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A germ-free humanized mouse model shows the contribution of resident microbiota to human-specific pathogen infection

Nature Biotechnology (2023)Cite this article

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Abstract

Germ-free (GF) mice, which are depleted of their resident microbiota, are the gold standard for exploring the role of the microbiome in health and disease; however, they are of limited value in the study of human-specific pathogens because they do not support their replication. Here, we develop GF mice systemically reconstituted with human immune cells and use them to evaluate the role of the resident microbiome in the acquisition, replication and pathogenesis of two human-specific pathogens, Epstein–Barr virus (EBV) and human immunodeficiency virus (HIV). Comparison with conventional (CV) humanized mice showed that resident microbiota enhance the establishment of EBV infection and EBV-induced tumorigenesis and increase mucosal HIV acquisition and replication. HIV RNA levels were higher in plasma and tissues of CV humanized mice compared with GF humanized mice. The frequency of CCR5+ CD4+ T cells throughout the intestine was also higher in CV humanized mice, indicating that resident microbiota govern levels of HIV target cells. Thus, resident microbiota promote the acquisition and pathogenesis of two clinically relevant human-specific pathogens.

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Fig. 1: GF-BLT mice are systemically reconstituted by human hematopoietic cells.
Fig. 2: The establishment of EBV infection and EBV-induced tumorigenesis is increased in the presence of resident microbiota.
Fig. 3: Oral HIV acquisition is increased in the presence of resident microbiota.
Fig. 4: Rectal HIV acquisition and virus replication in the intestinal tract are enhanced in the presence of resident microbiota.
Fig. 5: Resident microbiota increase HIV target cell levels in the intestinal tract.

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Source data for Figs. 1–5 and Extended Data Figs. 1–8 are provided with the manuscript.

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Acknowledgements

We thank current and former members of the Garcia and Wahl laboratories for technical assistance and technicians at the UNC National Gnotobiotic Rodent Resource Center, Microbiome Core Facility, Division of Comparative Medicine, and Animal Histopathology and Clinical Chemistry Core for technical support. We also thank M. Kane, S. Lemon, J. Turpin and N. Raab-Traub for helpful comments and discussions. Figure 1a was created using BioRender.com. This work was supported by funding from NIH grants AI123010 (A.W.), DK131585 (A.W., J.V.G. and R.B.S), 1UM1AI126619 (current award 1UM1AI164567; J.V.G), P40OD010995 (R.B.S. and A.R.R.), P30DK034987 (R.B.S), U19AI082637 (I.M.) and FIC D43TW009532 (J.D.T). The UNC CFAR Biostatistics Core is supported by NIH-funded program P30AI050410. UNC Animal Histopathology & Clinical Chemistry is supported in part by an NCI Center Core Support Grant (5P30CA016080-42). The UNC Microbiome Core is funded in part by the Center for Gastrointestinal Biology and Disease (P30 DK034987) and the UNC Nutrition Obesity Research Center (P30 DK056350).

Author information

Author notes

  1. These authors contributed equally: Angela Wahl, Wenbo Yao, Baolin Liao.

Authors and Affiliations

  1. International Center for the Advancement of Translational Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Angela Wahl, Wenbo Yao, Baolin Liao, Morgan Chateau, Cara Richardson, Lijun Ling, Adrienne Franks, Krithika Senthil, Genevieve Doyon & J. Victor Garcia

  2. Division of Infectious Diseases, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Angela Wahl, Wenbo Yao, Baolin Liao, Morgan Chateau, Cara Richardson, Lijun Ling, Adrienne Franks, Krithika Senthil, Genevieve Doyon, Joseph D. Tucker & J. Victor Garcia

  3. Center for AIDS Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Angela Wahl, Wenbo Yao, Baolin Liao, Morgan Chateau, Cara Richardson, Lijun Ling, Adrienne Franks, Krithika Senthil, Genevieve Doyon & J. Victor Garcia

  4. Guangzhou Eighth People’s Hospital, Guangzhou Medical University, Guangzhou, China

    Baolin Liao

  5. Center for Gastrointestinal Biology and Disease, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Fengling Li, Josh Frost, M. Andrea Azcarate-Peril, Allison R. Rogala, R. Balfour Sartor & J. Victor Garcia

  6. Division of Comparative Medicine, Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Josh Frost, Craig A. Fletcher & Allison R. Rogala

  7. Department of Pathology, Microbiology, and Immunology, New York Medical College, Valhalla, NY, USA

    Christopher B. Whitehurst

  8. Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Joseph S. Pagano & R. Balfour Sartor

  9. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Joseph S. Pagano

  10. Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Joseph S. Pagano

  11. Division of Gastroenterology and Hepatology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    M. Andrea Azcarate-Peril & R. Balfour Sartor

  12. UNC Microbiome Core, University of North Carolina, Chapel Hill, NC, USA

    M. Andrea Azcarate-Peril

  13. Department of Biostatistics, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Michael G. Hudgens

  14. Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK

    Joseph D. Tucker

  15. Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, University of Pittsburgh Medical School, Pittsburgh, PA, USA

    Ian McGowan

  16. Orion Biotechnology, Ottawa, Ontario, Canada

    Ian McGowan

Authors
  1. Angela Wahl
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  2. Wenbo Yao
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  3. Baolin Liao
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  4. Morgan Chateau
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  5. Cara Richardson
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  6. Lijun Ling
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  7. Adrienne Franks
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  8. Krithika Senthil
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  9. Genevieve Doyon
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  10. Fengling Li
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  11. Josh Frost
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  12. Christopher B. Whitehurst
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  13. Joseph S. Pagano
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  14. Craig A. Fletcher
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  15. M. Andrea Azcarate-Peril
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  16. Michael G. Hudgens
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  17. Allison R. Rogala
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  18. Joseph D. Tucker
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  19. Ian McGowan
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  20. R. Balfour Sartor
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  21. J. Victor Garcia
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Contributions

W.Y., B.L., C.R., M.C. and A.W. constructed BLT mice, necropsied mice, and performed flow cytometric analysis of peripheral blood and tissues. G.D. contributed to the flow cytometric analysis of tissues. W.Y. and A.W. performed the immunohistochemical analysis. A.W., A.F., K.S. and G.D. performed experiments with EBV-exposed BLT mice, and A.W. analyzed the data. C.B.W and J.S.P. contributed to the EBV studies. W.Y., C.R. and A.W. performed experiments with HIV-exposed BLT mice and analyzed data. L.L. assisted with rectal HIV exposures. F.L. and J.F. contributed to the rederivation of GF mice and microbial testing. M.A.A. contributed to the microbiome sequencing analysis. M.G.H assisted with statistical analyses and data presentation. A.R.R. and R.B.S contributed to the rederivation of GF mice, microbial testing and experimental design. I.M. contributed to the conceptualization of the study. C.A.F and J.D.T. contributed to data interpretation, and J.D.T also assisted with the supervision of B.L. J.V.G. and A.W. conceived and designed the study and experiments; supervised the work; and contributed to data interpretation, analysis, data presentation, and manuscript conceptualization and writing.

Corresponding authors

Correspondence to Angela Wahl or J. Victor Garcia.

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The authors declare no competing interests.

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Nature Biotechnology thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Fecal bacterial microbiome of CV-BLT mice.

The composition of the bacterial microbiome was analyzed by 16S amplicon sequencing in fecal pellets collected from CV-BLT mice (n = 10). The mean relative abundance at the a, phylum and b, genus levels are shown. Taxa with a mean relative abundance <2% were grouped together as other.

Source data

Extended Data Fig. 2 Human hematopoietic cells are present in lymphoid and non-lymphoid tissues of GF-BLT mice.

Immunohistochemical staining for a, human hematopoietic cells (hCD45+) including human dendritic cells (hCD11c+), myeloid cells (hCD68+), B cells (hCD20+) and T cells (hCD3+) in the spleen (n = 6 analyzed), lymph nodes (n = 5 analyzed), liver (n = 5 analyzed), and lung (n = 6 analyzed) of GF-BLT mice and b, human B cells (hCD20+) in the small intestine (n = 3 analyzed), cecum (n = 6 analyzed), and large intestine colon (n = 3 analyzed). Positive cells are stained brown. Scale bars, 100 um. c, Flow cytometric analysis of human T cell levels in the intraepithelial layer (IEL) and lamina propria layer (LPL) of the small intestine (S), cecum (C), and large intestine (L) of GF-BLT mice (n = 14 S IEL, C LPL; n = 13 S LPL, C IEL, L IEL; n = 12 L LPL). Horizontal and vertical lines represent the mean and standard error mean respectively.

Source data

Extended Data Fig. 3 CD21 expression on human splenic B cells in CV-BLT and GF-BLT mice.

CD21 expression was evaluated on human B cells isolated from the spleen of CV-BLT (n = 5, black) and GF-BLT (n = 5, red) mice using flow cytometry. The a, percent of human B cells expressing CD21 and the b, mean fluorescent intensity (MFI) of CD21 staining on CD21+ human B cells was compared between CV-BLT and GF-BLT mice with a two-sided Mann-Whitney test. Horizontal and vertical lines represent the mean and standard error mean respectively.

Source data

Extended Data Fig. 4 HIV replication is enhanced in the presence of resident microbiota following a systemic HIV exposure.

CV-BLT mice (n = 8) and GF-BLT mice (n = 8) were challenged systemically (via intraperitoneal injection) with HIV-1JRCSF. HIV RNA levels in peripheral blood plasma were monitored longitudinally by real-time PCR. Five weeks post-exposure, aviremic BLT mice were administered a second systemic dose of HIV. GF-BLT mice were housed in a gnotobiotic isolator for the duration of the study and their GF status monitored longitudinally. a, Peripheral blood plasma viral load (HIV RNA copies/ml) in CV-BLT mice (left panel, black) and GF-BLT mice (right panel, red) following HIV challenge. The limit of detection is shown with a dashed line. b, Percent HIV positive CV-BLT mice (black) and GF-BLT mice were compared with a two-sided log-rank Mantel Cox test based on the presence of HIV RNA and/or HIV DNA in peripheral blood and/or tissues. c, Peripheral blood plasma viral load of viremic CV-BLT mice (n = 7, black) and GF-BLT mice (n = 6, red). For mice that acquired HIV infection after the second challenge, week one represents the viral load one week after the second HIV exposure (6 weeks after the first exposure). Solid lines represent mean plasma viral loads. d, Mean and e, peak plasma viral load of viremic CV-BLT mice (n = 7, black) and GF-BLT mice (n = 6, red). f, HIV RNA levels in the bone marrow (BM), human thymus (THY), spleen (SPL), lymph nodes (LN), liver (LIV), and lung (LNG) of viremic CV-BLT mice (n = 6, black) and GF-BLT mice (n = 6, red). In d–f, horizontal and vertical lines represent the mean and standard error mean respectively. c–f, HIV RNA levels were compared with a two-sided Mann-Whitney test.

Source data

Extended Data Fig. 5 CD8+ T cell activation is higher in the intestinal tract in the presence of resident microbiota following rectal HIV acquisition.

Flow cytometric analysis of a, activated (HLA-DR+CD38+) human CD8+ T cells of viremic GF-BLT (red) and CV-BLT (black) mice at day 8 (GF, n = 4; CV n = 12), day 13 (GF, n = 4; CV n = 12), day 20 (GF, n = 4; CV n = 9), day 28 (GF, n = 4; CV n = 5) and day 35 (GF, n = 4; CV n = 4) post rectal HIV acquisition. Percent activated human CD8+ T cells in the b, PB, bone marrow (BM), spleen (SPL), lymph nodes (LN), human thymic organoid (THY), liver (LIV), and lung (LNG) as well as the c, small intestine (S), cecum (C), and large intestine (L) intraepithelial layer (IEL) and lamina propria layer (LPL) of aviremic (filled bars) and viremic (open bars) GF-BLT mice. Aviremic GF-BLT mice, n = 9 (PB, BM, SPL, LN, THY, LIV), n = 8 (LNG, S IEL, C IEL, C LPL, L IEL, L LPL), or n = 4 (S LPL). Viremic GF-BLT mice, n = 4 (PB, BM, SPL, LN, THY, LIV, LNG) or n = 3 (S IEL, S LPL, C IEL, C LPL, L IEL, L LPL). Percent activated human CD8+ T cells in the d, PB, BM, SPL, LN, THY, LIV, and LNG as well as the e, S IEL, S LPL, C IEL, C LPL, L IEL, and L LPL of aviremic (filled bars) and viremic (open bars) CV-BLT mice. Aviremic CV-BLT mice, n = 5 (PB, BM, SPL, LN, THY, LIV, LNG, S IEL, C IEL, C LPL, L IEL, L LPL), n = 3 (S LPL). Viremic CV-BLT mice, n = 8 (PB, BM, SPL, LN, LIV, LNG), n = 7 (S IEL, C IEL, C LPL, L IEL, L LPL), or n = 6 (THY, S LPL). SP, CD8+ single positive thymocyte. DP, CD4+CD8+ double positive thymocyte. b–e, Shown is the difference in percent activated CD8+ T cells between viremic and aviremic mice. Horizontal and vertical lines represent the mean and standard error mean respectively. a-e, Cell levels mice were compared with a two-sided Mann-Whitney test.

Source data

Extended Data Fig. 6 HIV infection mediated CD4+ T cell depletion is not impacted by the presence of resident microbiota.

Flow cytometric analysis of a, human CD4+ T cells in the peripheral blood (PB) of viremic GF-BLT (red) and CV-BLT (black) mice at day 8 (GF, n = 4; CV n = 12), day 13 (GF, n = 4; CV n = 12), day 20 (GF, n = 4; CV n = 9), day 28 (GF, n = 4; CV n = 5) and day 35 (GF, n = 4; CV n = 4) post rectal HIV acquisition. Percent CD4+ of human T cells in the b, PB, bone marrow (BM), spleen (SPL), lymph nodes (LN), human thymic organoid (THY), liver (LIV), and lung (LNG) as well as the c, small intestine (S), cecum (C), and large intestine (L) intraepithelial layer (IEL) and lamina propria layer (LPL) of aviremic (filled bars) and viremic (open bars) GF-BLT mice. Aviremic GF-BLT mice, n = 9 (PB, BM, SPL, LN, THY, LIV), n = 8 (LNG, S IEL, C IEL, C LPL, L IEL, L LPL), or n = 5 (S LPL). Viremic GF-BLT mice, n = 4 (PB, BM, SPL, LN, THY, LIV, LNG) or n = 3 (S IEL, S LPL, C IEL, C LPL, L IEL, L LPL). Percent CD4+ of human T cells in the d, PB, BM, SPL, LN, THY, LIV, and LNG as well as the e, S IEL, S LPL, C IEL, C LPL, L IEL, and L LPL of aviremic (filled bars) and viremic (open bars) CV-BLT mice. Aviremic CV-BLT mice, n = 5 (PB, BM, SPL, LN, THY, LIV, LNG, S IEL, C IEL, C LPL, L IEL, L LPL), n = 4 (S LPL). Viremic CV-BLT mice, n = 8 (PB, BM, SPL, LN, LIV, LNG), n = 7 (S IEL, C IEL, C LPL, L IEL, L LPL), or n = 6 (THY, S LPL). SP, CD4+ single positive thymocyte. DP, CD4+CD8+ double positive thymocyte. b–e, Shown is the difference in percent CD4+ T cells between viremic and avirmic mice. Horizontal and vertical lines represent the mean and standard error mean respectively. a-e, Cell levels mice were compared with a two-sided Mann-Whitney test.

Source data

Extended Data Fig. 7 Minimal impact of resident microbiota on human CD4+ T cell homeostasis in the peripheral blood and nonintestinal tissues.

Numbers of a, human hematopoietic cells (hCD45+), including b, T cells (hCD3+) and c, CD4+ T cells in the small intestine (S) and large intestine (L) intraepithelial (IEL) and lamina propria (LPL) layers of GF-BLT mice (GF; red bars; S IEL, n = 14; S LPL, n = 13; L IEL, n = 13; L LPL, n = 12) and CV-BLT mice (CV; black; S IEL, n = 11; S LPL, n = 9; L IEL, n = 11; L LPL, n = 11) were determined by flow cytometric analysis. Flow cytometric analysis of human hematopoietic cells (hCD45+) including T cells (hCD3+) and CD4+ T cells in the d, peripheral blood (GF, n = 16; CV, n = 11), e, bone marrow (GF, n = 14; CV, n = 11), f, thymic organoid (GF, n = 15; CV, n = 11), g, spleen (GF, n = 16; CV, n = 11), h, lymph nodes (GF, n = 15; CV, n = 10), i, liver (GF, n = 16; CV, n = 11), and j, lung (GF, n = 16; CV, n = 11) of GF-BLT (GF; red boxes) and CV-BLT (CV; black boxes). Cell counts are normalized to a-c, tissue length (cm) or f, g, i, j, weight (g). SP, CD4+ single positive thymocyte. DP, CD4+CD8+ double positive thymocyte. Horizontal and vertical lines represent the mean and standard error mean respectively. Cell levels between GF-BLT and CV-BLT mice were compared with a two-sided Mann-Whitney test. a and b, The exact p values shown as P<0.0001 for comparisons of human CD45+ and CD3+ T cell numbers in the S IEL are P = 0.000020 and P = 0.000043 respectively.

Source data

Extended Data Fig. 8 Resident microbiota regulate human CD8+ T cell homeostasis in the intestinal tract.

Levels of human a–c, B cells, d–f, myeloid cells, and g–i, CD8+ T cells in the peripheral blood (GF, n = 15; CV, n = 11), bone marrow (BM; GF, n = 14; CV, n = 11), thymic organoid (THY; GF, n = 15; CV, n = 11), spleen (SPL; GF, n = 16; CV, n = 11), lymph nodes (LN; GF, n = 15; CV, n = 10), liver (LIV; GF, n = 16; CV, n = 11), lung (LNG; GF, n = 16; CV, n = 11) and the small intestine (S), cecum (C), and large intestine (L) intraepithelial layer (IEL; GF, n = 13; CV, n = 11) and lamina propria layer (LPL; GF S LPL, n = 13; CV S LPL, n = 9 CV-BLT; GF C LPL, n = 14; CV CLPL, n = 11; GF LPL, n = 12; CV LPL, n = 11) of GF-BLT (GF, red boxes) and CV-BLT mice (CV, black boxes). Horizontal and vertical lines represent the mean and standard error mean respectively. Cell levels between GF-BLT and CV-BLT mice were compared with a two-sided Mann-Whitney test. e and i, The exact p values shown as P<0.0001 for comparisons of human myeloid cell numbers in the SPL and human CD8+ T cell numbers in the S IEL and L IEL are P = 0.000041, P = 0.000020, and P = 0.000077 respectively.

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Supplementary information

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Supplementary Figs. 1–2 and Tables 1–10.

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Wahl, A., Yao, W., Liao, B. et al. A germ-free humanized mouse model shows the contribution of resident microbiota to human-specific pathogen infection. Nat Biotechnol (2023). https://doi.org/10.1038/s41587-023-01906-5

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