Plant Molecular Biology

, 69:503 | Cite as

Identification of two Arabidopsis genes encoding a peroxisomal oxidoreductase-like protein and an acyl-CoA synthetase-like protein that are required for responses to pro-auxins

  • Andrew A. G. Wiszniewski
  • Wenxu Zhou
  • Steven M. Smith
  • John D. Bussell


Indole-3-butyric acid (IBA) and 2,4-dichlorophenoxybutyric acid (2,4-DB) are metabolised by peroxisomal β-oxidation to active auxins that inhibit root growth. We screened Arabidopsis mutants for resistance to IBA and 2,4-DB and identified two new 2,4-DB resistant mutants. The mutant genes encode a putative oxidoreductase (SDRa) and a putative acyl-activating enzyme (AAE18). Both proteins are localised to peroxisomes. SDRa is coexpressed with core β-oxidation genes, but germination, seedling growth and the fatty acid profile of sdra seedlings are indistinguishable from wild type. The sdra mutant is also resistant to IBA, but aae18 is not. AAE18 is the first example of a gene required for response to 2,4-DB but not IBA. The closest relative of AAE18 is AAE17. AAE17 is predicted to be peroxisomal, but an aae17 aae18 double mutant responded similarly to aae18 for all assays. We propose that AAE18 is capable of activating 2,4-DB but IBA activating enzymes remain to be discovered. We present an updated model for peroxisomal pro-auxin metabolism in Arabidopsis that includes SDRa and AAE18.


Acyl-activating enzyme Auxin Indole-3-butyric acid Peroxisome β-Oxidation 



This project was funded by the Australian Research Council (Grants FF0457721 and CE0561495), the Western Australian Government’s Centre of Excellence Program and an Australian Postgraduate Award to AAGW. We thank Peter Eastmond for kind donation of sucrose dependent lines from which we obtained kat2-2. We thank also ABRC, SALK, INRA Versailles, NASC, GABI and CSHL for T-DNA seed lines.

Supplementary material

11103_2008_9431_MOESM1_ESM.tif (740 kb)
Supplementary Figure 1 RT-PCRs of new T-DNA lines reported in this study. Seedlings were grown for 5–7 days on half-strength MS media supplemented with 1% sucrose. RNA was isolated using Biorad Aurum RNA isolation kit. RT utilised Biorad iScript. Where insertions interrupted putative transcripts, primers were designed to anneal to transcribed sequences bounding the insertion sites. In cases of insertions in UTRs, 300–400 bp, amplicons were designed using primer3. RT-PCR of actin2 was used as a control. Lines are assumed to be knockouts if transcript was absent; knockouts are indicated by allelic designation if transcript was absent and by their name if transcript remained in the line. AGIs, and a full list of alleles and T-DNA names can be found in Table 1. (740 kb)
11103_2008_9431_MOESM2_ESM.eps (1.4 mb)
Supplementary Figure 2 SDRa expression correlates with β-oxidation genes during the diurnal cycle. Many β-oxidation genes are co-ordinately down-regulated during the light period. Core β-oxidation genes (LACS6, LACS7, ACX2, MFP2, AIM1, KAT2, PMDH1) and transcripts of some putative auxiliary genes (e.g. CSY3, ECH1a, ECH2, SCP-2) experience a maximum during the dark period and reduced expression in the light. SDRa follows a similar pattern. There are rapid changes in transcript levels upon transition from light to dark and dark to light. For many of these genes, there is also an increase in expression during the light period similar to that seen for starch-degrading enzymes (Smith et al. 2004) that may be anticipatory of a dark phase where net energy reserves are consumed. Putative PTS1- and PTS2-encoding transcripts (identified using ARAPEROX; Reumann et al. 2004) and from other peroxisomal, non-PTS containing genes were identified in the transcriptome data from Smith et al. (2004). These 254 transcripts were further filtered to remove those for which the maximum normalised signal across the 11 time points was less than 50. The signal data for the remaining 158 transcripts were log2 transformed, then normalised against their time 0 values to obtain log2 fold changes through the diurnal cycle. This matrix was analysed with the CAST algorithm of TMEV ( using Pearson correlation coefficient and a threshold of 0.8. The cluster containing SDRa is depicted. ACX2 did not cluster in this group, but is superimposed for comparison. (1418 kb)


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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Andrew A. G. Wiszniewski
    • 1
  • Wenxu Zhou
    • 1
    • 2
  • Steven M. Smith
    • 1
    • 2
  • John D. Bussell
    • 1
  1. 1.Australian Research Council Centre of Excellence in Plant Energy BiologyUniversity of Western AustraliaCrawleyAustralia
  2. 2.Centre of Excellence for Plant MetabolomicsUniversity of Western AustraliaCrawleyAustralia

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