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Horizontal gene transfer enables programmable gene stability in synthetic microbiota

Nature Chemical Biology volume 18, pages 1245–1252 (2022)Cite this article

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Abstract

The functions of many microbial communities exhibit remarkable stability despite fluctuations in the compositions of these communities. To date, a mechanistic understanding of this function–composition decoupling is lacking. Statistical mechanisms have been commonly hypothesized to explain such decoupling. Here, we proposed that dynamic mechanisms, mediated by horizontal gene transfer (HGT), also enable the independence of functions from the compositions of microbial communities. We combined theoretical analysis with numerical simulations to illustrate that HGT rates can determine the stability of gene abundance in microbial communities. We further validated these predictions using engineered microbial consortia of different complexities transferring one or more than a dozen clinically isolated plasmids, as well as through the reanalysis of data from the literature. Our results demonstrate a generalizable strategy to program the gene stability of microbial communities.

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Fig. 1: Stability of gene abundance mediated by static or dynamic redundancy.
Fig. 2: Theoretical analysis and numerical simulations suggest that HGT enables stabilization of gene abundance against composition fluctuations in two-species communities.
Fig. 3: Dynamic redundancy by HGT promoted the gene stability of two-strain communities transferring a single plasmid.
Fig. 4: HGT rate modulated the abundance stability of a single plasmid transferred in synthetic communities.
Fig. 5: Experiments and literature data confirmed the ability of HGT to stabilize plasmid and gene abundances against compositional variations in complex communities transferring multiple plasmids.

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Data availability

Experimental data generated for this manuscript are deposited at GitHub at https://github.com/youlab/GeneStability_NCB2022. Source data are provided with this paper.

Code availability

The simulation and data analysis codes used in this study are deposited at GitHub at https://github.com/youlab/GeneStability_NCB2022.

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Acknowledgements

We thank C. Tan, H. Qian and T. Hwa for thorough reading and comments on an earlier draft of the manuscript. This work is partially supported by the National Institutes of Health (grant Nos. R01AI125604 and R01EB031869 to L.Y.) and the National Science Foundation (grant No. MCB-1937259 to L.Y.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Author notes

  1. These authors contributed equally: Teng Wang, Andrea Weiss.

Authors and Affiliations

  1. Department of Biomedical Engineering, Duke University, Durham, NC, USA

    Teng Wang, Andrea Weiss, Feilun Wu, Lawrence A. David & Lingchong You

  2. Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA

    Ammara Aqeel, Lawrence A. David & Lingchong You

  3. Department of Chemical Engineering, University of Rochester, Rochester, NY, USA

    Allison J. Lopatkin

  4. Center for Genomic and Computational Biology, Duke University, Durham, NC, USA

    Lawrence A. David & Lingchong You

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Contributions

T.W. and A.W. conceived the research, designed and performed modeling and experiments, interpreted the results and wrote the manuscript. A.A. assisted with the construction of the barcoded Keio communities. F.W. assisted with the development of the model. A.J.L. and L.A.D. assisted with data interpretation and manuscript revisions. L.Y. conceived the research, assisted in research design and data interpretation and wrote the manuscript.

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Correspondence to Lingchong You.

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Extended data

Extended Data Fig. 1 Dynamic redundancy by HGT promoted the gene abundance stability of two-strain communities transferring a single plasmid.

a. The conjugation efficiency of R388 between MG1655 and Top10. Data are presented as mean values +/− standard deviations of three replicates. b. The growth curves of MG1655 and Top10 under different Strp concentrations. Data are presented as mean values +/− standard deviations of three replicates. c. The maximum growth rates of MG1655 and Top10 under different Strp concentrations. Data are presented as mean values +/− standard deviations of three replicates. d. The fitness burden of R388 in MG1655 or Top10. Data are presented as mean values +/− standard deviations of three replicates. e. Linoleic acid (LAC) inhibited the transfer of R388. The conjugations rates were normalized with the mean rate without LAC treatment. Data are presented as mean values +/− standard deviations of three replicates. f. Streptomycin did not impact the inhibition effects of linoleic acid on R388 transfer. The conjugations rates were normalized with the mean rate of the control group (0 mM LAC and 0 μg/mL Strp). Data are presented as mean values +/− standard deviations of three replicates. g. The temporal dynamics of Top10 relative abundances in the five communities during the experiment. Data are presented as mean values +/− standard deviations of three replicates. h. The relationship between community composition and R388 abundance at day 15. Data are presented as mean values of three replicates. i. The gene abundance stability ϕ increases with the plasmid transfer rate in a model of two species transferring a single plasmid. The x-axis is divided into multiple bins with widths of 0.015. Error bars represent mean +/− standard deviation of the ϕ values in each bin (n = 200 independent data points).

Source data

Extended Data Fig. 2 HGT promoted the gene stability of three-member communities transferring a single plasmid.

We assembled five communities transferring plasmid R388, each consisting of a P. aeruginosa strain (PA14) and two E. coli strains (MG1655 and Top10). The three members carried different antibiotic resistances (Cm, Tet and Strp, respectively), which allowed us to modulate the community composition by different antibiotic treatments. Specifically, the five communities (A to E) were treated with no antibiotic or with Cm, Tet, Strp or Strp+Tet, respectively. We further changed the plasmid transfer rate using LAC. a. The variations of the community compositions at the end of the experiment (day 15). The colored bars indicate different members, and the heights of the bars represent the relative abundances of the strains within the community. b. The dynamics of R388 abundance during the experiment. The results of three LAC concentrations and two dilution ratios were shown here. Data are presented as mean values +/− standard deviations of three replicates. c. The stability of plasmid abundance increased with the plasmid transfer rate. The results of day 5, 10 and 15 were shown in different line styles, while the two dilution ratios were represented by different marker styles.

Source data

Extended Data Fig. 3 A two-species model predicts the plasmid R388 dynamics in monocultures or cocultures of MG1655 and Top10.

Dynamic parameters, including the plasmid transfer rates, strain growth rates under different Strp doses, plasmid burdens and LAC inhibition effects were measured and used to parameterize the model. a. Dynamics of R388 abundances in MG1655 or Top10 cultured separately. For each strain, three LAC doses and two dilution ratios were tested. Experiment data are presented as mean values +/− standard deviations of three replicates. b. Dynamics of R388 abundances and strain compositions in cocultures of MG1655 or Top10. Five communities, treated by different concentrations of Strp, were modeled or experimentally measured. For each community, three LAC doses and two dilution ratios were tested. Experiment data are presented as mean values +/− standard deviations of three replicates. c. The degree of gene abundance stability in the MG1655-Top10 cocultures increased with the plasmid transfer rate. The results of day 5, 10 and 15 were shown in different line styles, while the two dilution ratios were represented by different marker styles.

Source data

Extended Data Fig. 4 Numerical simulations demonstrated the stabilization of gene abundance mediated by HGT in complex communities.

a. A schematic of random sampling from a pool of interacting species to multiple local communities. The filled circles of different colors represent different species. The sizes of the circles describe the species abundances. The black arrows stand for positive interspecies interactions while the red arrows represent negative interactions. b. The stability of plasmid abundance against species fluctuations is promoted by HGT. Each column represents a single community. The colored bars stand for different species (first panel) or plasmids carrying functional genes (second to fourth panel), and the heights of the bars represent the relative abundances of species or plasmids within the community. The 40 communities differ from each other in their species compositions, due to random sampling. With slow plasmid transfer, the plasmid abundances vary drastically across different communities, while with rapid transfer, the functional profile is stable against compositional changes. Three different HGT rates (0.002, 0.005 and 0.01, from left to right) are shown as examples here. c. The gene stability ϕ increases with the plasmid transfer rate. Here, 200 species pools are created, and each consists of 100 species transferring 20 plasmids. For each species pool, we randomize the parameters in the ranges of −0.05 < γ < 0.05, 0 < δ <0.2, 0.2 < μ < 0.6, 0 < κ < 0.05, −0.05 < λ < 0.05, and 0 < η < 0.1. 40 local communities were created for every species pool by random sampling. On average, each local population contained 50 species. Then we simulated the community dynamics until it reached a steady state and calculated the ϕ values of the plasmids as a function of their mean transfer rates. The x-axis is divided into multiple bins with widths of 0.005. Error bars represent mean +/− standard deviation of the ϕ values in each bin (n = 400 independent data points).

Extended Data Fig. 5 The stability of plasmid abundance increases with the plasmid transfer rate even before the system has reached equilibrium.

Here, 200 species pools were assembled in silico, and each was composed of 100 species transferring 20 plasmids. For each master community, we randomized the parameters in the ranges of −0.05 < γ < 0.05, 0 < δ <0.2, 0.2 < μ < 0.6, 0 < κ < 0.05, −0.05< λ < 0.05, and 0 < η < 0.1. 40 local communities were created for every master community by random sampling. On average, each local population contained 50 species. The ϕ values of the plasmids in the local communities were calculated by numerical simulations. The relationships between the stability ϕ and mean plasmid transfer rate at 4 different timepoints (t = 70, 100, 200 and 500 hours) were shown. Error bars represent mean +/− standard deviation of the ϕ values in each bin (n = 400 independent data points).

Extended Data Fig. 6 Construction of barcoded Keio strains and sequencing quantification.

a. The backbone of barcoded plasmids. Structure of plasmid vector includes the origin of replication (p15A), a selection marker (chloramphenicol), a fluorescence marker (mCherry) and the unique barcode sequence. b. Sequence of the synthesized DNA fragments. Sequence of the synthetic barcode when assembled into vector backbone includes the 15–20 base-pair overlap with the plasmid vector used for Gibson Assembly (orange), Illumina® adapter sequences (green) and two 18 base-pair barcode sequences (purple). c. Design of calibration experiments. Samples prepared at known concentrations were generated and underwent NGS library preparation, sequencing and data analysis pipelines. Images represent the layout of samples where each well contained a single barcoded strain. Strains were mixed together based on the indicated layout by column where darker shading indicates higher densities. Samples were prepared using a 2-fold dilution in each group. d. Overall calibration results. Normalized relative abundance of sequencing counts obtained for each barcode plotted versus the expected sample ratio shows a good correlation between expected and actual barcode abundances. Each data point represents a single barcoded Keio strain. e. Correction of NGS plasmid barcode reads. Results of correcting calibration samples using different data correction approaches. The measured relative abundance of NGS read counts for each plasmid barcode was plotted against the expected relative abundance of samples with no data correction (left), empirical correction (middle graph) by normalizing reads with equal ratio NGS sample, and numerical correction (right graph) using plasmid-specific correction coefficient, respectively. R-squared values suggest an improved correlation between expected and actual relative abundance when applying numerical data correction.

Source data

Extended Data Fig. 7 HGT stabilized gene abundances against compositional variations in complex communities.

a. Different Keio strains transferred plasmid p13 with different conjugation rates ((cells/ml)-1hr-1). Here, Top10 carrying p13 served as the donor and 72 Keio strains served as recipients. Data are presented as mean values +/− standard deviations of three replicates. b. The temporal dynamics of strain compositions of Keio communities transferring plasmid p13 during the experiment. The results of three linoleic acid (LAC) concentrations and two dilution ratios were shown. In each panel, the colored bars stand for different Keio strains, and the heights of the bars represent their relative abundances within the community. c. The 13 plasmids were transferred within the synthetic communities with different conjugation efficiencies. Here, Top10 strain carrying the each of the 13 plasmids served as the donors, and Keio strain 1 served as the recipient. Data are presented as mean values +/− standard deviations of three replicates.

Source data

Extended Data Fig. 8 The functional stability ϕ increases with the plasmid transfer rate even when different species express the genes at different levels.

xij (0 ≤ xij ≤ 1) describes the relative expression level of each copy of the j-th plasmid in the i-th species. The numerical simulations were performed following the same protocols as described in Extended Data Fig. 4c and Methods of the main text. Four different ranges of xij were considered, corresponding to different magnitudes of heterogeneity of gene expression levels. The x-axis is divided into multiple bins with widths of 0.005. Error bars represent mean +/− standard deviation of the ϕ values in each bin (n = 400 independent data points).

Supplementary information

Source data

Source Data Fig. 3 (download XLSX )

R388 abundances in two-strain communities.

Source Data Fig. 4 (download XLSX )

Population dynamics of Keio communities transferring a single plasmid.

Source Data Fig. 5 (download XLSX )

Population dynamics of Keio communities transferring 13 plasmids.

Source Data Extended Data Fig. 1 (download XLSX )

Kinetic parameters of two-strain communities.

Source Data Extended Data Fig. 2 (download XLSX )

Population dynamics of three-member communities transferring a single plasmid.

Source Data Extended Data Fig. 3 (download XLSX )

Plasmid dynamics in monocultures of MG1655 and Top10.

Source Data Extended Data Fig. 6 (download XLSX )

Calibration of sequencing results.

Source Data Extended Data Fig. 7 (download XLSX )

Plasmid transfer rates and composition dynamics of Keio communities transferring 13 plasmids.

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Wang, T., Weiss, A., Aqeel, A. et al. Horizontal gene transfer enables programmable gene stability in synthetic microbiota. Nat Chem Biol 18, 1245–1252 (2022). https://doi.org/10.1038/s41589-022-01114-3

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