Large-Scale Proteomics of the Cassava Storage Root and Identification of a Target Gene to Reduce Postharvest Deterioration<sup><a href="#fn1" rid="fn1" class=" fn">[C]</a></sup><sup><a href="#fn2" rid="fn2" class=" fn">[W]</a></sup><sup><a href="#fn3" rid="fn3" class=" fn">[OPEN]</a></sup>
Supplementary Material
Abstract
Cassava (Manihot esculenta) is the most important root crop in the tropics, but rapid postharvest physiological deterioration (PPD) of the root is a major constraint to commercial cassava production. We established a reliable method for image-based PPD symptom quantification and used label-free quantitative proteomics to generate an extensive cassava root and PPD proteome. Over 2600 unique proteins were identified in the cassava root, and nearly 300 proteins showed significant abundance regulation during PPD. We identified protein abundance modulation in pathways associated with oxidative stress, phenylpropanoid biosynthesis (including scopoletin), the glutathione cycle, fatty acid α-oxidation, folate transformation, and the sulfate reduction II pathway. Increasing protein abundances and enzymatic activities of glutathione-associated enzymes, including glutathione reductases, glutaredoxins, and glutathione S-transferases, indicated a key role for ascorbate/glutathione cycles. Based on combined proteomics data, enzymatic activities, and lipid peroxidation assays, we identified glutathione peroxidase as a candidate for reducing PPD. Transgenic cassava overexpressing a cytosolic glutathione peroxidase in storage roots showed delayed PPD and reduced lipid peroxidation as well as decreased H2O2 accumulation. Quantitative proteomics data from ethene and phenylpropanoid pathways indicate additional gene candidates to further delay PPD. Cassava root proteomics data are available at www.pep2pro.ethz.ch for easy access and comparison with other proteomics data.
Acknowledgments
We thank Judith Owiti for initiating the research project on PPD and Irene Zurkirchen (Eidgenössisch Technische Hochschule Zurich) for special care of the cassava plants. We thank the Institute of Complex Systems Biomechanik, Forschungszentrum Jülich, for providing initial access to and training on the MatLab package to N.K. This work was supported by ETH Zurich and by the Bill & Melinda Gates Foundation (BioCassava Plus Program Phase 1 trainee fellowship to E.N.).
AUTHOR CONTRIBUTIONS
H.V., E.N., and J.S.P. designed research. H.V., E.N., J.S.P., and P.N. performed research. H.V., E.N., J.S.P., K.B., and J.G. analyzed the data. N.K. and M.H.-H. contributed new computational tools. H.V. wrote the article. W.G. edited the article.
Notes
Glossary
PPD | postharvest physiological deterioration |
MS/MS | tandem mass spectrometry |
ROS | reactive oxygen species |
MS | mass spectrometry |
ACC | 1-aminocyclopropane-1-carboxylate |
SAM | S-adenosyl-l-methionine |
CDNB | 1-chloro-2,4-dinitrobenzene |
MDA | malondialdehyde |
T3PQ | top-three protein quantification |
Glossary
PPD | postharvest physiological deterioration |
MS/MS | tandem mass spectrometry |
ROS | reactive oxygen species |
MS | mass spectrometry |
ACC | 1-aminocyclopropane-1-carboxylate |
SAM | S-adenosyl-l-methionine |
CDNB | 1-chloro-2,4-dinitrobenzene |
MDA | malondialdehyde |
T3PQ | top-three protein quantification |
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