Quantitative proteome comparison of human hearts with those of model organisms

Autor: Jesper V. Olsen, Nora Linscheid, Christian Stolte, Alberto Santos, Lars Juhl Jensen, Pia R. Lundegaard, Morten S. Olesen, Johan Z. Ye, Pi Camilla Poulsen, Kirstine Calloe, Ulrike Leurs, Morten B. Thomsen, Bo Hjorth Bentzen, Robert W. Mills, Alicia Lundby
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Proteomics
0301 basic medicine
Proteome
Swine
Biopsy
Protein Expression
ved/biology.organism_classification_rank.species
030204 cardiovascular system & hematology
Mice
Mathematical and Statistical Techniques
0302 clinical medicine
Medicine and Health Sciences
Cardiac Atria
Biology (General)
Zebrafish
Principal Component Analysis
General Neuroscience
Statistics
Methods and Resources
Eukaryota
Heart
Animal Models
Experimental Organism Systems
Osteichthyes
Organ Specificity
Vertebrates
Physical Sciences
Models
Animal
Anatomy
General Agricultural and Biological Sciences
Cardiac Ventricles
QH301-705.5
Heart Ventricles
Surgical and Invasive Medical Procedures
Computational biology
Biology
Research and Analysis Methods
General Biochemistry
Genetics and Molecular Biology
03 medical and health sciences
Model Organisms
Species Specificity
Gene Expression and Vector Techniques
Animals
Humans
Horses
Statistical Methods
Molecular Biology Techniques
Model organism
Molecular Biology
Gene
Molecular Biology Assays and Analysis Techniques
General Immunology and Microbiology
ved/biology
Myocardium
Organisms
Biology and Life Sciences
Cardiac Ventricle
biology.organism_classification
Rats
Fish
030104 developmental biology
Cardiac chamber
Multivariate Analysis
Cardiovascular Anatomy
Animal Studies
Zoology
Protein Processing
Post-Translational
Mathematics
Function (biology)
Zdroj: PLoS Biology, Vol 19, Iss 4, p e3001144 (2021)
Linscheid, N, Santos, A, Poulsen, P C, Mills, R W, Calloe, K, Leurs, U, Ye, J Z, Stolte, C, Thomsen, M B, Bentzen, B H, Lundegaard, P R, Olesen, M S, Jensen, L J, Olsen, J V & Lundby, A 2021, ' Quantitative proteome comparison of human hearts with those of model organisms ', PLOS Biology, vol. 19, no. 4, e3001144 . https://doi.org/10.1371/journal.pbio.3001144
PLoS Biology
ISSN: 1545-7885
1544-9173
Popis: 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.
This study provides protein abundance profiles for thousands of proteins across cardiac chambers for humans and five commonly used model organisms. This quantitative proteomics dataset represents the most comprehensive such resource to date, and can be queried via a web browser to identify the most appropriate model organism for future studies.
Databáze: OpenAIRE
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