Abstract
As synthetic biology advances, labeling of genes or organisms, like other high-value products, will become important not only to pinpoint their identity, origin, or spread, but also for intellectual property, classification, bio-security or legal reasons. Ideally information should be inseparably interlaced into expressed genes. We describe a method for embedding messages within open reading ...
Abstract
As synthetic biology advances, labeling of genes or organisms, like other high-value products, will become important not only to pinpoint their identity, origin, or spread, but also for intellectual property, classification, bio-security or legal reasons. Ideally information should be inseparably interlaced into expressed genes. We describe a method for embedding messages within open reading frames of synthetic genes by adapting steganographic algorithms typically used for watermarking digital media files. Text messages are first translated into a binary string, and then represented in the reading frame by synonymous codon choice. To aim for good expression of the labeled gene in its host as well as retain a high degree of codon assignment flexibility for gene optimization, codon usage tables of the target organism are taken into account. Preferably amino acids with 4 or 6 synonymous codons are used to comprise binary digits. Several different messages were embedded into open reading frames of T7 RNA polymerase, GFP, human EMG1 and HIV gag, variously optimized for bacterial, yeast, mammalian or plant expression, without affecting their protein expression or function. We also introduced Vigenere polyalphabetic substitution to cipher text messages, and developed an identifier as a key to deciphering codon usage ranking stored for a specific organism within a sequence of 35 nucleotides.
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