bioRxivBiochemistryPreprint
Differential Boric Acid and Water Transport in Type I and Type II Pores of Arabidopsis Nodulin 26-Intrinsic Protein
Z. G. Beamer, P. Routray, R. Agarwal, T. Li, K. M. Gibson, K. E. Ostrouchov, J. C. Smith, D. M. Roberts
Abstract
Nodulin-26 intrinsic proteins (NIPs) are plant-specific multifunctional aquaporin-like channels that are phylogenetically and structurally segregated into three subfamilies: NIP I, II, and III. Each subfamily has a characteristic selectivity filter sequence (the "aromatic-arginine" region, or ar/R) that controls substrate transport specificity based on steric constraints, hydrophobicity, and the spatial orientation of hydrogen bonding moieties. All three NIP subfamilies transport metalloid hydroxides, both beneficial as well as toxic, but with different selectivities. Here we investigated the B, As, and water selectivity of representative Arabidopsis thaliana NIP I and II proteins as well as their ar/R mutants in transport assays as well as through B complementation analysis in the B sensitive nip5;1 mutant background. All NIP proteins, and their ar/R mutants, showed equal permeability to arsenite, but showed differences in boric acid and aquaporin activities that was linked to the amino acid at the helix 2 (H2) position of the ar/R filter (Ala for NIP II and Trp for NIP I). The presence of an alanine at this position in NIP II proteins enhances boric acid permeability and drastically reduces the aquaporin/water permeability of the channel. A NIP II structural model generated from the AlphaFold2 resource and evaluated by MD simulation shows that the alanine results in a wider ar/R pore that accommodates the trigonal boric acid molecule and may allow gating of the pore in a manner that affects water permeability. In contrast, NIP I proteins adopt a more classical aquaporin/glyceroporin arrangement in the ar/R that allows metalloid permeability, although with greater selectivity, as well as permeation by water.
- organism: Arabidopsis
- assay: proteomics
- research focus: cell type annotation
- research focus: differential expression
- approach: deep learning
- approach: statistical model
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