Multi-dimensional studies of synthetic genetic promoters enabled by microfluidic impact printing

Abstract

Natural genetic promoters are regulated by multiple cis and trans regulatory factors. For quantitative studies of these promoters, the concentration of only a single factor is typically varied to obtain dose response or transfer function of the promoters with respect to the factor. Such design of experiments has limited our ability to understand quantitative, combinatorial interactions between multiple regulatory factors at promoters. The limitation is primarily due to the intractable number of experimental combinations that arise from multifactorial design of experiments. To overcome this major limitation, we integrate impact printing and cell-free systems to enable multi-dimensional studies of genetic promoters. We first present a gradient printing system which comprises parallel piezoelectric cantilever beams as a scalable actuator array to generate droplets with tunable volumes in the range of 100pL – 10nL, which facilitates highly accurate direct dilutions in the range of 1 – 10,000 fold in a 1μL drop. Next, we apply this technology to study interactions between three regulatory factors at a synthetic genetic promoter. Finally, a mathematical model of gene regulatory modules is established using the multi-parametric and multi-dimensional data. Our work creates a new frontier in the use of cell-free systems and droplet printing for multi-dimensional studies of synthetic genetic constructs.

Bottom-Up Construction of Complex Biomolecular Systems With Cell-Free Synthetic Biology

“…Functional repression assays and quantitative affinity measurements (Maerkl and Quake, 2007) were used to characterize a library of synthetic transcription factors, enabling gene regulatory networks to be built from purely synthetic parts de novo (Figure 3A). Another quantitative and multi-dimensional study of genetic promoters was carried out using parallel piezoelectric cantilever beams that were able to generate an array of droplets containing cell-free TX-TL reaction mixtures with highly accurate concentration gradients (Fan et al, 2017) (Figure 3A).…”

Scaling up genetic circuit design for cellular computing: advances and prospects

“…By example, Schwarz-Schilling et al ( 2016 ) produced functional AND gates and sender circuits in droplets containing cell free systems and bacteria. Fan et al ( 2017 ) use droplet microfluidics to print accurate and small quantities of cell free systems to measure interactions between three genetic factors at a synthetic promoter and used this data generate a model. Wang et al ( 2018 ) used a similar method, only combining a locked nucleic acid probe (measuring mRNA levels) with fluorescent proteins enabling simultaneous measurement of transcription and translation in massively parallel cell free droplet experiments.…”

High-throughput screening of biomolecules using cell-free gene expression systems

“…The most recent in vitro display and microarray approaches have focused on increasing the range of applications and the screening of more complex biomolecules, such as membrane proteins and proteins that require multiple disulfide bonds. High-throughput screening of biomolecules using cell-free transcription and translation systems may be improved based on advances in several foundational technologies, including the development of better data analysis tools, the creation of new and improved cell-free protein expression systems ( 125 ), the advancement in automation of the screening processes ( 23 ) and further miniaturization to single molecule level that can still yield a detectable signal.…”

“…The use of cell-free systems adds an additional layer of complexity due to the high diversity of molecules present in the analysis solution, the increased possibility of non-specific interactions with cellular components and the myriad ways of controlling protein expression. Despite this complexity, cell-free protein expression systems bring forth several advantages over conventional cell-based approaches, including the capability to express toxic or insoluble proteins ( 19 ), the incorporation of unnatural or isotope-labeled amino acids into the peptide chain ( 20 , 21 ), reduced processing time ( 22 ) and reaction volumes ( 23 ), as well as the lack of gene-cloning steps ( 24 ). These advantages make cell-free systems ideal for high-throughput applications ( 25 , 26 ).…”