Characterization of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection Clusters Based on Integrated Genomic Surveillance, Outbreak Analysis and Contact Tracing in an Urban Setting.

BACKGROUND: Tracing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission chains is still a major challenge for public health authorities, when incidental contacts are not recalled or are not perceived as potential risk contacts. Viral sequencing can address key questions about SARS-CoV-2 evolution and may support reconstruction of viral transmission networks by integration of molecular epidemiology into classical contact tracing. METHODS: In collaboration with local public health authorities, we set up an integrated system of genomic surveillance in an urban setting, combining a) viral surveillance sequencing, b) genetically based identification of infection clusters in the population, c) integration of public health authority contact tracing data, and d) a user-friendly dashboard application as a central data analysis platform. RESULTS: Application of the integrated system from August to December 2020 enabled a characterization of viral population structure, analysis of 4 outbreaks at a maximum care hospital, and genetically based identification of 5 putative population infection clusters, all of which were confirmed by contact tracing. The system contributed to the development of improved hospital infection control and prevention measures and enabled the identification of previously unrecognized transmission chains, involving a martial arts gym and establishing a link between the hospital to the local population. CONCLUSIONS: Integrated systems of genomic surveillance could contribute to the monitoring and, potentially, improved management of SARS-CoV-2 transmission in the population.

Integrated genomic surveillance enables tracing of person-to-person SARS-CoV-2 transmission chains during community transmission and reveals extensive onward transmission of travel-imported infections, Germany, June to July 2021.

BackgroundTracking person-to-person SARS-CoV-2 transmission in the population is important to understand the epidemiology of community transmission and may contribute to the containment of SARS-CoV-2. Neither contact tracing nor genomic surveillance alone, however, are typically sufficient to achieve this objective.AimWe demonstrate the successful application of the integrated genomic surveillance (IGS) system of the German city of Düsseldorf for tracing SARS-CoV-2 transmission chains in the population as well as detecting and investigating travel-associated SARS-CoV-2 infection clusters.MethodsGenomic surveillance, phylogenetic analysis, and structured case interviews were integrated to elucidate two genetically defined clusters of SARS-CoV-2 isolates detected by IGS in Düsseldorf in July 2021.ResultsCluster 1 (n = 67 Düsseldorf cases) and Cluster 2 (n = 36) were detected in a surveillance dataset of 518 high-quality SARS-CoV-2 genomes from Düsseldorf (53% of total cases, sampled mid-June to July 2021). Cluster 1 could be traced back to a complex pattern of transmission in nightlife venues following a putative importation by a SARS-CoV-2-infected return traveller (IP) in late June; 28 SARS-CoV-2 cases could be epidemiologically directly linked to IP. Supported by viral genome data from Spain, Cluster 2 was shown to represent multiple independent introduction events of a viral strain circulating in Catalonia and other European countries, followed by diffuse community transmission in Düsseldorf.ConclusionIGS enabled high-resolution tracing of SARS-CoV-2 transmission in an internationally connected city during community transmission and provided infection chain-level evidence of the downstream propagation of travel-imported SARS-CoV-2 cases.

Global expression patterns of R-genes in tomato and potato.

Introduction: As key-players of plant immunity, the proteins encoded by resistance genes (R-genes) recognize pathogens and initiate pathogen-specific defense responses. The expression of some R-genes carry fitness costs and therefore inducible immune responses are likely advantageous. To what degree inducible resistance driven by R-genes is triggered by pathogen infection is currently an open question. Methods: In this study we analyzed the expression of 940 R-genes of tomato and potato across 315 transcriptome libraries to investigate how interspecific interactions with microbes influence R-gene expression in plants. Results: We found that most R-genes are expressed at a low level. A small subset of R-genes had moderate to high levels of expression and were expressed across many independent libraries, irrespective of infection status. These R-genes include members of the class of genes called NRCs (NLR required for cell death). Approximately 10% of all R-genes were differentially expressed during infection and this included both up- and down-regulation. One factor associated with the large differences in R-gene expression was host tissue, reflecting a considerable degree of tissue-specific transcriptional regulation of this class of genes. Discussion: These results call into question the widespread view that R-gene expression is induced upon pathogen attack. Instead, a small core set of R-genes is constitutively expressed, imparting upon the plant a ready-to-detect and defend status.