Rapid Discrimination between Methicillin-Sensitive and Methicillin-Resistant &lt;i&gt;Staphylococcus aureus&lt;/i&gt; Using MALDI-TOF Mass Spectrometry

Sogawa, Kazuyuki; Watanabe, Masaharu; Ishige, Takayuki; Segawa, Syunsuke; Miyabe, Akiko; Murata, Syota; Saito, Tomoko; Sanda, Akihiro; Furuhata, Katsunori; Nomura, Fumio

doi:10.4265/bio.22.163

Cited by 35 publications

(36 citation statements)

References 30 publications

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“…aureus is based on bacterial culturing. There are many reports describing the application of immunoassays [57] and mass spectrometry [58] to improve and hasten the diagnosis. However, other issues should be tackled, such as differentiation between sporadic and contagious strains [12] and between strains associated with specific mastitis outcomes.…”

Section: Discussionmentioning

confidence: 99%

Comparative genomics of Staphylococcus aureus associated with subclinical and clinical bovine mastitis

Rocha

Silva

et al. 2019

PLoS ONE

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Many efforts have been made to understand the pathogenesis of bovine mastitis to reduce losses and promote animal welfare. Staphylococcus aureus may cause bovine clinical mastitis, but it is mainly associated with subclinical infection, which is usually persistent and can easily reoccur. Here, we conducted a comparative genomic analysis between strains of S . aureus causing subclinical infection (Sau170, 302, 1269, 1364), previously sequenced by our group, and two well-characterized strains causing clinical mastitis (N305 and RF122) to find differences that could be linked to mastitis outcome. A total of 146 virulence-associated genes were compared and no appreciable differences were found between the bacteria. However, several nonsynonymous single nucleotide polymorphisms (SNPs) were identified in genes present in the subclinical strains when compared to RF122 and N305, especially in genes encoding host immune evasion and surface proteins. The secreted and surface proteins predicted by in silico tools were compared through multidimensional scaling analysis (MDS), revealing a high degree of similarity among the strains. The comparison of orthologous genes by OrthoMCL identified a membrane transporter and a lipoprotein as exclusive of bacteria belonging to the subclinical and clinical groups, respectively. No hit was found in RF122 and N305 for the membrane transporter using BLAST algorithm. For the lipoprotein, sequences of Sau170, 302, 1269, and 1364 with identities between 68–73% were found in the MDS dataset. A conserved region found only in the lipoprotein genes of RF122 and N305 was used for primer design. Although the polymerase chain reaction (PCR) on field isolates of S . aureus did not validate the findings for the transporter, the lipoprotein was able to separate the clinical from the subclinical isolates. These results show that sequence variation among bovine S . aureus , and not only the presence/absence of virulence factors, is an important aspect to consider when comparing isolates causing different mastitis outcomes.

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Section: Discussionmentioning

confidence: 99%

Comparative genomics of Staphylococcus aureus associated with subclinical and clinical bovine mastitis

Rocha

Silva

et al. 2019

PLoS ONE

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“…Feature selection was applied to this study to detect which m/z features along with their average intensity may achieve the best performance in differentiating class MRSA from class MSSA. 24,25,28,29 The Lasso regression was utilized for feature selection to reduce the dimensions of features and select the most meaningful features effectively. 30 The regularization parameter (λ) was determined by five-fold cross-validation and grid search, and the coefficients were calculated for each feature.…”

Section: Feature Selectionmentioning

confidence: 99%

“…therefore, it could effectively analyze complex data and distinguish between MRSA and MSSA. 24,25 Our study developed a workflow using a discriminative machinelearning algorithm for rapid MRSA/MSSA classification in minutes based on m/z features employing the MALDI-TOF MS instrumentation routinely available in clinical microbiology laboratories. Furthermore, our approach can be readily integrated into the database currently used to facilitate subsequent studies into early diagnosis and control of MRSA and MSSA.…”

Section: Introductionmentioning

confidence: 99%

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

Liu

Hsu

et al. 2020

Rapid Comm Mass Spectrometry

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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.

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“…Still, modern laboratories now consider matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI ToF MS) as Gold Standard for staphylococcal identification ( Bernardo et al, 2002 ; Szabados et al, 2010 ; Zhu et al, 2015 ). Distinguishing MRSA from MSSA using MALDI ToF MS is controversial with positive reports ( Ueda et al, 2015 ; Rhoads et al, 2016 ; Sogawa et al, 2017 ) alternating with more negative ones ( Du et al, 2002 ; Goldstein et al, 2013 ). Recent papers document the successful distinction between MSSA and MRSA, even including characterization of different MRSA clones ( Østergaard et al, 2015 ; Zhang et al, 2015 ; Camoez et al, 2016 ).…”

Section: Culture-based Detection Of Mssa and Mrsamentioning

confidence: 99%

Laboratory-Based and Point-of-Care Testing for MSSA/MRSA Detection in the Age of Whole Genome Sequencing

Belkum

Rochas

2018

Front. Microbiol.

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Staphylococcus aureus is an opportunistic pathogen of animals and humans that is capable of both colonizing and infecting its eukaryotic host. It is frequently detected in the clinical microbiology routine laboratory. S. aureus is capable of acquiring antibiotic resistance traits with ease and, given its rapid global dissemination, resistance to meticillin in S. aureus has received extensive coverage in the popular and medical press. The detection of meticillin-resistant versus meticillin-susceptible S. aureus (MRSA and MSSA) is of significant clinical importance. Detection of meticillin resistance is relatively straightforward since it is defined by a single determinant, penicillin-binding protein 2a’, which exists in a limited number of genetic variants carried on various Staphylococcal Cassette Chromosomes mec. Diagnosis of MRSA and MSSA has evolved significantly over the past decades and there has been a strong shift from culture-based, phenotypic methods toward molecular detection, especially given the close correlation between the presence of the mec genes and phenotypic resistance. This brief review summarizes the current state of affairs concerning the mostly polymerase chain reaction-mediated detection of MRSA and MSSA in either the classical laboratory setting or at the point of care. The potential diagnostic impact of the currently emerging whole genome sequencing (WGS) technology will be discussed against a background of diagnostic, surveillance, and infection control parameters. Adequate detection of MSSA and MRSA is at the basis of any subsequent, more generic antibiotic susceptibility testing, epidemiological characterization, and detection of virulence factors, whether performed with classical technology or WGS analyses.

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Rapid Discrimination between Methicillin-Sensitive and Methicillin-Resistant <i>Staphylococcus aureus</i> Using MALDI-TOF Mass Spectrometry

Cited by 35 publications

References 30 publications

Comparative genomics of Staphylococcus aureus associated with subclinical and clinical bovine mastitis

Comparative genomics of Staphylococcus aureus associated with subclinical and clinical bovine mastitis

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

Laboratory-Based and Point-of-Care Testing for MSSA/MRSA Detection in the Age of Whole Genome Sequencing

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