Linked Life Data

15936018

Source:http://linkedlifedata.com/resource/pubmed/id/15936018

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-8-1
pubmed:abstractText
To identify new vaccine candidates, Eimeria tenella expressed sequence tags (ESTs) from public databases were analysed for secretory molecules with an especially developed automated in silico strategy termed DNAsignalP. A total of 12,187 ESTs were clustered into 2881 contigs followed by a blastx search, which resulted in a significant number of E. tenella contigs with homologies to entries in public databases. Amino acid sequences of appropriate homologous proteins were analysed for the occurrence of an N-terminal signal sequence using the algorithm signalP. The resulting list of 84 entries comprised 51 contigs whose deduced proteins showed homologies to proteins of apicomplexan parasites. Based on function or localisation, we selected candidate proteins classified as (i) secreted proteins of Apicomplexa parasites, (ii) secreted enzymes, and (iii) transport and signalling proteins. To verify our strategy experimentally, we used a functional complementation system in yeast. For five selected candidate proteins we found that these were indeed secreted. Our approach thus represents an efficient method to identify secretory and surface proteins out of EST databases.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0014-4894
pubmed:author
pubmed:issnType
Print
pubmed:volume
111
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
14-23
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Eimeria tenella: identification of secretory and surface proteins from expressed sequence tags.
pubmed:affiliation
Department of Molecular Parasitology, Humboldt University, Berlin, Germany.
pubmed:publicationType
Journal Article