RESUMEN
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.
Asunto(s)
Ingeniería Metabólica , Células Vegetales , Células Vegetales/metabolismo , Inteligencia Artificial , Plantas/genética , Plantas/metabolismoRESUMEN
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. To overcome these limitations, we have developed a plant biosensor (phytosensor) to detect low-dose ionizing radiation. The system utilizes synthetic biology to engineer a dosimetric switch into potato utilizing the plant's native DNA damage response (DDR) machinery to produce a fluorescent output. In this work, the radiation phytosensor was shown to respond to a wide range of gamma radiation exposure (10-80 Grey) producing a reporter signal that was detectable at >3 m. Further, a pressure test of the top radiation phytosensor in a complex mesocosm demonstrated full function of the system in a 'real world' scenario.
Asunto(s)
Ecosistema , Plantas , Humanos , Rayos gamma , Plantas/genética , Monitoreo del AmbienteRESUMEN
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. While the first instance of plant canopy imaging of green fluorescent protein (GFP) was performed over 25 years ago, modern phenomics has largely ignored fluorescence as a transgene expression device despite the burgeoning FP colour palette available to plant biologists. Here, we show a new platform for stand-off imaging of plant canopies expressing a wide variety of FP genes. The platform-the fluorescence-inducing laser projector (FILP)-uses an ultra-low-noise camera to image a scene illuminated by compact diode lasers of various colours, coupled with emission filters to resolve individual FPs, to phenotype transgenic plants expressing FP genes. Each of the 20 FPs screened in plants were imaged at >3 m using FILP in a laboratory-based laser range. We also show that pairs of co-expressed fluorescence proteins can be imaged in canopies. The FILP system enabled a rapid synthetic promoter screen: starting from 2000 synthetic promoters transfected into protoplasts to FILP-imaged agroinfiltrated Nicotiana benthamiana plants in a matter of weeks, which was useful to characterize a water stress-inducible synthetic promoter. FILP canopy imaging was also accomplished for stably transformed GFP potato and in a split-GFP assay, which illustrates the flexibility of the instrument for analysing fluorescence signals in plant canopies.