The origin of the central dogma through conflicting multilevel selection

Abstract

The central dogma of molecular biology rests on two kinds of asymmetry between genomes and enzymes: informatic asymmetry, where information flows from genomes to enzymes but not from enzymes to genomes; and catalytic asymmetry, where enzymes provide chemical catalysis but genomes do not. How did these asymmetries originate? Here, we show that these asymmetries can spontaneously arise from conflict between selection at the molecular level and selection at the cellular level. We developed a model consisting of a population of protocells, each containing a population of replicating catalytic molecules. The molecules are assumed to face a trade-off between serving as catalysts and serving as templates. This trade-off causes conflicting multilevel selection: serving as catalysts is favoured by selection between protocells, whereas serving as templates is favoured by selection between molecules within protocells. This conflict induces informatic and catalytic symmetry breaking, whereby the molecules differentiate into genomes and enzymes, establishing the central dogma. We show mathematically that the symmetry breaking is caused by a positive feedback between Fisher’s reproductive values and the relative impact of selection at different levels. This feedback induces a division of labour between genomes and enzymes, provided variation at the molecular level is sufficiently large relative to variation at the cellular level, a condition that is expected to hinder the evolution of altruism. Taken together, our results suggest that the central dogma is a logical consequence of conflicting multilevel selection.

A scaling law of multilevel evolution: how the balance between within- and among-collective evolution is determined

“…Evolution thus operates at multiple levels of the biological hierarchy in conflicting directions—conflicting multilevel evolution. Whether within- or among-collective evolution predominates exerts profound impacts on the stability and evolution of hierarchically organized replicating systems ( Wilson 1975 ; Slatkin and Wade 1978 ; Aoki 1982 ; Crow and Aoki 1982 ; Leigh 1983 ; Kimura 1984 , 1986 ; Frank 1994 ; Rispe and Moran 2000 ; Goodnight 2005 ; Traulsen and Nowak 2006 ; Bijma et al 2007 ; Chuang et al 2009 ; Leigh 2010 ; Frank 2012 ; Simon et al 2013 ; Tarnita et al 2013 ; Fontanari and Serva 2014 ; Luo 2014 ; Takeuchi et al 2016 , 2017 ; Blokhuis et al 2018 ; Cooney 2019 ; Takeuchi and Kaneko 2019 ; van Vliet and Doebeli 2019 ), which abound in nature ( Buss 1987 ; Maynard Smith and Szathmáry 1995 ; Burt and Trivers 2006 ; Davies et al 2012 ; Gershwin et al 2014 ; Joyce and Szostak 2018 ). Therefore, how the balance between within- and among-collective evolution is determined is an important question in biology.…”

“…Previously, we have demonstrated that the balance between within- and among-collective evolution involves a simple scaling relation between parameters of population dynamics ( Takeuchi et al 2016 , 2017 ; Takeuchi and Kaneko 2019 ). These parameters are the mutation rate of components (denoted by m ) and the number of replicating components per collective (denoted by N )—in general, N represents the “size” of a collective, such as the number of replicating molecules per protocell, organelles per cell, cells per multicellular organism, and organisms per colony.…”

“…, no bias toward the evolution of cheating or altruism): is a constant ( i.e. , ), where scaling exponent α is approximately one half ( Takeuchi et al 2016 , 2017 ; Takeuchi and Kaneko 2019 ). This scaling relation indicates that although m and N have quantitatively different impacts on the balance between within- and among-collective evolution, their impacts are identical if m is scaled with exponent α ( e.g.…”

“…While the above scaling relation provides a novel insight into how the balance between within- and among-collective evolution is determined, the generality of this relation is unknown because the relation has originally been demonstrated in specific models of protocells through computer simulations ( Takeuchi et al 2016 , 2017 ; Takeuchi and Kaneko 2019 ). To shed light on the generality of the scaling relation, here, we adapt a standard model of population genetics, the Wright–Fisher model ( Ewens 2004 ), to investigate the balance between within- and among-collective evolution.…”

Footprints of a Singular 22-Nucleotide RNA Ring at the Origin of Life

“…A recent model [38] in the spirit of the Eigen-Schuster's hypercycles [2,3] presents a plausible co-evolution of two types of replicating molecules, denoted P and Q: P can represent the primitive RNA molecules and Q the primitive DNA molecules. The dynamical evolution of P and Q leads to a stable stationary state, in which coexist the functional species P (ancestor of enzymes) and the informative species Q (ancestor of DNA).…”