CD14+CD16+ Monocytes Are the Main Target of Zika Virus Infection in Peripheral Blood Mononuclear Cells in a Paediatric Study in Nicaragua

Letters DOI: 10.1038/s41564-017-0035-0

CD14+CD16+ monocytes are the main target of Zika virus infection in peripheral blood mononuclear cells in a paediatric study in Nicaragua

Daniela Michlmayr1, Paulina Andrade1,2, Karla Gonzalez3,4, Angel Balmaseda3,4 and Eva Harris 1*

The recent Zika pandemic in the Americas is linked to congen- of DENV infection in human peripheral blood mononuclear cells ital birth defects and Guillain–Barré syndrome. White blood (PBMCs) and in the skin7–9. cells (WBCs) play an important role in host immune responses Here, we identify cellular targets of ZIKV in human blood, com- early in arboviral infection. Infected WBCs can also function pare this to DENV-infected patients, and analyse gene expression as ‘Trojan horses’ and carry viruses into immune-sheltered profiles of monocytes isolated from ZIKV- and DENV-infected spaces, including the placenta, testes and brain. Therefore, patients. Our results reveal a detailed immune profile of ZIKV defining which WBCs are permissive to Zika virus (ZIKV) is infection in PBMCs in vitro and in patients, which is pivotal to critical. Here, we analyse ZIKV infectivity of peripheral blood understanding the initial stages of Zika pathogenesis prior to dis- mononuclear cells (PBMCs) in vitro and from Nicaraguan Zika semination throughout the body and into immune-sheltered sites, patients and show CD14+CD16+ monocytes are the main target leading to neurological complications and vertical and sexual trans- of infection, with ZIKV replication detected in some dendritic mission of the virus. cells. The frequency of CD14+ monocytes was significantly To determine whether WBCs become infected with ZIKV, we decreased, while the CD14+CD16+ monocyte population was first infected isolated PBMCs from four healthy blood donors for significantly expanded during ZIKV infection compared to 48 h and stained intracellularly for ZIKV E and NS3 proteins to uninfected controls. Viral RNA was detected in PBMCs from all identify replicating virus. Immunophenotyping of in-vitro-infected patients, but in serum from only a subset, suggesting PBMCs cells showed a significantly higher percentage and number of may be a reservoir for ZIKV. In Zika patients, the frequency CD14+CD16+ monocytes (P < 0.01), a significantly lower per- of infected cells was lower but the percentage of infected centage and number of CD14+ monocytes (P < 0.01 and P < 0.05, CD14+CD16+ monocytes was significantly higher compared respectively) and a lower percentage of CD16+ monocytes (P < 0.05) to dengue cases. The gene expression profile in monocytes compared to uninfected PBMCs (Fig. 1a–c). In addition, the isolated from ZIKV- and dengue virus-infected patients was CD14+CD16+ monocyte population increased, while CD14+ mono- comparable, except for significant differences in interferon-γ, cytes decreased from 24 h to 48 h post-infection (Supplementary CXCL12, XCL1, interleukin-6 and interleukin-10 levels. Thus, Fig. 1a). The mean percentage of B cells was somewhat increased our study provides a detailed picture of the innate immune (P < 0.05), CD4+ memory T cells decreased (P < 0.01), and myeloid profile of ZIKV infection and highlights the important role of (mDC) and plasmacytoid (pDC) DCs, NK cells, CD8+ T cells, and monocytes, and CD14+CD16+ monocytes in particular. naive and effector CD4+ T cells remained the same compared to Zika virus (ZIKV) is an arthropod-borne positive-sense RNA uninfected cells (Fig. 1d–f and Supplementary Fig. 1c–j). We found flavivirus, composed of seven non-structural and three structural that an average of 6.8% of all live PBMCs were actively infected in proteins1. Since 2015, ZIKV has spread rapidly throughout the vitro, consisting of 83.7% monocytes, 14.8% mDCs, 1.1% B cells, Americas, concurrent with an increase in congenital birth defects, 0.1% T cells and 0.7% NK cells (Fig. 1g,h). Among monocytic cells, including microcephaly and Guillain–Barré syndrome2. ZIKV infec- 58.3% of all monocytes were infected, with CD14+CD16+ mono- tion can be asymptomatic or can cause a mild febrile illness clini- cytes being the main target of ZIKV at 48 h post-infection, fol- cally resembling infection with other co-circulating arboviruses, lowed by CD14+ monocytes (Fig. 1i,j). Within DCs, mDCs were including dengue (DENV) and chikungunya (CHIKV) viruses. infected while pDCs were not (Fig. 1k and Supplementary Fig. 2a), At present, it is unclear how ZIKV reaches immune-privileged and more CD8+ T cells than CD4+ T cells were infected; however, sites within the body and breaches protective placental–fetal and ZIKV-infected T cells were found at very low frequency (Fig. 1l and blood–testis barriers, which leads to sexual transmission and con- Supplementary Fig. 2b), similar to NK and B cells (Supplementary genital defects3. One possible route is ZIKV-infected white blood Fig. 2c–e). Thus, PBMCs are susceptible to ZIKV infection in vitro, cells (WBCs), which disseminate the virus into different compart- with monocytes being the main target. ments of the body or serve as a viral reservoir upon recruitment to We then analysed PBMCs collected during acute illness from 29 the infection site, a mechanism known as ‘Trojan horse’4. West Nile ZIKV-infected and 8 DENV-infected patients enrolled in a paediat- virus (WNV), another flavivirus, infects monocytes, contributing to ric hospital study in Managua, Nicaragua (Supplementary Table 1). its dissemination into the brain, resulting in encephalitis and men- To more accurately compare the clinical characteristics of Zika ingitis5,6. Monocytes and dendritic cells (DCs) are the main target and dengue patients, Zika cases were stratified into earlier (1–2)

1Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley 94720-3370 CA, USA. 2Universidad de San Francisco de Quito, Quito 170157, Ecuador. 3Sustainable Sciences Institute, Managua 14007, Nicaragua. 4Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua 16064, Nicaragua. *e-mail: [email protected]

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a b + + + + c Uninfected PBMC Infected PBMC CD14 CD14 CD16 CD16 CD14+ CD14+ CD16+ CD16+ 5 ** 10 57.6 36.5 28.8 68.1 80 200,000 ** ** 104 60 150,000 * WBC 103 40 6 100,000 20 50,000

2 % monocytes 10 2.92 1.06 * per 10

0 Number of monocytes 0 101 CD14-PE-Cy7 101 102 103 104 105 CD16-FITC Infected PBMCInfected PBMCInfected PBMC Infected PBMCInfected PBMCInfected PBMC Uninfected PBMCUninfected PBMCUninfected PBMC Uninfected PBMCUninfected PBMCUninfected PBMC

de f Naive Memory E ector Naive Memory E ector B cells mDC pDC 50 60 15 5 * 40 4 40 T cells 10 30 T cells + 3 ** + 20 5 2 20 % of WBC % of WBC 10 % of CD8 1 % of CD4 0 0 0 0

Infected PBMC Infected PBMC Infected PBMC Infected PBMCInfected PBMCInfected PBMC Infected PBMCInfected PBMCInfected PBMC Uninfected PBMC Uninfected PBMC Uninfected PBMC Uninfected PBMCUninfected PBMCUninfected PBMC Uninfected PBMCUninfected PBMCUninfected PBMC g h i Isotype Infected PBMC 5 5 10 10 21.7 63.3 0.1% T cells 4 10 104 83.7% monocytes 0.1 0.2 2.6 6.7 1.1% B cells 103 14.8% DC 103 2 0.7% NK cells 10 0.04 0 1 0.4 1.2 10 –103 CD14-PE-Cy7 ZIKV/DENV E 2 5 5 Total = 6.8% 101 10 103 104 10 101 102 103 104 10 ZIKV/DENV NS3 CD16-FITC

jkl 80 ** *** 25 0.8

60 20 0.6 (%) T cells 15 + 40 cells (% ) 0.4 cells (%) + cell s + + 10

20 within DC s 0.2

ZIKV 5 ZIKV ZIKV within monocytes 0 0 within CD 3 0.0 + + +

+ pDC + mDC + CD4 + CD8 + CD14 + CD16 + CD16

ZIKV ZIKV ZIKV ZIKV ZIKV + CD14 ZIKV

ZIKV

Fig. 1 | CD14+CD16+ monocytes are expanded during ZIKV infection compared to uninfected PBMC and are the main target of virus infection in vitro. PBMCs isolated from healthy blood bank donors were infected with ZIKV at an MOI of 1 for 48 h. a, Representative dot plots with percentage of CD14+, CD14+CD16+ and CD16+ cells in the monocyte compartment. Cells were pregated on live cells and CD11b+ and HLA-DR+ cells. b,c, Flow cytometric analysis of the percentage (b) and absolute number (c) of CD14+, CD14+CD16+ and CD16+ monocytes. d,e, Frequency of B cells (d) and mDCs and pDCs (e). f, Phenotyping of CD4+ T cells, which were gated on live CD3+ T cells, as CD45RA+CD45RO−CCR7+ naive, CD3+CD4+CD45RA−CD45RO+ memory and CD3+CD4+CD45RA+ CD45RO−CCR7− effector T cells. g, Pie chart showing the mean percentage of cell types within ZIKV-infected (E+NS3+) PBMCs. h, Representative flow plot of ZIKV-infected (E+NS3+) cells within all live WBCs. i, Within the E+ NS3+ cell population, a representative flow plot for ZIKV-infected monocytes. These monocytes were pregated on CD11b+HLA-DR+ cells. j, Frequency of CD14+, CD14+CD16+ and CD16+ monocytes that are ZIKV E+NS3+. k,l, Percentage of ZIKV-infected pDCs and mDCs (k) or CD4+ and CD8+ T cells (l). Mean ± s.d. is shown for all bar graphs. Doublet exclusion was performed for all samples. A representative flow plot for all bar graphs is shown in Supplementary Fig. 1d–j for d–f and Supplementary Fig. 2a,b for k and l. Significance was determined by Student’s t-test or (in j) one-way ANOVA with Tukey’s post-test. *P < 0.05, **P < 0.01, ***P < 0.001. For all panels, n = 4 donors from two individual experiments.

and later (3–6) days of illness at enrolment, and the latter com- all (94.7%) Zika, compared to 50% of dengue cases, respectively, pared to dengue cases (3–6 days). Of the Zika and dengue patients, developed rash (P < 0.01). Conjunctivitis, arthralgia and abdominal 63.2% and 37.5% had been exposed to DENV previously. Almost pain were not significantly different. All dengue cases were febrile

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Monocytosis NS3-double-positive cells we found that an average of 4.6% of all is important for the rapid control of virus and clearance from the PBMCs become infected. While many studies of ZIKV exclusively body and is associated with reduced viral titres in the central ner- use anti-E antibodies, our study demonstrates that both antibodies vous system (CNS) and lower mortality in mice 4,10,11. are necessary to identify ZIKV-infected cells, as 32–40% of the E ZIKV RNA was measured in serum and urine by real-time staining was detected on the surface of in-vitro-infected cells and reverse transcription-polymerase chain reaction (RT-PCR) on day PBMCs from Zika patients and does not necessarily imply infection 1 of presentation, corresponding to days 1 to 6 of illness. All patients (Supplementary Fig. 5; see Methods). Within the patients’ infected were negative for DENV and CHIKV. ZIKV was detectable exclu- (E+NS3+) WBCs, 82.6% were monocytes, 10.7% mDCs, 2% NK cells, sively in serum in 6 patients (21%), whereas 9 (31%) and 14 (48%) 0.8% B cells and 0.6% T cells (Fig. 3a). Furthermore, of all E+NS3+ patients were ZIKV-positive in serum and urine or were serum-neg- WBCs, a mean of 18.8 ± 11.3% (s.d.) were CD14+, 59.8 ± 16.1% were ative but urine-positive, respectively (Fig. 2a,b) 2,12. ZIKV in serum CD14+CD16+ and 4 ± 3.5% were CD16+ monocytes (Fig. 3b). Thus, and PBMCs was quantified by quantitative reverse transcription- CD14+CD16+ monocytes are the main target of infection within polymerase chain reaction (qRT-PCR) on days 1–3 post-presen- WBCs of patients, consistent with our in vitro experiments. tation; viraemia peaked on days 1–3 post-onset of symptoms and Studies of WNV and DENV infection in humans have also shown declined thereafter, whereas no significant differences in viral load monocytes and macrophages to be highly susceptible to infection5–7. were detected in PBMCs at days 1–6 post-symptom onset (Fig. 2b,c). Several receptors, including DC-SIGN, AXL, Tyro 3 and TIM- Thus, ZIKV RNA is detectable in PBMCs longer than in serum, sug- 1, have been described as possible entry receptors for ZIKV into gesting that WBCs may function as a potential reservoir. Similarly, cells. In particular, the TAM receptor AXL has been identified as an PBMCs are permissive to infection with DENV and WNV1,3,6–8. entry factor for ZIKV in fetal endothelial, microglia and other brain However, the level of ZIKV infection in PBMCs was lower than in cells16–18. Interestingly, AXL and the other receptors are also strongly serum, suggesting that other sources may contribute to viraemia. expressed on monocytes, macrophages and DCs, all of which are Based on phenotypic differences detected in vitro, we next deter- highly susceptible to ZIKV infection19. The closely related DENV mined the impact of ZIKV infection in the WBCs of Zika patients. uses AXL for entry into cells through indirect binding to AXL via For each patient, we analysed PBMCs collected on days 1, 2 and 3 Gas620. Therefore, we speculate that AXL could also play a role in post-presentation and did not detect differences in any cell popula- ZIKV infection of monocytes; however, further studies are needed tions over time (Supplementary Fig. 3c–i). Thereafter, we selected to determine the role of AXL and other receptors, such as DC-SIGN day 1 post-enrolment for phenotypic cell comparisons to healthy and Tyro3, in the tropism of ZIKV for monocyte populations. uninfected blood donors (Fig. 2d–h). The overall proportions of Monocytes can play a pathogenic role upon infection by flavivi- cell populations within each patient were comparable to healthy ruses and other pathogens by contributing to the spread of infection individuals (Supplementary Fig. 4a,b). To identify changes within within the body via the ‘Trojan horse’ mechanism, whereby mono- monocytes, we first gated cells on CD11b+HLA-DR+ and examined cytes infected directly or indirectly disseminate virus and thereby the level of CD14 and CD16 expression (Fig. 2d,e). ZIKV infec- potentiate disease and increase mortality7–9,15,21. In animal models of tion resulted in significant expansion of CD14+CD16+ monocytes HIV and WNV infection, virus is spread into the CNS through infil- compared to uninfected individuals (P < 0.01), although the overall tration of infected monocytes across the blood–brain barrier4,10,22–24. frequency and absolute cell number was low in all patient samples, HIV-infected monocytes and T cells can also disseminate infection and there was a reduction in the percentage and number of classical across the blood–testis barrier, resulting in sexual transmission of (CD14+CD16−) monocytes (P < 0.05) (Fig. 2e and Supplementary HIV through infected sperm2,25,26. Because ZIKV is also sexually Fig. 4c). Thus, we found CD14+CD16+ monocytes are expanded transmitted through infected sperm, infected WBCs could be a during ZIKV infection in vitro and in vivo, consistent with other vehicle for transporting virus across the blood–testis barrier3,6–8,27. studies of HIV or DENV infection2,4,13,14. CD14+CD16+ monocytes We found that mDCs are also susceptible to ZIKV infection, produce large quantities of inflammatory cytokines and display but that the percentage of pDCs in blood is increased during ZIKV high phagocytic activity, contributing to an inflammatory immune infection. pDCs are major producers of type I interferon after viral response to clear pathogens1,5,6,14. CD14+CD16+ monocytes can exposure13,14,28,29, and their increase results in reduced disease sever- quickly differentiate into DCs and activate T cells during viral infec- ity30. Thus, the observed increase of pDCs during ZIKV infection tion2,7–9,15, as well as induce plasmablast differentiation and antibody could have beneficial implications for Zika pathogenesis. responses during acute DENV infection in humans and primates, ZIKV is closely related to the flavivirus DENV, so we compared demonstrating they are important mediators of adaptive immune the immune profile of ZIKV to DENV infection by analysing sam- responses3,5,7,13. Therefore, CD14+CD16+ monocytes may play an ples from day 1 post-enrolment from dengue patients in the same important role in the immune response during ZIKV infection, and hospital-based study. We found that DENV infects 4.5-fold more additional studies are needed to determine the exact role of mono- PBMCs than ZIKV (P < 0.0001, Fig. 3c,d). The percentage of clas- cytes during ZIKV pathogenesis. sical CD14+ monocytes was higher (P < 0.01) and that of CD16+ Next, we gated WBCs on CD3+ T cells and found an increase in monocytes was decreased in ZIKV- compared to DENV-infected the percentage of CD4+ T cells (P < 0.05) and naive CD4+ T cells patients (P < 0.001) (Fig. 3e and Supplementary Fig. 6a), while (P < 0.001) and a decrease in CD8+ T cells (P < 0.05), CD4+ effec- the percentage of CD14+CD16+ monocytes was similar in both tor memory T cells (P < 0.001) and CD4+ effector T cells compared groups. However, CD14+CD16+ monocytes were significantly more to healthy individuals (Fig. 2f–h and Supplementary Fig. 4d). The infected with ZIKV compared to DENV (P < 0.01), while infection percentage of pDCs was higher in ZIKV-infected patients (P < 0.05) of CD16+ monocytes was higher in DENV-infected compared to (Supplementary Fig. 4e), while mDCs, NK cells and B cells were ZIKV-infected patients (P < 0.05) (Fig. 3f). Similarly, the frequency unchanged (Supplemental Fig. 4f–h). of CD4+ T cells was elevated, whereas CD8+ T cells were decreased We then examined which WBCs are targeted by ZIKV during during ZIKV infection compared to DENV (P < 0.01) (Fig. 3g and acute infection by staining a subset (n = 19) of the same patients Supplementary Fig. 6b), and significantly fewer CD3+ T cells became

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ab c 0.45 Zika serum+ urine+ 8 0.4 Zika serum+ urine– PBMC + + Zika serum urine 7 Serum 31% 0.35 0.3 6 48% 0.25 5 0.2 copies per ml 10 21% 0.15 4 Proportion by 0.1 3 + + serum/urine positivity 0.05 ZIKV serum urine 0 ZIKV log 2 ZIKV serum+ urine– 123456 123456 – + ZIKV serum urine Days of illness Days of illness

de+ + + + Healthy Zika patient CD14 CD14 CD16 CD16 250 × 103 100 * 200 × 103 80 7.7 8.1 3 150 × 10 60 100 × 103 40 3 ** 50 × 10 % of monocytes 20 FSC 0 101 102 103 104 105 0 CD11b-Pac Blue 250 × 103 Healthy Healthy Healthy 3 Zika patients Zika patients Zika patients 200 × 10 37.9 33.8 150 × 103 f Healthy Zika patient 100 × 103 105 50 × 103 4 FSC 0 10 –103 0 103 104 105 39.7 59.2 3 HLA-DR-PE-CY7 10 0 105 62.9 42.8 87.2 6.9 69.8 14.8 3

CD4-APC-Cy7 –10 104 101 102 103 104 105 103 CD3-FITC 102 5.9 9.1 101 h Central E ector

CD14-PE-Cy7 Naive Memory E ector 80 memory memory 101 102 103 104 105 *** CD16-FITC g 100 CD4+ CD8+ 60 ***

80 * T cell s

* + 40 60 T cells + ** 40 % of CD4 20 % of CD3 20

0 0

Healthy Healthy Healthy Healthy Healthy Healthy Healthy

Zika patients Zika patients Zika patients Zika patients Zika patients Zika patients Zika patients

Fig. 2 | Detection of ZIKV in serum, PBMCs and urine and characterization of phenotypic changes of cell populations in the blood of Zika patients. a, Frequency of all patients who were ZIKV RT-PCR-positive in serum only (n = 6), serum and urine (n = 9) or urine only (n = 14). b, Proportion of serum/urine positivity by day of illness. c, Viral titres quantified in PBMCs (n = 19) and serum (n = 15) by qRT-PCR on day 1 of presentation (days 1–6 post-onset of illness). The median viral titre is shown. In d–h, phenotypic analyses are shown of changes in cell population in healthy individuals (n = 6) and all patients (n = 29) that are ZIKV RT-PCR-positive. d, Representative dot plots of the gating strategy used for identifying CD14+, CD14+CD16+ and CD16+ monocytes within live CD11b+ and HLA-DR+ cell populations of patients. e, Frequency of CD14+, CD14+CD16+ and CD16+ cells within all monocytes in healthy individuals and Zika cases. f, Representative dot plot of CD4+ and CD8+ T cells in a healthy and ZIKV-infected patient. g, Frequency of CD4+ and CD8+ T cells within CD3+ T cells. h, Phenotypic analysis of CD4+ T cells and identification of naive (CD45RA+CD45RO−CCR7+), memory (CD3+CD4+CD 45RA−CD45RO+), central memory (CD3+CD4+CD45RA−CD45RO+CCR7–), effector memory CD3+CD4+CD45RA−CD45RO+CCR7−) and effector T cells (CD3+CD4+CD45RA+CD45RO−CCR7−) in healthy and ZIKV-infected individuals. For all bar graphs, mean ± s.d. is shown. Representative flow plots for h are provided in Supplementary Fig. 4d. Significance was determined by Student’s t-test; *P < 0.05, **P < 0.01, ***P < 0.001.

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ab80 *** ***

0.6% T cells cells 4.0% CD16+ monocytes + 18.8% CD14+ monocytes 40 59.8% CD14+CD16+ monocytes 20 2.0% NK cells Monocytes (%) within ZIKV 10.7% mDC 0 0.8% B cells + + + Total = 4.6% CD14 + CD16 CD16

CD14

c d Isotype Zika patient Dengue patient 20 **** 105 15 104 1.54 13.9 0.78 4.76

3 cells (%) 10 + 10 NS 3

2 within WBCs 10 + 0.64 0.95 E 5 101 ZIKV/DENV E 0 101 102 103 104 105 ZIKV/DENV NS3 Zika Dengue efMonocytes Infected monocytes CD14+ CD14+ CD16+ CD16+ 100 80 ** ** Zika

80 Dengue cells

+ 60 60 *** 40 and NS3

40 + Monocytes (% )

% of monocytes 20 20 * within E 0 0

+ + + + + + Zika Zika Zika CD14 CD14 + CD16 + CD16 CD16 CD16 Dengue Dengue Dengue

CD14 CD14 ghi CD3+ T cells Infected T cells NK cells CD4+ CD8+ 100 8 20 *** ** **

80 ** cells + 6 15 T cells

60 + 4 10 and NS3

40 + % of WBC T cells (% ) 2 5

% of CD 3 20 within E 0 0 0

Zika Zika Zika Zika Dengue Dengue Dengue Dengue

Fig. 3 | Staining for ZIKV E and NS3 identifies replicating virus mainly in CD14+CD16+ monocytes in Zika patients, compared to dengue, but viral replication is higher in dengue patients. Infection of WBCs in Zika patients was examined in a subset of Zika patients (n = 19) by staining for E and NS3. a, Pie chart showing the mean frequency of cell types that are infected with ZIKV (E+NS3+). b, Percentage of CD14+, CD14+CD16+ and CD16+ monocytes that are infected with ZIKV (E+NS3+). Data are from patient samples on day 1 of presentation to the hospital, which is mean day 3.3 post-illness onset (n = 19). In c–i, infection of WBCs in patients with Zika is compared to WBCs of dengue patients. WBCs were collected on day 1 of presentation to the hospital from Zika or dengue patients, 3–6 days post-onset of illness. c, Representative dot plot of intracellular E and NS3 staining in a ZIKV- and a DENV-infected patient. An isotype control for E and NS3 staining was included. Cells were gated on live PBMCs. Doublet exclusion was performed for all samples. d, Percentage of ZIKV or DENV infection (E+NS3+) in WBCs from Zika and dengue patients. e, Frequency of CD14+, CD14+CD16+ and CD16+ cells within all monocytes in Zika and dengue patients. f, Percentage of infected CD14+, CD14+CD16+ and CD16+ monocytes (E+NS3+) within PBMCs from Zika or dengue cases. g, Frequency of CD4+ and CD8+ T cells within CD3+ T cells of ZIKV- or DENV- infected patients. h, Staining for E and NS3 within all CD3+ T cells in Zika versus dengue patients. i, Frequency of NK cells within PBMCs of ZIKV- or DENV-infected patients. Bar graphs show mean ± s.d.; n = 19 (a–d) or n = 29 (e, g, i) Zika patients and n = 8 dengue patients. A representative flow plot for e–i is shown in Supplementary Fig. 6a–d. Significance was determined by Student’s t-test and, in b, one-way ANOVA; *P < 0.05, **P < 0.05, ***P < 0.001, ****P < 0.0001.

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infected in Zika patients (P < 0.01) (Fig. 3h and Supplementary and November of 2012. Suspected Zika and dengue cases presenting to the Fig. 6c). The frequency of NK cells was significantly reduced in Zika HIMJR 1–6 days post-symptom onset were enrolled afer informed consent, and cases (P 0.001) (Fig. 3i and Supplementary Fig. 6d), while mDC blood and urine were collected on days 1, 2 and 3 post-enrolment. Children were < examined by study physicians, and clinical data were recorded systematically on and B cell frequency was not different (Supplementary Fig. 6e,f). study collection forms. Enrolment criteria consisted of age less than 15 years and Thus, WBCs from patients are less susceptible to ZIKV infection presentation with an acute febrile illness of fewer than 7 days duration consistent compared to DENV, and phenotypic differences occur between with the case defnition for dengue or Zika (the latter, rash with one or more of the following symptoms: conjunctivitis, arthralgia, myalgia and/or periarticular ZIKV- and DENV-infected patients, despite the close structural 37 similarity of the viruses. oedema regardless of fever) . ZIKV and DENV infection were confrmed by real-time RT-PCR performed at the National Virology Laboratory of the Ministry Next, we analysed the transcriptional profile of monocytes of Health in Managua using either of two triplex assays that simultaneously detect infected in vitro with ZIKV for 24 and 48 h compared to monocytes ZIKV, CHIKV and DENV infections: the ZCD assay38 or the CDC Trioplex assay39. from healthy uninfected blood donors using a TaqMan gene expres- Patients with acute ZIKV infection (n = 29) or DENV infection (n = 3 DENV2 from sion assay. Certain chemokines were >1,000-fold or 100–700-fold 2016 and n = 5 DENV1 from 2012) were selected for our study. For the comparison upregulated (Fig. 4a), including several chemokines (for example, of PBMCs from Zika versus dengue, Zika and dengue patients presenting to the 31 hospital on days 3–6 of illness (mean 3.8 (±0.9) for Zika and mean 4.5 (±1.1) CXCL8 ) important for neutrophil trafficking. Neutrophils could days for dengue, P > 0.05) were included in the analysis. Te hospital study was play a critical role in ZIKV pathogenesis or control; studies with reviewed and approved by the Institutional Review Boards (IRB) of the University WNV and Japanese encephalitis virus have demonstrated that of California, Berkeley, and the Nicaraguan Ministry of Health. Parents or legal neutrophils serve as a virus reservoir and facilitate viral dissemina- guardians of all subjects provided written informed consent, and subjects 6 years of 32,33 age and older provided assent. Healthy blood donor samples were collected at the tion . Interestingly, many genes involved in the immune response American Red Cross Blood Donation Center and the Nicaraguan National Blood and almost all interleukins were not differentially expressed during Bank, with two adult patient samples from Oakland and four adult patient samples ZIKV infection. from Nicaragua, respectively. Finally, we compared the gene expression profile of monocytes in ZIKV- versus DENV-infected patients and found a similar profile, PBMC isolation. Daily blood samples were collected on days 1, 2 and 3 post- with many genes upregulated and four genes downregulated during enrolment into the hospital study. PBMCs, plasma and serum were prepared as previously described7,40. For PBMC preparation, blood samples were collected in both infections (Fig. 4b, Supplementary Fig. 7 and Supplementary Vacutainer tubes (Becton-Dickenson) with EDTA anticoagulant reagent. Upon Table 2). Genes that were >100-fold upregulated during ZIKV or receipt in the Nicaraguan National Virology Laboratory, 4–5 ml of blood was DENV infection were CCL2, CXCL12, XCL1, CXCR5, IL-6, PF4/ transferred into a Leucosep tube (Greiner Bio-One) containing 3 ml of Ficoll CXCL4 and IFN-γ (Supplementary Fig. 7 and Supplementary Histopaque (Sigma) and centrifuged at 500g for 20 min at room temperature. Table 2). The median expression of CXCL12 and IL-6 was >100-fold The PBMC fraction was collected and transferred to a 15 ml conical tube containing 9 ml of PBS with 2% fetal bovine serum (FBS; Denville Scientific) higher during ZIKV infection (P < 0.05), while expression of XCL1, and 1% penicillin/streptomycin (Sigma). Cells were washed three times in interferon (IFN)-γ and interleukin (IL)-10 was >100-fold higher this solution by centrifugation at 500g for 10 min and resuspended in 10 ml of during DENV infection (P < 0.05) (Fig. 4b and Supplementary complete medium. Before the third wash, an aliquot was used to obtain a cell Fig. 7). Thus, the cytokine expression profile induced in monocytes count using a haematology analyser (Sismex XS-1000i). After the third wash, 7 in the blood of ZIKV- and DENV-infected patients is comparable cells were resuspended at a concentration of 10 cells per ml in freezing medium consisting of 90% FBS and 10% dimethyl sulfoxide, and aliquoted. Cryovials but differs in selected inflammatory cytokines. Chemokines with an containing the cell suspension were placed in isopropanol containers important role in the chemotactic activity of monocytes and T cells (Mr. Frosty, Nalgene) at −80 °C overnight and transferred to liquid nitrogen for were upregulated in both diseases. However, CXCL12 was signifi- storage. For in vitro infection experiments, PBMCs were isolated from Buffy cantly higher in monocytes during ZIKV infection. Dysregulation coats from healthy blood donors obtained from the American Red Cross Oakland of CXCL12 is associated with reduced integrity of the blood–brain Blood Donation Center and the Nicaraguan National Blood Bank using the protocol described above. barrier during viral encephalitis34,35. WNV studies showed that CXCL12 is implicated in WBC retention in the CNS perivascular Monocyte isolation. Monocytes were isolated from PBMCs of healthy blood space and regulation of CD8+ T cell trafficking into the brain for donors and from ZIKV- and DENV-infected patients from the Nicaraguan viral clearance36. Thus, CXCL12 could play a role in inflammation hospital study using the Pan-monocyte Isolation Kit (Miltenyi) according to of the brain in the fetus and associated brain abnormalities. the manufacturer’s protocol. In brief, PBMCs were quickly thawed at 37 °C and washed twice in RPMI containing 10% FBS, 2 mM l-glutamine and 1% penicillin/ In summary, we have shown that WBCs are permissive to ZIKV streptomycin. The cells were then blocked with 10 µl FcR-blocking reagent and + + infection and that monocytes, particularly CD14 CD16 mono- stained with 10 µl biotin–antibody cocktail for 5 min at 4 °C. After incubation, cytes, followed by DCs, are the main target of infection. Because cells were stained with 20 µl anti-biotin Microbeads (Miltenyi) for 10 min at 4 °C. monocytes can infiltrate many tissues, including immune-sheltered For manual separation, an LS cell separation column (Miltenyi) was placed into a organs, they are ideal targets for infection, as they can act as ‘Trojan MACS Separator (Miltenyi), and the negative fraction containing the flow-through + + of enriched and unlabelled monocytes was collected and counted. The purity of horses’. We found that the percentage of CD14 CD16 monocytes the isolated monocyte populations was determined by flow cytometry using the 13 is increased, consistent with their role in infection with DENV . markers CD11b, CD14 and CD16, and was found to be >95% pure. The gene expression profile of monocytes during ZIKV infection is generally muted, with low induction of cytokines/chemokines, Virus and in vitro infection of PBMCs and monocytes. ZIKV strain Nica 2–16 consistent with the mild symptomatology of Zika. Identifying cel- was used for in vitro experiments and was initially isolated in early 2016 from a ZIKV-infected patient by the National Virology Laboratory, Nicaraguan Ministry lular targets of ZIKV infection in the blood is an important step in of Health41. Nica 2–16 was propagated at low passage in C6/36 cells in MEM understanding the early stages of the ZIKV-induced innate immune (Gibco) supplemented with 5% FBS, 1% penicillin/streptomycin, and 2 mM response, when drug therapies could be applied to prevent compli- l-glutamine (Invitrogen), and cell-free supernatants were collected 4, 5 and 6 days cations and severe outcomes of Zika. Future studies are needed to post-infection (p.i.). The C6/36 cells were donated by R. Baric, University of define the specific role monocytes play during ZIKV pathogenesis North Carolina, Chapel Hill. Cells were tested for DENV and ZIKV contamination by RT-PCR and for mycoplasma contamination by PCR. This cell line is not listed and how they contribute to dissemination via the maternal–fetal in the database of commonly misidentified cell lines maintained by ICLAC and and blood–testis barriers. NCBI Biosample. For in vitro infections, PBMCs from healthy blood donors were plated onto a 24-well plate (Corning), and 2 to 5 × 105 cells per well were infected Methods with Nica 2–16 at a multiplicity of infection (MOI) of 1 for 1 h in serum-free RPMI Study design and population. PBMCs from ZIKV-infected patients were obtained at 37 °C. Fresh medium was then added to each well, and PBMCs were collected at from an ongoing study in the Infectious Disease Ward of the Nicaraguan National 48 h and 72 h p.i. for analysis by flow cytometry and immunofluorescence. Isolated Pediatric Reference Hospital, Hospital Infantil Manuel de Jesús Rivera (HIMJR), monocytes were infected with Nica 2–16 for 1 h at 37 °C in serum-free DMEM in Managua, Nicaragua, between July and August of 2016. PBMCs from dengue medium before adding DMEM supplemented with 5% FBS and 1% penicillin/ patients were obtained between July and August of 2016 and between September streptomycin. Monocytes were isolated after 24 and 48 h of infection in vitro and

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CCL24 CXCL16 10 3 CMTM1 CXCL12 NFKB1 CXCL6 2 CLCF1 PF4 CCL3 TNFSF14 IL−6 5 1 TYMP CCL2 GRB2 CXCR5 IFNGR1 XCL1 0 CXCL11 IL1B 0 IL1A CCL25 CCL4 –1 CCL4 CXCL1 STAT4 CXCL14 CCL22 –2 CCRL1 –5 CXCL9 CCR4 IFNGR1 IL10 –3 CCL1 NFKB1 CCL13 CLCF1 CCL19 –10 –4 IL1B SOCS5 CKLF STAT4 JAK2 CMTM1 TLR2 CCL25 TLR4 IL1RAP IL18 MYD88 MYD88 C5 GRB2 SCYE1 IL18 TNFSF14 SLIT2 TYMP TNF−alpha TNFRSF1A TNFSF10 TNFRSF1A C5 HIF1A CCR2 STAT3 SOCS5 CXCL12 IL−6 CXCL5 XCL1 PPBP CXCR5 CCL19 CCL2 CCL5 CCL8 PF4 CXCL10 IFN−gamma CCL1 CXCL5 PPBP IL10 CCL8 IL−8 CXCL10 CCR4 IL16 CCL22 CCRL1 CCL24 TNFSF10 CCL20 HIF1A CXCL13 CXCL11 IL−2 CCL21 SCYE1 IL13 STAT3 IL−9 JAK2 IL−5 IL−4 CKLF DARC CCL5 CX3CL1 TLR2 CXCL7 CXCL6 IL16 CCL28 IL1RAP CCL27 TLR4 CCL26 CCL17 CCL3 CCL11 CXCL2 CCL16 IFN−gamma CCL23 CCR10 TNF−alpha CCR3 CCL23 IL12B IL−2 CXCL1 CSF2 IL12A CXCL3 CCL7 IL1A CXCL16 IL12A CXCL2 CXCL3 CXCL9 CCR3 CCL7 CCRL2 CCRL2 CCL18 CXCR4 GDF5 CCL20 GPR81 XCR1 CCR2 CXCR4 CCL18 XCR1 GDF5 IL−8 ZIKV 24 h ZIKV 48 h Zika Dengue

Fig. 4 | Gene expression analysis in monocytes from in vitro ZIKV-infected PBMCs or monocytes isolated from Zika and dengue patients reveals significant differences in several cytokines and chemokines. a,b, TaqMan gene expression analysis of in vitro ZIKV-infected monocytes after 24 h or 48 h post-infection at an MOI = 1 (a) and monocytes isolated from Zika and dengue patients in the acute phase of illness (b). Samples were tested in triplicate. Heatmaps are shown for log10-fold changes of mean gene expression. Hierarchical clustering was performed for all samples using R. n = 3 for in vitro ZIKV infection experiments and n = 3 each for Zika and dengue patients. Data were derived from two individual experiments.

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from infected patients, and cell pellets were resuspended in 1 ml of Trizol for RNA conditions: 50 °C for 30 min, 95 °C for 12.5 min, followed by 40 cycles of 95 °C extraction and subsequent TaqMan gene expression analysis. for 15 s and 60 °C for 1 min. RNA in each sample was quantified by using a linear regression equation for the standard curve, as described previously45, and the titre Flow cytometry. PBMCs were removed from liquid nitrogen storage and quickly was expressed as log10 copies per ml. thawed at 37 °C. Thawed cells were then washed with RPMI (Gibco) supplemented with 10% FBS, 2 mM l-glutamine and 1% penicillin/streptomycin and centrifuged TaqMan gene expression assay. RNA (10 μl) from isolated monocytes from for 5 min at 300g before counting cells with a haemocytometer. PBMCs were then ZIKV- or DENV-infected Nicaraguan hospital patients was converted to cDNA resuspended in flow cytometry buffer (PBS without Ca2+/Mg2+ containing 2% FBS using the high-capacity RNA-to-cDNA kit (Applied Biosystems) following the and 2 mM EDTA (LifeTech)) and stained with 1:100 Zombie Aqua (BioLegend) manufacturer’s protocol. To determine the relative quantitation of gene expression viability dye for 15 min at room temperature. PBMCs were divided into different of chemokines, cytokines and other immune response-related genes, a chemokine wells of a 96-well plate, distributing between 70,000 and 200,000 cells per well. TaqMan gene signature plate (Applied Biosystems) was used, containing FAM-(5′) Next, PBMCs were blocked with human Fc block (1:100, Miltenyi) for 10 min at and MGB-(3′) labelled TaqMan probes and corresponding primers for one of the 4 °C, and the appropriate antibody cocktail for each staining panel was added to 92 test genes and 4 house-keeping genes as described by the manufacturer (Applied each sample and stained for 20 min at 4 °C for surface markers. All antibodies were Biosystems). ROX was used as a passive reference dye. For each plate, 1–100 ng obtained from eBioscience unless stated otherwise: CD45RA, CD45RO, CD3, CD4, cDNA per 20 µl reaction was used, and 10 µl of TaqMan Gene Expression master CD8, CCR7, CD11b, CD16, CD14, CCR2, CD1a, CD1c, CD209, CD11c, CD56, mix (Applied Biosystems) was added into each well (Applied Biosystems) and CD27, IgM, CD19, CD38, CD20, CD123 and HLA-DR. For data acquisition, the run under the following cycling conditions: 50 °C for 2 min, 95 °C for 10 min and samples were read with an LSR Fortessa high-throughput sampler (HTS) plate then 95 °C for 15 s and 60 °C for 1 min, repeated for 40 cycles using the standard -ΔΔCt reader (BD Biosciences) with 405, 488, 562 and 632 nm laser excitation lines and mode on an Applied Biosystems 7300 PCR system. Using the 2 method, the were analysed using FlowJo software (TreeStar) version 10.2. All cells were gated mRNA-fold change was calculated as previously described, comparing all genes to 46 on live WBCs that were negative for Zombie Aqua dye. Negative and positive gates uninfected monocytes and to the house-keeping gene 18S (Supplementary Fig. 8). were determined using isotype controls, uninfected controls and/or ‘Fluorescence Fold changes were visualized by transforming the data to log10 and generating a Minus One’ controls. A doublet-exclusion using SSC-Area versus SSC-Height was heatmap using R version 3.3.1. performed for all samples. To set up a compensation matrix, BD CompBeads (BD Biosciences) were used. Statistical analysis. Viraemia and viral load data obtained from cells were analysed using a Mann–Whitney U-test. The flow cytometry data set was analysed using a Student’s t-test for pairwise comparisons and a one-way analysis of variance Staining for viral proteins by flow cytometry. To identify ZIKV- and DENV- (ANOVA) for multiple comparisons applying a Tukey’s post-test unless stated infected cells, a Cytofix/Cytperm kit (BD) was used for intracellular staining with otherwise. To calculate statistical differences in outcomes for ZIKV and DENV a pan-flavivirus mAb against the envelope protein, E (4G2, ATCC) and a mAb infection, we used a Pearson’s chi-squared test. Statistical significance was defined against nonstructural protein 3, NS3 (E1D842) as per the manufacturer’s protocol. as *P 0.05, **P 0.01, ***P 0.001 and ****P 0.0001. To remove bound virus from the cell surface, cells were incubated with trypsin < < < < for 60 min on ice and washed with flow cytometry buffer prior to performing Code availability. The R code for generation of the heatmaps is available from the intracellular staining. mAbs 4G2 and E1D8 were conjugated with phycoerythrin corresponding author upon request. (PE) and Alexa Fluor 647, respectively, using protein-labelling kits (Thermo Fisher), and were used at a concentration of 1:500 to 1:800. For isotype controls Data availability. The data that support the findings of this study are available for 4G2 and E1D8, a mouse IgG2a and mouse IgG2b were used, respectively. To from the corresponding author upon reasonable request. assess the proportion of actively infected cells among E+-positive cells, because staining for E alone is widely used in the field, we stained with only 4G2 and found that an average of 9.1% (±2.4 s.d.) of WBCs were positive for ZIKV E in in-vitro- Received: 26 June 2017; Accepted: 1 September 2017; infected PBMCs and 8.4% (±2.6 s.d.) were ZIKV E+ in patient samples (n = 29, Published online: 2 October 2017 Supplementary Fig. 5). When we also stained for NS3 protein, which is expressed only by replicating virus, we found that an average of 6.8% (±0.9) and 4.6% (±1.7) References of WBCs were double-positive for E and NS3 in in-vitro-infected cells and Zika 1. Kuno, G. & Chang, G. J. J. Full-length sequencing and genomic patients (n = 19), respectively (Supplementary Fig. 5). To determine how much characterization of Bagaza, Kedougou and Zika viruses. Arch. Virol. 152, virus is adherent on the surface of cells, we tested non-permeabilized PBMCs from 687–696 (2007). the same cells and patients and performed surface staining with mAbs against E 2. Zika - Epidemiological Update (Americas) (PAHO, 2017); http://www.paho. and NS3. We found that 2.7% (±1.2) and 3.4% (±0.9) of in-vitro-infected cells and org/hq/index.php?option=com_docman&task=doc_view&Itemid=270&gid= patient PBMCs were positive for E on the cell surface, respectively (Supplementary 40222&lang=en Fig. 5), whereas no NS3 was detectable on the surface of cells. Together, these 3. D’Ortenzio, E. et al. Evidence of sexual transmission of Zika virus. N. Engl. results indicate that 68–60% of the E protein detected by intracellular and surface J. Med. 374, 2195–2198 (2016). staining is from replicating virus and the other 32–40% adheres to the surface of 4. Salinas, S., Schiavo, G. & Kremer, E. J. A hitchhiker’s guide to the nervous cells, while only a minimal amount of virus is phagocytosed. Thus, to determine system: the complex journey of viruses and toxins. Nat. Rev. Microbiol. 8, the frequency of replicating ZIKV, it is necessary to use the E and NS3 antibodies 645–655 (2010). in conjunction. 5. Garcia-Tapia, D., Loiacono, C. M. & Kleiboeker, S. B. Replication of West Nile virus in equine peripheral blood mononuclear cells. Vet. Immunol. RNA extraction and qRT-PCR. To quantify ZIKV and DENV infection in Immunopathol. 110, 229–244 (2006). serum and in PBMCs from hospital patients, quantitative real-time RT-PCR was 6. Rios, M. et al. Monocytes–macrophages are a potential target in human performed. RNA was extracted from 140 µl of serum using the QIAmp Viral infection with West Nile virus through blood transfusion. Transfusion 46, RNA Mini kit (Qiagen) and was stored at −80 °C. 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Clin. Microbiol. 40, 4472–4478 (2002). Primers ZIKV 1086 and ZIKV 1162c were used, with a probe modified to 9. Kou, Z. et al. Monocytes, but not T or B cells, are the principal target cells for match the Nicaraguan strain Nica 2–1641 ZIKV_1107-FAM_UG&Nica ([FAM] dengue virus (DV) infection among human peripheral blood mononuclear AGCCTACCTTGACAAGCAGTCAGACACTCAA [BHQ1]). RNA standards cells. J. Med. Virol. 80, 134–146 (2007). consisted of RNA transcripts that were generated from an amplicon derived from 10. Ben-Nathan, D., Huitinga, I., Lustig, S., Van Rooijen, N. & Kobiler, D. West ZIKV Nica 2–16 (GenBank KX421194) using the following primer set modified Nile virus neuroinvasion and encephalitis induced by macrophage depletion from the CDC singleplex assay44: ZIKV 835_T7 ± 10 (5′TAATACGACTCACT in mice. Arch. Virol. 141, 459–469 (1996). ATAGGGAGTCATATACTT GGTCATGATACTGCTGATTGC3′) and ZIKV 11. Michlmayr, D. & Lim, J. K. Chemokine receptors as important regulators of 1162c ± 10_Nica (5′CAGCCTCTGTCCACTAA CGTTCTTTTGCAGACAT3′). pathogenesis during arboviral encephalitis. Front. Cell Neurosci. 8, 264 (2014). RNA transcripts were generated using RiboMA Large Scale RNA Production 12. Faria, N. R. et al. Establishment and cryptic transmission of Zika virus in System-T7 (Promega). For quantitation, clinical samples and the RNA standards Brazil and the Americas. Nature 546, 406–410 (2017). were processed in duplicate on a single run using a Verso 1-Step QRT-PCR Kit 13. Kwissa, M. et al. Dengue virus infection induces expansion of a CD14+CD16+ (Fisher Scientific). The mean cycle count (Ct) was used for all calculations. The monocyte population that stimulates plasmablast diferentiation. Cell Host 96-well plate was run on a 7300 Applied Biosystems machine using the following Microbe 16, 115–127 (2014).

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Wang for optimizing primers, probes and standards for use of the 25. Faria, N. R. et al. Zika virus in the Americas: early epidemiological and CDC qRT-PCR assay with Nicaraguan ZIKV strains and J. Waggoner for advice and genetic fndings. Science 352, 345–349 (2016). technical support regarding quantitation of viral RNA using the ZCD qRT-PCR assay. 26. Barré-Sinoussi, F., Ross, A. L. & Delfraissy, J.-F. Past, present and future: The authors also thank R. Ben-Shachar for help with statistical analysis and graphs, 30 years of HIV research. Nat. Rev. Microbiol. 11, 877–883 (2013). and D. Glasner for his invaluable assistance with figure preparation. Past and present 27. Musso, D. et al. Potential sexual transmission of Zika virus. Emerg. Infect. Dis. members of the study team based at the Hospital Infantil Manuel de Jesús Rivera, the 21, 359–361 (2015). National Virology Laboratory in the Centro Nacional de Diagnóstico y Referencia of 28. Vremec, D. et al. Production of interferons by dendritic cells, plasmacytoid the Nicaraguan Ministry of Health, and the Sustainable Sciences Institute in Managua, cells, natural killer cells, and interferon-producing killer dendritic cells. Blood Nicaragua, are thanked for their dedication and high-quality work, particularly 109, 1165–1173 (2007). S. Argüello, W. Avilés, C. Cerpas, D. Elizondo, F. McNally, B. Moraga, F. Narváez, 29. Cella, M. et al. Plasmacytoid monocytes migrate to infamed lymph nodes A. Núñez, M. de los Ángeles Pérez, M. Vega, R. Zapata and other study personnel. The and produce large amounts of type I interferon. Nat. Med. 5, 919–923 (1999). authors are also grateful to the children who participated in the study and their families. 30. Colonna, M., Trinchieri, G. & Liu, Y.-J. Plasmacytoid dendritic cells in This work was supported by grants U19AI118610 (to E.H.) and R33AI100186 (to A.B. immunity. Nat. Immunol. 5, 1219–1226 (2004). and E.H.) from the National Institute of Allergy and Infectious Diseases, National 31. Jufrie, M. et al. Infammatory mediators in dengue virus infection in Institutes of Health (NIH). children: interleukin-8 and its relationship to neutrophil degranulation. Infect. Immunol. 68, 702–707 (2000). 32. Srivastava, S. et al. Degradation of Japanese encephalitis virus by neutrophils. Author contributions Int. J. Exp. Pathol. 80, 17–24 (1999). D.M., P.A. and E.H. conceived and designed the experiments. D.M, P.A. and K.G. 33. Bai, F. et al. A paradoxical role for neutrophils in the pathogenesis of West performed experiments. D.M., P.A. and E.H. analysed the data. A.B. and E.H. Nile virus. J. Infect. Dis. 202, 1804–1812 (2010). directed the human studies. D.M., P.A. and E.H. wrote the manuscript. All authors 34. Nanki, T. & Lipsky, P. E. Cutting edge: stromal cell-derived factor-1 is a reviewed the manuscript. costimulator for CD4+ T cell activation. J. Immunol. 164, 5010–5014 (2000). 35. McCandless, E. E. et al. Pathological expression of CXCL12 at the blood– Competing interests brain barrier correlates with severity of multiple sclerosis. Am. J. Pathol. 172, The authors declare no competing financial interests. 799–808 (2008). 36. McCandless, E. E., Zhang, B., Diamond, M. S. & Klein, R. S. CXCR4 antagonism increases T cell trafcking in the central nervous system and Additional information improves survival from West Nile virus encephalitis. Proc. Natl Acad. Sci. Supplementary information is available for this paper at https://doi.org/10.1038/ USA 105, 11270 (2008). s41564-017-0035-0. 37. Narvaez, F. et al. Evaluation of the traditional and revised WHO classifcations Reprints and permissions information is available at www.nature.com/reprints. of dengue disease severity. PLoS Negl. Trop. Dis. 5, e1397 (2011). 38. Waggoner, J. J. et al. Viremia and clinical presentation in Nicaraguan patients Correspondence and requests for materials should be addressed to E.H. infected with Zika virus, chikungunya virus, and dengue virus. Clin. Infect. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in Dis. 63, 1584–1590 (2016). published maps and institutional affiliations.

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Corresponding author(s): Eva Harris Initial submission Revised version Final submission Life Sciences Reporting Summary Nature Research wishes to improve the reproducibility of the work that we publish. This form is intended for publication with all accepted life science papers and provides structure for consistency and transparency in reporting. Every life science submission will use this form; some list items might not apply to an individual manuscript, but all fields must be completed for clarity. For further information on the points included in this form, see Reporting Life Sciences Research. For further information on Nature Research policies, including our data availability policy, see Authors & Referees and the Editorial Policy Checklist.

` Experimental design 1. Sample size Describe how sample size was determined. Blood samples were collected from suspected Zika cases from an ongoing study in the Infectious Disease Ward of the Nicaraguan National Pediatric Reference Hospital, Hospital Infantil Manuel de Jesús Rivera (HIMJR), in Managua between July and August of 2016, during the Zika epidemic. All RT-PCR confirmed ZIKV- positive patients were included in this study (n=29). The number of dengue cases included (n=8) was determined to provide statistical significance when compared with Zika samples; dengue samples were compared to comparable days of illness in the ZIKV-positive samples (see Supplemental Table 1). 2. Data exclusions Describe any data exclusions. No data exclusion. 3. Replication Describe whether the experimental findings were Replication of each experiment yielded consistent and reproducible results; data reliably reproduced. analyzed were consistent, and the mean +/- standard deviation is reported. 4. Randomization Describe how samples/organisms/participants were Randomization was not required in our study because we were not performing an allocated into experimental groups. intervention trial or applying a treatment; it was purely observational. 5. Blinding Describe whether the investigators were blinded to Blinding was not relevant to our study because we were not performing an group allocation during data collection and/or analysis. intervention trial or applying a treatment; it was purely observational. Note: all studies involving animals and/or human research participants must disclose whether blinding and randomization were used. June 2017

1 6. Statistical parameters nature research | life sciences reporting summary For all figures and tables that use statistical methods, confirm that the following items are present in relevant figure legends (or in the Methods section if additional space is needed). n/a Confirmed

The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement (animals, litters, cultures, etc.) A description of how samples were collected, noting whether measurements were taken from distinct samples or whether the same sample was measured repeatedly A statement indicating how many times each experiment was replicated The statistical test(s) used and whether they are one- or two-sided (note: only common tests should be described solely by name; more complex techniques should be described in the Methods section) A description of any assumptions or corrections, such as an adjustment for multiple comparisons The test results (e.g. P values) given as exact values whenever possible and with confidence intervals noted A clear description of statistics including central tendency (e.g. median, mean) and variation (e.g. standard deviation, interquartile range) Clearly defined error bars

See the web collection on statistics for biologists for further resources and guidance.

` Software Policy information about availability of computer code 7. Software Describe the software used to analyze the data in this Data analysis was performed with Graphpad Prism version 6 for Mac and with R study. software.

For manuscripts utilizing custom algorithms or software that are central to the paper but not yet described in the published literature, software must be made available to editors and reviewers upon request. We strongly encourage code deposition in a community repository (e.g. GitHub). Nature Methods guidance for providing algorithms and software for publication provides further information on this topic.

` Materials and reagents Policy information about availability of materials 8. Materials availability Indicate whether there are restrictions on availability of No unique materials were used. unique materials or if these materials are only available for distribution by a for-profit company. 9. Antibodies Describe the antibodies used and how they were validated 1. Antigen CD45RA. Primary murine antibody that reacts with human. Fluorophore for use in the system under study (i.e. assay and species). eFluor450. Supplier name eBiosciences. Catalog Number 48045842. Clone name HI100. Lot number E08506-1632. Validation: The following antibody was used in this experiment: CD45RA Monoclonal Antibody (HI100), FITC, eBioscience™ from Thermo Fisher Scientific, catalog # 11-0458-42, RRID AB_11219672. 2. Antigen CD11b. Primary murine antibody that reacts with human. Fluorophore BV421. Supplier name BD Biosciences. Catalog Number 562632. Clone name ICRF44. Lot number 6056980. Validation: David A, Kacher Y, Specks U, Aviram I. Interaction of proteinase 3 with CD11b/CD18 (beta2 integrin) on the cell membrane of human neutrophils. J Leukoc Biol. 2003; 74(4):551-557. 3. Antigen CD1a. Primary murine antibody that reacts with human. Flurophore eFluor450. Supplier eBiosciences. Catalog #48001941. Clone HI149. Lot#E10906-1632. Validation: See manufacturer's website. 4. Antigen CD27. Primary murine antibody that reacts with human. Fluorophore BV421. Supplier Biolegend. Catalog #356417. Clone M-T271. Lot#B213956. June 2017 Validation: Ma S, et al. 2011. J. Virol. 85:165. (IHC) 5. Antigen CD56. Primary murine antibody that reacts with human. Fluorophore BV605. Supplier Biolegend. Catalog #318334. Clone HCD56. Lot#B228072. Validation: Lanier L, et al. 1991. J. Immunol. 146:4421 6. Antigen IgM. Primary murine antibody that reacts with human. Flurophore BV 605. Supplier Biolegend. Catalog #230638. Clone MHM-88. Lot#B201168. Validation: Perez-Shiyama C, et al. 2014. J Immunol. 192:5192. 7. Primary murine antibody that reacts with human. Fluorophore FITC. Supplier Biolegend. Catalog #300406. Clone UCHT1. Lot #B2118880. Validation: Salmeron A, et al. 1991. J. Immunol. 147:3047. 8. Antigen CD14. Primary murine antibody that reacts with human. Fluorohore 2 FITC. Supplier BD Biosciences. Catalog #555397. Clone M5E2. Lot #46168. Validation: Knapp W, Dörken B, Gilks WR, et al, ed. Leucocyte Typing IV. New York, f 10. Eukaryotic cell lines nature research | life sciences reporting summary a. State the source of each eukaryotic cell line used. No eukaryotic cell lines were used.

b. Describe the method of cell line authentication used. No eukaryotic cell lines were used.

c. Report whether the cell lines were tested for No eukaryotic cell lines were used. mycoplasma contamination.

d. If any of the cell lines used are listed in the database N/A. of commonly misidentified cell lines maintained by ICLAC, provide a scientific rationale for their use.

` Animals and human research participants Policy information about studies involving animals; when reporting animal research, follow the ARRIVE guidelines 11. Description of research animals Provide details on animals and/or animal-derived No animals were used. materials used in the study.

Policy information about studies involving human research participants 12. Description of human research participants Describe the covariate-relevant population The study involved 29 patients who were confirmed as positive for ZIKV infection characteristics of the human research participants. by RT-PCR. Eighteen patients were males and 11 were females, and the age of the patients ranged from 1-14 years old. Fourteen patients were previously exposed to DENV before ZIKV infection and 15 were DENV-naive. Eight dengue patients were also included; 5 female and 3 male, with an average age of 8. Three were sedondary DENV infections (prior exposure to DENV). Additional information is provided in Supplementary Table 1. For in vitro experiments PBMC were isolated from 4 blood donors from Oakland, USA and Managua, Nicaragua. June 2017