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...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BioMed Central Ltd.
2015
|
Subjects: | |
Online Access: | View Fulltext in Publisher View in Scopus |
LEADER | 02976nam a2200589Ia 4500 | ||
---|---|---|---|
001 | 10.1186-s13068-015-0238-7 | ||
008 | 220112s2015 CNT 000 0 und d | ||
020 | |a 17546834 (ISSN) | ||
245 | 1 | 0 | |a Automated nutrient screening system enables high-throughput optimisation of microalgae production conditions |
260 | 0 | |b BioMed Central Ltd. |c 2015 | |
856 | |z View Fulltext in Publisher |u https://doi.org/10.1186/s13068-015-0238-7 | ||
856 | |z View in Scopus |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929335045&doi=10.1186%2fs13068-015-0238-7&partnerID=40&md5=ff292b1ad0542af6a62e713be9ae4ed6 | ||
520 | 3 | |a 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 OD750 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. © 2015 Radzun et al.; licensee BioMed Central. | |
650 | 0 | 4 | |a algae |
650 | 0 | 4 | |a Algae |
650 | 0 | 4 | |a Animalia |
650 | 0 | 4 | |a Batch cell culture |
650 | 0 | 4 | |a biological production |
650 | 0 | 4 | |a biomass |
650 | 0 | 4 | |a Biomass |
650 | 0 | 4 | |a Calcium |
650 | 0 | 4 | |a Ecology |
650 | 0 | 4 | |a fuel |
650 | 0 | 4 | |a Growth |
650 | 0 | 4 | |a Growth (materials) |
650 | 0 | 4 | |a growth response |
650 | 0 | 4 | |a High throughput |
650 | 0 | 4 | |a High-throughput |
650 | 0 | 4 | |a Manganese |
650 | 0 | 4 | |a microalga |
650 | 0 | 4 | |a Microorganisms |
650 | 0 | 4 | |a Multi-dimensional space |
650 | 0 | 4 | |a Nutrient |
650 | 0 | 4 | |a nutrient dynamics |
650 | 0 | 4 | |a Nutrient interactions |
650 | 0 | 4 | |a Nutrients |
650 | 0 | 4 | |a Production system |
650 | 0 | 4 | |a Renewable fuels |
650 | 0 | 4 | |a renewable resource |
650 | 0 | 4 | |a Screening |
650 | 0 | 4 | |a Screening system |
650 | 0 | 4 | |a Specific growth rate |
650 | 0 | 4 | |a Throughput |
650 | 0 | 4 | |a Two-step process |
700 | 1 | 0 | |a Hankamer, B. |e author |
700 | 1 | 0 | |a Jakob, G. |e author |
700 | 1 | 0 | |a Radzun, K.A. |e author |
700 | 1 | 0 | |a Ross, I. |e author |
700 | 1 | 0 | |a Stephens, E. |e author |
700 | 1 | 0 | |a Wolf, J. |e author |
700 | 1 | 0 | |a Zhang, E. |e author |
773 | |t Biotechnology for Biofuels |