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. 2019 Mar 2;13:328–338. doi: 10.1016/j.isci.2019.02.032

Functional Heterogeneity of Mouse Prostate Stromal Cells Revealed by Single-Cell RNA-Seq

Oh-Joon Kwon 1,6, Yiqun Zhang 2, Yumei Li 3, Xing Wei 1,4,6, Li Zhang 6, Rui Chen 3, Chad J Creighton 2,5, Li Xin 1,2,6,7,8,∗
PMCID: PMC6423355  PMID: 30878879

Summary

We perform a single-cell RNA sequencing analysis to investigate the phenotypic and functional heterogeneity of the adult mouse prostate stromal cells. Our analysis identifies three major cell populations representing the smooth muscle cells and two types of fibroblast cells enriched by Sca-1 and CD90. The Sca-1+CD90+ fibroblast cells are in direct contact with the epithelial cells and express growth factors and genes associated with cell motility, developmental process, and androgen biosynthesis. This suggests that they may regulate epithelial cell survival and growth. The Sca-1+CD90-/low myofibroblast-like cells highly express genes associated with the extracellular matrix and cytokine-mediated signaling pathways, indicating a role in tissue repair and immune responses. The Sca-1+CD90-/low cells significantly suppress the capacity of the basal cells for bipotent differentiation in the prostate organoid assay. Collectively, we identify the surface markers enabling physical separation of stromal subpopulations and generate the gene expression profiles implying their cellular functions.

Subject Areas: Biological Sciences, Cell Biology, Integrative Aspects of Cell Biology, Molecular Biology

Graphical Abstract

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Highlights

  • •

    scRNA-seq reveals three distinct mouse prostate stromal cell populations

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    Sca-1+CD90+ cells produce growth factors mediating developmental process

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    Sca-1+CD90-/low cells express genes mediating immune response and tissue repair

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    Sca-1+CD90-/low cells robustly suppress bipotent differentiation of basal cells

Biological Sciences; Cell Biology; Integrative Aspects of Cell Biology; Molecular Biology

Introduction

The prostate is an organ that develops from the embryonic urogenital sinus under the regulation of androgens (Marker et al., 2003). Besides the endoderm-derived epithelial cells, there are many other types of cells of different embryonic origins in the prostate, such as the stromal cells, immune cells, endothelial cells, nerve cells, and adipocytes. The term prostate stromal cells is vague, but generally refers to the non-hematopoietic and non-epithelial fibroblast cells. Stromal-epithelial interaction has been demonstrated to play an important role in the development and homeostasis of the prostate as well as in the initiation and progression of the prostate-related diseases including prostate cancer and benign prostatic hyperplasia (Barron and Rowley, 2012, Brennen et al., 2013, Cunha and Ricke, 2011, Risbridger and Taylor, 2008, Strand et al., 2017).

During the past few decades, much progress has been made in understanding the lineage hierarchy of the prostate epithelial cells, especially that in the mouse (Lawson and Witte, 2007, Shibata and Shen, 2013, Xin, 2013). In contrast, our understanding of the stromal lineages lags. Stromal cells are abundant in the human prostate but are relatively scarce in the mouse prostate. It is well accepted that the prostate stromal cells consist of distinct subpopulations with different functions and cellular origins. Functionally, the prostate stromal cells consist of smooth muscle cells and fibroblasts. The smooth muscle cells carry the contractile function. In the literature, mouse prostate smooth muscle cells are often roughly identified as bands of cells encapsulating prostatic epithelial glands based on the expression of α-smooth muscle actin. Fibroblast cells are referred to as the cells expressing vimentin and are often found in the interglandular space. Fibroblasts per se are also heterogeneous depending on their activation states and play important roles in immune surveillance and tissue repair (Kalluri, 2016, Ohlund et al., 2014). Fibroblasts are thought to be capable of differentiating into myofibroblasts and then to smooth muscle cells in a reversible manner (Barron and Rowley, 2012). A recent study classified the mouse prostate stroma into four compartments based on the expression of α-smooth muscle actin and CD34, but the functional relevance of this classification is unknown (Peng et al., 2013). In addition, how the homeostasis of the prostate stromal cells is maintained remains unclear. Several studies demonstrated the existence of resident and infiltrated stromal cells in the prostate that possess the multipotent stem cell activity (Brennen et al., 2016, Kim et al., 2014, Lin et al., 2007). However, a lineage tracing study by Peng et al. suggested that distinct stromal cell subpopulations are replenished independently (Peng et al., 2013).

Despite these findings, our understanding of the prostate stromal cells is quite limited. There is a lack of the marker that can definitively define individual stromal cell subpopulations. Fibroblast-specific protein 1, actin alpha 2, and vimentin are frequently used markers for the prostate stromal cells. However, these markers cannot distinguish different stromal cell lineages under physiological and pathological conditions and are also not specific to the stromal cells. In addition, they are all intracellular proteins. Therefore it is technically infeasible to use these antigens to investigate the heterogeneity of the stromal cells, separate different stromal cell lineages, and uncover novel information regarding stromal cell biology and function.

Recent breakthrough in global analysis of transcriptomes at the single-cell level has made it possible to study cellular lineage heterogeneity and relationship (Papalexi and Satija, 2017, Treutlein et al., 2014, Wollny et al., 2016). In this study, we perform single-cell RNA sequencing (scRNA-seq) analysis of adult mouse prostate stromal cells. Our study indicates that there are three major cell populations in the prostate stroma that roughly represent smooth muscle cells and two types of fibroblast cells. Our study identifies novel surface markers that enable physical separation of the different cell fractions and generate gene expression profiles that not only corroborate known cellular roles but also imply previously unknown functions of these cell lineages.

Results

ScRNA-Seq Reveals Distinctive Subpopulations in Adult Mouse Prostate Stromal Cells

To dissect the stromal cell heterogeneity in the adult mouse prostates, we performed scRNA-seq analysis of individual adult mouse prostate stromal cells. Prostate stromal cells were isolated by fluorescence-activated cell sorting (FACS) from 8- to 10-week-old C57BL/6 mice based on their surface antigen expression profile (Lin−CD24−CD49f−) (Figure S1A) (Xin et al., 2005). We employed the iCell8 Single-Cell System (Takara Bio) for single-cell capture to achieve an intermediate in-depth expression profiling of single prostate stromal cells. Combined with Illumina sequencing, we were able to assign on the order of 78 million reads and detect up to 3,967 genes per cell. We analyzed profiles from 1,159 single stromal cells that passed strict quality control thresholds (Transparent Methods) and used the Seurat 2.0 clustering algorithm to identify robust clusters of cells within the data. Using these methods, we identified five major clusters of cell populations (Figure 1A). To determine the identities and functions of each subpopulation, we compiled the top 200 genes that could be specifically associated with each subgroup (Figure 1B) and performed Gene Ontology (GO) (Figure 1C) and network pathway analyses (Figure S1B) for each subgroup based on differential genes. Figure 1D shows some representative genes of biological interest for each subpopulation.

Figure 1.

Figure 1

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scRNA-seq Reveals Distinctive Subpopulations on Prostate Stromal Cells

(A) Multidimensional scaling plot of scRNA-seq identifies five clusters of populations (R1–R5).

(B) Heatmap showing clustering with top 200 highly expressed genes within each group.

(C) Gene Ontology analysis of subpopulations of prostate stromal cells.

(D) Heatmap of selected genes differentially expressed among prostate stromal subpopulations.

See also Figure S1.

Three subpopulations (R1–R3) constitute most of the FACS-isolated single stromal cells, whereas the R4 and R5 subpopulations represent 4% and 7% of the total cells, respectively. The R5 subpopulation likely represents the luminal epithelial cell contamination because it highly expresses the luminal-cell-associated genes such as Krt8, Krt18, Cdh1, and Pbsn (Figure 1D). Gene ontology analysis shows that the R4 cells express genes associated with DNA packaging, nucleosome assembly, and organization (Figure 1C). However, the identity and function of this small cell population remain unclear based on the top expressed genes and the GO analysis. Therefore we focused on the characterization of the R1–R3 subpopulations in this study.

The R1 subpopulation (42% of the total cells) highly expresses a fibroblast cell marker Thy-1 (CD90) but expresses a relatively lower level of another fibroblast marker Vimentin (Figure 1D). GO analysis shows that these cells express genes associated with extracellular matrix, anatomical structure morphogenesis, cell motility, developmental process, and Wnt signaling (Figure 1C), including Mmp2, Bmp2, Bmp7, Hoxd13, Yap1, Runx2, and Wnt signaling components (Wnt2, Fzd1, Tcf4, Lef1, Sfrp2, and Wif1) (Figure 1D). This indicates that this cell population mediates signaling that regulates prostate morphogenesis. In addition, Srd5a2, an essential enzyme for dihydrotestosterone (DHT) production is also highly expressed in this cell population (Figure 1D), which suggests that these cells play a critical role in the prostatic intracrine androgen biosynthesis (Wang et al., 2017).

The R2 subpopulation (34% of the total cells) highly expresses S100a4 (Fsp1), Ddr2, Fn1, and Igf1 (Figure 1D). It also highly expresses Cd34 and Ly6 family members (Ly6a, Ly6c1, and Ly6c2), but expresses a relatively lower level of Cd200. The R2 subpopulation expresses many genes associated with the extracellular matrix and exosome, cytokine- and chemokine-mediated signaling pathways, and complement activation (Figure 1C), including many cytokines, chemokines, and complement components such as Ccl2, Ccl7, Ccl11, Cxcl1, Cxcl2, and C3 (Figure 1D). Collectively, these observations indicate that the R2 subpopulation may play a role in defense and immune responses and tissue repair.

Cells in the R3 cluster (12.5% of the total cells) highly express Acta2, Tagln, Mfap2, and Mfap4, suggestive of a smooth muscle cell phenotype (Figure 1D). In addition, Notch3, Gli2, Gli3, Rspo3, and two stem cell-associated markers, Lgr5 and Hopx, are also highly expressed in this cell population. GO analysis reveals that the genes associated with the potassium channel regulator activity (Cav1, Kcnip1) are enriched among the top 200 genes of the R3 subgroup (Figure 1C). This is consistent with the ion-channel-mediated contractile function of the smooth muscle cells. Interestingly, these cells also expressed various neuropeptide genes (Npy, Mdk, and Nrep) and regulators of angiogenesis (Angpt1, Angpt2, and Ctla2a) (Figure 1C), suggesting the existence of cross talk between these cells with the nerves and endothelial cells.

Isolation of Distinctive Mouse Prostatic Stromal Cell Populations Based on Surface Expression Profiles

We sought to use surface antigens identified in the scRNA-seq analysis to separate the prostate stromal cells into functionally distinct subpopulations. According to the scRNA-seq analysis, Cd90 and Cd200 are highly expressed in the R1 cells, whereas Sca-1 and Cd34 are highly expressed by the R2 cells. FACS analysis revealed that all CD90+ cells are CD200+, whereas most CD34+ (all CD34high) cells are Sca-1+ (Figure S1C). We therefore attempted to use CD200 and Sca-1 to further fractionate stromal cells. Surprisingly, contrary to the inverse correlation between the expression of CD200 and Sca-1 shown in the scRNA-seq analysis, the two antigens costained predominantly in the FACS analysis (Figure S1D). This is probably because one of the markers is expressed at a very wide range. We therefore used CD90 instead, in combination with Sca-1, to further fractionate prostate stromal cells.

As shown in Figure 2A, Sca-1 and CD90 separate the Lin−CD24−CD49f− stromal cells into four populations (S1, Sca-1+CD90+, 36.7%; S2, Sca-1+CD90-/low, 21.6%; S3, Sca-1−CD90+, 6.6%; S4, Sca-1−CD90-, 35.1%). Immunostaining of cytospin preparations revealed that the S4 population was mainly composed of cell debris (data not shown). To determine the identities of the remaining three cell populations, we FACS-isolated individual cell populations, extracted RNAs, and performed qRT-PCR analysis of the genes associated with the three subpopulations (R1–R3) identified by the scRNA-seq analysis (Figure 1D). Figures 2B and 2C show that the S1 and S2 fractions highly express representative genes enriched in the R1 and R2 populations, respectively. However, among the genes enriched in the R3 population, only Notch3 and Cav1 were highly expressed in the S3 cell population, whereas other genes were mostly expressed in the S2 cells, suggesting that the R3 cell population was not efficiently separated from the R2 cells using this combination of surface antigens (Figure S2A). Of note, S2 cells also highly express Acta2 (Figure S2A). Considering that many factors expressed by myofibroblasts are highly expressed in the S2 cells, such as Acta2, Fn1, and inflammatory cytokines (Sun et al., 2016), it is naturally to reason that the R2/S2 cells represent myofibroblast cells.

Figure 2.

Figure 2

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Sca-1 and CD 90 Fractionates Prostate Stromal Cells

(A) FACS plot shows that Sca-1 and CD90 fractionate four distinct subpopulations on prostate stromal cells.

(B) qRT-PCR analysis of R1-cell-associated genes in FACS-sorted prostate stromal subpopulations. Results show means ± SEM from five independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001.

(C) qRT-PCR analysis of R2-cell-associated genes. Dot plot shows means ± SEM of relative expression to Gapdh (N = 5 each). *p < 0.05, **p < 0.01, ***p < 0.001.

(D) qRT-PCR analysis of hormone receptors. Dot plot shows means ± SEM of relative expression to Gapdh (N = 5 for S1 and S2 and N = 3 for S3). *p < 0.05, **p < 0.01.

(E) Dot plot shows means ± SEM of percentage of BrdU+ cells in stromal subpopulations by flow cytometric analysis. **p < 0.01, ***p < 0.001. BrdU, bromodeoxyuridine.

See also Figure S2.

We also investigated the expression levels of several major hormone receptors in the three cell populations (Figure 2D). Estrogen receptor α (Esr1) and progesterone receptor (Pr) are expressed at a relatively higher level in the S1 and S3 cells, whereas glucocorticoid receptor (Gr) is highly expressed in the S2 cells. The androgen receptor is expressed in all the three subpopulations at a similar level. The proliferative index of the S1 cells is relatively higher than those of the S2 and S3 cells based on the flow cytometric analysis of bromodeoxyuridine incorporation (Figure 2E).

The molecular and phenotypic profiles of individual stromal subpopulations are quite stable. For example, after FACS-isolated S1 and S2 cells were cultured and expanded in Petri dish separately, they still expressed their respective representative genes differentially (Figure S2B), although the expression levels of these genes decreased significantly in the cultured cells than in freshly isolated cells (Figures 2B and 2C). In addition, when these cells were cultured in vitro in Matrigel under the condition of a prostate organoid culture (Karthaus et al., 2014) they retained their respective surface marker expression profiles (Figures S2C and S2D). These observations suggest that the two fibroblast subpopulations have undergone a strict lineage specification and do not display lineage plasticity at least under these two in vitro culture conditions.

Anatomic Localization and Hormonal Regulation of Different Stromal Cell Populations

We then investigated whether the three different stromal cell populations separated by Sca-1 and CD90 are equally distributed among different mouse prostatic lobes. Figures 3A and 3B show that the Sca-1+CD90+ S1 population is rare in the ventral prostate but is most abundant in the anterior lobe. Immunostaining corroborates that Sca-1 is expressed in the stromal cells in all different lobes, but CD90 is barely detectable in the ventral prostate stromal cells (Figures 3C and S3A). Owing to the restriction of the source species of the antibodies, we were not able to perform coimmunostaining of Sca-1 and CD90. Instead, we performed coimmunostaining of CD34 and CD90. Consistent with the scRNA-seq and FACS analyses (Figures 1D and S1C), CD34 staining surrounds the keratin 14-expressing basal cells and overlapped significantly with Sca-1 staining in stromal cells (middle and bottom panels, Figures 3C, S3B, and S3C). In contrast, CD90 and CD34 mostly mark different stromal cell populations, which is also consistent with the FACS analysis (Figure S1D). More interestingly, CD90+ stromal cells are in direct contact with the epithelial cells, whereas the CD34+ and Sca-1+ cells are localized outside the layer of the CD90+ cells (white arrow in the inset in the of middle image of top panel, Figure 3C).

Figure 3.

Figure 3

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Anatomic Distribution and Hormonal Regulation of Distinct Prostate Stromal Cells

(A) FACS plot shows that each lobe has different percentage of subpopulations. AP: anterior prostate, DP: dorsal prostate, LP: lateral prostate, VP: ventral prostate.

(B) Bar graph shows means ± SEM of percentage of each subpopulation in different lobes from three independent experiments.

(C) Coimmunostaining of CD34/CD90, CD34/Sca-1, and K14/CD34 in different prostate lobes. White arrow denotes that CD34+ stromal cells are located outside of CD90+ stromal cells. Scale bars, 100 μm. DLP: dorsolateral prostate.

(D and E) (D) FACS plot and (E) bar graph show means ± SEM of percentages of individual subpopulations in prostate of castrated mice.

(F) qRT-PCR analysis for representative genes associated with R1 and R2 cells in stromal subpopulations from intact and castrated mice. Dot plots show means ± SEM of relative expression to Gapdh. N=4. *p < 0.05, **p < 0.01, ***p < 0.001.

See also Figure S3.

We then investigated how the stromal cell subpopulations change in response to androgen deprivation. Figures 3D and 3E show that the overall pattern of the proportions of individual stromal subpopulations did not alter drastically in the castrated mice, except that the CD90- and CD90low populations within the Sca-1+CD90-/low S2 cells became more distinctive (Figure 3D). qRT-PCR analysis of several representative genes associated with the R1–R2 subpopulations reveals that the Sca-1+CD90low cells in castrated mice display a similar gene expression profile with both the Sca-1+CD90-/low total S2 cells and the Sca-1+CD90low S2 cells in intact mice (Figure 3F), suggesting that these cells are not the S1 cells that had a reduced CD90 expression in response to androgen deprivation. Although androgen deprivation did not alter the phenotypic appearance of individual stromal cell populations, it downregulated Bmp2 and Srd5a2 but upregulated Bmp7 in the S1 cells and downregulated Ccl2, Ccl11, and Ly6c1 in the S2 cells (Figure 3F).

Previous study has shown that high fat diet can induce a very mild inflammatory microenvironment in the prostate (Kwon et al., 2016). We therefore investigated how the stromal cell subpopulations were affected by high-fat diet. Figures S3D and S3E shows that there was no drastic change in the phenotypic profile and proportion of individual stromal subpopulations in mice fed with high-fat diet. Ccl2 was upregulated in the S2 cells in the high-fat-diet-fed group, corroborating a mild prostate inflammation induced by high-fat diet (Figure S3F). However, there was no widespread change in the expression of representative genes associated with individual populations except that Bmp7 and Wif1 were downregulated in the S1 cells and Fn1 was downregulated in the S2 cells.

Distinct Impact of Different Stromal Cell Lineages on Basal Cell Differentiation

Prostate stromal cells have been shown to regulate epithelial cell survival and proliferation via juxtacrine or paracrine signaling (Marker et al., 2003). We employed a previously established prostate organoid assay (Karthaus et al., 2014) to determine whether different stromal cell populations may affect the organoid-forming capability of the prostate basal cells and their differentiating capacity. Briefly, FACS-isolated adult mouse prostate basal (Lin−Sca-1+CD49f+) cells were cultured in the organoid assay alone, or cocultured with FACS-isolated S1 and S2 cells separately. To test whether cross talk between S1 and S2 cells is necessary for them to regulate basal epithelial stem cell activity, we included a fourth group in which basal cells were cocultured with both S1 and S2 cells. Figure 4A shows that the organoid-forming activity of the basal cells is increased by 1.27 to 1.38-fold in all the three coculture groups compared with that in the control group with the basal cells only. FACS-sorted stromal cells do not form organoids when cultured alone (organoid-forming unit <1/4,000, Figure S4A). The stromal cells can survive during the 7- to 10-day culture in the organoid culture condition. They did not undergo senescence as measured by qRT-PCR analysis of the senescence markers p16 and p19 (Figure S4B). Neither did they proliferate during the culture (Figure S4C). Therefore the increased organoid-forming unit was from the basal cells. In addition, the size of the organoid was also increased by 1.08 to 1.15-fold significantly (Figure 4B). By coculturing the stromal cells expressing tdTomato with wild-type basal cells, we showed that the stromal cells did not incorporate into the basal-cell-derived organoids (Figure S4D). Therefore the increased organoid size likely reflects an increase in the proliferation of the organoid cells.

Figure 4.

Figure 4

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S2 Cells Suppress Bipotent Differentiation of Prostate Basal Cells

(A) Dot plot shows means ± SD of organoid-forming units of basal cell (Ba) when cultured alone or with stromal subpopulation (S1, S2, or the mixture of S1 and S2). Results were from three independent experiments. *p < 0.05.

(B) Dot plot shows means ± SD of organoid size. *p < 0.05, ***p < 0.001.

(C) Coimmunostaining of keratin 5 (K5) and keratin 8 (K8) in Type I and Type II organoids. Scale bars, 25 μm.

(D) Coimmunostaining of K5 and K8 in organoids derived from basal cells when cultured alone or with stromal subpopulations. Pie charts quantify types of organoids. Scale bars, 50 μm.

(E) Dot plot shows means ± SD of organoid-forming units from passaged organoid. ***p < 0.001.

(F) Dot plot shows means ± SD of size of passaged organoid. *p < 0.05.

(G) Pie charts quantify types of passaged organoids.

See also Figure S4.

The majority (96.7%) of the organoids formed in the control group are composed of cells that express both the basal cell marker cytokeratin 5 (K5) and the luminal cell marker cytokeratin 8 (K8) (hereafter referred to as the Type I organoid, Figure 4C). In contrast, the remaining 3.3% of organoids consists of cells that highly express K5 but with a weak expression of K8 (hereafter referred to as the Type II organoids, Figure 4C). These two types of organoids may reflect either the differentiation status of the organoid cells or different features of their respective cellular origins.

Interestingly, coculture of the basal cells with different types of stromal cells significantly increased the percentage of the Type II organoids (19.5% and 74.1% in the S1 and S2 coculture, respectively) (Figure 4D). The percentage of the Type II organoids in the coculture group with both the S1 and S2 cells (23.8%) fell between those of the S1 coculture and S2 coculture groups, which suggests that there is no synergy or interference between the two stromal cell populations in this assay. As the increase in the organoid-forming activity is minor, we believe that the increased frequency of the type II organoids is not because the S1 and S2 cells can promote the survival and growth of a basal cell subpopulation that specifically generate the Type II organoids. Instead, this observation supports that the S1 and S2 stromal cells suppress bipotent differentiation of the basal cells.

To determine whether such activity is mediated via direct cell-cell contact or paracrine signaling, we suspended FACS-sorted prostate basal cells and stromal cells in Matrigel separately so that they were cocultured in the organoid assay but did not contact directly. We obtained very similar results (Figures S4E and S4F), which supports the fact that the stromal cells suppress bipotent differentiation of the basal cells in the organoid assay in a paracrine manner. Figures S4G and S4H show that even after coculture with the basal cells, the S1 and S2 cells still retained their molecular and phenotypic properties. Together, these results suggest that the distinct capacity of the S1 and S2 cells to suppress bipotent differentiation of basal cells in the organoid assay is determined by their different secretomes.

To determine whether coculture of the basal cells with stromal cells affects their capacity for self-renewal, we FACS-sorted basal cells in each organoid culture shown in Figure 4D and passaged them alone, separately. Figure 4E shows that the organoid-forming activities were all decreased in the secondary culture, but the reduction was more significant in the coculture groups (from 19.9% to 4.8% in the basal cell alone group versus from 25.8% to 2.3% in the coculture groups). The sizes of the organoids in the S2 and S1 + S2 group were slightly bigger than that in the control group (1.15- to 1.17-fold) (Figure 4F). Surprisingly, in all the cultures, the Type II organoid became the predominant type of the organoids (Figure 4G). This implies that during the organoid culture the FACS-sorted basal cells have changed. They lost some bipotent differentiation capacity and became committed to unipotent basal cells. Coculturing with the stromal cells accelerates this process in the organoid assay.

Discussion

Distinct Stromal Cell Populations with Possibly Specialized Functions

We separated prostate stromal cells into three major populations (R1–R3) with distinct biological functions using scRNA-seq. Based on the information obtained from the scRNA-seq we were able to identify surface antigens that distinguish two of the three populations: the Sca-1+CD90+ (S1) and Sca-1+CD90-/low (S2) stromal cells roughly correspond to the R1 and R2 cells, respectively. Both cell populations display a fibroblastic phenotype based on their expression of representative fibroblast cell-associated genes, but the R1 cells express the fibroblastic cell marker Vimentin at a relatively lower level compared with the R2 cells. The R2 cells highly express S100a4 and Acta2 as well as many inflammation-associated genes, suggesting a myofibroblast phenotype. It should be noted that Sca-1 and CD90 only separate stromal cells into rough subpopulations and that other markers are necessary to further define purer stromal subpopulations in the mouse prostate.

The R1 cells express various growth factors, including Bmps and Wnts, as well as Srd5a2, the essential enzyme for DHT synthesis. These features suggest that the CD90+ cells play an important role in the growth and androgen-mediated survival of prostate epithelial cells. This is further supported by the fact that these cells are in direct contact with the epithelial cells. The features of these cells are similar to those of the telocytes reported in the small intestines (Shoshkes-Carmel et al., 2018), suggesting that they may share the same developmental origin or differentiation trajectories. The growth factors and DHT generated by these cells are easily accessible to the epithelial cells via paracrine signaling. DHT may also be transported to epithelial cells via gap junctions. Interestingly, Srd5a2, an enzyme critical for DHT synthesis, is downregulated in the S1 cells after castration. These observations indicate that the CD90+ stromal cells may play a critical role in the androgen-regulated survival of prostate epithelial cells. It is interesting that the CD90+ cells are rare in the ventral prostate lobes that are more resistant to androgen deprivation than the other prostate lobes (O.-J.K. and X.W., unpublished data). This suggests that the epithelial cells in ventral prostate lobes may employ distinct signaling to maintain their growth and survival after androgen ablation.

R3 cells consist of cells that are phenotypically smooth muscle cells. Genes involved in tissue development and homeostasis, neurogenesis, and angiogenesis are also highly expressed by these cells, suggesting that the smooth muscle cells carry other important functions than the simple supporting and contractile roles. Unfortunately, we were not able to identify a combination of surface markers that can specifically separate the R3 cells. It is possible that the smooth muscle cells are more susceptible to the mechanical and enzymatic digestion during single-cell preparation, and thereby are partially depleted during the assay (the S4 cell debris in Figure 2A). In addition, CD90 and Sca-1 are not enough to distinguish the R3 cells from the other cell populations as our qRT-PCR analysis showed that the genes highly expressed in the R3 cells (Figure 1C) can be detected in both the S2 and S3 cells. Other markers are necessary to isolate this cell population in the future.

Fibroblast and myofibroblast have been shown to undergo phenotypic conversion between each other upon stimulation such as mechanical tension (Meran and Steadman, 2011). Interestingly, we showed that even after extended in vitro culture, the phenotypic profiles of S1 and S2 cells, such as the expression of surface antigens and specific genes, are relatively stable. This observation indicates that they may have distinct developmental origins that shape their molecular phenotypes and functional properties. This is also consistent with the previous study showing that different types of stromal cells in the mouse prostate are independently sustained (Peng et al., 2013). Future studies using lineage tracing should be able to corroborate this theory more definitively.

Stromal Regulation of Basal Cell Differentiation

The prostate organoid assay provides a permissive environment for the prostate basal cells to survive, proliferate, and undergo differentiation to generate cells with a luminal phenotype. We showed that coculture of the basal cells with the S1 and especially S2 cells block the luminal differentiation of the basal cells. Basal-to-luminal differentiation is often associated with an increase in cellular proliferation (Karthaus et al., 2014, Lamb et al., 2010, Xin et al., 2003). For example, when basal cells are cultured in Petri dish stimulated with growth factors they can proliferate and differentiate. In addition, we showed previously that prostate inflammation can induce basal-to-luminal differentiation, which is also accompanied by increased cellular proliferation. Therefore, it is surprising that the cytokine-producing Sca-1+CD90-/low cells can stimulate organoid growth yet suppress differentiation. This indicates that the inflammatory and growth-stimulating signaling in vivo and in the organoid assay are not completely the same. Alternatively, direct interaction of basal cells with immune cells may play a role in basal-to-luminal differentiation.

One suspected candidate signaling through which S1 and S2 cells block basal-to-luminal differentiation is the Wnt signaling because it has been reported to be necessary for basal-to-luminal differentiation (Lu and Chen, 2015, Madueke et al., 2018). The Wnt agonist R-spondin is an essential component for organoid growth (Karthaus et al., 2014, Kwon et al., 2015). Nevertheless, removing R-spondin or adding the Wnt inhibitor IWP-2 in the organoid assay only reduces the number and size of the organoids, but not the differentiation status of the cells (Figures S4I and S4L). In addition, the S2 cells do not always express the various Wnt inhibitors more than the S1 cells (Figure S4M). Therefore it is unlikely that the S2 cells block basal-to-luminal differentiation by interfering with the Wnt signaling in the basal cells in the organoid assay. Future gene expression and proteomic profiling may provide more insights into the underlying mechanisms.

Limitations of the Study

We classify the mouse prostate stromal cells into three distinct populations in this study. These populations are also heterogeneous and should be able to be further subclassified by additional studies including more cells with deeper reads.

Methods

All methods can be found in the accompanying Transparent Methods supplemental file.

Acknowledgments

We thank the technical support by the Cytometry and Cell Sorting Core at Baylor College of Medicine with funding from the NIH (P30 AI036211, P30 CA125123, and S10 RR024574) and the expert assistance of Joel M. Sederstrom. This work is supported by NIH R01 DK092202 and DK107436 (L.X.).

Author Contributions

O.-J.K. and L.X. designed the experiments. O.-J.K., Y.L., X.W., and L.Z. performed experiments, acquired the data, and analyzed the data. Y.Z. and C.J.C. analyzed the data. L.X. wrote the manuscript with input from C.J.C. and O.-J.K.

Declaration of Interests

The authors declare no competing interests.

Published: March 29, 2019

Supplemental Information

Document S1. Transparent Methods, Figures S1–S4, and Tables S1 and S2
mmc1.pdf (690.7KB, pdf)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Transparent Methods, Figures S1–S4, and Tables S1 and S2
mmc1.pdf (690.7KB, pdf)

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