The Type III Effectome of the Symbiotic Bradyrhizobium vignae Strain ORS3257. - Busset, Nicolas; Gully, Djamel; Teulet, Albin; Fardoux, Joël; Camuel, Alicia; Cornu, David; Severac, Dany; Giraud, Eric; Mergaert, Peter (MDPI AG, 2021)
Many Bradyrhizobium strains are able to establish a Nod factor-independent symbiosis with the leguminous plant Aeschynomene indica by the use of a type III secretion system (T3SS). Recently, an important advance in the understanding of the molecular factors supporting this symbiosis has been achieved by the in silico identification and functional characterization of 27 putative T3SS effectors (T3Es) of Bradyrhizobium vignae ORS3257. In the present study, we experimentally extend this catalog of T3Es by using a multi-omics approach. Transcriptome analysis under non-inducing and inducing conditions in the ORS3257 wild-type strain and the ttsI mutant revealed that the expression of 18 out of the 27 putative effectors previously identified, is under the control of TtsI, the global transcriptional regulator of T3SS and T3Es. Quantitative shotgun proteome analysis of culture supernatant in the wild type and T3SS mutant strains confirmed that 15 of the previously determined candidate T3Es are secreted by the T3SS. Moreover, the combined approaches identified nine additional putative T3Es and one of them was experimentally validated as a novel effector. Our study underscores the power of combined proteome and transcriptome analyses to complement in silico predictions and produce nearly complete effector catalogs. The establishment of the ORS3257 effectome will form the basis for a full appraisal of the symbiotic properties of this strain during its interaction with various host legumes via different processes.
Keywords: Bradyrhizobium; effector; legume symbiosis; nod factor; nodulation; proteome; transcriptome; type III secretion system; Bradyrhizobium; Symbiosis; Type III Secretion Systems; Bacterial Proteins; Gene Expression Regulation, Bacterial; Fabaceae; Transcriptome; Proteome; Gene Expression Profiling; Proteomics