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.

  • Review Article
  • Published:

The biogeography of infection revisited

Nature Reviews Microbiology volume 20, pages 579–592 (2022)Cite this article

Subjects

Abstract

Many microbial communities, including those involved in chronic human infections, are patterned at the micron scale. In this Review, we summarize recent work that has defined the spatial arrangement of microorganisms in infection and begun to demonstrate how changes in spatial patterning correlate with disease. Advances in microscopy have refined our understanding of microbial micron-scale biogeography in samples from humans. These findings then serve as a benchmark for studying the role of spatial patterning in preclinical models, which provide experimental versatility to investigate the interplay between biogeography and pathogenesis. Experimentation using preclinical models has begun to show how spatial patterning influences the interactions between cells, their ability to coexist, their virulence and their recalcitrance to treatment. Future work to study the role of biogeography in infection and the functional biogeography of microorganisms will further refine our understanding of the interplay of spatial patterning, pathogen virulence and disease outcomes.

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

Fig. 1: Polymicrobial biogeography can determine the severity of disease and treatment outcomes.
Fig. 2: Microbiogeography of human-associated microbial communities is the benchmark for in vitro preclinical models.
Fig. 3: Preclinical in vitro model SCFM2 provides a platform to study biological implications of microbiogeography.

Similar content being viewed by others

References

  1. Hall-Stoodley, L., Costerton, J. W. & Stoodley, P. Bacterial biofilms: from the natural environment to infectious diseases. Nat. Rev. Microbiol. 2, 95–108 (2004).

    Article  CAS  PubMed  Google Scholar 

  2. Flemming, H. C. & Wuertz, S. Bacteria and archaea on Earth and their abundance in biofilms. Nat. Rev. Microbiol. 17, 247–260 (2019).

    Article  CAS  PubMed  Google Scholar 

  3. Azimi, S., Klementiev, A. D., Whiteley, M. & Diggle, S. P. Bacterial quorum sensing during infection. Annu. Rev. Microbiol. 74, 201–219 (2020).

    Article  CAS  PubMed  Google Scholar 

  4. Ibberson, C. B. & Whiteley, M. The social life of microbes in chronic infection. Curr. Opin. Microbiol. 53, 44–50 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Martiny, J. B. et al. Microbial biogeography: putting microorganisms on the map. Nat. Rev. Microbiol. 4, 102–112 (2006).

    Article  CAS  PubMed  Google Scholar 

  6. Nemergut, D. R. et al. Global patterns in the biogeography of bacterial taxa. Env. Microbiol. 13, 135–144 (2011).

    Article  Google Scholar 

  7. Whiteley, M., Lee, K. M. & Greenberg, E. P. Identification of genes controlled by quorum sensing in Pseudomonas aeruginosa. Proc. Natl Acad. Sci. USA 96, 13904–13909 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Giraudo, A. T., Mansilla, C., Chan, A., Raspanti, C. & Nagel, R. Studies on the expression of regulatory locus sae in Staphylococcus aureus. Curr. Microbiol. 46, 246–250 (2003).

    Article  CAS  PubMed  Google Scholar 

  9. Ibberson, C. B. et al. Co-infecting microorganisms dramatically alter pathogen gene essentiality during polymicrobial infection. Nat. Microbiol. 2, 17079 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Cornforth, D. M. et al. Pseudomonas aeruginosa transcriptome during human infection. Proc. Natl Acad. Sci. USA 115, E5125–E5134 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Stacy, A. et al. Bacterial fight-and-flight responses enhance virulence in a polymicrobial infection. Proc. Natl Acad. Sci. USA 111, 7819–7824 (2014). In this pivotal study, the authors show that precise spatial patterning impacts virulence and characterize the metabolic and genetic factors involved in this relationship.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kolenbrander, P. E., Egland, P. G., Diaz, P. I. & Palmer, R. J. Jr. Genome–genome interactions: bacterial communities in initial dental plaque. Trends Microbiol. 13, 11–15 (2005).

    Article  CAS  PubMed  Google Scholar 

  13. Whiteley, M., Diggle, S. P. & Greenberg, E. P. Progress in and promise of bacterial quorum sensing research. Nature 551, 313–320 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Bassler, B. L. How bacteria talk to each other: regulation of gene expression by quorum sensing. Curr. Opin. Microbiol. 2, 582–587 (1999).

    Article  CAS  PubMed  Google Scholar 

  15. Williams, P. et al. Quorum sensing and the population-dependent control of virulence. Phil. Trans. R. Soc. Lond. B 355, 667–680 (2000).

    Article  CAS  Google Scholar 

  16. Tegtmeyer, N., Wessler, S. & Backert, S. Role of the cag-pathogenicity island encoded type IV secretion system in Helicobacter pylori pathogenesis. FEBS J. 278, 1190–1202 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Zhou, Y. et al. Hcp family proteins secreted via the type VI secretion system coordinately regulate Escherichia coli K1 interaction with human brain microvascular endothelial cells. Infect. Immun. 80, 1243–1251 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Aubert, D. F. et al. A Burkholderia type VI effector deamidates Rho GTPases to activate the pyrin inflammasome and trigger inflammation. Cell Host Microbe 19, 664–674 (2016).

    Article  CAS  PubMed  Google Scholar 

  19. Shalom, G., Shaw, J. G. & Thomas, M. S. In vivo expression technology identifies a type VI secretion system locus in Burkholderia pseudomallei that is induced upon invasion of macrophages. Microbiology 153, 2689–2699 (2007).

    Article  CAS  PubMed  Google Scholar 

  20. Stacy, A., McNally, L., Darch, S. E., Brown, S. P. & Whiteley, M. The biogeography of polymicrobial infection. Nat. Rev. Microbiol. 14, 93–105 (2016). This review provides a primer on the factors that drive microbiogeography during infection, including attachment, the physiochemical environment, host factors and polymicrobial interactions.

    Article  CAS  PubMed  Google Scholar 

  21. Alhede, M. et al. Combination of microscopic techniques reveals a comprehensive visual impression of biofilm structure and composition. FEMS Immunol. Med. Microbiol. 65, 335–342 (2012).

    Article  CAS  PubMed  Google Scholar 

  22. Hughes, C. V., Kolenbrander, P. E., Andersen, R. N. & Moore, L. V. Coaggregation properties of human oral Veillonella spp.: relationship to colonization site and oral ecology. Appl. Env. Microbiol. 54, 1957–1963 (1988).

    Article  CAS  Google Scholar 

  23. Werner, E. et al. Stratified growth in Pseudomonas aeruginosa biofilms. Appl. Env. Microbiol. 70, 6188–6196 (2004).

    Article  CAS  Google Scholar 

  24. Rogers, J. D., Palmer, R. J. Jr., Kolenbrander, P. E. & Scannapieco, F. A. Role of Streptococcus gordonii amylase-binding protein A in adhesion to hydroxyapatite, starch metabolism, and biofilm formation. Infect. Immun. 69, 7046–7056 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Angelichio, M. J., Spector, J., Waldor, M. K. & Camilli, A. Vibrio cholerae intestinal population dynamics in the suckling mouse model of infection. Infect. Immun. 67, 3733–3739 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Earle, K. A. et al. Quantitative imaging of gut microbiota spatial organization. Cell Host Microbe 18, 478–488 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. McAlester, G., O’Gara, F. & Morrissey, J. P. Signal-mediated interactions between Pseudomonas aeruginosa and Candida albicans. J. Med. Microbiol. 57, 563–569 (2008).

    Article  CAS  PubMed  Google Scholar 

  28. Reddinger, R. M., Luke-Marshall, N. R., Sauberan, S. L., Hakansson, A. P. & Campagnari, A. A. Streptococcus pneumoniae modulates Staphylococcus aureus biofilm dispersion and the transition from colonization to invasive disease. mBio 9, e02089-17 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Schulte, M. & Hensel, M. Models of intestinal infection by Salmonella enterica: introduction of a new neonate mouse model. F1000Res. 5, 1498 (2016).

    Article  Google Scholar 

  30. Frank, R. M. & Houver, G. in Dental Plaque (ed. McHugh, W. D.) 85–108 (S Livingstone, 1970).

  31. Kharazmi, A., Giwercman, B. & Hoiby, N. Robbins device in biofilm research. Methods Enzymol. 310, 207–215 (1999).

    Article  CAS  PubMed  Google Scholar 

  32. Marrie, T. J. & Costerton, J. W. Mode of growth of bacterial pathogens in chronic polymicrobial human osteomyelitis. J. Clin. Microbiol. 22, 924–933 (1985).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Gristina, A. G. & Costerton, J. W. Bacterial adherence to biomaterials and tissue. The significance of its role in clinical sepsis. J. Bone Jt. Surg. Am. 67, 264–273 (1985).

    Article  CAS  Google Scholar 

  34. DeLong, E. F., Taylor, L. T., Marsh, T. L. & Preston, C. M. Visualization and enumeration of marine planktonic archaea and bacteria by using polyribonucleotide probes and fluorescent in situ hybridization. Appl. Env. Microbiol. 65, 5554–5563 (1999).

    Article  CAS  Google Scholar 

  35. DeLong, E. F., Wickham, G. S. & Pace, N. R. Phylogenetic stains: ribosomal RNA-based probes for the identification of single cells. Science 243, 1360–1363 (1989).

    Article  CAS  PubMed  Google Scholar 

  36. Pernthaler, A., Pernthaler, J. & Amann, R. Fluorescence in situ hybridization and catalyzed reporter deposition for the identification of marine bacteria. Appl. Env. Microbiol. 68, 3094–3101 (2002).

    Article  CAS  Google Scholar 

  37. Stoecker, K., Dorninger, C., Daims, H. & Wagner, M. Double labeling of oligonucleotide probes for fluorescence in situ hybridization (DOPE-FISH) improves signal intensity and increases rRNA accessibility. Appl. Env. Microbiol. 76, 922–926 (2010).

    Article  CAS  Google Scholar 

  38. Valm, A. M. et al. Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging. Proc. Natl Acad. Sci. USA 108, 4152–4157 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Valm, A. M., Oldenbourg, R. & Borisy, G. G. Multiplexed spectral imaging of 120 different fluorescent labels. PLoS ONE 11, e0158495 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Cohen-Cymberknoh, M., Kerem, E., Ferkol, T. & Elizur, A. Airway inflammation in cystic fibrosis: molecular mechanisms and clinical implications. Thorax 68, 1157–1162 (2013).

    Article  PubMed  Google Scholar 

  41. Boucher, R. C. Airway surface dehydration in cystic fibrosis: pathogenesis and therapy. Annu. Rev. Med. 58, 157–170 (2007).

    Article  CAS  PubMed  Google Scholar 

  42. Bjarnsholt, T. et al. Pseudomonas aeruginosa biofilms in the respiratory tract of cystic fibrosis patients. Pediatr. Pulmonol. 44, 547–558 (2009). This study combines numerous techniques to visualize P. aeruginosa in the cystic fibrosis lung and in sputum, relative to immune cells.

    Article  PubMed  Google Scholar 

  43. Alhede, M. et al. The origin of extracellular DNA in bacterial biofilm infections in vivo. Pathog. Dis. 78, ftaa018 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Treweek, J. B. et al. Whole-body tissue stabilization and selective extractions via tissue–hydrogel hybrids for high-resolution intact circuit mapping and phenotyping. Nat. Protoc. 10, 1860–1896 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Yang, B. et al. Single-cell phenotyping within transparent intact tissue through whole-body clearing. Cell 158, 945–958 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. DePas, W. H. et al. Exposing the three-dimensional biogeography and metabolic states of pathogens in cystic fibrosis sputum via hydrogel embedding, clearing, and rRNA labeling. mBio 7, e00796-1 (2016). This study demonstrates that the use of tissue clearing and hybridization chain reaction probes allows for detecting physiological heterogeneity and spatial organization of multiple species in cystic fibrosis sputum.

    Article  Google Scholar 

  47. Rogers, G. B., Taylor, S. L., Hoffman, L. R. & Burr, L. D. The impact of CFTR modulator therapies on CF airway microbiology. J. Cyst. Fibros. 19, 359–364 (2020).

    Article  CAS  PubMed  Google Scholar 

  48. Zhao, G. et al. Delayed wound healing in diabetic (db/db) mice with Pseudomonas aeruginosa biofilm challenge: a model for the study of chronic wounds. Wound Repair Regen. 18, 467–477 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Bjarnsholt, T. et al. Why chronic wounds will not heal: a novel hypothesis. Wound Repair Regen. 16, 2–10 (2008).

    Article  PubMed  Google Scholar 

  50. Thuenauer, R. et al. The Pseudomonas aeruginosa lectin LecB causes integrin internalization and inhibits epithelial wound healing. mBio 11, e03260-19 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Brothers, K. M. et al. Putting on the brakes: bacterial impediment of wound healing. Sci. Rep. 5, 14003 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Sen, C. K. Human wounds and its burden: an updated compendium of estimates. Adv. Wound Care 8, 39–48 (2019).

    Article  Google Scholar 

  53. Kirketerp-Moller, K. et al. Distribution, organization, and ecology of bacteria in chronic wounds. J. Clin. Microbiol. 46, 2717–2722 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Fazli, M. et al. Nonrandom distribution of Pseudomonas aeruginosa and Staphylococcus aureus in chronic wounds. J. Clin. Microbiol. 47, 4084–4089 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Bay, L. et al. Bacterial aggregates establish at the edges of acute epidermal wounds. Adv. Wound Care 7, 105–113 (2018).

    Article  Google Scholar 

  56. MacLeod, A. S. & Mansbridge, J. N. The innate immune system in acute and chronic wounds. Adv. Wound Care 5, 65–78 (2016).

    Article  Google Scholar 

  57. Mark Welch, J. L., Ramirez-Puebla, S. T. & Borisy, G. G. Oral microbiome geography: micron-scale habitat and niche. Cell Host Microbe 28, 160–168 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Palmer, R. J. Jr. et al. Retrieval of biofilms from the oral cavity. Methods Enzymol. 337, 393–403 (2001).

    Article  PubMed  Google Scholar 

  59. Jones, S. J. A special relationship between spherical and filamentous microorganisms in mature human dental plaque. Arch. Oral. Biol. 17, 613–616 (1972).

    Article  CAS  PubMed  Google Scholar 

  60. Mark Welch, J. L., Rossetti, B. J., Rieken, C. W., Dewhirst, F. E. & Borisy, G. G. Biogeography of a human oral microbiome at the micron scale. Proc. Natl Acad. Sci. USA 113, E791–E800 (2016). In this article, the authors use CLASI-FISH imaging to visualize the complex microbial consortium in human dental plaque and propose a model of the plaque microbial community microbiogeography.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Wilbert, S. A., Mark Welch, J. L. & Borisy, G. G. Spatial ecology of the human tongue dorsum microbiome. Cell Rep. 30, 4003–4015 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Mark Welch, J. L., Dewhirst, F. E. & Borisy, G. G. Biogeography of the oral microbiome: the site-specialist hypothesis. Annu. Rev. Microbiol. 73, 335–358 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Carpenter, G. H. Salivary factors that maintain the normal oral commensal microflora. J. Dent. Res. 99, 644–649 (2020).

    Article  CAS  PubMed  Google Scholar 

  64. Kolenbrander, P. E. et al. Bacterial interactions and successions during plaque development. Periodontol 2000 42, 47–79 (2006).

    Article  PubMed  Google Scholar 

  65. Kim, D. et al. Spatial mapping of polymicrobial communities reveals a precise biogeography associated with human dental caries. Proc. Natl Acad. Sci. USA 117, 12375-12386 (2020). This study combines imaging of specimens from the human oral cavity, preclinical models and quantification of microbiogeography to link spatial patterning with disease.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Dufrene, Y. F. et al. Imaging modes of atomic force microscopy for application in molecular and cell biology. Nat. Nanotechnol. 12, 295–307 (2017).

    Article  CAS  PubMed  Google Scholar 

  67. Connell, J. L., Kim, J., Shear, J. B., Bard, A. J. & Whiteley, M. Real-time monitoring of quorum sensing in 3D-printed bacterial aggregates using scanning electrochemical microscopy. Proc. Natl Acad. Sci. USA 111, 18255–18260 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Klementiev, A. D., Jin, Z. & Whiteley, M. Micron scale spatial measurement of the O2 gradient surrounding a bacterial biofilm in real time. mBio 11, e02536-20 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Garg, N. et al. Three-dimensional microbiome and metabolome cartography of a diseased human lung. Cell Host Microbe 22, 705–716.e4 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Wagner, M. & Horn, H. Optical coherence tomography in biofilm research: a comprehensive review. Biotechnol. Bioeng. 114, 1386–1402 (2017).

    Article  CAS  PubMed  Google Scholar 

  71. Sussulini, A., Becker, J. S. & Becker, J. S. Laser ablation ICP-MS: application in biomedical research. Mass. Spectrom. Rev. 36, 47–57 (2017).

    Article  CAS  PubMed  Google Scholar 

  72. Zhang, P., Chen, Y. P., Qiu, J. H., Dai, Y. Z. & Feng, B. Imaging the microprocesses in biofilm matrices. Trends Biotechnol. 37, 214–226 (2019).

    Article  CAS  PubMed  Google Scholar 

  73. Caniglia, G. & Kranz, C. Scanning electrochemical microscopy and its potential for studying biofilms and antimicrobial coatings. Anal. Bioanal. Chem. 412, 6133–6148 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Skaar, E. P. Imaging infection across scales of size: from whole animals to single molecules. Annu. Rev. Microbiol. 75, 407–426 (2021). This review provides an overview of imaging methods for various infection models.

    Article  PubMed  Google Scholar 

  75. Kara, D., Luppens, S. B., van Marle, J., Özok, R. & ten Cate, J. M. Microstructural differences between single-species and dual-species biofilms of Streptococcus mutans and Veillonella parvula, before and after exposure to chlorhexidine. FEMS Microbiol. Lett. 271, 90–97 (2007).

    Article  CAS  PubMed  Google Scholar 

  76. Palmer, R. J. Jr., Diaz, P. I. & Kolenbrander, P. E. Rapid succession within the Veillonella population of a developing human oral biofilm in situ. J. Bacteriol. 188, 4117–4124 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Roberts, A. E., Kragh, K. N., Bjarnsholt, T. & Diggle, S. P. The limitations of in vitro experimentation in understanding biofilms and chronic infection. J. Mol. Biol. 427, 3646–3661 (2015).

    Article  CAS  PubMed  Google Scholar 

  78. Cornforth, D. M., Diggle, F. L., Melvin, J. A., Bomberger, J. M. & Whiteley, M. Quantitative framework for model evaluation in microbiology research using Pseudomonas aeruginosa and cystic fibrosis infection as a test case. mBio 11, e03042-19 (2020). In this study, the authors provide a framework for quantifying the accuracy of preclinical models, relative to human infections.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Ibberson, C. B. & Whiteley, M. The Staphylococcus aureus transcriptome during cystic fibrosis lung infection. mBio 10, e02774-19 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Kwiecinski, J. M. & Horswill, A. R. Staphylococcus aureus bloodstream infections: pathogenesis and regulatory mechanisms. Curr. Opin. Microbiol. 53, 51–60 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Paulsson, M., Su, Y. C., Ringwood, T., Udden, F. & Riesbeck, K. Pseudomonas aeruginosa uses multiple receptors for adherence to laminin during infection of the respiratory tract and skin wounds. Sci. Rep. 9, 18168 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Kavanaugh, J. S. et al. Identification of extracellular DNA-binding proteins in the biofilm matrix. mBio 10, e01137-19 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  83. Moscoso, M., Garcia, E. & Lopez, R. Biofilm formation by Streptococcus pneumoniae: role of choline, extracellular DNA, and capsular polysaccharide in microbial accretion. J. Bacteriol. 188, 7785–7795 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Moser, C. et al. Novel experimental Pseudomonas aeruginosa lung infection model mimicking long-term host–pathogen interactions in cystic fibrosis. APMIS 117, 95–107 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Darch, S. E. et al. Spatial determinants of quorum signaling in a Pseudomonas aeruginosa infection model. Proc. Natl Acad. Sci. USA 115, 4779–4784 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Palmer, K. L., Aye, L. M. & Whiteley, M. Nutritional cues control Pseudomonas aeruginosa multicellular behavior in cystic fibrosis sputum. J. Bacteriol. 189, 8079–8087 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Turner, K. H., Wessel, A. K., Palmer, G. C., Murray, J. L. & Whiteley, M. Essential genome of Pseudomonas aeruginosa in cystic fibrosis sputum. Proc. Natl Acad. Sci. USA 112, 4110–4115 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Darch, S. E. et al. Phage inhibit pathogen dissemination by targeting bacterial migrants in a chronic infection model. mBio 8, e00240-17 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  89. Barraza, J. P. & Whiteley, M. A Pseudomonas aeruginosa antimicrobial affects the biogeography but not fitness of Staphylococcus aureus during coculture. mBio 12, e00047-21 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Palmer, K. L., Mashburn, L. M., Singh, P. K. & Whiteley, M. Cystic fibrosis sputum supports growth and cues key aspects of Pseudomonas aeruginosa physiology. J. Bacteriol. 187, 5267–5277 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Azimi, S. et al. O-Specific antigen-dependent surface hydrophobicity mediates aggregate assembly type in Pseudomonas aeruginosa. mBio 12, e00860-21 (2021).

    Article  PubMed Central  Google Scholar 

  92. Sun, Y., Dowd, S. E., Smith, E., Rhoads, D. D. & Wolcott, R. D. In vitro multispecies Lubbock chronic wound biofilm model. Wound Repair Regen. 16, 805–813 (2008).

    Article  PubMed  Google Scholar 

  93. DeLeon, S. et al. Synergistic interactions of Pseudomonas aeruginosa and Staphylococcus aureus in an in vitro wound model. Infect. Immun. 82, 4718–4728 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Machan, Z. A., Taylor, G. W., Pitt, T. L., Cole, P. J. & Wilson, R. 2-Heptyl-4-hydroxyquinoline N-oxide, an antistaphylococcal agent produced by Pseudomonas aeruginosa. J. Antimicrob. Chemother. 30, 615–623 (1992).

    Article  CAS  PubMed  Google Scholar 

  95. Hoffman, L. R. et al. Selection for Staphylococcus aureus small-colony variants due to growth in the presence of Pseudomonas aeruginosa. Proc. Natl Acad. Sci. USA 103, 19890–19895 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Hotterbeekx, A., Kumar-Singh, S., Goossens, H. & Malhotra-Kumar, S. In vivo and in vitro interactions between Pseudomonas aeruginosa and Staphylococcus spp. Front. Cell Infect. Microbiol. 7, 106 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  97. Chattoraj, S. S. et al. Rhinovirus infection liberates planktonic bacteria from biofilm and increases chemokine responses in cystic fibrosis airway epithelial cells. Thorax 66, 333–339 (2011).

    Article  PubMed  Google Scholar 

  98. Hendricks, M. R. et al. Respiratory syncytial virus infection enhances Pseudomonas aeruginosa biofilm growth through dysregulation of nutritional immunity. Proc. Natl Acad. Sci. USA 113, 1642–1647 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Kiedrowski, M. R. et al. Staphylococcus aureus biofilm growth on cystic fibrosis airway epithelial cells is enhanced during respiratory syncytial virus coinfection. mSphere 3, e00341-18 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  100. Landi, A. et al. Pseudomonas aeruginosa lectin LecB impairs keratinocyte fitness by abrogating growth factor signalling. Life Sci. Alliance 2, e201900422 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  101. Jordana-Lluch, E. et al. A simple polymicrobial biofilm keratinocyte colonization model for exploring interactions between commensals, pathogens and antimicrobials. Front. Microbiol. 11, 291 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  102. Barrila, J. et al. Modeling host–pathogen interactions in the context of the microenvironment: three-dimensional cell culture comes of age. Infect. Immun. 86, e00282-18 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  103. Bartfeld, S. Modeling infectious diseases and host-microbe interactions in gastrointestinal organoids. Dev. Biol. 420, 262–270 (2016).

    Article  CAS  PubMed  Google Scholar 

  104. Sachs, N. et al. Long-term expanding human airway organoids for disease modeling. EMBO J. 38, e100300 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Edwards, S. & Kjellerup, B. V. Exploring the applications of invertebrate host–pathogen models for in vivo biofilm infections. FEMS Immunol. Med. Microbiol. 65, 205–214 (2012).

    Article  CAS  PubMed  Google Scholar 

  106. Wiles, T. J. et al. Host gut motility promotes competitive exclusion within a model intestinal microbiota. PLoS Biol. 14, e1002517 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  107. Bergeron, A. C. et al. Candida albicans and Pseudomonas aeruginosa interact to enhance virulence of mucosal infection in transparent zebrafish. Infect. Immun. 85, e00475-17 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  108. Mulcahy, H., Sibley, C. D., Surette, M. G. & Lewenza, S. Drosophila melanogaster as an animal model for the study of Pseudomonas aeruginosa biofilm infections in vivo. PLoS Pathog. 7, e1002299 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Limmer, S. et al. Pseudomonas aeruginosa RhlR is required to neutralize the cellular immune response in a Drosophila melanogaster oral infection model. Proc. Natl Acad. Sci. USA 108, 17378–17383 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Garsin, D. A. et al. A simple model host for identifying Gram-positive virulence factors. Proc. Natl Acad. Sci. USA 98, 10892–10897 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Begun, J. et al. Staphylococcal biofilm exopolysaccharide protects against Caenorhabditis elegans immune defenses. PLoS Pathog. 3, e57 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Rezzoagli, C., Granato, E. T. & Kummerli, R. In-vivo microscopy reveals the impact of Pseudomonas aeruginosa social interactions on host colonization. ISME J. 13, 2403–2414 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  113. Chua, S. L. et al. Dispersed cells represent a distinct stage in the transition from bacterial biofilm to planktonic lifestyles. Nat. Commun. 5, 4462 (2014).

    Article  CAS  PubMed  Google Scholar 

  114. Cassat, J. E. et al. Integrated molecular imaging reveals tissue heterogeneity driving host-pathogen interactions. Sci. Transl Med. 10, eaan6361 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  115. Perry, W. J. et al. Staphylococcus aureus exhibits heterogeneous siderophore production within the vertebrate host. Proc. Natl Acad. Sci. USA 116, 21980–21982 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Tropini, C., Earle, K. A., Huang, K. C. & Sonnenburg, J. L. The gut microbiome: connecting spatial organization to function. Cell Host Microbe 21, 433–442 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Nava, G. M., Friedrichsen, H. J. & Stappenbeck, T. S. Spatial organization of intestinal microbiota in the mouse ascending colon. ISME J. 5, 627–638 (2011).

    Article  CAS  PubMed  Google Scholar 

  118. Keilberg, D., Zavros, Y., Shepherd, B., Salama, N. R. & Ottemann, K. M. Spatial and temporal shifts in bacterial biogeography and gland occupation during the development of a chronic infection. mBio 7, e01705-16 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  119. Mark Welch, J. L., Hasegawa, Y., McNulty, N. P., Gordon, J. I. & Borisy, G. G. Spatial organization of a model 15-member human gut microbiota established in gnotobiotic mice. Proc. Natl Acad. Sci. USA 114, E9105–E9114 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Harrison, F. & Diggle, S. P. An ex vivo lung model to study bronchioles infected with Pseudomonas aeruginosa biofilms. Microbiology 162, 1755–1760 (2016).

    Article  CAS  PubMed  Google Scholar 

  121. Harrison, F., Muruli, A., Higgins, S. & Diggle, S. P. Development of an ex vivo porcine lung model for studying growth, virulence, and signaling of Pseudomonas aeruginosa. Infect. Immun. 82, 3312–3323 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  122. Sweeney, E. et al. An ex vivo cystic fibrosis model recapitulates key clinical aspects of chronic Staphylococcus aureus infection. Microbiology 167, 000987 (2021).

    Article  Google Scholar 

  123. Hassan, M. M., Harrington, N. E., Sweeney, E. & Harrison, F. Predicting antibiotic-associated virulence of Pseudomonas aeruginosa using an ex vivo lung biofilm model. Front. Microbiol. 11, 568510 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  124. Cheong, J. Z. A. et al. Priority effects dictate community structure and alter virulence of fungal–bacterial biofilms. ISME J. 17, 2012-2027 (2021).

    Article  Google Scholar 

  125. Jorth, P., Spero, M. A., Livingston, J. & Newman, D. K. Quantitative visualization of gene expression in mucoid and nonmucoid Pseudomonas aeruginosa aggregates reveals localized peak expression of alginate in the hypoxic zone. mBio 10, e02622-19 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  126. Dar, D., Dar, N., Cai, L. & Newman, D. K. Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution. Science 373, eabi4882 (2021). This study assesses the gene expression heterogeneity in spatially organized aggregates of P. aeruginosa at the single-cell level by developing the par-seqFISH technique.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Wang, X. et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science 361, eaat5691 (2018). This study develops and uses the single-cell approach STARmap to determine changes in the transcriptional profile across space.

    Article  PubMed  PubMed Central  Google Scholar 

  128. Shah, S. et al. Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing. Development 143, 2862–2867 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  129. Stahl, P. L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78–82 (2016).

    Article  CAS  PubMed  Google Scholar 

  130. Järbrink, K. et al. The humanistic and economic burden of chronic wounds: a protocol for a systematic review. Syst. Rev. 6, 15 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  131. Connell, J. L. et al. Probing prokaryotic social behaviors with bacterial “lobster traps”. mBio 1, e00202-10 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  132. Heydorn, A. et al. Quantification of biofilm structures by the novel computer program COMSTAT. Microbiology 146, 2395–2407 (2000).

    Article  CAS  PubMed  Google Scholar 

  133. Nilsson, M., Givskov, M., Twetman, S. & Tolker-Nielsen, T. Inactivation of the pgmA gene in Streptococcus mutans significantly decreases biofilm-associated antimicrobial tolerance. Microorganisms 7, 310 (2019).

    Article  CAS  PubMed Central  Google Scholar 

  134. Beaudoin, T. et al. Staphylococcus aureus interaction with Pseudomonas aeruginosa biofilm enhances tobramycin resistance. npj Biofilms Microbiomes 3, 25 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Ciofu, O., Mandsberg, L. F., Wang, H. & Hoiby, N. Phenotypes selected during chronic lung infection in cystic fibrosis patients: implications for the treatment of Pseudomonas aeruginosa biofilm infections. FEMS Immunol. Med. Microbiol. 65, 215–225 (2012).

    Article  CAS  PubMed  Google Scholar 

  136. Daims, H., Lucker, S. & Wagner, M. daime, a novel image analysis program for microbial ecology and biofilm research. Env. Microbiol. 8, 200–213 (2006).

    Article  CAS  Google Scholar 

  137. Hartmann, R. et al. Quantitative image analysis of microbial communities with BiofilmQ. Nat. Microbiol. 6, 151–156 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank the Cystic Fibrosis foundation for a postdoctoral fellowship to S.A. (AZIMI18F0); the National Institutes of Health (NIH) for funding to G.R.L. (F32DE027281 and K99DE031018); and NIH Grants R01DE023193, R01DE020100 and 1R01GM116547 and a grant from the Shurl and Kay Curci Foundation to M.W.

Author information

Author notes

  1. These authors contributed equally: Sheyda Azimi, Gina R. Lewin.

Authors and Affiliations

  1. School of Biological Sciences and Center for Microbial Dynamics and Infection, Georgia Institute of Technology, Atlanta, GA, USA

    Sheyda Azimi

  2. Emory-Children’s Cystic Fibrosis Center, Atlanta, GA, USA

    Gina R. Lewin & Marvin Whiteley

Authors
  1. Sheyda Azimi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gina R. Lewin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marvin Whiteley
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The authors contributed equally to all aspects of the article.

Corresponding author

Correspondence to Marvin Whiteley.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Microbiology thanks Gary Borisy, Kevin Foster, Nicholas Jakubovics and Jessica Mark Welch for their contribution to the peer review of this work.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Glossary

Biogeography

The spatial assembly and distribution of various organisms in an environment through time.

Microbiogeography

The spatial patterning of microorganisms at the micron scale within a single environment.

Quorum sensing

The detection of an increased concentration of small signal molecules at high cell density, which can control gene expression in bacterial populations.

Cystic fibrosis

A disorder that is caused by mutation(s) in the cystic fibrosis transmembrane conductance regulator gene, which affects cells that produce mucus, sweat and digestive enzymes. In people with cystic fibrosis, the build-up of mucus in the airways results in chronic polymicrobial lung infections.

Function

A physiological property of a bacterium, such as glucose catabolism or motility.

Catalysed reporter deposition FISH

(CARD-FISH). In CARD-FISH, the nucleotide probe is conjugated to horseradish peroxidase that amplifies the fluorescence in situ hybridization (FISH) signal. This method is used for bacterial taxa or bacterial functions with inherently low signal, for example bacteria with low ribosome content.

Double labelling of oligonucleotide probes FISH

(DOPE-FISH). DOPE-FISH uses 5′ and 3′ double-labelled oligonucleotide probes to increase the fluorescence in situ hybridization (FISH) signal.

Combinatorial labelling and spectral imaging FISH

(CLASI-FISH). Simultaneous fluorescence in situ hybridization (FISH) labelling of individual taxa using multiple fluorophores. By mixing the fluorophore combinations used for each taxon, this method enables the detection of tens to hundreds of taxa concurrently. Spectral imaging is usually followed by linear unmixing analysis to differentiate between taxa.

Alginate

An exopolysaccharide produced by Pseudomonas aeruginosa that helps cells to attach to surfaces and form biofilms.

Extracellular DNA

(eDNA). eDNA can be produced by host cells or bacteria. It is one of the main components of the biofilm matrix that can provide structural scaffold for bacterial cells and may play a role in protecting bacterial cells in response to host cells and antibiotics.

NETosis

Neutrophil extracellular traps (NETs) are nucleic acid and intracellular components that are forced out of polymorphonuclear leukocytes in response to microorganisms and proinflammatory cytokines. NETosis is a type of programmed cell death in polymorphonuclear leukocytes such as neutrophils that functions as cellular defence. During NETosis, cells force out their chromatin, forming sticky traps that can trap bacterial cells.

Mucin

A type of high molecular weight glycosylated protein produced by epithelial cells in animals that forms gels and is found in high levels in lung infections. Bovine and porcine mucins can be purchased commercially, which has led to their use in numerous preclinical models.

Hybridization chain reaction

The detection and quantification of RNA transcripts using exogenously added fluorophore-conjugated DNA hairpins. These hairpins self-assemble, amplifying their signal.

Coagulase

An enzyme produced by several types of bacteria that converts the soluble protein fibrinogen in blood to insoluble fibrin, leading to clot formation.

Preclinical infection models

In vitro and in vivo models used to study microbial infection.

Raman microscopy

A combination of laser-based imaging and Raman spectroscopy to detect the differential excitation levels of photons. This method is used to identify certain molecules without disturbing the spatial arrangement of the samples.

Atomic force microscopy

A powerful imaging technique that uses a fine and specific tip attached to a cantilever that scans along the surface of a sample. The changes in contact forces between the tip and the surface of the sample are recorded by a laser beam that generates an accurate topographic image of the surface at nanometre resolution.

Surface plasmon resonance imaging

A label-free imaging method that is used to detect and measure the attachment level and surface properties of bacterial biofilms. This method analyses changes in the angle of reflected light of a surface covered with the sample of interest, compared with a control surface.

Scanning electrochemical microscopy

A label-free microscopy method using probes that detect redox reactions and can provide an electrochemical map of an environment.

Imaging mass spectrometry

Mass spectrometry performed across a spatial plane to build a map of detected chemicals.

Hydroxyapatite

A mineral form of calcium apatite that is the main component of tooth enamel and bones.

Fibrin

A glycosylated protein in blood formed by the enzymatic action of a serine protease on soluble fibrinogen. Polymerized fibrin leads to clotting of the blood.

Transferrin

A glycoprotein that binds to iron and transports iron through the bloodstream.

Keratinocyte

A cell that forms the outer layer of skin and produces keratin to form a protective barrier.

Organoid

A small, differentiated collection of cells containing similar cell types and functions as an organ. Organoids are produced in vitro using stem cells derived from the organ of interest that are cultured in a medium containing growth factors and extracellular matrix.

Organ-on-a-chip

A cell culture device that contains a multichannel 3D microfluidics chip, designed to mimic the physical and chemical properties of an organ. Organ-on-a-chip models can provide a structured microenvironment for high-throughput assessment of bacterial–host interactions, for instance in response to various stimuli.

Glycol methacrylate resin

An ester form of epoxy resin that can be used instead of paraffin for embedding biological samples for better quality imaging.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Azimi, S., Lewin, G.R. & Whiteley, M. The biogeography of infection revisited. Nat Rev Microbiol 20, 579–592 (2022). https://doi.org/10.1038/s41579-022-00683-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41579-022-00683-3

This article is cited by

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