Proteomic Analysis of Phytase Transgenic and Non-transgenic Maize Seeds

Overview

Journal Sci Rep

Specialty Science

Date 2017 Aug 25

PMID 28835691

Citations 11

Authors

Yanhua Tan

Zheng Tong

Qian Yang

Yong Sun

Xiang Jin

Cunzhi Peng

Anping Guo

Xuchu Wang

Affiliations

Soon will be listed here.

Abstract

Proteomics has become a powerful technique for investigating unintended effects in genetically modified crops. In this study, we performed a comparative proteomics of the seeds of phytase-transgenic (PT) and non-transgenic (NT) maize using 2-DE and iTRAQ techniques. A total of 148 differentially expressed proteins (DEPs), including 106 down-regulated and 42 up-regulated proteins in PT, were identified. Of these proteins, 32 were identified through 2-DE and 116 were generated by iTRAQ. It is noteworthy that only three proteins could be detected via both iTRAQ and 2-DE, and most of the identified DEPs were not newly produced proteins but proteins with altered abundance. These results indicated that many DEPs could be detected in the proteome of PT maize seeds and the corresponding wild type after overexpression of the target gene, but the changes in these proteins were not substantial. Functional classification revealed many DEPs involved in posttranscriptional modifications and some ribosomal proteins and heat-shock proteins that may generate adaptive effects in response to the insertion of exogenous genes. Protein-protein interaction analysis demonstrated that the detected interacting proteins were mainly ribosomal proteins and heat-shock proteins. Our data provided new information on such unintended effects through a proteomic analysis of maize seeds.

Citing Articles

Insight into phytase-producing microorganisms for phytate solubilization and soil sustainability.

Rizwanuddin S, Kumar V, Singh P, Naik B, Mishra S, Chauhan M Front Microbiol. 2023; 14:1127249.

PMID: 37113239 PMC: 10128089. DOI: 10.3389/fmicb.2023.1127249.

Improvement of cell suspension cultures of transformed and untransformed cell lines, towards the development of an antiparasitic product against the gastrointestinal nematode .

Ortiz Caltempa A, Hernandez M, Perez A, Aguilar L, Guzman C, Ayon-Nunez D Front Cell Infect Microbiol. 2022; 12:958741.

PMID: 36159651 PMC: 9493254. DOI: 10.3389/fcimb.2022.958741.

Proteomics as a promising biomarker in food authentication, quality and safety: A review.

Afzaal M, Saeed F, Hussain M, Shahid F, Siddeeg A, Al-Farga A Food Sci Nutr. 2022; 10(7):2333-2346.

PMID: 35844910 PMC: 9281926. DOI: 10.1002/fsn3.2842.

Untargeted Proteomics-Based Approach to Investigate Unintended Changes in Genetically Modified Maize for Environmental Risk Assessment Purpose.

Agapito-Tenfen S, Guerra M, Nodari R, Wikmark O Front Toxicol. 2022; 3:655968.

PMID: 35295118 PMC: 8915820. DOI: 10.3389/ftox.2021.655968.

Proteomic Advances in Cereal and Vegetable Crops.

Agregan R, Echegaray N, Lopez-Pedrouso M, Aadil R, Hano C, Franco D Molecules. 2021; 26(16).

PMID: 34443513 PMC: 8401599. DOI: 10.3390/molecules26164924.

References

Zieske L . A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies. J Exp Bot. 2006; 57(7):1501-8. DOI: 10.1093/jxb/erj168. View

Benesova M, Hola D, Fischer L, Jedelsky P, Hnilicka F, Wilhelmova N . The physiology and proteomics of drought tolerance in maize: early stomatal closure as a cause of lower tolerance to short-term dehydration?. PLoS One. 2012; 7(6):e38017. PMC: 3374823. DOI: 10.1371/journal.pone.0038017. View

Wang X, Wang D, Wang D, Wang H, Chang L, Yi X . Systematic comparison of technical details in CBB methods and development of a sensitive GAP stain for comparative proteomic analysis. Electrophoresis. 2012; 33(2):296-306. DOI: 10.1002/elps.201100300. View

Zorb C, Schmitt S, Muhling K . Proteomic changes in maize roots after short-term adjustment to saline growth conditions. Proteomics. 2010; 10(24):4441-9. DOI: 10.1002/pmic.201000231. View

Li S, Niu Y, Liu J, Lu L, Zhang L, Ran C . Energy, amino acid, and phosphorus digestibility of phytase transgenic corn for growing pigs. J Anim Sci. 2012; 91(1):298-308. DOI: 10.2527/jas.2012-5211. View

Robledo S, Idol R, Crimmins D, Ladenson J, Mason P, Bessler M . The role of human ribosomal proteins in the maturation of rRNA and ribosome production. RNA. 2008; 14(9):1918-29. PMC: 2525958. DOI: 10.1261/rna.1132008. View

Li J, Ding X, Han S, He T, Zhang H, Yang L . Differential proteomics analysis to identify proteins and pathways associated with male sterility of soybean using iTRAQ-based strategy. J Proteomics. 2016; 138:72-82. DOI: 10.1016/j.jprot.2016.02.017. View

Ruebelt M, Lipp M, Reynolds T, Schmuke J, Astwood J, DellaPenna D . Application of two-dimensional gel electrophoresis to interrogate alterations in the proteome of gentically modified crops. 3. Assessing unintended effects. J Agric Food Chem. 2006; 54(6):2169-77. DOI: 10.1021/jf052358q. View

Wu X, Wang W . Increasing Confidence of Proteomics Data Regarding the Identification of Stress-Responsive Proteins in Crop Plants. Front Plant Sci. 2016; 7:702. PMC: 4877514. DOI: 10.3389/fpls.2016.00702. View

10.

Alvarez S, Berla B, Sheffield J, Cahoon R, Jez J, Hicks L . Comprehensive analysis of the Brassica juncea root proteome in response to cadmium exposure by complementary proteomic approaches. Proteomics. 2009; 9(9):2419-31. DOI: 10.1002/pmic.200800478. View

11.

Ye J, Fang L, Zheng H, Zhang Y, Chen J, Zhang Z . WEGO: a web tool for plotting GO annotations. Nucleic Acids Res. 2006; 34(Web Server issue):W293-7. PMC: 1538768. DOI: 10.1093/nar/gkl031. View

12.

Fukao Y, Ferjani A, Tomioka R, Nagasaki N, Kurata R, Nishimori Y . iTRAQ analysis reveals mechanisms of growth defects due to excess zinc in Arabidopsis. Plant Physiol. 2011; 155(4):1893-907. PMC: 3091079. DOI: 10.1104/pp.110.169730. View

13.

Wang W, Vinocur B, Shoseyov O, Altman A . Role of plant heat-shock proteins and molecular chaperones in the abiotic stress response. Trends Plant Sci. 2004; 9(5):244-52. DOI: 10.1016/j.tplants.2004.03.006. View

14.

Wang X, Li Q, Jin X, Xiao G, Liu G, Liu N . Quantitative proteomics and transcriptomics reveal key metabolic processes associated with cotton fiber initiation. J Proteomics. 2014; 114:16-27. DOI: 10.1016/j.jprot.2014.10.022. View

15.

Tan Y, Yi X, Wang L, Peng C, Sun Y, Wang D . Comparative Proteomics of Leaves from Phytase-Transgenic Maize and Its Non-transgenic Isogenic Variety. Front Plant Sci. 2016; 7:1211. PMC: 4987384. DOI: 10.3389/fpls.2016.01211. View

16.

Peng J, Elias J, Thoreen C, Licklider L, Gygi S . Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J Proteome Res. 2003; 2(1):43-50. DOI: 10.1021/pr025556v. View

17.

Rappsilber J, Mann M . What does it mean to identify a protein in proteomics?. Trends Biochem Sci. 2002; 27(2):74-8. DOI: 10.1016/s0968-0004(01)02021-7. View

18.

Zolla L, Rinalducci S, Antonioli P, Righetti P . Proteomics as a complementary tool for identifying unintended side effects occurring in transgenic maize seeds as a result of genetic modifications. J Proteome Res. 2008; 7(5):1850-61. DOI: 10.1021/pr0705082. View

19.

Wang X, Shan X, Wu Y, Su S, Li S, Liu H . iTRAQ-based quantitative proteomic analysis reveals new metabolic pathways responding to chilling stress in maize seedlings. J Proteomics. 2016; 146:14-24. DOI: 10.1016/j.jprot.2016.06.007. View

20.

Smith L, Kelleher N . Proteoform: a single term describing protein complexity. Nat Methods. 2013; 10(3):186-7. PMC: 4114032. DOI: 10.1038/nmeth.2369. View