Multiscale analysis of autotroph-heterotroph interactions in a high-temperature microbial community.
Multiscale analysis of autotroph-heterotroph interactions in a high-temperature microbial community.
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DOI：
10.1371/journal.pcbi.1006431
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发表时间：
2018-09
影响因子：
4.3
通讯作者：
Carlson RP
中科院分区：
文献类型：
--
作者：
Hunt KA;Jennings RM;Inskeep WP;Carlson RP
微生物群落成员之间的相互作用可以导致紧急特性，例如提高生产力，稳定性和健壮性。黄石国家公园酸性（pH 2-4）、高温（bb0 - 65°C）泉水中的氧化铁垫含有相对简单的微生物群落，并具有良好的地球化学特征。因此，这些群落是研究个体群体代谢活动和关键微生物相互作用的优秀模型系统。当前研究的主要目标是将原位收集的数据与跨过程尺度的计算机计算相结合，包括酶活性、细胞代谢、群落相互作用和生态系统生物地球化学，以及预测和量化自养-异养相互作用的功能极限。利用元基因组和转录组学数据重建了铁（III）氧化物席群落中重要的自养生物（Metallosphaera yellowstonensis）和异养生物（Geoarchaeum sp. OSPB）的碳和能量代谢。代谢模型的标准通量模式和混合基本通量模式以及通量平衡分析分别预测了细胞水平和群落水平对模拟环境胁迫的代谢适应。原位地球化学分析，包括氧深度剖面、Fe(III)-氧化物沉积速率、稳定碳同位素和基质生物量浓度，与细胞模型相结合，探索对群落结构-功能重要的自养-异养相互作用。将代谢模型与原位测量相结合，包括自养生物与异养生物的相对种群丰度，表明Fe(III)-oxide mat群落以其最大总群落增长率（即自养生物和异养生物增长率之和）运行，而不是像最功率原理预测的那样以净群落增长率（即群落总增长率减去异养生物消耗的自养生物）运行。多尺度数据与生态学理论的整合为预测自养-异养相互作用和群落水平的细胞组织提供了基础。与孤立的微生物群落相比，微生物群落往往表现出突发性的特性，如提高的生产力、稳定性和健壮性。然而，由于在很大程度上不同的观测尺度上收集的基因组和地球化学数据集的解释和整合的复杂性，确定这些涌现特性的支配原则可能是难以捉摸的。在这里，我们使用多尺度、宏基因组支持的Fe（II）氧化群落模型来提取有关生物量生产力限制、相对种群丰度、总生物量浓度和电子受体吸收率的信息。本文使用的系统方法广泛适用于具有适度活性和宏基因组数据的任何微生物群落，并提供了一种机制来表征包括未培养生物在内的群落中的相互作用基序。
Interactions among microbial community members can lead to emergent properties, such as enhanced productivity, stability, and robustness. Iron-oxide mats in acidic (pH 2–4), high-temperature (> 65 °C) springs of Yellowstone National Park contain relatively simple microbial communities and are well-characterized geochemically. Consequently, these communities are excellent model systems for studying the metabolic activity of individual populations and key microbial interactions. The primary goals of the current study were to integrate data collected in situ with in silico calculations across process-scales encompassing enzymatic activity, cellular metabolism, community interactions, and ecosystem biogeochemistry, as well as to predict and quantify the functional limits of autotroph-heterotroph interactions. Metagenomic and transcriptomic data were used to reconstruct carbon and energy metabolisms of an important autotroph (Metallosphaera yellowstonensis) and heterotroph (Geoarchaeum sp. OSPB) from the studied Fe(III)-oxide mat communities. Standard and hybrid elementary flux mode and flux balance analyses of metabolic models predicted cellular- and community-level metabolic acclimations to simulated environmental stresses, respectively. In situ geochemical analyses, including oxygen depth-profiles, Fe(III)-oxide deposition rates, stable carbon isotopes and mat biomass concentrations, were combined with cellular models to explore autotroph-heterotroph interactions important to community structure-function. Integration of metabolic modeling with in situ measurements, including the relative population abundance of autotrophs to heterotrophs, demonstrated that Fe(III)-oxide mat communities operate at their maximum total community growth rate (i.e. sum of autotroph and heterotroph growth rates), as opposed to net community growth rate (i.e. total community growth rate subtracting autotroph consumed by heterotroph), as predicted from the maximum power principle. Integration of multiscale data with ecological theory provides a basis for predicting autotroph-heterotroph interactions and community-level cellular organization. Microbial communities often display emergent properties, such as enhanced productivity, stability, and robustness, compared to their component populations in isolation. However, determining the governing principles of these emergent properties can be elusive due to the complexities of interpreting and integrating genomic and geochemical data sets collected at largely different observational scales. Here, we use multiscale, metagenome-enabled modeling of an Fe(II)-oxidizing community to extract information regarding biomass productivity limitations, relative population abundance, total biomass concentration, and electron acceptor uptake rates. The systematic approach used herein is broadly applicable to any microbial community with modest activity and metagenomic data as well as provides a mechanism to characterize interaction motifs in communities that include uncultivated organisms.
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影响因子：
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