Normalizing the environment recapitulates adult human immune traits in laboratory mice (original) (raw)

Nature volume 532, pages 512–516 (2016)Cite this article

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Abstract

Our current understanding of immunology was largely defined in laboratory mice, partly because they are inbred and genetically homogeneous, can be genetically manipulated, allow kinetic tissue analyses to be carried out from the onset of disease, and permit the use of tractable disease models. Comparably reductionist experiments are neither technically nor ethically possible in humans. However, there is growing concern that laboratory mice do not reflect relevant aspects of the human immune system, which may account for failures to translate disease treatments from bench to bedside1,2,3,4,5,6,7,8. Laboratory mice live in abnormally hygienic specific pathogen free (SPF) barrier facilities. Here we show that standard laboratory mouse husbandry has profound effects on the immune system and that environmental changes produce mice with immune systems closer to those of adult humans. Laboratory mice—like newborn, but not adult, humans—lack effector-differentiated and mucosally distributed memory T cells. These cell populations were present in free-living barn populations of feral mice and pet store mice with diverse microbial experience, and were induced in laboratory mice after co-housing with pet store mice, suggesting that the environment is involved in the induction of these cells. Altering the living conditions of mice profoundly affected the cellular composition of the innate and adaptive immune systems, resulted in global changes in blood cell gene expression to patterns that more closely reflected the immune signatures of adult humans rather than neonates, altered resistance to infection, and influenced T-cell differentiation in response to a de novo viral infection. These data highlight the effects of environment on the basal immune state and response to infection and suggest that restoring physiological microbial exposure in laboratory mice could provide a relevant tool for modelling immunological events in free-living organisms, including humans.

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Acknowledgements

This study was supported by National Institutes of Health grants 1R01AI111671, R01AI084913 (to D.M.), R01AI116678, R01AI075168 (to S.C.J.) and a BSL-3 suite rental waiver grant from the University of Minnesota. We thank R. Ahmed for providing reagents for pilot studies, P. Southern and D. McKenna for tissue samples or cord blood, and all members of the BSL-3 mouse team (University of Minnesota).

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Author notes

  1. Oludare A. Odumade & Kerry A. Casey
    Present address: † Present addresses: Department of Pediatrics, University of California San Diego, Rady Children’s Hospital, San Diego, California 92123, USA (O.A.O.); Department of Respiratory, Inflammation and Autoimmunity, MedImmune LLC, Gaithersburg, Maryland 20878, USA (K.A.C.).,

Authors and Affiliations

  1. Department of Microbiology and Immunology, Center for Immunology, University of Minnesota, Minneapolis, Minnesota, 55414, USA
    Lalit K. Beura, Jason M. Schenkel, Kerry A. Casey, Emily A. Thompson, Kathryn A. Fraser, Pamela C. Rosato, Marc K. Jenkins, Vaiva Vezys & David Masopust
  2. Department of Laboratory Medicine and Pathology, Center for Immunology, University of Minnesota, Minneapolis, Minnesota, 55414, USA
    Sara E. Hamilton, Oludare A. Odumade & Stephen C. Jameson
  3. Department of Pediatric Oncology, Dana-Farber Cancer Institute, and Pediatric Hematology and Oncology, Children's Hospital, Boston, 02115, Massachusetts, USA
    Kevin Bi & W. Nicholas Haining
  4. Department of Pathology, Case Western Reserve University, Cleveland, 44106, Ohio, USA
    Ali Filali-Mouhim & Rafick P. Sekaly

Authors

  1. Lalit K. Beura
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  2. Sara E. Hamilton
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  3. Kevin Bi
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  4. Jason M. Schenkel
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  5. Oludare A. Odumade
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  6. Kerry A. Casey
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  7. Emily A. Thompson
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  8. Kathryn A. Fraser
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  9. Pamela C. Rosato
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  10. Ali Filali-Mouhim
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  11. Rafick P. Sekaly
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  12. Marc K. Jenkins
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Contributions

L.K.B., S.E.H., J.M.S., O.A.O., K.A.C., E.A.T., K.A.F, P.C.R, V.V., and D.M. performed the experiments and analysed the data. K.B. and W.N.H. analysed the transcriptome data. M.K.J., A.F.-M., and R.P.S. provided input on research design. L.K.B., S.E.H., W.N.H., S.C.J., and D.M. wrote the manuscript.

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Correspondence toStephen C. Jameson or David Masopust.

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Extended data figures and tables

Extended Data Figure 1 Frequency of CD8+ T-cell subsets in newborn versus adult humans.

CD8+ T-cell subsets were defined in adult PBMCs (n = 13) and cord blood PBMCs (n = 8) by fluorescence flow cytometry based on the following markers: naive, CD45RAhiCCR7hi; TCM, CD45RAloCCR7hi; TEM, CD45RAloCCR7lo; TEMRA, CD45RAhiCCR7lo. Significance was determined using unpaired two-sided _t_-test. ***P < 0.001, ****P < 0.0001; error bars indicate mean ± s.e.m.

Extended Data Figure 2 Co-housing laboratory mice with pet store mice induces accumulation of TRM-phenotype CD8+ T cells and other innate cells in tissues of laboratory mice.

a, CD8+ T-cell density within the indicated tissues of adult laboratory mice (n = 5) and co-housed mice (n = 7). Representative immunofluorescence staining, CD8β (red), DAPI (nuclei, blue); scale bars, 50 μm. b, Phenotype of CD8+ T cells was compared between laboratory mice (n = 9) and age-matched laboratory mice that were co-housed (n = 9, representative flow cytometry plots shown). Samples gated on CD44hi cells isolated from the indicated tissue (vasculature populations were excluded, see Methods). c, Enumeration of CD11b+ granulocytes and Ly6Chi inflammatory monocytes in spleens of laboratory (n = 6) and co-housed (n = 6) mice. Significance was determined using unpaired two-sided Mann–Whitney _U_-test. **P < 0.01; error bars indicate mean ± s.e.m.

Extended Data Figure 3 LEM metagene analysis.

For each comparison, standard GSEA was performed using the ImmSigDB database of gene-sets. Genes in the top 150 enriched sets (FDR < 0.001, ranked by P value) were filtered to only leading edge genes and subsequently clustered into groups (metagenes) using an NMF algorithm. Hierarchical clustering of genes within individual metagenes was performed to obtain the final heatmap. Metagenes with qualitatively discernible ‘blocks’ of gene-set membership were annotated according to the identity of corresponding enriched gene-sets. Heatmaps for adult versus neonatal, pet store versus laboratory, co-housed versus laboratory, neonatal versus adult, laboratory versus pet store, and laboratory versus co-housed comparisons are shown. Individual genes within each metagene are listed in Supplementary Table 1. Pairwise overlaps between metagenes from different comparisons are visualized in Fig. 4c.

Extended Data Figure 4 Environment altered antimicrobial resistance and CD8+ T-cell differentiation.

Laboratory mice were co-housed with pet store mice as described in Figure 3. a, Bacterial load in the spleen 3 days after challenge with 8.5 × 104 c.f.u. of L. monocytogenes (LM) in laboratory (n = 8), LM-immune (n = 9), co-housed (n = 9) and pet store mice (n = 9) in two independent experiments. b, Survival of laboratory mice (n = 15), co-housed mice (n = 19) and pet store mice (n = 15) after challenge with 106 P. berghei ANKA parasitized RBCs in two independent experiments. c, Laboratory (n = 9) and co-housed (n = 8) mice were infected with LCMV. Four weeks later, LCMV-specific CD8+ T cells (identified with H-2Db/gp33 MHC I tetramers) were evaluated for expression of the indicated markers. Top row, gated on live CD8α+ T cells. Bottom three rows, gated on live CD8α+ H-2Db/gp33+ T cells. Significance was determined using Kruskal–Wallis (ANOVA) test (a) and log-rank (Mantel–Cox) test (b). *P < 0.05, ***P < 0.001, ****P < 0.0001; error bars indicate mean ± s.e.m.

Extended Data Table 1 Microbial exposure in laboratory, pet store and co-housed mice

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Supplementary information

Supplementary Table 1

Genes belonging to all indicated metagenes identified are shown in this table. (XLSX 81 kb)

Supplementary Table 2

Adult vs. Neonatal metagene 1, Petstore vs. Laboratory metagene 2, and Cohoused vs. Laboratory metagene 1 are three metagenes exhibiting consistent and conserved enrichment of type-I interferon response-related GO terms. Genes are separated into columns depending on whether they belong uniquely to a single metagene, are shared between two specific metagenes, or shared between all three type-I interferon response-related metagenes. (XLSX 33 kb)

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Beura, L., Hamilton, S., Bi, K. et al. Normalizing the environment recapitulates adult human immune traits in laboratory mice.Nature 532, 512–516 (2016). https://doi.org/10.1038/nature17655

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Editorial Summary

Do 'dirty' mice make better immunological models?

The laboratory mouse is by far the dominant model organism for in vivo immunological research which — particularly in the light of disappointing results obtained with some recent transfers of disease treatments from laboratory to clinic — raises the question of how accurately the model reflects the human immune system. These authors compare the immune status of laboratory mice with that of feral mice and with mice bought commercially as pets. They find that the immune system of the ubiquitous laboratory 'specific pathogen free' mouse approximates that of human neonates, rather than human adults. Co-housing laboratory mice with 'pet store' mice leads to maturation of the immune system, making it more similar to that of the human adult, and resulting in increased resistance in several models of infection. The use of such 'dirty' mice could supplement current models to either increase translational potential to human disease or to better inform the efficacy of preclinical prophylactic and therapeutic modalities.