Biosynthesis and Bioactivity of Anti-Inflammatory Triterpenoids in Calendula officinalis(pot marigold)

Biosynthesis and Bioactivity of Anti-Inflammatory Triterpenoids in Calendula officinalis (pot marigold) | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Biosynthesis and Bioactivity of Anti-Inflammatory Triterpenoids in Calendula officinalis (pot marigold) View ORCID Profile D Golubova , View ORCID Profile M Salmon , View ORCID Profile H Su , View ORCID Profile C Tansley , View ORCID Profile GG Kaithakottil , View ORCID Profile G Linsmith , View ORCID Profile S Schudoma , View ORCID Profile D Swarbreck , View ORCID Profile MA O’Connell , View ORCID Profile NJ Patron doi: https://doi.org/10.1101/2025.01.11.632544 D Golubova 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ 2 School of Chemistry, Pharmacy and Pharmacology, University of East Anglia , Norwich, NR4 7TJ Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for D Golubova M Salmon 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for M Salmon For correspondence: melissa.salmon{at}earlham.ac.uk m.oconnell{at}uea.ac.uk njp56{at}cam.ac.uk H Su 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ 3 Department of Plant Sciences, University of Cambridge , Downing Street, Cambridge, CB2 3EA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for H Su C Tansley 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ 3 Department of Plant Sciences, University of Cambridge , Downing Street, Cambridge, CB2 3EA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for C Tansley GG Kaithakottil 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for GG Kaithakottil G Linsmith 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for G Linsmith S Schudoma 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for S Schudoma D Swarbreck 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for D Swarbreck MA O’Connell 2 School of Chemistry, Pharmacy and Pharmacology, University of East Anglia , Norwich, NR4 7TJ Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for MA O’Connell For correspondence: melissa.salmon{at}earlham.ac.uk m.oconnell{at}uea.ac.uk njp56{at}cam.ac.uk NJ Patron 1 Engineering Biology, Earlham Institute, Norwich Research Park , Norwich, NR4 7UZ 3 Department of Plant Sciences, University of Cambridge , Downing Street, Cambridge, CB2 3EA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for NJ Patron For correspondence: melissa.salmon{at}earlham.ac.uk m.oconnell{at}uea.ac.uk njp56{at}cam.ac.uk Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Plants have been central to traditional medicine for millennia, yet the precise metabolites responsible for their therapeutic properties often remain unidentified. Moreover, the low natural abundance and structural complexity of bioactive molecules can hinder their accessibility and chemical synthesis. Here, we investigate the widely reported anti-inflammatory properties of Calendula officinalis (pot marigold), an ancient medicinal herb. We confirm C16-hydroxylated triterpenoids as key contributors to the anti-inflammatory activity of C. officinalis floral extracts and uncover a novel mechanism by which they act in modulating interleukin 6 release. Through biosynthetic pathway elucidation, we demonstrate that the oxidosqualene synthase catalysing the first committed step emerged early in Asteraceae evolution and identify residues governing product specificity. Further, we functionally characterise cytochrome P450s and acyltransferases responsible for downstream modifications. By reconstructing the complete biosynthetic pathway in the heterologous plant chassis Nicotiana benthamiana , we provide a platform for production of the anti-inflammatory components. Our work highlights how integrated studies of bioactivity and biosynthesis can unlock the therapeutic potential of medicinal plants. Introduction The Asteraceae (aster) family is one of the largest families of flowering plants with an estimated 23,000 to 35,000 species 1 . Their history of use in medicine dates back thousands of years; written references to the medicinal uses of Calendula officinalis (pot marigold) were recorded by Pliny the Elder 2 . Indeed, species in the Calendula genus remained in medical use until the twentieth century. For example, until 1942, pot marigold was listed in the British Pharmacopoeia and the United States National Formulary, which provide official standards for pharmaceutical substances 3 . In the modern era, extracts of numerous Asteraceae species have been demonstrated to exhibit antibacterial, antiviral, antifungal, anti-inflammatory, and antiplasmodial bioactivities 4 . However, in only a few species has bioactivity been unequivocally associated with a specific compound. Of these, the anti-plasmodial bioactivity of artemisinin, found in the glandular trichomes of Artemisia annua L. (sweet wormwood) is perhaps the most famous 5 . Nonetheless, drawing on their history of use in traditional medicine, extracts of many Asteraceae species are commercially exploited: extracts of pot marigold are used in a wide range of skin care products. Pot marigold extracts have been reported to contain numerous compounds, most notably triterpenoids. These include oleanolic acid saponins (glucosides or glucuronides), α-amyrin, β-amyrin, lupeol, and triterpene fatty acid esters (TFAEs), of which faradiol myristate and faradiol palmitate are the most abundant 6 . Triterpenoids are one of the largest classes of secondary metabolites in plants, with more than 14,000 types of structures described 7 , many of which are bioactive and several of which are in use as vaccine adjuvants, anti-cancer drugs and food sweeteners 8 . Anti-inflammatory bioactivity has been reported for several pentacyclic triterpenes, particularly lupeol 9 and betulin 10 , which are ingredients in an FDA-approved wound-healing hydrogel, FILSUVEZ ® . Early studies observed that extracts of pot marigold, as well triterpenoids present in those extracts, could reduce oedema in mouse ear inflammation models 11 , 12 . Further studies showed that the triterpene diols faradiol and arnidiol had more anti-oedematous activity than the less-polar Ψ-taraxasterol, taraxasterol and their FAEs 13 . Pot marigold floral extracts also reduced inflammation in acute and chronic mouse models of paw oedema and sepsis 14 . These anti-inflammatory effects may be due to a variety of mechanisms. For example, pot marigold flower extracts stimulate fibroblast proliferation and migration 15 . In addition, they inhibit production of the pro-inflammatory cytokines interleukin-1 beta (IL-1β), interleukin 6 (IL-6) and tumour necrosis factor-alpha (TNF-α) in response to lipopolysaccharide (LPS) in macrophages in vitro and in vivo 16 . Furthermore, in gastric epithelial cells, fractions rich in triterpene diols and TFAEs inhibited the activity of the transcription factor NF-κB, which is a pivotal mediator of inflammatory responses and regulator of these pro-inflammatory cytokines 17 . In contrast, more recently, it was shown that floral extracts of pot marigold increased NF-κB DNA-binding and the pro-inflammatory chemokine interleukin 8 in human keratinocytes 18 . This study also reported that the pot marigold triterpenes were unable to modulate NF-κB DNA-binding, leading the authors to conclude that triterpenes play a minor role in the anti-inflammatory bioactivity of pot marigold extracts and that further studies are necessary to evaluate which constituents are responsible for this activity. Most triterpene scaffolds are biosynthesised from the linear 2,3-oxidosqualene by oxidosqualene cyclases (OSCs). These scaffolds are then decorated by various enzymes to produce the enormous diversity of triterpenoids 19 . The most abundant triterpenoids found in pot marigold are derived from the pentacyclic triterpene scaffold, Ψ-taraxasterol. To date, OSCs that produce Ψ-taraxasterol as the primary product have yet to be characterised. Enzymes identified from Taraxacum kok-saghyz, Taraxacum coreanum (Russian and Korean dandelion, respectively) 20 , 21 and Lactuca sativa (lettuce) 22 predominantly produce a related scaffold, taraxasterol, as well as limited quantities of Ψ-taraxasterol. In this manuscript, we show that faradiol fatty acid esters are a major contributor to the anti-inflammatory bioactivity of pot marigold floral extracts and provide evidence of a mechanism of action for the non-acylated diol, faradiol, that excludes part of the pathway which may not be required for the regulation of this cytokine by NF-kB. We elucidate the genetic basis of the biosynthetic pathway from pot marigold, characterising the function and evolution of each enzyme and reconstructing biosynthesis in the photosynthetic production chassis, Nicotiana benthamiana . Results The anti-inflammatory activity of C:16 hydroxylated triterpenoids To quantify the composition and distribution of triterpenes in extracts of pot marigold we conducted metabolic profiling of extracts of leaf, root, disc and ray florets using gas chromatography/mass spectrometry (GC-MS) ( Figure 1A ; Supplementary Figure 1; Supplementary Table 1) and liquid-chromatography/mass spectrometry (LC-MS) (Supplementary Figure 2). Triterpene monols and diols were identified by comparing retention times and mass fragmentation patterns with those of authentic standards and quantified using an internal reference (Supplementary Figures 3-5). Faradiol palmitate was purified by fractionation (Supplementary Figures 6-8) and the structure was confirmed by NMR (Supplementary Figures 9-14; Supplementary Tables 2-3). Triterpene fatty acid esters were exclusively found in floral tissue, with ray florets containing approximately 8-fold higher amounts of TFAEs than disc florets. In ray florets, faradiol myristate and faradiol palmitate were the most abundant TFAEs (13.18 and 12.46 mg/g dry weight respectively). Faradiol esters constituted the majority (77%) of TFAEs observed in ray florets. No TFAEs were detected in leaf or root tissue ( Figure 1A ) (Supplementary Figure 1; Supplementary Table 1). In addition, LC-MS confirmed the previously reported presence of oleanane-glucosides and glucuronides (Supplementary Figure 2). Download figure Open in new tab Figure 1. The anti-inflammatory activity of Calendula officinalis (pot marigold) floral extracts and triterpenoids. A Total ion chromatogram showing spectral peaks identified by GC-MS analysis of pot marigold leaf and ray floret tissues. Metabolite groups are highlighted as follows: triterpene monols (orange); triterpene diols (grey); triterpene fatty acid esters (magenta). Faradiol esters and their precursors are highlighted in a darker shade. Metabolite amounts were determined by peak area analysis using friedelin as an internal standard (•); details of all triterpenes detected are provided in Supplementary Figure 1 and Supplementary Table 1. B The anti-inflammatory effect of pot marigold floral extracts (50 µg/mL) on the release of TNF- α (above) and IL-6 (below) in LPS-induced human monocytic THP-1 cells. C Anti-inflammatory effects of seven fractions of pot marigold extracts on the release of IL-6 in LPS-activated THP-1 cells. Details of fractionation and analysis of fractions are provided in Supplementary Figures 6-8. D Anti-inflammatory effect of different triterpenoids (20 µM) on the release of IL-6 in LPS-activated THP-1 cells. E Effect of faradiol (20 µM) on NF-κB and STAT3 signalling pathways in LPS-induced human monocytic THP-1 cells. BAY: BAY 11-7082, (E)-3- (4-Methylphenylsulfonyl)-2-propenenitrile (positive control); DMSO (solvent control). n=4; errors bars indicate standard error; statistical significance was determined using one-way ANOVA with a Post-hoc Dunnett test to LPS+DMSO; *= p <0.0332, **= p <0.0021, ***= p <0.0002, ****= p <0.0001. To investigate the anti-inflammatory activity, the ability of extracts to inhibit the release of the pro-inflammatory cytokines, TNF-α and IL-6, in lipopolysaccharide (LPS)-activated human monocytic (THP-1) cells were assessed by enzyme-linked immunosorbent assays (ELISAs). BAY 11-7082, (E)-3-(4-methylphenylsulfonyl)-2-propenenitrile was used as a positive control. Ethyl acetate extracts of floral tissues had negligible effects on cell viability compared to the solvent control dimethyl sulfoxide (DMSO) (Supplementary Figure 15). Extracts showed a concentration-dependent repression of pro-inflammatory cytokines; 50 µg/mL extracts reduced LPS-activated TNF-α and IL-6 release by 46% and 56%, respectively ( Figure 1B ; Supplementary Table 4 and Supplementary Figure 16). To investigate the contribution of triterpenes to the bioactivity of floral extracts, the extracts were fractionated using liquid chromatography (LC) to obtain seven fractions. The major compounds detected were fatty acids (fractions 1, 2, 3 and 7), triterpene monols (fraction 4), and faradiol fatty acid esters (fractions 5 and 6) (Supplementary Figure 8). Fraction 6 (containing faradiol-FAEs) as well as fractions 1 and 7 (containing fatty acids) showed significant anti-inflammatory activity, inhibiting the release of LPS-induced IL-6 ( Figure 1C ; Supplementary Table 4). To investigate the activity of specific pot marigold triterpenes, we compared the activity of taraxasterol, Ψ-taraxasterol, arnidiol, faradiol, faradiol myristate, and faradiol palmitate. Unexpectedly, taraxasterol showed pro-inflammatory activity, enhancing LPS-induced IL-6 release. All other tested compounds (Ψ-taraxasterol, faradiol, arnidiol, faradiol myristate, faradiol palmitate and mixture of esters) displayed significant anti-inflammatory activity reducing LPS-induced IL6 release. The C:16 hydroxylated compounds (faradiol and arnidiol) demonstrated the strongest anti-inflammatory activity, and significantly inhibited LPS-induced IL6 release by 59% and 61%, respectively. No synergistic effect was noted with a combination of faradiol myristate and faradiol palmitate, compared to the activity of individual compounds ( Figure 1D ; Supplementary Table 4). For faradiol, concentration-dependent activity was observed between 5 µM and 20 µM (Supplementary Figure 16). To identify the mechanism by which faradiol regulates IL-6 production, we investigated the effect of faradiol on the phosphorylation of two transcription factors, NF-κB and STAT3, by Western blotting with primary antibodies to the phosphorylated and unphosphorylated proteins. Treatment of THP-1 cells with 20 µM of faradiol reduced phosphorylation of STAT3 but not NF-κB p65 ( Figure 1E ). Identification of candidate Ψ-taraxasterol synthases After confirming the anti-inflammatory bioactivity of faradiol and its esters, we aimed to uncover the genetic basis of their production in pot marigold. Faradiol is derived from a Ψ-taraxasterol triterpene scaffold, differing from taraxasterol only in the structure of the final E ring. Enzymes responsible for synthesizing taraxasterol have been characterised in three species of the Cichorioideae subfamily: Russian and Korean dandelions and lettuce. To identify a candidate taraxasterol/Ψ-taraxasterol synthase (TXSS), we first sequenced the pot marigold nuclear genome using PacBio HiFi reads polished with 10X linked-reads and scaffolded with Omni-C data. A detailed description of sequencing and genome assembly is provided in the Supplementary Methods. This produced an assembly of 1.3 Gb, consisting of 2,811 contigs with an N50 of 80.2 Mb and including 16 highly contiguous scaffolds over 25 Mb in length (Supplementary Table 5). A k-mer analysis showed three clear peaks consistent with an allotetraploid background. We observed low heterozygosity within haplotype pairs but significant variation between the pairs which supports an ancient hybridisation event. BUSCO (Benchmarking Universal Single-Copy Orthologs) analysis indicated most genes are duplicated with a proportion that are single-copy, indicating the genome is likely to have undergone some diploidisation (Supplementary Table 5). We also sequenced and assembled transcriptomes of leaf, disc floret and ray floret tissues harvested from pot marigold and Calendula arvensis (field marigold). T. kok-saghyz taraxasterol synthase (TkTXSS) and Artemisia annua (sweet wormwood) cycloartenol synthase (AaCAS) were used as queries to search the genome and transcriptome of pot marigold, identifying 27 candidate genes encoding OSCs (CoOSCs) . Transcripts from 16 of these genes were identified in the transcriptome data (Supplementary Tables 6-8). We next performed a phylogenetic analysis of the translated proteins of all retrieved gene sequences together with 133 previously characterised plant OSCs ( Figure 2A ; Supplementary Figure 16; Supplementary Table 9). Download figure Open in new tab Figure 2. Phylogenetic analysis of plant oxidosqualene cyclases (OSCs). A Maximum-likelihood tree of characterised plant OSCs constructed in IQTree using the JTT matrix-based model. Taraxasterol synthases (TXSSs) are highlighted in orange and mixed-amyrin synthases are highlighted in light blue (Asteraceae) and blue (non-Asteraceae) and annotated with chemical structures of their major products. A full tree showing collapsed clades (grey triangles) is provided in Supplementary Data 16 and a list of taxa and accession numbers are provided in Supplementary Table 9. Functionally characterised OSCs are shown in bold, those in red are characterised in this paper (Supplementary Figure 20). An asterisk (*) indicates likely pseudogenes. Filled grey circles indicate bootstrap supports for each node. The scale bar represents the number of substitutions per site. B Species cladogram of Asteraceae and related species with fully sequenced genomes. Filled box indicates presence of a TXSS gene in the genome or transcriptome, unfilled box indicates absence in the genome. ONS=onocerin synthase; CAS=cycloartenol synthase; PTS=poacetapetol synthase; bAS=β-amyrin synthase; MAS=mixed amyrin synthase; TXSS=taraxasterol/Ψ-taraxasterol synthase. Almost all CoOSCs were observed to be most closely related to another CoOSC, with each pair having between 77% and 92% sequence identity. Nine of these gene pairs were located in regions with conserved synteny suggesting homeology, while two gene pairs and one triplet were located adjacent to each other on the same contig (Supplementary Table 6; Supplementary Figure 18). Commonly, one of each gene pair was not expressed and comparative analysis of the intron-exon structure, sequence and conserved catalytic motifs indicated these were likely to be non-functional pseudogenes (Supplementary Tables 6-7). Exceptions were the cycloartenol synthases of which five candidates were identified, all of which were expressed (Supplementary Tables 6-7). Seven CoOSCs were in clades containing proteins involved in plant sterol biosynthesis, with the remainder belonging to clades involved in pentacyclic triterpenoid biosynthesis ( Figure 2A ; Supplementary Figure 16; Supplementary Table 9). One strongly supported clade included previously characterised TXSSs from lettuce, Russian and Korean dandelion as well as two sequences each from pot marigold, field marigold and sequences from several other Asteraceae (candidate CoTXSSs) ( Figure 2A ; Supplementary Figure 16; Supplementary Table 9). Differential expression analysis of the corresponding CoOSCs genes indicated that nine were mainly expressed in leaves, three were expressed in all tissues, and four were predominantly expressed in floral tissues, including one of the candidate CoTXSSs ; the other was not expressed (Supplementary Figure 19). TXSSs evolved in the Asteraceae from a multifunctional amyrin synthase and have been maintained in all major lineages Candidate TXSS genes were only identified in the genomes of the Asteraceae, including species from all three major Asteraceae subfamilies (Carduoideae, Cichorioideae and Asteroideae). No candidates were found in other plant lineages including the non-Asteraceae Asterales ( Figure 2 ). To characterise candidate TXSSs, we synthesised and cloned the coding sequences of genes from pot marigold ( CoTXSS ), field marigold ( CarTXSS ), Cynara cardunculus (globe artichoke; CcTXSS ), Helianthus annuus (common sunflower; HaTXSS ), Cicorium endivia (endive; CeTXSS ) , Tragopogon dubius (yellow salsify; TdTXSS ), Lactuca sativa (lettuce; LsTXSS ), Russian dandelion (TkTXSS) and Korean dandelion ( TcTXSS ) into binary expression vectors with a constitutive promoter. These constructs were transformed into Agrobacterium tumefaciens and co-infiltrated into the leaves of Nicotiana benthamiana with strains expressing a truncated HMGR (tHMGR) and a suppressor of silencing (P19). GC-MS analyses of the extracts of infiltrated leaves indicated that the primary products of all enzymes were either taraxasterol or Ψ-taraxasterol, with the ratio of these two products differing between species, which is further investigated below. All enzymes also produced trace quantities of ꞵ-amyrin and lupeol (Supplementary Figure 20). Phylogenetic analysis indicated that TXSSs are closely related to a clade containing mixed amyrin synthases (MASs) from diverse plant taxa, reported to produce either alpha or beta amyrin as the major product. We therefore sought to compare these sequences to identify residues important for activity in taraxasterol/Ψ-taraxasterol production. We inferred structural models of CoMAS and CoTXSS using AlphaFold2 23 , both of which showed high structural similarity (RMSD=0.806 and = 0.778, respectively) to the crystal structure of human lanosterol synthase (PDB:1W6K) 24 . In the formation of pentacyclic triterpenes, the 2,3-oxidosqualene precursor is folded within the OSC enzyme which catalyses cyclisations that form the four-ringed dammarenyl cation. The enzyme then directs a series of ring expansion and closures that determine the structure of the fifth ring. In the production of amyrins, this results in a lupanyl cation which undergoes a ring expansion to create either an ursanyl cation (deprotonated to α-amyrin) or an oleanyl cation (deprotonated to β-amyrin). To produce taraxasterol/Ψ-taraxasterol, a methyl shift of the oleanyl cation creates the final taraxasteryl cation ( Figure 3A ). Download figure Open in new tab Figure 3. Functional characterisation of a pot marigold Ψ-taraxasterol synthase (Co TXSS). A Biosynthesis of Ψ-taraxasterol, taraxasterol, a-amyrin, β-amyrin and lupeol by 2,3-oxidosqualene cyclases. B Structural models showing the predicted position of the taraxasteryl cation in the active site of CoTXSS and CoMAS (mixed amyrin synthase). Residues that differ are highlighted in blue. C Phylogenetic tree and sequence alignment of selected residues of MASs and TXSSs with active site residues highlighted in grey and residues selected for mutagenesis in dark grey. Ia =Ilex asprella; C r =Catharanthus roseus; Oe =Olea europaea; Ob =Ocimum basilicum; Co =Calendula officinalis; Aa =Artemisia annua; Ha = Helianthus annuus; Cc =Cynara cardunculus; Td =Tragopogon dubius; Ls =Lactuca sativa; Ce= Cichorium endivia ; Tk =Taraxacum kok-saghyz; Tc =Taraxacum coreanum . A list of taxa and accession numbers/protein sequences are provided in Supplementary Table 10. D Total ion chromatograms of extracts of N. benthamiana leaves transiently expressing wild type and mutated CoMAS and CoTXSS. E Quantification of triterpenes produced by wild type and mutated CoMAS and CoTXSS; n=6; error bars indicate standard error. Significant differences in α/β-amyrin content (blue lowercase letters) and Ψ-taraxasterol/ taraxasterol content (red lowercase letters) were analysed using a Kruskal-Wallis test followed by post-hoc Wilcoxon rank sum test with a Benjamini-Hochberg correction (Supplementary Table 11). Samples that do not share the same lower-case letter are significantly different from each other (p<0.05). Based on the position of lanosterol in 1W6K, we predicted the active site of CoMAS and CoTXSS and manually docked the taraxasteryl cation ( Figure 3B ; Supplementary Table 10). We then compared residues within 12Å of the predicted active sites, identifying two sites that differed between MASs and TXSSs: I367 and E371 ( Figure 3C ). These residues were mutated in CoMAS, substituting them with those found in CoTXSS. The product profiles of the single and double mutants were compared to those obtained from the wild-type enzymes following transient expression in Nicotiana benthamiana ( Figure 3D ). CoMAS I367M produced significantly less α/β-amyrin and significantly more taraxasterol/Ψ-taraxasterol than CoMAS ( Figure 3E ; Supplementary Table 11). CoMAS E371D also produced significantly more taraxasterol/psi-taraxasterol than CoMAS though α/β-amyrin production was not significantly affected ( Figure 3E ; Supplementary Table 11). CoMAS I367M,E371D produced significantly less α/β-amyrin than CoMAS and the single mutants and similar levels of taraxasterol/Ψ-taraxasterol as those produced by CoTXSS ( Figure 3E ; Supplementary Table 11). These data, together with the phylogenetic position of the clade, suggest that TXSSs evolved by duplication and neofunctionalisation of an MAS following the divergence of the Asteraceae. To further investigate this, we dated the origin of the TXSS clade using Bayesian phylogenetic analysis with a strict clock and two fossil calibrations. These data suggested that TXSSs emerged 83-121 mya (Supplementary Figure 21). The product specificity of TXSSs varies across Asteraceae lineages As noted above, we observed differences in the product profiles of TXSSs, notably that enzymes from species of Carduoideae, Asteroideae and some Cichorioideae (globe artichoke, pot marigold, sunflower, yellow salsify) produced more Ψ-taraxasterol than taraxasterol. In contrast, enzymes from most species of the Cichorioideae either produced equal quantities of both products (endive, lettuce), or predominantly taraxasterol (Russian dandelion, Korean dandelion) (Supplementary Figure 20). Using pot marigold and Russian dandelion as examples, we first investigated if this was reflected in the metabolic profile of plant extracts. Intriguingly, although this was found to be true, quantitative analysis also revealed that pot marigold accumulates Ψ-taraxasterol and derivatives (predominantly faradiol FAEs) exclusively in floral extracts, while Russian dandelion (Cichorioideae) predominantly accumulates taraxasterol roots with smaller quantities in the leaves and floral tissues ( Figure 4a , Supplementary Figures 22-23). Download figure Open in new tab Figure 4. Identification of residues involved in the product specificity of TXSSs. A Peak area analysis of triterpenoids detected in the floral, leaf and root tissues of pot marigold and Russian dandelion plants; n=3; error bars indicate standard error. B Phylogenetic tree of TXSSs in which the foreground branch containing taxa that predominantly produce taraxasterol is highlighted in light red. The Log likelihood ratio test at the foreground branch node indicates that this branch is likely under positive selection (p<0.01). Cc= Cynara cardunculus ; Tpr= Tragopogon pratensis ; Td= Tragopogon dubius ; Ls= Lactuca sativa ; Ce= Cichorium endivia ; Tc= Taraxacum coreanum ; Tm= Taraxacum mongolicum ; Tk =Taraxacum kok-saghyz ; Co= Calendula officinalis ; Ca= Calendula arvensis ; Hn= Helianthus niveus ; Ha= Helianthus annuus ; Tpa= Tanacetum parthemium ; Cse= Chrysanthemum seticuspe . Accession numbers are provided in Supplementary Table 10. C Structural models illustrating the predicted position of the taraxasteryl cation in the active site of CoTXSS and TkTXSS. Residues that differ between them are highlighted in orange (CoTXSS) and red (TkTXSS). D Total ion chromatograms of extracts of N. benthamiana leaves transiently expressing wild type and mutated CoTXSS and TkTXSS; n=6; error bars indicate standard error. Significant differences in Ψ-taraxasterol (orange lowercase letters) and taraxasterol (red lowercase letters) were analysed using a Kruskal-Wallis test followed by post-hoc Wilcoxon rank sum test with a Benjamini-Hochberg correction. Samples that do not share the same lower-case letter are significantly different from each other ( p <0.05). To identify the residues involved in defining these highly similar triterpene scaffolds, and to investigate if there is evidence of natural selection on this enzyme, we investigated if the TXSSs producing predominantly taraxasterol that are found in all except the most basal groups of the Cichorioideae, are under positive selection ( Figure 4B ; Supplementary Table 10). To do this, we constructed a maximum likelihood phylogenetic tree and fitted a branch-site model and a corresponding null model. This revealed that TXSSs in non-basal Cichorioideae are under positive selection (likelihood ratio test p-value<0.01) and that 11 sites are likely to be under positive selection with probabilities higher than 0.9. Of these, two amino acid residues (D385 and H492; CoTXSS numbering) were within 12Å of the predicted active site ( Figure 4C ). In parallel, we aligned the sequences of all characterised TXSSs, identifying four residues within 12Å of the active site that differed between non-basal Cichorieae TXSSs and sequences from other lineages: the two sites under positive selection (D385 and H492), G380 and P751 ( Figure 4B,C ). To gain evidence that these residues influence product specificity, we made reciprocal mutants of CoTXSS and TkTXSS. CoTXSS D385E and the reciprocal mutant TkTXSS E379D showed a significant reduction of both products indicating the importance of this residue ( Figure 4D , Supplementary Figure 24; Supplementary Table 12). However, CoTXSS D385E+H492Q showed a reduction in Ψ-taraxasterol, resulting in a shift of the dominant product from Ψ-taraxasterol to taraxasterol. The mutation of the additional sites (those not under positive selection) CoTXSS G380T+D385E+H492Q+P751A had no further effect. In contrast, TkTXSS E379D+Q486H showed an increase in the production of Ψ-taraxasterol and a decrease in taraxasterol but only the quadruple mutant (TkTXSS T374G+E379D+Q486H+A745P ) resulted in a reversal of the major product to Ψ-taraxasterol ( Figure 4D , Supplementary Figure 24; Supplementary Table 12). Identification and characterisation of a taraxasterol C16 hydroxylase As noted above, in pot marigold and field marigold, the majority of taraxasterol-based compounds are present as faradiol myristate and palmitate with faradiol and arnidiol showing the greatest anti-inflammatory bioactivity ( Figure 1 ). To investigate the biosynthesis of these compounds, we identified candidate genes encoding cytochromes P450s (CYPs) able to catalyse the hydroxylation of Ψ-taraxasterol C16. Previously characterised CYPs active on C16 of other triterpene scaffolds include CYP51H10 (C12-C13β-epoxidase, C16β-hydroxylase) from Avena strigosa (black oat); AsCYP716A111 (C16β-hydroxylase) from Aquilegia coerulea (rocky mountain columbine), and AcCYP716A141A (C28 oxidase, C16β-hydroxylase) from Platycodon grandifloras (Chinese bellflower). Due to its mono-functionality, AsCYP716A111 was used as a query to identify candidate genes in the pot marigold genome. Phylogenetic analysis of nine candidate genes from pot marigold, nine from field marigold, 68 uncharacterised candidate CYPs from publicly available genomes of Asteraceae, and 171 previously characterised CYPs confirmed that clades are predominantly grouped by substrate specificity (Supplementary Figure 25). All nine pot marigold CYP candidates resolved in a clade containing previously characterised CYPs known to act on pentacyclic triterpene scaffolds including α-amyrin, β--amyrin and lupeol. Of these, five were identified in the transcriptome data and differential expression analyses indicated that CoCYP716A392, CoCYP716A393, CoCYP716A429, and CoCYP716A430 were predominantly expressed in floral tissues, while CoCYP716A431, was more highly expressed in leaves (Supplementary Figure 26). Candidates were characterised by co-expression with CoTXSS in N . benthamiana leaves. Co-expression of CoTXSS with either CoCYP716A392 or CoCYP716A393 resulted in the production of faradiol together with smaller quantities of maniladiol and calenduladiol indicating that these enzymes are C16β-hydroxylase able to use Ψ-taraxasterol, β-amyrin and lupeol as substrates ( Figure 5A ). CoCYP716A392 and CoCYP716A393 are 83.69% identical and encoded in genomic regions with conserved synteny indicating that they are likely homeologues (Supplementary Figure 27). We note that the peak area of the terpene diols (faradiol, arnidiol, calenduladiol, and maniladiol) was not equivalent to the area depleted from the triterpene scaffold substrates. Notably, we did not detect the presence of arnidiol, despite a reduction in the taraxasterol peak, possibly the result of derivation by an endogenous enzyme. Further, co-expression of CoTXSS with either CoCYP716A392 or CoCYP716A393 also resulted in a small quantity of faradiol palmitate, suggesting that an endogenous N . benthamiana acyl transferase (ACT) is able to add fatty acids to faradiol. Co-expression of CoTXSS with CoCYP716A431 resulted in the depletion of β-amyrin and lupeol; the presence of peaks corresponding to oleanolic and betulinic acids suggested that this enzyme is a promiscuous C28 hydroxylase (Supplementary data 28). Co-expression of CoTXSS with Co CYP716A429 or CoCYP716A430 did not yield any new peaks. In addition, we tested the activity of a candidate CYP from field marigold, that was closely related to CoCYP716A392 or CoCYP716A393 and also catalysed the production of faradiol (Supplementary Figure 28). The clade containing CYPs active on pentacyclic triterpenes also contained sequences from common sunflower (Supplementary Figure 25). To investigate if this species accumulates faradiol we analysed floral extracts identifying low quantities (as compared to pot marigold), which are likely insufficient to confer detectable anti-inflammatory activity (Supplementary Figure 29). Download figure Open in new tab Figure 5 Characterisation of pot marigold C16 hydroxylases. A Total ion chromatograms of extracts of N. benthamiana leaves transiently co-expressing CoTXSS with CoCYP716A392 or CoCYP716A393. Ca= Calendula arvensis (field marigold); Co= Calendula officinalis (pot marigold). B Structural model illustrating the predicted position of Ψ-taraxasterol in the active site of CoCYP716A392. Residues selected for mutagenesis are highlighted in grey. Phylogenetic tree of CYP716A and alignment of residues in the active sites; taxa that are predominantly use Ψ-taraxasterol as a substrate are highlighted in orange and those use β-amyrin are highlighted in blue. The grey triangle represents a collapsed clade of 26 characterised CYPs from the CYP716A subfamily that hydroxylate residues of β-amyrin other than C16. C Extracted ion chromatograms and peak area analysis of extracts of N. benthamiana leaves transiently co-expressing CoTXSS with wild type and mutated CoCYP716A392. Control=HMGR+P19. D Significant differences in total Ψ-taraxasterol/β-amyrin content compared to wild type CoCYP716A392 (black lowercase letters), and significant differences in taraxasterol/β-amyrin ratio compared to wild type CoCYP716A392 (blue lowercase letters) were analysed using a Kruskal-Wallis test followed by post-hoc Wilcoxon rank sum test with a Benjamini-Hochberg correction (Supplementary Table 11). Samples that do not share the same lower-case letter are significantly different from each other (p<0.05). To identify residues important for activity on Ψ-taraxasterol, we examined the structure of the predicted active sites CoCYP716A392 and CoCYP716A393. To do this we inferred structural models using AlphaFold2 23 , which showed high similarity (RMSD: 1.283 CoCYP716A392; RMSD:1.235 CoCYP716A393) to the crystal structure of CYP90B1A in a complex with cholesterol (PDB:6A15) 25 . Based on the position of cholesterol in CYP90B1A, we predicted residues within 12Å of the active site ( Figure 5B ). We compared these residues in 22 CYPs active on β-amyrin or Ψ-taraxasterol, including the C:16 hydroxylases, CoCYP716A111 and CoCYP716A141, and two CYPs from pot marigold and two CYPs from field marigold. Three sites, A285, A357, and H424, within an otherwise conserved region were observed to differ between β-amyrin and Ψ-taraxasterol hydroxylases. These were mutated in both pot marigold enzymes, CoCYP716A392 and CoCYP716A393, and the mutants were co-expressed in N. benthamiana with CoTXSS. As previously observed with the wild-type enzymes, the quantity of diols did not correspond to the reduction of the substrate peak. We therefore quantified the reduction of the substrates. In both enzymes, A285V resulted in a greater depletion of β-amyrin and reduced depletion of Ψ-taraxasterol. In CoCYP716A392 the A357L and H424R mutations also shifted activity towards β-amyrin ( Figure 5C-D ; Supplementary Figure 30; Supplementary Table 13). Identification of an acyl transferase and reconstruction of TFAE biosynthesis in N. benthamiana To identify enzymes involved in the addition of fatty acid groups we used Arabidopsis thaliana ACYL-CoA STEROL ACYLTRANSFERASE 1 ( AtASAT1 : At3g51970) as a query to search the transcriptome and genome of pot marigold and publicly available Asteraceae species. We identified 13 candidate pot marigold triterpene ACT genes ( CoACTs 1-13 ), predicted to be members of the membrane-bound O-acyltransferase (MBOAT) superfamily, two of which contained missense mutations (Supplementary Figure 31). As for the OSC and CYPs , many candidates were paired in the phylogeny. In these cases, we selected one for further study ( CoACT1-7 ). CoACT1-5 were all more highly expressed in flowers than leaves, with CoACT1 and CoACT2 upregulated in ray florets compared to disk florets (Supplementary Figure 32). All seven candidates were cloned and co-expressed with constructs expressing either CoTXSS alone, or CoTXSS and CoCYP716A392 in N. benthamiana ( Figure 6A ; Supplementary Figures 33-34). As noted above, small quantities of faradiol palmitate were detected in N. benthamiana leaves infiltrated with constructs expressing CoTXSS and CoCYP716A392. Therefore, samples expressing candidate CoACTs were compared to control samples expressing these genes. In samples co-infiltrated with CoTXSS alone, samples with all CoACTs except CoACT1 and CoACT6 accumulated more taraxasterol/Ψ-taraxasterol palmitate than controls indicating activity on both triterpene scaffolds ( Figure 6B ; Supplementary Figure 33; Supplementary Table 14). Samples infiltrated with constructs expressing CoACT3 produced the largest quantities of Ψ-taraxasterol/taraxasterol palmitate ( Figure 6B ; Supplementary Table 14). When co-expressed with CoTXSS and CoCYP716A392 , only CoACT1 and CoACT2 produced more faradiol palmitate than the control. CoACT1 and CoACT2 are encoded in genomic regions with conserved synteny indicating that they are likely homeologues (Supplementary Figure 35). Download figure Open in new tab Figure 6. Characterisation of pot marigold triterpene acyl transferases, pathway reconstruction and expression analysis. A Total ion chromatograms of extracts of N. benthamiana leaves transiently co-expressing CoTXSS with CoACT1-3 or CoTXSS, CoCYP716A392 and CoACT1-3. B Peak area analysis showing products of pathway reconstruction in N. benthamiana through agroinfiltration of indicated genes, quantified compared to friedelin internal standard, n=6, error bars represent standard error. Statistical significance was inferred using a Kruskal-Wallis test with a post-hoc Dunns test and Benjamini-Hochberg correction, except faradiol palmitate which was inferred by one-way ANOVA and post-hoc Dunnetts test (Supplementary Table 14). C Pathway schematic. D Relative expression of CoTXSS , CoCYP716A392, CoCYP716A393, CoACT1, CoACT2 through six stages of floral development (S1-6); n=3; error bars indicate standard deviation. Having identified genes for the production of faradiol FAEs ( CoTXSS , CoCYP716A392 , CoCYP716A393, CoACT1 and CoACT2; Figure 6C ), we note that the genes are not co-located in the genome. To investigate their expression, we extracted RNA from flowers sampled at six stages through development ( Figure 6D ) and compared the expression of each gene by qRT-PCR. We found the expression to be asynchronous, with CoTXSS, CoACT1 and CoACT2, being most highly expressed in young buds with limited expression later in development and CoCYP716A392 , CoCYP716A393 being most highly expressed in mature buds ( Figure 6D ). Discussion The development of drugs from natural products requires both the identification of specific compounds, and a route to access sufficient quantities of those molecules. Plants have historically been an important source of drugs 26 , 27 . However, there are numerous technical challenges to the isolation and characterisation of bioactives. Even when a specific compound has been identified, it may occur in complex mixtures or accumulate at low volumes in limited cell types. These challenges, together with rapid advances in chemical synthesis in 20 th century led to a decline in the importance of plants as sources of new drugs 28 . In recent decades, a rapid increase in plant genome information and powerful bioinformatic tools for genome and protein analysis have made pathway discovery more accessible 29 , 30 . Alongside this, advances in molecular and synthetic biology have made the functional characterisation of candidate enzymes increasingly easy. Notably, the plant system N. benthamiana , has become a well-used experimental platform for the characterisation of plant enzymes and the reconstruction of plant natural product pathways 31 . This ability to program easily cultivable organisms to produce high levels of natural products has the potential to provide sustainable routes to access of plant natural products 31 – 33 . While molecules responsible for the bioactivity of some species used in traditional medicines have been definitively identified, in many species, compounds remain unknown. In this study, we simultaneously investigated the identity of bioactive molecules found in pot marigold and the genetic basis of their production. This enabled us to confirm one of the molecules responsible for anti-inflammatory bioactivity ( Figure 1D ) and understand why similar bioactivity has not been reported for other species that accumulate closely related molecules. It also enabled us to reconstruct the full biosynthetic pathway ( Figure 6 ), and that of the highly bioactive pathway intermediate, faradiol, obtaining yields of up to 1.32 μg/mg dw, 3.5-fold more than found in floral extracts of pot marigold ( Figure 1 and Figure 5 ). While our work confirmed that faradiol and its fatty acid ester are key contributors to anti-inflammatory activity of pot marigold extracts ( Figure 1D ), in agreement with previous observations 15 , 17 , our experiments with fractionated extracts indicate that other molecules are likely to contribute to the overall activity ( Figure 1C ). Specifically, while the fraction containing faradiol FAEs displayed significant anti-inflammatory activity via the IL-6 pathway, fractions containing fatty acids also showed significant bioactivity. Also consistent with the literature, we observed that triterpene diols faradiol and arnidiol have the most significant anti-inflammatory bioactivity ( Figure 1D ) 12 , 13 . Our investigation of the mechanisms by which faradiol influences IL-6 production in LPS-stimulated monocytes revealed an unexpected result, inhibiting phosphorylation of STAT3 ( Figure 1E ). A recent investigation of the role of long non-coding RNA brain and reproductive organ-expressed protein (BRE) antisense RNA 1 (BRE-AS1) as a regulatory element in the LPS-induced JAK2/STAT3 inflammatory pathway showed that knockdown of BRE-AS1 enhances LPS-induced expression of IL-6 and IL-1β, but does not affect levels of TNF-α 34 . These results suggest that induction and regulation of JAK2/STAT3 is independent of the TNF-α pathway. In previous work, faradiol was reported to inhibit NF-κB-driven transcription of a synthetic reporter gene in AGS (adenocarcinoma of the stomach) cells 17 . Here, it did not inhibit p65 NF-κB phosphorylation, which may not be required for TNF or IL6 transcriptional activation in response to LPS. More work is needed to clarify if NF-κB is influenced by faradiol and, if so, which part of the pathway is involved and to what extent these previously reported effects are cell-specific. Taraxasterol and psi-taraxasterol are found as esters, acetates, diols and triols across the Asteraceae 35 . However, we identified only a few species that are likely to be capable of producing faradiol, as determined by the presence of orthologs of CoCYP716A392 and CoCYP716A393 ( Figure 5 ; Supplementary Figure 25). While faradiol compounds are abundant in Calendula species, other species were found to accumulate relatively small quantities (Supplementary Figure 29), perhaps explaining the use of this genus in wound healing remedies. We also found that the closely related compound, arnidiol, to have comparable activity to faradiol ( Fig 1D ). Interestingly, arnidiol takes its name from the species from which it was first isolated, Arnica montana L. (wolf’s bane), extracts of which are used in topical treatments for bruising and muscle pain. Decorations of the C16 position of triterpenes have also been associated with anti-microbial bioactivity, toxicity and the ability to suppress neuroinflammation 36 – 38 . Our ability to characterise the CYPs was likely compromised by the endogenous metabolism of N. benthamiana : yields of faradiol were not equivalent to the reduction in Ψ-taraxasterol substrate and we were unable to detect arnidiol in this species, despite a reduction in the presence of the taraxasterol substrate ( Figure 5 C-D ). It is most likely that these products were derivatised by an endogenous enzyme as we and others have previously reported for a range of other molecules 39 – 44 . We also note that in pot marigold we detected the presence of faradiol-stearate, -myristate and -palmitate but expression of all pathway genes in N. benthamiana , only resulted in the accumulation of faradiol palmitate ( Figure 6 ). This is likely due to the availability of fatty acids in this species, although further characterisation of the ACTs is required to confirm this. Previously, TXSS genes have been identified and characterised from Cichorioideae species, Russian and Korean dandelion, and lettuce. Here we characterised six TXSSs, finding that they all are multifunctional (Supplementary Figure 20). Multifunctionality has been described for numerous triterpene-producing OSCs 19 . However, as little is known about the biological function of most plant triterpenes, or at which concentration they are bioactive, it is not possible to predict if these are side-products of promiscuous enzymes or if these production profiles have biological significance 45 , 46 . Interestingly, we found evidence that Cichorioideae TXSSs show evidence of positive selection ( Figure 4B ). Coupled with our observed differences in the site of accumulation ( Figure 4A ), this suggests that taraxasterol and Ψ-taraxasterol may fulfil different biological functions in plants. Further, we observed differences in the bioactivity of Ψ-taraxasterol compared to taraxasterol ( Figure 1D ). The multifunctionality of triterpene-producing OSCs is also likely responsible for trace quantities of taraxasterol reported in non-Asteraceae species e.g. olive, Arabidopsis, pea and tomato 47 – 50 . We found no evidence of TXSS genes outside the Asteraceae ( Figure 2 ) and Bayesian analysis suggested that TXSSs emerged 83-121 mya (Supplementary Figure 21), consistent with duplication after divergence of Asteraceae, estimated to have occurred 64-91 mya 1 . Further, knowledge of the relationship between structure and product specificity of OSC can be applied to engineering 51 . We identified two residues important for a decrease in the production of β-amyrin and an increase in production of Ψ-taraxasterol ( Figure 3 ), as well as residues that control the ratio of Ψ-taraxasterol:taraxasterol ( Figure 4 ). Interestingly, though genes for some plant terpenes are found to be clustered within plant genomes and/or tightly co-expressed 52 , although pathway gene expression was confined to floral tissues (Supplementary figures 19, 26 and 32), the genes of this pathway are not collocated, and expression levels differed through floral development ( Figure 6D ), which is consistent with the accumulation of pathway intermediates ( Figure 1A , Supplementary Figure 1, Supplementary Table 1). While we detected evidence of homeologous pairs for all pathway genes, one copy of the TXSS contained mutations indicative of pseudogenisation (Supplementary figures 18, 27 and 35), indicative of diploidisation seen in ancient polyploids 53 . Pathway elucidation and reconstruction in heterologous hosts provides opportunities for sustainable access to useful molecules such as faradiol, for which we have shown exhibits anti-inflammatory activity by preventing the phosphorylation of STAT3. The ability to use metabolic profiling of plant extracts to simultaneously investigate bioactivity and elucidate the biosynthetic pathway has the potential to fast-track the discovery and production of bioactive plant natural products. METHODS Plant growth Seeds of Calendula officinalis (pot marigold) and Helianthus annuus (common sunflower) were obtained from Chiltern Seeds (Wallingford, UK). Seeds of Calendula arvensis (field marigold; # 32133) were obtained from the Millennium Seed Bank (Wakehurst, UK). Seeds of Taraxacum kok-saghyz (Russian dandelion; #W635156) were obtained from the National Plant Germplasm System Germplasm Resources Information Network (GRIN). Seeds were sown in 9 cm plastic pots containing Levington F2 starter (100% peat). Approximately ten days post-emergence, seedlings were transplanted into 11 cm plastic pots containing John Innes cereal mix (60% peat, 20% grit, 20% perlite, 2.25 kg/m 3 dolomitic limestone, 1.3 kg/m 3 PG mix, 3 kg/m 3 Osmocote Exact). Plants for genome sequencing and transcriptomics were grown in controlled environment conditions at 22 °C (day) and 25 °C (night) with a 16-h photoperiod. All other plants were grown in summer glasshouse conditions with natural day length and temperature. In addition, Russian dandelion seedlings were cold treated at 4 °C for four weeks before returning to summer glasshouse conditions. Nicotiana benthamiana was cultivated in a peat-based potting mix (90% peat, 10% grit, with 4 kg/m 3 dolomitic limestone, 0.75 kg/m 3 powdered compound fertiliser, 1.5 kg/m 3 slow-release fertiliser). N. benthamiana plants were grown in a controlled environment room with 16 h light, 8 h dark at 22 °C, 80% humidity and ∼200 µmol/m 2 /s light intensity. Metabolite extraction and GC-MS analysis For analysis of Asteraceae species, 30 mg of freeze-dried plant material was homogenised using 3 mm tungsten carbide beads (Qiagen, Hilden, Germany) with a TissueLyser (25 Hz, 1 min) and 500 μL ethyl acetate was added (Sigma Aldrich, Burlington, MA, USA). For N. benthamiana , one to five freeze-dried discs (1 cm) were sampled from infiltrated leaves and similarly homogenised. 100 μL ethyl acetate (Sigma Aldrich) was added per 2 mg of dry weight. Samples were agitated in ethyl acetate at 700 rpm at 40 °C for 2 hours then incubated at room temperature for 48 hours. Plant material was collected by centrifugation at 15,000 rpm for 5 minutes and 50 μL of supernatant was transferred to a 2 mL glass vial. Samples were dried in a centrifugal evaporator and derivatised with 50 μL N-Methyl-N- (trimethylsilyl)trifluoroacetamide (Sigma Aldrich) at 37 °C for 30 minutes then transferred to glass inserts in 2 mL glass vials. GC-MS analysis was performed using a 7890B GC (Agilent; Sata Clara, CA, USA) fitted with a Zebron ZB5-HT Inferno column (Phenomenex; Washington D.C, USA). Injections (2 μL) were performed in pulsed splitless mode (10 psi pulse pressure) with the inlet temperature set to 325 °C. The GC oven temperature program was 150 °C and held for 30 seconds with subsequent increase to 360 °C (20 °C/min) and held at 360 °C for an additional 12.5 min (total run time 27 min). The GC oven was coupled to an Agilent 5977B Mass Selective Detector set to scan mode from 60-800 mass units (solvent delay 3 minutes). Data analysis was carried out using MassHunter workstation software (Agilent). LC-MS analysis For analysis of Calendula officinalis , 10 mg of freeze-dried plant material was homogenised using 3 mm tungsten carbide beads (Qiagen, Hilden, Germany) with a TissueLyser (25 Hz, 1 min) and 500 μL 80% methanol was added (Sigma Aldrich, Burlington, MA, USA). Samples were agitated in ethyl acetate at 700 rpm at 40 °C for 20 minutes. Plant material was collected by centrifugation at 15, 000 rpm for 5 minutes and the supernatant was transferred to a 2 mL glass vial. Samples were dried in the fume hood at room temperature for 3 days. Samples were resuspended in 100 μL 80% methanol, filtered through 0.2 µm Mini-Filter Spin Columns (Geneflow; Staffordshire, UK) then transferred to glass inserts in 2 mL glass vials. LC-MS analysis was performed using a 6546 LC/Q-TOF (Agilent; Sata Clara, CA, USA) fitted with a 1.7 μM Acuity UPLC BEH C18 column (Waters; Wilmslow, UK). Separation was carried out using 0.1% formic acid in water (A) versus acetonitrile (B) run at 0.6 mL/min and following gradients of solvent B; 15% from 0-0.75 min, 15-60% from 0.75-13 min, 60-100% from 13-13.25 min, 100-15% from 13.25-14.5 min, and 15% 14.5-16.5 min. Analytes were detected by negative electrospray ionisation using the JetStream source. The instrument collected full spectra from m/z 100-1700 (200msec per spectrum), and data-dependent MS/MS spectra for the two most abundant precursors (125msec per spectrum) with medium isolation width ( m/z 4) and 35% collision energy. Spray chamber conditions were 10 L.min -1 drying gas at 325°C, 20 psi nebulizer pressure, 12 L.min -1 sheath gas at 400°C, 120 V fragmentor voltage, 3500 V Vcap, and 1000 V nozzle voltage.. Data analysis was carried out using MassHunter workstation software (Agilent). Fractionation and purification of floral extracts Extracts were fractionated using an adaptation of a previously described method 54 . Liquid chromatography of methanol extracts was performed on an ACQUITY UPLC BEH C18 2.1 mm X 50 mm column (Waters Corp.; Milford, MA, USA) on a single quadrupole LC-MS/MS (Nexera UHPLC from Shimadzu; Kypto, Japan). The flow rate was set to 0.6 ml/min and the column temperature was kept constant at 40 °C for 28 mins. Eluent A (50% methanol) was applied for 2.5 minutes followed by a gradient of 85% to 100% methanol for 20 minutes, followed by eluent B (100% methanol) for 2.5 minutes. Sequential fractions of 1.8 ml were collected and dried to yield seven samples of 234 μg, 253 μg, 213 μg, 325 μg, 244 μg, 593 μg, and 237 μg. These fractions were analysed by GC-MS before use in cell proliferation and cytokine assays. To purify faradiol palmitate the same method was used except that eluent A (90% methanol) was applied for 2.5 minutes followed by a gradient of 90% to 97.5% methanol for 20 minutes, followed by eluent B (97.5% methanol) for 5.5 minutes. Sixteen fractions were collected and analysed by GC-MS to identify a fraction containing a single peak with the mass and spectra for faradiol palmitate (15-16 minutes). This fraction was collected and dried, yielding 1.2 mg of compound. Nuclear Magnetic Resonance (NMR) spectroscopy The structure of faradiol palmitate was confirmed by 1D and 2D NMR analysis. Spectra were recorded in 3 mm tubes using CDCl3 as a solvent at 298 K on a Bruker Neo 600 MHz spectrometer (Billerica, MA, USA) equipped with 5 mm TCI CryoProbe. 1D 1H, 13C NMR, 2D 1H-1H-COSY, 1H-13C-HSQCed and 1H-13C-HMBC experiments were performed using standard pulse sequences from the Bruker Topspin 4 library. Data was analysed using Topspin 4.1.4 and MestReNova 15.0.1 software and spectra were calibrated to an internal TMS reference. Cell maintenance and proliferation assays The human monocytic leukaemia cell line THP-1 (ECACC 88081201) was obtained from the European Collection of Cell Cultures (Health Protection Agency, Salisbury, UK). THP-1 cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 media supplemented with 10% heat-inactivated bovine foetal calf serum (FCS), L-glutamine (2 mM) and antibiotics (penicillin (100 U/mL); streptomycin (100 μg/mL) (GIBCO, Carlsbad, CA, USA). Cells were maintained at 37 °C in a humidified atmosphere with 5% CO 2 and passaged every 3.5 days to ensure the desired cell density of 3 x10 5 to 9 x 10 5 cells/mL. Cell density was measured using a Neubauer haemocytometer according to the manufacturer’s instructions (Sigma-Aldrich, Poole, UK). THP-1 cells were seeded into a 96-well plate at a density of 1 x 10 6 cells/mL in 100 µL volume. The appropriate wells were left untreated or treated with solvent control (DMSO; Sigma-Aldrich) and the compounds of interest as previously described for 24 h at 37°C/5% CO 2 55 . 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)- 2H-tetrazolium MTS (CellTiter 96 Aqueous One Solution Reagent, Promega, Southampton, UK) was added for 3 hrs at 37°C; 5% CO 2 and absorbance at 492 nm was measured using a POLARstar Optima microplate reader (BMG Labtech, Aylesbury, UK). Data analysis was performed using GraphPad Prism software (v. 10.3.1) (Dotmatics, Boston, MA, USA). Cytokine assays THP-1 cells were seeded into a 24-well plate at 1 x 10 6 cells/ml and treated with triterpenoids or plant extracts at predetermined non-cytotoxic concentrations of 20 µM and 50 µg/ml, respectively. DMSO was used as a solvent control. BAY 11-7082, a NLRP3 inflammasome and NF-κB inhibitor (E)-3-(4-Methylphenylsulfonyl)-2-propenenitrile (BAY; 10 µM, Sigma-Aldrich), was used as a positive control. Cells were incubated at 37°C/5% CO 2 for 30 min prior to treatment with 10 ng/mL LPS from Escherichia coli O55:B5 (Sigma Aldrich) for 3 hrs to stimulate TNF-α release or 1 μg/ml LPS for 24 h to stimulate IL-6 release. Supernatants were then collected and stored at −80°C until required. TNF-α or IL-6 concentrations were determined using the OptEIA human TNF-α ELISA and human Il-6 ELISA sets (BD Biosciences, Berkshire, UK), according to the manufacturer’s instructions. Purification of nucleic acids Leaves were harvested from young (16-18 days post germination) pot marigold plants. Flowers were harvested from mature (flowering) plants and deconstructed to separate ray florets and disk florets. Plant tissues were flash frozen in liquid nitrogen and stored at −80 °C. High molecular weight DNA was purified from young leaf tissue using the Nucleon Phytopure kit (Cytiva, Portsmouth, UK) according to the manufacturer’s instructions. DNA quantity and size distribution were measured using a Bioanalyzer (Agilent Technologies) and Femto Pulse (Agilent Technologies). Total RNA was purified from leaf, disc floret and ray floret tissue collected from four independent plants, snap-frozen frozen in liquid nitrogen and stored at −70 °C. RNA was extracted using the Spectrum Plant Total RNA Kit (STRN250; Merck, Darmstadt, Germany) following manufacturer’s instructions with the following exception: during column washing, 300 μl of column wash 1 was used to wash RNA and then 80 μL of DNase I (RNA-Free Dnase Set 79254; Qiagen, Hilden, Germany) was added to the column and incubated for 15 minutes followed by 500 μl of wash 1. RNA integrity was assessed by gel electrophoresis on a 1.5 % agarose gel and RNA quantity and size distribution were measured using a Bioanalyzer (Agilent Technologies, Sata Clara, CA, USA). Genome assembly and differential expression analyses Pot marigold Genomic DNA was sequenced using Illumina, PacBio, Chromium linked-read, and OmniC technologies (see Extended Methods). Pot marigold and field marigold cDNA were sequenced using Illumina and PacBio (Isoseq) chemistries. The genome and transcriptome were assembled and annotated as detailed in the extended methods (see Extended Methods). Contig synteny was determined using the progressive Mauve algorithm 56 and visualised in Geneious Prime® 2024.0.5 ( https://www.geneious.com ). Expression was quantified with salmon quant and differential gene expression analysis was carried out using DESeq2 (R: 3.6.2; DESeq2: 1.26.0). Conditions were compared pairwise as follows: Disc vs Leaf; Disc vs Ray; Leaf vs Ray. For comparisons involving disc tissue samples, “disc” was set as the baseline, while leaf was set as baseline for leaf vs ray comparison. Differential gene expression data is available at doi:10.5281/zenodo.13869958. Identification of candidate genes To identify candidate Co OSC , Co CYP and Co ACT genes, the pot marigold genome was searched using (i) T. koksaghyz taraxasterol synthase (GenBank ID: AXU93516) (ii) CYP716A111 (APG38190.1) and (iii) THAA3 (ASAT1; At3g51970.1) as queries in tBLASTn. Cut-off values were selected to include at least five expressed genes (present in the transcriptome datasets), except for Co OSC s, for which we aimed to identify the entire gene family. The E value cut offs for gene identification were 1e-50 (TXSS), 4.52e-76 ( CYP ), and 1e-60 ( ACT ). To find the whole family for OSCs, CoTXSS was used as query with the first exon (E value cut-off: 2.43e-98), last exon (E value cut-off:1.66e-45), and the exon containing the catalytic motif DCTAE (E value cut-off:8.49e-57). The publicly available genomes of Artemisia annua (txid:35608), Lactuca sativa (txid:4236), Cichorium endive (txid:114280), Taraxacum kok-saghyz (txid:333970), Helianthus anuus (txid:4232), Chrysanthemum seticuspe (txid:1111766), Cynara cardunculus (txid:4265) and the C. arvensis transcriptome were similarly interrogated. Phylogenetic analysis Protein sequences were aligned using MUSCLE V3.8.425 57 and sites with gaps were trimmed using ClipKIT with smartgap mode (v2.1.3) 58 . Maximum likelihood phylogenetic trees were inferred using IQ-TREE for all TXSS, CYP and ACT trees. For the OSC and ACT phylogenies, a JTT matrix-based model allowing for invariable sites plus discrete Gamma model and 1000 bootstraps was used (OSC and ACT model: JTT+F+I+G4) 59 . For construction of the CYP phylogeny, a LG model with empirical amino acid frequencies plus a discrete Gamma model and 1000 bootstraps was used (CYP model: LG+F+I+G4). All models were selected using ModelFinder 60 . For Bayesian phylogenetic analysis, DNA sequences were aligned by codons, and all gaps were trimmed. BEAUTi2 was used to split the alignment into three partitions and generate an input file. The clock models and tree were linked among the three partitions. Analysis was performed using BEAST2 61 with a GTR model and an Artemisia fossil 62 and a Cichorium intybus type fossil 63 as calibrators 1 . A strict molecular clock with rate=1 was used. A Yule Model was used as a prior model and 10, 000, 000 rounds of MCMC were run with 10% of burn-in. The ESS of each parameter was verified using Tracer 64 and the maximum clade credibility tree was generated with TreeAnnotator. 95% length HPD was used to represent the branch length range. Construction of plant gene expression vectors Candidate coding sequences were chemically synthesised (Twist Bioscience, South San Francisco, CA, USA) introducing synonymous mutations to remove recognition sites for BpiI, BsaI, BsmBI and SapI in accordance with the phytobrick standard 65 . Coding sequences were assembled into a binary backbone (pICH47732; Addgene #48000) together with a CaMV35s promoter and the omega sequence from tobacco mosaic virus (TMV) (pICH51277; Addgene #50268), and CaMV 35s terminator (pICH41414; Addgene #50337). Constructs were assembled using a one-step digestion-ligation reaction as previously described 66 . Sequence-verified constructs were transformed into Agrobacterium tumefaciens GV3101 by electroporation. Site directed mutagenesis of coding sequences was performed on expression constructs using the previously reported golden mutagenesis method 67 . A list of plasmids is provided in Supplementary Table 15; DNA and full sequences have been deposited in the Addgene repository (227509-227578). Transient expression in Nicotiana benthamiana Single colonies of A. tumefaciens GV3101 containing candidate and control genes as well as the suppressor of gene silencing, P19 from Tomato Bushy Stunt Virus (TBSV), (pEPQD1CB0104; #177038) 68 , and a feedback-insensitive form of HMG-CoA reductase, tHMGR (pEPQD1CB0817; #177039) 33 were used to inoculate liquid 20 ml LB with 50 μg/mL rifampicin, 20 μg/ml gentamicin, and 100 μg/ml carbenicillin. Overnight saturated cultures were centrifuged at 3,400 × g for 30 min at room temperature and cells were resuspended in infiltration medium (10 mM 2-(N-morpholino)ethanesulfonic acid (MES) pH 5.7, 10 mM MgCl2, 200 µM 3′,5′-Dimethoxy-4′-hydroxyacetophenone (acetosyringone)) and incubated at room temperature for 2-3 h at 100 rpm. Resuspended cultures were diluted to 0.8 OD 600 and mixed in equal volumes to a final volume of 2 ml. Cultures were infiltrated into a nick in the abaxial surface of leaves of young (4 true leaves; 29-34 days old) N. benthamiana plants using a 1 ml needleless syringe. Infiltrated plants were grown at 22 °C in a MLR-352-PE plant growth chamber (Panasonic Healthcare Co, Oizumi-Machi, Japan) with a 16 hr light, 8 hr dark cycle for five days. Positive selection analysis TXSS peptide sequences were aligned using MAFFT 69 and their codons were mapped to the alignment using pal2nal and all gaps in the alignment were trimmed. A maximum likelihood tree was constructed as above. The non-basal Cichorieae TXSSs were selected as the foreground. A null model (fix_omega=1, omega=1) and alternative model (fix_omega=0, omega=1) of branch-site model A were fitted to the phylogenetic tree and codon alignment using codeml function of PAML package 70 . A likelihood ratio test was used to evaluate positive selection 71 and Bayes Empirical Bayes was used to infer residues under positive selection 72 . Structure modelling Structural models of CoOSC3, CoTXSS, TkTXSS, CoCYP716A392 and CoCYP716A393 were constructed using AlphaFold2 23 . The best ranked models were used for docking. For TXSS, a taraxasteryl cation structural model was made based on 3D structure of taraxasterol (PubChem ID: 115250) and optimised in Gaussian with HF/6-31* basis set. TXSS structural models were aligned to the crystal structure of human lanosterol synthase with lanosterol in its active site (PDB:1W6K) using the align function of PyMOL (Schrödinger, Inc., New York, NY, USA) and the taraxasteryl cation was manually docked to the active site based on the location of lanosterol in 1W6K. Energy minimisation was performed with AMBER22 73 . Protein structural models of CoCYP716A392 and CoCYP716A393 were aligned to the crystal structure of CYP90B1A in a complex with cholesterol (PDB:6A15) 25 and Ψ-taraxasterol (PubChem ID: 115250) was manually docked to the active site based on the location of cholesterol in 6A15. Energy minimisation was performed with YASARA 74 . All structures were visualised in PyMOL. Quantitative reverse transcription PCR Reverse transcription was carried out using the M-MLV cDNA synthesis system (Sigma: M1302) in a 12 μl reaction with 300 ng/μl of total RNA, 1 μl of dNTP mix (10 mM) and 1 μl of oligo dT 12-18 (0.5 μg/ml). Reactions were heated to 65 °C then cooled to 4 °C before addition of 4 μl of first-strand buffer (5X), 2 μl of DTT (0.1M) and 1 μl of RNaseOUT TM (40 units/μl). Samples were incubated at 37 °C for 2 minutes before addition of water (control) or 200 U M-MLV reverse transcriptase and incubated at 37 °C for 50 minutes followed by inactivation at 70 °C for 15 minutes. cDNA was diluted 1:10 in TE Buffer (5 mM Tris-HCl + 0.5 mM EDTA, pH 8.0) before use in amplification reactions. SAND (SAND family protein), PROTEIN PHOSPHATASE 2A and PHOSPHOGLYCERATE KINASE were previously identified as appropriate reference genes in Chrysanthemum morifolium 75 , 76 . Orthologues of these genes were identified in the pot marigold genome and their variance was assessed in the transcriptome data. From this analysis, CoSAND was selected as the most appropriate reference gene. Primers (Integrated DNA Technologies, Coralville, IA, US) were tested for efficiency (95 % - 105 %) and a melt curve with a single peak (Supplementary Table 16) using a QuantStudio TM 6 Pro Real-Time PCR system (Applied Biosystems, Waltham, MA, USA). Amplification was performed in 10 μl reactions with 0.2 μM each primer, 6 ng cDNA and 1 μl SYBR Green Jumpstart TM Taq ReadyMix TM . Reactions were cycled at 94 °C for 2 minutes, followed by 40 cycles of 94 °C for 15 seconds and 58 °C for 60 seconds, followed by a melt curve. For each reaction, two technical replicates (qPCR reactions) of at least three biological replicates were performed. Control reactions (no reverse transcriptase; no template controls) had Cq values of >35. Relative expression analysis was carried out using the ΔΔCt method with timepoint S1 time point used for normalisation. Conflict of Interest Statement The authors have no conflicts of interests to declare. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author Contributions MS, MO’C and NJP conceptualised the study. MS and HS performed metabolic profiling. DG and MO’C performed all bioassays with human cell lines. MS extracted genomic DNA and RNA. GGK, GL, CS, and DS assembled the transcriptome and genome, and performed differential expression analysis. MS, DG, HS, and CT identified candidate genes, performed phylogenetic analysis, cloned and performed function characterisation of candidate genes. HS and DG performed structural modelling and functional analysis of TXSS and CYP mutations with supervision from MS. HS performed analyses for positive selection, Bayesian molecular clock analysis and structural modelling. MS, DG and CT performed qRT-PCR. MS, CT, MO’C and NJP were responsible for supervision and project management. NJP was responsible for fundraising. MS, DG, HS, CT, GGK, DS, MO’C and NJP drafted the figures and text. All authors contributed to revisions and editing. Funding statement We gratefully acknowledge the support of the Biotechnology and Biological Sciences Research Council (BBSRC), part of UK Research and Innovation (UKRI) for funding via grants BB/W014173/1 and the Earlham Institute strategic programme grant, Decoding Biodiversity (BBX011089/1) and its constituent work package (BBS/E/ER/230002B). Part of this work was delivered by Transformative Genomics, a BBSRC-funded National Bioscience Research Infrastructure (BBS/E/ER/23NB0006). DG is supported by a scholarship from the John Innes Foundation; HS is supported by a BBSRC NRP-DTP scholarship (BB/T008717/1 Project No. 2578291). Data Availability Statement The assembled genome of C. officinalis is available under accession ERZ24880564. The functional annotation of the C.officinalis genome and transcriptome assemblies of C. officinalis and C. arvensis are available at doi: 10.5281/zenodo.13869958. Reads are available under accession numbers: PRJEB80524 ( C.officinalis ) and PRJEB80545 ( C. arvensis ). Plasmids are available at Addgene (227509-227578). Differential gene expression data is available at doi: 10.5281/zenodo.13869958. All other data is provided as supplementary data. The following supporting information is available for this article: Supplementary Figure 1: Metabolite analysis of Calendula officinalis by GC-MS Supplementary Figure 2: Metabolite analysis of Calendula officinalis by LC-MS Supplementary Figure 3: GC-MS standards and mass spectra for triterpene monols Supplementary Figure 4: GC-MS standards and mass spectra for triterpene diols and acids Supplementary Figure 5: GC-MS standards and mass spectra for faradiol fatty acid esters Supplementary Figure 6: Semi-preparative uHPLC chromatograms of the methanol extract of Calendula officinalis ray florets Supplementary Figure 7: GC-MS analysis of compounds purified from C. officinalis ray floret extracts Supplementary Figure 8: GC-MS analysis of Calendula officinalis ray floret fractions Supplementary Figure 9: Structure of 3- O -palmitoyl faradiol (faradiol palmitate) Supplementary Figure 10: 1 H NMR spectra of faradiol palmitate Supplementary Figure 11: 13 C NMR spectra of faradiol palmitate Supplementary Figure 12: 1 H- 1 H COSY NMR (600 MHz, CDCl3, 298 K) of faradiol palmitate Supplementary Figure 13: 1 H- 13 C-HSQC-edited NMR (600 MHz, CDCl3, 298 K) of faradiol palmitate Supplementary Figure 14: 1 H- 13 C HMBC NMR (600 MHz, CDCl3, 298 K) of faradiol palmitate Supplementary Figure 15: Effects of C. officinalis extracts and triterpenoids on the viability of human monocytic (THP-1) cells Supplementary Figure 16. Concentration-dependent responses to floral extracts and faradiol Supplementary Figure 17: Phylogenetic analysis of plant oxidosqualene cyclases Supplementary Figure 18: Chromosomal location of Calendula officinalis oxidosqualene cyclases Supplementary Figure 19: Differential expression of Calendula officinalis oxidosqualene cyclases candidate genes Supplementary Figure 20: GC-MS analysis of N. benthamiana leaf extracts infiltrated with constructs expressing oxidosqualene cyclases Supplementary Figure 21: Bayesian phylogenetic analysis of oxidosqualene cyclases Supplementary Figure 22: GC-MS profile of Calendula officinalis tissues Supplementary Figure 23: GC-MS profile of Taraxacum kok-saghyz tissues Supplementary Figure 24: GC-MS analysis (total ion chromatograms) of N. benthamiana leaf extracts infiltrated expressing wild type and mutant taraxasterol synthases Supplementary Figure 25: Phylogenetic analysis of cytochrome p450s Supplementary Figure 26: Differential expression of Calendula officinalis cytochrome p450 candidate genes Supplementary Figure 27. Genomic location and synteny of Calendula officinalis (pot marigold) cytochrome P450 genes encoding CYP716A392 and CYP716A393. Supplementary Figure 28:GC-MS analysis of Nicotiana benthamiana expressing cytochrome P450s (CYPs). Supplementary Figure 29: GC-MS profiling of floral extracts from Asteraceae species. Supplementary Figure 30: Supp Figure 30_GC-MS analysis of Nicotiana benthamiana expressing cytochrome P450 mutants Supplementary Figure 31. Maximum-likelihood tree of plant acyltransferases. Supplementary Figure 32: ACT Diff gene expression Supplementary Figure 33: TIC TXSS and ACT Supplementary Figure 34: TIC TXSS and CYP and ACT Supplementary Figure 35: Genomic location and synteny of Calendula officinalis (pot marigold) acyltransferases Supplementary Table 1: Triterpenes detected in Calendula officinalis Supplementary Table 2: NMR data for faradiol palmitate Supplementary Table 3: Comparison of experimental and literature assignment of NMR data for faradiol palmitate Supplementary Table 4: Tables of statistics for Figure 1 Supplementary Table 5: Table of genome assembly statistics Supplementary Table 6: Table of candidate oxidosqualene cyclase genes ( OSCs ) identified in the Calendula officinalis genome. Supplementary Table 7: Table of Calendula officinalis oxidosqualene cycle transcripts Supplementary Table 8: Table of coding and protein sequences of Calendula officinalis oxidosqualene cyclases Supplementary Table 9: Table of all oxidosqualene cyclases with accession numbers Supplementary Table 10: Table of mixed amyrin synthases and taraxasterol synthases Supplementary Table 11: Statistical tests used in Figure 3 Supplementary Table 12: Statistical tests used in Figure 4 Supplementary Table 13: Statistical tests used in Figure 5 Supplementary Table 14: Statistical tests used in Figure 6 Supplementary Table 15: List of plasmids used in this study Supplementary Table 16: List of primers used in this study Supplementary Methods: Extended method for genome assembly, annotation and differential gene expression analysis Acknowledgements The plasmid pL0-AstHMGR, containing the coding sequence of truncated HMGR from A. strigosa as well as β-amyrin, α-amyrin, lupeol, oleanolic acid and betulinic acid standards were a kind gift from Anne Osbourn, John Innes Centre. C. arvensis seeds (Serial No. 32133) were gratefully retrieved from the Millennium Seed Bank. T. kok-saghyz seeds (Serial No. #W635156) were obtained from the National Plant Germplasm System Germplasm Resources Information Network (GRIN). We additionally thank Earlham Institute Transformative Genomics for library preparation and sequencing; Sergey Nepogodiev at the John Innes Centre NMR facility for assistance with NMR; the John Innes Centre horticultural services team for help with plant husbandry; the John Innes Centre metabolomics facility for help with LC-MS and GC-MS and Lionel Hill for assistance with LC-MS analysis; Andrew Hemmings at the University of East Anglia for invaluable guidance with AlphaFold2 and for help and discussions on structural modelling and docking; Wilfried Haerty, Dave Wright and Will Nash at the Earlham Institute for advice and assistance with positive selection analysis; James Reed at the John Innes Centre for advice on triterpene detection; Ilia Leitch at the Royal Botanic Gardens at Kew for discussions on genome size and ploidy in the Asteraceae. We are grateful for the use of the ADA High Performance Computing facility at University of East Anglia. REFERENCES 1. ↵ Mandel , J. R. et al. A fully resolved backbone phylogeny reveals numerous dispersals and explosive diversifications throughout the history of Asteraceae . Proc. Natl. Acad. Sci. U. S. A . 116 , 14083 – 14088 ( 2019 ). OpenUrl Abstract / FREE Full Text 2. ↵ Riley , H. T . The Natural History of Pliny, A Translation of: Naturalis Historia . ( Taylor and Francis, Woking, Surrey , 1855 ). 3. ↵ Macht , D. I . Calendula or marigold in medical history and in Shakespeare . Bull. Hist. Med . 29 , 491 – 502 ( 1955 ). OpenUrl PubMed 4. ↵ Rolnik , A. & Olas , B . The Plants of the Asteraceae Family as Agents in the Protection of Human Health . Int. J. Mol. Sci . 22 , ( 2021 ). 5. ↵ Tu , Y . The discovery of artemisinin (qinghaosu) and gifts from Chinese medicine . Nat. Med . 17 , 1217 – 1220 ( 2011 ). OpenUrl CrossRef PubMed 6. ↵ Niżyński , B. , Alsoufi , A. S. M. , Pączkowski , C. , Długosz , M. & Szakiel , A . The content of free and esterified triterpenoids of the native marigold (Calendula officinalis) plant and its modifications in in vitro cultures . Phytochem. Lett . 11 , 410 – 417 ( 2015 ). OpenUrl CrossRef 7. ↵ Cárdenas , P. D. , Almeida , A. & Bak , S . Evolution of Structural Diversity of Triterpenoids . Front. Plant Sci . 10 , 1523 ( 2019 ). OpenUrl CrossRef PubMed 8. ↵ Miettinen , K. et al. The TriForC database: a comprehensive up-to-date resource of plant triterpene biosynthesis . Nucleic Acids Res . 46 , D586 – D594 ( 2018 ). OpenUrl CrossRef PubMed 9. ↵ Fernández , M. A. , de las Heras , B. , García , M. D. , Sáenz , M. T. & Villar , A. New insights into the mechanism of action of the anti-inflammatory triterpene lupeol . J. Pharm. Pharmacol . 53 , 1533 – 1539 ( 2001 ). OpenUrl CrossRef PubMed 10. ↵ Ci , X. et al. Betulin exhibits anti-inflammatory activity in LPS-stimulated macrophages and endotoxin-shocked mice through an AMPK/AKT/Nrf2-dependent mechanism . Cell Death Dis . 8 , e2798 ( 2017 ). OpenUrl CrossRef PubMed 11. ↵ Della Loggia , R. et al. The role of triterpenoids in the topical anti-inflammatory activity of Calendula officinalis flowers . Planta Med 60 , 516 – 520 ( 1994 ). OpenUrl CrossRef PubMed Web of Science 12. ↵ Zitterl-Eglseer , K. et al. Anti-oedematous activities of the main triterpendiol esters of marigold (Calendula officinalis L .). J. Ethnopharmacol . 57 , 139 – 144 ( 1997 ). OpenUrl CrossRef PubMed 13. ↵ Neukirch , H. et al. Improved anti-inflammatory activity of three new terpenoids derived, by systematic chemical modifications, from the abundant triterpenes of the flowery plant Calendula officinalis . Chem Biodivers 2 , 657 – 671 ( 2005 ). OpenUrl CrossRef PubMed 14. ↵ Preethi , K. C. , Kuttan , G. & Kuttan , R . Anti-inflammatory activity of flower extract of Calendula officinalis Linn. and its possible mechanism of action . Indian J Exp Biol 47 , 113 – 120 ( 2009 ). OpenUrl PubMed 15. ↵ Fronza , M. , Heinzmann , B. , Hamburger , M. , Laufer , S. & Merfort , I . Determination of the wound healing effect of Calendula extracts using the scratch assay with 3T3 fibroblasts . J. Ethnopharmacol . 126 , 463 – 467 ( 2009 ). OpenUrl CrossRef PubMed 16. ↵ Preethi , K. C. & Kuttan , R . Wound healing activity of flower extract of Calendula officinalis . J Basic Clin Physiol Pharmacol 20 , 73 – 79 ( 2009 ). OpenUrl CrossRef PubMed 17. ↵ Colombo , E. et al. A Bio-Guided Fractionation to Assess the Inhibitory Activity of Calendula officinalis L. on the NF-κB Driven Transcription in Human Gastric Epithelial Cells . Evid Based Complement Alternat Med 2015 , 727342 ( 2015 ). OpenUrl PubMed 18. ↵ Nicolaus , C. et al. In vitro studies to evaluate the wound healing properties of Calendula officinalis extracts . J. Ethnopharmacol . 196 , 94 – 103 ( 2017 ). OpenUrl CrossRef PubMed 19. ↵ Thimmappa , R. , Geisler , K. , Louveau , T. , O’Maille , P. & Osbourn , A . Triterpene biosynthesis in plants . Annu. Rev. Plant Biol . 65 , 225 – 257 ( 2014 ). OpenUrl CrossRef PubMed Web of Science 20. ↵ Pütter , K. M. et al. The enzymes OSC1 and CYP716A263 produce a high variety of triterpenoids in the latex of Taraxacum koksaghyz . Sci. Rep . 9 , 5942 ( 2019 ). OpenUrl CrossRef PubMed 21. ↵ Han , J. Y. , Jo , H.-J. J. , Kwon , E. K. & Choi , Y. E . Cloning and Characterization of Oxidosqualene Cyclases Involved in Taraxasterol, Taraxerol and Bauerenol Triterpene Biosynthesis in Taraxacum coreanum . Plant Cell Physiol . 60 , 1595 – 1603 ( 2019 ). OpenUrl CrossRef PubMed 22. ↵ Choi , H. S. , Han , J. Y. & Choi , Y. E . Identification of triterpenes and functional characterization of oxidosqualene cyclases involved in triterpene biosynthesis in lettuce (Lactuca sativa) . Plant Sci . 301 , 110656 ( 2020 ). 23. ↵ Jumper , J. et al. Highly accurate protein structure prediction with AlphaFold . Nature 596 , 583 – 589 ( 2021 ). OpenUrl CrossRef PubMed 24. ↵ Thoma , R. et al. Insight into steroid scaffold formation from the structure of human oxidosqualene cyclase . Nature 432 , 118 – 122 ( 2004 ). OpenUrl CrossRef PubMed Web of Science 25. ↵ Fujiyama , K. et al. Structural insights into a key step of brassinosteroid biosynthesis and its inhibition . Nature Plants 5 , 589 – 594 ( 2019 ). OpenUrl CrossRef PubMed 26. ↵ Atanasov , A. G. et al. Discovery and resupply of pharmacologically active plant-derived natural products: A review . Biotechnology Advances vol. 33 1582 – 1614 Preprint at doi: 10.1016/j.biotechadv.2015.08.001 ( 2015 ). OpenUrl CrossRef PubMed 27. ↵ Newman , D. J. & Cragg , G. M . Natural Products as Sources of New Drugs from 1981 to 2014 . Journal of Natural Products vol. 79 629 – 661 Preprint at doi: 10.1021/acs.jnatprod.5b01055 ( 2016 ). OpenUrl CrossRef PubMed 28. ↵ Atanasov , A. G. , Zotchev , S. B. , Dirsch , V. M. & Supuran , C. T . Natural products in drug discovery: advances and opportunities . Nature Reviews Drug Discovery 20 , 200 – 216 ( 2021 ). OpenUrl CrossRef PubMed 29. ↵ Kim , J. & Buell , C. R . A revolution in plant metabolism: Genome-enabled pathway discovery . Plant Physiol . 169 , 1532 – 1539 ( 2015 ). OpenUrl Abstract / FREE Full Text 30. ↵ Durand , M. , Besseau , S. , Papon , N. & Courdavault , V . Unlocking plant bioactive pathways: omics data harnessing and machine learning assisting . Curr. Opin. Biotechnol . 87 , 103135 ( 2024 ). 31. ↵ Golubova , D. , Tansley , C. , Su , H. & Patron , N. J . Engineering Nicotiana benthamiana as a platform for natural product biosynthesis . Curr Opin Plant Biol 81 , 102611 ( 2024 ). 32. Cravens , A. , Payne , J. & Smolke , C. D . Synthetic biology strategies for microbial biosynthesis of plant natural products . Nature Communications vol. 10 2142 Preprint at doi: 10.1038/s41467-019-09848-w ( 2019 ). OpenUrl CrossRef 33. ↵ Reed , J. et al. A translational synthetic biology platform for rapid access to gram-scale quantities of novel drug-like molecules . Metab. Eng . 42 , 185 – 193 ( 2017 ). OpenUrl CrossRef PubMed 34. ↵ Shin , J.-J. , Suk , K. & Lee , W.-H . LncRNA BRE-AS1 regulates the JAK2/STAT3-mediated inflammatory activation via the miR-30b-5p/SOC3 axis in THP-1 cells . Sci Rep 14 , 25726 ( 2024 ). 35. ↵ Olennikov , D. N. & Kashchenko , N. I . Marigold Metabolites: Diversity and Separation Methods of Genus Phytochemicals from 1891 to 2022 . Molecules 27 , ( 2022 ). 36. ↵ Geisler , K. et al. Biochemical analysis of a multifunctional cytochrome P450 (CYP51) enzyme required for synthesis of antimicrobial triterpenes in plants . Proc. Natl. Acad. Sci. U. S. A . 110 , E3360 – 7 ( 2013 ). OpenUrl Abstract / FREE Full Text 37. He , D. et al. Echinocystic Acid Inhibits Inflammation and Exerts Neuroprotective Effects in MPTP-Induced Parkinson’s Disease Model Mice . Front. Pharmacol . 12 , 787771 ( 2022 ). 38. ↵ Ge , W. et al. Synthesis of Cucurbitacin B Derivatives as Potential Anti-Hepatocellular Carcinoma Agents . Molecules 23 , 3345 ( 2018 ). OpenUrl CrossRef PubMed 39. ↵ Dudley , Q. M. et al. Reconstitution of monoterpene indole alkaloid biosynthesis in genome engineered Nicotiana benthamiana . Communications Biology 5 , 1 – 12 ( 2022 ). OpenUrl CrossRef PubMed 40. Liu , Q. et al. Elucidation and in planta reconstitution of the parthenolide biosynthetic pathway . Metab. Eng . 23 , 145 – 153 ( 2014 ). OpenUrl CrossRef PubMed 41. Liu , Q. et al. Reconstitution of the costunolide biosynthetic pathway in yeast and Nicotiana benthamiana . PLoS One 6 , e23255 ( 2011 ). OpenUrl CrossRef PubMed 42. Brückner , K. & Tissier , A . High-level diterpene production by transient expression in Nicotiana benthamiana . Plant Methods 9 , 46 ( 2013 ). 43. van Herpen , T. W. J. M. et al. Nicotiana benthamiana as a production platform for artemisinin precursors . PLoS One 5 , e14222 ( 2010 ). OpenUrl CrossRef PubMed 44. ↵ Dong , L. , Jongedijk , E. , Bouwmeester , H. & Van Der Krol , A . Monoterpene biosynthesis potential of plant subcellular compartments . New Phytol . 209 , 679 – 690 ( 2016 ). OpenUrl CrossRef PubMed 45. ↵ Khersonsky , O. & Tawfik , D. S . Enzyme promiscuity: a mechanistic and evolutionary perspective . Annu Rev Biochem 79 , 471 – 505 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 46. ↵ Copley , S. D . An evolutionary perspective on protein moonlighting . Biochem Soc Trans 42 , 1684 – 1691 ( 2014 ). OpenUrl Abstract / FREE Full Text 47. ↵ Saimaru , H. et al. Production of triterpene acids by cell suspension cultures of Olea europaea . Chem Pharm Bull (Tokyo ) 55 , 784 – 788 ( 2007 ). OpenUrl CrossRef PubMed 48. Segura , M. J. R. , Michelle M. Meyer , A. & Matsuda *, S. P. T. Arabidopsis thaliana LUP1 Converts Oxidosqualene to Multiple Triterpene Alcohols and a Triterpene Diol . ( 2000 ) doi: 10.1021/ol006016b . OpenUrl CrossRef PubMed 49. Morita , M. , Shibuya , M. , Kushiro , T. , Masuda , K. & Ebizuka , Y . Molecular cloning and functional expression of triterpene synthases from pea (Pisum sativum) new alpha-amyrin-producing enzyme is a multifunctional triterpene synthase . Eur J Biochem 267 , 3453 – 3460 ( 2000 ). OpenUrl PubMed Web of Science 50. ↵ Wang , Z. et al. Two oxidosqualene cyclases responsible for biosynthesis of tomato fruit cuticular triterpenoids . Plant Physiol 155 , 540 – 552 ( 2011 ). OpenUrl Abstract / FREE Full Text 51. ↵ Guo , H. , Chen , T. , Zhu , H. , Wang , H. & Huo , Y.-X . Engineering amino acid residues of pentacyclic triterpene synthases for improving the activity . Appl Microbiol Biotechnol 108 , 195 ( 2024 ). OpenUrl CrossRef 52. ↵ Nützmann , H.-W. , Huang , A. & Osbourn , A . Plant metabolic clusters – from genetics to genomics . New Phytologist 211 , 771 – 789 ( 2016 ). OpenUrl CrossRef PubMed 53. ↵ Li , Z. et al. Patterns and Processes of Diploidization in Land Plants . Annu Rev Plant Biol 72 , 387 – 410 ( 2021 ). OpenUrl CrossRef PubMed 54. ↵ Reznicek , G. & Zitterl-Eglseer , K . Quantitative determination of the faradiol esters in marigold flowers and extracts . Sci. Pharm . 71 , 121 – 128 ( 2003 ). OpenUrl CrossRef 55. ↵ di Gesso , J. L. et al. Flavonoid metabolites reduce tumor necrosis factor-α secretion to a greater extent than their precursor compounds in human THP-1 monocytes . Mol. Nutr. Food Res . 59 , 1143 – 1154 ( 2015 ). OpenUrl CrossRef PubMed 56. ↵ Darling , A. E. , Mau , B. & Perna , N. T . progressiveMauve: Multiple Genome Alignment with Gene Gain, Loss and Rearrangement . PLOS ONE 5 , e11147 ( 2010 ). OpenUrl CrossRef PubMed 57. ↵ Edgar , R. C . MUSCLE: multiple sequence alignment with high accuracy and high throughput . Nucleic Acids Res . 32 , 1792 – 1797 ( 2004 ). OpenUrl CrossRef PubMed Web of Science 58. ↵ Steenwyk , J. L. , Buida , T. J. , III . , Li , Y. , Shen , X.-X. & Rokas , A. ClipKIT: A multiple sequence alignment trimming software for accurate phylogenomic inference . PLoS Biol . 18 , e3001007 ( 2020 ). OpenUrl CrossRef PubMed 59. ↵ Trifinopoulos , J. , Nguyen , L.-T. , von Haeseler , A. & Minh , B. Q . W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis . Nucleic Acids Res . 44 , W232 – 5 ( 2016 ). OpenUrl CrossRef PubMed 60. ↵ Kalyaanamoorthy , S. , Minh , B. Q. , Wong , T. K. F. , von Haeseler , A. & Jermiin , L. S . ModelFinder: fast model selection for accurate phylogenetic estimates . Nature Methods 14 , 587 – 589 ( 2017 ). OpenUrl CrossRef PubMed 61. ↵ Bouckaert , R. et al. BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis . PLOS Computational Biology 15 , e1006650 ( 2019 ). OpenUrl CrossRef 62. ↵ Hobbs , C. R. & Baldwin , B. G . Asian origin and upslope migration of Hawaiian Artemisia (Compositae–Anthemideae) . Journal of Biogeography 40 , 442 – 454 ( 2013 ). OpenUrl CrossRef 63. ↵ Tremetsberger , K. et al. Divergence time estimation in Cichorieae (Asteraceae) using a fossil-calibrated relaxed molecular clock . Organisms Diversity & Evolution 13 , 1 – 13 ( 2012 ). OpenUrl 64. ↵ Rambaut , A. , Drummond , A. J. , Xie , D. , Baele , G. & Suchard , M. A . Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7 . Syst Biol 67 , 901 – 904 ( 2018 ). OpenUrl CrossRef PubMed 65. ↵ Patron , N. J. et al. Standards for plant synthetic biology: a common syntax for exchange of DNA parts . New Phytologist 208 , 13 – 19 ( 2015 ). OpenUrl CrossRef PubMed 66. ↵ Cai , Y.-M. , Carrasco Lopez , J. A. & Patron , N. J . Phytobricks: Manual and Automated Assembly of Constructs for Engineering Plants . in DNA Cloning and Assembly: Methods and Protocols (eds. Chandran , S. & George , K. W. ) 179 – 199 ( Springer US , New York, NY , 2020 ). doi: 10.1007/978-1-0716-0908-8_11 . OpenUrl CrossRef 67. ↵ Püllmann , P. et al. Golden Mutagenesis: An efficient multi-site-saturation mutagenesis approach by Golden Gate cloning with automated primer design . Sci. Rep . 9 , 10932 ( 2019 ). 68. ↵ Garabagi , F. , Gilbert , E. , Loos , A. , McLean , M. D. & Hall , J. C . Utility of the P19 suppressor of gene-silencing protein for production of therapeutic antibodies in Nicotiana expression hosts . Plant Biotechnol. J . 10 , 1118 – 1128 ( 2012 ). OpenUrl CrossRef PubMed Web of Science 69. ↵ Rozewicki , J. , Li , S. , Amada , K. M. , Standley , D. M. & Katoh , K . MAFFT-DASH: integrated protein sequence and structural alignment . Nucleic Acids Res . 47 , W5 – W10 ( 2019 ). OpenUrl CrossRef PubMed 70. ↵ Yang , Z . PAML 4: phylogenetic analysis by maximum likelihood . Mol. Biol. Evol . 24 , 1586 – 1591 ( 2007 ). OpenUrl CrossRef PubMed Web of Science 71. ↵ Zhang , J. , Nielsen , R. & Yang , Z . Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level . Mol. Biol. Evol . 22 , 2472 – 2479 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 72. ↵ Yang , Z. , Wong , W. S. W. & Nielsen , R . Bayes empirical bayes inference of amino acid sites under positive selection . Mol. Biol. Evol . 22 , 1107 – 1118 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 73. ↵ Case , D. A. et al. Amber 2022 . ( University of California , San Francisco , 2022 ). 74. ↵ Land , H. & Humble , M. S . YASARA: A Tool to Obtain Structural Guidance in Biocatalytic Investigations . Methods Mol Biol 1685 , 43 – 67 ( 2018 ). OpenUrl CrossRef PubMed 75. ↵ Qi , S. et al. Reference Gene Selection for RT-qPCR Analysis of Flower Development in Chrysanthemum morifolium and Chrysanthemum lavandulifolium . Front. Plant Sci . 7 , 173132 ( 2016 ). OpenUrl 76. ↵ Li , X. et al. Selection of optimal reference genes for qRT-PCR analysis of shoot development and graviresponse in prostrate and erect chrysanthemums . PLoS One 14 , e0225241 ( 2019 ). OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted January 14, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Biosynthesis and Bioactivity of Anti-Inflammatory Triterpenoids in Calendula officinalis (pot marigold) Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. 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Share Biosynthesis and Bioactivity of Anti-Inflammatory Triterpenoids in Calendula officinalis (pot marigold) D Golubova , M Salmon , H Su , C Tansley , GG Kaithakottil , G Linsmith , S Schudoma , D Swarbreck , MA O’Connell , NJ Patron bioRxiv 2025.01.11.632544; doi: https://doi.org/10.1101/2025.01.11.632544 Share This Article: Copy Citation Tools Biosynthesis and Bioactivity of Anti-Inflammatory Triterpenoids in Calendula officinalis (pot marigold) D Golubova , M Salmon , H Su , C Tansley , GG Kaithakottil , G Linsmith , S Schudoma , D Swarbreck , MA O’Connell , NJ Patron bioRxiv 2025.01.11.632544; doi: https://doi.org/10.1101/2025.01.11.632544 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Plant Biology Subject Areas All Articles Animal Behavior and Cognition (7622) Biochemistry (17648) Bioengineering (13871) Bioinformatics (41880) Biophysics (21423) Cancer Biology (18558) Cell Biology (25460) Clinical Trials (138) Developmental Biology (13364) Ecology (19866) Epidemiology (2067) Evolutionary Biology (24290) Genetics (15589) Genomics (22475) Immunology (17711) Microbiology (40327) Molecular Biology (17145) Neuroscience (88473) Paleontology (666) Pathology (2827) Pharmacology and Toxicology (4816) Physiology (7635) Plant Biology (15114) Scientific Communication and Education (2044) Synthetic Biology (4286) Systems Biology (9815) Zoology (2268)