Publications

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Background: The efficient biological production of industrially and economically important compounds is a challenging problem. Brute-force determination of the optimal pathways to efficient production of a target chemical in a chassis organism is computationally intractable. Many current methods provide a single solution to this problem, but fail to provide all optimal pathways, optional sub-optimal solutions or hybrid biological/non-biological solutions. Results: Here we present RetSynth, software with a novel algorithm for determining all optimal biological pathways given a starting biological chassis and target chemical. By dynamically selecting constraints, the number of potential pathways scales by the number of fully independent pathways and not by the number of overall reactions or size of the metabolic network. This feature allows all optimal pathways to be determined for a large number of chemicals and for a large corpus of potential chassis organisms. Additionally, this software contains other features including the ability to collect data from metabolic repositories, perform flux balance analysis, and to view optimal pathways identified by our algorithm using a built-in visualization module. This software also identifies sub-optimal pathways and allows incorporation of non-biological chemical reactions, which may be performed after metabolic production of precursor molecules. Conclusions: The novel algorithm designed for RetSynth streamlines an arduous and complex process in metabolic engineering. Our stand-alone software allows the identification of candidate optimal and additional sub-optimal pathways, and provides the user with necessary ranking criteria such as target yield to decide which route to select for target production. Furthermore, the ability to incorporate non-biological reactions into the final steps allows determination of pathways to production for targets that cannot be solely produced biologically. With this comprehensive suite of features RetSynth exceeds any open-source software or webservice currently available for identifying optimal pathways for target production.

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More efficient engines enabled by better fuels derived from biomass could increase the fuel economy of the light duty (LD) fleet by 10% over current technology and planned developments. This report identifies top LD boosted spark ignition (BSI) biofuel candidates for further development and commercialization identified using a fuel property basis. The BSI merit function was used to evaluate the performance of candidate bio-blendstocks in improving engine efficiency. This report is aimed at biofuel researchers looking to better understand the efficiency implications of biofuels under development, as well as engine researchers who are interested in future biofuels with properties that enable more efficient engine design and operation.

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This work describes the first documented case of an effect defined herein as “octane hyperboosting” by an oxygenated fuel compound, 3-methyl-2-buten-1-ol (prenol). Octane hyperboosting is characterized by the Research Octane Number (RON) of a mixture (e.g. an oxygenate biofuel blended into gasoline) exceeding the RON of the individual components in that mixture. This finding counters the widely held assumption that interpolation between the RON values of a pure compound and the base fuel provides the bounds for the RON performance of the blend. This is clearly distinct from the more commonly observed synergistic blending of oxygenates with gasoline, where the RON never exceeds the performance of the highest performing component. Octane hyperboosting was observed for blends of prenol and six different gasoline fuels with varying composition. Testing of compounds chemically similar to prenol yielded no qualitatively similar instances of octane hyperboosting, which suggests that the effect may not be widespread among fuel candidates. The phenomenon suggests an unexplored aspect of autoignition kinetics research for fuel blends, and may provide a new mechanism for significantly increasing fuel octane number, which is necessary for increasing combustion efficiency in spark ignition engines. This phenomenon also increases the potential candidate list of biofuels, as compounds hitherto discounted due to their lower pure component RON may exhibit hyperboosting behavior, and thereby enhanced performance, in blends.

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