Heat stress memory differentially regulates the expression of nitrogen transporter genes in the filamentous red alga ' Bangia' sp. ESS1

Abstract

Introduction: To withstand high temperatures that would be lethal to a plant in the naïve state, land plants must establish heat stress memory. The acquisition of heat stress tolerance via heat stress memory in algae has only been observed in the red alga 'Bangia' sp. ESS1.

Methods: In this study, we further evaluated the intrinsic ability of this alga to establish heat stress memory by monitoring hydrogen peroxide (H₂O₂) production and examining the relationship between heat stress memory and the expression of genes encoding nitrogen transporters, since heat stress generally reduces nitrogen absorption. Next, genes encoding nitrogen transporters were selected from our unpublished transcriptome data of 'Bangia' sp. ESS1.

Results: We observed a reduction in H₂O₂ content when heat stress memory was established in the alga. In addition, six ammonium transporter genes, a single-copy nitrate transporter gene and two urea transporter genes were identified. Two of these nitrogen transporter genes were induced by heat stress but not by heat stress memory, two genes showed heat stress memory-dependent expression, and one gene was induced by both treatments. Heat stress memory therefore differentially regulated the expression of the nitrogen transporter genes by reducing heat stress-inducible gene expression and inducing heat stress memory-dependent gene expression.

Discussion: These findings point to the functional diversity of nitrogen transporter genes, which play different roles under various heat stress conditions. The characteristic effects of heat stress memory on the expression of individual nitrogen transporter genes might represent an indispensable strategy for reducing the threshold of sensitivity to recurrent high-temperature conditions and for maintaining nitrogen absorption under such conditions in 'Bangia' sp. ESS1.

Keywords: gene expression; heat stress; hydrogen peroxide; nitrogen transporter; red alga; stress memory.

Figure 1

Effects of heat stress memory on hydrogen peroxide (H₂O₂) production in ‘Bangia’ sp. ESS1. (A) Schematic representation of the experimental conditions, including priming, recovery, and triggering, used to assess the biological significance of heat stress memory in this study. Seven conditions were employed: control, growth at 15°C (C); priming, incubation at 28°C for 7 days after growth at 15°C (P); recovery from 28°C treatment by incubation at 15°C for 2 days (R); triggering, 32°C treatment for 1 or 6 days (T-1 and T-6, respectively); and direct transfer to a lethal high temperature 32°C for 1 or 6 days (LHT-1 and LHT-6, respectively). (B) Quantitative analysis of H₂O₂ production under various heat stress conditions. H₂O₂ contents in algae treated with the experimental conditions indicated in (A) were quantified; mean values ± SD per 0.2 g sample fresh weight were calculated from three independent experiments. Different letters denote statistically significant differences (p < 0.05), as determined by one-way ANOVA.

Figure 2

Neighbor-joining-based phylogenetic tree of AMTs from ‘Bangia’ sp. ESS1 compared with those of terrestrial plants and other algae. Boxes indicate BE1AMTs and BE1Rh from ‘Bangia’ sp. ESS1. AMTs from Rhodophyta, Chlorophyta, and Ochrophyta are highlighted by red, green, and blue font, respectively. The bootstrap values from 1000 replicates are indicated at the nodes of the tree. The DDBJ/EMBL/GenBank accession numbers of the AMTs and Rhs used in the phylogenetic analysis are shown next to the species names. Bar, 0.2 substitutions per site.

Figure 3

Neighbor-joining-based phylogenetic tree of NRTs from terrestrial plants and algae. The box indicates BE1NRT2 from ‘Bangia’ sp. ESS1. NRT2s from Rhodophyta, Chlorophyta, and Ochrophyta are highlighted by red, green, and blue font, respectively. The bootstrap values from 1000 replicate are indicated at the nodes of the tree. The DDBJ/EMBL/GenBank accession numbers of the NRTs used in the phylogenetic analysis are shown next to the species names. Bar, 0.2 substitutions per site.

Figure 4

Neighbor-joining-based phylogenetic tree of DUR3s from ‘Bangia’ sp. ESS1 compared with those of terrestrial plants and other algae. Boxes indicate BE1DUR3.1 and BE1DUR3.2 from ‘Bangia’ sp. ESS1. DUR3s from Rhodophyta and Chlorophyta are highlighted by red and green font, respectively. The bootstrap values from 1000 replicates are indicated at the nodes of the tree. The DDBJ/EMBL/GenBank accession numbers of the DUR3s used in the phylogenetic analysis are shown next to the species names. Bar, 0.05 substitutions per site.

Figure 5

Differences in the expression patterns of the five BE1AMT1 genes under various heat stress conditions. The expression levels of BE1AMT1.1, BE1AMT1.3, BE1AMT1.4, BE1AMT1.5, and BE1AMT1.7 in algal samples treated with the experimental conditions indicated in Figure 1A were measured by qRT-PCR. Relative mRNA levels, which were normalized to the expression of the Actin gene as the reference (Li et al., 2019a), are mean fold changes compared to control (C) samples, with error bars representing the standard deviations of triplicate experiments (n = 3), each with triple technical replicates for qRT-PCR. ND, not detected. Different letters denote statistically significant differences (p < 0.05), as determined by one-way ANOVA.

Figure 6

Differences in the expression patterns of BE1NRT2 and BE1DUR3 genes under various heat stress conditions. The expression levels of BE1NRT2, BE1DUR3.1, and BE1DUR3.2 in algal samples treated with the experimental conditions indicated in Figure 1A were examined by qRT-PCR. Relative mRNA levels, which were normalized to the expression of the Actin gene as the reference (Li et al., 2019a), are mean fold changes compared to control (C) samples, with error bars representing the standard deviations of triplicate experiments (n = 3), each with triple technical replicates for qRT-PCR. Different letters denote statistically significant differences (p < 0.05), as determined by one-way ANOVA.