Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
ShengShee Thor, Joseph R. Peterson, Z. Luthey-Schulten
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引用次数: 21

Abstract

Decades of biochemical, bioinformatic, and sequencing data are currently being systematically compiled into genome-scale metabolic reconstructions (GEMs). Such reconstructions are knowledge-bases useful for engineering, modeling, and comparative analysis. Here we review the fifteen GEMs of archaeal species that have been constructed to date. They represent primarily members of the Euryarchaeota with three-quarters comprising representative of methanogens. Unlike other reviews on GEMs, we specially focus on archaea. We briefly review the GEM construction process and the genealogy of the archaeal models. The major insights gained during the construction of these models are then reviewed with specific focus on novel metabolic pathway predictions and growth characteristics. Metabolic pathway usage is discussed in the context of the composition of each organism's biomass and their specific energy and growth requirements. We show how the metabolic models can be used to study the evolution of metabolism in archaea. Conservation of particular metabolic pathways can be studied by comparing reactions using the genes associated with their enzymes. This demonstrates the utility of GEMs to evolutionary studies, far beyond their original purpose of metabolic modeling; however, much needs to be done before archaeal models are as extensively complete as those for bacteria.
古菌基因组规模的代谢建模使我们得以深入了解代谢功能的多样性
几十年的生物化学、生物信息学和测序数据目前正在系统地汇编成基因组规模的代谢重建(GEM)。这种重建是对工程、建模和比较分析有用的知识库。在这里,我们回顾了迄今为止已经构建的15个古菌物种的GEM。它们主要代表Euryarchaeota的成员,其中四分之三代表产甲烷菌。与其他关于GEM的评论不同,我们特别关注古菌。我们简要回顾了GEM的构建过程和古模型的谱系。然后回顾了在构建这些模型过程中获得的主要见解,特别关注新的代谢途径预测和生长特征。代谢途径的使用是在每个生物体的生物量组成及其特定能量和生长需求的背景下讨论的。我们展示了如何使用代谢模型来研究古菌代谢的进化。特定代谢途径的保护可以通过使用与其酶相关的基因比较反应来研究。这证明了GEM在进化研究中的效用,远远超出了它们最初的代谢建模目的;然而,在古菌模型像细菌模型一样广泛完整之前,还有很多工作要做。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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