Biology subjects

Zhao, T.

Publications and source records attributed to Zhao, T..

At least 145 records · Page 8Linked to original sources

bioRxiv2021

3D-MASNet: 3D Mixed-scale Asymmetric Convolutional Segmentation Network for 6-month-old Infant Brain MR Images

Precise segmentation of infant brain MR images into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) are essential for studying neuroanatomical hallmarks of early brain development. However, for 6-month-old infants, the extremely low-intensity contrast caused by inherent myelination hinders accurate tissue segmentation. Existing convolutional neural networks (CNNs) based segmentation models for this task generally employ single-scale symmetric convolutions, which are inefficient for encoding the isointense tissue boundaries in baby brain images. Here, we propose a 3D mixed-scale asymmetric convolutional segmentation network (3D-MASNet) framework for brain MR images of 6-month-old infants. We replaced the traditional convolutional layer of an existing to-be-trained network with a 3D mixed-scale convolution block consisting of asymmetric kernels (MixACB) during the training phase and then equivalently converted it into the original network. Five canonical CNN segmentation models were evaluated using both T1- and T2-weighted images of 23 6-month-old infants from iSeg-2019 datasets, which contained manual labels as ground truth. MixACB significantly enhanced the average accuracy of all five models and obtained the most considerable improvement in the fully convolutional network model (CC-3D-FCN) and the highest performance in the Dense U-Net model. This approach further obtained Dice coefficient accuracies of 0.931, 0.912, and 0.961 in GM, WM, and CSF, respectively, ranking first among 30 teams on the validation dataset of the iSeg-2019 Grand Challenge. Thus, the proposed 3D-MASNet can improve the accuracy of existing CNNs-based segmentation models as a plug-and-play solution that offers a promising technique for future infant brain MRI studies.

neuroscience↗

bioRxiv2021

GPI anchor remodeling by the plant PGAP1 ortholog HLD1 is essential for Papaver self-incompatibility

In eukaryotes, glycosylphosphatidylinositol anchored proteins (GPI-APs) are tethered to the outer leaflet of the plasma membrane where they function as key regulators of a plethora of biological processes. Self-incompatibility (SI) plays a pivotal role regulating fertilization in higher plants through recognition and rejection of self pollen. Here we used Arabidopsis thaliana lines engineered to be self-incompatible by expression of Papaver SI determinants for an SI suppressor screen. We identify HLD1, an ortholog of human GPI-inositol deacylase PGAP1, whose mutation completely abolishes the SI response. We show that HLD1 functions as a GPI-inositol deacylase and that this GPI-remodeling activity is essential for SI. Using GFP-SKU5 as a representative GPI-AP, we show that HLD1 mutation does not affect GPI-AP production and targeting, but alters the configuration of mature GPI-APs. This prevents GPI-AP release from the plasma membrane, suggesting that this process plays a critical role in the regulation of SI. Our data not only identify GPI anchoring as a new pathway of SI providing new directions to investigate SI mechanisms, but identifies for the first time a function for GPI-AP remodeling by inositol deacylation in plants. One sentence summaryThe Papaver self-incompatibility response requires GPI-anchor modification by HLD1, an ortholog of the mammalian PGAP1.

plant biology↗

bioRxiv2021

A contraction-reaction-diffusion model for circular pattern formation in embryogenesis

Reaction-diffusion models have been widely used to elucidate pattern formation in developmental biology. More recently, they have also been applied in modeling cell fate patterning that mimic early-stage human development events utilizing geometrically confined pluripotent stem cells. However, the traditional reaction-diffusion equations could not satisfactorily explain the concentric ring distributions of various cell types, as they do not yield circular patterns even for circular domains. In previous mathematical models that yield ring patterns, certain conditions that lack biophysical understandings had been considered in the reaction-diffusion models. Here we hypothesize that the circular patterns are the results of the coupling of the mechanobiological factors with the traditional reaction-diffusion model. We propose two types of coupling scenarios: tissue tension-dependent diffusion flux and traction stress-dependent activation of signaling molecules. By coupling reaction-diffusion equations with the elasticity equations, we demonstrate computationally that the contraction-reaction-diffusion model can naturally yield the circular patterns.

bioengineering↗

bioRxiv2021

Ssl2/TFIIH Function in Transcription Start Site Scanning by RNA Polymerase II in Saccharomyces cerevisiae

In Saccharomyces cerevisiae, RNA Polymerase II (Pol II) selects transcription start sites (TSS) by a unidirectional scanning process. During scanning, a preinitiation complex (PIC) assembled at an upstream core promoter initiates at select positions within a window [~]40-120 basepairs downstream. Several lines of evidence indicate that Ssl2, the yeast homolog of XPB and an essential and conserved subunit of the general transcription factor (GTF) TFIIH, drives scanning through its DNA-dependent ATPase activity, therefore potentially controlling both scanning rate and scanning extent (processivity). To address questions of how Ssl2 functions in promoter scanning and interacts with other initiation activities, we leveraged distinct initiation-sensitive reporters to identify novel ssl2 alleles. These ssl2 alleles, many of which alter residues conserved from yeast to human, confer either upstream or downstream TSS shifts at the model promoter ADH1 and genome-wide. Specifically, tested ssl2 alleles alter TSS selection by increasing or narrowing the distribution of TSSs used at individual promoters. Genetic interactions of ssl2 alleles with other initiation factors are consistent with ssl2 allele classes functioning through increasing or decreasing scanning processivity but not necessarily scanning rate. These alleles underpin a residue interaction network that likely modulates Ssl2 activity and TFIIH function in promoter scanning. We propose that the outcome of promoter scanning is determined by two functional networks, the first being Pol II activity and factors that modulate it to determine initiation efficiency within a scanning window, and the second being Ssl2/TFIIH and factors that modulate scanning processivity to determine the width of the scanning widow.

molecular biology↗

bioRxiv2021

Evaluation of different concentrations antibiotics on gut bacteria and growth of Ectropis obliquaProut (Lepidoptera: Geometridae)

The use of antibiotics to remove gut bacteria is a commonly used method to study gut function of insects. We assessed the impact of the artificial diet made from tea powder with different concentrations of antibiotics mixture (containing tetracycline, gentamicin, penicillin, and rifampicin) on Ectropis obliqua Prout (Lepidoptera: Geometridae) survival, growth, and reproduction. Antibiotic-induced bacterial clearance was monitored by Polymerase Chain Reaction (PCR) and by Colony-counting Methods. The results indicated that administration of the antibiotic mixture at a concentration of 200g/ml caused the increase of gut bacteria, while a concentration of 300g/ml was more effective in clearing gut bacteria but the concentration of 400g/ml caused a large number of larval deaths. The concentration of 300g/ml had no significant effect on the growth and development of E. obliqua, but had impact on fecundity. Therefore, we could use 300g/ml concentrations of the antibiotic mixture to obtain sterile E. obliqua to study the function of intestinal microbes.

animal behavior and cognition↗

bioRxiv2021

Interpretable Artificial Neural Networks incorporating Bayesian Alphabet Models for Genome-wide Prediction and Association Studies

In conventional linear models for whole-genome prediction and genome-wide association studies (GWAS), it is usually assumed that the relationship between genotypes and phenotypes is linear. Bayesian neural networks have been used to account for non-linearity such as complex genetic architectures. Here, we introduce a method named NN-Bayes, where "NN" stands for neural networks, and "Bayes" stands for Bayesian Alphabet models, including a collection of Bayesian regression models such as BayesA, BayesB, BayesC, Bayesian LASSO, and BayesR. NN-Bayes incorporates Bayesian Alphabet models into non-linear neural networks via hidden layers between SNPs and observed traits. Thus, NN-Bayes attempts to improve the performance of genome-wide prediction and GWAS by accommodating non-linear relationships between the hidden nodes and the observed trait, while maintaining genomic interpretability through the Bayesian regression models that connect the SNPs to the hidden nodes. For genomic interpretability, the posterior distribution of marker effects in NN-Bayes is inferred by Markov chain Monte Carlo (MCMC) approaches and used for inference of association through posterior inclusion probabilities (PIPs) and window posterior probability of association (WPPA). In simulation studies with dominance and epistatic effects, performance of NN-Bayes was significantly better than conventional linear models for both GWAS and whole-genome prediction, and the differences on prediction accuracy were substantial in magnitude. In real data analyses, for the soy dataset, NN-Bayes achieved significantly higher prediction accuracies than conventional linear models, and results from other four different species showed that NN-Bayes had similar prediction performance to linear models, which is potentially due to the small sample size. Our NN-Bayes is optimized for high-dimensional genomic data and implemented in an open-source package called "JWAS". NN-Bayes can lead to greater use of Bayesian neural networks to account for non-linear relationships due to its interpretability and computational performance.

genetics↗

bioRxiv2021

Development of Large-Scale Brain Network Dynamics in Children

Functional brain networks require dynamic reconfiguration to support flexible cognitive function. However, the developmental principles shaping brain network dynamics remain poorly understood. Here, we report the longitudinal development of large-scale brain network dynamics during childhood and adolescence, and its connection with gene expression profiles. Using a multilayer network model, we show the temporally varying modular architecture of child brain networks, with higher network switching primarily in the association cortex and lower switching in the primary regions. This topographical profile exhibits progressive maturation, which manifests as reduced modular dynamics, particularly in the transmodal (e.g., default-mode and frontoparietal) and sensorimotor regions. These developmental refinements mediate age-related enhancements of global network segregation and are linked with the expression profiles of genes associated with the enrichment of ion transport and nucleobase-containing compound transport. These results highlight a progressive stabilization of brain dynamics, which expand our understanding of the neural mechanisms that underlie cognitive development.

neuroscience↗

bioRxiv2021

The global carrier frequency and genetic prevalence of Upshaw-Schulman syndrome

PurposeUpshaw-Schulman syndrome (USS) is an autosomal recessive disease of thrombotic microangiopathy, caused by pathogenic variants in ADAMTS13. We aimed to (1) perform data mining pathogenicity of ADAMTS13 variants, (2) estimate carrier frequency and genetic prevalence of USS from gnomAD data, and (3) curated ADAMTS13 gene pathogenic variants dataset. MethodsPubMed and Scopus were comprehensive retrieved. All previously reported pathogenic ADAMTS13 variants were compiled and annotated with gnomAD allele frequencies. Pooled global and population-specific carrier frequency and genetic prevalence for USS were calculated using Hardy-Weinberg equation. Resultswe mined reported disease-causing variants, of these were present in gnomAD exomes v2.1.1, filtering by allele frequency, pathogenicity of variants were classified by American College of Medical Genetics and Genomics criteria. The genetic prevalence and carrier frequency of USS was 0.43 per 1 million (95% CI: [0.36, 0.55]) and 1.31 per thousand, respectively. Combining known with novel pathogenic/likely pathogenic variants, the genetic prevalence and carrier frequency are 1.1 per 1 million (95% CI: [0.89, 1.37]) and 2.1 per thousand, respectively. Conclusionthe genetic prevalence and carrier frequency of Upshaw-Schulman syndrome are within range of previously rough estimated.

bioinformatics↗

bioRxiv2021

Regeneration of spinal motor axons: Negative regulation by Celsr2 implicating Cdc42/Rac1 and JNK/c-Jun signaling

During development, cadherins Celsr2 and Celsr3 control axon navigation. Unlike Celsr3, Celsr2 remains expressed in the adult, suggesting unexplored roles in maintenance and repair. Here we show that Celsr2 knockdown promotes motor axon regeneration in mouse and human spinal cord explants and cultured motor neurons. Celsr2 downregulation is accompanied by increased levels of GTP-bound Rac1 and Cdc42, and of JNK and c-Jun proteins. Using a branchial plexus injury model, we show that forelimb functional recovery is improved in Celsr2 mutant versus control mice. Compared to controls, in mutant mice, reinnervated biceps muscles are less atrophic, contain more newly formed neuromuscular junctions, and generate larger electromyographic potentials, while motor neuron survival and axon regeneration are improved. GTP-bound Rac1 and Cdc42, JNK and c-Jun are upregulated in injured mutant versus control spinal cord. In conclusion, Celsr2 negatively regulates motor axon regeneration via Cdc42/Rac1/JNK/c-Jun signaling and is a target for neural repair.

neuroscience↗

bioRxiv2021

Structure of TFIIH/Rad4-Rad23-Rad33 in damaged DNA opening in Nucleotide Excision Repair

The versatile nucleotide excision repair (NER) pathway initiates as the XPC-RAD23B-CETN2 complex first recognizes DNA lesions from the genomic DNA and recruits the general transcription factor complex, TFIIH, for subsequent lesion verification. Here, we present a cryo-EM structure of an NER initiation complex containing Rad4-Rad23-Rad33 (yeast homologue of XPC-RAD23B-CETN2) and 7-subunit core TFIIH assembled on a carcinogen-DNA adduct lesion at 3.9-9.2 [A] resolution. A ~30-bp DNA duplex could be mapped as it straddles between Rad4 and the Ssl2 (XPB) subunit of TFIIH on the 3 and 5 side of the lesion, respectively. The simultaneous binding with Rad4 and TFIIH was permitted by an unwinding of DNA at the lesion. Translocation coupled with torque generation by Ssl2 would extend the DNA opening at the lesion and deliver the damaged strand to Rad3 (XPD) in an unwound form suitable for subsequent lesion scanning and verification.

biophysics↗

bioRxiv2020

Impaired phosphatidylethanolamine metabolism activates a reversible stress response that detects and resolves mutant mitochondrial precursors

Phosphatidylethanolamine made in mitochondria has long been recognized as an important precursor for phosphatidylcholine production that occurs in the endoplasmic reticulum (ER). Recently, the strict mitochondrial localization of the enzyme that makes PE in the mitochondrion, phosphatidylserine decarboxylase 1 (Psd1), was questioned. Since a dual localization of Psd1 to the ER would have far-reaching implications, we initiated our study to independently re-assess the subcellular distribution of Psd1. Our results support the unavoidable conclusion that the vast majority, if not all, of functional Psd1 resides in the mitochondrion. Through our efforts, we discovered that mutant forms of Psd1 that impair a self-processing step needed for it to become functional are dually localized to the ER when expressed in a PE-limiting environment. We conclude that severely impaired cellular PE metabolism provokes an ER-assisted adaptive response that is capable of identifying and resolving nonfunctional mitochondrial precursors.

cell biology↗

bioRxiv2020

Multivalency transforms SARS-CoV-2 antibodies into broad and ultrapotent neutralizers

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes Coronavirus Disease 2019 (COVID-19), has caused a global pandemic. Antibodies are powerful biotherapeutics to fight viral infections; however, discovery of the most potent and broadly acting clones can be lengthy. Here, we used the human apoferritin protomer as a modular subunit to drive oligomerization of antibody fragments and transform antibodies targeting SARS-CoV-2 into exceptionally potent neutralizers. Using this platform, half-maximal inhibitory concentration (IC50) values as low as 9 x 10-14 M were achieved as a result of up to 10,000-fold potency enhancements. Combination of three different antibody specificities and the fragment crystallizable (Fc) domain on a single multivalent molecule conferred the ability to overcome viral sequence variability together with outstanding potency and Ig-like in vivo bioavailability. This MULTi-specific, multi-Affinity antiBODY (Multabody; or MB) platform contributes a new class of medical countermeasures against COVID-19 and an efficient approach to rapidly deploy potent and broadly-acting therapeutics against infectious diseases of global health importance. One Sentence Summarymultimerization platform transforms antibodies emerging from discovery screens into potent neutralizers that can overcome SARS-CoV-2 sequence diversity.

molecular biology↗

bioRxiv2020

Sequence- and structure-selective mRNA m5C methylation by NSUN6 in animals

mRNA m5C, which has recently been implicated in the regulation of mRNA mobility, metabolism, and translation, plays important regulatory roles in various biological events. Two types of m5C sites are found in mRNAs. Type I m5C sites, which contain a downstream G-rich triplet motif and are computationally predicted to locate in the 5 end of putative hairpin structures, are methylated by NSUN2. Type II m5C sites contain a downstream UCCA motif and are computationally predicted to locate in the loops of putative hairpin structures. However, their biogenesis remains unknown. Here we identified NSUN6, a methyltransferase that is known to methylate C72 of tRNAThr and tRNACys, as an mRNA methyltransferase that targets Type II m5C sites. Combining the RNA secondary structure prediction, miCLIP, and results from a high-throughput mutagenesis analysis, we determined the RNA sequence and structural features governing the specificity of NSUN6-mediated mRNA methylation. Integrating these features into an NSUN6-RNA structural model, we identified an NSUN6 variant that largely loses tRNA methylation but retains mRNA methylation ability. Finally, we revealed a negative correlation between m5C methylation and translation efficiency. Our findings uncover that mRNA m5C is tightly controlled by an elaborate two-enzyme system, and the protein-RNA structure analysis strategy established may be applied to other RNA modification writers to distinguish the functions of different RNA substrates of a writer protein.

molecular biology↗

bioRxiv2020

Comparative analysis of temporal transcriptome reveals the relationship between pectin degradation and pathogenicity of defoliating Verticillium dahliae to Upland cotton (Gossypium hirsutum)

Verticillium wilt (VW), caused by Verticillium dahliae Kleb., is a major plant disease that causes heavy annual losses around the world, especially in Upland cotton (Gossypium hirsutum). The disease-causing pathogen can be classified into defoliating (D) and non-defoliating (ND) pathotypes based on the induced symptoms. At present, little is known about the complex mechanisms of fungal pathogenicity and cotton resistance to it. Comparative analysis of temporal transcriptome was performed on two V. dahliae strains, Vd_086 (D) and Vd_BP2 (ND), at key development stages (hyphal growth, microsclerotia production, and spore germination) to reveal the functional process on plant defoliation and death. Differentially expressed gene (DEG) analysis revealed a strong correlation between cell wall protein kinase activities and the early pathogenicity of defoliating Vd_086. With weighted gene co-expression network analysis (WGCNA), six specific gene modules were correlated with the biological traits of the fungal samples. Functional enrichment with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways together with DEG analysis revealed six pectin degrading enzymes including Polygalacturonase gene 1 (PG1), Pectate lyase gene (PEL) and Pectinesterase gene 1 (PME1) expressed in the early development of Vd_086 that may be related to the robust pathogenicity of this strain during the early invasion. The expression of four of these genes was verified by real-time quantitative reverse transcription PCR (qRT-PCR). In addition, we identified Mitogen-Activated Protein Kinase (MAPK) signaling "hub" genes that may regulate these pectinases. In a word, enhanced expression of pectin degradation enzymes is associated with the stronger pathogenicity of Vd_086 than Vd_BP2, especially at early infection stages. The disease-causing capability is likely regulated by MAPK signaling genes. This study provides new insight into molecular mechanisms of the plant-pathogen interaction on the VW disease, facilitating more effective control measures against this pathogen, including molecular breeding for the VW-resistant cotton cultivars. Author summaryVerticillium wilt (VW), caused by fungal pathogen Verticillium dahliae (Vd), is arguably the most devastating disease in cotton production for decades. Molecular biologists and plant breeders have been working hard to identify host plant resistant genes for many years but have met with little success due to the large complex genome of cotton. The V. dahliae strains are grouped in two pathotypes, of which defoliating (D) strains cause total leaf loss of infected cotton plants and non-defoliating (ND) strains do not. Comparative transcriptome analysis of D strain Vd_086 and ND strain Vd_BP2 identified the candidate genes and molecular mechanisms related to the Vd pathogenicity. Besides the difference in pathogenicity, these strains are distinguishable by the rate of hyphal elongation, microsclerotia production, and spore germination. With these phenotypes, transcriptome sequencing of both strains was performed at the three growth phases. By the combination of comparative transcriptomic differentially expressed gene (DEG) analysis and weighted gene correlation network analysis (WGCNA), cell wall-associated pectinase genes were found to be active at hyphal elongation stage of the V. dahliae pathogen and ribosome-related processes were activated for microsclerotia production. Gene modification processes were activated with many protein kinases at spore germination stage that for the next infection cycle. Furthermore, four pectinases in the pentose and glucuronate interconversion (PGI) pathway were identified and verified as highly expressed in the D strain with strong pathogenicity to Upland cotton (Gossypium hirsutum). Our results provided evidence in support of the hypothesis that stronger early pathogenicity of the D strain is resulted from greater plant cell wall pectin degradability. Transcription factors (TFs) and "hub" module genes were identified in searching of protein interaction for possible regulators of the recognized pectinases. TFs involved in mitogen-activated protein kinase (MAPK) signaling pathway were shown to regulate not only hyphal processes but also the entire growth period of V. dahliae. This is the first study known to use module extraction techniques of WGCNA to identify differentially co-expressed genes between two fungal pathotypes of V. dahliae strains. The study provides new insights into molecular mechanisms of the plant-pathogen interaction and may lead to molecular breeding for resistant cotton cultivars to effectively control this devastating disease.

microbiology↗

bioRxiv2020

An endoplasmic reticulum (ER) ATPase safeguards ER identity by removing ectopically localized mitochondrial proteins

Stringent targeting of membrane proteins to corresponding organelles is essential for organelle identity and functions. In addition to molecular pathways that target proteins to appropriate organelles, surveillance mechanisms clear mistargeted proteins from undesired destinations. While Msp1 functions on mitochondrial membrane to remove mistargeted proteins, the surveillance mechanism for the ER is not well understood. Here, we show that mitochondrial tail-anchored (TA) and signal-anchored (SA) proteins mislocalize to ER membrane in neurons and muscles in C. elegans catp-8 mutants. catp-8 encodes a conserved P5A type ATPase, which localizes to ER and removes ectopic mitochondrial TA/SA proteins from ER. In catp-8 mutant, mitochondria fission protein FIS-1 mislocalizes to ER membrane. Together with another mitochondria fission protein MFF-2, FIS-1 causes ER fragmentation in a Dynamin related protein (DRP-1) dependent manner. Additionally, CATP-8 is essential for dendrite development. catp-8 mutant dramatically reduces the level of the dendrite guidance receptor DMA-1, leading to diminished dendritic arbors. Hence, P5A ATPase safeguards ER morphology and functions by preventing mitochondrial proteins mislocalization. HIGHLIGHTSCATP-8, a P5A type ATPase, localizes to ER and functions as a surveillance mechanism to remove mistargeted mitochondrial proteins. Multiple mitochondria proteins are mistargeted to ER in catp-8 mutants. Ectopic recruitment of mitochondria fission mechinary to ER causes ER fragmentation in catp-8 mutants. CATP-8 is essential for PVD dendrite morphogenesis through modulating the level of transmembrane receptor DMA-1.

cell biology↗

bioRxiv2020

Improved Prediction of Smoking Status via Isoform-Aware RNA-seq Deep Learning Models

Most predictive models based on gene expression data do not leverage information related to gene splicing, despite the fact that splicing is a fundamental feature of eukaryotic gene expression. Cigarette smoking is an important environmental risk factor for many diseases, and it has profound effects on gene expression. Using smoking status as a prediction target, we developed deep neural network predictive models using gene, exon, and isoform level quantifications from RNA sequencing data in over 2,000 subjects in the COPDGene Study. We observed that models using exon and isoform quantifications clearly outperformed gene-level models when using data from 5 genes from a previously published five gene prediction model. Whereas the test set performance of the previously published model was 0.82 in the original publication, our exon-based models including an exon-to-isoform mapping layer achieved a test set AUC of 0.88 using data from the same 5 genes and an AUC of 0.94 using a larger set of exon quantifications. Isoform variability is an important source of latent information in RNA-seq data that can be used to improve clinical prediction models. Author summaryPredictive models based on gene expression are already a part of medical decision making for selected situations such as early breast cancer treatment. Most of these models are based on measures that do not capture critical aspects of gene splicing, but with RNA sequencing it is possible to capture some of these aspects of alternative splicing and use them to improve clinical predictions. Building on previous models to predict cigarette smoking status, we show that measures of alternative splicing significantly improve the accuracy of these predictive models.

genomics↗

bioRxiv2020

BNIP3 phosphorylation by JNK1/2 promotes mitophagy via enhancing its stability under hypoxia

Mitophagy is an important metabolic mechanism that modulates mitochondrial quality and quantity by selectively removing damaged or unwanted mitochondria. BNIP3, a mitochondrial outer membrane protein, is a mitophagy receptor that mediates mitophagy under various stresses, particularly hypoxia, since BNIP3 is a hypoxia-responsive protein. However, the underlying mechanisms that regulate BNIP3 and thus mediate mitophagy under hypoxic conditions remain elusive. Here, we demonstrate that in hypoxia JNK1/2 phosphorylates BNIP3 at Ser 60/Thr 66, which hampers proteasomal degradation of BNIP3 and drives mitophagy by facilitating the direct binding of BNIP3 to LC3, while PP1/2A represses mitophagy by dephosphorylating BNIP3 and triggering its proteasomal degradation. These findings reveal the intrinsic mechanisms cells use to regulate mitophagy via the JNK1/2-BNIP3 pathway in response to hypoxia. Thus, the JNK1/2-BNIP3 signaling pathway strongly links mitophagy to hypoxia and may be a promising therapeutic target for hypoxia-related diseases.

cell biology↗

bioRxiv2020

Drug Repurposing Screen for Compounds Inhibiting the Cytopathic Effect of SARS-CoV-2

Drug repurposing is a rapid approach to identifying therapeutics for the treatment of emerging infectious diseases such as COVID-19. To address the urgent need for treatment options, we carried out a quantitative high-throughput screen using a SARS-CoV-2 cytopathic assay with a compound collection of 8,810 approved and investigational drugs, mechanism-based bioactive compounds, and natural products. Three hundred and nineteen compounds with anti-SARS-CoV-2 activities were identified and confirmed, including 91 approved drug and 49 investigational drugs. Among these confirmed compounds, the anti-SARS-CoV-2 activities of 230 compounds, including 38 approved drugs, have not been previously reported. Chlorprothixene, methotrimeprazine, and piperacetazine were the three most potent FDA approved drugs with anti-SARS-CoV-2 activities. These three compounds have not been previously reported to have anti-SARS-CoV-2 activities, although their antiviral activities against SARS-CoV and Ebola virus have been reported. These results demonstrate that this comprehensive data set of drug repurposing screen for SARS-CoV-2 is useful for drug repurposing efforts including design of new drug combinations for clinical trials.

microbiology↗