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Royston Goodacre

Publications and source records attributed to Royston Goodacre.

At least 37 records · Page 2Linked to original sources
PubMed2004

Genetic algorithm optimization for pre-processing and variable selection of spectroscopic data.

MOTIVATION: The major difficulties relating to mathematical modelling of spectroscopic data are inconsistencies in spectral reproducibility and the black box nature of the modelling techniques. For the analysis of biological samples the first problem is due to biological, experimental and machine variability which can lead to sample size differences and unavoidable baseline shifts. Consequently, there is often a requirement for mathematical correction(s) to be made to the raw data if the best possible model is to be formed. The second problem prevents interpretation of the results since the variables that most contribute to the analysis are not easily revealed; as a result, the opportunity to obtain new knowledge from such data is lost. METHODS: We used genetic algorithms (GAs) to select spectral pre-processing steps for Fourier transform infrared (FT-IR) spectroscopic data. We demonstrate a novel approach for the selection of important discriminatory variables by GA from FT-IR spectra for multi-class identification by discriminant function analysis (DFA). RESULTS: The GA selects sensible pre-processing steps from a total of approximately 10(10) possible mathematical transformations. Application of these algorithms results in a 16% reduction in the model error when compared against the raw data model. GA-DFA recovers six variables from the full set of 882 spectral variables against which a satisfactory DFA model can be formed; thus inferences can be made as to the biochemical differences that are reflected by these spectral bands.

Algorithms↗
PubMed2004

Comparison of diffuse-reflectance absorbance and attenuated total reflectance FT-IR for the discrimination of bacteria.

A collection of bacteria belonging to the genus Bacillus were analysed by diffuse reflectance absorbance and attenuated total reflectance Fourier transform infrared (FT-IR) spectroscopy in the mid-infrared. The diffuse reflectance absorbance method is a rapid whole organism fingerprinting method, which generates a biochemical profile of the bacteria, where samples are presented to the FT-IR spectrometer dried on a metal carrier. The attenuated total reflectance FT-IR used in conjunction with a diamond attenuated total reflectance (ATR) accessory produces a biochemical profile of the surface chemistry of bacteria directly without the need for drying, and has not previously been used in the discrimination of bacteria. Principal component, discriminant function and hierarchical cluster analysis were performed on the data to discriminate the bacteria. The differentiation of the bacteria to species level was observed in both analyses however, it was concluded that the ATR FT-IR illustrated better sub-species differentiation of the microorganisms. This may imply that the total biochemical profiling infers discrimination to species level whereas strain specific markers are present on the cell surface chemistry.

Bacillus↗
PubMed2004

Surface-enhanced Raman spectroscopy for bacterial discrimination utilizing a scanning electron microscope with a Raman spectroscopy interface.

Surface-enhanced Raman scattering (SERS) utilizing colloidal silver has already been shown to provide a rapid means of generating "whole-organism fingerprints" for use in bacterial identification and discrimination. However, one of the main drawbacks of the technique for the analysis of microbiological samples with optical Raman microspectroscopy has been the inability to acquire pre-emptively a region of the sample matrix where both the SERS substrate and biomass are both present. In this study, we introduce a Raman interface for scanning electron microscopy (SEM) and demonstrate the application of this technology to the reproducible and targeted collection of bacterial SERS spectra. In secondary electron mode, the SEM images clearly reveal regions of the sample matrix where the sodium borohydride-reduced silver colloidal particles are present, Stokes spectra collected from these regions are rich in vibrational bands, whereas spectra taken from other areas of the sample elicit a strong fluorescence response. Replicate SERS spectra were collected from two bacterial strains and show excellent reproducibility both by visual inspection and as demonstrated by principal components analysis on the whole SERS spectra.

Bacillus subtilis↗
PubMed2004

Selective detection of proteins in mixtures using electrospray ionization mass spectrometry: influence of instrumental settings and implications for proteomics.

We studied the effects of electrospray mass spectrometric instrumental settings on the relative and absolute detection of individual proteins in a five-component mixture. Conditions that were effective for a given protein could be very poor for the others, and vice versa, such that to a good approximation it was possible to find conditions for selective detection of individual proteins in a complex mixture without prior analytical separation. Some of these could be rationalized on the basis of the known biophysical properties of the individual proteins. The ability to vary the conditions of a mass spectrometric detection method on-line provides an important degree of freedom for the selective detection, and hence discrimination, of individual proteins and peptides in complex mixtures and has implications in proteomics, in particular with respect to top-down strategies for proteomic characterizations.

Animals↗
PubMed2004

Ultra-violet resonance Raman spectroscopy for the rapid discrimination of urinary tract infection bacteria.

The ability to identify pathogenic organisms rapidly provides significant benefits to clinicians; in particular, with respect to best prescription practices and tracking of recurrent infections. Conventional bioassays require 3-5 days before identification of an organism can be made, thus compromising the effectiveness with which patients can be treated for bacterial infections. We analysed 20 clinical isolates of urinary tract infections (UTI) by ultra-violet resonance Raman (UVRR) spectroscopy, utilising 244 nm excitation delivering approximately 0.1 mW laser power at the sample, with typical spectral collection times of 120 s. UVRR results in resonance-enhanced Raman signals for certain chromophoric segments of macromolecules, intensifying those selected bands above what would otherwise be observed for a normal Raman experiment. Utilising the whole-organism 'fingerprints' obtained by UVRR we were able to discriminate successfully between UTI pathogens using chemometric cluster analyses. This work demonstrates significant improvements in the speed with which spectra can be obtained by Raman spectroscopic techniques for the discrimination of clinical bacterial samples.

Algorithms↗
PubMed2004

Application of high-throughput Fourier-transform infrared spectroscopy in toxicology studies: contribution to a study on the development of an animal model for idiosyncratic toxicity.

An evaluation of high-throughput Fourier-transform infrared spectroscopy (FT-IR) as a technology that could support a "metabonomics" component in toxicological studies of drug candidates is presented. The hypothesis tested in this study was that FT-IR had sufficient resolving power to discriminate between urine collected from control rat populations and rats subjected to treatment with a potent inflammatory agent, bacterial lipopolysaccharide (LPS). It was also hypothesized that co-administration of LPS with ranitidine, a drug associated with reports of idiosyncratic susceptibility, would induce hepatotoxicity in rats and that this could be detected non-invasively by an FT-IR-based metabonomics approach. The co-administration of LPS with "idiosyncratic" drugs represents an attempt to develop a predictive model of idiosyncratic toxicity and FT-IR is used herein to support characterization of this model. FT-IR spectra are high dimensional and the use of genetic programming to identify spectral sub-regions that most contribute to discrimination is demonstrated. FT-IR is rapid, reagentless, highly reproducible and inexpensive. Results from this pilot study indicate it could be extended to routine applications in toxicology and to supporting characterization of a new animal model for idiosyncratic susceptibility.

Animals↗
PubMed2004

Characterization of microorganisms using UV resonance Raman spectroscopy and chemometrics.

The past decade has seen an increased interest in the application of several physicochemical analytical techniques for the rapid detection and identification of microorganisms. We report the development of UV resonance Raman (UVRR) spectroscopy for the reproducible acquisition of information rich Raman fingerprints from endospore-forming bacteria belonging to the genera Bacillus and Brevibacillus. UVRR was conducted at 244 nm, and spectra were collected in typically 60 s. Cluster analyses of these spectra showed that UVRR spectroscopy could be used to discriminate between these microorganisms to species level, and the clustering pattern from this phenotypic classification was highly congruent with phylogenetic trees constructed from 16S rDNA sequence analysis. Therefore, we conclude that UVRR spectroscopy when coupled with chemometrics constitutes a powerful approach to the characterization and speciation of microorganisms.

Bacillus↗
PubMed2004

Discrimination of bacteria using surface-enhanced Raman spectroscopy.

Raman spectroscopy has recently been shown to be a potentially powerful whole-organism fingerprinting technique and is attracting interest within microbial systematics for the rapid identification of bacteria and fungi. However, while the Raman effect is so weak that only approximately 1 in 10(8) incident photons are Raman scattered (so that collection times are in the order of minutes), it can be greatly enhanced (by some 10(3)-10(6)-fold) if the molecules are attached to, or microscopically close to, a suitably roughened surface, a technique known as surface-enhanced Raman scattering (SERS). In this study, SERS, employing an aggregated silver colloid substrate, was used to analyze a collection of clinical bacterial isolates associated with urinary tract infections. While each spectrum took 10 s to collect, to acquire reproducible data, 50 spectra were collected making the spectral acquisition times per bacterium approximately 8 min. The multivariate statistical techniques of discriminant function analysis (DFA) and hierarchical cluster analysis (HCA) were applied in order to group these organisms based on their spectral fingerprints. The resultant ordination plots and dendrograms showed correct groupings for these organisms, including discrimination to strain level for a sample group of Escherichia coli, which was validated by projection of test spectra into DFA and HCA space. We believe this to be the first report showing bacterial discrimination using SERS.

Escherichia coli↗
PubMed2004

A proposed framework for the description of plant metabolomics experiments and their results.

The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.

Database Management Systems↗
PubMed2004

Whole-organism fingerprinting of the genus Carnobacterium using Fourier transform infrared spectroscopy (FT-IR).

Sixty seven strains of Carnobacterium, atypical Lactobacillus, Enterococcus durans, Lactobacillus maltaromicus and Vagacoccus salmoninarum were examined by Fourier transform infrared (FT-IR) spectroscopy. The effects of culture age and reproducibility over a six month period were also investigated. The results were analysed by multivariate statistics and compared with those from a previous numerical phenetic study, a pyrolysis mass spectrometry (PyMS) study and with investigations which used DNA-DNA and 16S rRNA sequencing homologies. Taxonomic correlations were observed between the FT-IR data and these studies. Culture age was observed to have little effect on the spectra obtained. The reproducibility study indicated that there was correlation between spectra produced on two occasions over the six month period. It was concluded that FTIR is a reliable method for investigating carnobacterial classification, and may have further potential as a rapid method for use in Carnobacterium identification.

Food Microbiology↗
PubMed2004

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.

Bacterial Typing Techniques↗
PubMed2003

Explanatory optimization of protein mass spectrometry via genetic search.

Optimizing experimental conditions for the effective analysis of intact proteins by mass spectrometry is challenging, as many analytical factors influence the spectral quality, often in very different ways for different proteins and especially with complex protein mixtures. We show that genetic search methods are highly effective in this kind of optimization and that it was possible in 6 generations with a total of <500 experiments out of some 10(14) to find good combinations of experimental variables (electrospray ionization mass spectral settings) that would not have been detected by optimizing each variable alone (i.e., the search space is epistatic). Moreover, by inspecting the evolution of the variables to be optimized using genetic programming, we discovered an important relationship between two of the mass spectrometer settings that accounts for much of this success. Specifically, the conditions that were evolved included very low values of skimmer 1 voltage (the sample cone) and a skimmer 2 voltage (extraction cone) above a threshold that would nevertheless minimize the potential difference between the sample and extraction skimmers. The discovery of this relationship demonstrates the hypothesis-generating ability of genetic search in optimization processes where the size of the search space means that little or no a priori knowledge of the optimal conditions is available.

Animals↗
PubMed2003

Rapid quantitative assessment of the adulteration of virgin olive oils with hazelnut oils using Raman spectroscopy and chemometrics.

The authentication of extra virgin olive oil and its adulteration with lower-priced oils are serious problems in the olive oil industry. In addition to the obvious effect on producer profits, adulteration can also cause severe health and safety problems. A number of techniques, including chromatographic and spectroscopic methods, have recently been employed to assess the purity of olive oils. In this study Raman spectroscopy together with multivariate and evolutionary computational-based methods have been employed to assess the ability of Raman spectroscopy to discriminate between chemically very closely related oils. Additionally, the levels of hazelnut oils used to adulterate extra virgin olive oil were successfully quantified using partial least squares and genetic programming.

Corylus↗
PubMed2003

Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry.

Metabolic fingerprints were obtained from unfractionated Pharbitis nil leaf sap samples by direct infusion into an electrospray ionization mass spectrometer. Analyses took less than 30 s per sample and yielded complex mass spectra. Various chemometric methods, including discriminant function analysis and the machine-learning methods of artificial neural networks and genetic programming, could discriminate the metabolic fingerprints of plants subjected to different photoperiod treatments. This rapid automated analytical procedure could find use in a variety of phytochemical applications requiring high sample throughput.

Artificial Intelligence↗
PubMed2003

Metabolic fingerprinting of salt-stressed tomatoes.

The aim of this study was to adopt the approach of metabolic fingerprinting through the use of Fourier transform infrared (FT-IR) spectroscopy and chemometrics to study the effect of salinity on tomato fruit. Two varieties of tomato were studied, Edkawy and Simge F1. Salinity treatment significantly reduced the relative growth rate of Simge F1 but had no significant effect on that of Edkawy. In both tomato varieties salt-treatment significantly reduced mean fruit fresh weight and size class but had no significant affect on total fruit number. Marketable yield was however reduced in both varieties due to the occurrence of blossom end rot in response to salinity. Whole fruit flesh extracts from control and salt-grown tomatoes were analysed using FT-IR spectroscopy. Each sample spectrum contained 882 variables, absorbance values at different wavenumbers, making visual analysis difficult and therefore machine learning methods were applied. The unsupervised clustering method, principal component analysis (PCA) showed no discrimination between the control and salt-treated fruit for either variety. The supervised method, discriminant function analysis (DFA) was able to classify control and salt-treated fruit in both varieties. Genetic algorithms (GA) were applied to identify discriminatory regions within the FT-IR spectra important for fruit classification. The GA models were able to classify control and salt-treated fruit with a typical error, when classifying the whole data set, of 9% in Edkawy and 5% in Simge F1. Key regions were identified within the spectra corresponding to nitrile containing compounds and amino radicals. The application of GA enabled the identification of functional groups of potential importance in relation to the response of tomato to salinity.

Algorithms↗
PubMed2003

Investigating plant-plant interference by metabolic fingerprinting.

New analytical developments in post-genomic technologies are being introduced to the field of plant ecology. FT-IR fingerprinting coupled with chemometrics via cluster analysis is proposed as a tool for correlating global metabolic changes with abiotic or biotic perturbation and/or interactions. The current study concentrates on detecting chemical responses by inter-species competition between a monocotyledon Brachypodium distachyion and a dicotyledon Arabidopsis thaliana. Growth analysis of 42 days old plants showed differences in both species under competition. Clear changes in the FT-IR metabolic fingerprints of B. distachyion in competition with A. thaliana were observed, whilst there were no apparent chemical differences in the A. thaliana plant tissues. This study demonstrates the power of this approach in detecting changes in the global metabolic profiles of plants in response to biotic interactions, and we believe FT-IR is appropriate for rapid screening (10 s per sample) prior to targeted metabolite analyses.

Arabidopsis↗