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Needles in the EST haystack: large-scale identification and analysis of excretory-secretory (ES) proteins in parasitic nematodes using expressed sequence tags (ESTs).

Nagaraj SH, Gasser RB, Ranganathan S - PLoS Negl Trop Dis (2008)

Bottom Line: Of these 4,710 proteins, 2,490 (52.8%) had orthologues in Caenorhabditis elegans, whereas 621 (13.8%) appeared to be novel, currently having no significant match to any molecule available in public databases.We report the large-scale analysis of ES proteins inferred from EST data for a range of parasitic nematodes.This set of ES proteins provides an inventory of known and novel members of ES proteins as a foundation for studies focused on understanding the biology of parasitic nematodes and their interactions with their hosts, as well as for the development of novel drugs or vaccines for parasite intervention and control.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, New South Wales, Australia.

ABSTRACT

Background: Parasitic nematodes of humans, other animals and plants continue to impose a significant public health and economic burden worldwide, due to the diseases they cause. Promising antiparasitic drug and vaccine candidates have been discovered from excreted or secreted (ES) proteins released from the parasite and exposed to the immune system of the host. Mining the entire expressed sequence tag (EST) data available from parasitic nematodes represents an approach to discover such ES targets.

Methods and findings: In this study, we predicted, using EST2Secretome, a novel, high-throughput, computational workflow system, 4,710 ES proteins from 452,134 ESTs derived from 39 different species of nematodes, parasitic in animals (including humans) or plants. In total, 2,632, 786, and 1,292 ES proteins were predicted for animal-, human-, and plant-parasitic nematodes. Subsequently, we systematically analysed ES proteins using computational methods. Of these 4,710 proteins, 2,490 (52.8%) had orthologues in Caenorhabditis elegans, whereas 621 (13.8%) appeared to be novel, currently having no significant match to any molecule available in public databases. Of the C. elegans homologues, 267 had strong "loss-of-function" phenotypes by RNA interference (RNAi) in this nematode. We could functionally classify 1,948 (41.3%) sequences using the Gene Ontology (GO) terms, establish pathway associations for 573 (12.2%) sequences using Kyoto Encyclopaedia of Genes and Genomes (KEGG), and identify protein interaction partners for 1,774 (37.6%) molecules. We also mapped 758 (16.1%) proteins to protein domains including the nematode-specific protein family "transthyretin-like" and "chromadorea ALT," considered as vaccine candidates against filariasis in humans.

Conclusions: We report the large-scale analysis of ES proteins inferred from EST data for a range of parasitic nematodes. This set of ES proteins provides an inventory of known and novel members of ES proteins as a foundation for studies focused on understanding the biology of parasitic nematodes and their interactions with their hosts, as well as for the development of novel drugs or vaccines for parasite intervention and control.

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Assignment of Gene Ontology (GO) terms for putative excretory-secretory proteins.Components, such as Biological Process, Molecular Function and Cellular Component, are indicated. Individual GO categories can have multiple mappings. Percentages shown reflect the total categories annotated and not the total sequences annotated under each component.
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pntd-0000301-g003: Assignment of Gene Ontology (GO) terms for putative excretory-secretory proteins.Components, such as Biological Process, Molecular Function and Cellular Component, are indicated. Individual GO categories can have multiple mappings. Percentages shown reflect the total categories annotated and not the total sequences annotated under each component.

Mentions: For our parasitic nematode dataset, the 1,948 ES sequences with GO annotations could be annotated further, with 1,092 being assigned biological process (BP), 1,210 molecular function (MF) and 779 cellular component (CC) GO terms. A summary of GO annotation by biological process, cellular component and molecular function is provided in Figure 3. When we examined the GO terms in detail, we found that more than half of the sequences (420/779) were annotated specifically with terms pertaining to the extracellular region (GO: 0005576), including extracellular matrix (GO: 0031012), extracellular matrix part (GO: 0044420), extracellular space (GO: 0005615) and extracellular region part (GO: 0044421). While each sequence was annotated with multiple cellular component terms, leading to 18% overall instances of “extracellular” among the total 2285 cellular component terms, these annotations strengthened the computational prediction of ES proteins from EST datasets. We also validated the GO terms for overall instances of the GO term “extracellular” by comparing with 2,649 inferred ES proteins derived from C. elegans proteome. We assigned GO terms to these ES proteins and found an overall percentage of 29% of “extracellular” GO terms in the C. elegans proteome (data not shown). The higher percentage in C. elegans dataset could be due to the use of full-length protein sequences from C. elegans, compared with the dataset analysed, which is derived exclusively from ESTs. Amongst the most common GO categories representing biological processes were metabolic process (GO: 0008152) and cellular process (GO: 0009987). The largest number of GO terms in molecular function was binding (GO: 0005488) and catalytic activity (GO: 0003824), both of which are significant from the viewpoint of identifying novel drug or vaccine candidates. A complete listing of GO mappings assigned to ES protein data is provided in Table S1.


Needles in the EST haystack: large-scale identification and analysis of excretory-secretory (ES) proteins in parasitic nematodes using expressed sequence tags (ESTs).

Nagaraj SH, Gasser RB, Ranganathan S - PLoS Negl Trop Dis (2008)

Assignment of Gene Ontology (GO) terms for putative excretory-secretory proteins.Components, such as Biological Process, Molecular Function and Cellular Component, are indicated. Individual GO categories can have multiple mappings. Percentages shown reflect the total categories annotated and not the total sequences annotated under each component.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2553489&req=5

pntd-0000301-g003: Assignment of Gene Ontology (GO) terms for putative excretory-secretory proteins.Components, such as Biological Process, Molecular Function and Cellular Component, are indicated. Individual GO categories can have multiple mappings. Percentages shown reflect the total categories annotated and not the total sequences annotated under each component.
Mentions: For our parasitic nematode dataset, the 1,948 ES sequences with GO annotations could be annotated further, with 1,092 being assigned biological process (BP), 1,210 molecular function (MF) and 779 cellular component (CC) GO terms. A summary of GO annotation by biological process, cellular component and molecular function is provided in Figure 3. When we examined the GO terms in detail, we found that more than half of the sequences (420/779) were annotated specifically with terms pertaining to the extracellular region (GO: 0005576), including extracellular matrix (GO: 0031012), extracellular matrix part (GO: 0044420), extracellular space (GO: 0005615) and extracellular region part (GO: 0044421). While each sequence was annotated with multiple cellular component terms, leading to 18% overall instances of “extracellular” among the total 2285 cellular component terms, these annotations strengthened the computational prediction of ES proteins from EST datasets. We also validated the GO terms for overall instances of the GO term “extracellular” by comparing with 2,649 inferred ES proteins derived from C. elegans proteome. We assigned GO terms to these ES proteins and found an overall percentage of 29% of “extracellular” GO terms in the C. elegans proteome (data not shown). The higher percentage in C. elegans dataset could be due to the use of full-length protein sequences from C. elegans, compared with the dataset analysed, which is derived exclusively from ESTs. Amongst the most common GO categories representing biological processes were metabolic process (GO: 0008152) and cellular process (GO: 0009987). The largest number of GO terms in molecular function was binding (GO: 0005488) and catalytic activity (GO: 0003824), both of which are significant from the viewpoint of identifying novel drug or vaccine candidates. A complete listing of GO mappings assigned to ES protein data is provided in Table S1.

Bottom Line: Of these 4,710 proteins, 2,490 (52.8%) had orthologues in Caenorhabditis elegans, whereas 621 (13.8%) appeared to be novel, currently having no significant match to any molecule available in public databases.We report the large-scale analysis of ES proteins inferred from EST data for a range of parasitic nematodes.This set of ES proteins provides an inventory of known and novel members of ES proteins as a foundation for studies focused on understanding the biology of parasitic nematodes and their interactions with their hosts, as well as for the development of novel drugs or vaccines for parasite intervention and control.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, New South Wales, Australia.

ABSTRACT

Background: Parasitic nematodes of humans, other animals and plants continue to impose a significant public health and economic burden worldwide, due to the diseases they cause. Promising antiparasitic drug and vaccine candidates have been discovered from excreted or secreted (ES) proteins released from the parasite and exposed to the immune system of the host. Mining the entire expressed sequence tag (EST) data available from parasitic nematodes represents an approach to discover such ES targets.

Methods and findings: In this study, we predicted, using EST2Secretome, a novel, high-throughput, computational workflow system, 4,710 ES proteins from 452,134 ESTs derived from 39 different species of nematodes, parasitic in animals (including humans) or plants. In total, 2,632, 786, and 1,292 ES proteins were predicted for animal-, human-, and plant-parasitic nematodes. Subsequently, we systematically analysed ES proteins using computational methods. Of these 4,710 proteins, 2,490 (52.8%) had orthologues in Caenorhabditis elegans, whereas 621 (13.8%) appeared to be novel, currently having no significant match to any molecule available in public databases. Of the C. elegans homologues, 267 had strong "loss-of-function" phenotypes by RNA interference (RNAi) in this nematode. We could functionally classify 1,948 (41.3%) sequences using the Gene Ontology (GO) terms, establish pathway associations for 573 (12.2%) sequences using Kyoto Encyclopaedia of Genes and Genomes (KEGG), and identify protein interaction partners for 1,774 (37.6%) molecules. We also mapped 758 (16.1%) proteins to protein domains including the nematode-specific protein family "transthyretin-like" and "chromadorea ALT," considered as vaccine candidates against filariasis in humans.

Conclusions: We report the large-scale analysis of ES proteins inferred from EST data for a range of parasitic nematodes. This set of ES proteins provides an inventory of known and novel members of ES proteins as a foundation for studies focused on understanding the biology of parasitic nematodes and their interactions with their hosts, as well as for the development of novel drugs or vaccines for parasite intervention and control.

Show MeSH
Related in: MedlinePlus