Functional transcriptomics in diverse intestinal epithelial cell types reveals robust gut microbial sensitivity of microRNAs in intestinal stem cells

Gut microbiota play an important role in regulating the development of the host immune system, metabolic rate, and at times, disease pathogenesis. The factors and mechanisms that mediate communication between microbiota and the intestinal epithelium are poorly understood. We provide novel evidence that microbiota may control intestinal epithelial stem cell (IESC) proliferation in part through microRNAs (miRNAs). We demonstrate that miRNA profiles differ dramatically across functionally distinct cell types of the mouse jejunal intestinal epithelium and that miRNAs respond to microbiota in a highly cell-type specific manner. Importantly, we also show that miRNAs in IESCs are more prominently regulated by microbiota compared to miRNAs in any other intestinal epithelial cell (IEC) subtype. We identify miR-375 as one miRNA that is significantly suppressed by the presence of microbiota in IESCs. Using a novel method to knockdown gene and miRNA expression ex vivo enteroids, we demonstrate that we can knockdown gene expression in Lgr5+ IESCs. Furthermore, when we knockdown miR-375 in IESCs, we observe significantly increased proliferative capacity. Understanding the mechanisms by which microbiota regulate miRNA expression in IESCs and other IEC subtypes will elucidate a critical molecular network that controls intestinal homeostasis and, given the heightened interest in miRNA-based therapies, may offer novel therapeutic strategies in the treatment of gastrointestinal diseases associated with altered IESC function.

elucidate a critical molecular network that controls intestinal homeostasis and, given the heightened interest in miRNA-based therapies, may offer novel therapeutic strategies in the treatment of gastrointestinal diseases associated with altered IESC function.
The intestinal epithelium is a single layer of cells exposed to the intestinal lumen, and is composed of multiple cell types including the proliferative IESCs and progenitor cells (also known as transit amplifying cells), as well as differentiated absorptive enterocytes and secretory goblet, Paneth, and enteroendocrine cells (EECs). IESCs divide to yield more rapidly proliferating progenitors that give rise to all of the other IEC types and drive continuous renewal of the intestinal epithelium every ~3-5 days(1). Proper renewal facilitates important intestinal epithelial functions including barrier integrity to protect against invasion of harmful toxins present in the intestinal lumen, nutrient digestion and absorption, and production of hormones that regulate systemic energy homeostasis. These physiological processes are mediated in part by interactions with resident microbiota (2). Studies using germ-free animals have demonstrated that gut microbiota influence intestinal barrier function, nutrient absorption, proliferation, differentiation, cellular signaling, and migration (3,4). However, the molecular factors and mechanisms underlying microbiota-mediated control of IEC functions, particularly IESC proliferation, are unknown. miRNAs have emerged as critical regulatory factors of many biological processes in numerous tissues and are known to confer phenotypic robustness in response to environmental stimuli (5). However, less is known about miRNA expression and function in the intestinal epithelium compared to most other tissues. Recently, miRNAs were implicated in the regulation of IEC physiology (6,7). McKenna et al. (2010) demonstrated in mice that the IECspecific knockout of Dicer1, an essential enzyme for canonical miRNA biogenesis, results in altered IEC proliferation, differentiation, nutrient absorption, and impaired barrier function, indicating that miRNAs are likely important modulators of intestinal homeostasis (6). Furthermore, the presence of microbiota in the gut has been shown to alter miRNA expression profiles in intestinal macrophages (8), as well as in whole intestine (9,10). Understanding the mechanisms by which microbiota regulate miRNA and gene expression in IESCs and other IEC subtypes will elucidate a critical molecular network that controls intestinal homeostasis and, given the heightened interest in miRNA-based therapies, may offer novel therapeutic strategies in the treatment of gastrointestinal diseases associated with altered IESC function. However, no study to date has investigated miRNA expression and activity across the functionally distinct IEC subtypes, and cell-type specific effects of microbiota on miRNAs is completely unknown. We hypothesized that each IEC population has a distinct miRNA profile, and that miRNAs respond to gut microbiota in a cell-type specific manner in order to control function and overall homeostasis of the intestinal epithelium.

RESULTS
Germ-free mice have an altered jejunal IEC composition compared to their conventionalized and conventionally-raised counterparts-We selected the well-characterized Sox9-EGFP transgenic mouse model to evaluate miRNA expression and response to microbiota in functionally distinct IECs. This model was originally created by GENSAT (11), who developed the model by randomly inserting into the mouse genome a BAC containing the EGFP gene driven by the cloned genomic regions upstream and downstream of Sox9 (12). A beneficial feature of this model is that EGFP expression is fully penetrant within the mouse intestine, which permits the isolation and analysis Mean percentage of each IEC subtype sorted from jejunum of conventionally-raised (CR), germ-free (GF) and conventionalized (CV) mice (n=4 each). Error bars depict standard error of the mean. Significance determined using twotailed unpaired t-Test relative to CR, and is denoted as follows: * p < 0.05. c) Cartoon showing location and types of IECs in the Sox9-EGFP animal. Listed are miRNAs with mean expression in reads per million mapped to miRNAs (RPMMM) across all CR, CV, and GF animals that were found to be at least 2-fold enriched in each respective population. Fold enrichment indicates enrichment of the miRNA to the IEC subpopulation with the next highest mean expression. Only miRNAs with RPMMM > 400 in at least one sample are included in the analysis.

Sox9-EGFP mice (4 per group)
Small RNA-seq RNA-seq of Sox9 Low of four distinct IEC populations (12). Applying the same fluorescence-activated cell sorting (FACS)based approach used to isolate IESCs from the commonly used Lgr5-EGFP model, which demonstrates mosaic expression among crypts in the intestine, both actively cycling IESCs (Sox9 Low ) and transit-amplifying progenitor cells (Sox9 Sublow ) can be isolated from the Sox9-EGFP mouse intestine (12,13). Moreover, two additional differentiated cell populations can also be isolated on the basis of variable EGFP intensity, including Sox9 Neg (mostly differentiated enterocytes as well as goblet cells and Paneth cells), and Sox9 High (primarily EECs as well as reserve/quiescent +4 stem cells) (12)(13)(14)(15)(16)(17).

Littermates
To evaluate the effect of microbiota on miRNA expression in IECs, we first took a conventionalization approach (Figure 1a). A twoweek conventionalization was selected because previous studies show this to be a time point at which the gene expression profile begins stabilizing in the small intestine of young mice following conventionalization (18)(19)(20). After generating germ-free (GF) Sox9-EGFP animals at the University of North Carolina at Chapel Hill (UNC) Gnotobiotic core facility, we selected four pairs of female GF Sox9-EGFP littermates from 4 different litters born between February and July 2015. One littermate from each pair was randomly selected at 8-10 weeks of age for conventionalization.
The 2-week conventionalization resulted in slightly decreased body weight relative to the remaining germ-free sibling, along with a commensurate increase in liver weight (Supplemental Figure 1). However, no differences were observed in length of the small intestine or colon between GF and conventionalized (CV) animals (Supplemental Figure 1). IECs were collected from the midregion of the small intestine (Methods), hereafter referred to as jejunum, of the GF and CV animals and FACS was performed based on Sox9-EGFP intensity (Figure 1a). Special care was taken to gate out cellular debris, dead and dying cells, immune cells, and multiplets during FACS (See Methods, Supplemental Figure 2). Additionally, a strict gating scheme was used to avoid contamination between cell populations.
We began by comparing the abundances of each major IEC subpopulation in GF and CV animals to conventionally-raised (CR) chow-fed animals. We found very similar abundances of Sox9 Sublow cells (transit amplifying) and Sox9 Neg cells (enterocytes, Paneth, and goblet) in CV and GF populations relative to CR mice ( Figure 1b). Notably, GF mice had significantly more Sox9 High cells (EECs) than CR mice (fold change=2.04, p=0.04, Figure 1b), which is consistent with previous studies comparing EECs in the jejunum of GF and CR rodents (21,22). Also, there were on average fewer Sox9 Low cells (actively cycling IESCs) in GF mice relative to CR and CV mice, which has not been shown before, but could help explain previous reports suggesting reduced proliferation in the small intestine of GF animals (23)(24)(25). IESCs demonstrate robust transcriptional changes in response to gut microbiota-To evaluate the transcriptional changes that occur in response to conventionalization in the IESCs of GF and CV animals, we performed RNA-sequencing analysis on the Sox9 Low population (which we will refer to as IESCs for simplicity). We identified 823 genes and long, non-coding RNAs (lncRNAs) significantly elevated in GF IESCs and 334 genes and lncRNAs significantly elevated in CV IESCs (Supplemental Figure 3a). Gene Ontology Biological Process(26, 27) enrichment analysis using Enrichr (28) revealed that genes elevated in CV IESCs are most significantly over-represented in pathways related to proliferation such as 'mitotic cell cycle' and 'nuclear division' (Supplemental Figure 3b). The genes elevated in GF IESCs genes were associated with processes related to hormone secretion and transport (Supplemental Figure 3b). Consistent with these findings, we observed that established markers of proliferation (Ccnb1, Cdk1, and Mki67) are significantly up-regulated, positive transcriptional regulators of IESC proliferation and self-renewal (Gata4 and Gata6) are up-regulated, and negative regulators of IESC proliferation and self-renewal (Bmp4) are down-regulated in CV IESCs (Supplemental Figure 3c). Also, some, but not all, classic markers of enteroendocrine cells are upregulated in GF IESCs (Supplemental Figure 3c), which could indicate some priming for cells to enter the EEC lineage, consistent with our observation that GF mice have more Sox9 High cells. Known markers of reserve (quiescent) stem cells were not significantly different between CV and GF IESCs (Supplemental Figure 3c), nor were markers for Paneth cells (Lyz), goblet cells (Muc2), and enterocytes (Elf3). These data confirm that the Sox9 Low cells are indeed enriched for IESCs and that CV IESCs harbor a gene signature consistent with increased proliferative capacity. As miRNAs are known regulators of proliferation and differentiation, we performed small RNA-sequencing of each of the functionally distinct IEC subpopulations from four CR, GF, and CV animals. miRNAs show cell-type specific expression across functionally distinct populations of IECs-Total RNA was isolated from the four sorted populations from each animal, as well as from non-sorted IECs (NS IECs; NS IECs were purified by FACS, but not sorted based on Sox9-EGFP intensity). Small RNA-sequencing was performed in three batches, two of which contained small RNA libraries from sorted and unsorted IECs from two GF animals and two CV animals. The third batch contained libraries of the four CR animals. miRNAs and their isomiRs were aligned and quantified using miRquant, our previously described method (see Methods for details) (29). To test our hypothesis that miRNAs are differentially expressed among functionally distinct IEC subtypes, we evaluated miRNAs with an expression level of at least 400 reads per million mapped to miRNAs (RPMMM) in one or more samples, identifying 149 robustly expressed miRNAs across all IEC populations.
Many miRNAs were uniquely enriched in one IEC subtype relative to all others (>2-fold more highly expressed than any other cell type across all samples; Figure 1c). For example, we found that miR-215 and miR-194 are enriched in Sox9 Neg cells, which consist primarily of enterocytes. Both of these miRNAs are processed from a single primary miRNA transcript on Chr1 and were previously shown to be induced by HNF4α during differentiation of Caco-2 colon carcinoma cells (30).

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Sox9 High cells (EECs and reserve stem cells),
including miR-182-5p and miR-183-5p ( Figure  1c), which are also generated from a single primary miRNA transcript. Consistent with enrichment in a subpopulation of cells composed largely of EECs, miR-182 has been shown to have important functions in other endocrine cells, specifically, pancreatic beta cells (31). Unexpectedly, we did not find any miRNAs enriched in the Sox9 Low IESCs or Sox9 Sublow progenitors, which are the only actively proliferating cell populations (Figure 1c).
To further assess variability within and across samples, we performed principal component analysis (PCA) to reduce dimensionality and assess the effect of microbial presence on each sample. The first three principal components (PC1-PC3) captured 67% of the variability across samples. Using biplots we evaluated segregation of samples by cell type and mouse condition (GF, CV, or CR). We showed that miRNA expression profiles are sufficient to cluster most samples by their respective cell types regardless of microbial status (Figure 2a & 2b). For example, Sox9 Neg cells and NS IECs are tightly clustered, which is expected given that NS IECs are composed of 85-90% Sox9 Neg cells. In the first biplot, GF Sox9 Low IESCs do not cluster together with CV and CR Sox9 Low IESCs ( Figure  2a), which indicates that IESCs are particularly sensitive to the presence or absence of microbiota. However, when PC1 and PC3 are projected, clear cell type specific clustering is observed regardless of mouse condition (Figure 2b), suggesting that the subset of miRNAs loaded into PC2, some 40 miRNAs, contribute to the grouping observed in Figure 2a. Taken together, these data indicate strong cell type specific expression of miRNAs across IEC populations and a robust effect of microbial presence on the IESC population specifically. Both observations are supported by visualization of the most highly expressed miRNAs across GF and CV samples ( Figure 2c). miRNAs of IESCs are the more responsive to microbial presence than other IEC types-To evaluate the cell type specific responses to microbiota and account for batch and littermate effects, we used a linear modeling approach (See Methods). We found the expression levels of 11 miRNAs (miR-34a-5p, miR-200c-3p, miR-200c-3p-1, miR-143-3p, miR-130b-3p, miR-140-3p+1,   miR-378-3p+1, miR-20a-5p, miR-17-5p, miR-93-5p, and miR-29a-3p) to be significantly influenced by microbial status across all cell populations. These miRNAs in general are elevated in CV mice across all cell populations, though the magnitude of effect is always most pronounced in the Sox9 Low (IESC) population. When we considered cell type specific responses to microbiota in the functionally distinct subpopulations, we were surprised to find miRNAs are only significantly changing in the IESC population in response to microbiota, whereas no miRNAs were identified as significant changed in the Sox9 High , Sox9 Sublow , or Sox9 Neg populations (Figure 3a, Supplementary File 1). A total of 19 miRNAs were significantly altered by microbiota in IESCs (Figure 3b), which underscores the highly cell-type specific miRNA response to microbiota. Of these 19 microbiota-sensitive miRNAs in IESCs, miR-375-3p is ~2.5-fold (FDR=0.003) reduced in CV IESCs compared to GF IESCs and is the most highly expressed (Figure 3a & 3b). Notably, miR-375-3p is 2.4-and 7.2-fold more highly expressed than the next-most significant microbiota-sensitive miRNA in the CV and GF IESC populations, respectively (Figure 3b). We also found that its isomiRs, miR-375-3p-1 and miR-375-3p+1, are also both significantly downregulated in IESCs upon conventionalization (FC=-2.45, FDR=0.0006; and FC=-2.47, FDR=0.02, respectively; Figure 3b). qRT-PCR in Sox9 Low cells confirmed that the miR-375-3p family is significantly downregulated by conventionalization (FC= -3.85, p=0.03; Figure  3c). Of note, miR-375-3p exhibits rather low expression in Sox9 Sublow progenitors and Sox9 Neg cells (Figure 3d). Although miR-375-3p is highly expressed in Sox9 High EECs, it is not altered in EECs by conventionalization, and is only significantly downregulated by microbiota in the IESCs. Knockdown of gene expression in IESCs of ex vivo enteroids using gymnosis-To functionally evaluate the effect of the observed miRNA and gene expression changes, we sought out methods to downregulate gene expression in IESCs of ex vivo enteroid culture systems, which have been shown to maintain in vivo cellular composition and molecular gene expression profiles over time (32). We evaluated the use of gymnosis, a term coined by the Troels Koch laboratory in 2009 (33), to describe a process of introducing modified or locked nucleic acids (LNA) complementary to a specific gene or miRNA into cells without the use of traditional transfection reagents. Gymnosis has been used previously to knockdown gene expression in enteroids (34), however knockdown capacity specifically in IESCs has not been evaluated. To evaluate whether IESCs of ex vivo cultured enteroids would take up LNAs introduced through the media and/or matrigel via gymnosis and downregulate target gene/miRNA expression (Figure 4a), we tested knockdown efficacy of an LNA against EGFP (LNA-EGFP) in Lgr5-EGFP + enteroids (Figure 4b, Supplemental Figure 5a-c). We identified EGFP + crypts immediately after seeding into matrigel, and followed the growth of the enteroid over the course of 8 days (Supplemental Figure 5b). As Lgr5-EGFP crypts demonstrate mosaic expression (in our colony, approximately 1 in 30 crypts are EGFP + ), qRT-PCR analysis was inconclusive (data not shown). However by Day 4, there was an appreciable depletion of EGFP based on fluorescence imaging, indicating successful knockdown of gene expression in IESCs of ex vivo enteroids using gymnosis. Knockdown of miR-375-3p in enteroids results in increased proliferation-To test the functional effect of miR-375-3p downregulation, we knocked-down miR-375-3p by gymnosis in enteroids. We achieved a robust ~700-fold knockdown of miR-375-3p at day 8 using a LNA inhibitor complementary to miR-375-3p (LNA-375; Figure 4c). At both day 4 and 8, LNA-375 treated enteroids exhibited dramatically increased budding (Figure 4d & 4e, Supplemental Figure 6ac), a marker of IESC proliferative capacity (35,36), relative to Mock and LNA-Scramble treated enteroids. Consistent with this finding, whole mount staining of the enteroids also showed increased Ki67 upon knockdown of miR-375-3p (Figure 4f), though no difference in enteroid size (Supplemental Figure 6d) nor passage efficiency was observed (data not shown). These data indicate that miR-375-3p is a potent regulator of IESC proliferation and that microbiota may regulate IESC renewal in part via modulation of miR-375-3p ( Figure 5). Bright field (BF) and FITC fluorescence images are shown for each treatment. A final merged image contains stacked BF and FITC images, as well as TxRed, which was used to estimate autofluorescence. As enteroids are three-dimensional (3D) and filled with shed cells, the enteroid center may exhibit fluorescence due to its shape and density (autofluorescence) and/or accumulation of EGFP either secreted from or within shed cells. Dashed and solid white lines are used to indicate the region of focus on the 3D enteroid, which have minimal projection into the z-frame. Cells that fall between the solid and dashed lined are used to determine knockdown efficacy. c) Relative quantitative values (RQVs) are shown for miR-375-3p in Mock, LNA-375, and LNA-Scramble treated enteroids isolated from female germ-free (GF) Sox9-EGFP mice at Day 8 as measured by qRT-PCR relative to U6. d) Mean percent of enteroids isolated from female GF Sox9-EGFP mice with 0, 1, 2, or 3+ buds at Day 4 and Day 8 following Mock (n=12), LNA-375 (Day 4 n=12, Day 8 n=11), or LNA-Scramble (Day 4 n=12, Day 8 n=9) uptake by gymnosis. Data is combined from 3 independent experiments, consisting of 3-4 wells per condition. e) Representative images of enteroids isolated from female GF Sox9-EGFP mice at Day 1, Day 4, and Day 8, following Mock, LNA-375, or LNA-Scramble uptake by gymnosis. Sox9-EGFP expression (FITC/green) is overlaid on the bright field images. f) Confocal images of whole mount enteroids stained for Ki67 and DNA (DAPI). Experiments were performed in duplicate or triplicate. The 'n' refers to number of wells. Significance was determined using a Student's two-tailed unpaired t-Test relative to Mock (black asterisks) or LNA-Scramble (blue asterisks). * p < 0.05, ** p < 0.01, *** p < 0.001. Error bars depict standard error of the mean. Scale bars depict 80 µm.

DISCUSSION
In this study, we have provided novel evidence that miRNAs are responsive to the presence of gut microbiota in a cell-type specific manner. Microbiota exert the strongest effect on host miRNA expression in the Sox9 Low population, which is highly enriched in IESCs (12-14, 16, 37). Subpopulation analysis was necessary to identify this effect, as IESCs make up only 1-3% of all IEC types. miR-375-3p was identified as significantly downregulated in the IESC population in response to microbiota, and follow-up experiments ex vivo demonstrated miR-375-mediated control of IESC expansion and proliferation, thereby providing a mechanism by which microbiota may regulate these processes during conventionalization in vivo. miR-375-3p has been associated previously with the regulation of proliferation and differentiation in several tissues (34,38,39). It is predicted to target many members of the Wnt/β-catenin and Hippo signaling pathways, but so far has only been experimentally shown to directly inhibit Frizzled-8 (39) and Yap1 (40). miR-375-3p has been knocked down systemically in mice, and while the authors did not study intestinal proliferation, they observed an increased rate of intestinal transit (41). miR-375-3p is best studied in the context of pancreatic endocrine cell differentiation and function(42-44), and more recently, Knudsen at al. (2015) identified a role for miR-375-3p in regulating EEC differentiation as well (34). We found that miR-375-3p is robustly expressed in both IESCs and EECs; however, we observed that miR-375-3p is responsive to microbiota only in IESCs (Figure 3d). This observation might suggest cell type specific microbial signaling pathways and cell type specific roles for miR-375-3p.
Our RNA-sequencing analysis, the first to our knowledge comparing GF and CV IESCs, demonstrates substantial gene expression differences in IESCs in response to microbiota. CV IESCs showed upregulation of genes associated with proliferation. Of note, our data indicate a ~4-fold increase in Lgr5 mRNA expression (Supplemental Figure 3c). Microbiota may regulate Wnt signaling upstream of Lgr5, an R-spondin ligand receptor, as known upstream regulators of Lgr5 are also altered by the presence of microbiota, including Gata4, Gata6, and Bmp4 (Supplemental Figure 3c) (45,46). This is a finding that deserves further investigation.
An unexpected finding was that GF IESCs (Sox9 Low ) have a gene and miRNA expression profile demonstrating some similarity to Sox9 High cells. Given the careful sorting protocol, and the observation that Sox9 High enriched genes and miRNAs change in both the upward and downward directions within the Sox9 Low population, our finding is unlikely to be solely driven by contamination between populations. One possible explanation is that Sox9 Low cells are primed for the EEC lineage in the absence of microbial influence. Alternatively, one of the caveats of the Sox9-EGFP model is that while the Sox9 High populations consist primarily of EECs, they also include a small population of reserve stem cells (17). It is therefore possible that microbiota influence the maintenance of reserve stem cells in addition to their role in regulating actively cycling IESCs through miR-375-3p, though the gene expression data does not fully support this hypothesis. Though outside the scope of this study, more research including single cell analyses will need to be conducted to delineate more precisely the differences between GF and CV IESCs, as well as to determine which miRNAs are involved in the maintenance of active and quiescent IESC states.
An important added value of our study is the first ever map of miRNA expression across different IEC subtypes, and the cell type specific influence of microbial conventionalization on miRNA expression. We also provide evidence that IESC microbiota-sensitive miR-375-3p influences IEC proliferation, most likely through physiological maintenance of actively cycling IESC. Of course many questions still remain, including how microbiota influence miRNA expression in IESCs. This phenomenon may be explained by direct and/or indirect mechanisms. Regarding the former, although thus far bacteria have only been found to reside within the crypts of the caecum and colon, where microbial density is highest (47), it nevertheless remains a possibility that bacteria residing within the jejunal crypt may directly influence miRNAs in the stem cell subpopulation. Indirect mechanisms are also possible, such as changes in the microenvironment (metabolites and bacterial endotoxins) or through indirect signaling by immune or mesenchymal cells, which were not profiled in this study. Though outside the scope of this analysis, further research is certainly warranted to investigate the interesting relationship between host miRNAs and resident microbiota.
It is also important to note that each segment of the intestinal epithelium has distinct physiological roles and differing magnitudes of microbial load. Our study only examined changes in response to microbiota in IECs from the jejunum. In the future it would be important to assess differences in cell type specific responses to microbiota along the entire length of the intestine. Additionally, it would be interesting to investigate cell type specific responses to microbiota in other populations not sorted herein, including goblet and Paneth cell populations. These cell types do not express Sox9-EGFP, and are rare cell populations in the Sox9 Neg fraction, which is comprised primarily of enterocytes. Nevertheless, Paneth and goblet cells may experience robust changes in response to microbial presence based on their known functions. While our current study focuses on the Sox9-EGFP model, which precluded examining these populations, they deserve attention in future work.
From an experimental standpoint, our study also provided validation of an important new tool to knockdown gene expression in IESCs of intestinal enteroids using gymnosis, a technique that does not rely on cytotoxic transfection reagents (33,34). While not fully investigated in our study, it is possible that gymnosis allows for the uptake of LNAs into other IEC types in addition to IESCs. A previous study using transfection of LNAs in an intestinal cell line, indicate stable knockdown of target miRNAs following a single transfection after 21 days(48), emphasizing the stability of LNAs in culture. While ex vivo culture demonstrates significantly more proliferation, further investigation of the stability of LNAs in enteroids, as well as the knockdown efficacy in other cell types is warranted to evaluate the full utility of this assay. Nevertheless, knockdown of gene expression in enteroids and in stem cells has proven quite difficult, requiring electroporation and adenoviral mediate knockdown. This study presents a quick and affordable alternative to knockdown gene and miRNA expression in IESCs of enteroids.

CONCLUSIONS
In summary, we provide novel data on the miRNA landscape in four distinct cell populations from the intestinal epithelium, and demonstrate that miRNA profiles are very different across the IEC subtypes, and also that miRNAs respond to the presence of microbiota in a highly cell type specific manner. IESCs demonstrate robust gene and miRNA expression changes at 14 days postconventionalization. We investigate one IESC microbiota-sensitive miRNA, miR-375-3p, and show that its downregulation results in significantly increased proliferative capacity, providing one possible mechanism by which microbiota regulate proliferation of IESCs in vivo. We believe the data provided herein progresses the field, and provides the scientific community a valuable resource through which researchers can initiate novel studies into miRNAs and microbiota-mediated regulation of intestinal physiology, homeostasis, and disease pathogenesis.

EXPERIMENTAL PROCEDURES
Animals-All animal studies were approved by the University of North Carolina at Chapel Hill's Institutional Animal Care and Use Committee.  The original source and maintenance of Sox9-EGFP mice have been described elsewhere (12)(13)(14). Germ-free (GF) Sox9-EGFP mice on a C57BL/6J background were generated at the UNC Gnotobiotic Core Facility. Four pairs of female GF littermates were used in these experiments at 8-10 weeks of age. Each pair came from separate litters born between April and July 2015. GF mice were housed with animals of the same sex from the same litter, on Envigo 7070C Tekland Diamond Dry Cellulose bedding. Four age-matched conventionally-raised Sox9-EGFP animals and wild-type C56BL/6J animals were included as controls in each individual FACS experiment. Conventionally-raised and conventionalized mice were bedded on Andersons irradiated ¼ inch Bed-O'cobs laboratory animal bedding. The small RNA-seq data presented for conventionally-raised animals was generated in a separate experiment, which isolated each IEC population from female conventionally-raise animals fed a standard chow diet at 30-weeks of age. Crypt culture studies were performed using female conventionally-raised C56BL/6J, female GF Sox9-EGFP animals, and male conventionally-raised Lgr5-EGFP-IRES-creERT2. Conventionally-raised animal colonies were maintained several generations at the University of North Carolina at Chapel Hill. Conventionalization-For each littermate pair, 0.2-0.7 grams of fresh fecal pellets were collected on separate days from multiple animals across 6-8 cages in the conventionally raised Sox9-EGFP animal colony housed at UNC and were frozen at -80C until reconstitution. Less than one hour before conventionalization, the fecal sample was thawed on ice and then reconstituted at 1 gram/10 mL cold PBS under anaerobic conditions. The fecal slurry was passed through a 100-µm filter to remove debris and 1 mL was aliquoted into a fresh microcentrifuge tube. For each littermate pair, one GF animal was conventionalized (CV) using prepared fecal slurry and administered by oral gavaged at 10 µL/gram body weight. To ensure conventionalization, whiskers and anus were swabbed and the remaining slurry was painted onto several pieces of food left on the bottom of the animal's cage. CV animals were housed individually throughout the duration of conventionalization with access to food and water ad libitum.

Intestinal epithelial cell (IEC) isolation and fluorescence-activated cell sorting (FACS)-After
a two-week conventionalization, both the CV and GF animals were anesthetized using isofluorane, then euthanized by cervical dislocation. The small intestine was removed and divided into 3 equal sections. The proximal and distal 10 cm were considered duodenum and ileum, respectively. The middle section was considered jejunum and used for all studies. Jejunum was flushed with ice cold PBS to remove contents, and total IEC were prepared for FACS as previously described (14). IECs were sorted using a Mo-Flo XDP cell sorter (Beckman-Coulter, Fullerton, CA) at the University of North Carolina Flow Cytometry Core Facility using previously described gating parameters (13)(14)(15). Conventionally-raised agematched Sox9-EGFP animals were included in each individual sorting experiment and used to set Sox9-EGFP gates. CD31-APC (BioLegend, San Diego, CA), CD45-APC (BioLegend), and Annexin-V-APC (Life Technologies, Carlsbad, CA), and Sytox-Blue (Life Technologies) staining excluded immune cells, endothelial cells and apoptotic cells, respectively. Sox9-EGFP cells were then subsequently sorted based on Sox9-EGFP intensity directly into RNA lysis buffer (Norgen Biotek, Thorold, ON, Canada). Additionally, non-sorted IECs (NS) were collected for each animal, except one conventionalized mouse (CV314), which did not have enough remaining sample to isolate a NS IEC population. NS IECs were purified by FACS to exclude nonepithelial and dying cells, but were not sorted based on Sox9-EGFP intensity. Due to the density of cells, Sox9 Neg cells were sorted into cell culture media, then pelleted following sorting by centrifugation.  (54). Transcript counts were then imported into R (v3.3.1), and were normalized and differential expression of genes quantified using DESeq2 (v1.12.4) (55,56). Raw sequencing data as well as counts are available through GEO accession GSE81126. Small RNA library preparation and sequencing-The small RNA sequencing was done at Genome Sequencing Facility of Greehey Children's Cancer Research Institute at University of Texas Health Science Center at San Antonio. Libraries were prepared using an average of 50 ng of total RNA using the TriLink CleanTag Small RNA Ligation kit (TriLink Biotechnologies, San Diego, CA) and suggested library preparation method. Six to seven libraries were pooled per lane, and were sequenced single-end 50x on the HiSeq2000 platform. One GF Sox9 Sublow sample failed during sequencing. However, for the remaining samples, we received an average of 26.5 million reads per sample. Raw sequencing data and miRNA quantification tables for all samples can be accessed through GEO record GSE81126. Bioinformatics-Sequencing quality was extremely high as assessed using FASTQC. Reads were trimmed and aligned to the mouse genome (mm9) as previously described (29), with the following modification: only contigs with greater than one read alignment were passed into the to Shrimp alignment pipeline. An average of 58.9% of reads mapped to the mouse genome across samples (Mapping statistics can be found in Supplementary File 1). Due to the large number of reads mapping throughout the genome in GF315 NS IECs, Shrimp failed to align this sample, and it was eliminated from further analysis. Annotated miRNAs with a reads per million mapped to miRNAs (RPMMM) expression threshold of greater than 400 in at least one sample were used in further analyses. One aberrant CV Sox9 Sublow sample was identified on the basis of poor clustering by PCA and hierarchical clustering analyses, and was removed from subsequent analyses (Supplemental Figure 4). Enteroid culture-Jejunum was isolated and flushed with cold PBS (Gibco cat. 14190-144, ThermoFisher Scientific, Waltham, MA), opened, and divided into 6 cm sections. Sections were placed in cold high glucose DMEM and rocked to remove excess fecal matter. Each section was then placed in 3 mM EDTA (cat 46-034-Cl, Corning, Corning, NY) diluted in PBS and rocked at 4ºC for 15 minutes. The luminal side of the tissue was gently scraped to remove villi and placed into fresh 3 mM EDTA/PBS and rocked an additional 30 minutes at 4ºC. Sections were shaken for 2 minutes in ice cold PBS to remove crypts, then filtered through a 70 µm cell strainer and counted. Analysis of enteroid area-At day 8, a z-stack of 4x bright field images capturing the entire well was taken every 10 µm throughout the matrigel patty. Each enteroid was measured for area at its maximal projection within the z-stack as an estimation of enteroid size, using imageJ. All enteroids that reached at least 1000 µm 2 within each well were included. Three wells from each condition were analyzed from a single experiment. Validation of miRNA expression levels-miRNA expression in the CV and GF animals was validated by qRT-PCR using Taqman assays (Applied Biosystems, Foster City, CA). Relative quantitative value (RQV) was determined relative to control gene U6. Linear Model-The model covariates include cell type, T; condition, C; littermate pair, P; and sequencing group, G; as well as an interaction term between cell type and condition (Equation 1).
To determine significance, a multiple testing correction (False Discovery Rate) was performed on p-values for each covariate across all miRNAs.

MAIN FIGURE LEGENDS
FIGURE 1. The Sox9-EGFP mouse model for characterizing subpopulations of the mouse intestinal epithelium. a) Diagram of our experimental design to profile the transcriptional landscape of distinct intestinal epithelial cell (IEC) populations and their response to microbial conventionalization. b) Mean percentage of each IEC subtype sorted from jejunum of conventionally-raised (CR), germ-free (GF) and conventionalized (CV) mice (n=4 each). Error bars depict standard error of the mean. Significance determined using two-tailed unpaired t-Test relative to CR, and is denoted as follows: * p < 0.05. c) Cartoon showing location and types of IECs in the Sox9-EGFP animal. Listed are miRNAs with mean expression in reads per million mapped to miRNAs (RPMMM) across all CR, CV, and GF animals that were found to be at least 2-fold enriched in each respective population. Fold enrichment indicates enrichment of the miRNA to the IEC subpopulation with the next highest mean expression. Only miRNAs with RPMMM > 400 in at least one sample are included in the analysis.   To demonstrate within-well variability, all EGFP + enteroids from one well of LNA-EGFP treated enteroids are shown at day 8. EGFPenteroids are marked with a red 'x.' (a-c) The images within contain bright field and/or FITC and TxRed stacked images. As enteroids are three-dimensional (3D) and filled with shed cells, the enteroid center may fluorescence due to on its shape and density (autofluorescence) and/or accumulation of EGFP either secreted from or within shed cells. TxRed was used to estimate autofluorescence in 3D enteroids. Dashed and solid white lines are used to indicate the region of focus on the 3D enteroid, which have minimal projection into the z-frame. Cells that fall between the solid and dashed lined are used to determine knockdown efficacy. Scale bars depict 80 µm.