Encoding information in synthetic metabolomes

Biomolecular information systems offer numerous potential advantages over conventional semiconductor technologies. Downstream from DNA, the metabolome is an information-rich molecular system with diverse chemical dimensions which could be harnessed for information storage and processing. As a proof of principle of postgenomic data storage, here we demonstrate a workflow for representing abstract data in synthetic metabolomes. Our approach leverages robotic liquid handling for writing digital information into chemical mixtures, and mass spectrometry for extracting the data. We present several kilobyte-scale image datasets stored in synthetic metabolomes, which are decoded with accuracy exceeding 98-99% using multi-mass logistic regression. Cumulatively, >100,000 bits of digital image data was written into metabolomes. These early demonstrations provide insight into the benefits and limitations of postgenomic chemical information systems.