Systems Level Approaches Towards Understanding Heavy Metal Response and Resistance in Plants

Uptake of toxic heavy metals and metalloids in plants primarily occurs through transporters designed to import essential nutrients. Cadmium uptake is mediated by zinc and iron (ZIP) transporters and arsenic by organic phosphate transporters. Therefore plants have developed a complex and dynamic system to detoxify and sequester heavy metals to minimize detrimental effects. Exposure to heavy metals causes rapid and diverse changes in gene expression to control and initiate the detoxification machinery. While several key mechanisms in the chelation and transport pathways have been identified, the signaling network behind this rapid gene regulation remains largely unknown. We are pursuing two distinct methods In order to uncover components of the Cd-specific transcriptional response network. First, using our Cd-dependent transcriptome data sets, we generated an Arabidopsis line carrying a cadmium-inducible promoter (SULTR1;2) fused to a luciferase reporter gene, which was then mutagenized using ethyl methanesulfonate (EMS). Mutants were then screened for shifts in Cd-inducible luciferase responses. Identified mutants were categorized into three groups based on the response: super response to cadmium (SRC), constitutive response to cadmium (CRC), and non-response or reduced response to cadmium (NRC). Two non-response mutants, NRC1 and NRC2, have been mapped and characterized as γ-glutamylcysteine synthetase and glutathione synthetase, respectively, both of which are involved in the generation of chelators essential for heavy metal detoxification. The NRC2 mutation is the first viable recessive mutation in the glutathione synthetase gene. We are currently working to map and characterize two additional mutants, one super response mutant, SRC1, and one constitutive response mutant, CRC1, using segregation and genomic resequencing.

                Traditional forward genetic screens in plants are limited in the identification of homologous genes with overlapping functions, with only approximately 10% of Arabidopsis genes having been linked to a single-gene mutant phenotype. Thus (partial) genetic redundancies greatly limit forward genetic screens. To address over-lapping gene functions on a genomic systems level scale, the P.I.’s laboratory has computationally designed artificial microRNA (amiRNA)  libraries using over 90,000 hours CPU time at the San Diego Supercomputer Center, for genome-wide knock-down of homologous gene family members. We generated 10 amiRNA libraries consisting of 22,000 amiRNAs in total, with 96% of the amiRNAs targeting 2 to 5 genes. This enables rapid progression from phenotype to gene. System level screens of amiRNA plants grown in the presence of cadmium or arsenic are identifying a wealth of new genes that affect these toxic heavy metal and metalloid responses.