Comparison of the accuracy of matrix-assisted laser desorption ionization-time of flight mass spectrometry with that of other commercial identification systems for identifying Staphylococcus saprophyticus in urine

Rapid and accurate detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 by mass spectrometry directly from the isolate, using 10 potential biomarker peaks and machine learning predictive models

Introduction. The different pathotypes of Escherichia coli can produce a large number of human diseases. Surveillance is complex since their differentiation is not easy. In particular, the detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 consists of stool culture of a diarrhoeal sample on enriched and/or selective media and identification of presumptive colonies and confirmation, which require a certain level of training and are time-consuming and expensive.Hypothesis. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a quick and easy way to obtain the protein spectrum of a microorganism, identify the genus and species, and detect potential biomarker peaks of certain characteristics.Aim. To verify the usefulness of MALDI-TOF MS to rapidly identify and differentiate STEC O157 : H7 from other E. coli pathotypes.Methodology. The direct method was employed, and the information obtained using Microflex LT platform-based analysis from 60 clinical isolates (training set) was used to detect differences between the peptide fingerprints of STEC O157 : H7 and other E. coli strains. The protein profiles detected laid the foundations for the development and evaluation of machine learning predictive models in this study.Results. The detection of potential biomarkers in combination with machine learning predictive models in a new set of 142 samples, called 'test set', achieved 99.3 % (141/142) correct classification, allowing us to distinguish between the isolates of STEC O157 : H7 and the other E. coli group. Great similarity was also observed with respect to this last group and the Shigella species when applying the potential biomarkers algorithm, allowing differentiation from STEC O157 : H7Conclusion. Given that STEC O157 : H7 is the main causal agent of haemolytic uremic syndrome, and based on the performance values obtained in the present study (sensitivity=98.5 % and specificity=100.0 %), the implementation of this technique provides a proof of principle for MALDI-TOF MS and machine learning to identify biomarkers to rapidly screen or confirm STEC O157 : H7 versus other diarrhoeagenic E. coli in the future.

From days to hours: Can MALDI-TOF MS system replace both conventional and molecular typing methods with new cut off level for Vancomycin Resistant Enterococcus faecium

Vancomycin-Resistant E. faecium (VRE) strains from clinical specimens were identified by conventional methods before. Following the phenotype-based identification, all strains were also identified using both BD Phoenix and VITEK MS bioMérieux System. Strains were typed with the Bruker MALDI-TOF MS system, pulsed field gel electrophoresis (PFGE) and 16S rRNA gene sequencing analysis and then the sensitivity compared for each. A cut off value of 850 assigned with Bruker MALDI-TOF MS system was found to give equal sensitivity to that of PFGE. Results obtained were compared with those of molecular typing. The main advantage of MALDI-TOF MS technology over the others was the much shorter analysis time which lasted only a few hours rather than days or a whole week. Also, the Bruker MALDI-TOF MS system was used for typing and compared with the gold standard method and this study is first to report the determined cut off level for typing of VRE strains.

Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for the Rapid Detection of Antimicrobial Resistance Mechanisms and Beyond

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been successfully applied in recent years for first-line identification of pathogens in clinical microbiology because it is simple to use, rapid, and accurate and has economic benefits in hospital management. The range of clinical applications of MALDI-TOF MS for bacterial isolates is increasing constantly, from species identification to the two most promising applications in the near future: detection of antimicrobial resistance and strain typing for epidemiological studies. The aim of this review is to outline the contribution of previous MALDI-TOF MS studies in relation to detection of antimicrobial resistance and to discuss potential future challenges in this field. Three main approaches are ready (or almost ready) for clinical use, including the detection of antibiotic modifications due to the enzymatic activity of bacteria, the detection of antimicrobial resistance by analysis of the peak patterns of bacteria or mass peak profiles, and the detection of resistance by semiquantification of bacterial growth in the presence of a given antibiotic. This review provides an expert guide for MALDI-TOF MS users to new approaches in the field of antimicrobial resistance detection, especially possible applications as a routine diagnostic tool in microbiology laboratories.

Molecular Characteristics of Methicillin-Resistant Staphylococci Clinical Isolates from a Tertiary Hospital in Northern Thailand

Methicillin-resistant staphylococci are now recognized as a major cause of infectious diseases, particularly in hospitals. Molecular epidemiology is important for prevention and control of infection, but little information is available regarding staphylococcal infections in Northern Thailand. In the present study, we examined antimicrobial susceptibility patterns, detection of antimicrobial resistance genes, and SCCmec types of methicillin-resistant S. aureus (MRSA) and methicillin-resistant coagulase-negative staphylococci (MR-CoNS) isolated from patients in a hospital in Northern Thailand. The species of MRSA and MR-CoNS were identified using combination methods, including PCR, MALDI-TOF-MS, and tuf gene sequencing. The susceptibility pattern of all isolates was determined by the disk diffusion method. Antimicrobial resistance genes, SCCmec types, and ST239 were characterized using single and multiplex PCR. ST239 was predominant in MRSA isolates (10/23). All MR-CoNS (N=31) were identified as S. haemolyticus (N=18), S. epidermidis (N=3), S. cohnii (N=3), S. capitis (N=6), and S. hominis (N=1). More than 70% of MRSA and MR-CoNS were resistant to cefoxitin, penicillin, oxacillin, erythromycin, clindamycin, gentamicin, and ciprofloxacin. In MRSA isolates, the prevalence of ermA (78.3%) and ermB (73.9%) genes was high compared to that of the ermC gene (4.3%). In contrast, ermC (87.1%) and qacA/B genes (70.9%) were predominant in MR-CoNS isolates. SCCmec type III was the dominant type of MRSA (13/23), whereas SCCmec type II was more present in S. haemolyticus (10/18). Ten MRSA isolates with SCCmec type III were ST239, which is the common type of MRSA in Asia. This finding provides useful information for a preventive health strategy directed against methicillin-resistant staphylococcal infections.

Evaluation of MALDI-TOF VITEK®MS and VITEK® 2 system for the identification of Staphylococcus saprophyticus

AIM

To compare two identification methods for coagulase-negative staphylococci (CoNS) isolated from patients with urinary tract infections, VITEK^® 2 and MALDI-TOF VITEK^®MS, with genotypic identification by internal transcribed spacer PCR (ITS-PCR).

RESULTS

A total of 217 CoNS isolates were studied. Agreement of the VITEK^® 2 system with ITS-PCR was 84.8%, with 98% sensitivity and 100% specificity. Thirty-one of the 33 strains incorrectly identified by VITEK^® 2 belonged to the species Staphylococcus saprophyticus. MALDI-TOF VITEK^®MS showed an excellent correlation with ITS-PCR since it correctly identified all CoNS isolates.

CONCLUSION

MALDI-TOF VITEK^®MS is more accurate than the automated VITEK^® 2 system in identifying CoNS isolated from urinary tract infections to species level, particularly urinary isolates of S. saprophyticus.

Staphylococcus saprophyticus Recovered from Humans, Food, and Recreational Waters in Rio de Janeiro, Brazil

Staphylococcus saprophyticus is an important agent of urinary tract infection (UTI) in young women, but information about this pathogen in human microbiota and in common environment is lacking. The aim of this study was to characterize S. saprophyticus isolates from genitoanal microbiota of 621 pregnant women, 10 minas cheese packs, and five beaches in Rio de Janeiro city and compare PFGE profiles of these isolates with five UTI PFGE clusters described in this city. We investigated 65 S. saprophyticus isolates from microbiota, 13 from minas cheese, and 30 from beaches and 32 UTI isolates. Antimicrobial resistance was determined by disk diffusion, MIC by agar dilution, and PCR. Erythromycin-resistance genes erm(C), msr(A), msr(B), mph(C), and lin(A) were found in 93% of isolates. Trimethoprim-sulfamethoxazole resistance correlated with dfrG or dfrA genes. Three cefoxitin-resistant isolates carried the mecA gene. All isolates obtained from cheese were susceptible to all antimicrobial agents. Six of 10 pregnant women with >1 isolate had monoclonal colonization. Isolates from pregnant women shared 100% similarity with UTI PFGE cluster types A and E obtained almost 10 years previously, suggesting temporal persistence of S. saprophyticus. Antimicrobial resistance of beach isolates reflected the profiles of human isolates. Taken together, results indicate a shared source for human and environmental isolates.

Presence of multidrug-resistant organisms in the residents and environments of long-term care facilities in Taiwan

OBJECTIVES

This study investigated the prevalence of multidrug-resistant organisms (MDROs) in the residents and environments of long-term care facilities (LTCFs) in Taiwan.

METHODS

We prospectively investigated the distribution of MDROs in residents of six LTCFs and their environments from January 2015 to December 2015 (intervention period). Active surveillance of colonization of MDROs was performed by culturing rectal and nasal swab samples every 3 months for the residents: 63, 79, and 73 in the first, second, and third surveillance investigations, respectively. If MDROs, including methicillin-resistant Staphylococcus aureus, carbapenem-resistant Enterobacteriaceae, carbapenem-resistant Pseudomonas aeruginosa, and MDR Acinetobacter baumannii were identified, then swab specimens from environmental sources were also collected and cultured. During the study period, several infection control measures were also implemented.

RESULTS

The overall infection density decreased significantly from 2.69 per 1000 patient-days in the preintervention (January 2014 to December 2014) to 2.39 per 1000 patient-days during the intervention period (p < 0.001). A total of 154 samples from residents and environmental sources were positive for MDROs. Methicillin-resistant S. aureus (n = 83, 53.9%) was the predominant organism, followed by carbapenem-resistant Enterobacteriaceae (n = 35, 22.7%), MDR A. baumannii (n = 30, 19.5%), and carbapenem-resistant P. aeruginosa (n = 6, 3.9%). The rates of detection of MDROs were 27.9% (60/215) in nasal swabs, 15.8% (34/215) in rectal swabs, and 11.1% (60/542) in the environmental sources.

CONCLUSIONS

The distribution and persistence of MDROs varied among the different LTCFs and time periods.

Identification of coagulase-negative Staphylococcus saprophyticus by polymerase chain reaction based on the heat-shock repressor encoding hrcA gene

Staphylococcus saprophyticus is an uropathogen belonging to the human microbiota and is responsible for community-acquired infections of the urinary tract. Identification of Staphylococcus species by biochemical tests is laborious and costly when compared to routine laboratory tests. Because of their high sensitivity and specificity, molecular methods are better suited for accurate identification of Staphylococcusspp. Therefore, the goal of this work was to standardize a polymerase chain reaction (PCR) protocol using species-specific primers, based on the heat-shock repressor coding hrcA gene, for the identification of S.saprophyticus. A total of 142 S. saprophyticus strains were obtained from different sources, including clinical, environmental, and foodborne strains. We also included 98 strains of Staphylococcus spp. to further validate the proposed method. Reliable results for the detection of S. saprophyticus isolates were obtained for 100% of the strains evaluated. The results were in accordance with matrix-assisted laser desorption ionization-time of flight mass spectrometry identification, thus highlighting the applicability of species-specific PCR for the molecular identification of S. saprophyticus.