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. 2021 Aug;172(4):1853-1866.
doi: 10.1111/ppl.13392. Epub 2021 Apr 1.

A drought-responsive rice amidohydrolase is the elusive plant guanine deaminase with the potential to modulate the epigenome

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A drought-responsive rice amidohydrolase is the elusive plant guanine deaminase with the potential to modulate the epigenome

Dhananjay Gotarkar et al. Physiol Plant. 2021 Aug.

Abstract

Drought stress in plants causes differential expression of numerous genes. One of these differentially expressed genes in rice is a specific amidohydrolase. We characterized this amidohydrolase gene on the rice chromosome 12 as the first plant guanine deaminase (OsGDA1). The biochemical activity of GDA is known from tea and coffee plants where its catalytic product, xanthine, is the precursor for theine and caffeine. However, no plant gene that is coding for GDA is known so far. Recombinant OsGDA1 converted guanine to xanthine in vitro. Measurement of guanine and xanthine contents in the OsGDA1 knockout (KO) line and in the wild type Tainung 67 rice plants also suggested GDA activity in vivo. The content of cellular xanthine is important because of its catabolic products allantoin, ureides, and urea which play roles in water and nitrogen stress tolerance among others. The identification of OsGDA1 fills a critical gap in the S-adenosyl-methionine (SAM) to xanthine pathway. SAM is converted to S-adenosyl-homocysteine (SAH) and finally to xanthine. SAH is a potent inhibitor of DNA methyltransferases, the reduction of which leads to increased DNA methylation and gene silencing in Arabidopsis. We report that the OsGDA1 KO line exhibited a decrease in SAM, SAH and adenosine and an increase in rice genome methylation. The OsGDA1 protein phylogeny combined with mutational protein destabilization analysis suggested artificial selection for null mutants, which could affect genome methylation as in the KO line. Limited information on genes that may affect epigenetics indirectly requires deeper insights into such a role and effect of purine catabolism and related genetic networks.

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Figures

FIGURE 1
FIGURE 1
In vitro assay of recombinant OsGDA1 with guanine. (A) HPLC elution peak for the standards (1) xanthine and (2) guanine. (B, C) Activity of the recombinant OsGDA1 of Vandana and Way Rarem, respectively. More of the guanine substrate (s) is utilized and more of the xanthine product (p) is produced by the recombinant protein from Way Rarem (C), when all other variables are constant in the assay. X axis represents time in minutes and Y axis represents the arbitrary units (AU). Even if the Vandana protein was increased, the activity was lower than Way Rarem
FIGURE 2
FIGURE 2
Guanine and xanthine content analysis in leaves and roots of the KO and WT plants. Barplots representing (A) guanine content, (B) xanthine content in KO (in grey), and WT (in black) in the leaves and roots sampled at 3 weeks (21 days) growth stage. In the roots of the KO and WT lines, there was a difference between the KO and WT plants in both the guanine and xanthine content (t(3) = 5.79, P = <0.001 and t(3) = 2.17, P = 0.06, respectively). No significant difference was noted in either the guanine or xanthine content in the leaves at the same growth stage
FIGURE 3
FIGURE 3
Neighbor‐joining tree of wild and cultivated rice based on the protein sequence. The percentage of replicate trees in which the associated accessions clustered together in the bootstrap test (1000 replicates) are shown next to the branches. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. Evolutionary distances were computed using the Poisson correction method and are in units of the number of amino acid substitutions per site. The analysis involved 472 amino acid sequences. All positions containing gaps and missing data were excluded. There were a total of 131 positions in the final dataset. Evolutionary analyses were conducted in MEGA7. The three clades are shown with numbers 1, 2, and 3
FIGURE 4
FIGURE 4
Cytosine methylation, SAH, SAM, and adenosine content analysis in two contrasting sets of rice lines. Barplots representing (A) percentage of genomic cytosine methylation, (B) S‐Adenosyl homocysteine content, (C) S‐Adenosyl methionine content, and (D) adenosine content in KO, WT, Vandana, and 481‐B in leaves sampled at 21 day growth stage. Significance levels between KO and WT indicate P < 0.01 represented with “**”P < 0.05 with “*” and P < 0.1 with “.”. There was a difference between KO and WT lines in the percentage of methylation (t(5) = 4.65, P = 0.002); in the content of SAM [t (5) = −3.16, P = 0.024); and also in SAH content (t(5) = −1.85, P = 0.10) but not in the adenosine content. Differences were also found between Vandana and 481‐B in the percentage of methylation (t(3) = 7.82, P = 0.008), SAH content (t(3) = −2.56, P = 0.081) and adenosine content (t(3) = −2.97, P = 0.04) but not in SAM content

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