We thank Dr. K. Kamachi of the National Institute of Infectious Diseases (Japan) for providing pBP136 and Prof. Dr. H. Nojiri of the University of Tokyo (Japan) for providing pCAR1. We are also grateful to Professor Dr. Molin S&#248;len of the Technical University of Denmark for providing pJBA28. This work was supported by JSPS KAKENHI (Grant Numbers 15H05618 and 15KK0278) to MS (https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15H05618/, https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15KK0278/).

1. Preparation of a Donor with Green Fluorescent Protein (GFP)- and Kanamycin Resistance Gene-Tagged Plasmids
<ol>
	<li>Introduction of marker genes into the target plasmid pBP136 
	Note: The goal of this protocol is to generate pBP136::gfp. The bacterial strains and plasmids used in this study are listed in Table 1.
	<ol>
		<li>Grow cultures of Escherichia coli DH10B harboring pBP13617 in 5 mL of sterile Luria broth (LB) and E. coli S17-1&#955;pir18 harboring pJBA2819 [containing a kanamycin (Km)-resistance gene and gfpmut3* gene with its promoter and terminator in a mini-Tn5] in 5 mL of sterile LB containing 50 &#956;g/mL Km at 37 &#176;C overnight (O/N, 16&#8211;24 h) with shaking at 200 revolutions per minute (rpm).</li>
		<li>Harvesting and washing
		<ol>
			<li>Harvest 1 mL of each culture, place it into a 2 mL microtube, and centrifuge (10,000 &#215; g, room temperature, 2 min). Then, discard the supernatant and resuspend the cell pellet in 2 mL of sterile phosphate buffered saline (PBS).</li>
			<li>Centrifuge again (10,000 &#215; g, room temperature, 2 min), and resuspend in 500 &#956;L of sterile PBS.</li>
		</ol>
		</li>
		<li>Filter mating
		<ol>
			<li>Prepare sterile LB plates (with 1.6% agar), and place a sterile 0.22 &#956;m pore size membrane filter on it. Mix 500 &#956;L of E. coli S17-1&#955;pir harboring pJBA28 with E. coli DH10B harboring pBP136 and spot the mixture on the filter on the LB plate. Incubate the plate O/N at 30 &#176;C. Remove the filter from the LB plate, place it into a sterile 50 mL plastic tube, and add 1 mL of sterile PBS. 
			Note: pJBA28 can replicate in the presence of &#928; protein, encoded by the pir gene18, and can be transferred from S17-1&#955;pir to DH10B. pBP136 carries no marker gene17 and can be transferred from DH10B to S17-1&#955;pir. Therefore, we could not distinguish S17-1&#955;pir harboring pBP136 and pJBA28 from DH10B harboring pBP136 and the mini-Tn5 (transposed into the chromosome or pBP136) at this stage. Then, we used mixtures of them as donors in subsequent steps (1.1.4.&#8211;1.1.5.).</li>
		</ol>
		</li>
		<li>Grow an O/N culture of the above mating mixture in sterile LB containing 50 &#956;g/mL Km at 37 &#176;C with shaking at 200 rpm and a culture of Pseudomonas putida KT2440 [Km-sensitive (Kms), rifampicin-sensitive (Rifs), gentamicin-sensitive (Gms), and tetracycline resistant (Tcr)] in medium containing 12.5 &#956;g/mL Tc at 30 &#176;C with shaking at 200 rpm.</li>
		<li>After harvesting and washing the cells as in step 1.1.2, use them (the mating mixture and KT2440) for filter mating (O/N, 30 &#176;C) as in step 1.1.3.</li>
		<li>Prepare sterile LB plates containing 50 &#956;g/mL Km and 12.5 &#956;g/mL Tc (LB + Km + Tc plates).</li>
		<li>Dilute the resuspended mixture on the membrane filter with sterile PBS (101&#8211;105-fold), and then spread each dilution onto LB + Km + Tc plates and incubate the plates at 30 &#176;C for 2&#8211;3 d.</li>
		<li>Pick colonies from the plates, grow an O/N culture in sterile LB containing Km and Tc as well as P. resinovorans CA10dm4RG (Rifr and Gmr)6 in sterile LB containing Rif (25 &#956;g/mL) and Gm (30 &#956;g/mL) at 30 &#176;C and 200 rpm. 
		Note: As described in the previous note, the colonies on the LB + Km + Tc plates (from 1.1.7.) may be KT2440 harboring pBP136 carrying a mini-Tn5 and KT2440 with a mini-Tn5, because pJBA28 could be directly transferred from S17-1&#955;pir harboring pBP136 and pJBA28 to KT2440. This is why another mating with P. resinovorans CA10RG is required to obtain the target pBP136 with a mini-Tn5 in the following steps.</li>
		<li>After harvesting and washing the cells as in step 1.1.2, use them for filter mating (O/N, 30 &#176;C) as in step 1.1.3.</li>
		<li>Prepare sterile LB plates containing Rif, Gm, and Km (LB + Rif + Km + Gm plates).</li>
		<li>Resuspend the mixture on the filter and then dilute it 101&#8211;105-fold, spread it onto LB + Rif + Km + Gm plates, and incubate the plates for 2&#8211;3 d at 30&#160;&#176;C.</li>
		<li>Pick the colonies and check if they harbor pBP136 by PCR using specific primers for the plasmid.</li>
	</ol>
	</li>
	<li>Introduction of a selective marker gene into the target plasmid pCAR1 
	Note: The goal of this protocol is to generate pCAR1::gfp
	<ol>
		<li>Grow an O/N culture of P. putida KT2440 harboring pCAR1 (Kms, Gms, Rifs, Tcr)20 at 200 rpm and 30 &#176;C and E. coli S17-1&#955;pir18 harboring pJBA28 in 5 mL of sterile LB containing 50 &#956;g/mL Km at 200 rpm and 37 &#176;C.</li>
		<li>After harvesting and washing the cells as in step 1.1.2, use them for filter mating (O/N, 30 &#176;C) as in step 1.1.3.</li>
		<li>Remove the filter from the LB plate, place it into a sterile 50 mL plastic tube, and add 1 mL of sterile PBS.</li>
		<li>Dilute the resuspended mixture with sterile PBS (101&#8211;105-fold), and spread the diluted mixture onto sterile selective LB + Tc + Km plates. 
		Note: pCAR1 does not replicate in E. coli; thus, P. putida KT2440 harboring pCAR1 with a mini-Tn5 can be selected on LB + Tc + Km plates.</li>
		<li>Pick a colony from the plate, and grow an O/N culture in sterile LB containing Km and Tc and a culture of P. resinovorans CA10dm4RG in sterile LB containing Rif and Gm (200 rpm, 30 &#176;C).</li>
		<li>After harvesting and washing as in step 1.1.2, use the cells for filter mating (O/N, 30 &#176;C) as in step 1.1.3.</li>
		<li>Resuspend the mixture on the filter and then dilute it, spread onto LB + Rif + Km + Gm plates, and incubate the plates for 2&#8211;3 d at 30&#160;&#176;C.</li>
		<li>Pick the colonies and check if they harbor pCAR1 by PCR with specific primers for the plasmid.</li>
	</ol>
	</li>
	<li>Confirm the transferability of the tagged-plasmids and prepare the donors for the next steps 
	Note: The goal of this protocol is to confirm the transferability of the above constructed plasmids and prepare the donors for the next steps.
	<ol>
		<li>Grow an O/N culture of P. resinovorans CA10dm4RG harboring pBP136::gfp or pCAR1::gfp in sterile LB containing Km and a culture of P. putida SMDBS [Kms, Gms, Rifr, Tcr, lacIq, in which PA1/O4/O3-gfpmut3* is not expressed because of its chromosomal lacIq gene]21 in 3 mL of LB containing Tc (200 rpm, 30 &#176;C).</li>
		<li>After harvesting and washing the cells as in step 1.1.2, use them for filter mating (O/N, 30 &#176;C) as in step 1.1.3.</li>
		<li>Place the filter into a sterile 50 mL plastic tube, and resuspend with 1 mL of sterile PBS. Dilute the resuspended mixture with sterile PBS (101&#8211;105-fold), spread the diluted mixture onto sterile selective LB + Tc + Km plates.</li>
		<li>Pick the colonies and check if they harbor each of the plasmids by PCR with specific primers. 
		Note: Confirmation of the insertion position of the mini-Tn5 by direct sequencing after plasmid extraction is optional, to confirm that the insertion does not affect the transfer function of the plasmids.</li>
	</ol>
	</li>
</ol>
2. Calculation of Conjugation Frequency by the MPN Method
<ol>
	<li>Prepare sterile LB + Km and LB + Gm plates.</li>
	<li>Grow an O/N culture of P. putida SMDBS harboring pBP136::gfp or pCAR1::gfp in 3 mL of sterile LB containing Km and a culture of P. putida KT2440RGD (Gmr, Rifr) in 3 mL of LB containing Gm (140 rpm, 30 &#176;C).</li>
	<li>After harvesting and washing the cells as in step 1.1.2, use them for filter mating at 30 &#176;C for 45 min as in step 1.1.3.</li>
	<li>Serially dilute the above donor and recipient culture (101 &#8211;107) and spread it onto LB + Km (donor) or LB + Gm (recipient) plates (each in triplicate) to count the colony forming units (CFU). Incubate the plates at 30 &#176;C for 2 d.</li>
	<li>Resuspend the mixture on the filter in sterile LB containing Km and Gm, and serially dilute (from 21 to 224&#8211;107.2) using a 96-well cell culture plate (in quadruplicate).</li>
	<li>Incubate the 96-well plate for the appropriate time (2 d at 30 &#176;C).</li>
	<li>Count the CFU of the donor and recipient on the plates (step 2.4.) and count the number of wells in which the transconjugants grow.</li>
	<li>Calculate the MPN and its deviation by using the MPN calculation program developed by Jarvis et al.22, which is available at http://www.wiwiss.fu-berlin.de/fachbereich/vwl/iso/ehemalige/professoren/wilrich/MPN_ver5.xls.
	<ol>
		<li>Enter the name of the experiment (ex., &#8216;test&#8217;), the date of the experiment (ex., 2018/4/9), the number of test series, and the max. no. of dilutions (enter &#8216;24&#8217;) in row #7 of the &#8216;Program&#8217; sheet of the Excel file (&#8216;MPN_ver5.xls&#8217;).</li>
		<li>Enter &#8216;2-1 (= 0.5) to 2-24 (= 5.96 &#215; 10-8)&#8217; in the &#8216;dilution factor d&#8217; column, &#8216;0.01&#8217; in &#8216;volume in ml or g w&#8217; column, and &#8216;4&#8217; in &#8216;No. of tubes n&#8217; in the automatically produced tables of &#8216;input data&#8217;.</li>
		<li>Enter the number of wells in which the transconjugants grow at each sample dilution (0&#8211;4).</li>
		<li>Push the upper right &#8216;Calculate Results&#8217; button, and then obtain the results (in MPN/&#956;L) and their 95% confidence limits (lower and upper).</li>
	</ol>
	</li>
	<li>Calculate the conjugation frequency of the plasmids by dividing the number of transconjugants (MPN/mL) by the numbers of donor and recipient cells (CFU/mL).</li>
</ol>
3. Preparation for Estimation of the Probability of Donor-Initiated Conjugation
<ol>
	<li>Grow an O/N culture of P. putida SMDBS harboring pBP136::gfp or pCAR1::gfp in 3 mL of sterile LB containing Km and a culture of P. putida KT2440RGD (Gmr, Rifr) in 3 mL of sterile LB containing Gm using 300 mL flasks (140 rpm, 30 &#176;C) as precultures.</li>
	<li>Transfer 200 &#956;L of the preculture into 200 mL of fresh sterile LB containing Km or Gm in 500 mL flasks and incubate at 30 &#176;C with shaking at 140 rpm.</li>
	<li>Measure the turbidity at 600 nm (OD600) of the culture using a UV-VIS spectrophotometer and spot the culture, diluted in LB (101&#8211;108-fold dilutions), onto an LB plate containing Km or Gm. Incubate these LB plates at 30 &#176;C for 1&#8211;2 d, and determine the CFU.</li>
	<li>Plot the OD600 values and the CFU with growth time to generate growth curves of the donor and recipient.</li>
	<li>Grow cultures of the donor and recipient strain to mid-log phase, based on the growth curve.</li>
	<li>After harvesting and washing the cells, prepare 101&#8211;103 CFU of the donor in 10 &#956;L of LB and 105&#8211;107 CFU of the recipient in 100 &#956;L of LB.</li>
	<li>Mix 10 &#956;L of the donor and 100 &#956;L of the recipient cultures at different densities in 96-well plates (in triplicate). For example, mix 101 CFU of the donor and 105 CFU of the recipient and add it to each of the 96 wells, and mix 101 CFU of the donor and 106 CFU of the recipient in another 96-well plate, and so on.</li>
	<li>Incubate the mixture at 30 &#176;C for 45 min, and then add high concentrations of antibiotics (100 &#956;g/mL Km and 60 &#956;g/mL Gm) to each well to inhibit further conjugation.</li>
	<li>Incubate the plate at 30 &#176;C for 2 d.</li>
	<li>Count the number of wells in which transconjugants grow.</li>
	<li>Choose the recipient density that is appropriate for estimation of the probability of donor-initiated conjugation based on the above data (transconjugants should be found in at least 1 well of a 96-well plate). 
	Note: Transconjugants will grow in all wells when the densities of the donor and recipient cells are high and more than one conjugation occurs in a well. In contrast, no transconjugants will be found in any wells when the cell density is too low. In the following section, a single donor cell is sorted into a well. Therefore, the recipient density should be at maximum.</li>
</ol>
4. Estimation of the Probability of Donor-Initiated Conjugation
<ol>
	<li>Prepare 200 mL of a mid-log phase culture of donor P. putida SMDBS harboring pBP136::gfp or pCAR1::gfp and that of recipient P. putida KT2440RGD, as described in 3.6&#8211;3.7.</li>
	<li>Place 106 CFU of the recipient in 100 &#956;L of LB in each well of a 96-well plate.</li>
	<li>Set up the FACS system (flow cytometry and cell sorter with a robotic arm, a 488 nm argon laser, and a 70 &#956;m nozzle orifice). Set to forward scatter (FSC), with a 1% threshold as the acquisition trigger. Tune the H gain and A gain of the FSC and side scatter (SSC) at maximum sensitivity, which can exclude false positive signals, using PBS as a negative control. Set the sort gate based on FSC and SSC and 0.5 drop sort mode for maximal sort purity.</li>
	<li>Sort a single donor cell by FACS on an LB plate (384 different spots), incubate the plate at 30 &#176;C for 2 d, and then count how many colonies appear on the plate from the sorted cells. 
	Note: This procedure is for validation of the set gate. If there are 384 colonies on the plate, it means that 100% of the sorted cells could form colonies. The average validity of the sorting is always 90&#8211;95%.</li>
	<li>Sort a single donor cell by FACS into each well of a 96-well plate with the recipient (4.2).</li>
	<li>Incubate the plate for 45 min at 30 &#176;C, and then add high concentrations of antibiotics (100 &#956;g/mL Km and 60 &#956;g/mL Gm) to each well to prevent further conjugation.</li>
	<li>Incubate the plate at 30 &#176;C for 2 d.</li>
	<li>Count the number of wells in which transconjugants grew as determined by visual inspection with the naked eye.</li>
	<li>Calculate the probability of donor-initiated conjugation by dividing the number of wells with transconjugants by the total number of wells in which the donor was sorted.</li>
</ol>

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N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transposon+vectors+containing+non-antibiotic+resistance+selection+markers+for+cloning+and+stable+chromosomal+insertion+of+foreign+genes+in+gram-negative+bacteria.">Transposon vectors containing non-antibiotic resistance selection markers for cloning and stable chromosomal insertion of foreign genes in gram-negative bacteria.</a> Journal of Bacteriology. 172 (11), 6557-6567 (1990).</li><li>Bagdasarian, 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=Specific-purpose+plasmid+cloning+vectors.+II.+Broad+host+range,+high+copy+number,+RSF1010-derived+vectors,+and+a+host-vector+system+for+gene+cloning+in+Pseudomonas.">Specific-purpose plasmid cloning vectors. II. Broad host range, high copy number, RSF1010-derived vectors, and a host-vector system for gene cloning in Pseudomonas.</a> Gene. 16 (1-3), 237-247 (1981).</li><li>Maeda, K., 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=Complete+nucleotide+sequence+of+carbazole/dioxin-degrading+plasmid+pCAR1+in+Pseudomonas+resinovorans+strain+CA10+indicates+its+mosaicity+and+the+presence+of+large+catabolic+transposon+Tn4676.">Complete nucleotide sequence of carbazole/dioxin-degrading plasmid pCAR1 in Pseudomonas resinovorans strain CA10 indicates its mosaicity and the presence of large catabolic transposon Tn4676.</a> Journal of Molecular Biology. 326 (1), 21-33 (2003).</li><li>Takahashi, Y., Shintani, M., Yamane, H., Nojiri, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+complete+nucleotide+sequence+of+pCAR2:+pCAR2+and+pCAR1+were+structurally+identical+IncP-7+carbazole+degradative+plasmids.">The complete nucleotide sequence of pCAR2: pCAR2 and pCAR1 were structurally identical IncP-7 carbazole degradative plasmids.</a> Bioscience, Biotechnology, and Biochemistry. 73 (3), 744-746 (2009).</li></ol>

The authors have nothing to disclose.

Here, we present a high-resolution protocol for detecting differences in conjugation frequency under different conditions, using a MPN method to estimate the number of transconjugants. One important step in the protocol is diluting the mixture of donor and recipient after mating until no transconjugants grow. Another step is adding high concentrations of antibiotics to the selective liquid medium to prevent further conjugation. These procedures can reduce the background caused by further conjugation in the selective medium. We could successfully detect differences, even after a short mating duration between the donor and recipient. The conjugative frequency calculated by this protocol could be altered by small differences in the growth conditions of the donor and recipient strains. Thus, these conditions should be carefully designed.
In addition, we present a protocol for estimating the second step of conjugation by using FACS for single donor cell sorting. The most important step in this protocol is determining the appropriate density of recipient cells for a sorted single donor cell. When the number of recipient cells surrounding a single donor cell is large enough, physical contact between the donor and recipient is certain. Then, the conjugation frequency can be influenced, not by the probability of how often the donor and recipient cells contact each other, but by the probability of donor-initiated conjugation. Sorting a single donor cell by FACS is not difficult; however, 96 wells are not always sufficient to estimate the probability. Therefore, 10-100 plates should be prepared. One of the limits of the protocol is that it is not appropriate for measuring the probability of donor-initiated conjugation of a plasmid with low-frequency transmissibility.
Based on these methods and their results, we recently reported that two plasmids showed different conjugation frequencies in liquid media by changing the stirring rates, which can affect the first and third steps of conjugation, attachment and detachment of donor-recipient pairs. In addition, we also found differences in the probability of the second step10. These results demonstrate how the conjugation frequency changes under different conditions. These protocols are useful for comparing the conjugation features of plasmids under various conditions, including aerobic or anaerobic conditions, different donor-recipient pairs, different temperature or pH, and in the presence or absence of specific chemicals, such as cations, nutrients, and antibiotics.

Bacterial conjugation of mobile genetic elements, conjugative plasmids, and integrative and conjugative elements (ICEs) is important for the horizontal spread of genetic information. It can promote rapid bacterial evolution and adaptation and transmit multidrug resistance genes1,2. The conjugation frequency can be affected by proteins encoded on the conjugative elements for mobilization of DNA (MOB) and mating pair formation (MPF), including sex pili, which are classified according to MOB and MPF type3,4,5. It can also be affected by the donor and recipient pair6 and the growth conditions of the cells7,8,9,10,11,12 (growth rate, cell density, solid surface or liquid medium, temperature, nutrient availability, and the presence of cations). To understand how the conjugative elements spread among bacteria, it is necessary to compare conjugation frequency in detail.
The conjugation frequency between donor and recipient pairs after mating are usually estimated by conventional methods as follows. (i) First, the numbers of donor and recipient colonies are counted; (ii) then, the recipient colonies, which received the conjugative elements (= transconjugants) are counted; (iii) and finally, the conjugation frequency is calculated by dividing the colony forming units (CFU) of the transconjugants by those of the donor and/or recipient13. However, when using this method, the background is high due to additional conjugation events that can also occur on the selective plates used to obtain transconjugants when the cell density is high10. Therefore, it is difficult to detect small differences in frequency (below a 10-fold difference). We recently introduced a most probable number (MPN) method using liquid medium containing a higher concentration of antibiotics. This method reduced the background by inhibiting further conjugation in selective medium; thus, the conjugation frequency could be estimated with higher resolution.
Conjugation can be divided into three steps: (1) attachment of the donor-recipient pair (2) initiation of conjugative transfer, and (3) dissociation of the pair14. During steps (1) and (3), there is physical interaction between the donor and recipient cells; thus, cell density and the environmental conditions can influence these steps, although the features of the sex pili are also important. Step (2) is likely regulated by the expression of several genes involved in conjugation in response to external changes, which could be affected by various features of the plasmid, donor, and recipient. Although the physical attachment or detachment of donor-recipient pairs can be mathematically simulated using an estimation of cells as particles, the frequency of step (2) should be experimentally measured. There have been a few reports on direct observations of how often donors can initiate conjugation [step (2)] using fluorescence microscopy15,16; however, these methods are not high-throughput because a large number of cells must be monitored. Therefore, we developed a new method to estimate the probability of the occurrence of step (2) by using fluorescence activated cell sorting (FACS). Our method can be applied to any plasmid, without identification of the essential genes for conjugation.

<table>
	<tbody>
		<tr>
			<td>MoFlo XDP</td>
			<td>Beckman-Coulter</td>
			<td>ML99030</td>
			<td>FACS</td>
		</tr>
		<tr>
			<td>IsoFlow</td>
			<td>Beckman-Coulter</td>
			<td>8599600</td>
			<td>Sheath solution</td>
		</tr>
		<tr>
			<td>Fluorospheres (10 &#956;m)</td>
			<td>Beckman-Coulter</td>
			<td>6605359</td>
			<td>beads to set up the FACS</td>
		</tr>
		<tr>
			<td>Incubator</td>
			<td>Yamato Scientific Co. Ltd</td>
			<td>211197-IC802</td>
			<td></td>
		</tr>
		<tr>
			<td>UV-VIS Spectrophotometer UV-1800</td>
			<td>SIMADZU Corporation</td>
			<td>UV-1800</td>
			<td></td>
		</tr>
		<tr>
			<td>96-well plates</td>
			<td>NIPPON Genetics Co, Ltd</td>
			<td>TR5003</td>
			<td></td>
		</tr>
		<tr>
			<td>microplate type Petri dish</td>
			<td>AXEL</td>
			<td>1-9668-01</td>
			<td>for validation of sorting</td>
		</tr>
		<tr>
			<td>membrane filter</td>
			<td>ADVANTEC</td>
			<td>C045A025A</td>
			<td>for filter mating</td>
		</tr>
		<tr>
			<td>pippettes</td>
			<td>Nichiryo CO. Ltd</td>
			<td>00-NPX2-20, 
			00-NPX2-200, 
			00-NPX2-1000</td>
			<td>0.5-10 &#956;L, 20-200 &#956;L, 100-1000 &#956;L</td>
		</tr>
		<tr>
			<td>multi-channel pippetes</td>
			<td>Nichiryo CO. Ltd</td>
			<td>00-NPM-8VP, 
			00-NPM-8LP</td>
			<td>0.5-10 &#956;L, 20-200 &#956;L</td>
		</tr>
		<tr>
			<td>Tryptone</td>
			<td>BD Difco</td>
			<td>211705</td>
			<td></td>
		</tr>
		<tr>
			<td>Yeast extract</td>
			<td>BD Difco</td>
			<td>212750</td>
			<td></td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>Sigma</td>
			<td>S-5886</td>
			<td></td>
		</tr>
		<tr>
			<td>Agar</td>
			<td>Nakarai tesque</td>
			<td>01162-15</td>
			<td></td>
		</tr>
		<tr>
			<td>rifampicin</td>
			<td>Wako</td>
			<td>185-01003</td>
			<td></td>
		</tr>
		<tr>
			<td>gentamicin</td>
			<td>Wako</td>
			<td>077-02974</td>
			<td></td>
		</tr>
		<tr>
			<td>kanamycin</td>
			<td>Wako</td>
			<td>115-00342</td>
			<td></td>
		</tr>
		<tr>
			<td>Petri dish</td>
			<td>AXEL</td>
			<td>3-1491-51</td>
			<td>JPND90-15</td>
		</tr>
		<tr>
			<td>microtubes</td>
			<td>Fukaekasei</td>
			<td>131-815C</td>
			<td></td>
		</tr>
		<tr>
			<td>500 mL disposable spinner flask</td>
			<td>Corning</td>
			<td>CLS3578</td>
			<td></td>
		</tr>
	</tbody>
</table>

high-resolution comparison of bacterial conjugation frequencies

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

Comparison of conjugation frequency by the MPN method
In our previous report, we compared the conjugation frequencies of pBP136::gfp and pCAR1::gfp in three-fold diluted LB (1/3 LB) liquid medium with different stirring rates after a 45 min mating using 125 mL spinner flasks10. We compared the conjugation frequencies of pBP136::gfp and pCAR1::gfp with 106 CFU/mL of donor and recipient strains under different stirring conditions (0-600 rpm). The conjugation frequency of both plasmids increased at higher stirring rates, and the maximum difference in the conjugation frequency was &#60;10-fold for pBP136::gfp (between 0 and 400 rpm), while that of pCAR1::gfp was ~25-fold (between 0 and 200 rpm; Fig. 1).
Estimation of the probability of donor-initiated conjugation
The previously estimated probability of donor-initiated conjugation is shown in Table 2. To determine the density of recipient cells required to compare the probability of conjugation, mating assays were performed with different densities of donor and recipient. As shown in Table 2, pBP136::gfp transconjugants were detected in 100% (96/96) of wells containing 103 CFU of donor and 105-107 CFU of recipient, and those with 102 CFU of donor and 106-107 CFU of recipient, indicating that the cell density was too high. Mating assays with 101 CFU of donor and 106 or 105 CFU of recipient resulted in a decreased number of transconjugant-positive wells (66% and 2.1%, respectively, Table 2). Thus, &#62;105 CFU of recipient was predicted to be required for mating with a single donor cell. Similarly, we performed the mating assays with pCAR1::gfp at different densities of donor and recipient strains. The percentages of transconjugant-positive wells were much lower than those of pBP136::gfp (Table 2). Assuming that the donor and recipient cells can attach to each other similarly, the probability of conjugation initiation for the pCAR1 donor was lower than that for the pBP136 donor. Based on these results, we determined that 107 CFU of recipient was required for a single donor cell sorted by FACS.
Then, the numbers of transconjugant-positive wells were counted. The percentage of transconjugant-positive wells for pBP136::gfp was larger (1.9%) than that for pCAR1::gfp (&#60;0.052%; Table 2). Thus, there was more than a 36-fold difference in the probability of donor-initiated conjugation between these two plasmids.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57812/57812fig1.jpg" /> 
Figure 1. Comparison of the conjugation frequencies of pBP136::gfp and pCAR1::gfp with 106 colony forming units (CFU) mL-1 of donor (Pseudomonas putida SMDBS) and recipient (P. putida KT2440RGD) at different stirring rates (0-600 rpm). The error bars were calculated based on 95% confidence limits by the MPN method and the standard deviation of CFU of donor and recipient. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/57812/57812fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Bacterial strains</td>
			<td>Genotype and relevent phenotype</td>
			<td>Reference or source</td>
		</tr>
		<tr>
			<td>Escherichia coli DH10B</td>
			<td>F&#8211;, mcrA, &#916;(mrr-hsdRMS-mcrBC), &#934;80dlacZ&#916;M15, &#916;lacX74, deoR, recA1, araD139, &#916;(ara leu)7697, galU, galK, &#955;-, rpsL, endA1, nupG</td>
			<td>Thermo</td>
		</tr>
		<tr>
			<td>E. coli S17-1(&#955;pir)</td>
			<td>Tmr, Smr, recA, thi, pro, hsdR-M+, RP4: 2-Tc:Mu: Km Tn7 &#955;pir</td>
			<td>18</td>
		</tr>
		<tr>
			<td>Pseudomoans putida KT2440</td>
			<td>Kms, Rifs, Gms, Tcr</td>
			<td>25</td>
		</tr>
		<tr>
			<td>Pseudomoans putida KT2440(pCAR1)</td>
			<td>KT2440 harboring pCAR1</td>
			<td>20</td>
		</tr>
		<tr>
			<td>Pseudomoans putida KT2440RGD</td>
			<td>Kms, Rifr, Gmr, Tcr, miniTn7(Gm) PA1/O4/O3 DsRedExpress-a is inseted in chromosome</td>
			<td>10</td>
		</tr>
		<tr>
			<td>Pseudomoans putida SMDBS</td>
			<td>Derivative strain of P. putida KT2440, dapB-deleted, Kms, Gms, Rifr, Tcr, lacIq is inserted in chromosome</td>
			<td>21</td>
		</tr>
		<tr>
			<td>P. resinovorans CA10RG</td>
			<td>Kms, Rifr, Gmr, Tcs</td>
			<td>6</td>
		</tr>
		<tr>
			<td>Plasmids</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>pBP136</td>
			<td>IncP-1, MOBP, MPFT plasmid</td>
			<td>17</td>
		</tr>
		<tr>
			<td>pBP136::gfp</td>
			<td>pBP136 carrying Kmr and PA1/04/03-gfp cassette in parA (26,137 nt)</td>
			<td>21</td>
		</tr>
		<tr>
			<td>pCAR1</td>
			<td>IncP-7, MOBH, MPFF, carbazole degradative plasmid</td>
			<td>26, 27</td>
		</tr>
		<tr>
			<td>pCAR1::gfp</td>
			<td>pCAR1 carrying Kmr and PA1/04/03-gfp cassette in ORF171 (182,625 nt)</td>
			<td>21</td>
		</tr>
		<tr>
			<td>pJBA28</td>
			<td>Apr, Kmr, delivery plasmid for mini-Tn5-Km-PA1/04/03-RBSII-gfpmut3*-T0-T1</td>
			<td>18</td>
		</tr>
	</tbody>
</table>
Table 1. Bacterial strains and plasmids.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td rowspan="2">Plasmid</td>
			<td>aDonor</td>
			<td>aRecipient</td>
			<td rowspan="2">The numbers of wells with transconjugants per 96 wells</td>
			<td>Percentage</td>
		</tr>
		<tr>
			<td>[CFUs or cell]</td>
			<td>[CFUs]</td>
			<td>[%]</td>
		</tr>
		<tr>
			<td rowspan="10">pBP136::gfp</td>
			<td rowspan="3">103</td>
			<td>107</td>
			<td>96/96</td>
			<td>100</td>
		</tr>
		<tr>
			<td>106</td>
			<td>96/96</td>
			<td>100</td>
		</tr>
		<tr>
			<td>105</td>
			<td>96/96</td>
			<td>100</td>
		</tr>
		<tr>
			<td rowspan="3">102</td>
			<td>107</td>
			<td>96/96</td>
			<td>100</td>
		</tr>
		<tr>
			<td>106</td>
			<td>96/96</td>
			<td>100</td>
		</tr>
		<tr>
			<td>105</td>
			<td>54/96</td>
			<td>56</td>
		</tr>
		<tr>
			<td rowspan="3">101</td>
			<td>107</td>
			<td>71/96</td>
			<td>74</td>
		</tr>
		<tr>
			<td>106</td>
			<td>63/96</td>
			<td>66</td>
		</tr>
		<tr>
			<td>105</td>
			<td>2/96</td>
			<td>2.1</td>
		</tr>
		<tr>
			<td>1</td>
			<td>107</td>
			<td>23/1212</td>
			<td>1.9</td>
		</tr>
		<tr>
			<td rowspan="10">pCAR1::gfp</td>
			<td rowspan="3">103</td>
			<td>107</td>
			<td>6/96</td>
			<td>6.3</td>
		</tr>
		<tr>
			<td>106</td>
			<td>6/96</td>
			<td>6.3</td>
		</tr>
		<tr>
			<td>105</td>
			<td>0/96</td>
			<td>0</td>
		</tr>
		<tr>
			<td rowspan="3">102</td>
			<td>107</td>
			<td>1/96</td>
			<td>1</td>
		</tr>
		<tr>
			<td>106</td>
			<td>1/96</td>
			<td>1</td>
		</tr>
		<tr>
			<td>105</td>
			<td>0/96</td>
			<td>0</td>
		</tr>
		<tr>
			<td rowspan="3">101</td>
			<td>107</td>
			<td>0/96</td>
			<td>0</td>
		</tr>
		<tr>
			<td>106</td>
			<td>0/96</td>
			<td>0</td>
		</tr>
		<tr>
			<td>105</td>
			<td>0/96</td>
			<td>0</td>
		</tr>
		<tr>
			<td>1</td>
			<td>107</td>
			<td>1/1920</td>
			<td>&#60; 0.052</td>
		</tr>
	</tbody>
</table>
Table 2. The number of wells, with different cell densities, containing transconjugants to compare the probability of donor-initiated conjugation between pBP136::gfp and pCAR1::gfp.

Watch this Scientific Journal Video about High-Resolution Comparison of Bacterial Conjugation Frequencies at JoVE.com

High-Resolution Comparison of Bacterial Conjugation Frequencies

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

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

high-resolution-comparison-of-bacterial-conjugation-frequencies

Nanyang Technological University

Research

JoVE Journal

Genetics

10.6K Views.  Shizuoka University. With an aim to understand the behaviors of various bacterial conjugative DNA elements under different conditions, we describe a protocol for detecting differences in conjugation frequency, with high resolution, to estimate how efficiently the donor bacterium initiates conjugation.

Video: High-Resolution Comparison of Bacterial Conjugation Frequencies

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 ...

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 ...

High-resolution Melting PCR for Complement Receptor 1 Length Polymorphism Genotyping: An Innovative Tool for Alzheimer's Disease Gene Susceptibility Assessment

Complement receptor 1 (CR1), a transmembrane glycoprotein that plays a key role in the innate immune system, is expressed on many cell types, but especially on red blood cells (RBCs). As a receptor for the complement components C3b and C4b, CR1 regulates the activation of the complement cascade and promotes the phagocytosis of immune complexes and cellular debris, as well as the amyloid-beta (A&#946;) peptide in Alzheimer's disease (AD). Several studies have confirmed AD-associated single nucleotide polymorphisms (SNPs), as well as a copy-number variation (CNV) in the CR1 gene. Here, we describe an innovative method for determining the length polymorphism of the CR1 receptor. The receptor includes three domains, called long homologous repeats (LHR)-LHR-A, LHR-C, and LHR-D-and an n domain, LHR-B, where n is an integer between 0 and 3. Using a single pair of specific primers, the genetic material is used to amplify a first fragment of the LHR-B domain (the variant amplicon B) and a second fragment of the LHR-C domain (the invariant amplicon). The variant amplicon B and the invariant amplicon display differences at five nucleotides outside of the hybridization areas of said primers. The numbers of variant amplicons B and of invariant amplicons is deduced using a quantitative tool (high-resolution melting (HRM) curves), and the ratio of the variant amplicon B to the invariant amplicon differs according to the CR1 length polymorphism. This method provides several advantages over the canonical phenotype method, as it does not require fresh material and is cheaper, faster, and therefore applicable to larger populations. Thus, the use of this method should be helpful to better understand the role of CR1 isoforms in the pathogenesis of diseases such as AD.

Here, we describe an innovative method to determine complement receptor 1 (CR1) length polymorphisms for use in several applications, particularly the assessment of susceptibility to diseases such as Alzheimer&#39;s disease (AD). This method could be useful to better understand the role of CR1 isoforms in the pathogenesis of AD.

Complement receptor 1 (CR1), a transmembrane glycoprotein that plays a key role in the innate immune system, is expressed on many cell types, but ...

High Resolution Fluorescent In Situ Hybridization in Drosophila Embryos and Tissues Using Tyramide Signal Amplification

In our efforts to determine the patterns of expression and subcellular localization of Drosophila RNAs on a genome-wide basis, and in a variety of tissues, we have developed numerous modifications and improvements to our original fluorescent in situ hybridization (FISH) protocol. To facilitate throughput and cost effectiveness, all steps, from probe generation to signal detection, are performed using exon 96-well microtiter plates. Digoxygenin (DIG)-labelled antisense RNA probes are produced using either cDNA clones or genomic DNA as templates. After tissue fixation and permeabilization, probes are hybridized to transcripts of interest and then detected using a succession of anti-DIG antibody conjugated to biotin, streptavidin conjugated to horseradish peroxidase (HRP) and fluorescently conjugated tyramide, which in the presence of HRP, produces a highly reactive intermediate that binds to electron dense regions of immediately adjacent proteins. These amplification and localization steps produce a robust and highly localized signal that facilitates both cellular and subcellular transcript localization. The protocols provided have been optimized to produce highly specific signals in a variety of tissues and developmental stages. References are also provided for additional variations that allow the simultaneous detection of multiple transcripts, or transcripts and proteins, at the same time.

High Resolution Fluorescent In Situ Hybridization in Drosophila Embryos and Tissues Using Tyramide Signal Amplification

The described RNA in situ hybridization protocol allows the detection of RNA in whole Drosophila embryos or dissected tissues. Using 96-well microtiter plates and tyramide signal amplification, transcripts can be detected at high resolution, sensitivity, and throughput, and at a relatively low cost.

In our efforts to determine the patterns of expression and subcellular localization of Drosophila RNAs on a genome-wide basis, and in a variety of ...

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.

DNA regulatory elements, such as enhancers, control gene expression by physically contacting target gene promoters, often through long-range chromosomal interactions spanning large genomic distances. Promoter Capture Hi-C (PCHi-C) identifies significant interactions between promoters and distal regions, enabling the assignment of potential regulatory sequences to their target genes.

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the ...

Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to abiotic stresses and diseases. As the plant microbiome can be highly complex, low-cost, high-throughput methods such as amplicon-based sequencing of the 16S rRNA gene are often preferred for characterizing its microbial composition and diversity. However, the selection of appropriate methodology when conducting such experiments is critical for reducing biases that can make analysis and comparisons between samples and studies difficult. This protocol describes in detail a standardized methodology for the collection and extraction of DNA from soil, rhizosphere, and root samples. Additionally, we highlight a well-established 16S rRNA amplicon sequencing pipeline that allows for the exploration of the composition of bacterial communities in these samples, and can easily be adapted for other marker genes. This pipeline has been validated for a variety of plant species, including sorghum, maize, wheat, strawberry, and agave, and can help overcome issues associated with the contamination from plant organelles.

Here, we describe a protocol to obtain amplicon sequence data of soil, rhizosphere, and root endosphere microbiomes. This information can be used to investigate the composition and diversity of plant-associated microbial communities, and is suitable for the use with a wide range of plant species.

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to ...

A Fluorescence-based Method to Study Bacterial Gene Regulation in Infected Tissues

Bacterial virulence genes are often regulated at the transcriptional level by multiple factors that respond to different environmental signals. Some factors act directly on virulence genes; others control pathogenesis by adjusting the expression of downstream regulators or the accumulation of signals that affect regulator activity. While regulation has been studied extensively during in vitro growth, relatively little is known about how gene expression is adjusted during infection. Such information is important when a particular gene product is a candidate for therapeutic intervention. Transcriptional approaches like quantitative, real-time RT-PCR and RNA-Seq are powerful ways to examine gene expression on a global level but suffer from many technical challenges including low abundance of bacterial RNA compared to host RNA, and sample degradation by RNases. Evaluating regulation using fluorescent reporters is relatively easy and can be multiplexed with fluorescent proteins with unique spectral properties. The method allows for single-cell, spatiotemporal analysis of gene expression in tissues that exhibit complex three-dimensional architecture and physiochemical gradients that affect bacterial regulatory networks. Such information is lost when data are averaged over the bulk population. Herein, we describe a method for quantifying gene expression in bacterial pathogens in situ. The method is based on simple tissue processing and direct observation of fluorescence from reporter proteins. We demonstrate the utility of this system by examining the expression of Staphylococcus aureus thermonuclease (nuc), whose gene product is required for immune evasion and full virulence ex vivo and in vivo. We show that nuc-gfp is strongly expressed in renal abscesses and reveal heterogeneous gene expression due in part to apparent spatial regulation of nuc promoter activity in abscesses fully engaged with the immune response. The method can be applied to any bacterium with a manipulatable genetic system and any infection model, providing valuable information for preclinical studies and drug development.

Described here is a method for analyzing bacterial gene expression in animal tissues at a cellular level. This method provides a resource for studying the phenotypic diversity occurring within a bacterial population in response to the tissue environment during an infection.

Bacterial virulence genes are often regulated at the transcriptional level by multiple factors that respond to different environmental signals. Some ...

Identifying Mutations by High Resolution Melting in a TILLING Population of Rice

Target Induced Local Lesions In Genomes (TILLING) is a strategy of reverse genetics for the high-throughput screening of induced mutations. However, the TILLING system has less applicability for insertion/deletion (Indel) detection and traditional TILLING needs more complex steps, like CEL I nuclease digestion and gel electrophoresis. To improve the throughput and selection efficiency, and to make the screening of both Indels and single base substitions (SBSs) possible, a new high-resolution melting (HRM)-based TILLING system is developed. Here, we present a detailed HRM-TILLING protocol and show its application in mutation screening. This method can analyze the mutations of PCR amplicons by measuring the denaturation of double-stranded DNA at high temperatures. HRM analysis is directly performed post-PCR without additional processing. Moreover, a simple, safe and fast (SSF) DNA extraction method is integrated with HRM-TILLING to identify both Indels and SBSs. Its simplicity, robustness and high throughput make it potentially useful for mutation scanning in rice and other crops.

In this article, we present the protocol that is described as high-resolution melting analysis (HRM)-based Target Induced Local Lesions In Genomes (TILLING). This method utilizes fluorescence changes during the melting of the DNA duplex and is suitable for high-throughput screening of both insertion/deletion (Indel) and single base substition (SBS).

Target Induced Local Lesions In Genomes (TILLING) is a strategy of reverse genetics for the high-throughput screening of induced mutations. However, the ...

Tomato Root Transformation Followed by Inoculation with Ralstonia Solanacearum for Straightforward Genetic Analysis of Bacterial Wilt Disease

Ralstonia solanacearum is a devastating soil borne vascular pathogen that can infect a large range of plant species, causing an important threat to agriculture. However, the Ralstonia model is considerably underexplored in comparison to other models involving bacterial plant pathogens, such as Pseudomonas syringae in Arabidopsis. Research targeted to understanding the interaction between Ralstonia and crop plants is essential to develop sustainable solutions to fight against bacterial wilt disease but is currently hindered by the lack of straightforward experimental assays to characterize the different components of the interaction in native host plants. In this scenario, we have developed a method to perform genetic analysis of Ralstonia infection of tomato, a natural host of Ralstonia. This method is based on Agrobacterium rhizogenes-mediated transformation of tomato roots, followed by Ralstonia soil-drenching inoculation of the resulting plants, containing transformed roots expressing the construct of interest. The versatility of the root transformation assay allows performing either gene overexpression or gene silencing mediated by RNAi. As a proof of concept, we used this method to show that RNAi-mediated silencing of SlCESA6 in tomato roots conferred resistance to Ralstonia. Here, we describe this method in detail, enabling genetic approaches to understand bacterial wilt disease in a relatively short time and with small requirements of equipment and plant growth space.

Tomato Root Transformation Followed by Inoculation with Ralstonia Solanacearum for Straightforward Genetic Analysis of Bacterial Wilt Disease

Here, we present a versatile method for tomato root transformation followed by inoculation with Ralstonia solanacearum to perform straightforward genetic analysis for the study of bacterial wilt disease.

Ralstonia solanacearum is a devastating soil borne vascular pathogen that can infect a large range of plant species, causing an important threat to ...

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.

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 ...

High-Resolution Comparison of Bacterial Conjugation Frequencies

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Chapters in this video

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

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

High-resolution Melting PCR for Complement Receptor 1 Length Polymorphism Genotyping: An Innovative Tool for Alzheimer's Disease Gene Susceptibility Assessment

High Resolution Fluorescent In Situ Hybridization in Drosophila Embryos and Tissues Using Tyramide Signal Amplification

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere

A Fluorescence-based Method to Study Bacterial Gene Regulation in Infected Tissues

Identifying Mutations by High Resolution Melting in a TILLING Population of Rice

Tomato Root Transformation Followed by Inoculation with Ralstonia Solanacearum for Straightforward Genetic Analysis of Bacterial Wilt Disease

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