Rapid detection of S.aureus and S.pneumoniae by real-time analysis of volatile metabolites

A prompt and accurate identification of the causative pathogens of a bacterial infection is essential for providing patients with adequate treatments to reduce mortality and to prevent antibiotic resistance.

This study "Rapid Detection of Staphylococcus aureus and Streptococcus pneumoniae by Real-time Analysis of Volatile Metabolites" delves into the utilization of Secondary Electrospray Ionization-High Resolution Mass Spectrometry (SESI-HRMS) for identifying pathogens in bacterial infections, underscoring the necessity for swift and precise pathogen identification to enhance treatment and curb antibiotic resistance.

This research showcases the proficiency of SESI-HRMS in discerning between S. aureus and S. pneumoniae using their distinct volatile organic compounds (VOCs). Even at low bacterial counts ranging from 140 to 2000 colony-forming units (CFUs) per plate, the technique effectively identifies these bacteria. This rapid, non-invasive diagnostic method is pivotal for early detection and treatment of infections caused by these prevalent pathogens, with the study also touching on its limitations and possible clinical applications.

The researchers noted that VOCs emitted by S. aureus or S. pneumoniae cultures on blood agar plates were detected within minutes, allowing for species and even strain-level differentiation within hours. Clinical patient samples yielded distinguishable fingerprints within minutes, predominantly showing a separation between samples with live bacterial growth and those without any growth. The development of this technique promises to shorten the time required for microbiological diagnosis and enhance patient-specific treatment.

The study also involved measuring low CFUs of these bacteria over 15 hours using SESI-HRMS, supplemented by time-lapse imaging to track bacterial growth for up to 38 hours in certain cases. This comprehensive approach underlines SESI-HRMS's potential in revolutionizing diagnostic procedures in microbiology.

(A) Example of an unspecific feature time trace at m/z 144.04765 with proposed molecular formula [C6H11O2NS]+ acquired by SESI-HRMS over 15 h of measurement is illustrated for S. aureus Cowan1.

(B) Corresponding TL normalized pixel intensity of the measured replicates along with pictures showing visually captured growth at 15, 24, and 38 h after the bacteria were put on the plate. The four colored lines represent four biological replicates and the four dashed black lines represent the four control replicates. The colors indicate how many CFUs were put on the blood agar plate for each replicate measured. MS=Mass spectrometer, CFU = Colony forming unit, TL = Time lapse.

Detection and quantification of low-level bacterial colony forming units (CFUs):

Together with TL image row examples at 15, 24, and 38 h of measurement. No bacteria were visually detected by the TL system by the end of SESI-HRMS acquisition at 15 h. In contrast, m/z 144.04765 in S. aureus Cowan1 was detected by SESI-HRMS in all four replicates within the first minutes of growth/measurement even if CFU numbers are as low as 140 CFUs. To control for bacterial growth, the plates were further analyzed via TL beyond the 15 h analysis with SESI-HRMS, confirming the appearance of colonies after 24 h of growth. In general, growth was detected for all bacterial strains under low CFU condition as well as under high CFU condition.

Discrimination ability: Real-time detection of unique features on species and strain level:

In the study, 392 characteristics were assigned to Staphylococcus aureus and Streptococcus pneumoniae bacterial species, with strain-specific characteristics. By increasing the density of cultures to billions of CFU, 1,269 unique characteristics were identified for different strains and species. Three specific features were only found in S. aureus Cowan1 and 26 features in S. aureus JE2. For S. pneumoniae, 15 specific features were present in both strains D39 and TIGR4. Higher signal abundance and reproducibility were observed in high-density cultures. This approach demonstrates the utility of SESI-HRMS to identify strain- and species-specific features, even in complex samples such as unprocessed tissues and prostheses in real time.

Measurement of clinical patient samples by SESI-HRMS:

The study tested SESI-HRMS on 17 clinical samples from 13 patients, including samples from heart valves, skin, deep tissue, and foreign bodies like pacemakers. Most patients had undergone antibiotic treatment, which hindered bacterial growth in conventional culture diagnostics. However, the SESI-HRMS method identified specific features in clinical samples, demonstrating its potential in real-world applications. This targeted analysis, visualized through t-SNE, showed distinct clustering for clinical samples containing S. aureus (MSSA).

Conclusion:

This study demonstrates that SESI-HRMS can detect unique features of S. aureus and S. pneumoniae in real-time, even in low bacterial counts (less than 103 CFUs). It highlights the method's ability to differentiate between these pathogens, crucial for early diagnosis and treatment. This approach is faster and requires less sample preparation compared to traditional methods, offering a balance between DNA-based and mass spectrometric techniques. It has the potential for automation and real-time monitoring, significantly improving the efficiency and accuracy of bacterial infection diagnostics.