Comprehensive evaluation of differential serodiagnosis ...Dec 10, 2018 · 1 C omprehensive evaluation of differential serodiagnosis between Zika and dengue 2 viral infection 3 4

1

Comprehensive evaluation of differential serodiagnosis between Zika and dengue 1

viral infection 2

3

Day-Yu Chao1*

, Matthew T. Whitney2, Brent S. Davis

2, Freddy A Medina

3, Jorge L Munoz

3, 4

Gwong-Jen J. Chang2*

5

1. Graduate Institute of Microbiology and Public Health, College of Veterinary Medicine, National 6

Chung-Hsing University, Taichung, Taiwan (402) 7

2. US Department of Health and Human Services, Public Health Services, Division of Vector-Borne 8

Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado 80521 9

3. US Department of Health and Human Services, Public Health Services, Division of Vector-Borne 10

Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico 00920 11

12

*Corresponding author: Chang, Gwong-Jen J 13

Email: [email protected] 14

Tel: 970-221-6497 15

or 16

Day-Yu Chao 17

Email: [email protected] 18

Tel: 886-4-22840694 19

20

21

Keywords: Zika, Dengue, MAC-ELISA, Differential diagnoses 22

Running headline: differential serodiagnosis of Zika and dengue 23

JCM Accepted Manuscript Posted Online 12 December 2018J. Clin. Microbiol. doi:10.1128/JCM.01506-18This is a work of the U.S. Government and is not subject to copyright protection in the United States.Foreign copyrights may apply.

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Word counts: 250 (abstract); 3499 (text) 24

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Summary 26

Diagnostic testing for Zika virus (ZIKV) or dengue virus (DENV) infection can be accomplished by a 27

nucleic acid detection method; however, a negative result does not exclude infection due to the low virus 28

titer during infection depending on the timing of sample collection. Therefore, a ZIKV- or DENV-29

specific serological assay is essential for the accurate diagnosis of patients and to mitigate potential 30

severe health outcomes. A retrospective study design with dual approaches of collecting human serum 31

samples for testing was developed. All serum samples were extensively evaluated by using both non-32

infectious wild-type (wt) virus-like particles (VLPs) and soluble non-structural protein 1 (NS1) in the 33

standard immunoglobulin M (IgM) antibody-capture enzyme-linked immunosorbent assay (MAC-34

ELISA). Both ZIKV-derived wt-VLP- and NS1-MAC-ELISAs were found to have similar sensitivity 35

for detecting anti-premembrane/envelope and NS1 antibodies from ZIKV-infected patient sera, although 36

lower cross-reactivity to DENV2/3-NS1 was observed. Furthermore, group cross reactive (GR)-37

antibody-ablated homologous fusion peptide-mutated (FP)-VLPs consistently showed higher P/N values 38

than homologous wt-VLPs. Therefore, we used DENV-2/3 and ZIKV FP-VLPs to develop a novel, 39

serological algorithm for differentiating ZIKV from DENV infection. Overall, the sensitivity and 40

specificity of the FP-VLP-MAC-ELISA and the NS1-MAC-ELISA were each higher than 80% with no 41

statistical significance. The accuracy can reach up to 95% with the combination of FP-VLP and NS1 42

assays. In comparison to current guidelines using neutralization tests to measure ZIKV antibody, this 43

approach can facilitate laboratory screening for ZIKV infection, especially in regions where DENV 44

infection is endemic and capacity for neutralization testing does not exist. 45

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Introduction 48

Zika virus (ZIKV) and dengue virus (DENV), members of the Flaviviridae family, are 49

associated with the resurgence of mosquito-transmitted diseases worldwide(22). While DENV continues 50

to impose a great economic and public health burden in tropical and subtropical countries, the recent 51

emergence of ZIKV, potentially circulated in Central and South America since 2013(8), has resulted in 52

terrifying outbreaks with severe health outcomes, including Guillain-Barre syndrome in adults as well as 53

microcephaly, congenital neurologic malformations, and fetal demise in fetuses(2, 27). Clinically, ZIKV 54

and DENV share similar symptoms of infection, geographical distribution, and transmission cycles 55

between humans and Aedes aegypti mosquitoes(6). A confirmatory diagnosis can be obtained by virus 56

isolation or viral RNA detection in serum and other body fluids, but given the low virus titer during 57

ZIKV infection, timing of specimen collection, and the high proportion of mild or asymptomatic ZIKV 58

infections, a ZIKV-specific serological assay is essential to accurately diagnose the patients who were 59

negative by virus isolation or viral RNA detection(33, 38). 60

61

Mosquito-borne flaviviruses can be serologically classified into several complexes, including 62

medically important members of the Japanese encephalitis virus (JEV) complex, dengue viruses 63

(DENV), yellow fever virus (YFV), as well as the recently emerged ZIKV(14). During natural infection, 64

the majority of elicited antibodies (Abs) recognize structural proteins pre-membrane (prM) and envelope 65

(E), and non-structural protein 1 (NS1)(11, 14, 32, 35). Anti-E antibodies that recognize all members of 66

the flavivirus group, members from different serocomplexes, or members within a serocomplex, are 67

classified as group-reactive (GR), complex-reactive (CR), or type-specific (TS)-Abs, respectively(5, 25, 68

28). Although GR or CR anti-NS1 antibodies could be found from other flavivirus infections, recent 69

studies suggested the majority of anti-NS1 antibodies from primary ZIKV infections are dominated by 70

TS Abs and can be used as serological markers to differentiate ZIKV from DENV infections(1, 35). 71


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However, the cross-reactivity of human anti-NS1 antibodies increased after sequential DENV and ZIKV 72

infections(35). Furthermore, the low sensitivity in detecting anti-NS1 antibodies and the discrepancy in 73

determining sero-positivity between detecting anti-E and anti-NS1 antibodies were continuously 74

reported(13, 31). Currently, there are five serological assays approved by U.S. Food and Drug 75

Administration (FDA) for emergency use with two assays for detecting anti-E antibodies and three 76

assays for detecting anti-NS1 antibodies(36). A rigorous evaluation comparing the serological assays of 77

detecting anti-E or anti-NS1 antibodies is still not available. To ensure optimal patient care and to 78

improve the accuracy of epidemiologic surveillance in regions where active transmission of both DENV 79

and ZIKV is probable, a validated, virus specific sero-diagnostic test is urgently needed. 80

81

The objectives of this study were to develop/evaluate (Phase I) and validate (Phase II) anti-E and 82

anti-NS1 sero-diagnostic assay that can reliably distinguish and diagnose current/acute ZIKV and/or 83

DENV infection in humans. In the Phase I, we selected and applied several well-characterized, archived 84

serum panels, collected during the 2008 West Nile virus outbreak in South Dakota, the 2009 DENV 85

outbreak in Brazil and the 2016 introduction of ZIKV to Puerto Rico, to thoroughly evaluate anti-prM/E 86

and anti-NS1 IgM antibodies using wild-type and fusion-peptide mutated virus-like particles (wt-VLP 87

and FP-VLP) and soluble NS1 antigens of ZIKV and DENV-2/3, respectively. We applied the Receiver 88

Operation Characteristic (ROC) analysis to estimate the proper cut-off and to determine an algorithm 89

that can specifically distinguish and diagnose ZIKV and DENV infection using acute/convalescent 90

human serum specimens. We then conducted a double-blind study (phase II) using clinical serum 91

specimens collected and provided by Division of Vector-borne Disease (DVBD)-Dengue Branch, 92

Centers for Disease Control and Prevention (CDC), in Puerto Rico to validate the reliability of the 93

algorithm developed in Phase I. Using the classical immunoglobulin M (IgM) antibody-capture enzyme-94

linked immunosorbent assay (MAC-ELISA), we were able to differentiate between ZIKV and DENV 95


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with accuracy higher than 85%. Furthermore, combining both FP-VLP and NS1-MAC-ELISAs, 95% 96

accuracy could be achieved. 97


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Materials and Methods 98

Study design and human serum panels 99

A two-stage retrospective study design was implemented in this study including the use of a 100

developmental serum panel in Phase I and a validation panel in Phase II. Serum specimens of all 101

suspected DENV- or ZIKV-infected patients were evaluated by real-time reverse-transcription 102

polymerase chain reaction (rRT-PCR) for acute-stage specimens and wtVLP-MAC-ELISA for IgM 103

seroconversion of the convalescent-phase specimens by the CDC Dengue Branch in San Juan, Puerto 104

Rico(15). Since there was a possibility of IgM antibody cross-reactivity between closely related 105

flaviviruses from prior flaviviral infections or vaccination, a supplementary focus-reduction micro-106

neutralization test (FRµNT) was conducted for all specimens positive by MAC-ELISA. FRµNT is still 107

the only reference standard test by far for differentiating flavivirus infection serologically(23). Due to 108

high cross-reactivity of antibodies during the acute phase of infection(8, 20), limited volume of available 109

serum specimens and the urgency of developing a serological assay to differentiate ZIKV and DENV 110

infection to fulfill the mission of CDC, DENV-2 was the only DENV serotype used for FRµNT and the 111

starting dilution of the serum was 20 (Table S1). 112

The retrospective, archived serum panels (summarized in Table 1) were used as developmental 113

panels in Phase I to determine the proper cut-off value for the assay and to establish the test algorithm. 114

Only the ZIKV-infected patient serum panel (the testing panel, Table S1) was collected in Puerto Rico 115

after the first confirmation of ZIKV circulation in the Americas; the rest of the archived specimens were 116

collected prior to the first appearance of ZIKV in the Americas. The ZIKV patient serum panel used for 117

testing included forty-two acute and convalescent ZIKV-infected patient serum pairs from Puerto Rico 118

in 2016, confirmed by rRT-PCR and CDC wtVLP-MAC-ELISA. Acute specimens were collected 119

within seven days and the convalescent phase specimens were taken within seven to thirty days after 120

onset of symptoms. The ninety percent end-point FRµNT (FRµNT90) on ZIKV and DENV-2 was used 121


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to verify recent infections by following the CDC guidelines(26). Primary ZIKV infection is determined 122

by an anti-DENV-2 FRµNT90 titer of less than 20 from both acute and convalescent sera with a 123

concurrent positive ZIKV titer (>20). Secondary ZIKV infection is defined by a positive ZIKV titer with 124

an anti-DENV-2 titer of equal to or greater than 20 from either acute or convalescent sera. 125

A double-blinded test of VLP- and NS1-MAC-ELISA was conducted in Phase II to validate the 126

diagnostic algorithm established in Phase I. Serum specimens used in this Phase were all collected from 127

Puerto Rico based on convenient series, with only single serum collection from each participant. This 128

study was conducted and reported in accordance with the Standards for Reporting Diagnostic Accuracy 129

Studies (STARD) guidelines(3). Informed consent documents for all eligible participants were waived 130

based on the protocol number 6874. An institutional review board (IRB) waiver to use this serum panel 131

for research purposes was approved by the CDC-human studies review board. Since all the specimens 132

were de-identified, the basic demographic and clinical characteristics of the participants were not 133

available to the researchers in this study. 134

135

Plasmid construction, soluble protein expression and antibody production 136

A transcriptional and translational optimized eukaryotic cell expression plasmid was used as the 137

backbone to express NS1 protein or pre-membrane/envelope (prM/E) that generate VLPs from ZIKV 138

BPH-2016 strain (Brazil 2016) based on standard molecular cloning procedures as described 139

previously(7, 12). The constructed plasmids were electroporated into COS-1 cells using a protocol 140

described previously. VLPs and soluble nonstructural protein 1 (sNS1) were expressed by COS-1 cells 141

electroporated with recombinant expression plasmids encoding the prM/E and NS1 genes, respectively. 142

Electroporated cells were recovered in 150 cm2 culture flasks with 50 ml DMEM and incubated at 28°C 143

with 5% CO2 for VLP/sNS1 expression. VLPs and sNS1 from DENV-2 strain 16681, DENV-3 strain 144


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C0331/94, and West Nile virus (WNV) strain NY99 were produced as described previously(7, 12) and 145

used in this study. Additionally, the prM/E expressing plasmid was modified by site-directed 146

mutagenesis to mutate E 106/107, an epitope recognized by GR antibody(9), from DENV-2 147

GL106/107RK, DENV-3 GL106/107DR and ZIKV GL106/107KD and the VLPs generated were named 148

DENV2- or DENV3-FP-VLP or ZIKV-FP-VLP. The un-mutated wild-type VLPs were named DENV2- 149

or DENV3-wt-VLP or ZIKV-wt-VLP for differentiation. 150

151

Both anti-ZIKV polyclonal rabbit and mouse sera containing high-titer immunoglobulin 152

recognizing all potential antigenic epitopes were generated at US-CDC. Anti-DENV-2, DENV-3, or 153

WNV wt-VLP, and anti-NS1 polyclonal rabbit sera were produced in-house as described previously. 154

Murine hyperimmune ascetic fluid (MHIAF) specific for DENV-2 or DENV-3, or WNV were obtained 155

from the Diagnostic and Reference Laboratory, DVBD-CDC. 156

157

VLP- and NS1-specific MAC/GAC-ELISAs 158

Human serum specimens were assayed for the presence of prM/E- and NS1-specific antibodies 159

using MAC- ELISAs as previously described(7, 12, 13, 26). Briefly, 96-well plates were coated with 160

goat anti-human IgM or IgG (Kirkegaard & Perry Laboratories, Gaithersburg, MD) diluted 1:2,000 in 161

coating buffer (0.015 M sodium carbonate, 0.035 M sodium bicarbonate) at pH 9.6 and incubated at 4°C 162

overnight. The infected patient serum as well as negative control serum were diluted 1:1,000 in wash 163

buffer (PBS with 0.05% Tween-20), 50 µl were added to wells, and incubated at 37°C for 60 min. 164

ZIKV, DENV-2/3, WNV VLPs and NS1, pre-determined and standardized at an optical density (OD) of 165

1·0 at 450nm (OD450) by antigen-capture ELISA (Ag-ELISA) using rabbit and mouse polyclonal serum 166


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as capture and detector antibodies, respectively, were diluted in wash buffer and tested against each 167

serum sample in triplicate. 168

To deplete anti-prM/E antibodies from serum samples, Ag-ELISA was used to capture VLP 169

immune-complexes in 96-well plates as previously suggested(7, 12). In brief, the patient and negative 170

control sera were diluted 1:1,000 in PBS, mixed with wt-VLP antigens, and added immediately to wells 171

pre-coated with anti-prM/E rabbit sera and incubated at 37°C for 60 min. VLP concentrations used for 172

depletion were pre-determined at an OD450 of 1.4, within the region of excess antigen near the upper 173

asymptote of the sigmoidal dilution standard curve. A total of 50 L of prM/E antibody-depleted sera 174

were transferred to 96-well plates pre-coated with anti-human IgM for performing the NS1-specific 175

MAC-ELISA as described above. 176

Due to the cross-reactivity of anti-E antibodies, using VLPs derived from DENV-2 and DENV-3 177

(DENV-2/3) is sufficient to detect human E-specific IgM or IgG by wt-VLP-MAC-ELISA from the 178

dengue infected patient serum based on our previous publications(7). Similar combination of DENV-2/3 179

FP-VLP and NS1 was applied for FP-VLP-MAC-ELISA and NS1-MAC-ELISA. 180

181

Data processing and statistical analysis 182

Both positive and negative values were determined as the average OD450 from triplicate samples of 183

each specimen (P) or normal human control sera (N) reacting with VLP or NS1 antigens, respectively. 184

Positive-to-negative (P/N) ratios were derived for each specimen as well as positive and negative serum 185

controls on each plate for validation of the quality of the assay. The P/N ratios from the ZIKV patient 186

sera were compared with the ratios from different serum specimens of the developmental serum panel 187

and the positive likelihood ratio (LR+), shown as ROC curve, was calculated by dividing sensitivity by 188

1-specificity to determine the optimal cutoff value of P/N ratios from VLP- and NS1-MAC-ELISAs. 189


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The Bland-Altman plot was used to measure the consistency of higher P/N values of the ZIKV-FP-190

MAC-ELISA over DENV2/3-FP-MAC-ELISA, or ZIKV-NS1-MAC-ELISA over DENV2-NS1-MAC-191

ELISA by plotting the ratios of the two methods’ P/N ratio values (ratio of P/N value between ZIKV-192

MAC-ELISA and DENV2/3-MAC-ELISA) versus the averages of P/N values from both methods. Two-193

by-two contingency tables were prepared to determine the sensitivity, specificity, positive predictive 194

value (PPV) and negative predictive value (NPV) of the assays based on the algorithm generated in this 195

study according to the results from the validation serum panel. For all statistical analyses, we used 196

GraphPad Prism version 6 and p values less than 0·05 were considered statistically significant. 197


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Results 198

Participant serum panels 199

Figure 1 showed the flowchart of the archived serum panel retrospectively collected for Phase I 200

and Phase II study. Since the first index patient reported onset of symptoms on November 23, 2015, 201

Puerto Rico became the first U.S jurisdiction to report local transmission of ZIKV when DENV was 202

already endemic in Puerto Rico. In order to properly establish the cut-off value of the assay, the criteria 203

of all ZIKV and DENV-confirmed specimens used in Phase I included paired sera collected during the 204

acute and convalescent phase of illness and confirmation of disease status by FRµNT90 on ZIKV and 205

DENV-2. 206

Detail characteristics of four groups of well-characterized, archived patient serum specimens 207

used in Phase I were outlined in Table 1. To meet the outbreak reality when the paired specimens were 208

difficult to obtain, the only criteria for the serum panel used in Phase II was double-blinded. All DENV 209

positive specimens were collected during 2010-2012 when the paired specimen from the same patient 210

was rare. The negative specimens were taken during 2016 and they are all negative for DENV, ZIKV, 211

WNV and Chikungunya virus (CHIK) in acute phase and negative for IgM in convalescent phase 212

samples. 213

214

Establishment of ZIKV NS1-MAC-ELISA 215

IgM antibody-capture ELISA has traditionally been used to selectively detect the IgM antibodies 216

and to avoid the competition between IgM and IgG for a specific target antigen (such as prM/E 217

containing flavi-VLP antigens). This is in contrast of using E or NS1 antigens for direct detection of 218

anti-E or anti-NS1 antibodies in other studies(18, 37, 39, 41). The use of VLPs in MAC-ELISA has 219

good sensitivity, safety, and acceptable specificity for determining a current flaviviral infection(7, 16, 26, 220


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29) and was chosen here. Also, the use of MAC-ELISA allows us to simultaneously compare the cross-221

reactivity of antibodies against E and NS1 from both DENV and ZIKV infection. Based on our previous 222

publications(7), depletion of anti-prM/E antibodies in advance is essential to increase the sensitivity of 223

detecting flavivirus-specific anti-NS1 antibodies using MAC-ELISA. To confirm if this is true for ZIKV 224

infection, ZIKV-infected patient sera were added to pre-coated anti-IgM ELISA plates with or without 225

depletion of prM/E antibodies. As shown in Fig 2A, depletion of anti-prM/E antibodies significantly 226

increased the P/N ratios of detecting anti-NS1 IgM antibodies. 227

Since ZIKV and DENV co-circulate in the same geographic location, we determined if a 228

combination of multiple flavivirus VLPs would be required for depletion when the status of infection 229

from the patient serum is unknown. Also, our previous publications have demonstrated that using VLP 230

derived from DENV serotype 2 and 3 are sufficient to deplete most of the cross-reactive anti-E 231

antibodies(7). Therefore, only DENV serotype 2/3 will be tested in combination with other flavivirus 232

VLP antigens. As shown in Fig 2B, although depletion with ZIKV+DENV-2 VLP had higher P/N ratio 233

on ZIKV-infected serum than depletion with ZIKV+DENV-2+DENV-3, only depletion with 234

ZIKV+DENV-2+DENV-3 had high P/N ratio on DENV-infected serum. This suggested that using a 235

single serotype of DENV VLP, such as DENV-2, could potentially result in a false negative result if 236

infection from a different serotype of DENV occurred, which is consistent with our previous 237

publication(7). Although using the combination of VLPs from ZIKV, DENV-2 and DENV-3 slightly 238

decreased the P/N ratio from ZIKV serum panel, significantly increase the P/N ratio from DENV serum 239

panel was noticed. Thus, all follow-up experiments of detecting anti-NS1 antibodies from serum 240

specimens, we used the combination of VLPs from ZIKV, DENV-2, and DENV-3 to deplete VLPs 241

antibodies. 242

243

Cross-reactivity of anti-prM/E and anti-NS1 antibodies 244


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In order to compare the cross-reactivity of anti-prM/E and anti-NS1 antibodies, the proper cut-245

off values for wt-VLP- and NS1-MAC-ELISAs were determined using a well-characterized 246

developmental serum panel in Phase I. Fig 3A shows the results of a ZIKV-wt-VLP-MAC-ELISA for 247

four different serum panels including antibodies to ZIKV, WNV, DENV and others (including other 248

flaviviruses). Significant elevation of the P/N ratio in the convalescent phase sera was observed for 249

patient antisera from both ZIKV and DENV infections. WNV and other anti-serum panels have little 250

cross-reactivity with ZIKV-VLP, and were used to determine the cut-off values for the ZIKV-wt-VLP-251

MAC-ELISA. The ROC analysis in Figure 3B, showing the curve of sensitivity vs 100-specificity, 252

provides information on how strongly a given test result can be used to predict the likelihood of 253

evidence of infection or non-infection based on P/N values from forty-two ZIKV patient sera and the 254

WNV/other control serum panels (Fig 3B). The optimal cutoff values of P/N ratios for both ZIKV-wt-255

VLP-MAC-ELISAs of acute and convalescent phase sera were set at 2.837 and 2.76, respectively (Fig. 256

3C). Similarly, the results of ZIKV-NS1-MAC-ELISAs for four different serum panels are shown in Fig 257

4A. The optimal cutoff values of P/N ratios for ZIKV-NS1-MAC-ELISAs of both acute and 258

convalescent sera were set at 1.014 and 1.136, respectively (Fig. 4B and 4C). 259

Based on the cutoff, similar percentages of ZIKV acute (69.6% and 69.6%), and convalescent 260

sera (94.7% and 100%) were positive for both ZIKV-wt-VLP-MAC-ELISA and ZIKV-NS1-MAC-261

ELISA, respectively (Table 2). However, significant numbers of the DENV panel were also positive to 262

ZIKV-wt-VLP-MAC-ELISA (63.6%) and ZIKV-NS1-MAC-ELISAs (72.7%). When ZIKV serum 263

specimens were tested against DENV2/3 wt-VLP and NS1 antigens, 95.7% were positive to wt-VLP but 264

only 8.7% were positive to NS1 from acute phase sera. On the contrary, 100% and 52.6% of the 265

convalescent phase sera were positive for wt-VLP and NS1 antigens of DENV-2 and DENV-3, 266

respectively (Table 2). In summary, the uses of wt-VLP- and NS1-MAC-ELISAs have similar 267

sensitivity detecting anti-prM/E and NS1 antibodies from ZIKV-infected patients’ sera. Although a 268


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significantly lower percentage of ZIKV patient sera was positive to DENV-derived NS1 antigens 269

(DENV2/3-NS1-MAC-ELISA) than wt-VLP (DENV-2/3-wt-VLP-MAC-ELISA), no difference of 270

cross-reactivity to ZIKV antigens (ZIKV-wt-VLP-MAC-ELISA vs ZIKV-NS1-MAC-ELISA) was 271

observed for DENV patient sera. 272

273

Using ZIKV/DENV ratio to differentiate between ZIKV and DENV infection 274

Previous studies suggested that a significant proportion of anti-E antibodies were GR antibodies 275

that recognized the highly conserved fusion peptide during flavivirus infection.(9, 30) To avoid the 276

binding of such GR antibodies on the ZIKV VLP, a fusion peptide mutant (GL106/107KD) ZIKV VLP 277

(ZIKV FP-VLP) was generated for MAC-ELISA and the proper cutoff value was determined similarly 278

(Fig S1). A significant decrease of the cross-reactivity to ZIKV FP-VLP among the DENV serum 279

specimens were noticed; in addition, the positive proportions of MAC-ELISA detected by ZIKV-wt-280

VLP or ZIKV-FP-VLP among ZIKV serum panel remained similar (Table 3). Thus ZIKV FP-VLP, 281

compared to ZIKV wt-VLP as a diagnostic reagent, would be a more specific antigen for detecting 282

ZIKV-specific anti-prM/E antibodies. However, the problem remained due to close to 40% of 283

DENV/nonZIKV sera still recognized and cross-reactive with ZIKV FP-VLP. 284

Further comparing the P/N ratios of the MAC-ELISA between ZIKV and DENV-2/3 FP-VLP, 285

consistently higher values against homologous antigens were observed; that is, for a ZIKV infection, 286

higher values of the P/N ratio was observed for ZIKV FP-VLP than for the use of DENV-2/3 FP-VLP 287

(Fig 5). Similar results were also observed for the NS1-MAC-ELISA. Therefore, an algorithm of 288

serological diagnosis to differentiate between ZIKV and DENV infection was developed in this study 289

(Fig 6). 290

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Validation of the algorithm 292

The prospectively collected validation serum panel was provided to the investigator and blind 293

tested in Phase II by VLP-MAC-ELISA and NS1-MAC-ELISA using FP-VLP and NS1 from ZIKV and 294

DENV-2/3 and the results were interpreted based on the developed algorithm in Fig 6. Twenty (100%) 295

of the ZIKV-confirmed sera were classified as ZIKV infection by FP-VLP-MAC-ELISA and 80% by 296

NS1-MAC-ELISA. For DENV-confirmed specimens, 75% and 100% were classified as DENV 297

infection by FP-VLP-MAC-ELISA and NS1-MAC-ELISA, respectively (Table S2). Fifteen percent of 298

the negative specimens were falsely classified as positive by FP-VLP-MAC-ELISA and 10% by NS1-299

MAC-ELISA (Table S2). Overall, the sensitivity and specificity of FP-VLP-MAC-ELISA and NS1-300

MAC-ELISA based on the algorithm was higher than 80% with no statistical significance, although 301

slightly lower sensitivity (75%) of FP-VLP-MAC-ELISA in classifying DENV infection (Table 4) was 302

observed. The overall PPV of both assays for diagnosis of ZIKV or DENV infection demonstrates no 303

statistical significance. 304

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Discussion 307

Five serological assays has been approved by U.S. FDA for emergency use(36). Currently, 308

however, no publications have simultaneously evaluated anti-E or anti-NS1 antibodies under the same 309

ELISA format against DENV or ZIKV using well characterized, archived human serum samples. In this 310

study, we comprehensively evaluated the cross-reactivity of anti-prM/E antibodies induced by ZIKV 311

infection using wild-type and FP-mutated VLP antigens from ZIKV, DENV-2 and DENV-3. The test 312

results were compared to the prM/E antibody-depleted NS1 MAC-ELISA. Using ZIKV-FP-VLP 313

significantly reduced the observed cross-reactivity for a DENV patient serum panel, compared to using 314

wild-type ZIKV VLP. Although ZIKV-NS1-MAC-ELISA is more specific in determining ZIKV 315

infection, we still observed 57.1% cross-reactivity to DENV-2/3-NS1 for ZIKV-infected sera and 72.7% 316

to ZIKV-NS1 for DENV-infected patients’ serum specimens, which is consistent with a previous 317

publication(39). Flavivirus infection can induce group-reactive (GR), complex-reactive (CR), or type-318

specific (TS)-Abs(5, 25, 28). The generation of FP-VLP for detection of anti-E antibodies is attempted 319

to reduce the binding of cross-reactive GR antibodies, but still maintain the binding of CR or TS 320

antibodies(10, 17). However, the remaining antibodies from infection by different serotypes of DENV 321

can still bind to DENV-2/3-FP-VLP due to the presence of complex cross-reactive DENV antibodies. 322

Using a combination of a ZIKV/DENV ratio from FP-VLP- and NS1-MAC-ELISAs, we successfully 323

differentiated between ZIKV and DENV infection with 90-100% accuracy. Thus, we have demonstrated 324

a testing algorithm for differentiating ZIKV and DENV infections that can be applied in dengue- and/or 325

other flavivirus-endemic regions where most patients have experienced previous flavivirus infection. 326

Serological cross-reactivity between flaviviruses is common and several recent publications have 327

shown the global efforts trying to resolve this issue to determine the status of ZIKV infection(1, 21, 24, 328

37). Using well-characterized, archived serum panels including ZIKV, DENV, WNV and others, our 329

study compared the cross-reactivity of anti-prM/E and anti-NS1 antibodies across different sero-330


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complexes. The overall cross-reactivity of anti-NS1 antibodies induced by ZIKV infection was 331

significantly lower than anti-prM/E antibodies, possibly due to the difference in electrostatic surface 332

potential of NS1(4, 35, 40). However, we did not observe any significant differences in cross-reactivity 333

between VLP- and NS1-MAC-ELISAs for DENV infection. The results of highly cross-reactive anti-334

prM/E antibodies were consistent with FRµNT results (Table S1). The majority of ZIKV-infected 335

patients had prior DENV infection as suggested by FRµNT titers greater than 10 against DENV-2 in 336

acute serum specimens. During secondary ZIKV infection, the FRµNT titer in the convalescent sera 337

showed at least 4-fold increase against both ZIKV and DENV. The majority of cross-reactive anti-338

prM/E antibodies during flaviviral infection are GR (4G-2 and 6B6C-1 like) antibodies recognizing the 339

FP, with the potential to enhance viral infection and induce low-to-moderate neutralizing activity(14). 340

The current CDC guideline recommends that all ZIKV IgM positive and equivocal specimens be 341

confirmed by the more specific plaque reduction neutralization assays(26). However, recent publication 342

suggests that FRµNT confirmation is limited and is not routinely recommended for clinical diagnosis by 343

Dengue Branch-CDC in Puerto Rico(20). 344

Flaviviruses have been traditionally subdivided into different serocomplexes, comprised of 345

members that are cross-neutralized by polyclonal sera(5). Such sero-classification is correlated with the 346

similarity of amino acid sequence of prM/E(14). ZIKV, clustered with Spondweni virus and shows an 347

intermediate position with viruses from JEV and DENV serocomplexes in the phylogenetic tree (based 348

on complete genome, E, or NS1 gene sequences). The overall picture of flavivirus serocomplexes 349

indicates that cross-reactive neutralizing antibodies is usually lost when the amino acid sequence 350

divergence of E is more than 50%(14). Therefore, ZIKV together with the viruses from the Spondweni 351

viral group could form an independent serocomplex. This is the basis of using the ratio test of 352

ZIKV/DENV IgM antibodies to distinguish ZIKV from DENV infection. NS1 also shares the similar 353

degree of amino acid sequence divergence as E. Thus, a similar IgM ratio test to detect VLP-antibodies-354


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depleted anti-NS1 antibodies could also be used to distinguish ZIKV or DENV infection between 355

viruses belong to different serocomplexes. The use of FP-VLP in MAC-ELISA has several advantages, 356

including the avoidance of a pre-depletion step prior to detecting anti-NS1 antibodies, and the reduced 357

binding of cross-reactive fusion-peptide antibodies to significantly enhance the specificity and accuracy 358

of using a ZIKV/DENV ratio test in differentiating ZIKV and DENV infections. 359

Similar percentages of ZIKV acute (69.6% and 69.6%), and convalescent sera (94.7% and 100%) 360

were positive for both ZIKV-wt-VLP-MAC-ELISA and ZIKV-NS1-MAC-ELISA, respectively. 361

Previous publications suggested a lower sensitivity of detecting anti-NS1 antibodies might be due to the 362

relatively low abundance of NS1 antibodies compared to anti-prM/E antibody in human sera.(7, 31) This 363

observation is supported by our study showed that depletion of anti-prM/E antibodies is essential to 364

enhance the sensitivity of detecting anti-NS1 antibody. As the result, FP-VLP-MAC-ELISA and anti-365

VLP-antibodies-depleted NS1-MAC-ELISA had similar PPV and NPV (Table 4). Multiple groups have 366

assessed the performance of anti-ZIKV IgM/IgG testing based on ZIKV NS1 antigens and suggested 367

that combined interpretation of results from both IgM and IgG ELISAs increased both sensitivity and 368

specificity(13, 19, 31, 34). In our study, by combining assays of both FP-VLP-MAC-ELISA and anti-369

VLP-antibodies-depleted NS1-MAC-ELISA, the accuracy of sero-diagnosis can reach up to 95% (57/60) 370

(Table S2). Considering the severe outcome of congenital Zika syndrome, three false positive specimens 371

(5%), misclassified as ZIKV infections, may be acceptable (Table S2). Our observation will require 372

further evaluation independently by other groups. We will provide VLPs and NS1 antigens directly or 373

through a commercial source for researchers who are interested to confirm our observation. 374

The important limitations of the current study is the small sample size of the validation serum 375

panel and the generalizability to a more complex acute serum panels such as subjects with prior 376

exposure to St. Louis Encephalitis virus, Japanese encephalitis virus, Powassan virus, and yellow fever 377

virus. Also, due to the co-circulation of both DENV and ZIKV in the same geographic locations, it is 378


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important in the future study to include serum specimens from those with current DENV infection with 379

prior exposure to ZIKV. Unfortunately, these types of serum collections are currently not available and 380

it will be the future goal in our ongoing study. In summary, the current study successfully develops a 381

novel approach to accurately differentiate ZIKV and DENV infections for evidence-based public health 382

intervention. 383


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Role of the funding source 384

The funding source of this study had no role in the study design, data collection, data analysis, 385

data interpretation, or writing of the report. The corresponding author had full access to all the data in 386

the study and had final responsibility for the decision to submit for publication. 387

388

389

Contributors 390

MTW and BSD performed all the construction of recombinant NS1 and VLP expression plasmids as 391

well as rabbit serum production. DYC and GJC designed the experiments and wrote the manuscript. 392

GJC provided the collection of well characterized developmental serum panels. DYC performed all the 393

ELISA and statistical analysis. FAM and JLM characterized all ZIKV and DENV serum panels from 394

Puerto Rico-Dengue Branch. All authors reviewed the draft, had critical input, and reviewed the final 395

submission. 396

397

Declaration of interests 398

We declare no competing interests. 399

400

Acknowledgements 401

DYC was supported by MOST oversea short-term fellowship in CDC to conduct this study. We are 402

thankful Ann Hunt and Ann Powers for scientific comments and English editing. 403

404

Funding 405


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Portions of this publication was made possible through support provided by the CDC intramural 406

research fund and the Office of Infectious Disease, Bureau for Global Health, U.S. Agency for 407

International Development, under the terms of an Interagency Agreement with CDC. The opinions 408

expressed herein are those of the author(s) and do not necessarily reflect the views of the CDC and U.S. 409

Agency for International Development. 410

411


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41. Zhang, B., B. Pinsky, J. Ananta, S. Zhao, S. Arulkumar, H. Wan, M. Sahoo, J. Abeynayake, J. Waggoner, 543 C. Hopes, M. Tang, and H. Dai. 2017. Diagnosis of Zika virus infection on a nanotechnology platform. Nat 544 Med 23:548-550. 545

546

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550

Figure legends 551

Fig 1. Flow chart of subject recruitment for the serum panels and case classification during Phase 552

I and II. The source of ZIKV-infected serum specimens was from participants presenting at the Puerto 553

Rico hospital from 2015-2017. Suspected cases of flavivirus infection were those with clinical 554

symptoms matching the case reporting criteria defined by US-CDC and were admitted to the hospital for 555

further diagnosis. All patients were classified as ZIKV or DENV infection based on the results of ZIKV- 556

or DENV-specific RT-PCR , respectively. Patients who tested negative by either ZIKV- or DENV-557

specific RT-PCR will be further subjected to an IgM test for the sera collected during a convalescent 558

phase. Only the specimens that were ZIKV-specific RT-PCR positive in the acute phase and had 559

seroconversion of IgM in the convalescent phase were included here. Those without confirmations by 560

RT-PCR or IgM laboratory results were excluded. The criteria of all ZIKV and DENV-confirmed 561

specimens used in Phase I included paired sera collected during the acute and convalescent phase of 562

illness and the disease status was further determined by FRµNT90 on ZIKV and DENV-2 in order to 563

properly establish the cut-off value of our assay. The only criteria for the serum panel used in Phase II 564

was double-blinded. All DENV positive specimens were collected during 2010-2012 during the time the 565

paired specimen from the same patient was rare. The negative specimens were taken during 2016 and 566

they are all negative by RT-PCR assay for DENV, ZIKV, and Chikungunya virus (CHIK) in acute phase 567

and negative for IgM in convalescent samples. 568

569

Fig 2. Analysis of the effect of depletion of anti-prM/E antibodies on NS1-MAC-ELISA using 570

ZIKV VLP alone or in combination with VLPs from DENV-2, DENV-3 and WNV. (A) Values of 571

P/N ratio of IgM from ZIKV-infected patient serum #1 (primary Zika infection patient ID:48B) and #2 572

(secondary Zika infection patient ID:45B) using ZIKV VLP alone for depletion and ZIKV-NS1 antigens 573


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for NS1-MAC-ELISA (+ on the x axis indicated with depletion and – indicated without depletion). (B) 574

Values of P/N ratio of IgM from one ZIKV- (Black bar) or DENV-infected (white bar) patient serum 575

using single, double, triple or quadruple combination of VLP antigens of ZIKV, DENV-2, DENV-3, 576

WNV for depletion as indicated in x-axis. Normal human serum was used as a negative control to 577

calculate the P/N ratio value by dividing the OD450 of ZIKV or DENV-confirmed patient serum with 578

that of negative-control serum. All data were obtained based on triplicate results from three independent 579

experiments, and standard deviations are indicated. **p<0.0001. P values were calculated by the two-580

tailed Student’s t test. 581

582

Fig 3. Distribution of P/N ratio of four groups of archived human patient sera and the 583

determination of optimal cutoff P/N value of ZIKV-VLP-MAC-ELISA from acute (left panel) and 584

convalescent (right panel) sera. (A) Values of P/N ratio for ZIKV, WNV DENV and other serum 585

specimens. (B) The plot of sensitivity versus 100-specificity based on P/N values from 42 ZIKV-586

confirmed sera and 173 control serum panel. (C) Optimal cutoff value was determined by the magnitude 587

of likelihood ratio positive (LR+) calculated by dividing sensitivity by 100-specificity. 588

589

590

Fig 4. Distribution of P/N ratio of four groups of human patient sera and the determination of 591

optimal cutoff P/N value of ZIKV-NS1-MAC-ELISA from acute (left panel) and convalescent 592

(right panel) sera. (A) Values of P/N ratio for ZIKV, WNV DENV and other serum specimens. (B) 593

The plot of sensitivity versus 100-specificity based on P/N values from 42 ZIKV-confirmed sera and 594

173 control serum panel. (C) Optimal cutoff value was determined by the magnitude of likelihood ratio 595

positive (LR+) calculated by dividing sensitivity by 100-specificity. 596


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597

Fig 5. P/N values (A) and Blant-Altman plots (B) of FP-VLP- and NS1-MAC-ELISA from 42 598

ZIKV-patient’s serum specimens 599

600

Fig 6. Algorithm of differentiating ZIKV and DENV infection by FP-VLP-MAC-ELISA and NS1-601

MAC-ELISA602


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603

604

605 606

607


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Table 1. Characteristics of serum panels used in this study

Serum Panel No of

specimens

Single/paired# RT-PCR 90%FRµNT Country Year

Testing panel

ZIKV 42 Paired (+) 4-fold increase Puerto Rico 2016

DENV 54 Paired (+) 4-fold increase Brazil 2009

WNV 97 Single n/d^ Highest titer South Dakota, USA 2008

Other* 76 Single

# paired specimens including acute specimens collected within 7 days of disease onset and convalescent phase specimens were collected

within 7-30 days after onset of symptoms

*A control serum panel consists of thirty non-DENV patient serum specimens, including IgG-positive yellow fever-17D (YF-17D)

post-vaccination sera (n=10), acute serum specimens from St. Louis encephalitis virus (SLEV) (n=2), chikungunya virus (n=10), or other

non-arboviral (n=8) infections, as well as forty-six normal human sera from the CDC blood bank.

^n/d: not determined due to undetectable viremia


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Table 2. Cross-reactivity of antibodies from four groups of human patient serum specimens against ZIKV and DENV-2/3 wild-type

(wt)-VLP and NS1 antigens

Serum panel ZIKV-WT-VLP-

MAC-ELISA

ZIKV-NS1-

MAC-ELISA

DENV2/3-WT-VLP-

MAC-ELISA+

DENV2-NS1-

MAC-ELISA*

ZIKV (21) 21/21(100%) 21/21(100%) 20/21(95.2%)* 12/21(57.1%)*

Acute (23) 16/23(69.6%) 16/23(69.6%) 22/23(95.7%)** 2/23 (8.7%)**

Convalescent(19) 18/19(94.7%) 19/19(100%) 19/19(100%)***

10/19(52.6%)***

WNV (56) 2/56 (3.6%) 0/56 (0%) NA NA

DENV (44) 28/44(63.6%) 32/44(72.7%) 42/44(95.5%) 40/44(90.9%)

Acute (40) 17/40(42.5%) 25/40(62.5%) 26/40(65.0%) 23/40(57.5%)

Convalescent(42) 23/42(54.8%) 24/42(57.1%) 40/42(95.2%) 38/42(90.5%)

Other(76) 0/76 (0%) 0/76 (0%) 0/76 (0%) 2/76 (2.6%)

NA: not available

+The cutoff of DENV-2/3 VLP or NS1-MAC-ELISA was based on our previous publication

24.

*P=0.0042 with significance level at 0.05

**p<0.0001 with significance level at 0.05

***p=0.0007 with significance level at 0.05


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Table 3. Positivity rate of MAC-ELISA using wild-type (wt)-VLP and FP-VLP from ZIKV and DENV-2/3 among four different groups of

serum panels

Serum panel ZIKV-wt-VLP ZIKV-FP-VLP DENV2/3-wt-VLP# DENV2/3-FP-VLP

ZIKV (21) 21/21 (100%) 21/21 (100%) 20/21 (95.2%) 20/21 (95.2%)

Acute (23) 16/23 (69.6%) 18/23 (78.3%) 22/23 (95.7%) 22/23 (95.7%)

Convalescent (19) 18/19 (94.7%) 19/19 (100%) 19/19 (100%) 18/19 (94.7%)

WNV (56) 2/56 (3.6%) 0/56 (0%) NA NA

DENV (44) 28/44 (63.6%)+ 17/44 (38.6%)

+ 42/44 (95.5%) 38/44 (86.4%)

Acute (40) 17/40 (42.5%)+ 13/40 (32.5%)

+ 22/40 (55.0%) 15/40 (37.5%)

Convalescent (42) 23/42 (54.8%)+ 9/42 (21.4%)

+ 40/42 (95.2%) 38/42 (90.5%)

Other (76)@

0/76 (0%) 0/76 (0%) 0/76 (0%) 0/76 (0%) # The cutoff of DENV-2/3 VLP based on our previous publications

24, 25

@

A control serum panel including ten yellow fever IgG-positivepost (17D vaccinated), two St. Louis encephalitis virus (SLEV) IgM postive), ten

chikungunya virus IgM positive,

eight non-arboviral patients' and 46 normal human serum specimens from CDC blood

bank collection.

+ P<0.05 with statistical significance


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Table 4. Sensitivity, Specificity, positive predictive value (PPV) and negative predictive value (NPV) of

FP-VLP-MAC-ELISA and NS1-MAC-ELISA for the validation serum panel based on the developed algorithm

Assay Disease

status

Disease

prevalence

(95%CI*)

Sensitivity

(95%CI*)

Specificity

(95%CI*)

PPV

(95%CI*)

NPV

(95%CI*)

FP-VLP-MAC-ELISA ZIKV 33.30% 100% 80% 71.40%

100% (21.7-46.7%) (83.2-100%) (64.4-91.0%) (57.4-82.3%)

DENV

75% 92.50% 83.30% 88.10%

(50.9-91.3%) (79.6-98.4%) (62.1-93.9%) (77.5-94.1%)

NS1-MAC-ELISA ZIKV 33.30% 80% 95% 88.90% 90.50%

(21.7-46.7%) (56.3-94.3%) (83.1-99.4%) (67.1-96.9%) (79.8-95.8%)

DENV

100% 92.50% 87.00% 100%

(83.2-100%) (79.6-98.4%) (69.2-95.2%)

*95%CI: 95% confidence interval


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Comprehensive evaluation of differential serodiagnosis ...Dec 10, 2018 · 1 C omprehensive evaluation of differential serodiagnosis between Zika and dengue 2 viral infection 3 4

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