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. Author manuscript; available in PMC: 2016 Jan 7.
Published in final edited form as: Mol Ecol. 2014 Oct;23(19):4679–4681. doi: 10.1111/mec.12895

Tending a complex microbiota requires major immune complexity

KEATON STAGAMAN *, KAREN GUILLEMIN , KATHRYN MILLIGAN-MYHRE *,
PMCID: PMC4704785  NIHMSID: NIHMS748360  PMID: 25263404

Abstract

Animals maintain complex microbial communities within their guts that fill important roles in the health and development of the host. To what degree a host’s genetic background influences the establishment and maintenance of its gut microbial communities is still an open question. We know from studies in mice and humans that external factors, such as diet and environmental sources of microbes, and host immune factors play an important role in shaping the microbial communities (Costello et al. 2012). In this issue of Molecular Ecology, Bolnick et al. (2014a) sample the gut microbial community from 150 genetically diverse stickleback isolated from a single lake to provide evidence that another part of the adaptive immune response, the major histocompatibility complex class II (MHCII) receptors of antigen-presenting cells, may play a role in shaping the gut microbiota of the threespine stickleback, Gasterosteus aculeatus (Bolnick et al. 2014a). Bolnick et al. (2014a) provide insight into natural, interindividual variation in the diversity of both stickleback MHCII alleles and their gut microbial communities and correlate changes in the diversity of MHCII receptor alleles with changes in the microbiota.

Keywords: adaptive immune response, major histocompatibility complex class II, microbiota, stickleback


The study of human-associated microbiota began with the description of mouth microbes by Antonie van Leeuwenhoek in 1683. However, until the recent advent of culture-independent deep sequencing and computing power required to analyze large data sets, researchers were not able to examine the structures of entire bacterial communities and make inferences into how those communities are shaped. Now that we have achieved a relatively cost-effective and efficient way to examine whole microbial communities, several studies have illustrated the importance of the environment, microbe–microbe interactions and genetic background of the host in shaping the complex microbial community in the gut (Spor et al. 2011). While we have made large strides in describing host-associated microbial communities, genetic studies in humans and mice designed to address the extent to which host genetics shape microbiota have their limitations. Such studies in humans, for example comparing monozygotic and dizygotic twin pairs (Turnbaugh et al. 2009), are limited by the small family sizes and uncontrolled environments of humans and have surveyed relatively small numbers of individuals to date. In the instances of laboratory animals reared in controlled environments, studies have typically surveyed the gut microbiota of inbred animals with single gene deletions that disrupt major signaling pathways (Vijay-Kumar et al. 2010), and even when genetically diverse populations have been examined, husbandry constraints that require segregating small populations into isolated cages have complicated analyses (Benson et al. 2010). Therefore, additional studies are needed to examine how natural genetic variation in hosts shapes their associated microbial communities.

To begin to address this question, Bolnick and colleagues focus on a single immune gene, the MHCII receptor, which plays a critical role in connecting the innate and adaptive arms of the immune system and had previously been implicated in microbiota diversity in human infants (De Palma et al. 2010). The authors surveyed MHCII gene sequences and gut microbiota membership in 150 three-spine stickleback from a single lake. Significantly, they uncovered pairwise correlations between the presence of specific MHCII alleles and the abundance of specific microbial taxa.

The adaptive immune system, characterized by highly polymorphic MHC receptors that interact with somatically diversified B- and T-cell receptors, evolved rapidly after its emergence in jawed vertebrates (Schluter et al. 1999). Margaret McFall-Ngai has proposed that the function of this complex and dynamic system may be to maintain highly complex communities of commensal microbes (McFall-Ngai 2007). In support of this hypothesis, Bolnick et al. (2014a) found an inverse relationship between MHCII allele diversity and gut bacterial community diversity. That is, individuals with greater MHCII allele diversity had less diverse bacterial communities, suggesting that adaptive immunity could constrain commensal bacterial communities.

While the specific correlations between MHCII alleles and taxa uncovered by Bolnick and colleagues were statistically significant, their measured effect sizes were quite small and involved only a few taxa. The small effect size may be due to the complexity and interconnectedness of the adaptive immune system in which each part works in conjunction with others, as well as with the innate immunity branch (Fig. 1). For example, high levels of flagellin in the intestine are associated with complex innate and adaptive immune responses: the innate immune response induces gut inflammation and mucosal barrier breakdown. Concurrently, signals from the flagellin-specific innate receptor TLR5 enhance MHCII presentation of flagellin to the adaptive immune response-specific T cells (Letran et al. 2011) and promote production of flagellin-specific immunoglobulins (Cullender et al. 2013). In the Bolnick study, the finding of significant correlations between MHCII alleles and only a small number of bacterial taxa suggests that bacteria may differ in the extent to which they are influenced by host immunity. In support of this idea, a recent study of Fox3p+ T cells in mice demonstrated their preferential effects on Firmicutes diversity in the gut via regulation of B-cell antibody diversity (Kawamoto et al. 2014).

Fig. 1.

Fig. 1

Vertebrates, such as stickleback, maintain a complex microbial community in their guts. The adaptive immune system is a complex, dynamic system that utilizes both highly diverse major histocompatiblity complexes (MHCs) on antigen-presenting cells (APCs) and somatically differentiating antibodies (Abs) and T-cell receptors (TCRs) to sense and respond to particular members of the host-associated microbial community. This figure highlights the integral part MHC class II receptors play in cell-to-cell communication within the adaptive immune system.

Interestingly, the authors found that biological sex determinants influence the degree and direction of influence of the MHCII receptors. In a murine study, McKnite et al. (2012) determined that the microbiota of female, but not male, mice correlated with weekly body weight changes. Comparisons of the wild stickleback population in this current study to laboratory stickleback, mice and humans also revealed sex-dependent effects of diet on the composition of the microbiota (Bolnick et al. 2014c). In each of these cases, the differences in the correlation between microbiota and the sexes could be due to multiple factors such as differences in hormones, physical body shape, differences in the rate of development, expression of genes that are specific to one sex, or previously undescribed sex-specific factors.

While the authors emphasize that these are correlative, not causative, studies, their work offers insight into variation of the gut microbiota in a natural, wild population of fish and possible effects of MHCII diversity and sex on individual variation. There are a number of studies that could help validate the observations described here. Unlike antibodies and T-cell receptors, MHCII receptors do not somatically differentiate; hence, it would be possible to breed lines of stickleback with specific MHCII allele combinations. Such lines would allow for the experimental manipulation of MHCII diversity to determine the direction and magnitude of its causal relationship with gut microbe diversity. Moreover, only a minority of bacterial taxa were involved in these relationships, implying that those taxa could be of particular importance to the host; experimental manipulation of the microbial community could help determine if this is the case.

Considering the number of factors that could feasibly contribute to diversity of the microbial community, a deep multiscalar analysis of the complex gut microbiota that examines correlations with physical and physiological phenotypes, such as facial bone structure, standard length and presence of fatty tissue, may be required to better explain differences in the microbiota that MHCII variation alone cannot account for. Indeed, the authors recently reported that diet also contributes to microbial diversity in the same fish (Bolnick et al. 2014b), an interaction not explored in this current study. However, their identification of a correlation between MHCII alleles and associated bacteria demonstrates the feasibility of studying the influence of natural genetic variation at individual loci in host-microbe systems.

This study’s suggestion that MHCII receptors may influence the microbiota highlights the potential fitness advantages conferred by a host’s ability to cultivate its associated microbial communities. The benefits of immune control of gut microbes likely extend beyond the cultivation of useful digestive functions or protection against infection. For example, in mice, differences in MHCII alleles have been correlated with scents, which play an important role in mate choice. These MHCII effects are mediated through the composition of the mouse’s microbiota, which determines the production of metabolites affecting mouse scents and thus their reproductive success (Lanyon et al. 2007). Studies of natural populations, such as this one, provide great insight into the selective pressures that are likely to be important in influencing the assembly and evolution of host-microbe systems. The continuing development of the threespine stickleback as an experimental model system will allow us to rigorously test causal direction and magnitude of the correlated factors and thus develop a powerful theoretical model that could be used across multiple systems.

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