与最小细菌基因组相似的手写人工基因组

D. Axe, P. Lu, Stephanie Flatau
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引用次数: 4

摘要

在解释生命及其组成部分的功能多样性的尺度上解释进化创新的困难一直困扰着进化理论。实验正在揭示这一点,但这个问题的复杂性也需要其他方法。特别是,捕捉简单生命的某些方面的计算模型,可能为关于进化如何起作用或不能起作用的想法提供有用的证明依据。我们面临的挑战是找到一个足够简单的模型“世界”,以便快速模拟,但又不能简单到失去了真正感兴趣的东西。应对这一挑战的最佳方式是建立一个模型世界,在这个模型世界中,现实世界的问题可以得到解决,否则,与真正创新的联系就会受到质疑。Stylus是先前描述的一种模型,它基于现实世界中最强大的解决问题的工具之一:书面语言,从而满足了这一标准。Stylus使用遗传密码将类似基因的序列翻译成矢量序列,然后根据简单的几何规则进行处理,形成类似笔画的图案。这些翻译产物被称为载体蛋白,除非它们能形成易读的汉字,否则它们是没有功能的,在这种情况下,它们的真正功能是书写。这种人工遗传因果关系与真实语言世界的耦合使得进化实验成为可能,在这种环境下,创新可以具有丰富的多样性和深度的因果复杂性,至少暗示了解释细菌蛋白质组复杂性所需要的东西。为了实现这种可能性,我们在这里提供一个完整的针笔基因组作为实验起点。为了构建它,我们首先用中文对Stylus算法进行了简明的描述。将其作为蛋白质组规范,我们构建了Stylus基因来对其进行编码。通过这种方式,触针蛋白组指定了其编码基因组的解码方式,使其类似于细菌的基因表达机制。完整的70,701碱基Stylus基因组编码223种载体蛋白,具有112种不同的载体结构域类型,使其比最小的细菌基因组更紧凑,但具有相当的蛋白质组学复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Stylus-Generated Artificial Genome with Analogy to Minimal Bacterial Genomes
The difficulty of explaining evolutionary innovation on a scale that would account for the functional diversity of life and its components continues to dog evolutionary theory. Experiments are shedding light on this, but the complexity of the subject calls for other approaches as well. In particular, computational models that capture some aspects of simple life may provide useful proving grounds for ideas about how evolution can or cannot work. The challenge is to find a model ‘world’ simple enough for rapid simulation but not so simple that the real thing of interest has been lost. That challenge is best met with a model world in which real-world problems can be solved, as otherwise the connection with real innovation would be in doubt. Stylus is a previously described model that meets this criterion by being based on one of the most powerful real-world problem-solving tools: written language. Stylus uses a genetic code to translate gene-like sequences into vector sequences that, when processed according to simple geometric rules, form patterns resembling penned strokes. These translation products, called vector proteins, are functionless unless they form legible Chinese characters, in which case they serve the real function of writing. This coupling of artificial genetic causation to the real world of language makes evolutionary experimentation possible in a context where innovation can have a richness of variety and a depth of causal complexity that at least hints at what is needed to explain the complexity of bacterial proteomes. In order for this possibility to be realized, we here provide a complete Stylus genome as an experimental starting point. To construct it we first wrote a concise description of the Stylus algorithm in Chinese. Using that as a proteome specification, we then constructed the Stylus genes to encode it. In this way the Stylus proteome specifies how its encoding genome is decoded, making it analogous to the gene-expression machinery of bacteria. The complete 70,701 base Stylus genome encodes 223 vector proteins with 112 distinct vector domain types, making it more compact than the smallest bacterial genome but with comparable proteomic complexity for its size.
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