Rapid Biotyping Discrimination of Methicillin-Susceptible and -Resistant Staphylococcus aureus Using Flow Injection Analysis–Ion Mobility–Mass Spectrometry

1. Introduction

Antimicrobial resistance (AMR) has emerged as one of the most critical public health issues [1]. AMR is expected to cause 10 million fatalities annually by 2050, emphasizing the importance of rapid and accurate identification of microorganisms [2].

Staphylococcus aureus is an opportunistic pathogen that colonizes about one-third of people worldwide and may result in invasive disorders such as endocarditis, skin and soft tissue infection, bacteremia, pneumonia, osteomyelitis, and medical implant–associated infection [3]. S. aureus infections are mostly challenging due to the prevalence of AMR among isolates, the most common and clinically relevant being methicillin-resistant S. aureus (MRSA) [4]. MRSA infections are associated with higher mortality and morbidity and longer hospital stays when compared with methicillin-susceptible S. aureus (MSSA) infections [5], causing a reported 20,000 deaths in 2018, the most deaths of any antibiotic-resistant bacteria in the United States [6]. Several MSSA lineages can also be extremely virulent, resulting in lethal infections [7, 8].

Therefore, rapid identification of S. aureus and discrimination between MSSA and MRSA strains are essential to ensure proper intervention strategies. However, the accurate optimization of treatments requires a comprehensive antibiotic-resistance profile, which may take up to 72 h using current culture-based approaches [9]. Such prolonged diagnostics often lead to empiric therapy, unnecessarily exposing patients to broad-spectrum agents such as vancomycin. The two most common modalities for MRSA testing are culture and polymerase chain reaction (PCR). Rapid sample-to-answer PCR platforms (e.g., GeneXpert) can provide results within about an hour [10], but their high cartridge cost and low throughput limit routine use [11]. Conversely, chromogenic agar culture is cost-effective and widely applied, particularly for the high-volume colonization screening of inpatients and long-term care residents [10], but it is labor-intensive and requires at least 18–24 h of incubation [12]. Consequently, new methodologies with increased efficiency and less labor-intensive screening are desperately needed [2].

Mass spectrometry (MS) is a promising analytical technique for the investigation of microorganisms because of its advantages in sensitivity, specificity, and speed [13]. MS-based bacterial screening has been mostly achieved by utilizing matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF MS) [14]. The commercially available MALDI Biotyper (Bruker Daltonics, Billerica, MA) and VITEK MS (bioMérieux S.A., Craponne, France) systems [15, 16], approved by the US Food and Drug Administration, can identify microbes at the species level but struggle to distinguish antimicrobial-resistant types [17]. As a result, MALDI-TOF MS is followed by the detection of antibiotic susceptibilities using traditional techniques. Such a delay in diagnostics makes it difficult to rapidly select proper antimicrobial therapies [18]. Several ionization approaches use membrane lipids as diagnostic markers for discriminating different bacteria [19, 20]. However, lipids might have an array of isomers due to changes in headgroup, chain length, sn-position, the position of the double bond, and configuration, making structural studies difficult [21, 22].

An alternative rapid analytical technique is offered by flow injection analysis mass spectrometry (FIA-MS), in which the samples are injected into the ionization source of an MS without any chromatographic separation. The utilization of FIA-MS with contemporary high-resolution MS (HRMS), such as Orbitrap and TOF, makes it possible to identify hundreds to thousands of m/z features in biological samples [23, 24]. Compared with liquid chromatography (LC) analysis, FIA may be utilized to deliver a sample aliquot to the MS without chromatographic separation, thereby resulting in run times from 20 s to 2 min, significantly reducing the analysis time and solvent used.

Ion mobility spectrometry (IMS) is a gas-phase method that separates and distinguishes structurally distinct compounds based on their drift time and can provide collisional cross sections using collisions between analyte ions and the inert buffer gas under the influence of a weak electric field [25]. Traveling wave ion mobility spectrometry (TWIMS) differs from other IMS techniques by employing an oscillating electric field to generate voltage “waves” along the ion path, propelling ions through inert gas collisions. Structures for lossless ion manipulation (SLIM) technology build upon the oscillating fields used in TWIMS and incorporate additional applied potentials across sandwiched printed circuit boards. This configuration enables a nonlinear (serpentine) ion path, thereby increasing resolution through extended path length and offering high-resolution ion mobility (HR-IM) [26].

Therefore, the current study was conducted to develop a method for rapid discrimination between MSSA and MRSA using a flow injection analysis–ion mobility–high-resolution mass spectrometry (FIA-IM-HRMS) approach.

2. Materials and Methods

3. Results

3.1. FIA-IM-HRMS Analysis of S. aureus Samples

In our initial analysis of the data, we focused on visual inspection of spectra to identify differences between MRSA and MSSA colonies. The FIA-IM-HRMS analysis of MSSA wild type (S. aureus 12600) and MRSA (S. aureus 131) revealed spectral differences based on two peaks by comparing the spectra with blank and negative control (growth media) samples after incubation for 24 h. The samples were analyzed in duplicate. A prominent, singly charged peak at m/z 691.613 was found to be present in both MSSA (S. aureus 12600) and MRSA (S. aureus 131), while a triply charged peak at m/z 733.792 was found only in MRSA samples, as shown in Figure 1.

3.2. Optimization of Assay Time

Visual inspection of the spectra from the FIA-IM-HRMS analysis of MSSA (S. aureus 12600) and MRSA (S. aureus 131) samples showed that differentiation can be observed based on the peak at m/z 733.792, which was elevated only in MRSA. The next assignment was to optimize an incubation period that could be used for rapid analysis and determine whether the observed peak was dependent on growth time. Therefore, the strains (S. aureus 12600 and S. aureus 131) were incubated at three different periods (3 h, 6 h, and 24 h) to observe any changes in signal intensity for m/z 733.792 with respect to incubation time. The intensity of the peak was found to increase with increasing incubation time, as represented in Figure 2. It can be observed that the peak at 6 h had a higher intensity compared to 3 h and lower than at 24 h. A considerable intensity of the peak was present at the 6 h period, and incubating for 24 h did not substantially increase the peak intensity. We also compared MRSA and MSSA at 6 h and observed that the peak at m/z 733.790 was very low in abundance in the MSSA strain (Supplemental Figure S1). Based on these observations, the incubation time at 6 h was selected for further validation.

3.3. Validation in Other Species and Clinical Isolates

The observed peaks (m/z 733.790 and m/z 691.613) were further validated by analyzing five different species from the same genus, including S. caprae, S. epidermidis, S. lugdunensis, S. capitis, and S. warneri, after incubating for 6 h. Neither of the m/z values were observed in any of these species, indicating specificity for MRSA and MSSA (Figure 3). For further validation of the study, a total of 20 clinical isolates (MSSA = 10, MRSA = 10) were also analyzed after incubating for 6 h. Data analysis revealed that the peak at m/z 691.613 (not shown) was found in all clinical isolates, while the peak at m/z 733.790 was only observed in MRSA clinical isolates and not in MSSA clinical isolates (Supplementary Figure S2 and S3, respectively). The intensity of the peak at m/z 733.790 after incubation for 6 h was not very intense in the MRSA clinical isolates but was observed to be the peak of interest based on the m/z value, the charge state (+3), and its drift time (IM) (Figure 4A–C). The findings indicate that these peaks are only found in S. aureus and could be used to identify it as either MSSA or MRSA with m/z 691.613 and determine its resistance to methicillin (MRSA) using m/z 733.790. In the absence of chromatography or MS/MS, an additional dimension (i.e., IM) of analysis is important to reduce chemical noise and improve detection. In this case, the use of IM was key in reducing chemical noise, as can be observed when comparing the total ion signal as might be done in a typical FIA-HRMS experiment versus adding the IM dimension (Figure 4B and C). When IM is added, then chemical noise is significantly reduced to show a clear isotopic pattern for m/z 733.790 (Figure 4C).

3.4. Initial Identification of Marker Peaks

Another important task in a biomarker study is to identify the proposed marker peaks. The peak at m/z 691.613 was not identified due to poor MS/MS fragmentation, while the ion at m/z 733.791 was identified using de novo sequencing by matching the fragments for the amino acid losses from the MS/MS spectrum. The approach led us to the identification of a known peptide, phenol-soluble modulin alpha 4 (PSMα4), with a sequence of 20 amino acids (MAIVGTIIKIIKAIIDIFAK) as shown (with different colors) in the annotated MS/MS spectrum (Figure 5). The N-formylation is a common modification in bacterial proteins [28]. Hence, the sequence of the identified peptide has a monoisotopic mass of 2170.342 and is N-formylated, having a mass shift of 28 daltons (Da) to give a mass of 2198.347. Therefore, the [M + 3H]³⁺ peak of the peptide would appear at m/z 733.789 (theoretical), matching our observed m/z value. The remaining five amino acids are not presented in the spectrum due to the lack of sequence coverage. While the identified peptide has been frequently demonstrated for its role in S. aureus pathogenicity and virulence [29], we propose that the peak at m/z 733.792 could be used as a marker for rapid discrimination between MRSA and MSSA in clinical samples.

3.5. Multivariate Statistical Analysis

For further validation of the proposed marker peak at m/z 733.790 in clinical isolates, multivariate statistical analysis was performed using MetaboAnalyst. The t-test analysis resulted in 34 significant features (p ≤ 0.05), which were further subjected to hierarchical clustering analysis for the comparison between the MSSA and MRSA strains, where only the top 30 are displayed in a heatmap (Figure 6A). The heatmap shows that the intensities of the features that correspond to PSMα4 (peaks at 733 and 734 from the isotopic pattern) are higher in MRSA strains compared with MSSA. We then conducted sPLS-DA to evaluate the variable selection of two-block datasets in a one-step procedure while integrating variables of two types, improving interpretability via graphical outputs. Figure 6B shows the sPLS-DA score plot that separates the two groups into two components based on the features, while Figure 6C shows the error rates of the sPLS-DA classification model. The model had a 5% error rate with two components, indicating strong performance. Figure 6D represents the VIP scores from the sPLS-DA and shows the variables that were either up- or downregulated. In addition to the peaks corresponding to PSMα4, the VIP score plot also shows a feature at m/z 769.1418, which we identified to be PSMα2 with a sequence of 21 amino acids (MGIIAGIIKFIKGLIEKFTGK) using the annotated MS/MS spectra in Supplementary Figure S4. The monoisotopic mass of this peptide from the sequence is 2276.369, while N-formylation causes a mass shift of 28 Da (2304.364). Therefore, the [M + 3H]³⁺ peak would give m/z 769.129 (theoretical), and our measured m/z was 769.142. This peptide has also been identified for its role in S. aureus pathogenicity and virulence [30]. The peaks at m/z 763.176 and 763.489 can be assigned to PSMα1 using [M + 3H]³⁺ (level 3 identification, the exact m/z of 763.121). We then returned to the incubation experiment to further validate the presence of PSMα1 and PSMα2 and show that both peaks are present at all time points but are observed at their highest at 6 h and 24 h (Supplementary Figure S5).

The most significant VIP and the most significant from the t-test was m/z 246.151 (p = 2.78 × 10^⁻8), and it was elevated in MSSA. A search for this m/z value in the Human Metabolome Database matched to S-3-oxodecanoyl cysteamine and several dipeptides (Asn-Leu, Ala-Arg, Val-Glu). The exact identification of this small molecule was not conducted to confirm the validity of the assignment. Our model was able to discriminate between both MRSA and MSSA based on several significant features observed from FIA-IM-MS. Hence, the statistical analysis also validated the efficacy of the initial proposed marker (m/z 733.790) for discriminating resistant strains from sensitive ones.

4. Discussion

In this study, we developed a rapid FIA-IM-HRMS method for discrimination between MSSA and MRSA strains after incubating for 6 h and proposed a marker peak at m/z 733.790, which can be utilized for this discrimination. We also presented work from multivariate statistical analysis that identified two other peaks, which were discriminatory for MRSA versus MSSA at m/z 763.176 and 769.180, independently of the peak at 733.790. The marker peaks were identified as peptides from a peptide family known as PSMs. Previously, a similar approach was used for typing and discrimination between MSSA and MRSA based on some characteristic peaks using intact cell MS. However, no peaks were identified for any specific compounds [31]. Recently, an untargeted lipidomic study has also been conducted to track differences between MSSA and MRSA strains, in which three lipid species were observed to differ between the two by using UHPLC-MS [39].

S. aureus can produce a variety of pathogenic elements that harm its host and circumvent immunity, accounting for its ability to survive in the human host [40]. Numerous pathogenic and virulent agents, including enterotoxins, α-toxins, toxic shock syndrome toxins, and PSMs, can be produced by S. aureus [41]. PSMs, including δ-toxin, can make up 60% of all proteins produced in a culture grown overnight and constitute the most prominent peptides. The family of PSM peptides plays an important role in the pathogenicity of S. aureus [42, 43].

The formation of biofilm and virulence in S. aureus is regulated by the family of these small toxin peptides known as PSMs [29, 44]. The PSMs contribute to pathogenesis in a variety of ways, including killing red and white blood cells, regulating both adaptive and innate immune responses, promoting skin colonization, and contributing to the emergence of infections associated with biofilms [29].

The peptide identified as PSMα4 in this study was previously reported by Kocurek et al. in the S. aureus strain (MSSA 476) as a (+3) charged peak at m/z 733.7894 and has been shown to cause the lysis of human neutrophils [45]. Its increased production is reported to be associated with high virulence in specific community-associated MRSA strains [42]. The peptide PSMα4 from the supernatant of the USA300 strain culture has been shown to induce the release of heparin-binding protein (HBP) from polymorphonuclear neutrophils (PMNs), and this HBP release from PMNs induced by PSMα4 causes the vascular leakage [46].

Despite the known association of PSMα4 with pathogenicity, there is a lack of reports on its association with S. aureus antibiotic resistance. Future research should evaluate the effectiveness of our method employing direct inoculation and broth extraction, which could improve workflow efficiency and enable integration with automated systems. Such advancements would improve utility compared to chromogenic agar by combining rapid detection with higher throughput and reduced labor. In addition to genetic assays, protein-based detection of the mecA gene product PBP2a has been explored as a diagnostic marker for MRSA, using immunochromatographic and latex agglutination assays [47, 48]. While our method focuses on small molecules and peptide signatures, these approaches highlight complementary strategies that may further support rapid MRSA detection and reveal the association of the proposed marker peptide with the development of AMR among S. aureus strains.

5. Conclusion

Our study revealed a rapid assay for discrimination between MRSA and MSSA after 6 h of incubation. The developed method using FIA-IM-HRMS has substantially improved the detection time for discrimination between resistant and sensitive strains of S. aureus, which may provide an opportunity for early intervention and guided therapy. The IM dimension was key in reducing chemical noise to enable detection in the absence of chromatography. The proposed biomarker peaks that could be used for discrimination have also been identified from the family of PSMs, which may play a pivotal role in the early identification and detection of AMR, and future work on developing a quantitative assay could help to define clinical reference ranges needed for diagnostics. The role of the identified peptides in the development of AMR is not fully understood. However, future work on its role and association in the development of AMR in clinical isolates could be a potential breakthrough in early and rapid AMR diagnostics.

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