Growth of Cyanobacteria Is Constrained by the Abundance of Light and Carbon Assimilation Proteins.

Cyanobacteria must balance separate demands for energy generation, carbon assimilation, and biomass synthesis. We used shotgun proteomics to investigate proteome allocation strategies in the model cyanobacterium Synechocystis sp. PCC 6803 as it adapted to light and inorganic carbon (Ci) limitation. When partitioning the proteome into seven functional sectors, we find that sector sizes change linearly with growth rate. The sector encompassing ribosomes is significantly smaller than in E. coli, which may explain the lower maximum growth rate in Synechocystis. Limitation of light dramatically affects multiple proteome sectors, whereas the effect of Ci limitation is weak. Carbon assimilation proteins respond more strongly to changes in light intensity than to Ci. A coarse-grained cell economy model generally explains proteome trends. However, deviations from model predictions suggest that the large proteome sectors for carbon and light assimilation are not optimally utilized under some growth conditions and may constrain the proteome space available to ribosomes.

A multicentric study to evaluate the use of relative retention times in targeted proteomics.

Despite the maturity reached by targeted proteomic strategies, reliable and standardized protocols are urgently needed to enhance reproducibility among different laboratories and analytical platforms, facilitating a more widespread use in biomedical research. To achieve this goal, the use of dimensionless relative retention times (iRT), defined on the basis of peptide standard retention times (RT), has lately emerged as a powerful tool. The robustness, reproducibility and utility of this strategy were examined for the first time in a multicentric setting, involving 28 laboratories that included 24 of the Spanish network of proteomics laboratories (ProteoRed-ISCIII). According to the results obtained in this study, dimensionless retention time values (iRTs) demonstrated to be a useful tool for transferring and sharing peptide retention times across different chromatographic set-ups both intra- and inter-laboratories. iRT values also showed very low variability over long time periods. Furthermore, parallel quantitative analyses showed a high reproducibility despite the variety of experimental strategies used, either MRM (multiple reaction monitoring) or pseudoMRM, and the diversity of analytical platforms employed. BIOLOGICAL SIGNIFICANCE: From the very beginning of proteomics as an analytical science there has been a growing interest in developing standardized methods and experimental procedures in order to ensure the highest quality and reproducibility of the results. In this regard, the recent (2012) introduction of the dimensionless retention time concept has been a significant advance. In our multicentric (28 laboratories) study we explore the usefulness of this concept in the context of a targeted proteomics experiment, demonstrating that dimensionless retention time values is a useful tool for transferring and sharing peptide retention times across different chromatographic set-ups.

Apoptosis of Candida albicans during the Interaction with Murine Macrophages: Proteomics and Cell-Death Marker Monitoring.

Macrophages may induce fungal apoptosis to fight against C. albicans, as previously hypothesized by our group. To confirm this hypothesis, we analyzed proteins from C. albicans cells after 3 h of interaction with macrophages using two quantitative proteomic approaches. A total of 51 and 97 proteins were identified as differentially expressed by DIGE and iTRAQ, respectively. The proteins identified and quantified were different, with only seven in common, but classified in the same functional categories. The analyses of their functions indicated that an increase in the metabolism of amino acids and purine nucleotides were taking place, while the glycolysis and translation levels dropped after 3 h of interaction. Also, the response to oxidative stress and protein translation were reduced. In addition, seven substrates of metacaspase (Mca1) were identified (Cdc48, Fba1, Gpm1, Pmm1, Rct1, Ssb1, and Tal1) as decreased in abundance, plus 12 proteins previously described as related to apoptosis. Besides, the monitoring of apoptotic markers along 24 h of interaction (caspase-like activity, TUNEL assay, and the measurement of ROS and cell examination by transmission electron microscopy) revealed that apoptotic processes took place for 30% of the fungal cells, thus supporting the proteomic results and the hypothesis of macrophages killing C. albicans by apoptosis.

A comprehensive Candida albicans PeptideAtlas build enables deep proteome coverage.

To provide new and expanded proteome documentation of the opportunistically pathogen Candida albicans, we have developed new protein extraction and analysis routines to provide a new, extended and enhanced version of the C. albicans PeptideAtlas. Two new datasets, resulting from experiments consisting of exhaustive subcellular fractionations and different growing conditions, plus two additional datasets from previous experiments on the surface and the secreted proteomes, have been incorporated to increase the coverage of the proteome. High resolution precursor mass spectrometry (MS) and ion trap tandem MS spectra were analyzed with three different search engines using a database containing allele-specific sequences. This approach, novel for a large-scale C. albicans proteomics project, was combined with the post-processing and filtering implemented in the Trans Proteomic Pipeline consistently used in the PeptideAtlas project and resulted in 49,372 additional peptides (3-fold increase) and 1630 more proteins (1.6-fold increase) identified in the new C. albicans PeptideAtlas with respect to the previous build. A total of 71,310 peptides and 4174 canonical (minimal non-redundant set) proteins (4115 if one protein per pair of alleles is considered) were identified representing 66% of the 6218 proteins in the predicted proteome. This makes the new PeptideAtlas build the most comprehensive C. albicans proteomics resource available and the only large-scale one with detections of individual alleles.

Proteogenomics Dashboard for the Human Proteome Project.

dasHPPboard is a novel proteomics-based dashboard that collects and reports the experiments produced by the Spanish Human Proteome Project consortium (SpHPP) and aims to help HPP to map the entire human proteome. We have followed the strategy of analog genomics projects like the Encyclopedia of DNA Elements (ENCODE), which provides a vast amount of data on human cell lines experiments. The dashboard includes results of shotgun and selected reaction monitoring proteomics experiments, post-translational modifications information, as well as proteogenomics studies. We have also processed the transcriptomics data from the ENCODE and Human Body Map (HBM) projects for the identification of specific gene expression patterns in different cell lines and tissues, taking special interest in those genes having little proteomic evidence available (missing proteins). Peptide databases have been built using single nucleotide variants and novel junctions derived from RNA-Seq data that can be used in search engines for sample-specific protein identifications on the same cell lines or tissues. The dasHPPboard has been designed as a tool that can be used to share and visualize a combination of proteomic and transcriptomic data, providing at the same time easy access to resources for proteogenomics analyses. The dasHPPboard can be freely accessed at: http://sphppdashboard.cnb.csic.es.

Surfing transcriptomic landscapes. A step beyond the annotation of chromosome 16 proteome.

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC-MS/MS and gel/LC-MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study.

A Candida albicans PeptideAtlas.

Candida albicans public proteomic datasets, though growing steadily in the last few years, still have a very limited presence in online repositories. We report here the creation of a C. albicans PeptideAtlas comprising near 22,000 distinct peptides at a 0.24% False Discovery Rate (FDR) that account for over 2500 canonical proteins at a 1.2% FDR. Based on data from 16 experiments, we attained coverage of 41% of the C. albicans open reading frame sequences (ORFs) in the database used for the searches. This PeptideAtlas provides several useful features, including comprehensive protein and peptide-centered search capabilities and visualization tools that establish a solid basis for the study of basic biological mechanisms key to virulence and pathogenesis such as dimorphism, adherence, and apoptosis. Further, it is a valuable resource for the selection of candidate proteotypic peptides for targeted proteomic experiments via Selected Reaction Monitoring (SRM) or SWATH-MS. BIOLOGICAL SIGNIFICANCE: This C. albicans PeptideAtlas resolves the previous absence of fungal pathogens in the PeptideAtlas project. It represents the most extensive characterization of the proteome of this fungus that exists up to the current date, including evidence for uncharacterized ORFs. Through its web interface, PeptideAtlas supports the study of interesting proteins related to basic biological mechanisms key to virulence such as apoptosis, dimorphism and adherence. It also provides a valuable resource to select candidate proteotypic peptides for future (SRM) targeted proteomic experiments. This article is part of a Special Issue entitled: Trends in Microbial Proteomics.

Cell surface shaving of Candida albicans biofilms, hyphae, and yeast form cells.

We used a brief trypsin treatment followed by peptide separation and identification using nano-LC followed by off-line MS/MS to identify the surface proteins on live Candida albicans organisms growing in biofilms and planktonic yeast cells and hyphae. One hundred thirty-one proteins were present in at least two of the three replicates of one condition and distributed in various combinations of the three growth conditions. Both previously reported and new surface proteins were identified and these were distributed between covalently attached proteins and noncovalently attached proteins of the cell wall.

Proteopathogen, a protein database for studying Candida albicans--host interaction.

There exist, at present, public web repositories for management and storage of proteomic data and also fungi-specific databases. None of them, however, is focused to the specific research area of fungal pathogens and their interactions with the host, and contains proteomics experimental data. In this context, we present Proteopathogen, a database intended to compile proteomics experimental data and to facilitate storage and access to a range of data which spans proteomics workflows from description of the experimental approaches leading to sample preparation to MS settings and peptides supporting protein identification. Proteopathogen is currently focused on Candida albicans and its interaction with macrophages; however, data from experiments concerning different pathogenic fungi species and other mammalian cells may also be found suitable for inclusion into the database. Proteopathogen is publicly available at http://proteopathogen.dacya.ucm.es.