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

Guillo, Christelle; Barlow, D. J.; Perrett, David; Hanna-Brown, Melissa

doi:10.1016/j.chroma.2003.11.102

Cited by 31 publications

(35 citation statements)

References 49 publications

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“…Prior to daily use, the capillary was rinsed at 207C with 1 M NaOH (3 min), 0.1 M NaOH (3 min) and H 2 O (3 min). The experimental procedure for electrophoresis was based on Guillo et al [18], with slight modifications. Between analyses, the capillary was washed at 207C with 0.1 M NaOH (1 min), water (1 min) and the running buffer (2 min).…”

Section: Ce In Mekc Modementioning

confidence: 99%

“…MEKC, applicable to both ionic and neutral species, has proved to be a useful tool in the study of different target metabolites in urine [15][16][17][18]. However, its application as a nontargeted approach has not yet been fully exploited.…”

Section: Introductionmentioning

confidence: 99%

“…These methods either involve interpolation between aligned reference peaks [28,29] or the alignment of each electropherogram to a reference signal [18,30,31]. Here we combine both approaches and utilise information from several different wavelengths when checking the similarity of aligned electropherograms.…”

Section: Introductionmentioning

confidence: 99%

“…However, its application as a nontargeted approach has not yet been fully exploited. CD-modified MEKC allows the separation of over 80 UVabsorbing endogenous analytes of different charge types (neutral, anionic and cationic) below 25 min [18][19][20]. Since minimal sample pretreatment is required, this methodology has the potential for high-throughput analysis of the large number of samples required in screening applications.…”

mentioning

confidence: 99%

“…CE has recently been incorporated to the family of metabolic fingerprinting techniques used for clinical studies [11][12][13][14]. CE is an efficient and sensitive high-resolution separation technique that allows fast analysis of ionic species and the use of small samples.MEKC, applicable to both ionic and neutral species, has proved to be a useful tool in the study of different target metabolites in urine [15][16][17][18]. However, its application as a nontargeted approach has not yet been fully exploited.…”

mentioning

confidence: 99%

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

Soria

Wright²,

Goodall

et al. 2007

Electrophoresis

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Data processing in metabolic fingerprinting by CE-UV: Application to urine samples from autistic childrenMetabolic 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. Keywords IntroductionMetabolic fingerprinting approaches [1] have recently emerged as a nonbiased alternative to the determination of individual levels of a specific metabolite or class of metabolites in large sets of samples, as is necessary for clinical diagnosis purposes. 1 H-NMR has been widely used in urinary fingerprinting and the search for disease biomarkers [2,3]. The approach has been recently complemented by chromatographic techniques hyphenated to MS (GC-MS and LC-MS), with the advantage over 1 H-NMR of a higher sensitivity [4][5][6][7]. Other spectroscopic techniques used less frequently for urinary fingerprinting include direct injection MS [8,9] and FTIR spectroscopy [10]. CE has recently been incorporated to the family of metabolic fingerprinting techniques used for clinical studies [11][12][13][14]. CE is an efficient and sensitive high-resolution separation technique that allows fast analysis of ionic species and the use of small samples.MEKC, applicable to both ionic and neutral species, has proved to be a useful tool in the study of different target metabolites in urine [15][16][17][18]. However, its application as a nontargeted approach has not yet been fully exploited. CD-modified MEKC allows the separation of over 80 UVabsorbing endogenous analytes of different charge types (neutral, anionic and cationic) below 25 min [18][19][20]. Since minimal sample pretreatment is required, this methodology has the potential for high-throughput analysis of the large number of samples required in screening applications.Urinary fingerprints produced by MEKC are highly complex datasets and require multivariate techniques for interpretation. Unsupervised pattern recognition methods such as cluster analysis and principal component analysis (PCA) have been used to examine the structure of these dataset...

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Section: Ce In Mekc Modementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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

Soria

Wright²,

Goodall

et al. 2007

Electrophoresis

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Do not just do it, do it right: urinary metabolomics –establishing clinically relevant baselines

Trivedi

Iles

2014

Biomedical Chromatography

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Metabolomics is currently being adopted as a tool to understand numerous clinical pathologies. It is essential to choose the best combination of techniques in order to optimize the information gained from the biological sample examined. For example, separation by reverse-phase liquid chromatography may be suitable for biological fluids in which lipids, proteins and small organic compounds coexist in a relatively nonpolar environment, such as serum. However, urine is a highly polar environment and metabolites are often specifically altered to render them polar suitable for normal phase/hydrophilic interaction liquid chromatography. Similarly, detectors such as high-resolution mass spectrometry (MS) may negate the need for a pre-separation but specific detection and quantification of less abundant analytes in targeted metabolomics may require concentration of the ions by methods such an ion trap MS. In addition, the inherent variability of metabolomic profiles need to be established in appropriately large sample sets of normal controls. This review aims to explore various techniques that have been tried and tested over the past decade. Consideration is given to various key drawbacks and positive alternatives published by active research groups and an optimum combination that should be used for urinary metabolomics is suggested to generate a reliable dataset for baseline studies.

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The application of capillary electrophoresis techniques in toxicological analysis

Sieradzka

Witt

Milnerowicz

2014

Biomedical Chromatography

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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.

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

Cited by 31 publications

References 49 publications

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

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

Do not just do it, do it right: urinary metabolomics –establishing clinically relevant baselines

The application of capillary electrophoresis techniques in toxicological analysis

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