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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 11  |  Issue : 3  |  Page : 293-298

Messenger RNA expression of toll-like receptors (TLR2, TLR4, and TLR9) in HIV-1 infected patients with and without tuberculosis co-infection


1 Department of Allied Health Sciences, School of Allied Health Sciences, Sharda University, Greater Noida, Uttar Pradesh; Department of Medicine, All India Institute of Medical Sciences, New Delhi, India
2 Department of Medicine, All India Institute of Medical Sciences, New Delhi, India

Date of Submission20-May-2022
Date of Decision21-Jul-2022
Date of Acceptance10-Aug-2022
Date of Web Publication12-Sep-2022

Correspondence Address:
Gaurav Kaushik
School of Allied Health Sciences, Sharda University, Greater Noida, Uttar Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijmy.ijmy_108_22

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  Abstract 


Background: Gene expression levels of TLRs (TLR2, TLR4 and TLR9) are directly involved in the virus recognition and initiation of innate immune responses, therefore, the effect of HIV infection on TLRs gene expression was investigated in functional context through mRNA levels estimations of selected TLRs. Methods: In the present study mRNA gene expression of TLR2, TLR4 and TLR9 has been investigated in HIV+ and HIV+TB patients and compared with healthy subjects. Result: The increase expression of TLR2, TLR4 and TLR9 (mRNA level) relative to the internal gene GAPDH was observed in HIV+ and HIV+TB patients as compared to healthy subjects. Similarly, increase in TLRs mRNA expression was observed in HIV+TB patients as compared to HIV+ patients. Conclusion: A modest increase in expression of TLRs in HIV+ patients with and without TB co-infection suggest a potential role for these TLRs in HIV-1 immunopathogenesis.

Keywords: HIV, messenger RNA, toll-like receptor, tuberculosis


How to cite this article:
Kaushik G, Vashishtha R. Messenger RNA expression of toll-like receptors (TLR2, TLR4, and TLR9) in HIV-1 infected patients with and without tuberculosis co-infection. Int J Mycobacteriol 2022;11:293-8

How to cite this URL:
Kaushik G, Vashishtha R. Messenger RNA expression of toll-like receptors (TLR2, TLR4, and TLR9) in HIV-1 infected patients with and without tuberculosis co-infection. Int J Mycobacteriol [serial online] 2022 [cited 2022 Sep 29];11:293-8. Available from: https://www.ijmyco.org/text.asp?2022/11/3/293/355916




  Introduction Top


Globally, HIV accounted for 37.7 million prevalent cases, 1.5 million incident cases and 6,80,000 deaths.[1] The seroprevalence of HIV reported in India is 0.22% (0.17%–0.29%), which corresponds to 23.48 lakhs people.[2] It has been estimated that one-third of the world population, i.e., approximately 2 billion people of the world is infected with tuberculosis (TB) bacilli.[3] It is one of the leading causes of mortality across the globe.[4],[5] In India, 2.64 million incident cases of TB (of these, 71,000 cases occur among HIV-positive individuals) were reported in 2019.[6] Deaths due to TB were reported at 26.9 lakhs in India in a recent study.[7]

The human immune system is broadly classified into innate and adaptive immune systems. Innate immunity serves as the body's first line of defense against an invading pathogen.[8] Definite work on the innate immune system lead to the remarkable discovery of the highly skillful phylogenetically conserved family of proteins known as pattern recognition receptors (PRRs). PRRs had the ability to identify specific pathogen-associated molecular patterns. The most potent of all PRRs which play a central role in the innate immune system is toll-like receptors (TLRs). TLRs are a class of proteins mostly expressed on leukocytes, including macrophages that have an important role in TB pathogenesis.[9] These receptors recognize structurally conserved molecules derived from microorganisms such as bacteria and viruses.[10]

Till date, 13 TLRs (TLR1-TLR13) have been identified in mammalian species, these include 11 TLRs found in humans.[11] TLRs are expressed on a wide variety of cells (immune cells like macrophages, dendritic cells, B-cells, T-cells, and nonimmune cells like fibroblast, epithelial cell) tissues and organs including lymphoid organs.[11],[12] Some TLRs are expressed extracellularly on the cell surface (TLRs 1, 2, 4, 5, and 6) while others (TLRs 3, 7, 8, and 9) intracellularly.[13] TLR10 gene is mostly expressed in lymphoid tissues such as the spleen, lymph node, thymus, and tonsils. TLR11 is expressed in macrophages and dendritic cells. The exact function of the TLR10 and TLR11 genes is still not known in humans.

Since gene expression levels of TLRs are directly involved in the virus recognition and initiation of innate immune responses; therefore, the effect of HIV infection on TLRs gene expression was also investigated in functional context (through messenger RNA [mRNA] levels estimations of above mentioned TLRs). However, the more specific objective is to study the mRNA expression of TLRs (TLR2, TLR4, and TLR9) in HIV-1 infected patients with and without TB co-infection.


  Methods Top


Study setting and design

The study protocol was approved by the institutional ethics committee (Ref. No.: A-35/May 05, 2008) of the All India Institute of Medical Sciences (AIIMS), New Delhi. Written informed consent was obtained from all the study participants before enrollment in the study. This study was carried out in the Department of Medicine, AIIMS, New Delhi, India.

Study population

The present study was designed to investigate the gene expression of TLRs (TLR2, TLR4, and TLR9) among HIV-infected patients with and without TB co-infection. The study population consisted of the following three groups: (i) HIV-positive patients without TB infection and disease (HIV + patients); (ii) HIV-positive patients with active TB disease (HIV + TB patients); (iii) healthy controls.

Study procedure

The demographic and clinical information of all the recruited participants was captured in the standardized questionnaire. Baseline body weight and height were measured in all the subjects. Details of smoking, alcoholism, substance abuse, family history of TB, etc., were also collected.

Biological samples

Approximately 6–8 ml of peripheral venous blood was obtained aseptically in the ethylenediaminetetraacetic acid vials from all the study participants for RNA isolation.

Molecular techniques

RNA extraction from whole blood

Whole blood RNA was extracted from peripheral blood using a manual perfect pureTM RNA blood kit (5 PRIME Eppendorf®, Germany) according to the manufacturer's instructions.

Quantification of RNA

The quantification of RNA was carried out using optical density measurement of 1 μl of RNA at a wavelength of 260 nm and 280 nm using a nanophotometer with pure RNA preparation giving OD 260/OD 280 ratio close to 2. The OD value at 260 nm was used to calculate the concentration of RNA considering that 1 OD at 260 nm is equivalent to 40 μg RNA.

First-strand complementary DNA synthesis by reverse transcriptase polymerase chain reaction

After RNA extraction complementary DNA synthesis was done using Promega kit (GoScriptTM Reverse Transcription System, Promega Corporation Madison, USA) according to the manufacturer's instructions [Figure 1].
Figure 1: GAPDH, TLR2, TLR4 and TLR9 cDNA reverse transcriptase PCR amplicons (2% agarose gel (1 × TAE), GAPDH: Glyceraldehyde 3-phosphate dehydrogenase, TLR: Toll-like receptors, PCR: Polymerase chain reaction, TAE: Tris acetate EDTA, cDNA: Complementary DNA

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Messenger RNA expression by real-time polymerase chain reaction

Relative quantification is a standard procedure used to compare the differences in mRNA targets among different subjects. In this method, real-time polymerase chain reaction (PCR) was used for measurement of variations in the expression of TLR2, TLR4, and TLR9 mRNA molecules and compared with internal control glyceraldehyde 3-phosphate dehydrogenase (GAPDH) among healthy subjects, HIV+ and HIV+TB patients.

The TLRs (TLR2, TLR4, and TLR9) and GAPDH (housekeeping) gene mRNA expression was assessed by real-time PCR using respective gene-specific primers for TLR2 (F, 5'-TCTCCCATTTCCGTCTTTTT-3' and R, 5'-GGTCTTGGTGTTCATTATCTTC-3'), TLR4 (F, 5'-GAAGCTGGTGGCTGTGGA-3' and R, 5'-GATGTAGAACCCGCAAG-3'), TLR9 (F, 5'-CGCCAACGCCCTCAAGACA-3' and R, 5'-GGCGCTTACATCTAGTATTTGC-3') and for GAPDH (F, 5'-CCCCACACACATGCACTTACC-3' and R, 5'TTGCCAAGTTGCCTGTCCTT-3') as reported by Jin X et al. 2007.[14]

The program was set at 50°C for 2 min and 95°C for 10 min, followed by 40 cycles of denaturation at 95°C for 15s and annealing at 60°C for 60s. The melting curve was analyzed by elevating the temperature from 60°C to 95°C while monitoring fluorescence [Figure 3]. SYBR green fluorescence was monitored after each elongation period. Negative controls (without template) were included for each run. Samples were amplified in duplicate, averages were calculated, and differences in computed tomography (CT) data were evaluated. For data analysis, we used the comparative CT method (ΔΔCT method) with the following formula: First, the CT of the target gene and the reference gene for the patient were normalized (ΔCT [Patient] = CT [Target gene]–CT [Reference gene]) and for healthy controls (ΔCT [Control] = CT [Target gene]–CT [Reference gene]), Second, the Δ CT of the patient group were normalized to the Δ CT of the control (ΔΔCT = ΔCT [Patient]–ΔCT [Control]) Finally, the relative expression was calculated by using the following formula 2–ΔΔCT = Normalized expression. Data were interpreted as the expression of the TLR gene (target gene) relative to the GAPDH (internal control) in the patient groups compared with the healthy subjects.
Figure 2: Amplification chart of Real-time PCR for mRNA expression analysis of GAPDH, TLR2, TLR4 and TLR9 in different study participants, GAPDH: Glyceraldehyde 3-phosphate dehydrogenase, TLR: Toll-like receptors, PCR: Polymerase chain reaction, mRNA: Messenger RNA

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Figure 3: Melting curve chart of Real-time PCR for mRNA expression analysis of GAPDH, TLR2, TLR4 and TLR9 in different subjects, GAPDH: Glyceraldehyde 3-phosphate dehydrogenase, TLR: Toll-like receptors, PCR: Polymerase chain reaction, mRNA: Messenger RNA

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Melting curve

Melt-curve analysis was used to identify different reaction products, including nonspecific products and primer dimers. This was done as nonspecific products and primer dimers can severely reduce the amplification efficiency and accuracy of the data.

The melt peak distinguishes specific products from other products, such as primer dimers, which melt at different temperatures. Because of their small size, primer dimers usually melt at lower temperatures than the desired product, whereas nonspecific amplification can result in PCR products that melt at temperatures above or below that of the desired product [Figure 3],[Figure 4].
Figure 4: Melt peak chart of real-time PCR showing mRNA expression analysis of GAPDH, TLR2, TLR4 and TLR9 in various groups. Note: As shown above in [Figure 4], a single sharp melt peak was observed validating the specificity of PCR product and absence of primer dimmers in the RT-PCR reaction. RT-PCR: Reverse transcription-polymerase chain reaction, GAPDH: Glyceraldehyde 3-phosphate dehydrogenase, TLR: Toll-like receptors, PCR: Polymerase chain reaction, mRNA: Messenger RNA

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The fluorescence is plotted against temperature [Figure 2], and then, ΔF/ΔT (change in fluorescence/change in temperature) is plotted against temperature to obtain a clear view of the melting dynamics [Figure 2].

Baseline – In the initial cycles of PCR, there is little change in fluorescence signal that defines the baseline.

Threshold – The threshold of the real-time PCR reaction is the level of signal that reflects a significant increase over the calculated baseline signals.

  • CT (cycle threshold) – The CT is the cycle number at which the fluorescent signal of the reaction crosses the threshold. The CT is used to calculate the initial copy number
  • Rn − Rn value of a reaction containing all components (sample of interest)
  • Rn − Rn value detected in no template control
  • DRn − The difference between Rn+ and Rn. It is an indicator of the magnitude of the signal generated by the PCR.


Statistical analysis

Baseline characteristics (age, body mass index [BMI]) are presented as mean ± standard deviation/median (interquartile range [IQR]). The nonnormal distributed quantitative variables such as CD4 count and plasma viral load (PVL) were compared by using Wilcoxon–Ranksum/Kruskal–Wallis test. For mRNA expression analysis Wilcoxon–Rank sum test was applied. All analysis was performed using Stata version 12.0 (Stata Corporation, College Station, TX, USA). Two-sided P < 0.05 was considered statistically significant.


  Results Top


In the present study, mRNA expression of TLRs was studied among HIV+ patients (n = 25) and HIV+TB patients (n = 25) and was compared with healthy controls (n = 25).

Baseline characteristics of recruited study subjects

The demographic and baseline characteristics of the three study groups recruited in the study are provided in [Table 1]. There were 25 HIV+patients (mean age: 33 ± 7.7 years; 14 (56%) were male and 11 (44%) were female, 25 HIV+TB+ patients (mean age: 35 ± 7.2 years, 20 males and 05 female), and 25 healthy controls (mean age: 36 ± 2.04 years, 17 (68%) male and 08 (32%) female).
Table 1: Comparison of baseline characteristics of study subjects

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The BMI of various subgroups is provided in [Table 1]. It was observed that HIV+TB+ patients were severely malnourished/underweight with a BMI of 15.6 ± 1.4, as per the WHO classification of BMI (WHO Expert Consultation, 2004).

The CD4 cell count and PVL have been expressed as the median and IQR, data are shown in [Table 1]. The HIV+TB patients had lower CD4 cell counts (median 288 cells/mm3) and highest PVL (median 5.10 log10 copies/ml) as compared to HIV+ patient groups.

Messenger RNA expression of toll-like receptors

This is the first study where mRNA gene expression of TLR2, TLR4, and TLR9 has been compared between HIV+ and HIV+TB patients with reference to levels in healthy controls.

Experiments based on real-time quantitation of mRNA were carried out among 25 antiretroviral therapy (ART) naïve, asymptomatic HIV + patients and 25 HIV + TB patients. Similarly, 25 healthy controls were also included in this study as a control group. The expression data were compared among three groups and are shown in [Table 2],[Table 3],[Table 4].
Table 2: Comparison of toll-like receptors mRNA expression between HIV + patients and healthy subjects

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Table 3: Comparison of toll-like receptors mRNA expression between HIV + tuberculosis patients and healthy subjects

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Table 4: Comparison of toll-like receptors mRNA expression between HIV+and HIV+tuberculosis patients

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Healthy subjects

A mild increase in expression of TLR2, TLR4, and TLR9 (mRNA level) relative to the internal gene GAPDH was observed in HIV+ patients as compared to healthy controls, however, the difference was not statistically significant [Table 2]. The fold increase (or relative quantity [RQ]) in the expression of specific mRNA among patient groups as compared to healthy controls was calculated as 2−ΔΔCT. The 2−ΔΔCT values were 5.95, 3.23, and 9.61 for TLR2, TLR4, and TLR9, respectively, in the case of HIV+TB patients.

Likewise, a slight increase in TLR expression was observed in HIV+TB patients as compared to healthy controls but was not statistically significant [Table 3]. The fold increase (or RQ) in the expression of specific mRNA among patient groups as compared to healthy controls was calculated as 2−ΔΔCT. The 2−ΔΔCT values were 8.45, 4.82, and 6.33 for TLR2, TLR4, and TLR9, respectively, in the case of HIV+TB patients.

Healthy subjects

Similarly, a mild increase in TLR expression was observed in HIV+TB patients as compared to HIV+ patients; however, it was not statistically significant [Table 4]. The fold increase (or RQ) in the expression of specific mRNA among HIV+TB patient group as compared to HIV + patients was calculated as 2−ΔΔCT. The 2−ΔΔCT values were 8.32, 6.46, and 8.12 for TLR2, TLR4, and TLR9, respectively, in the case of HIV + TB patients.


  Discussion Top


The results of the present study indicate that TLRs were differentially expressed in chronic HIV-1 infected patients with CD4+T-cell count >200 cells/mm3 and in controlswith more advanced disease with CD4+T cell count <200 cells/mm3. The fold increase in the mRNA expression of TLR2 and TLR4 was observed in patients with advanced HIV disease with CD4+T-cell count <200 cells/mm3 and in HIV-TB co-infected patients as compared to healthy controls. The fold increase in the mRNA expression of TLR9 was also observed in chronic HIV-infected patients with CD4+T-cell count >200 cells/ml, as compared to healthy subjects. However, the difference in the expression of TLRs was not statistically significant.

Previous studies have demonstrated that patients having different viral infections show changes in their TLR expression.[15],[16] A study from Ethiopia investigated the expression of selected TLR mRNAs in peripheral blood in latent TB infection.[17] Study reporting that TLR2 and TLR4 mRNA expression is increased in HIV+ patients with CD4 cell count <200 cells/ml as compared to those with CD4 count >200 cells/ml[18] are consistent with the findings of the present study. A study from Italy found reduced expression of TLR4 and TLR9 in HIV+ patients failing to respond to ART as compared to healthy controls.[19]

The central role of TLRs in innate immune response and initiation of appropriate adaptive response, have suggested that regulation of their expression might be important in determining the HIV-1 disease course. The results of the present study indicate that TLRs were differentially expressed in chronic HIV-1 infected patients with CD4 + T-cell count >200 cells/mm3 and in subjects with more advanced disease with CD4 + T cell count <200 cells/mm3. The fold increase in the mRNA expression of TLR2 and TLR4 was observed in patients with advanced HIV disease with CD4 + T-cell count <200 cells/mm3 and in HIV-TB co-infected patients as compared to healthy controls. The fold increase in the mRNA expression of TLR9 was also observed in chronic HIV-infected patients with CD4 + T-cell count >200 cells/ml, as compared to healthy controls. However, the difference in the expression of TLRs was not statistically significant.

In the present study, mRNA gene expression of TLR2, TLR4 and TLR9 has been investigated in HIV + and HIV + TB patients and compared with healthy controls. The fold increase (or RQ) in the expression of specific mRNA among patient groups as compared to healthy controls was calculated as 2−ΔΔCT.


  Conclusion Top


The increase expression of TLR2, TLR4 and TLR9 (mRNA level) relative to the internal gene GAPDH was observed in HIV+ and HIV+TB patients as compared to healthy subjects. Similarly, increase in TLR expression was observed in HIV+TB patients as compared to HIV+ patients. A modest increase in expression of TLRs in HIV+ patients with and without TB co-infection could suggest a potential role for these TLRs in HIV-1 immunopathogenesis.

Limitations of the study

The limited sample size for mRNA expression analysis in the present study due to constrained resources might be responsible for observing no or very less significant difference in mRNA expression analysis of TLRs between different study groups.

Ethical statement

The ethical clearance was obtained by the Institutional Ethics Committee of the AIIMS, New Delhi (Ref. No.: A35/May 5, 2008).

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Global Report: UNAIDS Report on the Global AIDS Epidemic; 2020.  Back to cited text no. 1
    
2.
NACO Report 2019. HIV Facts & Figures. NACO; 2019.  Back to cited text no. 2
    
3.
Kajogoo VD, Twebaze C, Said B, Tesfahunei HA, Charlie L, Getachew E, et al. Post tuberculosis chronic lung disease in tuberculosis HIV coinfected and non-HIV individuals in Sub-Saharan Africa: A systematic review and meta-analysis. Int J Mycobacteriol 2022;11:139-44.  Back to cited text no. 3
  [Full text]  
4.
Saleemi SA, Alothman B, Alamer M, Alsayari S, Almogbel A, Mohammed S, et al. Tuberculosis presenting as metastatic lung cancer. Int J Mycobacteriol 2021;10:327-9.  Back to cited text no. 4
[PUBMED]  [Full text]  
5.
Mengesha D, Manyazewal T, Woldeamanuel Y. Five-year trend analysis of tuberculosis in Bahir dar, Northwest Ethiopia, 2015-2019. Int J Mycobacteriol 2021;10:437-41.  Back to cited text no. 5
[PUBMED]  [Full text]  
6.
WHO. Global Tuberculosis Report; 2019.  Back to cited text no. 6
    
7.
Kaushik G, Vashishtha R, Tripathi H, Yadav RN. Genetic polymorphism of toll-like receptors in HIV-I infected patients with and without tuberculosis co-infection. Int J Mycobacteriol 2022;11:95-102.  Back to cited text no. 7
[PUBMED]  [Full text]  
8.
Marshall JS, Warrington R, Watson W. An introduction to immunology and immunopathology. Allergy Asthma Clin Immunol 2018;14:49.  Back to cited text no. 8
    
9.
Kleinnijenhuis J, van Crevel R, Netea MG. Trained immunity: consequences for the heterologous effects of BCG vaccination. Trans R Soc Trop Med Hyg 2015;109:29–35.  Back to cited text no. 9
    
10.
Dowling JK, Mansell A. Toll-like receptors: The swiss army knife of immunity and vaccine development. Clin Transl Immunol. 2016;5:e85.  Back to cited text no. 10
    
11.
Vijay K. Toll-like receptors in immunity and inflammatory diseases: Past, present, and future. Int Immunopharmacol 2018;59:391-412.  Back to cited text no. 11
    
12.
Kawasaki T, Kawai T. Toll-like receptor signaling pathways. Front Immunol 2014;5:461.  Back to cited text no. 12
    
13.
Barton GM. Viral recognition by Toll-like receptors. Semin Immunol 2007;19:33-40.  Back to cited text no. 13
    
14.
Jin X, Qin Q, Tu L, Zhou X, Lin Y, Qu J. Toll-like receptors (TLRs) expression and function in response to inactivate hyphae of fusarium solani in immortalized human corneal epithelial cells. Mol Vis 2007;13:1953-61.  Back to cited text no. 14
    
15.
Riordan SM, Skinner NA, Kurtovic J, Locarnini S, McIver CJ, Williams R, et al. Toll-like receptor expression in chronic hepatitis C: Correlation with pro-inflammatory cytokine levels and liver injury. Inflamm Res 2006;55:279-85.  Back to cited text no. 15
    
16.
Dolganiuc A, Garcia C, Kodys K, Szabo G. Distinct toll-like receptor expression in monocytes and T cells in chronic HCV infection. World J Gastroenterol 2006;12:1198-204.  Back to cited text no. 16
    
17.
Alemnew B, Hoff ST, Abebe T, Abebe M, Aseffa A, Howe R, et al. Ex vivo mRNA expression of toll-like receptors during latent tuberculosis infection. BMC Immunol 2021;22:9.  Back to cited text no. 17
    
18.
Lester RT, Yao XD, Ball TB, McKinnon LR, Kaul R, Wachihi C, et al. Toll-like receptor expression and responsiveness are increased in viraemic HIV-1 infection. AIDS 2008;22:685-94.  Back to cited text no. 18
    
19.
Scagnolari C, Selvaggi C, Chiavuzzo L, Carbone T, Zaffiri L, d'Ettorre G, et al. Expression levels of TLRs involved in viral recognition in PBMCs from HIV-1-infected patients failing antiretroviral therapy. Intervirology 2009;52:107-14.  Back to cited text no. 19
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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