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. 2013 Feb 6;3(1):20120037.
doi: 10.1098/rsfs.2012.0037.

Monster Potential Meets Potential Monster: Pros and Cons of Deploying Genetically Modified Microalgae for Biofuels Production

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Free PMC article

Monster Potential Meets Potential Monster: Pros and Cons of Deploying Genetically Modified Microalgae for Biofuels Production

K J Flynn et al. Interface Focus. .
Free PMC article

Abstract

Biofuels production from microalgae attracts much attention but remains an unproven technology. We explore routes to enhance production through modifications to a range of generic microalgal physiological characteristics. Our analysis shows that biofuels production may be enhanced ca fivefold through genetic modification (GM) of factors affecting growth rate, respiration, photoacclimation, photosynthesis efficiency and the minimum cell quotas for nitrogen and phosphorous (N : C and P : C). However, simulations indicate that the ideal GM microalgae for commercial deployment could, on escape to the environment, become a harmful algal bloom species par excellence, with attendant risks to ecosystems and livelihoods. In large measure, this is because an organism able to produce carbohydrate and/or lipid at high rates, providing stock metabolites for biofuels production, will also be able to attain a stoichiometric composition that will be far from optimal as food for the support of zooplankton growth. This composition could suppress or even halt the grazing activity that would otherwise control the microalgal growth in nature. In consequence, we recommend that the genetic manipulation of microalgae, with inherent consequences on a scale comparable to geoengineering, should be considered under strict international regulation.

Keywords: biofuels; genetic modification; microalgae; predator–prey; stoichiometry.

Figures

Figure 1.
Figure 1.
Biomass and biofuels areal production. Variation of areal production of biomass (i) and biofuels (ii) against dilution rate (i.e. growth rate, µ) for different physiological characteristics under chemostat-style steady-state conditions. (iii) The percentage of biomass as biofuels; note the different axes directions. (a) Maximum growth rate (µmax); (b) maximum chlorophyll content (ChlCmax); and (c) overall phenotypic efficiency of the photochemistry (αChl, given here with units of (gC mol−1 photon) (m2 g−1 Chla)). (d) Minimum (subsistence) quota for N (NC0, N : C). Note that at high dilution rates biofuels production falls as the microalgae become N-sufficient.
Figure 2.
Figure 2.
Predator–prey simulations. Simulated interaction between a microalgal prey (algae) and its zooplanktonic predator (zoo). Simulations were run with the microalga configured to represent a non-GM (thin line) or a biofuels-optimized GM strain (thick line; table 2). In (a), the mole nutrient ratio is N : P = 16 representing pristine water bodies. In (b), N : P = 64 representing the skewed nutrient content seen in eutrophic coastal waters. Temporal development of the interaction would depend on initial conditions. Plots show development of the algal and zooplankton biomass, and changes in the algal N : C and P : C ratios. Decreases in algal N : C and P : C indicate changes in nutrient stress (through exhaustion of external nutrient supply).

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