Title

The Luria-Delbrück Mutation Model

Presenter Information

Tara CroftFollow

Academic Level at Time of Presentation

Senior

Major

Chemistry

Minor

Mathematics

List all Project Mentors & Advisor(s)

Dr. Maeve McCarthy

Presentation Format

Oral Presentation

Abstract/Description

Microbial organisms have the ability to resist harsh environmental conditions such as antibiotics by developing mutations. The scientific community had two opposing theories about the origin of these resistance mutations. Some hypothesized that a Lamarckian mutation, acquired immunity brought on by harsh environment, and others opted for the Darwinian explanation, random mutations before exposure. Luria and Delbruck conducted a series of experiments in 1943 to address these conflicting hypotheses. Their fluctuation test showed that phage-resistant bacteria follow a Darwinian explanation and develop at a predictable growth rate related to population size, P=e-un. The Luria-Delbruck equation is still used as the optimal model to estimate mutation growth rates. Luria and Delbruck spearheaded the use of applied statistical analysis to biological issues to achieve meaningful results. This paper provides mathematical justification and current adaptations to the model. Biological significance and modern research which applies the Luria-Delbruck model are also discussed.

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The Luria-Delbrück Mutation Model

Microbial organisms have the ability to resist harsh environmental conditions such as antibiotics by developing mutations. The scientific community had two opposing theories about the origin of these resistance mutations. Some hypothesized that a Lamarckian mutation, acquired immunity brought on by harsh environment, and others opted for the Darwinian explanation, random mutations before exposure. Luria and Delbruck conducted a series of experiments in 1943 to address these conflicting hypotheses. Their fluctuation test showed that phage-resistant bacteria follow a Darwinian explanation and develop at a predictable growth rate related to population size, P=e-un. The Luria-Delbruck equation is still used as the optimal model to estimate mutation growth rates. Luria and Delbruck spearheaded the use of applied statistical analysis to biological issues to achieve meaningful results. This paper provides mathematical justification and current adaptations to the model. Biological significance and modern research which applies the Luria-Delbruck model are also discussed.