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. 2026 Mar 7;12(2):e70867. doi: 10.1002/vms3.70867

Association of Haematological Parameters With TLR Genes in Healthy and Distemper‐Infected Dogs Haematology and TLRs in Distemper

İlknur Karaca Bekdik 1,✉, Fadime Daldaban 2, Korhan Arslan 2, Bilal Akyüz 2, Öznur Aslan 1
PMCID: PMC12966964  PMID: 41793260

ABSTRACT

Background

Determining the expression levels of TLRs involved in innate and adaptive immunity in canine distemper infections would provide a significant advantage for controlling the disease.

Objectives

This study aimed to investigate the correlation between the expression levels of the genes toll‐like receptors 1–9 (TLR1–9) and haematological parameters in healthy and distemper‐infected dogs.

Materials and Methods

The study material was composed of healthy dogs (n = 8) and distemper‐infected dogs (n = 8). Haematologic analyses were performed on EDTA blood samples taken from the dogs, and the expression levels of TLR1‐9 genes were determined.

Results

TLR3, TLR4 and TLR9 gene expression levels significantly differed between healthy and infected dogs (p < 0.05). The comparative analysis of the haematological parameters of the two groups revealed the presence of statistically significant differences for lymphocyte count (Lymph), lymphocyte percentage (Lymph%) and granulocyte percentage (Gran%; p < 0.05). The present study demonstrated that, in the dogs infected with distemper, based on the correlation coefficients between the expression levels of TLR1‐9 genes and haematological parameters, there was a positive correlation between TLR1 and PDW, TLR4 and WBC, Gran and Gran%, TLR5 and HCT, TLR6 and Gran%, TLR7 and MCV and TLR7 and PDW and a negative correlation between TLR2 and Lymph and monocyte, TLR3 and WBC and TLR5 and RDW.

Conclusions

We believe that more studies are needed to understand the effect of TLRs and haematological parameters on the course and prognosis of the distemper diseases.

Keywords: canine distemper virus, dog, haematological parameters, TLR

The distemper‐infected dogs presented with an upregulated expression of the immune recognition receptors TLR3, TLR4 and TLR9. In the distemper‐infected dogs, there was a positive correlation between the TLR1 and PWD, TLR4 and WBC, Gran and Gran%, TLR5 and HCT, TLR6 and Gran%, TLR7 and MCV and TLR7 and PDW, as well as a negative correlation between the TLR2 and Lymph, TLR2 and MON, TLR3 and WBC and the TLR5 and RDW.

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1. Introduction

Distemper is a highly contagious and globally widespread disease caused by the canine distemper virus (CDV), characterized by high morbidity and mortality (Duque‐Valencia et al. 2019). The CDV, which is a negative‐sense and single‐stranded RNA virus, is classified under the Paramyxoviridae family and Morbilivirus genus together with the cetacean morbillivirus, feline morbillivirus, measles virus, phocine distemper virus, peste des petits ruminants virus and rinderpest virus (Maes et al. 2019; Wilkes 2022; Gaur, Jain, et al. 2024).

Distemper infection occurs through inhaling aerosol droplets containing viral particles or direct contact with contaminated body fluids and fomites (Aida et al. 2021). The CDV first replicates in tissue macrophages (Zhao and Ren 2022; Gonzales‐Viera et al. 2023) and lymphocytes (Zhao and Ren 2022) and is then distributed to the tonsils and respiratory lymph nodes within 24 h via the lymphatic system (Du et al. 2022), eventually resulting in severe immunosuppression (Du et al. 2022; Zhao and Ren 2022). Following the transmission of the CDV, the infection spreads to other lymphoid tissues within 2–4 days and to the gastrointestinal mucosa, hepatic Kupffer cells and spleen by the sixth day. This infection results in a systemic reaction characterized by fever and leukopenia. Cell‐associated viremia enables the further spread of the CDV. Thereby, the virus accesses other epithelial cells and the central nervous system (CNS; Loots et al. 2017). Distemper causes respiratory, gastrointestinal and CNS symptoms and ocular and cutaneous lesions (Saaed and Al‐Obaidi 2021).

Toll‐like receptors (TLRs) are pattern recognition receptors (PRRs), which are capable of specifically recognizing pathogen‐associated molecular patterns (PAMPs) found on the surface of pathogens (Alexopoulou et al. 2001). Functioning as the primary regulators of both innate and adaptive immunity, TLRs have critical roles in the recognition of microbial products, the secretion of inflammatory mediators via induced transcription factors during immune response development and the inflammatory process and the control of the adaptive immune response (Carpenter and O'Neill 2007). TLRs are found not only in immune cells, including monocytes, macrophages, dendritic cells, neutrophil leukocytes, B cells, T cells, mast cells and natural killer (NK) cells, but also in nonimmune cells, including fibroblasts, epithelial cells, astrocytes, keratinocytes and thrombocytes (Farooq et al. 2021). To date, 10 TLRs have been identified in dogs. While TLR1, 2, 5 and 6 are expressed on the cell surface, TLR3, 7, 8 and 9 are expressed on the endosomal surface, and TLR 4 is expressed on both surfaces (Shekarian et al. 2017). TLR1, 2, 4, 5 and 6 of these receptors detect pathogens’ extracellular compounds, and TLR3, 7, 8 and 9 detect their nucleic acids, while there is no known ligand for TLR10 (Kawai and Akira 2010).

Not all clinical symptoms of an infection arise from the infectious agent itself; most of them arise from the host's immune reaction to the pathogen. Thus, understanding how immune responses are induced and regulated is critical to illuminating the host‐pathogen interactions (Fitzgerald and Kagan 2020).

It is highly important to gain a more profound insight into the induction and modulation mechanisms of immune reactions against infections. In this context, determining the expression levels of TLRs, involved in innate and adaptive immunity in canine distemper infection would provide a significant advantage for controlling the disease. In studies on haematological parameters in distemper disease, nonspecific findings such as anaemia, leukocytosis/leukopenia, thrombocytopenia, lymphopenia, neutropenia/neutrophilia, monocytopenia/monocytosis and eosinophilia have been obtained depending on whether the disease is acute or chronic or the presence of secondary infection (Buragohain et al. 2017; Yanar et al. 2024). From this perspective, this study aimed to determine the expression levels of TLR1‐9 genes in healthy and distemper‐infected dogs and the haematological profile reflecting the immune response associated with these gene expressions.

2. Materials and Methods

2.1. Animal Material

The number of animals used in the study was determined based on a power analysis conducted according to the 3R principle to ensure the minimum number of animals required. According to the power analysis performed using the G*Power program, it was determined that eight animals should be included in each group.

The animal material was assigned to two groups, one of which included healthy dogs (control group, n = 8, three females and five males) and the other distemper‐infected dogs (n = 8, three females and five males). Clinical and laboratory examinations confirmed the health statuses of the dogs in the healthy group. Dogs with no abnormal findings in their clinical and haematological examinations and negative CDV rapid tests and reverse transcription polymerase chain reaction (RT‐PCR) tests were considered healthy. This group included unvaccinated dogs of similar breed, age and sex to the distemper‐infected group, whose owners gave informed consent to participate in the study. The distemper‐infected group included 2‐ to 4‐month‐old unvaccinated dogs admitted to the veterinary clinic with signs of diarrhoea, emesis, coughing, fever and mucopurulent nasal and ocular discharge, and they were confirmed to be infected using a rapid test kit. Swab samples were taken from the ocular and nasal discharge of the animals that were brought to the clinic, and distemper was diagnosed with the aid of a rapid test kit (Asan Easy Test Distemper, Canine Distemper Virus Antigen (CDV aAg) Test, 022321, Asan Pharmaceutical Co. Ltd., Korea).

2.2. Collection of Blood Samples and Haematological Analyses

Blood samples were taken from the vena cephalica antebrachii of the animals into ethylene diamine tetra acetic acid (EDTA)‐coated tubes for the determination of haematological parameters and the conduct of real‐time quantitative polymerase chain reaction (RT‐qPCR) analyses. Complete blood counts (CBC) were performed to using a hemogram device (Mindray BC‐2800Vet, China).

2.3. CDV Identification With Reverse Transcriptase‐Polymerase Chain Reaction

All dogs included in the study were tested for distemper through the CDV rapid test kit and RT‐PCR. For this purpose, the presence of the CDV genome was determined (Figure 1) using the Qiagen One‐Step Reverse Transcriptase PCR kit (Qiagen, Hilden, Germany; Cat. No. 210210) and the Qiagen Thermal Cycler PCR system (Qiagen, Hilden, Germany) as described by Frisk et al. (1999). Following RT‐PCR band images were visualized on agarose gel, and samples yielding positive results were included in the distemper‐infected group (Figure 1).

FIGURE 1.

FIGURE 1

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CDV Rt‐PCR agarose gel results. Line 2,3,5 and 9: CDV positive; Line 1, 4, 6, 7, 8, 10–13: CDV negative; bp: base pair.

2.4. RNA Isolation

After the blood samples of the healthy and distemper‐infected dogs were transferred to the laboratory on the day of their collection, RNA isolation was performed manually using Trizol (TriPure Trizol, Sigma, Germany, Darmstadt, Cat. No. 11 667 157 001). DNAase (Invitrogen DNA‐free DNA removal kit, Invitrogen, Thermo Fisher Scientific, Carlsbad, US, Cat. No. AM1906) was used to avoid the DNA contamination of the isolated RNA samples. After being treated with DNAase, the RNA samples were checked for purity and integrity with a nanodrop device (Synergy H1 Hybrid Multi‐Mode Microplate Reader, BioTek, USA) and were imaged by 1% agarose gel electrophoresis. Until being used for c‐DNA synthesis, the isolated RNA samples were stored at ‐ 80°C.

2.5. c‐DNA Synthesis and RT‐qPCR Analysis

c‐DNA synthesis was performed using a Transcriptor First Strand c‐DNA Synthesis Kit (Roche Ltd., Mannheim, Germany, Cat. No. 04379012001), in accordance with the manufacturer's protocol on a Qiagen thermal cycler (Qiagen SensoQuest, Hilden, Germany). The synthesized c‐DNA samples were diluted 1:4 with nuclease‐free water (NFW). RT‐qPCR was performed with three repetitions on a Light Cycler Nano device (Roche Ltd., Mannheim, Germany) using the Fast Start SYBR Green Master Mix (Roche Ltd., Mannheim, Germany, Cat. No: 4673484001) kit. A melting curve analysis was performed to prevent nonspecific binding. Target gene data were normalized with housekeeping genes. Crude data derived from the application of the 2–ΔΔCt formula to normalized data were further adapted for use in statistical analyses (Schmittgen and Livak 2008). The primary sequences of the genes analysed by RT‐qPCR are presented in Table 1 (Daldaban et al. 2021).

TABLE 1.

Primer sequences of TLR1‐9 genes (Daldaban et al. 2021).

Gene Primer sequences A (bp) Reference
TLR1 F GCCATCCTACCGTGAACCT 114 Igarashi et al. (2014)
R GCACTCAACCCCAGAAACTC
TLR2 F ATGATTCCTACTGGGTGGAGAAC 310 Linde et al. (2007)
R CGCAGCTTACAGAATCGCTG
TLR3 F GCAACACCCAGCTACACAGA 130 Igarashi et al. (2014)
R ATGTGGAAGCCAGACAAAGG
TLR4 F CCTGGAAGGACTGTGCAATT 372 Linde et al. (2007)]
R TGCTTCAGTCTGGTTGTCCC
TLR5 F CCAGGACCAGACGTTCAGAT 109 Turchetti et al. (2015)
R GCCCAGGAAGATGGTGTCTA
TLR6 F TCAAGCATTTAGACCTCTCATTCA 109 Igarashi et al. (2014)
R CCGTAACTTTGTAGCACTTAAACCT
TLR7 F GGAAGACCCAAGGGAGAAAC 98 Turchetti et al. (2015)
R GCTGTATGCTCTGGGAAAGG
TLR8 F TCAGCTACAATGCACACTACTTCC 138 Igarashi et al. (2014)
R ACGCTTCTCAGGTCTTGCTC
TLR9 F ACTGGCTGTTCCTCAAGTCC 104 Igarashi et al. (2014)
R AGTCATGGAGGTGGTGGATG
GAPDH F GGAGAAAGCTGCCAAATATG 194 McMahon et al. (2010)
R ACCAGGAAATGAGCTTGACA
β‐Actin F CTTCTACAACGAGCTGCGCG 307 Alves et al. (2009)
R TCATGAGGTAGTCGGTCAGG
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Abbreviations: A: amplicon size; bp: base pair; F: forward primer; R: reverse primer.

2.6. Statistical Analyses

The normality distribution of the data was assessed using histograms, Q–Q plot graphs and the Shapiro–Wilk test. Differences between the healthy and distemper‐infected groups for the genetic and haematological parameters were analysed with the independent two‐sample t‐test, and the correlations between the genetic and phenotypic parameters were determined with Pearson's correlation coefficient. The statistical analysis of the study data was performed with the IBM SPSS 14.01 software, and the level of statistical significance was accepted as p < 0.05.

3. Results

In the distemper‐infected dogs, diarrhoea was observed in four dogs and emesis in one dog; all displayed body temperatures ranging from 38.5°C to 40.3°C, along with mucopurulent ocular and nasal discharge, cough and dehydration. The degree of dehydration was recorded as mild in two dogs, moderate in four dogs and severe in two dogs.

The analyses demonstrated that there was no statistically significant difference between the study groups for the expression levels of TLR1, TLR2, TLR5, TLR6, TLR7 and TLR8 genes (p > 0.05; Table 2). On the other hand, the study groups significantly differed for the expression levels of TLR3, TLR4 and TLR9 genes (p < 0.05). The expression levels of TLR3, TLR4 and TLR9 were significantly upregulated in the distemper‐infected group, compared to the control group (Table 2).

TABLE 2.

TLR1‐9 genes expression levels and relationship between groups.

Gene Group n Mean ± standard deviation t p
TLR1 Healthy 8 0.000 ± 1.539 −1.931 0.074
Distemper 8 1.150 ± 0.686
TLR2 Healthy 8 0.000 ± 0.866 −2.049 0.060
Distemper 8 0.975 ± 1.031
TLR3 Healthy 8 0.000 ± 1.491 −3.208 0.006 *
Distemper 8 2.094 ± 1.089
TLR4 Healthy 8 0.000 ± 0.743 −2.608 0.021 *
Distemper 8 1.148 ± 0.998
TLR5 Healthy 8 0.000 ± 1.086 1.041 0.315
Distemper 8 −0.641 ± 1.360
TLR6 Healthy 8 0.000 ± 1.148 0.220 0.829
Distemper 8 −0.134 ± 1.292
TLR7 Healthy 8 0.000 ± 1.240 −1.729 0.106
Distemper 8 0.817 ± 0.497
TLR8 Healthy 8 0.000 ± 0.819 1.073 0.301
Distemper 8 −0.508 ± 1.061
TLR9 Healthy 8 0.000 ± 1.093 −2.479 0.027 *
Distemper 8 1.974 ± 1.969
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*p < 0.05.

As a result of the comparison of haematological parameters between the groups, it was determined that there was no statistically significant difference in terms of white blood cell count (WBC), monocyte count (Mon), granulocyte count (Gran), monocyte percentage (Mon), red blood cell count (RBC), haemoglobin level (HGB), haematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH), mean corpuscular haemoglobin concentration (MCHC), red blood cell distribution width (RDW), platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW) and plateletcrit (PCT; p > 0.05; Table 3). However, lymphocyte count (Lymph) and lymphocyte percentage (Lymph%) values were found to be significantly higher, and the granulocyte percentage (Gran%) value was lower in the distemper‐infected group, compared to the control group (p < 0.05; Table 3).

TABLE 3.

Comparison of haematological parameters between groups.

Hematology parameters Group n Mean ± standard deviation t p
WBC 109/L Control 8 18.275 ± 10.904 1.289 0.232
Distemper 8 13.075 ± 3.361
Lymph 109/L Control 8 1.338 ± 0.733 −3.489 0.004 *
Distemper 8 2.925 ± 1.058
Mon 109/L Control 8 0.663 ± 0.504 −0.123 0.904
Distemper 8 0.688 ± 0.275
Gran 109/L Control 8 16.013 ± 9.722 2.050 0.073
Distemper 8 8.625 ± 3.059
Lymph % Control 8 8.013 ± 4.418 −4.654 0.000 *
Distemper 8 23.325 ± 8.191
Mon % Control 8 3.563 ± 1.509 −1.673 0.117
Distemper 8 5.550 ± 3.003
Gran % Control 8 87.025 ± 6.656 5.019 0.000 *
Distemper 8 65.425 ± 10.191
RBC 1012/L Control 8 5.195 ± 0.966 0.736 0.474
Distemper 8 4.850 ± 0.909
HGB g/dl Control 8 10.338 ± 1.567 0.306 0.764
Distemper 8 10.000 ± 2.701
HCT % Control 8 30.588 ± 5.250 −0.018 0.986
Distemper 8 30.638 ± 5.793
MCV fL Control 8 59.438 ± 7.036 −1.207 0.247
Distemper 8 63.563 ± 6.627
MCH pg Control 8 20.088 ± 1.895 −0.363 0.722
Distemper 8 20.550 ± 3.071
MCHC g/dl Control 8 34.000 ± 2.929 0.817 0.430
Distemper 8 32.463 ± 4.448
RDW % Control 8 17.238 ± 2.941 −0.662 0.519
Distemper 8 18.200 ± 2.872
PLT 109/L Control 8 313.625 ± 136.917 −1.025 0.323
Distemper 8 403.000 ± 205.035
MPV fL Control 8 7.288 ± 1.246 −1.280 0.221
Distemper 8 8.400 ± 2.120
PDW Control 3 16.100 ± 0.755 −0.161 0.877
Distemper 5 16.180 ± 0.638
PCT % Control 3 0.202 ± 0.068 −1.054 0.332
Distemper 5 0.253 ± 0.065
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Abbreviations: Gran: granulocyte, HCT: haematocrit, HGB: haemoglobin, Lymph: lymphocyte, MCH: mean corpuscular haemoglobin, MCHC: mean corpuscular haemoglobin concentration, MCV: mean corpuscular volume, Mon: monocyte, MPV: mean platelet volume, PCT: plateletcrit, PDW: platelet distribution width, PLT: platelet, RBC: erythrocyte, RDW: red blood cell distribution width, WBC: leukocyte.

*p < 0.05.

Table 4 presents the correlation between the levels of expression of TLR1‐9 genes and the haematological parameters.

TABLE 4.

Correlations between TLR1‐9 gene expression levels and hematologic parameters.

Group Gene WBC Lymph Mon Gran RBC HGB HCT MCV MCH MCHC RDW PLT MPV PDW PCT
Healthy TLR1 −0.487 −0.557 −0.390 −0.473 0.002 −0.097 −0.426 −0.542 −0.092 0.643 0.324 0.469 −0.485 0.247 0.282
TLR2 −0.610 −0.682 −0.388 −0.601 −0.495 −0.562 −0.795 * −0.344 0.149 0.604 0.215 0.196 −0.355 0.688 −0.221
TLR3 −0.078 −0.337 −0.090 −0.047 −0.879 ** −0.876 ** −0.652 0.360 0.317 −0.183 0.127 −0.321 0.327 −0.750 0.982
TLR4 −0.017 −0.099 0.261 −0.040 −0.544 −0.568 −0.867 ** −0.363 0.215 0.686 0.341 0.490 −0.264 0.033 0.482
TLR5 −0.415 −0.717 * −0.334 −0.378 −0.448 −0.537 −0.541 −0.122 0.038 0.195 0.284 0.008 −0.270 −0.981 0.744
TLR6 −0.257 −0.648 −0.375 −0.199 −0.737 * −0.723 * −0.636 0.200 0.295 0.029 0.198 −0.179 0.129 −0.566 0.908
TLR7 −0.475 −0.741 * −0.487 −0.427 −0.613 −0.668 −0.614 0.042 0.159 0.099 0.145 −0.216 −0.081 −0.795 0.993
TLR8 −0.352 −0.530 −0.117 −0.346 −0.796 * −0.742 * −0.852 ** −0.018 0.417 0.430 0.016 −0.091 −0.181 0.578 −0.081
TLR9 −0.129 −0.124 −0.073 −0.120 −0.717 * −0.890 ** −0.713 * 0.075 0.012 −0.120 0.247 −0.183 0.217 −0.439 0.836
Distemper TLR1 0.474 −0.200 −0.106 0.636 0.239 0.322 0.591 0.689 0.177 −0.309 −0.816 * −0.425 0.335 0.987 ** 0.156
TLR2 −0.244 −0.729 * −0.753 * −0.010 0.432 0.170 0.328 −0.127 −0.251 −0.203 −0.439 −0.420 0.040 0.164 −0.597
TLR3 −0.775 * −0.303 0.353 −0.694 0.463 0.220 0.346 −0.252 −0.183 −0.038 −0.244 −0.001 −0.287 −0.364 −0.324
TLR4 0.737 * 0.084 −0.138 0.893 ** −0.401 −0.023 −0.098 0.600 0.451 0.093 −0.267 0.012 0.403 0.825 0.126
TLR5 0.607 −0.262 0.179 0.640 0.463 0.650 0.770 * 0.559 0.463 0.089 −0.843 ** 0.035 −0.106 0.838 0.723
TLR6 −0.088 0.031 −0.155 0.277 0.202 −0.107 0.064 −0.172 −0.465 −0.403 −0.382 −0.409 0.193 −0.427 −0.384
TLR7 0.244 −0.303 0.078 0.438 −0.130 0.179 0.293 0.791 * 0.463 −0.041 −0.663 −0.150 0.397 0.928 * −0.032
TLR8 0.004 0.555 0.143 −0.126 0.068 −0.203 0.106 0.081 −0.516 −0.644 0.091 −0.552 0.262 −0.578 0.218
TLR9 0.302 −0.223 −0.280 0.444 0.603 0.496 0.648 0.128 0.029 −0.078 −0.551 −0.213 −0.102 0.092 −0.751
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Abbreviations: Gran: granulocyte, HCT: hematocrit, HGB: haemoglobin, Lymph: lymphocyte, MCH: mean corpuscular haemoglobin, MCHC: mean corpuscular haemoglobin concentration, MCV: mean corpuscular volume, Mon: monocyte, MPV: mean platelet volume, PCT: plateletcrit, PDW: platelet distribution width, PLT: platelet, RBC: erythrocyte, RDW: red blood cell distribution width, TLR: toll‐like receptor, WBC: leukocyte.

*p < 0.05; **p < 0.001.

Based on the correlation coefficients between the expression levels of the investigated genes and the haematological parameters in the distemper‐infected group, positive correlations were determined between TLR1 and PDW; TLR4 and WBC, Gran and Gran%; TLR5 and HCT; TLR6 and Gran%; and TLR7 and MCV and PDW. On the other hand, based on the correlation coefficients between the expression levels of the investigated genes and the haematological parameters, in the distemper‐infected group, negative correlations were determined between TLR2 and Lymph and Mon; TLR3 and WBC; and TLR5 and RDW. Furthermore, the expression levels of the genes TLR5 and TLR7 were found to be significantly negatively correlated with the lymphocyte count in the control group (p < 0.05), but these correlations were insignificant in the distemper‐infected group (p > 0.05; Table 4).

4. Discussion

TLR1, 2, 4, 6 and 10 are involved in the specific recognition of viral proteins (Boozari et al. 2019). Furthermore, TLR2, 3, 4, 7, 8 and 9 have been shown to be involved in the innate immune response against viral stimulation in humans (Kawai and Akira 2006). Bieback et al. (2002) reported that the MeV‐H protein is recognized by TLR2, resulting in increased surface expression of the CD150 (SLAM) receptor, further promoting viral infection in host cells. Rojas et al. (2021) demonstrated that the PPRV‐H protein activates TLR2 signaling and stimulates the release of proinflammatory cytokines. Gaur, Chaudhary, et al. 2024) stated that the PPRV‐H protein shares significant structural homology with the haemagglutinin protein in MeV and CDV. Necesankova et al. (2016) observed a single amino acid change in the leucine‐rich repeat of TLR2 in the only surviving female lion among five lions diagnosed with CDV. They have reported that this alteration resulted in a nonpolar to polar group change, potentially influencing the expression and function of TLR2 (Necesankova et al. 2016). In our study, although TLR2 was upregulated in dogs infected with distemper, compared to healthy dogs, no statistically significant difference was determined between the groups (p > 0.05). It is thought that further research is needed to understand whether TLR2 initiates a signaling cascade similar to that of MeV and PPRV via the CDV‐H protein and to understand its effect on survival in CDV infection.

TLR3 is reported to play a critical role in the induction of antiviral immunity and the prevention of viral replication (Lester and Li 2014). TLR3 has been demonstrated to be capable of detecting infections with dsRNA viruses, ssRNA viruses and DNA viruses (Kawai and Akira 2011). High TLR3 and TLR7 levels have been reported to be associated with increased inflammatory cytokine and decreased immunomodulatory cytokine expression in Indian goat breeds and water buffaloes infected with the peste des petits ruminant virus (PPRV) (Dhanasekaran et al. 2014). While CNS infections with the herpes simplex virus (HSV) have been reported to be more severe in TLR3‐knockout mice in comparison to wild‐type mice and mice null for other TLRs, it has been ascertained that in the absence of TLR3, astrocytes were incapable of detecting HSV‐2 infection, which eventually led to uncontrolled viral replication and distribution (Reinert et al. 2012). Several researchers have determined that children born with deficiencies of the TLR3 pathway are predisposed to encephalitis caused by HSV‐1, which is a severe viral infection of the CNS (Audry et al. 2011; Herman et al. 2012). Furthermore, it has been indicated that TLR3 is activated by apoptotic cells infected with viruses (Thompson and Iwasaki 2008). In the present study, we found that the expression levels of the TLR3 gene were significantly higher in the distemper‐infected dogs, compared to the healthy dogs. This information suggests that TLR3 could be a significant factor in recognizing viral infection and stimulating immune response, which agrees with previous studies (Thompson and Iwasaki 2008; Reinert et al. 2012), in the prevention of the development of CNS infection in distemper cases. We consider that further studies are needed to understand whether the negative correlation we identified between TLR3 expression and WBC in dogs with distemper is related to the prognosis of the disease.

In an investigation conducted by Geng et al. (2020) on immune reactions against CDV vaccination in giant pandas, when compared to Day 0, it was determined that on Day 1, TLR4 and TLR8 genes, which are associated with innate immunity, were upregulated. Reports indicate that various viral envelope proteins, including the F protein of the human respiratory syncytial virus (RSV) (Haynes et al. 2001), the envelope proteins of the mouse mammary tumor virus (Rassa et al. 2002) and the Ebola virus proteins (Okumura et al. 2010), activate TLR4 in primary immune cells. Viral proteins that activate TLR4 are either membrane‐bound or membrane‐associated. Tong et al. (2016) reported that, in minks, the expression levels of TLR2, TLR4, TLR7 and TLR8 genes were significantly upregulated from the 24th hour following infection with the CDV. While the RSV fusion protein has been reported to induce the formation of the pathogen‐immobilizing and killer neutrophil extracellular traps (NETs) through TLR4 activation, it has also been indicated that the excessive production of NETs contributes to the pathology of viral respiratory system diseases (Funchal et al. 2015). In agreement with the previous studies referred to above, the observation of increased expression levels for the TLR4 gene and the detection of positive correlations between TLR4 and WBC and granulocyte counts in the present study were attributed to the interaction of the fusion protein of the CDV with TLR4.

Thrombocytes recognize signs of danger from pathogens and cells damage through the expression of TLRs on their surface and within the cell, thereby playing a protective role in immunoregulation (D'Atri and Schattner 2017). Lund et al. (2004) demonstrated the role of TLR7 as an endosomal receptor capable of detecting single‐stranded RNA viruses. The encephalomyocarditis virus activates thrombocytes through TLR7 (Koupenova et al. 2014). Koupenova et al. (2019) determined that, through TLR7, the influenza A virus induces thrombocyte activation and increases both thrombocyte‐neutrophil aggregation and the in vitro and in vivo secretion of NETs. It has been shown that while the synthetic TLR7 agonist loxoribine induces thrombocytes, infections with RNA viruses such as the encephalomyocarditis and influenza A viruses increase thrombocyte‐neutrophil aggregation, both processes eventually leading to thrombocytopenia, which has been attributed to the thrombocyte‐TLR7 interaction (Koupenova et al. 2014; Koupenova et al. 2019). Despite the role of thrombocyte‐TLR7 activation in the development of thrombocytopenia, thrombocyte‐granulocyte aggregation has been reported to increase the survival rate of mice with encephalomyocarditis, owing to these aggregates enabling the clearance of the causative virus (Koupenova et al. 2014). In the present study, TLR1 and TLR7 expressions have been determined to be positively correlated with PDW in the distemper‐infected dogs, suggesting that thrombocytes are effective in the detection of pathogens both on the cell surface (TLR1) and within the cell (TLR7). Furthermore, in the presented study, the platelet count increased in dogs with distemper, compared to healthy dogs, whereas the neutrophil count decreased. It was considered that thrombocyte‐TLR7 activation caused neutrophil aggregation in the dogs infected with distemper. In light of these findings, we believe that further research is needed to determine the role of platelet‐TLR7 in canine distemper disease and the survival of infected animals and to reveal the reason for the increase in platelet count in animals with distemper.

Into et al. (2002) determined that mycoplasmal lipoproteins induced caspase‐dependent necrotic and apoptotic cell death in lymphocytes and monocytes/macrophages, partly induced by TLR2‐mediated signalling. Rojas et al. (2021) reported that the H protein of the PPRV triggered TLR2 activation. Furthermore, Rojas et al. (2019) determined that PPRV infection led to the production of antibodies that triggered the in vivo antibody‐dependent cell‐mediated cytotoxicity (ADCC) of infected cells and described the H protein as one of the main targets of this cytotoxic mechanism. Reports indicate that the effect of the TLR2 signal on NK cells, which are one of the primary mediators of ADCC among innate immune cells, is to induce NK activation, which is a mechanism critical to the control of infection with viruses, including the vaccinia virus and HSV (Martinez et al. 2010; Uyangaa et al. 2018). Therefore, the activation of TLR2 by the H protein of the PPRV may potentially cause NK cell activation, which in turn may support the impact of effector mechanisms, such as ADCC responses, on NK cells. NK cells also act as major regulators of acquired immunity during viral infections (Schuster et al. 2014). Activated NK cells may eliminate CD4+T and CD8+T cells, affecting T cell functions required for viral clearance (Waggoner et al. 2011). In the present study, the observation of lymphocytosis and negatively correlated TLR2 expression with lymphocyte count in the distemper‐infected dogs was attributed to the induction of NK cells by the activation of TLR2 by the distemper H protein and the role of these cells in the elimination of CDV‐infected T cells.

Uyangaa et al. (2018) reported that in cases of HSV infection, TLR2 and TLR9 could be directly involved in the differentiation and maturation of infiltrated Ly‐6Chi monocytes and NK cells. The negative correlation we determined between TLR2 expression and monocyte count in the present study was likely to have arisen from the role of TLR2 in monocyte differentiation.

5. Conclusion

In conclusion, upregulated expression of TLR3, TLR4 and TLR9 genes in dogs with distemper infection, compared to healthy dogs, indicated that these TLR genes play a role in basic recognition and immune response induction functions as part of the innate immune system of CDV‐infected dogs. The negative correlations were determined between TLR2 and lymphocyte and monocyte counts, TLR3 and WBC and TLR5 and RDW in the distemper‐infected dogs. The positive correlation of TLR1 expression with PDW, TLR4 expression with WBC and granulocyte, TLR5 expression with HCT, TLR6 expression with Gran% and TLR7 expression with MCV and PDW was observed. In view of the study data, we suggest further investigation to understand whether the effects of TLR7 on platelet activation and survival in distemper patients and the negative correlation between TLR3 expression and WBC in dogs with distemper are related to the prognosis of the disease.

Author Contributions

İlknur Karaca Bekdik: conceptualization, data curation, formal analysis, investigation, methodology, writing – original draft, writing – review and editing. Fadime Daldaban: conceptualization, data curation, formal analysis, investigation, methodology, writing – original draft. writing – review and editing. Korhan Arslan: conceptualization, methodology, project administration, supervision. Bilal Akyüz: conceptualization, methodology, project administration, supervision. Öznur Aslan: conceptualization, data curation, formal analysis, investigation, methodology, project administration, supervision, writing – original draft, writing – review and editing.

Funding

This study was supported by the Erciyes University Scientific Research Unit with project number TKB‐2021‐11120.

Conflicts of Interest

The authors declare no conflicts of interest.

Ethics Statement

The authors confirm that the ethical policies of the journal, as noted on the journal's author guidelines page, have been adhered to and the appropriate ethical review committee approval has been received. This study was conducted according to the 3.02.2021‐dated and 21/29‐numbered approval of the Local Ethics Board for Animal Experiments of Erciyes University and all animal rights issues were appropriately observed.

Data Availability Statement

All data are available from the corresponding author upon a reasonable request.

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Data Availability Statement

All data are available from the corresponding author upon a reasonable request.

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