Protein Identification Data Research Articles

Evaluation of method parameters for sound undecalcified dental enamel proteomics using liquid chromatography-mass spectrometry

ObjectiveThis study aims to validate a methodology for analyzing undecalcified, sound dental enamel proteomics using Liquid Chromatography-Mass Spectrometry (LC-MS). The study evaluates various parameters, including the impact of dental root coverage on protein contamination, the efficacy of protease inhibitors during enamel sample preparation, repeatability of LC-MS measurements on dental enamel, and statistical analysis. The study also assesses the effectiveness of combined trypsin and semi-trypsin searches in Mascot for obtaining additional protein identification data. DesignSound dental enamel was removed using a wet grinding technique, then digested with trypsin and labeled with TMT prior to LC-MS analysis. The resulting proteomes were matched against the Homo sapiens Swissprot Database, with searches in Mascot performed using both trypsin and semitrypsin. Statistical methods were employed to analyze the data. ResultsThe study found that covering dental roots with composite during dental enamel microdissection is advisable, while using protease inhibition during microdissection may not be fully supported. The proteomic analyses demonstrated statistical repeatability and reliability, with consistent and reproducible proteomic data obtained from healthy dental enamel. Furthermore, employing both trypsin and semitrypsin searches in Mascot provided additional proteomic information. ConclusionsOverall, this study validates a methodology for analyzing undecalcified, sound dental enamel proteomics using LC-MS, and provides insights into various factors that can affect the quality and reliability of proteomic data. These findings have implications for future studies pursuant to understanding the proteomic mechanisms underlying dental enamel formation and other associated processes.

Proteomic Discovery: Elevated Neurogranin Levels in Children with Sickle Cell Disease

Sickle cell disease (SCD) is an inherited hemoglobinopathy that frequently causes neurological complications, such as stroke, silent cerebral infarct (SCI) and other forms of brain injury, including loss of cognition. SCI is defined as any ischemic lesion visible on T2-weighted magnetic resonance imaging (MRI) that is not associated with a focal neurologic deficit in the same vascular distribution, and is the most commonly recognized form of brain injury in SCD. SCI is associated with decreased neurocognitive function and increased risk for new or enlarging SCI/stroke. The purpose of this study was to use mass spectrometry (MS) based proteomics to discover and validate plasma brain proteins associated with brain injury in children with SCD. The plasma samples used for the proteomics discovery analyses were from two groups: screening samples of participants in the Silent Cerebral Infarct Multi-Center Clinical Trial (SIT Trial) (n=15), and 6 age-matched, healthy non-SCD controls, three of whom had sickle cell trait. Samples from children with SCD were divided into two groups: those with SCI (n=7) and those without SCI (n=8) matched for age, hemoglobin (Hb) and white blood cell counts. To identify circulating markers of SCI, plasma proteomes were analyzed using a sequential separation approach of Hb and top abundant plasma protein depletion, followed by reverse phase separation of intact proteins, trypsin digestion and tandem MS. Neurogranin (NRGN), a small calmodulin-binding synaptic protein (PMID 9886843), was the most abundant brain-enriched protein found in the plasma of children with SCD. We developed a NRGN sandwich immunoassay for verification of MS analysis results in an independent cohort from the SIT Trial longitudinal samples. For this verification study, plasma samples from the SIT Trial and 25 normal controls were tested for NRGN levels at study entry and exit by immunoassay. The majority of the SCD samples were obtained from an ancillary study to collect longitudinal samples that started after the SIT Trial had begun. There was no overlap between the discovery and the verification group samples. The normal control samples were from 25 healthy, age and gender comparable non-SCD pediatric controls unrelated to the SIT Trial, without evidence of acute/chronic illness. From the discovery SCD group, 1172 unambiguous proteins were identified; 639 proteins were identified from normal controls, as shown in Figure 1. Twenty-five percent (289/1172) of these proteins were found solely in the SCI group. Our MS protein identification data were filtered against this list of expressed brain proteins to produce a composite list of brain proteins found in plasma from children with SCD, but not found in plasma from age, gender and race-matched healthy control children. Twenty-five plasma proteins known to be expressed in one or more cell type enriched in the human brain based on bioinformatics searches were more abundant in the SCD vs control groups, as shown in Table 1. Median NRGN levels were higher at study entry in children with SCD (0.44 ng/mL, N=98), in comparison to a healthy, non-SCD control group (0.12 ng/mL, N=25, p < 0.0001), as shown in Figure 2. Using the longitudinal samples from the SIT Trial, there were no differences in NRGN levels between the observation group and the treatment group (p=0.35) over time. There was no significant difference in median NRGN levels between the observation group and the treatment group at the initial visit (0.36 vs 0.19, p=0.069) or final visit (0.39 vs 0.52, p=0.52). Using the initial visit samples from the SIT Trial, there was no significant difference in median NRGN levels between the non-SCI (n=35) and SCI groups (n=61) (p=0.073). There was no significant correlation between NRGN levels and neuropsychological measures of executive function (rho=0.089, p=0.58) and IQ (rho=-0.081, p=0.62). Our non-biased proteomic discovery studies demonstrate that NRGN levels are increased in children with SCD, when compared to normal children. Additional studies will be necessary to determine whether NRGN levels correlate with specific forms of neurologic injury. Further validation studies of larger cohorts with a multi-analyte ELISA of these brain proteins identified in plasma (Table 1) are warranted, and could help establish possible links between brain-specific proteins and neurocognitive outcomes. Disclosures Lance: NIH: Research Funding; KKI: Research Funding. Faulcon:FDA: Employment, Other: Although the author is a FDA/CTP employee, this work was not done as part his/her official duties. This publication reflects the views of the author and should not be construed to reflect the FDA/CTP's views or policies.. Fu:GSK: Employment. Yang:ImmunArray: Patents & Royalties: ImmunArray. Strouse:Global Blood Therapeutics: Consultancy. Barron-Casella:Mast Pharmaceudicals - spouse: Consultancy; ImmunArray - spouse: Patents & Royalties. Van Eck:ImmunArray: Consultancy, Patents & Royalties. Casella:NIH: Research Funding; Mast Pharmaceuticals: Consultancy; Immunoarray Ltd.: Patents & Royalties. Everett:ImmunArray: Consultancy, Patents & Royalties.

The Response of Haloferax volcanii to Salt and Temperature Stress: A Proteome Study by Label-Free Mass Spectrometry.

In-depth proteome analysis of the haloarchaeal model organism Haloferax volcanii has been performed under standard, low/high salt, and low/high temperature conditions using label-free mass spectrometry. Qualitative analysis of protein identification data from high-pH/reversed-phase fractionated samples indicates 61.1% proteome coverage (2509 proteins), which is close to the maximum recorded values in archaea. Identified proteins match to the predicted proteome in their physicochemical properties, with only a small bias against low-molecular-weight and membrane-associated proteins. Cells grown under low and high salt stress as well as low and high temperature stress are quantitatively compared to standard cultures by sequential window acquisition of all theoretical mass spectra (SWATH-MS). A total of 2244 proteins, or 54.7% of the predicted proteome, are quantified across all conditions at high reproducibility, which allowed for global analysis of protein expression changes under these stresses. Of these, 2034 are significantly regulated under at least one stress condition. KEGG pathway enrichment analysis shows that several major cellular pathways are part of H. volcanii's universal stress response. In addition, specific pathways (purine, cobalamin, and tryptophan) are affected by temperature stress. The most strongly downregulated proteins under all stress conditions, zinc finger protein HVO_2753 and ribosomal protein S14, are found oppositely regulated to their immediate genetic neighbors from the same operon.

Exploratory proteomics of human synovial fluid in knee osteoarthritis: towards biomarker identification

Purpose: There is a lack of valid and robust biomarkers in the field of OA diagnosis, prognosis, and treatment evaluation. Thus, our aim was to perform mass spectrometry (MS) of human synovial fluid using a global discovery approach, to identify biomarker candidates associated with meniscus degradation and/or knee OA. Methods: Synovial fluid was sampled from 3 different subject groups: i) end-stage medial compartment knee OA patients undergoing arthroplasty (n=11, 3 men, 8 women; age range 55-80 years), ii) knee arthroscopy patients who had knee symptoms but no or only minor knee trauma, typically having a degenerative meniscal tear (n=7, 3 men, 5 women; age range 50-64 years), and iii) deceased human donors (within 48 hours post mortem) without known chronic knee disease (n=13, 8 men, 5 women; age range 19-79 years). These 3 groups were roughly assumed to represent i) end-stage knee OA, ii) early knee OA, and iii) healthy controls, respectively. For all 3 groups, we required no visual signs of blood contamination to be present in the synovial fluid. For the cadaver knee tissues (controls), we further required the meniscus and the weight-bearing femoral surface of cartilage/bone to be macroscopically intact. All synovial fluids were centrifuged and freshly frozen and stored at -80°C. For the analysis, 50 μL of synovial fluid from each sample was mixed with MS-safe proteinase inhibitor cocktail and hyaluronidase, and further depleted of the 7 most abundant proteins with the multiple affinity removal system (MARS Hu7 spin cartridge). After reduction and alkylation, the samples were precipitated and the pellets were further digested with sequencing grade trypsin (Promega. Following digestion, samples were cleaned with a 30kDa filter and desalted. The samples were further spiked with iRT peptides before analysis by MS. The samples were analyzed with an EASY-nLC 1000 coupled to an Orbitrap Fusion mass spectrometer. The samples were analyzed with data-independent acquisition settings. The raw MS data were further analyzed with Spectronaut™ software for protein identification and quant data extraction. The quant data extracted using Spectronaut™ were further imported into the R environment (http://www.R-project.org/) to facilitate data analysis and visualization. Differences in protein levels between the 3 different groups were analyzed using the limma package and multiple logistic regression analysis. Differentially expressed proteins between the groups were clustered by hierarchical clustering using Pearson correlation coefficient as the distance metric. For each cluster, the enriched Gene Ontology terms and Reactome pathway names were identified and the most representative ones were annotated. Results: In total, 529 proteins were identified in the 31 different synovial fluid samples. Principal component analysis suggested a profound difference between the protein profiles of synovial fluid from controls vs arthroplasty patients, while the arthroscopy group had a protein profile that was in-between controls and the arthroplasty group (Figure 1). Statistical differential analysis yielded significant differences in the levels of 45 proteins comparing controls vs arthroplasty patients, 43 proteins for controls vs arthroscopy patients, and 58 proteins for arthroplasty vs arthroscopy patients. Extracellular matrix proteins like collagens and aggrecan showed higher expression in controls than in arthroplasty patients. Collagen on the other hand was higher in arthroscopy patients compared to controls. Decorin, a previously suggested biomarker candidate for OA, was significantly higher in controls compared to both arthroscopy and arthroplasty patients. The differentially expressed proteins associated with the acute inflammatory response (Table 1) were higher in the arthroscopy group compared to both controls and arthroplasty patients. Generally, extracellular matrix proteins were negatively correlated with immune system proteins and positively correlated with proteins involved in wound healing (Figure 2). Conclusions: There is a profound difference in the protein profile of human synovial fluid in knee-healthy controls vs knee OA patients. The inflammatory response seems to be higher in the early stages of OA than in later stages of the disease. Our findings emphasize the importance of OA staging in the development and use of biomarkers.View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT)

2016 update of the PRIDE database and its related tools.

The PRoteomics IDEntifications (PRIDE) database is one of the world-leading data repositories of mass spectrometry (MS)-based proteomics data. Since the beginning of 2014, PRIDE Archive (http://www.ebi.ac.uk/pride/archive/) is the new PRIDE archival system, replacing the original PRIDE database. Here we summarize the developments in PRIDE resources and related tools since the previous update manuscript in the Database Issue in 2013. PRIDE Archive constitutes a complete redevelopment of the original PRIDE, comprising a new storage backend, data submission system and web interface, among other components. PRIDE Archive supports the most-widely used PSI (Proteomics Standards Initiative) data standard formats (mzML and mzIdentML) and implements the data requirements and guidelines of the ProteomeXchange Consortium. The wide adoption of ProteomeXchange within the community has triggered an unprecedented increase in the number of submitted data sets (around 150 data sets per month). We outline some statistics on the current PRIDE Archive data contents. We also report on the status of the PRIDE related stand-alone tools: PRIDE Inspector, PRIDE Converter 2 and the ProteomeXchange submission tool. Finally, we will give a brief update on the resources under development 'PRIDE Cluster' and 'PRIDE Proteomes', which provide a complementary view and quality-scored information of the peptide and protein identification data available in PRIDE Archive.

Effective Leveraging of Targeted Search Spaces for Improving Peptide Identification in Tandem Mass Spectrometry Based Proteomics.

In shotgun proteomics, peptides are typically identified using database searching, which involves scoring acquired tandem mass spectra against peptides derived from standard protein sequence databases such as Uniprot, Refseq, or Ensembl. In this strategy, the sensitivity of peptide identification is known to be affected by the size of the search space. Therefore, creating a targeted sequence database containing only peptides likely to be present in the analyzed sample can be a useful technique for improving the sensitivity of peptide identification. In this study, we describe how targeted peptide databases can be created based on the frequency of identification in the global proteome machine database (GPMDB), the largest publicly available repository of peptide and protein identification data. We demonstrate that targeted peptide databases can be easily integrated into existing proteome analysis workflows and describe a computational strategy for minimizing any loss of peptide identifications arising from potential search space incompleteness in the targeted search spaces. We demonstrate the performance of our workflow using several data sets of varying size and sample complexity.

2016 update of the PRIDE database and its related tools.

The PRoteomics IDEntifications (PRIDE) database is one of the world-leading data repositories of mass spectrometry (MS)-based proteomics data. Since the beginning of 2014, PRIDE Archive (http://www.ebi.ac.uk/pride/archive/) is the new PRIDE archival system, replacing the original PRIDE database. Here we summarize the developments in PRIDE resources and related tools since the previous update manuscript in the Database Issue in 2013. PRIDE Archive constitutes a complete redevelopment of the original PRIDE, comprising a new storage backend, data submission system and web interface, among other components. PRIDE Archive supports the most-widely used PSI (Proteomics Standards Initiative) data standard formats (mzML and mzIdentML) and implements the data requirements and guidelines of the ProteomeXchange Consortium. The wide adoption of ProteomeXchange within the community has triggered an unprecedented increase in the number of submitted data sets (around 150 data sets per month). We outline some statistics on the current PRIDE Archive data contents. We also report on the status of the PRIDE related stand-alone tools: PRIDE Inspector, PRIDE Converter 2 and the ProteomeXchange submission tool. Finally, we will give a brief update on the resources under development ‘PRIDE Cluster’ and ‘PRIDE Proteomes’, which provide a complementary view and quality-scored information of the peptide and protein identification data available in PRIDE Archive.

On Credibility, Clarity, and Compliance

On Credibility, Clarity, and Compliance

Quantitative Proteomics in Laser Capture Microdissected Sleep Nuclei From Rat Brain

The combination of stable isotope labeling of amino acids in mammals (SILAM) and laser capture microdissection (LCM) for selective proteomic analysis of the targeted tissues holds tremendous potential for refined characterization of proteome changes within complex tissues such as the brain. The authors have applied this approach to measure changes in relative protein abundance in ventral tegmental area (VTA) of the rat brain that correlate to pharmacological perturbations. Enriched 13C615N2-lysine was introduced in vivo via diet. These animals were sacrificed during the middle of the 12-hour light period to extract isotopically “heavy” proteins, which were then used as a reference for extracts from dosed, unlabeled rats. Animals were administered an orexin peptide (Ox-B), an orexin receptor antagonist (ORA), or a mixture of both (Ox-B + ORA). All samples were obtained at same phase of the sleep cycle. Labeled-pair identification and differential quantitation provided protein identification and expression ratio data. Five proteins were found to exhibit decreased relative abundance after administration of an ORA, including α-synuclein and rat myelin basic protein. Conversely, six proteins showed increased relative abundance upon antagonist treatment, including 2’,3’-cyclic nucleotide 3’-phosphodiesterase.

Current Bioinformatics Challenges in Proteome Dynamics using Heavy Water-based Metabolic Labeling.

Current Bioinformatics Challenges in Proteome Dynamics using Heavy Water-based Metabolic Labeling.

Comprehensive Identification of Proteins from MALDI Imaging

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool for the visualization of proteins in tissues and has demonstrated considerable diagnostic and prognostic value. One main challenge is that the molecular identity of such potential biomarkers mostly remains unknown. We introduce a generic method that removes this issue by systematically identifying the proteins embedded in the MALDI matrix using a combination of bottom-up and top-down proteomics. The analyses of ten human tissues lead to the identification of 1400 abundant and soluble proteins constituting the set of proteins detectable by MALDI IMS including >90% of all IMS biomarkers reported in the literature. Top-down analysis of the matrix proteome identified 124 mostly N- and C-terminally fragmented proteins indicating considerable protein processing activity in tissues. All protein identification data from this study as well as the IMS literature has been deposited into MaTisse, a new publically available database, which we anticipate will become a valuable resource for the IMS community.

The mzIdentML Data Standard for Mass Spectrometry-Based Proteomics Results

We report the release of mzIdentML, an exchange standard for peptide and protein identification data, designed by the Proteomics Standards Initiative. The format was developed by the Proteomics Standards Initiative in collaboration with instrument and software vendors, and the developers of the major open-source projects in proteomics. Software implementations have been developed to enable conversion from most popular proprietary and open-source formats, and mzIdentML will soon be supported by the major public repositories. These developments enable proteomics scientists to start working with the standard for exchanging and publishing data sets in support of publications and they provide a stable platform for bioinformatics groups and commercial software vendors to work with a single file format for identification data.

JmzIdentML API: A Java interface to the mzIdentML standard for peptide and protein identification data

We present a Java application programming interface (API), jmzIdentML, for the Human Proteome Organisation (HUPO) Proteomics Standards Initiative (PSI) mzIdentML standard for peptide and protein identification data. The API combines the power of Java Architecture of XML Binding (JAXB) and an XPath-based random-access indexer to allow a fast and efficient mapping of extensible markup language (XML) elements to Java objects. The internal references in the mzIdentML files are resolved in an on-demand manner, where the whole file is accessed as a random-access swap file, and only the relevant piece of XMLis selected for mapping to its corresponding Java object. The APIis highly efficient in its memory usage and can handle files of arbitrary sizes. The APIfollows the official release of the mzIdentML (version 1.1) specifications and is available in the public domain under a permissive licence at http://www.code.google.com/p/jmzidentml/.

The ProteoRed MIAPE web toolkit: A User-friendly Framework to Connect and Share Proteomics Standards

The development of the HUPO-PSI's (Proteomics Standards Initiative) standard data formats and MIAPE (Minimum Information About a Proteomics Experiment) guidelines should improve proteomics data sharing within the scientific community. Proteomics journals have encouraged the use of these standards and guidelines to improve the quality of experimental reporting and ease the evaluation and publication of manuscripts. However, there is an evident lack of bioinformatics tools specifically designed to create and edit standard file formats and reports, or embed them within proteomics workflows. In this article, we describe a new web-based software suite (The ProteoRed MIAPE web toolkit) that performs several complementary roles related to proteomic data standards. First, it can verify that the reports fulfill the minimum information requirements of the corresponding MIAPE modules, highlighting inconsistencies or missing information. Second, the toolkit can convert several XML-based data standards directly into human readable MIAPE reports stored within the ProteoRed MIAPE repository. Finally, it can also perform the reverse operation, allowing users to export from MIAPE reports into XML files for computational processing, data sharing, or public database submission. The toolkit is thus the first application capable of automatically linking the PSI's MIAPE modules with the corresponding XML data exchange standards, enabling bidirectional conversions. This toolkit is freely available at http://www.proteored.org/MIAPE/.

Identification of Outer Membrane Proteins from an Antarctic Bacterium Pseudomonas syringae Lz4W

Subcellular fractionation of proteins is a preferred method of choice for detection and identification of proteins from complex mixtures such as bacterial cells. To characterize the membrane proteins of the Antarctic bacterium Pseudomonas syringae Lz4W, the membrane fractions were prepared using three different methods, namely Triton X-100 solubilization, sucrose density gradient, and carbonate extraction methods. The proteins were separated on one-dimensional polyacrylamide gels and analyzed using a combination of liquid chromatography-coupled electrospray ionization-MS. The membrane proteins that were prepared by carbonate extraction were separated on two-dimensional PAGE in different pI ranges using the detergent 2% amidosulfobetaine (ASB). The proteins were then subjected to matrix-assisted laser desorption ionization-time-of-flight/time-of-flight for analysis and identification. Because the genome sequence of P. syringae Lz4W is not known, the proteins were identified by using the relevant sequence databases of the Pseudomonas sp available at National Centre for Biotechnology Information (NCBI). The sequence identification of some tryptic peptides were validated by de novo sequencing and others by chemical modification and mass spectrometry. The peptide sequences of P. syringae Lz4W were then matched with the sequences of the peptides from different Pseudomonas sp. by similarity search of the proteins from different species using clustal W2 program. Thus by using a combination of the methods, we have been able to identify large number of proteins of this bacterial strain, which include most of the outer membrane proteins.

A DIGE study on the effects of salbutamol on the rat muscle proteome - an exemplar of best practice for data sharing in proteomics

BackgroundProteomic techniques allow researchers to perform detailed analyses of cellular states and many studies are published each year, which highlight large numbers of proteins quantified in different samples. However, currently few data sets make it into public databases with sufficient metadata to allow other groups to verify findings, perform data mining or integrate different data sets. The Proteomics Standards Initiative has released a series of "Minimum Information About a Proteomics Experiment" guideline documents (MIAPE modules) and accompanying data exchange formats. This article focuses on proteomic studies based on gel electrophoresis and demonstrates how the corresponding MIAPE modules can be fulfilled and data deposited in public databases, using a new experimental data set as an example.FindingsWe have performed a study of the effects of an anabolic agent (salbutamol) at two different time points on the protein complement of rat skeletal muscle cells, quantified by difference gel electrophoresis. In the DIGE study, a total of 31 non-redundant proteins were identified as being potentially modulated at 24 h post treatment and 110 non redundant proteins at 96 h post-treatment. Several categories of function have been highlighted as strongly enriched, providing candidate proteins for further study. We also use the study as an example of best practice for data deposition.ConclusionsWe have deposited all data sets from this study in public databases for further analysis by the community. We also describe more generally how gel-based protein identification data sets can now be deposited in the PRoteomics IDEntifications database (PRIDE), using a new software tool, the PRIDESpotMapper, which we developed to work in conjunction with the PRIDE Converter application. We also demonstrate how the ProteoRed MIAPE generator tool can be used to create and share a complete and compliant set of MIAPE reports for this experiment and others.

Exploring the proteome of an echinoderm nervous system: 2-DE of the sea star radial nerve cord and the synaptosomal membranes subproteome

We describe the first proteomic characterization of the radial nerve cord (RNC) of an echinoderm, the sea star Marthasterias glacialis. The combination of 2-DE with MS (MALDI-TOF/TOF) resulted in the identification of 286 proteins in the RNC. Additionally, 158 proteins were identified in the synaptosomal membranes enriched fraction after 1-DE separation. The 2-DE RNC reference map is available via the WORLD-2DPAGE Portal (http://www.expasy.ch/world-2dpage/) along with the associated protein identification data which are also available in the PRIDE database. The identified proteins constitute the first high-throughput evidence that seems to indicate that echinoderms nervous transmission relies primarily on chemical synapses which is similar to the synaptic activity in adult mammal's spinal cord. Furthermore, several homologous proteins known to participate in the regeneration events of other organisms were also identified, and thus can be used as targets for future studies aiming to understand the poorly uncharacterized regeneration capability of echinoderms. This "echinoderm missing link" is also a contribution to unravel the mystery of deuterostomian CNS evolution.

The sheep milk fat globule membrane proteome

Milk fat globule membranes (MFGM) are three-layered structures that enclose fat droplets, and are composed by an internal monolayer of endoplasmic reticulum origin, surrounded by a bilayer derived from the apical membrane of the lactating cell. In this work, an optimized protein extraction method was applied to sheep MFGM, and extracts were subjected to SDS-PAGE separation followed by shotgun LC tandem mass spectrometry (GeLC-MS/MS) for identification and characterization. In total, 140 unique sheep MFGM proteins (MFGMPs) were identified. All protein identification data were subjected to Gene Ontology (GO) classification for localization and function. Moreover, the relative abundance of all identified MFGMPs was estimated by means of the normalized spectral abundance factor (NSAF) approach, and GO abundance classes were obtained. The data gathered in this work provide a detailed picture of the proteome expressed in healthy sheep MFGs, and lay the foundations for future studies on sheep lactation physiology and on its alterations in pathological conditions.

Protecs, a comprehensive and powerful storage and analysis system for OMICS data, applied for profiling the anaerobiosis response ofStaphylococcus aureusCOL

Broad functional genomic studies call for comprehensive and powerful data repositories for storage of genome sequences, experimental information, protein identification data, protein properties and expression values. The better such data repositories can integrate and display complex data in a clear and structured way the more biologically meaningful conclusions or novel hypotheses can be derived from extensive omics data sets. This work presents the web accessible database system Protecs and how it was used to support analysis of 50 samples drawn from four Staphylococcus aureus cultivations under anaerobiosis. Protecs incorporates findings from visualization science, e.g. micro charts and heat maps in the user interface. Its integrated tools for expression data analysis in combination with TIGR Multi Experiment Viewer were used to highlight similar gene expression profiles in single or multiple experiments based on the continuously updated S. aureus master gel. Raw data analysis results are available online at www.protecs.uni-greifswald.de. Our meta-study revealed that S. aureus responds in different anaerobiotic experimental setups (growth without oxygen; growth without oxygen but with supplemental pyruvate and uracil; growth without oxygen but with NO(3)(-); growth without oxygen but with NO(3)(-) and without functional nreABC genes) with a general anaerobiosis response. Among others, this response is characterized by an induction of fermentation enzymes (PflB, Ldh1, SACOL0135, SACOL0660) as well as the response regulator SrrA. Interestingly, especially genes with a high codon adaptation index highly overlap with anaerobically induced genes.

Megadalton Complexes in the Chloroplast Stroma of Arabidopsis thaliana Characterized by Size Exclusion Chromatography, Mass Spectrometry, and Hierarchical Clustering

To characterize MDa-sized macromolecular chloroplast stroma protein assemblies and to extend coverage of the chloroplast stroma proteome, we fractionated soluble chloroplast stroma in the non-denatured state by size exclusion chromatography with a size separation range up to approximately 5 MDa. To maximize protein complex stability and resolution of megadalton complexes, ionic strength and composition were optimized. Subsequent high accuracy tandem mass spectrometry analysis (LTQ-Orbitrap) identified 1081 proteins across the complete native mass range. Protein complexes and assembly states above 0.8 MDa were resolved using hierarchical clustering, and protein heat maps were generated from normalized protein spectral counts for each of the size exclusion chromatography fractions; this complemented previous analysis of stromal complexes up to 0.8 MDa (Peltier, J. B., Cai, Y., Sun, Q., Zabrouskov, V., Giacomelli, L., Rudella, A., Ytterberg, A. J., Rutschow, H., and van Wijk, K. J. (2006) The oligomeric stromal proteome of Arabidopsis thaliana chloroplasts. Mol. Cell. Proteomics 5, 114-133). This combined experimental and bioinformatics analyses resolved chloroplast ribosomes in different assembly and functional states (e.g. 30, 50, and 70 S), which enabled the identification of plastid homologues of prokaryotic ribosome assembly factors as well as proteins involved in co-translational modifications, targeting, and folding. The roles of these ribosome-associating proteins will be discussed. Known RNA splice factors (e.g. CAF1/WTF1/RNC1) as well as uncharacterized proteins with RNA-binding domains (pentatricopeptide repeat, RNA recognition motif, and chloroplast ribosome maturation), RNases, and DEAD box helicases were found in various sized complexes. Chloroplast DNA (>3 MDa) was found in association with the complete heteromeric plastid-encoded DNA polymerase complex, and a dozen other DNA-binding proteins, e.g. DNA gyrase, topoisomerase, and various DNA repair enzymes. The heteromeric >or=5-MDa pyruvate dehydrogenase complex and the 0.8-1-MDa acetyl-CoA carboxylase complex associated with uncharacterized biotin carboxyl carrier domain proteins constitute the entry point to fatty acid metabolism in leaves; we suggest that their large size relates to the need for metabolic channeling. Protein annotations and identification data are available through the Plant Proteomics Database, and mass spectrometry data are available through Proteomics Identifications database.