Rapid species and strain differentiation of non-tubercoulous mycobacteria by Fourier-Transform Infrared microspectroscopy

Optimal Spectral Resolution for Infrared Studies of Solids and Liquids

Due to a legacy originating in the limited capability of early computers, the spectroscopic resolution used in Fourier transform infrared spectroscopy and other systems has largely been implemented using only powers of two for more than 50 years. In this study, we investigate debunking the spectroscopic lore of, e.g., using only 2, 4, 8, or 16 cm-1 resolution and determine the optimal resolution in terms of both (i) a desired signal-to-noise ratio and (ii) efficient use of acquisition time. The study is facilitated by the availability of solids and liquids reference spectral data recorded at 2.0 cm-1 resolution and is based on an examination in the 4000-400 cm-1 range of 61 liquids and 70 solids spectra, with a total analysis of 4237 peaks, each of which was also examined for being singlet/multiplet in nature. Of the 1765 liquid bands examined, only 27 had widths <5 cm-1. Of the 2472 solid bands examined, only 39 peaks have widths <5 cm-1. For both the liquid and solid bands, a skewed distribution of peak widths was observed: For liquids, the mean peak width was 24.7 cm-1 but the median peak width was 13.7 cm-1, and, similarly, for solids, the mean peak width was 22.2 cm-1 but the median peak width was 11.2 cm-1. While recognizing other studies may differ in scope and limiting the analysis to only room temperature data, we have found that a resolution to resolve 95% of all bands is 5.7 cm-1 for liquids and 5.3 cm-1 for solids; such a resolution would capture the native linewidth (not accounting for instrumental broadening) for 95% of all the solids and liquid bands, respectively. After decades of measuring liquids and solids at 4, 8, or 16 cm-1 resolution, we suggest that, when accounting only for intrinsic linewidths, an optimized resolution of 6.0 cm-1 will capture 91% of all condensed-phase bands, i.e., broadening of only 9% of the narrowest of bands, but yielding a large gain in signal-to-noise with minimal loss of specificity.

Spectroscopic Characterization of Bovine, Avian and Johnin Purified Protein Derivative (PPD) with High-Throughput Fourier Transform InfraRed-Based Method

Tuberculins purified protein derivatives (PPDs) are obtained by precipitation from heat treated mycobacteria. PPDs are used in diagnosis of mycobacterial infections in humans and animals. Bovine PPD (PPDB) is obtained from Mycobacterium bovis (Mycobacterium tuberculosis complex), while Avian PPD (PPDA) and Johnin PPD (PPDJ) are extracted, respectively, from Mycobacterium avium and M. avium subsp. paratuberculosis (M. avium complex). PPDB and PPDA are used for bovine tuberculosis diagnosis, while PPDJ is experimentally used in the immunodiagnosis of paratuberculosis. Although PPDs date back to the 19th Century, limited knowledge about their composition is currently available. The goal of our study was to evaluate Fourier Transform InfraRed (FTIR) spectroscopy as a tool to differentiate PPDB, PPDA, and three PPDJs. The results highlighted that the three PPDs have specific profiles, correlated with phylogenetic characteristics of mycobacteria used for their production. This analysis is eligible as a specific tool for different PPDs batches characterization and for the assessment of their composition. The entire PPD production may be efficiently controlled, since the N content of each preparation is related to IR spectra, with a reference spectrum for each PPD and a standardized analysis protocol.

Detection and Identification of Bacillus cereus, Bacillus cytotoxicus, Bacillus thuringiensis, Bacillus mycoides and Bacillus weihenstephanensis via Machine Learning Based FTIR Spectroscopy

The Bacillus cereus group comprises genetical closely related species with variable toxigenic characteristics. However, detection and differentiation of the B. cereus group species in routine diagnostics can be difficult, expensive and laborious since current species designation is linked to specific phenotypic characteristic or the presence of species-specific genes. Especially the differentiation of Bacillus cereus and Bacillus thuringiensis, the identification of psychrotolerant Bacillus mycoides and Bacillus weihenstephanensis, as well as the identification of emetic B. cereus and Bacillus cytotoxicus, which are both producing highly potent toxins, is of high importance in food microbiology. Thus, we investigated the use of a machine learning approach, based on artificial neural network (ANN) assisted Fourier transform infrared (FTIR) spectroscopy, for discrimination of B. cereus group members. The deep learning tool box of Matlab was employed to construct a one-level ANN, allowing the discrimination of the aforementioned B. cereus group members. This model resulted in 100% correct identification for the training set and 99.5% correct identification overall. The established ANN was applied to investigate the composition of B. cereus group members in soil, as a natural habitat of B. cereus, and in food samples originating from foodborne outbreaks. These analyses revealed a high complexity of B. cereus group populations, not only in soil samples but also in the samples from the foodborne outbreaks, highlighting the importance of taking multiple isolates from samples implicated in food poisonings. Notable, in contrast to the soil samples, no bacteria belonging to the psychrotolerant B. cereus group members were detected in the food samples linked to foodborne outbreaks, while the overall abundancy of B. thuringiensis did not significantly differ between the sample categories. None of the isolates was classified as B. cytotoxicus, fostering the hypothesis that the latter species is linked to very specific ecological niches. Overall, our work shows that machine learning assisted (FTIR) spectroscopy is suitable for identification of B. cereus group members in routine diagnostics and outbreak investigations. In addition, it is a promising tool to explore the natural habitats of B. cereus group, such as soil.

Identification of microorganisms by Fourier-transform infrared spectroscopy

The need for novel techniques of rapid identification of pathogenic microorganisms arises from the massive spread of drug-resistant nosocomial strains and the emergence of centers for biohazard control. Fourier-transform infrared spectroscopy is a promising alternative to mass spectrometry as it is cost-effective, fast and suitable for field use. The aim of this work was to propose an algorithm for the identification of microorganisms in pure cultures based on the analysis of their Fourier transform infrared spectra. The algorithm is based on the automated principal component analysis of infrared spectra. Unlike its analogues described in the literature, the algorithm is capable of identifying bacteria regardless of the culture medium or growth phase. The training sample included the most prevalent causative agents of infections and sepsis in humans: Staphylococcus aureus (n = 67), Enterococcus faecalis (n = 10), Enterococcus faecium (n = 10), Klebsiella pneumoniae (n = 10), Escherichia coli (n = 10), Serratia marcescens (n = 10), Enterobacter cloacae (n = 10), Acinetobacter baumannii (n = 10), Pseudomonas aeruginosa (n = 10), and Candida albicans (n = 10). The model we built successfully passed a series of blind tests involving clinical isolates of 10 methicillin-resistant (MRSA) and 10 methicillin-sensitive (MSSA) Staphylococcus aureus strains as well as pair mixes of these cultures with clinical isolates of Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumoniae.

Rapid characterisation of Klebsiella oxytoca isolates from contaminated liquid hand soap using mass spectrometry, FTIR and Raman spectroscopy

Microbiological monitoring of consumer products and the efficiency of early warning systems and outbreak investigations depend on the rapid identification and strain characterisation of pathogens posing risks to the health and safety of consumers. This study evaluates the potential of three rapid analytical techniques for identification and subtyping of bacterial isolates obtained from a liquid hand soap product, which has been recalled and reported through the EU RAPEX system due to its severe bacterial contamination. Ten isolates recovered from two bottles of the product were identified as Klebsiella oxytoca and subtyped using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI TOF MS), near-infrared Fourier transform (NIR FT) Raman spectroscopy and Fourier transform infrared (FTIR) spectroscopy. Comparison of the classification results obtained by these phenotype-based techniques with outcomes of the DNA-based methods pulsed-field gel electrophoresis (PFGE), multi-locus sequence typing (MLST) and single nucleotide polymorphism (SNP) analysis of whole-genome sequencing (WGS) data revealed a high level of concordance. In conclusion, a set of analytical techniques might be useful for rapid, reliable and cost-effective microbial typing to ensure safe consumer products and allow source tracking.

A Critical Review on Ultrasensitive, Spectroscopic-based Methods for High-throughput Monitoring of Bacteria during Infection Treatment

The world is in the midst of a pre-emptive public health emergency, one that is just as dramatic as the global aggressive viruses-related crises (Ebola, Zika, or SARS), but not as visible. The "superbugs" and their antimicrobial resistance do not cause much public alarm or awareness, but provoke financial losses of $100 trillion annually (WHO, http://www.who.int/mediacentre/commentaries/superbugs-action-now/en/ ). This status quo review offers an overview of ultrasensitive methods for high-throughput monitoring of bacteria during infection treatment, the effects of antibiotics on bacteria at single-cell level and the challenges we will face in their detection due to the extraordinary capability of these "superbugs" to gain and constantly improve multiresistance to antibiotics. A special emphasis is put on the ultrasensitive spectroscopic-based analysis techniques, using nanotechnology or not necessarily, that are more and more promising alternatives to conventional culture-based ones. The particular case of Mycobacteria detection is discussed based on recent reported work.

High-resolution subtyping of Staphylococcus aureus strains by means of Fourier-transform infrared spectroscopy

Staphylococcus aureus causes a variety of serious illnesses in humans and animals. Subtyping of S. aureus isolates plays a crucial role in epidemiological investigations. Metabolic fingerprinting by Fourier-transform infrared (FTIR) spectroscopy is commonly used to identify microbes at species as well as subspecies level. In this study, we aimed to assess the suitability of FTIR spectroscopy as a tool for S. aureus subtyping. To this end, we compared the subtyping performance of FTIR spectroscopy to other subtyping methods such as pulsed field gel electrophoresis (PFGE) and spa typing in a blinded experimental setup and investigated the ability of FTIR spectroscopy for identifying S. aureus clonal complexes (CC). A total of 70 S. aureus strains from human, animal, and food sources were selected, for which clonal complexes and a unique virulence and resistance gene pattern had been determined by DNA microarray analysis. FTIR spectral analysis resulted in high discriminatory power similar as obtained by spa typing and PFGE. High directional concordance was found between FTIR spectroscopy based subtypes and capsular polysaccharide expression detected by FTIR spectroscopy and the cap specific locus, reflecting strain specific expression of capsular polysaccharides and/or other surface glycopolymers, such as wall teichoic acid, peptidoglycane, and lipoteichoic acid. Supervised chemometrics showed only limited possibilities for differentiation of S. aureus CC by FTIR spectroscopy with the exception of CC45 and CC705. In conclusion, FTIR spectroscopy represents a valuable tool for S. aureus subtyping, which complements current molecular and proteomic strain typing.

Diversity of yeast strains of the genus Hanseniaspora in the winery environment: What is their involvement in grape must fermentation?

Isolated yeast populations of Chardonnay grape must during spontaneous fermentation were compared to those isolated on grape berries and in a winery environment before the arrival of the harvest (air, floor, winery equipment) and in the air through time. Two genera of yeast, Hanseniaspora and Saccharomyces, were isolated in grape must and in the winery environment before the arrival of the harvest but not on grape berries. The genus Hanseniaspora represented 27% of isolates in the must and 35% of isolates in the winery environment. The isolates of these two species were discriminated at the strain level by Fourier transform infrared spectroscopy. The diversity of these strains observed in the winery environment (26 strains) and in must (12 strains) was considerable. 58% of the yeasts of the genus Hanseniaspora isolated in the must corresponded to strains present in the winery before the arrival of the harvest. Although the proportion and number of strains of the genus Hanseniaspora decreased during fermentation, some strains, all from the winery environment, subsisted up to 5% ethanol content. This is the first time that the implantation in grape must of populations present in the winery environment has been demonstrated for a non-Saccharomyces genus.

Identification and differentiation of food-related bacteria: A comparison of FTIR spectroscopy and MALDI-TOF mass spectrometry

The food industry requires easy, accurate, and cost-effective techniques for microbial identification to ensure safe products and identify microbial contaminations. In this work, FTIR spectroscopy and MALDI-TOF mass spectrometry were assessed for their suitability and applicability for routine microbial diagnostics of food-related microorganisms by analyzing their robustness according to changes in incubation time and medium, identification accuracy and their ability to differentiate isolates down to the strain level. Changes in the protocol lead to a significantly impaired performance of FTIR spectroscopy, whereas they had only little effects on MALDI-TOF MS. Identification accuracy was tested using 174 food-related bacteria (93 species) from an in-house strain collection and 40 fresh isolates from routine food analyses. For MALDI-TOF MS, weaknesses in the identification of bacilli and pseudomonads were observed; FTIR spectroscopy had most difficulties in identifying pseudomonads and enterobacteria. In general, MALDI-TOF MS obtained better results (52-85% correct at species level), since the analysis of mainly ribosomal proteins is more robust and seems to be more reliable. FTIR spectroscopy suffers from the fact that it generates a whole-cell fingerprint and intraspecies diversity may lead to overlapping species borders which complicates identification. In the present study values between 56% and 67% correct species identification were obtained. On the opposite, this high sensitivity offers the opportunity of typing below the species level which was not possible using MALDI-TOF MS. Using fresh isolates from routine diagnostics, both techniques performed well with 88% (MALDI-TOF) and 75% (FTIR) correct identifications at species level, respectively.

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

Fourier transform infrared (FTIR) spectroscopy was introduced in 1991 as a technique to identify and classify microbes. Since then, it has gained growing interest and has undergone a remarkable evolution. Highly sophisticated spectrometers have been developed, enabling a high sample throughput. Today, the generation of high-quality data in a short time and the application of the technique for rapid and reliable identification of microbes to the species level are well documented. What makes FTIR spectroscopy even more attractive is the fact that spectral information can also be exploited for strain typing purposes, which is particularly important for epidemiological analyses and some technological applications. Accordingly, in recent years, FTIR spectroscopy has been increasingly used for typing and classifying microorganisms below the species level. The intention of this review is to give an overview over current knowledge and strategies of using FTIR spectroscopy for species identification and to describe different approaches for strain typing.

Infrared spectral changes identified during different stages of herpes viruses infection in vitro

Microscopic Fourier transform infrared spectroscopy (FTIR) which is based on the characteristic molecular vibrational spectra of cells was previously applied for the identification of various biological samples. In the present study, FTIR spectroscopy was used for the characterization of different stages during the development of herpes viruses infection. Vero cells in culture were infected with high and low doses of different herpes viruses [herpes simplex virus types 1 and 2 (HSV-1, -2) or varicella-zoster virus (VZV)], and cellular changes were observed by optical and electron microscopy and analyzed by FTIR microscopy at different periods of time post-infection. Specific different spectral changes were observed at various stages of the viral infection development. The spectral intensity in the 1220-1260 cm(-1) region (mainly attributed to phosphate levels) was considerably increased in all infected cells compared to normal uninfected cells during the early stages of the viral infection development. However, at the late stages of the viral infection development (when all the cells in the infected culture lost their spindle shape and became circular) the spectral intensities in this region significantly decreased in the infected compared to the control cells. In addition, the peak at 1023 cm(-1), attributed to carbohydrates, almost fully disappeared at early stages of the viral infection development, whereas at late stages of the infection it raised to an equivalent or higher level than that of the uninfected control cells. These results support the potential of developing FTIR microspectroscopy as a simple, reagent free method for the early detection and accurate differentiation of different stages during the development of herpes virus infection.

Influence of cell geometry and number of replicas in the reproducibility of whole cell FTIR analysis

Fourier Transform InfraRed (FTIR) spectroscopy is an increasingly used technique in biology, especially for whole cell metabolomic fingerprint. The reproducibility of this technique is influenced by a large number of factors such as the physiological state of cells, sample manipulation and growth conditions. Evidence exists suggesting that the cell shape and dimension can be further elements to consider in whole cell FTIR analysis. In this study we aimed to address the effect of cell geometry on the FTIR spectra and to define the extent of variability occurring between machine and biological replicas with a standardized protocol. The yeast species Saccharomyces cerevisiae (large oval-shaped cells) and Debaryomyces hansenii (small round shaped cells) were employed for their different morphology. Thirty machine replicas of each were analyzed separately and after averaging in groups of three, showing a three to four-fold reduction of the variability. Similarly, a two-fold reduction of variability was observed when thirty biological replicas of the two yeast species were analyzed. The optimal number of replicas to average was then estimated with a bootstrap-like procedure in which biological and machine replicas were randomly resampled 2000 times and averaged in groups spanning from 2 to 12 replicas. This simulation has shown that little if any advantage can be obtained by increasing the number of replicas over five and that the variability exhibited by the small regular cells of D. hansenii was always roughly half of that displayed by the large S. cerevisiae cells, confirming the results obtained with standard non-bootstrapped averages.

The infrared spectra of Bacillus bacteria part I: vegetative Bacillus versus sporulated cells and the contributions of phospholipids to vegetative infrared spectra

This paper highlights the distinctions between the infrared (IR) absorption spectra of vegetative versus sporulated Bacillus bacteria. It is observed that there are unique signatures clearly associated with either the sporulated or vegetative state and that vegetative cells (or cell debris) can contribute to the spore spectra. A distinct feature at approximately 1739 cm(-1) appears to be unique to vegetative cell spectra and can also be used as an indicator of vegetative cells or cell debris in the spore spectra. The data indicate that the band arises from a lipid-soluble species such as an ester or phospholipid carbonyl bond and are consistent with it being either phosphatidyl glycerol (PG) or phosphatidylethanolamine (PE), two major classes of phospholipids found in vegetative cells of Bacillus species. A companion work discusses bands associated with the sporulated state.

Classification of select category A and B bacteria by Fourier transform infrared spectroscopy

Fourier transform infrared (FT-IR) spectroscopy historically is a powerful tool for the taxonomic classification of bacteria by genus, species, and strain when they are grown under carefully controlled conditions. Relatively few reports have investigated the determination and classification of pathogens such as the National Institute of Allergy and Infectious Diseases (NIAID) Category A Bacillus anthracis spores and cells (BA), Yersinia species, Francisella tularensis (FT), and Category B Brucella species from FT-IR spectra. We investigated the multivariate statistics classification ability of the FT-IR spectra of viable pathogenic and non-pathogenic NIAID Category A and B bacteria. The impact of different growth media, growth time and temperature, rolling circle filter of the data, and wavelength range were investigated for their microorganism differentiation capability. Viability of the bacteria was confirmed by agar plate growth after the FT-IR experimental procedures were performed. Principal component analysis (PCA) was reduced to maps of two PC vectors in order to distill the FT-IR spectral features into manageable, visual presentations. The PCA results of the strains of BA, FT, Brucella, and Yersinia spectra from conditions of varying growth media and culture time were readily separable in two-dimensional (2D) PC plots. FT spectra were separated from those of the three other genera. The BA pathogenic spore strains 1029, LA1, and Ames were clearly differentiated from the rest of the dataset. Yersinia rhodei, Y. enterocolitica, and Y. pestis species were distinctly separated from the remaining dataset and could also be classified by growth media. Different growth media produced distinct subsets in the FT, BA, and Yersinia spp. regions in the 2D PC plots. Various 2D PC plots provided differential degrees of separation with respect to the four viable bacterial genera including the BA sub-categories of pathogenic spores, vegetative cells, and nonpathogenic vegetative cells. This work provided evidence that FT-IR spectroscopy can indeed separate the four major pathogenic bacterial genera of NIAID Category A and B biological threat agents including details according to the growth conditions and statistical parameters.

Rapid identification of mycobacteria by Raman spectroscopy

A number of rapid identification methods have been developed to improve the accuracy for diagnosis of tuberculosis and to speed up the presumptive identification of Mycobacterium species. Most of these methods have been validated for a limited group of microorganisms only. Here, Raman spectroscopy was compared to 16S rRNA sequencing for the identification of Mycobacterium tuberculosis complex strains and the most frequently found strains of nontuberculous mycobacteria (NTM). A total of 63 strains, belonging to eight distinct species, were analyzed. The sensitivity of Raman spectroscopy for the identification of Mycobacterium species was 95.2%. All M. tuberculosis strains were correctly identified (7 of 7; 100%), as were 54 of 57 NTM strains (94%). The differentiation between M. tuberculosis and NTM was invariably correct for all strains. Moreover, the reproducibility of Raman spectroscopy was evaluated for killed mycobacteria (by heat and formalin) versus viable mycobacteria. The spectra of the heat-inactivated bacteria showed minimal differences compared to the spectra of viable mycobacteria. Therefore, the identification of mycobacteria appears possible without biosafety level 3 precautions. Raman spectroscopy provides a novel answer to the need for rapid species identification of cultured mycobacteria in a clinical diagnostic setting.

Rapid diagnostic testing for mycobacterial infections

Tests based on nucleic acid amplification can rapidly detect mycobacteria in clinical samples. These appear to be promising and may change how mycobacterial diseases are diagnosed in the future. Utilization of nucleic acid hybridization and DNA sequencing has enabled the identification of mycobacteria to the species level and detection of mutations associated with antimicrobial resistance. Combining nucleic acid amplification with genotypic identification methods allows detection and identification of mycobacteria directly in clinical samples and, to a limited extent, detection of antimicrobial resistance. IFN-gamma-based assays provide results faster than the tuberculin skin test and address many of its shortcomings, and are thus poised to replace the latter in the coming years.