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Building a morbidostat: an automated continuous-culture device for studying bacterial drug resistance under dynamically sustained drug inhibition


We present a protocol for building and operating an automated fluidic system for continuous culture that we call the 'morbidostat'. The morbidostat is used to follow the evolution of microbial drug resistance in real time. Instead of exposing bacteria to predetermined drug environments, the morbidostat constantly measures the growth rates of evolving microbial populations and dynamically adjusts drug concentrations inside culture vials in order to maintain a constant drug-induced inhibition. The growth rate measurements are done using an optical detection system that is based on measuring the intensity of back-scattered light from bacterial cells suspended in the liquid culture. The morbidostat can additionally be used as a chemostat or a turbidostat. The whole system can be built from readily available components within 2–3 weeks by biologists with some electronics experience or engineers familiar with basic microbiology.

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Figure 1: The morbidostat is an automated continuous-culture device that maintains a constant level of growth inhibition on evolving bacterial populations.
Figure 2: Construction steps for morbidostat vial assembly.
Figure 3: Construction steps for tube holder assembly.
Figure 4: Circuit diagrams for the OD detection system.
Figure 5: Construction steps for pump array and medium reservoir assemblies.
Figure 6: Calibration of the detectors.

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The authors thank J. Horn, J. Marchionna, K. Reynolds and all members of the Kishony lab and Toprak lab for technical help and discussions. This work was supported in part by US National Institutes of Health grant no. R01 GM081617 (to R.K.), and by The New England Regional Center of Excellence for Biodefense and Emerging Infectious Diseases grant no. AI057159 (to R.K.). E.T. is supported by a Marie Curie Career Integration grant (no. 303786). J.M.P. and J.P. were supported by US National Institutes of Health grant no. R01 GM081563-04 and National Science Foundation grant no. DMS-074876-0.

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Authors and Affiliations



E.T., A.V., S.Y., R.C., J.M.P., J.P. and R.K. contributed to the design of the setup. E.T., A.V. and R.K. developed the assay and the algorithm for the morbidostat. E.T., A.V. and R.K. performed the experiments and analyzed the data. A.V. and S.Y. wrote the MATLAB code. E.T., A.V., S.Y., R.C., J.M.P., J.P. and R.K. wrote the manuscript.

Corresponding authors

Correspondence to Erdal Toprak or Roy Kishony.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Figure 1

Technical drawings for machining the custom components of tube holder array. Tube holders are machined from black Delrin or polycarbonate material. The adaptor plate and the cover plate are made from clear Plexiglass. All dimensions are in inches. (PDF 417 kb)

Supplementary Figure 2

Solid model of the tube holder array. A detailed drawing of the assembled tube holder array is shown. All components that are used in the tube holder array are numbered. Components required for the assembly, their quantities, and vendors are listed in the table. (PDF 5265 kb)

Supplementary Figure 3

Technical drawing of the pump holder array. The body of the pump holder rack is made from aluminum sigma profile (40mm x 40mm thickness) and commercially available assembly brackets. Threaded holes are opened on the sigma profiles for mounting the peristaltic pumps. (PDF 574 kb)

Supplementary Figure 4

Algorithm of the morbidostat software. Morbidostat algorithm runs three parallel timers. Using these timers OD values are acquired, data is periodically saved, and the dilution decisions are made and executed. Using the existing settings, morbidostat can be used also as a chemostat or turbidostat (PDF 1125 kb)

Supplementary Figure 5

Calibration algorithm of the morbidostat software illustrated. Calibrator function can be used directly from the GUI (gui.m). A glass vial filled with cell culture is used for converting voltage values read by the computer into OD values. OD of the sample is first measured with a standard OD reading device such as spectrophotometers. Culture vial is then placed into the tube holders and the median voltage on across the detector is recorded. This procedure is repeated for all tube holders using several dilutions of the cell culture. Typically 8-10 samples that are distributed between the 0.03-0.75 OD is enough for an accurate calibration. Use of different cell types or different media may need extra calibrations. (PDF 649 kb)

Supplementary Figure 6

User interface of the pump control software. All of the injection pumps and suction pump can be controlled using the interface shown. This feature is particularly useful for sterilization of the tubings. (PDF 451 kb)

Supplementary Data

Morbidostat control software and necessary files for executing the code. Supplementary Data contains several Matlab files and file folders that are necessary to execute the code. The folder named as “Numbers” includes the audio files used in calibrator.m. The folder named as “Images” includes images used for the control interface. The folder named as “background data” includes a sample data set that we use for correcting optical density readings by subtracting the background voltage values. The folder named as “calibration data” includes a sample data set we use to convert voltage readings to optical density values. (ZIP 90 kb)

Morbidostat control software is written in Matlab. Following Matlab files are provided: Calibrator.m, cleanMatlab.m, DataMonitor.m, DataReceiver.m, ExperimentController.m, gui.fig, gui.m, PumpController.m, and Simulator.m. ExperimentController.m, PumpController.m, DataReceiver.m, DataMonitor.m, Calibrator.m, and Simulator.m are Matlab classes that can be independently instantiated as objects. ExperimentController.m is the main class file that controls all timers and objects for running the morbidostat. PumpController.m is the class file that controls the pumps via relay boxes according to orders that it takes from the parent ExperimentController.m object or the manual commands given from MATLAB command window. DataReceiever.m is the class file that receives analog input from the data acquisition devices and converts the voltage readings to optical density values according to the calibration parameters. DataMonitor.m is the class file that monitors the real time data to the user as the experiment is running on.

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Toprak, E., Veres, A., Yildiz, S. et al. Building a morbidostat: an automated continuous-culture device for studying bacterial drug resistance under dynamically sustained drug inhibition. Nat Protoc 8, 555–567 (2013).

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