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Acylsugars are defensive, trichome-synthesized sugar esters produced in plants across the Solanaceae (nightshade) family. Although assembled from simple metabolites and synthesized by a relatively short core biosynthetic pathway, tremendous within- and across-species acylsugar structural variation is documented across the family. To advance our understanding of the diversity and the synthesis of acylsugars within the Nicotiana genus, trichome extracts were profiled across the genus coupled with transcriptomics-guided enzyme discovery and in vivo and in vitro analysis. Differences in the types of sugar cores, numbers of acylations, and acyl chain structures contributed to over 300 unique annotated acylsugars throughout Nicotiana. Placement of acyl chain length into a phylogenetic context revealed that an unsaturated acyl chain type was detected in a few closely related species. A comparative transcriptomics approach identified trichome-enriched Nicotiana acuminata acylsugar biosynthetic candidate enzymes. More than 25 acylsugar variants could be produced in a single enzyme assay with four N. acuminata acylsugar acyltransferases (NacASAT1–4) together with structurally diverse acyl-CoAs and sucrose. Liquid chromatography coupled with mass spectrometry screening of in vitro products revealed the ability of these enzymes to make acylsugars not present in Nicotiana plant extracts. In vitro acylsugar production also provided insights into acyltransferase acyl donor promiscuity and acyl acceptor specificity as well as regiospecificity of some ASATs. This study suggests that promiscuous Nicotiana acyltransferases can be used as synthetic biology tools to produce novel and potentially useful metabolites.

 

Plants produce phylogenetically and spatially restricted, as well as structurally diverse specialized metabolites via multistep metabolic pathways. Hallmarks of specialized metabolic evolution include enzymatic promiscuity and recruitment of primary metabolic enzymes and examples of genomic clustering of pathway genes. Solanaceae glandular trichomes produce defensive acylsugars, with sidechains that vary in length across the family. We describe a tomato gene cluster on chromosome 7 involved in medium chain acylsugar accumulation due to trichome specific acyl-CoA synthetase and enoyl-CoA hydratase genes. This cluster co-localizes with a tomato steroidal alkaloid gene cluster and is syntenic to a chromosome 12 region containing another acylsugar pathway gene. We reconstructed the evolutionary events leading to this gene cluster and found that its phylogenetic distribution correlates with medium chain acylsugar accumulation across the Solanaceae. This work reveals insights into the dynamics behind gene cluster evolution and cell-type specific metabolite diversity. 

The target of rapamycin (TOR) kinase is an evolutionarily conserved hub of nutrient sensing and metabolic signaling. In plants, a functional connection of TOR activation with glucose availability was demonstrated, while it is yet unclear whether branched-chain amino acids (BCAAs) are a primary input of TOR signaling as they are in yeast and mammalian cells. Here, we report on the characterization of an Arabidopsis mutant over-accumulating BCAAs. Through chemical interventions targeting TOR and by examining mutants of BCAA biosynthesis and TOR signaling, we found that BCAA over-accumulation leads to up-regulation of TOR activity, which causes reorganization of the actin cytoskeleton and actin-associated endomembranes. Finally, we show that activation of TOR is concomitant with alteration of cell expansion, proliferation and specialized metabolism, leading to pleiotropic effects on plant growth and development. These results demonstrate that BCAAs contribute to plant TOR activation and reveal previously uncharted downstream subcellular processes of TOR signaling. 

Abstract Plant specialized metabolites mediate interactions between plants and the environment and have significant agronomical/pharmaceutical value. Most genes involved in specialized metabolism (SM) are unknown because of the large number of metabolites and the challenge in differentiating SM genes from general metabolism (GM) genes. Plant models like Arabidopsis thaliana have extensive, experimentally derived annotations, whereas many non-model species do not. Here we employed a machine learning strategy, transfer learning, where knowledge from A. thaliana is transferred to predict gene functions in cultivated tomato with fewer experimentally annotated genes. The first tomato SM/GM prediction model using only tomato data performs well (F-measure = 0.74, compared with 0.5 for random and 1.0 for perfect predictions), but from manually curating 88 SM/GM genes, we found many mis-predicted entries were likely mis-annotated. When the SM/GM prediction models built with A. thaliana data were used to filter out genes where the A. thaliana-based model predictions disagreed with tomato annotations, the new tomato model trained with filtered data improved significantly (F-measure = 0.92). Our study demonstrates that SM/GM genes can be better predicted by leveraging cross-species information. Additionally, our findings provide an example for transfer learning in genomics where knowledge can be transferred from an information-rich species to an information-poor one. 

Specialized metabolites are structurally diverse and cell‐ or tissue‐specific molecules produced in restricted plant lineages. In contrast, primary metabolic pathways are highly conserved in plants and produce metabolites essential for all of life, such as amino acids and nucleotides. Substrate promiscuity – the capacity to accept non‐native substrates – is a common characteristic of enzymes, and its impact is especially apparent in generating specialized metabolite variation. However, promiscuity only leads to metabolic diversity when alternative substrates are available; thus, enzyme cellular and subcellular localization directly influence chemical phenotypes. We review a variety of mechanisms that modulate substrate availability for promiscuous plant enzymes. We focus on examples where evolution led to modification of the ‘cellular context’ through changes in cell‐type expression, subcellular relocalization, pathway sequestration, and cellular mixing via tissue damage. These varied mechanisms contributed to the emergence of structurally diverse plant specialized metabolites and inform future metabolic engineering approaches.

 

Plant specialized metabolism (SM) enzymes produce lineage-specific metabolites with important ecological, evolutionary, and biotechnological implications. UsingArabidopsis thalianaas a model, we identified distinguishing characteristics of SM and GM (general metabolism, traditionally referred to as primary metabolism) genes through a detailed study of features including duplication pattern, sequence conservation, transcription, protein domain content, and gene network properties. Analysis of multiple sets of benchmark genes revealed that SM genes tend to be tandemly duplicated, coexpressed with their paralogs, narrowly expressed at lower levels, less conserved, and less well connected in gene networks relative to GM genes. Although the values of each of these features significantly differed between SM and GM genes, any single feature was ineffective at predicting SM from GM genes. Using machine learning methods to integrate all features, a prediction model was established with a true positive rate of 87% and a true negative rate of 71%. In addition, 86% of known SM genes not used to create the machine learning model were predicted. We also demonstrated that the model could be further improved when we distinguished between SM, GM, and junction genes responsible for reactions shared by SM and GM pathways, indicating that topological considerations may further improve the SM prediction model. Application of the prediction model led to the identification of 1,220A. thalianagenes with previously unknown functions, each assigned a confidence measure called an SM score, providing a global estimate of SM gene content in a plant genome.

 

l‐Tyrosine (Tyr) is an aromatic amino acid synthesized de novo in plants and microbes downstream of the shikimate pathway. In plants, Tyr and a Tyr pathway intermediate, 4‐hydroxyphenylpyruvate (HPP), are precursors to numerous specialized metabolites, which are crucial for plant and human health. Tyr is synthesized in the plastids by a TyrA family enzyme, arogenate dehydrogenase (ADH/TyrA_a), which is feedback inhibited by Tyr. Additionally, many legumes possess prephenate dehydrogenases (PDH/TyrA_p), which are insensitive to Tyr and localized to the cytosol. Yet the role of PDH enzymes in legumes is currently unknown. This study isolated and characterizedTnt1‐transposon mutants ofMtPDH1(pdh1) inMedicago truncatulato investigate PDH function. The pdh1mutants lackedPDHtranscript and PDH activity, and displayed little aberrant morphological phenotypes under standard growth conditions, providing genetic evidence thatMtPDH1is responsible for the PDH activity detected inM. truncatula. Though plant PDH enzymes and activity have been specifically found in legumes, nodule number and nitrogenase activity ofpdh1 mutants were not significantly reduced compared with wild‐type (Wt) during symbiosis with nitrogen‐fixing bacteria. Although Tyr levels were not significantly different between Wt and mutants under standard conditions, when carbon flux was increased by shikimate precursor feeding, mutants accumulated significantly less Tyr than Wt. These data suggest that MtPDH1 is involved in Tyr biosynthesis when the shikimate pathway is stimulated and possibly linked to unidentified legume‐specific specialized metabolism.