Rapid Classification and Differentiation of Sepsis-Related Pathogens Using FT-IR Spectroscopy

Area of Science:

• Microbiology and Spectroscopy
• Infectious Disease Diagnostics
• Computational Biology and Cheminformatics

Background:

• Sepsis, a life-threatening immune response to infection, poses a significant global health challenge.
• Accurate identification of bacterial pathogens is crucial for effective antimicrobial therapy and improved patient outcomes in sepsis.
• Traditional culture-based methods for bacterial identification are time-consuming and have limitations.

Purpose of the Study:

• To evaluate the efficacy of Fourier-transform infrared (FT-IR) spectroscopy coupled with chemometrics for classifying and discriminating microbial species and strains from sepsis patients.
• To assess the potential of FT-IR spectroscopy as a rapid and accurate diagnostic tool for invasive infections.
• To explore the application of FT-IR for differentiating between bacterial and fungal pathogens, as well as specific strains and resistance profiles.

Main Methods:

• Analysis of 212 microbial isolates (202 bacterial, 10 fungal) from children with suspected sepsis using FT-IR spectroscopy.
• Application of chemometric techniques, including Principal Component Analysis (PCA), Principal Component Discriminant Function Analysis (PC-DFA), and Partial Least Squares-Discriminant Analysis (PLS-DA).
• Inclusion of quality control samples to manage variations in spectral analysis over time and across sample batches.

Main Results:

• Consistent clustering of 14 microbial genera was observed using PCA, with distinct separation of fungal (Candida) from bacterial samples.
• PC-DFA effectively discriminated between Gram-negative and Gram-positive bacteria, and differentiated between Staphylococcus aureus strains (MRSA vs. MSSA) and coagulase-negative staphylococci (CNS).
• PLS-DA achieved 98.4% accuracy in distinguishing Enterococcus from vancomycin-resistant enterococci and demonstrated species-level discrimination for Streptococcus and Candida.

Conclusions:

• FT-IR spectroscopy combined with chemometrics is a powerful tool for accurate microbial classification and discrimination in the context of invasive infections.
• This approach offers a promising alternative to traditional methods, potentially accelerating diagnosis and guiding antimicrobial treatment in sepsis.
• The findings support the broader clinical and microbiological application of FT-IR spectroscopy for enhanced pathogen identification and improved patient management.