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1 DISCLAIMER This paper was submitted to the Bulletin of the World Health Organization and was posted to the Zika open site, according to the protocol for public health emergencies for international concern as described in Christopher Dye et al. ( The information herein is available for unrestricted use, distribution and reproduction in any medium, provided that the original work is properly cited as indicated by the Creative Commons Attribution 3.0 Intergovernmental Organizations licence (CC BY IGO 3.0). RECOMMENDED CITATION Chang HH, Grad YH, Camerini D, Lipsitch M. Designing serological diagnostics based on evolutionarily divergent immunogenic regions in the Zika virus genome. [Submitted]. Bull World Health Organ. E-pub: 18 July doi: Designing serological diagnostics based on evolutionarily divergent immunogenic regions in the Zika virus genome Hsiao-Han Chang, a Yonatan H. Grad, b David Camerini, c & Marc Lipsitch d a Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA b Division of Infectious Diseases, Brigham and Women s Hospital, Harvard Medical School, Boston, Massachusetts, USA c The Center for Virus Research, University of California, Irvine, California, USA d Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA Correspondence to Hsiao-Han Chang ( hhchang@hsph.harvard.edu). (Submitted: 14 July 2016 Published online: 18 July 2016)

2 Abstract Objective A sensitive and specific serodiagnostic test that can detect past ZIKV infection is required for monitoring the current Zika virus (ZIKV) outbreak. Developing serodiagnostics for ZIKV is challenging due to cross-reactivity with other flaviviruses. Here we analyze the patterns of homology using publicly available genomic sequencing data with the goal of helping develop better a serodiagnostic test. Methods We performed comparative genomes of ZIKV, other flaviviruses, and Chikungunya virus to obtain the proportion of shared amino acid between viruses and within-zikv diversity were calculated for all amino acid k-mers across the genome, with k ranging from 10 to 100. Findings We identified peptide fragments that are most divergent between ZIKV and other flaviviruses and CHIKV and conserved within-zikv. These peptide fragments are most likely to have both sensitivity and specificity if used for serodiagnostics. Conclusion This analysis provides a step toward the development of a serodiagnostic test that achieves the WHO target product profile for ZIKV infection and co-circulating flaviviruses.

3 Introduction Two critical goals in the ongoing Zika virus (ZIKV) epidemic are (1) monitoring the number and geographical and demographical distribution of cases and (2) defining the association of ZIKV infection with other diseases, such as microcephaly and Guillain Barre syndrome. However, achieving these goals is very difficult in the absence of a sensitive and specific serodiagnostic test that can detect past ZIKV infection. WHO target product profiles describe the importance of developing a diagnostic test for ZIKV that differentiates Chikungunya virus (CHIKV), dengue virus (DENV) and ZIKV (1). While nucleic acid-based diagnostic tools can detect ZIKV RNA genome in the context of active infection and differentiate between ZIKV and DENV (2, 3), there is currently no widely available serodiagnostic test that can detect anti- ZIKV IgM and IgG and differentiate past infection with CHIKV, DENV and ZIKV with high specificity. It is challenging to develop serodiagnostics for ZIKV infection because antibodies against ZIKV, DENV, and other flaviviruses are cross-reactive and can even be crossneutralizing (4-10). Current serological assays, plaque reduction neutralization tests (PRNT), may not be able to distinguish between ZIKV and other flavivirus infections or previous vaccination with yellow fever virus (YFV) and Japanese encephalitis virus (JEV) due to crossreactive antibodies (11, 12). It has been shown that neutralizing monoclonal antibodies generated against recombinant fragments of the envelope (E) protein of dengue serotype 2 virus tend to be cross-reactive among flaviviruses, while non-neutralizing antibodies can be species specific (13). We propose that there may be regions of dissimilarity across flaviviruses that are immunogenic can be used as the basis for serodiagnostics that will provide readouts specific for ZIKV and/or other related viruses. Utilizing publicly available genomic sequencing data of ZIKV, other flaviviruses (DENV, West Nile virus [WNV], JEV, YFV), and CHIKV, we analyzed patterns of inferred protein sequence homology across species and diversity within ZIKV. We identified protein fragments that are conserved within ZIKV and variable among different flaviviruses and CHIKV. These fragments may be less likely to be cross-reactive because of dissimilarity and can aid in the development of much-needed Zika serotdiagnostics. Methods We used dataset A of ZIKV sequences from Faria et al. (14). All the protein sequences of DENV, WNV, JEV, YFV and CHIKV were downloaded from the NCBI protein database or Virus Variation Resource (Table S1) (15). We used BLASTP (16) to find homologous regions across virus species with the E-value threshold = 10 for all flaviviruses and = 1000 for CHIKV due to its larger divergence from ZIKV. The proportion of shared amino acid between viruses and within-zikv genetic diversity were calculated for all amino acid k-mers across the genome, with k ranging from 10 to 100, using a sliding window approach. In order to be conservative, we identified peptide homology between species by the maximum homology among all the pairs of isolates for each window considered. For the homology with DENV, we used the highest homology between ZIKV and all different serotypes of DENV for each window considered. We used both the average pairwise polymorphism (π) and the proportion of segregating sites (S) to

4 characterize within-zikv diversity. In the figures, we show the proportion of segregating sites because it is less sensitive to population structure. Results On average, ZIKV shares 55.6% (DENV), 46.0% (YFV), 56.1% (JEV), 57.0%(WN) and 1.26% (CHIKV) homology with other flaviviruses and CHIKV. Figure 1 and Figure S1 shows the homology between ZIKV and other closely related virus species and within-zikv diversity for all 100-mers throughout the genome. Regions of NS2A have the lowest between-virus similarity and relatively low within-zikv diversity, and are therefore the regions most likely to have both sensitivity and specificity for diagnostics. In addition, NS2A has the lowest homology among all pairs of flavivirus species (Figure S2). While NS2A has low diversity in ZIKV, it has high diversity in other flavivirus species (Figure S3). Because our homology measure is the highest homology among all pairs of isolates between species, high diversity in other species means that the homology in real-world settings can be even smaller. The homology between ZIKV and other species and within ZIKV diversity for k-mers other than 100 can be found in Table S2. Interestingly, homology with ZIKV is negatively associated with within-denv diversity, especially for DENV1 (Figure 2). This can be explained by purifying selection: regions under stronger selective constraints tend to more conserved and have higher homology between species and lower diversity within species. We do not observe this pattern for within-zikv diversity, and this could be possibly due to the smaller sample size or smaller effective population size for ZIKV. Discussion We showed that some regions in the proteome of ZIKV have lower homology among different flavivirus species and low within-species diversity. These regions can potentially be useful for the development of diagnostics. This possibility could be evaluated using peptide microarrays made up of k-mers from a collection of viruses to identify signatures of single and potentially multiple infections by these viruses. Moreover, the advantage of array-based method is to combine information from all different protein fragments in the genome. The signal from individual fragments does not need to be very strong, and the level of reactivity across all different fragments can be used together to distinguish ZIKV and other flavivirus infections. Protein microarrays have been used for distinguishing serologic responses between closely related bacterial pathogens (17). Once a signature is identified, a diagnostic employing only the most important contributors to that signature might be designed and produced. Recently, Euroimmun developed immunoglobulin M and immunoglobulin G enzymelinked immunosorbent assay (IgM and IgG ELISA) based on ZIKV nonstructural protein NS1 and preliminary tests were shown to be specific to ZIKV (18, 19). Our analysis showed that within-zikv NS1 diversity is low (Figure 1, S1 and S3), suggesting high sensitivity for ZIKV detection across geographical locations, while its cross-flavivirus homology is not particularly low (Figure 1 and S1). However, although the specificity they presented is encouraging, the evidence is limited because the sample size is small and the assays have not been tested on the

5 samples from regions with endemic DENV infections or different stages of infection. Moreover, multiple approaches are needed. It will be valuable to have a diagnostic that is simultaneously sensitive for other flaviviruses (1) and usable for those who have been multiply infected, so that multiple assays are not required to diagnose current or past flavivirus infection(s). The peptide array-based method we present has the potential to include markers that together are sensitive and specific for each flavivirus infection. Other factors, such as glycosylation, might affect cross-reactivity, and peptide-sequence homology is unlikely to fully predict cross-reactivity. Nonetheless, this analysis based on publicly available sequences provides a step toward the development of a serodiagnostic test that achieves the WHO target product profile for ZIKV infection and co-circulating flaviviruses. Author contributions ML and YHG designed and oversaw the analysis. HC performed the analysis. DC commented on the analysis. HC wrote the manuscript with input from all other authors. Acknowledgements We thank Xiaowu Liang and Taj Azarian for helpful discussions. Funding Research reported in this article was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award no. U54GM The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Conflict of Interest HC and YHG declare no conflict of interest. DC has dual employment at UC Irvine and Antigen Discovery Inc. ML has received consulting fees from Pfizer and Affinivax and Antigen Discovery and grants through Harvard T.H. Chan School of Public Health from Pfizer and PATH Vaccine Solutions.

6 Figure 1. Within-ZIKV diversity vs. homology between ZIKV and other flaviviruses and CHIKV of all sliding-window 100-mers across the genome. NS2A shows lowest homology with other viruses and relatively low within-zikv diversity.

7 Figure 2. Within-DENV diversity vs. their homology with ZIKV of all sliding-window 100-mers across the genome. Within-DENV diversity is negatively associated with the homology between DENV and ZIKV.

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