# Zika virus reprograms the host tRNA epitranscriptome to adapt translation to A-ending codon bias

Patrick Eldin, Eric Bernard, Cathrine B Vågbø, Lynn George, Masahiko

Ajiro, Masatoshi Hagiwara, Geir Slupphaug, Laurence Briant

► To cite this version:

Patrick Eldin, Eric Bernard, Cathrine B Vågbø, Lynn George, Masahiko Ajiro, et al. Zika virus reprograms the host tRNA epitranscriptome to adapt translation to A-ending codon bias. 2025. [https://doi.org/10.3128/j.cnrs-05343300-1](https://doi.org/10.3128/j.cnrs-05343300-1)

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Preprint submitted on 3 Nov 2025

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# Zika virus reprograms the host tRNA epitranscriptome to adapt translation to A-ending codon bias

Patrick ELDIN<fnref n="1" />*, Eric BERNARD<fnref n="1" />, Cathrine B. VÅGBØ<fnref n="2" />,<fnref n="3" />, Lynn GEORGE<fnref n="4" />, Masahiko AJIRO<fnref n="5" />, Masatoshi HAGIWARA<fnref n="6" />, Geir SLUPPHAUG<fnref n="2" />,<fnref n="3" /> and Laurence BRIANT<fnref n="1" />.

## Abstract

The codon usage bias of the Zika virus (ZIKV) genome is skewed towards AA-ending codons, which are preferentially decoded by U34-modified cognate tRNAs. This contrasts with the human host's preference for AG-ending codons, suggesting that ZIKV may exploit specific tRNA modifications to optimize protein synthesis within human cells. To test this hypothesis, we used codon-biased eGFP sensors and found that ZIKV infection transiently increased the expression of AA-biased GFP at the expense of AG-biased GFP. Mass spectrometry analysis further showed that ZIKV virus infection increases mcm⁵s²U34 tRNA modification content in host cells. In ELP1-deficient cells, which exhibit reduced U34 modifications, ZIKV replication was impaired. Enhancing U34 modification through using a small molecule known to restore ELP1 expression, rescued viral replication in these cells. Moreover, CRISPR/Cas9 and shRNA-mediated knockdown of key enzymes involved in U34 modification, ELP1, ALKBH8, and CTU1, significantly reduced ZIKV replication. Collectively, these results provide strong evidence that ZIKV reprograms the host tRNA epitranscriptome and exploits host cell tRNA modifications, particularly at the wobble position U34, to optimize translation of its own proteins and promote viral replication.

<footnote n="1">¹ Institut de Recherche en Infectiologie de Montpellier (IRIM), Université de Montpellier, CNRS UMR 9004, 1919 Rte de Mende, 34293 Montpellier, France.</footnote>

<footnote n="2">² Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, NTNU, N-7491, Trondheim, Norway.</footnote>

<footnote n="3">³ PROMEC Core Facility for Proteomics and Modomics, Norwegian University of Science and Technology, NTNU, and the Central Norway Regional Health Authority Norway, N-7491, Trondheim, Norway.</footnote>

<footnote n="4">⁴ Department of Biological and Physical Sciences, Montana State University Billings, Billings, MT, 59101, USA.</footnote>

<footnote n="5">⁵ Div. of Cancer RNA Research, National Cancer Center Research Institute, Room 12B, 12th Floor, 1-1, 5 Choume, Tsukiji, Chuo-Ku, Tokyo 104-0045, Japan</footnote>

<footnote n="6">⁶ Department of Drug Discovery Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.</footnote>

<footnote>* Correspondence: patrick.eldin@irim.cnrs.fr</footnote>
Introduction

Zika virus (ZIKV), a mosquito-borne flavivirus, causes a wide range of neurological complications including fetal microcephaly and Guillain-Barré syndrome(1). First identified in 1947 in Uganda, ZIKV remained confined to sporadic human cases in Africa and Asia until recently, when large outbreaks successively occurred in the Pacific Yap Islands (2007), French Polynesia (2013) and South America (2015). In 2015, the widespread presence of ZIKV primary *Aedes* sp. vectors across Latin America, combined with favorable climatic conditions, created the ideal environment for a massive outbreak in Brazil, which rapidly spread across Latin America and the Caribbean(2). The global distribution and continued geographic expansion of these mosquito vectors underscore the urgent need for a coordinated response to prevent future ZIKV outbreaks and limit viral spread.

ZIKV is a positive-sense single-stranded RNA virus with a genome of ~10.7 kb. It contains a single long open reading frame encoding a polyprotein (5'-C-prM-E-NS1-NS2A-NS2B-NS3-NS4A-NS4B-NS5-3'), flanked by non-coding regions (5'- and 3'-UTRs). This polyprotein is processed into three structural proteins, capsid (C), precursor of membrane (prM), and envelope (E), and seven non-structural (NS) proteins(3). Upon entry into target cells, ZIKV strictly depends on the host's translational machinery for the early synthesis of ZIKV NS proteins required for replication and, subsequently, for the production of new viral progeny(4). In this process, tRNAs are key effector molecules bridging the genetic code and amino acid identity. Since the genetic code is highly degenerate, the usage of synonymous codons, referred to as codon usage bias (CUB), can greatly differ between cell types or organisms. This bias is echoed by the composition and abundance of the cellular tRNA pool. Many viruses, including RNA viruses, display a codon bias incompatible with the tRNA pool of their host cells, posing a potential barrier to efficient viral protein synthesis and consequently to their propagation(5, 6). To overcome this major obstacle, viruses may either adapt their codon usage to match that of their hosts(7, 8) or remodel the host tRNA pool to favor their own codon preferences(9–11).

The spectacular emergence of Asian-genotype ZIKV strains during recent outbreaks may at least in part rely on the evolutionary optimization of this vital translation step aimed at optimizing viral translation both in their human host and mosquito vector(12). Nevertheless, analysis of codon-based evolution using eleven ZIKV strains from different geographical locations has revealed only a modest overall codon usage bias, with a consistent preference for A/U-ending codons(13, 14), which contrasts with the human genome's preference toward C/G-ending codons(15). This mismatch poses a potential challenge for efficient viral translation, especially when host tRNAs corresponding to these preferred viral codons are underrepresented or lack necessary modifications. Since the efficient decoding of 11 out of the 14 A-ending codons used in humans require post-transcriptional modifications (PTMs) at the wobble U34 position of the cognate tRNAs(16) (Figure 1A), the proper modification of these U34-tRNAs by the adequate cellular enzymatic machinery may be an important factor influencing the efficiency of ZIKV genome translation in human cells.

This machinery (Figure 1B) involves the coordinated activities of the conserved six-subunit acetyltransferase Elongator protein (ELP) complex, the methyltransferase ALKBH8 and the thiouridylase complex CTU1–CTU2. Together with the ubiquitin-related modifier (URM) pathway(17–19), these enzymes catalyze the addition of 5-carbamoylmethyl- (ncm⁵), 5-methoxycarbonylmethyl (mcm⁵), a 2-thiol (s²), or both (mcm⁵s²) at the wobble U34 position of
tRNAs. These PTMs are critical to enhance codon recognition and decoding efficiency, thereby enabling efficient translation of A-ending codons that otherwise impose suboptimal codon-anticodon interactions(20). It is typically the case for codons encoding lysine (AAA/G), glutamine (CAA/G), and glutamic acid (GAA/G), each encoded by two synonymous codons ending in either AA or AG but decoded by a single tRNA species with a U at the wobble position (U₃₄) (tKUU for lysine, tQUUG for glutamine, tEUC for glutamic acid). While these tRNAs can recognize both the AA- and AG-ending versions of these codons, efficient decoding of the AA-ending triplet strictly requires the presence of the mcm⁵s² modification at U₃₄(21, 22). Any disparity between ZIKV codon usage and the composition or modification state of the host tRNA pool, particularly inadequate levels of U₃₄ modifications, could result in stalled translation, mistranslation, and proteotoxic stress, which would ultimately be detrimental to the virus replication. Idiosyncratic recognition of other U₃₄-sensitive AA-ending codons, including Arg (AGA/G), Ser (UCA/G) or Pro (CCA/G), by their cognate tRNAs (tRUCU and tSUGA or tPUGG, respectively), also requires proper U₃₄ modification to establish stable contact with their cognate A-ending codons(23). In the absence of these modifications, the tRNAs cannot efficiently induce the expected conformational changes in the small ribosomal subunit (SSU), disrupting translation elongation, protein synthesis and potentially hindering viral propagation(24).

In this study, we investigated whether ZIKV manipulates the host's tRNA modification machinery to optimize the translation of its A-ending codon-biased genome. We first reassessed codon usage patterns across different ZIKV genotypes (African and Asian) and compared them with those in the human host, paying particular attention to codons recognized by U34-modified cognate tRNAs. This analysis suggests that optimal ZIKV translation in human cells requires adjustments of the host tRNA pool, either through the upregulation of U34-containing tRNAs or through increased U34 modification within U34-containing tRNA subtypes. To functionally assess this hypothesis, we employed codon-biased eGFP reporter constructs and demonstrated that ZIKV infection transiently enhanced the expression of an AA-biased GFP construct relative to an AG-biased counterpart. Consistently, mass spectrometry analysis of modifications in the small RNA fraction of ZIKV-infected cells confirmed an increased abundance of mcm⁵s²U34 modification. The absolute necessity for ZIKV to optimize decoding of its A-ending codon-biased genome through U34 modification of host tRNA pool was clearly demonstrated in ELP1-deficient human primary cells. Here, the intrinsic hypomethylation of U34-tRNAs significantly impaired ZIKV translation and spread. Strikingly, treatment with RECTAS (RECTifier of Aberrant Splicing), a small molecule which restores ELP1 expression and normalizes U34 tRNA modification levels in ELP1-deficient human primary cells, rescued the cell's permissiveness to ZIKV infection. Concurrently, targeted disruption of each of the three key enzymes in U34 modification, ELP1, ALKBH8 and CTU1, using CRISPR/Cas9 and shRNA approaches, further underscored the virus's strong dependency on a properly modified tRNA pool for efficient translation. Collectively, these findings highlight the essential role of U34 modification containing tRNAs in the efficient decoding of ZIKV's codon-biased genome and establish a direct functional link between the host tRNA epitranscriptomic regulation and viral replication efficiency.
<figure><img src="image_2.png" /><figcaption>**Figure 1.** U34 tRNA modifications required for decoding AA-ending, U34-sensitive codons for Lys, Gln, Glu and Arg. (A) Modifications at the wobble uridine (U34) position of tRNA molecules are highlighted with colored boxes corresponding to each modification. Modifications occurring outside U34 are boxed in grey. (B) Enzymatic pathway responsible for U34 tRNA modifications. A subsequent hydroxylation of mcm⁵U by the oxygenase activity of ALKBH8 can generate mchm⁵U R/S-diastereoisomers found on tG⁵UC and tR⁵UC. Note that tR⁵UC can carry either mcm⁵U or mcm⁵s²U modification.</figcaption></figure>

# Results

## ZIKV genome is heavily biased toward A-ending codons

To assess the extent of codon usage bias (CUB) in ZIKV genomes, we performed a comprehensive bioinformatic analysis, including calculations of the Codon Adaptation Index (CAI) and Relative Synonymous Codon Usage (RSCU). These analyses suggest that ZIKV translation efficiency in host cells may be significantly influenced by the availability of compatible tRNAs (Figure 2). Global CAI analysis revealed that none of the ZIKV genomes examined, including the ancestral African strain MR766 and the Asian strains PR15, BeH8, PF13 or SPH15, are fully adapted the human host codon preference, with CAIs between 0.755 and 0.759 (Figure 2A and Supplementary Material Table 1). For comparison, highly expressed human genes with protein abundances exceeding 10,000 ppm, such as β-globin, β-myosin or β-tubulin, exhibit higher CAI values (0.869, 0.882, and 0.819 respectively) (Supplementary Material Table 2). In contrast, poorly expressed human genes, such as RHA, RIG-I or Kallmann Syndrome protein, with protein abundances below 300 ppm, show lower CAI values (0.748, 0.765 and 0.778, respectively). For further analysis, we selected the Asian strain PF13 as a representative prototype due to its phylogenetic clustering with other Asian strains (SPH15, PR15, BeH8), which contrasts with the
more divergent African MR766 strain (Figure 2A, right). By mapping CAI scores across the PF13 genome using *Homo sapiens* codon usage as a reference, we observed a non-uniform distribution of translational adaptation (Figure 2B). Several stretches in the ZIKV genome are characterized by poorly adapted codons, resulting in CAI values between 0.5 and 0.6, potentially representing translational bottlenecks in the host.

<figure><img src="image_3.png" /><figcaption>**Figure 2.** Codon usage and preferences of ZIKV. (A) Global Codon Adaptation Index (CAI) values for various ZIKV strains compared to *Homo sapiens* reference codon usage alongside a phylogenetic analysis showing the divergence between African and Asian ZIKV strains (scale: genetic distance). (B) CAI profile plotted along of the genome of the ZIKV PF13 strain (Asian genotype isolate from French Polynesia 2013) relative to *H. sapiens* reference codon usage preference. (C) Comparative analysis of Relative Synonymous Codon Usage (RSCU) values for ZIKV strains MR766 and PF13, and for *H. sapiens*. Codons are ordered according to their RSCU values for the PF13 strain. (D) Hierarchical clustering of normalized RSCU values across different ZIKV genotypes compared to human ORFs. Agglomeration was performed using the average linkage method (WPGMA: weighted pair group method with averaging). (E) Principal component analysis (PCA) of RSCU values derived from coding sequences of various ZIKV genotypes compared to *H. sapiens*. (F) Codon frequency differences between ZIKV PF13 and *H. sapiens*, ranked from human-preferred (left) to ZIKV-preferred codons (right). U₃₄-sensitive codons are highlighted with their corresponding U₃₄ modifications.</figcaption></figure>

RSCU analysis further confirmed a mismatch between ZIKV PF13 codon usage and the codon preference of *H. sapiens* (Figure 2C). Codons highly enriched in ZIKV are infrequently utilized in the human genome. Hierarchical clustering based on RSCU values revealed a striking preference for A-ending codons in the ZIKV genome, while the human genome favors G-ending codons (Figure 2D). Given that many of these ZIKV-enriched A-ending codons necessitate proper U₃₄ modifications for effective decoding (termed U₃₄-sensitive codons), ZIKV may potentially manipulate host tRNA U₃₄ modification pathways to overcome its suboptimal codon usage. To confirm these patterns, we performed principal component analysis (PCA) on the RSCU dataset (Figure 2E). The first and second principal components explained 63.3 % and 34.5 % of total variation, respectively. The plot clearly segregates Asian ZIKV strains from human codon usage, underscoring their distinct CUB profiles. Notably, while the ancestral African genotype MR766 is distinct from both the ZIKV Asian genotypes and the human genome, it also shows a light enrichment in U₃₄-sensitive codons (Figure 2D).
Finally, we visualized the codon usage differences between the ZIKV PF13 genome and the human genome by plotting codon frequency differences (Figure 2F). This analysis shows that the viral genome is heavily biased toward A-ending codons, whereas the human genome is biased towards C- and G-ending codons. Collectively, these findings suggest that optimal translation of ZIKV proteins in human cells may require a profound reprogramming of the host tRNA pool, particularly targeting tRNAs that require U34 modification, to accommodate the virus's highly skewed codon usage.

## ZIKV infection enhances translation of A-ending codons

To experimentally assess whether ZIKV infection enhances the translation of A-ending codons, we took advantage of two engineered eGFP reporter constructs with opposing codon bias for the three amino acids that require mcm⁵s²U₃₄ modification on their respective tRNAs for efficient decoding of AA-ending codons. The AG-biased eGFP (GFP-AG) corresponds to the human-optimized eGFP sequence in which 42 out of 44 codons for Lys, Gln or Glu, are AG-ending, reflecting the codon usage of highly translated human genes. Conversely, the AA-biased GFP (GFP-AA) construct is a fully synthetic variant in which all such codons have been changed to their AA-ending counterparts (Figure 3A), thereby mimicking the codon preference observed in the ZIKV genome (a sequence alignment of both GFP constructs is provided in Supplementary Material Figure S5). Both GFP sensors were delivered by lentiviral vectors in ZIKV-permissive HeLa cells pre-infected with BeH8-mCherry, a modified ZIKV strain engineered to express the mCherry marker, allowing identification of infected cells. GFP expression was monitored at different time points after transduction (Figure 3B) using both fluorescence microscopy and flow cytometry to evaluate their relative translation efficiency under ZIKV infection.

<figure><img src="image_4.png" /><figcaption>**Figure 3.** Expression of codon-biased GFP reporter constructs in ZIKV-infected cells. (A) Distribution of Lys, Gln and Glu codons in the GFP-AG (human-optimized AG-biased) and the GFP-AA (ZIKV-mimicking AA-biased) sensors. (B) Schematic representation of the experimental workflow: HeLa cells were infected with ZIKV (MOI=0.5) followed by transduction with virus-like particles encoding either GFP-AA or GFP-AG sensors. (C) Representative fluorescence microscopy images of non-infected (NI) and ZIKV-infected cells 72 h post-transduction, expressing either AA- or AG-biased GFP constructs. GFP signal intensity in ZIKV infected cells was quantified exclusively in mCherry-positive cells and expressed as gray values per square pixel. Error bars denote SEM; scale bar: 5 µm. (D) Representative dot plots from flow cytometry analysis of ZIKV-infected HeLa cells expressing GFP-AA or GFP-AG sensors at 72 h post-transduction (10,000 cells per analysis, n=4). Mean GFP intensities [GFP-Area (total fluorescence per cell) and GFP-</figcaption></figure>
Height (maximum fluorescence intensity per cell)] were recorded for non-infected (quadrant Q2-4) and ZIKV-infected (quadrant Q2-2) samples. The histogram (right) displays the ratio of GFP-AA/GFP-AG intensities (n=4). (E) Quantification of GFP mean relative fluorescence units (RFU) in non-infected (quadrant Q2-4) and ZIKV-infected (quadrant Q2-2) samples. (F) Ratio of GFP-AA/GFP-AG mean fluorescence intensity per ZIKV-infected cell, normalized to corresponding values of non-infected (NI) control cells (quadrant Q2-4).

Immunofluorescence analysis performed 72 h after transduction with the codon-biased GFP sensors revealed a striking shift in translational efficiency upon ZIKV infection, with a marked increase in GFP-AA expression and a concomitant reduction in GFP-AG expression (Figure 3C). Quantification of mean fluorescence intensity per square pixel confirmed that in non-infected cells, GFP-AG was translated more efficiently than GFP-AA, consistent with the codon preferences of human cells. In contrast, ZIKV-infected cells displayed the opposite pattern, with GFP-AA expression surpassing that of GFP-AG. This shift was further validated by flow cytometry analysis of ZIKV-infected mCherry⁺ cells (Figure 3D). At early time points post-transduction, we observed a transient increase in the GFP-AA/GFP-AG expression ratio, indicating a preferential translation of AA-ending codons. This effect gradually diminished over time, with the AA/AG-ratio returning to baseline levels (Figure 3D and 3F). Despite this normalization, the global translational capacity remained suppressed in ZIKV-infected cells, as reflected by the total GFP signal (Figure 3E). These findings suggest that ZIKV infection transiently reshapes host codon decoding preferences to favor translation of AA-ending codons for Lys, Gln, Glu, while reducing translation of AG-ending codons.

## Dynamic variation of tRNA modifications in ZIKV-infected cells

Given the enhanced translation of the GFP-AA sensor observed during ZIKV infection, likely dependent on the host cell's ability to decode AA-ending codons through specific tRNA modifications, we investigated the dynamic changes in tRNA post-transcriptional modifications (PTMs) in ZIKV-infected brain cells. These cells, known to be highly permissive to ZIKV, offer a physiologically relevant model for studying neurotropic virus-host interactions. We infected two types of human brain-resident cells: the neuroblastoma SH-SY5Y cell line, and primary astrocytes. Following infection, we confirmed viral replication by RT-qPCR (Supplementary Figure S1). Total RNA was extracted and fractionated to isolate small RNA species, in which tRNA represent over 75 % (Supplementary Figure S2). This approach enabled the identification of 28 distinct tRNA modifications in samples from mock-infected astrocytes (Figure 4A).
<figure><img src="image_5.png" /><figcaption>**Figure 4.** Dynamic variation of tRNA modifications in ZIKV-infected cells. (A) Profiles of 28 RNA PTMs obtained from small RNA fraction prepared from mock-infected human primary astrocytes. Identified PTMs are expressed as % of total unmodified ribonucleosides (rNs). U34 modifications are color-coded according to their chemical groups as in Figure 1, including: 5-methoxycarmonylmethyluridine (mcm⁵U), 5-methoxycarmonylmethyl-2-thiouridine (mcm⁵s²U), 5-carboxyhydroxymethyluridine methyl ester (R or S mchm⁵U) and 5-carbamoylmethyluridine (ncm⁵U). (B) Hierarchical clustering of 19 PTMs showing significant changes in ZIKV-infected SH-SY5Y human neuroblastoma cells and primary astrocytes (MOI = 10), expressed as row Z-scores. Colors reflect variations of abundance relative to mock-infected controls (*P* < 0.05). U34-related modifications are boxed in purple. (C), time-course analysis of fold-change variations in U34 modifications relative to mock-infected controls (NI) in ZIKV-infected human primary astrocytes and SH-SY5Y cells (MOI = 10).</figcaption></figure>

We then investigated how ZIKV infection altered the levels of individual PTMs. Analysis of tRNA-enriched RNA from ZIKV-infected astrocytes and SH-SY5Y cells revealed significant alterations in several PTMs, especially those located at the U34 position of tRNAs. Among these, the modifications mcm⁵s² and mcm⁵ were particularly affected (Figure 4B). A more detailed temporal analysis revealed that most U34-related PTMs were transiently upregulated in the early stages of infection, with a particularly acute increase in mcm⁵s²U and, to a lower extent, ncm⁵U (Figure 4C). This early spike in mcm⁵s²U levels was followed by a progressive decline in the levels of this tRNA mark, mirroring the temporal dynamics of GFP-AA translation enhancement observed during ZIKV infection (Figure 3).
ZIKV infection efficiency depends on the functional integrity of the U34-tRNA modification pathway

In mammals, the enzymes responsible for catalyzing chemical U34 modification include the Elongator complex (ELP1–6), the tRNA methyltransferase ALKBH8 and the thiouridylases CTU1/CTU2(25). If ZIKV translation indeed depends on the presence of the mcm5s2U modification at U34, then efficient viral replication should require a fully functional Elongator complex. To test this hypothesis, we used primary fibroblasts derived from patients with Familial Dysautonomia (FD), a genetic disorder characterized by loss-of-function mutations in *ELP1* (also known as IKBKAP)(26), resulting in reduced levels of mcm5s2U tRNA(27). In FD fibroblasts, we observed markedly reduced levels of ZIKV translation and infection compared to control fibroblasts (WT) derived from healthy individuals, as indicated by the diminished expression of the virus-encoded mCherry reporter (Figure 5A). Although fibroblasts are poorly infected by ZIKV (typically 1-5 % infected cells), quantification of mCherry-positive cells nonetheless serves as a useful proxy for viral translation efficiency. Strikingly, the proportion of mCherry-expressing cells was drastically reduced in ELP1-deficient FD fibroblasts relative to controls, strongly suggesting that Elongator-mediated U34 modifications are critical for efficient ZIKV translation (Figure 5B). This phenotype was also observed, though to a lesser extent, across a range of lower MOIs (0.1, 0.5 and 1.0) (Figure 5C), where infection levels were monitored by measuring ZIKV RNA copy number using RT-qPCR, normalized against GAPDH. By monitoring mCherry fluorescence intensities 48 h and 72 h after ZIKV infection at high MOI (20), we observed a strong and consistent reduction in reporter signals in FD cells compared to WT cells (Figure 5D). Given that mCherry fluorescence intensities correlate with ZIKV translation levels, these results strongly support a model in which the absence of functional Elongator-mediated U34 modifications disrupts viral protein synthesis. Two independent experiments conducted at MOIs of 10 and 20 with recording fluorescence intensities at 48 h and 72 h post-infection yielded identical results (Supplementary Figure S4), further reaffirming the crucial role of the Elongator complex and Elongator-mediated U34 tRNA modifications in facilitating efficient ZIKV infection *in vitro*.

<figure><img src="image_6.png" /><figcaption>**Figure 5.** Impaired ZIKV infection in FD fibroblasts lacking U34 tRNA modifications can be reverted by RECTAS treatment. (A). Human primary fibroblasts derived from skin biopsies from either a healthy control (WT) or from a patient with Familial Dysautonomia (FD) were infected with ZIKV BeH8-mCherry at MOI of 1, 5 or 20. (B) 48 h post-infection, ZIKV replication was assessed by quantifying the number of mCherry-positive cells per 10⁴ cells using fluorescence</figcaption></figure>
microscopy. (C) ZIKV infection levels at low MOIs (0.1, 0.5 and 1.0) were quantified by RTqPCR 48 h post-infection. (D) mCherry fluorescence intensities were visualized by fluorescence microscopy. Fluorescence intensities per square pixel were quantified with ImageJ in non-FD (WT) and FD fibroblasts at 48 h and 72 h post-infection (hpi) at MOI of 20. Results are presented as box-plots where *n* corresponds to the number of cells analyzed. (E) Experimental workflow outlining the use of RECTAS, a small molecule previously shown to upregulate U34 modification pathways, for functional rescue experiments in FD fibroblasts. (F) U34 tRNA modification levels in FD cells following 72 h RECTAS treatment (0.2 µM and 1.0 µM) compared to untreated FD cells and WT controls. (G and H), ZIKV infection efficiency in RECTAS-treated WT and FD fibroblasts infected at MOIs of 0.5, 1.0 and 2.0. Viral RNA levels were determined by RTqPCR at 24 hpi (G) and 48 hpi (H) and normalized to GAPDH.

In parallel, we took advantage of the small molecule RECTAS, which is known to rescue ELP1 expression and normal $mcm^5s^2U_{34}$ levels(28) in cells from FD patients, to generate a cellular system with graded levels of U34-modified tRNAs. FD patients carry a common IVS20 + 6 T > C mutation in the *ELP1* gene that impairs proper recognition of the 5' splice site by U1 snRNP, resulting in exon 20 skipping, a frameshift, and a premature termination codon in exon 21. This defective splicing event markedly reduces ELP1 expression and impairs tRNA modification(29). RECTAS corrects this splicing defect, restoring normal ELP1 mRNA processing and expression. Functional U34 tRNA modifications are subsequently re-established, offering a potential therapeutic avenue for FD patients(30). To determine whether this correction could also restore ZIKV susceptibility, FD and WT fibroblasts were treated with 0.2 µM or 1.0 µM RECTAS for 72 h before ZIKV infection (Figure 5E). Mass spectrometry analysis confirmed that RECTAS treatment efficiently restored five U34 tRNA modifications in FD cells to levels comparable to those of WT cells (Figure 5F). Three days after treatment, cells were infected with ZIKV, and infection levels were monitored by RTqPCR-quantification of viral RNA at 24 h and 48 h post-infection. Notably, RECTAS treatment progressively restored ZIKV infection levels in FD fibroblasts, reaching levels similar to WT cells (Figure 5G and 5H). These results demonstrate that pharmacological restoration of U34 tRNA modifications reactivates ZIKV protein synthesis in FD cells, reinforcing the critical role of the Elongator-dependent tRNA modification pathway in facilitating efficient viral translation and replication.

## Inactivation of U34 tRNA modification enzymes via CRISPR/Cas9 and shRNA impairs ZIKV infection

To further validate the critical role of U34 tRNA modifications in ZIKV replication, we disrupted the activity of enzymes responsible for the stepwise biosynthesis of $mcm^5s^2U$-modified tRNAs. Using CRISPR/Cas9, we generated HeLa cells with individual knockouts of *ELP1*, *ALKBH8* and *CTU1*, each encoding a key enzyme in the stepwise formation of the $mcm^5s^2U$ modification (Figure 1B). After clonal selection, KO cells were challenged with ZIKV-mCherry (BeH8-strain) at a MOI of 0.5. The level of infection was then monitored by quantifying mCherry-positive cells between 4- and 26-days post-infection (dpi) (Figure 6A). At 4 dpi, the infection level in ELP1-KO cells was approximately 25 % lower than in the WT control. Over time, viral infection progressive cleared from the U34-KO cell population. By 26 dpi, only a few KO cells remained infected (Figure 6B). In contrast, control cells reached 100 % infection at 4 dpi, and succumbed to virus-induced cytotoxic effects between 8 and 15 dpi. Knockout efficiency was validated by Western blot analysis (Figure 6C). These data demonstrate that cells devoid of U34 tRNA-modifying enzymes are unable to support the full replication and sustained spread of ZIKV.

In parallel to CRISPR/Cas9, we also employed shRNAs-mediated knockdown to reduce the expression of ELP1, *ALKBH8* and *CTU1* in human A549 cells. Following lentiviral transduction of
shRNAs targeting each gene or a non-targeting irrelevant control (IRV1), and puromycin selection, cells were infected with ZIKV (MOI=0.5), and viral infection was quantified by RT-qPCR quantification. Knockdown of each enzyme in the three steps of U34 tRNA modifications (Figure 6E) resulted in substantial reduction of genomic RNA levels, confirming impaired replication (Figure 6D).

Together, the results from both gene inactivation consistently corroborate the essential role of mcm<sup>5</sup>s<sup>2</sup> writers in ZIKV replication. While full knockouts resulted in the progressive clearance of ZIKV infection, partial shRNA knockdowns led to a noticeable attenuation of the infection. Collectively, these complementary experiments provide strong evidence that mcm<sup>5</sup>s<sup>2</sup> modification of tRNAs is crucial for efficient ZIKV RNA translation and replication.

<figure><img src="image_7.png" /><figcaption>**Figure 6.** Disruption of the tRNA U34 modification pathway impairs ZIKV infection. (A) Representative time course images of ZIKV-infection (MOI = 0.5) in control HeLa cells (left) and ELP1-CRISPR/Cas9 KO cells. Infection was assessed by fluorescence microscopy based on mCherry reporter expression. (B) Quantification of ZIKV infection in controls and CRISPR/Cas9-edited HeLa clones lacking ELP1, ALKBH8 or CTU1. Measurements were conducted in triplicate. (C) Western blot validation of gene knockouts in CRISPR/Cas9-edited HeLa clones. (D) Puromycin-selected A549 cells stably expressing the indicated shRNAs were infected with ZIKV at MOI of 0.5. At 48 h post-infection, viral RNA levels were determined by RTqPCR using GAPDH as an internal control. A549 corresponds to ZIKV-infected cells without shRNAs. Data represent 6 independent experiments (n=6). (E) Western blot analysis of shRNA-treated A549 clones showing protein expression for the respective targeted genes.</figcaption></figure>

Discussion

Our findings identify a previously unrecognized mechanism by which ZIKV exploits host U34 tRNA modifications to overcome its codon usage bias, representing a novel layer of viral adaptation within the expanding field of epitranscriptomic regulation of virus-host interactions. Bioinformatic analysis indicate that ZIKV exhibits a strong preference for A-ending codons, which contrasts with the human host's preference for G-ending codons, confirming its poor adaptation of codon usage towards its host(31). Since the proper decoding of A-ending codons relies on specific modifications at the wobble position (U34) of the cognate tRNAs, we postulated that ZIKV manipulates host tRNA U34 modifications to compensate for its non-optimal codon usage, thereby enhancing translation efficiency. RSCU analysis further revealed codon usage differences between Asian strains and the historical African isolate MR766. While MR766 codon usage
remains distinct from the host preferences, its enrichment in U34-sensitive codons is less pronounced than that of Asian strains. Notably, MR766 is known to be more virulent, inducing lower innate and inflammatory activation(32) than Asian lineages, leading to more acute infections and more severe brain damages(33, 34). In light of the recent resurgence of MR766-related African strains in West Africa(35, 36), additional investigation is warranted to determine whether codon bias disparities influence the phenotypic characteristics of contemporary African strains(37, 38).

The use of codon-biased GFP sensors, designed to reflect either human or viral gene preferences, strongly indicated that ZIKV can manipulate the host translation machinery to promote its own protein synthesis. This was supported by analysis of tRNA epitranscriptome dynamics during ZIKV infection, which revealed a transient increase in the major U34 tRNA modification, mcm⁵s². The critical role of this modification was underscored by the severely impaired ZIKV translation observed in ELP1-deficient human fibroblasts, which are intrinsically unable to generate U34-modified tRNAs. Remarkably, treatment with RECTAS, a small molecule that restores U34 modifications, reversed this phenotype and significantly enhanced ZIKV translation when applied to infected cells. Furthermore, disruption of U34-modifying enzymes via CRISPR or shRNA approaches consistently impaired ZIKV replication, underscoring the critical requirement of the mcm⁵s²U modification machinery in viral translation. Building on the mechanistic insight provided by RECTAS, which promotes exon 20 inclusion in *ELP1* transcripts of FD cells(30, 39), a new therapeutic strategy involving the identification of derivative molecules capable of excluding exon 20 in wild-type ELP1 mRNA in normal cells can be conceptualized, as we recently exemplified in the context of SARS-CoV-2 infection through splice-switching of OAS1 isoforms(40). Exclusion of ELP1 exon 20 could reduce U34 tRNA modifications, thereby disrupting ZIKV translation and potentially curbing infection. However, a significant challenge remains in achieving antiviral efficacy without inducing host cell toxicity, as this strategy targets a mechanism used by both host and virus.

Viruses are highly dependent on the host cell's translation machinery, including host tRNAs, for efficient protein synthesis(5, 11, 41). Some viruses can alter tRNA abundance as part of their adaptive strategy(42), as described by us for SARS-CoV-2(43) and by others for retroviruses such as HIV(44) and DNA viruses, including SV40(45), EBV(46), Adenovirus(47), and HSV-1(48). In addition, viral translation is influenced by chemical modifications of tRNAs, particularly within the anticodon loop region, catalyzed by a suite of tRNA-modifying enzymes(24, 49). Notably, we have already shown the ability of SARS-CoV-2's to directly alter the host tRNA epitranscriptome(50) by upregulating U34-modified tRNAs that can optimize the translation of its genome, which is enriched in U34-sensitive codons(43). A similar strategy has been proposed for other RNA viruses, including Chikungunya virus (CHIKV) and Dengue virus (DENV), though direct experimental validation remains limited(15, 51-53). Our findings now extend this concept to ZIKV and our functional analyses provide some of the most direct evidence to date of this mechanism in action.

While a universal mechanism used by different RNA viruses to exploit U34 modifications for their benefit has not been identified, recent studies have demonstrated that infection by the Alphavirus CHIKV upregulates the expression of KIAA1456, an ALKBH8 homolog responsible for generating the mcm⁵U34 modification of tRNAs. This enhancement results in reprogramming codon optimality and favors CHIKV RNA translation(51). DENV exploits host tRNA through a different mechanism by manipulating the levels of ALKBH1, which introduces 2'-O-methyl-5-formylcytidine (f⁵Cm)-modification at the wobble position C34 of cytoplasmic tRNA-Leu(CAA), promoting viral
translational remodeling during DENV infection(52). For ZIKV, the observed enhancement of mcm<sup>5</sup>s<sup>2</sup>U34 tRNA modifications during infection may potentially be linked to PI3K-Akt-mTORC2 signaling. This pathway is known to reprogram the translation of genes enriched in U34-sensitive codons in cancer cells by phosphorylating the ELP1 subunit of the Elongator complex at Ser1174, thereby increasing mcm<sup>5</sup>s<sup>2</sup>U34 tRNA modifications(54, 55). Interestingly, ZIKV NS4A/NS4B viral proteins have been implicated in deregulating the Akt-mTOR pathway(56), suggesting a plausible molecular connection to tRNA reprogramming during infection. This finding provides a compelling avenue for future investigations.

Finally, whether ZIKV-mediated U34 alterations impact the host cell metabolism is also an open question. ZIKV infection is strongly associated with microcephaly in infants born to infected mothers, as well as Guillain-Barré Syndrome (GBS) in adults, cognitive disability, and symptoms of autonomic dysfunction(57). In this study we focused on brain-resident cells such as astrocytes, the most abundant neuronal cells targeted by ZIKV(58). The ZIKV-driven enhancement of the translation of genes enriched in A-ending codons at the expense of genes preferring G-ending codons, may profoundly alter the cellular proteome integrity(59). Indeed, among disease-relevant modifications affecting cytoplasmic tRNA species, neurological disorders including Familial Dysautonomia (FD)(27, 60) and epilepsy, appear to be most common. Specifically, mutations impairing m<sup>5</sup>C, mcm<sup>5</sup>U, mcm<sup>5</sup>s<sup>2</sup>U, ncm<sup>5</sup>U, pseudouridine (Ψ), m<sup>1</sup>G, inosine (I)(61) and m<sup>2</sup>₂G(50, 62) tRNA modifications are all associated with intellectual disability and neurodevelopmental disorders, suggesting normal brain function and development to be particularly dependent on the presence of these modifications(19). In many aspects, the neurological consequences of ZIKV infection, that are still barely understood, might be prospectively phenocopying (to a certain extent) alterations related to U34 enzymes and tRNA modifications.

In conclusion, our findings place ZIKV within a growing group of RNA viruses that modulate host tRNA modifications as a strategy to facilitate viral protein synthesis. The virus's reliance on the mcm<sup>5</sup>s<sup>2</sup>U34 modification pathway highlights a critical vulnerability that may be therapeutically exploitable, albeit with caution due to the essential nature of these modifications in host physiology.

# Material and Methods

## Viruses and cells

PF13, and MR766 ZIKV molecular clones were obtained from Mathew Evans(63). BeH8 (mCherry reporter) ZIKV replicon(64) was a generous gift of Andres Merits (University of Tartu, Estonia). Virus production and titration were performed in VeroE6 cells. HeLa, A549, HEK293T, VeroE6, SH-SY5Y cells and human primary astrocytes (obtained from ScienCell) were cultured in DMEM Glutamax medium (GIBCO) supplemented with Penicillin/Streptomycin and 5 % fetal calf serum. Patient primary fibroblasts were from Coriell Institute: GMO1652 was derived from non-FD control [Skin fibroblast (arm) from 11 years old Caucasian female]; GMO4959 derived from FD patient [Skin fibroblast (arm) from 10 years old Caucasian female]. ZIKV strains are displayed in Supplementary Table 1. Infections were done at the indicated MOIs and checked routinely by RTqPCR as outlined in Supplementary Figure S1.
## Plasmid and vectors

GFP-sensor constructs (GFP-AG and GFP-AA) were generated in plenti-PGK with Puro® (Vigene Biosciences, Charles River, USA). Corresponding VSV-G pseudo-typed virus-like-particles were produced in HEK293T cells as previously described(65).

## Reagents and antibodies

RECTAS was produced as previously described(28, 30) and diluted in DMSO to treat cells at the required concentration. Anti-ELP1 rabbit polyclonal antibody (#A10127) was from ABclonal. Anti-ALKBH8 rabbit polyclonal antibody (#OACA06811) was from AvivaSysBio. Anti-CTU1 rabbit polyclonal antibody (#9663252) was from Affinity Biosciences. HRP-conjugated Goat-anti-Rabbit antiserum was from Pierce (Thermo Fischer). HRP-conjugated anti-actin was from Sigma-Aldrich.

## Codon analysis

Codon adaptation index (CAI) and Relative Synonymous Codon Usage (RSCU) calculations were done using CAIcal tools (http://genomes.urv.es/CAIcal) (66) as previously described (43). Codon frequencies were calculated with Codon Utilization Tool (CUT) website (http://pare.sunycnse.com/cut/index.jsp) (67). Relative synonymous codon usage (RSCU) is defined as the ratio of the observed frequency of codons to the expected frequency given that all the synonymous codons for the same amino acids are used equally. The codon adaptation index (CAI) was used to estimate the extent of bias towards codons that were known to be preferred in highly expressed genes for the given host organism. Cluster analyses were done using Genesis 1.8.1(68) and Cluster 3.0(69) and visualization were made with Java Treeview(70). Principal component analysis (PCA) was performed using ClustVis(71) v.2.0 (https://biit.cs.ut.ee/clustvis/) and R programming language (version 4.3.3). CAIs of selected human genes was calculated as above. Corresponding protein abundances were derived from PaxDb database version 4.1 (https://pax-db.org/) (72). Values are given in Supplementary Table 2. Phylogenic tree was generated using EMBL-EBI online "Simple phylogeny" tool (73) (https://ebi.ac.uk/jdispatcher/phylogeny/) with the virus sequences displayed in Supplementary Material Table I, previously aligned with T-Coffee algorithm (74) (https://ebi.ac.uk/jdispatcher/msa/tcoffee).

## Flow cytometry and fluorescence microscopy

Flow cytometry was performed on LSR FORTESSA (Becton Dickinson) and NOVOCYTE ACEA (Agilent) flow cytometers (MRI platform, CNRS Montpellier) using 96 well microplates containing 20,000 cells. Analysis were performed on 10,000 events in quadruplicates. Fluorescence microscopy images were acquired on a Zeiss AxioImager Z2 microscope (MRI platform) and analyzed on ImageJ(75).

## Quantification of tRNA Modifications by Mass Spectrometry (LC-MS/MS)

RNA preparations enriched in tRNAs were obtained using mirVana™ miRNA Isolation Kit (Thermo Fischer). Fractionation accuracy was checked by capillary electrophoresis on a LabChip GX II (Caliper Life Sciences, Hopkinton, USA) (Supplementary Figure S2). RNA samples were then digested by benzonase, nuclease P1, phosphodiesterase I and alkaline phosphatase prior to acetonitrile precipitation, vacuum concentration and LC-MS/MS analysis. The nucleosides were separated by reverse phase ultra-performance liquid chromatography on a C18 column with online detection using an Agilent 6495 Triple Quadrupole LC mass spectrometer in multiple
reactions monitoring (MRM) positive electrospray ionization (ESI) mode and quantified as previously described(76).

## Gene disruption by CRISPR-Cas9 and shRNA

The plasmids for CRISPR-Cas9 were obtained from the Montpellier Genomic Collection Platform (Biocampus, Montpellier, France). Guide RNA targeting U34-related genes were designed using three online gRNA-optimizing softwares: CRISPR design (http://crispr.mit.edu.insb.bib.cnrs.fr), CRISPR RNA Configurator (http://dharmacon.gelifesciences.com/gene-editing/edit-r/custom-crrna), and CRISPR gRNA Design tool (https://www.dna20.com/eCommerce/cas9). Guides used in this study are presented in Table I. Guides were cloned into pUC57 attB U6 gRNA vectors(77). The generated plasmid pUC57 attB U6 gRNA was transfected into HeLa cells with Lipofectamine 2000, along with the pSpCas9(BB)-2A-GFP (PX458) plasmid(78). At 6 h after transfection, the cells were trypsin treated and resuspended in complete DMEM medium at 2 × 10⁴ cells per ml. Portions (200 µl) of the cell suspension (4 × 10³ cells) were used to inoculate 96-well plates and to isolate single cell-derived clones by serial dilution. Isolated green fluorescent protein (GFP)-positive clones were amplified and analyzed by Western blotting to check target gene expression. ShRNAs were Mission shRNAs from SIGMA cloned into pIKO.1-puro presented in Table II. Corresponding VSV-G pseudo-typed virus-like-particles were produced in HEK293T cells as previously described(65) and used to transduce A549 cells. Individual clones were isolated after puromycin selection and analyzed by Western blotting to check target gene expression.

## Assays for Viral Replication

Cells were lysed with the Luna cell-ready lysis module (New England Biolabs). The amplification reaction was run on a Lightcycler R 480 thermocycler (Roche Diagnostics) using the Luna Universal One-Step RT-qPCR kit (New England Biolabs), and ZIKV For: 5'-AGGATCATAGGTGATGAAGAAAAGT (hybridizes at the end of NS5 sequence); ZIKV Rev: 5'-CCTGACAACATTAAGATTGGTGC (hybridizes in the 3'UTR region); GAPDH For: 5'-GCTCACCGGCATGGCCTTTCGCGT and GAPDH Rev: 5'-TGGAGGAGTGGGTGTCGCTGTTGA primers. Each qPCR was performed in triplicate, and the means and standard deviations were calculated. Relative quantification of data obtained from RT-qPCR was used to determine changes in ZIKV gene expression across multiple samples after normalization to the internal reference GAPDH gene. GAPDH and ZIKV amplicons are respectively 200 bp and 116 bp in length.

<table><caption>Table I - CRISPR/Cas9 guides targeting U34 enzyme genes</caption><thead><tr><td>Gene name</td><td>NCBI geneID</td><td>Target Site_with_PAM</td><td>HeLa CRISPR Clone name</td></tr></thead><tbody><tr><td>ELP1</td><td>8518</td><td>GACTGTTGGAACTATCACTGG</td><td>ELP1 1c</td></tr><tr><td>ALKBH8</td><td>91801</td><td>CTCTAAAACCGGGAGCAGCTGG</td><td>ALK8 1c</td></tr><tr><td>CTU1</td><td>90353</td><td>GAGGCCGAGGTGCTGCACACGG</td><td>CTU1 09c</td></tr></tbody></table>

<table><caption>Table II - shRNAs targeting U34 enzyme genes</caption><thead><tr><td>Target Gene</td><td>NCBI gene ID</td><td>Target location</td><td>Sequence</td><td>VLP name</td></tr></thead><tbody><tr><td>ELP1</td><td>8518</td><td>exon 29</td><td>CCGGGCTGTGCTCTTGCTGTTAGAACTCGAGTTCTAACAGCAAGAGCACAGCTTTTTG</td><td>E1-3</td></tr><tr><td>ALKBH8</td><td>91801</td><td>exon 12</td><td>CCGGCAGGTGGGAAGGCACTCATTCTCGAGAAATGAGTGCCTTCCCACCTGTTTTTG</td><td>A8-8</td></tr><tr><td>CTU1</td><td>90353</td><td>exon 3</td><td>CCGGCTTCTCCGAGGAGTGCGTCTACTCGAGTAGACGCACTCCTCGGAGAAGTTTTTG</td><td>C1-1</td></tr><tr><td>none</td><td>NA</td><td>non target</td><td>CCGGGCGCGATAGCGCTAATAATTTCTCGAGAAATTAGCGCTATCGCGCTTTTT</td><td>IRV1</td></tr></tbody></table>
## Acknowledgements

This work was initially facilitated by a Hubert Curien exchange program from Campus France (PHC Aurora 2018 - EpiArbo N°40969YB) between PE and GS. PROMEC is a member of the National Network of Advanced Proteomics Infrastructure (NAPI), which is funded by the RCN INFRASTRUKTUR-program (295910). The Human Primary Astrocytes used in this study were kindly provided by Dr. Sara Salinas (INSERM, Montpellier, France), to whom we express our sincere gratitude.

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SUPPLEMENTARY MATERIAL

**Supplementary Material Table 1**

Origins of the ZIKV strains<sup>a</sup>

<table><thead><tr><th>Strain</th><th>GenBank ID</th><th>GI</th><th>Subtype/Genotype</th><th>Collection Date</th><th>Host</th><th>Country</th><th># Codons</th></tr></thead><tbody><tr><td>BeH819015</td><td>KU365778</td><td>975885996</td><td>Asian</td><td>2015</td><td>Human</td><td>Brazil</td><td>3424</td></tr><tr><td>MR766</td><td>MK105975</td><td>1511212707</td><td>East African</td><td>2016</td><td>Monkey</td><td>Uganda</td><td>3420</td></tr><tr><td>PF13</td><td>KY766069</td><td>1168020439</td><td>Asian</td><td>2013</td><td>Human</td><td>French polynesia</td><td>3424</td></tr><tr><td>PRVABC59</td><td>MH158237</td><td>1386872121</td><td>Asian</td><td>2015</td><td>Human</td><td>Puerto Rico</td><td>3424</td></tr><tr><td>ZikaSPH2015</td><td>KU321639</td><td>969945756</td><td>Asian</td><td>2015</td><td>Human</td><td>Brazil</td><td>3424</td></tr></tbody></table>

**Supplementary Material Table 2**

CAI and abundance of human ORFs

<table><thead><tr><th>Human ORFs</th><th>https://pax-db.org/</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr><tr><th>Name</th><th>Protein ID</th><th># Codons</th><th>CAI Homo sapiens</th><th>CAI Aedes aegypti</th><th>% G+C</th><th>% G+C(1)</th><th>% G+C(2)</th><th>% G+C(3)</th><th>Nc</th><th>Protein abundance (ppm)</th></tr></thead><tbody><tr><td>HBG</td><td>Q29025</td><td>147</td><td>0.869</td><td>0.804</td><td>56.1</td><td>66.2</td><td>36.5</td><td>65.5</td><td>33.9</td><td>beta-globin</td><td>16296</td><td></td><td></td></tr><tr><td>HBM</td><td>P12883.5</td><td>1935</td><td>0.882</td><td>0.821</td><td>57.3</td><td>59.8</td><td>30.6</td><td>81.4</td><td>39.3</td><td>beta-myosin</td><td>13415</td><td></td><td></td></tr><tr><td>HBT</td><td>AAC52035</td><td>1305</td><td>0.819</td><td>0.772</td><td>58.2</td><td>57.2</td><td>42.1</td><td>75.2</td><td>44.4</td><td>beta-tubulin</td><td>10158</td><td></td><td></td></tr><tr><td>HBI</td><td>AAC41702</td><td>187</td><td>0.808</td><td>0.754</td><td>53.7</td><td>52.9</td><td>43.3</td><td>64.8</td><td>50.6</td><td>beta-interferon</td><td>12.3</td><td></td><td></td></tr><tr><td>DHX9</td><td>AAH25245</td><td>593</td><td>0.748</td><td>0.718</td><td>44.7</td><td>54.7</td><td>40.9</td><td>38.6</td><td>51.3</td><td>RHA</td><td>806</td><td></td><td></td></tr><tr><td>DDX58</td><td>AAL36611.1</td><td>925</td><td>0.765</td><td>0.716</td><td>40.6</td><td>48.2</td><td>32.6</td><td>41</td><td>51.4</td><td>RIG-I</td><td>130</td><td></td><td></td></tr><tr><td>KAL</td><td>NP_000207</td><td>680</td><td>0.778</td><td>0.749</td><td>52.5</td><td>54.5</td><td>46.3</td><td>56.8</td><td>53.6</td><td>Kallmann syndrome</td><td>1.54</td><td></td><td></td></tr></tbody></table>

**Supplementary Material Figure S1**

Infection levels of cells infected by ZIKV at MOI of 10 determined by RTqPCR

<figure><img src="image_8.png" /></figure>

<footnote><sup>a</sup> All data were obtained from ViPR (Virus Pathogen Resource) March of 2019 (https://www.viprbrc.org/brc/home.spg?decorator=vipr)</footnote>
## Supplementary Material Figure S2

Accuracy of RNA fractionation of tRNA and rRNA from total cellular RNA preparations. Analysis were performed by capillary electrophoresis using Caliper Life Sciences GX II.

<figure><img src="image_9.png" /></figure>

## Supplementary Figure S3

Schematic representation of ZIKV BeH8-mCherry genomic sequence in which the mCherry coding region is followed by a "self-cleaving" 2A peptide is inserted between two tandem capsid (C) segments.

<figure><img src="image_10.png" /></figure>

## Supplementary Material Figure S4

As in Figure 5D. Two independent experiments of ZIKV infection of wt and FD human primary fibroblasts are presented. mCherry fluorescence intensities were visualized by fluorescence microscopy. Fluorescence intensities per square pixels were quantified with ImageJ in non-FD (wt) and FD fibroblasts at 48 and 72 hours post-infection (hpi) and presented as a box-plot diagram. *n* represents the number of cells in which fluorescence intensities were determined.

<figure><img src="image_11.png" /></figure>

* Gray value per square pixels
## Supplementary Material Figure S5

Sequence alignment of GFP-AG vs GFP-AA showing G to A transitions of the third base of Lys, Glu and Gln codons. Note that Glu91 and Lys210 codons were already AA-ending in GFP-AG (shown in red).

<figure><img src="image_12.png" /></figure>