DROPLET BASED DIRECTED EVOLUTION OF YEAST CELL FACTORIES DOUBLES PRODUCTION OF INDUSTRIAL ENZYMES

Staffan L. Sjostroma*, Yunpeng Baia, Mingtao Huangb, Jens Nielsena, b, c, Haakan N. Joenssona and Helene Andersson Svahna

aDivision of Proteomics and Nanobiotechnology, Science for Life Laboratory, Royal Institute of Technology (KTH), Sweden

bDepartment of Chemical and Biological Engineering, Chalmers University of Technology, Sweden cNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Denmark

ABSTRACT

We present a high throughput micro-droplet based method for directed evolution of yeast cell factories for improved production of industrial enzymes. The workflow includes a fluorescently activated droplet sorter which was found to ac-curately sort droplets with a false positive rate of 0.0002 at 300 Hz. The workflow was used to screen a library of α-amylase expressing yeast mutants. A candidate yeast strain with a more than twofold increase in α-amylase production was isolated from a single round of directed evolution. KEYWORDS: Directed evolution, High throughput, Enzymes, Cell factories, Droplet microfluidics

INTRODUCTION

Enzymes are important to a wide range of industrial applications including wastewater treatment, synthesis of chemi-cals and production of biofuels. Directed evolution towards improved enzymatic activity is difficult but recent works have shown that improved enzyme variants can be evolved using droplet microfluidics.[1,2] Here, we demonstrate a gen-eral platform for directed evolution of improved enzyme production hosts. In our work, we improve the production of an industrially relevant enzyme, α-amylase, overcoming the challenge of a non-ideal enzymatic substrate and verifying the results in large-scale batch production.

THEORY

Cell metabolism is highly complex, which limits the predictive power of rational genetic engineering approaches to increase production of a specific product (for example an enzyme) from a strain. Instead, directed evolution methods may be employed in which mutations are randomly introduced to a large population of microorganisms to create a library of variants with altered production. Subsequently, the microorganism library is screened for variants with improved produc-tion of the desired product. The bottleneck of a directed evolution scheme is that to efficiently screen a large library of microorganism variants, a suitable high throughput screening system is needed.[3]

We present a droplet microfluidic based method for screening of yeast (S. cerevisae) for enhanced enzyme produc-

tion. The method encompasses encapsulation of single yeast cells from a mutant library in droplets together with a fluo-rogenic enzyme substrate followed by sorting of droplets based on the fluorescent signal produced by digestion of the substrate by the target enzyme (Figure 1). The encapsulation of the cell in the droplet links the cell phenotype (secreted enzyme) to genotype (yeast cell) and the fluorogenic substrate enables measurement of the enzyme concentration. Sort-ing of droplets is done by flowing the droplets past the sorting junction and measuring the fluorescence of each droplet which passes a fluorescence exciting laser. If the droplet fluorescence exceeds a predefined threshold, a powerful electric field is automatically activated pulling the droplet of interest to a separate outlet. The cell in the sorted droplet can subse-quently be recovered for further analysis. EXPERIMENTAL

Microfluidic devices were manufactured in glass and Polydimethylsiloxane (PDMS) using standard soft lithography with injected electrodes. The workflow includes two circuits (Figure 1). The first circuit generates 20 pL droplets at a rate of 2.8 kHz, encapsulating a cell library together with a fluorogenic α-amylase substrate (BODIPY-starch). Droplets are incubated off-chip for three hours during which the encapsulated cells produce α-amylase that breaks down BOD-IPY-starch into a fluorescent product. The droplets are then injected into the second circuit where they are sorted using fluorescence activated droplet sorting (FADS) [4] at 400 Hz to sort droplets containing cells with high enzyme produc-tion. Droplet fluorescence measurements utilized a photomultiplier tube for detection centered at 525 nm and a 50 mW 491 nm laser for excitation.

978-0-9798064-6-9/µTAS 2013/$20©13CBMS-0001 1270 17th International Conference on MiniaturizedSystems for Chemistry and Life Sciences27-31 October 2013, Freiburg, Germany

Figure 1. Workflow schematic for directed evolution of improved industrial enzyme production hosts. A library of

whole genome mutated yeast cells are encapsulated into droplets together with a fluorogenic substrate. Single yeast cells in droplets are incubated for three hours to produce enzyme that digest the substrate into a fluorescent product, linking the enzyme production of the encapsulated cell to the fluorescence of the droplet. The droplets are reinjected into a se-cond circuit where the droplets with the highest fluorescence are sorted and the remainder going to the waste fraction, thus enriching for cells with higher enzyme production. RESULTS AND DISCUSSION

To validate the workflow, the FADS module was characterized by sorting a small fraction (1.9 - 4.4%) of high fluo-rescent droplets from a background of low fluorescent droplets (n=3). The sorted droplets were reanalyzed and it was found that 99.0% - 99.6% of the droplets were high fluorescent corresponding to false positive rates between 0.0001 and 0.0003 (Figure 2A-B). A low false positive rate is important for sorting rare events to ensure that sufficient enrichment can be achieved. According to the model sorts, the theoretical maximum enrichment that can be achieved would be ca. 104 which is sufficient for the directed evolution workflow. Furthermore, if the fraction of high fluorescent droplets was reduced further we speculate that the false positive rate would decrease, as the majority of the false positives are thought to be events where a low fluorescent droplet is mistakenly sorted together with a high fluorescent droplet.

The BODIPY-starch substrate was investigated by assaying various concentrations of α-amylase in droplets (Figure 2C). The BODIPY-starch substrate consists of quenched BODIPY fluorophores attached to starch molecules, which are gradually unquenched as α-amylase digest the starch. Thus, higher enzyme concentration corresponds to higher fluores-cent signal, which was verified experimentally in droplets. It was also found that a twofold difference in enzyme concen-tration could be resolved in the droplet format.

Figure 2. Validation of workflow. A) An emulsion containing high (1.9%) and low (98.1%) fluorescent droplets was

sorted using FADS at 300 Hz. B) The sorted material from the emulsion shown in A) was reinjected and analyzed. It was found that 99.4% of the droplets were highly fluorescent. Color indicates density of events. C) Droplets were generated containing α-amylase at various concentrations (0, 6, 12, 50 ng/mL) together with fluorogenic substrate BODIPY-starch and droplet fluorescence was followed over time.

Finally, a library of yeast with mutations randomly introduced throughout the genome was sorted to enrich for cells with mutations that improved α-amylase production. The sorted material was analyzed for α-amylase production (nor-malized for cell count) and it was found that the sorted fraction had an improved enzyme production (Figure 3A). Sixty yeast clones were picked from the polyclonal sorted fraction and were further analyzed (Figure 3B) and the top-performing clone was found to have more than twice enzyme production of the mother strain, a result which was verified in large scale batch production (Figure 3C). Additional rounds of directed evolution are currently ongoing and are ex-pected to yield strains with even higher enzyme production.

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Figure 3. A) Bulk α-amylase production of yeast library, sorted fraction and waste fraction respectively relative to

the production of the mother strain from which the yeast library was derived. B) α-amylase production of 60 clones picked from the sorted material compared to the mother strain. Red arrow highlights candidate strain (clone #34). C) Validation of productivity of candidate strain in bioreactor fermentation scale. CONCLUSION

We demonstrate a micro droplet based method for directed evolution of microorganisms with improved enzyme pro-duction. The method was used to select an yeast variant with a more than twofold improvement in α-amylase production compared to the mother strain in a single round of directed evolution. This platform can have great industrial value as the throughput of the droplet system is more than 300 times higher than industry state of the art microtiter plate robot system while also reducing reagent consumption by a million fold. ACKNOWLEDGEMENTS

This work was funded by the Novo Nordisk Foundation Center for Biosustaninability, Denmark. We acknowledge Raindance Technologies, MA, USA, for generously providing the droplet stabilizing surfactants used in this work. REFERENCES [1] B. Kintses, et al., “Picoliter cell lysate assays in microfluidic droplet compartments for directed enzyme evolution”,

Chemistry & Biology, vol. 19, 1001 – 1009, Aug. 2012. [2] J.J. Agresti, et al., “Ultrahigh-throughput screening in drop-based microfluidics for directed evolution”, Proceed-

ings of the National Academy of Sciences of the United States of America, vol. 107,4004 – 4009, Dec. 2009. [3] E. Nevogit, “Progress in metabolic engineering of Saccharomyces cerevisiae”, Microbiol Mol Biol Rev., vol. 186,

pp. 379 – 412, Sept. 2008. [4] J.C. Baret, et. al, “Fluorescence-activated droplet sorting (FADS): efficient microfluidic cell sorting based on en-

zymatic activity”, Lab On a Chip , vol 9,1850 – 1858, Apr. 2009. CONTACT *S.L. Sjostrom, tel: +46-8-52481233; staffan.sjostrom@scilifelab.se

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