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Dermacentor andersoni, known as the Rocky Mountain wood tick, is found in the western United States and transmits pathogens that cause diseases of veterinary and public health importance including Rocky Mountain spotted fever, tularemia, Colorado tick fever and bovine anaplasmosis. Tick saliva is known to modulate both innate and acquired immune responses, enabling ticks to feed for several days without detection. During feeding ticks subvert host defences such as hemostasis and inflammation, which would otherwise result in coagulation, wound repair and rejection of the tick. Molecular characterization of the proteins and pharmacological molecules secreted in tick saliva offers an opportunity to develop tick vaccines as an alternative to the use of acaricides, as well as new anti-inflammatory drugs. We performed proteomics informed by transcriptomics to identify D. andersoni saliva proteins that are secreted during feeding. The transcript data generated a database of 21,797 consensus sequences, which we used to identify 677 proteins secreted in the saliva of D. andersoni ticks fed for 2 and 5days, following proteomic investigations of whole saliva using mass spectrometry. Salivary gland transcript levels of unfed ticks were compared with 2 and 5day fed ticks to identify genes upregulated early during tick feeding. We cross-referenced the proteomic data with the transcriptomic data to identify 157 proteins of interest for immunomodulation and blood feeding. Proteins of unknown function as well as known immunomodulators were identified., (Copyright © 2014 Australian Society for Parasitology Inc. All rights reserved.)

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.

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.