Simon Barkow-Oesterreicher

Implementation and evaluation of relative and absolute quantification in shotgun proteomics with label-free methods.

Tandem mass spectrometry allows for fast protein identification in a complex sample. As mass spectrometers get faster, more sensitive and more accurate, methods were devised by many academic research groups and commercial suppliers that allow protein research also in quantitative respect. Since label-free methods are an attractive alternative to labeling approaches for proteomics researchers seeking for accurate quantitative results we evaluated several open-source analysis tools in terms of performance on two reference data sets, explicitly generated for this purpose. In this paper we present an implementation, T3PQ (Top 3 Protein Quantification), of the method suggested by Silva and colleagues for LC-MS(E) applications and we demonstrate its applicability to data generated on FT-ICR instruments acquiring in data dependent acquisition (DDA) mode. In order to validate this method and to show its usefulness also for absolute protein quantification, we generated a reference data set of a sample containing four different proteins with known concentrations. Furthermore, we compare three other label-free quantification methods using a complex biological sample spiked with a standard protein in defined concentrations. We evaluate the applicability of these methods and the quality of the results in terms of robustness and dynamic range of the spiked-in protein as well as other proteins also detected in the mixture. We discuss drawbacks of each method individually and consider crucial points for experimental designs. The source code of our implementation is available under the terms of the GNU GPLv3 and can be downloaded from sourceforge (http://fqms.svn.sourceforge.net/svnroot/fqms). A tarball containing the data used for the evaluation is available on the FGCZ web server (http://fgcz-data.uzh.ch/public/T3PQ.tgz).

Optimization of LTQ-Orbitrap Mass Spectrometer Parameters for the Identification of ADP-Ribosylation Sites

ADP-ribosylation of proteins alters their function or provides a scaffold for the recruitment of other proteins, thereby regulating several important cellular processes. Mono- or poly-ADP-ribosylation is catalyzed by different ADP-ribosyltransferases (ARTs) that have different subcellular localizations and modify different amino acid acceptor sites. However, our knowledge of ADP-ribosylated proteins and their acceptor amino acids is still limited due to the lack of suitable mass spectrometry (MS) tools. Here, we describe an MS approach for the detection of ADP-ribosylated peptides and identification of the ADP-ribose acceptor sites, combining higher-energy collisional dissociation (HCD) and electron-transfer dissociation (ETD) on an LTQ-Orbitrap mass spectrometer. The presence of diagnostic ions of ADP-ribose in the HCD spectra allowed us to detect putative ADP-ribosylated peptides to target in a second LC-MS/MS analysis. The combination of HCD with ETD fragmentation gave a more comprehensive coverage of ADP-ribosylation sites than that with HCD alone. We successfully identified different ADP-ribose acceptor sites on several in vitro modified proteins. The combination of optimized HCD and ETD methods may be applied to complex samples, allowing comprehensive identification of ADP-ribosylation acceptor sites.

Phosphoproteome profile of Fusarium graminearum grown in vitro under nonlimiting conditions

This study presents a high‐throughput proteomic analysis of phosphopeptides from Fusarium graminearum strain DAOM 233423 grown in vitro without nutritional limitation. Using a combination of strong cation exchange (SCX) and immobilized metal affinity chromatography (IMAC) followed by LC‐MS, we identified 2902 putative phosphopeptides with homologous matches to 1496 different proteins. Functional classification of the annotated protein set revealed that phosphopeptides from nuclear proteins with ATP‐binding function were the most abundant. There are indications that phosphorylation sites from well‐characterized phosphoproteins representing diverse biological processes are conserved in F. graminearum: sequences of three phosphopeptides from known phosphoproteins (transcription elongation factor 1β, acidic ribosomal proteins, and glycogen synthase) revealed phosphorylation site conservation.

Proteomic profiling of Cronobacter turicensis 3032, a food-borne opportunistic pathogen

Members of the genus Cronobacter are opportunistic pathogens for neonates and are often associated with contaminated milk powder formulas. At present little is known about the virulence mechanisms or the natural reservoir of these organisms. The proteome of Cronobacter turicensis 3032, which has recently caused two deaths, was mapped aiming at a better understanding of physiology and putative pathogenic traits of this clinical isolate. Our analyses of extracellular, surface‐associated and whole‐cell proteins by two complementary proteomics approaches, 1D‐SDS‐PAGE combined with LC‐ESI‐MS/MS and 2D‐LC‐MALDI‐TOF/TOF MS, lead to the identification of 832 proteins corresponding to a remarkable 19% of the theoretically expressed protein complement of C. turicensis. The majority of the identified proteins are involved in central metabolic pathways, translation, protein folding and stability. Several putative virulence factors, whose expressions were confirmed by phenotypic assays, could be identified: a macrophage infectivity potentiator involved in C. turicensis persistence in host cells, a superoxide dismutase protecting the pathogen against reactive oxygen species and an enterobactin‐receptor protein for the uptake of siderophore‐bound iron. Most interestingly, a chitinase and a metalloprotease that might act against insects and fungi but no casein hydrolysing enzymes were found, suggesting that there is an environmental natural habitat of C. turicensis 3032.

The extracellular proteome of two Bifidobacterium species reveals different adaptation strategies to low iron conditions

BackgroundBifidobacteria are among the first anaerobic bacteria colonizing the gut. Bifidobacteria require iron for growth and their iron-sequestration mechanisms are important for their fitness and possibly inhibit enteropathogens. Here we used combined genomic and proteomic analyses to characterize adaptations to low iron conditions of B. kashiwanohense PV20-2 and B. pseudolongum PV8-2, 2 strains isolated from the feces of iron-deficient African infants and selected for their high iron-sequestering ability.ResultsAnalyses of the genome contents revealed evolutionary adaptation to low iron conditions. A ferric and a ferrous iron operon encoding binding proteins and transporters were found in both strains. Remarkably, the ferric iron operon of B. pseudolongum PV8-2 is not found in other B. pseudolongum strains and likely acquired via horizontal gene transfer. The genome B. kashiwanohense PV20-2 harbors a unique region encoding genes putatively involved in siderophore production.Additionally, the secretomes of the two strains grown under low-iron conditions were analyzed using a combined genomic-proteomic approach. A ferric iron transporter was found in the secretome of B. pseudolongum PV8-2, while ferrous binding proteins were detected in the secretome of B. kashiwanohense PV20-2, suggesting different strategies to take up iron in the strains. In addition, proteins such as elongation factors, a glyceraldehyde-3-phosphate dehydrogenase, and the stress proteins GroEL and DnaK were identified in both secretomes. These proteins have been previously associated with adhesion of lactobacilli to epithelial cells.ConclusionAnalyses of the genome and secretome of B. kashiwanohense PV20-2 and B. pseudolongum PV8-2 revealed different adaptations to low iron conditions and identified extracellular proteins for iron transport. The identified extracellular proteins might be involved in competition for iron in the gastrointestinal tract.

FCC – An automated rule-based processing tool for life science data

BackgroundData processing in the bioinformatics field often involves the handling of diverse software programs in one workflow. The field is lacking a set of standards for file formats so that files have to be processed in different ways in order to make them compatible to different analysis programs. The problem is that mass spectrometry vendors at most provide only closed-source Windows libraries to programmatically access their proprietary binary formats. This prohibits the creation of an efficient and unified tool that fits all processing needs of the users. Therefore, researchers are spending a significant amount of time using GUI-based conversion and processing programs. Besides the time needed for manual usage, such programs also can show long running times for processing, because most of them make use of only a single CPU. In particular, algorithms to enhance data quality, e.g. peak picking or deconvolution of spectra, add waiting time for the users.ResultsTo automate these processing tasks and let them run continuously without user interaction, we developed the FGCZ Converter Control (FCC) at the Functional Genomics Center Zurich (FGCZ) core facility. The FCC is a rule-based system for automated file processing that reduces the operation of diverse programs to a single configuration task. Using filtering rules for raw data files, the parameters for all tasks can be custom-tailored to the needs of every single researcher and processing can run automatically and efficiently on any number of servers in parallel using all available CPU resources.ConclusionsFCC has been used intensively at FGCZ for processing more than hundred thousand mass spectrometry raw files so far. Since we know that many other research facilities have similar problems, we would like to report on our tool and the accompanying ideas for an efficient set-up for potential reuse.

B-Fabric: the Swiss Army Knife for life sciences

This paper demonstrates B-Fabric, an all-in-one solution for two major purposes in life sciences. On the one hand, it is a system for the integrated management of experimental data and scientific annotations. On the other hand, it is a system infrastructure supporting on-the fly coupling of user applications, and thus serving as extensible platform for fast-paced, cutting-edge, collaborative research.