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Anaplasma marginale is a tick-borne rickettsial pathogen of cattle with a worldwide distribution. Currently a safe and efficacious vaccine is unavailable. Outer membrane protein (OMP) extracts or a defined surface protein complex reproducibly induce protective immunity. However, there are several knowledge gaps limiting progress in vaccine development. First, are these OMPs conserved among the diversity of A. marginale strains circulating in endemic regions? Second, are the most highly conserved outer membrane proteins in the immunogens recognized by immunized and protected animals? Lastly, can this subset of OMPs recognized by antibody from protected vaccinates and conserved among strains recapitulate the protection of outer membrane vaccines? To address the first goal, genes encoding OMPs AM202, AM368, AM854, AM936, AM1041, and AM1096, major subdominant components of the outer membrane, were cloned and sequenced from geographically diverse strains and isolates. AM202, AM936, AM854, and AM1096 share 99.9 to 100% amino acid identity. AM1041 has 97.1 to 100% and AM368 has 98.3 to 99.9% amino acid identity. While all four of the most highly conserved OMPs were recognized by IgG from animals immunized with outer membranes, linked surface protein complexes, or unlinked surface protein complexes and shown to be protected from challenge, the highest titers and consistent recognition among vaccinates were to AM854 and AM936. Consequently, animals were immunized with recombinant AM854 and AM936 and challenged. Recombinant vaccinates and purified outer membrane vaccinates had similar IgG and IgG2 responses to both proteins. However, the recombinant vaccinates developed higher bacteremia after challenge as compared to adjuvant-only controls and outer membrane vaccinates. These results provide the first evidence that vaccination with specific antigens may exacerbate disease. Progressing from the protective capacity of outer membrane formulations to recombinant vaccines requires testing of additional antigens, optimization of the vaccine formulation and a better understanding of the protective immune response. [ABSTRACT FROM AUTHOR]

Identification of specific antigens responsible for the ability of complex immunogens to induce protection is a major goal in development of bacterial vaccines. Much of the investigation has focused on highly abundant and highly immunodominant outer membrane proteins. Recently however, genomic and proteomic approaches have facilitated identification of minor components of the bacterial outer membrane that have previously been missed or ignored in immunological analyses. Immunization with Anaplasma marginale outer membranes or a cross-linked surface complex induces protection against bacteremia, however the components responsible for protection within these complex immunogens are unknown. Using outer membrane protein AM779 as a model, we demonstrated that this highly conserved but minor component of the A. marginale surface was immunologically sub-dominant in the context of the outer membrane or surface complex vaccines. Immunologic sub-dominance could be overcome by targeted vaccination with AM779 for T lymphocyte responses but not for antibody responses, suggesting that both abundance and intrinsic immunogenicity determine relative dominance. Importantly, immunization with AM779 supports that once priming is achieved by specific targeting, recall upon infectious challenge is achieved. While immunization with AM779 alone was not sufficient to induce protection, the ability of targeted immunization to prime the immune response to highly conserved but low abundance proteins supports continued investigation into the role of sub-dominant antigens, individually and collectively, in vaccine development for A. marginale and related bacterial pathogens. [ABSTRACT FROM AUTHOR]

Background: To decipher the complexity and improve the understanding of host-pathogen interactions, biologists must adopt new system level approaches in which the hierarchy of biological interactions and dynamics can be studied. This paper presents the application of systems biology for the cross-comparative analysis and interactome modeling of three different infectious agents, leading to the identification of novel, unique and common molecular host responses (biosignatures). Methods: A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Salmonella enterica Typhimurium (STM) and Mycobacterium avium paratuberculosis (MAP). A bovine ligated ileal loop biological model was employed to capture the host gene expression response at four time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a systematic comparative analysis of pathway and Gene Ontology category perturbations. Results: A cross-comparative assessment of 219 pathways and 1620 gene ontology (GO) categories was performed on each pathogen-host condition. Both unique and common pathway and GO perturbations indicated remarkable temporal differences in pathogen-host response profiles. Highly discriminatory pathways were selected from each pathogen condition to create a common system level interactome model comprised of 622 genes. This model was trained with data from each pathogen condition to capture unique and common gene expression features and relationships leading to the identification of candidate host-pathogen points of interactions and discriminatory biosignatures. Conclusions: Our results provide deeper understanding of the overall complexity of host defensive and pathogen invasion processes as well as the identification of novel host-pathogen interactions. The application of advanced computational methods for developing interactome models based on DBN has proven to be instrumental in conducting multi-conditional cross-comparative analyses. Further, this approach generates a fully simulateable [ABSTRACT FROM AUTHOR]

Global protein identification through current proteomics methods typically depends on the availability of sequenced genomes. In spite of increasingly high throughput sequencing technologies, this information is not available for every microorganism and rarely available for entire microbial communities. Nevertheless, the protein-level homology that exists between related bacteria makes it possible to extract biological information from the proteome of an organism or microbial community by using the genomic sequences of a near neighbor organism. Here, we demonstrate a trans-organism search strategy for determining the extent to which near-neighbor genome sequences can be applied to identify proteins in unsequenced environmental isolates. In proof of concept testing, we found that within a CLUSTAL W distance of 0.089, near-neighbor genomes successfully identified a high percentage of proteins within an organism. Application of this strategy to characterize environmental bacterial isolates lacking sequenced genomes, but having 16S rDNA sequence similarity to Shewanella resulted in the identification of 300-500 proteins in each strain. The majority of identified pathways mapped to core processes, as well as to processes unique to the Shewanellae, in particular to the presence of c-type cytochromes. Examples of core functional categories include energy metabolism, protein and nucleotide synthesis and cofactor biosynthesis, allowing classification of bacteria by observation of conserved processes. Additionally, within these core functionalities, we observed proteins involved in the alternative lactate utilization pathway, recently described in Shewanella. [ABSTRACT FROM AUTHOR]

While comparative bacterial genomic studies commonly predict a set of genes indicative of common ancestry, experimental validation of the existence of this core genome requires extensive measurement and is typically not undertaken. Enabled by an extensive proteome database developed over six years, we have experimentally verified the expression of proteins predicted from genomic ortholog comparisons among 17 environmental and pathogenic bacteria. More exclusive relationships were observed among the expressed protein content of phenotypically related bacteria, which is indicative of the specific lifestyles associated with these organisms. Although genomic studies can establish relative orthologous relationships among a set of bacteria and propose a set of ancestral genes, our proteomics study establishes expressed lifestyle differences among conserved genes and proposes a set of expressed ancestral traits. [ABSTRACT FROM AUTHOR]