Akihito Nakanishi

Optimizing biodiesel production in marine Chlamydomonas sp. JSC4 through metabolic profiling and an innovative salinity-gradient strategy.

BackgroundBiodiesel production from marine microalgae has received much attention as microalgae can be cultivated on non-arable land without the use of potable water, and with the additional benefits of mitigating CO2 emissions and yielding biomass. However, there is still a lack of effective operational strategies to promote lipid accumulation in marine microalgae, which are suitable for making biodiesel since they are mainly composed of saturated and monounsaturated fatty acids. Moreover, the regulatory mechanisms involved in lipid biosynthesis in microalgae under environmental stress are not well understood.ResultsIn this work, the combined effects of salinity and nitrogen depletion stresses on lipid accumulation of a newly isolated marine microalga, Chlamydomonas sp. JSC4, were explored. Metabolic intermediates were profiled over time to observe transient changes during the lipid accumulation triggered by the combination of the two stresses. An innovative cultivation strategy (denoted salinity-gradient operation) was also employed to markedly improve the lipid accumulation and lipid quality of the microalga, which attained an optimal lipid productivity of 223.2 mg L-1 d-1 and a lipid content of 59.4% per dry cell weight. This performance is significantly higher than reported in most related studies.ConclusionsThis work demonstrated the synergistic integration of biological and engineering technologies to develop a simple and effective strategy for the enhancement of oil production in marine microalgae.

Development of lipid productivities under different CO2 conditions of marine microalgae Chlamydomonas sp. JSC4.

Biodiesel production from microalgae has become a popular research topic. In this study, Chlamydomonas sp. JSC4 isolated from the southern coast of Taiwan was selected for a detailed study on cell growth and lipid accumulation under marine salinity (3.5% sea salt). Proper CO2 was supplied as the improvement of lipid productivity. Under the optimal condition, the highest lipid productivity was 169.1mg/L/d, which was significantly higher than those reported in current studies for marine green algae. To date, only very few studies have reported a marine algae strain with both high cell growth and lipid productivity. This study demonstrated that a newly isolated marine green alga Chlamydomonas sp. JSC4 would be a feasible oil producer due to its high biomass production and lipid productivity under marine salinity.

Dynamic metabolic profiling together with transcription analysis reveals salinity-induced starch-to-lipid biosynthesis in alga Chlamydomonas sp. JSC4

Biodiesel production using microalgae would play a pivotal role in satisfying future global energy demands. Understanding of lipid metabolism in microalgae is important to isolate oleaginous strain capable of overproducing lipids. It has been reported that reducing starch biosynthesis can enhance lipid accumulation. However, the metabolic mechanism controlling carbon partitioning from starch to lipids in microalgae remains unclear, thus complicating the genetic engineering of algal strains. We here used “dynamic” metabolic profiling and essential transcription analysis of the oleaginous green alga Chlamydomonas sp. JSC4 for the first time to demonstrate the switching mechanisms from starch to lipid synthesis using salinity as a regulator, and identified the metabolic rate-limiting step for enhancing lipid accumulation (e.g., pyruvate-to-acetyl-CoA). These results, showing salinity-induced starch-to-lipid biosynthesis, will help increase our understanding of dynamic carbon partitioning in oleaginous microalgae. Moreover, we successfully determined the changes of several key lipid-synthesis-related genes (e.g., acetyl-CoA carboxylase, pyruvate decarboxylase, acetaldehyde dehydrogenase, acetyl-CoA synthetase and pyruvate ferredoxin oxidoreductase) and starch-degradation related genes (e.g., starch phosphorylases), which could provide a breakthrough in the marine microalgal production of biodiesel.

Improving polyglucan production in cyanobacteria and microalgae via cultivation design and metabolic engineering

Photosynthetic microorganisms, such as cyanobacteria and microalgae, are currently being investigated as alternative biomass resources for bioethanol production, owing to their benefits, including high‐photosynthetic activity and whole‐year cultivation without utilization of arable land. Polyglucans comprise the major carbohydrate content of these organisms. Polyglucans can be utilized as a carbon source for microbial fermentation. Although polyglucan production has so far been promoted by nutrient limitation, it must be further enhanced to accommodate market demand. This review focuses on the recent progress in the production of α‐polyglucans such asglycogen and starch in cyanobacteria and green microalgae via cultivation design, including modifying the nutrient supply and replacing the growth medium. The control and manipulation of polyglucan metabolism necessitates the elucidation of the polyglucan production mechanism. We reviewed gene expression and metabolite accumulation profiles of cyanobacteria and green microalgae during nutrient limitation‐stimulated α‐polyglucan accumulation. We also focus on the enhancement in cyanobacterial glycogen production via the genetic engineering of glycolysis, CO2 concentration mechanism, and photosynthetic light‐harvesting protein based on the polyglucan accumulation mechanism. The combined strategies of cultivation design and genetic engineering should be considered for further enhancement of polyglucan productivity for bioethanol production.

Lipase cocktail for efficient conversion of oils containing phospholipids to biodiesel.

The presence of phospholipid has been a challenge in liquid enzymatic biodiesel production. Among six lipases that were screened, lipase AY had the highest hydrolysis activity and a competitive transesterification activity. However, it yielded only 21.1% FAME from oil containing phospholipids. By replacing portions of these lipases with a more robust bioFAME lipase, CalT, the combination of lipase AY-CalT gave the highest FAME yield with the least amounts of free fatty acids and partial glycerides. A higher methanol addition rate reduced FAME yields for lipase DF-CalT and A10D-CalT combinations while that of lipase AY-CalT combination improved. Optimizing the methanol addition rate for lipase AY-CalT resulted in a FAME yield of 88.1% at 2h and more than 95% at 6h. This effective use of lipases could be applied for the rapid and economic conversion of unrefined oils to biodiesel.

High-Speed Scanning for the Quantitative Evaluation of Glycogen Concentration in Bioethanol Feedstock Synechocystis sp. PCC6803 Using a Near-Infrared Hyperspectral Imaging System with a New Near-Infrared Spectral Camera

In the present study, the high-speed quantitative evaluation of glycogen concentration accumulated in bioethanol feedstock Synechocystis sp. PCC6803 was performed using a near-infrared (NIR) imaging system with a hyperspectral NIR spectral camera named Compovision. The NIR imaging system has a feature for high-speed and wide area monitoring and the two-dimensional scanning speed is almost 100 times faster than the general NIR imaging systems for the same pixel size. For the quantitative analysis of glycogen concentration, partial least squares regression (PLSR) and moving window PLSR (MWPLSR) were performed with the information of glycogen concentration measured by high performance liquid chromatography (HPLC) and the calibration curves for the concentration within the Synechocystis sp. PCC6803 cell were constructed. The results had high accuracy for the quantitative estimation of glycogen concentration as the best squared correlation coefficient R2 was bigger than 0.99 and a root mean square error (RMSE) was less than 2.9%. The present results proved not only the potential for the applicability of NIR spectroscopy to the high-speed quantitative evaluation of glycogen concentration in the bioethanol feedstock but also the expansivity of the NIR imaging instrument to in-line or on-line product evaluation on a factory production line of bioethanol in the future.