Biology subjects

Rattray, N. J.

Publications and source records attributed to Rattray, N. J..

7 recordsLinked to original sources

bioRxiv2026

Plate-based ISD-SPE enables dual proteome-secretome concentration-response profiling of TLR signalling in iPSC-derived macrophages

Protein secretion represents a key functional output of cellular signalling, capturing dynamic responses to stimulation and pharmacological perturbation that shape immune behaviour. In macrophages, activation of Toll-like receptors (TLRs) drives tightly regulated secretion programmes that mediate inflammatory responses and provide a biologically meaningful readout of pathway activity. Whilst mass spectrometry (MS)-based secretomics enables unbiased profiling of these processes, broader application in drug discovery remains constrained by sample preparation workflows that limit scalability. Here, we describe a plate-based in-solution digestion and solid-phase extraction (ISD-SPE) workflow that enables 96-well processing of conditioned media for integrated proteome and secretome analysis from the same sample well. Benchmarking against a precipitation-based approach demonstrated comparable proteomic depth with improved quantitative reproducibility and robust performance across multiple plates. Coupled with dia-PASEF acquisition, this workflow enabled in-depth profiling of macrophage responses to TLR activation, resolving receptor-specific secretory programmes following TLR3, TLR4 and TLR7/8 activation. Extension of the approach to concentration-response studies enabled quantitative characterisation of pharmacological perturbation across intracellular and extracellular protein landscapes, revealing both shared and compartment-specific responses to TLR inhibition, as well as differences in apparent potency linked to secretion dynamics. Together, this workflow provides a scalable strategy for integrated analysis of intracellular signalling and downstream protein secretion, enabling systems-level characterisation of inflammatory responses and compound mechanisms of action.

immunology↗

bioRxiv2026

Translational toolkit for reproducible, cross-study profiling of human ageing hallmarks in human blood and tissue

BackgroundAgeing is a complex, multi-dimensional process, underpinned by interacting biological hallmarks that collectively contribute to functional decline and increased susceptibility to disease. While considerable progress has been made in delineating individual ageing pathways, translation into human studies has been hindered by methodological heterogeneity and a lack of standardised, multi-system approaches. Here, we describe a validated, high-resolution toolkit for the simultaneous quantification of multiple ageing hallmarks in clinically accessible human samples, encompassing cellular senescence, immune ageing, inflammation, mitochondrial function, mTOR signalling, autophagy, genomic instability, and stem cell exhaustion. MethodsBlood (25ml) was obtained from young and aged donors (26-81y). Deep immunophenotyping was performed using a novel 30-colour spectral flow cytometry panel. T-cell mTOR activation and autophagic flux were assessed by flow cytometry. Metabolic flux was measured by Seahorse. From whole blood (4 ml), muscle, and adipose tissue (AT) (obtained during elective hip arthroplasty) RNA, DNA, AT stem cells, and myoblasts were isolated. DNA copy number and senescent cell burden were assessed by q-PCR and SA-{beta}-gal staining, respectively. FindingsUtilising this toolkit, we identified pronounced age-related immune remodelling, increased senescent T-cell burden, diminished mitochondrial capacity and altered mTOR-autophagy signalling between healthy young and aged donors. Furthermore, metabolism was significantly affected by anti-coagulant and freezing sample before analysis. InterpretationThis integrated platform provides a foundation for reproducible, cross-study analyses and facilitates translational investigation of interventions targeting health-span extension. FundingWellcome Leap Dynamic Resilience program (co-funded by Temasek Trust).

immunology↗

bioRxiv2026

Pan-repository analysis reveals a drug-activating function of microbial bile acid conjugation

Microbially modified bile acids shape host physiology by regulating nutrient absorption, glucose homeostasis, circadian rhythms and thermoregulation. Here we identify a previously unrecognized drug-activating function of microbial bile acid conjugation. By systematically mining human LC-MS/MS datasets across public repositories and linking uncharacterized bile acid spectra to health-associated metadata, we discovered conjugates of the >75-year-old anti-inflammatory drug 5-aminosalicylic acid (5-ASA) with primary and secondary bile acids, including cholic, deoxycholic and lithocholic acids. These bile acid-drug conjugates were detected specifically in individuals treated with 5-ASA or its prodrugs. Multiple gut bacteria, including members of the Bacteroidota and Bacillota, generated cholyl-5-ASA in vitro, and bile salt hydrolase-associated transaminase activity was required for conjugate formation. In a mouse model of colitis, cholyl-5-ASA was associated with reduced intestinal inflammatory pathology and showed markedly enhanced activation of PPAR-{gamma} in cell-based reporter assays compared with 5-ASA alone. Consistent with this activity, cholyl-5-ASA elicited selective immunophenotypic changes in CD4 T cells in vitro, including increased Foxp3+ regulatory T cells. Together with prior evidence that 5-ASA efficacy depends on the microbiome, these findings support a model in which microbial bile acid conjugation represents a key activation step for 5-ASA therapy. More broadly, this work demonstrates how pan-repository metabolomics can uncover previously unrecognized microbiome-dependent chemical functions with direct therapeutic relevance.

biochemistry↗

bioRxiv2026

dia-PASEF Enables Rapid Profiling of the Human Secretome for Deeper Insights into Cellular Dynamics and Inflammatory Mechanisms

Protein secretion is a fundamental mechanism for cellular coordination and signalling, with its dysregulation leading to widespread physiological dysfunction and disease. Immunoassay formats that utilise secondary antibody readouts are the current gold standard for measuring secreted proteins, offering high specificity and sensitivity, but relying on predefined protein panels that constrain the discovery of novel biology. We present a scalable mass spectrometry-based workflow that combines data-independent acquisition with ion mobility and parallel fragmentation to deliver rapid, global profiling of the secretome. Using a translationally relevant human iPSC-derived macrophage model, our approach identified over 1200 proteins in under 15 minutes of acquisition time, delivering exceptional reproducibility across a large sample set. We applied this approach to profile pro-inflammatory phenotypes, confirming robust identification of key cytokines and chemokines whilst revealing non-canonical immune responses absent from both targeted panels and the intracellular proteome. In particular, we identified a unique cholesterol efflux signature, marked by the secretion of APOA1 and PON1, in response to Mycobacterium Tuberculosis, consistent with the metabolic reprogramming that takes place during infection. Furthermore, temporal profiling of macrophage responses to lipopolysaccharide over 24 hours resolved dynamic secretion trajectories that distinguish between acute and chronic inflammatory states. The extended time period facilitated the observation of distinct cytokine-dependent secretion phenotypes, with early secretion of TNF and IL6 initiating downstream signalling cascades that resulted in the delayed secretion of chemokines such as CXCL10 and CCL8. Collectively, these findings establish a robust, scalable platform for global characterisation of secretory networks. Beyond macrophage biology, this workflow offers broad utility for biomarker discovery, mechanistic studies of disease progression and evaluation of new therapeutic interventions, providing a powerful tool for advancing precision medicine.

immunology↗

bioRxiv2023

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

bioinformatics↗

bioRxiv2022

Integration of mass-spectrometry-based metabolomics and proteomics to characterise different senescence induced molecular sub-phenotypes

Cellular senescence is a key driver of ageing and its related disease. Thus, targeting and eliminating senescent cells is a major focus in biogerontology to predict and ameliorate age-related malady. Many studies have focused on targeting senescence through the identification of its molecular biomarkers. However, these are not specific for senescence and have different expression patterns across various senescence phenotypes. Here we report a combination of molecular studies ({beta}-galactosidase expression, DNA damage and replication immunodetection) with a mass spectrometry analysis integrating intra and extracellular global metabolomics to reveal small molecules differentially expressed across multiple senescence phenotypes (replicative senescence, x-ray, and chemical-induced senescence). Altered key intracellular metabolic changes were identified, depending on the stress stimuli, which were consistent with the presence of pro-inflammatory metabolites in the cellular secretome. Our work shows the advantage of combining molecular and metabolomics studies for the detailed analysis of cellular senescence and that senescence phenotype changes upon induction method.

molecular biology↗

bioRxiv2022

The differential metabolic signature of breast cancer cellular response to olaparib treatment

Metabolic reprogramming and genomic instability are key hallmarks of cancer, the combined analysis of which has gained recent popularity. Given the emerging evidence indicating the role of oncometabolites in DNA damage repair and its routine use in breast cancer treatment, it is timely to fingerprint the impact of olaparib treatment in cellular metabolism. Here, we report the biomolecular response of breast cancer cell lines with DNA damage repair defects to olaparib exposure. Following evaluation of olaparib sensitivity in breast cancer cell lines, we immunoprobed DNA double strand break foci and evaluated changes in cellular metabolism at various olaparib treatment doses using untargeted mass spectrometry-based metabolomics analysis. Following identification of altered features, we performed pathway enrichment analysis to measure key metabolic changes occurring in response to olaparib treatment. We show a cell-line dependent response to olaparib exposure, and an increased susceptibility to DNA damage foci accumulation in triple-negative breast cancer cell lines. Metabolic changes in response to olaparib treatment were cell-line and dose-dependent, where we predominantly observed metabolic reprogramming of glutamine-derived amino acids and lipids metabolism. Our work demonstrates the effectiveness of combining molecular biology and metabolomics studies for the comprehensive characterisation of cell lines with different genetic profiles. Follow-on studies are needed to map the baseline metabolism of breast cancer cells and their unique response to drug treatment. Fused with genomic and transcriptomics data, such readout can be used to identify key oncometabolites and inform the rationale for the design of novel drugs or chemotherapy combinations.

cancer biology↗