Proteomic analysis of four Brazilian MON810 maize varieties and their four non-genetically-modified isogenic varieties

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

Profiling technologies, such as proteomics, allow the simultaneous measurement and comparison of thousands of plant components without prior knowledge of their identity. The combination of these non-targeted methods facilitates a more comprehensive approach than targeted methods and thus provides additional opportunities to identify genotypic changes resulting from genetic modification, including new allergens or toxins. The purpose of this study was to investigate unintended changes in GM Bt maize grown in South Africa. In the present study, we used bi-dimensional gel electrophoresis based on fluorescence staining, coupled with mass spectrometry in order to compare the proteome of the field-grown transgenic hybrid (MON810) and its near-isogenic counterpart. Proteomic data showed that energy metabolism and redox homeostasis were unequally modulated in GM Bt and non-GM maize variety samples. In addition, a potential allergenic protein-pathogenesis related protein -1 has been identified in our sample set. Our data shows that the GM variety is not substantially equivalent to its non-transgenic near-isogenic variety and further studies should be conducted in order to address the biological relevance and the potential risks of such changes. These finding highlight the suitability of unbiased profiling approaches to complement current GMO risk assessment practices worldwide.

Proteomic analysis of the seeds of transgenic rice lines and the corresponding nongenetically modified isogenic variety

BACKGROUND

An isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic analysis was employed to study the seeds of two genetically modified (GM) rice lines, T2A-1 and T1C-19, and their nontransgenic isogenic variety, MH63, to investigate the unintended effects of genetic modification.

RESULTS

A total of 3398 proteins were quantitatively identified. Seventy-seven differentially abundant proteins (DAPs) were identified in the T2A-1/MH63 comparison, and 70 and 7 of these DAPs were upregulated and downregulated, respectively. A pathway enrichment analysis showed that most of these DAPs participated in metabolic pathways and protein processing in endoplasmic reticulum and were ribosome components. Some 181 DAPs were identified from the T1C-19/MH63 comparison, and these included 115 upregulated proteins and 66 downregulated proteins. The subsequent pathway enrichment analysis showed that these DAPs mainly participated in protein processing in endoplasmic reticulum and carbon fixation in photosynthetic organisms and were ribosome components. None of these DAPs were identified as new unintended toxins or allergens, and only changes in abundance were detected. Fifty-four co-DAPs were identified in the seeds of the two GM rice lines, and protein-protein interaction analysis of these co-DAPs demonstrated that some interacting proteins were involved in protein processing in endoplasmic reticulum and metabolic pathways, whereas others were identified as ribosome components. Representative co-DAPs and proteins related to nutrients were analyzed using qRT-PCR to determine their transcriptional levels.

CONCLUSIONS

The results suggested that the seed proteomic profiles of the two GM rice lines studied were not substantially altered from those of their natural isogenic control. © 2020 Society of Chemical Industry.

Investigation and development of maize fused network analysis with multi-omics

Maize is a critically important staple crop in the whole world, which has contributed to both economic security and food in planting areas. The main target for researchers and breeding is the improvement of maize quality and yield. The use of computational biology methods combined with multi-omics for selecting biomolecules of interest for maize breeding has been receiving more attention. Moreover, the rapid growth of high-throughput sequencing data provides the opportunity to explore biomolecules of interest at the molecular level in maize. Furthermore, we constructed weighted networks for each of the omics and then integrated them into a final fused weighted network based on a nonlinear combination method. We also analyzed the final fused network and mined the orphan nodes, some of which were shown to be transcription factors that played a key role in maize development. This study could help to improve maize production via insights at the multi-omics level and provide a new perspective for maize researchers. All related data have been released at http://lab.malab.cn/∼jj/maize.htm.

Comparative Proteomics of Phytase-transgenic Maize Seeds Indicates Environmental Influence is More Important than that of Gene Insertion

Proteomic differences were compared between phytase-transgenic (PT) maize seeds and nontransgenic (NT) maize seeds through two-dimensional electrophoresis (2-DE) with mass spectrometry (MS). When maize was grown under field conditions, 30 differentially accumulated proteins (DAPs) were successfully identified in PT seeds (PT/NT). Clusters of Orthologous Groups (COG) functional classification of these proteins showed that the largest group was associated with posttranslational modifications. To investigate the effects of environmental factors, we further compared the seed protein profiles of the same maize planted in a greenhouse or under field conditions. There were 76 DAPs between the greenhouse- and field-grown NT maize seeds and 77 DAPs between the greenhouse- and field-grown PT maize seeds However, under the same planting conditions, there were only 43 DAPs (planted in the greenhouse) or 37 DAPs (planted in the field) between PT and NT maize seeds. The results revealed that DAPs caused by environmental factors were more common than those caused by the insertion of exogenous genes, indicating that the environment has much more important effects on the seed protein profiles. Our maize seed proteomics results also indicated that the occurrence of unintended effects is not specific to genetically modified crops (GMCs); instead, such effects often occur in traditionally bred plants. Our data may be beneficial for biosafety assessments of GMCs at the protein profile level in the future.

iTRAQ-based quantitative tissue proteomic analysis of differentially expressed proteins (DEPs) in non-transgenic and transgenic soybean seeds

The unintended effects of transgenesis have increased food safety concerns, meriting comprehensive evaluation. Proteomic profiling provides an approach to directly assess the unintended effects. Herein, the isobaric tags for relative and absolute quantitation (iTRAQ) comparative proteomic approach was employed to evaluate proteomic profile differences in seed cotyledons from 4 genetically modified (GM) and 3 natural genotypic soybean lines. Compared with their non-GM parents, there were 67, 61, 13 and 22 differentially expressed proteins (DEPs) in MON87705, MON87701 × MON89788, MON87708, and FG72. Overall, 170 DEPs were identified in the 3 GM soybean lines with the same parents, but 232 DEPs were identified in the 3 natural soybean lines. Thus, the differences in protein expression among the genotypic varieties were greater than those caused by GM. When considering ≥2 replicates, 4 common DEPs (cDEPs) were identified in the 3 different GM soybean lines with the same parents and 6 cDEPs were identified in the 3 natural varieties. However, when considering 3 replicates, no cDEPs were identified. Regardless of whether ≥2 or 3 replicates were considered, no cDEPs were identified among the 4 GM soybean lines. Therefore, no feedback due to GM was observed at the common protein level in this study.

Omics analyses of potato plant materials using an improved one-class classification tool to identify aberrant compositional profiles in risk assessment procedures

The objective of this study was to quantitatively assess potato omics profiles of new varieties for meaningful differences from analogous profiles of commercial varieties through the SIMCA one-class classification model. Analytical profiles of nine commercial potato varieties, eleven experimental potato varieties, one GM potato variety that had acquired Phytophtora resistance based on a single insert with potato-derived DNA sequences, and its non-GM commercial counterpart were generated. The ten conventional varieties were used to construct the one-class model. Omics profiles from experimental non-GM and GM varieties were assessed using the one-class SIMCA models. No potential unintended effects were identified in the case of the GM variety. The model showed that varieties that were genetically more distant from the commercial varieties were recognized as aberrant, highlighting its potential in determining whether additional evaluation is required for the risk assessment of materials produced from any breeding technique, including genetic modification.

Proteomic analysis of phytase transgenic and non-transgenic maize seeds

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.

Molecular responses of genetically modified maize to abiotic stresses as determined through proteomic and metabolomic analyses

Some genetically modified (GM) plants have transgenes that confer tolerance to abiotic stressors. Meanwhile, other transgenes may interact with abiotic stressors, causing pleiotropic effects that will affect the plant physiology. Thus, physiological alteration might have an impact on the product safety. However, routine risk assessment (RA) analyses do not evaluate the response of GM plants exposed to different environmental conditions. Therefore, we here present a proteome profile of herbicide-tolerant maize, including the levels of phytohormones and related compounds, compared to its near-isogenic non-GM variety under drought and herbicide stresses. Twenty differentially abundant proteins were detected between GM and non-GM hybrids under different water deficiency conditions and herbicide sprays. Pathway enrichment analysis showed that most of these proteins are assigned to energetic/carbohydrate metabolic processes. Among phytohormones and related compounds, different levels of ABA, CA, JA, MeJA and SA were detected in the maize varieties and stress conditions analysed. In pathway and proteome analyses, environment was found to be the major source of variation followed by the genetic transformation factor. Nonetheless, differences were detected in the levels of JA, MeJA and CA and in the abundance of 11 proteins when comparing the GM plant and its non-GM near-isogenic variety under the same environmental conditions. Thus, these findings do support molecular studies in GM plants Risk Assessment analyses.

Comparative Proteomics of Leaves from Phytase-Transgenic Maize and Its Non-transgenic Isogenic Variety

To investigate unintended effects in genetically modified crops (GMCs), a comparative proteomic analysis between the leaves of the phytase-transgenic maize and the non-transgenic plants was performed using two-dimensional gel electrophoresis and mass spectrometry. A total of 57 differentially expressed proteins (DEPs) were successfully identified, which represents 44 unique proteins. Functional classification of the identified proteins showed that these DEPs were predominantly involved in carbohydrate transport and metabolism category, followed by post-translational modification. KEGG pathway analysis revealed that most of the DEPs participated in carbon fixation in photosynthesis. Among them, 15 proteins were found to show protein-protein interactions with each other, and these proteins were mainly participated in glycolysis and carbon fixation. Comparison of the changes in the protein and tanscript levels of the identified proteins showed that most proteins had a similar pattern of changes between proteins and transcripts. Our results suggested that although some significant differences were observed, the proteomic patterns were not substantially different between the leaves of the phytase-transgenic maize and the non-transgenic isogenic type. Moreover, none of the DEPs was identified as a new toxic protein or an allergenic protein. The differences between the leaf proteome might be attributed to both genetic modification and hybrid influence.

Tuber proteome comparison of five potato varieties by principal component analysis

BACKGROUND

Data analysis of omics data should be performed by multivariate analysis such as principal component analysis (PCA). The way data are clustered in PCA is of major importance to develop some classification systems based on multivariate analysis, such as soft independent modeling of class analogy (SIMCA). In a previous study a one-class classifier based on SIMCA was built using microarray data from a set of potatoes. The PCA grouped the transcriptomic data according to varieties. The present work aimed to use PCA to verify the clustering of the proteomic profiles for the same potato varieties.

RESULTS

Proteomic profiles of five potato varieties (Biogold, Fontane, Innovator, Lady Rosetta and Maris Piper) were evaluated by two-dimensional gel electrophoresis (2-DE) performed on two immobilized pH gradient (IPG) strip lengths, 13 and 24 cm, both under pH range 4-7. For each strip length, two gels were prepared from each variety; in total there were ten gels per analysis. For 13 cm strips, 199-320 spots were detected per gel, and for 24 cm strips, 365-684 spots.

CONCLUSION

All four PCAs performed with these datasets presented clear grouping of samples according to the varieties. The data presented here showed that PCA was applicable for proteomic analysis of potato and was able to separate the samples by varieties. © 2016 Society of Chemical Industry.

Review on proteomics for food authentication

Consumers have the right to know what is in the food they are eating. Accordingly, European and global food regulations require that the provenance of the food can be guaranteed from farm to fork. Many different instrumental techniques have been proposed for food authentication. Although traditional methods are still being used, new approaches such as genomics, proteomics, and metabolomics are helping to complement existing methodologies for verifying the claims made about certain food products. During the last decade, proteomics (the large-scale analysis of proteins in a particular biological system at a particular time) has been applied to different research areas within food technology. Since proteins can be used as markers for many properties of a food, even indicating processes to which the food has been subjected, they can provide further evidence of the foods labeling claim. This review is a comprehensive and updated overview of the applications, drawbacks, advantages, and challenges of proteomics for food authentication in the assessment of the foods compliance with labeling regulations and policies.

SIGNIFICANCE

This review paper provides a comprehensive and critical overview of the application of proteomics approaches to determine the authenticity of several food products updating the performances and current limitations of the applied techniques in both laboratory and industrial environments.

Leaf proteome comparison of two GM common bean varieties and their non-GM counterparts by principal component analysis

BACKGROUND

A genetically modified (GM) common bean event, namely Embrapa 5.1, was approved for commercialization in Brazil. The present work aimed to use principal component analysis (PCA) to compare the proteomic profile of this GM common bean and its non-GM counterpart.

RESULTS

Seedlings from four Brazilian common bean varieties were grown under controlled environmental conditions. Leaf proteomic profiles were analyzed by two-dimensional gel electrophoresis (2DE). First, a comparison among 12 gels from four common bean varieties was performed by PCA using volume percentage of 198 matched spots, presented in all gels. The first two principal components (PC) accounted for 46.8% of total variation. Two groups were clearly separated by the first component: Pérola and GM Pérola from Pontal and GM Pontal. Secondly, another comparison among six gels from the same variety GM and its non-GM counterpart was performed by PCA; in this case it was possible to distinguish GM and non-GM.

CONCLUSION

Separation between leaf proteomic profile of GM common bean variety and its counterpart was observed only when they were compared in pairs. These results showed higher similarity between GM variety and its counterpart than between two common bean varieties. PCA is a useful tool to compare proteomes of GM and non-GM plant varieties.

Comparative Proteomic Analysis of Two Varieties of Genetically Modified (GM) Embrapa 5.1 Common Bean (Phaseolus vulgaris L.) and Their Non-GM Counterparts

The genetically modified (GM) common bean event Embrapa 5.1 was commercially approved in Brazil in 2011; it is resistant to golden mosaic virus infection. In the present work grain proteome profiles of two Embrapa 5.1 common bean varieties, Pérola and Pontal, and their non-GM counterparts were compared by two-dimensional gel electrophoresis (2-DE) followed by mass spectrometry (MS). Analyses detected 23 spots differentially accumulated between GM Pérola and non-GM Pérola and 21 spots between GM Pontal and non-GM Pontal, although they were not the same proteins in Pérola and Pontal varieties, indicating that the variability observed may not be due to the genetic transformation. Among them, eight proteins were identified in Pérola varieties, and four proteins were identified in Pontal. Moreover, we applied principal component analysis (PCA) on 2-DE data, and variation between varieties was explained in the first two principal components. This work provides a first 2-DE-MS/MS-based analysis of Embrapa 5.1 common bean grains.

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

Background

As 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.

Results

Using 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.

Conclusions

Our 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 material

The online version of this article (doi:10.1186/s12953-015-0071-8) contains supplementary material, which is available to authorized users.

Effect of stacking insecticidal cry and herbicide tolerance epsps transgenes on transgenic maize proteome

BACKGROUND

The safe use of stacked transgenic crops in agriculture requires their environmental and health risk assessment, through which unintended adverse effects are examined prior to their release in the environment. Molecular profiling techniques can be considered useful tools to address emerging biosafety gaps. Here we report the first results of a proteomic profiling coupled to transgene transcript expression analysis of a stacked commercial maize hybrid containing insecticidal and herbicide tolerant traits in comparison to the single event hybrids in the same genetic background.

RESULTS

Our results show that stacked genetically modified (GM) genotypes were clustered together and distant from other genotypes analyzed by PCA. Twenty-two proteins were shown to be differentially modulated in stacked and single GM events versus non-GM isogenic maize and a landrace variety with Brazilian genetic background. Enrichment analysis of these proteins provided insight into two major metabolic pathway alterations: energy/carbohydrate and detoxification metabolism. Furthermore, stacked transgene transcript levels had a significant reduction of about 34% when compared to single event hybrid varieties.

CONCLUSIONS

Stacking two transgenic inserts into the genome of one GM maize hybrid variety may impact the overall expression of endogenous genes. Observed protein changes differ significantly from those of single event lines and a conventional counterpart. Some of the protein modulation did not fall within the range of the natural variability for the landrace used in this study. Higher expression levels of proteins related to the energy/carbohydrate metabolism suggest that the energetic homeostasis in stacked versus single event hybrid varieties also differ. Upcoming global databases on outputs from "omics" analyses could provide a highly desirable benchmark for the safety assessment of stacked transgenic crop events. Accordingly, further studies should be conducted in order to address the biological relevance and implications of such changes.

Comparative proteomic analysis of genetically modified maize grown under different agroecosystems conditions in Brazil

BACKGROUND

Profiling technologies allow the simultaneous measurement and comparison of thousands of cell components without prior knowledge of their identity. In the present study, we used two-dimensional gel electrophoresis combined with mass spectrometry to evaluate protein expression of Brazilian genetically modified maize hybrid grown under different agroecosystems conditions. To this effect, leaf samples were subjected to comparative analysis using the near-isogenic non-GM hybrid as the comparator.

RESULTS

In the first stage of the analysis, the main sources of variation in the dataset were identified by using Principal Components Analysis which correlated most of the variation to the different agroecosystems conditions. Comparative analysis within each field revealed a total of thirty two differentially expressed proteins between GM and non-GM samples that were identified and their molecular functions were mainly assigned to carbohydrate and energy metabolism, genetic information processing and stress response.

CONCLUSIONS

To the best of our knowledge this study represents the first evidence of protein identities with differentially expressed isoforms in Brazilian MON810 genetic background hybrid grown under field conditions. As global databases on outputs from "omics" analysis become available, these could provide a highly desirable benchmark for safety assessments.

Promise and issues of genetically modified crops

The growing area of genetically modified (GM) crops has substantially expanded since they were first commercialized in 1996. Correspondingly, the adoption of GM crops has brought huge economic and environmental benefits. All these achievements have been primarily supported by two simple traits of herbicide tolerance and insect resistance in the past 17 years. However, this situation will change soon. Recently, the advance of new products, technologies and safety assessment approaches has provided new opportunities for development of GM crops. In this review, we focus on the developmental trend in various aspects of GM crops including new products, technical innovation and risk assessment approaches, as well as potential challenges that GM crops are currently encountering.

Proteomic evaluation of genetically modified crops: current status and challenges

Hectares of genetically modified (GM) crops have increased exponentially since 1996, when such crops began to be commercialized. GM biotechnology, together with conventional breeding, has become the main approach to improving agronomic traits of crops. However, people are concerned about the safety of GM crops, especially GM-derived food and feed. Many efforts have been made to evaluate the unintended effects caused by the introduction of exogenous genes. "Omics" techniques have advantages over targeted analysis in evaluating such crops because of their use of high-throughput screening. Proteins are key players in gene function and are directly involved in metabolism and cellular development or have roles as toxins, antinutrients, or allergens, which are essential for human health. Thus, proteomics can be expected to become one of the most useful tools in safety assessment. This review assesses the potential of proteomics in evaluating various GM crops. We further describe the challenges in ensuring homogeneity and sensitivity in detection techniques.

Assessment of GE food safety using '-omics' techniques and long-term animal feeding studies

Despite the fact that a thorough, lengthy and costly evaluation of genetically engineered (GE) crop plants (including compositional analysis and toxicological tests) is imposed before marketing some European citizens remain sceptical of the safety of GE food and feed. In this context, are additional tests necessary? If so, what can we learn from them? To address these questions, we examined data from 60 recent high-throughput '-omics' comparisons between GE and non-GE crop lines and 17 recent long-term animal feeding studies (longer than the classical 90-day subchronic toxicological tests), as well as 16 multigenerational studies on animals. The '-omics' comparisons revealed that the genetic modification has less impact on plant gene expression and composition than that of conventional plant breeding. Moreover, environmental factors (such as field location, sampling time, or agricultural practices) have a greater impact than transgenesis. None of these '-omics' profiling studies has raised new safety concerns about GE varieties; neither did the long-term and multigenerational studies on animals. Therefore, there is no need to perform such long-term studies in a case-by-case approach, unless reasonable doubt still exists after conducting a 90-day feeding test. In addition, plant compositional analysis and '-omics' profiling do not indicate that toxicological tests should be mandatory. We discuss what complementary fundamental studies should be performed and how to choose the most efficient experimental design to assess risks associated with new GE traits. The possible need to update the current regulatory framework is discussed.