Proteomics

The slowing down or stalling of replication forks is commonly known as replication stress and arises from multiple causes such as DNA lesions, nucleotide depletion, RNA‐DNA hybrids, and oncogene activation. The ataxia telangiectasia and Rad3‐related kinase (ATR) plays an essential role in the cellular response to replication stress and inhibition of ATR has emerged as therapeutic strategy for the treatment of cancers that exhibit high levels of replication stress. However, the cellular signaling induced by replication stress and the substrate spectrum of ATR has not been systematically investigated. In this study, we employed quantitative MS‐based proteomics to define the cellular signaling after nucleotide depletion‐induced replication stress and replication fork collapse following ATR inhibition. We demonstrate that replication stress results in increased phosphorylation of a subset of proteins, many of which are involved in RNA splicing and transcription and have previously not been associated with the cellular replication stress response. Furthermore, our data reveal the ATR‐dependent phosphorylation following replication stress and discover novel putative ATR target sites on MCM6, TOPBP1, RAD51AP1, and PSMD4. We establish that ATR inhibition rewires cellular signaling networks induced by replication stress and leads to the activation of the ATM‐driven double‐strand break repair signaling.

The monocyte‐like human histiocytic lymphoma cell line U937 can be induced by phorbol 12‐myristate 13‐acetate (PMA) to undergo differentiation into a macrophage‐like phenotype. We have used two‐dimensional gel electrophoresis (2‐DE), oligonucleotide microarrays and principal component analysis (PCA) to characterize the U937 cell line as a model system for the differentiation of monocytes into macrophages. A total of 226 differentially expressed proteins were found, of which 41 were selected by PCA for identification using matrix‐assisted laser desorption/ionization tandem mass spectrometry. Based on the PCA results, three marker proteins were selected for confirmation of differential expression using Western blot and quantitative real time‐PCR. The selected marker proteins were: gamma interferon inducible lysosomal thiol reductase, cathepsin D and adipocyte‐fatty acid binding protein. All three proved to be good differentiation markers for macrophage maturation of U937 cells as well as peripheral blood‐derived macrophages. The transcriptomics data revealed a large number of additional putative differentiation markers in U937 macrophages, many of which are known to be expressed in peripheral blood‐derived macrophages. These include osteospontin, matrix metalloproteinase 9, and HC‐gp39. Our results show that the characteristics of U937 macrophages resemble those of inflammatory (exudate) macrophages, exemplified by the down‐regulation of 5' nucleotidase and the up‐regulation of leucine aminopeptidase mRNAs. In conclusion, using the powerful combination of transcriptomics, 2‐DE and PCA, our results show that U937 cells differentiated by PMA treatment are an excellent model system for monocyte derived macrophage generation from blood.

The pharmacological activities displayed by Bothrops jararaca venom undergo a significant ontogenetic shift. Similarly, the diet of this species changes from ectothermic prey in early life to endothermic prey in adulthood. In this study we used large and representative newborn and adult venom samples consisting of pools from 694 and 110 specimens, respectively, and demonstrate a significant ontogenetic shift in the venom proteome complexity of B. jararaca. 2‐DE coupled to MS protein identification showed a clear rearrangement of the toxin arsenal both in terms of the total proteome, as of the glycoproteome. N‐glycosylation seems to play a key role in venom protein variability between newborn and adult specimens. Upon the snake development, the subproteome of metalloproteinases undergoes a shift from a P‐III‐rich to a P‐I‐rich profile while the serine proteinase profile does not vary significantly. We also used isobaric tag labeling (iTRAQ) of venom tryptic peptides for the first time to examine the quantitative changes in the venom toxins of B. jararaca upon neonate to adult transition. The iTRAQ analysis showed changes in various toxin classes, especially the proteinases. Our study expands the in‐depth understanding of venom complexity variation particularly with regard to toxin families that have been associated with envenomation pathogenesis.

The major difference between inorganic minerals and biominerals is the presence of an organic matrix consisting of proteins, glycoproteins, proteoglycans, and polysaccharides, which is synthesized by specialized cells under genetic control before or during mineralization. The organic matrix is thought to play a major role in the assembly of the biomineral and determination of its mechanical properties. The recent elucidation of the chicken genome provided an opportunity to explore the matrix proteome of a biomineral using up‐to‐date MS‐based technology. We identified 520 proteins in this matrix including the ten matrix proteins already known before. The identified proteins were divided into three abundance groups using the exponentially modified protein abundance index described recently which was roughly calibrated with the few known data on protein yield derived from Edman sequence analysis. A small group of 32 highly abundant proteins contained the presently known eggshell‐specific proteins and all of the other known eggshell matrix constituents identified before with much less sensitive conventional methods. The present study, which is the first comprehensive proteomic study of a vertebrate biomineral, is intended as a starting point for the detailed molecular characterization of eggshell matrix proteins, their interactions in the matrix network and functional studies.

The bacteria Xylella fastidiosa is the causative agent of a number of economically important crop diseases, including citrus variegated chlorosis. Although its complete genome is already sequenced, X. fastidiosa is very poorly characterized by biochemical approaches at the protein level. In an initial effort to characterize protein expression in X. fastidiosa we used one‐ and two‐dimensional gel electrophoresis and mass spectrometry to identify the products of 142 genes present in a whole cell extract and in an extracellular fraction of the citrus isolated strain 9a5c. Of particular interest for the study of pathogenesis are adhesion and secreted proteins. Homologs to proteins from three different adhesion systems (type IV fimbriae, mrk pili and hsf surface fibrils) were found to be coexpressed, the last two being detected only as multimeric complexes in the high molecular weight region of one‐dimensional electrophoresis gels. Using a procedure to extract secreted proteins as well as proteins weakly attached to the cell surface we identified 30 different proteins including toxins, adhesion related proteins, antioxidant enzymes, different types of proteases and 16 hypothetical proteins. These data suggest that the intercellular space of X. fastidiosa colonies is a multifunctional microenvironment containing proteins related to in vivo bacterial survival and pathogenesis. A codon usage analysis of the most expressed proteins from the whole cell extract revealed a low biased distribution, which we propose is related to the slow growing nature of X. fastidiosa. A database of the X. fastidiosa proteome was developed and can be accessed via the internet (URL: www.proteome.ibi.unicamp.br).

The human salivary acidic proline‐rich proteins (aPRPs) complex was investigated by different chromatographic and mass spectrometric approaches and the main aPRPs, namely PRP‐1, PRP‐2 and PIF‐s (15 515 amu), Db‐s (17 632 amu) and Pa (15 462 amu) proteins, were detected. All these isoforms are phosphorylated at Ser‐8 and Ser‐22 and have a pyroglutamic moiety at the N‐terminus. Apart from Pa, all the other aPRPs undergo a proteolytic cleavage at Arg‐106 residue (Arg‐127 in Db‐s protein), that generates the small PC peptide (4371 amu) and PRP‐3, PRP‐4, PIF‐f (11 162 amu) and Db‐f (13 280 amu) proteins, all of which were detected. With regard to the Pa protein, the main form detected was the dimeric derivative (Pa 2‐mer, 30 922 amu) originated by a disulfide bond involving Cys‐103 residue. Besides these known isoforms, several previously undetected aPRP derivatives were found (in minor amounts): (i) the triphosphorylated derivatives of PRP‐1/PRP‐2/PIF‐s and Db‐s, showing the additional phosphate group at Ser‐17; (ii) the mono‐phosphorylated forms at either Ser‐22 or Ser‐8 of PRP‐1/PRP‐2/PIF‐s, PRP‐3/PRP‐4/PIF‐f, Db‐s and Db‐f; (iii) a nonphosphorylated form of PRP‐3/PRP‐4/PIF‐f; (iv) the triphosphorylated and diphosphorylated forms of Pa 2‐mer. Moreover, minor quantities of PRP‐3/PRP‐4/PIF‐f lacking the C‐terminal Arg (11 006 amu), and of Pa 2‐mer lacking the C‐terminal Gln (30 793 amu) were found. By this approach the different phenotypes of PRH1 locus in 59 different subjects were characterized.

Large amounts of human protein interaction data have been produced by experiments and prediction methods. However, the experimental coverage of the human interactome is still low in contrast to predicted data. To gain insight into the value of publicly available human protein network data, we compared predicted datasets, high‐throughput results from yeast two‐hybrid screens, and literature‐curated protein‐protein interactions. This evaluation is not only important for further methodological improvements, but also for increasing the confidence in functional hypotheses derived from predictions. Therefore, we assessed the quality and the potential bias of the different datasets using functional similarity based on the Gene Ontology, structural iPfam domain‐domain interactions, likelihood ratios, and topological network parameters. This analysis revealed major differences between predicted datasets, but some of them also scored at least as high as the experimental ones regarding multiple quality measures. Therefore, since only small pair wise overlap between most datasets is observed, they may be combined to enlarge the available human interactome data. For this purpose, we additionally studied the influence of protein length on data quality and the number of disease proteins covered by each dataset. We could further demonstrate that protein interactions predicted by more than one method achieve an elevated reliability.