Abstract
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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