Structure and function of cytidine monophosphate kinase from Yersinia pseudotuberculosis, essential for virulence but not for survival.

The need for new antibiotics has become pressing in light of the emergence of antibiotic-resistant strains of human pathogens. Yersinia pestis, the causative agent of plague, is a public health threat and also an agent of concern in biodefence. It is a recently emerged clonal derivative of the enteric pathogen Yersinia pseudotuberculosis. Previously, we developed a bioinformatic approach to identify proteins that may be suitable targets for antimicrobial therapy and in particular for the treatment of plague. One such target was cytidine monophosphate (CMP) kinase, which is an essential gene in some organisms. Previously, we had thought CMP kinase was essential for Y. pseudotuberculosis, but by modification of the mutagenesis approach, we report here the production and characterization of a Δcmk mutant. The isogenic mutant had a growth defect relative to the parental strain, and was highly attenuated in mice. We have also elucidated the structure of the CMP kinase to 2.32 Å, and identified three key residues in the active site that are essential for activity of the enzyme. These findings will have implications for the development of novel CMP kinase inhibitors for therapeutic use.

Yersinia pseudotuberculosis mntH functions in intracellular manganese accumulation, which is essential for virulence and survival in cells expressing functional Nramp1.

Manganese has an important yet undefined role in the virulence of many bacterial pathogens. In this study we confirm that a null mutation in Yersinia pseudotuberculosis mntH reduces intracellular manganese accumulation. An mntH mutant was susceptible to killing by reactive oxygen species when grown under manganese-limited conditions. The mntH mutant was defective in survival and growth in macrophages expressing functional Nramp1, but in macrophages deficient in Nramp the bacteria were able to survive and replicate. In Galleria mellonella, the mntH mutant was attenuated. Taken together, these data suggest a role for manganese in Y. pseudotuberculosis during macrophage intracellular survival, protecting the bacteria from the antimicrobial products released during the respiratory burst.

Predicting conserved essential genes in bacteria: in silico identification of putative drug targets.

Many genes have been listed as putatively essential for bacterial viability in the Database of Essential Genomes (DEG), although few have been experimentally validated. By prioritising targets according to the criteria suggested by the Research and Training in Tropical Diseases (TDR) Targets database, we have developed a modified down-selection tool to identify essential genes conserved across diverse genera. Using this approach we identified 52 proteins conserved to 7 or more of the 14 genomes in DEG. We confirmed the validity of the down-selection by attempting to make mutants of 8 of these targets in a model organism, Yersinia pseudotuberculosis, which is not closely related to any of the bacteria in DEG. Mutants were recovered for only one of the 8 targets, suggesting that the other 7 were essential in Y. pseudotuberculosis, an impressive success rate compared to other approaches of identification for such targets. Identification of essential proteins common in diverse bacterial genera can then be used to facilitate the selection of effective targets for novel broad-spectrum antibiotics.

Steps toward broad-spectrum therapeutics: discovering virulence-associated genes present in diverse human pathogens.

BACKGROUND: New and improved antimicrobial countermeasures are urgently needed to counteract increased resistance to existing antimicrobial treatments and to combat currently untreatable or new emerging infectious diseases. We demonstrate that computational comparative genomics, together with experimental screening, can identify potential generic (i.e., conserved across multiple pathogen species) and novel virulence-associated genes that may serve as targets for broad-spectrum countermeasures. RESULTS: Using phylogenetic profiles of protein clusters from completed microbial genome sequences, we identified seventeen protein candidates that are common to diverse human pathogens and absent or uncommon in non-pathogens. Mutants of 13 of these candidates were successfully generated in Yersinia pseudotuberculosis and the potential role of the proteins in virulence was assayed in an animal model. Six candidate proteins are suggested to be involved in the virulence of Y. pseudotuberculosis, none of which have previously been implicated in the virulence of Y. pseudotuberculosis and three have no record of involvement in the virulence of any bacteria. CONCLUSION: This work demonstrates a strategy for the identification of potential virulence factors that are conserved across a number of human pathogenic bacterial species, confirming the usefulness of this tool.

A Burkholderia pseudomallei protein microarray reveals serodiagnostic and cross-reactive antigens.

Understanding the way in which the immune system responds to infection is central to the development of vaccines and many diagnostics. To provide insight into this area, we fabricated a protein microarray containing 1,205 Burkholderia pseudomallei proteins, probed it with 88 melioidosis patient sera, and identified 170 reactive antigens. This subset of antigens was printed on a smaller array and probed with a collection of 747 individual sera derived from 10 patient groups including melioidosis patients from Northeast Thailand and Singapore, patients with different infections, healthy individuals from the USA, and from endemic and nonendemic regions of Thailand. We identified 49 antigens that are significantly more reactive in melioidosis patients than healthy people and patients with other types of bacterial infections. We also identified 59 cross-reactive antigens that are equally reactive among all groups, including healthy controls from the USA. Using these results we were able to devise a test that can classify melioidosis positive and negative individuals with sensitivity and specificity of 95% and 83%, respectively, a significant improvement over currently available diagnostic assays. Half of the reactive antigens contained a predicted signal peptide sequence and were classified as outer membrane, surface structures or secreted molecules, and an additional 20% were associated with pathogenicity, adaptation or chaperones. These results show that microarrays allow a more comprehensive analysis of the immune response on an antigen-specific, patient-specific, and population-specific basis, can identify serodiagnostic antigens, and contribute to a more detailed understanding of immunogenicity to this pathogen.

Proteins accessible to immune surveillance show significant T-cell epitope depletion: Implications for vaccine design.

T cell activation is the final step in a complex pathway through which pathogen-derived peptide fragments can elicit an immune response. For it to occur, peptides must form stable complexes with Major Histocompatibility Complex (MHC) molecules and be presented on the cell surface. Computational predictors of MHC binding are often used within in silico vaccine design pathways. We have previously shown that, paradoxically, most bacterial proteins known experimentally to elicit an immune response in disease models are depleted in peptides predicted to bind to human MHC alleles. The results presented here, derived using software proven through benchmarking to be the most accurate currently available, show that vaccine antigens contain fewer predicted MHC-binding peptides than control bacterial proteins from almost all subcellular locations with the exception of cell wall and some cytoplasmic proteins. This effect is too large to be explained from the undoubted lack of precision of the software or from the amino acid composition of the antigens. Instead, we propose that pathogens have evolved under the influence of the host immune system so that surface proteins are depleted in potential MHC-binding peptides, and suggest that identification of a protein likely to contain a single immuno-dominant epitope is likely to be a productive strategy for vaccine design.

Galleria mellonella as an alternative infection model for Yersinia pseudotuberculosis.

We report that larvae of the wax moth (Galleria mellonella) are susceptible to infection with the human enteropathogen Yersinia pseudotuberculosis at 37 degrees C. Confocal microscopy demonstrated that in the initial stages of infection the bacteria were taken up into haemocytes. To evaluate the utility of this model for screening Y. pseudotuberculosis mutants we constructed and tested a superoxide dismutase C (sodC) mutant. This mutant showed increased susceptibility to superoxide, a key mechanism of killing in insect haemocytes and mammalian phagocytes. It showed reduced virulence in the murine yersiniosis infection model and in contrast to the wild-type strain IP32953 was unable to kill G. mellonella. The complemented mutant regained all phenotypic properties associated with SodC, confirming the important role of this metalloenzyme in two Y. pseudotuberculosis infection models.

From protein microarrays to diagnostic antigen discovery: a study of the pathogen Francisella tularensis.

MOTIVATION: An important application of protein microarray data analysis is identifying a serodiagnostic antigen set that can reliably detect patterns and classify antigen expression profiles. This work addresses this problem using antibody responses to protein markers measured by a novel high-throughput microarray technology. The findings from this study have direct relevance to rapid, broad-based diagnostic and vaccine development. RESULTS: Protein microarray chips are probed with sera from individuals infected with the bacteria Francisella tularensis, a category A biodefense pathogen. A two-step approach to the diagnostic process is presented (1) feature (antigen) selection and (2) classification using antigen response measurements obtained from F.tularensis microarrays (244 antigens, 46 infected and 54 healthy human sera measurements). To select antigens, a ranking scheme based on the identification of significant immune responses and differential expression analysis is described. Classification methods including k-nearest neighbors, support vector machines (SVM) and k-Means clustering are applied to training data using selected antigen sets of various sizes. SVM based models yield prediction accuracy rates in the range of approximately 90% on validation data, when antigen set sizes are between 25 and 50. These results strongly indicate that the top-ranked antigens can be considered high-priority candidates for diagnostic development. AVAILABILITY: All software programs are written in R and available at http://www.igb.uci.edu/index.php?page=tools and at http://www.r-project.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The identification and evaluation of ATP binding cassette systems in the intracellular bacterium Francisella tularensis.

Francisella tularensis is a facultative intracellular bacterium responsible for the disease tularemia. Analysis of the fully sequenced genome of the virulent F. tularensis strain SCHU S4 has led to the identification of twenty ATP binding cassette (ABC) systems, of which five appear to be non-functional. The fifteen complete systems comprise three importers, five exporters, four systems involved in non-transport processes, and three systems of unknown or ill-defined function. The number and classification of the ABC systems in F. tularensis is similar to that observed in other intracellular bacteria, indicating that some of these systems may be important for the intracellular lifestyle of these organisms. Among the ABC systems identified in the genome are systems that may be involved in the virulence of F. tularensis SCHU S4. Six ABC system proteins were evaluated as candidate vaccine antigens against tularemia, although none provided significant protection against F. tularensis. However, a greater understanding of these systems may lead to the development of countermeasures against F. tularensis.

The complete genome sequence of Francisella tularensis, the causative agent of tularemia.

Francisella tularensis is one of the most infectious human pathogens known. In the past, both the former Soviet Union and the US had programs to develop weapons containing the bacterium. We report the complete genome sequence of a highly virulent isolate of F. tularensis (1,892,819 bp). The sequence uncovers previously uncharacterized genes encoding type IV pili, a surface polysaccharide and iron-acquisition systems. Several virulence-associated genes were located in a putative pathogenicity island, which was duplicated in the genome. More than 10% of the putative coding sequences contained insertion-deletion or substitution mutations and seemed to be deteriorating. The genome is rich in IS elements, including IS630 Tc-1 mariner family transposons, which are not expected in a prokaryote. We used a computational method for predicting metabolic pathways and found an unexpectedly high proportion of disrupted pathways, explaining the fastidious nutritional requirements of the bacterium. The loss of biosynthetic pathways indicates that F. tularensis is an obligate host-dependent bacterium in its natural life cycle. Our results have implications for our understanding of how highly virulent human pathogens evolve and will expedite strategies to combat them.

Analysis of known bacterial protein vaccine antigens reveals biased physical properties and amino acid composition.

Many vaccines have been developed from live attenuated forms of bacterial pathogens or from killed bacterial cells. However, an increased awareness of the potential for transient side-effects following vaccination has prompted an increased emphasis on the use of sub-unit vaccines, rather than those based on whole bacterial cells. The identification of vaccine sub-units is often a lengthy process and bioinformatics approaches have recently been used to identify candidate protein vaccine antigens. Such methods ultimately offer the promise of a more rapid advance towards preclinical studies with vaccines. We have compared the properties of known bacterial vaccine antigens against randomly selected proteins and identified differences in the make-up of these two groups. A computer algorithm that exploits these differences allows the identification of potential vaccine antigen candidates from pathogenic bacteria on the basis of their amino acid composition, a property inherently associated with sub-cellular location.