Analysis of Cytokine and Chemokine Gene Expression in Classically Activated Macrophages: Influence

Analysis of Cytokine and Chemokine Gene Expression in Classically Activated Macrophages:
Influence of lipopolysaccharide in the response of human macrophages to IFN-Ɣ
Word count: 8442 (total) Abstract (250), introduction (2663), Methods (248), results (1824 ), discussion and conclusion (2175)
ANALYSIS OF CYTOKINE AND CHEMOKINE GENE EXPRESSION IN CLASSICALLY ACTIVATED MACROPHAGES:
INFLUENCE OF LIPOPOLYSACCHARIDE IN THE RESPONSE OF HUMAN MACROPHAGES TO IFN-Ɣ
Abstract
Background: Activation of proinflammatory and antimicrobial macrophage phenotypes is known to be regulated by IFN-γ and LPS, through the induction of NF-κB target genes. However, the exact nature of the influence of LPS-driven signalling on macrophage response to IFN-γ activation remains unclear.
Methods: A transcriptomics approach (RNAseq) approach was used to determine differences in cytokine and chemokine induction in macrophages exposed to IFN-γ compared with those treated with both IFN-γ and LPS. Read counts were analysed to determine differentially expressed genes between the various groups tested.
Results: Both synergistic and inhibitory profiles were observed. Most notably, the LPS+IFN-γ combination significantly upregulated TGFB3 (involved in immune response and tissue homeostasis) and downregulated IL10 (anti-inflammatory), CCL23, TNFSF18 (known to be LPS-responsive), and CSF3 (an NF-κB effector). The IFN-γ-treated macrophages (without LPS) showed increased expression of the immunomodulatory IL7 and TNFSF10 (an LPS-responsive tumour necrosis factor (TNF) ligand superfamily member), and suppression of IL10 and CX3CL1. In the absence of IFN-γ, LPS signalling significantly upregulated the proinflammatory set IL1B, IL6, and TNF, as well as CCL23, TNFSF10, TNFSF18 and IL7. Additionally, LPS attenuated the induction of IL16 (an immunomodulator highly expressed in M1 macrophages) and did not affect CX3CL1 and IL-10.
Conclusions: The findings of the current study provide further evidence that IFN-γ can both potentiate and attenuate LPS-driven macrophage responses. In the conditions tested, IFN-γ showed a more suppressive than inducive or synergistic effect on LPS-mediated signalling. These data provide additional insight into how IFN-γ selectively inhibits LPS/TLR4-induced transcription in macrophages.
Table of contents
Chapter One: Introduction 4
Chapter Two: Materials and Methods 10
Monocyte preparation 10
Cell treatment and RNA extraction 11
Statistical Analysis 11
Chapter Three: Results 12
Chapter Four: Discussion 24
Summary.. 27
Chapter Five: Conclusion and Recommendations 28
References 29
Chapter One: Introduction
Immunology is an important division of the biological and medical sciences that studies the immune system. The immune system protects organisms against diverse infections, which can be fungal, viral, or bacterial or caused by parasitic microorganisms. It is a complex system of body structures and processes, including cellular and molecular components, which evolved to protect against infections and diseases (2). The immune responses can also trigger the development of disorders, including cardiovascular, metabolic, and neurodegenerative illnesses. The molecular and cellular components make the immune system either innate to the organism or adapted to defined pathogens. This work focuses on macrophages, which are part of the innate immune system, and describes the macrophage activation process, which plays a significant role in strengthening the body’s immunity. Further, the roles of lipopolysaccharide (LPS) and interferon-gamma (IFN-γ) will be discussed as the inducing agents of classical macrophage activation. This introduction will also address the role of chemokines and cytokines in facilitating immunity and how cytokines are markers of macrophage activation. Finally, the aims of this study will be defined.
Macrophages
Macrophages are specialised white blood cells that detect, phagocytose, and destroy bacteria and other harmful microorganisms that attack the organism. Macrophages also present antigens to T-cells and facilitate inflammation by releasing cytokines, that induce activation of other cells (2). Some tissue macrophages originate from the monocytes, which leave the blood circulation to differentiate in different body tissues. In some organs all macrophages derive from precursors seeded during development and are maintained by self-replication. Macrophages are found in almost all body tissues removing dead cells and patrolling for pathogenic components. There are different macrophages in the body, including Kupffer cells found in the liver, adipose tissue macrophages located in the adipose tissue, and microglia found in the central nervous system (4). Other essential types of macrophages include sinus histiocytes located in the lymph nodes, alveolar macrophages found in the lung alveoli, osteoclasts in bones, and macrophages located in the bone marrow, among others.
The resident liver macrophages are central to the role of the liver. They are the first innate immune cells and protect the liver from bacterial infections under physiological circumstances (11). If the conditions are pathological, the Kupffer cells are activated and can differentiate into classical and alternative macrophages or M1-like and M2-like, respectively (11). A study by Nguyen-Lefebvre and Horuzsko (11) suggests that the special functions and metabolism of the macrophages make them an attractive target for liver therapy associated with inflammation, cancer, and infectious diseases.
The adipose tissue macrophages are the most abundant class of leukocytes in the adipose tissue and are responsible for the regulation of tissue remodelling, insulin sensitivity, and other physiological processes (12). The macrophages microglial cells are essential to maintain the health of the central nervous system. They remove damaged neurons and infections from the CNS. The microglia originate front the sac-primitive macrophages and automatically proliferate into adulthood. They do not get replaced by the bone marrow-derived circulating cells (12). The study by Augusto-Oliveira et al. posits that these macrophages are vital in the preservation of homeostasis and the cognitive activities in the brain of a healthy adult.
The microglial cells account for an estimated 10 percent of brain cells and are involved in virtually all pathological processes in the brain. These processes include stroke, inflammation, neurodegenerative diseases, and bacterial and viral infections (12). The osteal macrophages, in recent times categorized as myeloid cells, are dissimilar from the osteoclasts and regulate bone formation (13). Osteal macrophages also play a crucial role in skeletal homeostasis. Significant bone phenotypes are proven to depend on the subset of macrophage altered. Apart from the evidenced and generally accepted role of macrophages in the initial inflammatory stage of bone repair, there is corroborative proof validating macrophages involvement in collagen deposition and mineralization in no osseous tissues (13). Osteoclasts are primarily viewed as the primary macrophages of bone tissue. They are responsible for the resorption of bone.
Macrophages destroy and eliminate harmful microorganisms in the body through the phagocytosis process. These cells are amoeba-like and rely on phagocytosis to internalise microorganisms as a means of destroying them. The phagocytosis process occurs by forming a pocket-like structure known as a phagosome that forms around a particle when the macrophage engulfs it. After phagosome formation, lysosomes deliver enzymes into the phagosomes, which digests the engulfed particle. The digested material exits the macrophage and get reabsorbed in the body. However, macrophages are unique in identifying which microorganisms to destroy and the ones not to. The living cells in the human body comprise specific protein components on their outer membrane that enable the immune system to distinguish its own cells from foreign ones. Macrophages detect the proteins found on the outer membranes of cells to distinguish and destroy the foreign microorganisms (4).
Furthermore, macrophages play a crucial role in eradicating unhealthy and damaged cells via the process of apoptosis. Typically, macrophages consume and disintegrate dead cells, tumour cells, debris, and foreign materials. The macrophages respond to internal and external changes through trophic, regulatory functions as well as the phagocytic and repair functions (14).
Thus, macrophages are an essential part of the immune system that helps in fighting against infections and diseases.
Macrophage Activation
Macrophages are activated by the TH1 CD4 T cells to become M1-like, thus becoming extremely microbial. In contrast, the M2-like macrophages occur in TH2-dominated responses and help in tissue healing, resolve inflammation, and can contribute to tolerance to self-antigens and particular neoantigens. This implies that M2- like macrophages are necessary for processes such as normal pregnancy (15). The characteristics of the M2-like macrophages are similar to properties of tumour-associated macrophages (15).
When a TH1 cell for a certain bacterial peptide comes into contact with a highly microbial macrophage presenting the specific peptide on MHCII, the T-cell is induced to produce interferon-gamma (IFN-γ), a macrophage activating factor, and express the CD40 ligand that interacts with CD40. In other words, a TH1 cell stimulates the infected macrophage via cell contact and focal secretion of IFN-γ. The contact between the infected macrophage and the TH1 cell produces a sequence of biochemical reactions that transforms the macrophage into a strong antimicrobial effector cell (9). IFN-γ signalling is associated with inflammation and cell-mediated immune responses (16). The cytokine is essential to the regulation of the host defence system through the mediation of both innate and adaptive immune responses. Represented as an antitumour cytokine that facilitates immunosurveillance in tumour cells, IFN-γ signalling elicits pro-tumorigenic transformation. It also promotes tumour progression and orchestrates immunomodulation, apoptosis leucocyte trafficking, and anti- and pro-tumorigenic roles (16). The activated macrophages go through a series of changes that strengthen their antimicrobial efficiency while also amplifying the macrophages’ immune response. The autocrine stimulus interacts with IFN-γ released by TH1 cells to strengthen the antimicrobial activity of the macrophage by prompting the production of oxygen radicals and nitric oxide. Further, the macrophage readjusts its B7 molecules (peripheral membrane proteins) as a reaction to bind to the CD28 ligand on the T-cell. The activated macrophage also increases expression of major histocompatibility complex class II molecules and thus facilitates the activation of CD4 T cells at rest.
Different molecules are key markers in macrophage activation, including CD14, CD68, CD16, CCR5, and CD64. Membrane receptors are used as macrophage markers in different contexts, such as markers for monocyte-macrophage transition, tissue-specific subtypes, M1 and M2 polarization, and tumour-associated macrophages. CD11b and CD68 are perceived as the total markers in macrophage activation (6). In M1 and M2 polarization, M1 macrophages possess the proinflammatory function linked to immune responses against intracellular and bacterial pathogens. The M1 activation for macrophages takes place through TNF and IFN-γ signalling. The genetic markers linked to M1 polarization include IL-6, IL-1a, TLR-4, IL1b, CD80, TLR-2, and CD86. In contrast, M2 is linked to anti-inflammatory functions, such as wound healing and the formation of new blood vessels from existing ones. M2 activation occurs in response to cytokines such as IL-10, IL-4, and IL-13. The key markers for M2 include ARG1, CD115, PPARG, PDL2, CD163, Fizz-1, Dectin-1, and CD206 (10).
The activated macrophage produces Interleukin-12, which leads to the differentiation of activated CD4 T-cells into TH1 effector cells. The already activated macrophages then merge their lysosomes more effectively with the phagosomes. The fusion exposes the internalized extracellular microbes or intracellular microbes to a wide variety of lysosomal enzymes. Further, the activated macrophages facilitate the synthesis of antimicrobial proteases and peptides, which can be released to attack and destroy the extracellular parasites (5). Although there is a lack of substantive research, it is posited that activated macrophages are good at destroying harmful microorganisms, they cannot be maintained at the activated state because they consume a lot of glucose when activated. The activated macrophages can also destroy the surrounding tissues from the formation of antimicrobial mediators, including nitric oxide, oxygen radicals, and proteases, which are toxic (1). However, triggering the toxic mediators enable macrophages to attack the huge extracellular microorganisms, such as parasitic worms, that they cannot phagocytize.
IFN-γ and LPS as Inducers of Classical Activation
When macrophages are stimulated by lipopolysaccharide (LPS) and IFN-γ, they are termed as classically activated, which is represented by M1. The differentiation of macrophages during classical activation requires a priming signal, which is IFN-γ. The IFN-γ is usually produced by different cells, including the Th1 cells,CD8⁺ cells and NK cells. When the primed macrophage comes across a suitable stimulus, such as bacterial LPS, it is then considered classically activated. The LPS is a major component of the outer cell wall of gram-negative bacteria. The large glycolipid LPS comprises three domains in its structure, including Lipid A, the core Oligosaccharide, and the O antigen. The Lipid A of the structural domain is an aquaphobic section of the particle. It is an acylated β-1‘-6-linked glucosamine disaccharide. It typically structures on the external leaflet of the OM (17).
LPS is transported by soluble lipopolysaccharide-binding protein and afterward by a membrane-bound or soluble CD14. The CD14 then transfers LPS to the recognition complex consisting of MD-2 and TLR4 (8). As mentioned above, classical activation of macrophages promotes destruction of ingested pathogens or pathogenic components. The internalised cargo is exposed to different degradation enzymes in the lysosomes, such as cathepsin cysteine protease. Antigens are then sorted and laden onto MHC class II molecules in the antigen complexes and endocytic compartments, while co-stimulatory B7 components are handed over to T-cells. These activities are trailed by a noteworthy change in cellular morphology and modification in the production profile of the cell. Numerous chemokines are produced and released for immature dendritic cells, activated T-cells, neutrophils, and natural killer cells, followed by the production of proinflammatory cytokines, such as TNF-alpha, IL-1, and IL-6. TNF-α leads to the proapoptotic event of the classically stimulated macrophages.
Further, M1 produces proteolytic enzymes, such as MMP-1, MMP-2, MMP-7, MMP-9, and MMP-12, used in degrading Fibronectin and Collagen, among other components. Thus, the classical activation of macrophages is related to CD86 and MHC class II expression and their capacity to produce chemokines, such as CCL15, CXCL12, CCL20, and CXCL8-11, and proinflammatory cytokines, such as IL-1β, TNF-α, IL-12, and IL-18 (8). The release of the different molecules during the classic activation is significant for the adaptive immune system as well as host defence; however, they can cause collateral damage to the body tissues if not controlled. The classic activation of macrophages can dismantle body tissues or even cause severe injuries because it produces huge leukocyte infiltration and floods the tissues with proapoptotic factors, inflammatory mediators, and even matrix degrading proteases. Thus, LPS and IFN-γ induce the classical activation of macrophages; however, uncontrolled activation may lead to tissue destruction, causing tumour development and glomerulonephritis, among others.
Role of Cytokines and Chemokines in Immunity
Cytokines and chemokines play key roles in the growth, activation, and differentiation functions of cells. Their functions lead to regulation and identification of nature immune responses and also regulate cell trafficking and cellular appearance of the immune organs. Cytokines, are glycoproteins, regulate inflammation, immunity, and haematopoiesis in the body. Cytokines play a significant role in the innate or natural responses by inducing – direct-action mechanisms against foreign agents in the early infection stages or through an immune-modulatory mechanism that stimulates monocyte macrophages and natural killer cells, thus triggering the release of more cytokines (3). Cytokines and chemokines guide the differentiation of migrated monocytes into macrophages. If tissue damage occurs because of trauma or infection, the neutrophils migrate out of circulation and initiate crosstalk with non-immune and immune cells (18). If an antigen breaks through the physical and chemical barriers of the organism, the innate immunity offers the first non-specific defence. In the non-specific defence response, cytokines enhance the immunity by either blocking the viral replication via the interferons or by activating natural killer cells, trigger an inflammatory response or activate macrophages. The IL-1, IL-12, and IL-6 cytokines stimulate natural killer cells and monocytes/macrophages and enable processes that elevate body temperature (5). Further, TNF-α enhances vascular permeability, leading to fluid and immunoglobulin accumulation and other blood proteins in tissues, which enhance protection against infections. As mentioned above, IFN (α, β, or γ) inhibits viral reproduction by generating a transitory resistance stage against viral infections in the cells. These cytokine activities stimulate fast immune response and reduce the ability of pathogen to replicate.
Chemokines are proteins within the cytokine family, which play a key role in inducing the migration of cells into the injured tissues. Termed as chemotactic cytokines, they play a key role in immune cell trafficking into different body tissues and also leukocyte chemo-attraction. Inflammatory chemokines are triggered in response to an inflammatory stimulus or in case of infection to expedite an immune response and target the adaptive and innate cells of the immune system. Cytokine binding to its specific receptor leads to stimulation of the receptor, thus triggering signalling events that control different cellular functions, including cytokine production, cell propagation, cell survival, phagocytosis, proliferation, and apoptosis “cell death”. Further, chemokines are perceived to play significant roles in the functioning of the nervous system, such as cell proliferation, migration of neurons, neuro-inflammation mediation, as well as synaptic activity (3). Although they prompt inflammation through enrolling leukocytes via their chemotactic activity, they also impact neuronal cells. Chemokines prompt the death of neurons by stimulating neuronal chemokine receptors or by activating the killing mechanism of the microglia. Other chemokines partake in neuroprotective functions as either anti- or proinflammatory mediators.
Cytokines as Markers of Macrophage Activation
Cytokines are significant indicators in the activation of macrophages. For monocyte-macrophage transition, macrophages can come from bone marrow derivative monocytes or embryonic precursors. The monocytes differentiate into macrophages during the immune response or after migrating into different tissues, which works as a reservoir for replacing macrophage populations. Examples of monocyte heredity markers include CD68, CD14, F4/80, CD11b, CD16, and Ly6c1. Further, for tissue-specific subtype markers, macrophages live within tissues, leading to different cell populations that carry out a niche- and tissue-specific functions. For instance, lung alveolar, which live in the lungs, clear surplus pulmonary surfactants, and attack foreign agents. Examples of these markers include CD68, CD11c, PPARG, CD206, MARCO, and CD80 (6). Finally, markers related to tumour-associated macrophages (TAM) can stimulate angiogenesis of tumours, suppress the immunity of tumours, and help in the migration and invasion of tumour cells. These TAM outcomes are facilitated by cancer signalling, impacting macrophage function and protein production by the TAMs to stimulate tumour growth (10). Some of the tumour markers include CCR2, CD40, CCL2, CD16, CSF1, and CCR2.
Aims of the Study
While the term classical activation refers to macrophages exposed to IFN-γ in the presence and absence of LPS, there is limited information on how the presence of IFN-γ impacts – LPS responses.
The primary aims of the study are:
To generate a novel RNAseq dataset and analyse cytokine and chemokine induction in classically-activated macrophages.
To determine differences in cytokine and chemokine production between macrophages exposed to IFN-γ and those treated with IFN-γ and LPS.
Chapter Two: Materials and Methods
Monocyte preparation
Monocytes were prepared as described in the LMP-SOP (Reference). On day 0, the cells were seeded in complete media containing 50ng/ml M-CSF, at a volume of 500 µl and a density of 1million per well. On day 3, the cells were replenished or refreshed with the same media described above. On the 6th day, cells were harvested – by placing plates on a box of ice for 20minutes and using a 1ml pipette to flush off cells. The cells were subsequently washed twice by centrifugation at 300 g acceleration and deceleration 3 at 4 37°C. The cells were then counted and seeded in 6 well tissue culture treated plates at 1.2 million cells in 1500 µl per well and incubated at 37 °C overnight.
Cell treatment and RNA extraction
On the 7th day, complete media with M-CSF(50ng/ml) was prepared and aliquoted into 1.5ml Eppendorf tubes with a total of 550 µl in each tube, which were labelled accordingly for the various conditions to be tested. The following complete media conditions were prepared: MCSF(50ng/ml) only, MCSF(50ng/ml) +INF-gamma(20ng/ml), MCSF(50ng/ml) +LPS(20ng/ml), and MCSF(50ng/ml) +INF-gamma(20ng/ml) +LPS(20ng/ml). The different treatment combinations were mixed well and subsequently added to cells at 500 µl per well and incubated at 37 °C for 4 hours.
After the 4 hour- incubation, RNA extraction was performed using the Promega kit: Z6212 (ReliaPrep™ miRNA Cell and Tissue Miniprep System) according to the manufacturer’s protocol.
Statistical Analysis “Graphpad PRISM8 was used”
Statistical analysis was performed using …
Chapter Three: Results
This study aimed to analyse cytokine and chemokine expression in classically activated macrophages and the influence of LPS in response to IFN-γ. The results (Figure 1-11) are represented as bar charts, and each shows the read count on the y-axis and the conditions in which each cytokine or chemokine was under on the x-axis. The read count refers to the predicted total number of reads which originate from each genomic locus and this analysis was performed to determine which loci exhibit statistically significant differences between various groups of samples (19, 20). When illustrated correctly, bar charts are a useful method of illustrating research findings when analysing gene expression as it allows for comparison to be performed with ease, and any statistically significant results can be clearly observed (21). All statistically significant relationships or probabilities between two data sets at different conditions are represented on the bar charts as P values (22). Furthermore, error bars represent the variation across the values obtained from the analysis which provide an indication of the uncertainty or error of the data (23), and these are included on each bar within the bar charts shown in Figure 1-11. Error bars are calculated using the standard deviation of the sample group divided by the square root of the group sample size, and this is known as the standard error.
Figure 1 shows the read count observation for IL1B (A), CCL4 (B), CCL4L2 (C) and CCL20 (D). The findings show that, in the presence of macrophage colony-stimulating factor (M-CSF), IFN-γ and LPS, IL1B is expressed, and this relationship is statistically significant to the presence of M-CSF alone and M-CSF with IFN-γ (p ≤ 0.05) in which no expression was found. A higher expression was found for IL1B when treated with M-CSF and LPS, however, this was not statistically significant. Similar findings were observed for CCL4 (p ≤ 0.01) and CCL4L2 (p ≤ 0.05), however, for CCL20, only the relationship between treatment with M-CSF, IFN-γ and LPS, and M-CSF and LPS was statistically significant (p ≤ 0.05).
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Figure 1: Bar charts showing read counts observed for IL1B (A), CCL4 (B), CCL4L2 (C), and CCL20 (D) under various different conditions. Read counts were measured for genes treated with macrophage colony-stimulating factor (M-CSF) in combination with interferon-gamma (IFN-γ) and lipopolysaccharide (LPS), M-CSF in combination with IFN-γ only, M-CSF in combination with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by * and ** which refer to a P value of ≤ 0.05 and ≤ 0.01, respectively
Figure 2 shows the read count value for CXCL3 (A), CXCL5 (B), TNFSF18 (C), CXCL1 (D) and CXCL2 (E) in the presence of the – treatments described above. The highest expression of all five of these genes was found in macrophages exposed to M-CSF and LPS, and there was a statistically significant relationship at a p-value of ≤ 0.05 shown between this treatment and treatment with M-CSF, IFN-γ and LPS for CXCL3, CXCL5, TNFSF18 and CXCL2. A p-value of ≤ 0.01 was observed between these two treatments for CXCL1. Low expression of CXCL5 and TNFSF18 was observed under treatments with M-CSF and IFN-γ, and M-CSF alone, and a significant relationship (p ≤ 0.01) was observed between M-CSF with IFN-γ and M-CSF with LPS for CXCL5.
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Figure 2: Bar charts showing read counts observed for CXCL3 (A), CXCL5 (B), TNFSF18 (C), CXCL1 (D) and CXCL2 (E) under various different conditions. Read counts were measured for genes treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by * and ** which refer to a P value of ≤ 0.05 and ≤ 0.01, respectively.
TNF was expressed in treatment with M-CSF, IFN-γ and LPS, as well as with M-CSF with LPS (Figure 3). A P value of ≤ 0.05 was determined between M-CSF with IFN-γ and M-CSF with LPS. In contrast, CX3CL1 was highly expressed in the presence of M-CSF alone, whereas little or no expression was observed in the presence of M-CSF alone for TNF, TNFSF10, and IL7. P ≤ 0.01 was found between M-CSF with IFN-γ and M-CSF alone. Expression of TNFSF10 occurred – in all treatments except M-CSF alone, and in IL7, expression was observed during all treatments, however, in the presence of M-CSF alone, this expression was minimal.
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Figure 3: Bar charts showing read counts observed for TNF (A), CX3CL1 (B), TNFSF10 (C), IL7 (D) under various different conditions. Read counts were measured for genes treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by * and ** which refer to a P value of ≤ 0.05 and ≤ 0.01, respectively.
Figure 4A shows that IL1A is expressed under treatment with M-CSF, IFN-γ and LPS, as well as under treatment with M-CSF and LPS. There is a statistically significant relationship (p ≤ 0.01) between treatment with M-CSF and LPS and both treatment with M-CSF alone and M-CSF with IFN-γ. No expression was observed for IL1A under treatment with M-CSF and IFN- γ or M-CSF alone. Figure 4B shows the highest CSF3 expression in the presence of M-CSF with LPS, and a statistically significant relationship (p ≤ 0.00001) was found between treatment with M-CSF with LPS, M-CSF with IFN-γ, and M-CSF alone.
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Figure 4: Bar charts showing read counts observed for IL1A (A) and CSF3 (B) under various different conditions. Read counts were measured for genes treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by ** and **** which refer to a P value of ≤ 0.01 and ≤ 0.00001, respectively.
Figure 5 shows that CCL13 was expressed in the presence of M-CSF with IFN-γ and LPS, M-CSF with IFN-γ, and M-CSF with LPS, however, no statistically significance was found. No expression was found under treatment with M-CSF alone.
Figure 5: Bar chart showing read counts observed for CCL13 under various different conditions. Read counts were measured for CCL13 treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone.
CCL23 expression was highest under treatment of macrophages with M-CSF and LPS, as shown in Figure 6, however, some expression was also observed in the presence of M-CSF, IFN-γ, and LPS, as well as lower levels of expression for M-CSF with IFN-γ and M-CSF alone. Statistical significance at p ≤ 0.001 for macrophages treated with M-CSF and LPS was found between treatment with M-CSF and IFN-γ and treatment with M-CSF alone. Furthermore, p ≤ 0.05 was observed between treatment with M-CSF, IFN-γ and LPS and treatment with M-CSF and LPS.
Figure 6: Bar chart showing read counts observed for CCL23 under various different conditions. Read counts were measured for CCL23 treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by * and *** which refer to a P value of ≤ 0.05 and ≤ 0.001, respectively.
Figure 7 shows expression of IL-6 in the presence of M-CSF, IFN-γ and LPS as well as M-CSF and LPS, and a statistically significant relationship (p ≤ 0.05) was observed between several groups. No expression was observed under treatment with M-CSF and IFN-γ or M-CSF alone.
Figure 7: Bar chart showing read counts observed for IL-6 under various different conditions. Read counts were measured for IL-6 treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by * which refers to a P value of ≤ 0.05.
Figure 8 illustrates that IL10 is expressed under all four treatments, with the highest expression observed under treatment with M-CSF alone and this is statistically significant (p ≤ 0.01) to the expression of IL10 in the presence of M-CSF, IFN-γ and LPS. P ≤ 0.05 was also found between treatment with M-CSF, IFN-γ and LPS, and M-CSF and LPS.
Figure 8: Bar chart showing read counts observed for IL10 under various different conditions. Read counts were measured for IL10 treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by * and ** which refer to a P value of ≤ 0.05 and ≤ 0.01, respectively.
The expression of IL16 is shown in Figure 9, and the two highest levels of expression were observed under treatment with M-CSF and IFN-γ and M-CSF alone, between which there is a statistically significant relationship (p ≤ 0.01). Lower expression of IL16 was observed in the presence of M-CSF, IFN-γ and LPS, as well as M-CSF and LPS, and these are both statistically significant (p ≤ 0.05) to the expression under treatment with M-CSF and IFN-γ.
Figure 9: Bar chart showing read counts observed for IL16 under various different conditions. Read counts were measured for IL16 treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by * and ** which refer to a P value of ≤ 0.05 and ≤ 0.01, respectively.
Figure 10 illustrates gene expression of TGFB3 under all four treatments, with statistical significance (p ≤ 0.01) observed between treatment with M-CSF, IFN-γ and LPS (highest expression) and treatment with M-CSF and IFN-γ, treatment with M-CSF and LPS, and treatment with M-CSF alone.
Figure 10: Bar chart showing read counts observed for TGFB3 under various different conditions. Read counts were measured for TGFB3 treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by ** which refers to a P value of ≤ 0.01.
Figure 11 shows expression of TNFSF18 under treatment with M-CSF and LPS. A statistically significant relationship at p ≤ 0.01 was found between this treatment and treatment with M-CSF, IFN-γ and LPS. Furthermore, p ≤ 0.001 was observed between TNFSF18 expression under treatment with M-CSF and LPS and both treatments with M-CSF alone and M-CSF and IFN-γ.
Figure 11: Bar chart showing read counts observed for TNFSF18 under various different conditions. Read counts were measured for TNFSF18 treated with M-CSF with IFN-γ and LPS, M-CSF with IFN-γ only, M-CSF with LPS only, and M-CSF alone. Statistically significant relationships between read counts at different conditions are represented by ** and *** which refer to a P value of ≤ 0.01 and ≤ 0.001, respectively.
Chapter Four: Discussion
Both the LPS and IFN-γ signalling pathways play a significant role in host immune defence against pathogens and in chronic inflammatory disease pathogenesis (24). LPS, a well-known TLR4 agonist which signals through the NF-κB pathway, has been shown to significantly impair the survival of intracellular pathogens within macrophages (24). This effect has been attributed to the downstream induction of proinflammatory cytokines such as IL-6, IL-10, TNF-α, chemoattractants such as MIP-1β (also known as CCL4), as well as that of nitric oxide (NO) and reactive oxidative species (ROS) (25, 26). IFN-γ signalling via the Jak-STAT1 pathway forms part of the classical Th1-mediated bactericidal activities, and also leads to macrophage activation and the subsequent expression of inflammatory cytokines (such as TNF and IL-6), chemokines, and the release of antigen-presentation molecules (24), NO and ROS (27).
In macrophages, IFN-γ priming has been shown to potentiate activation and synergize with LPS to trigger proinflammatory and antimicrobial responses (24). Recent studies have reported that IFN-γ enhances macrophage activation by selectively abrogating LPS-induced inhibitory feedback signals and altering metabolic pathway components through the suppression of TLR4-mediated gene activation (24). Interestingly, IFN-γ was also demonstrated to attenuate the induction of some pro-inflammatory cytokines such as IL-1B, while having no effect on others including IL-6, IL-12p40 and TNF (28).
Nonetheless, current knowledge on how LPS-driven responses are influenced by IFN-γ, and the resultant impact of this effect on macrophage activation remain limited. Consequently, this current study used a transcriptomics approach with a view to further unpack the impact of the relationships between IFN-γ and LPS- driven responses in macrophages. A novel RNAseq data set was generated and used to determine differences in cytokine and chemokine induction between macrophages exposed to IFN-γ and those treated with both IFN-γ and LPS. Gene expression in macrophages was analysed, specifically comparing the following groups: M-CSF only, M-CSF with LPS, M-CSF with IFN-γ, and M-CSF with IFN-γ and LPS.
In this study, significant induction of IL1B was only observed in the presence of LPS, and IFN-γ did not seem to notably influence this effect in the LPS-treated samples nor trigger IL1B expressions in samples without LPS. Interestingly, this IFN-γ-driven downregulation of IL1B is consistent with that observed in previous studies, which showed that IFN-γ suppressed LPS-induced IL-1β transcription in murine macrophages, but had no effect on IL-6, IL-12p40 or TNF (28). Consequently, this transcriptional suppression attenuated the IL-1β effector functions and impaired Th17 cell differentiation and CXCL1 production (28).
A similar pattern of expression to that of IL1B was observed for CCL4 and CCL4L2 in the current study. In contrast, the presence of IFN-γ in LPS-treated samples reduced CCL20 expression. Interestingly, previous studies have reported that the IFN-γ + LPS combination reduced CCL4 expression in murine macrophages (29), and increased that of CCL20 (30, 31) in human monocytes. The latter is an example of the double-edged sword nature of macrophage activation, as CCL20 has been shown to contribute to the progression of various cancers, such as pancreatic cancer, colon cancer and breast cancer (reviewed in 32). Our results suggest that IFN-γ may have an inhibitory effect on this LPS-induced upregulation of CCL20.
For chemokines CXCL1, CXCL2 CXCL3, and CXCL5, the highest expression was observed in the M-CSF + LPS samples in the current study. This effect, which appears to be highly LPS-driven, was significantly attenuated by the presence of IFN-γ. Apart from activation of macrophages, the IFN/STAT pathway can induce macrophage polarization, thus influencing the chemokine repertoire and associated cells during infection (33). Consistent with previous reports (33), the data from the current study show that CXCL1 and CXCL2 are indeed not typically upregulated by IFN/STAT signalling. However, the other chemokines are reported to show a more situation-dependent pattern of upregulation or suppression (33). Although, the underlying mechanisms controlling these inductions or inhibitions are yet unclear.
TNFSF18 was also highly expressed in the presence of LPS relative to M-CSF and IFN-γ samples; and the addition of IFN-γ significantly reduced this LPS-induced effect. TNFSF18, a member of the tumour necrosis factor superfamily, is a known LPS-induced cytokine involved in the activation, differentiation and migration of immune cells (34). TNFSF18 expression has been previously shown to be upregulated upon activation in CD4+ and CD8+ T cells, and is thought to play a role in leukocyte adhesion and migration, as well as noncanonical NF-κB pathway activation and immunological self-tolerance (35).
Similarly, the LPS-only macrophages showed the highest TNFSF10 expression, which is consistent with previous reports. Das et al. (36) found that in BMDMs, the LPS only group expressed significantly higher levels of TNFSF10 than did the LPS and IFN-γ groups (36). Moreover, the authors noted functionally distinct spectra of expression. For instance, genes which were upregulated in the IFN-γ-primed LPS-treated groups were involved in biological adhesion, while those upregulated in the LPS only group had roles in intracellular signal transduction (36).
Moreover, TNF expression was observed in the LPS-treated groups, and appeared to be slightly elevated in the LPS + M-CSF+ IFN-γ samples. This elevation, while very modest in our case, is consistent with findings from previous studies which showed that in M-CSF-differentiated macrophages, priming with IFN-γ superinduced LPS-driven TNF expression (24). Kang et al (24) suggested that in order to promote activation, IFN-γ may synergize with LPS to activate inflammatory response through various mechanisms including metabolic reprogramming and remodelling at the translational level.
For CX3CL1, which is involved in the migration and adhesion of leukocytes (37), the highest expression was observed in M-CSF only samples, followed by those treated with LPS. The IFN-γ samples showed significantly less CX3CL1, suggesting that IFN-γ may downregulate the M-CSF and LPS-induced CX3CL1 expression. Interestingly, this is in contrast with results observed by Panek et al (37), who found that LPS+ IFN-γ upregulated the expression of CX3CR1 (the CX3CL1 receptor. The authors also described an IL-4-mediated downregulation of this response, and noted that the classical and alternative macrophage activation pathways antagonistically influence CX3CR1 expression (37).
Significantly higher IL7 expression was observed in cells treated with LPS and/or IFN-γ, with the highest levels observed for the LPS+ IFN-γ group. The M-CSF only samples showed very modest levels of IL7 which were significantly lower than those in the other three groups. This upregulation in the expression of the immunomodulatory IL7, which is linked to inflammation, has been previously shown to be a consequence of macrophage activation (36).
We also found that IL1A was induced in the presence of LPS. IFN-γ did not trigger IL1A expression nor have any impact on the observed LPS-driven upregulation. The LPS+ IFN-γ combination has been previously shown to increase the induction of IL1A among others in the same pathway (38). In contrast, increased expression of CSF3 was observed in the presence of LPS, and this effect was significantly reduced by IFN-γ. Both IL1A and CSF3 are downstream effectors of the MyD88/NF-κB signalling pathway (39). Previous studies have shown that some pathogens, such as mycobacteria, increase CSF3 expression via TLR-mediated pathways (39).
Analysis of monocyte chemoattractant expression revealed that CCL13, which is involved in the recruitment of inflammatory cell subtypes such as DCs and T cells (40) was expressed in the presence of both LPS and IFN-γ, albeit modestly in the IFN-γ only group. The combination of LPS and IFN-γ showed a moderate but not statistically significant additive effect relative to LPS alone. On the other hand, the expression of CCL23 was observed in the presence LPS, and the LPS-driven expression was significantly reduced by the addition of IFN-γ. CCL23 is known to selectively recruit resting T lymphocytes and monocytes, and inhibit the proliferation of myeloid progenitor cells (40). Interestingly, previous studies have demonstrated CCL23 expression by monocytes following stimulation with IL-1β and IL-4, and by human neutrophils CCL23 upon stimulation with TLR7/8 ligand R848 and LPS (40).
We found that the proinflammatory IL6 was only upregulated in the presence of LPS. While there was no expression of IL6 in the IFN-γ only samples in this study, the presence of IFN-γ neither potentiated nor attenuated the LPS-induced IL6 expression. This is in contrast with previous studies which reported that in M-CSF-differentiated macrophages, IFN-γ and LPS acted synergistically to driven induce the expression of IL6, along with other canonical inflammatory genes such as IL23A, and CXCL9 (24).
On the other hand, the highest expression of the anti-inflammatory IL10, was observed in the M-CSF only samples, followed by the LPS- and the IFN-γ only groups, respectively. The M-CSF + LPS+ IFN-γ groups showed the lowest expression levels, suggesting the induction of inhibitory mechanisms in this combination. Similar results were reported by Kang et al (24) who found that in M-CSF-differentiated macrophages, priming with IFN-γ priming suppressed LPS-induced IL10 expression. On this basis, the authors suggested that IFN-γ may disrupt the IL-10-mediated LPS-induced feedback-loop which negatively regulates inflammation, partially through IL10 suppression (24).
In this study, the expression of IL16 was highest in macrophages treated with M-CSF alone, followed by the IFN-γ, and LPS-treated groups, respectively. IL16 is an immunomodulatory chemokine which is known to signal through macrophages, CD4 + T cells, monocytes, and dendritic cells (41). Previous reports have shown higher IL16 expression in M1 than in M2 macrophages, and proposed that IL16 may have a role in macrophage polarization through regulating the expression of IL-1α, IL-6, and IL-10 (41).
Remarkably, TGFB3 expression was observed in all conditions tested in this study, with the highest levels observed in the M-CSF+, LPS+ IFN-γ groups suggesting a synergistic effect for the combination. TGFB3 belongs to the TGF-β family, and plays a role in a number of functions including immune responses and tissue homeostasis (reviewed in 42). Fittingly, LPS and IFN-γ have been previously shown to synergistically activate macrophages to inhibit tumour cell growth (43).
To summarise the most notable findings of the current study, the LPS + IFN-γ combination group showed significant upregulation of TGFB3, which plays a role in immune response and tissue homeostasis. This combination resulted in the downregulation of several genes, most notably the anti-inflammatory IL10, CCL23 and TNFSF18, both of which are known to be LPS-responsive, as well as the NF-κB effector CSF3. In the absence of LPS, the IFN-γ-treated macrophages showed significant upregulation of IL-7, which plays a role in the proliferation and differentiation of B and T cells, and TNFSF10 (a tumor necrosis factor (TNF) family member). The same treatment also showed significant suppression of CX3CL1 and IL10. In the absence of IFN-γ, the LPS-induced cytokines and chemokine gene repertoire included the proinflammatory cytokines IL1B, IL6, and TNF. LPS signalling also significantly upregulated TNFSF10 (a TNF ligand superfamily member), as well as TNFSF18, IL7 and CCL23. LPS significantly attenuated the expression of IL16, an immunomodulator which is highly expressed in M1 macrophages. In contrast, the LPS only treatment showed no notable impact on CX3CL1 and IL-10 induction, which were shown to be suppressed by IFN-γ in the current study.
Study limitations and proposed future studies
The limitations of the current study included a small sample size, donor diversity (or the lack thereof), quality of sequencing data due to technical hurdles in sample preparation, as well as challenges in accurate sequence annotation and interpretation of data
While RNA-Seq permits the identification and quantitation of RNA molecules in biological samples, the integration of transcriptomic and epigenomic analysis may provide further insight into these gene regulatory mechanisms involving LPS and IFN signalling, as was shown by Kang et al (24). It may also be interesting to explore a time-course experiment to determine the interplay between LPS and IFN at different time points over a 24 hour period. Furthermore, mechanistic studies such as forward and reverse genetic screening using CRISPR knockout and/or siRNA silencing of specific genes may further elucidate these relationships, and highlight potential targets for remedying insufficient immunomodulation or excess inflammation.
Chapter Five: Conclusions
It is widely accepted that both IFN-γ and LPS regulate the activation of proinflammatory and antimicrobial macrophage phenotypes, through the induction of NF-κB target genes. This study explored how components of LPS-driven macrophage responses are influenced by the presence of IFN-γ. We found that LPS-treated macrophages resulted in the expression of many of the cytokines and chemokines typically induced in classical activation. Importantly, our findings provide further evidence that IFN-γ has both inducive/synergistic and suppressive effects on LPS-driven macrophage responses, thus supporting previous reports. For the most part, IFN-γ displayed a more suppressive than inducive effect on LPS-mediated signalling in macrophages in the conditions tested in this study.
Notably, this study revealed that M-CSF-differentiated macrophages treated with either LPS or IFN-γ showed an upregulation of TNFSF10, IL7, and CCL13 expression, and the suppression of IL16. IFN-γ also downregulated IL10 and CXC3CL1, while LPS showed no significant modulatory effect on these. These data provide additional insight into how IFN-γ might selectively inhibit LPS/TLR4-induced transcription in macrophages.
Indeed, transcriptomics analysis served as an important tool in further exploring the role of IFN-γ and LPS in macrophage activation and the key relationships thereof. Further transcriptomic and epigenomic analysis, and in mechanistic studies are needed to unpack these intricate relationships and their beneficial or detrimental effects on antimicrobial and inflammatory immune responses.
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