Pseudomonas aeruginosa is a Gram-negative, opportunistic pathogen that causes chronic and acute infections in immunocompromised patients. Most P. aeruginosa strains encode an active type III secretion system (T3SS), utilized by the bacteria to deliver effector proteins from the bacterial cell directly into the cytoplasm of the host cell. Four T3SS effectors have been discovered and extensively studied in P. aeruginosa: ExoT, ExoS, ExoU, and ExoY. This is especially intriguing in light of P. aeruginosa’s ability to infect a wide range of hosts. We therefore hypothesized that additional T3SS effectors that have not yet been discovered are encoded in the genome of P. aeruginosa. Here, we applied a machine learning classification algorithm to identify novel P. aeruginosa effectors. In this approach, various types of data are integrated to differentiate effectors from the rest of the open reading frames of the bacterial genome. Due to the lack of a sufficient learning set of positive effectors, our machine learning algorithm integrated genomic information from another Pseudomonas species and utilized dozens of features accounting for various aspects of the effector coding genes and their products. Twelve top-ranking predictions were experimentally tested for T3SS-specific translocation, leading to the discovery of two novel T3SS effectors. We demonstrate that these effectors are not part of the injection structural complex and report initial efforts toward their characterization. IMPORTANCE Pseudomonas aeruginosa uses a type III secretion system (T3SS) to secrete toxic proteins, termed effectors, directly into the cytoplasm of the host cell. The activation of this secretion system is correlated with disease severity and patient death. Compared with many other T3SS-utilizing pathogenic bacteria, P. aeruginosa has a fairly limited arsenal of effectors that have been identified. This is in sharp contrast with the wide range of hosts that this bacterium can infect. The discovery of two novel effectors described here is an important step toward better understanding of the virulence and host evasion mechanisms adopted by this versatile pathogen and may provide novel approaches to treat P. aeruginosa infections.
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© 2015 Burstein et al.