Identification of microorganisms by FTIR spectroscopy: perspectives and limitations of the method

Fluorescence Spectroscopy Based Identification of Pseudomonas Aeruginosa and Escherichia Coli Suspensions

In this article, Fluorescence spectroscopy has been employed for the identification of Pseudomonas aeruginosa (PA) and Escherichia coli (E. coli) in water suspension. Emission spectra of PA and E. coli suspensions have been acquired by using excitation wavelengths from 270 to 420 nm with steps of 10 nm to explore their spectral features. It has been found that the emission spectra of tryptophan, tyrosine, NADH and FAD, being the intracellular biomolecules present in both bacteria, can be used as fingerprints for their identification, differentiation and quantification. Both bacterial strains can clearly be differentiated from water and from each other by using λex 270-290 nm through spectral analysis and from λex: 300-500 nm by applying statistical analysis. Furthermore, calibration curves for different bacterial loads of PA and E. coli suspensions have been produced between colonies forming units per ml (CFUs/ml) the integrated intensities of their emission spectra. CFUs/ml of both bacterial suspensions have been determined through plate count method which was used as cross-reference for the analysis of emission spectra of both bacterial suspensions. These curves may be used to estimate CFU/ml of both PA and E. coli in unknown water suspensions by determining the integrating intensity of their emission spectra.

Rapid Identification of Clinically Relevant Candida spp. by I-dOne Software Using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) Spectroscopy

Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy is a spectrum-based technique that quantifies the absorption of infrared light by molecules present in the microbial cell. The aim of the present study was to evaluate the performance of the ATR-FTIR spectroscopic technique via I-dOne software (Version 2.0) compared with the MALDI-TOF MS in identifying Candida spp. Each infrared spectrum was compared with spectra stored in the software database. The updated version of the I-dOne software was used to analyze ATR-FTIR spectra. All Candida isolates 284/284 (100%) were classified correctly according to the genus. Overall species identification yielded 272/284 (95.8%) concordant identification results with MALDI-TOF MS. Additionally, all 79 isolates belonging to the Candida parapsilosis species complex were identified correctly to the species level with the updated version of the I-dOne software. Only 12 (4.2%) isolates were misidentified at the species level. The present study highlights the potential diagnostic performance of the I-dOne software with ATR-FTIR spectroscopic technique referral spectral database as a real alternative for routine identification of the most frequently isolated Candida spp.

I-dOne: A diagnostic tool in the field of identification of clinically relevant microbial strains

This study evaluates the performance of I-dOne, the first CE-IVD marked software for microbial species identification based on Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR) and compares its results with MALDI-TOF MS technology (Vitek MS, bioMérieux). A total of 410 clinical isolates were analyzed, spanning 45 species and 24 genera. I-dOne demonstrated a high agreement rate (97.3 %) with the Vitek MS, meeting CLSI standard for microbial identification accuracy. Additionally, this study explored the development of a novel algorithm within I-dOne to discriminate between Bacteroides fragilis and Bacteroides ovatus strains, overcoming the current limitations in species-level differentiation. Finally, the influence of ageing under prolonged aerobic exposure on ATR-FTIR profiles was investigated, highlighting no significant spectral changes in Bacteroides fragilis strains under prolonged aerobic exposure. These findings underscore the accuracy of I-dOne software in microbial identification, offering a reliable alternative to conventional methods.

Formulation and evaluation of the effective microorganisms in sewage treatment

Effective microorganisms pose a great potential in wastewater treatment. In the present study, effective microorganisms' formulations were developed using different organic substrates that support the growth of more beneficial microorganisms for sewage treatment. Based on the metagenomic analysis and biochemical profile information, the fish waste-based effective microorganisms' formulation was identified as the effective formulation. Metagenomic analysis showed that fish-based effective microorganisms' formulation had the Lactobacillus and Acetobacter groups of bacteria. The dominant groups were Lactobacillus pontis (64.85%), Acetobacter aceti (8.92%), and Lactobacillus reuteri (8.98%). The developed fish waste-based effective microorganisms' formulation was used to treat the sewage water with different concentrations. Effective microorganisms' formulation at 3% showed appreciable results. It recorded a significant reduction in BOD from 389.2 to 117.9 mg L-1 and COD from 820.5 to 257.1 mg L-1 in 96 h. It also significantly decreased the concentration of ammoniacal and nitrate nitrogen, phosphorus, sulphate, and coliforms. Besides, the effective microorganisms' formulation ensured the reduced level of odour from sewage water. Therefore, we can effectively use the effective microorganisms' formulation for sewage water treatment and recycling.

Rapid bacterial identification through volatile organic compound analysis and deep learning

BACKGROUND

The increasing antimicrobial resistance caused by the improper use of antibiotics poses a significant challenge to humanity. Rapid and accurate identification of microbial species in clinical settings is crucial for precise medication and reducing the development of antimicrobial resistance. This study aimed to explore a method for automatic identification of bacteria using Volatile Organic Compounds (VOCs) analysis and deep learning algorithms.

RESULTS

AlexNet, where augmentation is applied, produces the best results. The average accuracy rate for single bacterial culture classification reached 99.24% using cross-validation, and the accuracy rates for identifying the three bacteria in randomly mixed cultures were SA:98.6%, EC:98.58% and PA:98.99%, respectively.

CONCLUSION

This work provides a new approach to quickly identify bacterial microorganisms. Using this method can automatically identify bacteria in GC-IMS detection results, helping clinical doctors quickly detect bacterial species, accurately prescribe medication, thereby controlling epidemics, and minimizing the negative impact of bacterial resistance on society.

Fluorescence Spectroscopy Based Characterization of Pseudomonas Aeruginosa Suspension

In this article, optical characterization of Pseudomonas aeruginosa (PA) suspension has been performed by using Fluorescence spectroscopy. Optical density (OD) and plate count methods have been employed as a reference for the analysis of emission spectra of Pseudomonas aeruginosa in water suspension. Emission spectra of PA suspension has been acquired by using excitation wavelengths from 270 to 420 nm with step of 10 nm to explore its spectral behavior. It has been found that emission spectra of tryptophan, tyrosine, NADH and FAD, the intracellular biomolecules of bacteria, can be used as finger prints for the detection of Pseudomonas aeruginosa. Furthermore, the effect of water matrix on the spectral emission of Pseudomonas aeruginosa has been investigated that might be one of the limitation of Fluorescence spectroscopy for complex water matrices. Moreover, a calibration curve has been produced between ODs600 of Pseudomonas aeruginosa suspensions of different bacterial load and integrated intensities of the emission spectra of same samples. These ODs600 and integrating intensities have been further vetted through plate count method by determining their corresponding colony forming units per ml (CFU/ml). This calibration curve may be used to determine CFU/ml of Pseudomonas aeruginosa in water sample by determining integrating intensity of its emission spectrum.

Machine Learning in FTIR Spectrum for the Identification of Antibiotic Resistance: A Demonstration with Different Species of Microorganisms

Recent studies introduced the importance of using machine learning algorithms in research focused on the identification of antibiotic resistance. In this study, we highlight the importance of building solid machine learning foundations to differentiate antimicrobial resistance among microorganisms. Using advanced machine learning algorithms, we established a methodology capable of analyzing the FTIR structural profile of the samples of Streptococcus pyogenes and Streptococcus mutans (Gram-positive), as well as Escherichia coli and Klebsiella pneumoniae (Gram-negative), demonstrating cross-sectional applicability in this focus on different microorganisms. The analysis focuses on specific biomolecules-Carbohydrates, Fatty Acids, and Proteins-in FTIR spectra, providing a multidimensional database that transcends microbial variability. The results highlight the ability of the method to consistently identify resistance patterns, regardless of the Gram classification of the bacteria and the species involved, reinforcing the premise that the structural characteristics identified are universal among the microorganisms tested. By validating this approach in four distinct species, our study proves the versatility and precision of the methodology used, in addition to bringing support to the development of an innovative protocol for the rapid and safe identification of antimicrobial resistance. This advance is crucial for optimizing treatment strategies and avoiding the spread of resistance. This emphasizes the relevance of specialized machine learning bases in effectively differentiating between resistance profiles in Gram-negative and Gram-positive bacteria to be implemented in the identification of antibiotic resistance. The obtained result has a high potential to be applied to clinical procedures.

Label-Free Monitoring of Coculture System Dynamics: Probing Probiotic and Cancer Cell Interactions via Infrared Spectroscopic Imaging

Evaluating the dynamic interaction of microorganisms and mammalian cells is challenging due to the lack of suitable platforms for examining interspecies interactions in biologically relevant coculture conditions. In this work, we demonstrate the interaction between probiotic bacteria (Lactococcus lactis and Escherichia coli) and A498 human cancer cells in vitro, utilizing a hydrogel-based platform in a label-free manner by infrared spectroscopy. The L. lactis strain recapitulated in the compartment system secretes polypeptide molecules such as nisin, which has been reported to trigger cell apoptosis. We propose a mid-infrared (IR) spectroscopic imaging approach to monitor the variation of biological components utilizing kidney cells (A498) as a model system cocultured with bacteria. We characterized the biochemical composition (i.e., nucleic acids, protein secondary structures, and lipid conformations) label-free using an unbiased measurement. Several IR spectral features, including unsaturated fatty acids, β-turns in protein, and nucleic acids, were utilized to predict cellular response. These features were then applied to establish a quantitative relationship through a multivariate regression model to predict cellular dynamics in the coculture system to assess the effect of nisin on A498 kidney cancer cells cocultured with bacteria. Overall, our study sheds light on the potential of using IR spectroscopic imaging as a label-free tool to monitor complex microbe-host cell interactions in biological systems. This integration will enable mechanistic studies of interspecies interactions with insights into their underlying physiological processes.

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.

Advancements in medical research: Exploring Fourier Transform Infrared (FTIR) spectroscopy for tissue, cell, and hair sample analysis

BACKGROUND

Fourier Transform Infrared (FTIR) spectroscopy has emerged as a powerful analytical tool in medical research, offering non-invasive and precise examination of the molecular composition of biological samples. The primary objective of this review is to underscore the benefits of FTIR spectroscopy in medicinal research, emphasizing its ability to delineate molecular fingerprints and assist in the identification of biochemical structures and key peaks in biological samples.

METHODS

This review comprehensively explores the diverse applications of FTIR spectroscopy in medical investigations, with a specific focus on its utility in analyzing tissue, cells, and hair samples. Various sources, including Google Scholar, PubMed, WorledCat and Scopus, were utilized to conduct this comprehensive literature review.

RESULTS

Recent advancements showcase the versatility of FTIR spectroscopy in elucidating cellular and molecular processes, facilitating disease diagnostics, and enabling treatment monitoring. Notably, FTIR spectroscopy has found significant utility in clinical assessment, particularly in screening counterfeit medicines, owing to its user-friendly operation and minimal sample preparation requirements. Furthermore, customs officials can leverage this technique for preliminary analysis of suspicious samples.

CONCLUSION

This review aims to bridge a gap in the literature and serve as a valuable resource for future research endeavors in FTIR spectroscopy within the medical domain. Additionally, it presents fundamental concepts of FTIR spectroscopy and spectral data interpretation, highlighting its utility as a tool for molecular analysis using Mid-Infrared (MIR) radiation.

Antimicrobial Ionic Liquids: Ante-Mortem Mechanisms of Pathogenic EPEC and MRSA Examined by FTIR Spectroscopy

Ionic liquids (ILs) have gained considerable attention due to their versatile and designable properties. ILs show great potential as antibacterial agents, but understanding the mechanism of attack on bacterial cells is essential to ensure the optimal design of IL-based biocides. The final aim is to achieve maximum efficacy while minimising toxicity and preventing resistance development in target organisms. In this study, we examined a dose-response analysis of ILs' antimicrobial activity against two pathogenic bacteria with different Gram types in terms of molecular responses on a cellular level using Fourier-transform infrared (FTIR) spectroscopy. In total, 18 ILs with different antimicrobial active motifs were evaluated on the Gram-negative enteropathogenic Escherichia coli (EPEC) and Gram-positive methicillin-resistant Staphylococcus aureus (MRSA). The results showed that most ILs impact bacterial proteins with increasing concentration but have a minimal effect on cellular membranes. Dose-response spectral analysis revealed a distinct ante-mortem response against certain ILs for MRSA but not for EPEC. We found that at sub-lethal concentrations, MRSA actively changed their membrane composition to counteract the damaging effect induced by the ILs. This suggests a new adaptive mechanism of Gram-positive bacteria against ILs and demonstrates the need for a better understanding before using such substances as novel antimicrobials.

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.

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.

A rapid spectroscopic method for the identification of the filamentous fungi isolated from Turkish traditional mold-ripened cheeses

Fourier transform infrared spectroscopy (FTIR) is an alternative microbial identification technique due to its faster analysis times and lower cost compared to molecular methods. In this study, forty-three fungal strains isolated from different Turkish traditional mold-ripened cheeses representing nine different Penicillium species (P. roqueforti, P. corylophilum, P. before, P. crustosum, P. spinulosum, P. rubens, P. brevicompactum, P. paneum, and P. solitum) were analyzed by using FTIR HTS-XT (High Throughput Screening Extension) method in the 4000-400 cm-1 wavenumber range. The spectra of the isolates were evaluated, and the chemical structures corresponding to the fungus-specific spectral regions were determined as fatty acids (3600-2800 cm-1), amide I and amide II of proteins and peptides (1740-1500 cm-1), polysaccharides (1200-900 cm-1) and carbohydrates (900-600 cm-1). The isolates were grouped according to the hierarchical clustering analysis (HCA) by applying chemometrics combined with FTIR spectroscopy. Results showed that FTIR spectroscopy has a high capability for rapid determination of cheese fungi based on their FTIR spectra.

Investigating the chemical pathway to the formation of a single biofilm using infrared spectroscopy

Diagnosing biofilm infections has remained a constant challenge for the last 50 years. Existing diagnostic methods struggle to identify the biofilm phenotype. Moreover, most methods of biofilm analysis destroy the biofilm making the resultant data interpretation difficult. In this study we introduce Fourier Transform Infra-Red (FTIR) spectroscopy as a label-free, non-destructive approach to monitoring biofilm progression. We have utilised FTIR in a novel application to evaluate the chemical composition of bacterial biofilms without disrupting the biofilm architecture. S. epidermidis (RP62A) was grown onto calcium fluoride slides for periods of 30 min-96 h, before semi-drying samples for analysis. We report the discovery of a chemical marker to distinguish between planktonic and biofilm samples. The appearance of new proteins in biofilm samples of varying maturity is exemplified in the spectroscopic data, highlighting the potential of FTIR for identifying the presence and developmental stage of a single biofilm.

Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives

Microorganisms play pivotal roles in shaping ecosystems and biogeochemical cycles. Their intricate interactions involve complex biochemical processes. Fourier Transform-Infrared (FT-IR) spectroscopy is a powerful tool for monitoring these interactions, revealing microorganism composition and responses to the environment. This review explores the diversity of applications of FT-IR spectroscopy within the field of microbiology, highlighting its specific utility in microbial cell biology and environmental microbiology. It emphasizes key applications such as microbial identification, process monitoring, cell wall analysis, biofilm examination, stress response assessment, and environmental interaction investigation, showcasing the crucial role of FT-IR in advancing our understanding of microbial systems. Furthermore, we address challenges including sample complexity, data interpretation nuances, and the need for integration with complementary techniques. Future prospects for FT-IR in environmental microbiology include a wide range of transformative applications and advancements. These include the development of comprehensive and standardized FT-IR libraries for precise microbial identification, the integration of advanced analytical techniques, the adoption of high-throughput and single-cell analysis, real-time environmental monitoring using portable FT-IR systems and the incorporation of FT-IR data into ecological modeling for predictive insights into microbial responses to environmental changes. These innovative avenues promise to significantly advance our understanding of microorganisms and their complex interactions within various ecosystems.

Evaluation of copper-induced biomolecular changes in different porin mutants of Escherichia coli W3110 by infrared spectroscopy

Copper (Cu), one of the heavy metals, plays a vital role in many complex biochemical reactions as a trace element. However, it often becomes toxic when its concentration in the cell exceeds a certain level. Homeostasis of metals in the cell is primarily related to regulating metal transport into and out of the cell. Therefore, it is thought that porin proteins, which have a role in membrane permeability, may also play a role in developing Cu resistance. This study identified the differences between the molecular profiles of wild-type Escherichia coli W3110 and its seven different porin mutants exposed to Cu ions using attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy. The results showed that the absence of porin genes elicits global changes in the structure and composition of membrane lipids and proteins, in both the absence and presence of Cu. The lack of porin genes significantly elevated the amounts of fatty acids and phospholipids. When the alterations in protein secondary structures were compared, the quantity of amide I proteins was diminished by the presence of Cu. However, the amount of amide II proteins increased in porin mutant groups independent of Cu presence or absence. The DNAs are transformed from B- and Z-form to A-form due to porin mutations and the presence of Cu ions. The lack of porin genes increased polysaccharide content independent of Cu presence. This study can help characterize Cu detoxification efficiency and guide for obtaining active living cells to be used in bioremediation.

Harmonic Vibrational Frequency Simulation of Pharmaceutical Molecules via a Novel Multi-Molecular Fragment Interception Method

By means of a computational method based on Density Functional Theory (DFT), using commercially available software, a novel method for simulating equilibrium geometry harmonic vibrational frequencies is proposed. Finasteride, Lamivudine, and Repaglinide were selected as model molecules to study the adaptability of the new method. Three molecular models, namely the single-molecular, central-molecular, and multi-molecular fragment models, were constructed and calculated by Generalized Gradient Approximations (GGAs) with the PBE functional via the Material Studio 8.0 program. Theoretical vibrational frequencies were assigned and compared to the corresponding experimental data. The results indicated that the traditional single-molecular calculation and scaled spectra with scale factor exhibited the worst similarity for all three pharmaceutical molecules among the three models. Furthermore, the central-molecular model with a configuration closer to the empirical structure resulted in a reduction of mean absolute error (MAE) and root mean squared error (RMSE) in all three pharmaceutics, including the hydrogen-bonded functional groups. However, the improvement in computational accuracy for different drug molecules using the central-molecular model for vibrational frequency calculation was unstable. Whereas, the new multi-molecular fragment interception method showed the best agreement with experimental results, exhibiting MAE and RMSE values of 8.21 cm^-1 and 18.35 cm^-1 for Finasteride, 15.95 cm^-1 and 26.46 cm^-1 for Lamivudine, and 12.10 cm^-1 and 25.82 cm^-1 for Repaglinide. Additionally, this work provides comprehensive vibrational frequency calculations and assignments for Finasteride, Lamivudine, and Repaglinide, which have never been thoroughly investigated in previous research.

Optical Immunosensor for the Detection of Listeria monocytogenes in Food Matrixes

In this paper, simple imine-based organic fluorophore 4-amino-3-(anthracene-9 yl methyleneamino) phenyl (phenyl) methanone (APM) has been synthesized via a greener approach and the same was used to construct a fluorescent immunoassay for the detection of Listeria monocytogenes (LM). A monoclonal antibody of LM was tagged with APM via the conjugation of the amine group in APM and the acid group of anti-LM through EDC/NHS coupling. The designed immunoassay was optimized for the specific detection of LM in the presence of other interfering pathogens based on the aggregation-induced emission mechanism and the formation of aggregates and their morphology was confirmed with the help of scanning electron microscopy. Density functional theory studies were done to further support the sensing mechanism-based changes in the energy level distribution. All photophysical parameters were measured by using fluorescence spectroscopy techniques. Specific and competitive recognition of LM was done in the presence of other relevant pathogens. The immunoassay shows a linear appreciable range from 1.6 × 10⁶-2.7024 × 10⁸ cfu/mL using the standard plate count method. The LOD has been calculated from the linear equation and the value is found as 3.2 cfu/mL, and this is the lowest LOD value reported for the detection of LM so far. The practical applications of the immunoassay were demonstrated in various food samples, and their accuracy obtained was highly comparable with the standard existing ELISA method.

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.

Vibrational Spectroscopy as a Tool for Bioanalytical and Biomonitoring Studies

The review briefly describes various types of infrared (IR) and Raman spectroscopy methods. At the beginning of the review, the basic concepts of biological methods of environmental monitoring, namely bioanalytical and biomonitoring methods, are briefly considered. The main part of the review describes the basic principles and concepts of vibration spectroscopy and microspectrophotometry, in particular IR spectroscopy, mid- and near-IR spectroscopy, IR microspectroscopy, Raman spectroscopy, resonance Raman spectroscopy, Surface-enhanced Raman spectroscopy, and Raman microscopy. Examples of the use of various methods of vibration spectroscopy for the study of biological samples, especially in the context of environmental monitoring, are given. Based on the described results, the authors conclude that the near-IR spectroscopy-based methods are the most convenient for environmental studies, and the relevance of the use of IR and Raman spectroscopy in environmental monitoring will increase with time.

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

Background

Development of an accessible method to routinely evaluate the clonality of strains is needed in microbiology laboratories. We compared the discriminatory power of the Fourier-transform infrared (FTIR) spectroscopy-based IR Biotyper (Bruker Daltonics GmbH, Bremen, Germany) to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), using whole-genome sequencing (WGS) as the reference method.

Methods

Eighty-three extended-spectrum β-lactamase-producing Escherichia coli isolates were tested using WGS, MALDI-TOF MS, and IR Biotyper. Simpson's diversity index (SDI), a statistical analysis for testing the homogeneity of a dendrogram, and the adjusted Rand index (aRI) were used to compare the discriminatory ability between typing tests.

Results

The SDI (95% confidence interval) was 0.969 (0.952-0.985) for WGS, 0.865 (0.807-0.924) for MALDI-TOF MS, and 0.974 (0.965-0.983) for IR Biotyper. Compared with WGS, IR Biotyper showed compatible diversity, whereas MALDI-TOF MS did not. The concordance and aRI improved from 66.3% to 84.3% and from 0.173 to 0.538, respectively, for IR Biotyper versus MALDI-TOF MS with WGS as the reference method. IR Biotyper showed substantially improved performance in strain typing compared with MALDI-TOF MS.

Conclusions

IR Biotyper is useful for diversity analysis with improved discriminatory power over MALDI-TOF MS in comparison with WGS as a reference method. IR Biotyper is an accessible method to evaluate the clonality of strains and could be applied in epidemiological analysis during an outbreak of a health care facility, as well as for research on the transmission of resistant bacteria in community settings.

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.

Fast detection of bacterial contamination in fresh produce using FTIR and spectral classification

Screening for microbial contaminants in fresh produce is a lengthy process relative to their short shelf-life. The aim of this study is to develop a comprehensive assay which employs FTIR and spectral classification algorithm for detection of bacterial contamination of fresh produce. The procedure starts by soaking a sample of the fresh produce in broth for 5 h. Then, magnetic nanoparticles are added to capture bacteria which are then collected and prepared for FTIR scanning. The generated FTIR spectra are compared against an in-house database of different bacterial species (n = 6). The ability of the database to discriminate contaminated and uncontaminated samples and to identify the bacterial species was assessed. The compatibility of the FTIR procedures with subsequent DNA extraction and PCR was tested. The developed procedure was applied for assessment of bacterial contamination in fresh produce samples from the market (n = 78). Results were compared to the conventional culture methods. The generated FTIR database coupled to spectral classification was able to detect bacterial contamination with overall accuracy exceeding 90%. The sample processing did not alter the integrity of the bacterial DNA which was suitable for PCR. On application to fresh produce samples collected from the market, the developed method was able to detect bacterial contamination with 94% concordance with the culture method. In conclusion, the developed procedure can be applied for fast detection of microbial contamination in fresh produce with comparable accuracy to conventional microbiological assays and is compatible with subsequent molecular assays.

Identification of hepatocellular carcinoma and paracancerous tissue based on the peak area in FTIR microspectroscopy

Hepatocellular carcinoma (HCC) is one of the most common primary hepatic malignancies across the world. The annual incidence and death rates have increased at the highest rate of all cancers in recent years. Surgical resection is a potentially curative option for solitary HCC or unilobar disease without evidence of metastases or vascular invasion. This study focuses on the molecular differences between the HCC foci and paracancerous tissues and provides some valuable biomarkers based on the vibrational spectrum. Fourier transform infrared (FTIR) spectroscopy is a non-invasive and qualitative and semi-quantitative analysis technique that has been widely applied for the identification of macromolecular changes in biological tissues. In this study, the FTIR spectra of the HCC foci and the paracancerous tissues were recorded separately, and ten areas under the absorption peaks of all the specimens were calculated. The result demonstrates that the areas of protein-related absorption peaks at 1398 cm^-1, 1548 cm^-1, 1654 cm^-1 and 3070 cm^-1 may be the key indicators of the two different regions. After coupling with the classification algorithms of k-nearest neighbor (KNN), random forest (RF) and support vector machine (SVM), it was found that SVM with an RBF kernel performed best with the AUC (area under the ROC curve) reaching 0.997, and the performance was better than the feature based on the full spectrum. This reveals that the peak area-based FTIR spectra combined with the SVM algorithm may be a promising tool in identifying the HCC foci and the paracancerous tissues.

The structural effects of Vitamin A deficiency on biological macromolecules due to ethanol consumption and withdrawal: An FTIR study with chemometrics

The structural effects of vitamin A-deficiency were examined on the molecular profiles of biomolecules of male rat hippocampus during prolonged ethanol intake/withdrawal using FT-IR spectroscopy coupled with chemometrics. Liquid ethanol diet with/without vitamin A was maintained to adult rats for 3-months. The rats were decapitated at different ethanol withdrawal times and FT-IR spectra were obtained. Ethanol consumption/withdrawal produced significant changes in proteins' conformations, while having insignificant structural effects on lipids. In vitamin A deficiency, ethanol produced structural changes in lipids by lipid ordering especially in the early-ethanol withdrawal. Furthermore, an increase in lipid and protein content, saturated/unsaturated lipid ratio, a decrease in nucleic acids content and decrease in membrane fluidity were observed. These changes were less severe in the presence of Vitamin A. This study is clinically important for individuals with vitamin A deficiency because they have to be more cautious when consuming alcohol to protect themselves from cognitive dysfunctions.

Infra-red spectroscopy combined with machine learning algorithms enables early determination of Pseudomonas aeruginosa's susceptibility to antibiotics

Pseudomonas (P.) aeruginosa is a bacterium responsible for severe infections that have become a real concern in hospital environments. Nosocomial infections caused by P. aeruginosa are often hard to treat because of its intrinsic resistance and remarkable ability to acquire further resistance mechanisms to multiple groups of antimicrobial agents. Thus, rapid determination of the susceptibility of P. aeruginosa isolates to antibiotics is crucial for effective treatment. The current methods used for susceptibility determination are time-consuming; hence the importance of developing a new method. Fourier-transform infra-red (FTIR) spectroscopy is known as a rapid and sensitive diagnostic tool, with the ability to detect minor abnormal molecular changes including those associated with the development of antibiotic- resistant bacteria. The main goal of this study is to evaluate the potential of FTIR spectroscopy together with machine learning algorithms, to determine the susceptibility of P. aeruginosa to different antibiotics in a time span of ∼20 min after the first culture. For this goal, 590 isolates of P. aeruginosa, obtained from different infection sites of various patients, were measured by FTIR spectroscopy and analyzed by machine learning algorithms. We have successfully determined the susceptibility of P. aeruginosa to various antibiotics with an accuracy of 82-90%.

Applying spectrochemical analyses on venous disease patients treated by N-Butyl Cyanoacrylate Ablation Surgery

BACKGROUND: The venous disease of the legs is a common disease among adults that may lead to a deterioration in the structure and concentration of biomolecules. N-Butyl Cyanoacrylate Ablation Surgery (NBCA) or cyanoacrylate embolization (CAE) technique to adhesive the saphenous vein is an alternative method for the treatment of venous disease. OBJECTIVE: We aimed to show what kind of changes occurs after CAE surgery using FTIR spectroscopy combined chemometrics. We compared before and after surgery blood sera of patients to find whether a correlation between spectral data and laboratory indexes. We studied the blood sera of those who suffered from varicose veins and treated them by CAE technique. METHODS: In order to examine the molecular profiles in blood sera who underwent the CAE technique of the great saphenous vein for the treatment we used Fourier Transform InfraRed spectroscopy (FTIR) spectroscopy of blood samples of patients before and after surgery as a fast diagnostic technique. To obtain information about the spectra variation among the types of samples Principal component analysis (PCA) was performed for fingerprint, amide II with amide I regions. To find normality among variations Partial Least Square P-P plot of residual was performed. RESULTS: Absorbance values were statistically significant only in amide II, amide I, and OH vibrations. In the blood collected before surgery, higher peaks area of α-helix and β-harmonica were noticed. However, in both groups of samples, a higher amount of β-harmonica was visible. Pearson correlation analysis showed that the value of white blood cells (WBC) correlate with absorbance at 2858 cm-1 wavenumber. Moreover, a correlation between neutrophil (NEU) and OH vibrations, and between hematocrit (HCT) and 1082 cm-1, were found. Furthermore, a high correlation Platelets (PLT) and FTIR peak at 1165 cm-1, was noticed. CONCLUSIONS: This methodology suggests with PCA analysis CAE caused structural and quantitative chemical changes in blood samples of patients.

Protein FT-IR amide bands are beneficial to bacterial typing

Bacterial FT-IR signals are extremely specific and highly reproducible, making FT-IR an efficient tool for bacterial typing at the subspecies level. The polysaccharide and nucleic acid FT-IR regions (1200-900 cm^-1) are recommended as a precise and reproducible pattern for bacterial typing. However, proteins are the major macromolecules present in bacteria, and the FT-IR spectral region of proteins (1800-1300 cm^-1) is conceivably an important factor in bacterial typing. In this study, we investigated the influence of water on bacterial protein amide bands by comparing spectra obtained with and without FT-IR system dehydration. Eight Escherichia coli, ten Klebsiella pneumoniae, and eleven Staphylococcus aureus strains were typed by FT-IR under different conditions in a blinded experimental setup. Hierarchical clustering analysis (HCA) showed that, when protein signals were included (1800-900 cm^-1), the typing accuracies for select E. coli, K. pn and S. aureus strains without system dehydration were 50%, 30% and 18.2%, respectively. However, the accuracies greatly improved to 100%, 90% and 90.9% when the FT-IR system was dehydrated. These results indicate that the FT-IR signals of protein amide bands are beneficial for bacterial typing.

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.

Vibrational Spectroscopy: A Valuable Screening and Diagnostic Tool for Obstetric Disorders?

Preeclampsia (PE) is a common obstetric disorder typically affecting 2–8% of all pregnancies and can lead to several adverse obstetric outcomes for both mother and fetus with the greatest burden of severe outcomes in low middle-income countries (LMICs), therefore, screening for PE is vital. Globally, screening is based on maternal characteristics and medical history which are nonspecific for the disorder. In 2004, the World Health Organization acknowledged that no clinically useful test was able to predict the onset of PE, which prompted a universal search for alternative means of screening. Over the past decade or so, emphasis has been placed on the use of maternal characteristics in conjunction with biomarkers of disease combined into predictive algorithms, however these are yet to transition into the clinic and are cost prohibitive in LMICs. As a result, the screening paradigm for PE remains unchanged. It is evident that novel approaches are needed. Vibrational spectroscopy, specifically Raman spectroscopy and Fourier-transform infrared spectroscopy (FTIR), could provide better alternatives suited for implementation in low resource settings as no specialized reagents are required for conventional approaches and there is a drive to portable platforms usable in both urban and rual community settings. These techniques are based on light scattering and absorption, respectively, allowing detailed molecular analysis of samples to produce a unique molecular fingerprint of diseased states. The specificity of vibrational spectroscopy might well make it suited for application in other obstetric disorders such as gestational diabetes mellitus and obstetric cholestasis. In this review, we summarize current approaches sought as alternatives to current screening methodologies and introduce how vibrational spectroscopy could offer superior screening and diagnostic paradigms in obstetric care. Additionally, we propose a real benefit of such tools in LMICs where limited resources battle the higher prevalence of obstetric disorders.

Determination of Klebsiella pneumoniae Susceptibility to Antibiotics Using Infrared Microscopy

Klebsiella pneumoniae (K. pneumoniae) is one of the most aggressive multidrug-resistant bacteria associated with human infections, resulting in high mortality and morbidity. We obtained 1190 K. pneumoniae isolates from different patients with urinary tract infections. The isolates were measured to determine their susceptibility regarding nine specific antibiotics. This study's primary goal is to evaluate the potential of infrared spectroscopy in tandem with machine learning to assess the susceptibility of K. pneumoniae within approximately 20 min following the first culture. Our results confirm that it was possible to classify the isolates into sensitive and resistant with a success rate higher than 80% for the tested antibiotics. These results prove the promising potential of infrared spectroscopy as a powerful method for a K. pneumoniae susceptibility test.

A robust metabolomics approach for the evaluation of human embryos from in vitro fertilization

The identification of the most competent embryos for transfer to the uterus constitutes the main challenge of in vitro fertilization (IVF). We established a metabolomic-based approach by applying Fourier transform infrared (FTIR) spectroscopy on 130 samples of 3-day embryo culture supernatants from 26 embryos that implanted and 104 embryos that failed. On examining the internal structure of the data by unsupervised multivariate analysis, we found that the supernatant spectra of nonimplanted embryos constituted a highly heterogeneous group. Whereas ∼40% of these supernatants were spectroscopically indistinguishable from those of successfully implanted embryos, ∼60% exhibited diverse, heterogeneous metabolic fingerprints. This observation proved to be the direct result of pregnancy's multifactorial nature, involving both intrinsic embryonic traits and external characteristics. Our data analysis strategy thus involved one-class modelling techniques employing soft independent modelling of class analogy that identified deviant fingerprints as unsuitable for implantation. From these findings, we could develop a noninvasive Fourier-transform-infrared-spectroscopy-based approach that represents a shift in the fundamental paradigm for data modelling applied in assisted-fertilization technologies.

Evaluation of the IR Biotyper for Klebsiella pneumoniae typing and its potentials in hospital hygiene management

Klebsiella pneumoniae has emerged as one of the most important pathogens that frequently encounter in community-acquired or hospital-acquired infections. Timely epidemiological surveillance could greatly facilitate infection control of K. pneumoniae and many deadly pathogens alike. In this study, we evaluated the performance of the IR Biotyper, a Fourier transform infrared (FTIR) spectroscopy system for K. pneumoniae isolates typing through (i) optimizing the culture scheme and defining the cutoff value (COV) range and (ii) comparing with commonly used typing tools such as multi-locus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE) and whole-genome sequencing (WGS). We found that a non-selective and non-chromogenic medium with 24 ± 2 h incubation gives the best discriminatory power for the IR Biotyper (IRBT). COV evaluation indicated that the IRBT is a robust typing method with good reproducibility. Besides, we observed that the modified H2 O-EtOH suspensions preparation method could enhance the quality of the spectrum, especially for those hypermucoviscous strains. For the method comparison study, our data demonstrated that FTIR spectroscopy could accurately cluster K. pneumoniae strains. The typing results of the IRBT were almost entirely in concordance with those from PFGE and WGS. Together with the advantages such as low costs and short turnaround time (less than 3h), the IRBT is a promising tool for strain typing that could make real-time outbreak investigation a reality.

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.

Rapid classification of chromoblastomycosis agents genera by infrared spectroscopy and chemometrics supervised by sequencing of rDNA regions

Chromoblastomycosis (CBM) is a skin and subcutaneous infection caused by species of seven fungal genera. Identification of CBM species is performed by DNA sequencing of one or more genes, which becomes a time-consuming work. Fourier Transform Infrared Spectroscopy (FTIR) has been used for the identification of other microorganisms, however, only one CBM genus was evaluated by FTIR analysis to date. Therefore, the study is aimed to differentiate the CBM agents for identification at genera level using FTIR supervised by Internal Transcribed Spacer (ITS) rDNA region. Seventy-seven isolates of the main five CBM genera were prepared for Attenuated Total Reflection FTIR (ATR-FTIR) with a new methodology using slices of dry fungus in glass fixing-modeling proposed in this study. The algorithm Hierarchical Cluster Analysis (HCA) was used to analyze the differences and similarities between species through the spectra. Orthogonal Partial Least Square Discriminant Analysis (OPLS-DA) allowed to correctly classify all samples of five CBM genera. The ATR-FTIR/OPLS-DA models highlighted important contributions of regions attributed to NH and OH stretching, amide I of proteins, polysaccharides bands and fingerprint region for the complete differentiation of the genera investigated. Thus, FTIR can be a fast and inexpensive alternative for identification of CBM agents.

Epidemiologic case investigation on the zoonotic transmission of Staphylococcus aureus infection from goat to veterinarians

Staphylococcus aureus infection led to a case of goat abortion, and four veterinarians contracted S. aureus infection from the goat during and after the abortion. Three veterinarians assisted a doe during the dystocic delivery of a dead foetus. Seventy-two hours after the dystocia, which ended with the goat's death, the veterinarians who assisted during the kidding and the veterinarian who performed the necropsy showed the presence of multiple, isolated, painful pustules 1-5 mm in diameter located along their forearms and knees. S. aureus was isolated from the pustules of the veterinarians, the placenta and uterus of the goat, the organs (brain, thymus gland, abomasum, liver and spleen) of the foetus, the scrotum and eye swabs of the buck, and mammary pustules of another goat from the same herd. Histological analysis revealed purulent metritis and inflammation of the placental cotyledons. Additional investigations eliminated the chances of other infections. S. aureus isolates recovered from the veterinarians, goats, foetus and buck were sensitive to the tested anti-microbials and did not encode staphylococcal enterotoxin genes (sea, ser, sep, see, seg and sei). The isolates were closely related, as indicated by the results of Fourier-transform infrared spectroscopy and comparative whole-genome sequencing analysis. The results of this study clearly support the hypothesis that an episode of professional zoonosis was caused by S. aureus infection during the abortion and also highlight the need for bacterial subtyping in epidemiological surveys.

Assessing the Biofilm Formation Capacity of the Wine Spoilage Yeast Brettanomyces bruxellensis through FTIR Spectroscopy

Brettanomyces bruxellensis is a wine spoilage yeast known to colonize and persist in production cellars. However, knowledge on the biofilm formation capacity of B. bruxellensis remains limited. The present study investigated the biofilm formation of 11 B. bruxellensis strains on stainless steel coupons after 3 h of incubation in an aqueous solution. FTIR analysis was performed for both planktonic and attached cells, while comparison of the obtained spectra revealed chemical groups implicated in the biofilm formation process. The increased region corresponding to polysaccharides and lipids clearly discriminated the obtained spectra, while the absorption peaks at the specific wavenumbers possibly reveal the presence of β-glucans, mannas and ergosterol. Unsupervised clustering and supervised classification were employed to identify the important wavenumbers of the whole spectra. The fact that all the metabolic fingerprints of the attached versus the planktonic cells were similar within the same cell phenotype class and different between the two phenotypes, implies a clear separation of the cell phenotype; supported by the results of the developed classification model. This study represents the first to succeed at applying a non-invasive technique to reveal the metabolic fingerprint implicated in the biofilm formation capacity of B. bruxellensis, underlying the homogenous mechanism within the yeast species.

Fast Screening and Primary Diagnosis of COVID-19 by ATR-FT-IR

The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial for quick isolation and clinical intervention. In this work, we showed that attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FT-IR) can be a primary diagnostic tool for COVID-19 as a supplement to in-use techniques. It requires only a small volume (∼3 μL) of the serum sample and a shorter detection time (several minutes). The distinct spectral differences and the separability between normal control and COVID-19 were investigated using multivariate and statistical analysis. Results showed that ATR-FT-IR coupled with partial least squares discriminant analysis was effective to differentiate COVID-19 from normal controls and some common respiratory viral infections or inflammation, with the area under the receiver operating characteristic curve (AUROC) of 0.9561 (95% CI: 0.9071-0.9774). Several serum constituents including, but not just, antibodies and serum phospholipids could be reflected on the infrared spectra, serving as "chemical fingerprints" and accounting for good model performances.

Fast Screening and Primary Diagnosis of COVID-19 by ATR-FT-IR

The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial for quick isolation and clinical intervention. In this work, we showed that attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FT-IR) can be a primary diagnostic tool for COVID-19 as a supplement to in-use techniques. It requires only a small volume (∼3 μL) of the serum sample and a shorter detection time (several minutes). The distinct spectral differences and the separability between normal control and COVID-19 were investigated using multivariate and statistical analysis. Results showed that ATR-FT-IR coupled with partial least squares discriminant analysis was effective to differentiate COVID-19 from normal controls and some common respiratory viral infections or inflammation, with the area under the receiver operating characteristic curve (AUROC) of 0.9561 (95% CI: 0.9071-0.9774). Several serum constituents including, but not just, antibodies and serum phospholipids could be reflected on the infrared spectra, serving as "chemical fingerprints" and accounting for good model performances.

Potential of FTIR-Spectroscopy for Drugs Screening against Helicobacter pylori

Helicobacter pylori colonizes the human stomach of half of the world's population. The infection if not treated, persists through life, leading to chronic gastric inflammation, that may progress to severe diseases as peptic ulcer, gastric adenocarcinoma, and mucosa-associated lymphoid tissue lymphoma. The first line of treatment, based on 7 to 21 days of two antibiotics associated with a proton pump inhibitor, is, however, already failing most due to patient non-compliance that leads to antibiotic resistance. It is, therefore, urgent to screen for new and more efficient antimicrobials against this bacterium. In this work, Fourier Transform Infrared (FTIR) spectroscopy was evaluated to screen new drugs against H. pylori, in rapid (between 1 to 6 h), and high-throughput mode and based on a microliter volume processes in relation to the agar dilution method. The reference H. pylori strains 26,695 and J99, were evaluated against a peptide-based antimicrobial and the clinical antibiotic clarithromycin, respectively. After optimization of the assay conditions, as the composition of the incubation mixture, the time of incubation, and spectral pre-processing, it was possible to reproducibly observe the effect of the drug on the bacterial molecular fingerprint as pointed by the spectra principal component analysis. The spectra, obtained from both reference strains, after its incubation with drugs concentrations lower than the MIC, presented peak ratios statistically different (p < 0.05) in relation to the bacteria incubated with drugs concentrations equal or higher to the MIC. It was possible to develop a partial least square regression model, enabling to predict from spectra of both bacteria strains, the drug concentration on the assay, with a high correlation coefficient between predicted and experimental data (0.91) and root square error of 40% of the minimum inhibitory concentration. All this points to the high potential of the technique for drug screening against this fastidious growth bacterium.

Prediction of itraconazole minimum inhibitory concentration for Fonsecaea pedrosoi using Fourier Transform Infrared Spectroscopy (FTIR) and chemometrics

Fonsecaea pedrosoi is one of the main agents of chromoblastomycosis, a chronic subcutaneous mycosis. Itraconazole (ITC) is the most used antifungal in its treatment, however, in vitro antifungal susceptibility tests are important to define the best therapy. These tests are standardized by the Clinical and Laboratory Standards Institute (CLSI), but these protocols have limitations such as the high complexity, cost and time to conduct. An alternative to in vitro susceptibility test, which overcomes these limitations, is FTIR. This study determined the minimum inhibitory concentration (MIC) of itraconazole for F. pedrosoi, using FTIR and chemometrics. The susceptibility to ITC of 36 strains of F. pedrosoi was determined according to CLSI and with the addition of tricyclazole (TCZ), to inhibit 1,8-dihydroxynaphthalene (DHN)-melanin biosynthesis. Strains were grown in Sabouraud agar and prepared for Attenuated Total Reflection (ATR)/FTIR. Partial least squares (PLS) regression was performed using leave-one-out cross-validation (by steps of quintuplicates), then tested on an external validation set. A coefficient of determination (R²) higher than 0.99 was obtained for both the MIC-ITC and MIC-ITC+TCZ ATR/PLS models, confirming a high correlation of the reference values with the ones predicted using the FTIR spectra. This is the first study to propose the use of FTIR and chemometric analyses according to the M38-A2 CLSI protocol to predict ITC MICs of F. pedrosoi. Considering the limitations of the conventional methods to test in vitro susceptibility, this is a promising methodology to be used for other microorganisms and drugs.

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.

Artificial neural network-assisted Fourier transform infrared spectroscopy for differentiation of Salmonella serogroups and its application on epidemiological tracing of Salmonella Bovismorbificans outbreak isolates from fresh sprouts

Salmonellae represent one of the most common bacterial infection reagents in both humans and animals. For detection and epidemiological elucidation of Salmonella infections, determination of Salmonella serotypes and differentiation between different Salmonella isolates is crucial. In the first part of this study, Artificial Neural Network (ANN)-assisted Fourier transform infrared (FTIR) spectroscopy was used to establish a method for subtyping Salmonella isolates according to their serogroups. For this, 290 Salmonella strains from 35 different serogroups were used to establish an ANN for differentiation between infrared spectra of 10 different Salmonella serogroups (B, C1, C2-C3, D1/D2, E1, E4, F, G, H, O:55) vs. the remaining serogroups. In the final ANN, sensitivity values ranged between 90 and 100% for most of the 10 serogroups under investigation. In the second part of this study, ANN-assisted FTIR spectroscopy was applied for epidemiological distinction of Salmonella Bovismorbificans outbreak isolates from fresh sprouts vs. isolates from other sources. Four Salmonella Bovismorbificans isolates from human and food origin in the context of a Southern German outbreak were successfully discriminated from other S. Bovismorbificans isolates from various sources. ANN-assisted FTIR spectroscopy is thus an effective tool for discrimination of Salmonella isolates at or even below serogroup level.

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.