Integrated re-analysis of transcriptomic and proteomic datasets reveals potential mechanisms for Zika viral-based oncolytic therapy in neuroblastoma

Background Paediatric neuroblastoma and brain tumours account for a third of all childhood cancer-related mortality. High-risk neuroblastoma is highly aggressive and survival is poor despite intensive multi-modal therapies with significant toxicity. Novel therapies are desperately needed. The Zika virus (ZIKV) can access the nervous system and there is growing interest in employing ZIKV as a potential therapy against paediatric nervous system tumours, including neuroblastoma. Methods Here, we perform extensive data mining, integration and re-analysis of ZIKV infection datasets to highlight molecular mechanisms that may govern the oncolytic response in neuroblastoma cells. We collate infection data of multiple neuroblastoma cell lines by different ZIKV strains from a body of published literature to inform the susceptibility of neuroblastoma to the ZIKV oncolytic response. Integrating published transcriptomics, interaction proteomics, dependency factor and compound datasets we propose the involvement of multiple host systems during ZIKV infection. Results Through data mining of published literature, we observed most paediatric neuroblastoma cell lines to be highly susceptible to ZIKV infection and propose the PRVABC59 ZIKV strain to be the most promising candidate for neuroblastoma oncolytic virotherapy. ZIKV induces TNF signalling, lipid metabolism, the Unfolded Protein Response (UPR), and downregulates cell cycle and DNA replication processes. ZIKV infection is dependent on sterol regulatory element binding protein (SREBP)-regulated lipid metabolism and three protein complexes; V-ATPase, ER Membrane Protein Complex (EMC) and mammalian translocon. We propose ZIKV non-structural protein 4B (NS4B) as a likely mediator of ZIKVs interaction with IRE1-mediated UPR, lipid metabolism and mammalian translocon. Conclusions Our work provides a significant understanding of ZIKV infection in neuroblastoma cells, which will facilitate the progression of ZIKV-based oncolytic virotherapy through pre-clinical research and clinical trials.

strains from a body of published literature to inform the susceptibility of neuroblastoma to the ZIKV oncolytic response.Integrating published transcriptomics, interaction proteomics, dependency factor and compound datasets we propose the involvement of multiple host systems during ZIKV infection.
Introduction Neuroblastoma is the most common extracranial solid cancer in children, accounting for 6-10% of all paediatric cancers and disproportionately causing 12-15% of paediatric cancer-related deaths. 1 It is an embryonal tumour originating from transformed cells of neural crest lineage and predominately forms tumours in the adrenal medulla and paraspinal sympathetic ganglia.Whilst the majority of patients are diagnosed by the age of 5 years, the median age of patients is 18 months.Prognosis is highly heterogenous and can be predicted by a number of factors, including the presence of metastatic disease, age, chromosomal aberrations and molecular signatures, such as MYC-N amplification. 2 Patients are categorised according to internationally agreed risk groups (INRG), and treatment is stratified accordingly.
Outcome for low-and intermediate-risk neuroblastoma is good, with some patients requiring little or no treatment.However, approximately 50% of patients have high-risk disease, for which prognosis is poor, with overall survival of less than 60%. 3 Current high-risk neuroblastoma treatment regimens are aggressive.These include multiple rounds of induction chemotherapy, surgical resection, myeloablative chemotherapy, autologous stem cell transplantation and post-consolidation therapy such as immunotherapy. 4The aggressive nature of this regimen carries significant treatmentrelated mortality and frequently results in long-term toxicities and sequelae impacting the quality of life for surviving patients.Consequently, there is a clear and unmet need for safer and less toxic treatment regimens to combat high-risk neuroblastoma.
Oncolytic virotherapy exploits viruses that preferentially infect and destroy cancer cells via two distinct routes of therapeutic action.Following infection, intense viral replication induces oncolysis, releasing virions into the tumour microenvironment to infect neighbouring tumour cells.Induction of a tumour-specific immune response is a crucial secondary mechanism employed by oncolytic virotherapy that can address highly heterogeneous tumours such as highrisk neuroblastoma and central nervous system (CNS) tumours.There is significant interest in combining immunomodulating cancer therapies with oncolytic virotherapy to augment the anti-tumoral immune response.Oncolytic virotherapy clinical studies have in general reported low toxicity and minimal adverse effects in patients, mainly lowgrade constitutional symptoms. 5ka virus (ZIKV) is a mosquito-borne flavivirus consisting of historical African and epidemic-associated Asian lineages.The latter can access the central nervous system and may cause microcephaly in the developing foetus through infection of neural stem and progenitor cells, causing cell death and growth reduction. 6,7By contrast, ZIKV rarely causes adverse effects in children and adults, with the majority of cases (50-80%) being asymptomatic. 8In symptomatic children, ZIKV may cause short-term side effects, namely rash, fever and gastrointestinal symptoms, and in rare instances in adults can cause more severe conditions, such as Guillain-Barré Syndrome, meningitis and encephalitis. 8,9VISED Amendments from Version 2 Corrected figures and edits made to improve clarity according to reviewer suggestions.
Any further responses from the reviewers can be found at the end of the article Since 2017, the concept of employing the ZIKV as oncolytic virotherapy against brain tumours has gained momentum.
1][12] An initial study assessing ZIKV infection in multiple neuroblastoma cell lines demonstrated ZIKV's potential as a novel neuroblastoma oncolytic virotherapy. 13ere, we survey over 35 studies that have used neuroblastoma cell lines to model ZIKV infection.These studies focused on understanding ZIKV pathology and assessing anti-viral compounds.Through re-analysis and integration of the transcriptomics, proteomics and dependency factor screens from these studies, we propose multiple molecular mechanisms to be implicated in ZIKV infection of neuroblastoma which help to determine its potential as oncolytic virotherapy.

ZIKV interactome source and analysis
We sourced 130 and five high-confidence interactions of ZIKV NS4B and NS2B-3, respectively, in SK-N-BE2 paediatric neuroblastoma cells from IMEx -The International Molecular Exchange Consortium (RRID:SCR_002805) (IM-26452). 29Scaturro et al., produced this interactome through stable expression of HA-tagged ZIKV proteins in SK-N-BE2 cells, isolation of ZIKV-host protein complexes through HA-affinity purifications, then sample preparation and run for LC-MS/MS (n = 4). 30Scaturro et al., processed the raw data using MaxQuant with Andromeda search engine.
(FDR ≤ 0.01), and they determined high-confidence interactions by Bayesian statistical modelling, with log2(fold change) ≥ 2.5; unadjusted one-sided P ≤ 0.05.The current study used the processed results obtained by Scaturro et al.
Further details of the data processing and analysis can be sourced from the original Scaturro et al. publication. 30e viral-host interactome was submitted to STRING (RRID:SCR_005223) 31 for high confidence (0.7) evidence-based physical subnetwork analysis to identify host-host interactions.We integrated and mapped the viral-host and STRING derived host-host interactions in Cytoscape (3.9.1) (RRID:SCR_003032) 32 to identify the interaction of ZIKV NS4B with host protein complexes.ZIKV NS4B host interaction partners were also submitted to DAVID for GO, KEGG and REACTOME term enrichment analysis to shed light on the possible host processes and pathways which ZIKV may interact with through NS4B.ZIKV dependency factors were integrated into Cytoscape map to highlight known protein interaction of ZIKV dependency factors with ZIKV proteins.

ZIKV dependency factor source and analysis
Extensive data mining revealed there are currently only 22 known ZIKV dependency factors in neuroblastoma cells, identified via a shRNA screen in paediatric SK-N-BE2 neuroblastoma cells. 30In an attempt to supplement this limited pool of ZIKV dependency factors, we sourced known factors from genome-wide CRISPR/Cas9 screens performed in glioma stem cells (GSCs), 33 hiPSC-NPC, 34 HEK293FT 33 and HeLa cells. 35All can ZIKV dependency factors are shown in Table 4.A combination of DAVID GO and pathway analysis, STRING interaction and literature mining approaches were employed to identify relationships between host factors to inform dependencies of ZIKV on host protein complexes and cell machinery.

Results and Discussion
ZIKV displays strong oncolytic properties against neuroblastoma cells ZIKV infects and significantly reduces the cell viability of a multitude of neuroblastoma cell lines from both primary tumour and metastatic sites (Table 1).ZIKV can significantly reduce neuroblastoma cell viability at multiplicity of infection (MOI) as low as 0.001. 36The cell viability of 11/15 neuroblastoma cell lines is significantly reduced to approximately 20% or less following ZIKV infection and these observations are apparent despite the differences in the cell line, ZIKV strain, viral MOI and the type of assay performed (Table 1).SK-N-BE1 and SK-N-BE2 cells are from bone marrow metastasis from the same patient before and after treatment, respectively, and are both highly susceptible to ZIKV.SK-N-AS, T-268 and JFEN are highly resistant (cell viability >80%) to ZIKV infection.Susceptibility is independent of patient sex, cell line origin, morphology and MYC-N status (Table 1).The non-sympathetic nervous system and non-paediatric origin of the T-268 and JFEN cells likely explain their resistance to ZIKV infection, as ZIKV has a tropism for paediatric nervous system cancer cells. 11The resistance of the paediatric SK-N-AS cell line is governed by CD24 expression, which regulates the basal antiviral state of these cells. 13,37Whilst LA-N-6 shows partial resistance to ZIKV infection (Table 1), analysis of bulk mRNA and protein show cell LA-N-6 to express CD24. 13otential reasoning for this partial resistance is that subpopulations within LA-N-6 may be CD24 -or a CD24-independent mechanism may be employed to infer resistance.From Table 1 we conclude ZIKV to be a promising oncolytic virotherapy candidate to employ against paediatric neuroblastoma since it can target neuroblastoma cells originating from the primary tumour, metastatic sites, and metastatic sites that are resistant to standard neuroblastoma therapy.
ZIKV strains possess different therapeutic potential against neuroblastoma cells Independent studies have demonstrated inherent differences in the ability of varying ZIKV strains to infect, replicate, and kill neuroblastoma cells. 38,39Here, we assess published data concerning ZIKV infection of neuroblastoma cells and ranked the viral strains based on their ability to infect neuroblastoma cells, produce fresh viral progeny and reduce cell viability (Table 2).Data mining showed the PRVABC59 Asian and Uganda #976 African strains as the top two candidates (Table 2).The PRVABC59 Asian strain induces significantly more DEGs and splice events of immune and inflammatory response genes in SH-SY5Y cells compared to the African MR766 strain, which has 99.95% sequence identity to Uganda #976. 14Brain metastases develop in 5-11% of patients with neuroblastoma and are correlated with poor prognosis. 40The ability of the Asian lineage to access the brain may enhance the therapeutic potential of ZIKV by targeting these brain metastases.Population level data has shown the epidemic Asian ZIKV lineage to rarely cause anything other than mild symptoms in children and adolescents, thus providing evidence for the safety of employing an Asian strain. 41Consequently, from those tested to date, we propose that the PRVABC59 Asain strain holds the greatest promise for development as oncolytic virotherapy against paediatric neuroblastoma.

ZIKV infection of neuroblastoma cells induces changes at the transcriptome level
Differential gene expression analysis identifies 453 and 256 significantly upregulated and downregulated genes (fold change > 1.5), respectively, in ZIKV-infected paediatric neuroblastoma SH-SY5Y cells (Figure 1A).GO, Reactome and KEGG pathway analysis identifies nine significantly upregulated and 12 significantly downregulated terms (Figure 1B-C).Upregulated processes include "TNF signalling pathway", lipid metabolism ("Cholesterol biosynthesis", "Cholesterol biosynthetic process", "Activation of gene expression by SREBF (SREBP)"), endoplasmic reticulum (ER) stress ("Response to endoplasmic reticulum stress", "XBP1(S) activates chaperone genes") and transcription ("BMAL1:CLOCK, NPAS2 activates circadian gene expression", "Positive regulation of transcription from RNA polymerase II promoter").The downregulated terms are predominantly cell cycle-and DNA replication-related processes and this downregulation is apparent when the "Cell Cycle" KEGG pathway is plotted for all DEGs (fold change > 0) (Figure 2B).A potential explanation for this observation is that ZIKV can disrupt the cell cycle by targeting the centrioles in neuroblastoma cells. 42KV induces TNF signalling in neuroblastoma cells Of the top 10 upregulated DEGs in SH-SY5Y cells, four (BIRC3, TNFAIP3, ICAM1 and BCL3) are components of the TNF signalling pathway (Figure 1A).The TNF pathway is particularly noteworthy to consider for oncolytic virotherapy since it may play a role in both oncolysis (direct cell death) and the anti-tumoral immune response.Here, mapping the "TNF Signalling" KEGG pathway for ZIKV-infected SH-SY5Y cannot deduce if ZIKV may activate CASP-mediated apoptosis or CASP-independent necroptosis (Figure 2A).However, ZIKV-infected SH-SY5Y cells clearly show significant upregulation of transcription factors (AP-1, cEBPβ and CREB), leukocyte recruitment and activation (CCL2 and CSF1), intracellular signalling (BCL3, NFKBIA, TNFAIP3 and TRAF1) and cell adhesion genes (Icam1 and Vcam1) (Figure 2A).ZIKV significantly upregulates the expression of multiple Activator protein 1 (AP-1) transcription factors, including members from all four AP-1 subfamilies (ATF, JUN, FOS and MAF) in SH-SY5Y cells (Figure 3A).AP-1 can regulate the expression of a diverse set of genes in response to nutrients, cytokines, stress or pathogen infection, and is involved in innate and adaptive immunity, differentiation, proliferation, survival and apoptosis. 43AP-1 transcription factors can regulate the immune response of tumours, and significant AP-1 upregulation by ZIKV infection potentially identifies AP-1 as a mechanism through which ZIKV could yield an anti-tumoral immune response against neuroblastoma in vivo. 44re, CCL2 (MCP-1) is significantly upregulated at the transcriptome level by ZIKV infection, and two independent studies have shown CCL2 to be secreted by ZIKV-infected SH-SY5Y cells. 45,46CCL2 is a pro-inflammatory mediator that recruits leukocytes via chemotaxis to infiltrate tissues, including the CNS, to stimulate inflammation. 47A nonneurotoxic herpes simplex virus (HSV)-based oncolytic virotherapy, engineered to express physiologically relevant levels of CCL2 (M010), significantly reduced Neuro-2a neuroblastoma growth in the flank of immune-competent mice and recruited CD4+ and CD8+ T-cells to infiltrate the tumour. 47Additionally, CCL2 is secreted by ZIKV-infected cultured canine glioblastoma cells when in the presence of monocytes and is detected in serum and CSF samples of canines bearing spontaneous brain tumours following ZIKV infection. 12We propose here that CCL2 may be capable of inducing an anti-tumoral immune response against paediatric neuroblastoma during ZIKV infection.Supporting the notion of a ZIKV-induced inflammatory response, 32 genes implicated in cytokine signalling in the immune system are significantly differentially expressed in ZIKV-infected SH-SY5Y cells: 27 upregulated and five downregulated (Figure 3B).ZIKV induces lipid metabolism in neuroblastoma cells ZIKV infection significantly upregulates lipid metabolism-related terms in SH-SY5Y cells; specifically, "Cholesterol biosynthesis" and "Activation of gene expression by SREBF (SREBP)" (Figure 1B).Cholesterol and lipids are essential cellular components and there are complex systems that function to regulate their intracellular abundance and localisation.These systems include regulation of cholesterol biosynthesis by the sterol regulatory element binding protein (SREBP) pathway, intracellular cholesterol trafficking, and cholesterol efflux by the liver X receptor (LXR) pathway.
Cholesterol and fatty acids are required for multiple stages of the flavivirus life cycle, including regulating viral entry, the formation of viral replication complexes in the ER membrane and viral egress. 48ZIKV elevates lipogenesis and remodels the composition of the lipid classes in infected SK-N-SH cells. 49Our data mining of published literature identified several approaches to regulate ZIKV infection of neuroblastoma cells through modification of intracellular lipid levels (Table 3).These include supplementation with pathway regulators (PF-429242, fenofibrate, lovastatin, U18666A and LXR 623) or exogenous lipids (oleic acid, docosahexaenoic acid (DHA) and cholesterol).
Three SREBP pathway inhibitors (PF-429242, fenofibrate and lovastatin) reduce the capability of ZIKV to infect SK-N-SH neuroblastoma cells (Table 3).The SREBP pathway is a principal regulator of fatty acid and cholesterol biosynthesis.The SREBF1 and SREBF2 transcription factors control this pathway, and although they share a small degree of redundancy, they primarily regulate the expression of fatty acid biosynthesis and cholesterol biosynthesis target genes, respectively. 50Both SREBF2 and SREBF2-AS1 are significantly upregulated in ZIKV-infected SH-SY5Y cells, and the most highly upregulated SREBF downstream gene (HMGCS1) is a SREBF2 responsive gene (Figure 4A).Pathway analysis identifies significant upregulation of "Cholesterol biosynthesis" (Figure 1B) and here we observe significant upregulation of multiple enzymes of the SREBF2 cholesterol biosynthetic pathway (HMG-CoA synthase (HMGCS1), Mevalonate Diphosphate Decarboxylase (MVD), CYP51 (CYP51A1), Mevalonate Kinase (MVK), squalene synthase (FDFT1), Squalene Epoxidase (SQLE), Lanosterol Synthase (LSS), Lathosterol Oxidase (SC5D)) (Figure 4A).The SREBP pathway is essential for ZIKV infection, and we propose that it may contribute, through the SREBF2 transcriptional pathway, to the upregulation of cholesterol biosynthesis in neuroblastoma cells.
Both U18666A and exogenous cholesterol restricts ZIKV infection of neuroblastoma cells (Table 3).U18666A is an intracellular cholesterol transport inhibitor that causes the accumulation of cholesterol in lysosomes to hinder the endosomal-lysosomal system. 51Exogenous cholesterol also leads to the inactivation of the late endosomal-lysosomal compartments through a build-up of cholesterol. 51Collectively, this identifies a dependence of the ZIKV life cycle in neuroblastoma cells on intracellular cholesterol for the correct functioning of the endosomal-lysosomal system.The LXR pathway agonist (LXR 623) promotes cholesterol efflux (Table 3).Flaviviruses require cholesterol for the restructuring of host membranes, and LXR 623 demonstrates this dependence of ZIKV in neuroblastoma by preventing ZIKV-induced vesicle production and ER expansion in SK-N-SH cells. 52The LXR pathway and expression of its downstream lipid homeostasis genes are regulated by the transcription factors LXR-α (NR1H3) and LXR-β (NR1H2).LXR-α protein is significantly increased by ZIKV infection of SK-N-SH neuroblastoma cells from 48 hr. 52Although LXR-α mRNA is only marginally upregulated in our study, two major cholesterol efflux factors that are downstream of the LXR pathway, ATP-Binding Cassette A1 and G1 (ABCA1 and ABCG1), are significantly upregulated (Figure 4B).Interestingly, exogenous addition of oleic acid enhances ZIKV infection in neuroblastoma cells (Table 3).Oleic acid is one of the main monounsaturated fatty acid synthesised by the LXR pathway, which is achieved through induction of FASN and SCD. 53We observe significant upregulation of both FASN and SCD in ZIKV-infected neuroblastoma cells (Figure 4B) and propose that this may induce oleic acid synthesis to aid ZIKV infection in neuroblastoma cells.Collectively, our data mining identifies a dependence of ZIKV on the LXR pathway and suggests that ZIKV may manipulate this pathway in neuroblastoma cells to upregulate cholesterol efflux and/or induce oleic acid synthesis.
We propose that lipid abundance, localisation, trafficking and metabolism regulate ZIKV infection of neuroblastoma cells, and that remodelling of the cellular lipid composition within the host cell may produce a favourable environment for efficient replication.
ZIKV induces and is dependent on the ER stress response in neuroblastoma cells ZIKV upregulates ER-stress-related terms in SH-SY5Y cells, principally "Response to endoplasmic reticulum stress" and "XBP1(S) activates chaperone genes" (Figure 1B).The Unfolded Protein Response (UPR) dictates the ER-stress response.The UPR is normally inactive due to the ER chaperone binding immunoglobulin protein (BIP) sequestering three ER stress sensors (IRE1, PERK and ATF6).Under stress conditions BIP releases IRE1, PERK and ATF6 to assist protein folding, allowing them to activate their respective UPR-mediated ER-stress pathways.
Activation of the IRE1-mediated UPR leads to IRE1 splicing a 26 bp region from the ubiquitously expressed XBP1 mRNA.The active transcription factor XBP1(S) then drives the expression of genes to help alleviate ER stress, primarily chaperone and ER-associated protein degradation (ERAD) genes.ZIKV infection significantly upregulates 15 genes of the IRE1-mediated "XBP1(S) activates chaperone genes" Reactome pathway in SH-SY5Y cells (Figure 5A).XBP1 is the most highly upregulated gene and others include the endoplasmic-reticulum-associated protein degradation (ERAD) gene SYVN1 and the chaperones DNAJC3 and DNAJB9 (Figure 5A).Multiple IRE1-mediated UPR genes (EDEM1, SYVN1, SSR1, SRPRB, ATP6V0D1, and EXTL3) are ZIKV dependency factors in hiPSC-NPCs (Table 4).Chemical inhibition of IRE1 by 4μ8C impairs ZIKV infection in vivo. 54Our data mining and re-analysis shows that ZIKV significantly upregulates the IRE1-mediated UPR in SH-SY5Y cells and that ZIKV is dependent on this for efficient infection, likely as a means to regulate and combat viral replication-induced ER stress.
PERK-mediated UPR regulates the expression of genes involved in apoptosis, redox, amino acid transport and autophagy through eIF2 phosphorylation and the transcription factor ATF4. ZIKV infection significantly upregulates seven genes of the Reactome pathway "ATF4 activates genes in response to endoplasmic reticulum stress" (Figure 5B), including the ERAD gene HERPUD1 and the transcription factors ATF3, CEBPB and CEBPG.GADD34 (PPP1R15A), which usually dephosphorylates eIF2α in a negative feedback loop, is significantly upregulated here by ZIKV infection, and ZIKV induces eIF2 phosphorylation in SK-N-SH cells. 55ZIKV likely upregulates GADD34 to combat ER stressinduced translational repression, as fresh virions require de novo protein synthesis.C/EBP homologous protein (CHOP) (DDIT3) is a pro-apoptotic protein downstream of the PERK UPR pathway that others have observed to be significantly upregulated in SH-SY5Y and SK-N-SH cells in response to ZIKV infection. 14,55,56CHOP induces apoptotic markers, including Caspase 3, leading to cell death.Notably, multiple PERK-mediated UPR genes (ATF4, EIF2AK1, EIF2AK2, EIF2AK3 and EIF2AK4) are ZIKV dependency factors in hiPSC-NPCs (Table 4).
Our data mining, integration and re-analysis suggests that ZIKV specifically upregulates and is dependent on the IRE1 and PERK branches of the UPR ER stress response in SH-SY5Y cells; observations that are supported by others. 55,56KV is dependent on the EMC in neuroblastoma cells To determine which host mechanisms ZIKV may be dependent on, we cross-referenced the 22 known proteins that ZIKV requires to infect neuroblastoma cells with ZIKV dependency factors from four cell lines (Figure 6A and Table 4).Between 72-94% of the dependency factors identified across the five different cell lines are cell-specific, highlighting how ZIKV utilises differing host factors across different cell types for its life cycle.The sparse overlap of ZIKV dependency factors identifies only one factor common to all five cell types.MMGT1 (EMC5) is a key component of the Endoplasmic Reticulum (ER) Membrane Protein Complex (EMC).The EMC is a hetero-oligomer composed of 10 subunits, has chaperone properties by assisting multi-transmembrane protein folding, and is implicated in ER stress, flavivirus infection and lipid trafficking.57 To assess if ZIKV is dependent on additional EMC subunits during infection, we searched for them in our ZIKV dependency factor dataset.Our integration of varying ZIKV-dependency factor datasets show ZIKV to have a strong dependence on the EMC independent of cell type; all 10 EMC proteins are ZIKVdependency factors in hiPSC-NPC, eight are in HeLa and three in GSC and HEK293FT cells (Figure 6B).The EMC facilitates the expression of ZIKV transmembrane proteins (NS2B, NS4A and NS4B), ZIKV NS4B interacts with EMC subunits, and disrupting the EMC impedes infection by ZIKV and other flaviviruses.58,59 We propose that the EMC stabilises ZIKV proteins through integration into the ER membrane, thus permitting efficient infection in neuroblastoma cells.If investigated, we predict that additional EMC subunits would present as ZIKV dependency factors in neuroblastoma cells.
ZIKV is dependent on the V-ATPase in neuroblastoma cells Acidification of the endosomal-lysosomal system by the V-ATPase is a property that viruses can utilise to drive the release of their nucleocapsid into the cytosol.ATP6V0C, a central component of the V-ATPase, is a ZIKV-dependency factor in neuroblastoma, hiPSC-NPC and HEK293FT cells (Figure 6A).A total of 12 additional V-ATPase subunits are ZIKV dependency factors across GSC, hiPSC-NPC and HeLa cells (Figure 6C).These 13 genes consist of multiple subunits from the Vo proton translocation and V1 ATP hydrolytic domains, identifying a functional dependence of ZIKV on the entire V-ATPase complex.The V-ATPase inhibitor Bafilomycin A1 specifically binds ATP6V0C and through V-ATPase inhibition prevents lysosomal acidification and the autophagy-lysosome pathway. 60Bafilomycin A1 inhibits ZIKV infection of SH-SY5Y cells, supporting our observation (Table 3).siRNA silencing of the V-ATPase significantly impairs ZIKV infection of T98G glioblastoma cells, collaborating its requirement for infection of nervous system tumour cells. 61We propose that loss of V-ATPase function impairs ZIKV infection in SH-SY5Y cells due to a perturbed pH gradient in the endosomal system.This likely prevents fusion of the viral envelope with the endosomal membrane for release of the nucleocapsid, therefore, trapping ZIKV for degradation in the lysosome, as observed in Vero cells. 62KV NS4B possesses oncolytic capability against neuroblastoma cells ZIKV NS4B protein is principally responsible for the oncolytic effect in SH-SY5Y cells, via activating the mitochondrial apoptotic pathway.63 Determining the interactions and mechanisms underpinning this may yield opportunities to develop a paediatric neuroblastoma therapy based on ZIKV NS4B.ZIKV NS4B has 130 known host interaction partners in SK-N-BE2 neuroblastoma cells.30 Re-analysing this interactome, we observe multiple pathways previously implicated during ZIKV infection of neuroblastoma cells: including mitochondrial-, lipid metabolism-and ER-associated processes (Figure 7).ZIKV NS4B interacts with 10 lipid biosynthesis proteins, three (SCD, SC5D and DHCR7) of which are expressed in response to SREBP pathway activation.This identifies a direct interaction between ZIKV and host lipid metabolism and the SREBP pathway, supporting our previous observations at the transcriptome level.
ZIKV NS4B recruits BAX to the mitochondria, triggers its activation, and releases Cytochrome c from mitochondria to induce mitochondrial cell death in SH-SY5Y cells. 63ZIKV NS4B interacts with a multitude of mitochondrial genes (Figure 7).Including, electron transport chain proteins (TIMMDC1, MT-CO2, COX15 and OXA1L), mitochondrial translocases that import proteins into the mitochondrial matrix (TOMM22, TIMM23, TIMM50 and TIMM17B) and Solute Carrier Family 25 members for transport of solutes across the mitochondrial membrane (SLC25A1, SLC25A3, SLC25A6, SLC25A11, SLC25A12, SLC25A13 and SLC25A22).Specifically, MT-CO2, COX15 and OXA1L are conserved catalytic core, assembly and accessory subunits of the Cytochrome c oxidase complex, respectively.The Cytochrome c oxidase complex tightly couples Cytochrome c to the inner mitochondrial membrane.We propose that NS4B interacts with Cytochrome c oxidase to uncouple it from Cytochrome c, causing Cytochrome c release through the BAX pore into the cytosol to drive the mitochondrial cell death pathway in neuroblastoma cells.

ZIKV NS4B interacts with the Mammalian Translocon in neuroblastoma cells
ZIKV NS4B interacts with and is dependent on multiple proteins of the Mammalian Translocon (Figures 5A and 6).The mammalian translocon is primarily composed of the Oligosaccharyl Transferase (OST) complex, the Sec61 complex and the translocon-associated protein (TRAP) complex. 64The multimeric OST complex co-translationally N-glycosylates proteins within the ER to assist protein folding, stability and trafficking.The Sec61 complex, a heterotrimer of Sec61α, Sec61β and Sec61γ, co-translationally translocates newly synthesised proteins across the ER and during ER stress can regulate IRE1α activity.TRAP is a heterotetramer of SSR1, SSR2, SSR3 and SSR4 that assists co-translational translocation of proteins into the ER and can prevent aberrant N-linked glycosylation during ER stress.
STT3A, a principal component of the OST complex, interacts with ZIKV NS4B and is a ZIKV dependency factor in neuroblastoma, GSC, hiPSC-NPC and HeLa cells (Figures 5A and 6).Regarding the additional OST subunits, ZIKV NS4B interacts with DDOST, RPN1, RPN2 and KRTCAP2, and OSTC and OST4 are ZIKV dependency factors in HeLa cells and GSCs, respectively (Figures 5A and 6).Two forms of the OST complex exist, the STT3A and STT3B OST paralogs.KRTCAP2 and OSTC are STT3A-specific OST factors, which permit interaction of STT3A with the translocon, whilst TUSC3 and MAGT1 are STT3B-specific OST factors. 64STT3A and both STT3A-specific OST factors are ZIKV interaction partners and/or dependency factors, but neither STT3B nor the STT3B-specific OST factors are.In addition to the OST factors, multiple N-linked glycosylation-related proteins (DPM1, DERL3, SYVN1, UBE2G2 and UBE2J1) are also ZIKV dependency factors in non-neuroblastoma cells (Table 4).The OST complex inhibitor NGI-1 blocks ZIKV infection of Huh7 cells, and disrupting ZIKV prM and E protein N-glycosylation impairs the release of infectious ZIKV particles from Vero cells. 65,66We propose that STT3A functions as a bonafide ZIKV dependency factor in multiple cell types, and propose that efficient infection of neuroblastoma cells by ZIKV is likely dependent on the STT3A OST paralog for N-glycosylation of its viral proteins.
ZIKV NS4B interacts with SEC61A1 and SEC61B of the Sec61 complex in neuroblastoma cells and the Sec61α inhibitor Mycolactone impedes ZIKV infection of HeLa cells. 67ZIKV NS4B interacts with SSR3 of the TRAP complex in neuroblastoma cells and ZIKV is dependent on at least two of the four TRAP complex subunits for infection of GSC, hiPSC-NPC and HeLa cells (Figure 6A).Further supporting our observation of ZIKV interacting and being dependent on the mammalian translocon is its dependence on SRPRB, SPCS3 and TRAM1; subunits of the Signal Recognition Particle (SRP), the Signal Peptidase Complex (SPCS) and the Translocating chain-associated membrane protein (TRAM), respectively.Notably, the viral protease NS2B-3 also interacts with subunits of the OST complex (STT3A, RPN1), Sec61 Nodes are grouped and labelled according to any sets of high-confidence interactions between the host proteins, and by pathways they are involved in.Cross-referencing the interactome with the ZIKV dependency factor datasets identifies the interaction of NS4B with dependency factors in neuroblastoma cells (red) and in GSC, hiPSC-NPC, HeLa and HEK293FT cells (collectively termed non-neuroblastoma cells, orange).To aid visualisation, any nodes possessing no high confidence interactions, other than their interaction with NS4B, have been grouped.All nodes within Figure 7 interact with NS4B, thus, to aid visualisation all edges between NS4B and nodes within a group have been condensed into a single edge between NS4B and the grouped set of nodes.ZIKV, Zika virus; NS4B, non-structural protein 4B; GSC, glioma stem cell.
complex (SEC61B) and TRAP complex (SSR3) (Figure 7).These interactions likely facilitate the co-translational cleavage of the viral polypeptide by NS2B-3 into its individual viral proteins.
From our re-analysis of a published ZIKV interactome we propose ZIKV NS4B and NS2B-3 to interact with the core complexes of the mammalian translocon, and hypothesise that ZIKV infection in neuroblastoma cells may be dependent on these interactions.The dependency of ZIKV likely stems from the mammalian translocon facilitating viral polyprotein co-translational translocation, viral polyprotein cleavage, viral membrane protein insertion and/or viral protein N-glycosylation.Additionally, ZIKV may utilise its protein interactions with the Sec61 complex, TMEM33 and VAPB, to regulate the IRE1-and PERK-mediated UPR ER stress responses, that we observed to be significantly upregulated at the transcriptome level in ZIKV infected-neuroblastoma cells.

Conclusions
Our study highlights the strong therapeutic potential of ZIKV, specifically the PRVABC59 strain, against multiple neuroblastoma cell-lines.Our data mining, integration and re-analysis suggest ZIKV to interact with, and be dependent on, multiple host protein complexes and pathways for its life cycle in paediatric neuroblastoma cells and for inducing oncolysis (Figure 8).Although this area of research is still at an early stage, our extensive survey of neuroblastoma ZIKV infection studies clearly demonstrates the potential of a ZIKV-based therapeutic.There are a few avenues that need to be addressed to progress this area of research, including; (1) assessing ZIKV's oncolytic effect against neuroblastoma in xenograft mouse models, (2) assessing ZIKV's capability to induce an anti-tumoral immune response against neuroblastoma in immune-competent in vivo models, and (3) considering the effectiveness and safety of employing different forms of ZIKV-based therapeutics against neuroblastoma.Examples of the latter may include live attenuated ZIKV strains or the construction of a virotherapy that collectively expresses ZIKV NS4B and CCL2, which we observe here to hold elements of ZIKV's oncolytic and immune activation potential, respectively.Although this finding may contribute to this research field, authors should consider significant revisions before indexing.Next, I expose my comments for the author's and editors' consideration: 1.In the Keypoints section, what do the authors mean by "Most pediatric neuroblastoma cell lines are susceptible to Zika viral infection" when they only analyzed data from two neuroblastoma cell lines?The statement should not be included as a Keypoint if it refers to previous literature on the potential Zika viral infection of neuroblastoma cell lines.Keypoints should be made based on their research results only.
2. The authors have chosen to work with the SK-N-BE(2) cell line, a neuroblastoma cell line established from a bone marrow biopsy taken from a patient with disseminated neuroblastoma after repeated courses of chemotherapy and radiotherapy.They propose a potential ZIKV-based therapeutic for neuroblastoma.The decision to use this cell line rather than one from a nontreated patient may only partially fulfill their research strategy outcome.Analyses should be made on non-treated neuroblastoma data to understand the effect of Zika viral infection as an oncotherapy alternative.
3. Authors must justify the usage of four different databases for enrichment analyses.
4. Authors must include a link to the pipeline and scripts used for bioinformatic analyses.This will significantly enhance the transparency and reproducibility of their research.
5. Literature mining results presented in the Results section be included as a Keypoint if the authors incorporate the related methods in the Methods section.

Is the work clearly and accurately presented and does it cite the current literature? Yes
Is the study design appropriate and is the work technically sound?Yes

Are sufficient details of methods and analysis provided to allow replication by others? Partly
If applicable, is the statistical analysis and its interpretation appropriate?Yes Are all the source data underlying the results available to ensure full reproducibility?Partly

Are the conclusions drawn adequately supported by the results? Yes
Competing Interests: No competing interests were disclosed.
I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
Reviewer Report 24 May 2024 https://doi.org/10.5256/f1000research.166562.r280953 © 2024 Leung T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Thomas C. N. Leung
The Chinese University of Hong Kong,, Hong Kong, China Most of the concerns raised have been adequately addressed.However, I noticed that my comment #4 from the previous review has not been addressed, and I did not receive a response from the authors regarding this issue.
To clarify my concern from comment #4: In the section, specifically the "ZIKV dependency factor source and analysis" subsection, the authors state, Extensive data mining revealed there are currently only 22 known ZIKV dependency factors in neuroblastoma cells, identified via a shRNA screen in paediatric SK-N-BE2 neuroblastoma cells."This suggests that the first column of Table 4 should reflect the results from this experiment.However, the header of the first column in Table 4 indicates the use of 'SH-SY5Y' cells instead of the 'SK-N-BE2' cells mentioned in the methodology section.
Clarification is needed to determine whether the discrepancy lies in the table or the methods description.Most of the concerns raised have been adequately addressed.However, I noticed that my comment #4 from the previous review has not been addressed, and I did not receive a response from the authors regarding this issue.
To clarify my concern from comment #4: In the methods section, specifically the "ZIKV dependency factor source and analysis" subsection, the authors state, "Extensive data mining revealed there are currently only 22 known ZIKV dependency factors in neuroblastoma cells, identified via a shRNA screen in paediatric SK-N-BE2 neuroblastoma cells."This suggests that the first column of Table 4 should reflect the results from this experiment.However, the header of the first column in Table 4 indicates the use of 'SH-SY5Y' cells instead of the 'SK-N-BE2' cells mentioned in the methodology section.
Clarification is needed to determine whether the discrepancy lies in the table or the methods description.

Is the work clearly and accurately presented and does it cite the current literature? Yes
Is the study design appropriate and is the work technically sound?Yes

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility?Yes

Are the conclusions drawn adequately supported by the results? Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Proteomics, Cellular Biology I confirm that I have read this submission and believe I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Version 2
Reviewer Report 06 May 2024 https://doi.org/10.5256/f1000research.158746.r267294 © 2024 Leung T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Thomas C. N. Leung
The Chinese University of Hong Kong,, Hong Kong, China The manuscript examines the potential of Zika virus (ZIKV) as an oncolytic virotherapy for neuroblastoma.Neuroblastoma is an aggressive childhood cancer and the leading cause of cancer deaths in infants.Current treatments have significant toxicity.Oncolytic virotherapy could help develop safer therapies.ZIKV interests researchers due to its ability to access the nervous system and kill neural cells.
The study analyzes the papers examining ZIKV infection in neuroblastoma cell lines.Most cell lines are highly susceptible to ZIKV and viability reduces to 20% or less.Susceptibility is independent of clinical factors.The PRVABC59 strain shows most promise due to better RNA replication and ability to cross the blood-brain barrier.RNA sequencing of infected cells shows changes in pathways like TNF signaling, lipid metabolism and endoplasmic reticulum stress response.ZIKV increases TNF transcription factors and CCL2, pointing to an immune response.Analysis of interactomes identifies ZIKV NS4B interacting with 130 host proteins.Networks link NS4B to IRE1 stress response, lipid metabolism proteins and the translocon complex.The paper reviews host dependency factors identified in screens and proposes relationships to protein complexes.Modulating lipids and associated pathways alters ZIKV infection.Inhibitors of SREBP and treatments affecting late endosomes reduce infection.Overall, the work evaluated ZIKV's potential as an oncolytic virotherapy for neuroblastoma through direct cytotoxicity and immunogenicity.Integrative omics uncover molecular insights into host factors and pathways regulated during infection that could inform therapeutic development.However, some clarification is needed regarding: Regarding the methodology section on 'ZIKV interactome source and analysis', some additional details could aid reproducibility.The authors mention raw data was processed using MaxQuant and Andromeda, but it is unclear if they re-analyzed the raw data or obtained processed results.Providing search parameters, such as post-translational modifications considered and database details, as well as the false discovery rate threshold used, would strengthen the method description. 1.
Additionally, when describing DAVID analysis of ZIKV NS4B interacting partners, more details on the specific functional analysis performed would be informative, as DAVID is commonly used for annotation rather than direct interaction identification.

2.
A few minor points regarding data presentation could also be clarified.The bar charts in 3.
Figure 1B and 1C contain numbers at the end of bars but the meaning of these numbers is unspecified.Figures 4 and 5 employ asterisks but it is unclear if they denote statistical significance levels or something else, as some bars contain double lines of asterisks.Lastly, first column of Table header of 'SH-SY5Y' appears inconsistent with the methods section stating analyses used the SK-N-BE2 cell line.Clarification is needed on whether the table or method description requires correction.Addressing these points of clarity would help fully evaluate the rigour and reproducibility of the work.With revision, this study could provide valuable insights into ZIKV oncolysis and neuroblastoma biology.The article presents an integration of transcriptomics and proteomics of several previous studies where is used the Zika virus (ZIKV) in neuroblastoma cells as a potential therapy in high-risk neuroblastoma.This pediatric cancer, characterized by its aggressive nature and limited treatment options in state-of-the-art non-responder patients, presents a pressing challenge in pediatric oncology.The authors focus on the explanation of the unique properties of ZIKV, its tropism in neuroblastoma cancer cells, and an extensive review of the host immune response in a large-scale analysis referring to previous studies.
The study focuses on different aspects regarding ZIKV-induced cell response, trying to integrate published data to propose possible targets that are characteristic of ZIKV in neuroblastoma.However, all the hypotheses and conclusions made in the study need to be validated in normalized conditions without the bias of putting together many different studies performed in different conditions.Moreover, the article should be rewritten excluding the expressions where the authors attribute the actual empirical work of the assays.They should also state and point out that the work is collecting data from previous studies and better describe the integration methodology putting all together to offer an easier view of unequivocal unique conclusions beyond previous studies.
Overall, the information provided in this article would be enlightening for having a general descriptive view of the different relevant stages in ZIKV infection that can elucidate an integrative understanding of strategies to improve the virotherapy but lacks scientific value since no validation of the the hypothesis is performed.

MAJOR POINTS
Authors should experimentally validate their bioinformatic-based hypothesis.

MINOR POINTS
At the end of the introduction, the sentence: "Pediatric neuroblastoma, like pediatric brain tumors, are predominantly tumors of the nervous system consisting of cancerous cells with neural characteristics."Is redundant and not necessary.

○
Authors should better describe the original data used for bioinformatic analysis.Papers that study the topic are presented, but the source of the data should be better described.
○ "The non-sympathetic nervous system and non-pediatric origin of the T-268 and JFEN cells likely explain their resistance to ZIKV infection, as ZIKV has a tropism for pediatric nervous system cancer cells" needs citation.• "The non-sympathetic nervous system and non-pediatric origin of the T-268 and JFEN cells likely explain their resistance to ZIKV infection, as ZIKV has a tropism for pediatric nervous system cancer cells" needs citation.
Citation added ○ "Data accordance is a qualitative measure which we employed to describedenotes the degree of similarity of the results between publications that performed ZIKV cell viability of cell death assaysinfection assays in of neuroblastoma cells using the same ZIKV strain.Data accordance of five denotes that the findings of one publication closely support the findings from another, a data accordance of one denotes publications reporting vastly contrasting results.When a viral strain is published in only one paper, it is allocated a data accordance of NA" ○ "The multiple ZIKV pandemics identified that infection by an Asian strain is generally well accommodated by children, thus providing evidence for the safety of employing an Asian strain" needs citation.

○
• In Figure 3A, why authors propose that SREBF2 transcriptional pathway is responsible for the upregulation of cholesterol biosynthesis when there are other pathways with more statistical difference and fold-change.
Text has been added to the manuscript to help clarify why we believe the SREBF2 transcriptional pathway may contribute to the upregulation of cholesterol biosynthesis in ZIKV-infected neuroblastoma cells.

○
• In the sentence "ZIKV likely remodels the cellular lipid composition to help produce a favorable environment for efficient replication", it should be taken into account that ZIKV cannot be the one producing that, but the host viral response be responsible for those

Griffith D Parks
Burnett School of Biological Sciences, University of Central Florida, Orlando, Florida, USA There is very high interest in mechanisms for improving the potency and specificity of oncolytic viruses, and much of this interest is in large scale analysis of host cell responses.Thus, there is potential significance for the work described here, in the analysis of transcriptomic changes that occur with Zika virus (ZIKV) infection of neuroblastoma cells in culture.An unfortunate weakness is that the work is not presented as what it is: a review of the literature and not a primary study of ZIKV infection.
Strengths of the work include the importance of understanding host factors that modulate RNA virus infections such as those by ZIKV, the global omics approach to the study using prior data sets and literature searches, the survey of published results to conclude best virus and cell type, and the identification of distinct pathways.The work is largely well done, with interpretations which are consistent with the data.Figure 7 is particularly useful.
The main weakness of the manuscript is the presentation of findings as new and "identified" by the authors.For example, for nearly all the sections there are phrases such as "Here, we identify ZIKV NS4B….directlyinteract with core complexes…."The authors have not identified a direct interaction, but rather have used prior databases to develop a hypothesis that this may occur.This is a misleading representation of the data presented in this manuscript and there should be a rewrite of the text to state that this is from analysis of the literature and data mining.
The authors should make it clear in the abstract in title that this is not a new study, but rather an evaluation of the literature and mining of prior data.In fact, the title is misleading by stating it is a study of ZIKV infection, when it is in reality an analysis of the published data (still useful).In reality, there is a major strength in this large amount of work and the authors are to be commended for it.There needs to be a clear statement that this is a review manuscript.
Other comments.The text states that ZIKV is neurotropic.This should be modified, as this virus appears to have a lot of different host cell types it can infect.Disease is manifested when there is infection of neuro-cells, but this is not tropism. 1.
In the results of abstract -please clarify "ZIKV is dependent What part of ZIKV is dependent? 2.
The text does not come to a conclusion on data from Table I other than to say lots of cells can be infected.What is the reason behind the graded difference between the 5 and 4 and 3.The authors speculate on the reason for grade 1, but not the others.

3.
Page 4 text -"the Asian lineage…..is the clear choice for oncolytic therapy."Not clear where this comes from, and no citation was given.

4.
Table 2 is useful, but has the caveat that it does not list the cells that were tested.It would be very useful to include a column with "shared cell lines tested in publications" 5.
Fig 1D and 2A are entirely too small for anyone to read.These should be expanded and used a separate figures, so as to allow a reader to see the results. 6.

Is the work clearly and accurately presented and does it cite the current literature? Yes
Is the study design appropriate and is the work technically sound?Yes

Are sufficient details of methods and analysis provided to allow replication by others? Partly
If applicable, is the statistical analysis and its interpretation appropriate?I cannot comment.A qualified statistician is required.

Are the conclusions drawn adequately supported by the results? Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: RNA Viruses I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have to have a lot of different host cell types it can infect.Disease is manifested when there is infection of neuro-cells, but this is not tropism.

○
In the results of abstract -please clarify "ZIKV is dependent on…" What part of ZIKV is dependent? 1.
Has been corrected to "ZIKV infection is dependent on sterol regulatory element binding protein (SREBP)-regulated lipid metabolism and three protein complexes; V-ATPase, ER Membrane Protein Complex (EMC) and mammalian translocon.".

○
The text does not come to a conclusion on data from Table I other than to say lots of cells can be infected.What is the reason behind the graded difference between the 5 and 4 and 3.The authors speculate on the reason for grade 1, but not the others. 1.
We have replaced the rankings with the actual values/ranges to make this easier to interpret.

○
We have updated the values of LA-N-6 and SK-N-Be(1).

○
We have added the following text: "Whilst LA-N-6 shows partial resistance to ZIKV infection ( Table 1), analysis of bulk mRNA and protein show cell LA-N-6 to express CD24.13 Potential reasoning for this partial resistance is that subpopulations within LA-N-6 may be CD24-or a CD24-independent mechanism may be employed to infer resistance.From Table 1 we conclude ZIKV to be a promising oncolytic virotherapy candidate to employ against paediatric neuroblastoma since it can target neuroblastoma cells originating from the primary tumour, metastatic sites, and metastatic sites that are resistant to standard neuroblastoma therapy."

○
Page 4 text -"the Asian lineage…..is the clear choice for oncolytic therapy."Not clear where this comes from, and no citation was given. 1.

This text has been removed
○ Table 2 is useful, but has the caveat that it does not list the cells that were tested.It would be very useful to include a column with "shared cell lines tested in publications" 1.The benefits of publishing with F1000Research:

The cell lines have now been added to Table 2, including
Your article is published within days, with no editorial bias • You can publish traditional articles, null/negative results, case reports, data notes and more • The peer review process is transparent and collaborative • Your article is indexed in PubMed after passing peer review • Dedicated customer support at every stage • For pre-submission enquiries, contact research@f1000.com , Boadilla del Monte, Spain Vicent Tur-Planells, Universidad CEU San Pablo, Madrid, Spain2.

Figure 1 .
Figure 1.Differential gene expression, GO and pathway analysis of ZIKV infection in SH-SY5Y cells.Volcano plot of genes differentially expressed in response to ZIKV infection of SH-SY5Y cells, with the top 10 upregulated genes labelled (A).Significantly upregulated (B) and downregulated (C) GO Biological Processes, KEGG and Reactome pathways in response to ZIKV infection in SH-SY5Y neuroblastoma cells.The number at the end of each bar in the bar chart denotes the number of DEGs identified for the given term.Significance values are corrected for multiple testing using the Benjamini and Hochberg method (padj < 0.05).GO, Gene Ontology; ZIKV, Zika virus; DEG, differentially expressed gene.

Figure 2 .
Figure 2. Pathway mapping of ZIKV infection in SH-SY5Y cells.KEGG maps of the up-reulated TNF Signalling Pathway (A) and down-regulated Cell Cycle (B), plotted using all DEGs (fold change > 0).Significance values are corrected for multiple testing using the Benjamini and Hochberg method (padj < 0.05).ZIKV, Zika virus; KEGG, Kyoto Encyclopedia of Genes and Genomes; DEG, differentially expressed gene.

Figure 3 .
Figure 3. ZIKV infection upregulates the TNF signalling pathway in neuroblastoma cells.Expression levels of TNF Signalling Transcription Factors in SH-SY5Y cells in response to ZIKV infection (A).Expression levels of cytokine signalling in immune system genes in SH-SY5Y cells in response to ZIKV infection (B).Significance values are corrected for multiple testing using the Benjamini and Hochberg method (padj < 0.05).A threshold line of Log

Figure 7 .
Figure 7.The ZIKV NS4B interactome in neuroblastoma cells and its interaction with ZIKV dependency factors.Nodes are grouped and labelled according to any sets of high-confidence interactions between the host proteins, and by pathways they are involved in.Cross-referencing the interactome with the ZIKV dependency factor datasets identifies the interaction of NS4B with dependency factors in neuroblastoma cells (red) and in GSC, hiPSC-NPC, HeLa and HEK293FT cells (collectively termed non-neuroblastoma cells, orange).To aid visualisation, any nodes possessing no high confidence interactions, other than their interaction with NS4B, have been grouped.All nodes within Figure7interact with NS4B, thus, to aid visualisation all edges between NS4B and nodes within a group have been condensed into a single edge between NS4B and the grouped set of nodes.ZIKV, Zika virus; NS4B, non-structural protein 4B; GSC, glioma stem cell.

Figure 8 .
Figure 8. Diagram of the proposed ZIKV life cycle in neuroblastoma cells (Step 1-5), with a summary of all the currently known dependencies that the virus has for infection of neuroblastoma cells.Highlighted are the three essential properties of an oncolytic virus; the production of fresh viral particles to infect additional cancer cells (A), the ability to induce cancer cell death (B) and a mechanism through which ZIKV may induce an anti-tumoral immune response (C).ZIKV, Zika virus; EMC, endoplasmic reticulum membrane protein complex; SREBP, sterol regulatory element binding protein; ER, endoplasmic reticulum; NS4B, non-structural protein 4B.

4 . 1 Reviewer
Is the work clearly and accurately presented and does it cite the current literature?PartlyIs the design appropriate and is the work technically sound?YesAre sufficient details of methods and analysis provided to allow replication by others?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?I cannot comment.A qualified statistician is required.Are all the source data underlying the results available to ensure full reproducibility?YesAre the conclusions drawn adequately supported by the results?YesCompeting Interests: No competing interests were disclosed.Reviewer Expertise: Proteomics, Cellular BiologyI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptablescientific standard, however I have significant reservations, as outlined above.Version Report 12 October 2023 https://doi.org/10.5256/f1000research.145561.r196248Estanislao Nistal-Villan Instituto de Medicina Molecular Aplicada (IMMA) Nemesio Díez, Facultad de Medicina, Universidad San Pablo-CEU, Boadilla del Monte, Spain Vicent Tur-Planells Universidad CEU San Pablo, Madrid, Community of Madrid, Spain Integrative transcriptomic and proteomic study of Zika viral infection potential mechanisms for oncolytic therapy in neuroblastoma.

○"○○
The neurotropism of the Asian lineage makes it the clear choice, over the African lineage, reviewer for the constructive critique of the manuscript.The intention of our study is to integrate and repurpose the multiple omics datasets that have been published the literature investigating how Zika infects mammalian cells.Many of these studies have used neuroblastoma cells as a model, and we therefore see this as an opportunity to study the potential oncolytic activity of the virus in neuroblastoma, which the original aforementioned studies did not.The reviewer points out that the analysis will be strengthened by validating the hypotheses with further lab-based studies -and we agree with this.However, our intention in this paper is to layout potential molecular mechanisms that are important in the oncolytic response that can be investigated by us and others going forward.We see our paper as an important first step in establishing potential mechanisms using data mining techniques that should stand alone in a field in which there are as yet relatively few studies.MAJOR POINTS • Authors should experimentally validate their bioinformatic-based hypothesis.The intent of the paper was to use in silico methods to identify molecular mechanisms involved in ZIKV infection of neuroblastoma cells.For many of the components that are highlighted by our integration and re-analysis of published datasets we have sourced and referenced functional experiments that support any propositions/conclusions which we make.Two representative examples of these include:We re-analyse RNA-Seq data of ZIKV-infected neuroblastoma cells and propose the SREBP pathway to be upregulated at the transcriptome level.We link this to data that regulation of this pathway through three different inhibitors hinders ZIKV infection in neuroblastoma cells, thus supporting the involvement of this pathway during infection.We use ZIKV dependency factor screens to propose that ZIKV infection is dependent on the ATPase for infection in neuroblastoma cells.We back this hypothesis up with data that shows the ATPase inhibitor Bafilomycin A1 inhibits ZIKV infection in neuroblastoma○MINOR POINTS• At the end of the introduction, the sentence: "Pediatric neuroblastoma, like pediatric brain tumors, are predominantly tumors of the nervous system consisting of cancerous cells with neural characteristics."Is redundant and not necessary.This sentence has been removed ○ • Authors should better describe the original data used for bioinformatic analysis.Papers that study the topic are presented, but the source of the data should be better described.Additional details have been added throughout the methods section to better describe the original data.A representative example is "Scaturro et al., produced this interactome through stable expression of HA-tagged ZIKV proteins in SK-N-BE2 cells, isolation of ZIKV-host protein complexes through HAaffinity purifications, then sample preparation and run for LC-MS/MS (n = 4).31 Raw data was processed using MaxQuant with Andromeda search engine.Highconfidence interactions were determined by Bayesian statistical modelling, with log2(fold ≥ 2.5; unadjusted one-sided P ≤ 0.05."

the reference for the publication from which the data has come from ○Fig 1 .
Fig 1D and 2A are entirely too small for anyone to read.These should be expanded and used a separate figures, so as to allow a reader to see the results.1.

Table 1 .
ZIKV infects and reduces cell viability in a multitude of paediatric neuroblastoma cell lines.Cell lines are ranked by the degree to which ZIKV infection reduces their cell viability.Cell viability assay reagent/marker used in the original assay is stated with its accompanying reference.Note: ZIKV, Zika virus; MYCN, MYCN Proto-Oncogene; NA, not applicable.

Table 2 .
Different ZIKV strains demonstrate varying therapeutic potential against paediatric neuroblastoma cells.ZIKV strains are ranked by their ability to infect (Degree of Infection), replicate within (Viral Titer) and significantly reduce the cell viability (Cell Viability) of a multitude of neuroblastoma cells.The Data accordance is a qualitative measure which we employed to describe the degree of similarity of the results between publications that performed ZIKV infection assays of neuroblastoma cells using the same ZIKV strain.Data accordance of five denotes that the findings of one publication closely support the findings from another, a data accordance of one denotes publications reporting vastly contrasting results.When a viral strain is published in only one paper, it is allocated a data accordance of NA.ZIKV, Zika virus; NA, not applicable.

Table 3
. ZIKV infection in neuroblastoma cells can be regulated through modifying lipid abundance, composition and localisation.List of compounds that regulate lipid homeostasis and are capable of restricting or enhancing ZIKV infection in paediatric neuroblastoma cells.ZIKV, Zika virus; LXR, liver X receptor; SREBP, sterol regulatory element binding protein; DHA, docosahexaenoic acid.

Table 1 and
The neurotropism of the Asian lineage makes it the clear choice, over the African lineage, for ZIKV oncolytic virotherapy against brain tumors" needs citation.Table2, it is necessary to say in which in vitro viability test is based on the assay (metabolic, death markers, etc.)The ○• "○ • In

details of the assays have now been added to both tables
○• In

Table 2 ,
the degree of infection, viral titer, and cell viability, is it normalized with the same MOI, and cancer cell type?Which cancer cell type?Would be better to explain how the authors establish the Data accordance value.No

has been changed to "We propose that lipid abundance, localisation, trafficking and metabolism regulate ZIKV infection of neuroblastoma cells, and that of the cellular lipid composition within the host cell may produce a favourable environment for efficient replication."
effects, and that has not been proved.It could be changed by "ZIKV infection induces all those changes…" Sentence ○ Competing Interests: No competing interests were disclosed.Reviewer Report 17 August 2023 https://doi.org/10.5256/f1000research.145561.r184590© 2023 Parks G.This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.