A METHOD OF IDENTIFYING A FLAVIVIRUS INFECTION, AND RELATED PEPTIDES, KITS AND COMPOSITIONS

Abstract

There is provided a method of identifying a flavivirus infection selected from Zika virus (ZIKV), Dengue virus (DENV) and combination thereof in a subject, the method comprising determining whether a sample of the subject reacts with a peptide associated with a certain relative binding capacity. Also claimed are kits, isolated peptides, immune system stimulating compositions comprising specific peptides and a method of distinguishing ZIKV infection from DENV infection.

Claims

1. A method of identifying a flavivirus infection selected from Zika virus ZIKV), dengue virus (DENV) and combination thereof in a subject, the method comprising: determining whether a sample of the subject reacts with a peptide P that is capable of giving a relative binding capacity BC.sub.relative≤0.05 or ≥0.1, wherein ${BC}_{relative} = \frac{R_{P 1 z} - R_{P 2 z}}{R_{P 2 z}} - \frac{R_{P 1 d} - R_{P 2 d}}{R_{P 2 d}}$ (i) wherein where the peptide P comprises a ZIKV-derived peptide, R.sub.P1z=response of a ZIKV-induced antigen binding protein with peptide P, R.sub.P2z=response of the ZIKV-induced antigen binding protein with a corresponding peptide C comprising a DENV-derived peptide having a sequence homologous to the peptide P, R.sub.P1d=response of a DENV-induced antigen binding protein with the peptide P, R.sub.P2d=response of the DENV-induced antigen binding protein with the corresponding peptide C comprising a DENV-derived peptide having a sequence homologous to the peptide P, $\frac{R_{P 1 z} - R_{P 2 z}}{R_{P 2 z}} = binding capacity of the ZIKV-induced antigen binding protein, \frac{R_{P 1 d} - R_{P 2 d}}{R_{P 2 d}} = binding capacity of the DENV-induced antigen binding protein,$ or (ii) wherein where the peptide P comprises a DENV-derived peptide, R.sub.P1z=response of a ZIKV-induced antigen binding protein with a corresponding peptide C comprising a ZIKV-derived peptide having a sequence homologous to the peptide P, R.sub.P2z=response of the ZIKV-induced antigen binding protein with the peptide P, R.sub.P1d=response of a DENV-induced antigen binding protein with the corresponding peptide C comprising a ZIKV-derived peptide having a sequence homologous to the peptide P, R.sub.P2d=response of the DENV-induced antigen binding protein with the peptide P, $\frac{R_{P 1 z} - R_{P 2 z}}{R_{P 2 z}} = binding capacity of the ZIKV-induced antigen binding protein, \frac{R_{P 1 d} - R_{P 2 d}}{R_{P 2 d}} = binding capacity of the DENV-induced antigen binding protein .$

2. The method of claim 1, wherein the peptide P comprises an epitope on a prM protein, an E glycoprotein or a NS1 protein of ZIKV or DENV, optionally wherein the epitope is located in a solvent-exposed region of the prM protein, the E glycoprotein or the NS1 protein.

3. (canceled)

4. The method of claim 1, wherein the peptide P is from 5 to 25 amino acids long.

5. The method of claim 1, wherein the peptide P shares no more than 50% sequence similarity with the corresponding peptide C.

6. The method of claim 1, wherein the peptide P comprises one or more ZIKV-derived peptide selected from the group consisting of: TABLE-US-00020 SEQ ID NO: 7 (LDEGVEPDDVDCWCNTT); SEQ ID NO: 36 (SVEGELNAILEENGVQ); SEQ ID NO: 38 (GKSYFVRAAKTNNSFVVD); SEQ ID NO: 39 (GDTLKECPLKHRAWNSFL); SEQ ID NO: 46 (KVHVEETCGTRGPSLRST); SEQ ID NO: 49 (ECTMPPLSFRAK); SEQ ID NO: 3 (SFPTTLGMNKCYIQIMDL); SEQ ID NO: 26 (GALEAEMDGAKGRLSSGH); SEQ ID NO: 32 (FKSLFGGMSWFSQILIGT); SEQ ID NO: 9 (YGTCHHKKGEARRSR); SEQ ID NO: 17 (PENLEYRIMLSVHGSQHS); SEQ ID NO: 43 (REGYRTQMKGPWHSEELE); SEQ ID NO: 45 (IRFEECPGTKVHVEETCG); a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof; and/or one or more DENV-derived peptide selected from the group consisting of: TABLE-US-00021 SEQ ID NO: 58 (HITEVEPEDIDCWCNLT); SEQ ID NO: 87 (QIANELNYILWENNIK); SEQ ID NO: 89 (GKAKIVTAETQNSSFIID); SEQ ID NO: 90 (GPNTPECPSASRAWNVWE); SEQ ID NO: 97 (TVVITENCGTRGPSLRTT); SEQ ID NO: 100 (SCTLPPLRYMGE); SEQ ID NO: 54 (LFKTASGINMCTLIAMDL); SEQ ID NO: 77 (GATEIQNSGGTSIFAGH); SEQ ID NO: 83 (YTALFSGVSWVMKIGIGV); SEQ ID NO: 60 (TSTWVTYGTCNQAG); SEQ ID NO: 68 (YENLKYTVIITVHTGDQH); SEQ ID NO: 94 (RPGYHTQTAGPWHLGKLE); SEQ ID NO: 96 (LDFNYCEGTTVVITENCG); or a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof.

7. The method of claim 1, wherein the method comprises determining whether the sample reacts with one or more peptide selected from the group consisting of: TABLE-US-00022 SEQ ID NO: 7 (LDEGVEPDDVDCWCNTT); SEQ ID NO: 36 (SVEGELNAILEENGVQ); SEQ ID NO: 38 (GKSYFVRAAKTNNSFVVD); SEQ ID NO: 39 (GDTLKECPLKHRAWNSFL); SEQ ID NO: 46 (KVHVEETCGTRGPSLRST); SEQ ID NO: 49 (ECTMPPLSFRAK); SEQ ID NO: 58 (HITEVEPEDIDCWCNLT); SEQ ID NO: 87 (QIANELNYILWENNIK); SEQ ID NO: 89 (GKAKIVTAETQNSSFIID); SEQ ID NO: 90 (GPNTPECPSASRAWNVWE); SEQ ID NO: 97 (TVVITENCGTRGPSLRTT); SEQ ID NO: 100 (SCTLPPLRYMGE); a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof; and/or wherein where the sample reacts with the one or more peptide or the portions thereof, the subject is indicated for flavivirus infection.

8. The method of claim 1, wherein the method is a method of identifying a flavivirus infection in an acute phase, and the method comprises determining whether the sample reacts with one or more peptide selected from the group consisting of: TABLE-US-00023 SEQ ID NO: 7 (LDEGVEPDDVDCWCNTT); SEQ ID NO: 36 (SVEGELNAILEENGVQ); SEQ ID NO: 38 (GKSYFVRAAKTNNSFVVD); SEQ ID NO: 58 (HITEVEPEDIDCWCNLT); SEQ ID NO: 87 (QIANELNYILWENNIK); SEQ ID NO: 89 (GKAKIVTAETQNSSFIID); wherein where the sample reacts with the one or more peptide or the portions thereof, the subject is indicated for flavivirus infection in an acute phase.

9. The method of claim 1, wherein the method comprises determining whether the sample reacts with one or more peptide selected from the group consisting of: TABLE-US-00024 SEQ ID NO: 3 (SFPTTLGMNKCYIQIMDL); SEQ ID NO: 26 (GALEAEMDGAKGRLSSGH); SEQ ID NO: 32 (FKSLFGGMSWFSQILIGT); a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof; wherein where the sample reacts with the one or more peptide or the portions thereof, the subject is indicated for ZIKV infection.

10. The method of claim 1, wherein the method is a method of identifying a ZIKV infection in an acute phase, and the method comprises determining whether the sample reacts with: TABLE-US-00025 SEQ ID NO: 32 (FKSLFGGMSWFSQILIGT); a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof; wherein where the sample reacts with the peptide or the portions thereof, the subject is indicated for ZIKV infection in an acute phase.

11. The method of claim 1, wherein the method comprises determining whether the sample reacts with one or more peptide selected from the group consisting of: TABLE-US-00026 SEQ ID NO: 60 (TSTWVTYGTCNQAG); SEQ ID NO: 68 (YENLKYTVIITVHTGDQH); SEQ ID NO: 94 (RPGYHTQTAGPWHLGKLE); SEQ ID NO: 96 (LDFNYCEGTTVVITENCG); and/or a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof; wherein where the sample reacts with the one or more peptide or the portions thereof, the subject is indicated for DENV infection.

12. The method of claim 1, wherein determining whether the sample reacts with the peptide P comprises performing an immunoassay to assess whether antigen-binding proteins that are capable of binding to the peptide are present in the sample.

13. The method of claim 1, the method further comprising administering to the subject a ZIKV and/or DENV treatment regimen if the subject is indicated for ZIKV and/or DENV infection.

14. A kit for identifying a flavivirus infection selected from Zika virus, dengue virus and combination thereof in a subject, the kit comprising a peptide P that is capable of giving a relative binding capacity BC.sub.relative≤0.05 or ≥0.1, wherein ${BC}_{relative} = \frac{R_{P 1 z} - R_{P 2 z}}{R_{P 2 z}} - \frac{R_{P 1 d} - R_{P 2 d}}{R_{P 2 d}}$ wherein where the peptide P comprises a ZIKV-derived peptide, R.sub.P1z=response of a ZIKV-induced antigen binding protein with peptide P, R.sub.P2z=response of the ZIKV-induced antigen binding protein with a corresponding peptide C comprising a DENV-derived peptide having a sequence homologous to the peptide P, R.sub.P1d=response of a DENV-induced antigen binding protein with the peptide P, R.sub.P2d=response of the DENV-induced antigen binding protein with the corresponding peptide C comprising a DENV-derived peptide having a sequence homologous to the peptide P, $\frac{R_{P 1 z} - R_{P 2 z}}{R_{P 2 z}} = binding capacity of the ZIKV-induced antigen binding protein, \frac{R_{P 1 d} - R_{P 2 d}}{R_{P 2 d}} = binding capacity of the DENV-induced antigen binding protein,$ wherein where the peptide P comprises a DENV-derived peptide, R.sub.P1z=response of a ZIKV-induced antigen binding protein with a corresponding peptide C comprising a ZIKV-derived peptide having a sequence homologous to the peptide P, R.sub.P2z=response of the ZIKV-induced antigen binding protein with the peptide P, R.sub.P1d=response of a DENV-induced antigen binding protein with the corresponding peptide C comprising a ZIKV-derived peptide having a sequence homologous to the peptide P, R.sub.P2d=response of the DENV-induced antigen binding protein with the peptide P, $\frac{R_{P 1 z} - R_{P 2 z}}{R_{P 2 z}} = binding capacity of the ZIKV-induced antigen binding protein, \frac{R_{P 1 d} - R_{P 2 d}}{R_{P 2 d}} = binding capacity of the DENV-induced antigen binding protein .$

15. The kit of claim 14, wherein the peptide P comprises one or more ZIKV-derived peptide selected from the group consisting of: TABLE-US-00027 SEQ ID NO: 7 (LDEGVEPDDVDCWCNTT); SEQ ID NO: 36 (SVEGELNAILEENGVQ); SEQ ID NO: 38 (GKSYFVRAAKTNNSFVVD); SEQ ID NO: 39 (GDTLKECPLKHRAWNSFL); SEQ ID NO: 46 (KVHVEETCGTRGPSLRST); SEQ ID NO: 49 (ECTMPPLSFRAK); SEQ ID NO: 3 (SFPTTLGMNKCYIQIMDL); SEQ ID NO: 26 (GALEAEMDGAKGRLSSGH); SEQ ID NO: 32 (FKSLFGGMSWFSQILIGT); SEQ ID NO: 9 (YGTCHHKKGEARRSR); SEQ ID NO: 17 (PENLEYRIMLSVHGSQHS); SEQ ID NO: 43 (REGYRTQMKGPWHSEELE); SEQ ID NO: 45 (IRFEECPGTKVHVEETCG); a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof; and/or one or more DENV-derived peptide selected from the group consisting of: TABLE-US-00028 SEQ ID NO: 58 (HITEVEPEDIDCWCNLT); SEQ ID NO: 87 (QIANELNYILWENNIK); SEQ ID NO: 89 (GKAKIVTAETQNSSFIID); SEQ ID NO: 90 (GPNTPECPSASRAWNVWE); SEQ ID NO: 97 (TVVITENCGTRGPSLRTT); SEQ ID NO: 100 (SCTLPPLRYMGE); SEQ ID NO: 54 (LFKTASGINMCTLIAMDL); SEQ ID NO: 77 (GATEIQNSGGTSIFAGH); SEQ ID NO: 83 (YTALFSGVSWVMKIGIGV); SEQ ID NO: 60 (TSTWVTYGTCNQAG); SEQ ID NO: 68 (YENLKYTVIITVHTGDQH); SEQ ID NO: 94 (RPGYHTQTAGPWHLGKLE); SEQ ID NO: 96 (LDFNYCEGTTVVITENCG); or a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof.

16. The kit of claim 14 further comprising one or more of the following: a plate coated with a capture agent for anti-ZIKV and/or anti-DENV, and a detection agent for detecting the presence of captured anti-ZIKV and/or anti-DENV, wherein the capture agent and the detection agent comprise a ZIKV and/or DENV antigen and/or an anti-immunoglobulin.

17. The method of claim 1, wherein the subject comprises an Asian subject.

18. A composition comprising an isolated peptide or an immune system stimulating composition comprising an isolated peptide, wherein said isolated peptide is selected from the group consisting of: TABLE-US-00029 SEQ ID NO: 7 (LDEGVEPDDVDCWCNTT); SEQ ID NO: 36 (SVEGELNAILEENGVQ); SEQ ID NO: 38 (GKSYFVRAAKTNNSFVVD); SEQ ID NO: 39 (GDTLKECPLKHRAWNSFL); SEQ ID NO: 46 (KVHVEETCGTRGPSLRST); SEQ ID NO: 49 (ECTMPPLSFRAK); SEQ ID NO: 3 (SFPTTLGMNKCYIQIMDL); SEQ ID NO: 26 (GALEAEMDGAKGRLSSGH); SEQ ID NO: 32 (FKSLFGGMSWFSQILIGT); SEQ ID NO: 9 (YGTCHHKKGEARRSR); SEQ ID NO: 17 (PENLEYRIMLSVHGSQHS); SEQ ID NO: 43 (REGYRTQMKGPWHSEELE); SEQ ID NO: 45 (IRFEECPGTKVHVEETCG); SEQ ID NO: 58 (HITEVEPEDIDCWCNLT); SEQ ID NO: 87 (QIANELNYILWENNIK); SEQ ID NO: 89 (GKAKIVTAETQNSSFIID); SEQ ID NO: 90 (GPNTPECPSASRAWNVWE); SEQ ID NO: 97 (TVVITENCGTRGPSLRTT); SEQ ID NO: 100 (SCTLPPLRYMGE); SEQ ID NO: 54 (LFKTASGINMCTLIAMDL); SEQ ID NO: 77 (GATEIQNSGGTSIFAGH); SEQ ID NO: 83 (YTALFSGVSWVMKIGIGV); SEQ ID NO: 60 (TSTWVTYGTCNQAG); SEQ ID NO: 68 (YENLKYTVIITVHTGDQH); SEQ ID NO: 94 (RPGYHTQTAGPWHLGKLE); SEQ ID NO: 96 (LDFNYCEGTTVVITENCG); or a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof.

19. (canceled)

20. The method of claim 1, wherein the method further distinguishes ZIKV infection from DENV infection in a subject, the method comprising: determining whether a sample of the subject reacts with a peptide of SEQ ID NO: 32 (FKSLFGGMSWFSQILIGT); a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof, wherein where the sample reacts with the peptide or the portions thereof, the subject is indicated for ZIKV infection; and/or determining whether a sample of the subject reacts with a peptide of SEQ ID NO: 9 (YGTCHHKKGEARRSR); a peptide sharing at least 75% sequence identity thereto; or a peptide differing by one, two, three or four amino acids thereto; or portions thereof, wherein where the sample reacts with the peptide or the portions thereof, the subject is indicated for DENV infection.

21. The kit of claim 14, wherein the subject comprises an Asian subject.

Description

BRIEF DESCRIPTION OF FIGURES

[0198] FIG. 1. Antibody profiles of healthy controls and ZIKV patients of Singapore cohort in 2016. Total (a) IgM and (b) IgG antibody titres of 45 healthy donors were determined by virion-based ELISA using purified ZIKV, DENV or CHIKV virions and plasma dilution of 1:2000. Data are presented as mean, with dotted line indicating the respective mean+SD values. Samples with OD values less than mean+SD for both IgM and IgG, and across all three viruses are highlighted in black (n=22), and were combined together to form the pooled healthy control for subsequent experiments. Samples with OD values more than the cut-off are denoted as clear symbols (n=23). (c) Total anti-ZIKV IgM and IgG of ZIKV patients were determined at plasma dilutions of 1:200, 1:1000, 1:2000, 1:4000 and 1:8000 in virion-based ELISA using purified ZIKV virions at time points of acute (n=58), early convalescent (n=43), late convalescent (n=45), early recovery (n=41), late recovery (n=38), and full recovery (n=32). Pooled plasma of healthy donors was used as negative control. Data are presented as mean±SEM. (d-e) Total anti-DENV (d) IgM and (e) IgG antibody titres in plasma samples of ZIKV patients at first collection time point were determined by virion-based ELISA using purified DENV virions in the same method as (c). Data are presented as mean±SEM. All ELISA readings were in duplicates. (f) Number and percentage of patients that were positive or negative for anti-DENV IgM and IgG at the first collection of plasma specimen (1:200 and 1:2000 dilutions respectively)

[0199] FIG. 2 Antibody profiles of ZIKV patients of Singapore cohort in 2016 over time. (a-c) Total anti-ZIKV (a) IgM and (b) IgG antibody titres in patients' plasma samples, at dilutions 1:200 and 1:2000 respectively, were determined by virion-based ELISA using purified ZIKV virions. Pooled plasma of healthy donors was used as negative control. Data are presented as mean±SEM, with dotted line indicating mean of pooled healthy control. (c) Number and percentage of patients that are positive or negative for anti-ZIKV IgM and IgG at the respective time points. (d) IgG isotype titres in patients' plasma samples were determined at 1:200 dilution in a ZIKV virion-based ELISA. Data are presented as mean±SEM, with dotted line indicating mean of pooled healthy control. All ELISA readings were conducted in duplicates or triplicates. [Acute (n=58), early convalescent (n=43), late convalescent (n=45), early recovery (n=41), late recovery (n=38), full recovery (n=32)]. (e-f) In vitro neutralising capacity of pooled ZIKV patients and pooled healthy control were tested at 1:1000 plasma dilution via flow cytometry. (e) Plasma samples were pooled according to levels of anti-ZIKV IgG titre [group of low titre patients are denoted as square symbol, while group of high titres are denoted as triangle symbol as shown in (b)] for acute [low (n=37), high (n=21)], early convalescent [low (n=29), high (n=14)], and late convalescent [low (n=28), high (n=17)] time points. (f) Plasma samples collected at the recovery phases were pooled together at the respective time points [early recovery (n=41), late recovery (n=38), full recovery (n=32)]. Results are expressed as percentage of control infection. Data presented as mean±SD and representative of 2 independent experiments. Statistical analysis between virus only and pooled healthy or patient samples was carried out using Mann-Whitney U test, two-tailed, with Bonferroni correction for multiple testing (*P<0.05).

[0200] FIG. 3. Neutralising capacities of antibodies of ZIKV patients against ZIKV and DENV. In vitro neutralising capacity of pooled ZIKV patients against (a) ZIKV and (b) DENV were tested at 1:500, 1:1000 and 1:2000 plasma dilutions via flow cytometry. Plasma samples were pooled according to levels of anti-ZIKV IgG titre (shown in FIG. 2) for acute [low (n=37), high (n=21)], early convalescent [low (n=29), high (n=14)], and late convalescent [low (n=28), high (n=17)] time points. Plasma samples collected at the recovery phases were pooled together at the respective time points [early recovery (n=41), late recovery (n=38), full recovery (n=32)]. Plasma of pooled healthy was used as negative control. Results are expressed as percentage of control infection. Data presented as mean±SD and representative of 2 independent experiments.

[0201] FIG. 4. Preliminary mapping of common flavivirus, ZIKV-specific, and DENV-specific linear B-cell pooled epitopes within ZIKV and DENV proteome using ZIKV and DENV patient samples. (a) Polyprotein of ZIKV H/PF/2013 (UniProtKB accession: A0A024B7W1), matched to results of pooled peptide-based ELISA experiments. Plasma samples of ZIKV patients (n=30) and serum samples of DENV patients (n=20) at 1:2000 dilution in duplicates were subjected to peptide-based ELISA using pooled peptides covering the precursor of membrane (prM; pools 1-4), envelope (E; pools 5-17) and nonstructural 1 (NS1; pools 18-25) proteins of ZIKV and DENV proteome. Each pool consists of 5 peptides of 18-mer length, with overlapping sequence of 10 amino acids. IgG response of patients were normalised to mean of pooled healthy control. Patients' response to ZIKV and DENV pooled peptide-pairs were compared and the mean binding capacity are presented in a heat-map. A value of 0 on the scale denotes patients showing equal binding response to a ZIKV and DENV pooled peptide-pair, whereas values larger than 0 show preferential of patients to bind to ZIKV pooled peptide. Values smaller than 0 show binding preference of patients to DENV pooled peptide. (b) Percentage recognition of ZIKV and DENV patients to peptide pools were calculated. (c) A schematic representation to denote potential common flavivirus, ZIKV-specific, and DENV-specific pools across prM, E and NS1 based on the heat-map analysis above.

[0202] FIG. 5. Mapping of common flavivirus, ZIKV-specific, and DENV-specific linear B cell epitopes using ZIKV and DENV patient samples. (a) Polyprotein of ZIKV H/PF/2013 (UniProtKB accession: A0A024B7W1). Plasma samples of ZIKV patients (n=30-44) and serum samples of DENV (n=20) patients at late convalescent phase were tested at 1:2000 dilution in a peptide-based ELISA in duplicates, using peptides that cover the precursor of membrane (prM: peptides 1-10), envelope (E; peptides 11-32) and non-structural 1 (NS1; peptides 33-51) proteins of ZIKV and DENV proteome. IgG response of patients were normalised to mean of pooled healthy control. Patients' response to ZIKV and DENV peptide-pairs were compared and the mean binding capacity are presented in a heat-map. A value of 0 on the scale denotes patients showing equal binding response to a ZIKV and DENV peptide-pair, whereas values larger than 0 show preferential of patients to bind to ZIKV peptide. Values smaller than 0 show binding preference of patients to DENV peptide. (b) A schematic representation to denote common flavivirus, ZIKV-specific, and DENV-specific peptides across prM, E and NS1 based on heat-map analysis above. (c-e) Genome organisation of ZIKV prM, E and NS1. Regions of amino acids corresponding to the identified linear B-cell epitopes in (c) prM, (d) E and (e) NS1 are shown. Numbers in boxes denote the peptide number, and the amino acid position in the respective proteome.

[0203] FIG. 6. Peptide binding capacity of ZIKV and DENV patients on potential common flavivirus, ZIKV-specific, and DENV-specific linear B-cell epitopes. Plasma samples of ZIKV (n=30-44) and serum samples of DENV (n=20) patients at late convalescent phase were tested at 1:2000 dilution in duplicates in a peptide-based ELISA, with pooled plasma of healthy donors used as negative control. The IgG binding capacity of patients positive for respective ZIKV and DENV peptide-pairs were calculated as [(ZIKV peptide response-DENV peptide response)/DENV peptide response] and the mean±SEM values are presented in (a) for potential common flavivirus, ZIKV-specific, and DENV-specific linear B-cell epitopes. The distribution of binding capacity of individual ZIKV and DENV patients are shown in (b) for common flavivirus, (c) for ZIKV-specific and (d) for DENV-specific peptides. Data presented as mean±SD. Statistical analysis was carried out using Mann-Whitney U test, two-tailed, with Bonferroni correction for multiple testing (**P<0.01).

[0204] FIG. 7. Characterisation of the antibody profile kinetics of ZIKV patients on common flavivirus and ZIKV-specific linear B-cell epitopes, and localisation of potential epitopes within the ZIKV and DENV proteome. (a-b) Plasma samples of ZIKV patients (n=27) at acute, late convalescent and full recovery phases were tested for IgG at 1:2000 dilution in duplicates using ZIKV and DENV peptides in a peptide-based ELISA. Pooled plasma of healthy donors was used as negative control and patients' data were normalised to mean of pooled healthy control. (a) Percentage of ZIKV patients positively binding to ZIKV and DENV peptides, and (b) binding capacity of ZIKV patients positively binding to peptides were calculated and presented in a heat-map. (c-e) Schematic diagrams showing the localisation of common flavivirus, ZIKV-specific, and DENV-specific epitopes on (c) prM protein of ZIKV and DENV (PDB: 3C6E), (d) E glycoprotein of ZIKV (PDB: 5JHM) and DENV (PDB: 1UZG), (e) stem-transmembrane (TM) domain of E glycoprotein of ZIKV (PDB: 51Z7) and DENV (PDB: 3J2P), and (f) NS1 protein of ZIKV (PDB: 5K6K) and DENV (PDB: 406B).

[0205] FIG. 8. Preliminary diagnostic validation of identified linear B-cell epitopes with patient cohorts. Convalescent plasma samples of ZIKV (n=10) and serum samples of DENV (n=10) patients from Singapore, and DENV (n=5), bacteria (n=5) and unknown (n=8) patients from Thailand were tested in a peptide-based ELISA in duplicates at 1:2000 dilution. Pooled healthy plasma was used as a negative control. (a) Sensitivity and specificity were determined for individual peptides. (b) Sensitivity and specificity of peptide mix of selected epitopes were determined. (c) Principal component analysis (PCA) of pooled healthy and patients' anti-IgG peptide response (OD values) were plotted in a graph with the percentage of variance indicated. (d-e) The peptide binding capacity of patients positively binding to peptides were calculated and statistically analysed by using Kruskal-Wallis tests with Bonferroni correction for multiple testing. Post hoc tests were done using Dunn's multiple comparison tests to determine (d) peptides with discriminating power, and (e) the peptide binding capacity distribution of patients. Data are presented as mean±SD. (*P<0.05, **P<0.01).

[0206] FIG. 9. Correlation analysis of antibody and peptide response. (a) Plasma samples of ZIKV patients (n=65) were pooled according to the levels of anti-ZIKV IgG titre (shown in FIG. 2b). Mean neutralising capacity of pooled ZIKV patients (shown in FIG. 2e-f) and mean anti-ZIKV IgG levels of ZIKV patients were calculated for all time points (from acute to full recovery) and correlation was carried out. (b-d) Plasma samples from ZIKV (n=30-44) and serum samples from DENV (n=20) patients at late convalescent time point were tested for anti-ZIKV or anti-DENV IgG respectively at 1:2000 dilution, using purified ZIKV or DENV virions in a virion-based ELISA. In addition, plasma/serum samples were tested at 1:2000 dilution in duplicates for peptide-specific IgG using ZIKV and DENV peptides in a peptide-based ELISA. Patients' response to ZIKV and DENV peptide-pairs were compared and peptide binding capacity was calculated. Correlation of (b) both ZIKV and DENV patients' antibody response to common flavivirus peptides, (c) ZIKV patients' antibody response to ZIKV-specific peptides, and (d) DENV patients' antibody response to DENV-specific peptides. Correlation analysis was carried out using Spearman's rank correlation. Spearman's rho (ρ) and P-value (P) are presented.

EXAMPLES

[0207] Example embodiments of the disclosure will be better understood and readily apparent to one of ordinary skill in the art from the following discussions and if applicable, in conjunction with the figures. It should be appreciated that other modifications related to structural, electrical and optical changes may be made without deviating from the scope of the invention. Example embodiments are not necessarily mutually exclusive as some may be combined with one or more embodiments to form new exemplary embodiments.

ZIKV Patients Produce a Robust and Protective Humoral Response

[0208] Forty-five healthy donors were first screened for the presence of IgM and IgG against ZIKV, DENV and chikungunya virus (CHIKV), the three main arboviruses co-circulating in Singapore and several parts of Asia using virion-based ELISA. Twenty-two donors which had antibody levels lower than the assigned cut-off (mean+SD) in all three viruses (FIG. 1a-b) were used as the healthy control pool, and set as a baseline reference.

[0209] Anti-ZIKV IgM and IgG levels of ZIKV patients from the Singapore outbreak in 2016 were longitudinally assessed using virion-based ELISA. Majority of the patients showed a robust ZIKV-specific humoral response FIG. 2a-c, FIG. 1c). Anti-ZIKV IgM was detected as early as in the acute phase (2-7 days post-illness onset, pio) and peaked at early convalescent (10-14 days pio), before decreasing during the recovery phases (3 months to 1 year pio) (FIGS. 2a and c, FIG. 1c). ZIKV-specific IgG titres peaked at early convalescent, persisted at high levels during late recovery, and were still detectable a year after infection (FIG. 2b-c, FIG. 1c). These patients were also screened for the presence of DENV-specific antibodies and 80% of the patients were negative for anti-DENV IgM in samples taken at the acute phase (FIGS. 1d and 1f). However, 75% of the patients were found to have anti-DENV IgG (FIG. 1e-f), suggesting that ZIKV IgG, but not IgM, cross-reacts with DENV.

[0210] IgG isotypes produced by ZIKV patients were then determined and highest titres of anti-ZIKV IgG1 and IgG3 subtypes were produced at early convalescent for IgG3, and late convalescent for IgG1 (FIG. 2d). To determine if antibodies produced in these patients were protective against ZIKV, neutralisation assays were carried out via flow cytometry (FIG. 2e-f, FIG. 3a). Efficient neutralisation (71% to 93%) was observed in early and late convalescent stages (FIG. 2e), whilst weak neutralisation (37% to 47%) was seen in late and full recovery stages (FIG. 2f). Neutralisation capacity of ZIKV patients correlated with levels of anti-ZIKV IgG (FIG. 1c and FIG. 9a). Plasma from these patients only minimally neutralised DENV (FIG. 3b), indicating ZIKV-specificity.

Identification of Specific B-Cell Linear Epitopes Recognised by Antibodies from ZIKV and DENV Patients

[0211] Preliminary mapping of specific ZIKV and DENV epitopes was first performed in a peptide-based ELISA on the most antigenic flavivirus antigens: prM, E and NS1, using pooled linear ZIKV and consensus DENV peptides. Plasma/serum samples of ZIKV and DENV patients taken at the late convalescent phase were used as IgG levels were highest at this time point (FIG. 1c). Results specifically showed two common flavivirus (pools 1 and 21), six potential ZIKV-specific (pools 6, 10, 11, 16, 17 and 24) and one potential DENV-specific (pool 19) pools were identified within the ZIKV and DENV proteome (Table 1, FIG. 4).

TABLE-US-00012 TABLE 1 Preliminary results of ZIKV and DENV patients response to ZIKV and DENV pooled peptides Percentage recognition (%).sup.† ZIKV Patients DENV Patients Mean binding Preliminary (n = 30) (n = 20) capacity.sup.‡ classification Peptide ZIKV DENV ZIKV DENV ZIKV DENV Relative of peptide Protein Pool Pool Pool Pool Pool Patients Patients difference.sup.§ pool.sup.¶ prM 1 96.7 96.7 95 100 −0.325 −0.360 0.035 Common 2 90.0 93.3 90 100 −0.392 −0.295 0.097 3 76.7 93.3 75 100 −0.684 −0.553 0.131 4 83.3 96.7 90 100 −0.313 −0.254 0.059 E 5 86.7 16.7 90 0 5.066 10.343 5.277 6 86.7 13.3 90 0 10.379 9.512 0.867 ZIKV-specific 7 86.7 30.0 80 5 3.102 4.222 1.120 8 40.0 13.3 10 0 1.212 0.741 0.471 9 73.3 76.7 75 60 −0.029 0.653 0.681 10 83.3 33.3 85 5 4.730 4.043 0.687 ZIKV-specific 11 83.3 96.7 90 85 0.763 0.301 0.462 ZIKV-specific 12 60.0 60.0 65 15 0.267 1.222 0.954 13 86.7 16.7 90 0 12.259 12.399 0.140 14 23.3 56.7 10 25 −0.513 −0.279 0.234 15 90.0 16.7 95 0 6.344 6.814 0.470 16 90.0 13.3 95 35 4.429 4.040 0.388 ZIKV-specific 17 83.3 20.0 85 0 7.079 5.210 1.869 ZIKV-specific NS1 18 90.0 100.0 85 100 −0.562 −0.601 0.039 19 50.0 100.0 20 100 −0.595 −0.716 0.120 DENV-specific 20 90.0 96.7 70 100 −0.600 −0.665 0.065 21 93.3 96.7 95 95 −0.014 −0.016 0.002 Common 22 90.0 96.7 90 90 −0.427 −0.404 0.022 23 90.0 96.7 90 90 −0.445 −0.396 0.049 24 90.0 93.3 85 90 0.134 −0.055 0.189 ZIKV-specific 25 83.3 96.7 80 95 −0.548 −0.533 0.015 .sup.†Patient samples are positive if their normalised peptide responses (calculated as OD of patient sample/mean OD of pooled healthy) are more than 1.01. .sup.‡Binding capacity of a patient positive for a peptide-pair was calculated as: normalised values of [(ZIKV peptide response-DENV peptide response)/DENV peptide response]. Values close to 0 denote equal binding of patient to ZIKV and DENV peptide. Values more than 0 denote a patients preference to bind to ZIKV peptide more than DENV peptide. Values less than 0 denote a patients preference to bind to DENV peptide more than ZIKV peptide. .sup.§Relative difference is calculated as the difference in the mean binding capacity of ZIKV patients and DENV patients. Values are rounded up to 3 decimal places. .sup.¶Common flavivirus epitopes: 60% of ZIKV and DENV patients recognise both ZIKV and DENV peptides of peptide-pair; ZIKV-specific epitopes: 60% of ZIKV patients recognise at least ZIKV peptide of peptide-pair; DENV-specific epitopes: 60% of DENV patients recognise at least DENV peptide of peptide-pair.

[0212] Thereafter, new peptides selectively designed based on exposed residues and computational predictions were re-synthesised for subsequent experiments (Table 2).

TABLE-US-00013 TABLE 2 ZIKV and DENV peptides information Amino acid position Peptide on ZIKV similarity % (accession Corresponding Corresponding identity, % Classification Peptide KJ776791) ZIKV DENV query of potential Protein no Start End sequence sequence cover) epitope prM 1 6 23 RGSAYYMYLDRNDAGEAI RDGEPRMIVGKNERGKSL No similarity 2 15 32 DRNDAGEAISFPTTLGMN GKNERGKSLLFKTASGIN No similarity 3 24 41 SFPTTLGMNKCYIQIMDL LFKTASGINMCTLIAMDL No ZIKV-specific similarity 4 33 50 KCYIQIMDLGHMCDATMS MCTLIAMDLGEMCDDTVT 80%, 55% 5 42 59 GHMCDATMSYECPMLDEG GEMCDDTVTYKCPHITE 62%, 72% 6 51 68 YECPMLDEGVEPDDVDCW YKCPHITEVEPEDIDCW 61%, 100% 7 56 72 LDEGVEPDDVDCWCNTT HITEVEPEDIDCWCNLT 82%, 64% Common flavivirus 8 69 86 CNTTSTWVVYGTCHHKKG CNLTSTWVTYGTCNQAG 73%, 83% 9 78 92 YGTCHHKKGEARRSR TSTWVTYGTCNQAG 67%, 40% DENV- specific 10 100 118 HSTRKLQTRSQTWLESREY VGMGLDTRTQTVVMSAEGAW 67%, 47% E 11 37 54 DKPTVDIELVTTTVSNMA NKPTLDIELQKTEATQLA 78%, 50% 12 61 72 YEASISDMASDS IEGKITNITTDS No similarity 13 73 90 RCPTQGEAYLDKQSDTQY RCPTQGEAVLPEEQDQNY 100%, 44% 14 91 108 VCKRTLVDRGWGNGCGLF VCKHTYVDRGWGNGCGLF 89%, 100% 15 113 130 LVTCAKFACSKKMTGKSI LVTCAKFQCLEPIEGKVV 89%, 50% 16 123 140 KKMTGKSIQPENLEYRIM EPIEGKVVQYENLKYTVI 64%, 61% 17 131 149 PENLEYRIMLSVHGSQHS YENLKYTVIITVHTGDQH 53%, 88% DENV- specific 18 149 166 SGMIVNDTGHETDENRAK GDQHQVGNETQGVTAEIT No similarity 19 157 174 GHETDENRAKVEITPNSP GNETQGVTAEITPQASTT 100%, 22% 20 166 183 KVEITPNSPRAEATLGGF TAEITPQASTTEAILPEY 54%, 72% 21 191 203 EPRTGLDFSDLYY SPRTGLDFNEMIL 70%, 76% 22 199 216 SDLYYLTMNNKHWLVHKE NEMILLTMKNKAVVMVHRQ 62%, 72% 23 217 234 WFHDIPLPWHAGADTGTP WFFDLPLPWTSGATTETP 67%, 100% 24 235 245 HWNNKEALVEF TWNRKELLVTF 70%, 90% 25 244 261 EFKDAHAKRQTVVVLGSQ TFKNAHAKKQEVVVLGSQ 82%, 94% 26 271 288 GALEAEMDGAKGRLSSGH GATEIQNSGGTSIFAGH 100%, 11% ZIKV-specific 27 306 319 SLCTAAFTFTKIPA AMCTNTFVLKKEVS No similarity 28 325 342 TVTVEVQYAGTDGPCKVP TILIKVEYKGEDAPCKIP 62%, 72% 29 343 355 AQMAVDMQTLTPV FSTEDGQGKAHN No similarity 30 361 378 ANPVITESTENSKMMLEL ANPVVTKKEEPVNIEA 83%, 33% 31 402 419 RSGSTIGKAFEATVRGAK KKGSSIGKMFEATARGAR 80%, 83% 32 453 470 FKSLFGGMSWFSQILIGT YTALFSGVSWVMKIGIGV 71%, 38% ZIKV- specific NS1 33 1 18 DVGCSVDFSKKETRCGTG DMGCVINWKGKELKCGSG 44%, 100% 34 19 36 VFVYNDVEAWRDRYKYHP IFVTNEVHTVVTEQYKFQA 41%, 94% 35 55 72 CGISSVSRMENIMWRSVE CGIRSTTRMENLLWKQIA 64%, 77% 36 70 85 SVEGELNAILEENGVQ QIANELNYILWENNIK 70%, 56% Common flavivirus 37 91 112 GSVKNPMWRGPQRLPVPVNELP GDIIGVLEQGKRTLTPQPMELK No similarity 38 119 136 GKSYFVRAAKTNNSFVVD GKAKIVTAETQNSSFIID 57%, 38% Common flavivirus 39 137 154 GDTLKECPLKHRAWNSFL GPNTPECPSASRAWNVWE 70%, 55% Common flavivirus 40 155 176 VEDHGFGVFHTSVWLKVREDYS VEDYGFGVFTTNIWLKLREVYT 71%, 95% 41 239 256 SDLIIPKSLAGPLSHHNT SDMIIPKSLAGPISQHNH 82%, 94% 42 248 265 AGPLSHHNTREGYRTQMK AGPISQHNHRPGYHTQTA 69%, 88% 43 257 274 REGYRTQMKGPWHSEELE RPGYHTQTAGPWHLGKLE 69%, 72% DENV- specific 44 270 281 SEELEIRFEECP LGKLELDFNYCE No similarity 45 275 292 IRFEECPGTKVHVEETCG LDFNYCEGTTVVITENCG 54%, 72% DENV- specific 46 284 301 KVHVEETCGTRGPSLRST TVVITENCGTRGPSLRTT 85%, 72% Common flavivirus 47 293 310 TRGPSLRSTTASGRVIEE TRGPSLRTTTVSGKLIHE 72%, 100% 48 302 319 TASGRVIEEWCCRECTMP TVSGKLIHEWCCRSCTLP 67%, 100% 49 315 326 ECTMPPLSFRAK SCTLPPLRYMGE 83%, 50% Common flavivirus 50 320 337 PLSFRAKDGCVVYGMEIRP PLRYMGEDGCVVYGMEIRP 72%, 100% 51 338 353 RKEPESNLVRSMVTAG ISEKEENMVKSLVSAG No similarity

[0213] Interestingly, results showed differences between pooled and individual peptides (Table 3, FIG. 5).

TABLE-US-00014 TABLE 3 Singapore ZIKV and DENV patients' response to ZIKV and DENV peptides Percentage recognition (%).sup.† ZIKV patients DENV patients Mean binding (n = 30-44) (n = 20) capacity.sup.‡ Peptide ZIKV DENV ZIKV DENV ZIKV DENV Relative Epitope Protein no peptide peptide peptide peptide patients patients difference.sup.§ classification.sup.¶ prM 1 55 39 55 40 0.244 0.226 0.018 2 63 60 95 80 0.634 0.612 0.022 3 70 66 80 75 0.132 −0.033 0.165 ZIKV-specific 4 30 50 0 15 −0.356 −0.346 0.010 5 59 45 55 50 0.306 0.272 0.034 6 59 61 40 50 −0.120 −0.079 0.041 7 86 86 90 85 0.056 0.014 0.042 Common 8 59 64 30 0 −0.088 −0.293 0.205 9 52 55 25 60 −0.210 −0.455 0.246 DENV-specific 10 62 86 40 70 −0.263 −0.355 0.092 E 11 64 61 55 35 0.066 0.271 0.205 12 84 89 65 65 0.065 0.076 0.011 13 59 57 30 20 −0.030 0.088 0.118 14 68 66 60 65 −0.015 0.043 0.059 15 61 64 30 50 −0.138 −0.157 0.020 16 53 90 55 85 −0.415 −0.379 0.036 17 70 75 55 85 0.084 −0.227 0.311 DENV-specific 18 70 100 85 100 −0.218 −0.260 0.042 19 57 57 50 55 0.084 0.006 0.078 20 60 50 30 20 0.186 0.314 0.129 21 54 78 25 45 −0.314 −0.264 0.050 22 47 37 25 0 0.610 0.620 0.010 23 34 30 0 0 0.152 N.A. N.A. 24 86 98 90 100 −0.235 −0.041 0.194 25 77 75 55 40 0.177 0.209 0.032 26 64 59 25 25 0.340 0.173 0.167 ZIKV-specific 27 68 78 40 50 −0.081 −0.114 0.033 28 87 90 95 95 0.095 −0.001 0.097 29 76 70 40 45 −0.109 −0.018 0.090 30 64 80 45 55 −0.182 −0.157 0.025 31 93 95 90 75 0.319 0.681 0.362 32 100 100 100 100 0.189 0.039 0.150 ZIKV-specific NSI 33 82 86 65 60 0.013 0.033 0.020 34 86 82 90 50 0.431 0.853 0.422 35 84 89 65 70 −0.223 −0.134 0.089 36 79 83 80 90 0.012 −0.031 0.042 Common 37 84 82 60 60 −0.012 −0.023 0.011 38 82 89 60 70 0.019 0.000 0.019 Common 39 89 91 75 75 −0.041 −0.069 0.027 Common 40 89 91 80 75 −0.082 −0.079 0.002 41 68 66 35 35 0.154 0.103 0.051 42 68 59 35 35 0.177 0.110 0.068 43 84 91 75 95 −0.137 −0.244 0.107 DENV-specific 44 81 83 65 45 0.192 0.183 0.010 45 84 89 55 75 −0.131 −0.267 0.136 DENV-specific 46 84 82 70 60 0.118 0.098 0.020 Common 47 82 86 50 70 −0.132 −0.120 0.012 48 84 59 65 35 −0.757 1.234 1.992 49 78 86 50 60 −0.019 −0.019 0.001 Common 50 80 75 80 40 0.334 0.720 0.386 51 86 83 90 80 0.019 0.160 0.141 .sup.†Patient samples are positive if their normalised peptide responses (calculated as OD of patient sample/mean OD of pooled healthy) are more than 1.01. .sup.‡Binding capacity of a patient positive for a peptide-pair was calculated using normalised values of: [(ZIKV peptide response-DENV peptide response)/DENV peptide response]. Values close to 0 denote equal recognition of sample to ZIKV and DENV peptide. Values more than 0 denote a sample recognising ZIKV peptide more. Values less than 0 denote a sample recognising DENV peptide more. .sup.§Relative difference is calculated as the difference in the mean binding capacity of ZIKV patients and DENV patients. Values are rounded up to 3 decimal places. .sup.¶Common flavivirus epitopes: 60% of ZIKV and DENV patients recognise both ZIKV and DENV peptides of peptide-pair; ZIKV-specific epitopes: 60% of ZIKV patients recognise at least ZIKV peptide of peptide-pair; DENV-specific epitopes: 60% of DENV patients recognise at least DENV peptide of peptide-pair.

[0214] These differences could be due to interferences of the pooled peptides, while single peptides allowed for more enhanced specific binding. Nevertheless, six potential common flavivirus peptides were identified which displayed less than 0.05 relative difference in the binding capacity between ZIKV and DENV patients (peptides 7, 36, 38, 39, 46, 49) (Table 3, FIG. 5, FIG. 6). These peptides were also selected based on the close similarity between the ZIKV and DENV peptide sequence (Table 2). Additionally, three potential ZIKV-specific (peptides 3, 26 and 32), and four potential DENV-specific peptides (peptides 9, 17, 43 and 45) with a binding capacity difference of more than 0.1 were identified (Table 3, FIG. 5, FIG. 6).

Epitope Recognition by ZIKV Patients Over Time

[0215] In order to characterise the changes in epitope recognition by ZIKV patients over time, the common flavivirus and ZIKV-specific peptides were screened with plasma of ZIKV patients in acute, late convalescent, and full recovery phases. For the common flavivirus hits, more than 60% of the ZIKV patients were able to recognise the six peptide-pairs at late convalescent and beyond (FIG. 7a). However, at the acute phase, only peptides 7, 36 and 38 were recognised by ZIKV patients (FIG. 7a). In terms of binding capacity, there was equal binding between ZIKV and DENV peptide-pairs over time for peptides 7, 36, 38 and 49 (FIG. 7b).

[0216] For ZIKV-specific epitopes, more than 60% of the ZIKV patient samples were able to recognise peptides 3 and 26 (FIG. 7a), with positive peptide binding capacity (FIG. 7b) at late convalescent phase. On the other hand, peptide 32 showed strong recognition by the patient samples (FIG. 7a) as well as high binding capacity (FIG. 7b) at various time points from acute to full recovery. The localisation of all potential epitopes within the viral proteins are shown in FIGS. 7c-f.

Evaluation of Epitopes with Patient Cohorts

[0217] To assess the diagnostic performance of identified epitopes, the 13 peptides were screened using patient serum samples from a Thailand cohort that had DENV, bacteria, or unknown infections. Results of a randomised selection of Singapore ZIKV and DENV patients were also analysed in parallel (Table 4).

TABLE-US-00015 TABLE 4 Evaluation of patients of different diagnoses and cohorts with potential linear B-cell epitopes Peptide Common flavivirus.sup.† ZIKV-specific.sup.‡ DENV-specific.sup.‡ Cohort Patient 7 36 38 39 46 49 3 26 32 9 17 43 45 ZIKV 1 y y y y y y e z e d z e e (Singapore) 2 y y y y n n z n z d d d d 3 y y y y y n z z d n z d d 4 y y y y y y z z z n z e d 5 y y y y y y e z e d z d d 6 y y y y y y z z z n e e d 7 y y y y y y z z z n e e e 8 y n y n y y n n z n d d n 9 y y y y y y z z e e z d z 10 y y y y y y e z e d z d e DENV 1 y y y y y y e e z d z e z (Singapore) 2 y n n n n n d n z n n n n 3 y y y n n n z n z d d d d 4 y y y y y y e n e d d d d 5 y y y y y y e z e d d d d 6 y n n n n n e n z n n d d 7 y y y n y y e n d d e d n 8 y n y y y n z n d n d e n 9 y y y y y y e z d d d e e 10 y y y y y y d e d d e d e DENV 1 n y n n n n n n d n n d n (Thailand) 2 y y n y n n z n d z d d z 3 y n n y n n z n d d d d n 4 n n n n n n n n e z d d n 5 n n n n n n e n e z d d n Bacteria 1 y n n y n n d n d z d d n (Thailand) 2 n n n n n n d n d z d d n 3 y n n n n n e n d z d d n 4 y y y y y y e n d z d d e 5 y n n n n n d n d z d d n Unknown 1 y y y y y n d z d d d z d (Thailand) 2 n n n n n n n n z n d d n 3 y y y y y n d n d d d d n 4 y n y y n n d n d z d d n 5 y n y y n n n n d n d d n 6 y y y y y y e z d d d d e 7 n n n n n n n n d n n n n 8 n n n n y n d n d n n d n .sup.†A patient sample is considered positive (indicated as “y”) if it has a normalised peptide response higher than pooled healthy control for both ZIKV and DENV peptide-pair. If a sample peptide-pair response is lower than the healthy, it is considered negative (indicated as “n”) .sup.‡If a patient sample is positive for a peptide, i.e. has a higher normalised peptide response than pooled healthy control, the binding capacity of peptides (calculated as [(ZIKV peptide response-DENV peptide response)/DENV peptide response] was then determined. For patients with peptide binding capacity values of i) binding capacity ≥ 0.1 .fwdarw. positive for ZIKV peptide (indicated as “z”) ii) binding capacity ≤ 0.1 .fwdarw. positive for DENV peptide (indicated as “d”) ii) −0.1 < binding capacity < 0.1 .fwdarw. equal recognition of ZIKV and DENV peptide-pair (indicated as “e”)

[0218] Interestingly, results showed a wide range of specificity and sensitivity for each peptide (Table 5, FIG. 8a).

TABLE-US-00016 TABLE 5 Diagnostic evaluation of linear B-cell epitopes No of patients.sup.† Epitope Peptide True True False False Sensitivity Specificity Analysis classification Protein no positive negative negative positive (%).sup.‡ (%).sup.¶ Individual Common prM 7 22 4 3 9 88.0 30.8 peptide flavivirus NS1 36 18 9 7 4 72.0 69.2 38 18 7 7 6 72.0 53.8 39 17 6 8 7 68.0 46.2 46 16 8 9 5 64.0 61.5 49 14 11 11 2 56.0 84.6 ZIKV- prM 3 6 24 4 4 60.0 85.7 specific E 26 8 24 2 4 80.0 85.7 32 5 23 5 5 50.0 82.1 DENV- prM 9 8 16 7 7 53.3 69.6 specific E 17 9 10 6 13 60.0 43.5 NS1 43 11 6 4 17 73.3 26.1 45 4 17 11 6 26.7 73.9 Peptide Common NS1 36 17 8 8 5 68 61.5 combination flavivirus 38 46 49 ZIKV- prM 3 6 27 5 1 54.5 96.4 specific E 26 32 DENV- prM 9 8 16 7 7 53.3 69.6 specific .sup.†ZIKV (n = 10) and DENV (n = 10) patients from Singapore, and DENV (n = 5), bacteria (n = 5) and unknown (n = 8) patients from Thailand were used in the diagnostic evaluation. .sup.‡Sensitivity is calculated as the percentage of [true positive patients/(true positive patients + false negative patients)]. .sup.¶Specificity is calculated as the percentage of [true negative patients/(true negative patients + false positive patients)].

[0219] ZIKV-specific peptide 26 (amino acid residues 271-288) on the E protein of domain I/II (EDI/II) had the best sensitivity and specificity profile (80% and 85.7% respectively) (Table 5, FIG. 8a). Nevertheless, eight peptides (common flavivirus peptides 36, 38, 46, 49; ZIKV-specific peptides 3, 26, 32; and DENV-specific peptide 9) showed more than 50% sensitivity and specificity (Table 5, FIG. 8a), and were selected for further evaluation. These peptides were used to “diagnose” the patients (Table 6), and the performance of the peptide combination based on the epitope groupings were determined collectively (Table 5, FIG. 8b).

TABLE-US-00017 TABLE 6 Evaluation of common and differential flavivirus peptide mix with patient cohorts Percentage of positive peptides (%) Outcome of patients Common ZIKV- DENV- Common ZIKV- DENV- Final Cohort Patient flavivirus.sup.† specific.sup.‡ specific.sup.§ flavivirus.sup.† specific.sup.‡ specific.sup.§ “diagnosis”.sup.¶ ZIKV 1 100 33.3 100 y n y d (Singapore) 2 50 66.7 100 n y y n 3 100 66.7 0 y y n z 4 100 100.0 0 y y n z 5 100 33.3 100 y n y d 6 100 100.0 0 y y n z 7 100 100.0 0 y y n z 8 75 33.3 0 y n n n 9 100 66.7 0 y y n z 10 100 33.3 100 y n y d DENV 1 100 33.3 100 y n y d (Singapore) 2 0 33.3 0 n n n n 3 50 66.7 100 n y y n 4 100 0.0 100 y n y d 5 100 33.3 100 y n y d 6 25 33.3 0 n n n n 7 75 0.0 100 y n y d 8 75 33.3 0 y n n n 9 100 33.3 100 y n y d 10 100 0.0 100 y n y d DENV 1 25 0.0 0 n n n n (Thailand) 2 75 33.3 0 y n n n 3 50 33.3 100 n n y n 4 25 0.0 0 n n n n 5 25 0.0 0 n n n n Bacteria 1 50 0.0 0 n n n n (Thailand) 2 25 0.0 0 n n n n 3 25 0.0 0 n n n n 4 100 0.0 0 y n n n 5 25 0.0 0 n n n n Unknown 1 100 33.3 100 y n y d (Thailand) 2 25 33.3 0 n n n n 3 100 0.0 100 y n y d 4 75 0.0 0 y n n n 5 50 0.0 0 n n n n 6 100 33.3 100 y n y d 7 25 0.0 0 n n n n 8 50 0.0 0 n n n n Based on Table 4, the percentage of positive peptides were calculated and “outcome” of patients were assigned. .sup.†If sample is positive for 3 or more (out of 4) common flavivirus peptides, i.e. 75% positive, the patient is considered positive (indicated as “y” in the outcome) for flavivirus infection. If sample is ≥75% positive, the patient is considered negative (indicated as “n” in the outcome). .sup.‡If sample is positive for 2 or more (out of 3) ZIKV-specific peptides, i.e. ≥66.7% positive, the patient is considered positive (indicated as “y” in the outcome) for ZIKV infection. If sample is ≤66.7% positive, the patient is considered negative (indicated as “n” in the outcome). .sup.§If sample is positive for the DENV-specific peptide, i.e. ≥100% positive, the patient is considered positive (indicated as “y” in the outcome) for DENV infection, whereas negative for the DENV- specific peptide is indicated as “n” in the outcome. .sup.¶Based on the respective outcomes of the epitope categories, the following combinations produce the final ZIKV and DENV “diagnosis” of patients: Common flavivirus ZIKV-specific DENV-specific Final “diagnosis” y y n ZIKV positive (“z”) y n y DENV positive (“d”) y n n ZIKV and DENV negative (“n”) n y n n n y n n n

[0220] Although the common flavivirus and DENV-specific groups demonstrated modest measurements, the ZIKV-specific peptide mix showed a robust specificity of 96.4% (Table 5, FIG. 8b). Furthermore, when the anti-peptide IgG response of patients was plotted in a principal component analysis (PCA), it was observed that patients of different diagnoses and cohorts formed separate dusters, and ZIKV patients stood out when compared to the healthy control (FIG. 8c). To identify peptides with discriminating power, the binding capacity of positive peptides were calculated. The virus-specific ZIKV and DENV epitopes were significantly differential (FIG. 8d). Peptide 32 (amino acid residues 453-470 on E protein) was the best performing ZIKV-specific epitope, and was able to distinguish Singapore ZIKV patients from bacteria and unknown infections from Thailand (FIGS. 8d-e). DENV-specific peptide 9 (amino acid residues 78-92 on prM) could be used to differentiate Singapore DENV patients from bacteria-infected patients from Thailand (FIG. 8e). Overall, we have identified the best differential epitopes to differentiate between DENV and ZIKV patients.

Conclusion

[0221] ZIKV patients were shown to produce high levels of ZIKV-specific IgG antibodies. Specifically, IgG1 and IgG3 were the subclasses induced following ZIKV infection, closely resembling DENV-infected patients. Although patients from this cohort had detectable DENV IgG levels due to the high level of cross-reactivity among flaviviruses, DENV neutralisation was significantly less efficient compared to ZIKV, indicating that the antibodies were ZIKV-specific (FIGS. 2e-f, FIG. 3). This observation is also supported by another study, in which the profiles of ZIKV neutralising antibodies of patients from Nicaragua, Sri Lanka and Thailand were not affected by previous DENV infection. Nonetheless, it is imperative to consider the possible implications of virus-infection enhancement. Moreover, none of the ZIKV patients in our study displayed severe symptoms to suggest occurrence of antibody-dependent enhancement (ADE), and similar observations were also reported from Brazil.

[0222] Peptides identified from B-cell epitope mapping have been reported on flavivirus E, prM NS1 and NS3 antigens from antibodies of patients and animal models. Identification of antigenic epitopes and characterisation of cross-reactive epitopes are crucial in vaccine and immunodiagnostic developments. While various reports have shown the specificity of the NS1 antigen to differentiate between ZIKV and DENV, majority of the common flavivirus peptides identified in this disclosure are on the NS1 protein, possibly due to the conserved regions of NS1 amongst the flaviviruses. For example, common flavivirus peptides 36 (amino acid residues 70-85), 38 (amino acid residues 119-136) and 49 (amino acid residues 315-326) were identified as ZIKV-specific in other patient cohorts from South America. However, it remains to be seen if these peptides could be used to detect all flaviviruses such as yellow fever virus (YFV) and Japanese encephalitis virus (JEV).

[0223] Differential ZIKV and DENV epitopes identified were located across prM, E and NS1. Of interest, DENV-specific peptide 17 (amino acid residues 131-149) and ZIKV-specific peptide 26 are found on EDI and EDII of E glycoprotein, which share 35% and 51% amino acid identity between ZIKV and DENV respectively, whereas ZIKV-specific peptide 32 is found in the transmembrane domain of the anchor region (FIG. 7e). Interestingly, peptide 32 (amino acid residues 453-470) maps to a region that overlaps with a DENV-2 epitope (amino acid residues 451-468) described for immune sera of DENV-2 infected patients. Computational analyses of ZIKV-specific peptide 32 and DENV-2-equivalent epitope showed that they remain moderately accessible on the virus particle. Since they share low sequence identity (43.75%), this epitope could be conformationally different, and thus differentially recognised by ZIKV and DENV-specific antibodies. It would also be useful to assess the use of the identified peptides as a ZIKV vaccine target, particularly peptides 26 and 32. Interestingly, despite the similarity between the sequence of these ZIKV and DENV peptide-pairs (Table 2), they were able to distinguish ZIKV and DENV patients. Moreover, ZIKV patients at different disease stages have different peptide recognition, and the current set-up could identify ZIKV infection at any point, independent of the patients' level of ZIKV-specific antibodies (FIGS. 9b-c). However, given that the identified epitopes were screened and validated using adult patient samples, it would be important to assess how these epitope profiles will perform in other patient cohorts, specifically ZIKV-infected pregnant women from Brazil.

[0224] Identified putative epitopes were preliminary diagnostically evaluated with 38 patient samples. Intriguingly, the Singapore DENV and Thailand DENV patients were not clustered together in the PCA (FIG. 8c). Most of the Singapore DENV patients selected for validation had moderate to severe forms of plasma leakage, a clinical feature of severe manifestations of DENV infection, whereas DENV patients from Thailand displayed mild symptoms (unpublished data). The latter being “negative” in our assays could thus be due to differences in epitope recognition in different DENV disease states, and the different strain of viruses circulating in Singapore and Thailand. Nonetheless, further refinements are required to identify serotype-specific DENV epitopes.

[0225] Furthermore, comparing these results and computationally-predicted diagnostic peptide regions revealed differences. Firstly, majority of the computationally predicted peptide regions were not ZIKV-specific. NS1 peptide 36, for example, was predicted to be differential, but was in fact a common flavivirus. Furthermore, peptide 26 on E glycoprotein, predicted to recognise both ZIKV and DENV, was shown to be ZIKV-specific in this disclosure. Despite differences in various approaches, computational prediction remains a useful tool.

[0226] Overall, this disclosure offers important valuable information on the human antibody response against ZIKV and insights into epitope cross-reactivity. Notably, several novel differential ZIKV and DENV epitopes with potential diagnostic efficacies have been identified on prM and E proteins. These results offer useful insights towards the development of diagnostics or vaccines.

Methods

Ethics Statement

[0227] Written informed consent was obtained from participants in accordance with the tenets of the Declaration of Helsinki. Study protocols of Singapore ZIKV (2016-2018) and DENV (2010-2012) patient cohorts were approved by the SingHealth Centralised Institutional Review Board (CIRB Ref: 2016/2219) and National Healthcare Group (NHG) Domain Specific Review Board (DSRB-E-2009/432) respectively. Specimens from Singapore healthy donors (2010-2015) and patients from Thailand (2011-2013) were collected in accordance to study guidelines of approval numbers: NUS-IRB 09-256 and NUS-IRB 10-445; MUTM 2011-008-01, OXTREC 42-10 and TCAB-01-11 respectively.

Study Subjects and Sample Collection

Singapore ZIKV Patients

[0228] Collection of specimens from subjects during the ZIKV outbreak in 2016 was previously described.sup.30. Briefly, 65 patients that were RT-PCR positive for ZIKV in whole blood or urine, and negative for DENV RT-PCR were enrolled. Whole blood specimens were collected in EDTA-coated vacutainer tubes (Becton Dickinson, Franklin Lakes, N.J., USA) after peripheral venipuncture and were centrifuged at 12000 rpm for 10 min. Plasma was collected and heat-inactivated for 30 min at 56° C. before storage at −80° C. Specimens were obtained over a period of six time points: (1) acute [2-7 days post-illness onset (pio)], (2) early convalescent (10-14 days pio), (3) late convalescent (1 month pio), (4) early recovery (3 months pio), (5) late recovery (5-6 months pio), and (6) full recovery (1 year pio) phases.

Singapore DENV Patients

[0229] Twenty DENV patient serum samples (2010-2012) collected before the ZIKV outbreak were used in this study. Patients were DENV PCR and/or NS1 positive upon hospital admission, and were a combination of the following: one unknown serotype, six DENV-1, seven DENV-2, three DENV-3, and three DENV-4 patients. Serum samples used were obtained at late convalescent phase (21-37 days pio).

Thailand Patients

[0230] Archived serum samples from an undifferentiated fever study conducted at Shoklo Malaria Research Unit (SMRU) were used. Five DENV patients were confirmed by gold standard paired serology, and all but one was DENV PCR positive. Five bacteria-infected patients were diagnosed with leptospirosis, scrub typhus, murine typhus or Streptococcus pneumoniae infections, or a combination of above, and all were DENV PCR and DENV NS1, IgM and IgG RDT negative. Eight patients with unknown diagnoses were negative for the above pathogens by serology, blood culture and PCR. Convalescent serum samples used were collected at 14-20 days pio.

Viruses

[0231] ZIKV Polynesian isolate (H/PF/2013) was obtained from the European Virus Archive (EVA, Marseille, France). DENV-3 was used as a reference DENV serotype because it is widespread in Southeast Asia, and was kindly provided by the National Public Health Laboratory (NPHL), Singapore. CHIKV SGP011 was isolated from a patient from Singapore. Viruses were propagated in VeroE6 cells (ATCC, Manassas, Va., USA) and purified via ultracentrifugation before being titered by standard plaque assays in VeroE6 cells.

Virion-Based ELISA

[0232] Antibody titres were determined by a virion-based ELISA as previously described.sup.18, 24-27. Briefly, purified virus was immobilised on 96-well maxisorp microtitre plates overnight (Thermo Fisher Scientific, Waltham, Mass., USA). Wells were blocked with 0.05% PBST [0.05% Tween-20 (Sigma-Aldrich, Saint Louis, Mo., USA) in PBS] containing 5% skim milk (Nacalai Tesque, Kyoto, Japan) at 37° C. for 1.5 h. Heat-inactivated patient and pooled healthy control plasma samples at 1:200 to 1:8000 dilutions prepared in PBST with 2.5% milk were incubated at 37° C. for 1 h. HRP-conjugated goat anti-human IgM or IgG (H+L) (Thermo Fisher Scientific) or mouse anti-human IgG1, IgG2, IgG3 and IgG4 (Thermo Fischer Scientific) antibodies were used for detection. Reactions were developed using TMB (3,3,5,5-tetramethyl benzidine) substrate (Sigma-Aldrich) and terminated with Stop reagent (Sigma-Aldrich), and absorbance was measured at 450 nm in a microplate autoreader (Tecan, Männedorf, Zürich, Switzerland) 18, 24-27. ELISA readings were conducted in duplicates or triplicates.

Sero-Neutralisation

[0233] Neutralising capacity of antibodies from ZIKV patients were determined via flow cytometry. Briefly, pooled patient and healthy plasma samples at 1:500, 1:1000 and 1:2000 dilutions were incubated with ZIKV or DENV-3 at MOI 10 for 2 h at 37° C. with gentle agitation (350 rpm). Virus-antibody suspensions were then added in duplicates to HEK 293T cells (ATCC) at 37° C. After 2 h, media were removed and Dulbecco's Modified Eagle Medium (DMEM; GE Healthcare Life Sciences, Pittsburgh, Pa., USA) with 10% foetal bovine serum (FBS; GE Healthcare Life Sciences) were added. After 48 h, cells were harvested and stained as described.sup.54, using ZIKV NS3 protein-specific rabbit polyclonal antibody or DENV human monoclonal antibody 1B25, and counter-stained with fluorophore-tagged goat anti-rabbit or anti-human IgG (H+L) (Thermo Fisher Scientific) respectively. Cells were acquired with MacsQuant Analyser 10 (Miltenyi-Biotec, Bergisch Gladbach, Germany). Assay was carried out in duplicates with two independent experiments. Flow cytometry results were analysed with FlowJo (version 10.4.1, Tree Star Inc, Ashland, Oreg., USA). Data of patient and pooled healthy neutralisation assays were normalised using the respective untreated infections and calculated as a percentage of virus-only control infection.

Epitopes Determination

Linear Peptide Libraries

[0234] The sequences used for the design of biotinylated linear peptides of prM, E and NS1 proteins were derived from ZIKV Polynesian isolate (KJ776791) and consensus sequence of DENV-3 strains (KR296743, KF973487, EU081181, KF041254, JF808120, JF808121, KJ189293, KC762692, KC425219, KJ830751, KF973479, and AY099336). Peptides were generated as a ZIKV and DENV peptide-pair of corresponding sequences. Preliminary epitope screening was used with a library of peptides (Mimotopes, Mulgrave, Victoria, Australia) consisting of 18-mer overlapping sequences. Five peptides were combined to form one pooled peptide set. Screening and validation of patients were done with higher purity of peptides ((290%, EMC microcollections GmbH, Tuebingen, Germany) with lengths ranging from 11 to 22-mer (Table 2). Peptides were dissolved in DMSO (Sigma-Aldrich) to obtain a stock concentration of 3.75 μg μl.sup.−1.

Peptide-Based ELISA

[0235] Epitope determination was performed via peptide-based ELISA as previously described.sup.24,25,27. Briefly, streptavidin-coated plates (Thermo Fisher Scientific) were blocked with 0.1% PBST (0.1% Tween-20 in PBS) containing 1% sodium caseinate (Sigma-Aldrich) and 1% bovine serum albumin (BSA; Sigma-Aldrich) overnight at 4° C., before addition of biotinylated peptides (1:1000 dilution in 0.1% PBST), followed by heat-inactivated pooled healthy control and patient plasma/serum samples (1:2000 dilution in 0.1% PBST). HRP-conjugated goat-anti human IgG (H+L) antibody (Thermo Fisher Scientific) prepared in 0.1% blocking buffer was used for detection of peptide-bound antibodies. TMB substrate and Stop reagent (Sigma-Aldrich) were used for development, prior to absorbance measurements at 450 nm (Tecan). All incubation steps were at room temperature for 1 h on a rotating shaker, and ELISA readings were conducted in duplicates.

Data Analysis

[0236] OD values obtained from ZIKV and DENV peptide-based ELISA experiments were first normalised against mean OD values of pooled healthy donors. Patient samples were considered positive if the normalised response was more than 1.01. Subsequently, peptide binding capacity was calculated using the normalised values as [(ZIKV peptide response−DENV peptide response)/DENV peptide response]. Binding capacities with positive values denote the binding preference of the sample to ZIKV peptide, whereas negative values denote a binding preference to the corresponding DENV peptide. Difference in the mean peptide binding capacity of ZIKV patients and DENV patients of a peptide-pair (i.e. ZIKV and DENV peptides with complementary sequence) was calculated. Peptides with a relative difference of 0.1 or more are considered to be differential ZIKV and DENV epitopes of interest, whereas peptides with a difference of 0.05 or less, and share amino acid similarity between the peptide-pair (Table 2) are considered as common flavivirus epitopes.

Data Visualisation and Statistical Analysis

[0237] Heat-maps were generated using Multi Experiment Viewer (version 4.8, Microarray Software Suite TM4, Boston, Mass., USA). For structural localisation, ZIKV prM was simulated using Phyre (version 2, Structural Bioinformatics Group, London, UK) 55. Structures of DENV-3 prM, ZIKV E glycoprotein, DENV-3 E glycoprotein, ZIKV stem-transmembrane domain of E glycoprotein, DENV-3 stem-transmembrane domain of E glycoprotein, ZIKV NS1 and DENV-3 NS1 were modelled based on PDB 3C6E, 5JHM, 1UZG, 51Z7, 3J2P, 5K6K and 406B respectively. All structures were visualised using PyMol (Schrödinger, Cambridge, Mass., USA). Principal component analysis (PCA) was performed using the OD values of the anti-peptide IgG response by patients using prcomp function in R (version 3.3.1; R Foundation for Statistical Computing, Vienna, Austria).

[0238] Statistics were done using GraphPad Prism (version 7.03, San Diego, Calif., USA). Mann-Whitney U tests, two-tailed, with Bonferroni correction for multiple testing, or Kruskal-Wallis tests with Bonferroni correction for multiple testing, and post hoc tests using Dunn's multiple comparison tests were used to derive any statistical significance. Correlation analysis was carried out using Spearman's rank correlation. P-values less than 0.05 are considered significant.

[0239] It will be appreciated by a person skilled in the art that other variations and/or modifications may be made to the embodiments disclosed herein without departing from the spirit or scope of the disclosure as broadly described. For example, in the description herein, features of different exemplary embodiments may be mixed, combined, interchanged, incorporated, adopted, modified, included etc. or the like across different exemplary embodiments. The present embodiments are, therefore, to be considered in all respects to be illustrative and not restrictive.

REFERENCES

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TABLE-US-00018 TABLE 7 Sequence of peptide pairs Amino acid position Peptide on ZIKV similarity % Classi- (accession Corresponding Corresponding identity, % fication Peptide KJ776791) ZIKV DENV query of potential Protein no Start End sequence sequence cover) epitope prM 7 56 72 LDEGVEPDDVDCWCNTT HITEVEPEDIDCWCNLT 82%, Common 64% flavivirus NS1 36 70 85 SVEGELNAILEENGVQ QIANELNYILWENNIK 70%, Common 56% flavivirus NS1 38 119 136 GKSYFVRAAKTNNSFVVD GKAKIVTAETQNSSFIID 57%, Common 38% flavivirus NS1 39 137 154 GDTLKECPLKHRAWNSFL GPNTPECPSASRAWNVWE 70%, Common 55% flavivirus NS1 46 284 301 KVHVEETCGTRGPSLRST TVVITENCGTRGPSLRTT 85%, Common 72% flavivirus NS1 49 315 326 ECTMPPLSFRAK SCTLPPLRYMGE 83%, Common 50% flavivirus prM 3 24 41 SFPTTLGMNKCYIQIMDL LFKTASGINMCTLIAMDL No ZIKV- similarity specific E 26 271 288 GALEAEMDGAKGRLSSGH GATEIQNSGGTSIFAGH 100%, ZIKV- 11% specific E 32 453 470 FKSLFGGMSWFSQILIGT YTALFSGVSwVMKIGIGV 71%, ZIKV- 38% specific prM 9 78 92 YGTCHHKKGEARRSR TSTwVTYGTCNQAG 67%, DENV- 40% specific E 17 131 149 PENLEYRIMLSVHGSQHS YENLKYTVIITVHTGDQH 53%, DENV- 88% specific NS1 43 257 274 REGYRTQMKGPWHSEELE RPGYHTQTAGPWHLGKLE 69%, DENV- 72% specific NS1 45 275 292 IRFEECPGTKVHVEETCG LDFNYCEGTTVVITENCG 54%, DENV- 72% specific

TABLE-US-00019 TABLE 8 Sequences and their corresponding sequence identity numbers (SEQ ID NOs.) Corresponding SEQ Corresponding SEQ Peptide ZIKV ID DENV ID Protein no sequence NO. sequence NO. prM 1 RGSAYYMYLDRNDAGEAI 1 RDGEPRMIVGKNERGKSL 52 2 DRNDAGEAISFPTTLGMN 2 GKNERGKSLLFKTASGIN 53 3 SFPTTLGMNKCYIQIMDL 3 LFKTASGINMCTLIAMDL 54 4 KCYIQIMDLGHMCDATMS 4 MCTLIAMDLGEMCDDTVT 55 5 GHMCDATMSYECPMLDEG 5 GEMCDDTVTYKCPHITE 56 6 YECPMLDEGVEPDDVDCW 6 YKCPHITEVEPEDIDCW 57 7 LDEGVEPDDVDCWCNTT 7 HITEVEPEDIDCWCNLT 58 8 CNTTSTWVVYGTCHHKKG 8 CNLTSTWVTYGTCNQAG 59 9 YGTCHHKKGEARRSR 9 TSTWVTYGTCNQAG 60 10 HSTRKLQTRSQTWLESREY 10 VGMGLDTRTQTWMSAEGAW 61 E 11 DKPTVDIELVTTTVSNMA 11 NKPTLDIELQKTEATQLA 62 12 YEASISDMASDS 12 IEGKITNITTDS 63 13 RCPTQGEAYLDKQSDTQY 13 RCPTQGEAVLPEEQDQNY 64 14 VCKRTLVDRGWGNGCGLF 14 VCKHTYVDRGWGNGCGLF 65 15 LVTCAKFACSKKMTGKSI 15 LVTCAKFQCLEPIEGKVV 66 16 KKMTGKSIQPENLEYRIM 16 EPIEGKVVQYENLKYTVI 67 17 PENLEYRIMLSVHGSQHS 17 YENLKYTVIITVHTGDQH 68 18 SGMIVNDTGHETDENRAK 18 GDQHQVGNETQGVTAEIT 69 19 GHETDENRAKVEITPNSP 19 GNETQGVTAEITPQASTT 70 20 KVEITPNSPRAEATLGGF 20 TAEITPQASTTEAILPEY 71 21 EPRTGLDFSDLYY 21 SPRTGLDFNEMIL 72 22 SDLYYLTMNNKHWLVHKE 22 NEMILLTMKNKAWMVHRQ 73 23 WFHDIPLPWHAGADTGTP 23 WFFDLPLPWTSGATTETP 74 24 HWNNKEALVEF 24 TWNRKELLVTF 75 25 EFKDAHAKRQTVVVLGSQ 25 TFKNAHAKKQEVVVLGSQ 76 26 GALEAEMDGAKGRLSSGH 26 GATEIQNSGGTSIFAGH 77 27 SLCTAAFTFTKIPA 27 AMCTNTFVLKKEVS 78 28 TVTVEVQYAGTDGPCKVP 28 TILIKVEYKGEDAPCKIP 79 29 AQMAVDMQTLTPV 29 FSTEDGQGKAHN 80 30 ANPVITESTENSKMMLEL 30 ANPVVTKKEEPVNIEA 81 31 RSGSTIGKAFEATVRGAK 31 KKGSSIGKMFEATARGAR 82 32 FKSLFGGMSWFSQILIGT 32 YTALFSGVSWVMKIGIGV 83 NS1 33 DVGCSVDFSKKETRCGTG 33 DMGCVINWKGKELKCGSG 84 34 VFVYNDVEAWRDRYKYHP 34 IFVTNEVHTVVTEQYKFQA 85 35 CGISSVSRMENIMWRSVE 35 CGIRSTTRMENLLWKQIA 86 36 SVEGELNAILEENGVQ 36 QIANELNYILWENNIK 87 37 GSVKNPMWRGPQRLPVPVNELP 37 GDIIGVLEQGKRTLTPQPMELK 88 38 GKSYFVRAAKTNNSFVVD 38 GKAKIVTAETQNSSFIID 89 39 GDTLKECPLKHRAWNSFL 39 GPNTPECPSASRAWNVWE 90 40 VEDHGFGVFHTSVWLKVREDYS 40 VEDYGFGVFTTNIWLKLREVYT 91 41 SDLIIPKSLAGPLSHHNT 41 SDMIIPKSLAGPISQHNH 92 42 AGPLSHHNTREGYRTQMK 42 AGPISQHNHRPGYHTQTA 93 43 REGYRTQMKGPWHSEELE 43 RPGYHTQTAGPWHLGKLE 94 44 SEELEIRFEECP 44 LGKLELDFNYCE 95 45 IRFEECPGTKVHVEETCG 45 LDFNYCEGTTVVITENCG 96 46 KVHVEETCGTRGPSLRST 46 TVVITENCGTRGPSLRTT 97 47 TRGPSLRSTTASGRVIEE 47 TRGPSLRTTTVSGKLIHE 98 48 TASGRVIEEWCCRECTMP 48 TVSGKLIHEWCCRSCTLP 99 49 ECTMPPLSFRAK 49 SCTLPPLRYMGE 100 50 PLSFRAKDGCVVYGMEIRP 50 PLRYMGEDGCVVYGMEIRP 101 51 RKEPESNLVRSMVTAG 51 ISEKEENMVKSLVSAG 102

APPLICATIONS

[0295] In the present disclosure, antibody and neutralising responses by ZIKV patients from Singapore were characterised longitudinally. Common and differential linear B-cell epitopes recognised by antibodies from Singapore ZIKV and DENV patients were then identified. Importantly, the potential value of these identified epitopes in a diagnostic setting was further assessed using sera from patients from Thailand previously diagnosed with DENV, bacterial, and including those of unknown infections.

[0296] This present disclosure furthers the development of a serology-driven differential flavivirus diagnosis, particularly between ZIKV and DENV, allowing for accurate diagnosis that will improve patient management. The application can also be further expanded to study sero-prevalence and vaccine strategies.

[0297] Embodiments of the method advantageously provide a proper serology diagnostic tool that is able to accurately identify a flavivirus infection such as ZIKV and/or DENV, or differentiate between the two flavivirus infections such as between ZIKV and DENV.

A METHOD OF IDENTIFYING A FLAVIVIRUS INFECTION, AND RELATED PEPTIDES, KITS AND COMPOSITIONS

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C12N2770/24134

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C07K14/005

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GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS

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Abstract

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Description