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A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation

Mixed microorganism cultures are prevalent in the food industry. A variety of microbiological mixtures have been used in these unique fermenting processes to create distinctive flavor profiles and potential health benefits. Mixed cultures are typically not well characterized, which may be due to the...

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Autores principales: Williamson, Cecelia, Kennedy, Kevin, Bhattacharya, Sayak, Patel, Samir, Perry, Jennifer, Bolton, Jason, Perkins, Lewis Brian, Chan, Leo Li-Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10124123/
https://www.ncbi.nlm.nih.gov/pubmed/36948609
http://dx.doi.org/10.1093/jimb/kuad007
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author Williamson, Cecelia
Kennedy, Kevin
Bhattacharya, Sayak
Patel, Samir
Perry, Jennifer
Bolton, Jason
Perkins, Lewis Brian
Chan, Leo Li-Ying
author_facet Williamson, Cecelia
Kennedy, Kevin
Bhattacharya, Sayak
Patel, Samir
Perry, Jennifer
Bolton, Jason
Perkins, Lewis Brian
Chan, Leo Li-Ying
author_sort Williamson, Cecelia
collection PubMed
description Mixed microorganism cultures are prevalent in the food industry. A variety of microbiological mixtures have been used in these unique fermenting processes to create distinctive flavor profiles and potential health benefits. Mixed cultures are typically not well characterized, which may be due to the lack of simple measurement tools. Image-based cytometry systems have been employed to automatically count bacteria or yeast cells. In this work, we aim to develop a novel image cytometry method to distinguish and enumerate mixed cultures of yeast and bacteria in beer products. Cellometer X2 from Nexcelom was used to count of Lactobacillus plantarum and Saccharomyces cerevisiae in mixed cultures using fluorescent dyes and size exclusion image analysis algorithm. Three experiments were performed for validation. (1) Yeast and bacteria monoculture titration, (2) mixed culture with various ratios, and (3) monitoring a Berliner Weisse mixed culture fermentation. All experiments were validated by comparing to manual counting of yeast and bacteria colony formation. They were highly comparable with ANOVA analysis showing p-value > 0.05. Overall, the novel image cytometry method was able to distinguish and count mixed cultures consistently and accurately, which may provide better characterization of mixed culture brewing applications and produce higher quality products.
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spelling pubmed-101241232023-04-25 A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation Williamson, Cecelia Kennedy, Kevin Bhattacharya, Sayak Patel, Samir Perry, Jennifer Bolton, Jason Perkins, Lewis Brian Chan, Leo Li-Ying J Ind Microbiol Biotechnol Biotechnology Methods Mixed microorganism cultures are prevalent in the food industry. A variety of microbiological mixtures have been used in these unique fermenting processes to create distinctive flavor profiles and potential health benefits. Mixed cultures are typically not well characterized, which may be due to the lack of simple measurement tools. Image-based cytometry systems have been employed to automatically count bacteria or yeast cells. In this work, we aim to develop a novel image cytometry method to distinguish and enumerate mixed cultures of yeast and bacteria in beer products. Cellometer X2 from Nexcelom was used to count of Lactobacillus plantarum and Saccharomyces cerevisiae in mixed cultures using fluorescent dyes and size exclusion image analysis algorithm. Three experiments were performed for validation. (1) Yeast and bacteria monoculture titration, (2) mixed culture with various ratios, and (3) monitoring a Berliner Weisse mixed culture fermentation. All experiments were validated by comparing to manual counting of yeast and bacteria colony formation. They were highly comparable with ANOVA analysis showing p-value > 0.05. Overall, the novel image cytometry method was able to distinguish and count mixed cultures consistently and accurately, which may provide better characterization of mixed culture brewing applications and produce higher quality products. Oxford University Press 2023-03-22 /pmc/articles/PMC10124123/ /pubmed/36948609 http://dx.doi.org/10.1093/jimb/kuad007 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Society of Industrial Microbiology and Biotechnology. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Biotechnology Methods
Williamson, Cecelia
Kennedy, Kevin
Bhattacharya, Sayak
Patel, Samir
Perry, Jennifer
Bolton, Jason
Perkins, Lewis Brian
Chan, Leo Li-Ying
A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation
title A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation
title_full A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation
title_fullStr A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation
title_full_unstemmed A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation
title_short A novel image-based method for simultaneous counting of Lactobacillus and Saccharomyces in mixed culture fermentation
title_sort novel image-based method for simultaneous counting of lactobacillus and saccharomyces in mixed culture fermentation
topic Biotechnology Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10124123/
https://www.ncbi.nlm.nih.gov/pubmed/36948609
http://dx.doi.org/10.1093/jimb/kuad007
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