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A comparative study: the impact of different lipid extraction methods on current microalgal lipid research.

ABSTRACT: Microalgae cells have the potential to rapidly accumulate lipids, such as triacylglycerides that contain fatty acids important for high value fatty acids (e.g., EPA and DHA) and/or biodiesel production. However, lipid extraction methods for microalgae cells are not well established, and there is currently no standard extraction method for the determination of the fatty acid content of microalgae. This has caused a few problems in microlagal biofuel research due to the bias derived from different extraction methods. Therefore, this study used several extraction methods for fatty acid analysis on marine microalga Tetraselmis sp. M8, aiming to assess the potential impact of different extractions on current microalgal lipid research. These methods included classical Bligh & Dyer lipid extraction, two other chemical extractions using different solvents and sonication, direct saponification and supercritical CO? extraction. Soxhlet-based extraction was used to weigh out the importance of solvent polarity in the algal oil extraction. Coupled with GC/MS, a Thermogravimetric Analyser was used to improve the quantification of microalgal lipid extractions. Among these extractions, significant differences were observed in both, extract yield and fatty acid composition. The supercritical extraction technique stood out most for effective extraction of microalgal lipids, especially for long chain unsaturated fatty acids. The results highlight the necessity for comparative analyses of microalgae fatty acids and careful choice and validation of analytical methodology in microalgal lipid research.

SUBMITTER: Li Y

PROVIDER: S-EPMC3926349 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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A comparative study: the impact of different lipid extraction methods on current microalgal lipid research.

Li Yan Y Li Yan Y Ghasemi Naghdi Forough F Garg Sourabh S Adarme-Vega Tania Catalina TC Thurecht Kristofer J KJ Ghafor Wael Abdul WA Tannock Simon S Schenk Peer M PM

Microbial cell factories 20140124

Microalgae cells have the potential to rapidly accumulate lipids, such as triacylglycerides that contain fatty acids important for high value fatty acids (e.g., EPA and DHA) and/or biodiesel production. However, lipid extraction methods for microalgae cells are not well established, and there is currently no standard extraction method for the determination of the fatty acid content of microalgae. This has caused a few problems in microlagal biofuel research due to the bias derived from different ...[more]

PMID: 24456581

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Project description:Plant proteins with improved solubility, foaming, and emulsifying properties are required to meet the demand for plant-based foods. This study evaluated the influence of alkaline extraction combined with enzyme- and ultrasound-assisted extraction on lentil protein structure and functionality. Enzyme- and ultrasound-assisted extractions were not capable of increasing the protein yield compared to alkaline extraction alone. However, the purity of isolated protein was dependent on the extraction process, ranging from 82.7% to 90%. Although the molecular mass, zeta potential profiles, and denaturation temperature were not dependent on the extraction method, the enthalpy of denaturation for protein obtained solely by alkaline extraction was significantly lower than that for assisted processes, indicating that protein denaturation is caused by an alkaline process. Changes in protein structure were also suggested by solubility analyses that showed that lentil proteins obtained by enzyme-assisted and ultrasound-assisted extraction have better solubility at pH 7 when compared to alkaline extraction alone. The surface activity of lentil protein was evidenced by interfacial and surface analysis, and it was influenced by the extraction process applied. We demonstrated that combining alkaline extraction with assisted processes, especially ultrasound technology, results in concentrates/isolates with higher solubility as compared to ones obtained solely by the traditional alkaline method, even though the choice of extraction method should depend on the desired functionality. Highlights • Proteins from lentil were efficiently recovered by alkaline extraction.• Lentil protein solubility was improved by ultrasound and enzyme extraction.• Lentil protein surface activity was dependent on the extraction process.• Foaming properties were improved by ultrasound extraction.• Emulsifying properties were not influenced by the extraction process. Ultrasound-assisted; Enzyme-assisted; Viscozyme L; Plant protein; Functional properties.

Project description:The bacterial communities associated with microalgae are vital for the growth and health of the host, and engineering algal microbiomes can enhance the fitness of the algae. Characterization of these microbiomes mostly relies on sequencing of DNA, which can be extracted with an array of protocols that potentially impact DNA quantity and quality and thus potentially affect subsequent analyses of microbiome composition. Here, we extracted DNA from Isochrysis galbana, Tetraselmis suecica, and Conticribra weissflogii microbiomes using four different protocols. DNA yield and quality was greatly impacted by the choice of extraction protocol, whereas microbiome composition determined by 16S rRNA gene amplicon sequencing was only impacted to a minor degree, with microalgal host species being the main determinant of microbiome composition. The I. galbana microbiome was dominated by the genus Alteromonas, whereas the microbiome associated with T. suecica was dominated by Marinobacteraceae and Rhodobacteraceae family members. While these two families were also prevalent in the microbiome associated with C. weissflogii, Flavobacteriaceae and Cryomorphaceae were also highly dominant. Phenol-chloroform extraction resulted in higher DNA quality and quantity compared to commercial kits; however, because they have other advantages such as high throughput and low toxicity, commercial kits can be employed to great benefit for the characterization of microalgal microbiomes. IMPORTANCE Microalgae are very important as primary producers in the ocean, but also as forthcoming sustainable producers of biotechnologically interesting compounds. Accordingly, the bacterial microbiomes associated with microalgae are attracting increasing attention due to their effects on the growth and health of microalgae. Since most members of these microbiomes cannot be cultured, knowledge about community composition is best obtained using sequencing-based methods. This study evaluates the impact of DNA extraction methods on DNA quantity and quality along with sequence-based characterization of the bacterial microbiome composition of three microalgae: Isochrysis galbana, Tetraselmis suecica, and Conticribra weissflogii.

Project description:BackgroundVariable selection for regression models plays a key role in the analysis of biomedical data. However, inference after selection is not covered by classical statistical frequentist theory, which assumes a fixed set of covariates in the model. This leads to over-optimistic selection and replicability issues.MethodsWe compared proposals for selective inference targeting the submodel parameters of the Lasso and its extension, the adaptive Lasso: sample splitting, selective inference conditional on the Lasso selection (SI), and universally valid post-selection inference (PoSI). We studied the properties of the proposed selective confidence intervals available via R software packages using a neutral simulation study inspired by real data commonly seen in biomedical studies. Furthermore, we present an exemplary application of these methods to a publicly available dataset to discuss their practical usability.ResultsFrequentist properties of selective confidence intervals by the SI method were generally acceptable, but the claimed selective coverage levels were not attained in all scenarios, in particular with the adaptive Lasso. The actual coverage of the extremely conservative PoSI method exceeded the nominal levels, and this method also required the greatest computational effort. Sample splitting achieved acceptable actual selective coverage levels, but the method is inefficient and leads to less accurate point estimates. The choice of inference method had a large impact on the resulting interval estimates, thereby necessitating that the user is acutely aware of the goal of inference in order to interpret and communicate the results.ConclusionsDespite violating nominal coverage levels in some scenarios, selective inference conditional on the Lasso selection is our recommended approach for most cases. If simplicity is strongly favoured over efficiency, then sample splitting is an alternative. If only few predictors undergo variable selection (i.e. up to 5) or the avoidance of false positive claims of significance is a concern, then the conservative approach of PoSI may be useful. For the adaptive Lasso, SI should be avoided and only PoSI and sample splitting are recommended. In summary, we find selective inference useful to assess the uncertainties in the importance of individual selected predictors for future applications.

Dataset Information

A comparative study: the impact of different lipid extraction methods on current microalgal lipid research.

Publications

A comparative study: the impact of different lipid extraction methods on current microalgal lipid research.

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