Modeling and Experimental Validation of Large Scale Fluorescence Sensor Networks

Fluorescence microscopy is by far the dominant assay used to measure molecular scale interactions in a wide range of disciplines including biochemistry, biophysics, bioengineering, biomedical imaging and clinical diagnostics. However, the technique can probe only a small number of molecular interactions with previous attempts at detecting more than 11 fluorophores simultaneously resulting in barcodes that are too big for in vivo analysis, expensive and involve time-consuming detection schemes. Here, we create DNA self-assembled Resonance Energy Transfer networks that generate a unique time-resolved fluorescence signature when probed by a series of light pulses. An experimentally informed theoretical model predicts that networks containing up to 125 fluorophores may be distinguished from other extremely similar networks. Through the largest experimental survey of RET networks, we demonstrate that minor changes made to the RET network result in a unique, experimentally resolvable optical signature. We show that we can generate over 300 unique signatures using only 3 fluorophores. Furthermore, from 1296 time-resolved fluorescence signatures, we show that the optical signatures are reproducible 99.48% of the time. The ability to simultaneously detect multiple biological entities, the high spatial information density and the high repeatability of the synthetic RET networks will potentially find use in many biological and clinical applications.