SHORT REPORT Adaptation of hydroxymethylbutenyl diphosphate reductase enables volatile isoprenoid production Mareike Bongers1,2*, Jordi Perez-Gil2,3, Mark P Hodson2,4,5, Lars Schrübbers1, Tune Wulff1, Morten OA Sommer1, Lars K Nielsen1,2†, Claudia E Vickers2,6†* 1 Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark; 2Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Australia; 3Centre for Research in Agricultural Genomics (CRAG) CSIC-IRTA-UAB-UB, Campus UAB Bellaterra, Barcelona, Spain; 4Metabolomics Australia, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Australia; 5School of Pharmacy, The University of Queensland, Brisbane, Australia; 6 CSIRO Synthetic Biology Future Science Platform, Brisbane, Australia Abstract Volatile isoprenoids produced by plants are emitted in vast quantities into the atmosphere, with substantial effects on global carbon cycling. Yet, the molecular mechanisms regulating the balance between volatile and non-volatile isoprenoid production remain unknown. Isoprenoids are synthesised via sequential condensation of isopentenyl pyrophosphate (IPP) to dimethylallyl pyrophosphate (DMAPP), with volatile isoprenoids containing fewer isopentenyl subunits. The DMAPP:IPP ratio could affect the balance between volatile and non-volatile isoprenoids, but the plastidic DMAPP:IPP ratio is generally believed to be similar across different *For correspondence: species. Here we demonstrate that the ratio of DMAPP:IPP produced by hydroxymethylbutenyl marbon@biosustain.dtu.dk (MB); diphosphate reductase (HDR/IspH), the final step of the plastidic isoprenoid production pathway, is c.vickers@uq.edu.au (CEV) not fixed. Instead, this ratio varies greatly across HDRs from phylogenetically distinct plants, † These authors contributed correlating with isoprenoid production patterns. Our findings suggest that adaptation of HDR plays equally to this work a previously unrecognised role in determining in vivo carbon availability for isoprenoid emissions, Competing interests: The directly shaping global biosphere-atmosphere interactions. authors declare that no competing interests exist. Funding: See page 13 Introduction Received: 22 May 2019 Biogenic volatile organic compounds (BVOCs) emitted from the biosphere have significant effects Accepted: 16 February 2020 on global climate and air quality (Loreto and Fares, 2013). Short-chain isoprenoids such as iso- Published: 12 March 2020 prene, a C5 hydrocarbon, contribute more than 80% of BVOCs, totalling about 650 million tonnes of carbon per year (Sindelarova et al., 2014). The vast quantity and high reactivity of emitted volatile Reviewing editor: Joerg Bohlmann, University of British isoprenoids affect the oxidative capacity of the troposphere (Thompson, 1992; Wennberg et al., Columbia, Canada 2018), impact the residence time of the greenhouse gas methane (Fehsenfeld et al., 1992), and contribute to air pollution through formation of secondary organic aerosols, surface-level ozone and Copyright Bongers et al. This carbon monoxide (Claeys et al., 2004; Poisson et al., 2000; Granier et al., 2000; Figure 1). The article is distributed under the effects of isoprenoid emissions may be exacerbated by climate change and shifts in land use terms of the Creative Commons Attribution License, which (Peñuelas and Staudt, 2010), warranting a better understanding of how plants accomplish and reg- permits unrestricted use and ulate these vast emissions. redistribution provided that the All isoprenoids are made from the C5 isomers isopentenyl pyrophosphate (IPP) and dimethylallyl original author and source are pyrophosphate (DMAPP) (Figure 1). Two non-homologous metabolic pathways produce DMAPP credited. and IPP in plants: the cytosolic mevalonic acid (MVA) and the plastidic methylerythritol phosphate Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 1 of 16 Short report Biochemistry and Chemical Biology Plant Biology Figure 1. Simplified scheme of the plastidic MEP pathway, important volatile isoprenoids, and their atmospheric reactions. The MEP pathway makes IPP and DMAPP simultaneously through the action of HDR (pink box), and produces the bulk of volatile isoprenoids, contributing >80 % of total BVOCs (Sindelarova et al., 2014) . Non- volatile isoprenoids are essential and synthesised by all organisms, while volatile isoprenoid production is non- essential and highly species-dependent. The cytosolic MVA pathway contributes most sesquiterpenes (<3 % of BVOCs), but is omitted here for clarity. Emitted volatile isoprenoids are rapidly oxidised, resulting in complex atmospheric photochemistry impacting aerosol and cloud condensation nuclei formation, extension of methane residence time, ozonolysis as well as surface-level ozone formation in the presence of mono-nitrogen oxide (NOx) pollutants (Wennberg et al., 2018). BVOCs, biogenic organic volatile compounds; DMAPP, dimethylallyl pyrophosphate; DXS, deoxyxylulose synthase; IDI, isopentenyl diphosphate isomerase; IPP, isopentenyl pyrophosphate; IspS, isoprene synthase; HDR, hydroxymethylbutenyl diphosphate reductase. (MEP) pathways, the latter contributing almost all volatile isoprenoids (Pulido et al., 2012). The final step of the MEP pathway is catalyzed by the enzyme hydroxymethylbutenyl diphosphate reductase (HDR/IspH), which produces both IPP and DMAPP (Figure 1). Isoprenoid chain length is initially determined by how many units of IPP are condensed with one molecule of DMAPP, before terpene synthases and other modifying enzymes convert these intermediates into isoprenoids. The resulting compounds are classified by carbon chain length. In plants, longer-chain isoprenoids (C15 and higher) serve many essential roles, e.g. as membrane components and parts of the photosynthetic apparatus (Pulido et al., 2012; Figure 1). Short-chain Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 2 of 16 Short report Biochemistry and Chemical Biology Plant Biology isoprenoids (C5, C10, and some C15 compounds) are volatile under physiological conditions, and their functions are generally not essential for plant survival (Vickers et al., 2009). It is currently unknown how plants control carbon allocation between short-chain and long-chain isoprenoids in the chloro- plast. While the demand for essential isoprenoids (for example, photosynthetic pigments) is assumed to be relatively similar across plants (Monson et al., 2013), different species produce markedly dif- ferent amounts of non-essential, short-chain volatile isoprenoids (Wiedinmyer et al., 2020). For example, some oak (Quercus) species produce vast amounts of isoprene, while closely related oaks produce little or none at all (Wiedinmyer et al., 2020). Synthesis of isoprenoids with different chain lengths requires different DMAPP:IPP substrate ratios. Much more IPP than DMAPP is needed for long-chain isoprenoid production, so presumably high relative IPP concentrations are necessary for chain elongation while an excess of DMAPP and insufficient IPP could favour short-chain isoprenoid production. Isoprene synthase (IspS) uses only DMAPP, but not IPP, as a substrate. Volatile isoprenoid emissions can represent a significant loss of carbon; for example, up to 20% of recently fixed carbon can be emitted as isoprene in high-emitting plants (Sharkey and Loreto, 1993). Isoprene synthase (IspS) has a high Km for its substrate DMAPP (0.5–8 mM; BRENDA, 2020); despite this, it successfully competes with prenyl phosphate synthases, which typically have KM (DMAPP) values 10- to 100-fold lower (BRENDA, 2020). Similarly, monoterpene synthases, which also show lower affinity for the substrates (BRENDA, 2020), compete with downstream prenyl phosphate synthases. Hence, the relative abundance of DMAPP may determine the balance between volatile and non-volatile isoprenoids. Here we examined HDR as a potential mechanism to provide variability in the DMAPP:IPP ratio. Previous studies in diverse organisms (Escherichia coli, the bacterium Aquifex aeolicus, red pepper chromoplasts, and cultured tobacco cells) all found that HDR produces DMAPP:IPP ratios between 1:4 and 1:6 (Rohdich et al., 2003; Altincicek et al., 2002; Adam et al., 2002; Tritsch et al., 2010). Consequently, it has been assumed that HDR has a fixed product ratio of about 1:5. However, none of these species produce significant amounts of volatile isoprenoids (Wiedinmyer et al., 2020). Iso- pentenyl diphosphate isomerase (IDI) interconverts DMAPP and IPP, but the reaction is slow (Jonnalagadda et al., 2012) and IDI is rate-limiting for isoprenoid production generally, including isoprene (Vickers et al., 2014). We hypothesised that HDR enzymes from species that emit large amounts of short-chain volatile isoprenoids produce a higher ratio of DMAPP to IPP, which could support production of volatiles like isoprene. Results and discussion We selected HDR genes from the bacterium E. coli, Synechococcus sp. strain PCC 7002 (a photosyn- thetic prokaryote) and eight species from diverse taxa of the plant kingdom (Table 1). Many plants harbour more than one annotated HDR gene, some of which may be pseudogenes. Therefore, we first identified functional HDR genes by their ability to complement an otherwise lethal knockout of the ispH/HDR gene in E. coli (Altincicek et al., 2001). We found at least one functional gene from each species (Figure 2—figure supplement 1a); however, severe dose-dependent growth defects were observed when overexpressing certain HDR genes, possibly due to toxicity of prenyl phos- phates (George et al., 2018; Figure 2—figure supplement 1b). This precluded accurate steady- state metabolite quantification and required alleviating toxicity by the introduction of a metabolic sink for IPP and DMAPP. Here we used a lycopene (C40 isoprenoid) biosynthetic pathway, including expression of a heterologous idi (Cunningham et al., 1994). Deoxyxylulose synthase (DXS), the pri- mary rate-limiting step of the MEP pathway, was also overexpressed in order to achieve intracellular IPP and DMAPP concentrations above quantification limits in E. coli. A spectrum of DMAPP:IPP ratios was observed, ranging from almost exclusive IPP production (Picea sitchensis HDR1) to almost exclusive DMAPP production (Populus trichocarpa and Ricinus communis, Figure 2a). A control without HDR overexpression (labelled (-) in Figure 2a) showed a DMAPP:IPP ratio of ~1.5 to 1 in our experimental setup, serving as a reference point. Overexpress- ing the E. coli HDR shifted the ratio slightly towards IPP, in agreement with previous reports (Rohdich et al., 2002). However, HDR enzymes from species known to emit volatile isoprenoids pro- duced considerably more DMAPP - a noteworthy exception being P. sitchensis HDR1 (PsHDR1, Figure 2a). Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 3 of 16 Table 1. Genetic information and volatile isoprenoid emission profiles for species studied in this work. Key: blank cell indicates species has not been tested, or genome sequence (or other information) not available; Y indicates significant emissions of isoprene or isopre- noids have been detected, or gene/transcript has been identified; N indicates significant emissions of isoprene or isoprenoids have NOT been detected, or gene/tran- script has NOT been identified; MTs, monoterpenes; IspS, isoprene synthase; TPS, terpene synthase. Gene/ Short report Emissions transcript* E. coli HDR protein construct Short Phylum/ Genus, Common accession Genbank Isoprene MTs chain Kingdom Clade Clade species Name number ID Complements?† (C5) (C10) IspS TPS Reference Plantae Angiosperms Eudicots Ricinus communis castor bean XP_002519102.1 MH605331 yes N Y N Y Wiedinmyer et al., plant 2020; Kadri et al., 2011; Xie et al., 2012) Plantae Angiosperms Eudicots Populus black 1 ACD70402 MH605329 yes Y Y Y Y Wiedinmyer et al., trichocarpa‡ cottonwood 2020; Tuskan, 2006) 2 PNT41333.1 MH605330 no Plantae Angiosperms Eudicots Prunus peach XP_007199828.1 MH605326 yes N Y N Y Wiedinmyer et al., persica 2020; Verde et al., 2013) Plantae Angiosperms Eudicots Eucalyptus grandis flooded gum 1 XP_010028563.1 MH605323 yes Y Y Y Y Wiedinmyer et al., Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 2020; 2 XP_010047332.1 MH605324 no Myburg et al., 2014 Plantae Angiosperms Eudicots Theobroma cacao cacao tree XP_007042717.1 MH605333 yes N Y N Y Wiedinmyer et al., 2020; Argout et al., 2008 Plantae Angiosperms Eudicots Arabidopsis thale cress AEE86362.1 MH605322 yes N Y N Y Sharkey et al., 2005; thaliana Chen et al., 2004; Bohlmann et al., 2000 Plantae Angiosperms Monocots Elaeis guineensis oil palm XP_010909277.1 MH605325 yes Y Y Wiedinmyer et al., 2020; Wilkinson et al., 2006 Plantae Gymnosperms Pinophyta Picea Sitka spruce 1 ACN40284.1 MH605327 yes Y Y Y Wiedinmyer et al., sitchensis 2020; 2 ACN39959.1 MH605328 yes – toxic Hayward et al., 2004 Bacteria Cyanobacteria Synechococcus sp. Synechococcus ACA98524.1 MH605332 yes N N N PCC 7002 * Identified from data/genomes available on NCBI (https://www.ncbi.nlm.nih.gov/) and literature search (references noted). † Whether protein expression was able to functionally complement an E. coli DispH knockout in this study. ‡ Also known as Populus balsamifera ssp. trichocarpa. 4 of 16 Biochemistry and Chemical Biology Plant Biology Short report Biochemistry and Chemical Biology Plant Biology Figure 2. DMAPP:IPP ratio and isoprene production with different HDR enzymes. (a) In vivo ratio of DMAPP:IPP measured via LC-MS/MS in E. coli overexpressing HDR genes from different species, in the genetic context of dxs and lycopene biosynthetic pathway overexpression. Filled circles and squares indicate that the HDR source species natively emits C5 or C10 isoprenoids. Open symbols indicate no emission, and no symbol indicates no data or conflicting data. (b) Isoprene production in E. coli when the HDR enzymes shown in panel (a) are overexpressed with dxs and an isoprene synthase. (c) Comparison of DMAPP:IPP ratios between selected HDRs co-expressed with dxs and with expression of either lycopene or isoprene as the metabolic sink. (d) Comparison of DMAPP:IPP ratios in E. coli overexpressing Picea sitchensis (Ps) HDR1 or HDR2 in the context of dxs and lycopene biosynthetic pathway overexpression. (e) Isoprene production in E. coli overexpressing P. sitchensis HDR1 or HDR2 along with dxs and an isoprene synthase. (f) The maximum specific growth rate (mmax) of E. coli expressing selected HDRs in the context of dxs and lycopene biosynthetic pathway overexpression, with or without induction of HDR expression by addition of IPTG. All data shown as mean ± SD from > 3 biological replicates; (-) indicates the control strain without HDR overexpression. The online version of this article includes the following source data and figure supplement(s) for figure 2: Source data 1. Raw data for metabolomics, proteomics and isoprene measurements shown in Figure 2 and supplements. Figure supplement 1. Complementation of lethal knockout of ispH in E. coli using different HDRs, and associated DMAPP toxicity. Figure supplement 2. Protein quantification of IDI, HDR and the lycopene biosynthetic pathway. Figure supplement 3. Quantification of DMAPP and IPP using LC-MS/MS. Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 5 of 16 Short report Biochemistry and Chemical Biology Plant Biology These values do not represent direct product ratios of the examined HDRs due to the presence of the heterologously expressed lycopene pathway and idi. However, they show that product ratios vary up to 40-fold between HDRs, and that the assumed fixed 1:5 DMAPP to IPP ratio is in fact an exception, rather than the rule. Using LC-MS proteomics, we tested whether the observed pheno- types were influenced by differences in expression of the native E. coli HDR, IDI, or the plasmid- encoded lycopene production pathway. We found no difference in protein levels in any of the HDR overexpression strains compared to the no HDR overexpression control (one-way ANOVA, p>0.05), except for the anticipated increase in E. coli HDR in the respective overexpression strain (Welch’s ANOVA, Dunnett’s post hoc test p<0.005; Figure 2—figure supplement 2). Because no shared Figure 3. Phylogenetic tree of HDR proteins from land plants, the cyanobacterium Synechococcus and Escherichia coli. Where known, each species’ C5 (isoprene) and C10 (monoterpenes) emission spectra are shown (Wiedinmyer et al., 2020). High DMAPP-producing HDR proteins (from P. trichocarpa, R. communis and P. persica) cluster together based on high sequence similarity. Homologues within species, such as P. trichocarpa, tend to be highly similar; except for in gymnosperms where two separate groups of likely paralogous HDRs exist. Proteins analysed in this study are highlighted in bold. The Asterids clade is collapsed for clarity. Tree generated from BLAST sequence alignment with A. thaliana HDR against all land plants, using maximum likelihood phylogeny. Empty symbol, no volatile emission; filled symbol, volatile emission; no symbol, no or conflicting data available. The online version of this article includes the following source data for figure 3: Source data 1. List of HDR sequences used for phylogenetic analysis in Figure 3. Source data 2. Phylogenetic tree of HDRs in Newick format. Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 6 of 16 Short report Biochemistry and Chemical Biology Plant Biology proteotypic peptides exist across all heterologous HDRs, quantitative comparison of HDR protein levels across strains is not possible. However, we confirmed that all tested HDRs were strongly over- expressed (Figure 2—figure supplement 2c), and that there was no correlation between HDR abun- dance and the DMAPP:IPP ratio (rho = 0.488, data not shown). Taken together, these data demonstrate that different HDR enzymes produce vastly different DMAPP:IPP ratios, with some plant HDRs producing a ratio significantly shifted towards more DMAPP than previously recognized. To test whether an increased in vivo DMAPP:IPP ratio would favour isoprene production, we replaced the lycopene pathway with an overexpressed isoprene synthase (IspS) as a metabolic sink. A high DMAPP:IPP ratio was indeed closely associated with isoprene production (Figure 2b). To confirm that differences in DMAPP:IPP ratios are robust when changing from lycopene (C40) to iso- prene (C5) production, we compared selected HDR product ratios with both downstream metabolic sinks (Figure 2c). While the absolute values shifted towards DMAPP (left y-axis; lycopene requires 6 IPP and 2 DMAPP) or IPP (right y-axis; isoprene is made only from DMAPP) depending on down- stream requirements, the relative difference between HDRs remained similar, demonstrating that our experimental setup captures representative differences between the enzymes. Isoprene was not produced in the presence of Theobroma cacao, Arabidopsis thalianaor E. coli HDR (all species that do not emit short-chain isoprenoids), presumably because the available DMAPP was insufficient for IspS to compete with downstream enzymes (Figure 2b). All HDRs from isopren- oid-emitting species enabled isoprene production, supporting our hypothesis. Interestingly, a high DMAPP:IPP ratio and high isoprene production was also observed with HDRs from P. persica and R. communis, species that emit some monoterpenes but not isoprene (Wiedinmyer et al., 2020; Kadri et al., 2011). PpHDR and RcHDR have high (>87%) sequence identity with HDR proteins from high isoprene-emitting species P. trichocarpa and Hevea brasiliensis, respectively (Figure 3), but R. communis and P. persica do not have an isoprene synthase (Table 1). Together, these data suggest that HDR from different plant species has adapted to produce dif- fering ratios of DMAPP to IPP, and that an increased DMAPP:IPP ratio is an important prerequisite for production of isoprene and perhaps other non-essential, short-chain isoprenoids. Our data indi- cate that a high DMAPP:IPP ratio is a necessary, but not a sufficient requirement for volatile isopren- oid emission. This places HDR at a key junction in the evolution of isoprene emission, a trait that appeared and disappeared several times across the plant kingdom (Dani et al., 2014). Picea sitchensis (Sitka spruce) is a coniferous gymnosperm that emits both isoprene and monoter- penes (Hayward et al., 2004), but contrary to our expectation PsHDR1 produced the highest rela- tive amount of IPP and showed very low isoprene production in E. coli (Figure 2a and b). Recently, the HDR from another gymnosperm, Ginkgo biloba (GbHDR1), was shown to produce an even lower DMAPP to IPP ratio in vitro (Shin et al., 2017). Most sequenced gymnosperms have two or more HDR isoforms which fall into two distinct classes based on sequence similarity (Kim et al., 2008; Fig- ure 3). Interestingly, transcriptional studies (Celedon et al., 2017; Kim et al., 2009) suggest that gymnosperm Type II HDRs are particularly abundant at the site of monoterpene-rich resin formation and are generally expressed at higher levels than Type I HDRs (Celedon et al., 2017) (such as PsHDR1 and GbHDR1). It was therefore tempting to speculate that HDR adaptation in gymnosperms has resulted in paralogues with complementary functions: Type I HDRs, which primarily produce IPP, show basal expression throughout the plant, and are important for long-chain isoprenoid produc- tion; and Type II HDRs, which primarily produce DMAPP and are expressed where short-chain iso- prenoids are made. This prompted us to investigate the Type II HDR from P. sitchensis (Figure 2d– f). PsHDR2 failed in our initial complementation assay (data not shown), most likely due to toxicity as no metabolic sink was present for IPP/DMAPP. Indeed, even in the presence of a sink, overexpres- sion of PsHDR2 reduced E. coli growth rate by about 50% (Figure 2f), a level of toxicity exceeding that of other high DMAPP-producing HDRs. Interestingly, PsHDR2 produced a > 10 fold excess of DMAPP over IPP, while PsHDR1 had a ratio shifted towards more IPP (DMAPP:IPP = 0.447 +/- 0.19; Figure 2d). PsHDR2 also enabled higher isoprene production than PsHDR1 (Figure 2e), albeit at a lower yield than the other high DMAPP-producing enzymes, which is most likely an effect of the high toxicity in E. coli. The complementary product ratios of PsHDR1 and PsHDR2 strongly suggest functional specialization of these genes, making them paralogues in P. sitchensis. While many plants encode more than one HDR gene (Figure 3), these homologues are often closely related and thus likely arose from relatively recent large-scale genome duplications Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 7 of 16 Short report Biochemistry and Chemical Biology Plant Biology (Saladié et al., 2014). In gymnosperms, the two HDR homologues are phylogenetically more distant (Figure 3) and likely define functionally specialised paralogues. Hence, we propose that two differ- ent strategies might have been employed to adapt HDR to isoprenoid production spectra: either using a single HDR and shifting the DMAPP:IPP ratio to allow production of specific isoprenoid pro- files (Figure 2a), or having two functionally distinct HDRs each dedicated to the synthesis of one iso- mer (Figure 2d). Whether adaptation of HDR is a result of a change in the demand for DMAPP, or whether it is a driver of its release as isoprene and other volatile isoprenoids, is a fascinating ques- tion that remains to be answered. The discovery of HDR enzymes with different product ratios has important implications for heter- ologous production of industrially valuable isoprenoids such as biofuels, fragrances and pharmaceut- icals (Vickers, 2015) in engineered microorganisms. We have shown that only certain HDR enzymes enable production of isoprene in our engineered E. coli, and our data indicate that the choice of HDR is important to ensure availability of DMAPP and IPP at appropriate relative concentrations to achieve balanced pathway flux towards the product of interest and to avoid DMAPP toxicity. The presented LC-MS/MS method for separation and absolute quantification of the two isomers (Fig- ure 2—figure supplement 3) proved crucial for our discovery, and will enable a deeper understand- ing of the processes regulating isoprenoid biosynthesis in nature and biotechnology. Demands from downstream metabolism may determine IPP and DMAPP requirements, and could form an evolutionary driver for enzymatic activities that impact their ratio. Our data suggest that the adaptation of HDR to generate different DMAPP:IPP ratios allows for the production of large amounts of short-chain isoprenoids in certain species or tissues. Our findings illuminate the molecu- lar mechanism underlying how plants emit isoprene and suggest a central role for HDR in determin- ing the spectrum of isoprenoids produced by plants, including isoprenoid BVOCs. Unravelling the mechanism by which plants distribute carbon between volatile and non-volatile isoprenoids will help resolve the complex interplay between BVOC emissions, land-use management and climate change. Materials and methods Key resources table Reagent type (species) or Source or Additional resource Designation reference Identifiers information Gene ispH/HDR NCBI ‘Gene’ Gene_ID:944777; hydroxymethylbutenyl (Escherichia EcoGene:EG11081; diphosphate coli) ECK0030; lytB reductase Strain, strain Escherichia ATCC ATCC:9637 obtained from background coli W L. Nielsen lab, (Escherichia coli) Australia Genetic reagent E. coli WDcscR, This paper and PMID: 21782859 knockout of cscR, (Escherichia coli) lacZ::PtDXS, (Arifin et al., 2011) knock-in of PtDXS arsB::PaISPS and PaISPS Genetic reagent E. coli WDcscR, This paper and knock-in of MVA (Escherichia coli) lacZ::MVA, DispH PMID: 11115399 pathway, knockout (Campos et al., 2001) of ispH Genetic DXS NCBI ‘Reference XP_006378082.1 Deoxyxylulose reagent Sequence’ phosphate (Populus synthase, gene was trichocarpa) truncated for expression in E. coli Genetic reagent ISPS(del2-52, Patent WO2012058494 Isoprene synthase (Populus alba) A3T,L70R,S288C) (Beck et al., 2011) (Genbank:EF638224) variant, truncated and mutated Recombinant pLacZ-KIKO PMID: 23799955 Addgene:46764 used to integrate DNA reagent (cm) plasmid (Sabri et al., 2013) PtDXS into the genome Continued on next page Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 8 of 16 Short report Biochemistry and Chemical Biology Plant Biology Continued Reagent type (species) or Source or Additional resource Designation reference Identifiers information Recombinant pArsBKIKO PMID: 23799955 (Sabri et al., 2013) Addgene:46763 used to integrate DNA reagent (cm) plasmid PaISPS into the genome Recombinant pT-HDR plasmids This paper derived from all HDR genes were DNA reagent pTrc99a cloned into this expression vector Recombinant pAC-LYC04 PMID: 7919981 DNA reagent (Cunningham et al., 1994) Recombinant Ricinus communis Genbank MH605331 HDR protein DNA reagent HDR expression XP_002519102.1 plasmid Recombinant Populus trichocarpa Genbank MH605329 HDR protein DNA reagent HDR 1 expression ACD70402 plasmid Recombinant Populus trichocarpa Genbank MH605330 HDR protein DNA reagent HDR 2 expression PNT41333.1 plasmid Recombinant Prunus persica Genbank MH605326 HDR protein DNA reagent HDR expression XP_007199828.1 plasmid Recombinant Eucalyptus grandis Genbank MH605323 HDR protein DNA reagent HDR 1 expression XP_010028563.1 plasmid Recombinant Eucalyptus grandis Genbank MH605324 HDR protein DNA reagent HDR 2 expression XP_010047332.1 plasmid Recombinant Theobroma cacao Genbank MH605333 HDR protein DNA reagent HDR expression XP_007042717.1 plasmid Recombinant Arabidopsis thaliana Genbank MH605322 HDR protein DNA reagent HDR expression plasmid AEE86362.1 Recombinant Elaeis guineensis HDR Genbank MH605325 HDR protein DNA reagent expression plasmid XP_010909277.1 Recombinant Picea sitchensis HDR 1 Genbank MH605327 HDR protein DNA reagent expression plasmid ACN40284.1 Recombinant Picea sitchensis HDR 2 expression Genbank MH605328 HDR protein DNA reagent plasmid ACN39959.1 Recombinant Synechococcus sp. Genbank MH605332 HDR protein DNA reagent PCC 7002 HDR ACA98524.1 expression plasmid Commercial Astec Cyclobond Sigma Aldrich 20024AST HPLC column used assay or kit I2000 chiral HPLC for IPP/DMAPP column separation Chemical Isoprene Sigma Aldrich Cat. # I19551 compound, drug Chemical Isopentenyl Sigma Aldrich Cat. # I0503 compound, pyrophosphate drug Chemical Dimethylallyl Sigma Aldrich Cat. # D4287 compound, pyrophosphate drug Chemical (±)-Mevalonic Sigma Aldrich Cat. # 79849 compound, acid 5-phosphate drug Continued on next page Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 9 of 16 Short report Biochemistry and Chemical Biology Plant Biology Continued Reagent type (species) or Source or Additional resource Designation reference Identifiers information Chemical Mevalonolactone Sigma Aldrich Cat. # M4667 compound, drug Software, CLC Main Qiagen RRID:SCR_000354 algorithm Workbench Software, iTOL PMID: 27095192 https://itol.embl.de/ Interactive algorithm (Letunic and Bork, 2016) Tree of Life Chemicals and reagents Isoprene (Cat. No I19551), IPP (Ca. No I0503), DMAPP (Ca. No D4287), Isopropyl b-D-thiogalacto- side (IPTG, Cat. No I6758), (±)-Mevalonic acid 5-phosphate (MVA-P, Ca. No 79849) were purchased from Sigma Aldrich. Mevalonate (MVA) was prepared from (±)-mevalonolactone (Sigma Aldrich, Cat. No M4667) through base-catalyzed hydrolysis (Campos et al., 2001). Ammonium acetate was pur- chased from Sigma Aldrich (Ca. No 73594–25 G-F). Acetonitrile hypergrade for LC-MS LiChrosolv (Ca. No 1000292500) and Methanol hypergrade for LC-MS LiChrosolv (Ca. No 1060352500) was pur- chased from Merck Millipore. Milli-Q water was generated via a Merck Millipore Integral 3 water purification system. Gene, plasmid and E. coli strain construction E. coli Top10 (Cat. No C404050, Thermo Fischer Scientific) was used for cloning. For all other experi- ments, E. coli W (ATCC 9637) with a knock-out in the csc operon (E. coli WDcscR Arifin et al., 2011) was used. Plant HDR chloroplast targeting peptides were predicted using the ChloroP 1.1 server (http://www.cbs.dtu.dk/services/ChloroP/). Genes were truncated to remove chloroplast targeting peptides, codon-optimised for E. coli (http://idtdna.com/CodonOpt) and synthesised by Integrated DNA Technologies (Singapore). All plant genes were placed under control of the IPTG-inducible trc promoter in a pTrc99-derived (Amann et al., 1988) vector, generating the pT-HDR series of plas- mids. The DXS gene from Populus trichocarpa (Genbank Accession No. XP_006378082.1) was inte- grated into the genome using the pLacZ-KIKO(cm) vector (Sabri et al., 2013). The chloramphenicol resistance gene was removed from the genome using pCP20 (Datsenko and Wanner, 2000). The resulting strain (E. coli WDcscR, lacZ::PtDXS) was transformed with each of the pT-HDR plasmids and pAC-LYC04 (Cunningham et al., 1994) for IPP and DMAPP measurements. For isoprene production experiments, an engineered ISPS gene from Populus alba (Genbank Accession No. EF638224) was integrated into the genome of E. coli WDcscR, lacZ::PtDXS using pArsBKIKO(cm). Apart from removal of the chloroplast-targeting sequence, this gene was also engineered to contain three muta- tions to enhance specific activity: ISPS(del2-52,A3T,L70R,S288C) (Beck et al., 2011). Bacterial growth media LB medium contained 10 g/L tryptone, 5 g/L yeast extract and 10 g/L NaCl. TB medium contained 12 g/L tryptone, 24 g/L yeast extract, 0.4% (v/v) glycerol, 2 mM MgSO4, 1 mM thiamine, 17 mM KH2PO4, 7.2 mM K2HPO4. Where indicated, media were supplemented with 1 mM mevalonate and 1 mM L-arabinose for induction of the MVA pathway operon, or with 0.2% (w/v) glucose or 0.1 mM IPTG for repression or induction of the trc promoter. All cultures were grown at 37˚C with 250 rpm shaking unless stated otherwise. Complementation of the ispH/HDR knockout mutant in E. coli A partial MVA pathway under control of the arabinose-inducible PBAD promoter (Campos et al., 2001) was cloned into a pLacZ-KIKO(cm) vector and integrated into the E. coli WDcscR genome. This strain (WDcscR, lacZ::MVA) was used to knock out ispH using recombineering (Datsenko and Wanner, 2000), making growth dependent on supplementation with mevalonate and arabinose. Each pT-HDR plasmid was transformed into this strain and tested for its ability to grow in the absence of mevalonate and arabinose. Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 10 of 16 Short report Biochemistry and Chemical Biology Plant Biology Growth rate measurements Cells were grown in LB medium; glucose, mevalonate or IPTG were added where indicated. Precul- tures were grown at 37˚C with 250 rpm shaking in 96-well plates (Corning, Cat No. CLS3799) until stationary phase. Cultures were diluted to a starting optical density (OD600) of 0.05 and the growth was monitored in a microplate reader (BioTek ELx808) at 37˚C with 700 rpm double-orbital shaking, measuring OD600 every 10 min. All bacterial cultures for quantification of specific growth rates, metabolites and isoprene were grown at least in biological triplicates (from 3 single colonies of the same strain), and means +/- standard deviations are shown. Fermentations for metabolite measurements Strains harbouring the different pT-HDR plasmids and pAC-LYC04 were grown for determination of IPP and DMAPP concentrations. Chloramphenicol (30 mg L 1) and ampicillin (250 mg L 1) were added to the media for plasmid maintenance. Precultures were grown in LB medium as described above. A culture volume of 10 ml of TB medium was inoculated with an overnight preculture in 100 ml baffled flasks to a starting OD600 of 0.05. Protein expression was induced with 0.1 mM IPTG at an OD600 of 0.5. When an OD600 of 5 was reached (exponential growth phase in TB medium), cultures were harvested for metabolite quantification. Quantification of IPP and DMAPP Intracellular metabolites were quenched and extracted using a method adapted from Bongers et al. (2015). To harvest, the equivalent of 1 ml of culture of an optical density of OD600 = 5 was centri- fuged at 4˚C for 20 s at 13,000 x g, the supernatant was discarded and the pellet snap-frozen in liq- uid nitrogen. The pellet was resuspended in 95 ml of 90% acetonitrile (v/v) in water and metabolites were extracted by vortexing for 10 min at room temperature. Cell debris was removed by centrifu- gation at 4˚C for 15 min at 13,000 x g. Extracts were transferred into HPLC vials, 5 ml internal stan- dard (MVA-P) was added at a final concentration of 16 mM for analysis using liquid chromatography tandem mass spectrometry (LC-MS/MS). LC-MS/MS data were acquired on an Advance UHPLC system (Bruker Daltonics, Fremont, CA, USA) equipped with a binary pump, degasser and PAL HTC-xt autosampler (CTC Analytics AG, Swit- zerland) coupled to an EVOQ Elite triple quadrupole mass spectrometer (Bruker Daltonics, Fremont, CA, USA). Separation of the structural isomers IPP and DMAPP was achieved by adapting a method from Köhling et al. (2014), by injecting 5 ml onto an Astec Cyclobond I2000 chiral HPLC column (250 mm 4.6 mm; 5 mm particle size) (Sigma Aldrich) with an injection loop size of 2 mL. The column oven temperature was controlled and maintained at 35˚C throughout the acquisition and the mobile phases were as follows: 50 mM aqueous ammonium acetate (eluent A) and 90:10 (% v/v) acetoni- trile:purified water (eluent B). The mobile phase flow rate was maintained at 600 mL/min and was introduced directly into the mass spectrometer with no split. The mobile phase gradient profile was as follows: Starting condition 100% eluent B, 0.0–1.0 min: 100% B to 25% B, 1.0–22.0 min: 25% B, 22.0–22.5 min: 25% B to 0% B, 22.5–23.0 min: 0% B, 23.0–24.0 min: 0% B to 100% B, 24.0–30.0 min: 100% B. The mass spectrometer was controlled by MS Workstation 8.2.1 software (Bruker Daltonics) using electrospray ionization operated in negative ion mode. The following parameters were used to acquire Multiple Reaction Monitoring (MRM) data: spray voltage: 3.0 kV, cone temperature: 350˚C, cone gas flow 20, probe gas flow: 50, nebulizer gas flow: 50, heated probe temperature: 350˚C, exhaust gas: on, CID: 1.5 mTorr. The MRM scan time was set to 1000 ms for DMAPP and IPP, and 200 ms for MVA-P with standard resolution for all transitions. The collision energy (CE) was opti- mised for each transition. The quantifier was m/z 245.0 fi 79 (CE: 16 eV) and qualifier m/z 245.0fi 159 (CE: 16 eV) for both DMAPP and IPP. For the internal standard MVA-P the quantifier was m/z 227.0 fi 79 (CE: 24 eV) and qualifier m/z 227.0fi 97 (CE: 13 eV). Initial retention times (RT) were 14.1 min (MVA-P) 19.2 min (DMAPP) and 23.6 min (IPP) but shifted to less retention as the column presumably deteriorated during the runs. For quality control (QC) and to ensure correct peak inte- gration a 1 mM standard DMAPP/IPP mix was injected every 12th sample. The RTs decreased in a lin- ear fashion from the first 1 mM QC standard to the last QC standard (n = 52) with 0.024 min, 0.044 min, and 0.061 min per injection for MVA-P, DMAPP, and IPP respectively (R2 = 0.990, R2 = 0.991, R2 = 0.989). Analytes were integrated manually. Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 11 of 16 Short report Biochemistry and Chemical Biology Plant Biology To obtain quantitative data, a matrix-matched internal standard calibration was used. Analyte stock solutions were prepared in 90% (v/v) acetonitrile and were diluted with blank matrix extract, extracted with 90:10 (% v/v) acetonitrile:Milli-Q water). The internal standard was added to the final HPLC vial at a concentration of 16 mM. The calibration curve ranged from 0.25 mM to 10 mM with R2 values of 0.968 and 0.981 for DMAPP and IPP, respectively. For both calibration curves a 1/x2 weighting factor was applied. Sample concentrations lower than the lowest standard were obtained through extrapolation of the calibration curve. The limit of quantification (LOQ) was approximated, using the lowest standard as reference (0.25 mM, n = 4), as 10x the signal-to-noise ratio. The LOQ estimate was 0.033 and 0.045 mM for DMAPP and IPP respectively. The 1 mM QC standard (n = 8) recovery was 85.6 (RSD 18.7%) and 93.2 (RSD 15.9%) for DMAPP and IPP respectively. Additionally, five standards with different DMAPP/IPP ratios were injected to verify the ratio accuracy. DMAPP: IPP ratios fortified were 10, 2, 1, 0.5, and 0.1, while ratios found were 11.1, 1.8, 0.96, 0.56, and 0.10 (bias ranging from 9.9 to 12.5% with a mean bias of 1.9%). Protein quantification Cells were harvested for proteomics analyses at the same time point as metabolomics samples. Cell pellets corresponding to 1 ml of cultures of an optical density of OD600 = 5 were processed accord- ing to Rennig et al. (2019), both regarding preparation of samples, the applied gradient on the CapLC system and the settings for Orbitrap HF_X mass spectrometer. Here, a total of 1 mg of pepti- des/sample was injected into the mass spectrometer. After acquisition the raw files were analysed using Proteome Discoverer 2.3 (P.D. 2.3) in order to identify and quantify detected proteins. The fol- lowing software settings were used: Fixed modification: Carbamidomethyl (C) and Variable modifica- tions: oxidation of methionine residues. First search mass tolerance 10 ppm and a MS/MS tolerance of 0.02 Da., trypsin as proteolytic enzyme and allowing two missed cleavages. FDR was set at 0.1%. For match between runs the DRT was set to 0.2 min and the minimum peptide length was set to 7. As database for the searches the E. coli W proteome (UP000008525) was used combined with a con- taminant database (cRAP) and the sequences of heterologous HDRs (see Table 1) and lycopene pro- duction proteins Idi (Genbank ID AAC32208.1), CrtE (WP026199135.1), CrtI (AAA64981.1), and CrtB (WP020503292.1). Normalization of the data across samples was done with P.D. 2.3. using total pep- tide amount, meaning all identified peptides in the individual samples are used for normalization, while using one file as master file to which all other counts are normalized. For quantification only unique peptides were used, and for all HDR proteins, hits were manually inspected to ensure correct identification and quantification. HDR overexpression strains were compared by analysing normal- ized peptide counts using one-way analysis of variance (ANOVA) or Welch’s ANOVA test in case of unequal variances, respectively. Where reported, p-values were adjusted for multiple comparison testing using Dunnett’s method, n  3 biological replicates. Isoprene production The different pT-HDR plasmids were transformed into E. coli WDcscR, lacZ::Pt-DXS, arsB::PaISPS (del2-52,A3T,L70R,S288C). All growth media contained 250 mg L 1 ampicillin for plasmid mainte- nance. Strains were grown in LB medium until stationary phase, then diluted in 0.5 ml TB medium containing 0.1 mM IPTG to a starting OD600 of 0.1, and grown at 30˚C, with 250 rpm shaking. Cul- tures were grown in 20 ml sealed gas chromatography vials and isoprene was quantified after 48 hr as described previously (Vickers et al., 2015). Sequence alignments and generation of phylogenetic trees HDR protein sequences were downloaded from the results of a BLASTP search with A. thaliana HDR against land plants (taxid: 3193), manually removing identical duplicates and obvious pseudogenes (deletions or mutations in highly conserved regions). Sequences were truncated to remove N-termi- nal chloroplast targeting sequences and aligned using CLC Main Workbench (Qiagen). HDR phylo- genetic tree (unrooted) was generated using maximum likelihood phylogeny, neighbour-joining method, WAG protein substitution model, and bootstrap analysis with 100 replicates, also in CLC Main Workbench. Phylogenetic trees were visualised using Interactive Tree of Life (iTOL) v3 (Letunic and Bork, 2016). Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 12 of 16 Short report Biochemistry and Chemical Biology Plant Biology Acknowledgements Research at the University of Queensland was funded by an Australian Research Council grant to LKN and CEV. Research at the Center for Biosustainability was supported by The Novo Nordisk Foundation under NFF grant number NNF10CC1016517. JPG was supported by a Marie Curie Inter- national outgoing Fellowship within the 7th European Community Framework Programme. CEV was supported by Queensland Government Smart Futures and Accelerate Fellowships. Metabolomics Australia is part of the Bioplatforms Australia network, funded through the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS). The authors would like to thank James Behrendorff for valuable feedback on this work. Additional information Funding Funder Grant reference number Author Australian Research Council DP140103514 Lars K Nielsen Claudia E Vickers Novo Nordisk Foundation NNF10CC1016517 Lars Schrübbers Tune Wulff Morten O A Sommer Lars K Nielsen Mareike Bongers Marie Skłodowska-Curie Ac- FP7-PEOPLE-2013-IOF. Jordi Perez-Gil tions Project: 623679 Department of Education, National Collaborative Mark P Hodson Australian Government Research Infrastructure Lars K Nielsen Strategy (NCRIS) Queensland Government Accelerate Fellowship Claudia E Vickers The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. Author contributions Mareike Bongers, Conceptualization, Data curation, Investigation, Visualization, Methodology, Proj- ect administration; Jordi Perez-Gil, Investigation, Methodology; Mark P Hodson, Lars Schrübbers, Data curation, Methodology; Tune Wulff, Formal analysis, Performed and analysed the proteomics work; Morten OA Sommer, Resources, Funding acquisition; Lars K Nielsen, Conceptualization, Resources, Supervision, Funding acquisition; Claudia E Vickers, Conceptualization, Supervision, Funding acquisition, Investigation Author ORCIDs Mareike Bongers https://orcid.org/0000-0003-4739-3852 Jordi Perez-Gil https://orcid.org/0000-0002-5632-9556 Mark P Hodson https://orcid.org/0000-0002-5436-1886 Tune Wulff https://orcid.org/0000-0002-8822-1048 Lars K Nielsen https://orcid.org/0000-0001-8191-3511 Claudia E Vickers https://orcid.org/0000-0002-0792-050X Decision letter and Author response Decision letter https://doi.org/10.7554/eLife.48685.sa1 Author response https://doi.org/10.7554/eLife.48685.sa2 Additional files Supplementary files . Transparent reporting form Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 13 of 16 Short report Biochemistry and Chemical Biology Plant Biology Data availability All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2 and 3. The following datasets were generated: References Adam P, Hecht S, Eisenreich W, Kaiser J, Grawert T, Arigoni D, Bacher A, Rohdich F. 2002. Biosynthesis of terpenes: studies on 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate reductase. PNAS 99:12108–12113. DOI: https://doi.org/10.1073/pnas.182412599 Altincicek B, Kollas A, Eberl M, Wiesner J, Sanderbrand S, Hintz M, Beck E, Jomaa H. 2001. LytB, a novel gene of the 2-C-methyl-D-erythritol 4-phosphate pathway of isoprenoid biosynthesis in Escherichia coli. FEBS Letters 499:37–40. DOI: https://doi.org/10.1016/s0014-5793(01)02516-9, PMID: 11418107 Altincicek B, Duin EC, Reichenberg A, Hedderich R, Kollas AK, Hintz M, Wagner S, Wiesner J, Beck E, Jomaa H. 2002. LytB protein catalyzes the terminal step of the 2-C-methyl-D-erythritol-4-phosphate pathway of isoprenoid biosynthesis. FEBS Letters 532:437–440. DOI: https://doi.org/10.1016/s0014-5793(02)03726-2, PMID: 12482608 Amann E, Ochs B, Abel KJ. 1988. Tightly regulated tac promoter vectors useful for the expression of unfused and fused proteins in Escherichia coli. Gene 69:301–315. DOI: https://doi.org/10.1016/0378-1119(88)90440-4, PMID: 3069586 Argout X, Fouet O, Wincker P, Gramacho K, Legavre T, Sabau X, Risterucci AM, Da Silva C, Cascardo J, Allegre M, Kuhn D, Verica J, Courtois B, Loor G, Babin R, Sounigo O, Ducamp M, Guiltinan MJ, Ruiz M, Alemanno L, et al. 2008. Towards the understanding of the cocoa transcriptome: production and analysis of an exhaustive dataset of ESTs of Theobroma cacao L. generated from various tissues and under various conditions. BMC Genomics 9:512. DOI: https://doi.org/10.1186/1471-2164-9-512, PMID: 18973681 Arifin Y, Sabri S, Sugiarto H, Krömer JO, Vickers CE, Nielsen LK. 2011. Deletion of cscR in Escherichia coli W improves growth and poly-3-hydroxybutyrate (PHB) production from sucrose in fed batch culture. Journal of Biotechnology 156:275–278. DOI: https://doi.org/10.1016/j.jbiotec.2011.07.003, PMID: 21782859 Beck ZQ, Estell DA, Rife CL, Wells DH, Miller JV. 2011. Isoprene synthase variants for improved production of isoprene. International Patent. WO2012058494. https://patentscope.wipo.int/search/en/detail.jsf?docId= WO2012058494. Bohlmann J, Martin D, Oldham NJ, Gershenzon J. 2000. Terpenoid secondary metabolism in Arabidopsis thaliana: cDNA Cloning, Characterization, and Functional Expression of a Myrcene/(E)-b-Ocimene Synthase. Archives of Biochemistry and Biophysics 375:261–269. DOI: https://doi.org/10.1006/abbi.1999.1669 Bongers M, Chrysanthopoulos PK, Behrendorff JBYH, Hodson MP, Vickers CE, Nielsen LK. 2015. Systems analysis of methylerythritol-phosphate pathway flux in E. coli: insights into the role of oxidative stress and the validity of lycopene as an isoprenoid reporter metabolite. Microbial Cell Factories 14:193. DOI: https://doi.org/ 10.1186/s12934-015-0381-7 BRENDA. 2020. Enzyme Database. http://www.brenda-enzymes.org/ [Accessed June 8, 2018]. Campos N, Rodrı́guez-concepción M, Sauret-güeto S, Gallego F, Lois L-M, Boronat A. 2001. Escherichia coli engineered to synthesize isopentenyl diphosphate and dimethylallyl diphosphate from mevalonate: a novel system for the genetic analysis of the 2-C-methyl-d-erythritol 4-phosphate pathway for isoprenoid biosynthesis. Biochemical Journal 353:59–67. DOI: https://doi.org/10.1042/bj3530059 Celedon JM, Yuen MMS, Chiang A, Henderson H, Reid KE, Bohlmann J. 2017. Cell-type- and tissue-specific transcriptomes of the white spruce (Picea glauca) bark unmask fine-scale spatial patterns of constitutive and induced conifer defense. The Plant Journal 92:710–726. DOI: https://doi.org/10.1111/tpj.13673, PMID: 2 8857307 Chen F, Ro D-K, Petri J, Gershenzon J, Bohlmann J, Pichersky E, Tholl D. 2004. Characterization of a Root- Specific Arabidopsis terpene synthase responsible for the formation of the volatile monoterpene 1,8-Cineole. Plant Physiology 135:1956–1966. DOI: https://doi.org/10.1104/pp.104.044388 Claeys M, Graham B, Vas G, Wang W, Vermeylen R, Pashynska V, Cafmeyer J, Guyon P, Andreae MO, Artaxo P, Maenhaut W. 2004. Formation of secondary organic aerosols through photooxidation of isoprene. Science 303: 1173–1176. DOI: https://doi.org/10.1126/science.1092805, PMID: 14976309 Cunningham FX, Sun Z, Chamovitz D, Hirschberg J, Gantt E. 1994. Molecular structure and enzymatic function of lycopene cyclase from the Cyanobacterium synechococcus sp strain PCC7942. The Plant Cell 6:1107–1121. DOI: https://doi.org/10.1105/tpc.6.8.1107, PMID: 7919981 Dani KG, Jamie IM, Prentice IC, Atwell BJ. 2014. Evolution of isoprene emission capacity in plants. Trends in Plant Science 19:439–446. DOI: https://doi.org/10.1016/j.tplants.2014.01.009, PMID: 24582468 Datsenko KA, Wanner BL. 2000. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. PNAS 97:6640–6645. DOI: https://doi.org/10.1073/pnas.120163297, PMID: 10829079 Fehsenfeld F, Calvert J, Fall R, Goldan P, Guenther AB, Hewitt CN, Lamb B, Liu S, Trainer M, Westberg H, Zimmerman P. 1992. Emissions of volatile organic compounds from vegetation and the implications for atmospheric chemistry. Global Biogeochemical Cycles 6:389–430. DOI: https://doi.org/10.1029/92GB02125 George KW, Thompson MG, Kim J, Baidoo EEK, Wang G, Benites VT, Petzold CJ, Chan LJG, Yilmaz S, Turhanen P, Adams PD, Keasling JD, Lee TS. 2018. Integrated analysis of isopentenyl pyrophosphate (IPP) toxicity in Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 14 of 16 Short report Biochemistry and Chemical Biology Plant Biology isoprenoid-producing Escherichia coli. Metabolic Engineering 47:60–72. DOI: https://doi.org/10.1016/j.ymben. 2018.03.004 Granier C, Pétron G, Müller J-F, Brasseur G. 2000. The impact of natural and anthropogenic hydrocarbons on the tropospheric budget of carbon monoxide. Atmospheric Environment 34:5255–5270. DOI: https://doi.org/10. 1016/S1352-2310(00)00299-5 Hayward S, Tani A, Owen SM, Hewitt CN. 2004. Online analysis of volatile organic compound emissions from sitka spruce (Picea sitchensis). Tree Physiology 24:721–728. DOI: https://doi.org/10.1093/treephys/24.7.721, PMID: 15123443 Jonnalagadda V, Toth K, Richard JP. 2012. Isopentenyl diphosphate isomerase catalyzed reactions in D2O: product release limits the rate of this sluggish enzyme-catalyzed reaction. Journal of the American Chemical Society 134:6568–6570. DOI: https://doi.org/10.1021/ja302154k, PMID: 22471428 Kadri A, Gharsallah N, Damak M, Gdoura R. 2011. Chemical composition and in vitro antioxidant properties of essential oil of ricinus communis L. Journal of Medicinal Plant Research 5:1466–1470. DOI: https://doi.org/10. 5897/JMPR Kim SM, Kuzuyama T, Kobayashi A, Sando T, Chang YJ, Kim SU. 2008. 1-Hydroxy-2-methyl-2-(E)-butenyl 4- diphosphate reductase (IDS) is encoded by multicopy genes in gymnosperms Ginkgo biloba and pinus taeda. Planta 227:287–298. DOI: https://doi.org/10.1007/s00425-007-0616-x, PMID: 17763867 Kim YB, Kim SM, Kang MK, Kuzuyama T, Lee JK, Park SC, Shin SC, Kim SU. 2009. Regulation of resin acid synthesis in pinus densiflora by differential transcription of genes encoding multiple 1-deoxy-D-xylulose 5- phosphate synthase and 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate reductase genes. Tree Physiology 29: 737–749. DOI: https://doi.org/10.1093/treephys/tpp002, PMID: 19203978 Köhling R, Meier R, Schönenberger B, Wohlgemuth R. 2014. Analysis of Isoprenoid Pathway Metabolites by LC- MS Buchs, Switzerland:: Biofiles, Sigma-Aldrich. https://www.sigmaaldrich.com/technical-documents/articles/ biofiles/isoprenoid-pathway-metabolites.html. Letunic I, Bork P. 2016. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Research 44:W242–W245. DOI: https://doi.org/10.1093/nar/ gkw290, PMID: 27095192 Loreto F, Fares S. 2013. Biogenic volatile organic compounds and their impacts on biosphere-atmosphere interactions. Developments in Environmental Science 13:57–75. DOI: https://doi.org/10.1016/B978-0-08- 098349-3.00004-9 Monson RK, Jones RT, Rosenstiel TN, Schnitzler JP. 2013. Why only some plants emit isoprene. Plant, Cell & Environment 36:503–516. DOI: https://doi.org/10.1111/pce.12015, PMID: 22998549 Myburg AA, Grattapaglia D, Tuskan GA, Hellsten U, Hayes RD, Grimwood J, Jenkins J, Lindquist E, Tice H, Bauer D, Goodstein DM, Dubchak I, Poliakov A, Mizrachi E, Kullan AR, Hussey SG, Pinard D, van der Merwe K, Singh P, van Jaarsveld I, et al. 2014. The genome of Eucalyptus grandis. Nature 510:356–362. DOI: https://doi. org/10.1038/nature13308, PMID: 24919147 Peñuelas J, Staudt M. 2010. BVOCs and global change. Trends in Plant Science 15:133–144. DOI: https://doi. org/10.1016/j.tplants.2009.12.005, PMID: 20097116 Poisson N, Kanakidou M, Crutzen PJ. 2000. Impact of non-methane hydrocarbons on tropospheric chemistry and the oxidizing power of the global Troposphere: 3-dimensional modelling results. Journal of Atmospheric Chemistry 36:157–230. DOI: https://doi.org/10.1023/A:1006300616544 Pulido P, Perello C, Rodriguez-Concepcion M. 2012. New insights into plant isoprenoid metabolism. Molecular Plant 5:964–967. DOI: https://doi.org/10.1093/mp/sss088, PMID: 22972017 Rennig M, Mundhada H, Wordofa GG, Gerngross D, Wulff T, Worberg A, Nielsen AT, Nørholm MHH. 2019. Industrializing a bacterial strain for l-Serine production through translation initiation optimization. ACS Synthetic Biology 8:2347–2358. DOI: https://doi.org/10.1021/acssynbio.9b00169, PMID: 31550142 Rohdich F, Hecht S, Gärtner K, Adam P, Krieger C, Amslinger S, Arigoni D, Bacher A, Eisenreich W. 2002. Studies on the nonmevalonate terpene biosynthetic pathway: metabolic role of IspH (LytB) protein. PNAS 99: 1158–1163. DOI: https://doi.org/10.1073/pnas.032658999, PMID: 11818558 Rohdich F, Zepeck F, Adam P, Hecht S, Kaiser J, Laupitz R, Gräwert T, Amslinger S, Eisenreich W, Bacher A, Arigoni D. 2003. The deoxyxylulose phosphate pathway of isoprenoid biosynthesis: studies on the mechanisms of the reactions catalyzed by IspG and IspH protein. PNAS 100:1586–1591. DOI: https://doi.org/10.1073/pnas. 0337742100, PMID: 12571359 Sabri S, Steen JA, Bongers M, Nielsen LK, Vickers CE. 2013. Knock-in/Knock-out (KIKO) vectors for rapid integration of large DNA sequences, including whole metabolic pathways, onto the Escherichia coli chromosome at well-characterised loci. Microbial Cell Factories 12:60. DOI: https://doi.org/10.1186/1475- 2859-12-60, PMID: 23799955 Saladié M, Wright LP, Garcia-Mas J, Rodriguez-Concepcion M, Phillips MA. 2014. The 2-C-methylerythritol 4- phosphate pathway in melon is regulated by specialized isoforms for the first and last steps. Journal of Experimental Botany 65:5077–5092. DOI: https://doi.org/10.1093/jxb/eru275, PMID: 25013119 Sharkey TD, Yeh S, Wiberley AE, Falbel TG, Gong D, Fernandez DE. 2005. Evolution of the isoprene biosynthetic pathway in kudzu. Plant Physiology 137:700–712. DOI: https://doi.org/10.1104/pp.104.054445, PMID: 15653 811 Sharkey TD, Loreto F. 1993. Water stress, temperature, and light effects on the capacity for isoprene emission and photosynthesis of kudzu leaves. Oecologia 95:328–333. DOI: https://doi.org/10.1007/BF00320984, PMID: 28314006 Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 15 of 16 Short report Biochemistry and Chemical Biology Plant Biology Shin BK, Kim M, Han J. 2017. Exceptionally high percentage of IPP synthesis by Ginkgo biloba IspH is mainly due to phe residue in the active site. Phytochemistry 136:9–14. DOI: https://doi.org/10.1016/j.phytochem.2017.01. 012, PMID: 28139297 Sindelarova K, Granier C, Bouarar I, Guenther A, Tilmes S, Stavrakou T, Müller J-F, Kuhn U, Stefani P, Knorr W. 2014. Global data set of biogenic VOC emissions calculated by the MEGAN model over the last 30 years. Atmospheric Chemistry and Physics 14:9317–9341. DOI: https://doi.org/10.5194/acp-14-9317-2014 Thompson AM. 1992. The oxidizing capacity of the earth’s atmosphere: probable past and future changes. Science 256:1157–1165. DOI: https://doi.org/10.1126/science.256.5060.1157, PMID: 1317061 Tritsch D, Hemmerlin A, Bach TJ, Rohmer M. 2010. Plant isoprenoid biosynthesis via the MEP pathway: in vivo IPP/DMAPP ratio produced by (E)-4-hydroxy-3-methylbut-2-enyl diphosphate reductase in tobacco BY-2 cell cultures. FEBS Letters 584:129–134. DOI: https://doi.org/10.1016/j.febslet.2009.11.010, PMID: 19903472 Tuskan GA. 2006. The genome of black cottonwood, Populus trichocarpa. Science 313:1596–1604. DOI: https:// doi.org/10.1126/science.1128691 Verde I, Abbott AG, Scalabrin S, Jung S, Shu S, Marroni F, Zhebentyayeva T, Dettori MT, Grimwood J, Cattonaro F, Zuccolo A, Rossini L, Jenkins J, Vendramin E, Meisel LA, Decroocq V, Sosinski B, Prochnik S, Mitros T, Policriti A, et al. 2013. The high-quality draft genome of peach (Prunus persica) identifies unique patterns of genetic diversity, domestication and genome evolution. Nature Genetics 45:487–494. DOI: https:// doi.org/10.1038/ng.2586, PMID: 23525075 Vickers CE, Gershenzon J, Lerdau MT, Loreto F. 2009. A unified mechanism of action for volatile isoprenoids in plant abiotic stress. Nature Chemical Biology 5:283–291. DOI: https://doi.org/10.1038/nchembio.158, PMID: 1 9377454 Vickers CE, Bongers M, Liu Q, Delatte T, Bouwmeester H. 2014. Metabolic engineering of volatile isoprenoids in plants and microbes. Plant, Cell & Environment 37:1753–1775. DOI: https://doi.org/10.1111/pce.12316, PMID: 24588680 Vickers CE, Bongers M, Bydder SF, Chrysanthopoulos P, Hodson MP. 2015. Protocols for the Production and Analysis of Isoprenoids in Bacteria and Yeast . In: McGenity T. J, Timmis K. N, Nogales Fernández B (Eds). Hydrocarbon and Lipid Microbiology Protocols: Synthetic and Systems Biology - Applications. Berlin Heidelberg: Springer. p. 23–52. DOI: https://doi.org/10.1007/8623_2015_107 Vickers CE. 2015. Production of Industrially Relevant Isoprenoid Compounds in Engineered Microbes. In: Microorganisms in Biorefineries. 26 Berlin, Heidelberg: Springer. p. 303–334. DOI: https://doi.org/10.1007/ 978-3-662-45209-7_11 Wennberg PO, Bates KH, Crounse JD, Dodson LG, McVay RC, Mertens LA, Nguyen TB, Praske E, Schwantes RH, Smarte MD, St Clair JM, Teng AP, Zhang X, Seinfeld JH. 2018. Gas-Phase reactions of isoprene and its major oxidation products. Chemical Reviews 118:3337–3390. DOI: https://doi.org/10.1021/acs.chemrev.7b00439, PMID: 29522327 Wiedinmyer C, Guenther A, Harley P, Hewitt N, Geron C, Artaxo P, Steinbrecher R, Rasmussen R, Biosphere - Atmosphere Interactions Group (BAI). 2020. Biogenic volatile organic compounds (BVOC) Data. National Center for Atmospheric Research. Identifier: BVOC. Wilkinson MJ, Owen SM, Possell M, Hartwell J, Gould P, Hall A, Vickers C, Nicholas Hewitt C. 2006. Circadian control of isoprene emissions from oil palm (Elaeis guineensis). The Plant Journal : For Cell and Molecular Biology 47:960–968. DOI: https://doi.org/10.1111/j.1365-313X.2006.02847.x, PMID: 16899082 Xie X, Kirby J, Keasling JD. 2012. Functional characterization of four sesquiterpene synthases from ricinus communis (castor bean). Phytochemistry 78:20–28. DOI: https://doi.org/10.1016/j.phytochem.2012.02.022, PMID: 22459969 Bongers et al. eLife 2020;9:e48685. DOI: https://doi.org/10.7554/eLife.48685 16 of 16