Quantitative proteome comparison of human hearts with those of model organisms

Abstract

Delineating human cardiac pathologies and their basic molecular mechanisms relies on research conducted in model organisms. Yet translating findings from preclinical models to humans present a significant challenge, in part due to differences in cardiac protein expression between humans and model organisms. Proteins immediately determine cellular function, yet their large-scale investigation in hearts has lagged behind those of genes and transcripts. Here, we set out to bridge this knowledge gap: By analyzing protein profiles in humans and commonly used model organisms across cardiac chambers, we determine their commonalities and regional differences. We analyzed cardiac tissue from each chamber of human, pig, horse, rat, mouse, and zebrafish in biological replicates. Using mass spectrometry–based proteomics workflows, we measured and evaluated the abundance of approximately 7,000 proteins in each species. The resulting knowledgebase of cardiac protein signatures is accessible through an online database: atlas.cardiacproteomics.com. Our combined analysis allows for quantitative evaluation of protein abundances across cardiac chambers, as well as comparisons of cardiac protein profiles across model organisms. Up to a quarter of proteins with differential abundances between atria and ventricles showed opposite chamber-specific enrichment between species; these included numerous proteins implicated in cardiac disease. The generated proteomics resource facilitates translational prospects of cardiac studies from model organisms to humans by comparisons of disease-linked protein networks across species.

AdipoAtlas: A reference lipidome for human white adipose tissue

“…To support in-depth lipidome profiling, we created tissue pools of WAT representing SAT and VAT depots of lean (n = 5; BMI = 23.1 ± 1.5 kg/m 2 ; age = 68 ± 10.9 years; male/female = 3/2) and obese (n = 81; BMI = 45.1 ± 1.2 kg/m 2 ; age = 45 ± 2.2 years; male/female = 26/55) individuals. Indeed, pooling approaches are often used for time- and cost-intensive profiling of different levels of -ome organization including transcriptome, 14 , 15 proteome, 16 and lipidome (e.g., NIST Standard Reference Material [SRM] 1950 Metabolites in Frozen Human Plasma 6 ) characterizations. Here, we created three independent pools per each experimental group by using different subsets of individual samples, allowing the pools to be treated as independent biological replicates.…”

Loss of Nuclear Envelope Integrity and Increased Oxidant Production Cause DNA Damage in Adult Hearts Deficient in PKP2: A Molecular Substrate of ARVC

“…For proteomics, we extracted proteins through a combination of tissue homogenization, solubilization, and sonication followed by enzymatic digestion. 14,15 Peptides were labeled with chromatographically indistinguishable isobaric tandem mass tags, 16,17 separated into 46 fractions by high-pH reversed-phase fractionation and measured by high-resolution mass spectrometry. The resulting proteome dataset comprised 67 033 sequence-unique peptides accounting for 6181 proteins with an average protein sequence coverage of 24% (Figure 3A and Figure S7A).…”

A practical guide to interpreting and generating bottom‐up proteomics data visualizations

“…Mass spectrometry (MS)‐based bottom‐up proteomics allows comprehensive analysis of highly complex proteomes [1–6]. Thanks to recent technological advances that dramatically increased proteomic depth and throughput, MS technology is nowadays accessible to many non‐expert labs either through core facilities or individual proteomics setups.…”