Pooled and dual-guided CRISPRi, a genome-wide tool for genetic interaction mapping in high-throughput
汇集和双引导 CRISPRi,一种用于高通量遗传相互作用图谱的全基因组工具
基本信息
- 批准号:10305684
- 负责人:
- 金额:$ 19.56万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-11-19 至 2023-04-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Project Summary
No single gene acts by itself, instead the genome is organized into an intricate network of interacting components
to ensure the organism mounts an appropriate response to its environment. A genetic interaction network (GIN)
represents a global view of these relationships and, for instance, can depict a cell as a functional wiring diagram.
Thereby GINs are key to develop an integrated understanding of all processes in a cell or organism. A genetic
interaction is defined as a combination of mutations that have an unexpected phenotype with respect to the effect
of the individual perturbations. For instance, two mutations that have little effect by themselves when combined
may be lethal (a negative interaction) or two mutations that have a negative effect individually may have no effect
when combined (a positive interaction). For model systems including yeast, tools such as synthetic genetic array
analyses exist that allows for sampling of double gene knockouts on a genome-wide scale. This approach has
enabled sampling of >23 million interactions and has resulted in the most detailed genetic interaction network to
date consisting of ~900,000 genetic interactions. In contrast, an easily implementable approach for bacteria that
can map genome-wide genetic interactions in high-throughput is lacking. In this proposal we solve this
challenge by developing pooled and dual-guided CRISPRi (p&dgCRISPRi) in the bacterial pathogen
Streptococcus pneumoniae. As a proof-of-principle we developed a relatively small version of p&dgCRISPRi.
To enable this, we designed a cloning strategy aimed at combining two single guide RNAs (gRNAs) into a single
genome targeting all pairwise combinations of a set of 105 genes in S. pneumoniae. Thereby ~5000 pairwise
interactions were screened in a pool, resulting in ~500 negative interactions and ~200 positive interactions. In
Aim 1, we scale-up the approach and generate saturated libraries totaling ~1.2 million interactions. We first
evaluate 10 gRNAs for each open reading frame (ORF) in the genome, and select two efficient ones. These
gRNAs are than used to generate over 1.2 million pooled S. pneumoniae CRISPRi strains where each bacterium
expresses 2 gRNAs. Each gRNA-pair is linked to two random barcodes, and the change in frequency of these
barcodes in the population, which is determined by Illumina sequencing, is used to calculate their effect on
fitness. In Aim 2, we build
the first genome-wide genetic interaction network for S. pneumoniae by screening the
p&dgCRISPRi libraries in rich and minimal media, and in rich media supplemented with an antibiotic from one of
the four major classes. Networks are analyzed in detail and are combined and fused with additional (omics)data
to provide context, and mined for new biological insights, while 30-50 interactions are validated to confirm high-
confidence interactions. Most importantly, these GINs will proof central to developing an integrated
understanding of all processes in an organism and may for instance aid in the design of new antimicrobial
strategies.
项目摘要
没有单个基因的作用本身,而是将基因组组织成复杂的相互作用网络
确保生物体对其环境产生适当的反应。遗传相互作用网络(GIN)
代表这些关系的全局视图,例如,可以将单元描绘成功能性接线图。
因此,杜松是对细胞或生物体中所有过程的综合理解的关键。遗传
相互作用定义为具有意外表型相对于效应的突变的组合
个人扰动。例如,两个突变在合并时几乎没有效果
可能是致命的(负相互作用)或两个具有负面影响的突变可能没有效果
当组合时(正相互作用)。对于包括酵母在内的模型系统,诸如合成遗传阵列之类的工具
存在分析,可以在全基因组范围内对双基因敲除取样。这种方法有
启用了> 2300万相互作用的采样,并导致了最详细的遗传相互作用网络
日期由约900,000个遗传相互作用组成。相反,一种易于实施的细菌方法
缺乏在高通量中绘制全基因组的遗传相互作用。在这个建议中,我们解决了这个问题
通过在细菌病原体中开发汇集和双引导的CRISPRI(P&DGCRISPRI)来挑战
肺炎链球菌。作为原理证明,我们开发了一个相对较小的P&Dgcrispri版本。
为了实现这一目标,我们设计了一种克隆策略
靶向肺炎链球菌中一组105个基因的所有成对组合的基因组。因此〜5000成对
在池中筛选了相互作用,导致约500个负相互作用和约200个正相互作用。在
AIM 1,我们扩大方法并产生饱和的库,总计约120万个相互作用。我们首先
评估基因组中每个开放式阅读框(ORF)的10个GRNA,并选择两个有效的grnas。这些
GRNA所用来产生超过120万张肺炎链球菌Crispri菌株,每种细菌
表达2个grnas。每个GRNA对与两个随机条形码有关,并且这些频率的变化
通过Illumina测序确定的人口中的条形码用于计算其对
健康。在AIM 2中,我们构建
肺炎链球菌的第一个全基因组遗传相互作用网络通过筛查
P&Dgcrispri图书馆中的富裕媒体和富裕媒体中,并补充了一种抗生素
四个主要班级。网络进行详细分析,并与其他(OMIC)数据结合并融合
提供背景并为新的生物学见解而开采,而30-50个相互作用得到验证以确认高
置信度相互作用。最重要的是,这些杜松子会证明开发综合的核心
了解有机体中的所有过程,例如,可能有助于设计新抗菌剂的设计
策略。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
LptD depletion disrupts morphological homeostasis and upregulates carbohydrate metabolism in Escherichia coli.
- DOI:10.1093/femsmc/xtad013
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
共 1 条
- 1
Juan Cesar Federic...的其他基金
Consequences of Direct Viral-Bacterial Interactions
病毒-细菌直接相互作用的后果
- 批准号:1043720410437204
- 财政年份:2021
- 资助金额:$ 19.56万$ 19.56万
- 项目类别:
A priori adaptive evolution predictions for antibiotic resistance through genome-wide network analyses and machine learning
通过全基因组网络分析和机器学习对抗生素耐药性进行先验适应性进化预测
- 批准号:1039653710396537
- 财政年份:2020
- 资助金额:$ 19.56万$ 19.56万
- 项目类别:
A priori adaptive evolution predictions for antibiotic resistance through genome-wide network analyses and machine learning
通过全基因组网络分析和机器学习对抗生素耐药性进行先验适应性进化预测
- 批准号:1064170010641700
- 财政年份:2020
- 资助金额:$ 19.56万$ 19.56万
- 项目类别:
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