Silver nanoparticles (AgNPs), embedded into a specific polysaccharide (EPS), were biogenerated by Klebsiella oxytoca DSM 29614 under aerobic (AgNPs-EPSaer) and anaerobic conditions (AgNPs-EPSanaer). Both AgNPs-EPS matrices were tested by MTT assay for cytotoxic activity against human breast (SKBR3 and 8701-BC) and colon (HT-29, HCT 116 and Caco-2) cancer cell lines, revealing AgNPs-EPSaer as the most active, in terms of IC50, with a more pronounced efficacy against breast cancer cell lines. Therefore, colony forming capability, morphological changes, generation of reactive oxygen species (ROS), induction of apoptosis and autophagy, inhibition of migratory and invasive capabilities and proteomic changes were investigated using SKBR3 breast cancer cells with the aim to elucidate AgNPs-EPSaer mode of action. In particular, AgNPs-EPSaer induced a significant decrease of cell motility and MMP-2 and MMP-9 activity and a significant increase of ROS generation, which, in turn, supported cell death mainly through autophagy and in a minor extend through apoptosis. Consistently, TEM micrographs and the determination of total silver in subcellular fractions indicated that the Ag+ accumulated preferentially in mitochondria and in smaller concentrations in nucleus, where interact with DNA. Interestingly, these evidences were confirmed by a differential proteomic analysis that highlighted important pathways involved in AgNPs-EPSaer toxicity, including endoplasmic reticulum stress, oxidative stress and mitochondrial impairment triggering cell death trough apoptosis and/or autophagy activation.

BackgroundThe endemic seagrass Posidonia oceanica (L.) Delile colonizes soft bottoms producing highly productive meadows that play a crucial role in coastal ecosystems dynamics. Human activities and natural events are responsible for a widespread meadows regression; to date the identification of "diagnostic" tools to monitor conservation status is a critical issue. In this study the feasibility of a novel tool to evaluate ecological impacts on Posidonia meadows has been tested. Quantification of a putative stress indicator, i.e. phenols content, has been coupled to 2-D electrophoretic protein analysis of rhizome samples.ResultsThe overall expression pattern from Posidonia rhizome was determined using a preliminary proteomic approach, 437 protein spots were characterized by pI and molecular weight. We found that protein expression differs in samples belonging to sites with high or low phenols: 22 unique protein spots are peculiar of "low phenols" and 27 other spots characterize "high phenols" samples.ConclusionPosidonia showed phenols variations within the meadow, that probably reflect the heterogeneity of environmental pressures. In addition, comparison of the 2-D electrophoresis patterns allowed to highlight qualitative protein expression differences in response to these pressures. These differences may account for changes in metabolic/physiological pathways as adaptation to stress. A combined approach, based on phenols content determination and 2-D electrophoresis protein pattern, seems a promising tool to monitor Posidonia meadows health state.

The S100 gene family is the largest subfamily of calcium binding proteins of EF-hand type, expressed in tissue and cell-specific manner, acting both as intracellular regulators and extracellular mediators. There is a growing interest in the S100 proteins and their relationships with different cancers because of their involvement in a variety of biological events closely related to tumorigenesis and cancer progression. However, the collective role and the possible coordination of this group of proteins, as well as the functional implications of their expression in breast cancer (BC) is still poorly known. We previously reported a large-scale proteomic investigation performed on BC patients for the screening of multiple forms of S100 proteins. Present study was aimed to assess the functional correlation between protein and gene expression patterns and the prognostic values of the S100 family members in BC. By using data mining, we showed that S100 members were collectively deregulated in BC, and their elevated expression levels were correlated with shorter survival and more aggressive phenotypes of BC (basal like, HER2 enriched, ER-negative and high grading). Moreover a multi-omics functional network analysis highlighted the regulatory effects of S100 members on several cellular pathways associated with cancer and cancer progression, expecially immune response and inflammation. Interestingly, for the first time, a pathway analysis was successfully applied on different omics data (transcriptomics and proteomics) revealing a good convergence between pathways affected by S100 in BC. Our data confirm S100 members as a promising panel of biomarkers for BC prognosis.

Autism Spectrum Disorders (ASDs) are childhood neurodevelopmental disorders with complex genetic origins. Previous studies have investigated the role of de novo Copy Number Variants (CNVs) and microRNAs as important but distinct etiological factors in ASD. We developed a novel computational procedure to assess the potential pathogenic role of microRNA genes overlapping de novo CNVs in ASD patients. Here we show that for chromosomes # 1, 2 and 22 the actual number of miRNA loci affected by de novo CNVs in patients was found significantly higher than that estimated by Monte Carlo simulation of random CNV events. Out of 24 miRNA genes over-represented in CNVs from these three chromosomes only hsa-mir-4436b-1 and hsa-mir-4436b-2 have not been detected in CNVs from non-autistic subjects as reported in the Database of Genomic Variants. Altogether the results reported in this study represent a first step towards a full understanding of how a dysregulated expression of the 24 miRNAs genes affect neurodevelopment in autism. We also propose that the procedure used in this study can be effectively applied to CNVs/miRNA genes association data in other genomic disorders beyond autism.

According to recent statistics, breast cancer remains one of the leading causes of death among women in Western countries. Breast cancer is a complex and heterogeneous disease, presently classified into several subtypes according to their cellular origin. Among breast cancer histotypes, infiltrating ductal carcinoma represents the most common and potentially aggressive form. Despite the current progress achieved in early cancer detection and treatment, including the new generation of molecular therapies, there is still need for identification of multiparametric biomarkers capable of discriminating between cancer subtypes and predicting cancer progression for personalized therapies. One established step in this direction is the proteomic strategy, expected to provide enough information on breast cancer profiling. To this aim, in the present study we analyzed 13 breast cancer tissues and their matched non-tumoral tissues by 2-DE. Collectively, we identified 51 protein spots, corresponding to 34 differentially expressed proteins, which may represent promising candidate biomarkers for molecular-based diagnosis of breast cancer and for pattern discovery. The relevance of these proteins as factors contributing to breast carcinogenesis is discussed.