Authors:
Alessandra Melo1, Nº Mec: 111616, email: [email protected]; Alícia Freitas1, Nº Mec: 112869, email: [email protected]; Cláudia Bié1 , Nº Mec: 111583, email: [email protected]; Laura Duarte1, Nº Mec: 113130, email: [email protected]
1Bachelor’s degree in Biomedical Sciences, University of Aveiro
Abstract
With the sole purpose of evaluating the expression of pro-inflammatory cytokineencoding genes in response to LPS and Eritoran tetrasodium (E5564) for later analysis of the drug’s efficiency as an anti-inflammatory agent, we studied the role of macrophages RAW 264.7 derived from mice in innate immunity using the qPCR technique, focusing specifically on inflammation. Following the exposure of these cells’ receptors to PAMPs, a process of recognition takes place, unleashing a signalization cascade which will later cause a production of transcription factors, these have a purpose of regulating the gene expression of the markers that we intend to study, specifically: TNF-α, Il-6, IL-1β. In addition, two reference genes were used: GAPDH and β-actin. Their expression doesn’t change significantly when exposed to neither LPS nor E5564. It was observed that LPS has a greater influence in the proinflammatory pathways of the gene expression compared to E5564, which will present antiinflammatory effects.
Key Words
- ALRs - AIM2-like receptors
- CLRs – C-type lectin receptors
- cRNA – Complementary DNA
- Ct – Cycle of threshold
- DAMPs – Damage-associated molecular
- patterns
- DNA - Deoxyribonucleic acid
- GAPDH - Glyceraldehyde 3-Phosphate
- Dehydrogenase
- IKK - IκB kinase
- IKKi - IκB kinase-i
- IRAK-1 - IL-1 receptor-associated kinase-1
- IRAK-4 – IL-1 receptor-associated kinase4
- LPS - Lipopolysaccharide
- MAPK - mitogen-activated protein kinase
- Master Mix – Reaction Buffer and
- Transcriptase Reverse
- MyD88 - myeloid differentiation primary
- response gene 88
- NF-κB – nuclear factor kappa B
- NLRs – NOD-like receptors
- PAMPs - Pathogen-associated molecular
- patterns
- PRRs – Pattern recognition receptor
- qPCR – Quantitative polymerase chain
- reaction
- RLRs – RIG-l-like receptors
- RNA – Ribonucleic acid
- TAK1 - transforming growth factor-βactivated kinase 1
- TANK – TRAF family member-associated
Introduction
The immune response can be categorized into innate and adaptive components. The adaptive response is highly specific and relies on the presence of specific antigen receptors on T and B lymphocytes, as well as on prior exposure to antigens. This previous exposure allows for a quicker and more effective response due to the immune system's "memory." In contrast the innate immunity encompasses various molecular and cellular processes that serve as the body's initial defence against external threats. It includes physical and chemical barriers, pattern recognition receptors (PRRs) that identify common pathogenic patterns, macrophage cells, and the complement system. The innate immunity aims for the rapid recognition and the elimination of pathogens, but it lacks specificity and cannot discern specific antigens (1).
The macrophages are immune system cells derived from circulating monocytes, that play critical roles in the inflammation. They have three main functions: antigen presentation, phagocytosis, and modulation of cellular responses through the production of cytokines and growth factors (4). Macrophages exhibit plasticity and can assume different states, known as M1 (pro-inflammatory) and M2 (anti-inflammatory), depending on the signals in their microenvironment. The activation of macrophages, either towards the M1 or M2 profile, depends on specific signalling molecules present in their surrounding environment (2). M1 macrophages are stimulated by molecules like LPS and IFN-γ, leading to the production of pro-inflammatory cytokines, while M2 macrophages respond to signals such as IL-4 and IL-13, which result in the production of anti-inflammatory cytokines.
The pattern recognition receptors (PRRs) are proteins encoded in the genomic DNA of immune system cells. They are responsible for recognizing pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs). Toll-like receptors (TLRs) are a subset of PRRs. These receptors are located on the cell's surface, in internal membrane compartments, and within the cytosol. When activated, they initiate signalling pathways and the production of pro-inflammatory cytokines (1) (3).
An example of a PAMP is LPS (lipopolysaccharide), a molecule found in the outer membrane of Gram-negative bacteria (1) (4). The LPS stimulates the TLR4, CD14 (aglycosylphosphatidylinositol-anchored protein), and MD-2 (a soluble protein), leading to the release of pro-inflammatory cytokines such as TNF-α, IL-1β, and IL-6. The LPS associates with CD14 via LBP (LPS binding protein), forming a complex with the TLR4/MD-2 receptor complex. This activates the TLR4, leading to downstream signalling pathways, including both MyD88-dependent and independent pathways (5).
In the MyD88-dependent pathway, MyD88 triggers the activation of IRAK-4, which subsequently recruits, activates, and degrades IRAK-1. This activation leads to TRAF-6, an Adaptor protein forming a complex with UBC13 and UEV1A, which activates TAK1. TAK1 then initiates the IKK and MAPK pathways. The IKK pathway involves a complex of IKKa, IKKb, and IKKgamma, leading to the phosphorylation of IκB proteins, causing their degradation and the translocation of the transcription factor NF-κB. This factor controls the expression of pro-inflammatory cytokines. The MAPK pathway activates the transcription factor AP-1, also involved in regulating pro-inflammatory cytokine expression (5). The MyD88-independent pathway depends on TRIF, which activates RIP1 and TRAF3.
The RIP1 activation leads to the activation of the MAPK and IKK pathways, resulting in the translocation of AP-1 and NF-kB. TRAF3 activation recruits TANK, TBK1, and IKKi, necessary for the translocation of IRF3 and the activation of target gene transcription (5).
In this study, a gene expression analysis was conducted for genes IL-6, IL-1β, TNF-α, beta-actin, and GADPH. These genes have different cellular targets and biological effects, but IL-6, IL-1β, and TNF-α are involved in inflammatory processes. β-actin and GADPH serve as housekeeping genes for normalizing target gene expression, given their stable expression levels (1).
This study also evaluated the drug E5564, or Eritoran Tetrasodium, a synthetic analogue of LPS, which possesses a strong immunomodulatory potential. The E5564 interacts with a receptor complex, including TLR4, CD14, and MD-2 (LY96), blocking binding sites and inhibiting their activation. This action down-regulates genes responsible for pro-inflammatory cytokine production, thereby dampening the inflammatory response. The results from the E5564 conditions align with existing literature, supporting its effectiveness in inhibiting LPS induced pro-inflammatory cytokine production (7).
In summary, this study's objective was to assess the expression of pro-inflammatory cytokine-encoding genes in response to LPS and E5564, aiming to evaluate the drug's effectiveness as an anti-inflammatory agent.
Results
RNA concentration
The RNA concentrations in the samples and the absorbance ratios were obtained using Nanodrop (Table 1). The control and LPS + 1nM E5564 conditions present similar values (674.058 ng/µL and 679.852 ng/µL, respectively). LPS (without E5564) and LPS + 100 nM E5564 conditions also present similarities (160.027 ng/µL and 185.111 ng/µL, respectively). LPS + 10 nM E5564 condition is an outlier, with a value of 893.228 ng/µL.
Analysis of gene expression
Analyses of IL-1β, IL-6 and TNF-α gene expression were carried out after comparing the data obtained using the Delta-Delta Ct method during the qPCR process. Graph 1 shows the variation in expression of the genes of interest compared with the housekeeping gene b-actin. A relatively continuous decrease in gene expression was observed after exposure to E5564, varying according to the increase in drug concentration. Graph two shows the expression of genes using GAPDH as the housekeeping gene.
Discussion
I – RNA concentration and purity
RNA concentration in LPS + 10nM E5564 condition is an outlier, due to being significantly higher than the other values. Is worth mentioning that LPS + 100 nM presents a significantly lower value compared with other E5564 conditions. It shouldn't exist such a gap between conditions, so, it's worth considering mistakes during sample preparation.
The A260/280 ratio is used to determine the purity of RNA concerning the presence of proteins. If this number is too low, it means that the sample is considered contaminated with proteins. An ideal value for this ratio is between 1.8 and 2.1, meaning that the sample is pure enough to be worked with.
The A260/230 ratio is used to determine the purity of RNA concerning the presence of organic solvents in the sample. The standard value for pure nucleic acids falls between 1.6 to 2.0. If this value is too low, the sample is considered contaminated by organic solvents that absorb radiation at a 230 nm wavelength.
Control, LPS + 1nM E5564, and LPS + 10nM E5564 conditions present values slightly above the standard interval, leading us to conclude that these samples have the highest purity grade. LPS (without E5564) and LPS + 100nM E5564 condition present values for both ratios between the standard values. As ratios’ variations between conditions and between conditions and standard values are not significant, we can consider that our sample was not contaminated with proteins or organic solvents.
II – Analysis of gene expression and E5564 effect
Ct values are indirectly proportional to gene expression. Lower Ct values correspond to high levels of gene expression and high Ct values correspond to low levels of gene expression. Knowing this, we can say that the results we obtained (presented in Table x, appendices) are what we predicted, based on literature.
H20, PCR grade condition presents no gene expression (“undetermined”), except for C11 and H11 wells. However, the Ct values of these wells are relatively higher than the Ct values of the genes in the other conditions of the study. The interpretation suggests that the Ct values in C11 and H11 may indicate the detection of fluorescence but not necessarily real gene expression. For this reason, those values are overlooked and considered as just interference or contamination during PCR-plate preparation, rather than relevant expression of IL-6 and GAPDH.
Housekeeping genes GAPDH And β-actin presented stable Ct values, that had minimal fluctuation between conditions, showing that LPS and E5564 presence just influences some pathways and not the whole gene expression regulation.
Across all conditions, TNF-α presented the lowest Ct values, showing that this gene has higher expression comparing to IL-6 and IL-1β. IL-1β gene has the lowest expression amongst pro-inflammatory genes in study.
The highest Ct value for genes IL-6, IL-1β and TNF-α corresponded to the control condition, in which gene expression is at its basal level, hence minimal. The lowest Ct value For these genes happened in LPS condition (without E5564), indicating higher gene expression of this pro-inflammatory cytokine genes. This is supported by literature, as LPS is known for stimulating MyD88-dependent and MyD88-independent pathways that lead to the stimulation of gene expression for pro-inflammatory cytokines by NF-kB, AP-1 and IRF3.
E5564 conditions, from 1nM to 100nM, show gradually higher Ct values across IL-6, IL-1β and TNF-α genes, indicating decreased gene expression, although this values never reach control Ct numbers. This indicates that E5564 has anti-inflammatory effects, which is supported by literature, where E5564 is presented as an inhibitor for TLR4/MD-2/CD14 receptor complex activation, by blocking LPS binding sites, down-regulating genes responsible for pro-inflammatory cytokine production (6). The E5564 effect increased with the concentration dosage. By comparing 1nM condition with 100nM, across all inflammatory genes, it is possible to observe higher gene expression with lower E5564 concentration. We can conclude that, for all genes, E5564 concentration of 100nM was the most effective for lowering gene expression.
Methods
I - Sample preparation and Acquisition
The sample consists of RAW 264.7 cells, cultured in DMEM with a supplement of 10% inactivated bovine serum, 100 U/mL of penicillin, and 10 µg/ml of streptomycin at 37ºC in a humidified atmosphere composed of 95% air and 5% CO2. RAW 264.7 cells were allowed to stabilize on the plate for 12 hours. The cells were kept in culture medium (control), treated with LPS (100ng/µl) for 6 hours, or pre-incubated for 1 hour with E564 (Eritoran) at different concentrations (1, 10, and 100 nM) and then treated with LPS for 6 hours.
II – RNA extraction
The RNA extraction was carried out using the GRS Total RNA Kit. The R1 buffer was mixed with β-mercaptoethanol. In addition, an optional treatment with DNAse was carried out to remove unwanted DNA residues from the sample.
III – RNA quantification and assessment of the degree of contamination
In order to quantify the RNA, it was used the NanoDrop Microvolume Spectrophotometers and Fluorometer techniques. For control purposes, it was used a H2O DNAse RNAse free solvent. This sample was read, and its value was registered. After this process, each sample with RNA was read and each concentration result was obtained, and the 260/230 and 260/280 ratios were recorded.
IV – cDNA Synthesis
To perform the reverse transcription of the RNA into cDNA, the NZY-first Strand cDNA Synthesis Kit was used. The components, except for the NZYRT Enzyme Mix (containing reverse transcriptase), were centrifuged together. To each Eppendorf tube, a volume of RNAse-free water was added so that the sum of the volumes equals 8 μL, and these values were calculated based on the RNA sample quantification. By using the NZYRT Enzyme Mix, a Master Mix was prepared along with the NZYRT 2x Master Mix (the ratio being 1 part NZYRT Enzyme Mix to 5 parts NZYRT 2x Master Mix), taking care to prepare an additional 15% volume of the Master Mix to compensate pipetting errors.
V – Analysing macrophage activation markers by qPCR
In order to assess macrophage activation by qPCR, it is necessary to proceed with the preparation of solutions with suitable primers for each of the genes under study. Two types of primers (Forward (F) and Reverse (R)) were prepared for the IL-1β, IL-6, TNF-α, β-actin, and GAPDH genes. Each of the primers (10 in total) should have a final concentration of 10 µM. A primer mix was prepared for each gene under study using the SYBR Green Supermix reagent, H2O, PCR grade, and the previously prepared F and R primers.
The cDNA was diluted to 5x. The same amount of cDNA corresponding to each condition was pipetted into the bottom of the PCR plate wells, according to the planned layout, and the mix for each gene was added to each well, according to the planned layout. The final reaction volume in each well should be 15 µL.
The 96-well PCR plate was sealed with sealing tape and centrifuged in a plate centrifuge. Finally, the reaction was run on a qPCR apparatus, according to 3 stages: 50ºC for 2min, 95ºC for 20 seconds, and 95ºC for 15 seconds followed by 60ºC for 30 seconds, completing one cycle. A total of 40 cycles were carried out.
References
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Appendices
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