Transmission Dynamics of Clostridioides difficile in 2 High-Acuity Hospital Units

Retrospective Study of the Epidemiology of Clostridioides difficile Infection in the Neurosurgery Department of a Tertiary Hospital in China

Background

Although the epidemiology of Clostridioides difficile is important, few studies examining transmission of C. difficile have been reported, especially in wards with low detection rates, such as neurosurgery departments.

Purpose

This retrospective study investigated the epidemiology of C. difficile infection in a neurosurgery department over a 24-month period, particularly examining the transmission of C. difficile using whole-genome sequencing (WGS).

Methods

Clostridioides difficile strains were isolated and identified from fecal samples of neurosurgical patients. Toxigenic strains were typed using multilocus sequence typing, PCR ribotyping and using capillary gel electrophoresis. WGS was used to characterize C. difficile ST-37/RT017 isolates, and comparative genomic analyses were performed to compare genomic differences between all ST-37 strains from other wards. The susceptibility to 8 antimicrobial agents was examined using the E-test.

Results

Comparative genomic analyses revealed that isolates obtained from neurosurgical patients clustered into two lineages. Only strains s11052403 and s10090304, respectively, isolated from a patient on the 8th floor of the neurosurgery ward and a patient on the 9th floor, were highly similar, exhibiting differences of only two single-nucleotide polymorphisms. All C. difficile ST-37/RT017 strains isolated from neurosurgical patients were resistant to multiple classes of antibiotics.

Conclusion

There is an urgent need to raise awareness of C. difficile infection, and epidemiologic surveillance is required to detect clustering and transmission of C. difficile cases in China. Strict disinfection of the environment is essential to reduce transmission of C. difficile and achieve effective infection control in the hospital setting.

A review of epidemiological models of Clostridioides difficile transmission and control (2009-2021)

Clostridioides difficile is the leading cause of infectious diarrhea and one of the most common healthcare-acquired infections worldwide. We performed a systematic search and a bibliometric analysis of mathematical and computational models for Clostridioides difficile transmission. We identified 33 publications from 2009 to 2021. Models have underscored the importance of asymptomatic colonized patients in maintaining transmission in health-care settings. Infection control, antimicrobial stewardship, active testing, and vaccination have often been evaluated in models. Despite active testing and vaccination being not currently implemented, they are the most commonly evaluated interventions. Some aspects of C. difficile transmission, such community transmission and interventions in health-care settings other than in acute-care hospitals, remained less evaluated through modeling.

Modeling transmission of pathogens in healthcare settings

PURPOSE OF REVIEW

Mathematical, statistical, and computational models provide insight into the transmission mechanisms and optimal control of healthcare-associated infections. To contextualize recent findings, we offer a summative review of recent literature focused on modeling transmission of pathogens in healthcare settings.

RECENT FINDINGS

The COVID-19 pandemic has led to a dramatic shift in the modeling landscape as the healthcare community has raced to characterize the transmission dynamics of SARS-CoV-2 and develop effective interventions. Inequities in COVID-19 outcomes have inspired new efforts to quantify how structural bias impacts both health outcomes and model parameterization. Meanwhile, developments in the modeling of methicillin-resistant Staphylococcus aureus, Clostridioides difficile, and other nosocomial infections continue to advance. Machine learning continues to be applied in novel ways, and genomic data is being increasingly incorporated into modeling efforts.

SUMMARY

As the type and amount of data continues to grow, mathematical, statistical, and computational modeling will play an increasing role in healthcare epidemiology. Gaps remain in producing models that are generalizable to a variety of time periods, geographic locations, and populations. However, with effective communication of findings and interdisciplinary collaboration, opportunities for implementing models for clinical decision-making and public health decision-making are bound to increase.

What's a Biofilm?-How the Choice of the Biofilm Model Impacts the Protein Inventory of Clostridioides difficile

The anaerobic pathogen Clostridioides difficile is perfectly equipped to survive and persist inside the mammalian intestine. When facing unfavorable conditions C. difficile is able to form highly resistant endospores. Likewise, biofilms are currently discussed as form of persistence. Here a comprehensive proteomics approach was applied to investigate the molecular processes of C. difficile strain 630Δerm underlying biofilm formation. The comparison of the proteome from two different forms of biofilm-like growth, namely aggregate biofilms and colonies on agar plates, revealed major differences in the formation of cell surface proteins, as well as enzymes of its energy and stress metabolism. For instance, while the obtained data suggest that aggregate biofilm cells express both flagella, type IV pili and enzymes required for biosynthesis of cell-surface polysaccharides, the S-layer protein SlpA and most cell wall proteins (CWPs) encoded adjacent to SlpA were detected in significantly lower amounts in aggregate biofilm cells than in colony biofilms. Moreover, the obtained data suggested that aggregate biofilm cells are rather actively growing cells while colony biofilm cells most likely severely suffer from a lack of reductive equivalents what requires induction of the Wood-Ljungdahl pathway and C. difficile’s V-type ATPase to maintain cell homeostasis. In agreement with this, aggregate biofilm cells, in contrast to colony biofilm cells, neither induced toxin nor spore production. Finally, the data revealed that the sigma factor SigL/RpoN and its dependent regulators are noticeably induced in aggregate biofilms suggesting an important role of SigL/RpoN in aggregate biofilm formation.