Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Abstract

Continuous culture methods enable cells to be grown under quantitatively controlled environmental conditions, and are thus broadly useful for measuring fitness phenotypes and improving our understanding of how genotypes are shaped by selection. Extensive recent efforts to develop and apply niche continuous culture devices have revealed the benefits of conducting new forms of cell culture control. This includes defining custom selection pressures and increasing throughput for studies ranging from long-term experimental evolution to genome-wide library selections and synthetic gene circuit characterization. The eVOLVER platform was recently developed to meet this growing demand: a continuous culture platform with a high degree of scalability, flexibility, and automation. eVOLVER provides a single standardizing platform that can be (re)-configured and scaled with minimal effort to perform many different types of high-throughput or multi-dimensional growth selection experiments. Here, a protocol is presented to provide users of the eVOLVER framework a description for configuring the system to conduct a custom, large-scale continuous growth experiment. Specifically, the protocol guides users on how to program the system to multiplex two selection pressures -- temperature and osmolarity -- across many eVOLVER vials in order to quantify fitness landscapes of Saccharomyces cerevisiae mutants at fine resolution. We show how the device can be configured both programmatically, through its open-source web-based software, and physically, by arranging fluidic and hardware layouts. The process of physically setting up the device, programming the culture routine, monitoring and interacting with the experiment in real-time over the internet, sampling vials for subsequent offline analysis, and post experiment data analysis are detailed. This should serve as a starting point for researchers across diverse disciplines to apply eVOLVER in the design of their own complex and high-throughput cell growth experiments to study and manipulate biological systems.

Optimal evolutionary control for artificial selection on molecular phenotypes

“…One class of experiments for artificial selection uses targeted mutations that are inferred to be beneficial, using machine learning techniques to characterize genotypephenotype maps [56]. Another class of experiments relies on implementing feedback control to tune artificial selection during continuous evolution of molecules and proteins, to direct them towards a desired target [17,18,[20][21][22]. For example, implementing proportional-integralderivative (PID) control [19], which is known for its role in cruise control during driving, has shown significant improvements for molecular optimization by directed con-tinuous evolution [22].…”

“…an experimental setup [17,18]. More recently, control protocols, such as proportional-integral-derivative control [19], have been experimentally implemented in highthroughput continuous directed evolution of proteins to automatically tune artificial selection based on the state of the population and optimize function [20][21][22]. Implementing optimal control in these automated and continuous directed evolution experiments will have significant impact in efficiently synthesizing molecules with desired function.…”

Environmental fluctuations reshape an unexpected diversity-disturbance relationship in a microbial community

“…For more precise tuning of dilution or other parameters, experimentalists have long relied on continuous culture methods (27,28,34); unfortunately, these systems have traditionally been intractable to large-scale, multidimensional experiments. Recently, we developed eVOLVER, a flexible and automated continuous culture platform that enables independent control over conditions in a large number of mini-bioreactors (35,36), thus opening up the possibility to explore microbial community dynamics under controlled, multidimensional environmental disturbances. By programming different dilution profiles with eVOLVER, we set out to independently quantify the effects of disturbance intensity and fluctuations on the composition and diversity of microbial communities.…”

“…Running eVOLVER Experiments eVOLVER lines were sterilized using 10% bleach and ethanol (35,36), then autoclaved vials were loaded with 23 mL of 0.1X NB. Each vial was inoculated with 1 mL of inoculum, and grown for 5 h at 25˚C with stirring prior to the first dilution disturbance.…”

Automated Continuous Evolution of Proteins in Vivo

“…Enter eVOLVER. eVOLVER is a versatile continuous culture platform that enables multiparameter control of growth selection conditions across independent microbial cultures 11,12 (Fig. 1b).…”