-compulsive disorder and gambling disorder correlate with effective connectivity in cortical-striatal-thalamic-cortical circuits.

BackgroundIndividual differences in impulsivity and compulsivity is thought to underlie vulnerability to a broad range of disorders and are closely tied to cortical-striatal-thalamic-cortical (CSTC) function. However, whether impulsivity and compulsivity in clinical disorders is continuous with the healthy population and explains CSTC dysfunction across different disorders remains unclear.\n\nMethodsWe characterized the relationship between CSTC effective connectivity, estimated using dynamic causal modelling of functional magnetic resonance imaging data, and dimensional phenotypes of impulsivity and compulsivity in two symptomatically distinct but phenotypically related disorders, obsessive-compulsive disorder (OCD) and gambling disorder (GD). 487 online participants provided data for modelling of dimensional phenotypes. These data were combined with 34 OCD patients, 22 GD patients, and 39 healthy controls, who underwent functional magnetic resonance imaging.\n\nResultsThree core dimensions were identified: disinhibition, impulsivity, and compulsivity. Patients scores on these dimensions were continuously distributed with the healthy participants, supporting a continuum model of psychopathology. Across all participants, higher disinhibition correlated with lower bottom-up connectivity in the dorsal circuit and increased bottom-up connectivity in the ventral circuit, and higher compulsivity correlated with reduced bottom-up connectivity in the dorsal circuit. Similar changes in effective connectivity were observed with increasing clinical severity that were not accounted for by phenotypic variation, demonstrating convergence towards behaviourally and clinically relevant changes in brain dynamics. Effective connectivity did not differ as a function of traditional diagnostic labels.\n\nConclusionsCSTC dysfunction across OCD and GD is better characterized by dimensional phenotypes than diagnostic comparisons, supporting investigation of quantitative liability phenotypes.

neuroscience↗

bioRxiv2017

Treatment-resistant depression and peripheral C-reactive protein

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSDysregulation of the peripheral innate immune system has been implicated in the pathophysiology of major depressive disorder (MDD), and may partly account for why many patients do not experience symptomatic improvement. Elevated CRP has been demonstrated in meta-analysis for MDD compared to healthy volunteers, but little is known about whether this is the case for particular clinical phenotypes of the disorder, as opposed to MDD in general.\n\nAdded value of this studyThis study recruited a large cohort of MDD patients, stratified by prior exposure to monoamine reuptake inhibitor treatment. MDD participants were carefully screened for physical comorbidity, and were compared to healthy volunteers matched for age, sex, body mass indices, and cigarette smoking status. Using group-wise comparisons and the innovative statistical approach of partial least squares, we demonstrated that elevated CRP was associated with treatment-resistance, childhood adversity, and specific depressive and anxious symptoms.\n\nImplications of all the available evidenceCRP is significantly increased \"on average\" in MDD patients, However, CRP was most abnormally increased in the subgroup of patients with treatment-resistant depression. High BMI, high scores on vegetative symptoms of depression, low scores on calmness, and a history of childhood adversity, were all predictive of increased CRP. In future, stratification of MDD patients using pro-inflammatory biomarkers, like CRP, may be valuable for sample enrichment and targeted treatment interventions.\n\nAbstractO_ST_ABSBackgroundC_ST_ABSC-reactive protein (CRP) is a candidate biomarker for major depressive disorder (MDD), but it is unclear how peripheral CRP levels relate to the heterogeneous clinical phenotypes of the disorder.\n\nMethodsWe recruited 102 treatment-resistant, depressed MDD patients, 48 treatment-responsive, non-depressed MDD patients, 48 depressed but un-medicated patients, and 54 healthy volunteers. High sensitivity CRP in peripheral venous blood, body mass index (BMI), and questionnaire assessments of depression, anxiety, and childhood trauma, were measured. Group differences in CRP were estimated, before and after correction for BMI. Partial least squares (PLS) analysis explored the relationships between CRP and specific clinical phenotypes.\n\nOutcomesCompared to healthy volunteers, BMI-corrected CRP was significantly elevated in treatment-resistant patients (P = 0.007; Cohens d = 0.47); but not significantly so in the treatment-responsive (d = 0.29) and untreated (d = 0.18) groups. PLS yielded an optimal two factor solution that accounted for 34.7% of variation in clinical measures, and for 36.0% of variation in CRP. The clinical phenotypes most strongly associated with CRP and heavily weighted on the first PLS component were: vegetative depressive symptoms, BMI, state anxiety, and feeling unloved as a child or wishing for a different childhood.\n\nInterpretationPeripheral CRP was elevated in MDD, especially in treatment-resistant cases. Other phenotypes associated with elevated CRP included childhood adversity, and specific depressive and anxious symptoms. We suggest that MDD patients stratified for pro-inflammatory biomarkers, like CRP, have a distinctive clinical profile that might be responsive to second-line treatment with anti-inflammatory drugs.\n\nFundingWellcome Trust strategy award to the Neuroimmunology of Mood Disorders and Alzheimers Disease (NIMA) Consortium.

neuroscience↗