Understanding the limits to generalizability of experimental evolutionary models

被引:33
作者
Forde, Samantha E. [2 ]
Beardmore, Robert E. [3 ]
Gudelj, Ivana [3 ,4 ]
Arkin, Sinan S. [3 ]
Thompson, John N. [2 ]
Hurst, Laurence D. [1 ]
机构
[1] Univ Bath, Dept Biol & Biochem, Bath BA2 7AY, Avon, England
[2] Univ Calif Santa Cruz, Dept Ecol & Evolutionary Biol, Santa Cruz, CA 95064 USA
[3] Univ London Imperial Coll Sci Technol & Med, Dept Math, London SW7 2AZ, England
[4] Univ Bath, Dept Math Sci, Bath BA2 7AY, Avon, England
基金
英国自然环境研究理事会; 英国工程与自然科学研究理事会; 美国国家科学基金会;
关键词
D O I
10.1038/nature07152
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Given the difficulty of testing evolutionary and ecological theory in situ, in vitro model systems are attractive alternatives(1); however, can we appraise whether an experimental result is particular to the in vitro model, and, if so, characterize the systems likely to behave differently and understand why? Here we examine these issues using the relationship between phenotypic diversity and resource input in the T7 - Escherichia coli co- evolving system as a case history. We establish a mathematical model of this interaction, framed as one instance of a super- class of host - parasite co- evolutionary models, and show that it captures experimental results. By tuning this model, we then ask how diversity as a function of resource input could behave for alternative co- evolving partners ( for example, E. coli with lambda bacteriophages). In contrast to populations lacking bacteriophages, variation in diversity with differences in resources is always found for co- evolving populations, supporting the geographic mosaic theory of co- evolution(2). The form of this variation is not, however, universal. Details of infectivity are pivotal: in T7 - E. coli with a modified gene- for- gene interaction, diversity is low at high resource input, whereas, for matching- allele interactions, maximal diversity is found at high resource input. A combination of in vitro systems and appropriately configured mathematical models is an effective means to isolate results particular to the in vitro system, to characterize systems likely to behave differently and to understand the biology underpinning those alternatives.
引用
收藏
页码:220 / U44
页数:5
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