Yeoman Carl J, Chia Nicholas, Yildirim Suleyman, Miller Margret E Berg, Kent Angela, Stumpf Rebecca, Leigh Steven R, Nelson Karen E, White Bryan A, Wilson Brenda A
Institute of Genomic Biology, University of Illinois, Urbana, IL 61801, USA.
Department of Physics, University of Illinois, Urbana, IL 61801, USA.
Entropy (Basel). 2011 Mar;13(3):570-594. doi: 10.3390/e13030570. Epub 2011 Feb 25.
Second-generation sequencing technologies have granted us greater access to the diversity and genetics of microbial communities that naturally reside endo- and ecto-symbiotically with animal hosts. Substantial research has emerged describing the diversity and broader trends that exist within and between host species and their associated microbial ecosystems, yet the application of these data to our evolutionary understanding of microbiomes appears fragmented. For the most part biological perspectives are based on limited observations of oversimplified communities, while mathematical and/or computational modeling of these concepts often lack biological precedence. In recognition of this disconnect, both fields have attempted to incorporate ecological theories, although their applicability is currently a subject of debate because most ecological theories were developed based on observations of macro-organisms and their ecosystems. For the purposes of this review, we attempt to transcend the biological, ecological and computational realms, drawing on extensive literature, to forge a useful framework that can, at a minimum be built upon, but ideally will shape the hypotheses of each field as they move forward. In evaluating the top-down selection pressures that are exerted on a microbiome we find cause to warrant reconsideration of the much-maligned theory of multi-level selection and reason that complexity must be underscored by modularity.
第二代测序技术使我们能够更深入地了解与动物宿主内共生和外共生的微生物群落的多样性和遗传学。大量研究描述了宿主物种及其相关微生物生态系统内部和之间存在的多样性和更广泛的趋势,但这些数据在我们对微生物组进化理解中的应用似乎是零散的。在很大程度上,生物学观点基于对过度简化群落的有限观察,而这些概念的数学和/或计算建模往往缺乏生物学依据。认识到这种脱节,两个领域都试图纳入生态学理论,尽管其适用性目前存在争议,因为大多数生态学理论是基于对宏观生物及其生态系统的观察而发展起来的。出于本综述的目的,我们试图超越生物学、生态学和计算领域,借鉴大量文献,构建一个有用的框架,这个框架至少可以作为基础,但理想情况下,随着各领域的发展,它将塑造每个领域的假设。在评估施加于微生物组的自上而下的选择压力时,我们发现有理由重新考虑备受诟病的多层次选择理论,并认为复杂性必须通过模块化来强调。