Microbial Informatics and Experimentation最新文献

Background: Helicobacter pylori HP0958 protein (FlgZ) prevents the rapid turnover of RpoN (σ(54)), a transcription factor required for expression of several flagellar genes in H. pylori. FlgZ possesses a zinc-ribbon domain (DUF164) that contains two conserved CXXC motifs which coordinate a zinc ion and is thought to interact with nucleic acids or proteins. Two conserved cysteine residues in FlgZ (Cys-202 and Cys-223) were replaced with serine to assess their significance in FlgZ function. After confirming the importance of the CXXC motifs in the DUF164 domain of FlgZ, the distribution of DUF164 proteins and RpoN homologs in other bacteria was examined to determine if a correlation existed for the concurrence of the two proteins.

Results: Levels of RpoN were greatly reduced in H. pylori strains that expressed the FlgZ(C202S) or FlgZ(C223S) variants. The FlgZ(C202S) variant, but not the FlgZ(C223S) variant, accumulated at levels similar to the wild-type protein. DUF164 proteins are not universally distributed and appear to be absent in several major bacterial taxa, including Cyanobacteria as well as Alpha-, Beta- and Gammaproteobacteria. With the exception of the Actinobacteria, members of which generally lack RpoN, genes encoding DUF164 proteins and RpoN are frequently found in the same genome. Interestingly, many of the DUF164 proteins in Actinobacteria and Bacteroidetes lack most or even all of the conserved cysteine residues.

Conclusions: These findings suggest the importance of the zinc-ribbon domain of FlgZ in protecting RpoN from turnover. Since many bacteria that possess a DUF164 protein also contain RpoN, DUF164 proteins may have roles in RpoN protection or function in other bacteria.

Background: The associations between bacteria and environment underlie their preferential interactions with given physical or chemical conditions. Microbial ecology aims at extracting conserved patterns of occurrence of bacterial taxa in relation to defined habitats and contexts.

Results: In the present report the NCBI nucleotide sequence database is used as dataset to extract information relative to the distribution of each of the 24 phyla of the bacteria superkingdom and of the Archaea. Over two and a half million records are filtered in their cross-association with each of 48 sets of keywords, defined to cover natural or artificial habitats, interactions with plant, animal or human hosts, and physical-chemical conditions. The results are processed showing: (a) how the different descriptors enrich or deplete the proportions at which the phyla occur in the total database; (b) in which order of abundance do the different keywords score for each phylum (preferred habitats or conditions), and to which extent are phyla clustered to few descriptors (specific) or spread across many (cosmopolitan); (c) which keywords individuate the communities ranking highest for diversity and evenness.

Conclusions: A number of cues emerge from the results, contributing to sharpen the picture on the functional systematic diversity of prokaryotes. Suggestions are given for a future automated service dedicated to refining and updating such kind of analyses via public bioinformatic engines.

The biochemical and physical factors controlling protein expression level and solubility in vivo remain incompletely characterized. To gain insight into the primary sequence features influencing these outcomes, we performed statistical analyses of results from the high-throughput protein-production pipeline of the Northeast Structural Genomics Consortium. Proteins expressed in E. coli and consistently purified were scored independently for expression and solubility levels. These parameters nonetheless show a very strong positive correlation. We used logistic regressions to determine whether they are systematically influenced by fractional amino acid composition or several bulk sequence parameters including hydrophobicity, sidechain entropy, electrostatic charge, and predicted backbone disorder. Decreasing hydrophobicity correlates with higher expression and solubility levels, but this correlation apparently derives solely from the beneficial effect of three charged amino acids, at least for bacterial proteins. In fact, the three most hydrophobic residues showed very different correlations with solubility level. Leu showed the strongest negative correlation among amino acids, while Ile showed a slightly positive correlation in most data segments. Several other amino acids also had unexpected effects. Notably, Arg correlated with decreased expression and, most surprisingly, solubility of bacterial proteins, an effect only partially attributable to rare codons. However, rare codons did significantly reduce expression despite use of a codon-enhanced strain. Additional analyses suggest that positively but not negatively charged amino acids may reduce translation efficiency in E. coli irrespective of codon usage. While some observed effects may reflect indirect evolutionary correlations, others may reflect basic physicochemical phenomena. We used these results to construct and validate predictors of expression and solubility levels and overall protein usability, and we propose new strategies to be explored for engineering improved protein expression and solubility.

Scientific discovery is incremental. The Merriam-Webster definition of 'Scientific Method' is "principles and procedures for the systematic pursuit of knowledge involving the recognition and formulation of a problem, the collection of data through observation and experiment, and the formulation and testing of hypotheses". Scientists are taught to be excellent observers, as observations create questions, which in turn generate hypotheses. After centuries of science we tend to assume that we have enough observations to drive science, and enable the small steps and giant leaps which lead to theories and subsequent testable hypotheses. One excellent example of this is Charles Darwin's Voyage of the Beagle, which was essentially an opportunistic survey of biodiversity. Today, obtaining funding for even small-scale surveys of life on Earth is difficult; but few argue the importance of the theory that was generated by Darwin from his observations made during this epic journey. However, these observations, even combined with the parallel work of Alfred Russell Wallace at around the same time have still not generated an indisputable 'law of biology'. The fact that evolution remains a 'theory', at least to the general public, suggests that surveys for new data need to be taken to a new level.

Background: The world's oceans are home to a diverse array of microbial life whose metabolic activity helps to drive the earth's biogeochemical cycles. Metagenomic analysis has revolutionized our access to these communities, providing a system-scale perspective of microbial community interactions. However, while metagenome sequencing can provide useful estimates of the relative change in abundance of specific genes and taxa between environments or over time, this does not investigate the relative changes in the production or consumption of different metabolites.

Results: We propose a methodology, Predicted Relative Metabolic Turnover (PRMT) that defines and enables exploration of metabolite-space inferred from the metagenome. Our analysis of metagenomic data from a time-series study in the Western English Channel demonstrated considerable correlations between predicted relative metabolic turnover and seasonal changes in abundance of measured environmental parameters as well as with observed seasonal changes in bacterial population structure.

Conclusions: The PRMT method was successfully applied to metagenomic data to explore the Western English Channel microbial metabalome to generate specific, biologically testable hypotheses. Generated hypotheses linked organic phosphate utilization to Gammaproteobactaria, Plantcomycetes, and Betaproteobacteria, chitin degradation to Actinomycetes, and potential small molecule biosynthesis pathways for Lentisphaerae, Chlamydiae, and Crenarchaeota. The PRMT method can be applied as a general tool for the analysis of additional metagenomic or transcriptomic datasets.

Background: Base-By-Base is a Java-based multiple sequence alignment editor. It is capable of working with protein and DNA molecules, but many of its unique features relate to the manipulation of the genomes of large DNA viruses such as poxviruses, herpesviruses, baculoviruses and asfarviruses (1-400 kb). The tool was built to serve as a platform for comparative genomics at the level of individual nucleotides.

Results: In version 2, BBB-v2, of Base-By-Base we have added a series of new features aimed at providing the bench virologist with a better platform to view, annotate and analyze these complex genomes. Although a poxvirus genome, for example, may be less than 200 kb, it probably encodes close to 200 proteins using multiple classes of promoters with frequent overlapping of promoters and coding sequences and even some overlapping of genes. The new features allow users to 1) add primer annotations or other data sets in batch mode, 2) export differences between sequences to other genome browsers, 3) compare multiple genomes at a single nucleotide level of detail, 4) create new alignments from subsets/subsequences of a very large master alignment and 5) allow display of summaries of deep RNA sequencing data sets on a genome sequence.

Conclusion: BBB-v2 significantly improves the ability of virologists to work with genome sequences and provides a platform with which they can use a multiple sequence alignment as the basis for their own editable documents. Also, a .bbb document, with a variety of annotations in addition to the basic coding regions, can be shared among collaborators or made available to an entire research community. The program is available via Virology.ca using Java Web Start and is platform independent; the Java 1.5 virtual machine is required.

Background: Pseudomonas aeruginosa is an important bacterial model due to its metabolic and pathogenic abilities, which allow it to interact and colonize a wide range of hosts, including plants and animals. In this work we compile and analyze the structure and organization of an experimentally supported regulatory network in this bacterium.

Results: The regulatory network consists of 690 genes and 1020 regulatory interactions between their products (12% of total genes: 54% sigma and 16% of transcription factors). This complex interplay makes the third largest regulatory network of those reported in bacteria. The entire network is enriched for activating interactions and, peculiarly, self-activation seems to occur more prominent for transcription factors (TFs), which contrasts with other biological networks where self-repression is dominant. The network contains a giant component of 650 genes organized into 11 hierarchies, encompassing important biological processes, such as, biofilms formation, production of exopolysaccharide alginate and several virulence factors, and of the so-called quorum sensing regulons.

Conclusions: The study of gene regulation in P. aeruginosa is biased towards pathogenesis and virulence processes, all of which are interconnected. The network shows power-law distribution -input degree -, and we identified the top ten global regulators, six two-element cycles, the longest paths have ten steps, six biological modules and the main motifs containing three and four elements. We think this work can provide insights for the design of further studies to cover the many gaps in knowledge of this important bacterial model, and for the design of systems strategies to combat this bacterium.