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Cahoon, E. B.

Publications and source records attributed to Cahoon, E. B..

7 recordsLinked to original sources

Polyketide Synthase-Like Functionality Acquired by Plant Fatty Acid Elongase

Fatty acid elongation (FAE) typically proceeds through a four-step cycle of condensation, reduction, dehydration, and reduction to yield very long-chain fatty acids. Here, we describe a variation of this pathway in Orychophragmus limprichtianus, whose seed oil was found to contains previously unknown C24-C28 keto-hydroxy fatty acids that account for [~]25% of total fatty acids. Our studies revealed that these compounds are produced through an endoplasmic reticulum-localized discontinuous elongation process in which a 3-keto hydroxy intermediate bypasses full reduction and is extended through a polyketide synthase-like mechanism. Transcriptomic and functional assays identified two divergent enzymes, OlFAE1-2 and the low-activity ketoreductase OlKCR1-1, as central to this process. Protein modeling and mutant analysis suggest that specific amino acid substitutions underlie the altered activity of OlKCR1-1, enabling accumulation of keto intermediates. A portion of these unusual fatty acids accumulated in estolides, complex triacylglycerols that expand the chemical repertoire of seed oils. Together, our findings reveal unexpected flexibility in plant fatty acid elongation and provide new tools for engineering plants and microbes to produce renewable oils with tailored industrial functions.

plant biology↗

Enhancing lipid production in plant cells through high-throughput genome editing and phenotyping via a scalable automated pipeline

Plant bioengineering is a time-consuming and labor-intensive process, with no guarantee of achieving the desired trait. Here we report a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB). FAST-PB achieves gene cloning, genome editing, and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrate that FAST-PB can streamline the Golden Gate cloning process, with the capacity to construct 96 vectors in parallel. To prove the concept, using FAST-PB, we first found that PEG2050 significantly increases transfection efficiency by over 45%. To validate the pipeline, we established a reporter-gene-free method for CRISPR editing via mutation of HCF136, affecting cellular chlorophyll fluorescence. Next, we applied this pipeline for lipid production and found that diverse lipids were significantly enhanced up to sixfold through introducing multi-gene cassettes via CRISPR activation, and regenerated plant using this platform. Lastly, we harnessed FAST-PB to achieve high-throughput single-cell lipid profiling through the integration of MALDI-MS with the biofoundry, and differentiated engineered and unengineered cells using the single-cell lipidomics. These innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering, and change what is possibly using single-cell metabolomics in plants.

synthetic biology↗

Glucosylceramides impact cellulose deposition and cellulose synthase complex motility in Arabidopsis

Cellulose is an abundant component of plant cell wall matrices, and this para-crystalline polysaccharide is synthesized at the plasma membrane by motile Cellulose Synthase Complexes (CSCs). However, the factors that control CSC activity and motility are not fully resolved. In a targeted chemical screen, we identified the alkylated nojirimycin analog N-Dodecyl Deoxynojirimycin (ND-DNJ) as a small molecule that severely impacts Arabidopsis seedling growth. Previous work suggests that ND-DNJ-related compounds inhibit the biosynthesis of glucosylceramides (GlcCers), a class of glycosphingolipid associated with plant membranes. Our work uncovered major changes in the sphingolipidome of plants treated with ND-DNJ, including reductions in GlcCer abundance and altered acyl chain length distributions. Crystalline cellulose content was also reduced in ND-DNJ-treated plants as well as plants treated with the known GlcCer biosynthesis inhibitor N-[2-hydroxy-1-(4-morpholinylmethyl)-2-phenyl ethyl]-decanamide (PDMP) or plants containing a genetic disruption in GLUCOSYLCERAMIDE SYNTHASE (GCS), the enzyme responsible for sphingolipid glucosylation that results in GlcCer synthesis. Live-cell imaging revealed that CSC speed distributions were reduced upon treatment with ND-DNJ or PDMP, further suggesting an important relationship between glycosylated sphingolipid composition and CSC motility across the plasma membrane. These results indicated that multiple interventions compromising GlcCer biosynthesis disrupt cellulose deposition and CSC motility, suggesting that GlcCers impact cellulose biosynthesis in plants.

plant biology↗

Quantitative Dynamic Analysis of de novo Sphingolipid Biosynthesis in Arabidopsis thaliana

Sphingolipids are pivotal for plant development and stress responses. Growing interest has been directed towards fully comprehending the regulatory mechanisms of the sphingolipid pathway. We explore its de novo biosynthesis and homeostasis in Arabidopsis thaliana cell cultures, shedding light on fundamental metabolic mechanisms. Employing 15N isotope labeling and quantitative dynamic modeling approach, we developed a regularized and constraint-based Dynamic Metabolic Flux Analysis (r-DMFA) framework to predict metabolic shifts due to enzymatic changes. Our analysis revealed key enzymes such as sphingoid-base hydroxylase (SBH) and long-chain-base kinase (LCBK) to be critical for maintaining sphingolipid homeostasis. Disruptions in these enzymes were found to affect cellular viability and increase the potential for programmed cell death (PCD). Thus, this work enhances our understanding of sphingolipid metabolism and demonstrates the utility of dynamic modeling in analyzing complex metabolic pathways.

systems biology↗

Project ChemicalBlooms: Collaborating with Citizen Scientists to Survey the Chemical Diversity and Phylogenetic Distribution of Plant Epicuticular Wax Blooms

Plants use chemistry to overcome diverse challenges. A particularly striking chemical trait that some plants possess is the ability to synthesize massive amounts of epicuticular wax that accumulates on the plants surfaces as a white coating visible to the naked eye. The ability to synthesize basic wax molecules appears to be shared among virtually all land plants and our knowledge of ubiquitous wax compound synthesis is reasonably advanced. However, the ability to synthe-size thick layers of visible epicuticular crystals ("wax blooms") is restricted to specific lineages and our knowledge of how wax blooms differ from ubiquitous wax layers is less developed. Here, we recruited the help of citizen scientists and middle school students to survey the wax bloom chemistry of 78 species spanning dicot, monocot, and gymnosperm lineages. Using gas chromatography-mass spectrometry, we found that the major wax classes reported from bulk wax mixtures can be present in wax bloom crystals, with fatty acids, fatty alcohols, and alkanes being present in many species bloom crystals. In contrast, other compounds including aldehydes, ketones, secondary alcohols, and triterpenoids were present in only a few species wax bloom crystals. By mapping the 78 wax bloom chemical profiles onto a phylogeny and using phylogenetic comparative analyses, we found that secondary alcohol and triterpenoid-rich wax blooms were present in lineage-specific patterns that would not be expected to arise by chance. That finding is consistent with reports that secondary alcohol biosynthesis enzymes are found only in certain lineages, but was a surprise for triterpenoids, which are intracellular components in virtually all plant lineages. Thus, our data suggest that a lineage-specific mechanism other than biosynthesis exists that enables select species to generate triterpenoid-rich surface wax crystals. Overall, our study outlines a general mode in which research scientists can collaborate with citizen scientists as well as middle and high school classrooms not only to enhance data collection and generate testable hypotheses, but also directly involve classrooms in the scientific process and inspire future STEM workers. Significance StatementPlants coat themselves in a protective layers of waxes. Some plants produce exceptionally thick layers of wax ("wax blooms"), and these thick layers are associated with enhanced abilities to tolerate stress, including drought and insect attack. In collaboration with citizen scientists and middle school classrooms, we provide an overview of the chemistry and phylogenetic distribution of plant epicuticular wax blooms. These data constitute a foundation upon which future studies of diverse wax blooms and their functions can build.

biochemistry↗

Dissecting the regulatory roles of ORM proteins in the sphingolipid pathway of plants

Sphingolipids are a vital component of plant cellular endomembranes and carry out multiple functional and regulatory roles. Different sphingolipid species confer rigidity to the membrane structure, facilitate trafficking of secretory proteins, and initiate programmed cell death. Although the regulation of the sphingolipid pathway is yet to be uncovered, increasing evidence has pointed to orosomucoid proteins (ORMs) playing a major regulatory role and potentially interacting with a number of components in the pathway, including both enzymes and sphingolipids. However, experimental exploration of new regulatory interactions is time consuming and often infeasible. In this work, a computational approach was taken to address this challenge. A metabolic network of the sphingolipid pathway in plants was reconstructed. The steady-state rates of reactions in the network were then determined through measurements of growth and cellular composition of the different sphingolipids in Arabidopsis seedlings. The Ensemble modeling framework was modified to accurately account for activation mechanisms and subsequently used to generate sets of kinetic parameters that converge to the measured steady-state fluxes in a thermodynamically consistent manner. In addition, the framework was appended with an additional module to automate screening the parameters and to output models consistent with previously reported network responses to different perturbations. By analyzing the networks response in the presence of different combinations of regulatory mechanisms, the model captured the experimentally observed repressive effect of ORMs on SPT. Furthermore, predictions point to a second regulatory role of ORM proteins, namely as an activator of class II (or LOH1 and LOH3) ceramide synthases. This activating role was found to be modulated by the concentration of free ceramides, where an accumulation of these sphingolipid species dampened the activating effect of ORMs on ceramide synthase. The predictions pave the way for future guided experiments and have implications in engineering crops with higher biotic stress tolerance. Author summaryDue to their vital functional and regulatory roles in plant cells, increasing interest has gone into obtaining a complete understanding of the regulatory behavior of the sphingolipid pathway. However, the process of identifying new regulatory interactions is time consuming and often infeasible. To address this issue, ensemble modeling was used as an in silico method to test the ability of different regulatory schemes to predict all known pathway responses in a thermodynamically consistent manner. The analysis resulted in a significant reduction in the number of possible regulatory interactions. Mainly, the model predicts regulatory interactions between ceramides, ORMs, and ceramide synthases (especially class II). This framework can pave the way for biochemists to systematically identify plausible regulatory networks in understudied metabolic networks where knowledge on the underlying regulatory mechanisms is often missing. As future experimental works explore these predictions, an iterative cycle can begin wherein model predictions allow for targeted experiments which in turn generate results that can be reincorporated into the model to further increase prediction accuracy. Such a model-driven approach will significantly reduce the solution space traversed by the experimentalist.

systems biology↗

A consensus-based ensemble approach to improve de novo transcriptome assembly

BackgroundSystems-level analyses, such as differential gene expression analysis, co-expression analysis, and metabolic pathway reconstruction, depend on the accuracy of the transcriptome. Multiple tools exist to perform transcriptome assembly from RNAseq data. However, assembling high quality transcriptomes is still not a trivial problem. This is especially the case for non-model organisms where adequate reference genomes are often not available. Different methods produce different transcriptome models and there is no easy way to determine which are more accurate. Furthermore, having alternative-splicing events exacerbates such difficult assembly problems. While benchmarking transcriptome assemblies is critical, this is also not trivial due to the general lack of true reference transcriptomes. ResultsIn this study, we first provide a pipeline to generate a set of the benchmark transcriptome and corresponding RNAseq data. Using the simulated benchmarking datasets, we compared the performance of various transcriptome assembly approaches including both de novo and genome-guided methods. The results showed that the assembly performance deteriorates significantly when alternative transcripts (isoforms) exist or for genome-guided methods when the reference is not available from the same genome. To improve the transcriptome assembly performance, leveraging the overlapping predictions between different assemblies, we present a new consensus-based ensemble transcriptome assembly approach, ConSemble. ConclusionsWithout using a reference genome, ConSemble using four de novo assemblers achieved an accuracy up to twice as high as any de novo assemblers we compared. When a reference genome is available, ConSemble using four genome-guided assemblies removed many incorrectly assembled contigs with minimal impact on correctly assembled contigs, achieving higher precision and accuracy than individual genome-guided methods. Furthermore, ConSemble using de novo assemblers matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms. We thus demonstrated that the ConSemble consensus strategy both for de novo and genome-guided assemblers can improve transcriptome assembly. The RNAseq simulation pipeline, the benchmark transcriptome datasets, and the script to perform the ConSemble assembly are all freely available from: http://bioinfolab.unl.edu/emlab/consemble/.

bioinformatics↗