Micellar electrokinetic capillary chromatography and data alignment analysis: a new tool in urine profiling

Fluorescence photobleaching of urine for improved signal to noise ratio of the Raman signal - An exploratory study

Urine analysis is an important clinical test routinely performed in pathology labs for disease diagnosis and prognosis. In recent years, near-infrared Raman spectroscopy has drawn considerable attention for urine analysis as it can provide rapid, reliable, and reagent-free analysis of urine samples. However, one important practical problem encountered in such Raman measurements is the orders of magnitude stronger spectral background preventing one to utilize the full dynamic range of the detector which is required for the measurement of Raman signal with good signal-to-noise ratio (SNR). We report here the results of an exploratory study carried out on human urine samples to show that the photobleaching, which is a major disadvantage during the fluorescence measurement, could be utilized for suppressing the measured background to improve the SNR of the Raman peaks. It was found that once the photobleaching reached its plateau, there were improvements by ~67% and ~47% in the SNR and the signal to background ratio (SBR), respectively, of the Raman signals as compared to the spectra measured at the start of acquisition. Further, the reduced background also allowed us to utilize the full dynamic range of the detector at increased integration time without saturating the detector indicating the possibility of obtaining an improved detection limit.

Advances in capillary electrophoresis for the life sciences

Capillary electrophoresis (CE) played an important role in developments in the life sciences. The technique is nowadays used for the analysis of both large and small molecules in applications where it performs better than or is complementary to liquid chromatographic techniques. In this review, principles of different electromigration techniques, especially capillary isoelectric focusing (CIEF), capillary gel (CGE) and capillary zone electrophoresis (CZE), are described and recent developments in instrumentation, with an emphasis on mass spectrometry (MS) coupling and microchip CE, are discussed. The role of CE in the life sciences is shown with applications in which it had a high impact over the past few decades. In this context, current practice for the characterization of biopharmaceuticals (therapeutic proteins) is shown with CIEF, CGE and CZE using different detection techniques, including MS. Subsequently, the application of CGE and CZE, in combination with laser induced fluorescence detection and CZE-MS are demonstrated for the analysis of protein-released glycans in the characterization of biopharmaceuticals and glycan biomarker discovery in biological samples. Special attention is paid to developments in capillary coatings and derivatization strategies for glycans. Finally, routine CE analysis in clinical chemistry and latest developments in metabolomics approaches for the profiling of small molecules in biological samples are discussed. The large number of CE applications published for these topics in recent years clearly demonstrates the established role of CE in life sciences.

The application of capillary electrophoresis techniques in toxicological analysis

Capillary electrophoresis (CE) comprises a group of techniques used to separate chemical mixtures. Analytical separation is based on different electrophoretic mobilities, thereby allowing qualitative and quantitative evaluations to be made. The application of CE in medical science, especially in toxicological studies, is developing rapidly because of the short time required for analysis and its high sensitivity, selectivity and ability to determine substances of an acidic, alkaline and neutral character. This review focuses on the possibility of applying CE in toxicological analysis. Advances in different CE analyses and detection techniques connected with this method are described.

Development of a CZE-ESI-MS assay with a sulfonated capillary for profiling picolinic acid and quinolinic acid formation in multienzyme system

This article describes the development of a reliable CZE-ESI-MS method to simultaneously separate and quantitate three specific metabolites (3-hydroxyanthranilic acid (3-HAA), quinolinic acid (QA), and picolinic acid (PA)) of the kynurenine pathway (KP) of tryptophan catabolism. Using a covalently bonded sulfonated capillary, the parameters such as pH, type of background electrolyte, type of organic solvent, nebulizer pressure as well as both negative and positive ESI-MS modes were optimized to achieve the best Rs and S/N of three KP metabolites. The developed CZE-ESI-MS assay provided high resolution of PA/QA, high specificity, a total analysis time of 10 min with satisfactory intraday and interday repeatability of migration time and peak areas. Under optimized CZE-ESI-MS conditions, the calibration curves over a concentration range of 19-300 μM for 3-HAA and QA, and 75-300 μM for PA were simultaneously generated. The method was successfully applied for the first time to profile the concentrations of initial substrate, 3-HAA, and its eventual products, PA and QA, formed in the complex multienzyme system. As the ratio of two enzymes, 3-hydroxyanthranilate 3,4-dioxygenase (HAO) and α-amino-β-carboxymuconate-ε-semialdehyde decarboxylase (ACMSD) decreases, the concentration of QA approaches essentially zero indicating that all ACMS formed by the action of HAO is consumed by ACMSD rather than its spontaneous decay to QA.

Capillary electrophoresis as a metabolomics tool for non-targeted fingerprinting of biological samples

Metabolomics, understood as a data driven strategy trying to find markers of a situation under study without a priori hypothesis, has rapidly caught the attention and evolved from the simple pattern recognition strategy, which was a great innovation at its origins, to the interest for the final identification of markers responsible for class separation, i.e., from data to knowledge. Due to differences in physico-chemical properties and concentrations of the metabolites, but also due to differences in matrix properties, cross-platform approaches are proving to increase the capability of information. Once more techniques do not compete. This is the scene where capillary electrophoresis (CE) has its niche to provide information mainly on polar or ionic compounds in biological fluids. General advantages and disadvantages of CE for sample fingerprinting will be discussed and methods will be classified depending on the detection system (UV or MS) as this strongly affects all the conditions. Recent developments will be presented in different biological fluids, although urine is without a doubt the preferred sample for CE analysis.

MEKC as a powerful growing analytical technique

This review summarizes the principle and the developments in MEKC in terms of separation power, sensitivity, and detection approaches more than 25 years after its appearance. Newly used surfactants are mentioned. Classical and new sample concentration techniques in MEKC are described. The different detection approaches in MEKC with advantages, limitations, and future prospects are also discussed. This review highlights the wider application of MEKC in different analytical fields. Various recent selected applications of this technique in different analytical fields are reported.

Metabolic fingerprinting of Schistosoma mansoni infection in mice urine with capillary electrophoresis

Schistosoma mansoni infection in mice has been fingerprinted using CE to study the capabilities of this technique as a diagnostic tool for this parasitic disease. Two modes of separation were used in generating the electrophoretic data, with each untreated urine sample the following methods were applied: (i) a fused-silica capillary, operating with an applied potential of 18 kV, in micellar EKC (MEKC) and (ii) a polyacrylamide-coated capillary, operating with an applied potential of -20 kV under zonal CZE conditions. By combining normal and reverse polarities in the data treatment we have extracted more information from the samples, which is a better approach for CE metabolomics. The traditional problems associated with variability in electrophoretic peak migration times for analytes were countered by using a dynamic programming algorithm for the electropherograms alignment. Principal component analyses of these aligned electropherograms and partial least square discriminant analysis (PLS-DA) data are shown to provide a valuable means of rapid and sample classification. This approach may become an important tool for the identification of biomarkers, diagnosis and disease surveillance.

Pattern recognition in capillary electrophoresis data using dynamic programming in the wavelet domain

A novel approach for CE data analysis based on pattern recognition techniques in the wavelet domain is presented. Low-resolution, denoised electropherograms are obtained by applying several preprocessing algorithms including denoising, baseline correction, and detection of the region of interest in the wavelet domain. The resultant signals are mapped into character sequences using first derivative information and multilevel peak height quantization. Next, a local alignment algorithm is applied on the coded sequences for peak pattern recognition. We also propose 2-D and 3-D representations of the found patterns for fast visual evaluation of the variability of chemical substances concentration in the analyzed samples. The proposed approach is tested on the analysis of intracerebral microdialysate data obtained by CE and LIF detection, achieving a correct detection rate of about 85% with a processing time of less than 0.3 s per 25,000-point electropherogram. Using a local alignment algorithm on low-resolution denoised electropherograms might have a great impact on high-throughput CE since the proposed methodology will substitute automatic fast pattern recognition analysis for slow, human based time-consuming visual pattern recognition methods.

Capillary electrophoresis as a metabolomic tool in antioxidant therapy studies

The development of an approach by which two CE methods operating with opposite polarities and orthogonal capillary electrophoretic separation modes (method 1: normal polarity cyclodextrin modified MEKC (CD-MEKC) and method 2: reversed polarity CZE) for the sequential application to urinary samples from a type I diabetes metabolomics investigation is discussed. During method development, problematic MEKC profile drift issues arising from the high glucose content of the diabetic animal urine samples required some electrolyte modifications involving the use of hexafluoroisopropanol (HFIP) to circumvent the drift. Data derived from both methods were subsequently subjected to alignment, normalization and multi-dimensional scaling (MDS) procedures. In such a way, classification of samples derived from control and diabetic animals receiving a placebo from those receiving an antioxidant nutraceutical, was successfully demonstrated. Such a strategy is a cost effective and comprehensive metabolomics tool useful for describing UV absorbing metabolite disease-related changes in nutra/pharma-ceutical studies.

Evaluation of different warping methods for the analysis of CE profiles of urinary nucleosides

Nowadays, numerous metabolite concentrations can readily be determined in a given biological sample by high-throughput analytical methods. However, such raw analytical data comprise noninformative components due to many disturbances normally occurring in the analyses of biological material. To eliminate those unwanted original analytical data components, advanced chemometric data preprocessing methods might be of help. Here, such methods are applied to electrophoretic nucleoside profiles in urine samples of cancer patients and healthy volunteers. In this study, three warping methods: dynamic time warping (DTW), correlation optimized warping (COW), and parametric time warping (PTW) were examined on two sets of electrophoretic data by means of quality of peaks alignment, time of preprocessing, and way of customization. The application of warping methods helped to limit shifting of peaks and enabled differentiation between whole electropherograms of healthy and cancer patients objectively by a principal component analysis (PCA). The evaluation of preprocessed data and raw data by PC analysis confirms differences between the applied warping tools and proves their suitability in metabonomic data interpretation.

Data processing in metabolic fingerprinting by CE-UV: Application to urine samples from autistic children

Metabolic fingerprinting of biofluids such as urine can be used to detect and analyse differences between individuals. However, before pattern recognition methods can be utilised for classification, preprocessing techniques for the denoising, baseline removal, normalisation and alignment of electropherograms must be applied. Here a MEKC method using diode array detection has been used for high-resolution separation of both charged and neutral metabolites. Novel and generic algorithms have been developed for use prior to multivariate data analysis. Alignment is achieved by combining the use of reference peaks with a method that uses information from multiple wavelengths to align electropherograms to a reference signal. This metabolic fingerprinting approach by MEKC has been applied for the first time to urine samples from autistic and control children in a nontargeted and unbiased search for markers for autism. Although no biomarkers for autism could be determined using MEKC data here, the general approach presented could also be applied to the processing of other data collected by CE with UV-Vis detection.

Increasing conclusiveness of metabonomic studies by chem-informatic preprocessing of capillary electrophoretic data on urinary nucleoside profiles

Nowadays, bioinformatics offers advanced tools and procedures of data mining aimed at finding consistent patterns or systematic relationships between variables. Numerous metabolites concentrations can readily be determined in a given biological system by high-throughput analytical methods. However, such row analytical data comprise noninformative components due to many disturbances normally occurring in analysis of biological samples. To eliminate those unwanted original analytical data components advanced chemometric data preprocessing methods might be of help. Here, such methods are applied to electrophoretic nucleoside profiles in urine samples of cancer patients and healthy volunteers. The electrophoretic nucleoside profiles were obtained under following conditions: 100 mM borate, 72.5 mM phosphate, 160 mM SDS, pH 6.7; 25 kV voltage, 30 degrees C temperature; untreated fused silica capillary 70 cm effective length, 50 microm I.D. Different most advanced preprocessing tools were applied for baseline correction, denoising and alignment of electrophoretic data. That approach was compared to standard procedure of electrophoretic peak integration. The best results of preprocessing were obtained after application of the so-called correlation optimized warping (COW) to align the data. The principal component analysis (PCA) of preprocessed data provides a clearly better consistency of the nucleoside electrophoretic profiles with health status of subjects than PCA of peak areas of original data (without preprocessing).

Urine profiling using capillary electrophoresis-mass spectrometry and multivariate data analysis

This work presents the development of a general and fast method for metabolic profiling of urine, using capillary electrophoresis-electrospray ionisation mass spectrometry (CE-ESIMS) and multivariate data analysis (DA). Human urine samples collected before and after ingestion of paracetamol were analysed at acidic and basic CE conditions, using both positive and negative ESI-MS detection. Analysis of the entire resulting data set, with no prior knowledge of the target compounds, using pair-wise 'fuzzy' correlation and eigenvalue analysis enabled the samples to be discriminated between on the basis of blank urine and urine collected after drug intake. By generating two-dimensional loadings plots, it was also possible to identify the m/z values of the substances responsible for the differentiation between control and dosed samples.

Progressive peak clustering in GC-MS Metabolomic experiments applied to Leishmania parasites

MOTIVATION

A common problem in the emerging field of metabolomics is the consolidation of signal lists derived from metabolic profiling of different cell/tissue/fluid states where a number of replicate experiments was collected on each state.

RESULTS

We describe an approach for the consolidation of peak lists based on hierarchical clustering, first within each set of replicate experiments and then between the sets of replicate experiments. The problems of finding the dendrogram tree cutoff which gives the optimal number of peak clusters and the effect of different clustering methods were addressed. When applied to gas chromatography-mass spectrometry metabolic profiling data acquired on Leishmania mexicana, this approach resulted in robust data matrices which completely separated the wild-type and two mutant parasite lines based on their metabolic profile.

Urinary electrophoretic profiles from chronic fatigue syndrome and chronic fatigue syndrome/fibromyalgia patients: a pilot study for achieving their normalization

Aim of our study was to determine if there were distinct, disease-related patterns of urinary analytes in chronic fatigue syndrome (CFS) and chronic fatigue syndrome/fibromyalgia (CFS/FM) compared to normal controls (NC). Urine was collected from these subjects for two consecutive 24 h periods and aliquots were submitted to micellar electrokinetic chromatography (MEKC). To compensate for the differences in peak migration times, these were normalized from the 35 min duration of run to a 100-point scale, and each peak was assigned its normalized time measure. Peak heights were also normalized by dividing the mAU by that of the internal standard (creatinine) and multiplying by 100. MEKC with normalization for peak height and migration time generated comparable results within each of the patient groups. CFS/FM and CFS had significant differences in peaks compared to NC that may be of significance as biomarkers of illnesses.

Recent advances in micellar electrokinetic chromatography

This review contains nearly 200 reference citations, and covers advances in electrokinetic capillary chromatography based on micelles, including stabilized micelle complexes, polymeric and mixed micelles from 2003-2004. Detection strategies, analyte determinations, and applications in micellar electrokinetic capillary chromatography (MEKC) are discussed. Information regarding methods of analyte concentration, analyte specific analyses, and nonstandard micelles has been summarized in tabular form to provide a means of rapid access to information pertinent to the reader.

Micellar electrokinetic chromatographic and capillary zone electrophoretic methods for screening urinary biomarkers of human disorders: a critical review of the state-of-the-art

Human urine plays a central role in clinical diagnostic being one of the most-frequently used body fluid for detection of biological markers. Samples from patients with different diseases display patterns of biomarkers that differ significantly from those obtained from healthy subjects. The availability of fast, reproducible, and easy-to-apply analytical techniques that would allow identification of a large number of these analytes is thus highly desiderable since they may provide detailed information about the progression of a pathological process. From among the variety of methods so far applied for the determination of urinary metabolites, capillary electrophoresis, both in the capillary zone electrophoresis (CZE) and micellar electrokinetic chromatography (MEKC) modes, represents a robust and reliable analytical tool widely used in this area. The aim of the present article is to focus the interest of the reader on recent applications of MEKC and CZE in the field of urinary biomarkers and to discuss advantages and/or limitations of each mode.

Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS

An overview is presented of gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS), the two major hyphenated techniques employed in metabolic profiling that complement direct 'fingerprinting' methods such as atmospheric pressure ionization (API) quadrupole time-of-flight MS, API Fourier transform MS, and NMR. In GC/MS, the analytes are normally derivatized prior to analysis in order to reduce their polarity and facilitate chromatographic separation. The electron ionization mass spectra obtained are reproducible and suitable for library matching, mass spectral collections being readily available. In LC/MS, derivatization and library matching are at an early stage of development and mini-reviews are provided. Chemical derivatization can dramatically increase the sensitivity and specificity of LC/MS methods for less polar compounds and provides additional structural information. The potential of derivatization for metabolic profiling in LC/MS is demonstrated by the enhanced analysis of plant extracts, including the potential to measure volatile acids such as formic acid, difficult to achieve by GC/MS. The important role of mass spectral library creation and usage in these techniques is discussed and illustrated by examples.