Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York, USA
Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York, USA.
mBio. 2018 Jan 9;9(1):e01453-17. doi: 10.1128/mBio.01453-17.
A priority in gut microbiome research is to develop methods to investigate ecological processes shaping microbial populations in the host from readily accessible data, such as fecal samples. Here, we demonstrate that these processes can be inferred from the proportion of ingested microorganisms that is egested and their egestion time distribution, by using general mathematical models that link within-host processes to statistics from fecal time series. We apply this framework to and its gut bacterium Specifically, we investigate changes in their interactions following ingestion of a food bolus containing bacteria in a set of treatments varying the following key parameters: the density of exogenous bacteria ingested by the flies (low/high) and the association status of the host (axenic or monoassociated with ). At 5 h post-ingestion, ~35% of the intact bacterial cells have transited through the gut with the food bolus and ~10% are retained in a viable and culturable state, leaving ~55% that have likely been lysed in the gut. Our models imply that lysis and retention occur over a short spatial range within the gut when the bacteria are ingested from a low density, but more broadly in the host gut when ingested from a high density, by both gnotobiotic and axenic hosts. Our study illustrates how time series data complement the analysis of static abundance patterns to infer ecological processes as bacteria traverse the host. Our approach can be extended to investigate how different bacterial species interact within the host to understand the processes shaping microbial community assembly. A major challenge to our understanding of the gut microbiome in animals is that it is profoundly difficult to investigate the fate of ingested microbial cells as they travel through the gut. Here, we created mathematical tools to analyze microbial dynamics in the gut from the temporal pattern of their abundance in fecal samples, i.e., without direct observation of the dynamics, and validated them with fruit flies. Our analyses revealed that over 5 h after ingestion, most bacteria have likely died in the host or have been egested as intact cells, while some living cells have been retained in the host. Bacterial lysis or retention occurred across a larger area of the gut when flies ingest bacteria from high densities than when flies ingest bacteria from low densities. Our mathematical tools can be applied to other systems, including the dynamics of gut microbial populations and communities in humans.
肠道微生物组研究的一个重点是开发方法,以便从粪便等易于获取的样本中研究宿主中塑造微生物群体的生态过程。在这里,我们通过使用将宿主内过程与粪便时间序列统计数据联系起来的一般数学模型,证明可以从被排出的摄入微生物的比例及其排出时间分布推断出这些过程。我们将该框架应用于 和其肠道细菌 。具体来说,我们研究了在摄入含有一组处理中细菌的食物团块后,它们之间相互作用的变化,这些处理改变了以下关键参数:被苍蝇摄入的外生细菌的密度(低/高)和宿主的关联状态(无菌或单联)与 。在摄入后 5 小时,约 35%的完整细菌细胞随食物团块穿过肠道,约 10%以存活和可培养的状态保留,约 55%的细菌可能在肠道中被裂解。我们的模型表明,当细菌从低密度摄入时,裂解和保留发生在肠道内的短空间范围内,但当从高密度摄入时,无论是无菌还是单联宿主,裂解和保留发生在更广泛的宿主肠道内。我们的研究说明了时间序列数据如何补充静态丰度模式的分析,以推断细菌穿过宿主时的生态过程。我们的方法可以扩展到研究不同细菌物种在宿主内如何相互作用,以了解塑造微生物群落组装的过程。了解动物肠道微生物组的一个主要挑战是,深入研究摄入的微生物细胞在肠道中移动的命运非常困难。在这里,我们创建了数学工具,以便从粪便样本中微生物丰度的时间模式来分析肠道中的微生物动态,即,无需直接观察动态,并用 果蝇对其进行了验证。我们的分析表明,在摄入后 5 小时内,大多数细菌可能已经在宿主中死亡或作为完整细胞排出,而一些存活细胞则被宿主保留。当苍蝇从高浓度摄入细菌时,细菌裂解或保留发生在肠道的更大区域,而当苍蝇从低浓度摄入细菌时则发生在肠道的较小区域。我们的数学工具可以应用于其他系统,包括人类肠道微生物种群和群落的动态。