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

Siddiki AM, Wastling JM - J. Vet. Sci. (2009)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Preclinical Veterinary Sciences, Faculty of Veterinary Science, University of Liverpool, Crown Street, Liverpool, L69 7ZJ, UK. zsiddiki@gmail.com

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.

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Related in: MedlinePlus

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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Figure 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.

Mentions: The MASCOT search of LC-MS/MS data (while searched against the non redundant NCBI database) from all 20 samples in 1D-SDS-PAGE gel bands (Fig. 2) revealed 33 hits of Cryptosporidium. To obtain further information from the same MS data, the MS BLAST strategy was applied for a sequence similarity based protein homology search. While the mass fragmentation data of each individual band from LC-MS/MS were searched against the locally downloaded Cryptosporidium ORF (open reading frame) dataset, a total of 196 significant hits against contigs were recorded from 20 searches. When the contig sequences were analysed, each contig was found to contain at least one significant peptide hit, while some contained as many as 20 significant peptides hits (data not shown). In many instances the identified peptides with significant scores were found closely situated in a long continuous contig. The predicted ORF sequences (with significant peptides within each sequence string) were then used for BLAST search (protein-protein BLAST) for homology based protein identification. A total of 165 Cryptosporidium proteins were identified by this MS-BLAST approach. However, those hits included both C. parvum (n = 84) and C. hominis (n = 81) entries. In nearly all cases, the C. hominis homologous proteins were found with the same query in MS BLAST and the peptides were almost identical to C. parvum. Incorporating the two protein lists from the 1D-SDS-PAGE experiment (derived by MASCOT searching against the non redundant NCBI database and a MS BLAST search with peptides from Cryptosporidium ORF dataset) identified 100 C. parvum proteins (Table 1). Comparing the two approaches, the MS BLAST search strategy was found to provide 5 times greater (33 to 165) information than the NCBI search alone.


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

Siddiki AM, Wastling JM - J. Vet. Sci. (2009)

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.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2801136&req=5

Figure 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.
Mentions: The MASCOT search of LC-MS/MS data (while searched against the non redundant NCBI database) from all 20 samples in 1D-SDS-PAGE gel bands (Fig. 2) revealed 33 hits of Cryptosporidium. To obtain further information from the same MS data, the MS BLAST strategy was applied for a sequence similarity based protein homology search. While the mass fragmentation data of each individual band from LC-MS/MS were searched against the locally downloaded Cryptosporidium ORF (open reading frame) dataset, a total of 196 significant hits against contigs were recorded from 20 searches. When the contig sequences were analysed, each contig was found to contain at least one significant peptide hit, while some contained as many as 20 significant peptides hits (data not shown). In many instances the identified peptides with significant scores were found closely situated in a long continuous contig. The predicted ORF sequences (with significant peptides within each sequence string) were then used for BLAST search (protein-protein BLAST) for homology based protein identification. A total of 165 Cryptosporidium proteins were identified by this MS-BLAST approach. However, those hits included both C. parvum (n = 84) and C. hominis (n = 81) entries. In nearly all cases, the C. hominis homologous proteins were found with the same query in MS BLAST and the peptides were almost identical to C. parvum. Incorporating the two protein lists from the 1D-SDS-PAGE experiment (derived by MASCOT searching against the non redundant NCBI database and a MS BLAST search with peptides from Cryptosporidium ORF dataset) identified 100 C. parvum proteins (Table 1). Comparing the two approaches, the MS BLAST search strategy was found to provide 5 times greater (33 to 165) information than the NCBI search alone.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Preclinical Veterinary Sciences, Faculty of Veterinary Science, University of Liverpool, Crown Street, Liverpool, L69 7ZJ, UK. zsiddiki@gmail.com

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.

Show MeSH
Related in: MedlinePlus