Proteome scale turnover analysis in live animals using stable isotope metabolic labeling

At present most quantitative proteomics investigations are focused on the analysis of protein expression differences between two or more sample specimens. With each analysis a static snapshot of a cellular state is captured with regard to protein expression. However, any information on protein turnover cannot be obtained using classic methodologies. Protein turnover, the result of protein synthesis and degradation, represents a dynamic process, which is of equal importance to understanding physiological processes. Methods employing isotopic tracers have been developed to measure protein turnover. However, applying these methods to live animals is often complicated by the fact that an assessment of precursor pool relative isotope abundance is required. Also, data analysis becomes difficult in case of low label incorporation, which results in a complex convolution of labeled and unlabeled peptide mass spectrometry signals. Here we present a protein turnover analysis method that circumvents this problem using a (15)N-labeled diet as an isotopic tracer. Mice were fed with the labeled diet for limited time periods and the resulting partially labeled proteins digested and subjected to tandem mass spectrometry. For the interpretation of the mass spectrometry data, we have developed the ProTurnyzer software that allows the determination of protein fractional synthesis rates without the need of precursor relative isotope abundance information. We present results validating ProTurnyzer with Escherichia coli protein data and apply the method to mouse brain and plasma proteomes for automated turnover studies.     

Synthesis/degradation ratio mass spectrometry for measuring relative dynamic protein turnover

One of the major unanswered questions in quantitative proteomics is that of dynamic protein turnover in the cell. Here we present a new approach to quantitative proteomics that measures the relative dynamic turnover of proteins in cellular systems. In this approach, termed synthesis/degradation ratio mass spectrometry, stable isotope labeling is employed to calculate a relative synthesis/degradation ratio that reflects the relative rate at which 13C is incorporated into individual proteins in the cell. This synthesis/degradation ratio calculation is based on a Poisson distribution model that is designed to support high-throughput analysis. Protein separation and analysis is accomplished by utilizing one-dimensional SDS-PAGE gel electrophoresis followed by cutting the gel into a series of bands for in-gel digestion. The resulting peptide mixtures are analyzed via solid-phase MALDI LC-MS and LC-MS/MS using a tandem time-of-flight mass spectrometer. A portion of the soluble protein fraction from an E. coli K-12 strain was analyzed with synthesis/degradation ratios varying from approximately 0.1 to 4.4 for a variety of different proteins. Unlike other quantitative techniques, synthesis/degradation ratio mass spectrometry requires only a single cell culture to obtain useful biological information about the processes occurring inside a cell. This technique is highly amenable to shotgun proteomics-based approaches and thus should allow relative turnover measurements for whole proteomes in the future.     

Quantitative analysis of isotope distributions in proteomic mass spectrometry using least-squares Fourier transform convolution

Quantitative proteomic mass spectrometry involves comparison of the amplitudes of peaks resulting from different isotope labeling patterns, including fractional atomic labeling and fractional residue labeling. We have developed a general and flexible analytical treatment of the complex isotope distributions that arise in these experiments, using Fourier transform convolution to calculate labeled isotope distributions and least-squares for quantitative comparison with experimental peaks. The degree of fractional atomic and fractional residue labeling can be determined from experimental peaks at the same time as the integrated intensity of all of the isotopomers in the isotope distribution. The approach is illustrated using data with fractional (15)N-labeling and fractional (13)C-isoleucine labeling. The least-squares Fourier transform convolution approach can be applied to many types of quantitative proteomic data, including data from stable isotope labeling by amino acids in cell culture and pulse labeling experiments.     

SILACtor: software to enable dynamic SILAC studies

Stable isotope labeling by amino acids in cell culture (SILAC) is a versatile tool in proteomics that has been used to explore protein turnover on a large scale. However, these studies pose a significant undertaking that can be greatly simplified through the use of computational tools that automate the data analysis. While SILAC technology has enjoyed rapid adoption through the availability of several software tools, algorithms do not exist for the automated analysis of protein turnover data generated using SILAC technology. Presented here is a software tool, SILACtor, designed to trace and compare SILAC-labeled peptides across multiple time points. SILACtor is used to profile protein turnover rates for more than 500 HeLa cell proteins using a SILAC label-chase approach. Additionally, SILACtor contains a method for the automated generation of accurate mass and retention time inclusion lists that target peptides of interest showing fast or slow turnover rates relative to the other peptides observed in the samples. SILACtor enables improved protein turnover studies using SILAC technology and also provides a framework for features extensible to comparative SILAC analyses and targeted methods.     

改进的灰色模型在光催化数据预测中的应用

光催化去除水中污染物的研究通常得到的是小样本的离散数据,利用拟一级动力学模型对实验结果进行模拟和分析,有时拟合效果较差,且无法用于数据预测.本研究在离散灰色预测模型(DGM(1,1))的基础上,考虑数据的非线性特征并结合等维信息替代思想建立了非线性动态离散灰色模型(EDGM(1,1,α)),利用该模型对三元复合材料Bi...     

Designing experiments to understand the variability in biochemical reaction networks

Exploiting the information provided by the molecular noise of a biological process has proved to be valuable in extracting knowledge about the underlying kinetic parameters and sources of variability from single-cell measurements. However, quantifying this additional information a priori, to decide whether a single-cell experiment might be beneficial, is currently only possible in systems where either the chemical master equation is computationally tractable or a Gaussian approximation is appropriate. Here, we provide formulae for computing the information provided by measured means and variances from the first four moments and the parameter derivatives of the first two moments of the underlying process. For stochastic kinetic models for which these moments can be either computed exactly or approximated efficiently, the derived formulae can be used to approximate the information provided by single-cell distribution experiments. Based on this result, we propose an optimal experimental design framework which we employ to compare the utility of dual-reporter and perturbation experiments for quantifying the different noise sources in a simple model of gene expression. Subsequently, we compare the information content of a set of experiments which have been performed in an engineered light-switch gene expression system in yeast and show that well-chosen gene induction patterns may allow one to identify features of the system which remain hidden in unplanned experiments.     

Analysis of an apoptotic core model focused on experimental design using artificial data

The activation of caspases is a central mechanism in apoptosis. To gain further insights into complex processes like this, mathematical modelling using ordinary differential equations (ODEs) can be a very powerful research tool. Unfortunately, the lack of measurement data is a common problem in building such kinetic models, because it practically constrains the identifiability of the model parameters. An existing mathematical model of caspase activation during apoptosis was used in order to design future experimental setups that will help to maximise the obtained information. For this purpose, artificial measurement data are generated in silico to simulate potential experiments, and the model is fitted to this data. The model is also analysed using observability gramian and sensitivity analyses. The used analysis methods are compared. The artificial data approach allows one to make conclusions about system properties, identifiability of parameters and the potential information content of additional measurements for the used caspase activation model. The latter facilitates to improve the experimental design of further measurements significantly. The performed analyses reveal that several kinetic parameters are not at all, or only scarcely, identifiable, and that measurements of activated caspase 8 will maximally improve the parameter estimates. Furthermore, we can show that many assays with inhibitor of apoptosis protein (IAP) knockout cells only provide redundant information for our needs and as such do not have to be carried out.     

Critical perspective on the consequences of the limited availability of kinetic data in metabolic dynamic modelling

Detailed kinetic models at the network reaction level are usually constructed using enzymatic mechanistic rate equations and the associated kinetic parameters. However, during the cellular life cycle thousands of different reactions occur, which makes it very difficult to build a detailed large-scale ldnetic model. In this work, we provide a critical overview of specific limitations found during the reconstruction of the central carbon metabolism dynamic model from E. coli (based on kinetic data available). In addition, we provide clues that will hopefully allow the systems biology community to more accurately construct metabolic dynamic models in the future. The difficulties faced during the construction of dynamic models are due not only to the lack of kinetic information but also to the fact that some data are still not curated. We hope that in the future, with the standardization of the in vitro enzyme protocols the approximation of in vitro conditions to the in vivo ones, it will be possible to integrate the available kinetic data into a complete large scale model. We also expect that collaborative projects between modellers and biologists will provide valuable kinetic data and permit the exchange of important information to solve most of these issues.     

Inverse 18O labeling mass spectrometry for the rapid identification of marker/target proteins

Systematic analysis of proteins is essential in understanding human diseases and their clinical treatments. To achieve the rapid and unambiguous identification of marker or target proteins, a new procedure termed "inverse labeling" is proposed. With this procedure, to evaluate protein expression of a diseased or a drug-treated sample in comparison with a control sample, two converse labeling experiments are performed in parallel. The perturbed sample (by disease or by drug treatment) is labeled in one experiment, whereas the control is labeled in the second experiment. When mixed and analyzed with its unlabeled counterpart for differential comparison using mass spectrometry, a characteristic inverse labeling pattern of mass shift will be observed between the two parallel analyses for proteins that are differentially expressed. In this study, protein labeling is achieved through 18O incorporation into peptides by proteolysis performed in [18O]water. Once the peptides are identified with the characteristic inverse labeling pattern of 18O/16O ion intensity shift, MS data of peptide fingerprints or peptide sequence information can be used to search a protein database for protein identification. The methodology has been applied successfully to two model systems in this study. It permits quick focus on the signals of differentially expressed proteins. It eliminates the detection ambiguities caused by the dynamic range of detection on proteins of extreme changes in expression. It enables the detection of protein modifications responding to perturbation. This strategy can also be extended to other protein-labeling methods, such as chemical or metabolic labeling, to realize the same benefits.     

Mechanistic studies on enzymatic reactions by electrospray ionization MS using a capillary mixer with adjustable reaction chamber volume for time-resolved measurements

Mass spectrometry (MS)-based techniques have enormous potential for kinetic studies on enzyme-catalyzed processes. In particular, the use of electrospray ionization (ESI) MS for steady-state measurements is well established. However, there are very few reports of MS-based studies in the pre-steady-state regime, because it is difficult to achieve the time resolution required for this type of experiment. We have recently developed a capillary mixer with adjustable reaction chamber volume for kinetic studies by ESI-MS with millisecond time resolution (Wilson, D. J.; Konermann, L. Anal. Chem. 2003, 75, 6408-6414). Data can be acquired in kinetic mode, where the concentrations of selected reactive species are monitored as a function of time, or in spectral mode, where entire mass spectra are obtained for selected reaction times. Here, we describe the application of this technique to study the kinetics of enzyme reactions. The hydrolysis of p-nitrophenyl acetate by chymotrypsin was chosen as a simple chromophoric model system. On-line addition of a "makeup solvent" immediately prior to ionization allowed the pre-steady-state accumulation of acetylated chymotrypsin to be monitored. The rate constant for acetylation, as well as the dissociation constant of the enzyme-substrate complex obtained from these data, is in excellent agreement with results obtained by conventional stopped-flow methods. Bradykinin was chosen to illustrate the performance of the ESI-MS-based method with a nonchromophoric substrate. In this case, the unfavorable rate constant ratio for acylation and deacylation of the enzyme precluded measurements in the pre-steady-state regime. Steady-state experiments were carried out to determine the turnover number and the Michaelis constant for bradykinin. The methodologies used in this work open a wide range of possibilities for future ESI-MS-based kinetic assays in enzymology.     

Determination of global protein turnover in stressed mycobacterium cells using hybrid-linear ion trap-fourier transform mass spectrometry

We determined the global protein turnover profiles for Mycobacterium smegmatis under acid shock and iron starvation conditions using a simple (15)N isotope doping technique and a complete medium replacement method for chasing. We used a high-resolution hybrid-linear ion trap-Fourier transform mass spectrometer coupled with nanoliquid chromatography separation to measure protein turnover values for 151 proteins over a dynamic range of 3 orders of magnitude ranging from about 0.2 to 500. Of these 151 proteins, 31 had significant protein turnover changes (p <0.05) at both stress conditions and had protein turnover values increased or decreased by more than 2-fold under at least one stress condition. Protein turnover increased under acid shock for 28 of the 31 proteins but decreased under iron starvation for all the 31 proteins. Only two proteins had protein turnover lowered by more than 2-fold (p <0.05) under both stress conditions, including an ATP synthase F1 beta subunit (MSMEG4921; AtpD) and a catalase/peroxidase (MSMEG6346; KatG). KatG is required for in vivo activation of isoniazid to be bacterialcidal. Decrease of KatG protein turnover under both stress conditions supports the view that isoniazid may induce a dormancy program in mycobacteria, which in turn limits the efficacy of this drug against dormant subpopulation of mycobacteria. Thus, measuring protein turnover in stressed Mycobacterium cells has implications in understanding drug action and resistance mechanisms.     

Modelling deuterium labelling of lymphocytes with temporal and/or kinetic heterogeneity

To study the kinetics of lymphocytes, models have divided the cell population into subpopulations with different turnover rates. These have been called ‘kinetic heterogeneity models’ so as to distinguish them from ‘temporal heterogeneity models’, in which a cell population may have different turnover rates at different times, e.g. when resting versus when activated. We model labelling curves for temporally heterogeneous populations, and predict that they exhibit equal biphasic up- and downslopes. We show when cells divide only once upon activation, these slopes are dominated by the slowest exponent, yielding underestimates of the average turnover rate. When cells undergo more than one division, the labelling curves allow fitting of the two exponential slopes in the temporal heterogeneity model. The same data can also be described with a two-compartment kinetic heterogeneity model. In both instances, the average turnover rate is correctly estimated. Because both models assume a different cell biology but describe the data equally well, the parameters of either model have no simple biological interpretation, as each parameter could reflect a combination of parameters of another biological process. Thus, even if there are sufficient data to reliably estimate all exponentials, one can only accurately estimate an average turnover rate. We illustrate these issues by re-fitting labelling data from healthy and HIV-infected individuals.     

先进复合材料用环氧树脂的固化反应和化学流变

用等温差示扫描量热法(DSC)研究了HD03环氧树脂在一定温度范围内的固化反应。试验结果表明,该环氧树脂体系的固化动力学符合自催化固化反应模型。由试验确定了模型中的动力学参数。发现在树脂的固化后期,固化反应由化学反应控制转变为扩散控制。用以绝对反应速率理论为基础的化学粘度分析模型研究了较高温度范围内HD03环氧树脂的等温粘度和变温的动态粘度变化。用MCR 300流变仪测量并计算了HD03环氧树脂的等温粘度和动态粘度。理论预测与试验结果相吻合。      

Hydrogen/deuterium scrambling during quadrupole time-of-flight MS/MS analysis of a zinc-binding protein domain

It remains an open question as to whether experiments involving collision-induced dissociation (CID) can provide a viable approach for monitoring spatially resolved deuteration levels in electrosprayed polypeptide ions. A number of laboratories reported the successful application of CID following solution-phase H/D exchange (HDX), whereas others found that H/D scrambling precluded site-specific measurements. The aim of the current work is to help clarify the general feasibility of HDX-CID methods, using a 22-residue zinc-bound protein domain (Zn-ZBD) as model system. Metal binding in Zn-ZBD should confer structural rigidity, and the presence of several basic residues should sequester mobile charge carriers in the gas phase. Both of these factors were expected to suppress the extent of scrambling. HDX was carried out by employing rapid on-line mixing, thereby mimicking conditions typically encountered in kinetic pulse-labeling studies. Quadrupole time-of-flight MS/MS of pulse-labeled Zn-ZBD provides high sequence coverage. However, the measured fragment deuteration levels do not correlate with the known H-bonding pattern of Zn-ZBD, suggesting the occurrence of extensive scrambling. Instead of showing a uniform distribution, the fragment ions reveal a distinct nonrandom pattern of deuteration levels. In the absence of prior information, these data could erroneously be ascribed to the presence of protected sites. However, the observed patterns clearly originate from other factors; possibly they are caused by modulations of the amide CID efficiency by kinetic isotope effects. It is concluded that scrambling does not represent the only conceptual problem in HDX-CID studies and that control experiments on uniformly labeled samples are essential for ruling out interpretation artifacts.     

Quantitative proteomic analysis by accurate mass retention time pairs

Current methodologies for protein quantitation include 2-dimensional gel electrophoresis techniques, metabolic labeling, and stable isotope labeling methods to name only a few. The current literature illustrates both pros and cons for each of the previously mentioned methodologies. Keeping with the teachings of William of Ockham, "with all things being equal the simplest solution tends to be correct", a simple LC/MS based methodology is presented that allows relative changes in abundance of proteins in highly complex mixtures to be determined. Utilizing a reproducible chromatographic separations system along with the high mass resolution and mass accuracy of an orthogonal time-of-flight mass spectrometer, the quantitative comparison of tens of thousands of ions emanating from identically prepared control and experimental samples can be made. Using this configuration, we can determine the change in relative abundance of a small number of ions between the two conditions solely by accurate mass and retention time. Employing standard operating procedures for both sample preparation and ESI-mass spectrometry, one typically obtains under 5 ppm mass precision and quantitative variations between 10 and 15%. The principal focus of this paper will demonstrate the quantitative aspects of the methodology and continue with a discussion of the associated, complementary qualitative capabilities.     

Kinetics of SiHCl3 chemical vapor deposition and fluid dynamic simulations

Though most of the current silicon photovoltaic technology relies on trichlorosilane (SiHCl3) as a precursor gas to deposit Si, only a few studies have been devoted to the investigation of its gas phase and surface kinetics. In the present work we propose a new kinetic mechanism apt to describe the gas phase and surface chemistry active during the deposition of Si from SiHCl3. Kinetic constants of key reactions were either taken from the literature or determined through ab initio calculations. The capability of the mechanism to reproduce experimental data was tested through the implementation of the kinetic scheme in a fluid dynamic model and in the simulation of both deposition and etching of Si in horizontal reactors. The results of the simulations show that the reactivity of HCl is of key importance in order to control the Si deposition rate. When HCl reaches a critical concentration in the gas phase it starts etching the Si surface, so that the net deposition rate is the net sum of the adsorption rate of the gas phase precursors and the etching rate due to HCl. In these conditions the possibility to further deposit Si is directly related to the rate of consumption of HCl through its reaction with SiHCl3 to give SiCl4. The proposed reaction mechanism was implemented in a 3D fluid dynamic model of a simple Siemens reactor. The simulation results indicate that the proposed interpretation of the growth process applies also to this class of reactors, which operate in what can be defined as a mixed kinetic-transport controlled regime.     

Using stable-isotope-labeled proteins for hydrogen exchange studies in complex mixtures

The use of mass spectrometry to measure hydrogen exchange rates for individual proteins in complex mixtures is described. Incorporation of stable-isotope-labeled (SIL) amino acids into a protein of interest during overexpression in bacteria produced distinctive isotope patterns in mass spectra of peptic peptides from the labeled protein. The isotope pattern was used as a signature for peptides originating from the SIL protein. In addition, stable-isotope labeling simplified identification of the peptic peptides by providing partial amino acid composition information. Despite the complex isotope patterns associated with SIL peptides, hydrogen exchange rates could still be measured for peptides from SIL protein and were found to be the same as exchange rates for unlabeled protein. Hydrogen exchange in a single protein of interest was measured in a complex mixture of proteins, a bacterial cell lysate. This methodology, which includes easy recognition of peptic peptides from the protein(s) of interest during hydrogen exchange studies in heterogeneous systems, will permit analysis of structural properties and dynamics of large protein complexes and complex protein systems.     

Sorption of copper(II) ion from aqueous solution by Tectona grandis l.f. (teak leaves powder)

Studies on a batch sorption system using Tectona grandis l.f. as adsorbent was investigated to remove copper(II) from aqueous solutions. The adsorption experiments were performed under various conditions such as different initial concentrations, pH, adsorbent dosage and adsorbent particle size. The data showed that 0.1 g of Tectona grandis l.f. was found to remove 71.66% of 20 mg/L copper(II) from 30 mL aqueous solution in 180 min. The experimental equilibrium data were adjusted by the adsorption isotherms from Langmuir and Freundlich models and their equilibrium parameters were determined. The best-adjusted model to the experimental equilibrium data for Tectona grandis l.f. was the Langmuir model. Using the Langmuir model equation, the monolayer sorption capacity of Tectona grandis l.f. was evaluated and found to be 95.40 mg/g. The optimum pH value was found to be 5.5. The pseudo-first-order and pseudo-second-order kinetic models were used to describe the kinetic data. The dynamic data fitted the pseudo-second-order kinetic model.     

A computational reaction-diffusion model for the analysis of transport-limited kinetics

Optical, evanescent wave biosensors have become popular tools for quantitatively characterizing the kinetic properties of biomolecular interactions. Analyzing data from biosensor experiments, however, is often complicated when mass-transfer influences the detection kinetics. We present a computational, transport-kinetic model that can be used to analyze transport-limited biosensor data. This model describes a typical biosensor experiment in which a soluble analyte diffuses through a flow chamber and binds to a receptor immobilized on the transducer surface. Analyte transport in the flow chamber is described by the diffusion equation while the kinetics of analyte-surface association and dissociation are captured by a reactive boundary condition at the sensor surface. Numerical integration of the model equations and nonlinear least-squares fitting are used to compare model kinetic data to experimental results and generate estimates for the rate constants that describe analyte detection. To demonstrate the feasibility of this model, we use it to analyze data collected for the binding of fluorescently labeled trinitrobenzene to immobilized monoclonal anti-TNT antibodies. A successful analysis of this antigen-antibody interaction is presented for data collected with a fluorescence-based fiber-optic immunoassay. The results of this analysis are compared with the results obtained with existing methods for analyzing diffusion-limited kinetic data.