Comparative proteomics of Bt-transgenic and non-transgenic cotton leaves

Abstract

BackgroundAs the rapid growth of the commercialized acreage in genetically modified (GM) crops, the unintended effects of GM crops’ biosafety assessment have been given much attention. To investigate whether transgenic events cause unintended effects, comparative proteomics of cotton leaves between the commercial transgenic Bt + CpTI cotton SGK321 (BT) clone and its non-transgenic parental counterpart SY321 wild type (WT) was performed.ResultsUsing enzyme linked immunosorbent assay (ELISA), Cry1Ac toxin protein was detected in the BT leaves, while its content was only 0.31 pg/g. By 2-DE, 58 differentially expressed proteins (DEPs) were detected. Among them 35 were identified by MS. These identified DEPs were mainly involved in carbohydrate transport and metabolism, chaperones related to post-translational modification and energy production. Pathway analysis revealed that most of the DEPs were implicated in carbon fixation and photosynthesis, glyoxylate and dicarboxylate metabolism, and oxidative pentose phosphate pathway. Thirteen identified proteins were involved in protein-protein interaction. The protein interactions were mainly involved in photosynthesis and energy metabolite pathway.ConclusionsOur study demonstrated that exogenous DNA in a host cotton genome can affect the plant growth and photosynthesis. Although some unintended variations of proteins were found between BT and WT cotton, no toxic proteins or allergens were detected. This study verified genetically modified operation did not sharply alter cotton leaf proteome, and the target proteins were hardly checked by traditional proteomic analysis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12953-015-0071-8) contains supplementary material, which is available to authorized users.

An integrated multi-omics analysis of the NK603 Roundup-tolerant GM maize reveals metabolism disturbances caused by the transformation process

“…Comparative omics analyses have been performed comparing GMO crops and their isogenic counterpart. A number of them have shown metabolic disturbances from potential unintended effects of the GM transformation process in Bt maize9101112, glyphosate-tolerant soybean131415, potato16, cotton17 and rice18. However, these studies do not report consistent or coherent results, which can be explained by the use of a variety of genetic backgrounds and/or different growth conditions, as well as variations in the technologies and threshold levels applied19.…”

RNA Interference for Functional Genomics and Improvement of Cotton (Gossypium sp.)

“…It includes: (1) the evaluation of the RNAi cultivar for desired trait expression; (2) experimental quantification of the gene-knockdown level of targeted gene expression; and (3) comparative sequencing of siRNA sequence profile before and after RNAi. Although currently not validated within the regulatory framework for food safety assessment, additionally, comparative studying of proteome and metabolome profiles of RNAi cultivar/product may be considered ( Ricroch et al, 2011 ; Clarke et al, 2013 ; Simó et al, 2014 ; Wang et al, 2015b ). These steps could identify any “off-target” phenotypes, visible side effects, production of unexpected novel siRNA or/and secondary RNA signatures as well as unknown proteome/metabolome components in RNAi cultivar genome and its products.…”

Prospecting for Microelement Function and Biosafety Assessment of Transgenic Cereal Plants

“…Transgenic technology has brought many promising GM plants with improved quality and/or enhanced stress tolerance and has also allowed microelement non-accumulators to accumulate trace minerals and common plants to hyperaccumulate them. Lots of work has been done to compare GM crops and their non-transgenic counterparts (Yang et al, 2013 ; Wang L. et al, 2015 ). These comparative analyses were mostly conducted by proteomics methods, which mainly use two-dimensional electrophoresis (2-DE) coupled with mass spectrometry (MS) to distinguish differential proteins or protein content between GM crops and their wild types (Barros et al, 2010 ; Brandão et al, 2010 ; Yang et al, 2013 ; Wang L. et al, 2015 ).…”

“…Lots of work has been done to compare GM crops and their non-transgenic counterparts (Yang et al, 2013 ; Wang L. et al, 2015 ). These comparative analyses were mostly conducted by proteomics methods, which mainly use two-dimensional electrophoresis (2-DE) coupled with mass spectrometry (MS) to distinguish differential proteins or protein content between GM crops and their wild types (Barros et al, 2010 ; Brandão et al, 2010 ; Yang et al, 2013 ; Wang L. et al, 2015 ). Metabolomics techniques such as HPLC, NMR, and GC/MS have also been used to analyze differences between metabolites including carbohydrates, lipids, and amino acids (Brandão et al, 2010 ).…”