Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089, USA.
Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA.
BMC Bioinformatics. 2024 Jan 29;25(1):45. doi: 10.1186/s12859-024-05655-3.
Microbial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions and identify strategies to optimize the community. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model; however, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling can capture additional heterogeneity across a population, especially when cells exhibit sub-maximal growth rates.
In this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. With sampling, we find significant differences in the predicted metabolism, including an increase in cooperative interactions and pathway-specific changes in predicted flux.
Our results suggest the importance of sampling-based approaches to evaluate metabolic interactions. Furthermore, we emphasize the utility of flux sampling in quantitatively studying interactions between cells and organisms.
微生物群落通过代谢相互作用在生态系统功能中起着至关重要的作用。基因组规模建模是一种了解这些相互作用并确定优化群落策略的有前途的方法。通量平衡分析（FBA）最常用于预测基因组规模模型中所有反应的通量；然而，FBA 预测的通量取决于用户定义的细胞目标。通量采样是 FBA 的替代方法，因为它提供了微生物群落中可能的通量范围。此外，通量采样可以在整个种群中捕获额外的异质性，特别是当细胞表现出亚最大生长速率时。
在这项研究中，我们模拟了微生物群落的新陈代谢，并比较了 FBA 和通量采样发现的代谢特征。通过采样，我们发现预测代谢存在显著差异，包括合作相互作用的增加和预测通量的途径特异性变化。
我们的结果表明，基于采样的方法对于评估代谢相互作用非常重要。此外，我们强调通量采样在定量研究细胞和生物体之间相互作用的有用性。
