Leveraging core enzyme structures for microbiota targeted functional regulation: Urease as an example

Abstract

Microbial communities play critical roles in various ecosystems. Despite extensive research on the taxonomic and functional diversity of microbial communities, effective approaches to regulate targeted microbial functions remain limited. Here, we present an innovative methodology that integrates core enzyme identification, protein structural characterization, regulator virtual screening, and functional validation to achieve precise microbiome functional regulation. As a proof of concept, we focused on the regulation of urea decomposition by the rumen microbiota in ruminants. Through metagenomic analysis, we identified the core urease gene and its corresponding microbial genome (MAG257) affiliated with the unclassified Succinivibrionaceae, and reconstructed its complete gene cluster. Structural analysis of the urease catalytic subunit (UreC) via cryo-electron microscopy (cryo-EM) revealed detailed features of its active site, guiding molecular docking studies that identified epiberberine, a natural compound with potent urease inhibitory activity. Validation in a rumen simulation system demonstrated that epiberberine significantly reduced urea decomposition and enhanced nitrogen utilization. This study establishes a robust framework that combines structural biology and computational screening to achieve targeted microbiome functional regulation, offering a promising tool for microbiome engineering and broader applications in animal productivity, human health, environmental improvement, and biotechnology.

Keywords

core / epiberberine / function / microbiome / protein structure / rumen / urease

References

[1] Blaser, Martin, Peer Bork, Claire Fraser, Rob Knight, and Jun Wang. 2013. “The Microbiome Explored: Recent Insights and Future Challenges.” Nature Reviews Microbiology 11: 213-217. https://doi.org/10.1038/nrmicro2973

[2] Roux, Simon, Blair G. Paul, Sarah C. Bagby, Stephen Nayfach, Michelle A. Allen, Graeme Attwood, Ricardo Cavicchioli, et al. 2021. “Ecology and Molecular Targets of Hypermutation in the Global Microbiome.” Nature Communications 12: 3076. https://doi.org/10.1038/s41467-021-23402-7

[3] Burz, Sebastian Dan, Senka Causevic, Alma Dal Co, Marija Dmitrijeva, Philipp Engel, Daniel Garrido-Sanz, Gilbert Greub, et al. 2023. “From Microbiome Composition to Functional Engineering, One Step at a Time.” Microbiology and Molecular Biology Reviews 87: e00063-e00023. https://doi.org/10.1128/mmbr.00063-23

[4] Sanchez, Alvaro, Djordje Bajic, Juan Diaz-Colunga, Abigail Skwara, Jean C. C. Vila, and Seppe Kuehn. 2023. “The Community-Function Landscape of Microbial Consortia.” Cell Systems 14: 122-134. https://doi.org/10.1016/j.cels.2022.12.011

[5] Aagaard, Kjersti, and Elizabeth Hohmann. 2019. “Regulating Microbiome Manipulation.” Nature Medicine 25: 874-876. https://doi.org/10.1038/s41591-019-0451-1

[6] Jia, Baolei, Xiao Han, Kyung Hyun Kim, and Che Ok Jeon. 2022. “Discovery and Mining of Enzymes From the Human Gut Microbiome.” Trends in Biotechnology 40: 240-254. https://doi.org/10.1016/j.tibtech.2021.06.008

[7] Escalas, Arthur, Lauren Hale, James W. Voordeckers, Yunfeng Yang, Mary K. Firestone, Lisa Alvarez-Cohen, and Jizhong Zhou. 2019. “Microbial Functional Diversity: From Concepts to Applications.” Ecology and Evolution 9: 12000-12016. https://doi.org/10.1002/ece3.5670

[8] Lin, Limei, Huiting Ma, Jiawei Zhang, Huisheng Yang, Jiyou Zhang, Zheng Lai, Weibiao Qi, et al. 2024. “Lignocellulolytic Microbiomes Orchestrating Degradation Cascades in the Rumen of Dairy Cattle and Their Diet-Influenced Key Degradation Phases.” Animal Advances 1: e002. https://doi.org/10.48130/animadv-0024-0002

[9] Napolitano, Fabio, Andrea Bragaglio, Emilio Sabia, Francesco Serrapica, Ada Braghieri, and Giuseppe De Rosa. 2020. “The Human−Animal Relationship in Dairy Animals.” Journal of Dairy Research 87: 47-52. https://doi.org/10.1017/S0022029920000606

[10] Niazifar, Masoumeh, Maghsoud Besharati, Muhammad Jabbar, Shakira Ghazanfar, Muhammad Asad, Valiollah Palangi, Hüseyin Eseceli, and Maximilian Lackner. 2024. “Slow-Release Non-Protein Nitrogen Sources in Animal Nutrition: A Review.” Heliyon 10: e33752. https://doi.org/10.1016/j.heliyon.2024.e33752

[11] Ceconi, I., M. J. Ruiz-Moreno, N. DiLorenzo, A. DiCostanzo, and G. I. Crawford. 2015. “Effect of Urea Inclusion in Diets Containing Corn Dried Distillers Grains on Feedlot Cattle Performance, Carcass Characteristics, Ruminal Fermentation, Total Tract Digestibility, and Purine Derivatives-To-Creatinine Index.” Journal of Animal Science 93: 357-369. https://doi.org/10.2527/jas.2014-8214

[12] Hailemariam, Samson, Shengguo Zhao, Yue He, and Jiaqi Wang. 2021. “Urea Transport and Hydrolysis in the Rumen: A Review.” Animal Nutrition 7: 989-996. https://doi.org/10.1016/j.aninu.2021.07.002

[13] Herrero, Mario, Benjamin Henderson, Petr Havlík, Philip K. Thornton, Richard T. Conant, Pete Smith, Stefan Wirsenius, et al. 2016. “Greenhouse Gas Mitigation Potentials in the Livestock Sector.” Nature Climate Change 6: 452-461. https://doi.org/10.1038/nclimate2925

[14] Clark, Michael, and David Tilman. 2017. “Comparative Analysis of Environmental Impacts of Agricultural Production Systems, Agricultural Input Efficiency, and Food Choice.” Environmental Research Letters 12: 064016. https://doi.org/10.1088/1748-9326/aa6cd5

[15] Behera, Sailesh N., Mukesh Sharma, Viney P. Aneja, and Rajasekhar Balasubramanian. 2013. “Ammonia in the Atmosphere: A Review on Emission Sources, Atmospheric Chemistry and Deposition on Terrestrial Bodies.” Environmental Science and Pollution Research 20: 8092-8131. https://doi.org/10.1007/s11356-013-2051-9

[16] Liu, Sijia, Nan Zheng, Shengguo Zhao, and Jiaqi Wang. 2020. “Exploring the Diversity of Active Ureolytic Bacteria in the Rumen by Comparison of cDNA and gDNA.” Animals 10: 2162. https://doi.org/10.3390/ani10112162

[17] Carlini, Celia R., and Rodrigo Ligabue-Braun. 2016. “Ureases as Multifunctional Toxic Proteins: A Review.” Toxicon 110: 90-109. https://doi.org/10.1016/j.toxicon.2015.11.020

[18] Duin, Evert C., Tristan Wagner, Seigo Shima, Divya Prakash, Bryan Cronin, David R. Yáñez-Ruiz, Stephane Duval, et al 2016. “Mode of Action Uncovered for the Specific Reduction of Methane Emissions From Ruminants by the Small Molecule 3-nitrooxypropanol.” Proceedings of the National Academy of Sciences of the United States of America 113: 6172-6177. https://doi.org/10.1073/pnas.1600298113

[19] Hristov, Alexander N., Joonpyo Oh, Fabio Giallongo, Tyler W. Frederick, Michael T. Harper, Holley L. Weeks, Antonio F. Branco, et al 2015. “An Inhibitor Persistently Decreased Enteric Methane Emission From Dairy Cows With no Negative Effect on Milk Production.” Proceedings of the National Academy of Sciences of the United States of America 112: 10663-10668. https://doi.org/10.1073/pnas.1504124112

[20] Neu, Alexander T., Eric E. Allen, and Kaustuv Roy. 2021. “Defining and Quantifying the Core Microbiome: Challenges and Prospects.” Proceedings of the National Academy of Sciences of the United States of America 118: e2104429118. https://doi.org/10.1073/pnas.2104429118

[21] Henderson, Gemma, Faith Cox, Siva Ganesh, Arjan Jonker, Wayne Young, Leticia Abecia, Erika Angarita, et al 2015. “Rumen Microbial Community Composition Varies With Diet and Host, But a Core Microbiome Is Found Across a Wide Geographical Range.” Scientific Reports 5: 14567. https://doi.org/10.1038/srep14567

[22] Mazzei, Luca, Francesco Musiani, and Stefano Ciurli. 2020. “The Structure-Based Reaction Mechanism of Urease, a Nickel Dependent Enzyme: Tale of a Long Debate.” JBIC Journal of Biological Inorganic Chemistry 25: 829-845. https://doi.org/10.1007/s00775-020-01808-w

[23] Cunha, Eva S., Xiaorui Chen, Marta Sanz-Gaitero, Deryck J. Mills, and Hartmut Luecke. 2021. “Cryo-EM Structure of Helicobacter pylori Urease With an Inhibitor in the Active Site At 2.0 Å Resolution.” Nature Communications 12: 230. https://doi.org/10.1038/s41467-020-20485-6

[24] Cobellis, Gabriella, Zhongtang Yu, Claudio Forte, Gabriele Acuti, and Massimo Trabalza-Marinucci. 2016. “Dietary Supplementation of Rosmarinus officinalis L. Leaves in Sheep Affects the Abundance of Rumen Methanogens and Other Microbial Populations.” Journal of Animal Science and Biotechnology 7: 27. https://doi.org/10.1186/s40104-016-0086-8

[25] Liu, Sijia, Zhenyu Zhang, Samson Hailemariam, Nan Zheng, Min Wang, Shengguo Zhao, and Jiaqi Wang. 2020. “Biochanin A Inhibits Ruminal Nitrogen-Metabolizing Bacteria and Alleviates the Decomposition of Amino Acids and Urea In Vitro.” Animals 10: 368. https://doi.org/10.3390/ani10030368

[26] He, Yue, Xiaoyin Zhang, Ming Li, Nan Zheng, Shengguo Zhao, and Jiaqi Wang. 2022. “Coptisine: A Natural Plant Inhibitor of Ruminal Bacterial Urease Screened by Molecular Docking.” Science of the Total Environment 808: 151946. https://doi.org/10.1016/j.scitotenv.2021.151946

[27] Mazzei, L., M. Cianci, F. Musiani, and S. Ciurli. 2016. “Inactivation of Urease by 1,4-benzoquinone: Chemistry at the Protein Surface.” Dalton Transactions 45: 5455-5459. https://doi.org/10.1039/C6DT00652C

[28] Li, Cailan, Ping Huang, Kambo Wong, Yifei Xu, Lihua Tan, Hanbin Chen, Qiang Lu, et al. 2018. “Coptisine-Induced Inhibition of Helicobacter pylori: Elucidation of Specific Mechanisms by Probing Urease Active Site and Its Maturation Process.” Journal of Enzyme Inhibition and Medicinal Chemistry 33: 1362-1375. https://doi.org/10.1080/14756366.2018.1501044

[29] Krajewska, Barbara. 2009. “Ureases I. Functional, Catalytic and Kinetic Properties: A Review.” Journal of Molecular Catalysis B: Enzymatic 59: 9-21. https://doi.org/10.1016/j.molcatb.2009.01.003

[30] Minas, Konstantinos, Neil R. McEwan, Charles Jamie Newbold, and Karen P. Scott. 2011. “Optimization of a High-Throughput CTAB-Based Protocol for the Extraction of qPCR-grade DNA From Rumen Fluid, Plant and Bacterial Pure Cultures.” FEMS Microbiology Letters 325: 162-169. https://doi.org/10.1111/j.1574-6968.2011.02424.x

[31] Jin, Di, Shengguo Zhao, Nan Zheng, Dengpan Bu, Yves Beckers, Stuart E. Denman, Christopher S. McSweeney, and Jiaqi Wang. 2017. “Differences in Ureolytic Bacterial Composition Between the Rumen Digesta and Rumen Wall Based on ureC Gene Classification.” Frontiers in Microbiology 8: 385. https://doi.org/10.3389/fmicb.2017.00385

[32] Edgar, Robert C., Brian J. Haas, Jose C. Clemente, Christopher Quince, and Rob Knight. 2011. “UCHIME Improves Sensitivity and Speed of Chimera Detection.” Bioinformatics 27: 2194-2200. https://doi.org/10.1093/bioinformatics/btr381

[33] Boyd, Joel A., Ben J. Woodcroft, and Gene W. Tyson. 2018. “GraftM: A Tool for Scalable, Phylogenetically Informed Classification of Genes Within Metagenomes.” Nucleic Acids Research 46: e59. https://doi.org/10.1093/nar/gky174

[34] Caporaso, J Gregory, Justin Kuczynski, Jesse Stombaugh, Kyle Bittinger, Frederic D. Bushman, Elizabeth K. Costello, Noah Fierer, et al. 2010. “QIIME Allows Analysis of High-Throughput Community Sequencing Data.” Nature Methods 7: 335-336. https://doi.org/10.1038/nmeth.f.303

[35] Kumar, Sudhir, Glen Stecher, Michael Li, Christina Knyaz, and Koichiro Tamura. 2018. “MEGA X: Molecular Evolutionary Genetics Analysis Across Computing Platforms.” Molecular Biology and Evolution 35: 1547-1549. https://doi.org/10.1093/molbev/msy096

[36] Bolger, Anthony M., Marc Lohse, and Bjoern Usadel. 2014. “Trimmomatic: A Flexible Trimmer for Illumina Sequence Data.” Bioinformatics 30: 2114-2120. https://doi.org/10.1093/bioinformatics/btu170

[37] Li, Dinghua, Chi-Man Liu, Ruibang Luo, Kunihiko Sadakane, and Tak-Wah Lam. 2015. “MEGAHIT: An Ultra-Fast Single-Node Solution for Large and Complex Metagenomics Assembly via Succinct De Bruijn Graph.” Bioinformatics 31: 1674-1676. https://doi.org/10.1093/bioinformatics/btv033

[38] Uritskiy, Gherman V., Jocelyne DiRuggiero, and James Taylor. 2018. “MetaWRAP—a Flexible Pipeline for Genome-Resolved Metagenomic Data Analysis.” Microbiome 6: 158. https://doi.org/10.1186/s40168-018-0541-1

[39] Seemann, Torsten. 2014. “Prokka: Rapid Prokaryotic Genome Annotation.” Bioinformatics 30: 2068-2069. https://doi.org/10.1093/bioinformatics/btu153

[40] Krzywinski, Martin, Jacqueline Schein, İnanç Birol, Joseph Connors, Randy Gascoyne, Doug Horsman, Steven J. Jones, and Marco A. Marra. 2009. “Circos: An Information Aesthetic for Comparative Genomics.” Genome Research 19: 1639-1645. https://doi.org/10.1101/gr.092759.109

[41] Huerta-Cepas, Jaime, Kristoffer Forslund, Luis Pedro Coelho, Damian Szklarczyk, Lars Juhl Jensen, Christian von Mering, and Peer Bork. 2017. “Fast Genome-Wide Functional Annotation Through Orthology Assignment by eggNOG-Mapper.” Molecular Biology and Evolution 34: 2115-2122. https://doi.org/10.1093/molbev/msx148

[42] Parks, Donovan H., Michael Imelfort, Connor T. Skennerton, Philip Hugenholtz, and Gene W. Tyson. 2015. “CheckM: Assessing the Quality of Microbial Genomes Recovered From Isolates, Single Cells, and Metagenomes.” Genome Research 25: 1043-1055. https://doi.org/10.1101/gr.186072.114

[43] Zhou, Chenfen, Qingwei Xu, Sheng He, Wei Ye, Ruifang Cao, Pengyu Wang, Yunchao Ling, et al. 2020. “GTDB: An Integrated Resource for Glycosyltransferase Sequences and Annotations.” Database 2020: baaa047. https://doi.org/10.1093/database/baaa047

[44] Zhang, Xiaoyin, Zhanbo Xiong, Ming Li, Nan Zheng, Shengguo Zhao, and Jiaqi Wang. 2022. “Activity- and Enrichment-Based Metaproteomics Insights Into Active Urease From the Rumen Microbiota of Cattle.” International Journal of Molecular Sciences 23: 817. https://doi.org/10.3390/ijms23020817

[45] Xie, Fei, Wei Jin, Huazhe Si, Yuan Yuan, Ye Tao, Junhua Liu, Xiaoxu Wang, et al. 2021. “An Integrated Gene Catalog and over 10,000 Metagenome-Assembled Genomes From the Gastrointestinal Microbiome of Ruminants.” Microbiome 9: 137. https://doi.org/10.1186/s40168-021-01078-x

[46] Li, Xueming, Paul Mooney, Shawn Zheng, Christopher R. Booth, Michael B. Braunfeld, Sander Gubbens, David A. Agard, and Yifan Cheng. 2013. “Electron Counting and Beam-Induced Motion Correction Enable Near-Atomic-Resolution Single-Particle Cryo-EM.” Nature Methods 10: 584-590. https://doi.org/10.1038/nmeth.2472

[47] Rohou, Alexis, and Nikolaus Grigorieff. 2015. “CTFFIND4: Fast and Accurate Defocus Estimation From Electron Micrographs.” Journal of Structural Biology 192: 216-221. https://doi.org/10.1016/j.jsb.2015.08.008

[48] Scheres, Sjors H. W. 2012. “RELION: Implementation of a Bayesian Approach to Cryo-EM Structure Determination.” Journal of Structural Biology 180: 519-530. https://doi.org/10.1016/j.jsb.2012.09.006

[49] Jumper, John, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, et al. 2021. “Highly Accurate Protein Structure Prediction With AlphaFold.” Nature 596: 583-589. https://doi.org/10.1038/s41586-021-03819-2

[50] Pettersen, Eric F., Thomas D. Goddard, Conrad C. Huang, Elaine C. Meng, Gregory S. Couch, Tristan I. Croll, John H. Morris, and Thomas E. Ferrin. 2021. “UCSF ChimeraX: Structure Visualization for Researchers, Educators, and Developers.” Protein Science 30: 70-82. https://doi.org/10.1002/pro.3943

[51] Bond, Paul S., Keith S. Wilson, and Kevin D. Cowtan. 2020. “Predicting Protein Model Correctness in Coot Using Machine Learning.” Acta Crystallographica Section D Structural Biology 76: 713-723. https://doi.org/10.1107/S2059798320009080

[52] Afonine, Pavel V., Billy K. Poon, Randy J. Read, Oleg V. Sobolev, Thomas C. Terwilliger, Alexandre Urzhumtsev, and Paul D. Adams. 2018. “Real-Space Refinement in PHENIX for Cryo-EM and Crystallography.” Acta Crystallographica Section D Structural Biology 74: 531-544. https://doi.org/10.1107/S2059798318006551

[53] Chen, Vincent B., W. Bryan Arendall, Jeffrey J. Headd, Daniel A. Keedy, Robert M. Immormino, Gary J. Kapral, Laura W. Murray, Jane S. Richardson, and David C. Richardson. 2010. “MolProbity: All-Atom Structure Validation for Macromolecular Crystallography.” Acta Crystallographica Section D Biological Crystallography 66: 12-21. https://doi.org/10.1107/S0907444909042073

[54] Sorokina, Maria, Peter Merseburger, Kohulan Rajan, Mehmet Aziz Yirik, and Christoph Steinbeck. 2021. “COCONUT Online: Collection of Open Natural Products Database.” Journal of Cheminformatics 13: 2. https://doi.org/10.1186/s13321-020-00478-9

RIGHTS & PERMISSIONS

2025 The Author(s). iMeta published by John Wiley & Sons Australia, Ltd on behalf of iMeta Science.