Comparison of fast Fourier transform infrared spectroscopy biotyping with whole genome sequencing-based genotyping in common nosocomial pathogens

Bacterial discrimination by Fourier transform infrared spectroscopy, MALDI-mass spectrometry and whole-genome sequencing

Aim: Proof-of-concept study, highlighting the clinical diagnostic ability of FT-IR compared with MALDI-TOF MS, combined with WGS. Materials & methods: 104 pathogenic isolates of Neisseria meningitidis, Streptococcus pneumoniae, Streptococcus pyogenes and Staphylococcus aureus were analyzed. Results: Overall prediction accuracy was 99.6% in FT-IR and 95.8% in MALDI-TOF-MS. Analysis of N. meningitidis serogroups was superior in FT-IR compared with MALDI-TOF-MS. Phylogenetic relationship of S. pyogenes was similar by FT-IR and WGS, but not S. aureus or S. pneumoniae. Clinical severity was associated with the zinc ABC transporter and DNA repair genes in S. pneumoniae and cell wall proteins (biofilm formation, antibiotic and complement permeability) in S. aureus via WGS. Conclusion: FT-IR warrants further clinical evaluation as a promising diagnostic tool.

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.

Use of Fourier-transform infrared spectroscopy for real-time outbreak investigation of OXA-48-producing Escherichia coli

BACKGROUND

Efficient infection control during carbapenem-resistant Enterobacterales outbreaks demands rapid and simple techniques for outbreak investigations. WGS, the current gold standard for outbreak identification, is expensive, time-consuming and requires a high level of expertise. Fourier-transform infrared (FTIR) spectroscopy (IR Biotyper) is a rapid typing method based on infrared radiation applied to samples, which provides a highly specific absorption spectrum.

OBJECTIVES

To investigate an outbreak of OXA-48-producing Escherichia coli in real-time using FTIR and subsequently compare the results with WGS.

METHODS

Twenty-one isolates were collected during a nosocomial outbreak, and identification and antibiotic susceptibilities were confirmed by VITEK®2. FTIR was conducted for all isolates, and nine representative isolates were sequenced.

RESULTS

FTIR was able to correctly determine the clonal relatedness of the isolates and to identify the outbreak cluster, as confirmed by WGS. By WGS, isolates in the main FTIR cluster belonged to the same MLST type and core-genome MLST type, and they harboured similar plasmids and resistance genes, whereas the singletons external to the FTIR cluster had different genetic content.

CONCLUSIONS

FTIR can operate as a rapid, efficient and reliable first-line tool for outbreak investigations during a real-time ongoing E. coli outbreak, which can contribute to limiting the spread of pathogens.

Evaluation of Fourier transform-infrared spectroscopy (FT-IR) as a control measure for nosocomial outbreak investigations

Whole-genome sequencing (WGS) provides greater resolution than other molecular epidemiology strategies and is emerging as a new gold standard approach for microbial strain typing. The Bruker IR Biotyper is designed as a screening tool to identify bacterial isolates that require WGS to establish accurate relationships, but its performance and utility in nosocomial outbreak investigations have not been thoroughly investigated. Here, we evaluated the IR Biotyper by retrospectively examining isolates tested by WGS during investigations of potential nosocomial transmission events or outbreaks. Ninety-eight clinical isolates from 14 different outbreak investigations were examined: three collections of Acinetobacter baumannii (n = 2, n = 9, n = 5 isolates in each collection), one of Escherichia coli (n = 16), two of Pseudomonas aeruginosa (n = 2 and n = 5), two of Serratia marcescens (n = 9 and n = 7), five of Staphylococcus aureus (n = 8, n = 4, n = 3, n = 3, n = 17), and one of Stenotrophomonas maltophilia (n = 8). Linear regression demonstrated a weak, positive correlation between the number of pairwise genome-wide single-nucleotide polymorphisms (SNPs) and IR Biotyper spectral distance values for Gram-positive (r = 0.43, P ≤ 0.0001), Gram-negative (r = 0.1554, P = 0.0639), and all organisms combined (r = 0.342, P ≤ 0.0001). Overall, the IR Biotyper had a positive predictive value (PPV) of 55.81% for identifying strains that were closely related by genomic identity, but a negative predictive value (NPV) of 86.79% for identifying unrelated isolates. When experimentally adjusted cut-offs were applied to A. baumannii, P. aeruginosa, and E. coli, the PPV was 62% for identifying strains that were closely related and the NPV was 100% for identifying unrelated isolates. Implementation of the IR Biotyper as a screening tool in this cohort would have reduced the number of Gram-negative isolates requiring further WGS analysis by 50% and would reduce the number of S. aureus isolates needing WGS resolution by 48%.

Fourier-transform infrared spectroscopy for typing of vancomycin-resistant Enterococcus faecium: performance analysis and outbreak investigation

Vancomycin-resistant Enterococci, mainly Enterococcus faecium (VREfm), are causing nosocomial infections and outbreaks. Bacterial typing methods are used to assist in outbreak investigations. Most of them, especially genotypic methods like multi-locus sequence typing (MLST), whole genome sequencing (WGS), or pulsed-field gel electrophoresis, are quite expensive and time-consuming. Fourier-transform infrared (FT-IR) spectroscopy assesses the biochemical composition of bacteria, such as carboxyl groups in polysaccharides. It is an affordable technique and has a faster turnaround time. Thus, the aim of this study was to evaluate FT-IR spectroscopy for VREfm outbreak investigations. Basic performance requirements like reproducibility and the effects of incubation time were assessed in distinct sample sets. After determining a FT-IR spectroscopy cut-off range, the clustering agreement between FT-IR and WGS within a retrospective (n: 92 isolates) and a prospective outbreak (n: 15 isolates) was investigated. For WGS an average nucleotide identity (ANI) cut-off score of 0.999 was used. Basic performance analysis showed reproducible results. Moreover, FT-IR spectroscopy readouts showed a high agreement with WGS-ANI analysis in clinical outbreak investigations (V-measure 0.772 for the retrospective and 1.000 for the prospective outbreak). FT-IR spectroscopy had a higher discriminatory power than MLST in the outbreak investigations. After determining cut-off values to achieve optimal resolution, FT-IR spectroscopy is a promising technique to assist in outbreak investigation as an affordable, easy-to-use tool with a turnaround time of less than one day. IMPORTANCE Vancomycin-resistant Enterococci, mainly Enterococcus faecium (VREfm), are a frequent cause of nosocomial outbreaks. Several bacterial typing methods are used to track transmissions and investigate outbreaks, whereby genome-based techniques are used as a gold standard. Current methods are either expensive, time-consuming, or both. Additionally, often, specifically trained staff needs to be available. This study provides insight into the use of Fourier-transform infrared (FT-IR) spectroscopy, an affordable, easy-to-use tool with a short turnaround time as a typing method for VREfm. By assessing clinical samples, this work demonstrates promising results for species discrimination and reproducibility. FT-IR spectrosopy shows a high level of agreement in the analysis of VREfm outbreaks in comparison with whole genome sequencing-based methods.