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Comprehensive Assessment of TranscriptionalRegulation Facilitates Metabolic Engineering of IsoprenoidAccumulation in Arabidopsis1[OPEN]

Iris Lange, Brenton C. Poirier, Blake K. Herron, and Bernd Markus Lange*

Institute of Biological Chemistry and M.J. Murdock Metabolomics Laboratory, Washington State University,Pullman, Washington 99164–6340

ORCID IDs: 0000-0002-1677-6757 (B.C.P.); 0000-0001-6583-9112 (B.K.H.).

In plants, two spatially separated pathways provide the precursors for isoprenoid biosynthesis. We generated transgenicArabidopsis (Arabidopsis thaliana) lines with modulated levels of expression of each individual gene involved in the cytosolic/peroxisomal mevalonate and plastidial methylerythritol phosphate pathways. By assessing the correlation of transgeneexpression levels with isoprenoid marker metabolites (gene-to-metabolite correlation), we determined the relative importanceof transcriptional control at each individual step of isoprenoid precursor biosynthesis. The accumulation patterns of metabolicintermediates (metabolite-to-gene correlation) were then used to infer flux bottlenecks in the sterol pathway. The extent ofmetabolic cross talk, the exchange of isoprenoid intermediates between compartmentalized pathways, was assessed by acombination of gene-to-metabolite and metabolite-to-metabolite correlation analyses. This strategy allowed the selection ofgenes to be modulated by metabolic engineering, and we demonstrate that the overexpression of predictable combinations ofgenes can be used to significantly enhance flux toward specific end products of the sterol pathway. Transgenic plantsaccumulating increased amounts of sterols are characterized by significantly elevated biomass, which can be a desirable traitin crop and biofuel plants.

Isoprenoids are ubiquitous metabolites with diversebiological functions in plants as membrane compo-nents (sterols), photosynthetic pigments (carotenoidsand chlorophylls), side chains of quinones involved inelectron transport systems, phytohormones (GAs,brassinosteroids, abscisic acid, and cytokinins), andantioxidants (carotenoids and tocopherols; Bouvieret al., 2005). There are also numerous commercial usesfor isoprenoids in the flavor and fragrance industry(e.g. essential oils and resins), as nutritional supplements(e.g. vitamins A, D, E, and K), and as pharmaceutical

drugs (e.g. the anticancer diterpene taxol or the anti-malarial sesquiterpene artemisinin; Holstein and Hohl,2004). Across all kingdoms of life, isoprenoids are de-rived from two universal five-carbon building blocks,isopentenyl diphosphate (IPP) and dimethylallyl di-phosphate (DMAPP). In most plant cells, the mevalo-nate (MVA) pathway, which is localized to the cytosol,endoplasmic reticulum, and peroxisomes, is the pre-dominant source of IPP and DMAPP for the synthesisof sterols (C30), whereas the plastidial methylerythritol4-phosphate (MEP) pathway provides the bulk ofIPP and DMAPP for the synthesis of carotenoids (C40)and the C20 isoprenoid side chain of chlorophylls(Hemmerlin et al., 2012; Fig. 1). The exchange of com-mon intermediates of isoprenoid biosynthesis be-tween different compartments has been inferred fromfeeding experiments with labeled precursors, but theextent of this metabolic cross talk varies significantlybetween different experimental systems and is stillpoorly understood at a mechanistic level (Rodríguez-Concepción, 2006; Hemmerlin et al., 2012).

To evaluate isoprenoid pathway regulation and op-portunities for metabolic engineering, several groupshave generated transgenic plant lines in which the ex-pression levels of individual genes involved in theMVA and MEP pathways are modulated. The focus ofthese studies has been on genes that encode enzymesassumed to catalyze rate-limiting reactions. In animals,where the MEP pathway does not operate, the en-zyme HMGR plays an important role in controlling

1 This work was supported by the National Science Foundation(grant no. NSF–MCB–0920758 to B.M.L.).

* Address correspondence to [email protected] author responsible for distribution of materials integral to the

findings presented in this article in accordance with the policy de-scribed in the Instructions for Authors (www.plantphysiol.org) is:Bernd Markus Lange ([email protected]).

I.L. and B.M.L. designed the experiments; I.L. cloned genes, per-formed transformations, selected for homozygous lines, grew andharvested plants, and performed real-time quantitative PCR analyses;B.K.H. performed real-time quantitative PCR and metabolite profil-ing analyses, and was involved in tissue harvests; B.C.P. generatedtransgenic lines overexpressing 3-hydroxy-3-methylglutaryl-CoAreductase/sterol methyl oxidase1 or 3-hydroxy-3-methylglutaryl-CoAreductase/sterol C24 reductase, grew and harvested plants, andperformed real-time quantitative PCR analyses; I.L., B.K.H., B.C.P.,and B.M.L. analyzed data and wrote the manuscript.

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flux through the MVA pathway (Chappell et al.,1995). In plants, the up-regulation of HMGR tran-script levels in transgenic plants has led to increases inthe major sterol end products in some cases (Schalleret al., 1995; Harker et al., 2003; Holmberg et al., 2003;Hey et al., 2006; Muñoz-Bertomeu et al., 2007; Saleset al., 2007), but not in others (Re et al., 1995). In-creased sterol levels have also been reported fortransgenic plants overexpressing the HMGS gene,which codes for the enzyme just upstream of HMGR(Wang et al., 2012).

Some authors suggested a limiting role for DXS toprovide precursors of chlorophylls and carotenoids viathe MEP pathway (Lois et al., 2000; Estévez et al., 2001;Rodríguez-Concepción et al., 2001; Enfissi et al., 2005),but there are also reports in which no correlation be-tween DXS transcript levels and these plastidial endproducts was observed (Muñoz-Bertomeu et al., 2006).

Several studies demonstrated correlations between theexpression levels of the genes encoding DXR (Mahmoudand Croteau, 2001; Carretero-Paulet et al., 2002;Hasunuma et al., 2008) or HDR (Botella-Pavía et al.,2004) with chlorophyll and carotenoid concentrationsin transgenic plants, whereas others did not find evi-dence for a limiting role of DXR in carotenoid biosyn-thesis (Rodríguez-Concepción et al., 2001).

Although we are only beginning to appreciate therelevance of posttranscriptional control, the currentlyavailable evidence suggests that the MVA and MEPpathways are both regulated at multiple feedbacklevels (Rodríguez-Concepción, 2006; Espenshade andHughes, 2007; Cordoba et al., 2009). For the develop-ment of metabolic engineering strategies, it is thus im-perative to understand to what extent carbon fluxthrough a pathway of interest is regulated at the tran-scriptional level. Here, we report, to the best of our

Figure 1. Outline and compartmenta-tion of isoprenoid biosynthesis in plants.The enzymes involved in the MVA andMEP pathways are numbered as follows:1, acetoacetyl-CoA thiolase (AACT); 2,3-hydroxy-3-methylglutaryl-CoA synthase(HMGS); 3, 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR); 4,mevalonate kinase (MK); 5, phospho-mevalonate kinase (PMK); 6, mevalonate5-diphosphate decarboxylase (MPDC); 7,1-deoxy-D-xylulose 5-phosphate synthase(DXS); 8, 1-deoxy-Dxylulose 5-phosphatereductoisomerase (DXR); 9, 2C-methyl-D-erythritol 4-phosphate cytidyltransferase(MCT); 10, 4-(cytidine 59-diphospho)-2C-methyl-D-erythritol kinase (CMK); 11, 2C-methyl-D-erythritol 2,4-cyclodiphosphatesynthase (MDS); 12, 1-hydroxy-2-methyl-2-butenyl 4-phosphate synthase (HDS);and 13, (E)-4-hydroxy-3-methyl-but-2-enyldiphosphate reductase (HDR). Multistepreactions are depicted with hollow arrows.The potential exchange of isoprenoid in-termediates across the plastidial envelopemembrane (metabolic cross talk) is indi-cated with a gray circle. Evidence for theexistence of an alternative pathway in-volving isopentenyl monophosphate (IP)has been presented, but its role in plants iscurrently unknown (depicted with brokenarrows). ER, Endoplasmic reticulum.

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knowledge, the first systematic investigation evaluatingthe relative importance of the expression levels of eachindividual MVA andMEP pathway gene for controllingthe accumulation of marker isoprenoids in Arabidopsis(Arabidopsis thaliana). This information was then used toeliminate bottlenecks in the sterol pathway and dra-matically enhance flux toward sterol end products.

RESULTS

Gene-to-Metabolite Correlation Analysis Identifies Geneswith Highest Impact on Isoprenoid Accumulation

Complementary DNAs (cDNAs) for all MVA andMEP pathway genes were cloned into suitable planttransformation vectors (three different selectablemarkers to facilitate subsequent crossing), and follow-ing Agrobacterium tumefaciens GV3101-mediated trans-formation, homozygous transgenic Arabidopsis lineswere selected. Wild-type controls and homozygoustransgenic lines were grown on soil under tightly con-trolled conditions in a growth chamber, and rosetteleaves were harvested right before bolting. We har-vested tissue only from plants with a normal visiblephenotype to avoid complications from analyzingpleiotropic effects resulting from secondary outcomesof transgene modulation. In particular, we observedthat lines with extremely low sterol amounts were se-verely dwarfed, and those with extremely low chloro-phyll or carotenoid levels had an albino phenotype.Very high overexpression of the DXS gene (and corre-sponding increases in chlorophylls and carotenoids)has previously been described as causing dwarfism(Estévez et al., 2001), indicating that detrimental effects

can occur when isoprenoid levels are increased abovea certain level. We determined the relative expressionlevels of transgenes and the quantities of the majorisoprenoid end products (sterols derived from theMVApathway; chlorophylls and carotenoids as end productsof the MEP pathway). Transgenic lines transformedwith a vector containing a GUS gene (tested as controlswith a gene insert unrelated to isoprenoid biosynthesis)yielded results that introduced more variation, butwere statistically indistinguishable from those obtainedwith untransformed wild-type plants (SupplementalFig. S1), and we thus used the latter in all furtheranalyses.

The correlation between transgene expression levelsand the amounts of marker isoprenoids was evaluatedby linear regression analysis. A positive slope of thetrend line (m $ 0.005), a significantly high Pearsoncorrelation coefficient (r $ 0.30), and a low P value forthe significance of the found correlation (deemedacceptable at a confidence threshold of 0.05) wereobtained for the following gene-to-metabolite correla-tions: HMGR-sterols (overexpression of the HMG1gene), DXR-chlorophylls and carotenoids, and MDS-chlorophylls and carotenoids (Table I; SupplementalFigs. S2 and S3). Although no significant correlationbetween the transcript levels of other transgenes andisoprenoid end products was detectable when all datapoints were considered, individual transgenic lines inwhich an MVA pathway gene was overexpressed didaccumulate increased amounts of chlorophylls andcarotenoids (Fig. 2A). Analogously, in individualtransgenic lines, a positive correlation between the ex-pression levels of MEP pathway genes with sterols wasobserved (Fig. 2A).

Table I. Gene-to-metabolite correlation analysis to identify genes with the highest impact on isoprenoid accumulation

The expression levels of genes involved in the cytosolic/peroxisomal MVA and plastidial MEP pathways were modulated in transgenic Arabidopsislines, and major end products derived from these pathways (sterols [MVA] and chlorophylls/carotenoids [MEP]) were quantified. Important pa-rameters of the statistical analysis (fold change versus untransformed controls for both genes and metabolites) are provided (m = slope of correlationtrend line; r = Pearson correlation coefficient; P = Student’s t test P value). Gray background is used to indicate positive gene-to-metabolite cor-relations. Full data are presented in Supplemental Figs. S2 and S3.

Gene

Metabolite

Chlorophylls Carotenoids Sterols

m r P m R P m r P

MVA pathwayAACT 0.007 0.19 0.293 0.012 0.16 0.395 0.002 0.08 0.690HMGS 0.003 0.03 0.423 0.005 0.27 0.244 7 3 1025 0.004 0.978HMGR 0.003 0.03 0.423 0.002 0.14 0.360 0.04 0.49 1.4 3 1027

MK 2 3 1024 0.09 0.612 3 3 1024 0.18 0.315 7 3 1025 0.05 0.776PMK 0.002 0.26 0.097 0.002 0.16 0.311 0.003 0.31 0.038MPDC 0.009 0.19 0.293 0.01 0.20 0.221 0.003 0.05 0.755

MEP pathwayDXS 0.025 0.11 0.456 0.061 0.29 0.055 0.013 0.12 0.446DXR 0.006 0.31 0.05 0.006 0.37 0.016 0.004 0.25 0.104MCT 5 3 1025 0.01 0.929 5 3 1024 0.11 0.491 5 3 1024 0.12 0.456CMK 3 3 1024 0.08 0.609 2 3 1025 0.004 0.979 0.001 0.32 0.032MDS 0.011 0.37 0.019 0.012 0.40 0.012 8 3 1025 4 3 1024 0.981HDS 0.002 0.05 0.738 0.002 0.03 0.834 0.002 0.04 0.819HDR 0.008 0.07 0.691 0.004 0.02 0.900 0.011 0.16 0.384

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Figure 2. Transgenic lines with elevated sterol levels accumulate pathway intermediates. A, Selected transgenic lines with highisoprenoid concentrations. Asterisks indicate the level of significance in a Student’s t test (*, P # 0.05; and **, P # 0.01). B,Representative chromatogram of HPLC-diode array analysis of chlorophylls and carotenoids (top, untransformed controls; bot-tom, transgenic lines with increased flux into chlorophylls and carotenoids [MDS overexpressor]). The chromatograms of wild-type and transgenic plants overexpressing the MDS gene are essentially identical, and no accumulation of chlorophyll or


Lange et al.



Metabolite-to-Gene Correlation Analysis IdentifiesFlux Bottlenecks

The results presented above are indicative of sharedcontrol, with certain genes exerting a higher level ofcontrol compared with others. At the enzymatic level,this notion is consistent with the summation theorem ofmetabolic control analysis, which implies that meta-bolic fluxes are systems-level properties and that reg-ulation is shared by all reactions (Kacser and Burns,1973; Heinrich and Rapoport, 1974). Due to the sub-stantial experimental challenges associated with deter-mining specific activities of all enzymes of the MVAand MEP pathways (Hemmerlin et al., 2012), the cal-culation of flux control coefficients formetabolic controlanalysis was impractical, and we thus investigated theutility of metabolite-to-gene correlations to identify fluxbottlenecks. The major end products of the plastidialchlorophyll and carotenoid pathways (chlorophyll a,chlorophyll b, trans-lutein, trans-b-carotene, trans-violaxanthin, and cis-neoxanthin) accumulated in allArabidopsis plants, whereas pathway intermediatesaccessible with our analytical methods were presentonly in small amounts (a-carotene) or were undetect-able (e.g. phytoene, lycopene, d-carotene, and [non-prenylated] chlorophyllides). Transgenic plants withincreased total chlorophyll and carotenoid levels, whencompared with controls, did not accumulate higherlevels of these plastidial isoprenoid pathway interme-diates (Fig. 2B). In contrast, transgenic lines withsignificantly increased sterol levels appeared toaccumulate disproportionately high amounts of certainbiosynthetic intermediates (Fig. 2C). When data setsfrom all transgenic lines were considered, there was acorrelation between total sterol amounts and sterolpathway end products (b-sitosterol and campesterol)that was best described (highest R2 value) by a loga-rithmic function (strong increase at lower fold change,reaching a plateau for larger fold change values;Fig. 2D). In contrast, for sterol pathway intermediates(isofucosterol, cycloartenol, and 24-methylene cyclo-artanol), there was a strong linear correlation with totalsterol levels (fold change versus controls; Fig. 2D).Based on the position of the accumulating intermedi-ates in the sterol pathway (Fig. 3), we hypothesized thattwo enzymatic activities, those acting on cycloartenol/24-methylene-cycloartanol or isofucosterol as substrates(sterol methyl oxidase1 [SMO1] and sterol C24 reductase[DWF1], respectively), exerted an increased level ofcontrol in transgenic lines engineered for high fluxthrough the sterol pathway.

Metabolic Engineering of Sterol Biosynthesis UsingPredictable Combinations of Genes Results in TransgenicPlants with Increased Biomass

To test the hypothesis that SMO1 catalyzes, in addi-tion to sterol methyltransferase 1 as demonstratedpreviously (Sitbon and Jonsson, 2001), a rate-limitingreaction of the sterol pathway in leaves, we generateda population of SMO1 overexpressors and selected aline with dramatically increased SMO1 transcript levels(740-fold increase compared with appropriate wild-type controls; Fig. 4A; Supplemental Fig. S4) and2.4-fold higher sterol amounts (Fig. 4B). Importantly,the amounts of the SMO1 substrates, cycloartenoland 24-methylene-cycloartanol, in the highest SMO1overexpressor were comparable with those inuntransformed control plants (Fig. 4C). These resultsdemonstrate that, in SMO1 transgenics, there werehigher sterol end product pools but no differences inintermediate pools (compared with untransformedcontrols) at a defined harvest time point, which is anindication of increased flux through the sterol pathway.The developmental time course was the same intransgenic lines and controls. To investigate if additiveeffects of transgene overexpression would further in-crease flux through the sterol pathway, we performedcrosses to generate transgenic lines overexpressing bothHMG1 and SMO1. A transgenic HMGR/SMO1 doubleoverexpressor accumulated sterol levels (3.8-foldhigher than wild-type controls) comparable with thoseobserved with HMG1 overexpressor (3.4-fold higherthan wild-type controls; Fig. 4, A and B). However, theHMG1/SMO1 double overexpressor contained signifi-cantly lower amounts of the SMO1 substrate cyclo-artenol (1.5% of total sterols) compared with HMG1overexpressor (7.1% of total sterols), with an overallcomposition of sterols similar to that of wild-type con-trols (Fig. 4C). A separate set of transgenic lines over-expressing DWF1 was also evaluated to decrease theaccumulation of the DWF1 substrate isofucosterol(Supplemental Fig. S4). Interestingly, an HMG1/DWF1double overexpressor indeed contained significantlyreduced amounts of isofucosterol when compared withthe HMG1 overexpressor, while maintaining the highsterol amounts (Fig. 4, A–C). This is particularly note-worthy because DWF1 expression levels in the HMG1/DWF1 double overexpressor were not as high as in theDWF1 (single) overexpressor. Furthermore, transgeniclines in which the flux into the sterol pathway isincreased (HMG1, SMO1, and HMG1/SMO1 over-expressors) were characterized by a significantly higher

Figure 2. (Continued.)carotenoid pathway intermediates is apparent. C, Representative total ion current chromatogram of gas chromatography-massspectrometry analysis of sterols (top, untransformed controls; bottom, transgenic lines with increased flux into sterols [HMG1overexpressor]). There is an increased accumulation of the sterol pathway intermediates isofucosterol, cycloartenol, and 24-methylene-cycloartanol in transgenic lines overexpressing theHMG1 gene. D, Correlation analysis for sterol pathway end productsagainst total sterols (left) and sterol pathway intermediates against total sterols (right; all expressed as fold change versus control).Trend lines for linear (blue) and logarithmic (black) correlations are shown for selected end products.







above-ground biomass (up to 54% increase in HMG1/SMO1 double overexpressor), with less significant ef-fects on stem length (Fig. 4, D and E).

Gene-to-Metabolite and Metabolite-to-MetaboliteCorrelation Analyses Indicate that Metabolic Cross TalkIs Negligible

Most studies investigating metabolic cross talk haveused feeding experiments with isotopically labeledprecursors to investigate the distribution of label inisoprenoid end products, and then inferred the extent ofexchange between plastidial and cytosolic intermediatepools (Hemmerlin et al., 2012). However, such an ap-proach is essentially impossible to implement with thelarge number of transgenic lines generated as part of theefforts described here. As an alternative, we used a se-ries of statistical correlation analyses to assess the extentof metabolic cross talk between compartmentalizedisoprenoid pathways.

To evaluate the likelihood of metabolic cross talk, wetested whether the expression levels of any gene codingfor an extraplastidial enzyme correlated with plastidialend products, or whether there was evidence for a cor-relation of transcript abundance for a plastidial enzymeand extraplastidial isoprenoids. No statistically signifi-cant correlation (neither positive nor negative) was de-tectable for the expression levels ofMVA pathway genes(which encode extraplastidial enzymes) and plastidialisoprenoid end products (chlorophylls and carotenoids;Table I). There was also a lack of correlation between theexpression levels of MEP pathway genes (which encodeplastidial enzymes) and extraplastidial isoprenoid endproducts (sterols; Table I). To further evaluate the pos-sibility of metabolic cross talk, we evaluated metabolite-to-metabolite correlations. The rationale was that, ifisoprenoid intermediates were exchanged betweencompartments, plastidial and nonplastidial isoprenoidend products should both be increased in elite trans-genic lines. The amounts of the two major classes of endproducts from the MEP pathway, carotenoids and

Figure 3. Outline of sterol biosynthesis withan emphasis on the reactions catalyzed bySMO1 and DWF1. Triple arrows indicate mul-tiple enzymatic steps.


Lange et al.



chlorophylls, were positively correlated across all trans-genic and control lines (m = 0.76, r = 0.67, P = 3.83 10264;Fig. 5). In contrast, no correlation, neither positive nornegative, was detected for chlorophylls/carotenoidsand MVA pathway-derived sterols (Fig. 5). Taken to-gether, these results provide evidence that, in thisstudy, metabolic cross talk across the chloroplast en-velope membrane was negligible.

DISCUSSION

Are There Rate-Limiting Steps in ArabidopsisSterol Biosynthesis?

As early as the mid-1990s, Chappell et al. (1995)posed the question of whether HMGR, an enzymewidely regarded as being critical for controlling fluxthrough the MVA pathway in animals (Espenshadeand Hughes, 2007), played a similar role in plants. Theauthors expressed a hamster HMGR gene in transgenic

tobacco plants (Nicotiana tabacum) and observed a3-fold increase (compared with controls) in leaf sterolamounts. However, it was also reported that cyclo-artenol, an intermediate of the sterol pathway, accu-mulated to very high levels (70-fold increase) in HMGRoverexpressors (Chappell et al., 1995). Similar resultswere obtained in several independent studies in whichHMGR genes from various species were overexpressedin tobacco (Schaller et al., 1995; Harker et al., 2003; Heyet al., 2006). Only Re et al. (1995) found that HMGRoverexpression did not result in measurable changes insterol amounts, but these authors only studied twotransgenic lines, which may not have been sufficient toobtain interpretable data. It was then hypothesized thatsterol C24 methyltransferase1 (SMT1), which acts oncycloartenol (accumulated intermediate in transgenicplants) as a substrate, was a sterol pathway-specificrate-limiting enzyme. Indeed, when SMT1 was over-expressed in transgenic tobacco, sterol levels wereincreased (1.4-fold increase), without a significant

Figure 4. Effects of overexpressingcombinations of genes involved inprecursor biosynthesis and the coresterol pathway. A, Expression levels oftransgenes in selected single and dou-ble overexpressors. WT, Wild type; Ox,overexpression construct. B, Total ste-rol amounts (as fold change versus un-transformed controls) in selected singleand double overexpressors. C, Individ-ual sterol profiles (as percentage of totalsterols) in selected single and doubleoverexpressors. D, Above-ground bio-mass in selected single and doubleoverexpressors. E, Stem height enhance-ments in selected single and doubleoverexpressors. Asterisks indicate thelevel of significance in a Student’s t test(*, P # 0.05; and **, P # 0.01).





accumulation of cycloartenol (Holmberg et al., 2003).The combined overexpression of HMGR and SMT1resulted in elevated sterol concentrations (2.5-foldincrease), with low levels of pathway intermediates(Holmberg et al., 2003). Does this mean that there areonly two rate-limiting enzymes in the plant sterolpathway? To investigate this issue systematically, wegenerated populations of transgenic lines with varyinglevels of expression for each gene involved in the MVA

pathway. Interestingly, almost anyMVApathway genecould be overexpressed to achieve an enhanced accu-mulation of sterols (Fig. 2A). For some genes, these in-creases were very small or moderate (MK, PMK, andMPDC), but for both HMGS and HMGR (HMG1 gene),highly significant sterol increases were detected in se-lected lines. The most dramatic sterol increases (4-fold)were observed with an HMG1 overexpressor. HMG1transgenics were also the only population in which apositive correlation between transgene expressionlevels and sterol amounts was determined when alllines were considered (Table I). From these data sets,one can deduce that the HMG1 gene exerts the highestlevel of control over flux into the sterol pathway, de-spite the known complexities with the multilevel reg-ulation of HMGR activity (Hemmerlin et al., 2012).However, as mentioned above, HMGS expression alsohas a considerable effect on sterol accumulation (Fig.2A), and the term rate limiting would thus be an ex-aggeration for HMGR.

All Arabidopsis transgenic lines with elevated sterolamounts accumulated disproportionately high levels ofcycloartenol (Fig. 2D), which is consistent with trans-genic tobacco overexpressing HMGR (Chappell et al.,1995). In addition, we detected dramatically increasedconcentrations of the intermediates 24-methylene-cycloartanol and isofucosterol. These findings pro-vided evidence that, in addition to SMT1 (Holmberget al., 2003), SMO1 (which uses cycloartenol and24-methylene-cycloartanol as substrates [Darnet andRahier, 2004]) and DWF1 (which acts on isofucosterolas a substrate [Choe et al., 1999]) may contribute sig-nificantly to the regulation of the sterol pathway. In-deed, transgenic lines overexpressing combinations ofgenes, namely, HMG1/SMO1 or HMG1/DWF1, werecharacterized by increased sterol amounts, with lowaccumulation levels of intermediates (Fig. 4, A–C).Taken together, the results presented here indicate thatcontrol over flux through the sterol pathway is sharedby several enzymes.

Are There Rate-Limiting Steps in Arabidopsis Carotenoidand Chlorophyll (Side Chain) Biosynthesis?

In our hands, almost any MEP pathway gene couldbe overexpressed to achieve an enhanced accumulationof carotenoids and chlorophylls (Fig. 2A). Transcrip-tional regulation therefore plays an important role indetermining the accumulation of isoprenoid end pro-ducts. However, since we did not observe a positivecorrelation between expression levels and end productsfor all MEP pathway genes (exceptions are DXR andMDS as discussed below), the transcript level may haveto be titrated just right to facilitate an increased fluxthrough the pathway. Alternatively, posttranscriptionalcontrol, which is still poorly understood (Rodríguez-Concepción, 2006), may become a flux-limiting factorwhen the expression levels of MEP pathway genesare modulated above or below a certain threshold.

Figure 5. Metabolite-to-metabolite correlation analysis of transgeniclines: chlorophylls versus carotenoids (A), carotenoids versus sterols (B),and chlorophylls versus sterols (C; all expressed as fold change versusuntransformed controls). Important parameters of the statistical analysis(fold change versus untransformed controls for both genes and metab-olites) are provided (m = slope of correlation trend line; r = Pearsoncorrelation coefficient; P = Student’s t test P value). WT, Wild type.


Lange et al.



The only transgenes for which we did not identify asingle line with consistently increased marker iso-prenoid levels were those encoding DXS and HDS.HDS had previously been described as being non-limiting for the biosynthesis of Arabidopsis carotenoids(Flores-Pérez et al., 2008). Yet, a nonlimiting role ofDXS for chlorophyll and carotenoid biosynthesis inArabidopsis contrasts with the data of Estévez et al.(2001). However, these authors reported that DXSoverexpressors with elevated plastidial isoprenoidlevels were significantly affected by growth retarda-tion, whereas we did not include transgenic lines withsevere phenotypes. Therefore, a direct comparison withthe study by Estévez et al. (2001) is not possible. Pheno-typically normal transgenic plants had only a fairlynarrow range of DXS expression levels (1.1- to 3.9-foldhigher than wild-type controls) in our population,which might be explained by the fact that DXS is themost highly expressed gene of the MEP pathway inrosette leaves of wild-type plants (Schmid et al., 2005).When carotenoids and chlorophylls were assayed as

metabolic end products, positive gene-to-metabolitecorrelations across entire populations of transgenicswere only detected in lines with altered DXR or MDSexpression levels (Table I). Furthermore, significantenhancements (.50%) in the amounts of isoprenoidend products derived from the MEP pathway weredetected solely when the transcript levels of MDS wereappreciably increased (Table I). Interestingly, theproduct of the MDS-catalyzed reaction, 2C-methyl-D-erythritol-2,4-cyclodiphosphate, was recently demon-strated to be a plastid-to-nucleus signaling metabolitethat elicits stress-responsive genes (Xiao et al., 2012). Itis intriguing to speculate that MEP pathway regulation,and thus the accumulation of plastidial isoprenoids,involves retrograde signaling, and that MDS mightplay an important role in this process.HPLC chromatograms of extracts from transgenic

lines with significantly elevated carotenoid and chlo-rophyll amounts had the same metabolite pattern asthose of untransformed controls (with higher signalintensities; Fig. 2, B and C). The fact that we did not findevidence for the accumulation of carotenoid pathwayintermediates is consistent with previous studies dem-onstrating that phytoene synthase, the entry enzymeinto the carotenoid pathway, plays a regulatory role inArabidopsis vegetative tissues (von Lintig et al., 1997;Rodríguez-Villalón et al., 2009). One way to interpretthis might be that regulation of the carotenoid path-way, under favorable conditions, is less complex whencompared with the sterol pathway. However, in thiscontext, it is important to note that the highest carote-noid and chlorophyll amounts, without negatively af-fecting plant growth, were in a fairly narrow range(0.6- to 1.7-fold change compared with untransformedcontrols), whereas significantly increased sterol levels(up to 6-fold change compared with untransformedcontrols) did not have negative effects on growth.Regulatory complexity arises under stress conditions,when a higher xanthophyll accumulation is desirable

and additional levels of control need to be considered(Davison et al., 2002).

MVA and MEP Transgenic Lines Are a Valuable Resourcefor Assessing the Functional Roles of Isoprenoids

We demonstrate that transgenic plant lines withsignificantly increased sterol levels are characterized byincreased above-ground biomass (Fig. 4D). Biomassyield is a critical trait for bioenergy crops, particularlybecause the chemical composition of feedstocks is onlya minor concern for emerging technologies such ashydroprocessing combined with zeolite catalysis (Visputeet al., 2010). On a different token, sterols have beenshown to contribute to meristem organization andvascular patterning independent of brassinosteroidhormones (Souter et al., 2002; Men et al., 2008), and ourtransgenic lines are an invaluable resource to shed lighton important but poorly understood developmentalfunctions of sterols. Furthermore, isoprenoid volatileshave recently been described as determinants ofArabidopsis resistance to bacterial infection and insectherbivory, and their biosynthesis appears to be con-strained mostly by precursor availability (Tholl andLee, 2011). Our transgenic lines with significantly in-creased flux through the MVA or MEP pathways maytherefore release altered levels of isoprenoid volatiles(has not been tested yet) and could contribute to a betterunderstanding of the roles of isoprenoids in plantdefense.

MATERIALS AND METHODS

Generation of Transgenic Arabidopsis Lines

Genes involved in the MVA and MEP pathways of isoprenoid biosynthesiswere PCR amplified from several pooled Arabidopsis (Arabidopsis thaliana)cDNA libraries (Supplemental Table S1). Purified PCR products were sequenceverified and recombined with the pDONR201 Gateway vector (Invitrogen),thus yielding an entry clone. Cassettes containing the genes of interest werethen transferred from the entry clone to the p*7WG2 transfer DNA destinationvector suite (Karimi et al., 2002). These vectors are engineered to contain one ofthe plant selectable marker genes encoding neomycin phosphotransferase II,hygromycin phosphotransferase, or bialaphos acetyltransferase, which conferresistance against kanamycin, hygromycin, or glufosinate ammonium (Basta),respectively. Target genes (13 genes with three different selection markers;39 constructs total) were placed between the promoter and terminator of theCauliflower mosaic virus 35S gene (Odell et al., 1985). The destination vector wastransformed into competent Agrobacterium tumefaciens GV3101 cells by elec-troporation (Koncz and Schell, 1986), and transformed into Arabidopsis plants(Columbia ecotype accession) using the floral dip method (Clough and Bent,1998). Seedlings from the T2 seed generation were grown to select for a 3:1survivor to nonsurvivor rate on the appropriate antibiotic/herbicide (as ex-pected for single copy gene insertions following Mendelian genetics) usingstandard laboratory protocols (Weigel and Glazebrook, 2002), and seed fromsurviving plants was collected (T3 seed). Homozygous T3 lines were identifiedby a 100% survival rate of their progeny seedlings under selection pressure. Inaddition, homozygosity was tested using routine PCR methods (Weigel andGlazebrook, 2002). To generate double transgenics, line HMG1-9.1.7 (kana-mycin resistant) was used as a pollen donor in a cross with SMO1-1.1 (Bastaresistant), and lineHMG1-6.1.7 (Basta resistant) was the pollen donor for a crosswith DWF1-7.1 (hygromycin resistant). F1 seedlings derived from cross polli-nation were selected by 10 d of growth on appropriate selective medium. Theresulting F1 plants were self-pollinated and grown to maturity for seed






collection, providing a segregating F2 population for each cross. To identifydouble-homozygous plants from the F2 generation, seed was collected fromeach F2 plant and plated on medium containing two selection agents (one foreach overexpression cassette). Plants with a progeny survival rate greater than98% were considered homozygous for both transgenes.

Plant Growth and Harvest

Wild-type and homozygous transgenic lines were grown on soil (in 6- 36-cm pots) and maintained in a growth chamber (16-h-day/8-h-night pho-toperiod; 100 mmol m22 s21 light intensity at soil level; constant temperatureat 23°C; 70% relative humidity). Pots were arranged in a random grid androtated once a day. Three independent pools of plants were grown at differenttimes to generate biological replicates. Rosette leaves were collected atgrowth stage 5.10 (just as the inflorescence starts to appear; Boyes et al., 2001),pooled, weighed, and shock frozen in liquid nitrogen. Harvested plant ma-terial from each pool was homogenized (Ball Mill MM301, Retsch) in thepresence of liquid nitrogen, weighed, and aliquots were stored in 2-mLEppendorf tubes. Representative plants of each line were grown to maturity(growth stage 8.0; prior to onset of senescence; Boyes et al., 2001) and phe-notypic measurements taken (stem length; number of flowers; number andlength of siliques; diameter, length, and number of rosette leaves; and visualphenotype scoring). For dry weight biomass measurements, tissue wasplaced in an oven at 50°C for 8 d.

Quantitative Real-Time PCR

RNAwas extracted using the Trizol reagent (Life Technologies) according tothe manufacturer’s instructions. Isolated RNA (1,000 ng) was treated withRNase-free DNase (Thermo Scientific) and first strand cDNA synthesized usingSuperscript III reverse transcriptase (Life Technologies). In a 10-mL quantitativePCR reaction, concentrations were adjusted to 150 nM (primers), 13 PowerSYBR Green PCR Master Mix (Life Technologies), and 103 diluted first strandcDNA as template (see Supplemental Table S2 for primer sequences). Reactionswere performed in a 96-well optical plate at 95°C for 10 min, followed by40 cycles of 95°C for 15 s and 60°C for 10 min in a 7500 Real-Time PCR system(Life Technologies). Fluorescence intensities of three independent measure-ments (technical replicates) were normalized against the ROX reference dye(ThermoFisher Scientific). Relative transcript levels were calculated based onthe comparative CT method as specified in the manufacturer’s instructions(Life Technologies) using b-actin (At3g18780) as the constitutively expressedendogenous control and the expression levels of the corresponding wild-typeallele as the calibrator.

Sterol Analyses

Tissue homogenate (60–70mg)was extracted at 75°C for 60minwith 4mL ofCHCl3/MeOH (2:1, v:v; containing 1.25 mg L21 epi-cholesterol as an internalstandard). Samples were evaporated to dryness (EZ2-Bio, GeneVac), and theremaining residue was saponified at 90°C for 60 min in 2 mL of 6% (w/v) KOHinMeOH. Upon cooling to room temperature, 1 mL of hexane and 1 mL of H2Owere added, and the mixture was shaken vigorously for 20 s. Following cen-trifugation (3,000g for 2 min) to separate the phases, the hexane phase wastransferred to a 2-mL glass vial, the aqueous phase reextracted with 1 mL ofhexane as above, centrifuged as above, and the hexane phase added to the 2-mLglass vial containing the hexane phase from the first extraction. The combinedorganic phases were evaporated to dryness as above, 50 mL of N-methyl-N-trimethylsilyltrifluoroacetamide was added to the residue, the sample wasshaken vigorously for 20 s, and the mixture was transferred to a 2-mL auto-sampler glass vial with a 100-mL conical glass insert. After capping the vial, thereaction mixture was incubated at room temperature for 5 min. Gaschromatography-mass spectrometry analyses were performed on an Agilent6890N gas chromatograph coupled to an Agilent 5973 inert mass selective de-tector (MSD) detector. Samples were loaded (injection volume 1 mL) with aLEAP CombiPAL autosampler onto an Agilent HP-5MS fused silica column(30 m 3 250 mm; 0.25-mm film thickness). The temperatures of the injector andMSD interface were both set to 280°C. Analytes were separated at a flow rate of1 mL min21, with He as the carrier gas, using a thermal gradient starting at170°C (hold for 1.5 min), a first ramp from 170°C to 280°C at 37°C/min, asecond ramp from 280°C to 300°C at 1.5°C/min, and a final hold at 300°C for5.0 min. Analytes were fragmented in electron impact mode with an ionizationvoltage of 70 eV and data acquired using MSD ChemStation software (revision

D.01.02.SP1, Agilent Technologies). Background was subtracted and peakswere deconvoluted using Automatic Mass Spectral Deconvolution and Iden-tification Software. Analytes were identified based on their mass fragmentationpatterns by comparison with those of authentic standards using the NationalInstitute of Standards and Technology Mass Spectral Search Program (versionD.05.00). Peak areas were obtained from the total ion chromatogram for alldetectable peaks with a phytosterol mass fragmentation signature. Raw datawere exported toMicrosoft Excel and peak areas normalized to tissue mass andinternal standard. A blank injection was performed after each sample run, andthe background signal from the blank subtracted from the sample values for theentire run. Prior to sample analyses, and then after every 20 samples, a standardmix was run to evaluate the reproducibility of the analyses. The adjusted peakareas for sterols were added up and compared with the corresponding sum ofsterol peak areas for untransformed controls (expressed as fold change versuscontrol). Linear regression analyses for gene-to-metabolite, metabolite-to-gene,and metabolite-to-metabolite correlations were performed in Microsoft Excel.

Chlorophyll and Carotenoid Analyses

Tissue homogenate (approximately 110–120 mg) was extracted with threealiquots of 2 mL of CHCl3/MeOH (2:1; v/v), containing 2 mg L21 ubiquinone-10as an internal standard, in a dark roomwith supplemental lighting from a 40-Wgreen bulb. Each extraction included a 15-min incubation at room temperature,and the three organic extracts were combined in a glass vial wrapped withaluminum foil to avoid light exposure. The pooled organic phases wereextracted against 1.5 mL of 1 M NaCl/50 mM Tris-HCl (pH 7.5), and the vialswere centrifuged (3,000g for 2 min) to achieve phase separation. The (lower)organic phase was transferred to a new tube (kept in darkness) and the solventevaporated to dryness (EZ2-Bio, GeneVac). Analytes were dissolved in 200 mLof ethyl acetate, and the mixture was filtered through a 0.45-mm nylon syringefilter and transferred to a brown 2-mL autosampler glass vial with a 100-mLconical glass insert. HPLC/diode array detector/mass spectrometry analyseswere performed using anAgilent Series 1100HPLC system (including a G1315Bdiode array detector) coupled to an Agilent G2445D LC/MSD Trap SL massspectrometer. Samples were loaded (injection volume, 20 mL) onto a ProntosilC30 column (250 3 4.6 mm; 5-mm particle size; Bischoff Chromatography dis-tributed via MAC-MODAnalytical) equippedwith a guard column of the samestationary phase. The mobile phase consisted of methanol (A), water/methanol(20:80; v:v) containing 0.2% (w/v) ammonium formate (B), and tert-butylmethyl ether (C). A gradient flow rate of 1 mL min21 was used to separateanalytes (Fraser et al., 2000): 11 min of isocratic gradient of 95% A/5% B, a stepchange to 90%A/5%B/5%C, a linear gradient (15min) to 30%A/5%B/65%C,a hold at this condition for 5 min, and a conditioning phase to return to theinitial conditions. Ultraviolet/visible absorbance was monitored at 275, 287,460, and 655 nm, and spectra were recorded from 250 to 750 nm in 2-nm in-crements. Analytes were identified and quantified by comparison of retentiontimes and ultraviolet/visible spectra with those of corresponding referencestandards. To further ensure proper peak assignments, eluting analytes fromrandom samples were also ionized using atmospheric pressure chemical ioni-zation, and mass traces were acquired by single-ion monitoring in positive ionmode to detect the following mass ion transitions: mass-to-charge ratio (m/z)864 → 680 (ubiquinone-10; internal standard), m/z 538 → 444 (a- andb-carotene),m/z 569→ 551 (lutein),m/z 894→ 615 (chlorophyll a),m/z 907→ 629(chlorophyll b), andm/z 872→ 593 (pheophytin a). The probe voltage was set to4.0 kV, the capillary voltage was at 2,200 V, the gas temperature was 350°C, andthe nebulizer gas flow was 9.0 L min21. Raw data were exported to MicrosoftExcel and peak areas normalized to tissue mass and internal standard usingMicrosoft Access. To ensure low background signals, a blank injection wasperformed after every six samples. Prior to sample analyses, and then afterevery 20 samples, a standard mix was run to evaluate the reproducibility of theanalyses. The adjusted peak areas for carotenoids and chlorophylls were addedup separately and compared with the corresponding sum of peak areas foruntransformed controls (expressed as fold change versus control). Linear re-gression analyses for gene-to-metabolite, metabolite-to-gene, and metabolite-to-metabolite correlations were performed in Microsoft Excel.

Three copies of the gene encoding DXS are present in the Arabidopsis ge-nome. The gene encoding the most broadly expressed isoform (At4g15560) hasbeen characterized biochemically and was chosen for the current study. Thesubsequent steps are catalyzed by DXR, 2C-methyl-D-erythritol 4-phosphatecytidyltransferase, CMK, MECPS, HDS, and HDR, all of which are encoded bysingle genes in Arabidopsis. Biochemical characterizations have been per-formed with the Arabidopsis genes encoding DXR (At5g62790), 2C-methyl-D-erythritol 4-phosphate cytidyltransferase (At2g02500), HDS (At5g60600), and


Lange et al.




HDR (At4g34350). Functional data have also been obtained for a gene encodingCMK from tomato (Solanum lycopersicum), and a gene coding for MECPS hasbeen characterized inGinkgo biloba, but the putativeArabidopsis orthologs havenot yet been characterized. However, when the putative plastidial targetingsequences are excluded, the sequence identity/homology of functionallycharacterized CMK and MECPS proteins and the translated peptides ofAt1g63970 and At2g26930 in Arabidopsis are above 85% and 94%, respectively,and the corresponding cDNAs were cloned for the current study. Acetoacetyl-CoA thiolase is encoded by two genes in the Arabidopsis genome, but it wasshown that At5g48230 coded for the isozyme involved primarily in sterol bi-osynthesis. HMGS (At4g11820) and MK (At5g27450) are both encoded bysingle-copy genes in Arabidopsis, and both of these enzymes have been bio-chemically characterized. Two HMGR gene copies are present in Arabidopsis,and we cloned a cDNA representing the functionally characterized and con-stitutively expressedHMG1 isoform (At1g76490). Only a distant homolog of thewell-characterized yeast (Saccharomyces cerevisiae) PMK gene is detectable in theArabidopsis genome (At1g31910), but this enzyme is generally poorly con-served across species. Two MPDC copies are detectable in the Arabidopsisgenome, one of which (At2g38700) encodes a protein that has been functionallycharacterized. The corresponding cDNAwas cloned for the activities describedhere. Three copies of sterol C4 methyl oxidase are present in Arabidopsis, andwe selected the most widely expressed isoform (At4g22756) for overexpression.The DWF1 gene (encoding sterol C24 reductase) occurs as a single copy(At3g19820) in the Arabidopsis genome.

Supplemental Data

The following supplemental materials are available.

Supplemental Figure S1. A graph comparing isoprenoid end productlevels in wild-type versus GUS transgenic plants.

Supplemental Figure S2. Graphs for transgenics in which expression levelsof a gene of the MVA pathway are modulated.

Supplemental Figure S3. Graphs for transgenics in which expression levelsof a gene of the MEP pathway are modulated.

Supplemental Figure S4. Transgenic Arabidopsis lines overexpressingeither SMO1 or DWF1.

Supplemental Table S1. List of genes cloned for generating transgenicplants.

Supplemental Table S2. Cloning primers.

ACKNOWLEDGMENTS

We thank Maximilian J. Feldman, Sean R. Johnson, Jared Mell, AmberParrish, and Lyuba S. Yurgel for technical assistance.

Received April 17, 2015; accepted August 14, 2015; published August 17, 2015.

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