J Vet Sci.  2009 Sep;10(3):203-210. 10.4142/jvs.2009.10.3.203.

Charting the proteome of Cryptosporidium parvum sporozoites using sequence similarity-based BLAST searching

• Siddiki AM
• Wastling J

• KMID: 1726919
• DOI: http://doi.org/10.4142/jvs.2009.10.3.203

Abstract

Cryptosporidium (C.) spp. are important zoonotic parasites causing widespread diarrhoeal disease in man and animals. The recent release of the complete genome sequences for C. parvum and C. hominis has facilitated the comprehensive global proteome analysis of these opportunistic pathogens. The well-known approach for mass spectrometry (MS) based data analysis using the BLAST tool (MS BLAST) is a database search protocol for identifying unknown proteins by sequence similarity to homologous proteins using peptide sequences produced by mass spectrometry. We have used several complementary approaches to explore the global sporozoite proteome of C. parvum with available proteomic tools. To optimize the output of the MS data, a sequence similarity-based MS BLAST strategy was employed for bioinformatic analysis. Most significantly, almost all the constituents of glycolysis and several mitochondrion-related proteins were identified. In addition, many hypothetical Cryptosporidium proteins were validated by the identification of their constituent peptides. The MS BLAST approach was found to be useful during the study and could provide valuable information towards a complete understanding of the unique biology of Cryptosporidium.

Keyword

Cryptosporidium; LC-MS/MS; MS BLAST; proteomics; sporozoites

MeSH Terms

Chromatography, Liquid
Cryptosporidium parvum/genetics/*metabolism
Electrophoresis, Polyacrylamide Gel
*Proteome
Proteomics/*methods
Protozoan Proteins/isolation & purification/*metabolism
Sporozoites/*metabolism
Tandem Mass Spectrometry

Figure

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  Fig. 1 Roadmap for database searches towards identifying known and putative protein sequences.

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  Fig. 2 First dimension SDS-PAGE of the sporozoite proteins of Cryptosporidium (C.) parvum. The lane was then excised into 20 slices and analysed by tandem mass spectrometry. The side bar shows the number of hits per slice.

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  Fig. 3 Functional categorization of 84 C. parvum proteins identified by mass spectrometry based BLAST searching of MS data in an 1D-SDS-PAGE experiment.

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