Methods for measuring the evolutionary stability of engineered genomes to improve their longevity

Abstract

Diverse applications rely on engineering microbes to carry and express foreign transgenes. This engineered baggage rarely benefits the microbe and is thus prone to rapid evolutionary loss when the microbe is propagated. For applications where a transgene must be maintained for extended periods of growth, slowing the rate of transgene evolution is critical and can be achieved by reducing either the rate of mutation or the strength of selection. Because the benefits realized by changing these quantities will not usually be equal, it is important to know which will yield the greatest improvement to the evolutionary half-life of the engineering. Here, we provide a method for jointly estimating the mutation rate of transgene loss and the strength of selection favoring these transgene-free, revertant individuals. The method requires data from serial transfer experiments in which the frequency of engineered genomes is monitored periodically. Simple mathematical models are developed that use these estimates to predict the half-life of the engineered transgene and provide quantitative predictions for how alterations to mutation and selection will influence longevity. The estimation method and predictive tools have been implemented as an interactive web application, MuSe.

Modelling genetic stability in engineered cell populations

“…While these experiments shed light on the workings of specific mutation mechanisms, they provide little insight into how evolution can be predicted a priori. More general and quantifiable approaches have resulted using deterministic models that define separate parameters for (i) the genetic stability of a synthetic construct and (ii) the selection pressures that act on the cells containing the construct 19 , 20 . Here, genetic stability is captured by assigning a parameter for the rate at which a function-disabling mutation occurs.…”

Inferring the disruption of rabies circulation in vampire bat populations using a betaherpesvirus-vectored transmissible vaccine

“…Unless the antigenic cargo of the vaccine causes severe detriment to the replication of the vector virus, full vaccine loss in an individual in this time frame seems unlikely. While inserted sequences are lost from virions in cell culture during passage ( 31 , 47 ), this process may be slower at the level of a whole organism given the possibility of viral compartmentalization within different tissues, protective effects of latency, and differences in selection pressures. Maintaining vaccine fitness and reducing any increased host immunity due to the presence of the vaccine antigen by selection of an appropriate region for antigen insertion into the vector genome will be important to consider.…”

Modelling genetic stability in engineered cell populations

“…A number of computational tools attempt to capture these phenomena [9–11], however they do not provide insight into the functional effect of mutations in the context of a growing cell – a prerequisite to capturing population-wide selection pressures. Using a different approach, the combined effect of genetic stability and selection pressure has been captured by more recent models that consider how disabling a genetic construct’s expression impacts cell growth rate [12, 13]. While this provides another layer of understanding, these models are ultimately constrained by the fact that they only describe single types of mutation, and account for changes to cell growth through a single fixed parameter.…”