Institute of Microbiology and Infection & Centre for Computational Biology & School of Biosciences, University of Birminghamgrid.6572.6, Edgbaston, Birmingham, United Kingdom.
Appl Environ Microbiol. 2022 Jan 11;88(1):e0108221. doi: 10.1128/AEM.01082-21. Epub 2021 Oct 20.
With increasing antimicrobial resistance, alternatives for treating infections or removing resistant bacteria are urgently needed, such as the bacterial predator Bdellovibrio bacteriovorus or bacteriophage. Therefore, we need to better understand microbial predator-prey dynamics. We developed mass-action mathematical models of predation for chemostats, which capture the low substrate concentration and slow growth typical for intended application areas of the predators such as wastewater treatment, aquaculture, or the gut. Our model predicted that predator survival required a minimal prey cell size, explaining why is much smaller than its prey. A predator considered to be "too good" (attack rate too high, mortality too low) overexploited its prey, leading to extinction (tragedy of the commons). Surprisingly, a predator taking longer to produce more offspring outcompeted a predator producing fewer offspring more rapidly (rate versus yield trade-off). Predation was only efficient in a narrow region around optimal parameters. Moreover, extreme oscillations under a wide range of conditions led to severe bottlenecks. These could be avoided when two prey species became available in alternating seasons. A bacteriophage outcompeted due to its higher burst size and faster life cycle. Together, results suggest that would struggle to survive on a single prey, explaining why it must be a generalist predator and suggesting it is better suited than phage to environments with multiple prey. The discovery of antibiotics led to a dramatic drop in deaths due to infectious disease. Increasing levels of antimicrobial resistance, however, threaten to reverse this progress. There is thus a need for alternatives, such as therapies based on phage and predatory bacteria that kill bacteria regardless of whether they are pathogens or resistant to antibiotics. To best exploit them, we need to better understand what determines their effectiveness. By using a mathematical model to study bacterial predation in realistic slow growth conditions, we found that the generalist predator is most effective within a narrow range of conditions for each prey. For example, a minimum prey cell size is required, and the predator should not be "too good," as this would result in overexploitation risking extinction. Together these findings give insights into the ecology of microbial predation and help explain why needs to be a generalist predator.
随着抗菌药物耐药性的增加,我们迫切需要替代治疗感染或去除耐药菌的方法,例如细菌捕食者蛭弧菌或噬菌体。因此,我们需要更好地了解微生物捕食者-猎物的动态。我们为恒化器开发了捕食的质量作用数学模型,这些模型捕获了捕食者应用领域(如废水处理、水产养殖或肠道)中常见的低基质浓度和缓慢生长的特征。我们的模型预测,捕食者的生存需要一个最小的猎物细胞大小,这解释了为什么 比它的猎物小得多。一种被认为“太好了”(攻击率太高,死亡率太低)的捕食者会过度利用其猎物,导致灭绝(公地悲剧)。令人惊讶的是,一种需要更长时间才能产生更多后代的捕食者比快速产生更少后代的捕食者更有竞争力(速度与产量的权衡)。只有在最佳参数的狭窄范围内,捕食才是有效的。此外,在广泛的条件下,极端的振荡会导致严重的瓶颈。当两种猎物物种在交替季节出现时,可以避免这种情况。由于更高的爆发大小和更快的生命周期,噬菌体比 更具竞争力。总的来说,这些结果表明, 很难在单一猎物上生存,这解释了为什么它必须是一种泛食性捕食者,并表明它比噬菌体更适合有多种猎物的环境。抗生素的发现导致因传染病导致的死亡人数大幅下降。然而,抗菌药物耐药性的增加威胁到这一进展的逆转。因此,需要替代品,例如基于噬菌体和捕食性细菌的疗法,这些疗法可以杀死细菌,而不管它们是否是病原体或对抗生素耐药。为了最好地利用它们,我们需要更好地了解是什么决定了它们的有效性。通过使用数学模型在现实的缓慢生长条件下研究细菌捕食,我们发现,在每种猎物的狭窄条件范围内,泛食性捕食者 最为有效。例如,需要最小的猎物细胞大小,并且捕食者不应该“太好了”,因为这会导致过度利用,从而有灭绝的风险。这些发现共同揭示了微生物捕食的生态学,并有助于解释为什么 需要成为一种泛食性捕食者。