Name: identification of host pathways targeted by bacterial effector proteins using yeast toxicity and suppressor screens
Uploaded: 2019-10-25T15:00:00
Description: Watch this Scientific Journal Video about Identification of Host Pathways Targeted by Bacterial Effector Proteins using Yeast Toxicity and Suppressor Screens at JoVE.com

We thank Shelby Andersen, Abby McCullough, and Laurel Woods for their assistance with these techniques. This study was funded by startup funds from the University of Iowa Department of Microbiology and Immunology to Mary M. Weber.

1. Preparation of media and reagents
NOTE: Plates should be prepared before the day of the assay and are good for 1 month. Media and reagents can be made at any point and are good for 1 month.
<ol>
	<li>Prepare 1 L of the glucose solution (10% w/v) by dissolving 100 g of D-(+)-glucose in 800 mL of distilled water in a 1, 000 mL beaker. Adjust the volume to 1 L with distilled water. Filter through a 0.2 &#181;m sterile filter into a sterile 1 L media storage bottle.</li>
	<li>Prepare 1 L of t...

<ol>
	<li>Tan, Y., Luo, Z. Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Legionella+pneumophila+SidD+is+a+deAMPylase+that+modifies+Rab1.">Legionella pneumophila SidD is a deAMPylase that modifies Rab1.</a> Nature. 475 (7357), 506-509 (2011).</li><li>Guo, Z., Stephenson, R., Qiu, J., Zheng, S., Luo, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Legionella+effector+modulates+host+cytoskeletal+structure+by+inhibiting+actin+polymerization.">A Legionella effector modulates host cytoskeletal structure by inhibiting actin polymerization.</a> Microbes and Infection. 16 (3), 225-236 (2014).</li><li>Tan, Y., Arnold, R. J., Luo, Z. -. Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Legionella+pneumophila+regulates+the+small+GTPase+Rab1+activity+by+reversible+phosphorylcholination.">Legionella pneumophila regulates the small GTPase Rab1 activity by reversible phosphorylcholination.</a> Proceedings of the National Academy of Sciences of the United States of America. 108 (52), 21212-21217 (2011).</li><li>Weber, M. M., 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+type+IV+secreted+effector+protein+CirA+stimulates+the+GTPase+activity+of+RhoA+and+is+required+for+virulence+in+a+mouse+model+of+Coxiella+burnetii+infection.">The type IV secreted effector protein CirA stimulates the GTPase activity of RhoA and is required for virulence in a mouse model of Coxiella burnetii infection.</a> Infection and Immunity. 84, (2016).</li><li>Faris, R., 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=Chlamydia+trachomatis+CT229+subverts+Rab+GTPase-dependent+CCV+trafficking+pathways+to+promote+chlamydial+infection.">Chlamydia trachomatis CT229 subverts Rab GTPase-dependent CCV trafficking pathways to promote chlamydial infection.</a> Cell Reports. 26, 3380-3390 (2019).</li><li>Mumberg, D., M&#252;ller, R., Funk, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Yeast+vectors+for+the+controlled+expression+of+heterologous+proteins+in+different+genetic+backgrounds.">Yeast vectors for the controlled expression of heterologous proteins in different genetic backgrounds.</a> Gene. 156, 119 (1995).</li><li>Hill, J., Donald, K. A. G., Griffiths, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DMSO-enhanced+whole+cell+yeast+transformation.">DMSO-enhanced whole cell yeast transformation.</a> Nucleic Acids Research. 19 (20), 41070 (1991).</li><li>Kramer, R. W., 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=Yeast+Functional+Genomic+Screens+Lead+to+Identification+of+a+Role+for+a+Bacterial+Effector+in+Innate+Immunity+Regulation.">Yeast Functional Genomic Screens Lead to Identification of a Role for a Bacterial Effector in Innate Immunity Regulation.</a> PLoS Pathogens. 3 (2), 21 (2007).</li><li>H&#228;user, R. T. S., Rajagopala, S. V., Uetz, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Array-Based+Yeast+Two-Hybrid+Screens:+A+Practical+Guide.">Array-Based Yeast Two-Hybrid Screens: A Practical Guide.</a> Two Hybrid Technologies: Methods and Protocols, Methods in Molecular Biology. , 21-38 (2012).</li><li>Mirrashidi, K. M., 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=Global+mapping+of+the+inc-human+interactome+reveals+that+retromer+restricts+chlamydia+infection.">Global mapping of the inc-human interactome reveals that retromer restricts chlamydia infection.</a> Cell Host and Microbe. 18 (1), 109-121 (2015).</li><li>Wang, 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=Development+of+a+transformation+system+for+chlamydia+trachomatis:+Restoration+of+glycogen+biosynthesis+by+acquisition+of+a+plasmid+shuttle+vector.">Development of a transformation system for chlamydia trachomatis: Restoration of glycogen biosynthesis by acquisition of a plasmid shuttle vector.</a> PLoS Pathogens. 7 (9), 1002258 (2011).</li><li>Mueller, K. E., Wolf, K., Fields, K. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+deletion+by+fluorescence-reported+allelic+exchange+mutagenesis+in+Chlamydia+trachomatis.">Gene deletion by fluorescence-reported allelic exchange mutagenesis in Chlamydia trachomatis.</a> mBio. 7 (1), 1-9 (2016).</li><li>Johnson, C. M., Specific Fisher, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Site-Specific,+Insertional+Inactivation+of+incA+in+Chlamydia+trachomatis+Using+a+Group+II+Intron.">Site-Specific, Insertional Inactivation of incA in Chlamydia trachomatis Using a Group II Intron.</a> PLoS ONE. 8 (12), 83989 (2013).</li><li>Weber, M. M., 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=Absence+of+specific+Chlamydia+trachomatis+inclusion+membrane+proteins+triggers+premature+inclusion+membrane+lysis+and+host+cell+death.">Absence of specific Chlamydia trachomatis inclusion membrane proteins triggers premature inclusion membrane lysis and host cell death.</a> Cell Reports. 19 (7), 1406-1417 (2017).</li><li>Weber, M. M., 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=A+functional+core+of+IncA+is+required+for+Chlamydia+trachomatis+inclusion+fusion.">A functional core of IncA is required for Chlamydia trachomatis inclusion fusion.</a> Journal of Bacteriology. 198 (8), 1347-1355 (2016).</li></ol>

This protocol outlines step-by-step procedures for identifying host biological pathways targeted by bacterial effector proteins using a modified yeast toxicity and suppressor screen. The yeast strain used, S. cerevisiae W303, is auxotrophic for both uracil and leucine. Uracil auxotrophy of the strain is used to select yeast carrying the protein of interest on the pYesNTA-Kan vector while leucine auxotrophy is used to select for the yeast genomic library vector pYep13. The yeast genomic library plasmids carry 3&#...

The first report of procedures similar to those presented here characterized the Legionella pneumophila type IV effector SidD, a deAMPylase that modifies Rab11. Comparable techniques were used for the characterization of several L. pneumophila effectors1,2,3. The assay was adapted to characterize a Coxiella burnetii type IV effector protein4, and recently the utility of this technique was expanded for the characterization of Chlamydia trachomatis inclusion membrane proteins5.
This protocol can be broken into two major parts: 1) the yeast toxicity screen, in which the bacterial effector protein of interest is expressed in yeast and clones are screened for a toxic phenotype as evidenced by a growth defect, and 2) the yeast suppressor screen, in which the toxic phenotype is suppressed by expression of a yeast genomic library in the toxic strain. Thus, the toxicity screen is a screen for toxic phenotypes that manifest as growth defects when the bacterial effector of interest is overexpressed. Toxic clones, successfully transformed with and expressing the bacterial effector, are selected and saved for the next step. The second major step involves overexpressing a partially digested yeast genomic library in the toxic yeast clone. Plasmids making up the yeast genomic library suggested for the use in this protocol carry 5&#8722;20 kb inserts, usually corresponding to 3&#8722;13 yeast open reading frames (ORF) of an average gene size of ~1.5 kb across all plasmids, representing the whole yeast genome covered approximately 10x. This part of the assay is called the suppressor screen, as the goal is to suppress the toxicity of the bacterial effector protein. Potential suppressor plasmids are isolated from yeast, sequenced, and the suppressing ORFs identified. The rationale underlying the suppressor screen is that the effector protein binds, interacts with, and/or overwhelms components of the host pathway it targets, and that providing those host proteins back in excess can rescue the toxic effect on the pathway and thus, the growth defect. Thus, identified ORFs that suppress toxicity often represent multiple participants of a host pathway. Orthogonal experiments are then performed to verify that the bacterial effector indeed interacts with the implicated pathway. This is especially necessary if a binding partner such as clathrin or actin has been identified, because these proteins are involved in a multitude of host processes. Further experiments can then elucidate the physiological function of the effector protein during infection. The toxicity and suppressor screens are also powerful tools for deciphering the physiological function of bacterial effector proteins that do not physically bind host proteins with affinities sufficient to detect by immunoprecipitation or that interact with the host in enzymatic hit-and-run interactions that may not be detected by a yeast-two hybrid screen.
Although the suppressor screen can be a powerful method to reveal potential physiological interactions between bacterial effector proteins and host pathways, the bacterial effector protein must induce a growth defect in yeast, otherwise using it in the suppressor screen will be of little use. Furthermore, the toxic phenotype must result in at least a 2&#8722;3 log10 deficit in growth or it will be difficult to identify suppressors. If a laboratory is set up for cell culture, screening effector proteins for toxicity in common cell lines such as HeLa can often give insight as to whether it is worth the effort to proceed with the yeast toxicity screen. Ectopic expression of the effector protein in HeLa cells sometimes results in toxicity that correlates very strongly with toxicity in the yeast strain used for these screens4. Observable hallmarks of stress in HeLa cells include loss of stress fibers, cell detachment from the plate, and nuclear condensation indicating apoptosis. Any visual indication of stress in HeLa cells make the protein of interest a good candidate for inducing a growth defect in yeast, which replicate much more rapidly and are thus more responsive to perturbation of essential pathways.
It should be noted that the suppressor screen does not always identify host binding partners as suppressors, but it can still implicate critical components of the host pathway(s) targeted, yielding a holistic view of the biological processes being hijacked by the bacterial effector protein. On the surface, this seems counterintuitive, because providing the binding partner of the effector protein in excess would be expected to rescue the growth defect. In efforts to identify pathways targeted by the C. trachomatis effector protein CT229 (CpoS), which binds to at least 10 different Rab GTPases during infection5, none of the Rab binding partners suppressed the toxicity of CT229. However, numerous suppressors involved in clathrin-coated vesicle (CCV) trafficking were identified, which led to further work demonstrating that CT229 specifically subverts Rab-dependent CCV trafficking. Similarly, when investigating the C. burnetii effector protein Cbu0041 (CirA) several Rho GTPases that rescued the yeast growth defect were identified, and it was later found that CirA functions as a GTPase activating protein (GAP) for RhoA4.
The usefulness of the yeast suppressor screen for elucidating host pathways targeted by bacterial effector proteins cannot be overstated, and other researchers attempting to characterize intracellular bacterial effector proteins can greatly benefit from these techniques. These assays are of value if immunoprecipitations and/or yeast-two hybrid screens have failed to find a binding partner and can elucidate which pathways are targeted by the bacterial effector protein. Here, detailed protocols for the toxicity and suppressor screens to identify host biological pathways targeted by intracellular bacterial effector proteins are provided, as well as some of the common obstacles experienced when using these assays and their corresponding solutions.

<table border="0" cellpadding="0" cellspacing="0" style="width:871px;" width="870">
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	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Agar</td>
			<td style="width:199px;">Fisher Scientific</td>
			<td style="width:119px;">BP2641500</td>
			<td style="width:235px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Galactose</td>
			<td style="width:199px;">MilliporeSigma</td>
			<td>G0750-1KG</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">GeneJet Gel extraction kit</td>
			<td style="width:199px;">ThermoFisher Scientific</td>
			<td style="width:119px;">K0691</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">GeneJet PCR purification kit</td>
			<td style="width:199px;">ThermoFisher Scientific</td>
			<td style="width:119px;">K0701</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">GeneJet plasmid miniprep kit</td>
			<td style="width:199px;">Thermo</td>
			<td style="width:119px;">K0503</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Glucose</td>
			<td style="width:199px;">MilliporeSigma</td>
			<td>G8270-1KG</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Herring Sperm DNA</td>
			<td style="width:199px;">Promega</td>
			<td>D1811</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">KpnI-HF</td>
			<td style="width:199px;">New England Biolabs</td>
			<td style="width:119px;">R3142S</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Lithium acetate dihydrate</td>
			<td style="width:199px;">MilliporeSigma</td>
			<td>L6883-250G</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Peptone</td>
			<td style="width:199px;">Fisher Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Phusion High-Fidelity DNA Polymerase</td>
			<td style="width:199px;">New England Biolabs</td>
			<td style="width:119px;">M0530</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Poly(ethylene glycol) 3350</td>
			<td style="width:199px;">MilliporeSigma</td>
			<td>1546547-1G</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">pYep13</td>
			<td style="width:199px;">ATCC</td>
			<td style="width:119px;">37323</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">T4 DNA ligase</td>
			<td style="width:199px;">New England Biolabs</td>
			<td style="width:119px;">M0202S</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Tryptophan</td>
			<td style="width:199px;">MilliporeSigma</td>
			<td>470031-1G</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">XhoI-HF</td>
			<td style="width:199px;">New England Biolabs</td>
			<td style="width:119px;">R0146S</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Yeast extract</td>
			<td style="width:199px;">Fisher Scientific</td>
			<td>BP1422-500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Yeast miniprep kit</td>
			<td style="width:199px;">Zymo</td>
			<td style="width:119px;">D2001</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:319px;">Yeast nitrogen base without amino acids</td>
			<td style="width:199px;">MilliporeSigma</td>
			<td>Y0626-250G</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Yeast Synthetic Drop-out Medium Supplements</td>
			<td style="width:199px;">MilliporeSigma</td>
			<td>Y1501-20G</td>
			<td>without uracil</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Yeast Synthetic Drop-out Medium Supplements</td>
			<td style="width:199px;">MilliporeSigma</td>
			<td>Y1771-20G</td>
			<td>without uracil, leucine, tryptophan</td>
		</tr>
	</tbody>
</table>

identification of host pathways targeted by bacterial effector proteins using yeast toxicity and suppressor screens

Intracellular bacteria secrete virulence factors called effector proteins into the host cytosol that act to subvert host proteins and/or their associated biological pathways to the benefit of the bacterium. Identification of putative bacterial effector proteins has become more manageable due to advances in bacterial genome sequencing and the advent of algorithms that allow in silico identification of genes encoding secretion candidates and/or eukaryotic-like domains. However, identification of these important virulence factors is only an initial step. Naturally, the goal is to determine the molecular function of effector proteins and elucidate how they interact with the host. In recent years, techniques like the yeast two-hybrid screen and large-scale immunoprecipitations coupled with mass spectrometry have aided in the identification of protein-protein interactions. Although identification of a host binding partner is the crucial first step toward elucidating the molecular function of a bacterial effector protein, sometimes the host protein is found to have multiple biological functions (e.g., actin, clathrin, tubulin), or the bacterial protein may not physically bind host proteins, depriving the researcher of crucial information about the precise host pathway being manipulated. A modified yeast toxicity screen coupled with a suppressor screen has been adapted to identify host pathways impacted by bacterial effector proteins. The toxicity screen relies on a toxic effect in yeast caused by the effector protein interfering with the host biological pathways, which often manifests as a growth defect. Expression of a yeast genomic library is used to identify host factors that suppress the toxicity of the bacterial effector protein and thus identify proteins in the pathway that the effector protein targets. This protocol contains detailed instructions for both the toxicity and suppressor screens. These techniques can be performed in any lab capable of molecular cloning and cultivation of yeast and Escherichia coli.

Before the actual yeast suppressor screen can be performed, the effector protein of interest must be tested for toxicity in yeast. This is accomplished by expressing the protein of interest in yeast under the control of a galactose-inducible promoter. Growth on glucose (noninducing conditions) should first be compared to ensure toxicity is specifically due to the expression of the protein of interest and is not a general defect. As shown in Figure 3, toxicity manifests as smaller colonies an...

Watch this Scientific Journal Video about Identification of Host Pathways Targeted by Bacterial Effector Proteins using Yeast Toxicity and Suppressor Screens at JoVE.com

Identification of Host Pathways Targeted by Bacterial Effector Proteins using Yeast Toxicity and Suppressor Screens

Bacterial pathogens secrete proteins into the host that target crucial biological processes. Identifying the host pathways targeted by bacterial effector proteins is key to addressing molecular pathogenesis. Here, a method using a modified yeast suppressor and toxicity screen to elucidate host pathways targeted by toxic bacterial effector proteins is described.

Intracellular bacteria secrete virulence factors called effector proteins into the host cytosol that act to subvert host proteins and/or their associated ...

Intracellular bacteria secrete effector proteins into the host that can manipulate biological pathways to promote pathogen survival. Revealing host targets of effectors is essential for understanding intracellular pathogens like Chlamydia trachomatis. Yeast toxicity and suppressor screens can provide key insight regarding the natural biological target of bacterial effector proteins and can be particularly useful when a binding partner is unknown.We demonstrate the yeast toxicity and suppressor assays here for screening for Chlamydia trachomatis effector proteins, but this technique has also been used for characterizing Legionella pneumophila and Coxiella burnetii effectors. Begin by inoculating five milliliters of single drop-out broth with the single colony of yeast transformed with the effector protein containing plasmid. Use yeast transformed with the vector alone as a negative control and incubate the inoculum overnight at 30 degrees Celsius while shaking.On the next day, add 180 microliters of sterile water to the A2 through A6 wells of a 96-well plate. Vortex the overnight culture and add 180 microliters of yeast to well A1.Then serially dilute the yeast in the wells with water. Use a multi-channel pipette to spot five microliters of each dilution onto single drop-out glucose and single drop-out galactose agar plates and incubate the plates at 30 degrees Celsius for 48 hours.After the incubation, visually assess toxicity by comparing the growth of yeast expressing the effector protein grown on the galactose-containing media to the growth of yeast expressing the vector alone. Inoculate 100 milliliters of the single drop-out broth with one milliliter of the previously prepared yeast stock and incubate it for 16 to 24 hours at 30 degrees Celsius with shaking at 150 RPM. On the next day, add the entire 100 milliliters of the overnight culture to 900 milliliters of pre-warmed single drop-out broth and incubate the flask for four to five hours at 30 degrees Celsius while shaking.After the incubation, pellet the culture at 6, 000 times g for 10 minutes at four degrees Celsius. Discard the supernatant and resuspend the pellet in 250 milliliters of sterile water. Repeat the centrifugation and discard the supernatant.Then resuspend the pellet in 250 milliliters of one millimolar lithium acetate. Pellet the culture by centrifugation, remove the lithium acetate, and resuspend the pellet in 9.6 milliliters of 50%PEG 3350. Then add transformation reagents as described in the manuscript and adjust the volume to 15 milliliters with sterile water inverting gently to mix.Incubate the mixture at 30 degrees Celsius for 30 minutes. Then add 750 microliters of DMSO and incubate in a water bath at 42 degrees Celsius for another 30 minutes. Adding the DMSO before heat shock is crucial to achieve a high transformation efficiency.After the incubation, pellet the yeast by centrifuging at 3, 000 times g for five minutes. Discard the supernatant and wash the pellet with 10 milliliters of sterile water then repeat the centrifugation to pellet the yeast. Resuspend the pellet in eight milliliters of water.Determine the transformation efficiency by diluting the sample one to 10 and plating 100 microliters of each dilution onto double drop-out agar. Then plate 200 microliters of the sample on double drop-out galactose agar plates and incubate the plates at 30 degrees Celsius for 48 to 96 hours or until colonies appear. Once colonies have appeared, patch them on double drop-out galactose agar and incubate them for another 24 to 48 hours.Use part of the patch to inoculate five milliliters of double drop-out broth and incubate the inoculum overnight at 26 degrees Celsius with shaking at 150 RPM. On the next day, add 180 microliters of sterile water to five wells of a 96-well plate starting with well A2.Vortex the overnight culture mix. Add 180 microliters of yeast to well A1 and serially dilute it using the water in wells A2 through A6.Spot five microliters of each dilution on single drop-out glucose and single drop-out galactose agar plates making sure to include the toxic effector alone as a control.Incubate the plates at 30 degrees Celsius for 48 hours then compare the growth of the yeast with toxic effector alone to the growth of yeast with the potential suppressor. To confirm suppressors that have demonstrated diminished toxicity compared to the toxic effector alone, isolate the plasmid according to manuscript directions and re-transform it into the toxic yeast. Inoculate double drop-out glucose broth with a colony from the transformation plate.Incubate it overnight and spot on double drop-out glucose and galactose agar to confirm suppression of toxicity. Prior to performing the yeast suppressor screen, the effector proteins of interest were tested for toxicity in yeast. The protein of interest was expressed in yeast under the control of a galactose inducible promoter and growth on galactose was compared to growth on glucose.When CT229 was tested for toxicity, smaller colonies and growth suppression were observed. Ideally, a two to three log decrease should be observed to proceed with yeast suppressor screens. The suppressor screen was conducted by transforming the toxic strain with the yeast genomic library pYAP 13 and plating the transformants on galactose agar.The obtained suppressor clones were spotted on double drop-out galactose agar to confirm suppression of toxicity. Suppressors pSup1 and pSup2 suppressed the toxicity of the effector protein whereas pSup3 did not. These procedures require careful attention to detail in addition to critical preparatory work including having large amounts of media and plates ready prior to performing the experiment.Once suppressors are identified, experiments can be performed to verify interactions with the effector of interest including pull downs, immunofluorescence colocalization, effector knockout or knockdown of host factors identified in the screens. Development of this technique for Chlamydia effectors has allowed for expedited preliminary characterization of effector proteins and helped to focus our efforts on elucidating the underlying molecular mechanisms that mediate host pathogen interactions.

identification-host-pathways-targeted-bacterial-effector-proteins

Research

JoVE Journal

Genetics

Conjugative Mating Assays for Sequence-specific Analysis of Transfer Proteins Involved in Bacterial Conjugation

The transfer of genetic material by bacterial conjugation is a process that takes place via complexes formed by specific transfer proteins. In Escherichia coli, these transfer proteins make up a DNA transfer machinery known as the mating pair formation, or DNA transfer complex, which facilitates conjugative plasmid transfer. The objective of this paper is to provide a method that can be used to determine the role of a specific transfer protein that is involved in conjugation using a series of deletions and/or point mutations in combination with mating assays. The target gene is knocked out on the conjugative plasmid and is then provided in trans through the use of a small recovery plasmid harboring the target gene. Mutations affecting the target gene on the recovery plasmid can reveal information about functional aspects of the target protein that result in the alteration of mating efficiency of donor cells harboring the mutated gene. Alterations in mating efficiency provide insight into the role and importance of the particular transfer protein, or a region therein, in facilitating conjugative DNA transfer. Coupling this mating assay with detailed three-dimensional structural studies will provide a comprehensive understanding of the function of the conjugative transfer protein as well as provide a means for identifying and characterizing regions of protein-protein interaction.

Here, we present a protocol to knockout a gene of interest involved in plasmid conjugation and subsequently analyze the impact of its absence using mating assays. The function of the gene is further explored to a specific region of its sequence using deletion or point mutations.

The transfer of genetic material by bacterial conjugation is a process that takes place via complexes formed by specific transfer proteins. In Escherichia ...

Targeted in Situ Mutagenesis of Histone Genes in Budding Yeast

We describe a PCR- and homologous recombination-based system for generating targeted mutations in histone genes in budding yeast cells. The resulting mutant alleles reside at their endogenous genomic sites and no exogenous DNA sequences are left in the genome following the procedure. Since in haploid yeast cells each of the four core histone proteins is encoded by two non-allelic genes with highly homologous open reading frames (ORFs), targeting mutagenesis specifically to one of two genes encoding a particular histone protein can be problematic. The strategy we describe here bypasses this problem by utilizing sequences outside, rather than within, the ORF of the target genes for the homologous recombination step. Another feature of this system is that the regions of DNA driving the homologous recombination steps can be made to be very extensive, thus increasing the likelihood of successful integration events. These features make this strategy particularly well-suited for histone gene mutagenesis, but can also be adapted for mutagenesis of other genes in the yeast genome.

Targeted in Situ Mutagenesis of Histone Genes in Budding Yeast

A strategy for generating mutations in histone genes at their endogenous location in Saccharomyces cerevisiae is presented.

We describe a PCR- and homologous recombination-based system for generating targeted mutations in histone genes in budding yeast cells. The resulting ...

Determination of the Optimal Chromosomal Location(s) for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach

The optimal chromosomal position(s) of a given DNA element was/were determined by transposon-mediated random insertion followed by fitness selection. In bacteria, the impact of the genetic context on the function of a genetic element can be difficult to assess. Several mechanisms, including topological effects, transcriptional interference from neighboring genes, and/or replication-associated gene dosage, may affect the function of a given genetic element. Here, we describe a method that permits the random integration of a DNA element into the chromosome of Escherichia coli and select the most favorable locations using a simple growth competition experiment. The method takes advantage of a well-described transposon-based system of random insertion, coupled with a selection of the fittest clone(s) by growth advantage, a procedure that is easily adjustable to experimental needs. The nature of the fittest clone(s) can be determined by whole-genome sequencing on a complex multi-clonal population or by easy gene walking for the rapid identification of selected clones. Here, the non-coding DNA region DARS2, which controls the initiation of chromosome replication in E. coli, was used as an example. The function of DARS2 is known to be affected by replication-associated gene dosage; the closer DARS2 gets to the origin of DNA replication, the more active it becomes. DARS2 was randomly inserted into the chromosome of a DARS2-deleted strain. The resultant clones containing individual insertions were pooled and competed against one another for hundreds of generations. Finally, the fittest clones were characterized and found to contain DARS2 inserted in close proximity to the original DARS2 location.

Determination of the Optimal Chromosomal Locations for a DNA Element in Escherichia coli Using a Novel Transposon-mediated Approach

Here, the power of a transposon-mediated random insertion of a non-coding DNA element was used to resolve its optimal chromosomal position.

The optimal chromosomal position(s) of a given DNA element was/were determined by transposon-mediated random insertion followed by fitness selection. In ...

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation

Biological radiation dose can be estimated from dicentric chromosome frequencies in metaphase cells. Performing these cytogenetic dicentric chromosome assays is traditionally a manual, labor-intensive process not well suited to handle the volume of samples which may require examination in the wake of a mass casualty event. Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software automates this process by examining sets of metaphase images using machine learning-based image processing techniques. The software selects appropriate images for analysis by removing unsuitable images, classifies each object as either a centromere-containing chromosome or non-chromosome, further distinguishes chromosomes as monocentric chromosomes (MCs) or dicentric chromosomes (DCs), determines DC frequency within a sample, and estimates biological radiation dose by comparing sample DC frequency with calibration curves computed using calibration samples. This protocol describes the usage of ADCI software. Typically, both calibration (known dose) and test (unknown dose) sets of metaphase images are imported to perform accurate dose estimation. Optimal images for analysis can be found automatically using preset image filters or can also be filtered through manual inspection. The software processes images within each sample and DC frequencies are computed at different levels of stringency for calling DCs, using a machine learning approach. Linear-quadratic calibration curves are generated based on DC frequencies in calibration samples exposed to known physical doses. Doses of test samples exposed to uncertain radiation levels are estimated from their DC frequencies using these calibration curves. Reports can be generated upon request and provide summary of results of one or more samples, of one or more calibration curves, or of dose estimation.

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification ADCI and Dose Estimation

The cytogenetic dicentric chromosome (DC) assay quantifies exposure to ionizing radiation. The Automated Dicentric Chromosome Identifier and Dose Estimator software accurately and rapidly estimates biological dose from DCs in metaphase cells. It distinguishes monocentric chromosomes and other objects from DCs, and estimates biological radiation dose from the frequency of DCs.

Biological radiation dose can be estimated from dicentric chromosome frequencies in metaphase cells. Performing these cytogenetic dicentric chromosome ...

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our entire society's ability to treat systemic infections. In the United States alone, antibiotic-resistant infections kill approximately 23,000 people a year and cost around 20 billion USD in additional healthcare. One approach to combat antimicrobial resistance is combination therapy, which is particularly useful in the critical early stage of infection, before the infecting organism and its drug resistance profile have been identified. Many antimicrobial treatments use combination therapies. However, most of these combinations are additive, meaning that the combined efficacy is the same as the sum of the individual antibiotic efficacy. Some combination therapies are synergistic: the combined efficacy is much greater than additive. Synergistic combinations are particularly useful because they can inhibit the growth of antimicrobial drug resistant strains. However, these combinations are rare and difficult to identify. This is due to the sheer number of molecules needed to be tested in a pairwise manner: a library of 1,000 molecules has 1 million potential combinations. Thus, efforts have been made to predict molecules for synergy. This article describes our high-throughput method for predicting synergistic small molecule pairs known as the Overlap2 Method (O2M). O2M uses patterns from chemical-genetic datasets to identify mutants that are hypersensitive to each molecule in a synergistic pair but not to other molecules. The Brown lab exploits this growth difference by performing a high-throughput screen for molecules that inhibit the growth of mutant but not wild-type cells. The lab's work previously identified molecules that synergize with the antibiotic trimethoprim and the antifungal drug fluconazole using this strategy. Here, the authors present a method to screen for novel synergistic combinations, which can be altered for multiple microorganisms.

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Synergistic drug combinations are difficult and time-consuming to identify empirically. Here, we describe a method for identifying and validating synergistic small molecules.

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our ...

Gene-targeted Random Mutagenesis to Select Heterochromatin-destabilizing Proteasome Mutants in Fission Yeast

Random mutagenesis of a target gene is commonly used to identify mutations that yield the desired phenotype. Of the methods that may be used to achieve random mutagenesis, error-prone PCR is a convenient and efficient strategy for generating a diverse pool of mutants (i.e., a mutant library). Error-prone PCR is the method of choice when a researcher seeks to mutate a pre-defined region, such as the coding region of a gene while leaving other genomic regions unaffected. After the mutant library is amplified by error-prone PCR, it must be cloned into a suitable plasmid. The size of the library generated by error-prone PCR is constrained by the efficiency of the cloning step. However, in the fission yeast, Schizosaccharomyces pombe, the cloning step can be replaced by the use of a highly efficient one-step fusion PCR to generate constructs for transformation. Mutants of desired phenotypes may then be selected using appropriate reporters. Here, we describe this strategy in detail, taking as an example, a reporter inserted at centromeric heterochromatin.

This article describes a detailed methodology for random mutagenesis of a target gene in fission yeast. As an example, we target rpt4+, which encodes a subunit of the 19S proteasome, and screen for mutations that destabilize heterochromatin.

Random mutagenesis of a target gene is commonly used to identify mutations that yield the desired phenotype. Of the methods that may be used to achieve ...

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

We have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing high-throughput short-read DNA sequencing. The resulting sequence datasets can not only track what genes in a population that are enriched during selection for positive yeast 2-hybrid interactions, but also give detailed information about the relevant subdomains of proteins sufficient for interaction. Here, we describe a full suite of stand-alone software programs that allow non-experts to perform all the bioinformatics and statistical steps to process and analyze DNA sequence fastq files from a batch yeast 2-hybrid assay. The processing steps covered by these software include: 1) mapping and counting sequence reads corresponding to each candidate protein encoded within a yeast 2-hybrid prey library; 2) a statistical analysis program that evaluates the enrichment profiles; and 3) tools to examine the translational frame and position within the coding region of each enriched plasmid that encodes the interacting proteins of interest.

Deep sequencing of yeast populations selected for positive yeast 2-hybrid interactions potentially yields a wealth of information about interacting partner proteins. Here, we describe the operation of specific bioinformatics tools and customized updated software to analyze sequence data from such screens.

We have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing ...

A Deep-sequencing-assisted, Spontaneous Suppressor Screen in the Fission Yeast Schizosaccharomyces pombe

A genetic screen for mutant alleles that suppress phenotypic defects caused by a mutation is a powerful approach to identify genes that belong to closely related biochemical pathways. Previous methods such as the Synthetic Genetic Array (SGA) analysis, and random mutagenesis techniques using ultraviolet (UV) or chemicals like ethyl methanesulfonate (EMS) or N-ethyl-N- nitrosourea (ENU), have been widely used but are often costly and laborious. Also, these mutagen-based screening methods are frequently associated with severe side effects on the organism, inducing multiple mutations that add to the complexity of isolating the suppressors. Here, we present a simple and effective protocol to identify suppressor mutations in mutants which confer a growth defect in Schizosaccharomyces pombe. The fitness of cells with a growth deficiency in standard rich liquid media or synthetic liquid media can be monitored for recovery using an automated 96-well plate reader over an extended period. Once a cell acquires a suppressor mutation in the culture, its descendants outcompete those of the parental cells. The recovered cells that have a competitive growth advantage over the parental cells can then be isolated and backcrossed with the parental cells. The suppressor mutations are then identified using whole-genome sequencing. Using this approach, we have successfully isolated multiple suppressors that alleviate the severe growth defects caused by loss of Elf1, an AAA+ family ATPase that is important in nuclear mRNA transport and maintenance of genomic stability. There are currently over 400 genes in S. pombe with mutants conferring a growth defect. As many of these genes are uncharacterized, we propose that our method will hasten the identification of novel functional interactions with this user-friendly, high-throughput approach.

A Deep-sequencing-assisted, Spontaneous Suppressor Screen in the Fission Yeast Schizosaccharomyces pombe

We present a simple suppressor screen protocol in fission yeast. This method is efficient, mutagen-free, and&#160; selective&#160; for&#160; mutations that&#160; often&#160; occur at&#160; &#160;a&#160; single&#160; genomic&#160; locus.&#160; The protocol is suitable for isolating suppressors that alleviate growth defects in liquid culture that are caused by a mutation or a drug.

A genetic screen for mutant alleles that suppress phenotypic defects caused by a mutation is a powerful approach to identify genes that belong to closely ...

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

Identifying the sets of transcription factors (TFs) that regulate each human gene is a daunting task that requires integrating numerous experimental and computational approaches. One such method is the yeast one-hybrid (Y1H) assay, in which interactions between TFs and DNA regions are tested in the milieu of the yeast nucleus using reporter genes. Y1H assays involve two components: a &#8216;DNA-bait&#8217; (e.g., promoters, enhancers, silencers, etc.) and a &#8216;TF-prey,&#8217; which can be screened for reporter gene activation. Most published protocols for performing Y1H screens are based on transforming TF-prey libraries or arrays into DNA-bait yeast strains. Here, we describe a pipeline, called enhanced Y1H (eY1H) assays, where TF-DNA interactions are interrogated by mating DNA-bait strains with an arrayed collection of TF-prey strains using a high density array (HDA) robotic platform that allows screening in a 1,536 colony format. This allows for a dramatic increase in throughput (60 DNA-bait sequences against &#62;1,000 TFs takes two weeks per researcher) and reproducibility. We illustrate the different types of expected results by testing human promoter sequences against an array of 1,086 human TFs, as well as examples of issues that can arise during screens and how to troubleshoot them.

Here, we present an enhanced yeast one-hybrid screening protocol to identify the transcription factors (TFs) that can bind to a human DNA region of interest. This method uses a high-throughput screening pipeline that can interrogate the binding of &#62;1,000 TFs in a single experiment.

Identifying the sets of transcription factors (TFs) that regulate each human gene is a daunting task that requires integrating numerous experimental and ...

Pooled CRISPR-Based Genetic Screens in Mammalian Cells

Genome editing using the CRISPR-Cas system has vastly advanced the ability to precisely edit the genomes of various organisms. In the context of mammalian cells, this technology represents a novel means to perform genome-wide genetic screens for functional genomics studies. Libraries of guide RNAs (sgRNA) targeting all open reading frames permit the facile generation of thousands of genetic perturbations in a single pool of cells that can be screened for specific phenotypes to implicate gene function and cellular processes in an unbiased and systematic way. CRISPR-Cas screens provide researchers with a simple, efficient, and inexpensive method to uncover the genetic blueprints for cellular phenotypes. Furthermore, differential analysis of screens performed in various cell lines and from different cancer types can identify genes that are contextually essential in tumor cells, revealing potential targets for specific anticancer therapies. Performing genome-wide screens in human cells can be daunting, as this involves the handling of tens of millions of cells and requires analysis of large sets of data. The details of these screens, such as cell line characterization, CRISPR library considerations, and understanding the limitations and capabilities of CRISPR technology during analysis, are often overlooked. Provided here is a detailed protocol for the successful performance of pooled genome-wide CRISPR-Cas9 based screens.

CRISPR-Cas9 technology provides an efficient method to precisely edit the mammalian genome in any cell type and represents a novel means to perform genome-wide genetic screens. A detailed protocol discussing the steps required for the successful performance of pooled genome-wide CRISPR-Cas9 screens is provided here.

Genome editing using the CRISPR-Cas system has vastly advanced the ability to precisely edit the genomes of various organisms. In the context of mammalian ...