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SUMMARY Rapid and accurate profiling of infection-causing pathogens remains a significant challenge in modern health care. Despite advances in molecular diagnostic techniques, blood culture analysis remains the gold standard for diagnosing sepsis. However, this method is too slow and cumbersome to significantly influence the initial management of patients. The swift initiation of precise and targeted antibiotic therapies depends on the ability of a sepsis diagnostic test to capture clinically relevant organisms along with antimicrobial resistance within 1 to 3 h. The administration of appropriate, narrow-spectrum antibiotics demands that such a test be extremely sensitive with a high negative predictive value. In addition, it should utilize small sample volumes and detect polymicrobial infections and contaminants. All of this must be accomplished with a platform that is easily integrated into the clinical workflow. In this review, we outline the limitations of routine blood culture testing and discuss how emerging sepsis technologies are converging on the characteristics of the ideal sepsis diagnostic test. We include seven molecular technologies that have been validated on clinical blood specimens or mock samples using human blood. In addition, we discuss advances in machine learning technologies that use electronic medical record data to provide contextual evaluation support for clinical decision-making.

Phytophthora species secrete a large array of effectors during infection of their host plants. The Crinkler (CRN) gene family encodes a ubiquitous but understudied class of effectors with possible but as of yet unknown roles in infection. To appreciate CRN effector function in Phytophthora, we devised a simple Crn gene identification and annotation pipeline to improve effector prediction rates. We predicted 84 full-length CRN coding genes and assessed CRN effector domain diversity in sequenced Oomycete genomes. These analyses revealed evidence of CRN domain innovation in Phytophthora and expansion in the Peronosporales. We performed gene expression analyses to validate and define two classes of CRN effectors, each possibly contributing to infection at different stages. CRN localisation studies revealed that P. capsici CRN effector domains target the nucleus and accumulate in specific sub-nuclear compartments. Phenotypic analyses showed that few CRN domains induce necrosis when expressed in planta and that one cell death inducing effector, enhances P. capsici virulence on Nicotiana benthamiana. These results suggest that the CRN protein family form an important class of intracellular effectors that target the host nucleus during infection. These results combined with domain expansion in hemi-biotrophic and necrotrophic pathogens, suggests specific contributions to pathogen lifestyles. This work will bolster CRN identification efforts in other sequenced oomycete species and set the stage for future functional studies towards understanding CRN effector functions.