Biology subjects

Quinn, P.

Publications and source records attributed to Quinn, P..

4 recordsLinked to original sources

bioRxiv2026

The single nucleotide polymorphism rs1053230 modulates kynurenine 3-monooxygenase stability and is associated with cognitive and mood phenotypes

BackgroundThe single nucleotide polymorphism (SNP) rs1053230 within the kynurenine 3-monooxygenase (KMO) gene encodes either an arginine (CGC) or cysteine (TGC) at amino acid residue 452. The rs1053230 genotype is associated with alterations in KMO expression and activity, and impaired cognition. Additionally, KMO intronic SNP rs2275163 is associated with schizophrenia endophenotypes. However, the direct functional consequences of these SNPs on KMO function have never been investigated. MethodsHere we performed the first in vitro cell-based examination of the rs1053230 genotype on KMO expression, activity, cellular localisation and KMO-protein interactions, as well as examination of the effects of rs1053230 on schizophrenia-relevant clinical measures. We also examined the effects of rs2275163 genotype on KMO pre-mRNA stability and alternative splicing. ResultsHEK293T cells expressing KMO-Arg452 or KMO-Cys452 with a red fluorescent protein (RFP) tag produced equivalent levels of KMO mRNA, protein and enzymatic activity, and localised to mitochondria to the same extent. However, cycloheximide-mediated inhibition of protein translation revealed a striking reduction in protein stability of KMO-Arg452-RFP. KMO-RFP-trap pull-down followed by tandem liquid-chromatography-mass spectrometry (LC-MS/MS) identified dramatic differences in protein partners between KMO variants. Indeed, gene ontology-term enrichment analysis revealed that terms associated with synaptic function were more highly enriched amongst KMO-Cys452 interacting proteins. rs1053230 genotype was found to associate with chronic, trait-like depressive mood symptoms in patients. rs2275163 genotype had no effect on KMO pre-mRNA. ConclusionsDifferences in protein stability and protein-protein interactions may underlie the mechanisms by which the KMO rs1053230 genotype influences neuronal function, leading to cognitive differences in psychiatric conditions.

molecular biology↗

bioRxiv2026

Dynamic, single-cell monitoring of CAR T cell identity and activation with Raman spectroscopy

Chimeric antigen receptor (CAR) T cell therapies have reshaped treatment for cancers and immune-mediated diseases, yet their safety and efficacy depend on both the proliferation of engineered cells and their dynamic functional state -- features that remain challenging to monitor in real-time clinical settings. Current methods require targeted labels, extensive processing, and provide only static snapshots of cell identity and activation. Here, we introduce a surface-enhanced Raman spectroscopy (SERS) and machine learning (ML) approach that enables single-cell identification of engineered CAR T cells without molecularly-targeted labels and time-resolved, semi-continuous monitoring of their functional activation state through a single physical readout spanning donor-derived cells and patient blood. From intrinsic vibrational signatures of live cells, we detect spectral differences resulting from engineered receptor expression in donor-derived CD19- and GD2-targeted CAR T cells (nine and five donors, respectively) with 81-85% donor-level accuracy, and resolve dynamic antigen-specific activation trajectories with temporal precision. Applying this same SERS-ML method to longitudinal samples from a four-patient CD19-CAR T therapy cohort, we classify patient peripheral blood mononuclear cells across pre-and post-infusion timepoints with a mean patient-level accuracy of 84%, and show that isolated CAR-positive T cells are distinguishable from both CAR-negative T cells and background populations with average 86-88% accuracies. These capabilities stem from biochemical signatures consistent with processes such as receptor expression, tonic signalling, and immune synapse formation, demonstrating a single method that reports both cellular identity and activation state with biochemical specificity across cell engineering and clinical monitoring contexts. Our results extend CAR T cell monitoring beyond static phenotyping and support the potential of SERS-ML analysis for rapid, point-of-care assessment of engineered immune cells across the therapeutic lifecycle.

bioengineering↗

bioRxiv2022

Reproducibility problem with a proposed standard method to measure disinfection efficacy

A collaborative study was carried out in four laboratories to determine the reproducibility of a proposed ASTM International standard method for quantitatively evaluating the efficacy of disinfectants on hard, non-porous surfaces against bacteria. The method, known as the Quantitative Method, has also been suggested as a future regulatory standard for the United States and internationally. The multi-lab study was carried out using Pseudomonas aeruginosa and an alkyl dimethyl benzyl ammonium chloride antimicrobial product diluted in hard water. Results of the study showed acceptable repeatability in log10 reductions within each laboratory, but unacceptable reproducibility across laboratories despite careful analyst training and standardization of test conditions. A follow-up study ruled out analyst-to-analyst differences as the cause of the poor reproducibility. As it currently exists, the Quantitative Method is not sufficiently reproducible. Ruggedness testing to assess the sensitivity of the method to small changes in operational factors is recommended.

microbiology↗

bioRxiv2020

Extreme phenotypes define epigenetic and metabolic signatures in cardiometabolic syndrome.

Improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis are ongoing healthcare challenges. Using plasma biomarkers analysis coupled with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (obese and lipodystrophy) and comparing these to lean individuals and blood donors, the present study identifies the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells and shows that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, six months after bariatric surgery shows the loss of the patterns of abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurs via the establishment of novel gene expression landscapes. Netosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Taken together, by integrating across data layers, the observed molecular and metabolic differences form a disease signature that is able to discriminate, amongst the blood donors, those individuals with a higher likelihood of having cardiometabolic syndrome, even when not presenting with the classic features.

genomics↗