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噬菌体策略促进了细菌在环境变异性下的共存。

Phage strategies facilitate bacterial coexistence under environmental variability.

作者信息

Voigt Esther, Rall Björn C, Chatzinotas Antonis, Brose Ulrich, Rosenbaum Benjamin

机构信息

German Centre for Integrative Biodiversity Research (iDiv), Leipzig, Germany.

Institute of Biodiversity, Friedrich Schiller University Jena, Jena, Germany.

出版信息

PeerJ. 2021 Nov 4;9:e12194. doi: 10.7717/peerj.12194. eCollection 2021.

DOI:10.7717/peerj.12194
PMID:34760346
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8572521/
Abstract

Bacterial communities are often exposed to temporal variations in resource availability, which exceed bacterial generation times and thereby affect bacterial coexistence. Bacterial population dynamics are also shaped by bacteriophages, which are a main cause of bacterial mortality. Several strategies are proposed in the literature to describe infections by phages, such as "Killing the Winner", "Piggyback the loser" (PtL) or "Piggyback the Winner" (PtW). The two temperate phage strategies PtL and PtW are defined by a change from lytic to lysogenic infection when the host density changes, from high to low or from low to high, respectively. To date, the occurrence of different phage strategies and their response to environmental variability is poorly understood. In our study, we developed a microbial trophic network model using ordinary differential equations (ODEs) and performed '' experiments. To model the switch from the lysogenic to the lytic cycle, we modified the lysis rate of infected bacteria and their growth was turned on or off using a density-dependent switching point. We addressed whether and how the different phage strategies facilitate bacteria coexistence competing for limiting resources. We also studied the impact of a fluctuating resource inflow to evaluate the response of the different phage strategies to environmental variability. Our results show that the viral shunt (. nutrient release after bacterial lysis) leads to an enrichment of the system. This enrichment enables bacterial coexistence at lower resource concentrations. We were able to show that an established, purely lytic model leads to stable bacterial coexistence despite fluctuating resources. Both temperate phage models differ in their coexistence patterns. The model of PtW yields stable bacterial coexistence at a limited range of resource supply and is most sensitive to resource fluctuations. Interestingly, the purely lytic phage strategy and PtW both result in stable bacteria coexistence at oligotrophic conditions. The PtL model facilitates stable bacterial coexistence over a large range of stable and fluctuating resource inflow. An increase in bacterial growth rate results in a higher resilience to resource variability for the PtL and the lytic infection model. We propose that both temperate phage strategies represent different mechanisms of phages coping with environmental variability. Our study demonstrates how phage strategies can maintain bacterial coexistence in constant and fluctuating environments.

摘要

细菌群落经常面临资源可用性的时间变化,这种变化超过了细菌的世代时间,从而影响细菌的共存。细菌种群动态也受到噬菌体的影响,噬菌体是导致细菌死亡的主要原因。文献中提出了几种描述噬菌体感染的策略,如“杀死胜者”“搭失败者的便车”(PtL)或“搭胜者的便车”(PtW)。两种温和噬菌体策略PtL和PtW的定义是,当宿主密度分别从高到低或从低到高变化时,感染从裂解性感染转变为溶原性感染。迄今为止,不同噬菌体策略的出现及其对环境变异性的反应仍知之甚少。在我们的研究中,我们使用常微分方程(ODEs)开发了一个微生物营养网络模型并进行了实验。为了模拟从溶原性周期到裂解性周期的转变,我们修改了受感染细菌的裂解率,并使用密度依赖的切换点来开启或关闭它们的生长。我们探讨了不同的噬菌体策略是否以及如何促进细菌在争夺有限资源时的共存。我们还研究了波动的资源流入的影响,以评估不同噬菌体策略对环境变异性的反应。我们的结果表明,病毒分流(细菌裂解后的营养物质释放)导致系统富集。这种富集使细菌能够在较低的资源浓度下共存。我们能够证明,一个既定的、纯粹的裂解模型尽管资源波动,但仍能导致稳定的细菌共存。两种温和噬菌体模型的共存模式不同。PtW模型在有限的资源供应范围内产生稳定的细菌共存,并且对资源波动最敏感。有趣的是,纯粹的裂解噬菌体策略和PtW在贫营养条件下都能导致稳定的细菌共存。PtL模型在大范围的稳定和波动的资源流入情况下促进稳定的细菌共存。细菌生长速率的增加导致PtL和裂解性感染模型对资源变异性具有更高的恢复力。我们提出,两种温和噬菌体策略代表了噬菌体应对环境变异性的不同机制。我们的研究证明了噬菌体策略如何在恒定和波动的环境中维持细菌的共存。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/c0db88b96485/peerj-09-12194-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/98e91b5147c9/peerj-09-12194-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/38dabaec4771/peerj-09-12194-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/c0db88b96485/peerj-09-12194-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/98e91b5147c9/peerj-09-12194-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/cfd1bea17bda/peerj-09-12194-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/fd1c8b9fcfeb/peerj-09-12194-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/17d1a3f7b042/peerj-09-12194-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7dd/8572521/c0db88b96485/peerj-09-12194-g006.jpg

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