Edgar Badell

Corynebacterium ulcerans is an emerging zoonotic pathogen which causes diphtheria-like infections. Although C. ulcerans is found in multiple domestic and wild animal species, most human cases are linked with pets. Our ability to decipher cross-host species transmission dynamics and to understand the emergence of clinically relevant clones (e.g., diphtheria toxin-positive) is currently hampered by a limited knowledge of C. ulcerans strain diversity and genome evolution. Here, we explore the genomic population structure and evolution of C. ulcerans with 582 isolates from diverse hosts and geographical locations. A newly developed core genome genotyping scheme captures the population structure of C. ulcerans both at deep and shallow phylogenetic levels, uncovering its main sublineages and offering high strain subtyping resolution for epidemiological surveillance. Additionally, we reveal the diversity and distribution of the diphtheria toxin gene (tox), and those of its associated mobile elements. Considering the entire Corynebacterium diphtheriae Species Complex, we find four diphtheria toxin families, five tox-prophage families, and a novel tox-carrying genetic element. We show that some toxin families are shared across Corynebacterium species, revealing tox-prophage cross-species transfer. Our work enhances knowledge on the ecology and evolution of C. ulcerans and provides a genomic framework for tracking the dissemination of emerging sublineages.

Background: Diphtheria, caused by Corynebacterium diphtheriae, reemerges in Europe since 2022. Genomic sequencing can inform on transmission routes and genotypes of concern, but currently, no standard approach exists to detect clinically important genomic features and to interpret emergence in the global C. diphtheriae population framework. Methods: We developed the bioinformatics pipeline diphtOscan (available at https://gitlab.pasteur.fr/BEBP/diphtoscan) to extract from genomes of Corynebacteria of the diphtheriae species complex, medically relevant features including tox gene presence and disruption. We analyzed 101 human C. diphtheriae isolates collected in 2022 in metropolitan and overseas France (France-2022). To define the population background of this emergence, we sequenced 379 additional isolates (mainly from France, 2018-2021) and collated 870 publicly-available genomes. Results: The France-2022 isolates comprised 45 tox-positive (44 toxigenic) isolates, mostly imported, belonging to 10 sublineages (tox-positive genomes, with diphtOscan predicting non-toxigenicity in 16.0% of these. 12% of the global isolates, and 43.6% of France-2022 ones, were multidrug resistant. Convergence of toxigenicity with penicillin and erythromycin resistance was observed in 2 isolates from France-2022. Phylogenetic lineages Gravis and Mitis contrasted strikingly in their pathogenicity-associated genes. Conclusions: This work provides a bioinformatics tool and global population framework to analyze C. diphtheriae genomes, revealing important heterogeneities in virulence and resistance features. Emerging genotypes combining toxigenicity and first-line antimicrobial resistance represent novel threats. Genomic epidemiology studies of C. diphtheriae should be intensified globally to improve understanding of reemergence and spatial spread.

Background: Diphtheria, caused by Corynebacterium diphtheriae , reemerges in Europe since 2022. Genomic sequencing can inform on transmission routes and genotypes of concern, but currently, no standard approach exists to detect clinically important genomic features and to interpret emergence in the global C. diphtheriae population framework. Methods: We developed the bioinformatics pipeline DIPHTOSCAN (available at https://gitlab.pasteur.fr/BEBP/diphtoscan ) to extract from genomes of Corynebacteria of the diphtheriae species complex, medically relevant features including tox gene presence and disruption. We analyzed 101 human C. diphtheriae isolates collected in 2022 in metropolitan and overseas France (France-2022). To define the population background of this emergence, we sequenced 379 additional isolates (mainly from France, 2018-2021) and collated 870 publicly-available genomes. Results: The France-2022 isolates comprised 45 tox -positive (44 toxigenic) isolates, mostly imported, belonging to 10 sublineages (tox- positive genomes, with DIPHTOSCAN predicting non-toxigenicity in 16.0% of these. 12% of the global isolates, and 43.6% of France-2022 ones, were multidrug resistant. Convergence of toxigenicity with penicillin and erythromycin resistance was observed in 2 isolates from France-2022. Phylogenetic lineages Gravis and Mitis contrasted strikingly in their pathogenicity-associated genes. Conclusions: This work provides a bioinformatics tool and global population framework to analyze C. diphtheriae genomes, revealing important heterogeneities in virulence and resistance features. Emerging genotypes combining toxigenicity and first-line antimicrobial resistance represent novel threats. Genomic epidemiology studies of C. diphtheriae should be intensified globally to improve understanding of reemergence and spatial spread.

Background: An outbreak of diphtheria, declared in Yemen in October 2017, is still ongoing. Methods. Probable cases were recorded through an electronic diseases early warning system. Microbiological culture, genomic sequencing, antimicrobial susceptibility and toxin production testing were performed. Methods: Probable cases were recorded through an electronic diseases early warning system. Microbiological culture, genomic sequencing, antimicrobial susceptibility and toxin production testing were performed. Findings: The Yemen diphtheria outbreak developed in three epidemic waves, which affected nearly all governorates (provinces) of Yemen, with 5701 probable cases and 330 deaths (October 2017 - April 2020). The median age of patients was 12 years (range, 0.17-80). Virtually all outbreak isolates (40 of 43 tested ones) produced the diphtheria toxin. We observed low level of antimicrobial resistance to penicillin. We identified six separate Corynebacterium diphtheriae phylogenetic sublineages, three of which are genetically related to isolates from Saudi Arabia and Somalia. The predominant sublineage was resistant to trimethoprim and was associated with unique genomic features, more frequent neck swelling ( p =0.002) and a younger age of patients ( p =0.06). Its evolutionary rate was estimated at 1.67 × 10 ⁻⁶ substitutions per site year ^-1 , placing its most recent common ancestor in 2015, and indicating silent circulation of C. diphtheriae in Yemen earlier than outbreak declaration. Interpretation: We disclose clinical, epidemiological and microbiological characteristics of one of the largest contemporary diphtheria outbreaks and demonstrate clinically relevant heterogeneity of C. diphtheriae isolates, underlining the need for laboratory capacity and real-time microbiological analyses to inform prevention, treatment and control of diphtheria. Funding: This work was supported by institutional funding from the National Centre of the Public Health Laboratories (Sanaa, Yemen) and Institut Pasteur (Paris, France) and by the French Government Investissement d ‘Avenir Program.

Introduction. Diphtheria is caused by toxigenic strains of Corynebacterium diphtheriae , Corynebacterium ulcerans and Corynebacterium pseudotuberculosis . For diagnostic purposes, species identification and detection of toxigenic strains (diphtheria toxin (tox)-positive strains) is typically performed using end-point PCR. A faster quadruplex real-time PCR (qPCR) was recently developed (De Zoysa et al. J . Med . Microbiol. 2016;65(12):1521–1527). Aims. We aimed to improve the quadruplex method by adding a 16S rRNA gene target as an internal processing control, providing confirmation of the presence of bacterial DNA in the assays, thus avoiding the possibility of false-negative reporting. Methodology. Universal 16S rRNA gene primers and a probe were defined. The novel method was tested using 36 bacterial isolates and 17 clinical samples. Experimental robustness to temperature and reagent concentration variations was assessed. Results. The method allows detection of the tox gene and distinguishing C. diphtheriae (including the newly described species Corynebacterium belfantii) from C. ulcerans and C. pseudotuberculosis . Complete diagnostic specificity, sensitivity and experimental robustness were demonstrated. The lower limit of detection for C. diphtheriae , C. ulcerans and tox targets was 1.86 genome copies per 5 µl reaction volume. The method was successfully used on two distinct qPCR technologies (LightCycler 480, Roche Diagnostics and Rotor-Gene Q, Qiagen) and in two laboratories (Institut Pasteur, Paris, France and Public Health England – National Infection Service, London, UK). Conclusion. This work describes validation of the improved qPCR quadruplex method and supports its implementation for the biological diagnosis of diphtheria.

Diphtheria is caused by toxigenic strains of Corynebacterium diphtheriae, Corynebacterium ulcerans and Corynebacterium pseudotuberculosis . For diagnostic purposes, species identification and detection of toxigenic strains (diphtheria toxin (tox)-positive strains) is typically performed using end-point PCR. A faster quadruplex real-time PCR (qPCR) was recently developed (De Zoysa et al . J Med Microbiol. 2016 65(12):1521-1527). Here, we present an improvement of the quadruplex method, in which a 16S rRNA gene target was added as an internal processing control, providing confirmation of the presence of bacterial DNA in the assays. This improved qPCR method was validated using 36 bacterial isolates and 16 clinical samples. The method allows detection of the tox gene and distinguishing C. diphtheriae (including the newly described species C. belfantii ) from C. ulcerans and C. pseudotuberculosis . Complete diagnostic specificity, sensitivity and experimental robustness of the method to temperature and reagent concentration variations were demonstrated. The lower limit of detection for C. diphtheriae, C. ulcerans and tox targets was 1.86 genome copies per 5 μL reaction volume. Finally, the method was successfully used on two distinct qPCR technologies (LightCycler 480, Roche Diagnostics and Rotor-Gene Q, Qiagen) and in two laboratories (Institut Pasteur, Paris, France and Public Health England – National Infection Service, London, UK). This work describes validation of the improved qPCR quadruplex method and supports its implementation for the biological diagnosis of diphtheria.

Cystic fibrosis (CF) patients are commonly colonized by bacterial pathogens, which can induce persistent lung inflammation and may contribute to clinical deterioration. Colonization of CF patients and cross-transmission by Corynebacterium diphtheriae has not been reported so far. The aim of this article was to investigate the possibility of a cross transmission of C. diphtheriae biovar Belfanti between four patients of a CF center. C. diphtheriae biovar belfanti (now formally called C. belfantii ) isolates were collected from four patients in a single CF care center over a 6 years period and analyzed by microbiological methods and whole genome sequencing. Epidemiological links among patients were investigated. Ten isolates were collected from 4 patients. Whole genome sequencing of one isolate from each patient showed that a single strain was shared among them. In addition, one patient had the same strain on two consecutive samplings nine months apart. The strain was non-toxigenic and was susceptible to most antimicrobial agents. Ciprofloxacin resistance was observed in one patient. Transmission of the strain among patients was supported by the occurrence of same-day visits to the CF center. This study demonstrates colonization of CF patients by C. diphtheriae biovar Belfanti ( C. belfantii ) and shows persistence and transmission of a unique strain during at least six years in a single CF patient care center. Previous meeting presentations: The information in this work was not previously presented in any meeting. Accession numbers: The genomic sequence data generated in this work were submitted to the European Nucleotide Archive and are available from the International Nucleotide Sequence Database Collaboration (NCBI/ENA/DDBJ) databases under project accession number PRJEB28372 and run data accession numbers ERR2757916 to ERR2757921.