@article {49578, title = {The effects of telomere shortening on cancer cells: a network model of proteomic and microRNA analysis.}, volume = {105}, year = {2015}, month = {2015 Jan}, pages = {5-16}, abstract = {

Previously, we have shown that shortening of telomeres by telomerase inhibition sensitized cancer cells to cisplatinum, slowed their migration, increased DNA damage and impaired DNA repair. The mechanism behind these effects is not fully characterized. Its clarification could facilitate novel therapeutics development and may obviate the time consuming process of telomere shortening achieved by telomerase inhibition. Here we aimed to decipher the microRNA and proteomic profiling of cancer cells with shortened telomeres and identify the key mediators in telomere shortening-induced damage to those cells. Of 870 identified proteins, 98 were differentially expressed in shortened-telomere cells. 47 microRNAs were differentially expressed in these cells; some are implicated in growth arrest or act as oncogene repressors. The obtained data was used for a network construction, which provided us with nodal candidates that may mediate the shortened-telomere dependent features. These proteins{\textquoteright} expression was experimentally validated, supporting their potential central role in this system.

}, keywords = {Gene Expression Regulation, Neoplastic, Gene Regulatory Networks, HUMANS, MicroRNAs, Neoplasms, Oligonucleotides, Proteome, proteomics, Telomere Shortening, Tumor Cells, Cultured}, issn = {1089-8646}, doi = {10.1016/j.ygeno.2014.10.013}, author = {Uziel, O and Yosef, N and Sharan, R and Ruppin, E and Kupiec, M and Kushnir, M and Beery, E and Cohen-Diker, T and Nordenberg, J and Lahav, M} } @article {49736, title = {Stoichiometry of site-specific lysine acetylation in an entire proteome.}, journal = {J Biol Chem}, volume = {289}, year = {2014}, month = {2014 Aug 1}, pages = {21326-38}, abstract = {

Acetylation of lysine ϵ-amino groups influences many cellular processes and has been mapped to thousands of sites across many organisms. Stoichiometric information of acetylation is essential to accurately interpret biological significance. Here, we developed and employed a novel method for directly quantifying stoichiometry of site-specific acetylation in the entire proteome of Escherichia coli. By coupling isotopic labeling and a novel pairing algorithm, our approach performs an in silico enrichment of acetyl peptides, circumventing the need for immunoenrichment. We investigated the function of the sole NAD(+)-dependent protein deacetylase, CobB, on both site-specific and global acetylation. We quantified 2206 peptides from 899 proteins and observed a wide distribution of acetyl stoichiometry, ranging from less than 1\% up to 98\%. Bioinformatic analysis revealed that metabolic enzymes, which either utilize or generate acetyl-CoA, and proteins involved in transcriptional and translational processes displayed the highest degree of acetylation. Loss of CobB led to increased global acetylation at low stoichiometry sites and induced site-specific changes at high stoichiometry sites, and biochemical analysis revealed altered acetyl-CoA metabolism. Thus, this study demonstrates that sirtuin deacetylase deficiency leads to both site-specific and global changes in protein acetylation stoichiometry, affecting central metabolism.

}, keywords = {Acetylation, Amino Acid Sequence, Bacterial Proteins, Chromatography, High Pressure Liquid, Computational Biology, Escherichia coli, Lysine, Molecular Sequence Data, Proteome, Tandem Mass Spectrometry}, issn = {1083-351X}, doi = {10.1074/jbc.M114.581843}, author = {Baeza, Josue and Dowell, James A and Smallegan, Michael J and Fan, Jing and Amador-Noguez, Daniel and Khan, Zia and Denu, John M} } @article {49653, title = {Functional genomics of trypanosomatids.}, journal = {Parasite Immunol}, volume = {34}, year = {2012}, month = {2012 Feb-Mar}, pages = {72-9}, abstract = {

The decoding of the Tritryp reference genomes nearly 7 years ago provided a first peek into the biology of pathogenic trypanosomatids and a blueprint that has paved the way for genome-wide studies. Although 60-70\% of the predicted protein coding genes in Trypanosoma brucei, Trypanosoma cruzi and Leishmania major remain unannotated, the functional genomics landscape is rapidly changing. Facilitated by the advent of next-generation sequencing technologies, improved structural and functional annotation and genes and their products are emerging. Information is also growing for the interactions between cellular components as transcriptomes, regulatory networks and metabolomes are characterized, ushering in a new era of systems biology. Simultaneously, the launch of comparative sequencing of multiple strains of kinetoplastids will finally lead to the investigation of a vast, yet to be explored, evolutionary and pathogenomic space.

}, keywords = {Animals, Genome, Protozoan, Genomics, HUMANS, Proteome, Protozoan Proteins, Transcriptome, Trypanosomatina}, issn = {1365-3024}, doi = {10.1111/j.1365-3024.2011.01347.x}, author = {Choi, J and El-Sayed, N M} } @article {49740, title = {Global secretome analysis identifies novel mediators of bone metastasis.}, journal = {Cell Res}, volume = {22}, year = {2012}, month = {2012 Sep}, pages = {1339-55}, abstract = {

Bone is the one of the most common sites of distant metastasis of solid tumors. Secreted proteins are known to influence pathological interactions between metastatic cancer cells and the bone stroma. To comprehensively profile secreted proteins associated with bone metastasis, we used quantitative and non-quantitative mass spectrometry to globally analyze the secretomes of nine cell lines of varying bone metastatic ability from multiple species and cancer types. By comparing the secretomes of parental cells and their bone metastatic derivatives, we identified the secreted proteins that were uniquely associated with bone metastasis in these cell lines. We then incorporated bioinformatic analyses of large clinical metastasis datasets to obtain a list of candidate novel bone metastasis proteins of several functional classes that were strongly associated with both clinical and experimental bone metastasis. Functional validation of selected proteins indicated that in vivo bone metastasis can be promoted by high expression of (1) the salivary cystatins CST1, CST2, and CST4; (2) the plasminogen activators PLAT and PLAU; or (3) the collagen functionality proteins PLOD2 and COL6A1. Overall, our study has uncovered several new secreted mediators of bone metastasis and therefore demonstrated that secretome analysis is a powerful method for identification of novel biomarkers and candidate therapeutic targets.

}, keywords = {Animals, Biomarkers, Tumor, Bone Neoplasms, Cell Line, Tumor, Collagen Type VI, Computational Biology, HUMANS, Mass Spectrometry, Mice, Neoplasms, Plasminogen Activators, Procollagen-Lysine, 2-Oxoglutarate 5-Dioxygenase, Proteome, proteomics, Salivary Cystatins}, issn = {1748-7838}, doi = {10.1038/cr.2012.89}, author = {Blanco, Mario Andres and LeRoy, Gary and Khan, Zia and Ale{\v c}kovi{\'c}, Ma{\v s}a and Zee, Barry M and Garcia, Benjamin A and Kang, Yibin} } @article {49744, title = {Accurate proteome-wide protein quantification from high-resolution 15N mass spectra.}, journal = {Genome Biol}, volume = {12}, year = {2011}, month = {2011}, pages = {R122}, abstract = {

In quantitative mass spectrometry-based proteomics, the metabolic incorporation of a single source of 15N-labeled nitrogen has many advantages over using stable isotope-labeled amino acids. However, the lack of a robust computational framework for analyzing the resulting spectra has impeded wide use of this approach. We have addressed this challenge by introducing a new computational methodology for analyzing 15N spectra in which quantification is integrated with identification. Application of this method to an Escherichia coli growth transition reveals significant improvement in quantification accuracy over previous methods.

}, keywords = {algorithms, Amino Acid Sequence, Bacterial Proteins, Escherichia coli, Isotope Labeling, Mass Spectrometry, Molecular Sequence Data, Nitrogen Isotopes, Proteome, proteomics, Sensitivity and Specificity, software}, issn = {1474-760X}, doi = {10.1186/gb-2011-12-12-r122}, author = {Khan, Zia and Amini, Sasan and Bloom, Joshua S and Ruse, Cristian and Caudy, Amy A and Kruglyak, Leonid and Singh, Mona and Perlman, David H and Tavazoie, Saeed} } @article {38294, title = {Genome Properties: a system for the investigation of prokaryotic genetic content for microbiology, genome annotation and comparative genomics}, journal = {Bioinformatics (Oxford, England)Bioinformatics (Oxford, England)}, volume = {21}, year = {2005}, note = {http://www.ncbi.nlm.nih.gov/pubmed/15347579?dopt=Abstract}, type = {10.1093/bioinformatics/bti015}, abstract = {MOTIVATION: The presence or absence of metabolic pathways and structures provide a context that makes protein annotation far more reliable. Compiling such information across microbial genomes improves the functional classification of proteins and provides a valuable resource for comparative genomics. RESULTS: We have created a Genome Properties system to present key aspects of prokaryotic biology using standardized computational methods and controlled vocabularies. Properties reflect gene content, phenotype, phylogeny and computational analyses. The results of searches using hidden Markov models allow many properties to be deduced automatically, especially for families of proteins (equivalogs) conserved in function since their last common ancestor. Additional properties are derived from curation, published reports and other forms of evidence. Genome Properties system was applied to 156 complete prokaryotic genomes, and is easily mined to find differences between species, correlations between metabolic features and families of uncharacterized proteins, or relationships among properties. AVAILABILITY: Genome Properties can be found at http://www.tigr.org/Genome_Properties SUPPLEMENTARY INFORMATION: http://www.tigr.org/tigr-scripts/CMR2/genome_properties_references.spl.}, keywords = {Chromosome mapping, database management systems, Databases, Genetic, documentation, Gene Expression Profiling, Gene Expression Regulation, Genomics, Information Storage and Retrieval, Microbiological Techniques, natural language processing, Prokaryotic Cells, Proteome, signal transduction, software, User-Computer Interface, Vocabulary, Controlled}, author = {Haft, Daniel H. and J. Selengut and Brinkac, Lauren M. and Zafar, Nikhat and White, Owen} } @article {38304, title = {Genome sequence of the human malaria parasite Plasmodium falciparum}, journal = {NatureNature}, volume = {419}, year = {2002}, note = {http://www.ncbi.nlm.nih.gov/pubmed/12368864?dopt=Abstract}, type = {10.1038/nature01097}, abstract = {The parasite Plasmodium falciparum is responsible for hundreds of millions of cases of malaria, and kills more than one million African children annually. Here we report an analysis of the genome sequence of P. falciparum clone 3D7. The 23-megabase nuclear genome consists of 14 chromosomes, encodes about 5,300 genes, and is the most (A + T)-rich genome sequenced to date. Genes involved in antigenic variation are concentrated in the subtelomeric regions of the chromosomes. Compared to the genomes of free-living eukaryotic microbes, the genome of this intracellular parasite encodes fewer enzymes and transporters, but a large proportion of genes are devoted to immune evasion and host-parasite interactions. Many nuclear-encoded proteins are targeted to the apicoplast, an organelle involved in fatty-acid and isoprenoid metabolism. The genome sequence provides the foundation for future studies of this organism, and is being exploited in the search for new drugs and vaccines to fight malaria.}, keywords = {Animals, Chromosome Structures, DNA Repair, DNA Replication, DNA, Protozoan, Evolution, Molecular, Genome, Protozoan, HUMANS, Malaria Vaccines, Malaria, Falciparum, Membrane Transport Proteins, Molecular Sequence Data, Plasmodium falciparum, Plastids, Proteome, Protozoan Proteins, Recombination, Genetic, Sequence Analysis, DNA}, author = {Gardner, Malcolm J. and Hall, Neil and Fung, Eula and White, Owen and Berriman, Matthew and Hyman, Richard W. and Carlton, Jane M. and Pain, Arnab and Nelson, Karen E. and Bowman, Sharen and Paulsen, Ian T. and James, Keith and Eisen, Jonathan A. and Rutherford, Kim and Salzberg, Steven L. and Craig, Alister and Kyes, Sue and Chan, Man-Suen and Nene, Vishvanath and Shallom, Shamira J. and Suh, Bernard and Peterson, Jeremy and Angiuoli, Sam and Pertea, Mihaela and Allen, Jonathan and J. Selengut and Haft, Daniel and Mather, Michael W. and Vaidya, Akhil B. and Martin, David M. A. and Fairlamb, Alan H. and Fraunholz, Martin J. and Roos, David S. and Ralph, Stuart A. and McFadden, Geoffrey I. and Cummings, Leda M. and Subramanian, G. Mani and Mungall, Chris and Venter, J. Craig and Carucci, Daniel J. and Hoffman, Stephen L. and Newbold, Chris and Davis, Ronald W. and Fraser, Claire M. and Barrell, Bart} } @article {38492, title = {Sequence of Plasmodium falciparum chromosomes 2, 10, 11 and 14}, journal = {NatureNature}, volume = {419}, year = {2002}, note = {http://www.ncbi.nlm.nih.gov/pubmed/12368868?dopt=Abstract}, type = {10.1038/nature01094}, abstract = {The mosquito-borne malaria parasite Plasmodium falciparum kills an estimated 0.7-2.7 million people every year, primarily children in sub-Saharan Africa. Without effective interventions, a variety of factors-including the spread of parasites resistant to antimalarial drugs and the increasing insecticide resistance of mosquitoes-may cause the number of malaria cases to double over the next two decades. To stimulate basic research and facilitate the development of new drugs and vaccines, the genome of Plasmodium falciparum clone 3D7 has been sequenced using a chromosome-by-chromosome shotgun strategy. We report here the nucleotide sequences of chromosomes 10, 11 and 14, and a re-analysis of the chromosome 2 sequence. These chromosomes represent about 35\% of the 23-megabase P. falciparum genome.}, keywords = {Animals, Chromosomes, DNA, Protozoan, Genome, Protozoan, Plasmodium falciparum, Proteome, Protozoan Proteins, Sequence Analysis, DNA}, author = {Gardner, Malcolm J. and Shallom, Shamira J. and Carlton, Jane M. and Salzberg, Steven L. and Nene, Vishvanath and Shoaibi, Azadeh and Ciecko, Anne and Lynn, Jeffery and Rizzo, Michael and Weaver, Bruce and Jarrahi, Behnam and Brenner, Michael and Parvizi, Babak and Tallon, Luke and Moazzez, Azita and Granger, David and Fujii, Claire and Hansen, Cheryl and Pederson, James and Feldblyum, Tamara and Peterson, Jeremy and Suh, Bernard and Angiuoli, Sam and Pertea, Mihaela and Allen, Jonathan and J. Selengut and White, Owen and Cummings, Leda M. and Smith, Hamilton O. and Adams, Mark D. and Venter, J. Craig and Carucci, Daniel J. and Hoffman, Stephen L. and Fraser, Claire M.} }