This protocol describes the use of whole-cell MALDI-TOF mass spectrometry on eukaryotic cells. Here, we illustrate the accuracy of this technique by analyzing the multiple activation states of macrophages in response to their microenvironment.
MALDI-TOF is an extensively used mass spectrometry technique in chemistry and biochemistry. It has been also applied in medicine to identify molecules and biomarkers. Recently, it has been used in microbiology for the routine identification of bacteria grown from clinical samples, without preparation or fractionation steps. We and others have applied this whole-cell MALDI-TOF mass spectrometry technique successfully to eukaryotic cells. Current applications range from cell type identification to quality control assessment of cell culture and diagnostic applications. Here, we describe its use to explore the various polarization phenotypes of macrophages in response to cytokines or heat-killed bacteria. It allowed the identification of macrophage-specific fingerprints that are representative of the diversity of proteomic responses of macrophages. This application illustrates the accuracy and simplicity of the method. The protocol we described here may be useful for studying the immune host response in pathological conditions or may be extended to wider diagnostic applications.
Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) is a popular mass spectrometry technique to study biological samples. Using a laser beam and an energy-absorbing matrix allows a soft ionization process: the evaporation and genesis of large mostly single-charged biomolecules. This process is called desorption/ionization, justifying the acronym MALDI. These ions are then accelerated by application of voltage and enter a TOF analyzer that allows the separation of these ions and the quantification of their respective masses1.
MALDI-TOF MS has been extensively used in biology, chemistry, and medicine to identify molecules and biomarkers2-4 or to monitor post-translational modifications on proteins5,6. Recently, several groups applied MALDI-TOF MS to the identification of microorganisms from clinical samples7,8. This microbiological application is now used routinely in the clinical settings. Whole cell MALDI-TOF has many advantages compared to classical applications of MALDI-TOF MS. Samples containing whole cells are directly processed, avoiding time consuming steps to fractionate or separate large amounts of material. Moreover, no characterization of the various peaks is needed: the whole spectrum is considered as a fingerprint of the sample, and matching algorithms compare the tested spectrum with a database of reference spectra.
We and others have applied this whole-cell analysis technique to eukaryotic cells. Many applications may be derived from this technique: (1) identify the main cell types from a mixed sample9-11; (2) assess the viability of cell cultures over time (including quality control industrial applications)12; (3) monitor activation states of a single cell type13; (4) assess the malignant transformation of a clinical sample14,15.
Here, we describe the use of whole-cell MALDI-TOF MS to explore the various polarization phenotypes of macrophages in response to cytokines or heat-killed bacteria. Macrophages play a pivotal role in the immune response to microbial pathogens. They detect infectious agents in the tissues through pattern recognition receptors able to detect conserved microbial patterns, such as lipopolysaccharide (LPS)16. Macrophages are professional antigen-presenting cells that interact with T cells to mount the adaptive immune response. T cells influence macrophages by releasing cytokines that either reinforce or regulate the microbicidal activity of macrophages. By analogy to the Th1/Th2 lymphocyte polarization, inflammatory, microbicidal, and tumoricidal macrophages have been classified into M1 macrophages and immunoregulator macrophages as M2 macrophages17-19. The term M1 refers to the classical activation of macrophages by type I cytokines, such as interferon (IFN)-γ and tumor necrosis factor (TNF), or bacterial products, such as LPS18,20-23, whereas macrophages activated by alternative pathways (interleukin (IL)-4, IL-10, Transforming Growth Factor-β1 are considered M2 macrophages19,24,25. The high phenotypic and functional plasticity of macrophages in response to their microenvironment renders these macrophages useful to analyze subtle changes by a MALDI-TOF MS approach.
In the present protocol, the whole-cell MALDI-TOF technique is used to obtain a mass spectrum considered as a fingerprint of the sample. A bioinformatic analysis allowed the comparison and the classification of these fingerprints. There were three main parts in this protocol:
Prepare sterile solutions for cell isolation and culture. Prepare and store all reagents at 4 °C
1. Preparation of Human Monocytes
2. Analysis of Macrophages by Whole-Cell Maldi-TOF MS
3. Bioinformatic Analysis
Note: the bioinformatic analysis was performed using the free and open source statistical analysis software R, along with specific analysis libraries (MALDIquant). R can be downloaded freely from its website http://cran.r-project.org/. A detailed description of the script is provided as supplementary material.
The aim of the present protocol is to demonstrate the accuracy of whole-cell MALDI-TOF MS to assess the responsiveness of macrophages to their microenvironment.
Figure 1 describe preparation of stimulated macrophages from blood samples. Figure 2 represents the analysis of monocytes and MDMs by flow cytometry. Note that monocytes expressed CD14 but not CD68 (Figure 1A). Conversely, MDMs expressed CD68 but not CD14 (Figure 1B).
Figure 3 describes the principle of whole-cell MALDI-TOF MS. Cells are deposited with matrix on the target plate. Within the mass spectrometer, a laser beam induces the desorption and ionization of molecules by shooting multiple times on the sample (240 shots). The produced ions are accelerated by a magnetic field and separated according to their m/z ratio in the tube. The TOF analyzer records the impact of the various ions at the end of the tube. According to the time of flight, each impact is converted into a m/z ratio, and impacts corresponding to the same m/z ratio are summed up to generate the full raw spectrums.
Figure 4 illustrates the role of sample preparations in the interpretation of MALDI-TOF MS results. A good quality spectrum is represented in Figure 4A. It usually contains a major peak around 5 kD (m/z = 4,965). A minimum cell concentration is required to obtain good samples: Figure 4B shows a poor quality spectrum obtained with a low cell concentration. However, raising MDM concentration above 1 x 105/µl does not improve the quality of spectra. Similar poor results are obtained when the sample is mixed with matrix before deposition on the target plate. If mixing is done on the target plate, it may also result in heterogeneous crystallization, as shown in Figure 4C. Hence, deposition of the samples on the target is a tricky and critical step in this protocol.
The reproducibility of the spectra is shown in Figure 5. Here, spectra from various samples are represented as a heatmap. Relative abundance (intensity) is color-coded by intensities of blue. This virtual gel-view representation illustrates the reproducibility of the samples within each class. The normalization and alignment of the spectra is a critical step to obtain such results. An unsupervised analysis by hierarchical clustering is summarized as a dendrogram on the right hand side of the figure. It illustrates that all samples clustered within three different groups: unstimulated MDMs (NS), IFN-γ-stimulated or IL-4-stimulated MDMs.
Figure 6 illustrates the discrimination of M1 macrophages (MDMs stimulated with IFN-γ) from M2 macrophages (MDMs stimulated with IL-4) and unstimulated MDMs. Indeed, the peak representation of a reference spectrum for IFN-γ, IL-4 or unstimulated MDMs shows specific peaks for each class. This representation is obtained using the R MALDIquant library27.
Figure 7 illustrates the specific fingerprints induced by several agonists. It is commonly accepted that IFN-γ, TNF and LPS induce an inflammatory (M1-type) response in macrophages. We used MDM samples stimulated with these cytokines alone or in combination to illustrate the accuracy of whole-cell MALDI-TOF MS. Indeed, spectra from all stimulated samples were clearly separated from those of unstimulated macrophages (Figure 7A). However, we obtained a specific fingerprint from each type of stimulation, as illustrated by the clustering of the samples according to the stimuli. Interestingly, MDMs also exhibited specific fingerprints induced by heat-killed bacteria (Figure 7B). These results support the hypothesis that MALDI-TOF MS may be used to analyze circulating cells to assess the host-response to infection or inflammatory diseases in the clinical setting.
Figure 1. Preparation of biological samples. 1. Monocytes were selected from peripheral blood mononuclear cells (PBMC) by positive selection with magnetic beads coated with anti-CD14+ antibodies. 2. Macrophages were obtained in 7 days by culture of monocytes in RPMI. 3. Stimulated samples were obtained by adding either cytokines or heat-killed bacteria for 18h on differentiated macrophages. RBC: Red blood cells.
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Figure 2. Assessment of CD14 and CD68 expression by flow cytometry. Monocytes (left panel) or MDMs (right panel) were labeled with anti-CD14-PE and anti-CD68-AF647 antibodies to assess membrane expression of these molecules. The differentiation of monocytes into MDMs is accompanied by the down-modulation of CD14 expression and the up-modulation of CD68 expression.
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Figure 3. Principle of MALDI-TOF MS technology. This drawing describes the principle of the MALDI-TOF mass spectrometry.
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Figure 4. Whole-cell MALDI-TOF MS spectra. A zoomed view of spots deposited on the MALDI target (left panels) with corresponding spectra (right panels). Note that a good quality spot leads to an accurate spectra (A) whereas bad quality spots lead to spectra with a very poor signal to noise ratio (B, C).
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Figure 5. Reproducibility of MALDI-TOF MS spectra. Virtual gel-view of the whole spectra obtained from control and IL-4- or IFN-γ-stimulated MDMs are presented as a heatmap. Horizontal axis refers to the m/z ratio. Spectra are classified according to the presence/absence of peaks. NS: non stimulated; IFN-γ: interferon-gamma; IL-4: interleukin 4. This figure was reproduced from Ouedraogo et al.13 with permission.
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Figure 6. Reference spectra for M1 and M2 macrophages. The reference spectra for IFN-γ- and IL-4-stimulated MDMs are compared to the reference spectrum of nonstimulated (NS) MDMs. The peaks that are shared by stimulated and NS MDMs are in black. The peaks that are induced by stimulation are in red, whereas peaks that are detected only in NS MDMs are in green. m/z: mass/charge ratio; IFN-γ: interferon-gamma; IL-4: interleukin 4. This figure was reproduced from Ouedraogo et al.13 with permission.
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Figure 7. Hierarchical clustering of activated MDMs. MDMs were stimulated with different agonists for 18 hr. The results are shown as hierarchical clustering of the data. MDMs were activated with M1-related agonists (A) and intracellular bacteria or IL-4 (B). Unstimulated MDMs are presented in grey. IFN-γ: interferon-gamma; LPS: lipopolysaccharide from Escherichia coli; TNF: tumor necrosis factor, IL-4: interleukin 4; BCG; bacillus Calmette-Guérin; C. burnetii: Coxiella burnetii; O. tsutsugamushi: Orientia tsutsugamushi. This figure was reproduced from Ouedraogo et al.13 with permission.
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This protocol describes the use of MALDI-TOF-MS on eukaryotic whole cells. Here, we illustrate the accuracy of the method by analyzing the multiple activation states of macrophages in response to their microenvironment.
The success of the protocol relies on few critical steps. First, any solution contaminant may alter the spectra. For example, it is important to wash cells in PBS to remove culture medium and serum proteins before deposition on the target. A cell concentration of 1 x 105 cells/µl is also needed to ensure reproducible results. Second, the crystallization is an important step in the protocol. To ensure good quality results, the target plate must be carefully washed and the matrix should be prepared before the deposition of samples on the target. The best results are obtained when the samples are deposited on the target just before the matrix solution (avoid mixing the samples with the matrix before the deposition on the target). Correct spontaneous mixing between samples and the matrix solution needs homogeneous deposits. Third, whole-cell MALDI-TOF-MS is a high-throughput technique, which can rapidly result in high amounts of raw data. Bioinformatics analysis is thus a major tool to systematically analyze the data in a reasonable amount of time. Quality assessment, background correction and normalization can be automated. The selection of relevant peaks (e.g. above a given signal-to-noise ratio) and the comparison of spectra based on the presence/absence of these peaks require important computational steps. These methods are described in details in the supplementary material of this article.
Although the acquisition of a mass spectrometer may represent a significant investment, daily running costs are low, and a high number of biological and technical replicates may be easily obtained in one run. For example, our university hospital is able to routinely identify bacteria in 200 clinical samples each day with a similar whole-cell technique. The cell concentration may be a limit for specific clinical applications such as the analysis of needle biopsies or cells harvested from broncho-alveolar lavages. A recent article described an automated approach of whole-cell MALDI-TOF analysis that allowed the robust classification of samples with as few as 250 cells on each spot11. A proof of concept of the clinical application of this technique to the diagnosis of oral cancer has also been recently published15. The matrix choice may limit the type of analyzed molecules. Some matrices will favor the ionization of specific type of molecules (proteins, lipids, sugars…) and of a given mass range. In our conditions, we were not able to retrieve good quality spectra with ions above 20 kDa. In our protocol, we focused on the analysis of whole spectra as a fingerprint of a given activation state of cells. Therefore, we did not try to identify the proteins that form the main peaks of the spectrum. The identification of specific biomarkers requires an alternative use of mass spectrometry.
In conclusion, we describe here the application of a whole-cell MALDI-TOF MS approach for the accurate and rapid analysis of macrophage activation. This method allowed the identification of macrophage-specific fingerprints that are representative of the diversity of proteomic responses to cytokines and bacterial pathogens. The protocol we described here may be useful for studying the immune host response in pathological conditions or may be extended to wider diagnostic applications.
The authors have nothing to disclose.
Richard Ouedraogo is supported by a grant from the Ministère de la Santé (PHRC 2010). We thank Laurent Gorvel, Christophe Flaudrops and Nicolas Amstrong for technical assistance.