Transgenic Research

, Volume 24, Issue 3, pp 447–461 | Cite as

Impacts on the metabolome of down-regulating polyphenol oxidase in potato tubers

  • Louise Vida Traill ShepherdEmail author
  • Colin James Alexander
  • Christine Anne Hackett
  • Diane McRae
  • Julia Anne Sungurtas
  • Susan Ramsay Verrall
  • Jennifer Anne Morris
  • Peter Edward Hedley
  • David Rockhold
  • William Belknap
  • Howard Vivian Davies
Original Paper


Tubers of potato (Solanum tuberosum L. cv. Estima) genetically modified to reduce polyphenol oxidase (PPO) activity and enzymatic discolouration were assessed for changes in the metabolome using Liquid Chromatography–Mass Spectrometry (LC–MS) and Gas Chromatography (GC)–MS. Metabolome changes induced over a 48 hour (h) period by tuber wounding (sliced transverse sections) were also assessed using two PPO antisense lines (asPPO) and a wild-type (WT) control. Data were analysed using Principal Components Analysis and Analysis of Variance to assess differences between genotypes and temporal changes post-tuber wounding (by slicing). The levels of 15 metabolites (out of a total of 134 that were detected) differed between the WT and asPPO lines in mature tubers at harvest. A considerably higher number (63) of these metabolites changed significantly over a 48 h period following tuber wounding. For individual metabolites the magnitude of the differences between the WT and asPPO lines at harvest were small compared with the impacts of tuber wounding on metabolite levels. Some of the observed metabolite changes are explicable in terms of pathways known to be affected by wound responses. Whilst some statistically significant interactions (11 metabolites) were observed between line and time after wounding, very few profiles were consistent when comparing the WT with both asPPO lines, and the underlying metabolites appeared to be random in terms of the pathways they occupy. Overall, mechanical damage to tubers has a considerably greater impact on the metabolite profile than any potential unintended effects resulting from the down-regulation of PPO gene expression.


Bruising Genetic modification Metabolomics Potato PPO Transgenic 



This work was supported by SAFEFOODS (EU FP6 Contract No. Food-CT-2004-506446); QualityLowInputFood (QLIF; EU FP6 Contract No CT-2004-506358) and by the Scottish Government’s Rural and Environment Science and Analytical Services (RESAS) Division. The authors would like to thank James W McNicol (Biomathematics and Statistics Scotland, Invergowrie, Dundee) for general statistical advice. The authors would also like to thank Sean Connor, Gary Dobson and Tom Shepherd for advice with data processing and metabolite identification.

Supplementary material

11248_2014_9850_MOESM1_ESM.tif (7.6 mb)
Supplementary material Fig. SI Visual assessment of discolouration in tuber slices of both the WT control (a) and the antisense GM line ppo17 (b) after 24 hours (T1) incubation at room temperature in the dark. Where GM = genetically modified; PPO = polyphenol oxidase; T = time; WT = wild-type. (TIFF 7804 kb)
11248_2014_9850_MOESM2_ESM.tif (6.4 mb)
Supplementary material 2 (TIFF 6570 kb)
11248_2014_9850_MOESM3_ESM.eps (575 kb)
Supplementary material Fig. SII Microarray expression profile plot (normalised fold-change on log10 scale) of PPO gene in tuber slices of the WT control and the two antisense GM lines (ppo17 and ppo39), after 0 h (T0), 24 h (T1) and 48 h (T2) incubation at room temperature in the dark. Where h = hours; PPO or ppo = polyphenol oxidase; GM = genetically modified; SED = standard error of difference; T = time; WT = wild-type. (EPS 574 kb)
11248_2014_9850_MOESM4_ESM.eps (530 kb)
Supplementary material Fig. SIII Microarray expression profile plot (normalised fold-change on log10 scale) of PAL1 (a) and PAL2 (b) genes in tuber slices of the WT control and the two antisense GM lines (ppo17 and ppo39) ), after 0 h (T0), 24 h (T1) and 48 h (T2) incubation at room temperature in the dark. Where h = hours; PAL = phenylalanine ammonia-lyase; ppo = polyphenol oxidase; SED = standard error of difference; T = time; WT = wild-type. (EPS 529 kb)
11248_2014_9850_MOESM5_ESM.eps (538 kb)
Supplementary material 5 (EPS 539 kb)
11248_2014_9850_MOESM6_ESM.docx (31 kb)
Supplementary material 6 (DOCX 31 kb)
11248_2014_9850_MOESM7_ESM.docx (31 kb)
Supplementary material 7 (DOCX 32 kb)
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Supplementary material 8 (DOCX 33 kb)
11248_2014_9850_MOESM9_ESM.docx (31 kb)
Supplementary material 9 (DOCX 32 kb)
11248_2014_9850_MOESM10_ESM.docx (32 kb)
Supplementary material 10 (DOCX 33 kb)


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Louise Vida Traill Shepherd
    • 1
    Email author
  • Colin James Alexander
    • 2
  • Christine Anne Hackett
    • 2
  • Diane McRae
    • 1
  • Julia Anne Sungurtas
    • 1
  • Susan Ramsay Verrall
    • 3
  • Jennifer Anne Morris
    • 4
  • Peter Edward Hedley
    • 4
  • David Rockhold
    • 5
  • William Belknap
    • 5
  • Howard Vivian Davies
    • 1
  1. 1.Environmental and Biochemical Sciences GroupThe James Hutton InstituteDundeeScotland, UK
  2. 2.Biomathematics and Statistics ScotlandDundeeScotland, UK
  3. 3.Information and Computational Sciences GroupThe James Hutton InstituteDundeeScotland, UK
  4. 4.Cell and Molecular Sciences GroupThe James Hutton InstituteDundeeScotland, UK
  5. 5.Crop Improvement and Utilization Research Unit, Agricultural Research Service, Western Regional Research Centre USDAAlbanyUSA

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