Selection or drift: The population biology underlying transposon insertion sequencing experiments.

Area of Science:

• Microbiology
• Population Genetics
• Bioinformatics

Background:

• Transposon insertion sequencing (Tn-seq) is a powerful genomics tool for identifying essential genes in various environments.
• Tn-seq experiments often exhibit limited reproducibility, potentially due to population dynamics rather than true fitness differences.
• The influence of random genetic drift and selection on mutant frequencies in Tn-seq is not fully understood.

Purpose of the Study:

• To develop a mathematical model simulating the population biology of Tn-seq experiments.
• To investigate how mutagenesis, library growth, and bottlenecks affect mutant frequencies and viability.
• To understand the impact of the distribution of fitness effects (DFE) on experimental outcomes and reproducibility.

Main Methods:

• Development of a mathematical model to describe changes in mutant population size and composition during Tn-seq.
• Simulation of mutagenesis, mutant library growth, and passage through population bottlenecks.
• Analysis of mutant extinction probabilities based on individual fitness and the overall DFE.

Main Results:

• In vitro experiments show minimal extinction of high-fitness mutants.
• Bottlenecks, common in animal models, cause substantial random extinction, leading to misclassification of viable mutants.
• Mutants with intermediate fitness are often overrepresented, contributing to false positives in hit identification.

Conclusions:

• Population dynamics, particularly bottlenecks, significantly impact Tn-seq reproducibility by causing random mutant loss.
• Incorporating the DFE of mutations into Tn-seq analysis can improve the reliability of results, especially under bottleneck conditions.
• Understanding these population-level effects is crucial for accurate interpretation of Tn-seq data and gene essentiality.