Extreme Sensitivity of Fitness to Environmental Conditions: Lessons from #1BigBatch.

The phrase "survival of the fittest" has become an iconic descriptor of how natural selection works. And yet, precisely measuring fitness, even for single-celled microbial populations growing in controlled laboratory conditions, remains a challenge. While numerous methods exist to perform these measurements, including recently developed methods utilizing DNA barcodes, all methods are limited in their precision to differentiate strains with small fitness differences. In this study, we rule out some major sources of imprecision, but still find that fitness measurements vary substantially from replicate to replicate. Our data suggest that very subtle and difficult to avoid environmental differences between replicates create systematic variation across fitness measurements. We conclude by discussing how fitness measurements should be interpreted given their extreme environment dependence. This work was inspired by the scientific community who followed us and gave us tips as we live tweeted a high-replicate fitness measurement experiment at #1BigBatch.

Fitness variation across subtle environmental perturbations reveals local modularity and global pleiotropy of adaptation.

Building a genotype-phenotype-fitness map of adaptation is a central goal in evolutionary biology. It is difficult even when adaptive mutations are known because it is hard to enumerate which phenotypes make these mutations adaptive. We address this problem by first quantifying how the fitness of hundreds of adaptive yeast mutants responds to subtle environmental shifts. We then model the number of phenotypes these mutations collectively influence by decomposing these patterns of fitness variation. We find that a small number of inferred phenotypes can predict fitness of the adaptive mutations near their original glucose-limited evolution condition. Importantly, inferred phenotypes that matter little to fitness at or near the evolution condition can matter strongly in distant environments. This suggests that adaptive mutations are locally modular - affecting a small number of phenotypes that matter to fitness in the environment where they evolved - yet globally pleiotropic - affecting additional phenotypes that may reduce or improve fitness in new environments.

One of the goals of evolutionary biology is to understand the relationship between genotype, phenotype, and fitness. An organism's genes ­ its genotype ­ determine its physical and behavioral traits ­ its phenotype. Phenotypes, in turn, affect the organisms' chances of survival and reproduction ­ its fitness. However, mapping the relationships among these three variables is far from easy. Recently researchers have become able to identify many genetic mutations that increase an organism's fitness, but it is more difficult to work out how these mutations affect an organism's phenotype, and why they are beneficial. The mutations that help organisms thrive in a particular environment are often limited to a handful of genes that affect similar biological processes. For example, microbes that grow in environments with limited sugar tend to accumulate mutations in genes involved in systems that determine whether to grow fast and carelessly or to be careful in case the sugar is never replenished. It is possible that these mutations all affect the same one or two phenotypes, such as the decision to grow or to hunker down. If this were the case, researchers should be able to easily predict how well these organisms adapt to new environments. However, it is possible that specific mutations affect several phenotypes, but these extra effects remain invisible until the environment changes and these phenotypes are revealed. To explore this possibility, Kinsler, Geiler-Samerotte, and Petrov obtained hundreds of individual yeast strains that each contained a different mutation that improved the yeast's fitness in a low sugar environment. They placed these strains into similar environments and measured their fitness. The patterns observed were used to build several models that predicted how many phenotypes each mutation must affect to explain the changes in fitness. Kinsler, Geiler-Samerotte and Petrov found that the model in which only five phenotypes were affected by the mutations was able to predict the fitness of the yeast in low-sugar environments. However, to predict the fitness of the same mutations in environments that were very different, the model had to include eight phenotypes. This suggests that although the mutations that helped yeast do well in the low sugar environment were similar in their benefits in this environment, they were not truly all the same. In fact, some mutations were quite different from the others in terms of their hidden phenotypic effects. The hidden effects of mutations can be positive or negative. One mutation might cause an organism to die in a new environment, whereas another might allow it to thrive. Understanding how this works has implications not only for evolutionary biology, but also for medical research. Pathogens that cause infection, and cells that cause cancer, often accumulate mutations in small numbers of crucial genes. Understanding how these mutations affect phenotypes that become important as the environment changes ­ for instance as the cells encounter new challenges as a tumor grows ­ and whether different mutations have different hidden effects, could improve treatments in the future.

Prebiotic selection for motifs in a model of template-free elongation of polymers within compartments.

The transition from prelife where self-replication does not occur, to life which exhibits self-replication and evolution, has been a subject of interest for many decades. Membranes, forming compartments, seem to be a critical component of this transition as they provide several concurrent benefits. They maintain localized interactions, generate electro-chemical gradients, and help in selecting cooperative functions as they arise. These functions pave the way for the emergence and maintenance of simple metabolic cycles and polymers. In the context of origin of life, evolution of information-carrying molecules and RNA based enzymes within compartments has been subject to intensive theoretical and experimental research. Hence, many experimental efforts aim to produce compartments that contain elongating polynucleotides (also referred to as protocells), which store information and perform catalysis. Despite impressive experimental progress, we are still relatively ignorant about the dynamics by which elongating polynucleotides can produce more sophisticated behaviors. Here we perform computer simulations to couple information production through template-free elongation of polymers with dividing compartments. We find that polymers with a simple ability-biasing the concentration of monomers within their own compartment-can acquire a selective advantage in prelife. We further investigate whether such a mechanism allows for cooperative dynamics to dominate over purely competitive ones. We show that under this system of biased monomer addition, even without template-directed self-replication, genetic motifs can emerge, compete, cooperate, and ultimately survive within the population.