A synthetic biology approach to analyze evolution of programmed bacterial death

分析程序性细菌死亡进化的合成生物学方法

• 批准号: 9274315
• 负责人: LINGCHONG YOU
• 金额: $ 28.89万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9274315
• 关键词: Altruism; Antibiotic Therapy; Antibiotics; Apoptosis; Automation; Bacteria; Behavior; Biological Models; Biological Process; Biology; Cessation of life; Death Rate; Development; Engineering; Escherichia coli; Evolution; Foundations; Genes; Goals; Growth; Investigation; Maintenance; Measurement; Measures; Mediating; Microfluidic Microchips; Microfluidics; Modeling; Population; Population Dynamics; Process; Public Health; Research; Social Behavior; Starvation; Stress; Structure; Survivors; Synthetic Genes; System; Techniques; Technology; Treatment Protocols; Virulence; Vision; Work; antimicrobial; base; clinically relevant; design; effective therapy; experimental study; fitness; innovation; insight; microbial; novel; novel therapeutics; pathogen; public health relevance; response; synthetic biology; trait; treatment strategy

DESCRIPTION (provided by applicant): A synthetic biology approach to analyze evolution of programmed bacterial death Programmed death is commonly associated with a bacterial response to stressful conditions, such as starvation, presence of competitors, and antibiotic treatment. As death offers no benefit to its actor, evolution of programmed bacterial death is a fundamental, unresolved problem in biology. A popular explanation is that the death is "altruistic": it can provide direct or indirect benefitsto the survivors. In other words, death may represent the ultimate form of cooperation. By making this assumption, evolution of programmed death can be analyzed under the general framework of public-good cooperation. Using this framework, studies have suggested possible public goods resulting from death in various bacterial pathogens. However, there remains a fundamental gap in the definitive understanding of microbial social behavior in general and programmed bacterial death in particular. Indeed, advantage of altruistic death has never been unequivocally demonstrated in an experimental system. A major challenge in tackling this problem is the complexity of natural biological processes, where numerous confounding factors obscure interpretation and quantitative analysis of the benefits associated with death. For example, previous work has been criticized because gene manipulations involved led to multiple effects and so it is hard to tease apart different fitness consequences. These issues make the results open to alternative explanations, such as PCD representing a maladaptive response to stress. We propose to use a combination of synthetic-biology techniques and microfluidics to overcome these limitations. In particular, using a set of synthetic gene circuits in bacterium Escherichia coli to implement tunable altruistic death, we will quantitatively define the condition under which altruistic death can become advantageous at the population level and examine their evolutionary dynamics in the presence of cheating. To enable such analysis, we will develop a novel droplet-based platform to examine the evolutionary dynamics under different conditions. Building on such understanding, we will develop and evaluate new treatment strategies that will exploit the evolutionary dynamics. It is our vision that the proposed research will have several broad impacts. First, it will fill the critical conceptual gap in our understandig of the evolution of programmed death. Second, it will generate novel insights into how bacteria respond to antibiotic-mediated stress, which has implications for designing novel therapeutic strategies against bacterial pathogens.

描述（由申请人提供）：

项目成果

Collective antibiotic tolerance: mechanisms, dynamics and intervention.

• DOI: 10.1038/nchembio.1754
• 发表时间: 2015-03
• 期刊: Nature chemical biology
• 影响因子: 14.8
• 作者: Meredith HR;Srimani JK;Lee AJ;Lopatkin AJ;You L
• 通讯作者: You L

A noisy linear map underlies oscillations in cell size and gene expression in bacteria.

• DOI: 10.1038/nature14562
• 发表时间: 2015-07-16
• 期刊: Nature
• 影响因子: 64.8
• 作者: Tanouchi Y;Pai A;Park H;Huang S;Stamatov R;Buchler NE;You L
• 通讯作者: You L

Dissecting the effects of antibiotics on horizontal gene transfer: Analysis suggests a critical role of selection dynamics.

• DOI: 10.1002/bies.201600133
• 发表时间: 2016-12
• 期刊: BioEssays : news and reviews in molecular, cellular and developmental biology
• 作者: Lopatkin AJ;Sysoeva TA;You L
• 通讯作者: You L

Coupling spatial segregation with synthetic circuits to control bacterial survival.

• DOI: 10.15252/msb.20156567
• 发表时间: 2016-02-29
• 期刊: Molecular systems biology
• 影响因子: 9.9
• 作者: Huang S;Lee AJ;Tsoi R;Wu F;Zhang Y;Leong KW;You L
• 通讯作者: You L

Nonviral gene editing via CRISPR/Cas9 delivery by membrane-disruptive and endosomolytic helical polypeptide.

通过膜破坏性和内体溶解螺旋多肽通过 CRISPR/Cas9 传递进行非病毒基因编辑

• DOI: 10.1073/pnas.1712963115
• 发表时间: 2018-05-08
• 期刊: Proceedings of the National Academy of Sciences of the United States of America
• 影响因子: 11.1
• 作者: Wang HX;Song Z;Lao YH;Xu X;Gong J;Cheng D;Chakraborty S;Park JS;Li M;Huang D;Yin L;Cheng J;Leong KW
• 通讯作者: Leong KW