Proteotyping of Clostridioides difficile as Alternate Typing Method to Ribotyping Is Able to Distinguish the Ribotypes RT027 and RT176 From Other Ribotypes

Emerging Diagnostics in Clostridioides difficile Infection

Clostridioides difficile detection in community settings is time-intensive, resulting in delays in diagnosing and quarantining infected individuals. However, with the advent of semi-automated devices and improved algorithms in recent decades, the ability to discern CDI infection from asymptomatic carriage has significantly improved. This, in turn, has led to efficiently regulated monitoring systems, further reducing endemic risk, with recent concerns regarding a possible surge in hospital-acquired Clostridioides difficile infections post-COVID failing to materialize. This review highlights established and emerging technologies used to detect community-acquired Clostridioides difficile in research and clinical settings.

Contribution of MALDI-TOF mass spectrometry and machine learning including deep learning techniques for the detection of virulence factors of Clostridioides difficile strains

Clostridioides difficile (CD) infections are defined by toxins A (TcdA) and B (TcdB) along with the binary toxin (CDT). The emergence of the 'hypervirulent' (Hv) strain PR 027, along with PR 176 and 181, two decades ago, reshaped CD infection epidemiology in Europe. This study assessed MALDI-TOF mass spectrometry (MALDI-TOF MS) combined with machine learning (ML) and Deep Learning (DL) to identify toxigenic strains (producing TcdA, TcdB with or without CDT) and Hv strains. In total, 201 CD strains were analysed, comprising 151 toxigenic (24 ToxA+B+CDT+, 22 ToxA+B+CDT+ Hv+ and 105 ToxA+B+CDT-) and 50 non-toxigenic (ToxA-B-) strains. The DL-based classifier exhibited a 0.95 negative predictive value for excluding ToxA-B- strains, showcasing accuracy in identifying this strain category. Sensitivity in correctly identifying ToxA+B+CDT- strains ranged from 0.68 to 0.91. Additionally, all classifiers consistently demonstrated high specificity (>0.96) in detecting ToxA+B+CDT+ strains. The classifiers' performances for Hv strain detection were linked to high specificity (≥0.96). This study highlights MALDI-TOF MS enhanced by ML techniques as a rapid and cost-effective tool for identifying CD strain virulence factors. Our results brought a proof-of-concept concerning the ability of MALDI-TOF MS coupled with ML techniques to detect virulence factor and potentially improve the outbreak's management.

Discrimination between hypervirulent and non-hypervirulent ribotypes of Clostridioides difficile by MALDI-TOF mass spectrometry and machine learning

Hypervirulent ribotypes (HVRTs) of Clostridioides difficile such as ribotype (RT) 027 are epidemiologically important. This study evaluated whether MALDI-TOF can distinguish between strains of HVRTs and non-HVRTs commonly found in Europe. Obtained spectra of clinical C. difficile isolates (training set, 157 isolates) covering epidemiologically relevant HVRTs and non-HVRTs found in Europe were used as an input for different machine learning (ML) models. Another 83 isolates were used as a validation set. Direct comparison of MALDI-TOF spectra obtained from HVRTs and non-HVRTs did not allow to discriminate between these two groups, while using these spectra with certain ML models could differentiate HVRTs from non-HVRTs with an accuracy >95% and allowed for a sub-clustering of three HVRT subgroups (RT027/RT176, RT023, RT045/078/126/127). MALDI-TOF combined with ML represents a reliable tool for rapid identification of major European HVRTs.

Characterization of Clostridioides difficile Strains from an Outbreak Using MALDI-TOF Mass Spectrometry

The epidemiology of Clostridioides difficile infection (CDI) has changed over the last two decades, due to the emergence of C. difficile strains with clinical relevance and responsible for nosocomial outbreaks with severe outcomes. This study reports an outbreak occurred in a Long-term Care Unit from February to March 2022 and tracked by using a Matrix-Assisted Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) typing approach (T-MALDI); subsequently, a characterization of the toxigenic and antimicrobial susceptibility profiles of the C. difficile isolates was performed. A total of 143 faecal samples belonging to 112 patients was evaluated and C. difficile DNA was detected in 51 samples (46 patients). Twenty-nine C. difficile isolates were obtained, and three different clusters were revealed by T-MALDI. The most representative cluster accounted 22 strains and was considered to be epidemic, in agreement with PCR-Ribotyping. Such epidemic strains were susceptible to vancomycin (MIC ≤ 0.5 mg/mL) and metronidazole (MIC ≤ 1 mg/mL), but not to moxifloxacin (MIC > 32 mg/mL). Moreover, they produced only the Toxin A and, additionally, the binary toxin. To our knowledge, this is the first reported outbreak referable to a tcdA+/tcdB-/cdt+ genotypic profile. In light of these results, T-MALDI is a valid and rapid approach for discovering and tracking outbreaks.

Differentiation of Bacillus cereus and Bacillus thuringiensis Using Genome-Guided MALDI-TOF MS Based on Variations in Ribosomal Proteins

Bacillus cereus and B. thuringiensis are closely related species that are relevant to foodborne diseases and biopesticides, respectively. Unambiguous differentiation of these two species is crucial for bacterial taxonomy. As genome analysis offers an objective but time-consuming classification of B. cereus and B. thuringiensis, in the present study, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) was used to accelerate this process. By combining in silico genome analysis and MALDI-TOF MS measurements, four species-specific peaks of B. cereus and B. thuringiensis were screened and identified. The species-specific peaks of B. cereus were m/z 3211, 6427, 9188, and 9214, and the species-specific peaks of B. thuringiensis were m/z 3218, 6441, 9160, and 9229. All the above peaks represent ribosomal proteins, which are conserved and consistent with the phylogenetic relationship between B. cereus and B. thuringiensis. The specificity of the peaks was robustly verified using common foodborne pathogens. Thus, we concluded that genome-guided MALDI-TOF MS allows high-throughput differentiation of B. cereus and B. thuringiensis and provides a framework for differentiating other closely related species.

Rapid Classification of Clostridioides difficile Strains Using MALDI-TOF MS Peak-Based Assay in Comparison with PCR-Ribotyping

Typing methods are needed for epidemiological tracking of new emerging and hypervirulent strains because of the growing incidence, severity and mortality of Clostridioides difficile infections (CDI). The aim of this study was the evaluation of a typing Matrix-Assisted Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS (T-MALDI)) method for the rapid classification of the circulating C. difficile strains in comparison with polymerase chain reaction (PCR)-ribotyping results. Among 95 C. difficile strains, 10 ribotypes (PR1-PR10) were identified by PCR-ribotyping. In particular, 93.7% of the isolates (89/95) were grouped in five ribotypes (PR1-PR5). For T-MALDI, two classifying algorithm models (CAM) were tested: the first CAM involved all 10 ribotypes whereas the second one only the PR1-PR5 ribotypes. Better performance was obtained using the second CAM: recognition capability of 100%, cross-validation of 96.6% and agreement of 98.4% (60 correctly typed strains, limited to PR1-PR5 classification, out of 61 examined strains) with PCR-ribotyping results. T-MALDI seems to represent an alternative to PCR-ribotyping in terms of reproducibility, set up time and costs, as well as a useful tool in epidemiological investigation for the detection of C. difficile clusters (either among CAM included ribotypes or out-of-CAM ribotypes) involved in outbreaks.

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.

An Outbreak of Clostridium (Clostridioides) difficile Infections within an Acute and Long-Term Care Wards Due to Moxifloxacin-Resistant PCR Ribotype 176 Genotyped as PCR Ribotype 027 by a Commercial Assay

We aimed to characterize Clostridioides difficile isolates cultured during a six-month single-center study from stool samples of patients with C. difficile infection (CDI) genotyped by the Xpert^®C. difficile/Epi assay by polymerase chain reaction (PCR) ribotyping, toxin genes’ detection and multi-locus variable number tandem repeats analysis (MLVA). The susceptibility to metronidazole, vancomycin and moxifloxacin was determined by agar dilution. In addition, the presence of Thr82Ile in the GyrA and a single nucleotide deletion at position (Δ117) in the tcdC gene were investigated. Between January 1 and June 30, 2016, of 114 CDIs, 75 cases were genotyped as presumptive PCR ribotype (RT) 027 infections using a commercial assay. C. difficile isolates cultured from presumptive RT027 stool samples belonged to RT176. These isolates carried genes for toxin A (tcdA), B (tcdB), binary (cdtA/B) and had Δ117 in the tcdC gene. Using MLVA, the 71/75 isolates clustered into two clonal complexes (CCs). Of these, 39 isolates (54.9%) were from patients hospitalized in acute care and 32 isolates (45.1%) were isolated from patients hospitalized in the long-term care department. All isolates were susceptible to metronidazole and vancomycin, and 105 isolates were resistant to moxifloxacin (92%) carrying Thr83Ile in the GyrA. An outbreak of RT176 CDIs, suspected as RT027, was recognized in a Slovakian hospital. In order to monitor the emergence and spread of RT027-variants, the identification of a presumptive RT027 CDI should be confirmed at a strain level by PCR ribotyping.

Antimicrobial Resistance Patterns in Clostridioides difficile Strains Isolated from Neonates in Germany

Young children are frequently colonized with Clostridioides (C.) difficile. Depending on their resistance patterns, antibiotic treatment can facilitate gastrointestinal spreading in colonized individuals, potentially leading to transmission to others. C. difficile was isolated from stool samples from infants born in two hospitals in Göttingen and Darmstadt, Germany. All isolates were subjected to phenotypic antimicrobial resistance testing, PCR-based screening for toxin genes and mass spectrometry-based exclusion of ribotypes 027 and 176. Within an initial cohort of 324 neonates with a longitudinal survey of C. difficile, 137 strains were isolated from 48 individuals. Antimicrobial resistance was recorded against metronidazole in one (0.7%), erythromycin in 16 (11.7%) and moxifloxacin in 2 (1.5%) of the strains, whereas no resistance was observed against vancomycin (0.0%) or rifampicin (0.0%). Newly observed resistance against erythromycin in children with detection of previously completely sensitive isolates was reported for C. difficile isolates from 2 out of 48 children. In 20 children (42%), non-toxigenic strains were detected, and from 27 children (56%), toxigenic strains were isolated, while both toxigenic and non-toxigenic strains were recorded for 1 child (2%). Ribotypes 027 or 176 were not observed. In conclusion, the German C. difficile strains isolated from the children showed mild to moderate resistance with predominance of macrolide resistance, a substance class which is frequently applied in children. The observed switches to the dominance of macrolide-resistant isolates suggests likely selection of resistant C. difficile strains already in children.

On detection thresholds-a review on diagnostic approaches in the infectious disease laboratory and the interpretation of their results

Diagnostic testing in the infectious disease laboratory facilitates decision-making by physicians at the bedside as well as epidemiological assessments and surveillance at study level. Problems may arise if test results are uncritically considered as being the same as the unknown true value. To allow a better understanding, the influence of external factors on the interpretation of test results is introduced with the example of prevalence, followed by the presentation of strengths and weaknesses of important techniques in the infectious disease laboratory like microscopy, cultural diagnostics, serology, mass spectrometry, nucleic acid amplification and hypothesis-free metagenomic sequencing with focus on basic, high-technology and potential future approaches. Special problems like multiplex testing as well as uncertainty of test evaluations, if no gold standard is available, are also stressed with a final glimpse on emerging future technologies for the infectious disease laboratory. In the conclusions, suitability for point-of-care-testing and field laboratory applications is summarized. The aim is to illustrate the limitations of diagnostic accuracy to both clinicians and study planners and to stress the importance of close cooperation with experts in laboratory disciplines so as to avoid potentially critical misunderstandings due to inappropriate interpretation of diagnostic test results.