Proteomics Reveals a Role for Attachment in Monocyte Differentiation into Efficient Proinflammatory Macrophages

Identification of Inflammatory Proteomics Networks of Toll-like Receptor 4 through Immunoprecipitation-Based Chemical Cross-Linking Proteomics

Toll-like receptor 4 (TLR4) is a receptor on an immune cell that can recognize the invasion of bacteria through their attachment with bacterial lipopolysaccharides (LPS). Hence, LPS is a pro-immune response stimulus. On the other hand, statins are lipid-lowering drugs and can also lower immune cell responses. We used human embryonic kidney (HEK 293) cells engineered to express HA-tagged TLR-4 upon treatment with LPS, statin, and both statin and LPS to understand the effect of pro- and anti-inflammatory responses. We performed a monoclonal antibody (mAb) directed co-immunoprecipitation (CO-IP) of HA-tagged TLR4 and its interacting proteins in the HEK 293 extracted proteins. We utilized an ETD cleavable chemical cross-linker to capture weak and transient interactions with TLR4 protein. We tryptic digested immunoprecipitated and cross-linked proteins on beads, followed by liquid chromatography–mass spectrometry (LC-MS/MS) analysis of the peptides. Thus, we utilized the label-free quantitation technique to measure the relative expression of proteins between treated and untreated samples. We identified 712 proteins across treated and untreated samples and performed protein network analysis using Ingenuity Pathway Analysis (IPA) software to reveal their protein networks. After filtering and evaluating protein expression, we identified macrophage myristoylated alanine-rich C kinase substrate (MARCKSL1) and creatine kinase proteins as a potential part of the inflammatory networks of TLR4. The results assumed that MARCKSL1 and creatine kinase proteins might be associated with a statin-induced anti-inflammatory response due to possible interaction with the TLR4.

Spatiotemporal proteomic profiling of the pro-inflammatory response to lipopolysaccharide in the THP-1 human leukaemia cell line

Protein localisation and translocation between intracellular compartments underlie almost all physiological processes. The hyperLOPIT proteomics platform combines mass spectrometry with state-of-the-art machine learning to map the subcellular location of thousands of proteins simultaneously. We combine global proteome analysis with hyperLOPIT in a fully Bayesian framework to elucidate spatiotemporal proteomic changes during a lipopolysaccharide (LPS)-induced inflammatory response. We report a highly dynamic proteome in terms of both protein abundance and subcellular localisation, with alterations in the interferon response, endo-lysosomal system, plasma membrane reorganisation and cell migration. Proteins not previously associated with an LPS response were found to relocalise upon stimulation, the functional consequences of which are still unclear. By quantifying proteome-wide uncertainty through Bayesian modelling, a necessary role for protein relocalisation and the importance of taking a holistic overview of the LPS-driven immune response has been revealed. The data are showcased as an interactive application freely available for the scientific community.

Proteomic analysis of lipopolysaccharide activated human monocytes

Monocytes are key mediators of innate immunity and comprise an important cellular defence against invading pathogens. However, exaggerated or dysregulated monocyte activation can lead to severe immune-mediated pathology such as sepsis or chronic inflammatory diseases. Thus, detailed insight into the molecular mechanisms of monocyte activation is essential to understand monocyte-driven inflammatory pathologies. We therefore investigated the global protein changes in human monocytes during lipopolysaccharide (LPS) activation to mimic bacterial activation. Purified human monocytes were stimulated with LPS for 17 h and analyzed by state-of-the-art liquid chromatography tandem mass spectrometry (LC-MS/MS). The label-free quantitative proteome analysis identified 2746 quantifiable proteins of which 101 had a statistically significantly different abundance between LPS-stimulated cells and unstimulated controls. Additionally, 143 proteins were exclusively identified in either LPS stimulated cells or unstimulated controls. Functional annotation clustering demonstrated that LPS, most significantly, regulates proteasomal- and lysosomal proteins but in opposite directions. Thus, seven proteasome subunits were upregulated by LPS while 11 lysosomal proteins were downregulated. Both systems are critically involved in processing of proteins for antigen-presentation and together with LPS-induced regulation of CD74 and tapasin, our data suggest that LPS can skew monocytic antigen-presentation towards MHC class I rather than MHC class II. In summary, this study provides a sensitive high throughput protein analysis of LPS-induced monocyte activation and identifies several LPS-regulated proteins not previously described in the literature which can be used as a source for future studies.

In-Depth Proteomic Characterization of Classical and Non-Classical Monocyte Subsets

Monocytes are bone marrow-derived leukocytes that are part of the innate immune system. Monocytes are divided into three subsets: classical, intermediate and non-classical, which can be differentiated by their expression of some surface antigens, mainly CD14 and CD16. These cells are key players in the inflammation process underlying the mechanism of many diseases. Thus, the molecular characterization of these cells may provide very useful information for understanding their biology in health and disease. We performed a multicentric proteomic study with pure classical and non-classical populations derived from 12 healthy donors. The robust workflow used provided reproducible results among the five participating laboratories. Over 5000 proteins were identified, and about half of them were quantified using a spectral counting approach. The results represent the protein abundance catalogue of pure classical and enriched non-classical blood peripheral monocytes, and could serve as a reference dataset of the healthy population. The functional analysis of the differences between cell subsets supports the consensus roles assigned to human monocytes.

Inflammatory Proteomic Network Analysis of Statin-treated and Lipopolysaccharide-activated Macrophages

A significant component of immune biology research is the investigation of protein encoding genes that play central roles in contributing inflammatory response. A gel-free quantitative bottom-up proteomics study was performed on immune cell macrophages after the combined treatment of lipopolysaccharide (LPS) and statin drugs using mass spectrometry and a detailed bioinformatics analyses were conducted. Systematic bioinformatics analysis was applied for discovering novel relationships among proteins and effects of statin and lipopolysaccharide in macrophage cells. Based on gene ontology, majority of protein encoding genes was involved in metabolic and cellular processes and are actively associated with binding, structural molecular, and catalytic activity. Notably, proteomic data analyzed by Ingenuity Pathway Analysis (IPA), discovered the plectin and prohibitin 2 protein interactions network and inflammatory-disease based protein networks. Two up-regulated proteins, plectin and prohibitin 2, were further validated by immunoblotting. Plectin was also cross-validated by immunocytochemistry, since its expression was highly modulated by statin but inhibited during LPS-stimulation. Collectively, the significant up-regulation of plectin due to the treatment of statin, suggests that statin has a significant impact on the cytoskeletal networks of cells. Plectin might have a significant role in the intermediate filament assembly and dynamics, and possibly stabilizing and crosslinking intermediate filament networks.

Cytotoxic and Proinflammatory Effects of Metal-Based Nanoparticles on THP-1 Monocytes Characterized by Combined Proteomics Approaches

Thorough characterization of toxic effects of nanoparticles (NP) is desirable due to the increasing risk of potential environmental contamination by NP. In the current study, we combined three recently developed proteomics approaches to assess the effects of Au, CuO, and CdTe NP on the innate immune system. The human monocyte cell line THP-1 was employed as a model. The anticancer drugs camptothecin and doxorubicin were used as positive controls for cell death, and lipopolysaccharide was chosen as a positive control for proinflammatory activation. Despite equivalent overall toxicity effect (50 ± 10% dead cells), the three NP induced distinctly different proteomics signatures, with the strongest effect being induced by CdTe NP, followed by CuO and gold NP. The CdTe toxicity mechanism involves down-regulation of topoisomerases. The effect of CuO NP is most reminiscent of oxidative stress and involves up-regulation of proteins involved in heat response. The gold NP induced up-regulation of the inflammatory mediator, NF-κB, and its inhibitor TIPE2 was identified as a direct target of gold NP. Furthermore, gold NP triggered activation of NF-κB as evidenced by phosphorylation of the p65 subunit. Overall, the combined proteomics approach described here can be used to characterize the effects of NP on immune cells.

Exploring high-affinity binding properties of octamer peptides by principal component analysis of tetramer peptides

To investigate the binding properties of a peptide sequence, we conducted principal component analysis (PCA) of the physicochemical features of a tetramer peptide library comprised of 512 peptides, and the variables were reduced to two principal components. We selected IL-2 and IgG as model proteins and the binding affinity to these proteins was assayed using the 512 peptides mentioned above. PCA of binding affinity data showed that 16 and 18 variables were suitable for localizing IL-2 and IgG high-affinity binding peptides, respectively, into a restricted region of the PCA plot. We then investigated whether the binding affinity of octamer peptide libraries could be predicted using the identified region in the tetramer PCA. The results show that octamer high-affinity binding peptides were also concentrated in the tetramer high-affinity binding region of both IL-2 and IgG. The average fluorescence intensity of high-affinity binding peptides was 3.3- and 2.1-fold higher than that of low-affinity binding peptides for IL-2 and IgG, respectively. We conclude that PCA may be used to identify octamer peptides with high- or low-affinity binding properties from data from a tetramer peptide library.

Approach for Identifying Human Leukocyte Antigen (HLA)-DR Bound Peptides from Scarce Clinical Samples

Immune-mediated diseases strongly associating with human leukocyte antigen (HLA) alleles are likely linked to specific antigens. These antigens are presented to T cells in the form of peptides bound to HLA molecules on antigen presenting cells, e.g. dendritic cells, macrophages or B cells. The identification of HLA-DR-bound peptides presents a valuable tool to investigate the human immunopeptidome. The lung is likely a key player in the activation of potentially auto-aggressive T cells prior to entering target tissues and inducing autoimmune disease. This makes the lung of exceptional interest and presents an ideal paradigm to study the human immunopeptidome and to identify antigenic peptides.Our previous investigation of HLA-DR peptide presentation in the lung required high numbers of cells (800 × 10(6) bronchoalveolar lavage (BAL) cells). Because BAL from healthy nonsmokers typically contains 10-15 × 10(6) cells, there is a need for a highly sensitive approach to study immunopeptides in the lungs of individual patients and controls.In this work, we analyzed the HLA-DR immunopeptidome in the lung by an optimized methodology to identify HLA-DR-bound peptides from low cell numbers. We used an Epstein-Barr Virus (EBV) immortalized B cell line and bronchoalveolar lavage (BAL) cells obtained from patients with sarcoidosis, an inflammatory T cell driven disease mainly occurring in the lung. Specifically, membrane complexes were isolated prior to immunoprecipitation, eluted peptides were identified by nanoLC-MS/MS and processed using the in-house developed ClusterMHCII software. With the optimized procedure we were able to identify peptides from 10 × 10(6) cells, which on average correspond to 10.9 peptides/million cells in EBV-B cells and 9.4 peptides/million cells in BAL cells. This work presents an optimized approach designed to identify HLA-DR-bound peptides from low numbers of cells, enabling the investigation of the BAL immunopeptidome from individual patients and healthy controls in order to identify disease-associated peptides.

Establishing a Proteomics-Based Monocyte Assay To Assess Differential Innate Immune Activation Responses

Innate immune cells are complex systems that can be simultaneously activated in a variety of ways. Common methods currently used to estimate the response of innate immune cells to stimuli are usually biased toward a single mode of activation. The aim of this study was to assess the possibility of designing an assay based on unbiased proteome analysis that would be capable of predicting the complex response of the innate immune system to various challenges. Monocytes were used as representative cells of the innate immune system. The underlying hypothesis was that their proteome response to different activating molecules would reflect the immunogenicity of these molecules. To identify the main modes of response, we treated the human monocytic THP-1 cell line with nine different stimuli. Differentiation and activation were determined to be the two major modes of monocyte response, with PMA causing the strongest differentiation and Pam3CSK4 causing the strongest proinflammatory activation. The established assay was applied to characterize the monocyte response to epidermal growth factor peptide containing isoaspartate, which induced differentiation but not proinflammatory activation. Because of its versatility, robustness, and specificity, this new assay is likely to find a niche among the more established immunological methods.