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 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.
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.
1. Preparation of a Donor with Green Fluorescent Protein (GFP)- and Kanamycin Resistance Gene-Tagged Plasmids
2. Calculation of Conjugation Frequency by the MPN Method
3. Preparation for Estimation of the Probability of Donor-Initiated Conjugation
4. Estimation of the Probability of Donor-Initiated Conjugation
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 <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, >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 (<0.052%; Table 2). Thus, there was more than a 36-fold difference in the probability of donor-initiated conjugation between these two plasmids.
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. Please click here to view a larger version of this figure.
Bacterial strains | Genotype and relevent phenotype | Reference or source |
Escherichia coli DH10B | F–, mcrA, Δ(mrr–hsdRMS–mcrBC), Φ80dlacZΔM15, ΔlacX74, deoR, recA1, araD139, Δ(ara leu)7697, galU, galK, λ–, rpsL, endA1, nupG | Thermo |
E. coli S17-1(λpir) | Tmr, Smr, recA, thi, pro, hsdR–M+, RP4: 2-Tc:Mu: Km Tn7 λpir | 18 |
Pseudomoans putida KT2440 | Kms, Rifs, Gms, Tcr | 25 |
Pseudomoans putida KT2440(pCAR1) | KT2440 harboring pCAR1 | 20 |
Pseudomoans putida KT2440RGD | Kms, Rifr, Gmr, Tcr, miniTn7(Gm) PA1/O4/O3 DsRedExpress-a is inseted in chromosome | 10 |
Pseudomoans putida SMDBS | Derivative strain of P. putida KT2440, dapB-deleted, Kms, Gms, Rifr, Tcr, lacIq is inserted in chromosome | 21 |
P. resinovorans CA10RG | Kms, Rifr, Gmr, Tcs | 6 |
Plasmids | ||
pBP136 | IncP-1, MOBP, MPFT plasmid | 17 |
pBP136::gfp | pBP136 carrying Kmr and PA1/04/03–gfp cassette in parA (26,137 nt) | 21 |
pCAR1 | IncP-7, MOBH, MPFF, carbazole degradative plasmid | 26, 27 |
pCAR1::gfp | pCAR1 carrying Kmr and PA1/04/03–gfp cassette in ORF171 (182,625 nt) | 21 |
pJBA28 | Apr, Kmr, delivery plasmid for mini-Tn5-Km-PA1/04/03-RBSII-gfpmut3*-T0-T1 | 18 |
Table 1. Bacterial strains and plasmids.
Plasmid | aDonor | aRecipient | The numbers of wells with transconjugants per 96 wells | Percentage |
[CFUs or cell] | [CFUs] | [%] | ||
pBP136::gfp | 103 | 107 | 96/96 | 100 |
106 | 96/96 | 100 | ||
105 | 96/96 | 100 | ||
102 | 107 | 96/96 | 100 | |
106 | 96/96 | 100 | ||
105 | 54/96 | 56 | ||
101 | 107 | 71/96 | 74 | |
106 | 63/96 | 66 | ||
105 | 2/96 | 2.1 | ||
1 | 107 | 23/1212 | 1.9 | |
pCAR1::gfp | 103 | 107 | 6/96 | 6.3 |
106 | 6/96 | 6.3 | ||
105 | 0/96 | 0 | ||
102 | 107 | 1/96 | 1 | |
106 | 1/96 | 1 | ||
105 | 0/96 | 0 | ||
101 | 107 | 0/96 | 0 | |
106 | 0/96 | 0 | ||
105 | 0/96 | 0 | ||
1 | 107 | 1/1920 | < 0.052 |
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.
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.
The authors have nothing to disclose.
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 Sølen 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/).
MoFlo XDP | Beckman-Coulter | ML99030 | FACS |
IsoFlow | Beckman-Coulter | 8599600 | Sheath solution |
Fluorospheres (10 μm) | Beckman-Coulter | 6605359 | beads to set up the FACS |
Incubator | Yamato Scientific Co. Ltd | 211197-IC802 | |
UV-VIS Spectrophotometer UV-1800 | SIMADZU Corporation | UV-1800 | |
96-well plates | NIPPON Genetics Co, Ltd | TR5003 | |
microplate type Petri dish | AXEL | 1-9668-01 | for validation of sorting |
membrane filter | ADVANTEC | C045A025A | for filter mating |
pippettes | Nichiryo CO. Ltd | 00-NPX2-20, 00-NPX2-200, 00-NPX2-1000 |
0.5-10 μL, 20-200 μL, 100-1000 μL |
multi-channel pippetes | Nichiryo CO. Ltd | 00-NPM-8VP, 00-NPM-8LP |
0.5-10 μL, 20-200 μL |
Tryptone | BD Difco | 211705 | |
Yeast extract | BD Difco | 212750 | |
NaCl | Sigma | S-5886 | |
Agar | Nakarai tesque | 01162-15 | |
rifampicin | Wako | 185-01003 | |
gentamicin | Wako | 077-02974 | |
kanamycin | Wako | 115-00342 | |
Petri dish | AXEL | 3-1491-51 | JPND90-15 |
microtubes | Fukaekasei | 131-815C | |
500 mL disposable spinner flask | Corning | CLS3578 |