LocateP: Genome-scale subcellular-location predictor for bacterial proteins

Contains fulltext : 69477.pdf ( ) (Open Access)BACKGROUND: In the past decades, various protein subcellular-location (SCL) predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase) cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP. RESULTS: LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms current tools especially where the N-terminally anchored and the SPIase-cleaved secreted proteins are concerned. Overall, the accuracy of LocateP was always higher than 90%. LocateP was then used to predict the SCLs of all proteins encoded by completed Gram-positive bacterial genomes. The results are stored in the database LocateP-DB http://www.cmbi.ru.nl/locatep-db1. CONCLUSION: LocateP is by far the most accurate and detailed protein SCL predictor for Gram-positive bacteria currently available

Predicting cis-acting elements of Lactobacillus plantarum by comparative genomics with different taxonomic subgroups

Cis-acting elements in Lactobacillus plantarum were predicted by comparative analysis of the upstream regions of conserved genes and predicted transcriptional units (TUs) in different bacterial genomes. TUs were predicted for two species sets, with different evolutionary distances to L.plantarum. TUs were designated ‘cluster of orthologous transcriptional units’ (COT) when >50% of the genes were orthologous in different species. Conserved DNA sequences were detected in the upstream regions of different COTs. Subsequently, conserved motifs were used to scan upstream regions of all TUs. This method revealed 18 regulatory motifs only present in lactic acid bacteria (LAB). The 18 LAB-specific candidate regulatory motifs included 13 that were not described previously. These LAB-specific different motifs were found in front of genes encoding functions varying from cold shock proteins to RNA and DNA polymerases, and many unknown functions. The best-described LAB-specific motif found was the CopR-binding site, regulating expression of copper transport ATPases. Finally, all detected motifs were used to predict co-regulated TUs (regulons) for L.plantarum, and transcriptome profiling data were analyzed to provide regulon prediction validation. It is demonstrated that phylogenetic footprinting using different species sets can identify and distinguish between general regulatory motifs and LAB-specific regulatory motifs

Accelerating the reconstruction of genome-scale metabolic networks

BACKGROUND: The genomic information of a species allows for the genome-scale reconstruction of its metabolic capacity. Such a metabolic reconstruction gives support to metabolic engineering, but also to integrative bioinformatics and visualization. Sequence-based automatic reconstructions require extensive manual curation, which can be very time-consuming. Therefore, we present a method to accelerate the time-consuming process of network reconstruction for a query species. The method exploits the availability of well-curated metabolic networks and uses high-resolution predictions of gene equivalency between species, allowing the transfer of gene-reaction associations from curated networks. RESULTS: We have evaluated the method using Lactococcus lactis IL1403, for which a genome-scale metabolic network was published recently. We recovered most of the gene-reaction associations (i.e. 74 – 85%) which are incorporated in the published network. Moreover, we predicted over 200 additional genes to be associated to reactions, including genes with unknown function, genes for transporters and genes with specific metabolic reactions, which are good candidates for an extension to the previously published network. In a comparison of our developed method with the well-established approach Pathologic, we predicted 186 additional genes to be associated to reactions. We also predicted a relatively high number of complete conserved protein complexes, which are derived from curated metabolic networks, illustrating the potential predictive power of our method for protein complexes. CONCLUSION: We show that our methodology can be applied to accelerate the reconstruction of genome-scale metabolic networks by taking optimal advantage of existing, manually curated networks. As orthology detection is the first step in the method, only the translated open reading frames (ORFs) of a newly sequenced genome are necessary to reconstruct a metabolic network. When more manually curated metabolic networks will become available in the near future, the usefulness of our method in network prediction is likely to increase

Spectroscopic characterization of reaction centers of the (M)Y210W mutant of the photosynthetic bacterium Rhodobacter sphaeroides

The tyrosine-(M)210 of the reaction center of Rhodobacter sphaeroides 2.4.1 has been changed to a tryptophan using site-directed mutagenesis. The reaction center of this mutant has been characterized by low-temperature absorption and fluorescence spectroscopy, time-resolved sub-picosecond spectroscopy, and magnetic resonance spectroscopy. The charge separation process showed bi-exponential kinetics at room temperature, with a main time constant of 36 ps and an additional fast time constant of 5.1 ps. Temperature dependent fluorescence measurements predict that the lifetime of P* becomes 4–5 times slower at cryogenic temperatures. From EPR and absorbance-detected magnetic resonance (ADMR, LD-ADMR) we conclude that the dimeric structure of P is not significantly changed upon mutation. In contrast, the interaction of the accessory bacteriochlorophyll BA with its environment appears to be altered, possibly because of a change in its position

Energy migration in Rhodobacter sphaeroides mutants altered by mutagenesis of the peripheral LH2 complex or by removal of the core LH1 complex

AbstractThe photosynthetic apparatus of the purple bacterium Rhodobacter sphaeroides is organised so that light energy absorbed by the peripheral antenna (LH2) complexes migrates towards the core (LH1) complex, before being trapped by the reaction centre (RC). This migration and trapping process has been studied in mutants where the energy levels of the LH2 BChls have been raised by mutagenesis of the C-terminal aromatic residues (Fowler, G.J.S., Visschers, R.W., Grief, G.G., Van Grondelle, R. and Hunter, C.N. (1992) Nature 355, 848–850), and in a mutant which lacks the core complex. In the former case, the alterations to the LH2 complexes did not prevent efficient energy transfer to the LHI-RC complex, but fluorescence emission spectra indicated that the equilibrium of energy within the system was affected so that back transfer from the LH1-RC core is minimised. This mimics the situation found in some other bacteria such as Rhodopseudomonas acidophila and Rps. cryptolactis. In the mutant lacking LH1, energy is transferred from LH2 directly to the RC, despite the absence of the core antenna. Energy transfer efficiencies for carotenoids and LH2 to LH1 were measured for the blue-shifted LH2 mutants, and were found to be high (70%) in each case. These data, together with measurements of excitation annihilation as a function of incident excitation energy, were used to estimate the domain sizes for energy transfer in these mutants. In the LH2 mutants, domains of about 50 to 170 core BChls were found, depending on the type of mutation. One effect of the removal of LH1 appears to be the reorganisation of the peripheral LH2 antenna to form domains of at least 250 BChls

Comparative analyses imply that the enigmatic sigma factor 54 is a central controller of the bacterial exterior

Contains fulltext : 95738.pdf (publisher's version ) (Open Access)BACKGROUND: Sigma-54 is a central regulator in many pathogenic bacteria and has been linked to a multitude of cellular processes like nitrogen assimilation and important functional traits such as motility, virulence, and biofilm formation. Until now it has remained obscure whether these phenomena and the control by Sigma-54 share an underlying theme. RESULTS: We have uncovered the commonality by performing a range of comparative genome analyses. A) The presence of Sigma-54 and its associated activators was determined for all sequenced prokaryotes. We observed a phylum-dependent distribution that is suggestive of an evolutionary relationship between Sigma-54 and lipopolysaccharide and flagellar biosynthesis. B) All Sigma-54 activators were identified and annotated. The relation with phosphotransfer-mediated signaling (TCS and PTS) and the transport and assimilation of carboxylates and nitrogen containing metabolites was substantiated. C) The function annotations, that were represented within the genomic context of all genes encoding Sigma-54, its activators and its promoters, were analyzed for intra-phylum representation and inter-phylum conservation. Promoters were localized using a straightforward scoring strategy that was formulated to identify similar motifs. We found clear highly-represented and conserved genetic associations with genes that concern the transport and biosynthesis of the metabolic intermediates of exopolysaccharides, flagella, lipids, lipopolysaccharides, lipoproteins and peptidoglycan. CONCLUSION: Our analyses directly implicate Sigma-54 as a central player in the control over the processes that involve the physical interaction of an organism with its environment like in the colonization of a host (virulence) or the formation of biofilm

How Phosphotransferase System-Related Protein Phosphorylation Regulates Carbohydrate Metabolism in Bacteria

The phosphoenolpyruvate(PEP):carbohydrate phosphotransferase system (PTS) is found only in bacteria, where it catalyzes the transport and phosphorylation of numerous monosaccharides, disaccharides, amino sugars, polyols, and other sugar derivatives. To carry out its catalytic function in sugar transport and phosphorylation, the PTS uses PEP as an energy source and phosphoryl donor. The phosphoryl group of PEP is usually transferred via four distinct proteins (domains) to the transported sugar bound to the respective membrane component(s) (EIIC and EIID) of the PTS. The organization of the PTS as a four-step phosphoryl transfer system, in which all P derivatives exhibit similar energy (phosphorylation occurs at histidyl or cysteyl residues), is surprising, as a single protein (or domain) coupling energy transfer and sugar phosphorylation would be sufficient for PTS function. A possible explanation for the complexity of the PTS was provided by the discovery that the PTS also carries out numerous regulatory functions. Depending on their phosphorylation state, the four proteins (domains) forming the PTS phosphorylation cascade (EI, HPr, EIIA, and EIIB) can phosphorylate or interact with numerous non-PTS proteins and thereby regulate their activity. In addition, in certain bacteria, one of the PTS components (HPr) is phosphorylated by ATP at a seryl residue, which increases the complexity of PTS-mediated regulation. In this review, we try to summarize the known protein phosphorylation-related regulatory functions of the PTS. As we shall see, the PTS regulation network not only controls carbohydrate uptake and metabolism but also interferes with the utilization of nitrogen and phosphorus and the virulence of certain pathogens