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Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions

BACKGROUND: Microalgae provide an excellent platform for the production of high-value-products and are increasingly being recognised as a promising production system for biomass, animal feeds and renewable fuels. RESULTS: Here, we describe an automated screen, to enable high-throughput optimisation...

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Autores principales: Radzun, Khairul Adzfa, Wolf, Juliane, Jakob, Gisela, Zhang, Eugene, Stephens, Evan, Ross, Ian, Hankamer, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4432509/
https://www.ncbi.nlm.nih.gov/pubmed/25984234
http://dx.doi.org/10.1186/s13068-015-0238-7
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author Radzun, Khairul Adzfa
Wolf, Juliane
Jakob, Gisela
Zhang, Eugene
Stephens, Evan
Ross, Ian
Hankamer, Ben
author_facet Radzun, Khairul Adzfa
Wolf, Juliane
Jakob, Gisela
Zhang, Eugene
Stephens, Evan
Ross, Ian
Hankamer, Ben
author_sort Radzun, Khairul Adzfa
collection PubMed
description BACKGROUND: Microalgae provide an excellent platform for the production of high-value-products and are increasingly being recognised as a promising production system for biomass, animal feeds and renewable fuels. RESULTS: Here, we describe an automated screen, to enable high-throughput optimisation of 12 nutrients for microalgae production. Its miniaturised 1,728 multiwell format allows multiple microalgae strains to be simultaneously screened using a two-step process. Step 1 optimises the primary elements nitrogen and phosphorous. Step 2 uses Box-Behnken analysis to define the highest growth rates within the large multidimensional space tested (Ca, Mg, Fe, Mn, Zn, Cu, B, Se, V, Si) at three levels (−1, 0, 1). The highest specific growth rates and maximum OD(750) values provide a measure for continuous and batch culture. CONCLUSION: The screen identified the main nutrient effects on growth, pairwise nutrient interactions (for example, Ca-Mg) and the best production conditions of the sampled statistical space providing the basis for a targeted full factorial screen to assist with optimisation of algae production. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13068-015-0238-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-44325092015-05-16 Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions Radzun, Khairul Adzfa Wolf, Juliane Jakob, Gisela Zhang, Eugene Stephens, Evan Ross, Ian Hankamer, Ben Biotechnol Biofuels Methodology BACKGROUND: Microalgae provide an excellent platform for the production of high-value-products and are increasingly being recognised as a promising production system for biomass, animal feeds and renewable fuels. RESULTS: Here, we describe an automated screen, to enable high-throughput optimisation of 12 nutrients for microalgae production. Its miniaturised 1,728 multiwell format allows multiple microalgae strains to be simultaneously screened using a two-step process. Step 1 optimises the primary elements nitrogen and phosphorous. Step 2 uses Box-Behnken analysis to define the highest growth rates within the large multidimensional space tested (Ca, Mg, Fe, Mn, Zn, Cu, B, Se, V, Si) at three levels (−1, 0, 1). The highest specific growth rates and maximum OD(750) values provide a measure for continuous and batch culture. CONCLUSION: The screen identified the main nutrient effects on growth, pairwise nutrient interactions (for example, Ca-Mg) and the best production conditions of the sampled statistical space providing the basis for a targeted full factorial screen to assist with optimisation of algae production. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13068-015-0238-7) contains supplementary material, which is available to authorized users. BioMed Central 2015-04-11 /pmc/articles/PMC4432509/ /pubmed/25984234 http://dx.doi.org/10.1186/s13068-015-0238-7 Text en © Radzun et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Radzun, Khairul Adzfa
Wolf, Juliane
Jakob, Gisela
Zhang, Eugene
Stephens, Evan
Ross, Ian
Hankamer, Ben
Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions
title Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions
title_full Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions
title_fullStr Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions
title_full_unstemmed Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions
title_short Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions
title_sort automated nutrient screening system enables high-throughput optimisation of microalgae production conditions
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4432509/
https://www.ncbi.nlm.nih.gov/pubmed/25984234
http://dx.doi.org/10.1186/s13068-015-0238-7
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