In this issue: Proteomics 8/2008

In this issue of Proteomics you will find the following highlighted articles: Have a heart (mitochondrial) proteome Is a rose always a rose? How clean is clean? Is a proteome always a proteome? Such deep questions to ponder. Zhang et al. don't just ponder, they attack the last two questions. Taking meticulous care to prepare clean mouse cardiac mitochondria, they identify almost a thousand proteins from the functionally and morphologically validated organelle. Half of the proteins had not been previously identified. Functional clusters include the expected and the “under‐appreciated” – proteolysis, protein folding, apoptosis and redox signaling. A close association with rough ER could not be disrupted without damage to the outer mitochondrial membrane. Immunocytological localization of many of the proteins revealed roles in other sites as well, including ER, cytoplasm, and Golgi. Comparative analysis of published mitochondrial proteomes from different tissues suggests that the proteomes are functionally adapted to their particular milieu. A mitochondrion (heart) is not a mitochondrion (liver). Zhang, J. et al., Proteomics 2008, 8, 1564–1575. Ibuprofen: split personality complicates proteome analyses Ibuprofen is one of those two‐fisted drugs that comes in an S form and an R form. The S form of this nonsteroidal anti‐inflammatory drug (NSAID) is the only active one, in this case. Normally sold over the counter for general aches and pains in the US, statistical analysis of its regular users has found it associated with a reduced incidence of Alzheimer's disease. Following up on this lead, Zhang et al. performed proteomic analysis of the effect of the R and S forms and their mixture on neuroblastoma cells. From three replicates, 167 proteins were identified as being quantitatively shifted. A total of 13 were unique. Functionally, they included representatives from metabolic enzymes (5), signaling (6), and cytoskeleton (2). Of interest for the Alzheimer's association was the reduced levels of reactive oxygen species (ROS), probably linked to levels of peroxiredoxins 2 and 6 in ibuprofen S‐treated cells. Zhang, J. et al., Proteomics 2008, 8, 1595–1607. Not your usual marine bacterium Rhodopirellula baltica is a member of the Planctomycetes phylum. These bacteria exhibit a proteinaceous cell wall, budding cell division, and intracellular compartments. From genome sequencing, it has >7300 ORFs. Analyzing the soluble proteins over the range of pH 3–10 by 2‐D PAGE, using narrow range pH gradient gels, nHPLC‐MS, and 1‐D SDS‐PAGE, Hieu et al. added 709 proteins to the proteins identified previously to bring the total identified to 1267, 17% of the predicted total ORFs. Gel‐free analysis (multiple dimension LC‐MS) yielded 145 proteins not seen in gel‐based methods. Both 1‐D and gel‐free methods were used for identification of cell wall and ribosomal proteins. Ninety three proteins were identified in the cell wall proteome and 13 extracellular proteins. No support was found for the hypothesis that R. baltica fed on sinking dead “marine snow” organisms by secreting proteases. Hieu, C. X. et al., Proteomics 2008, 8, 1608–1623.     

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.     

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.     

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 1/2008

In this issue of Proteomics you will find the following highlighted articles: Arachnophilia: A Charlotte working on the web In the children’s book Charlotte’s Web, a spider communicates with a pig by weaving messages into her web. In this Technical Brief, Mayer’s spider is the intermediate, a program taking queries about the protein world and weaving relevant information from the www’s libraries and databases into spreadsheets. PIC (Protein Information Crawler) can link directly to a number of databases including BLAST, SMART, PROSITE, and CDD. Selected data is deposited in an Excel spreadsheet or HTML table for sorting and browsing. The system is customizable to anyone with minimal programming skills in LabView G, an easy‐to‐learn graphical language. Using PIC reduced the initial data search for a system of ～1000 neural proteins from 8 wks to 2 days. The software is free. Mayer, U., Proteomics 2008, 8, 42–44. Hard heart, soft heart: analyzing tropomyosin links to types of cardiomyopathy I don’t know if the type of a heart patient’s cardiomyopathy has been diagnosed by behavioral observations but Warren et al. examined the behavior of tropomyosin on improved 2‐D PAGE and 2‐D DIGE separations. First dimension separations were run on 18‐cm long narrow range (pH 4.5 to pH 5.5) IPG strips. Second dimension gels were 16 cm wide, 1 mm thick, and 8 cm long. Ends of the IPG strips were trimmed off to fit the vertical gel. The equilibrated strip was put in place without agarose on top of stacking and resolving gels that included 10% glycerol and, in the stacking gel, 15% N,N’‐diallyltartardiamide to ensure efficient transfer of the protein from the first‐ to the second‐dimension gel. With these changes they were able to distinguish wild type tropomyosin from an E54K mutant and phosphorylated from unphosphorylated tropomyosin, potentially key prognostic clues. Warren, C. M. et al., Proteomics 2008, 8, 100–105. Moo‐ving into ART: Cows lead the way Cow ART is not the product of a bovine Moonet or Moodigliani, it is “Assist­ed Reproductive Technology.” Not simply artificial insemination, ART includes somatic cell nuclear transfer and other advanced techniques which are critical to creating breeding herds with “elite” genetics. But the success rate is not what was expected or required for effective use. Riding et al. apply proteome analysis techniques to establish a foundation for pregnancy progress biomarkers. Ruminants have two fluid‐filled sacs, amniotic and allantoic, that are critical to fetal development. After developing an improved sample prep procedure, the 5–50 kDa fraction of the allantoic proteome was analyzed. Some 139 proteins were identified and ontologically classified into nine functional groups. Too little amniotic fluid was recovered for thorough analysis but the two fluids were clearly distinguishable at 45 days post‐conception. Riding, G. et al., Proteomics 2008, 8, 160–177.     

Cover Picture: Proteomics 1/2008

In this issue of Proteomics you will find the following highlighted articles: Arachnophilia: A Charlotte working on the web In the children’s book Charlotte’s Web, a spider communicates with a pig by weaving messages into her web. In this Technical Brief, Mayer’s spider is the intermediate, a program taking queries about the protein world and weaving relevant information from the www’s libraries and databases into spreadsheets. PIC (Protein Information Crawler) can link directly to a number of databases including BLAST, SMART, PROSITE, and CDD. Selected data is deposited in an Excel spreadsheet or HTML table for sorting and browsing. The system is customizable to anyone with minimal programming skills in LabView G, an easy‐to‐learn graphical language. Using PIC reduced the initial data search for a system of ～1000 neural proteins from 8 wks to 2 days. The software is free. Mayer, U., Proteomics 2008, 8, 42–44. Hard heart, soft heart: analyzing tropomyosin links to types of cardiomyopathy I don’t know if the type of a heart patient’s cardiomyopathy has been diagnosed by behavioral observations but Warren et al. examined the behavior of tropomyosin on improved 2‐D PAGE and 2‐D DIGE separations. First dimension separations were run on 18‐cm long narrow range (pH 4.5 to pH 5.5) IPG strips. Second dimension gels were 16 cm wide, 1 mm thick, and 8 cm long. Ends of the IPG strips were trimmed off to fit the vertical gel. The equilibrated strip was put in place without agarose on top of stacking and resolving gels that included 10% glycerol and, in the stacking gel, 15% N,N’‐diallyltartardiamide to ensure efficient transfer of the protein from the first‐ to the second‐dimension gel. With these changes they were able to distinguish wild type tropomyosin from an E54K mutant and phosphorylated from unphosphorylated tropomyosin, potentially key prognostic clues. Warren, C. M. et al., Proteomics 2008, 8, 100–105. Moo‐ving into ART: Cows lead the way Cow ART is not the product of a bovine Moonet or Moodigliani, it is “Assist­ed Reproductive Technology.” Not simply artificial insemination, ART includes somatic cell nuclear transfer and other advanced techniques which are critical to creating breeding herds with “elite” genetics. But the success rate is not what was expected or required for effective use. Riding et al. apply proteome analysis techniques to establish a foundation for pregnancy progress biomarkers. Ruminants have two fluid‐filled sacs, amniotic and allantoic, that are critical to fetal development. After developing an improved sample prep procedure, the 5–50 kDa fraction of the allantoic proteome was analyzed. Some 139 proteins were identified and ontologically classified into nine functional groups. Too little amniotic fluid was recovered for thorough analysis but the two fluids were clearly distinguishable at 45 days post‐conception. Riding, G. et al., Proteomics 2008, 8, 160–177.     

The human eye proteome project

The human eye proteome is the latest addition to the HUPO Human Proteome Project (HPP). Semba et al. (The Human Eye Proteome Project: Perspectives on an emerging proteome. Proteomics 2013, 13, 2500–2511) establish a provisional baseline for the proteomes of the many anatomical compartments of the eye, based on literature review. As part of the Biology and Disease‐driven HPP, they and their colleagues will generate fresh data and meet the stringent guidelines for protein identification and characterization as established by the HPP.     

Proteomic mapping for legume nodule organogenesis

While genetic screens have identified mutants of the model legume Lotus japonicus that can nodulate in the absence of rhizobia, the lack of a proteome map is a major hindrance to understanding the functional protein networks associated with this nodulation process. In this issue of Proteomics, Dam et al. (Proteomics 2014, 14, 230–240) developed 2D gel‐based reference maps of nodules and roots of Lotus and a spontaneous nodule formation mutant (snf1). Comparative proteomic analysis of roots and two developmental stages of nodules provide useful insights into tissue‐specific mechanisms underlying nodule organogenesis. Additionally, a comparison of interspecies nodule proteomes displays that overlapping and individual mechanisms are associated with legume nodulation.     

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.     

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.     

In this issue: Proteomics 6/2009

In this issue of Proteomics you will find the following highlighted articles: Keeping up with the lung cancers You're in good company if you smoke and develop lung cancer. The World Health Organization estimates 1.2 million new cases occur every year. On the other hand, 1.1 million people die from it every year‐bummer. One reason for the high death rate is the frequent development of resistance to several of the most commonly used drugs simultaneously. Multiple drug resistance (MDR) is the major cause of chemotherapeutic failure. Keenan et al. explored the proteomic changes associated with MDR failure (adriamycin) in a cultured lung cancer cell line (DLKP) and several subtypes. Adriamycin normally kills by blocking replication at DNA gyrase and by generating reactive oxygen species that lead to apoptosis. Proteomes were examined by 2‐D DIGE. Approximately 80 proteins displayed quantitative shifts, 32 showed a correlation with resistance, 24 being linked positively to resistance, 6 correlated negatively. Some known targets did not appear on the 2‐D maps consistently. Keenan, J. et al., Proteomics 2009, 9, 1556‐1566. An image of spit Spitting images have been around for a long time. The phrase is possibly human‐kind's first recognition of genetically transmitted traits. Proteomic analysis of saliva has only developed recently. The question raised by Walz et al. here is “What is the possible contribution of saliva to the high level of infection by Helicobacter pylori?” H. pylori is known to have extracellular adhesins that bind to a number of salivary proteins. A convenient way to detect targets of adhesins was found to be incubating 1‐D and 2‐D PAGE Western blots with an overlay of whole H. pylori. Targets detected included mucins, sialic acid‐containing glycoproteins, fucose‐containing blood group antigens and each pair of salivary glands had a different binding pattern. Walz, A. et al., Proteomics 2009, 9, 1582‐1592. Mix'em up, folks Conventional analytical chemical identifications frequently yield a characteristic spectrum of peaks for particular compounds on particular instruments. Just look up the observed spectrum in the “library” of standard spectra for identification. It is not so simple for proteins. Because of the size of a potential proteomic peptide library and the diversity of instruments used, most often the observed spectrum is compared to a theoretical spectrum for a peptide of interest. Ahrné et al. combine the two for improved performance. First they run the spectrum of interest through an exhaustive proteome search program (Phenyx), then through a sensitive library search (SpectraST) of the highest scoring sequences in the previous Phenyx search plus a number of controls. In the first (relatively simple) test, Phenyx matched 362 spectra, SpectraST made 639 matches at the same error detection level. In a more complex test, Phenyx generated >1000 hits, SpectraST 1304 hits. Ahrné, E. et al., Proteomics 2009, 9, 1731‐1736.     

Proteogenomics Gets onto the Regulation of mRNA Decoding and Translation into Protein

Proteogenomics, the integrative analysis of the proteome and the genome, increasingly provides protein‐level insights about the regulation of gene expression and protein translation. Armengaud et al. (Proteomics 2017, 17, 1700211) nicely illustrate this trend with the first in‐depth proteomic analysis of the eukaryotic and unicellular intestinal parasite Blastocystis sp. Not only this work constitutes an important milestone toward the proteogenomics profile of this human pathogen, but also it demonstrates at the protein level the occurrence of a specific mechanism of mRNA decoding. GU‐rich motifs located downstream of mRNA polyadenylation sites create termination codons that ultimately result in the synthesis of proteins with lower molecular weight than predicted from gene sequence. Thus, the scope of proteogenomics now extends to the regulation of mRNA translation into proteins, providing a proof of concept for future studies in multicellular eukaryotes such as humans and plants.     

Cover Picture: Proteomics 6/2009

In this issue of Proteomics you will find the following highlighted articles: Keeping up with the lung cancers You're in good company if you smoke and develop lung cancer. The World Health Organization estimates 1.2 million new cases occur every year. On the other hand, 1.1 million people die from it every year‐bummer. One reason for the high death rate is the frequent development of resistance to several of the most commonly used drugs simultaneously. Multiple drug resistance (MDR) is the major cause of chemotherapeutic failure. Keenan et al. explored the proteomic changes associated with MDR failure (adriamycin) in a cultured lung cancer cell line (DLKP) and several subtypes. Adriamycin normally kills by blocking replication at DNA gyrase and by generating reactive oxygen species that lead to apoptosis. Proteomes were examined by 2‐D DIGE. Approximately 80 proteins displayed quantitative shifts, 32 showed a correlation with resistance, 24 being linked positively to resistance, 6 correlated negatively. Some known targets did not appear on the 2‐D maps consistently. Keenan, J. et al., Proteomics 2009, 9, 1556‐1566. An image of spit Spitting images have been around for a long time. The phrase is possibly human‐kind's first recognition of genetically transmitted traits. Proteomic analysis of saliva has only developed recently. The question raised by Walz et al. here is “What is the possible contribution of saliva to the high level of infection by Helicobacter pylori?” H. pylori is known to have extracellular adhesins that bind to a number of salivary proteins. A convenient way to detect targets of adhesins was found to be incubating 1‐D and 2‐D PAGE Western blots with an overlay of whole H. pylori. Targets detected included mucins, sialic acid‐containing glycoproteins, fucose‐containing blood group antigens and each pair of salivary glands had a different binding pattern. Walz, A. et al., Proteomics 2009, 9, 1582‐1592. Mix'em up, folks Conventional analytical chemical identifications frequently yield a characteristic spectrum of peaks for particular compounds on particular instruments. Just look up the observed spectrum in the “library” of standard spectra for identification. It is not so simple for proteins. Because of the size of a potential proteomic peptide library and the diversity of instruments used, most often the observed spectrum is compared to a theoretical spectrum for a peptide of interest. Ahrné et al. combine the two for improved performance. First they run the spectrum of interest through an exhaustive proteome search program (Phenyx), then through a sensitive library search (SpectraST) of the highest scoring sequences in the previous Phenyx search plus a number of controls. In the first (relatively simple) test, Phenyx matched 362 spectra, SpectraST made 639 matches at the same error detection level. In a more complex test, Phenyx generated >1000 hits, SpectraST 1304 hits. Ahrné, E. et al., Proteomics 2009, 9, 1731‐1736.     

Cover Picture: Proteomics 13/2008

In this issue of Proteomics you will find the following highlighted articles: Mini pig kidney pie? A lot of antigens to chew on Miniature pigs have been of interest as potential organ xeno‐transplant donors for a number of years but mostly without success. A galactosyl transferase gene knock‐out heart lasted for 6 months, but then succumbed to vascular rejection, indicating previously unrecognized antigens. Kim, et al. applied current glycome analysis techniques to mini‐pig kidney surface antigens. They found an abundance of new ones–over 100 N‐glycans total, some sialylated, some neutral, some never reported before. The structures of many were determined and relatively quantitated. What was sauce for the kidney was not necessarily sauce for the heart. The information gathered and the questions raised will keep transplanters chewing for a long time. Y.‐G. Kim et al., Proteomics 2008, 8, 2596–2610. PACE‐ing along with the DUKX that are really hamsters Turning a marching band or moving it through a bottleneck requires different speeds at different points across the ranks. So does maximal production of biologically produced pharmaceuticals. Here Meleady, et al. use 2‐D DIGE technology to look at the required proteins and the levels of expression required for optimal production of human bone morphogenetic protein 2 (rhBMP‐2) in Chinese hamster ovary‐derived cell lines (CHO DUKX and engineered derivatives). Maturation of BMP‐2 requires the action of PACE (paired basic amino acid cleaving enzyme) and PACE levels are improved by co‐transfection with a soluble PACE gene. With high levels of PACE activity, yields of BMP‐2 improved 4‐fold. PACEsol enhances production of a variety of other proteins as well. Comparison of DUKX‐BMP‐2 cells expressing vs. not expressing PACEsol showed ～180 differentially expressed proteins, 60 identified, that were assigned to a number of functional categories. P. Meleady et al., Proteomics 2008, 8, 2611–2624. Ever deeper into cheesy secretome Kluyveromyces lactis, a budding yeast related to Saccharomyces cerevisiae, is of genetic and industrial interest. Its name comes from its ability to convert sweet milk to sour by fermentation of lactose to lactic acid, not quite the same as glucose to ethanol, but useful nonetheless. Industrially, it has been engineered to produce a vegetarian rennet for cheese‐making as well as other secreted protein products. Swaim, et al. compared the proteins in spent fermentation broth of the industrial expression strain K. lactis GG799 to the predicted secretion products based on genome sequence information and to predicted secretions from Candida albicans and S. cerevisiae. Using multidimensional LC‐MS/MS to analyze tryptic digests, they found 81 secreted products out of 178 predicted. Twenty‐six of those did not exhibit an N‐terminal secretion signal, suggesting that there are alternative pathways to the cell surface. An intracellular nano‐Swiss, perhaps? C. L. Swaim et al., Proteomics 2008, 8, 2714–2723.     

Cell wall proteomics contributes to explore the functional proteins of Brachypodium distachyon grains

The plant cell wall is the first barrier in response to external stimuli and cell wall proteins (CWPs) can play an important role in the modulation of plant growth and development. In the past 10 years, the plant cell wall proteomics has increasingly become a very active research filed, which provides a broader understanding of CWPs for people. The cell wall proteome of Arabidopsis, rice, and other model plants has begun to take shape, and proteomic technology has become an effective way to identify the candidate functional CWPs in large scale. The challenging work of Francin‐Allami et al. (Proteomics 2015, 15, 2296–2306) is a vital step toward building the most extensive cell wall proteome of a monocot species. They identified 299 cell wall proteins in Brachypodium distachyon grains, and also compared the grain cell wall proteome with those of B. distachyon culms and leaves, which provides a new perspective for further explaining the plant cell wall structures and remodeling mechanism.