Spatial Organization of a Model 15-Member Human Gut Microbiota

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 natural gut beled with a different fluorophore, targeting six species (Bacteroides communities, it was complex enough to allow for a variety of spatial cellulosilyticus, Bacteroides caccae, Parabacteroides distasonis, distributions and metabolic interactions between its members (4, 53, Ruminococcus torques, Clostridium scindens,andCollinsella aero- 54). Moreover, our multiplexed imaging approach provided an faciens); (ii) four probes, all labeled with Alexa 488, targeting four opportunity to examine the degree of spatial organization of this moderately abundant members of Bacteroides (Bacteroides the- defined community at multiple scales, ranging from hundreds of taiotaomicron, Bacteroides vulgatus, Bacteroides ovatus, Bacteroides micrometers across the diameter of the gut, to a mesoscale of tens uniformis); and (iii) five probes, all labeled with Alexa 532, tar- of micrometers, to just a few micrometers at the highest resolution. geting five low abundance Firmicutes (Eubacterium rectale, Clos- tridium spiroforme, Faecalibacterium prausnitzii, Ruminococcus Results obeum,andDorea longicatena) (see Methods and Fig. S1 for de- Strategy for Imaging the Distribution of Microbes in the Gnotobiotic tails of probe design and for validation of their taxon specificities). Colon. The experimental design and workflow of our strategy are In addition, we labeled all bacteria with the universal bacterial shown in Fig. 1. Adult germ-free mice were colonized with a probe Eub338 conjugated to Alexa 514 and used DAPI to label consortium of 15 human gut-derived bacterial species (Table S1), host and bacterial DNA. In some experiments, wheat germ ag- and gut segments were fixed and embedded in a glycol meth- glutinin (WGA), which binds to N-acetyl-D-glucosamine and sialic acrylate (GMA) resin. The GMA remained in place not only acid, or an antibody to mouse colonic mucin (MCM) was included during sectioning but also during subsequent in situ hybridization to localize mucus. Finally, we made use of endogenous auto- and imaging steps, preserving the 3D structure of the gut contents. fluorescence to image food particles and host tissue. The proportional representation of members of this community, When gut samples are imaged at a resolution sufficient to dis- whose genome sequences had been defined, was initially estimated tinguish individual microbial cells, the field of view is necessarily by shotgun sequencing of DNA prepared from fecal samples (see limited (∼100 × 100 μm) and the depth of field is shallow (∼1 μm), Table S2 for the results of Community Profiling by Sequencing; so that ∼10,000 cubic micrometers of material are visualized in a COPRO-Seq). single image. The density of microbes in the small intestine has

Germ-free Gnotobiotic Proximal Colonic 5 µ m thick mouse mouse colon segment cross sections

Oral Encase in Fixation, gavage agarose methacrylate embedding

Binarized False-color overlay of unmixed Segmented Image images for visual inspection FISH and tile taxon-assigned scan imaging image for cell counts

Merge Linear unmixing

Abundance heat map Unmixed images for Watershed Individual each fluorophore image unmixed images

Fig. 1. Experimental design and workflow. Germ-free mice were gavaged with a 15-member consortium of human gut bacterial strains and killed 14 d later. Segments of proximal colon were encased in agarose, fixed with formaldehyde, embedded in glycol methacrylate (GMA) resin, sectioned, and hybridized with fluorescent probes. The resin remained in place during hybridization and imaging steps, preserving 3D spatial structure. Gut cross-sections were imaged as a tile scan of multiple fields of view to image entire sections at high resolution. Each field of view was imaged by excitation with six laser lines sequentially and processed by linear unmixing to create separate images for each of nine fluorophores and for autofluorescence from host tissue and ingested food particles. Each image was then segmented into binary images to allow for an automated count of cells in each square of an 8 × 8 grid for each field of view. The results are displayed as a heat map of cell abundance. The unmixed fluorophore channels were also false-colored and overlaid to produce the final unmixed image.

E9106 | www.pnas.org/cgi/doi/10.1073/pnas.1711596114 Mark Welch et al. Downloaded by guest on September 30, 2021 been reported to be 104 to 107 cells per mL of luminal contents, Heat maps of the individual bacterial taxa showed a broadly PNAS PLUS whereas in the colon and feces it is orders of magnitude greater (as similar pattern of distribution at the scale of tens to hundreds of much as 1011–1012 cells per g; refs. 55 and 56). This translates to micrometers (Fig. 2B). This similarity was evaluated quantita- 1,000 microbes per field of view in the colon and feces, but this tively by line-scan analysis of transects running from the edge of number decreases 10,000- to 1 million-fold in the jejunum and the mucosa into the lumen (Fig. 2C). In these scans, the transects ileum. The FISH probe that reacted with all 15 members of the extended far enough into the lumen to determine the width of community (Eub338) confirmed that the distal small intestine of the high density microbial zone near the mucosa but not so far as these gnotobiotic mice was sparsely colonized (Fig. S2A), whereas to intersect patches of high luminal concentration. Data were the colon was densely colonized (Fig. S2B; compare with the ab- collected for 245 transects, and abundances were expressed as sence of microbes in the ileum and colon of germ-free controls in the fraction of bacterial cells present in discrete segments of the Fig. S2 C and D). Because of its significantly higher microbial transect. When averaged across the 245 transects, the abundance density, we chose to focus our multiscale multiplex imaging anal- pattern for each taxon was similar, peaking close to the mucosa ysis on the proximal colon. and then falling off sharply to a low level at distances greater than 75 μm into the lumen. Characterizing the Distribution of Bacteria in the Gut Is a Multiscale We focused our analysis on four “microhabitats”:(i) densely Problem. To quantitatively evaluate the overall distribution of colonized regions adjacent to the colonic mucosa, (ii) dense bacteria in the proximal colon, we tile-scanned five nearly patches of microbes within the lumen of the colon, (iii) sparsely complete cross-sections and a total of 372 microscopic fields colonized areas within the lumen, and (iv) sparsely colonized from this region in two mice and represented the data as heat crypts of Lieberkühn. All of the abundant taxa were detectable maps of bacterial cell abundance (see Fig. 1 for a summary of the in each of these microhabitats. In some images, large auto- approach). As demonstrated by the universal Eub338 probe, fluorescent particles of food pressed close to the mucosa so that bacteria were not distributed homogeneously across cross- the microbe-rich region was only 10–20 μm thick (Fig. 3A). Other sections; rather, they were concentrated at the border between images show a wider, densely colonized region at the edge of the the lumen and mucosa, as well as in patches in the interior of the mucosa (Fig. 3B). The lumen contained densely colonized re- lumen (Fig. 2A). These regions of highest density contained gions bordered by irregularly shaped autofluorescent food par- ∼50 cells per 100 μm2. Substantially lower densities occurred in ticles of variable size and brightness (Fig. 3C). A diverse the remainder of the lumen, consisting primarily of regions in microbial community was thinly arrayed on some of these par- and surrounding large autofluorescent particles that we interpret ticles and colonized the edges of cavities within them (Fig. 3 A as remnants of food (Fig. 2A). and C). This latter observation is consistent with the notion that

B. cellulosilyticus 4 Bacteroides C. aerofaciens R. torques AB50 40 7 20 6 40 30 5 Lumen 15 30 Mucosa 4 20 20 10 3 2 10 10 5 1 500 µm 0 0 0 0

10 3.5 18 B. caccae P. distasonis C. scindens 5 Firmicutes 9 16 16 Mucosa Highest 3 8 14 density 14 2.5 7 12 12 6 2 10 10 5 8 8 1 FOV = 4 1.5 Lowest 6 6 8 x 8 grid 3 1 density 2 4 4 0.5 500 µm 1 2 2 0 0 0 0 MICROBIOLOGY

C 20 Edge of B. cellulosilyticus mucosa 4 Bacteroides 15 B. caccae 10 C. aerofaciens C. scindens abundance 5 Taxon relative R. torques 0 -57 -38 -19 0 19 38 57 76 95 114 133 152 171 190 209 228 247 266 285 304 323 342 361 380 Distance from edge of proximal colonic mucosa (µm)

Fig. 2. Microbes are most abundant near host tissue and in patches in the lumen. Microbial density in each region of the cross-section is shown as a heat map (A) representing the number of cells hybridizing to the Eub338 probe and ranging from zero (dark blue) to 158 cells (red) per 19 × 19 μm grid square. The heat map is overlaid on a tile scan (Inset) of the section showing autofluorescence from host tissue and ingested food particles. (B) The density of individual taxa or groups of taxa shows a similar distribution. (C) A line-scan analysis of cell abundance along transects perpendicular to host tissue illustrates that taxa have similar distributions at this scale. Values shown are the percent of cells observed in each quantum of the transect, and are the mean of 245 transects from a total of five intestinal cross-sections from two mice. Transects consisted of 24 adjacent grid squares placed so that the fifth grid square contained the first bacterial cell labeled with the universal probe Eub338. Thus, the first four grid squares (76 μm) of each transect line would be empty unless occupied with a bacterial cell hybridizing to a specific probe but not to Eub338.

Mark Welch et al. PNAS | Published online October 9, 2017 | E9107 Downloaded by guest on September 30, 2021 AB

B. cellulosilyticus 4 BBacteroidesacteroides B. cellulosilyticus B. caccae B. theta C. aerofaciens B. vulgatus C. scindens C. aerofaciens R. torques R. torques auautofluorescencetofluorescence auautofluorescencetofluorescence

CD B. cellulosilyticus 4 BBacteroidesacteroides B. caccae C. aerofaciens C. scindens R. torques auautofluorescencetofluorescence

B. cellulosilyticus B. theta B. vulgatus B. ovatus R. torques. auautofluorescencetofluorescence DAPI

20 μm

5 μm

Fig. 3. Colonization patterns in distinct microhabitats in the colon. Tiled images show the distribution of microbes relative to host tissue and large autofluorescent food particles. Images shown are representative of the region proximal to the epithelium (A and B), the region distal to the epithelium (lumen; C), and crypts (D). White boxes show the positions of higher magnification views (Lower) where individual bacterial cells are visible; low-magnification image in C shows the image location in the lumen. Microbes were spatially mixed at micrometer scales in all microhabitats. Legend in A also applies to C. Scale bars in D apply throughout the figure.

food particles can serve as platforms for attachment of bacterial serve as microhabitats for any select groups within the 15-member taxa (including potential syntrophic partners). Crypts were colo- model human gut microbiota. nized by a sparse, taxonomically mixed community (Fig. 3D), The overall composition of the microbial community differed only suggesting that they were colonized from the lumen and did not modestly from microhabitat to microhabitat within a cross-section

E9108 | www.pnas.org/cgi/doi/10.1073/pnas.1711596114 Mark Welch et al. Downloaded by guest on September 30, 2021 when measured at a mesoscale (i.e., on the order of 100 μm). To dipoles as implemented in DAIME (57). Linear dipole analysis PNAS PLUS quantify these differences, we compared, from a single cross- calculates a pair cross-correlation function for two categories of section, 11 fields of view (each 152 × 152 μm) containing pri- objects by estimating the probability, normalized to their density marily the dense community and 12 fields containing almost in the image, that the ends of a line segment of a given length will exclusively the sparser, food particle-associated community. The touch both of them. six Bacteroides species collectively dominated in all microhabi- Linear dipole analysis demonstrated a tendency of microbes to tats; for example, B. cellulosilyticus made up 43 ± 4% (mean ± be in low abundance near crypts and invaginations in the mu- SD) of the cells in the densely colonized fields and 46 ± 4% in cosal epithelium (Fig. 4). This result is not surprising because the sparsely colonized fields (Table S2). C. aerofaciens was most these regions are generally occupied by a dense mucus layer abundant in the densely colonized areas, where it made up 11 ± resistant to bacterial penetration (58). Bordering this largely 1% of bacteria cells versus 6 ± 2% within the sparsely colonized microbe-free zone there was dense colonization of microbes. For areas. Of the two members of Clostridia targeted with specific purposes of analysis, we marked this border of dense coloniza- probes, C. scindens comprised 8 ± 2–4% of the community in tion with a hand-drawn line and calculated the spatial cross- both microhabitats, while R. torques made up 3 ± 1% in dense correlation between the microbes and this line (Fig. 4). The re- fields and 2 ± 1% in sparsely colonized regions of the lumen. sults revealed a concentration of microbes within ∼30 μm of this Thus, modest differences in overall microbial community com- line (Fig. 4). By contrast, and counterintuitively, microbes were position in mucus-rich and food-rich regions were detectable. underrepresented within 5–10 micrometers of large food parti- Summing FISH results across all of the sections yielded relative cles (Fig. 4). It is possible that this underrepresentation was due abundances that in many cases were comparable to results in part to a failure to detect the edges of food particles accu- obtained from COPRO-Seq analysis of fecal DNA (Table S2). rately, as food particles were detected by virtue of their endog- Communities observed at 10-μm scales consisted of a mixture enous fluorescence rather than by specific staining. However, the of diverse species, with the relative proportions of species varying images also give no visual evidence of any clustering of microbes from region to region. The autofluorescent particles we observed close to these autofluorescent particles. ranged in size from distinctively shaped objects several hundreds of micrometers long (Fig. 2) down to small “blobs” only a few Micrometer-Scale Analysis Reveals Differences in the Organization of micrometers in diameter. While the larger objects were generally Specific Taxa with Respect to the Mucosa and One Another. Turning only thinly colonized, smaller particles were present in densely from the distribution of bacteria overall to the distribution of colonized patches, with the exception of some patches near the individual taxa within the community, we detected an un- mucosa (Fig. 3). derrepresentation of R. torques in the dense community at the border between the mucosa and the lumen. Bacteroides were Quantitative Analysis of Spatial Organization at Micrometer Scales. abundantly represented throughout this microbe-dense region, To assess whether the spatial arrangement of microbes at mi- but R. torques exhibited marked scarcity in the region closest to crometer scales differed relative to the visible landmarks of the the mucosa (Fig. 5). To quantify the distribution of taxa relative epithelial border and large food particles, we carried out an to the edge of the mucosa, we marked the limit of dense mi- analysis of spatial arrangement using the method of linear crobial colonization with a 1-μm-thick line (Fig. 5) and used

100 µm 100 µm

3.5 MICROBIOLOGY to food edge 3 to host edge 2.5 to edge of microbial colonization 2 1.5 1 Pair correlation 0.5 0 .4 0 2 .4 .8 .0 .2 .4 5 .7 .9 1 .3 .5 .7 .1 .3 .5 .7 9 0 4.6 8.8 4 8 4 1 13. 17. 21 25.6 29 3 3 42 46. 50 5 59. 63 67 7 75.9 80 84 88 92 96. Microns

Fig. 4. Spatial analysis of bacteria relative to visible landmarks. A tiled image (Upper Left) was segmented to identify bacterial cells and to outline the edge of large food particles, host tissue, and the edge of dense colonization (Upper Right; orange, green, and purple lines). Spatial correlation analysis was carried out using the method of linear dipoles (57), which calculates the pair cross-correlation function as the probability that two categories of object are located at a given distance from one another, normalized to their density in the image. This analysis revealed that bacteria tend to localize within 30 μm of the marked edge of colonization, but are underrepresented within 20 μm of the epithelium and within 5–10 μm of large food particles. Interiors of food particles and host tissue (Upper Right, magenta) were excluded from the analysis. Dotted lines indicate 95% confidence intervals generated by dividing the image into 10 radial sectors for analysis. Food particles and host tissue were identified by autofluorescence with 405-nm excitation, and their edges were outlined by eroding the image by seven pixels (∼1 μm) using FIJI. The edge of dense colonization was outlined by hand.

Mark Welch et al. PNAS | Published online October 9, 2017 | E9109 Downloaded by guest on September 30, 2021 2 B. cellulosilyticus 4 Bacteroides 1.5 C. aerofaciens B. caccae 1 C. scindens R. torques 0.5 Pair correlation

0 0.2 2.3 4.4 6.5 8.6 17 10.7 12.8 14.9 19.1 21.2 23.3 24.8 Microns 1.2 B. cellulosilyticus 1 to line 0.8 R. torques to line 0.6 0.4 Pair correlation 0.2 0

0.2 1.9 3.6 5.2 6.9 8.6 10.3 12.0 13.6 15.3 17.0 18.7 20.3 22.0 23.7 24.5 10 µm Microns

Fig. 5. Distinctive community organization in the 10 μm closest to the mucosa. The microbial community near the mucosal epithelium is abundantly populated by B. cellulosilyticus, but R. torques is underrepresented in a narrow band close to the mucosa. The white boxed area in Inset shown in Upper Left denotes the field shown at higher magnification in Upper Left and Lower Left.(Upper Left) A representative image near the mucosa showing all taxa and a 1-μm-thick line representing the edge of microbial colonization. (Upper Right) Pair cross-correlation (PCC) analysis showing the probability of detecting a cell at each distance from the line, normalized to the density of cells in the image. Analysis was carried out using the method of linear dipoles as implemented in DAIME (57). (Lower Left) The B. cellulosilyticus and R. torques channels are shown separately for clarity and to demonstrate the rarity of R. torques in the 5- to 10-μm zone at the edge of the microbe-dense region. (Lower Right) Results of PCC analysis depicted as the mean of all 11 images from two sections in which a 100 μm length and 40 μm width of mucosal border was visible. Confidence intervals of 95% are shown for these two bacterial strains.

linear dipole analysis to calculate the cross-correlation between epithelial border and microbial community, whereas the edge of each taxon and the line. The use of the line, rather than the microbial colonization itself was relatively smooth. The results mucosa itself, was necessary because of crypts and invaginations confirmed the visual observation that R. torques is frequently, in the mucosa that resulted in variable distances between the although not universally, underrepresented in the microbial

B. vulgatus vs. B. cellulosilyticus R. torques vs. B. cellulosilyticus 40 16 2 R2 = 0.193 R = 0.155 12

30 cells 8 20 4 per grid square per grid square R. torques B. vulgatus cells 10 0

0 -4 020406080100 020406080100 B. cellulosilyticus cells per grid square B. cellulosilyticus cells per grid square

B. cellulosilyticus B. thetaiotaomicron B. vulgatus C. aerofaciens R. torques

Fig. 6. Distinctive organization of microbes relative to one another. Abundance of each taxon was tabulated within 1,572 grid squares measuring 19 × 19 μm(cf. individual squares in the heat map in Fig. 2) from a section hybridized with the species-specific probe set 1. Scatter plots of individual taxa show that the abundance of B. cellulosilyticus and B. vulgatus are positively correlated (Upper Left) while the abundance of B. cellulosilyticus and R. torques are negatively correlated (Upper Right). Scatter plots include only those grid squares that contain a high density of bacterial cells (at least 50% of the maximum density). An image of such a densely populated region (Lower)showsthatB. cellulosilyticus and B. vulgatus are abundant in the same region of the image, while the abundance of R. torques is highest where abundance of the Bacteroides is low. These spatial relationships are consistent across mice, as demonstrated by analysis of both mice with the comprehensive probe set 3 (Fig. S4).

E9110 | www.pnas.org/cgi/doi/10.1073/pnas.1711596114 Mark Welch et al. Downloaded by guest on September 30, 2021 community positioned in the 5- to 10-μm region closest to host bacterial probe in conjunction with WGA and a mouse colonic PNAS PLUS cells (Fig. 5). mucin antibody (anti-MCM) to localize mucus (Fig. 7 and Figs. Differences in the distribution of individual taxa relative to one S5 and S6). As before, bacteria were detected in high abundance another were also evident at micrometer scales. Images were di- in regions of the lumen as well as close to the mucosa (Fig. 7 B vided into grid squares of 19 × 19 μm, and bacterial cells within and C). WGA and anti-MCM showed similar staining patterns to each grid square were tallied. Scatter plots comparing the abun- one another (Fig. S5), and a qualitative inspection of the images dance of pairs of taxa within these grid squares showed a linear revealed dense concentrations of mucus in regions corresponding regression with a positive slope (Fig. S3), likely reflecting the to areas of high bacterial density, as well as in goblet cells (Fig. 7 presence of a mixed microbial community in regions of both high B and C and Fig. S6). Large autofluorescent particles, by con- and low microbial abundance. One possibility is that the primary trast, generally occupied regions in which bacteria were not driver of correlations in abundances among taxa is simply the abundant, although small autofluorescent particles were mixed overall abundance of bacterial cells in any given 19 × 19 μmgrid with mucus and bacteria even in regions of highest bacterial square. However, analyzing only “densely populated” grid squares density (Fig. 7D). These results are consistent with the notion (defined as those containing at least half the maximum number of that dense concentrations of mucus support high bacterial den- bacterial cells) revealed differences in taxon distribution (Fig. 6 sity, both in the loose mucus layer at the mucosal border and in and Figs. S3 and S4). For example, abundance of the most the interior of the lumen. prominent taxon, B. cellulosilyticus, was positively correlated with that of B. vulgatus but negatively correlated with R. torques. Discussion Among the possible explanations for these observed distributional We investigated the spatial arrangement of members of a de- differences are cooperative (attractive) versus competitive (re- fined artificial 15-member human gut microbiota in the proximal pulsive) interactions between taxa, or an indirect effect of binding colon of gnotobiotic mice at macroscale, mesoscale, and micro- or proliferation of taxa in distinct microenvironments. meter scale. At a macrolevel scale of hundreds of micrometers, To further investigate factors underlying differences in taxon bacterial cell density was heterogeneous throughout the colon but density and distribution, we imaged the distribution of bacteria, was highest in regions rich in mucus, both in a layer near the ep- mucus, and food in additional cross-sections using the Eub338 ithelium and in patches in the lumen. Compositional “patchiness”

A Bacteria (Eub338-Rhodamine Red X) Mucus (Wheat Germ Agglutinin-Alexa488) Autofluorescence

Bacteria Mucus Food & Tissue Overlay B i ii iii iv

a

b

C i ii iii iv

c MICROBIOLOGY

D abc

Fig. 7. Dense bacterial aggregations occupy regions rich in mucus. (A) Cross-section of colon highlighting location of panels shown at higher magnification below. (B) Bacterial density (i) is heterogeneous in the lumen. Staining with fluorophore-labeled WGA (ii) shows high density of mucus in areas of the lumen that contain abundant bacteria. Large autofluorescent food particles (iii) occupy areas of the lumen in which bacterial density is low. (iv) Overlay of i–iii. (C) Bacterial density (i) is also high in a narrow zone located at the edge of the mucosa. WGA staining (ii) shows a high density of mucus in this zone. Autofluorescent food particles (iii) are located within micrometers of the mucosa. (D) High-magnification views showing regions of the lumen with abundant mucus (a), large food particles (b), and a large food particle pressed close to the mucosa (c). The cross-section shown is adjacent to the one presented in Fig. 2. (Scale bars: A, 200 μm; B and C,50μm; D,10μm.)

Mark Welch et al. PNAS | Published online October 9, 2017 | E9111 Downloaded by guest on September 30, 2021 was observed at a mesoscale (tens of micrometers), while at mi- the native mouse gut microbiota. Moreover, members of a more crometer scales, each microhabitat was generally occupied by a complex community of human gut microbes, representing lineages complex community of microbes intermingled with one another. from Bacteria and other domains of life (e.g., methanogenic This extensive mixing at micrometer scales, the absence of large archaeons and eukaryotes) could demonstrate more pronounced microcolonies associated with the mucosa or food particles, and differences in their replication rates and stronger spatial associa- the broad similarity of luminal and mucosa-adjacent communities tions with one another or with food particles, host cells, mucus, or lead us to view the lumen and mucosa in the proximal colon not as other features of the gut habitat. stratified compartments but as components of a partially mixed The observed spatial arrangement differs dramatically from the bioreactor. By “bioreactor,” we mean an environment constructed highly ordered and more clustered arrangements visible in human to harbor microbes and harness their metabolism of available dental plaque (68). These dissimilarities could reflect a number of nutrients, where the degree of spatial homogenization of com- factors including differences in flow rates in the two ecosystems munity members is a manifestation of a complex dynamic involving and the absence of a surface in the gut to which microbes can many factors including flux of mucus and epithelial cells into the stably adhere. In the mouth, continuous rapid flow of saliva en- lumen, the affinities of community members for these host con- sures that adherence to a surface, either directly or indirectly via stituents and food particles, cooperative/competitive (attractive/ binding to other adherent microbes, is critical for remaining in the repulsive) interactions between microorganisms, and peristaltic habitat. Further, chemical communication in salivary flow is most flow of bulk material through the lumen. effective at distances on the order of micrometers (1) so precise One might have expected a priori that differences between taxa positioning relative to metabolic partners is critical. in their binding affinities for substrates such as mucus or food Deeper understanding of spatial relationships in the gut should particles, combined with more rapid replication in a preferred be gained as methods are developed for quantifying the distribu- microhabitat, would lead to localized clonal expansion. The tion of nutrients and metabolic products over different spatial resulting communities would have spatial structure in the form of scales. Gnotobiotic animal models harboring defined consortia of microcolonies and a distinctive community composition within the microbes and fed diets of known composition and physical (e.g., mucus layer compared with luminal contents. Instead, the spatial particulate) properties represent a starting point for these types of distribution of both substrates and microbes suggests a dynamic studies. For example, follow-up experiments in which gnotobiotic model for the proximal colon in which mixing and dispersal by host mice are fed purified dietary fibers of defined composition and size factors tend to homogenize the community. Such mixing could also could provide an opportunity to identify taxa that exhibit re- explain why large clusters with strongly distinctive taxonomic producible patterns of cooccurrence or spatial association with the composition were not observed between the mucus layer and the population of food particles represented in their colons. In addi- ∼ lumen. The turnover time for mucus is 6 h for mucus in goblet tion, the relative effects of propulsive contractions, nonpropulsive cells and as little as a single hour for the inner mucus layer in the mixing, and/or the rate of renewal of the mucus layer can be ex- distal colon (59). The replication time of two common gut sym- plored using gnotobiotic animals with mutations that affect their bionts, B. thetaiotaomicron and Escherichia coli, has been estimated gut motility and/or the composition of their mucus (e.g., ref. 67). – at 3 h in the mucus layer and 3 8 h in colonic contents (29). Thus, These genetic manipulations can also be applied to gnotobiotic these and other gut bacterial taxa may carry out only a few rounds zebrafish where the transparency of the organism can support in of cell division within the mucus layer before being shed along with vivo imaging of microbial communities (69, 70). This latter feature mucus into the lumen. Adhesion to the epithelium could support avoids a potentially confounding variable; namely, that mesoscale persistence of microbes for a longer time, but epithelial cells are and microscale spatial structure may be disrupted in unknown ways continuously discarded; with the exception of Paneth cells, the during the processing of gut tissues taken from euthanized animals. other three mouse gut epithelial lineages turn over every 3–5d – The resulting datasets should enable modeling both in silico and in (60 64). Microbes in the lumen also have limited opportunity for ex vivo experimental bioreactors, including “gut-on-a-chip” sys- replication before being expelled, as the contents of the gut tra- – – tems (71). Together, these efforts should provide information verse the mouse intestine in 4 6 h (65 67). We hypothesize that about forces that promote or retard mixing at microscale levels. through rapid turnover and mixing of the mucus layer, the epi- Put another way, studies of microscale mixing provide an oppor- thelium, and the gut contents as a whole, the mammalian host acts tunity to determine how this parameter is related to the niches to diminish the ability of the microbiota to establish spatially (“jobs”) of community members (both symbionts and pathogens), segregated communities or sizeable single-taxon agglomerations the expressed functional properties of a microbiota (including its both in the lumen and adjacent to the mucosa. Whether the resiliency to perturbations), and whether changes in this spatial physiology of the microbes themselves also fosters mixing is a feature are a reflection of, or causally related to, various types question raised by the extensive micrometer-scale taxonomic of dysbioses. intermingling in densely populated mucus-rich regions of our im- ages. The bacteria comprising the artificial human gut microbiota Materials and Methods characterized in this study are nonflagellated. Diffusion is unlikely Collection of Samples from Gnotobiotic Mice and Preparation for Imaging. All to be a significant force within the viscous gel of the mucus layer experiments involving mice were performed using protocols approved by the (29), although there is little information about how foraging of Animal Studies Committee of the Washington University School of Medicine. mucus glycans by resident microbes affects mucus viscosity. Re- Two 8-wk-old, male, germ-free C57BL/6J mice were gavaged with a 15-member gardless of the means by which mixing is achieved, its effect is to bacterial consortium prepared and administered using procedures described in diminish micrometer-scale spatial structure in the community. earlier reports (4, 54), and then maintained in a gnotobiotic isolator under a The microbial assemblage we employed was simple enough so strict light cycle (lights on at 0600 hours and off at 1800 hours). Two additional most of the abundant taxa could be simultaneously visualized with mice were gavaged with a two-member bacterial community composed of multilabel FISH and complex enough to permit a variety of pos- B. thetaioatomicron VPI-5482 and E. rectale ATCC 33656, and two control mice sible taxon–taxon interactions and spatial distributions. Inevitably, were maintained as germ-free. All animals were fed a sterilized, low-fat, plant polysaccharide-rich chow (Product 7378000; B&K Universal) ad libitum. All mice our findings are dictated by the microbes that we chose to create were killed 14 d after gavage of their bacterial consortium. this synthetic community. We do not know whether the consor- The distal fourth of the small intestine and the proximal third of the colon were tium of 15 taxa studied display a spatial organization that is rep- snap-frozen in optimal cutting temperature compound and stored at −80 °C. resentative of the native mouse gut microbiota. It is possible that These frozen segments were cut into 5- to 10-mm-long pieces, and molten this low diversity consortium of human gut-derived bacterial 0.5% agarose was pipetted onto the two cut ends of each piece. Samples were strains is less likely to form spatially structured communities than then fixed in 2% paraformaldehyde in PBS for 12 h at 4 °C, then washed,

E9112 | www.pnas.org/cgi/doi/10.1073/pnas.1711596114 Mark Welch et al. Downloaded by guest on September 30, 2021 resubmerged in molten 0.5% agarose, dehydrated in acetone for 1 h, infil- W11261; Invitrogen) in PBS at room temperature for 15 min in the dark. PNAS PLUS

trated with Technovit 8100 glycol methacrylate resin with several changes over Slides were washed briefly in PBS, dipped in distilled H2O, dehydrated 12 h at 4 °C, and were then transferred to embedding solution where they through a series of ethanol washes and mounted as above. Slides to be la- were allowed to solidify for 12 h at 4 °C. Embedded samples were sectioned beled with anti-mouse colonic mucin (anti-MCM, a gift of Dr. Ingrid B. Renes, with a Sorvall JB-4 microtome (Dupont Instruments) to 5–10 μmthickness Erasmus MC-Josephine Nefkens Institute, Rotterdam, The Netherlands) were and subjected to fluorescent labeling experiments. We employed para- treated with blocking buffer (2% goat serum; 1% BSA; 0.2% Triton X-100; formaldehyde rather than Carnoy’s fixative because paraformaldehyde is 0.05% Tween 20) for 1 h at room temperature, incubated with anti-MCM commonly used for microbial FISH (72, 73). Moreover, our direct comparison of diluted 1:50 in blocking buffer for 12 h at 4 °C, rinsed three times for 3 min the two methods revealed similar preservation of mucus and other spatial each in PBS, incubated with blocking buffer at room temperature for 1 h, landmarks in methacrylate-embedded colonic segments fixed with either incubated with a 1:1,000 dilution of Alexa Fluor 633 goat anti-rabbit IgG Carnoy’s solution or paraformaldehyde (74). (catalog no. A21070; Invitrogen) in blocking buffer for 1 h, rinsed three times for 3 min each in PBS, incubated with WGA, washed, and mounted Probe Design. Candidate probes identified using the “probe design” function as above. of the ARB software package (75) were further analyzed by calculating the Δ 0 overall free energy of hybridization ( G overall; ref. 76) for each. A set of 16S Image Acquisition and Linear Unmixing. Spectral image stacks were acquired rRNA-directed oligonucleotides was selected that were predicted to be using a Zeiss LSM 710 confocal microscope equipped with a QUASAR spectral taxon-specific at the same hybridization stringency (arbitrarily chosen to be detector and a Plan-Apochromat 63×, 1.4 N.A. objective lens or a Zeiss LSM ′ 20% formamide). Probes were synthesized (Invitrogen) with a 5 fluo- 780 confocal microscope equipped with a GaAsP spectral detector and a rophore and their specificity evaluated by hybridization to pure cultures of Plan-Apochromat 40×, 1.4 N.A. objective. Excitation wavelengths of 633 nm, target and nontarget bacterial strains. 594 nm, 561 nm, 514 nm, 488 nm, and 405 nm were employed sequentially. Linear unmixing was carried out using ZEN software (Carl Zeiss) or using a FISH Analysis of Colonic Sections. FISH was carried out at 46 °C for 6 h in 0.9 M custom algorithm on the Mathematica platform (Wolfram Research) using NaCl, 0.02 M Tris pH 7.5, 0.01% SDS, 20% HiDi formamide (Applied Bio- the concatenated reference spectra shown in Fig. S1. Details of the unmixing μ systems), and 2 M of each probe. Sections were then washed twice for procedure and figure preparation are given in SI Materials and Methods. 10 min each at 48 °C in wash buffer (0.215 M NaCl, 0.02 M Tris pH 7.5, 5 mM EDTA), incubated in DAPI in PBS at room temperature for 15 min in the dark, Spatial Arrangement Analysis. Images of each taxon were segmented in FIJI washed in PBS, dehydrated through a series of ethanol washes [3 min each using the IsoData or RenyiEntropy global thresholding algorithm (77) and in 50%, 80%, and 96% (vol/vol) ethanol], mounted in ProLong Gold antifade were then imported into DAIME version 2.1 for analysis of spatial arrange- reagent (catalog no. P36934; Invitrogen) with a No. 1.5 coverslip, and placed ment using linear dipoles. in the dark at room temperature for at least 24 h before imaging. FISH on pure cultures was carried out in the same way, but without DAPI staining. ACKNOWLEDGMENTS. We thank David O’Donnell and Maria Karlsson for help with gnotobiotic animal husbandry; Louie Kerr for microscopy support; Lectin and Mucin Staining. Labeling of methacrylate sections with WGA was and Christopher Rieken, Blair Rossetti, and Liping Xun for outstanding techni- carried out after the FISH hybridization and washing steps. Slides were in- cal support. This work was supported in part by NIH Grants DE 022586, cubated in 40 μg/mL WGA conjugated to Alexa Fluor 488 (catalog no. DK30292, DK70977, and DK78669.

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