(102b) High-Throughput Approaches for Engineering Tunable Gene Expression Regulation in Non-Model Bacteria

Predictable control of transcription within living systems can help achieve high production yields and titers by reducing carbon flux through undesirable pathways. To achieve such control, genetic parts must be developed that can allow user-defined control. Although much recent progress has been made in transcription factor-based biosensors for workhorse organisms, non-model organisms such as Clostridium still lack tools for rapid and customizable gene expression control1. Clostridium species are promising microorganisms to produce advanced biofuels (e.g., butanol) and platform chemicals, yet a lack of efficiency reduces their economic viability. While effort has been dedicated to studying and engineering Clostridium species, progress has been slow compared to the common workhorse organisms, due to the dearth of synthetic biology tools. Additionally, low throughput screening methods such as liquid chromatography are a bottleneck in evaluating more than a handful of strain designs at once, limiting the ‘test’ step in the design-build-test cycle.

In this work, we have developed two systems for transcriptional control in bacterial systems. First, we demonstrate optimization of transcription factor (TF) DNA binding sites through both a rationale and high-throughput naïve approach (sort-seq). We engineer a set of engineered product-responsive transcription factor regulated promoters (biosensors) for real-time single cell monitoring of butanol accumulation. We demonstrate tunability of gene expression though altering the number, location, and sequence of the transcription factor binding sites. Additionally, we show transcription factor-operator binding energy plays a key factor in the tunability of such systems. Biophysical characteristics between the TF-operator are evaluated using surface plasmon resonance (SPR). This strategy is further demonstrated in which an activating TF was converted into a transcriptional repressor by relocating operating binding sites near or overlapping the RNAP binding site. This work can enable rational strategies to edit the dynamic range of transcription factor-based biosensors. Second, we have developed a regulatable CRISPRi gene repression for the fine-tuning of biosynthetic pathways using Cas12a effector proteins, which are better suited for use in Clostridium due to the genus’ AT-rich genomes and the corresponding simple and T-rich protospacer adjacent motif. We demonstrate in Clostridium pasteurianum tunable repression based on proximity to regulation elements, strand, and number of targeted sites through reporter genes, transcription levels, and redistribution of carbon flux. We propose a set of heuristics for such control as well as compare single versus multiplexed repression.