One of the largest problems facing modern medicine is drug resistance. Many classes of drugs can be rendered ineffective if their target is able to acquire beneficial mutations. While this is an excellent showcase of the power of evolution, it necessitates the development of increasingly stronger drugs to combat resistant pathogens. Not only is this strategy costly and time consuming, it is also unsustainable. To contend with this problem, many multi-drug treatment strategies are being explored. Previous studies have shown that resistance to some drug combinations is not possible, for example, resistance to a common antifungal drug, fluconazole, seems impossible in the presence of radicicol. We believe that in order to understand the viability of multi-drug strategies in combating drug resistance, we must understand the full spectrum of resistance mutations that an organism can develop, not just the most common ones. It is possible that rare mutations exist that are resistant to both drugs. Knowing the frequency of such mutations is important for making predictions about how problematic they will be when multi-drug strategies are used to treat human disease. This experiment aims to expand on previous research on the evolution of drug resistance in S. cerevisiae by using molecular barcodes to track ~100,000 evolving lineages simultaneously. The barcoded cells were evolved with serial transfers for seven weeks (200 generations) in three concentrations of the antifungal Fluconazole, three concentrations of the Hsp90 inhibitor Radicicol, and in four combinations of Fluconazole and Radicicol. Sequencing data was used to track barcode frequencies over the course of the evolution, allowing us to observe resistant lineages as they rise and quantify differences in resistance evolution across the different conditions. We were able to successfully observe over 100,000 replicates simultaneously, revealing many adaptive lineages in all conditions. Our results also show clear differences across drug concentrations and combinations, with the highest drug concentrations exhibiting distinct behaviors.

Ontogeny and Phylogeny is a book published in 1977, in which the author Stephen J. Gould, who worked in the US, tells a history of the theory of recapitulation. A theory of recapitulation aims to explain the relationship between the embryonic development of an organism (ontogeny) and the evolution of that organism's species (phylogeny). Although there are several variations of recapitulationist theories, most claim that during embryonic development an organism repeats the adult stages of organisms from those species in it's evolutionary history. Gould suggests that, although fewer biologists invoked recapitulation theories in the twentieth century compared to those in the nineteenth and eighteenth centuries, some aspects of the theory of recapitulation remained important for understanding evolution. Gould notes that the concepts of acceleration and retardation during development entail that changes in developmental timing (heterochrony) can result in a trait appearing either earlier or later than normal in developmental processes. Gould argues that these changes in the timing of embryonic development provide the raw materials or novelties upon which natural selection acts.

The Spandrels of San Marco and the Panglossian Paradigm:
A Critique of the Adaptationist Programme, hereafter called
The Spandrels, is an article written by Stephen J. Gould and
Richard C. Lewontin published in the Proceedings of the Royal
Society of London in 1979. The paper emphasizes issues with
what the two authors call adaptationism or the adaptationist
programme as a framework to explain how species and traits evolved. The paper
is one in a series of works in which Gould emphasized the
role of development in evolutionary theories. The article suggests
that constraints on how organisms can develop and constraints on how species can evolve from others play a
central role in explaining the how species and traits evolve. The
authors note that organisms from different species develop as
embryos through stages similar across species, genera, and higher
classes. Gould and Lewontin hypothesize that those stages
constrained the possible pathways of evolution and has therefore
guided the history of life. Throughout the paper, the authors rely on analogy of some parts of organisms to architectural structures called spandrels, marked in this image as 'a'."

The Law of Acceleration of Growth is a theory proposed by Edward Drinker Cope in the US during the nineteenth century. Cope developed it in an attempt to explain the evolution of genera by appealing to changes in the developmental timelines of organisms. Cope proposed this law as an additional theory to natural selection. He argued that the evolution of genera, the more general groups within which biologists group species, occurs when the individual in a species move through developmental stages faster than did their ancestors, but within the same fixed period of gestation, and thus can undergo new developmental stages and develop new traits. The Law of Acceleration compliments Cope's Law of Retardation of Growth. He described the later law as the process by which organisms revert to an ancestral stage. In these cases, forces suppress the most recent traits or stages common to the development of individuals from different species within the same genus. Cope described evolution as progressive, following a predetermined path, a perspective about evolution sometimes called orthogenetic. Cope's was one among many orthogenic theories in the second half of the nineteenth century. Furthermore, the theory was part of a trend in nineteenth century in which some biologists claimed that the changes in developmental timing of organisms could explain large changes in biological forms throughout natural history.

Mutual Affinities of Organic Beings: Morphology: Embryology: Rudimentary Organs is the thirteenth chapter of Charles Darwin's book The Origin of Species, first published in England in 1859. The book details part of Darwin's argument for the common ancestry of life and natural selection as the cause of speciation. In this chapter, Darwin summarizes the evidence for evolution by connecting observations of development in organisms to the processes of natural selection. Darwin shows how the theory of special creation, which claims that God directly created all organisms in their current form, is inferior to the theory of natural selection for its ability to explain the diversity of life. In this chapter, Darwin also discusses classification and homology as they relate to natural selection.

Stephen Jay Gould studied snail fossils and worked at Harvard University in Cambridge, Massachusetts during the latter half of the twentieth century. He contributed to philosophical, historical, and scientific ideas in paleontology, evolutionary theory, and developmental biology. Gould, with Niles Eldredge, proposed the theory of punctuated equilibrium, a view of evolution by which species undergo long periods of stasis followed by rapid changes over relatively short periods instead of continually accumulating slow changes over millions of years. In his 1977 book, Ontogeny and Phylogeny, Gould reconstructed a history of developmental biology and stressed the importance of development to evolutionary biology. In a 1979 paper coauthored with Richard Lewontin, Gould and Lewonitn criticized many evolutionary bioligists for relying solely on adaptive evolution as an explanation for morphological change, and for failing to consider other explanations, such as developmental constraints.

The biogenetic law is a theory of development and evolution proposed by Ernst Haeckel in Germany in the 1860s. It is one of several recapitulation theories, which posit that the stages of development for an animal embryo are the same as other animals' adult stages or forms. Commonly stated as ontogeny recapitulates phylogeny, the biogenetic law theorizes that the stages an animal embryo undergoes during development are a chronological replay of that species' past evolutionary forms. The biogenetic law states that each embryo's developmental stage represents an adult form of an evolutionary ancestor. According to the law, by studying the stages of embryological development, one is, in effect, studying the history and diversification of life on Earth. The biogenetic law implied that researchers could study evolutionary relationships between taxa by comparing the developmental stages of embryos for organisms from those taxa. Furthermore, the evidence from embryology supported the theory that all of species on Earth share a common ancestor.

Pathogenic drug resistance is a major global health concern. Thus, there is great interest in modeling the behavior of resistant mutations–how quickly they will rise in frequency within a population, and whether they come with fitness tradeoffs that can form the basis of treatment strategies. These models often depend on precise measurements of the relative fitness advantage (s) for each mutation and the strength of the fitness tradeoff that each mutation suffers in other contexts. Precisely quantifying s helps us create better, more accurate models of how mutants act in different treatment strategies. For example, P. falciparum acquires antimalarial drug resistance through a series of mutations to a single gene. Prior work in yeast expressing this P. falciparum gene demonstrated that mutations come with tradeoffs. Computational work has demonstrated the possibility of a treatment strategy which enriches for a particular resistant mutation that then makes the population grow poorly once the drug is removed. This treatment strategy requires knowledge of s and how it changes when multiple mutants are competing across various drug concentrations. Here, we precisely quantified s in varying drug concentrations for five resistant mutants, each of which provide varying degrees of drug resistance to antimalarial drugs. DNA barcodes were used to label each strain, allowing the mutants to be pooled together for direct competition in different concentrations of drug. This will provide data that can make the models more accurate, potentially facilitating more effective drug treatments in the future.