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BackgroundThe need for effective public health surveillance systems to track virus spread for targeted interventions was highlighted during the COVID-19 pandemic. It spurred an interest in the use of spatiotemporal clustering and genomic analyses to identify high-risk areas and track the spread of the SARS-CoV-2 virus. However, these two approaches are rarely combined in surveillance systems to complement each one's limitations; spatiotemporal clustering approaches usually consider only one source of virus transmission (i.e., the residential setting) to detect case clusters, while genomic studies require significant resources and processing time that can delay decision-making. Here, we clarify the differences and possible synergies of these two approaches in the context of infectious disease surveillance systems by investigating to what extent geographically-defined clusters are confirmed as transmission clusters based on genome sequences, and how genomic-based analyses can improve the epidemiological investigations associated with spatiotemporal cluster detection.MethodsFor this purpose, we sequenced the SARS-CoV-2 genomes of 172 cases that were part of a collection of spatiotemporal clusters found in a Swiss state (Vaud) during the first epidemic wave. We subsequently examined intra-cluster genetic similarities and spatiotemporal distributions across virus genotypes.ResultsOur results suggest that the congruence between the two approaches might depend on geographic features of the area (rural/urban) and epidemic context (e.g., lockdown). We also identified two potential superspreading events that started from cases in the main urban area of the state, leading to smaller spreading events in neighboring regions, as well as a large spreading in a geographically-isolated area. These superspreading events were characterized by specific mutations assumed to originate from Mulhouse and Milan, respectively. Our analyses propose synergistic benefits of using two complementary approaches in public health surveillance, saving resources and improving surveillance efficiency.

Whole genome sequencing (WGS) enables high resolution typing of bacteria up to the single nucleotide polymorphism (SNP) level. WGS is used in clinical microbiology laboratories for infection control, molecular surveillance and outbreak analyses. Given the large palette of WGS reagents and bioinformatics tools, the Swiss clinical bacteriology community decided to conduct a ring trial (RT) to foster harmonization of NGS-based bacterial typing. The RT aimed at assessing methicillin-susceptible Staphylococcus aureus strain relatedness from WGS and epidemiological data. The RT was designed to disentangle the variability arising from differences in sample preparation, SNP calling and phylogenetic methods. Nine laboratories participated. The resulting phylogenetic tree and cluster identification were highly reproducible across the laboratories. Cluster interpretation was, however, more laboratory dependent, suggesting that an increased sharing of expertise across laboratories would contribute to further harmonization of practices. More detailed bioinformatic analyses unveiled that while similar clusters were found across laboratories, these were actually based on different sets of SNPs, differentially retained after sample preparation and SNP calling procedures. Despite this, the observed number of SNP differences between pairs of strains, an important criterion to determine strain relatedness given epidemiological information, was similar across pipelines for closely related strains when restricting SNP calls to a common core genome defined by S. aureus cgMLST schema. The lessons learned from this pilot study will serve the implementation of larger-scale RT, as a mean to have regular external quality assessments for laboratories performing WGS analyses in a clinical setting.

Corynebacterium diphtheriae is the etiological agent of diphtheria, a disease caused by the presence of the diphtheria toxin. However, an increasing number of records report non-toxigenic C. diphtheriae infections. Here, a C. diphtheriae strain was recovered from a patient with a past history of bronchiectasis who developed a severe tracheo-bronchitis with multiple whitish lesions of the distal trachea and the mainstem bronchi. Whole-genome sequencing (WGS), performed in parallel with PCR targeting the toxin gene and the Elek test, provided clinically relevant results in a short turnaround time, showing that the isolate was non-toxigenic. A comparative genomic analysis of the new strain (CHUV2995) with 56 other publicly available genomes of C. diphtheriae revealed that the strains CHUV2995, CCUG 5865 and CMCNS703 share a lower average nucleotide identity (ANI) (95.24 to 95.39%) with the C. diphtheriae NCTC 11397T reference genome than all other C. diphtheriae genomes (>98.15%). Core genome phylogeny confirmed the presence of two monophyletic clades. Based on these findings, we propose here two new C. diphtheriae subspecies to replace the lineage denomination used in previous multilocus sequence typing studies: C. diphtheriae subsp. lausannense subsp. nov. (instead of lineage-2), regrouping strains CHUV2995, CCUG 5865, and CMCNS703, and C. diphtheriae subsp. diphtheriae subsp. nov, regrouping all other C. diphtheriae in the dataset (instead of lineage-1). Interestingly, members of subspecies lausannense displayed a larger genome size than subspecies diphtheriae and were enriched in COG categories related to transport and metabolism of lipids (I) and inorganic ion (P). Conversely, they lacked all genes involved in the synthesis of pili (SpaA-type, SpaD-type and SpaH-type), molybdenum cofactor and of the nitrate reductase. Finally, the CHUV2995 genome is particularly enriched in mobility genes and harbors several prophages. The genome encodes a type II-C CRISPR-Cas locus with 2 spacers that lacks csn2 or cas4, which could hamper the acquisition of new spacers and render strain CHUV2995 more susceptible to bacteriophage infections and gene acquisition through various mechanisms of horizontal gene transfer.

The Chlamydiae phylum exclusively encompasses bacteria sharing a similar obligate intracellular life cycle. Existing 16S rDNA data support a high diversity within the phylum, however genomic data remain scarce owing to the difficulty in isolating strains using culture systems with eukaryotic cells. Yet, Chlamydiae genome data extracted from large scale metagenomic studies might help fill this gap. This work compares 33 cultured and 27 environmental, uncultured chlamydial genomes, in order to clarify the phylogenetic relatedness of the new chlamydial clades and to investigate the genetic diversity of the Chlamydiae phylum. The analysis of published chlamydial genomes from metagenomics bins and single cell sequencing allowed the identification of seven new deeply branching chlamydial clades sharing genetic hallmarks of parasitic Chlamydiae. Comparative genomics suggests important biological differences between those clades, including loss of many proteins involved in cell division in the genus Similichlamydia, and loss of respiratory chain and tricarboxylic acid cycle in several species. Comparative analyses of chlamydial genomes with two proteobacterial orders, the Rhizobiales and the Rickettsiales showed that genomes of different Rhizobiales families are much more similar than genomes of different Rickettsiales families. On the other hand, the chlamydial 16S rRNAs exhibit a higher sequence conservation than their Rickettsiales counterparts, while chlamydial proteins exhibit increased sequence divergence. Studying the diversity and genome plasticity of the entire Chlamydiae phylum is of major interest to better understand the emergence and evolution of this ubiquitous and ancient clade of obligate intracellular bacteria.