Cover Picture: Proteomics 1/2009

In this issue of Proteomics you will find the following highlighted articles: How many tries before you get it right? British Prime Minister Benjamin Disraeli is reputed to have stated that “There are three types of lies: lies, damned lies and statistics.” As those immersed in bioinformatics have recognized, though they may be slippery characters, statistics are the only way some information can be extracted from an experimental structure. One of the recurring problems is the question of how many samples need to be tested to get a reasonable, reliable result. This is particularly important when samples are difficult to get, require arduous preparation, or yield only small amounts. These experiments are generally multidimensional. In this article Cairns et al., examine the number of mass spectrometry samples that are required for a quantitative answer in a biomarker search. They evaluate MALDI‐TOF and SELDI‐TOF data for sources and amounts of variability on a pilot scale (biological and technical particularly) which allows them to calculate the number of samples required for a valid full‐scale screen. Cairns, D. A. et al., Proteomics 2009, 9, 74‐86. Double‐barreled proteomic run on embryonic stem cell membranes Embryonic stem cells (ESC) appear to be as close to the fountain of youth as most of us can reasonably expect to get in this lifetime. How close they come to being a “silver bullet” for cancer and other diseases is yet to be determined. Intoh et al., have taken a major step forward in improving our understanding of ESC control and maintenance. They applied 2‐D DIGE and trypsin digestion + iTRAQ labeling to identify membrane and membrane‐associated proteins in mouse ESCs that had or had not been exposed to leukemia inhibitory factor, a factor which maintains pluripotency in ESCs. Some 338 membrane and membrane‐associated proteins, up‐ or down‐regulated, were identified and assigned to functional groups. Intoh, A. et al., Proteomics 2009, 9, 126‐137. H, M, L You see these three letters on a variety of simple controllers: pump speed, temperature, under‐desk foot warmers, etc. Now you can hope to see them soon on bottles in a cell mass isotope labeling kit. Schwanhäusser et al., describe here a protocol for following levels of protein expression in array volumes and numbers with array simplicity. They pulse label samples with Heavy, Medium, or Light amino acids. Pulse‐labeling has been used for determining protein turnover rates for eons but with a quantitation problem for translation: did the ratio change because the numerator changed or because the denominator changed? The answer comes from labeling the untreated control with the M amino acid, then mixing M+H or M+L samples before fractionating by SDS‐PAGE and high‐resolution LC‐MS/MS. It worked for cell fractions (HeLa) as well as whole cells (yeast). Schwanhäusser, B. et al., Proteomics 2009, 9, 205‐209.     

Cover Picture: Proteomics 15/2008

In this issue of Proteomics you will find the following highlighted articles: An old dog refines new tricks Old dogs are reputed to be slow learners but they can be subtle manipulators, able to induce younger dogs and gullible owners to share the food dish in their favor or choose the path they prefer. Two‐dimensional gel electrophoresis has been around for more than 25 years but “new and improved” versions continue to appear. Ericsson et al. scramble the order of several steps to get more information out of the combination of IPG/IEF and “shotgun” peptide analysis. Developed for studying mechanisms of drug resistance in small cell lung cancer, the modified protocol fractionates sonically disrupted cells into microsomes and soluble fractions before tryptic digestion and iTRAQ labeling for later quantitation. Digested samples were fractionated on narrow range immobilized pH gradient strips from which they were eluted for MALDI TOF or LC‐MS/MS analysis. Detection and identification of transmembrane proteins were dramatically improved. Ericsson, H. et al., Proteomics 2008, 8, 3008–3018. An evanescent view of a lectin micro‐array: through a glass faintly Lectins have the ability to distinguish closely‐related carbohydrate moieties attached (or not) to other molecules such as proteins, peptides, lipids, cells, etc. In some respects, they are much like antibodies, just not quite as specific. Using an array of 45 different lectins, the glycan portion of glycoproteins can be identified by its binding profile. Here, Uchiyama et al. report the improvements they have made to the reproducibility and sensitivity of the system. The binding of rhodamine‐labeled probes was detected in an evanescent field fluorescence‐based instrument that was capable of reaching, 10pM levels without having to wash off unbound probe. Depositing lectin spots with a non‐contact type printer, at the right humidity, and blocking with a non‐proteinaceous material greatly improved sensitivity. Uchiyama, N. et al., Proteomics 2008, 8, 3042–3050. The innate defense: multiplex proteomic probing The body's first line of defense against pathogen infection is the innate response. In the case of bacterial infection, it is initiated by the sensing of the universal Gram‐positive cell wall lipopolysaccharide (LPS) component by macrophages primarily (but not solely) through the Toll‐like receptor 4 (TLR4). To understand the regulation of the LPS response, Gu et al. developed a multiplex quantitative proteomic analysis procedure to follow the response of TLR4+ and TLR4? cell lines. The method of choice was amino acid‐coded mass tagging (AACT, also referred to as SILAC). It showed high efficiency of labeling (95%) which eliminated interference with quantitation by the unlabeled fraction. Using triplex labeling of lysine (13C, 15N), the authors confirmed that TLR4? cells did show a response to LPS: 25 proteins were up‐regulated in TLR4+ cells, 5 in TLR4? cells. More than 500 proteins could be quantitated. Gu, S. et al., Proteomics 2008, 8, 3061–3070.     

In this issue: Proteomics 15/2008

In this issue of Proteomics you will find the following highlighted articles: An old dog refines new tricks Old dogs are reputed to be slow learners but they can be subtle manipulators, able to induce younger dogs and gullible owners to share the food dish in their favor or choose the path they prefer. Two‐dimensional gel electrophoresis has been around for more than 25 years but “new and improved” versions continue to appear. Ericsson et al. scramble the order of several steps to get more information out of the combination of IPG/IEF and “shotgun” peptide analysis. Developed for studying mechanisms of drug resistance in small cell lung cancer, the modified protocol fractionates sonically disrupted cells into microsomes and soluble fractions before tryptic digestion and iTRAQ labeling for later quantitation. Digested samples were fractionated on narrow range immobilized pH gradient strips from which they were eluted for MALDI TOF or LC‐MS/MS analysis. Detection and identification of transmembrane proteins were dramatically improved. Ericsson, H. et al., Proteomics 2008, 8, 3008–3018. An evanescent view of a lectin micro‐array: through a glass faintly Lectins have the ability to distinguish closely‐related carbohydrate moieties attached (or not) to other molecules such as proteins, peptides, lipids, cells, etc. In some respects, they are much like antibodies, just not quite as specific. Using an array of 45 different lectins, the glycan portion of glycoproteins can be identified by its binding profile. Here, Uchiyama et al. report the improvements they have made to the reproducibility and sensitivity of the system. The binding of rhodamine‐labeled probes was detected in an evanescent field fluorescence‐based instrument that was capable of reaching, 10pM levels without having to wash off unbound probe. Depositing lectin spots with a non‐contact type printer, at the right humidity, and blocking with a non‐proteinaceous material greatly improved sensitivity. Uchiyama, N. et al., Proteomics 2008, 8, 3042–3050. The innate defense: multiplex proteomic probing The body's first line of defense against pathogen infection is the innate response. In the case of bacterial infection, it is initiated by the sensing of the universal Gram‐positive cell wall lipopolysaccharide (LPS) component by macrophages primarily (but not solely) through the Toll‐like receptor 4 (TLR4). To understand the regulation of the LPS response, Gu et al. developed a multiplex quantitative proteomic analysis procedure to follow the response of TLR4+ and TLR4? cell lines. The method of choice was amino acid‐coded mass tagging (AACT, also referred to as SILAC). It showed high efficiency of labeling (95%) which eliminated interference with quantitation by the unlabeled fraction. Using triplex labeling of lysine (13C, 15N), the authors confirmed that TLR4? cells did show a response to LPS: 25 proteins were up‐regulated in TLR4+ cells, 5 in TLR4? cells. More than 500 proteins could be quantitated. Gu, S. et al., Proteomics 2008, 8, 3061–3070.     

Cover Picture: Proteomics 11/2008

In this issue of Proteomics you will find the following highlighted articles: Pancreatic cancer signs autograph on micro antibody array Pancreatic cancer has been one of the nastier members of the “Discovered‐too‐late‐to‐do‐anything‐about‐it” disease club. Its 5‐year survival rate is 3–5 % because of late diagnosis and no effective therapy for advanced disease cases. This paper by Ingvarsson et al. reports their encouraging findings on the use of recombinant antibody microarrays to survey serum for diagnostic and prognostic proteins. In these “proof‐of‐concept” experiments they found a signature of 19 unique scFv antibodies, specific for immunoregulatory proteins, that could distinguish pancreatic cancer from normal and from Helicobacter pylori (an indicator of inflammation, 3 out of 14 overlap). The test panel distinguished long and short survivors (with only one long survivor misclassified). Data was classified using a Support Vector Machine. The classifier was validated by multiple splits of the data and leave‐one‐out tests. Ingvarsson, J. et al., Proteomics 2008, 8, 2211–2219. Of cadmium and zinc: Brothers or not? Cadmium and zinc occupy the same column in the periodic table so you might expect some biological similarities. Not much luck – mercury is also in that column. Zinc, under tight control, is an essential mineral; cadmium is toxic and induces a variety of defensive responses. A highly zinc‐resistant cell line (HZR) has been derived from the human HeLa line. Rousselet et al. have compared the proteomes of HZR and HeLa cultured in Cd and Zn using a variety of proteomic and genomic tools. MALDI‐TOF MS after 2‐DE revealed examples of a co‐chaperone, a heat‐shock organizing protein (Hop), ubiquitin and a number of reactive oxygen species control proteins elevated in HZR. Of special interest was 4‐hydroxyphenyl‐pyruvate dioxygenase (HPPD), catalyst of one of the first breakdown steps of tyrosine. The complex relationships revealed will require a lot more than one paragraph for explanation. Rousselet, E. et al., Proteomics 2008, 8, 2244–2255. Grey box proteomics of salty species In the classic black box experiment you know nothing about the contents of the box. I propose a grey box for experiments directed by homologous knowledge – like these. Pandhal et al. have developed a protocol for proteomic analysis of an unsequenced species by homology. The organism of interest is a halotolerant cyanobacterium, Euhalothece sp. which can grow in NaCl concentrations ranging from 0% to >9% NaCl. The nearest sequenced relative is a Synechocystis sp. By metabolic labeling with ¹⁵N/­¹⁴N, the researchers were able to use MS to match proteins from the two species and also quantitate changes in levels of proteins in response to salt levels. Three labelling experiments ([% NaCl], 0% +3%, 3% +6%, and 3% +9%) yielded 229, 212, and 96 proteins, respectively, by MASCOT search of proteins with two peptides of each isotope. MS BLAST found 32, 30, and 7 more proteins, respectively. Pandhal, J. et al., Proteomics 2008, 8, 2266–2284.     

In this issue: Proteomics 9/2009

In this issue of Proteomics you will find the following highlighted articles: Rafting on the pond It seems that any river with a drop of more than 20‐30 cm/km is a candidate for a commercially viable rafting business. Biochemical rafters are pickier. They need a detergent‐resistant lipid raft where they can set up their signaling system. Kim et al. examined the changes in the raft molecules involved in insulin stimulated pre‐adipocyte to adipocyte differentiation (adipogenesis). A substantial number of adipocyte raft‐specific proteins were identified by immunoblots and confirmed by 2‐DE MS. A protein of particular interest was gC1qR, specific for mature adipocyte rafts, which also binds complement C1q and a number of other extracellular proteins (vitronectin, fibrinogen, hyaluronic acids . . .). Down‐regulation of gC1qR by siRNA was paralleled by reduction of insulin signaling through gC1qR, through the insulin receptor, and prevented adipogenesis. The rafts also were home to a variety of mitochondrial proteins during adipogenesis. Kim, K.‐B. et al., Proteomics 2009, 9, 2373‐2382. E. coli chaperone SurA is recognized SurA was a sad protein. It was sad because it couldn't get promoted without proof that it had done a good job on its current assignment. But what was that assignment? Being a good little protein, it did its best to never make a mistake and its good was very good, making thousands of perfect cycles. Still, no‐one noticed. Then one day, Vertommen et al. decided to give SurA a rest (actually its clone rested). After creating the deletion clone, they fired up the proteome machines to see what had changed. The lab was quiet as the proteomers collected their results. They sat down with the data and looked and talked, studied and talked. They finally came to a conclusion: SurA was indeed a chaperone and was responsible for transport of eight important bbarrel proteins across the periplasmic space to the outer membrane! And now a publication! Vertommen, D.. et al., Proteomics 2009, 9, 2432‐2443. Aphid saliva: solvent, glue, caulk, . . . Children learn quickly that if they don't wash their faces properly, a mother's wet thumb will finish the job. If hair won't stay where it belongs, you can always use saliva. Spots on your glasses or your computer monitor? Aphids and mosquitoes extend the uses even further. Carolan et al. report on the active components of saliva of the pea aphid (Acrythosiphon pisum), an agricultural pest that attacks legumes. The researchers used mass spectrometry, RNAi, and various types of electrophoresis to identify the nine proteins secreted in pea aphid saliva. From the complete genome sequence, four proteins could be identified by homology: a metalloprotease [M2], a zinc [M1] protease, both probably cleaving plant defensive peptides, a glucose oxidoreductase that probably detoxifies phytochemicals, and a relative of regucalsin, which might suppress Ca+2 mediated defense. Three of the proteins could not be matched to any known proteins. Carolan, J. C. et al., Proteomics 2009, 9, 2457‐2467.     

In this issue: Proteomics 11/2008

In this issue of Proteomics you will find the following highlighted articles: Pancreatic cancer signs autograph on micro antibody array Pancreatic cancer has been one of the nastier members of the “Discovered‐too‐late‐to‐do‐anything‐about‐it” disease club. Its 5‐year survival rate is 3–5 % because of late diagnosis and no effective therapy for advanced disease cases. This paper by Ingvarsson et al. reports their encouraging findings on the use of recombinant antibody microarrays to survey serum for diagnostic and prognostic proteins. In these “proof‐of‐concept” experiments they found a signature of 19 unique scFv antibodies, specific for immunoregulatory proteins, that could distinguish pancreatic cancer from normal and from Helicobacter pylori (an indicator of inflammation, 3 out of 14 overlap). The test panel distinguished long and short survivors (with only one long survivor misclassified). Data was classified using a Support Vector Machine. The classifier was validated by multiple splits of the data and leave‐one‐out tests. Ingvarsson, J. et al., Proteomics 2008, 8, 2211–2219. Of cadmium and zinc: Brothers or not? Cadmium and zinc occupy the same column in the periodic table so you might expect some biological similarities. Not much luck – mercury is also in that column. Zinc, under tight control, is an essential mineral; cadmium is toxic and induces a variety of defensive responses. A highly zinc‐resistant cell line (HZR) has been derived from the human HeLa line. Rousselet et al. have compared the proteomes of HZR and HeLa cultured in Cd and Zn using a variety of proteomic and genomic tools. MALDI‐TOF MS after 2‐DE revealed examples of a co‐chaperone, a heat‐shock organizing protein (Hop), ubiquitin and a number of reactive oxygen species control proteins elevated in HZR. Of special interest was 4‐hydroxyphenyl‐pyruvate dioxygenase (HPPD), catalyst of one of the first breakdown steps of tyrosine. The complex relationships revealed will require a lot more than one paragraph for explanation. Rousselet, E. et al., Proteomics 2008, 8, 2244–2255. Grey box proteomics of salty species In the classic black box experiment you know nothing about the contents of the box. I propose a grey box for experiments directed by homologous knowledge – like these. Pandhal et al. have developed a protocol for proteomic analysis of an unsequenced species by homology. The organism of interest is a halotolerant cyanobacterium, Euhalothece sp. which can grow in NaCl concentrations ranging from 0% to >9% NaCl. The nearest sequenced relative is a Synechocystis sp. By metabolic labeling with ¹⁵N/­¹⁴N, the researchers were able to use MS to match proteins from the two species and also quantitate changes in levels of proteins in response to salt levels. Three labelling experiments ([% NaCl], 0% +3%, 3% +6%, and 3% +9%) yielded 229, 212, and 96 proteins, respectively, by MASCOT search of proteins with two peptides of each isotope. MS BLAST found 32, 30, and 7 more proteins, respectively. Pandhal, J. et al., Proteomics 2008, 8, 2266–2284.     

Cover Picture: Proteomics 9/2009

In this issue of Proteomics you will find the following highlighted articles: Rafting on the pond It seems that any river with a drop of more than 20‐30 cm/km is a candidate for a commercially viable rafting business. Biochemical rafters are pickier. They need a detergent‐resistant lipid raft where they can set up their signaling system. Kim et al. examined the changes in the raft molecules involved in insulin stimulated pre‐adipocyte to adipocyte differentiation (adipogenesis). A substantial number of adipocyte raft‐specific proteins were identified by immunoblots and confirmed by 2‐DE MS. A protein of particular interest was gC1qR, specific for mature adipocyte rafts, which also binds complement C1q and a number of other extracellular proteins (vitronectin, fibrinogen, hyaluronic acids . . .). Down‐regulation of gC1qR by siRNA was paralleled by reduction of insulin signaling through gC1qR, through the insulin receptor, and prevented adipogenesis. The rafts also were home to a variety of mitochondrial proteins during adipogenesis. Kim, K.‐B. et al., Proteomics 2009, 9, 2373‐2382. E. coli chaperone SurA is recognized SurA was a sad protein. It was sad because it couldn't get promoted without proof that it had done a good job on its current assignment. But what was that assignment? Being a good little protein, it did its best to never make a mistake and its good was very good, making thousands of perfect cycles. Still, no‐one noticed. Then one day, Vertommen et al. decided to give SurA a rest (actually its clone rested). After creating the deletion clone, they fired up the proteome machines to see what had changed. The lab was quiet as the proteomers collected their results. They sat down with the data and looked and talked, studied and talked. They finally came to a conclusion: SurA was indeed a chaperone and was responsible for transport of eight important bbarrel proteins across the periplasmic space to the outer membrane! And now a publication! Vertommen, D.. et al., Proteomics 2009, 9, 2432‐2443. Aphid saliva: solvent, glue, caulk, . . . Children learn quickly that if they don't wash their faces properly, a mother's wet thumb will finish the job. If hair won't stay where it belongs, you can always use saliva. Spots on your glasses or your computer monitor? Aphids and mosquitoes extend the uses even further. Carolan et al. report on the active components of saliva of the pea aphid (Acrythosiphon pisum), an agricultural pest that attacks legumes. The researchers used mass spectrometry, RNAi, and various types of electrophoresis to identify the nine proteins secreted in pea aphid saliva. From the complete genome sequence, four proteins could be identified by homology: a metalloprotease [M2], a zinc [M1] protease, both probably cleaving plant defensive peptides, a glucose oxidoreductase that probably detoxifies phytochemicals, and a relative of regucalsin, which might suppress Ca+2 mediated defense. Three of the proteins could not be matched to any known proteins. Carolan, J. C. et al., Proteomics 2009, 9, 2457‐2467.     

In this issue: Proteomics 10/2008

In this issue of Proteomics you will find the following highlighted articles: Open‐pit mining for compatible neighbors Open pit mines are an explosive topic in some parts of the US and elsewhere around the world. In this case, however, it is information, not coal or copper, that is being mined from computer files. Ahmad et al. are looking for patterns in the sequence of amino acids that surround a landmark, an amino acid that is frequently modified by phosphorylation or glycosylation. If an appropriate set of rules can be found, it becomes feasible to predict sites of post‐translational modification (PTM) and possibly winners in conflicts from overlapping sites. Algorithms (MAPRes) for O‐glycosylation (GalNAc) and O‐phosphorylation have been implemented that show good fit, correlating well with patterns predicted by existing software. The MAPRes software should also be useful in creating patterns for features such as protease targets and secondary protein structures. Ahmad, I. et al., Proteomics 2008, 8, 1954–1958. Synthetic sequence steals enzyme‐specific (PKCα) spot It is interesting that evolution has optimized, rather than maximized, many interactions. It was only after we maximized these interactions artificially that we began to recognize the subtleties possible with control systems that were not pushed to the max full time. On the other hand, less than 100% is not satisfactory if we are trying to clean out metastasizing tumor cells. Kang et al. are looking for maximum discrimination between protein kinase C (PKC) isozymes for diagnostic and therapeutic applications. PKCα is normally involved in differentiation, growth, and programmed death of many cell types. The researchers began by designing and screening a set of >1700 PKCα target peptides. They selected the one with the highest efficiency of being labeled and characterized it further for kinetics (K_m, and V_max) with 11 PKC isozymes. They also used it for Western blot evaluation of enzyme levels in tumor and normal tissues. Kang, J.‐H. et al., Proteomics 2008, 8, 2006–2011. Subtleties of B. subtilis biological labeling Bacilllus subtilis is a workhorse bacterium, if you'll allow a mixed metaphor. My grad school friends who worked with it always claimed it was a “higher organism” than E. coli because it could differentiate, sort of like yeast. Because it is well studied genetically and physiologically, it has been adopted as a useful model system for the study of stress responses. Dreisbach et al. wanted to extend proteome analysis to membrane proteins under different starvation conditions that generated the stringent response. Conventional methods (e.g. 2‐DE) were not quantitative enough, or had unacceptable error rates (in vitro labelling). They found in vivo labelling with either specific amino acids (SILAC with lysine) or general metabolic labelling (14N/15N‐metabolic) to meet their needs. Samples could be mixed with controls prior to extraction and digestion to markedly reduce technical error rates. Both methods were considered suitable for quantitative proteomic analysis of membrane proteins. Dreisbach, A. et al., Proteomics 2008, 8, 2062–2076.     

Cover Picture: Proteomics 7/2009

In this issue of Proteomics you will find the following highlighted articles: Computing clusters and complexes At first glance, the structure of a cell looks like a semi‐random collection of proteins, lipids and nucleic acids. With the development of high‐throughput tools and bioinformatic procedures, we can begin to see some order in the chaos, including relationships that regulate cell functions (the interactome). Carbonell et al. looked at hubs, hot spots, interfaces, modules, complexes, binding site disorder, affinity and alanine scanning in developing a model for the energetics and specificity of protein‐protein interactions. They observed self‐segregation of binding sites by affinity, i.e. specific‐specific and promiscuous‐ promiscuous interactions between hubs are much higher than random association. Examples of low and high affinity energetics are discussed for cytochrome b, cdc42 GTPase, ubiquitin, and calmodulin‐dependent kinase. Calculated values were selectively validated for a reality check. Carbonell, P. et al., Proteomics 2009, 9, 1744‐1753. Pursuing the Plasmodium plague: understanding malaria through homology Plasmodium falciparum is a difficult organism to work with because of its complex life cycle: ring, trophozoite and schizont phases. From recent genome sequencing work, proteins/open reading frames can be selected by homology to look at possible elements of the plasmodium interactome. Wuchty et al. took on the challenge. Information was derived from reliable interaction experiments with S. cerevisiae, D. melanogaster, C. elegans, and E. coli. Homologies were determined by BlastP (all‐vs.‐all). Shared GO annotations were found which added to further understanding of the sparsely annotated parasite. Other parameters examined included Cluster Participation Coefficient, Kernel Density Function, K‐Clique Clustering, and (drum roll please) the Rich‐Club Coefficient. Using the InParanoid yeast database, they found over 1800 interactions among almost 700 yeast proteins. Pooling the four organisms gave 5000 interactions among 1900 proteins. There should be some interesting targets in there . . . Wuchty, S.et al., Proteomics 2009, 9, 1841‐1849 Race to the finish‐aging nerve vs. aging muscle Our image of a “senior citizen” often has a wobbling gait and sagging face. These are both in part the result of muscle atrophy. A good surgeon and $150 000 will get you the Joan Rivers look that should hold you into your 90's. But what about your legs? Tough luck for now. Capitanio et al., however, are looking at the relationship between muscle and nerve breakdown with age using proteomic tools. Studying the gastrocnemius muscle and the sciatic nerve of young (8 month) and older (22 month) rats, the authors found a number of coordinate morphological and metabolic changes in the deterioration of nerves and their linked muscles. Light and electron microscopy, 2‐D DIGE, ESI‐MS/MS MALDI‐TOF, Western immunoblots and immunocytochemistry were all brought to bear on the question. The results were a much clearer understanding of the mechanics of muscle aging. Capitanio, D. et al., Proteomics 2009, 9, 2004‐2020.     

In this issue: Proteomics 7/2008

In this issue of Proteomics you will find the following highlighted articles: Modified amino peptides step out of line, reveal identity In thriller movies and spy stories, you can often tell which character is a bad guy if his “confession” changes under pressure or depends on the inquisitor. Likewise for peptides with modifications. Staes et al. use a similar technique to find α‐amino blocked peptides. After chromatography of a digest over a C₁₈ reverse phase column, fractions were treated with TNBS and re‐chromatographed on the same column, under the same conditions. The peptides that had trypsin‐exposed amino groups became much more hydrophobic in the second round because of the addition of the TNBS. The technique (COFRADIC) was also improved by preceding the C₁₈ column by use of a strong cation exchange for fractionation and using a kit for removal of any pyrrolidone carboxylic acid termini from peptides. The revised protocol raised the yield of true amino termini from 60% to 95%. Staes, A. et al., Proteomics 2008, 8, 1362–1370. Decrypting Cryptosporidium parvum: Proteome data revealed by triple analysis As hikers in North America and normal people in many parts of the world know, Cryptosporidium parvum is a protozoan parasite that causes an unpleasant intestinal infection in humans. It also infects livestock species, which leads to widespread waterborne transmission unless effective water treatment is employed. When the oocytes enter the gastrointestinal tract, they are stimulated to undergo excystation, releasing four sporozoites that enter the epithelial cells. There they undergo asexual reproduction and begin a complex series of steps before reproduction is complete and oocytes are released. Although the genome has been completely sequenced, many of the proteins predicted did not have recognizable functions. Sanderson et al. used a tissue culture system of excystation to collect enough sporozoites for proteomic analysis by MuDPIT and LC‐MS/MS after (a) 2‐DE and (b) 1‐DE. Over 1200 unique proteins were identified, representing >30% of the predicted organism proteome, >200 of which had transmembrane domains. Sanderson, S. J. et al., Proteomics 2008, 8, 1398–1414. Oxidized proteins in serum: Inside job or outside contractor? Reactive oxygen species (ROS) seem to be involved in a variety of diseases, including Alzheimer's, Parkinson's, cancer and heart disease. Searches for biomarkers for these diseases have most commonly been done in blood plasma, which contains proteins from essentially every cell type and tissue in the organism. Mirzaei et al. explore questions of cause and effect in rat plasma by trapping ROS‐caused carbonylation points with biotin hydrazide, followed by avidin affinity chromatography and proteomic analysis (LC‐MS/MS). Of 146 proteins identified in four rats, 44 had at least one carbonylation site and 38 had two or more sites. Over 30% of the proteins were membrane proteins, suggesting a major source of ROS was external, a hypothesis supported by the observation that mitochondrial proteins are not affected, despite their proximity to endogenous ROS. On the other hand, 13% were nuclear proteins. Another surprise: virtually no (2%) plasma proteins were found. Mirzaei, H. et al., Proteomics 2008, 8, 1516–1527.     

Cover Picture: Proteomics 7/2008

In this issue of Proteomics you will find the following highlighted articles: Modified amino peptides step out of line, reveal identity In thriller movies and spy stories, you can often tell which character is a bad guy if his “confession” changes under pressure or depends on the inquisitor. Likewise for peptides with modifications. Staes et al. use a similar technique to find α‐amino blocked peptides. After chromatography of a digest over a C₁₈ reverse phase column, fractions were treated with TNBS and re‐chromatographed on the same column, under the same conditions. The peptides that had trypsin‐exposed amino groups became much more hydrophobic in the second round because of the addition of the TNBS. The technique (COFRADIC) was also improved by preceding the C₁₈ column by use of a strong cation exchange for fractionation and using a kit for removal of any pyrrolidone carboxylic acid termini from peptides. The revised protocol raised the yield of true amino termini from 60% to 95%. Staes, A. et al., Proteomics 2008, 8, 1362–1370. Decrypting Cryptosporidium parvum: Proteome data revealed by triple analysis As hikers in North America and normal people in many parts of the world know, Cryptosporidium parvum is a protozoan parasite that causes an unpleasant intestinal infection in humans. It also infects livestock species, which leads to widespread waterborne transmission unless effective water treatment is employed. When the oocytes enter the gastrointestinal tract, they are stimulated to undergo excystation, releasing four sporozoites that enter the epithelial cells. There they undergo asexual reproduction and begin a complex series of steps before reproduction is complete and oocytes are released. Although the genome has been completely sequenced, many of the proteins predicted did not have recognizable functions. Sanderson et al. used a tissue culture system of excystation to collect enough sporozoites for proteomic analysis by MuDPIT and LC‐MS/MS after (a) 2‐DE and (b) 1‐DE. Over 1200 unique proteins were identified, representing >30% of the predicted organism proteome, >200 of which had transmembrane domains. Sanderson, S. J. et al., Proteomics 2008, 8, 1398–1414. Oxidized proteins in serum: Inside job or outside contractor? Reactive oxygen species (ROS) seem to be involved in a variety of diseases, including Alzheimer's, Parkinson's, cancer and heart disease. Searches for biomarkers for these diseases have most commonly been done in blood plasma, which contains proteins from essentially every cell type and tissue in the organism. Mirzaei et al. explore questions of cause and effect in rat plasma by trapping ROS‐caused carbonylation points with biotin hydrazide, followed by avidin affinity chromatography and proteomic analysis (LC‐MS/MS). Of 146 proteins identified in four rats, 44 had at least one carbonylation site and 38 had two or more sites. Over 30% of the proteins were membrane proteins, suggesting a major source of ROS was external, a hypothesis supported by the observation that mitochondrial proteins are not affected, despite their proximity to endogenous ROS. On the other hand, 13% were nuclear proteins. Another surprise: virtually no (2%) plasma proteins were found. Mirzaei, H. et al., Proteomics 2008, 8, 1516–1527.     

Cover Picture: Proteomics 10/2008

In this issue of Proteomics you will find the following highlighted articles: Open‐pit mining for compatible neighbors Open pit mines are an explosive topic in some parts of the US and elsewhere around the world. In this case, however, it is information, not coal or copper, that is being mined from computer files. Ahmad et al. are looking for patterns in the sequence of amino acids that surround a landmark, an amino acid that is frequently modified by phosphorylation or glycosylation. If an appropriate set of rules can be found, it becomes feasible to predict sites of post‐translational modification (PTM) and possibly winners in conflicts from overlapping sites. Algorithms (MAPRes) for O‐glycosylation (GalNAc) and O‐phosphorylation have been implemented that show good fit, correlating well with patterns predicted by existing software. The MAPRes software should also be useful in creating patterns for features such as protease targets and secondary protein structures. Ahmad, I. et al., Proteomics 2008, 8, 1954–1958. Synthetic sequence steals enzyme‐specific (PKCα) spot It is interesting that evolution has optimized, rather than maximized, many interactions. It was only after we maximized these interactions artificially that we began to recognize the subtleties possible with control systems that were not pushed to the max full time. On the other hand, less than 100% is not satisfactory if we are trying to clean out metastasizing tumor cells. Kang et al. are looking for maximum discrimination between protein kinase C (PKC) isozymes for diagnostic and therapeutic applications. PKCα is normally involved in differentiation, growth, and programmed death of many cell types. The researchers began by designing and screening a set of >1700 PKCα target peptides. They selected the one with the highest efficiency of being labeled and characterized it further for kinetics (K_m, and V_max) with 11 PKC isozymes. They also used it for Western blot evaluation of enzyme levels in tumor and normal tissues. Kang, J.‐H. et al., Proteomics 2008, 8, 2006–2011. Subtleties of B. subtilis biological labeling Bacilllus subtilis is a workhorse bacterium, if you'll allow a mixed metaphor. My grad school friends who worked with it always claimed it was a “higher organism” than E. coli because it could differentiate, sort of like yeast. Because it is well studied genetically and physiologically, it has been adopted as a useful model system for the study of stress responses. Dreisbach et al. wanted to extend proteome analysis to membrane proteins under different starvation conditions that generated the stringent response. Conventional methods (e.g. 2‐DE) were not quantitative enough, or had unacceptable error rates (in vitro labelling). They found in vivo labelling with either specific amino acids (SILAC with lysine) or general metabolic labelling (14N/15N‐metabolic) to meet their needs. Samples could be mixed with controls prior to extraction and digestion to markedly reduce technical error rates. Both methods were considered suitable for quantitative proteomic analysis of membrane proteins. Dreisbach, A. et al., Proteomics 2008, 8, 2062–2076.     

Cover Picture: Proteomics 5/2008

In this issue of Proteomics you will find the following highlighted articles: When is a stain not a stain? When it's dyeing! [Dumb proteomics joke!] This silly riddle is actually relat­ed to a recurrent question in proteomics: when is the best time to apply detection reagents to proteins for quantitative analysis? (a) pre‐electrophoresis labeling with DIGE/Cy‐type of covalent stains, or (b) post‐electrophoresis staining with silver, Sypro Ruby or Deep Purple? Karp et al. explore the question using a bacterial extract as a typical sample, DIGE Cy labels, and Deep Purple. It gets more complex when they have to deal with the “missingness” of spots: just because a spot doesn’t show up doesn’t mean it is not there, there just may not be enough to detect. Progenesis SameSpots software was used to analyze images for missing spots. In the end, DIGE gave better sensitivity as previously reported, and fewer missing spots. Deep Purple was more competitive when analyzed with SameSpots software. Karp, N. A. et al., Proteomics 2008, 8, 948–960. Your own best enemy? If there weren’t one maverick, black sheep, rebel, outlaw, eccentric, or rotten apple in most families, a lot of novels would never have been written. Mammalian immune systems seem to have the same structure – they mostly target enemies of the body but there always seem to be a few maverick antibodies that are targeted at their own body’s antigens. Servettaz et al. take up proteomic tools to identify the targets of the anti‐self antibodies expressed by apparently healthy individuals. Using umbilical cord endothelial cells as a source of antigens, the authors found 884 spots by ­2‐­DE, and 61 ± 25 of those were recognized by serum IgGs. All 12 sera tested recognized 11 antigens derived from 6 proteins. There were 3 cytoskeletal, 2 glycolytic, and 1 disulfide isomerase protein seen. These were confirmed by immunoblotting of 2‐D gels and identification by in‐gel tryptic digestion and MALDI‐TOF MS. Servettaz, A. et al., Proteomics 2008, 8, 1000–1008. Signature in scraps from kidney growth stages You can tell a lot about the quality of a new building, residential or commercial, by what doesn’t go into it. The scraps of lumber, pieces of masonry, lengths and varieties of cables are all revealing. Lee et al. watch the final maturation of the rat urinary tract by proteomic analysis of the debris found in urine over time. Taking special care not to mix adult and neonatal urine, they examined four samples over 2 weeks after birth and one at maturity, >30 d. Using nano‐ESI‐LC‐MS/MS technology, six proteins were found in all samples, 30 were adult specific. Proteins were further characterized by large format 1‐ and 2‐DE, immunoblots, and immunofluorescent analysis of tissue sections. Days 1, 3, and 7 had 37% of proteins in common whereas days 7, 14 and >30 shared only 7.4% of proteins. Levels of fibronectin and location of E‐cadherin expression shifted during maturation. Lee, R. S. et al., Proteomics 2008, 8, 1097–1112.     

In this issue: Proteomics 22/2008

In this issue of Proteomics you will find the following highlighted articles: Man bites dog! Noise improves signal! Yes, the right kind of noise does improve the signal (by about 10‐fold in the LC/MS case described here). Scheltema et al. used the noise generated by the ions remaining in the sample from the LC step as internal standards to standardize and calibrate the mass spectrum of interest. Given a set of well characterized contaminants at very low, but detectable levels, the researchers were able to appropriately stretch or compress spectra by comparison to a reference spectrum of contaminants expected in a particular sample. The demonstration was performed on a Thermo Fisher LTQ Orbitrap system which, run conventionally, yielded a mass accuracy of 1 to 2 parts per million. When the noise method was applied to the same data, the mass accuracy was 0.21 ppm. Scheltema, R. A. et al., Proteomics 2008, 8, 4647–4656. Rafting down the Melanoma river When the subject is rafts, Mark Twain's story of Tom Sawyer and Huckleberry Finn rafting down the Mississippi comes immediately to mind for most Americans. A raft of interest to life scientists is associated with detergent resistant membranes found in malignant melanoma cell lines. Made of predominantly cholesterol and sphingolipids, the raft and associated proteins have been shown to participate in signal regulation and protein trafficking as well as several diseases. Working from this information, Baruthio et al. have looked at the lipid raft proteome as a function of melanoma malignancy stage using LC‐MS/MS: radial growth phase, (pre‐metastatic); early vertical growth phase, (non‐metastatic); and fully transformed. They found >175 proteins total in all stages, the most abundant was AHNAK, a large membrane protein. Groups of potential stage markers were detected, although with some difficulty in reproducibility of extraction. Functions found included vacuolar ATPases, adhesion molecules, and signaling pathway regulators. Baruthio, F. et al., Proteomics 2008, 8, 4733–4747. Hot peppers maker confusing soup Capsaicin is the naturally occurring compound that gives chili peppers their “heat.” It is also a component of the pepper's arsenal, deterring some types of attacks. Another of its roles is in regulation of programmed cell death, apoptosis: sometimes it promotes it, sometimes it inhibits it and it always seems to involve reactive oxygen species (ROS). To look at its function as a potential anti‐cancer agent, Baek et al. compared its effect on two human cancer cell lines. HepG2, a hepatoblastoma and SK‐N‐SH, a neuroblastoma, were examined for proteomic changes after exposure to capsaicin at various levels and for various times. Both blastomas responded but in markedly different fashions. Apoptosis was induced in both cell lines, but the ROS levels were up in HepG2 and down in SK‐N‐SH. A number of ROS enzymes exhibited anomalous expression level changes, possibly due to the number of enzymes involved. Baek, Y. M. et al., Proteomics 2008, 8, 4748–4767.     

In this issue: Proteomics 5/2008

In this issue of Proteomics you will find the following highlighted articles: When is a stain not a stain? When it's dyeing! [Dumb proteomics joke!] This silly riddle is actually relat­ed to a recurrent question in proteomics: when is the best time to apply detection reagents to proteins for quantitative analysis? (a) pre‐electrophoresis labeling with DIGE/Cy‐type of covalent stains, or (b) post‐electrophoresis staining with silver, Sypro Ruby or Deep Purple? Karp et al. explore the question using a bacterial extract as a typical sample, DIGE Cy labels, and Deep Purple. It gets more complex when they have to deal with the “missingness” of spots: just because a spot doesn’t show up doesn’t mean it is not there, there just may not be enough to detect. Progenesis SameSpots software was used to analyze images for missing spots. In the end, DIGE gave better sensitivity as previously reported, and fewer missing spots. Deep Purple was more competitive when analyzed with SameSpots software. Karp, N. A. et al., Proteomics 2008, 8, 948–960. Your own best enemy? If there weren’t one maverick, black sheep, rebel, outlaw, eccentric, or rotten apple in most families, a lot of novels would never have been written. Mammalian immune systems seem to have the same structure – they mostly target enemies of the body but there always seem to be a few maverick antibodies that are targeted at their own body’s antigens. Servettaz et al. take up proteomic tools to identify the targets of the anti‐self antibodies expressed by apparently healthy individuals. Using umbilical cord endothelial cells as a source of antigens, the authors found 884 spots by ­2‐­DE, and 61 ± 25 of those were recognized by serum IgGs. All 12 sera tested recognized 11 antigens derived from 6 proteins. There were 3 cytoskeletal, 2 glycolytic, and 1 disulfide isomerase protein seen. These were confirmed by immunoblotting of 2‐D gels and identification by in‐gel tryptic digestion and MALDI‐TOF MS. Servettaz, A. et al., Proteomics 2008, 8, 1000–1008. Signature in scraps from kidney growth stages You can tell a lot about the quality of a new building, residential or commercial, by what doesn’t go into it. The scraps of lumber, pieces of masonry, lengths and varieties of cables are all revealing. Lee et al. watch the final maturation of the rat urinary tract by proteomic analysis of the debris found in urine over time. Taking special care not to mix adult and neonatal urine, they examined four samples over 2 weeks after birth and one at maturity, >30 d. Using nano‐ESI‐LC‐MS/MS technology, six proteins were found in all samples, 30 were adult specific. Proteins were further characterized by large format 1‐ and 2‐DE, immunoblots, and immunofluorescent analysis of tissue sections. Days 1, 3, and 7 had 37% of proteins in common whereas days 7, 14 and >30 shared only 7.4% of proteins. Levels of fibronectin and location of E‐cadherin expression shifted during maturation. Lee, R. S. et al., Proteomics 2008, 8, 1097–1112.     

In this issue: Proteomics 7/2009

In this issue of Proteomics you will find the following highlighted articles: Computing clusters and complexes At first glance, the structure of a cell looks like a semi‐random collection of proteins, lipids and nucleic acids. With the development of high‐throughput tools and bioinformatic procedures, we can begin to see some order in the chaos, including relationships that regulate cell functions (the interactome). Carbonell et al. looked at hubs, hot spots, interfaces, modules, complexes, binding site disorder, affinity and alanine scanning in developing a model for the energetics and specificity of protein‐protein interactions. They observed self‐segregation of binding sites by affinity, i.e. specific‐specific and promiscuous‐ promiscuous interactions between hubs are much higher than random association. Examples of low and high affinity energetics are discussed for cytochrome b, cdc42 GTPase, ubiquitin, and calmodulin‐dependent kinase. Calculated values were selectively validated for a reality check. Carbonell, P. et al., Proteomics 2009, 9, 1744‐1753. Pursuing the Plasmodium plague: understanding malaria through homology Plasmodium falciparum is a difficult organism to work with because of its complex life cycle: ring, trophozoite and schizont phases. From recent genome sequencing work, proteins/open reading frames can be selected by homology to look at possible elements of the plasmodium interactome. Wuchty et al. took on the challenge. Information was derived from reliable interaction experiments with S. cerevisiae, D. melanogaster, C. elegans, and E. coli. Homologies were determined by BlastP (all‐vs.‐all). Shared GO annotations were found which added to further understanding of the sparsely annotated parasite. Other parameters examined included Cluster Participation Coefficient, Kernel Density Function, K‐Clique Clustering, and (drum roll please) the Rich‐Club Coefficient. Using the InParanoid yeast database, they found over 1800 interactions among almost 700 yeast proteins. Pooling the four organisms gave 5000 interactions among 1900 proteins. There should be some interesting targets in there . . . Wuchty, S.et al., Proteomics 2009, 9, 1841‐1849 Race to the finish‐aging nerve vs. aging muscle Our image of a “senior citizen” often has a wobbling gait and sagging face. These are both in part the result of muscle atrophy. A good surgeon and $150 000 will get you the Joan Rivers look that should hold you into your 90's. But what about your legs? Tough luck for now. Capitanio et al., however, are looking at the relationship between muscle and nerve breakdown with age using proteomic tools. Studying the gastrocnemius muscle and the sciatic nerve of young (8 month) and older (22 month) rats, the authors found a number of coordinate morphological and metabolic changes in the deterioration of nerves and their linked muscles. Light and electron microscopy, 2‐D DIGE, ESI‐MS/MS MALDI‐TOF, Western immunoblots and immunocytochemistry were all brought to bear on the question. The results were a much clearer understanding of the mechanics of muscle aging. Capitanio, D. et al., Proteomics 2009, 9, 2004‐2020.     

Cover Picture: Proteomics 12/2008

In this issue of Proteomics you will find the following highlighted articles: TAP tag! You're it! TAP tag is a considerably more sophisticated game than the one we played as kids. For one, the tag is something actual as opposed to that ethereal “it” which was attached to your being by unknown forces only extant during recess period. In this technical note, Kito et al. describe a clever way of using the Tandem Affinity Purification protocol coupled to stable mass isotope labeling to study the character of the association of molecules in complexes. By mixing a TAP⁺/mass isotope⁺ tagged molecule with untagged molecules before or after affinity purification, they could distinguish stable associations from transient association from spurious noise. With some additional improvements, they should be able to generate quantitative interaction information such as the off and on rates of individual components. Kito, K. et al., Proteomics 2008, 8, 2366–2370. Rafting into place: Malaria moves machinery of infection About two million people die each year of malaria. The disease is mosquito‐borne, caused by Plasmodium falciparum in humans, P. berghei in rodents. During the mammalian phase of its life cycle, the microbe multiplies in enucleated erythrocytes, regular red blood cells (RBC). The RBC is modified extensively for Plasmodium replication. Di Girolamo et al. here report their exploration of the role of “rafts” of detergent‐resistant membranes in sorting and positioning proteins essential to malarial replication. They applied proteomic techniques to membrane fractions and found rafts carried both malarial and host components. Plasmodial raft proteins were up‐ or down‐regulated by P. berghei genes at specific stages of the plasmodial life cycle. However, there also appear to be host factors that are used to internalize selected parasite products. The raft association seems to be quite dynamic for the erythrocyte phase, particularly with multifunctional protein 14–3‐3, known for regulating protein localization. Di Girolamo, F. et al., Proteomics 2008, 8, 2500–2513. A multi‐dimensional proteomic analysis of ischemia‐reperfusion injury Cardiac surgery could be said to have a temporary mortality rate (ischemic arrest) of ～100%, but the operative rate is generally <10%. A third metric is survival – roughly 24% of high‐risk patients will die within 3 years after surgery. The problem is due primarily to the effects of reperfusion at the conclusion of the surgery. Fert‐Bober et al. report here on the proteomes of rat heart proteins at various times post‐surgery, with or without reperfusion. Hearts were subjected to 0, 15, 20–25 and 30 min of post ischemia perfusion then tested for gelatinase and for mechanical function before selecting those destined for proteome determination. Samples were analyzed by 2‐DE, MALDI/TOF‐MS, and Coomassie staining. The findings were striking: most spots showed increased intensity if the hearts had not been reperfused and the converse if they had. Both sets of 2‐DE spots included metabolism enzymes, muscle components, anti‐oxidant and stress proteins. Fert‐Bober, J. et al., Proteomics 2008, 8, 2543–2555.     

In this issue: Proteomics 12/2008

In this issue of Proteomics you will find the following highlighted articles: TAP tag! You're it! TAP tag is a considerably more sophisticated game than the one we played as kids. For one, the tag is something actual as opposed to that ethereal “it” which was attached to your being by unknown forces only extant during recess period. In this technical note, Kito et al. describe a clever way of using the Tandem Affinity Purification protocol coupled to stable mass isotope labeling to study the character of the association of molecules in complexes. By mixing a TAP⁺/mass isotope⁺ tagged molecule with untagged molecules before or after affinity purification, they could distinguish stable associations from transient association from spurious noise. With some additional improvements, they should be able to generate quantitative interaction information such as the off and on rates of individual components. Kito, K. et al., Proteomics 2008, 8, 2366–2370. Rafting into place: Malaria moves machinery of infection About two million people die each year of malaria. The disease is mosquito‐borne, caused by Plasmodium falciparum in humans, P. berghei in rodents. During the mammalian phase of its life cycle, the microbe multiplies in enucleated erythrocytes, regular red blood cells (RBC). The RBC is modified extensively for Plasmodium replication. Di Girolamo et al. here report their exploration of the role of “rafts” of detergent‐resistant membranes in sorting and positioning proteins essential to malarial replication. They applied proteomic techniques to membrane fractions and found rafts carried both malarial and host components. Plasmodial raft proteins were up‐ or down‐regulated by P. berghei genes at specific stages of the plasmodial life cycle. However, there also appear to be host factors that are used to internalize selected parasite products. The raft association seems to be quite dynamic for the erythrocyte phase, particularly with multifunctional protein 14–3‐3, known for regulating protein localization. Di Girolamo, F. et al., Proteomics 2008, 8, 2500–2513. A multi‐dimensional proteomic analysis of ischemia‐reperfusion injury Cardiac surgery could be said to have a temporary mortality rate (ischemic arrest) of ～100%, but the operative rate is generally <10%. A third metric is survival – roughly 24% of high‐risk patients will die within 3 years after surgery. The problem is due primarily to the effects of reperfusion at the conclusion of the surgery. Fert‐Bober et al. report here on the proteomes of rat heart proteins at various times post‐surgery, with or without reperfusion. Hearts were subjected to 0, 15, 20–25 and 30 min of post ischemia perfusion then tested for gelatinase and for mechanical function before selecting those destined for proteome determination. Samples were analyzed by 2‐DE, MALDI/TOF‐MS, and Coomassie staining. The findings were striking: most spots showed increased intensity if the hearts had not been reperfused and the converse if they had. Both sets of 2‐DE spots included metabolism enzymes, muscle components, anti‐oxidant and stress proteins. Fert‐Bober, J. et al., Proteomics 2008, 8, 2543–2555.