Performance Comparison Between Fourier-Transform Infrared Spectroscopy-based IR Biotyper and Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for Strain Diversity

Use of a national repository of Fourier-transform infrared spectroscopy spectra enables fast detection of silent outbreaks and prevention of spread of new antibiotic-resistant sequence types

BACKGROUND

The reference microbiology laboratory of Israel's National Institute for Antibiotic Resistance and Infection Control has established a national repository of isolates analyzed by Fourier-transform infrared (FTIR) spectroscopy and their spectra. Healthcare institutions send antibiotic-resistant isolates as part of outbreak investigation, periodic nation-wide collection of specific species, or point prevalence studies. Here, we describe the use of a national FTIR repository to detect the emergence and spread of new sequence types and resistance mechanisms.

METHODS

Using FTIR, we produced dendrograms of outbreaks and periodic country-level dendrograms of isolates from selected species. When FTIR identified new clusters that were distinct from previously characterized clusters, they were investigated further by whole genome sequencing.

RESULTS

FTIR analysis uncovered two clones new to Israel: NDM-5-producing E. coli ST650 harboring a novel plasmid, and NDM-producing K. pneumoniae ST307.

CONCLUSIONS

Establishing regional or national FTIR repositories could serve as a simple and effective tool for early detection of new antibiotic-resistant clones.

Microbial Identification Through Multispectral Infrared Imaging of Colonies: A New Type of Morpho-Spectral Fingerprinting

We describe a proof of concept for a new microbial identification technique using Direct Frequency Infrared (DFIR) multispectral imaging. This approach combines Quantum Cascade Laser (QCL) light sources with a microbolometer array in a lensless configuration to capture detailed multispectral images of microbial colonies. These optical fingerprints blend both morphological and spectral information, without the need for staining or colony picking. A proof-of-concept database was acquired, comprising 10 strains from 8 species across 4 distinct genera. In total, 2253 microbial colonies were imaged at 9 different mid-infrared wavelengths. Machine learning classification correctly identified up to 94.4% ± 1.6 of colonies fingerprints, efficiently discriminating even closely related strains. Reducing the number of wavelengths to 4 maintained high classification performance, demonstrating the method's robustness. The resulting system is faster and simpler than existing FTIR imaging systems, making it a promising tool for microbial identification.

A Comprehensive Methodology for Microbial Strain Typing Using Fourier-Transform Infrared Spectroscopy

Timely and accurate detection and characterization of microbial threats is crucial for effective infection and outbreak management. Additionally, in food production, rapid microbe identification is indispensable for maintaining quality control and hygiene standards. Current methods for typing microbial strains often rely on labor-intensive, time-consuming, and expensive DNA- and sera-serotyping techniques, limiting their applicability in rapid-response scenarios. In this context, the IR Biotyper®, utilizing Fourier-transform infrared (FTIR) spectroscopy, offers a novel approach, providing specific spectra for fast strain typing within 3 h. This methodology article serves as a comprehensive resource for researchers and technicians aiming to utilize FTIR spectroscopy for microbial strain typing. It encompasses detailed guidelines on sample preparation, data acquisition, and analysis techniques, ensuring the generation of reliable and reproducible results. We highlight the IR Biotyper®'s rapid and accurate discrimination capabilities, showcasing its potential for real-time pathogen monitoring and source-tracking to enhance public health and food safety. We propose its integration as an early screening method, followed by more detailed analysis with whole-genome sequencing, to optimize detection accuracy and response efficiency in microbial surveillance systems.

Comparative analysis of IR-Biotyper, MLST, cgMLST, and WGS for clustering of vancomycin-resistant Enterococcus faecium in a neonatal intensive care unit

Healthcare-associated infections caused by vancomycin-resistant Enterococcus faecium (VREFM) pose a significant threat to healthcare. Confirming the relatedness of the bacterial isolates from different patients is challenging. We aimed to assess the efficacy of IR-Biotyper, multilocus sequencing typing (MLST), and core-genome MLST (cgMLST) in comparison with whole-genome sequencing (WGS) for outbreak confirmation in the neonatal intensive care unit (NICU). Twenty VREFM isolates from four neonates and ten control isolates from unrelated patients were analyzed. Genomic DNA extraction, MLST, cgMLST, and WGS were performed. An IR-Biotyper was used with colonies obtained after 24 h of incubation on tryptic soy agar supplemented with 5% sheep blood. The optimal clustering cutoff for the IR-Biotyper was determined by comparing the results with WGS. Clustering concordance was assessed using the adjusted Rand and Wallace indices. MLST and cgMLST identified sequence types (ST) and complex types (CT), revealing suspected outbreak isolates with a predominance of ST17 and CT6553, were confirmed by WGS. For the IR-Biotyper, the proposed optimal clustering cut-off range was 0.106-0.111. Despite lower within-run precision, of the IR-Biotyper, the clustering concordance with WGS was favorable, meeting the criteria for real-time screening. This study confirmed a nosocomial outbreak of VREFM in the NICU using an IR-Biotyper, showing promising results compared to MLST. Although within-run precision requires improvement, the IR-Biotyper demonstrated high discriminatory power and clustering concordance with WGS. These findings suggest its potential as a real-time screening tool for the detection of VREFM-related nosocomial outbreaks.

IMPORTANCE

In this study, we evaluated the performance of the IR-Biotyper in detecting nosocomial outbreaks caused by vancomycin-resistant Enterococcus faecium, comparing it with MLST, cgMLST, and WGS. We proposed a cutoff that showed the highest concordance compared to WGS and assessed the within-run precision of the IR-Biotyper by evaluating the consistency in genetically identical strain when repeated in the same run.

Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing

The reliability of Fourier-transform infrared (FT-IR) spectroscopy for Klebsiella pneumoniae typing and outbreak control has been previously assessed, but issues remain in standardization and reproducibility. We developed and validated a reproducible FT-IR with attenuated total reflectance (ATR) workflow for the identification of K. pneumoniae lineages. We used 293 isolates representing multidrug-resistant K. pneumoniae lineages causing outbreaks worldwide (2002-2021) to train a random forest classification (RF) model based on capsular (KL)-type discrimination. This model was validated with 280 contemporaneous isolates (2021-2022), using wzi sequencing and whole-genome sequencing as references. Repeatability and reproducibility were tested in different culture media and instruments throughout time. Our RF model allowed the classification of 33 capsular (KL)-types and up to 36 clinically relevant K. pneumoniae lineages based on the discrimination of specific KL- and O-type combinations. We obtained high rates of accuracy (89%), sensitivity (88%), and specificity (92%), including from cultures obtained directly from the clinical sample, allowing to obtain typing information the same day bacteria are identified. The workflow was reproducible in different instruments throughout time (>98% correct predictions). Direct colony application, spectral acquisition, and automated KL prediction through Clover MS Data analysis software allow a short time-to-result (5 min/isolate). We demonstrated that FT-IR ATR spectroscopy provides meaningful, reproducible, and accurate information at a very early stage (as soon as bacterial identification) to support infection control and public health surveillance. The high robustness together with automated and flexible workflows for data analysis provide opportunities to consolidate real-time applications at a global level. IMPORTANCE We created and validated an automated and simple workflow for the identification of clinically relevant Klebsiella pneumoniae lineages by FT-IR spectroscopy and machine-learning, a method that can be extremely useful to provide quick and reliable typing information to support real-time decisions of outbreak management and infection control. This method and workflow is of interest to support clinical microbiology diagnostics and to aid public health surveillance.

Application of Fourier Transform Infrared Spectroscopy to Discriminate Two Closely Related Bacterial Species: Bacillus anthracis and Bacillus cereus Sensu Stricto

Fourier transform infrared spectroscopy (FTIRS) is a diagnostic technique historically used in the microbiological field for the characterization of bacterial strains in relation to the specific composition of their lipid, protein, and polysaccharide components. For each bacterial strain, it is possible to obtain a unique absorption spectrum that represents the fingerprint obtained based on the components of the outer cell membrane. In this study, FTIRS was applied for the first time as an experimental diagnostic tool for the discrimination of two pathogenic species belonging to the Bacillus cereus group, Bacillus anthracis and Bacillus cereus sensu stricto; these are two closely related species that are not so easy to differentiate using classical microbiological methods, representing an innovative technology in the field of animal health.

The Fourier-transform infrared spectroscopy-based method as a new typing tool for Candida parapsilosis clinical isolates

The Fourier-transform infrared spectroscopy-based IR Biotyper is a straightforward typing tool for bacterial species, but its use with Candida species is limited. We applied IR Biotyper to Candida parapsilosis, a common cause of nosocomial bloodstream infection (BSI), which is aggravated by the intra-hospital spread of fluconazole-resistant isolates. Of 59 C. parapsilosis isolates studied, n = 56 (48 fluconazole-resistant and 8 fluconazole-susceptible) and n = 3 (2 fluconazole-resistant and 1 fluconazole-susceptible) isolates, respectively, had been recovered from BSI episodes in 2 spatially distant Italian hospitals. The latter isolates served as an outgroup. Of fluconazole-resistant isolates, n = 40 (including one outgroup) harbored the Y132F mutation alone and n = 10 (including one outgroup) harbored both Y132F and R398I mutations in the ERG11-encoded azole-target enzyme. Using a microsatellite typing method, which relies on the amplification of genomic short tandem repeats (STR), two major clusters were obtained based on the mutation(s) (Y132F or Y132F/R398I) present in the isolates. Regarding IR Biotyper, each isolate was analyzed in quintuplicate using an automatic (i.e., proposed by the manufacturer's software) or tentative (i.e., proposed by us) cutoff value. In the first case, four clusters were identified, with clusters I and II formed by Y132F or Y132F/R398I isolates, respectively. In the second case, six subclusters (derived by the split of clusters I and II) were identified. This allowed to separate the outgroup isolates from other isolates and to increase the IR Biotyper typeability. The agreement of IR Biotyper with STR ranged from 47% to 74%, depending on type of cutoff value used in the analysis. IMPORTANCE Establishing relatedness between clinical isolates of Candida parapsilosis is important for implementing rapid measures to control and prevent nosocomial transmission of this Candida species. We evaluated the FTIR-based IR Biotyper, a new typing method in the Candida field, using a collection of fluconazole-resistant C. parapsilosis isolates supposed to be genetically related due to the presence of the Y132F mutation. We showed that IR Biotyper was discriminatory but not as much as the STR method, which is still considered the method of choice. Further studies on larger series of C. parapsilosis isolates or closely related Candida species will be necessary to confirm and/or extend the results from this study.