Abstract
Microalgae produce metabolites that could be useful for applications in food, biofuel or fine chemical production. The identification and development of suitable strains require analytical methods that are accurate and allow rapid screening of strains or cultivation conditions. We demonstrate the use of Fourier transform infrared (FT-IR) spectroscopy to screen mutant strains of Chlamydomonas reinhardtii. These mutants have knockdowns for one or more nutrient starvation response genes, namely PSR1, SNRK2.1 and SNRK2.2. Limitation of nutrients including nitrogen and phosphorus can induce metabolic changes in microalgae, including the accumulation of glycerolipids and starch. By performing multivariate statistical analysis of FT-IR spectra, metabolic variation between different nutrient limitation and non-stressed conditions could be differentiated. A number of mutant strains with similar genetic backgrounds could be distinguished from wild type when grown under specific nutrient limited and replete conditions, demonstrating the sensitivity of FT-IR spectroscopy to detect specific genetic traits. Changes in lipid and carbohydrate between strains and specific nutrient stress treatments were validated by other analytical methods, including liquid chromatography–mass spectrometry for lipidomics. These results demonstrate that the PSR1 gene is an important determinant of lipid and starch accumulation in response to phosphorus starvation but not nitrogen starvation. However, the SNRK2.1 and SNRK2.2 genes are not as important for determining the metabolic response to either nutrient stress. We conclude that FT-IR spectroscopy and chemometric approaches provide a robust method for microalgae screening.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-015-0878-4) contains supplementary material, which is available to authorized users.
Highlights
Algae have long been recognized as a promising resource for biotechnological applications, such as a source of nutritional supplements like omega-3 fatty acids or carotenoids, or as a feedstock for biofuel generation (Driver et al 2014; Guccione et al 2014; Guedes et al 2011; Larkum et al 2012)
We demonstrate the use of Fourier transform infrared (FTIR) spectroscopy to screen mutant strains of Chlamydomonas reinhardtii
We demonstrate here that multivariate analysis of Fourier transform infrared (FT-IR) spectra can clearly discriminate between the tested wild type and mutant lines of C. reinhardtii and in particular distinguish all lines with a psr1 mutant background
Summary
Algae have long been recognized as a promising resource for biotechnological applications, such as a source of nutritional supplements like omega-3 fatty acids or carotenoids, or as a feedstock for biofuel generation (Driver et al 2014; Guccione et al 2014; Guedes et al 2011; Larkum et al 2012). Some species of microalgae are good sources of carbohydrates, Several conventional methods of metabolite quantification including thin layer chromatography, high-performance liquid chromatography (HPLC), and gas chromatography (GC), often coupled with mass spectrometry (MS), are not amenable for highthroughput screening due to high cost and the requirement for large amounts of biomass, as well as the need for cell extraction and preparation, which can be time-consuming and technically laborious. There are alternative analytical methods that are more suitable for metabolomic screening of strain collections One of these is Fourier transform infrared (FT-IR) spectroscopy, which is a rapid, high-throughput and non-destructive analytical method that provides a robust metabolic fingerprint of a sample (Ellis et al 2012). The complex spectral data can be analysed using multivariate statistical tools to identify metabolic characteristics that are diagnostic markers for a particular trait (Dean et al 2010; Ellis et al 2002; Nicolaou and Goodacre 2008) such as oil production, starch production, or other primary or secondary metabolites
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