This study was financially supported by the Korean Ministry of Science, ICT and Future Planning (Intelligent Synthetic Biology Center program 2012M3A6A8054887). P. Kim was supported by a fellowship from the Catholic University of Korea (2015).

1. Equipment Preparation
<ol>
	<li>Obtain a chemostat jar (150-250 ml) or an Erlenmeyer flask (250 ml) containing an inlet port and an outlet port. Connect the ports with silicon tubing allowing for flow rates of 10-100 ml/hr. Optionally, use an air vent, an air outlet port, and temperature-controlled water inlet and outlet ports.</li>
	<li>Obtain a device suitable for the chemostat jar that provides for agitation and temperature control (or use a rotary shaking incubator).</li>
	<li>Obtain two peristaltic pumps in order to deliver fresh medium and collect the culture.</li>
	<li>Obtain a reservoir jar (10-20 L) containing a medium outlet port and an air inlet port.</li>
	<li>Obtain silicon tubing suitable for the dilution rate (i.e., ID 0.8 mm, flow range 0.06-36 ml/min; L/S 13 tubing).</li>
</ol>
2. Medium Preparation and Sterilization
<ol>
	<li>Initial Medium
	<ol>
		<li>Dissolve 0.3 g glucose, 0.08 g NH4Cl, 0.05 g NaCl, 0.75 g Na2HPO4&#183;2H2O, and 0.3 g KH2PO4 in 90 ml distilled water (D.W.) in a chemostat jar.</li>
		<li>Seal the chemostat jar along with the tubing using clamps. Do not seal the air vent.</li>
		<li>Sterilize the chemostat jar in an autoclave at 121 &#176;C for 15 min. After sterilization, store the chemostat jar at room temperature.</li>
		<li>Dissolve 0.02 g MgSO4&#183;7H2O, 0.01 g CaCl2, and 0.1 mg thiamine in 10 ml D.W. (solution A).</li>
		<li>Filter solution A using a syringe and a pre-sterilized syringe filter (a 0.45 &#181;m pore filter).</li>
		<li>Add the solution A filtrates to the chemostat jar.</li>
	</ol>
	</li>
	<li>Stress Medium
	<ol>
		<li>Dissolve 30 g glucose, 8 g NH4Cl, 5 g NaCl, 75 g Na2HPO4&#183;2H2O, 30 g KH2PO4, and 300 g disodium succinate hexahydrate (Na2&#183;succinate&#183;6H2O; the stressor used in this experiment) in 9.9 L D.W. in a reservoir jar.</li>
		<li>Seal the reservoir jar along with the tubing using clamps. Do not seal the air vent.</li>
		<li>Sterilize the reservoir jar in an autoclave at 121 &#176;C for 15 min. After sterilization, store the jar at room temperature.</li>
		<li>Dissolve 2 g MgSO4&#183;7H2O, 1 g CaCl2, and 10 mg thiamine in 100 ml D.W. (solution A).</li>
		<li>Filter solution A with a syringe and a pre-sterilized syringe filter (a 0.45 &#181;m pore filter).</li>
		<li>Add the solution A filtrates to the reservoir jar.</li>
		<li>Aseptically connect the sterilized silicon tubing to the reservoir jar and attach the peristaltic pumps.</li>
	</ol>
	</li>
	<li>High-stress Medium
	<ol>
		<li>Prepare the medium as in section 2.2, but with a greater concentration of stressor (i.e., 3-5 g/L higher in the succinate adaptation). 
		Note: This protocol is for adaptation to a stress that can be delivered via the medium. In the case of physical stressors such as temperature, agitation, or illumination, the cultivation should be designed accordingly.</li>
	</ol>
	</li>
</ol>
3. Initial Cultivation
<ol>
	<li>Inoculate a single colony of wild-type E. coli in a 15 ml test tube containing 4 ml of initial medium.</li>
	<li>Incubate the test tube in a shaking incubator for 12 hr at 37 &#176;C and 220 rpm.</li>
	<li>Aseptically transfer 1 ml of preculture to the chemostat jar.</li>
	<li>Incubate the chemostat jar, providing for aeration (air 50 ml/min) and agitation (200 rpm), at 37 &#176;C for 6 hr.</li>
</ol>
4. Stress Adaptation
<ol>
	<li>Aseptically connect the end of the silicon tubing from the pumps to the chemostat jar.</li>
	<li>Start the outlet pump (10 ml/hr or higher) and collect culture. 
	Note: The culture should be in the exponential phase, typically 4-8 hr after initial cultivation.</li>
	<li>Check the optical density (600 nm) of the culture from the outlet tubing.</li>
	<li>Start the inlet pump (10 ml/hr, corresponding to a rate of dilution of 0.1 hr-1).</li>
	<li>Check the optical density of the culture at 600 nm from the outlet tubing every 24 hr.</li>
	<li>Operate the chemostat for 96 hr (9.6-fold turnover) or more. If the optical density is stable, exchange the reservoir containing the high-stress medium. If the optical density is lower than 0.2, stop the feeding inlet pump for 6 hr. Restart the inlet pump and check that the optical density is over 0.2.</li>
	<li>Gradually increase the concentration of the stressor by changing to a reservoir containing a higher stressor concentration.</li>
	<li>Take samples of the adapted culture whenever it reaches a milestone (e.g., a strain adapted to 100 g/L succinate stress), and store for further genomic analysis.</li>
	<li>For sample storage, mix the culture sample (0.5 ml) with a sterilized 80% glycerol solution (0.5 ml) and store it at -80 &#176;C. 
	Note: If the microorganism acquires an ability to degrade the stressor during the ALE process, the stressor concentration in the fermentation jar is not the same as that in the fresh reservoir.</li>
</ol>
5. Single-colony Isolation of the Stress-adapted Strain
<ol>
	<li>Prepare agar plate medium (1.6% agar) containing the same stressor and at the same concentration of medium.</li>
	<li>Plate the outlet culture (0.1 ml) from the chemostat, and incubate at 37 &#176;C for 16 hr.</li>
	<li>Pick single colonies from the plate using a sterile toothpick and inoculate them in 15 ml test tubes containing the same stressor and at the same medium concentration as in the chemostat, and incubate for 6 hr.</li>
	<li>Transfer 1 ml of culture broth into a 250 ml Erlenmeyer flask containing 50 ml of medium. Harvest 0.5 ml of the culture broth every 1 hr, and measure the O.D. at 600 nm. Compare the growth rate of the adapted strain to that of the wild-type strain given the stressor.</li>
</ol>

<ol>
	<li>Rando, O. J., Verstrepen, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Timescales+of+genetic+and+epigenetic+inheritance.">Timescales of genetic and epigenetic inheritance.</a> Cell. 128, 655-668 (2007).</li><li>Kim, H. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Short-term+differential+adaptation+to+anaerobic+stress+via+genomic+mutations+by+Escherichia+coli+strains+K-12+and+B+lacking+alcohol+dehydrogenase.">Short-term differential adaptation to anaerobic stress via genomic mutations by Escherichia coli strains K-12 and B lacking alcohol dehydrogenase.</a> Front Microbiol. 5, 476 (2014).</li><li>Mendizabal, I., Keller, T. E., Zeng, J., Yi, S. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Epigenetics+and+evolution.">Epigenetics and evolution.</a> Integr Comp Biol. 54, 31-42 (2014).</li><li>Lee, J. Y., Seo, J., Kim, E. S., Lee, H. S., Kim, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Adaptive+evolution+of+Corynebacterium+glutamicum+resistant+to+oxidative+stress+and+its+global+gene+expression+profiling.">Adaptive evolution of Corynebacterium glutamicum resistant to oxidative stress and its global gene expression profiling.</a> Biotechnol Lett. 35, 709-717 (2013).</li><li>Lee, J. Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Artificial+oxidative+stress-tolerant+Corynebacterium+glutamicum.">Artificial oxidative stress-tolerant Corynebacterium glutamicum.</a> AMB Express. 4, 15 (2014).</li><li>Narang, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+steady+states+of+microbial+growth+on+mixtures+of+substitutable+substrates+in+a+chemostat.">The steady states of microbial growth on mixtures of substitutable substrates in a chemostat.</a> J Theor Biol. 190, 241-261 (1998).</li><li>Kwon, Y. D., Kim, S., Lee, S. Y., Kim, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Long-term+continuous+adaptation+of+Escherichia+coli+to+high+succinate+stress+and+transcriptome+analysis+of+the+tolerant+strain.">Long-term continuous adaptation of Escherichia coli to high succinate stress and transcriptome analysis of the tolerant strain.</a> J Biosci Bioeng. 111, 26-30 (2011).</li><li>Barrick, J. E., Lenski, R. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome+dynamics+during+experimental+evolution.">Genome dynamics during experimental evolution.</a> Nat Rev Genet. 14, 827-839 (2013).</li><li>Li, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Sequence+Alignment/Map+format+and+SAMtools.">The Sequence Alignment/Map format and SAMtools.</a> Bioinformatics. 25, 2078-2079 (2009).</li><li>McKenna, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Genome+Analysis+Toolkit:+a+MapReduce+framework+for+analyzing+next-generation+DNA+sequencing+data.">The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.</a> Genome Res. 20, 1297-1303 (2010).</li><li>Deatherage, D. E., Barrick, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+mutations+in+laboratory-evolved+microbes+from+next-generation+sequencing+data+using+breseq.">Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq.</a> Methods Mol Biol. 1151, 165-188 (2014).</li></ol>

The authors have nothing to disclose.

Microorganisms are capable of adapting to almost all environments because of their rapid growth rate and genetic diversity. Adaptive laboratory evolution enables microorganisms to evolve under designed conditions, which provides a way of selecting individual organisms harboring spontaneous mutations that are beneficial under the given conditions.
The chemostat technique is more robust for achieving artificially driven evolution than transfer techniques for the following reasons: (a) a steady environment&#160;&#8212; because transfer techniques are based on batch cultures either on solid or in liquid medium, the environment of the cells varies during batch culture while the environmental stress of the chemostat is steady; (b) a larger population and a continuous selection&#160;&#8212; the larger population of the chemostat provides more genetic diversity than the smaller population of transfer techniques. Continuous selection of the chemostat technique is a faster way to achieve evolution than intermittent selection of transfer techniques. It is critical that the chemostat culture not be contaminated by other microorganisms during the ALE procedure, and aseptic conditions are required throughout chemostat culture. The ALE procedure can be modified by changes to stressors, such as oxidative stress, osmotic stress, and toxic product stress. There are a few technical limitations to ALE by chemostat culture. Evolution takes place by chance; therefore, different researchers may not be able to obtain the same evolutionary result, although the consequences of mutations might be related. Another limitation is the wash-out of chemostat culture when the concentration of stressor is increased too quickly. If the biomass is decreased to a certain amount (i.e., O.D. = 0.2 in this procedure) after the concentration of stressor is increased, administration of the stressor should be halted for at least a few generations to give the strain time to adapt.
Recent developments in genome sequencing technology have helped the understanding of mutations that develop in response to certain stressful conditions. For example, a DNA mutation alters a particular systemic effect that is beneficial to the given environment (i.e., tolerance to a toxic stressor). Thus, ALE may be used to study gene function or network regulation, or as a raw material for &#39;accelerated evolution&#39;. ALE studies are also useful in simulating the development of antibiotic-resistant bacteria, indicating the mechanisms by which dangerous drug-resistant bacterial strains arise. As the trajectory of evolution is engraved on the genome, uncovering the genetic alterations that lead to the desired phenotypes (such as stress tolerance) is the next obstacle once evolved strains are obtained8. Among the currently available next-generation sequencing technologies, the Illumina and Ion Torrent platforms are suitable for the detection of nucleotide substitutions or small indels that occur in the evolved strains, and both are affordable. Because variant detection usually involves short-read mapping of the reference sequences, the availability of the genome sequence of the ancestral strain is crucial. Even if the genome sequence of the founder strain is available from public databases, it is often desirable to sequence it simultaneously with the evolved one, because there might be some additional differences in the actual starting strain. Protocols for mutation identification are easily available via the web or a literature search9,10. For example, BRESEQ is a specially-designed pipeline for genomic analysis of laboratory-evolved microbes using next-generation sequencing data11. Comparisons of the evolved strains at certain milestones (for example, in this representative data, wild type, DST50, DST100, and DST160) can provide the sequence of the evolved strains and give insight into the consequences of a given stressor. Therefore, knowledge and applications of ALE experiments, coupled with system biology and the identification of systemic perturbation variables, are expected in the near future.

Microorganisms can survive and adapt to diverse environments. Under severe stress, adaptation can occur via acquisition of beneficial phenotypes by random genomic mutations and subsequent positive selection1-3. Therefore, microbial cells can adapt by changing metabolic or regulatory networks for optimal growth, which is termed &#34;adaptive evolution&#34;. Recent important microbial tendencies, such as outbreaks of superbugs and the occurrence of robust microbial strains, are very closely related to adaptive evolution under stressful conditions. Under defined laboratory conditions, we are able to study the mechanisms of molecular evolution and even control the direction of microbial evolution for various applications. Unlike multicellular organisms, single-celled organisms are well suited to adaptive laboratory evolution (ALE) for the following reasons: they regenerate quickly, they maintain large populations, and it is easy to create and maintain homogeneous environments. Combined with recent advances in DNA sequencing techniques and high-throughput technologies, ALE allows for the direct observation of genomic changes that lead to systemic regulatory changes. Mutational dynamics and a diversity of the population are also observable. Genetic engineering strategies can be determined from the analysis of ALE strains4,5.
Chemostat culture is a method used to obtain steady-state cells and increase productivity in fermentation processes6. Fresh medium is added and culture broth is harvested during the process (the latter includes medium and biomass). Long-term chemostat culture, however, changes the steady-state productivity of the culture and brings about the accumulation of spontaneous mutations and selection during culture (Figure 1a). Under various selection pressures (stressors), the accumulation of mutations is enhanced. A gradual increase of stress in a long-term chemostat provides for a continuous selection of mutations that work against the given stressors, such as temperature, pH, osmotic pressure, nutrient starvation, oxidation, toxic end products, etc. Colony transfer from a solid medium and serial transfer from a liquid medium (repeated batch culture) also allow researchers to obtain evolved microorganisms (Figure 1b and 1c). Although chemostat culture requires complicated methods, the pool of diversity (number of replications and population size) is higher than that obtained by colony transfer and serial transfer techniques. The stable stress exposure to individual cells and decreased variation in the cellular state during chemostat culture (steady state) are other benefits of ALE compared to batch culture-based techniques. Stress-induced ALE of Escherichia coli subjected to high succinate conditions is introduced in this article.
<img alt="Figure 1" src="/files/ftp_upload/54446/54446fig1.jpg" /> 
Figure 1: Methods of adaptive laboratory evolution. (A) Chemostat; (B) serial transfer; (C) colony transfer. The top figures illustrate the concept of the methods for ALE, and the bottom figures illustrate the number of cells that grew during ALE. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54446/54446fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table border="0" cellpadding="0" cellspacing="0" width="573">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Mini-chemostat fermentor</td>
			<td style="width:71px;">Biotron Inc.</td>
			<td style="width:119px;">-</td>
			<td style="width:167px;">manufactured by special order</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">silicon tubing</td>
			<td style="width:71px;">Cole-Parmer</td>
			<td style="width:119px;">Masterflex L/S 13</td>
			<td>tubing size can be varied depending on the dilution rate and the size of fermentor jar.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">reservoir jar</td>
			<td style="width:71px;">Bellco</td>
			<td style="width:119px;">Media storage bottle&#160;</td>
			<td>20 L</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">chemicals</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">-</td>
			<td>reagent grade</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">glucose</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">G5767</td>
			<td>ACS reagent</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">NH4Cl</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">A9434</td>
			<td>for molecular biology, suitable for cell culture, &#8805;99.5%</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">NaCl</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td align="right" style="width:119px;">746398</td>
			<td>ACS reagent, &#8805;99%</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Na2HPO4&#183;2H2O</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td align="right" style="width:119px;">4272</td>
			<td>98.5-101%</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">KH2PO4&#160;</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td align="right" style="width:119px;">795488</td>
			<td>ACS reagent, &#8805;99%</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">MgSO4&#183;7H2O</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td align="right" style="width:119px;">230391</td>
			<td>ACS reagent, &#8805;98%</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">CaCl2</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td align="right" style="width:119px;">793639</td>
			<td>ACS reagent, &#8805;96%</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">thiamine&#183;HCl&#160;</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">T4625</td>
			<td>reagent grade, &#8805;99%</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Na2&#183;succinate&#183;6H2O</td>
			<td style="width:71px;">Sigma-Aldrich</td>
			<td style="width:119px;">S2378</td>
			<td>ReagentPlus, &#8805;99%</td>
		</tr>
	</tbody>
</table>

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.

For high-succinate stress adaptation, the wild-type E. coli W3110 strain was cultured in a chemostat at D = 0.1 hr-1 for 270 days (Figure 2).
<img alt="Figure 2" src="/files/ftp_upload/54446/54446fig2.jpg" /> 
Figure 2: High-succinate stress adaptation of E. coli W3110 using chemostat culture. Thin arrows indicate the times at which the concentration of stressor was increased, and bold arrows indicate the times at which cultures were preserved. Numbers with arrows indicate the concentrations of the stressor, disodium succinate hexahydrate. The change in biomass during ALE and the concentrations of stressor are represented. The figure was modified from J. Biosci. Bioeng7. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54446/54446fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
An initial stressor concentration of 30 g/L (disodium succinate hexahydrate) was gradually increased whenever the chemostat culture reached a steady state, until the concentration of stressor was 160 g/L. The adapted E. coli DST160 strain (tolerant to 160 g/L of disodium succinate stress) was acquired after 270 days. The DST160 strain exhibited uninhibited growth under high-succinate stress (160 g/L stressor), while the ancestor strain (W3110) showed nearly no growth (Figure 3).
<img alt="Figure 3" src="/files/ftp_upload/54446/54446fig3.jpg" /> 
Figure 3: Growth curves of the wild-type (W3110, white circle) and adapted strain (DST160, black circle) under high-succinate stress. The figure shows that the adapted strain grew without delay under high-succinate stressed conditions while the wild type did not. The error bars indicate standard deviation of three independent experiments. The figure was modified from J. Biosci. Bioeng7. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54446/54446fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat at JoVE.com

Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat | Genetics | Video

Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat

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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14.1K Views.  Korea Research Institute of Bioscience and Biotechnology (KRIBB). 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.

Video: Procedure for Adaptive Laboratory Evolution of Microorganisms Using a Chemostat

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.

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 ...

CRISPR/Cas9-mediated Targeted Integration In Vivo Using a Homology-mediated End Joining-based Strategy

As a promising genome editing platform, the CRISPR/Cas9 system has great potential for efficient genetic manipulation, especially for targeted integration of transgenes. However, due to the low efficiency of homologous recombination (HR) and various indel mutations of non-homologous end joining (NHEJ)-based strategies in non-dividing cells, in vivo genome editing remains a great challenge. Here, we describe a homology-mediated end joining (HMEJ)-based CRISPR/Cas9 system for efficient in vivo precise targeted integration. In this system, the targeted genome and the donor vector containing homology arms (~800 bp) flanked by single guide RNA (sgRNA) target sequences are cleaved by CRISPR/Cas9. This HMEJ-based strategy achieves efficient transgene integration in mouse zygotes, as well as in hepatocytes in vivo. Moreover, a HMEJ-based strategy offers an efficient approach for correction of fumarylacetoacetate hydrolase (Fah) mutation in the hepatocytes and rescues Fah-deficiency induced liver failure mice. Taken together, focusing on targeted integration, this HMEJ-based strategy provides a promising tool for a variety of applications, including generation of genetically modified animal models and targeted gene therapies.

CRISPR/Cas9-mediated Targeted Integration In Vivo Using a Homology-mediated End Joining-based Strategy

The clustered regularly interspaced short palindromic repeats/CRISPR associated protein 9 (CRISPR/Cas9) system provides a promising tool for genetic engineering, and opens up the possibility of targeted integration of transgenes. We describe a homology-mediated end joining (HMEJ)-based strategy for efficient DNA targeted integration in vivo and targeted gene therapies using CRISPR/Cas9.

As a promising genome editing platform, the CRISPR/Cas9 system has great potential for efficient genetic manipulation, especially for targeted integration ...

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 ...

High-Resolution Comparison of Bacterial Conjugation Frequencies

Bacterial conjugation is an important step in the horizontal transfer of antibiotic resistance genes via a conjugative DNA element. In-depth comparisons of conjugation frequency under different conditions are required to understand how the conjugative element spreads in nature. However, conventional methods for comparing conjugation frequency are not appropriate for in-depth comparisons because of the high background caused by the occurrence of additional conjugation events on the selective plate. We successfully reduced the background by introducing a most probable number (MPN) method and a higher concentration of antibiotics to prevent further conjugation in selective liquid medium. In addition, we developed a protocol for estimating the probability of how often donor cells initiate conjugation by sorting single donor cells into recipient pools by fluorescence-activated cell sorting (FACS). Using two plasmids, pBP136 and pCAR1, the differences in conjugation frequency in Pseudomonas putida cells could be detected in liquid medium at different stirring rates. The frequencies of conjugation initiation were higher for pBP136 than for pCAR1. Using these results, we can better understand the conjugation features in these two plasmids.

With an aim to understand the behaviors of various bacterial conjugative DNA elements under different conditions, we describe a protocol for detecting differences in conjugation frequency, with high resolution, to estimate how efficiently the donor bacterium initiates conjugation.

Bacterial conjugation is an important step in the horizontal transfer of antibiotic resistance genes via a conjugative DNA element. In-depth comparisons ...

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 ...

Using Sniper-Cas9 to Minimize Off-target Effects of CRISPR-Cas9 Without the Loss of On-target Activity Via Directed Evolution

The development of clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 9 (Cas9) into therapeutic modalities requires the avoidance of its potentially deleterious off-target effects. Several methods have been devised to reduce such effects. Here, we present an Escherichia coli-based directed evolution method called Sniper-screen to obtain a Cas9 variant with optimized specificity and retained on-target activity, called Sniper-Cas9. Using Sniper-screen, positive and negative selection can be performed simultaneously. The screen can also be repeated with other single-guide RNA (sgRNA) sequences to enrich for the true positive hits. By using the CMV-PltetO1 dual promoter to express Cas9 variants, the performance of the pooled library can be quickly checked in mammalian cells. Methods to increase the specificity of Sniper-Cas9 are also described. First, the use of truncated sgRNAs has previously been shown to increase Cas9 specificity. Unlike other engineered Cas9s, Sniper-Cas9 retains a wild-type (WT) level of on-target activity when combined with truncated sgRNAs. Second, the delivery of Sniper-Cas9 in a ribonucleoprotein (RNP) format instead of a plasmid format is possible without affecting its on-target activity.

Here, we present a protocol to optimize CRISPR-Cas9 to achieve a higher specificity without the loss of on-target activity. We use a directed evolution approach called Sniper-screen to find a mutant Cas9 with the desired characteristics. Sniper-Cas9 is compatible with truncated single-guide RNAs and delivery in a ribonucleoprotein format, well-known strategies for achieving higher specificities.

The development of clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 9 (Cas9) into therapeutic modalities requires the ...

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 ...

A New Toolkit for Evaluating Gene Functions using Conditional Cas9 Stabilization

The clustered regularly interspaced short palindromic repeat- (CRISPR-) associated protein 9 (CRISPR/Cas9) technology has become a prevalent laboratory tool to introduce accurate and targeted modifications in the genome. Its enormous popularity and rapid spread are attributed to its easy use and accuracy compared to its predecessors. Yet, the constitutive activation of the system has limited applications. In this paper, we describe a new method that allows temporal control of CRISPR/Cas9 activity based on conditional stabilization of the Cas9 protein. Fusing an engineered mutant of the rapamycin-binding protein FKBP12 to Cas9 (DD-Cas9) enables the rapid degradation of Cas9 that in turn can be stabilized by the presence of an FKBP12 synthetic ligand (Shield-1). Unlike other inducible methods, this system can be adapted easily to generate bi-cistronic systems to co-express DD-Cas9 with another gene of interest, without conditional regulation of the second gene. This method enables the generation of traceable systems as well as the parallel, independent manipulation of alleles targeted by Cas9 nuclease. The platform of this method can be used for the systematic identification and characterization of essential genes and the interrogation of the functional interactions of genes in in vitro and in vivo settings.

Here, we describe a genome-editing tool based on the temporal and conditional stabilization of clustered regularly interspaced short palindromic repeat- (CRISPR-) associated protein 9 (Cas9) under the small molecule, Shield-1. The method can be used for cultured cells and animal models.

The clustered regularly interspaced short palindromic repeat- (CRISPR-) associated protein 9 (CRISPR/Cas9) technology has become a prevalent laboratory ...