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Understanding and Engineering Distributed Biochemical Pathways in Microbial Communities

  • Xinyun Cao
    Xinyun Cao
    Department of Biochemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States
    More by Xinyun Cao
  • Joshua J. Hamilton
    Joshua J. Hamilton
    Department of Biochemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States
  • , and 
  • Ophelia S. Venturelli*
    Ophelia S. Venturelli
    Department of Biochemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States
    *E-mail: [email protected]
Cite this: Biochemistry 2019, 58, 2, 94–107
Publication Date (Web):November 20, 2018
https://doi.org/10.1021/acs.biochem.8b01006
Copyright © 2018 American Chemical Society
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Abstract

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Microbiomes impact nearly every environment on Earth by modulating the molecular composition of the environment. Temporally changing environmental stimuli and spatial organization are major variables shaping the structure and function of microbiomes. The web of interactions among members of these communities and between the organisms and the environment dictates microbiome functions. Microbial interactions are major drivers of microbiomes and are modulated by spatiotemporal parameters. A mechanistic and quantitative understanding of ecological, molecular, and environmental forces shaping microbiomes could inform strategies to control microbiome dynamics and functions. Major challenges for harnessing the potential of microbiomes for diverse applications include the development of predictive modeling frameworks and tools for precise manipulation of microbiome behaviors.

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This article is cited by 11 publications.

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  2. Elle M. Barnes, Susannah G. Tringe. Exploring the roles of microbes in facilitating plant adaptation to climate change. Biochemical Journal 2022, 479 (3) , 327-335. https://doi.org/10.1042/BCJ20210793
  3. Nathan Innard, James P.J. Chong. The challenges of monitoring and manipulating anaerobic microbial communities. Bioresource Technology 2022, 344 , 126326. https://doi.org/10.1016/j.biortech.2021.126326
  4. Patrick A. Leggieri, Yiyi Liu, Madeline Hayes, Bryce Connors, Susanna Seppälä, Michelle A. O'Malley, Ophelia S. Venturelli. Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes. Annual Review of Biomedical Engineering 2021, 23 (1) , 169-201. https://doi.org/10.1146/annurev-bioeng-082120-022836
  5. Xiaoqing Huang, Jie Ren, Peihua Li, Shun Feng, Pan Dong, Maozhi Ren. Potential of microbial endophytes to enhance the resistance to postharvest diseases of fruit and vegetables. Journal of the Science of Food and Agriculture 2021, 101 (5) , 1744-1757. https://doi.org/10.1002/jsfa.10829
  6. Abd Rahman Jabir Mohd Din, Kenshi Suzuki, Masahiro Honjo, Koki Amano, Tomoka Nishimura, Ryota Moriuchi, Hideo Dohra, Hidehiro Ishizawa, Motohiko Kimura, Yosuke Tashiro, Hiroyuki Futamata. Imbalance in Carbon and Nitrogen Metabolism in Comamonas testosteroni R2 Is Caused by Negative Feedback and Rescued by L-arginine. Microbes and Environments 2021, 36 (4) , n/a. https://doi.org/10.1264/jsme2.ME21050
  7. Sonali Gupta, Tyler D. Ross, Marcella M. Gomez, Job L. Grant, Philip A. Romero, Ophelia S. Venturelli. Investigating the dynamics of microbial consortia in spatially structured environments. Nature Communications 2020, 11 (1) https://doi.org/10.1038/s41467-020-16200-0
  8. Cameron McBride, Domitilla Del Vecchio. Trade-offs in Robustness to Perturbations of Bacterial Population Controllers *. 2020,,, 4276-4282. https://doi.org/10.23919/ACC45564.2020.9148039
  9. Sami Ben Said, Robin Tecon, Benedict Borer, Dani Or. The engineering of spatially linked microbial consortia – potential and perspectives. Current Opinion in Biotechnology 2020, 62 , 137-145. https://doi.org/10.1016/j.copbio.2019.09.015
  10. Maozhen Han, Yuguo Zha, Hui Chong, Chaofang Zhong, Kang Ning. Utilizing microbiome approaches to assist source tracking, treatment and prevention of COVID-19: Review and assessment. Computational and Structural Biotechnology Journal 2020, 18 , 3615-3622. https://doi.org/10.1016/j.csbj.2020.11.027
  11. Ryan H. Hsu, Ryan L. Clark, Jin Wen Tan, John C. Ahn, Sonali Gupta, Philip A. Romero, Ophelia S. Venturelli. Microbial Interaction Network Inference in Microfluidic Droplets. Cell Systems 2019, 9 (3) , 229-242.e4. https://doi.org/10.1016/j.cels.2019.06.008

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