Synthetic biology and artificial intelligence in crop improvement

Synthetic biology (SynBio) plays a pivotal role in improving crop traits and increasing bioproduction by using engineering principles that purposefully modify plants through "design, build, test and learn" cycles, ultimately resulting in improved bioproduction based on input genetic circuit (DNA, RNA, and Proteins). Crop synthetic biology is new tool following circular principles to redesign and create innovative biological components, devices, and systems to enhance yields, nutrient absorption, resilience, and nutritional quality. In the digital age, artificial intelligence (AI) has demonstrated great significance in the design and learning. The application of AI has become an irreversible trend, with its potential in the field of crop breeding being particularly remarkable. However, a systematic review of AI-driven synthetic biology pathways for plant engineering is lacking. In this review, we explore the fundamental engineering principles employed in crop synthetic biology and their applications in crop improvement. The approaches to genetic circuit design include gene editing, synthetic nucleic acid and protein technologies, multi-omics analysis, genomic selection, directed protein engineering and AI. We then outline strategies for developing crops with higher photosynthetic efficiency, reshaped plant architecture, modified crop metabolic pathways, improved environmental adaptability and nutrient absorption, establishing trait networks, and constructing crop factories. Additionally, we propose the development of Self-Monitoring, Adapted, and Responsive Technology (SMART) crops through AI-empowered synthetic biotechnology. Moreover, we address the challenges associated with synthetic biology development and present potential solutions for crop improvement.