Construction And Application Of Protein-Protein Interactions Network Between Forage Plants And Pathogens Based On Bioinformatics

Forage plants are various plant resources with certain nutritional value that can be eaten by livestock.They are the material basis for the development of herbivorous livestock and play a very important role in improving and protecting the living environment of human beings.Forage plants face different degrees of biological(such as pests and diseases)and abiotic stresses(such as drought,light and temperature,salt and heavy metals,etc.)during their growth and development.The production of forage plants has a very negative impact.Proteomics is one of the important tools to study plant stress response,especially the protein-protein interactions(PPIs)between plant and pathogen(including the interspecific and forage plant protein interactions of host plant-pathogen two groups),as the key to regulating hormone synthesis and function,adversity signal transduction,and activation of defense genes has attracted more and more attention from researchers at home and abroad.With the rapid development of high-throughput biological experimental technologies,researchers can use a variety of experimental methods to detect PPIs.However,biological experimental methods require a lot of manpower and material resources,are cumbersome and extremely time-consuming,and large-scale identification of protein interactions in forage plants is far from widespread.In recent years,with the continuous reduction of the cost of gene sequencing,almost all major forage plants have been sequenced whole genomes,and the amount of forage plant protein sequence data has increased rapidly,which provides a data basis for the development of computational methods to predict PPIs in forage plants.This research focuses on the scientific problem of identification of forage plant-pathogen protein interactions,and intends to solve the problem of incomplete forage plant PPIs map.The large-scale prediction of plant PPIs will help to deeply understand the mechanism of plant growth and development and the occurrence mechanism of plant disease resistance,and provide important support for the research on forage plant quality,yield formation and stress resistance molecular mechanism.Research has important scientific research value and application prospects.This research mainly includes the following aspects:(1)Developed a computational prediction model called ABSPPI to predict protein-protein interactions between Medicago sativa and Pseudomonas syringae based on protein sequence information and a PPIs network is constructed to systematically understand forage plants and pathogen interactions.We successful discovery 512 up-regulated genes and 361 down-regulated genes involved in the process of inducing disease resistance in plants.This study provides an in-depth understanding of the defense mechanism of Medicago sativa against Pseudomonas syringae,as well as the resistance and susceptibility of Medicago sativa to bacterial stem blight.(2)Developed a bioinformatics tool ABSPPI for predicting Medicago sativa and Pseudomonas syringae PPIs,providing a user-friendly online web server for plant science researchers(http://120.77.11.78/ABSPPI),which provides useful support for the further study of the sequence-interaction-function relationship between forage plants and pathogens.(3)A sequence-based computational method CPIELA for the prediction of three model plant PPIs is proposed.The performance evaluation on three model plant datasets of Arabidopsis,Zea mays and Medicago truncatula demonstrated that the proposed CPIELA model had better predictive performance.The developed simple and easy-to-use online web server CPIELA(http://120.77.11.78/CPIELA)can accurately and efficiently predict forage plants PPIs,thereby promoting the development of forage plant proteomics.(4)A three-model plant protein interaction prediction model DWPPI based on network analysis was proposed.In the case study,14 of the top 20 plant-protein interaction pairs predicted by the DWPPI model matched those reported by biological experiments.The DWPPI model can be used as an effective complementary method for the experimental detection of protein interactions in forage plants,bringing new insights into the discovery and exploration of plant molecular interactions.