Two technologies for single-molecule proteomics, three technologies for image analysis
Proteins are central players in biology. Being able to detect and quantify proteins in various circumstances such as in biochemically fractionated cellular lysates has proven to be highly informative about their characteristics, functions, and relationships with other proteins and cellular components in general. We currently lack high-throughput technologies for quantifying proteins that would resolve complex mixtures at single-molecule resolution across the large dynamic ranges found in cells. Here I present progress towards the two single-molecule proteomics technologies my colleagues and I have been developing: fluorosequencing and reverse translation. We computationally explore the feasibility and informational power of each technique, motivating further work. We demonstrate a working proof-of-concept for fluorosequencing, and significant progress towards a proof-of-concept for reverse translation. In addition to proteomics, I have contributed three computational technologies that can broadly be grouped as image analysis: quantitation of fluorescent nerve agent probes by chromaticity changes; recovery of molecular positions by DNA sequencing of immobilized, barcoded oligonucleotides; and automated, quantitative co-localization of protein puncta in cells.