Rapid and non-invasive quantification of metabolic substrates in biological cell suspensions using non-linear dielectric spectroscopy with multivariate calibration and artificial neural networks. Principles and applications

Generation of nonlinearity in the electrical response of yeast suspensions

The mechanism through which nonlinearity is generated in the response waveform of the electric current obtained by applying alternating current voltage to yeast suspension has not yet been elucidated. In this paper, we showed that the response waveform depends on the applied voltage and frequency. The results showed that distortion (nonlinearity) in the waveform increases as the applied voltage increases and/or the frequency decreases. We suggest a model for the generation of nonlinearity based on the influx of potassium ions into the cell via potassium ion channels and transporters in the membrane due to the applied voltage. Furthermore, we validated this model by simulating an electrical circuit.

Design and evaluation of a fast Fourier transform-based nonlinear dielectric spectrometer

Nonlinear dielectric spectroscopy of micro-organism is carried out by applying a moderate electrical field to an aqueous sample through two metal electrodes. Several ad hoc nonlinear spectrometers were proposed in the literature. However, these designs barely compensated the nonlinear distortion derived from the electrode-electrolyte interfaces (EEI). Moreover, the contribution of the suspension is masked by the effect of the nonlinearity introduced by the electrode contacts. Conversely, the nonlinear capability of a commercial tetrapolar analyzer has not been fully investigated. In this paper a new nonlinear tetrapolar spectrometer is proposed based on a commercial linear apparatus and ad hoc control and signal processing software. The system was evaluated with discrete electronic phantoms and showed that it can measure nonlinear properties of aqueous suspension independently of the presence of EEI (ANOVA test, p>0.001). It was also tested with real aqueous samples. The harmonics observed in the current that circulates through the sample reveals useful information about the transfer function of the sample. The total harmonic distortion was computed for linear mediums. Values lower than -60 dB suggest that the system has enough capability to perform nonlinear microbiological analysis. Design specifications, sources of interference, and equipment's limitations are discussed.

Importance of intermediary transitions and waveform in the enzyme-electric field interaction

The current theory of enzymes and electric field interaction does not account for all the observed data since we could not observe non-linear behavior of cell suspensions as anticipated by other authors. In our case, we used a pure sinusoidal source, however the experiments that do account for responses used a sum of a central sinusoidal and its harmonics frequencies. As a result, we suggest that the enzyme and electric interaction are favored when the field has a non-strictly sinusoidal waveform, and this behavior is related to the true intermediate transitions of the enzyme during its catalytic cycle. Therefore, we developed an iterative model of the interaction process based on previous models and actual trends. The model well verified all the previous simulations and showed that, for a non-symmetrical enzyme, the energy can harvest its maximal for non sinusoidal fields.

Non linear dielectric properties of microbiological suspensions at electrode-electrolyte interfaces

Nonlinear properties of biological suspensions have been previously presented as a bulk phenomenon, however, some authors consider that they are generated at the electrode-electrolyte interface and are reflected as a bulk property phenomenon. They were mainly ascribed to the H⁺-ATPase present in the plasma membrane of these cells. In this paper, we describe the construction of a dual-cell nonlinear dielectric spectrometer. The system is applied to the study of interfaces with resting cell suspensions of Saccharomyces cerevisiae. Substantial harmonics are generated at the interface when a sinusoidal current is applied and altered by the presence of yeast. When a second interface with yeast and enzyme inhibitor is used as reference, a decrease in the magnitude response of the third harmonic can be observed. As it was already described for the solution bulk, we obtained a similar behavior at the interface. Besides, we also found optimal intervals, respectively, for frequency and voltage to reach maximal response. This result would support the contention that biological nonlinearity is an interface-based phenomenon.

Theodor Bücher Lecture. Metabolomics, modelling and machine learning in systems biology - towards an understanding of the languages of cells. Delivered on 3 July 2005 at the 30th FEBS Congress and the 9th IUBMB conference in Budapest

The newly emerging field of systems biology involves a judicious interplay between high-throughput 'wet' experimentation, computational modelling and technology development, coupled to the world of ideas and theory. This interplay involves iterative cycles, such that systems biology is not at all confined to hypothesis-dependent studies, with intelligent, principled, hypothesis-generating studies being of high importance and consequently very far from aimless fishing expeditions. I seek to illustrate each of these facets. Novel technology development in metabolomics can increase substantially the dynamic range and number of metabolites that one can detect, and these can be exploited as disease markers and in the consequent and principled generation of hypotheses that are consistent with the data and achieve this in a value-free manner. Much of classical biochemistry and signalling pathway analysis has concentrated on the analyses of changes in the concentrations of intermediates, with 'local' equations - such as that of Michaelis and Menten v=(Vmax x S)/(S+K m) - that describe individual steps being based solely on the instantaneous values of these concentrations. Recent work using single cells (that are not subject to the intellectually unsupportable averaging of the variable displayed by heterogeneous cells possessing nonlinear kinetics) has led to the recognition that some protein signalling pathways may encode their signals not (just) as concentrations (AM or amplitude-modulated in a radio analogy) but via changes in the dynamics of those concentrations (the signals are FM or frequency-modulated). This contributes in principle to a straightforward solution of the crosstalk problem, leads to a profound reassessment of how to understand the downstream effects of dynamic changes in the concentrations of elements in these pathways, and stresses the role of signal processing (and not merely the intermediates) in biological signalling. It is this signal processing that lies at the heart of understanding the languages of cells. The resolution of many of the modern and postgenomic problems of biochemistry requires the development of a myriad of new technologies (and maybe a new culture), and thus regular input from the physical sciences, engineering, mathematics and computer science. One solution, that we are adopting in the Manchester Interdisciplinary Biocentre (http://www.mib.ac.uk/) and the Manchester Centre for Integrative Systems Biology (http://www.mcisb.org/), is thus to colocate individuals with the necessary combinations of skills. Novel disciplines that require such an integrative approach continue to emerge. These include fields such as chemical genomics, synthetic biology, distributed computational environments for biological data and modelling, single cell diagnostics/bionanotechnology, and computational linguistics/text mining.

Harmonic response of cellular membrane pumps to low frequency electric fields

We report on harmonic generation by budding yeast cells in response to a sinusoidal electric field, which is seen to be minimal when the field amplitude is less than a threshold value. Surprisingly, sodium metavanadate, an inhibitor of P-type ATPases reportedly responsible for nonlinear response in yeast, reduces the threshold field amplitude, increasing harmonic generation at low amplitudes while reducing it at large amplitudes, whereas the addition of glucose dramatically increases the production of even harmonics. Finally, a simple model is proposed to interpret the observed behavior.

Metabolomics, machine learning and modelling: towards an understanding of the language of cells

In answering the question ‘Systems Biology – will it work?’ (which it self-evidently has already), it is appropriate to highlight advances in philosophy, in new technique development and in novel findings. In terms of philosophy, we see that systems biology involves an iterative interplay between linked activities – for instance, between theory and experiment, between induction and deduction and between measurements of parameters and variables – with more emphasis than has perhaps been common now being focused on the first in each of these pairs. In technique development, we highlight closed loop machine learning and its use in the optimization of scientific instrumentation, and the ability to effect high-quality and quasi-continuous optical images of cells. This leads to many important and novel findings. In the first case, these may involve new biomarkers for disease, whereas in the second case, we have determined that many biological signals may be frequency-rather than amplitude-encoded. This leads to a very different view of how signalling ‘works’ (equations such as that of Michaelis and Menten which use only amplitudes, i.e. concentrations, are inadequate descriptors), lays emphasis on the signal processing network elements that lie ‘downstream’ of what are traditionally considered the signals, and allows one simply to understand how cross-talk may be avoided between pathways which nevertheless use common signalling elements. The language of cells is much richer than we had supposed, and we are now well placed to decode it.

Search and Discovery Strategies for Biotechnology: the Paradigm Shift

SUMMARY

Profound changes are occurring in the strategies that biotechnology-based industries are deploying in the search for exploitable biology and to discover new products and develop new or improved processes. The advances that have been made in the past decade in areas such as combinatorial chemistry, combinatorial biosynthesis, metabolic pathway engineering, gene shuffling, and directed evolution of proteins have caused some companies to consider withdrawing from natural product screening. In this review we examine the paradigm shift from traditional biology to bioinformatics that is revolutionizing exploitable biology. We conclude that the reinvigorated means of detecting novel organisms, novel chemical structures, and novel biocatalytic activities will ensure that natural products will continue to be a primary resource for biotechnology. The paradigm shift has been driven by a convergence of complementary technologies, exemplified by DNA sequencing and amplification, genome sequencing and annotation, proteome analysis, and phenotypic inventorying, resulting in the establishment of huge databases that can be mined in order to generate useful knowledge such as the identity and characterization of organisms and the identity of biotechnology targets. Concurrently there have been major advances in understanding the extent of microbial diversity, how uncultured organisms might be grown, and how expression of the metabolic potential of microorganisms can be maximized. The integration of information from complementary databases presents a significant challenge. Such integration should facilitate answers to complex questions involving sequence, biochemical, physiological, taxonomic, and ecological information of the sort posed in exploitable biology. The paradigm shift which we discuss is not absolute in the sense that it will replace established microbiology; rather, it reinforces our view that innovative microbiology is essential for releasing the potential of microbial diversity for biotechnology penetration throughout industry. Various of these issues are considered with reference to deep-sea microbiology and biotechnology.

Search and discovery strategies for biotechnology: the paradigm shift

Profound changes are occurring in the strategies that biotechnology-based industries are deploying in the search for exploitable biology and to discover new products and develop new or improved processes. The advances that have been made in the past decade in areas such as combinatorial chemistry, combinatorial biosynthesis, metabolic pathway engineering, gene shuffling, and directed evolution of proteins have caused some companies to consider withdrawing from natural product screening. In this review we examine the paradigm shift from traditional biology to bioinformatics that is revolutionizing exploitable biology. We conclude that the reinvigorated means of detecting novel organisms, novel chemical structures, and novel biocatalytic activities will ensure that natural products will continue to be a primary resource for biotechnology. The paradigm shift has been driven by a convergence of complementary technologies, exemplified by DNA sequencing and amplification, genome sequencing and annotation, proteome analysis, and phenotypic inventorying, resulting in the establishment of huge databases that can be mined in order to generate useful knowledge such as the identity and characterization of organisms and the identity of biotechnology targets. Concurrently there have been major advances in understanding the extent of microbial diversity, how uncultured organisms might be grown, and how expression of the metabolic potential of microorganisms can be maximized. The integration of information from complementary databases presents a significant challenge. Such integration should facilitate answers to complex questions involving sequence, biochemical, physiological, taxonomic, and ecological information of the sort posed in exploitable biology. The paradigm shift which we discuss is not absolute in the sense that it will replace established microbiology; rather, it reinforces our view that innovative microbiology is essential for releasing the potential of microbial diversity for biotechnology penetration throughout industry. Various of these issues are considered with reference to deep-sea microbiology and biotechnology.

Non-linear dielectric spectroscopy: antifouling and stabilisation of electrodes by a polymer coating

Non-linear dielectric spectroscopy (NLDS) has previously been shown to produce quantitative information that is indicative of the metabolic state of various organisms, by modeling the non-linear effects of their membranous enzymes on an applied oscillating electromagnetic field using supervised multivariate analysis methods. However, the instability of the characteristics of the measuring apparatus rendered the process temperamental at best in the laboratory and impractical for field use. The main practical problem, of the non-stationarity of the electrode-solution interface and the ease with which the electrode surfaces are subject to protein fouling. It is addressed by applying a thin, electrically transparent antifouling coat to the electrodes. This reduces the interminable cleaning procedures previously required to prepare the electrodes for use, increases their usable lifetime before recleaning, and also improves the precision and linearity of multivariate models on NLDS data.

Correction of the influence of baseline artefacts and electrode polarisation on dielectric spectra

The deconvolution of biological dielectric spectra can be difficult enough with artefact-free spectra but is more problematic when machine baseline artefacts and electrode polarisation are present as well. In addition, these two sources of anomalies can be responsible for significant interference with dielectric biomass measurements made using one- or two-spot frequencies. The aim of this paper is to develop mathematical models of baseline artefacts and electrode polarisation which can be used to remove these anomalies from dielectric spectra in a way that can be easily implemented on-line and in real-time on the Biomass Monitor (BM). We show that both artefacts can be successfully removed in solutions of organic and inorganic ions; in animal cell and microbial culture media; and in yeast suspensions of varying biomass. The high quality of the compensations achieved were independent of whether gold and platinum electrodes were used; the electrode geometry; electrode fouling; current density; the type of BM; and of whether electrolytic cleaning pulses had been applied. In addition, the calibration experiments required could be done off-line using a simple aqueous KCl dilution series with the calibration constants being automatically calculated by a computer without the need for user intervention. The calibration values remained valid for a minimum of 3 months for the baseline model and indefinitely for the electrode polarisation one. Importantly, application of baseline correction prior to polarisation correction allowed the latter's application to the whole conductance range of the BM. These techniques are therefore exceptionally convenient to use under practical conditions.

Rapid analysis of high-dimensional bioprocesses using multivariate spectroscopies and advanced chemometrics

There are an increasing number of instrumental methods for obtaining data from biochemical processes, many of which now provide information on many (indeed many hundreds) of variables simultaneously. The wealth of data that these methods provide, however, is useless without the means to extract the required information. As instruments advance, and the quantity of data produced increases, the fields of bioinformatics and chemometrics have consequently grown greatly in importance. The chemometric methods nowadays available are both powerful and dangerous, and there are many issues to be considered when using statistical analyses on data for which there are numerous measurements (which often exceed the number of samples). It is not difficult to carry out statistical analysis on multivariate data in such a way that the results appear much more impressive than they really are. The authors present some of the methods that we have developed and exploited in Aberystwyth for gathering highly multivariate data from bioprocesses, and some techniques of sound multivariate statistical analyses (and of related methods based on neural and evolutionary computing) which can ensure that the results will stand up to the most rigorous scrutiny.

Genetic programming as an analytical tool for non-linear dielectric spectroscopy

By modelling the non-linear effects of membranous enzymes on an applied oscillating electromagnetic field using supervised multivariate analysis methods, Non-Linear Dielectric Spectroscopy (NLDS) has previously been shown to produce quantitative information that is indicative of the metabolic state of various organisms. The use of Genetic Programming (GP) for the multivariate analysis of NLDS data recorded from yeast fermentations is discussed, and GPs are compared with previous results using Partial Least Squares (PLS) and Artificial Neural Nets (NN). GP considerably outperforms these methods, both in terms of the precision of the predictions and their interpretability.

A weak pulsed magnetic field affects adenine nucleotide oscillations, and related parameters in aggregating Dictyostelium discoideum amoebae

A model eukaryotic cell system was used to explore the effect of a weak pulsed magnetic field (PMF) on time-varying physiological parameters. Dictyostelium discoideum cells (V12 strain) were exposed to a pulsed magnetic field (PMF) of flux density 0.4 mT, generated via air-cored coils in trains of 2 ms pulses gated at 20 ms. This signal is similar to those used to treat non-uniting fractures. Samples were taken over periods of 20 min from harvested suspensions of amoebae during early aggregation phase, extracted and derivatised for HPLC fluorescent assay of adenine nucleotides. Analysis of variance showed a significant athermal damping effect (P < 0.002, n = 22) of the PMF on natural adenine nucleotide oscillations and some consistent changes in phase relationships. The technique of nonlinear dielectric spectroscopy (NLDS) revealed a distinctive effect of PMF, caffeine and EGTA in modulating the cellular harmonic response to an applied weak signal. Light scattering studies also showed altered frequency response of cells to PMF, EGTA and caffeine. PMF caused a significant reduction of caffeine induced cell contraction (P < 0.0006, n = 19 by paired t-test) as shown by Malvern particle size analyser, suggesting that intracellular calcium may be involved in mediating the effect of the PMF.