Entry Steps in the Biosynthetic Pathway to Diterpenoid Alkaloids in Delphinium grandiflorum and Aconitum plicatum

Entry Steps in the Biosynthetic Pathway to Diterpenoid Alkaloids | 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 Entry Steps in the Biosynthetic Pathway to Diterpenoid Alkaloids View ORCID Profile Garret P. Miller , View ORCID Profile Lana Mutabdžija-Nedelcheva , View ORCID Profile Trine B. Andersen , Imani Pascoe , Kathryn Van Winkle , Maryam Sabbaghan , View ORCID Profile Alexandre Bouillé , View ORCID Profile Tomáš Iliaš , View ORCID Profile Andrej Tekel , View ORCID Profile Tomáš Pluskal , View ORCID Profile Björn Hamberger doi: https://doi.org/10.1101/2025.05.15.654307 Garret P. Miller 1 Biochemistry and Molecular Biology, Michigan State University , East Lansing, Michigan, United States 2 Green Chemistry and Biochemistry, University of Michigan-Flint , Flint, Michigan, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Garret P. Miller Lana Mutabdžija-Nedelcheva 3 Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences , Flemingovo nám. 2, 160 00 Prague, Czechia 4 Department of Genetics and Microbiology, Charles University , Albertov 6, 128 00 Prague, Czechia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lana Mutabdžija-Nedelcheva Trine B. Andersen 1 Biochemistry and Molecular Biology, Michigan State University , East Lansing, Michigan, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Trine B. Andersen Imani Pascoe 1 Biochemistry and Molecular Biology, Michigan State University , East Lansing, Michigan, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kathryn Van Winkle 1 Biochemistry and Molecular Biology, Michigan State University , East Lansing, Michigan, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site Maryam Sabbaghan 1 Biochemistry and Molecular Biology, Michigan State University , East Lansing, Michigan, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alexandre Bouillé 3 Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences , Flemingovo nám. 2, 160 00 Prague, Czechia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alexandre Bouillé Tomáš Iliaš 3 Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences , Flemingovo nám. 2, 160 00 Prague, Czechia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Tomáš Iliaš Andrej Tekel 3 Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences , Flemingovo nám. 2, 160 00 Prague, Czechia 5 Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University , Prague, Czechia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Andrej Tekel Tomáš Pluskal 3 Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences , Flemingovo nám. 2, 160 00 Prague, Czechia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Tomáš Pluskal For correspondence: tomas.pluskal{at}uochb.cas.cz hamberge{at}msu.edu Björn Hamberger 1 Biochemistry and Molecular Biology, Michigan State University , East Lansing, Michigan, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Björn Hamberger For correspondence: tomas.pluskal{at}uochb.cas.cz hamberge{at}msu.edu Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Both the terpenoid and alkaloid classes of specialized metabolites have received considerable attention for their wide range of practical applications, however, few examples have been identified of these classes intersecting. The diterpenoid alkaloids are one such example of nitrogen-containing terpenoids which are found throughout many independent plant lineages, but primarily within the Aconitum (Wolf’s-Bane) and Delphinium (Larkspur) genera. While there is considerable interest in these compounds for their wide range of bioactivities, their structural complexity often precludes their production through chemical synthesis, and little progress has been made towards elucidation of their biosynthetic pathways. Here, we employ a comparative transcriptomics approach to identify six enzymatic steps in the biosynthesis of atisinium, conserved across both Delphinium grandiflorum and Aconitum plicatum . Key to this pathway is a reductase which selectively incorporates ethanolamine over ethylamine into the diterpenoid scaffold. While the majority of diterpenoid alkaloids contain an ethylamine moiety, we demonstrate through isotope labeling in Aconitum callus cultures and a computational metabolomics approach that ethanolamine is, unintuitively, the preferred source of nitrogen for these metabolites. Identification of these enzymes and production of a key intermediate in a heterologous host paves the way for biosynthetic production of this group of metabolites with promise for medicinal applications. Introduction To support their defense, interactions with other organisms, and ecological adaptation, land plants have evolved a plethora of structurally diverse specialized metabolites. Such metabolites often feature biologically relevant molecular scaffolds which have proven paramount for the discovery of chemical probes and drugs 1 . Among these, both the alkaloid and terpenoid classes have received considerable attention for their medicinal applications, with prominent examples including taxol 2 (anti-cancer), artemisinin 3 (antiplasmodial), morphine 4 (analgesic), colchicine 5 (anti-inflammatory), scopolamine 6 – 8 (anti-nausea), and vinblastine 9 – 11 (anti-cancer). Their importance in the pharmaceutical industry has led to a wealth of research into elucidation of their biosynthetic pathways and production in heterologous hosts, as direct extraction from plants or complete chemical synthesis is often challenging or unfeasible. Given the unique pathways towards initial scaffold formation, there is little overlap between the terpenoid and alkaloid classes of specialized metabolites. One notable exception is the diterpenoid alkaloids, which are found throughout many independent plant lineages 12 – 14 , but primarily within the cosmopolitan Ranunculaceae family 15 , 16 ( Supplementary Figure 1 ). The biosynthesis of this class of metabolites has not been elucidated, however it is apparent from their structure that it involves the initial formation of a diterpene scaffold followed by nitrogen incorporation, and extensive modifications by various oxygenases, acyltransferases, and methyltransferases. Plants from the Aconitum and Delphinium genera have long been used in traditional medicine due to the bioactivity of diterpenoid alkaloids, which primarily accumulate in their root tissue 17 – 20 . The use of “Fuzi”— the processed lateral root of A. carmichaelii (more commonly known as Wolf’s Bane or Aconite)—has been documented for at least two thousand years 16 . The diterpenoid alkaloids have a wide range of potential applications from antifeedants to anti-cancer, antiplasmodial, cholinesterase inhibitors, and analgesics 15 , 16 , 21 – 23 with lappaconitine, 3-acetylaconitine and crassicauline A used as non-narcotic analgesic drugs 24 . The therapeutic properties of many of these metabolites have prompted an extensive amount of research into their total chemical synthesis 25 – 29 , however, their structural complexity presents an enormous challenge in chemical synthesis. This is best exemplified by aconitine ( Figure 1 ), a potent neurotoxin with six interconnected rings and fifteen stereocenters. Despite being first isolated in 1833 by P. L. Geiger and numerous attempts to synthesize it chemically, aconitine has not yet been successfully synthesized by chemists 30 . Download figure Open in new tab Figure 1: Proposed biosynthetic pathway towards diterpenoid alkaloids. Putative enzyme classes or chemical transformations used to guide our approach are annotated along each arrow, with enzymes identified in this study for each step from D. grandiflorum and A. plicatum written in blue and orange, respectively. The transformations labeled “reductive amination” likely proceed through spontaneous condensation with ethanolamine followed by reduction by DAS, as described in the text. Compound numbers with blue dots are those supported by NMR or comparison to standards. Rationale for structural assignments and predictions are expanded upon in Supplementary Table 3 . Example diterpenoid alkaloid structures are shown below in gray. Elucidating the biosynthesis of these compounds would ameliorate some of the challenges in their production given the complexity of their scaffolds and the number of required stereospecific oxidations. The lack of current knowledge in their biosynthesis is not for a lack of effort, as there is a large body of work involving transcriptomic analysis of these pathways in various Aconitum species 31 – 36 . Only recently our understanding was further expanded beyond the initial steps involving terpene synthases 36 , 37 to include cytochrome P450-mediated oxidations 38 . However, the enzyme(s) responsible for nitrogen incorporation, a defining feature of diterpenoid alkaloids, remain unidentified. To our knowledge, similar work has not yet been done on the neighboring Delphinium genus, despite the likely conservation of this pathway between both genera. To address the gaps in the biosynthetic pathway of diterpenoid alkaloids, we carried out transcriptome sequencing on Delphinium grandiflorum , Aconitum plicatum and Aconitum lycoctonum , and also included public data from four other Aconitum species. Transcriptome assembly both for D. grandiflorum and for six representatives of the Aconitum genus ( A. plicatum , A. lycoctonum , A. carmichaelii , A. japonicum , A. kusnezoffii , and A. vilmorinianum )—all of which accumulate diterpenoid alkaloids—allowed for comparative transcriptomics across tissue types and genera, leading to the identification of six enzymes active in this pathway. Furthermore, the public data for A. vilmorinianum —a root tissue timecourse study 31 —allowed for coexpression analysis, resulting in the identification of a novel reductase active in the pathway which has little homology to previously characterized enzymes. This reductase catalyzes a key step in the pathway, supporting the formation of atisinium ( 10 , Figure 1 )—a bioactive diterpenoid alkaloid and potential intermediate in the biosynthesis of more complex diterpenoid alkaloids 23 . Despite the abundance of diterpenoid alkaloids with ethylamine groups attached to their central terpene scaffolds, we further demonstrate that ethanolamine is the preferred substrate for this reductase and the primary nitrogen source for the majority of detected diterpenoid alkaloids in Aconitum plants. Identification of these entry steps allowed for reconstruction of a minimal pathway sufficient for de novo biosynthesis of atisinium ( 10 ), and will serve as the basis for further pathway discovery towards more complex diterpenoid alkaloid natural products and their biosynthetic production in heterologous hosts. Results A Pair of TPSs Cyclize GGPP to ent -atiserene The majority of diterpenoid alkaloids in the Ranunculaceae family can be divided into three groups based on the number of carbons in their backbone structure (C 18 , C 19 , and C 20 ), each of which is further divided into multiple subgroups represented by 46 distinct scaffolds 15 , 24 . Despite considerable structural differences between them which reflect variations in their biosynthetic pathways, they appear to share the same initial biosynthesis with the majority of scaffolds believed to arise primarily from ent -atiserene ( 2 ) 24 , 39 . Our initially-proposed biosynthetic pathway is detailed in Figure 1 . Initially, the cyclization pattern of geranylgeranyl diphosphate (GGPP) follows a class II terpene synthase (TPS) mechanism, with three distinct stereocenters which suggest the involvement of an ent -copalyl diphosphate ( 1 , ent -CPP) synthase. The ring pattern of the majority of diterpenoid alkaloids is consistent with that of ent -atiserene ( 2 ), suggesting the involvement of a class I TPS to convert ent -CPP ( 1 ) to this scaffold. Subsequent nitrogen incorporation would first require oxidative functionalization of key methyl groups on the ent -atiserene ( 2 ) scaffold, likely to aldehydes ( 3 - 5 ), suggesting the involvement of one or more cytochromes P450 (CYPs). The final incorporation of this nitrogen group likely involves a reductive amination and marks the transition from diterpenoids to diterpenoid alkaloids 24 . In order to identify candidate enzymes for this pathway, we opted to cross-reference transcriptomic data across multiple species and tissue types. We isolated and sequenced RNA from several tissues of Aconitum plicatum (root, flower, leaf, and stem), Aconitum lycoctonum (root, flower, leaf, stem, and fruit), and Delphinium grandiflorum (root, leaf, and flower), and carried out de novo transcriptome assembly for each. Furthermore, datasets from A. carmichaelii (root, leaf, flower, bud; PRJNA415989) 33 , A. japonicum (root, root tuber, leaf, flower, stem; PRJDB4889), A. kusnezoffii (leaf, principal root, and lateral root; PRJNA670255) 38 and A. vilmorinianum (root time course; PRJNA667080) 31 from the NCBI Sequence Read Archive (SRA) were included as well. A BLAST search of the D. grandiflorum transcriptome against a reference set of plant TPSs (Supplementary Dataset 1) revealed fourteen putative TPS genes between the two subfamilies typically implicated in diterpene biosynthesis: class II TPSs from the TPS-c subfamily, and class I TPSs from the TPS-e subfamily. Only three of these were exclusively expressed in root tissue, matching the tissue-specific accumulation of diterpenoid alkaloids. Dgr TPS1 (TPS-c) and Dgr TPS2 (TPS-e) appeared to be the most likely candidates, as they belong to the pair of subfamilies typically implicated in labdane-related diterpene biosynthesis. Full-length genes for Dgr TPS1 and Dgr TPS2 were cloned from D. grandiflorum root cDNA for Agrobacterium- mediated transient expression in Nicotiana benthamiana . Two isoforms of Dgr TPS2, named Dgr TPS2a and Dgr TPS2b, were cloned from cDNA and both were tested. All screening through transient expression in N. benthamiana included coexpression with Cf DXS and Cf GGPPS (to increase precursor supply of GGPP 40 ). GC-MS analysis of hexane extracts revealed that Dgr TPS1 acts as a copalyl diphosphate (CPP) synthase ( Supplementary Figure 3A ). Coexpression of an enantioselective ent -kaurene synthase ( Nm TPS2) 41 led to production of ent -kaurene, suggesting an absolute stereochemistry for the product of Drg TPS1 consistent with ent -CPP ( 1 ) ( Supplementary Figure 3A ). Furthermore, Dgr TPS2a and 2b showed conversion of 1 ( Figure 2B ) to a new product with a fragmentation pattern ( Figure 2C ) similar to that of ent -atiserene ( 2 ) 42 for both isoforms. To confirm the identity of this new product as 2 , transient expression in N. benthamiana was scaled up with Dgr TPS1 and Dgr TPS2a, and the product was purified through silica chromatography and confirmed through NMR ( Supplementary Table 1 and Supplementary Figure 4 ). Since both isoforms of Dgr TPS2 exhibit the same function, Dgr TPS2a was used for further testing and is referred to as Dgr TPS2 hereafter. Cloning and characterization of the respective orthologs from Aconitum plicatum revealed that both Apl TPS1 and Apl TPS2 have this same activity and enantioselectivity, and demonstrates the conservation of the entry steps of this pathway across both genera ( Supplementary Figure 3C ). Download figure Open in new tab Figure 2: Identification of a pair of terpene synthases which produce ent-atiserene. A) Maximum likelihood phylogenetic tree of predicted D. grandiflorum TPS-c and TPC-e sequences and their respective expression across tissue types. Reference TPS sequences are in gray with Pp CPS-KS ( Physcomitrium patens ) used as an outgroup, scale bar represents substitutions per site, and branches with less than 50% bootstrap support have been collapsed. Expanded view of this tree with Aconitum sequences is given in Supplementary Figure 2 . B ) GC-MS analysis of Dgr TPS1 and Dgr TPS2 coexpression in N. benthamiana . Zm AN2 ( Zea mays ) serves as a reference ent -CPP ( 1 ) synthase. Marking of 1 * indicates the dephosphorylated derivative of 1 , as 1 itself is not detectable by GC-MS. Each assay has Cf DXS and Cf GGPPS ( Coleus forskohlii ) coexpressed in addition to those listed. C ) Mass spectrum (70 eV EI) of 2 from panel B, and select HMBC, NOESY, and COSY correlations for ent -atiserene ( 2 ) purified from N. benthamiana expressing Dgr TPS1 and Dgr TPS2a. Three Cytochromes P450 Oxidize the ent -atiserene Scaffold Following the confirmation that a pair of terpene synthases produce 2 , we continued with our proposed biosynthetic pathway to search for cytochromes P450 (CYPs) which can carry out oxidations of methyl groups 19 and 20 to aldehydes. The proposed intermediate ent -atiserene-19-al ( 3 ) resembles the central metabolite ent -kaurenoic acid—a key compound in the primary metabolic pathway towards gibberellins 43 —which is synthesized from GGPP through the activity of a class II/class I TPS pair and a CYP from the CYP701A subfamily 43 . Given the characterization above for a class II/class I TPS pair, it is plausible that the gene responsible for converting 2 to 3 is a recent duplicate of a CYP701A, especially given the occurrence of polyploidization within the Delphinieae tribe (containing Aconitum and Delphinium ) of the Ranunculaceae family 44 – 46 . In contrast to the TPS family, the identification of CYPs presents a challenge due to the number of genes that may be present in any given plant 47 . In our transcriptome assemblies for D. grandiflorum and the six Aconitum species, a BLAST search against a reference set of CYP sequences (Supplementary Dataset 1) yielded 2,123 predicted CYP transcripts after clustering by 99% sequence identity, with 284 for D. grandiflorum alone and roughly two to four hundred for each Aconitum assembly. To narrow this down to a manageable number to test, we took advantage of the assumed conservation of this pathway between neighboring genera and tissue-specific accumulation of metabolites. The total CYP transcripts from each assembly were first assigned to individual clans through a sequence-similarity network, and individual phylogenies were made for distinct clans ( Figure 3A and Supplementary Figures 5-7). We then filtered these transcripts to include only those in D. grandiflorum with high root expression and with a root-expressed ortholog in each Aconitum assembly. Expression values for each pathway gene are given in Supplementary Figure 8 , and orthologs were inferred from grouping in phylogenetic trees as in the example in Figure 3A and shown in Supplementary Figures 5-7. This narrowed a list of 284 possible CYPs from D. grandiflorum down to just six for testing. Download figure Open in new tab Figure 3: Search strategy and characterization of three CYPs active in the pathway. A ) Visual representation of the search strategy for candidate CYPs. CYPs mined from each transcriptome were grouped into distinct clans through a sequence similarity network, and each clan was built into an individual phylogenetic tree. Groups of CYPs which match the relative speciation pattern shown in the example–which also had high root expression–were selected for testing. D. grandiflorum sequences in blue, Aconitum spp. in orange, other Ranunculaceae in white, and reference sequences in black B ) GC-MS analysis and C ) LC-MS analysis of CYP candidates expressed in N. benthamiana . All assays have Cf DXS, Cf GGPPS, Dgr TPS1, and Dgr TPS2 coexpressed in addition to those listed. Mass spectra for all compounds are given in Supplementary Figures 9 and 12. These six CYPs were cloned from D. grandiflorum root cDNA and tested through transient expression in N. benthamiana . Each candidate was coexpressed with Dgr TPS1 and Dgr TPS2, and products were analyzed via GC-MS following ethyl acetate extraction. CYP701A127 and CYP71FH1 both showed activity in oxidizing the ent -atiserene ( 2 ) backbone ( Figure 3B ). Coexpression with either of these CYPs showed a depletion in 2 and the production of respective metabolites with a molecular ion at m/z 286 and retention of m/z 257 as the highest abundance fragment ion (Compounds 3 and 4 ; Supplementary Figure 9 ), consistent with two sequential oxidations of 2 to a carbonyl. A major product with a molecular ion at m/z 300 (compound 12 ) is also seen with CYP71FH1, which would suggest a net addition of two oxygen atoms and four oxidations from 2 . For the products of CYP71FH1, we scaled up biosynthesis in N. benthamiana to purify compounds and attempt to solve structures by NMR. While sufficient quantities were simple to produce through expression and extraction from roughly 30 g of infiltrated tissue, purification of the two major products from each other proved challenging. One fraction purified through a silica column was sufficiently enriched for the m/z 286 product that we could confirm the identity of 4 as ent -atiserene-20-al through NMR ( Supplementary Figures 10 - 11 ). The structure of the m/z 300 product ( 12 ) was not determined. The products of CYP701A127 gave weak signals by GC and may have been shuttled away to other products through conversion by endogenous N. benthamiana enzymes. We tentatively assigned CYP701A127’s product as ent -atiserene-19-al ( 3 ) based on its similar fragmentation pattern to 4 ( Supplementary Figure 9 ) and phylogenetic placement in the CYP701A subfamily ( Supplementary Figure 5 ). In our proposed biosynthetic pathway, we assumed that a pair of CYPs could oxidize both methyl groups at carbons 19 and 20 to aldehydes, and so we tested whether coexpression of both of these enzymes would further the pathway. Coexpression of each CYP and TPS revealed a depletion of both 2 and of both CYPs’ respective products when analyzing ethyl acetate extracts by GC-MS ( Figure 3B ). These assays were also analyzed by LC-MS on 80% methanol extracts, which revealed two products detectable through coexpression of CYP701A127 ( 13 and 14 ), five from CYP71FH1 ( 15 - 19 ), and one additional product with coexpression of both enzymes ( 20 ) ( Figure 3C and Supplementary Figure 12 ). Four of the products present with both CYPs coexpressed are an accumulation of those observed with CYP71FH alone (compounds 15 - 19 , including its major product 17 ), suggesting that these are products different than those detected by GC-MS for CYP71FH1 alone. This suggests that CYP71FH1 may share a partial functional redundancy with CYP701A127 in oxidizing the C19 methyl group ( Supplementary Figure 13 ). We cannot rule out, however, the possibility that an endogenous N. benthamiana enzyme (in particular a member of the CYP701A subfamily) could carry out the function of CYP701A127 in its absence when each other pathway enzyme is present. We further characterized this pair of CYPs against the remaining four candidates. Coexpression of both TPSs, both CYPs, and each remaining CYP candidate revealed that CYP729G1 can oxidize products formed by CYP701A127 and CYP71FH1 ( Figure 3C ). The molecular ions for products 21-25 suggest that they are each a single hydroxylation difference (additional 16 m/z) from major products for CYP701A127 and CYP71FH1 ( 15 - 19 ) alone ( Supplementary Figure 12 , and Supplementary Table 4 ). Additional CYP products observed in trace quantities are given in Supplementary Figure 14 and Supplementary Table 4 . Given that CYP701A127 and CYP71FH1 work in tandem and are both likely to carry out oxidations of relevant methyl groups to aldehydes, we opted to test candidates for further steps in the pathway to account for the possibility that the large number of products may accumulate primarily due to the absence of a downstream enzyme. Continuation of the Previously Proposed Biosynthetic Pathway In many alkaloid biosynthetic pathways, the formation of an alkaloid scaffold typically involves the accumulation of both an amine and aldehyde precursor 48 . The nitrogen present in the majority of diterpenoid alkaloids in Aconitum and Delphinium appears to be derived from ethylamine due to the attached -CH 2 CH 3 group (e.g. aconitine; Figure 1 ), while some metabolites presumably incorporate methylamine (-CH 3 ) or ethanolamine (-CH 2 CH 2 OH) 15 , 16 —the origin of which could come from decarboxylation of alanine, glycine, or serine, respectively. Serine decarboxylases are present in primary metabolism, and ethanolamine is a major component of plant phospholipids and is present as a free compound in plant cells 49 . A duplication of one of these enzymes in Camellia sinensis has been shown to decarboxylate alanine into ethylamine (AlaDC) in theanine biosynthesis 50 , although this is a specialized metabolism enzyme which is not present across all plants. Additionally, Spiraea japonica —an evolutionarily distinct plant which makes similar compounds—has been shown to produce isotopically labeled diterpenoid alkaloids through the addition of labeled serine 51 . In contrast to the steps elucidated thus far, the reaction of an amine and aldehyde to form an alkaloid scaffold could occur either spontaneously or through enzyme catalysis given the inherent reactivity between aldehydes and primary amines. Many of the major compounds detected by LC-MS in CYP screening have exact masses consistent with the product of a condensation between a diterpenoid scaffold and ethanolamine ( Supplementary Table 4 ). While the predicted dialdehyde products 5 and 8 were not directly observed, the exact masses for the major products 17 (predicted neutral formula C 22 H 33 NO 2 ) and 23 (predicted neutral formula C 22 H 33 NO 3 ) seen in our LC-MS data ( Supplementary Figure 12 ) are consistent with condensation of ethanolamine with 5 and 8 , respectively. An iminium ion formed through condensation of an amine and aldehyde is inherently unstable, and quenching of this cation through either a substitution or reduction 48 can avoid hydrolysis separating them back into their constituent parts. In the case of diterpenoid alkaloids, it likely follows both mechanisms based on the number of carbon-carbon bonds present on both attachment points for the nitrogen-containing group ( Figure 4A ). Carbon 20 almost always contains an extra carbon-carbon bond relative to 2 and the intermediate 4 , while carbon 19 does not, similar to both 2 and the putative intermediate 3 . This suggests that incorporation at carbon 19 involves a reductase, and at carbon 20 a spontaneous intramolecular condensation. Download figure Open in new tab Figure 4: Nitrogen incorporation into diterpenoid alkaloids. A ) Four example skeleton types of diterpenoid alkaloids. Highlighted in purple is a common attachment point (C19) for nitrogen-containing groups that does not typically form an additional carbon-carbon bond, and in yellow are examples of additional carbon-carbon bonds formed on the nitrogen-containing group’s second attachment point (C20), or a second carbon-nitrogen bond in an unresolved iminium ion in the case of 10 . B ) Coexpression analysis on A. vilmorinianum roots. Four predicted orthologs to the first four pathway genes are drawn as orange nodes, and all genes coexpressed with these four are drawn in a network with nodes representing transcripts and edge width representing magnitude of coexpression between them. Transcripts connected to a greater number of orange nodes are shown further to the outside, with transcripts in the center only connected by two degrees of separation. Drawn in black are three putative reductases which were selected for testing, with DAS highlighted. C ) LC-MS chromatograms for putative reductase testing in N. benthamiana . All genes have Cf DXS and Cf GGPPS coexpressed in addition to those listed, as well as Dgr TPS1, Dgr TPS2, CYP701A127, and CYP71FH1, or their respective A. plicatum orthologs. D. grandiflorum genes are written in blue and respective orthologs of each gene from A. plicatum are written in orange. Chromatograms are TICs except where otherwise indicated. D ) Isotope pattern of atisinium, after coinfiltration of isotopically labeled ethanolamine (1,1,2,2-D 4 ) with Agrobacteria carrying atisinium-forming genes from A. plicatum in N. benthamiana . The search for a putative reductase is not straightforward when considering how many different enzyme families from which this function could evolve. To search for the next step(s), we carried out a coexpression analysis to identify genes which were coexpressed with the first four enzymes already characterized in the pathway ( Dgr TPS1, Dgr TPS2, CYP701A127, and CYP71FH1). Given that our RNA sequencing only contained single replicates of each tissue type, we carried out this analysis on data collected for A. vilmorinianum instead ( Figure 4B ), which involved sequencing three replicates of root tissue at three different stages of development 31 . Among the genes found to be highly coexpressed with the A. vilmorinianum orthologs of our first four pathway genes, three were identified as putative reductases, and so the respective orthologs from D. grandiflorum and A. plicatum were selected for characterization. Coexpression Analysis Reveals that a Predicted Reductase is Active in the Pathway Each of these three putative reductases were cloned from D. grandiflorum root cDNA and tested for activity through transient expression in N. benthamiana and LC-MS analysis on 80% methanol extracts. Testing of each candidate was carried out along with either the first four pathway enzymes ( Dgr TPS1, Dgr TPS2, CYP701A127, and CYP71FH1) or these four plus CYP729G1. In addition, we cloned every respective A. plicatum ortholog of each CYP listed above and included these in testing for the same combinations. Coexpression of Dgr DAS (diterpenoid alkaloid synthase) with only the first four pathway enzymes led to a suppression in previously observed products ( 15 - 20 ) and the formation of a new peak 7 with a proposed neutral formula of C 22 H 33 NO (exact mass 328.2656 in ESI+; calculated m/z 328.2640: Figure 4C and Supplementary Figure 15 ). Coexpression of Dgr DAS with the first four pathway enzymes and CYP729G1 did not suppress all of CYP729G1’s products ( 21 - 25 ), however did lead to the formation of a new peak 10 which was identified as atisinium ( Figure 4C and Supplementary Figures 15 and 16), a diterpenoid alkaloid with antiplasmodial activity 23 . Comparison of MS/MS fragmentation spectra of 10 and 7 showed highly similar fragmentation patterns, thus supporting their proposed structural similarity and the role of CYP729G1 in the biosynthetic pathway of atisinium ( Supplementary Figure 17 ). To confirm the conservation of this biosynthetic step between both genera, the A. plicatum DAS ortholog ( Apl DAS) was cloned and characterized, which also resulted in atisinium ( 10 ) formation upon coexpression with A. plicatum ’s respective orthologs for preceding pathway genes ( Figure 4C ). Notably, phylogenetic analysis reveals that Dgr DAS and Apl DAS (Pfam domain PF13460) belong to a distinct clade with homologs found in green algae, bryophytes, lycophytes, and angiosperms, however no other enzyme within this clade has been characterized to our knowledge ( Supplementary Figure 18 and Supplementary Table 2 ). Comparison of MS/MS fragmentation spectra of 10 and 7 showed highly similar fragmentation patterns, thus supporting their proposed structural similarity and the role of CYP729G1 in the biosynthetic pathway of atisinium ( Supplementary Figure 17 ). Although the nitrogen in 7 and 10 appears to be derived from ethanolamine, consistent with predicted chemical formulas for 17 and 23 , many diterpenoid alkaloids contain an ethylamine group. We carried out an initial test to determine the source of nitrogen through coexpression of an alanine decarboxylase from C. sinensis (AlaDC) 48 , which would presumably increase the supply of ethylamine in planta . We observed very little change in product profile upon coexpression of this enzyme with preceding pathway enzymes except for trace amounts of one additional peak per combination ( 26 , or 27 with CYP729G1 included). The compounds 26 and 27 have exact masses consistent with a condensation between ethylamine and the putative intermediates 5 and 8 (predicted neutral formulas C 22 H 33 NO and C 22 H 33 NO 2 , respectively), although 17 and 23 (or 7 and 10 with addition of Dgr DAS) were still seen as the major products ( Supplementary Figure 15 ). We therefore sought to test the substrate specificity of Apl DAS to assess its potential involvement in formation of various scaffolds that serve as branching points in diterpenoid alkaloid biosynthetic pathways. In addition to the heterologous expression of characterized genes in N. benthamiana , we co-infiltrated isotopically labeled ethanolamine (1,1,2,2-D₄) or ethylamine (D₅). Atisinium ( 10 ) isotopic peak distribution demonstrated the incorporation of labeled ethanolamine ( Figure 4D ), whereas no novel peaks corresponding to an ethylamine-derived analogue of atisinium were detected. We observed a similar incorporation of labeled ethanolamine in compounds 17 and 23 in the absence of Apl DAS ( Supplementary Figure 19 ). This raised the question of whether ethanolamine is the preferred source of nitrogen across the majority of diterpenoid alkaloids, or if DAS is simply a branching point towards a more narrow range of ethanolamine-containing diterpenoid alkaloids. Ethanolamine as a preferred source of nitrogen in Aconitum diterpenoid alkaloids In order to better understand the biosynthesis of diterpenoid alkaloids and particularly the source of nitrogen, we attempted to establish A. plicatum hairy root cultures and to perform labeled substrate feeding in sterile plant cuttings. However, hairy root cultures could not be established and sterile cuttings did not remain viable under the set incubation conditions. We therefore developed callus cultures of A. plicatum as an alternative system. Comparative metabolomic analysis of callus cultures and A. plicatum tissues (leaf, root and flower) showed that callus cultures produce a significant amount of terpenoid alkaloids, indicating that they represent a suitable model for investigation of DA biosynthesis ( Figure 5A ). Established callus cultures were fed with either isotopically labeled ethanolamine (1,1,2,2-D 4 ), ethylamine (D 5 ), or 1 x PBS (control) over the course of one month. Due to the scarcity of available standards and lack of diterpenoid alkaloids in spectral libraries, we opted for computational solutions, in order to obtain a list of all detected and predicted diterpenoid alkaloids from callus LC-MS analysis ( Supplementary Figure 20 ; See Methods for details). Computational solutions for metabolite annotation problems in untargeted metabolomics have seen an expansion in recent years, with SIRIUS 52 being one of the most prominent. It relies on isotope patterns and fragmentation trees for molecular formula prediction, with further steps involving formula ranking (ZODIAC 53 ), prediction of a molecular fingerprint of the query compound through CSI:FingerID 54 and compound class prediction (CANOPUS 55 ). Relying on this approach, features were detected and aligned across all samples using MZmine 3 56 , ensuring consistent m/z and retention time assignment for each feature across feeding conditions. Out of 1,331 aligned features with MS/MS spectra, 144 were classified by SIRIUS as belonging to terpenoid alkaloids. Filtering only for features that were consistently present across the three feeding conditions, defined as being detected in at least one replicate of each condition, as well as the ones whose classification had a probability score higher than 0.6 further reduced the list to 60 putative terpenoid alkaloids. An additional feature, atisinium ( 10 ), was added manually, as it was not ranked as the top annotation by the computational pipeline and was consequently filtered out in later steps, thus resulting in a final table with 61 detected features. Interestingly, out of those, 41 features exhibited presence of deuterium-labeled isotopologue peaks exclusively in ethanolamine-fed callus cultures. More specifically, two features showed exclusively the M+4D isotopologue, six features displayed both M+3D and M+4D isotopologues, while the remaining features showed only the M+3D isotopologue ( Figure 5B ). No features showing the presence of isotopologue corresponding to M+5D were detected with our pipeline. Both atisinium and aconitine showed incorporation of deuterium atoms in the ethanolamine-feeding condition, as evident from their isotope patterns ( Figure 5C , D). The incorporation was further supported with MS/MS spectra, which confirmed the mass shift while retaining the same fragmentation pattern for both compounds ( Supplementary Figure 21 ). To further investigate the origin of nitrogen in these compounds, callus cultures were fed with isotopically labeled ʟ-serine (2,3,3-D₃, 15 N), resulting in a low-intensity isotopologue peaks for both compounds, consistent with incorporation of three deuterium atoms and one 15 N ( Supplementary Figure 22 ), in agreement with serine decarboxylation to ethanolamine. Download figure Open in new tab Figure 5: Deuterium incorporation in callus culture A) An UpSet plot showing shared and unique putative terpenoid alkaloids across callus cultures and leaf, flower and root tissue of A. plicatum. Filled circles indicate presence of a feature in the given tissue, while vertical bars represent the number of features shared among the indicated tissue combinations. B) LC-MS features classified as “Terpenoid alkaloids” by CANOPUS across feeding conditions for which M+3D and M+4D isotopologues were detected, indicating the role of ethanolamine in their biosynthesis. As no features corresponding to M+5D were detected, this is omitted from the figure. C) Isotope pattern of atisinium, showing isotopologue peaks corresponding to the incorporation of three and four deuterium atoms in ethanolamine-fed callus cultures. D ) Isotope pattern of aconitine, showing the isotopologue peak corresponding to incorporation of three deuterium atoms in ethanolamine-fed callus cultures. Despite ethylamine being intuitively inferred as the source of nitrogen, given its presence as the side group in the majority of diterpenoid alkaloids (aconitine included, Figure 5D ), no incorporation was observed. The difference in the number of detected putative terpenoid alkaloids and those with incorporated labeled substrate could reflect the presence of stored metabolites versus those actively synthesized during the feeding. Furthermore, the detection of secreted labeled diterpenoid alkaloid compounds in the agar could suggest their role in plant-plant communication, which has been poorly investigated so far 57 . Discussion Through a combination of comparative transcriptomics and coexpression analysis, we have identified six enzymes sufficient to reconstitute the biosynthetic pathway towards diterpenoid alkaloids conserved between the Delphinium and Aconitum genera within the Ranunculaceae family. There are hundreds of diterpenoid alkaloids in this family, and the identification of these enzymes will serve as the basis for further pathway discovery towards specific metabolites. This work highlights the utility of cross-referencing transcriptomic data between genera as an orthogonal filter for selection of candidate enzymes beyond the analysis of a single species, as it likely would not have been possible to identify all of these enzymes otherwise given the inherent complexity of these pathways. The size and ploidy of genomes throughout Delphinium and Aconitum vary widely, exemplified by Delphinium montanum , which is an autotetraploid with a predicted genome size of roughly 40 Gb 46 (2n = 32 58 ). The seven species studied here have a range of predicted ploidy levels ( D. grandiflorum : 2n = 16; A. carmichaelii : 2n = 32/64 – depending on cultivar; A. japonicum : 2n = 32; A . vilmorinianum : 2n = 16; A. kusnezoffii: 2n=32; A. plicatum: 2n=32; A. lycoctonum: 2n=16 ) 58 – 60 , and it has been suggested that, at least in the Aconitum genus, there may have been multiple recent events of polyploidization and diploidization 45 . This fits with the model of our initial biosynthetic pathway—and the phylogenetic relationships of these genes—in which we predicted that the first three steps may be recent duplications of primary metabolism enzymes given the similarity of these predicted intermediates to those in gibberellin biosynthesis 43 . Following our characterization of the TPS pair which produce ent -atiserene ( 2 ), Mao et al. 37 published a characterization of the entire TPS family from A. carmichaelli and identified enzymes orthologous to ours ( Dgr TPS1/ Apl TPS1 and Dgr TPS2/ Apl TPS2), as well as recently-duplicated paralogs of each which produce ent- CPP ( 1 ) and ent -kaurene. Very recently, Luo, Zhou, et al . 38 identified CYPs which oxidize the ent -atiserene backbone from A. carmichaelli and A. coreanum , including a member of the CYP701A subfamily (typically involved in gibberellin biosynthesis 61 ) which is orthologous to our CYP701A127 and CYP701A144 in addition to an ortholog of CYP71FH1 and CYP71FH4. It remains to be seen whether duplications of downstream gibberellin pathway genes could also be involved in further biosynthetic steps in diterpenoid alkaloid biosynthesis. It should be noted that Dgr TPS1 and Apl TPS1—being ent -CPP ( 1 ) synthases—are technically not enzymes that produce specialized metabolites. Given their high and exclusive expression in roots relative to their putative central metabolism paralogs, however, they are likely dedicated to specialized metabolism. A similar phenomenon is seen in both Oryza sativa 62 and Zea mays 63 , where two copies of an ent -CPP ( 1 ) synthase are present; one which is involved in gibberellin biosynthesis and another which is inducible by pathogens for the production of defensive ent -CPP-derived specialized metabolites. Given the presence of duplicate ent -CPP ( 1 ) synthases in each of these independent lineages of plants, there is likely a strong evolutionary pressure for the ability to tightly regulate these competing pathways. As we transitioned between different classes of enzymes in the pathway, we varied the approach to identify each based on what information was necessary. For the TPSs, for example, few enough transcripts were present in our assembly that we relied solely on data from D. grandiflorum . For the CYPs, cross-referencing both Delphinium and Aconitum datasets was essential given the presence of two to three hundred unique transcripts in each assembly. Orthologous genes present across each species have persisted over roughly 27 million years since the speciation between the common ancestors of each genera 64 , and choosing to work across both allowed us to filter these hundreds of candidates down to just six. Finally, even with tissue and species-specific transcriptomic data, the following step for nitrogen incorporation was not obvious; therefore, coexpression analysis allowed us to search for new candidates without prior knowledge of which enzyme families to search. Throughout the process of characterizing various steps in the pathway, not every intermediate product was identified prior to moving forward with following steps. Often it can be difficult to differentiate “actual” intermediates in terms of whether the observed products are relevant to the pathway of interest, or the result of an incomplete reconstruction of the pathway or a heterologous host’s interference. In the process of discovering the biosynthetic pathway for the diterpenoid forskolin from Coleus forskohlii , for example, coexpression of an incomplete set of genes in N. benthamiana led to an accumulation of many side products that were not present once the entire pathway was reconstructed (five CYPs acting on a single diterpene scaffold and at least sixteen total products) 65 . A similar–but deconstructive–example can be seen with accumulation of precursors and side products for the scopolamine pathway in Atropa belladonna following virus-induced gene silencing of various pathway steps 6 . This may be reflective of the capacity for specialized metabolism to evolve towards a range of different products with only a small change (e.g. a single gene deletion) in their respective biosynthetic pathways. We identified the activity of the two TPSs and confirmed our predicted activity of the first two CYPs, but thereafter we decided to test enzymes in different combinations to identify new steps in case the side products seen were due to a similar phenomenon. Given the appearance of multiple products with the first four pathway enzymes and convergence to primarily a single product 7 upon coexpression with Dgr DAS or Apl DAS, the initial range of products beyond the predicted intermediate 17 could be the result of incomplete pathway reconstruction. We initially proposed that ethylamine was the source of nitrogen in this pathway due to the abundance of diterpenoid alkaloids that have been identified with an ethyl group bonded to the nitrogen. The presence of a minor product forming upon coexpression with AlaDC–which would presumably increase the supply of ethylamine–was expected based on the presence of reactive aldehydes in our intermediates, however, very little product was observed in this case. We demonstrate here through isotope feeding in N. benthamiana that the preferred substrate for Apl DAS is ethanolamine, and in A. plicatum callus cultures that diterpenoid alkaloids generally incorporate ethanolamine preferentially over ethylamine, even in cases like aconitine where an ethylamine group is present in the final product. It remains to be seen how this is implicated in further biosynthetic steps towards more complex diterpenoid alkaloids. Similarly, probing substrate specifics and kinetics of Apl DAS through recombinant assays in vitro could be valuable in complementing our in planta characterization. We attempted engineering CYP-based substrate production through yeast microsomes 66 . However, our results indicated the need for substantial optimization for recombinant CYPs. Beyond this immediate question, more remain in the discovery of diterpenoid alkaloid pathways. Perhaps the most important is the differentiation between the C20 and C19/C18 metabolites, and at which point this occurs. With the central scaffold-forming steps investigated here, which are presumably shared between all diterpenoid alkaloids, further pathway discovery work towards more highly decorated metabolites within this class can be investigated. Some may be a significant challenge, exemplified by some of the compounds shown in Figure 1 , as there are likely many more enzymatic steps involved in their biosynthesis. Further discovery of such downstream steps will likely require different methodology than employed here given the species-and tissue-specificity of some of these products. The hydroxylation introduced by CYP729G1 and CYP729G2 appears to be present in many C20 compounds 24 , however it remains to be seen if this may be implicated in the rearrangement towards C19 compounds and if 7 and 10 represent metabolic branch points, as not all CYP729G orthologs across species studied here have identical expression patterns across tissue types relative to other pathway enzymes ( Supplementary Figure 8 ). Considering this variable expression, further work may benefit from correlating metabolomic and transcriptomic data to differentiate chemical conversions present in distinct lineages and tissue types in conjunction with the cross-species transcriptomics employed here. Materials and Methods Plant material, RNA isolation, and cDNA synthesis D. grandiflorum plants were grown in a greenhouse under ambient photoperiod and 24 °C day/17 °C night temperatures. RNA isolation, quality assessment, RNA sequencing, and cDNA synthesis for D. grandiflorum was carried out as described in Miller et al. 2020 67 . Total RNA was isolated from flowers, leaves, and roots with the Spectrum Plant Total RNA Kit (Sigma-Aldrich), and DNA was removed with the DNA-free DNA Removal Kit (Thermo Fisher Scientific). Quality of the resulting RNA was assessed with a Qubit (Thermo Fisher Scientific) and RNA-nano assays (Agilent Bioanalyzer 2100). RNA sequencing was carried out on an Illumina HiSeq 4000 at Novogene (Sacramento, CA, USA) Aconitum plicatum and Aconitum lycoctonum plants were collected from the Charles University Botanical Garden. For these species, RNA was isolated from roots, flowers, leaves, stems, and (for A. lycoctonum ) fruits using the RNeasy kit (Qiagen) according to the manufacturer’s instructions. The transcriptome library preparation and sequencing were performed at the Beijing Genomics Institute using the DNBSEQ Eukaryotic Strand-specific mRNA library. D. grandiflorum and Aconitum spp. de novo transcriptome assembly and analysis RNA-seq data were obtained through RNA sequencing on an Illumina HiSeq 4000 for D. grandiflorum , and from DNBseq platform for A. plicatum and A. lycoctonum . Raw data are accessible on the NCBI Sequence Read Archive (SRA; ncbi.nlm.nih.gov/sra ) under the accession PRJNA1261909. Additional data for A. carmichaelii (PRJNA415989) 33 , A. japonicum (PRJDB4889), A. kusnezoffii (PRJNA670255), and A. vilmorinianum (PRJNA667080) 31 were obtained from the SRA. Reads were filtered for quality by a Phred score of 10 or higher and adapters trimmed with TrimGalore (v0.6.10; github.com/FelixKrueger/TrimGalore ). Unless otherwise specified, a maximum of 150 million read pairs (or single-end reads) were used for each transcriptome assembly, and were taken evenly across samples. Transcriptome assembly and analysis followed a similar pipeline as described in Miller et al. 2020 67 . Transcriptomes were assembled de novo with Trinity (v2.8.5) 68 and open reading frames and translations were found with TransDecoder (v5.7.1) 69 . Transcriptomes were clustered at 99% sequence identity by local alignment to at least 15% of the larger sequence with CD-HIT (v4.8.1) 70 , 71 , and any sequences filtered out by this step were also filtered out from the translated TransDecoder output. Expression levels were calculated with Salmon (v0.14.1) 72 with the transcriptome filtered by CD-HIT used as the index. The results of this analysis are accessible at doi.org/10.5281/zenodo.15384649 , and a Nextflow pipeline which automates this process can be found at github.com/GarretPMiller/DiterpenoidAlkaloids . Initial assembly of the D. grandiflorum transcriptome resulted in incomplete transcripts for Dgr TPS1 and Dgr TPS2 (only ∼75% coverage of reference sequences), and although this was prior to our characterization of these enzymes, we noted that these transcripts were most likely misassembled given their high expression and likelihood of being involved in the pathway. Reassembly of the D. grandiflorum transcriptome was therefore done with only data acquired from root tissue, with reads from each tissue type mapped to this assembly. Transcripts for both of these genes in the new assembly aligned to the entire length of reference sequences, and so this assembly was used for further analysis. Sequence Similarity Networks and Phylogenetic Trees Sequences from all transcriptome assemblies, predicted genes from two other Ranunculaceae species ( Thalictrum thalictroides : PRJNA439007; Coptis chinensis : PRJNA662860), and reference sequences (given in Supplemental Dataset 1) were used to build the sequence similarity network and all phylogenetic trees for TPS and CYP discovery. The CYP sequence similarity network was made with BLAST (v2.7.1+) 73 at a sequence identity threshold of 42% and visualized with Cytoscape 74 . Sequences which only had one connection (primarily fungal contaminants and low percent identity reference sequences) were removed from the network. Multiple sequence alignments used for phylogenetic tree construction were made with Clustal Omega (v1.2.4) 75 (--iterations 3, otherwise default settings), and maximum likelihood phylogenetic trees were made with RAxML (v8.2.12) 76 (model: PROTGAMMAAUTO; algorithm: a). All trees were the result of 1,000 bootstrap replicates, except where otherwise indicated. Outgroups are indicated in their respective figure legends. Vector images of all trees used for TPS and CYP discovery are accessible at doi.org/10.5281/zenodo.15384649 . Sequences homologous to Dgr DAS and Apl DAS were mined from each Delphinium and Aconitum transcriptome assembly in addition to predicted genes from a wide range of model species as shown in Supplemental Table 2. All sequences meeting a BLASTp threshold of 1e-10 with Dgr DAS as the query sequence from these assemblies, model species, and UniProt were grouped into a sequence similarity network with a sequence identity threshold of 41%. All sequences which were not separated entirely from Dgr DAS were further filtered by clustering at 100% identity (by amino acid sequence, as previous clustering was done at the transcript level) and by those with an alignment length of at least 110 amino acids (∼45% of query sequence) in the initial BLASTp search. The phylogenetic tree shown in Supplemental Figure 18 was made as described above, with the exception that no outgroup was specified. Coexpression analysis Our assembly for A. vilmorinianum was used for coexpression analysis. To minimize the computational burden, we reduced the analysis through clustering by 99% identity with CD-HIT (v4.8.1) 70 , 71 , calculated expression levels through mapping reads to this clustered transcriptome, and eliminated any transcript with no samples that had at least 20% the expression level (in TPM) as any sample for either TPS. Coexpression analysis was carried out as described by Wisecaver et al. 2017 77 (pipeline at: https://github.itap.purdue.edu/jwisecav/mr2mods ). The resulting coexpression network shown in Figure 4B shows only genes with one or two degrees of separation from any of the first four genes in the pathway (respective orthologs from A. vilmorinianum of Dgr TPS1/ Apl TPS1, Dgr TPS2/ Apl TPS2, CYP701A127/CYP701A144, and CYP71FH1/CYP71FH4) based on a mutual rank (MR) cutoff of e^(-(MR-1)/5) > 0.01. Putative reductases from these coexpressed genes were identified by InterProScan (v5.59) 78 annotations. Cloning Candidate genes were PCR-amplified from root cDNA and cloned into pEAQ-HT 79 through In-Fusion cloning. Constructs for Zm AN2, Nm TPS1, and Nm TPS2 in pEAQ (used as positive controls for ent -CPP, ( + )-CPP, and ent -kaurene biosynthesis, respectively) were made by Johnson et al. 2019 41 . Nucleotide (verified by Sanger sequencing) and amino acid sequences for all Delphinium and Aconitum genes tested here are given in Supplemental Dataset 1. Transient expression in N. benthamiana, product scale-up, and NMR analysis Transient expression in N. benthamiana for screening assays was carried out as described in Miller et al. 2020 67 , with the exception of solvents used to extract each set of assays as described in the main text. For the co-infiltration of ethanolamine (1,1,2,2-D 4 ) and ethylamine (D 5 ), the compounds were dissolved in distilled water, filter sterilized, and co-infiltrated in N. benthamiana leaves 1 day after the candidate genes were infiltrated. For ent -atiserene and ent -atiserene-20-al scaleup, three whole plants were infiltrated with a syringe, and approximately 15/30 g of fresh weight were extracted with hexane/ethyl acetate (respectively). Products were purified through silica chromatography with 10% ethyl acetate:90% hexane as the mobile phase. Initial purification was carried out with approximately 100 mL of oven-dried silica, and fractions were collected in approximately 3 mL increments and assessed for purity by GC-FID. Fractions containing desired products were further purified with approximately 1.5 mL oven-dried silica in a Pasteur pipette, with fractions collected in 1 mL increments and purity assessed by GC-FID. NMR analysis was carried out on a Bruker 800 MHz spectrometer equipped with a TCl cryoprobe using CDCl 3 as the solvent. CDCl 3 peaks were referenced to 7.26 and 77.00 ppm for 1 H and 13 C spectra, respectively. GC-MS analysis All GC-MS analyses were performed on hexane or ethyl acetate extracts (described for each case in the text) with an Agilent 7890A GC with an Agilent VF-5ms column (30 m x 250 µm x 0.25 µm, with 10m EZ-Guard) and an Agilent 5975C mass spectrometer. The inlet was set to 250°C splitless injection of 1 µL, He carrier gas (1 ml/min), and the detector was activated following a 3 min solvent delay. Mass spectra were generated using 70 eV electron ionization with a scan range of m/z 50 to 350. The following method was used for analysis of each sample presented in the text: temperature ramp start 40 °C, hold 1 min, 40 °C/min to 200 °C, hold 2 min, 20 °C/min to 280 °C, 40 °C/min to 320 °C; hold 5 min. For initial GC-MS analysis of Apl TPS1 and Apl TPS2 products shown in Supplementary Figure 3 , the GC method varied by the following parameters: 275 °C splitless injection, scan range of m/z 50 to 400, 4.5 minute hold after reaching 200 °C, 20 °C/min to 240 °C, 10 °C/min to 280 °C. Figures for chromatograms and mass spectra were generated with Pyplot. LC-MS analysis All LC-MS analyses (except as specified below) were performed on 80% methanol : 20% H 2 O N. benthamiana extracts with a Waters Xevo G2-XS quadrupole ToF mass spectrometer with a Waters ACQUITY column manager and Waters ACQUITY BEH C18 column (2.1 x 100 mm; 1.7 µm). Injection volume for each sample was 10 µL, and flow rate was set to 0.3 mL/min with a column temperature of 40 °C. The mobile phase consisted of 10 mM ammonium formate (pH 2.8) (Solvent A) and acetonitrile (Solvent B) with the following method: initial 99% A : 1 % B, continuous gradient to 2% A : 98% B over 12 min, hold for 1.5 min, continuous gradient to 99% A : 1% B over 0.1 min, hold 1.5 min. Mass spectra were generated through electrospray ionization in positive-ion mode with leucine enkephalin as a lockmass, and continuum peak acquisition were collected with a mass range of m/z 50-1500 and a scan duration of 0.2 s. Capillary and cone voltage were 3.0 kV and 40 V, respectively, cone and desolvation gas flow rates were 40 and 600 L/h, respectively, and source and desolvation temperatures were 100 °C and 350 °C, respectively. High-energy spectra were generated with argon as the collision gas and a voltage ramp from 20 to 80 V. Figures for chromatograms and mass spectra were generated with Pyplot. LC-MS analyses of isotopically labeled atisinium were performed on 80% MeOH extracts of N. benthamiana with a Vanquish Flex UHPLC system interfaced to an Orbitrap ID-X Tribrid mass spectrometer using heated electrospray ionization (H-ESI). For LC analysis, Waters ACQUITY BEH C18 column (2.1 x 150 mm; 1.7 µm) was used. Injection per sample was 1 µL, with flow rate of 0.35 mL/min with the column temperature of 40 °C. The mobile phase consisted of water with 0.1% formic acid (Solvent A) and acetonitrile with 0.1% formic acid (Solvent B) with the following method: initial 95% A : 5 % B, continuous gradient to 100% B over 15.5 min, hold for 1.8 min, and a continuous gradient to 95% A over 2 minutes. Mass spectra were generated through H-ESI in positive mode, and continuum peak acquisition was collected with a mass range of m/z 100-1000. Capillary voltage was at 3.0 kV, ion transfer tube temperature was 325 °C, auxiliary gas flow rate 10 L/min, vaporizer temperature 350 °C, sheath gas flow rate 50 L/min, MS resolution 60,000 (at m/z 200), RF Lens 45% and maximum injection time 118 ms. The same method was used for the analysis of callus cultures, except the resolution was increased to 120,000 (at m/z 200) to improve the distinction of isotopic peaks arising as a result of deuterium incorporation. For ʟ-serine (2,3,3-D 3 , 15 N) fed callus, the resolution was increased to 500,000 (at m/z 200) to allow separation of the 15 N isotopic peak. As these measurements were acquired in a separate run, control samples were re-acquired under the same conditions to enable direct comparison. Callus culture establishment, substrate feeding and metabolite extraction A. plicatum petioles were cut into 0.5 cm pieces and sterilized by immersion in 70% ethanol over 2 minutes, followed by 20 minutes in 20% bleach (sodium hypochlorite) and rinsed with sterile distilled water. The sterilized petioles were placed on ½ Murashige and Skoog (MS) medium (Duchefa Biochemie, M0222) supplemented with 0.8% agar (Sigma-Aldrich, A7921), 3% sucrose, 0.1 mg/L kinetin and 1 mg/L 1-Naphthaleneacetic acid (NAA). Cultures were incubated in darkness at room temperature until callus formation was observed. Established calli were then transferred to fresh medium and maintained under the same conditions. For the substrate feeding studies, calli were divided into the following groups: (1) ethanolamine (1,1,2,2-D 4 )-fed (Cambridge Isotopes Laboratories, DLM-552-0.1), (2) ethylamine (D 5 )-fed (Cambridge Isotopes Laboratories, DLM-3471-0.5), (3) ʟ-serine-fed (2,3,3-D 3 , 15 N) (Cambridge Isotopes Laboratories DNLM-6863-0.25) and (4) control group to which 1x PBS was added. A sterile 1 mM solution of each substrate was applied directly on the callus surface, biweekly over the course of one month. During this period, calli were kept in darkness at room temperature. For the metabolite extraction, calli were collected in 2 mL Safe-Lock Eppendorf tubes, weighed, and extracted with ethyl acetate at a 1:10 (w/v) ratio. Samples were homogenized using a steel bead in a Qiagen TissueLyser. After centrifugation at 18,000 x g, the supernatant was collected and transferred to LC-MS vials. The same extraction protocol was used for A. plicatum tissues—leaf, root and flower. Computational metabolomics analysis Raw LC-MS data files were converted to open format (.mzML) using MSConvert 80 tool from ProteoWizard 81 package. Untargeted feature detection was performed in MZmine 3 56 (version 4.4.3). Briefly, the mass detection was based on the factor of lowest signal, which was set at 6.001 and 2.5 for MS1 and MS2 respectively. All signals below this threshold were discarded. Extracted ion chromatograms (EIC) were built for each m/z value that was detected over a minimum of 5 consecutive scans with minimum intensity of 1.0E5, with m/z tolerance between scans being 0.002 (or 10 ppm), and minimum absolute height of 5.0E5. Chromatograms were smoothed using a Savitzky–Golay filter (window size = 5 scans), after which EIC were resolved using the Local Minimum Feature Resolver module with the following parameters: chromatographic threshold= 93%; minimum search range: 0.05; minimum absolute height 5.0E4; minimum ratio of peak top/edge: 1.90; peak duration range: 0.03-0.60; minimum scans: 6. MS2 scans were paired to precursor features using an m/z tolerance of 0.01 (10 ppm) and retention-time constraints based on feature edges. Across all samples, features were aligned (Join aligner module) with an m/z tolerance of 0.002 or 5 ppm (weight=3) and a retention-time tolerance of 0.03 min (weight 1). Feature List Row Filter was used to filter features with retention time 2-17 minutes, and m/z 272-900. Peak Finder was used to look for missing peaks with the following parameters: intensity tolerance: 20%; m/z tolerance: 0.0010 (5 ppm); retention time tolerance: 0.03 minutes; minimum scans: 5. Duplicate Peak Filter module was used with following parameters: filter module: new average; m/z tolerance: 0.0008 (5 ppm); retention time tolerance: 0.03 minutes. This generated a feature list where each detected isotopic peak was retained as an individual feature. The second feature list was generated in MZmine 3 for SIRIUS software (v6.0.7) analysis using the same steps as the previous batch file, with addition of two extra modules which were necessary for SIRIUS analysis. Isotope grouper module was used with the following parameters: m/z tolerance of 0.0015 or 3 ppm; retention time tolerance: 0.03 min; maximum charge: 2; representative isotope: most intense, and Isotope Finder module was used with m/z constraints 0.0005 or 3 ppm and elemental constraints (H,C,N,O,S). The steps used for comparison of callus and A. plicatum tissues were the same as the aforementioned list, with minimum absolute height set to 5.0E5 in Local Minimum Feature Resolver module. For SIRIUS analysis of both datasets, default parameters were used except for the instrument type, which was set to Orbitrap. Molecular formula prediction was done based on isotope pattern and fragmentation tree reconstruction, with formula ranking refined using ZODIAC. Feature properties and compound class were computed using CSI:FingerID module and CANOPUS, respectively. Jupyter Notebook was used to filter SIRIUS results, creating a database of all compounds classified as terpenoid alkaloids. For each feature in the database, a theoretical m/z was calculated corresponding to incorporation of three, four or five deuteriums. Features in the MZmine output matching these m/z values within a 5 ppm mass tolerance and retention time tolerance of 0.05 min, were reported as showing incorporation of the labeled substrate The used script, as well as the batch files and the final output table can be freely accessed at https://github.com/lalalana5/Callus-culture-isotope-labelling/tree/main . Each predicted compound with incorporated deuterium was manually verified by inspecting the raw data. Features resulting from carryover between injections were excluded from further analysis. Data Availability RNA sequencing data for D. grandiflorum , A. plicatum , and A. lycoctonum can be found at the NCBI Sequence Read Archive under the BioProject accession number PRJNA1261909. Nucleotide sequences verified by Sanger sequencing for each characterized gene can be found in GenBank with the following accessions: ( Dgr TPS1: PV652189), ( Apl TPS1: PV652199), ( Dgr TPS2a: PV652190), ( Dgr TPS2b: PV652191), ( Apl TPS2: PV652200), (CYP701A127: PV652192), (CYP701A144: PV652201), (CYP71FH1: PV652193), (CYP71FH4: PV652202), (CYP729G1: PV652194), (CYP729G2: PV652203), ( Dgr DAS: PV652195), ( Apl DAS: PV652204). Additional CYP sequences from D. grandiflorum : (CYP71FH2: PV652196), (CYP72A932: PV652197), (CYP71FJ1: PV652198). These sequences, along with amino acid translations and all amino acid sequences of reference TPSs and CYPs used to build the phylogenetic trees can be found in Supplemental Dataset 1. Transcriptome assemblies, open reading frames, and expression values across RNA-seq samples are provided in the following Zenodo repository: doi.org/10.5281/zenodo.15384649 . All phylogenetic trees are also available in this repository ( doi.org/10.5281/zenodo.15384649 ). A Nextflow pipeline to carry out the transcriptome assembly and analysis process done here can be found at: github.com/GarretPMiller/DiterpenoidAlkaloids . Raw mzML files from the LC-MS analysis of A. plicatum callus culture feeding can be found in the Zenodo repository: https://doi.org/10.5281/zenodo.19150401 . The script, batch files, and final output table for the computational metabolomics of callus cultures can be found at: github.com/lalalana5/Callus-culture-isotope-labelling/tree/main. Funding GPM was supported by a fellowship from Michigan State University under the Training Program in Plant Biotechnology for Health and Sustainability (T32-GM110523). LMN is co-financed by the Governments of Czechia, Hungary, Poland, and Slovakia through Visegrad Grant 52410140 from the International Visegrad Fund. TP was supported by the Czech Science Foundation (GA CR) grant 21-11563M. BH and TBA gratefully acknowledge the US Department of Energy Great Lakes Bioenergy Research Center Cooperative Agreement DE-SC0018409. BH acknowledges support from AgBioResearch (MICL02454) and a generous endowment from James K. Billman, Jr., M.D. Author contributions Conceptualization: GPM, LMN, TP and BH; Methodology: GPM, LMN; Software: GPM, LMN; Formal Analysis: GPM, LMN, IP, KVW, TBA; Validation: GPM, LMN, TBA, MS, AB, TI, AT; Writing - original draft & editing: GPM, LMN; Supervision: TP, BH. Competing interests GPM, BH, IP, and KVW are inventors on a patent (US Patent Application Serial No.: 18/357,767) describing the production of diterpenoid alkaloids. SUPPLEMENTARY INFORMATION Download figure Open in new tab S. Figure 1. Angiosperm tree of life from Zuntini et al. 82 with mapped occurrence of diterpenoid alkaloids. The mapping is based on the literature review, highlighting the largest diversity of DA scaffolds observed within the Ranunculaceae family. Plant orders in the tree are separated by black dashed lines, whereas each leaf in the tree corresponds to the representative species of the genus, as described in the original publication. The original tree can be accessed at https://itol.embl.de/tree/14723112167277531728383616 . Download figure Open in new tab S. Figure 2. Maximum likelihood phylogenetic tree of candidate TPSs. This tree is an expanded view of that shown in Figure 2A . Branch lengths indicate substitutions per site and numbers at nodes represent percent support from 1,000 bootstrap replicates. A bifunctional ent -CPP/ ent -kaurene synthase from Physcomitrium patens is used as an outgroup. Leaves in blue ( D. grandiflorum ) and orange ( Aconitum spp. ) represent sequences either characterized in this study or respective orthologs from other species. Sequences are from open reading frames of assembled transcripts and so duplicates or assembly artifacts may be present. Abbreviations: Tth: Thalictrum thalictroides ; Cch: Coptis chinensis ; Dgr: Delphinium grandiflorum ; Apl: Aconitum plicatum ; Aly: Aconitum lycoctonum ; Aca: Aconitum carmichaelii ; Aja: Aconitum japonicum ; Avi: Aconitum vilmorinianum ; Aku: Aconitum kusnezoffii . Download figure Open in new tab S. Figure 3. Function and conservation of TPSs. Each panel shows GC-MS chromatograms of hexane extracts of N. benthamiana infiltrations. Each assay includes Cf DXS and Cf GGPPS in addition to those listed. A) Dgr TPS1 functions as an ent -CPP synthase. Zm AN2 is a reference ent -CPP synthase, and Nm TPS1 forms (+)-CPP. B) Expanded view of Figure 2B showing the enantioselectivity of Dgr TPS2a/2b. C ) Both A. plicatum TPS orthologs have the same function and enantioselectivity as Dgr TPS1 and Dgr TPS2. Retention times are not equal to other GC traces due to the use of a different GC method, as described in Methods. 1* , the dephosphorylated derivative of ent-CPP ( 1 ). Download figure Open in new tab Download figure Open in new tab Download figure Open in new tab S. Figure 4: 1 H, 13 C, HSQC, HMBC, COSY, and NOESY NMR spectra for ent-atiserene ( 2 ). Download figure Open in new tab S. Figure 5: Maximum likelihood phylogenetic tree of candidate CYPs from the CYP701 family. This tree represents the second largest cluster within the CYP71 clan shown in the sequence similarity network in Figure 3A . Branch lengths indicate substitutions per site and numbers at nodes represent percent support from 1,000 bootstrap replicates. CYP701A3 from Arabidopsis thaliana is used as an outgroup. Leaves in blue ( D. grandiflorum ) and orange ( Aconitum spp. ) represent sequences either characterized in this study or respective orthologs from other species, containing CYP701A127 ( D. grandiflorum ) and CYP701A144 ( A. plicatum ). Sequences are from open reading frames of assembled transcripts and so duplicates or assembly artifacts may be present. Abbreviations: Tth: Thalictrum thalictroides ; Cch: Coptis chinensis ; Dgr: Delphinium grandiflorum ; Apl: Aconitum plicatum ; Aly: Aconitum lycoctonum ; Aca: Aconitum carmichaelii ; Aja: Aconitum japonicum ; Avi: Aconitum vilmorinianum ; Aku: Aconitum kusnezoffii . Download figure Open in new tab S. Figure 6: Maximum likelihood phylogenetic tree of candidate CYPs from the CYP71 clan. This tree represents the largest cluster within the CYP71 clan shown in the sequence similarity network in Figure 3A . Branch lengths indicate substitutions per site and numbers at nodes represent percent support from 100 bootstrap replicates. CYP701A3 from Arabidopsis thaliana is used as an outgroup. Leaves in blue ( D. grandiflorum ) and orange ( Aconitum spp. ) are enlarged in the center and represent sequences either characterized in this study or respective orthologs from other species and contains CYP71FH1 ( D. grandiflorum ) and CYP71FH4 ( A. plicatum ). Sequences are from open reading frames of assembled transcripts, and so duplicates or assembly artifacts may be present. Abbreviations: Tth: Thalictrum thalictroides ; Cch: Coptis chinensis ; Dgr: Delphinium grandiflorum ; Apl: Aconitum plicatum ; Aly: Aconitum lycoctonum ; Aca: Aconitum carmichaelii ; Aja: Aconitum japonicum ; Avi: Aconitum vilmorinianum ; Aku: Aconitum kusnezoffii . Download figure Open in new tab S. Figure 7: Maximum likelihood phylogenetic tree of candidate CYPs from the CYP85 clan. This is an expanded view of the tree shown in Figure 3A . Branch lengths indicate substitutions per site and numbers at nodes represent percent support from 1,000 bootstrap replicates. CYP701A3 from Arabidopsis thaliana is used as an outgroup. Leaves in blue ( D. grandiflorum ) and orange ( Aconitum spp. ) represent sequences either characterized in this study or respective orthologs from other species, containing CYP729G1 ( D. grandiflorum ) and CYP729G2 ( A. plicatum ). This highlighted region is enlarged in Figure 3A . Sequences are from open reading frames of assembled transcripts, and so duplicates or assembly artifacts may be present, and a duplicate transcript from D. grandiflorum was omitted for clarity within Figure 3A . Abbreviations: Tth: Thalictrum thalictroides ; Cch: Coptis chinensis ; Dgr: Delphinium grandiflorum ; Apl: Aconitum plicatum ; Aly: Aconitum lycoctonum ; Aca: Aconitum carmichaelii ; Aja: Aconitum japonicum ; Avi: Aconitum vilmorinianum ; Aku: Aconitum kusnezoffii . Download figure Open in new tab S. Figure 8: Calculated expression values of assembled transcripts associated with characterized enzymes, and their respective orthologs from other Aconitum species. Numbers represent transcripts per million (TPM) values within each respective assembly. Color scale is individualized to each row to highlight relative expression of each transcript between tissue types. Some characterized enzymes had multiple associated transcripts in transcriptome assemblies, and are shown here individually. All data shown above, and additional data for A. kusnezoffii , are given in Supplementary Dataset 1. Download figure Open in new tab S. Figure 9: Initial screening of six CYPs with both TPSs. (Top Left) GC-MS chromatograms of EtOAc extracts of N. benthamiana infiltrations. Each assay includes Cf DXS, Cf GGPPS, Dgr TPS1, and Dgr TPS2 in addition to those listed. Compound 27 was not observed consistently across assays, likely due to low abundance. (Bottom Left) Mass spectra for compounds made through coexpression of Dgr TPS1 and Dgr TPS2. (Bottom Middle) Mass spectra for compounds made through coexpression of CYP701A127 with previous pathway steps. (Right) Mass spectra for compounds made through coexpression of CYP71FH1 with previous pathway steps. Download figure Open in new tab Download figure Open in new tab Download figure Open in new tab S. Figure 10: 1 H, 13 C, HSQC, HMBC, NOESY, and COSY NMR spectra of ent-atiserene-20-al ( 4 ). Aldehyde peak is present in 1 H spectrum at 10.16 ppm, which has the same integration value as terminal alkene protons (4.50 and 4.66 ppm). This product was not completely purified from 12 (peaks at 4.71 and 4.83 ppm are likely terminal alkene protons for 12 ). Download figure Open in new tab S. Figure 11: Select HMBC correlations for ent-atiserene-20-al ( 4 ). Correlations drawn show methyl groups for carbons 18 and 19 are retained following conversion of ent -atiserene ( 2 ) by CYP71FH1. Download figure Open in new tab S. Figure 12: Mass spectra for all compounds shown in Figure 3C in the main text. Mass spectra were recorded in positive ion mode, and high energy spectra were generated with a voltage ramp from 20 to 80 V. Relevant portion of Figure 3C is shown in the top left. Download figure Open in new tab S. Figure 13: CYP71FH1 complements a lack of CYP701A127 in atisinium ( 10 ) formation in N. benthamiana assays . LC-MS chromatograms of 80% MeOH extracts of N. benthamiana infiltrations. Each assay includes Cf DXS, Cf GGPPS, Dgr TPS1, and Dgr TPS2 in addition to those listed. Download figure Open in new tab S. Figure 14: Extracted ion chromatograms in LC-MS analysis of CYP candidates. Extracted ions correspond to various predicted and confirmed masses for CYP products detected in 80% MeOH extracts from N. benthamiana . Chromatograms are scaled proportionally to each other except as otherwise indicated. EIC values with an asterisk indicate spectra obtained at a higher collision energy. Associated chemical formulas are given in S. Table 4 . Compounds unique to this figure (numbered 29 or higher) are only visible by EIC and only accumulate in trace quantities. Download figure Open in new tab S. Figure 15: Initial testing to supplement the pathway with ethylamine through AlaDC. LC-MS chromatograms of 80% MeOH extracts of N. benthamiana infiltrations. Each assay includes Cf DXS, Cf GGPPS, Dgr TPS1, and Dgr TPS2 in addition to those listed. An alanine decarboxylase (AlaDC) was introduced to preceding pathway genes as an initial test to see how product profile changes with a presumed increase in supply of ethylamine. Only a trace amount of new product ( 26 , or 27 with addition of CYP729G1) was observed, even when combined with Dgr DAS, and these products did not overlap with Dgr DAS’s products. Products traced in orange are products of CYPs alone, in blue are products that form with addition of Dgr DAS, and in purple are products that form with addition of AlaDC. Note that only select products are highlighted in this figure. A potential structure for 7 is drawn based on the difference in observed molecular weight of 16 m/z between atisinium ( 10 ) and 7 , and the conditions which result in this additional product involving an additional CYP (CYP729G1). Download figure Open in new tab S. Figure 16: LC-MS data confirming atisinium formation. Atisinium formation resulting from infiltration of characterized genes in N. benthamiana ( Apl TPS1, Apl TPS2, CYP71FH4, CYP701A144, CYP729G2, Apl DAS) was confirmed by comparison of retention times (upper panel) and MS/MS spectra (mirror plot, lower panel) with atisinium standard. MS/MS spectra were acquired at HCD 70. XIC, extracted ion chromatogram. Download figure Open in new tab S. Figure 17: Mirror plot of MS/MS fragmentation spectra of atisinium and compound 7 . Highly similar fragmentation patterns of these compounds support their proposed structural similarity. Spectra for both compounds were acquired at HCD 70. Download figure Open in new tab S. Figure 18: Dgr DAS and Apl DAS similarity to other characterized sequences and those from model species . Sequence similarity network of sequences matching Dgr DAS at a BLASTp cutoff of 1e-10, separated by 41% identity. D. grandiflorum sequences in blue, Aconitum spp . sequences in orange, characterized sequences in black, and other sequences from UniProt entries or model species in white. Circled clusters were included in the phylogenetic tree with corresponding highlighted branches. Branches with less than 50% bootstrap support have been collapsed. Select pairs of amino acid sequences with Dgr DAS have their percent identity annotated with alignment lengths in parentheses. The largest clade in gray includes sequences which are not currently characterized from a range of species, and their phylogenetic topology roughly matches the evolutionary relationship of these species (species abbreviations are given in S. Table 2 ). Within Delphinium and Aconitum , a large expansion of genes within this clade may be present, however many sequences presented here are likely misassembled (e.g. short or chimeric) due to the abundance of highly-similar sequences, which is also reflected in the poor bootstrapping support for branch topology within this section. Download figure Open in new tab S. Figure 19: Isotope patterns of metabolites showing ethanolamine incorporation. The presence of highlighted isotopologues is consistent with labeled ethanolamine incorporation in N. benthamiana following infiltration with Apl TPS1, Apl TPS2, CYP701A144, CYP71FH4 and CYP729G2. Download figure Open in new tab S. Figure 20: Workflow involved in identification of isotopologues from isotopically-labeled substrate feeding of A. plicatum callus cultures. Download figure Open in new tab S. Figure 21: Mirror plots of aconitine, atisinium and their respective deuterated isotopologues demonstrating conserved fragmentation patterns. MS/MS fragmentation spectra of A) aconitine and its deuterated isotopologue at HCD 35 and B) atisinium and its deuterated isotopologue at HCD 70. The labeled compounds show the expected mass shift corresponding to incorporation of deuterium atoms while retaining comparable fragmentation patterns to the unlabeled compounds. Download figure Open in new tab S. Figure 22: Tracing nitrogen incorporation in atisinium and aconitine. Isotope pattern of A) atisinium and B) aconitine in ʟ-serine (2,3,3-D3, 15 N) fed callus. For each isotope pattern, the highlighted isotopologue corresponds to incorporation of three deuterium atoms and 15 N. View this table: View inline View popup Download powerpoint S. Table 1: 1 H and 13 C chemical shifts for ent -atiserene (2) . CDCl 3 peaks were referenced to 7.26 and 77.00 ppm for 1 H and 13 C spectra, respectively. View this table: View inline View popup Download powerpoint S. Table 2: List of species searched for sequences with homology to Dgr DAS and Apl DAS, with BioProject accessions associated with published genomes for model species. Three-letter abbreviations in parentheses correspond to those in phylogenetic trees. Select taxonomic classifications are included. View this table: View inline View popup Download powerpoint S. Table 3: Compound numbering, structures, associated pathway enzymes, and rationale for confirmed or tentative structural assignments for all compounds drawn in Figure 1 in the main text. View this table: View inline View popup S. Table 4: Compound numbering and associated pathway enzymes for remaining numbered compounds referenced in this study. Acknowledgments We would like to acknowledge three core facilities at Michigan State University including the Institute for Cyber-Enabled Research, the Mass Spectrometry and Metabolomics Core, and the Max T. Rogers NMR Facility, as well as Advanced Research Computing (ARC) at the University of Michigan. We would also like to thank Sean Johnson and Gina Roeppischer for technical assistance in D. grandiflorum RNA isolation, Prof. Tomáš Urfus from Charles University for providing us with A. plicatum and A. lycoctonum plants, and Prof. Tetiana Satarova from the Institute of Experimental Botany, Czech Academy of Sciences, for training in callus culture initiation and maintenance. Funder Information Declared National Institutes of Health, https://ror.org/01cwqze88 , T32-GM110523 International Visegrad Fund , 52410140 Czech Science Foundation , 21-11563M US Department of Energy Great Lakes Bioenergy Research Center , DE-SC0018409 Michigan State University AgBioResearch , MICL02454 Footnotes ↵ † T.P.and B.H. jointly supervised the work and share corresponding authorship. Structural identification and associated analytical data for all compounds has been added, including further high-resolution MS/MS and higher-energy fragmentation data. Substrate selectivity of DAS has been expanded with further clarification of metabolomics experiments and additional MS and labeled substrate feeding data. Further details on DAS and an analysis of its evolutionary relationship to other reductases has also been added. https://doi.org/10.5281/zenodo.15384649 https://github.com/GarretPMiller/DiterpenoidAlkaloids https://github.com/lalalana5/Callus-culture-isotope-labelling/tree/main https://doi.org/10.5281/zenodo.19150401 REFERENCES (1). ↵ Li , F.-S. ; Weng , J.-K . Demystifying Traditional Herbal Medicine with Modern Approach . Nature Plants 2017 , 3 ( 8 ), 1 – 7 . doi: 10.1038/nplants.2017.109 . OpenUrl CrossRef (2). ↵ Sabzehzari , M. ; Zeinali , M. ; Naghavi , M. R . Alternative Sources and Metabolic Engineering of Taxol: Advances and Future Perspectives . Biotechnology Advances 2020 , 43 , 107569 . doi: 10.1016/j.biotechadv.2020.107569 . OpenUrl CrossRef PubMed (3). ↵ Huang , Y. ; Yang , Y. ; Liu , G. ; Xu , M . New Clinical Application Prospects of Artemisinin and Its Derivatives: A Scoping Review . Infectious Diseases of Poverty 2023 , 12 ( 1 ), 115 . doi: 10.1186/s40249-023-01152-6 . OpenUrl CrossRef PubMed (4). ↵ Galanie , S. ; Thodey , K. ; Trenchard , I. J. ; Filsinger Interrante , M. ; Smolke , C. D . Complete Biosynthesis of Opioids in Yeast . Science 2015 , 349 ( 6252 ), 1095 – 1100 . doi: 10.1126/science.aac9373 . OpenUrl Abstract / FREE Full Text (5). ↵ Nett , R. S. ; Lau , W. ; Sattely , E. S . Discovery and Engineering of Colchicine Alkaloid Biosynthesis . Nature 2020 , 584 ( 7819 ), 148 – 153 . doi: 10.1038/s41586-020-2546-8 . OpenUrl CrossRef PubMed (6). ↵ Bedewitz , M. A. ; Jones , A. D. ; D’Auria , J. C. ; Barry , C. S . Tropinone Synthesis via an Atypical Polyketide Synthase and P450-Mediated Cyclization . Nat Commun 2018 , 9 , 5281 . doi: 10.1038/s41467-018-07671-3 . OpenUrl CrossRef PubMed (7). Wrenbeck , E. E. ; Bedewitz , M. A. ; Klesmith , J. R. ; Noshin , S. ; Barry , C. S. ; Whitehead , T. A . An Automated Data-Driven Pipeline for Improving Heterologous Enzyme Expression . ACS Synth. Biol . 2019 , 8 ( 3 ), 474 – 481 . doi: 10.1021/acssynbio.8b00486 . OpenUrl CrossRef (8). ↵ Srinivasan , P. ; Smolke , C. D . Biosynthesis of Medicinal Tropane Alkaloids in Yeast . Nature 2020 , 585 ( 7826 ), 614 – 619 . doi: 10.1038/s41586-020-2650-9 . OpenUrl CrossRef PubMed (9). ↵ Pan , Q. ; Mustafa , N. R. ; Tang , K. ; Choi , Y. H. ; Verpoorte , R . Monoterpenoid Indole Alkaloids Biosynthesis and Its Regulation in Catharanthus Roseus: A Literature Review from Genes to Metabolites . Phytochem Rev 2016 , 15 ( 2 ), 221 – 250 . doi: 10.1007/s11101-015-9406-4 . OpenUrl CrossRef (10). Caputi , L. ; Franke , J. ; Farrow , S. C. ; Chung , K. ; Payne , R. M. E. ; Nguyen , T.-D. ; Dang , T.-T. T .; Soares Teto Carqueijeiro , I. ; Koudounas , K. ; Dugé de Bernonville , T. ; Ameyaw , B. ; Jones , D. M. ; Vieira , I. J. C. ; Courdavault , V. ; O’Connor , S. E. Missing Enzymes in the Biosynthesis of the Anticancer Drug Vinblastine in Madagascar Periwinkle . Science 2018 , 360 ( 6394 ), 1235 – 1239 . doi: 10.1126/science.aat4100 . OpenUrl Abstract / FREE Full Text (11). ↵ Qu , Y. ; Safonova , O. ; De Luca , V . Completion of the Canonical Pathway for Assembly of Anticancer Drugs Vincristine/Vinblastine in Catharanthus Roseus . The Plant Journal 2019 , 97 ( 2 ), 257 – 266 . doi: 10.1111/tpj.14111 . OpenUrl CrossRef PubMed (12). ↵ Ma , Y. ; Mao , X.-Y. ; Huang , L.-J. ; Fan , Y.-M. ; Gu , W. ; Yan , C. ; Huang , T. ; Zhang , J.-X. ; Yuan , C.-M. ; Hao , X.-J . Diterpene Alkaloids and Diterpenes from Spiraea Japonica and Their Anti-Tobacco Mosaic Virus Activity . Fitoterapia 2016 , 109 , 8 – 13 . doi: 10.1016/j.fitote.2015.11.019 . OpenUrl CrossRef PubMed (13). Hart , N. ; Johns , S. ; Lamberton , J. ; Suares , H. ; Willing , R . New Alkaloids of the Ent-Kaurene Type From Anopterus Species (Escalloniaceae) . I. The Structure and Reactions of Anopterine. Aust. J. Chem . 1976 , 29 ( 6 ), 1295 – 1318 . doi: 10.1071/ch9761295 . OpenUrl CrossRef (14). ↵ Oneto , J. F . The Alkaloids of Species of Garrya. I. Isolation of Alkaloids* . Journal of the American Pharmaceutical Association (Scientific ed.) 1946 , 35 ( 7 ), 204 – 207 . doi: 10.1002/jps.3030350703 . OpenUrl CrossRef (15). ↵ Yin , T. ; Cai , L. ; Ding , Z . An Overview of the Chemical Constituents from the Genus Delphinium Reported in the Last Four Decades . RSC Advances 2020 , 10 ( 23 ), 13669 – 13686 . doi: 10.1039/D0RA00813C . OpenUrl CrossRef PubMed (16). ↵ Nyirimigabo , E. ; Xu , Y. ; Li , Y. ; Wang , Y. ; Agyemang , K. ; Zhang , Y. A Review on Phytochemistry, Pharmacology and Toxicology Studies of Aconitum . Journal of Pharmacy and Pharmacology 2015 , 67 ( 1 ), 1 – 19 . doi: 10.1111/jphp.12310 . OpenUrl CrossRef PubMed (17). ↵ Xu , J.-B. ; Li , Y.-Z. ; Huang , S. ; Chen , L. ; Luo , Y.-Y. ; Gao , F. ; Zhou , X.-L . Diterpenoid Alkaloids from the Whole Herb of Delphinium Grandiflorum L . Phytochemistry 2021 , 190 , 112866 . doi: 10.1016/j.phytochem.2021.112866 . OpenUrl CrossRef (18). Li , Y. ; Gao , F. ; Zhang , J.-F. ; Zhou , X.-L . Four New Diterpenoid Alkaloids from the Roots of Aconitum Carmichaelii . Chem. Biodivers . 2018 , 15 ( 7 ), e1800147 . doi: 10.1002/cbdv.201800147 . OpenUrl CrossRef PubMed (19). Yamashita , H. ; Takeda , K. ; Haraguchi , M. ; Abe , Y. ; Kuwahara , N. ; Suzuki , S. ; Terui , A. ; Masaka , T. ; Munakata , N. ; Uchida , M. ; Nunokawa , M. ; Kaneda , K. ; Goto , M. ; Lee , K.-H. ; Wada , K . Four New Diterpenoid Alkaloids from Aconitum Japonicum Subsp. Subcuneatum . J Nat Med 2018 , 72 ( 1 ), 230 – 237 . doi: 10.1007/s11418-017-1139-9 . OpenUrl CrossRef PubMed (20). ↵ Yin , T.-P. ; Cai , L. ; Fang , H.-X. ; Fang , Y.-S. ; Li , Z.-J. ; Ding , Z.-T . Diterpenoid Alkaloids from Aconitum Vilmorinianum . Phytochemistry 2015 , 116 , 314 – 319 . doi: 10.1016/j.phytochem.2015.05.002 . OpenUrl CrossRef PubMed (21). ↵ Csupor , D. ; Wenzig , E. M. ; Zupkó , I. ; Wölkart , K. ; Hohmann , J. ; Bauer , R . Qualitative and Quantitative Analysis of Aconitine-Type and Lipo-Alkaloids of Aconitum Carmichaelii Roots . Journal of Chromatography A 2009 , 1216 (11), 2079 – 2086 . doi: 10.1016/j.chroma.2008.10.082 . OpenUrl CrossRef (22). Zhou , G. ; Tang , L. ; Zhou , X. ; Wang , T. ; Kou , Z. ; Wang , Z . A Review on Phytochemistry and Pharmacological Activities of the Processed Lateral Root of Aconitum Carmichaelii Debeaux . J Ethnopharmacol 2015 , 160 , 173 – 193 . doi: 10.1016/j.jep.2014.11.043 . OpenUrl CrossRef PubMed (23). ↵ Wangchuk , P. ; Bremner , J. B. ; Samten ; Skelton , B. W. ; White , A. H. ; Rattanajak , R. ; Kamchonwongpaisan , S. Antiplasmodial Activity of Atisinium Chloride from the Bhutanese Medicinal Plant, Aconitum Orochryseum . Journal of Ethnopharmacology 2010 , 130 ( 3 ), 559 – 562 . doi: 10.1016/j.jep.2010.05.057 . OpenUrl CrossRef PubMed (24). ↵ Shen , Y. ; Liang , W.-J. ; Shi , Y.-N. ; Kennelly , E. J. ; Zhao, D.-K. Structural Diversity, Bioactivities, and Biosynthesis of Natural Diterpenoid Alkaloids . Nat. Prod. Rep . 2020 , 37 ( 6 ), 763 – 796 . doi: 10.1039/D0NP00002G . OpenUrl CrossRef PubMed (25). ↵ Liu , X.-Y. ; Wang , F.-P. ; Qin , Y . Synthesis of Three-Dimensionally Fascinating Diterpenoid Alkaloids and Related Diterpenes . Acc. Chem. Res . 2021 , 54 ( 1 ), 22 – 34 . doi: 10.1021/acs.accounts.0c00720 . OpenUrl CrossRef PubMed (26). Gong , J. ; Chen , H. ; Liu , X.-Y. ; Wang , Z.-X. ; Nie , W. ; Qin , Y . Total Synthesis of Atropurpuran . Nat Commun 2016 , 7 ( 1 ), 12183 . doi: 10.1038/ncomms12183 . OpenUrl CrossRef PubMed (27). Owens , K. R. ; McCowen , S. V. ; Blackford , K. A. ; Ueno , S. ; Hirooka , Y. ; Weber , M. ; Sarpong , R . Total Synthesis of the Diterpenoid Alkaloid Arcutinidine Using a Strategy Inspired by Chemical Network Analysis . J. Am. Chem. Soc . 2019 , 141 ( 35 ), 13713 – 13717 . doi: 10.1021/jacs.9b05815 . OpenUrl CrossRef PubMed (28). Pang , L. ; Liu , C.-Y. ; Gong , G.-H. ; Quan , Z.-S . Synthesis, in Vitro and in Vivo Biological Evaluation of Novel Lappaconitine Derivatives as Potential Anti-Inflammatory Agents . Acta Pharm Sin B 2020 , 10 ( 4 ), 628 – 645 . doi: 10.1016/j.apsb.2019.09.002 . OpenUrl CrossRef PubMed (29). ↵ Cherney , E. C. ; Baran , P. S . Terpenoid-Alkaloids: Their Biosynthetic Twist of Fate and Total Synthesis . Israel Journal of Chemistry 2011 , 51 ( 3–4 ), 391 – 405 . doi: 10.1002/IJCH.201100005 . OpenUrl CrossRef PubMed (30). ↵ Zhou , R.-J. ; Dai , G.-Y. ; Zhou , X.-H. ; Zhang , M.-J. ; Wu , P.-Z. ; Zhang , D. ; Song , H. ; Liu , X.-Y. ; Qin , Y . Progress towards the Synthesis of Aconitine: Construction of the AE Fragment and Attempts to Access the Pentacyclic Core . Org. Chem. Front . 2019 , 6 ( 3 ), 377 – 382 . doi: 10.1039/C8QO01228H . OpenUrl CrossRef (31). ↵ Li , Y.-G. ; Mou , F.-J. ; Li , K.-Z . De Novo RNA Sequencing and Analysis Reveal the Putative Genes Involved in Diterpenoid Biosynthesis in Aconitum Vilmorinianum Roots . 3 Biotech 2021 , 11 (2), 96. doi: 10.1007/s13205-021-02646-6 . OpenUrl CrossRef (32). Pal , T. ; Malhotra , N. ; Chanumolu , S. K. ; Chauhan , R. S . Next-Generation Sequencing (NGS) Transcriptomes Reveal Association of Multiple Genes and Pathways Contributing to Secondary Metabolites Accumulation in Tuberous Roots of Aconitum Heterophyllum Wall . Planta 2015 , 242 ( 1 ), 239 – 258 . doi: 10.1007/S00425-015-2304-6/FIGURES/11 . OpenUrl CrossRef PubMed (33). ↵ Rai , M. ; Rai , A. ; Kawano , N. ; Yoshimatsu , K. ; Takahashi , H. ; Suzuki , H. ; Kawahara , N. ; Saito , K. ; Yamazaki , M . De Novo RNA Sequencing and Expression Analysis of Aconitum Carmichaelii to Analyze Key Genes Involved in the Biosynthesis of Diterpene Alkaloids . Molecules : A Journal of Synthetic Chemistry and Natural Product Chemistry 2017 , 22 ( 12 ). doi: 10.3390/MOLECULES22122155 . OpenUrl CrossRef (34). Yang , Y. ; Hu , P. ; Zhou , X. ; Wu , P. ; Si , X. ; Lu , B. ; Zhu , Y. ; Xia , Y . Transcriptome Analysis of Aconitum Carmichaelii and Exploration of the Salsolinol Biosynthetic Pathway . Fitoterapia 2020 , 140 , 104412 . doi: 10.1016/j.fitote.2019.104412 . OpenUrl CrossRef (35). Zhao , D. ; Shen , Y. ; Shi , Y. ; Shi , X. ; Qiao , Q. ; Zi , S. ; Zhao , E. ; Yu , D. ; Kennelly , E. J . Probing the Transcriptome of Aconitum Carmichaelii Reveals the Candidate Genes Associated with the Biosynthesis of the Toxic Aconitine-Type C19-Diterpenoid Alkaloids . Phytochemistry 2018 , 152 , 113 – 124 . doi: 10.1016/j.phytochem.2018.04.022 . OpenUrl CrossRef PubMed (36). ↵ Chen , L. ; Tian , M. ; Jin , B. ; Yin , B. ; Chen , T. ; Guo , J. ; Tang , J. ; Cui , G. ; Huang , L . Integrating Metabolomics and Transcriptomics to Unveil Atisine Biosynthesis in Aconitum Gymnandrum Maxim . International Journal of Molecular Sciences 2022 , 23 ( 21 ), 13463 . doi: 10.3390/ijms232113463 . OpenUrl CrossRef PubMed (37). ↵ Mao , L. ; Jin , B. ; Chen , L. ; Tian , M. ; Ma , R. ; Yin , B. ; Zhang , H. ; Guo , J. ; Tang , J. ; Chen , T. ; Lai , C. ; Cui , G. ; Huang , L . Functional Identification of the Terpene Synthase Family Involved in Diterpenoid Alkaloids Biosynthesis in Aconitum Carmichaelii . Acta Pharmaceutica Sinica B 2021 . doi: 10.1016/J.APSB.2021.04.008 . OpenUrl CrossRef (38). ↵ Luo , F. ; Zhou , Q. ; Chen , F. ; Liu , X. ; Chiu , T.-Y. ; Zhu , G.-Y. ; Huang , A. C . Divergent Multifunctional P450s-Empowered Biosynthesis of Bioactive Tripterifordin and Cryptic Atiserenoids in Aconitum Implies Convergent Evolution . Nat Commun 2025 , 16 ( 1 ), 5857 . doi: 10.1038/s41467-025-61188-0 . OpenUrl CrossRef PubMed (39). ↵ Hong , Y. J. ; Tantillo , D. J. Formation of Beyerene, Kaurene, Trachylobane, and Atiserene Diterpenes by Rearrangements That Avoid Secondary Carbocations . J. Am. Chem. Soc . 2010 , 132 ( 15 ), 5375 – 5386 . doi: 10.1021/ja9084786 . OpenUrl CrossRef PubMed (40). ↵ Andersen-Ranberg , J. ; Kongstad , K. T. ; Nielsen , M. T. ; Jensen , N. B. ; Pateraki , I. ; Bach , S. S. ; Hamberger , B. ; Zerbe , P. ; Staerk , D. ; Bohlmann , J. ; Møller , B. L. ; Hamberger , B . Expanding the Landscape of Diterpene Structural Diversity through Stereochemically Controlled Combinatorial Biosynthesis . Angewandte Chemie International Edition 2016 , 55 ( 6 ), 2142 – 2146 . doi: 10.1002/anie.201510650 . OpenUrl CrossRef PubMed (41). ↵ Johnson , S. R. ; Bhat , W. W. ; Bibik , J. ; Turmo , A. ; Hamberger , B. ; Hamberger , B . A Database-Driven Approach Identifies Additional Diterpene Synthase Activities in the Mint Family (Lamiaceae) . J Biol Chem 2019 , 294 ( 4 ), 1349 – 1362 . doi: 10.1074/jbc.RA118.006025 . OpenUrl Abstract / FREE Full Text (42). ↵ Jin , B. ; Cui , G. ; Guo , J. ; Tang , J. ; Duan , L. ; Lin , H. ; Shen , Y. ; Chen , T. ; Zhang , H. ; Huang , L . Functional Diversification of Kaurene Synthase-Like Genes in Isodon Rubescens . Plant Physiology 2017 , 174 ( 2 ), 943 – 955 . doi: 10.1104/pp.17.00202 . OpenUrl Abstract / FREE Full Text (43). ↵ Grennan , A. K . Gibberellin Metabolism Enzymes in Rice . Plant Physiology 2006 , 141 ( 2 ), 524 – 526 . doi: 10.1104/pp.104.900192 . OpenUrl FREE Full Text (44). ↵ Kong , H. ; Zhang , Y. ; Hong , Y. ; Barker , M. S . Multilocus Phylogenetic Reconstruction Informing Polyploid Relationships of Aconitum Subgenus Lycoctonum (Ranunculaceae) in China . Plant Syst Evol 2017 , 303 ( 6 ), 727 – 744 . doi: 10.1007/s00606-017-1406-y . OpenUrl CrossRef (45). ↵ Park , S. ; An , B. ; Park , S . Recurrent Gene Duplication in the Angiosperm Tribe Delphinieae (Ranunculaceae) Inferred from Intracellular Gene Transfer Events and Heteroplasmic Mutations in the Plastid matK Gene . Sci Rep 2020 , 10 ( 1 ), 2720 . doi: 10.1038/s41598-020-59547-6 . OpenUrl CrossRef PubMed (46). ↵ Salvado , P. ; Aymerich Boixader , P. ; Parera , J. ; Vila Bonfill , A. ; Martin , M. ; Quélennec , C. ; Lewin , J.-M. ; Delorme-Hinoux , V. ; Bertrand , J. A. M . Little Hope for the Polyploid Endemic Pyrenean Larkspur (Delphinium Montanum): Evidences from Population Genomics and Ecological Niche Modeling . Ecology and Evolution 2022 , 12 ( 3 ), e8711 . doi: 10.1002/ece3.8711 . OpenUrl CrossRef (47). ↵ Nelson , D. ; Werck-Reichhart , D . A P450-Centric View of Plant Evolution . The Plant Journal 2011 , 66 ( 1 ), 194 – 211 . doi: 10.1111/j.1365-313X.2011.04529.x . OpenUrl CrossRef PubMed Web of Science (48). ↵ Lichman , B. R . The Scaffold-Forming Steps of Plant Alkaloid Biosynthesis . Natural Product Reports 2021 , 38 ( 1 ), 103 – 129 . doi: 10.1039/D0NP00031K . OpenUrl CrossRef PubMed (49). ↵ Coutinho , B. G. ; Mevers , E. ; Schaefer , A. L. ; Pelletier , D. A. ; Harwood , C. S. ; Clardy , J. ; Greenberg , E. P . A Plant-Responsive Bacterial-Signaling System Senses an Ethanolamine Derivative . Proceedings of the National Academy of Sciences 2018 , 115 ( 39 ), 9785 – 9790 . doi: 10.1073/pnas.1809611115 . OpenUrl Abstract / FREE Full Text (50). ↵ Bai , P. ; Wang , L. ; Wei , K. ; Ruan , L. ; Wu , L. ; He , M. ; Ni , D. ; Cheng , H . Biochemical Characterization of Specific Alanine Decarboxylase (AlaDC) and Its Ancestral Enzyme Serine Decarboxylase (SDC) in Tea Plants (Camellia Sinensis) . BMC Biotechnology 2021 , 21 ( 1 ), 17 . doi: 10.1186/s12896-021-00674-x . OpenUrl CrossRef PubMed (51). ↵ Zhao , P.-J. ; Gao , S. ; Fan , L.-M. ; Nie , J.-L. ; He , H.-P. ; Zeng , Y. ; Shen , Y.-M. ; Hao , X.-J . Approach to the Biosynthesis of Atisine-Type Diterpenoid Alkaloids . J. Nat. Prod 2009 , 72 , 645 – 649 . doi: 10.1021/np800657j . OpenUrl CrossRef PubMed (52). ↵ Dührkop , K. ; Fleischauer , M. ; Ludwig , M. ; Aksenov , A. A. ; Melnik , A. V. ; Meusel , M. ; Dorrestein , P. C. ; Rousu , J. ; Böcker , S . SIRIUS 4: A Rapid Tool for Turning Tandem Mass Spectra into Metabolite Structure Information . Nat Methods 2019 , 16 ( 4 ), 299 – 302 . doi: 10.1038/s41592-019-0344-8 . OpenUrl CrossRef PubMed (53). ↵ Ludwig , M. ; Nothias , L.-F. ; Dührkop , K. ; Koester , I. ; Fleischauer , M. ; Hoffmann , M. A. ; Petras , D. ; Vargas , F. ; Morsy , M. ; Aluwihare , L. ; Dorrestein , P. C. ; Böcker , S . Database-Independent Molecular Formula Annotation Using Gibbs Sampling through ZODIAC . Nature Machine Intelligence 2020 , 2 ( 10 ), 629 – 641 . doi: 10.1038/s42256-020-00234-6 . OpenUrl CrossRef (54). ↵ Dührkop , K. ; Shen , H. ; Meusel , M. ; Rousu , J. ; Böcker , S . Searching Molecular Structure Databases with Tandem Mass Spectra Using CSI:FingerID . Proceedings of the National Academy of Sciences 2015 , 112 ( 41 ), 12580 – 12585 . doi: 10.1073/pnas.1509788112 . OpenUrl Abstract / FREE Full Text (55). ↵ Dührkop , K. ; Nothias , L.-F. ; Fleischauer , M. ; Reher , R. ; Ludwig , M. ; Hoffmann , M. A. ; Petras , D. ; Gerwick , W. H. ; Rousu , J. ; Dorrestein , P. C. ; Böcker , S . Systematic Classification of Unknown Metabolites Using High-Resolution Fragmentation Mass Spectra . Nat Biotechnol 2021 , 39 ( 4 ), 462 – 471 . doi: 10.1038/s41587-020-0740-8 . OpenUrl CrossRef PubMed (56). ↵ Schmid , R. ; Heuckeroth , S. ; Korf , A. ; Smirnov , A. ; Myers , O. ; Dyrlund , T. S. ; Bushuiev , R. ; Murray , K. J. ; Hoffmann , N. ; Lu , M. ; Sarvepalli , A. ; Zhang , Z. ; Fleischauer , M. ; Dührkop , K. ; Wesner , M. ; Hoogstra , S. J. ; Rudt , E. ; Mokshyna , O. ; Brungs , C. ; Ponomarov , K. ; Mutabdžija , L. ; Damiani , T. ; Pudney , C. J. ; Earll , M. ; Helmer , P. O. ; Fallon , T. R. ; Schulze , T. ; Rivas-Ubach , A. ; Bilbao , A. ; Richter , H. ; Nothias , L.-F. ; Wang , M. ; Orešič , M. ; Weng , J.-K. ; Böcker , S. ; Jeibmann , A. ; Hayen , H. ; Karst , U. ; Dorrestein , P. C. ; Petras , D. ; Du , X. ; Pluskal , T . Integrative Analysis of Multimodal Mass Spectrometry Data in MZmine 3 . Nat Biotechnol 2023 , 41 ( 4 ), 447 – 449 . doi: 10.1038/s41587-023-01690-2 . OpenUrl CrossRef PubMed (57). ↵ Waller , G. R. ; Burström , H . Diterpenoid Alkaloids as Plant Growth Inhibitors . Nature 1969 , 222 ( 5193 ), 576 – 578 . doi: 10.1038/222576a0 . OpenUrl CrossRef Web of Science 58. ↵ Bosch i Daniel , M. ; Simon Pallisé , J. ; López i Pujol , J. ; Blanché i Vergés , C. DCDB: An Updated on-Line Database of Chromosome Numbers of Tribe Delphinieae (Ranunculaceae) . 2016 . (59). Mitka , J. ; Sutkowska , A. ; Ilnicki , T. ; Joachimiak , A . Reticulate Evolution of High-Alpine Aconitum (Ranunculaceae) in the Eastern Sudetes and Western Carpathians (Central Europe) . Acta biologica Cracoviensia. Series botanica 2007 , 49 , 15 – 26 . OpenUrl (60). ↵ Molero , J. ; Rovira , A. M. ; Bosch , M. ; Simon , J. ; Blanché , C . Karyological Study of the Genus Aconitum (Ranunculacae) in the W Mediterranean Area . Flora Mediterranea 2016 , 26 , 229 – 239 . doi: 10.7320/FlMedit26.229 . OpenUrl CrossRef (61). ↵ Morrone , D. ; Chen , X. ; Coates , R. M. ; Peters , R. J . Characterization of the Kaurene Oxidase CYP701A3, a Multifunctional Cytochrome P450 from Gibberellin Biosynthesis . Biochemical Journal 2010 , 431 ( 3 ), 337 – 347 . doi: 10.1042/BJ20100597 . OpenUrl Abstract / FREE Full Text (62). ↵ Prisic , S. ; Xu , M. ; Wilderman , P. R. ; Peters , R. J . Rice Contains Two Disparate Ent-Copalyl Diphosphate Synthases with Distinct Metabolic Functions . Plant Physiol 2004 , 136 ( 4 ), 4228 – 4236 . doi: 10.1104/pp.104.050567 . OpenUrl Abstract / FREE Full Text (63). ↵ Harris , L. J. ; Saparno , A. ; Johnston , A. ; Prisic , S. ; Xu , M. ; Allard , S. ; Kathiresan , A. ; Ouellet , T. ; Peters , R. J . The Maize An2 Gene Is Induced by Fusarium Attack and Encodesan Ent-Copalyl Diphosphate Synthase . Plant Mol Biol 2005 , 59 ( 6 ), 881 – 894 . doi: 10.1007/s11103-005-1674-8 . OpenUrl CrossRef PubMed Web of Science (64). ↵ Kumar , S. ; Stecher , G. ; Suleski , M. ; Hedges , S. B . TimeTree: A Resource for Timelines, Timetrees, and Divergence Times . Mol Biol Evol 2017 , 34 ( 7 ), 1812 – 1819 . doi: 10.1093/molbev/msx116 . OpenUrl CrossRef PubMed (65). ↵ Pateraki , I. ; Andersen-Ranberg , J. ; Jensen , N. B. ; Wubshet , S. G. ; Heskes , A. M. ; Forman , V. ; Hallström , B. ; Hamberger , B. ; Motawia , M. S. ; Olsen , C. E. ; Staerk , D. ; Hansen , J. ; Møller , B. L. ; Hamberger , B . Total Biosynthesis of the Cyclic AMP Booster Forskolin from Coleus Forskohlii . eLife 2017 , 6 , e23001 . doi: 10.7554/eLife.23001 . OpenUrl CrossRef PubMed (66). ↵ Bouillé , A. ; Larbat , R. ; Kumari , R. ; Olry , A. ; Charles , C. ; Nelson , D. R. ; Thornton , J. ; Villard , C. ; Hehn , A . Lineage-Specific Patterns in the Moraceae Family Allow Identification of Convergent P450 Enzymes Involved in Furanocoumarin Biosynthesis . New Phytologist 2025 , 245 ( 5 ), 2085 – 2102 . doi: 10.1111/nph.20381 . OpenUrl CrossRef (67). ↵ Miller , G. P. ; Bhat , W. W. ; Lanier , E. R. ; Johnson , S. R. ; Mathieu , D. T. ; Hamberger , B . The Biosynthesis of the Anti-Microbial Diterpenoid Leubethanol in Leucophyllum Frutescens Proceeds via an All-Cis Prenyl Intermediate . The Plant Journal 2020 , 104 ( 3 ), 693 – 705 . doi: 10.1111/tpj.14957 . OpenUrl CrossRef PubMed (68). ↵ Grabherr , M. G. ; Haas , B. J. ; Yassour , M. ; Levin , J. Z. ; Thompson , D. A. ; Amit , I. ; Adiconis , X. ; Fan , L. ; Raychowdhury , R. ; Zeng , Q. ; Chen , Z. ; Mauceli , E. ; Hacohen , N. ; Gnirke , A. ; Rhind , N. ; di Palma , F. ; Birren , B. W. ; Nusbaum , C. ; Lindblad-Toh , K. ; Friedman , N. ; Regev , A . Full-Length Transcriptome Assembly from RNA-Seq Data without a Reference Genome . Nat Biotechnol 2011 , 29 ( 7 ), 644 – 652 . doi: 10.1038/nbt.1883 . OpenUrl CrossRef PubMed (69). ↵ Haas , B. J. TransDecoder , 2025 . https://github.com/TransDecoder/TransDecoder . (70). ↵ Li , W. ; Godzik , A . Cd-Hit: A Fast Program for Clustering and Comparing Large Sets of Protein or Nucleotide Sequences . Bioinformatics 2006 , 22 ( 13 ), 1658 – 1659 . doi: 10.1093/bioinformatics/btl158 . OpenUrl CrossRef PubMed Web of Science (71). ↵ Fu , L. ; Niu , B. ; Zhu , Z. ; Wu , S. ; Li , W . CD-HIT: Accelerated for Clustering the next-Generation Sequencing Data . Bioinformatics 2012 , 28 ( 23 ), 3150 – 3152 . doi: 10.1093/bioinformatics/bts565 . OpenUrl CrossRef PubMed Web of Science (72). ↵ Patro , R. ; Duggal , G. ; Love , M. I. ; Irizarry , R. A. ; Kingsford , C . Salmon Provides Fast and Bias-Aware Quantification of Transcript Expression . Nat Methods 2017 , 14 ( 4 ), 417 – 419 . doi: 10.1038/nmeth.4197 . OpenUrl CrossRef PubMed (73). ↵ Altschul , S. F. ; Gish , W. ; Miller , W. ; Myers , E. W. ; Lipman , D. J . Basic Local Alignment Search Tool . J Mol Biol 1990 , 215 ( 3 ), 403 – 410 . doi: 10.1016/S0022-2836(05)80360-2 . OpenUrl CrossRef PubMed Web of Science (74). ↵ Shannon , P. ; Markiel , A. ; Ozier , O. ; Baliga , N. S. ; Wang , J. T. ; Ramage , D. ; Amin , N. ; Schwikowski , B. ; Ideker , T . Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks . Genome Res . 2003 , 13 ( 11 ), 2498 – 2504 . doi: 10.1101/gr.1239303 . OpenUrl Abstract / FREE Full Text (75). ↵ Sievers , F. ; Wilm , A. ; Dineen , D. ; Gibson , T. J. ; Karplus , K. ; Li , W. ; Lopez , R. ; McWilliam , H. ; Remmert , M. ; Söding , J. ; Thompson , J. D. ; Higgins , D. G. Fast, Scalable Generation of High-quality Protein Multiple Sequence Alignments Using Clustal Omega . Molecular Systems Biology 2011 , 7 ( 1 ), 539 . doi: 10.1038/msb.2011.75 . OpenUrl CrossRef PubMed Web of Science (76). ↵ Stamatakis , A . RAxML Version 8: A Tool for Phylogenetic Analysis and Post-Analysis of Large Phylogenies . Bioinformatics 2014 , 30 ( 9 ), 1312 – 1313 . doi: 10.1093/bioinformatics/btu033 . OpenUrl CrossRef PubMed Web of Science (77). ↵ Wisecaver , J. H. ; Borowsky , A. T. ; Tzin , V. ; Jander , G. ; Kliebenstein , D. J. ; Rokas , A . A Global Coexpression Network Approach for Connecting Genes to Specialized Metabolic Pathways in Plants . The Plant Cell 2017 , 29 ( 5 ), 944 – 959 . doi: 10.1105/TPC.17.00009 . OpenUrl Abstract / FREE Full Text (78). ↵ Jones , P. ; Binns , D. ; Chang , H.-Y. ; Fraser , M. ; Li , W. ; McAnulla , C. ; McWilliam , H. ; Maslen , J. ; Mitchell , A. ; Nuka , G. ; Pesseat , S. ; Quinn , A. F. ; Sangrador-Vegas , A. ; Scheremetjew , M. ; Yong , S.-Y. ; Lopez , R. ; Hunter , S . InterProScan 5: Genome-Scale Protein Function Classification . Bioinformatics 2014 , 30 ( 9 ), 1236 – 1240 . doi: 10.1093/bioinformatics/btu031 . OpenUrl CrossRef PubMed Web of Science (79). ↵ Sainsbury , F. ; Thuenemann , E. C. ; Lomonossoff , G. P . pEAQ: Versatile Expression Vectors for Easy and Quick Transient Expression of Heterologous Proteins in Plants . Plant Biotechnology Journal 2009 , 7 ( 7 ), 682 – 693 . doi: 10.1111/j.1467-7652.2009.00434.x . OpenUrl CrossRef PubMed Web of Science 80. ↵ (80) Adusumilli , R. ; Mallick , P. Data Conversion with ProteoWizard msConvert . In Proteomics: Methods and Protocols ; Comai , L. , Katz , J. E. , Mallick , P. , Eds.; Springer: New York , NY, 2017 ; pp 339–368. doi: 10.1007/978-1-4939-6747-6_23 . OpenUrl CrossRef PubMed (81). ↵ Chambers , M. C. ; Maclean , B. ; Burke , R. ; Amodei , D. ; Ruderman , D. L. ; Neumann , S. ; Gatto , L. ; Fischer , B. ; Pratt , B. ; Egertson , J. ; Hoff , K. ; Kessner , D. ; Tasman , N. ; Shulman , N. ; Frewen , B. ; Baker , T. A. ; Brusniak , M.-Y. ; Paulse , C. ; Creasy , D. ; Flashner , L. ; Kani , K. ; Moulding , C. ; Seymour , S. L. ; Nuwaysir , L. M. ; Lefebvre , B. ; Kuhlmann , F. ; Roark , J. ; Rainer , P. ; Detlev , S. ; Hemenway , T. ; Huhmer , A. ; Langridge , J. ; Connolly , B. ; Chadick , T. ; Holly , K. ; Eckels , J. ; Deutsch , E. W. ; Moritz , R. L. ; Katz , J. E. ; Agus , D. B. ; MacCoss , M. ; Tabb , D. L. ; Mallick , P . A Cross-Platform Toolkit for Mass Spectrometry and Proteomics . Nat Biotechnol 2012 , 30 ( 10 ), 918 – 920 . doi: 10.1038/nbt.2377 . OpenUrl CrossRef PubMed (82). ↵ Zuntini , A. R. ; Carruthers , T. ; Maurin , O. ; Bailey , P. C. ; Leempoel , K. ; Brewer , G. E. ; Epitawalage , N. ; Françoso , E. ; Gallego-Paramo , B. ; McGinnie , C. ; Negrão , R. ; Roy , S. R. ; Simpson , L. ; Toledo Romero , E. ; Barber , V. M. A. ; Botigué , L. ; Clarkson , J. J. ; Cowan , R. S. ; Dodsworth , S. ; Johnson , M. G. ; Kim , J. T. ; Pokorny , L. ; Wickett , N. J. ; Antar , G. M. ; DeBolt , L. ; Gutierrez , K. ; Hendriks , K. P. ; Hoewener , A. ; Hu , A.-Q. ; Joyce , E. M. ; Kikuchi , I. A. B. S. ; Larridon , I. ; Larson , D. A. ; De Lírio , E. J. ; Liu , J.-X. ; Malakasi , P. ; Przelomska , N. A. S. ; Shah , T. ; Viruel , J. ; Allnutt , T. R. ; Ameka , G. K. ; Andrew , R. L. ; Appelhans , M. S. ; Arista , M. ; Ariza , M. J. ; Arroyo , J. ; Arthan , W. ; Bachelier , J. B. ; Bailey , C. D. ; Barnes , H. F. ; Barrett , M. D. ; Barrett , R. L. ; Bayer , R. J. ; Bayly , M. J. ; Biffin , E. ; Biggs , N. ; Birch , J. L. ; Bogarín , D. ; Borosova , R. ; Bowles , A. M. C. ; Boyce , P. C. ; Bramley , G. L. C. ; Briggs , M. ; Broadhurst , L. ; Brown , G. K. ; Bruhl , J. J. ; Bruneau , A. ; Buerki , S. ; Burns , E. ; Byrne , M. ; Cable , S. ; Calladine , A. ; Callmander , M. W. ; Cano , Á. ; Cantrill , D. J. ; Cardinal-McTeague , W. M. ; Carlsen , M. M. ; Carruthers , A. J. A. ; De Castro Mateo , A. ; Chase , M. W. ; Chatrou , L. W. ; Cheek , M. ; Chen , S. ; Christenhusz , M. J. M. ; Christin , P.-A. ; Clements , M. A. ; Coffey , S. C. ; Conran , J. G. ; Cornejo , X. ; Couvreur , T. L. P. ; Cowie , I. D. ; Csiba , L. ; Darbyshire , I. ; Davidse , G. ; Davies , N. M. J. ; Davis , A. P. ; Van Dijk , K. ; Downie , S. R. ; Duretto , M. F. ; Duvall , M. R. ; Edwards , S. L. ; Eggli , U. ; Erkens , R. H. J. ; Escudero , M. ; De La Estrella , M. ; Fabriani , F. ; Fay , M. F. ; Ferreira , P. D. L. ; Ficinski , S. Z. ; Fowler , R. M. ; Frisby , S. ; Fu , L. ; Fulcher , T. ; Galbany-Casals , M. ; Gardner , E. M. ; German , D. A. ; Giaretta , A. ; Gibernau , M. ; Gillespie , L. J. ; González , C. C. ; Goyder , C. J. ; Graham , S. W. ; Grall , A. ; Green , L. ; Gunn , B. F. ; Gutiérrez , D. G. ; Hackel , J. ; Haevermans , T. ; Haigh , A. ; Hall , J. C. ; Hall , T. ; Harrison , M. J. ; Hatt , S. A. ; Hidalgo , O. ; Hodkinson , T. R. ; Holmes , G. D. ; Hopkins , H. C. F. ; Jackson , C. J. ; James , S. A. ; Jobson , R. W. ; Kadereit , G. ; Kahandawala , I. M. ; Kainulainen , K. ; Kato , M. ; Kellogg , E. A. ; King , G. J. ; Klejevskaja , B. ; Klitgaard , B. B. ; Klopper , R. R. ; Knapp , S. ; Koch , M. A. ; Leebens-Mack , J. H. ; Lens , F. ; Leon , C. J. ; Léveillé-Bourret , É. ; Lewis , G. P. ; Li , D.-Z. ; Li , L. ; Liede-Schumann , S. ; Livshultz , T. ; Lorence , D. ; Lu , M. ; Lu-Irving , P. ; Luber , J. ; Lucas , E. J. ; Luján , M. ; Lum , M. ; Macfarlane , T. D. ; Magdalena , C. ; Mansano , V. F. ; Masters , L. E. ; Mayo , S. J. ; McColl , K. ; McDonnell , A. J. ; McDougall , A. E. ; McLay , T. G. B. ; McPherson , H. ; Meneses , R. I. ; Merckx , V. S. F. T. ; Michelangeli , F. A. ; Mitchell , J. D. ; Monro , A. K. ; Moore , M. J. ; Mueller , T. L. ; Mummenhoff , K. ; Munzinger , J. ; Muriel , P. ; Murphy , D. J. ; Nargar , K. ; Nauheimer , L. ; Nge , F. J. ; Nyffeler , R. ; Orejuela , A. ; Ortiz , E. M. ; Palazzesi , L. ; Peixoto , A. L. ; Pell , S. K. ; Pellicer , J. ; Penneys , D. S. ; Perez-Escobar , O. A. ; Persson , C. ; Pignal , M. ; Pillon , Y. ; Pirani , J. R. ; Plunkett , G. M. ; Powell , R. F. ; Prance , G. T. ; Puglisi , C. ; Qin , M. ; Rabeler , R. K. ; Rees , P. E. J. ; Renner , M. ; Roalson , E. H. ; Rodda , M. ; Rogers , Z. S. ; Rokni , S. ; Rutishauser , R. ; De Salas , M. F. ; Schaefer , H. ; Schley , R. J. ; Schmidt-Lebuhn , A. ; Shapcott , A. ; Al-Shehbaz , I. ; Shepherd , K. A. ; Simmons , M. P. ; Simões , A. O. ; Simões , A. R. G. ; Siros , M. ; Smidt , E. C. ; Smith , J. F. ; Snow , N. ; Soltis , D. C. ; Soltis , P. S. ; Soreng , R. J. ; Sothers , C. A. ; Starr , J. R. ; Stevens , P. F. ; Straub , S. C. K. ; Struwe , L. ; Taylor , J. M. ; Telford , I. R. H. ; Thornhill , A. H. ; Tooth , I. ; Trias-Blasi , A. ; Udovicic , F. ; Utteridge , T. M. A. ; Del Valle , J. C. ; Verboom , G. A. ; Vonow , H. P. ; Vorontsova , M. S. ; De Vos , J. M. ; Al-Wattar , N. ; Waycott , M. ; Welker , C. A. D. ; White , A. J. ; Wieringa , J. J. ; Williamson , L. T. ; Wilson , T. C. ; Wong , S. Y. ; Woods , L. A. ; Woods , R. ; Worboys , S. ; Xanthos , M. ; Yang , Y. ; Zhang , Y.-X. ; Zhou , M.-Y. ; Zmarzty , S. ; Zuloaga , C. O. ; Antonelli , A. ; Bellot , S. ; Crayn , D. M. ; Grace , O. M. ; Kersey , P. J. ; Leitch , I. J. ; Sauquet , H. ; Smith , S. A. ; Eiserhardt , W. L. ; Forest , F. ; Baker , W. J . Phylogenomics and the Rise of the Angiosperms . Nature 2024 , 629 ( 8013 ), 843 – 850 . doi: 10.1038/s41586-024-07324-0 . OpenUrl CrossRef View the discussion thread. Back to top Previous Next Posted May 06, 2026. 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 Entry Steps in the Biosynthetic Pathway to Diterpenoid Alkaloids 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. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Entry Steps in the Biosynthetic Pathway to Diterpenoid Alkaloids Garret P. Miller , Lana Mutabdžija-Nedelcheva , Trine B. Andersen , Imani Pascoe , Kathryn Van Winkle , Maryam Sabbaghan , Alexandre Bouillé , Tomáš Iliaš , Andrej Tekel , Tomáš Pluskal , Björn Hamberger bioRxiv 2025.05.15.654307; doi: https://doi.org/10.1101/2025.05.15.654307 Share This Article: Copy Citation Tools Entry Steps in the Biosynthetic Pathway to Diterpenoid Alkaloids Garret P. Miller , Lana Mutabdžija-Nedelcheva , Trine B. Andersen , Imani Pascoe , Kathryn Van Winkle , Maryam Sabbaghan , Alexandre Bouillé , Tomáš Iliaš , Andrej Tekel , Tomáš Pluskal , Björn Hamberger bioRxiv 2025.05.15.654307; doi: https://doi.org/10.1101/2025.05.15.654307 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 Biochemistry Subject Areas All Articles Animal Behavior and Cognition (7629) Biochemistry (17660) Bioengineering (13881) Bioinformatics (41911) Biophysics (21436) Cancer Biology (18578) Cell Biology (25482) Clinical Trials (138) Developmental Biology (13371) Ecology (19887) Epidemiology (2067) Evolutionary Biology (24302) Genetics (15599) Genomics (22483) Immunology (17728) Microbiology (40364) Molecular Biology (17163) Neuroscience (88537) Paleontology (666) Pathology (2830) Pharmacology and Toxicology (4821) Physiology (7637) Plant Biology (15129) Scientific Communication and Education (2045) Synthetic Biology (4290) Systems Biology (9817) Zoology (2269)