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Nanoparticle-enabled plasma proteomics of a mouse atherosclerosis model
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ABSTRACT
Background
Dyslipidemia, 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.
Objectives
We aimed to profile the plasma proteins in experimental murine atherosclerosis with the primary goal of detecting low-abundant proteins.
Methods
Ldlr-/-
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® 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.
Results
We 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.
Conclusions
Nanoparticle-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.
Title: Nanoparticle-enabled plasma proteomics of a mouse atherosclerosis model
Description:
ABSTRACT
Background
Dyslipidemia, 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.
Objectives
We aimed to profile the plasma proteins in experimental murine atherosclerosis with the primary goal of detecting low-abundant proteins.
Methods
Ldlr-/-
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® 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.
Results
We 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.
Conclusions
Nanoparticle-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.
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