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Title: Leveraging microbial biosynthetic pathways for the generation of ‘drop-in’ biofuels

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Journal Article: Publisher's Accepted Manuscript
Journal Name:
Current Opinion in Biotechnology
Additional Journal Information:
Journal Volume: 45; Journal Issue: C; Related Information: CHORUS Timestamp: 2017-10-07 09:01:42; Journal ID: ISSN 0958-1669
Country of Publication:
United Kingdom

Citation Formats

Zargar, Amin, Bailey, Constance B., Haushalter, Robert W., Eiben, Christopher B., Katz, Leonard, and Keasling, Jay D. Leveraging microbial biosynthetic pathways for the generation of ‘drop-in’ biofuels. United Kingdom: N. p., 2017. Web. doi:10.1016/j.copbio.2017.03.004.
Zargar, Amin, Bailey, Constance B., Haushalter, Robert W., Eiben, Christopher B., Katz, Leonard, & Keasling, Jay D. Leveraging microbial biosynthetic pathways for the generation of ‘drop-in’ biofuels. United Kingdom. doi:10.1016/j.copbio.2017.03.004.
Zargar, Amin, Bailey, Constance B., Haushalter, Robert W., Eiben, Christopher B., Katz, Leonard, and Keasling, Jay D. 2017. "Leveraging microbial biosynthetic pathways for the generation of ‘drop-in’ biofuels". United Kingdom. doi:10.1016/j.copbio.2017.03.004.
title = {Leveraging microbial biosynthetic pathways for the generation of ‘drop-in’ biofuels},
author = {Zargar, Amin and Bailey, Constance B. and Haushalter, Robert W. and Eiben, Christopher B. and Katz, Leonard and Keasling, Jay D.},
abstractNote = {},
doi = {10.1016/j.copbio.2017.03.004},
journal = {Current Opinion in Biotechnology},
number = C,
volume = 45,
place = {United Kingdom},
year = 2017,
month = 6

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on April 17, 2018
Publisher's Accepted Manuscript

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Cited by: 1work
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  • The Biomass Scenario Model (BSM) is a system-dynamics simulation model intended to explore the potential for rapid expansion of the biofuels industry. The model is not predictive — it uses scenario assumptions based on various types of data to simulate industry development, emphasizing how incentives and technological learning-by-doing might accelerate industry growth. The BSM simulates major sectors of the biofuels industry, including feedstock production and logistics, conversion, distribution, and end uses, as well as interactions among sectors. The model represents conversion of biomass to biofuels as a set of technology pathways, each of which has allowable feedstocks, capital and operatingmore » costs, allowable products, and other defined characteristics. This study and the BSM address bioenergy modeling analytic needs that were identified in recent literature reviews. Simulations indicate that investments are most effective at expanding biofuels production through learning-by-doing when they are coordinated with respect to timing, pathway, and target sector within the biofuels industry. Effectiveness metrics include timing and magnitude of increased production, incentive cost and cost effectiveness, and avoidance of windfall profits. Investment costs and optimal investment targets have inherent risks and uncertainties, such as the relative value of investment in more-mature versus less mature pathways. These can be explored through scenarios, but cannot be precisely predicted. Dynamic competition, including competition for cellulosic feedstocks and ethanol market shares, intensifies during times of rapid growth. Ethanol production increases rapidly, even up to Renewable Fuel Standards-targeted volumes of biofuel, in simulations that allow higher blending proportions of ethanol in gasoline-fueled vehicles. Published 2014. This document is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts, Biorefining published by John Wiley & Sons, Ltd on behalf of Society of Chemical Industry.« less
  • Two biosynthetic pathways are known for the universal tetrapyrrole precursor, {delta}-aminolevulinic acid (ALA): condensation of glycine and succinyl-CoA to form ALA with the loss of C-1 of glycine as CO{sub 2}, and conversion of the intact carbon skeleton of glutamate to ALA in a process requiring tRNA{sup Glu}, ATP, Mg{sup 2+}, NADPH, and pyridoxal phosphate. The distribution of the two ALA biosynthetic pathways among various bacterial genera was determined, using cell-free extracts obtained from representative organisms. Evidence for the operation of the glutamate pathway was obtained by the measurement of RNase-sensitive label incorporation from glutamate into ALA using 3,4-({sup 3}H)glutamatemore » and 1-({sup 14}C)glutamate as substrate. The glycine pathway was indicated by RNase-insensitive incorporation of level from 2-({sup 14}C)glycine into ALA. The distribution of the two pathways among the bacteria tested was in general agreement with their previously phylogenetic relationships and clearly indicates that the glutamate pathway is the more ancient process, whereas the glycine pathway probably evolved much later. The glutamate pathway is the more widely utilized one among bacteria, while the glycine pathway is apparently limited to the {alpha} subgroup of purple bacteria (including Rhodobacter, Rhodospirillum, and Rhizobium). E. coli was found ALA via the glutamate pathway. The ALA-requiring hemA mutant of E. coli was determined to lack the dehydrogenase activity that utilizes glutamyl-tRNA as a substrate.« less
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