Re-engineering a lost trait:IPD3, a master regulator of arbuscular mycorrhizal symbiosis, affects genes for immunity and metabolism of non-host Arabidopsis when restored long after its evolutionary loss

Abstract

Arbuscular mycorrhizal symbiosis (AM) is a beneficial trait originating with the first land plants, which has subsequently been lost by species scattered throughout the radiation of plant diversity to the present day, including the model Arabidopsis thaliana. To explore why an apparently beneficial trait would be repeatedly lost, we generated Arabidopsis plants expressing a constitutively active form of Interacting Protein of DMI3, a key transcription factor that enables AM within the Common Symbiosis Pathway, which was lost from Arabidopsis along with the AM host trait. We characterize the transcriptomic effect of expressing IPD3 in Arabidopsis with and without exposure to the AM fungus (AMF) Rhizophagus irregularis, and compare these results to the AM model Lotus japonicus and its ipd3 knockout mutant cyclops-4. Despite its long history as a non-AM species, restoring IPD3 in the form of its constitutively active DNA-binding domain to Arabidopsis altered expression of specific gene networks. Surprisingly, the effect of expressing IPD3 in Arabidopsis and knocking it out in Lotus was strongest in plants not exposed to AMF, which is revealed to be due to changes in IPD3 genotype causing a transcriptional state which partially mimics AMF exposure in non-inoculated plants. Our results indicate that despite the long interval since loss of AM and IPD3 in Arabidopsis, molecular connections to symbiosis machinery remain in place in this nonAM species, with implications for both basic science and the prospect of engineering this trait for agriculture.

Arbuscular Mycorrhizal Fungi and Higher Plants

“…A set of conserved genes called "Symbiotic Toolkit" determine the ability of host plants to establish a functional symbiosis (Delaux et al 2013). Although there is little experimental evidence about the possible cause of AM loss, such as carbon cost, changes in resistance to pathogens and insects, and changes in lifestyle and root morphology, significant genetic evidences have been found for evolutionary loss of AM colonization (Delaux et al 2014;Radhakrishnan et al 2020;Hornstein et al 2023). In all non-mycorrhizal plants belonging to diverse taxonomic groups, a common subset of specific genes, e.g., the "common symbiosis pathway" (CPS) genes involved in signal perception and transduction, are absent (Table 2.1) (Genre et al 2020;Radhakrishnan et al 2020).…”

AraMultiOmics: a tool for generating multi-omics features for downstream statistical analysis to infer the molecular basis of symbiosis among non-host plant Arabidopsis thaliana, host plant, and arbuscular mycorrhizal fungi

“…We selected 12 categories from PO: defense, metabolism, phloem, protein_sorting, RNA, secretion, signal, sorting, transport, transporter, vesicular, and xylem. In addition, we incorporated IPD3 DEG module data, where module classification was obtained by applying weighted gene co-expression network analysis to transcriptome data of A. thaliana samples [5].…”

“…In addition, we created datasets according to GO/PO categories (e.g., signal transduction, protein sorting, defense and cell rescue, and abiotic stimuli and development), enzymes in volatile organic compound reactions (VOC), and DEG homologs (CYP76C1, CYP76C2, CYP76C3, CYP76C4, CYP76C5, CYP76C6, GUS1, GUS2, GUS3, CSLG1, CSLG2, CSLG3, VTE1, VTE5, HAI1, HAI2, HAI3). Then, we applied clustering and classification methods for demonstration purposes [4,5]. The program provides a convenient means to generate datasets with various features that can be conjoined with downstream statistical analyses to elucidate the molecular interactions of AM symbiosis.…”

“…In the third one, we created datasets according to GO/PO categories (e.g., signal transduction, subcellular localization sorting, defense and cell rescue, and abiotic stimuli and development). Then, we included examples of downstream statistical analyses-clustering and classification methods for demonstration purposes [4,5]. The program provides a convenient means to generate datasets with various features that can be conjoined with downstream statistical analyses to elucidate the molecular interactions of AM symbiosis.…”

“…Specifically, the program consisted of 8 modules where each module contains features derived from existing databases and software: 1) protein binding sites/open chromatin regions identified from chip-seq and their derivatives (ChIP-Hub, JASPAR, PCSD (Plant Chromatin State Database)), 2) DNA structure and metal binding profile (cran R gquad package (v2.1-2), QGRS program, and mebipred program), 3) DNA-TF binding profiles (TF-COMB (TF Co-Occurrence using Market Basket analysis. V0.1.0)), 4) Protein domain-domain interaction and membrane protein orientation (3did (three-dimensional interacting domains) and OPM (Orientations of Proteins in Membranes)), 5) metabolic pathway analysis (PMN (Plant Metabolic Network)), 6) DNA methylation and gene expression associated with ion concentration phenotype (Epigenome-wide association study (EWAS), transcriptome-wide association study (TWAS), and muti-omics association (AtMAD), 7) GO, PO, IPD3 DEG type classification (TAIR, Hornstein et al), 8) Medicago COG (String database) [5,[13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]. To compare the effects of AM molecules on PNI and PPI between host and non-host plants, we incorporated existing programs for predicting DNA structures.…”