Biology subjects

Pinto, S. M.

Publications and source records attributed to Pinto, S. M..

3 recordsLinked to original sources

bioRxiv2026

Capillary-based Subcellular Sampling Uncovers the Stress Granule Proteome in Single Cells

Many diseases arise from dysfunction within specific organelles or biomolecular condensates, highlighting the value of analysing proteins at subcellular resolution to uncover new biological mechanisms. We report a novel capillary-based subcellular sampling workflow coupled with liquid chromatography-mass spectrometry (LC-MS) for proteomic analysis of defined subcellular regions of individual cells. We applied this methodology to stress granules (SGs), membrane-less biomolecular condensates that form in response to cellular stress (including viral infection), and are implicated in infection, neuropathology and cancer. Comprehensive characterisation of SG protein composition remains limited by technical challenges associated with bulk purification, including loss of spatial context, dynamic behaviour and contamination from cytosolic material. Using our novel method, we identified a high-confidence set of 405 SG-associated proteins, including 46 established SG residents alongside numerous previously unreported candidates. Functional enrichment analysis revealed pathways consistent with known SG biology, while comparison with an independent cytosolic proteome dataset demonstrated minimal overlap, supporting the specificity of the sampling strategy. Selected novel SG protein candidates (AHNAK2, DDX39B, NUDT1 and FKBP2) were validated using immunofluorescence microscopy. These findings establish capillary-based subcellular sampling as a viable approach for proteomic analysis of SGs with preserved spatial context and provide a framework for analysing other subcellular compartments. Table of contentsWe report an LC-MS-based capillary sampling workflow for proteomic analysis of subcellular structures within single cells. This methodology identified 405 high-confidence stress granule-associated proteins, including 46 previously established and numerous novel candidates. The approach demonstrated high specificity and preserved spatial context, expanding the capabilities of subcellular proteomics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=55 SRC="FIGDIR/small/724230v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1fa0bb0org.highwire.dtl.DTLVardef@1158524org.highwire.dtl.DTLVardef@1d82812org.highwire.dtl.DTLVardef@2ee4d9_HPS_FORMAT_FIGEXP M_FIG C_FIG Figure made in Biorender.com.

cell biology↗

bioRxiv2026

Longitudinal serum proteomics analyses reveal biomarkers for porcine influenza and coronavirus infections

Respiratory virus infections affect both humans and livestock, causing considerable mortality and morbidity. While respiratory pathogens such as swine influenza A virus (pH1N1) and porcine respiratory coronavirus (PRCV) often present with overlapping clinical symptoms, their pathological trajectories and outcomes differ. Given the propensity for pathogen spillover and the use of pigs as a physiologically relevant large-animal translational model, we aimed to characterise host serum protein signatures that detect and differentiate pH1N1 from PRCV, enabling improved disease monitoring and control. Using high-resolution mass spectrometry- based proteomics, we identified 162 serum proteins that were significantly dysregulated across 3 infection timepoints (1, 5, and 12 days post-infection (DPI)), with signatures correlating with viral shedding and lung pathology as early as 1 DPI. Notably, multiplexed targeted analysis of a subset of proteins in an independent cohort from a different breed and geographic location demonstrated detection, femtomole-level targeted quantitation, and validation of SRGN as a diagnostic marker for pH1N1 and PRCV (AUC=0.85). Further, SOD1 was validated as an early marker for PRCV, increasing as early as 1 DPI (AUC= 0.9). Finally, a multi-peptide signature composed of SRGN, SOD1, and RAN demonstrated reasonable predictive power for pH1N1 (AUC=0.75) and PRCV (AUC=0.65) at 1 DPI. Our data validate the proteomic screening, provide insights into the role of early protein markers in distinguishing respiratory viral infections, and pave the way for the development of point-of-care diagnostics and targeted prevention strategies, enhancing preparedness against emerging zoonotic threats.

biochemistry↗

bioRxiv2022

MultiOMICs landscape of SARS-CoV-2-induced host responses in human lung epithelial cells

Despite the availability of vaccines and approved therapeutics, the COVID-19 pandemic continues to rise owing to the emergence of newer variants. Several multi-omics studies have made available extensive evidence on host-pathogen interactions and potential therapeutic targets. Nonetheless, an increased understanding of host signaling networks regulated by post-translational modifications and their ensuing effect on the biochemical and cellular dynamics is critical to expanding the current knowledge on the host response to SARS-CoV-2 infections. Here, employing unbiased global transcriptomics, proteomics, acetylomics, phosphoproteomics, and exometabolome analysis of a lung-derived human cell line, we show that SARS-CoV-2 Norway/Trondheim-S15 strain induces time-dependent alterations in the induction of type I IFN response, activation of DNA damage response, dysregulated Hippo signaling, among others. We provide evidence for the interplay of phosphorylation and acetylation dynamics on host proteins and its effect on the altered release of metabolites, especially organic acids and ketone bodies. Together, our findings serve as a resource of potential targets that can aid in designing novel host-directed therapeutic strategies.

systems biology↗