Evaluation of Staphylococcus aureus Subtyping Module for Methicillin-Resistant Staphylococcus aureus Detection Based on Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry

Accurate prediction of antimicrobial resistance and genetic marker of Staphylococcus aureus clinical isolates using MALDI-TOF MS and machine learning - across DRIAMS and Taiwan database

BACKGROUND

The use of matrix-assisted laser desorption/ionisation-time-of-flight mass spectra (MALDI-TOF MS) with machine learning (ML) has been explored for predicting antimicrobial resistance. This study evaluates the effectiveness of MALDI-TOF MS paired with various ML classifiers and establishes optimal models for predicting antimicrobial resistance and the presence of mecA gene among Staphylococcus aureus.

MATERIALS AND METHODS

Antimicrobial resistance against tier 1 antibiotics and MALDI-TOF MS of S. aureus were analysed using data from the Database of Resistance against Antimicrobials with MALDI-TOF Mass Spectrometry (DRIAMS) and one medical centre (CS database). Five ML classifiers were used to analyse performance metrics. The Shapley value quantified the predictive contribution of individual features.

RESULTS

The LightGBM demonstrated superior performance in predicting antimicrobial resistance for most tier 1 antibiotics among oxacillin-resistant S. aureus (ORSA) compared with all S. aureus and oxacillin-susceptible S. aureus (OSSA) in both databases. In DRIAMS, Multilayer Perceptron (MLP) was associated with excellent predictive performance, expressed as accuracy/AUROC/AUPR, for clindamycin (0.74/0.81/0.90), tetracycline (0.86/0.87/0.94), and trimethoprim-sulfamethoxazole (0.95/0.72/0.97). In the CS database, Ada and Light Gradient Boosting Machine (LightGBM) showed excellent performance for erythromycin (0.97/0.92/0.86) and tetracycline (0.68/0.79/0.86). Mass-to-charge ratio (m/z) features of 2411-2414 and 2429-2432 correlated with clindamycin resistance, whereas 5033-5036 was linked to erythromycin resistance in DRIAMS. In the CS database, overlapping features of 2423-2426, 4496-4499, and 3764-3767 simultaneously predicted the presence of mecA and oxacillin resistance.

CONCLUSION

The predictive performance of antimicrobial resistance against S. aureus using MALDI-TOF MS depends on database characteristics and the ML algorithm selected. Specific and overlapping mass spectra features are excellent predictive markers for mecA and specific antimicrobial resistance.

A side-by-side comparison of the new VITEK MS PRIME and the MALDI Biotyper sirius in the clinical microbiology laboratory

PURPOSE

This study aims to evaluate the performance of two latest generation matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) systems in routine laboratory settings, focusing on turnaround time (TAT), time to results (TTR), hands-on time, and identification rate.

METHODS

We conducted a time and motion study on three workflow scenarios to simulate different laboratory settings. Overall, 618 bacterial isolates from a tertiary hospital's laboratory were processed using the VITEK MS PRIME (bioMérieux) and the MALDI Biotyper sirius (Bruker Daltonics) and their corresponding databases VITEK IVD Database 3.2 and MBT reference library 12.

RESULTS

The target preparation process showed no significant difference in TAT, but the Biotyper workflow had a shorter hands-on time by 3 to 6 min. In the measurement process, TTR was three to five times shorter for the Biotyper sirius while hands-on time was significantly shorter for VITEK MS PRIME (approximately 1.5 min per target). The identification rate without retesting was 97.9% for VITEK MS PRIME and 98.9% for Biotyper sirius. Both systems achieved 100% agreement at genus and 96.2% at species level.

CONCLUSION

Both systems exhibited excellent identification rates for routine bacterial isolates. Due to its high speed, the Biotyper sirius is suited for laboratories with high sample throughput and a workflow designed for processing larger batches. The VITEK MS PRIME, with its "load and go" system accommodating up to 16 targets, reduces hands-on time, making it a reasonable choice for laboratories with fewer identifications overall but a higher number of targets and a workflow designed for parallel processing on different workstations.

Novel copper-containing ferrite nanoparticles exert lethality to MRSA by disrupting MRSA cell membrane permeability, depleting intracellular iron ions, and upregulating ROS levels

Objective

The widespread use of antibiotics has inevitably led to the emergence of multidrug-resistant bacterial strains, such as methicillin-resistant Staphylococcus aureus (MRSA), making treatment of this infection a serious challenge. This study aimed to explore new treatment strategies for MRSA infection.

Methods

The structure of Fe₃O₄ NPs with limited antibacterial activity was optimized, and the Fe²⁺ ↔ Fe³⁺ electronic coupling was eliminated by replacing 1/2 Fe²⁺ with Cu²⁺. A new type of copper-containing ferrite nanoparticles (hereinafter referred to as Cu@Fe NPs) that fully retained oxidation-reduction activity was synthesized. First, the ultrastructure of Cu@Fe NPs was examined. Then, antibacterial activity was determined by testing the minimum inhibitory concentration (MIC) and safety for use as an antibiotic agent. Next, the mechanisms underlying the antibacterial effects of Cu@Fe NPs were investigated. Finally, mice models of systemic and localized MRSA infections was established for in vivo validation.

Results

It was found that Cu@Fe NPs exhibited excellent antibacterial activity against MRSA with MIC of 1 μg/mL. It effectively inhibited the development of MRSA resistance and disrupted the bacterial biofilms. More importantly, the cell membranes of MRSA exposed to Cu@Fe NPs underwent significant rupture and leakage of the cell contents. Cu@Fe NPs also significantly reduced the iron ions required for bacterial growth and contributed to excessive intracellular accumulation of exogenous reactive oxygen species (ROS). Therefore, these findings may important for its antibacterial effect. Furthermore, Cu@Fe NPs treatment led to a significant reduction in colony forming units within intra-abdominal organs, such as the liver, spleen, kidney, and lung, in mice with systemic MRSA infection, but not for damaged skin in those with localized MRSA infection.

Conclusion

The synthesized nanoparticles has an excellent drug safety profile, confers high resistant to MRSA, and can effectively inhibit the progression of drug resistance. It also has the potential to exert anti-MRSA infection effects systemically in vivo. In addition, our study revealed a unique multifaceted antibacterial mode of Cu@Fe NPs: (1) an increase in cell membrane permeability, (2) depletion of Fe ions in cells, (3) generation of ROS in cells. Overall, Cu@Fe NPs may be potential therapeutic agents for MRSA infections.

Rapid identification of methicillin-resistant Staphylococcus aureus by MALDI-TOF MS: A meta-analysis

Invasive infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are associated with high mortality and morbidity. The sooner the pathogen is determined, the better it is beneficial to patient. However, routine laboratory inspections are time-consuming and laborious. A thorough research was conducted in PubMed and Web of Science (until June 2021) to identify studies evaluating the accuracy of MRSA identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). STATA 15.0 software was used to analyze the pooled results of sensitivity, specificity, and 95% confidence intervals (CI). The summary receiver operating characteristic curves (SROC) and area under the curve (AUC) were utilized to show the overall performance of MALDI-TOF MS. Fifteen studies involving 2471 isolates were included in this study after the final selection in this meta-analysis. Using the random effects model forest plot to summarize the overall statistics, the sensitivity of MALDI-TOF MS for identifying MRSA was 92% (95% CI: 81%-97%), and the specificity was 97% (95% CI: 89%-99%). In the SROC curve, the AUC reached 0.99 (95% CI: 97%-99%). Deeks' test showed no significant publication bias in this meta-analysis. Compared with clinical reference methods, MALDI-TOF MS identification of MRSA shows a higher degree of sensitivity and specificity.

Recent Developments in Phenotypic and Molecular Diagnostic Methods for Antimicrobial Resistance Detection in Staphylococcus aureus: A Narrative Review

Staphylococcus aureus is an opportunistic pathogen responsible for a wide range of infections in humans, such as skin and soft tissue infections, pneumonia, food poisoning or sepsis. Historically, S. aureus was able to rapidly adapt to anti-staphylococcal antibiotics and become resistant to several classes of antibiotics. Today, methicillin-resistant S. aureus (MRSA) is a multidrug-resistant pathogen and is one of the most common bacteria responsible for hospital-acquired infections and outbreaks, in community settings as well. The rapid and accurate diagnosis of antimicrobial resistance in S. aureus is crucial to the early initiation of directed antibiotic therapy and to improve clinical outcomes for patients. In this narrative review, I provide an overview of recent phenotypic and molecular diagnostic methods for antimicrobial resistance detection in S. aureus, with a particular focus on MRSA detection. I consider methods for resistance detection in both clinical samples and isolated S. aureus cultures, along with a brief discussion of the advantages and the challenges of implementing such methods in routine diagnostics.

Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning

Early use of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based techniques can take up to 72 hours to generate results. We have developed a novel machine learning approach to predict antimicrobial resistance directly from matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectra profiles of clinical isolates. We trained calibrated classifiers on a newly created publicly available database of mass spectra profiles from the clinically most relevant isolates with linked antimicrobial susceptibility phenotypes. This dataset combines more than 300,000 mass spectra with more than 750,000 antimicrobial resistance phenotypes from four medical institutions. Validation on a panel of clinically important pathogens, including Staphylococcus aureus, Escherichia coli and Klebsiella pneumoniae, resulting in areas under the receiver operating characteristic curve of 0.80, 0.74 and 0.74, respectively, demonstrated the potential of using machine learning to substantially accelerate antimicrobial resistance determination and change of clinical management. Furthermore, a retrospective clinical case study of 63 patients found that implementing this approach would have changed the clinical treatment in nine cases, which would have been beneficial in eight cases (89%). MALDI-TOF mass spectra-based machine learning may thus be an important new tool for treatment optimization and antibiotic stewardship.

Detection of Multidrug-Resistant Enterobacterales-From ESBLs to Carbapenemases

Multidrug-resistant Enterobacterales (MDRE) are an emerging threat to global health, leading to rising health care costs, morbidity and mortality. Multidrug-resistance is commonly caused by different β-lactamases (e.g., ESBLs and carbapenemases), sometimes in combination with other resistance mechanisms (e.g., porin loss, efflux). The continuous spread of MDRE among patients in hospital settings and the healthy population require adjustments in healthcare management and routine diagnostics. Rapid and reliable detection of MDRE infections as well as gastrointestinal colonization is key to guide therapy and infection control measures. However, proper implementation of these strategies requires diagnostic methods with short time-to-result, high sensitivity and specificity. Therefore, research on new techniques and improvement of already established protocols is inevitable. In this review, current methods for detection of MDRE are summarized with focus on culture based and molecular techniques, which are useful for the clinical microbiology laboratory.

Behind Every Great Infection Prevention Program is a Great Microbiology Laboratory: Key Components and Strategies for an Effective Partnership

A great clinical microbiology laboratory supporting a great infection prevention program requires focusing on the following services: rapid and accurate identification of pathogens associated with health care-associated infections; asymptomatic surveillance for health care-acquired pathogens before infections arise; routine use of broad and flexible antimicrobial susceptibility testing to direct optimal therapy; implementation of epidemiologic tracking tools to identify outbreaks; development of clear result communication with interpretative comments for clinicians. These goals are best realized in a collaborative relationship with the infection prevention program so that both can benefit from the shared priorities of providing the best patient care.

Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) Analysis for the Identification of Pathogenic Microorganisms: A Review

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been used in the field of clinical microbiology since 2010. Compared with the traditional technique of biochemical identification, MALDI-TOF MS has many advantages, including convenience, speed, accuracy, and low cost. The accuracy and speed of identification using MALDI-TOF MS have been increasing with the development of sample preparation, database enrichment, and algorithm optimization. MALDI-TOF MS has shown promising results in identifying cultured colonies and rapidly detecting samples. MALDI-TOF MS has critical research applications for the rapid detection of highly virulent and drug-resistant pathogens. Here we present a scientific review that evaluates the performance of MALDI-TOF MS in identifying clinical pathogenic microorganisms. MALDI-TOF MS is a promising tool in identifying clinical microorganisms, although some aspects still require improvement.

Recent advances in rapid antimicrobial susceptibility testing systems

INTRODUCTION

Until recently antimicrobial susceptibility testing (AST) methods based on the demonstration of phenotypic susceptibility in 16-24 h remained largely unchanged.

AREAS COVERED

Advances in rapid phenotypic and molecular-based AST systems.

EXPERT OPINION

AST has changed over the past decade, with many rapid phenotypic and molecular methods developed to demonstrate phenotypic or genotypic resistance, or biochemical markers of resistance such as β-lactamases associated with carbapenem resistance. Most methods still require isolation of bacteria from specimens before both legacy and newer methods can be used. Bacterial identification by MALDI-TOF mass spectroscopy is now widely used and is often key to the interpretation of rapid AST results. Several PCR arrays are available to detect the most frequent pathogens associated with bloodstream infections and their major antimicrobial resistance genes. Many advances in whole-genome sequencing of bacteria and fungi isolated by culture as well as directly from clinical specimens have been made but are not yet widely available. High cost and limited throughput are the major obstacles to uptake of rapid methods, but targeted use, continued development and decreasing costs are expected to result in more extensive use of these increasingly useful methods.

Healthcare-Associated Laboratory-Confirmed Bloodstream Infections-Species Diversity and Resistance Mechanisms, a Four-Year Retrospective Laboratory-Based Study in the South of Poland

INTRODUCTION

Regardless of the country, advancements in medical care and infection prevention and control of bloodstream infections (BSIs) are an enormous burden of modern medicine.

OBJECTIVES

The aim of our study was to describe the epidemiology and drug-resistance of laboratory-confirmed BSI (LC-BSIs) among adult patients of 16 hospitals in the south of Poland.

PATIENTS AND METHODS

Data on 4218 LC-BSIs were collected between 2016-2019. The identification of the strains was performed using MALDI-TOF. Resistance mechanisms were investigated according to European Committee on Antimicrobial Susceptibility Testing, EUCAST recommendations.

RESULTS

Blood cultures were collected from 8899 patients, and LC-BSIs were confirmed in 47.4%. The prevalence of Gram-positive bacteria was 70.9%, Gram-negative 27.8% and yeast 1.4%. The most frequently isolated genus was Staphylococcus (50% of all LC-BSIs), with a domination of coagulase-negative staphylococci, while Escherichia coli (13.7%) was the most frequent Gram-negative bacterium. Over 4 years, 108 (2.6%) bacteria were isolated only once, including species from the human microbiota as well as environmental and zoonotic microorganisms. The highest methicillin resistant Staphylococcus aureus (MRSA) prevalence was in intensive care units (ICUs) (55.6%) but S. aureus with resistance to macrolides, lincosamides and streptogramins B (MLSB) in surgery was 66.7%. The highest prevalence of E. faecalis with a high-level aminoglycoside resistance (HLAR) mechanism was in ICUs, (84.6%), while E. faecium-HLAR in surgery was 83.3%. All cocci were fully glycopeptide-sensitive. Carbapenem-resistant Gram-negative bacilli were detected only in non-fermentative bacilli group, with prevalence 70% and more.

CONCLUSIONS

The BSI microbiology in Polish hospitals was similar to those reported in other studies, but the prevalence of MRSA and enterococci-HLAR was higher than expected, as was the prevalence of carbapenem-resistant non-fermentative bacilli. Modern diagnostic techniques, such as MALDI-TOF, guarantee reliable diagnosis.

Rapid, sensitive and label-free detection of pathogenic bacteria using a bacteria-imprinted conducting polymer film-based electrochemical sensor

The rapid and sensitive detection of pathogenic bacteria is very important for timely prevention and treatment of foodborne disease. Here, a bacteria-imprinted conductive poly(3-thiopheneacetic acid) (BICP) film-based impedimetric sensor was developed for the rapid, sensitive and label-free detection of staphylococcus aureus (S. aureus). The BICP film preparation was very convenient and eco-friendly, which was in situ deposited on gold electrode surface without the use of toxic organic solvents and cross-linkers. The process of imprinting and recognition were characterized by electrochemical technique and scanning electron microscope. The BICP had a novel structure without cocci-shaped cavities formed in the poly(3-thiopheneacetic acid) (PTAA) matrices. To obtain the optimal sensing performance, a set of factors affecting the imprinting and recognition were investigated. Under the optimized conditions, an extremely rapid recognition within 10 min, a very low limit of detection (LOD) of 2 CFU/mL, and wide linear range from 10 to 10⁸ CFU/mL were achieved by the BICP film-based impedimetric sensor. The sensor also demonstrated high selectivity, and good universality and repeatability. Furthermore, the feasibility of its application has also been demonstrated in the analysis of real milk samples. This sensor offered a simple and universal method for rapid, sensitive, and selective detection of pathogenic bacteria, which could hold great potentials in fields like food safety.