A criterion for plasmid maintenance via conjugation

We used a simple kinetic model to investigate the extent to which HGT contributes to plasmid maintenance. The model describes one population (S) that either carries the plasmid (S 1) or is plasmid free (S 0) (Fig. 1b, Supplementary Methods, Supplementary Eqs. (3)–(4)). In particular, we determined the conditions where the plasmid-carrying population is dominant to provide a conservative estimate for a critical conjugation efficiency. For the limiting case where the rate of plasmid loss is relatively small (see Supplementary Methods, “Deriving a stability criterion”), we derived a critical conjugation efficiency (\({\eta _{\rm Crit}}\), Eq. (1)), which approximates an upper bound for dominant plasmid persistance:

$${\eta _{\rm Crit}} = \alpha \left( {\kappa + D} \right) - D,$$ (1)

where α indicates the relative cost (α > 1) or the benefit (α < 1) of the plasmid, κ is the rate constant of plasmid loss, and D is the dilution rate of the two populations. Thus, we use the term “species” to differentiate between any two populations with a uniquely defined \({\eta _{\rm Crit}}\), which minimally requires different bacterial clones with genetically distinct backgrounds (e.g., strains or taxonomically diverse species).

According to Eq. (1), a plasmid will be maintained as long as the conjugation efficiency is sufficiently fast compared with the rate of plasmid loss and fitness burden (Fig. 1c, d). Sufficiently fast conjugation efficiency is necessary for the plasmid-carrying population to be dominant (S 1 > S 0, Fig. 1c), even when a plasmid is slightly beneficial (α is slightly <1). Our criterion is similar to that derived by Stewart and Levin17, but is more stringent in that it further requires dominance of the plasmid-carrying population. It also avoids experimental challenges associated with decoupling plasmid loss measurements from fitness cost42. Experimentally, observed plasmid loss (κ obs ) can be determined by measuring the time constant of decay for a non-transferrable plasmid, which represents a combined effect of true κ and α (Supplementary Fig. 1A)43. Indeed, analysis shows that \(\kappa _{\mathrm{obs}} \approx \kappa\) for plasmids with minimal fitness effects (α ≈ 1). Since these two parameters are challenging to decouple, our criterion lumps the effects of α and κ together. To determine κ obs , we chose to use a low-cost plasmid (α = 1.02) to minimize the confounding effects of cost. Based on our experimentally determined parameters, analysis shows the standard error associated with fitting the plasmid loss rate (≈ 0.0022) is greater than the difference between κ obs and κ (see Supplementary Methods, “Plasmid loss calculations”, for complete derivation).

Conjugation-assisted persistence in a synthetic system

To test whether the conjugation efficiency for common conjugal plasmids is sufficiently fast to compensate for cost, we first adopted a synthetic conjugation system derived from the F plasmid. In this system, the conjugation machinery is encoded on a helper plasmid F HR , which is not self-transmissible44. A second plasmid can be mobilized through conjugation when it carries the F origin of transfer sequence oriT. Here, we use a mobilizable plasmid denoted K, which expresses YFP under the control of the strong constitutive promoter P R , a kanamycin (Kan) resistance gene (k a n R)44, and oriT. To quantify the effects of conjugation, we implemented a plasmid identical to K except that it does not carry oriT (K−), and therefore cannot be transferred by conjugation. The synthetic system was introduced into an engineered derivative of Escherichia coli MG1655 expressing a constitutive blue fluorescent protein (BFP) chromosomally and carbenicillin (Carb) resistance (AmpR)45, denoted B (Fig. 2a). The plasmid-carrying populations (BK, BK−) can be distinguished from the plasmid-free population (B0) by selective plating (using Carb+Kan) or flow cytometry (using YFP) (Supplementary Fig. 2A). This notation will be used to describe all species and plasmid combinations throughout the text (see Supplementary Methods, “Nomenclature”).

This system provides a clean experimental configuration to elucidate the contribution of conjugation to plasmid maintenance. K enables more precise parameter estimates compared to natural self-transmissible plasmids. Native plasmids often encode additional functions that complicate measurements, such as addiction modules that can result in post-segregational killing of daughter cells46. Importantly, without a non-transmissible control plasmid, it is difficult to decouple the effects of HGT from other processes. Instead, plasmid loss and fitness burden can be precisely quantified using K−, which eliminates the confounding influence of conjugation. Since oriT did not significantly affect the burden of K compared to K− (Supplementary Fig. 1B, P > 0.5, two-sided t-test), differences that arise in the overall dynamics can be attributed to conjugation.

From our measurements of K, we expect conjugation to be fast enough to enable maintenance in the absence of antibiotic selection. In particular, our measurements of κ = 0.001 h−1 (Supplementary Fig. 1A), α = 1.02 (Supplementary Fig. 1C), and assuming D ≈ 0.05 h−1, we estimate the critical efficiency \({\eta _{\rm Crit}} = 0.002\) h−1 to be well below the estimate of conjugation efficiency from exponential phase growth \({\eta_{\rm C}} \approx 0.01\) h−1 34 (see Methods, “Estimating \({\eta _{\rm Crit}}\)”). Indeed, cell physiology can drastically change the conjugation efficiency34, as this value is almost four orders of magnitude greater than the efficiency measured from cells harvested from stationary phase (Supplementary Table 3).

To test conjugation-mediated plasmid maintenance, we mixed BK and B0 in equal fractions and cultured them together. A strong dilution (10,000×) was performed every 24 h to maintain growth. Different concentrations of Kan (0, 0.5, and 2 μg/mL) were used to vary α (1.02, 0.97, 0.42, respectively) (Supplementary Fig. 1C). Every few days, we quantified the fractions of plasmid-bearing cells (expressing BFP and YFP) and plasmid-free cells (expressing BFP only) using flow cytometry (see Supplementary Fig. 2A and Methods section “Flow cytometry calibration” for calibration details).

In the absence of conjugation, when the plasmid carries a cost (e.g., Kan = 0 and α > 1) the plasmid-bearing population was eliminated after 2 weeks (Fig. 2b, left modeling and right experiment). Thus, for a non-transferrable costly plasmid, eliminating antibiotics results in resistance reversal. If the plasmid was sufficiently beneficial, the plasmid-bearing population could coexist with the plasmid-free population (Fig. 2b, left modeling and right experiment). The fraction of plasmid-bearing cells depended on the relative magnitude of growth advantage compared with plasmid loss. In contrast, if the plasmid is transferrable through conjugation, even when the plasmid carries a cost, plasmid-bearing cells dominate the population in a short period of time (Fig. 2c, left modeling and right experiment). Intuitively, decreasing cost or increasing benefit (i.e., decreasing α) facilitates conjugation-assisted persistence, and therefore plasmid stability occurs on a faster timescale (Fig. 2c). Once the plasmid benefit is sufficiently high (Fig. 2c), the plasmid persists regardless of whether or not it can conjugate, indicating that conjugation is no longer required to maintain resistance.

Fig. 2 Conjugation-assisted persistence of costly plasmids. For all modeling and experimental results, x-axis is days and y-axis is fraction of cells. a Engineered conjugation. The background strain, B, expresses BFP and AmpR constitutively45. B carries the helper plasmid F HR (B0), which is non-self-transmissible, but can mobilize plasmids in trans. The mobile plasmid K carries the transfer origin (oriT), a kanamycin-resistant gene (KanR), and yfp under the control of strong constitutive promoter P R 44. When B carries K, it is denoted BK. K without transferability (i.e., without oriT) is denoted K−, and when carried by B, BK−. b Long-term dynamics without conjugation. Blue represents plasmid-free and orange plasmid-carrying cells. Shaded lines indicate different initial conditions generated by a strong dilution experimentally (~80 cells/well, 16 wells), or randomly chosen from a uniform distribution (total initial density maintained at 1 × 10−6, 20 replicates). Bold lines are the average across all initial conditions of corresponding color. Modeling (left): i–iii is α = 1.02, 0.97, and 0.42, respectively, estimated from experimental measurements (Supplementary Fig. 1C). Experiment (right): i–iii is Kan = 0, 0.5, and 2 μg/mL. Quantification is performed using flow cytometry, where the orange lines are cells expressing both BFP and YFP (BK−), and the blue line are cells expressing BFP only (B0). c Long-term dynamics with conjugation. Experiments were done identically to (B), with BK instead of BK−. Without antibiotics, the plasmid-carrying population dominated despite the plasmid cost, exhibiting conjugation-assisted persistence. All modeling parameters are identical except for \({\eta _{\rm C}} = 0.025\) h−1. d Nine conjugation plasmids carried by species R (except C with B0, which behaves similarly, Supplementary Fig. 3D) exhibit conjugation-assisted persistence. R0 was mixed in equal fraction with RP (P for plasmid generality) and diluted 10,000× daily. CFU from four-to-six double-selection plates were divided by the total number of colonies averaged across four-to-six Cm plates for quantification. Experiments are repeated at least twice. Error bars represent the standard deviation of the four-to-six measurements. The plasmids used are (i) #168, (ii) #193, (iii) R388, (iv) C, (v) #41, (vi) RP4, (vii) K, (viii) PCU1, and (ix) R6K (see Supplementary Tables 1 and 3) Full size image

Further, analysis suggests compensatory mutations, even at a high mutation rate, did not contribute significantly to the overall dynamics (Supplementary Fig. 2B). We note that our model assumes a constant dilution rate constant (D), which represents an approximation of the discrete, periodic dilutions in our experiments. Simulations using a model implementing discrete dilutions generated qualitatively the same results (Supplementary Fig. 1D). Finally, we introduced noise in the conjugation rate for each set of initial conditions such that \({\eta_{\rm C}}\) can vary a small amount from the basal value, within 10% of the mean, consistent with clonal variability34. This variability does not change the qualitative results (Supplementary Fig. 2C).

Conjugation-assisted persistence for diverse plasmids

We previously demonstrated that the conjugation efficiency of the synthetic system is comparable to that of natural F plasmids and several other natural conjugation plasmids34. Therefore, we expect these plasmids to also exhibit conjugation-assisted persistence. To this end, we quantified the dynamics of eight additional conjugative plasmids, covering six incompatibility groups (incF, incN, incI, incX, incW, and incP) which encompass >70% of the most common large plasmids isolated from Enterobacteriacea (335 plasmids that are >20 kB from GenBank)47, cover a wide range of conjugation efficiencies and fitness effects (Supplementary Fig. 3A, B), and include three clinically isolated conjugative plasmids encoding extended-spectrum β-lactamases (ESBLs). ESBL-producing pathogens are notorious for plasmid-mediated conjugation48,49,50 and are of paramount global health concern51, 52. We transferred each individual plasmid into a common background strain (E. coli MG1655 with chromosomally integrated dTomato, and chloramphenicol (Cm) resistance (CmR), denoted R), and quantified the relevant parameters to estimate \({\eta _{\rm Crit}}\); the plasmid C was quantified with background strain B since both plasmid C and strain R express CmR, and B behaves qualitatively similarly to R (Supplementary Fig. 3D).

Our estimates suggest a high likelihood for persistence \(\left( {{\mathrm{\Delta }}n = {\eta _{\rm C}} - {\eta _{\rm Crit}} >0} \right)\) for each of the nine plasmids (Supplementary Fig. 3C, including RK for control), either because they are sufficiently beneficial and/or transferred fast enough. To test this, we implemented the same competition experiments as previously described, and quantified the fraction of plasmid-bearing cells using colony-forming units (CFU) on double-antibiotic plates (see Methods). Daily dilutions were performed for 14–20 days. Indeed, each plasmid persisted throughout the duration of the experiment (Fig. 2d). The maintenance or dominance of several plasmids (#168, #193, RP4, R6K, and R388) was likely due to them being neutral or slight beneficial (Supplementary Fig. 3C), in addition to their fast transfer. In contrast, PCU1 was maintained despite its very high cost (estimated α ≈ 3, Fig. 2d; see Supplementary Fig. 3E for logscale).

Conjugation-assisted persistence in greater complexity consortia

Natural environments are typically far more complex, consisting of diverse species interconnected through an intricate web of gene exchange6, 53. Such networks can serve as reservoirs for antibiotic resistance in so-called HGT “hot spots”, enabling the dissemination of resistance to various pathogens or commensal microbes54,55,56. Therefore, we wondered whether conjugation-assisted persistence could occur in a multi-species community. This question was never conclusively explored previously.

Modeling suggests that, as long as the stability criterion is met, a single plasmid can be maintained via conjugation regardless of the number of species present (Fig. 3a, Supplementary Methods, Supplementary Eqs. (7)–(10)). To test this, we introduced a second E. coli strain R with or without oriT (RK or RK−) (Supplementary Fig. 4A). The total plasmid content is quantified as the sum of all plasmid-bearing species (RK+BK). Consistent with our predictions, results demonstrate that conjugation enables plasmid persistence compared to the non-conjugating control (Fig. 3a).

Fig. 3 Conjugation-assisted persistence with multiple species and/or plasmids. a–c x-axis is days and y-axis is fraction of cells. Bold and shaded lines represent average across, or individual, initial conditions, respectively. Color indicates blue for plasmid free (S 0), and orange or red for plasmid-carrying cells (S 1) K or C, respectively. a Two-species, one-plasmid community. Left two panels: no conjugation; right two panels: with conjugation. S 0 = B0 + R0 and S 1 = BK + RK. Modeling: From bottom (i) to top (iii) α 1 = α = 1.02, 0.97, and 0.42, respectively, and α 2 = 1.03, 1.02, and 0.9 (see Supplementary Eqs. (7)–(10), Supplementary Fig. 4A). Experiment from bottom (i) to top (iii): Kan = 0, 0.5, and 2 μg/mL, respectively. b Higher cost plasmid dynamics. Modeling (left column): From bottom (i) to top (iii) α = 1.13, 1.03, and 0.3, respectively (see Supplementary Eqs. (3)–(4), Supplementary Fig. 4B). Experiment (right column): From bottom (i) to top (iii): Cm = 0, 0.5, and 2 μg/mL. c One species, two-plasmid community. Each row represents a different combination of α, modulated with no antibiotic (i), Kan (ii–iii), or Cm (iv–v). The species can carry two (S 11), one (S 10, S 01), or no plasmids (S 00). Modeling (first and third columns): From bottom (i) to top (v) α 3 = 1.3, 1.2, 0.42, 1.01, 0.35 (see Supplementary Eqs. (11)–(14), Supplementary Fig. 4B). Experiment: (second and fourth column such that S 1 = BK + BCK or S 1 = BC + BCK for K or C, respectively). BC is mixed equally with BK. d, e Three-species, three-plasmid community. Species (R, Y, and B) are uniquely fluorescent (expressing dTomato, YFP, or BFP, respectively) and plasmids (R6K, RP4, and R388, diamond, square, and circle markers, respectively) have distinct resistance markers (StrpR, KanR, and TmR, respectively). Shading color corresponds to the respective population fraction (left y-axis), and markers indicate fraction of each plasmid (right y-axis). The initial experimental composition consists of R0, RR6K, Y0, YR388, B0, and BRP4. Modeling (left): Randomized initial conditions such that the total plasmid-free populations is maintained at 1 × 10−4 , and plasmid population arbitrarily chosen between 1 × 10–5 and 1 × 106, consistent with data (Supplementary Table 2 for parameter estimates). Experiment (right): Error bars indicate averaging across four-to-six plate replicates, and repeated five times Full size image

Moreover, modeling predicts conjugation-assisted persistence to occur for a single species carrying multiple conjugation plasmids. This is contingent on the plasmids’ ability to exist independently of each other (e.g., distinct incompatibility groups to ensure compatible replication machinery and the absence of surface exclusion that prevents entry of one of the plasmids), and the fact that other relevant plasmid parameters (i.e., \({\eta _{\rm C}}\), α, or κ) are not drastically altered by the presence of another plasmid (Supplementary Methods, Supplementary Eqs. (11)–(14)). To test this idea, we implemented a bi-directionally conjugating population by mixing B carrying either K or another mobilizable plasmid C. C expresses mCherry, CmR, and is compatible with K (p15A and pSC101 replication origins, respectively). Independently, since C has a greater cost compared to K (Supplementary Fig. 3B), conjugation required a longer time-scale to overcome competition and stably persist (Fig. 3b). Together, the dynamics of each plasmid individually were identical to that of the single-plasmid population dynamics, regardless of how we modulated α (Fig. 3c, no antibiotic, Kan, and Cm; see Supplementary Fig. 4A, B for α estimates).

These results suggest that, despite the apparent complexity, plasmid fate in a community consisting of multiple (n) species and (p) plasmids (leading to n2p populations) can be inferred from the individual plasmid dynamics, if these plasmids do not interfere with each other. The fate of each plasmid is governed by the criterion for conjugation-assisted persistence (e.g., \({\eta _{\rm C}} >{\eta _{\rm Crit}}\)). If \({\eta _{\rm C}} >{\eta _{\rm Crit}}\) for at least one such pair, the plasmid will persist if the particular host(s) can coexist within the population long term (which is largely driven by fitness). Importantly, the coexisting species must acquire the plasmid, either in the initial population structure, or via conjugation. This results in an initial barrier for the plasmid to establish itself due to competition, resulting in a dependence on the initial composition in determining plasmid fate (see Supplementary Methods, “Three-species three-plasmids model”).

To test this, we constructed a community consisting of three species (E. coli strains denoted B0, R0, and Y0) transferring three mutually compatible plasmids (Supplementary Fig. 5A, Supplementary Methods, Supplementary Eq. (16), Supplementary Table 4). Each plasmid was initiated in a single species, respectively (RP4, R6K, and R388, denoted 1, 2, and 3 in Fig. 3d, Supplementary Fig. 5A). These three plasmids were chosen in particular since they belong to distinct incompatibility groups (X, P, and W), and are distinguishable using antibiotic selection (Streptomycin (Strep), Kan, and Trimethoprim (Tm), respectively, Supplementary Table 3). Since all species express chromosomal CmR, we used selective plating to determine the plasmid fraction and flow cytometry to determine the species composition. In this scenario, although plasmids individually appear beneficial to their own host (α < 1), they exhibit a cost compared to another species/plasmid pair (e.g., compare BRP4 to RR388, Supplementary Fig. 5B). Based on our previous estimates, we predict persistence for all three plasmids in this community. Indeed, results demonstrate that each individual plasmid exhibited persistence throughout the duration of the experiment, for up to 2 weeks (Fig. 3e). In the absence of conjugation (R0, B0, and Y0 only), competition between the three species favors the fittest population (Y0), suppressing the growth of both R0 and B0 (Supplementary Fig. 5B).

Reversing conjugation-assisted persistence of resistance

Our results demonstrate that diverse conjugal plasmids are indeed transferred fast enough to enable plasmid persistence. According to the existence criterion (Eq. (1)), however, resistance reversal can be achieved by inhibiting conjugation, promoting the rate of plasmid loss, or both (Fig. 4a). The efficacy of this strategy depends on how much \({\eta _{\rm C}}\) exceeds \({\eta _{\rm Crit}}\). If \({\eta _{\rm C}}\) is only slightly greater than \({\eta _{\rm Crit}}\), inhibiting conjugation alone might be sufficient to reverse resistance. If inhibition alone is incomplete, however, promoting κ may act in synergy to destabilize the plasmid.

We first tested this inhibition strategy on the engineered conjugation system by using linoleic acid57 (Lin) to inhibit conjugation (Fig. 4b, left panel) and phenothiazine (Pheno) to enhance the plasmid segregation error58, 59 (Fig. 4b, right panel). Both compounds had been identified in literature for these specific properties. Importantly, at the concentrations we used, neither compound affected the bacterial growth rate (Supplementary Fig. 6A). Indeed, Lin alone was sufficient to destabilize a plasmid with low conjugation efficiency (Fig. 4c, plasmid K). For a plasmid with greater \({\eta _{\rm C}}\) (e.g., for plasmid #41) or conferred a benefit, Lin alone was insufficient, and the synergistic combination of Lin with Pheno was critical to reverse resistance (Fig. 4d). We note that Pheno alone did not affect the conjugation efficiency (Supplementary Fig. 6B).

Fig. 4 Reversing resistance due to conjugation-assisted persistence. a Combining inhibition of conjugation and promotion of plasmid loss to reverse resistance. This strategy is expected to increase \({\eta _{\rm Crit}}\) and decrease \({\eta _{\rm C}}\), potentially destabilizing the plasmid (Eq. (1)). b Evaluating conjugation inhibitor linoleic acid (Lin) and plasmid loss rate promoter phenothiazine (Pheno). Left: BK and R0 were grown overnight with or without 3.25 mM Lin to quantify conjugation efficiency (see Methods). Right: BK− was propagated daily in the presence of 50 μg/mL Kan, nothing, or 120 μM of Pheno. Kan was used as a control. Y-axis is the fraction of BK− without antibiotic normalized by that treated with Kan quantified via flow cytometry. Pheno significantly increased the rate of plasmid loss by ~four-fold (see Supplementary Fig. 6B, right panel). c, d Inhibition of RK and R41. R0 and RK or R41 were mixed in equal fractions and diluted 10,000× daily for 11 days. Y-axis is fraction of plasmid-carrying cells and x-axis is days. Green shading indicates the treatments from dark to light: control, Pheno, Lin, and combined. Both plasmids were successfully reversed; when Lin was sufficient alone, Pheno had minimal effect (K). If Lin alone was insufficient, Lin with Pheno synergistically destabilized the plasmid. e Combination treatment with Lin and Pheno suppressed or reversed resistance. The same strains and protocol were used as in Fig. 2d, except media was supplemented with 3.25 mM Lin and 120 μM Pheno fresh daily (see Methods). The plasmids used are (i) #168, (ii) #193, (iii) R388, (iv) C, (v) #41, (vi) RP4, (vii) K, (viii) PCU1, and (ix) R6K (see Supplementary Tables 1 and 3). All CFU measurements were done in replicates of four-to-six plates, and repeated at least twice for reproducibility. All flow measurements were propagated with at least eight well replicates and repeated at least twice for reproducibility. Error bars represent the standard deviation of the plate or well replicates Full size image

We found that Lin reduced the conjugation efficiency for most of the native plasmids by three-fold (Supplementary Fig. 6C) and even by 50-fold in one (see Supplementary Table 3 for all fold changes). Adjusting for this decrease in predicted \({\eta _{\rm Crit}}\), maintaining the same cost (Supplementary Fig. 6D), and assuming a four-fold increase in the Pheno-enhanced plasmid loss rate (Supplementary Fig. 6B, right), our criterion predicts that conjugation-assisted persistence would be significantly reduced for most plasmids (Supplementary Fig. 6E, Supplementary Table 3). Indeed, a combination of Lin and Pheno led to >99% elimination of plasmids where Δn < 0 (Fig. 4e, plasmids K, #41, #168, PCU1, Supplementary Fig. 6F for log-scale PCU1 as comparison to Supplementary Fig. 3E). If Δn is close to but slightly greater than 0, the plasmid still persisted but with a reduced infectivity (Fig. 4e plasmids C, #193). If Δn is sufficiently large (>>0), the plasmid was maintained (Fig. 4e plasmids RP4, R6K, R388). However, they were less dominant in comparison with the absence of Lin and Pheno (Fig. 2d), indicating the role of conjugation in their maintenance. That these three plasmids were more difficult to reverse is not surprising, since they carry a small burden or even a benefit, to R (Supplementary Fig. 3B).