Lack of evidence for an association between Iridovirus and colony collapse disorder

Colony collapse disorder (CCD) is characterized by the unexplained losses of large numbers of adult worker bees (Apis mellifera) from apparently healthy colonies. Although infections, toxins, and other stressors have been associated with the onset of CCD, the pathogenesis of this disorder remains obscure. Recently, a proteomics study implicated a double-stranded DNA virus, invertebrate iridescent virus (Family Iridoviridae) along with a microsporidium (Nosema sp.) as the cause of CCD. We tested the validity of this relationship using two independent methods: (i) we surveyed healthy and CCD colonies from the United States and Israel for the presence of members of the Iridovirus genus and (ii) we reanalyzed metagenomics data previously generated from RNA pools of CCD colonies for the presence of Iridovirus-like sequences. Neither analysis revealed any evidence to suggest the presence of an Iridovirus in healthy or CCD colonies.     

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.     

Evaluating peptide mass fingerprinting-based protein identification

Identification of proteins by mass spectrometry (MS) is an essential step in proteomic studies and is typically accomplished by either peptide mass fingerprinting (PMF) or amino acid sequencing of the peptide. Although sequence information from MS/MS analysis can be used to validate PMF-based protein identification, it may not be practical when analyzing a large number of proteins and when high- throughput MS/MS instrumentation is not readily available. At present, a vast majority of proteomic studies employ PMF. However, there are huge disparities in criteria used to identify proteins using PMF. Therefore, to reduce incorrect protein identification using PMF, and also to increase confidence in PMF-based protein identification without accompanying MS/MS analysis, definitive guiding principles are essential. To this end, we propose a value-based scoring system that provides guidance on evaluating when PMF-based protein identification can be deemed sufficient without accompanying amino acid sequence data from MS/MS analysis.     

Rapidly maturing field of proteomics: A gateway to studying diseases

The proteomics work reported by Smith et al. represents a giant step forward in characterizing the cerebrospinal fluid (CSF) proteome in mouse models of human diseases. Whereas prior studies were limited to analysis of CSF pools, Smith et al. (Proteomics 2014, 14, 1102–1106) base their conclusions on data derived from individual mice, thereby capturing a fuller range of the biological diversity present. These results underscore how far proteomics has come in the past few years, developing into a modern tool with the capacity to remove bottlenecks in the study of neuropsychiatric diseases. Past efforts with mass spectrometry (MS) have been hampered by limitations in access to CSF samples, and small volumes when available. These barriers have been overcome with newer MS platforms and advances in sample preparation. We are far closer than before to producing the production of clinically useful proteomic data for biomarker discovery and for deriving insights into pathogenesis that can lead to more effective treatments for many diseases.     

A proteomic-based approach for the characterization of some major structural proteins involved in host-parasite relationships from the silkworm parasite Nosema bombycis (Microsporidia)

Nosema bombycis is the causative agent of the silkworm Bombyx mori pebrine disease which inflicts severe worldwide economical losses in sericulture. Little is known about host-parasite interactions at the molecular level for this spore-forming obligate intracellular parasite which belongs to the fungi-related Microsporidia phylum. Major microsporidian structural proteins from the spore wall (SW) and the polar tube (PT) are known to be involved in host invasion. We developed a proteomic-based approach to identify few N. bombycis proteins belonging to these cell structures. Protein extraction protocols were optimized and four N. bombycis spore protein extracts were compared by SDS-PAGE and 2-DE to establish complementary proteomic profiles. Three proteins were shown to be located at the parasite SW. Moreover, 17 polyclonal antibodies were raised against major N. bombycis proteins from all extracts, and three spots were shown to correspond to polar tube proteins (PTPs) by immunofluorescent assay and transmission electron microscopy immunocytochemistry on cryosections. Specific patterns for each PTP were obtained by MALDI-TOF-MS and MS/MS. Peptide sequence tags were deduced by de novo sequencing using Peaks Online and DeNovoX, then evaluated by MASCOT and SEQUEST searches. Identification parameters were higher than false-positive hits, strengthening our strategy that could be enlarged to a nongenomic context.     

Proteomics made more accessible

MS‐based proteomics is a bioinformatic‐intensive field. Additionally, the instruments and instrument‐related and analytic software are expensive. Some free Internet‐based proteomics tools have gained wide usage, but there have not been any single bioinformatic framework that in an easy and intuitive way guided the user through the whole process from analyses to submission. Together, these factors may have limited the expansion of proteomics analyses, and also the secondary use (reanalyses) of proteomic data. Vaudel et al. (Proteomics 2014, 14, 1001–1005) are now describing their Compomics framework that guides the user through all the main steps, from the database generation, via the analyses and validation, and through the submission process to PRIDE, a proteomic data bank. Vaudel et al. partly base the framework on tools that they have developed themselves, and partly they are integrating other freeware tools into the workflow. One of the most interesting aspects with the Compomics framework is the possibility of extending MS‐based proteomics outside the MS laboratory itself. With the Compomics framework, any laboratory can handle large amounts of proteomic data, thereby facilitating collaboration and in‐depth data analyses. The described software also opens the potential for any laboratory to reanalyze data deposited in PRIDE.     

Two birds with one stone: Doing metabolomics with your proteomics kit

Proteomic research facilities and laboratories are facing increasing demands for the integration of biological data from multiple ‘‐OMICS’ approaches. The aim to fully understand biological processes requires the integrated study of genomes, proteomes and metabolomes. While genomic and proteomic workflows are different, the study of the metabolome overlaps significantly with the latter, both in instrumentation and methodology. However, chemical diversity complicates an easy and direct access to the metabolome by mass spectrometry (MS). The present review provides an introduction into metabolomics workflows from the viewpoint of proteomic researchers. We compare the physicochemical properties of proteins and peptides with metabolites/small molecules to establish principle differences between these analyte classes based on human data. We highlight the implications this may have on sample preparation, separation, ionisation, detection and data analysis. We argue that a typical proteomic workflow (nLC‐MS) can be exploited for the detection of a number of aliphatic and aromatic metabolites, including fatty acids, lipids, prostaglandins, di/tripeptides, steroids and vitamins, thereby providing a straightforward entry point for metabolomics‐based studies. Limitations and requirements are discussed as well as extensions to the LC‐MS workflow to expand the range of detectable molecular classes without investing in dedicated instrumentation such as GC‐MS, CE‐MS or NMR.     

Mitochondrial building blocks

Despite many genomic and proteomic attempts, approximately half of all mitochondrial proteins remain unidentified. Moreover, the composition of mitochondria varies in different mammalian cell types and the details of this tissue specificity are unclear. Two recent reports provide a major advance in our understanding of mitochondrial function. Sickmann et al. used an exhaustive proteomic approach and came very close to identifying the complete set of yeast mitochondrial proteins. Mootha et al. examined mitochondria from mouse brain, heart, kidney and liver cells, finding that a surprising fraction of the proteins are expressed in only a subset of tissues.     

Why complexity and entropy matter: information, posttranslational modifications, and assay fidelity

Computationally aided protein identification of mass spectrometry (MS) data has been a challenge for the proteomic community since the field's inception. As the community attempts to address challenges such as computational site assignment of posttranslational modifications (PTMs), selective reaction monitoring data analysis, and the transition of proteomic assays to the clinic a robust framework with defined metrics is essential. The frameworks used for protein identification are currently score based, not hypothesis driven nor deterministic, resulting in a gradation from poor to good but without the ability to recognize when a given tandem MS spectrum has insufficient information in the context of the proteome to be identified. Means of computing deterministic and pseudodeterministic assays have been proposed by both us and others [Sherman, J., McKay, M.J., Ashman, K., Molloy, M.P., Unique ion signature mass spectrometry, a deterministic method to assign peptide identity. Mol. Cell. Proteomics 2009, 8, 2051-2062; Kiyonami, R., Schoen, A., Prakash, A., Peterman, S., et al., Increased selectivity, analytical precision, and through-put in targeted proteomics. Mol. Cell. Proteomics 2011, 10, M110.002931]. We believe it is crucial to incorporate the complexity of the proteome into the design of the experiment/data analysis upstream and that by doing so proteomic data analysis will become more robust. The seminal paper by Claude Shannon published in 1948 provides the robust mathematical framework now called Information Theory, to achieve this goal. Information Theory defines appropriate metrics for information and complexity as well as means to account for interference, all of which is directly applicable to peptide identification. We attempt to encourage the adoption of Information Theory as a means to ensure that appropriate metrics are used to measure the uncertainty in a peptide identification with or without PTM site assignment.     

LC‐MS/MS‐based serum proteomics for identification of candidate biomarkers for hepatocellular carcinoma

Associating changes in protein levels with the onset of cancer has been widely investigated to identify clinically relevant diagnostic biomarkers. In the present study, we analyzed sera from 205 patients recruited in the United States and Egypt for biomarker discovery using label‐free proteomic analysis by LC‐MS/MS. We performed untargeted proteomic analysis of sera to identify candidate proteins with statistically significant differences between hepatocellular carcinoma (HCC) and patients with liver cirrhosis. We further evaluated the significance of 101 proteins in sera from the same 205 patients through targeted quantitation by MRM on a triple quadrupole mass spectrometer. This led to the identification of 21 candidate protein biomarkers that were significantly altered in both the United States and Egyptian cohorts. Among the 21 candidates, ten were previously reported as HCC‐associated proteins (eight exhibiting consistent trends with our observation), whereas 11 are new candidates discovered by this study. Pathway analysis based on the significant proteins reveals upregulation of the complement and coagulation cascades pathway and downregulation of the antigen processing and presentation pathway in HCC cases versus patients with liver cirrhosis. The results of this study demonstrate the power of combining untargeted and targeted quantitation methods for a comprehensive serum proteomic analysis, to evaluate changes in protein levels and discover novel diagnostic biomarkers. All MS data have been deposited in the ProteomeXchange with identifier PXD001171 ( http://proteomecentral.proteomexchange.org/dataset/PXD001171 ).     

Proteome analysis of Schizosaccharomyces pombe by two-dimensional gel electrophoresis and mass spectrometry

The fission yeast Schizosaccharomyces pombe (S. pombe) is a unicellular eukaryote and contains many genes and regulatory mechanisms that are close to those of mammals. In this study, we performed a global proteomic analysis of the fission yeast S. pombe wild type h(-S) L 972 proteome. More than 1,500 protein spots were visualized on silver stained 2-D gels in the 3-10 pI range with a high resolution and high reproducibility. Protein identification was carried out by MALDI-TOF-MS and/or nanoLC-MS/MS. Advantage of the complementarity of these two MS approaches was used to enhance the identification quality. So far, 364 proteins (representing 157 different proteins) have been identified. We report here the identification of 117 new proteins on our 2-D reference map of this yeast compared to the first reference map. Of these identified proteins, 40.1% were involved in metabolism. The present work provides a very useful tool for all studies relying on S. pombe as a model organism and is a considerable complement to the first reference map of S. pombe published recently by Sun and coworkers (Sun, N., Jang, J., Lee, S., Kim, S. et al.., Proteomics 2005, 5, 1574-1579).     

Tissue proteomics using chemical immobilization and mass spectrometry

Proteomics analysis is important for characterizing tissues to gain biological and pathological insights, which could lead to the identification of disease-associated proteins for disease diagnostics or targeted therapy. However, tissues are commonly embedded in optimal cutting temperature medium (OCT) or are formalin-fixed and paraffin-embedded (FFPE) in order to maintain tissue morphology for histology evaluation. Although several tissue proteomic analyses have been performed on FFPE tissues using advanced mass spectrometry (MS) technologies, high-throughput proteomic analysis of OCT-embedded tissues has been difficult due to the interference of OCT in the MS analysis. In addition, molecules other than proteins present in tissues further complicate tissue proteomic analysis. Here, we report the development of a method using chemical immobilization of proteins for peptide extraction (CIPPE). In this method, proteins are chemically immobilized onto a solid support; interferences from tissues and OCT embedding are removed by extensive washing of proteins conjugated on the solid support. Peptides are then released from the solid phase by proteolysis, enabling MS analysis. This method was first validated by eliminating OCT interference from a standard protein, human serum albumin, where all of the unique peaks contributed by OCT contamination were eradicated. Finally, this method was applied for the proteomic analysis of frozen and OCT-embedded tissues using iTRAQ (isobaric tag for relative and absolute quantitation) labeling and two-dimensional liquid chromatography tandem mass spectrometry. The data showed reproducible extraction and quantitation of 10,284 proteins from 3996 protein groups and a minimal impact of OCT embedding on the analysis of the global proteome of the stored tissue samples.     

Analysis of secreted proteins from Aspergillus flavus

MS/MS techniques in proteomics make possible the identification of proteins from organisms with little or no genome sequence information available. Peptide sequences are obtained from tandem mass spectra by matching peptide mass and fragmentation information to protein sequence information from related organisms, including unannotated genome sequence data. This peptide identification data can then be grouped and reconstructed into protein data. In this study, we have used this approach to study protein secretion by Aspergillus flavus, a filamentous fungus for which very little genome sequence information is available. A. flavus is capable of degrading the flavonoid rutin (quercetin 3-O-glycoside), as the only source of carbon via an extracellular enzyme system. In this continuing study, a proteomic analysis was used to identify secreted proteins from A. flavus when grown on rutin. The growth media glucose and potato dextrose were used to identify differentially expressed secreted proteins. The secreted proteins were analyzed by 1- and 2-DE and MS/MS. A total of 51 unique A. flavus secreted proteins were identified from the three growth conditions. Ten proteins were unique to rutin-, five to glucose- and one to potato dextrose-grown A. flavus. Sixteen secreted proteins were common to all three media. Fourteen identifications were of hypothetical proteins or proteins of unknown functions. To our knowledge, this is the first extensive proteomic study conducted to identify the secreted proteins from a filamentous fungus.     

A novel approach and protocol for discovering extremely low-abundance proteins in serum

The proteomic analysis of serum (plasma) has been a major approach to determining biomarkers essential for early disease diagnoses and drug discoveries. The determination of these biomarkers, however, is analytically challenging since the dynamic concentration range of serum proteins/peptides is extremely wide (more than 10 orders of magnitude). Thus, the reduction in sample complexity prior to proteomic analyses is essential, particularly in analyzing low-abundance protein biomarkers. Here, we demonstrate a novel approach to the proteomic analyses of human serum that uses an originally developed serum protein separation device and a sequentially linked 3-D-LC-MS/MS system. Our hollow-fiber-membrane-based serum pretreatment device can efficiently deplete high-molecular weight proteins and concentrate low-molecular weight proteins/peptides automatically within 1 h. Four independent analyses of healthy human sera pretreated using this unique device, followed by the 3-D-LC-MS/MS successfully produced 12 000-13 000 MS/MS spectra and hit around 1800 proteins (>95% reliability) and 2300 proteins (>80% reliability). We believe that the unique serum pretreatment device and proteomic analysis protocol reported here could be a powerful tool for searching physiological biomarkers by its high throughput (3.7 days per one sample analysis) and high performance of finding low abundant proteins from serum or plasma samples.     

Proteomic profiling of the mitochondrial inner membrane of rat renal proximal convoluted tubules

The proximal convoluted tubule is the primary site of renal fluid, electrolyte, and nutrient reabsorption, processes that consume large amounts of adenosine‐5′‐triphosphate. Previous proteomic studies have profiled the adaptions that occur in this segment of the nephron in response to the onset of metabolic acidosis. To extend this analysis, a proteomic workflow was developed to characterize the proteome of the mitochondrial inner membrane of the rat renal proximal convoluted tubule. Separation by LC coupled with analysis by MS/MS (LC‐MS/MS) confidently identified 206 proteins in the combined samples. Further proteomic analysis identified 14 peptides that contain an N‐?‐acetyl‐lysine, seven of which are novel sites. This study provides the first proteomic profile of the mitochondrial inner membrane proteome of this segment of the rat renal nephron. The MS data have been deposited in the ProteomeXchange with the identifier PXD000121.     

Local database and the search program for proteomic analysis of sperm proteins in the ascidian Ciona intestinalis

Separation of proteins by two-dimensional electrophoresis and following mass spectrometry (MS) is now a conventional technique for proteomic analysis. For proteomic analysis of a certain tissue with a limited information of primary structures of proteins, we have developed an analytical system for peptide mass fingerprinting in gene products in the testis of the ascidian Ciona intestinalis. Ciona sperm proteins were separated by two-dimensional gel electrophoresis and the tryptic fragments were subjected to MALDI-TOF/MS. The mass pattern was searched against on-line databases but resulted in less identification of these proteins. We have constructed a MS database from Ciona testis ESTs and the genome draft sequence, along with a newly devised, perl-based search program PerMS for peptide mass fingerprinting. This system could identify more than 80% of Ciona sperm proteins, suggesting that it could be widely applied for proteomic analysis for a limited tissue with less genomic information.