We thank Emma Chory and Kevin Esvelt for their help and advice with hardware and software setup. Samir Aoudjane, Osaid Ather, and Erika DeBenedictis are supported by the Steel Perlot Early Investigator Grant.&#160;This work was supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (CC2239), the UK Medical Research Council (CC2239), and the Wellcome Trust (CC2239).

1. Hardware setup
NOTE: See Figure 2 for an overview of the hardware components of a PRANCE system and Figure 3 for photos of these components physically assembled.
<ol>
	<li>Obtain the primary hardware for the PRANCE system, including a liquid handling instrument, a plate reader, and auxiliary pumps. 
	NOTE: All PRANCE systems to date have been implemented on Medium to Large liquid handling instruments equipped with an 8-channel, individually addressable pipetting arms, a single-piston 96-tip pipetting arm, a robotic gripper for moving plates, an integrated wash station for tip sterilization, and an integrated plate reader capable of absorbance and luminescence measurements.</li>
	<li>Configure the heating strategies depending on the model and features of the liquid-handling robot. Use a heated plate carrier or heater-mediated robot climate control.</li>
	<li>Establish a tip-wash station to allow for tip reuse. 
	NOTE: To date, PRANCE systems have used off-the-shelf wash stations, although, in principle, this component could easily be constructed out of low-cost components.</li>
	<li>Establish a source of bacterial culture maintained at log-phase by setting up a real-time bioreactor running at 37 &#176;C as a chemostat/turbidostat. Alternatively, arrest a log-phase bacterial culture of at least 1 L volume pre-grown at 37 &#176;C in log-phase (OD600 between 0.25 and 0.45) at 4 &#176;C in a nearby refrigerator. Ensure that the culture, whether chilled or warm, is stirred regularly using a shaker plate or stir plate to prevent sedimentation.</li>
	<li>Configure the preferred pumps for robotic integration with the necessary software and drivers. Implement the software to enable the pumps to deliver defined quantities of liquid on the order of 10-100 mL. 
	NOTE: See the Table of Materials for pumps used in this implementation and the manufacturer&#39;s website for software used to operate these pumps and documentation on how to configure them. Such software for the pumps used in the PRANCE setup illustrated in this manuscript is provided open source in the following GitHub repository&#160;https://github.com/dgretton/std-96-pace PRANCE requires at least a three-pump manifold capable of pumping three separate channels (deliver bacteria to bacterial reservoir, deliver bleach to bacterial reservoir, and drain bacterial reservoir to waste), with the speed of each calibrated and controlled independently. In the past, people have used fish tank pumps and hydroponics pump arrays, although, in principle, any python-controllable peristaltic pump can be used. Essential functions include the ability to use a robot gripper to transfer plates in or out of the reader, to initiate a plate reader measurement, and to access measurements.</li>
	<li>3D-Print the required custom deck components for the PRANCE system, including, at minimum, the bacterial reservoir/distribution manifold (&#34;waffle&#34;), as found in Supplemental File 1 (https://drive.google.com/file/d/16ELcvfFPzBzNSto0xUrBe-shi23J9Na7/view?usp=share_link). Secure these containers onto the deck and calibrate their positions using standard Liquid Handling Robot software. Connect the reservoir to the pump array. 
	NOTE: Consult the robot manufacturer&#39;s documentation for details of how to perform the calibration as it will be robot-dependent. Resin-based 3D printers are most appropriate; an example of the printer type used is given in the Table of Materials; standard clear resin was used with the default printer settings.</li>
	<li>Equip the system with a drain compatible with the local biosafety recommendations.</li>
	<li>Place labware on the deck of the Liquid Handling Robot as exemplified in Figure 4.</li>
	<li>Follow standard safety procedures, including the use of standard laboratory personal protective equipment (i.e., lab coat, gloves, and eye protection).</li>
</ol>
2. Software preparation
<ol>
	<li>Install open-source software used for controlling Liquid Handling robots with python11, available from the open-source PyHamilton repository.&#160;https://github.com/dgretton/pyhamilton</li>
	<li>Modify and calibrate the deck layout file for the Liquid Handling robot software to accurately reflect the labware positions on the robot deck, as shown in&#160;Figure 4. 
	NOTE: The setup used here uses the software provided by the manufacturer of the liquid handling robot, according to the provided documentation.</li>
	<li>Run the PRANCE robot method program in simulation mode.
	<ol>
		<li>Open the Command Line with the following commands (in the Windows operating system), as shown in Figure 5. 
		Windows key + R 
		&#8203;Enter: cmd</li>
		<li>Change the parent directory to the directory of the robot method program. Enter a command as below with the correct path, as shown in Figure 5. 
		&#8203;CD c:\Robot_methods_directory\PRANCE</li>
		<li>Call the robot method program with Python with the simulation mode flag, as shown in Figure 5. 
		py robot_method.py --simulate</li>
		<li>Select the PLAY button in the upper left of the Robot Run Control window that will open when the program is executed (Figure 5). 
		NOTE: Ensure that the PRANCE method can run without errors in simulation before moving forward. It becomes obvious if the script is able to operate in simulation mode without errors, as it will complete multiple loops of the main program without the system&#39;s error handling being called, which terminates the main program loop.</li>
	</ol>
	</li>
	<li>Run the PRANCE robot method program with the simulation mode disabled.
	<ol>
		<li>Open the Command Line in the appropriate directory (Figure 5). 
		Windows key + R 
		Enter: cmd 
		&#8203;CD c:\Robot_methods_directory\PRANCE</li>
		<li>Call the robot method program with Python without flags: 
		py robot_method.py</li>
		<li>Select the PLAY button in the upper left of the Robot Run Control window that will open when the program is executed.</li>
		<li>Confirm that PyHamilton can control the instrument and cause it to initialize.</li>
	</ol>
	</li>
	<li>Establish real-time data synchronization. 
	NOTE: To date, PRANCE systems have used networked computers that allow users to monitor the log files and real-time plate reader measurement graphs via remote file-sharing software, or via a remote desktop.</li>
	<li>Turn off automatic updates.</li>
</ol>
3. Pre-run preparation
<ol>
	<li>Ensure that log-phase bacterial culture sources are available for all cultures required for the planned run and that they are being actively stirred to prevent sedimentation. Use an active chemostat/turbidostat or a growth-arrested refrigerated pregrown culture.</li>
	<li>Update the controller manifest file with the details of what volume (range 0-500 &#181;L) of which bacterial culture is to be pumped into each well of the 96-well lagoon per program cycle. This allows precise control of the effective lagoon dilution rate. This can be seen in Figure 6.
	<ol>
		<li>Calculate the Dilution rate of the lagoon using the DilutionCalculator.xlsx spreadsheet (provided as Supplemental File 2), as seen in Figure 7.</li>
	</ol>
	</li>
	<li>Update the robot_method.py file with the intended lagoon height. To follow this protocol, use 14 (in millimeter units) as the default value for the variable fixed_lagoon_height in the program. This corresponds to a lagoon volume of 550 &#181;L on the system but may differ depending on the particular 96-deep-well plate used.</li>
	<li>Place clean filtered pipette tips onto the robot deck in their designated positions and tape the tip racks to the tip holders to ensure stability during the run.</li>
	<li>Place clean 96-deep-well plates onto the robot deck in their designated positions.</li>
	<li>Place clean 96-well reader plates onto the robot deck in their designated positions.</li>
	<li>Ensure that the plate reader tray is not occupied by a pre-existing plate.</li>
	<li>Ensure that pumps are connected to the computer and are assigned to the correct address.</li>
	<li>Clean the pump lines by activating the pumps to pump bleach and then water.</li>
	<li>Connect pump lines to the appropriate sources and outputs, paying close attention to ensure the correct lines are connected to the relevant bacterial cultures.</li>
	<li>Refill tanks/buckets containing bleach/water for bacterial reservoir and pipette tip washing.</li>
	<li>Ensure all on-deck components, particularly mobile elements, are stabilized in their designated positions.</li>
	<li>Activate heaters as per local implementation to target temperature (i.e.&#160;37 &#176;C; Figure 8).</li>
	<li>Run the UV Sterilization Protocol file for 10 min to operate the built-in UV sterilization lamp in the liquid-handling robots as supplied by the manufacturer (Figure 9).
	<ol>
		<li>Select the PLAY button in the upper left of the Robot Run Control window that will open when the program is executed.</li>
		<li>Run the file with the parametrized option for 600 s.</li>
	</ol>
	</li>
	<li>Ensure that the Robot Run Control software is closed. 
	NOTE: The robot method program will crash if there are any existing instances of the Run Control software running.</li>
</ol>
4. Hardware and software integration
<ol>
	<li>Conduct a &#39;water run,&#39; where the PRANCE robot method program is run overnight with water substituting for all cultures and wet reagents. 
	NOTE: This test can be run at room temperature.
	<ol>
		<li>Complete the pre-run preparation as detailed above with the controller_manifest and robot_method set up for an effective lagoon dilution rate of 1 volume/h as shown in Figure 5 and Figure 6.</li>
		<li>Connect the &#39;bacteria in&#39; line to a container of water to replace log-phase bacteria for the water run. 
		NOTE: Food coloring can be added to the water sources to track liquid movement through the experiment.</li>
		<li>Open the Command Line in the appropriate directory.</li>
		<li>Call the robot method program with Python with the new run flag (py robot_method.py --new) and input the requested arguments, including log file name (TestRun), number of lagoon wells (16), cycle duration (30), number of cycles per reader plate measurement (4), and inducer volume (inducer volume is 0 &#181;L for this test run, during an evolution where mutagenesis is induced with arabinose, this value may be 10 &#181;L), as shown in Figure 5.</li>
		<li>Select the PLAY button in the upper left of the Robot Run Control window that will open when the program is executed once arguments have been provided. 
		NOTE: The PRANCE method can be started using an empty lagoon plate, and the liquid volume of the lagoons will equilibrate to the final volume over the first six cycles.</li>
	</ol>
	</li>
	<li>Conduct a &#39;bacteria-only run&#39;, where the PRANCE protocol is run overnight only with bacterial culture at target temperature but with no bacteriophage.
	<ol>
		<li>Complete the pre-run preparation as detailed above with the controller_manifest and robot_method set up for an effective lagoon dilution rate of 1 volume/h, as shown in Figure 5 and Figure 6. Ensure that heaters are switched on for a target temperature of 37 &#176;C.</li>
		<li>Connect the &#39;bacteria in&#39; line to the selected source of log-phase bacteria.</li>
		<li>Open the Command Line in the appropriate directory.</li>
		<li>Call the robot method program with Python with the new run flag (py robot_method.py --new) and input the requested arguments, as detailed previously in section 4.1.4.</li>
		<li>Select the PLAY button in the upper left of the Robot Run Control window that will open when the program is executed once the arguments have been provided.</li>
	</ol>
	</li>
	<li>Run an &#39;infection test,&#39; where phages bearing an evolved protein are challenged to propagate on bacteria requiring that protein. 
	NOTE: Decide in advance which lagoons will be inoculated with phage and which lagoons will not be inoculated and thus serve as no-phage control lagoons to detect cross-contamination.
	<ol>
		<li>Complete the pre-run preparation as detailed above with the controller_manifest and robot_method set up for an effective dilution rate of 1 volume/h, as shown in Figure 5 and Figure 6. Ensure that heaters are switched on for a target temperature of 37 &#176;C.</li>
		<li>Connect the &#39;bacteria in&#39; line to the selected source of log-phase bacteria.</li>
		<li>Open the Command Line in the appropriate directory.</li>
		<li>Call the robot method program with Python with the new run flag (py robot_method.py --new) and input the requested arguments as detailed previously in section 4.1.4.</li>
		<li>Select the PLAY button in the upper left of the Robot Run Control window that will open when the program is executed once arguments have been provided.</li>
		<li>Before adding bacteriophage, run the method for 2-3 h to equilibrate the volume and bacteria OD in the lagoon plates.</li>
		<li>Inoculate the with-phage lagoons with 106 pfu/mL of bacteriophage at the end of a run cycle when the program is sleeping (e.g., 5.5 &#181;L of phage aliquot at 108 pfu/mL, as determined by plaque assay or qPCR), into a 550 &#181;L lagoon.</li>
		<li>Run the program overnight and then check the phage titer in the lagoon wells by plaque assay or qPCR.</li>
	</ol>
	</li>
</ol>

Setting Up PRANCE: A Comprehensive Guide for Robotics-Accelerated Evolution

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The authors have no conflicts to disclose.

Despite efforts to standardize equipment, practically speaking, every PRANCE setup will be different due to changes in equipment supply, hardware, and software versioning. As a result, each PRANCE setup manifests unique setup challenges, demanding a comprehensive understanding of the purpose of each component for effective modular troubleshooting.
This method delineates a step-by-step protocol for the setup and testing of an established PRANCE system. We first focus on the critical elements of the hardware and software and then detail the essential steps to prepare for and conduct a series of test runs, which establish that the system is ready for PRANCE.
An essential feature of the hardware is optimization to reduce the risk of sample cross-contamination during multiplexed experiments using bacteriophage. It is recommended to use exclusively filtered tips with robot tip technology that is compatible with tip reuse and is thought to minimize aerosols produced during tip ejection by avoiding force-fit tips. Robust tip washing as per this protocol allows for tip reuse although the adequacy of this must be validated as part of the infection test on each system. Self-sterilization is also dependent on a consistent supply of water and bleach for the system. These are stored in tanks/buckets and if depleted will result in impaired self-sterilization and rapid cross-contamination. Photographs can be taken of the tanks/buckets taken before and after the program runs to benchmark the rate at which the washing equipment consumes water and bleach given a particular pump setup.
Another key element of the system is the maintenance of the bacterial growth phase and temperature. PRANCE experiments are conducted using the S2060 E. coli bacterial strain (Addgene: #105064). This is a K12-derived F-plasmid-containing strain optimized to reduce biofilms7. In addition, the F-plasmid in this strain has been edited with the addition of a tetracycline resistance cassette for plasmid maintenance, luxCDE and luxR to complement luxAB-mediated luminescence monitoring, as well as lacZ under the phage shock promoter to allow for colorimetric visualization of plaques. The F-plasmid-encoded F-pilus is necessary for M13 phage infection. Bacteria used in PACE must therefore be cultured at 37 &#176;C and at mid-log phase when the F-pilus12 is expressed and M13 phage infection, propagation, and evolution are possible. For static temperature regulation, an off-the-shelf heated plate carrier can be employed. An alternative is simply heating the air going into the HEPA filter using inexpensive heaters, though this is not recommended as it may lead to accelerated wear and tear on the hardware. In addition, this accelerates the evaporation of auxiliary on-deck fluids, such as the bleach/water buckets and inducer, when used.
Calibration of the software packages is also essential for proper system function. Divergences between the software deck layout and the actual robot deck are the most common cause of system failure during operation. Regular calibration of the auxiliary pumps that supply bacterial culture, bleach, and drain the system is vital as peristaltic pump usage can lead to tubing wear and fluid volume alterations.
The water run test will rapidly reveal a number of common setup problems, including incorrect liquid handling settings, fluidics leaks/faulty connections, and software instability. A successful water run will exhibit no unexpected liquid leaks and run stably without errors overnight. There are a number of common issues that may arise during a water run such as failure to execute certain liquid-handling steps, dripping from pipettes, and the protocol stopping mid-run. In case of failure to execute certain liquid handling steps, confirm that all liquid classes have been installed. These list the appropriate viscosity and pipetting speeds and are adjusted in the robot control software provided by the manufacturer. If there is dripping from pipettes, it is important for robot pipetting arm settings to be correct to enable clean pipetting and eliminate phage cross-contamination. Successful robotic pipetting requires, in addition to correct liquid classes, correct deck layout heights of all labware, and appropriate pipetting height offsets specified in the PRANCE robot method program. These height offsets may require direct adjustment. If the protocol stops mid-run, often this will be generated by a wide array of errors that indicate that the deck layout file may not match the actual deck configuration.
The bacteria-only run test will reveal issues with plate reader settings and real-time data visualization, problems with excessive bleach concentration or insufficient rinsing, and temperature stability. A successful bacteria-only run will exhibit equilibration of lagoon absorbance over the first three cycles, followed by stable absorbance for the duration of the run. In addition, it may reveal several common issues. This is the first step where the data generated by the plate reader are plotted. Data in the plate reader database may not be saved properly or plotted properly. If bacteria fail to equilibrate in their absorbance, this may indicate that the bleach concentration is too high. Excessive bleach or insufficient washing can sterilize the entire experiment, rather than just the piece of labware. If this is suspected, bleach-detecting strips can be used to test the lagoon. The stability of the temperature of the culture can be checked with a thermometer gun.
A successful infection test indicates that the system is ready for PRANCE runs. An infection test can be performed by inoculating a subset of lagoons containing bacterial culture. These bacteria will express pIII when infected by the appropriate phage that lacks the gene for pIII (&#916;gIII), allowing phage propagation. One possible combination for testing is to use S2060 bacteria transformed with a plasmid expressing pIII under the phage shock promoter with any &#916;gIII phage. We recommend using &#916;gIII phage bearing the wild-type T7 RNA Polymerase with S2060 bacteria transformed with an accessory plasmid, in which pIII and luxAB are driven by the T7 promoter (Plasmid pJC173b13), as illustrated in Figure 1. This also allows plate-reader-mediated monitoring of infection during the test run. Definitive evidence of the success of the infection test and lack of cross-contamination will come from phage titering of test and control lagoons. Where a luciferase reporter&#160;is used, an increase in luminescence in test wells only, as seen in Figure 3, is also an indicator of successful phage infection and propagation. The gold standard for phage titer quantification is the plaque assay7. There is also a protocol for M13 quantification by qPCR7 that may be faster, although this does not discriminate between infectious and non-infectious phage particles and thus may overestimate titers.
The main program references a manifest file, this is a plain text database file, which dictates the dilution volume per cycle of each propagating culture as well as the selection of any number of potential bacterial culture feedstocks, which may differ in selection stringency. In this manner, the manifest file defines many of the parameters of the PRANCE run. It should be noted that this file can be edited during the run by either the operator or the system, meaning that manual or automatic feedback control can be effected.
The utility of a fully functioning PRANCE setup lies in its capacity to rapidly evolve large populations in a carefully monitored and controlled environment. The plate-based format distinguishes PRANCE from other techniques, like using smaller off-the-shelf turbidostat-based systems14,15. The plate-based setup not only facilitates easy integration with additional robotic processing steps but also compatibility with other laboratory instruments such as centrifuges. Moreover, the ability to conduct accelerated evolution concurrently across multiple instances introduces an additional dimension to the experiment, enhancing the prospect of achieving diverse and robust results. The granular control and feedback system integral to PRANCE further bolsters the predictability and reliability of the experiment, marking a significant advancement in the field of directed evolution techniques. However, this technique is limited in the number of parallel experiments it can conduct. Depending on the configuration, PRANCE setups are usually limited either by robot pipetting speed or by available deck space.
The same hardware and software used for PRANCE can also be applied to evolution methods that do not involve bacteriophage. As demonstrated in the many-turbidostats method11, this same instrument can be employed exclusively with bacteria, enabling whole-genome adaptive evolution experiments. This adaptability widens the scope of this instrument, paving the way for new forms of Robotics-accelerated Evolution.

PRANCE is a combination of two powerful directed evolution techniques. First is PACE1, a molecular technique that couples rounds of gene diversification and selection to the fast life cycle of the M13 bacteriophage, enabling rapid rounds of evolution to occur continuously in liquid phage culture. This selection is driven by the use of a plasmid-encoded gene circuit that couples the function of the evolving protein to the expression of pIII, M13&#39;s tail coat protein, which is needed for phage propagation, this&#160;is illustrated in Figure 1. At the experimental level, continuous dilution of the liquid phage culture allows for continuous selection. Selection stringency can thus be modulated both at the level of the gene circuit as well as at the experimental level by controlling the phage culture dilution rate. PACE can therefore be applied to any biomolecule engineering challenge for which there is a molecular sensor that can detect the desired activity in E. coli bacteria to induce pIII expression. Applications include the evolution of protein-protein binding2,3,4, protein-DNA binding5, protein solubility6, and numerous specific enzymatic functions7. Second is Robotics-accelerated Evolution8,9, which uses a feedback controller to eliminate two common failure modes of directed evolution: extinction, which occurs when the environment is too stringent, and lack of evolution, which occurs when the environment is too lenient. Unlike serial passaging of phage as done in PANCE (Phage-assisted Non-continuous Evolution)7,10, Robotics-accelerated &#34;near-continuous&#34; evolution involves rapid pipetting that maintains cultures at mid-log phase, allowing populations to experience continuous cycles of infection and propagation. When these two technologies are used together, they are referred to as PRANCE, for Phage and Robotics-assisted Near-continuous Evolution8, which enables robust, multiplexed, and rapid continuous evolution. PRANCE has been used to evolve polymerases, tRNAs, and amino-acyl tRNA synthetases and to do feedback control during those evolutions to improve their speed and reliability8.
There are several details of the hardware and software setup for PRANCE that enable the use of bacteriophage on a liquid-handling robot. Instead of using default software provided by the robot manufacturer, we use a python-based open-source software package11, which enables fast, concurrent execution and thus, the ability to keep the semi-continuous bioreactors at mid-log phase. Researcher hands-off time can be extended to several days by having several on-deck components routinely self-sterilize, and this is achieved with automatic control of pumps that can bleach and rinse these components. Phage cross-contamination can be eliminated by the use of a liquid handling robot that does not use force-fit tips and careful adjustment of liquid handling settings.

<table><tbody><tr><td>3D printed bacterial reservoir &quot;waffle&quot;</td><td>-</td><td>-</td><td>https://drive.google.com/file/d/16ELcvfFPzBzNSto0xUrBe-shi23J9Na7/view; For Robot deck</td></tr><tr><td>3D printer</td><td>FormLabs</td><td>Form 3B+</td><td>3D printer components</td></tr><tr><td>3D printer resin (clear)</td><td>FormLabs</td><td>RS-F2-GPCL-04</td><td>consumable for 3D printer</td></tr><tr><td>8-1,000 &amp;micro;L head</td><td>Hamilton</td><td>10140943</td><td>For Liquid handling robot</td></tr><tr><td>96-1,000 &amp;micro;L pipetting head</td><td>Hamilton</td><td>10120001</td><td>For Liquid handling robot</td></tr><tr><td>Black polystyrene plate reader microplates</td><td>Millipore Sigma</td><td>CLS3603</td><td>For Robot deck</td></tr><tr><td>BMG Labtech Spectrostar FLuorstar Omega</td><td>BMG Labtech</td><td>10086700</td><td>For Liquid handling robot</td></tr><tr><td>Cleaning solution</td><td>Fluorochem Limited</td><td>F545154-1L</td><td>used to clean the liquid handling parts of the robot</td></tr><tr><td>Deep Well plates</td><td>Appleton Woods</td><td>ACP006</td><td>these are used to contain evolving bacteria on the deck of the robot</td></tr><tr><td>encolsure heater</td><td>Stego</td><td>13060.0-01</td><td>heats inside robot enclosure</td></tr><tr><td>Hamilton STAR</td><td>Hamilton</td><td>870101</td><td>For Liquid handling robot</td></tr><tr><td>Heater</td><td>Erbauer</td><td>BGP2108-25</td><td>For Liquid handling robot</td></tr><tr><td>HIG Bionex centrifuge</td><td>Hamilton</td><td>10086700</td><td>For Liquid handling robot</td></tr><tr><td>iSWAP plate gripper</td><td>Hamilton</td><td>190220</td><td>For Liquid handling robot</td></tr><tr><td>laboratory tubing</td><td>Merck</td><td>Z280356</td><td>to construct liquid handling manifold</td></tr><tr><td>luer to barb connector</td><td>AIEX</td><td>B13193/B13246</td><td>for connectorizing tubing</td></tr><tr><td>Magnetic stir plate</td><td>Camlab</td><td>SKU - 1189930</td><td>For Auxiliary Fridge</td></tr><tr><td>Molcular pipetting arm</td><td>Hamilton</td><td>173051</td><td>For Liquid handling robot</td></tr><tr><td>Omega</td><td>BMG labtech</td><td>5.7</td><td>plate reader control software</td></tr><tr><td>One way Check Valves</td><td>Masterflex</td><td>MFLX30505-91</td><td>to one way sections of liquid handling manifold</td></tr><tr><td>pyhamilton</td><td>MIT/Open source</td><td>https://github.com/dgretton/std-96-pace%20PRANCE</td><td>open source python robot control software</td></tr><tr><td>pymodbus</td><td>opensource</td><td>3.5.2</td><td>python pump software interface</td></tr><tr><td>Refrigetator</td><td>Tefcold</td><td>FSC175H</td><td>allows cooled bacteria to be used instead of turbidostat</td></tr><tr><td>S2060 Bacterial strain</td><td>Addgene</td><td>Addgene: #105064</td><td>&lt;em&gt;E. coli&lt;/em&gt;</td></tr><tr><td>temperature controller</td><td>Digiten</td><td>DTC102UK</td><td>Used to control heaters thermostatically</td></tr><tr><td>Thermostat switch controller</td><td>WILLHI</td><td>WH1436A</td><td>WILLHI WH1436A 10 A Temperature Controller 110 V Digital Thermostat Switch Sous Vide Controller NTC 10K Sensor Improved Version; for Liquid handling robot</td></tr><tr><td>Venus</td><td>Hamilton</td><td>4.6</td><td>proprietary robot control software</td></tr><tr><td>Wash Station for MPH 96/384</td><td>Hamilton</td><td>190248</td><td>For Liquid handling robot</td></tr><tr><td>&lt;strong&gt;Suggested pump manufacturers&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>&lt;strong&gt;Company&lt;/strong&gt;</td><td>&lt;strong&gt;Catalog number&lt;/strong&gt;</td><td>&lt;strong&gt;Notes&lt;/strong&gt;</td><td>&lt;strong&gt;Documentation&lt;/strong&gt;</td></tr><tr><td>Agrowtek</td><td>AD6i Hexa Pump</td><td></td><td>https://www.agrowtek.com/doc/im/IM_ADi.pdf</td></tr><tr><td>Amazon</td><td>INTLLAB 12V DC</td><td></td><td></td></tr><tr><td>Cole-Parmer</td><td>EW-07522-3</td><td>Masterflex L/S Digital Drive, 100 RPM, 115/230 VAC</td><td>https://pim-resources.coleparmer.com/instruction-manual/a-1299-1127b-en.pdf</td></tr><tr><td>Cole-Parmer</td><td>EW-07554-80</td><td>Masterflex L/S Economy variable-speed drive, 7 to 200 rpm, 115 VAC</td><td>https://pim-resources.coleparmer.com/instruction-manual/a-1299-1127b-en.pdf</td></tr></tbody></table>

a practical guide to phage- and robotics-assisted near-continuous evolution

Robotics-accelerated Evolution techniques improve the reliability and speed of evolution using feedback control, improving the outcomes of protein and organism evolution experiments. In this article, we present a guide to setting up the hardware and software necessary to implement Phage- and Robotics-assisted Near-continuous Evolution (PRANCE). PRANCE combines fast phage-based molecular evolution with the ability to run hundreds of independent, feedback-controlled evolution experiments simultaneously. This paper will describe the hardware requirements and setup for PRANCE, including a liquid-handling instrument, a plate reader, auxiliary pumps, heaters, and 3D-printed containers. We describe how to configure the liquid handling robot to be compatible with Python-based open-source software. Finally, we provide suggestions for the first two experiments that can be conducted with a newly constructed PRANCE system that exercises its capabilities and validates that the system is ready to conduct multiplexed evolution. This guide is intended to serve as a handbook for navigating the considerable equipment setup associated with conducting robotics-accelerated evolution.

Infection test results 
This test will reveal problems with bacterial culture, phage cloning and titer, temperature stability of the equipment, liquid handling settings, and plate reader integration. A successful phage infection test will reveal clear and rapid phage infection in lagoons inoculated with phage, and no signal in no-phage lagoons. Figure 10 shows some representative results of a phage infection test. Experimental results can also be compared to Figures 1d and 1c of this PRANCE paper8, depending on whether a &#34;hot PRANCE&#34; (fed by a live bacterial turbidostat) or &#34;cool PRANCE&#34; (fed by chilled mid-log phase culture) configuration is being implemented. This test may reveal several common issues. Issues with bacterial culture preparation can often result in weak or absent infection. Bacteria can only be optimally infected by M13 phage when they are in mid-log phase and at 37 &#176;C. At other temperatures and growth stages, they exhibit weaker pilus expression and thus are less susceptible to phage infection12. Inoculating with low-titer phage, or phage with backbone mutations can result in delayed or absent signal. Issues with plate reader gain settings for fluorescence or luminescence will be revealed by this test.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65974/65974fig01v4.jpg" /> 
Figure 1: Schematic of the genetic circuit operating during the infection test run of the PRANCE apparatus. When T7 RNA polymerase, encoded on the phage genome, infects the Escherichia coli host, it is transcribed and binds on the AP at the T7 promoter, which leads to transcription of the pIII phage protein and luxAB protein, which, in turn, facilitates phage propagation and production of luminescence. Abbreviations: PRANCE = Phage- and Robotics-assisted Near-continuous Evolution; AP = accessory plasmid. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65974/65974fig02.jpg" /> 
Figure 2: A schematic of the physical components of the PRANCE system. A fridge stores stirred cultures, which are then moved onto the robot deck by an array of pumps, to the bacterial reservoir, &#34;the waffle.&#34; The liquid-handling robot is used to move bacterial cultures from &#34;the waffle&#34; using the pipetting head to the holding wells to warm up to incubation temperature, and then to the lagoons where the main incubation occurs. Both the holding wells and the lagoons are standard 2 mL deep-well plates. The robot takes samples into single-use reader plates, which are in turn moved to a plate reader for measurement. Abbreviation: PRANCE = Phage- and Robotics-assisted Near-continuous Evolution. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65974/65974fig03.jpg" /> 
Figure 3: The PRANCE robotic apparatus. (A) PRANCE setup. (I) HEPA filter and external heater. (II) Culture refrigerator. (III) Main robot enclosure. (IV) Plate reader. (V) Pumps and tanks. (B) Robot enclosure. (VI) Main culture pumps. (VII) Water, waste, and bleach tanks. (VIII) Washer pumps. (C) Robot enclosure. (IX) Robot pipetting arm and gripper. (X) Pipette tips. (XI) 3D-Printed component to allow culture distribution onto the robot (&#34;the waffle&#34;). (XII) Plates for sampling in the plate reader. (XIII) Buckets for tip washing. (XIV) &#34;Lagoons&#34;: culture vessels where evolutionary culturing takes place. Abbreviations: PRANCE = Phage- and Robotics-assisted Near-continuous Evolution; HEPA = high-efficiency particulate air. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/65974/65974fig04.jpg" /> 
Figure 4: Deck Layout. (A) 3D representation of the deck layout in the robot control software. (B) Photograph of the deck components. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/65974/65974fig05.jpg" /> 
Figure 5: Screenshot of the command line with example parameters (above) and run control software (below). The play button is located at the top left and can be clicked with a mouse or actuated with a touchscreen depending on local implementation. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/65974/65974fig06.jpg" /> 
Figure 6: The controller manifest file as configured for test runs. Lagoons containing culture #0 would be in columns 1 and 3 of the 96-deep-well plate. Remaining columns would be empty. Rows A, B, D, and E of the 96-deep-well-plate are marked on the right column for infection by phage (1), the other rows (0) are no-phage controls.This instance of the controller manifest would result in the program diluting the lagoon with 210 &#181;L of culture every cycle. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/65974/65974fig07.jpg" /> 
Figure 7: Calculation of the effective lagoon dilution rate using the DilutionCalculator Spreadsheet. See Supplemental File 2 for the DilutionCalculator Spreadsheet. As seen in this figure, a 550 &#181;L lagoon that is diluted by 210 &#181;L of fresh culture every 30 min cycle, with 150 &#181;L samples for reader plate measurement being taken every four cycles will correspond to an effective dilution rate of 1.0 lagoon volumes/h (after every 1 h, 50% of the original lagoon liquid at the start of the hour will remain) <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/65974/65974fig08.jpg" /> 
Figure 8: Robot&#160;heater system. The heater is activated by plugging in the power supply as indicated by the red circle. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/65974/65974fig09.jpg" /> 
Figure 9: Settings of the UV decontamination protocol. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig09large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/65974/65974fig10.jpg" /> 
Figure 10: A measurement of an infection test run on the PRANCE system. Samples are taken during the run and measurements of the luminescence and absorbance are made. For each lagoon, the luminescence measurements are divided by the corresponding absorbance measurement and plotted as a function of time. The lagoons that have been infected with Phage are colored in green, whereas the uninfected control lagoons are colored in black. Abbreviation: PRANCE = Phage- and Robotics-assisted Near-continuous Evolution. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental File 1: STL file for 3D-printing the required custom deck components for the PRANCE system, including, at minimum, the bacterial reservoir/distribution manifold (&#34;waffle&#34;). <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/waffle_mini (1).zip" target="_blank">Please click here to download this File.</a>
Supplemental File 2: DilutionCalculator Spreadsheet. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/65974/65974_SI DilutionCalculator.zip" target="_blank">Please click here to download this File.</a>

Watch this Scientific Journal Video about Author Spotlight: Advancing Protein Engineering – Harnessing Evolution Through PRANCE and Lab Automation at JoVE.com

Author Spotlight: Advancing Protein Engineering &#8211; Harnessing Evolution Through PRANCE and Lab Automation

Phage- and Robotics-assisted Near-continuous Evolution (PRANCE) is a technique for rapid, robust protein evolution. Robotics allows the parallelization of experiments, real-time monitoring, and feedback control.

A Practical Guide to Phage- and Robotics-Assisted Near-Continuous Evolution

Robotics-accelerated Evolution techniques improve the reliability and speed of evolution using feedback control, improving the outcomes of protein and ...

a-practical-guide-to-phage-robotics-assisted-near-continuous

Universidad de Cartagena UDEC

Research

JoVE Journal

Bioengineering

1.4K Views.  The Francis Crick Institute. Phage- and Robotics-assisted Near-continuous Evolution (PRANCE) is a technique for rapid, robust protein evolution. Robotics allows the parallelization of experiments, real-time monitoring, and feedback control.

Video: Author Spotlight: Advancing Protein Engineering – Harnessing Evolution Through PRANCE and Lab Automation

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) ...

Genetics

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 ...

Following Cell-fate in E. coli After Infection by Phage Lambda

The system comprising bacteriophage (phage) lambda and the bacterium E. coli has long served as a paradigm for cell-fate determination1,2. Following the simultaneous infection of the cell by a number of phages, one of two pathways is chosen: lytic (virulent) or lysogenic (dormant)3,4. We recently developed a method for fluorescently labeling individual phages, and were able to examine the post-infection decision in real-time under the microscope, at the level of individual phages and cells5. Here, we describe the full procedure for performing the infection experiments described in our earlier work5. This includes the creation of fluorescent phages, infection of the cells, imaging under the microscope and data analysis. The fluorescent phage is a "hybrid", co-expressing wild- type and YFP-fusion versions of the capsid gpD protein. A crude phage lysate is first obtained by inducing a lysogen of the gpD-EYFP (Enhanced Yellow Fluorescent Protein) phage, harboring a plasmid expressing wild type gpD. A series of purification steps are then performed, followed by DAPI-labeling and imaging under the microscope. This is done in order to verify the uniformity, DNA packaging efficiency, fluorescence signal and structural stability of the phage stock. The initial adsorption of phages to bacteria is performed on ice, then followed by a short incubation at 35&deg;C to trigger viral DNA injection6. The phage/bacteria mixture is then moved to the surface of a thin nutrient agar slab, covered with a coverslip and imaged under an epifluorescence microscope. The post-infection process is followed for 4 hr, at 10 min interval. Multiple stage positions are tracked such that ~100 cell infections can be traced in a single experiment. At each position and time point, images are acquired in the phase-contrast and red and green fluorescent channels. The phase-contrast image is used later for automated cell recognition while the fluorescent channels are used to characterize the infection outcome: production of new fluorescent phages (green) followed by cell lysis, or expression of lysogeny factors (red) followed by resumed cell growth and division. The acquired time-lapse movies are processed using a combination of manual and automated methods. Data analysis results in the identification of infection parameters for each infection event (e.g. number and positions of infecting phages) as well as infection outcome (lysis/lysogeny). Additional parameters can be extracted if desired.

Following Cell-fate in E. coli After Infection by Phage Lambda

This article describes the procedure for preparing a fluorescently-labeled version of bacteriophage lambda, infection of E. coli bacteria, following the infection outcome under the microscope, and analysis of infection results.

The system comprising bacteriophage (phage) lambda and the bacterium E. coli has long served as a paradigm for cell-fate determination1,2. Following the ...

Immunology and Infection

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 ...

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

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 ...

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

The Long-Term Evolution Experiment (LTEE) has followed twelve populations of Escherichia coli as they have adapted to a simple laboratory environment for more than 35 years and 77,000 bacterial generations. The setup and procedures used in the LTEE epitomize reliable and reproducible methods for studying microbial evolution. In this protocol, we first describe how the LTEE populations are transferred to fresh medium and cultured each day. Then, we describe how the LTEE populations are regularly checked for possible signs of contamination and archived to provide a permanent frozen "fossil record" for later study. Multiple safeguards included in these procedures are designed to prevent contamination, detect various problems when they occur, and recover from disruptions without appreciably setting back the progress of the experiment. One way that the overall tempo and character of evolutionary changes are monitored in the LTEE is by measuring the competitive fitness of populations and strains from the experiment. We describe how co-culture competition assays are conducted and provide both a spreadsheet and an R package (fitnessR) for calculating relative fitness from the results. Over the course of the LTEE, the behaviors of some populations have changed in interesting ways, and new technologies like whole-genome sequencing have provided additional avenues for investigating how the populations have evolved. We end by discussing how the original LTEE procedures have been updated to accommodate or take advantage of these changes. This protocol will be useful for researchers who use the LTEE as a model system for studying connections between evolution and genetics, molecular biology, systems biology, and ecology. More broadly, the LTEE provides a tried-and-true template for those who are beginning their own evolution experiments with new microbes, environments, and questions.

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

This protocol describes how to maintain the Escherichia coli Long-Term Evolution Experiment (LTEE) by performing its daily transfers and periodic freeze-downs and how to conduct competition assays to measure fitness improvements in evolved bacteria. These procedures can serve as a template for researchers starting their own microbial evolution experiments.

The Long-Term Evolution Experiment (LTEE) has followed twelve populations of Escherichia coli as they have adapted to a simple laboratory environment for ...

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.

Here, we present phenomic approaches for the functional characterization of putative phage genes. Techniques include a developed assay capable of monitoring host anabolic metabolism, the Multi-phenotype Assay Plates (MAPs), in addition to the established method of metabolomics, capable of measuring effects to catabolic metabolism.

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage ...

Using Phage Display to Develop Ubiquitin Variant Modulators for E3 Ligases

Ubiquitin is a small 8.6 kDa protein that is a core component of the ubiquitin-proteasome system. Consequently, it can bind to a diverse array of proteins with high specificity but low affinity. Through phage display, ubiquitin variants (UbVs) can be engineered such that they exhibit improved affinity over wildtype ubiquitin and maintain binding specificity to target proteins. Phage display utilizes a phagemid library, whereby the pIII coat protein of a filamentous M13 bacteriophage (chosen because it is displayed externally on the phage surface) is fused with UbVs. Specific residues of human wildtype ubiquitin are soft and randomized (i.e., there is a bias towards to native wildtype sequence) to generate UbVs so that deleterious changes in protein conformation are avoided while introducing the diversity necessary for promoting novel interactions with the target protein. During the phage display process, these UbVs are expressed and displayed on phage coat proteins and panned against a protein of interest. UbVs that exhibit favorable binding interactions with the target protein are retained, whereas poor binders are washed away and removed from the library pool. The retained UbVs, which are attached to the phage particle containing the UbV's corresponding phagemid, are eluted, amplified, and concentrated so that they can be panned against the same target protein in another round of phage display. Typically, up to five rounds of phage display are performed, during which a strong selection pressure is imposed against UbVs that bind weakly and/or promiscuously so that those with higher affinities are concentrated and enriched. Ultimately, UbVs that demonstrate higher specificity and/or affinity for the target protein than their wildtype counterparts are isolated and can be characterized through further experiments.

Ubiquitination is a critical protein post-translational modification, dysregulation of which has been implicated in numerous human diseases. This protocol details how phage display can be utilized to isolate novel ubiquitin variants that can bind and modulate the activity of E3 ligases that control the specificity, efficiency, and patterns of ubiquitination.

Ubiquitin is a small 8.6 kDa protein that is a core component of the ubiquitin-proteasome system. Consequently, it can bind to a diverse array of proteins ...

Biochemistry

Directed Evolution Method in Saccharomyces cerevisiae: Mutant Library Creation and Screening

Directed evolution in Saccharomyces cerevisiae offers many attractive advantages when designing enzymes for biotechnological applications, a process that involves the construction, cloning and expression of mutant libraries, coupled to high frequency homologous DNA recombination in vivo. Here, we present a protocol to create and screen mutant libraries in yeast based on the example of a fungal aryl-alcohol oxidase (AAO) to enhance its total activity. Two protein segments were subjected to focused-directed evolution by random mutagenesis and in vivo DNA recombination. Overhangs of ~50 bp flanking each segment allowed the correct reassembly of the AAO-fusion gene in a linearized vector giving rise to a full autonomously replicating plasmid. Mutant libraries enriched with functional AAO variants were screened in S. cerevisiae supernatants with a sensitive high-throughput assay based on the Fenton reaction. The general process of library construction in S. cerevisiae described here can be readily applied to evolve many other eukaryotic genes, avoiding extra PCR reactions, in vitro DNA recombination and ligation steps.

Directed Evolution Method in Saccharomyces cerevisiae: Mutant Library Creation and Screening

We present a detailed protocol to construct and screen mutant libraries for directed evolution campaigns in Saccharomyces cerevisiae.

Directed evolution in Saccharomyces cerevisiae offers many attractive advantages when designing enzymes for biotechnological applications, a process that ...

Biology

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Structural variants (SVs) (i.e., deletions, insertions, duplications, and inversions) are now known to play an important role in phenotypic variation, and consequently in processes such as disease determination or adaptation to a new environment. However, single-nucleotide variants receive much more attention than SVs, probably because they are easier to detect, and their phenotypic effects are easier to predict. The development of short- and long-read deep sequencing technologies have strongly improved the detection of SVs, but the quantification of their frequency from pooled sequencing (poolseq) data is still technically complex and expensive.
Here, we present a rather simple and inexpensive method, which allows researchers to follow the dynamics of SV allele frequency. As an example of application, we follow the frequency of an insertion sequence (IS) insertion in experimental evolution populations of bacteria. This method is based on the design of triplets of primers around the structural variant borders, such that the amplicons produced by amplification of the wild-type (WT) and derived alleles differ in size by at least 5%, and that their amplification efficiency is similar. The quantity of each amplicon is then determined by parallel capillary electrophoresis and normalized to a calibration curve. This method can be easily extended to the quantification of the frequency of other structural variants (deletions, duplications, and inversions) and to pool-seq approaches of natural populations, including within-patient pathogen populations.

We developed a cost-effective method to follow non-single nucleotide polymorphism allele dynamics that can easily be adapted to experimental evolution frozen archives. A triplet PCR technique was coupled with automated parallel capillary electrophoresis to quantify the relative frequency of an insertion allele over the course of experimental evolution.

Structural variants (SVs) (i.e., deletions, insertions, duplications, and inversions) are now known to play an important role in phenotypic variation, and ...

A Practical Guide to Phage- and Robotics-Assisted Near-Continuous Evolution

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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

Following Cell-fate in E. coli After Infection by Phage Lambda

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

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

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins

Using Phage Display to Develop Ubiquitin Variant Modulators for E3 Ligases

Directed Evolution Method in Saccharomyces cerevisiae: Mutant Library Creation and Screening

Following the Dynamics of Structural Variants in Experimentally Evolved Populations