AI to enable plant cell metabolic engineering.

Plant metabolic engineering must take into consideration the heterogeneous cell types that play a role in metabolite production; cells do not participate equally. We posit that artificial intelligence (AI) developed for biomedical purposes can be applied to plant cell characterization to accelerate the development of metabolic engineering strategies in plants.

Engineered gamma radiation phytosensors for environmental monitoring.

Nuclear energy, already a practical solution for supplying energy on a scale similar to fossil fuels, will likely increase its footprint over the next several decades to meet current climate goals. Gamma radiation is produced during fission in existing nuclear reactors and thus the need to detect leakage from nuclear plants, and effects of such leakage on ecosystems will likely also increase. At present, gamma radiation is detected using mechanical sensors that have several drawbacks, including: (i) limited availability; (ii) reliance on power supply; and (iii) requirement of human presence in dangerous areas.

Imaging of multiple fluorescent proteins in canopies enables synthetic biology in plants.

Reverse genetics approaches have revolutionized plant biology and agriculture. Phenomics has the prospect of bridging plant phenotypes with genes, including transgenes, to transform agricultural fields. Genetically encoded fluorescent proteins (FPs) have revolutionized plant biology paradigms in gene expression, protein trafficking and plant physiology.