Literature DB >> 32737554

Microfluidic Single-Cell Analytics.

Christian Dusny1.   

Abstract

What is the impact of cellular heterogeneity on process performance? How do individual cells contribute to averaged process productivity? Single-cell analysis is a key technology for answering such key questions of biotechnology, beyond bulky measurements with populations. The analysis of cellular individuality, its origins, and the dependency of process performance on cellular heterogeneity has tremendous potential for optimizing biotechnological processes in terms of metabolic, reaction, and process engineering. Microfluidics offer unmatched environmental control of the cellular environment and allow massively parallelized cultivation of single cells. However, the analytical accessibility to a cell's physiology is of crucial importance for obtaining the desired information on the single-cell production phenotype. Highly sensitive analytics are required to detect and quantify the minute amounts of target analytes and small physiological changes in a single cell. For their application to biotechnological questions, single-cell analytics must evolve toward the measurement of kinetics and specific rates of the smallest catalytic unit, the single cell. In this chapter, we focus on an introduction to the latest single-cell analytics and their application for obtaining physiological parameters in a biotechnological context from single cells. We present and discuss recent advancements in single-cell analytics that enable the analysis of cell-specific growth, uptake, and production kinetics, as well as the gene expression and regulatory mechanisms at a single-cell level.
© 2020. Springer Nature Switzerland AG.

Entities:  

Keywords:  Analytics; Biochemical engineering; Microfluidics; Single-cell analysis; Whole-cell biocatalysis

Mesh:

Year:  2022        PMID: 32737554     DOI: 10.1007/10_2020_134

Source DB:  PubMed          Journal:  Adv Biochem Eng Biotechnol        ISSN: 0724-6145            Impact factor:   2.768


  150 in total

Review 1.  Industrial biocatalysis today and tomorrow.

Authors:  A Schmid; J S Dordick; B Hauer; A Kiener; M Wubbolts; B Witholt
Journal:  Nature       Date:  2001-01-11       Impact factor: 49.962

2.  Re-birth of microbial physiology.

Authors:  Julian Davies
Journal:  Environ Microbiol       Date:  2002-01       Impact factor: 5.491

Review 3.  Single cell analytics: an overview.

Authors:  Hendrik Kortmann; Lars M Blank; Andreas Schmid
Journal:  Adv Biochem Eng Biotechnol       Date:  2011       Impact factor: 2.635

Review 4.  Systems biotechnology for strain improvement.

Authors:  Sang Yup Lee; Dong-Yup Lee; Tae Yong Kim
Journal:  Trends Biotechnol       Date:  2005-07       Impact factor: 19.536

5.  Multidimensional optimality of microbial metabolism.

Authors:  Robert Schuetz; Nicola Zamboni; Mattia Zampieri; Matthias Heinemann; Uwe Sauer
Journal:  Science       Date:  2012-05-04       Impact factor: 47.728

Review 6.  A systems biology approach to optimising hosts for industrial protein production.

Authors:  Kate Royle; Cleo Kontoravdi
Journal:  Biotechnol Lett       Date:  2013-07-27       Impact factor: 2.461

7.  Metabolic capacity estimation of Escherichia coli as a platform for redox biocatalysis: constraint-based modeling and experimental verification.

Authors:  Lars M Blank; Birgitta E Ebert; Bruno Bühler; Andreas Schmid
Journal:  Biotechnol Bioeng       Date:  2008-08-15       Impact factor: 4.530

Review 8.  Whole-cell biocatalysis for selective and productive C-O functional group introduction and modification.

Authors:  Manfred Schrewe; Mattijs K Julsing; Bruno Bühler; Andreas Schmid
Journal:  Chem Soc Rev       Date:  2013-08-07       Impact factor: 54.564

Review 9.  Metabolic-flux dependent regulation of microbial physiology.

Authors:  Athanasios Litsios; Álvaro D Ortega; Ernst C Wit; Matthias Heinemann
Journal:  Curr Opin Microbiol       Date:  2017-11-15       Impact factor: 7.934

Review 10.  Microfluidic single-cell analysis in biotechnology: from monitoring towards understanding.

Authors:  Christian Dusny; Alexander Grünberger
Journal:  Curr Opin Biotechnol       Date:  2019-12-04       Impact factor: 9.740

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