An Overview of the Evolution of Infrared Spectroscopy Applied to Bacterial Typing

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.

Evaluating Fourier-transform infrared spectroscopy with IR Biotyper as a faster and simpler method for investigating the sources of an outbreak of legionellosis

Fourier-transform infrared (FTIR) spectroscopy using the IR Biotyper and core genome single nucleotide polymorphism (cgSNP) analysis were performed on 12 Legionella isolates associated with an outbreak at a spa house in Kanagawa Prefecture, Japan, and 3 non-outbreak isolates. The discriminative power of FTIR spectroscopy for 48-h incubation conditions of L. pneumophila in this outbreak was lower than cgSNP-based typing but higher than serogroup typing. FTIR spectroscopy could screen outbreak isolates from a group of genetically related isolates and may be useful as an initial typing method in Legionella outbreak investigations.

Characterization of an outbreak caused by Elizabethkingia miricola using Fourier-transform infrared (FTIR) spectroscopy

Fourier-transform infrared (FTIR) spectroscopy has the potential to be used for bacterial typing and outbreak characterization. We evaluated FTIR for the characterization of an outbreak caused by Elizabethkingia miricola. During the 2020-2021 period, 26 isolates (23 clinical and 3 environmental) were collected and analyzed by FTIR (IR Biotyper) and core-genome MLST (cgMLST), in addition to antimicrobial susceptibility testing. FTIR spectroscopy and cgMLST showed that 22 of the isolates were related to the outbreak, including the environmental samples, with only one discordance between both methods. Then, FTIR is useful for E. miricola typing and can be easily implemented in the laboratory.

Strain typing and antimicrobial susceptibility of Salmonella enterica Albany isolates from duck farms in South Korea

Salmonella enterica is distributed worldwide and is a common cause of bacterial food poisoning in humans and a serious public health problem. Although duck meat consumption has recently increased in Korea, studies on the epidemiological relationship between S. enterica contamination in duck farms are scarce. Salmonella enterica serovar Albany isolates recovered from duck farms were analyzed using two typing methods - IR Biotyper® (IRBT) and multilocus variable-number tandem repeat analysis (MLVA). The clustering results were compared with the epidemiological survey findings and the antimicrobial resistance profiles. From April 2019 to October 2020, 20 individual feces per farm from 5-6-week-old ducks were collected repeatedly from 105 duck farms. Salmonella spp. isolated from duck feces were identified using PCR and multilocus sequence typing to investigate the prevalence and distribution of the Salmonella serovars. The prevalence of S. enterica was 19%, and S. enterica Albany was the predominantly recovered isolate. The S. enterica Albany isolates underwent antimicrobial susceptibility testing to determine the minimum inhibitory concentration. MLVA and IRBT methods established relatedness and diversity among the S. enterica Albany isolates. Multidrug-resistant S. enterica Albany was distributed in all the farms. Antimicrobial resistance profiles reflected the duck farm characteristics and isolates recovered from the same farm showed an identical profile. Isolates repeatedly recovered from the same farm also showed identical IRBT clusters and MLVA groups. These findings suggest that the isolates remained on the duck farm and re-infected new duck flocks. Thus, proper cleaning and disinfection is required before the farms are repopulated.

Regulation of ARGs abundance by biofilm colonization on microplastics under selective pressure of antibiotics in river water environment

Interactions of microplastics (MPs) biofilm with antibiotic resistance genes (ARGs) and antibiotics in aquatic environments have made microplastic biofilm an issue of keen scholarly interest. The process of biofilm formation and the degree of ARGs enrichment in the presence of antibiotic-selective pressure and the impact on the microbial community need to be further investigated. In this paper, the selective pressure of ciprofloxacin (CIP) and illumination conditions were investigated to affect the physicochemical properties, biomass, and extracellular polymer secretion of polyvinyl chloride (PVC) microplastic biofilm. In addition, relative copy numbers of nine ARGs were analyzed by real-time quantitative polymerase chain reaction (qPCR). In the presence of CIP, microorganisms in the water and microplastic biofilm were more inclined to carry associated ARGs (2-3 times higher), which had a contributing effect on ARGs enrichment. The process of pre-microplastic biofilm formation might have an inhibitory effect on ARGs (total relative abundance up to 0.151) transfer and proliferation compared to the surrounding water (total relative abundance up to 0.488). However, in the presence of CIP stress, microplastic biofilm maintained the abundance of ARGs (from 0.151 to 0.149) better compared to the surrounding water (from 0.488 to 0.386). Therefore, microplastic biofilm act as abundance buffer island of ARGs stabilizing the concentration of ARGs. In addition, high-throughput analyses showed the presence of antibiotic-resistant (Pseudomonas) and pathogenic (Vibrio) microorganisms in biofilm under different conditions. The above research deepens our understanding of ARGs enrichment in biofilm and provides important insights into the ecological risks of interactions between ARGs, antibiotics, and microplastic biofilm.

Detection limit of FT-IR-based bacterial typing based on optimized sample preparation and typing model

Accurate and efficient bacterial typing methods are crucial to microbiology. Fourier transform infrared (FT-IR) spectroscopy enables highly distinguishable fingerprint identification of closely related bacterial strains by producing highly specific fingerprints of bacteria, which is increasingly being considered as an alternative to genotypic methods, such as pulsed field gel electrophoresis (PFGE) and whole genome sequencing (WGS), for bacterial typing. Compared with genotypic methods, FT-IR has significant advantages of convenient operation, fast speed, and low cost. Fundamental research into the detection limit based on optimized analytical conditions for FT-IR bacterial typing, which can avoid excessive bacterial culture time or sampling volume, is particularly important, especially in clinical practice. However, the corresponding parameters have not been fully investigated. In this study, we developed a simplified and reliable procedure for sample preparation, optimized the data analysis procedure, and evaluated the FT-IR detection limit based on the above conditions. In particular, we combined the film mold and calcium fluoride plate for sample preparation. We evaluated the detection limit (about 108 CFU/mL) after parameter optimization using hierarchical cluster analysis (HCA) and artificial neural network (ANN). The optimization and evaluation of these key fundamentals will better promote future application of FT-IR-based bacterial typing.

Recent Advances in the Determination of Milk Adulterants and Contaminants by Mid-Infrared Spectroscopy

The presence of chemical contaminants, toxins, or veterinary drugs in milk, as well as the adulteration of milk from different species, has driven the development of new tools to ensure safety and quality. Several analytical procedures have been proposed for the rapid screening of hazardous substances or the selective confirmation of the authenticity of milk. Mid-infrared spectroscopy and Fourier-transform infrared have been two of the most relevant technologies conventionally employed in the dairy industry. These fingerprint methodologies can be very powerful in determining the trait of raw material without knowing the identity of each constituent, and several aspects suggest their potential as a screening method to detect adulteration. This paper reviews the latest advances in applying mid-infrared spectroscopy for the detection and quantification of adulterants, milk dilution, the presence of pathogenic bacteria, veterinary drugs, and hazardous substances in milk.

Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Molecular Typing of Acinetobacter baumannii in Comparison with Orthogonal Methods

Colonization and subsequent health care-associated infection (HCAI) with Acinetobacter baumannii are a concern for vulnerable patient groups within the hospital setting. Outbreaks involving multidrug-resistant strains are associated with increased patient morbidity and mortality and poorer overall outcomes. Reliable molecular typing methods can help to trace transmission routes and manage outbreaks. In addition to methods deployed by reference laboratories, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) may assist by making initial in-house judgments on strain relatedness. However, limited studies on method reproducibility exist for this application. We applied MALDI-TOF MS typing to A. baumannii isolates associated with a nosocomial outbreak and evaluated different methods for data analysis. In addition, we compared MALDI-TOF MS with whole-genome sequencing (WGS) and Fourier transform infrared spectroscopy (FTIR) as orthogonal methods to further explore their resolution for bacterial strain typing. A related subgroup of isolates consistently clustered separately from the main outbreak group by all investigated methods. This finding, combined with epidemiological data from the outbreak, indicates that these methods identified a separate transmission event unrelated to the main outbreak. However, the MALDI-TOF MS upstream approach introduced measurement variability impacting method reproducibility and limiting its reliability as a standalone typing method. Availability of in-house typing methods with well-characterized sources of measurement uncertainty could assist with rapid and dependable confirmation (or denial) of suspected transmission events. This work highlights some of the steps to be improved before such tools can be fully integrated into routine diagnostic service workflows for strain typing. IMPORTANCE Managing the transmission of antimicrobial resistance necessitates reliable methods for tracking outbreaks. We compared the performance of MALDI-TOF MS with orthogonal approaches for strain typing, including WGS and FTIR, for Acinetobacter baumannii isolates correlated with a health care-associated infection (HCAI) event. Combined with epidemiological data, all methods investigated identified a group of isolates that were temporally and spatially linked to the outbreak, yet potentially attributed to a separate transmission event. This may have implications for guiding infection control strategies during an outbreak. However, the technical reproducibility of MALDI-TOF MS needs to be improved for it to be employed as a standalone typing method, as different stages of the experimental workflow introduced bias influencing interpretation of biomarker peak data. Availability of in-house methods for strain typing of bacteria could improve infection control practices following increased reports of outbreaks of antimicrobial-resistant organisms during the COVID-19 pandemic, related to sessional usage of personal protective equipment (PPE).

Improving the Detection of Epidemic Clones in Candida parapsilosis Outbreaks by Combining MALDI-TOF Mass Spectrometry and Deep Learning Approaches

Identifying fungal clones propagated during outbreaks in hospital settings is a problem that increasingly confronts biologists. Current tools based on DNA sequencing or microsatellite analysis require specific manipulations that are difficult to implement in the context of routine diagnosis. Using deep learning to classify the mass spectra obtained during the routine identification of fungi by MALDI-TOF mass spectrometry could be of interest to differentiate isolates belonging to epidemic clones from others. As part of the management of a nosocomial outbreak due to Candida parapsilosis in two Parisian hospitals, we studied the impact of the preparation of the spectra on the performance of a deep neural network. Our purpose was to differentiate 39 otherwise fluconazole-resistant isolates belonging to a clonal subset from 56 other isolates, most of which were fluconazole-susceptible, collected during the same period and not belonging to the clonal subset. Our study carried out on spectra obtained on four different machines from isolates cultured for 24 or 48 h on three different culture media showed that each of these parameters had a significant impact on the performance of the classifier. In particular, using different culture times between learning and testing steps could lead to a collapse in the accuracy of the predictions. On the other hand, including spectra obtained after 24 and 48 h of growth during the learning step restored the good results. Finally, we showed that the deleterious effect of the device variability used for learning and testing could be largely improved by including a spectra alignment step during preprocessing before submitting them to the neural network. Taken together, these experiments show the great potential of deep learning models to identify spectra of specific clones, providing that crucial parameters are controlled during both culture and preparation steps before submitting spectra to a classifier.

Protocol for bacterial typing using Fourier transform infrared spectroscopy

The Fourier transform infrared (FT-IR) signals obtained from bacterial samples are specific and reproducible, making FT-IR an efficient tool for bacterial typing at a subspecies level. However, the typing accuracy could be affected by many factors, including sample preparation and spectral acquisition. Here, we present a unified protocol for bacterial typing based on FT-IR spectroscopy. We describe sample preparation from bacterial culture and FT-IR spectrum collection. We then detail FT-IR spectrum preprocessing and multivariate analysis of spectral data for bacterial typing.

Successful autologous hematopoietic stem cell transplants using Salmonella positive products collected from asymptomatic donors

BACKGROUND

Bacterial contamination of hematopoietic stem cell (HSC) products is most commonly due to normal skin flora. Salmonella in HSC products is rare, and to our knowledge safe administration of an autologous HSC product containing Salmonella has not been reported.

STUDY DESIGN AND METHODS

We describe two patients undergoing autologous HSC transplant: peripheral blood HSC collection was performed by leukapheresis, and samples were cultured according to standard institutional protocol. Subsequent microorganism identification was performed using MALDI-TOF (Bruker Biotyper). Strain-relatedness was investigated by infrared spectroscopy using the IR Biotyper (Bruker).

RESULTS

The patients were asymptomatic throughout the collection process; however, HSC products collected on two consecutive days from each patient were positive for Salmonella. Isolates from both cultures were further characterized as Salmonella enterica serovar Dublin by the local public health department. Antibiotic susceptibility testing revealed different sensitivity patterns for the two strains. IR Biotyper demonstrated significant discriminatory power among the clinically significant Salmonella enterica subspecies, serogroups B, C1, and D. The patient strains were similar as both belonged to Group D Salmonella enterica serovar Dublin but were not identical. The Salmonella positive autologous HSC products were infused to both patients following administration of empiric antibiotic therapy. Both patients successfully engrafted and did well.

CONCLUSION

Salmonella is rarely seen in cellular therapy products and positivity may be the result of asymptomatic bacteremia at the time of collection. We present two instances of autologous HSC products containing Salmonella that were infused, along with prophylactic antimicrobial therapy without significant adverse clinical effects.

Raman Scattering-Based Optical Sensing Of Chronic Liver Diseases

Chronic liver diseases (CLDs) are a major public health problem. Despite the progress achieved in fighting against viral hepatitis, the emergence of non-alcoholic fatty liver disease might pose a serious challenge to the public's health in the coming decades. Medical management of CLDs represents a substantial burden on the public health infrastructures. The health care cost of these diseases is an additional burden that weighs heavily on the economies of developing countries. Effective management of CLDs requires the adoption of reliable and cost-effective screening and diagnosing methods to ensure early detection and accurate clinical assessment of these diseases. Vibrational spectroscopies have emerged as universal analytical methods with promising applications in various industrial and biomedical fields. These revolutionary analytical techniques rely on analyzing the interaction between a light beam and the test sample to generate a spectral fingerprint. This latter is defined by the analyte's chemical structure and the molecular vibrations of its functional groups. Raman spectroscopy and surface-enhanced Raman spectroscopy have been used in combination with various chemometric tests to diagnose a wide range of malignant, metabolic and infectious diseases. The aim of the current review is to cast light on the use of these optical sensing methods in the diagnosis of CLDs. The vast majority of research works that investigated the potential application of these spectroscopic techniques in screening and detecting CLDs were discussed here. The advantages and limitations of these modern analytical methods, as compared with the routine and gold standard diagnostic approaches, were also reviewed in details.

Fourier transform infrared spectroscopy; can it be used as a rapid typing method of Neisseria gonorrhoeae?

BACKGROUND

Typing of Neisseria gonorrhoeae is necessary for epidemiologic surveillance, while time consuming and resource intensive. Fourier transform infrared (FTIR) spectroscopy has shown promising results when typing several bacterial species. This study investigates whether FTIR spectroscopy can be used as a rapid method for typing clinical N. gonorrhoeae isolates, comparing FTIR spectroscopy to multi locus sequence typing (MLST), N. gonorrhoeae multi antigen sequence typing (NG-MAST) and whole genome sequencing (WGS).

METHODS

Sixty consecutive isolates from a venereology clinic and three isolates from an outbreak were included. Isolates were analysed with FTIR spectroscopy on the IR Biotyper system (Bruker Daltonik) with the IR Biotyper software (version 2.1) with default analysis settings (spectral range 1300-800 cm^-1). Four technical replicates of each isolate were analysed in three different runs. The output was a hierarchical cluster analysis (HCA) presented as a dendrogram; a tree-like overview of how closely different isolates are related. FTIR spectroscopy was compared to MLST, NG-MAST and WGS to see if the FTIR spectroscopy-dendrogram grouped the isolates in the same clusters.

RESULTS

Fifty-one out of 60 isolates, and the three outbreak isolates, produced at least one spectrum in each run and were included. No agreement between FTIR spectroscopy and MLST or NG-MAST or WGS was shown. The FTIR spectroscopy-dendrogram failed to cluster the outbreak isolates.

CONCLUSION

FTIR spectroscopy (spectral range 1300-800 cm^-1) is not yet suitable for epidemiologic typing of N. gonorrhoeae. Absence of a capsule as well as phase- and antigenic variation of carbohydrate surface structures of the gonococcal cell wall may contribute to our findings. Future studies should include analysis of a wider range of the spectrum recorded (4000-500 cm^-1), and should also explore further mathematical analytic approaches of the similarity between spectra.

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.

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

Early detection of bacterial transmission and outbreaks in hospitals is important because nosocomial infections can result in health complications and longer hospitalization. Current practice to detect outbreaks uses genotyping methods amplified fragment length polymorphism (AFLP) and whole genome sequencing (WGS), which are not suitable methods for real-time transmission screening of both susceptible and resistant bacteria. The aim was to assess the typing technique Fourier transform infrared (FTIR) spectroscopy as real-time screening method to discriminate large amounts of susceptible and resistant bacteria at strain level when there is no evident outbreak in comparison with the WGS reference. Isolates of past hospital outbreak strains of Acinetobacter baumannii/calcoaceticus complex (n = 25), Escherichia coli (n = 31), Enterococcus faecium (n = 22), Staphylococcus aureus (n = 37) and Pseudomonas aeruginosa (n = 30) were used for validation of FTIR. Subsequently, Enterococcus faecalis (n = 106) and Enterococcus faecium (n = 104) isolates from weekly routine screening samples when no potential outbreak was present were analysed. FTIR showed reproducibility and congruence of cluster composition with WGS for A. baumannii/calcoaceticus complex and E. faecium outbreak isolates. The FTIR results of E. faecalis and E. faecium isolates from routine samples showed reproducibility, but the congruence of cluster composition with WGS was low. For A. baumannii/calcoaceticus complex and E. faecium outbreak isolates, FTIR appears to be a discriminatory typing tool. However, our study shows the discriminatory power is too low to screen real-time for transmission of E. faecium and E. faecalis at patient wards based on isolates acquired in routine surveillance cultures when there is no clear suspicion of an ongoing outbreak.

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.

Evaluation of IR Biotyper for Lactiplantibacillus plantarum Typing and Its Application Potential in Probiotic Preliminary Screening

IR Biotyper (IRBT), which is a spectroscopic system for microorganism typing based on Fourier transform infrared (FTIR) technology, has been used to detect the spread of clones in clinical microbiology laboratories. However, the use of IRBT to detect probiotics has rarely been reported. Herein, we evaluated the discriminatory power of IRBT to type Lactiplantibacillus plantarum isolates at the strain level and explored its application potential in probiotic preliminary selection. Twenty Lactiplantibacillus isolates collected from pickled radishes during successive fermentation were used to test the robustness of IRBT at the strain level. IRBT was then compared with genotyping methods such as whole-genome sequencing (WGS), pulsed-field gel electrophoresis (PFGE), and multilocus sequence typing (MLST) to evaluate its discrimination power. IRBT distributed the 20 isolates into five clusters, with L. argentoratensis isolate C7-83 being the most distant from the other isolates, which belonged to L. plantarum. IRBT showed good reproducibility, although deviation in the discriminative power of IRBT was found at the strain level across laboratories, probably due to technical variance. All examined methods allowed bacterial identification at the strain level, but IRBT had higher discriminatory power than MLST and was comparable to the WGS and PFGE. In the phenotypic comparison study, we observed that the clustering results of probiotic physiological attributes (e.g., sensitivity to acid and bile salts, hydrophobicity of the cell surface, and resistance to antibiotics) were consistent with the typing results of IRBT. Our results indicated that IRBT is a robust tool for L. plantarum strain typing that could improve the efficiency of probiotic identification and preliminary screening, and can potentially be applied in probiotic traceability and quality control.

Progress in infrared spectroscopy as an efficient tool for predicting protein secondary structure

Infrared (IR) spectroscopy is a highly sensitive technique that provides complete information on chemical compositions. The IR spectra of proteins or peptides give rise to nine characteristic IR absorption bands. The amide I bands are the most prominent and sensitive vibrational bands and widely used to predict protein secondary structures. The interference of H₂O absorbance is the greatest challenge for IR protein secondary structure prediction. Much effort has been made to reduce/eliminate the interference of H₂O, simplify operation steps, and increase prediction accuracy. Progress in sampling and equipment has rendered the Fourier transform infrared (FTIR) technique suitable for determining the protein secondary structure in broader concentration ranges, greatly simplifying the operating steps. This review highlights the recent progress in sample preparation, data analysis, and equipment development of FTIR in A/T mode, with a focus on recent applications of FTIR spectroscopy in the prediction of protein secondary structure. This review also provides a brief introduction of the progress in ATR-FTIR for predicting protein secondary structure and discusses some combined IR methods, such as AFM-based IR spectroscopy, that are used to analyze protein structural dynamics and protein aggregation.

Bifidobacteria Strain Typing by Fourier Transform Infrared Spectroscopy

Fourier transform infrared (FTIR) spectroscopy, a technology traditionally used in chemistry to determine the molecular composition of a wide range of sample types, has gained growing interest in microbial typing. It is based on the different vibrational modes of the covalent bonds between atoms of a given sample, as bacterial cells, induced by the absorption of infrared radiation. This technique has been largely used for the study of pathogenic species, especially in the clinical field, and has been proposed also for the typing at different subspecies levels. The high throughput, speed, low cost, and simplicity make FTIR spectroscopy an attractive technique also for industrial applications, in particular, for probiotics. The aim of this study was to compare FTIR spectroscopy with established genotyping methods, pulsed-field gel electrophoresis (PFGE), whole-genome sequencing (WGS), and multilocus sequence typing (MLST), in order to highlight the FTIR spectroscopy potential discriminatory power at strain level. Our study focused on bifidobacteria, an important group of intestinal commensals generally recognized as probiotics. For their properties in promoting and maintaining health, bifidobacteria are largely marketed by the pharmaceutical, food, and dairy industries. Strains belonging to Bifidobacterium longum subsp. longum and Bifidobacterium animalis subsp. lactis were taken into consideration together with some additional type strains. For B. longum subsp. longum, it was possible to discriminate the strains with all the methods used. Although two isolates were shown to be strictly phylogenetically related, constituting a unique cluster, based on PFGE, WGS, and MLST, no clustering was observed with FTIR. For B. animalis subsp. lactis group, PFGE, WGS, and MLST were non-discriminatory, and only one strain was easily distinguished. On the other hand, FTIR discriminated all the isolates one by one, and no clustering was observed. According to these results, FTIR analysis is not only equivalent to PFGE, WGS, and MLST, but also for some strains, in particular, for B. animalis subsp. lactis group, more informative, being able to differentiate strains not discernible with the other two methods based on phenotypic variations likely deriving from certain genetic changes. Fourier transform infrared spectroscopy has highlighted the possibility of using the cell surface as a kind of barcode making tracing strains possible, representing an important aspect in probiotic applications. Furthermore, this work constitutes the first investigation on bifidobacterial strain typing using FTIR spectroscopy.

Advances in differentiation and identification of foodborne bacteria using near infrared spectroscopy

Rapid and sensitive detection of foodborne bacteria is a growing concern for ensuring safe food supply and preventing human foodborne infections. It is difficult for conventional methods to meet these detection requirements because they are often tedious and time-consuming. In the recent years, near infrared (NIR) spectroscopy has been found to be a promising method for all sorts of analyses in microbiology due to its highly specific absorption signature and non-destructive measurements. In this review, we first briefly introduce the fundamental and basic operational procedure of NIR spectroscopy for foodborne bacteria detection. Then we summarize the main advances and contributions of this technique in the study of foodborne bacteria. Finally, we conclude that much work still remains to be done before NIR spectroscopy really becomes a viable alternative in the field of microbiological characterization.

Tapioca Starch Modulates Cellular Events in Oral Probiotic Streptococcus salivarius Strains

Considering the implications of microbiota in health, scientists are in search of microbiota-oriented strategies for the effective prevention and/or treatment of a wide variety of serious diseases. A microbiota comprises diverse microorganisms with either probiotic or pathogenic properties. The fermentation of prebiotic carbohydrates by probiotic bacteria can affect host metabolism. Therefore, understanding the prebiotic-mediated metabolic modulations in probiotics is crucial to develop functional foods for the improvement of disturbed microbiota. Studies have emphasized the importance of prebiotics in probiotic therapies for mucosal diseases and highlighted the need for extensive research on oral bacteria. In the present study, the cellular events have been studied in batch cultures of probiotic Streptococcus salivarius exposed to the natural prebiotic, tapioca starch (TS). TS modulated the keystone metabolic events in Streptococcus salivarius in a dose-dependent manner. Besides increasing the live cell counts and altering the colony morphologies, TS affected the protein metabolism in terms of cellular expression and conformational changes in protein secondary structures. After treatment with TS, the nucleic acid synthesis increased and B-DNA was more than A- and Z-DNA, together with the diminished fatty acids and increased polysaccharide synthesis. The study results can be considered for the assessment of functional foods and probiotics in oral health.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Monitoring E. coli Cell Integrity by ATR-FTIR Spectroscopy and Chemometrics: Opportunities and Caveats

During recombinant protein production with E. coli, the integrity of the inner and outer membrane changes, which leads to product leakage (loss of outer membrane integrity) or lysis (loss of inner membrane integrity). Motivated by current Quality by Design guidelines, there is a need for monitoring tools to determine leakiness and lysis in real-time. In this work, we assessed a novel approach to monitoring E. coli cell integrity by attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. Various preprocessing strategies were tested in combination with regression (partial least squares, random forest) or classification models (partial least squares discriminant analysis, linear discriminant analysis, random forest, artificial neural network). Models were validated using standard procedures, and well-performing methods were additionally scrutinized by removing putatively important features and assessing the decrease in performance. Whereas the prediction of target compound concentration via regression was unsuccessful, possibly due to a lack of samples and low sensitivity, random forest classifiers achieved prediction accuracies of over 90% within the datasets tested in this study. However, strong correlations with untargeted spectral regions were revealed by feature selection, thereby demonstrating the need to rigorously validate chemometric models for bioprocesses, including the evaluation of feature importance.

Novel application of isolated Micrococcus luteus and Bacillus pumilus for Li+ ion biosorption: a comparative study

In this study, Li⁺ biosorption profiles of Micrococcus luteus and Bacillus pumilus bacterial strains were investigated. Comparative surface characterization of the biomasses revealed that B. pumilus had a significantly greater surface negativity than the other, which had a direct positive effect on the ability to attract the Li⁺ ions. Biosorption experiments showed that B. pumilus cell had more efficient performance at all pH and initial Li⁺ concentration values in the ranges of 3.0-10.0 and 2.5-20.0 mg/L, respectively. The maximum adsorption capacities obtained at initial Li⁺ concentration of 20.0 mg/L and pH 9.0 were 1.160 mg Li⁺/g (167.1 µmol/g) and 2.280 mg Li⁺/g (328.5 µmol/g) for M. luteus and B. pumilus, respectively. For all the cases studied, the biosorption equilibrium was reached very quickly, suggesting that physical interaction dominated this process. Experimental data were found to be compatible with both Langmuir and Freundlich models under the studied experimental conditions. This study highlights the idea that B. pumilus bacterial strain will be a new and preferred biosorbent for Li⁺ ions by providing a low cost, rapid and quite efficient process.

Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning

The low rate of discovery and rapid spread of resistant pathogens have made antibiotic discovery a worldwide priority. In cell-based screening, the mechanism of action (MOA) is identified after antimicrobial activity. This increases rediscovery, impairs low potency candidate detection, and does not guide lead optimization. In this study, high-throughput Fourier-transform infrared (FTIR) spectroscopy was used to discriminate the MOA of 14 antibiotics at pathway, class, and individual antibiotic level. For that, the optimal combinations and parametrizations of spectral preprocessing were selected with cross-validated partial least squares discriminant analysis, to which various machine learning algorithms were applied. This coherently resulted in very good accuracies, independently of the algorithms, and at all levels of MOA. Particularly, an ensemble of subspace discriminants predicted the known pathway (98.6%), antibiotic classes (100%), and individual antibiotics (97.8%) with exceptional accuracy, and similar results were obtained for simulated novel MOA. Even at very low concentrations (1 μg/mL) and growth inhibition (15%), over 70% pathway and class accuracy was achieved, suggesting FTIR spectroscopy can probe the grey chemical matter. Prediction of inhibitory effect was also examined, for which a squared exponential Gaussian process regression yielded a root mean square error of 0.33 and a R² of 0.92, indicating that metabolic alterations leading to growth inhibition are intrinsically reflected on FTIR spectra beyond cell density. KEY POINTS: • Antibiotic MOA and potency estimated with high-throughput FTIR spectroscopy • Sub-inhibitory MOA identification suggests ability to explore grey chemical matter • Data analysis optimization improved MOA identification at antibiotic level by 38.

Discrimination of bacteria using whole organism fingerprinting: the utility of modern physicochemical techniques for bacterial typing

This review compares and contrasts MALDI-MS, FT-IR spectroscopy and Raman spectroscopy for whole organism fingerprinting and bacterial typing.

Sensitivity and Calibration of the FT-IR Spectroscopy on Concentration of Heavy Metal Ions in River and Borehole Water Sources

Heavy metals in water sources can threaten human life and the environment. The analysis time, need for chemical reagents, and sample amount per analysis assist in monitoring contaminants. Application of the Fourier Transform Infrared (FT-IR) Spectroscopy for the investigation of heavy metal elements has significantly developed due to its cost effectiveness and accuracy. Use of chemometric models such as Partial Least Square (PLS) and Principle Component Regression Analysis (PCA) relate the multiple spectral intensities from numerous calibration samples to the recognized analytes. This study focused on the FT-IR calibration and quantification of heavy metals (Ag, Cd, Cu, Pb and Zn) in surveyed water sources. FT-IR measurements were compared with the atomic absorption spectrometer (AAS) measurements. Quantitative analysis methods, PCA and PLS, were used in the FT-IR calibration. The spectral analyses were done using the Attenuated Total Reflectance (ATR-FTIR) technique on three river and four borehole water sources sampled within two seasons in QwaQwa, South Africa (SA). The PLS models had good R2 values ranging from 0.95 to 1 and the PCA models ranged from 0.98 to 0.99. Significant differences were seen at 0.001 and 0.05 levels between the PLS and PCA models for detecting Cd and Pb in the water samples. The PCA models detected Ag concentrations more (˂0 mg L−1 on selected sites). Both the PLS and PCA models had lower detection only for Zn ions mostly above 45 mg L−1 deviating from the AAS measurements (<0.020 mg L−1). The FT-IR spectroscopy demonstrated good potential for heavy metal determination purposes.

Discrimination of heavy metal acclimated environmental strains by chemometric analysis of FTIR spectra

Heavy metal acclimated bacteria are profoundly the preferred choice for bioremediation studies. Bacteria get acclimated to toxic concentrations of heavy metals by induction of specific enzymes and genetic selection favoring new metabolic abilities leading to activation of one or several of resistance mechanisms creating bacterial populations with differences in resistance profile and/or level. Therefore, to use in bioremediation processes, it is important to discriminate acclimated bacterial populations and choose a more resistant strain. In this study, we discriminated heavy metal acclimated bacteria by using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy and multivariate analysis methods namely Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). Two acclimation methods, acute and gradual, were used which cause differences in molecular changes resulting in bacterial populations with different molecular and resistance profiles. Brevundimonas sp., Gordonia sp., and Microbacterium oxydans were exposed to the toxic concentrations of Cd (30 μg/ml) or Pb (90 μg/ml) by using broth medium as a growth media. Our results revealed that PCA and HCA clearly discriminated the acute-acclimated, gradual-acclimated, and control bacteria from each other in protein, carbohydrate, and whole spectral regions. Furthermore, we classified acclimated (acute and gradual) and control bacteria more accurately by using SIMCA with 99.9% confidence. This study demonstrated that heavy metal acclimated and control group bacteria can be discriminated by using chemometric analysis of FTIR spectra in a powerful, cost-effective, and handy way. In addition to the determination of the most appropriate acclimation procedure, this approach can be used in the detection of the most resistant bacterial strains to be used in bioremediation studies.

Near-Infrared Spectroscopy Evaluations for the Differentiation of Carbapenem-Resistant from Susceptible Enterobacteriaceae Strains

Antimicrobial Resistance (AMR) caused by Carbapenem-Resistant Enterobacteriaceae (CRE) is a global threat. Accurate identification of these bacterial species with associated AMR is critical for their management. While highly accurate methods to detect CRE are available, they are costly, timely and require expert skills, making their application infeasible in low-resource settings. Here, we investigated the potential of Near-Infrared Spectroscopy (NIRS) for a range of applications: (i) the detection and differentiation of isolates of two pathogenic Enterobacteriaceae species, Klebsiella pneumoniae and Escherichia coli, and (ii) the differentiation of carbapenem resistant and susceptible K. pneumoniae. NIRS has successfully differentiated between K. pneumoniae and E. coli isolates with a predictive accuracy of 89.04% (95% CI; 88.7–89.4%). K. pneumoniae isolates harbouring carbapenem-resistance determinants were differentiated from susceptible K. pneumoniae strains with an accuracy of 85% (95% CI; 84.2–86.1%). To our knowledge, this is the largest proof of concept demonstration for the utility and feasibility of NIRS to rapidly differentiate between K. pneumoniae and E. coli as well as carbapenem-resistant K. pneumoniae from susceptible strains.

Vibrational Spectroscopy as a Sensitive Probe for the Chemistry of Intra-Phase Bacterial Growth

Bacterial growth in batch cultures occurs in four phases (lag, exponential/log, stationary and death phase) that differ distinctly in number of different bacteria, biochemistry and physiology. Knowledge regarding the growth phase and its kinetics is essential for bacterial research, especially in taxonomic identification and monitoring drug interactions. However, the conventional methods by which to assess microbial growth are based only on cell counting or optical density, without any insight into the biochemistry of cells or processes. Both Raman and Fourier transform infrared (FTIR) spectroscopy have shown potential to determine the chemical changes occurring between different bacterial growth phases. Here, we extend the application of spectroscopy and for the first time combine both Raman and FTIR microscopy in a multimodal approach to detect changes in the chemical compositions of bacteria within the same phase (intra-phase). We found a number of spectral markers associated with nucleic acids (IR: 964, 1082, 1215 cm⁻¹; RS: 785, 1483 cm⁻¹), carbohydrates (IR: 1035 cm⁻¹; RS: 1047 cm⁻¹) and proteins (1394 cm⁻¹, amide II) reflecting not only inter-, but also intra-phase changes in bacterial chemistry. Principal component analysis performed simultaneously on FTIR and Raman spectra enabled a clear-cut, time-dependent discrimination between intra-lag phase bacteria probed every 30 min. This demonstrates the unique capability of multimodal vibrational spectroscopy to probe the chemistry of bacterial growth even at the intra-phase level, which is particularly important for the lag phase, where low bacterial numbers limit conventional analytical approaches.

The Travelling Particles: Investigating microplastics as possible transport vectors for multidrug resistant E. coli in the Weser estuary (Germany)

The prevalence of multidrug-resistant Gram-negative bacteria in aquatic environments has been a long withstanding health concern, namely extended-spectrum beta-lactamase (ESBL) producing Escherichia coli. Given increasing reports on microplastic (MP) pollution in these environments, it has become crucial to better understand the role of MP particles as transport vectors for such multidrug-resistant bacteria. In this study, an incubation experiment was designed where particles of both synthetic and natural material (HDPE, tyre wear, and wood) were sequentially incubated at multiple sites along a salinity gradient from the Lower Weser estuary (Germany) to the offshore island Helgoland (German Bight, North Sea). Following each incubation period, particle biofilms and water samples were assessed for ESBL-producing E. coli, first by the enrichment and detection of E. coli using Fluorocult® LMX Broth followed by cultivation on CHROMAgar™ ESBL media to select for ESBL-producers. Results showed that general E. coli populations were present on the surfaces of wood particles across all sites but none were found to produce ESBLs. Additionally, neither HDPE nor tyre wear particles were found to harbour any E. coli. Conversely, ESBL-producing E. coli were present in surrounding waters from all sites, 64% of which conferred resistances against up to 3 other antibiotic groups, additional to the beta-lactam resistances intrinsic to ESBL-producers. This study provides a first look into the potential of MP to harbour and transport multidrug-resistant E. coli across different environments and the approach serves as an important precursor to further studies on other potentially harmful MP-colonizing species.

Rapid Approach for Detection of Antibiotic Resistance in Bacteria Using Vibrational Spectroscopy

Here, we applied vibrational spectroscopy to investigate the drug response following incubation of S. aureus with oxacillin. The main focus of this work was to identify the chemical changes caused by oxacillin over time and to determine the feasibility of the spectroscopic approach to detect antimicrobial resistance. The oxacillin-induced changes in the chemical composition of susceptible bacteria, preceding (and leading to) the inhibition of growth, included an increase in the relative content of nucleic acids, alteration in the α-helical/β-sheet protein ratio, structural changes in carbohydrates (observed via changes in the band at 1035 cm^-1), and significant thickening of the cell wall. These observations enabled a dose-dependent discrimination between susceptible bacteria incubated with and without oxacillin after 120 min. In methicillin resistant strains, no spectral differences were observed between cells, regardless of drug exposure. These results pave the way for a new, rapid spectroscopic approach to detect drug resistance in pathogens, based on their early positive/negative drug response.

Near-infrared spectroscopy coupled with chemometrics algorithms for the quantitative determination of the germinability of Clostridium perfringens in four different matrices

Clostridium perfringens (C. perfringens) has the ability to form metabolically-dormant spores that can survive food preservation processes and cause food spoilage and foodborne safety risks upon germination outgrowth. This study was conducted to investigate the effects of different AGFK concentrations (0, 50, 100, 200 mM/mL) on the spore germination of C. perfringens in four matrices, including Tris-HCl, FTG, milk, and chicken soup. C. perfringens spore germinability was investigated using near infrared spectroscopy (NIRS) combined with chemometrics. The spore germination rate (S), the OD₆₀₀%, and the Ca²⁺-DPA% were measured using traditional spore germination methods. The results of spore germination assays showed that the optimum germination rate was obtained using 100 mM/L concentrations of AGFK in the FTG medium, and the S, OD₆₀₀% and Ca²⁺-DPA% were 98.6%, 59.3% and 95%, respectively. The best prediction models for the S, OD₆₀₀% and Ca²⁺-DPA% were obtained using SNV as the preprocessing method for the original spectra, with the competitive adaptive weighted resampling method (CARS) as the characteristic variables related to the selected spore germination methods from NIRS data. The results of the S showed that the optimum model was built by CARS-PLSR (RMSEV = 0.745, R_c = 0.897, RMSEP = 0.769, R_p = 0.883). For the OD₆₀₀%, interval partial least squares regression (CARS-siPLS) was performed to optimize the models. The calibration yielded acceptable results (RMSEV = 0.218, R_c = 0.879, RMSEP = 0.257, R_p = 0.845). For the Ca²⁺-DPA%, the optimum model with CARS-siPLS yielded acceptable results (RMSEV = 44.7, R_c = 0.883, RMSEP = 50.2, R_p = 0.872). This indicated that quantitative determinations of the germinability of C. perfringens spores using NIR technology is feasible. A new method based on NIR was provided for rapid, automatic, and non-destructive determination of the germinability of C. perfringens spores.

Fourier Transform Infrared Spectroscopy Is a New Option for Outbreak Investigation: a Retrospective Analysis of an Extended-Spectrum-Beta-Lactamase-Producing Klebsiella pneumoniae Outbreak in a Neonatal Intensive Care Unit

The IR Biotyper is a new automated typing system based on Fourier-transform infrared (FT-IR) spectroscopy that gives results within 4 h. We aimed (i) to use the IR Biotyper to retrospectively analyze an outbreak of extended-spectrum beta-lactamase-producing Klebsiella pneumoniae (ESBL-KP) in a neonatal intensive care unit and to compare results to BOX-PCR and whole-genome sequencing (WGS) results as the gold standard and (ii) to assess how the cutoff values used to define clusters affect the discriminatory power of the IR Biotyper. The sample consisted of 18 isolates from 14 patients. Specimens were analyzed in the IR Biotyper using the default analysis settings, and spectra were analyzed using OPUS 7.5 software. The software contains a feature that automatically proposes a cutoff value to define clusters; the cutoff value defines up to which distance the spectra are considered to be in the same cluster. Based on FT-IR, the outbreak represented 1 dominant clone, 1 secondary clone, and several unrelated clones. FT-IR results, using the cutoff value generated by the accompanying software after 4 replicates, were concordant with WGS for all but 1 isolate. BOX-PCR was underdiscriminatory compared to the other two methods. Using the cutoff value generated after 12 replicates, the results of FT-IR and WGS were completely concordant. The IR Biotyper can achieve the same typeability and discriminatory power as genome-based methods. However, to attain this high performance requires either previous, strain-dependent knowledge about the optimal technical parameters to be used or validation by a second method.

Discrimination of Staphylococcus aureus Strains from Coagulase-Negative Staphylococci and Other Pathogens by Fourier Transform Infrared Spectroscopy

Staphylococcus aureus is an extremely infectious and malignant pathogen among many bacteria species. The aim of this work is to provide a robust classification model that would be able to identify S. aureus independent of the culture growth stage and the variations in bacteria concentration in suspension and also one that would be able to identify the pathogen among both taxonomically close species of the same genus and taxonomically distant species of different genera, using Fourier transform infrared spectroscopy (FTIR). In total, the spectra of 141 isolates of 17 bacteria have been used. Based on a combination of principal component analysis (PCA) and linear discriminant analysis (LDA), an identification model providing 100% sensitivity and 98% specificity was built. Inherent reliability and flexibility of the model have been shown. The proposed method of analysis allows us to get closer to the diagnostic requirements in the field of clinical microbiology, and it can be utilized for typing of other pathogenic bacteria species.

Influence of the Sample Preparation Method in Discriminating Candida spp. Using ATR-FTIR Spectroscopy

Several studies have investigated the capacity of ATR-FTIR spectroscopy for fungal species discrimination. However, preparation methods vary among studies. This study aims to ascertain the effect of sample preparation on the discriminatory capacity of ATR-FTIR spectroscopy. Candida species were streaked to obtain colonies and spectra were collected from each preparation type, which included: (a) untreated colonies being directly transferred to the ATR crystal, (b) following washing and (c) following 24-h fixation in formalin. Spectra were pre-processed and principal component analysis (PCA) and K-means cluster analysis (KMC) were performed. Results showed that there was a clear discrimination between preparation types. Groups of spectra from untreated and washed isolates clustered separately due to intense protein, DNA and polysaccharide bands, whilst fixed spectra clustered separately due to intense polysaccharide bands. This signified that sample preparation had influenced the chemical composition of samples. Nevertheless, across preparation types, significant species discrimination was observed, and the polysaccharide (1200-900 cm^-1) region was a common critical marker for species discrimination. However, different discriminatory marker bands were observed across preparation methods. Thus, sample preparation appears to influence the chemical composition of Candida samples; however, does not seem to significantly impact the species discrimination potential for ATR-FTIR spectroscopy.

Bioluminescent Imaging and Tracking of Bacterial Transport in Soils

Bioimaging instrumentation can be used to observe environmental phenomena such as the transport, retention, and distribution of bacteria in soils in situ in a real-time, nondestructive manner. Bacteria designed to emit bioluminescence light signals are injected into a transparent column packed with soils, and then the column is placed into a bioimaging instrument, such as a PerkinElmer IVIS Spectrum, while it is connected through thin teflon tubes to other parts of the column system located outside of the imaging chamber, including a fraction collector for collecting effluent solution and a pump for introducing bacterial suspension or experimental solution. After self-correction of soil autofluorescence and bioluminescence and setup of required imaging parameters, the transport experiment is initiated by introducing the bacterial suspension to the soil column while the spatiotemporal distribution of bioluminescent bacteria in the entire soil column is imaged. Finally, the images are processed to analyze bacterial migration in the soil under various environmental conditions in comparison with the breakthrough and elution curves of the bacteria obtained by analyzing the effluent samples.

Detection of Antimicrobial Resistance-Related Changes in Biochemical Composition of Staphylococcus aureus by Means of Atomic Force Microscopy-Infrared Spectroscopy

The development of antimicrobial resistance (AMR) resulting from widespread antibiotic usage is occurring at an alarming pace, much faster than our understanding of the mechanisms behind resistance. Knowledge about resistance-related phenotypic and genotypic changes is critical for the development of new drugs. Here, we identify changes in the chemical composition of Staphylococcus aureus associated with the development of resistance to last resort drugs, vancomycin and daptomycin, using a novel, single cell, nanoscale technique, atomic force microscopy-infrared spectroscopy (AFM-IR), combined with chemometric analysis. We utilized paired clinical isolates, with the parent (susceptible) strain isolated prior to treatment and the daughter (resistant) strain obtained from the same patient after drug admission and clinical failure. We observed an increase in the amount of nonintracellular carbohydrates, indicating thickening or changes in the packing of the cell wall, as well as changes in the phospholipid content in relation to vancomycin resistance and daptomycin nonsusceptibility, respectively.

Fourier-Transform Infrared (FTIR) Spectroscopy for Typing of Clinical Enterobacter cloacae Complex Isolates

Members of the Enterobacter (E.) cloacae complex have emerged as important pathogens frequently encountered in nosocomial infections. Several outbreaks with E. cloacae complex have been reported in recent years, especially in neonatal units. Fast and reliable strain typing methods are crucial for real-time surveillance and outbreak analysis to detect pathogen reservoirs and transmission routes. The aim of this study was to evaluate the performance of Fourier-transform infrared (FTIR) spectroscopy as a fast method for typing of clinical E. cloacae complex isolates, when whole genome sequencing (WGS) analysis was used as reference. First, the technique was used retrospectively on 24 first isolates of E. cloacae complex strains from neonatal patients and showed good concordance with SNP-based clustering [adjusted rand index (ARI) = 0.818] and with the sequence type (ST) (ARI = 0.801). 29 consecutive isolates from the same patients were shown by WGS analysis to almost always belong to the same SNP cluster as the first isolates, which was only inconsistently recognized by FTIR spectroscopy. Training of an artificial neural network (ANN) with all FTIR spectra from sequenced strains markedly improved the recognition of related and unrelated isolate spectra. In a second step, FTIR spectroscopy was applied on 14 strains during an outbreak with E. cloacae complex and provided fast typing results that were confirmed by WGS analysis. In conclusion, FTIR spectroscopy is a promising tool for strain typing of clinical E. cloacae complex strains. Discriminatory power can be improved by implementing an ANN for spectrum analysis. Due to its low costs and fast turnaround times, the method presents a valuable tool for real-time surveillance as well as outbreak analysis.

Is Infrared Spectroscopy Ready for the Clinic?

Fourier transform-infrared spectroscopy (FT-IR) represents an attractive molecular diagnostic modality for translation to the clinic, where comprehensive chemical profiling of biological samples may revolutionize a myriad of pathways in clinical settings. Principally, FT-IR provides a rapid, cost-effective platform to obtain a molecular fingerprint of clinical samples based on vibrational transitions of chemical bonds upon interaction with infrared light. To date, considerable research activities have demonstrated competitive to superior performance of FT-IR strategies in comparison to conventional techniques, with particular promise for earlier, accessible disease diagnostics, thereby improving patient outcomes. However, amidst the changing healthcare landscape in times of aging populations and increased prevalence of cancer and chronic disease, routine adoption of FT-IR within clinical laboratories has remained elusive. Hence, this perspective shall outline the significant clinical potential of FT-IR diagnostics and subsequently address current barriers to translation from the perspective of all stakeholders, in the context of biofluid, histopathology, cytology, microbiology, and biomarker discovery frameworks. Thereafter, future perspectives of FT-IR for healthcare will be discussed, with consideration of recent technological advances that may facilitate future clinical translation.

Application of FTIR Method for the Assessment of Immobilization of Active Substances in the Matrix of Biomedical Materials

Background: The purpose of the study was to demonstrate the usefulness of the Fourier transform infrared spectroscopy (FTIR) method for the evaluation of the modification process of biomaterials with the participation of active substances. Methods: Modified catheter samples were prepared by activating the matrix with an acid, iodine, or bromine, and then immobilizing the active molecules. To carry out the modification process, the Fourier transform infrared-attenuated total reflectance (FTIR-ATR) method was used. Results: FTIR analysis indicated the presence of the immobilized substances in the catheter matrix and site-specific reactions. Conclusion: We surmise that the infrared spectroscopic technique is an ideal tool for the assessment of the drug immobilization and the changes occurring in the course of the modification process.

Recent trends in molecular diagnostics of yeast infections: from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside.

Preliminary Assessment of Visible, Near-Infrared, and Short-Wavelength-Infrared Spectroscopy with a Portable Instrument for the Detection of Staphylococcus aureus Biofilms on Surfaces

Bacterial biofilms constitute a major source of sanitary problems and economic losses in the food industry. Indeed, biofilm removal may require intense mechanical cleaning procedures or very high concentrations of disinfectants or both, which can be damaging to the environment and human health. This study assessed the efficacy of a technique based on spectroscopy in the visible, near-infrared, and short-wavelength infrared range for the quick detection of biofilms formed on polystyrene by the pathogenic bacterium Staphylococcus aureus. To do that, biofilms corresponding to three S. aureus strains, which differed in biofilm-forming ability and composition of the extracellular matrix, were allowed to develop for 5 or 24 h, representing an active formation stage and mature biofilms, respectively. Spectral analysis of the samples, corresponding to three biological replicates of each condition, was then performed by using a portable device. The results of these experiments showed that partial least-squares discriminant analysis of the spectral profile could discriminate between surfaces containing attached bacterial biomass and noninoculated ones. In this model, the two first principal components accounted for 39 and 19% of the variance and the estimated error rate stabilized after four components. Cross-validation accuracy of this assessment was 100%. This work lays the foundation for subsequent development of a spectroscopy-based protocol that allows biofilm detection on food industrial surfaces.

Analysis of Streptococcus pneumoniae using Fourier-transformed infrared spectroscopy allows prediction of capsular serotype

Determination of the capsule type of clinical isolates of Streptococcus pneumoniae is a prerequisite for epidemiological studies and further vaccine development. The Quellung reaction for serotyping is expensive and mostly done in reference centres. We wanted to evaluate whether Fourier-transformed infrared (FT-IR) spectroscopy is suitable for capsular type analysis and prediction of pneumococcal serotypes. We used the IR-Biotyper™ (Bruker) to create a database containing the spectra of 120 strains from invasive disease. The strains covered the 24 vaccine serotypes contained in the 13-valent conjugate vaccine (PCV13) and the 23-valent polysaccharide vaccine (PSV23). Hierarchical clustering analysis was performed. Finally, two different classification sets were created (PCV13 and PSV23). They were used to predict the serotype of 168 different challenge strains (invasive and non-invasive disease) covering 48 different serotypes (vaccine and non-vaccine types). FT-IR spectra from pneumococci (1300–800 cm⁻¹) clustered along their serotype as determined by the Quellung reaction (120 strains, 24 different serotypes). Strains with unknown serotype fell within the cluster of the correct serotype, as long as the latter was represented in the database (168 strains, 48 different serotypes). Concordance between the Quellung reaction and FT-IR spectroscopy was excellent (kappa ≥ 0.75). FT-IR spectroscopy is a fast and cost-effective method to predict the capsular serotype of pneumococci.