Biology subjects

Schenck, C. A.

Publications and source records attributed to Schenck, C. A..

6 recordsLinked to original sources

bioRxiv2025

Novel production of structurally diverse and sticky defense metabolites on wild tomatillo fruits

Plants have evolved a structurally diverse chemical repertoire to mediate various environmental interactions. Yet, little is known about the chemical complexity and metabolic pathways across many plant genera. Acylsugars are a class of specialized metabolites widely distributed across the Solanaceae that play a role in defense. Although acylsugars have been extensively characterized from leaf glandular trichomes, they have also been detected in other tissues. Nevertheless, acylsugar structures, biosynthesis, and functions outside of leaf trichomes remain unknown. Here, we performed tissue specific metabolomics across 29 Physalis species, an emerging model and crop genus closely related to important Solanum crops. Automated mass spec feature identification and library searches from surface extracts of leaf, calyx, and fruit tissues revealed metabolite diversity including putative metabolite classes of flavonoids, phenolics, and terpenoids. Acylsugar mass spec features were manually annotated, revealing at least 323 unique acylsugars - substantially expanding the known Physalis acylsugar diversity. Some, but not all, Physalis species accumulated acylsugars on the trichome-less fruit surface, and were as abundant or sometimes more abundant, in fruits than in leaves or calyces. Hierarchical clustering and phylogenetic tests indicated that species with similar acylsugar profiles do not cluster taxonomically. To determine the biochemical mechanism underlying acylsugar structural diversity, we characterized the first step of acylsugar biosynthesis, catalyzed by an acylsugar acyltransferase (ASAT). ASAT1s from three Physalis species displayed broad substrate preferences, which may explain the differences in acylsugar profiles. The diverse fruit-localized acylsugars across Physalis can inform engineering strategies for increased crop resilience.

plant biology↗

bioRxiv2024

A new spin on chemotaxonomy using non-proteogenic amino acids as a test case

PremiseSpecialized metabolites serve various roles for plants and humans. Unlike core metabolites, specialized metabolites are restricted to certain lineages. Thus, in addition to their ecological functions, specialized metabolites can serve as diagnostic markers of plant lineages. MethodsWe investigate the phylogenetic distribution of plant metabolites using non-proteogenic amino acids (NPAA). Species-NPAA associations for eight NPAAs were identified from the existing literature and placed within a phylogenetic context using R packages and interactive tree of life. To confirm and extend the literature-based NPAA distribution we selected azetidine-2-carboxylic acid (Aze) and screened over 70 diverse plants using GC-MS. ResultsLiterature searches identified > 900 NPAA-relevant articles, which were manually inspected to identify 560 species-NPAA associations. NPAAs were mapped at the order and genus level, revealing that some NPAAs are restricted to single orders, whereas others are present across divergent taxa. The distribution of Aze across plants suggests a convergent evolutionary history. DiscussionThe reliance on chemotaxonomy has decreased over the years. Yet, there is still value in placing metabolites within a phylogenetic context to understand the evolutionary processes of plant chemical diversification. This approach can be applied to metabolites present in any organism and compared at a range of taxonomic levels.

plant biology↗

bioRxiv2020

Evolution of a plant gene cluster in Solanaceae and emergence of metabolic diversity

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, recruitment of primary metabolic enzymes and genomic clustering of pathway genes. Solanaceae plant glandular trichomes produce defensive acylsugars, with aliphatic 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 forming a supercluster, and is syntenic to a chromosome 12 region containing another acylsugar pathway gene. We reconstructed the evolutionary events leading to emergence of this gene cluster and found that its phylogenetic distribution correlates with medium chain acylsugar accumulation across the Solanaceae. This work reveals dynamics behind emergence of novel enzymes from primary metabolism, gene cluster evolution and cell-type specific metabolite diversity.

plant biology↗

bioRxiv2020

Within and cross species predictions of plant specialized metabolism genes using transfer learning

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.

plant biology↗

bioRxiv2019

Role of Cytosolic, Tyrosine-Insensitive Prephenate Dehydrogenase in Medicago truncatula

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/TyrAa), which is feedback inhibited by Tyr. In addition to ADH enzymes, many legumes possess prephenate dehydrogenases (PDH/TyrAp), which are insensitive to Tyr and localized to the cytosol. Yet the role of PDH in legumes is currently unknown. This study isolated and characterized Tnt1-transposon mutants of MtPDH1 (pdh1) in Medicago truncatula to investigate PDH function. The pdh1 mutants lacked PDH transcript, PDH activity, and displayed little aberrant morphological phenotypes under standard growth conditions providing genetic evidence that MtPDH1 is responsible for the PDH activity detected in M. truncatula. Though plant PDH enzymes and activity have been specifically found in legumes, nodule number and nitrogenase activity of pdh1 mutants were not significantly reduced compared to 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.

plant biology↗

bioRxiv2018

Robust predictions of specialized metabolism genes through machine learning

Plant specialized metabolism (SM) enzymes produce lineage-specific metabolites with important ecological, evolutionary, and biotechnological implications. Using Arabidopsis thaliana as 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, co-expressed 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 well performing prediction model was established with a true positive rate of 0.87 and a true negative rate of 0.71. In addition, 86% of known SM genes not used to create the machine learning model were predicted as SM genes, further demonstrating its accuracy. 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. Application of the prediction model led to the identification of 1,217 A. thaliana genes with previously unknown functions, providing a global, high-confidence estimate of SM gene content in a plant genome.\n\nSignificanceSpecialized metabolites are critical for plant-environment interactions, e.g., attracting pollinators or defending against herbivores, and are important sources of plant-based pharmaceuticals. However, it is unclear what proportion of enzyme-encoding genes play roles in specialized metabolism (SM) as opposed to general metabolism (GM) in any plant species. This is because of the diversity of specialized metabolites and the considerable number of incompletely characterized pathways responsible for their production. In addition, SM gene ancestors frequently played roles in GM. We evaluate features distinguishing SM and GM genes and build a computational model that accurately predicts SM genes. Our predictions provide candidates for experimental studies, and our modeling approach can be applied to other species that produce medicinally or industrially useful compounds.

plant biology↗