Science Forum: A low-cost, open-source evolutionary bioreactor and its educational use

  1. Vishhvaan Gopalakrishnan  Is a corresponding author
  2. Dena Crozier
  3. Kyle J Card
  4. Lacy D Chick
  5. Nikhil P Krishnan
  6. Erin McClure
  7. Julia Pelesko
  8. Drew FK Williamson
  9. Daniel Nichol
  10. Soumyajit Mandal
  11. Robert A Bonomo
  12. Jacob G Scott  Is a corresponding author
  1. Lerner College of Medicine, Cleveland Clinic, United States
  2. Case Western Reserve University School of Medicine, United States
  3. Department of Translational Hematology and Oncology Research, Cleveland Clinic, United States
  4. Hawken School, United States
  5. Department of Physics, Case Western Reserve University, United States
  6. Department of Pathology, Massachusetts General Hospital, United States
  7. Department of Pathology, Brigham & Women’s Hospital, United States
  8. Cancer Program, Broad Institute of Harvard and MIT, United States
  9. Centre for Evolution and Cancer, Institute of Cancer Research, United Kingdom
  10. Integrated Circuits and Sensor Physics Lab, Case Western Reserve University School of Engineering, United States
  11. Louis Stokes Cleveland Department of Veteran Affairs Medical Center, United States
  12. Departments of Medicine, Pharmacology, Molecular Biology and Microbiology, Biochemistry, and Proteomics and Bioinformatics, Case Western Reserve University School of Medicine, United States
  13. CWRU-Cleveland VAMC Center for Antimicrobial Resistance and Epidemiology, United States
  14. Department of Radiation Oncology, Cleveland Clinic, United States

Abstract

A morbidostat is a bioreactor that uses antibiotics to control the growth of bacteria, making it well-suited for studying the evolution of antibiotic resistance. However, morbidostats are often too expensive to be used in educational settings. Here we present a low-cost morbidostat called the EVolutionary biorEactor (EVE) that can be built by students with minimal engineering and programming experience. We describe how we validated EVE in a real classroom setting by evolving replicate Escherichia coli populations under chloramphenicol challenge, thereby enabling students to learn about bacterial growth and antibiotic resistance.

Introduction

The first bioreactor, the chemostat, was built over 70 years ago to study the growth of bacteria suspended in a liquid medium (Novick and Szilard, 1950). In particular, the chemostat maintains the specific growth rate of the bacteria at a fixed value by supplying fresh medium and removing unused nutrients, cells and metabolic byproducts. Studies performed with chemostats and other bioreactors made various physiological and biochemical analyses more tractable and led to the development of quantitative models that describe microbial growth (Hoskisson and Hobbs, 2005).

The morbidostat is a bioreactor that maintains a steady death rate. Specifically, a morbidostat regulates the bacterial growth rate by measuring the cell density of a population at fixed time intervals and subsequently introducing factors that cause the growth rate to increase (such as nutrient-rich media) or factors that cause the growth rate to decrease (such as antibiotic-rich media). Antibiotics are introduced into the medium when the population size exceeds a predetermined threshold and the growth rate is greater than zero. The morbidostat, therefore, adjusts the selective pressure to maintain near-constant growth inhibition as the population becomes resistant to the antibiotics over time. Studies performed with morbidostats have improved our understanding of the evolution of antibiotic resistance in bacteria (Toprak et al., 2012; Dößelmann et al., 2017; Yoshida et al., 2017; Leyn et al., 2021) and the temperature-stress response in yeast (Wong et al., 2018).

Introducing the morbidostat into high-school or college curricula has many benefits. First, educators often use passive, lecture-based instruction to teach gradual long-term species evolution. In contrast, in-classroom morbidostat use enables inquiry-based research where students combine hypothesis generation and experimental design with measurement of real-time adaptation of microbial populations. This active learning approach improves student understanding of bacterial growth and how natural selection acts on heritable genetic variation to promote drug resistance (Freeman et al., 2014; Tomandl et al., 2015). In the context of biology classes, the use of a morbidostat in the classroom complements existing inquiry-based laboratory curricula (Cooper et al., 2019). Second, constructing a morbidostat will teach students critical engineering and computer programming skills.

We have developed a low-cost open-source morbidostat called the EVolutionary biorEactor (EVE) with these goals in mind. Our platform, which builds on the methodology outlined by Toprak and colleagues (Toprak et al., 2012; Toprak et al., 2013), supports multiple culture units that each run independently with precise control over exchange of the growth medium, cell density measurement rates, and drug addition. EVE costs about $115–200 to construct using printed circuit board (PCB) and 3D-printed component files; circuit diagrams, software and complete build instructions are available in our GitHub repository (Gopalakrishnan, 2022).

In this article we discuss the design and construction of EVE. We also describe how high school students in a class taught by one of the authors (LDC) used it to study the growth of bacteria and the evolution of antibiotic resistance, demonstrating that EVE is an accessible alternative to other bioreactors for use in low-resource classrooms, and in settings where instructors and students have limited engineering and programming experience.

The EVolutionary biorEactor

The EVE is functionally similar to other small, automated bioreactors (Toprak et al., 2012; Dößelmann et al., 2017; Wong et al., 2018). In summary, several bacterial cultures are grown simultaneously in small glass vials under well-mixed, drug-selective conditions (Figure 1A). A control algorithm maintains these conditions by: (i) supplying power to fans (with attached magnets) that rotate magnetic stir bars; (ii) introducing fresh medium into each culture at a constant rate through the activation of peristaltic pumps; (iii) monitoring population growth via absorbance measurements taken from paired light-emitting and photo-sensitive diodes; (iv) introducing selective medium when these absorbance measurements exceed a user-defined value. Nonetheless, the EVE differs from other bioreactors in its hardware, software, and production costs. We detail these aspects below.

The EVolutionary bioreactor (EVE).

Schematic illustration of the EVE hardware and software architecture. (A) Reservoirs containing permissive (i.e., drug-free) and selective growth media are each connected to a culture unit (CU) through silicone tubing. Peristaltic pumps control the rate at which the media are added to the evolving bacterial population, and an additional pump removes waste. Multiple CUs can fit into an incubator, allowing users to simultaneously evolve several independent replicate populations. (B) A Raspberry Pi interfaces with a custom printed circuit board (PCB) to monitor culture growth and coordinate the addition and removal of growth media and waste. The user controls the EVE hardware with a web application. (C) The PCB chips measure voltage and temperature. These voltage measurements are proportional to optical density and thus are a way to estimate population size. The chips also control the fluidic pumps, diodes, onboard indicators, and stirring speed. The PCB diagram illustrates where these chips are located on the board.

Hardware and software

The EVE uses a primary onboard Raspberry Pi microcomputer to execute the software and serve as a bridge between the user interface and a PCB (Figure 1B, C). This design keeps costs low while allowing the device to be self-contained in environments without internet access. One can also construct the EVE with a breadboard. Breadboards give users more flexibility to modify the hardware but require prior experience and come at the cost of increased assembly time and device footprint. In either case, circuit diagrams, 3D-printed component files, complete build instructions, and a part list are in our GitHub repository (Gopalakrishnan, 2022).

One may access population growth and temperature measurements, edit configuration files, define experimental parameters, and monitor and control experiments remotely with our free, open-source software run inside any web browser. Users install this software by downloading the pre-compiled Raspberry Pi image or executing the installation script directly from our GitHub repository. Data can be saved to network locations mounted to the Pi’s file system or an attached USB device.

Comparisons to alternative bioreactors

The EVE differs from other bioreactors, including the eVOLVER (Wong et al., 2018) and Flexostat (Takahashi et al., 2014), in its design philosophy and customization capabilities. The EVE and eVOLVER software are hosted on a Raspberry Pi and written in Python, a common programming language with a broad user base and community support. This combination of hardware and software allows for fast code execution and the Linux operating system facilitates customization. In contrast, other automated culture systems use proprietary or third-party software that may be inaccessible or cost-prohibitive for educators (Toprak et al., 2012).

One does not need to be familiar with Python to install the software, edit experimental parameters, or run the pre-configured control algorithms. However, working knowledge of this language is necessary to create custom algorithms, for which we uniquely provide design instructions in our GitHub repository. Moreover, the EVE uses a more modern serial connection between the motherboard and the Pi than the eVOLVER, which permits the use of more up-to-date software packages. Lastly, the Flexostat and the EVE have a similar broadly open software license that permits unrestricted use of the software.

Production cost

We designed the EVE to be cost-effective. The total cost varies between $115 and $200 to build a system that performs simple growth or evolution experiments in triplicate with a negative control. These estimates include all parts except the incubator, glassware, and 3D printer. The circuit board design can be downloaded from our repository and sent to a PCB manufacturer for printing and assembly; in our case, we purchased fully assembled PCBs for approximately $42 per board, including the power supply. Users may further decrease costs and increase accessibility in low-resource classrooms by incubating bacterial cultures at room temperature and using a pressure cooker to sterilize growth media instead of an autoclave.

Validation

We validated the EVE in two ways. First, we examined voltage measurement variability across seven independent culture units and compared these results with previously reported measurements (Toprak et al., 2012). Voltage is the raw measurement that is used to estimate optical density (i.e., population size). Smaller voltage measurement variability between individual culture units indicates better construct and internal validity. Variability in measurements is introduced due to subtle differences when printing the vial holder, leading to slightly altered positioning of the diodes responsible for voltage measurements. The average variability was 8.0% (mean ± sd = 2.93±0.23), comparable to the 7.5% of Toprak and colleagues.

Second, we experimentally evolved bacterial populations and again compared the results to those of Toprak et al., 2012. We revived E. coli ATCC 25922 from a frozen stock by overnight growth in Mueller-Hinton broth (MHB) (Sigma). We inoculated 100 µL of this culture into three separate culture units containing 12 mL of MHB. We then prepared the selective growth medium by diluting a chloramphenicol stock solution to 40 µg/mL in MHB. The selective and permissive media were connected to the culture units, which were incubated at 37 °C with constant stirring (∼225 rpm). Samples were taken from each culture’s effluent waste every 12 hours and frozen at –80 °C with 15% glycerol as a cryoprotectant.

We estimated each sample’s half-maximal inhibitory concentration (IC50) following the broth microdilution method (Wiegand et al., 2008) and by fitting a Hill function to the resulting optical density data (Maltas and Wood, 2019). The three ancestral populations began the experiment with an IC50 of 4 µg/mL, and chloramphenicol resistance increased to 9.3–13.9 µg/mL. These results are comparable to Toprak et al., 2012, where resistance increased, on average, to approximately 15 µg/mL over the same time period (Figure 2).

The evolution of chloramphenicol resistance over time.

Half-maximal inhibitory concentration (IC50) values for two biologically independent replicates (CU1 and CU2) are plotted against time. Points represent the estimated IC50 determined by fitting a Hill function to OD600 measurements across this dilution series after 18 hours of population growth. Error bars represent the variance in IC50. The data used to generate this figure are available in our Github repository: https://github.com/vishhvaan/eve-pi (Gopalakrishnan, 2022).

Educational use

The EVE is well-suited for classroom settings because it was designed in collaboration with educators and tested by high school students at Hawken School in Gates Mills, Ohio. We discuss our curriculum design, the students’ experience using the EVE, and its potential applications in other educational contexts.

We first examined the Advanced Placement (AP) Biology curriculum and then developed a pilot curriculum for the evolutionary unit of the course that detailed the desired learning outcomes, assessment evidence for those outcomes, and a learning plan (see Supplementary file 1). The AP curriculum introduces several key learning objectives about the importance of phenotypic variation, how natural selection acts on this variation, and how this phenomenon affects populations over time. The AP instructional model also emphasizes that students use supporting resources and perform appropriate experiments to build and strengthen their conceptual understanding of these objectives. More generally, for most biology classrooms, bioreactor experiments introduce basic microbiology techniques, biotechnology, and data analysis to students. We therefore developed our unit to facilitate student understanding of population growth dynamics and trait evolution through independent experimentation with the EVE. To reinforce this objective, we asked the students to consider how bacterial populations respond to changing environments, such as introducing antimicrobial agents.

Two high school students followed the instructions in our GitHub repository (Gopalakrishnan, 2022) to assemble the EVE bioreactor with 3D-printed equipment, a fabricated circuit board, and a Raspberry Pi microcomputer with the necessary pre-installed software. Then two AP Biology students, working as a team, calibrated the device (Figure 3) and evolved a population of E. coli ATCC 25922 to increasing chloramphenicol concentrations over several days (Figure 4A–G). The population initially expanded in size, decreased after the introduction of the antibiotic into the culture unit, and later rebounded as drug-resistant variants rose in frequency (Figure 4G). From these data, the students calculated growth rates and predicted how these rates would change with varying drug selective pressures. This authentic research experience introduced the students to standard microbiology practices and concepts, including how to prepare drug solutions and use sterile technique to maintain bacterial cultures, when logistic growth models apply, and the relationship between light absorbance and cell number (i.e., Beer’s law). We share testimonials from these students in Box 1.

Calibration of culture optical density with reported voltage.

(Top) Culture units behave similarly when measuring voltage. (Bottom) Various regression methods were used to quantify the relationship between the optical density (OD) and voltage. R2 values of 0.97, 0.99, and 0.99 were calculated for the linear, quadratic, and cubic fits respectively. We used a linear model to translate voltage to optical density in our experiments.

High school students at Hawken School built the EVE and performed an evolution experiment.

(A) Prior to experimentation, the students practiced pipetting with media. (B) They prepared the selective growth medium and (C) inoculated E. coli into a culture unit containing the permissive medium. (D) The system was sterilized with bleach and ethanol solutions. (E) Before the experiment, the students printed a culture unit stand in the maker-space at Hawken School. (F) The media and waste reservoirs were attached to the culture unit by silicon tubing, and then (G) the students began the experiment. (H) Bacterial growth and inhibition in the EVE over 28 hours. The grey boxes and vertical lines indicate when the EVE control algorithm added the permissive and selective media into the culture units, respectively.

Box 1

Testimonials from students.

The bioreactor experiment was a very valuable learning experience. Learning the evolution of bacterial growth against drug resistance deepened my understanding of the wonders of the evolution unit in my current biology class. Through our hands-on experience, I have learned many new terms and biotechnology techniques including pipetting, working with bacterial cultures, and learning the Beer’s Law. This was a complex but also at the same time simple lab to do, and I think it would definitely be beneficial for students to learn more about bacterial evolution and practice important skills such as calculating concentrations and analyzing data.

— Lillian Fu.

The Bioreactor experiment was very informational for me; I learned how bacterial growth works and how drug resistance plays a role in it through my first-hand experience with being able to actually work with the bacterial cultures, drugs, pipettes, and EVE. I think this was a fun project to do, and it would definitely be an easy and helpful project for other high school students to do while learning about bacterial growth and evolution. Students can also utilize and strengthen skills such as analyzing data and calculating different concentrations. Overall, I think this project was accessible and simple but still very interesting and informative.

— Grace Shum.

Notably, the students adjusted the experimental protocol to account for classroom limitations. For example, the Hawken School does not have Bunsen burners or standing incubators. The students therefore created a spartan workspace and disinfected all surfaces with 70% ethanol, visually inspected the growth medium to ensure that it remained free of contamination, and incubated bacterial cultures in an oven set to approximately 30–40ºC. Moreover, although this particular high school has autoclaves, there are several alternative ways that users can sterilize glassware and media, including using liquid chemicals and microwaves. The Centers for Disease Control and Prevention describe some of these methods in greater detail (https://www.cdc.gov/infectioncontrol/guidelines/disinfection/sterilization/other-methods.html).

One could also use the EVE in other educational contexts (i.e., college laboratory classrooms) or outside the classroom. Since the EVE functions through a combination of engineering and biology, project work within clubs may offer unique experiences to students wishing to learn about how multiple disciplines interact. These projects could combine construction and experimentation for a seamless educational experience. Interested parties may acquire non-pathogenic E. coli K12, growth medium, and antibiotic powders through the Carolina Biological Supply Company or a similar vendor.

The EVE has also been implemented in several other contexts. For instance, the EVE is being used to study bacteriophages in continuous culture at the University of Exeter in the United Kingdom, and to develop research bioreactors at a French biotech company. Additionally, undergraduate students used its design to build their own custom morbidostat as part of the International Genetically Engineered Machine (iGEM) competition. The manual produced by these students represents an example of what the EVE would look like in a college setting (https://static.igem.org/mediawiki/2019/c/c6/T--Athens--Morbidostat_manual.pdf).

Future directions and conclusion

In addition to its educational utility, the EVE can address questions of evolutionary repeatability. For instance, one might examine whether correlated drug responses are conserved across time as populations evolve under single- or multi-drug selection (Nichol et al., 2015; Nichol et al., 2019; Card et al., 2021; Iram et al., 2021; King, 2022). Although the current EVE system can only introduce one drug solution into the growth medium, we are designing a PCB to allow the simultaneous or sequential addition of multiple drugs across more replicate cultures. Moreover, users could substitute the existing hardware with LEDs and photodiodes corresponding to fluorescence proteins’ excitation and emission frequencies. This hardware alteration would allow bacterial head-to-head competitions without periodic sampling and cell enumeration.

The EVE device has several limitations, some of which we will address with additional design and hardware improvements. Although one could buy 3D-printed parts from several internet vendors, the need of a 3D printer may still restrict use in resource-limited classrooms. Future implementations will include alternative hardware construction methods that preclude the need for a 3D printer and thus lower indirect costs. Second, the EVE may require slightly more setup than a pre-constructed and calibrated commercially available bioreactor. For example, fluid pumps may vary in flow rate; thus, they must be individually calibrated to avoid accidental overflow. Although there is educational value in solving hardware and software challenges, especially in a classroom setting, we encourage individuals to use EVE’s GitHub repository to report challenges and potential solutions. We will also continue to work on automated solutions to mitigate these setup tasks for the user.

In summary, we believe that EVE is uniquely suited for use in educational settings because of its low-cost and open-source design. High school students demonstrated these aspects by building the EVE and performing a simple evolution experiment in the classroom. We are optimistic about a future where more classrooms use the EVE and other platforms to spur student interest in experimental biology and technology.

Data availability

We provide the materials to build an EVE in our Github repository: https://github.com/vishhvaan/eve-pi (copy archived at swh:1:rev:92c8be59379f42bf9e210270704456b1d02f0e44). We have also included the data to generate Figure 2 on the Github.

References

Decision letter

  1. Peter Rodgers
    Senior and Reviewing Editor; eLife, United Kingdom

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Decision letter after peer review:

Thank you for submitting your article "A Low-Cost, Open Source, Self-Contained Bacterial EVolutionary biorEactor (EVE)" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Patricia Wittkopp as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Vaughn S Cooper (Reviewer #1).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision in consultation with the Senior Editor.

The editors have judged that your manuscript is of interest, but as described below much additional work is needed to make it suitable for publication in eLife. We suspect that these changes will require more than the 2 months typically allowed for revisions, so are rejecting the paper in its current form. We are, however, very interested in seeing a revised version that addresses the reviewers concerns. In fact, the journal is currently considering adding a new category to its Features section focusing on education and outreach, and we think this work would be a good fit for that format. We share the author's passion for finding ways to bring experimental systems into high-schools and think that the changes requested below will make adoption more likely.

Summary:

This article introduces a flexible continuous culture device built with open source hardware and based on readily (and cheaply) available hardware. The paper also presents a proof of concept using antibiotic selection to demonstrate the ability to use feedback control. The manuscript claims it can replicate the functionality of more elaborate and expensive reactors on the market and thus enable students to build their own devices and conduct their own research. However, no such data are presented to substantiate these claims, either to demonstrate the performance of the device relative to the competing standards or to show its usability by less trained students.

Essential revisions:

1) Provide evidence for the first claim: present data that shows that the bioreactor works and provides useable data and compare the bioreactor's result to other currently available reactors. While we don't expect that the authors purchase expensive reactors for these comparisons themselves, they should compare their findings with the product specs of others. How variable are the replicates, typically? What are key issues to be cautious with? Are the parts easy to come by, even though they are cheap?

2) Show ease of use, e.g. by providing the parts of a bioreactor together with a manual to a number of college or high school classes, and ask them to build the reactor and perform a simple experiment. They could then report the data on how many classes were able to do this, and how the data compares with a reference experiment. Even several anecdotal examples of it being used in non-traditional lab settings? The more of these the better! Please also add a photograph of the device.

3) Regarding educational use -- what would they learn? What are the learning objectives for experiments based on this setup?

4) Who is the target user, and what must they know to succeed?

5) What kinds of experiments would this target user ideally conduct?

6) We would like to know more specifically how this method advances your research, and think a research advance (rather than Amp killing E coli) would be the use case that proves its merit.

7) Figure 2 is hard to follow, and without some effort. The letter labels are placed oddly for my preference, a border around the subfigures might make that easier. It took a little bit of time to figure out what I was looking at in b) with regard to the concentration and the voltage. I also didn't see the data from b) in c) but was expecting to.

8) There is no data that suggests that drug concentrations can be set to a desired and reliable level. Please provide.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting the revised version of your article "A low-cost, open-source evolutionary bioreactor and its educational use" to eLife for consideration as a Feature Article. I sent the revised version of the article to the three reviewers who reviewed the original version and their comments are below. As you will see, there are still a small number of points you need to address. The following individuals involved in review of your submission have agreed to reveal their identity: Vaughn Cooper.

Summary

This paper presents the author's low-cost continuous culture device EVE. It presents a case study of this device as a morbidostat, and its use within a high school AP Biology lesson. The stated goal is to show how this open source device is a viable alternative to other more expensive or cumbersome technology. This is a great idea and the method is impressive. However, there are a number of points that need to be addressed to make the article suitable for publication.

Essential revisions:

1. Evidence for the efficacy of the program is anecdotal: how well did students learn AP material?

2. Please say more about the challenges of implementation and any potential limitations of this approach/device.

3. Please say more about other options (e.g., eVOLVER, Flexostat, commercial bioreactors) and how EVE compares to them. What are the benefits and/or unique features of EVE compared with other options.

https://doi.org/10.7554/eLife.83067.sa1

Author response

Summary:

This article introduces a flexible continuous culture device built with open source hardware and based on readily (and cheaply) available hardware. The paper also presents a proof of concept using antibiotic selection to demonstrate the ability to use feedback control. The manuscript claims it can replicate the functionality of more elaborate and expensive reactors on the market and thus enable students to build their own devices and conduct their own research. However, no such data are presented to substantiate these claims, either to demonstrate the performance of the device relative to the competing standards or to show its usability by less trained students.

We thank the reviewers for raising this point. We have now addressed this concern in two ways. First, we replicated an experiment from Toprak et al. (2012) by challenging replicate E. coli populations to increasing chloramphenicol concentrations over time. We detail this work and our confirmatory results in a new Validation section. Second, we introduced the EVE into a high school classroom setting. The students constructed the device from available parts and experimentally evolved a bacterial population. We have now included a new section (Educational Use) detailing their experience.

Essential revisions:

1) Provide evidence for the first claim: present data that shows that the bioreactor works and provides useable data and compare the bioreactor's result to other currently available reactors. While we don't expect that the authors purchase expensive reactors for these comparisons themselves, they should compare their findings with the product specs of others. How variable are the replicates, typically? What are key issues to be cautious with? Are the parts easy to come by, even though they are cheap?

To address this concern, we replicated an experiment from Toprak et al. 2011. We used the EVE to evolve three replicate populations over 4.5 days to dynamically increasing chloramphenicol concentrations. Our results were qualitatively similar to those in Figure 2 of their paper. For instance, the magnitude of resistance increases from the drug-susceptible E. coli ancestors (MG1655 in their case and ATCC 25922 in ours) was roughly the same over the same period. We report our results in the new Validation section.

2) Show ease of use, e.g. by providing the parts of a bioreactor together with a manual to a number of college or high school classes, and ask them to build the reactor and perform a simple experiment. They could then report the data on how many classes were able to do this, and how the data compares with a reference experiment. Even several anecdotal examples of it being used in non-traditional lab settings? The more of these the better! Please also add a photograph of the device.

We thank the reviewers for this suggestion and have reframed the manuscript to emphasize the EVE’s educational utility. We provided hardware and instructions to high school students and asked them to build the EVE and perform simple growth and evolution experiments. We detail these efforts in our new Educational Use section, as follows (page 5):

“Two high school students followed the instructions in our GitHub repository to assemble the EVE bioreactor with 3D-printed equipment, a fabricated circuit board, and a Raspberry π microcomputer with the necessary pre-installed software. Then three AP Biology students, working as a team, calibrated the device and evolved a population of E. coli ATCC 25922 to increasing chloramphenicol concentrations over several days.”

Moreover, we have included several examples of EVE’s use in other non-traditional settings (page 7):

“The EVE has been implemented in several laboratories and classrooms throughout the world. For instance, the EVE is being used to study bacteriophages in continuous culture at the University of Exeter, and used to develop research bioreactors in a French biotech company. Undergraduate students used its designs to build their own custom morbidostat as part of the International Genetically Engineered Machine (iGEM) competition. Their manual represents an example of what the EVE would look like in a college setting.”

Lastly, we added a schematic illustration of the device (Figure 1) and photos of the high school experimental setup (Figure 3).

3) Regarding educational use -- what would they learn? What are the learning objectives for experiments based on this setup?

We collaborated with Dr. Lacy Chick (now a co-author on our revised manuscript) to address this issue. Dr. Chick is a high school biology teacher at the Hawken School in Gates Mills, Ohio. She has experience in curriculum design, including developing unit plans for AP and general biology courses. With her expertise, we co-developed a unit plan with essential questions and goals centered on the EVE. These documents are now included in the supplementary materials. Moreover, we added several sentences to the Educational Use section (page 5):

“We first examined the Advanced Placement (AP) Biology curriculum and developed a unit plan to complement this program. The AP curriculum introduces several key learning objectives about the importance of phenotypic variation, how natural selection acts on this variation, and how this phenomenon affects populations over time. The AP instructional model also emphasizes that students use supporting resources, and perform appropriate experiments, to build and strengthen their conceptual understanding of these objectives. More generally, for most biology classrooms, experiments with a bioreactor introduce basic microbiology techniques, biotechnology, and data analysis.”

4) Who is the target user, and what must they know to succeed?

We are targeting academic users and students. In the manuscript we present possibilities for both groups. Instructions and materials to construct the device are in our Github repository.

5) What kinds of experiments would this target user ideally conduct?

We now include a Future Directions section that highlights two possibilities (page 7):

“In addition to its educational utility, the EVE is an ideal system to address questions of evolutionary repeatability. For instance, one might examine whether correlated drug responses are conserved across time as populations evolve under single- or multi-drug selection. Although the current EVE system can only introduce one drug solution into the growth medium, we are currently designing a PCB that will allow the simultaneous or sequential addition of multiple drugs. Second, users could substitute the existing hardware with LEDs and photodiodes corresponding to fluorescence proteins’ excitation and emission frequencies. This hardware alteration would allow bacterial head-to-head competitions without periodic sampling and cell enumeration.”

Students could perform evolution experiments, as was done in this manuscript, or even simple bacterial growth experiments.

6) We would like to know more specifically how this method advances your research, and think a research advance (rather than Amp killing E coli) would be the use case that proves its merit.

We now focus on the EVE’s educational value, and therefore we place less emphasis on how the device advances our research. However, we include two possible future studies that our device would be well-suited for.

7) Figure 2 is hard to follow, and without some effort. The letter labels are placed oddly for my preference, a border around the subfigures might make that easier. It took a little bit of time to figure out what I was looking at in b) with regard to the concentration and the voltage. I also didn't see the data from b) in c) but was expecting to.

We have removed this figure from the manuscript.

8) There is no data that suggests that drug concentrations can be set to a desired and reliable level. Please provide.

We have removed this claim.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Essential revisions:

1. Evidence for the efficacy of the program is anecdotal: how well did students learn AP material?

Because this pilot program was a special project within the overarching AP curriculum, two students constructed and used the EVE to perform the evolution experiment. Therefore, we decided to focus on the students’ qualitative experiences through testimonials, as formal statistics on a small sample size would be less meaningful. Nevertheless, we agree that collecting quantitative data which compares student performance on evolution-related test questions or qualitative pre- and post-experiment surveys evaluating self-reported learning would be invaluable outcomes to gather in the future. As we perform further investigations on how the EVE can fit into bigger and more diverse classrooms, we will be sure to gather this outcome data.

2. Please say more about the challenges of implementation and any potential limitations of this approach/device.

We have added this paragraph to the Future Directions section to address limitations:

“The EVE device has several limitations, some of which we will address with additional design and hardware improvements. Although one could buy 3Dprinted parts from several internet vendors, the need of a 3D printer may still restrict EVE’s use in resource-limited classrooms. Future implementations will include alternative hardware construction methods that preclude the need for a 3D printer and thus lower indirect costs. Second, the EVE may require slightly more setup than a pre-constructed and calibrated commercially available bioreactor. For example, fluid pumps may vary in flow rate; thus, they must be individually calibrated to avoid accidental overflow. Although there is educational value in solving hardware and software challenges, especially in a classroom setting, we encourage individuals to use EVE’s GitHub repository to report challenges and potential solutions. We will also continue to work on automated solutions to mitigate these setup tasks for the user.”

3. Please say more about other options (e.g., eVOLVER, Flexostat, commercial bioreactors) and how EVE compares to them. What are the benefits and/or unique features of EVE compared with other options.

We added a section called Comparisons to Alternative Bioreactors under the Hardware and Software section. This section addresses alternative bioreactors and where the EVE differs:

“The EVE differs from other bioreactors, including the eVOLVER and Flexostat, in its design philosophy and customization capabilities. The EVE and eVOLVER software are written in Python, a common programming language with a broad user base and community support, and hosted on a Raspberry π microcomputer. This combination of hardware and software allows for fast code execution and a Linux operating system that enables customization. In contrast, other automated culture systems use proprietary or third-party software that may be inaccessible or cost-prohibitive for educators. One does not need to be familiar with Python to install the software, edit experimental parameters, or run the pre-configured control algorithms. However, working knowledge of this language is necessary to create custom algorithms, for which we uniquely provide design instructions in our GitHub repository. Moreover, the EVE uses a more modern serial connection between the motherboard and the π than the eVOLVER, which permits the use of more up-to-date software packages. Lastly, the Flexostat and the EVE have a similar broadly open software license that permits unrestricted use of the software.”

https://doi.org/10.7554/eLife.83067.sa2

Article and author information

Author details

  1. Vishhvaan Gopalakrishnan

    Vishhvaan Gopalakrishnan is in the Lerner College of Medicine, Cleveland Clinic, Cleveland, United States

    Contribution
    Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing
    Contributed equally with
    Dena Crozier and Kyle J Card
    For correspondence
    vxg135@case.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0532-7710
  2. Dena Crozier

    Dena Crozier is in the Lerner College of Medicine, Cleveland Clinic, and the Case Western Reserve University School of Medicine, Cleveland, United States

    Contribution
    Formal analysis, Validation, Investigation, Visualization, Writing – review and editing
    Contributed equally with
    Vishhvaan Gopalakrishnan and Kyle J Card
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1841-0011
  3. Kyle J Card

    Kyle J Card is in the Department of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, United States

    Contribution
    Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing – review and editing
    Contributed equally with
    Vishhvaan Gopalakrishnan and Dena Crozier
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0462-2777
  4. Lacy D Chick

    Lacy D Chick is at Hawken School, Gates Mills, United States

    Contribution
    Resources, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3059-4300
  5. Nikhil P Krishnan

    Nikhil P Krishnan is at Case Western Reserve University School of Medicine, Cleveland, United States

    Contribution
    Conceptualization, Software, Formal analysis, Investigation
    Competing interests
    No competing interests declared
  6. Erin McClure

    Erin McClure is in the Department of Translational Hematology and Oncology, Research, Cleveland Clinic, Cleveland, United States

    Present address
    University of South Florida Morsani School of Medicine, Tampa, United States
    Contribution
    Validation, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6604-1273
  7. Julia Pelesko

    Julia Pelesko is in the Department of Translational Hematology and Oncology Research, Cleveland Clinic, and the Department of Physics, Case Western Reserve University, Cleveland, United States

    Contribution
    Investigation
    Competing interests
    No competing interests declared
  8. Drew FK Williamson

    Drew FK Williamson is in the Department of Pathology, Massachusetts General Hospital, Boston, the Department of Pathology, Brigham & Women’s Hospital, Boston, and the Cancer Program, Broad Institute of Harvard and MIT, Cambridge, United States

    Contribution
    Conceptualization, Software, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1745-8846
  9. Daniel Nichol

    Daniel Nichol is in the Centre for Evolution and Cancer, Institute of Cancer Research, London, United Kingdom

    Contribution
    Conceptualization
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2662-1836
  10. Soumyajit Mandal

    Soumyajit Mandal is in the Integrated Circuits and Sensor Physics Lab, Case Western Reserve University School of Engineering, Cleveland, United States

    Present address
    Department of Electrical and Computer Engineering, University of Florida, Gainesville, United States
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  11. Robert A Bonomo

    Robert A Bonomo is in the Louis Stokes Cleveland Department of Veteran Affairs Medical Center, Cleveland, United States; the Departments of Medicine, Pharmacology, Molecular Biology and Microbiology, Biochemistry, and Proteomics and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, United States; and the CWRU-Cleveland VAMC Center for Antimicrobial Resistance and Epidemiology, Cleveland, United States

    Contribution
    Conceptualization
    Competing interests
    No competing interests declared
  12. Jacob G Scott

    Jacob G Scott is in the Department of Translational Hematology and Oncology Research, Cleveland Clinic, the Department of Physics, Case Western Reserve University, and the Department of Radiation Oncology, Cleveland Clinic, Cleveland, United States

    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Project administration, Writing – review and editing
    For correspondence
    scottj10@ccf.org
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2971-7673

Funding

No external funding was received for this work.

Senior and Reviewing Editor

  1. Peter Rodgers, eLife, United Kingdom

Publication history

  1. Preprint posted: August 9, 2019 (view preprint)
  2. Received: August 30, 2022
  3. Accepted: October 20, 2022
  4. Accepted Manuscript published: November 1, 2022 (version 1)
  5. Version of Record published: November 23, 2022 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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  1. Vishhvaan Gopalakrishnan
  2. Dena Crozier
  3. Kyle J Card
  4. Lacy D Chick
  5. Nikhil P Krishnan
  6. Erin McClure
  7. Julia Pelesko
  8. Drew FK Williamson
  9. Daniel Nichol
  10. Soumyajit Mandal
  11. Robert A Bonomo
  12. Jacob G Scott
(2022)
Science Forum: A low-cost, open-source evolutionary bioreactor and its educational use
eLife 11:e83067.
https://doi.org/10.7554/eLife.83067
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