Bioinformatics as a Tool for Assessing the Quality of Sub-Cellular Proteomic Strategies and Inferring Functions of Proteins: Plant Cell Wall Proteomics as a Test Case

Bioinformatics is used at three different steps of proteomic studies of sub-cellular compartments. First one is protein identification from mass spectrometry data. Second one is prediction of sub-cellular localization, and third one is the search of functional domains to predict the function of identified proteins in order to answer biological questions. The aim of the work was to get a new tool for improving the quality of proteomics of sub-cellular compartments. Starting from the analysis of problems found in databases, we designed a new Arabidopsis database named ProtAnnDB (http://www.polebio.scsv.ups-tlse.fr/ProtAnnDB/). It collects in one page predictions of sub-cellular localization and of functional domains made by available software. Using this database allows not only improvement of interpretation of proteomic data (top-down analysis), but also of procedures to isolate sub-cellular compartments (bottom-up quality control)

Evaluation of cell wall preparations for proteomics: a new procedure for purifying cell walls from Arabidopsis hypocotyls

The ultimate goal of proteomic analysis of a cell compartment should be the exhaustive identification of resident proteins; excluding proteins from other cell compartments. Plant cell walls possess specific difficulties. Several reported procedures to isolate cell walls for proteomic analyses led to the isolation of a high proportion (more than 50%) of predicted intracellular proteins. The rationales of several published procedures to isolate cell walls for proteomics were analyzed, with regard to the bioinformatic-predicted subcellular localization of the identified proteins. A new procedure was developed to prepare cell walls from etiolated hypocotyls of Arabidopsis thaliana. After salt extraction, a high proportion of proteins predicted to be secreted was released (73%), belonging to the same functional classes as proteins identified using previously described protocols. The new cell wall preparation described in this paper gives the lowest proportion of proteins predicted to be intracellular when compared to available protocols. The application of its principles should lead to a more realistic view of the cell wall proteome, at least for the weakly bound CWP extractable by salts. In addition, it offers a clean cell wall preparation for subsequent extraction of strongly bound CWP

Cell wall biogenesis of Arabidopsis thaliana elongating cells: transcriptomics complements proteomics

<p>Abstract</p> <p>Background</p> <p>Plant growth is a complex process involving cell division and elongation. <it>Arabidopsis thaliana </it>hypocotyls undergo a 100-fold length increase mainly by cell elongation. Cell enlargement implicates significant changes in the composition and structure of the cell wall. In order to understand cell wall biogenesis during cell elongation, mRNA profiling was made on half- (active elongation) and fully-grown (after growth arrest) etiolated hypocotyls.</p> <p>Results</p> <p>Transcriptomic analysis was focused on two sets of genes. The first set of 856 genes named cell wall genes (CWGs) included genes known to be involved in cell wall biogenesis. A significant proportion of them has detectable levels of transcripts (55.5%), suggesting that these processes are important throughout hypocotyl elongation and after growth arrest. Genes encoding proteins involved in substrate generation or in synthesis of polysaccharides, and extracellular proteins were found to have high transcript levels. A second set of 2927 genes labeled secretory pathway genes (SPGs) was studied to search for new genes encoding secreted proteins possibly involved in wall expansion. Based on transcript level, 433 genes were selected. Genes not known to be involved in cell elongation were found to have high levels of transcripts. Encoded proteins were proteases, protease inhibitors, proteins with interacting domains, and proteins involved in lipid metabolism. In addition, 125 of them encoded proteins with yet unknown function. Finally, comparison with results of a cell wall proteomic study on the same material revealed that 48 out of the 137 identified proteins were products of the genes having high or moderate level of transcripts. About 15% of the genes encoding proteins identified by proteomics showed levels of transcripts below background.</p> <p>Conclusion</p> <p>Members of known multigenic families involved in cell wall biogenesis, and new genes that might participate in cell elongation were identified. Significant differences were shown in the expression of such genes in half- and fully-grown hypocotyls. No clear correlation was found between the abundance of transcripts (transcriptomic data) and the presence of the proteins (proteomic data) demonstrating (i) the importance of post-transcriptional events for the regulation of genes during cell elongation and (ii) that transcriptomic and proteomic data are complementary.</p

Cell wall proteome of sugarcane stems: comparison of a destructive and a non-destructive extraction method showed differences in glycoside hydrolases and peroxidases

Abstract\ud \ud Background\ud Sugarcane has been used as the main crop for ethanol production for more than 40 years in Brazil. Recently, the production of bioethanol from bagasse and straw, also called second generation (2G) ethanol, became a reality with the first commercial plants started in the USA and Brazil. However, the industrial processes still need to be improved to generate a low cost fuel. One possibility is the remodeling of cell walls, by means of genetic improvement or transgenesis, in order to make the bagasse more accessible to hydrolytic enzymes. We aimed at characterizing the cell wall proteome of young sugarcane culms, to identify proteins involved in cell wall biogenesis. Proteins were extracted from the cell walls of 2-month-old culms using two protocols, non-destructive by vacuum infiltration vs destructive. The proteins were identified by mass spectrometry and bioinformatics.\ud \ud \ud Results\ud A predicted signal peptide was found in 84 different proteins, called cell wall proteins (CWPs). As expected, the non-destructive method showed a lower percentage of proteins predicted to be intracellular than the destructive one (33 % vs 44 %). About 19 % of CWPs were identified with both methods, whilst the infiltration protocol could lead to the identification of 75 % more CWPs. In both cases, the most populated protein functional classes were those of proteins related to lipid metabolism and oxido-reductases. Curiously, a single glycoside hydrolase (GH) was identified using the non-destructive method whereas 10 GHs were found with the destructive one. Quantitative data analysis allowed the identification of the most abundant proteins.\ud \ud \ud Conclusions\ud The results highlighted the importance of using different protocols to extract proteins from cell walls to expand the coverage of the cell wall proteome. Ten GHs were indicated as possible targets for further studies in order to obtain cell walls less recalcitrant to deconstruction. Therefore, this work contributed to two goals: enlarge the coverage of the sugarcane cell wall proteome, and provide target proteins that could be used in future research to facilitate 2G ethanol production

Cell wall proteins: a new insight through proteomics

Cell wall proteins are essential constituents of plant cell walls; they are involved in modifications of cell wall components, wall structure, signaling and interactions with plasma membrane proteins at the cell surface. The application of proteomic approaches to the cell wall compartment raises important questions: are there technical problems specific to cell wall proteomics? What kinds of proteins can be found in Arabidopsis walls? Are some of them unexpected? What sort of post-translational modifications have been characterized in cell wall proteins to date? The purpose of this review is to discuss the experimental results obtained to date using proteomics, as well as some of the new questions challenging future research