Edited by: Lester J. Perez, University of Illinois at Urbana–Champaign, United States
Reviewed by: Erika Sousa Guimarães, Federal Institute of Minas Gerais, Brazil; Fengyang Wang, Hainan University, China
This article was submitted to Veterinary Infectious Diseases, a section of the journal Frontiers in Veterinary Science
†Present address: Soojin Shim, Department of Mechanical and Biofunctional Systems, Institute of Industrial Science, University of Tokyo, Tokyo, Japan
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Research has been undertaken to understand the host immune response to
Brucellosis is a reemerging worldwide zoonotic disease caused by the genus
Immunological studies of
Therefore, in this study, an
In the coculture model, ~5.0 × 105 cells/well of the D17 cell line (ATCC CCL-183) were seeded onto the apical side of a Transwell insert (Transwell permeable support; Corning, MA, USA) and incubated for 3 h in DMEM (Gibco, NY, USA) containing 15% fetal bovine serum (FBS; Gibco, NY, USA) at 37°C in a humidified chamber containing 5% CO
In the single cell line culture model, 5.0 × 105 cells/well of the DH82 cell line were seeded onto one well of a 12-well plate (Corning, MA, USA) with DMEM containing 15% FBS. After the DH82 cell line was stabilized, it was stimulated by using DPBS (negative control) and
Each experiment was conducted three times.
The D17 cell line and DH82 cell line were purchased through ATCC (
The infection of
After 2, 12, and 24 h of the incubation, total RNA was extracted from the DH82 cell line using the RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the instructions of the manufacturer. RNA purity and integrity were evaluated by determining the OD 260/280 ratio and an analysis using the Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA). The total RNA concentration was measured by using the Quant-IT Ribogreen (Invitrogen, CA, USA). To determine the integrity of the total RNA, the TapeStation RNA Screen Tape system (Agilent Technologies, CA, USA) was used. Only high-quality RNA preparation, with RNA integrity numbers (RINs) > 7.0, was used for the RNA library construction.
The libraries were prepared for 100-bp paired-end sequencing using a TruSeq Stranded mRNA Sample Preparation Kit (Illumina, CA, USA). Specifically, mRNA molecules were purified and fragmented from 1 μg of total RNA using oligo (dT) magnetic beads. The fragmented mRNAs were synthesized as a single-stranded complementary DNA (cDNA) using a Random Hexamer Primer (Kapa Biosystems, MA, USA). By applying cDNA as a template for the second strand synthesis, a double-stranded cDNA was prepared. After sequential end repair, A-tailing, and adapter ligation, the cDNA libraries were amplified by using a PCR. The quality of these cDNA libraries was evaluated using the Agilent 2100 Bioanalyzer (Agilent, CA, USA). These values were quantified using the KAPA library quantification kit (Kapa Biosystems, MA, USA) according to the library quantification protocol of the manufacturer. Following the cluster amplification of denatured templates, sequencing was progressed as paired end (2 × 150 bp) by using an Illumina platform sequencer (Illumina, CA, USA). Each gene was compared with the results of 0 h to proceed with the analysis.
Low-quality reads were filtered according to the following criteria: reads containing more than 10% of the skipped base reads (marked as “N”s'), reads containing more than 40% of the bases whose quality score was < 20, and reads whose average quality scores are per read was < 20. The whole filtering process was performed using the in-house scripts.
The filtered reads were mapped to the reference genome species using the aligner TopHat (
The gene expression level was measured by Cufflinks v2.1.1 (
Differentially expressed gene (DEG) analysis was performed by using Cuffdiff (
The gene ontology (GO) database classifies the genes according to the three categories, such as biological process (BP), cellular component (CC), and molecular function (MF), and provides information on the functions of genes. To characterize the identified genes from the DEG analysis, a GO-based trend test was carried out using the Fisher's exact test (
The data were analyzed using IPA (Qiagen, Hilden, Germany,
The data were analyzed by using IPA (Qiagen Inc., Hilden, Germany,
The expression of levels of five genes, IL6, CCL5, CXCL10, CXCL8, and IL1B, in RNA-seq at 2, 12, and 24 time points were compared with those from the quantitative real-time PCR (qRT-PCR) of the two different experiments. The qRT-PCR was performed by using 1 μl of cDNA, a Rotor-Gene SYBR Green PCR Kit (Qiagen Inc., Hilden, Germany), and a Rotor-Gene Q real-time PCR cycler (Qiagen, Hilden, Germany) (
Canine forward and reverse primers for validation by quantitative real-time PCR.
IL-6 | 5′-CTGGCAGGAGATTCCAAGGAT-3′ | 5′-TCTGCCAGTGCCTCTTTGC-3′ | |
CCL5 | 5′-CAGAAGAAATGGGTGCGGGAGTA-3′ | 5′-CAAGAAGCAGTAGGAAAGTTTGCATG-3′ | |
CXCL10 | 5′-TCCTGCAAGTCCATCGTGTC-3′ | 5′-ATTGCTTTCACTAAACTCTTGATGGTC-3′ | |
CXCL8 | 5′-GACAGTGGCCCACAATGTGAAAACTC-3′ | 5′-GTTGTTTCACGGATCTTGTTTCTCAGC-3′ | |
IL1β | 5′-GGAAATGTGAAGTGCTGCTGCCAA-3′ | 5′-GCAGGGCTTCTTCAGCTTCTCCAA-3′ |
Statistical significance of internalization was analyzed by using the Student's
The invasibility of the
Each gene was analyzed for a change in the expression through the fold change value compared to 0 h. By stimulating cells with
Differentially expressed genes (DEGs) result.
Differentially expressed genes (DEGs) identified for each model and each time.
FHIT | 89.264 | 83.286 | 86.223 | – | – | – |
ACOD1 | 64.445 | 18.126 | 53.446 | 156.498 | 71.012 | – |
CXCL10 | 55.330 | 26.723 | – | 168.897 | 95.010 | – |
CCL4 | 45.887 | 13.642 | 410.148 | 149.086 | 184.823 | 302.334 |
OLR1 | 33.128 | 28.840 | 270.597 | 49.522 | 36.504 | 57.282 |
FFAR2 | 29.243 | 9.646 | 88.035 | 99.044 | – | – |
CCL5 | 22.943 | 18.636 | 63.119 | 63.558 | 81.572 | 85.627 |
SAA1 | 22.471 | 28.051 | 198.088 | 95.010 | 436.549 | 826.001 |
CCL3L3 | 20.393 | 22.316 | 719.076 | 60.969 | 286.026 | 588.134 |
IL1A | 19.427 | 13.454 | 704.277 | 84.449 | 337.794 | 608.874 |
SAA1 | 17.388 | 21.407 | 116.970 | 74.028 | 328.557 | 481.036 |
NEURL3 | 16.679 | 13.086 | 54.569 | 27.284 | – | – |
IL1B | 16.679 | 13.929 | 1002.926 | 77.708 | 1351.176 | 1144.102 |
SAA1 | 16.223 | 24.251 | 116.970 | 86.223 | 354.588 | 398.932 |
IL6 | 14.026 | 12.126 | 202.251 | 54.569 | 421.679 | 471.136 |
CXCL8 | 12.295 | – | 89.884 | 34.060 | 138.141 | 181.019 |
GPR84 | 12.042 | 10.556 | 88.035 | 19.562 | 52.346 | – |
FST | 10.056 | – | – | 25.634 | 43.111 | – |
CXCL5 | 8.456 | 10.483 | 97.681 | 16.450 | 174.853 | 138.141 |
TNFAIP2 | 7.516 | – | – | 19.293 | – | – |
STEAP4 | 7.062 | – | – | 23.425 | – | – |
RASSF6 | 6.409 | – | – | 18.126 | 45.887 | – |
PTGS2 | 6.320 | – | 272.479 | 21.857 | 95.670 | 396.177 |
IL1RN | 5.242 | – | 58.081 | 17.030 | – | – |
EGLN3 | – | 25.813 | 110.661 | −3.182 | – | 108.383 |
TSHZ2 | – | 7.621 | 56.493 | – | – | – |
IL23A | – | – | 1009.902 | 29.041 | 76.639 | 1418.352 |
SRGN | – | – | 91.139 | – | – | 56.103 |
OSM | – | – | 88.035 | – | – | 237.207 |
F3 | – | – | 48.840 | – | – | 75.061 |
LIF | – | – | 48.503 | – | 38.586 | – |
INHBA | – | – | – | – | 134.364 | 240.518 |
MMP3 | – | – | – | – | 54.569 | 247.280 |
MMP13 | – | – | – | – | 44.324 | 83.865 |
MMP10 | – | – | – | – | 38.854 | 168.897 |
FCRL2 | – | – | – | – | 36.252 | 64.000 |
SMPDL3A | – | – | – | – | 33.359 | 53.446 |
SERPINB2 | – | – | – | – | 31.341 | 59.714 |
DEGs identified for each model and each time.
SIRPB1 | −4.823 | −10.126 | ||||
HTR1D | −2.657 | −5.464 | −19.293 | −27.096 | ||
MLLT11 | −2.297 | −3.506 | ||||
SORBS2 | −2.219 | −5.856 | ||||
TMEM273 | −2.189 | – | ||||
GRIA4 | −2.144 | −3.605 | ||||
ADGRD1 | −4.724 | −6.727 | ||||
ANKRD66 | −4.347 | −7.062 | ||||
MRVI1 | −4.141 | −9.849 | −12.381 | |||
WDR31 | −4.000 | −11.158 | ||||
FMN2 | −3.580 | −9.254 | −17.388 | |||
LGR6 | −3.531 | −3.294 | −8.340 | |||
FGFR2 | −3.506 | −18.507 | −12.126 | |||
DHRS3 | −3.387 | −3.227 | −9.448 | |||
SLC27A6 | −3.053 | −9.254 | −12.817 | |||
SERTAD4 | −33.359 | −7.516 | −49.867 | |||
ADGRF1 | −26.909 | −7.516 | −170.072 | |||
FZD1 | −15.562 | −15.032 | ||||
CD180 | −13.929 | −19.973 | −38.055 | |||
SMAD6 | −12.906 | −6.916 | ||||
SYPL2 | −11.876 | −13.929 | ||||
HUNK | −11.392 | −6.964 | −16.679 | |||
TRPM2 | −10.411 | −8.515 | −24.761 | |||
PADI4 | −10.267 | −12.729 | ||||
RAB36 | −7.210 | −7.413 | ||||
NIPAL1 | −7.013 | −10.339 | ||||
CAVIN1 | −3.160 | −6.964 | ||||
TRIM72 | −7.210 | −40.224 |
Raw files and normalized data sets are available from the Gene Expression Omnibus (GEO)
Of all DEGs that mapped to the Ingenuity Knowledge Base and passed the data set filter (
Major canonical pathways related to immune response.
Communication between adaptive immune cells and innate immune cells | 1.10E-15 | NaN | 4.74E-11 | NaN | 1.17E-09 | NaN | 1.98E-11 | NaN | 3.52E-08 | NaN | 7.77E-07 | NaN |
Acute phase responses | 5.49E-08 | 2.714 | 2.15E-04 | 3.317 | 5.77E-06 | 2.828 | 2.76E-10 | 2.683 | 1.87E-09 | 2.556 | 3.69E-04 | 2.828 |
Dendritic cell maturation | 2.64E-12 | 3.742 | 1.61E-03 | 2.714 | 1.07E-06 | 4.564 | 5.82E-09 | 4.359 | 1.59E-07 | 4.041 | 1.86E-05 | 4.333 |
Toll-like receptor signaling | 1.02E-09 | 1.633 | 1.56E-06 | 2.121 | 3.38E-09 | 2.668 | 2.30E-09 | 2.333 | 7.04E-08 | 2.887 | 1.79E-04 | 2.887 |
TREM1 signaling | 1.18E-15 | 3.207 | 9.47E-08 | 3.606 | 3.83E-13 | 5.112 | 3.35E-14 | 3.771 | 3.42E-09 | 3.578 | 8.24E-08 | 4.315 |
Role of pattern of recognition receptors of bacteria and viruses | 4.03E-10 | 2.828 | 2.48E-11 | 2.887 | 1.65E-12 | 3.838 | 9.08E-09 | 2.530 | 3.81E-12 | 2.500 | 8.01E-11 | 3.000 |
NF-κB signaling | 4.44E-10 | 2.138 | 1.37E-05 | 2.500 | 4.08E-12 | 2.480 | 7.09E-09 | 1.147 | 3.83E-12 | 2.000 | 2.69E-07 | 3.429 |
IL-6 signaling | 9.64E-10 | 3.464 | 2.68E-04 | 3.317 | 1.55E-08 | 4.352 | 1.72E-12 | 4.025 | 1.62E-12 | 3.772 | 1.04E-05 | 4.596 |
Role of cytokines in mediating communication between immune cells | 1.41E-08 | NaN | 1.47E-05 | NaN | 8.89E-03 | NaN | 2.99E-06 | NaN | 2.05E-04 | NaN | 1.86E-02 | NaN |
HMGB1 signaling | 9.79E-11 | 3.464 | 6.58E-07 | 3.606 | 6.45E-09 | 3.528 | 2.08E-11 | 3.638 | 8.80E-14 | 3.286 | 3.20E-06 | 3.528 |
Signaling related to dendritic cell maturation, which is involved in the host innate immunity, was generally high in all models (
Ingenuity pathway analysis of the dendritic cell maturation signaling pathway in the DH82 cell line treated with
In both the models, the expression of TLR signaling was observed to increase with time, and the expression was more pronounced in the single cell culture model (
Ingenuity pathway analysis of the Toll-like receptor (TLR) signaling pathway in the DH82 cell line treated with
TREM1 signaling, similar to the other pathways, was found to increase gradually over time in both the models, especially in the 24-h results of the coculture model (
Ingenuity pathway analysis of the TREM1 signaling pathway in the DH82 cell line treated with
In the comparison analysis, the 2-h results of both the culture models identified the pathways that are closely related to the cell immune responses, such as dendritic cell maturation, HMGB1 signaling, TREM1 signaling, IL-1 signaling, acute-phase response, the role of pattern recognition receptors (PRRs) in the recognition of bacteria and viruses, B-cell receptor signaling, and the IL-8 signaling pathway. Gene expression related to a communication between the innate and the adaptive immune cell was confirmed. At the 2- and 12-h time points of the early infection stage, the expression of acute-phase response signaling was high. The 12-h and the 24-h culture model also showed similar results to the 2-h culture model, but in the case of TNFR2 signaling, a differential regulation of the cytokine production in macrophage and T-helper cells by IL-17A and an acute-phase response, the 24-h model showed no high expression. In each model, the expression of canonical pathways with respect to time was commonly observed. In a single-culture model, the expression of genes associated with an acute-phase response was identified at all-time points. In the coculture model, the expression of genes was confirmed up to 12 h, but no expression was observed in the 24-h result. Most of the results showed the expression of the osteoarthritis pathway and neuroinflammation signaling pathway among the pathways that are not related to the cell immune response (
Comparative analysis of canonical pathway by each model and time period by
Changes in various DEGs related to dendritic cell maturation were identified. In FcγR, a difference in the expression was clearly observed according to the model. In the coculture model, the expression of FcγR was inhibited at the 2-h time point, but the expression was increased at 12- and 24-h time points. This finding is observed because the expression of two DEGs, except for FCGR1A, among FCGR1A, FCGR2B, and FCGR3A, which are related to FcγR and exhibit expression, is reduced (fold change value, FCGR1A: 1.240, FCGR2B:−2.099, and FCGR3A:−1.257). In contrast, in the single cell line culture model, the expression of FcγR increased at the 2-h result, but it was difficult to determine the expression pattern at 12- and 24-h results. This difficulty was due to the increase in FCGR1A at 2 h, but an increase in FCGR1A but a decrease in FCGR2B at 12 h (fold change value at 2 h, FCGR1A: 1.828, fold change values at 12 h, FCGR1A: 3.411, FCGR2B: −2.888). The 24-h results of the single cell line culture model were similar to the 12-h results, but the expression of FCGR1A increased but the expression of FCGR2B decreased (fold change value at 24 h, FCGR1A: 4.993, FCGR2B: −4.627).
Among the TREM1 signaling pathways, differences in pathways related to phagocytosis and apoptosis in the host were found. The 2-h results in the coculture model did not confirm the expression of TREM1- and TLR-related genes in relation to DEGs. However, at 12 h, the expression increased as the expression of TLR-related DEGs was confirmed. At 24 h, the expression of the pathway increased significantly, as the expression of not only TLR-related DEGs but also TREM1 increased. In the single cell culture model, the expression of TLR-related DEGs in the pathway associated with phagocytosis and apoptosis decreased by 2 h. However, as TLR-related DEGs increased at 12 and 24 h, the expression of related pathways also increased significantly.
In the case of TLR signaling, the differences were observed depending on the model. In the coculture model, the expression was reduced in the center of the TRAP6 gene for the 2- and 12-h results. However, the 24-h results showed an overall increase in the expression. When looking at the pattern over time, it was confirmed that the expression of TLR-associated DEGs gradually increased. The expression of TLR-related DEGs was not confirmed in the 2-h results, but the expression of TLR-related DEGs was confirmed in the subsequent results. The fold change values of TLR 1, 2, 3, 4, 6, 7, and 8 DEGs at 12 h were 1.602, 1.329, 3.531, 1.257, 1.474, 8.877, and 2.585, respectively. The expression of TLR 1, 2, 4, 5, 6, 7, and 8 DEGs was confirmed at 24 h, and the fold change values were 5.278, 2.990, 1.580, 2.751, 3.864, 42.224, and 5.426. All expression levels of TLR-related DEGs, which are commonly expressed, increased over time. In the single cell line culture model, TLR signaling was found to have an overall increase. When fold change values were confirmed at the genetic level, it was confirmed that the 2-h result was downregulated in some TLR-related DEGs (fold change values, TLR 1: −1.753, TLR 2: −1.301, TLR 4: 1.301, TLR 6: −2.395, and TLR 8: 1.347). The fold change values of DEGs increased over the 12-h period. The fold change value of TLR 2, TLR 7, and TLR 8 was 2.250, 22.785, and 3.272, respectively. The expression of more diverse TLR-related DEGs was observed to increase at 24 h. The expression of the TLR 1, 2, 4, 6, 7, and 8 DEGs was increased, and the fold change value of each was 4.141, 2.732, 1.223, 2.329, 29.651, and 4.563, respectively.
In addition, the expression of the “role of macrophages, fibroblast, and endothelial cells in rheumatoid arthritis,” “role of osteoblasts, osteoclasts, and chondrocytes in rheumatoid arthritis,” and the “neuroinflammation signaling pathway” associated with arthritis and neurological symptoms caused by the known
The RNA-seq results were verified following a qRT-PCR with samples from the two different experiments. The results of the five selected genes from the two analytic methods were highly correlated (
Validation of gene expression by RNA-sequencing (RNA-seq) and quantitative real-time PCR. The relative expression was compared to that observed in the controls to determine the fold change in the expression for each gene. This indicates the two independent experiments.
In this study, gene expressions were analyzed in the DH82 cell line treated with
In the aforementioned pathways, the expression of pathways, such as “communication between the innate and the adaptive immune cell,” has been confirmed based on the same pathway, which suggests that the host immune mechanism is closely related to the innate immunity and the activity of the adaptive immunity following pathogen invasion. It can be observed that signaling related to acute-phase response is clearly expressed at 2 and 12 h in both the models by a comparison analysis. This finding suggests that
In addition, this effect is known to be closely related to TREM1 signaling. TREM1 signaling is associated with pro-inflammatory cytokine activation. TREM1 activation triggers signals such as JAK2 and STAT3 and affects signals, such as NF-κB. TREM1 signaling is closely related to TLR signaling, and the synergy of the two produces neutrophil degranulation, phagocytosis, and the respiratory burst but also produces pro-inflammatory cytokines (
Dendritic cells are among the most efficient antigen-presenting cells (APCs) of the immune response system. Immature dendritic cells are responsible for capturing and processing antigens and for presenting major histocompatibility complex (MHC)-specific antigens in secondary lymphoid organs. After antigen capture, dendritic cells mature, antigen capture capacity is downregulated, and costimulatory molecules and MHC class I and II molecules are upregulated to enhance the antigen presentation. Matured dendritic cells have the ability to produce the cytokines that can enhance the innate and the adaptive immune response and have the ability to cross exogenous antigens to cytotoxic lymphocytes (
In many situations, dendritic cells are simultaneously stimulated by antigens and danger signals. This stimulation occurs, the release of the TLR ligand occurs and the innate sensor is associated with the endosomes and phagocytosis. In fact, the expression of various TLR DEGs was increased in the dendritic cell maturation signaling pathway identified in this study, and the expression of CD40 and MAPK pathways was increased. Changes in various DEGs related to dendritic cell maturation were identified. The expression of DEGs for related cytokines, such as IL-1, IL-6, IL-10, and IL-12, was found to be increasing in all the results, which induced dendritic cell maturation. FcγR is commonly known to be associated with the activation of dendritic cells, and this study has identified the expression of MHC I, II, and CD40 with the actual expression of FcγR (
TREM1, a triggering receptor expressed on myeloid cell 1, is an activation receptor expressed on myeloid cells included in the Ig superfamily (
The TLR family is a part of the widely studied PRR class. TLRs have been identified in 10 humans and 12 murines, which play a role in recognizing intracellular and extracellular pathogen-associated molecular patterns (PAMPs). TLRs 1, 2, 4, 5, 6, and 11 are expressed in cell membranes, and TLRs 3, 7, 8, and 9 are present in endosomes in cells (
The pathways characterized by a manifestation in major canonical pathways are mostly associated with pro-inflammatory cytokines, which are known to be associated with the early immune response of a host. These results show that the infection of
As dendritic cell maturation is performed, the TLR signaling expression is increased to play an antigen-presenting role. In this study, the expression of TLR signaling gradually increased as dendritic cell maturation increased in both models. In particular, TLR7 was found to change the fold change value up to 40 times, unlike other TLR-related DEGs. Recent studies on TLR3 and TLR7 have shown that they are involved in the detection of
As is well-known,
Based on the RNA-seq analysis, the host immune response to the infection of
By using the coculture model, a model similar to the
The results of this study have been analyzed at the genetic level of the host immune response, free from the investigation of the host simple immune response, isolation, and epidemiology. High expression of pathways, such as dendritic cell maturation, TREM1 signaling, and TLR signaling, provided more specific evidence of the host early immune response to
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at:
All experiments were reviewed and approved by the Seoul National University Institutional Biosafety Committee (protocol: SNUIBC-R180912-3).
WP conceived and designed the experiments, data curation, formal analysis, software, and writing the original draft. SK data curation, formal analysis, and software. SS data curation and formal analysis. HY conceptualization, project administration, supervision, and writing—review and editing. All authors contributed to the article and approved the submitted version.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The authors would like to thank the BK21 PLUS and the Veterinary Research Institute of the College of Veterinary Medicine, Seoul National University for their assistance in the research.
The Supplementary Material for this article can be found online at: