Michael Wildpaner

Glycosylphosphatidylinositol Lipid Anchoring of Plant Proteins. Sensitive Prediction from Sequence- and Genome-Wide Studies for Arabidopsis and Rice

Posttranslational glycosylphosphatidylinositol (GPI) lipid anchoring is common not only for animal and fungal but also for plant proteins. The attachment of the GPI moiety to the carboxyl-terminus after proteolytic cleavage of a C-terminal propeptide is performed by the transamidase complex. Its four known subunits also have obvious full-length orthologs in the Arabidopsis and rice (Oryza sativa) genomes; thus, the mechanism of substrate protein processing appears similar for all eukaryotes. A learning set of plant proteins (substrates for the transamidase complex) has been collected both from the literature and plant sequence databases. We find that the plant GPI lipid anchor motif differs in minor aspects from the animal signal (e.g. the plant hydrophobic tail region can contain a higher fraction of aromatic residues). We have developed the “big-Π plant” program for prediction of compatibility of query protein C-termini with the plant GPI lipid anchor motif requirements. Validation tests show that the sensitivity for transamidase targets is approximately 94%, and the rate of false positive prediction is about 0.1%. Thus, the big-Π predictor can be applied as unsupervised genome annotation and target selection tool. The program is also suited for the design of modified protein constructs to test their GPI lipid anchoring capacity. The big-Π plant predictor Web server and lists of potential plant precursor proteins in Swiss-Prot, SPTrEMBL, Arabidopsis, and rice proteomes are available at http://mendel.imp.univie.ac.at/gpi/plants/gpi_plants.html. Arabidopsis and rice protein hits have been functionally classified. Several GPI lipid-anchored arabinogalactan-related proteins have been identified in rice.

MYRbase: analysis of genome-wide glycine myristoylation enlarges the functional spectrum of eukaryotic myristoylated proteins

We evaluated the evolutionary conservation of glycine myristoylation within eukaryotic sequences. Our large-scale cross-genome analyses, available as MYRbase, show that the functional spectrum of myristoylated proteins is currently largely underestimated. We give experimental evidence for in vitro myristoylation of selected predictions. Furthermore, we classify five membrane-attachment factors that occur most frequently in combination with, or even replacing, myristoyl anchors, as some protein family examples show.

ANNIE: integrated de novo protein sequence annotation

Function prediction of proteins with computational sequence analysis requires the use of dozens of prediction tools with a bewildering range of input and output formats. Each of these tools focuses on a narrow aspect and researchers are having difficulty obtaining an integrated picture. ANNIE is the result of years of close interaction between computational biologists and computer scientists and automates an essential part of this sequence analytic process. It brings together over 20 function prediction algorithms that have proven sufficiently reliable and indispensable in daily sequence analytic work and are meant to give scientists a quick overview of possible functional assignments of sequence segments in the query proteins. The results are displayed in an integrated manner using an innovative AJAX-based sequence viewer. ANNIE is available online at: http://annie.bii.a-star.edu.sg. This website is free and open to all users and there is no login requirement.

An agent-based simulation approach for the new product diffusion of a novel biomass fuel

Marketing activities support the market introduction of innovative goods or services by furthering their diffusion and, thus, their success. However, such activities are rather expensive. Managers must therefore decide which specific marketing activities to apply to which extent and/or to which target group at which point in time. In this paper, we introduce an agent-based simulation approach that supports decision-makers in these concerns. The practical applicability of our tool is illustrated by means of a case study of a novel, biomass-based fuel that will likely be introduced on the Austrian market within the next 5 years.

Application of a sensitive collection heuristic for very large protein families: Evolutionary relationship between adipose triglyceride lipase (ATGL) and classic mammalian lipases

BackgroundManually finding subtle yet statistically significant links to distantly related homologues becomes practically impossible for very populated protein families due to the sheer number of similarity searches to be invoked and analyzed. The unclear evolutionary relationship between classical mammalian lipases and the recently discovered human adipose triglyceride lipase (ATGL; a patatin family member) is an exemplary case for such a problem.ResultsWe describe an unsupervised, sensitive sequence segment collection heuristic suitable for assembling very large protein families. It is based on fan-like expanding, iterative database searches. To prevent inclusion of unrelated hits, additional criteria are introduced: minimal alignment length and overlap with starting sequence segments, finding starting sequences in reciprocal searches, automated filtering for compositional bias and repetitive patterns. This heuristic was implemented as FAMILYSEARCHER in the ANNIE sequence analysis environment and applied to search for protein links between the classical lipase family and the patatin-like group.ConclusionThe FAMILYSEARCHER is an efficient tool for tracing distant evolutionary relationships involving large protein families. Although classical lipases and ATGL have no obvious sequence similarity and differ with regard to fold and catalytic mechanism, homology links detected with FAMILYSEARCHER show that they are evolutionarily related. The conserved sequence parts can be narrowed down to an ancestral core module consisting of three β-strands, one α-helix and a turn containing the typical nucleophilic serine. Moreover, this ancestral module also appears in numerous enzymes with various substrate specificities, but that critically rely on nucleophilic attack mechanisms.

Reducing the haystack to find the needle: improved protein identification after fast elimination of non-interpretable peptide MS/MS spectra and noise reduction.

BackgroundTandem mass spectrometry (MS/MS) has become a standard method for identification of proteins extracted from biological samples but the huge number and the noise contamination of MS/MS spectra obstruct swift and reliable computer-aided interpretation. Typically, a minor fraction of the spectra per sample (most often, only a few %) and about 10% of the peaks per spectrum contribute to the final result if protein identification is not prevented by the noise at all.ResultsTwo fast preprocessing screens can substantially reduce the haystack of MS/MS data. (1) Simple sequence ladder rules remove spectra non-interpretable in peptide sequences. (2) Modified Fourier-transform-based criteria clear background in the remaining data. In average, only a remainder of 35% of the MS/MS spectra (each reduced in size by about one quarter) has to be handed over to the interpretation software for reliable protein identification essentially without loss of information, with a trend to improved sequence coverage and with proportional decrease of computer resource consumption.ConclusionsThe search for sequence ladders in tandem MS/MS spectra with subsequent noise suppression is a promising strategy to reduce the number of MS/MS spectra from electro-spray instruments and to enhance the reliability of protein matches. Supplementary material and the software are available from an accompanying WWW-site with the URL http://mendel.bii.a-star.edu.sg/mass-spectrometry/MSCleaner-2.0/.

Integrated Tools for Biomolecular Sequence-Based Function Prediction as Exemplified by the ANNOTATOR Software Environment

Given the amount of sequence data available today, in silico function prediction, which often includes detecting distant evolutionary relationships, requires sophisticated bioinformatic workflows. The algorithms behind these workflows exhibit complex data structures; they need the ability to spawn subtasks and tend to demand large amounts of resources. Performing sequence analytic tasks by manually invoking individual function prediction algorithms having to transform between differing input and output formats has become increasingly obsolete. After a period of linking individual predictors using ad hoc scripts, a number of integrated platforms are finally emerging. We present the ANNOTATOR software environment as an advanced example of such a platform.

Induction of Short Interspersed Nuclear Repeat- containing Transcripts in Epithelial Cells upon Infection with a Chicken Adenovirus

Chicken embryo lethal orphan adenovirus (CELO) is used as a vector for expression of exogenous genes in mammalian cells. Here, we analyzed transcriptional alterations in mouse epithelial host cells following infection with CELO using cDNA microarray analysis. Sequence data characterization revealed that a major portion of CELO-induced genes contained short interspersed nuclear elements of the B2 subclass (B2 SINEs). In fact, we could identify SINEs and other repetitive sequences as contributing significantly to the cDNAs used for microarray construction. Moreover, we found that the CELO protein Gam1 was able to mediate transcriptional activation of these B2 SINE-containing RNAs. We hypothesize that upregulation of B2-SINE-containing RNAs could be a novel contribution of Gam1 to CELO host cell infection.

PhyloDome--visualization of taxonomic distributions of domains occurring in eukaryote protein sequence sets.

The analysis of taxonomic distribution and lineage-specific variation of domains and domain combinations is an important step in the assessment of their functional roles and potential interoperability. In the study of eukaryote sequence sets with many multi-domain proteins, it can become laborious to evaluate the phylogenetic context of the many occurring domains and their mutual relationships. PhyloDome is an answer to that problem. It provides a fast overview on the taxonomic spreading and potential interrelation of domains that are either given as a list of names and PFAM/SMART accessions or derived from a user-defined set of sequences. This taxonomic distribution analysis can be helpful in protein function and interaction assignment as the comparative study of potential Hedgehog pathway members in C.elegans shows. An implementation of PhyloDome is accessible for public use as a WWW-Service at . Software components are available on request.