Biological trajectories toward universal computation: Transposons and chaperone-assisted folding as models of molecular logic.
TL;DR
This paper argues that transposons, exemplified by the ONSEN retrotransposon in Arabidopsis thaliana, implement signal-responsive genome state transitions formally analogous to probabilistic finite-state machine computation, with capacity for computational expressiveness consistent with that of a linear-bounded automaton (LBA).
Abstract
The question of whether biological systems implement computation-like processes is central to synthetic biology and theoretical biophysics. This paper proposes a formal conceptual framework in which two well-characterized molecular mechanisms-transposable elements ("jumping genes") and chaperone-mediated protein folding-are modeled as computational systems. We argue that transposons, exemplified by the ONSEN retrotransposon in Arabidopsis thaliana, implement signal-responsive genome state transitions formally analogous to probabilistic finite-state machine computation, with capacity for computational expressiveness consistent with that of a linear-bounded automaton (LBA) under explicit assumptions of bounded memory, state-dependent branching and heritable epigenetic memory (a hypothesis, not a proof). Simultaneously, molecular chaperones such as heat shock protein 70 (Hsp70) and GroEL/GroES realize an analog computation paradigm, navigating protein energy landscapes through iterative, constraint-driven optimization. Together, these systems suggest that biological macromolecular networks may intrinsically embed logical operations capable of sophisticated information processing. We develop component-level mappings, present a comparative analysis, and outline falsifiable experimental predictions and synthetic biology applications that follow from this framework. These findings carry implications for bio-computing architectures, evolutionary genomics, and the theoretical foundations of life as an information-processing substrate.
