从时间序列推断微生物群落中的资源竞争
Inferring resource competition in microbial communities from time series
AI总结：
本研究利用群落丰度动态测量，证明考虑时间延迟效应的谱方法（如CPSD和相干性）优于简单相关性，能有效推断微生物群落内资源竞争结构。
摘要：
资源竞争是微生物群落的一个决定性特征。在从土壤到宿主相关群落的许多情境中，高度多样化的微生物被组织成具有相似资源偏好的代谢组或功能群。导致这些功能群形成的单个类群的资源偏好，对于理解群落中资源通量及系统多样性结构至关重要。然而，推断群落内单个类群的代谢能力及其与其他类群的竞争极具挑战且尚未解决。在此，我们通过利用群落丰度的动态测量来填补这一知识空白。我们表明，简单的相关性在预测资源竞争时往往具有误导性。我们表明，考虑时间延迟效应的谱方法，如交叉功率谱密度（CPSD）和相干性，是推断群落中资源竞争结构的更优指标。我们首先在由资源可用性随时间变化的消费者-资源模型生成的合成数据上证明了这一事实，其中类群被组织成具有相似资源偏好的组或功能群。通过将谱方法应用于海洋浮游生物时间序列数据，我们证明这些方法能够检测具有相似基因组序列的物种间的相互作用结构。我们的结果表明，分析跨多个时间尺度的时间数据可以揭示群落内资源竞争的潜在结构。
英文摘要：
The competition for resources is a defining feature of microbial communities. In many contexts, from soils to host-associated communities, highly diverse microbes are organized into metabolic groups or guilds with similar resource preferences. The resource preferences of individual taxa that give rise to these guilds are critical for understanding fluxes of resources through the community and the structure of diversity in the system. However, inferring the metabolic capabilities of individual taxa, and their competition with other taxa, within a community is challenging and unresolved. Here we address this gap in knowledge by leveraging dynamic measurements of abundances in communities. We show that simple correlations are often misleading in predicting resource competition. We show that spectral methods such as the cross-power spectral density (CPSD) and coherence that account for time-delayed effects are superior metrics for inferring the structure of resource competition in communities. We first demonstrate this fact on synthetic data generated from consumer-resource models with time-dependent resource availability, where taxa are organized into groups or guilds with similar resource preferences. By applying spectral methods to oceanic plankton time-series data, we demonstrate that these methods detect interaction structures among species with similar genomic sequences. Our results indicate that analyzing temporal data across multiple timescales can reveal the underlying structure of resource competition within communities.
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