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Spirochetes belonging to the Borrelia (B.) burgdorferi sensu lato complex differ in their resistance to complement-mediated killing, particularly in regard to human serum. In the present study, we elucidate the serum and complement susceptibility of B. valaisiana, a genospecies with the potential to cause Lyme disease in Europe as well as in Asia. Among the investigated isolates, growth of ZWU3 Ny3 was not affected while growth of VS116 and Bv9 was strongly inhibited in the presence of 50% human serum. Analyzing complement activation, complement components C3, C4 and C6 were deposited on the surface of isolates VS116 and Bv9, and similarly the membrane attack complex was formed on their surface. In contrast, no surface-deposited components and no aberrations in cell morphology were detected for serum-resistant ZWU3 Ny3. While further investigating the protective role of bound complement regulators in mediating complement resistance, we discovered that none of the B. valaisiana isolates analyzed bound complement regulators Factor H, Factor H-like protein 1, C4b binding protein or C1 esterase inhibitor. In addition, B. valaisiana also lacked intrinsic proteolytic activity to degrade complement components C3, C3b, C4, C4b, and C5. Taken together, these findings suggest that certain B. valaisiana isolates differ in their capability to resist complement-mediating killing by human serum. The molecular mechanism utilized by B. valaisiana to inhibit bacteriolysis appears not to involve binding of the key host complement regulators of the alternative, classical, and lectin pathways as already known for serum-resistant Lyme disease or relapsing fever borreliae.
Borrelia burgdorferi evades complement-mediated killing by interacting with complement regulators through distinct complement regulator-acquiring surface proteins (CRASPs). Here, we extend our analyses to the contribution of CRASP-4 in mediating complement resistance of B. burgdorferi and its interaction with human complement regulators. CRASP-4 (also known as ErpC) was immobilized onto magnetic beads and used to capture proteins from human serum. Following Western blotting, factor H (CFH), CFH-related protein 1 (CFHR1), CFHR2, and CFHR5 were identified as ligands of CRASP-4. To analyze the impact of native CRASP-4 on mediating survival of serum-sensitive cells in human serum, a B. garinii strain was generated that ectopically expresses CRASP-4. CRASP-4-producing bacteria bound CFHR1, CFHR2, and CFHR5 but not CFH. In addition, transformed spirochetes deposited significant amounts of lethal complement components on their surface and were susceptible to human serum, thus indicating that CRASP-4 plays a subordinate role in complement resistance of B. burgdorferi.
Introduction: Clinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy. Methods and analysis: Planned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter. Scope: general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients. Population: patients (≥18 years) with polypharmacy (≥5 prescriptions). Sample size: initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved. Intervention: complex intervention eMMa. Follow-up: at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa. Outcomes: primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse. Statistical analysis: primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints.