Multi-omics approach identifies novel pathogen-derived prognostic biomarkers in patients with Pseudomonas aeruginosa bloodstream infection

Willmann, M.; Goettig, S.; Bezdan, D.; Macek, B.; Velic, A.; Marschal, M.; Vogel, W.; Flesch, I.; Markert, U.; Schmidt, A.; Kuebler, P.; Haug, M.; Javed, M.; Jentzsch, B.; Oberhettinger, P.; Schuetz, M.; Bohn, E.; Sonnabend, M.; Klein, K.; Autenrieth, I.; Ossowski, S.; Schwarz, S.; Peter, S.

doi:10.1101/309898

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bioRxiv · 10.1101/309898

Multi-omics approach identifies novel pathogen-derived prognostic biomarkers in patients with Pseudomonas aeruginosa bloodstream infection

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Abstract

Pseudomonas aeruginosa is a human pathogen that causes health-care associated blood stream infections (BSI). Although P. aeruginosa BSI are associated with high mortality rates, the clinical relevance of pathogen-derived prognostic biomarker to identify patients at risk for unfavorable outcome remains largely unexplored. We found novel pathogen-derived prognostic biomarker candidates by applying a multi-omics approach on a multicenter sepsis patient cohort. Multi-level Cox regression was used to investigate the relation between patient characteristics and pathogen features (2298 accessory genes, 1078 core protein levels, 107 parsimony-informative variations in reported virulence factors) with 30-day mortality. Our analysis revealed that presence of the helP gene encoding a putative DEAD-box helicase was independently associated with a fatal outcome (hazard ratio 2.01, p = 0.05). helP is located within a region related to the pathogenicity island PAPI-1 in close proximity to a pil gene cluster, which has been associated with horizontal gene transfer. Besides helP, elevated protein levels of the bacterial flagellum protein FliL (hazard ratio 3.44, p < 0.001) and of a bacterioferritin-like protein (hazard ratio 1.74, p = 0.003) increased the risk of death, while high protein levels of a putative aminotransferase were associated with an improved outcome (hazard ratio 0.12, p < 0.001). The prognostic potential of biomarker candidates and clinical factors was confirmed with different machine learning approaches using training and hold-out datasets. The helP genotype appeared the most attractive biomarker for clinical risk stratification due to its relevant predictive power and ease of detection.

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Willmann, M., Goettig, S., Bezdan, D., Macek, B., Velic, A., Marschal, M., Vogel, W., Flesch, I., Markert, U., Schmidt, A., Kuebler, P., Haug, M., Javed, M., Jentzsch, B., Oberhettinger, P., Schuetz, M., Bohn, E., Sonnabend, M., Klein, K., Autenrieth, I., Ossowski, S., Schwarz, S., Peter, S.. 2018-04-28. Multi-omics approach identifies novel pathogen-derived prognostic biomarkers in patients with Pseudomonas aeruginosa bloodstream infection. https://doi.org/10.1101/309898

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