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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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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. |
format | Online Article Text |
id | pubmed-4432509 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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