Microbial experience fundamentally shapes immunity, particularly during the perinatal period when the immune system is underdeveloped, and novel microbial encounters are common. Most animal models are raised in specific pathogen-free (SPF) conditions with relatively uniform microbial communities. How SPF housing conditions alter early-life immune development relative to natural microbial exposure (NME) has not been thoroughly investigated. In this article, we compare immune development in SPF-raised mice with mice born from immunologically experienced mothers in microbially diverse environments. NME induced broad immune cell expansion, including naive cells, suggesting mechanisms besides activation-induced proliferation contribute to the increase in immune cell numbers. We found NME conditions also expanded immune cell progenitor cell populations in the bone marrow, suggesting microbial experience enhances immune development at the earliest stages of immune cell differentiation. Multiple immune functions characteristically impaired in infants were also enhanced by NME, including T cell memory and Th1 polarization, B cell class switching and Ab production, proinflammatory cytokine expression, and bacterial clearance after Listeria monocytogenes challenge. Collectively, our studies reveal numerous impairments in immune development in SPF conditions relative to natural immune development.

At birth, newborns abruptly encounter a diverse community of previously unencountered microbes. The newborn immune system has the complex task of simultaneously defending the host against dangerous pathogens while ignoring innocuous signals and nurturing the formation of a healthy commensal microbiome. Failures of these processes can result in infection, sepsis, malnutrition, developmental delay, allergic reactions, or death. Immune development is a prolonged process whereby early-life immune suppression is progressively reduced. This process can take months to years for some mammalian immune systems, during which the organism is susceptible to infections. Although the factors that orchestrate immune development are not clearly defined, evidence suggests microbial experience can augment immune development (1–4). Moreover, the perinatal immune system may be more sensitive to modulation by microbial exposure than the mature immune system (5). The effects of microbial exposure on immune development are not limited to the postnatal period, because prenatal maternal microbial exposure also impacts immune development in offspring (6, 7). However, the field has been limited to single-pathogen models and the use of relatively uniform conventional microbiota. Although some recent naturalization models have elegantly incorporated physiological microbial exposures during pregnancy and preconception (4, 8, 9), the impact of perinatal and maternal microbial exposures on the trajectory of early immune development remains incompletely defined. In this study, we use a mouse model that incorporates physiological microbial exposure beginning with the mother before conception and persisting through pregnancy and the postpartum period. We define how natural microbial exposure (NME) influences immune system development through characterization of immune cells and immune cell progenitor populations, cytokine/chemokine production, pattern recognition receptor (PRR) expression, and pathogen clearance.

Male and female C57BL/6J (B6) (000664) and female B6.129(Cg)-Gt(ROSA)26Sortm4(ACTB-tdTomato-EGFP)Luo/J (B6.mTmG) (007676) mice were purchased from Jackson Laboratories (Bar Harbor, ME). B6.mTmG+/− mice were used as female breeders in some experiments to track immune cell origins. We observed no difference between mTmG and B6 mice in these experiments. Female pet-store mice were purchased from local pet stores in the Minneapolis-Saint Paul, Minnesota, metro area. Serological testing has revealed pet-store mice often carry some combination of rotavirus (epizootic diarrhea of infant mice), mouse hepatitis virus, murine norovirus, mouse parvovirus NS1, type 1/2, minute virus of mice, Theiler’s murine encephalomyelitis virus (TMEV), Sendai virus, lymphocytic choriomeningitis, mouse adenovirus types 1 and 2, mouse CMV, polyomavirus, pneumonia virus of mice, Mycoplasma pulmonis, Clostridium piliforme, pinworms, fur mites, and Encephalitozoon cuniculi. The pet-store mice are also tested for ectromelia virus (mousepox), reovirus, and cilia-associated respiratory Bacillus, but they have never tested positive for these microbes. Our specific pathogen-free (SPF) colony is routinely tested to ensure the absence of the following pathogens: mouse parvovirus, minute virus of mice, mouse hepatitis virus, mouse rotavirus-A (epizootic diarrhea of infant mice), Theiler’s murine encephalomyelitis virus (TMEV), Sendai virus, pneumonia virus of mice, reovirus, Ectromelia (Mousepox), mouse adenovirus types 1 and 2, polyomavirus, lymphocytic choriomeningitis virus, mouse CMV, Mycoplasma pulmonis, Clostridium piliforme (Tyzzer’s disease), cilia-associated respiratory Bacillus, fur mites (Myobia musculi, Radfordia affinis, Radfordia ensifera, Myocoptes musculinus), pinworms (Aspiculuris tetraptera, Syphacia obvelata, Syphacia muris), and Encephalitozoon cuniculi. Female laboratory mice were cohoused with pet-store mice for >3 wk in large rat cages to normalize microbial experience before introduction of male breeders. All mice were housed in Association for Assessment and Accreditation of Laboratory Animal Care–approved animal facilities at the University of Minnesota (BSL-1/BSL-2 for SPF mice and BSL-3 for cohoused mice). All animal use was performed per a University of Minnesota Institutional Animal Care and Use Committee–approved protocol (2106-39195A).

Analysis was performed on the LSR Fortessa (BD Biosciences). Data were analyzed with FlowJo Software version 10 (BD Biosciences). Abs used for flow cytometry included CD3 (145-2C11), CD4 (GK1.5), CD8 (53-6.7), CD34 (RAM34), CD44 (IM7), CD45.2 (104), CD62L (MEL-14), CD64a/b (X54-5/7.1), Gata3 (L50-823), I-A/I-E (2G9), IgM (II/41), Ly6G (18A), and RORγt (Q31-378) purchased from BD Biosciences; B220 (RA3-682), CD11b (M1/70), CD11c (N418), FOXP3 (FJK-16s), IgD (11-26c[11-26]), Ki67 (SolA15), Ly6G (1AB-Ly6G), NK1.1 (PK136), PD-1 (J43), and Ter119 (Ter119) purchased from Invitrogen; CD16 (S17011E), CD19 (6D5), CD138 (281-2), c-kit (ACK2), CXCR5 (L138D7), Flt-3 (A2F10), Ly6C (HK1.4), Sca-1 (E13-161.7), T-bet (4B10), and TCR γδ (GL3) purchased from BioLegend; and B220 (RA3-682), Ghost Dye Violet 510, and Ghost Dye Red 780 purchased from Tonbo.

Blood was collected in EDTA tubes and centrifuged at 1000 × g for 10 min. The plasma layer was removed and sent to the University of Minnesota Cytokine Reference laboratory for cytokines/chemokines quantification by Luminex magnetic bead immunoassay using the MILLIPLEX mouse 32-plex [G-CSF, GM-CSF, IFN-γ, IL-1α, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17, CXCL10/IP-10, CXCL1/KC, LIF, CXCL5/LIX, CCL2/MCP-1, M-CSF, CxCL9/MIG, CCL3/MIP-1α, CCL4/MIP-1β, CXCL2/MIP-2, CCL/5RANTES, TNF-α, VEGF, CCL11/Eotaxin; Millipore Sigma].

Listeria monocytogenes was grown to log phase in tryptic soy broth (TSB) supplemented with 50 μg/ml streptomycin. Mice were infected with 1 × 105 to 2 × 105 CFUs i.p. Four days postinfection, the spleens of infected animals were homogenized in 4 ml of 0.2% IGEPAL solution. Serial dilutions were plated on TSB agar supplemented with 50 μg/ml streptomycin for 24 h at 37°C, and the colonies were enumerated.

Splenocytes were cultured overnight in complete RPMI at 37°C and 5% CO2 to permit the isolation of myeloid cells by plastic adherence (10, 11). Nonplastic adherent cells were washed away with two washes of 5 ml PBS. Total RNA was isolated from the adherent myeloid cells using TRIzol reagent (Invitrogen, Carlsbad, CA), and 1 μg RNA was reverse transcribed into cDNA using random hexamers and Superscript III (Invitrogen, Carlsbad, CA). The resulting cDNA was used as a template for quantitative real-time PCR (qPCR) using TaqMan primer/probe sets for Tlr1, Tlr2, Tlr3, Tlr4, Tlr6, Cd14, Myd88, and 18s rRNA (Applied Biosystems).

Data were collected across multiple experiments performed over 2.5 y. GraphPad Prism 9 was used to perform statistical analysis. A two-tailed unpaired, nonparametric Mann–Whitney U test was used to compare two groups at a single time point. Simple linear regression analysis was used to test whether the slopes of cells or cytokines/chemokines over time were different between groups; *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

We cohoused female C57BL/6 background mice with female pet-store mice for >3 wk before breeding to ensure the dams acquired an experienced immune system and exposed new litters to the diverse microbial communities of pet-store mice from the earliest natural point (Fig. 1A). Breeding mice under NME conditions resulted in slight reductions in litter size and weight at weaning relative to litters born under conventional SPF conditions (Fig. 1B, 1C). We took a comprehensive and agnostic approach to measure the impact of NME on immune development using two flow cytometry panels to quantify 26 unique immune cell markers at three different ages: infancy (2 wk of age), weaning (3 wk of age), and adolescence (6 wk of age). We observed a 4.4-fold expansion of leukocyte numbers (CD45+) in the lymph nodes of NME mice relative to SPF mice by 6 wk of age (Fig. 2A). We subdivided this population into eight major immune cell types: CD4 T cells, CD8 T cells, B cells (CD19+), monocytes/macrophages (CD11b+), dendritic cells (CD11c+MHC class II+ [MHC II+]), neutrophils (Ly6G+), NK cells (NK1.1+), and γδ T cells (γδ TCR+). As expected, we observed a measurable expansion of most immune cell types in the lymph nodes (superficial cervical, axillary, brachial, inguinal, and mesenteric) of NME pups relative to SPF pups at 2 wk of age and found this gap widened through 3 and 6 wk of age (Fig. 2B–I). By 6 wk, all eight major immune cell types were significantly more numerous in NME mice relative to SPF mice. Neutrophils and NK cells demonstrated the greatest expansion, achieving a >8-fold expansion in NME mice over SPF mice (Fig. 2D, 2G). This disproportionate expansion resulted in neutrophils, NK cells, and monocytes/macrophages making up a larger proportion of the immune cells in NME mice than SPF mice, whereas CD4 T cells were less frequent at certain time points (Fig. 2D, 2E, 2G, 2H). In the spleen, the degree of NME-induced immune cell expansion was more modest than what was observed in the lymph nodes but followed similar trends (data not shown). These data reveal NME has a measurable impact on the immune system during early life, inducing global numerical expansion.

We next measured the effect of NME on CD8 T cell activation and memory commitment using a combination of standard murine markers of activation (CD44) and naive or central memory (CD62L). In the lymph nodes of NME mice, we observed more central memory T (Tcm; CD44+CD62L+) and effector (Teff)/effector memory CD8 T (Tem; CD44+CD62L) cells; however, we also observed an unexpected increase in the number of naive (CD44CD62L+) T cells (Fig. 3A–C). Compared with SPF mice, NME mice maintained higher proportions of activated CD8 T cells than SPF mice at each age (Fig. 3D). The lymph node–derived CD4 T cell population mirrored the CD8 T cell population with increased numbers and proportions of activated and memory committed CD4 T cells at each time point (Fig. 3E–H). Much like the CD8 T cells population, the naive CD4 population was larger in NME mice than SPF mice at 2 and 6 wk of age (Fig. 3E).

In addition to examining the extent of CD4 T cell activation and memory commitment, we also investigated the impact of NME on CD4 Th cell lineage commitment by assessing the expression of lineage-defining transcription factors. SPF mice maintained a steady level of ∼10% commitment of CD4 T cells to definable Th subsets in the lymph nodes throughout the study, whereas the proportion of polarized CD4 T cells in NME mice reached 15% by 6 wk (Fig. 4F). Foxp3-expressing regulatory T (Treg) cells exhibited a slight increase in number in NME mice relative to SPF mice at 2 wk but made up a similar proportion of total cells in the lymph node (Fig. 4A). However, by 6 wk, Treg cells in NME mice outnumbered those of SPF mice and were more frequent (Fig. 4A). We observed robust increases in the number and proportion of Th1 (Tbet+) cells in NME mice relative to SPF mice at all developmental stages (Fig. 4B). Th17 (RORγt+) and Th2 (Gata3+) cells were also significantly more numerous and made up a greater proportion of lymph node cells in NME mice than SPF mice at 2 and 6 wk (Fig. 4C, 4D). Finally, follicular helper T (Tfh; PD-1+CXCR5+) cells were more numerous in NME relative to SPF mice at each time point, although their relative proportion was not significantly different (Fig. 4E). In the spleen, the number and proportion of Th subsets were equivalent between NME and SPF mice through 3 wk; however, by 6 wk, NME mice displayed a slight increase in the number of each Th subset over SPF mice (data not shown). CD4 T cell phenotypes are often described in simplified terms of the Th1 versus Th2 dichotomy, intending to contrast the cellular and humoral potential of the immune system, respectively (12, 13). Low Th1:Th2 ratios are often associated with tolerance, like those observed in neonates and pregnant women, whereas higher Th1:Th2 ratios suggest a more proinflammatory immune environment (12, 13). We found the CD4 T cell compartment in NME mice was skewed toward a more proinflammatory ratio (Th1 and Th17: Treg, Th2, and Tfh) than SPF mice early in both the lymph node (Fig. 4G) and spleen (data not shown). Collectively, these data demonstrate microbial exposure during early life enhances T cell commitment to mature effector and memory lineages; however, it unexpectedly also increased the number of naive T cells.

T cell activation and lineage commitment are mediated by interactions with APCs. Therefore, we measured the influence of early-life microbial exposure on the activation status of the APC populations. When we analyzed the lymph node–derived monocyte/macrophage population (CD11b+CD11c) for the expression of activation markers Ly6C and MHC II, we identified five distinct populations: Ly6C+MHC II (P1), Ly6C+MHC IIint (P2), Ly6ClowMHC IIint (P3a), Ly6ClowMHC IIhi (P3b), and Ly6CMHC II (P4) (Fig. 5A–E). These populations correspond with the “waterfall” developmental progression pattern described in multiple organs, where the Ly6C+MHC II (P1) population is similar to blood monocytes that begin to express MHC II after activation to become Ly6C+MHC IIint (P2) (14–16). These cells then decrease Ly6C expression to extravasate and become P3 macrophages (14–16). We also observed distinct MHC IIint (P3a) and MHC IIhi (P3b) populations in the lymph node (Fig. 5D, 5E). The Ly6CMHC II population (P4) likely consists of mature macrophages and other rare immune cell lineages not effectively excluded by upstream gating (i.e., CD11b+ T cells and granulocytes) (14–16). Each of these five monocyte/macrophage subpopulations were more numerous in NME mice than SPF mice across all ages (Fig. 5A–E). Much like our observations with T cells, NME appeared to expand all macrophage subsets, even the least activated, P1 subset (Fig. 5A). When we considered the proportions of these populations in the lymph nodes, we observed several notable NME-induced alterations to the immune cell composition. Ly6C+MHC II (P1) cells made up a greater proportion of lymph cells early in NME pups but equaled SPF proportions by 6 wk (Fig. 5A, 5C). The Ly6CMHC II (P4) and Ly6ClowMHC IIint (P3a) population made up a larger proportion of lymph cells in NME pups at only the 3-wk time point (Fig. 5C, 5D), whereas the Ly6C+MHC IIint (P2) and Ly6ClowMHC IIhi (P3b) populations trended toward a larger proportion of lymph cells in NME mice at every developmental stage (Fig. 5B, 5D). Together, these data demonstrate that NME conditions broadly expand and activate monocytes/macrophages relative to SPF mice, likely facilitating the observed maturation of the T cell compartment.

Infant B cells produce less Ig, undergo less class switching, and produce fewer memory B cells and plasma cells in response to Ag than adult B cells. Although cell-intrinsic factors are involved, the relative paucity of Tfh cells and germinal centers are also contributing factors (17, 18). We observed a >2-fold increase in the quantity of Tfh cells in NME mice (Fig. 4E). To determine whether this NME-induced increase in Tfh cells correlated with enhanced B cell activation, we measured the expression of IgD and IgM among the CD19+B220+ B cell population to define IgD+IgM+ Ag-inexperienced naive B cells, IgDIgM+ immature B cells, IgD+IgM mature activated B cells, and IgDIgM class-switched B cells. All B cell subsets expanded in NME mice relative to SPF mice in the lymph node, resulting in a similar proportion at 2 and 3 wk (Fig. 6A–D). By 6 wk, class-switched (IgDIgM) B cells made up a larger proportion of lymph node cells in NME mice than SPF mice (Fig. 6C). Plasma cells are terminally differentiated B cells that secrete large amounts of Ab. Although plasma cells typically reside in the bone marrow, they are generated in the germinal centers of the spleen and lymph nodes. We found NME mice had increased numbers of plasma cells (B220CD19CD138+) at 3 and 6 wk of age in the lymph node (Fig. 6F) and spleen (data not shown) compared with SPF mice. Ab production was also greater in NME mice than SPF mice at 3 wk of age as measured by total IgG ELISA (Fig. 6G). Altogether, our observations suggest NME conditions expand all B cell populations and augment B cell activation and germinal center activity during early life.

The observation that all immune cell types were expanded in NME mice, including multiple naive immune cell populations (Figs. 3A, 3E, 5A, 6B), led us to investigate whether NME conditions influence the production of hematopoietic stem cells and progenitors (HSCPs). LSK (LinSca-1+c-Kit+) cells, defined by the lack of expression of mature immune cell markers (Lin) and the coexpression of Sca-1 and c-Kit, include multipotent progenitor (MPP) cell subsets 1–4, which give rise to oligopotent progenitors: common lymphoid progenitors (CLPs), granulocyte–monocyte progenitors, and megakaryocyte-erythroid progenitors (MEPs) (Fig. 7A) (19). We enumerated LSK cells in the bone marrow of 3-d-old NME and SPF pups and found NME pups had more LSK cells than SPF pups, indicating NME conditions stimulated expansion of HSPCs (Fig. 7B). Enumeration of Lin, Sca-1+, c-kit+, CD34, Flt3 cells, which fit the profile of hematopoietic stem cells (HSCs) thought to have the broadest differentiation potential, were not as robustly expanded but did trend toward increased numbers in NME mice compared with SPF mice (Fig. 7B). Given that NME broadly induced expansion of many leukocyte subsets, we investigated whether oligopotent progenitor subsets were also expanded. We identified a population of Lin, Sca-1+, c-kit+, CD34+, Flt3hi-expressing cells enriched for MPP4 cells, also referred to as lympho-myeloid primed progenitors (LMPPs) (20), which are thought to give rise to oligopotent CLPs (enriched for this study by Lin, Sca-1lo, c-kitlo, Flt3+) that differentiate into lymphocytes. Both the MPP4/LMPP and CLP populations were expanded in NME mice relative to SPF mice (Fig. 7D, 7G). Likewise, granulocyte–monocyte progenitor (Lin, Sca-1, c-kit+, CD16+, CD34+) cells, which differentiate into granulocytes and monocytes, were also expanded in NME mice relative to SPF mice (Fig. 7E). Conversely, the number of MEP cells, which differentiate into platelets and RBCs, were not altered by NME conditions, indicating a bias toward leukocyte expansion (Fig. 7F). Altogether, these observations suggest that physiological microbial experience during early life stimulates production of the earliest immune cell progenitors, which may promote the expansion of both innate and adaptive immune cells.

To gain insight into the possible signaling pathways orchestrating immune cell expansion and activation in NME mice, we measured the concentrations of 32 cytokines and chemokines in the plasma from NME and SPF mice at 3 and 6 wk of age. At 3 wk, NME mice displayed elevated plasma levels of IL-6, IL-17, G-CSF, and CCL5 over SPF mice. By 6 wk, 22 of 32 cytokines/chemokines tested were elevated in NME mice over SPF mice (Fig. 8A, Supplemental Fig. 1). CCL11, an eosinophil chemoattractant, was the only chemokine that demonstrated decreased plasma levels in NME mice relative to SPF mice (Fig. 8A, Supplemental Fig. 1). Individual cytokines and chemokines followed similar trends in NME and SPF mice from 3 to 6 wk, although NME mice displayed more exaggerated slopes for IL-4, VEGF, IL-12p70, LIF, IL-17, IL-10, M-CSF, GM-CSF, CCL3, IL-15, IL-9, and CCL11 (Supplemental Fig. 1). Notably, plasma levels of TNF-α in 3-wk-old NME pups were equivalent to those of 6-wk-old SPF mice, suggesting NME induced earlier expression of TNF-α than SPF conditions (Supplemental Fig. 1). Age-associated increases in IFN-γ are also well documented (21–25). Our analysis revealed 15% of 3-wk-old NME pups displayed unusually high levels of plasma IFN-γ, whereas no SPF pups had detectable serum levels of IFN-γ (Supplemental Fig. 1). Furthermore, IFN-γ was never detected in 6-wk-old SPF pups, whereas two-thirds of 6-wk-old NME mice registered detectable plasma IFN-γ levels (Supplemental Fig. 1).

PRRs recognize conserved pathogen-associated molecular patterns (PAMPs). PRRs are expressed by a wide variety of mammalian cells but are most often associated with innate immune cells. PRRs play a crucial role in early detection of pathogens and the initiation immune responses by directing the expression of cytokines and transcription factors. PAMP stimulation is known to induce upregulation of PRRs, although the extent to which diverse microbial exposure alters PRR profiles during early life has not been described. We harvested cDNA from adherent splenocytes and measured the expression of a panel of PRRs and downstream signaling proteins by qPCR. We found multiple TLRs were upregulated, including membrane-bound TLR2, which can heterodimerize with TLR1 and TLR6 to recognize a wide variety of PAMPs. TLR2 binding partner TLR6 and TLR signal adapter protein MyD88 were also significantly upregulated. TLR3, an endosomal TLR that recognized dsRNA and signals through TRAM/TRIF instead of MyD88, also demonstrated increased expression in NME mice compared with SPF mice (Fig. 8B). These data suggest NME conditions increased the sensitivity of myeloid cells to some PAMPs, which might begin to explain the differences between NME and SPF cytokine profiles and downstream activation of immune cells.

In prior studies, cohousing adult laboratory mice with pet-store mice improved bacterial clearance after challenge with a virulent strain of Listeria monocytogenes, a bacterial strain commonly used to assess immune function in mouse models and a pathogen in human infants (26–28). Importantly, L. monocytogenes has not been observed to be a part of the natural ecology of pet-store mice in our colony; therefore, to our knowledge, L. monocytogenes challenge represents a novel pathogen under these conditions (27). We challenged 3-wk-old NME and SPF pups with L. monocytogenes and measured bacterial burden in the spleen 4 d postinfection. Much like the adult cohoused mice, 3-wk-old NME pups demonstrated a >2 log reduction in bacterial burden compared with their age-matched SPF counterparts (Fig. 8C). These data show microbial experience during early life exerts not only a quantitative impact on basal immunity but also improves protective immune function.

NME broadly and dramatically increased the quantity of immune cells. As expected, we observed NME-induced increases in the number of activated macrophages and lymphocytes, suggesting proliferation in response to microbial exposure expands the number of immune cells. However, we also observed more naive lymphocytes and undifferentiated macrophages/monocytes, implying some other mechanism must contribute to the observed expansion of immune cells. Enumeration of HSCPs in the bone marrow indicated NME also increased the size of multiple immune cell progenitor subsets, including LSK (inclusive of HSCs and MPPs) and oligopotent progenitors, granulocyte–monocyte progenitor, and CLP, demonstrating NME broadly expanded immune cell progenitors. It is well established that inflammation can modulate hematopoiesis (29–32). Multiple proinflammatory cytokines augment hematopoiesis in vivo, including cytokines that we observed to be induced by NME: IL-6 (3 and 6 wk), IL-17 (3 and 6 wk), G-CSF (3 and 6 wk), TNF-α (6 wk), M-CSF (6 wk), GM-CSF (6 wk), and IFN-γ (6 wk) (29–32). HSCPs have also been demonstrated to express TLRs and may therefore sense PAMPs directly (31, 33). It has been hypothesized that microbial sensing by HSPCs helps to replenish depleted innate cells, which lack the proliferative capacity of many adaptive cells, during system infections (33). However, our observations suggest NME induces the production of HSPCs with broad lineage commitment potential, including both innate and adaptive cell lineages. In line with our observations in NME mice, recently published research found that administering poly(I:C) to the mother during gestation to mimic viral infection induced inflammatory cytokine-mediated expansion of fetal lymphoid progenitors (34).

The newborn immune system is characterized by broad immunosuppression (35, 36). Compared with the immune systems of mice raised in low microbial burden conditions, the immune systems of mice exposed to microbially diverse environments from conception demonstrated improved immune responsiveness. Indeed, when we challenged recently weaned NME and SPF mice with a previously unencountered bacterial pathogen (i.e., virulent L. monocytogenes), NME mice cleared the infection more rapidly. Because L. monocytogenes has not been observed in our NME colony, it is less likely that persistent passively transferred L. monocytogenes–specific maternal Ab contributed to bacterial clearance. A hallmark of infant immunity is a reduced ability to produce Th1 and memory T cell responses. Our data show T cells from NME mice commit to Th1 and memory more often than those of SPF mice, making up a greater proportion of the T cell compartment throughout development. Likewise, germinal center function is considered deficient in infants. However, NME conditions enhanced class switching, plasma cell differentiation, and Ab production. Infant cytokine profiles also differ from those of adults, favoring anti-inflammatory over proinflammatory cytokines (36–38). NME conditions stimulated more robust and in some cases earlier expression of proinflammatory cytokines compared with SPF counterparts. One interpretation of these observations is that diverse microbial exposure during early life accelerates immune maturation; alternatively, microbial experience may be inducing trained immunity, whereby immune stimuli enhance innate immunity, heightening immune responsiveness and supporting adaptive responses. Although the two concepts share many features, trained immunity is not thought to be permanent, whereas immune maturation would be expected to result in enduring and progressive change. Continued tracking, manipulation of the timing of microbial exposure, and comparisons of epigenetic profiles might provide insights into whether NME induces trained immunity, accelerates immune maturation, or both. We noted multiple parallels between immunological changes induced by Mycobacterium bovis bacillus Calmette-Guérin (BCG) vaccination in human infants and those of mice raised in NME conditions. Like NME, BCG induces Th1-memory responses and proinflammatory cytokines and provides immunity to nonmycobacterial pathogens (17, 39, 40). The BCG vaccine is thought to invoke superior long-term innate immune function because it stimulates five different TLRs, perhaps triggering multiple microbial-sensing pathways in a manner similar to NME conditions (40). The BCG vaccine might thus be a real-world example of the impact of microbial stimulation on infant immunity and a precedent for applying this concept to improve infant immunity. However, the BCG vaccine consists of a singular weakened strain of tuberculosis bacteria and is administered only once, typically between 4 and 6 wk of age; therefore, it may serve to supplement the diverse microbes naturally encountered by human infants.

Cytokines are key regulators of immune responses. Cohousing adult laboratory mice with pet-store mice induced greater expression of numerous cytokines/chemokines (27). Conversely, when we analyzed 3-wk-old NME mice, we observed increased expression of only 4 of 32 cytokines/chemokines measured. However, by 6 wk of age, most of the cytokines/chemokines were augmented by NME conditions, demonstrating age-restricted effects of NME on plasma cytokine expression. Multiple infant immune cells have reduced capacity to produce proinflammatory cytokines, leading to a cytokine profile skewed toward Th2-associated and anti-inflammatory cytokines, which could explain the limited effect of NME at 3 wk of age (21, 23, 35–37, 41). Age-dependent expression of several cytokines has been described, most notably, TNF-α, IFN-γ, and IL-12 increase with age, whereas IL-6 and IL-10 display a bimodal expression pattern (21–25, 35, 41). In line with this literature, we observed an increase in TNF-α expression between 3 and 6 wk of age. Interestingly, TNF-α levels in 3-wk-old NME mice were equivalent to that of 6-wk-old SPF mice, suggesting NME conditions induce precocious expression of TNF-α. IL-6, an anti-inflammatory and Th2-polarizing cytokine, appeared to decrease in NME and SPF mice from 3 to 6 wk. The opposing functional, temporal relationships and the pleotropic effects of IL-6 and TNF-α could signify important roles for these cytokines in immune development (25). Indeed, the TNF superfamily was recently identified as an important modulator of early-life immune development (42).

Altogether, we found exposure to diverse microorganisms from conception has a prodigious impact on mammalian immune development. The combined effect broadly activated the innate and adaptive arms of immunity and improved immune function. Microbial experience is a major contributor to immune development; however, the multiple mechanisms that orchestrate immune development are still unresolved. Many questions about the complex immunology of healthy pregnancy, infection, preeclampsia, and premature birth have been difficult to answer with conventional animal models. NME could provide a more faithful model of normal pregnancy immunology, vertical transfer of immunity, and maternal vaccination strategies. Furthermore, some features of newborn mice are underdeveloped relative to newborn humans such that they more closely resemble preterm infants, who are 10–19% more likely to suffer severe complications from infection than term infants (43–47). NME conditions may better model the complex microbial ecology of preterm infant infections. Better understanding of the deficiencies and strengths of infant immunity could uncover novel developmental stage-specific treatments and preventions to reduce infant hospitalization and deaths from infection. The ability to evaluate and appropriately support immune development could help close the gap between premature and term infant immune function. The data herein provide the foundation and improved model for these future studies. Although vital differences still exist between the NME model and human immune development, NME provides a unified model of natural immune development that complements SPF research and could prove invaluable as a preclinical model.

NME is inherently variable, and although serology identifies the presence of many pathogens, including bacteria, viruses, and parasites, many more cannot be identified, making it difficult to interrogate microbe-specific effects. Ongoing research is investigating how NME conditions alter the formation of the infant microbiome. We view microbial variability as a key feature of the model that better replicates natural development; however, it can complicate interpretation. Importantly, despite this variability, many of the metrics tested in this study display similar variance among NME mice as was observed in SPF mice.

Advancements in transcriptomics and proteomics have led to changes in how HSCPs are subcategorized and defined (19). The HSCP flow cytometry panel we used in this study is limited. As such, some populations, although enriched for the cells of interest, may not be pure or may be referred to by different names in the literature. In addition, inflammation can induce the expression of Sca-1 in otherwise Sca-1 progenitor populations, including granulocyte–monocyte progenitors. These points raise the possibility that the LSK population of NME mice, although it may be more representative of physiological conditions, could contain granulocyte–monocyte progenitor cells, confounding interpretation (48).

Our experiments were designed to capture the levels of cytokines/chemokines induced by NME conditions; we did not assess the total capacity of immune cells to produce an individual cytokine/chemokine. Ex vivo stimulation or cytokine reporter mice might demonstrate age-related deficiencies in cytokine/chemokine production more clearly and could reveal whether NME-induced increases in cytokine/chemokine expression represent augmented capacity or reflect increased stimulation within the same limits of SPF conditions. Plasma cytokine/chemokine profiles are helpful for understanding systemic characteristics of the immune system, but they do not necessarily correspond to the cytokine/chemokine profiles of bone marrow or sites of infection. Deeper analyses will have to be performed to investigate how NME alters the profiles of specific microenvironments.

The “hygiene hypothesis” and “neonatal window of opportunity” posit that a perinatal period exists during which microbial exposures have the greatest impact on immune development (49–51). Increasingly, clean human environments are thought to limit immune activation during childhood, preventing appropriate immune development that leads to future immunopathology in the form of asthma, allergy, and/or autoimmunity (49–52). Our data clearly demonstrate a potent effect of diverse microbial experiences on early-life immune development, but the current research does not address the impact on future immune health or immunopathology. Although previous studies investigated the effects of cohousing adult laboratory mice with pet-store mice, we do not directly compare the two models in this study (26, 27, 53). It is possible the unique function of the early-life immune system could establish a very different baseline in response to diverse microbial experiences that cannot be achieved by microbial experience later in life. Multiple studies support the idea that early-life exposures can have long-term impacts on immunity, some of which cannot be replicated by similar exposures later in life (4–9, 54, 55). However, the period of optimum effect in the context of diverse microbial exposure and normal immune development has yet to be defined. The NME model could provide a system in which the timing of diverse microbial exposure can be manipulated to determine whether a window of optimum microbial experience exists during development.

The authors have no financial conflicts of interest.

We extend gratitude to the University of Minnesota Flow Cytometry Core, Research Animal Resources (RAR), Cytokine Reference Lab, and the Center for Immunology for support and thanks to Dr. Bryce Binstadt for critical review and suggestions regarding the manuscript.

This work was supported by the awards from the University of Minnesota Department of Pediatrics, the Masonic Cross-Departmental Grant in Children’s Health Research (to N.J.S. and S.E.H.) and Pediatrics “R” Award (to N.J.S.); the University of Minnesota Undergraduate Research Opportunities Program (to T.S.); National Institute of General Medical Sciences, National Institutes of Health Grant GM140881 (to T.S.G.); Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health Grant R01AI155468 (to S.E.H.), and a U.S. Department of Veterans Affairs Merit Review Award I01BX001324 (to T.S.G.). T.S.G. is the recipient of a Research Career Scientist award (IK6BX006192) from the U.S. Department of Veterans Affairs.

The online version of this article contains supplemental material.

B6

C57BL/6J

bCG

bacillus Calmette-Guérin

CLP

common lymphoid progenitor

HSCP

hematopoietic stem cell and progenitor

LMPP

lympho-myeloid primed progenitor

LSK

LinSca-1+c-Kit+

MEP

megakaryocyte-erythroid progenitor

MHC II+

MHC class II+

MPP

multipotent progenitor

NME

natural microbial exposure

PAMP

pathogen-associated molecular pattern

PRR

pattern recognition receptor

qPCR

quantitative real-time PCR

SPF

specific pathogen-free

Tcm

central memory T

Teff

effector CD8 T

Tem

memory CD8 T

Tfh

follicular Th

Treg

regulatory T

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Supplementary data