Kurkjian Helen M, Akbari M Javad, Momeni Babak
Department of Biology, Boston College, Chestnut Hill, Massachusetts, United States of America.
PLoS Comput Biol. 2021 Jan 22;17(1):e1008643. doi: 10.1371/journal.pcbi.1008643. eCollection 2021 Jan.
In human microbiota, the prevention or promotion of invasions can be crucial to human health. Invasion outcomes, in turn, are impacted by the composition of resident communities and interactions of resident members with the invader. Here we study how interactions influence invasion outcomes in microbial communities, when interactions are primarily mediated by chemicals that are released into or consumed from the environment. We use a previously developed dynamic model which explicitly includes species abundances and the concentrations of chemicals that mediate species interaction. Using this model, we assessed how species interactions impact invasion by simulating a new species being introduced into an existing resident community. We classified invasion outcomes as resistance, augmentation, displacement, or disruption depending on whether the richness of the resident community was maintained or decreased and whether the invader was maintained in the community or went extinct. We found that as the number of invaders introduced into the resident community increased, disruption rather than augmentation became more prevalent. With more facilitation of the invader by the resident community, resistance outcomes were replaced by displacement and augmentation. By contrast, with more facilitation among residents, displacement outcomes shifted to resistance. When facilitation of the resident community by the invader was eliminated, the majority of augmentation outcomes turned into displacement, while when inhibition of residents by invaders was eliminated, invasion outcomes were largely unaffected. Our results suggest that a better understanding of interactions within resident communities and between residents and invaders is crucial to predicting the success of invasions into microbial communities.
在人类微生物群中,入侵的预防或促进对人类健康可能至关重要。反过来,入侵结果又受到常驻群落组成以及常驻成员与入侵者相互作用的影响。在这里,我们研究当相互作用主要由释放到环境中或从环境中消耗的化学物质介导时,相互作用如何影响微生物群落中的入侵结果。我们使用一个先前开发的动态模型,该模型明确包含物种丰度以及介导物种相互作用的化学物质浓度。使用这个模型,我们通过模拟将一个新物种引入现有的常驻群落来评估物种相互作用如何影响入侵。我们根据常驻群落的丰富度是保持还是降低以及入侵者在群落中是保持还是灭绝,将入侵结果分类为抗性、增强、取代或破坏。我们发现,随着引入常驻群落的入侵者数量增加,破坏而非增强变得更加普遍。随着常驻群落对入侵者的促进作用增加,抗性结果被取代和增强所取代。相比之下,随着常驻成员之间的促进作用增加,取代结果转变为抗性。当入侵者对常驻群落的促进作用被消除时,大多数增强结果转变为取代,而当入侵者对常驻成员的抑制作用被消除时,入侵结果基本不受影响。我们的结果表明,更好地理解常驻群落内部以及常驻成员与入侵者之间的相互作用对于预测微生物群落入侵的成功至关重要。