Integrated proteomics identified up-regulated focal adhesion-mediated proteins in human squamous cell carcinoma in an orthotopic murine model

Understanding the molecular mechanisms of oral carcinogenesis will yield important advances in diagnostics, prognostics, effective treatment, and outcome of oral cancer. Hence, in this study we have investigated the proteomic and peptidomic profiles by combining an orthotopic murine model of oral squamous cell carcinoma (OSCC), mass spectrometry-based proteomics and biological network analysis. Our results indicated the up-regulation of proteins involved in actin cytoskeleton organization and cell-cell junction assembly events and their expression was validated in human OSCC tissues. In addition, the functional relevance of talin-1 in OSCC adhesion, migration and invasion was demonstrated. Taken together, this study identified specific processes deregulated in oral cancer and provided novel refined OSCC-targeting molecules.Understanding the molecular mechanisms of oral carcinogenesis will yield important advances in diagnostics, prognostics, effective treatment, and outcome of oral cancer. Hence, in this study we have investigated the proteomic and peptidomic profiles by co95e98208FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO2009/54067-3; 2010/19278-0; 2011/22421-2; 2009/53839-2; 2011/02267-9470567/2009-0; 470549/2011-4; 301702/2011-0; 470268/2013-1; 505413/2013-

Integrative analysis to select cancer candidate biomarkers to targeted validation

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOTargeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS.Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS6414363543652FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO2009/54067-3; 2010/19278-0; 2011/22421-2; 2009/53839-2470567/2009-0; 470549/2011-4; 301702/2011-0; 470268/2013-

Nop53p interacts with 5.8S rRNA co-transcriptionally, and regulates processing of pre-rRNA by the exosome

In eukaryotes, pre-rRNA processing depends on a large number of nonribosomal trans-acting factors that form intriguingly organized complexes. One of the early stages of pre-rRNA processing includes formation of the two intermediate complexes pre-40S and pre-60S, which then form the mature ribosome subunits. Each of these complexes contains specific pre-rRNAs, ribosomal proteins and processing factors. The yeast nucleolar protein Nop53p has previously been identified in the pre-60S complex and shown to affect pre-rRNA processing by directly binding to 5.8S rRNA, and to interact with Nop17p and Nip7p, which are also involved in this process. Here we show that Nop53p binds 5.8S rRNA co-transcriptionally through its N-terminal region, and that this protein portion can also partially complement growth of the conditional mutant strain Delta nop53/GAL:NOP53. Nop53p interacts with Rrp6p and activates the exosome in vitro. These results indicate that Nop53p may recruit the exosome to 7S pre-rRNA for processing. Consistent with this observation and similar to the observed in exosome mutants, depletion of Nop53p leads to accumulation of polyadenylated pre-rRNAs

The Flood Risk and Water Supply Implications of Seasonal Precipitation Reconstructions in Northern California

Subsets of annual and sub-annual tree-ring chronologies are used to reconstruct seasonal precipitation totals in northern California. The specific seasons selected for reconstruction are based on the strongest monthly precipitation signals recorded in the tree-ring data. Earlywood width of gray pine is best correlated with Oct-Dec precipitation at the onset of the wet season. Latewood width of ponderosa pine is correlated with Mar–Apr totals at the end of the wet season. These earlywood and latewood width chronologies are used to develop separate reconstructions of precipitation for the “autumn” (Oct–Dec) and “spring” (Mar–Apr) seasons. Total ring-width chronologies of blue oak are highly correlated with October–April precipitation totals and are used to reconstruct precipitation for the “wet season.” We then computed one additional skillful reconstruction by subtracting the reconstructed spring totals from the wet season precipitation estimates (i.e., “winter” [Oct–Feb]). We compare the winter and spring reconstructions because they are well calibrated and provide an interesting long-term perspective on the interaction of winter–spring precipitation amounts near March 1, when important reservoir management decisions are often made. Consecutive wet winter and very wet spring precipitation anomalies increased after 1950 in the instrumental and reconstructed time-series, often coinciding with the largest spring streamflow and flood events recorded on the American River at Folsom. Once the sub-annual tree-ring data can be improved, it may be possible to develop discrete reconstructions of early-, middle-, and late-season precipitation for the past 250 to 500 years, to help define natural variability and anthropogenic forcing of seasonal precipitation totals in California

Typic: A Practical and Robust Tool to Rank Proteotypic Peptides for Targeted Proteomics

The selection of a suitable proteotypic peptide remains a challenge for designing a targeted quantitative proteomics assay. Although the criteria are well-established in the literature, the selection of these peptides is often performed in a subjective and time-consuming manner. Here, we have developed a practical and semiautomated workflow implemented in an open-source program named Typic. Typic is designed to run in a command line and a graphical interface to help selecting a list of proteotypic peptides for targeted quantitation. The tool combines the input data and downloads additional data from public repositories to produce a file per protein as output. Each output file includes relevant information to the selection of proteotypic peptides organized in a table, a colored ranking of peptides according to their potential value as targets for quantitation and auxiliary plots to assist users in the task of proteotypic peptides selection. Taken together, Typic leads to a practical and straightforward data extraction from multiple data sets, allowing the identification of most suitable proteotypic peptides based on established criteria, in an unbiased and standardized manner, ultimately leading to a more robust targeted proteomics assay

Typic: A Practical and Robust Tool to Rank Proteotypic Peptides for Targeted Proteomics

The selection of a suitable proteotypic peptide remains a challenge for designing a targeted quantitative proteomics assay. Although the criteria are well-established in the literature, the selection of these peptides is often performed in a subjective and time-consuming manner. Here, we have developed a practical and semiautomated workflow implemented in an open-source program named Typic. Typic is designed to run in a command line and a graphical interface to help selecting a list of proteotypic peptides for targeted quantitation. The tool combines the input data and downloads additional data from public repositories to produce a file per protein as output. Each output file includes relevant information to the selection of proteotypic peptides organized in a table, a colored ranking of peptides according to their potential value as targets for quantitation and auxiliary plots to assist users in the task of proteotypic peptides selection. Taken together, Typic leads to a practical and straightforward data extraction from multiple data sets, allowing the identification of most suitable proteotypic peptides based on established criteria, in an unbiased and standardized manner, ultimately leading to a more robust targeted proteomics assay

Different interactomes for p70‐S6K1 and p54‐S6K2 revealed by proteomic analysis

S6Ks are major effectors of the mTOR (mammalian target of rapamycin) pathway, signaling for increased protein synthesis and cell growth in response to insulin, AMP/ATP levels, and amino acids. Deregulation of this pathway has been related to disorders and diseases associated with metabolism, such as obesity, diabetes, and cancer. S6K family is composed of two main members, S6K1 and S6K2, which comprise different isoforms resulted from alternative splicing or alternative start codon use. Although important molecular functions have been associated with p70‐S6K1, the most extensively studied isoform, the S6K2 counterpart lacks information. In the present study, we performed immunoprecipitation assays followed by mass spectrometry (MS) analysis of FLAG‐tagged p70‐S6K1 and p54‐S6K2 interactomes, after expression in HEK293 cells. Protein lists were submitted to CRAPome (Contaminant Repository for Affinity Purification) and SAINT (Significance Analysis of INTeractome) analysis, which allowed the identification of high‐scoring interactions. By a comparative approach, p70‐S6K1 interacting proteins were predominantly related to “cytoskeleton” and “stress response,” whereas p54‐S6K2 interactome was more associated to “transcription,” “splicing,” and “ribosome biogenesis.” Moreover, we have found evidences for new targets or regulators of the S6K protein family, such as proteins NCL, NPM1, eIF2α, XRCC6, PARP1, and ILF2/ILF3 complex. This study provides new information about the interacting networks of S6Ks, which may contribute for future approaches to a better understanding of the mTOR/S6K pathway162026502666FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP2012/13558-7; 2013/16848-9; 2013/22696-7; 2014/01386-

Aspartic peptidase of Phialophora verrucosa as target of HIV peptidase inhibitors: blockage of its enzymatic activity and interference with fungal growth and macrophage interaction

Phialophora verrucosa causes several fungal human diseases, mainly chromoblastomycosis, which is extremely difficult to treat. Several studies have shown that human immunodeficiency virus peptidase inhibitors (HIV-PIs) are attractive candidates for antifungal therapies. This work focused on studying the action of HIV-PIs on peptidase activity secreted by P. verrucosa and their effects on fungal proliferation and macrophage interaction. We detected a peptidase activity from P. verrucosa able to cleave albumin, sensitive to pepstatin A and HIV-PIs, especially lopinavir, ritonavir and amprenavir, showing for the first time that this fungus secretes aspartic-type peptidase. Furthermore, lopinavir, ritonavir and nelfinavir reduced the fungal growth, causing remarkable ultrastructural alterations. Lopinavir and ritonavir also affected the conidia-macrophage adhesion and macrophage killing. Interestingly, P. verrucosa had its growth inhibited by ritonavir combined with either itraconazole or ketoconazole. Collectively, our results support the antifungal action of HIV-PIs and their relevance as a possible alternative therapy for fungal infections