Application of Fourier transform infrared spectroscopy for real-time typing of Acinetobacter baumannii outbreak in intensive care unit

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.

Perspectives of FTIR as Promising Tool for Pathogen Diagnosis, Sanitary and Welfare Monitoring in Animal Experimentation Models: A Review Based on Pertinent Literature

Currently, there is a wide application in the literature of the use of the Fourier Transform Infrared Spectroscopy (FTIR) technique. This basic tool has also proven to be efficient for detecting molecules associated with hosts and pathogens in infections, as well as other molecules present in humans and animals' biological samples. However, there is a crisis in science data reproducibility. This crisis can also be observed in data from experimental animal models (EAMs). When it comes to rodents, a major challenge is to carry out sanitary monitoring, which is currently expensive and requires a large volume of biological samples, generating ethical, legal, and psychological conflicts for professionals and researchers. We carried out a survey of data from the relevant literature on the use of this technique in different diagnostic protocols and combined the data with the aim of presenting the technique as a promising tool for use in EAM. Since FTIR can detect molecules associated with different diseases and has advantages such as the low volume of samples required, low cost, sustainability, and provides diagnostic tests with high specificity and sensitivity, we believe that the technique is highly promising for the sanitary and stress and the detection of molecules of interest of infectious or non-infectious origin.

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.

WITHDRAWN: Evaluation of Fourier Transform Infrared spectroscopy (IR Biotyper) as a complement to Whole genome sequencing (WGS) to characterise Enterobacter cloacae , Citrobacter freundii and Klebsiella pneumoniae isolates recovered from hospital sinks

The authors have withdrawn their manuscript due to becoming aware of methodology issues related to the curation of the training set used to determine cut-off values for Biotyper cluster assignation and lack of replicate measurements on different days for the isolates analysed. It is therefore unclear whether the conclusions of the manuscript are founded and no further work is possible to correct these issues as the instrument is no longer available to the authors. If you have any questions, please contact the corresponding author.

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.

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.

Evaluation of IR Biotyper for carbapenem-resistant Pseudomonas aeruginosa typing and its application potential for the investigation of nosocomial infection

Pseudomonas aeruginosa is one of the most common opportunistic pathogens causing severe nosocomial infections for its patterns of multidrug resistance, particularly for carbapenems. Timely epidemiological surveillance could greatly facilitate infection control of P. aeruginosa and many deadly pathogens alike. IR Biotyper (IRBT), is a novel real-time typing tool, based on a Fourier-transform infrared (FTIR) spectroscopy system. It is critical to comprehensively establish and evaluate the feasibility of IRBT in P. aeruginosa strain typing. In the current study, we first established standards and schemes for its routine laboratory application, and we found that Mueller-Hinton agar plates give better discriminatory power than blood agar plates. Data showed that the cut-off value of 0.15 with an additional 0.025 range was optimal. Secondly, 27 clinically isolated carbapenem-resistant P. aeruginosa (CRPA) strains collected from October 2010 to September 2011 were evaluated for typing effectiveness by comparing IRBT to the other commonly used typing methods, such as multi-locus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE) and whole-genome sequencing (WGS)-based typing. When using WGS-based typing as the reference method, the typing method of FTIR spectroscopy (AR = 0.757, SID = 0.749) could better cluster P. aeruginosa strains than MLST and in silico serotyping (AR = 0.544, SID = 0.470). Though PFGE showed the highest discriminatory power, low concordance was observed between PFGE and the other methods. Above all, this study demonstrates the utility of the IRBT as a quick, low-cost, real-time typing tool for the detection of CRPA strains.

In-process real-time probiotic phenotypic strain identity tracking: The use of Fourier transform infrared spectroscopy

Probiotic bacteria, capable of conferring benefits to the host, can present challenges in design, development, scale-up, manufacturing, commercialization, and life cycle management. Strain identification is one of the main quality parameters; nevertheless, this task can be challenging since established methodologies can lack resolution at the strain level for some microorganisms and\or are labor-intensive and time-consuming. Fourier transform infrared spectroscopy (FTIRS) has been largely used for the investigation of pathogenic species in the clinical field, whereas only recently has been proposed for the identification of probiotic strains. Within the probiotic industrial production, bacterial strains can be subjected to stressful conditions that may affect genomic and phenotypic characteristics; therefore, real-time monitoring of all the sequential growth steps is requested. Considering the fast, low-cost, and high-throughput features, FTIRS is an innovative and functional technology for typing probiotic strains from bench-top experiments to large-scale industrial production, allowing the monitoring of stability and identity of probiotic strains. In this study, the discriminatory power of FTIRS was assessed for four Lactiplantibacillus plantarum probiotic strains grown under different conditions, including temperatures (30 and 37°C) and medium (broth and agar), after consecutive sub-culturing steps. A comparison between the generated spectra with pulsed-field gel electrophoresis (PFGE) profiles was also performed. FTIRS was not only able to distinguish the strains of L. plantarum under different growth conditions but also to prove the phenotypic stability of L. plantarum type strain LP-CT after six growing steps. Regardless of the growth conditions, FTIRS spectra related to LP-CT constituted a unique hierarchical cluster, separated from the other L. plantarum strains. These results were confirmed by a PFGE analysis. In addition, based on FTIRS data, broth cultures demonstrated a higher reproducibility and discriminatory power with respect to agar ones. These results support the introduction of FTIRS in the probiotic industry, allowing for the step-by-step monitoring of massive microbial production while also guaranteeing the stability and purity of the probiotic strain. The proposed novel approach can constitute an impressive improvement in the probiotic manufacturing process.

Machine learning-based typing of Salmonella enterica O-serogroups by the Fourier-Transform Infrared (FTIR) Spectroscopy-based IR Biotyper system

BACKGROUND

Salmonella enterica is among the major burdens for public health at global level. Typing of salmonellae below the species level is fundamental for different purposes, but traditional methods are expensive, technically demanding, and time-consuming, and therefore limited to reference centers. Fourier transform infrared (FTIR) spectroscopy is an alternative method for bacterial typing, successfully applied for classification at different infra-species levels.

AIM

This study aimed to address the challenge of subtyping Salmonella enterica at O-serogroup level by using FTIR spectroscopy. We applied machine learning to develop a novel approach for S. enterica typing, using the FTIR-based IR Biotyper® system (IRBT; Bruker Daltonics GmbH & Co. KG, Germany). We investigated a multicentric collection of isolates, and we compared the novel approach with classical serotyping-based and molecular methods.

METHODS

A total of 958 well characterized Salmonella isolates (25 serogroups, 138 serovars), collected in 11 different centers (in Europe and Japan), from clinical, environmental and food samples were included in this study and analyzed by IRBT. Infrared absorption spectra were acquired from water-ethanol bacterial suspensions, from culture isolates grown on seven different agar media. In the first part of the study, the discriminatory potential of the IRBT system was evaluated by comparison with reference typing method/s. In the second part of the study, the artificial intelligence capabilities of the IRBT software were applied to develop a classifier for Salmonella isolates at serogroup level. Different machine learning algorithms were investigated (artificial neural networks and support vector machine). A subset of 88 pre-characterized isolates (corresponding to 25 serogroups and 53 serovars) were included in the training set. The remaining 870 samples were used as validation set. The classifiers were evaluated in terms of accuracy, error rate and failed classification rate.

RESULTS

The classifier that provided the highest accuracy in the cross-validation was selected to be tested with four external testing sets. Considering all the testing sites, accuracy ranged from 97.0% to 99.2% for non-selective media, and from 94.7% to 96.4% for selective media.

CONCLUSIONS

The IRBT system proved to be a very promising, user-friendly, and cost-effective tool for Salmonella typing at serogroup level. The application of machine learning algorithms proved to enable a novel approach for typing, which relies on automated analysis and result interpretation, and it is therefore free of potential human biases. The system demonstrated a high robustness and adaptability to routine workflows, without the need of highly trained personnel, and proving to be suitable to be applied with isolates grown on different agar media, both selective and unselective. Further tests with currently circulating clinical, food and environmental isolates would be necessary before implementing it as a potentially stand-alone standard method for routine use.

Surveillance diagnostic algorithm using real-time PCR assay and strain typing method development to assist with the control of C. auris amid COVID-19 pandemic

Candida auris continues to be a global threat for infection and transmission in hospitals and long-term care facilities. The emergence of SARS-CoV-2 has rerouted attention and resources away from this silent pandemic to the frontlines of the ongoing COVID-19 disease. Cases of C. auris continue to rise, and clinical laboratories need a contingency plan to prevent a possible outbreak amid the COVID-19 pandemic. Here, we introduce a two-tier Candida auris surveillance program that includes, first, a rapid qualitative rt-PCR for the identification of high-risk patients and, second, a method to analyze the isolated C. auris for strain typing using the Fourier-Transform Infrared spectroscopy. We have performed this two-tier surveillance for over 700 at-risk patients being admitted into our hospital and have identified 28 positive specimens (4%) over a 1-year period. Strain typing analysis by the IR spectrum acquisition typing method, supplemented by whole genome sequencing, has shown grouping of two significant clusters. The majority of our isolates belong to circulating African lineage associated with C. auris Clade III and an isolated strain grouping differently belonging to South Asian lineage C. auris Clade I. Low numbers of genomic variation point to local and ongoing transmission within the Los Angeles area not specifically within the hospital setting. Collectively, clinical laboratories having the ability to rapidly screen high-risk patients for C. auris and to participate in outbreak investigations by offering strain typing will greatly assist in the control of C. auris transmission within the hospital setting.

Performance Evaluation of the IR Biotyper® System for Clinical Microbiology: Application for Detection of Staphylococcus aureus Sequence Type 8 Strains

Background: Methicillin-resistant S. aureus (MRSA) clonal lineages have been classified based on sequence type (ST) and pulsotype associated with human infection. Providing rapid and accurate epidemiological insight is important to address proper infection control in both community-acquired and nosocomial hospital settings. In this regard, this study was performed to evaluate the IR Biotyper^® (IRBT^®) for strain typing of S. aureus clinical isolates on three media. Methods: A total of 24 S. aureus clinical isolates comprising 15 MRSA isolates (six ST5, three ST72, three ST8, and three ST188 isolates) and nine methicillin-susceptible S. aureus (MSSA) isolates (three ST5, three ST72, and three ST8 isolates) were included for evaluating the IRBT^®. Molecular characterization of all S. aureus isolates was performed by conventional PCR and sequencing methods. The IRBT^® was evaluated according to manufacturer instructions and a modified sample procedure on commonly used BAP, MHA, and TSA media. Subsequently, the spectra obtained by IRBT^® software were compared with dendrograms of PFGE analysis. Results: In this study, the modified sample procedure for reducing the amount of bacteria and bacterial concentration improved the acquisition quality pass rate of the IRBT^®. Each spectrum of S. aureus ST5, ST72, and ST188 isolates on all three media could not be clustered by IRBT^®. However, the dendrogram obtained from the spectra of S. aureus ST8 isolates on TSA medium were in concordance with that obtained by PFGE analysis. In addition, the visual distribution of S. aureus ST8 isolates on TSA medium in a 2D scatter plot appeared as separated point set from those of S. aureus ST5, ST72, and ST188 isolates. Conclusions: The IRBT^® system is a rapid strain typing tool using the FTIR spectroscopic method. This system demonstrated the possibility of discriminating the strain types of S. aureus clinical isolates. Indeed, S. aureus ST8 isolates on TSA medium were successfully differentiated from other strain type isolates.

Evaluation of Fourier Transform Infrared Spectroscopy as a First-Line Typing Tool for the Identification of Extended-Spectrum β-Lactamase-Producing Klebsiella pneumoniae Outbreaks in the Hospital Setting

Early detection of pathogen cross-transmission events and environmental reservoirs is needed to control derived nosocomial outbreaks. Whole-genome sequencing (WGS) is considered the gold standard for outbreak confirmation, but, in most cases, it is time-consuming and has elevated costs. Consequently, the timely incorporation of WGS results to conventional epidemiology (CE) investigations for rapid outbreak detection is scarce. Fourier transform infrared spectroscopy (FTIR) is a rapid technique that establishes similarity among bacteria based on the comparison of infrared light absorption patterns of bacterial polysaccharides and has been used as a typing tool in recent studies. The aim of the present study was to evaluate the performance of the FTIR as a first-line typing tool for the identification of extended-spectrum β-lactamase-producing Klebsiella pneumoniae (ESBL-Kp) outbreaks in the hospital setting in comparison with CE investigations using WGS as the gold standard method. Sixty-three isolates of ESBL-Kp collected from 2018 to 2021 and classified according to CE were typed by both FTIR and WGS. Concordance was measured using the Adjusted Rand index (AR) and the Adjusted Wallace coefficient (AW) for both CE and FTIR clustering considering WGS as the reference method. Both AR and AW were significantly higher for FTIR clustering than CE clustering (0.475 vs. 0.134, p = 0.01, and 0.521 vs. 0.134, p = 0.009, respectively). Accordingly, FTIR inferred more true clustering relationships than CE (38/42 vs. 24/42, p = 0.001). However, a similar proportion of genomic singletons was detected by both FTIR and CE (13/21 vs. 12/21, p = 1). This study demonstrates the utility of the FTIR method as a quick, low-cost, first-line tool for the detection of ESBL-Kp outbreaks, while WGS analyses are being performed for outbreak confirmation and isolate characterization. Thus, clinical microbiology laboratories would benefit from integrating the FTIR method into CE investigations for infection control measures in the hospital setting.

Analysis of four carbapenem-resistant Acinetobacter baumannii outbreaks using Fourier-transform infrared spectroscopy

We used Fourier-transform infrared (FTIR) spectroscopy to analyze 4 carbapenem-resistant Acinetobacter baumannii outbreaks. FTIR distinguished between isolates from different hospitals and uncovered the relatedness between isolates from acute-care hospitals and a post-acute-care hospital. Using higher cutoffs reveals more distant relationships and lower cutoffs support analyses of recent events.