벼의 차세대 단백질체 분석을 위한 질량분석기 호환의 광분해성 계면활성제의 적용
Application of mass-spectrometry compatible photocleavable surfactant for next-generation proteomics using rice leaves
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초록
The solubilization of isolated proteins into the adequate buffer containing of surfactants is primary step for proteomic analysis. Particularly, sodium dodecyl sulfate (SDS) is the most widely used surfactant, however, it is not compatible with mass spectrometry (MS). Therefore, it must be removed prior to MS analysis through rigorous washing, which eventually results in inevitable loss. Recently, photocleavable surfactant, 4-hexylphenylazosulfonate (Azo), was reported which can be easily degraded by UV irradiation and is compatible with MS during proteomic approach using animal tissues. In this study, we employed comparative label-free proteomic analysis for evaluating the solubilization efficacy of the Azo and SDS surfactants using rice leave samples. This approach led to identification of 3,365 proteins and out of 682 proteins were determined as significantly modulated. Further, according to the subcellular localization prediction in SDS and Azo, proteins localized in the chloroplast were the major organelle accounting for 64% of the total organelle in the SDS sample, while only 37.5% of organelle proteins solubilized in the Azo were predicted to be localized in chloroplast. Taken together, this study validates the efficient solubilization of total protein isolated from plant material for bottom-up proteomics. Azo surfactant is suitable as substituents of SDS and promising for bottomup proteomics as it facilitates robust protein extraction, rapid washing step during enzymatic digestion, and MS analysis.
Abstract
The solubilization of isolated proteins into the adequate buffer containing of surfactants is primary step for proteomic analysis. Particularly, sodium dodecyl sulfate (SDS) is the most widely used surfactant, however, it is not compatible with mass spectrometry (MS). Therefore, it must be removed prior to MS analysis through rigorous washing, which eventually results in inevitable loss. Recently, photocleavable surfactant, 4-hexylphenylazosulfonate (Azo), was reported which can be easily degraded by UV irradiation and is compatible with MS during proteomic approach using animal tissues. In this study, we employed comparative label-free proteomic analysis for evaluating the solubilization efficacy of the Azo and SDS surfactants using rice leave samples. This approach led to identification of 3,365 proteins and out of 682 proteins were determined as significantly modulated. Further, according to the subcellular localization prediction in SDS and Azo, proteins localized in the chloroplast were the major organelle accounting for 64% of the total organelle in the SDS sample, while only 37.5% of organelle proteins solubilized in the Azo were predicted to be localized in chloroplast. Taken together, this study validates the efficient solubilization of total protein isolated from plant material for bottom-up proteomics. Azo surfactant is suitable as substituents of SDS and promising for bottomup proteomics as it facilitates robust protein extraction, rapid washing step during enzymatic digestion, and MS analysis.
참고문헌 (29)
- Alfonso-Garrido J, "Sample preparation strategies for improving the identification of membrane proteins by mass spectrometry", Anal Bioanal Chem, 407, pp.4893~4905 (2015)
- Bhuyan AK, "On the mechanism of SDS-induced protein denaturation", Biopolymers, 93, pp.186~199 (2010)
- Brown KA, "A photocleavable surfactant for top-down proteomics", Nat Methods, 16, pp.417~420 (2019)
- Brown KA, "High-throughput proteomics enabled by a photocleavable surfactant", Angew Chemie, 132, pp.8484~8488 (2020)
- Chang YH, "New massspectrometry-compatible degradable surfactant for tissue proteomics", J Proteome Res, 14, pp.1587~1599 (2015)
- Cox J, "Is poteomics the nw gnomics?", Cell, 130, pp.95~398 (2007)
- Darie CC, "Post-translational modification(PTM)proteomics : Challenges and perspectives", Mod Chem Appl, 1 (2013)
- Gillet LC, "Mass spectrometry applied to bottom-up proteomics : Entering the high-throughput era for hypothesis testing", Annu Rev Anal Chem, 9, pp.449~472 (2016)
- Gupta R, "Identification of Msp1-induced signaling components in rice leaves by integrated proteomic and phosphoproteomic analysis", Int J Mol Sci, 20, pp.1~17 (2019)
- Hengel SM, "Evaluation of SDS depletion using an affinity spin column and IMS-MS detection", Proteomics, 12, pp.3138~3142 (2012)
- Kalipatnapu S, "Membrane protein solubilization : Recent advances and challenges in solubilization of serotonin1A receptors", IUBMB Life, 57, pp.505~512 (2005)
- Kanehisa M, "KEGG : New perspectives on genomes, pathways, diseases and drugs", Nucleic Acids Res, 45, pp.D353~D361 (2017)
- Kanehisa M, "KEGG Mapper for inferring cellular functions from protein sequences", Protein Sci, 29, pp.28~35 (2020)
- Loo RRO, "Surfactant effects on protein structure examined by electrospray ionization mass spectrometry", Protein Sci, 3, pp.1975~1983 (1994)
- Meng Q, "A proteomic insight into the MSP1 and flg22 induced signaling in Oryza sativa leaves", J Proteomics, 196, pp.120~130 (2019)
- Min CW, "Concepts and strategies of soybean seed proteomics using the shotgun proteomics approach", Expert Rev Proteomics, 16, pp.795~804 (2019)
- 민철우, "A TMT-based quantitative proteomic analysis provides insights into the protein changes in the seeds of high- and low- protein content soybean cultivars", Journal of Plant Biotechnology, 47(3), pp.209~217 (2020), 한국식물생명공학회[DOI]
- Min CW, "Integrated proteomics and metabolomics analysis highlights correlative metaboliteprotein networks in soybean seeds subjected to warm-water soaking", J Agric Food Chem, 68, pp.8057~8067 (2020)
- Min CW, "In-depth investigation of low-abundance proteins in matured and filling stages seeds of Glycine max employing a combination of protamine sulfate precipitation and TMT-based quantitative proteomic analysis", Cells, 9, pp.1517~ (2020)
- Perez-Riverol Y, "The PRIDE database and related tools and resources in 2019 : Improving support for quantification data", Nucleic Acids Res, 47, pp.D442~D450 (2019)
- Tian T, "AgriGO v2. 0 : A GO analysis toolkit for the agricultural community, 2017 update", Nucleic Acids Res, 45, pp.W122~W129 (2017)
- Tyanova S, "The MaxQuant computational platform for mass spectrometry-based shotgun proteomics", Nat Protoc, 11, pp.2301~2319 (2016)
- Tyanova S, "The Perseus computational platform for comprehensive analysis of(prote)omics data", Nat Methods, 13, pp.731~740 (2016)
- Wiśniewski JR, "Universal sample preparation method for proteome analysis", Nat Methods, 6, pp.359~362 (2009)
- Yoshida SD, "Laboratory manual for physiological studies of rice", pp.61~ (1976), The International Rice Research Institute, Manila
- Yu CS, "CELLO2GO : A web server for protein subCELlular lOcalization prediction with functional gene ontology annotation", PLoS One, 9, pp.e99368~ (2014)
- Yu YQ, "Enzyme-friendly, mass spectrometry-compatible surfactant for in-solution enzymatic digestion of proteins", Anal Chem, 75, pp.6023~6028 (2003)
- Zhang X, "Less is more : Membrane protein digestion beyond urea-trypsin solution for next-level proteomics", Mol Cell Proteomics, 14, pp.2441~2453 (2015)
- Zhang Y, "Protein analysis by shotgun", bottom-up proteomics, 2013, pp.113, 2343~2394
