Proteomic analysis reveals a major role for contact inhibition in the terminal differentiation of hepatocytes

Hepatocytes are considered an exception of the paradigmatic inverse correlation between cell proliferation and terminal differentiation. In fact, hepatic vital functions are guaranteed by proliferating parenchymal cells during liver regeneration. However, a fine molecular characterization of the relationship between proliferation and differentiation in hepatocytes has been hampered by the lack of reliable in vivo or in vitro models

Analysis of the periplasmic proteome of Pseudomonas aeruginosa, a metabolically versatile opportunistic pathogen

The Gram-negative bacterium Pseudomonas aeruginosa is a main cause of infection in hospitalized, burned, immunocompromised, and cystic fibrosis patients. Many processes essential for P. aeruginosa pathogenesis, e.g., nutrient uptake, antibiotic resistance, and virulence, take place in the cell envelope and depend on components residing in the periplasmic space. Recent high-throughput studies focused on P. aeruginosa membrane compartments. However, the composition and dynamics of its periplasm remain largely uncharacterized. Here, we report a detailed description of the periplasmic proteome of the wild-type P. aeruginosa strain PAO1 by 2-DE and MALDI-TOF/TOF analysis. Three extraction methods were compared at proteome level in order to achieve the most reliable and comprehensive periplasmic protein map. A total of 495 spots representing 395 different proteins were identified. Most of the high intensity spots corresponded to periplasmic proteins, while cytoplasmic contaminants were mainly detected among faint spots. The majority, of the identified periplasmic proteins is involved in transport, cell envelope integrity, and protein folding control. Notably, more than 30% still has an unpredicted function. This work provides the first overview of the P. aeruginosa periplasm and offers the basis for future studies on periplasmic proteome changes occurring during P. aeruginosa adaptation to different environments and/or antibiotic treatments

Proteomic analysis reveals a major role for contact inhibition in the terminal differentiation of hepatocytes

Hepatocytes are considered an exception of the paradigmatic inverse correlation between cell proliferation and terminal differentiation. In fact, hepatic vital functions are guaranteed by proliferating parenchymal cells during liver regeneration. However, a fine molecular characterization of the relationship between proliferation and differentiation in hepatocytes has been hampered by the lack of reliable in vivo or in vitro models

Liver protein profiling in chronic hepatitis C: identification of potential predictive markers for interferon therapy outcome

The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks

Autophagy protects cells from HCV-induced defects in lipid metabolism

Autophagy is a lysosome-mediated catabolic process that mediates degradation and recycling of all major components of eukaryotic cells. Different stresses, including viral and bacterial infection, induce autophagy, which can promote cell survival by removing the stress inducer or by attenuating its dangerous effects. High levels of autophagy occur during infection of cells with hepatitis C virus (HCV), but the clinical relevance of this process is not clear

Liver Protein Profiling in Chronic Hepatitis C: Identification of Potential Predictive Markers for Interferon Therapy Outcome

The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks

Liver Protein Profiling in Chronic Hepatitis C: Identification of Potential Predictive Markers for Interferon Therapy Outcome

The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks

Liver Protein Profiling in Chronic Hepatitis C: Identification of Potential Predictive Markers for Interferon Therapy Outcome

The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks

Liver Protein Profiling in Chronic Hepatitis C: Identification of Potential Predictive Markers for Interferon Therapy Outcome

The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks

Liver Protein Profiling in Chronic Hepatitis C: Identification of Potential Predictive Markers for Interferon Therapy Outcome

The current anti-hepatitis C virus (HCV) therapy, based on pegylated-interferon alpha and ribavirin, has limited success rate and is accompanied by several side effects. The aim of this study was to identify protein profiles in pretreatment liver biopsies of HCV patients correlating with the outcome of antiviral therapy. Cytosolic or membrane/organelle-enriched protein extracts from liver biopsies of eight HCV patients were analyzed by two-dimensional fluorescence difference gel electrophoresis and mass spectrometry. Overall, this analysis identified 21 proteins whose expression levels correlate with therapy response. These factors are involved in interferon-mediated antiviral activity, stress response, and energy metabolism. Moreover, we found that post-translational modifications of dihydroxyacetone kinase were also associated with therapy outcome. Differential expression of the five best performing markers (STAT1, Mx1, DD4, DAK, and PD-ECGF) was confirmed by immunoblotting assays in an independent group of HCV patients. Finally, we showed that a prediction model based on the expression levels of these markers classifies responder and nonresponder patients with an accuracy of 85.7%. These results provide evidence that the analysis of pretreatment liver protein profiles is valuable for discriminating between responder and nonresponder HCV patients, and may contribute to reduce the number of nonresponder patients exposed to therapy-associated risks