Background and objectives To understand how organisms evolve, it is fundamental to study how mutations emerge and establish. Here, we estimated the rate of mutation accumulation of SARS-CoV-2 in vitro and investigated the repeatability of its evolution when facing a new cell type but no immune or drug pressures. Methodology We performed experimental evolution with two strains of SARS-CoV-2, one carrying the originally described spike protein (CoV-2-D) and another carrying the D614G mutation that has spread worldwide (CoV-2-G). After 15 passages in Vero cells and whole genome sequencing, we characterized the spectrum and rate of the emerging mutations and looked for evidences of selection across the genomes of both strains. Results From the frequencies of the mutations accumulated, and excluding the genes with signals of selection, we estimate a spontaneous mutation rate of 1.3x1 0 −6 ± 0.2x1 0 −6 per-base per-infection cycle (mean across both lineages of SARS-CoV-2 ± 2SEM). We further show that mutation accumulation is larger in the CoV-2-D lineage and heterogeneous along the genome, consistent with the action of positive selection on the spike protein, which accumulated five times more mutations than the corresponding genomic average. We also observe the emergence of mutators in the CoV-2-G background, likely linked to mutations in the RNA-dependent RNA polymerase and/or in the error-correcting exonuclease protein. Conclusions and implications These results provide valuable information on how spontaneous mutations emerge in SARS-CoV-2 and on how selection can shape its genome towards adaptation to new environments. LAY SUMMARY Each time a virus replicates inside a cell, errors (mutations) occur. Here, via laboratory propagation in cells originally isolated from the kidney epithelium of African green monkeys, we estimated the rate at which the SARS-CoV-2 virus mutates—an important parameter for understanding how it can evolve within and across humans. We also confirm the potential of its Spike protein to adapt to a new environment and report the emergence of mutators—viral populations where mutations occur at a significantly faster rate.

How and at what pace bacteria evolve when colonizing healthy hosts remains unclear. Here, by monitoring evolution for more than six thousand generations in the mouse gut, we show that the successful colonization of an invader Escherichia coli depends on the diversity of the existing microbiota and the presence of a closely related strain. Following colonization, two modes of evolution were observed: one in which diversifying selection leads to long-term coexistence of ecotypes and a second in which directional selection propels selective sweeps. These modes can be quantitatively distinguished by the statistics of mutation trajectories. In our experiments, diversifying selection was marked by the emergence of metabolic mutations, and directional selection by acquisition of prophages, which bring their own benefits and costs. In both modes, we observed parallel evolution, with mutation accumulation rates comparable to those typically observed in vitro on similar time scales. Our results show how rapid ecotype formation and phage domestication can be in the mammalian gut.

The fitness cost of antibiotic resistance in the absence of antibiotics is crucial to the success of suspending antibiotics as a strategy to lower resistance. Here we show that after antibiotic treatment the cost of resistance within the complex ecosystem of the mammalian gut is personalized. Using mice as an in vivo model, we find that the fitness effect of the same resistant mutation can be deleterious in a host, but neutral or even beneficial in other hosts. Such antagonistic pleiotropy is shaped by the microbiota, as in germ-free mice resistance is consistently costly across all hosts. An eco-evolutionary model of competition for resources identifies a general mechanism underlying between host variation and predicts that the dynamics of compensatory evolution of resistant bacteria should be host specific, a prediction that was supported by experimental evolution in vivo. The microbiome of each human is close to unique and our results suggest that the short-term costs of resistance and its long-term withinhost evolution will also be highly personalized, a finding that may contribute to the observed variable outcome of control therapies.

Microbial ecosystems harbor an astonishing diversity that can persist for long times. To understand how such diversity is structured and maintained, ecological and evolutionary processes need to be integrated at similar timescales. Here, we study a model of resource competition that allows for evolution via de novo mutation, and focus on rapidly adapting asexual populations with large mutational inputs, as typical of many bacteria species. We characterize the adaptation and diversification of an initially maladapted population and show how the eco-evolutionary dynamics are shaped by the interaction between simultaneously emerging lineages -clonal interference. We find that in large populations, more intense clonal interference can foster diversification under sympatry, increasing the probability that phenotypically and genetically distinct clusters coexist. In smaller populations, the accumulation of deleterious and compensatory mutations can push further the diversification process and kick-start speciation. Our findings have implications beyond microbial populations, providing novel insights about the interplay between ecology and evolution in clonal populations.

"How predictable is evolution?" is a key question in evolutionary biology. Experimental evolution has shown that the evolutionary path of microbes can be extraordinarily reproducible. Here, using experimental evolution in two circulating SARS-CoV-2, we estimate its mutation rate and demonstrate the repeatability of its evolution when facing a new cell type but no immune or drug pressures. We estimate a genomic mutation rate of 3.7x10^-6 nt^-1 cycle^-1 for a lineage of SARS-CoV-2 with the originally described spike protein (CoV-2-D) and of 2.9x10^-6 nt^-1 cycle-1 for a lineage carrying the D614G mutation that has spread worldwide (CoV-2-G). We further show that mutation accumulation is heterogeneous along the genome, with the spike gene accumulating mutations at a mean rate 16x10^-6 nt^-1 per infection cycle across backgrounds, five-fold higher than the genomic average. We observe the emergence of mutators in the CoV-2-G background, likely linked to mutations in the RNA-dependent RNA polymerase and/or in the error-correcting exonuclease protein. Despite strong bottlenecks, several de novo mutations spread to high frequencies by selection and considerable convergent evolution in spike occurs. These results demonstrate the high adaptive potential of SARS-CoV-2 during the first stages of cell infection in the absence of immune surveillance.

Experimental evolution studies with microorganisms such as bacteria and yeast have been an increasingly important and powerful way to draw inferences about the genetic and molecular basis of adaptive evolution. The clearer our understanding of how microbes interact is, the easier it will be to control and design communities with applications in important areas ranging from industrial,

Microbial ecosystems harbor an astonishing diversity that can persist for long times. To understand how such diversity is generated and maintained, ecological and evolutionary processes need to be integrated at similar timescales, but this remains a difficult challenge. Here, we extend an ecological model of resource competition to allow for evolution via de novo mutation, focusing on large and rapidly adapting asexual populations. Through numerical and analytical approaches, we characterize adaptation and diversity at different levels and show how clonal interference – the interaction between simultaneously emerging lineages – shapes the eco-evolutionary dynamics. We find that large mutational inputs can foster diversification under sympatry, increasing the probability that phenotypically and genetically distinct clusters arise and stably coexist, constituting an initial form of community. Our findings have implications beyond microbial populations, providing novel insights about the interplay between ecology and evolution in clonal populations.

10The fitness cost of antibiotic resistance in the absence of antibiotics is crucial to the 11 success of suspending antibiotics as a strategy to lower resistance. Here we show that 12 after antibiotic treatment the cost of resistance within the complex ecosystem of the 13 mammalian gut is personalized. Using mice as an in vivo model, we find that the 14 fitness effect of the same resistant mutation can be deleterious in a host, but neutral or 15 even beneficial in other hosts. Such antagonistic pleiotropy is shaped by the 16 microbiota, as in germ-free mice resistance is consistently costly across all hosts. An 17 eco-evolutionary model of competition for resources identifies a general mechanism 18 underlying between host variation and predicts that the dynamics of compensatory 19 evolution of resistant bacteria should be host specific, a prediction that was supported 20 by experimental evolution in vivo. The microbiome of each human is close to unique 21 and our results suggest that the short-term costs of resistance and its long-term within-22 host evolution will also be highly personalized, a finding that may contribute to the 23 observed variable outcome of control therapies. 24 25 few studies where pathogens 25-31 were tested during in vivo colonization and infection 51suggest that fitness costs of AR are not always high in the context of bacterial 52 colonization or virulence. Yet to the best of our knowledge, no study so far has 53 analyzed the temporal dynamics of resistant strains colonizing the key ecosystem of 54 the gut microbiota. In particular, it is currently unclear how the results from in vitro 55 studies or in the context of invasive pathogens are informative about AR in gut 56 commensal strains, which are by far the main colonizers of a natural complex 57 ecosystem. Here, we performed in vivo competitive fitness assays, mathematical 58 modeling and in vivo experimental evolution to unravel the fitness effects of AR in 59 commensal E. coli colonizing its natural environment. 60 61 RESULTS 62Competitive fitness of AR in the mouse gut 63We focused on common resistance mutations to streptomycin -Str R (rpsL K43T ) and 64 rifampicin-Rif R (rpoB H526Y ), and also studied double resistant clones -Str R Rif R 65 (rpsL K43T rpoB H526Y ). These have been identified in many important pathogens, such 66as Mycobacterium tuberculosis and Salmonella, and also in pathogenic and 67 commensal E. coli [32][33][34] . 68To query how inter-species interactions, present in the natural ecosystem comprising 69 the mammalian gut, influence the costs of AR, we performed competitive fitness 70 assays in mice that have a complex microbiota (SPF mice). To mimic conditions 71where the rise of AR can occur, mice were given an antibiotic treatment -72 streptomycin -for a week (see Fig. 1a and Methods). Such treatment is known to 73 cause perturbations in the microbiota species composition and also to break 74 colonization resistant to E. coli 35 , thus increasing the probability that colonization by 75