Quality assurance for genotyping and resistance testing of Clostridium (Clostridioides) difficile isolates - Experiences from the first inter-laboratory ring trial in four German speaking countries

Update on Commonly Used Molecular Typing Methods for Clostridioides difficile

This review aims to provide a comprehensive overview of the significant Clostridioides difficile molecular typing techniques currently employed in research and medical communities. The main objectives of this review are to describe the key molecular typing methods utilized in C. difficile studies and to highlight the epidemiological characteristics of the most prevalent strains on a global scale. Geographically distinct regions exhibit distinct strain types of C. difficile, with notable concordance observed among various typing methodologies. The advantages that next-generation sequencing (NGS) offers has changed epidemiology research, enabling high-resolution genomic analyses of this pathogen. NGS platforms offer an unprecedented opportunity to explore the genetic intricacies and evolutionary trajectories of C. difficile strains. It is relevant to acknowledge that novel routes of transmission are continually being unveiled and warrant further investigation, particularly in the context of zoonotic implications and environmental contamination.

Prevalence, Antimicrobial Resistance and Toxin-Encoding Genes of Clostridioides difficile from Environmental Sources Contaminated by Feces

Clostridioides difficile (C. difficile) is the most common pathogen causing antibiotic-associated intestinal diseases in humans and some animal species, but it can also be present in various environments outside hospitals. Thus, the objective of this study was to investigate the presence and the characteristics of toxin-encoding genes and antimicrobial resistance of C. difficile isolates from different environmental sources. C. difficile was found in 32 out of 81 samples (39.50%) after selective enrichment of spore-forming bacteria and in 45 samples (55.56%) using a TaqMan-based qPCR assay. A total of 169 C. difficile isolates were recovered from those 32 C. difficile-positive environmental samples. The majority of environmental C. difficile isolates were toxigenic, with many (88.75%) positive for tcdA and tcdB. Seventy-four isolates (43.78%) were positive for binary toxins, cdtA and cdtB, and 19 isolates were non-toxigenic. All the environmental C. difficile isolates were susceptible to vancomycin and metronidazole, and most isolates were resistant to ciprofloxacin (66.86%) and clindamycin (46.15%), followed by moxifloxacin (13.02%) and tetracycline (4.73%). Seventy-five isolates (44.38%) showed resistance to at least two of the tested antimicrobials. C. difficile strains are commonly present in various environmental sources contaminated by feces and could be a potential source of community-associated C. difficile infections.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

MALDI-TOF MS: An alternative approach for ribotyping Clostridioides difficile isolates in Brazil

Clostridioides difficile is an important organism causing healthcare-associated infections. It has been documented that specific strains caused multiple outbreaks globally, and patients infected with those strains are more likely to develop severe C. difficile infection (CDI). With the appearance of a variant strain, BI/NAP1 ribotype 027, responsible for several outbreaks and high mortality rates worldwide, the epidemiology of the CDI changed drastically in the United States, Europe, and some Latin American countries. Although the epidemic strain 027 was not yet detected in Brazil, there are ribotypes exclusively found in the country, such as, 131, 132, 133, 135, 142 and 143, which are responsible for outbreaks in Brazilian hospitals and nursing homes. Although PCR-ribotyping is the most used method in epidemiology studies of C. difficile, it is not available in Brazil. This study aimed to develop and validate an in-house database for detecting C. difficile ribotypes, usually involved in CDI in Brazilian hospitals, by using MALDI-TOF MS. A database with 19 different ribotypes, 13 with worldwide circulation and 6 Brazilian-restricted, was created based on 27 spectra readings of each ribotype. After BioNumerics analysis, neighbor-joining trees revealed that spectra were distributed in clusters according to ribotypes, showing that MALDI-TOF MS could discriminate all 19 ribotypes. Moreover, each ribotype showed a different profile with 42 biomarkers detected in total. Based on their intensity and occurrence, 13 biomarkers were chosen to compose ribotype-specific profiles, and in silico analysis showed that most of these biomarkers were uncharacterized proteins or well-conserved peptides, such as ribosomal proteins. A double-blind assessment using the 13 biomarkers correctly assigned the ribotype in 73% of the spectra analyzed, with 94%-100% of correct hits for 027 and for Brazilian ribotypes. Although further analyses are required, our results show that MALDI-TOF MS might be a reliable, fast and feasible alternative for epidemiological surveillance of C. difficile in Brazil.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain "live" (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines' implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

High Prevalence of Genetically Related Clostridium Difficile Strains at a Single Hemato-Oncology Ward Over 10 Years

Aims: Clostridium difficile (C. difficile) infection (CDI) is the main cause of healthcare-associated infectious diarrhea. We used whole-genome sequencing (WGS) to measure the prevalence and genetic variability of C. difficile at a single hemato-oncology ward over a 10 year period. Methods: Between 2008 and 2018, 2077 stool samples were obtained from diarrheal patients hospitalized at the Department of Lymphoma; of these, 618 were positive for toxin A/B. 140 isolates were then subjected to WGS on Ion Torrent PGM sequencer. Results: 36 and 104 isolates were recovered from 36 to 46 patients with single and multiple CDIs, respectively. Of these, 131 strains were toxigenic. Toxin gene profiles tcdA(+);tcdB(+);cdtA/cdtB(+) and tcdA(+);tcdB(+);cdtA/cdtB(-) were identified in 122 and nine strains, respectively. No isolates showed reduced susceptibility to metronidazole and vancomycin. All tested strains were resistant to ciprofloxacin, and 72.9, 42.9, and 72.9% of strains were resistant to erythromycin, clindamycin, or moxifloxacin, respectively. Multi-locus sequence typing (MLST) identified 23 distinct sequence types (STs) and two unidentified strains. Strains ST1 and ST42 represented 31 and 30.1% of all strains tested, respectively. However, while ST1 was detected across nearly all years studied, ST42 was detected only from 2009 to 2011. Conclusion: The high proportion of infected patients in 2008-2011 may be explained by the predominance of more transmissible and virulent C. difficile strains. Although this retrospective study was not designed to define outbreaks of C. difficile, the finding that most isolates exhibited high levels of genetic relatedness suggests nosocomial acquisition.