Self-replication

Abstract: Membrane systems are purely abstract computational models afar inspired by biological cells, their membranes, and their biochemistry. The inherently parallel nature of membrane systems makes them obviously highly inefficient to execute on a sequential von Neumann computer architecture and in addition, programming a membrane system is often a painstakingly difficult undertaking. The main goal of this paper is to provide some key elements for bringing membrane systems from the abstract model closer to a genuine, novel, and unconventional in silico computer architecture. In particular, we will address the mechanisms of self-configuration and self-replication on a macroscopic level and will discuss some general issues related to genuine hardware realizations on the microscopic level.

Abstract: Cellular automata models have historically been a major approach to studying the information-processing properties of self-replication. Here we explore the feasibility of adopting genetic programming so that, when it is given a fairly arbitrary initial cellular automata configuration, it will automatically generate a set of rules that make the given configuration replicate. We found that this approach works surprisingly effectively for structures as large as 50 components or more. The replication mechanisms discovered by genetic programming work quite differently than those of many past manually designed replicators: There is no identifiable instruction sequence or construction arm, the replicating structures generally translate and rotate as they reproduce, and they divide via a fissionlike process that involves highly parallel operations. This makes replication very fast, and one cannot identify which descendant is the parent and which is the child. The ability to automatically generate self-replicating structures in this fashion allowed us to examine the resulting replicators as their properties were systematically varied. Further, it proved possible to produce replicators that simultaneously deposited secondary structures while replicating, as in some past manually designed models. We conclude that genetic programming is a powerful tool for studying self-replication that might also be profitably used in contexts other than cellular spaces.

Abstract: The growth and operation of all living beings are directed by the interpretation, in each of their cells, of a chemical program, the DNA string or genome. This process is the source of inspiration for the Embryonics (embryonic electronics) project, whose final objective is the design of highly robust integrated circuits, endowed with properties usually associated with the living world: self-repair (cicatrization) and self-replication. The Embryonics architecture is based on four hierarchical levels of organization: 1) the basic primitive of our system is the molecule, a multiplexer-based element of a novel programmable circuit; 2) a finite set of molecules makes up a cell, essentially a small processor with an associated memory; 3) a finite set of cells makes up an organism, an application-specific multiprocessor system; 4) the organism can itself replicate, giving rise to a population of identical organisms. In this paper, we provide an overview of our latest research in the domain of the self-replication of processing elements within a programmable logic substrate, a key prerequisite for achieving system-level fault tolerance in our bio-inspired approach.

Abstract: Self-replication is one of the major principles without life could not exist. The emergence of self-replicating systems on the early earth is generally believed to have taken place before the advent of instructed protein synthesis based on a complex translation machinery. Whether the origin of self-replication is identical to the origin of the hypothetical RNA world or whether it existed at an earlier stage of evolution is an open question that has stimulated chemists to search for chemical systems capable of making copies of itselves via autocatalytic reactions. As self-replication means autocatalysis plus information transfer, the reaction products must necessarily be able to store more structural information than their precursors. Templating as a means to transfer structural information has been exploited since the first successful example of a chemical self-replicating system almost two decades ago [1]. Today we have a broad variety of such systems employing oligonucleotides, peptides, and small organic molecules as templates and autocatalytic [1-3], cross-catalytic [4], collectively autocatalytic and non-autonomous (stepwise) schemes of self-replication [5]. A link between the chemical self-replication and nanotechnology was first pointed out by G.M.Whitesides in his debate with Drexler. The ribosome is an example for a nanomachine which may be viewed as a three-dimensionally defined array of 51 modular proteins positioned by the rRNA scaffold. Biomimetic approaches towards the 3D-nano-scaffolding of modular functions may be based on trisoligonucleotides [6], viz. synthetic 3-arm junctions in which the 3'-ends of three oligonucleotides are connected by a suitable linker. We report on trisoligos as building blocks for the noncovalent construction of nanoobjects. Kinetic control - applied by rapid cooling during self-assembly - was found to favor small and defined nano-structures instead of large polymeric networks [6]. Maximal instruction was employed as design principles to generate noncovalent 3D-nano-objects in which both, the topology and the geometry is defined [7]. Examples include dodecahedral nano-scaffolds composed from 20 trisoligos each bearing three individually defined sequences [8]. It was demonstrated that the connectivity information in the nano-scaffold junctions can be copied by chemical means [9]. Chemical copying schemes may be seen in conjunction with "surface-promoted replication and exponential amplification of DNA analogues" (SPREAD) [5]. Applications of such scaffolds include the positioning of modular functions such as multidentate thioether-based gold cluster labels (RUBiGold) [10] which have been tailored for monoconjugability and thermostability. My lecture will introduce chemical self-replication and multicomponent assembly as facets of systems chemistry [3,11,12] - a nascent field which understands itself as the bottom-up pendant of systems biology towards synthetic biology [14]. The field is clearly inspired by the origin-of-life problem but goes beyond traditional prebiotic chemistry in its mission towards a quantititive dynamic understanding of complex reaction networks with autocatalytic components. Software tools like our SimFit and kinetic NMR titration [2] may significantly help to decipher signatures of interesting dynamic phenomena such as self-replication, chiral symmetry-breaking, and metabolic autocatalysis found in organic [13] and biomolecular [12] reaction systems.