揭示双向启动子调控酿酒酵母基因共表达和代谢通量的调控动力学。

IF 13.1 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Zimo Jin, Yueming Dong, Abdul Muntakim Rafi, Md Mohsin Patwary, Catherine Xu, Morten H Raadam, Carl G de Boer, Codruta Ignea
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引用次数: 0

摘要

双向启动子(Bidirectional promoter, BDPs)能够以最小的启动子大小实现多个基因的共表达,在合成生物学中有着广阔的应用前景。然而,缺乏表征良好的bdp以及对其调控机制的不完全理解限制了其更广泛的应用。在这里,我们对酵母中含有单个共享核小体缺失区域的749个BDP候选物进行了全基因组筛选和表征。使用转录组学和荧光报告分析观察到BDP强度明显不对称。我们证明了这些不平衡的BDP强度可以用于微调酵母的代谢通量,在所检查的条件下,实现与常用的萜类化合物生产的组成或诱导启动子相当或超过的产量。利用DREAM-CNN酵母顺式调控人工智能预测模型指导的硅诱变技术,我们在63.8%的BDP候选物的中心区域发现了保守的激活物结合热点。在六个选定的BDPs中,这些热点的破坏显著降低了两个方向上的启动子强度,这表明这些人工智能预测的基序确实对BDPs的功能至关重要。总体而言,本研究为BDP鉴定和工程提供了一个全面的框架,利用人工智能指导模型推进合理的合成启动子设计,从而为合成生物学中的精确遗传控制铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unraveling the regulatory dynamics of bidirectional promoters for modulating gene co-expression and metabolic flux in Saccharomyces cerevisiae.

Bidirectional promoters (BDPs) hold great promise for applications in synthetic biology by enabling co-expression of multiple genes with minimized promoter size. However, the lack of well-characterized BDPs along with an incomplete understanding of their regulatory mechanisms limits broader applications. Here, we conducted genome-wide screening and characterization of 749 BDP candidates containing a single shared nucleosome-depleted region in yeast Saccharomyces cerevisiae. A pronounced asymmetry in BDP strength was observed using both transcriptomic and fluorescence reporter analyses. We demonstrated that these unbalanced BDP strengths could be utilized for fine-tuning metabolic flux in yeast, achieving yields comparable to or exceeding those of commonly used constitutive or inducible promoters for terpenoid production under the examined conditions. Using in silico mutagenesis guided by the DREAM-CNN yeast cis-regulatory AI prediction model, we identified conserved activator-binding hotspots within the central region of 63.8% of identified BDP candidates. Disruption of these hotspots in six selected BDPs significantly reduced promoter strength in both orientations, suggesting that these AI-predicted motifs are indeed critical for the functionality of BDPs. Overall, this study provides a comprehensive framework for BDP identification and engineering, leveraging AI-guided models to advance rational synthetic promoter design, thus paving the way for precise genetic control in synthetic biology.

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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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