Design, Construction, and Application of Synthetic Microbial Consortia.

Mixtures of interacting microbes, or microbial consortia, may be a key part of the solution to overcoming current environmental and technological challenges, such as a dearth of renewable fuel sources. Microbial consortia have various advantages over single species, or “superbugs”, such as efficiency, robustness, and modularity. The goal of this dissertation is to develop tools for making use of microbial consortia and to demonstrate their utility through practical applications. Specifically, our efforts in technology development and application include: a tunable, programmable cross-feeding circuit; production of isobutanol (a next-generation biofuel); and sensing/screening of metabolite secretion. First, we designed and constructed a programmable genetic circuit based on engineered symbiosis between two E. coli auxotrophs. By regulating and tuning the export or production of the cross-fed metabolites we were able to tune the exchanges and achieve a wide range of growth rates and strain ratios. In addition, we created two-dimensional design space plots by inverting the relationship of growth/ratio vs. inducer concentrations. Using the plots, we could “program” the co-culture for pre-specified outcomes. This proof-of-concept circuit can be applied to more complex systems where precise tuning of the consortium would facilitate the optimization of specific objectives. Next, we engineered a consortium of E. coli specialist strains fermenting either hexose or pentose sugars into isobutanol, and demonstrated that this co-culture exhibits improved isobutanol production over a diauxic monoculture under several growth conditions. Notably, the co-culture outperformed the monoculture on an enzymatically-hydrolyzed lignocellulosic biomass, producing up to almost 3 g/L isobutanol without detoxification or supplementation. Lastly, we demonstrated the utility of a microbial consortium for detecting highly-secreting L-valine (and subsequently isobutanol) production strains. We designed a secretor/sensor pair that can be used to detect increased L-valine secretion by the “secretor” via the changes in growth of the “sensor”, a fluorescently-tagged L-valine auxotroph. This will be part of a larger effort to develop a new method for high-throughout screening of microbial over-production strains. This dissertation presents the design, construction, and/or application of three synthetic microbial consortia. Through tool development and biofuel applications, our work demonstrates the potential, utility, and benefits of microbial consortia in synthetic biology.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/97925/1/akerner_1.pd

A Programmable Escherichia coli Consortium via Tunable Symbiosis

Synthetic microbial consortia that can mimic natural systems have the potential to become a powerful biotechnology for various applications. One highly desirable feature of these consortia is that they can be precisely regulated. In this work we designed a programmable, symbiotic circuit that enables continuous tuning of the growth rate and composition of a synthetic consortium. We implemented our general design through the cross-feeding of tryptophan and tyrosine by two E. coli auxotrophs. By regulating the expression of genes related to the export or production of these amino acids, we were able to tune the metabolite exchanges and achieve a wide range of growth rates and strain ratios. In addition, by inverting the relationship of growth/ratio vs. inducer concentrations, we were able to “program” the co-culture for pre-specified attributes with the proper addition of inducing chemicals. This programmable proof-of-concept circuit or its variants can be applied to more complex systems where precise tuning of the consortium would facilitate the optimization of specific objectives, such as increasing the overall efficiency of microbial production of biofuels or pharmaceuticals

Microdroplet-Enabled Highly Parallel Co-Cultivation of Microbial Communities

Microbial interactions in natural microbiota are, in many cases, crucial for the sustenance of the communities, but the precise nature of these interactions remain largely unknown because of the inherent complexity and difficulties in laboratory cultivation. Conventional pure culture-oriented cultivation does not account for these interactions mediated by small molecules, which severely limits its utility in cultivating and studying “unculturable” microorganisms from synergistic communities. In this study, we developed a simple microfluidic device for highly parallel co-cultivation of symbiotic microbial communities and demonstrated its effectiveness in discovering synergistic interactions among microbes. Using aqueous micro-droplets dispersed in a continuous oil phase, the device could readily encapsulate and co-cultivate subsets of a community. A large number of droplets, up to ∼1,400 in a 10 mm×5 mm chamber, were generated with a frequency of 500 droplets/sec. A synthetic model system consisting of cross-feeding E. coli mutants was used to mimic compositions of symbionts and other microbes in natural microbial communities. Our device was able to detect a pair-wise symbiotic relationship when one partner accounted for as low as 1% of the total population or each symbiont was about 3% of the artificial community

XN. A programmable Escherichia coli consortium via tunable symbiosis. PLoS One

Abstract Synthetic microbial consortia that can mimic natural systems have the potential to become a powerful biotechnology for various applications. One highly desirable feature of these consortia is that they can be precisely regulated. In this work we designed a programmable, symbiotic circuit that enables continuous tuning of the growth rate and composition of a synthetic consortium. We implemented our general design through the cross-feeding of tryptophan and tyrosine by two E. coli auxotrophs. By regulating the expression of genes related to the export or production of these amino acids, we were able to tune the metabolite exchanges and achieve a wide range of growth rates and strain ratios. In addition, by inverting the relationship of growth/ratio vs. inducer concentrations, we were able to ''program'' the co-culture for pre-specified attributes with the proper addition of inducing chemicals. This programmable proof-of-concept circuit or its variants can be applied to more complex systems where precise tuning of the consortium would facilitate the optimization of specific objectives, such as increasing the overall efficiency of microbial production of biofuels or pharmaceuticals. Citation: Kerner A, Park J, Williams A, Lin XN (2012) A Programmable Escherichia coli Consortium via Tunable Symbiosis. PLoS ONE 7(3): e34032

Co-culture growth and ratio dynamics: baseline and with tuning.

<p>(<b>A</b>) Co-culture density (measured by OD₆₀₀) and Y3∶W3 ratio during growth in minimal medium without inducers. The ratio measurement is shown only for the exponential growth phase because the YFP calibration is not reliable after the cells enter the stationary phase. (<b>B</b>) An example of Y3∶W3 ratio dynamics at various arabinose concentrations. Propionate concentration was held at 20 mM. Only the exponential growth phase is shown. Each curve represents the mean of 4 replicates. Note: the secondary y-axis label in (<b>A</b>), Ratio Y3∶W3, is also the label for the primary y-axis in (<b>B</b>).</p

Basic schematic of the tunable cross-feeding circuit.

<p>(<b>A</b>) In this general design, inducer 1 and inducer 2 control the export of metabolites 1 and 2, respectively. The two auxotrophs must cross-feed in order to survive in the minimal medium. (<b>B</b>) In our specific implementation, two <i>E. coli</i> auxotrophic strains exchange tryptophan (Trp) and tyrosine (Tyr). The forced symbiosis is controlled by plasmids pAK1 (in the Trp auxotroph, W3) and pAK5 (in the Tyr auxotroph, Y3). Plasmid pAK1 contains gene <i>yddG</i> behind the tunable promoter P_BAD, and pAK5 contains <i>trpEDfbr</i> behind P_prpB (Methods). Strain Y3 is tagged with yellow fluorescent protein (YFP).</p

Design space and testing.

<p>(<b>A, B</b>) By inverting the relationships of growth rate/strain ratio vs. inducer concentrations, a design space was generated to represent the two-dimensional space of achievable growth rates and strain ratios, and to determine the arabinose (<b>A</b>) and propionate (<b>B</b>) concentrations for a desired growth rate and end-exponential ratio combination. The colored circles are “prediction” points and the asterisks of the same color are the “actual” results of using that combination of arabinose and propionate in the co-culture. The colors denote inducer combinations: purple (0.11%, 8 mM); pink (0.02%, 5 mM); orange (0.13%, 30 mM); red (0.06%, 12 mM); yellow (0.06%, 20 mM); black (0.11%, 5 mM). (<b>C, D</b>) Comparing the predicted and actual outcome for growth rate (<b>C</b>) and end-exponential ratio (<b>D</b>) in bar graph form; the predictions are in darker colors and the actual (experimental) results are in lighter ones. Error bars: ± standard deviation. The mid-exponential ratio design space is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034032#pone.0034032.s004" target="_blank">Figure S4</a>. Experimental data are given <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034032#pone.0034032.s009" target="_blank">Data S1</a>.</p

Negative control experiments.

<p>(<b>A</b>) Addition of arabinose has no effect on the growth rate of the negative tryptophan control strain (W4) and the positive tyrosine strain (Y3). (<b>B</b>) The growth rate of both cultures is decreased with the addition of increasing amounts of propionate, but the growth rate decreases less with the addition of the cross-feeding genes. For both (<b>A</b>) and (<b>B</b>) the negative control strain is either W4 or Y4. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034032#pone.0034032.s007" target="_blank">Table S1</a> for the complete strain genotypes.</p

Comparison of a fast growing pair (K-12 W^- and Y^-) and a slow growing pair (EcNR1 W^- and Y^-) on the same device.

<p>(A) Three droplets carrying the pair of <i>E. coli</i> K-12 W^- expressing mCherry and Y^- (not labeled with fluorescence). Top panels – before cultivation. Bottom panels – after 18-hour cultivation. (B) Three droplets carrying the pair of <i>E. coli</i> EcNR1 W^- expressing GFP and K-12 Y^-. Top panels – before cultivation. Bottom panels – after 18-hour cultivation.</p

Number of droplets carrying various subsets of the triplet system.

<p>(a) S-: W-: Y- = 1∶1∶1 (b) S-: W-: Y- = 50∶50∶1 (c) S-: W-: Y- = 30∶1∶1.</p