Abstract
Switchgrass (Panicum virgatum) is a perennial crop producing deep roots and thus highly tolerant to soil water deficit conditions. However, seedling establishment in the field is very susceptible to prolonged and periodic drought stress. In this study, a “sandwich” system simulating a gradual water deletion process was developed. Switchgrass seedlings were subjected to a 20-day gradual drought treatment process when soil water tension was increased to 0.05 MPa (moderate drought stress) and leaf physiological properties had expressed significant alteration. Drought-induced changes in leaf proteomes were identified using the isobaric tags for relative and absolute quantitation (iTRAQ) labeling method followed by nano-scale liquid chromatography mass spectrometry (nano-LC-MS/MS) analysis. Additionally, total leaf proteins were processed using a combinatorial library of peptide ligands to enrich for lower abundance proteins. Both total proteins and those enriched samples were analyzed to increase the coverage of the quantitative proteomics analysis. A total of 7006 leaf proteins were identified, and 257 (4% of the leaf proteome) expressed a significant difference (p < 0.05, fold change <0.6 or >1.7) from the non-treated control to drought-treated conditions. These proteins are involved in the regulation of transcription and translation, cell division, cell wall modification, phyto-hormone metabolism and signaling transduction pathways, and metabolic pathways of carbohydrates, amino acids, and fatty acids. A scheme of abscisic acid (ABA)-biosynthesis and ABA responsive signal transduction pathway was reconstructed using these drought-induced significant proteins, showing systemic regulation at protein level to deploy the respective mechanism. Results from this study, in addition to revealing molecular responses to drought stress, provide a large number of proteins (candidate genes) that can be employed to improve switchgrass seedling growth and establishment under soil drought conditions (Data are available via ProteomeXchange with identifier PXD004675).
Highlights
Switchgrass (Panicum virgatum), has been selected as a model herbaceous bioenergy species in the USA due to its high biomass yield, strong tolerance to drought and flooding conditions, relatively low herbicide and fertilizer input requirements, and widespread adaptability to temperate climate [1,2,3].Recently, a shortage of fresh water and increasingly severe drought have become a significant challenge to crop production [4]
We have shown for the first time that the abscisic acid (ABA)-dependent pathway are regulated at protein level, which in turn may have a significant role in activating the transcription of drought tolerance genes in switchgrass
Three proteins annotated to the regulatory components of ABA receptor 3 (Pavir.Ab01039.1, Pavir.Ca00496.1, and Pavir.Cb01723.1) showed varied changes (0.78–1.48-fold), but none of them passed the threshold criteria for significantly changed proteins in this study. These results indicate a very dynamic adjustment system regulating the expression of proteins in ABA biosynthesis and signaling pathways, which in turn modulates the activation of drought tolerance mechanism in switchgrass leaves (Figure 2)
Summary
Switchgrass (Panicum virgatum), has been selected as a model herbaceous bioenergy species in the USA due to its high biomass yield, strong tolerance to drought and flooding conditions, relatively low herbicide and fertilizer input requirements, and widespread adaptability to temperate climate [1,2,3]. Quantitative proteomics using the shot-gun bottom-up approach has been used to evaluate drought-responsive proteins in important crop species, such as rice, maize, wheat, cotton, amaranth, alfalfa, sugar beets, and tomatoes [18,20,27,28,29,30,31,32,33,34,35,36,37] These proteomics studies have significantly increased our understanding of molecular regulation at the translational and post-translational levels in plants. CChhaannggeess iinn tthheessee pphhyyssiioollooggiiccaall pprrooppeerrttiieesssshhoowweeddtthhaattlleeaavveess aanndd ppllaannttss aass aa wwhhoollee eexxppeerriieenncceedd aa pprrooggrreessssiivvee ddrroouugghhtt--ssttrreessss dduurriinngg tthhee 2200 ddaayyss ooff wwiitthhhhoollddiinngg wwaatteerr..AAtttthhiissttiimmee--ppooiinntt((2200ddaayyssaafftteerrwwiitthhhhoollddiinnggwwaatteerr)),,tthheeddrroouugghhttttrreeaattmmeennttsswweerreetteerrmmiinnaatteedd aanndd ttiissssuueesswweerreehhaarrvveesstteeddffoorrffuurrtthheerraannaallyyssiiss((FFiigguurree11)). These results demonstrate that ProteoMiner did deplete the concentration of the highly abundant proteins while simultaneously enriching low-abundance proteins
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