Interdisciplinary studies on Coxiella burnetii: From molecular to cellular, to host, to one health research.

The Q-GAPS (Q fever GermAn interdisciplinary Program for reSearch) consortium was launched in 2017 as a German consortium of more than 20 scientists with exceptional expertise, competence, and substantial knowledge in the field of the Q fever pathogen Coxiella (C.) burnetii. C. burnetii exemplifies as a zoonotic pathogen the challenges of zoonotic disease control and prophylaxis in human, animal, and environmental settings in a One Health approach. An interdisciplinary approach to studying the pathogen is essential to address unresolved questions about the epidemiology, immunology, pathogenesis, surveillance, and control of C. burnetii. In more than five years, Q-GAPS has provided new insights into pathogenicity and interaction with host defense mechanisms. The consortium has also investigated vaccine efficacy and application in animal reservoirs and identified expanded phenotypic and genotypic characteristics of C. burnetii and their epidemiological significance. In addition, conceptual principles for controlling, surveilling, and preventing zoonotic Q fever infections were developed and prepared for specific target groups. All findings have been continuously integrated into a Web-based, interactive, freely accessible knowledge and information platform (www.q-gaps.de), which also contains Q fever guidelines to support public health institutions in controlling and preventing Q fever. In this review, we will summarize our results and show an example of how an interdisciplinary consortium provides knowledge and better tools to control a zoonotic pathogen at the national level.

Sensitivities of a Rapid Test Versus an ELISA Kit for Detecting Anti-SARS-CoV-2 IgM/IgG in Sera from an Egyptian Cohort.

This study aimed to compare diagnostic sensitivities of a rapid test (Rt) and an ELISA kit for detecting anti-SARS-CoV-2 IgM/IgG in virus-RT-PCR-positive (VPP) and virus-RT-PCR-unchecked (VPU) subjects in an Egyptian cohort during the first wave of SARS-CoV-2 infection. The results revealed higher sensitivity of the Rt for detecting IgM/IgG in the VPP subjects. Both the Rt and ELISA showed identical sensitivities for IgM detection in the VPU subjects. The ELISA was more sensitive for detecting IgG in the VPU subjects. Generally, within both the VPP and the VPU groups, Rt was more sensitive for detecting IgM/IgG among the symptomatic (S) compared to asymptomatic (AS) subjects than ELISA. Within the VPP group, the Rt was more sensitive for detecting both IgM/IgG among the AS subjects than ELISA. In the VPU group, the Rt was more sensitive for detecting IgM among the S subjects than ELISA. The ELISA was more sensitive for detecting IgM/IgG among AS subjects than the Rt. From these results we concluded that, despite the limitation of sample size, this study indicates suitability of the used Rt for detecting anti-SARS-CoV-2 IgM/IgG among S subjects and sheds light on possibility of relying on the used ELISA for IgG detection among AS human subjects.

CoxBase: an Online Platform for Epidemiological Surveillance, Visualization, Analysis, and Typing of Coxiella burnetii Genomic Sequences.

Q (query) fever is an infectious zoonotic disease caused by the Gram-negative bacterium Coxiella burnetii. Although the disease has been studied for decades, it still represents a threat due to sporadic outbreaks across farms in Europe. The absence of a central platform for Coxiella typing data management is an important epidemiological gap that is relevant in the case of an outbreak. To fill this gap, we have designed and implemented an online, open-source, web-based platform called CoxBase (https://coxbase.q-gaps.de). This platform includes a database that holds genotyping information on more than 400 Coxiella isolates alongside metadata that annotate them. We have also implemented features for in silico genotyping of completely or minimally assembled Coxiella sequences using five different typing methods, querying of existing isolates, visualization of isolate geodata via aggregation on a world map, and submission of new isolates. We tested our in silico typing method on 50 Coxiella genomes downloaded from the RefSeq database, and we successfully genotyped all genomes except for cases where the sequence quality was poor. We identified new spacer sequences using our implementation of the multispacer sequence typing (MST) in silico typing method and established adaA gene phenotypes for all 50 genomes as well as their plasmid types. IMPORTANCE Q fever is a zoonotic disease that is a source of active epidemiological concern due to its persistent threat to public health. In this project, we have identified areas in the field of Coxiella research, especially regarding public health and genomic analysis, where there is an inadequacy of resources to monitor, organize, and analyze genomic data from C. burnetii. Subsequently, we have created an open, web-based platform that contains epidemiological information, genome typing functions comprising all the available Coxiella typing methods, and tools for isolate data discovery and visualization that could help address the above-mentioned challenges. This is the first platform to combine all disparate genotyping systems for Coxiella burnetii as well as metadata assets with tools for genomic comparison and analyses. This platform is a valuable resource for laboratory researchers as well as research epidemiologists interested in investigating the relatedness or dissimilarity among C. burnetii strains.