title: BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors.
abstract: Gram-negative pathogenic bacteria inject type III secreted effectors (T3SEs) into host cells to sabotage their immune signaling networks. Because T3SEs constitute a meeting-point of pathogen virulence and host defense, they are of keen interest to host-pathogen interaction research community. To accelerate the identification and functional understanding of T3SEs, we present BEAN 2.0 as an integrated web resource to predict, analyse and store T3SEs. BEAN 2.0 includes three major components. First, it provides an accurate T3SE predictor based on a hybrid approach. Using independent testing data, we show that BEAN 2.0 achieves a sensitivity of 86.05% and a specificity of 100%. Second, it integrates a set of online sequence analysis tools. Users can further perform functional analysis of putative T3SEs in a seamless way, such as subcellular location prediction, functional domain scan and disorder region annotation. Third, it compiles a database covering 1215 experimentally verified T3SEs and constructs two T3SE-related networks that can be used to explore the relationships among T3SEs. Taken together, by presenting a one-stop T3SE bioinformatics resource, we hope BEAN 2.0 can promote comprehensive understanding of the function and evolution of T3SEs.
authors.affiliation: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China.
authors.forename: Xiaobao
authors.initials: X
authors.lastname: Dong
authors.affiliation: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China.
authors.forename: Xiaotian
authors.initials: X
authors.lastname: Lu
authors.affiliation: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China zidingzhang@cau.edu.cn.
authors.forename: Ziding
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D001419:Bacteria / Q000235:genetics / Q000378:metabolism; D058947:Bacterial Secretion Systems / Q000235:genetics / Q000378:metabolism; D019143:Evolution, Molecular; D020407:Internet; D012984:Software
chemical_list: D058947:Bacterial Secretion Systems