MultiFun, a Multifunctional Classification Scheme for Escherichia coli K-12 Gene Products

Role of the Putative Histidine Kinase BP1092 in Bordetella pertussis Virulence Regulation and Intracellular Survival

Bordetella pertussis persists inside host cells, and virulence factors are crucial for intracellular adaptation. The regulation of B. pertussis virulence factor transcription primarily occurs through the modulation of the two-component system (TCS) known as BvgAS. However, additional regulatory systems have emerged as potential contributors to virulence regulation. Here, we investigate the impact of BP1092, a putative TCS histidine kinase that shows increased levels after bacterial internalization by macrophages, on B. pertussis proteome adaptation under nonmodulating (Bvg+) and modulating (Bvg-) conditions. Using mass spectrometry, we compare B. pertussis wild-type (wt), a BP1092-deficient mutant (ΔBP1092), and a ΔBP1092 trans-complemented strain under both conditions. We find an altered abundance of 10 proteins, including five virulence factors. Specifically, under nonmodulating conditions, the mutant strain showed decreased levels of FhaB, FhaS, and Cya compared to the wt. Conversely, under modulating conditions, the mutant strain exhibited reduced levels of BvgA and BvgS compared to those of the wt. Functional assays further revealed that the deletion of BP1092 gene impaired B. pertussis ability to survive within human macrophage THP-1 cells. Taken together, our findings allow us to propose BP1092 as a novel player involved in the intricate regulation of B. pertussis virulence factors and thus in adaptation to the intracellular environment. The data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD041940.

Multiomics Study of Bacterial Growth Arrest in a Synthetic Biology Application

We investigated the scalability of a previously developed growth switch based on external control of RNA polymerase expression. Our results indicate that, in liter-scale bioreactors operating in fed-batch mode, growth-arrested Escherichia coli cells are able to convert glucose to glycerol at an increased yield. A multiomics quantification of the physiology of the cells shows that, apart from acetate production, few metabolic side effects occur. However, a number of specific responses to growth slow-down and growth arrest are launched at the transcriptional level. These notably include the downregulation of genes involved in growth-associated processes, such as amino acid and nucleotide metabolism and translation. Interestingly, the transcriptional responses are buffered at the proteome level, probably due to the strong decrease of the total mRNA concentration after the diminution of transcriptional activity and the absence of growth dilution of proteins. Growth arrest thus reduces the opportunities for dynamically adjusting the proteome composition, which poses constraints on the design of biotechnological production processes but may also avoid the initiation of deleterious stress responses.

MicroScope: an integrated platform for the annotation and exploration of microbial gene functions through genomic, pangenomic and metabolic comparative analysis

Large-scale genome sequencing and the increasingly massive use of high-throughput approaches produce a vast amount of new information that completely transforms our understanding of thousands of microbial species. However, despite the development of powerful bioinformatics approaches, full interpretation of the content of these genomes remains a difficult task. Launched in 2005, the MicroScope platform (https://www.genoscope.cns.fr/agc/microscope) has been under continuous development and provides analysis for prokaryotic genome projects together with metabolic network reconstruction and post-genomic experiments allowing users to improve the understanding of gene functions. Here we present new improvements of the MicroScope user interface for genome selection, navigation and expert gene annotation. Automatic functional annotation procedures of the platform have also been updated and we added several new tools for the functional annotation of genes and genomic regions. We finally focus on new tools and pipeline developed to perform comparative analyses on hundreds of genomes based on pangenome graphs. To date, MicroScope contains data for >11 800 microbial genomes, part of which are manually curated and maintained by microbiologists (>4500 personal accounts in September 2019). The platform enables collaborative work in a rich comparative genomic context and improves community-based curation efforts.

MicroScope-an integrated resource for community expertise of gene functions and comparative analysis of microbial genomic and metabolic data

The overwhelming list of new bacterial genomes becoming available on a daily basis makes accurate genome annotation an essential step that ultimately determines the relevance of thousands of genomes stored in public databanks. The MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Starting from the results of our syntactic, functional and relational annotation pipelines, MicroScope provides an integrated environment for the expert annotation and comparative analysis of prokaryotic genomes. It combines tools and graphical interfaces to analyze genomes and to perform the manual curation of gene function in a comparative genomics and metabolic context. In this article, we describe the free-of-charge MicroScope services for the annotation and analysis of microbial (meta)genomes, transcriptomic and re-sequencing data. Then, the functionalities of the platform are presented in a way providing practical guidance and help to the nonspecialists in bioinformatics. Newly integrated analysis tools (i.e. prediction of virulence and resistance genes in bacterial genomes) and original method recently developed (the pan-genome graph representation) are also described. Integrated environments such as MicroScope clearly contribute, through the user community, to help maintaining accurate resources.

Shotgun proteomic analysis of Bordetella parapertussis provides insights into the physiological response to iron starvation and potential new virulence determinants absent in Bordetella pertussis

Bordetella parapertussis is one of the pathogens that cause whooping cough. Even though its incidence has been rising in the last decades, this species remained poorly investigated. This study reports the first extensive proteome analysis of this bacterium. In an attempt to gain some insight into the infective phenotype, we evaluated the response of B. parapertussis to iron starvation, a critical stress the bacteria face during infection. Among other relevant findings, we observed that the adaptation to this condition involves significant changes in the abundance of two important virulence factors of this pathogen, namely, adenylate cyclase and the O-antigen. We further used the proteomic data to search for B. parapertussis proteins that are absent or classified as pseudogenes in the genome of Bordetella pertussis to unravel differences between both whooping cough causative agents. Among them, we identified proteins involved in stress resistance and virulence determinants that might help to explain the differences in the pathogenesis of these species and the lack of cross-protection of current acellular vaccines. Altogether, these results contribute to a better understanding of B. parapertussis biology and pathogenesis. SIGNIFICANCE: Whooping cough is a reemerging disease caused by both Bordetella pertussis and Bordetella parapertussis. Current vaccines fail to induce protection against B parapertussis and the incidence of this species has been rising over the years. The proteomic analysis of this study provided relevant insights into potential virulence determinants of this poorly-studied pathogen. It further identified proteins produced by B. parapertussis not present in B. pertussis, which might help to explain both the differences on their respective infectious process and the current vaccine failure. Altogether, the results of this study contribute to the better understanding of B. parapertussis pathogenesis and the eventual design of improved preventive strategies against whooping cough.

Forecasting cell fate during antibiotic exposure using stochastic gene expression

Antibiotic killing does not occur at a single, precise time for all cells within a population. Variability in time to death can be caused by stochastic expression of genes, resulting in differences in endogenous stress-resistance levels between individual cells in a population. Here we investigate whether single-cell differences in gene expression prior to antibiotic exposure are related to cell survival times after antibiotic exposure for a range of genes of diverse function. We quantified the time to death of single cells under antibiotic exposure in combination with expression of reporters. For some reporters, including genes involved in stress response and cellular processes like metabolism, the time to cell death had a strong relationship with the initial expression level of the genes. Our results highlight the single-cell level non-uniformity of antibiotic killing and also provide examples of key genes where cell-to-cell variation in expression is strongly linked to extended durations of antibiotic survival.

Exploring the transcriptome of luxI- and ΔainS mutants and the impact of N-3-oxo-hexanoyl-L- and N-3-hydroxy-decanoyl-L-homoserine lactones on biofilm formation in Aliivibrio salmonicida

Background

Bacterial communication through quorum sensing (QS) systems has been reported to be important in coordinating several traits such as biofilm formation. In Aliivibrio salmonicida two QS systems the LuxI/R and AinS/R, have been shown to be responsible for the production of eight acyl-homoserine lactones (AHLs) in a cell density dependent manner. We have previously demonstrated that inactivation of LitR, the master regulator of the QS system resulted in biofilm formation, similar to the biofilm formed by the AHL deficient mutant ΔainSluxI⁻. In this study, we aimed to investigate the global gene expression patterns of luxI and ainS autoinducer synthases mutants using transcriptomic profiling. In addition, we examined the influence of the different AHLs on biofilm formation.

Results

The transcriptome profiling of ΔainS and luxI⁻ mutants allowed us to identify genes and gene clusters regulated by QS in A. salmonicida. Relative to the wild type, the ΔainS and luxI⁻ mutants revealed 29 and 500 differentially expressed genes (DEGs), respectively. The functional analysis demonstrated that the most pronounced DEGs were involved in bacterial motility and chemotaxis, exopolysaccharide production, and surface structures related to adhesion. Inactivation of luxI, but not ainS genes resulted in wrinkled colony morphology. While inactivation of both genes (ΔainSluxI⁻) resulted in strains able to form wrinkled colonies and mushroom structured biofilm. Moreover, when the ΔainSluxI⁻ mutant was supplemented with N-3-oxo-hexanoyl-L-homoserine lactone (3OC6-HSL) or N-3-hydroxy-decanoyl-L-homoserine lactone (3OHC10-HSL), the biofilm did not develop. We also show that LuxI is needed for motility and for repression of EPS production, where repression of EPS is likely operated through the RpoQ-sigma factor.

Conclusion

These findings imply that the LuxI and AinS autoinducer synthases play a critical role in the regulation of biofilm formation, EPS production, and motility.

Tracing the phylogenetic history of the Crl regulon through the Bacteria and Archaea genomes

Background

Crl, identified for curli production, is a small transcription factor that stimulates the association of the σ^S factor (RpoS) with the RNA polymerase core through direct and specific interactions, increasing the transcription rate of genes during the transition from exponential to stationary phase at low temperatures, using indole as an effector molecule. The lack of a comprehensive collection of information on the Crl regulon makes it difficult to identify a dominant function of Crl and to generate any hypotheses concerning its taxonomical distribution in archaeal and bacterial organisms.

Results

In this work, based on a systematic literature review, we identified the first comprehensive dataset of 86 genes under the control of Crl in the bacterium Escherichia coli K-12; those genes correspond to 40% of the σ^S regulon in this bacterium. Based on an analysis of orthologs in 18 archaeal and 69 bacterial taxonomical divisions and using E. coli K-12 as a framework, we suggest three main events that resulted in this regulon’s actual form: (i) in a first step, rpoS, a gene widely distributed in bacteria and archaea cellular domains, was recruited to regulate genes involved in ancient metabolic processes, such as those associated with glycolysis and the tricarboxylic acid cycle; (ii) in a second step, the regulon recruited those genes involved in metabolic processes, which are mainly taxonomically constrained to Proteobacteria, with some secondary losses, such as those genes involved in responses to stress or starvation and cell adhesion, among others; and (iii) in a posterior step, Crl might have been recruited in Enterobacteriaceae; because its taxonomical pattern constrained to this bacterial order, however further analysis are necessary.

Conclusions

Therefore, we suggest that the regulon Crl is highly flexible for phenotypic adaptation, probably as consequence of the diverse growth environments associated with all organisms in which members of this regulatory network are present.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5619-z) contains supplementary material, which is available to authorized users.

Stochastic modelling reveals mechanisms of metabolic heterogeneity

Phenotypic variation is a hallmark of cellular physiology. Metabolic heterogeneity, in particular, underpins single-cell phenomena such as microbial drug tolerance and growth variability. Much research has focussed on transcriptomic and proteomic heterogeneity, yet it remains unclear if such variation permeates to the metabolic state of a cell. Here we propose a stochastic model to show that complex forms of metabolic heterogeneity emerge from fluctuations in enzyme expression and catalysis. The analysis predicts clonal populations to split into two or more metabolically distinct subpopulations. We reveal mechanisms not seen in deterministic models, in which enzymes with unimodal expression distributions lead to metabolites with a bimodal or multimodal distribution across the population. Based on published data, the results suggest that metabolite heterogeneity may be more pervasive than previously thought. Our work casts light on links between gene expression and metabolism, and provides a theory to probe the sources of metabolite heterogeneity.

Differential expression profiling of ΔlitR and ΔrpoQ mutants reveals insight into QS regulation of motility, adhesion and biofilm formation in Aliivibrio salmonicida

BACKGROUND

The coordination of group behaviors in bacteria is achieved by a cell-cell signaling process called quorum sensing (QS). QS is an intercellular communication system, which synchronously controls expression of a vast range of genes in response to changes in cell density and is mediated by autoinducers that act as extracellular signals. Aliivibrio salmonicida, the causative agent of cold-water vibrosis in marine aquacultures, uses QS to regulate several activities such as motility, biofilm formation, adhesion and rugose colony morphology. However, little is known about either genes or detailed mechanisms involved in the regulation of these phenotypes.

RESULTS

Differential expression profiling allowed us to define the genes involved in controlling phenotypes related to QS in A. salmonicida LFI1238. RNA sequencing data revealed that the number of expressed genes in A. salmonicida, ΔlitR and ΔrpoQ mutants were significantly altered due to changes in cell density. These included genes that were distributed among the 21 functional groups, mainly presented in cell envelope, cell processes, extrachromosomal/foreign DNA and transport-binding proteins functional groups. The comparative transcriptome of A. salmonicida wild-type at high cell density relative to low cell density revealed 1013 genes to be either up- or downregulated. Thirty-six downregulated genes were gene clusters encoding biosynthesis of the flagellar and chemotaxis genes. Additionally we identified significant expression for genes involved in acyl homoserine lactone (AHL) synthesis, adhesion and early colonization. The transcriptome profile of ΔrpoQ compared to the wild-type revealed 384 differensially expressed genes (DEGs) that allowed us to assign genes involved in regulating motility, adhesion and colony rugosity. Indicating the importance of RpoQ in controlling several QS related activities. Furthermore, the comparison of the transcriptome profiles of ΔlitR and ΔrpoQ mutants, exposed numerous overlapping DEGs that were essential for motility, exopolysaccharide production via syp operon and genes associated with tad operon.

CONCLUSION

Our findings indicate previously unexplained functional roles for LitR and RpoQ in regulation of different phenotypes related to QS. Our transcriptome data provide a better understanding of the regulation cascade of motility, wrinkling colony morphology and biofilm formation and will offer a major source for further research and analysis on this important field.

The EcoCyc Database

EcoCyc is a bioinformatics database available at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene product, metabolite, reaction, operon, and metabolic pathway. The database also includes information on E. coli gene essentiality and on nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc and can be executed via EcoCyc.org. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. This review outlines the data content of EcoCyc and of the procedures by which this content is generated.

A genome-wide screen of bacterial mutants that enhance dauer formation in C. elegans

Molecular pathways involved in dauer formation, an alternate larval stage that allows Caenorhabditis elegans to survive adverse environmental conditions during development, also modulate longevity and metabolism. The decision to proceed with reproductive development or undergo diapause depends on food abundance, population density, and temperature. In recent years, the chemical identities of pheromone signals that modulate dauer entry have been characterized. However, signals derived from bacteria, the major source of nutrients for C. elegans, remain poorly characterized. To systematically identify bacterial components that influence dauer formation and aging in C. elegans, we utilized the individual gene deletion mutants in E. coli (K12). We identified 56 diverse E. coli deletion mutants that enhance dauer formation in an insulin-like receptor mutant (daf-2) background. We describe the mechanism of action of a bacterial mutant cyaA, that is defective in the production of cyclic AMP, which extends lifespan and enhances dauer formation through the modulation of TGF-β (daf-7) signaling in C. elegans. Our results demonstrate the importance of bacterial components in influencing developmental decisions and lifespan in C. elegans. Furthermore, we demonstrate that C. elegans is a useful model to study bacterial-host interactions.

The EcoCyc Database

EcoCyc is a bioinformatics database available at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene, metabolite, reaction, operon, and metabolic pathway. The database also includes information on E. coli gene essentiality and on nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. This review provides a detailed description of the data content of EcoCyc and of the procedures by which this content is generated.

Annotation enrichment analysis: an alternative method for evaluating the functional properties of gene sets

Gene annotation databases (compendiums maintained by the scientific community that describe the biological functions performed by individual genes) are commonly used to evaluate the functional properties of experimentally derived gene sets. Overlap statistics, such as Fishers Exact test (FET), are often employed to assess these associations, but don't account for non-uniformity in the number of genes annotated to individual functions or the number of functions associated with individual genes. We find FET is strongly biased toward over-estimating overlap significance if a gene set has an unusually high number of annotations. To correct for these biases, we develop Annotation Enrichment Analysis (AEA), which properly accounts for the non-uniformity of annotations. We show that AEA is able to identify biologically meaningful functional enrichments that are obscured by numerous false-positive enrichment scores in FET, and we therefore suggest it be used to more accurately assess the biological properties of gene sets.

Array-based synthetic genetic screens to map bacterial pathways and functional networks in Escherichia coli

Cellular processes are carried out through a series of molecular interactions. Various experimental approaches can be used to investigate these functional relationships on a large-scale. Recently, the power of investigating biological systems from the perspective of genetic (gene-gene, or epistatic) interactions has been evidenced by the ability to elucidate novel functional relationships. Examples of functionally related genes include genes that buffer each other's function or impinge on the same biological process. Genetic interactions have traditionally been investigated in bacteria by combining pairs of mutations (for example, gene deletions) and assessing deviation of the phenotype of each double mutant from an expected neutral (or no interaction) phenotype. Fitness is a particularly convenient phenotype to measure: when the double mutant grows faster or slower than expected, the two mutated genes are said to show alleviating or aggravating interactions, respectively. The most commonly used neutral model assumes that the fitness of the double mutant is equal to the product of individual single mutant fitness. A striking genetic interaction is exemplified by the loss of two nonessential genes that buffer each other in performing an essential biological function: deleting only one of these genes produces no detectable fitness defect; however, loss of both genes simultaneously results in systems failure, leading to synthetic sickness or lethality. Systematic large-scale genetic interaction screens have been used to generate functional maps for model eukaryotic organisms, such as yeast, to describe the functional organization of gene products into pathways and protein complexes within a cell. They also reveal the modular arrangement and cross-talk of pathways and complexes within broader functional neighborhoods (Dixon et al. Annu Rev Genet 43:601-625, 2009). Here, we present a high-throughput quantitative Escherichia coli synthetic genetic array (eSGA) screening procedure, which we developed to systematically infer genetic interactions by scoring growth defects among large numbers of double mutants in a classic gram-negative bacterium. The eSGA method exploits the rapid colony growth, ease of genetic manipulation, and natural efficient genetic exchange via conjugation of laboratory E. coli strains. Replica pinning is used to grow and mate arrayed sets of single-gene mutant strains as well as to select double mutants en mass. Strain fitness, which is used as the eSGA readout, is quantified by the digital imaging of the plates and subsequent measuring and comparing single and double mutant colony sizes. While eSGA can be used to screen select mutants to probe the functions of individual genes; using eSGA more broadly to collect genetic interaction data for many combinations of genes can help reconstruct a functional interaction network to reveal novel links and components of biological pathways as well as unexpected connections between pathways. A variety of bacterial systems can be investigated, wherein the genes impinge on a essential biological process (e.g., cell wall assembly, ribosome biogenesis, chromosome replication) that are of interest from the perspective of drug development (Babu et al. Mol Biosyst 12:1439-1455, 2009). We also show how genetic interactions generated by high-throughput eSGA screens can be validated by manual small-scale genetic crosses and by genetic complementation and gene rescue experiments.

MicroScope: a platform for microbial genome annotation and comparative genomics

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone.Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc.

Long-range periodic patterns in microbial genomes indicate significant multi-scale chromosomal organization

Genome organization can be studied through analysis of chromosome position-dependent patterns in sequence-derived parameters. A comprehensive analysis of such patterns in prokaryotic sequences and genome-scale functional data has yet to be performed. We detected spatial patterns in sequence-derived parameters for 163 chromosomes occurring in 135 bacterial and 16 archaeal organisms using wavelet analysis. Pattern strength was found to correlate with organism-specific features such as genome size, overall GC content, and the occurrence of known motility and chromosomal binding proteins. Given additional functional data for Escherichia coli, we found significant correlations among chromosome position dependent patterns in numerous properties, some of which are consistent with previously experimentally identified chromosome macrodomains. These results demonstrate that the large-scale organization of most sequenced genomes is significantly nonrandom, and, moreover, that this organization is likely linked to genome size, nucleotide composition, and information transfer processes. Constraints on genome evolution and design are thus not solely dependent upon information content, but also upon an intricate multi-parameter, multi-length-scale organization of the chromosome.

Computational characterization of proteins

Computational characterization of proteins is a necessary first step in understanding the biologic role of a protein. The composite architecture of mammalian proteins makes the prediction of the biologic role rather difficult. Nevertheless, integration of many different prediction methods allows for a more accurate representation. Information on the 3D structure of a protein improves the reliability of predictions of many features. This article reviews existing methods used to characterize proteins and several tools that provide an integrated access to different types of information. The authors point out the increasing importance of structural constraints and an increasing need to integrate different approaches.

Bayesian decomposition analysis of bacterial phylogenomic profiles

BACKGROUND

The past two decades have seen the appearance of new infectious diseases and the reemergence of old diseases previously thought to be under control. At the same time, the effectiveness of the existing antibacterials is rapidly decreasing due to the spread of multidrug-resistant pathogens.

AIM

The aim of this study was to the identify candidate molecular targets (e.g. enzymes) within essential metabolic pathways specific to a significant subset of bacterial pathogens as the first step in the rational design of new antibacterial drugs.

METHODS

We constructed a dataset of phylogenomic profiles (vectors that encode the similarity, measured by BLAST scores, of a gene across many species) for a series of 31 pathogenic bacteria of interest with 1073 genes taken from the reference organisms Escherichia coli and Mycobacterium tuberculosis. We applied Bayesian Decomposition, a matrix decomposition algorithm, to identify functional metabolic units comprising overlapping sets of genes in this dataset.

RESULTS

Although no information on phylogeny was provided to the system, Bayesian Decomposition retrieved the known bacteria phylogenic relationships on the basis of the proteins necessary for survival. In addition, a set of genes required by all bacteria was identified, as well as components and enzymes specific to subsets of bacteria.

CONCLUSION

The use of phylogenomic profiles and Bayesian Decomposition provide important insights for the design of new antibacterial therapeutics.

Genome-wide identification of plant-upregulated genes of Erwinia chrysanthemi 3937 using a GFP-based IVET leaf array

A green fluorescent protein-based in vivo expression technology leaf array was used to identify genes in Erwinia chrysanthemi 3937 that were specifically upregulated in plants compared with growth in a laboratory culture medium. Of 10,000 E. chrysanthemi 3937 clones, 61 were confirmed as plant upregulated. On the basis of sequence similarity, these were recognized with probable functions in metabolism (20%), information transfer (15%), regulation (11%), transport (11%), cell processes (11%), and transposases (2%); the function for the remainder (30%) is unknown. Upregulated genes included transcriptional regulators, iron uptake systems, chemotaxis components, transporters, stress response genes, and several already known or new putative virulence factors. Ten independent mutants were constructed by insertions in these plant-upregulated genes and flanking genes. Two different virulence assays, local leaf maceration and systemic invasion in African violet, were used to evaluate these mutants. Among these, mutants of a purM homolog from Escherichia coli (purM::Tn5), and hrpB, hrcJ, and a hrpD homologs from the Erwinia carotovorum hrpA operon (hrpB::Tn5, hrcJ::Tn5, and hrpD::Tn5) exhibited reduced abilities to produce local and systemic maceration of the plant host. Mutants of rhiT from E. chrysanthemi (rhiT::Tn5), and an eutR homolog from Salmonella typhimurium (eutR::TnS) showed decreased ability to cause systemic inva sion on African violet. However, compared with the wild-type E. chrysanthemi 3937, these mutants exhibited no significant differences in local leaf maceration. The pheno type of hrpB::Tn5, hrcC::Tn5, and hrpD::Tn5 mutants further confirmed our previous findings that hrp genes are crucial virulence determinants in E. chrysanthemi 3937.

Classification schemes for protein structure and function

We examine the structural and functional classifications of the protein universe, providing an overview of the existing classification schemes, their features and inter-relationships. We argue that a unified scheme should be based on a natural classification approach and that more comparative analyses of the present schemes are required both to understand their limitations and to help delimit the number of known protein folds and their corresponding functional roles in cells.