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Spatially distinct physiology of Bacteroides fragilis within the proximal colon of gnotobiotic mice

Nature Microbiology volume 5, pages 746–756 (2020)Cite this article

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Abstract

A complex microbiota inhabits various microenvironments of the gut, with some symbiotic bacteria having evolved traits to invade the epithelial mucus layer and reside deep within the intestinal tissue of animals. Whether these distinct bacterial communities across gut biogeographies exhibit divergent behaviours is largely unknown. Global transcriptomic analysis to investigate microbial physiology in specific mucosal niches has been hampered technically by an overabundance of host RNA. Here, we employed hybrid selection RNA sequencing (hsRNA-Seq) to enable detailed spatial transcriptomic profiling of a prominent human commensal as it colonizes the colonic lumen, mucus or epithelial tissue of mice. Compared to conventional RNA-Seq, hsRNA-Seq increased reads mapping to the Bacteroides fragilis genome by 48- and 154-fold in mucus and tissue, respectively, allowing for high-fidelity comparisons across biogeographic sites. Near the epithelium, B. fragilis upregulated numerous genes involved in protein synthesis, indicating that bacteria inhabiting the mucosal niche are metabolically active. Further, a specific sulfatase (BF3086) and glycosyl hydrolase (BF3134) were highly induced in mucus and tissue compared to bacteria in the lumen. In-frame deletion of these genes impaired in vitro growth on mucus as a carbon source, as well as mucosal colonization of mice. Mutants in either B. fragilis gene displayed a fitness defect in competing for colonization against bacterial challenge, revealing the importance of site-specific gene expression for robust host-microbial symbiosis. As a versatile tool, hsRNA-Seq can be deployed to explore the in vivo spatial physiology of numerous bacterial pathogens or commensals.

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Fig. 1: hsRNA-Seq enables spatial bacterial transcriptomics during commensal colonization.
Fig. 2: B. fragilis gene expression across gut microenvironments.
Fig. 3: Discovery of candidate mucosal colonization factors in B. fragilis.
Fig. 4: BF3086 and BF3134 promote the robustness of B. fragilis colonization.

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Data availability

RNA-Seq and hsRNA-Seq data have been deposited in the NCBI SRA under accession no. PRJNA438372. The B. fragilis NCTC 9343 genome used for mapping is available at GenBank under assembly no. GCA_000025985.1. Source data for Figs. 1–4 and Source Data Extended Data Figs. 1, 8, 9 and 10 are included in this article.

Code availability

The code used in the analysis is available at https://github.com/wenchichou/bugInHost.

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Acknowledgements

We thank E. Hsiao, E. Martens, D. Gevers, C. Desjardins, B. Haas and J. Livny for helpful discussions, and members of the Mazmanian laboratory for comments. G.P.D. was supported by an NIH training grant no. 5T32 GM07616, National Science Foundation Graduate Research Fellowship no. DGE-1144469 and the Center for Environmental Microbial Interactions at Caltech. The project was funded by NIH grant no. U19AI110818 to the Broad Institute; NIH grant no. DK110534 to H.C.; NIH grant nos. GM099535 and DK078938, and the Heritage Medical Research Institute to S.K.M.

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Author notes

  1. These authors contributed equally to this work: Gregory P. Donaldson, Wen-Chi Chou.

Authors and Affiliations

  1. Divison of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA

    Gregory P. Donaldson & Sarkis K. Mazmanian

  2. Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Wen-Chi Chou, Abigail L. Manson, Peter Rogov, Thomas Abeel, James Bochicchio, Dawn Ciulla, Alexandre Melnikov, Georgia Giannoukos & Ashlee M. Earl

  3. Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands

    Thomas Abeel

  4. Department of Pathology, University of California, San Diego, CA, USA

    Peter B. Ernst & Hiutung Chu

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  1. Gregory P. Donaldson
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Contributions

G.P.D. and S.K.M. conceived the study. G.P.D., W.-C.C., G.G., A.M.E. and S.K.M. designed the study. G.P.D. prepared the samples for sequencing and performed the mouse colonization and microbiology experiments. D.C., P.R., J.B., A.M. and G.G. performed the hybrid capture and sequencing experiments. W.-C.C., A.L.M. and T.A. performed the computational analysis. H.C. performed the colitis model and flow cytometry. P.B.E. scored the sections for histology. G.P.D., W.-C.C. and A.L.M. created the figures. A.M.E. and S.K.M. supervised the work. G.P.D., W.-C.C., A.L.M., A.M.E. and S.K.M. wrote the paper. All authors provided input on the paper.

Corresponding authors

Correspondence to Gregory P. Donaldson, Ashlee M. Earl or Sarkis K. Mazmanian.

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Extended data

Extended Data Fig. 1 Intestinal biogeography of Bacteroides fragilis during mono-colonization.

a, CFU per gram of lumen content and b, CFU per cm of mucus from indicated regions of intestine after 4 weeks of mono-colonization with wild-type B. fragilis (mean and standard error, n = 4 animals). c, CFU per sample in lumen, mucus, and tissue samples of the proximal intestine of mice mono-colonized for 4 weeks with wild-type B. fragilis (mean and standard error, n = 4 animals). These samples were collected using the same dissection method used to prepare samples for RNA-Seq (Fig. 1a).

Source data

Extended Data Fig. 2 Individual mouse correlation plots to assess hybrid selection performance.

Correlation plots for HS vs non-HS in individual mice (3 individual-mouse samples from lumen, 3 from mucus, and 3 from tissue, Pearson’s r). Each dot represents a single gene.

Extended Data Fig. 3 Host gene expression comparisons between samples with and without hybrid selection.

Total RNA-Seq reads were mapped to mm10 mouse genome using STAR, and the mapped reads were converted into read counts for each gene by HTSeq. After excluding genes with < 10 reads mapping across any sample, the read counts for each sample were normalized by TPM (Transcripts Per Million). Each dot represents a single gene. The average TPM for each gene is shown from non-hybrid selected libraries (x-axis) and hybrid selected libraries (y-axis) (n = 3 animals, Pearson’s r).

Extended Data Fig. 4 Normalized gene expression levels with and without hybrid selection are highly correlated with few outliers.

Each gene is represented by a single dot. The correlation coefficients for lumen, mucus, and tissue are 0.99, 0.96, and 0.98, respectively. Outliers where the difference between the HS and non-HS values is larger than three standard deviations are numbered and listed in Supplementary Table 3. These represent primarily short genes (median length 110 nucleotides), particularly tRNA and 5 s rRNA genes. Short genes (<200 nt) are colored blue, showing that most protein-coding genes are enriched properly.

Extended Data Fig. 5 Correlation in gene expression between different sample sites was improved with hybrid selection.

Each dot represents a single gene with all genes plotted (n = 3 animals, Pearson’s r).

Extended Data Fig. 6 Structural modeling for genes of interest using Phyre.

a, The predicted structure for BF3134, modeled using Phyre72, indicated that BF3134 is a likely cyclo-malto-dextrinase, closely related to neopullulanase and maltogenic amylase and a member of glycosyl hydrolase family 13 (96% of the sequence was modeled with 100% confidence to the cyclo-malto-dextrinase template c3edeB, with 42% identity). b, Secondary structure prediction for BF3134 using Phyre. Pfam domain analysis for BF3134 also indicated the presence of an N-terminal cyclo-malto-dextrinase domain (PF09087), a central alpha-amylase domain (glycosyl hydrolase family 13; PF00128), and a C-terminal cyclo-malto-dextrinase domain (PF10438). c, The predicted structure for BF3086 indicated a role as an acetylglucosamine-6-sulfatase (93% of the sequence was modeled with 100% confidence by the single highest scoring template, c5g2va, an n-acetylglucosamine-6-sulfatase, with 51% identity). d, Secondary structure prediction for BF3086. Pfam domain analysis indicated the presence of a sulfatase domain, in addition to a domain of unknown function (DUF4976) downstream of the sulfatase domain. The region aligned by Phyre with the c5g2va template included both the regions encompassed by the Pfam sulfatase domain, as well as the Pfam domain of unknown function (DUF4976).

Extended Data Fig. 7 BF3086 and BF3134 are conserved and share a potential regulatory motif.

a, Phylogeny of 92 Bacteroides and Parabacteroides strains74 showing the presence of BF3086 and BF3134 orthologues, with horizontal bar graphs indicating the percent protein sequence identity to the studied type strain (NCTC9343, highlighted with red font). The teal box indicates strains that can be confidently assigned to the B. fragilis species (average pairwise ANI78 between them is 98%, whereas it falls below 95% for the next-closest strains also labeled as B. fragilis). The black squares indicate the presence of the conserved upstream motif (0-2 mismatches), using the GLAM2Scan algorithm75. b, Sequence of the conserved motif upstream of both genes. The asterisk (*) at position 18 indicates a position that differs between the upstream regions of the glycosyl hydrolase (BF3086) and the sulfatase (BF3134). The glycosyl hydrolase upstream region has an “A” at this position, whereas the sulfatase upstream region has a deletion at this position.

Extended Data Fig. 8 Additional in vitro and in vivo phenotypes of ∆BF3086 and ∆BF3134.

a, BF3086 and BF3134 biological replicates. Fold-change for individual mice indicate consistently induced expression of BF3086 and BF3134 in the mucus and tissue relative to the lumen. b-e, Growth of individual B. fragilis strains in a defined minimal medium with b, inulin, c, pullulan, d, mannan, or e, pig mucin (mean and standard error, n = 8 independent cultures). f-h, Quantitative RT–PCR (∆∆Ct method normalized to gyrB) on fecal samples of mice mono-colonized with indicated strains of B. fragilis, assessing the expression of f, ccfC (BF3581), g, PSB flippase (BF1900), and h, PSC flippase (BF1014) (mean and standard error, Tukey ANOVA, n = 4 animals).

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Extended Data Fig. 9 BF3134 is required for B. fragilis protection from experimental colitis.

a, Mice were mono-colonized with B. fragilis strains at weaning (3 weeks of age) before inducing DNBS colitis at 7 weeks of age. Body weights of mice were measured every 24 hours and are represented as a percentage of their starting weight on day 0 (Tukey 2-way ANOVA, n = 10, 9, 9, representative of two independent experiments). b, 72 hours after colitis induction, mice were sacrificed and the length of the colon from rectum to the cecal junction was dissected (representative images of 3 colons per group, images normalized to size using rulers and then cropped around the colon) and c, colon length measured (Tukey ANOVA, n = 10, 9, 9). d, Histopathologic scores of whole colons (max 48, mean and interquartile range, Tukey ANOVA, n = 10, 9, 9). e, Quantitative RT–qPCR (∆∆Ct method normalized to gyrB) on fecal samples of mice mono-colonized with indicated strains of B. fragilis, assessing the expression of the PSA flippase (BF1369) (Tukey ANOVA, n = 4 animals). f, Lymphocytes isolated from mesenteric lymph nodes of mono-colonized, DNBS-induced mice were analyzed using flow cytometry. IL-17A-producing T cells quantified as a percent of total CD4 + Foxp3 + regulatory T cells (Tukey ANOVA, n = 10, 9, 9 animals). g, IL-10-producing T cells quantified as a percent of total CD4 + Foxp3 + regulatory T cells (Tukey ANOVA, n = 10, 9, 9 animals, representative of two independent experiments) (all panels unless noted: mean and standard error, * p < 0.05, ** p < 0.01, *** p < 0.001).

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Extended Data Fig. 10 Control experiments and flow cytometry methods for DNBS colitis.

a, Quantitative RT–qPCR (∆∆Ct method normalized to gyrB) for PSA flippase (BF1369) in lumen, mucus and tissue samples (mean and standard error, n = 4 animals). Fold-change between sample sites was quantified within each mouse individually. b, Mice mono-colonized with indicated strains of B. fragilis for one month were treated with 50% ethanol, the vehicle control for DNBS colitis induction. Mice were weighed every 24 hours, graphed as a percentage of their weight at day 0 (Tukey 2-way ANOVA, n = 5, 4, 4). c, 72 hours after treatment the mice were sacrificed and the length of the colon was measured from rectum to the cecal junction (Tukey 2-way ANOVA, n = 5, 4, 4) d, Example live cell gating for flow cytometry in Extended Data 9f and 9 g (representative from two independent experiments with similar results). e, Example flow plots (1 from each group) for assessing the proportion of IL-10 and IL-17 positive regulatory T cells, as quantified in Extended Data 9f and g (representative from two independent experiments with similar results, mean and standard error in graphs, * p < 0.05).

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Supplementary information

Supplementary Information

Supplementary Tables 1, 2, 7, 9 and references. Descriptions for Supplementary Tables 3–6, 8 and 10.

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Supplementary Tables 3–6, 8 and 10.

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Donaldson, G.P., Chou, WC., Manson, A.L. et al. Spatially distinct physiology of Bacteroides fragilis within the proximal colon of gnotobiotic mice. Nat Microbiol 5, 746–756 (2020). https://doi.org/10.1038/s41564-020-0683-3

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