Claudia Fortes

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).

Directed shotgun proteomics guided by saturated RNA-seq identifies a complete expressed prokaryotic proteome

Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, we could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ∼90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor.

The longissimus thoracis muscle proteome in Alentejana bulls as affected by growth path

Beef production is an important economic activity. In Southern Europe there are two types of beef production systems based on growth paths: continuous (CG) versus discontinuous growth (DG). DG is a traditional system dependent on pasture; whereas in CG animals are supplemented on concentrate feed. We compare the protein abundance profiles of the longissimus thoracis (LT) muscle in CG and DG animals using label-free quantitative proteomics. Twenty three Alentejana male calves (9months-old, 239kg live-weight) were allocated to two feeding regimens. In CG (n=12) production system, animals were fed ad libitum on concentrates plus hay and slaughtered at 18months. In DG (n=11) production system, animals were fed ad libitum on hay from 9 to 15months of age and then the same diet provided to the CG group and slaughtered at 24months. The LT muscle was sampled and protein abundance profiles determined using label-free quantification. We identified 510 proteins, of which 26 showed differential abundance. Several proteins (e.g. Myozenin-2, glyoclythic enzymes and 14-3-3 protein zeta/delta) are proposed as indicators of a more intensive growth path. Myosin binding protein H had higher abundance in the DG group, suggesting it could be associated to discontinuous growth path.

Natural Genetic Variation Differentially Affects the Proteome and Transcriptome in Caenorhabditis elegans

Natural genetic variation is the raw material of evolution and influences disease development and progression. An important question is how this genetic variation translates into variation in protein abundance. To analyze the effects of the genetic background on gene and protein expression in the nematode Caenorhabditis elegans, we quantitatively compared the two genetically highly divergent wild-type strains N2 and CB4856. Gene expression was analyzed by microarray assays, and proteins were quantified using stable isotope labeling by amino acids in cell culture. Among all transcribed genes, we found 1,532 genes to be differentially transcribed between the two wild types. Of the total 3,238 quantified proteins, 129 proteins were significantly differentially expressed between N2 and CB4856. The differentially expressed proteins were enriched for genes that function in insulin-signaling and stress-response pathways, underlining strong divergence of these pathways in nematodes. The protein abundance of the two wild-type strains correlates more strongly than protein abundance versus transcript abundance within each wild type. Our findings indicate that in C. elegans only a fraction of the changes in protein abundance can be explained by the changes in mRNA abundance. These findings corroborate with the observations made across species.

The sheep (Ovis aries) muscle proteome: Decoding the mechanisms of tolerance to Seasonal Weight Loss using label-free proteomics

Seasonal Weight Loss (SWL) is one of the most pressing issues in animal production in the tropics and Mediterranean. This work aims to characterize muscle proteome changes as a consequence of SWL in meat producing sheep, using a label-free proteomics approach. We compare three breeds: the Australian Merino (SWL susceptible), the Damara (SWL tolerant) and the Dorper (SWL intermediate tolerance). We identified 668 proteins of the sheep proteome, 95 with differential regulation. Also we observe that the more vulnerable to SWL a breed is, the more differential abundance proteins we find. Protein binding was the most frequently altered molecular function identified. We suggest 6 putative markers for restricted nutritional conditions independently of breed: ferritin heavy-chain; immunoglobulin V lambda chain; transgelin; fatty acid synthase; glutathione S-transferase A2; dihydrodiol dehydrogenase 3-like. Moreover, we suggest as related to SWL tolerance: S100-A10 Serpin A3-5-like and Catalase, subject however to necessary validation assays. The identification of SWL-tolerance related proteins using proteomics will lead to increased stock productivity of relevant interest to animal production, particularly if identified at the muscle level, the tissue of economic importance in meat production. BIOLOGICAL SIGNIFICANCE Seasonal Weight Loss (SWL) is the most pressing issue in animal production in the tropics and the Mediterranean. To counter SWL, farmers often use animal breeds that have a natural ability to withstand pasture scarcity. Here we study the sheep muscle proteome at the muscle level, the tissue of economic importance in meat production. Furthermore, the identification of proteins that change their abundance in response to SWL using proteomics can contribute to increased stock productivity of relevant interest to animal production. We identified 668 proteins of the sheep proteome. We demonstrate that the following proteins are affected by restricted nutritional conditions: ferritin heavy chain; immunoglobulin V lambda chain; transgelin; fatty acid synthase; glutathione S-transferase A2; dihydrodiol dehydrogenase 3-like. Furthermore, S100-A10, Serpin A3-5-like and Catalase are proteins that changed their abundance in response to SWL. Nevertheless, it is important to highlight that Catalase values for the merino breed were close to significance and therefore catalase validation is of utmost importance.