Bioinformatical Analysis of Organ-Related (Heart, Brain, Liver, and Kidney) and Serum Proteomic Data to Identify Protein Regulation Patterns and Potential Sepsis Biomarkers

During the last years, proteomic studies have revealed several interesting findings in experimental sepsis models and septic patients. However, most studies investigated protein alterations only in single organs or in whole blood. To identify possible sepsis biomarkers and to evaluate the relationsh...

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Bibliographic Details
Published in:BioMed research international 2018-01, Vol.2018 (2018), p.1-11
Main Authors: Hinkelbein, Jochen, Boehm, Lennert, Kleinbrahm, Kathrin, Drinhaus, Hendrik, Cirillo, Fabrizio, Iovino, Ivan, Hohn, Andreas, De Robertis, Edoardo
Format: Article
Language:English
Subjects:
Analysis
Animals
Biological markers
Biomarkers
Blood
Blood proteins
Brain
Brain - metabolism
Cluster analysis
Critical care
Energy metabolism
Gene expression
Gene Expression Regulation
Genomics
Heart
Humans
Infection
Inflammation
Inflammatory response
Kidney - metabolism
Kidneys
Lipoproteins
Liver
Liver - metabolism
Male
Mass spectrometry
Medical research
Medicine, Experimental
Metabolism
Myocardium
Organs
Protein expression
Proteins
Proteome
Proteomics
Rats
Rats, Wistar
Regeneration
Scientific imaging
Sepsis
Sepsis - metabolism
Serum proteins
Software
Studies
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Summary:During the last years, proteomic studies have revealed several interesting findings in experimental sepsis models and septic patients. However, most studies investigated protein alterations only in single organs or in whole blood. To identify possible sepsis biomarkers and to evaluate the relationship between protein alteration in sepsis affected organs and blood, proteomics data from the heart, brain, liver, kidney, and serum were analysed. Using functional network analyses in combination with hierarchical cluster analysis, we found that protein regulation patterns in organ tissues as well as in serum are highly dynamic. In the tissue proteome, the main functions and pathways affected were the oxidoreductive activity, cell energy generation, or metabolism, whereas in the serum proteome, functions were associated with lipoproteins metabolism and, to a minor extent, with coagulation, inflammatory response, and organ regeneration. Proteins from network analyses of organ tissue did not correlate with statistically significantly regulated serum proteins or with predicted proteins of serum functions. In this study, the combination of proteomic network analyses with cluster analyses is introduced as an approach to deal with high-throughput proteomics data to evaluate the dynamics of protein regulation during sepsis.
ISSN:2314-6133
2314-6141
DOI:10.1155/2018/3576157