Premium
In this issue
Publication year - 2009
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200990090
Subject(s) - biology , gene , proteome , computational biology , genetics , microbiology and biotechnology
Abstract Shigellosis, dysentery — by whatever name — Don't kiss the chimps pp. 5029–5045 With a 10–15% mortality rate when untreated in young children and immunedeficient patients, over one million deaths per year are attributable to this primate/human‐only disease. Furthermore, the Shigella spp. have developed resistance to b‐lactam, tetracycline, and aminoglycoside antibiotics very rapidly. A non‐primate model of the disease is based on gnotobiotic piglets. Aerobically grown bacteria shift to anaerobic metabolism when introduced into the GI tract of the piglets. Pieper et al. examined the aerobic and anaerobic proteomes using differential display methodology on 2‐D gels. Over 1050 separate gene products were identified. Bacterial defense genes and secretion system genes were among the types found. Novel proteins that might be targets for vaccines or drugs were also identified (OmpA, HtpG, and OspC2).Form follow/leads functions? Essentiality, centrality and network topology pp. 5143–5154 Who ever thought eight or ten years ago that we would be learning network‐speak to keep up with contemporary molecular and cell biology? Collaborating with mathematicians and physicists? Raise your hand. As I thought, not many. With the completion of the human genome DNA sequence it became clear that the sequence did not code for enough proteins to account for the complexity of life. At least two sources of complexity have been discovered to date: post‐translational modification and protein–protein interaction networks (PPINs). The structure of PPINs is examined in this work from Park et al. , who raise the question (in Facebook terms): does popularity correlate with importance? They used two yeast PPINs to see how well centrality correlated with essentiality and found that, using 40 measures of centrality, the relationship was close for path‐based localized information centrality and gene essentiality. They found that random forest classifiers can work, too.Standing on the shoulders of the great: Telomerase proteomics pp. 5175–5187 In those early days of molecular biology, when all “model replication systems” (bacteria and phages) went through circular intermediates, we did not need to worry about linear ends. Then we came to the end of the world, the end of the linear chromosome. Elizabeth Blackburn, Carol Greider, and Jack Szostak worked out the mechanics and enzymology of faithful replication of those linear ends and for that work received the 2009 Nobel Prize in physiology and medicine. Now researchers such as Zimmermann et al. can apply the tools of proteomics to tease apart the subtleties of telomere control of and control by other proteins. These researchers demonstrate the utility of SELDI MS/MS to examine the changes in specific cell fractions upon up‐ or down‐expression of telomere regulatory components. They confirmed several observations and found a new role for S100A6 (AKA “calcyclin”) in cell response to telomere dysfunction.