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ISSN: 2329-891X
Journal of Tropical Diseases & Public Health
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Proteomic Profile of Circulating Immune Complexes in Dengue Infected Patients

Nguyen Tien Huy1,2#, Huynh Trung Trieu1#,, Kenta Okamoto3, Tran Thi Hai Ninh1, Tran Thi Ngoc Ha1, Kouichi Morita3, Vu Thi Que Huong3, Nguyen Thi Phuong Lan4, Tran Thi Thuy5, Cao Thi Phi Nga6, Mihoko Kikuchi1, Naotaka Kuroda7, Juntra Karbwang2, Kaname Ohyama7,8* and Kenji Hirayama1,9*

1Department of Immunogenetics, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Japan

2Department of Clinical Product Development, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Japan

3Department of Virology, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Japan

4Laboratory of Arbovirus, Pasteur Institute in Ho Chi Minh City, Vietnam

5Children’s Hospital No.2, Ho Chi Minh City, Vietnam

6Center for Preventive Medicine, Vinh Long, Vietnam

7Course of Pharmaceutical Sciences, Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan

8Nagasaki University Research Centre for Genomic Instability and Carcinogenesis (NRGIC), Nagasaki, Japan

9Global COE program, Nagasaki University, Japan

#These authors contributed equally to this work

*Corresponding Author:
Kaname Ohyama
Course of Pharmaceutical Sciences
Nagasaki University
Research Centre for
Genomic Instability and Carcinogenesis
Nagasaki University, Japan
E-mail: [email protected]

Kenji Hirayama
Department of Immunogenetics
Institute of Tropical Medicine (NEKKEN)
Nagasaki University, Japan
E-mail: [email protected]

Received Date: June 13, 2013; Accepted Date: June 24, 2013; Published Date: June 27, 2013

Citation: Huy NT, Trieu HT, Okamoto K, Ninh TTH, Ha TTN, et al. (2013) Proteomic Profile of Circulating Immune Complexes in Dengue Infected Patients. J Trop Dis 1:109. doi: 10.4172/2329-891X.1000109

Copyright: © 2013 Huy NT, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Dengue virus is a flavivirus that causes Dengue Fever (DF), Dengue Hemorrhagic Fever (DHF), and Dengue Shock Syndrome (DSS), a serious public health problem in many countries. An auto-immune response is thought to play an important role in the pathogenesis of severe dengue and the increased level of Circulating Immune Complexes (CIC) in dengue infected patients. Therefore, a proteomic analysis of proteins in the CIC can provide a better knowledge of the pathogenesis and a potential biomarker for severe dengue. A proteomic strategy based immune complexome analysis was performed to analyze the composition of CIC from plasma of fifteen dengue infected patients and five healthy control children. A total of 111 proteins were identified in the CIC from all individuals, with 17 proteins shared by healthy, DF, DHF, and DSS groups. All detected proteins were of similar relative proportion in the CIC of healthy, DF, DHF, and DSS groups. The results also revealed a high similarity of CIC profiles between four groups of subjects when classifying identified proteins according to cellular components or functional protein categories. These results showed no evidence to support the roles of CIC mediated by auto-immune response in the pathogenesis of severe dengue.

Keywords

Auto-immune; Circulating immune complexes; Dengue; DSS; Proteome; Severity

Introduction

Dengue infection has been becoming a serious public health problem in many countries with a dramatic increase globally. There are approximately 2.5 billion people at risk of dengue in over 100 countries. It is estimated that over 20,000 deaths occur every year due to this disease [1]. Dengue hemorrhagic fever (DHF) is the severe form of dengue infection, which is characterized by plasma leakage possibly inducing hypovolemic shock, known as dengue shock syndrome (DSS). Some patients infected by dengue virus develop dengue fever (DF), some develop DHF and about 20-30% of them, who suffer from DHF, develop shock [2]. At present, there is no approved dengue vaccine nor antiviral drug, although some potential solutions are currently being studied [3]. Early treatment, vector control, and educational program are the only methods to reduce global disease burden and mortality [4-7]. Therefore, it is important to understand the pathogenesis of dengue infection in order to find an appropriate management.

There are many factors contributing the pathogenesis of dengue virus infection, including virulence factor, secondary infection [8], host genetic factors [9-11], host immune response [12-14] and physiological factors [15]. An auto-immune response has also been proposed as an underlying mechanism in the pathogenesis of dengue infection [16-22]. In this hypothesis, immune complexes (IC) formed by auto-antibodies and human proteins are the main feature resulting in severity of disease. Ohyama et al. proposed a novel proteomic strategy (immune complexome analysis) that entails the separation of CICs from blood, direct tryptic digestion, and nano-liquid chromatography-tandem mass spectrometry [23]. They analyzed the CICs in rheumatoid arthritis which is a representative autoimmune disease and found two CICs which includes antigens specifically detected in that disease [23,24]. Therefore, it is important to analyze the composition of CIC in dengue infected patients not only to be used as diagnostic tools, but also to understand new molecular pathways involved in diseases. In this study, an immune complexome analysis of plasma from different groups of healthy, DF, DHF, and DSS were performed and compared using a proteomic approach.

Materials and Methods

Study design

The current study was performed at the Infectious Department of Pediatric Hospital Number 2, Ho Chi Minh City, and the Center for Preventive Medicine in Vinh Long province, Vietnam. It was a hospital-based case control study in children aged 6 months to 15 years with suspected dengue infections from 2006 to 2007. The study was approved by the institutional ethical review committees of the Institute of Tropical Medicine, Nagasaki University, Pediatric Hospital Number 2, Center for Preventive Medicine in Vinh Long, and the Pasteur Institute in Ho Chi Minh City. Written informed consent was required from the parents or guardians on the behalf of all children participants involved in the study. All experiments were conducted in accordance with the Declaration of Helsinki.

The entry criteria were children with suspected dengue infection based on clinical symptoms. After admission, the patients were diagnosed using standardized dengue virus isolation, serology techniques, and RT-PCR assay as previously described [10,25]. A positive confirmed laboratory test was made when the result of dengue virus isolation was positive or RT-PCR assay determined a dengue serotype, or when there was a positive anti-DV IgM antibody-capture ELISA, a positive seroconversion, or a ≥ 4-fold increase in anti-DV IgG titres between acute and convalescent samples. The molecular detection of the dengue virus genome was performed using a Ready- To-Go reverse transcriptase PCR test kit (Amersham, MA, USA) [26]. Dengue virus isolation was carried out on the C6/36 cell line and viral identification was detected by a direct and indirect fluorescent antibody technique with monoclonal antibodies supplied by the Centers for Disease Control and Prevention (For Collins, CO, USA) [27]. Serological assays for anti-DV IgM and IgG by IgM-and IgG-capture ELISA were conducted by an in-house Kit of the Pasteur Institute (HCMC) on both the acute and convalescent plasma samples, collected at ≥ 3-day intervals [28]. The cases were defined as secondary infection if the DV IgM/IgG ratio was <1.8.

The severity of the disease was classified according to the WHO (1997) classification criteria for dengue virus infection [29]. Plasma samples were obtained from five patients in each groups of DF, DHF, and DSS patients during the transition period of fever to defervescence. In addition, school children living in Ho Chi Minh City who had no symptoms of any diseases and a negative standardized dengue serological test were chosen as a healthy control group. Five samples in each group have been suggested as the minimal number of samples in the shotgun proteomic study [30]. This number has been also used in several proteomic analysis [31-33].

Sample collection and preparation

Blood samples were drawn into EDTA tubes. Plasma was separated by centrifugation at 3000 rpm for 10 min, stored at -80°C and centrifuged again at 3000 rpm for 10 min before being used for CIC isolation.

CIC was isolated by magnetic beads with immobilized protein A/G (an equal mixture of PureProteome™ Protein A and PureProteome™ Protein G Magnetic Bead Systems; Millipore) as previously described [23] and illustrated in Figure 1. Briefly, plasma (5μL) was diluted with 90 μL PBS (9.0 mM Na2HPO4, 2.9 mM NaH2PO4, and 137 mM NaCl) and incubated with magnetic beads (20 μL) for 30 min at room temperature with gentle mixing. The unbound fraction was washed 3 times with 500 μL PBS using a magnet. The beads with bound CIC were recovered and resuspended in 100 μL of 10 mM dithiothreitol and incubated at 56°C for 45 min. The sample was next added by 100 μL of 55 mM iodoacetamide and incubated at room temperature for 30 min in the dark. Trypsin (Promega) was further added into the sample at a final concentration of 0.5 mg/mL. After an overnight incubation at 37°C, the sample was subsequently added with 5 μL of 5% formic acid to stop the digestion. The supernatant containing the peptide digests of CIC was dried by a centrifugal vacuum evaporator. The sample was dissolved in 10 μL of 0.3% formic acid and was centrifuged at 20,000xg for 10 min to collect 5 μL of supernatant for injection into the LC-MS/ MS analysis.

tropical-diseases-community-methodology

Figure 1: Flow diagram of methodology in this study.

Mass Spectrometric Analysis and Database Search

The MS and tandem-MS (MS/MS) spectra of trypsinized peptides were obtained using the NanoFrontier nLC and NanoFrontier eLD Liquid Chromatography Mass Spectrometer (Hitachi Hightechnologies, Tokyo, Japan). The nano-Liquid Chromatography/ ElectroSpray Ionization/ Linear Ion Trap/ Time of Flight (nLC-ESI/LIT/ TOF) and collision induced dissociation (CID) modes were used for MS detection and peptide fragmentation as previously described [34]. In the nLC-ESI/LIT/TOF, the trypsinized peptides (5 μL) were trapped on monolith trap column [C18-50-150 column, (0.05 mm I.D.x150 mm L). Hitachi High-technologies] and separated by a nano-capillary column [NTCC-360/75-3-123, (0.075 mm I.D.x100 mm L, particle diameter 3 μm), Nikkyo Technos Co., Ltd, Tokyo, Japan] at a flow rate of 200 nL/min. The peptides were then eluted using a stepwise acetonitrile (ACN) gradient (mobile phase A: 2% ACN, 0.1% formic acid; mobile phase B: 98% ACN, 0.1% formic acid, the A: B concentration gradient was 100:0 at zero min and 0:100 at 60 min, respectively). In the nLCESI/ LIT/TOF system, the eluted peptides were ionized with a capillary voltage of 1700 V and detected in a detector potential TOF range of 2050-2150 V.

Raw MS and MS/MS spectra were converted into Mascot generic format (mgf) using a Data Processing software 2008 (Hitachi Hightechnologies) and subsequently searched using the MS/MS Ion Search provided by MASCOT Sequence Query sever version 2.3 against the Swiss-Prot database (human and dengue virus only). The following search parameters were used, enzyme: trypsin, variable modifications: carbamidomethylation (C) and oxidation (M), mass values: monoisotopic, protein mass: unrestricted, peptide mass tolerance: ± 0.5 Da, fragment mass tolerance:±0.2 Da (CID data), maximum missed cleavages: 1 and Instrument type: ESI-TRAP.

For MASCOT output, significant peptides were determined by the peptides score from the probability-based molecular weight search (MOWSE) which identifies proteins from the molecular weight of peptides created by the trypsin digestion [35]. Peptide score >25 indicated an identity or extensive homology (p<0.05). Further stringency was added by eliminating any single peptide that could be assigned to more than one protein. The protein identifications were further checked manually in the database for possible redundancies including multiple names and homologies. Keratins and trypsin were considered as contaminating proteins and were excluded from our analysis. The Venn diagrams were created using a web-based Venny program [36] (Figure 1).

Functional Annotation of Identified Proteins

Identified proteins of all individuals in each group were combined and were characterized into molecular functions and cellular components using an online based UniProt-GOA program.

Statistical Analysis

Kruskal-Wallis test was used for comparison of three or more unmatched groups. Fisher´s exact test was used for pairwise comparison of two unmatched groups as the sample size was small in each group. The difference was considered significant at p<0.05.

Results

The schematized Fig. 1 gives information on the design and experimental procedures. A total of 20 subjects, including 5 DF, 5 DHF, 5 DSS patients, and 5 healthy children were enrolled in this study, and their characteristics are summarized in Table 1. All plasma samples of dengue patients were collected during the transition period of fever to defervescence (day 3-5), which were not significantly different between dengue groups (p-value>0.10, Kruskal-Wallis test).

  HT DF DHF DSS
Number of patients 5 5 5 5
Agea 5 (3-8) 10 (5-13) 9 (8-11) 7 (5-11)
Male : Female 3:2 1:4 4:1 1:4
Day of illness on admissiona   4(2-4) 4 (4-4) 4 (3-5)
Day of samplinga   4(3-5) 4 (4-4) 4 (3-5)
Serology diagnosis        
Primary infection   0 2 0
Secondary infection   5 3 5
Dengue serotype        
DEN-1   1 2 3
DEN-2   1 1 1
DEN-3       1

Table 1: Clinical characteristics of subjects.

An immune complexome analysis of plasma from patients with dengue virus infection and healthy individuals were performed. A total of 35, 60, 49, and 46 proteins were identified in the healthy, DF, DHF, and DSS groups, respectively, resulting in a total identification of 111 identified proteins(Figure 2 and Table 2). Analysis of the Venn diagrams showed that only 17 identified proteins were overlapped in all groups of DF, DHF, and DSS (Figure 2). Among identified proteins (n=18) that were detected in only patients with DSS, only one protein (YLP motif-containing protein 1) appeared in two patients, while other 17 proteins appeared in only one patient with DSS. Four proteins (serum albumin, complement C4-A, immunoglobulin J chain, and nesprin-1) were detected in patients with DF, DHF, and DSS but not in healthy individuals, however, all of four proteins were only identified in less than three of five patients in each group of DF, DHF, and DSS. All detected proteins were of similar relative frequency in the circulating immune complexome of healthy, DF, DHF, and DSS groups (p-value >0.10, Kruskal-Wallis test). Pairwise comparison of all detected proteins showed no significant difference in the frequency of particular protein between groups (p-value>0.10, Fisher´s exact test).

tropical-diseases-community-proteins

Figure 2: Overlap of identified proteins in different groups. Venn diagram showing total proteins identified in at least one individual from each group of healthy (blue), DF (yellow), DHF (green), and DSS (red). Numbers of identified proteins were shown in different overlaps between groups. Table 2 shows the lists of identified proteins in this study.

No. Protein ID Protein MW Frequency
Healthy DF DHF DSS
1 ALBU_HUMAN Serum albuminc 69321 0/5  1/5  1/5  2/5
2 ARID2_HUMAN AT-rich interactive domain-containing protein 2b 197268 0/5 0/5 0/5  1/5
3 ASXL1_HUMAN Additional sex combs like 1 165432 0/5  1/5 0/5 0/5
4 AT7L3_HUMAN Ataxin-7-like protein 3 38651 0/5  1/5 0/5  1/5
5 BPAEA_HUMAN Bullous pemphigoid antigen 1, isoforms 6/9/10 590626 0/5  1/5 0/5 0/5
6 BPTF_HUMAN Nucleosome-remodeling factor subunit BPTF 338262 0/5  1/5  1/5 0/5
7 BRD7_HUMAN Bromodomain-containing protein 7 74092 0/5  1/5  1/5 0/5
8 C1QB_HUMAN Complement C1q subcomponent subunit Bb 26442 0/5 0/5 0/5  1/5
9 C1QC_HUMAN Complement C1q subcomponent subunit Ca 25757  3/5  3/5  3/5  1/5
10 C1QR1_HUMAN Complement component C1q receptor 68515 0/5 0/5  1/5 0/5
11 CB016_HUMAN Uncharacterized protein C2orf16 224321 0/5  1/5 0/5 0/5
12 CCD68_HUMAN Coiled-coil domain-containing protein 68 38845  1/5  3/5  3/5 0/5
13 CE042_HUMAN Uncharacterized protein C5orf42 236516 0/5  1/5 0/5 0/5
14 CHRD_HUMAN Chordin 101966 0/5  1/5 0/5  1/5
15 CK042_HUMAN Uncharacterized protein C11orf42 36358 0/5  1/5 0/5 0/5
16 CO4A_HUMAN Complement C4-Ac 192650 0/5  1/5  2/5  2/5
17 COBA1_HUMAN Collagen alpha-1(XI) chain 180954  1/5  2/5  1/5  1/5
18 CP2E1_HUMAN Cytochrome P450 2E1 56812 0/5  1/5 0/5 0/5
19 CSTFT_HUMAN Cleavage stimulation factor 64 kDa subunit, tau variant 64396 0/5  1/5 0/5 0/5
20 DI3L1_HUMAN DIS3-like exonuclease 1b 120711 0/5 0/5 0/5  1/5
21 DMD_HUMAN Dystrophin 426692 0/5  1/5 0/5 0/5
22 DOCK2_HUMAN Dedicator of cytokinesis protein 2d 211948  1/5 0/5 0/5 0/5
23 DYH6_HUMAN Dynein heavy chain 6, axonemal 475982 0/5 0/5  1/5 0/5
24 DYHC1_HUMAN Cytoplasmic dynein 1 heavy chain 1b 532072 0/5 0/5 0/5  1/5
25 ELMO1_HUMAN Engulfment and cell motility protein 1b 83829 0/5 0/5 0/5  1/5
26 EMIL3_HUMAN EMILIN-3 82596 0/5 0/5  1/5 0/5
27 EPHAA_HUMAN Ephrin type-A receptor 10 109716 0/5  1/5 0/5 0/5
28 FA156_HUMAN Protein FAM156A 24411 0/5 0/5  1/5 0/5
29 FGD6_HUMAN FYVE, RhoGEF and PH domain-containing protein 6 160816 0/5  1/5 0/5 0/5
30 FIBA_HUMAN Fibrinogen alpha chain 94914 5/5 5/5 5/5 5/5
31 FIBB_HUMAN Fibrinogen beta chain 55892 5/5 5/5 5/5 5/5
32 FIBG_HUMAN Fibrinogen gamma chain 51479 5/5 5/5 5/5 4/5
33 FUK_HUMAN L-fucose kinase 117623  1/5  2/5  1/5 0/5
34 GLI1_HUMAN Zinc finger protein GLI1b 117904 0/5 0/5 0/5  1/5
35 HAIR_HUMAN Protein hairless 127495 0/5 0/5  1/5 0/5
36 HKR1_HUMAN Krueppel-related zinc finger protein 1b 75080 0/5 0/5 0/5  1/5
37 HRG_HUMAN Histidine-rich glycoprotein 59541 0/5 0/5  1/5 0/5
38 HV304_HUMAN Ig heavy chain V-III region TIL 12348 0/5  1/5 0/5 0/5
39 HV305_HUMAN Ig heavy chain V-III region BRO 13218  1/5  1/5 0/5  1/5
40 IGHA1_HUMAN Ig alpha-1 chain C region 37631  1/5  2/5  3/5  3/5
41 IGHG1_HUMAN Ig gamma-1 chain C region 36083 5/5 5/5 5/5 5/5
42 IGHG2_HUMAN Ig gamma-2 chain C region 35878  2/5  2/5  3/5  1/5
43 IGHG3_HUMAN Ig gamma-3 chain C region 41260  4/5 5/5   5/5     4/5
44 IGHG4_HUMAN Ig gamma-4 chain C region 35918  2/5  1/5  1/5 0/5
45 IGHM_HUMAN Ig mu chain C region 49276  3/5 5/5     4/5  3/5
46 IGJ_HUMAN Immunoglobulin J chainc 15585 0/5  1/5  2/5  1/5
47 IGKC_HUMAN Ig kappa chain C region 11602 5/5    5/5    5/5    5/5   
48 INSR_HUMAN Insulin receptor 156206 0/5  3/5 0/5  2/5
49 ITPR3_HUMAN Inositol 1,4,5-trisphosphate receptor type 3b 303912 0/5 0/5 0/5  1/5
50 JPH2_HUMAN Junctophilin-2d 74221  1/5 0/5 0/5 0/5
51 K0494_HUMAN EF-hand domain-containing protein KIAA0494b 54997 0/5 0/5 0/5  1/5
52 K0753_HUMAN Uncharacterized protein KIAA0753b 109350 0/5 0/5 0/5  1/5
53 KNG1_HUMAN Kininogen-1 71957  1/5  1/5 0/5 0/5
54 KV106_HUMAN Ig kappa chain V-I region EU 11781 0/5  1/5 0/5 0/5
55 KV201_HUMAN Ig kappa chain V-II region Cum 12668 0/5  2/5 0/5 0/5
56 KV301_HUMAN Ig kappa chain V-III region B6 11628  1/5  1/5  1/5 0/5
57 KV302_HUMAN Ig kappa chain V-III region SIE 11768  2/5  2/5  1/5  2/5
58 L2HDH_HUMAN  L-2-hydroxyglutarate dehydrogenase, mitochondrialb 50327 0/5 0/5 0/5  1/5
59 LAC_HUMAN Ig lambda chain C regions 11230  4/5 5/5     4/5 5/5   
60 LRP1_HUMAN Prolow-density lipoprotein receptor-related protein 1 504605 0/5 0/5  1/5 0/5
61 LTBP3_HUMAN Latent-transforming growth factor beta-binding protein 3 139359 0/5  1/5 0/5 0/5
62 LV302_HUMAN Ig lambda chain V-III region LOIb 11928 0/5 0/5 0/5  1/5
63 LYG2_HUMAN Lysozyme g-like protein 2 23498 0/5  1/5 0/5 0/5
64 M2OM_HUMAN Mitochondrial 2-oxoglutarate/malate carrier proteind 34062  1/5 0/5 0/5 0/5
65 MCM9_HUMAN DNA replication licensing factor MCM9d 43983  1/5 0/5 0/5 0/5
66 MD12L_HUMAN Mediator of RNA polymerase II transcription subunit 12-like proteind 239967  1/5 0/5 0/5 0/5
67 MECR_HUMAN Trans-2-enoyl-CoA reductase, mitochondriald 40462  1/5 0/5 0/5 0/5
68 MY15B_HUMAN Putative myosin-XVB b 167013 0/5 0/5 0/5  1/5
69 MYH7B_HUMAN Myosin-7B 221252 0/5  1/5 0/5 0/5
70 MYH9_HUMAN Myosin-9 226392 0/5  1/5 0/5  1/5
71 MYO7A_HUMAN Myosin-VIIa 254245 0/5  2/5 0/5 0/5
72 NIPS2_HUMAN Protein NipSnap homolog 2 33721  3/5  2/5  3/5  3/5
73 NP1L3_HUMAN Nucleosome assembly protein 1-like 3 57593 0/5 0/5  1/5 0/5
74 NSD2_HUMAN Probable histone-lysine N-methyltransferase NSD2 152258 0/5 0/5  1/5 0/5
75 NU153_HUMAN Nuclear pore complex protein Nup153 153938 0/5  1/5 0/5 0/5
76 ODPX_HUMAN Pyruvate dehydrogenase protein X component, mitochondrialb 54089 0/5 0/5 0/5  1/5
77 OR2G3_HUMAN Olfactory receptor 2G3 34506 0/5  1/5 0/5 0/5
78 PB1_HUMAN  Protein polybromo-1b 192947 0/5 0/5 0/5  1/5
79 PCD23_HUMAN Protocadherin-23 b 322034 0/5 0/5 0/5  1/5
80 PCNT_HUMAN Pericentrin 378037 0/5  1/5 0/5 0/5
81 PRKDC_HUMAN DNA-dependent protein kinase catalytic subunit 468788  2/5  1/5  3/5  1/5
82 PSD1_HUMAN PH and SEC7 domain-containing protein 1 109475 0/5 0/5  1/5 0/5
83 RA51D_HUMAN DNA repair protein RAD51 homolog 4 35027 0/5 0/5  1/5 0/5
84 RBM45_HUMAN RNA-binding protein 45 d 53346  1/5 0/5 0/5 0/5
85 RFPLB_HUMAN Ret finger protein-like 4B 29903 0/5 0/5  1/5 0/5
86 RHG18_HUMAN Rho GTPase-activating protein 18 74900 0/5 0/5  1/5  1/5
87 RRBP1_HUMAN Ribosome-binding protein 1 152381 0/5 0/5  1/5 0/5
88 RL36X_HUMAN Putative 60S ribosomal protein L36-like 1 12056 0/5 0/5  1/5 0/5
89 SPKAP_HUMAN A-kinase anchor protein SPHKAP 186339  1/5  1/5  1/5  1/5
90 SLK_HUMAN STE20-like serine/threonine-protein kinase d 142695  1/5 0/5 0/5 0/5
91 SPAST_HUMAN Spastin OS=Homo sapiens 67155 0/5 0/5  1/5 0/5
92 ST18_HUMAN Suppression of tumorigenicity 18 protein b 115083 0/5 0/5 0/5  1/5
93 STIM1_HUMAN Stromal interaction molecule 1 77375  3/5  3/5  2/5  3/5
94 STRN4_HUMAN Striatin-4 81266 0/5 0/5  1/5 0/5
95 SYAM_HUMAN Probable alanyl-tRNA synthetase, mitochondrial 107273 0/5 0/5  1/5 0/5
96 SYNE1_HUMAN Nesprin-1c 1010412 0/5  1/5  2/5  1/5
97 T22D1_HUMAN TSC22 domain family protein 1 109592 0/5 0/5 0/5 0/5
98 TITIN_HUMAN Titin 3813810 0/5  1/5 0/5 0/5
99 UBN1_HUMAN Ubinuclein 121520 0/5  1/5 0/5 0/5
100 UBP33_HUMAN Ubiquitin carboxyl-terminal hydrolase 33 d 106727  1/5 0/5 0/5 0/5
101 UBP37_HUMAN Ubiquitin carboxyl-terminal hydrolase 37 d 110144  1/5 0/5 0/5 0/5
102 UEVLD_HUMAN Ubiquitin-conjugating enzyme E2 variant 3 52231 0/5 0/5  1/5  1/5
103 WNK4_HUMAN Serine/threonine-protein kinase WNK4 134655  1/5  2/5  3/5 0/5
104 YLPM1_HUMAN YLP motif-containing protein 1 b 219849 0/5 0/5 0/5  2/5
105 ZEP2_HUMAN Transcription factor HIVEP2 d 269052  1/5 0/5 0/5 0/5
106 ZN177_HUMAN Zinc finger protein 177 36473 0/5  1/5 0/5 0/5
107 ZN226_HUMAN Zinc finger protein 226 91921 0/5 0/5  1/5 0/5
108 ZN514_HUMAN Zinc finger protein 514 45938 0/5  1/5 0/5 0/5
109 ZN561_HUMAN Zinc finger protein 561 55161 0/5 0/5  1/5 0/5
110 ZN669_HUMAN Zinc finger protein 669 52597 0/5  1/5 0/5 0/5
111 ZNF48_HUMAN Zinc finger protein 48 67833 0/5  1/5 0/5 0/5

Table 2: Frequency of identified proteins in CIC isolated from plasma.

Two proteins including Rho GTPase-activating protein 18 and Ubiquitin-conjugating enzyme E2 variant 3 were detected in one DHF and DSS patients but not in any DF/health individual. In addition, no significant differences in the relative frequency of detected proteins were found between the severe dengue groups (DHF/DSS) and the DF/ healthy groups (p-value>0.10, Fisher´s exact test).

Functional analysis by UniProt-GOA program revealed ten protein classes including immunoglobulin, coagulation system, cell communication, DNA/RNA association, cell growth/maintenance/ movement, complement, energy metabolism, protein metabolism, and transport system (Figure 3). All ten functional classes were found in all groups of the healthy, DF, DHF, and DSS. The immunoglobulin class accounted the highest number of proteins in all groups, followed by coagulation system, cell communication, and DNA/RNA associated classes. There are no significant differences in the percentage of numbers of proteins found per group in any functional protein class (p-value>0.10, Kruskal-Wallis test).

tropical-diseases-community-analysis

Figure 3: Functional analysis of identified proteins in different groups. Pie graph showing total proteins identified in at least one individual from each group and sorted by functional characteristics. The area in the graph represents the percentage of numbers of proteins found per group.

We further classified those identified proteins in terms of cellular components using the UniProt-GOA program. Figure 4 shows the proportions (%) of proteins in different cellular components for each category of subjects. Three dominant protein classes are extracellular, nucleus, and cytoplasm. It is evidenced that other main cellular components including cytoskeleton, plasma membrane, mitochondrion, and endoplasmic reticulum also had identified proteins in the CIC. The results also indicated a high similarity of CIC profile between four groups when looking only at the cellular components. No significant differences were found when pairwise comparing the percentage of numbers of proteins in all cellular components´ categories (p-value>0.10, Kruskal-Wallis test).

tropical-diseases-community-component

Figure 4: Cellular component of identified proteins in different groups. Pie graph showing total proteins identified in at least one individual from each group and sorted by functional characteristics. Rare cellular components (<3%) were grouped as ‘other’. The area in the graph represents the percentage of numbers of proteins found per group.

Discussion

Formation of CIC is a normal process of humoral immune response against an antigen. CIC is quickly uptake by monocytes, but in some situation they persist longer in the circulation or deposit in the local tissue, causing some pathology. It has been suggested that the IC can play an important role in pathogenesis of auto-immune diseases [23,24,37]. Moreover, CIC associated antigens have been detected as a hallmark of the auto-immune arthritis [23,24].

An auto-immune response has been proposed as a mechanism in the pathogenesis of dengue infection, in which antibodies against dengue non-structural protein 1 (NS1) cross reacts with the host endothelial cells [16], platelets [17], active sites on human clotting factors and integrin/adhesin proteins [18]. Lin et al. [20] have detected that antibodies against NS1 cross-react with platelets and have higher binding activity to platelets in DHF/DSS than those in DF. Another study in Vietnamese children showed that levels of auto-antibodies against platelets and endothelial cells are higher in DHF/DSS compared to DF patients [21]. Level of CIC has been reportedly increased in dengue infection and peaked at the transition period of fever to defervescence [38]. The level of CIC is related to the severity of the disease. However, there were no strong evidences of (i) an association with other autoimmune diseases, (ii) infiltration of lymphocytes in the target site of the disease, and (iii) response to steroid treatment [39-41], which have been proposed as the criteria for an auto-immune pathogenesis [42].

In this study we found a similar relative composition of the CIC in all groups of healthy, DF, DHF, and DSS which suggests the absence of any specific antigen consistently detectable during the transition from fever to defervescence. These results are in good agreement with the argument of Halstead [43], where he suggested that auto-antibodies would not play an important role in the pathogenesis of dengue severity because (i) the thrombocytopenia and hyper permeability occur in the early stage of the disease even in infant, while the antibody is produced later in the course of the disease [44]; (ii) the thrombocytopenia and hyperpermeability are transient while the production of antibody lasts for months [44]; (iii) the kinetics of antibody production in primary infections are completely different from secondary infections but the pathogenesis of DHF is not so much different between infants and children [8]. There was a limitation in this study such as the method could not detect non-protein substances of antigen including lipids and carbohydrates.

It is suggested that the lower sensitivity of dengue virus nonstructural protein-1 antigen (NS1) detection in secondary dengue infection compared with primary infection is due to the formation of CIC by anti-NS1 antibody IgG [45]. The dengue virus-containing immune complexes have been also detected using an immuno-precipitation assay coupled with a real-time RT-PCR method [46]. However, we didn´t detect any dengue antigen including NS1 in the proteomic analysis of CIC, probably due to lower sensitivity of proteomic approach compare to the real-time RT-PCR method and a possible deposition of CIC at the local tissue. Thus, more sensitivity proteomic method is required for further studies to clarify this issue.

This study is the first to report a proteomic profile of circulating immune complexes from plasma of dengue infected patients. Our results showed similarity of CIC profiles between four groups of healthy, DF, DHF, and DSS when classifying identified proteins according to the frequency, cellular components or functional protein categories. Thus, it is unlikely that the CIC mediated by auto-immune response plays an important role in the pathogenesis of the acute dengue infection.

Acknowledgements

We thank all the members of the Laboratory of Arbovirus, Ho Chi Minh City, Vietnam. We also express our appreciation to the staff of Children´s Hospital No. 2 in Ho Chi Minh City (HCMC) and the Center for Preventive Medicine in the Vinh Long Province (VL) of the Mekong Delta.

This work was supported in part by the Global COE Program (2008 - 2012) and Japan Initiative for Global Research Network on Infectious Diseases (J-GRID) for KH. It was also supported in part by a “Grant-in-Aid for Scientific Research” from Nagasaki University to NTH (2012-2013).

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