The metaphor of a bottleneck has been used in a variety of fields to describe the critical constraints that limit a system’s performance or capacity. In biology, particularly in studies of population dynamics and evolution, the bottleneck concept is often used in reference to events that sharply limit population size [1]. Such events frequently produce stochastic changes in the genetic composition of a population (Fig 1), referred to as genetic drift. In extreme cases, population-reducing events can eliminate genotypes from a gene pool (Fig 1), even genotypes not associated with reduced fitness.

If the limited number of these surviving organisms found a population in a new environment, such as the colonization or infection of a host by microorganisms, those few organisms determine the genetic composition of subsequent generations, creating a “founder effect” within the post-bottleneck population [1]. These changes in genotype frequency are an important driver of evolutionary change and speciation. In infection biology, bottlenecks shape genetic diversity of epidemics and have been shown to have an important influence on the effect of recombination and horizontal gene transfer, as well as the evolution of drug resistance [2–6]. Furthermore, bottlenecks may reduce pathogen virulence and adaptability to new hosts, as they increase the rate at which attenuating mutations become fixed in a population [7, 8]. Traditionally, population biologists have taken advantage of natural genetic variation to investigate transmission bottlenecks, eg, during HIV transmission (reviewed in [9]). In addition, with pathogens that contain or accumulate high amounts of genetic diversity over a small timescale, such as HIV, it is possible to investigate bottlenecks within a single host [5]. However, many pathogens do not possess sufficient natural genetic variation for quantification of bottlenecks in this setting. Measuring bottleneck sizes in animal models allows experimental access to valuable information regarding the anatomical sites, sizes, and causes of population restrictions, which can provide key insights into the nature of host–pathogen interactions. Here, we focus on recent new methods that rely on introduction of artificial genetic variation to quantify bottleneck events during experimental infection, enabling more precise understanding of pathogen population dynamics.