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

被引:34
作者
Bajhaiya, Amit K. [1 ]
Dean, Andrew P. [1 ,2 ]
Driver, Thomas [1 ]
Trivedi, Drupad K. [3 ]
Rattray, Nicholas J. W. [3 ]
Allwood, J. William [3 ,4 ]
Goodacre, Royston [3 ]
Pittman, Jon K. [1 ]
机构
[1] Univ Manchester, Fac Life Sci, Manchester M13 9PT, Lancs, England
[2] Univ Sheffield, Dept Geog, Sheffield S10 2TN, S Yorkshire, England
[3] Univ Manchester, Sch Chem, Manchester Inst Biotechnol, Manchester M1 7DN, Lancs, England
[4] James Hutton Inst, Environm & Biochem Sci Grp, Dundee DD2 5DA, Scotland
基金
英国生物技术与生命科学研究理事会;
关键词
Metabolite screening; FT-IR spectroscopy; Microalgae; Lipids; Starch; Chlamydomonas reinhardtii; TRANSFORM-INFRARED-SPECTROSCOPY; FT-IR SPECTROSCOPY; SULFUR DEPRIVATION RESPONSES; CHLAMYDOMONAS-REINHARDTII; SPECIES IDENTIFICATION; QUANTITATIVE DETECTION; MICROBIAL SPOILAGE; BIOFUEL PRODUCTION; MASS-SPECTROMETRY; PHOSPHORUS;
D O I
10.1007/s11306-015-0878-4
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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 (FTIR) 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.
引用
收藏
页码:1 / 14
页数:14
相关论文
共 46 条
[1]   A workflow for bacterial metabolic fingerprinting and lipid profiling: application to Ciprofloxacin challenged Escherichia coli [J].
Allwood, J. William ;
AlRabiah, Haitham ;
Correa, Elon ;
Vaughan, Andrew ;
Xu, Yun ;
Upton, Mathew ;
Goodacre, Royston .
METABOLOMICS, 2015, 11 (02) :438-453
[2]   Metabolomic approaches reveal that phosphatidic and phosphatidyl glycerol phospholipids are major discriminatory non-polar metabolites in responses by Brachypodium distachyon to challenge by Magnaporthe grisea [J].
Allwood, JW ;
Ellis, DI ;
Heald, JK ;
Goodacre, R ;
Mur, LAJ .
PLANT JOURNAL, 2006, 46 (03) :351-368
[3]   Multiple metabolomics of uropathogenic E-coli reveal different information content in terms of metabolic potential compared to virulence factors [J].
AlRabiah, Haitham ;
Xu, Yun ;
Rattray, Nicholas J. W. ;
Vaughan, Andrew A. ;
Gibreel, Tarek ;
Sayqal, Ali ;
Upton, Mathew ;
Allwood, William ;
Goodacre, Royston .
ANALYST, 2014, 139 (17) :4193-4199
[4]   Metabolite profiling of Chlamydomonas reinhardtii under nutrient deprivation [J].
Bölling, C ;
Fiehn, O .
PLANT PHYSIOLOGY, 2005, 139 (04) :1995-2005
[5]   Discrimination of cyanobacterial strains isolated from saline soils in Nakhon Ratchasirna, Thailand using attenuated total reflectance FTIR spectroscopy [J].
Bounphanmy, Somchanh ;
Thammathaworn, Sompong ;
Thanee, Nathawut ;
Pirapathrungsuriya, Komson ;
Beardall, John ;
McNaughton, Don ;
Heraud, Philip .
JOURNAL OF BIOPHOTONICS, 2010, 3 (8-9) :534-541
[6]   Microalgae-Novel Highly Efficient Starch Producers [J].
Branyikova, Irena ;
Marsalkova, Barbora ;
Doucha, Jiri ;
Branyik, Tomas ;
Bisova, Katerina ;
Zachleder, Vilem ;
Vitova, Milada .
BIOTECHNOLOGY AND BIOENGINEERING, 2011, 108 (04) :766-776
[7]   Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets [J].
Brown, Marie ;
Wedge, David C. ;
Goodacre, Royston ;
Kell, Douglas B. ;
Baker, Philip N. ;
Kenny, Louise C. ;
Mamas, Mamas A. ;
Neyses, Ludwig ;
Dunn, Warwick B. .
BIOINFORMATICS, 2011, 27 (08) :1108-1112
[8]   Development of a forward genetic screen to isolate oil mutants in the green microalga Chlamydomonas reinhardtii [J].
Cagnon, Caroline ;
Mirabella, Boris ;
Hoa Mai Nguyen ;
Beyly-Adriano, Audrey ;
Bouvet, Severine ;
Cuine, Stephan ;
Beisson, Fred ;
Peltier, Gilles ;
Li-Beisson, Yonghua .
BIOTECHNOLOGY FOR BIOFUELS, 2013, 6
[9]   Microalgae As Sources of High Added-Value Compounds-A Brief Review of Recent Work [J].
Catarina Guedes, A. ;
Amaro, Helena M. ;
Xavier Malcata, F. .
BIOTECHNOLOGY PROGRESS, 2011, 27 (03) :597-613
[10]   A high throughput Nile red method for quantitative measurement of neutral lipids in microalgae [J].
Chen, Wei ;
Zhang, Chengwu ;
Song, Lirong ;
Sommerfeld, Milton ;
Hu, Qiang .
JOURNAL OF MICROBIOLOGICAL METHODS, 2009, 77 (01) :41-47