Département de Biologie, Université de Sherbrooke, Sherbrooke, Quebec, Canada.
Department of Bioengineering, University of California, San Diego, La Jolla, California, USA.
mBio. 2024 Oct 16;15(10):e0087324. doi: 10.1128/mbio.00873-24. Epub 2024 Aug 29.
Microorganisms with simplified genomes represent interesting cell chassis for systems and synthetic biology. However, genome reduction can lead to undesired traits, such as decreased growth rate and metabolic imbalances. To investigate the impact of genome reduction on strain DGF-298, a strain in which ~ 36% of the genome has been removed, we reconstructed a strain-specific metabolic model (AC1061), investigated the regulation of gene expression using iModulon-based transcriptome analysis, and performed adaptive laboratory evolution to let the strain correct potential imbalances that arose during its simplification. The model notably predicted that the removal of all three key pathways for glycolaldehyde disposal in this microorganism would lead to a metabolic bottleneck through folate starvation. Glycolaldehyde is also known to cause self-generation of reactive oxygen species, as evidenced by the increased expression of oxidative stress resistance genes in the SoxS iModulon. The reintroduction of the gene, responsible for one native glycolaldehyde disposal route, alleviated the constitutive oxidative stress response. Our results suggest that systems-level approaches and adaptive laboratory evolution have additive benefits when trying to repair and optimize genome-engineered strains.
Genomic streamlining can be employed in model organisms to reduce complexity and enhance strain predictability. One of the most striking examples is the bacterial strain DGF-298, notable for having over one-third of its genome deleted. However, such extensive genome modifications raise the question of how similar this simplified cell remains when compared with its parent, and what are the possible unintended consequences of this simplification. In this study, we used metabolic modeling along with iModulon-based transcriptomic analysis in different growth conditions to assess the impact of genome reduction on metabolism and gene regulation. We observed little impact of genomic reduction on the regulatory network of DGF-298 and identified a potential metabolic bottleneck leading to the constitutive activity of the SoxS iModulon. We then leveraged the model's predictions to successfully restore SoxS activity to the basal level.
具有简化基因组的微生物是系统和合成生物学中有趣的细胞底盘。然而，基因组的减少会导致不理想的特性，例如生长速度减慢和代谢失衡。为了研究基因组减少对菌株 DGF-298 的影响，我们构建了一个菌株特异性的代谢模型（AC1061），使用基于 iModulon 的转录组分析研究了基因表达的调控，并进行了适应性实验室进化，让菌株纠正简化过程中出现的潜在失衡。该模型特别预测，在这种微生物中去除所有三条用于处理乙醛酸的关键途径会导致叶酸饥饿引起的代谢瓶颈。乙醛酸也被认为会导致活性氧的自我产生，这一点可以从 SoxS iModulon 中氧化应激抗性基因的表达增加得到证明。引入负责一种天然乙醛酸处理途径的基因缓解了组成型氧化应激反应。我们的研究结果表明，在试图修复和优化基因组工程菌株时，系统水平的方法和适应性实验室进化具有附加的益处。
基因组简化可用于模型生物以减少复杂性并提高菌株的可预测性。最引人注目的例子之一是细菌菌株 DGF-298，其基因组有三分之一以上被删除。然而，如此广泛的基因组修改提出了一个问题，即与亲本相比，这种简化后的细胞仍然有多少相似之处，以及这种简化可能带来哪些意想不到的后果。在这项研究中，我们使用代谢建模以及不同生长条件下基于 iModulon 的转录组分析来评估基因组减少对代谢和基因调控的影响。我们观察到基因组减少对 DGF-298 调控网络的影响很小，并发现了一个可能导致 SoxS iModulon 组成性激活的潜在代谢瓶颈。然后，我们利用模型的预测成功地将 SoxS 活性恢复到基础水平。
