The rapid identification of Acinetobacter species using Fourier transform infrared spectroscopy

Rapid classification of heavy metal-exposed freshwater bacteria by infrared spectroscopy coupled with chemometrics using supervised method

Rapid, cost-effective, sensitive and accurate methodologies to classify bacteria are still in the process of development. The major drawbacks of standard microbiological, molecular and immunological techniques call for the possible usage of infrared (IR) spectroscopy based supervised chemometric techniques. Previous applications of IR based chemometric methods have demonstrated outstanding findings in the classification of bacteria. Therefore, we have exploited an IR spectroscopy based chemometrics using supervised method namely Soft Independent Modeling of Class Analogy (SIMCA) technique for the first time to classify heavy metal-exposed bacteria to be used in the selection of suitable bacteria to evaluate their potential for environmental cleanup applications. Herein, we present the powerful differentiation and classification of laboratory strains (Escherichia coli and Staphylococcus aureus) and environmental isolates (Gordonia sp. and Microbacterium oxydans) of bacteria exposed to growth inhibitory concentrations of silver (Ag), cadmium (Cd) and lead (Pb). Our results demonstrated that SIMCA was able to differentiate all heavy metal-exposed and control groups from each other with 95% confidence level. Correct identification of randomly chosen test samples in their corresponding groups and high model distances between the classes were also achieved. We report, for the first time, the success of IR spectroscopy coupled with supervised chemometric technique SIMCA in classification of different bacteria under a given treatment.

High-throughput metabolic screening of microalgae genetic variation in response to nutrient limitation

Microalgae produce metabolites that could be useful for applications in food, biofuel or fine chemical production. The identification and development of suitable strains require analytical methods that are accurate and allow rapid screening of strains or cultivation conditions. We demonstrate the use of Fourier transform infrared (FT-IR) spectroscopy to screen mutant strains of Chlamydomonas reinhardtii. These mutants have knockdowns for one or more nutrient starvation response genes, namely PSR1, SNRK2.1 and SNRK2.2. Limitation of nutrients including nitrogen and phosphorus can induce metabolic changes in microalgae, including the accumulation of glycerolipids and starch. By performing multivariate statistical analysis of FT-IR spectra, metabolic variation between different nutrient limitation and non-stressed conditions could be differentiated. A number of mutant strains with similar genetic backgrounds could be distinguished from wild type when grown under specific nutrient limited and replete conditions, demonstrating the sensitivity of FT-IR spectroscopy to detect specific genetic traits. Changes in lipid and carbohydrate between strains and specific nutrient stress treatments were validated by other analytical methods, including liquid chromatography-mass spectrometry for lipidomics. These results demonstrate that the PSR1 gene is an important determinant of lipid and starch accumulation in response to phosphorus starvation but not nitrogen starvation. However, the SNRK2.1 and SNRK2.2 genes are not as important for determining the metabolic response to either nutrient stress. We conclude that FT-IR spectroscopy and chemometric approaches provide a robust method for microalgae screening.

Metabolic responses of eukaryotic microalgae to environmental stress limit the ability of FT-IR spectroscopy for species identification

Fourier Transform Infrared (FT-IR) spectroscopy is a robust method for macromolecular analysis and differentiation of microorganisms. However, most studies are performed in controlled conditions and it is unclear whether this tool is appropriate for the identification of eukaryotic microalgae species from variable environments. In order to address this, nine closely-related species of marine and freshwater microalgae were grown under controlled (non-stressed) and variable (non-stressed and stressed) conditions, including nutrient-stressed and wastewater-stressed conditions. Following optimization of data processing methods, FT-IR spectra from all species and conditions were compared. The substantial metabolic changes that were caused by nutrient starvation restricted the ability of FT-IR spectroscopy to differentiate the microalgal species grown under variable conditions efficiently. Comparison of unsupervised and supervised multivariate data analysis methods found that principal component-discriminant function analysis was able best to differentiate between some species under controlled conditions but still gave poor differentiation under variable environmental conditions.

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FT-IR spectroscopy can be used to generate metabolic fingerprints in algae.

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Metabolic fingerprinting has been proposed to differentiate species and strains.

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Algae exhibit high metabolic plasticity in response to environmental change.

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This restricts the use of FT-IR spectroscopy as a discriminatory tool.

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Discrimination is improved by multivariate statistical analysis techniques.

Profiling of spatial metabolite distributions in wheat leaves under normal and nitrate limiting conditions

The control and interaction between nitrogen and carbon assimilatory pathways is essential in both photosynthetic and non-photosynthetic tissue in order to support metabolic processes without compromising growth. Physiological differences between the basal and mature region of wheat (Triticum aestivum) primary leaves confirmed that there was a change from heterotrophic to autotrophic metabolism. Fourier Transform Infrared (FT-IR) spectroscopy confirmed the suitability and phenotypic reproducibility of the leaf growth conditions. Principal Component-Discriminant Function Analysis (PC-DFA) revealed distinct clustering between base, and tip sections of the developing wheat leaf, and from plants grown in the presence or absence of nitrate. Gas Chromatography-Time of Flight/Mass Spectrometry (GC-TOF/MS) combined with multivariate and univariate analyses, and Bayesian network (BN) analysis, distinguished different tissues and confirmed the physiological switch from high rates of respiration to photosynthesis along the leaf. The operation of nitrogen metabolism impacted on the levels and distribution of amino acids, organic acids and carbohydrates within the wheat leaf. In plants grown in the presence of nitrate there was reduced levels of a number of sugar metabolites in the leaf base and an increase in maltose levels, possibly reflecting an increase in starch turnover. The value of using this combined metabolomics analysis for further functional investigations in the future are discussed.

Acclimation of metabolism to light in Arabidopsis thaliana: the glucose 6-phosphate/phosphate translocator GPT2 directs metabolic acclimation

Mature leaves of plants transferred from low to high light typically increase their photosynthetic capacity. In Arabidopsis thaliana, this dynamic acclimation requires expression of GPT2, a glucose 6-phosphate/phosphate translocator. Here, we examine the impact of GPT2 on leaf metabolism and photosynthesis. Plants of wild type and of a GPT2 knockout (gpt2.2) grown under low light achieved the same photosynthetic rate despite having different metabolic and transcriptomic strategies. Immediately upon transfer to high light, gpt2.2 plants showed a higher rate of photosynthesis than wild-type plants (35%); however, over subsequent days, wild-type plants acclimated photosynthetic capacity, increasing the photosynthesis rate by 100% after 7 d. Wild-type plants accumulated more starch than gpt2.2 plants throughout acclimation. We suggest that GPT2 activity results in the net import of glucose 6-phosphate from cytosol to chloroplast, increasing starch synthesis. There was clear acclimation of metabolism, with short-term changes typically being reversed as plants acclimated. Distinct responses to light were observed in wild-type and gpt2.2 leaves. Significantly higher levels of sugar phosphates were observed in gpt2.2. We suggest that GPT2 alters the distribution of metabolites between compartments and that this plays an essential role in allowing the cell to interpret environmental signals.

Rapid differentiation of Listeria monocytogenes epidemic clones III and IV and their intact compared with heat-killed populations using Fourier transform infrared spectroscopy and chemometrics

The objectives of this study were to determine if Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis (chemometrics) could be used to rapidly differentiate epidemic clones (ECs) of Listeria monocytogenes, as well as their intact compared with heat-killed populations. FT-IR spectra were collected from dried thin smears on infrared slides prepared from aliquots of 10 μL of each L. monocytogenes ECs (ECIII: J1-101 and R2-499; ECIV: J1-129 and J1-220), and also from intact and heat-killed cell populations of each EC strain using 250 scans at a resolution of 4 cm(-1) in the mid-infrared region in a reflectance mode. Chemometric analysis of spectra involved the application of the multivariate discriminant method for canonical variate analysis (CVA) and linear discriminant analysis (LDA). CVA of the spectra in the wavelength region 4000 to 600 cm(-1) separated the EC strains while LDA resulted in a 100% accurate classification of all spectra in the data set. Further, CVA separated intact and heat-killed cells of each EC strain and there was 100% accuracy in the classification of all spectra when LDA was applied. FT-IR spectral wavenumbers 1650 to 1390 cm(-1) were used to separate heat-killed and intact populations of L. monocytogenes. The FT-IR spectroscopy method allowed discrimination between strains that belong to the same EC. FT-IR is a highly discriminatory and reproducible method that can be used for the rapid subtyping of L. monocytogenes, as well as for the detection of live compared with dead populations of the organism.

PRACTICAL APPLICATION

Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis can be used for L. monocytogenes source tracking and for clinical case isolate comparison during epidemiological investigations since the method is capable of differentiating epidemic clones and it uses a library of well-characterized strains. The FT-IR method is potentially less expensive and more rapid compared to genetic subtyping methods, and can be used for L. monocytogenes strain typing by food industries and public health agencies to enable faster response and intervention to listeriosis outbreaks. FT-IR can also be applied for routine monitoring of the pathogen in food processing plants and for investigating postprocessing contamination because it is capable of differentiating heat-killed and viable L. monocytogenes populations.

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.

Vibrational spectroscopy: a tool being developed for the noninvasive monitoring of wound healing

Wound care and management accounted for over 1.8 million hospital discharges in 2009. The complex nature of wound physiology involves hundreds of overlapping processes that we have only begun to understand over the past three decades. The management of wounds remains a significant challenge for inexperienced clinicians. The ensuing inflammatory response ultimately dictates the pace of wound healing and tissue regeneration. Consequently, the eventual timing of wound closure or definitive coverage is often subjective. Some wounds fail to close, or dehisce, despite the use and application of novel wound-specific treatment modalities. An understanding of the molecular environment of acute and chronic wounds throughout the wound-healing process can provide valuable insight into the mechanisms associated with the patient's outcome. Pathologic alterations of wounds are accompanied by fundamental changes in the molecular environment that can be analyzed by vibrational spectroscopy. Vibrational spectroscopy, specifically Raman and Fourier transform infrared spectroscopy, offers the capability to accurately detect and identify the various molecules that compose the extracellular matrix during wound healing in their native state. The identified changes might provide the objective markers of wound healing, which can then be integrated with clinical characteristics to guide the management of wounds.

Fourier transform infrared spectroscopy as a metabolite fingerprinting tool for monitoring the phenotypic changes in complex bacterial communities capable of degrading phenol

The coking process produces great volumes of wastewater contaminated with pollutants such as cyanides, sulfides and phenolics. Chemical and physical remediation of this wastewater removes the majority of these pollutants; however, these processes do not remove phenol and thiocyanate. The removal of these compounds has been effected during bioremediation with activated sludge containing a complex microbial community. In this investigation we acquired activated sludge from an industrial bioreactor capable of degrading phenol. The sludge was incubated in our laboratory and monitored for its ability to degrade phenol over a 48 h period. Multiple samples were taken across the time-course and analysed by Fourier transform infrared (FT-IR) spectroscopy. FT-IR was used as a whole-organism fingerprinting approach to monitor biochemical changes in the bacterial cells during the degradation of phenol. We also investigated the ability of the activated sludge to degrade phenol following extended periods (2-131 days) of storage in the absence of phenol. A reduction was observed in the ability of the microbial community to degrade phenol and this was accompanied by a detectable biochemical change in the FT-IR fingerprint related to cellular phenotype of the microbial community. In the absence of phenol a decrease in thiocyanate vibrations was observed, reflecting the ability of these communities to degrade this substrate. Actively degrading communities showed an additional new band in their FT-IR spectra that could be attributed to phenol degradation products from the ortho- and meta-cleavage of the aromatic ring. This study demonstrates that FT-IR spectroscopy when combined with chemometric analysis is a very powerful high throughput screening approach for assessing the metabolic capability of complex microbial communities.

Changes in ultrastructure and Fourier transform infrared spectrum of Salmonella enterica serovar typhimurium cells after exposure to stress conditions

The effect of exposure to acid (pH 2.5), alkaline (pH 11.0), heat (55°C), and oxidative (40 mM H₂O₂) lethal conditions on the ultrastructure and global chemical composition of Salmonella enterica serovar Typhimurium CECT 443 cells was studied using transmission electron microscopy and Fourier transform infrared spectroscopy (FT-IR) combined with multivariate statistical methods (hierarchical cluster analysis and factor analysis). Infrared spectra exhibited marked differences in the five spectral regions for all conditions tested compared to those of nontreated control cells, which suggests the existence of a complex bacterial stress response in which modifications in a wide variety of cellular compounds are involved. The visible spectral changes observed in all of the spectral regions, together with ultrastructural changes observed by transmission electron microscopy and data obtained from membrane integrity tests, indicate the existence of membrane damage or alterations in membrane composition after heat, acid, alkaline, and oxidative treatments. Results obtained in this study indicate the potential of FT-IR spectroscopy to discriminate between intact and injured bacterial cells and between treatment technologies, and they show the adequacy of this technique to study the molecular aspects of bacterial stress response.

Rapid monitoring of recombinant antibody production by mammalian cell cultures using fourier transform infrared spectroscopy and chemometrics

Fourier transform infrared (FT-IR) spectroscopy combined with multivariate statistical analyses was investigated as a physicochemical tool for monitoring secreted recombinant antibody production in cultures of Chinese hamster ovary (CHO) and murine myeloma non-secreting 0 (NS0) cell lines. Medium samples were taken during culture of CHO and NS0 cells lines, which included both antibody-producing and non-producing cell lines, and analyzed by FT-IR spectroscopy. Principal components analysis (PCA) alone, and combined with discriminant function analysis (PC-DFA), were applied to normalized FT-IR spectroscopy datasets and showed a linear trend with respect to recombinant protein production. Loadings plots of the most significant spectral components showed a decrease in the C-O stretch from polysaccharides and an increase in the amide I band during culture, respectively, indicating a decrease in sugar concentration and an increase in protein concentration in the medium. Partial least squares regression (PLSR) analysis was used to predict antibody titers, and these regression models were able to predict antibody titers accurately with low error when compared to ELISA data. PLSR was also able to predict glucose and lactate amounts in the medium samples accurately. This work demonstrates that FT-IR spectroscopy has great potential as a tool for monitoring cell cultures for recombinant protein production and offers a starting point for the application of spectroscopic techniques for the on-line measurement of antibody production in industrial scale bioreactors.

Monitoring the effects of chiral pharmaceuticals on aquatic microorganisms by metabolic fingerprinting

The effects of the chiral pharmaceuticals atenolol and propranolol on Pseudomonas putida, Pseudomonas aeruginosa, Micrococcus luteus, and Blastomonas natatoria were investigated. The growth dynamics of exposed cultures were monitored using a Bioscreen instrument. In addition, Fourier-transform infrared (FT-IR) spectroscopy with appropriate chemometrics and high-performance liquid chromatography (HPLC) were employed in order to investigate the phenotypic changes and possible degradation of the drugs in exposed cultures. For the majority of the bacteria studied there was not a statistically significant difference in the organism's phenotype when it was exposed to the different enantiomers or mixtures of enantiomers. In contrast, the pseudomonads appeared to respond differently to propranolol, and the two enantiomers had different effects on the cellular phenotype. This implies that there were different metabolic responses in the organisms when they were exposed to the different enantiomers. We suggest that our findings may indicate that there are widespread effects on aquatic communities in which active pharmaceutical ingredients are present.

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.

Rapid identification of coagulase-negative staphylococci by Fourier transform infrared spectroscopy

Coagulase-negative staphylococci (CNS), frequently associated with both community-acquired and nosocomial bloodstream infections, must be distinguished from Staphylococcus aureus for clinical purposes. Conventional methods are too laborious and time-consuming and often lack sensitivity to CNS. Fourier transform infrared (FTIR) spectroscopy combined with the use of a universal growth medium (Que-Bact Universal Medium No. 2) and chemometrics was evaluated for its potential as a rapid and simple clinical tool for making this distinction. FTIR spectra of 11 methicillin-sensitive and 11 methicillin-resistant CNS isolates as well as 25 methicillin-sensitive, 47 methicillin-resistant, 34 borderline oxacillin-resistant and 35 glycopeptide intermediate S. aureus isolates were obtained from dried films of stationary-phase cells grown on the universal medium. Principal component analysis (PCA), self-organizing maps, and the K-nearest neighbor algorithm were employed to cluster the different phenotypes based on similarity of their FTIR spectra. PCA of the first-derivative normalized spectral data from a single narrow region (2888-2868 cm(-1)) yielded complete differentiation of CNS from both methicillin-sensitive and methicillin-resistant S. aureus. The rate of correct classification was somewhat reduced, from 100% to 90%, after inclusion of borderline oxacillin-resistant and glycopeptide intermediate S. aureus strains in the data set. Differentiation based on the data in broader spectral regions was much less reliable. The results of this study indicate that with proper spectral region selection, FTIR spectroscopy and cluster analysis may provide a simple and accurate means of CNS species identification.

Epidemiological typing of methicillin-resistant Staphylococcus aureus strains by Fourier transform infrared spectroscopy

A rapid and simple typing system is needed for controlling the spread of epidemic methicillin-resistant Staphylococcus aureus (MRSA), currently one of the most widespread multi-resistant nosocomial pathogens in Canadian hospitals. Fourier transform infrared (FTIR) spectroscopy was used to subtype 85 isolates representing five strains of epidemic Canadian MRSA (CMRSA). Spectral fingerprints of whole cells grown on Que-Bact(R) Universal Medium No. 2 were transformed to first derivative peak-height normalized files and examined visually and by singular-value decomposition (SVD). Distinguishing spectral regions were processed by principal component analysis (PCA), self-organizing map and K-nearest neighbor supervised cluster analysis. Among the visually identified regions, 1070-1050 and 1155-1137 cm(-1) were found suitable for discrimination of CMRSA-4 and CMRSA-2 respectively, while CMRSA-1, CMRSA-3, and CMRSA-5 each exhibited distinctive spectral profiles in the 1123-1094 cm(-1) region. The combination, 1123-1094, 1174-1154 and 2904-2864 cm(-1) separated the five CMRSA with 84.6% correct classification by PCA. Five clusters were also obtained using the SVD-selected regions 1096-1066, 1118-1090 and 2914-2880 cm(-1), with 87.8% correct classification based on visual examination of the PCA scores plot and 97% based on supervised cluster analysis. These results demonstrate that FTIR spectroscopy has considerable potential as a rapid (1-hour) and simple method for MRSA strain typing and monitoring in clinical settings.

Fourier transform infrared (FT-IR) spectroscopy in bacteriology: towards a reference method for bacteria discrimination

Rapid and reliable discrimination among clinically relevant pathogenic organisms is a crucial task in microbiology. Microorganism resistance to antimicrobial agents increases prevalence of infections. The possibility of Fourier transform infrared (FT-IR) spectroscopy to assess the overall molecular composition of microbial cells in a non-destructive manner is reflected in the specific spectral fingerprints highly typical for different microorganisms. With the objective of using FT-IR spectroscopy for discrimination between diverse microbial species and strains on a routine basis, a wide range of chemometrics techniques need to be applied. Still a major issue in using FT-IR for successful bacteria characterization is the method for spectra pre-processing. We analyzed different spectra pre-processing methods and their impact on the reduction of spectral variability and on the increase of robustness of chemometrics models. Different types of the Enterococcus faecium bacterial strain were classified according to chromosomal DNA restriction patterns produced by pulsed-field gel electrophoresis (PFGE). Samples were collected from human patients. Collected FT-IR spectra were used to verify if the same classification was obtained. In order to further optimize bacteria classification we investigated whether a selected combination of the most discriminative spectral regions could improve results. Two different variable selection methods (genetic algorithms (GAs) and bootstrapping) were investigated and their relative merit for bacteria classification is reported by comparing with results obtained using the entire spectra. Discriminant partial least-squares (Di-PLS) models based on corrected spectra showed improved predictive ability up to 40% when compared to equivalent models using the entire spectral range. The uncertainty in estimating scores was reduced by about 50% when compared to models with all wavelengths. Spectral ranges with relevant chemical information for Enterococcus faecium bacteria discrimination were outlined.

Metabolic fingerprints of Mycobacterium bovis cluster with molecular type: implications for genotype-phenotype links

Mycobacterium bovis is the causative agent of bovine tuberculosis. Various genetic typing techniques have been used to trace the reservoirs of infection; however, they have limited success in population genetics and outbreak studies. Fourier-transform infrared spectroscopy (FT-IR) is a rapid phenotypic typing technique, which may be used to generate a metabolic fingerprinting and is increasingly used to characterize bacteria. When coupled with multivariate cluster analysis, this powerful combination has sufficient resolving power to discriminate bacteria down to subspecies level; however, to date this method has not been used in the differentiation of mycobacteria. Multiple isolates of the ten major spoligotypes in the UK, recovered from different geographical locations, were analysed using FT-IR. Hierarchical cluster analysis of the spectra showed that the isolates could be differentiated according to their spoligotypes. Six of the spoligotype FT-IR clusters were very homogeneous and all isolates were recovered together. However, the remaining four groups displayed a more heterogeneous phenotype, which may reflect greater variation than previously suspected within these groups. Included in the ten spoligotypes are the two most dominant isolates in the UK, designated types 9 and 17. Whilst type 17 showed a highly conserved phenotype as judged by FT-IR, type 9 showed a very heterogeneous metabolic profile and isolates were recovered throughout the dendrogram. This variation in type 9 is reflected in the high degree of diversity observed by variable number tandem repeats (VNTR) analysis, underlining the exquisite resolving power of FT-IR.

Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy

The ability to diagnose the early onset of disease, rapidly, non-invasively and unequivocally has multiple benefits. These include the early intervention of therapeutic strategies leading to a reduction in morbidity and mortality, and the releasing of economic resources within overburdened health care systems. Some of the routine clinical tests currently in use are known to be unsuitable or unreliable. In addition, these often rely on single disease markers which are inappropriate when multiple factors are involved. Many diseases are a result of metabolic disorders, therefore it is logical to measure metabolism directly. One of the strategies employed by the emergent science of metabolomics is metabolic fingerprinting; which involves rapid, high-throughput global analysis to discriminate between samples of different biological status or origin. This review focuses on a selective number of recent studies where metabolic fingerprinting has been forwarded as a potential tool for disease diagnosis using infrared and Raman spectroscopies.

Discrimination of enterobacterial repetitive intergenic consensus PCR types of Campylobacter coli and Campylobacter jejuni by Fourier transform infrared spectroscopy

Fourier transform infrared spectroscopy (FT-IR) has been used together with pattern recognition methodology to study isolates belonging to the species Campylobacter coli and Campylobacter jejuni and to compare FT-IR typing schemes with established genomic profiles based on enterobacterial repetitive intergenic consensus PCR (ERIC-PCR). Seventeen isolates were cultivated under standardized conditions for 2, 3, and 4 days to study variability and improve reproducibility. ERIC-PCR profiles and FT-IR spectra were obtained from strains belonging to the species Campylobacter coli and C. jejuni, normalized, and explored by hierarchical clustering and stepwise discriminant analysis. Strains could be differentiated by using mainly the first-derivative FT-IR spectral range, 1,200 to 900 cm(-1) (described as the carbohydrate region). The reproducibility index varied depending on the ages of the cultures and on the spectral ranges investigated. Classification obtained by FT-IR spectroscopy provided valuable taxonomic information and was mostly in agreement with data from the genotypic method, ERIC-PCR. The classification functions obtained from the discriminant analysis allowed the identification of 98.72% of isolates from the validation set. FT-IR can serve as a valuable tool in the classification, identification, and typing of thermophilic Campylobacter isolates, and a number of types can be differentiated by means of FT-IR spectroscopy.

Rapid identification of Candida species by FT-IR microspectroscopy

Due to the continuous increase of human candidiasis and the great diversity of yeasts of the Candida genera, it is indispensable to identify this yeast as early as possible. Early identification enables an early diagnostic and patient-adapted anti-fungal therapy, thus reducing morbidity and mortality related to these infections. In view of this, we have in this study investigated microcolonies using a method based on Fourier transform-infrared microspectroscopy (FTIRM) for a rapid and early identification of the most frequent Candida species encountered in human pathology. FTIR spectroscopy is a whole-cell "fingerprinting" method by which microorganisms can be identified. By exploiting the huge discriminating capacity of this technique, we identified 6 species (Candida albicans, Candida glabrata, Candida parapsilosis, Candida tropicalis, Candida krusei, and Candida kefyr) from a collection of 57 clinical strains of Candida, isolated from hospitalised patients. Data obtained on 10- to 18-h-old microcolonies were compared to cultures of 24 h. Our results clearly show the efficiency and the robustness of FTIR (micro)spectroscopy in identifying species with a classification rate of 100% for both microcolonies and 24-h cultures. FTIR microspectroscopy is thus a promising clinical approach, because compared to conventional and molecular techniques, it is time and money saving, has great identification and discriminating potentials, and is amenable to an automated high-throughput routine system.

Methods for isolation and confirmation of Vibrio vulnificus from oysters and environmental sources: a review

The gram-negative bacterium Vibrio vulnificus is a natural inhabitant of estuarine waters and poses a significant health threat to humans who suffer from immune disorders, liver disease, or hemochromatosis (iron overload). V. vulnificus enters human hosts via wound infections or consumption of raw shellfish (primarily oysters), and infections frequently progress to septicemia and death in susceptible individuals. Prevalence in waters and shellfish is not correlated with fecal indicator organisms; therefore, species-specific detection and enumeration of V. vulnificus in the environment has become a priority for agencies that are responsible for shellfish safety. The many selective-differential media developed for isolation of Vibrio spp., and specifically for V. vulnificus detection, are reviewed here; however, none of the media developed to date combines the sensitivity to low numbers with the specificity necessary to inhibit growth of other organisms. Therefore, immunological and molecular protocols are needed for confirmation of the identity of the organism and are discussed in detail. Methods under development that hold promise for rapid, accurate, and sensitive detection and enumeration of the organism include multiplex and real-time PCR. Developing technologies that have proven useful for detection and investigation of other pathogens such as biosensors, spectroscopy and microarrays may provide the next generation of tools for investigation of the prevalence and ecology of V. vulnificus.

Differentiation of Micromonospora isolates from a coastal sediment in Wales on the basis of Fourier transform infrared spectroscopy, 16S rRNA sequence analysis, and the amplified fragment length polymorphism technique

A number of actinomycetes isolates were recovered from coastal sediments in Aberystwyth (Wales, United Kingdom) with standard isolation techniques. Most of them were putatively assigned to the genera Streptomyces and Micromonospora on the basis of their morphological characteristics, and there appeared to be no difference whether the isolation media contained distilled water or seawater. A group of 20 Micromonospora isolates was selected to undergo further polyphasic taxonomic investigation. Three approaches were used to analyze the diversity of these isolates, 16S rDNA sequencing, fluorescent amplified fragment length polymorphism (AFLP), and Fourier transform infrared spectroscopy (FT-IR). The 16S rDNA sequence analysis confirmed that all of these isolates should be classified to the genus Micromonospora, and they were analyzed with a group of other Micromonospora 16S rDNA sequences available from the Ribosomal Database Project. The relationships of the 20 isolates were observed after hierarchical clustering, and almost identical clusters were obtained with these three techniques. This has obvious implications for high-throughput screening for novel actinomycetes because FT-IR spectroscopy, which is a rapid and reliable whole-organism fingerprinting method, can be applied as a very useful dereplication tool to indicate which environmental isolates have been cultured previously.