Programming stress‐induced altruistic death in engineered bacteria

Yu, Tao; Pai, Anand; Buchler, Nicolas E.; Li, You

doi:10.1038/msb.2012.57

Cited by 64 publications

(64 citation statements)

References 60 publications

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“…This enzymatic deactivation occurs both in the periplasmic space of the cell and in the extracellular medium (28,31) (SI Appendix, Fig. S1), thus leading to immediate benefits to the sensitive partner (19,32). The second strain is chloramphenicolresistant as a result of a plasmid carrying a gene encoding the chloramphenicol acetyltransferase type I enzyme, which deactivates the antibiotic chloramphenicol (33,34) (Fig.…”

Section: Resultsmentioning

confidence: 99%

Oscillatory dynamics in a bacterial cross-protection mutualism

Yurtsev

Conwill

Gore

2016

Proc. Natl. Acad. Sci. U.S.A.

135

127

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Cooperation between microbes can enable microbial communities to survive in harsh environments. Enzymatic deactivation of antibiotics, a common mechanism of antibiotic resistance in bacteria, is a cooperative behavior that can allow resistant cells to protect sensitive cells from antibiotics. Understanding how bacterial populations survive antibiotic exposure is important both clinically and ecologically, yet the implications of cooperative antibiotic deactivation on the population and evolutionary dynamics remain poorly understood, particularly in the presence of more than one antibiotic. Here, we show that two Escherichia coli strains can form an effective crossprotection mutualism, protecting each other in the presence of two antibiotics (ampicillin and chloramphenicol) so that the coculture can survive in antibiotic concentrations that inhibit growth of either strain alone. Moreover, we find that daily dilutions of the coculture lead to large oscillations in the relative abundance of the two strains, with the ratio of abundances varying by nearly four orders of magnitude over the course of the 3-day period of the oscillation. At modest antibiotic concentrations, the mutualistic behavior enables long-term survival of the oscillating populations; however, at higher antibiotic concentrations, the oscillations destabilize the population, eventually leading to collapse. The two strains form a successful cross-protection mutualism without a period of coevolution, suggesting that similar mutualisms may arise during antibiotic treatment and in natural environments such as the soil.

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Section: Resultsmentioning

confidence: 99%

Oscillatory dynamics in a bacterial cross-protection mutualism

Yurtsev

Conwill

Gore

2016

Proc. Natl. Acad. Sci. U.S.A.

135

127

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“…Moreover, similar twogene altruistic models have been created experimentally. 41 Such self-destructive cooperation can be seen as an extreme form of the division of labor between at least two phenotypes, in which one does not survive. For simplicity, here we will introduce the term "protophagy" as a synonym of bacterial cannibalism, autolysis, programmed cell death and other self-destructing patterns within bacterial colonies.…”

Section: Prokaryotes As Multicellular Organismsmentioning

confidence: 99%

“…Activation of the host immune response kills or restricts commensal bacteria and allows the pathogen to take advantage of reduced competition to invade host tissues. 44 This mechanism is employed by the enteropathogenic bacteria Salmonella enterica serovar Typhimurium, 41 and Clostridium difficile. 35,44 A similar protophagic strategy is also used by Streptococcus pneumoniae during lung colonization, 45 colicinogenic strains of E. coli, 46 Staphylococcus aureus, 47 and Pseudomonas aeruginosa.…”

Section: Prokaryotes As Multicellular Organismsmentioning

confidence: 99%

“…Acceptance of multicellular organization of bacteria suggests a path for the development of a new type of drug: instead of killing each individual bacterium (as antibiotics do) it may be possible to target the global properties of infection by the disorganization of bacterial regulatory systems. 41 Indeed, many infectious diseases are associated with bacterial biofilms-microbial accretions covered with a mucus shield that adhere to biological or nonbiological surfaces. Bacterial biofilms are implicated in a number of chronic infections including gastrointestinal and urinary tract infections, coronary heart disease, pulmonary diseases and others.…”

Section: Deltaproteobacteriamentioning

confidence: 99%

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A bird’s-eye view of autophagy

Starokadomskyy

Dmytruk

2013

Autophagy

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“…[9][10][11][12] Interactions between the host cell and synthetic circuits have been recognized since the observation that oscillations in the repressilator stopped upon entry of the cell into stationary phase. 10 More recently, interactions between the host cell and synthetic circuits have been used to uncover novel aspects of host physiology 13 and population-level altruism 14,15 and to guide design. These interactions are also an important consideration when porting circuits between organisms.…”

Section: Introductionmentioning

confidence: 99%

Towards a whole-cell modeling approach for synthetic biology

Purcell

Jain

Karr

et al. 2013

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Despite rapid advances over the last decade, synthetic biology lacks the predictive tools needed to enable rational design. Unlike established engineering disciplines, the engineering of synthetic gene circuits still relies heavily on experimental trial-and-error, a time-consuming and inefficient process that slows down the biological design cycle. This reliance on experimental tuning is because current modeling approaches are unable to make reliable predictions about the in vivo behavior of synthetic circuits. A major reason for this lack of predictability is that current models view circuits in isolation, ignoring the vast number of complex cellular processes that impinge on the dynamics of the synthetic circuit and vice versa. To address this problem, we present a modeling approach for the design of synthetic circuits in the context of cellular networks. Using the recently published whole-cell model of Mycoplasma genitalium, we examined the effect of adding genes into the host genome. We also investigated how codon usage correlates with gene expression and find agreement with existing experimental results. Finally, we successfully implemented a synthetic Goodwin oscillator in the whole-cell model. We provide an updated software framework for the whole-cell model that lays the foundation for the integration of wholecell models with synthetic gene circuit models. This software framework is made freely available to the community to enable future extensions. We envision that this approach will be critical to transforming the field of synthetic biology into a rational and predictive engineering discipline. Synthetic biology aims to engineer synthetic genetic circuits to endow cells and organisms with the ability to address new applications, including the production of drugs and industrial products, the design of new therapeutics for human diseases, and the study of basic biological processes. Despite significant advances in the field over the last decade, the synthetic biology design cycle has been hampered by the lack of predictive models. In contrast, more established engineering disciplines, such as civil and electrical engineering can rely on rational design by using models that can capture the behavior of real-world systems with a high degree of accuracy. This is currently not the case for synthetic biology, as models are generally only able to make qualitative predictions about system behavior. As a result, producing a functional engineered biological system usually requires extensive manual tuning by trial-and-error, a timeconsuming process that significantly slows the biological design process. The lack of predictive power in current models is partly because these models account for only the synthetic circuits themselves, but not other ongoing processes in the cells in which they reside. However, the complex dynamics of synthetic circuits may affect the host cell and vice versa, leading to divergence between current models and experimental results. Recently, a whole-cell model of a small and simple bacteri...

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Programming stress‐induced altruistic death in engineered bacteria

Abstract: Altruistic death is shown to confer a population level advantage in engineered E. coli. Cost-benefit trade-offs are analyzed and altruistic death is shown to account for the 'Eagle effect', whereby bacteria appear to grow better in high antibiotics concentrations.

Cited by 64 publications

References 60 publications

Oscillatory dynamics in a bacterial cross-protection mutualism

Oscillatory dynamics in a bacterial cross-protection mutualism

A bird’s-eye view of autophagy

Towards a whole-cell modeling approach for synthetic biology

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