We present a protocol to obtain proteomic signatures of human macrophages and apply this to determination of the impact of a low oxygen environment on macrophage polarization.
Macrophages are innate immune cells involved in a number of physiological functions ranging from responses to infectious pathogens to tissue homeostasis. The various functions of these cells are related to their activation states, which is also called polarization. The precise molecular description of these various polarizations is a priority in the field of macrophage biology. It is currently acknowledged that a multidimensional approach is necessary to describe how polarization is controlled by environmental signals. In this report, we describe a protocol designed to obtain the proteomic signature of various polarizations in human macrophages. This protocol is based on a label-free quantification of macrophage protein expression obtained from in-gel fractionated and Lys C/trypsin-digested cellular lysis content. We also provide a protocol based on in-solution digestion and isoelectric focusing fractionation to use as an alternative. Because oxygen concentration is a relevant environmental parameter in tissues, we use this protocol to explore how atmospheric composition or a low oxygen environment affects the classification of macrophage polarization.
Macrophages are innate immune cells involved in a number of physiological functions ranging from responses to infectious pathogens to tissue homeostasis, including removal of apoptotic cells and remodelling of the extracellular matrix1. These cells are characterized by a strong phenotypic plasticity2 that translates into a many possible activation states, which are also called polarizations. The precise molecular description of these various polarizations is a priority in the field of macrophage biology3. It has been proposed to classify these polarizations using the so-called M1/M2 dichotomy, in which M1 represents pro-inflammatory and M2 represents anti-inflammatory macrophages. This model fits well in various pathological situations like acute infections, allergy, and obesity4. However, in chronically inflamed tissues and cancer, it has been demonstrated that this classification is unable to grasp the broad phenotypic repertoire that macrophages present in certain cellular environments5,6,7. The current consensus is that macrophage polarization is better described using a multidimensional model to integrate specific microenvironmental signals8. This conclusion has been confirmed through transcriptomic analysis of human macrophages showing that the M1/M2 model is inefficient in describing the obtained polarizations9.
The study presented aims to provide a protocol to obtain proteomic signatures of various polarizations in human macrophages. We describe how to differentiate human macrophages in environments of various oxygen levels and obtain peptides from the whole macrophage proteome to perform a label-free quantification. This quantification allows the comparison of expression levels of various proteins. As research on stem cells has revealed the importance of oxygen as an environmental key parameter10, we seek to understand how this tissue parameter can influence macrophage polarization in humans. The partial pressure of oxygen has been found to range from 3 to 20% (of total atmospheric pressure) in the human body, where 20% corresponds roughly to what is commonly used in a cell culture incubator (the exact value is around 18.6% while taking the presence of water into account).
Previous work has shown that alveolar differ from interstitial macrophages from functional and morphological point of views11 and that these differences are probably partially due to the different oxygen levels to which they are exposed12. Furthermore, bone marrow-derived macrophages show an increased ability to phagocytize bacteria when exposed to a low oxygen environment12. The opposite effect has been found for THP1-differentiated human macrophages13, but these results support the idea that oxygen is a regulator of macrophage biology and that it is necessary to clarify this role at the molecular level in human macrophages. In a previous study, we have applied a proteomics approach to address these issues. By measuring expression levels for thousands of proteins simultaneously, we highlighted the impact of oxygen on polarization and provided a list of new molecular markers. We were also able to relate these findings to some macrophages functions. Notably, we found that the rate of phagocytosis of apoptotic cells was increased in IL4/IL13-polarized macrophages, which was linked to the upregulation of ALOX15 as revealed by the proteomic analysis14. In the present study, we describe how to perform such an analysis.
Human blood samples (LRSC) from healthy, de-identified donors were obtained from EFS (French National Blood Service) as part of an authorized protocol (CODECOH DC-2018–3114). Donors gave signed consent for the use of blood.
1. Media and Buffer Preparation
2. Isolation of Peripheral Blood Mononuclear Cells (PBMCs) from Leukoreduction System Chamber (LRSC)
3. Magnetic Labeling and Isolation of CD14+ Cells (Monocytes)
4. Plating of Monocytes
5. Polarization of Macrophages at Day 6
6. Cell Culture Under Low Oxygen Conditions
7. Lysis and In-Gel Digestion (Protocol 1)
NOTE: In this and the following sections, two protocols used to obtain peptides and perform LC-MS/MS analysis are described. Protocol 1 describes cell lysis and in-gel fractionation and digestion, and protocol 2 describes in-solution cell lysis followed by in-solution digestion and fractionation using an isoelectric focusing method.
8. Protein Extraction and In-Solution Digestion (Protocol 2)
9. In-Solution Digestion (Protocol 2)
10. Clean-up Cartridge (Protocol 2)
11. Fractionation by Isoelectric Focusing (Protocol 2)
NOTE: Peptides are separated according to their isoelectric points using an off-gel fractionator on a 13 cm strip covering a pH range from 3 to 10. We used the following protocol provided by the supplier (summarized below):
12. Clean-up Harvard Apparatus Column Reverse C18 Post-IEF (Protocol 2)
13. Analysis of Proteomic Data and Bioinformatics18
Starting from peripheral blood mononuclear cells (PBMCs) obtained by differential centrifugation, the protocol permits the obtaining of a population of CD14+ monocytes with an assessed purity of more than 98% by flow cytometry (Figure 1). These monocytes are secondarily differentiated toward various polarizations (Figure 2). When a fractionation on gel is chosen, the migration on SDS-page gels is adapted to obtain the number of desired bands, and the bands are excised (Figure 3). The digestion is secondarily performed in the excised bands of the gel, then the peptides are extracted. The peptides are analyzed using a nano-LC (liquid chromatography)-MS/MS mass spectrometer. MS/MS spectra give the identity of various proteins according to the annotation of spectra obtained for known peptides (Figure 4A). The quantification of the abundance of a protein is then calculated in connection with the quantity of identified peptides coming from the protein using published software and databases15,16. This protocol with in-gel digestion gives approximately 4000 identified proteins, and the dynamic range has been found to cover 5 logarithmic scale units (Figure 4B). Analysis of the differential expression of these identified proteins can be used to determine the clustering of various polarizations under different oxygen environments.
With this method, we can also recognize clusters of proteins that are up-regulated when exposed to a low oxygen concentration of 3% (Figure 5, Table 1). To assess efficiency of the digestion, which is not possible when an in-gel protocol is used, we proposed an in-solution digestion method that has been adapted to human macrophages (Figure 6A). With this method, we can easily obtain (after in-solution digestion) identification of 3600 proteins without fractionation, meaning that fractionation with IEF will sensibly increase this number (Figure 6B).
Figure 1: Flow cytometry analysis of CD14 expression of PBMC before sorting (left panel) and after sorting (right panel) showing the obtained purity after magnetic beads selection. Please click here to view a larger version of this figure.
Figure 2: Phase-contrast images of differentiated human macrophages showing heterogeneity of the obtained morphologies for two different polarizations. Scale bar represents 50 µm. Please click here to view a larger version of this figure.
Figure 3: Imaging of Coomassie blue stained gel showing the various bands that will be excised [here, 6 bands in M(Ø) macrophages] for 5 polarizations of macrophages exposed to a low oxygen environment. IC = immune complexes, DXM = dexamethasone. Please click here to view a larger version of this figure.
Figure 4: MS/MS spectrum and quantification. (A) An example of an MS/MS spectrum. Shown here is the CID (collision-induced dissociation) spectrum of a peptide found at m/z 597.29 on the MS spectrum with an electric charge of +2. The corresponding sequence was determined from this spectrum as Val-Ala-Glu-Leu-Glu-Asn-Ser-Glu-Phe-Arg from the protein CD58. (B) Rank ordered label-free quantification for each of the identified proteins (log10 LFQ). Please click here to view a larger version of this figure.
Figure 5: Heat map representing the hierarchical clustering of all polarization states using differentially expressed proteins. Analysis reveals a cluster of proteins overexpressed in all polarizations in the 3% O2 condition (red rectangle). The color scale represents z-scores (log2 intensity). Each row is a protein and each column is a sample. This figure originated from a previous publication14. Please click here to view a larger version of this figure.
Figure 6: SDS-PAGE and chromatogram. (A) Silver-stained SDS-PAGE gels with protein from cell lysis and after in-solution digestion showing the absence of degradation during lysis and efficiency of the digestion. (B) Chromatogram obtained from after in-solution digestion without fractionation. Please click here to view a larger version of this figure.
Cluster | proteinID | Protein names | Gene names | Peptides | Razor + unique peptides | Unique peptides | Protein IDs | ||
Red | P0DMV9 | Heat shock 70 kDa protein 1B | HSPA1A | 40 | 37 | 4 | P0DMV9; P0DMV8; A8K5I0; Q59EJ3; B4DNT8; B4DWK5; B4DFN9; B4DI39; B4E1S9; B4DVU9; V9GZ37; B3KTT5; B4DNX1; B4E1T6; B4DNV4; Q9UQC1 | ||
Red | P54709 | Sodium/potassium-transporting ATPase subunit beta-3 | ATP1B3 | 8 | 8 | 8 | P54709; D3DNF9; C9JXZ1; C9JA36; H7C547; F8WBY4; Q58I18 | ||
Red | O00462 | Beta-mannosidase | MANBA | 14 | 13 | 13 | O00462; A7LFP5; A8K6D3; E9PFW2; B4DT18; Q59EG5 | ||
Red | Q8NAS7 | NADH dehydrogenase [ubiquinone] iron-sulfur protein 7, mitochondrial | NDUFS7 | 4 | 4 | 4 | Q8NAS7; Q6ZQU6; F5H5N1; B7Z1U1; A8K0V6; Q7LD69; F5GXJ1; O75251; B7Z4P1; Q9H3K5; A0A087WXF6; A0A087WTI3; Q6ZS38 | ||
Red | Q8WWQ0 | PH-interacting protein | PHIP | 5 | 5 | 4 | Q8WWQ0; Q9NWP3 | ||
Red | E5RHK8 | Dynamin-3 | DNM3 | 11 | 2 | 2 | E5RHK8; Q9UQ16; B3KPF2; E5RIK2 | ||
Red | A0A024QZ64 | Fructose-bisphosphate aldolase C | ALDOC | 18 | 14 | 7 | A0A024QZ64; P09972; B7Z1Y2; B7Z3K9; B7Z1N6; B7Z3K7; A8MVZ9; J3KSV6; J3QKP5; B7Z1L5; C9J8F3; K7EKH5; J3QKK1; B7Z1H6 | ||
Red | O75489 | NADH dehydrogenase [ubiquinone] iron-sulfur protein 3, mitochondrial | NDUFS3 | 12 | 12 | 12 | O75489; Q9UF24; Q53FM7; E9PS48; E9PKL8; G3V194 | ||
Red | P21912 | Succinate dehydrogenase [ubiquinone] iron-sulfur subunit, mitochondrial | SDHB | 11 | 11 | 11 | P21912; A0A087WXX8; A0A087WWT1 | ||
Red | A0A024R1Y7 | GH3 domain-containing protein | LGP1; GHDC | 7 | 7 | 7 | A0A024R1Y7; Q8N2G8; B3KVB0; K7ESN3; K7EJT7; K7EQ41; K7EL54 | ||
Red | E5KRK5 | NADH-ubiquinone oxidoreductase 75 kDa subunit, mitochondrial | NDUFS1 | 29 | 29 | 29 | E5KRK5; P28331; B4DJ81; Q9P1A0; C9JPQ5; F8WDL5 | ||
Red | A0A024QZ30 | Succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial | SDHA | 17 | 17 | 17 | A0A024QZ30; P31040; D6RFM5; B3KT34; A0A087X1I3; Q0QF12; B4DYN5; B3KYA5; B4DNB2; H0Y8X1; B7Z6J5 | ||
Red | A0A024R2F9 | Transmembrane protein 43 | TMEM43 | 16 | 16 | 16 | A0A024R2F9; Q9BTV4; Q8TEP9; V9GY05 | ||
Red | A0A024R5K3 | NADH dehydrogenase [ubiquinone] iron-sulfur protein 8, mitochondrial | NDUFS8 | 5 | 5 | 5 | A0A024R5K3; E9PPW7; O00217; E9PN51; F8W9K7; E9PKH6; B4DYI3; Q53G17 | ||
Red | O76003 | Glutaredoxin-3 | GLRX3 | 13 | 13 | 13 | O76003 | ||
Red | Q1HBJ4 | Mitogen-activated protein kinase;Mitogen-activated protein kinase 1 | MAPK1 | 26 | 26 | 21 | Q1HBJ4; P28482; B4DHN0; Q499G7; K7ELV1; K7EN18; B4E104; P31152; Q16659 | ||
Red | Q13151 | Heterogeneous nuclear ribonucleoprotein A0 | HNRNPA0 | 8 | 8 | 8 | Q13151 | ||
Red | V9HWN7 | Fructose-bisphosphate aldolase A | ALDOA | 36 | 36 | 14 | V9HWN7; P04075; J3KPS3; H3BQN4; H3BUH7; H3BR04; H3BMQ8; H3BU78; H3BR68; A4UCS9; A4UCT0 | ||
Red | B4DVJ0 | Glucose-6-phosphate isomerase | GPI | 32 | 32 | 23 | B4DVJ0; P06744; B4DE36; A0A0A0MTS2; K7EQ48; K7EP41; K7EPY4; K7ELR7; K7ERC6; K7ENA0; K7ESF4; K7EIL4; K7ERK8; Q59F85 | ||
Red | V9HWB9 | L-lactate dehydrogenase;L-lactate dehydrogenase A chain | LDHA | 36 | 36 | 34 | V9HWB9; P00338; B4DJI1; F5GXY2; F5GYU2; F5GXH2; F5H5J4; F5H6W8; F5GZQ4; F5H8H6; F5GXC7; F5GWW2; F5GXU1; A0A087WUM2; Q96L19; Q6ZMR3 | ||
Red | P13674 | Prolyl 4-hydroxylase subunit alpha-1 | P4HA1 | 26 | 26 | 26 | P13674; Q5VSQ6 | ||
Red | Q6FHV6 | Gamma-enolase;Enolase | ENO2 | 18 | 15 | 14 | Q6FHV6; P09104; A8K3B0; F5H0C8; F5H1C3; U3KQP4; U3KQQ1; Q9NPL4 | ||
Red | Q99798 | Aconitate hydratase, mitochondrial | ACO2 | 40 | 40 | 40 | Q99798; B4DZ08; B2RBW5; A2A274; B4DJW1; B4DLY4; Q71UF1; B4DEC3; B4DW08; O75944 | ||
Red | P17858 | ATP-dependent 6-phosphofructokinase, liver type | PFKL | 32 | 29 | 28 | P17858; Q7L2M7; Q9BSP4; B3KNQ7; B4E108; Q59GI2; F8WEU2; Q7Z3R9; Q6MZK4 | ||
Red | A0A024R872 | Niban-like protein 1 | FAM129B | 32 | 32 | 32 | A0A024R872; Q96TA1; Q9H8K1; Q2YD88; Q9H6L6 | ||
Red | A0A024RC61 | Aminopeptidase N | ANPEP | 58 | 58 | 25 | A0A024RC61; P15144; Q59E93; B4DV63; B4DP01; B4DP96; H0YKT6; H0YLZ8; Q71E46; H0YMC1; Q8IVL7 | ||
Red | V9HWF4 | Phosphoglycerate kinase;Phosphoglycerate kinase 1 | PGK1 | 41 | 41 | 35 | V9HWF4; P00558; B4E1H9; B4DHM5; B4DHB3; B4DWQ3; Q16444 | ||
Red | Q12882 | Dihydropyrimidine dehydrogenase [NADP(+)] | DPYD | 44 | 44 | 44 | Q12882; B4DML1 | ||
Red | B4DEQ0 | Electron transfer flavoprotein-ubiquinone oxidoreductase, mitochondrial | ETFDH | 9 | 9 | 9 | B4DEQ0; Q547S8; A7UNU5; Q16134; D6RAD5 | ||
Red | D9UAX9 | MHC class I antigen | HLA-B | 13 | 3 | 2 | D9UAX9 | ||
Red | V9HWK1 | Triosephosphate isomerase | TPI1 | 29 | 29 | 17 | V9HWK1; P60174; Q53HE2; B4DUI5; U3KPZ0; U3KQF3; U3KPS5 | ||
Red | Q96HE7 | ERO1-like protein alpha | ERO1L | 28 | 28 | 28 | Q96HE7; G3V3E6; G3V5B3; G3V2H0; G3V503; Q5TAE8; B2RD00; Q86YB8 | ||
Red | P14868 | Aspartate–tRNA ligase, cytoplasmic | DARS | 29 | 29 | 2 | P14868; Q53T60; Q53R85; H7BZ35; H7C278 | ||
Red | P36871 | Phosphoglucomutase-1 | PGM1 | 24 | 24 | 5 | P36871; B4DFP1; Q9H1D2 |
Table 1: List of over-expressed proteins for human macrophages common to each polarization under low oxygen tension.
Because proteomics is a powerful tool to study the expression of different proteins from a whole cell or subcellular compartments, optimization of the cell lysis protocol and digestion of proteins has been addressed by a number of studies. There are three main classes of methods, which include in-gel digestion (digestion of proteins in polyacrylamide gel matrix)17, digestion in solution18 and filter-aided sample preparation19. This last method, at first described as universal, has been reported to exhibit low reproducibility and possible loss of proteins on the filter20. In-gel digestion is a robust method that can be time-consuming and disadvantageous in that assessing the efficiency of digestion is not easy, if possible. In-solution digestion offers this possibility but requires the cleaning of samples after digestion and IEF. When these two methods are compared between the same sample, in-solution digestion with IEF fractionation protocol yields a higher number of identified proteins (with the same number of fractions) than in-gel digestion21.
Despite this advantage, it is necessary to consider the possible protein degradation during in-solution lysis due to intracellular proteases (especially in myeloid cells). It is also important to bear in mind that these techniques are based on protein digestion and only able to analyze proteins presenting trypsin specific cleavage sites. It is possible to use a top-down proteomic approach that relieves this digestion constraint but adds data analysis steps and bioinformatics ressources22. The solubilization of proteins from various cellular compartments can also be difficult to obtain, especially from plasma membranes, leading to an uncontrolled sampling of cellular proteome. In order to proceed with a nano-LC-MS/MS mass spectrometer analysis of the samples, it is important to obtain a sufficient quantity of peptides, which can depend on the mass spectrometer used (usually, starting total protein should be at least 1 µg for a condition, and it is implied to increase this quantity according to the number of fraction used with IEF). This constraint may be a drawback if the cell population being studied is scarce, which differentiates proteomic from genomic techniques in which amplification of raw material is possible.
Even after the seminal works of Richer and colleagues23 and Packer and Fuehr24, the importance of oxygen in cell cultures has been insufficiently recognized. We now know that culturing cells under low oxygen concentrations favors adhesion, lifespan, and division. It is recognized that this is of utmost importance in stem cell research25. The main technical issue for cell cultures under controlled oxygen conditions is related to maintenance of the desired oxygen concentration during the entire experiment. This requires pre-incubation of all media to prevent release of dissolved oxygen and use of hypoxic working stations to permit the manipulation of cells under low oxygen (processing chamber with glove box) and prevent transient exposition to high oxygen conditions.
The described protocol was used to obtain the molecular signatures of various polarizations of human monocyte-derived macrophages and study the effects of oxygen modulation on these signatures. This study has given insight on the description of those polarizations and has revealed some functional consequences. For example, we found that many proteins involved in efferocytosis were modulated by a low oxygen environment. This proteomic approach, based on the described protocol, presents the opportunity to explore how environmental parameters modify macrophage functions and how these signals can be used to design new therapeutic approaches14.
The proteomic approach described in this work is complementary to genomic approaches that have been used during recent years in the field of human macrophage polarization studies. Proteomics offer the advantage of protein quantification, which may present a different expression than their corresponding mRNAs due to post-translational modifications and lead to the discovery of new biomarkers. Despite this advantage, proteomic data is usually difficult to interpret, in part due to the high sensitivity of mass spectrometry, leading to very complex MS spectra and false positive detection of peptides. Recently, analysis software has gained efficiency in order to prevent this. Even if it is a changing situation, proteomics also faces lower reproducibility than genomics26 and is associated with validation steps using other techniques (flow cytometry, immunoblotting) to confirm quantitative modifications of protein expression levels.
The authors have nothing to disclose.
AM is funded by the Young Group Leader Program (ATIP/Avenir Inserm-CNRS), by la Ligue Nationale contre le Cancer and la Fondation ARC pour la recherche sur le Cancer. We thank Mariette Matondo from the Mass Spectrometry for Biology platform (UTECHS MSBIO, Pasteur Institute, Paris). We thank Lauren Anderson for her reading of the manuscript.
Hypoxia Working Station | Oxford Optronix | Hypoxylab | |
C6 Flow cytometer | BD | Accuri C6 | |
Urea | Agilent Technologies | 5188-6435 | |
Formic acid (FA) | ARISTAR | 450122M | |
R-250 Coomassie blue | Biorad | 1,610,436 | |
Lipopolysaccharide, E.Coli (LPS) | Calbiochem | 437627 | |
2D clean-up kit | GE Healthcare | 80-6484-51 | |
RPMI 1640 medium, glutamax supplement | Gibco | 61870044 | |
HEPES 1 M | Gibco | 15630-080 | |
MEM Non-Essential Amino Acids (NEAA) Solution 100X | Gibco | 11140-035 | |
Phosphate Buffered Saline (PBS) 1X | Gibco | 14190-094 | |
Harvard Apparatus column Reverse C18 micro spin column | Harvard Apparatus | 74-4601 | |
EDTA 0.5 M, pH 8.0 | Invitrogen | AM9260G | |
NuPAGE Bis-Tris 4-12% | Life Technologies SAS | NP0321 BOX | |
CD14 Microbeads human | Miltenyi Biotec | 130-050-201 | |
MACS separation column LS | Miltenyi Biotec | 130-042-401 | |
Macrophage colony-stimulating factor (M-CSF) | Miltenyi Biotec | 130-096-485 | |
Interleukin 4 (IL4) | Miltenyi Biotec | 130-093-917 | |
Interleukin 13 (IL13) | Miltenyi Biotec | 130-112-410 | |
Interferon gamma (INFγ) | Miltenyi Biotec | 130-096-482 | |
CD14-FITC (clone TÜK4) | Miltenyi Biotec | 130-080-701 | |
MACSmix Tube Rotator | Miltenyi Biotec | 130-090-753 | |
Trifluoroacetic Acid (TFA) | Pierce | 28904 | |
Trypsin/Lys-C Mix | PROMEGA | V5073 | |
Complete Mini, EDTA-free Protease Inhibitor cocktail | Roche | 11836170001 | |
Density Gradient Solution (Histopaque 1077) | Sigma Aldrich | 10771-100ML | |
Accumax | Sigma Aldrich | A7089-100ML | |
Human Serum from human male AB plasma (SAB) | Sigma Aldrich | H4522-100ML | |
Bovine Serum Albumin (BSA) solution 30% | Sigma Aldrich | A9576-50ML | |
Trisma-base | Sigma Aldrich | T1503 | |
Glycerol | Sigma Aldrich | 49767 | |
β-Mercaptoethanol | Sigma Aldrich | M3148 | |
Bromophenol blue | Sigma Aldrich | 114405 | |
Sodium Dodecyl Sulfate (SDS) 20% | Sigma Aldrich | 5030 | |
Ammonium bicarbonate | Sigma Aldrich | 9830 | |
Acetonitrile | Sigma Aldrich | 34888 | |
Dithiothreitol | Sigma Aldrich | 43819 | |
Iodoacetamide | Sigma Aldrich | 57670 | |
Thiourea | Sigma Aldrich | T8656 | |
CHAPS | Sigma Aldrich | C9426 | |
Micro BCA Assay Kit | ThermoFisher | 23235 | |
5 mL sterile plastic pipette | VWR | 612-1685 | |
Thermomixer C Eppendorf | VWR | 460-0223 | |
Sep-Pak tC18 reverse phase cartridges, 100 mg | Waters | WAT036820 |