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 studie...

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.

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			<td style="width:135px;">Saint Gobain</td>
			<td style="width:163px;">ABW00001</td>
			<td>ID: 1/32&#34; OD: 3/32&#34; L:50&#39;&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Magnetic Stir bar</td>
			<td style="width:135px;">COWIE</td>
			<td style="width:163px;"></td>
			<td>tapered shape dim: 10 mm x 4mm</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:275px;">Glass scintillation 20ml vial</td>
			<td style="width:135px;">DGS</td>
			<td style="width:163px;"></td>
			<td>Pyrex glass 28mm(dia.)x 61 mm(h)</td>
		</tr>
		<tr height="48">
			<td height="48" style="height:48px;width:275px;">Culture vial holder</td>
			<td style="width:135px;"></td>
			<td style="width:163px;"></td>
			<td>Custom made from Polyformaldehyde&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Silicone&#160;</td>
			<td style="width:135px;">Dow Corning</td>
			<td style="width:163px;">Sylgald 184</td>
			<td>used to seal the glass vial</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Medium bottle</td>
			<td style="width:135px;">VWR</td>
			<td style="width:163px;">66022-065</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Difco M9 minimal salt 5x</td>
			<td style="width:135px;">BD</td>
			<td style="width:163px;"></td>
			<td>Medium</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Cadamino Acid</td>
			<td style="width:135px;">BD</td>
			<td style="width:163px;"></td>
			<td>Medium</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">glucose</td>
			<td style="width:135px;">Sigma</td>
			<td style="width:163px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Agar Bateriological</td>
			<td style="width:135px;">Oxoid</td>
			<td style="width:163px;"></td>
			<td>for agar plate</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Luria Bertani medium</td>
			<td style="width:135px;"></td>
			<td style="width:163px;"></td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:275px;">Inverted microscope</td>
			<td style="width:135px;">Leica Microsystems</td>
			<td style="width:163px;">Leica DMI-LED</td>
			<td style="width:227px;">used for microfluidic measurement Use X40 objective NA=0.55</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:275px;">Microscope Incubator</td>
			<td style="width:135px;">Live Cell Instrument</td>
			<td style="width:163px;">CU-109</td>
			<td>used for microfluidic measurement</td>
		</tr>
		<tr height="49">
			<td height="49" style="height:49px;width:275px;">Solenoidal valves</td>
			<td style="width:135px;">Pneumadyne</td>
			<td style="width:163px;">S10MM-31-12-3</td>
			<td>Normally open 1.3 Watt 12 Vdc</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">USB interface card</td>
			<td style="width:135px;">Hobby Engineering</td>
			<td>USBIO24-R Digital I/O Module&#160;</td>
			<td>for microfluidics measurement</td>
		</tr>
		<tr height="45">
			<td height="45" style="height:45px;width:275px;">Air compressor</td>
			<td style="width:135px;">Rocker Scientific</td>
			<td style="width:163px;">ROCKER 440</td>
			<td style="width:227px;">Pressure source for microfluidcs Max. Pressure 80 Psi</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Male luer-lock fittings to 1/8&#34; barb</td>
			<td>ValuePlastics.com</td>
			<td style="width:163px;">MTLL230-1</td>
			<td>used for microfluidic control</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">1/8&#34; barb to 10-32 threaded port</td>
			<td>ValuePlastics.com</td>
			<td style="width:163px;">B-1</td>
			<td>used for microfluidic control</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Female luer-lock fittings to 10-32 threaded port</td>
			<td>ValuePlastics.com</td>
			<td style="width:163px;">KFTL-1</td>
			<td>used for microfluidic control</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">NPN darlington transistor 500mA, 40V (2N6427)</td>
			<td>DigiKey.com</td>
			<td>2N6427GOS-ND</td>
			<td>used for microfluidic control</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">10kOhm, carbon film resistor, 0.25W</td>
			<td>DigiKey.com</td>
			<td>P10KBACT-ND</td>
			<td>used for microfluidic control</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Tantalum capacitor, 10uF, 25V, 10%</td>
			<td>DigiKey.com</td>
			<td>478-1841-ND</td>
			<td>used for microfluidic control</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Andor CCD camera</td>
			<td style="width:135px;">Andor</td>
			<td style="width:163px;">Zyla 4.2 Plus SCMOS</td>
			<td>used for microfluidic on chip imaging</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">ELISA plate reader</td>
			<td style="width:135px;"></td>
			<td style="width:163px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">two component Silicone&#160;</td>
			<td style="width:135px;">Momentive</td>
			<td style="width:163px;">RTV 615</td>
			<td>used for microfluidic chip fabrication</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">SU-8 photoresist</td>
			<td style="width:135px;">Micrchem</td>
			<td style="width:163px;">SU8 2015</td>
			<td>used for microfluidic chip fabrication</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">AZ4620 photoresist</td>
			<td style="width:135px;">Clariant</td>
			<td style="width:163px;">AZ 4620</td>
			<td>used for microfluidic chip fabrication</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Plasma cleaner</td>
			<td style="width:135px;">Harrick Plasma</td>
			<td style="width:163px;">PDC 32G</td>
			<td>used for microfluidic chip fabrication</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">20 Gauge Syringe Needle</td>
			<td style="width:135px;">BD</td>
			<td style="width:163px;"></td>
			<td>used for microfluidic chip fabrication</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Labcycler</td>
			<td style="width:135px;">Sensoquest</td>
			<td style="width:163px;">Labcycler</td>
			<td>PCR&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">DNA polymerase</td>
			<td style="width:135px;">Toyobo</td>
			<td style="width:163px;">KDO Plus</td>
			<td>PCR amplification</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Trimethoprim</td>
			<td style="width:135px;">Sigma</td>
			<td style="width:163px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:275px;">Plate reader</td>
			<td style="width:135px;">Biotek</td>
			<td style="width:163px;">Synergy H1 hybrid&#160;</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. Therefo...

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

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) ...

Testing 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 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 ...

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Accurate transcription is required for the faithful expression of genetic information. Surprisingly though, little is known about the mechanisms that control the fidelity of transcription. To fill this gap in scientific knowledge, we recently optimized the circle-sequencing assay to detect transcription errors throughout the transcriptome of Saccharomyces cerevisiae, Drosophila melanogaster, and Caenorhabditis elegans. This protocol will provide researchers with a powerful new tool to map the landscape of transcription errors in eukaryotic cells so that the mechanisms that control the fidelity of transcription can be elucidated in unprecedented detail.

This protocol provides researchers with a new tool to monitor the fidelity of transcription in multiple model organisms.

Accurate transcription is required for the faithful expression of genetic information. Surprisingly though, little is known about the mechanisms that ...

Producing Gene Deletions in Escherichia coli by P1 Transduction with Excisable Antibiotic Resistance Cassettes

A first approach to study the function of an unknown gene in bacteria is to create a knock-out of this gene. Here, we describe a robust and fast protocol for transferring gene deletion mutations from one Escherichia coli strain to another by using generalized transduction with the bacteriophage P1. This method requires that the mutation be selectable (e.g., based on gene disruptions using antibiotic cassette insertions). Such antibiotic cassettes can be mobilized from a donor strain and introduced into a recipient strain of interest to quickly and easily generate a gene deletion mutant. The antibiotic cassette can be designed to include flippase recognition sites that allow the excision of the cassette by a site-specific recombinase to produce a clean knock-out with only a ~100-base-pair-long scar sequence in the genome. We demonstrate the protocol by knocking out the tamA gene encoding an assembly factor involved in autotransporter biogenesis and test the effect of this knock-out on the biogenesis and function of two trimeric autotransporter adhesins. Though gene deletion by P1 transduction has its limitations, the ease and speed of its implementation make it an attractive alternative to other methods of gene deletion.

Producing Gene Deletions in Escherichia coli by P1 Transduction with Excisable Antibiotic Resistance Cassettes

Here we present a protocol for the use of pre-existing antibiotic resistance-cassette deletion constructs as a basis for making deletion mutants in other E. coli strains. Such deletion mutations can be mobilized and inserted into the corresponding locus of a recipient strain using P1 bacteriophage transduction.

A first approach to study the function of an unknown gene in bacteria is to create a knock-out of this gene. Here, we describe a robust and fast protocol ...

qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like Receptor Genes

Killer cell immunoglobulin-like receptors (KIRs) are a set of inhibitory and activating immune receptors, on natural killer (NK) and T cells, encoded by a polymorphic cluster of genes on chromosome 19. Their best-characterized ligands are the human leukocyte antigen (HLA) molecules that are encoded within the major histocompatibility complex (MHC) locus on chromosome 6. There is substantial evidence that they play a significant role in immunity, reproduction, and transplantation, making it crucial to have techniques that can accurately genotype them. However, high-sequence homology, as well as allelic and copy number variation, make it difficult to design methods that can accurately and efficiently genotype all KIR genes. Traditional methods are usually limited in the resolution of data obtained, throughput, cost-effectiveness, and the time taken for setting up and running the experiments. We describe a method called quantitative KIR semi-automated typing (qKAT), which is a high-throughput multiplex real-time polymerase chain reaction method that can determine the gene copy numbers for all genes in the KIR locus. qKAT is a simple high-throughput method that can provide high-resolution KIR copy number data, which can be further used to infer the variations in the structurally polymorphic haplotypes that encompass them. This copy number and haplotype data can be beneficial for studies on large-scale disease associations, population genetics, as well as investigations on expression and functional interactions between KIR and HLA.

Quantitative killer cell immunoglobulin-like receptor (KIR) semi-automated typing (qKAT) is a simple, high-throughput, and cost-effective method to copy number type KIR genes for their application in population and disease association studies.

Killer cell immunoglobulin-like receptors (KIRs) are a set of inhibitory and activating immune receptors, on natural killer (NK) and T cells, encoded by a ...

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria

Dictyostelium discoideum is an intriguing model organism for the study of cell differentiation processes during development, cell signaling, and other important cellular biology questions. The technologies available to genetically manipulate Dictyostelium cells are well-developed. Transfections can be performed using different selectable markers and marker re-cycling, including homologous recombination and insertional mutagenesis. This is supported by a well-annotated genome. However, these approaches are optimized for axenic cell lines growing in liquid cultures and are difficult to apply to non-axenic wild-type cells, which feed only on bacteria. The mutations that are present in axenic strains disturb Ras signaling, causing excessive macropinocytosis required for feeding, and impair cell migration, which confounds the interpretation of signal transduction and chemotaxis experiments in those strains. Earlier attempts to genetically manipulate non-axenic cells have lacked efficiency and required complex experimental procedures. We have developed a simple transfection protocol that, for the first time, overcomes these limitations. Those series of large improvements to Dictyostelium molecular genetics allow wild-type cells to be manipulated as easily as standard laboratory strains. In addition to the advantages for studying uncorrupted signaling and motility processes, mutants that disrupt macropinocytosis-based growth can now be readily isolated. Furthermore, the entire transfection workflow is greatly accelerated, with recombinant cells that can be generated in days rather than weeks. Another advantage is that molecular genetics can further be performed with freshly isolated wild-type Dictyostelium samples from the environment. This can help to extend the scope of approaches used in these research areas.

Genetic Engineering of Dictyostelium discoideum Cells Based on Selection and Growth on Bacteria

Dictyostelium discoideum is a popular model organism to study complex cellular processes such as cell migration, endocytosis, and development. The utility of the organism is dependent on the feasibility of genetic manipulation. Here, we present methods to transfect Dictyostelium discoideum cells that overcome existing limitations of culturing cells in liquid media.

Dictyostelium discoideum is an intriguing model organism for the study of cell differentiation processes during development, cell signaling, and other ...

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 ...

Use of Frozen Tissue in the Comet Assay for the Evaluation of DNA Damage

The comet assay is gaining popularity as a means to assess DNA damage in cultured cells and tissues, particularly following exposure to chemicals or other environmental stressors. Use of the comet assay in regulatory testing for genotoxic potential in rodents has been driven by adoption of an Organisation for Economic Co-operation and Development (OECD) test guideline in 2014. Comet assay slides are typically prepared from fresh tissue at the time of necropsy; however, freezing tissue samples can avoid logistical challenges associated with simultaneous preparation of slides from multiple organs per animal and from many animals per study. Freezing also enables shipping samples from the exposure facility to a different laboratory for analysis, and storage of frozen tissue facilitates deferring a decision to generate DNA damage data for a given organ. The alkaline comet assay is useful for detecting exposure-related DNA double- and single-strand breaks, alkali-labile lesions, and strand breaks associated with incomplete DNA excision repair. However, DNA damage can also result from mechanical shearing or improper sample processing procedures, confounding the results of the assay. Reproducibility in collection and processing of tissue samples during necropsies may be difficult to control due to fluctuating laboratory personnel with varying levels of experience in harvesting tissues for the comet assay. Enhancing consistency through refresher training or deployment of mobile units staffed with experienced laboratory personnel is costly and may not always be feasible. To optimize consistent generation of high quality samples for comet assay analysis, a method for homogenizing flash frozen cubes of tissue using a customized tissue mincing device was evaluated. Samples prepared for the comet assay by this method compared favorably in quality to fresh and frozen tissue samples prepared by mincing during necropsy. Moreover, low baseline DNA damage was measured in cells from frozen cubes of tissue following prolonged storage.

This protocol describes several procedures for preparing high quality frozen tissue samples at the time of necropsy for use in the comet assay to assess DNA damage: 1) minced tissue, 2) scraped epithelial cells from the gastrointestinal tract, and 3) cubed tissue samples, requiring homogenization using a tissue mincing device.

The comet assay is gaining popularity as a means to assess DNA damage in cultured cells and tissues, particularly following exposure to chemicals or other ...

Use of Drosophila S2 Cells for Live Imaging of Cell Division

Drosophila S2 cells are an important tool in studying mitosis in tissue culture, providing molecular insights into this fundamental cellular process in a rapid and high-throughput manner. S2 cells have proven amenable to both fixed- and live-cell imaging applications. Notably, live-cell imaging can yield valuable information about how loss or knockdown of a gene can affect the kinetics and dynamics of key events during cell division, including mitotic spindle assembly, chromosome congression, and segregation, as well as overall cell cycle timing. Here we utilize S2 cells stably transfected with fluorescently tagged mCherry:&#945;-tubulin to mark the mitotic spindle and GFP:CENP-A (referred to as &#8216;CID&#8217; gene in Drosophila) to mark the centromere to analyze the effects of key mitotic genes on the timing of cell divisions, from prophase (specifically at Nuclear Envelope Breakdown; NEBD) to the onset of anaphase. This imaging protocol also allows for the visualization of the spindle microtubule and chromosome dynamics throughout mitosis. Herein, we aim to provide a simple yet comprehensive protocol that will allow readers to easily adapt S2 cells for live imaging experiments. Results obtained from such experiments should expand our understanding of genes involved in the cell division by defining their role in several simultaneous and dynamic events. Observations made in this cell culture system can be validated and further investigated in vivo using the impressive toolkit of genetic approaches in flies.

Use of Drosophila S2 Cells for Live Imaging of Cell Division

Cell divisions can be visualized in real time using fluorescently tagged proteins and time-lapse microscopy. Using the protocol presented here, users can analyze cell division timing dynamics, mitotic spindle assembly, and chromosome congression and segregation. Defects in these events following RNA interference (RNAi)-mediated gene knockdown can be assessed and quantified.

Drosophila S2 cells are an important tool in studying mitosis in tissue culture, providing molecular insights into this fundamental cellular process in a ...

A FACS-based Protocol to Isolate RNA from the Secondary Cells of Drosophila Male Accessory Glands

To understand the function of an organ, it is often useful to understand the role of its constituent cell populations. Unfortunately, the rarity of individual cell populations often makes it difficult to obtain enough material for molecular studies. For example, the accessory gland of the Drosophila male reproductive system contains two distinct secretory cell types. The main cells make up 96% of the secretory cells of the gland, while the secondary cells (SC) make up the remaining 4% of cells (about 80 cells per male). Although both cell types produce important components of the seminal fluid, only a few genes are known to be specific to the SCs. The rarity of SCs has, thus far, hindered transcriptomic analysis study of this important cell type. Here, a method is presented that allows for the purification of SCs for RNA extraction and sequencing. The protocol consists in first dissecting glands from flies expressing a SC-specific GFP reporter and then subjecting these glands to protease digestion and mechanical dissociation to obtain individual cells. Following these steps, individual, living, GFP-marked cells are sorted using a fluorescent activated cell sorter (FACS) for RNA purification. This procedure yields SC-specific RNAs from ~40 males per condition for downstream RT-qPCR and/or RNA sequencing in the course of one day. The rapidity and simplicity of the procedure allows for the transcriptomes of many different flies, from different genotypes or environmental conditions, to be determined in a short period of time.

A FACS-based Protocol to Isolate RNA from the Secondary Cells of Drosophila Male Accessory Glands

Here, we present a protocol to dissociate and sort a specific cell population from the Drosophila male accessory glands (secondary cells) for RNA sequencing and RT-qPCR. Cell isolation is accomplished through FACS purification of GFP-expressing secondary cells after a multistep-dissociation process requiring dissection, proteases digestion and mechanical dispersion.

To understand the function of an organ, it is often useful to understand the role of its constituent cell populations. Unfortunately, the rarity of ...