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Although the COVID-19 pandemic has ended, it is important to understand the pathology of severe SARS-CoV-2 infection associated with respiratory failure and high mortality. The plasma proteome, including protein modification by lipid peroxidation products in COVID-19 survivors (COVID-19; n = 10) and deceased individuals (CovDeath; n = 10) was compared in samples collected upon admission to the hospital, when there was no difference in their status, with that of healthy individuals (Ctr; n = 10). The obtained results show that COVID-19 development strongly alters the expression of proteins involved in the regulation of exocytosis and platelet degranulation (top 20 altered proteins indicated by analysis of variance; p-value (False Discovery Rate) cutoff at 5%). These changes were most pronounced in the CovDeath group. In addition, the levels of 4-hydroxynonenal (4-HNE) adducts increased 2- and 3-fold, whereas malondialdehyde (MDA) adducts increased 7- and 2.5-fold, respectively, in COVID-19 and CovDeath groups. Kinases and proinflammatory proteins were particularly affected by these modifications. Protein adducts with 15-deoxy-12,14-prostaglandin J2 (15d-PGJ2) were increased 2.5-fold in COVID-19 patients, including modifications of proteins such as p53 and STAT3, whereas CovDeath showed a decrease of approximately 60% compared with Ctr. This study for the first time demonstrates the formation of lipid metabolism products—protein adducts in plasma from survived and deceased COVID-19 patients, significantly distinguishing them, which may be a predictor of the course of SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]

Although the COVID-19 pandemic has ended, it is important to understand the pathology of severe SARS-CoV-2 infection associated with respiratory failure and high mortality. The plasma proteome, including protein modification by lipid peroxidation products in COVID-19 survivors (COVID-19; n = 10) and deceased individuals (CovDeath; n = 10) was compared in samples collected upon admission to the hospital, when there was no difference in their status, with that of healthy individuals (Ctr; n = 10). The obtained results show that COVID-19 development strongly alters the expression of proteins involved in the regulation of exocytosis and platelet degranulation (top 20 altered proteins indicated by analysis of variance; p-value (False Discovery Rate) cutoff at 5%). These changes were most pronounced in the CovDeath group. In addition, the levels of 4-hydroxynonenal (4-HNE) adducts increased 2- and 3-fold, whereas malondialdehyde (MDA) adducts increased 7- and 2.5-fold, respectively, in COVID-19 and CovDeath groups. Kinases and proinflammatory proteins were particularly affected by these modifications. Protein adducts with 15-deoxy-12,14-prostaglandin J2 (15d-PGJ2) were increased 2.5-fold in COVID-19 patients, including modifications of proteins such as p53 and STAT3, whereas CovDeath showed a decrease of approximately 60% compared with Ctr. This study for the first time demonstrates the formation of lipid metabolism products—protein adducts in plasma from survived and deceased COVID-19 patients, significantly distinguishing them, which may be a predictor of the course of SARS-CoV-2 infection.

Beef quality is a complex phenotype that can be evaluated only after animal slaughtering. Previous research has investigated the potential of genetic markers or muscle-derived proteins to assess beef tenderness. Thus, the use of low-invasive biomarkers in living animals is an issue for the beef sector. We hypothesized that publicly available data may help us discovering candidate plasma biomarkers. Thanks to a review of the literature, we built a corpus of articles on beef tenderness. Following data collection, aggregation, and computational reconstruction of the muscle secretome, the putative plasma proteins were searched by comparison with a bovine plasma proteome atlas and submitted to mining of biological information. Of the 44 publications included in the study, 469 unique gene names were extracted for aggregation. Seventy-one proteins putatively released in the plasma were revealed. Among them 13 proteins were predicted to be secreted in plasma, 44 proteins as hypothetically secreted in plasma, and 14 additional candidate proteins were detected thanks to network analysis. Among these 71 proteins, 24 were included in tenderness quantitative trait loci. The in-silico workflow enabled the discovery of candidate plasma biomarkers for beef tenderness from reconstruction of the secretome, to be examined in the cattle plasma proteome. [ABSTRACT FROM AUTHOR]

Beef quality is a complex phenotype that can be evaluated only after animal slaughtering. Previous research has investigated the potential of genetic markers or muscle-derived proteins to assess beef tenderness. Thus, the use of low-invasive biomarkers in living animals is an issue for the beef sector. We hypothesized that publicly available data may help us discovering candidate plasma biomarkers. Thanks to a review of the literature, we built a corpus of articles on beef tenderness. Following data collection, aggregation, and computational reconstruction of the muscle secretome, the putative plasma proteins were searched by comparison with a bovine plasma proteome atlas and submitted to mining of biological information. Of the 44 publications included in the study, 469 unique gene names were extracted for aggregation. Seventy-one proteins putatively released in the plasma were revealed. Among them 13 proteins were predicted to be secreted in plasma, 44 proteins as hypothetically secreted in plasma, and 14 additional candidate proteins were detected thanks to network analysis. Among these 71 proteins, 24 were included in tenderness quantitative trait loci. The in-silico workflow enabled the discovery of candidate plasma biomarkers for beef tenderness from reconstruction of the secretome, to be examined in the cattle plasma proteome.