The authors would like to thank Prof. Sze-Bi Hsu and Ms. Zhenzhen for useful discussions and help in the theoretical analysis and numerical simulation. Y. T. Y. would like to acknowledge funding support from the Ministry of Science and Technology under grant numbers MOST 103-2220-E-007-026 and MOST 104-2220-E-007-011, and from the National Tsing Hua University under grant numbers 103N2042E1, 104N2042E1, and 105N518CE1.

1. Assembly and Pretesting of the Morbidostat Device
<ol>
	<li>Assembly of the Morbidostat
	<ol>
		<li>Punch 3 holes on the cap of the culture vial with an 18 G syringe needle. Cut three pieces of polyethylene tubing ~7 cm in length. Insert these three pieces of polyethylene tubing on the cap.</li>
		<li>Use tape to wrap the edge of the cap to serve as the cast for the polydimethylsiloxane (PDMS) mixture. Mix 5 g of A component and 0.5 g of B component of the PDMS in a 150 ml plastic container by stirring manually with a toothpick. Load the mixture into a 10 ml syringe.
		<ol>
			<li>Pour the PDMS mixture on the cap with the syringe. Bake the entire cap to cure the PDMS for 8 hr in the oven at 70 &#176;C.</li>
		</ol>
		</li>
		<li>Solder the LED anode with the 24 gauge wire and LED cathode with the carbon resistor with a soldering iron. Solder a 680&#160;&#937; carbon resistor with a 24 G wire. Insulate the wire connection using electrical tape.</li>
		<li>Solder the collector of the photodetector with the 24 G wire and the emitter of the photodetector with a 100 k&#937; carbon resistor. Insulate the wire connection using electrical tape.</li>
		<li>Place the light emitting diode in the culture vial holder. By following the circuit diagram in Supplementary Figure 2, connect the light emitting diode and power it with a power supply of 5 V. Ensure that the LED works by using a digital camera that can detect IR (e.g., a mobile phone camera).</li>
		<li>Place the photodetector in the culture vial holder. By following the circuit diagram in Supplementary Figure 2, connect the photodetector and power it with a power supply of 5 V. Connect the wire to both sides of the photodetector resistors to measure the voltage across the electronic control board.</li>
		<li>Glue a magnet on the shaft of the cooling fan, which serves as the magnetic stirrer unit. Note that the alignment of the shaft of the fan to the culture vial, and the spacing between the culture vial and the magnet is very critical for the proper function of the magnetic stirring unit.</li>
		<li>Connect each piece of polyethylene tubing of the culture vial into the corresponding piece of silicone tubing for the micro-pumps, medium bottles, and waste bottle. Turn on the pump for 1 hr and measure the total volume being pumped from the medium bottle to the culture vial to determine the pump rate. Note that the typical pumping rate should be ~4 ml/hr, which corresponds to the dilution rate D = 0.33 hr&#8722;1 for a 12 ml working volume of the culture vial.</li>
		<li>Place the whole assembly on a mid-sized (34 cm x 34 cm x 43.5 cm) shaker incubator.</li>
	</ol>
	</li>
	<li>Pretesting the Morbidostat
	<ol>
		<li>Set power supply voltage of cool fan to 5 V to start its motor to test the magnetic stirring bar. Note that the stirring action can be inspected visually. The voltage that drives the cooling fan motor is precisely controlled by pulse width modulation (PWM).</li>
		<li>Prepare a series of wild type E. coli samples with optical densities at 600 nm typically ranging from 0.07 to 0.3 for calibration. Place a test E. coli sample in the culture vial and record the photodetector voltage.
		<ol>
			<li>Place ~100 &#181;l of the same sample in the plate reader and record the optical density. Use the photodetector voltage versus optical density data to plot the calibration curve. Note that typically, one unit change in optical density corresponds to ~7.6 V change in the photodetector with the bias scheme used here.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
2. Running the Morbidostat
<ol>
	<li>Preparation Before Starting the Daily Experiment
	<ol>
		<li>Prepare the culture vial with three ultra-chemical resistant Tygon tubings with inner diameter 1/32 inch and outer diameter 3/32 inch for inlets to form the device as in section 1.1 and in Supplementary Figure 1.</li>
		<li>Prepare the M9 minimal medium (0.2% glucose) and trimethoprim (TMP) drug containing medium. Sterilize the medium, the medium bottle, the drug medium bottle, the waste bottle, and the culture vial in an autoclave at 121 &#176;C. 
		NOTE: The TMP is a stock solution that is used to later achieve the concentrations in Table 1 and the TMP drug containing medium is not autoclaved.</li>
	</ol>
	</li>
	<li>Running the Morbidostat
	<ol>
		<li>On the first day of the experiment, thaw 1 ml of frozen wild type E. coli MG1655 cells for 5 min at room temperature and transfer 120 &#181;l of the cells to the culture vial containing ~12 ml of M9 growth medium. After the first day, thaw 1 ml of frozen E. coli cells from the previous day for 5 min and transfer 120 &#181;l of the cells to a new culture vial containing ~12 ml of M9 growth medium.</li>
		<li>Turn on the shaker incubator and set the temperature to 30 &#176;C with no shaking.</li>
		<li>Start the morbidostat operation by turning on the micro-pump, the magnetic stirring unit, and the optical density measurement. 
		NOTE: During the operation, a feedback threshold algorithm is used to control the drug injection. When the measured optical density exceeds a preset threshold, the drug injection pump would be turned on and the medium pump would be turned off. Otherwise, the drug injection pump remains off and the medium pump is on.</li>
		<li>Monitor the voltage from time to time to ensure there is microbial growth. 
		Note: Because of the freeze and thaw cycle, E. coli cells exhibit a delay of ~4 hr during each day&#39;s growth.</li>
		<li>After ~23 hr, stop the micro-pump by turning off its supply voltage and take out the culture vial. Add 15% glycerol into the culture vial and freeze the sample at -80 &#176;C for storage.</li>
		<li>Repeat steps 2.2.1 to 2.2.5.</li>
	</ol>
	</li>
</ol>
3. Antibiotic Susceptibility Measurement in 96 Well Format
NOTE: Perform the growth rate measurement in a plate reader with a 96 well format to determine the antibiotic resistance level.
<ol>
	<li>Thaw the daily frozen sample at room temperature for 5 min and transfer 15 &#181;l of the cell to the culture vial containing ~15 ml M9 medium. Allow them to grow until the optical density at 600 nm reaches ~0.1. Divide the 15 ml into 1 ml bottles and add the TMP drug at this step to obtain the desired drug concentrations as shown in Table 1.</li>
	<li>Take 200 &#181;l of the sample from step 3.1 and place into each well in the plate reader and allow them to grow for 12 hr5. The optical density at wavelength 600 nm is recorded automatically during the measurement. 
	NOTE: For each data point, triplicate measurements are recorded and averaged to ensure the consistency of the data. The data on optical density versus time can be used to obtain the growth rate.</li>
	<li>Plot the growth rate data versus the drug concentration to obtain IC50. Note that IC50 is defined as the drug concentration at which the growth rate is fifty percent of the maximal growth rate5.</li>
</ol>
4. Single Cell Morphology and Antibiotic Susceptibility Measurement in Microfluidic Devices
<ol>
	<li>Perform fabrication of the microfluidic devices via multilayer soft lithography from PDMS as described elsewhere15.
	<ol>
		<li>Use photolithography to make the photoresist mold for the control and flow layers. Note that for the control layer, use negative photoresist (~15 &#181;m height) and positive photoresist (~8 &#181;m height) to produce a mold on a bare silicon wafer.</li>
		<li>Prepare PDMS mixtures with cross linking ratios of 5:1 and 20:1 for the control layer and the flow layer, respectively. Put the mixtures into a desiccator under vacuum to remove any bubbles, for 1 hr.</li>
		<li>Expose the control layer photoresist molds on silicon wafer to trimethylchlorosilane (TMCS) vapor. Make the control layer of ~6 mm thickness by casting the PDMS mixture (with cross linking ratio 5:1) on the silicon wafer on the control layer photoresist mold. Bake the control layer for 40 min at 80 &#176;C for 1 hr in the oven.</li>
		<li>Make the flow layer by spin coating a PDMS mixture (with cross linking ratio 20:1, spin speed 3,000 rpm for 60 sec) on a flow layer photoresist mold. Bake the flow layer for 30 min at 80 &#176;C for 1 hr in the oven.</li>
		<li>Use a razor blade to cut the control layer into the desired chip size (typically 3 cm x 2 cm) and manually peel off the control layer. Place the control layer on top of the flow layer and align them under a stereomicroscope. Cure the aligned assembly at 80 &#176;C in the oven overnight. Afterwards, soak the assembly in 250 ml of deionized water in a plastic container for 5 hr to dissolve the residual TMCS.</li>
		<li>Subsequently, punch the inlet holes with 20 G needles and bond the entire elastomer to a glass slide coated with a blank PDMS layer (PDMS cross linking ratio 5:1, spin speed 2,000 rpm for 30 sec) by air plasma treatment for 40 sec at 1.2 Torr air pressure.</li>
		<li>Carry out extensive baking for 36 hr at 80 &#176;C to reduce the cytotoxic effects from PDMS. Note that this baking step is critical to minimize the toxicity to the bacterial cells.</li>
	</ol>
	</li>
	<li>On Chip Growth Experiment
	<ol>
		<li>Before loading into the microfluidic device, flush it with deionized water for 1 hr and M9 medium for 1 hr.</li>
		<li>Thaw the daily frozen sample at room temperature for 5 min and inoculate a new test tube with fresh M9 medium. Place the sample in a shaker incubator at 37 &#176;C overnight.</li>
		<li>Dilute the microbial sample 10 fold with M9 medium and load it into the microfluidic device by pressuring the microbial sample container at 5 psi. Then load the TMP drug medium into the chip by pressuring the drug medium container at 5 psi. Execute the mixing between the microbe and drug by actuating the micromechanical valve between the two chambers on the microfluidic chip for 15 min.</li>
		<li>Place the microfluidic chip in the microscope incubator mounted on the inverted microscope. Acquire the cell image in the growth chamber every hr for 8 hr with the CCD camera mounted on the inverted microscope.</li>
		<li>Use the custom program script to calculate the cell numbers through a threshold algorithm on the cell image data18. Note that the cell number data are averaged typically over three microfluidic chambers.</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

A low-footprint morbidostat device from low-cost components is demonstrated. The increases in drug resistance level registered by the device are consistent with those of previous reports5. Designed for evolutionary studies of drug resistance, the device is potentially applicable to many other experiments. First, a comprehensive database of drug-induced mutations can be established for a large set of clinically relevant antibiotics. For example, the evolutionary pathway of multiple drug resistance can be studied by simply increasing the number of drugs used in the experiment. The main advantage of the module reported here is its flexible configurability, enabling large-scale, parallel experiments under different experimental conditions.
Although the concept was demonstrated in the microfluidics measurements, the investigative power can be improved by combining microfluidics with fluidic technology23. The cost per measurement (economy of scale) is dramatically reduced by the lowered reagent consumption and reduced labor. Here, single cell morphology data can be extracted from the microfluidic platform. Recently, microfluidic morphology testing of single cells has been successfully implemented in clinical microbiology laboratories, and performs comparably to standard broth serial dilution tests24. With the increasing availability of microfluidic devices, combined technologies will enable large-scale, high-throughput laboratory evolution experiments.
Several steps are critical to run the morbidostat. Firstly, because the magnetic stirring unit is formed from magnets and a cooling fan, it is crucial to align the shaft of the fan to the culture vial. Also, the distance between the culture vial and the magnet is very critical to ensure a stable operation. Secondly, switching to a new culture vial in the beginning of each day&#39;s experiment is also important to avoid biofilm formation. Otherwise, biofilm formation can occur within 2 or 3 days. Thirdly, because E. coli samples are thawed daily from a frozen sample during each day&#39;s experiment to ensure consistency, it is important to set a delay period of at least 4 hr to avoid a total washing out of the microbes. Alternatively, one can choose not to freeze E. coli samples and directly use the sample to inoculate a new culture vial to start a new culture.
In a practical setting, the current system design must overcome several limitations to extend its potential usages. The volume of the whole system is currently limited by the medium consumed per day (during chemostatic operation, one culture vial consumes approximately 0.5 L of medium per day at the typical dilution rate of 0.33 hr&#8722;1). To reduce the working volume, further optimization can be achieved by careful simulation on the drug-inhibited population dynamics with plumbing parameters25.
Finally, the morbidostat is easily adaptable to a wide range of bacterial culture experiments. For example, by attaching a light emitting diode, the system could be reconfigured as a photo-bioreactor, enabling the evolutionary monitoring of cyanobacteria or micro algae26. The module can be extended to anaerobic and microaerobic cultivation in a gas-tight container with adsorbents by wirelessly operating the device in a battery pack. As another example, the concentration of a toxin could be gradually increased to engineer strains that are resistant to the target chemical27.

Since the introduction of the first antibiotic drug penicillin, microbial antibiotic resistance has developed into a global health problem1. Although the acquisition of antibiotic resistance can be retrospectively studied in vivo, the conditions of these experiments are often not controlled throughout the entire evolution2. Alternatively, adaptive laboratory evolution can reveal the molecular evolution of a microbial species under environmental stresses or selection pressure from an antibiotic drug3. Recently, many well-controlled evolutionary experiments of antibiotic drug resistance have elucidated the emergence of antibiotic drug resistance. For example, Austin&#39;s group demonstrated rapid emergence in a properly engineered microfluidic compartmented environment4. The recently developed morbidostat induces systematic mutations under drug selection pressure5,6. The morbidostat, a microbial selection device that continuously adjusts the antibiotic concentration to maintain a nearly constant population, is a major advance from the fluctuation test used in microbiology7,8. In the fluctuation test, an antibiotic drug is injected at high concentration, and the surviving mutants are screened and counted. Instead, microbes in a morbidostat are constantly challenged and acquire multiple mutations.
The morbidostat operates similarly to the chemostat, a culture device invented by Novick and Szliard in 1950 that maintains a constant population by continuously supplying nutrients while diluting the microbial population9. Since its introduction, the chemostat has been advanced and improved. Current microfluidic chemostats have reached nanoliter and single-cell capacities. However, these devices are unsuitable for adaptive evolution experiments, which require a large cell population with many mutation events10,11. Recently, mini-chemostats with working volumes of ~10 ml have also been developed to fill in the gap between liter scale bioreactors and the microfluidic chemostat12,13.
Here we present the design and use of a low-cost, automated morbidostat for an antibiotic drug resistance study. The proposed module can be employed in a shaker incubator in a microbiology laboratory with minimal hardware requirement. The open-source firmware is also easily tailored to specific applications of adaptive evolution, such as metabolic engineering3. Finally, the morbidostat is integrated into a multiplexed microfluidic platform for antibiotic susceptibility testing14.

<table><tbody><tr><td>Environmental Shaker Incubator</td><td>BioSan</td><td>ES-20</td><td></td></tr><tr><td>Arduino Leonardo board</td><td>Arduino</td><td>Leonardo</td><td></td></tr><tr><td>680 Ohm Carbon Resistor</td><td>Digikey</td><td></td><td>Bias resistor for LED</td></tr><tr><td>100k Ohm Carbon resistor</td><td>Digikey</td><td></td><td>Bias resistor for phototransistor</td></tr><tr><td>940 nm light emitting diode</td><td>Bright LED Electronic</td><td>BIR-BM13E4G-2</td><td>Optical density measurement</td></tr><tr><td>940 nm phototransistor</td><td>Kodenshi&amp;nbsp;</td><td>ST-2L2B</td><td>Optical density measurement</td></tr><tr><td>Darlington pair IC Toshiba</td><td>Mouser</td><td>ULN2803APG</td><td>this IC drives micropumps and magnetic stirring unit</td></tr><tr><td>5 V DC brushless fan</td><td>ADDA</td><td>AD0405LX-G70</td><td>spec: 5 V supply voltage and 80&amp;nbsp;mA; available www.jameco.com</td></tr><tr><td>Piezoelectric micropump</td><td>CurieJet</td><td>PS15I-FT-5L</td><td>Pressure &gt; 3&amp;nbsp;kPa; Flow rate &gt;5 ml/min</td></tr><tr><td>Tygon 3350 Tuning</td><td>Saint Gobain</td><td>ABW00001</td><td>ID: 1/32&quot; OD: 3/32&quot; L:50&#039;&amp;nbsp;</td></tr><tr><td>Magnetic Stir bar</td><td>COWIE</td><td></td><td>tapered shape dim: 10&amp;nbsp;mm x 4 mm</td></tr><tr><td>Glass scintillation 20 ml vial</td><td>DGS</td><td></td><td>Pyrex glass 28 mm (diameter) x 61 mm (height)</td></tr><tr><td>Culture vial holder</td><td></td><td></td><td>Custom made from Polyformaldehyde&amp;nbsp;</td></tr><tr><td>Silicone</td><td>Dow Corning</td><td>Sylgald 184</td><td>used to seal the glass vial</td></tr><tr><td>Medium bottle</td><td>VWR</td><td>66022-065</td><td></td></tr><tr><td>Difco M9 minimal salt 5x</td><td>BD</td><td></td><td>Medium</td></tr><tr><td>Cadamino Acid</td><td>BD</td><td></td><td>Medium</td></tr><tr><td>glucose</td><td>Sigma</td><td></td><td></td></tr><tr><td>Agar Bateriological</td><td>Oxoid</td><td></td><td>for agar plate</td></tr><tr><td>Luria Bertani medium</td><td></td><td></td><td></td></tr><tr><td>Inverted microscope</td><td>Leica Microsystems</td><td>Leica DMI-LED</td><td>used for microfluidic measurement Use 40X objective NA = 0.55</td></tr><tr><td>Microscope Incubator</td><td>Live Cell Instrument</td><td>CU-109</td><td>used for microfluidic measurement</td></tr><tr><td>Solenoidal valves</td><td>Pneumadyne</td><td>S10MM-31-12-3</td><td>Normally open 1.3 Watt 12 Vdc</td></tr><tr><td>USB interface card</td><td>Hobby Engineering</td><td>USBIO24-R Digital I/O Module&amp;nbsp;</td><td>for microfluidics measurement</td></tr><tr><td>Air compressor</td><td>Rocker Scientific</td><td>ROCKER 440</td><td>Pressure source for microfluidcs; Max. Pressure 80 psi</td></tr><tr><td>Male luer-lock fittings to 1/8&quot; barb</td><td>ValuePlastics.com</td><td>MTLL230-1</td><td>used for microfluidic control</td></tr><tr><td>1/8&quot; barb to 10-32 threaded port</td><td>ValuePlastics.com</td><td>B-1</td><td>used for microfluidic control</td></tr><tr><td>Female luer-lock fittings to 10-32 threaded port</td><td>ValuePlastics.com</td><td>KFTL-1</td><td>used for microfluidic control</td></tr><tr><td>NPN darlington transistor 500 mA, 40&amp;nbsp;V (2N6427)</td><td>DigiKey.com</td><td>2N6427GOS-ND</td><td>used for microfluidic control</td></tr><tr><td>10 kOhm, carbon film resistor, 0.25 W</td><td>DigiKey.com</td><td>P10KBACT-ND</td><td>used for microfluidic control</td></tr><tr><td>Tantalum capacitor, 10&amp;nbsp;&amp;mu;F, 25 V, 10%</td><td>DigiKey.com</td><td>478-1841-ND</td><td>used for microfluidic control</td></tr><tr><td>Andor CCD camera</td><td>Andor</td><td>Zyla 4.2 Plus SCMOS</td><td>used for microfluidic on chip imaging</td></tr><tr><td>ELISA plate reader</td><td></td><td></td><td></td></tr><tr><td>two component Silicone&amp;nbsp;</td><td>Momentive</td><td>RTV 615</td><td>used for microfluidic chip fabrication</td></tr><tr><td>SU-8 photoresist</td><td>Micrchem</td><td>SU8 2015</td><td>used for microfluidic chip fabrication</td></tr><tr><td>AZ4620 photoresist</td><td>Clariant</td><td>AZ 4620</td><td>used for microfluidic chip fabrication</td></tr><tr><td>Plasma cleaner</td><td>Harrick Plasma</td><td>PDC 32G</td><td>used for microfluidic chip fabrication</td></tr><tr><td>20 Gauge Syringe Needle</td><td>BD</td><td></td><td>used for microfluidic chip fabrication</td></tr><tr><td>Labcycler</td><td>Sensoquest</td><td>Labcycler</td><td>PCR</td></tr><tr><td>DNA polymerase</td><td>Toyobo</td><td>KDO Plus</td><td>PCR amplification</td></tr><tr><td>Trimethoprim</td><td>Sigma</td><td></td><td></td></tr><tr><td>Plate reader</td><td>Biotek</td><td>Synergy H1 hybrid&amp;nbsp;</td><td>antibiotic resistane measurement</td></tr></tbody></table>

design and use of a low cost, automated morbidostat for adaptive evolution of bacteria under antibiotic drug selection

We describe a low cost, configurable morbidostat for characterizing the evolutionary pathway of antibiotic resistance. The morbidostat is a bacterial culture device that continuously monitors bacterial growth and dynamically adjusts the drug concentration to constantly challenge the bacteria as they evolve to acquire drug resistance. The device features a working volume of ~10 ml and is fully automated and equipped with optical density measurement and micro-pumps for medium and drug delivery. To validate the platform, we measured the stepwise acquisition of trimethoprim resistance in Escherichia coli MG 1655, and integrated the device with a multiplexed microfluidic platform to investigate cell morphology and antibiotic susceptibility. The approach can be up-scaled to laboratory studies of antibiotic drug resistance, and is extendible to adaptive evolution for strain improvements in metabolic engineering and other bacterial culture experiments.

The above-described morbidostat is schematized in Figure 1. The common morbidostat operations, including experimental evolution, antibiotic susceptibility test and cell morphology checking, were validated in an E. coli MG1655 culture exposed to trimethoprim (TMP), a commonly used antibiotic drug5,6. TMP induces very distinctive stepwise increases in drug resistance, and the mutations are clustered around the dihydrofolate reductase (DHFR) gene. Therefore, TMP is a highly effective standard drug for validating the morbidostat operation. Each day, the microbe is expected to grow above the preset optical density threshold and trigger the drug injection as shown in Figure 2a. The drug injection is expected to inhibit the growth and as a result, decrease the optical density. Several trial runs may be needed to determine the optimal drug concentration. As a rule of thumb, we increase the concentration of the drug medium by 5-fold after finding that the drug medium fails to suppress the growth. After the entire course of the experiment, daily frozen samples are thawed and used to determine IC50, a quantitative measure of the drug resistance level. The plot in Figure 2b shows the temporal increase in the antibiotic drug resistance. The drug resistance increased approximately 1,500-fold to ~1,000 &#181;g/ml over ~12 days, consistent with previous findings in laboratory evolution5 and clinical isolates19. The DHFR point mutations in the last-day mutant were measured by Sanger sequencing and are listed in Table 2. One mutation is found located on the promoter region and indicates that single point mutation in the promoter region can significantly change the expression level of the DHFR enzyme20. Another mutation at location 49,910 is located in the gene region of DHFR and is close to the active site of the DHFR enzyme21. The acquisition of drug resistance with multiple mutations proves the usefulness of the morbidostat, as the selection on drug containing agar plate tends to confer only the single mutation.
As a more sensitive readout of the cell morphology, the single-cell morphology check with antibiotic susceptibility is carried out in a parallel, multiplexed microfluidic platform14. Figure 3 shows the design of the multiplexed microfluidic chip. Micrographs of the bacterial cells (Figure 5) reveal morphology changes in both wild type and mutant strains under sub-inhibitory concentrations of TMP. Wild type strains show significant filamentation while the mutant strain shows no significant filamentation. This morphology change at a single cell level can be used in the rapid diagnostic of antibiotic resistance. Figure 4 displays the on-chip growth curves at various concentrations of TMP. The mutant sample shows a significant increase in antibiotic drug resistance. The on-chip growth data in Figure 4 is also consistent with the IC50 value from the plate reader displayed in Figure 2b.
<img alt="Figure 1" src="/files/ftp_upload/54426/54426fig1.jpg" /> 
Figure 1: Schematic of the morbidostat. The morbidostat is a continuous culture device that measures the optical density of the microbial population, and accordingly adjusts the drug concentration. The device runs in drug-injection mode and drug-dilution mode. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54426/54426fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54426/54426fig2.jpg" /> 
Figure 2: Growth curve and increase of antibiotic drug resistance level. (a) Representative growth curve under feedback. The microbial growth is inhibited by the antibiotic drug, whose injection is triggered by a threshold algorithm. When the positive growth rate raises the optical density above the preset threshold (ODTH = 0.086), the device switches to drug-injection mode. Otherwise, the device runs in drug-dilution mode. Red and purple arrows indicate switching into drug injection and drug dilution modes, respectively. (b) Resistance level of the cells during 12 days of exposure to trimethoprim. The IC50 shows a distinct stepwise increase of antibiotic drug resistance. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54426/54426fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54426/54426fig3.jpg" /> 
Figure 3: Microfluidic devices for investigating cell morphology and on-chip antibiotic susceptibility. (a) Micrograph of the chip layout. Green and blue compartments are the growth and drug medium chambers, respectively, and the red layout denotes the control layer. The dimensions of the growth chamber are 450 &#181;m (l) x 400 &#181;m (w) x 8 &#181;m (h). The growth chamber is loaded with the bacteria, and the drug chamber is loaded with TMP. Scale bar is 1 cm. (b) Magnified view of the same chip. Scale bar = 500 &#181;m. (c) Magnified view of both chambers before and after mixing. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54426/54426fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54426/54426fig4.jpg" /> 
Figure 4: On-chip growth curves of E. coli exposed to various concentrations of TMP: (a) wild-type ancestral strain and (b) mutant strain (at day 12). The mutant sample shows a significant increase in antibiotic drug resistance. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54426/54426fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/54426/54426fig5.jpg" /> 
Figure 5: Single-cell morphologies (a-d) Bright field images of the cell after treatment with sub-inhibitory levels of TMP. Note the significant filamentation of the wild type cells in (b), which is absent in the mutants (d). Panels (e-h) are digitalized images of (a-d). All bacterial images were taken by a CCD camera with a 40X magnification objective. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54426/54426fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary Figure 1: The dimensions and assembly of the culture vial holder. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54426/Supplemental_Figure_1.pdf" target="_blank">Please click here to download this file.</a>
Supplementary Figure 2: The circuit diagram for the LED and photodetector. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54426/Supplementary_Figure_2.PNG" target="_blank">Please click here to download this file.</a>
Supplementary Code: Custom script to count the cell number from the acquired cell images from the microfluidic chips. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54426/renamed_40eb7.pdf" target="_blank">Please click here to download this file.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2">Sample</td>
			<td colspan="11">TMP Drug (&#181;g/ml)</td>
		</tr>
		<tr>
			<td colspan="2">Day 1-3</td>
			<td>0</td>
			<td>0.06</td>
			<td>0.12</td>
			<td>0.25</td>
			<td>0.5</td>
			<td>1</td>
			<td>2</td>
			<td>4</td>
			<td>8</td>
			<td>16</td>
			<td>32</td>
		</tr>
		<tr>
			<td colspan="2">Day 4</td>
			<td>0</td>
			<td>1</td>
			<td>2</td>
			<td>3</td>
			<td>5</td>
			<td>10</td>
			<td>20</td>
			<td>40</td>
			<td>80</td>
			<td>160</td>
			<td>320</td>
		</tr>
		<tr>
			<td colspan="2">Day 5-7</td>
			<td>0</td>
			<td>2</td>
			<td>4</td>
			<td>8</td>
			<td>15</td>
			<td>30</td>
			<td>60</td>
			<td>120</td>
			<td>240</td>
			<td>480</td>
			<td>960</td>
		</tr>
		<tr>
			<td colspan="2">Day 8-12</td>
			<td>0</td>
			<td>3</td>
			<td>7</td>
			<td>15</td>
			<td>30</td>
			<td>60</td>
			<td>125</td>
			<td>250</td>
			<td>500</td>
			<td>1,000</td>
			<td>2,000</td>
		</tr>
	</tbody>
</table>
Table 1: Drug concentration used to determine IC50 in the plate reader measurement. Drug concentrations in unit of &#181;g/ml are displayed for the daily frozen sample. As the cells develop higher drug resistance, the drug concentrations used are increased accordingly.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>No</td>
			<td>Location</td>
			<td>SNP</td>
			<td>Note</td>
		</tr>
		<tr>
			<td>1</td>
			<td>49,894</td>
			<td>C-&#62;T&#160;</td>
			<td>DHFR gene&#160;</td>
		</tr>
		<tr>
			<td>2</td>
			<td>49,910</td>
			<td>T-&#62;A&#160;</td>
			<td>DHFR gene&#160;</td>
		</tr>
		<tr>
			<td>3</td>
			<td>49,795</td>
			<td>C-&#62;T&#160;</td>
			<td>DHFR promoter</td>
		</tr>
	</tbody>
</table>
Table 2: Mutation in DHFR identified by Sanger sequencing. The representative sequence data show the three DHFR point mutations in the last-day mutant (day 12). The promoter and gene regions contain one and 2 SNPs, respectively. The forward and reverse primers used in the PCR were 3&#39;TCTAGAGAGATCATTACCGA GGACCGCGAACATCTGTCAT5&#39; and 3&#39;ACTAGT TTACCGCCGCTC CAGAATCTCAA AGCAATAGCTG5&#39;.

Watch this Scientific Journal Video about Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection at JoVE.com

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection

We describe a low cost, configurable morbidostat that enables the characterization of antibiotic drug resistance by dynamically adjusting the drug concentration. The device can be integrated with a multiplexed microfluidic platform. The approach can be scaled up for laboratory antibiotic drug resistance studies.

We describe a low cost, configurable morbidostat for characterizing the evolutionary pathway of antibiotic resistance. The morbidostat is a bacterial ...

design-use-low-cost-automated-morbidostat-for-adaptive-evolution

Nanyang Technological University

Research

JoVE Journal

Genetics

9.6K Views.  National Tsing Hua University. We describe a low cost, configurable morbidostat that enables the characterization of antibiotic drug resistance by dynamically adjusting the drug concentration. The device can be integrated with a multiplexed microfluidic platform. The approach can be scaled up for laboratory antibiotic drug resistance studies.

Video: Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection

Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat

Natural evolution involves genetic diversity such as environmental change and a selection between small populations. Adaptive laboratory evolution (ALE) refers to the experimental situation in which evolution is observed using living organisms under controlled conditions and stressors; organisms are thereby artificially forced to make evolutionary changes. Microorganisms are subject to a variety of stressors in the environment and are capable of regulating certain stress-inducible proteins to increase their chances of survival. Naturally occurring spontaneous mutations bring about changes in a microorganism's genome that affect its chances of survival. Long-term exposure to chemostat culture provokes an accumulation of spontaneous mutations and renders the most adaptable strain dominant. Compared to the colony transfer and serial transfer methods, chemostat culture entails the highest number of cell divisions and, therefore, the highest number of diverse populations. Although chemostat culture for ALE requires more complicated culture devices, it is less labor intensive once the operation begins. Comparative genomic and transcriptome analyses of the adapted strain provide evolutionary clues as to how the stressors contribute to mutations that overcome the stress. The goal of the current paper is to bring about accelerated evolution of microorganisms under controlled laboratory conditions.

Here, we present a protocol to obtain adaptive laboratory evolution of microorganisms under conditions using chemostat culture. Also, genomic analysis of the evolved strain is discussed.

Natural evolution involves genetic diversity such as environmental change and a selection between small populations. Adaptive laboratory evolution (ALE) ...

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Multicopy plasmids are extremely abundant in prokaryotes but their role in bacterial evolution remains poorly understood. We recently showed that the increase in gene copy number per cell provided by multicopy plasmids could accelerate the evolution of plasmid-encoded genes. In this work, we present an experimental system to test the ability of multicopy plasmids to promote gene evolution. Using simple molecular biology methods, we constructed a model system where an antibiotic resistance gene can be inserted into Escherichia coli MG1655, either in the chromosome or on a multicopy plasmid. We use an experimental evolution approach to propagate the different strains under increasing concentrations of antibiotics and we measure survival of bacterial populations over time. The choice of the antibiotic molecule and the resistance gene is so that the gene can only confer resistance through the acquisition of mutations. This &#34;evolutionary rescue&#34; approach provides a simple method to test the potential of multicopy plasmids to promote the acquisition of antibiotic resistance. In the next step of the experimental system, the molecular bases of antibiotic resistance are characterized. To identify mutations responsible for the acquisition of antibiotic resistance we use deep DNA sequencing of samples obtained from whole populations and clones. Finally, to confirm the role of the mutations in the gene under study, we reconstruct them in the parental background and test the resistance phenotype of the resulting strains.

Here we present an experimental method to test the role of multicopy plasmids in the evolution of antibiotic resistance.

Multicopy plasmids are extremely abundant in prokaryotes but their role in bacterial evolution remains poorly understood. We recently showed that the ...

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

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 &#8212; temperature and osmolarity &#8212; 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.

The eVOLVER framework enables high-throughput continuous microbial culture with high resolution and dynamic control over experimental parameters. This protocol demonstrates how to apply the system to conduct a complex fitness experiment, guiding users on programming automated control over many individual cultures, measuring, collecting, and interacting with experimental data in real-time.

Continuous culture methods enable cells to be grown under quantitatively controlled environmental conditions, and are thus broadly useful for measuring ...

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Plasmids play a major role in microbial ecology and evolution as vehicles of lateral gene transfer and reservoirs of accessory gene functions in microbial populations. This is especially the case under rapidly changing environments such as fluctuating antibiotics exposure. We recently showed that plasmids maintain antibiotic resistance genes in Escherichia coli without positive selection for the plasmid presence. Here we describe an experimental system that allows following both the plasmid genotype and phenotype in long-term evolution experiments. We use molecular techniques to design a model plasmid that is subsequently introduced to an experimental evolution batch system approach in an E. coli host. We follow the plasmid frequency over time by applying replica plating of the E. coli populations while quantifying the antibiotic resistance persistence. In addition, we monitor the conformation of plasmids in host cells by analyzing the extent of plasmid multimer formation by plasmid nicking and agarose gel electrophoresis. Such an approach allows us to visualize not only the genome size of evolving plasmids but also their topological conformation-a factor highly important for plasmid inheritance. Our system combines molecular strategies with traditional microbiology approaches and provides a set-up to follow plasmids in bacterial populations over a long time. The presented approach can be applied to study a wide range of mobile genetic elements in the future.

Our experimental approach provides a strategy to follow plasmid abundance and antibiotic resistance over time in bacterial populations.

Plasmids play a major role in microbial ecology and evolution as vehicles of lateral gene transfer and reservoirs of accessory gene functions in microbial ...

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The efficient generation of genetic diversity represents an invaluable molecular tool that can be used to label DNA synthesis, to create unique molecular signatures, or to evolve proteins in the laboratory. Here, we present a protocol that allows the generation of large (>1011) mutant libraries for a given target sequence. This method is based on replication of a ColE1 plasmid encoding the desired sequence by a low-fidelity variant of DNA polymerase I (LF-Pol I). The target plasmid is transformed into a mutator strain of E. coli and plated on solid media, yielding between 0.2 and 1 mutations/kb, depending on the location of the target gene. Higher mutation frequencies are achieved by iterating this process of mutagenesis. Compared to alternative methods of mutagenesis, our protocol stands out for its simplicity, as no cloning or PCR are involved. Thus, our method is ideal for mutational labeling of plasmids or other Pol I templates or to explore large sections of sequence space for the evolution of activities not present in the original target. The tight spatial control that PCR or randomized oligonucleotide-based methods offer can also be achieved through subsequent cloning of specific sections of the library. Here we provide protocols showing how to create a random mutant library and how to establish drug-based selections in E. coli to identify mutants exhibiting new biochemical activities.

Mutagenesis and Functional Selection Protocols for Directed Evolution of Proteins in E. coli

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The efficient generation of genetic diversity represents an invaluable molecular tool that can be used to label DNA synthesis, to create unique molecular ...

Biology

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Conventional microbial cultivation methods usually have cumbersome operations, low throughput, low efficiency, and large consumption of labor and reagents. Moreover, microplate-based high-throughput cultivation methods developed in recent years have poor microbial growth status and experiment parallelization because of their low dissolved oxygen, poor mixture, and severe evaporation and thermal effect. Due to many advantages of micro-droplets, such as small volume, high throughput, and strong controllability, the droplet-based microfluidic technology can overcome these problems, which has been used in many kinds of research of high-throughput microbial cultivation, screening, and evolution. However, most prior studies remain&#160;at the stage of laboratory construction and application. Some key issues, such as high operational requirements, high construction difficulty, and lack of automated integration technology, restrict the wide application of droplet microfluidic technology in microbial research. Here, an automated Microbial Microdroplet Culture system (MMC) was successfully developed based on droplet microfluidic technology, achieving the integration of functions such as inoculation, cultivation, online monitoring, sub-cultivation, sorting, and sampling required by the process of microbial droplet cultivation. In this protocol, wild-type Escherichia coli (E. coli) MG1655 and a methanol-essential E. coli strain (MeSV2.2) were taken as examples to introduce how to use the MMC to conduct automated and relatively high-throughput microbial cultivation and adaptive evolution in detail. This method is easy to operate, consumes less labor and reagents, and has high experimental throughput and good data parallelity, which has great advantages compared with conventional cultivation methods. It provides a low-cost, operation-friendly, and result-reliable experimental platform for scientific researchers to conduct related microbial research.

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Bioengineering

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Cells regulate their rate of growth in response to signals from the external world. As the cell grows, diverse cellular processes must be coordinated including macromolecular synthesis, metabolism and ultimately, commitment to the cell division cycle. The chemostat, a method of experimentally controlling cell growth rate, provides a powerful means of systematically studying how growth rate impacts cellular processes - including gene expression and metabolism - and the regulatory networks that control the rate of cell growth. When maintained for hundreds of generations chemostats can be used to study adaptive evolution of microbes in environmental conditions that limit cell growth. We describe the principle of chemostat cultures, demonstrate their operation and provide examples of their various applications. Following a period of disuse after their introduction in the middle of the twentieth century, the convergence of genome-scale methodologies with a renewed interest in the regulation of cell growth and the molecular basis of adaptive evolution is stimulating a renaissance in the use of chemostats in biological research.

Cell growth rate is a regulated process and a primary determinant of cell physiology. Continuous culturing using chemostats enables extrinsic control of cell growth rate by nutrient limitation facilitating the study of molecular networks that control cell growth and how those networks evolve to optimize cell growth.

Cells regulate their rate of growth in response to signals from the external world. As the cell grows, diverse cellular processes must be coordinated ...

An Automated Culture System for Use in Preclinical Testing of Host-Directed Therapies for Tuberculosis

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), was the most significant infectious disease killer globally until the advent of COVID-19. Mtb has evolved to persist in its intracellular environment, evade host defenses, and has developed resistance to many anti-tubercular drugs. One approach to solving resistance is identifying existing&#160;approved drugs that will boost the host immune response to Mtb. These drugs could then be repurposed as adjunctive host-directed therapies (HDT) to shorten treatment time and help overcome antibiotic resistance.
Quantification of intracellular Mtb growth in macrophages is a crucial aspect of assessing potential HDT. The gold standard for measuring Mtb growth is counting colony-forming units (CFU) on agar plates. This is a slow, labor-intensive assay that does not lend itself to rapid screening of drugs. In this protocol, an automated, broth-based culture system, which is more commonly used to detect Mtb in clinical specimens, has been adapted for preclinical screening of host-directed therapies. The capacity of the liquid culture assay system to investigate intracellular Mtb growth in macrophages treated with HDT was evaluated. The HDTs tested for their ability to inhibit Mtb growth were all-trans Retinoic acid (AtRA), both in solution and encapsulated in poly(lactic-co-glycolic acid) (PLGA) microparticles and the combination of interferon-gamma and linezolid. The advantages of this automated liquid culture-based technique over the CFU method include simplicity of setup, less labor-intensive preparation, and faster time to results (5-12 days compared to 21 days or more for agar plates).

Rapid and efficient quantification of intracellular M. tuberculosis growth is crucial for pursuing improved therapies against tuberculosis (TB). This protocol describes a broth-based colorimetric detection assay using an automated liquid culture system to quantify Mtb growth in macrophages treated with candidate host-directed therapies.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), was the most significant infectious disease killer globally until the advent ...

Immunology and Infection

Monitoring Intraspecies Competition in a Bacterial Cell Population by Cocultivation of Fluorescently Labelled Strains

Many microorganisms such as bacteria proliferate extremely fast and the populations may reach high cell densities. Small fractions of cells in a population always have accumulated mutations that are either detrimental or beneficial for the cell. If the fitness effect of a mutation provides the subpopulation with a strong selective growth advantage, the individuals of this subpopulation may rapidly outcompete and even completely eliminate their immediate fellows. Thus, small genetic changes and selection-driven accumulation of cells that have acquired beneficial mutations may lead to a complete shift of the genotype of a cell population. Here we present a procedure to monitor the rapid clonal expansion and elimination of beneficial and detrimental mutations, respectively, in a bacterial cell population over time by cocultivation of fluorescently labeled individuals of the Gram-positive model bacterium Bacillus subtilis. The method is easy to perform and very illustrative to display intraspecies competition among the individuals in a bacterial cell population.

Bacteria may accumulate either detrimental or beneficial mutations during their lifetime. In a population of cells individuals that have accumulated beneficial mutations may rapidly outcompete their fellows. Here we present a simple procedure to visualize intraspecies competition in a bacterial cell population over time using fluorescently labeled individuals.&#160;

Many microorganisms such as bacteria proliferate extremely fast and the populations may reach high cell densities. Small fractions of cells in a ...

High-Throughput Screening Assay for Mycobacterium abscessus Using Dual Reporters

Assay Development for High-Throughput Drug Screening Against Mycobacteria

Mycobacterium abscessus (Mab) infections are challenging to treat due to high intrinsic drug resistance, comparable to multidrug-resistant tuberculosis. Treatments are extremely ineffective and based on a multi-drug regimen, resulting in low patient compliance. Consequently, the scientific community is urged to identify new and effective drugs to treat these infections. One of the strategies employed to this end is drug repurposing - the process of identifying new therapeutic opportunities for existing drugs in the market, circumventing the time required to establish pharmacokinetic and safety profiles of new drugs. With most studies on drug development against Mab relying on traditional and time-consuming methods, an assay for high-throughput drug screening was developed against mycobacteria using an in house developed double-reporter strain of Mab. Using liquid-handling robotics, automated microscopy, and analysis, alongside in house developed double reporter strains, bacterial viability can be rapidly measured using two different readouts, luminescence and fluorescence, without adding reagents or performing any extra steps. This reduces time and variability between assays, a major advantage for high-throughput screenings. The described protocol was validated by screening a library of 1280 compounds. The obtained results were corroborated by the literature, with efficient detection of active compounds. Thus, this work fulfilled the aim of supplying the field with a new tool to help fight this extremely drug-resistant bacteria.

Author Spotlight: Scalable Drug Screening Protocol for Efficient Discovery of M. abscessus Treatments

This study developed an assay for high-throughput screening against Mycobacterium abscessus with a&#160;recently created double reporter strain, using fluorescence and luminescence to assess bacterial viability quickly. This protocol will be relevant for researchers aiming to screen new drugs against this drug-resistant bacteria.

Mycobacterium abscessus (Mab) infections are challenging to treat due to high intrinsic drug resistance, comparable to multidrug-resistant tuberculosis. ...

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection

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Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat

Testing the Role of Multicopy Plasmids in the Evolution of Antibiotic Resistance

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

Quantification of Plasmid-Mediated Antibiotic Resistance in an Experimental Evolution Approach

Mutagenesis and Functional Selection Protocols for Directed Evolution of Proteins in E. coli

Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System (MMC)

The Use of Chemostats in Microbial Systems Biology

An Automated Culture System for Use in Preclinical Testing of Host-Directed Therapies for Tuberculosis

Monitoring Intraspecies Competition in a Bacterial Cell Population by Cocultivation of Fluorescently Labelled Strains

Assay Development for High-Throughput Drug Screening Against Mycobacteria