Taffs Reed, Aston John E, Brileya Kristen, Jay Zackary, Klatt Christian G, McGlynn Shawn, Mallette Natasha, Montross Scott, Gerlach Robin, Inskeep William P, Ward David M, Carlson Ross P
Thermal Biology Institute, Montana State University, Bozeman, MT 59717, USA.
BMC Syst Biol. 2009 Dec 10;3:114. doi: 10.1186/1752-0509-3-114.
Three methods were developed for the application of stoichiometry-based network analysis approaches including elementary mode analysis to the study of mass and energy flows in microbial communities. Each has distinct advantages and disadvantages suitable for analyzing systems with different degrees of complexity and a priori knowledge. These approaches were tested and compared using data from the thermophilic, phototrophic mat communities from Octopus and Mushroom Springs in Yellowstone National Park (USA). The models were based on three distinct microbial guilds: oxygenic phototrophs, filamentous anoxygenic phototrophs, and sulfate-reducing bacteria. Two phases, day and night, were modeled to account for differences in the sources of mass and energy and the routes available for their exchange.
The in silico models were used to explore fundamental questions in ecology including the prediction of and explanation for measured relative abundances of primary producers in the mat, theoretical tradeoffs between overall productivity and the generation of toxic by-products, and the relative robustness of various guild interactions.
The three modeling approaches represent a flexible toolbox for creating cellular metabolic networks to study microbial communities on scales ranging from cells to ecosystems. A comparison of the three methods highlights considerations for selecting the one most appropriate for a given microbial system. For instance, communities represented only by metagenomic data can be modeled using the pooled method which analyzes a community's total metabolic potential without attempting to partition enzymes to different organisms. Systems with extensive a priori information on microbial guilds can be represented using the compartmentalized technique, employing distinct control volumes to separate guild-appropriate enzymes and metabolites. If the complexity of a compartmentalized network creates an unacceptable computational burden, the nested analysis approach permits greater scalability at the cost of more user intervention through multiple rounds of pathway analysis.
开发了三种方法，用于将基于化学计量学的网络分析方法（包括基本模式分析）应用于微生物群落中物质和能量流的研究。每种方法都有独特的优缺点，适用于分析具有不同复杂程度和先验知识的系统。使用来自美国黄石国家公园章鱼泉和蘑菇泉的嗜热光合垫群落的数据对这些方法进行了测试和比较。这些模型基于三种不同的微生物类群：产氧光合生物、丝状无氧光合生物和硫酸盐还原细菌。对白天和黑夜两个阶段进行了建模，以考虑物质和能量来源以及它们交换途径的差异。
计算机模拟模型用于探索生态学中的基本问题，包括预测和解释垫中初级生产者的实测相对丰度、总体生产力与有毒副产物生成之间的理论权衡，以及各种类群相互作用的相对稳健性。
这三种建模方法代表了一个灵活的工具箱，用于创建细胞代谢网络，以研究从细胞到生态系统等不同尺度的微生物群落。对这三种方法的比较突出了选择最适合给定微生物系统的方法时需要考虑的因素。例如，仅由宏基因组数据表示的群落可以使用汇总方法进行建模，该方法分析群落的总代谢潜力，而不尝试将酶分配到不同的生物体。具有关于微生物类群的广泛先验信息的系统可以使用分区技术来表示，采用不同的控制体积来分离适合类群的酶和代谢物。如果分区网络的复杂性带来了不可接受的计算负担，嵌套分析方法允许更大的可扩展性，但代价是需要通过多轮途径分析进行更多的用户干预。
