Moderate heat response involves proteins related to lipid biogenesis, cytoskeleton structure, sulfate assimilation, thiamine and hydrophobic amino acid biosynthesis, and nuclear transport. Photostasis is achieved through carbon metabolism adjustment, a decrease of photosystem II (PSII) abundance and an increase of PSI contribution to photosynthetic linear electron flow. Thioredoxin h may have a special role in this process in P. euphratica upon moderate heat exposure.

For more than 420 million years, plants, insects and their predators have co-evolved based on a chemical arms race including deployment of refined chemical defence systems by each player. Cyanogenic glucosides are produced by numerous plants and by some specialized insects and serve an important role as defence compounds in these intimate interactions. Burnet moth larvae are able to sequester cyanogenic glucosides from their food plant as well as to carry out de novo biosynthesis. Here we show that three genes (CYP405A2, CYP332A3 and UGT33A1) encode the entire biosynthetic pathway of cyanogenic glucosides in the Burnet moth Zygaena filipendulae. In both plants and insects, convergent evolution has led to two multifunctional P450 enzymes each catalysing unusual reactions and a glucosyl-transferase acting in sequence to catalyse cyanogenic glucoside formation. Thus, plants and insects have independently found a way to package a cyanide time bomb to fend off herbivores and predators.

Proteomic screening of strawberry (Fragaria ananassa) yielded a 58% success rate in protein identification in spite of the fact that no genomic sequence is available for this species. This was achieved by a combination of MALDI-MS/MS de novo sequencing of double-derivatized peptides and indel-tolerant searching against local protein databases built on both EST and full-length nucleotide sequences. The amino acid sequence of a strawberry allergen, homologous to the well-known major birch pollen allergen Bet v 1, was partially determined. This strawberry allergen, named Fra a 1 according to the nomenclature for allergen proteins, showed sequence identity of 54 and 77%, respectively, with corresponding allergens from birch and apple. Differential expression, as evaluated by 2-D DIGE, occurred in 10% of protein spots when red strawberries were compared to a colorless (white) strawberry mutant. White strawberries, known to be tolerated by individuals affected by allergy, were found to be virtually free from the strawberry allergen. Also several enzymes in the pathway for biosynthesis of flavonoids, to which the red color pelargonidin belongs, were down-regulated. This approach to assess differential protein expression without access to genomic sequence information can also be applied to other crop plants and phenotypic traits.

Proteomic technologies, such as yeast twohybrid, mass spectrometry (MS), protein/peptide arrays and fluorescence microscopy, yield multi-dimensional data sets, which are often quite large and either not published or published as supplementary information that is not easily searchable. Without a system in place for standardizing and sharing data, it is not fruitful for the biomedical community to contribute these types of data to centralized repositories. Even more difficult is the annotation and display of pertinent information in the context of the corresponding proteins. Wikipedia, an online encyclopedia that anyone can edit, has already proven quite successful1 and can be used as a model for sharing biological data. However, the need for experimental evidence, data standardization and ownership of data creates scientific obstacles. Here, we describe Human Proteinpedia (http://www.humanproteinpedia.org/) as a portal that overcomes many of these obstacles to provide an integrated view of the human proteome. Human Proteinpedia also allows users to contribute and edit proteomic data with two significant differences from Wikipedia: first, the contributor is expected to provide experimental evidence for the data annotated; and second, only the original contributor can edit their data. Human Proteinpedia's annotation system provides investigators with multiple options for contributing data including web forms and annotation servers. Although registration is required to contribute data, anyone can freely access the data in the repository. The web forms simplify submission through the use of pull-down menus for certain data fields and pop-up menus for standardized vocabulary terms. Distributed annotation servers using modified protein DAS (distributed annotation system) protocols developed by us (DAS protocols were originally developed for sharing mRNA and DNA data) permit contributing laboratories to maintain protein annotations locally. All protein annotations are visualized in the context of corresponding proteins in the Human Protein Reference Database (HPRD)3. Figure 1 shows tissue expression data for alpha-2-HS glycoprotein derived from three different types of experiments. Our unique effort differs significantly from existing repositories, such as PeptideAtlas and PRIDE5 in several respects. First, most proteomic repositories are restricted to one or two experimental platforms, whereas Human Proteinpedia can accommodate data from diverse platforms, including yeast two-hybrid screens, MS, peptide/protein arrays, immunohistochemistry, western blots, coimmunoprecipitation and fluorescence microscopy-type experiments. Second, Human Proteinpedia allows contributing laboratories to annotate data pertaining to six features of proteins (posttranslational modifications, tissue expression, cell line expression, subcellular localization, enzyme substrates and protein-protein interactions;). No existing repository currently permits annotation of all these features in proteins. Third, all data submitted to Human Proteinpedia...

We describe an approach to screen large sets of MALDI-MS mass spectra for protein isoforms separated on two-dimensional electrophoresis gels. Mass spectra are matched against each other by utilizing extracted peak mass lists and hierarchical clustering. The output is presented as dendrograms in which protein isoforms cluster together. Clustering could be applied to mass spectra from different sample sets, dates, and instruments, revealed similarities between mass spectra, and was a useful tool to highlight peptide peaks of interest for further investigation. Shared peak masses in a cluster could be identified and were used to create novel peak mass lists suitable for protein identification using peptide mass fingerprinting. Complex mass spectra consisting of more than one protein were deconvoluted using information from other mass spectra in the same cluster. The number of peptide peaks shared between mass spectra in a cluster was typically found to be larger than the number of peaks that matched to calculated peak masses in databases, thus modified peaks are probably among the shared peptides. Clustering increased the number of peaks associated with a given protein.