Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kemitorvet, Building 220. Kongens Lyngby 2800, Denmark.
Department of Bioengineering, University of California, San Diego, La Jolla ,California92093-0412 ,United States.
ACS Synth Biol. 2024 Jul 19;13(7):2045-2059. doi: 10.1021/acssynbio.3c00572. Epub 2024 Jun 27.
As the availability of data sets increases, meta-analysis leveraging aggregated and interoperable data types is proving valuable. This study leveraged a meta-analysis workflow to identify mutations that could improve robustness to reactive oxygen species (ROS) stresses using an industrially important melatonin production strain as an example. ROS stresses often occur during cultivation and negatively affect strain performance. Cellular response to ROS is also linked to the SOS response and resistance to pH fluctuations, which is important to strain robustness in large-scale biomanufacturing. This work integrated more than 7000 adaptive laboratory evolution (ALE) mutations across 59 experiments to statistically associate mutated genes to 2 ROS tolerance ALE conditions from 72 unique conditions. Mutant , , , and were significantly associated and hypothesized to contribute fitness in ROS stress. Across these genes, 259 total mutations were inspected in conjunction with transcriptomics from 46 iModulon experiments. Ten mutations were chosen for reintroduction based on mutation clustering and coinciding transcriptional changes as evidence of fitness impact. Strains with mutations reintroduced into , , , and exhibited increased tolerance to HO and acid stress and reduced SOS response, all of which are related to ROS. Additionally, new evidence was generated toward understanding the function of , an uncharacterized gene. This meta-analysis approach utilized aggregated and interoperable multiomics data sets to identify mutations conferring industrially relevant phenotypes with the least drawbacks, describing an approach for data-driven strain engineering to optimize microbial cell factories.
随着数据集的可用性增加，利用聚合和可互操作的数据类型进行荟萃分析被证明是有价值的。本研究利用荟萃分析工作流程，以工业上重要的褪黑素生产菌株为例，确定可以提高对活性氧 (ROS) 应激的稳健性的突变。ROS 应激通常在培养过程中发生，并对菌株性能产生负面影响。细胞对 ROS 的反应也与 SOS 反应和对 pH 波动的抗性有关，这对于大规模生物制造中菌株的稳健性很重要。这项工作整合了超过 7000 个适应性实验室进化 (ALE) 突变，涉及 59 个实验，以统计地将突变基因与来自 72 个独特条件的 2 个 ROS 耐受 ALE 条件相关联。突变体 、 、 、 和 与 ROS 应激的适应度显著相关，并假设其具有适应性。在这些基因中，共检查了 259 个总突变，同时结合了 46 个 iModulon 实验的转录组学数据。根据突变聚类和转录变化的一致性，选择了 10 个突变进行重新引入，作为对适应度影响的证据。引入突变的菌株在 HO 和酸应激方面表现出更高的耐受性，同时 SOS 反应减少，所有这些都与 ROS 有关。此外，还产生了新的证据，以了解未被描述的基因 的功能。这种荟萃分析方法利用聚合和可互操作的多组学数据集来识别赋予具有最小缺点的工业相关表型的突变，描述了一种用于数据驱动的菌株工程的方法，以优化微生物细胞工厂。
