Mammary adipocyte flow cytometry as a tool to study mammary gland biology

Abstract

The mammary gland is a vital exocrine organ that has evolved in mammals to secrete milk and provide nutrition to ensure the growth and survival of the neonate The mouse mammary gland displays extraordinary plasticity each time the female undergoes pregnancy and lactation, including a sophisticated process of tertiary branching and alveologenesis to form a branched epithelial tree and subsequently milk-producing alveoli. Upon the cessation of lactation, the gland remodels back to a simple ductal architecture via highly regulated involution processes. At the cellular level, the plasticity is characterised by proliferation of mammary cell populations, differentiation and apoptosis, accompanied by major changes in cell function and morphology. The mammary epithelium requires a specific stromal environment to grow, known as the mammary fat pad. Mammary adipocytes are one of the most prominent cell types in the fat pad, but despite their vast proportion in the tissue and their crucial interaction with epithelial cells, their physiology remains largely unknown. Over the past decade, the need to understand the properties and contribution of mammary adipocytes has become more recognised. However, the development of adequate methods and protocols to study this cellular niche is still lagging, partially due to their fragile nature, the difficulty of isolating them, the lack of reliable cell surface markers and the heterogenous environment in this tissue, which differs from other adipocyte depots. Here, we describe a new rapid and simple flow cytometry protocol specifically designed for the analysis and isolation of mouse mammary adipocytes across mammary gland developmental stages.

Keywords: cell sorting; cell surface staining; flow cytometry; mammary adipocytes; mammary gland.

Fig. 1

(A) Schematic representation of mouse mammary glands. Black dashed line represents the incisions necessary for the dissection. (B) Open necropsy of mouse mammary glands.

Fig. 2

(A) Top: Schematic representation of mammary cell processing from dissection until cell‐sorting stage. Bottom: Image of the adipocyte layer in a falcon tube after spinning. (B) Typical flow cytometry dot plot for a mammary adipocyte sample generated using the described protocol. (C) Representative haematoxylin and eosin stainings of mammary glands from nulliparous, gestation Day 9.5, lactation Day 5 and involution Day 1. This protocol was performed on mammary glands from these time points and additional ones. Scale bar = 100 μm.

Fig. 3

(A) Gating strategy for mammary adipocytes flow cytometry. In the first stage, adipocytes are identified based on their large size using forward and side scatter plots. This population is then divided based on Alexa Fluor 488 labelling CD45, CD31, CD49f, Ter119 and BP‐1, which are used to exclude immune, endothelial and epithelial cells, erythrocytes and tumours, respectively. LipidTox Red fluorescence labels adipocytes and neutral lipid droplets. (B) Density plots of sorted adipocytes at different developmental stages of the mammary gland. Top: Gestation Day 9.5, middle: Lactation Day 5, bottom: Involution Day 1.

Fig. 4

(A) Absolute numbers and percentages of isolated mammary adipocytes. Bars represent the absolute number of sorted mammary adipocytes across mammary gland development (left y‐axis). The line represents the percentage of mammary adipocytes of the total number of sorted cells in a single experiment where the pellet was used to isolate epithelial, endothelial and stromal cells. n = 8 biological replicates for each time point, error bars represent SEM. (B) Representative images of unsorted mammary adipocytes following the protocol, stained with LipidTox Red, scale bar = 50 μm. (C) Representative images of isolated mammary adipocytes, which were subsequently stained with DAPI, scale bar = 50 μm. (D) Expression profiles of isolated populations of mammary adipocytes, Alexa Fluor488⁺ cells and lipids, based on the gating strategy described in Fig. 3. Expression profiles were quantified using quantitative real‐time PCR. n = 4 biological replicates, error bars represent SEM.