iMS2Flux--a high-throughput processing tool for stable isotope labeled mass spectrometric data used for metabolic flux analysis.

BACKGROUND: Metabolic flux analysis has become an established method in systems biology and functional genomics. The most common approach for determining intracellular metabolic fluxes is to utilize mass spectrometry in combination with stable isotope labeling experiments. However, before the mass spectrometric data can be used it has to be corrected for biases caused by naturally occurring stable isotopes, by the analytical technique(s) employed, or by the biological sample itself. Finally the MS data and the labeling information it contains have to be assembled into a data format usable by flux analysis software (of which several dedicated packages exist). Currently the processing of mass spectrometric data is time-consuming and error-prone requiring peak by peak cut-and-paste analysis and manual curation. In order to facilitate high-throughput metabolic flux analysis, the automation of multiple steps in the analytical workflow is necessary. RESULTS: Here we describe iMS2Flux, software developed to automate, standardize and connect the data flow between mass spectrometric measurements and flux analysis programs. This tool streamlines the transfer of data from extraction via correction tools to ¹³C-Flux software by processing MS data from stable isotope labeling experiments. It allows the correction of large and heterogeneous MS datasets for the presence of naturally occurring stable isotopes, initial biomass and several mass spectrometry effects. Before and after data correction, several checks can be performed to ensure accurate data. The corrected data may be returned in a variety of formats including those used by metabolic flux analysis software such as 13CFLUX, OpenFLUX and 13CFLUX2. CONCLUSION: iMS2Flux is a versatile, easy to use tool for the automated processing of mass spectrometric data containing isotope labeling information. It represents the core framework for a standardized workflow and data processing. Due to its flexibility it facilitates the inclusion of different experimental datasets and thus can contribute to the expansion of flux analysis applications.

A Markov-chain model for the analysis of high-resolution enzymatically 18O-labeled mass spectra.

The enzymatic 18O-labeling is a useful quantification technique to account for between-spectrum variability of the results of mass spectrometry experiments. One of the important issues related to the use of the technique is the problem of incomplete labeling of peptide molecules, which may result in biased estimates of the relative peptide abundance. In this manuscript, we propose a Markov-chain model, which takes into account the possibility of incomplete labeling in the estimation of the relative abundance from the observed data. This allows for the use of less precise but faster labeling strategies, which should better fit in the high-throughput proteomic framework. Our method does not require extra experimental steps, as proposed in the approaches developed by Mirgorodskaya et al. (2000), López-Ferrer et al. (2006) and Rao et al. (2005), while it includes the model proposed by Eckel-Passow et al. (2006) as a special case. The method estimates information about the isotopic distribution directly from the observed data and is able to account for biases induced by the different sulphur content in peptides as reported by Johnson and Muddiman (2004). The method is integrated in a statistically sound framework and allows for the calculation of the errors on the parameter estimates based on model theory. In this manuscript, we describe the methodology in a technical matter and assess the properties of the algorithm via a thorough simulation study. The method is also tested on a limited dataset; more intense validation and investigation of the operational characteristics is being scheduled.

Labeling strategies in mass spectrometry-based protein quantitation.

Mass spectrometry-based techniques for relative and absolute protein quantitation have advanced greatly over the past decade. New measurement strategies and improvements to existing methodologies have expanded the utility of mass spectrometry-based characterization of protein expression profiles, in particular by targeting a diverse array of chemical functionality (e.g. post-translational modifications, specific amino acid residues, etc.) by selective stable isotope incorporation. This article focuses on current trends in stable isotope labeling for protein quantitation using enzymatic, metabolic, and chemical derivatization techniques. Furthermore, new advances in phosphoproteomic labeling and lanthanide-based labeling methods are described.

13C labeling experiments at metabolic nonstationary conditions: an exploratory study.

BACKGROUND: Stimulus Response Experiments to unravel the regulatory properties of metabolic networks are becoming more and more popular. However, their ability to determine enzyme kinetic parameters has proven to be limited with the presently available data. In metabolic flux analysis, the use of 13C labeled substrates together with isotopomer modeling solved the problem of underdetermined networks and increased the accuracy of flux estimations significantly. RESULTS: In this contribution, the idea of increasing the information content of the dynamic experiment by adding 13C labeling is analyzed. For this purpose a small example network is studied by simulation and statistical methods. Different scenarios regarding available measurements are analyzed and compared to a non-labeled reference experiment. Sensitivity analysis revealed a specific influence of the kinetic parameters on the labeling measurements. Statistical methods based on parameter sensitivities and different measurement models are applied to assess the information gain of the labeled stimulus response experiment. CONCLUSION: It was found that the use of a (specifically) labeled substrate will significantly increase the parameter estimation accuracy. An overall information gain of about a factor of six is observed for the example network. The information gain is achieved from the specific influence of the kinetic parameters towards the labeling measurements. This also leads to a significant decrease in correlation of the kinetic parameters compared to an experiment without 13C-labeled substrate.

Statistical identification of differentially labeled peptides from liquid chromatography tandem mass spectrometry.

LC-MS/MS with certain labeling techniques such as isotope-coded affinity tag (ICAT) enables quantitative analysis of paired protein samples. However, current identification and quantification of differentially expressed peptides (and proteins) are not reliable for large proteomics screening of complex biological samples. The number of replicates is often limited because of the high cost of experiments and the limited supply of samples. Traditionally, a simple fold change cutoff is used, which results in a high rate of false positives. Standard statistical methods such as the two-sample t-test are unreliable and severely underpowered due to high variability in LC-MS/MS data, especially when only a small number of replicates are available. Using an advanced error pooling technique, we propose a novel statistical method that can reliably identify differentially expressed proteins while maintaining a high sensitivity, particularly with a small number of replicates. The proposed method was applied both to an extensive simulation study and a proteomics comparison between microparticles (MPs) generated from platelet (platelet MPs) and MPs isolated from plasma (plasma MPs). In these studies, we show a significant improvement of our statistical analysis in the identification of proteins that are differentially expressed but not detected by other statistical methods. In particular, several important proteins - two peptides for beta-globin and three peptides for von Willebrand Factor (vWF) - were identified with very small false discovery rates (FDRs) by our method, while none was significant when other conventional methods were used. These proteins have been reported with their important roles in microparticles in human blood cells: vWF is a platelet and endothelial cell product that binds to P-selectin, GP1b, and GP IIb/IIIa, and beta-globin is one of the peptides of hemoglobin involved in the transportation of oxygen by red blood cells.

Automated statistical analysis of protein abundance ratios from data generated by stable-isotope dilution and tandem mass spectrometry.

We describe an algorithm for the automated statistical analysis of protein abundance ratios (ASAPRatio) of proteins contained in two samples. Proteins are labeled with distinct stable-isotope tags and fragmented, and the tagged peptide fragments are separated by liquid chromatography (LC) and analyzed by electrospray ionization (ESI) tandem mass spectrometry (MS/MS). The algorithm utilizes the signals recorded for the different isotopic forms of peptides of identical sequence and numerical and statistical methods, such as Savitzky-Golay smoothing filters, statistics for weighted samples, and Dixon's test for outliers, to evaluate protein abundance ratios and their associated errors. The algorithm also provides a statistical assessment to distinguish proteins of significant abundance changes from a population of proteins of unchanged abundance. To evaluate its performance, two sets of LC-ESI-MS/MS data were analyzed by the ASAPRatio algorithm without human intervention, and the data were related to the expected and manually validated values. The utility of the ASAPRatio program was clearly demonstrated by its speed and the accuracy of the generated protein abundance ratios and by its capability to identify specific core components of the RNA polymerase II transcription complex within a high background of copurifying proteins.

Marcación de un anticuerpo monoclonal con 99mTc por medio del grupo 99cTcN: evaluación de un modelo biológico / 99mTC labeling of a monoclonal antibody via a 99mTcN group: a biological model evaluation

El anticuerpo monoclonal (AcMo) anti-CEA B2C114 fue marcado con 99mTc utilizando uno de los métodos directos de marcación, en el cual la proteína (AcMo IgG1) se reuce utilizando una solución de Ditiotreitol (DTT) para generar grupos sulfhidrilos, uniendo el 99mTc a los mismos a través del anión [99mTcNCl4]- preparado por calentamiento a reflujo de pertecneciato en presencia de azida sódica y HCl conc. El exceso de DTT se eliminó pasando el AcMo reducido por Sephadex G-25 y del mismo modo se realizó la purificación del anticuerpo marcado. Las cromatografías en TLC y Whatman Nº1 usando Metanol 85 por ciento y solución fisiológica como solventes, mostraron una actividad unida a proteínas entre 55-60 por ciento, obteniéndose luego de la purificación por Sephadex G-25 un producto con 90-95 por ciento de pureza radioquímica. Se realizó la biodistribución en ratones Balb/c a las 21 h post inyección obteniéndose una relación de 2:1 de la dosis inyectada por gramo de tejido, con respecto al tumor reactivo:no reactivo. El ensayo de unión realizado demostró que el AcMo conservó su actividad biológica después de marcado

Marcación de un anticuerpo monoclonal con 99mTc por medio del grupo 99cTcN: evaluación de un modelo biológico / 99mTC labeling of a monoclonal antibody via a 99mTcN group: a biological model evaluation

El anticuerpo monoclonal (AcMo) anti-CEA B2C114 fue marcado con 99mTc utilizando uno de los métodos directos de marcación, en el cual la proteína (AcMo IgG1) se reuce utilizando una solución de Ditiotreitol (DTT) para generar grupos sulfhidrilos, uniendo el 99mTc a los mismos a través del anión [99mTcNCl4]- preparado por calentamiento a reflujo de pertecneciato en presencia de azida sódica y HCl conc. El exceso de DTT se eliminó pasando el AcMo reducido por Sephadex G-25 y del mismo modo se realizó la purificación del anticuerpo marcado. Las cromatografías en TLC y Whatman Nº1 usando Metanol 85 por ciento y solución fisiológica como solventes, mostraron una actividad unida a proteínas entre 55-60 por ciento, obteniéndose luego de la purificación por Sephadex G-25 un producto con 90-95 por ciento de pureza radioquímica. Se rea