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      An insight into the sialome of Glossina morsitans morsitans

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          Abstract

          Background

          Blood feeding evolved independently in worms, arthropods and mammals. Among the adaptations to this peculiar diet, these animals developed an armament of salivary molecules that disarm their host's anti-bleeding defenses (hemostasis), inflammatory and immune reactions. Recent sialotranscriptome analyses (from the Greek sialo = saliva) of blood feeding insects and ticks have revealed that the saliva contains hundreds of polypeptides, many unique to their genus or family. Adult tsetse flies feed exclusively on vertebrate blood and are important vectors of human and animal diseases. Thus far, only limited information exists regarding the Glossina sialome, or any other fly belonging to the Hippoboscidae.

          Results

          As part of the effort to sequence the genome of Glossina morsitans morsitans, several organ specific, high quality normalized cDNA libraries have been constructed, from which over 20,000 ESTs from an adult salivary gland library were sequenced. These ESTs have been assembled using previously described ESTs from the fat body and midgut libraries of the same fly, thus totaling 62,251 ESTs, which have been assembled into 16,743 clusters (8,506 of which had one or more EST from the salivary gland library). Coding sequences were obtained for 2,509 novel proteins, 1,792 of which had at least one EST expressed in the salivary glands. Despite library normalization, 59 transcripts were overrepresented in the salivary library indicating high levels of expression. This work presents a detailed analysis of the salivary protein families identified. Protein expression was confirmed by 2D gel electrophoresis, enzymatic digestion and mass spectrometry. Concurrently, an initial attempt to determine the immunogenic properties of selected salivary proteins was undertaken.

          Conclusions

          The sialome of G. m. morsitans contains over 250 proteins that are possibly associated with blood feeding. This set includes alleles of previously described gene products, reveals new evidence that several salivary proteins are multigenic and identifies at least seven new polypeptide families unique to Glossina. Most of these proteins have no known function and thus, provide a discovery platform for the identification of novel pharmacologically active compounds, innovative vector-based vaccine targets, and immunological markers of vector exposure.

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          Most cited references165

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment.

            S. KUMAR (2004)
            With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2010
                30 March 2010
                : 11
                : 213
                Affiliations
                [1 ]Vector Group, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK
                [2 ]Current address: The Healing Foundation Centre, Manchester, M13 9PT, UK
                [3 ]Section of Vector Biology, Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Rockville MD 20852, USA
                [4 ]Department of Parasitology, Unit of Entomology, Institute of Tropical Medicine, B-2000 Antwerp, Belgium
                [5 ]Department of Epidemiology of Microbial Diseases, Yale School of Public Heath, New Haven, CT 06520, USA
                [6 ]Children's Memorial Research Center, North-Western University, Chicago, IL 60614, USA
                [7 ]Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK
                Article
                1471-2164-11-213
                10.1186/1471-2164-11-213
                2853526
                20353571
                ee4e5209-a8f2-4597-ae07-8de8404552cd
                Copyright ©2010 Alves-Silva et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 6 November 2009
                : 30 March 2010
                Categories
                Research Article

                Genetics
                Genetics

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