Literature DB >> 25929796

Analysis of metabolites in single cells-what is the best micro-platform?

Petra Dittrich1, Alfredo J Ibáñez2.   

Abstract

This review covers new innovations and developments in the field of single-cell level analysis of metabolites, involving the role of microfluidic and microarray platforms to manipulate and handle the cells prior their detection. Microfluidic and microarray platforms have shown great promise. The latest developments demonstrate their potential to identify a particular cell or even an ensemble of cells (sharing a common property or phenotype) that co-exist in a much larger cell population. The reason for this is the capability of these platforms to perform several complex analytical processes, such as: cleanup, sorting, derivatization, separation, and detection, with great robustness, speed, and reduced sample/reagent consumption. Here, we present several examples that illustrate the rapid strides that have been made for the routine analysis of metabolites by coupling different microfluidics and microarrays devices to a wide range of analytical detectors (e.g. fluorescent microscopy, electrochemical, and mass spectrometry). Herein, we also present selected examples detailing the use of microfluidics and microarrays in the visualization of the natural occurring cell-to-cell heterogeneity in isogenic populations, in particular during the response to external cues. The possibility to accurate monitor the cell-to-cell heterogeneity based on different levels of key metabolites is of clinical relevance, since cell-to-cell heterogeneity can influence, for example, the outcome of a drug treatment.
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  Lab-on-a-chip/Metabolomics/Microarrays/Microfluidics/Single-cell analysis

Year:  2015        PMID: 25929796     DOI: 10.1002/elps.201500045

Source DB:  PubMed          Journal:  Electrophoresis        ISSN: 0173-0835            Impact factor:   3.535


  5 in total

Review 1.  Asymmetric Cell Division in T Lymphocyte Fate Diversification.

Authors:  Janilyn Arsenio; Patrick J Metz; John T Chang
Journal:  Trends Immunol       Date:  2015-10-20       Impact factor: 16.687

2.  A breath of information: the volatilome.

Authors:  M Mansurova; Birgitta E Ebert; Lars M Blank; Alfredo J Ibáñez
Journal:  Curr Genet       Date:  2017-12-26       Impact factor: 3.886

Review 3.  Single-cell approaches for molecular classification of endocrine tumors.

Authors:  James Koh; Nancy L Allbritton; Julie A Sosa
Journal:  Curr Opin Oncol       Date:  2016-01       Impact factor: 3.645

4.  On-line pre-treatment, separation, and nanoelectrospray mass spectrometric determinations for pesticide metabolites and peptides based on a modular microfluidic platform.

Authors:  Yinyin Hao; Yajing Bao; Xueying Huang; Yijun Hu; Bo Xiong
Journal:  RSC Adv       Date:  2018-11-28       Impact factor: 3.361

5.  Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks.

Authors:  Elisa Valletta; Lukáš Kučera; Lubomír Prokeš; Filippo Amato; Tiziana Pivetta; Aleš Hampl; Josef Havel; Petr Vaňhara
Journal:  PLoS One       Date:  2016-01-28       Impact factor: 3.240

  5 in total

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