Pulse experiments as a prerequisite for the quantification of in vivo enzyme kinetics in aromatic amino acid pathway of Escherichia coli

Glucose pulse experiments were performed to elucidate their effects on the carbon flux into the aromatic amino acid pathway in different Escherichia coli strains. Using a 3-deoxy-D-arabino-heptulosonate 7-phosphate (DAHP, aroB(-))-producing strain, a fed-batch fermentation strategy specialized for glucose pulse experiments was developed and further applied for 3-dehydroshikimate (DHS, aroE(-))- and shikimate 3-phosphate (S3P, aroA(-))-producing E. coli strains. The strains overexpress a feedback-resistant DAHP synthase and additional enzymes to prevent rate-limiting steps in the aromatic amino acid pathway. Changes of carbon flux into the aromatic amino acid pathway were determined via extracellular metabolite accumulations using (1)H NMR and HPLC measurements. As an important result, a close relationship between pulse intensity and aromatic metabolite formation rates was identified. The more downstream an aromatic pathway intermediate was located, the stronger the glucose pulse intensity had to be in order to detect significant changes in product formation. However, with the experimental conditions chosen, changes after pulse were detected even for shikimate 3-phosphate, the most downstream accumulating metabolite of this experimental series. Hence glucose pulse experiments are assumed to be a promising tool even for the analysis of final pathway products such as, for example, L-phenylalanine.     

Temperature response of mesophyll conductance. Implications for the determination of Rubisco enzyme kinetics and for limitations to photosynthesis in vivo

CO(2) transfer conductance from the intercellular airspaces of the leaf into the chloroplast, defined as mesophyll conductance (g(m)), is finite. Therefore, it will limit photosynthesis when CO(2) is not saturating, as in C3 leaves in the present atmosphere. Little is known about the processes that determine the magnitude of g(m). The process dominating g(m) is uncertain, though carbonic anhydrase, aquaporins, and the diffusivity of CO(2) in water have all been suggested. The response of g(m) to temperature (10 degrees C-40 degrees C) in mature leaves of tobacco (Nicotiana tabacum L. cv W38) was determined using measurements of leaf carbon dioxide and water vapor exchange, coupled with modulated chlorophyll fluorescence. These measurements revealed a temperature coefficient (Q(10)) of approximately 2.2 for g(m), suggesting control by a protein-facilitated process because the Q(10) for diffusion of CO(2) in water is about 1.25. Further, g(m) values are maximal at 35 degrees C to 37.5 degrees C, again suggesting a protein-facilitated process, but with a lower energy of deactivation than Rubisco. Using the temperature response of g(m) to calculate CO(2) at Rubisco, the kinetic parameters of Rubisco were calculated in vivo from 10 degrees C to 40 degrees C. Using these parameters, we determined the limitation imposed on photosynthesis by g(m). Despite an exponential rise with temperature, g(m) does not keep pace with increased capacity for CO(2) uptake at the site of Rubisco. The fraction of the total limitations to CO(2) uptake within the leaf attributable to g(m) rose from 0.10 at 10 degrees C to 0.22 at 40 degrees C. This shows that transfer of CO(2) from the intercellular air space to Rubisco is a very substantial limitation on photosynthesis, especially at high temperature.     

An automatic segmentation and classification framework for anti-nuclear antibody images

Autoimmune disease is a disorder of immune system due to the over-reaction of lymphocytes against one's own body tissues. Anti-Nuclear Antibody (ANA) is an autoantibody produced by the immune system directed against the self body tissues or cells, which plays an important role in the diagnosis of autoimmune diseases. Indirect ImmunoFluorescence (IIF) method with HEp-2 cells provides the major screening method to detect ANA for the diagnosis of autoimmune diseases. Fluorescence patterns at present are usually examined laboriously by experienced physicians through manually inspecting the slides with the help of a microscope, which usually suffers from inter-observer variability that limits its reproducibility. Previous researches only provided simple segmentation methods and criterions for cell segmentation and recognition, but a fully automatic framework for the segmentation and recognition of HEp-2 cells had never been reported before. This study proposes a method based on the watershed algorithm to automatically detect the HEp-2 cells with different patterns. The experimental results show that the segmentation performance of the proposed method is satisfactory when evaluated with percent volume overlap (PVO: 89%). The classification performance using a SVM classifier designed based on the features calculated from the segmented cells achieves an average accuracy of 96.90%, which outperforms other methods presented in previous studies. The proposed method can be used to develop a computer-aided system to assist the physicians in the diagnosis of auto-immune diseases.     

An ovine in vivo framework for tracheobronchial stent analysis

Tracheobronchial stents are most commonly used to restore patency to airways stenosed by tumour growth. Currently all tracheobronchial stents are associated with complications such as stent migration, granulation tissue formation, mucous plugging and stent strut fracture. The present work develops a computational framework to evaluate tracheobronchial stent designs in vivo. Pressurised computed tomography is used to create a biomechanical lung model which takes into account the in vivo stress state, global lung deformation and local loading from pressure variation. Stent interaction with the airway is then evaluated for a number of loading conditions including normal breathing, coughing and ventilation. Results of the analysis indicate that three of the major complications associated with tracheobronchial stents can potentially be analysed with this framework, which can be readily applied to the human case. Airway deformation caused by lung motion is shown to have a significant effect on stent mechanical performance, including implications for stent migration, granulation formation and stent fracture.     

An automatic apparatus for the study of enzyme kinetics

A continuous-flow apparatus is described for automatically plotting substrate saturation curves, and is suitable for use with a variety of enzymes. A linear concentration gradient of the variable substrate is combined with a fixed proportion of the other substrates and the enzyme, and after passing through a reaction coil the product concentrations are measured spectrophotometrically. Use of a 4cm. flow cell and modified spectrophotometer permits accurate measurement of NADH concentration in the region of 0.1mum. Precise control over reaction times and substrate concentration is achieved by using power-driven syringes with an integral mixer. Specimen results are given for yeast alcohol dehydrogenase.     

An intramolecular cyclization reaction is responsible for the in vivo inefficacy and apparent pH insensitive hydrolysis kinetics of hydrazone carboxylate derivatives of doxorubicin

Contradictory reports concerning the pH sensitive hydrolysis kinetics of certain hydrazone carboxylates of doxorubicin have appeared in this journal (Kaneko et al., Bioconjugate Chem. 1991, 2, 133. Padilla De Jesús et al., Bioconjugate Chem. 2002, 13, 453). Since the pH stability of the drug-carrier linkage in macromolecular prodrugs has a significant bearing on pharmacological efficacy, the hydrolysis kinetics of low molecular weight and polymeric doxorubicin hydrazone carboxylates were therefore reinvestigated. As observed previously, the conjugates readily release native doxorubicin at pH 5. Unexpectedly, in neutral buffer the hydrazone carboxylate conjugates do not release native doxorubicin, but instead rapidly release a doxorubicin derivative substituted at C-9 by 3,6-dihydro-1,3,4-oxadiazin-2-one with first-order kinetics (t(1/2) = 2.5 h). The proposed intramolecular cyclization reaction involving doxorubicin's C-14 hydroxyl and the carboxylate-substituted hydrazone rationalizes the seemingly anomalous hydrolysis kinetics seen for hydrazone carboxylate linked doxorubicin, and provides a possible explanation for the poor antitumor activity exhibited by polymer-doxorubicin conjugates utilizing this specific type of linkage.     

An intradermal assay for quantification and kinetics studies of tumor angiogenesis in mice.

A method is reported for the study of early phases of neovascularization in syngeneic murine tumors and human tumor xenografts in nude mice. Using this method, the effect of irradiation of tumor cells or tumor bed on tumor angiogenesis was studied. Tumor cells were injected intradermally in the abdominal skin flap, which was reopened at 2-day intervals to quantify newly formed blood vessels at the site of tumor cell injection. Both tumor cell injection and blood vessel counting were performed under a dissecting microscope. Using three syngeneic murine tumors and two clones of a human colonic adenocarcinoma, it was observed that new blood vessels started appearing within a few days after tumor cell injection and that this event preceded measurable tumor growth. The number of blood vessels increased exponentially for several days but then their further growth slowed. The extent of angiogenesis depended on the tumor type and the number of tumor cells injected. The exposure of the skin flap to ionizing radiation prior to tumor cell injection reduced neovascularization. We further observed that heavily irradiated tumor cells retained their ability to induce angiogenic response and that lymphoid cells (peritoneal exudate and spleen cells) could also elicit an angiogenic response, although it is weaker than the response elicited by tumor cells. Thus this method is suitable for quantification and kinetics of early phases of tumor angiogenesis in individual mice bearing transplants of syngeneic tumors or human tumor xenografts, and it can be useful for investigating various regulators of tumor angiogenesis.     

qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data

Although quantitative PCR (qPCR) is becoming the method of choice for expression profiling of selected genes, accurate and straightforward processing of the raw measurements remains a major hurdle. Here we outline advanced and universally applicable models for relative quantification and inter-run calibration with proper error propagation along the entire calculation track. These models and algorithms are implemented in qBase, a free program for the management and automated analysis of qPCR data.     

Simultaneous determination of thermodynamic and kinetic data by isothermal titration calorimetry

BackgroundThermodynamic and binding kinetic data increasingly support and guide the drug optimization process.MethodsBecause ITC thermograms contain binding thermodynamic and kinetic information, an efficient protocol for the simultaneous extraction of thermodynamic and kinetic data for 1:1 protein ligand reactions from AFFINImeter kinITC in one single experiment are presented.ResultsThe effort to apply this protocol requires the same time as for the standard protocol but increases the precision of both thermodynamic and kinetic data.ConclusionsThe protocol enables reliable extraction of both thermodynamic and kinetic data for 1:1 protein-ligand binding reactions with improved precision compared to the ‘standard protocol’.General significanceThermodynamic and kinetic data are recorded under exactly the same conditions in solution without any labeling or immobilization from a protein sample that is not 100% active and would otherwise render the extraction of kinetic parameters impossible.     

Standard apparent reduction potentials of biochemical half reactions and thermodynamic data on the species involved

Standard apparent reduction potentials E' degrees of half reactions of enzyme-catalyzed reactions are useful because they provide a global view of the apparent equilibrium constants of redox reactions. A table of E' degrees at a specified pH shows at a glance whether a given half reaction will drive another half reaction or be driven by it. This table can be used to calculate apparent equilibrium constants. Standard Gibbs energies of formation of species in a half reaction can be used to calculate E' degrees values at pHs in the range 5-9 and ionic strengths in the range of 0-0.35 M. My previously published values of E' degrees values for 42 half reactions has been extended by 22 new E' degrees values in this paper. When DeltafG degrees and DeltafH degrees are both known for all the species in an enzyme-catalyzed reaction at 298.15 K, it is possible to calculate all the standard transformed thermodynamic properties of the reaction over a range of pHs, ionic strengths, and temperatures.     

A novel thermodynamic relationship based on Kramers Theory for studying enzyme kinetics under high viscosity

In most studies of enzyme kinetics it has been found sufficient to use the classical Transition State Theory (TST) of Eyring and others. This theory was based on the solvent being an ideal dilute substance treated as a heat bath. However, enzymes found in organisms adapted to very low (psychrophiles) and very high (thermophiles) temperatures are also subjected to variable solute concentrations and viscosities. Therefore, the TST may not always be applicable to enzyme reactions carried out in various solvents with viscosities ranging from moderate to very high. There have been numerous advances in the theory of chemical reactions in realistic non-ideal solvents such as Kramers Theory. In this paper we wish to propose a modified thermodynamic equation, which have contributions from kcat, Km and the viscosity of the medium in which the enzyme reaction is occurring. These could be very useful for determining the thermodynamics of enzymes catalyzing reactions at temperature extremes in the presence of substrate solutions of different compositions and viscosities.     

Cell ontology in an age of data-driven cell classification

Background

Data-driven cell classification is becoming common and is now being implemented on a massive scale by projects such as the Human Cell Atlas. The scale of these efforts poses a challenge. How can the results be made searchable and accessible to biologists in general? How can they be related back to the rich classical knowledge of cell-types, anatomy and development? How will data from the various types of single cell analysis be made cross-searchable? Structured annotation with ontology terms provides a potential solution to these problems. In turn, there is great potential for using the outputs of data-driven cell classification to structure ontologies and integrate them with data-driven cell query systems.

Results

Focusing on examples from the mouse retina and Drosophila olfactory system, I present worked examples illustrating how formalization of cell ontologies can enhance querying of data-driven cell-classifications and how ontologies can be extended by integrating the outputs of data-driven cell classifications.

Conclusions

Annotation with ontology terms can play an important role in making data driven classifications searchable and query-able, but fulfilling this potential requires standardized formal patterns for structuring ontologies and annotations and for linking ontologies to the outputs of data-driven classification.

     

An enzyme electrode for on-line determination of ethanol and methanol

Since a stable alcohol oxidase with a high specific activity is not commercially available, we propose to produce and purify this enzyme from a strain of the yeast Hansenula polymorpha. This alcohol oxidase was immobilized into a gelatin matrix and its activity was estimated by a pO(2) sensor. The enzyme electrode obtained was then used in a continuous flow system to measure methanol or ethanol concentrations. The sample oxygen content dependence of the signal was minimized by the support properties. Measuring time for each sample were less than two minutes including response data treatment and rinsing step. The enzyme electrode response was set for ethanol from 0.5mM to 15mM and for methanol from 10mM to 300mM. On repeated use, the electrode signal for 10mM of ethanol was stable for at least 500 assays. Analysis have been performed in different beverages such as wine and beer, and the results compared to those obtained with classical methods of analysis.     

Normalization in the fitting of data by iterative methods. Application to tracer kinetics and enzyme kinetics

1. The normalization of biochemical data to weight them appropriately for parameter estimation is considered, with reference particularly to data from tracer kinetics and enzyme kinetics. If the data are in replicate, it is recommended that the sum of squared deviations for each experimental variable at each time or concentration point is divided by the local variance at that point. 2. If there is only one observation for each variable at each sampling point, normalization may still be required if the observations cover more than one order of magnitude, but there is no absolute criterion for judging the effect of the weighting that is produced. The goodness of fit that is produced by minimizing the weighted sum of squares of deviations must be judged subjectively. It is suggested that the goodness of fit may be regarded as satisfactory if the data points are distributed uniformly on either side of the fitted curve. A chi-square test may be used to decide whether the distribution is abnormal. The proportion of the residual variance associated with points on one or other side of the fitted curve may also be taken into account, because this gives an indication of the sensitivity of the residual variance to movement of the curve away from particular data points. These criteria for judging the effect of weighting are only valid if the model equation may reasonably be expected to apply to all the data points. 3. On this basis, normalizing by dividing the deviation for each data point by the experimental observation or by the equivalent value calculated by the model equation may both be shown to produce a consistent bias for numerically small observations, the former biasing the curve towards the smallest observations, the latter tending to produce a curve that is above the numerically smaller data points. It was found that dividing each deviation by the mean of observed and calculated variable appropriate to it produces a weighting that is fairly free from bias as judged by the criteria mentioned above. This normalization factor was tested on published data from both tracer kinetics and enzyme kinetics.     

An XML message broker framework for exchange and integration of microarray data

MOTIVATION: Microarrays are an important research tool for the advancement of basic biological sciences. However this technology has yet to be integrated with clinical decision making. We have implemented an information framework based on the Microarray Gene Expression Markup Language (MAGE-ML) specification. We are using this framework to develop a test-bed integrated database application to identify genomic and imaging markers for diagnosis of breast cancer. RESULTS: We developed extensible software architecture for retrieving data from different microarray databases using MAGE-ML and for combining microarray data with breast cancer image analysis and clinical data for correlation studies. The framework we developed will provide the necessary data integration to move microarray research from basic biological sciences to clinical applications. AVAILABILITY: Open source software will be available from SourceForge (http://sourceforge.net/projects/microsoap/).     

Phototransduction in cones: An inverse problem in enzyme kinetics

Phototransduction is a process which links the absorption of photons by a rod or cone to the modulation of voltage across the cell membrane. An important feature of many vertebrate photoreceptors is a mechanism that adjusts the sensitivity and dynamics of the response to light according to the level of illumination. We construct a system of ordinary differential equations that models what are currently thought to be the important molecule mechanisms involved in phototransduction: this includes consideration of both intracellular enzyme kinetics and the properties of light-insensitive and light-sensitive conductances in the cone membrane. The system contains negative feedback whose functional form is determined by constraining the steady-state behaviour of the system. Despite the highly nonlinear nature of the system of ordinary differential equations, our methods permit us to derive an analytic expression for the first-order frequency response parametric in the steady-state value of only one dynamic variable, the light input. Various unknown kinetic parameters are found by fitting the model to experimental data on the first-order frequency response of cones measured at several mean light levels spanning a range of four log units. Good fits are obtained to the data, and the computed shape of the feedback function agrees qualitatively with recent experiment. Moreover, the model accounts for the dramatic speeding up of the response kinetics and the decrease in response gain with increasing light level.     

An approach for classification of highly imbalanced data using weighting and undersampling

Real-world datasets commonly have issues with data imbalance. There are several approaches such as weighting, sub-sampling, and data modeling for handling these data. Learning in the presence of data imbalances presents a great challenge to machine learning. Techniques such as support-vector machines have excellent performance for balanced data, but may fail when applied to imbalanced datasets. In this paper, we propose a new undersampling technique for selecting instances from the majority class. The performance of this approach was evaluated in the context of several real biological imbalanced data. The ratios of negative to positive samples vary from ~9:1 to ~100:1. Useful classifiers have high sensitivity and specificity. Our results demonstrate that the proposed selection technique improves the sensitivity compared to weighted support-vector machine and available results in the literature for the same datasets.