Limits...
High-throughput metabolic screening of microalgae genetic variation in response to nutrient limitation.

Bajhaiya AK, Dean AP, Driver T, Trivedi DK, Rattray NJ, Allwood JW, Goodacre R, Pittman JK - Metabolomics (2015)

Bottom Line: Limitation of nutrients including nitrogen and phosphorus can induce metabolic changes in microalgae, including the accumulation of glycerolipids and starch.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.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester, M13 9PT UK.

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.

No MeSH data available.


Related in: MedlinePlus

FT-IR spectroscopy screening of wild type and mutant strains in response to P and N limitation. Principal component analysis (PCA) (a, b) and PC-discriminant function analysis (PC-DFA) (c, d) of FT-IR spectra (1780–950 cm−1) derived from strains cultured in replete or limited concentrations of P (high or low P), indicated by blue symbols and red symbols, respectively (a, c), and in replete or limited concentrations of N (high or low N), indicated by blue symbols and green symbols, respectively (b, d). Each symbol represents the average of 3 technical replicates per biological sample. Different symbols each represent 3 biological replicates of each wild type and mutant strain. For this plot snrk2.1 and snrk2.2 have been categorized together as ‘snrk’. PCA loading plots of PC1 (bold) and PC2 (dashed) corresponding to high and low P (a) and high and low N (b) data are shown below the PCA scores plots (Color figure online)
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Fig3: FT-IR spectroscopy screening of wild type and mutant strains in response to P and N limitation. Principal component analysis (PCA) (a, b) and PC-discriminant function analysis (PC-DFA) (c, d) of FT-IR spectra (1780–950 cm−1) derived from strains cultured in replete or limited concentrations of P (high or low P), indicated by blue symbols and red symbols, respectively (a, c), and in replete or limited concentrations of N (high or low N), indicated by blue symbols and green symbols, respectively (b, d). Each symbol represents the average of 3 technical replicates per biological sample. Different symbols each represent 3 biological replicates of each wild type and mutant strain. For this plot snrk2.1 and snrk2.2 have been categorized together as ‘snrk’. PCA loading plots of PC1 (bold) and PC2 (dashed) corresponding to high and low P (a) and high and low N (b) data are shown below the PCA scores plots (Color figure online)

Mentions: FT-IR spectra were collected from triplicates of all strains under all three growth conditions and analysed by PCA separately for P and N limitation. For clarity in the presented PCA plots, all of the snrk2.1 and snrk2.2 mutants are categorised together and indicated by identical symbols (e.g. all nine snrk2.1, snrk2.2-1 and snrk2.2-2 single mutant samples are indicated by crosses; snrk single mutants, while all nine psr1 snrk2.1, psr1 snrk2.2-1 and psr1 snrk2.2-2 double mutant samples are indicated by circles; psr1 snrk double mutants). Under high P conditions (blue symbols) the spectra from most of the mutants clustered close with the wild type, although the psr1 single mutant was slightly separated along PC1 (blue triangles) (Fig. 3a). However, under low P conditions many of the different mutant backgrounds were clearly separated. The spectra from the low P wild type (red squares) were clearly separated from high P wild type (blue squares) along PC1, with this PC determined in part by increased peaks particularly at wavenumbers ~1050 and 1036 cm−1, and the snrk2.1 and snrk2.2 single mutants showed an equivalent low-P response and were grouped with low P wild type. The snrk2.1 snrk2.2-1 double mutant strains also separated from the high P strains along PC1 but were also clustered away from wild type and snrk2.1 and snrk2.2 single mutants. All of the strains with a psr1 mutant background under low P conditions clustered very differently to low P wild type and were identical to the high P strains on the basis of PC1, but could still be distinguished from high P strains on the basis of PC2, determined partly by an increase in the peak at wavenumber ~1740 cm−1 and no increase in peaks at ~1160–1036 cm−1 (Fig. 3a). The single psr1 mutant (red triangles) was again separated from the other strains. However, the ability to discriminate the wild type and mutant strains was markedly reduced under N limitation conditions. All low N strains showed a clear separation with the high N strains on the basis of PC1 (partly determined by increases at wavenumbers ~1740, 1050 and 1036 cm−1, and decreases at wavenumbers ~1655 and 1545 cm−1) but there was less clear-cut separation amongst the low N strains (green symbols) along PC2 (Fig. 3b). Interestingly, the psr1 snrk2.2-1 double mutant (green circles) could be distinguished from wild type and other mutant strains.Fig. 3


High-throughput metabolic screening of microalgae genetic variation in response to nutrient limitation.

Bajhaiya AK, Dean AP, Driver T, Trivedi DK, Rattray NJ, Allwood JW, Goodacre R, Pittman JK - Metabolomics (2015)

FT-IR spectroscopy screening of wild type and mutant strains in response to P and N limitation. Principal component analysis (PCA) (a, b) and PC-discriminant function analysis (PC-DFA) (c, d) of FT-IR spectra (1780–950 cm−1) derived from strains cultured in replete or limited concentrations of P (high or low P), indicated by blue symbols and red symbols, respectively (a, c), and in replete or limited concentrations of N (high or low N), indicated by blue symbols and green symbols, respectively (b, d). Each symbol represents the average of 3 technical replicates per biological sample. Different symbols each represent 3 biological replicates of each wild type and mutant strain. For this plot snrk2.1 and snrk2.2 have been categorized together as ‘snrk’. PCA loading plots of PC1 (bold) and PC2 (dashed) corresponding to high and low P (a) and high and low N (b) data are shown below the PCA scores plots (Color figure online)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
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Fig3: FT-IR spectroscopy screening of wild type and mutant strains in response to P and N limitation. Principal component analysis (PCA) (a, b) and PC-discriminant function analysis (PC-DFA) (c, d) of FT-IR spectra (1780–950 cm−1) derived from strains cultured in replete or limited concentrations of P (high or low P), indicated by blue symbols and red symbols, respectively (a, c), and in replete or limited concentrations of N (high or low N), indicated by blue symbols and green symbols, respectively (b, d). Each symbol represents the average of 3 technical replicates per biological sample. Different symbols each represent 3 biological replicates of each wild type and mutant strain. For this plot snrk2.1 and snrk2.2 have been categorized together as ‘snrk’. PCA loading plots of PC1 (bold) and PC2 (dashed) corresponding to high and low P (a) and high and low N (b) data are shown below the PCA scores plots (Color figure online)
Mentions: FT-IR spectra were collected from triplicates of all strains under all three growth conditions and analysed by PCA separately for P and N limitation. For clarity in the presented PCA plots, all of the snrk2.1 and snrk2.2 mutants are categorised together and indicated by identical symbols (e.g. all nine snrk2.1, snrk2.2-1 and snrk2.2-2 single mutant samples are indicated by crosses; snrk single mutants, while all nine psr1 snrk2.1, psr1 snrk2.2-1 and psr1 snrk2.2-2 double mutant samples are indicated by circles; psr1 snrk double mutants). Under high P conditions (blue symbols) the spectra from most of the mutants clustered close with the wild type, although the psr1 single mutant was slightly separated along PC1 (blue triangles) (Fig. 3a). However, under low P conditions many of the different mutant backgrounds were clearly separated. The spectra from the low P wild type (red squares) were clearly separated from high P wild type (blue squares) along PC1, with this PC determined in part by increased peaks particularly at wavenumbers ~1050 and 1036 cm−1, and the snrk2.1 and snrk2.2 single mutants showed an equivalent low-P response and were grouped with low P wild type. The snrk2.1 snrk2.2-1 double mutant strains also separated from the high P strains along PC1 but were also clustered away from wild type and snrk2.1 and snrk2.2 single mutants. All of the strains with a psr1 mutant background under low P conditions clustered very differently to low P wild type and were identical to the high P strains on the basis of PC1, but could still be distinguished from high P strains on the basis of PC2, determined partly by an increase in the peak at wavenumber ~1740 cm−1 and no increase in peaks at ~1160–1036 cm−1 (Fig. 3a). The single psr1 mutant (red triangles) was again separated from the other strains. However, the ability to discriminate the wild type and mutant strains was markedly reduced under N limitation conditions. All low N strains showed a clear separation with the high N strains on the basis of PC1 (partly determined by increases at wavenumbers ~1740, 1050 and 1036 cm−1, and decreases at wavenumbers ~1655 and 1545 cm−1) but there was less clear-cut separation amongst the low N strains (green symbols) along PC2 (Fig. 3b). Interestingly, the psr1 snrk2.2-1 double mutant (green circles) could be distinguished from wild type and other mutant strains.Fig. 3

Bottom Line: Limitation of nutrients including nitrogen and phosphorus can induce metabolic changes in microalgae, including the accumulation of glycerolipids and starch.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.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester, M13 9PT UK.

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.

No MeSH data available.


Related in: MedlinePlus