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A transcriptomic analysis for identifying the unintended effects of introducing a heterologous glyphosate-tolerant EPSP synthase into Escherichia coli† Liang Li,‡ab Zhengfu Zhou,‡a Wujun Jin,ab Yusong Wan*ab and Wei Lu*a Glyphosate is one of the most commonly used broad-spectrum herbicides with little to no hazard to animals, human beings, or the environment. Some microbial 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase variants are not inhibited by glyphosate, and they provide a powerful tool to engineer glyphosatetolerant plants. However, the unintended effects of EPSP synthase expression patterns on microbes are not yet clear. Here, we use an Affymetrix GeneChip analysis to study how introduction of a heterologous glyphosate-tolerant EPSP synthase into a model microorganism Escherichia coli (E. coli) affects the global gene expression profile. The profile showed that 161 of 4071 genes were differentially expressed after the introduction of the synthase: 19 (0.47%) were up-regulated and 143 (3.49%) were down-regulated.
Received 24th September 2014, Accepted 17th December 2014
The microarray results, in combination with BiOLOG substrate utilization and amino acid composition
DOI: 10.1039/c4mb00566j
a small number of genes and metabolites were affected by EPSP synthase expression, no functional
assays, suggested that heterologous EPSP synthase expression had very minor effects on E. coli. Although correlations were identified among the dataset. This study may shed light on the effect of EPSP synthase
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expression on microbes, which should help in the assessment of environmental safety.
Introduction Glyphosate is one of the most commonly used broad-spectrum herbicides and demonstrates little to no hazard to animals, human beings, or the environment.1 It inhibits the enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase (EC 2.5.1.19), which is the sixth enzyme of the shikimate pathway.2 This enzyme is essential for the biosynthesis of aromatic amino acids and other aromatic compounds in plants and microorganisms, including apicomplexan parasites.3,4 The EPSP synthase variants derived from some microbes, such as Agrobacterium tumefaciens sp. CP4 and Pseudomonas stutzeri A1501, are not inhibited by glyphosate and are used to engineer glyphosate-tolerant genetically modified (GM) crops.5 Glyphosate-tolerant crops marketed as Roundup Readys occupy the greatest acreage. In 2013, globally, herbicide tolerance was deployed in soybeans, maize, canola, cotton, sugar, beets, and alfalfa, which occupied 99.4 million a
Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China b Inspection and Testing Center for Environmental Risk Assessment of Genetic Modified Plant-related Microorganism (Beijing), Ministry of Agriculture, Beijing 100081, China † Electronic supplementary information (ESI) available. See DOI: 10.1039/ c4mb00566j ‡ These authors contributed equally to this work.
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hectares or 57% of the 175.3 million hectares of biotech crops planted.6 In the safety assessment, GM crop-derived foods and feeds are compared with their counterparts from parental or near-isogenic lines to identify differences, which are subsequently evaluated with respect to their safety to the environment, humans and animals. Because of the rapid increase in the number of biotech crops used for food production, consumers are becoming increasingly concerned about the risks posed by GM crops and their derivatives.7 A major principle and guiding tool for the food safety assessment of GM crops is the concept of ‘‘substantial equivalence’’ according to the principles outlined in the Organization for Economic Cooperation and Development (OECD) consensus documents8 and further elaborated by the Food and Agriculture Organization (FAO) of the United Nations/World Health Organization. The current safety assessment procedures developed for GM crops are primarily based on a targeted compositional analysis of specific safety and nutrition-related compounds.9–11 Additionally, the subject to be addressed is as follows: the transfer of DNA from plants to microorganisms may occur because the heterologous gene in a glyphosate-tolerant plant is derived from microbes, and assessing the unintended effects caused by horizontal gene transfer is necessary. Targeted analysis may, however, have its limitations in detecting unintended effects on GM organisms. Therefore,
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non-targeted/fingerprinting technologies that are unbiased analytical approaches for detecting the potential occurrence of unintended effects have been developed.12 Profiling technologies such as transcriptomics, proteomics and metabolomics have been suggested to broaden the spectrum of detectable compounds and thus supplement the current targeted analytical approaches. These methodologies are widely used to investigate the unintended effects on GM crops compared with those on traditionally bred in recent years.13,14 In a recently published paper,15 three profiling technologies were used to compare two transgenic maize lines (one GM Bt variety and one GM glyphosatetolerant variety) with the respective control line. Although the sources of variation in the dataset were the same for all the techniques used (the environment being the dominant one), no functional correlations were identified between the genes, proteins and metabolites driving this variation. E. coli has been a model organism in the field of basic biomolecular sciences for ‘‘-omics’’ studies because it is a variable species with a highly dynamic genome.16,17 The metabolic networks in E. coli are known to evolve in response to changing environments by acquiring heterologous genes and operons by horizontal gene transfer.18 E. coli studies have played a pioneering role in our understanding of DNA replication, transcription, translation, gene regulation, restriction enzymes and horizontal gene transfer.19 Furthermore, E. coli is a model that is extensively used to study the molecular mechanisms underlying bacterial metabolic networks. We previously reported the first global analysis of the glyphosate shock response in E. coli by transcriptomics and indicated that the presence of glyphosate during growth induces metabolic starvation, energy drain and other off-target effects.20 These results demonstrate that, in addition to the genes encoding the enzymes of the shikimate pathway, glyphosate triggers transcriptional responses in the genes that are associated with non-shikimate pathways such as cell motility, energy production, and carbohydrate metabolism. Moreover, we identified an array of previously uncharacterized glyphosate-responsive genes, which may act as potential targets for non-toxic herbicides and anti-microbial compounds. In the current study, we performed DNA microarray experiments and used data from metabolite measurements and free amino acid composition to investigate the unintended effects of heterologous glyphosate-tolerant EPSP synthase expression in the E. coli host. It is hoped that the dataset presented serves as an exploratory study into the use of transcriptomics for assessment of unintended effects on microbes.
Materials and methods Bacterial strains, plasmids, and growth conditions E. coli JM109 [genotype: endA1, recA1, gyrA96, thi, hsdR17 (rk, mk+), relA1, supE44, D(lac-proAB), [F 0 , traD36, proAB, laqIqZDM15]] (Promega, Madison, WI, USA) harboring pUCA1501 (transformant strain) and the control plasmid pUC18 (control strain)21 were used in this study. Cells were grown aerobically in Luria-Bertani (LB) broth at 37 1C. Ampicillin
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(50 mg mL1) was added to the culture medium as appropriate. Overnight LB cultures were inoculated and sub-cultured to a starting OD600 of 0.001. The cultures were harvested at an OD600 of 0.400. For the functional validation of A1501 EPSP synthase, cells containing pUC-A1501 and pUC18 were incubated in M9 minimal medium supplemented with 0 mM and 200 mM glyphosate at 37 1C. The growth was monitored as the OD600 value. Compared with the control strain, the positive colonies with a higher tolerance to glyphosate were subjected to an additional assay to confirm the initial results. BiOLOG GN2 substrate utilization patterns To assess the effect of heterologous EPSP synthase on the metabolic potential of E. coli, the utilization of various carbon sources was determined in triplicate by using a BiOLOG GN2 microplate, which detects the utilization of 95 specific carbon sources, as recommended by the manufacturer.22 The plates were checked at regular times after 24 h of incubation for color development by using the BiOLOG microplate reader. The measured extinction values were automatically corrected by incorporating the extinction value of the substrate-free reference well (E0) according to the BiOLOG instruction manual (BiOLOG, Hayward, CA). The cell densities were determined by measuring turbidity using BiOLOG turbidity standards. Standardized microplates allow the simultaneous testing of 95 diagnostically significant carbon sources; one reference well contains no carbon substrate. In addition to the carbon sources, all 96 wells in the tray contained the necessary nutrients for growth in addition to the redox dye in a dry state. The dried preparations in the individual wells were rehydrated by inoculating with the cell suspension. After inoculation (150 mL per well) with an 8-channel repeating pipette, the microplates were incubated at 30 1C for 24 and 48 h. Formazan formation was evaluated using an automatic EL 340 microplate reader (Biotek Instruments, Inc., USA). The identification of the test strains according to their metabolic pattern was performed by using Biolog MicroLog software, which comprised the MicroLog 2-Manual System and the GN database (for Gram-negative bacteria). Microarray sample preparation, data collection and analysis The transformant and control strains were grown and harvested as previously described. The E. coli cells were transferred to M9 minimal medium for 1 h and then pelleted until the OD600 reached 0.4. Total RNA was extracted by the TRIzol (Invitrogen) technique. The RNA was finally resuspended in RNase-free water and quantitated using a Bioanalyzer 2100 (Agilent). The cDNA synthesis and fragmentation and the labeling, washing and scanning of E. coli GeneChip arrays were performed according to the manufacturer’s instructions (Affymetrix, Inc.). Each sample was analyzed using three biological replicates. For RNA manipulation, the cell broth was centrifuged at 10 000 g, and the pellet was quickly frozen in liquid nitrogen and stored at 70 1C. RNA was extracted from thawed cells by the TRIzol (Invitrogen) technique and then purified with an RNeasy Mini Kit (QIAGEN) and DNase I. The RNA was finally resuspended in
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RNase-free water and quantitated using Bioanalyzer 2100 (Agilent). Samples containing ten micrograms of RNA were reverse-transcribed and hybridized to the GeneChip E. coli Genome 2.1 Array by following the manufacturer’s instruction (Affymetrix). To perform this additional DNase digestion, the RNA was precipitated and redissolved in 85 ml of nuclease-free water. We then added 10 mL of 10 DNase I buffer and 5 mL of (1 U mL1) DNase I (Ambion). The DNase reaction mixture was incubated at 37 1C for 30 min and then chilled on ice. A second RNeasy column purification was performed. Chips were analyzed using a GeneArray scanner, GeneChip Fluidics Station 400, and GeneChip Hybridization Oven 640, which were all purchased from Affymetrix. The data were processed by using Microarray Suite version 5.0 (MAS5). The p values were calculated by applying Wilcoxon’s signed rank test and then used to generate the complex calls. Determination of free amino acids In brief, E. coli JM109 containing the pUC-A1501 or pUC18 plasmid was grown overnight at 37 1C in 20 mL of LB broth containing 50 mg mL1 of ampicillin. The cells were collected and transferred into M9 minimal medium. Cell growth was monitored by measuring absorbance at 600 nm (OD600) using a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA). The cells were obtained by centrifugation, washed with ddH2O, and redissolved in 0.5 mL of ddH2O. To analyze the free amino acids, 0.5 mL of the sample was mixed with 0.5 mL of 8% sulfosalicylic acid and centrifuged at 10 000 g for 5 min. The supernatant was then filtered, and an aliquot of 0.5 mL was dried by using an EYELA concentrator (TVE-1000, Tokyo Rikakikai Co., Ltd, Tokyo, Japan). The appropriately diluted supernatant was analyzed using a Sykam S433 amino-acid analyzer (Sykam GmbH, Eresing, Germany). Data verification by RT-qPCR To verify the microarray analysis results, a total of 31 gene encoding proteins in key pathways and differentially expressed proteins were selected to verify the microarray results by reverse transcriptase-qPCR (RT-qPCR). Total RNA was isolated using an SV Total RNA Isolation System (Promega, Madison, WI, USA) and treated with RNase-free DNase I (Promega). The integrity of the RNA was analyzed by agarose gel electrophoresis. First-strand cDNA was synthesized from 1 mg of total RNA in a 20 mL reaction volume using a Protoscript First-Strand cDNA Synthesis Kit (New England Biolabs, Ipswich, MA, USA). For qPCR experiments, the primer pairs shown in Table S4 (ESI†) were designed on the basis of the published reference genome sequence of E. coli str K12 by using Primer Premier 5.0. The amplicons (75 to 250 bp) and reaction specificity were confirmed by agarose gel electrophoresis and product dissociation curves. The qPCR reactions contained 2 mL of cDNA, 10 mL of 2 SYBR Premix Ex Taq (Takara, Dalian, China), 0.4 mL of each primer (20 mM stock), 0.4 mL of 50 Reference Dye II and 6.8 mL of RNase-free water. The amplifications were conducted on an ABI PRISM 7500 Real Time PCR System (Applied Biosystems, Foster City, CA, USA) under the following conditions: 10 min at
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95 1C, followed by 40 cycles of 15 s at 95 1C, 30 s at 60 1C, and 30 s at 72 1C, followed by a melting-curve program (55 1C to 99 1C, with a 5 s hold at each temperature). The qPCR data were analyzed by using the ABI PRISM 7500 Sequence Detection System software (Applied Biosystems). All cDNA samples were run in triplicate. The expression of l6S rRNA (forward primer 5 0 -ATT ACC GCG GCT GCT GG-3 0 ; reverse primer 5 0 -GTC CCG CCC TAC TCA TCG A-3 0 ) was used as an internal control. The RT-qPCR data were analyzed by a relative quantification 2-DDCT method.23 The difference in the cycle numbers at which the amplified gene amount reaches the threshold, or DDCT, was used to determine the differential gene expression. First, the DCT was calculated as the difference between the tested genes and the reference actin gene to normalize the template quantities across treatments. The DDCT was then obtained by comparing the difference in the DCTs of two treatments. The arithmetic fold change was calculated as the 2-DDCT and reported as the log 2-fold change (-DDCT). Microarray data accession number All microarray data (including GenBank accession numbers for sequenced genes) were deposited in the NCBI Gene Expression Omnibus at http://www.ncbi.nlm.nih.gov/geo under accession number GEO GSE46625.
Results In this study, we analyzed the expression of a heterologous glyphosate-tolerant EPSP synthase in E. coli JM 109. The aroA gene, 1,323 bp from P. stutzeri A1501 (accession no. ABP79994), encodes an EPSP synthase of 440 amino acid residues. Both E. coli containing pUCA1501 (aroA transformant) and the pUC18 (control) strain21 grew well on M9 minimal medium without glyphosate (Fig. 1A). In contrast to the control, the E. coli expressing A1501 EPSP synthase can grow well on M9 minimal medium supplemented with 200 mM glyphosate (Fig. 1B), which is consistent with the function of the gene.21,24 An analysis of BiOLOG GN2 substrate utilization patterns Researchers have used the BiOLOG GN method to determine the effects of non-indigenous bacterial species or transgenic plants on microbial communities in soil,25–27 plant litter,28,29 or the phyllosphere.30,31 In the studies published to date, the contribution of the heterologous EPSP synthase in E. coli to the observed pattern of carbon source oxidation is still unclear. To assess the effect of heterologous EPSP synthase on the metabolic potential of E. coli, the utilization of various carbon sources was analyzed over time using the BiOLOG GN system. E. coli without heterologous EPSP synthase was able to employ 39 different carbon sources. In the transformant, the utilization of 16 carbon sources was unchanged, 3 carbon sources were used more efficiently, and 20 carbon sources were used less efficiently (Table 1). The change in the direct amino acid utilization (L-asparagine, L-aspartic acid, glycyl-L-aspartic acid, D-serine, and L-serine) was particularly interesting because the
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Fig. 1 Growth of E. coli harboring either the pUCA1501 or the pUC18 plasmid in liquid M9 minimal medium supplemented with ampicillin (50 mg mL1) and glyphosate (A, 0 mM; B, 200 mM).
Table 1 Comparison of BiOLOG GN2 substrate utilization in the E. coli control strain and transformant
Compounda
pUC-A1501 pUC18
Dextrin L-arabinose L-fucose Maltose D-melibiose L-rhamnose Pyruvic acid methyl ester
38 734 17 26 118 19 5
9b 14 9 6 12 9 2
133 1527 266 375 214 195 230
Fold changec 21 146 36 71 28 13 4
3.50 2.08 15.65 14.42 1.81 10.26 46.00
Succinic acid mono-methyl ester 7 2 acid lactone 84 D-galacturonic acid 24 5
130 53 18.57 131 1 16.38 202 8 8.42
D-glucuronic
acid Succinic acid
62 22 2
372 1 62.00 137 21 6.23
Bromosuccinic acid
11 4 25 6 13 4
122 8 11.09 141 10 5.64 222 64 17.08
L-serine
25 6 73 31 30 13
245 11 9.80 197 37 2.70 414 43 13.80
Glycerol a-glycerol phosphate
78 28 28 5
226 37 192 18
249 34 336 21 352 36
115 6 138 7 214 6
D-galactonic
L-asparagine L-aspartic
acid
Glycyl-L-aspartic acid D-serine
D,L,
N-Acetyl-D-glucosamine a-D-glucose D-gluconic acid
E. coli, we monitored the mRNA expression profile using wholegenome microarrays to compare RNA transcript levels between the transformant and control strains. Of the 4071 predicted genes of the E. coli genome, only 19 genes showed significant (2-fold, P o 0.05) up-regulation, and 143 genes displayed significant (2-fold, P o 0.05) down-regulation, following A1501 EPSP synthase expression (ESI,† Tables S1 and S2). The differentially expressed genes were categorized by function according to the COG functional categories32 involved in various functions (Fig. 2); the annotation information was collected from the KEGG and BioCyc databases. Approximately 8 of the 19 (42%) up-regulated and 109 of the 143 (76%) down-regulated genes were annotated as unknown or hypothetical proteins. Notably, among the significant genes, approximately 45 of 162 (28%) are known. The array results suggested that the heterologous EPSP synthase did not significantly alter gene expression compared to the control strain. Therefore, at this level of investigation, the transformant could be considered to be substantially equivalent to the control strain. The shikimate pathway is a seven-step metabolic route used by bacteria, fungi, and plants for the biosynthesis of aromatic
2.90 6.86 3.38 6.73 5.93
a
Chemical compounds or growth/metabolic substrates tested in the BiOLOG GN2 plate, where there was a significant difference between the E. coli control and transformant strains. b The average signal for each BiOLOG GN2 well was calculated as the mean of the signal from the E. coli control strain or transformant strain in three independent PM array experiments. Wells in which there were few differences are not shown. c Significant changes in arbitrary units are given as the ratio of the sample versus the control (fold change).
transformant cells had an increased expression of heterologous EPSP synthase. Although the effects of the synthase in some cases might be attributed to its effect on metabolic capacity, the effects were most likely indirect in other cases. Analyzing microarray data To obtain a comprehensive understanding of the transcriptional response to heterologous EPSP synthase expression in
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Fig. 2 Number of differentially expressed genes by COGs functional categories, including all genes identified as differentially expressed from microarray experiments. The COGs functional categories are as follows: F, nucleotide transport and metabolism; P, inorganic ion transport and metabolism; K, transcription; E, amino acid transport and metabolism; C, energy production and conversion; T, signal transduction mechanisms; L, replication, recombination, and repair; G, carbohydrate transport and metabolism; M, cell envelope and outer membrane biogenesis; N, cell motility and secretion; J, translation, ribosomal structure, and biogenesis.
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amino acids (phenylalanine, tyrosine, and tryptophan).33 EPSP synthase catalyzes a step in the aromatic amino acid biosynthetic pathway; thus, assessing whether aroA expression influenced the transcript levels in the shikimate and aromatic amino acid biosynthetic pathways was important. In this study, we did not observe significantly altered gene expression levels in the shikimate and aromatic amino acid biosynthesis pathways (Table S3, ESI†). Because EPSP synthase is not the rate-limiting step in aromatic amino acid biosynthesis,34,35 increased EPSP synthase activity would not be expected to increase the transcript levels. A similar result has also been reported, as shown by the comparative proteomics of transgenic and non-transgenic soybean plant leaves.36 Heterologous EPSPS synthase may also produce an effect on biodegradative threonine dehydratase (tdc) operon expression, which is regulated by TdcA and TdcR proteins.37 The tdcABCDEFG operon encodes proteins that are involved in threonine and serine degradation. During anaerobiosis, TdcA participates in controlling the genes (tdc operon) that are involved in the transport and metabolism of threonine and serine.38,39 This operon is divergently transcribed with the tdcR gene, the product of which also activates the transcription of the operon.40 TdcA most likely interacts with TdcR to activate transcription,37 and these proteins appear to function together with CRP and IHF, which are proteins that bend DNA.39 We observed that tdcA (2.12-fold), tdcR (2.89-fold) and tdcE (3.26-fold) were repressed in the transformant; tdcB (1.58fold), tdcC (1.41-fold) and tdcD (1.41-fold) were down-regulated slightly; and tdcF (1.02-fold) and tdcG (0.97-fold) were unchanged. However, tdcE was induced by EPSP synthase expression (Table S3, ESI†). In addition, this operon is induced under anaerobiosis but is repressed by glucose.39 According to the BiOLOG assays, a-D-glucose was taken up in greater amounts by the transformant, which could explain why the tdc operon was down-regulated. In addition, D-serine ammonia-lyase (DsdA) catalyzes the deamination of D-serine to form pyruvate and ammonia. The down-regulation of dsdA (1.95-fold) by EPSP synthase has been shown to involve positive regulation by dsdC (1.90-fold) and cAMP-CRP (0.78-fold) in E. coli. D-serine has a bacteriostatic effect on E. coli; thus, when 41 D-serine is present, detoxification is necessary for cell growth. Once the cell expresses DsdA, D-serine can be used as the sole source of carbon and nitrogen.42 Toxicity from D-serine in minimal medium appears to be caused by an effect on the biosynthesis of L-serine and pantothenate.43 sfmACDHF is a putative chaperone-usher fimbrial operon in E. coli K-12 and is down-regulated by EPSP synthase. The operon is cryptic under normal laboratory conditions, but when constitutive expression is induced in a strain that lacks the type I fimbrial complex, the sfm operon promotes adhesion to eukaryotic epithelial cells (T4 bladder cells). Sfm operon expression is also regulated by the global regulators H-NS and CRP cAMP.44 We observed that sfmACDHF was down-regulated in the transformant strain whereas crp expression was unchanged. Amino acid composition The contents of 18 amino acids in the transformant strain were comparable with those of the control strain. The contents of 4 amino acids (Serine, Cysteine, Tyrosine, Lysine) were significantly
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Paper Table 2
Amino acid composition of transformant and control strains (n = 3)
Amino acid
Transformant strain (mg g1)
Serine Cysteine Tyrosine Lysine
0.049 0.047 1.812 0.123
0.004 0.004 0.131 0.021
Control strain (mg g1) 0.091 0.008 0.573 0.045
0.010 0.002 0.042 0.003
Fold changea 0.54 5.88 3.16 2.73
a
Values express the amino acid content of the transformant compared with the control strain.
different (Table 2). Serine (0.54-fold) was reduced; cysteine (5.88-fold), tyrosine (3.16-fold) and lysine (2.73-fold) were increased. A safety assessment of Roundup Readys Corn Event GA2145 reported that the serine and tyrosine contents of corn line GA21 were lower by 1.1% and higher by 3.5%, respectively, than those of the control line. However, these values (serine, lower; tyrosine, higher) are reversed in E. coli. Cysteine protease inhibitor expression levels are a potential unintended effect in Roundup Readys soybeans, which could fall within natural variation.46,47 We also found significantly consistent changes in the cysteine and tyrosine contents of E. coli expressing EPSP synthase. The differences are unlikely to be of biological significance because the levels are within the ranges established in the literature, and these significant differences were not observed in other reports. Verifying microarray data by RT-qPCR The microarray expression results were validated by reverse transcript-quantitative PCR by using a total of 31 genes encoding proteins involved in amino acid transport and metabolism, replication, recombination and repair, cell motility, energy production and conversion, nucleotide transport and metabolism, inorganic ion transport and metabolism, translation, signal transduction mechanisms, cell wall/membrane/envelope biogenesis, general function prediction only, and unknown function for microarray verification by RT-qPCR (Table S4, ESI†). Two biological replicates with three technical replicates of each treatment were produced, and the data were presented as the average of the two biological replicates. These genes were chosen from supplemental Tables S1 and S2 (ESI†) and were highly affected by aroA gene expression. The RT-qPCR results displayed similar trends of up- or downregulation to those of the microarray results, supporting the validity of the microarray data.
Discussion EPSP synthase was first reported by James Pittard and B. J. Wallace and was derived from E. coli K-12 in 1966.48 This enzyme has been extensively studied over the last four decades because it was identified as the target of glyphosate, the active ingredient of Monsanto’s broad-spectrum herbicide Roundup.49 Roundup Readys crops carry the gene coding for a glyphosate-insensitive form of this enzyme, which was obtained from Agrobacterium sp. strain CP4. Once incorporated into the plant genome, the gene product, known as CP4 EPSP synthase, confers crop resistance
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to glyphosate.5 Although widely used, the safety assessments for this heterologous EPSP synthase have been in continuous development. Current tools for assessing the food safety of GM crops include extensive multisite and multiyear agronomic evaluations, compositional analyses, animal nutrition, and classical toxicology evaluations. In the 2000s, new methodologies were developed to allow, in theory, a holistic search for alterations in GM crops at different biological levels (transcripts, proteins, and metabolites).12 These methodologies include cDNA microarrays, microRNA fingerprinting, proteome analyses, metabolome analyses, and toxicological profiling. The term ‘‘-omics’’ in relation to food and feed safety appeared for the first time in 2005.50 Over the last few years, a number of reports have been published on the study of the possible unintended effects of the introduction and expression of transgenes in plants, with the majority based upon general-omics technologies.12,50 These studies have primarily been performed with plants that are grown under optimal and controlled conditions. Nevertheless, transcriptomics plays a valuable role in the assessment of potential differences between two genotypes because of the broad coverage of the plant’s metabolic routes and networks compared with other -omics approaches.12 The aim of this report was to broaden the present state of knowledge on the transcriptional differences in an E. coli strain expressing heterologous EPSP synthase, relative to the control strain. E. coli is a well-established model microorganism that offers comprehensive resources, such as a complete genome sequence, a large collection of natural variants, a number of molecular tools, and several information platforms and databases. Importantly, as illustrated in this paper, E. coli provides a valuable model about the potential impact of heterologous genes expression. To better understand the unintended effects of heterologous EPSP synthase, we cloned an aroA gene from P. stutzeri A1501, confirmed its function in E. coli JM109 (Fig. 1) and performed a transcriptomic analysis of E. coli expressing EPSP synthase. In this study, we found that only a small set of genes (162/4071) were differentially expressed. These microarray results indicate that EPSP synthase expression has a very minor effect on E. coli. However, we could not identify any function that was predominantly altered by the expression of heterologous glyphosatetolerant EPSP synthase. In combining microarray, BiOLOG substrate utilization and amino acid composition data, we found that heterologous EPSP synthase expression did not disturb the gene expression of the shikimic acid and amino acid biosynthetic pathways. We only observed that two operons, namely tdcABCDEFG and sfmABCD, were regulated by the transcriptional dual regulator cAMP receptor protein (CRP), but CRP levels did not change significantly (0.78fold) in response to EPSP synthase expression. In addition, D-serine ammonia-lyase (DsdA) catalyzes the deamination of D-serine to form pyruvate and ammonia. The down-regulation of dsdA (1.95) by EPSP synthase has been shown to involve positive regulation by dsdC (1.90) and cAMP-CRP in E. coli. The BiOLOG assay indicated that the transformant employed lower levels of L-serine and D-serine (Table 1). The amino acid composition showed
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that the L-serine and D-serine contents of the transformant were lower than those in the control strain. The current study clearly demonstrated that EPSP synthase expression triggered the transcriptional responses of a small set of gene that are related to amino acid transport and metabolism, especially serine. This study also highlights the possibilities and challenges of profiling analyses for environmental safety evaluation. Although DNA transfer from plants to microorganisms has occurred throughout evolution, the transfer of aroA gene from plants to microbes or other living species in nature is extremely unlikely and, in terms of plant pests or the environment, is of no significant consequence.
Conclusion To the best of our knowledge, this study is the first work that attempts to link ‘‘substantial equivalence’’ with transcriptomics in E. coli that express heterologous EPSP synthase, and the database we reported provides efficient methods to assist researchers and regulators in assessing the frequency and magnitude of changes in microbes and to develop an understanding of the biological significance of these changes. These technologies must still be validated before they can be used on a case-by-case basis to confirm or supplement the current targeted analytical approaches. They are not intended to replace existing analyses, but they may trigger the need for a more detailed and targeted analysis of specific groups of genes, proteins, and metabolites. This study opens new possibilities for investigations concerning all aspects of plants, and a transcriptomic study should be performed to evaluate the changes found in terms of heterologous gene expression.
Acknowledgements We thank Dr Qingyu Wu at Cold Spring Harbor Laboratory for valuable feedback on the manuscript. This work was supported by the National Basic Research (973) Program of China (No. 2013CB733903); the National High Technology Research and Development (863) Program of China (2012AA021703, 2012AA02A703); the National Major Special Project for the Development of Transgenic Organisms (2014ZX08012-001, 2014ZX08012-003) and the National Natural Science Foundation of China (No. 31170081).
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5 T. Funke, H. Han, M. L. Healy-Fried, M. Fischer and E. Schonbrunn, Proc. Natl. Acad. Sci. U. S. A., 2006, 103, 13010–13015. 6 C. James, ISAAA Report on Global Status of Biotech/G Crops, 41: 10–12, 2014, http://www.isaaa.org. 7 L. Li, X. Zhang, Y. Wan and W. Jin, BioMed Res. Int., 2013, 134675. 8 OECD, An Introduction to the Food/Feed Safety Consensus Documents of the Task Force Series on the Safety of Novel Foods and Feeds, 2006, 14, 7–9. 9 OECD, Safety Evaluation of Foods Derived by Modern Biotechnology: Concept and Principles, 1993. 10 FAO/WHO, Rome: Food and Agriculture Organization of the United Nations, 2000a. 11 FAO/WHO, Rome: Food and Agriculture Organization of the United Nations, 2000b. 12 A. E. Ricroch, J. B. Berge and M. Kuntz, Plant Physiol., 2011, 155, 1752–1761. 13 A. Coll, A. Nadal, R. Collado, G. Capellades, J. Messeguer, ´, R. Palaudelma `s and M. Pla, Transgenic Res., 2009, E. Mele 18, 801–808. 14 K. C. Cheng, J. Beaulieu, E. Iquira, F. J. Belzile, M. G. Fortin ¨mvik, J. Agric. Food Chem., 2008, 56, 3057–3067. and M. V. Stro 15 E. Barros, S. Lezar, M. J. Anttonen, J. P. van Dijk, R. M. Rohlig, E. J. Kok and K. H. Engel, Plant Biotechnol. J., 2010, 8, 436–451. 16 J. G. Lawrence and H. Ochman, Proc. Natl. Acad. Sci. U. S. A., 1998, 95, 9413–9417. 17 U. Dobrindt, F. Agerer, K. Michaelis, A. Janka, C. Buchrieser, M. Samuelson, C. Svanborg, G. Gottschalk, H. Karch and J. Hacker, J. Bacteriol., 2003, 185, 1831–1840. 18 C. Pal, B. Papp and M. J. Lercher, Nat. Genet., 2005, 37, 1372–1375. 19 J. L. Hobman, C. W. Penn and M. J. Pallen, Mol. Microbiol., 2007, 64, 881–885. 20 W. Lu, L. Li, M. Chen, Z. Zhou, W. Zhang, S. Ping, Y. Yan, J. Wang and M. Lin, Mol. BioSyst., 2013, 9, 522–530. 21 L. Li, W. Lu, Y. Han, S. Ping, W. Zhang, M. Chen, Z. Zhao, Y. Yan, Y. Jiang and M. Lin, J. Biotechnol., 2009, 144, 330–336. 22 J. L. Garland and A. L. Mills, Appl. Environ. Microbiol., 1991, 57, 2351–2359. 23 K. J. Livak and T. D. Schmittgen, Methods, 2001, 25, 402–408. 24 A. Liang, J. Sha, W. Lu, M. Chen, L. Li, D. Jin, Y. Yan, J. Wang, S. Ping, W. Zhang, Y. Wang and M. Lin, Biotechnol. Lett., 2008, 30, 1397–1401. 25 P. M. Dewick, Nat. Prod. Rep., 1995, 12, 579–607. 26 L. S. England, H. Lee and J. T. Trevors, Mol. Ecol., 1995, 4, 221–230.
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A transcriptomic analysis for identifying the unintended effects of introducing a heterologous glyphosate-tolerant EPSP synthase into Escherichia coli† Liang Li,‡ab Zhengfu Zhou,‡a Wujun Jin,ab Yusong Wan*ab and Wei Lu*a Glyphosate is one of the most commonly used broad-spectrum herbicides with little to no hazard to animals, human beings, or the environment. Some microbial 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase variants are not inhibited by glyphosate, and they provide a powerful tool to engineer glyphosatetolerant plants. However, the unintended effects of EPSP synthase expression patterns on microbes are not yet clear. Here, we use an Affymetrix GeneChip analysis to study how introduction of a heterologous glyphosate-tolerant EPSP synthase into a model microorganism Escherichia coli (E. coli) affects the global gene expression profile. The profile showed that 161 of 4071 genes were differentially expressed after the introduction of the synthase: 19 (0.47%) were up-regulated and 143 (3.49%) were down-regulated.
Received 24th September 2014, Accepted 17th December 2014
The microarray results, in combination with BiOLOG substrate utilization and amino acid composition
DOI: 10.1039/c4mb00566j
a small number of genes and metabolites were affected by EPSP synthase expression, no functional
assays, suggested that heterologous EPSP synthase expression had very minor effects on E. coli. Although correlations were identified among the dataset. This study may shed light on the effect of EPSP synthase
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expression on microbes, which should help in the assessment of environmental safety.
Introduction Glyphosate is one of the most commonly used broad-spectrum herbicides and demonstrates little to no hazard to animals, human beings, or the environment.1 It inhibits the enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase (EC 2.5.1.19), which is the sixth enzyme of the shikimate pathway.2 This enzyme is essential for the biosynthesis of aromatic amino acids and other aromatic compounds in plants and microorganisms, including apicomplexan parasites.3,4 The EPSP synthase variants derived from some microbes, such as Agrobacterium tumefaciens sp. CP4 and Pseudomonas stutzeri A1501, are not inhibited by glyphosate and are used to engineer glyphosate-tolerant genetically modified (GM) crops.5 Glyphosate-tolerant crops marketed as Roundup Readys occupy the greatest acreage. In 2013, globally, herbicide tolerance was deployed in soybeans, maize, canola, cotton, sugar, beets, and alfalfa, which occupied 99.4 million a
Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China b Inspection and Testing Center for Environmental Risk Assessment of Genetic Modified Plant-related Microorganism (Beijing), Ministry of Agriculture, Beijing 100081, China † Electronic supplementary information (ESI) available. See DOI: 10.1039/ c4mb00566j ‡ These authors contributed equally to this work.
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hectares or 57% of the 175.3 million hectares of biotech crops planted.6 In the safety assessment, GM crop-derived foods and feeds are compared with their counterparts from parental or near-isogenic lines to identify differences, which are subsequently evaluated with respect to their safety to the environment, humans and animals. Because of the rapid increase in the number of biotech crops used for food production, consumers are becoming increasingly concerned about the risks posed by GM crops and their derivatives.7 A major principle and guiding tool for the food safety assessment of GM crops is the concept of ‘‘substantial equivalence’’ according to the principles outlined in the Organization for Economic Cooperation and Development (OECD) consensus documents8 and further elaborated by the Food and Agriculture Organization (FAO) of the United Nations/World Health Organization. The current safety assessment procedures developed for GM crops are primarily based on a targeted compositional analysis of specific safety and nutrition-related compounds.9–11 Additionally, the subject to be addressed is as follows: the transfer of DNA from plants to microorganisms may occur because the heterologous gene in a glyphosate-tolerant plant is derived from microbes, and assessing the unintended effects caused by horizontal gene transfer is necessary. Targeted analysis may, however, have its limitations in detecting unintended effects on GM organisms. Therefore,
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non-targeted/fingerprinting technologies that are unbiased analytical approaches for detecting the potential occurrence of unintended effects have been developed.12 Profiling technologies such as transcriptomics, proteomics and metabolomics have been suggested to broaden the spectrum of detectable compounds and thus supplement the current targeted analytical approaches. These methodologies are widely used to investigate the unintended effects on GM crops compared with those on traditionally bred in recent years.13,14 In a recently published paper,15 three profiling technologies were used to compare two transgenic maize lines (one GM Bt variety and one GM glyphosatetolerant variety) with the respective control line. Although the sources of variation in the dataset were the same for all the techniques used (the environment being the dominant one), no functional correlations were identified between the genes, proteins and metabolites driving this variation. E. coli has been a model organism in the field of basic biomolecular sciences for ‘‘-omics’’ studies because it is a variable species with a highly dynamic genome.16,17 The metabolic networks in E. coli are known to evolve in response to changing environments by acquiring heterologous genes and operons by horizontal gene transfer.18 E. coli studies have played a pioneering role in our understanding of DNA replication, transcription, translation, gene regulation, restriction enzymes and horizontal gene transfer.19 Furthermore, E. coli is a model that is extensively used to study the molecular mechanisms underlying bacterial metabolic networks. We previously reported the first global analysis of the glyphosate shock response in E. coli by transcriptomics and indicated that the presence of glyphosate during growth induces metabolic starvation, energy drain and other off-target effects.20 These results demonstrate that, in addition to the genes encoding the enzymes of the shikimate pathway, glyphosate triggers transcriptional responses in the genes that are associated with non-shikimate pathways such as cell motility, energy production, and carbohydrate metabolism. Moreover, we identified an array of previously uncharacterized glyphosate-responsive genes, which may act as potential targets for non-toxic herbicides and anti-microbial compounds. In the current study, we performed DNA microarray experiments and used data from metabolite measurements and free amino acid composition to investigate the unintended effects of heterologous glyphosate-tolerant EPSP synthase expression in the E. coli host. It is hoped that the dataset presented serves as an exploratory study into the use of transcriptomics for assessment of unintended effects on microbes.
Materials and methods Bacterial strains, plasmids, and growth conditions E. coli JM109 [genotype: endA1, recA1, gyrA96, thi, hsdR17 (rk, mk+), relA1, supE44, D(lac-proAB), [F 0 , traD36, proAB, laqIqZDM15]] (Promega, Madison, WI, USA) harboring pUCA1501 (transformant strain) and the control plasmid pUC18 (control strain)21 were used in this study. Cells were grown aerobically in Luria-Bertani (LB) broth at 37 1C. Ampicillin
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Molecular BioSystems
(50 mg mL1) was added to the culture medium as appropriate. Overnight LB cultures were inoculated and sub-cultured to a starting OD600 of 0.001. The cultures were harvested at an OD600 of 0.400. For the functional validation of A1501 EPSP synthase, cells containing pUC-A1501 and pUC18 were incubated in M9 minimal medium supplemented with 0 mM and 200 mM glyphosate at 37 1C. The growth was monitored as the OD600 value. Compared with the control strain, the positive colonies with a higher tolerance to glyphosate were subjected to an additional assay to confirm the initial results. BiOLOG GN2 substrate utilization patterns To assess the effect of heterologous EPSP synthase on the metabolic potential of E. coli, the utilization of various carbon sources was determined in triplicate by using a BiOLOG GN2 microplate, which detects the utilization of 95 specific carbon sources, as recommended by the manufacturer.22 The plates were checked at regular times after 24 h of incubation for color development by using the BiOLOG microplate reader. The measured extinction values were automatically corrected by incorporating the extinction value of the substrate-free reference well (E0) according to the BiOLOG instruction manual (BiOLOG, Hayward, CA). The cell densities were determined by measuring turbidity using BiOLOG turbidity standards. Standardized microplates allow the simultaneous testing of 95 diagnostically significant carbon sources; one reference well contains no carbon substrate. In addition to the carbon sources, all 96 wells in the tray contained the necessary nutrients for growth in addition to the redox dye in a dry state. The dried preparations in the individual wells were rehydrated by inoculating with the cell suspension. After inoculation (150 mL per well) with an 8-channel repeating pipette, the microplates were incubated at 30 1C for 24 and 48 h. Formazan formation was evaluated using an automatic EL 340 microplate reader (Biotek Instruments, Inc., USA). The identification of the test strains according to their metabolic pattern was performed by using Biolog MicroLog software, which comprised the MicroLog 2-Manual System and the GN database (for Gram-negative bacteria). Microarray sample preparation, data collection and analysis The transformant and control strains were grown and harvested as previously described. The E. coli cells were transferred to M9 minimal medium for 1 h and then pelleted until the OD600 reached 0.4. Total RNA was extracted by the TRIzol (Invitrogen) technique. The RNA was finally resuspended in RNase-free water and quantitated using a Bioanalyzer 2100 (Agilent). The cDNA synthesis and fragmentation and the labeling, washing and scanning of E. coli GeneChip arrays were performed according to the manufacturer’s instructions (Affymetrix, Inc.). Each sample was analyzed using three biological replicates. For RNA manipulation, the cell broth was centrifuged at 10 000 g, and the pellet was quickly frozen in liquid nitrogen and stored at 70 1C. RNA was extracted from thawed cells by the TRIzol (Invitrogen) technique and then purified with an RNeasy Mini Kit (QIAGEN) and DNase I. The RNA was finally resuspended in
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RNase-free water and quantitated using Bioanalyzer 2100 (Agilent). Samples containing ten micrograms of RNA were reverse-transcribed and hybridized to the GeneChip E. coli Genome 2.1 Array by following the manufacturer’s instruction (Affymetrix). To perform this additional DNase digestion, the RNA was precipitated and redissolved in 85 ml of nuclease-free water. We then added 10 mL of 10 DNase I buffer and 5 mL of (1 U mL1) DNase I (Ambion). The DNase reaction mixture was incubated at 37 1C for 30 min and then chilled on ice. A second RNeasy column purification was performed. Chips were analyzed using a GeneArray scanner, GeneChip Fluidics Station 400, and GeneChip Hybridization Oven 640, which were all purchased from Affymetrix. The data were processed by using Microarray Suite version 5.0 (MAS5). The p values were calculated by applying Wilcoxon’s signed rank test and then used to generate the complex calls. Determination of free amino acids In brief, E. coli JM109 containing the pUC-A1501 or pUC18 plasmid was grown overnight at 37 1C in 20 mL of LB broth containing 50 mg mL1 of ampicillin. The cells were collected and transferred into M9 minimal medium. Cell growth was monitored by measuring absorbance at 600 nm (OD600) using a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA). The cells were obtained by centrifugation, washed with ddH2O, and redissolved in 0.5 mL of ddH2O. To analyze the free amino acids, 0.5 mL of the sample was mixed with 0.5 mL of 8% sulfosalicylic acid and centrifuged at 10 000 g for 5 min. The supernatant was then filtered, and an aliquot of 0.5 mL was dried by using an EYELA concentrator (TVE-1000, Tokyo Rikakikai Co., Ltd, Tokyo, Japan). The appropriately diluted supernatant was analyzed using a Sykam S433 amino-acid analyzer (Sykam GmbH, Eresing, Germany). Data verification by RT-qPCR To verify the microarray analysis results, a total of 31 gene encoding proteins in key pathways and differentially expressed proteins were selected to verify the microarray results by reverse transcriptase-qPCR (RT-qPCR). Total RNA was isolated using an SV Total RNA Isolation System (Promega, Madison, WI, USA) and treated with RNase-free DNase I (Promega). The integrity of the RNA was analyzed by agarose gel electrophoresis. First-strand cDNA was synthesized from 1 mg of total RNA in a 20 mL reaction volume using a Protoscript First-Strand cDNA Synthesis Kit (New England Biolabs, Ipswich, MA, USA). For qPCR experiments, the primer pairs shown in Table S4 (ESI†) were designed on the basis of the published reference genome sequence of E. coli str K12 by using Primer Premier 5.0. The amplicons (75 to 250 bp) and reaction specificity were confirmed by agarose gel electrophoresis and product dissociation curves. The qPCR reactions contained 2 mL of cDNA, 10 mL of 2 SYBR Premix Ex Taq (Takara, Dalian, China), 0.4 mL of each primer (20 mM stock), 0.4 mL of 50 Reference Dye II and 6.8 mL of RNase-free water. The amplifications were conducted on an ABI PRISM 7500 Real Time PCR System (Applied Biosystems, Foster City, CA, USA) under the following conditions: 10 min at
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95 1C, followed by 40 cycles of 15 s at 95 1C, 30 s at 60 1C, and 30 s at 72 1C, followed by a melting-curve program (55 1C to 99 1C, with a 5 s hold at each temperature). The qPCR data were analyzed by using the ABI PRISM 7500 Sequence Detection System software (Applied Biosystems). All cDNA samples were run in triplicate. The expression of l6S rRNA (forward primer 5 0 -ATT ACC GCG GCT GCT GG-3 0 ; reverse primer 5 0 -GTC CCG CCC TAC TCA TCG A-3 0 ) was used as an internal control. The RT-qPCR data were analyzed by a relative quantification 2-DDCT method.23 The difference in the cycle numbers at which the amplified gene amount reaches the threshold, or DDCT, was used to determine the differential gene expression. First, the DCT was calculated as the difference between the tested genes and the reference actin gene to normalize the template quantities across treatments. The DDCT was then obtained by comparing the difference in the DCTs of two treatments. The arithmetic fold change was calculated as the 2-DDCT and reported as the log 2-fold change (-DDCT). Microarray data accession number All microarray data (including GenBank accession numbers for sequenced genes) were deposited in the NCBI Gene Expression Omnibus at http://www.ncbi.nlm.nih.gov/geo under accession number GEO GSE46625.
Results In this study, we analyzed the expression of a heterologous glyphosate-tolerant EPSP synthase in E. coli JM 109. The aroA gene, 1,323 bp from P. stutzeri A1501 (accession no. ABP79994), encodes an EPSP synthase of 440 amino acid residues. Both E. coli containing pUCA1501 (aroA transformant) and the pUC18 (control) strain21 grew well on M9 minimal medium without glyphosate (Fig. 1A). In contrast to the control, the E. coli expressing A1501 EPSP synthase can grow well on M9 minimal medium supplemented with 200 mM glyphosate (Fig. 1B), which is consistent with the function of the gene.21,24 An analysis of BiOLOG GN2 substrate utilization patterns Researchers have used the BiOLOG GN method to determine the effects of non-indigenous bacterial species or transgenic plants on microbial communities in soil,25–27 plant litter,28,29 or the phyllosphere.30,31 In the studies published to date, the contribution of the heterologous EPSP synthase in E. coli to the observed pattern of carbon source oxidation is still unclear. To assess the effect of heterologous EPSP synthase on the metabolic potential of E. coli, the utilization of various carbon sources was analyzed over time using the BiOLOG GN system. E. coli without heterologous EPSP synthase was able to employ 39 different carbon sources. In the transformant, the utilization of 16 carbon sources was unchanged, 3 carbon sources were used more efficiently, and 20 carbon sources were used less efficiently (Table 1). The change in the direct amino acid utilization (L-asparagine, L-aspartic acid, glycyl-L-aspartic acid, D-serine, and L-serine) was particularly interesting because the
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Fig. 1 Growth of E. coli harboring either the pUCA1501 or the pUC18 plasmid in liquid M9 minimal medium supplemented with ampicillin (50 mg mL1) and glyphosate (A, 0 mM; B, 200 mM).
Table 1 Comparison of BiOLOG GN2 substrate utilization in the E. coli control strain and transformant
Compounda
pUC-A1501 pUC18
Dextrin L-arabinose L-fucose Maltose D-melibiose L-rhamnose Pyruvic acid methyl ester
38 734 17 26 118 19 5
9b 14 9 6 12 9 2
133 1527 266 375 214 195 230
Fold changec 21 146 36 71 28 13 4
3.50 2.08 15.65 14.42 1.81 10.26 46.00
Succinic acid mono-methyl ester 7 2 acid lactone 84 D-galacturonic acid 24 5
130 53 18.57 131 1 16.38 202 8 8.42
D-glucuronic
acid Succinic acid
62 22 2
372 1 62.00 137 21 6.23
Bromosuccinic acid
11 4 25 6 13 4
122 8 11.09 141 10 5.64 222 64 17.08
L-serine
25 6 73 31 30 13
245 11 9.80 197 37 2.70 414 43 13.80
Glycerol a-glycerol phosphate
78 28 28 5
226 37 192 18
249 34 336 21 352 36
115 6 138 7 214 6
D-galactonic
L-asparagine L-aspartic
acid
Glycyl-L-aspartic acid D-serine
D,L,
N-Acetyl-D-glucosamine a-D-glucose D-gluconic acid
E. coli, we monitored the mRNA expression profile using wholegenome microarrays to compare RNA transcript levels between the transformant and control strains. Of the 4071 predicted genes of the E. coli genome, only 19 genes showed significant (2-fold, P o 0.05) up-regulation, and 143 genes displayed significant (2-fold, P o 0.05) down-regulation, following A1501 EPSP synthase expression (ESI,† Tables S1 and S2). The differentially expressed genes were categorized by function according to the COG functional categories32 involved in various functions (Fig. 2); the annotation information was collected from the KEGG and BioCyc databases. Approximately 8 of the 19 (42%) up-regulated and 109 of the 143 (76%) down-regulated genes were annotated as unknown or hypothetical proteins. Notably, among the significant genes, approximately 45 of 162 (28%) are known. The array results suggested that the heterologous EPSP synthase did not significantly alter gene expression compared to the control strain. Therefore, at this level of investigation, the transformant could be considered to be substantially equivalent to the control strain. The shikimate pathway is a seven-step metabolic route used by bacteria, fungi, and plants for the biosynthesis of aromatic
2.90 6.86 3.38 6.73 5.93
a
Chemical compounds or growth/metabolic substrates tested in the BiOLOG GN2 plate, where there was a significant difference between the E. coli control and transformant strains. b The average signal for each BiOLOG GN2 well was calculated as the mean of the signal from the E. coli control strain or transformant strain in three independent PM array experiments. Wells in which there were few differences are not shown. c Significant changes in arbitrary units are given as the ratio of the sample versus the control (fold change).
transformant cells had an increased expression of heterologous EPSP synthase. Although the effects of the synthase in some cases might be attributed to its effect on metabolic capacity, the effects were most likely indirect in other cases. Analyzing microarray data To obtain a comprehensive understanding of the transcriptional response to heterologous EPSP synthase expression in
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Fig. 2 Number of differentially expressed genes by COGs functional categories, including all genes identified as differentially expressed from microarray experiments. The COGs functional categories are as follows: F, nucleotide transport and metabolism; P, inorganic ion transport and metabolism; K, transcription; E, amino acid transport and metabolism; C, energy production and conversion; T, signal transduction mechanisms; L, replication, recombination, and repair; G, carbohydrate transport and metabolism; M, cell envelope and outer membrane biogenesis; N, cell motility and secretion; J, translation, ribosomal structure, and biogenesis.
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amino acids (phenylalanine, tyrosine, and tryptophan).33 EPSP synthase catalyzes a step in the aromatic amino acid biosynthetic pathway; thus, assessing whether aroA expression influenced the transcript levels in the shikimate and aromatic amino acid biosynthetic pathways was important. In this study, we did not observe significantly altered gene expression levels in the shikimate and aromatic amino acid biosynthesis pathways (Table S3, ESI†). Because EPSP synthase is not the rate-limiting step in aromatic amino acid biosynthesis,34,35 increased EPSP synthase activity would not be expected to increase the transcript levels. A similar result has also been reported, as shown by the comparative proteomics of transgenic and non-transgenic soybean plant leaves.36 Heterologous EPSPS synthase may also produce an effect on biodegradative threonine dehydratase (tdc) operon expression, which is regulated by TdcA and TdcR proteins.37 The tdcABCDEFG operon encodes proteins that are involved in threonine and serine degradation. During anaerobiosis, TdcA participates in controlling the genes (tdc operon) that are involved in the transport and metabolism of threonine and serine.38,39 This operon is divergently transcribed with the tdcR gene, the product of which also activates the transcription of the operon.40 TdcA most likely interacts with TdcR to activate transcription,37 and these proteins appear to function together with CRP and IHF, which are proteins that bend DNA.39 We observed that tdcA (2.12-fold), tdcR (2.89-fold) and tdcE (3.26-fold) were repressed in the transformant; tdcB (1.58fold), tdcC (1.41-fold) and tdcD (1.41-fold) were down-regulated slightly; and tdcF (1.02-fold) and tdcG (0.97-fold) were unchanged. However, tdcE was induced by EPSP synthase expression (Table S3, ESI†). In addition, this operon is induced under anaerobiosis but is repressed by glucose.39 According to the BiOLOG assays, a-D-glucose was taken up in greater amounts by the transformant, which could explain why the tdc operon was down-regulated. In addition, D-serine ammonia-lyase (DsdA) catalyzes the deamination of D-serine to form pyruvate and ammonia. The down-regulation of dsdA (1.95-fold) by EPSP synthase has been shown to involve positive regulation by dsdC (1.90-fold) and cAMP-CRP (0.78-fold) in E. coli. D-serine has a bacteriostatic effect on E. coli; thus, when 41 D-serine is present, detoxification is necessary for cell growth. Once the cell expresses DsdA, D-serine can be used as the sole source of carbon and nitrogen.42 Toxicity from D-serine in minimal medium appears to be caused by an effect on the biosynthesis of L-serine and pantothenate.43 sfmACDHF is a putative chaperone-usher fimbrial operon in E. coli K-12 and is down-regulated by EPSP synthase. The operon is cryptic under normal laboratory conditions, but when constitutive expression is induced in a strain that lacks the type I fimbrial complex, the sfm operon promotes adhesion to eukaryotic epithelial cells (T4 bladder cells). Sfm operon expression is also regulated by the global regulators H-NS and CRP cAMP.44 We observed that sfmACDHF was down-regulated in the transformant strain whereas crp expression was unchanged. Amino acid composition The contents of 18 amino acids in the transformant strain were comparable with those of the control strain. The contents of 4 amino acids (Serine, Cysteine, Tyrosine, Lysine) were significantly
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Paper Table 2
Amino acid composition of transformant and control strains (n = 3)
Amino acid
Transformant strain (mg g1)
Serine Cysteine Tyrosine Lysine
0.049 0.047 1.812 0.123
0.004 0.004 0.131 0.021
Control strain (mg g1) 0.091 0.008 0.573 0.045
0.010 0.002 0.042 0.003
Fold changea 0.54 5.88 3.16 2.73
a
Values express the amino acid content of the transformant compared with the control strain.
different (Table 2). Serine (0.54-fold) was reduced; cysteine (5.88-fold), tyrosine (3.16-fold) and lysine (2.73-fold) were increased. A safety assessment of Roundup Readys Corn Event GA2145 reported that the serine and tyrosine contents of corn line GA21 were lower by 1.1% and higher by 3.5%, respectively, than those of the control line. However, these values (serine, lower; tyrosine, higher) are reversed in E. coli. Cysteine protease inhibitor expression levels are a potential unintended effect in Roundup Readys soybeans, which could fall within natural variation.46,47 We also found significantly consistent changes in the cysteine and tyrosine contents of E. coli expressing EPSP synthase. The differences are unlikely to be of biological significance because the levels are within the ranges established in the literature, and these significant differences were not observed in other reports. Verifying microarray data by RT-qPCR The microarray expression results were validated by reverse transcript-quantitative PCR by using a total of 31 genes encoding proteins involved in amino acid transport and metabolism, replication, recombination and repair, cell motility, energy production and conversion, nucleotide transport and metabolism, inorganic ion transport and metabolism, translation, signal transduction mechanisms, cell wall/membrane/envelope biogenesis, general function prediction only, and unknown function for microarray verification by RT-qPCR (Table S4, ESI†). Two biological replicates with three technical replicates of each treatment were produced, and the data were presented as the average of the two biological replicates. These genes were chosen from supplemental Tables S1 and S2 (ESI†) and were highly affected by aroA gene expression. The RT-qPCR results displayed similar trends of up- or downregulation to those of the microarray results, supporting the validity of the microarray data.
Discussion EPSP synthase was first reported by James Pittard and B. J. Wallace and was derived from E. coli K-12 in 1966.48 This enzyme has been extensively studied over the last four decades because it was identified as the target of glyphosate, the active ingredient of Monsanto’s broad-spectrum herbicide Roundup.49 Roundup Readys crops carry the gene coding for a glyphosate-insensitive form of this enzyme, which was obtained from Agrobacterium sp. strain CP4. Once incorporated into the plant genome, the gene product, known as CP4 EPSP synthase, confers crop resistance
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to glyphosate.5 Although widely used, the safety assessments for this heterologous EPSP synthase have been in continuous development. Current tools for assessing the food safety of GM crops include extensive multisite and multiyear agronomic evaluations, compositional analyses, animal nutrition, and classical toxicology evaluations. In the 2000s, new methodologies were developed to allow, in theory, a holistic search for alterations in GM crops at different biological levels (transcripts, proteins, and metabolites).12 These methodologies include cDNA microarrays, microRNA fingerprinting, proteome analyses, metabolome analyses, and toxicological profiling. The term ‘‘-omics’’ in relation to food and feed safety appeared for the first time in 2005.50 Over the last few years, a number of reports have been published on the study of the possible unintended effects of the introduction and expression of transgenes in plants, with the majority based upon general-omics technologies.12,50 These studies have primarily been performed with plants that are grown under optimal and controlled conditions. Nevertheless, transcriptomics plays a valuable role in the assessment of potential differences between two genotypes because of the broad coverage of the plant’s metabolic routes and networks compared with other -omics approaches.12 The aim of this report was to broaden the present state of knowledge on the transcriptional differences in an E. coli strain expressing heterologous EPSP synthase, relative to the control strain. E. coli is a well-established model microorganism that offers comprehensive resources, such as a complete genome sequence, a large collection of natural variants, a number of molecular tools, and several information platforms and databases. Importantly, as illustrated in this paper, E. coli provides a valuable model about the potential impact of heterologous genes expression. To better understand the unintended effects of heterologous EPSP synthase, we cloned an aroA gene from P. stutzeri A1501, confirmed its function in E. coli JM109 (Fig. 1) and performed a transcriptomic analysis of E. coli expressing EPSP synthase. In this study, we found that only a small set of genes (162/4071) were differentially expressed. These microarray results indicate that EPSP synthase expression has a very minor effect on E. coli. However, we could not identify any function that was predominantly altered by the expression of heterologous glyphosatetolerant EPSP synthase. In combining microarray, BiOLOG substrate utilization and amino acid composition data, we found that heterologous EPSP synthase expression did not disturb the gene expression of the shikimic acid and amino acid biosynthetic pathways. We only observed that two operons, namely tdcABCDEFG and sfmABCD, were regulated by the transcriptional dual regulator cAMP receptor protein (CRP), but CRP levels did not change significantly (0.78fold) in response to EPSP synthase expression. In addition, D-serine ammonia-lyase (DsdA) catalyzes the deamination of D-serine to form pyruvate and ammonia. The down-regulation of dsdA (1.95) by EPSP synthase has been shown to involve positive regulation by dsdC (1.90) and cAMP-CRP in E. coli. The BiOLOG assay indicated that the transformant employed lower levels of L-serine and D-serine (Table 1). The amino acid composition showed
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that the L-serine and D-serine contents of the transformant were lower than those in the control strain. The current study clearly demonstrated that EPSP synthase expression triggered the transcriptional responses of a small set of gene that are related to amino acid transport and metabolism, especially serine. This study also highlights the possibilities and challenges of profiling analyses for environmental safety evaluation. Although DNA transfer from plants to microorganisms has occurred throughout evolution, the transfer of aroA gene from plants to microbes or other living species in nature is extremely unlikely and, in terms of plant pests or the environment, is of no significant consequence.
Conclusion To the best of our knowledge, this study is the first work that attempts to link ‘‘substantial equivalence’’ with transcriptomics in E. coli that express heterologous EPSP synthase, and the database we reported provides efficient methods to assist researchers and regulators in assessing the frequency and magnitude of changes in microbes and to develop an understanding of the biological significance of these changes. These technologies must still be validated before they can be used on a case-by-case basis to confirm or supplement the current targeted analytical approaches. They are not intended to replace existing analyses, but they may trigger the need for a more detailed and targeted analysis of specific groups of genes, proteins, and metabolites. This study opens new possibilities for investigations concerning all aspects of plants, and a transcriptomic study should be performed to evaluate the changes found in terms of heterologous gene expression.
Acknowledgements We thank Dr Qingyu Wu at Cold Spring Harbor Laboratory for valuable feedback on the manuscript. This work was supported by the National Basic Research (973) Program of China (No. 2013CB733903); the National High Technology Research and Development (863) Program of China (2012AA021703, 2012AA02A703); the National Major Special Project for the Development of Transgenic Organisms (2014ZX08012-001, 2014ZX08012-003) and the National Natural Science Foundation of China (No. 31170081).
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