Principles of Information Storage in Small-Molecule Mixtures

Abstract

Molecular data systems have the potential to store information at dramatically higher density than existing electronic media. Some of the first experimental demonstrations of this idea have used DNA, but nature also uses a wide diversity of smaller non-polymeric molecules to preserve, process, and transmit information. In this paper, we present a general framework for quantifying chemical memory, which is not limited to polymers and extends to mixtures of molecules of all types. We show that the theoretical limit for molecular information is two orders of magnitude denser by mass than DNA, although this comes with different practical constraints on total capacity. We experimentally demonstrate kilobyte-scale information storage in mixtures of small synthetic molecules, and we consider some of the new perspectives that will be necessary to harness the information capacity available from the vast non-genomic chemical space.

Encoding Information in Synthetic Metabolomes

“…To date, demonstrations using DNA have reached about 214 petabytes per gram [32], although this is still orders of magnitude from theoretical limits [33]. An encoded metabolome written using a large small-molecule library could improve on this number [34], but our experiments highlight several limitations and potential benefits that warrant further discussion.…”

Multicomponent molecular memory

“…Writing data as chemical mixtures. The composition of a chemical sample can represent abstract information, whether the sample consists of a single compound selected from a defined chemical space 17 , a pool of sequence-controlled polymers 4,13 , or a mixture of unique compounds 15 . With small molecule libraries, the most direct way to encode information is to use the presence or absence of each library element in a sample to represent one bit of data 14,39 .…”

“…While macromolecules will continue to be important for information systems, complementary small-molecule approaches can offer a number of potential advantages 13,15 . They do not require polymerization or enzymatic steps; they can be designed to resist cellular digestion 16 and extreme environmental conditions; and they can be economical to produce.…”

Leveraging autocatalytic reactions for chemical domain image classification

“…The idea of chemical computing has a long history, inspired in part by the power, complexity, and energy efficiency of living systems 10,11 . Recent advances in molecular information storage [12][13][14][15][16][17] have brought these unconventional systems closer to reality and have renewed interest in chemical computing. Much of the research on molecular computing has focused on in vitro gene expression circuits 18,19 and DNA strand-displacement reactions [20][21][22] .…”