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Record W1922818364 · doi:10.1186/s12864-015-1849-x

EST-based in silico identification and in vitro test of antimicrobial peptides in Brassica napus

2015· article· en· W1922818364 on OpenAlexaff
Tao Ke, Huihui Cao, Junyan Huang, Fan Hu, Jin Huang, Caihua Dong, Xiangdong Ma, Jingyin Yu, Han Mao, Xi Wang, Qiuhong Niu, Feng-Li Hui, Shengyi Liu

Bibliographic record

VenueBMC Genomics · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsMinistry of Agriculture
FundersNational Key Research and Development Program of ChinaSpecial Fund for Agro-scientific Research in the Public InterestNanyang Normal University
KeywordsUniGeneBiologyExpressed sequence tagcDNA libraryIn silicoDefensinGeneticsContigGeneComplementary DNABrassicaComputational biologyBotanyGenome

Abstract

fetched live from OpenAlex

BACKGROUND: Brassica napus is the third leading source of vegetable oil in the world after soybean and oil palm. The accumulation of gene sequences, especially expressed sequence tags (ESTs) from plant cDNA libraries, has provided a rich resource for genes discovery including potential antimicrobial peptides (AMPs). In this study, we used ESTs including those generated from B. napus cDNA libraries of seeds, pathogen-challenged leaves and deposited in the public databases, as a model, to perform in silico identification and consequently in vitro confirmation of putative AMP activities through a highly efficient system of recombinant AMP prokaryotic expression. RESULTS: In total, 35,788 were generated from cDNA libraries of pathogen-challenged leaves and 187,272 ESTs from seeds of B. napus, and the 644,998 ESTs of B. napus were downloaded from the EST database of PlantGDB. They formed 201,200 unigenes. First, all the known AMPs from the AMP databank (APD2 database) were individually queried against all the unigenes using the BLASTX program. A total of 972 unigenes that matched the 27 known AMP sequences in APD2 database were extracted and annotated using Blast2GO program. Among these unigenes, 237 unigenes from B. napus pathogen-challenged leaves had the highest ratio (1.15 %) in this unigene dataset, which is 13 times that of the unigene datasets of B. napus seeds (0.09 %) and 2.3 times that of the public EST dataset. About 87 % of each EST library was lipid-transfer protein (LTP) (32 % of total unigenes), defensin, histone, endochitinase, and gibberellin-regulated proteins. The most abundant unigenes in the leaf library were endochitinase and defensin, and LTP and histone in the pub EST library. After masking of the repeat sequence, 606 peptides that were orthologous matched to different AMP families were found. The phylogeny and conserved structural motifs of seven AMPs families were also analysed. To investigate the antimicrobial activities of the predicted peptides, 31 potential AMP genes belonging to different AMP families were selected to test their antimicrobial activities after bioinformatics identification. The AMP genes were all optimized according to Escherichia coli codon usage and synthetized through one-step polymerase chain reaction method. The results showed that 28 recombinant AMPs displayed expected antimicrobial activities against E. coli and Micrococcus luteus and Sclerotinia sclerotiorum strains. CONCLUSION: The study not only significantly expanded the number of known/predicted peptides, but also contributed to long-term plant genetic improvement for increased resistance to diverse pathogens of B.napus. These results proved that the high-throughput method developed that combined an in silico procedure with a recombinant AMP prokaryotic expression system is considerably efficient for identification of new AMPs from genome or EST sequence databases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.232
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2015
Admission routes1
Has abstractyes

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