Biology subjects

Price, S. J.

Publications and source records attributed to Price, S. J..

12 recordsLinked to original sources

bioRxiv2025

Extracellular Matrix Alterations in Chronic Ischemic Cardiomyopathy Revealed by Quantitative Proteomics

Ischemic cardiomyopathy (ICM) is a leading cause of heart failure characterized by extensive remodeling of the cardiac extracellular matrix (ECM). While initially adaptive, ECM deposition following ischemic injury eventually turns maladaptive, promoting adverse cardiac remodeling. The strong link between the extent of fibrosis and adverse clinical outcomes has led to growing interest in ECM targeted therapies to prevent or reverse maladaptive cardiac remodeling in ICM; yet, the precise composition of the ECM in ICM remains poorly defined. In this study, we employed a sequential protein extraction enabled by the photocleavable surfactant Azo to enrich ECM proteins from left ventricular tissues of patients with end-stage ICM (n=16) and nonfailing donor hearts (n=16). High-resolution mass spectrometry-based quantitative proteomics identified and quantified over 6,000 unique protein groups, including 315 ECM proteins. We discovered significant upregulation of key ECM components, particularly glycoproteins, proteoglycans, collagens, and ECM regulators. Notably, LOXL1, FBLN1, and VCAN were among the most differentially expressed. Functional enrichment analyses revealed enhanced TGF{beta} signaling, integrin-mediated adhesion, and complement activation in ICM tissues, suggesting a feedback loop driving continued ECM deposition in the end-stage failing heart. Together, our findings provide a comprehensive proteomic landscape of ECM alterations in the end-stage ICM myocardium and identify promising molecular targets for therapeutic intervention.

biochemistry↗

bioRxiv2023

High-throughput Extracellular Matrix Proteomics of Human Lungs Enabled by Photocleavable Surfactant and diaPASEF

The extracellular matrix (ECM) is a complex assembly of proteins that provide interstitial scaffolding and elastic recoil to human lungs. The pulmonary extracellular matrix (ECM) is increasingly recognized as an independent bioactive entity by creating biochemical and mechanical signals that influence disease pathogenesis, making it an attractive therapeutic target. However, the pulmonary ECM proteome ("matrisome") remains challenging to analyze by mass spectrometry due to its inherent biophysical properties and relatively low abundance. Here, we introduce a strategy designed for rapid and efficient characterization of the human pulmonary ECM using the photocleavable surfactant Azo. We coupled this approach with trapped ion mobility MS with diaPASEF to maximize depth of matrisome coverage. Using this strategy, we identify nearly 400 unique matrisome proteins with excellent reproducibility that are known to be important in lung biology, including key insoluble ECM proteins.

systems biology↗

bioRxiv2022

Population genetic analysis of Ophidiomyces ophidiicola, the causative agent of snake fungal disease, indicates recent introductions to the USA

Snake fungal disease (SFD; ophidiomycosis), caused by the pathogen Ophidiomyces ophidiicola (Oo), has been documented in wild snakes in North America and Eurasia, and is considered an emerging disease in the eastern USA. However, a lack of historical disease data has made it challenging to determine whether Oo is a recent arrival to the USA or whether SFD emergence is due to other factors. Here, we examined the genomes of 82 Oo strains to determine the pathogens history in the eastern USA. Oo strains from the USA formed a clade (Clade II) distinct from European strains (Clade I), and molecular dating indicated that these clades diverged too recently ([~]2,000 years ago) for transcontinental dispersal of Oo to have occurred via natural snake movements across Beringia. A lack of nonrecombinant intermediates between clonal lineages in Clade II indicates that Oo has actually been introduced multiple times to North America from an unsampled source population, and molecular dating indicates that several of these introductions occurred within the last few hundred years. Molecular dating also indicated that the most common Clade II clonal lineages have expanded recently in the USA, with time of most recent common ancestor mean estimates ranging from 1985-2007 CE. The presence of Clade II in captive snakes worldwide demonstrates a potential mechanism of introduction and highlights that additional incursions are likely unless action is taken to reduce the risk of pathogen translocation and spillover into wild snake populations.

microbiology↗

bioRxiv2021

Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients

Glioblastoma widely affects brain structure and function, and remodels neural connectivity. Characterizing the neural connectivity in glioblastoma may provide a tool to understand tumor invasion. Here, using a structural connectome approach based on diffusion MRI, we quantify the global and regional connectome disruptions in individual glioblastoma patients and investigate the prognostic value of connectome disruptions and topological properties. We show that the disruptions in the normal-appearing brain beyond the lesion could mediate the topological alteration of the connectome (P <0.001), associated with worse patient performance (P <0.001), cognitive function (P <0.001), and survival (overall survival: HR: 1.46, P = 0.049; progression-free survival: HR: 1.49, P = 0.019). Further, the preserved connectome in the normal-appearing brain demonstrates evidence of remodeling, where increased connectivity is associated with better overall survival (log-rank P = 0.005). Our approach reveals the glioblastoma invasion invisible on conventional MRI, promising to benefit patient stratification and precise treatment.

neuroscience↗

bioRxiv2019

A map of transcriptional heterogeneity and regulatory variation in human microglia

Microglia, the tissue resident macrophages of the CNS, are implicated in a broad range of neurological pathologies, from acute brain injury to dementia. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single cell and bulk RNA sequencing, we defined distinct cellular populations of acutely in vivo-activated microglia, and characterised a dramatic switch in microglial population composition in patients suffering from acute brain injury. We mapped expression quantitative trait loci (eQTLs) in human microglia and show that many disease-associated eQTLs in microglia replicate well in a human induced pluripotent stem cell (hIPSC) derived macrophage model system. Using ATAC-seq from 95 individuals in this hIPSC model we fine-map candidate causal variants at risk loci for Alzheimers disease, the most prevalent neurodegenerative condition in acute brain injury patients. Our study provides the first population-scale transcriptional map of a critically important cell for neurodegenerative disorders.

genomics↗

bioRxiv2018

Temperature is a key driver of a wildlife epidemic and future warming will increase impacts

Increasing environmental temperatures are predicted to have increasingly severe and deleterious effects on biodiversity. For the most part, the impacts of a warming environment are presumed to be direct, however some predict increasingly severe disease epidemics, primarily from vector-borne pathogens, that will have the capacity to deplete host populations. Data to support this hypothesis are lacking. Here we describe increasing severity of ranavirosis driven by increasing temperature affecting a widely distributed amphibian host. Both in vitro and in vivo experiments showed that increasing environmental temperature leads to increased propagation of ranavirus and, in the latter, increased incidence of host infection and mortality. Also, temperature was shown to be a key determinant of disease dynamics in wild amphibians, raising the odds and severity of disease incidents. The direction of this effect was highly consistent in the context of other interacting variables such as shading around ponds. Projections based on future climate indicate that changes in seasonal weather in the UK will result in the increased incidence of severe cases of ranavirosis in amphibian populations that could affect recruitment. These complementary lines of evidence present a clear case of direct environmental modulation of a host-pathogen interaction and provide information for proposing mitigation actions.

epidemiology↗

bioRxiv2017

Multi-Parametric and Multi-Regional Histogram Analysis of MRI: Revealing Imaging Phenotypes of Glioblastoma Correlated with Patient Survival

IntroductionGlioblastoma is characterized by its remarkable heterogeneity and dismal prognosis. Histogram analysis of quantitative magnetic resonance imaging (MRI) is an important in vivo method to study intratumoral heterogeneity. With large amounts of histogram features generated, integrating these modalities effectively for clinical decision remains a challenge.\n\nMethodsA total of 80 patients with supratentorial primary glioblastoma were recruited. All patients received surgery and standard regimen of temozolomide chemoradiotherapy. Diagnosis was confirmed by pathology. Anatomical T2-weighted, T1-weighted post-contrast and FLAIR images, as well as dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI) and chemical shift imaging were acquired preoperatively using a 3T MRI scanner. DTI-p, DTI-q, relative cerebral blood volume (rCBV), mean transit time (MTT) and relative cerebral blood flow (rCBF) maps were generated. Contrast-enhancing (CE) and non-enhancing (NE) regions of interest were manually delineated. Voxel intensity histograms were constructed from the CE and NE regions independently. Patient clustering was performed by the Multi-View Biological Data Analysis (MVDA) approach. Kaplan-Meier and Cox proportional hazards regression analyses were performed to evaluate the relevance of the patient clustering to survival. The histogram features selected from MVDA approach were evaluated using receiver operator characteristics (ROC) curve analysis. The metabolic signatures of the patient clusters were analyzed by multivoxel MR spectroscopy (MRS).\n\nResultsThe MVDA approach yielded two final patient clusters, consisting of 53 and 27 patients respectively. The two patient subgroups showed significance for overall survival (p = 0.007, HR = 0.32) and progression-free survival (p < 0.001, HR = 0.33) in multivariate Cox regression analysis. Among the features selected by MVDA, higher mean value of DTI-q in the non-enhancing region contributed to a worse OS (HR = 1.40, p = 0.020) and worse PFS (HR = 1.36, p = 0.031). Multivoxel MRS showed N-acetylaspartate/creatine (NAA/Cr) ratio between the two clusters, both in the CE region (p < 0.001) and NE region (p = 0.013). Glutamate/Cr (Glu/Cr) ratio and glutamate + glutamine/Cr (Glx/Cr) of the cluster 1 was significantly lower than cluster 2 (p = 0.037, and 0.027 respectively) In the NE region.\n\nDiscussionThis study demonstrated that integrating multi-parametric and multi-regional MRI histogram features may help to stratify patients. The histogram features selected from the proposed approach may be used as potential imaging markers in personalized treatment strategy and response determination.

bioinformatics↗

bioRxiv2017

Intratumoral Heterogeneity of Tumor Infiltration of Glioblastoma Revealed by Joint Histogram Analysis of Diffusion Tensor Imaging

IntroductionGlioblastoma exhibits profound tumor heterogeneity, which causes inconsistent treatment response. The aim of this study was to propose an interpretation method of diffusion tensor imaging (DTI) using joint histogram analysis of DTI-p and-q. With this method we explored the patterns of tumor infiltration which causes disruption of brain microstructure, and examined the prognostic value of tumor infiltrative patterns for patient survival.\n\nMaterials and methodsA total of 115 primary glioblastoma patients (mean age 59.3 years, 87 males) were prospectively recruited from July 2010 to August 2015. Patients underwent preoperative MRI scans and maximal safe resection. DTI was processed and decomposed into p and q components. The univariate and joint histograms of DTI-p and-q were constructed using the voxels of contrast-enhancing and non-enhancing regions respectively. Eight joint histogram features were obtained and correlated with tumor progression and patient survival. Their prognostic values were compared with clinical factors using receiver operating characteristic curves.\n\nResultsThe subregion of increased DTI-p and decreased DTI-q accounted for the largest proportion. Additional diffusion patterns can be identified via joint histogram analysis. Particularly, higher proportion of decreased DTI-p and increased DTI-q in non-enhancing region contributed to worse progression-free survival (hazard ratio = 1.08, p< 0.001) and overall survival (hazard ratio = 1.11, p < 0.001).\n\nConclusionsJoint histogram analysis of DTI can provide a comprehensive measure of tumor infiltration and microstructure change, which showed prognostic values. The subregion of decreased DTI-p and increased DTI-q in non-enhancing regions may indicate a more invasive habitat.

neuroscience↗

bioRxiv2017

Low Perfusion Compartments in Glioblastoma Quantified by Advanced Magnetic Resonance Imaging: Correlation with Patient Survival

BackgroundGlioblastoma exhibits profound intratumoral heterogeneity in blood perfusion, which may cause inconsistent therapy response. Particularly, low perfusion may create hypoxic microenvironment and induce resistant clones. Thus, developing validated imaging approaches that define low perfusion compartments is crucial for clinical management.\n\nMethodsA total of 112 newly-diagnosed supratentorial glioblastoma patients were prospectively recruited for maximal safe resection. Preoperative MRI included anatomical, dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI) and chemical shift imaging (CSI). The apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) were calculated from DTI and DSC respectively. Using thresholding methods, two low perfusion compartments (ADCH-rCBVL and ADCL-rCBVL) were identified. Volumetric analysis was performed. Lactate and macromolecule/lipid levels were determined from multivoxel spectroscopy. Progression-free survival (PFS) and overall survival (OS) were analysed using Kaplan-Meier and multivariate Cox regression analyses.\n\nResultsTwo compartments displayed higher lactate and macromolecule/lipid levels than normal controls (each P < 0.001), suggesting hypoxic and pro-inflammatory microenvironment. The proportional volume of ADCL-rCBVL compartment was associated with a larger infiltration area (P < 0.001, rho = 0.42). Lower lactate in this compartment was associated with a less invasive phenotype visualized on DTI. Multivariate Cox regression showed higher lactate level in the ADCL-rCBVL compartment was associated with a worse survival (PFS: HR 2.995, P = 0.047; OS: HR 4.974, P = 0.005).\n\nConclusionsThe ADCL-rCBVL compartment represent a treatment resistant sub-region associated with glioblastoma invasiveness. This approach was based on clinically available imaging modalities and could thus provide crucial pretreatment information for clinical decision making.

cancer biology↗

bioRxiv2017

Host Microbiome Richness Predicts Resistance to Disturbance by Pathogenic Infection in a Vertebrate Host

Environmental heterogeneity is known to modulate the interactions between pathogens and hosts. However, the impact of environmental heterogeneity on the structure of host-associated microbial communities, and how these communities respond to pathogenic exposure remain poorly understood. Here we use an experimental framework to probe the links between environmental heterogeneity, skin microbiome structure and infection by the emerging pathogen Ranavirus in a vertebrate host, the European common frog (Rana temporaria). We provide evidence that environmental complexity directly influences the diversity and structure of the host skin microbiome, and that more diverse microbiomes are more resistant to perturbation associated with exposure to Ranavirus. Our data also indicate that host microbiome diversity covaries with survival following exposure to Ranavirus. Our study highlights the importance of extrinsic factors in driving host-pathogen dynamics in vertebrate hosts, and suggests that environment-mediated variation in the structure of the host microbiome may covary with observed differences in host susceptibility to disease in the wild.

ecology↗

bioRxiv2017

An integrated genomic analysis of anaplastic meningioma identifies prognostic molecular signatures

Anaplastic meningioma is a rare and aggressive brain tumor characterised by intractable recurrences and dismal outcomes. Here, we present an integrated analysis of the whole genome, transcriptome and methylation profiles of primary and recurrent anaplastic meningioma. A key finding was the delineation of two distinct molecular subgroups that were associated with diametrically opposed survival outcomes. Relative to lower grade meningiomas, anaplastic tumors harbored frequent driver mutations in SWI/SNF complex genes, which were confined to the poor prognosis subgroup. Our analyses discern two biologically distinct variants of anaplastic meningioma with potential prognostic and therapeutic significance.

genomics↗

bioRxiv2017

Global Effects Of Focal Brain Tumours On Functional Complexity And Network Robustness

BackgroundNeurosurgical management of brain tumours has entered a new paradigm of supra-marginal resections that demands thorough understanding of their peri-tumoural functional effects. Historically the effects of tumours have been considered as local, and long-range effects have not been considered. This work tests the hypothesis that focal tumours affect the brain at a global level producing long-range gradients in cortical function.\n\nMethodsResting state functional (f)MRI data were acquired from 11 participants with glioblastoma and split into discovery and validation datasets. Fractal complexity was computed with a wavelet-based estimator of the Hurst exponent. Distance related effects of the tumours were tested with a tumour mask dilation technique and parcellation of the underlying Hurst maps. Functional connectivity networks were constructed and validated with different parcellation and statistical dependency methods prior to graph theory analysis.\n\nResultsFractal complexity, measured through the Hurst exponent and tumour mask dilation technique, demonstrates a penumbra of suppression in the peri-tumoural region. At a global level, as distance from the tumour increases, this initial suppression is balanced by a subsequent over-activity before finally normalizing. These effects were best fit by a quadratic model, and were consistent across different network construction pipelines. The Hurst exponent was significantly correlated with multiple graph theory measures of centrality including network robustness, but graph theory measures did not demonstrate distance dependent effects.\n\nConclusionsThis work provides evidence to support the theory that focal brain tumours produce long-range and non-linear gradients in function. Consequently the effects of focal lesions, and the resultant clinical effects, need to be interpreted in terms of the global changes on whole brain functional complexity and network architecture rather than purely in terms of functional localisation. Determining whether the peri-tumoural changes represent adaption or potential plasticity, for example, may facilitate extended resection of the tumour without functional cost.

neuroscience↗