Inexpensive petroleum is the cornerstone of the modern global economy despite its huge environmental costs and its nature as a non-renewable resource. While ninety percent of petroleum is ultimately used as fuel and can in principle be replaced by sources of renewable electricity, ten percent is used as a feedstock to produce societally important chemicals that cannot currently be made at a reasonable cost through alternative processes. In this dissertation, I will discuss my efforts, together with several colleagues, to apply synthetic biology approaches to the challenge of producing renewable petrochemical replacements. In Chapter 2, I discuss our efforts to engineer E. coli to produce fatty acids with a wide range of chain lengths at high yield, thereby providing an alternative platform for the production of diverse petrochemicals. In Chapter 3, I describe a novel method of DNA assembly that we developed to facilitate synthetic biology efforts such as those in Chapter 2. This method is capable of simultaneously assembling multiple DNA pieces with substantial sequence homology, a common challenge in synthetic biology. In Chapter 4, I discuss the development of a "bionic leaf": a hybrid microbial-inorganic catalyst that marries the advantages of photovoltaic-based light capture and microbial carbon fixation to achieve solar biomass yields greater than those observed in terrestrial plants. This technology offers a potentially low-cost alternative to photosynthesis as a source of biomass and derived chemicals and fuels. The work described in this dissertation demonstrates the capacity of synthetic biology to address the problem of renewable chemical production, and offers proof of principle demonstrations that both the scope and efficiency of biological chemical production may be improved.
Identifer | oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/13088835 |
Date | January 2014 |
Creators | Torella, Joseph Peter |
Contributors | Silver, Pamela A. |
Publisher | Harvard University |
Source Sets | Harvard University |
Language | en_US |
Detected Language | English |
Type | Thesis or Dissertation |
Rights | closed access |
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