The impact of short-term changes in sleeping and eating patterns on glucometabolic health and gut microbiota in healthy young adults: a proof-of-concept controlled feeding study

Epidemiological studies showed that night workers are at higher risk of developing chronic metabolic diseases.However,no study has investigated the changes in circadian rhythms caused by a combined effect of sleep and diet in a real-life setting on cardiometabolic health,gut microbiota,and psychological status in healthy people.A 4-week step-wise misaligned-realigned controlled-feeding trial with a 2×2 factorial design(sleep and diet)was conducted on healthy young adults.At first,subjects experienced a one-week circadian rhythm misalignment with a high-fat fast-food diet,extended eating window,and delayed sleep schedules,then gradually transited to a complete circadian rhythm realignment with a high-fiber balanced diet,8-h timerestricted eating,and normal sleep schedules.Circadian rhythm misalignment led to significantly higher levels of fasting glucose and homeostatic model assessment for insulin resistance(HOMA-IR)of subjects compared to baseline and failed to recover to the baseline level in circadian rhythm realignments.Notably,the incremental area under the curve(iAUC)of postprandial glucose decreased with circadian rhythm adjustments as compared to that in circadian rhythm misalignment,suggesting circadian rhythm realignment by sleep or/and diet could partly restore glucose metabolism impaired by a short-term circadian rhythm misalignment.However,circadian rhythm changes did not result in overall perturbations of gut microbiota diversities.

Comparison analysis of multiple-omics data between female germline stem cells and spermatogonial stem cells

Female germline stem cells(FGSCs)and spermatogonial stem cells(SSCs)are germline stem cells that transmit the genetic material from generation to generation.Hence,it is essential to understand the similarities and differences between FGSCs and SSCs.In this study,we comprehensively compared the epigenetics of FGSCs and SSCs,including high-order chromatin organization,chromatin histone modification,and transcriptome by analyzing multiple-omics data(Hi-C,ChIP-seq,and RNA-seq).

Transmission risk of asymptomatic SARS-CoV-2 infection:a systematic review and meta-analysis

Background:Global evidence on the transmission of asymptomatic SARS-CoV-2 infection needs to be synthesized.Methods:A search of 4 electronic databases(PubMed,EMBASE,Cochrane Library,and Web of Science databases)as of January 24,2021 was performed.Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines were followed.Studies which reported the transmission rate among close contacts with asymptomatic SARS-CoV-2 cases were included,and transmission activities occurred were considered.The trans-mission rates were pooled by zero-inflated beta distribution.The risk ratios(RRs)were calculated using random-effects models.Results:Of 4923 records retrieved and reviewed,15 studies including 3917 close contacts with asymptomatic indexes were eligible.The pooled transmission rates were 1.79 per 100 person-days(or 1.79%,95%confidence interval[CI]0.41%-3.16%)by asymptomatic index,which is significantly lower than by presymptomatic(5.02%,95%CI 2.37%-7.66%;p<0.001),and by symptomatic(5.27%,95%CI 2.40%-8.15%;p<0.001).Subgroup anal-yses showed that the household transmission rate of asymptomatic index was(4.22%,95%CI 0.91%-7.52%),four times significantly higher than non-household transmission(1.03%,95%CI 0.73%-1.33%;p=0.03),and the asymptomatic transmission rate in China(1.82%,95%CI 0.11%-3.53%)was lower than in other countries(2.22%,95%CI 0.67%-3.77%;p=0.01).Conclusions:People with asymptomatic SARS-CoV-2 infection are at risk of transmitting the virus to their close contacts,particularly in household settings.The transmission potential of asymptomatic infection is lower than symptomatic and presymptomatic infections.This meta-analysis provides evidence for predict-ing the epidemic trend and promulgating vaccination and other control measures.Registered with PROS-PERO International Prospective Register of Systematic Reviews,CRD42021269446;https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=269446.

Systems biology and metagenomics: a showcase of Chinese bioinformatics researchers and their work

It is our great honor to guest-edit this Thematic Issue on Bioinformatics in Science China Life Sciences. In recent years, a strong cohort of Chinese scientists has emerged as leading scholars in the exciting fields of bioinforrnatics and computational biology. In this issue, we are pleased to pre- sent outstanding research work produced from 10 world renowned researchers.

Genetic polymorphisms predict response to anti-tumor necrosis factor treatment in Crohn's disease

To investigate genetic factors that might help define which Crohn’s disease (CD) patients are likely to benefit from anti-tumor necrosis factor (TNF) therapy. METHODSThis was a prospective cohort study. Patients were recruited from a university digestive disease practice database. We included CD patients who received anti-TNF therapy, had available medical records (with information on treatment duration and efficacy) and who consented to participation. Patients with allergic reactions were excluded. Patients were grouped as ever-responders or non-responders. Genomic DNA was extracted from peripheral blood, and 7 single nucleotide polymorphisms (SNPs) were assessed. The main outcome measure (following exposure to the drug) was response to therapy. The patient genotypes were assessed as the predictors of outcome. Possible confounders and effect modifiers included age, gender, race, and socioeconomic status disease, as well as disease characteristics (such as Montreal criteria). RESULTS121 patients were included. Twenty-one were non-responders, and 100 were ever-responders. Fas ligand SNP (rs763110) genotype frequencies, TNF gene -308 SNP (rs1800629) genotype frequencies, and their combination, were significantly different between groups on multivariable analysis controlling for Montreal disease behavior and perianal disease. The odds of a patient with a Fas ligand CC genotype being a non-responder were four-fold higher as compared to a TC or TT genotype (P = 0.009, OR = 4.30, 95%CI: 1.45-12.80). The presence of the A (minor) TNF gene -308 allele correlated with three-fold higher odds of being a non-responder (P = 0.049, OR = 2.88, 95%CI: 1.01-8.22). Patients with the combination of the Fas ligand CC genotype and the TNF -308 A allele had nearly five-fold higher odds of being a non-responder (P = 0.015, OR = 4.76, 95%CI: 1.35-16.77). No difference was seen for the remaining SNPs. CONCLUSIONThe Fas-ligand SNP and TNF gene -308 SNP are associated with anti-TNF treatment response in CD and may help select patients likely to benefit from therapy.

Drug repurposing for cancer treatment through global propagation with a greedy algorithm in a multilayer network

Objective:Drug repurposing,the application of existing therapeutics to new indications,holds promise in achieving rapid clinical effects at a much lower cost than that of de novo drug development.The aim of our study was to perform a more comprehensive drug repurposing prediction of diseases,particularly cancers.Methods:Here,by targeting 4,096 human diseases,including 384 cancers,we propose a greedy computational model based on a heterogeneous multilayer network for the repurposing of 1,419 existing drugs in Drug Bank.We performed additional experimental validation for the dominant repurposed drugs in cancer.Results:The overall performance of the model was well supported by cross-validation and literature mining.Focusing on the top-ranked repurposed drugs in cancers,we verified the anticancer effects of 5 repurposed drugs widely used clinically in drug sensitivity experiments.Because of the distinctive antitumor effects of nifedipine(an antihypertensive agent)and nortriptyline(an antidepressant drug)in prostate cancer,we further explored their underlying mechanisms by using quantitative proteomics.Our analysis revealed that both nifedipine and nortriptyline affected the cancer-related pathways of DNA replication,the cell cycle,and RNA transport.Moreover,in vivo experiments demonstrated that nifedipine and nortriptyline significantly inhibited the growth of prostate tumors in a xenograft model.Conclusions:Our predicted results,which have been released in a public database named The Predictive Database for Drug Repurposing(PAD),provide an informative resource for discovering and ranking drugs that may potentially be repurposed for cancer treatment and determining new therapeutic effects of existing drugs.

Treatment outcomes of HIV patients with hepatitis B and C virus co-infections in Southwest China:an observational cohort study

Background:Antiretroviral therapy(ART)has reduced mortality among people living with HIV(PLWH)in China,but co-infections of hepatitis B virus(HBV)and hepatitis C virus(HCV)may individually or jointly reduce the effect of ART.This study aimed to evaluate the impacts of HBV/HCV coinfections on treatment drop-out and mortality among PLWH on ART.Methods:A retrospective cohort study analysis of 58,239 people living with HIV(PLWH)who initiated antiretroviral therapy(ART)during 2010-2018 was conducted in Guangxi Province,China.Data were from the observational database of the National Free Antiretroviral Treatment Program.Cox proportional hazard models were fitted to evaluate the effects of baseline infection of HBV or HCV or both on death and treatment attrition among PLWH.Results:Our study showed high prevalence of HBV(11.5%),HCV(6.6%)and HBV-HCV(1.5%)co-infections.The overall mortality rate and treatment attrition rate was 2.95[95%confidence interval(CI):2.88-3.02]and 5.92(95%CI:5.82-6.01)per 100 person-years,respectively.Compared with HIV-only patients,HBV-co-infected patients had 42%higher mortality[adjusted hazard ratio(a HR)=1.42;95%CI 1.32-1.54],HCV-co-infected patients had 65%higher mortality(a HR=1.65;95%CI:1.47-1.86),and patients with both HCV and HBV co-infections had 123%higher mortality(a HR=2.23;95%CI:1.87-2.66).Conclusions:HBV and HCV coinfection may have an additive effect on increasing the risk of all-cause death among PLWH who are on ART.It is suggested that there is need for primary prevention and access to effective hepatitis treatment for PLWH.

The structure of phospholamban and its MD simulations

Phospholamban is an important protein with responsibility for regulating the activity of the sarcoplasmic reticulum Ca2+ pump through reversible phosphorylation.And its three-dimensional structure in living cell has been a focus of attention.In the current case, we summarized the investigations on phospholamban structure, and on this base, employed long time-scale molecular dy-namics simulations to study its structure systematically.The first 22 residues from one chain of phospholamban in bellflower structure determined by NMR experiments, together with its phosphorylation at position 16 and mutation at position 9 were picked up as three different systems.By molecular dynamics simulations of 10 ns in the explicit solution surroundings, it was found that the 3–15 residues of the original structure retained their helix structures, while the phosphorylation and mutation had less probability to form helix structures.These structural changes might result in inhibition decrease to the sarcoplasmic reticulum Ca2+ pump, which is in accordance with previous experimental results.

Individualized red-cell transfusion strategy for non-cardiac surgery in adults:a randomized controlled trial

Background:Red-cell transfusion is critical for surgery during the peri-operative period;however,the transfusion threshold remains controversial mainly owing to the diversity among patients.The patient’s medical status should be evaluated before making a transfusion decision.Herein,we developed an individualized transfusion strategy using the West-China-Liu’s Score based on the physiology of oxygen delivery/consumption balance and designed an open-label,multicenter,randomized clinical trial to verify whether it reduced red cell requirement as compared with that associated with restrictive and liberal strategies safely and effectively,providing valid evidence for peri-operative transfusion.Methods:Patients aged>14 years undergoing elective non-cardiac surgery with estimated blood loss>1000 mL or 20%blood volume and hemoglobin concentration<10 g/dL were randomly assigned to an individualized strategy,a restrictive strategy following China’s guideline or a liberal strategy with a transfusion threshold of hemoglobin concentration<9.5 g/dL.We evaluated two primary outcomes:the proportion of patients who received red blood cells(superiority test)and a composite of in-hospital complications and all-cause mortality by day 30(non-inferiority test).Results:We enrolled 1182 patients:379,419,and 384 received individualized,restrictive,and liberal strategies,respectively.Approximately 30.6%(116/379)of patients in the individualized strategy received a red-cell transfusion,less than 62.5%(262/419)in the restrictive strategy(absolute risk difference,31.92%;97.5%confidence interval[CI]:24.42-39.42%;odds ratio,3.78%;97.5%CI:2.70-5.30%;P<0.001),and 89.8%(345/384)in the liberal strategy(absolute risk difference,59.24%;97.5%CI:52.91-65.57%;odds ratio,20.06;97.5%CI:12.74-31.57;P<0.001).No statistically significant differences were found in the composite of in-hospital complications and mortality by day 30 among the three strategies.Conclusion:The individualized red-cell transfusion strategy using the West-China-Liu’s Score reduced red-cell transfusion without increasing in-hospital complications and mortality by day 30 when compared with restrictive and liberal strategies in elective non-cardiac surgeries.Trial registration:ClinicalTrials.gov,NCT01597232.

Computational prediction and functional analysis of arsenic-binding proteins in human cells

Background:Arsenic has a broad anti-cancer ability against hematologic malignancies and solid tumors.To systematically understand the biological functions of arsenic,we need to identify arsenic-binding proteins in human cells.However,due to lack of effective theoretical tools and experimental methods,only a few arsenic-binding proteins have been identified.Methods:Based on the crystal structure of ArsM,we generated a single mutation free energy profile for arsenic binding using free energy perturbation methods.Multiple validations provide an indication that our computational model has the ability to predict arsenic-binding proteins with desirable accuracy.We subsequently apply this computational model to scan the entire human genome to identify all the potential arsenic-binding proteins.Results:The computationally predicted arsenic-binding proteins show a wide range of biological functions,especially in the signaling transduction pathways.In the signaling transduction pathways,arsenic directly binds to the key factors(e.g.,Notch receptors,Notch ligands,Wnt family proteins,TGF-beta,and their interacting proteins)and results in significant inhibitions on their enzymatic activities,further having a crucial impact on the related signaling pathways.Conclusions:Arsenic has a significant impact on signaling transduction in cells.Arsenic binding to proteins can lead to dysfunctions of the target proteins,having crucial impacts on both signaling pathway and gene transcription.We hope that the computationally predicted arsenic-binding proteins and the functional analysis can provide a novel insight into the biological functions of arsenic,revealing a mechanism for the broad anti-cancer of arsenic.

Thromboembolic events in metastatic testicular cancer treated with cisplatin-based chemotherapy

BACKGROUND Testicular germ cell tumor(TGCT)is the most curable solid tumor and most common cancer among men 18-39 years.While cisplatin-based chemotherapy has significantly lengthened the survival of patients with TGCT,it is associated with a high rate of thromboembolic events(TEE).AIM To summarize our single-center experience highlighting patients who were diagnosed with TGCT and received platinum-based chemotherapy,with special attention to those patients who suffered a TEE.METHODS A retrospective analysis of the medical records and imaging studies of 68 consecutive individuals who were diagnosed with TGCT and received platinumbased chemotherapy at our Institution in a metropolitan community between January 1,2014 and December 31,2019.RESULTS A total of 19(28%)patients experienced a TEE following orchiectomy which occurred during chemotherapy in 13(68%)of these patients.Patients with a higher pathologic stage(stage III)were significantly(P=0.023)more likely to experience a TEE compared to patients who had a lower stage.Additionally,patients who were treated with 3 cycles of bleomycine,etoposide,and cisplatin and 1 cycle of etoposide and cisplatin or 4 cycles of etoposide and cisplatin were significantly 5(P=0.02)times more likely to experience a TEE compared to patients who were treated with only 3 cycles of bleomycine,etoposide,and cisplatin.CONCLUSION Due to numerous factors that predispose to a TEE such as large retroperitoneal disease,higher clinical stage,greater number of chemotherapy cycle,central venous catheter,cigarette smoking,and possible cannabis use,high-risk ambulatory patients with TGCT treated with cisplatin-based chemotherapy may benefit from prophylactic anticoagulation.Randomized studies to evaluate the safety and efficacy of prophylactic anticoagulants are warranted in this young patient population generally devoid of medical co-morbidities.

Synthesis,Characterization,Biological and Docking Simulations of 4-(Benzylideneamino) Benzoic Acids

The present research paper presents the synthesis, characterization, biological and computational studies of 4-(benzylideneamino) benzoic acid derivatives(3a~3g). Derivatives 3a~3c displayed best antidiabetic potential with a glucose-lowering effect compared to the reference drug Glibenclamide. Biochemical parameters including plasma glucose, serum triglycerides, cholesterol, alanine amino transferase and aspartate amino transferase levels showed significant alterations in concentrations relative to the control. Similarly, the derivatives 3a, 3d and 3e displayed potent in vitro antibacterial potential. Molecular docking simulations delineated that the ligands and complexes were stabilized at the active site by electrostatic and hydrophobic forces, consistent with the corresponding experimental results. In silico study of the binding pattern predicted that the synthesized ligands, 3d and 3a could serve as a potential surrogate for hit-to-lead generation and the design of novel antibacterial drugs.

SysFinder：A customized platform for search,comparison and assisted design of appropriate animal models based on systematic similarity

Animal models are increasingly gaining values by cross-comparisons of response or resistance to clinical agents used for patients.However,many disease mechanisms and drug effects generated from animal models are not transferable to human.To address these issues,we developed SysFinder（http：//lifecenter.sgst.cn/SysFinder）,a platform for scientists to find appropriate animal models for translational research.SysFinder offers a ＂topic-centered＂ approach for systematic comparisons of human genes,whose functions are involved in a specific scientific topic,to the corresponding homologous genes of animal models.Scientific topic can be a certain disease,drug,gene function or biological pathway.SysFinder calculates multi-level similarity indexes to evaluate the similarities between human and animal models in specified scientific topics.Meanwhile,SysFinder offers species-specific information to investigate the differences in molecular mechanisms between humans and animal models.Furthermore,SysFinder provides a userfriendly platform for determination of short guide RNAs（sgRNAs） and homology arms to design a new animal model.Case studies illustrate the ability of SysFinder in helping experimental scientists.SysFinder is a useful platform for experimental scientists to carry out their research in the human molecular mechanisms.

Comprehensive Analysis of Ubiquitously Expressed Genes in Humans from A Data-driven Perspective

Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanisms of human diseases.Ubiquitously expressed genes(UEGs)refer to the genes expressed across a majority of,if not all,phenotypic and physiological conditions of an organism.It is known that many human genes are broadly expressed across tissues.However,most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns,thus limiting the potential use of UEG information.In this study,we proposed a novel data-driven framework to leverage the extensive collection of40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns,which offers a valuable resource to further characterize human transcriptome.Our results suggest that about half(12,234;49.01%)of the human genes are expressed in at least 80%of human transcriptomes,and the median size of the human transcriptome is 16,342 genes(65.44%).Through gene clustering,we identified a set of UEGs,named LoVarUEGs,which have stable expression across human transcriptomes and can be used as internal reference genes for expression measurement.To further demonstrate the usefulness of this resource,we evaluated the global expression patterns for 16 previously predicted disallowed genes in islet beta cells and found that seven of these genes showed relatively more varied expression patterns,suggesting that the repression of these genes may not be unique to islet beta cells.

Staged-probability strategy of processing shotgun proteomic data to discover more functionally important proteins

Biologically important proteins related to membrane receptors,signal transduction,regulation,transcription,and translation are usually low in abundance and identified with low probability in mass spectroscopy(MS)-based analyses.Most valuable proteomics information on them were hitherto discarded due to the application of excessively strict data filtering for accurate identification.In this study,we present a stagedprobability strategy for assessing proteomic data for potential functionally important protein clues.MS-based protein identifications from the second(L2)and third(L3)layers of the cascade affinity fractionation using the Trans-Proteomic Pipeline software were classified into three probability stages as 1.00–0.95,0.95–0.50,and 0.50–0.20 according to their distinctive identification correctness rates(i.e.100%–95%,95%–50%,and 50%–20%,respectively).We found large data volumes and more functionally important proteins located at the previously unacceptable lower probability stages of 0.95–0.50 and 0.50–0.20 with acceptable correctness rate.More importantly,low probability proteins in L2 were verified to exist in L3.Together with some MS spectrogram examples,comparisons of protein identifications of L2 and L3 demonstrated that the stagedprobability strategy could more adequately present both quantity and quality of proteomic information,especially for researches involving biomarker discovery and novel therapeutic target screening.

RePhine: An Integrative Method for Identification of Drug Response-related Transcriptional Regulators

Transcriptional regulators(TRs)participate in essential processes in cancer pathogenesis and are critical therapeutic targets.Identification of drug response-related TRs from cell line-based compound screening data is often challenging due to low m RNA abundance of TRs,protein modifications,and other confounders(CFs).In this study,we developed a regression-based pharmacogenomic and Ch IP-seq data integration method(Re Phine)to infer the impact of TRs on drug response through integrative analyses of pharmacogenomic and Ch IP-seq data.Re Phine was evaluated in simulation and pharmacogenomic data and was applied to pan-cancer datasets with the goal of biological discovery.In simulation data with added noises or CFs and in pharmacogenomic data,Re Phine demonstrated an improved performance in comparison with three commonly used methods(including Pearson correlation analysis,logistic regression model,and gene set enrichment analysis).Utilizing Re Phine and Cancer Cell Line Encyclopedia data,we observed that Re Phinederived TR signatures could effectively cluster drugs with different mechanisms of action.Re Phine predicted that loss-offunction of EZH2/PRC2 reduces cancer cell sensitivity toward the BRAF inhibitor PLX4720.Experimental validation confirmed that pharmacological EZH2 inhibition increases the resistance of cancer cells to PLX4720 treatment.Our results support that Re Phine is a useful tool for inferring drug response-related TRs and for potential therapeutic applications.The source code for Re Phine is freely available at https://github.com/coexps/Re Phine.

Proteomics and metabolic phenotyping define principal roles for the aryl hydrocarbon receptor in mouse liver

Dioxin-like molecules have been associated with endocrine disruption and liver disease.To better understand aryl hydrocarbon receptor(AHR)biology,metabolic phenotyping and liver proteomics were performed in mice following ligand-activation or whole-body genetic ablation of this receptor.Male wild type(WT)and Ahr^(-/-) mice(Taconic)were fed a control diet and exposed to 3,3',4,4',5-pentachlorobiphenyl(PCB126)(61 nmol/kg by gavage)or vehicle for two weeks.PCB126 increased expression of canonical AHR targets(Cyp1 a1 and Cyp1 a2)in WT but not Ahr^(-/-).Knockouts had increased adiposity with decreased glucose tolerance;smaller livers with increased steatosis and perilipin-2;and paradoxically decreased blood lipids.PCB126 was associated with increased hepatic triglycerides in Ahr^(-/-).The liver proteome was impacted more so by Ahr^(-/-) genotype than ligandactivation,but top gene ontology(GO)processes were similar.The PCB126-associated liver proteome was Ahr-dependent.Ahr principally regulated liver metabolism(e.g.,lipids,xenobiotics,organic acids)and bioenergetics,but it also impacted liver endocrine response(e.g.,the insulin receptor)and function,including the production of steroids,hepatokines,and pheromone binding proteins.These effects could have been indirectly mediated by interacting transcription factors or microRNAs.The biologic roles of the AHR and its ligands warrant more research in liver metabolic health and disease.

NetGO 3.0:Protein Language Model Improves Large-scale Functional Annotations

As one of the state-of-the-art automated function prediction(AFP)methods,NetGO 2.0 integrates multi-source information to improve the performance.However,it mainly utilizes the proteins with experimentally supported functional annotations without leveraging valuable information from a vast number of unannotated proteins.Recently,protein language models have been proposed to learn informative representations[e.g.,Evolutionary Scale Modeling(ESM)-1b embedding] from protein sequences based on self-supervision.Here,we represented each protein by ESM-1b and used logistic regression(LR)to train a new model,LR-ESM,for AFP.The experimental results showed that LR-ESM achieved comparable performance with the best-performing component of NetGO 2.0.Therefore,by incorporating LR-ESM into NetGO 2.0,we developed NetGO 3.0 to improve the performance of AFP extensively.

SPA: A Quantitation Strategy for MS Data in Patient-derived Xenograft Models

With the development of mass spectrometry(MS)-based proteomics technologies,patient-derived xenograft(PDX),which is generated from the primary tumor of a patient,is widely used for the proteome-wide analysis of cancer mechanism and biomarker identification of a drug.However,the proteomics data interpretation is still challenging due to complex data deconvolution from the PDX sample that is a cross-species mixture of human cancerous tissues and immunodeficient mouse tissues.In this study,by using the lab-assembled mixture of human and mouse cells with different mixing ratios as a benchmark,we developed and evaluated a new method,SPA(shared peptide allocation),for protein quantitation by considering the unique and shared peptides of both species.The results showed that SPA could provide more convenient and accurate protein quantitation in human–mouse mixed samples.Further validation on a pair of gastric PDX samples(one bearing FGFR2 amplification while the other one not)showed that our new method not only significantly improved the overall protein identification,but also detected the differential phosphorylation of FGFR2 and its downstream mediators(such as RAS and ERK)exclusively.The tool pdx SPA is freely available at https://github.com/LiLab-Proteomics/pdx SPA.

Different Gene Networks Are Disturbed by Zika Virus Infection in A Mouse Microcephaly Model

The association of Zika virus(ZIKV)infection with microcephaly has raised alarm worldwide.Their causal link has been confirmed in different animal models infected by ZIKV.However,the molecular mechanisms underlying ZIKV pathogenesis are far from clear.Hence,we performed global gene expression analysis of ZIKV-infected mouse brains to unveil the biological and molecular networks underpinning microcephaly.We found significant dysregulation of the sub-networks associated with brain development,immune response,cell death,microglial cell activation,and autophagy amongst others.We provided detailed analysis of the related complicated gene networks and the links between them.Additionally,we analyzed the signaling pathways that were likely to be involved.This report provides systemic insights into not only the pathogenesis,but also a path to the development of prophylactic and therapeutic strategies against ZIKV infection.