Biology subjects

Whitfield, M.

Publications and source records attributed to Whitfield, M..

3 recordsLinked to original sources

bioRxiv2026

Loss of PKN2 drives fibroblast reprogramming and extracellular matrix remodelling in pulmonary fibrosis

Introduction Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease characterised by aberrant fibroblast function, extracellular matrix (ECM) remodelling and defective tissue repair. Protein kinase N2 (PKN2) is associated with accelerated forced vital capacity decline in IPF, but its functional role in pulmonary fibrosis remains unknown. We hypothesised that PKN2 regulates fibroblast phenotype and tissue repair. Methods PKN2 expression was assessed in human lung tissue, induced sputum and primary airway and parenchymal fibroblasts from non-fibrotic controls and patients with interstitial lung disease (ILD). DNA methylation was profiled using the Illumina HumanMethylationEPIC array. PKN2 function was investigated by siRNA-mediated depletion in primary human lung fibroblasts using transcriptomic, proteomic and functional analyses. Tissue repair was assessed following pharmacological PKN inhibition in zebrafish. Results PKN2 expression was reduced in ILD lung tissue and primary airway and parenchymal fibroblasts and further suppressed by TGF-{beta}1. Differential methylation was identified across the PKN2 locus in both fibroblast populations. Integrated transcriptomic and proteomic profiling following PKN2 depletion revealed coordinated remodelling of ECM, cell adhesion, non-canonical WNT and VEGF pathways, including dysregulation of COL1A1, WNT, VEGF and MMP1. PKN2 loss increased VEGF and MMP-1 secretion and accelerated fibroblast wound closure. PKN inhibition altered epithelial organisation and collagen fibre alignment during zebrafish wound repair. Conclusion PKN2 loss drives fibroblast reprogramming and aberrant ECM remodelling, establishing PKN2 as an important regulator of pulmonary fibroblast homeostasis and tissue repair.

cell biology↗

bioRxiv2026

KCa3.1 Drives Pro-Fibrotic Activation and Represents a Novel Therapeutic Target in Aortic Stenosis

IntroductionAortic stenosis (AS) is characterised by progressive aortic valve (AV) leaflet fibrosis and calcification, yet no medical therapies exist to slow disease progression. AV interstitial cells (VICs) that differentiate into myofibroblasts are central drivers of fibrosis. The Ca2+-activated K+ channel KCa3.1 promotes pro-fibrotic signalling in several fibrotic diseases, however its role in AS remains unknown. MethodsKCa3.1 protein expression was examined in paraffin embedded tissue by Immunohistochemistry from control and AS valve tissue. VICs were isolated, cultured and phenotypically characterised as myofibroblasts from AV tissue obtained from patients with severe tricuspid AS undergoing surgical AV replacement (n=19). KCa3.1 mRNA and protein expression were assessed by qRT-PCR and immunohistochemistry, and functional channel activity confirmed using patch-clamp electrophysiology. The effects of transforming growth factor-{beta}1 (TGF{beta}1) stimulation and pharmacological inhibition with the selective KCa3.1 blocker senicapoc were examined. ResultsImmunoreactive KCa3.1 channels and smooth muscle actin were detected in both control and AS aortic valve tissue, localised to elongated, nucleated interstitial cells, with significantly higher expression observed in AS tissue compared to control. Isolated VICs exhibited an activated myofibroblast phenotype, expressing THY-1, vimentin, collagen and -smooth muscle actin (SMA) (n=9). Myofibroblasts expressed KCa3.1 mRNA and protein and demonstrated functional plasma membrane channels. TGF{beta}1 stimulation increased KCa3.1, SMA and collagen type I mRNA expression, while KCa3.1 blockade with senicapoc (100 nM) significantly attenuated TGF{beta}1-induced SMA expression, stress fibre formation and collagen gel contraction. Senicapoc had no effect on myofibroblast proliferation or migration. ConclusionsWe show for the first time that functional KCa3.1 channels are expressed in human AS tissue and AV myofibroblasts, where they regulate myofibroblast contraction, -SMA expression, and differentiation, promoting pro-fibrotic activity. These responses are attenuated by the selective KCa3.1 inhibitor senicapoc. Given its established safety in phase 3 clinical trials, KCa3.1 inhibition represents a promising and readily translatable anti-fibrotic therapeutic strategy for AS.

cell biology↗

bioRxiv2019

Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine learning approaches.

SynopsisO_ST_ABSBackgroundC_ST_ABSPyrazinamide is one of four first-line antibiotics used to treat tuberculosis, however antibiotic susceptibility testing for pyrazinamide is challenging. Resistance to pyrazinamide is primarily driven by genetic variation in pncA, an enzyme that converts pyrazinamide into its active form. MethodsWe curated a dataset of 664 non-redundant, missense amino acid mutations in pncA with associated high-confidence phenotypes from published studies and then trained three different machine learning models to predict pyrazinamide resistance. All models had access to a range of protein structural-, chemical- and sequence-based features. ResultsThe best model, a gradient-boosted decision tree, achieved a sensitivity of 80.2% and a specificity of 76.9% on the hold-out Test dataset. The clinical performance of the models was then estimated by predicting the binary pyrazinamide resistance phenotype of 4,027 samples harboring 367 unique missense mutations in pncA derived from 24,231 clinical isolates. ConclusionsThis work demonstrates how machine learning can enhance the sensitivity/specificity of pyrazinamide resistance prediction in genetics-based clinical microbiology workflows, highlights novel mutations for future biochemical investigation, and is a proof of concept for using this approach in other drugs.

microbiology↗