Elucidation of trophic interactions in an unusual single-cell nitrogen-fixing symbiosis using metabolic modeling

Marine nitrogen-fixing microorganisms are an important source of fixed nitrogen in oceanic ecosystems. The colonial cyanobacterium Trichodesmium and diatom symbionts were thought to be the primary contributors to oceanic N₂ fixation until the discovery of the unusual uncultivated symbiotic cyanobacterium UCYN-A (Candidatus Atelocyanobacterium thalassa). UCYN-A has atypical metabolic characteristics lacking the oxygen-evolving photosystem II, the tricarboxylic acid cycle, the carbon-fixation enzyme RuBisCo and de novo biosynthetic pathways for a number of amino acids and nucleotides. Therefore, it is obligately symbiotic with its single-celled haptophyte algal host. UCYN-A receives fixed carbon from its host and returns fixed nitrogen, but further insights into this symbiosis are precluded by both UCYN-A and its host being uncultured. In order to investigate how this syntrophy is coordinated, we reconstructed bottom-up genome-scale metabolic models of UCYN-A and its algal partner to explore possible trophic scenarios, focusing on nitrogen fixation and biomass synthesis. Since both partners are uncultivated and only the genome sequence of UCYN-A is available, we used the phylogenetically related Chrysochromulina tobin as a proxy for the host. Through the use of flux balance analysis (FBA), we determined the minimal set of metabolites and biochemical functions that must be shared between the two organisms to ensure viability and growth. We quantitatively investigated the metabolic characteristics that facilitate daytime N₂ fixation in UCYN-A and possible oxygen-scavenging mechanisms needed to create an anaerobic environment to allow nitrogenase to function. This is the first application of an FBA framework to examine the tight metabolic coupling between uncultivated microbes in marine symbiotic communities and provides a roadmap for future efforts focusing on such specialized systems.     

Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum

Background  

In silico genome-scale metabolic models enable the analysis of the characteristics of metabolic systems of organisms. In this study, we reconstructed a genome-scale metabolic model of Corynebacterium glutamicum on the basis of genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA), and the results of FBA were validated using data from culture experiments performed at different oxygen uptake rates.     

Identification of genome-scale metabolic network models using experimentally measured flux profiles

Genome-scale metabolic network models can be reconstructed for well-characterized organisms using genomic annotation and literature information. However, there are many instances in which model predictions of metabolic fluxes are not entirely consistent with experimental data, indicating that the reactions in the model do not match the active reactions in the in vivo system. We introduce a method for determining the active reactions in a genome-scale metabolic network based on a limited number of experimentally measured fluxes. This method, called optimal metabolic network identification (OMNI), allows efficient identification of the set of reactions that results in the best agreement between in silico predicted and experimentally measured flux distributions. We applied the method to intracellular flux data for evolved Escherichia coli mutant strains with lower than predicted growth rates in order to identify reactions that act as flux bottlenecks in these strains. The expression of the genes corresponding to these bottleneck reactions was often found to be downregulated in the evolved strains relative to the wild-type strain. We also demonstrate the ability of the OMNI method to diagnose problems in E. coli strains engineered for metabolite overproduction that have not reached their predicted production potential. The OMNI method applied to flux data for evolved strains can be used to provide insights into mechanisms that limit the ability of microbial strains to evolve towards their predicted optimal growth phenotypes. When applied to industrial production strains, the OMNI method can also be used to suggest metabolic engineering strategies to improve byproduct secretion. In addition to these applications, the method should prove to be useful in general for reconstructing metabolic networks of ill-characterized microbial organisms based on limited amounts of experimental data.     

Integrative network analysis reveals active microRNAs and their functions in gastric cancer

Background

Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO₂ and H₂ as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs) from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level.

Results

We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(-)-3hydroxybutyrate] (PHB) under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16.

Conclusion

The genome-scale metabolic model, RehMBEL1391, successfully represented metabolic characteristics of R. eutropha H16 at systems level. The reconstructed genome-scale metabolic model can be employed as an useful tool for understanding its metabolic capabilities, predicting its physiological consequences in response to various environmental and genetic changes, and developing strategies for systems metabolic engineering to improve its metabolic performance.     

Secreted Bacterial Effectors and Host-Produced Eiger/TNF Drive Death in a Salmonella-Infected Fruit Fly

Death by infection is often as much due to the host's reaction as it is to the direct result of microbial action. Here we identify genes in both the host and microbe that are involved in the pathogenesis of infection and disease in Drosophila melanogaster challenged with Salmonella enterica serovartyphimurium (S. typhimurium). We demonstrate that wild-type S. typhimurium causes a lethal systemic infection when injected into the hemocoel of D. melanogaster. Deletion of the gene encoding the secreted bacterial effector Salmonella leucine-rich (PslrP) changes an acute and lethal infection to one that is persistent and less deadly. We propose a model in which Salmonella secreted effectors stimulate the fly and thus cause an immune response that is damaging both to the bacteria and, subsequently, to the host. In support of this model, we show that mutations in the fly gene eiger, a TNF homolog, delay the lethality of Salmonella infection. These results suggest that S. typhimurium-infected flies die from a condition that resembles TNF-induced metabolic collapse in vertebrates. This idea provides us with a new model to study shock-like biology in a genetically manipulable host. In addition, it allows us to study the difference in pathways followed by a microbe when producing an acute or persistent infection.     

Engineering the nifH Promoter Region and Abolishing Poly-β-Hydroxybutyrate Accumulation in Rhizobium etli Enhance Nitrogen Fixation in Symbiosis with Phaseolus vulgaris

Rhizobium etli, as well as some other rhizobia, presents nitrogenase reductase (nifH) gene reiterations. Several R. etli strains studied in this laboratory showed a unique organization and contained two complete nifHDK operons (copies a and b) and a truncated nifHD operon (copy c). Expression analysis of lacZ fusion demonstrated that copies a and b in strain CFN42 are transcribed at lower levels than copy c, although this copy has no discernible role during nitrogen fixation. To increase nitrogenase production, we constructed a chimeric nifHDK operon regulated by the strong nifHc promoter sequence and expressed it in symbiosis with the common bean plant (Phaseolus vulgaris), either cloned on a stably inherited plasmid or incorporated into the symbiotic plasmid (pSym). Compared with the wild-type strain, strains with the nitrogenase overexpression construction assayed in greenhouse experiments had, increased nitrogenase activity (58% on average), increased plant weight (32% on average), increased nitrogen content in plants (15% at 32 days postinoculation), and most importantly, higher seed yield (36% on average), higher nitrogen content (25%), and higher nitrogen yield (72% on average) in seeds. Additionally, expression of the chimeric nifHDK operon in a poly-β-hydroxybutyrate-negative R. etli strain produced an additive effect in enhancing symbiosis. To our knowledge, this is the first report of increased seed yield and nutritional content in the common bean obtained by using only the genetic material already present in Rhizobium.     

Genome-Scale Metabolic Network Validation of Shewanella oneidensis Using Transposon Insertion Frequency Analysis

Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA). TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1) previous genome-wide direct gene-essentiality assignments; and, 2) flux balance analysis (FBA) predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.     

Odorant-binding proteins OBP57d and OBP57e affect taste perception and host-plant preference in Drosophila sechellia

Despite its morphological similarity to the other species in the Drosophila melanogaster species complex, D. sechellia has evolved distinct physiological and behavioral adaptations to its host plant Morinda citrifolia, commonly known as Tahitian Noni. The odor of the ripe fruit of M. citrifolia originates from hexanoic and octanoic acid. D. sechellia is attracted to these two fatty acids, whereas the other species in the complex are repelled. Here, using interspecies hybrids between D. melanogaster deficiency mutants and D. sechellia, we showed that the Odorant-binding protein 57e (Obp57e) gene is involved in the behavioral difference between the species. D. melanogaster knock-out flies for Obp57e and Obp57d showed altered behavioral responses to hexanoic acid and octanoic acid. Furthermore, the introduction of Obp57d and Obp57e from D. simulans and D. sechellia shifted the oviposition site preference of D. melanogaster Obp57d/e^KO flies to that of the original species, confirming the contribution of these genes to D. sechellia's specialization to M. citrifolia. Our finding of the genes involved in host-plant determination may lead to further understanding of mechanisms underlying taste perception, evolution of plant–herbivore interactions, and speciation.     

Flux analysis and metabolomics for systematic metabolic engineering of microorganisms

Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and ¹³C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering.     

Genes Essential for Nod Factor Production and Nodulation Are Located on a Symbiotic Amplicon (AMPRtrCFN299pc60) in Rhizobium tropici

Amplifiable DNA regions (amplicons) have been identified in the genome of Rhizobium etli. Here we report the isolation and molecular characterization of a symbiotic amplicon of Rhizobium tropici. To search for symbiotic amplicons, a cartridge containing a kanamycin resistance marker that responds to gene dosage and conditional origins of replication and transfer was inserted in the nodulation region of the symbiotic plasmid (pSym) of R. tropici CFN299. Derivatives harboring amplifications were selected by increasing the concentration of kanamycin in the cell culture. The amplified DNA region was mobilized into Escherichia coli and then into Agrobacterium tumefaciens. The 60-kb symbiotic amplicon, which we termed AMPRtrCFN299pc60, contains several nodulation and nitrogen fixation genes and is flanked by a novel insertion sequence ISRtr1. Amplification of AMPRtrCFN299pc60 through homologous recombination between ISRtr1 repeats increased the amount of Nod factors. Strikingly, the conjugal transfer of the amplicon into a plasmidless A. tumefaciens strain confers on the transconjugant the ability to produce R. tropici Nod factors and to nodulate Phaseolus vulgaris, indicating that R. tropici genes essential for the nodulation process are confined to an ampliable DNA region of the pSym.     

Genome-scale analysis of Mannheimia succiniciproducens metabolism

Mannheimia succiniciproducens MBEL55E isolated from bovine rumen is a capnophilic gram-negative bacterium that efficiently produces succinic acid, an industrially important four carbon dicarboxylic acid. In order to design a metabolically engineered strain which is capable of producing succinic acid with high yield and productivity, it is essential to optimize the whole metabolism at the systems level. Consequently, in silico modeling and simulation of the genome-scale metabolic network was employed for genome-scale analysis and efficient design of metabolic engineering experiments. The genome-scale metabolic network of M. succiniciproducens consisting of 686 reactions and 519 metabolites was constructed based on reannotation and validation experiments. With the reconstructed model, the network structure and key metabolic characteristics allowing highly efficient production of succinic acid were deciphered; these include strong PEP carboxylation, branched TCA cycle, relative weak pyruvate formation, the lack of glyoxylate shunt, and non-PTS for glucose uptake. Constraints-based flux analyses were then carried out under various environmental and genetic conditions to validate the genome-scale metabolic model and to decipher the altered metabolic characteristics. Predictions based on constraints-based flux analysis were mostly in excellent agreement with the experimental data. In silico knockout studies allowed prediction of new metabolic engineering strategies for the enhanced production of succinic acid. This genome-scale in silico model can serve as a platform for the systematic prediction of physiological responses of M. succiniciproducens to various environmental and genetic perturbations and consequently for designing rational strategies for strain improvement.     

Reconstruction and verification of a genome-scale metabolic model for <Emphasis Type="Italic">Synechocystis</Emphasis> sp. PCC6803

In terms of generating sustainable energy resources, the prospect of producing energy and other useful materials using cyanobacteria has been attracting increasing attention since these processes require only carbon dioxide and solar energy. To establish production processes with a high productivity, in silico models to predict the metabolic activity of cyanobacteria are highly desired. In this study, we reconstructed a genome-scale metabolic model of the cyanobacterium Synechocystis sp. PCC6803, which included 465 metabolites and 493 metabolic reactions. Using this model, we performed constraint-based metabolic simulations to obtain metabolic flux profiles under various environmental conditions. We evaluated the simulated results by comparing these with experimental results from ¹³C-tracer metabolic flux analyses, which were obtained under heterotrophic and mixotrophic conditions. There was a good agreement of simulation and experimental results under both conditions. Furthermore, using our model, we evaluated the production of ethanol by Synechocystis sp. PCC6803, which enabled us to estimate quantitatively how its productivity depends on the environmental conditions. The genome-scale metabolic model provides useful information for the evaluation of the metabolic capabilities, and prediction of the metabolic characteristics, of Synechocystis sp. PCC6803.     

Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels

Candida albicans is a leading cause of life-threatening hospital-acquired infections and can lead to Candidemia with sepsis-like symptoms and high mortality rates. We reconstructed a genome-scale C. albicans metabolic model to investigate bacterial-fungal metabolic interactions in the gut as determinants of fungal abundance. We optimized the predictive capacity of our model using wild type and mutant C. albicans growth data and used it for in silico metabolic interaction predictions. Our analysis of more than 900 paired fungal–bacterial metabolic models predicted key gut bacterial species modulating C. albicans colonization levels. Among the studied microbes, Alistipes putredinis was predicted to negatively affect C. albicans levels. We confirmed these findings by metagenomic sequencing of stool samples from 24 human subjects and by fungal growth experiments in bacterial spent media. Furthermore, our pairwise simulations guided us to specific metabolites with promoting or inhibitory effect to the fungus when exposed in defined media under carbon and nitrogen limitation. Our study demonstrates that in silico metabolic prediction can lead to the identification of gut microbiome features that can significantly affect potentially harmful levels of C. albicans.Subject terms: Fungi, Infectious diseases, Metagenomics, Gastrointestinal diseases, Microbiome     

Prevalence of the Rhizobium etli-Like Allele in Genes Coding for 16S rRNA among the Indigenous Rhizobial Populations Found Associated with Wild Beans from the Southern Andes in Argentina

A collection of rhizobial isolates from nodules of wild beans, Phaseolus vulgaris var. aborigineus, found growing in virgin lands in 17 geographically separate sites in northwest Argentina was characterized on the basis of host range, growth, hybridization to a nifH probe, analysis of genes coding for 16S rRNA (16S rDNA), DNA fingerprinting, and plasmid profiles. Nodules in field-collected wild bean plants were largely dominated by rhizobia carrying the 16S rDNA allele of Rhizobium etli. A similar prevalence of the R. etli allele was observed among rhizobia trapped from nearby soil. Intragroup diversity of wild bean isolates with either R. etli-like or Rhizobium leguminosarum bv. phaseoli-like alleles was generally found across northwest Argentina. The predominance of the R. etli allele suggests that in this center of origin of P. vulgaris the coevolution of Rhizobium spp. and primitive beans has resulted in this preferential symbiotic association.     

Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two <Emphasis Type="Italic">Blattabacterium cuenoti</Emphasis> strains,primary endosymbionts of cockroaches

BACKGROUND: Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria. RESULTS: We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence. CONCLUSIONS: The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach lineages. FBA performed on the reconstructed networks from the two bacteria helps to refine the functional analysis of the genomes enabling us to postulate how slightly different host metabolic contexts drove their parallel evolution.     

Asymmetrical reinforcement and Wolbachia infection in Drosophila

Reinforcement refers to the evolution of increased mating discrimination against heterospecific individuals in zones of geographic overlap and can be considered a final stage in the speciation process. One the factors that may affect reinforcement is the degree to which hybrid matings result in the permanent loss of genes from a species' gene pool. Matings between females of Drosophila subquinaria and males of D. recens result in high levels of offspring mortality, due to interspecific cytoplasmic incompatibility caused by Wolbachia infection of D. recens. Such hybrid inviability is not manifested in matings between D. recens females and D. subquinaria males. Here we ask whether the asymmetrical hybrid inviability is associated with a corresponding asymmetry in the level of reinforcement. The geographic ranges of D. recens and D. subquinaria were found to overlap across a broad belt of boreal forest in central Canada. Females of D. subquinaria from the zone of sympatry exhibit much stronger levels of discrimination against males of D. recens than do females from allopatric populations. In contrast, such reproductive character displacement is not evident in D. recens, consistent with the expected effects of unidirectional cytoplasmic incompatibility. Furthermore, there is substantial behavioral isolation within D. subquinaria, because females from populations sympatric with D. recens discriminate against allopatric conspecific males, whereas females from populations allopatric with D. recens show no discrimination against any conspecific males. Patterns of general genetic differentiation among populations are not consistent with patterns of behavioral discrimination, which suggests that the behavioral isolation within D. subquinaria results from selection against mating with Wolbachia-infected D. recens. Interspecific cytoplasmic incompatibility may contribute not only to post-mating isolation, an effect already widely recognized, but also to reinforcement, particularly in the uninfected species. The resulting reproductive character displacement not only increases behavioral isolation from the Wolbachia-infected species, but may also lead to behavioral isolation between populations of the uninfected species. Given the widespread occurrence of Wolbachia among insects, it thus appears that there are multiple ways by which these endosymbionts may directly and indirectly contribute to reproductive isolation and speciation.     

Modeling <Emphasis Type="Italic">Lactococcus lactis</Emphasis> using a genome-scale flux model

Background  

Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA) and minimization of metabolic adjustment (MOMA) were used as modeling frameworks.     

The complete genome sequence and comparative genome analysis of the high pathogenicity Yersinia enterocolitica strain 8081

The human enteropathogen, Yersinia enterocolitica, is a significant link in the range of Yersinia pathologies extending from mild gastroenteritis to bubonic plague. Comparison at the genomic level is a key step in our understanding of the genetic basis for this pathogenicity spectrum. Here we report the genome of Y. enterocolitica strain 8081 (serotype 0:8; biotype 1B) and extensive microarray data relating to the genetic diversity of the Y. enterocolitica species. Our analysis reveals that the genome of Y. enterocolitica strain 8081 is a patchwork of horizontally acquired genetic loci, including a plasticity zone of 199 kb containing an extraordinarily high density of virulence genes. Microarray analysis has provided insights into species-specific Y. enterocolitica gene functions and the intraspecies differences between the high, low, and nonpathogenic Y. enterocolitica biotypes. Through comparative genome sequence analysis we provide new information on the evolution of the Yersinia. We identify numerous loci that represent ancestral clusters of genes potentially important in enteric survival and pathogenesis, which have been lost or are in the process of being lost, in the other sequenced Yersinia lineages. Our analysis also highlights large metabolic operons in Y. enterocolitica that are absent in the related enteropathogen, Yersinia pseudotuberculosis, indicating major differences in niche and nutrients used within the mammalian gut. These include clusters directing, the production of hydrogenases, tetrathionate respiration, cobalamin synthesis, and propanediol utilisation. Along with ancestral gene clusters, the genome of Y. enterocolitica has revealed species-specific and enteropathogen-specific loci. This has provided important insights into the pathology of this bacterium and, more broadly, into the evolution of the genus. Moreover, wider investigations looking at the patterns of gene loss and gain in the Yersinia have highlighted common themes in the genome evolution of other human enteropathogens.     

Major structural differences and novel potential virulence mechanisms from the genomes of multiple campylobacter species

Sequencing and comparative genome analysis of four strains of Campylobacter including C. lari RM2100, C. upsaliensis RM3195, and C. coli RM2228 has revealed major structural differences that are associated with the insertion of phage- and plasmid-like genomic islands, as well as major variations in the lipooligosaccharide complex. Poly G tracts are longer, are greater in number, and show greater variability in C. upsaliensis than in the other species. Many genes involved in host colonization, including racR/S, cadF, cdt, ciaB, and flagellin genes, are conserved across the species, but variations that appear to be species specific are evident for a lipooligosaccharide locus, a capsular (extracellular) polysaccharide locus, and a novel Campylobacter putative licABCD virulence locus. The strains also vary in their metabolic profiles, as well as their resistance profiles to a range of antibiotics. It is evident that the newly identified hypothetical and conserved hypothetical proteins, as well as uncharacterized two-component regulatory systems and membrane proteins, may hold additional significant information on the major differences in virulence among the species, as well as the specificity of the strains for particular hosts.