Due to climate change and uncertainties in global fuel prices, there is a need to adopt
biomass derived feed stocks for sustainable manufacturing of fuels, chemicals and
pharmaceuticals. As a result, many major industrial manufacturers are now seeking
routes to their products that are sustainable, more efficient, and less waste or energy
intensive. While bioprocesses to produce compounds ranging from therapeutic drugs
to fuels have already been widely implemented, the current microbes being
employed are often relatively inefficient and limited in the feedstocks they can
utilise. Inherent to successful bioprocess development is the ability to rapidly and
predictably engineer microbes for the efficient flux of simple biomass towards
compounds of industrial significance. Current iterative and empirical processes for
microbial strain improvement are limited and therefore improved enabling
technologies to accelerate these processes are required.
To address these issues, this thesis describes the development of a platform for the
rapid and predictable engineering of microbes for industrial bioprocesses. This has
been achieved through complementing an accelerated DNA assembly technique for
biosynthetic pathway construction with quantitative proteomics to identify pathway
bottlenecks and guide subsequent rounds of pathway optimisation. Only through the
ability to rapidly construct biosynthetic pathways and then assess the failure or
success of the introduced pathways can microbes be engineered in an intuitive and
predictable manner.
A central theme of this thesis is the optimisation and implementation of a DNA
assembly technique for the construction of multicomponent pathways. Despite being
a fundamental aspect of strain engineering, DNA assembly is often unreliable and
time consuming. One limitation of this technique is the reduced efficiency observed
in the assembly of multiple DNA fragments (as is often the case when constructing a
heterologous pathway). To overcome this issue a ‘nested’ DNA assembly
methodology has been developed for the predictable construction of combinatorial
vector libraries and complex vectors resulting in the successful assembly of up to 10
fragments. Appropriate shake flask and microtiter plate assays were additionally
developed to characterise these constructs. A parallel strand of this work has been the
optimisation of the methodology to maximise throughput and efficiency whilst also
ensuring the method is amenable to process automation.
To exemplify the power of proteomics in guiding strain engineering the reverse
glyoxylate shunt was selected as a simple benchmark heterologous pathway in the
commonly used host, Escherichia coli. This pathway allows for the conversion of
tricarboxylic acid cycle intermediates malate and succinate to oxaloacetate and two
molecules of acetyl-CoA. Strains have been engineered to overexpress the pathway
genes and tryptic digestions of cell lysates carried out. Liquid chromatography, mass
spectrometry and data analysis methods have been developed for the identification of
over 100 proteins from these lysates. Work was then focused on developing
quantitative acquisitions which will allow for the identification of pathway
bottlenecks. The coupling of techniques for pathway engineering and pathway
analysis will create a step change in the speed and predictability with which microbes
can be engineered for industrial application
