High-throughput discovery of plant metabolic enzyme function using integrative approaches
Organismic Interactions, Chemical Ecology and Microbiomes of Plant Systems
Plant Physiology
Final Report Abstract
The overall aim of this study was to develop computational and wet-lab approaches for predicting putative substrates of enzymes with unknown function addressed this question using the functionally diverse BAHD acyltransferase family as a model. The results show that this fast-evolving enzyme family expanded drastically during land plant evolution from 1-5 copies in algae to ~100 copies in diploid angiosperm genomes. In vitro characterization of BAHD enzymes against a large panel of substrates and phylogenetic analyses revealed that the ancestral enzymes prior to origin of land plants were already capable of using most of the substrate classes used by currently characterized enzymes. For example, the ability to acylate anthocyanins was inferred to have existed millions of years prior to its fixation in specialized anthocyanin acyltransferases in angiosperms. The results illuminate how promiscuity in robust and evolvable enzymes contributes to functional diversity in enzyme families and identified features that can be used to improve functional prediction within the BAHD acyltransferase family but can also be extended to other gene families. Using a supplemental broad scale genomics approach, I also analyzed BAHDs across various different plant species for features that could potentially be used in a predictive fashion (e.g., number and size of introns). It was found that BAHDs underwent drastic gene architecture changes during evolution and identified motifs useful to enhance functional prediction within the family. These results illuminate how gene duplication, enzyme promiscuity as well as small and large sequence changes in robust and evolvable enzymes contributes to functional diversity in enzyme families. This study provides a template to assess functional evolution after duplication in large enzyme families and generates resources foundational for rational prediction of BAHD function in plant genomes. As part of fellowship project, I also studied resin glycosides (type of acylsugars) in the morning glory family (Convolvulaceae). This research had the goal to identify enzymes (BAHD acyltransferases) involved in the biosynthesis and would enhance our understanding of the independent evolution of acylsugars in different plant lineages. Understanding how BAHDs involved in their biosynthesis have evolved would enhance our understanding of functional divergence in the family. Using metabolomics, we first characterized the diversity of resin glycosides and found phylogenetic patterns of resin glycoside diversity between different clades of the family. We then applied transcriptomics and proteomics to generate a list of candidate genes for different steps of the biosynthesis, specifically acylation. However, in vitro enzyme assays have been unsuccessful in identifying BAHDs involved in the biosynthesis. Additional investigations in the Moghe lab are still ongoing and involve the establishment of virus induced gene silencing and hairy roots to test candidate genes in vivo. Additionally, using a large-scale transcriptomics and metabolomics study of Brachypodium distachyon was used to associate metabolites with transcripts and increase our knowledge about metabolic enzyme function. Proof-of-concept-analyses were successfully able to integrate metabolomics and transcriptomics and identified genes likely involved in arbuscular mycorrhizal symbiosis. Further analysis will significantly help to develop new predictive resources to study metabolic enzyme families and the metabolic diversity they create. Overall, the funded project provides a template for an integrative study tackling one of the biggest challenges of biology, the annotation of the ever-increasing number of known genes and metabolites. With the rise of machine learning technology, understanding which features are important to identify a genes function or a metabolites identity will become crucial to exploit its full potential.
Publications
- (2018) The study of plant specialized metabolism: Challenges and prospects in the genomics era. American Journal of Botany. 105: 959–962
Moghe GD & Kruse LH
(See online at https://doi.org/10.1002/ajb2.1101) - (2020) A massively parallel barcoded sequencing pipeline enables generation of the first ORFeome and interactome map for rice. PNAS 117 (21) 11836-11842
Wierbowski SD; Vo TV; Falter-Braun P; Jobe TO; Kruse LH; (…); Moghe GD; McCouch SR; Yu H
(See online at https://doi.org/10.1073/pnas.1918068117) - (2020) Machine learning: A powerful tool for gene function prediction in plants. Applications in Plant Sciences, e11376
Mahood EH; Kruse LH; Moghe GD
(See online at https://doi.org/10.1002/aps3.11376) - Acylsugars protect Nicotiana benthamiana against insect herbivory and desiccation. Plant Molecular Biology
Feng H; Acosta-Gamboa L; Kruse LH; Tracy JD; Chung SH; Nava Fereira AR; Shakir S; Xu H; Sunter G; Gore MA; Casteel CL; Moghe GD; Jander G
(See online at https://doi.org/10.1101/2020.08.04.237180) - Ancestral class-promiscuity as a driver of functional diversity in the BAHD acyltransferase family in plants
Kruse LH; Weigle A; Martinez-Gomez J; Younkin G; Chobirko J; Bennett AA; Fan K; Specht CD; Shukla D; Moghe GD
(See online at https://doi.org/10.1101/2020.11.18.385815) - Computational metabolomics illuminates the lineage-specific diversification of resin glycoside acylsugars in the morning glory (Convolvulaceae) family
Kruse LH; Bennett AA; Mahood E; Lazarus E; Park S; Schroeder F; Moghe GD
(See online at https://doi.org/10.1101/2021.08.20.457031)
