Department of Environmental Systems Science, ETH Zurich, Universitätstrasse 16, 8092 Zürich, Switzerland; The Department for Earth, Atmospheric and Planetary Science, MIT, Boston, MA, USA.
Department of Environmental Systems Science, ETH Zurich, Universitätstrasse 16, 8092 Zürich, Switzerland; Div. of Hydrologic Sciences, Desert Research Institute, Reno, NV, USA.
Curr Opin Biotechnol. 2021 Feb;67:65-71. doi: 10.1016/j.copbio.2021.01.004. Epub 2021 Jan 22.
The combination of genome-scale metabolic networks with spatially explicit representation of microbial habitats (spatiotemporal metabolic network modeling) paves the way to predict complex metabolic landscapes to a hitherto unparalleled detail, thus providing new insights into trophic interactions occurring at different scales. Placing detailed bacterial metabolism in realistic physical environment highlights the roles of physical barriers and diffusional bottlenecks on bacterial community interactions, structure and stability. We review recent advances in spatiotemporal metabolic network modeling using a few illustrative examples that highlight the immense potential of these novel approaches to interpret and design metabolic mediated interactions in structures (natural and engineered) environments.
将基因组规模的代谢网络与微生物栖息地的空间显式表示（时空代谢网络建模）相结合，为预测复杂的代谢景观铺平了道路，可以以前所未有的细节提供新的见解，从而了解不同尺度上发生的营养相互作用。将详细的细菌代谢置于现实的物理环境中，可以突出物理障碍和扩散瓶颈对细菌群落相互作用、结构和稳定性的作用。我们通过一些说明性示例回顾了时空代谢网络建模的最新进展，这些示例突出了这些新方法在解释和设计结构（自然和工程）环境中的代谢介导相互作用方面的巨大潜力。
