Flow Cytometric Analysis for Identification of the Innate and Adaptive Immune Cells of Murine Lung

Anthos Christofides; Carol Cao; Rinku Pal; Halil I. Aksoylar; Vassiliki  A. Boussiotis

doi:10.3791/62985

JoVE Journal > Immunology and Infection

Imunologia e Infecção

Flow Cytometric Analysis for Identification of the Innate and Adaptive Immune Cells of Murine Lung

Published: November 16, 2021

doi:

10.3791/62985

Anthos Christofides^1,2, Carol Cao^1,2,3, Rinku Pal^1,2, Halil I. Aksoylar^1,2, Vassiliki A. Boussiotis^1,2

¹Division of Hematology-Oncology,Beth Israel Deaconess Medical Center, Harvard Medical School, ²Department of Medicine,Beth Israel Deaconess Medical Center, Harvard Medical School, ³Harvard College

Summary

In this study, we present an effective and reproducible protocol to isolate the immune populations of the murine respiratory system. We also provide a method for the identification of all innate and adaptive immune cells that reside in the lungs of healthy mice, using a 9-color-based flow cytometry panel.

Abstract

The respiratory tract is in direct contact with the outside environment and requires a precisely regulated immune system to provide protection while suppressing unwanted reactions to environmental antigens. Lungs host several populations of innate and adaptive immune cells that provide immune surveillance but also mediate protective immune responses. These cells, which keep the healthy pulmonary immune system in balance, also participate in several pathological conditions such as asthma, infections, autoimmune diseases, and cancer. Selective expression of surface and intracellular proteins provides unique immunophenotypic properties to the immune cells of the lung. Consequently, flow cytometry has an instrumental role in the identification of such cell populations during steady-state and pathological conditions. This paper presents a protocol that describes a consistent and reproducible method to identify the immune cells that reside in the lungs of healthy mice under steady-state conditions. However, this protocol can also be used to identify changes in these cell populations in various disease models to help identify disease-specific changes in the lung immune landscape.

Introduction

The murine respiratory tract contains a unique immune system responsible for fighting pathogens and maintaining immune homeostasis. The pulmonary immune system consists of cellular populations with significant heterogeneity in their phenotype, function, origin, and location. Resident alveolar macrophages (AMs), originated mainly from fetal monocytes, reside in the alveolar lumen¹, while bone marrow-derived interstitial macrophages (IMs) reside in the lung parenchyma². IMs can be further subclassified by the expression of CD206. CD206⁺ IMs populate the peribronchial and perivascular area, while CD206^– IMs are located at the alveolar interstitium³. A few subclassifications of IMs have been proposed recently³^,⁴^,⁵^,⁶. Although IMs are less studied than AMs, recent evidence supports their crucial role in the regulation of the immune system of the lung⁷. In addition, CD206 is also expressed in alternatively activated AMs⁸.

Pulmonary dendritic cells (DCs) are another heterogeneous group of lung immune cells with respect to their functional properties, location, and origin. Four subcategories of DCs have been described in the lung: conventional CD103⁺ DCs (also known as cDC1), conventional CD11b⁺ DCs (also known as cDC2), monocyte-derived DCs (MoDCs), and plasmacytoid DCs⁹^,¹⁰^,¹¹^,¹²^,¹³. The first three subclasses can be defined as major histocompatibility complex (MHC) II⁺CD11c⁺⁹^,¹⁰^,¹⁴^,¹⁵. Plasmacytoid DCs express MHC II and are intermediately positive for CD11c but express high levels of B220 and PDCA-1⁹^,¹³^,¹⁶. In naïve murine lungs, CD103 DCs and CD11b DCs are located in the airway interstitium, whereas plasmacytoid DCs are located in the alveolar interstitium¹⁷.

Two major populations of monocytes reside in the lung during steady state: classical monocytes and non-classical monocytes. Classical monocytes are Ly6C⁺ and are critical for the initial inflammatory response. In contrast, non-classical monocytes are Ly6C^– and have been widely viewed as anti-inflammatory cells³^,¹⁶^,¹⁸. Recently, an additional population of CD64⁺CD16.2⁺ monocytes was described, which originate from Ly6C^– monocytes and give rise to CD206⁺ IMs³.

Eosinophils mainly appear in the lungs during helminth infection or allergic conditions. However, there is a small number of eosinophils in the pulmonary parenchyma during steady state, known as resident eosinophils. In contrast to the resident eosinophils, inflammatory eosinophils are found in the lung interstitium and bronchoalveolar lavage (BAL). In mouse models of house dust mite (HDM), inflammatory eosinophils are recruited into the lung after antigen-mediated stimulation. It has been proposed that resident eosinophils might have a regulatory role in allergy by inhibiting T helper 2 (Th2) sensitization to HDM¹⁹.

In contrast to the rest of pulmonary myeloid cells, neutrophils express Ly6G but not CD68 and are characterized by a signature of the CD68^–Ly6G⁺ immunophenotype¹⁶^,²⁰^,²¹. Visualization studies have shown that during steady state, the lung reserves a pool of neutrophils in the intravascular compartment and hosts a considerable number of extravascular neutrophils²². Similar to eosinophils, neutrophils are not found in BAL at steady state; however, several forms of immune stimulation, such as LPS challenge, asthma, or pneumonia, drive neutrophils into the alveolar lumen, resulting in their presence in BAL²¹^,²²^,²³.

A substantial number of CD45⁺ cells of the lung represent natural killer (NK), T cells, and B cells and are negative for most myeloid markers²⁴. In the lungs of naïve mice, these three cell types can be identified based on the expression of CD11b and MHC II¹⁸. Around 25% of pulmonary CD45⁺ cells are B cells, whereas the percentage of NK cells is higher in the lung than other lymphoid and non-lymphoid tissues²⁴^,²⁵^,²⁶. Among pulmonary T cells, a considerable fraction is CD4^–CD8^– and plays an important role in respiratory infections²⁶.

Because the lung hosts a very complex and unique immune system, several gating strategies for the identification of lung immune cells have been developed and reported¹⁶^,¹⁸^,²⁰^,²⁷. The gating strategy described herein provides a comprehensive and reproducible way to identify up to 12 different pulmonary myeloid and non-myeloid immune populations using 9 markers. Additional markers have been used to validate the results. Furthermore, a detailed method is provided for the preparation of a single-cell suspension that minimizes cell death and allows the identification of the most complete profile of the immune cell compartment of the lung. It should be noted that the identification of non-immune cells of the lung, such as epithelial cells (CD45^–CD326⁺CD31^–), endothelial cells (CD45^–CD326^–CD31⁺), and fibroblasts requires a different approach²⁸^,²⁹. Identification of such populations is not included in the protocol and method described here.

Protocol

All studies and experiments described in this protocol were conducted under guidelines according to the Institutional Animal Care and Use Committee (IACUC) of Beth Israel Deaconess Medical Center. Six to ten weeks old C57BL/6 mice of either sex were used to develop this protocol.

1. Surgical excision and tissue preparation

Euthanize the mouse by intraperitoneally injecting 1 mL of tribromoethanol (prepared according to standard protocol; Table of Materials).
NOTE: CO₂ asphyxiation should be avoided in lung studies as it might cause lung injury and alter the features and properties of lung immune cells. Cervical dislocation should also be avoided as it might cause mechanical injury of the lung.
Transfer the mouse to a clean and dedicated area for surgical operation.
Stabilize the mouse dorsal side down by using needles or tape on the four extremities. Use 70% ethanol to sanitize the skin of the ventral area.
Perform an incision in the skin, from the neck to the abdomen. Carefully remove the skin from the thoracic area.
Carefully remove the sternum and ribs.
Flush the lungs by injecting 10 mL of cold PBS directly in the right ventricle, using an 18-21 G needle, until the lungs become completely white.
Carefully remove the thymus and heart without touching the lungs.
Gently detach the lungs from the surrounding tissues and transfer them to a tube with cold BSA buffer (Table 1).
NOTE: Effort should be made to remove all adjacent fat from the lungs before further preparing the single-cell suspension, as this could bias the readouts.

2. Preparation of single-cell suspension

Transfer the lungs to an empty Petri dish and mince them with two fine scalpels. Transfer all the pieces of the minced lung to a new 50 mL conical tube. Use 5 mL of digestion buffer to wash the plate and add it to the 50 mL tube containing the minced lung (Table 1).
NOTE: Digestion buffer should be prepared immediately before use. Use 5 mg/mL of collagenase²⁸. Combining 1 or 5 mg of collagenase with BSA buffer or protein-free PBS did not improve results (Supplemental Figure S1).
Secure the lid of the tube and digest the lung for 30 min on an orbital shaker at a speed of 150 rpm at 37 °C. Stop the reaction by adding 10 mL of cold BSA buffer.
After digestion, use an 18 G needle to mix and dissolve the lung pieces. Place a 70 µm filter strainer at the top of a new 50 mL conical tube.
NOTE: Usage of a smaller micron filter might result in the loss of major myeloid populations.
Slowly transfer the digested lung mixture directly on the strainer. Use the rubber side of a 10 mL syringe plunger to smash the remaining lung pieces on the filter. Wash the processed material on the filter with BSA buffer.
Centrifuge the single-cell suspension at 350 × g for 8 min at 4 °C.
Carefully discard the supernatant and resuspend the cells in 1 mL of ACK lysis buffer. Mix well using a 1 mL pipet, and incubate for 90 s at room temperature.
Add 10 mL of cold BSA buffer to stop the reaction and centrifuge at 350 × g for 7 min at 4 °C.Carefully discard the supernatant and resuspend the pellet in Staining Buffer to count the cells using a hemocytometer.
Resuspend the cells at a concentration of 5 × 10⁶ cells/mL and use them for surface staining (see section 3).
NOTE: For this purpose, plate the cells in a 96-well round-bottom plate followed by antibody staining and washes. If a plate centrifuge is not available, use flow tubes instead of plates. With this protocol, ~15-20 × 10⁶ cells per lung can be obtained from a 6-10-week-old C57BL/6 mouse of average size.

3. Surface antibody staining

Transfer 1 × 10⁶ cells in 200 µL per well in a 96-well plate. Centrifuge the plate at 350 × g for 7 min at 4 °C. In the meantime, prepare the Fc-block solution by diluting anti-16/32 antibody (1:100) in staining buffer (Table 1).
Resuspend the cells in 50 µL of the pre-prepared Fc-blocking solution (Table of Materials) and incubate for 15-20 min at 4 °C or on ice.
Add 150 µL of staining buffer and centrifuge the plate at 350 × g for 5 min at 4 °C. Meanwhile, prepare the surface antibody cocktail by diluting surface antibodies (1:100; Table 2) in staining buffer.
NOTE: (i) Anti-16/32 antibody for Fc-blocking can be used with the surface antibodies in the same mixture. (ii) If fixable viability dye is used, add it to the surface antibody cocktail at a dilution of 1:1,000.
Resuspend the cells in 50 µL of the pre-prepared surface antibody cocktail and incubate for 30-40 min at 4 °C in the dark. Wash the cells with staining buffer twice.
NOTE: If no intracellular staining is required, resuspend the cells in 200 µL of staining buffer and proceed directly to the acquisition of data on the flow cytometer. Alternatively, cells might be fixed and stored at 4 °C for acquisition later. We recommend using the cells for flow cytometry within 24 h.

4. Cell fixation and intracellular staining

Prepare the fixation/permeabilization buffer (Fix/Perm Buffer) by mixing three parts of fixation/permeabilization concentrate and 1 part of fixation/permeabilization diluent of the FoxP3/Transcription Factor Staining Buffer Set (Table 1).
Resuspend the cells in 50 µL of the pre-prepared Fix/Perm Buffer per well of the 96-well plate, where cells were plated as described in section 3, and incubate them for 20-25 min at 4 °C in the dark.
Dilute the 10x permeabilization buffer as 1: 10 in purified deionized water to prepare 1x permeabilization buffer.
Wash the cells once with 1x permeabilization buffer. Meanwhile, prepare the intracellular antibody cocktail by diluting intracellular antibodies (1:100) in 1 mL of permeabilization buffer.
Resuspend the cells using 50 µL of the pre-prepared surface antibody cocktail per cell of the 96-well plate and incubate for 40 min at 4 °C in the dark.
Wash the cells once with permeabilization buffer and once with staining buffer. After the final wash, resuspend the cells in 200 µL of staining buffer.
NOTE: If no flow cytometer with plate reader is available, transfer the cells into flow cytometry tubes.
Acquire a minimum of 1.5 × 10⁶ cells per sample on the flow cytometer.
NOTE: For single colors and unstained control samples, 0.5-1 × 10⁶ cells per sample will be sufficient. It is recommended to titer the individual antibodies used to achieve optimal staining and reduce costs. The present protocol has been optimized using Fix/Perm Buffer prepared using the FoxP3 staining buffer set. Because CD68 is a cytoplasmic and not a nuclear marker, other permeabilization solutions such as a low concentration of paraformaldehyde or cytofix/ cytoperm kits from various vendors might be sufficient.

Representative Results

Gating strategy
The first step of our gating strategy is the exclusion of the debris and doublets (Figure 1A). Careful exclusion of doublets is critical to avoid false-positive populations (Supplemental Figure S2). Then, immune cells are identified using CD45⁺, a marker for hematopoietic cells (Figure 1B). The live-dead stain can be added to exclude dead cells. However, this protocol results in the death of <5% of the CD45⁺ cells (Figure 1C), whereas more CD45^– cells are identified as dead (Supplemental Figure S3).

To identify monocytes and neutrophils, in contrast to previous studies that used specific antibodies for each of these populations¹⁶^,¹⁸, we prefer to use an anti-GR-1 antibody that identifies both Ly6C⁺ and Ly6G⁺ cells. Using the anti-GR-1 antibody together with anti-CD68 allows the separation of the lung immune cells into three clusters: CD68^–GR-1⁺, CD68⁺(that can be further identified as GR-1⁺ or GR-1^–), and CD68^–GR-1^-/int(Figure 1D). CD68 is a marker that is predominantly detected intracellularly. Surface CD68 was probed but could not be detected without fixation/permeabilization (Supplemental Figure S4).

Polymorphonuclear cells (neutrophils) were identified as CD45⁺CD68^–GR-1⁺CD11b⁺ (Figure 1E). These results were verified using GR1 together with an antibody specific for Ly6G (Figure 2), a unique marker for polymorphonuclear neutrophils¹⁶^,¹⁸^,²⁷. Within the CD45⁺CD68^–GR-1^-/intpopulation, approximately 10-20% are MHCII^– and CD11b^low and represent the NK cells (Figure 1F). NK1.1, a unique marker for NK cells, was used to confirm this (Figure 3)²⁵^,³⁰. The CD45⁺CD68^–GR1^-/intCD11b^– population consists of MHCII^– T cells and MHCII⁺ B cells (Figure 1F). Two additional antibodies were used to verify T cells and B cells-CD3 and B220, respectively (Figure 3).

In healthy mice under steady-state conditions, the majority of CD45⁺ cells detected in BAL are AMs, the main residents of the airways. Hence, BAL was performed to assess the markers that characterize AMs²⁰^,³¹. These cells are CD45⁺CD68⁺Siglec-F⁺CD11c⁺ but, unlike other myeloid cells, do not express high levels of CD11b (Figure 4). The same combination of immune markers also identifies AMs in homogenates of total lungs (Figure 1G,H). In addition to AMs, in the CD45⁺CD68⁺Sigle-F⁺ gate (Figure 1G), there is a distinct cell population that is positive for CD11b but not for CD11c. This CD45⁺CD68⁺Siglec-F⁺CD11b⁺CD11c^– population of leukocytes represents eosinophils (Figure 1G)¹⁹^,³².

In the gate with the CD45⁺CD68⁺SiglecF^– cells (Figure 1G), there is a CD11c⁺MHC⁺ population that represents pulmonary DCs (Figure 1I). Several investigators identify pulmonary DCs as CD11c⁺MHCII⁺CD24⁺¹⁶^,¹⁸. CD24 expression was assessed to confirm the identity of this population (Figure 5A). The majority of the lung DCs are either CD103⁺CD11b^– or CD103^–CD11b⁺ (Figure 1J). The CD103⁺CD11b^– DCs represent the CD103⁺ conventional DCs and are identified as CD45⁺CD68⁺SiglecF^–MHCII⁺CH11c⁺CD103⁺CD11b^–. In contrast, CD103^–CD11b⁺ DCs are divided into conventional DCs and MoDCs based on CD64 expression (Figure 1K). Therefore, conventional CD11b⁺ DCs are identified as CD45⁺CD68⁺SiglecF^–MHCII⁺CH11c⁺CD103^–CD11b⁺CD64^– while the MoDCs are identified as CD45⁺CD68⁺SiglecF^–MHCII⁺CH11c⁺CD103^–CD11b⁺CD64⁺. In contrast to conventional DCs, MoDCs are low-positive for the DC marker CD24 and positive for pan-macrophage markers, including F4/80, CD64 and MERTK (Figure 5A)⁹^,¹⁰^,¹¹^,¹³^,³³^,³⁴.

IMs and classical and non-classical monocytes are in the CD45⁺CD68⁺Siglec-F^–CD11c^-/intCD11b⁺ gate (Figure 1L) and are distinguished based on CD64 and GR-1 expression (Figure 1M). CD64, a pan-macrophage marker, is mainly expressed by IMs and AMs, as well as a subset of DCs. Classical monocytes are also known as Ly6C⁺ monocytes and non-classical monocytes as Ly6C^– monocytes. Both monocytes and IMs are negative for Ly6G; however, classical monocytes express Ly6C and are therefore positive for GR-1. In contrast, both interstitial macrophages and non-classical monocytes are negative for GR-1 and Ly6C³^,⁴^,¹¹^,¹⁶^,¹⁸^,²⁰^,³⁵^,³⁶. In addition, non-classical monocytes are CD11c^int, while classical monocytes are CD11c^–. Although this difference in CD11c expression is generally insignificant for distinguishing the two types of monocytes at baseline, it could be critical for pathological conditions when classical monocytes accumulate. Based on the above, interstitial macrophages are defined as CD45⁺CD68⁺Siglec-F^–CD11c^-/intCD11b⁺GR-1^–CD64⁺, classical monocytes as CD45⁺CD68⁺Siglec-F^–CD11c^–CD11b⁺GR-1⁺CD64^–, and non-classical monocytes as CD45⁺CD68⁺CD11c^-/intCD11b⁺GR-1^–CD64^–. Both AMs and IMs are positive for all the macrophage markers, including CD68, CD64, F4/80, and MERTK proto-oncogene. However, unlike IMs, AMs are CX3CR1^–, in contrast to IMs, which could be explained by the difference in the origin of the two types of lung macrophages⁴^,³⁷^,³⁸^,³⁹ (Figure 5B).

Figure 1: Gating strategy of immune cells present in the murine lung. After careful exclusion of debris, doublets, dead cells, and the non-immune cells (CD45^–) (A-C), CD45⁺ cells were separated into 3 main clusters based on the expression of CD68 and GR-1 (D). Neutrophils belong to the CD68^–GR-1⁺ population (E) while the CD68^–GR-1^-/int population consists of NK cells, B cells, and T cells (F). CD68⁺ cells can be further divided into Siglec F⁺ cells (G), which are AMs and eosinophils (H), and Siglec F^– cells (G), which consist of monocytes, IMs, and DCs (I-M). Abbreviations: SSC-A = peak area of side-scattered light; FSC-A = peak area of forward-scattered light; SSC-H = peak height of side-scattered light; L/D = live/dead staining; MHC = major histocompatibility complex; SF = Siglec F; GR-1 = GPI-linked myeloid differentiation marker (Ly-6G); NK = natural killer; IMs = interstitial macrophages; DCs = dendritic cells; AMs = alveolar macrophages. Please click here to view a larger version of this figure.

Figure 2: Ly6G in the lung is expressed only by CD45⁺CD68^–GR-1⁺CD11b⁺ cells identified as polymorphonuclear neutrophils. Please click here to view a larger version of this figure.

Figure 3: Verification of the identification of NK cells, T cells, and B cells by the gating strategy. Markers specific for NK 1.1, CD3, and B220 were used to verify the identification of NK cells, T cells, and B cells, respectively. It should be noted that NKT cells, if present, might fall in the CD3⁺ cell population within the NK cell gate, and caution is required to avoid contamination of NK with NKT cells. Abbreviations: NK = natural killer; MHC = major histocompatibility complex. Please click here to view a larger version of this figure.

Figure 4: The majority of the immune cells obtained by bronchoalveolar lavage in naïve mice are alveolar macrophages. Abbreviations: AMs = alveolar macrophages; DCs = dendritic cells; IM = interstitial macrophage; SSC-A = peak area of side-scattered light; FSC-A = peak area of forward-scattered light; SSC-H = peak height of side-scattered light; SF = Siglec F; GR-1 = GPI-linked myeloid differentiation marker (Ly-6G). Please click here to view a larger version of this figure.

Figure 5: Comparison of the expression of different markers in immune cells. (A) Comparison of CD24, CD64, MERTK, F4/80, and CD103 expression in pulmonary DCs. (B) Comparison of CD68, CD64, MERTK, F4/80, CD11c, Siglec F (SF), CD11b, and CX3CR1 in pulmonary macrophages and monocytes. Abbreviations: DCs = dendritic cells; MoDCs = monocyte-derived DCs; AMs = alveolar macrophages; IMs = interstitial macrophages; SF = Siglec F; MERTK = myeloid-epithelial-reproductive tyrosine kinase. Please click here to view a larger version of this figure.

BSA buffer	PBS + 0.5% Bovine serum albumin
Digestion buffer	Prewarmed (37 °C) BSA buffer + 5 mg/mL collagenase type 1 + 0.2 mg/mL DNase I
Staining buffer	PBS + 2.5% FBS
Fix/Perm Buffer	Three parts of fixation/permeabilization diluent and 1 part of fixation/permeabilization diluent of the Foxp3/Transcription Factor Staining Buffer Set
Permeabilization buffer	10x permeabilization buffer from the Foxp3/Transcription Factor staining Buffer Set diluted 10 times in purified deionized water

Table 1: Buffers.

Antigen	Clone	Fluorochrome	Dilution	Surface/intracellular
CD45	30-F11	APC/CY7	1:100	surface
Gr-1	RB6-8C5	BV421	1:100	surface
CD68	FA-11	PerCPCy5.5	1:100	intracellular
CD11b	M1/70	PECy7	1:100	surface
Siglec F	S17007L	FITC	1:100	surface
CD11c	N418	BV650 or BV510	1:100	surface
CD64	X54-5/7.1	PE/Dazzle 594	1:100	surface
MHC-II	M5/114.15.2	AF700	1:100	surface
CD103	2.00E+07	PE / FITC	1:100	surface
Live/Dead Fixable Far Read Dead Cell Stain Kit		FarRed (APC) or Aqua (BV510)	1:1000	surface
CD3	17A2	PE	1:100	surface
B220	RA3-6B2	AF488	1:100	surface
NK1.1	PK136	FITC	1:100	surface
CD24	30-F1	PE	1:100	surface
MERTK	2B10C42	PE	1:100	surface
F4/80	BM8	BV605	1:100	surface
CX3CR1	SA011F11	PE	1:100	surface
FcBlock (CD16/32)	93		1:100	surface

Table 2: Usage of monoclonal antibodies.

Supplemental Figure S1: The best cellular dissociation is achieved by 5 mg/mL of collagenase 1 in prewarmed PBS + 0.5% BSA. In all different conditions, 0.2 mg of DNAse I was also included. Abbreviations: BSA = bovine serum albumin; FSC-A = peak area of forward-scattered light; L/D = live/dead staining; SF = Siglec F. Please click here to download this File.

Supplemental Figure S2: Inclusion of doublets might result in false-positive populations. Abbreviation: FP = false positive. Please click here to download this File.

Supplemental Figure S3: More CD45^– than CD45⁺ have features consistent with dead cells. Please click here to download this File.

Supplemental Figure S4: Surface staining for CD68 is not adequate to properly distinguish the individual immune cell populations of the lung. Please click here to download this File.

Discussion

Identification of pulmonary immune cells can be challenging because of the multiple immune cell types residing in the lung and their unique immunophenotypic characteristics compared to their counterparts residing in other tissues. In several pathologic conditions, cells with distinct phenotypic features appear in the lungs. For example, bleomycin-induced lung injury results in the recruitment of circulating monocyte-derived macrophages in the alveolar space, where they can remain for as long as one year and even persist after bleomycin-induced fibrosis. In contrast to tissue-resident AMs, the circulating monocyte-derived macrophages are Siglec F^lowCD11b⁺. Targeted depletion of the monocyte-derived macrophages results in the amelioration of bleomycin-mediated pulmonary fibrosis¹⁶^,⁴⁰. Cells with similar features are recruited to the lungs during influenza infection and provide prolonged protection against streptococcal pneumonia¹⁵.

Based on CD11c and MHC II expression, IMs have been further subcategorized into IM1, IM2, and IM3. IM1 are immunophenotypically defined as CD11c^–MHC II^–; IM2 are defined as CD11c^–MHC II⁺; and IM3 are defined as MHC II⁺CD11c⁺. It has been proposed that IM1, IM2, and IM3 represent the physiologic stages of monocyte to macrophage transition, rather than distinct macrophages categories, with IM3 representing the monocytic compartment⁴¹. As mentioned above, MoDCs are low-positive for the DC marker CD24 and positive for pan-macrophage markers, including F4/80, CD64, and MERTK⁹^,¹⁰^,¹¹^,¹³^,³³^,³⁴. However, several studies identify CD64⁺MERKT⁺ cells as pulmonary macrophages⁴^,¹⁰. Both IM3 and MoDCs have been defined as CD64⁺MERKT⁺MHCII⁺CD11C⁺, suggesting that these two populations most likely represent the same cell type. Consistent with this hypothesis, the gating strategy presented here does not identify a distinct population representing IM3 cells, in addition to MoDCs.

Critical steps of the protocol described here include: 1) the removal of all adjacent fat from the lungs before preparing the single-cell suspension, as this could bias the readouts; 2) permeabilization before staining with the anti-CD68 antibody. A limitation of the present protocol is that it cannot identify non-immune cells of the lung, such as epithelial (CD45^–CD326⁺CD31^–), endothelial cells (CD45^–CD326^–CD31⁺), and fibroblasts. Identification of such populations requires a different approach²⁸^,²⁹. In addition, the protocol requires staining for CD68, an intracellular marker, which might pose a limitation if the investigator is not experienced in intracellular staining. The significance of the present protocol and gating strategy with respect to existing methods is that this strategy provides a streamlined approach that uses a lower number of markers while allowing reproducible identification of all the immune populations of the lung.

Furthermore, a detailed method is provided for the preparation of a single-cell suspension that minimizes cell death and allows the identification of a complete profile of the immune cell compartment of the lung. Although the protocol outlined here describes the characterization and identification of lung immune populations under steady-state conditions, future applications may include the assessment of these populations in various disease models where it can help identify disease-specific changes in the lung immune landscape. In conclusion, this article presents a simple and reproducible protocol for lung single-cell preparation and a 9-color-based flow cytometry panel for the identification of 12 different immune cell populations.

Declarações

The authors have nothing to disclose.

Acknowledgements

This work was supported by NIH grants R01CA238263 and R01CA229784 (VAB).

Materials

10 mL syringe plunger	EXELINT	26265
18 G needles	BD Precision Glide Needle	305165
21 G needles	BD Precision Glide Needle	305195
50 mL conical tubes	Falcon	3520
70 μm cell strainer	ThermoFisher	22363548
96-well plates	Falcon/corning	3799
ACK Lysing Buffer	ThermoFisher	A10492-01
anti-mouse CD11b	Biolegend	101215	For details see Table 2
anti-mouse CD11c	Biolegend	117339 / 117337	For details see Table 2
anti-mouse CD45	Biolegend	103115	For details see Table 2
anti-mouse CD64	Biolegend	139319	For details see Table 2
anti-mouse CD68	Biolegend	137009	For details see Table 2
anti-mouse GR-1	Biolegend	108433	For details see Table 2
anti-mouse Siglec F	Biolegend	155503	For details see Table 2
AVERTIN	Sigma-Aldrich	240486
B220	Biolegend	103228	For details see Table 2
Bovine Serum Albumin (BSA)	Sigma-Aldrich	9048-46-8
CD103	Biolegend	121405 / 121419	For details see Table 2
CD24	Biolegend	138503	For details see Table 2
CD3	Biolegend	100205	For details see Table 2
Centrifuge
Collagenase Type 1	Worthington Biochemical Corp	LS004196
CX3CR1	Biolegend	149005	For details see Table 2
DNase I	Millipore Sigma	10104159001
Ethanol
F4/80	Biolegend	123133	For details see Table 2
FcBlock (CD16/32)	Biolegend	101301	For details see Table 2
Fetal Bovine Serum	R&D Systems
Fine Serrated Forceps	Roboz Surgical Instrument Co
Foxp3 / Transcription Factor Staining Buffer Set	ThermoFisher	00-5523-00
Futura Safety Scalpel	Merit Medical Systems	SMS210
Live/Dead Fixable Far Read Dead Cell Stain Kit	ThermoFisher	L34973	For details see Table 2
MERTK	Biolegend	151505	For details see Table 2
MHC-II	Biolegend	107621	For details see Table 2
NK1.1	Biolegend	108705	For details see Table 2
Orbital Shaker	VWR	Model 200
Petri dish	Falcon	351029
Refrigerated benchtop centrifuge	SORVAL ST 16R
Small curved scissor	Roboz Surgical Instrument Co

Referências

Guilliams, M., et al. Alveolar macrophages develop from fetal monocytes that differentiate into long-lived cells in the first week of life via GM-CSF. Journal of Experimental Medicine. 210 (10), 1977-1992 (2013).
Tan, S. Y., Krasnow, M. A. Developmental origin of lung macrophage diversity. Development. 143 (8), 1318-1327 (2016).
Schyns, J., et al. Non-classical tissue monocytes and two functionally distinct populations of interstitial macrophages populate the mouse lung. Nature Communications. 10 (1), 3964 (2019).
Gibbings, S. L., et al. Three unique interstitial macrophages in the murine lung at steady state. American Journal of Respiratory Cell and Molecular Biology. 57 (1), 66-76 (2017).
Ural, B. B., et al. Identification of a nerve-associated, lung-resident interstitial macrophage subset with distinct localization and immunoregulatory properties. Science Immunology. 5 (45), 8756 (2020).
Chakarov, S., et al. Two distinct interstitial macrophage populations coexist across tissues in specific subtissular niches. Science. 363 (6432), (2019).
Liegeois, M., Legrand, C., Desmet, C. J., Marichal, T., Bureau, F. The interstitial macrophage: A long-neglected piece in the puzzle of lung immunity. Cellular Immunology. 330, 91-96 (2018).
Stouch, A. N., et al. IkappaB kinase activity drives fetal lung macrophage maturation along a non-M1/M2 paradigm. Journal of Immunology. 193 (3), 1184-1193 (2014).
Kopf, M., Schneider, C., Nobs, S. P. The development and function of lung-resident macrophages and dendritic cells. Nature Immunology. 16 (1), 36-44 (2015).
Plantinga, M., et al. Conventional and monocyte-derived CD11b(+) dendritic cells initiate and maintain T helper 2 cell-mediated immunity to house dust mite allergen. Immunity. 38 (2), 322-335 (2013).
Liu, H., et al. Dendritic cell trafficking and function in rare lung diseases. American Journal of Respiratory Cell and Molecular Biology. 57 (4), 393-402 (2017).
Cook, P. C., MacDonald, A. S. Dendritic cells in lung immunopathology. Seminars in Immunopathology. 38, 449-460 (2016).
Guilliams, M., Lambrecht, B. N., Hammad, H. Division of labor between lung dendritic cells and macrophages in the defense against pulmonary infections. Mucosal Immunology. 6 (3), 464-473 (2013).
Nobs, S. P., et al. PPARγ in dendritic cells and T cells drives pathogenic type-2 effector responses in lung inflammation. Journal of Experimental Medicine. 214 (10), 3015-3035 (2017).
Aegerter, H., et al. Influenza-induced monocyte-derived alveolar macrophages confer prolonged antibacterial protection. Nature Immunology. 21 (2), 145-157 (2020).
Misharin, A. V., Morales-Nebreda, L., Mutlu, G. M., Budinger, G. R., Perlman, H. Flow cytometric analysis of macrophages and dendritic cell subsets in the mouse lung. American Journal of Respiratory Cell and Molecular Biology. 49 (4), 503-510 (2013).
Hoffmann, F. M., et al. Distribution and interaction of murine pulmonary phagocytes in the naive and allergic lung. Frontiers in Immunology. 9, 1046 (2018).
Yu, Y. R., et al. A protocol for the comprehensive flow cytometric analysis of immune cells in normal and inflamed murine non-lymphoid tissues. PLoS One. 11 (3), 0150606 (2016).
Mesnil, C., et al. Lung-resident eosinophils represent a distinct regulatory eosinophil subset. Journal of Clinical Investigation. 126 (9), 3279-3295 (2016).
Zaynagetdinov, R., et al. Identification of myeloid cell subsets in murine lungs using flow cytometry. American Journal of Respiratory Cell and Molecular Biology. 49 (2), 180-189 (2013).
Tavares, A. H., Colby, J. K., Levy, B. D., Abdulnour, R. E. A model of self-limited acute lung injury by unilateral intra-bronchial acid instillation. Journal of Visualized Experiments: JoVE. (150), e60024 (2019).
Kreisel, D., et al. In vivo two-photon imaging reveals monocyte-dependent neutrophil extravasation during pulmonary inflammation. Proceedings of the National Academy of Sciences of the United States of America. 107 (42), 18073-18078 (2010).
Krishnamoorthy, N., et al. Neutrophil cytoplasts induce TH17 differentiation and skew inflammation toward neutrophilia in severe asthma. Science Immunology. 3 (26), (2018).
Ascon, D. B., et al. Normal mouse kidneys contain activated and CD3+CD4- CD8- double-negative T lymphocytes with a distinct TCR repertoire. Journal of Leukocyte Biology. 84 (6), 1400-1409 (2008).
Wang, J., et al. Lung natural killer cells in mice: phenotype and response to respiratory infection. Immunology. 137 (1), 37-47 (2012).
Cowley, S. C., Meierovics, A. I., Frelinger, J. A., Iwakura, Y., Elkins, K. L. Lung CD4-CD8- double-negative T cells are prominent producers of IL-17A and IFN-gamma during primary respiratory murine infection with Francisella tularensis live vaccine strain. Journal of Immunology. 184 (10), 5791-5801 (2010).
Gibbings, S. L., Jakubzick, C. V., Alper, S., Janssen, W. Isolation and characterization of mononuclear phagocytes in the mouse lung and lymph nodes. In Lung innate immunity and inflammation. Methods in Molecular Biology. 1809, (2018).
Singer, B. D., et al. Flow-cytometric method for simultaneous analysis of mouse lung epithelial, endothelial, and hematopoietic lineage cells. American Journal of Physiology. Lung Cellular and Molecular Physiology. 310 (9), 796-801 (2016).
Matsushima, S., et al. CD248 and integrin alpha-8 are candidate markers for differentiating lung fibroblast subtypes. BMC Pulmonary Medicine. 20 (1), 21 (2020).
Cong, J., Wei, H. Natural killer cells in the lungs. Frontiers in Immunology. 10, 1416 (2019).
Daubeuf, F., et al. A fast, easy, and customizable eight-color flow cytometric method for analysis of the cellular content of bronchoalveolar lavage fluid in the mouse. Current Protocols in Mouse Biology. 7 (2), 88-99 (2017).
Yi, S., et al. Eosinophil recruitment is dynamically regulated by interplay among lung dendritic cell subsets after allergen challenge. Nature Communications. 9 (1), 3879 (2018).
Langlet, C., et al. CD64 expression distinguishes monocyte-derived and conventional dendritic cells and reveals their distinct role during intramuscular immunization. Journal of Immunology. 188 (4), 1751-1760 (2012).
Moran, T. P., Nakano, H., Kondilis-Mangum, H. D., Wade, P. A., Cook, D. N. Epigenetic control of Ccr7 expression in distinct lineages of lung dendritic cells. Journal of Immunology. 193 (10), 4904-4913 (2014).
Schyns, J., Bureau, F., Marichal, T. Lung interstitial macrophages: past, present, and future. Journal of Immunology Research. 2018, 5160794 (2018).
Krljanac, B., et al. RELMalpha-expressing macrophages protect against fatal lung damage and reduce parasite burden during helminth infection. Science Immunology. 4 (35), (2019).
Ginhoux, F., Guilliams, M. Tissue-resident macrophage ontogeny and homeostasis. Immunity. 44 (3), 439-449 (2016).
Svedberg, F. R., et al. The lung environment controls alveolar macrophage metabolism and responsiveness in type 2 inflammation. Nature Immunology. 20 (5), 571-580 (2019).
Yona, S., et al. Fate mapping reveals origins and dynamics of monocytes and tissue macrophages under homeostasis. Immunity. 38 (1), 79-91 (2013).
Misharin, A. V., et al. Monocyte-derived alveolar macrophages drive lung fibrosis and persist in the lung over the life span. Journal of Experimental Medicine. 214 (8), 2387-2404 (2017).
Koch, C. M., Chiu, S. F., Misharin, A. V., Ridge, K. M. Lung Interstitial Macrophages: Establishing Identity and Uncovering Heterogeneity. American Journal of Respiratory Cell and Molecular Biology. 57 (1), 7-9 (2017).

Play Video

PDF

DOI

DOWNLOAD MATERIALS LIST

Citar este artigo

Christofides, A., Cao, C., Pal, R., Aksoylar, H. I., Boussiotis, V. A. Flow Cytometric Analysis for Identification of the Innate and Adaptive Immune Cells of Murine Lung. J. Vis. Exp. (177), e62985, doi:10.3791/62985 (2021).