Showing papers by "Douglas B. Kell published in 1998"

Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation.

Abstract: MOTIVATION The simulation of biochemical kinetic systems is a powerful approach that can be used for: (i) checking the consistency of a postulated model with a set of experimental measurements, (ii) answering 'what if?' questions and (iii) exploring possible behaviours of a model. Here we describe a generic approach to combine numerical optimization methods with biochemical kinetic simulations, which is suitable for use in the rational design of improved metabolic pathways with industrial significance (metabolic engineering) and for solving the inverse problem of metabolic pathways, i.e. the estimation of parameters from measured variables. RESULTS We discuss the suitability of various optimization methods, focusing especially on their ability or otherwise to find global optima. We recommend that a suite of diverse optimization methods should be available in simulation software as no single one performs best for all problems. We describe how we have implemented such a simulation-optimization strategy in the biochemical kinetics simulator Gepasi and present examples of its application. AVAILABILITY The new version of Gepasi (3.20), incorporating the methodology described here, is available on the Internet at http://gepasi.dbs.aber.ac.uk/softw/Gepasi. html. CONTACT prm@aber.ac.uk

Viability and activity in readily culturable bacteria: a review and discussion of the practical issues

Abstract: In microbiology the terms 'viability' and 'culturability' are often equated. However, in recent years the apparently self-contradictory expression 'viable-but-nonculturable' ('VBNC') has been applied to cells with various and often poorly defined physiological attributes but which, nonetheless, could not be cultured by methods normally appropriate to the organism concerned. These attributes include apparent cell integrity, the possession of some form of measurable cellular activity and the apparent capacity to regain culturability. We review the evidence relating to putative VBNC cells and stress our view that most of the reports claiming a return to culturability have failed to exclude the regrowth of a limited number of cells which had never lost culturability. We argue that failure to differentiate clearly between use of the terms 'viability' and 'culturability' in an operational versus a conceptual sense is fuelling the current debate, and conclude with a number of proposals that are designed to help clarify the major issues involved. In particular, we suggest an alternative operational terminology that replaces 'VBNC' with expressions that are internally consistent.

A bacterial cytokine

Abstract: Viable cells of Micrococcus luteus secrete a factor, which promotes the resuscitation and growth of dormant, nongrowing cells of the same organism. The resuscitation-promoting factor (Rpf) is a protein, which has been purified to homogeneity. In picomolar concentrations, it increases the viable cell count of dormant M. luteus cultures at least 100-fold and can also stimulate the growth of viable cells. Rpf also stimulates the growth of several other high G+C Gram-positive organisms, including Mycobacterium avium, Mycobacterium bovis (BCG), Mycobacterium kansasii, Mycobacterium smegmatis, and Mycobacterium tuberculosis. Similar genes are widely distributed among high G+C Gram-positive bacteria; genome sequencing has uncovered examples in Mycobacterium leprae and Mb. tuberculosis and others have been detected by hybridization in Mb. smegmatis, Corynebacterium glutamicum, and Streptomyces spp. The mycobacterial gene products may provide different targets for the detection and control of these important pathogens. This report is thus a description of a proteinaceous autocrine or paracrine bacterial growth factor or cytokine.

Rapid identification of urinary tract infection bacteria using hyperspectral whole-organism fingerprinting and artificial neural networks

Abstract: Three rapid spectroscopic approaches for whole-organism fingerprinting-pyrolysis mass spectrometry (PyMS), Fourier transform infra-red spectroscopy (FT-IR) and dispersive Raman microscopy - were used to analyse a group of 59 clinical bacterial isolates associated with urinary tract infection. Direct visual analysis of these spectra was not possible, highlighting the need to use methods to reduce the dimensionality of these hyperspectral data. The unsupervised methods of discriminant function and hierarchical cluster analyses were employed to group these organisms based on their spectral fingerprints, but none produced wholly satisfactory groupings which were characteristic for each of the five bacterial types. In contrast, for PyMS and FT-IR, the artificial neural network (ANN) approaches exploiting multi-layer perceptrons or radial basis functions could be trained with representative spectra of the five bacterial groups so that isolates from clinical bacteriuria in an independent unseen test set could be correctly identified. Comparable ANNs trained with Raman spectra correctly identified some 80% of the same test set. PyMS and FT-IR have often been exploited within microbial systematics, but these are believed to be the first published data showing the ability of dispersive Raman microscopy to discriminate clinically significant intact bacterial species. These results demonstrate that modern analytical spectroscopies of high intrinsic dimensionality can provide rapid accurate microbial characterization techniques, but only when combined with appropriate chemometrics.

Variable Selection in Discriminant Partial Least-Squares Analysis

Abstract: Variable selection enhances the understanding and interpretability of multivariate classification models. A new chemometric method based on the selection of the most important variables in discriminant partial least-squares (VS-DPLS) analysis is described. The suggested method is a simple extension of DPLS where a small number of elements in the weight vector w is retained for each factor. The optimal number of DPLS factors is determined by cross-validation. The new algorithm is applied to four different high-dimensional spectral data sets with excellent results. Spectral profiles from Fourier transform infrared spectroscopy and pyrolysis mass spectrometry are used. To investigate the uniqueness of the selected variables an iterative VS-DPLS procedure is performed. At each iteration, the previously found selected variables are removed to see if a new VS-DPLS classification model can be constructed using a different set of variables. In this manner, it is possible to determine regions rather than individual variables that are important for a successful classification.

On resuscitation from the dormant state of Micrococcus luteus

Abstract: It has been found previously that a significant number of Micrococcus luteus cells starved in a prolonged stationary phase (up to 2 months) and then held on the bench at room temperature without agitation for periods of up to a further 2–7 months can be resuscitated in liquid media which contained (statistically) no initially-viable (colony-forming) cells but which were fortified with sterile supernatant from the late logarithmic phase of batch growth. Here it was found that such resuscitation can be done only within a defined time period after taking the first sample from such cultures, necessarily involving agitation of the cells. The duration of this period depends on the age of the starved culture: cells kept on the bench for 3 months possess a 2 month period of resuscitability while cells starved for 6 months can be resuscitated only within 10 days after the beginning of sampling. It is suggested that the input of oxygen to the starved cultures while they are agitated may exert a negative influence on the cells, since cultures stored in anaerobic conditions (under nitrogen) had a more prolonged ’survival' time. The cells which experienced between 10 and 60 days of starvation on the bench could be resuscitated, although the number of resuscitable cells depended strongly on the concentration of yeast extract in the resuscitation medium. This concentration for cells stored on the bench for more than 2 months was 0.05% while ’1-month-old‘ cells displayed a maximum resuscitability in the presence of 0.01% of yeast extract. Application of the fluorescent probe propidium iodide revealed the formation of cells with a damaged permeability barrier if resuscitation was performed by using concentrations of yeast extract of 0.1% and above. Thus the successful resuscitation of bacterial cultures under laboratory conditions may need rather strictly defined parameters if it is to be successfully performed for the majority of cells in a population.

The deconvolution of pyrolysis mass spectra using genetic programming: application to the identification of some Eubacterium species

Abstract: Pyrolysis mass spectrometry was used to produce complex biochemical fingerprints of Eubacterium exiguum, E. infirmum, E. tardum and E. timidum. To examine the relationship between these organisms the spectra were clustered by canonical variates analysis, and four clusters, one for each species, were observed. In an earlier study we trained artificial neural networks to identify these clinical isolates successfully ; however, the information used by the neural network was not accessible from this so-called ‘black box’ technique. To allow the deconvolution of such complex spectra (in terms of which masses were important for discrimination) it was necessary to develop a system that itself produces ‘rules’ that are readily comprehensible. We here exploit the evolutionary computational technique of genetic programming; this rapidly and automatically produced simple mathematical functions that were also able to classify organisms to each of the four bacterial groups correctly and unambiguously. Since the rules used only a very limited set of masses, from a search space some 50 orders of magnitude greater than the dimensionality actually necessary, visual discrimination of the organisms on the basis of these spectral masses alone was also then possible. z 1998 Federation of European Microbiological Societies. Published by Elsevier Science B.V.

Discrimination between methicillin-resistant and methicillin- susceptible Staphylococcus aureus using pyrolysis mass spectrometry and artificial neural networks

Abstract: Curie-point pyrolysis mass spectra were obtained from 15 methicillin-resistant and 22 methicillin-susceptible Staphylococcus aureus strains. Cluster analysis showed that the major source of variation between the pyrolysis mass spectra resulted from the phage group of the bacteria, not their resistance or susceptibility to methicillin. By contrast, artificial neural networks could be trained to recognize those aspects of the pyrolysis mass spectra that differentiated methicillin-resistant from methicillin-sensitive strains. The trained neural network could then use pyrolysis mass spectral data to assess whether an unknown strain was resistant to methicillin. These results give the first demonstration that the combination of pyrolysis mass spectrometry with neural networks can provide a very rapid and accurate antibiotic susceptibility testing technique.

Rheological phenomena occurring during the shearing flow of mayonnaise

Abstract: A rheometrical study reveals that mayonnaise exhibits apparent wall slip in both small amplitude oscillatory shear flow and torsional flow. Whereas in the case of small amplitude oscillatory shear classical techniques are applicable for extracting bulk material properties, this is not the case for torsional flow. Progressively increasing the shear stress in torsional flow manifests another flow phenomenon that dominates the slip process. It is argued that “particles” within the mayonnaise migrate radially towards the center of the geometry. Spectroscopic techniques are employed to confirm that, following an experiment, material at the rim of the geometry differs from that towards the center. Experiments performed in a cone-and-plate geometry yield results that are qualitatively similar to those obtained in torsional flow tests thus indicating that the migration is not due solely to the radial shear-rate gradient that is present in torsional flow.

Quantification of microbial productivity via multi-angle light scattering and supervised learning.

Abstract: This article describes the use of chemometric methods for prediction of biological parameters of cell suspensions on the basis of their light scattering profiles. Laser light is directed into a vial or flow cell containing media from the suspension. The intensity of the scattered light is recorded at 18 angles. Supervised learning methods are then used to calibrate a model relating the parameter of interest to the intensity values. Using such models opens up the possibility of estimating the biological properties of fermentor broths extremely rapidly (typically every 4 sec), and, using the flow cell, without user interaction. Our work has demonstrated the usefulness of this approach for estimation of yeast cell counts over a wide range of values (10(5)-10(9) cells mL-1), although it was less successful in predicting cell viability in such suspensions.

Method and apparatus for capacitance measurement of a dielectric medium utilizing the ratio of capacitance measurement made at different frequencies

Abstract: A method for analyzing a dielectric medium comprises the step of measuring, at one or more frequencies, the capacitance between a pair of electrodes immersed in the dielectric medium. The proportion of the or each capacitance measurement due to electrode polarization capacitance and/or to the residual capacitance of the dielectric medium is then determined using capacitance measurements made between the electrodes at a first frequency and at a second frequency, the ratio of the respective polarization capacitances at these two frequencies being predetermined. An apparatus for performing the method is also disclosed.

Rapid analysis of microbial systems using vibrational spectroscopy and supervised learning methods: application to the discrimination between methicillin-resistant and methicillin-susceptible Staphy

Abstract: FTIR spectra were obtained from 15 methicillin-resistant and 22 methicillin-susceptible Staphylococcus aureus strains using our DRASTIC approach. Cluster analysis showed that the major source of variation between the IR spectra was not due to their resistance or susceptibility to methicillin; indeed early studies suing pyrolysis mass spectrometry had shown that this unsupervised analysis gave information on the phage group of the bacteria. By contrast, artificial neural networks, based on a supervised learning, could be trained to recognize those aspects of the IR spectra which differentiated methicillin-resistant from methicillin- susceptible strains. These results give the first demonstration that the combination of FTIR with neural networks can provide a very rapid and accurate antibiotic susceptibility testing technique.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Capacitance measurement of a dielectric medium

Abstract: A method for analysing a dielectric mediun comprises the step of measuring, at one or more frequencies, the capacitance between a pair of electrodes immersed in the dielectric medium. The proportion of the or each capacitance measurement due to electrode polarisation capacitance and/or to the residual capacitance of the dielectic medium is then determined using capacitance measurements made between the electrodes at a first frequency and at a second frequency, the ratio of the respective polarisation capacitances at these two frequencies being predetermined.

Bacterial pheromones and uses therefor

Abstract: RP-factors, their cognate receptors, convertases, respective genes and inhibitors or mimetics thereof are described. In particular, antibodies, pharmaceutical compositions and (therapeutic, diagnostic) methods based on the RP-factors and their receptors/convertases are described.

A DRASTIC (Diffuse Reflectance Absorbance Spectroscopy Taking in Chemometrics) approach for the rapid analysis of microbial fermentation products: Quantification of aristeromycin and neplanocin A in Streptomyces citricolor broths

Abstract: Microbial cultures can provide metabolites which are useful as structural templates for rational drug design. Increasing the titre of the metabolite is an important part of this process and is often achieved by random mutagenesis. As titre improved mutants derived by this method are extremely rare, many thousands need to be screened. screening mutants for increased metabolite production relies on methods such as assessing binding via the scintilation proximity assay or identifying an increase in concentration using chromatography. Such methods are typically restricted by the necessity to perform solvent extractions and, in the case of HPLC analysis, to optimise separation of the components of interest. Although the routine procedures can be automated, such multi-step screening processes are far from ideal. Diffuse reflectance absorbance infra-red spectroscopy provides an alternative rapid, automated, quantitative approach which yields more detailed information about chemical characteristics than, for example, the UV absorbance spectrum typically used in HPLC analysis. The method can also be employed non-invasively on unprocessed fermentation samples. We demonstrate the use of this spectroscopictechnique in combination with chemometrics for determining the concentrations of aristeromycin and neplanocin A in Streptomyces citricolor fermentations. The fermentation broths of a range of mutants previously obtained during a titre improvement programme were analysed by standard HPLC techniques and by automated diffuse reflectance absorbance infra-red spectroscopy. Chemometric processing of the infra-red spectra was performed using supervised and unsupervised multivariate calibration methods. DRASTIC proved to be a rapid and reliable method for the estimation of metabolite overproduction in cultures of biotechnological interest, and it was possible to discriminate cultures overproducing closely related molecules.

DRASTIC(Diffuse Reflectance Absorbance Spectroscopy Taking In Chemometrics). A novel, rapid, hyperspectral, FT-IR-based approach to screening for biocatalytic activity and metabolite overproduction

Abstract: Diffuse-reflectance absorbance spectroscopy in the mid-infrared is a novel method of producing data with which to effect chemical imaging for the rapid screening of biological samples for metabolite overproduction. We have used mixtures of ampicillin and Escherichia coli , and Streptomyces citricolor producing aristeromycin and neplanocin A, as model systems. Deconvolution of the hyperspectral information provided by the raw diffuse reflectance-absorbance mid-infrared spectra may be achieved using a combination of principal components analysis (PCA) and supervised methods such as artificial neural networks (ANNs) and partial least squares regression (PLS). Whereas a univariate approach necessitates appropriate data selection to remove any interferences, the chemometrics/hyperspectral approach could be employed to permit filtering of undesired components either manually, or by taking the Fourier transform of the spectral information (in order to help isolate the signal from the baseline variation or noise) prior to applying linear multivariate regression techniques. Equivalent concentrations of ampicillin between 0.2mM and 13.5mM in an E. coli background could be quantified with good accuracy using this approach.