Identification of nutrient-responsive Arabidopsis and rapeseed microRNAs by comprehensive real-time polymerase chain reaction profiling and small RNA sequencing.

in Plant Physiology (2009), 150(3), 1541-55

Comprehensive expression profiles of Arabidopsis (Arabidopsis thaliana) MIRNA genes and mature microRNAs (miRs) are currently not available. We established a quantitative real-time polymerase chain ... [more ▼]

Comprehensive expression profiles of Arabidopsis (Arabidopsis thaliana) MIRNA genes and mature microRNAs (miRs) are currently not available. We established a quantitative real-time polymerase chain reaction platform that allows rapid and sensitive quantification of 177 Arabidopsis primary miR transcripts (pri-miRs). The platform was used to detect phosphorus (P) or nitrogen (N) status-responsive pri-miR species. Several pri-miR169 species as well as pri-miR398a were found to be repressed during N limitation, whereas during P limitation, pri-miR778, pri-miR827, and pri-miR399 species were induced and pri-miR398a was repressed. The corresponding responses of the biologically active, mature miRs were confirmed using specific stem-loop reverse transcription primer quantitative polymerase chain reaction assays and small RNA sequencing. Interestingly, the latter approach also revealed high abundance of some miR star strands. Bioinformatic analysis of small RNA sequences with a modified miRDeep algorithm led to the identification of the novel P limitation-induced miR2111, which is encoded by two loci in the Arabidopsis genome. Furthermore, miR2111, miR169, a miR827-like sequence, and the abundances of several miR star strands were found to be strongly dependent on P or N status in rapeseed (Brassica napus) phloem sap, flagging them as candidate systemic signals. Taken together, these results reveal the existence of complex small RNA-based regulatory networks mediating plant adaptation to mineral nutrient availability. [less ▲]

Metabolomics- and proteomics-assisted genome annotation and analysis of the draft metabolic network of Chlamydomonas reinhardtii.

in Genetics (2008), 179(1), 157-66

We present an integrated analysis of the molecular repertoire of Chlamydomonas reinhardtii under reference conditions. Bioinformatics annotation methods combined with GCxGC/MS-based metabolomics and LC/MS ... [more ▼]

We present an integrated analysis of the molecular repertoire of Chlamydomonas reinhardtii under reference conditions. Bioinformatics annotation methods combined with GCxGC/MS-based metabolomics and LC/MS-based shotgun proteomics profiling technologies have been applied to characterize abundant proteins and metabolites, resulting in the detection of 1069 proteins and 159 metabolites. Of the measured proteins, 204 currently do not have EST sequence support; thus a significant portion of the proteomics-detected proteins provide evidence for the validity of in silico gene models. Furthermore, the generated peptide data lend support to the validity of a number of proteins currently in the proposed model stage. By integrating genomic annotation information with experimentally identified metabolites and proteins, we constructed a draft metabolic network for Chlamydomonas. Computational metabolic modeling allowed an identification of missing enzymatic links. Some experimentally detected metabolites are not producible by the currently known and annotated enzyme set, thus suggesting entry points for further targeted gene discovery or biochemical pathway research. All data sets are made available as supplementary material as well as web-accessible databases and within the functional context via the Chlamydomonas-adapted MapMan annotation platform. Information of identified peptides is also available directly via the JGI-Chlamydomonas genomic resource database (http://genome.jgi-psf.org/Chlre3/Chlre3.home.html). [less ▲]

Docking without docking: ISEARCH--prediction of interactions using known interfaces.

in Proteins (2007), 69(4), 839-44

The increasing number of solved protein structures provides a solid number of interfaces, if protein-protein interactions, domain-domain contacts, and contacts between biological units are taken into ... [more ▼]

The increasing number of solved protein structures provides a solid number of interfaces, if protein-protein interactions, domain-domain contacts, and contacts between biological units are taken into account. An interface library gives us the opportunity to identify surface regions on a target molecule that are similar by local structure and residue composition. If both unbound components of a possible protein complex exhibit structural similarities to a known interface, the unbound structures can be superposed onto the known interfaces. The approach is accompanied by two mathematical problems. Protein surfaces have to be quickly screened by thousands of patches, and similarity has to be evaluated by a suitable scoring scheme. The used algorithm (NeedleHaystack) identifies similar patches within minutes. Structurally related sites are recognized even if only parts of the template patches are structurally related to the interface region. A successful prediction of the protein complex depends on a suitable template of the library. However, the performed tests indicate that interaction sites are identified even if the similarity is very low. The approach complements existing ab initio methods and provides valuable results on standard benchmark sets. [less ▲]

ZIB Structure Prediction Pipeline: Composing a Complex Biological Workflow through Web Services

in Nagel, Wolfgang E.; Walter, Wolfgang V.; Lehner, Wolfgang (Eds.) Euro-Par 2006 Parallel Processing (2006)

In life sciences, scientists are confronted with an exponential growth of biological data, especially in the genomics and proteomics area. The efficient management and use of these data, and its ... [more ▼]

In life sciences, scientists are confronted with an exponential growth of biological data, especially in the genomics and proteomics area. The efficient management and use of these data, and its transformation into knowledge are basic requirements for biological research. Therefore, integration of diverse applications and data from geographically distributed computing resources will become a major issue. We will present the status of our efforts for the realization of an automated protein prediction pipeline as an example for a complex biological workflow scenario in a Grid environment based on Web services. This case study demonstrates the ability of an easy orchestration of complex biological workflows based on Web services as building blocks and Triana as workflow engine. [less ▲]

Connectivity independent protein-structure alignment: a hierarchical approach.

in BMC Bioinformatics (2006), 7

BACKGROUND: Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. In the last decade several methods for structure alignment were introduced, but most ... [more ▼]

BACKGROUND: Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. In the last decade several methods for structure alignment were introduced, but most of them ignore that structurally similar proteins can share the same spatial arrangement of secondary structure elements (SSE) but differ in the underlying polypeptide chain connectivity (non-sequential SSE connectivity). RESULTS: We perform protein-structure alignment using a two-level hierarchical approach implemented in the program GANGSTA. On the first level, pair contacts and relative orientations between SSEs (i.e. alpha-helices and beta-strands) are maximized with a genetic algorithm (GA). On the second level residue pair contacts from the best SSE alignments are optimized. We have tested the method on visually optimized structure alignments of protein pairs (pairwise mode) and for database scans. For a given protein structure, our method is able to detect significant structural similarity of functionally important folds with non-sequential SSE connectivity. The performance for structure alignments with strictly sequential SSE connectivity is comparable to that of other structure alignment methods. CONCLUSION: As demonstrated for several applications, GANGSTA finds meaningful protein-structure alignments independent of the SSE connectivity. GANGSTA is able to detect structural similarity of protein folds that are assigned to different superfamilies but nevertheless possess similar structures and perform related functions, even if these proteins differ in SSE connectivity. [less ▲]