Fundamental computer science concepts have inspired novel information-processing molecular systems in test tubes^{1,2,3,4,5,6,7,8,9,10,11,12,13} and genetically encoded circuits in live cells^{14,15,16,17,18,19,20,21}. Recent research has shown that digital information storage in DNA, implemented using deep sequencing and conventional software, can approach the maximum Shannon information capacity²² of two bits per nucleotide²³. In nature, DNA is used to store genetic programs, but the information content of the encoding rarely approaches this maximum²⁴. We hypothesize that the biological function of a genetic program can be preserved while reducing the length of its DNA encoding and increasing the information content per nucleotide. Here we support this hypothesis by describing an experimental procedure for compressing a genetic program and its subsequent autonomous decompression and execution in human cells. As a test-bed we choose an RNAi cell classifier circuit²⁵ that comprises redundant DNA sequences and is therefore amenable for compression, as are many other complex gene circuits^{15,18,26,27,28}. In one example, we implement a compressed encoding of a ten-gene four-input AND gate circuit using only four genetic constructs. The compression principles applied to gene circuits can enable fitting complex genetic programs into DNA delivery vehicles with limited cargo capacity, and storing compressed and biologically inert programs in vivo for on-demand activation.

中文翻译：

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遗传程序可以在活细胞中进行压缩和自主解压缩

计算机科学的基本概念激发了试管^{1,2,3,4,5,6,7,8,9,10,11,12,13中的}新型信息处理分子系统以及活细胞^14,15中的遗传编码电路^{，16,17,18,19,20,21}。最近的研究已经表明，数字信息存储在DNA，使用深度测序和常规软件中实现，可以接近香农最大信息容量²²每核苷酸二者的比特²³。在自然界中，DNA被用于存储遗传程序，但是编码的信息内容很少达到这个最大值²⁴。我们假设可以保留遗传程序的生物学功能，同时减少其DNA编码的长度并增加每个核苷酸的信息含量。在这里，我们通过描述一种压缩遗传程序的实验程序及其在人类细胞中的自动解压缩和执行，来支持这一假设。作为测试平台，我们选择了一个RNAi细胞分类器回路²⁵，该回路包括冗余的DNA序列，因此适合压缩，就像许多其他复杂基因回路一样^{15,18,26,27,28}。在一个示例中，我们仅使用四个遗传结构实现了十基因四输入与门电路的压缩编码。应用于基因回路的压缩原理可以使复杂的遗传程序适合具有有限货物容量的DNA传递载体，并可以在体内存储经压缩的生物惰性程序以进行按需激活。