The gut microbiota influences host responses at practically every level, and as research into host-microbe interactions expands, it is not surprising that we are uncovering similar roles for the microbiota at other barrier sites, such as the lung and skin. Using standard laboratory mice to assess host-microbe interactions, or even host intrinsic responses, can be challenging, as slight variations in the microbiota can affect experimental outcomes. When it comes to designing and selecting an appropriate level of microbial diversity and community structure for colonization of our laboratory rodents, we have more choices available to us than ever before. Here we will discuss the different approaches used to modulate microbial complexity that are available to study host-microbe interactions. We will describe how different models have been used to answer distinct biological questions, covering the entire microbial spectrum, from germ-free to wild.
In recent decades, we have begun to uncover the extensive reach that host-microbe interactions have on our health, and a spotlight has been shone on our once “forgotten organ”, the microbiota. Novel technologies, methodologies and in vivo microbiome manipulation now allow us to explore host-microbe interactions in detail, leading to the question of which method is best to unravel the impact of the complex interplay between host and microbes. Should one take a reductionist approach, using gnotobiotic animals to tease out the effects of specific microbes or microbial metabolites, or should we embrace more complex paradigms, such as the wild microbiome, with the aim of more accurately recapitulating the human condition? Of course, the answer is simple: it depends. Each layer of microbial complexity adds dimension and nuance to the field. In this review, we will discuss the context-dependent benefits of the different approaches available to study host-microbe interactions in vivo and examine how models with varying microbial complexity (from germ-free to wild) have been used to make key advances in biomedical research.
Out with the old? Specific pathogen free models
Since its advent in the 1960s, the specific pathogen free (SPF) model has become the gold standard for laboratory animal research. The history of this model and the advantages of using animals free of pathogens for advancing biomedical research have been reviewed extensively. In general, although ubiquitous in animal facilities across the globe, the SPF model has some major pitfalls that shouldn’t be overlooked. These pitfalls are part of the reason for the diversification of methodologies used to study host-microbe interactions in vivo (Fig. 1).
Relatively speaking, the SPF microbiota is considered complex and diverse. In the main, colonization resistance renders the intestinal niche inaccessible to opportunistic pathogens, but also to the introduction of microbial species of interest. As such, whether they are used to induce dysbiosis or to create an empty niche prior to the introduction of novel microbes, microbial manipulation in SPF animals usually requires antibiotics. Unfortunately, these can have confounding, off-target effects on the host’s immune system and effects on off-target microbes that are difficult to control,1 thus limiting the effectiveness of using SPF animals to study host-microbe interactions. Even when experimental questions do not relate to the microbiome directly, the gut microbiota has a broad reach and variations in composition can both skew experimental outcomes and hamper experimental reproducibility. This might not be a problem if the SPF microbiota were standardized. However, there is enormous variability in the SPF gut microbiome composition from one facility to the next. Substantial differences in microbiome composition can even exist within barrier facilities: from one room to the next, or even from one cage to its neighbor. In fact, this specific pitfall has been utilized to identify novel host-microbe interactions. In 2009, Ivanov and colleagues discovered a large discrepancy between the abundance of mucosal T helper 17 (Th17) cells in two commercially available SPF C57BL/6 wild-type strains of mice.2 Although genetically identical, only one group of mice were colonized with segmented filamentous bacteria (SFB) in their terminal ileums. This turned out to be a driving force behind Th17 cell induction in SPF mice from Taconic, not just locally but systemically.2 Not only does this demonstrate that a single difference in microbiome community structure can drastically affect immune responses, but that vender-specific differences in the SPF microbiota can act as confounding experimental factors. In the case of SFB, this is likely to be particularly important for models where Th17 cells play prominent protective or pathological roles.3 In addition to housing and commercial sources, genetic differences can also influence colonization. We may never know how many manuscripts have been published that erroneously link biological phenotypes to genotype, when instead they could have been microbially mediated.
Arguably, one of the greatest challenges with animal research is that findings often fail to be translated to the clinic.4,5 Is this because humans and mice are fundamentally different, or does the SPF microbiota fall short of mimicking the human microbiota? Recent work shows a distinct “immature” phenotype of immunological responses in SPF mice compared to wild mice, laboratory mice with wild microbiomes or adult humans.6 These findings suggest that greater microbial diversity might be required for optimal immune system education and, thus, the full translational potential of laboratory rodents. This will be discussed in more depth below.
Coupling the above pitfalls with the newfound importance of the gut microbiome in host health and wellbeing, should we continue using SPF models? Is it time we moved away from the ‘old’ and set our sights on new methodologies? The truth is that, despite limitations, the SPF model has been an affordable, accessible workhorse in biomedical research, and it isn’t going anywhere anytime soon. Discoveries have been made using SPF rodents that have shed light on host-microbe interactions in barrier tissues including gut,7,8,9 lung,10,11,12,13 skin14,15 and beyond. For example, a recent publication by Hosang and colleagues used intratracheal antibiotics to deplete the microbiome locally in the lung, but not in the gut. In doing so, they demonstrated a role for the lung microbiome in modulating susceptibility to experimental autoimmune encephalitis (EAE), a murine model of multiple sclerosis.12 This seminal study provides evidence that the lung microbiome may have a more prominent role in immune function than was previously appreciated, and that targeting the lung microbiome might be a potential novel therapeutic approach.
Findings from studies using SPF mice have also paved the way for further research using more definitive approaches, such as gnotobiotics, to limit microbial diversity and richness. For example, in 2015 and 2016, the use of antibiotics in pregnant SPF dams was used to link the maternal microbiota to type I diabetes susceptibility in the offspring.16,17 Although these studies don’t rule out the confounding effect of the pups’ own microbiota, they represented a breakthrough for the “developmental origins of health and disease” hypothesis and were amongst several publications that sparked a widespread interest into the maternal microbiome, as well as follow up studies using gnotobiotic models. Thus, although a useful and accessible tool, it is important to remember and control for the confounding effects of antibiotic use and community variabilities, and to diversify as new methodologies become more and more accessible.
In with the new? Gnotobiotic models
The term “gnotobiotic” is based on the Greek words “gnotos” (known) and “bios” (life); i.e., a defined microbiota. This covers everything from axenic or germ-free (GF) models, where animals are maintained in a sterile environment from birth, up to models using a more diverse, but controlled microbial consortia consisting of many species. Although not technically new, the technology required to maintain animals under GF conditions is now becoming more accessible to the average research lab. The power of having gnotobiotic models is that they allow us to: (i) unequivocally attribute host biological phenotypes to the microbiota, and (ii) investigate the effects of specific microbes or metabolites in vivo, either alone or in concert. The simplicity and specificity of these models render them a powerful tool for mechanistic studies into host-microbe interactions (Fig. 1).
Lessons from germ-free mice
As research into the effects of the microbiome on mucosal immunity has steadily increased over the past several years, so too has the use of GF mouse models. Devoid of all microorganisms, GF mice are the perfect tool for studying physiological, immunological, and neurological development and function in the absence of a microbiome. Building upon studies made using antibiotics to deplete the microbiota in SPF mice, GF research has revealed that the microbiome plays a role in shaping virtually every biological system. Since a comparison of GF mice and antibiotics treatment has recently been performed,18 we will focus here on the use of GF mice to crystalize our understanding of microbial involvement in host responses.
A guiding hand in local physiological development
The gastrointestinal (GI) tract has the largest mucosal surface of the body as well as the largest bacterial community.19 Therefore, it is not surprising to find major changes in the GI tract in the absence of microbes. GF mice exhibit architectural and functional abnormalities along the GI tract, such as increased small intestinal villi length, an enlarged cecum, altered mucus layers, and slower peristalsis.20 The maturation signals for gut-associated lymphoid tissues (GALTs) are absent, leading to smaller Peyer’s patches and mesenteric lymph nodes (MLN).21 In contrast, no major morphological changes have been observed in other barrier sites, such as the skin or the lung, likely due to increased barrier thickness and/or lower microbial abundance.
Immune system education and maturation
Our immune system is heavily influenced by signals from the microbiome, which is apparent when one compares the immune system of GF mice to that of their SPF counterparts. One of the most prominent phenotypes associated with GF mice is their immature immune system. They are ill-equipped to handle microbial colonization, as evidenced by the reduced expression of antimicrobial peptides at barrier sites.22,23,24 The innate immune cell landscape is also changed. This is best characterized in the intestine, which has fewer macrophages, mast cells, mucosal-associated invariant T (MAIT) cells, and in most reports, subsets of group-3 innate lymphocyte cells (ILC3).25,26,27,28,29 Interestingly, the intrathymic development of MAIT cells requires presentation of a microbiota-derived metabolite.30 The innate immune cells present in the gut also exhibit an immature phenotype, with macrophages lacking the hypo-responsiveness to lipopolysaccharide (LPS) necessary to tolerate the commensal microbiota and ILC3 failing to produce the necessary levels of IL-22 required for host defence, even after stimulation.24,31,32 Collectively, these studies demonstrate that microbial cues are required to instruct and train innate immunity in the gut, however, the impact of the microbiome on innate immune cell function is likely to be global, particularly due to the dysregulated hematopoiesis observed in the GF bone marrow (for review, see McCoy and Thomson.33) Indeed, similar innate immune system deficits have been reported in other barrier sites, such as the skin27,34 and the lung,27 as well as the spleen,35 liver36 and brain37 of GF mice.
The intestine hosts a richly populated and highly specialized adaptive immune system, which must strike a balance between protection from pathogens and tolerance of commensal microbes and food antigens. It is not surprising that microbes have a hand in maintaining this balance. In the absence of a microbiota, fewer effector T cells patrol the lamina propria38 and fewer regulatory T cells protect the colon.38,39,40 Antibody responses are disrupted, with fewer IgA-producing plasma cells populating the GALT, lamina propria, lung and bone marrow41 and reduced circulating levels of all antibody classes with the exception of IgE, which is pathologically elevated.42,43 To summarize, GF mice can be used to elegantly demonstrate the requirement of microbial cues in immune education and training.
Identifying a critical window in immune development
Maintaining gnotobiotic conditions has been a useful tool for facilitating the controlled introduction of a microbiota at different periods of development. While many of the immunological deficits associated with GF mice can be rescued by colonization anytime in life, some phenotypes can only be reversed if mice are colonized in early life. For example, the immunological maturation that coincides with a substantial shift in microbiome composition at weaning, termed the “weaning reaction”, depends on early-life colonization.44,45 Weaning appears to be a crucial time for microbe-mediated immune education, as colonization before but not directly after weaning had a lasting effect on mucosal immune responses, protecting mice from several experimental inflammatory models and tumor formation.44,45 Exposing neonatal, but not adult, GF mice to an SPF microbiota has been shown to reverse the life-long over-representation of invariant natural killer T cells in the lungs and colon, thereby protecting them from the induction of experimental asthma or colitis.46 Likewise, exposure to a 5-species consortium of commensal bacteria rescued the MAIT cell deficiency observed in the skin of GF mice, but only if the mice were recolonized as neonates.27 Neonatal colonization with a diverse microbiota was required to reverse the characteristic “hyper-IgE” phenotype associated with GF mice.42
This critical period of microbe-mediated immune education may also be influenced by the lung microbiota. Despite having a lower biomass compared to other barrier sites, such as the GI tract,47,48 compelling evidence is beginning to emerge that highlights the importance of the lung microbiome in immune function and pathology. By monitoring lung microbiome composition and immune phenotypes in the lung over time, Golwitzer et al. demonstrated that lung microbiome formation and maturation during this critical window is important for inhibiting allergic airway inflammation in mice.49 It should be noted, however, that while numerous studies have attempted to attribute pulmonary phenotypes to the lung microbiome using GF mice,50,51 these studies can be difficult to interpret as the absence of a gut microbiome has widespread effects on host immune function.
Collectively, these observations have considerable clinical relevance considering the compelling epidemiological studies showing a link between childhood dysbiosis and the development of inflammatory disorders later in life. Collectively, these studies suggest that a critical window of opportunity exists early in life, when the establishment and maintenance of a healthy, diverse microbiota is crucial for long-term health outcomes.
Elucidating dietary effects on immune status independent from the microbiota
While eliminating the microbiome can help tease apart the contribution microbial antigens play in immune responses, it also provides an opportunity to determine how dietary antigens and/or environmental components can modulate immune responses independently of the microbiome. It is important to note that autoclaving or irradiating food and bedding does not eliminate microbial DNA, antigens, or endotoxins, all of which can induce expansion of B and T cells in the GALT, alter humeral responses and possibly impact the development of experimental inflammatory diseases.52,53 The relative contribution of microbial, dietary, and environmental components to antigen-specific immune responses can be dissected by feeding GF mice diets that are devoid of dietary antigens and/or microbial products. For example, feeding GF mice a diet consisting of extensively hydrolyzed protein did not limit the hyper-IgE phenotype normally observed in GF mice.42 However, feeding GF mice a chemically defined antigen free diet completely abrogated hyper-IgE, suggesting that the hyper-IgE phenotype in GF mice is driven by food antigens.54 IgA levels also appear to be influenced by dietary antigens. Bunker et al. found that absence of dietary antigens partially reduced the number of IgA+ plasma cells present in the small intestines of GF mice fed a chemically defined antigen-free diet, however, this had no bearing on levels of luminal IgA.41 Moreover, Hara et al. found that dietary antigens induced T follicular helper cells and germinal centre B cells in the Peyer’s patches leading to increased IgA production in the small intestine.55 Food antigens are also responsible for the induction and maintenance of Tregs in the small intestine. Although the GF colon is depleted of extra-thymic Tregs, Treg numbers in the small intestine of GF mice remain intact, as demonstrated by Kim et al., who fed GF and SPF mice an elemental diet and noted a marked reduction of Tregs in the small intestine, regardless of colonization state.39 These studies show the need for careful consideration of the various factors that influence intestinal immune responses, especially in the small intestine where dietary antigens are plentiful.
GF mice can be a useful tool to assess the role of specific metabolites on host responses in the absence of a metabolically active microbiome. Short chain fatty acids (SCFA) are generally considered to be beneficial, immunoregulatory small molecules, produced by the microbiota following the fermentation of dietary fibres. However, this seems to be dose- and context-dependent. Although butyrate is a potent inducer of Tregs,56 Kespohl et al. demonstrated that high doses of butyrate could drive acetylation at Foxp3, Ifng and Tbx21 (T-bet) promotor sites, resulting in increased IFNγ expression by T cells. Feeding butyrate to GF mice resulted in increased Th1 responses and exacerbated dextran-sodium sulfate (DSS)-induced colitis.57 Oral administration of succinate to GF mice has been shown to be sufficient to drive tuft cell hyperplasia, which may have downstream effects on Th2 responses.58 Metabolites are small and can easily transverse epithelial and endothelial barriers. As such, their effects are not restricted to the intestinal lamina propria and several studies have demonstrated that oral metabolite administration can remotely influence central nervous system (CNS) responses, including blood-brain barrier permeability, microglial cell maturation and neuroinflammation.37,59,60 Although these studies highlight a key component of the gut-brain axis, discussing them in full is outside the scope of this review. It is important to note that oral metabolite administration may not be a true reflection of metabolite production in the colon, as much will be taken up in the small intestine, which induces a distinct immunological response.61,62
Restricting the microbiota to one or a few known species has some key advantages over SPF models. Experimental variables are markedly lessened, and specific research questions can be addressed that have helped researchers uncover novel scientific discoveries and mechanistic insights that would have been difficult in conventionally colonized animals.
Transient microbial exposure
Building on re-colonization studies, an elegant method to study the effects of timing is to use transient methods of colonization, for example using auxotrophic microbes that cannot survive in vivo. In 2010, Hapfelmeier and colleagues genetically engineered an auxotrophic strain of Escherichia coli and used it to demonstrate the dynamics of microbially-induced IgA responses in vivo.63 More recently, we have used this model to transiently colonize GF dams during pregnancy to investigate the specific effects of the maternal microbiome on immune system development in the offspring. As dams were given sufficient time to return to GF status before giving birth to GF pups, exposure of the pups to microbial molecules could only occur in utero and via the milk. From this, we established that the mother’s microbiota primes the intestine for colonization by inducing transcriptional reprogramming that included the upregulation of genes encoding antimicrobial peptides. Microbial signals from mom also increased numbers of intestinal macrophages and NKp46+ ILC3. These changes, which were dependent on maternal antibodies, were associated with a reduction in inflammation and bacterial translocation when pups were colonized with commensal microbes later in life.64 Since this work was published in 2016, manuscripts have emerged that demonstrate a key role for the maternal microbiota in modulating metabolism, susceptibility to metabolic syndrome and anti-viral immunity in the offspring.65,66 Rather than using gnotobiotic conditions, these latter studies used surgical caesarian sections and cross-fostering experiments to attribute biological phenotypes to the maternal microbiome.
Simplification of the mouse microbiome to a single strain of bacteria allows in depth, precise testing of how a single strain of bacteria can contribute to the immune response. This has been pivotal for determining the microbial factors driving CD4+ T cell differentiation into T helper (Th) subsets. One keystone example of this was the discovery that SFB can single-handedly induce Th17 responses in vivo.2 SFB is now used as a model Th17 cell inducer and mice monocolonized with SFB are used to further investigate Th17 responses, as well as other changes to the adaptive immune system, such as germinal centre expansion and IgA induction.67,68,69 Tan et al. used gnotobiotic monocolonizations to screen the ability of numerous human commensals to induce a Th17 response in GF mice, and identified Bifidobacterium adolescentis as a potent inducer, on par with SFB.70 Candidate microbes that induce other Th subsets have similarly been used to monocolonize GF mice, and this has shed light on microbial regulation of T cell differentiation, particularly that of inducible Tregs. For example, by activating TLR2, Bifidobacterium bifidum and Bacteroides fragilis share the capacity to induce Tregs in a polysaccharide-dependent manner.71,72 The ability of individual microbes to shape CD4+ T cell differentiation in vivo has been reviewed extensively recently.73
Monocolonizations are frequently used to study the immunomodulatory roles of specific metabolites. For example, feeding different SCFAs to mice monocolonized with either E. coli or Bacteroides thetaiotaomicron revealed that acetate selectively induces a T cell-dependent IgA response to E. coli but not to B. theta.74 Our group also showed that monocolonization with Bifidobacterium pseudolongum, isolated from colorectal tumors following immune checkpoint blockade, increased the efficacy of anti-tumor immunotherapy.75 B. pseudolongum produced the metabolite inosine, which translocated the intestinal barrier and had a direct effect on T cells via the adenosine 2A receptor (A2AR). A2AR activation increased IFN-γ production by CD4+ and CD8+ T cells, enhancing antitumour immunity. Such gnotobiotic experiments demonstrate how a reductionist approach can be used to gain mechanistic insights that can be exploited for translational benefit.
Research using monocolonizations to study host-microbe interactions at mucosal sites is extensive and covering it all would be outside the scope of this review. Notably, however, Geva-Zatorsky et al. characterized the immunological impact of monocolonizing mice with 53 human commensals.76 Despite potential limitations of colonizing mice with human microbes77 (discussed below), these microbes induced immunological and transcriptional changes that were independent of phylogeny, demonstrating the functional redundancy present in our microbiomes. Interestingly, when comparing the effects of colonization with a mouse microbiota to colonization with a human microbiota, Gaboriau-Routhiau et al. found less functional redundancy with a species-specific microbiota.78 Of note, the functional redundancy for metabolic functions appeared greater than for immunological changes.
Simple, defined microbial communities
Whether due to cross-feeding, competition or cooperation, bacteria respond differently alone than they do in communities.79 For example, through molecular mimicry, Lactobacillus reuteri exacerbated the development of EAE, but only when mice were co-colonized with a novel strain of Th17-inducing Erysipelotrichaceae.80 In contrast, disease progression in L. reuteri monocolonized mice was indistinguishable from that in GF mice, which are highly resistant to EAE,81 and although Erysipelotrichaceae alone had a modest role in pathogenesis, disease progression in co-colonized mice was significantly more severe, suggesting that these microbes acted synergistically.
To study mechanisms of host-microbe mutualism in a more physiological setting, microbial consortia have been designed so that mice can be colonized with defined microbial communities. These have the advantage of being complex enough to facilitate a degree of immune maturation, yet simple enough to permit additional colonization by other single bacteria strains, thus allowing researchers to test responses to specific strains in a semi-mature immune environment. For example, the Schaedler Flora and then the Altered Schaedler Flora (ASF) were developed in 1965 and 1978, respectively, to move further along the complexity spectrum while still maintaining control of which bacteria are present. Now constituting eight bacterial members, this community remains a widely used gnotobiotic model to study host-microbiome interactions.82
The Oligo-Mouse Microbiota 12 (OMM12) consortia was created using 12 commensal isolates from the murine gut that span the 5 most dominant phyla.83 OMM12 is highly reproducible between animal facilities, stable over multiple generations and provides increased colonization resistance compared to ASF.83,84 Moreover, OMM12 induces a greater level of immune maturation compared to ASF, such as inhibition of hyper-IgE.85 Yet, its limited diversity still allows the addition of bacterial species to build up microbial community complexity and probe microbial function. For example, the addition of Extibacter muris to the OMM12 revealed the capacity of this bacteria to produce secondary bile acids.86 Tanoue et al. developed a defined microbial consortium consisting of 11 human commensal strains that stimulated increased levels of IFN-γ-producing CD8+ T cells, providing pathogen resistance to Listeria monocytogenes and promoting the anti-tumor activity of immune checkpoint inhibitors.87 Another microbial consortium comprised of 15 bacterial strains isolated from SPF mice was used to develop the GM15 gnotobiotic mouse model, which stimulated increased levels of serum antibodies and Peyer’s patch development, phenotypically resembling SPF mice.88
Moving further along the spectrum of complexity, several groups have endeavored to assemble large, complex communities of microbes while maintaining gnotobiotic status. In 2011, Atarashi et al. discovered that a mixture of 46 Clostridium species from the murine microbiome potently induced colonic Treg in a TGF-β-specific manner. These provided protection against DSS- and oxazolone-mediated colitis and systemic IgE induction in BALB/c mice, following a prime and boost with ovalbumin and alum.89 Treg induction was partially lost when mice were only colonized with 3 of the Clostridium strains. To facilitate clinical translation, this group then repeated this study using Clostridium species isolated from the human, rather than murine, microbiome. Colonization with 17 human Clostridium species was sufficient to phenocopy the Treg induction and regulatory phenotype induced by the 46 murine Clostridia.90 Monocolonizing mice with individual strains from this humanized consortium only induced a partial phenotype, demonstrating the need for more complex microbiota for full immune activation.
These gnotobiotic models allow the finely tuned dissection of how specific microbes within a community can mediate distinct immunological phenotypes. The same precision is not possible with more complex communities, such as SPF, or wild microbiome studies. New microbial consortia are now being developed and analyzed in in vitro cultures. For example, ten strains of human bacteria were selected for their combined capacity to efficiently convert dietary fibers into SCFA required for intestinal health.91 While this synthetic Diet-based Minimal Microbiome has been analyzed in vitro, the functional impact of such consortia could also be studied in vivo in gnotobiotic mice, although the metabolic activity of these microbes in vivo will be heavily influenced by their fitness to the rodent diet.
The mycobiome and the virome
An emerging field that has been long overlooked is the mouse and human mycobiome. Thus far, most microbiome studies and gnotobiotic models have focussed on the impact of bacteria, but we are also colonized with a diverse community of viruses, protozoa, archaea, and fungi that interact with the mucosal immune system.92,93,94 In fact, when introduced to SPF mice following antibiotics treatment, or to steady-state ASF mice, a consortium of mucosa-associated fungi was shown to alter epithelial transcription and permeability, induce intestinal Th17 responses and protect mice from colitis via IL-22- and CD4+ T cell-dependent mechanisms.95 These data suggest a role for the mucosal mycobiome in galvanizing barrier function. Moreover, when five specific human-associated yeast species were introduced into GF and OMM12 mice, they robustly impacted local, systemic, and distal immune responses.96 Most notably, fungal exposure modulated inflammation following induction of DSS colitis or ovalbumin-induced airway inflammation.96 Thus, adding fungal species into gnotobiotic models may be necessary to fully understand how the microbiome and mycobiome collaborate to modulate the mucosal immune system.
Using gnotobiotic mice to study host effects of the virome is in its infancy but has the potential to provide important information. Infection of GF mice with murine norovirus, an enteric RNA virus, was sufficient to restore intestinal morphology and stimulate immune development comparable to bacterial colonization.97 Gogokhia et al. treated GF mice with a cocktail of bacteriophage isolated from E. coli and found that was sufficient to increase the number of IFN-γ-producing T cells in the Peyer’s patches to levels found in SPF mice, indicating that bacteriophage can directly affect mucosal immunity.98 Additional studies using gnotobiotic mice to investigate bacteriophage effects on gut bacteria and host function are warranted.
Driving translation through increasing microbial diversity
A fundamental problem with using laboratory rodents for pre-clinical research is that a large proportion of findings fail to be translatable, leading to the ‘prediction problem’ currently plaguing translational research. Most mouse models cannot accurately predict human responses,5 and clinical trials in general have very low success rates.4,99 With an immune system more closely resembling that of a neonatal human,6 SPF mice often respond to immunological challenges differently than humans. To counter this, new mouse models have been developed to improve the predictive ability of translational research (Fig. 2).
Human microbiota-associated mouse models
Human microbiota-associated (HMA) mice are created via microbiota transplant of human feces into GF mice, which can be stably maintained in a laboratory setting.100,101 Although often referred to as ‘humanized’ it is important to note that HMA mice have not been humanized through human tissue or hematopoietic cell engraftment. Although not all microbes will engraft in the recipient mice,102 the HMA microbiota is still more complex and diverse than SPF mice and HMA mice are metabolically distinct from SPF mice and more closely correspond to the donor sample.103 As such, they have helped further our understanding of host-microbe interactions in the context of human immunity. For example, Planer et al. showed that HMA mice were able to recapitulate the variable IgA responses of human donors,104 demonstrating that microbiota composition plays a role in determining IgA responses.
HMA mice have been very useful for studying whether the human microbiome can transfer a disease phenotype to recipient mice and for elucidating causal relationships.105 The use of HMA mice has been used to study the role of the microbiome in many different diseases (reviewed in Walter et al.106) and has provided great insights. However, as in all microbiome studies, utilizing HMA mice requires careful consideration of experimental design, discussed in detail by Walter et al.106. For example, there is a high risk of pseudoreplication: fecal samples are collected from few human donors (sometimes as little as one) and transferred to higher numbers of mouse recipients, thereby artificially inflating the number of biological replicates.106 Moreover, mice are not humans and have not evolved with a human microbiota. This may sound trivial, particularly because it is the role of the human microbiome in health and disease that has captivated microbiologists and immunologists alike. However, these differences in evolutionary compatibility between host and microbiota could have important implications for the applicability of research involving HMA models. For example, Chung et al. observed that colonization of GF mice with human microbiota did not lead to the same degree of immune maturation as colonization with a mouse microbiota,77 suggesting that a host-specific microbiota is required. Therefore, researchers have begun looking for other ways to improve the immune responses of laboratory mice using microbes (and pathogens) that co-evolved with mice, rather than humans.
‘Dirty’ mouse models: wild mouse models and their derivatives
Other methods used to expand and diversify the microbiota of laboratory mice, while retaining genetic uniformity, include co-housing them with pet store mice, transferring bedding and feces between the cages of pet store mice and SPF mice, or intentionally infecting SPF with common pathogens.6,107,108,109,110 Using these methods to generate ‘dirty’ mice has been shown to reverse some of the immunological deficits associated with SPF mice6 and dampen humeral responses to vaccine challenge; an important factor when assessing vaccine efficacy.107,109
In the last decade, a major advancement toward generating translationally relevant mouse models is the characterization and utilization of the wild mouse microbiome. This has provided some hints as to why many pre-clinical trials involving laboratory mice have failed to translate to humans. The gut microbiota of laboratory mice is significantly different from that of wild mice (Mus musculus domesticus), likely due to differences in environment, diet, stressors, host genetics, and pathogen exposure. Two studies by the same group found that laboratory mice had a significantly higher relative abundance of Firmicutes bacteria, but lower Proteobacteria compared to wild mice.111,112 Other groups found that Firmicutes was the most frequently identified phylum in the gut microbiota of wild mice,113,114 but with marked seasonal changes.115 Wild mice have an enriched mycobiome, as well as an increased pathogen load.111,113,116,117 Collectively, these differences are associated with substantial changes in leukocyte maturation, education, activation and turnover.118,119,120,121 However, it should be noted that some clinically relevant bacterial families, such as Akkermansiaceae, Streptococcaceae, and Enterobacteriaceae, are generally undetectable in wild rodents but have been acquired by SPF mice within the laboratory environment over time.
An issue with working with captive wild mice is that it is hard to delineate between the effects of genes and the effects of the microbiota. Genetic variation can be controlled for using wild microbiota exposure experiments, where laboratory mice are given a wild microbiota via different methods (Fig. 2). These include: (i) introducing fecal matter from wild mice to GF mice by oral gavage;112 (ii) transferring embryos from lab mice to wild surrogate dams to generate “wildlings”;111 (iii) “re-wilding” laboratory mice by housing them in an outside enclosure that recapitulates the habitat of wild mice;122 or (iv) housing them with bedding from their natural environment.123 Each approach results in genetically identical laboratory mice with wild microbiomes that can be stably transferred and maintained over generations, thus facilitating microbiome diversification while preventing confounding results from genetic variability. Although similar, their resulting microbiomes may not fully converge with those of wild mice, as has been described for wildlings,111 possibly due to differences in host genomes and diets. Importantly, when compared to SPF mice, ‘re-wilding’ results in immune system reprogramming, particularly in the spleen, MLN and peripheral blood111,124 and alters susceptibility to infection in a context-dependent manner, with re-wilded mice being more susceptible to Trichuris muris infection but protected from lung pathology and death following a lethal dose of influenza A.112,122 Interestingly, the leukocyte profile in the gut of wildlings was bimodal, with 50% of wildlings clustering with SPF mice and the rest clustering with wild mice, suggesting a dual influence of the host and microbial genome on mucosal immunity.
In contrast to the intestine, the lung microbiota was relatively similar between SPF, wild-derived and wild-caught mice, with Betaproteobacteria being the most abundant phylum across multiple hygiene status, followed by Firmicutes.125 Ralstonia was the most abundant genus in SPF, wild-derived and wild-caught mice, followed by Lactobacillus in SPF mice and Helicobacter in the wild-caught mice. Wild-derived mice showed an intermediate phenotype, with similar levels of Lactobacillus and Helicobacter. Despite genus-level similarities, the overall community composition was significantly different among lung microbiota from these different groups of mice. It is possible that these differences are sufficient to shape the local innate immune cell landscape, as mast cells are enriched in the lung parenchyma of wild but not SPF mice.123 Yeh et al. found that housing SPF mice in a semi-natural environment consisting of farmhouse-sourced bedding was sufficient to increase mast cell recruitment to the lung.123 Although environmental components played a role in driving this phenotype, microbial communities present in the mice, or the bedding were not characterized in this study. Mast cells play a key role in IgE-mediated allergic responses and are present in abundance in the human lung parenchyma.126 Thus, murine colonization status and/or environmental antigen exposure likely has important implications for the translational potential of mouse models in asthma and allergy research.
Comparisons have also been made between the skin microbiomes of SPF, wild mice, and wildlings.111,127 However, despite wildlings possessing a similar skin microbiota to wild mice that differed from their SPF counterparts, the immune landscape of their skin more closely resembled that of laboratory mice, despite the differences in bacterial communities of these two mouse populations.111 Thus, the host genome may play a larger role in determining the immune landscape in the skin than the local microbiome.
The potential for incorporating wild mice in pre-clinical trials
Due to their differentially educated immune systems, mouse strains with ‘wild’ microbiomes may better predict human outcomes in clinical trials. Recently, Rosshart et al. elegantly demonstrated the superiority of wildlings, compared to SPF mice, when it came to accurately predicting the outcomes of two clinical trials, which had previously failed to be translated from SPF mice to humans.111 When assessing the ability of CD28-superantigen to induce Tregs therapeutically, pre-clinical trials showed a robust Treg expansion in rats that protected them from various autoimmune disorders, including EAE (previously reviewed extensively.128) However, the CD28-superantigen human clinical trial resulted in overt over-activation of inflammatory T cells followed by cytokine storm and a lack of Treg expansion.129 These catastrophic effects were recapitulated wildlings but not SPF mice.111 Similarly, when TNF-ɑ blockade was used at high doses to treat septic shock, increased mortality resulted in the trial being halted early.130 Following LPS-induced endotoxemia, TNF-ɑ blockade was sufficient to protect SPF mice but not wildlings, which exhibited a similar level of mortality to control animals.111 Dirty mouse models may also be useful for translational research as SPF mice had more “human-like” immune responses to vaccines after they were co-housed with pet store mice, housed with bedding from pet store cages or exposed to common pathogens.107,109 Collectively, these studies demonstrate the powerful potential of microbial diversification as a prerequisite for pre-clinical research, and highlights a potential role for wild mice, or mice with a wild or diverse microbiome, in pre-clinical trials.
Advancements in biomedical research require high-quality basic research coupled with translationally powerful models that can successfully predict clinical trials. There is no “one-size fits all” approach. Due to its far-reaching influence, microbiome diversity and community structure can majorly impact the suitability and effectiveness of different rodent models to address specific scientific questions, with microbial diversity and pathogen exposure emerging as a missing link in translating findings from rodent models to the clinic. In contrast, when it comes to mechanistic studies and reverse-translational research, arguably, less is more. Gnotobiotic models in genetically identical mice vastly limits experimental variables and allows for specific research questions to be addressed with precision.
Willing, B. P., Russell, S. L. & Finlay, B. B. Shifting the balance: antibiotic effects on host-microbiota mutualism. Nat. Rev. Microbiol. 9, 233–243 (2011).
Ivanov, I. I. et al. Induction of intestinal Th17 cells by segmented filamentous bacteria. Cell 139, 485–498 (2009).
Flannigan K. L. & Denning T.L. Segmented filamentous bacteria-induced immune responses: a balancing act between host protection and autoimmunity. Immunology 154, 537–546 (2018).
Mak, I. W., Evaniew, N. & Ghert, M. Lost in translation: animal models and clinical trials in cancer treatment. Am. J. Transl. Res. 6, 114–118 (2014).
Seok, J. et al. Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc. Natl Acad. Sci. USA 110, 3507–3512 (2013).
Beura, L. K. et al. Normalizing the environment recapitulates adult human immune traits in laboratory mice. Nature 532, 512–516 (2016).
Liu, Y. et al. Gut microbiome alterations in high-fat-diet-fed mice are associated with antibiotic tolerance. Nat. Microbiol. 6, 874–884 (2021).
Scott N. A. et al. Antibiotics induce sustained dysregulation of intestinal T cell immunity by perturbing macrophage homeostasis. Sci. Transl. Med. 10, eaao4755 (2018).
Strati, F. et al. Antibiotic-associated dysbiosis affects the ability of the gut microbiota to control intestinal inflammation upon fecal microbiota transplantation in experimental colitis models. Microbiome 9, 39 (2021).
Ashley S. L. et al. Lung and gut microbiota are altered by hyperoxia and contribute to oxygen-induced lung injury in mice. Sci. Transl. Med. 12, eaau9959 (2020).
Brown, R. L., Sequeira, R. P. & Clarke, T. B. The microbiota protects against respiratory infection via GM-CSF signaling. Nat. Commun. 8, 1512 (2017).
Hosang, L. et al. The lung microbiome regulates brain autoimmunity. Nature 603, 138–144 (2022).
Ichinohe, T. et al. Microbiota regulates immune defense against respiratory tract influenza A virus infection. Proc. Natl Acad. Sci. USA 108, 5354–5359 (2011).
Hurabielle, C. et al. Immunity to commensal skin fungi promotes psoriasiform skin inflammation. Proc. Natl Acad. Sci. USA 117, 16465–16474 (2020).
Naik, S. et al. Commensal-dendritic-cell interaction specifies a unique protective skin immune signature. Nature 520, 104–108 (2015).
Hu, Y. et al. Different immunological responses to early-life antibiotic exposure affecting autoimmune diabetes development in NOD mice. J. Autoimmun. 72, 47–56 (2016).
Hu, Y. et al. Maternal Antibiotic Treatment Protects Offspring from Diabetes Development in Nonobese Diabetic Mice by Generation of Tolerogenic APCs. J. Immunol. 195, 4176–4184 (2015).
Kennedy, E. A., King, K. Y. & Baldridge, M. T. Mouse Microbiota Models: comparing Germ-Free Mice and Antibiotics Treatment as Tools for Modifying Gut Bacteria. Front. Physiol. 9, 1534 (2018).
Sender, R., Fuchs, S. & Milo, R. Are We Really Vastly Outnumbered? Revisiting the Ratio of Bacterial to Host. Cells Hum. Cell 164, 337–340 (2016).
Sommer, F. & Backhed, F. The gut microbiota–masters of host development and physiology. Nat. Rev. Microbiol. 11, 227–238 (2013).
Renz, H., Brandtzaeg, P. & Hornef, M. The impact of perinatal immune development on mucosal homeostasis and chronic inflammation. Nat. Rev. Immunol. 12, 9–23 (2011).
Cash, H. L., Whitham, C. V., Behrendt, C. L. & Hooper, L. V. Symbiotic bacteria direct expression of an intestinal bactericidal lectin. Science 313, 1126–1130 (2006).
Meisel, J. S. et al. Commensal microbiota modulate gene expression in the skin. Microbiome 6, 20 (2018).
Sanos, S. L. et al. RORgammat and commensal microflora are required for the differentiation of mucosal interleukin 22-producing NKp46+ cells. Nat. Immunol. 10, 83–91 (2009).
Bain, C. C. et al. Constant replenishment from circulating monocytes maintains the macrophage pool in the intestine of adult mice. Nat. Immunol. 15, 929–937 (2014).
Chen Q., Nair S. & Ruedl C. Microbiota regulates the turnover kinetics of gut macrophages in health and inflammation. Life Sci Alliance. 5, e202101178 (2022).
Constantinides M. G. et al. MAIT cells are imprinted by the microbiota in early life and promote tissue repair. Science 366, eaax6624 (2019).
Schwarzer, M. et al. Germ-Free Mice Exhibit Mast Cells With Impaired Functionality and Gut Homing and Do Not Develop Food Allergy. Front. Immunol. 10, 205 (2019).
Shaw, T. N. et al. Tissue-resident macrophages in the intestine are long lived and defined by Tim-4 and CD4 expression. J. Exp. Med. 215, 1507–1518 (2018).
Legoux, F. et al. Microbial metabolites control the thymic development of mucosal-associated invariant T cells. Science 366, 494–499 (2019).
Satoh-Takayama, N. et al. Microbial flora drives interleukin 22 production in intestinal NKp46+ cells that provide innate mucosal immune defense. Immunity 29, 958–970 (2008).
Ueda, Y. et al. Commensal microbiota induce LPS hyporesponsiveness in colonic macrophages via the production of IL-10. Int. Immunol. 22, 953–962 (2010).
McCoy, K. D. & Thomson, C. A. The Impact of Maternal Microbes and Microbial Colonization in Early Life on Hematopoiesis. J. Immunol. 200, 2519–2526 (2018).
Wang, Z. et al. Skin microbiome promotes mast cell maturation by triggering stem cell factor production in keratinocytes. J. Allergy Clin. Immunol. 139, 1205–1216 (2017). e1206.
Ganal, S. C. et al. Priming of natural killer cells by nonmucosal mononuclear phagocytes requires instructive signals from commensal microbiota. Immunity 37, 171–186 (2012).
Almeida, J. I. et al. Hallmarks of the human intestinal microbiome on liver maturation and function. J. Hepatol. 76, 694–725 (2022).
Erny, D. et al. Host microbiota constantly control maturation and function of microglia in the CNS. Nat. Neurosci. 18, 965–977 (2015).
Geuking, M. B. et al. Intestinal bacterial colonization induces mutualistic regulatory T cell responses. Immunity 34, 794–806 (2011).
Kim, K. S. et al. Dietary antigens limit mucosal immunity by inducing regulatory T cells in the small intestine. Science 351, 858–863 (2016).
Weiss, J. M. et al. Neuropilin 1 is expressed on thymus-derived natural regulatory T cells, but not mucosa-generated induced Foxp3+ T reg cells. J. Exp. Med. 209, 1723–1742 (2012). S1721.
Bunker J. J. et al. Natural polyreactive IgA antibodies coat the intestinal microbiota. Science 358, eaan6619 (2017).
Cahenzli, J., Koller, Y., Wyss, M., Geuking, M. B. & McCoy, K. D. Intestinal microbial diversity during early-life colonization shapes long-term IgE levels. Cell Host Microbe 14, 559–570 (2013).
Herbst, T. et al. Dysregulation of allergic airway inflammation in the absence of microbial colonization. Am. J. Respir. Crit. Care Med. 184, 198–205 (2011).
Al Nabhani, Z. et al. A Weaning Reaction to Microbiota Is Required for Resistance to Immunopathologies in the Adult. Immunity 50, 1276–1288 (2019). e1275.
Knoop K. A. et al. Microbial antigen encounter during a preweaning interval is critical for tolerance to gut bacteria. Sci. Immunol. 2, eaao1314 (2017).
Olszak, T. et al. Microbial exposure during early life has persistent effects on natural killer T cell function. Science 336, 489–493 (2012).
Charlson, E. S. et al. Topographical continuity of bacterial populations in the healthy human respiratory tract. Am. J. Respir. Crit. Care Med. 184, 957–963 (2011).
Dickson, R. P. et al. The Lung Microbiota of Healthy Mice Are Highly Variable, Cluster by Environment, and Reflect Variation in Baseline Lung Innate Immunity. Am. J. Respir. Crit. Care Med. 198, 497–508 (2018).
Gollwitzer, E. S. et al. Lung microbiota promotes tolerance to allergens in neonates via PD-L1. Nat. Med. 20, 642–647 (2014).
Jin, C. et al. Commensal Microbiota Promote Lung Cancer Development via gammadelta T Cells. Cell 176, 998–1013 (2019). e1016.
O’Dwyer, D. N. et al. Lung Microbiota Contribute to Pulmonary Inflammation and Disease Progression in Pulmonary Fibrosis. Am. J. Respir. Crit. Care Med. 199, 1127–1138 (2019).
Hrncir, T., Stepankova, R., Kozakova, H., Hudcovic, T. & Tlaskalova-Hogenova, H. Gut microbiota and lipopolysaccharide content of the diet influence development of regulatory T cells: studies in germ-free mice. BMC Immunol. 9, 65 (2008).
Schwarzer, M. et al. Diet Matters: Endotoxin in the Diet Impacts the Level of Allergic Sensitization in Germ-Free Mice. PLoS ONE 12, e0167786 (2017).
Hong, S. W. et al. Food antigens drive spontaneous IgE elevation in the absence of commensal microbiota. Sci. Adv. 5, eaaw1507 (2019).
Hara, S. et al. Dietary Antigens Induce Germinal Center Responses in Peyer’s Patches and Antigen-Specific IgA Production. Front. Immunol. 10, 2432 (2019).
Furusawa, Y. et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature 504, 446–450 (2013).
Kespohl, M. et al. The Microbial Metabolite Butyrate Induces Expression of Th1-Associated Factors in CD4(+) T Cells. Front. Immunol. 8, 1036 (2017).
Nadjsombati, M. S. et al. Detection of Succinate by Intestinal Tuft Cells Triggers a Type 2 Innate Immune Circuit. Immunity 49, 33–41 (2018). e37.
Braniste, V. et al. The gut microbiota influences blood-brain barrier permeability in mice. Sci. Transl. Med. 6, 263ra158 (2014).
Sampson, T. R. et al. Gut Microbiota Regulate Motor Deficits and Neuroinflammation in a Model of Parkinson’s Disease. Cell 167, 1469–1480.e1412 (2016).
Esterhazy, D. et al. Compartmentalized gut lymph node drainage dictates adaptive immune responses. Nature 569, 126–130 (2019).
Houston, S. A. et al. The lymph nodes draining the small intestine and colon are anatomically separate and immunologically distinct. Mucosal. Immunol. 9, 468–478 (2016).
Hapfelmeier, S. et al. Reversible microbial colonization of germ-free mice reveals the dynamics of IgA immune responses. Science 328, 1705–1709 (2010).
Gomez de Aguero, M. et al. The maternal microbiota drives early postnatal innate immune development. Science 351, 1296–1302 (2016).
Fonseca, W. et al. Maternal gut microbiome regulates immunity to RSV infection in offspring. J. Exp. Med. 218, e20210235 (2021).
Kimura, I. et al. Maternal gut microbiota in pregnancy influences offspring metabolic phenotype in mice. Science 367, eaaw8429 (2020).
Atarashi, K. et al. Th17 Cell Induction by Adhesion of Microbes to Intestinal Epithelial Cells. Cell 163, 367–380 (2015).
Farkas, A. M. et al. Induction of Th17 cells by segmented filamentous bacteria in the murine intestine. J. Immunol. Methods 421, 104–111 (2015).
Lecuyer, E. et al. Segmented filamentous bacterium uses secondary and tertiary lymphoid tissues to induce gut IgA and specific T helper 17 cell responses. Immunity 40, 608–620 (2014).
Tan, T. G. et al. Identifying species of symbiont bacteria from the human gut that, alone, can induce intestinal Th17 cells in mice. Proc. Natl Acad. Sci. USA 113, E8141–E8150 (2016).
Round, J. L. & Mazmanian, S. K. Inducible Foxp3+ regulatory T-cell development by a commensal bacterium of the intestinal microbiota. Proc. Natl Acad. Sci. USA 107, 12204–12209 (2010).
Verma, R. et al. Cell surface polysaccharides of Bifidobacterium bifidum induce the generation of Foxp3(+) regulatory T cells. Sci. Immunol. 3, eaat6975 (2018).
Geuking, M. B. & Burkhard, R. Microbial modulation of intestinal T helper cell responses and implications for disease and therapy. Mucosal Immunol. 13, 855–866 (2020).
Takeuchi, T. et al. Acetate differentially regulates IgA reactivity to commensal bacteria. Nature 595, 560–564 (2021).
Mager, L. F. et al. Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy. Science 369, 1481–1489 (2020).
Geva-Zatorsky, N. et al. Mining the Human Gut Microbiota for Immunomodulatory Organisms. Cell 168, 928–943 (2017). e911.
Chung, H. et al. Gut immune maturation depends on colonization with a host-specific microbiota. Cell 149, 1578–1593 (2012).
Gaboriau-Routhiau, V. et al. The key role of segmented filamentous bacteria in the coordinated maturation of gut helper T cell responses. Immunity 31, 677–689 (2009).
Ohland, C. L. & Jobin, C. Microbial activities and intestinal homeostasis: a delicate balance between health and disease. Cell Mol. Gastroenterol. Hepatol. 1, 28–40 (2015).
Miyauchi, E. et al. Gut microorganisms act together to exacerbate inflammation in spinal cords. Nature 585, 102–106 (2020).
Lee, Y. K., Menezes, J. S., Umesaki, Y. & Mazmanian, S. K. Proinflammatory T-cell responses to gut microbiota promote experimental autoimmune encephalomyelitis. Proc. Natl Acad. Sci. USA 108 Suppl 1, 4615–4622 (2011).
Wymore Brand, M. et al. The Altered Schaedler Flora: Continued Applications of a Defined Murine Microbial Community. ILAR J. 56, 169–178 (2015).
Brugiroux, S. et al. Genome-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium. Nat. Microbiol. 2, 16215 (2016).
Eberl, C. et al. Reproducible Colonization of Germ-Free Mice With the Oligo-Mouse-Microbiota in Different Animal Facilities. Front. Microbiol. 10, 2999 (2019).
Wyss, M. et al. Using Precisely Defined in vivo Microbiotas to Understand Microbial Regulation of IgE. Front. Immunol. 10, 3107 (2019).
Streidl, T. et al. The gut bacterium Extibacter muris produces secondary bile acids and influences liver physiology in gnotobiotic mice. Gut Microbes 13, 1–21 (2021).
Tanoue, T. et al. A defined commensal consortium elicits CD8 T cells and anti-cancer immunity. Nature 565, 600–605 (2019).
Darnaud, M. et al. A standardized gnotobiotic mouse model harboring a minimal 15-member mouse gut microbiota recapitulates SOPF/SPF phenotypes. Nat. Commun. 12, 6686 (2021).
Atarashi, K. et al. Induction of colonic regulatory T cells by indigenous Clostridium species. Science 331, 337–341 (2011).
Atarashi, K. et al. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature 500, 232–236 (2013).
Shetty, S. A. et al. Inter-species Metabolic Interactions in an In-vitro Minimal Human Gut Microbiome of Core Bacteria. NPJ Biofilms Microbiomes 8, 21 (2022).
Barko, P. C., McMichael, M. A., Swanson, K. S. & Williams, D. A. The gastrointestinal microbiome: a review. J. Vet. Intern. Med. 32, 9–25 (2018).
Gutierrez, M. W. & Arrieta, M. C. The intestinal mycobiome as a determinant of host immune and metabolic health. Curr. Opin. Microbiol. 62, 8–13 (2021).
Liang, G. & Bushman, F. D. The human virome: assembly, composition and host interactions. Nat. Rev. Microbiol. 19, 514–527 (2021).
Leonardi, I. et al. Mucosal fungi promote gut barrier function and social behavior via Type 17 immunity. Cell 185, 831–846 (2022). e814.
van Tilburg Bernardes, E. et al. Intestinal fungi are causally implicated in microbiome assembly and immune development in mice. Nat. Commun. 11, 2577 (2020).
Kernbauer, E., Ding, Y. & Cadwell, K. An enteric virus can replace the beneficial function of commensal bacteria. Nature 516, 94–98 (2014).
Gogokhia, L. et al. Expansion of Bacteriophages Is Linked to Aggravated Intestinal Inflammation and Colitis. Cell Host Microbe 25, 285–299 (2019). e288.
Wong, C. H., Siah, K. W. & Lo, A. W. Estimation of clinical trial success rates and related parameters. Biostatistics 20, 273–286 (2019).
Brooks, P. T. et al. Transplanted human fecal microbiota enhanced Guillain Barre syndrome autoantibody responses after Campylobacter jejuni infection in C57BL/6 mice. Microbiome 5, 92 (2017).
Collins, J., Auchtung, J. M., Schaefer, L., Eaton, K. A. & Britton, R. A. Humanized microbiota mice as a model of recurrent Clostridium difficile disease. Microbiome 3, 35 (2015).
Zhang, L. et al. Environmental spread of microbes impacts the development of metabolic phenotypes in mice transplanted with microbial communities from humans. ISME J. 11, 676–690 (2017).
Marcobal, A. et al. A metabolomic view of how the human gut microbiota impacts the host metabolome using humanized and gnotobiotic mice. ISME J. 7, 1933–1943 (2013).
Planer, J. D. et al. Development of the gut microbiota and mucosal IgA responses in twins and gnotobiotic mice. Nature 534, 263–266 (2016).
Round J. L. & Palm N. W. Causal effects of the microbiota on immune-mediated diseases. Sci. Immunol. 3, eaao1603 (2018).
Walter, J., Armet, A. M., Finlay, B. B. & Shanahan, F. Establishing or Exaggerating Causality for the Gut Microbiome: Lessons from Human Microbiota-Associated Rodents. Cell 180, 221–232 (2020).
Fiege, J. K. et al. Mice with diverse microbial exposure histories as a model for preclinical vaccine testing. Cell Host Microbe 29, 1815–1827 (2021). e1816.
Huggins, M. A. et al. Microbial Exposure Enhances Immunity to Pathogens Recognized by TLR2 but Increases Susceptibility to Cytokine Storm through TLR4 Sensitization. Cell Rep. 28, 1729–1743 (2019). e1725.
Reese, T. A. et al. Sequential Infection with Common Pathogens Promotes Human-like Immune Gene Expression and Altered Vaccine Response. Cell Host Microbe 19, 713–719 (2016).
Takeda, A. J. et al. Human PI3Kgamma deficiency and its microbiota-dependent mouse model reveal immunodeficiency and tissue immunopathology. Nat. Commun. 10, 4364 (2019).
Rosshart S. P. et al. Laboratory mice born to wild mice have natural microbiota and model human immune responses. Science 365, eaaw4361 (2019).
Rosshart, S. P. et al. Wild Mouse Gut Microbiota Promotes Host Fitness and Improves Disease Resistance. Cell 171, 1015–1028 (2017). e1013.
Kreisinger J., Bastien G., Hauffe H. C., Marchesi J. & Perkins S. E. Interactions between multiple helminths and the gut microbiota in wild rodents. Philos. Trans. R Soc. Lond B. Biol. Sci. 370, 20140295 (2015).
Weldon, L. et al. The Gut Microbiota of Wild Mice. PLoS ONE 10, e0134643 (2015).
Maurice, C. F. et al. Marked seasonal variation in the wild mouse gut microbiota. ISME J. 9, 2423–2434 (2015).
Bowerman, K. L. et al. Effects of laboratory domestication on the rodent gut microbiome. ISME Commun. 1, 49 (2021).
Song, H. et al. Metagenomic Analysis of the Gut Microbiota of Wild Mice, a Newly Identified Reservoir of Campylobacter. Front. Cell Infect. Microbiol. 10, 596149 (2020).
Abolins, S. et al. The comparative immunology of wild and laboratory mice, Mus musculus domesticus. Nat. Commun. 8, 14811 (2017).
Abolins, S. R., Pocock, M. J., Hafalla, J. C., Riley, E. M. & Viney, M. E. Measures of immune function of wild mice, Mus musculus. Mol. Ecol. 20, 881–892 (2011).
Boysen, P., Eide, D. M. & Storset, A. K. Natural killer cells in free-living Mus musculus have a primed phenotype. Mol. Ecol. 20, 5103–5110 (2011).
Clerc, M., Devevey, G., Fenton, A. & Pedersen, A. B. Antibodies and coinfection drive variation in nematode burdens in wild mice. Int. J. Parasitol. 48, 785–792 (2018).
Leung, J. M. et al. Rapid environmental effects on gut nematode susceptibility in rewilded mice. PLoS Biol. 16, e2004108 (2018).
Yeh, Y. W. et al. Mast Cells Are Identified in the Lung Parenchyma of Wild Mice, Which Can Be Recapitulated in Naturalized Laboratory Mice. Front. Immunol. 12, 736692 (2021).
Yeung, F. et al. Altered Immunity of Laboratory Mice in the Natural Environment Is Associated with Fungal Colonization. Cell Host Microbe. 27, 809–822.e806 (2020).
Yun, Y. et al. Environmentally determined differences in the murine lung microbiota and their relation to alveolar architecture. PLoS ONE 9, e113466 (2014).
Andersson, C. K., Mori, M., Bjermer, L., Lofdahl, C. G. & Erjefalt, J. S. Novel site-specific mast cell subpopulations in the human lung. Thorax 64, 297–305 (2009).
Belheouane, M. et al. Assessing similarities and disparities in the skin microbiota between wild and laboratory populations of house mice. ISME J. 14, 2367–2380 (2020).
Hunig, T. & Dennehy, K. CD28 superagonists: mode of action and therapeutic potential. Immunol. Lett. 100, 21–28 (2005).
Suntharalingam, G. et al. Cytokine storm in a phase 1 trial of the anti-CD28 monoclonal antibody TGN1412. N. Engl. J. Med. 355, 1018–1028 (2006).
Fisher, C. J. Jr. et al. Treatment of septic shock with the tumor necrosis factor receptor:Fc fusion protein. The Soluble TNF Receptor Sepsis Study Group. N. Engl. J. Med. 334, 1697–1702 (1996).
S.M. is funded by IMPACTT, a Microbiome Research Core funded by the Canadian Institutes of Health Research (CIHR) Grant IMR-158322. Figures were generated using Biorender.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Thomson, C.A., Morgan, S.C., Ohland, C. et al. From germ-free to wild: modulating microbiome complexity to understand mucosal immunology. Mucosal Immunol 15, 1085–1094 (2022). https://doi.org/10.1038/s41385-022-00562-3