Integrated data mining of transcriptomic and proteomic datasets to predict the secretome of adipose tissue and muscle in ruminants

Abstract

Adipose tissue and muscle are endocrine organs releasing signalling and mediator proteins termed adipokines and myokines, enabling functioning of the organism and its adaption to a wide range of different challenges such as starvation, overfeeding, stress and diseases. They also contribute to the "adipose-muscular" cross-talk for an integrated control of body mass composition. This article integrates transcriptomic and proteomic data available in ruminant species (mainly in bovine, and when available in ovine and caprine) to computationally predict the large-scale secretome of adipose tissues and muscles. For this purpose predictive bioinformatics algorithms were employed to identify proteins putatively secreted by tissues thanks to a signal peptide. We predicted 1749 secreted proteins that were found from adipose tissues and muscles, more than a half of them being already declared as secreted proteins in public repositories. We also identified 188 and 357 proteins in the predictive secretome of adipose tissues and muscles respectively, only a minor part (3-11%) of them being reported in the overlap of public repositories used for comparison. Functional analysis of these proteins highlights their involvement in biological pathways known to sustain tissue growth and functioning. This strategy allowed us to identify some known and putative novel adipomyokines, adipokines and myokines. However their role and their expression signature depending on rearing practices remain largely to be explored.

Aggregation of Omic Data and Secretome Prediction Enable the Discovery of Candidate Plasma Biomarkers for Beef Tenderness

“…As a first step in the biomarker identification workflow [66], we designed a study based on the review of the literature and the aggregation of molecular data related to meat tenderness. According to Bonnet et al [67], we performed a computational reconstruction of the secretome putatively linked to tenderness from the aggregated data, and searched for proteins secreted in the plasma. With this approach, we proposed a list of 71 putative plasma proteins to be investigated further as candidate plasma biomarkers for meat tenderness.…”

“…In brackets in the QTL column: chromosome associated with the Tenderness score and/or Shear force QTL. The first 29 promising candidates were selected when located in tenderness QTL (n = 24) and/or identified (n = 5) in [67]. The four plasma proteins reported at the bottom of table were obtained by overlapping between the BPA and the list of 67 putative muscle biomarkers published in [67].…”

Proceedings of the 10th International Symposium on the Nutrition of Herbivores

“…Lists of unique Gene Names (GN) up-and down-regulated in low RFI groups were submitted to a custom analysis using ProteINSIDE. (http://www.proteinside.org/ ) to mine biological information and predict secreted proteins with Signal P sequence (Bonnet et al, 2016). The lists of proteins secreted thanks to a SignalP were compared to a list of 1106 plasma bovine proteins from publications and proteome analysis.…”

“…Materials & methods Proteomic, transcriptomic and genetic muscle data related to beef tenderness (with significant correlation, differential abundance in extreme groups, or gene polymorphism) were collected from 54 publications including 1 GEO dataset (GSE9256) and computed according to Bonnet et al (2016). Aggregation of the Gene Names (GN) from 3 datasets (proteomics, transcriptomics and genetics) were analysed using ProteINSIDE (http://www.proteinside.org/) to find biological information and predict secretion through a signal P sequence (SignalP score ≥ 0.5; TargetP score ≤ 2) or through a non-classical pathway without signal P (TargetP score ≤ 2).…”

Proteomics in Veterinary Medicine and Animal Science: Neglected Scientific Opportunities with Immediate Impact

“…Proteomic investigation has been applied to many aspects of cattle production, including adipose tissue and liver metabolism, and also the several conditions that constitute the periparturient diseases. While including mastitis, these transition period conditions also include endometritis, lameness, fat cow syndrome, milk fever, and ketosis which together make the period around calving of special research interest.…”