Literature DB >> 20960026

Direct concentration and viability measurement of yeast in corn mash using a novel imaging cytometry method.

Leo L Chan1, Emily J Lyettefi, Alnoor Pirani, Tim Smith, Jean Qiu, Bo Lin.   

Abstract

Worldwide awareness of fossil-fuel depletion and global warming has been increasing over the last 30 years. Numerous countries, including the USA and Brazil, have introduced large-scale industrial fermentation facilities for bioethanol, biobutanol, or biodiesel production. Most of these biofuel facilities perform fermentation using standard baker's yeasts that ferment sugar present in corn mash, sugar cane, or other glucose media. In research and development in the biofuel industry, selection of yeast strains (for higher ethanol tolerance) and fermentation conditions (yeast concentration, temperature, pH, nutrients, etc.) can be studied to optimize fermentation performance. Yeast viability measurement is needed to identify higher ethanol-tolerant yeast strains, which may prolong the fermentation cycle and increase biofuel output. In addition, yeast concentration may be optimized to improve fermentation performance. Therefore, it is important to develop a simple method for concentration and viability measurement of fermenting yeast. In this work, we demonstrate an imaging cytometry method for concentration and viability measurements of yeast in corn mash directly from operating fermenters. It employs an automated cell counter, a dilution buffer, and staining solution from Nexcelom Bioscience to perform enumeration. The proposed method enables specific fluorescence detection of viable and nonviable yeasts, which can generate precise results for concentration and viability of yeast in corn mash. This method can provide an essential tool for research and development in the biofuel industry and may be incorporated into manufacturing to monitor yeast concentration and viability efficiently during the fermentation process.

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Year:  2010        PMID: 20960026     DOI: 10.1007/s10295-010-0890-7

Source DB:  PubMed          Journal:  J Ind Microbiol Biotechnol        ISSN: 1367-5435            Impact factor:   3.346


  22 in total

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Review 5.  Flow cytometry: a clinical test of platelet function.

Authors:  A D Michelson
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6.  Flow cytometry and cell sorting for yeast viability assessment and cell selection.

Authors:  D Deere; J Shen; G Vesey; P Bell; P Bissinger; D Veal
Journal:  Yeast       Date:  1998-01-30       Impact factor: 3.239

7.  Genetic dissection of ethanol tolerance in the budding yeast Saccharomyces cerevisiae.

Authors:  X H Hu; M H Wang; T Tan; J R Li; H Yang; L Leach; R M Zhang; Z W Luo
Journal:  Genetics       Date:  2006-12-28       Impact factor: 4.562

8.  Buffering capacity of whole corn mash alters concentrations of organic acids required to inhibit growth of Saccharomyces cerevisiae and ethanol production.

Authors:  Derek A Abbott; W M Ingledew
Journal:  Biotechnol Lett       Date:  2004-08       Impact factor: 2.461

9.  Identification and characterization of nesfatin-1 immunoreactivity in endocrine cell types of the rat gastric oxyntic mucosa.

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Journal:  Endocrinology       Date:  2008-09-25       Impact factor: 4.736

Review 10.  Biofuels from microbes.

Authors:  Dominik Antoni; Vladimir V Zverlov; Wolfgang H Schwarz
Journal:  Appl Microbiol Biotechnol       Date:  2007-09-22       Impact factor: 4.813

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  6 in total

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Authors:  Leo L Chan; Alisha R Wilkinson; Benjamin D Paradis; Ning Lai
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2.  A novel concentration and viability detection method for Brettanomyces using the Cellometer image cytometry.

Authors:  Brian Martyniak; Jason Bolton; Dmitry Kuksin; Suzanne M Shahin; Leo Li-Ying Chan
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Authors:  Daniel J Laverty; Alexandria L Kury; Dmitry Kuksin; Alnoor Pirani; Kevin Flanagan; Leo Li-Ying Chan
Journal:  J Ind Microbiol Biotechnol       Date:  2013-04-05       Impact factor: 3.346

4.  Novel image cytometric method for detection of physiological and metabolic changes in Saccharomyces cerevisiae.

Authors:  Leo L Chan; Alexandria Kury; Alisha Wilkinson; Charlotte Berkes; Alnoor Pirani
Journal:  J Ind Microbiol Biotechnol       Date:  2012-08-05       Impact factor: 3.346

5.  Fast automated yeast cell counting algorithm using bright-field and fluorescence microscopic images.

Authors:  Dongpyo Hong; Gwanghee Lee; Neon Cheol Jung; Moongu Jeon
Journal:  Biol Proced Online       Date:  2013-11-11       Impact factor: 3.244

6.  Mechanisms of Biased β-Arrestin-Mediated Signaling Downstream from the Cannabinoid 1 Receptor.

Authors:  Francheska Delgado-Peraza; Kwang H Ahn; Carlos Nogueras-Ortiz; Imran N Mungrue; Ken Mackie; Debra A Kendall; Guillermo A Yudowski
Journal:  Mol Pharmacol       Date:  2016-03-23       Impact factor: 4.436

  6 in total

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