Toll-Like Receptor Dysregulation in The Hospitalized COVID-19 Patients

Abstract

Background:

A severe pro-inflammatory feedback is the main reason for novel coronavirus (COVID-19)-related complications. Here we intended to investigate the potential involvement of toll-like receptors (TLRs)3, TLR7, TLR8, and TLR9 in the etiopathogenesis of COVID-19.

Materials and Methods:

mRNA expression of TLR3, TLR7, TLR8, and TLR9 were evaluated in blood samples from 30 COVID-19-infected patients and 30 healthy controls by means of real-time polymerase chain reaction (PCR) approach.

Results:

The mRNA expressions of TLR3 (P = 0.038) and TLR9 (P = 0.009) significantly increased in patients with COVID-19 compared with healthy controls. Additionally, the mRNA expression of TLR3 was significantly higher in the male than in female COVID-19 patients (P = 0.020). Experiments indicated that the mRNA expression of TLRs was not significantly different between symptomatic and non-symptomatic COVID-19 subjects. Furthermore, no correlation was detected between mRNA expression of TLRs and patient’s clinicopathological data.

Conclusion:

It seems that TLR3 and TLR9 are involved during COVID-19 infection and might take part in the inflammatory outcome of the patients.

INTRODUCTION

The outbreak of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) has caused major health and economic problem all over the world.[1] Even though vaccination, accompanied by potential complementary therapeutics,[2,3] has been successful in controlling the pandemic, the waves often cause health problems.[4] The disease associates with a wide range of symptoms, acute respiratory distress syndrome (ARDS), multi-organ failure, and even death in severe cases.[5,6] SARS-CoV-2 infection not only triggers the antiviral innate and adaptive immune responses but also is able to trigger abnormal inflammatory responses, probably cytokine storm in intense activation of the immune system.[7,8,9,10]

A large number of investigations have revealed that SARS-CoV-2 infection disturbs the normal immune responses, resulting in abnormal inflammatory responses in COVID-19 cases with critical forms of the disease.[11,12,13] Pathogen recognition receptors (PRRs), which belong to the innate Immune system, are sensors of the pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs).[14] Among the PRRs, toll-like receptors (TLRs) have been shown to be involved in the initiation of appropriate immune responses against viruses.[15] Different TLR molecules play a role in sensing diverse PAMPs found in the microorganisms. TLR3 senses double-strand RNA (dsRNA), whereas TLR7 and TLR8 sense single-strand RNA (ssRNA) and TLR9 is the receptor for viral DNA.[14] However, some evidence show that TLR9 can be stimulated by viral RNA.[16] Due to the fact that COVID-19 has ssRNA as its genome and generates non-genomic RNA during replication, it can be detected by the TLRs.[17] However, the roles played by TLR3, TLR7, TLR8, and TLR9 in hospitalized patients who are suffering from COVID-19 are yet to be clarified.

Here we intended to assess the levels of mRNA expression of TLR3, TLR7, TLR8, and TLR9 in the blood leukocytes from hospitalized COVID-19-infected patients. Additionally, the association between TLR expression and lung involvement was assessed.

MATERIALS AND METHODS

Subjects

In this case-control investigation, 30 individuals with COVID-19 infection and 30 healthy subjects matched for age and gender were recruited. The COVID-19 cases were chosen among the hospitalized individuals in the Ali-Ibn Abi-Talib hospital, Rafsanjan, Iran. The detection of the COVID-19 genome in the subjects was accomplished through a real-time PCR test for the SARS-CoV2 genome. To distinguish between lung symptomatic and non-symptomatic COVID-19 cases, a computerized tomography (CT) scan was used. As the exclusion criteria, cases with alcoholism, smoking, opium consumption, autoimmune disorders, allergic disorders, other viral and bacterial infections, and those receiving immune suppressor medications were ruled out from the case group. The baseline data and clinical specifications of the study subjects are summarized in Table 1. The sampling was performed during hospitalization and before starting the treatment. To perform experiments, 5 ml of the peripheral blood samples were collected from each subject using venipuncture. The participants signed the informed consent form prior to entering into the project.

Table 1.

Baseline data and clinical specification of the study subjects

Item		COVID-19 patients (n=15)		Healthy controls (n=15)		P
Age; years (mean±SD)		62.40±16.68		60.7±17.24		>0.05
Gender; Male/Female		12 (40%)/18 (60%)		15 (50%)/15 (50%)		>0.05
WBC count (mean±SD)		5431.46±2633.69		-		-
Hypertension; Yes		5 (16.6%)/25 (83.4%)		-		-
T2D		4 (13.3%)/26 (86.7%)		-		-
BO		92.25±3.60		-		-
BUN		30.12±11.7		-		-
Creatinine		1.13±0.11		-		-

COVID-19; Coronavirus disease 2019, BO; Blood oxygen, BUN; Blood urea nitrogen, Cr; Creatinine, WBC; White blood cell, T2D; Type 2 diabetes

RNA extraction and cDNA synthesis

Total RNA was extracted from the whole blood leukocytes via a commercial kit (Karmania Pars Gene, Kerman, Iran), according to the manufacturer’s guidelines. The quality and purity of the RNA samples were determined by a NanoDrop spectrophotometer (ND-2000, Thermo Fisher Scientific, USA). The complementary DNA (cDNA) was synthesized from total RNA using a commercial kit (Karmania Pars Gene, Kerman, Iran), according to the company’s guidelines.

qPCR determination of TLR mRNA

Relative expressions of the TLRs were explored using a real-time PCR SYBR Green approach (Karmania Pars gene, Kerman, Iran). Exerting Primer Express 3.0.1 Software (ThermoFisher Scientific, USA), primers were designed for the quantitative expression analysis of TLRs. The specificity of all primer sets was assessed via the Basic Local Alignment Search Tool (BLAST) developed by the National Center for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov/tools/primer-blast/). Primers were synthesized via the custom oligonucleotide synthesis service Metabion (Martinsried, Germany). A list of primers is found in Table 2. Accordingly, 3 µL from cDNA, 5 µL master mix and 2 µL activator were added to the PCR microtubes. After mixing, relative expressions of the TLRs were evaluated in a Rotorgene thermal cycler (Rotorgene, Malaysia) instrument. To amplify cDNA, the following thermocycling program was designed for the instrument: 5 min at 95ºC followed by 45 cycles of 95ºC for 10 seconds and 60ºC for 30 seconds. Glyceraldehyde-3-phosphate dehydrogenase was measured in parallel with the TLRs as a housekeeping gene and the values were normalized using the 2^-∆∆Ct formula.

Table 2.

Primers used to determine the mRNA expression levels of TLRs by real-time PCR

Gene		Forward primer (5′→3′)		Reverse primer (5′→3′)
TLR3		GAAGATTTCTTGCCACCCTAC		GAACACAATGTGCAGACTCTC
TLR7		CTGGACAATGCCACATAC		CTAATGTAGGTGATCCTG
TLR8		CAGAACTGCAGGTGCTGG		GTTCTCTAGAGATGCTAG
TLR9		CTATTGTTAAAAGCTTCCATTTTGT		ACCTGAAGCTCAGCGATGTAGTTC
GAPDH		AGGTCGGTGTGAACGGATTTG		TGTAGACCATGTAGTTGAGGTCA

TLR; Toll-like receptor, GAPDH; Glyceraldehyde-3-Phosphate Dehydrogenase

Statistical analysis

Data analysis was conducted using SPSS software (version 20, IBM Corporation, Armonk, NY, USA). Normal distribution of data was explored by Kolmogorov–Smirnov test. As for the normal distribution of the scale data, the parametric tests were applied to compare means. Accordingly, the differences between COVID-19-infected patients and healthy controls, male and female, and the patients with and without lung symptoms were explored using an independent student t-test. Correlations were explored in the patient’s group using Pearson’s correlation test. The significance level was considered at 0.05.

RESULTS

Expression of TLRs in patients and controls

The experiments showed that the relative amounts of TLR3 (P = 0.038) and TLR9 (P = 0.009) mRNA expression significantly increased in patients with COVID-19 when compared to healthy controls. As illustrated in Figure 1, the relative expression of TLR3 was 5.21 ± 1.92 in patients with COVID-19 and 1.00 ± 0.18 in the healthy controls. The relative expression of TLR9 was 3.63 ± 0.87 in patients with COVID-19 and 1.00 ± 0.10 in the control group.

Figure 1.

Relative expression of TLR3, TLR7, TLR8, and TLR9 in patients suffering from COVID-19 in comparison to healthy controls. The figure illustrates that relative expression of TLR3 and TLR9 significantly increased in patients suffering from COVID-19 when compared to healthy controls (*P < 0.5, **P < 0.01, ns means non-significant)

The relative expression of TLR7 was 1.31 ± 0.37 and 1.00 ± 0.11 in the cases and controls, respectively, resulting in a non-significant difference statistically (P = 0.436). Figure 1 shows that the relative expression of TLR8 was not different significantly between the groups (P = 0.235).

Expression of TLRs between groups

According to Figure 2, the relative mRNA transcription of TLR3 was significantly higher in the male (8.67 ± 3.96) than female (1.54 ± 0.60) COVID-19 patients (P = 0.020). The relative expression of TLR7 (P = 0.624), TLR8 (P = 0.888), and TLR9 (P = 0.781) was not significantly different between male and female patients.

Figure 2.

Bar graph shows the mRNA expression of TLRs in male and female COVID-19 subjects (*P < 0.05, ns means non-significant)

Experiments indicated that the relative expression of TLR3 was 8.26 ± 5.57 and 4.38 ± 1.97 in patients with symptomatic and non-symptomatic COVID-19 subjects, respectively, which was not different significantly (P = 0.419). The differences of TLR7 (P = 0.235), TLR8 (P = 0.235), and TLR9 (P = 0.235) were not also significant statistically between symptomatic and non-symptomatic COVID-19 patients [Figure 3].

Figure 3.

Relative expression of TLR3, TLR7, TLR8, and TLR9 in patients with symptomatic versus non-symptomatic CT scan (lung involvement). The figure illustrates that the differences regarding relative expression of TLR3, TLR7, TLR8, and TLR9 were not significant (ns means non-significant)

Correlation analysis

The results revealed that there were no significant correlations among TLR3, 7, 8, and 9 with BO, BUN, Cr, and WBC counts in patients with COVID-19. There were no significant correlations between age and TLR3 (r = -0.346, P = 0.190), TLR7 (r = 0.178, P = 0.561), TLR8 (r = 0.011, P = 0.969), and TLR9 (r = -0.042, P = 0.877; Table 3).

Table 3.

Correlation between relative expressions of TLR3, TLR7, TLR8, and TLR9 with blood oxygen, blood urea nitrogen, creatinine, white blood cell counts and age

Gene		Correlation coefficient		BO		BUN		Cr		WBC		Age
TLR3		r*		-0.454		0.362		-0.181		-0.053		-0.346
		P		0.139		0.204		0.518		0.830		0.190
TLR7		r		-0.059		0.044		-0.183		-0.262		0.178
		P		0.880		0.891		0.568		0.346		0.561
TLR8		r		0.440		0.464		-0.112		-0.023		0.011
		P		0.152		0.094		0.691		0.925		0.969
TLR9		r		0.395		-0.370		-0.075		-0.054		-0.042
		P		0.229		0.214		0.799		0.828		0.877

TLR; Toll-like receptor, BO; Blood oxygen, BUN; Blood urea nitrogen, Cr; Creatinine, WBC; White blood cell. *r shows Pearson’s correlation coefficient

DISCUSSION

COVID-19 genome consists of RNA and generates non-coding RNA in the infected cells to replicate.[18] Therefore, the virus genome is potentially recognized by TLR3, TLR7, and TLR8. Additionally, it has been documented that although TLR9 itself is a well-known DNA recognizer, it is a relative RNA-sensing TLR as well.[19] Our previous investigation also indicated that TLR3, TLR7, TLR8, and TLR9 were upregulated in the epithelial cells of COVID-19 subjects with clinical presentations needing to be hospitalized.[20] Our results from ongoing research demonstrated that mRNA expressions of TLR3 or TLR9 significantly increased in the blood samples from patients suffering from COVID-19. Due to the fact that TLR3 recognizes viral dsRNA and both TLR7 and TLR8 are the sensors for ss-RNA, it may be hypothesized that the virus-related RNA, containing genomic and subgenomic RNA, may be recognized as dsRNA by TLR3. However, based on the fact that COVID-19 contains ssRNA as the genome, it may be hypothesized that other cytoplasmic sensors, which recognize viral ssRNA, might be potential receptors responsible for the detection of the virus genome.

Increased mRNA expression of TLR9 shows its possible involvement in the pathogenesis of COVID-19. It is interesting data regarding innate immune responses to COVID-19 because the virus does not have cDNA during replication. Thus, it appears that TLR9 recognizes some COVID-19-related RNA in the infected patients. The roles played by TLRs against COVID-19 have been discussed by Safaei and colleagues.[21] The study proposed that TLR antagonists can be considered as a molecular therapy against COVID-19.[21] Butchi et al.[22] showed that MyD88 was critically involved in the induction of early innate immune responses during coronavirus-associated encephalomyelitis. Due to the fact that TLR9 uses the MyD88 pathway,[23] it is suggested that using TLR9 antagonist might be useful to reduce adverse inflammatory responses in hospitalized COVID-19 patients. However, the results need to be considered in a precise manner, as our experiments indicated that the patients with involvement of the lung had no upregulated levels of TLR3, TLR7, TLR8, and TLR9.

Additionally, male subjects had increased mRNA expression of TLR3 compared to the female patients. Meta-analysis studies revealed that male patients had higher inflammatory responses and higher rates of hospitalization than females.[24] Therefore, based on our results, it may be proposed that male patients may show more inflammatory responses in a TLR3-dependent manner. As TLR3 uses TRIF pathway in the downstream signaling,[25] it appears that the pathway can be more active in males than in females. Conti and colleagues also reported that female COVID-19 patients had higher expression of TLR7 than male subjects.[26] Thus, it may be suggested that gender may be considered as a risk factor for the pathogenesis of COVID-19.

Although previous investigations served age as a risk factor for mortality of COVID-19,[27] the current study revealed that age had no correlations with levels of mRNA expression of TLR3, TLR7, TLR8, and TLR9. Thus, it seems that age-related mortality is independent of TLR3, TLR7, TLR8, and TLR9 mRNA expression.

The current study is not bereft of limitations and caveats. First, we did not analyze all TLRs. Second, the sample size is not satisfactory to obtain conclusive results. Third, we did not evaluate the levels of cytokines that could have been adding further insight into TLR’ role in modulating inflammation in COVID-19 subjects.

In conclusion, this study indicated that TLR3 and TLR9 are much more critical than TLR7 and TLR8 during COVID-19 infection and may take part in the inflammation-associated etiopathogenesis of SARS-CoV-2. However, since immune cells in the circulation are not target cells for SARS-CoV-2, the increased expression of TLR3 and TLR9 may be due to the involvement of other pathways. Hence, the results should be interpreted cautiously.

Ethics approval and consent to participate

This study was approved by the ethics committee of Rafsanjan University of Medical Sciences (IR.RUMS.REC.1399.014) and all individuals voluntarily signed a written informed consent form. All methods were performed in accordance with the relevant guidelines and regulations by Rafsanjan University of Medical Sciences.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

This article was supported by a grant from Deputy of Research, Rafsanjan University of Medical Sciences.