Inactivation of rice starch branching enzyme IIb triggers broad and unexpected changes in metabolism by transcriptional reprogramming

Abstract

Starch properties can be modified by mutating genes responsible for the synthesis of amylose and amylopectin in the endosperm. However, little is known about the effects of such targeted modifications on the overall starch biosynthesis pathway and broader metabolism. Here we investigated the effects of mutating the OsSBEIIb gene encoding starch branching enzyme IIb, which is required for amylopectin synthesis in the endosperm. As anticipated, homozygous mutant plants, in which OsSBEIIb was completely inactivated by abolishing the catalytic center and C-terminal regulatory domain, produced opaque seeds with depleted starch reserves. Amylose content in the mutant increased from 19.6 to 27.4% and resistant starch (RS) content increased from 0.2 to 17.2%. Many genes encoding isoforms of AGPase, soluble starch synthase, and other starch branching enzymes were up-regulated, either in their native tissues or in an ectopic manner, whereas genes encoding granule-bound starch synthase, debranching enzymes, pullulanase, and starch phosphorylases were largely down-regulated. There was a general increase in the accumulation of sugars, fatty acids, amino acids, and phytosterols in the mutant endosperm, suggesting that intermediates in the starch biosynthesis pathway increased flux through spillover pathways causing a profound impact on the accumulation of multiple primary and secondary metabolites. Our results provide insights into the broader implications of perturbing starch metabolism in rice endosperm and its impact on the whole plant, which will make it easier to predict the effect of metabolic engineering in cereals for nutritional improvement or the production of valuable metabolites.

Production of High Amylose and Resistant Starch Rice Through Targeted Mutagenesis of Starch Branching Enzyme Iib by Crispr/cas9

“…As expected, OsSBEIIb expression in the homozygous mutants is almost completely knocked down since rice genome contains only one copy of the gene (Yang et al, 2012). The transcript for OsSBEI is unaffected in OsSBEIIb RNAi mutant rice seed (Butardo et al, 2011;Baysal et al, 2020). Consistently, in the current work the mRNA level of SBEI is not affected at all in the mutant lines (Supplemental Fig.…”

“…Down-regulating or eliminating the expression of SBEII in several major crops also leads to increased contents of amylose and RS. For example, editing the exon 12 or exon 18 of OsSBEIIb in the japonica cultivar Nipponbare through CRISPR/Cas9 signi cantly decreases its expression level and signi cantly increases the contents of amylose and RS in the endosperm (Baysal et al, 2020). In the present study, we developed seven OsSBEIIb mutant lines including both heterozygous and homozygous lines through CRISPR/Cas9 in the low amylose and low RS japonica rice cultivar TNG82 for molecular and physiological studies.…”

“…The decreases in total SBE activity among the mutants were mainly due to the lower OsSBEIIb expression levels with a positive correlation coe cient of r = +0.95 (Supplemental Figure 2A). The substantial activities remaining in the mutant grains are presumably due to the normal expression of other SBEs (Baysal et al, 2020).…”

“…Signi cant increase of AC also changes starch chemical properties, e.g. decreased swelling power and viscosity or increased gelatinization temperature (Wei et al, 2010a; Butardo et al, 2011;Yang et al, 2012;Sun et al, 2017;Baysal et al, 2020). These studies suggest that overexpression of GBSSI to increase amylose biosynthesis or down-reulation of SBEIIb, SBEI, SSIIa and SSIIIa to inhibit amylopectin biosynthesis can effectively increase AC in the endosperms of cereal crops.…”

Multiscale plant modeling: from genome to phenome and beyond

“…However, similar to just connecting plant genomes and phenomes, predicting emergent phenotypic responses based solely on metabolic models are difficult. Integrating empirical and mechanistic modeling approaches [3,4,[13][14][15] and creating models that span across biological levels through integrative multiscale modeling (Figure 1) is necessary to understand how plants respond to a changing climate [16] or to explore how plants can be engineered to achieve specific phenotypic goals [17].…”