Recent News

We are thrilled to to announce the publication of an article featuring the latest release of the Plant Metabolic Network (PMN 16) in Nucleic Acids Research! This comprehensive update includes over 1,200 metabolic pathways, 1.3 million enzymes, 8,000 metabolites, and data for 155 plant and green algal genomes, with 29 new species added. PMN 16 also introduces 52 experimentally validated enzymes and an enhanced PlantCyc reference database. The article details how PMN 16 supports metabolic studies, omics data analysis, and educational efforts in plant science. Explore these significant advancements by accessing the full article here.

Hawkins, C., Xue, B., Yasmin, F., Wyatt, G., Zerbe, P., and Rhee, S. Y. (2024). Plant Metabolic Network 16: expansion of underrepresented plant groups and experimentally supported enzyme data. Nucleic Acids Research. DOI: 10.1093/nar/gkae991

We are super excited to announce the release of PMN 16! PMN 16 introduces twenty-eight new single-species databases, listed below, as well as new versions of the existing 127 single-species databases and to PlantCyc, bringing our total to 155.  Selection of new species was focused on understudied plants and plant groups, including non-angiosperm plant such as hornworts and gymnosperms, as well as plants listed by the African Orphan Crop Consortium such as teff, moringa, and bambara groundnut. All databases were (re)generated using our new internal pipeline, making use of Pathway Tools 28.0, the new E2P2 version 5, and updated SAVI validation lists (SAVI 3.2). The first new enzyme data from our collaboration with the labs of Hiroshi Maeda (UW-Madison) and Philipp Zerbe (UC Davis) are also incorporated into this release, with more to come!

E2P2 version 5, the ensemble prediction software developed by the PMN team to predict enzyme function from amino acid sequence, is now available on github (link), and features a significant back-end overhaul. It is now possible to swap out enzymy predictors and to add your own by writing a configuration file. The default predictors are now BLAST and DeepEC, the latter having been swapped in for PRIAM, the second predictor in previous releases. Along with E2P2v5, a new version of the reference protein sequence dataset (RPSD), the set of enzymes collected by the PMN team to use as the basis for E2P2's predictions, has been released. RPSD 5.2 can be downloaded here.

PMN 16 is the first release generated using our new internal pipeline. This update greatly improves the speed, scalability, and reproducability of the pipeline, and now that it is finished we plan to use it to scale up future releases, increasing both size and frequency. In addition, later this year we will, for the first time, be releasing our pipeline to the public. When released, this software will be able to generate pathway genome databases for plant and green algal species using the same procedure that PMN uses. Users will be able to generate their own databases, reproduce our results, and see how the databases change when input options are changed. We're excited to see the new pathway databases people will create!

Finally, we have been collaborating with the labs of Philipp Zerbe and Hiroshi Maeda as part of a new Enzyme Consortium, with the goal of elicidating the function of more members of large classes of enzyme. Our collaborators have already begun work to characterize enzymes in the terpene synthase (TPS), aminotransferase (AT), and cytochrome P450 (CYP) families, and some early results are already incorporated into some of the PMN databases. We look forward to a fruitful continued collaboration!

New databases in this release:

GarlicCyc (Allium sativum), Aagrestis_BonnCyc (Anthoceros agrestis Bonn), Aagrestis_oxfordCyc (Anthoceros agrestis Oxford), ApunctatusCyc (Anthoceros punctatus), AangustusCyc (Anthoceros angustus), SweetWormwoodCyc (Artemisia annua), JackfruitCyc (Artocarpus heterophyllus), BreadfruitCyc (Artocarpus altilis), AfilliculoidesCyc (Azolla filiculoides), CamelinaCyc (Camelina sativa), DrabaCyc (Draba nivalis), TeffCyc (Eragrostis tef), AppleRingAcaciaCyc (Faidherbia albida), StrawberryCyc (Fragaria x ananassa), GamNuiCyc (Gnetum montanum), AlyssumCyc (Lobularia maritima), MoringaCyc (Moringa oleifera), PocketWaterLilyCyc (Nymphaea colorata), MexicanAvocadoCyc (Persea americana drymifolia), HaasAvocadoCyc (Persea americana americana), HuskTomatoCyc (Physalis pubescens), BlackPepperCyc (Piper nigrum), RosemaryCyc (Salvia rosmarinus), WatermossCyc (Salvinia cucullata), RyeCyc (Secale cereale), CoastRedwoodCyc (Sequoia sempervirens), VanillaCyc (Vanilla planifolia), and BambaraBeanCyc (Vigna subterranea)

The PMN BLAST server will be updated in a couple of days with the new databases, and downloads of the new databases will also become available soon

The Plant Metabolic Network (PMN) once again left a lasting impression at the recent STEAM Expo Days event during the MSU Science Festival. Led by Charles Hawkins, director of PMN, a dedicated team of volunteers including Danielle Hoffman, Matt Stata, and Hillary Fischer engaged with approximately 300 students, showcasing an innovative outreach activity focused on the chemical nature of fragrance in fruits.

Titled "Why do Bananas Smell so A-Peeling," the activity captivated attendees with its hands-on approach and interactive demonstrations. Through engaging discussions and captivating experiments, participants were introduced to the fascinating world of plant metabolism and chemistry.

Big news! PMN has just received a new grant from the National Science Foundation's Plant Genome Research Program (PGRP). Worth $3 million over four years, this grant will allow us to significantly expand PMN in size, scope, and usefulness. In addition to our PI, Dr. Sue Rhee here at Michigan State University, whose lab created PMN and has operated and maintained it for more than 15 years, we have now also brought on collaborators Dr. Hiroshi Maeda at the University of Wisconsin-Madison, and Dr. Phillipp Zerbe from the University of California, Davis. Both these labs have tremendous expertise in the functional characterization of enzymes, and they have signed on to work with us to discover new enzymes as well as new functions for previously-known enzymes in a multitude of plant species. Newly-characterized enzymes will be represented in PMN directly in the appropriate species database, but will also be included in the dataset we use to make computational predictions of enzymes in all PMN species, so the impact of these new data will reach beyond their species of origin. These labs will form the core of an Enzyme Consortium, a collaboration of computational and experimental groups focused on identifying and filling gaps in our understanding of plant enzymes and metabolism.

As another major objective, we plan to massively increase the number of plant and green alge species databases in PMN, from the current total of 127 to more than 1000 by the end of the grant period. To achieve this increase, we will be overhauling the computational pipeline we use to create and update the PMN databases, making it faster, easier, more reproducible, and more scalable. Even better, we will be releasing the upgraded pipeline publicly as a Singularity container, so interested users can reproduce our results and generate their own plant databases comparable to the ones in PMN. Our next release, PMN 16, is due out in mid-2024 and will be the first to be built using the new pipeline.

We will also be releasing a new version of our Ensemble Enzyme Prediction Pipeline (E2P2) software [insert link to github], a core piece of the pipeline that predicts enzyme function from amino acid sequences. E2P2 is an ensemble classifier, meaning it combines the predictions of different classifier software to produce a final set of predictions, and the new E2P2 version 5 will be modularized so that users can easily add and swap out classifiers using a standardized interface. The default classifiers will be blastp [link to ncbi blast+] and DeepEC [link to paper], the latter replacing PRIAM which is no longer maintained, but users will be able to easily add more if desired.

Finally, we will be developing educational resources and materials to help K-12 teachers engage students from diverse backgrounds with plant science, helping to fostering the next generation of leaders in the field.

We're super excited to take PMN to the next level, and we can't wait to get started!