Experimental evolution of Escherichia coli harboring an ancient translation protein

Abstract

The ability to design synthetic genes and engineer biological systems at the genome scale opens new means by which to characterize phenotypic states and the responses of biological systems to perturbations. One emerging method involves inserting artificial genes into bacterial genomes, and examining how the genome and its new genes adapt to each other. Here we report the development and implementation of a modified approach to this method, in which phylogenetically inferred genes are inserted into a microbial genome, and laboratory evolution is then used to examine the adaptive potential of the resulting hybrid genome. Specifically, we engineered an approximately 700-million-year old inferred ancestral variant of tufB, an essential gene encoding Elongation Factor Tu, and inserted it in a modern Escherichia coli genome in place of the native tufB gene. While the ancient homolog was not lethal to the cell, it did cause a two-fold decrease in organismal fitness, mainly due to reduced protein dosage. We subsequently evolved replicate hybrid bacterial populations for 2,000 generations in the laboratory, and examined the adaptive response via fitness assays, whole-genome sequencing, proteomics and biochemical assays. We found that the hybrid lineages exhibit a general adaptive strategy in which the fitness cost of the ancient gene was ameliorated in part by up-regulation of protein production. We expect that this ancient-modern recombinant method may pave the way for the synthesis of organisms that exhibit ancient phenotypes, and that laboratory evolution of these organisms may prove useful in elucidating insights into historical adaptive processes.

Experimental evolution and the dynamics of adaptation and genome evolution in microbial populations

“…Schlüter et al (2016) demonstrated a complicated interplay between the physiological and evolutionary responses of the calcifying phytoplankton Emiliania huxleyi to ocean acidification. Kacar et al (2017) mixed paleobiology, synthetic biology and experimental evolution by making an ancient version of a core gene, moving it into the chromosome of a modern E. coli strain, and observing how the bacteria subsequently evolved.…”

Contingency and chance erase necessity in the experimental evolution of ancestral proteins

“…For example, experiments on ancestral proteins have shown that particular historical mutations have different effects when introduced into different ancestral backgrounds – suggesting contingency – but they do not reveal the extent to which context-dependence actually influenced evolutionary outcomes; further, these historical trajectories happened only once, so they cannot elucidate the effect of contingency relative to chance (Ortlund et al 2007; Bridgham et al 2009; Bloom et al 2010; Gong et al 2013; Harms and Thornton 2014; McKeown et al 2014; Risso et al 2015; Natarajan et al 2016; Starr et al 2018; Wu et al 2018). Experimental evolution studies could, in principle, characterize both chance and contingency if they had sufficient replication from multiple starting points, but to date no study has done so; further, historically relevant proteins have not been used as starting points and historically relevant functions have not been selected for, so these studies’ relevance to historical evolution is not clear (Wichman et al 1999; Couñago et al 2006; Bollback and Huelsenbeck 2009; Salverda et al 2011; Blount et al 2012; Meyer et al 2012; van Ditmarsch et al 2013; Dickinson et al 2013; Spor et al 2013; Kryazhimskiy et al 2014; Wünsche et al 2017; Kacar et al 2017; Baier et al 2019; Zheng et al 2019). Studies of phenotypic convergence in nature suggest some degree of repeatability at the genetic level (reviewed in (Arendt and Reznick 2008; Gompel and Prud’homme 2009; Orgogozo 2015; Storz 2016)), but these studies rarely involve replicate lineages from the same starting genotypes, and evolutionary conditions are seldom identical; similarities and differences among lineages can therefore not be attributed to chance, contingency, or necessity.…”

Constraining the timing of the Great Oxidation Event within the Rubisco phylogenetic tree

“…This approach utilizes phylogenetic models of sequence evolution to computationally reconstruct ancestral gene and protein sequences. Reconstructed ancestral sequences can then be resurrected through in vivo or in vitro synthesis and their properties can be characterized in the laboratory (Dean & Thornton, 2007;Jermann, Opitz, Stackhouse, & Benner, 1995;Kacar & Gaucher, 2012;Kacar, Garmendia, Tuncbag, Andersson, & Hughes, 2016) Reconstruction methods may be extended to test hypotheses related to the deep evolutionary past and to identify historically significant mutation sites for genes and proteins, providing insights into the mutational basis of evolutionary innovations and sequence and structural level protein evolution through billions of years of evolutionary time (Chang, Jonsson, Kazmi, Donoghue, & Sakmar, 2002;Harms & Thornton, 2013;Kacar & Gaucher, 2013;Kacar, Ge, Sanyal, & Gaucher, 2017;Perez-Jimenez et al, 2011;Trudeau, Kaltenbach, & Tawfik, 2016;Voordeckers et al, 2012).…”