Protein-DNA computation by stochastic assembly cascade

TL;DR

This paper models RecA protein assembly on DNA as a stochastic finite-state machine capable of discriminating sequences and performing computational operations through a cascade of nucleation and disassembly events.

Contribution

It introduces a novel stochastic model of RecA-DNA interaction that functions as a computational machine with sequence discrimination capabilities.

Findings

RecA assembly acts as a stochastic finite-state machine.

The process can discriminate single-base differences.

The mechanism resembles a multistage kinetic proofreading process.

Abstract

The assembly of RecA on single-stranded DNA is measured and interpreted as a stochastic finite-state machine that is able to discriminate fine differences between sequences, a basic computational operation. RecA filaments efficiently scan DNA sequence through a cascade of random nucleation and disassembly events that is mechanistically similar to the dynamic instability of microtubules. This iterative cascade is a multistage kinetic proofreading process that amplifies minute differences, even a single base change. Our measurements suggest that this stochastic Turing-like machine can compute certain integral transforms.