Engineering gene regulation in plants to yield predictable expression

• Applicant: Dr. Tobias Jores
• Subject Area: Plant Genetics and Genomics ; Plant Cell and Developmental Biology
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 552448431

Improving the sustainability of agriculture is vitally important for humans and the planet. Agricultural practices could be improved by using biotechnology to manipulate crop traits or to replace harmful agrochemicals with sustainable, plant-produced compounds. However, both approaches require engineering multiple genes or pathways to yield predictable outcomes. Thus far, predicting the expression in plants of synthetic genes and pathways, even those composed of well-characterized DNA sequences, remains a major challenge. Indeed, when individual pathway genes are assembled into larger designs, their performance becomes unpredictable because regulatory elements and genic regions show strong context-dependent properties. Moreover, plant biotechnology relies on only a handful of regulatory elements, often of bacterial and viral origin, that constitutively and ubiquitously drive gene expression, interfering with growth and reducing crop yields. The lack of programmable and tunable regulatory elements contributes to unpredictable gene expression through expression interference and silencing. Combining our expertise, we propose to make plant gene expression predictable by exploiting a toolbox of experimental and computational strategies that we recently pioneered. We will demonstrate success by constructing programmable and tunable multi-gene cassettes that produce antifeedants and insect sex pheromones as sustainable alternatives to traditional pesticides. We will achieve our goal by pursuing three objectives, each one testing novel hypotheses as to the causes of the outlined challenges: 1. First, to develop a large repertoire of programmable and tunable synthetic regulatory elements, we will use massively parallel reporter assays, machine learning and in silico evolution. 2. Second, we will control gene expression levels through insulation and stabilization, drawing on recent innovations in vaccine research. 3. Lastly, to determine how local sequence context affects gene expression within multi-gene cassettes, we will manipulate gene order and position, DNA shape, torsional stress, and nucleosome occupancy, using genetic engineering and a new single-molecule method to explore chromatin architecture. Together, our results will enable the construction of multi-gene cassettes in which the expression of each gene is induced in response to a specific stimulus and at a specified level to produce optimal pathway flux. Our efforts will generate large numbers of programmable and tunable regulatory elements and combinations of elements for future synthetic biology efforts in plants. Beyond transgenes, our ability to 'program' plants with predictable expression characteristics will deliver step-changes in manipulating endogenous pathways that control plant development and stress responses, thereby making feasible the targeted engineering of resilient and high-yielding crops capable of thriving in a changing climate.

• DFG Programme: Research Grants
• International Connection: United Kingdom, USA
• Partner Organisation: Biotechnology und Biological Sciences Research Council (BBSRC); National Science Foundation (NSF)
• Cooperation Partners: Professorin Nicola Patron, Ph.D.; Professorin Christine Queitsch, Ph.D.