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Matamalas, J. T.

Publications and source records attributed to Matamalas, J. T..

2 recordsLinked to original sources

Nanoparticle-enabled plasma proteomics of a mouse atherosclerosis model

BackgroundDyslipidemia, marked by elevated LDL-cholesterol (LDL-C), is a major risk factor for coronary heart disease. Mouse experimental models, such as Ldlr-/- mice that develop atherosclerosis and metabolic disorders when fed a high-fat diet (HFD), are indispensable for studying disease mechanisms and identifying potential biomarkers. ObjectivesWe aimed to profile the plasma proteins in experimental murine atherosclerosis with the primary goal of detecting low-abundant proteins. MethodsLdlr-/- mice were fed a chow diet or HFD for 3 (n = 27 per group) or 6 months (n = 12 per group). Plasma samples were processed using nanoparticle technology (Proteograph(R) XT Assay; Seer, Inc), and peptides were analyzed using the Orbitrap Astral (Thermo Fisher Scientific) in data-independent acquisition mode. For tissue proteomics, ten aortas were pooled for n = 4 pools per time point and diet, and n = 6 livers per time point and diet. Peptides were analyzed on the Orbitrap Exploris 480 in data-dependent mode. Proteomes were queried against the Tabula Muris mouse single-cell, STRING, and Gene Ontology databases, and queried against a genome-wide association list of 419 risk loci for coronary artery disease. ResultsWe sequenced 5,080 plasma proteins, surpassing previous reports by 10-fold. The prototypical apolipoproteins and complement factors were the most abundant proteins, whereas proteins associated with cytokine/chemokine signaling represented the previously uncharted mouse plasma proteome. We divided the proteome into quartiles (Q1-Q4) to monitor sweeping changes over time. Proteins with a sustained enrichment in HFD (n = 705) were indicative of liver cell subtypes (Tabula Muris). Whereas proteins that moved up from the lower quartiles - Q2 (n = 228), Q3 (115) and Q4 (63) - associated with leukocyte, fibroblasts, and endothelial cell markers, indicating that signatures of inflammation and endothelial activation increase with disease progression. Notably, 86 and 146 proteins were increased at 3 and 6 months, including MMP-12 and COL6A3. Classical apolipoproteins exhibited heterogeneous responses - SAA3 and APOC2 increased, while APOA1, APOE, and LCAT decreased with high-fat feeding, suggesting impaired high-density lipoprotein (HDL) functionality. Proteins shared between plasma and aorta were enriched for extracellular matrix components, while those overlapping with liver reflected metabolic processes. Finally, 120 coronary artery disease (CAD)-associated proteins from human GWAS were detected in Ldlr-/- plasma, of which 4, including lipoprotein lipase, exhibited an increase in abundance with HFD. ConclusionsNanoparticle-dependent proteome enrichment coupled to mass spectrometry may allow to identify novel plasma biomarkers in Ldlr-/- mice and facilitate monitoring of candidate proteins associated with human disease mechanisms in preclinical interventional studies, thereby opening new avenues for understanding disease pathology and uncovering novel molecular contributors.

pathology↗

Cross-species proteomics quantification pipeline distinguishes donor versus host extracellular matrix in explanted biomaterials

Xenogenic biomaterial durability, including bioprosthetic heart valves (BPVs), is compromised by pathological extracellular matrix (ECM) remodeling, resulting in progressive structural degeneration. Mass spectrometry-based proteomics can help reveal BPV degeneration mechanisms; however, peptide sequence similarity between donor and host species complicates protein-level analysis. We present a cross-species proteomic analytical strategy for xenogenic biomaterials and cross-species proteomic datasets. In silico tryptic digestion of human and bovine protein databases identified over 400 overlapping proteins with a high protein percent identity. Explanted human BPV tissue was divided into macroscopically distinct regions of degeneration and analyzed by mass spectrometry. A peptide-level strategy quantified protein abundances in a species-delineated analysis. We highlighted degeneration region-specific depositions of key human ECM proteins and bovine ECM proteins whose abundance is time dependent. We demonstrated that single-species analysis of a cross-species proteome results in inaccurate quantification. This study highlights the importance of distinguishing between donor and host species proteomes for accurate protein quantification. While focused on clinically explanted biomaterials, our approach is broadly applicable to all forms of xenotransplantation and the use of xenogenic matrices.

bioengineering↗