Cover Picture: Proteomics 2/2008

In this issue of Proteomics you will find the following highlighted articles: Particular particles pick out phosphopeptides promptly Phosphorylation/dephosphorylation is the most commonly used post‐translational signal in eukaryotic organisms. With a single site it might turn a pathway on or off, up or down; multiple site series can incrementally change the level of expression, effects can be direct or indirectly induced. Needless to say, phosphoproteins are extremely important subjects of study. Li et al. have developed a method for rapid collection and analysis of phosphopeptides: gallium oxide‐coated magnetic beads. Effective at very low phosphopeptide concentrations, a MALDI sample can be bound to the beads in 30 seconds. After a few washes, a small amount of the bead slurry is spotted on a MALDI plate, 2,5‐dihydroxybenzoic acid spotted as matrix, then, “Fire away!” The gallium oxide beads dramatically out perform silica‐Fe beads, Fe+3‐IMAC resin, and TiO2 beads. Li, Y. et al., Proteomics 2008, 8, 238–249. Plasma butyrylcholinesterase: multiple N‐glycan sites support multiple roles Cholinesterases have been of interest since their discovery in the early 1930’s. Acetylcholinesterase is the target of insecticides and nerve gases. Butyrylcholinesterase (BChE) plays a variety of roles because of its “relaxed” substrate requirements, able to detoxify heroin and aspirin as well as choline‐containing molecules. Of particular interest is its function as a scavenger of organophosphates to protect nerve‐associated acetylcholinesterase. Kolarich et al. explored the complexities of glycosylation of BChE, with 9 of 10 potential N‐glycosylation sites occupied in the 85 kDa protein. Of the variety of techniques applied to elucidating the glycan structures at particular sites, perhaps the most informative was porous graphitic carbon LC/MS. It yielded more information in 80 minutes than an overnight “classical” procedure. No evidence of O‐glycosylation or other post‐translational modifications were seen. Kolarich, D. et al., Proteomics 2008, 8, 254–263. DIGE digs up skeletal muscle fate The gradual loss of strength and muscle mass is a normal event in aging, measurable by published statistics for professional athletes, or by how long we take to push away from the table. Sarcopenia is the drastic form of muscle loss, resulting in severe impairment. Doran et al. selected the rat model of muscle mass loss between 3 months (young adult) and 30 months (old) to study, avoiding confounding human variables. Applying DIGE/MALDI‐TOF to gastrocnemius samples, they found 2493 spots, of which 69 exhibited dramatic up‐ or down‐regulation. The functional changes suggested by the quantitative changes included increased dependence on aerobic oxidative metabolism and fibre remodeling, probably due to impaired fibre repair. These findings were confirmed by Western blots and fluorescent confocal microscopy and concur with other published studies. Doran, P. et al., Proteomics 2008, 8, 364–377.     

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.     

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.     

Cover Picture: Proteomics 14/2008

In this issue of Proteomics you will find the following highlighted articles: A spoonful of reality helps the errors go down Physicists predict particles from a theory then go hunting for them. To see if they fit the theory, the scientists make measurements of mass, spin, half‐life, charge, symmetry, etc. Life scientists tend to find particles first, then theorize about what they found. Martinez et al. have developed pattern search/match software that is trained on a set of known data (amino acid sequences) to recognize signal sequences that cause cellular enzymes to modify N‐termini of specified cytosolic proteins. Their accuracy rose dramatically when they expanded the amount of training material and segregated it into modules for the various kingdoms (archaea, fungi, plants, animals, eubacteria). Terminal modifications examined included presence or absence of initial methionine, N‐acetylation, N‐myristoylation, and S‐palmitoylation. The particular modification led to varying degrees of internal accumulation. Martinez, A. et al., Proteomics 2008, 8, 2809–2831. Please don't pet the fish Salmon appear to have no fear of jumping several decimeters out of water on their annual upstream migration but they do seem to have a fear of being lifted out of water for a few seconds once a day. Liu et al. looked at the degree of O‐acetylation of serum N‐glycans of Atlantic salmon over a period of 4 weeks. The salmon N‐glycan pattern was similar to the human. Stress was created by holding the fish out of water for 15 seconds daily. Stressed fish showed a reduced level of mono‐O‐acetylated sialic acids. Di‐O‐acetylated species increased, however, over the 4‐week experimental period. The increase in O‐acetylsialic acid is a potential biomarker for long‐term stress in fish. More work is needed to evaluate the extensibility of these findings. Liu, X. et al., Proteomics 2008, 8, 2849–2857. Cattle and ART and proteomics The ART of cattle raising is not learned in a Parson's School of Bovine Design or Parisian cow ecole, it is “Assisted Reproduction Technologies” and is taught in veterinary programs and schools of agriculture. It includes in vitro fertilization (IVF), somatic cell nuclear transfer (SCNT), and multiple ovulation embryo transfer. Expensive procedures requiring specialized training, they are normally applied only to genetically superior breeding stock. Fetal losses are high — 2× to >10× natural fertilization failure rates. Riding et al. used proteomic technology (2‐D DIGE, MALDI‐TOF‐MS/MS) to look for biomarkers in conceptus fluids. In particular, they sought indicators of fetal‐maternal environment status and fetal health at 45 and 90 days post‐conception for IVF and SCNT. Allantoic fluid samples from 45 days showed elevated levels of cathelicidin antimicrobial protein (CAMP) family members (3 of 4 IVF, up ≤100×; 2 of 4 SCNT, up ≤45×; natural, up ≤6×) and several other proteins (PGLYRP, SERPINB1, COLT1). Riding, G. A. et al., Proteomics 2008, 8, 2967–2982.     

In this issue: Proteomics 14/2008

In this issue of Proteomics you will find the following highlighted articles: A spoonful of reality helps the errors go down Physicists predict particles from a theory then go hunting for them. To see if they fit the theory, the scientists make measurements of mass, spin, half‐life, charge, symmetry, etc. Life scientists tend to find particles first, then theorize about what they found. Martinez et al. have developed pattern search/match software that is trained on a set of known data (amino acid sequences) to recognize signal sequences that cause cellular enzymes to modify N‐termini of specified cytosolic proteins. Their accuracy rose dramatically when they expanded the amount of training material and segregated it into modules for the various kingdoms (archaea, fungi, plants, animals, eubacteria). Terminal modifications examined included presence or absence of initial methionine, N‐acetylation, N‐myristoylation, and S‐palmitoylation. The particular modification led to varying degrees of internal accumulation. Martinez, A. et al., Proteomics 2008, 8, 2809–2831. Please don't pet the fish Salmon appear to have no fear of jumping several decimeters out of water on their annual upstream migration but they do seem to have a fear of being lifted out of water for a few seconds once a day. Liu et al. looked at the degree of O‐acetylation of serum N‐glycans of Atlantic salmon over a period of 4 weeks. The salmon N‐glycan pattern was similar to the human. Stress was created by holding the fish out of water for 15 seconds daily. Stressed fish showed a reduced level of mono‐O‐acetylated sialic acids. Di‐O‐acetylated species increased, however, over the 4‐week experimental period. The increase in O‐acetylsialic acid is a potential biomarker for long‐term stress in fish. More work is needed to evaluate the extensibility of these findings. Liu, X. et al., Proteomics 2008, 8, 2849–2857. Cattle and ART and proteomics The ART of cattle raising is not learned in a Parson's School of Bovine Design or Parisian cow ecole, it is “Assisted Reproduction Technologies” and is taught in veterinary programs and schools of agriculture. It includes in vitro fertilization (IVF), somatic cell nuclear transfer (SCNT), and multiple ovulation embryo transfer. Expensive procedures requiring specialized training, they are normally applied only to genetically superior breeding stock. Fetal losses are high — 2× to >10× natural fertilization failure rates. Riding et al. used proteomic technology (2‐D DIGE, MALDI‐TOF‐MS/MS) to look for biomarkers in conceptus fluids. In particular, they sought indicators of fetal‐maternal environment status and fetal health at 45 and 90 days post‐conception for IVF and SCNT. Allantoic fluid samples from 45 days showed elevated levels of cathelicidin antimicrobial protein (CAMP) family members (3 of 4 IVF, up ≤100×; 2 of 4 SCNT, up ≤45×; natural, up ≤6×) and several other proteins (PGLYRP, SERPINB1, COLT1). Riding, G. A. et al., Proteomics 2008, 8, 2967–2982.     

Cover Picture: Proteomics 20/2008

In this issue of Proteomics you will find the following highlighted articles: Comprehensively confirmed annotation of short ORFs During the California gold rush, prospectors did not look only for large nuggets to pave their road to riches – they also collected gold dust. The proteomic equivalent of dust is the small ORF. It does not pay to put a lower limit on dust or ORF size because almost any size may be turned into “cash” or an important peptide. Wei et al. demonstrate how a combination of conventional genomics and proteomics can find small expressed ORFs in noisy mixtures. Their test system is Shigella flexneri rRNA genes. First, cells were lysed, pre‐fractionated through 100 kDa and 10 kDa cutoff membranes and split into two aliquots, one treated with trypsin the other not. Both were analyzed by LC‐MS/MS and queried for ORFs >15 amino acids. Total labeled RNA probed a DNA array, and, after BLAST classification, revealed 36 new small proteins. Wei, C. et al., Proteomics 2008, 8, 4209–4213. The end of an era: Late stage proteome of cheese bacterium The bacterium Streptococcus thermophilus is a common ingredient in food, serving as a starter culture for a wide variety of dairy foods, yogurt in partic­ular, in co‐culture with Lactobacillus delbrueckii ssp. bulgaricus. It is closely related to several pathogenic species but lacks critical genes for pathogenicity. Instead, it is better optimized for lactose digestion than even a teen‐aged boy. Specific genes transport lactose into the cell where it is cleaved by a β‐galactosidase. Because milk is poor in amino acids, some strains of S. thermophilius bring their own protease to digest milk peptides and proteins. This work by Herve‐Jimenez et al. finds that in the latest stage of fermentation a number of critical changes occur: carbon sources are diversified, nitrogen uptake and biosynthesis increase, and there is a dramatic up‐regulation of the entire sulfur‐containing amino acid synthetic pathways. Stimulation by L. bulgaricus is a more complex effect. Herve‐Jimenez, L. et al., Proteomics 2008, 8, 4273–4286. 2000‐spot 2‐D DIGE gels yield interesting new CJD marker from CSF Creutzfeld‐Jakob disease (CJD) is a rare, fatal neurodegenerative disease, caused by prions. It is normally seen in either a sporadic (sCJD) or variant (vCJD) form. Differential diagnosis is difficult because the few tests available are weak in sensitivity or specificity, or have not been thoroughly validated. Brechlin et al. report here a much improved cerebrospinal fluid test based on 2‐D DIGE technology and improved sample preparation. Samples were concentrated 20‐fold, then depleted of serum albumin and immunoglobulins, and, finally, labeled with CyDyes. When separated on 24‐cm pH 4 – 7 IPG strips, then on 10 % PAGE‐SDS second dimension gels, >2000 spots could be resolved. After spot analysis for significant differences (volume, p‐value, variance) five spots remained and 4 of the 5 were identified by MALDI‐TOF‐MS. The unidentified spot showed the highest discrimination (p <0.001). Identification work for the fifth spot is continuing. Brechlin, P. et al., Proteomics 2008, 8, 4357–4366.     

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.     

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.     

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.     

In this issue: 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.     

In this issue: Proteomics 20/2008

In this issue of Proteomics you will find the following highlighted articles: Comprehensively confirmed annotation of short ORFs During the California gold rush, prospectors did not look only for large nuggets to pave their road to riches – they also collected gold dust. The proteomic equivalent of dust is the small ORF. It does not pay to put a lower limit on dust or ORF size because almost any size may be turned into “cash” or an important peptide. Wei et al. demonstrate how a combination of conventional genomics and proteomics can find small expressed ORFs in noisy mixtures. Their test system is Shigella flexneri rRNA genes. First, cells were lysed, pre‐fractionated through 100 kDa and 10 kDa cutoff membranes and split into two aliquots, one treated with trypsin the other not. Both were analyzed by LC‐MS/MS and queried for ORFs >15 amino acids. Total labeled RNA probed a DNA array, and, after BLAST classification, revealed 36 new small proteins. Wei, C. et al., Proteomics 2008, 8, 4209–4213. The end of an era: Late stage proteome of cheese bacterium The bacterium Streptococcus thermophilus is a common ingredient in food, serving as a starter culture for a wide variety of dairy foods, yogurt in partic­ular, in co‐culture with Lactobacillus delbrueckii ssp. bulgaricus. It is closely related to several pathogenic species but lacks critical genes for pathogenicity. Instead, it is better optimized for lactose digestion than even a teen‐aged boy. Specific genes transport lactose into the cell where it is cleaved by a β‐galactosidase. Because milk is poor in amino acids, some strains of S. thermophilius bring their own protease to digest milk peptides and proteins. This work by Herve‐Jimenez et al. finds that in the latest stage of fermentation a number of critical changes occur: carbon sources are diversified, nitrogen uptake and biosynthesis increase, and there is a dramatic up‐regulation of the entire sulfur‐containing amino acid synthetic pathways. Stimulation by L. bulgaricus is a more complex effect. Herve‐Jimenez, L. et al., Proteomics 2008, 8, 4273–4286. 2000‐spot 2‐D DIGE gels yield interesting new CJD marker from CSF Creutzfeld‐Jakob disease (CJD) is a rare, fatal neurodegenerative disease, caused by prions. It is normally seen in either a sporadic (sCJD) or variant (vCJD) form. Differential diagnosis is difficult because the few tests available are weak in sensitivity or specificity, or have not been thoroughly validated. Brechlin et al. report here a much improved cerebrospinal fluid test based on 2‐D DIGE technology and improved sample preparation. Samples were concentrated 20‐fold, then depleted of serum albumin and immunoglobulins, and, finally, labeled with CyDyes. When separated on 24‐cm pH 4 – 7 IPG strips, then on 10 % PAGE‐SDS second dimension gels, >2000 spots could be resolved. After spot analysis for significant differences (volume, p‐value, variance) five spots remained and 4 of the 5 were identified by MALDI‐TOF‐MS. The unidentified spot showed the highest discrimination (p <0.001). Identification work for the fifth spot is continuing. Brechlin, P. et al., Proteomics 2008, 8, 4357–4366.     

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 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 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.     

In this issue: 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.