Pregnancy Restricts an Age-Driven Accumulation of Hybrid Cells in the Mammary Gland [scRNA-Seq]

Aging increases breast cancer risk while an early first pregnancy reduces a womans life-long risk. Several studies have explored the effect of either aging or pregnancy on mammary epithelial cells (MECs), but the combined effect of both remains unclear. Here, we interrogate the functional and transcriptomic changes at single cell resolution in the mammary gland of aged nulliparous and parous mice to discover that pregnancy normalizes age-related imbalances in lineage composition, while also inducing a permanently differentiated cell state. Importantly, we uncover a minority population of Il33-expressing hybrid cells with high cellular potency that accumulate in aged nulliparous mice but is significantly reduced in aged parous mice. Functionally, IL33 treatment of basal, but not luminal, epithelial cells from young mice phenocopies aged nulliparous MECs and promotes formation of organoids with Tp53 knockdown. Collectively, our study demonstrates that pregnancy blocks the age-associated loss of lineage integrity in the basal layer through a decrease in Il33+ hybrid cells, potentially contributing to pregnancy-induced breast cancer protection. We performed scRNA-seq from mammary glands of 18m NP and 18m P mice using 10x chromium scRNA-seq (n=3 mice/group) as per manufactures protocol using the 5 Gene expression workflow (1 GEM per condition, 3 mice pooled in equal proportions per condition) Libraries were sequenced on the Illumina NovoSeq 6000 Platform by Medgenome, Inc. Reads were mapped to the mouse genome (mm10). Additionally, we integrated an 18m NP data set from Tabula Muris Senis. Prior to preprocessing, there were 21,995 cells and 32,285 genes. For quality control, we used Scanpys scanpy.pp.calculate_qc_metrics, scanpy.pp.filter_genes, and scanpy.pp.filter_cells. We applied filters to eliminate (1) genes that are detected in less than 3 cells, (2) cells that have less than 200 genes, (3) cells with gene counts < 600 or > 8,000, (4) cells with total counts of UMIs per cell < 2,000 or > 12,000, and (5) cells with mitochondrial gene ratio > 1.5%. The mitochondrial gene ratio was defined as the percentage of UMIs mapped to mitochondrial genes compared to non-mitochondrial genes within each cell; cells with a high ratio are indicative of non-viable or apoptotic cells. Doublets were identified using Scrublet, which detected 588 cells as doublets; these cells were then filtered out. After filtering, the datasets were concatenated, the UMI counts for each cell were then normalized using a target sum of 1e4, and then log transformed using scanpy.pp.log1p, which computes X=log(X+1), where log denotes the natural logarithm. This quality control resulted in the detection of 10,001 cells and 13,892 genes.衰老会增加乳腺癌的患病风险，而首次早孕则可降低女性终身的乳腺癌风险。既往多项研究已分别探讨了衰老或妊娠对乳腺上皮细胞（mammary epithelial cells, MECs）的影响，但二者的联合效应仍不明确。本研究对未产（nulliparous, NP）与经产（parous, P）老年小鼠的乳腺组织开展单细胞分辨率下的功能与转录组学分析，发现妊娠可校正衰老诱导的谱系组成失衡，同时诱导一种永久性分化的细胞状态。值得注意的是，我们发现了一类占比极低的表达IL33的杂合细胞（Il33-expressing hybrid cells），其细胞潜能极高；这类细胞会在老年未产小鼠体内蓄积，但在老年经产小鼠体内显著减少。功能实验显示，对年轻小鼠的基底上皮细胞而非腔上皮细胞施加IL33处理，可模拟老年未产小鼠的乳腺上皮细胞表型，并促进携带有Tp53敲低的类器官形成。综上，本研究证实，妊娠可通过减少IL33+杂合细胞的数量，阻断衰老相关的基底层谱系完整性丧失，这可能是妊娠介导乳腺癌保护效应的潜在分子机制。我们参照厂商操作规程，采用5'基因表达工作流程，借助10x Chromium单细胞RNA测序（single-cell RNA sequencing, scRNA-seq）平台，对18月龄未产（18m NP）和18月龄经产（18m P）小鼠的乳腺组织进行单细胞RNA测序（每组n=3只小鼠，每个条件对应1个GEM（凝胶珠乳液，Gel Bead Emulsion, GEM），每组将3只小鼠的样本按等比例混合）。文库由Medgenome公司在Illumina NovaSeq 6000测序平台上完成测序。测序读段比对至小鼠基因组mm10版本。此外，我们整合了来自小鼠衰老细胞图谱（Tabula Muris Senis）的18月龄未产小鼠数据集。预处理前，该数据集共包含21995个细胞与32285个基因。我们采用Scanpy工具包中的scanpy.pp.calculate_qc_metrics、scanpy.pp.filter_genes以及scanpy.pp.filter_cells进行质量控制，并设置如下过滤规则：（1）仅在少于3个细胞中被检测到的基因予以剔除；（2）基因检出数少于200个的细胞予以剔除；（3）基因计数介于600至8000区间外的细胞予以剔除；（4）每个细胞的UMI（唯一分子标识符，Unique Molecular Identifier, UMI）总计数介于2000至12000区间外的细胞予以剔除；（5）线粒体基因占比超过1.5%的细胞予以剔除。线粒体基因占比定义为每个细胞中比对至线粒体基因的UMI数占该细胞总UMI数的百分比；占比过高提示细胞为非活细胞或凋亡细胞。我们通过Scrublet工具鉴定双细胞（doublets），共检出588个双细胞并将其过滤移除。过滤完成后，将各数据集进行合并，随后以1e4为目标总和对每个细胞的UMI计数进行归一化，再通过scanpy.pp.log1p进行对数转换，该步骤计算公式为X=log(X+1)，其中log代表自然对数。经上述质量控制流程后，最终共保留10001个细胞与13892个基因。