1887

Abstract

Heterogeneity of cells within exponentially growing populations was addressed in a bacterium, the facultative methylotroph AM1. A transcriptional fusion between a well-characterized methanol-inducible promoter () and was used with flow cytometry to analyse the distribution of gene expression in populations grown on either succinate or methanol, correlated with forward scatter as a measure of cell size. These cell populations were found to consist of three major subpopulations defined by cells that were actively growing and dividing, newly divided, and non-dividing. Through the use of flow cytometry, it was demonstrated that a significant percentage of the total population did not respond to carbon shift. In addition, these experiments demonstrated that a small subset of the total population was significantly brighter than the rest of the population and dominated fluorimetry data. These results were corroborated with a continuous flow-through system and laser scanning microscopy, confirming that subpopulations, not discernible in the population average, dominate population response. These results demonstrate that the combination of flow cytometry and microscopic single-cell analysis can be effectively used to determine the dynamics of subpopulations in population response. In addition, they support the concept that physiological diversity in isogenic populations can poise some proportion of the population to respond appropriately to changing conditions.

Loading

Article metrics loading...

/content/journal/micro/10.1099/mic.0.025890-0
2009-06-01
2024-10-13
Loading full text...

Full text loading...

/deliver/fulltext/micro/155/6/2040.html?itemId=/content/journal/micro/10.1099/mic.0.025890-0&mimeType=html&fmt=ahah

References

  1. Acar M., Mettetal J. T., van Oudenaarden A. 2008; Stochastic switching as a survival strategy in fluctuating environments. Nat Genet 40:471–475
    [Google Scholar]
  2. Aertsen A., Michiels C. W. 2005; Diversify or die: generation of diversity in response to stress. Crit Rev Microbiol 31:69–78
    [Google Scholar]
  3. Albano C. R., Randers-Eichhorn L., Bentley W. E., Rao G. 1998; Green fluorescent protein as a real time quantitative reporter of heterologous protein production. Biotechnol Prog 14:351–354
    [Google Scholar]
  4. Andersen J. B., Sternberg C., Poulsen L. K., Bjorn S. P., Givskov M., Molin S. 1998; New unstable variants of green fluorescent protein for studies of transient gene expression in bacteria. Appl Environ Microbiol 64:2240–2246
    [Google Scholar]
  5. Anthony C. 1982 The Biochemistry of Methylotrophs London: Academic Press;
  6. Attwood M. M., Harder W. 1972; A rapid and specific enrichment procedure for Hyphomicrobium spp. Antonie Van Leeuwenhoek 38:369–377
    [Google Scholar]
  7. Balaban N. Q., Merrin J., Chait R., Kowalik L., Leibler S. 2004; Bacterial persistence as a phenotypic switch. Science 305:1622–1625
    [Google Scholar]
  8. Banerjee B., Balasubramanian S., Ananthakrishna G., Ramakrishnan T. V., Shivashankar G. V. 2004; Tracking operator state fluctuations in gene expression in single cells. Biophys J 86:3052–3059
    [Google Scholar]
  9. Bongaerts R. J., Hautefort I., Sidebotham J. M., Hinton J. C. 2002; Green fluorescent protein as a marker for conditional gene expression in bacterial cells. Methods Enzymol 358:43–66
    [Google Scholar]
  10. Booth I. R. 2002; Stress and the single cell: intrapopulation diversity is a mechanism to ensure survival upon exposure to stress. Int J Food Microbiol 78:19–30
    [Google Scholar]
  11. Elowitz M. B., Levine A. J., Siggia E. D., Swain P. S. 2002; Stochastic gene expression in a single cell. Science 297:1183–1186
    [Google Scholar]
  12. Kalyuzhnaya M. G., Lidstrom M. E. 2003; QscR, a LysR-type transcriptional regulator and CbbR homolog, is involved in regulation of the serine cycle genes in Methylobacterium extorquens AM1. J Bacteriol 185:1229–1235
    [Google Scholar]
  13. Kalyuzhnaya M. G., Lidstrom M. E., Chistoserdova L. 2008; Real-time detection of actively metabolizing microbes via redox sensing as applied to methylotroph populations in Lake Washington. ISME J 2:696–706
    [Google Scholar]
  14. Korotkova N., Chistoserdova L., Lidstrom M. E. 2002; Poly- β -hydroxybutyrate biosynthesis in the facultative methylotroph Methylobacterium extorquens AM1: identification and mutation ofgap11 , gap20 , and phaR . J Bacteriol 184:6174–6181
    [Google Scholar]
  15. Kuang Y., Biran I., Walt D. R. 2004; Simultaneously monitoring gene expression kinetics and genetic noise in single cells by optical well arrays. Anal Chem 76:6282–6286
    [Google Scholar]
  16. Kussell E., Leibler S. 2005; Phenotypic diversity, population growth, and information in fluctuating environments. Science 309:2075–2078
    [Google Scholar]
  17. Leveau J. H., Lindow S. E. 2001; Predictive and interpretive simulation of green fluorescent protein expression in reporter bacteria. J Bacteriol 183:6752–6762
    [Google Scholar]
  18. Lewis K. 2007; Persister cells, dormancy and infectious disease. Nat Rev Microbiol 5:48–56
    [Google Scholar]
  19. Lissemore J. L., Jankowski J. T., Thomas C. B., Mascotti D. P., deHaseth P. L. 2000; Green fluorescent protein as a quantitative reporter of relative promoter activity in E. coli . Biotechniques 28:82–89
    [Google Scholar]
  20. Marx C. J., Lidstrom M. E. 2001; Development of improved versatile broad-host-range vectors for use in methylotrophs and other Gram-negative bacteria. Microbiology 147:2065–2075
    [Google Scholar]
  21. Marx C. J., Lidstrom M. E. 2002; Broad-host-range cre-lox system for antibiotic marker recycling in gram-negative bacteria. Biotechniques 33:1062–1067
    [Google Scholar]
  22. Marx C. J., Lidstrom M. E. 2004; Development of an insertional expression vector system for Methylobacterium extorquens AM1 and generation of null mutants lacking mtdA and/or fch . Microbiology 150:9–19
    [Google Scholar]
  23. Marx C. J., Van Dien S. J., Lidstrom M. E. 2005; Flux analysis uncovers key role of functional redundancy in formaldehyde metabolism. PLoS Biol 3:e16
    [Google Scholar]
  24. Moyed H. S., Bertrand K. P. 1983; hipA , a newly recognized gene of Escherichia coli K-12 that affects frequency of persistence after inhibition of murein synthesis. J Bacteriol 155:768–775
    [Google Scholar]
  25. Pedraza J. M., van Oudenaarden A. 2005; Noise propagation in gene networks. Science 307:1965–1969
    [Google Scholar]
  26. Rosenfeld N., Young J. W., Alon U., Swain P. S., Elowitz M. B. 2005; Gene regulation at the single-cell level. Science 307:1962–1965
    [Google Scholar]
  27. Siegele D. A., Hu J. C. 1997; Gene expression from plasmids containing the araBAD promoter at subsaturating inducer concentrations represents mixed populations. Proc Natl Acad Sci U S A 94:8168–8172
    [Google Scholar]
  28. Strovas T. J., Sauter L. M., Guo X., Lidstrom M. E. 2007; Cell-to-cell heterogeneity in growth and gene expression in Methylobacterium extorquens AM1. J Bacteriol 189:7127–7133
    [Google Scholar]
  29. Van Dien S. J., Lidstrom M. E. 2002; Stoichiometric model for evaluating the metabolic capabilities of the facultative methylotroph Methylobacterium extorquens AM1, with application to reconstruction of C3 and C4 metabolism. Biotechnol Bioeng 78:296–312
    [Google Scholar]
  30. Van Dien S. J., Okubo Y., Hough M. T., Korotkova N., Taitano T., Lidstrom M. E. 2003; Reconstruction of C3 and C4 metabolism in Methylobacterium extorquens AM1 using transposon mutagenesis. Microbiology 149:601–609
    [Google Scholar]
  31. Vorholt J. A., Marx C. J., Lidstrom M. E., Thauer R. K. 2000; Novel formaldehyde-activating enzyme in Methylobacterium extorquens AM1 required for growth on methanol. J Bacteriol 182:6645–6650
    [Google Scholar]
  32. Zhang M., Lidstrom M. E. 2003; Promoters and transcripts for genes involved in methanol oxidation in Methylobacterium extorquens AM1. Microbiology 149:1033–1040
    [Google Scholar]
  33. Zhao X., Duong T., Huang C. C., Kain S. R., Li X. 1999; Comparison of enhanced green fluorescent protein and its destabilized form as transcription reporters. Methods Enzymol 302:32–38
    [Google Scholar]
/content/journal/micro/10.1099/mic.0.025890-0
Loading
/content/journal/micro/10.1099/mic.0.025890-0
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error