Spatial Organization of a Model 15-Member Human Gut Microbiota
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Spatial organization of a model 15-member human gut PNAS PLUS microbiota established in gnotobiotic mice Jessica L. Mark Welcha,1, Yuko Hasegawaa, Nathan P. McNultyb,c, Jeffrey I. Gordonb,c, and Gary G. Borisyd,1 aThe Josephine Bay Paul Center for Comparative Molecular Biology and Evolution, Marine Biological Laboratory, Woods Hole, MA 02543; bCenter for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110; cCenter for Gut Microbiome and Nutrition Research, Washington University School of Medicine, St. Louis, MO 63110; and dDepartment of Microbiology, The Forsyth Institute, Cambridge, MA 02142 Contributed by Gary G. Borisy, September 12, 2017 (sent for review July 3, 2017; reviewed by Angela E. Douglas and Ruth E. Ley) Knowledge of the spatial organization of the gut microbiota is The lumen of the gut is considered to be a compartment important for understanding the physical and molecular interactions inhabited by a microbiota distinct from that of the mucus layer among its members. These interactions are thought to influence (23, 29–33). This view is largely based on studies that have com- microbial succession, community stability, syntrophic relationships, pared mucosal samples to feces (30, 34–36). In contrast, studies and resiliency in the face of perturbations. The complexity and that have directly compared mucosa-associated communities with dynamism of the gut microbiota pose considerable challenges for adjacent luminal contents have generally shown only modest dif- quantitative analysis of its spatial organization. Here, we illustrate ferences in the relative proportions of taxa (29, 33, 37–39), al- an approach for addressing this challenge, using (i) a model, defined though exceptions occur. For example, Yasuda et al. (33) reported 15-member consortium of phylogenetically diverse, sequenced hu- that Helicobacteraceae dominated the colonic mucosa in rhesus man gut bacterial strains introduced into adult gnotobiotic mice fed macaques but were a minor constituent in the luminal community. a polysaccharide-rich diet, and (ii) in situ hybridization and spectral The complexity and dynamism of the gut microbiota pose imaging analysis methods that allow simultaneous detection of considerable challenges for quantitative analysis of its spatial or- multiple bacterial strains at multiple spatial scales. Differences in ganization. The most comprehensive analysis to date used gno- the binding affinities of strains for substrates such as mucus or food tobiotic mice colonized with a human fecal community and particles, combined with more rapid replication in a preferred mi- fluorescence in situ hybridization (FISH) with probes having crohabitat, could, in principle, lead to localized clonally expanded specificities that ranged from phylum level to genus level (5). aggregates composed of one or a few taxa. However, our results Other studies have used FISH, antibody staining, or labeling of reveal a colonic community that is mixed at micrometer scales, with polysaccharides to investigate the distribution of particular taxa distinct spatial distributions of some taxa relative to one another, within the microbiota, or of the microbiota as a whole in the notably at the border between the mucosa and the lumen. Our data presence of host perturbations (38, 40–48). Using microbes ge- suggest that lumen and mucosa in the proximal colon should be netically engineered to express distinct combinations of two fluo- conceptualized not as stratified compartments but as components rescent proteins, Whitaker et al. (49) were able to discriminate six of an incompletely mixed bioreactor. Employing the experimental engineered strains of Bacteroides in the gut of gnotobiotic mice. approaches described should allow direct tests of whether and how Adherence to available substrates such as mucus, food particles, specified host and microbial factors influence the nature and func- or other microbes, including to the polysaccharide-rich capsular tional contributions of “microscale” mixing to the dynamic opera- structures that some community members produce, may localize tions of the microbiota in health and disease. an organism to a preferred microhabitat but may only modestly prolong its residence time in the gut. Interestingly, modeling gut microbial ecology | community biogeography | bacterial–bacterial studies performed in experimental bioreactors, notably recently interactions | microbiome function | multiplex fluorescence imaging Significance he functions expressed by members of a microbial community – Tare impacted by their neighbors (1 4) and by physiological Spatial structure is postulated to have a powerful influence on features of their environment (5–9). A substantial body of theory establishing and sustaining the signaling and metabolic ex- suggests that spatial structure has a powerful influence on the changes that define relationships among members of the gut evolutionary stability of mutualistic relationships among mem- microbiota and host. However, information about gut community bers of a microbial community and between the community and spatial structure is limited. Simultaneous imaging of components its host (10–17). Depending on the details of the model or the of a 15-member model human gut bacterial community over a experimental system, cooperative interactions can be either sta- range of spatial scales in gnotobiotic mice revealed that the colon MICROBIOLOGY bilized or destabilized by spatial structure (reviewed in refs. 12, is better conceptualized as an incompletely mixed bioreactor, 16, and 18). Recently, Coyte et al. used modeling to predict that rather than having sharply stratified luminal and mucosal com- the host would benefit from compartmentalizing microbial spe- partments. Identifying host and microbial factors that constrain cies in the gut to weaken interactions between species and pro- the ability of community members to establish sizeable single or mote community stability (16). oligotaxon agglomerations should yield new insights about how Microbes display diverse adherence properties and growth rates “micro”-scale mixing defines community function. that could contribute to spatially structured communities. In the gut, microbes can adhere to the epithelium and mucins (19–21); Author contributions: J.L.M.W., Y.H., N.P.M., J.I.G., and G.G.B. designed research; J.L.M.W., Y.H., and N.P.M. performed research; J.L.M.W., Y.H., and G.G.B. analyzed data; these components of the ecosystem are arranged nonrandomly in and J.L.M.W., Y.H., N.P.M., J.I.G., and G.G.B. wrote the paper. ways that could lead to spatial structuring of adherent community Reviewers: A.E.D., Cornell University; and R.E.L., Max Planck Institute. members (22, 23). Similarly, partially digested food particles in the The authors declare no conflict of interest. – lumen could serve as sites of attachment (24 28). Differential Published under the PNAS license. replication of a microbe based on its localization in the mucus 1To whom correspondence may be addressed. Email: [email protected] or gborisy@ layer or the lumen (29) could itself generate a spatially structured forsyth.org. microbial consortium or could amplify differences established by This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. differential adherence. 1073/pnas.1711596114/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1711596114 PNAS | Published online October 9, 2017 | E9105–E9114 Downloaded by guest on September 30, 2021 developed gut-on-a-chip technology, have shown that peristaltic To construct a probe set that would provide information on the mixing is a key factor in maintaining high bacterial densities, distribution of all 15 taxa simultaneously, we initially employed a counteracting the tendency of flow to cause rapid depletion of combinatorial labeling and spectral imaging strategy where each bacteria (50). The importance of “precise” spatial positioning of taxon was labeled with a unique binary combination chosen from microbiota members relative to their metabolic partners to the among six fluorophores (51, 52). However, we found that because of healthy functioning of the microbiota is largely unknown. More- the high microbial density in the colon, adjacent bacterial cells fre- over, published studies have yet to examine the biogeography of a quently overlapped one another in the same pixel of the image, diverse microbiota within the colon at a species level, and in a despite confocal optical sectioning. This overlap resulted in ambig- manner where most members of a complex community could be uous combinations of binary signals. Therefore, we reverted to a targeted simultaneously without their prior genetic engineering to strategy of labeling each microbe with a single fluorophore. To vi- produce reporter proteins. In the present report, we use a FISH sualize the distribution of each taxon, we hybridized some sections approach that allows simultaneous identification of many bacterial with mixtures of oligonucleotides targeting six or seven taxa in- species (51, 52) to study the spatial organization of a defined 15- dividually (e.g., probe sets 1 and 2 in Table S1). To evaluate the member community of sequenced and phylogenetically diverse distribution of the entire community, we used a mixture (probe set 3) human gut-derived taxa installed in the guts of gnotobiotic mice. comprising three sets of oligonucleotides: (i) six probes, each la- While this artificial community is simplified relative to