The prediction of a pathogenesis-related secretome of Puccinia helianthi through high-throughput transcriptome analysis.
Identifieur interne : 000066 ( Main/Corpus ); précédent : 000065; suivant : 000067The prediction of a pathogenesis-related secretome of Puccinia helianthi through high-throughput transcriptome analysis.
Auteurs : Lan Jing ; Dandan Guo ; Wenjie Hu ; Xiaofan NiuSource :
- BMC bioinformatics [ 1471-2105 ] ; 2017.
English descriptors
- KwdEn :
- Algorithms (MeSH), Aspartic Acid Endopeptidases (metabolism), Bacterial Proteins (metabolism), Basidiomycota (metabolism), Basidiomycota (pathogenicity), Fungal Proteins (metabolism), Gene Expression Profiling (MeSH), Helianthus (microbiology), Open Reading Frames (MeSH), Plant Diseases (microbiology), Plant Leaves (microbiology), Protein Sorting Signals (MeSH), Transcriptome (MeSH).
- MESH :
- chemical , metabolism : Aspartic Acid Endopeptidases, Bacterial Proteins, Fungal Proteins.
- metabolism : Basidiomycota.
- microbiology : Helianthus, Plant Diseases, Plant Leaves.
- pathogenicity : Basidiomycota.
- Algorithms, Gene Expression Profiling, Open Reading Frames, Protein Sorting Signals, Transcriptome.
Abstract
BACKGROUND
Many plant pathogen secretory proteins are known to be elicitors or pathogenic factors,which play an important role in the host-pathogen interaction process. Bioinformatics approaches make possible the large scale prediction and analysis of secretory proteins from the Puccinia helianthi transcriptome. The internet-based software SignalP v4.1, TargetP v1.01, Big-PI predictor, TMHMM v2.0 and ProtComp v9.0 were utilized to predict the signal peptides and the signal peptide-dependent secreted proteins among the 35,286 ORFs of the P. helianthi transcriptome.
RESULTS
908 ORFs (accounting for 2.6% of the total proteins) were identified as putative secretory proteins containing signal peptides. The length of the majority of proteins ranged from 51 to 300 amino acids (aa), while the signal peptides were from 18 to 20 aa long. Signal peptidase I (SpI) cleavage sites were found in 463 of these putative secretory signal peptides. 55 proteins contained the lipoprotein signal peptide recognition site of signal peptidase II (SpII). Out of 908 secretory proteins, 581 (63.8%) have functions related to signal recognition and transduction, metabolism, transport and catabolism. Additionally, 143 putative secretory proteins were categorized into 27 functional groups based on Gene Ontology terms, including 14 groups in biological process, seven in cellular component, and six in molecular function. Gene ontology analysis of the secretory proteins revealed an enrichment of hydrolase activity. Pathway associations were established for 82 (9.0%) secretory proteins. A number of cell wall degrading enzymes and three homologous proteins specific to Phytophthora sojae effectors were also identified, which may be involved in the pathogenicity of the sunflower rust pathogen.
CONCLUSIONS
This investigation proposes a new approach for identifying elicitors and pathogenic factors. The eventual identification and characterization of 908 extracellularly secreted proteins will advance our understanding of the molecular mechanisms of interactions between sunflower and rust pathogen and will enhance our ability to intervene in disease states.
DOI: 10.1186/s12859-017-1577-0
PubMed: 28284182
PubMed Central: PMC5346188
Links to Exploration step
pubmed:28284182Le document en format XML
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Bioinformatics approaches make possible the large scale prediction and analysis of secretory proteins from the Puccinia helianthi transcriptome. The internet-based software SignalP v4.1, TargetP v1.01, Big-PI predictor, TMHMM v2.0 and ProtComp v9.0 were utilized to predict the signal peptides and the signal peptide-dependent secreted proteins among the 35,286 ORFs of the P. helianthi transcriptome.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>908 ORFs (accounting for 2.6% of the total proteins) were identified as putative secretory proteins containing signal peptides. The length of the majority of proteins ranged from 51 to 300 amino acids (aa), while the signal peptides were from 18 to 20 aa long. Signal peptidase I (SpI) cleavage sites were found in 463 of these putative secretory signal peptides. 55 proteins contained the lipoprotein signal peptide recognition site of signal peptidase II (SpII). Out of 908 secretory proteins, 581 (63.8%) have functions related to signal recognition and transduction, metabolism, transport and catabolism. Additionally, 143 putative secretory proteins were categorized into 27 functional groups based on Gene Ontology terms, including 14 groups in biological process, seven in cellular component, and six in molecular function. Gene ontology analysis of the secretory proteins revealed an enrichment of hydrolase activity. Pathway associations were established for 82 (9.0%) secretory proteins. A number of cell wall degrading enzymes and three homologous proteins specific to Phytophthora sojae effectors were also identified, which may be involved in the pathogenicity of the sunflower rust pathogen.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>This investigation proposes a new approach for identifying elicitors and pathogenic factors. The eventual identification and characterization of 908 extracellularly secreted proteins will advance our understanding of the molecular mechanisms of interactions between sunflower and rust pathogen and will enhance our ability to intervene in disease states.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">28284182</PMID><DateCompleted><Year>2017</Year><Month>08</Month><Day>29</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2105</ISSN><JournalIssue CitedMedium="Internet"><Volume>18</Volume><Issue>1</Issue><PubDate><Year>2017</Year><Month>Mar</Month><Day>11</Day></PubDate></JournalIssue><Title>BMC bioinformatics</Title><ISOAbbreviation>BMC Bioinformatics</ISOAbbreviation></Journal><ArticleTitle>The prediction of a pathogenesis-related secretome of Puccinia helianthi through high-throughput transcriptome analysis.</ArticleTitle><Pagination><MedlinePgn>166</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s12859-017-1577-0</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Many plant pathogen secretory proteins are known to be elicitors or pathogenic factors,which play an important role in the host-pathogen interaction process. Bioinformatics approaches make possible the large scale prediction and analysis of secretory proteins from the Puccinia helianthi transcriptome. The internet-based software SignalP v4.1, TargetP v1.01, Big-PI predictor, TMHMM v2.0 and ProtComp v9.0 were utilized to predict the signal peptides and the signal peptide-dependent secreted proteins among the 35,286 ORFs of the P. helianthi transcriptome.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">908 ORFs (accounting for 2.6% of the total proteins) were identified as putative secretory proteins containing signal peptides. The length of the majority of proteins ranged from 51 to 300 amino acids (aa), while the signal peptides were from 18 to 20 aa long. Signal peptidase I (SpI) cleavage sites were found in 463 of these putative secretory signal peptides. 55 proteins contained the lipoprotein signal peptide recognition site of signal peptidase II (SpII). Out of 908 secretory proteins, 581 (63.8%) have functions related to signal recognition and transduction, metabolism, transport and catabolism. Additionally, 143 putative secretory proteins were categorized into 27 functional groups based on Gene Ontology terms, including 14 groups in biological process, seven in cellular component, and six in molecular function. Gene ontology analysis of the secretory proteins revealed an enrichment of hydrolase activity. Pathway associations were established for 82 (9.0%) secretory proteins. A number of cell wall degrading enzymes and three homologous proteins specific to Phytophthora sojae effectors were also identified, which may be involved in the pathogenicity of the sunflower rust pathogen.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">This investigation proposes a new approach for identifying elicitors and pathogenic factors. 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| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Corpus/biblio.hfd \
| NlmPubMed2Wicri -a RustEffectorV1
| This area was generated with Dilib version V0.6.37. |  |