Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Deletion of a mycobacterial divisome factor collapses single-cell phenotypic heterogeneity

Nature volume 546, pages 153–157 (2017)Cite this article

Subjects

Abstract

Microorganisms are often studied as populations but the behaviour of single, individual cells can have important consequences. For example, tuberculosis, caused by the bacterial pathogen Mycobacterium tuberculosis, requires months of antibiotic therapy even though the bulk of the bacterial population dies rapidly. Shorter courses lead to high rates of relapse because subpopulations of bacilli can survive despite being genetically identical to those that are easily killed1. In fact, mycobacteria create variability each time a cell divides, producing daughter cells with different sizes and growth rates2,3. The mechanism(s) that underlie this high-frequency variation and how variability relates to survival of the population are unknown. Here we show that mycobacteria actively create heterogeneity. Using a fluorescent reporter and a fluorescence-activated cell sorting (FACS)-based transposon screen, we find that deletion of lamA, a gene of previously unknown function, decreases heterogeneity in the population by decreasing asymmetric polar growth. LamA has no known homologues in other organisms, but is highly conserved across mycobacterial species. We find that LamA is a member of the mycobacterial division complex (the ‘divisome’). It inhibits growth at nascent new poles, creating asymmetry in polar growth. The kinetics of killing individual cells that lack lamA are more uniform and more rapid with rifampicin and drugs that target the cell wall. Our results show that mycobacteria encode a non-conserved protein that controls the pattern of cell growth, resulting in a population that is both heterogeneous and better able to survive antibiotic pressure.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Heterogeneity is important for survival in rifampicin.
Figure 2: Screen for mutants altered in calcein distribution.
Figure 3: Validation of mutants from screen and identification of lamA.
Figure 4: LamA creates asymmetry in polar growth and is a member of the divisome.

Similar content being viewed by others

References

  1. Mitchison, D. A. Role of individual drugs in the chemotherapy of tuberculosis. Int. J. Tuberc. Lung Dis. 4, 796–806 (2000)

    CAS  PubMed  Google Scholar 

  2. Aldridge, B. B. et al. Asymmetry and aging of mycobacterial cells lead to variable growth and antibiotic susceptibility. Science 335, 100–104 (2012)

    Article  CAS  ADS  Google Scholar 

  3. Santi, I., Dhar, N., Bousbaine, D., Wakamoto, Y. & McKinney, J. D. Single-cell dynamics of the chromosome replication and cell division cycles in mycobacteria. Nat. Commun. 4, 2470 (2013)

    Article  ADS  Google Scholar 

  4. Chiu, V. C. & Haynes, D. H. High and low affinity Ca2+ binding to the sarcoplasmic reticulum: use of a high-affinity fluorescent calcium indicator. Biophys. J. 18, 3–22 (1977)

    Article  CAS  Google Scholar 

  5. Tiberghien, F. & Loor, F. Ranking of P-glycoprotein substrates and inhibitors by a calcein-AM fluorometry screening assay. Anticancer Drugs 7, 568–578 (1996)

    Article  CAS  Google Scholar 

  6. Legrand, O., Simonin, G., Perrot, J. Y., Zittoun, R. & Marie, J. P. Pgp and MRP activities using calcein-AM are prognostic factors in adult acute myeloid leukemia patients. Blood 91, 4480–4488 (1998)

    Article  CAS  Google Scholar 

  7. Rubin, E. J. et al. In vivo transposition of mariner-based elements in enteric bacteria and mycobacteria. Proc. Natl Acad. Sci. USA 96, 1645–1650 (1999)

    Article  CAS  ADS  Google Scholar 

  8. Niederweis, M. et al. Cloning of the mspA gene encoding a porin from Mycobacterium smegmatis. Mol. Microbiol. 33, 933–945 (1999)

    Article  CAS  Google Scholar 

  9. van Kessel, J. C. & Hatfull, G. F. Recombineering in Mycobacterium tuberculosis. Nat. Methods 4, 147–152 (2007)

    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  CAS  ADS  Google Scholar 

  11. 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 

  12. Marmiesse, M. et al. Macro-array and bioinformatic analyses reveal mycobacterial ‘core’ genes, variation in the ESAT-6 gene family and new phylogenetic markers for the Mycobacterium tuberculosis complex. Microbiology 150, 483–496 (2004)

    Article  CAS  Google Scholar 

  13. Kieser, K. J. & Rubin, E. J. How sisters grow apart: mycobacterial growth and division. Nat. Rev. Microbiol. 12, 550–562 (2014)

    Article  CAS  Google Scholar 

  14. Landgraf, D. et al. Segregation of molecules at cell division reveals native protein localization. Nat. Methods 9, 480 (2012)

    Article  CAS  Google Scholar 

  15. Kieser, K. J. et al. Phosphorylation of the peptidoglycan synthase PonA1 governs the rate of polar elongation in Mycobacteria. PLoS Pathog. 11, e1005010 (2015)

    Article  Google Scholar 

  16. Wakamoto, Y. et al. Dynamic persistence of antibiotic-stressed mycobacteria. Science 339, 91–95 (2013)

    Article  CAS  ADS  Google Scholar 

  17. Campos, M. et al. A constant size extension drives bacterial cell size homeostasis. Cell 159, 1433–1446 (2014)

    Article  CAS  Google Scholar 

  18. Taheri-Araghi, S. et al. Cell-size control and homeostasis in bacteria. Curr. Biol. 25, 385–391 (2015)

    Article  CAS  Google Scholar 

  19. Dar, R. D., Hosmane, N. N., Arkin, M. R., Siliciano, R. F. & Weinberger, L. S. Screening for noise in gene expression identifies drug synergies. Science 344, 1392–1396 (2014)

    Article  CAS  ADS  Google Scholar 

  20. Lewis, J. A. & Hatfull, G. F. Control of directionality in L5 integrase-mediated site-specific recombination. J. Mol. Biol. 326, 805–821 (2003)

    Article  CAS  Google Scholar 

  21. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012)

    Article  CAS  Google Scholar 

  22. Kieser, K. J. et al. Peptidoglycan synthesis in Mycobacterium tuberculosis is organized into networks with varying drug susceptibility. Proc. Natl Acad. Sci. 112, 13087 (2015)

    Article  CAS  ADS  Google Scholar 

Download references

Acknowledgements

We thank B. Glick and I. Fitzgerald (University of Chicago) for mCherry2B, a variant of mCherry with modified N and C termini, C. Boutte for use of FtsZ–mCherry2B and thoughtful discussion, M. Dragset for the M. smegmatis transposon library, C. Araneo and the MBIB flow cytometry facility for assistance with FACS, B. Aldridge, and S. Fortune for help with preliminary microscopy experiments, D. Rudner and T. Bernhardt for access to their microscope, E. Garner, C. Sassetti, and C. Boutte for critical reading of the manuscript, and members of the Rubin laboratory for helpful suggestions and support. E.H.R. holds a Career Award at the Scientific Interface from BWF. Research reported in this publication was supported by NIAID of the National Institutes of Health under award numbers F32AI104287 to E.H.R. and U19 AI107774 to E.J.R. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author information

Author notes

  1. E. Hesper Rego

    Present address: Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, Connecticut, USA

Authors and Affiliations

  1. Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

    E. Hesper Rego, E. Hesper Rego, Rebecca E. Audette, Rebecca E. Audette, Eric J. Rubin & Eric J. Rubin

Authors
  1. E. Hesper Rego
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rebecca E. Audette
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eric J. Rubin
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.H.R. and E.J.R. designed experiments, analysed data, and wrote the paper. E.H.R. performed all microscopy experiments, flow cytometry experiments, the transposon screen, and the immunoprecipitation experiments. R.E.A. generated the M. tuberculosis strains and performed all M. tuberculosis experiments. E.H.R. and R.E.A. performed the M. smegmatis time–kill curves. E.H.R. developed all analysis tools including the image analysis tools and the transposon screen analysis. E.J.R. supervised the project.

Corresponding authors

Correspondence to E. Hesper Rego or Eric J. Rubin.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks A. Raj, D. Russell and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Figure 1 Validation of screen and identification of mutant with decreased heterogeneity.

a, The average of three biological replicates of the eight gene-deletion strains is stained with calcein and analysed by flow cytometry. The median of the distribution of each strain (in units of wild-type s.d.) is compared to the value expected from the screen (slope = 1; R2 = 0.95; error bars represent s.d. assuming independence in the measurements of wild type and mutant). b, Survival of three biological replicates of each strain is measured by plating and counting survivors after 42 h in rifampicin treatment and compared to wild type (**P < 0.01, *P < 0.05, calculated by a two-sided Student’s t-test in comparison to wild type). c, The average fluorescence value of calcein-stained M. smegmatis cells measured by microscopy (n = 147 for wild type; n = 174 for ΔlamA).

Extended Data Figure 2 Loss of lamA results in a more homogenous response to drug.

a, Two examples of growing lineages of wild-type M. smegmatis cells exposed to 5 μg ml−1 rifampicin. Blue, growing cells; pink, non-growing cells. The thick dotted line indicates the time at which rifampicin was added. Thin dotted lines represent division events. Data for around 100 of cells were recorded. The behaviour of single cells was highly variable: many cells stopped growing immediately whereas others were able to grow and divide in a non-heritable manner. Bulk measurements were recorded in Fig. 3d as a way of quantifying the variability over many more cells (approximately 1,000,000 cells). b, The geometric mean of two biological replicates for wild-type and mutant M. smegmatis cells growing in sub-MIC concentrations of rifampicin. c, The mean survival of four biological replicates at 40 h in rifampicin at normalized drug concentrations: wild type = 10 μg ml−1; ΔlamA = 5 μg ml−1; ΔumaA = 5 μg ml−1.

Extended Data Figure 3 mmpS3 is different than the other mmpS genes.

a, A clustal omega alignment of all the mycobacterial membrane protein, small (mmpS) genes in the M. tuberculosis genomes. b, The percentage identity of the mmpS genes are compared to the others.

Extended Data Figure 4 Growth properties of ΔlamA cells compared to wild type.

a, Using a pulse–chase experiment as in Fig. 4a, the amount of growth at the new and old poles (total growth = new pole + old pole) over the duration of a cell cycle is measured for both wild-type (grey, n = 137) and ΔlamA (blue, n = 125) cells. Dark black lines represent medians. b, Slopes were fitted to the data displayed in Fig. 4a. A P value was calculated using a t-test to compare the slopes of wild type and ΔlamA. c, d, Growth of wild type (grey), ΔlamA (blue), and complement (yellow) as measured by elongation rate (c, n = 49 for wild type; n = 71 for ΔlamA) and cell cycle time (d, n = 49 for WT; n = 71 for ΔlamA). Dark black lines represent medians. e, f, Optical density (e) and colony-forming units (f) are measured over time for three biological replicates.

Extended Data Figure 5 LamA functions during the switch between division and elongation.

a, The maximum values of FtsZ–mCherry2B, eGFP–Wag31, and GFPmut3–LamA in the middle of the cell are measured as a function of cell cycle time in both wild-type and ΔlamA cells. Shaded areas represent standard deviations across 20 cells for each strain. b, An example of the time lapse images that were quantified for a. Each panel is 15 min apart. Arrows, point to the appearance of either FtsZ or LamA at the septum. Data was recorded around 100 cells, and 20 cells were used for fine quantification shown as shown in a. Scale bar, 5 μm. c, d, For each phase indicated in a, the data were fit to a line and the slope was calculated; the averaged data are shown in c, while slopes for individual cells are plotted in d.

Extended Data Figure 6 Overexpression of LamA inhibits growth at the new pole.

a, The birth length of a strain carrying a replicating plasmid with LamA under an inducible promoter, pTetOR (circles), is compared to wild type (squares, n = 142) in the presence (red) or absence (grey) of inducer (aTc) over many division cycles (n = 10 division 0; n = 20 division 1; n = 36 division 2; n = 60 division 3). b, Average birth length of 10 cells as a function of birth length before inducer is measured for individual cells overexpressing LamA. Oldest pole cells have poles that were established before inducer was added. Newest pole cells have poles that were the newest in the presence of inducer. (***P < 0.001 by a two-sided Student’s t-test with Welch’s correction.)

Extended Data Figure 7 Loss of lamA leads to more uniform drug response for a variety of antibiotics.

a, Single-cell intensity of fluorescent-vancomycin-stained cells (n = 151 wild type; n = 140 ΔlamA; n = 126 ΔlamA L5::lamA). Black lines represent fit of the data to a Guassian curve. Survival over time for wild-type M. smegmatis (grey), ΔlamA (blue), and the complemented strain (yellow) are measured using colony-forming units (n = 3 biological replicates). b, Rifampicin 20 μg ml−1; c, teicoplanin 100 μg ml−1; d, ceftrioxone 50 μg ml−1 with 5 μg ml−1 clavulanate; e, vancomycin 3 μg ml−1. (*P < 0.05 by a two-sided Student’s t-test in comparison to wild type, dotted line represents limit of detection.) f, Cell density of three biological replicates in the presence of a range of vancomycin concentrations compared to a no-drug control for two strains: wild-type M. smegmatis and ΔlamA. The solid line represents the fit of the data to a sigmoid function. s is the best-fit value for the slope.

Extended Data Figure 8 The variation in a lamA deletion population is similar to the variation seen in other rod-shaped bacteria.

a, The variation in length of cells at the time of division (mother cells) for a variety of rod-shaped bacteria. b, Length of 130 C. glutamicum cells before division. Black line represents the fit of the data to a Gaussian function.

Extended Data Figure 9 The addition of a copy of lamA onto the chromosome under the native promoter complements all phenotypes and restores heterogeneity.

Wild-type (grey), ΔlamA (blue), and complement (yellow). a, Ratio of daughter cells at the time of division (n = 71 sister cell pairs for wild type; n = 63 sister cell pairs for ΔlamA; n = 60 sister cell pairs for complement). b, c, The length of cells at the time of division (b; n = 71 cells for wild type; n = 63 cells for ΔlamA; n = 60 cells for complement) and birth (c; n = 142 cells for wild type; n = 126 cells for ΔlamA; n = 120 cells for complement). Using a pulse–chase experiment as in Fig. 4a and Extended Data Fig. 6a, growth at the poles is measured. d, e, The absolute values (d) and the ratio (e) of new pole growth to old pole growth. n = 137 cells for wild type; n = 125 cells for ΔlamA; n = 45 cells for complement. Dark black lines represent medians.

Extended Data Table 1 MICs of various strains
Full size table

Supplementary information

Supplementary Figure

This file contains the uncropped blot from Figure 4c. (PDF 17 kb)

Supplementary Data

This file contains Supplementary Tables 1-5. Supplementary Table 1 contains results of the calcein transposon screen outlined in Figure 2 (column 1= genomic coordinate; column 2 = the name of the locus in MSMEG numbers; column 3 = the number of cells observed based on the total number of reads and the number of sorted cells; 4 = mean the mean of the distribution in units of standard deviation; column 5 = the inter-quartile range of the distribution; column 6 = the Mann-Whitney U value in comparison to a calculated WT distribution). Supplementary Table 2 contains descriptions of strains used in this study. Supplementary Table 3 contains primers and constructs used to make gene deletions. Supplementary Table 4 contains primers used to make integrating and overexpression vectors. Supplementary Table 5 contains the top 50 proteins for which peptides were found in the immunoprecipitation of a strain expressing LamA-strep and zero peptides were found in the strain not expressing LamA-strep. (ZIP 937 kb)

Time-lapse of wild type Msm cells as calcein is continuously flowed through the microfluidic chamber

Time-lapse of wild type Msm cells as calcein is continuously flowed through the microfluidic chamber. (AVI 973 kb)

Time-lapse of wild type and ΔlamA Msm cells exposed to 5 μg/ml rifampicin. Rifampicin is added 3 hours into the video

Time-lapse of wild type and ΔlamA Msm cells exposed to 5 μg/ml rifampicin. Rifampicin is added 3 hours into the video. (AVI 2638 kb)

Time-lapse of ΔlamA cells as calcein is continuously flowed through the microfluidic chamber

Time-lapse of ΔlamA cells as calcein is continuously flowed through the microfluidic chamber. (AVI 141 kb)

Time-lapse of wild type Msm cells expressing FtsZ-mCherry2B

Time-lapse of wild type Msm cells expressing FtsZ-mCherry2B. (AVI 657 kb)

Time-lapse of ΔlamA cells expressing FtsZ-mCherry2B

Time-lapse of ΔlamA cells expressing FtsZ-mCherry2B. (AVI 484 kb)

Time-lapse of wild type Msm cells expressing eGFP-Wag31

Time-lapse of wild type Msm cells expressing eGFP-Wag31 (AVI 259 kb)

Time-lapse of ΔlamA Msm cells expressing eGFP-Wag31

Time-lapse of ΔlamA Msm cells expressing eGFP-Wag31. (AVI 389 kb)

Time-lapse of Msm cells expressing mGFPmut3-LamA and FtsZ-mCherry2B

Red arrows point to the appearance of FtsZ-mCherry2B, while yellow arrows point to the appearance and co-localization of mGFPmut3-LamA. (AVI 324 kb)

Cells carrying a multi-copy plasmid, encoding LamA under an inducible promoter are imaged by time-lapse

The inducer aTc is added at the indicated time and then remains for the remainder of the experiment. (AVI 449 kb)

Time-lapse of GFP expressing wild type and ΔlamA Msm cells exposed to 8 μg/ml vancomycin

Propidium iodide is added throughout the video as an indicator of cell lysis. Vancomycin is added 3 hours into the video. (AVI 3127 kb)

PowerPoint slides

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rego, E., Audette, R. & Rubin, E. Deletion of a mycobacterial divisome factor collapses single-cell phenotypic heterogeneity. Nature 546, 153–157 (2017). https://doi.org/10.1038/nature22361

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature22361

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Microbiology