In biology, a mutation is an alteration in the nucleic acid sequence of the genome of an organism, virus, or extrachromosomal DNA. Viral genomes contain either DNA or RNA. Mutations result from errors during DNA or viral replication, mitosis, or meiosis or other types of damage to DNA, which then may undergo error-prone repair, cause an error during other forms of repair, or cause an error during replication. Mutations may also result from insertion or deletion of segments of DNA due to mobile genetic elements.
Escherichia coli ( ESH-ə-RIK-ee-ə KOH-lye) is a gram-negative, facultative anaerobic, rod-shaped, coliform bacterium of the genus Escherichia that is commonly found in the lower intestine of warm-blooded organisms. Most E. coli strains are harmless, but some serotypes such as EPEC, and ETEC are pathogenic and can cause serious food poisoning in their hosts, and are occasionally responsible for food contamination incidents that prompt product recalls. Most strains are part of the normal microbiota of the gut and are harmless or even beneficial to humans (although these strains tend to be less studied than the pathogenic ones). For example, some strains of E. coli benefit their hosts by producing vitamin K2 or by preventing the colonization of the intestine by pathogenic bacteria. These mutually beneficial relationships between E. coli and humans are a type of mutualistic biological relationship — where both the humans and the E. coli are benefitting each other. E. coli is expelled into the environment within fecal matter. The bacterium grows massively in fresh fecal matter under aerobic conditions for three days, but its numbers decline slowly afterwards.
A digital organism is a self-replicating computer program that mutates and evolves. Digital organisms are used as a tool to study the dynamics of Darwinian evolution, and to test or verify specific hypotheses or mathematical models of evolution. The study of digital organisms is closely related to the area of artificial life.
Avida is an artificial life software platform to study the evolutionary biology of self-replicating and evolving computer programs. Avida is under active development by Charles Ofria's Digital Evolution Lab at Michigan State University; the first version of Avida was designed in 1993 by Ofria, Chris Adami and C. Titus Brown at Caltech, and has been fully reengineered by Ofria on multiple occasions since then. The software was originally inspired by the Tierra system.
Experimental evolution is the use of laboratory experiments or controlled field manipulations to explore evolutionary dynamics. Evolution may be observed in the laboratory as individuals/populations adapt to new environmental conditions by natural selection.
Exaptation or co-option is a shift in the function of a trait during evolution. For example, a trait can evolve because it served one particular function, but subsequently it may come to serve another. Exaptations are common in both anatomy and behaviour.
In genetics, the mutation rate is the frequency of new mutations in a single gene, nucleotide sequence, or organism over time. Mutation rates are not constant and are not limited to a single type of mutation; there are many different types of mutations. Mutation rates are given for specific classes of mutations. Point mutations are a class of mutations which are changes to a single base. Missense, nonsense, and synonymous mutations are three subtypes of point mutations. The rate of these types of substitutions can be further subdivided into a mutation spectrum which describes the influence of the genetic context on the mutation rate.
A long-term experiment is an experimental procedure that runs through a long period of time, in order to test a hypothesis or observe a phenomenon that takes place at an extremely slow rate. What duration is considered "long" depends on the academic discipline. For example, several agricultural field experiments have run for more than 100 years, but much shorter experiments may qualify as "long-term" in other disciplines. An experiment is "a set of actions and observations", implying that one or more treatments is imposed on the system under study. Long-term experiments therefore contrast with nonexperimental long-term studies in which manipulation of the system studied is impossible or undesirable.
Christoph Carl Herbert "Chris" Adami is a professor of microbiology and molecular genetics, as well as professor of physics and astronomy, at Michigan State University.
Adaptive mutation, also called directed mutation or directed mutagenesis is a controversial evolutionary theory. It posits that mutations, or genetic changes, are much less random and more purposeful than traditional evolution, implying that organisms can respond to environmental stresses by directing mutations to certain genes or areas of the genome. There have been a wide variety of experiments trying to support the idea of adaptive mutation, at least in microorganisms.
Dr. Charles A. Ofria is a Professor in the Department of Computer Science and Engineering at Michigan State University, the director of the Digital Evolution (DEvo) Lab there, and Director of the BEACON Center for the Study of Evolution in Action. He is the son of the late Charles Ofria, who developed the first fully integrated shop management program for the automotive repair industry. Ofria attended Stuyvesant High School and graduated from Ward Melville High School in 1991. He obtained a B.S. in Computer Science, Pure Mathematics, and Applied Mathematics from Stony Brook University in 1994, and a Ph.D. in Computation and Neural Systems from the California Institute of Technology in 1999. Ofria's research focuses on the interplay between computer science and Darwinian evolution.
The E. coli long-term evolution experiment (LTEE) is an ongoing study in experimental evolution begun by Richard Lenski at the University of California, Irvine, carried on by Lenski and colleagues at Michigan State University, and currently overseen by Jeffrey Barrick at the University of Texas at Austin. It has been tracking genetic changes in 12 initially identical populations of asexual Escherichia coli bacteria since 24 February 1988. Lenski performed the 10,000th transfer of the experiment on March 13, 2017. The populations reached over 73,000 generations in early 2020, shortly before being frozen because of the COVID-19 pandemic. In September 2020, the LTEE experiment was resumed using the frozen stocks. When the populations reached 75,000 generations, the LTEE was transferred from the Lenski lab to the Barrick lab. In August 2024, the LTEE populations passed 80,000 generations in the Barrick lab.
Host–parasite coevolution is a special case of coevolution, where a host and a parasite continually adapt to each other. This can create an evolutionary arms race between them. A more benign possibility is of an evolutionary trade-off between transmission and virulence in the parasite, as if it kills its host too quickly, the parasite will not be able to reproduce either. Another theory, the Red Queen hypothesis, proposes that since both host and parasite have to keep on evolving to keep up with each other, and since sexual reproduction continually creates new combinations of genes, parasitism favours sexual reproduction in the host.
Escherichia coli is a Gram-negative gammaproteobacterium commonly found in the lower intestine of warm-blooded organisms (endotherms). The descendants of two isolates, K-12 and B strain, are used routinely in molecular biology as both a tool and a model organism.
Evolving digital ecological networks are webs of interacting, self-replicating, and evolving computer programs that experience the same major ecological interactions as biological organisms. Despite being computational, these programs evolve quickly in an open-ended way, and starting from only one or two ancestral organisms, the formation of ecological networks can be observed in real-time by tracking interactions between the constantly evolving organism phenotypes. These phenotypes may be defined by combinations of logical computations that digital organisms perform and by expressed behaviors that have evolved. The types and outcomes of interactions between phenotypes are determined by task overlap for logic-defined phenotypes and by responses to encounters in the case of behavioral phenotypes. Biologists use these evolving networks to study active and fundamental topics within evolutionary ecology.
Zachary D. Blount is an American evolutionary biologist best known for his work on the evolution of a key innovation, aerobic growth on citrate, in one of the twelve populations of the E. coli long-term evolution experiment. Blount is a research assistant professor working with Richard Lenski at Michigan State University. He was previously a postdoctoral research assistant for Lenski, and was a visiting assistant professor of biology at Kenyon College from 2018 to 2019.
A Muller plot, also known as Muller diagram, combines information about the succession of different operational taxonomic units (OTUs)—such as genotypes, phenotypes, or species—and information about dynamics of their abundances over time. Muller plots may be used to visualize evolutionary dynamics. They may be also employed in the study of diversity and its dynamics; that is, how diversity emerges and how it changes over time.
Michael Travisano is an American evolutionary biologist, and a Distinguished McKnight University Professor at the University of Minnesota Twin Cities. In 2020, he started his position as Head Department in Ecology, Evolution & Behavior Department at the College of Biological Sciences.
Albert Farrell Bennett is an American zoologist, physiologist, evolutionary biologist, author, and academic. He is Dean Emeritus of the School of Biological Sciences at University of California, Irvine.
Jeffrey E. Barrick is a Professor in the Department of Molecular Biosciences at The University of Texas at Austin. His research uses the tools of genomics, synthetic biology, and molecular biology to study the evolution of microorganisms, including symbionts of insects. Since 2022, Barrick has directed the E. coli Long-Term Evolution Experiment (LTEE), which has been underway since 1988.
