Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA.
Cell Syst. 2024 Mar 20;15(3):227-245.e7. doi: 10.1016/j.cels.2024.02.002. Epub 2024 Feb 27.
Many bacteria use operons to coregulate genes, but it remains unclear how operons benefit bacteria. We integrated E. coli's 788 polycistronic operons and 1,231 transcription units into an existing whole-cell model and found inconsistencies between the proposed operon structures and the RNA-seq read counts that the model was parameterized from. We resolved these inconsistencies through iterative, model-guided corrections to both datasets, including the correction of RNA-seq counts of short genes that were misreported as zero by existing alignment algorithms. The resulting model suggested two main modes by which operons benefit bacteria. For 86% of low-expression operons, adding operons increased the co-expression probabilities of their constituent proteins, whereas for 92% of high-expression operons, adding operons resulted in more stable expression ratios between the proteins. These simulations underscored the need for further experimental work on how operons reduce noise and synchronize both the expression timing and the quantity of constituent genes. A record of this paper's transparent peer review process is included in the supplemental information.
许多细菌使用操纵子来协同调控基因,但操纵子如何使细菌受益仍不清楚。我们将大肠杆菌的 788 个多顺反子操纵子和 1231 个转录单元整合到现有的全细胞模型中,发现提出的操纵子结构与模型从 RNA-seq 读值中参数化之间存在不一致。我们通过对两个数据集的迭代、模型引导的校正解决了这些不一致,包括校正了现有比对算法错误地报告为零的短基因的 RNA-seq 计数。该模型提出了操纵子使细菌受益的两种主要模式。对于 86%的低表达操纵子,添加操纵子增加了其组成蛋白的共表达概率,而对于 92%的高表达操纵子,添加操纵子导致蛋白之间的表达比更稳定。这些模拟强调了需要进一步进行实验工作,以了解操纵子如何降低噪声并协调组成基因的表达时间和数量。本文的透明同行评审过程记录包含在补充信息中。