Divergent roles of IREG/Ferroportin transporters from the nickel hyperaccumulator Leucocroton havanensis.
Dubiel Alfonso GonzálezVanesa Sánchez García de la TorreRolando Reyes FernándezLouise BarreauSylvain MerlotPublished in: Physiologia plantarum (2024)
In response to our ever-increasing demand for metals, phytotechnologies are being developed to limit the environmental impact of conventional metal mining. However, the development of these technologies, which rely on plant species able to tolerate and accumulate metals, is partly limited by our lack of knowledge of the underlying molecular mechanisms. In this work, we aimed to better understand the role of metal transporters of the IRON REGULATED 1/FERROPORTIN (IREG/FPN) family from the nickel hyperaccumulator Leucocroton havanensis from the Euphorbiaceae family. Using transcriptomic data, we identified two homologous genes, LhavIREG1 and LhavIREG2, encoding divalent metal transporters of the IREG/FPN family. Both genes are expressed at similar levels in shoots, but LhavIREG1 shows higher expression in roots. The heterologous expression of these transporters in A. thaliana revealed that LhavIREG1 is localized to the plasma membrane, whereas LhavIREG2 is located on the vacuole. In addition, the expression of each gene induced a significant increase in nickel tolerance. Taken together, our data suggest that LhavIREG2 is involved in nickel sequestration in vacuoles of leaf cells, whereas LhavIREG1 is mainly involved in nickel translocation from roots to shoots, but could also be involved in metal sequestration in cell walls. Our results suggest that paralogous IREG/FPN transporters may play complementary roles in nickel hyperaccumulation in plants.
Keyphrases
- reduced graphene oxide
- poor prognosis
- oxide nanoparticles
- carbon nanotubes
- single cell
- genome wide
- metal organic framework
- induced apoptosis
- electronic health record
- binding protein
- gold nanoparticles
- big data
- cell proliferation
- gene expression
- dna methylation
- oxidative stress
- high glucose
- cell therapy
- stem cells
- diabetic rats
- deep learning
- artificial intelligence
- machine learning
- drug induced
- mesenchymal stem cells