Biology subjects

Ma, H.

Publications and source records attributed to Ma, H..

At least 127 records · Page 7Linked to original sources

bioRxiv2023

CytoSIP: An annotated structural atlas for interactions involving cytokine or cytokine receptor

Cytokines primarily interact with specific cytokine receptors on the cell surface as essential signal transduction pathways in many physiological and pathological processes. Therapeutic agents targeting cytokine-cytokine receptor (CK-CKR) interactions lead to the disruption in cellular signaling function and have been demonstrated effective in the treatment of many diseases including tumors. However, a lack of universal and quick access to annotated structural surface regions on CK/CKR has limited the progress of a structure-driven approach to the development of targeted macromolecular drugs and precision medicine therapeutics. Herein we develop CytoSIP (Single nucleotide polymorphisms (SNPs), Interface, and Phenotype), a rich internet application based on a database of atomic interactions around hotspots in experimentally determined CK/CKR structural complexes. The content of the CytoSIP database includes the following key features: (1) SNPs on CK/CKR; (2) interactions involving CK/CKR at the domain level, including CK/CKR interfaces, oligomeric interfaces, epitopes, or other drug targeting surfaces; and (3) diseases and phenotypes associated with CK/CKR or SNPs. The database introduces a unique tri-level SIP data model to link genetic variants (atomic level) to disease phenotypes (organism level) using protein structure (complexes) as an underlying framework (molecule level). Moreover, CytoSIP implements screening criteria and tools to allow customized selection of relevant subset of CK/CKR for the study of interest. This reduces the time and resources needed to interrogate large datasets and allows rapid screening of cytokines and cytokine receptor proteins interfaces for hotspots targeted drug design and any other specific cellular signaling/function mechanisms and their correlation to pathologies. The CytoSIP framework crafted herein bridges CK/CKR genotype with phenotype, facilitating not only the panoramic investigation of the context-dependent crosstalk between CK/CKR but also the development of targeted therapeutic agents. CytoSIP portal website is publicly accessible at https://CytoSIP.biocloud.top.

immunology↗

bioRxiv2023

Identification of bioactive constituents for colitis from traditional Chinese medicine prescription via deep neural network

Colitis is a commonly encountered inflammatory disease in colon tissue, which can be triggered by various causes. Although traditional Chinese medicine (TCM) has been utilized for the treatment of colitis, it is still a great challenge to identify the major bioactive constituents and their modes of action among thousands of ingredients in TCM prescriptions. Inspired by the success of artificial intelligence and deep learning methods, we proposed a deep neural network (DNN) for TCM prescription recommendation. We constructed a graph-based DNN with 9,845 nodes and 161,950 edges, which integrated microscopic information including bioactive molecules, protein targets, and extracted features of prescriptions through feature embedding. A novel and efficient data augmentation strategy was implemented to expand the sample size based on 378 collected TCM prescriptions. Network pharmacology study revealed that the 10 most frequent ingredients in generated prescriptions were associated with multiple inflammatory signaling pathways. To verify the bioactive constituents in the generated prescriptions, 5 selected constituents were administrated to BALB/c mice with colitis. Suppressive effects of disease progression and pro-inflammatory factors comparable to sulfasalazin were observed with these compounds, revealing the effectiveness of our artificial intelligence strategy on idetification of bioactive constituents from TCM prescriptions.

bioinformatics↗

bioRxiv2023

Pathformer: biological pathway informed Transformer model integrating multi-modal data of cancer

Multi-omics data provide a comprehensive view of gene regulation at multiple levels, which is helpful in achieving accurate diagnosis of complex diseases like cancer. To integrate various multi-omics data of tissue and liquid biopsies for disease diagnosis and prognosis, we developed a biological pathway informed Transformer, Pathformer. It embeds multi-omics input with a compacted multi-modal vector and a pathway-based sparse neural network. Pathformer also leverages criss-cross attention mechanism to capture the crosstalk between different pathways and modalities. We first benchmarked Pathformer with 18 comparable methods on multiple cancer datasets, where Pathformer outperformed all the other methods, with an average improvement of 6.3%-14.7% in F1 score for cancer survival prediction and 5.1%-12% for cancer stage prediction. Subsequently, for cancer prognosis prediction based on tissue multi-omics data, we used a case study to demonstrate the biological interpretability of Pathformer by identifying key pathways and their biological crosstalk. Then, for cancer early diagnosis based on liquid biopsy data, we used plasma and platelet datasets to demonstrate Pathformers potential of clinical applications in cancer screen. Moreover, we revealed deregulation of interesting pathways (e.g., scavenger receptor pathway) and their crosstalk in cancer patients blood, providing new candidate targets for cancer microenvironment study.

bioinformatics↗

bioRxiv2023

Tailored chemical reactivity probes for systemic imaging of aldehydes in fibroproliferative diseases

During fibroproliferation, protein-associated extracellular aldehydes are formed by the oxidation of lysine residues on extracellular matrix proteins to form the aldehyde allysine. Here we report three Mn(II)-based, small molecule magnetic resonance (MR) probes that contain -effect nucleophiles to target allysine in vivo and report on tissue fibrogenesis. We used a rational design approach to develop turn-on probes with a 4-fold increase in relaxivity upon targeting. The effects of aldehyde condensation rate and hydrolysis kinetics on the performance of the probes to detect tissue fibrogenesis noninvasively in mouse models were evaluated by a systemic aldehyde tracking approach. We showed that for highly reversible ligations, off-rate was a stronger predictor of in vivo efficiency, enabling histologically validated, three-dimensional characterization of pulmonary fibrogenesis throughout the entire lung. The exclusive renal elimination of these probes allowed for rapid imaging of liver fibrosis. Reducing the hydrolysis rate by forming an oxime bond with allysine enabled delayed phase imaging of kidney fibrogenesis. The imaging efficacy of these probes, coupled with their rapid and complete elimination from the body, make them strong candidates for clinical translation.

biochemistry↗

bioRxiv2023

Spatiotemporal Genomic Profiling of Intestinal Metaplasia Reveals Clonal Dynamics of Gastric Cancer Progression

Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. We analyzed 1256 gastric samples (1152 IMs) from 692 subjects through a prospective 10-year study. We identified 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9), largely occurring as small clonal events. Analysis of clonal dynamics between and within subjects, and also longitudinally across time, revealed that IM clones are likely transient but increase in size upon progression to dysplasia, with eventual transmission of somatic events to paired GCs. Single-cell and spatial profiling highlighted changes in tissue ecology and lineage heterogeneity in IM, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling revealed expression-based molecular subtypes of IM, including a body-resident "pseudoantralized" subtype associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical- genomic models outperform clinical-only models in predicting IMs likely to progress. Our results raise opportunities for GC precision prevention and interception by highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression.

cancer biology↗

bioRxiv2023

Nucleolar structure connects with global nuclear organization

The nucleolus is a multi-functional nuclear body. To tease out the roles of nucleolar structure without resorting to multi-action drugs, we knocked down RNA polymerase I subunit RPA194 in HeLa cells by siRNA. Loss of RPA194 resulted in nucleolar structural segregation and effects on both nucleolus-proximal and distal nuclear components. The perinucleolar compartment was disrupted, centromere-nucleolus interactions were significantly reduced, and the intranuclear locations of specific genomic loci were altered. Moreover, Cajal bodies, distal from nucleoli, underwent morphological and compositional changes. To distinguish whether these global reorganizations are the results of nucleolar structural disruption or inhibition of ribosome synthesis, the pre-ribosomal RNA processing factor, UTP4, was also knocked down, which did not lead to nucleolar segregation, nor the intranuclear effects seen with RPA195A knockdown, demonstrating that they do not arise from a cessation of ribosome synthesis. These findings point to a commutative system that links nucleolar structure to the maintenance and spatial organization of certain nuclear bodies and genomic loci.

cell biology↗

bioRxiv2023

standard-GEM: standardization of open-source genome-scale metabolic models

The field of metabolic modelling at the genomescale continues to grow with more models being created and curated. This comes with an increasing demand for adopting common principles regarding transparency and versioning, in addition to standardisation efforts regarding file formats, annotation and testing. Here, we present a standardised template for git-based and GitHub-hosted genome-scale metabolic models (GEMs) supporting both new models and curated ones, following FAIR principles (findability, accessibility, interoperability, and reusability), and incorporating bestpractices. standard-GEM facilitates the reuse of GEMs across web services and platforms in the metabolic modelling field and enables automatic validation of GEMs. The use of this template for new models, and its adoption for existing ones, paves the way for increasing model quality, openness, and accessibility with minimal effort. Availabilitystandard-GEM is available from github.com/MetabolicAtlas/standard-GEM under the conditions of the CC BY 4.0 licence along with additional supporting material.

systems biology↗

bioRxiv2023

Hepatic conversion of acetyl-CoA to acetate plays crucial roles in energy stresses

Accumulating evidences indicate that acetate is increased in energy stresses such as diabetes mellitus and prolonged starvation. However, it is largely unknown how and where acetate is produced and what is its biological significance. We observed overproduction of acetate in an amount comparable to ketone bodies in patients and mice with diabetes or starvation. Mechanistically, ACOT 12&8 are dramatically upregulated in liver to convert FFA-derived acetyl-CoA to acetate and CoA. This conversion not only provides large amount of acetate which fuels brain preferentially rather than muscle, but also recycles CoA which is required for sustained fatty acid oxidation and ketogenesis. Taken together, we suggest that acetate is an emerging novel "ketone body" and may be used as a parameter to evaluate the progression of energy stress in the future.

biochemistry↗

bioRxiv2023

The cryptic step in biogeochemical Tellurium (Te) cycle: Indirect elementary Te oxidation mediated by manganese-oxidizing bacterium (MnOB)

Tellurium (Te) is a rare element in the chalcogen group, and its biogeochemical cycle has been investigated for decades. As the most soluble Te species, tellurite (Te(IV)) possess the highest toxicity to the organisms. Chemical or biological Te(IV) reduction to elemental tellurium (Te0) is generally considered as an effective detoxification route for Te(IV)-containing wastewater. Here, we reported a previously overlooked Te0 oxidation process mediated by manganese-oxidizing bacterium Bacillus sp. FF-1. This strain has both Mn(II)-oxidizing and Te(IV)-reducing activities, which could produce manganese oxides (BioMnOx) and Te0 (BioTe0) when incubating with Mn(II) and Te(IV), respectively. Te(IV) can co-precipitated with Mn(II) to form highly stable Te(IV)-Mn(II) compounds with low bioavailability. While when 5 mM Mn(II) was added after incubating 0.1 mM or 1 mM Te(IV) with strain FF-1 for 16 hours, the BioTe0 were certainly re-oxidized to Te(IV) by BioMnOx according to the results of X-ray photoelectron spectra (XPS) and Transmission electron microscope (TEM). The chemogenic and exogenous biogenic Te0 can also be oxidized by the BioMnOx, although with different rates. This study highlights a new transformation process of tellurium species mediated by manganese-oxidizing bacteria, revealing that the environmental fate and ecological risks of Te0 needed to be re-evaluated. ImportanceBiogeochemical cycle of Te mediated by bacteria mainly focus on the Tellurite reduction and methylation. In this study, the indirect tellurium (Te0) oxidation driven by manganese-oxidizing bacterium is firstly confirmed. As Te0 usually considered as a stable and safe products during Te(IV)-containing wastewater treatment, we suppose the ecological risks of Te0 needed to be re-evaluated due to the possible oxidation by manganese-oxidizing bacterium and its generated manganese oxides.

microbiology↗

bioRxiv2023

Design, evaluation and implementation of synthetic isopentyldiol pathways in Escherichia coli

Isopentyldiol (IPDO) is an important raw material in cosmetic industry. So far IPDO is exclusively produced through chemical synthesis. Growing interest in natural personal care products has inspired the quest to develop a bio-based process. We previously reported a biosynthetic route that produces IPDO via extending leucine catabolism (route A), the efficiency of which, however, is not satisfactory. To address this issue, we computational designed a novel non-natural IPDO synthesis pathway (Route B) using RetroPath RL, the state of art tool for bio-retrosynthesis based on Artificial Intelligence methods. We compared this new pathway with route A and another two intuitively designed routes for IPDO biosynthesis from various aspects. Route B, which exhibits the highest thermodynamic driving force, least non-native reaction steps and lowest energy requirements appeared to hold the greatest potential for IPDO production. All three newly designed routes were then implemented in E. coli BL21(DE3) strain. Results show that the computationally designed route B can produce 2.2 mg/L IPDO from glucose, whereas no IPDO production from routes C and D. These results highlight the importance and usefulness of in silico design and comprehensive evaluation of the potential efficiencies of candidate pathways in constructing novel non-natural pathways for the production of biochemicals.

bioengineering↗

bioRxiv2023

ATP is a major determinant of phototrophic bacterial longevity in growth arrest.

How bacteria transition into growth arrest as part of stationary phase has been well-studied, but our knowledge of features that help cells to stay alive in the following days and weeks is incomplete. Most studies have used heterotrophic bacteria that are growth-arrested by depletion of substrates used for both biosynthesis and energy generation, making is difficult to disentangle the effects of the two. In contrast, when grown anaerobically in light, the phototrophic bacterium Rhodopseudomonas palustris generates ATP from light via cyclic photophosphorylation and builds biomolecules from organic substrates such as acetate. As such, energy generation and carbon utilization are independent from one another. Here we compared the physiological and molecular responses of R. palustris to growth arrest caused by carbon source depletion in light (energy-replete) and dark (energy-depleted) conditions. Both sets of cells remained viable for six to ten days, at which point dark-incubated cells lost viability whereas light-incubated cells remained fully viable for 60 days. Dark-incubated cells were depleted in intracellular ATP prior to losing viability, suggesting that ATP depletion is a cause of cell death. Dark-incubated cells also shut down measurable protein synthesis, whereas light-incubated cells continued to synthesize proteins at low levels. Cells incubated in both conditions continued to transcribe genes. We suggest that R. palustris may completely shut down protein synthesis in dark, energy-depleted, conditions as a strategy to survive the nighttime hours of day/night cycles it experiences in nature, where there is a predictable source of energy in the form of sunlight during days. IMPORTANCEThe molecular and physiological basis of bacterial longevity in growth arrest is important to investigate for several reasons. Such investigations could improve treatment of chronic infections, advance use of non-growing bacteria as biocatalysts to make high yields of value-added products, and improve estimates of microbial activities in natural habitats, where cells are often growing slowly or not at all. Here we compared survival of the phototrophic bacterium Rhodopseudomonas palustris under conditions where it generates ATP (incubation in light) and where it does not generate ATP (incubation in dark) to directly assess effects of energy depletion on long-term viability. We found that ATP is important for long-term survival over weeks. However, R. palustris survives 12h periods of ATP depletion without loss of viability, apparently in anticipation of sunrise and restoration of its ability to generate ATP. Our work suggests that cells respond to ATP depletion by shutting down protein synthesis.

microbiology↗

bioRxiv2022

The necessity of considering enzymes as compartments in constraint-based genomescale metabolic models

As the most widespread and practical digital representations of living cells, metabolic network models have become increasingly precise and accurate. By integrating cellular resources and abiotic constraints, the prediction functions were significantly expanded in recent years. However, we found that if unreasonable modeling methods were adopted due to the lack of consideration of biological knowledge, the conflicts between stoichiometric and other constraints, such as thermodynamic feasibility and enzyme resource availability, would lead to distorted predictions. In this work, we investigated a prediction anomaly of EcoETM, a constraints-based metabolic network model, and introduced the idea of enzyme compartmentalization into the analysis process. Through rational combination of reactions, we avoid the false prediction of pathway feasibility caused by the unrealistic assumption of free intermediate metabolites. This allowed us to correct the pathway structures of L-serine and L-tryptophan. Specific analysis explains the application method of EcoETM-like model, demonstrating its potential and value in correcting the prediction results in pathway structure by resolving the conflict between different constraints and incorporating the evolved roles of enzymes as reaction compartments. Notably, this work also reveals the trade-off between product yield and thermodynamic feasibility. Finally, we provide a preliminary comparison of the thermodynamic feasibility of ammonia and glutamine as amino donors, which revealed that the direct utilization of ammonia does not have a decisive impact on the thermodynamic feasibility of the anthranilate pathway. Our work is of great value for the structural improvement of constraints-based models.

bioinformatics↗

bioRxiv2022

Exosome-mediated viral nucleic acid presentation in a crustacean reveals innate immunity evolution from a novel perspective

As an enduring hot topic in the field of innate immunity, apoptosis is widely considered as an effective approach to eliminate pathogenic microbes, and possesses crucial role during host-pathogen interactions. Recently, researchers have found that virus-containing host cells could transmit apoptotic signals to surrounding uninfected cells during infection, but the mechanism remains unclear. Here, we found that exosomes secreted by WSSV-infected mud crab hemocytes contain viral nucleic acid wsv277, which could be transported to the recipient cells and further expressed viral protein with phosphokinase activity. Besides, by using transcriptome, proteome, ChIP-seq and coIP techniques, the results revealed that wsv277 could activate the transcription and translation of apoptotic genes via interacting with CBF and EF-1, so as to suppress the spread of virus infection by inducing apoptosis of the surrounding cells. Therefore, for the first time, our study proved that the components of DNA virus could be encapsulated into exosomes, and elucidated the mechanism of apoptotic signal transduction between cells from the perspective of exosome. Moreover, comparing those of invertebrates, we hypothesized that the innate immune system of vertebrate was weakened or degenerated, allowing exosomes to be employed by virus as the vehicle for immune escape. Significance statementOur study revealed that the components of DNA virus could be packaged and transmitted through the exosomes of lower invertebrates, which strongly demonstrated the diversity of exosome-mediated viral immunity and its universality in animals. Furthermore, we elucidated the mechanism of apoptotic signal transduction between cells from the perspective of exosome, and revealed a novel strategy for the host to cope with viral infection. Since exosome is an important innate immune regulation approach, we hypothesize that the innate immune system of vertebrates is weakened or degenerated, allowing exosomes to be employed by virus as the vehicle for immune escape.

immunology↗

bioRxiv2022

Whole Human-Brain Mapping of Single Cortical Neurons for Profiling Morphological Diversity and Stereotypy

Quantification of individual cells morphology and their distribution at the whole brain scale is essential to understand the structure and diversity of cell types. Despite recent technological advances, especially single cell labeling and whole brain imaging, for many prevailing animal models, it is exceedingly challenging to reuse similar technologies to study human brains. Here we propose Adaptive Cell Tomography (ACTomography), a low-cost, high-throughput, high-efficacy tomography approach, based on adaptive targeting of individual cells suitable for human-brain scale modeling of single neurons to characterize their 3-D structures, statistical distributions, and extensible for other cellular features. Specifically, we established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and 1 donated fresh postmortem brain. We collected 3-D images of 1746 cortical neurons, of which 852 neurons were subsequentially reconstructed to quantify their local dendritic morphology, and mapped to standard atlases both computationally and semantically. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor-field of neuron morphology to characterize 3-D anatomical modularity of a human brain.

neuroscience↗

bioRxiv2022

The Serotonergic Neural Circuit Between The Dorsal Raphe Nucleus And The Basolateral Amygdala Is Implicated In Modulating The Arousal from Sevoflurane Anesthesia

Although some advancements concerning the arousal involved in mediating the delayed emergency from general anesthesia, which will lead to the serious complications, had been made, the role by arousal in modulating in delayed emergency still remains to be unclear. In our models, based on our previous working that activation of the 5-Hydroxytryptamine (5-HT) neurons in the dorsal raphe nucleus (DRN) by optogenetics can significantly reduce the emergency time by activating arousal pathway, we further test whether the serotonergic neural circuit between the DRN and the basolateral amygdala (BLA) is implicated in modulating the arousal from the sevoflurane anesthesia and the emergency time of sevoflurane anesthesia by the pharmacological, optogenetics and fiber photometry. Our findings showed that whether the serotonergic neural circuit between the DRN and the basolateral amygdala (BLA) plays a key role in modulating the arousal from the sevoflurane anesthesia and the emergency time of sevoflurane anesthesia. Based on the serotonergic neural circuit, the 5-HT 1 A receptor is of great significance to mediate the arousal and the emergency time of the sevoflurane anesthesia. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/511924v2_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@34621eorg.highwire.dtl.DTLVardef@115ae09org.highwire.dtl.DTLVardef@54eb12org.highwire.dtl.DTLVardef@11515ff_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure1C_FLOATNO C_FIG

neuroscience↗

bioRxiv2022

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.

We seek to transform how new and emergent variants of pandemiccausing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pretraining on over 110 million prokaryotic gene sequences and finetuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.

bioinformatics↗

bioRxiv2022

Long-term passaging of replication competent pseudo-typed SARS-CoV-2 reveals the antiviral breadth of monoclonal and bispecific antibody cocktails

The continuous emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants poses challenges to the effectiveness of neutralizing antibodies. Rational design of antibody cocktails is a realizable approach addressing viral immune evasion. However, evaluating the breadth of antibody cocktails is essential for understanding the development potential. Here, based on a replication competent vesicular stomatitis virus model that incorporates the spike of SARS-CoV-2 (VSV-SARS-CoV-2), we evaluated the breadth of a number of antibody cocktails consisting of monoclonal antibodies and bispecific antibodies by long-term passaging the virus in the presence of the cocktails. Results from over two-month passaging of the virus showed that 9E12+10D4+2G1 and 7B9-9D11+2G1 from these cocktails were highly resistant to random mutation, and there was no breakthrough after 30 rounds of passaging. As a control, antibody REGN10933 was broken through in the third passage. Next generation sequencing was performed and several critical mutations related to viral evasion were identified. These mutations caused a decrease in neutralization efficiency, but the reduced replication rate and ACE2 susceptibility of the mutant virus suggested that they might not have the potential to become epidemic strains. The 9E12+10D4+2G1 and 7B9-9D11+2G1 cocktails that picked from the VSV-SARS-CoV-2 system efficiently neutralized all current variants of concern and variants of interest including the most recent variants Delta and Omicron, as well as SARS-CoV-1. Our results highlight the feasibility of using the VSV-SARS-CoV-2 system to develop SARS-CoV-2 antibody cocktails and provide a reference for the clinical selection of therapeutic strategies to address the mutational escape of SARS-CoV-2.

cell biology↗

bioRxiv2022

Inhibition of CHK2 dependent DNA damage response suppresses Zika virus infection through a STING dependent mechanism

Zika virus (ZIKV) is a mosquito-borne flavivirus that causes neurological disorders and microcephaly. Recent research has shown that ZIKV causes cell cycle arrest and DNA damage response in neuronal progenitor cells that potentially leads to congenital neurodevelopmental defects. However, the specific role of regulators that control DNA damage response to ZIKV infection and the related mechanisms remain largely unknown. Here through both in vitro and in vivo studies, we observe that ZIKV induces DNA damage response in both human cell line and mouse embryo. When CHK2 dependent DNA damage response pathway is inhibited by a small molecule inhibitor or genetic deletion, ZIKV production is reduced and the embryonic developmental defects are rescued. Furthermore, we demonstrate that in ZIKV infected Chk2-/- mice, the reduced viral load correlates with elevated antiviral innate immune response which is found to be dependent on the STING signaling pathway. Collectively, our study reveals a specific role of CHK2 for ZIKV infection and pathogenesis, demonstrating a mechanism that inhibition of the CHK2 axis suppresses ZIKV infection through the STING-dependent antiviral pathway, thus providing a new therapeutic strategy against ZIKV. These findings also suggest the intriguing possibility that ZIKV evolved to orchestrate DNA damage response factors to create a beneficial environment for its infection in the host cells.

immunology↗