Performance of Matrix-Assisted Laser Desorption Ionization Time-of-Fight Mass Spectrometry for Rapid Discrimination of Methicillin-Resistant Staphylococcus aureus (MRSA): First Report of a Relation Between Protein Peaks and MRSA spa Type

MALDI-TOF MS method for differentiation of methicillin-sensitive and methicillin-resistant Staphylococcus aureus using (E)-Propyl α-cyano-4-Hydroxyl cinnamylate

Differentiating methicillin-sensitive and methicillin-resistant Staphylococcus aureus (MRSA and MSSA) is crucial for clinical diagnosis and anti-microbial treatment. Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) is an efficient tool for identifying pathogenic microorganisms at the bacterial species level. Here, we found that MRSA and MSSA can be differentiated by MALDI-TOF MS by employing (E)-propylα-cyano-4-hydroxyl cinnamylate (CHCA-C3) as the matrix, which shows great performance for proteins/peptides, especially hydrophobic proteins. The results show that the mass spectra profile of standard MRSA (ATCC 43300) is significantly different from the profiles of standard MSSA strains (ATCC 25923 and 29213) when using CHCA-C3 as the matrix compared to traditional matrix. The mass profiles had great reproducibility and were scarcely influenced by the growth medium. Due to the enhanced discrimination ability of CHCA-C3, we collected the mass spectra of 62 clinical S. aureus strains and selected four representative peaks for principal component analysis, which showed great differentiation. Our results suggest that employing a suitable matrix could enhance the discrimination ability of antibiotic-resistant bacteria by MALDI-TOF MS.

Rapid identification and discrimination of methicillin-resistant Staphylococcus aureus strains via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

RATIONALE

Methicillin-resistant Staphylococcus aureus (MRSA) is one of major clinical pathogens responsible for both hospital- and community-acquired infections worldwide. A delay in targeted antibiotic treatment contributes to longer hospitalization stay, higher costs, and increasing in-hospital mortality. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been integrated into the routine workflow for microbial identification over the past decade, and it has also shown promising functions in the detection of bacterial resistance. Therefore, we describe a rapid MALDI-TOF MS-based methodology for MRSA screening with machine-learning algorithms.

METHODS

A total of 452 clinical S. aureus isolates were included in this study, of which 194 were MRSA and 258 were methicillin-sensitive S. aureus (MSSA). The mass-to-charge ratio (m/z) features from MRSA and MSSA strains were binned and selected through Lasso regression. These features were then used to train a non-linear support vector machine (SVM) with radial basis function (RBF) kernels to evaluate the discrimination performance. The classifiers' accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC) were evaluated and compared with those from the random forest (RF) model.

RESULTS

A total of 2601 unique spectral peaks of all isolates were identified and 38 m/z features were selected for the classifying model. The AUCs of the non-linear RBF-SVM model and the RF model were 0.89 and 0.87, respectively, and the accuracy ranged between 0.86 (RBF-SVM) and 0.82 (RF).

CONCLUSIONS

Our study demonstrates that MALDI-TOF MS coupled with machine-learning algorithms could be used to develop a rapid and easy-to-use method to discriminate MRSA from MSSA. Considering that this method is easy to implement in routine microbiology laboratories, it suggests a cost-effective and time-efficient alternative to conventional resistance detection in the future to improve clinical treatment.

Study on Molecular Profiles of Staphylococcus aureus Strains: Spectrometric Approach

Staphylococcus aureus remains a major health problem responsible for many epidemic outbreaks. Therefore, the development of efficient and rapid methods for studying molecular profiles of S. aureus strains for its further typing is in high demand. Among many techniques, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI TOF MS) represents a timely, cost-effective, and reliable strain typing approach, which is still rarely used due to insufficient knowledge about the impact of sample preparation and analysis conditions on the molecular profiles and strain classification efficiency of S. aureus. The aim of this study was to evaluate the effect of the culture conditions and matrix type on the differentiation of molecular profiles of various S. aureus strains via the MALDI TOF MS analysis and different computational methods. The analysis revealed that by changing the culture conditions, matrix type, as well as a statistical method, the differentiation of S. aureus strains can be significantly improved. Therefore, to accelerate the incorporation of the MALDI-based strain typing in routine laboratories, further studies on the standardization and searching of optimal conditions on a larger number of isolates and bacterial species are of great need.

Rapid Discrimination of Methicillin-Resistant Staphylococcus aureus by MALDI-TOF MS

Methicillin-resistant Staphylococcus aureus (MRSA) is a serious pathogen in clinical settings and early detection is critical. Here, we investigated the MRSA discrimination potential of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) using 320 clinical S. aureus isolates obtained in 2005–2014 and 181 isolates obtained in 2018. We conducted polymerase chain reactions (PCR) for staphylococcal cassette chromosome mec (SCCmec) typing and MALDI-TOF MS to find specific markers for methicillin resistance. We identified 21 peaks with significant differences between MRSA and methicillin-susceptible S. aureus (MSSA), as determined by mecA and SCCmec types. Each specific peak was sufficient to discriminate MRSA. We developed two methods for simple discrimination according to these peaks. First, a decision tree for MRSA based on six MRSA-specific peaks, three MSSA-specific peaks, and two SCCmec type IV peaks showed a sensitivity of 96.5%. Second, simple discrimination based on four MRSA-specific peaks and one MSSA peak had a maximum sensitivity of 88.3%. The decision tree applied to 181 S. aureus isolates from 2018 had a sensitivity of 87.6%. In conclusion, we used specific peaks to develop sensitive MRSA identification methods. This rapid and easy MALDI-TOF MS approach can improve patient management.

The Continuing Threat of Methicillin-Resistant Staphylococcus aureus

Staphylococcus aureus has been an exceptionally successful pathogen, which is still relevant in modern age-medicine due to its adaptability and tenacity. This bacterium may be a causative agent in a plethora of infections, owing to its abundance (in the environment and in the normal flora) and the variety of virulence factors that it possesses. Methicillin-resistant S. aureus (MRSA) strains—first described in 1961—are characterized by an altered penicillin-binding protein (PBP2a/c) and resistance to all penicillins, cephalosporins, and carbapenems, which makes the β-lactam armamentarium clinically ineffective. The acquisition of additional resistance determinants further complicates their eradication; therefore, MRSA can be considered as the first representative of multidrug-resistant bacteria. Based on 230 references, the aim of this review is to recap the history, the emergence, and clinical features of various MRSA infections (hospital-, community-, and livestock-associated), and to summarize the current advances regarding MRSA screening, typing, and therapeutic options (including lipoglycopeptides, oxazolidinones, anti-MRSA cephalosporins, novel pleuromutilin-, tetracycline- and quinolone-derivatives, daptomycin, fusidic acid, in addition to drug candidates in the development phase), both for an audience of clinical microbiologists and infectious disease specialists.