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Salmonella persisters promote the spread of antibiotic resistance plasmids in the gut

Abstract

The emergence of antibiotic-resistant bacteria through mutations or the acquisition of genetic material such as resistance plasmids represents a major public health issue1,2. Persisters are subpopulations of bacteria that survive antibiotics by reversibly adapting their physiology3,4,5,6,7,8,9,10, and can promote the emergence of antibiotic-resistant mutants11. We investigated whether persisters can also promote the spread of resistance plasmids. In contrast to mutations, the transfer of resistance plasmids requires the co-occurrence of both a donor and a recipient bacterial strain. For our experiments, we chose the facultative intracellular entero-pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) and Escherichia coli, a common member of the microbiota12. S. Typhimurium forms persisters that survive antibiotic therapy in several host tissues. Here we show that tissue-associated S. Typhimurium persisters represent long-lived reservoirs of plasmid donors or recipients. The formation of reservoirs of S. Typhimurium persisters requires Salmonella pathogenicity island (SPI)-1 and/or SPI-2 in gut-associated tissues, or SPI-2 at systemic sites. The re-seeding of these persister bacteria into the gut lumen enables the co-occurrence of donors with gut-resident recipients, and thereby favours plasmid transfer between various strains of Enterobacteriaceae. We observe up to 99% transconjugants within two to three days of re-seeding. Mathematical modelling shows that rare re-seeding events may suffice for a high frequency of conjugation. Vaccination reduces the formation of reservoirs of persisters after oral infection with S. Typhimurium, as well as subsequent plasmid transfer. We conclude that—even without selection for plasmid-encoded resistance genes—small reservoirs of pathogen persisters can foster the spread of promiscuous resistance plasmids in the gut.

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Fig. 1: S. Typhimurium persisters associated with gut tissue are a reservoir for conjugative plasmids.
Fig. 2: Persisters at systemic sites are a reservoir for plasmid transfer in the gut.
Fig. 3: Plasmid transfer is initiated by rare re-seeding events from donors and can be prevented by vaccination.
Fig. 4: Tissue-associated persisters promote the transfer of resistance plasmids between different species of Enterobacteriaceae.

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Data availability

The genome and plasmid sequence of E. coli ESBL 15 have been deposited in GenBank under accession numbers CP041678–CP041681 (Biosample SAMN12275742). Numerical Source Data for all figures are provided with the paper. Source images are available upon request to the corresponding authors.

Code availability

Code for the stochastic simulation of plasmid-transfer dynamics and parameter estimation from the experimental data are provided with the paper. The R code follows the notation used in the Supplementary Information.

References

  1. Parisi, A. et al. Health outcomes from multidrug-resistant Salmonella infections in high-income countries: a systematic review and meta-analysis. Foodborne Pathog. Dis. 15, 428–436 (2018).

    Article  Google Scholar 

  2. Wright, G. D. The antibiotic resistome: the nexus of chemical and genetic diversity. Nat. Rev. Microbiol. 5, 175–186 (2007).

    Article  CAS  Google Scholar 

  3. Brauner, A., Fridman, O., Gefen, O. & Balaban, N. Q. Distinguishing between resistance, tolerance and persistence to antibiotic treatment. Nat. Rev. Microbiol. 14, 320–330 (2016).

    Article  CAS  Google Scholar 

  4. Fridman, O., Goldberg, A., Ronin, I., Shoresh, N. & Balaban, N. Q. Optimization of lag time underlies antibiotic tolerance in evolved bacterial populations. Nature 513, 418–421 (2014).

    Article  ADS  CAS  Google Scholar 

  5. Claudi, B. et al. Phenotypic variation of Salmonella in host tissues delays eradication by antimicrobial chemotherapy. Cell 158, 722–733 (2014).

    Article  CAS  Google Scholar 

  6. Helaine, S. et al. Internalization of Salmonella by macrophages induces formation of nonreplicating persisters. Science 343, 204–208 (2014).

    Article  ADS  CAS  Google Scholar 

  7. Kaiser, P. et al. Cecum lymph node dendritic cells harbor slow-growing bacteria phenotypically tolerant to antibiotic treatment. PLoS Biol. 12, e1001793 (2014).

    Article  Google Scholar 

  8. Dolowschiak, T. et al. IFN-γ hinders recovery from mucosal inflammation during antibiotic therapy for Salmonella gut infection. Cell Host Microbe 20, 238–249 (2016).

    Article  CAS  Google Scholar 

  9. Balaban, N. Q. et al. Definitions and guidelines for research on antibiotic persistence. Nat. Rev. Microbiol. 17, 441–448 (2019).

    Article  CAS  Google Scholar 

  10. Balaban, N. Q., Merrin, J., Chait, R., Kowalik, L. & Leibler, S. Bacterial persistence as a phenotypic switch. Science 305, 1622–1625 (2004).

    Article  ADS  CAS  Google Scholar 

  11. Levin-Reisman, I. et al. Antibiotic tolerance facilitates the evolution of resistance. Science 355, 826–830 (2017).

    Article  ADS  CAS  Google Scholar 

  12. Wotzka, S. Y. et al. Microbiota stability in healthy individuals after single-dose lactulose challenge–a randomized controlled study. PLoS ONE 13, e0206214 (2018).

    Article  Google Scholar 

  13. Coque, T. M., Baquero, F. & Canton, R. Increasing prevalence of ESBL-producing Enterobacteriaceae in Europe. Eurosurveillance 13, 19044 (2008).

    Google Scholar 

  14. Crump, J. A., Sjölund-Karlsson, M., Gordon, M. A. & Parry, C. M. Epidemiology, clinical presentation, laboratory diagnosis, antimicrobial resistance, and antimicrobial management of invasive Salmonella infections. Clin. Microbiol. Rev. 28, 901–937 (2015).

    Article  CAS  Google Scholar 

  15. Wilcock, B. P., Armstrong, C. H. & Olander, H. J. The significance of the serotype in the clinical and pathological features of naturally occurring porcine salmonellosis. Can. J. Comp. Med. 40, 80–88 (1976).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Wood, R. L., Pospischil, A. & Rose, R. Distribution of persistent Salmonella typhimurium infection in internal organs of swine. Am. J. Vet. Res. 50, 1015–1021 (1989).

    CAS  PubMed  Google Scholar 

  17. San Román, B. et al. Relationship between Salmonella infection, shedding and serology in fattening pigs in low–moderate prevalence areas. Zoonoses Public Health 65, 481–489 (2018).

    Article  Google Scholar 

  18. Tenaillon, O., Skurnik, D., Picard, B. & Denamur, E. The population genetics of commensal Escherichia coli. Nat. Rev. Microbiol. 8, 207–217 (2010).

    Article  CAS  Google Scholar 

  19. Apperloo-Renkema, H. Z., Van der Waaij, B. D. & Van der Waaij, D. Determination of colonization resistance of the digestive tract by biotyping of Enterobacteriaceae. Epidemiol. Infect. 105, 355–361 (1990).

    Article  CAS  Google Scholar 

  20. Stecher, B. et al. Gut inflammation can boost horizontal gene transfer between pathogenic and commensal Enterobacteriaceae. Proc. Natl Acad. Sci. USA 109, 1269–1274 (2012).

    Article  ADS  CAS  Google Scholar 

  21. Diard, M. et al. Inflammation boosts bacteriophage transfer between Salmonella spp. Science 355, 1211–1215 (2017).

    Article  ADS  CAS  Google Scholar 

  22. Moor, K. et al. High-avidity IgA protects the intestine by enchaining growing bacteria. Nature 544, 498–502 (2017).

    Article  ADS  CAS  Google Scholar 

  23. Monack, D. M., Bouley, D. M. & Falkow, S. Salmonella typhimurium persists within macrophages in the mesenteric lymph nodes of chronically infected Nramp1 +/+ mice and can be reactivated by IFNγ neutralization. J. Exp. Med. 199, 231–241 (2004).

    Article  CAS  Google Scholar 

  24. Diard, M. et al. Antibiotic treatment selects for cooperative virulence of Salmonella Typhimurium. Curr. Biol. 24, 2000–2005 (2014).

    Article  CAS  Google Scholar 

  25. Sampei, G. et al. Complete genome sequence of the incompatibility group I1 plasmid R64. Plasmid 64, 92–103 (2010).

    Article  CAS  Google Scholar 

  26. Hensel, M. et al. Simultaneous identification of bacterial virulence genes by negative selection. Science 269, 400–403 (1995).

    Article  ADS  CAS  Google Scholar 

  27. Stapels, D. A. C. et al. Salmonella persisters undermine host immune defenses during antibiotic treatment. Science 362, 1156–1160 (2018).

    Article  ADS  CAS  Google Scholar 

  28. Moor, K. et al. Peracetic acid treatment generates potent inactivated oral vaccines from a broad range of culturable bacterial species. Front. Immunol. 7, 34 (2016).

    Article  Google Scholar 

  29. Fauvart, M., De Groote, V. N. & Michiels, J. Role of persister cells in chronic infections: clinical relevance and perspectives on anti-persister therapies. J. Med. Microbiol. 60, 699–709 (2011).

    Article  Google Scholar 

  30. Roberts, M. E. & Stewart, P. S. Modelling protection from antimicrobial agents in biofilms through the formation of persister cells. Microbiology 151, 75–80 (2005).

    Article  CAS  Google Scholar 

  31. Knodler, L. A. et al. Noncanonical inflammasome activation of caspase-4/caspase-11 mediates epithelial defenses against enteric bacterial pathogens. Cell Host Microbe 16, 249–256 (2014).

    Article  CAS  Google Scholar 

  32. Sellin, M. E. et al. Epithelium-intrinsic NAIP/NLRC4 inflammasome drives infected enterocyte expulsion to restrict Salmonella replication in the intestinal mucosa. Cell Host Microbe 16, 237–248 (2014).

    Article  CAS  Google Scholar 

  33. Defraine, V., Fauvart, M. & Michiels, J. Fighting bacterial persistence: current and emerging anti-persister strategies and therapeutics. Drug Resist. Updat. 38, 12–26 (2018).

    Article  Google Scholar 

  34. Grant, A. J. et al. Modelling within-host spatiotemporal dynamics of invasive bacterial disease. PLoS Biol. 6, e74 (2008).

    Article  Google Scholar 

  35. Datsenko, K. A. & Wanner, B. L. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc. Natl Acad. Sci. USA 97, 6640–6645 (2000).

    Article  ADS  CAS  Google Scholar 

  36. Sternberg, N. L. & Maurer, R. Bacteriophage-mediated generalized transduction in Escherichia coli and Salmonella typhimurium. Methods Enzymol. 204, 18–43 (1991).

    Article  CAS  Google Scholar 

  37. Stecher, B. et al. Chronic Salmonella enterica serovar Typhimurium-induced colitis and cholangitis in streptomycin-pretreated Nramp1 +/+ mice. Infect. Immun. 74, 5047–5057 (2006).

    Article  CAS  Google Scholar 

  38. Barthel, M. et al. Pretreatment of mice with streptomycin provides a Salmonella enterica serovar Typhimurium colitis model that allows analysis of both pathogen and host. Infect. Immun. 71, 2839–2858 (2003).

    Article  CAS  Google Scholar 

  39. Johansson, M. E. & Hansson, G. C. Preservation of mucus in histological sections, immunostaining of mucins in fixed tissue, and localization of bacteria with FISH. Methods Mol. Biol. 842, 229–235 (2012).

    Article  CAS  Google Scholar 

  40. Marjoram, P., Molitor, J., Plagnol, V. & Tavare, S. Markov chain Monte Carlo without likelihoods. Proc. Natl Acad. Sci. USA 100, 15324–15328 (2003).

    Article  ADS  CAS  Google Scholar 

  41. Zankari, E. et al. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 67, 2640–2644 (2012).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank the members of the Hardt, Slack, Bonhoeffer, Stadler and Ackermann labs for helpful discussion, and the staff at the RCHCI and EPIC animal facilities for their excellent support. This work has been funded, in part, by grants from the Swiss National Science Foundation (SNF; 310030B-173338), the Promedica Foundation, Chur and the Helmut Horten Foundation to W.-D.H., and from the SNF NFP 72 (407240-167121) to W.-D.H., S.B. and A.E. M.D. is funded by an SNF professorship grant (PP00PP_176954), E.B. by a Boehringer Ingelheim Fonds PhD fellowship, and M.E.S. and S.A.F. (in part) by the Swedish Research Council (2015-00635, 2018-02223). R.R.R. is funded by SNF grant number 31003A_179170. E.S. is supported by grant GRS 073/17 from the ‘Microbials’ programme of the Gebert Rüf Foundation and the SNF Bridge Discover Grant 20B2-1 180953.

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Authors and Affiliations

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Contributions

E.B. (Figs. 1, 2, 3a, b, e, f, 4, Extended Data Figs. 1–3, 4a–c, e, f, 5–9), S.A.F. (Fig. 1e, Extended Data Fig. 4a–d), A.H. (Fig. 2, Extended Data Figs. 5, 6e, f, 9e), M.F. (Extended Data Fig. 4e–h) and E.S. (Fig. 3e, f, Extended Data Fig. 7b) performed the experiments shown in the indicated figures. J.S.H., S.B. and R.R.R. (Fig. 3c, d, Extended Data Figs. 1b, 6g, 10) performed mathematical modelling shown in the indicated figures. A.E. (Extended Data Fig. 1b) provided E. coli strain Z2115. E.B., M.D. and W.-D.H. designed the experiments. S.A.F., M.F. and M.E.S. designed the microscopy-based experiments and analysis. E.B., M.D. and W.-D.H. conceived the project and wrote the manuscript. All authors read, commented and approved this manuscript.

Corresponding authors

Correspondence to Médéric Diard or Wolf-Dietrich Hardt.

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Peer review information Nature thanks Sophie Helaine and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Fig. 1 Emergence and spread of antibiotic resistance in bacteria using P2 as a model for conjugation.

a, Antibiotic resistance in bacteria can emerge through mutation, or be acquired via horizontal gene transfer. Plasmid transfer is an important driver of the spread of antibiotic resistance. Tolerance increases the abundance of bacteria that survive antibiotic exposure, allowing for a higher probability of the emergence of mutations that lead to resistance11. We hypothesize that antibiotic resistance can also spread through the formation of reservoirs of persisters that contain plasmids; here, we hypothesize that the gut mucosa of the host can serve as a reservoir for persisters. The formation of long-term reservoirs, followed by re-seeding of bacteria from this reservoir into a niche occupied by other bacteria (for example, the gut lumen occupied by the microbiota following antibiotic therapy) increases the chance that two different strains interact with each other, leading to plasmid transfer (that is, increased strain co-occurrence). The representation in the bottom right panel is an example of donor persisters boosting co-occurrence. Note that tissue-associated recipient persisters may also increase co-occurrence. b, P2 shares homology with resistance plasmids. An alignment is shown between S. Typhimurium SL1344 P2 (GenBank sequence identifier HE654725.1), S. Typhimurium plasmid R64 (GenBank sequence identifier AP005147.1), and pESBL15 of E. coli Z2115 (strain isolated from a rectal swab of a patient at the University Hospital Basel) using the Artemis comparison tool (https://www.sanger.ac.uk/science/tools/artemis-comparison-tool-act). Red fill indicates high sequence identity (>85% sequence identity), blue fill indicates inversions and no fill indicates no sequence identity. For each plasmid, open reading frames (in each of the six translational frames) are shown by white regions (detected by the Artemis comparison tool). Antibiotic resistances (for example, streptomycin and tetracycline resistances on R64 and CTX-M-1 on pESBL15) are labelled, shown by light-blue directed rectangles (found by a Basic Local Alignment Search Tool (NCBI) search against the ResFinder antibiotic-resistance-gene database41). In P2, the locus for insertion of the chloramphenicol-resistance cassette and neutral sequence tags is shown. For each alignment, the percentage of the sequence that aligns to P2 is shown, as well as the average sequence similarity for these regions. c, Model strains for addressing evolution by conjugation in S. Typhimurium. SL1344 contains P2cat (chloramphenicol-resistance cassette (cat) that allows the enumeration of plasmid-bearing strains by selective plating) that can be conjugated to 14028S (kanamycin-resistance cassette (aphT) used for selective plating) to form a transconjugant (CmR and KanR). Transconjugants can then transfer P2cat to additional recipients. d, P2cat transfer kinetics in vitro. P2cat transfer is dependent on the density of donors and recipients. Donor and recipient strains were inoculated into LB (n = 2, 1 experiment) at a 1:1 ratio and selective plating was performed every hour. CFUs per millilitre are reported for each population (donors in blue, recipients in green and transconjugants in red). Solid lines connect medians. The dotted line indicates the detection limit by selective plating.

Source data

Extended Data Fig. 2 Antibiotic-resistance profile of key strains.

Antibiotic susceptibility testing was performed in LB in 96-well plates. Six strains (indicated on the figure axes) were tested against seven antibiotics, grown at 37 °C at 120 r.p.m. for 16 h, at which point the OD600 nm was measured. For each antibiotic, the highest concentration used was based on the working concentration in this study. For example, the concentration of antibiotic used for selective plating in the case of streptomycin, kanamycin, ampicillin and chloramphenicol (the highest concentration of chloramphenicol was fivefold-higher than the concentration used for selective plating, because this was already close to the minimum inhibitory concentration), or the concentration of antibiotic used for the gentamicin protection assay. Importantly, a very low minimum inhibitory concentration was observed for antibiotics used in vivo to enrich for persisters (that is, ciprofloxacin and ceftriaxone). The mean of three experiments is presented on a blue–white colour gradient, in which blue indicates a large amount of bacterial growth. This is calculated by subtracting the OD600 nm measured for each sample well from the background generated by the medium.

Source data

Extended Data Fig. 3 Controls for conjugation after antibiotic treatment in the oral infection model.

ac, Faecal bacterial-population sizes and inflammatory status of mice in Fig. 1c, d (comparison of invasive versus non-invasive donors in the oral model). Faecal loads of donors (blue, SmR and CmR), recipients (green, KanR), and transconjugants (red, CmR and KanR) were determined by selective plating on MacConkey agar. Black dotted line indicates detection limits for donors and transconjugants. Green dotted line indicates detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. Blue lines connect medians of donor populations; red lines connect medians of transconjugant populations. a, Mice infected with invasive S. Typhimurium donors (solid circles; n = 15 singly housed mice from 5 independent experiments). b, Mice infected with non-invasive S. Typhimurium donors (open circles; n = 6 singly housed mice from 2 independent experiments). c, Inflammatory status was determined by lipocalin-2 ELISA. Statistics were performed using a two-tailed Mann–Whitney U-test. NS, not significant (P ≥ 0.05), ****P < 0.0001, comparing mice infected with an invasive donor (solid black circles; n = 15 singly housed mice from 5 independent experiments) to mice infected with a non-invasive donor (open black circles; n = 6 singly housed mice from 2 independent experiments) at each time point. Medians are shown (solid red line for invasive donors; dotted red line for non-invasive donors). Dotted line indicates the detection limit. de, Carrying P2cat does not lead to a measurable fitness cost or benefit. d, A ‘locked’ transconjugant (14028S P2aphT ΔoriT (KanR and AmpR), in which conjugation is blocked by removing the origin of transfer) was competed against a recipient (14028S cat (CmR and AmpR)). e, To ensure that removing the origin of transfer did not affect fitness, the locked transconjugant was competed against a transconjugant with a normal P2cat plasmid (that is, mobile transconjugant) (14028S P2cat (CmR and AmpR)). In d, e, both strains were introduced at a 1:1 ratio (total inoculum size about 5 × 107 CFU per os) and faeces were monitored daily by selective plating (n = 6 singly housed mice from 2 independent experiments for both experiments). The competitive index is calculated by dividing the population size of one competitor by the other. Lines indicate medians. The dotted line indicates no competitive advantage for either strain. This is consistent with previously published data20. These data indicate that it is the plasmid-encoded conjugation efficiency (not the effects of the plasmid on host bacterial fitness) that drives the rise of transconjugants (Fig. 1c). f, g, Plasmid transfer in the oral model does not require an invasive recipient. Invasive donors (SL1344 P2cat (SmR and CmR)) were orally infected into pre-treated mice. After ciprofloxacin treatment, a non-invasive mutant of S. Typhimurium 14028S was used as a recipient (non-invasive 14028S aphT (KanR and AmpR)). n = 5 mice. f, Selective plating determined faecal loads of donors (blue, SmR and CmR), recipients (green, KanR), and transconjugants (red, CmR and KanR). Black dotted line indicates the detection limit for donors and transconjugants. Green dotted line indicates the detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. Blue lines connect medians of donor populations; red lines connect medians of transconjugant populations. g, Donor populations enumerated after a gentamicin protection assay on caecal tissue of mice shown in f. Median indicated by solid line. Dotted line indicates the detection limit. h, i, Conjugation is required for plasmid transfer after antibiotic treatment. Mice were infected with invasive S. Typhimurium that lacks the origin of transfer in P2cat (SL1344 P2cat ΔoriT (SmR and CmR)) as a donor, and 14028S aphT (KanR and AmpR) as a recipient, after antibiotic treatment. n = 5 mice. h, Selective plating determined the faecal loads of donors (blue, SmR and CmR), recipients (green, KanR) and transconjugants (red, CmR and KanR). Black dotted line indicates the detection limit for donors and transconjugants. Green dotted line indicates detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. Blue lines connect medians of donor populations; red lines connect medians of transconjugant populations. i, Donor populations enumerated after a gentamicin protection assay on caecal tissue of mice shown in h. Median indicated by solid line. Dotted line indicates the detection limit.

Source data

Extended Data Fig. 4 Quantification and localization of S. Typhimurium in the host mucosa after antibiotic treatments in the oral model.

ad, Mice were orally infected with either an invasive (SL1344 P2cat) (blue solid circles, n = 7 mice) or non-invasive (non-invasive SL1344 P2cat, TTSS-1 negative) (blue open circles, n = 7 mice) donor and treated with antibiotics. Mice were euthanized at day 8 after infection (at which point recipients were normally added), and organs were analysed. Dotted lines indicate the detection limits. a, Faecal populations were monitored daily by selective plating on MacConkey agar. Blue lines connect medians. b, Organ loads were determined by selective plating. c, Population size of donors in the caecal mucosa determined by selective plating after a gentamicin protection assay, or microscopy of tissue sections (same mice for each quantification method). Each data point is the average of 12 sections (10-μm thick). b, c, Statistics were performed using a two-tailed Mann–Whitney U-test. NS, not significant (P ≥ 0.05), *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, comparing mice infected with invasive or non-invasive donors for each organ. d, Localization of S. Typhimurium detected in the caecal tissue by microscopy, reported as a percentage of bacteria detected in c in either the lamina propria (l.p.) or epithelium (ep.). Bar indicates the median from five mice. e–h, Analysis of reservoirs of persisters in Carnoy-fixed caecal tissue sections. Mice were orally infected with an invasive (SL1344 P2cat, n = 5 mice) donor and treated with antibiotics. Mice were euthanized at day 8 after infection (at which point recipients are normally added) and organs were analysed. Dotted lines indicate the detection limits. e, Faecal populations were monitored daily by selective plating on MacConkey agar. Blue lines connect medians. f, Organ loads were determined by selective plating. Line indicates median. g, A Carnoy fixation was performed on caeca of mice to preserve the mucus structure. Ten-micrometre sections were stained to visualize S. Typhimurium (yellow, anti-LPS O5), actin (green, phalloidin–FITC), the mucus (red, wheat germ agglutinin AF647 conjugate) and nuclei (blue, DAPI). Mu., mucus. Scale bars, 20 μm. White arrows highlight S. Typhimurium (magnified in inset). Representative images shown from two independent experiments. h, Localization of S. Typhimurium detected in the caecal tissue by microscopy, reported as a percentage of bacteria detected each section (12 sections per mouse caecum) in the lamina propria, epithelium, mucus or lumen. Bar indicates the median from five mice.

Source data

Extended Data Fig. 5 Determination of reservoirs of tissue-associated persisters after intravenous infection, and subsequent plasmid transfer.

a, An equal mix of five SL1344 P2cat tag strains (SmR and CmR) were intravenously infected into mice (103 CFU). Treatments were as described in Fig. 2b (grey circles, 3 intraperitoneal doses of ceftriaxone; n = 8 singly housed mice from 2 independent experiments) or mice were left untreated (black circles; n = 8 singly housed mice from 2 independent experiments). Mice were euthanized on day 5 of the experiment (after the final dose of ceftriaxone was given). The tissue-associated populations in organs were enumerated by selective plating. Detection limit by selective plating is shown as a dotted line. Lines indicate median. b, c, Faecal bacterial population sizes of mice in Fig. 2d, e (comparison of wild-type and SPI-2-negative donors in the intravenous model). Faecal loads of donors (blue, SmR and CmR), recipients (green, KanR) and transconjugants (red, CmR and KanR) were determined by selective plating on MacConkey agar. Black dotted line indicates the detection limits for donors and transconjugants. Green dotted line indicates the detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. Blue lines connect medians of donor populations; red lines connect medians of transconjugant populations. b, Mice infected with wild-type S. Typhimurium donors (solid circles). c, Mice infected with SPI-2-deficient S. Typhimurium donors (open circles).

Source data

Extended Data Fig. 6 Experimental strategy for assessing population dynamics and tag frequencies.

Relates to Fig. 3a–d. ac, Tags introduced in the oral model. a, Tags coupled to a chloramphenicol-resistance cassette were introduced in P2. qPCR primers are specific to the chloramphenicol-resistance cassette and the specific tag (shown as one-sided arrows). Five tagged donors were pooled and orally infected as a 1:1:1:1:1 mix into mice. b, Relative plasmid-tag proportion detected by qPCR in the initial donor population, the donor population persisting in the caecal mucosa and the transconjugant population is shown for eight mice (three independent inocula). Dotted line indicates the detection limit. Each tag is given a unique colour. c, Scheme illustrating how tags were sorted and recoloured to yield the plots in Fig. 3a, b. Two mice are shown as examples. For the mucosa-associated donor populations (top) and for the faecal transconjugant populations (bottom), tags were sorted according to relative frequency. These tags were re-coloured (darker colour indicates higher frequency) to visualize the trends shown in Fig. 3a, b. These re-ordered tags were used as the experimental data for fitting the mathematical model. df, Experimental strategy to assess plasmid-transfer dynamics in the intravenous model. d, Tags coupled to a chloramphenicol-resistance cassette were introduced in P2. qPCR primers are specific to ydgA (a pseudogene flanking the specific tags) and the specific tag (shown as one-sided arrows). Five tagged donors were pooled and intravenously infected as a 1:1:1:1:1 mix into mice. e, Tags from the faecal transconjugant population at day 25 are sorted by abundance. Note that each abundance rank can consist of any tag (ranking and re-colouring scheme in c and raw tag data in f). n = 6 singly housed mice from 2 independent experiments. Dotted line indicates the conservative detection limit by qPCR. This detection limit refers to the most-conservative detection limit of any qPCR run (2.9 × 10−3; that is, tags can appear below this detection limit if the qPCR run yielded a lower detection limit). Line indicates the mean; error bars indicate the s.d. f, Relative plasmid-tag proportion detected by qPCR in the inoculum, the donor population persisting in the internal organs and the transconjugant population in the faeces is shown for six mice (three independent inocula; faeces and organ population data in Fig. 2d). Dotted line indicates the detection limit. Each tag is given a unique colour. g, Representation of key parameters in the mathematical model. Donors form a reservoir of persisters in host tissues. These cells can interact with other bacteria that colonize the gut lumen (that is, recipients), and transfer plasmids. Our mathematical model summarizes these plasmid-transfer dynamics using a few key parameters. Donors re-seed the gut lumen and transfer plasmids at rate η, transconjugants transfer plasmids to recipients (without a plasmid) at rate γ and the turn-over of each bacterial population is given by r − c, in which r is the birth rate and c is the clearance rate.

Source data

Extended Data Fig. 7 Faecal bacterial-population sizes and inflammatory status of mice (comparison of vaccinated versus naive mice in the oral model), and validation by mixtures of invasive and non-invasive donors.

Relates to Fig. 3e, f. a, b, Faecal loads of donors (blue, SmR and CmR), recipients (green, KanR), and transconjugants (red, CmR and KanR) were determined by selective plating on MacConkey agar. Barcode analysis of the recipient chromosome tags could not be performed because of technical issues with kanamycin enrichments and subsequent qPCR. Black dotted lines indicate the detection limits for donors and transconjugants. Green dotted line indicates the detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. Blue lines connect medians of donor populations; red lines connect medians of transconjugant populations. a, Naive mice infected with invasive S. Typhimurium donors (solid circles). b, Vaccinated mice infected with invasive S. Typhimurium donors (open circles with light-grey fill). c, Inflammatory status to determine the success of vaccination was determined by lipocalin-2 ELISA. Statistics were performed using a two-tailed Mann–Whitney U-test. NS, not significant (P ≥ 0.05), *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, comparing naive mice (black circles, n = 9 singly housed mice from 3 independent experiments) to vaccinated mice (open circles, n = 14 singly housed mice from 4 independent experiments) at each time point. Medians are shown (solid red line for naive mice and dotted red line for vaccinated mice). Dotted line the indicates detection limit. dg, Experimentally reducing the population size of mucosa-associated persisters by mixing invasive and non-invasive donors reduces plasmid transfer in the oral model. Mice were orally infected with a mixture of invasive (SL1344 P2cat, SmR and CmR) and non-invasive (non-invasive SL1344 P2cat, SmR and CmR) donors at two ratios: 1:10 (n = 6 singly housed mice) or 1:500 (n = 5 singly housed mice). In both cases, an excess of non-invasive donors was used to experimentally reduce the number of cells that can establish a reservoir of persisters in the intestinal mucosa (two independent experiments). S. Typhimurium 14028S aphT (KanR and AmpR) was used as a recipient after antibiotic treatment. d, Donor populations enumerated after a gentamicin protection assay on caecal tissue of mice infected with a 1:10 ratio (blue circles with dark grey fill; line indicates median) or 1:500 ratio (blue circles with light grey fill; line indicates median) of invasive to non-invasive donors. Statistics were performed using a two-tailed Mann–Whitney U-test **P < 0.01. e, Proportion of transconjugants (transconjugant population size divided by the sum of recipients and transconjugants) in the faeces is shown for each day, for mice infected with a 1:10 ratio (black circles with dark grey fill, grey bars indicate median) or a 1:500 ratio (black circles with light grey fill, light grey bars indicate median) of invasive to non-invasive donors. f, g, Faecal loads of donors (blue, SmR and CmR), recipients (green, KanR) and transconjugants (red, CmR and KanR) were determined by selective plating on MacConkey agar. f, Mice infected with a 1:10 ratio of invasive to non-invasive donors. g, Mice infected with a 1:500 ratio of invasive to non-invasive donors. In dg, the black dotted line indicates the detection limit for donors and transconjugants. Green dotted line indicates the detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit.

Source data

Extended Data Fig. 8 Faecal bacterial-population sizes of mice and the role of persistence and conjugation in host tissues if the recipient constitutes the reservoir.

Relates to Fig. 4. a, Faecal loads of donors (blue, SmR and CmR), recipients (green, AmpR), and transconjugants (red, CmR and AmpR) were determined by selective plating on MacConkey agar (same mice as in Fig. 4a, b; S. Typhimurium donor and E. coli recipient in the oral model). Black dotted line indicates the detection limit for donors and transconjugants. Green dotted line indicates the detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. Blue lines connect medians of donor populations; red lines connect medians of transconjugant populations. bd, Persistence in host tissues also promotes plasmid transfer if the recipient constitutes the reservoir. Pre-treated mice were orally infected with a S. Typhimurium recipient (SL1344 P2cured aphT, SmR and KanR) and treated with ciprofloxacin and ampicillin as in the oral model (Fig. 1b). On day 8, ampicillin was removed from the drinking water and an E. coli donor was introduced orally (E. coli 8178 P2cat, CmR and AmpR). b, Recipient populations enumerated after a gentamicin protection assay on caecal tissue (n = 5 singly housed mice from 2 independent experiments). Line indicates median. c, Proportion of transconjugants (transconjugant population size divided by sum of recipients and transconjugants) in the faeces is shown for each day. Grey bars indicate median. d, Faecal loads of recipients (green, SmR and KanR), donors (blue, CmR and AmpR), and transconjugants (red, SmR, CmR and KanR) were determined by selective plating on MacConkey agar. In bd, dotted lines indicate detection limits by selective plating. e, Faecal bacterial-populations sizes of mice in Fig. 4c, d (S. Typhimurium ESBL donor in the oral model). Faecal loads of donors (blue, SmR and AmpR), recipients (green, KanR) and transconjugants (red, KanR and AmpR) were determined by selective plating on MacConkey agar. Black dotted line indicates the detection limit for donors and transconjugants. Green dotted line indicates the detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. Blue lines connect medians of donor populations; red lines connect medians of transconjugant populations.

Source data

Extended Data Fig. 9 Exchanging ampicillin for kanamycin to limit gut-luminal growth of the donor does not affect the overall plasmid-transfer kinetics, and faecal bacteria-population sizes of intravenously infected mice.

Relates to Fig. 4. ad, Mice were orally infected with SL1344 P2cat (SmR and CmR) as a donor, and 14028S aphT (KanR and AmpR) as a recipient after antibiotic treatment. Mice were either treated with ampicillin in the drinking water until day 15 (normal protocol as in Fig. 1b), day 8 (when the recipient is added) or kanamycin until day 8. a, Donor populations enumerated after a gentamicin protection assay on caecal tissue of mice, in which ampicillin is maintained until day 15 (solid blue circles, n = 15 singly housed mice from 5 independent experiments; data taken from Fig. 1d), ampicillin is removed on day 8 (blue circles with pink fill, n = 3 singly housed mice from 1 experiment) or kanamycin is used until day 8 (blue circles with yellow fill, n = 3 singly housed mice from 1 experiment). Median indicated by solid line. b, Proportion of transconjugants (transconjugant population size divided by the sum of recipients and transconjugants) is shown for the groups receiving ampicillin treatment until day 15 (solid black circles, grey bars indicate median; n = 15 singly housed mice from 5 independent experiments; data taken from Fig. 1c), ampicillin treatment until day 8 (black circles with pink fill, pink bars indicate median; n = 3 singly housed mice from 1 experiment), and kanamycin treatment until day 8 (black circles with yellow fill, yellow bars indicate median; n = 3 singly housed mice from 1 experiment). c, d, Faecal loads of donors (blue, SmR and CmR), recipients (green, KanR) and transconjugants (red, CmR and KanR) were determined by selective plating on MacConkey agar. c, Mice treated until day 8 with ampicillin. d, Mice treated until day 8 with kanamycin. In ad, the black dotted line indicates the detection limit for donors and transconjugants. Green dotted line indicates the detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram of faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. e, Faecal bacterial-populations sizes of mice in Fig. 4e, f (S. Typhimurium donor and E. coli recipient in the intravenous model). Faecal loads of donors (blue, SmR and AmpR), recipients (green, KanR) and transconjugants (red, KanR and AmpR) were determined by selective plating on MacConkey agar. Black dotted line indicates the detection limit for donors and transconjugants. Green dotted line indicates the detection limit for recipients. The detection limit is higher for recipients once transconjugants reach a density of >108 CFU per gram faeces. Before this happens, recipients can be found below the detection limit; the black dotted line should then be considered as the detection limit. Blue lines connect medians of donor populations; red lines connect medians of transconjugant populations.

Source data

Extended Data Fig. 10 Increasing growth rate at carrying capacity to model inflammation, or running simulations on a finer parameter grid, does not affect overall simulation trends.

a, b, Simulations were run with identical parameters to Fig. 3c, d, but an increased birth and death rate at carrying capacity to simulate cases in which inflammation is present (Supplementary Information). The trends of the simulations remain the same as in Fig. 3c, d. a, Likelihood of the model as a function of the donor re-seeding (including donor-to-recipient conjugation) rate, and the rate of transconjugant-to-recipient plasmid transfer. All other parameter values are given in the Supplementary Information. The most-likely set of parameters is shown in red (η = 1 × 10−9 events per recipient per day; γ = 3.16 × 10−8 events per recipient per CFU per gram of faeces per day). b, The fraction of simulations with plasmid re-seeding (defined as a final transconjugant population size above 5 × 108 CFU per gram of faeces) is shown as a function of η. Here, γ is fixed at its most-likely value of 3.16 × 10−8 events per recipient per CFU per gram of faeces per day. The black vertical dotted line at η = 1 × 10−9 events per recipient per day indicates the estimated most-likely value from a. The red vertical dotted line at η = 1 × 10–11 events per recipient per day indicates a hypothetical 100-fold decrease of η (shown by a red arrow) (as might be caused, for example, by vaccination). cf, Running simulations on a finer parameter grid does not affect the overall simulation trends. Supplementary Table 4 provides details of the differences between specific simulation results. c, d, Simulations were run on a grid of η = 10−12 to 10−6 and γ = 10−10 to 10−1 with 0.25-log increments, instead of the η = 10−12 to 10−1 and γ = 10−12 to 10−1 with 0.5-log increments used in Fig. 3c, d. e, f, Simulations were run with parameters identical to a, b, but on a grid of η = 10−12 to 10−6 and γ = 10−10 to 10−1 with 0.25-log increments, instead of η = 10−12 to 10−1 and γ = 10−12 to 10−1 with 0.5-log increments. c, e, Likelihood of the model as a function of the donor re-seeding (including donor-to-recipient conjugation) rate, and the rate of transconjugant-to-recipient plasmid transfer. All other parameter values are given in the Supplementary Information. The most-likely set of parameters is shown in red. d, f, The fraction of simulations with plasmid re-seeding (defined as a final transconjugant population size above 5 × 108 CFU per gram of faeces) is shown as a function of η. Here γ is fixed at its most likely value. The black vertical dotted line indicates the estimated most-likely value (from c or e). The red vertical dotted line indicates a hypothetical 100-fold decrease of η (shown by a red arrow) (as might be caused, for example, by vaccination).

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Supplementary Information

The PDF file "Supplementary Materials" contains Supplementary Tables 1–4 and Supplementary Discussion A–D. Supplementary Tables 1 and 2 indicate the strains, plasmids and primers used in this study. Supplementary Table 3 contains input parameters and priors used in the stochastic simulations, and Supplementary Table 4 contains parameter estimate for different simulations. Supplementary Discussions A–C provide additional context and relevance for the present study, and Supplementary Discussion D provides a detailed description of the mathematical model.

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Supplementary Data

This zip file contains R scripts and input data used for running simulations.

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Bakkeren, E., Huisman, J.S., Fattinger, S.A. et al. Salmonella persisters promote the spread of antibiotic resistance plasmids in the gut. Nature 573, 276–280 (2019). https://doi.org/10.1038/s41586-019-1521-8

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