  Life is confronted with computation problems in a variety of domains
including animal behavior, single-cell behavior, and embryonic development. Yet
we currently do not know of a naturally existing biological system that is
capable of universal computation, i.e., Turing-equivalent in scope. Generic
finite-dimensional dynamical systems (which encompass most models of neural
networks, intracellular signaling cascades, and gene regulatory networks) fall
short of universal computation, but are assumed to be capable of explaining
cognition and development. I present a class of models that bridge two concepts
from distant fields: combinatory logic (or, equivalently, lambda calculus) and
RNA molecular biology. A set of basic RNA editing rules can make it possible to
compute any computable function with identical algorithmic complexity to that
of Turing machines. The models do not assume extraordinarily complex molecular
machinery or any processes that radically differ from what we already know to
occur in cells. Distinct independent enzymes can mediate each of the rules and
RNA molecules solve the problem of parenthesis matching through their secondary
structure. In the most plausible of these models all of the editing rules can
be implemented with merely cleavage and ligation operations at fixed positions
relative to predefined motifs. This demonstrates that universal computation is
well within the reach of molecular biology. It is therefore reasonable to
assume that life has evolved - or possibly began with - a universal computer
that yet remains to be discovered. The variety of seemingly unrelated
computational problems across many scales can potentially be solved using the
same RNA-based computation system. Experimental validation of this theory may
immensely impact our understanding of memory, cognition, development, disease,
evolution, and the early stages of life.
