Nosocomial infection with Clostridium difficile investigated by pyrolysis mass spectrometry

Prevalence and antimicrobial susceptibility pattern of toxigenic Clostridium difficilestrains isolated in Iran

Background/aim

Clostridium difficile is a frequent cause of nosocomial infections and has become a major public health concern in developed nations. In the present study, the prevalence and antimicrobial susceptibility pattern of toxigenic C. difficile strains isolated in Iran were investigated.

Materials and methods

Between June 2016 and May 2017, 2947 inpatient fecal samples were taken from symptomatic adult hospitalized patients in different units of 32 care facilities in Tehran, Iran. C. difficile strains were identified by microbiological/biochemical methods. Susceptibility to 20 antimicrobials was measured by E-test method. Toxin-specific immunoassays and cytotoxicity assays were used to determine in vitro toxin production.

Results

Out of 2947 fecal samples, 538 (18.25%) C. difficile isolates were obtained among those with suspected CDI. In E-test method, all C. difficile isolates were susceptible to fidaxomicin, vancomycin, amoxicillin/clavulanate, and meropenem and were resistant to penicillin G. The prevalence of multidrug resistant C. difficile was 69.33% (373/538). Among 538 C. difficile, 147 (27.32%), 169 (31.41%), and 222 (41.26%) isolates were TcdA+/TcdB+, TcdA-/TcdB+, and TcdA-/TcdB-, respectively.

Conclusion

The results evidently support the hypothesis of a probable role of toxigenic strains of C. difficile in developing gastrointestinal complaints in patients with diarrhea.

Rapid phenotypic characterization of Vibrio isolates by pyrolysis metastable atom bombardment mass spectrometry

Pyrolysis mass spectrometry was investigated for rapid characterization of food-borne bacterial pathogens. Nine isolates of Vibrio parahaemolyticus and one isolate each of Vibrio fluvialis, Vibrio hollisae, and Vibrio vulnificus were analyzed. Pyrolysis mass spectra, generated via an alternative ionization method, metastable atom bombardment, were subject to principal component-discriminant analysis. The spectral patterns were used to distinguish Vibrio isolates differing in species, serotype and expression of the thermostable direct hemolysin gene. The patterns of similarity and dissimilarity amongst spectra in the Vibrio test set generally reflected those associated with species, serotype or hemolysin-producing genes, though the combined influence of these and other variables in the multi-dimensional data did not produce a simple clustering with respect to any one of these characteristics. These results suggested that with enough examples to model the most common combinations, the method should be able to characterize Vibrio isolates according to their phenotypic characteristics. Pyrolysis-mass spectrometry with metastable atom bombardment and pattern recognition appeared suitable for rapid infraspecific comparison of Vibrio isolates. This integrated analytical, pattern-recognition system should be examined further for potential utility in clinical and public health diagnostic contexts.

Rapid phenotypic characterization of Salmonella enterica strains by pyrolysis metastable atom bombardment mass spectrometry with multivariate statistical and artificial neural network pattern recognition

Pyrolysis mass spectrometry was investigated for rapid characterization of bacteria. Spectra of Salmonella were compared to their serovars, pulsed-field gel electrophoresis (PFGE) patterns, antibiotic resistance profiles, and MIC values. Pyrolysis mass spectra generated via metastable atom bombardment were analyzed by multivariate principal component-discriminant analysis and artificial neural networks (ANNs). Spectral patterns developed by discriminant analysis and tested with Leave-One-Out (LOO) cross-validation distinguished Salmonella strains by serovar (97% correct) and by PFGE groups (49%). An ANN model of the same PFGE groups was cross-validated, using the LOO rule, with 92% agreement. Using an ANN, thirty previously unseen spectra were correctly classified by serotype (97%) and at the PFGE level (67%). Attempts by ANN to model spectra grouped by resistance profile-but ignoring PFGE or serotype-failed (10% correct), but ANNs differentiating ten samples of the same serotype/PFGE class were more successful. To assess the information content of PyMS data serendipitously associated with or directly related to resistance character, the ten isolates were grouped into four, three, or two categories. The four categories corresponded to four resistance profiles. The four class and three class ANNs showed much improved but insufficient modeling power. The two-class ANN and a corresponding multivariate model maximized inferential power for a coarse antibiotic-resistance-related distinction. They each cross-validated by LOO at 90%. This is the first direct correlation of pyrolysis metastable atom bombardment mass spectrometry with immunological (e.g. serology) or molecular biology (e.g. PFGE) based techniques.

Prevalence and characterization of a binary toxin (actin-specific ADP-ribosyltransferase) from Clostridium difficile

In addition to the two large clostridial cytotoxins (TcdA and TcdB), some strains of Clostridium difficile also produce an actin-specific ADP-ribosyltransferase, called binary toxin CDT. We used a PCR method and Southern blotting for the detection of genes encoding the enzymatic (CDTa) and binding (CDTb) components of the binary toxin in 369 strains isolated from patients with suspected C. difficile-associated diarrhea or colitis. Twenty-two strains (a prevalence of 6%) harbored both genes. When binary toxin production was assessed by Western blotting, 19 of the 22 strains reacted with antisera against the iota toxin of C. perfringens (anti-Ia and anti-Ib). Additionally, binary toxin activity, detected by the ADP-ribosyltransferase assay, was present in only 17 of the 22 strains. Subsequently, all 22 binary toxin-positive strains were tested for the production of toxins TcdA and TcdB, toxinotyped, and characterized by serogrouping, PCR ribotyping, arbitrarily primed PCR, and pulsed-field gel electrophoresis. All binary toxin-positive strains also produced TcdB and/or TcdA. However, they had significant changes in the tcdA and tcdB genes and belonged to variant toxinotypes III, IV, V, VII, IX, and XIII. We could differentiate 16 profiles by using typing methods, indicating that most of the binary toxin-positive strains were unrelated.

Defining and using microbial spectral databases

This work shows how fingerprints of mass spectral patterns from microbial isolates are affected by variations in instrumental condition, by sample environment, and by sample handling factors. It describes a novel method by which pattern distortions can be mathematically corrected for variations in factors not amenable to experimental control. One uncontrollable variable is "between-batch" differences in culture media. Another, relevant for determination of noncultured extracts, is differences between the cells' environmental experience (e.g., starved environmental extracts versus cultured standards). The method suggests that, after a single growth cycle on a solid medium (perhaps, a selective one), pyrolysis MS spectra of microbial isolates can be algorithmically compensated and an unknown isolate identified using a spectral database defined by culture on a different (perhaps, nonselective) medium. This reduces identification time to as few as 24 h from sample collection. The concept also proposes a possible way to compensate certain noncultured, nonisolated samples (e.g., cells concentrated from urine or impacted from aerosol or semi-selectively extracted by immunoaffinity methods from heavily contaminated matrices) for identification within half an hour. Using the method, microbial mass spectra from different labs can be assembled into coherent databases similar to those routinely used to identify pure compounds. This type of data treatment is applicable for rapid detection in biowarfare and bioterror events as well as in forensic, research, and clinical laboratory contexts.

Epidemiological typing of Klebsiella pneumoniae by pyrolysis mass spectrometry

Thirteen isolates of ceftazidime-resistant Klebsiella pneumoniae from a suspected cross-infection outbreak involving patients on an intensive care unit and a haematology ward were examined in pyrolysis-mass spectrometry (Py-MS), along with eight concurrent non-outbreak-associated clinical isolates of klebsiellae as controls. Py-MS showed tight clustering of the suspected outbreak isolates, suggesting cross-infection with a single strain. Non-outbreak isolates were clearly distinct from one another and from the outbreak strain. The results confirm that Py-MS is a powerful tool for rapid strain comparison in investigations of cross-infection incidents.

Typing of the fish pathogen Listonella (Vibrio) anguillara by pyrolysis mass spectrometry

Twenty-eight representatives of Listonella (Vibrio) anguillara serovars O1, O2 and O3 were compared by Curie-point pyrolysis mass spectrometry (PyMS). The representatives of serovars O1 and O3 formed discrete, homogeneous groups in ordination plots of the PyMS data. Strains from serovar O2 were recovered in two groups, one of which encompassed six strains including the type strain of the species and the reference strain for serovar O2, and the other included two strains which showed cross-reactions between serovars O2 and O5. The almost complete agreement found between the PyMS and the serological data suggests that pyrolysis mass spectrometry will prove to be an effective method for interstrain comparison within the species Listonella anguillara.

Curie-point pyrolysis mass spectrometry as a tool in clinical microbiology

Pyrolysis mass spectrometry is a well established analytical tool that has received a considerable boost from the development of low cost, dedicated instruments and sophisticated statistical analyses on personal computers. Further analytical developments, especially in the area of neural networks, are pushing the technology to the forefront of methods for the discrimination and identification of microorganisms and their products. The speed and reproducibility of pyrolysis mass spectrometry and its applicability to a wide range of microorganisms make it an attractive method for epidemiological studies. For inter-strain comparisons, the method is at least as discriminatory as conventional typing systems and usually gives discrimination similar to that of nucleic acid fingerprinting techniques. There has been some success in using neural networks to make identifications across pyrolysis mass spectrometric batches. Further development of methods used to handle data from multiple PyMS analyses can be expected to extend the value of pyrolysis mass spectrometry in clinical microbiology.

Application of neural networks to the analysis of pyrolysis mass spectra

Pyrolysis mass spectrometry is a data rich analysis technique now becoming widely applied in microbiology. Data analysis is a key step in the exploitation of the technique and the application of neural network analysis to pyrolysis mass spectrometric data offers new opportunities for classification, identification and inter-strain comparison of microorganisms in biotechnology and clinical microbiology. The use of a supervised neural network for the identification of members of a streptomycete species-group is described.

Outbreak of multi-drug resistant Staphylococcus aureus: a cluster analysis

BACKGROUND

Outbreaks of multi-drug resistant Staphylococcus aureus over eight years were investigated to prevent future endemic.

METHODS

Isolates of multiresistant S. aureus underwent a cluster analysis combined with canonical discriminant analysis using bacteriologic biotyping and sensitivity to 21 drugs.

RESULTS

Of a total of 786 strains recovered from 155 in-patients, the specialty surgical ward (SW) exhibited 470 isolates (59.8%) and the general SW 214 (27.2%). Among six clusters formed, four clusters were predominant in the general SW. An ordination diagram from the canonical discriminant analysis revealed a distribution in which clusters were localized temporally (year) and spatially (ward). A yearly shift of clusters indicated emergence of a new phenotype of multiresistant S. aureus.

CONCLUSIONS

The cluster analysis of isolates of multiresistant S. aureus using biotyping and sensitivity may supplement the classical method of tracing the spreading patterns of this microbe.

Identification of outbreak-associated and other strains of Clostridium difficile by numerical analysis of SDS-PAGE protein patterns

Seventy-three cultures of Clostridium difficile isolated both during, and in the period immediately following, an outbreak of infection in a group of three hospitals, were characterized by one-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) of whole-cell proteins. Each protein pattern was characterized by the presence of one or two dense bands which were highly reproducible. The protein patterns were used as the basis for a numerical analysis which divided the strains into five phenons (electrophoretic or EP types). The majority, 60 of the 73 cultures, belonged to a single phenon which included strains from both patients and the environment. We conclude that high-resolution SDS-PAGE of proteins provides an effective method for typing C. difficile and therefore for tracing the possible spread of epidemic strains in hospitals and other institutions, thereby allowing a better understanding of the epidemiology of the organism.

Management and control of a large outbreak of diarrhoea due to Clostridium difficile

In the six-month period 1 November 1991 to 1 May 1992 175 patients developed diarrhoea due to Clostridium difficile in three hospitals in Manchester, UK. Most patients (90%) were over 60 years old and had been admitted to acute geriatric or medical wards with other illnesses. Infection is thought to have contributed to 17 deaths. Twenty-two patients relapsed clinically after antibiotic treatment. The outbreak began in one ward and affected 15 patients and two nurses. During the following months cases occurred on 34 wards. The pattern of spread suggested that a ward index case was followed by several secondary cases. Pyrolysis mass spectrometry showed that 79% of isolates of C. difficile belong to a single cluster and this putative outbreak strain also extensively colonizes the hospital environment. It was also responsible for a smaller outbreak in 1991 and many 'sporadic' cases in our hospitals before then. An outbreak control team was convened at an early stage and expert opinion co-opted. Infection control measures included: intensive education of staff; increased vigilance; strict enteric precautions; cohort nursing in a designated ward; rigorous cleaning procedures including emptying and 'deep' cleaning of wards where several cases had occurred; restriction of staff and patient movement; and restriction of antibiotic use. Subsequent to these measures there has been a substantial and sustained decrease in the number of new cases.