HRA1 Is a Low Oxygen-Inducible Nuclear Factor

The A. thaliana Columbia-0 genome encodes 30 genes belonging to the plant-specific family of trihelix TFs [14]. A survey of public transcriptomic data showed that the gene At3g10040 (HRA1) is the only trihelix family member up-regulated by oxygen deprivation (Figure S1). Trihelix TFs are induced by low oxygen in different species (Table S1 and Figure S2) and therefore appear to be a component of the conserved stress response strategy in land plants [13]. Moreover, the HRA1 transcript, detected at medium-to-low levels throughout the plant life cycle (Figure S3A), was most strongly induced by short-term oxygen deficiency in plants subjected to a range of abiotic stress conditions (Figure 1A). Hypoxia enhanced the activity of the HRA1 promoter, as visualized by means of a promHRA1:GUS transgenic line (Figure 1B), and led to over 15-fold elevation of HRA1 mRNA in both the leaves and roots of seedlings (Figure S3B). A survey of our previously generated data of polysome-associated transcripts under the same hypoxia system [15] showed that this was accompanied by active loading of HRA1 mRNA onto polysomes (Figure S3C), indicating that the synthesis of HRA1 protein occurs during the stress. When HRA1 expression was monitored over time in hypoxia-treated seedlings, HRA1 mRNA accumulation was induced rapidly but transiently, whereas that of hypoxia marker ADH1 increased slowly and steadily during the stress (Figure 1C). This peculiar dynamics of gene expression hinted at a possible role for HRA1 in the early phase of the low oxygen response.

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Figure 1. HRA1 is a low oxygen-inducible gene from Arabidopsis.

(A) HRA1 mRNA steady state levels in hypoxia-treated seedlings, in comparison with other abiotic stress treatments. Data are mean ± s.d. (n = 3). (B) Visualization of HRA1 promoter activity by GUS-reporter staining. Nucleotide positions in the schematic are relative to HRA1 transcription start site. Scale bar, 2 mm. (C) Transcript accumulation of HRA1 and the hypoxic marker ADH1 in seedlings, over an initial and more prolonged time course of sublethal hypoxia (upper and lower left diagrams). Data are mean ± s.d. (n = 3).

https://doi.org/10.1371/journal.pbio.1001950.g001

HRA1 Represses Gene Transcription During Hypoxia

A green fluorescent protein (GFP) reporter fusion demonstrated that the HRA1 protein localized to the cell nucleus (Figure 2A), consistent with its prediction as a TF. To investigate the role of HRA1 in transcription, we performed a microarray analysis and compared the hypoxic reconfiguration of the transcriptome between Cauliflower Mosaic Virus 35S:HRA1:FLAG transgenics (OE-HRA1) and wild type Arabidopsis seedlings (Figure 2B and Table S2). Overexpression of HRA1 significantly reduced the up-regulation of 30 out of the 49 (61%) core hypoxia-responsive genes [13] induced in the wild type after short-term (2 h) hypoxia (|SLR|≥1, FDR<0.01) (Figure 2C), revealing the ability of HRA1 to broadly affect the hypoxic transcriptome. This included genes encoding key enzymes for anaerobic metabolism, such as the marker genes ADH1 and PDC1. The inhibition of hypoxic transcript accumulation by HRA1 overexpression contrasted to the constitutive up-regulation of the hypoxia-responsive genes observed in 35S:HA:RAP2.12 transgenic seedlings, which constitutively accumulate RAP2.12 due to masking of its N-terminus from the N-end rule machinery [7]. The hypoxic induction of 43% (7/16) of the RAP2.12 up-regulated genes was dampened by ectopic HRA1 expression (Figure 2C), suggesting there is antagonism between HRA1 and RAP2.12. Consistent with the dramatic reduction in ADH1 mRNA up-regulation, we found out that ADH activity was significantly repressed in hypoxic OE-HRA1 seedlings (Figure 2D). It was this squelching of low oxygen induction of many hypoxia-responsive genes that led us to name At3g10040 HYPOXIA RESPONSE ATTENUATOR 1.

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Figure 2. The nuclear factor HRA1 attenuates the expression of hypoxia-responsive genes.

(A) Subcellular localization of the HRA1:GFP protein in root cells. Nuclei were visualized by DAPI staining. Scale bar, 30 µm. (B) Differential gene expression in OE-HRA1 and wild type seedlings under air or hypoxia (2 h), compared with 35S:HA:RAP2.12 transgenics. (C) Venn diagram describing the overlap between genes with opposing regulation by HRA1 or RAP2.12 and 49 genes induced across cell types by hypoxia in wild type seedlings [13]. (D) ADH enzyme activity is affected by altered levels of HRA1 in plants at the seedling stage (mean ± s.d., one-way ANOVA, p<0.05, n = 3). Hypoxia, 3 h.

https://doi.org/10.1371/journal.pbio.1001950.g002

HRA1 Mediates Tissue-Specific Responses During Submergence-Induced Hypoxia

The impact of HRA1 on hypoxia-responsive gene expression prompted us to assess how altered levels of HRA1 expression affect plant performance under submergence-induced hypoxia. We compared two independent 35S:HRA1:FLAG transgenic genotypes (OE-HRA1#1 and #2) (Figure S4A) and two independent T-DNA insertion homozygous mutants (hra1-1 and hra1-2) (Figures S4B–C and S5) with the wild type. This revealed that both overexpression and failure to produce a full-length HRA1 transcript reduced the ability of plants to withstand the stress. When tested for tolerance to complete submergence in the dark with two distinct experimental setups, wild type Arabidopsis plants endured the stress significantly longer than OE-HRA1 plants at the 10-leaf rosette stage (Figure S6A) and, in older rosettes prior to bolting, recovered better than either OE-HRA1 or hra1-1 plants (Figure 3A and B). Underwater petiole elongation, a trait recognized as a part of the escape strategy from flooding in semiaquatic species (i.e., deepwater rice and the wetland species Rumex palustris) [8], was unaffected by HRA1 (Figure S6B), consistent with previous reports of a limited overall correlation between the trait and flooding survival of mutants in genes up-regulated by hypoxia and Arabidopsis accessions [16],[17]. Moreover, the analysis of the total soluble carbohydrate content in plants prior to submergence allowed us to rule out that a significant difference in the available reserves accounts for the poorer performance of the noticeably smaller OE-HRA1#1 plants (Figure S7). This was again in line with previous reports of a lack of correlation between carbohydrate content before submergence and stress survival in Arabidopsis [17]. The observation that altered HRA1 levels modified performance under submergence, at two stages of rosette development and in distinct growth environments, supports the hypothesis of a distinct role for the factor during the stress.

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Figure 3. HRA1 contributes to plant submergence survival.

(A) Effect of HRA1 misexpression on rosette growth in air, or after recovery from 72 h submergence in darkness. Scale bar, 2 cm. (B) Percentage of plants surviving flooding-induced hypoxia (n = 5), dry weight of rosette plants kept under control growth conditions (n = 6), and dry weight of rosettes after postsubmergence recovery (n = 6). Data are mean ± s.d.; *p<0.05, significant differences from the wild type after one-way ANOVA. (C) HRA1 regulates target gene transcripts in an age-dependent manner in leaves of plants treated with complete submergence. Transcripts were measured before submergence (“control conditions”), after 4 h submergence in darkness (“submergence”), and after 1 h de-submergence in the light (“reoxygenation”). Relative transcript values were calculated using old leaves of the wild type under control conditions as the reference sample. Data are mean ± s.d. (n = 3); letters indicate statistically significant differences between genotypes after one-way ANOVA (p<0.05) performed independently on each leaf type. (D) Western blot analysis of ADH and PDC protein accumulation in leaves at different developmental stages from control and submerged (4 h) plants. The full-size images of the hybridized membranes can be found in Figure S10. (E) Stability of the translational fusion RAP2.12:RrLuc protein (RrLuc, Renilla reniformis luciferase) in Arabidopsis mesophyll protoplasts upon transfection with increasing amounts of 35S:HRA1. RAP2.12:RrLuc abundance was evaluated from the RrLuc relative activity, measured through a dual luciferase assay. Data are mean ± s.d. (n = 4), and the asterisks indicate statistically significant differences (p<0.05) from protoplasts expressing RAP2.12:RrLuc alone, after one-way ANOVA.

https://doi.org/10.1371/journal.pbio.1001950.g003

A closer examination of the phenotype of the plants at the end of the recovery period revealed that susceptibility to submergence-induced hypoxia differed in young and older rosette leaves. As compared to the wild type, young leaves emerging from the shoot apex and the shoot apical meristem region were more sensitive in the hra1-1 mutant, and generally unable to recover during postsubmergence. Contrastingly, the fully expanded and mature leaves of OE-HRA1#1 plants were more sensitive to dark submergence than the wild type, but the shoot apical meristem performance was less damaged (Figure 3A, see magnified insert). This suggested that HRA1 is imperative for an effective anaerobic response in the meristematic zone and young leaves.

Following preliminary evaluation of temporal regulation of HRA1 expression in rosette leaves during submergence, which demonstrated an early peak of gene expression after 2 h of stress (Figure S8), we selected 4 h of submergence as a suitable time to study distinctions in gene transcript and protein accumulation in young and fully expanded leaves of wild type and HRA1 mutant genotypes. Firstly, we then found out that in young leaves, but not in older ones, the expression of the hypoxia marker genes ADH1 and PDC1 were differentially regulated by manipulation of HRA1. In control and submergence treated plants, ADH1 and PDC1 expression was enhanced in hra1-1 and dampened in young OE-HRA1 rosette leaves as compared to the wild type (Figure 3C). In all three genotypes, hypoxic gene expression was promptly reversed to presubmergence levels upon reaeration of the plants (Figure 3C, “Reoxygenation”), in agreement with earlier studies [7],[18]. The enhancement in anaerobic gene expression observed in young leaves of hra1-1 was also seen in the independent hra1-2 mutant (Figure S9), reinforcing the hypothesis that mutation of HRA1 leads to altered regulation of the hypoxic response.

Secondly, Western blot analyses performed to detect the products of ADH1 and all five PDCs [19] indicated that elevated levels of these transcripts in young leaves of hra1-1 plants was accompanied by higher hypoxic production of the encoded proteins (Figures 3D and S10). Although in older leaves some enhancement of PDC accumulation in submergence was visible in the mutant as compared to the wild type, ADH was always below the limit of detection. In younger leaves, contrastingly, ADH protein levels were enhanced in hra1-1 already under normoxic conditions. These results suggest that HRA1 plays a key role in negatively regulating the induction of ADH1 and PDC1 in younger tissues of rosette-stage plants.

We also considered that HRA1 expression could impact steady-state levels of its upstream regulator RAP2.12. To do so, we evaluated the effect of HRA1 on RAP2.12 protein stability, using mesophyll protoplasts that were transiently transfected with a 35S:RAP2.12:RrLuc plasmid construct. The stability of RAP2.12 was inferred from the activity of a C-terminal translational fusion of RAP2.12 to the Renilla reniformis luciferase (RrLuc) reporter. As RrLuc activity was unaffected by concurrent transfection of the 35S:HRA1 effector, we conclude that HRA1 expression does not affect RAP2.12 stability, at least in isolated leaf protoplasts (Figure 3E). Altogether, these data, presented in Figure 3, support the conclusion that HRA1 acts to limit accumulation of transcripts and the encoded proteins associated with anaerobic metabolism, even in air, particularly in younger rosette tissue.

HRA1 Contributes to Effective Anaerobic Responses and Normal Plant Development

The submergence survival studies suggested that HRA1 expression provides vital control of the anaerobic response in the meristematic region and young leaves. To further investigate the spatial and temporal regulation of HRA1, we monitored transgenics expressing promHRA1:GUS. The beta-glucuronidase (GUS) reporter confirmed that basal HRA1 promoter activity, detectable under normal growth conditions, was restricted to the shoot apical region and leaf vasculature in aboveground tissues (Figure S11, “Control”), and was pronounced in roots as well (Figure 1B). This pattern of expression is consistent with the hypothesis that HRA1 is active in cells experiencing physiological hypoxia, due to higher oxygen demand, lower permeability to oxygen, or a hypoxic environment [20],[21]. The elevated levels of hypoxia marker gene transcripts in the shoot apical area under normoxia suggest that this region is physiologically hypoxic (Figure 3C), as reported previously [22]. By use of the promHRA1:GUS transgenics, we also determined that submergence primarily enhanced GUS activity in the younger rosette tissues and to a much lesser extent in adult leaves, except within the vasculature (Figure S11, “Submergence”).

This pattern of GUS staining correlated well with the tissue-specific effect exerted by HRA1 on submergence tolerance, as described above (Figure 3A). In genotypes with altered HRA1 expression, the absence of a fully functional HRA1 protein in hra1 shoot meristem tissue led to its higher susceptibility to submergence. On the other hand, ectopic expression of HRA1 in older rosette leaves of OE-HRA1 plants reduced their survival of submergence and prolonged darkness, possibly due to accelerated senescence of older leaves (Figure S12).

Our data showed that HRA1 balances low oxygen acclimation responses, but also suggested that proper spatial expression of HRA1 is required for normal vegetative development. Overexpression of either the native HRA1 protein in OE-HRA1#3 plants or a FLAG-tagged protein in OE-HRA1#1 and #2 plants caused a pleiotropic phenotype that included reduced rosette size, due to shortened petiole length and altered leaf index, slower rosette growth (Figure S13A and B), increased leaf anthocyanin content (Figure S13B), partial loss of apical dominance, delayed flowering, and reduced seed production (Figure S13C). The conservation of these phenotypes across three independent transgenic lines allowed us to recognize their cause in the ectopic expression of high HRA1 levels in the whole plant, rather than ascribe it to random integration of the transgenes in unrelated genomic loci. We speculate that, although sustained HRA1 expression is beneficial in rapidly dividing and expanding leaf primordia under normal growth conditions, abnormal HRA1 accumulation in mature leaves has a negative impact on plant development. Moreover, because hra1-1 and hra1-2 showed no differences from the wild type under normal growth conditions (Figure S13), we can conclude that mutations in the 3′ region of the HRA1 transcript (Figure S4B and S5) particularly affect the hypoxic pathway (Figure 3A–D) but do not relate to the developmental phenotypes shown here.

HRA1 Associates with Few Differentially Regulated Genes in Hypoxic Seedlings

To gain insight into the role of HRA1 dampening core hypoxia gene transcription during hypoxia, we performed chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq analysis) using seedlings deprived of oxygen for 2 h, in the same manner as the transcriptome analysis. To identify chromatin bound by HRA1-FLAG, OE-HRA1#1 and Col-0 seedling tissue was cross-linked, nuclei were isolated, and immunopurification performed with a FLAG antibody. The Col-0 sample was used as a control to monitor nonspecific immunopurification. Deep sequencing of ∼100 bp fragments yielded 146 peak-to-gene associations (Table S3), corresponding to putative HRA1 target genes, 42% of which (62 elements) fell 5′ of the predicted transcription start sites (Figure S14A). We then focused on the 1,295 differentially expressed genes (DEGs) in the microarray dataset and found out that seven of the HRA1 binding sites resided on genes significantly regulated by hypoxia and/or HRA1 overexpression (HRA1; RAV1, At1g13260; HUP7, At1g43800; a hydroxyproline-rich glycoprotein family protein coding gene, At1g31310; WRKY7, At4g24240; CYP78A6, At2g46660; DCL1, At1g01040) (Figure S14B). The small number of stress-responsive genes identified by ChIP of HRA1 suggests that its effect on the hypoxia-responsive gene transcription may be mediated by other DNA binding factors, rather than HRA1's ability to recognize DNA. Finally, of the candidate targets of HRA1, only HUP7 and HRA1 itself (Figure 4A and Table S4) were constitutively up-regulated by HA-RAP2.12 and less hypoxia-induced in OE-HRA1 plants (Figure S14C). This led us to consider that repression of hypoxia-responsive genes by HRA1 was largely independent of its direct association to chromatin of the genes it regulates.

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Figure 4. HRA1 modulates transcription of anaerobic genes through protein–protein interaction with RAP2.12.

(A) HRA1 binding site on the upstream region of the HRA1 gene. The number next to the peak indicates the peak summit. ChIP-seq peak area for HRA1 was subsequently divided into six regions for confirmation of DNA binding using ChIP-qPCR (see Table S4 for primer sequences). TSS, transcription start site. (B) Yeast-two-hybrid assay between an HRA1 C-terminal fragment (HRA1_194–431) and the five Arabidopsis ERF-VII proteins. AD, activation domain; DBD, DNA binding domain; UAS, upstream activating sequence. SC-LW, control medium −Leu −Trp; SC-LWH+3AT, selective medium −Leu −Trp −His +3AT; LacZ, β-galactosidase assay. (C) Bimolecular fluorescence complementation between HRA1 and RAP2.12 in Arabidopsis mesophyll protoplasts. DAPI staining indicates the position of the nucleus. Scale bar, 20 µm. (D) Transcriptional activation of the PDC1 promoter, visualized through a firefly luciferase (PpLuc) reporter fusion, by RAP2.12 alone (blue bars) and in combination with HRA1 (yellow bars) or its C-terminal fragment HRA1_194–431 (orange bars). Data are mean ± s.d. (n = 4). (E) Dual luciferase assay showing that HRA1 repression of RAP2.12 is independent of HRA1 binding to DNA. A heterologous promoter made up of four repeats of the yeast GAL4 upstream activating sequence (“GAL4 UAS”) was introduced into plant protoplasts and could only be recognized by chimeric GAL4DBD (GAL4 DNA binding domain)-containing TFs, in this case by RAP2.12-GAL4DBD [7]. GFP was used as a negative control, as a RAP2.12 noninteracting protein. Data are mean ± s.d. (n = 3); *p<0.05, statistically significant difference from the positive interaction produced by RAP2.12-GAL4DBD.

https://doi.org/10.1371/journal.pbio.1001950.g004

HRA1 Directly Interacts with the ERF-VII TF RAP2.12

We hypothesized that HRA1 could attenuate hypoxia-responsive gene expression by directly inhibiting RAP2.12 activity. To address this, we first examined whether protein–protein interaction occurs between HRA1 and RAP2.12. Previously, interaction between rice GTγ-clade trihelix protein LOC_Os11g06410 (SAB18) (Figure S2) and the ERF-VII TFs SUBMERGENCE1A (SUB1A) and the related SUB1C (LOC_Os09g11460) was reported in a nondirected yeast-two-hybrid screen [23]. We confirmed that HRA1 and RAP2.12 interact in the heterologous yeast-two-hybrid system (Figures 4B and S15A–C). By systematically testing different combinations of full-length and truncated versions of HRA1 and RAP2.12 (Figure S15A), we determined that, firstly, the conserved C-terminal region rather than the trihelix domain of HRA1 was required for RAP2.12 association (Figures 4B and S15B) and, secondly, the N-terminal portion of the ERF-VII (RAP2.12_1–123) was sufficient for interaction (Figure S15C), while its DNA binding domain might enhance the association (Figure S15B). The interaction between HRA1 and RAP2.12 was subsequently validated in planta by means of bimolecular fluorescence complementation using Arabidopsis protoplasts (Figure 4C).

We also tested HRA1 interaction with the other four Arabidopsis ERF-VII factors in the yeast-two-hybrid system (Figure 4B). Interestingly, only RAP2.12 interacted with the HRA1 protein, consistent with the fact that the RAP2.12 1–123 region, which was sufficient for binding, is poorly conserved among Arabidopsis ERF-VII sequences (with the exception of the N-terminal region, critical to N-end rule regulation, which was anyway not required for HRA1 interaction in planta; Figure 4C). It remains an open question why no interaction was observed with RAP2.2, which has the highest level of sequence similarity with the RAP2.12 protein in the interaction region.

HRA1 Modulates the Activity of the ERF-VII TF RAP2.12

With the knowledge that HRA1 and RAP2.12 interact, we investigated if the interaction could account for HRA1-mediated attenuation of RAP2.12-driven transcriptional activation. Towards this goal, we used a firefly luciferase (PpLuc) reporter fusion to measure the activity of the RAP2.12-responsive PDC1 promoter (−911 to −1 relative to the start codon) in transiently transfected Arabidopsis mesophyll protoplasts. We confirmed that 35S:RAP2.12_14–358 effector plasmid DNA enhanced the luciferase activity of promPDC1:PpLuc (Figure 4D). When increasing amounts of 35S:HRA1 were co-transfected, the luciferase activity gradually fell towards basal levels, indicating that RAP2.12 potential in promPDC1:PpLuc transactivation was negatively affected by HRA1, presumably due to the interaction between factors. Inhibition of promPDC1:PpLuc expression was similarly achieved by concurrent expression of 35S:HRA1_194–431 (Figure 4D), which lacked the trihelix DNA binding domain (Figure S15A) but retained the C-terminal region that allowed interaction with RAP2.12 in the yeast-two-hybrid assay (Figures 4B and S15B). This demonstrates that the repression of RAP2.12 activation of PDC1 transcription by HRA1 was independent of the trihelix domain and, therefore, most likely the TF's binding of DNA. This is consistent with the absence of PDC1 and many other HRA1-regulated genes in the immunoprecipitated chromatin.

To further validate the hypothesis that HRA1 inhibits RAP2.12 through direct interaction rather than DNA binding, we took advantage of an artificial UAS promoter, made up of four repetitions of the yeast GAL4 upstream activating sequence [7], which cannot be recognized by endogenous plant factors. By this approach we confirmed that the activation of the UAS:PpLuc construct by a chimeric RAP2.12-GAL4DBD factor was inhibited by coexpression of 35S:HRA1 in protoplasts, in spite of the inability by HRA1 to recognize the UAS promoter (Figure 4E). Altogether, these observations demonstrated that HRA1 inhibits RAP2.12 function by direct protein–protein interaction, rather than by competition for DNA binding.

Additional evidence of the impact of RAP2.12 inhibition by HRA1 was obtained in protoplasts, whose survival of hypoxia was enhanced by transfection with 35S:RAP2.12 only if 35S:HRA1 was not concurrently transfected (Figure S16A), and in planta, where overexpression of a stabilized RAP2.12_14–358 protein in the OE-HRA1#1 background was sufficient to suppress the alteration in OE-HRA1 rosette morphology and return the overall phenotype to that of the wild type (Figure S16B).

HRA1 Is Regulated by a Negative Feedback Mechanism

Because the molecular response to hypoxia might entail a balance between RAP2.12 stabilization and attenuation under low oxygen stress, tight regulation of HRA1 was anticipated. As for the promoter of PDC1, we found that the HRA1 promoter (−849 to −1 relative to the start codon) was transactivated in a dosage-dependent manner by RAP2.12 and repressed by HRA1 itself in mesophyll protoplasts (Figure 5A). An additional mechanism contributing to HRA1 regulation involves binding of HRA1 to its own promoter, as revealed by ChIP-Seq and confirmed by ChIP-qPCR (Figure 4A). We hypothesize that this binding dampens RAP2.12 activation of this promoter. In support of this, when specific RT-qPCR was performed to detect the expression of the endogenous HRA1 gene (Figure S4B), strong down-regulation was observed in OE-HRA1 plants (Figure 5B). These results demonstrate that HRA1 transcription is activated upon hypoxia following the nuclear accumulation of RAP2.12 but is subsequently subjected to negative self-regulation. This can be considered a “double check” mechanism that takes advantage of HRA1's ability to both repress RAP2.12 activity and directly bind its own promoter, possibly competing with RAP2.12 binding. The double regulation of HRA1 transcription is most likely responsible for the transient dynamics of HRA1 transcript accumulation during hypoxia (Figure 1C) and allows the plant to limit hypoxic gene expression over time, as detected in the wild type and to a lesser extent in the hra1-1 mutant (Figure 5C).

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Figure 5. A negative feedback loop acting on HRA1 determines the extent of anaerobic gene expression over the time of stress.

(A) Modulation of HRA1 promoter activity, as visualized through the firefly luciferase reporter, by co-transfection of protoplasts with a stabilized RAP2.12_14–358, alone (blue bars) or in combination with a HRA1 effector construct (yellow bars). Data are mean ± s.d. (n = 4). (B) Steady-state levels, in Arabidopsis seedlings, of the full-length HRA1 mRNA (HRA1_Endo), measured with specific HRA1 3′-UTR primers, and of full-length (in the wild type), truncated (in hra1-1 and -2), and overexpressed transcripts (in OE-HRA1-#1 and -#2) (HRA1_Tot), measured with primers specific for HRA1 coding sequence; see Figure S4B for the position of primers used for HRA1_Tot and HRA1_Endo mRNA abundance measurement. Hypoxia, 2 h. Data are mean ± s.d. (n = 3 ). The absence of expression is indicated by grey rectangles (masked). Numeric expression values are provided in Table S5. (C) Abundance of HRA1 and hypoxia marker gene mRNAs over prolonged hypoxia stress in OE-HRA1 and hra1 seedlings. Data are mean ± s.d. (n = 4).

https://doi.org/10.1371/journal.pbio.1001950.g005

Plant Material

A. thaliana Columbia-0 (Col-0) was used as the wild type ecotype. hra1-1 (N541486; SALK_041486) and hra1-2 (N560275; SALK_060275) T-DNA mutants were obtained from the European Arabidopsis Stock Center (uNASC) and the Arabidopsis Biological Resource Center, respectively. Mutants were genotyped using standard nonquantitative PCR on genomic DNA, using primers listed in Table S7. See also Figure S4B for a graphical representation of primer binding sites.

Growth Conditions

Seeds were sown in a moist mixture of soil∶perlite∶sand mixture 3∶1∶1, stratified at 4°C in the dark for 48 h and germinated at 23°C day/18°C night under a neutral day cycle (12 h light/12 h darkness, ∼80 µmol photons m⁻² s⁻¹ light intensity). Experiments in sterile conditions were performed with 4-d-old seedlings grown in liquid MS medium [0.43% (w/v) Murashige–Skoog (MS) salts (Sigma-Aldrich), 1% (w/v) sucrose, pH 5.7] under continuous shaking conditions, or with 2- and 3-wk-old plants grown vertically on solid MS medium [liquid MS medium, 0.4% (w/v) Phytagel (Sigma–Aldrich)]. For the DNA microarray, chromatin immunopurification, and ADH assay experiments, sterilized seeds were grown for 7 d on solid MS medium in vertical orientation in a growth chamber (Model # CU36L5, Percival Scientific, Perry, IA) under a long day cycle (16 h light/8 h darkness, ∼80 µmol photons m⁻² s⁻¹), at 23°C, before treatments [18].

Low Oxygen Treatments

Hypoxic treatments were performed as described previously [18].

For submergence treatments, 4-wk-old plants (stage 3.50 [30]) grown in soil as described above were used. Treatments started at ZT (Zeitgeber Time) 2. Plants were submerged with deionized water in glass tanks, until the water surface reached 20 cm above the rosettes, and kept in the dark for the duration of the treatment. Submergence was for 72 h, after which plants were transferred to normal photoperiodic conditions (12 h light/12 h darkness) and allowed to recover for 1 wk before the phenotypic evaluation. Plants that were able to progress in vegetative development were scored as survivors (Figure 3A). The dry weight of whole rosettes was measured before submergence and at the end of the recovery phase. Five separate tanks were used in every submergence experiment, each containing five plants per genotype, and the experiment was repeated three times.

Samples for gene transcript abundance and Western blot analyses were, instead, collected after 4 h of submergence. Each sample was composed of young leaves (youngest three emerging leaves and shoot meristem) or old leaves (10th to 12th leaves) from five plants. Three biological replicates were used, and the experiment was repeated two times with comparable results. Gene expression data are mean ± s.d.

In an independent submergence survival assessment system [16],[17], seedlings at the 10-leaf rosette stage (stage 1.10 [30]) were submerged in complete darkness or held in complete darkness in air for 3, 5, 7, or 10 d (Figure S6). After desubmergence or re-illumination, the number of plants with alive apical meristem (green, nonwater-soaked) was recorded each day for 12 d. The median lethal time (LT₅₀), standard error, and the 95% confidence interval were determined using the 9-d recovery time point exactly as described previously [17].

Other Stress Treatments

Additional abiotic stress treatments were carried out on liquid-grown 4-d-old seedlings. The following conditions were used: 2 h at 4°C (cold stress); pinching of the seedlings with 10 consecutive pin pricks, 1 h before sampling (mechanical wounding); 3 h in the presence of 150 mM sodium chloride (salt stress); 3 h in the presence of 5 mM hydrogen peroxide (oxidative stress); 3 h in the presence of 100 mM mannitol (osmotic stress); 3-h-long desiccation under laminar air flux (dehydration stress); 90 min at 38°C (heat stress). Control plants were maintained at 23°C with continuous shaking.

Cloning of Constructs

Coding and upstream regulatory sequences were amplified from appropriate Arabidopsis cDNA or genomic DNA templates using Phusion High Fidelity DNA-polymerase (New England Biolabs). Fusion sequences were generated by overlapping PCR. Whenever the GATEWAY cloning system (Life Technologies) was exploited, sequences were cloned into pENTR/D-TOPO and the resulting entry vectors were recombined into destination vectors using the LR reaction mix II (Life Technologies). A list of plasmid constructs generated in this study and primers used for cloning can be found in Tables S6 and S7, respectively.

A construct for overexpression of HRA1 in the OE-HRA1#1 and OE-HRA1#2 transgenics, named 35S-HRA1-FLAG, was prepared by cloning the full-length HRA1 cDNA with gwHRA1_5′UTR_Fw and gwHRA1_3′UTR_Rv primers and recombination into the p35S:GATA-HF vector [15], in which a CaMV 35S promoter drives the expression of HRA1 cDNA linked to a C-terminal FLAG tag [NH2-Gly7-FLAG(AspTyrLysAsp4Lys)Gly3-His6-COOH]. A further 35S-HRA1 overexpression construct, used to obtain a third transgenic lacking any C-terminal epitope tag (OE-HRA1#3), was produced by amplification of HRA1 coding sequence with gwHRA1_Fw and gwHRA1_Rv primers and subsequent cloning in the pK7WG2 vector [31].

The 35S:RAP2.12:RrLuc construct exploited for Figure 3E was produced by GATEWAY cloning of a RAP2.12:RrLuc DNA sequence into p2GW7; this sequence, in turn, was produced by overlapping PCR after separate amplification of the RAP2.12 full CDS, from a cDNA template, and Renilla reniformis luciferase CDS, from the 35S:RrLuc plasmid (see Table S6). Moreover, the normalization vector 35S:PpLuc was generated by amplification of the firefly luciferase gene from pBGWL7 [31] and GATEWAY cloning into p2GW7.

Finally, the pGWL7 GATEWAY destination vector used for transactivation experiments in plant protoplasts was obtained by cutting an ApaI/SpeI fragment from pBGWL7 and ligating it into the p2GW7 backbone [31].

Plant Transformation

Stable transgenic Arabidopsis plants were generated by Agrobacterium-mediated transformation following the floral dip method [32]. T₀ seeds were screened on the appropriate selection plates, and single-insertion homozygous lines were identified. T₃ or later generations of single insertion homozygotes were evaluated.

Bimolecular Fluorescence Complementation and Reporter Transactivation Assays Using Protoplasts

Arabidopsis mesophyll protoplasts were obtained from rosette leaves and transfected according to [33].

In planta protein–protein interactions were investigated via bimolecular fluorescence complementation (BiFC) [34], using the C-terminal split-YFP constructs 35S:HRA1:YFPn and 35S:RAP2.12_14–358:YFPc [35]. As the negative control for nonspecific YFP complementation, empty 35S:YFPn and 35S:YFPc vectors were co-transfected into protoplasts. For each construct, 10 µg plasmid DNA was used. Fluorescence was observed with a Nikon ViCo microscope using filters for YFP (excitation wavelengths, 495–510 nm; barrier, 520–550 nm), TRITC (excitation wavelengths, 540–565 nm), and DAPI (excitation wavelengths, 385–400 nm). Micrographs are representative of three independent experiments.

In promoter transactivation assays performed with protoplasts, 3 µg transformation⁻¹ 35S:RrLuc plasmid DNA [36] was used for normalization of the PpLuc activity. Test constructs (test promoter:PpLuc, 3 µg transformation⁻¹) harboring the Photinus pyralis luciferase gene were co-transfected into protoplasts, along with the specified effector plasmid(s) encoding TFs (35S:effector, up to 6 µg transformation⁻¹). pAVA 393 [37] was used as the 35S:GFP construct, when needed. Samples were subsequently processed with the Dual-Luciferase Reporter Assay System (Promega), and luciferase activity was quantified with a Lumat LB 9507 luminometer (Bechtold Technologies). Each experiment was repeated three times and a representative replicate was shown. Relative luciferase intensity values (PpLuc/RrLuc) are presented as mean ± s.d. of four independent transfections.

RAP2.12:RrLuc protein stability from Figure 3E was assessed likewise through the Dual-Luciferase system. For each individual transfection, 5 µg 35S:RAP2.12:RrLuc plasmid DNA was supplemented with increasing amounts of the 35S:HRA1 effector construct and transfected into a mesophyll protoplast suspension. In this case, 35S:PpLuc was used for normalization. Relative Renilla luciferase intensity values (RrLuc/PpLuc) are presented as mean ± s.d. of four independent transfections.

Localization of GFP in Planta

For HRA1 localization in plant tissue, a 35S:HRA1:GFP-His6-FLAG translational fusion construct (named 35S-HRA1-GFP), was generated by subcloning of a HRA1:GFP-His6 construct, obtained by recombining the full-length HRA1 cDNA in the pEarleyGate103 vector [38], into the p35S:GATA-HF plasmid [15]. The construct was transformed into Arabidopsis Col-0 to produce transgenic plants accumulating the HRA1:GFP protein. Three-day-old seedlings were vacuum infiltrated with 5 µg ml⁻¹ 4′, 6-diamidino-2-phenylindole (DAPI) for 10 min, washed in water for 10 min under vacuum, and observed with a Leica SP2 (Bannockburn, IL) confocal microscope at the Microscopy Core Facility, Institute for Integrative Genome Biology, University of California, Riverside. GFP was viewed by excitation at 488 nm and emission at 500–600 nm. DAPI stained nuclei were visualized with a UV laser by excitation at 350 nm and emission at 399–600 nm.

GUS Staining

Histochemical GUS staining was carried out according to [39]. Briefly, plant material was fixed immediately after sampling in ice-cold 90% acetone for 1 h, rinsed several times in 100 mM phosphate buffer (pH 7.2), and then stained in a freshly prepared reaction solution [0.2% Triton X-100, 2 mM potassium ferrocyanide, 2 mM potassium ferricyanide, and 2 mM X-Gluc (5-bromo-4-chloro-3-indolyl ß-D-glucuronide, sodium salt dissolved in DMSO) in 100 mM phosphate buffer pH 7.2]. Plants were stained for 2–4 h (seedlings) or overnight (adult plants). Chlorophyll was eliminated from green tissues by washing them with absolute ethanol.

RT-qPCR

RNA extraction, removal of genomic DNA, cDNA synthesis, and RT-qPCR analyses were performed as described previously [36]. Steady-state mRNA levels were normalized using Ubiquitin10 (At4g05320) or β-TUB2 (At5g62690) as reference genes and relative expression values were calculated using the comparative Ct method [40]. The complete list of qPCR primers employed is reported in Table S8. Multiple qPCR primer couples were designed on HRA1-derived transcripts: Those named “sgHRA1_Endo” and “sgHRA1_Tot” were exploited to measure HRA1 mRNA levels in Figure 5B, while elsewhere “sgHRA1” primers were used. Data (mean ± s.d.) are representative of at least two independent experiments, each one carried out with three biological replicates, unless differently stated.

Microarray Analysis

Total RNA was extracted from frozen tissue using the RNeasy Plant Kit (Qiagen, Chatsworth, CA) and quantified with a NanoDrop 1000 spectrophotometer (ThermoScientific, Wilmington, DE). RNA quality was checked using the Agilent 2100 Bioanalyzer (Santa Clara, CA), and biotin-labeled cRNA was prepared with the GeneChip IVT Labeling Kit (Affymetrix, Santa Clara, CA). Hybridizations against the Arabidopsis ATH1 Genome Array were performed by the Institute for Integrative Genome Biology (IIGB) Genomics Core Facility, University of California, Riverside. Transcriptomes of each of the three genotypes—namely, Col-0, OE-HRA1#1, and OE-HRA1#2—were profiled under the two conditions. CEL files of two OE lines were processed as biological replicates along with two Col-0 replicates, using R and Bioconductor package. The NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) accession number for the generated dataset is GSE50679. The microarray dataset generated by [7] was obtained from NCBI GEO (http://www.ncbi.nlm.nih.gov/geo/) accession no. GSE29187. CEL files of aerobic-treated 5-wk-old rosette tissues of Col-0 and a transgenic overexpressing N-terminally HA-tagged RAP2.12 (RAP) line were processed together with the HRA1 microarray dataset (Col-0, OE-HRA1#1, and OE-HRA1#2). After computing the absent and present calls using the Affymetrix MAS 5.0 algorithm [41], datasets were normalized using the robust multichip average (RMA) method [42]. Mitochondrial and plastid gene probe pair sets were removed, and probe pair sets with present calls in greater than 50% of the samples were used in further analyses. DEGs were identified by comparisons using linear models for microarray data (LIMMA) available in the Bioconductor package [43]. A total of 1,295 DEGs were selected that satisfied the two following criteria, |SLR|>1 and adj. p<0.01 (SLR, signal log₂ ratio; adj. p, false discovery rate adjusted p value), in at least one comparison for each Affymetrix probe set. The DEGs were further analyzed using fuzzy k-means clustering with FANNY function. Clustering results were visualized using the Multi Expression Viewer (MEV) software (http://www.tm4.org/mev/) [44]. Gene ontology (GO) enrichment was evaluated for each cluster with the GO annotation file of A. thaliana from http://geneontology.org (downloaded 17 Jan 2012).

ChIP-seq and ChIP-qPCR Analysis

ChIP-seq libraries were prepared using the protocol of [45] with modifications. Arabidopsis seedlings were grown for 7 days on solid MS medium and hypoxia stressed for 2 hours as described above. Immediately at the termination of treatment, 1 g of plant material was transferred to a 50 ml Falcon tube and fixed in 25 ml MC buffer (10 mM sodium phosphate, pH 7, 50 mM NaCl, 0.1 M sucrose) containing 1% (w/v) formaldehyde by incubation on ice for 20 min. The fixation was stopped with the addition of 2.5 mL of 1.25 M glycine. After three washes with 25 mL MC buffer, the seedlings were frozen, ground and hydrated in 25 mL M1 buffer [10 mM sodium phosphate, pH 7, 0.1 M NaCl, 1 M 2-methyl 2,4-pentanediol, 10 mM β-mercaptoethanol and 0.5 tablet Complete Protease Inhibitor Cocktail (Roche Molecular Diagnostics, Pleasanton, CA) per 25 ml]. The slurry was filtered and centrifuged at 1000 g for 20 min at 4°C to obtain a nuclear pellet that was washed five times with 5 ml of M2 buffer (10 mM sodium phosphate, pH 7, 0.1 M NaCl, 10 mM MgCl₂, 1 M 2-methyl 2,4-pentanediol, 10 mM β-mercaptoethanol and 0.5% (v/v) Triton X-100, 0.5 tablet Complete Protease Inhibitor Cocktail per 25 ml). The final wash was performed with 5 ml M3 buffer (10 mM sodium phosphate, pH 7, 0.1 M NaCl, 10 mM β-mercaptoethanol and 0.5 tablet of Complete Protease Inhibitor Cocktail per 25 ml). The nuclear pellet was resuspended in 1 ml sonication buffer (10 mM sodium phosphate, pH 7, 0.1 M NaCl, 0.5% Sarkosyl, 10 mM EDTA) and sonicated using a Bioruptor UCD-200 (Denville, NJ) on ice, following the manufacturer's instruction. The sample was centrifuged twice at 15600 g for 10 min at 4°C and the supernatant was used for chromatin immunoprecipitation (ChIP) with 20 µl of EZview Red ANTI-FLAG® M2 Affinity Gel (Sigma-Aldrich, St. Louis, MO) following the manufacturer's instruction with IP buffer (50 mM HEPES, pH 7.5, 150 mM NaCl, 5 mM MgCl₂, 10 µM ZnSO₄, 1% (v/v) Triton X-100, 0.05% (w/v) SDS). After the samples were reverse-crosslinked,, the DNA was purified using the Qiagen PCR purification kit. Library construction involving end repair, A-tailing, and ligation to an adapter was conducted using the End-It DNA End-Repair Kit (Epicentre, Madison, WI), Klenow fragment (New England Biolabs, Ipswich, MA) and Fast-Link DNA Ligation Kit (Epicentre). Two custom barcodes of four nucleotides were used for multiplexing (Col-0 [5′-GTAT-3′] and OE-HRA1#1 [5′-ACGT-3′]). Samples were submitted to the IIGB Genomics Core Facility, University of California, Riverside, for single-end sequencing with 100 cycles using the Illumina Hiseq2000 platform. Raw data in fastq file format were imported into R using the ShortRead package [46], the barcode sequence was removed from the 100 bp read sequences and reads were aligned to the A. thaliana genome TAIR10 version (http://www.arabidopsis.org) using Bowtie (ver. 0.12.7) [47], allowing two nucleotide mismatches. Peaks were generated with the Model-based Analysis for ChIP-Seq (MACS) software [48] using Col-0 mock ChIP data as the control with default settings. ChIPpeakAnno was used to acquire gene annotation, determine location of peak regions from the nearest genes, and obtain DNA sequences of peak regions [49]. Peaks of ChIP-seq data were visualized using the Integrative Genomics Viewer software (2.1) [50].

SDS-PAGE and Western Blotting

Soluble protein samples from total tissue extracts were separated by SDS-PAGE on 10% polyacrylamide Bis-Tris NuPAGE midigels (Life Technologies) and then transferred onto a polyvinylidene difluoride membrane by means of the Trans-Blot Turbo System (Bio-Rad). Detection of the HRP-conjugated secondary antibody (goat anti-rabbit IgG, Agrisera, product code AS09 602) was performed with the LiteAblot Turbo Extra-Sensitive Chemiluminescent Substrate (EuroClone). Antibodies against PDC (product code AS10 691) and ADH (product code AS10 685) were purchased from Agrisera and antisera against FLAG (A8592) from Sigma-Aldrich. Equal loading of total protein samples was checked by amido black staining, as described in [19].

Measurement of ADH Activity and Soluble Carbohydrate Levels

ADH-specific activity was measured as described previously [51] with minor modifications, using Arabidopsis 7-d-old seedlings.

Soluble carbohydrates analyzed in Figure S7 were extracted from whole rosettes using perchloric acid and analyzed enzymatically in the neutralized supernatant, as described previously by [52].

Yeast-Two-Hybrid Assays

The ProQuest Two-Hybrid System (Life Technologies) was used. Saccharomyces cerevisiae strain MaV203 was transformed with the different combinations of bait (obtained after recombination of the inserts into pDEST32), prey (obtained after recombination of the inserts into pDEST22), and control vectors. Empty pDEST32 and pDEST22 were used as negative controls. Yeast transformation was performed according to the LiAc/SS carrier DNA/PEG method [53]. After transformation, yeast containing both vectors was grown for 3 d at 28°C on minimal selective dropout medium lacking Leu and Trp (SC-LW medium) to select colonies containing two vectors. Plating was then replicated on selective dropout medium (SC-LWH+3AT medium) lacking Leu, Trp, and His, supplemented with 10 mM 3-aminotriazole (3AT), in order to select colonies containing interacting partners. The strength of the interaction was further verified by β-galactosidase staining (LacZ) following the manufacturer's instructions.

Statistical Analysis

Significant variations between genotypes or treatments were evaluated statistically by Student's t test or one-way ANOVA, coupled with Tukey's posttest, for general comparisons, or Dunnet's posttest, for multiple comparisons with a reference sample, where appropriate. Mean values that were significantly different (p<0.05) from each other are marked with lower case letters or asterisks inside the figures. The statistical evaluation of the submergence survival, DNA microarray, and ChIP-seq experiments is described under the respective subsections.

Phylogenetic Analysis and Analysis of Hypoxia-Inducible Trihelix Genes

Full protein coding sequences of plant trihelix proteins were obtained from GenBank and aligned using ClustalW [54]. The maximum likelihood algorithm in the MEGA5.0 framework [55] was used with 500 bootstrap replicates to evaluate evolutionary relatedness. To identify trihelix genes positively regulated by low oxygen conditions across plant species (Table S1), existing transcriptomic data were surveyed. Genes belonging to the trihelix family in each of the organisms taken into consideration were extracted from the PlantTFDB [56] and used to query the selected public microarray datasets.