Biology subjects

Guo, X.

Publications and source records attributed to Guo, X..

At least 253 records · Page 14Linked to original sources

bioRxiv2021

Lentiviral vector optimization enhances the expression and cytotoxicity of chimeric antigen receptors

Adoptive chimeric antigen receptor (CAR)-modified T or NK cells (CAR-T/NK) have emerged as a novel form of disease treatment. Lentiviral vectors (LVs) are commonly employed to engineer T/NK cells for the efficient expression of CARs. This study reported for the first time the influence of single-promoter and dual-promoter LVs on the CAR expression and cytotoxicity of engineered NK cells. Our results demonstrated that the selected CAR exhibits both a higher expression level and a higher coexpression concordance with the GFP reporter in HEK-293T or NK92 cells by utilizing the optimized single-promoter pCDHsp rather than the original dual-promoter pCDHdp. After puromycin selection, the pCDHsp produces robust CAR expression and enhanced in vitro cytotoxicity of engineered NK cells. Therefore, infection with a single-promoter pCDHsp lentivector is recommended to prepare CAR-engineered cells. This research will help to optimize the production of CAR-NK cells and improve their functional activity, to provide CAR-NK cell products with better and more uniform quality.

cell biology↗

bioRxiv2021

Atp13a5 Marker Reveals Pericytes of The Central Nervous System in Mice

Perivascular mural cells including vascular smooth cells (VSMCs) and pericytes are integral components of the vascular system. In the central nervous system (CNS), pericytes are also known as the guardian of the blood-brain barrier, blood-spinal cord barrier and blood-retinal barrier, and play key roles in maintaining cerebrovascular and neuronal functions. However, the functional difference between CNS and peripheral pericytes has not been resolved at the genetic and molecular levels. Hence, the generation of reliable CNS pericyte-specific models and genetic tools remains very challenging. Here, we report a new CNS pericyte marker in mice. This cation-transporting ATPase 13A5 (Atp13a5) marker is highly specific to the pericytes in brain, spinal cord and retina. We generated a transgenic model with a knock-in tdTomato reporter and Cre recombinase. The tdTomato reporter reliably labels the CNS pericytes, but not found in any other CNS cell types including closely related VSMCs, or in peripheral organs. More importantly, Atp13a5 is turned on at embryonic day E15, suggesting brain pericytes are shaped by the developing neural environment. We hope that the new tools will allow us to further explore the heterogeneity of pericytes and achieve a better understanding of CNS pericytes in health and diseases.

neuroscience↗

bioRxiv2021

SAFA facilitates chromatin opening of immune genes through interacting with nascent antiviral RNAs

Regulation of chromatin accessibility determines the transcription activities of genes, which endow the host with function-specific gene expression patterns. It remains unclear how chromatin accessibility is specifically directed, particularly, during host defense against viral infection. We previously reported that the nuclear matrix protein SAFA surveils viral RNA and regulates antiviral immune genes expression. However, how SAFA regulates the expression and what determines the specificity of antiviral immune genes remains unknown. Here, we identified that the depletion of SAFA specifically decreased the chromatin accessibility, activation and expression of virus induced genes in a genome-wide scale after VSV infection. SAFA exclusively bound with antiviral related RNAs, which mediated the specific opening of the according chromatin and robust transcription of these genes. Knockdown of these associated RNAs dampened the accessibility of corresponding genes in an extranuclear signaling pathway dependent manner. Moreover, VSV infection cleaved SAFA protein at the C-terminus which deprived its RNA binding ability for immune evasion. Thus, our results demonstrated that SAFA and the interacting RNA products during viral infection collaborate and remodel chromatin accessibility to facilitate antiviral innate immune response.

immunology↗

bioRxiv2021

Formation, collective motion, and merging of macroscopicbacterial aggregates

Chemotactic bacteria form emergent spatial patterns of variable cell density within cultures that are initially spatially uniform. These patterns are the result of chemical gradients that are created from the directed movement and metabolic activity of billions of cells. A recent study on pattern formation in wild bacterial isolates has revealed unique collective behaviors of the bacteria Enterobacter cloacae. As in other bacteria species, Enterobacter cloacae form macroscopic aggregates. Once formed, these bacterial clusters can migrate several millimeters, sometimes resulting in the merging of two or more clusters. To better understand these phenomena, we examine the formation and dynamics of thousands of bacterial clusters that form within a 22 cm square culture dish filled with soft agar over two days. At the macroscale, the aggregates display spatial order at short length scales, and the migration of cell clusters is superdiffusive, with a merging acceleration that is correlated with aggregate size. At the microscale, aggregates are composed of immotile cells surrounded by low density regions of motile cells. The collective movement of the aggregates is the result of an asymmetric flux of bacteria at the boundary. An agent based model is developed to examine how these phenomena are the result of both chemotactic movement and a change in motility at high cell density. These results identify and characterize a new mechanism for collective bacterial motility driven by a transient, density-dependent change in motility. Author summaryBacteria growing and swimming in soft agar often aggregate to form elaborate spatial patterns. Here we examine the patterns formed by the bacteria Enterobacter cloacae. An unusual behavior of this bacteria is the movement of cell clusters, millions of bacteria forming a tiny spot and moving together in the same direction. These spots sometimes run into each other and combine. By looking at the cells within these spots under a microscope, we find that cells within each spot stop swimming. The process of switching back and forth between swimming and not swimming causes the movement and fusion of the spots. A numerical simulation shows that the migration and merging of these spots can be expected if the cells swim towards regions of space with high concentrations of attractant molecules and stop swimming in locations crowded with many cells. This work identifies a novel process through which populations of bacteria cooperate and control the movement of large groups of cells.

biophysics↗

bioRxiv2021

African swine fever virus structural protein p17 inhibits cGAS-STING signaling pathway through interacting with STING

African swine fever (ASF) is highly contagious, causes high mortality in domestic and feral swine, and has a significant economic impact on the global swine industry due to the lack of a vaccine or an effective treatment. African swine fever virus (ASFV) encodes more than 150 polypeptides, which may have intricate and delicate interactions with the host for the benefit of the virus to evade the hosts defenses. However, currently, there is still a lack of information regarding the roles of the viral proteins in host cells. Here, our data demonstrated that the p17, encoded by D117L gene could suppress porcine cGAS-STING signaling pathway, exhibiting the inhibitions of TBK1 and IRF3 phosphorylations, downstream promoter activities, cellular mRNA transcriptions and ISG56 induction, and antiviral responses. Further, we found that p17 was located in endoplasmic reticulum (ER) and Golgi apparatus, and interacted with STING, perturbing it in the recruitment of TBK1 and IKK{varepsilon}. Additionally, it appeared that the transmembrane domain (amino acids 39-59) of p17 could be required for interacting with STING and inhibiting cGAS-STING pathway. Taken together, p17 could inhibit the cGAS-STING pathway through its interaction with STING and interference with STING in the recruitment of TBK1 and IKK{varepsilon}. ImportanceAfrican swine fever (ASF) is a highly contagious disease in domestic and feral swine, posing significant economic impacts on the global swine industry, and the pathogen ASFV is a large icosahedral DNA virus. The innate immune cGAS-STING DNA sensing pathway plays a critical role in sensing invading ASFV and triggering antiviral responses. However, there is still a lack of information regarding the molecular mechanisms of ASFV evasion of the cGAS-STING pathway. We have analyzed the effects of whole genomic open reading frames (ORFs) of ASFV China 2018/1 on the activation of cGAS-STING pathway, and found that p17 was able to inhibit cGAS-STING mediated type I IFN production by targeting STING, altering its capacity to recruit both TBK1 and IKK{varepsilon}. Findings presented here will expand our knowledge on the molecular mechanisms by which ASFV counteracts the antiviral innate immunity and provide deep insights into ASF pathogenesis.

immunology↗

bioRxiv2021

The African swine fever virus protease pS273R inhibits DNA sensing cGAS-STING pathway by targeting IKKε

African swine fever virus (ASFV), a large and complex cytoplasmic double-stranded DNA virus, has developed multiple strategies to evade the antiviral innate immune responses. Cytosolic DNA arising from invading ASFV is mainly detected by the cyclic GMP-AMP synthase (cGAS) and then triggers a series of innate immune responses to prevent virus invasion. However, the immune escape mechanism of ASFV remains to be fully clarified. The pS273R of ASFV is a member of the SUMO-1-specific protease family and is crucial for valid virus replication. In this study, we identified pS273R as a suppressor of cGAS-STING pathway mediated type I interferon (IFN) production by ASFV genomic open reading frame screening. The pS273R was further confirmed as an inhibitor of IFN production as well as its downstream antiviral genes in cGAS-STING pathway. Mechanistically, pS273R greatly decreased the cGAS-STING signaling by targeting IKK{varepsilon} but not TBK1 and pS273R was found to disturb the interaction between IKK{varepsilon} and STING through its interaction with IKK{varepsilon}. Further, mutational analyses revealed that pS273R antagonized the cGAS-STING pathway by enzyme catalytic activity, which may affect the IKK{varepsilon} sumoylation state required for the interaction with STING. In summary, our results revealed for the first time that pS273R acts as an obvious negative regulator of cGAS-STING pathway by targeting IKK{varepsilon} via its enzymatic activity, which shows a new immune evasion mechanism of ASFV. ImportanceAfrican swine fever (ASF) is a devastating disease for domestic pigs and wild boar and the pathogen ASFV is a cytoplasmic double-stranded DNA virus. The innate immune cGAS-STING-IFN signaling pathway exerts a critical role in sensing ASFV infection. However, the functions of half ASFV encoded 150 plus proteins are still unknown and the evasion against the cGAS-STING pathway is not resolved. In our study, via ASFV genomic open reading frame (ORF) screening, we found that 29 ASFV proteins could inhibit cGAS-STING signaling pathway, with pS273R showing the most obvious inhibitory effect. Surprisingly, pS273R was found to antagonize the cGAS-STING signaling by targeting IKK{varepsilon}. Moreover, the pS273R enzyme activity is required for its ability to inhibit the cGAS-STING pathway. Our findings deepen the understanding of the immune evasion mechanism of ASFV, which will provide a support for the development of safe and effective ASFV vaccines.

immunology↗

bioRxiv2021

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits - the Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite notable anthropometric variability with ancestry proportions, and a high burden of growth stunting and overweight/obesity in Hispanic/Latino populations. This address this knowledge gap, we analyzed densely-imputed genetic data in a sample of Hispanic/Latino adults, to identify and fine-map common genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (Stage 1, n=59,769) and validated our findings in 9 additional studies (HISLA Stage 2, n=9,336). We conducted a trans-ethnic GWAS with summary statistics from HISLA Stage 1 and existing consortia of European and African ancestries. In our HISLA Stage 1+2 analyses, we discovered one novel BMI locus, as well two novel BMI signals and another novel height signal, each within established anthropometric loci. In our trans-ethnic meta- analysis, we identified three additional novel BMI loci, one novel height locus, and one novel WHRadjBMI locus. We also identified three secondary signals for BMI, 28 for height, and two for WHRadjBMI. We replicated >60 established anthropometric loci in Hispanic/Latino populations at genome-wide significance--representing up to 30% of previously-reported index SNP anthropometric associations. Trans-ethnic meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our novel findings demonstrate that future studies may also benefit from leveraging differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

genetics↗

bioRxiv2021

General Finite-Element Framework of the Virtual Fields Method in Nonlinear Elasticity

This paper presents a method to derive the virtual fields for identifying constitutive model parameters using the Virtual Fields Method (VFM). The VFM is an approach to identify unknown constitutive parameters using deformation fields measured across a given volume of interest. The general principle for solving identification problems with the VFM is first to derive parametric stress field, where the stress components at any point depend on the unknown constitutive parameters, across the volume of interest from the measured deformation fields. Applying the principle of virtual work to the parametric stress fields, one can write scalar equations of the unknown parameters and solve the obtained system of equations to deduce the values of unknown parameters. However, no rules have been proposed to select the virtual fields in identification problems related to nonlinear elasticity and there are multiple strategies possible that can yield different results. In this work, we propose a systematic, robust and automatic approach to reconstruct the systems of scalar equations with the VFM. This approach is well suited to finite-element implementation and can be applied to any problem provided that full-field deformation data are available across a volume of interest. We also successfully demonstrate the feasibility of the novel approach by multiple numerical examples. Potential applications of the proposed approach are numerous in biomedical engineering where imaging techniques are commonly used to observe soft tissues and where alterations of material properties are markers of diseased states. List of symbols O_TBL View this table: org.highwire.dtl.DTLVardef@1addce2org.highwire.dtl.DTLVardef@1808699org.highwire.dtl.DTLVardef@104dadeorg.highwire.dtl.DTLVardef@1bd527aorg.highwire.dtl.DTLVardef@71ef75_HPS_FORMAT_FIGEXP M_TBL C_TBL

bioengineering↗

bioRxiv2021

Genomic analysis reveals the influence of climate change and currents on adaptation in an estuarine species

Understanding the roles of genetic divergence and phenotypic plasticity in adaptation is central to evolutionary biology and important for assessing adaptive potential of species under climate change. Analysis of a chromosome-level assembly and resequencing of individuals across wide latitude distribution in the estuarine oyster (Crassostrea ariakensis) revealed unexpectedly low genomic diversity and population structures shaped by historical glaciation, geological events and oceanographic forces. Strong selection signals were detected in genes responding to temperature and salinity stress, especially of the expanded solute carrier families, highlighting the significance of gene expansion in environmental adaptation. Genes exhibiting high plasticity showed strong selection in upstream regulatory regions that modulate transcription, indicating selection favoring plasticity. Our findings suggest that genomic variation and population structure in marine bivalves are heavily influenced by climate history and physical forces, and gene expansion and selection may enhance phenotypic plasticity that is critical for the adaptation to rapidly changing environments.

evolutionary biology↗

bioRxiv2021

Renalase is a novel tissue and serological biomarker in pancreatic ductal adenocarcinoma

Dysregulated expression of the secretory protein renalase (RNLS) can promote pancreatic ductal adenocarcinoma (PDAC) growth in animal models. We characterized RNLS expression in premalignant and malignant PDAC tissue and investigated whether plasma RNLS levels corresponded to clinical PDAC characteristics. RNLS immunohistochemistry was used to determine the presence and distribution of RNLS in normal pancreas, chronic pancreatitis, PDAC precursor lesions, and PDAC tissues. Associations between pretreatment plasma RNLS and PDAC clinical status were assessed in patients with varied clinical stages of PDAC and included tumor characteristics, surgical resection in locally advanced/borderline resectable PDAC, and overall survival. Data were retrospectively obtained and correlated using non-parametric analysis. Mild to no RNLS was detected by histochemistry in the normal pancreas in the absence of abdominal trauma. In chronic pancreatitis, RNLS immunoreactivity localized to peri-acinar spindle-shaped cells in some samples. It was also widely present in PDAC precursor lesions and PDAC tissue. Among 240 patients with PDAC, elevated plasma RNLS levels were associated with worse tumor characteristics, including greater angiolymphatic invasion (80.0% vs. 58.1%, p = 0.012) and greater node positive disease (76.5% vs. 56.5%, p = 0.024). Overall survival was worse in patients with high plasma RNLS levels with median follow-up of 27.70 months vs. 65.03 months (p < 0.001). RNLS levels also predicted whether patients with locally advanced/borderline resectable (LA/BR) PDAC underwent resection (AUC 0.674; 95%CI 0.42-0.82, p = 0.04). Overall tissue RNLS was increased in both premalignant and malignant PDAC tissues compared to normal pancreas. Elevated plasma RNLS levels were associated with advanced tumor characteristics, decreased overall survival, and reduced resectability in patients with LA/BR PDAC. These studies show that RNLS levels are increased in premalignant pancreatic tissues and that its levels in plasma correspond to the clinical behavior of PDAC.

cancer biology↗

bioRxiv2021

A D-2-hydroxyglutarate biosensor based on specific transcriptional regulator DhdR

D-2-Hydroxyglutarate (D-2-HG) is a metabolite in many physiological metabolic processes. When D-2-HG is aberrantly accumulated due to mutations in isocitrate dehydrogenases or D-2-HG dehydrogenase, it functions in a pro-oncogenic manner and is thus considered a therapeutic target and biomarker in many cancers. In this study, DhdR from Achromobacter denitrificans NBRC 15125 was identified as an allosteric transcription factor that negatively regulates D-2-HG dehydrogenase expression and responds to presence of D-2-HG. It is the first known transcription regulator specifically responding to D-2-HG across all domains of life. Based on the allosteric effect of DhdR, a D-2-HG biosensor was developed by combining DhdR with amplified luminescent proximity homogeneous assay technology. The biosensor was able to detect D-2-HG in serum, urine, and cell culture with high specificity and sensitivity. Additionally, this biosensor was also successfully used to identify the role of D-2-HG metabolism in lipopolysaccharide biosynthesis of Pseudomonas aeruginosa, demonstrating its broad usages.

microbiology↗

bioRxiv2021

Crowdsourced Identification of Multi-Target Kinase Inhibitors for RET- and TAU- Based Disease: the Multi-Targeting Drug DREAM Challenge

A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ( polypharmacology). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology. Author SummaryMany modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact, dirty; they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop cleaner therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease.

pharmacology and toxicology↗

bioRxiv2021

Selective inhibition reveals the regulatory function of DYRK2 in protein synthesis and calcium entry

The dual-specificity tyrosine phosphorylation-regulated kinase DYRK2 has emerged as a key regulator of cellular processes such as proteasome-mediated protein degradation. To gain further insights into its function, we took a chemical biology approach and developed C17, a potent small-molecule DYRK2 inhibitor, through multiple rounds of structure-based optimization guided by a number of co-crystallized structures. C17 displayed an effect on DYRK2 at a single-digit nanomolar IC50 and showed outstanding selectivity for the human kinome containing 467 other human kinases. Using C17 as a chemical probe, we further performed quantitative phosphoproteomic assays and identified several novel DYRK2 targets, including eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) and stromal interaction molecule 1 (STIM1). DYRK2 phosphorylated 4E-BP1 at multiple sites, and the combined treatment of C17 with AKT and MEK inhibitors showed synergistic 4E-BP1 phosphorylation suppression. The phosphorylation of STIM1 by DYRK2 substantially increased the interaction of STIM1 with the ORAI1 channel, and C17 impeded the store-operated calcium entry process. Collectively, these studies further expand our understanding of DYRK2 and provide a valuable tool to further pinpoint its biological function.

biochemistry↗

bioRxiv2021

Alien chromatin but not Fhb7 confers Fusarium head blight resistance in wheat breeding

The lack of resistance resources is a major bottleneck for wheat Fusarium head blight (FHB) resistance breeding. Three wheat-Th. elongatum FHB resistant translocation lines have been developed and used for wheat breeding without yield penalty. Transcriptomic analysis identified a derivative glutathione S-transferase transcript T26102, which was homologous to Fhb7 and induced dramatically by Fusarium graminearum. Unlike other studies, Fhb7 homologs were detected not only in Thinopyrum but also in Elymus, Leymus, Pseudoroegeria and Roegeria. We also found that several wheat-Th. ponticum derivatives carrying Fhb7 and its homologs were highly susceptible to FHB. Moreover, the transgenic plants expressing Fhb7 and its homolog on different backgrounds did not improve the FHB resistance. One Sentence SummaryThe GST-encoding Fhb7 candidate cannot improve Fusarium head blight resistance in wheat breeding.

genetics↗

bioRxiv2021

Pre-stimulus alpha activities predict the confidence in subjective judgment by modulating post-stimulus theta oscillation

Even when making arbitrary decisions, people tend to feel varying levels of confidence, which is associated with the pre-stimulus neural oscillation of the brain. We investigated varying confidence in a pure subjective judgment task, and how this confidence was predicted by pre-stimulus alpha oscillations. Participants made pure subjective judgments where their prior experience seems to be helpful but actually useless, and their fluctuating confidence was related to the choice boundary process rather than the evidence accumulation process, suggesting participants underwent varying confidence resulting from the internal signals. With EEG and MEG analyses, we not only revealed the linkage between confidence and pre-stimulus alpha activities, but also successfully located this linkage onto decision-making relevant brain areas, i.e. MCC/PCC and SMA. Moreover, we unveiled a specific pathway underlying such linkage, that is, the influence of pre-stimulus alpha activities on decision confidence was fulfilled through modulating post-stimulus theta activities of SMA.

neuroscience↗

bioRxiv2021

BRD2 inhibition blocks SARS-CoV-2 infection in vitro by reducing transcription of the host cell receptor ACE2

SARS-CoV-2 infection of human cells is initiated by the binding of the viral Spike protein to its cell-surface receptor ACE2. We conducted a targeted CRISPRi screen to uncover druggable pathways controlling Spike protein binding to human cells. We found that the protein BRD2 is required for ACE2 transcription in human lung epithelial cells and cardiomyocytes, and BRD2 inhibitors currently evaluated in clinical trials potently block endogenous ACE2 expression and SARS-CoV-2 infection of human cells, including those of human nasal epithelia. Moreover, pharmacological BRD2 inhibition with the drug ABBV-744 inhibited SARS-CoV-2 replication in Syrian hamsters. We also found that BRD2 controls transcription of several other genes induced upon SARS-CoV-2 infection, including the interferon response, which in turn regulates the antiviral response. Together, our results pinpoint BRD2 as a potent and essential regulator of the host response to SARS-CoV-2 infection and highlight the potential of BRD2 as a novel therapeutic target for COVID-19.

cell biology↗

bioRxiv2021

DeepHBV: A deep learning model to predict hepatitis B virus (HBV) integration sites.

Hepatitis B virus (HBV) is one of the main causes for viral hepatitis and liver cancer. Previous studies showed HBV can integrate into host genome and further promote malignant transformation. In this study, we developed an attention-based deep learning model DeepHBV to predict HBV integration sites by learning local genomic features automatically. We trained and tested DeepHBV using the HBV integration sites data from dsVIS database. Initially, DeepHBV showed AUROC of 0.6363 and AUPR of 0.5471 on the dataset. Adding repeat peaks and TCGA Pan Cancer peaks can significantly improve the model performance, with an AUROC of 0.8378 and 0.9430 and an AUPR of 0.7535 and 0.9310, respectively. On independent validation dataset of HBV integration sites from VISDB, DeepHBV with HBV integration sequences plus TCGA Pan Cancer (AUROC of 0.7603 and AUPR of 0.6189) performed better than HBV integration sequences plus repeat peaks (AUROC of 0.6657 and AUPR of 0.5737). Next, we found the transcriptional factor binding sites (TFBS) were significantly enriched near genomic positions that were paid attention to by convolution neural network. The binding sites of AR-halfsite, Arnt, Atf1, bHLHE40, bHLHE41, BMAL1, CLOCK, c-Myc, COUP-TFII, E2A, EBF1, Erra and Foxo3 were highlighted by DeepHBV attention mechanism in both dsVIS dataset and VISDB dataset, revealing the HBV integration preference. In summary, DeepHBV is a robust and explainable deep learning model not only for the prediction of HBV integration sites but also for further mechanism study of HBV induced cancer. Author summaryHepatitis B virus (HBV) is one of the main causes for viral hepatitis and liver cancer. Previous studies showed HBV can integrate into host genome and further promote malignant transformation. In this study, we developed an attention-based deep learning model DeepHBV to predict HBV integration sites by learning local genomic features automatically. The performance of DeepHBV model significantly improves after adding genomic features, with an AUROC of 0.9430 and an AUPR of 0.9310. Furthermore, we enriched the transcriptional factor binding sites of proteins by convolution neural network. In summary, DeepHBV is a robust and explainable deep learning model not only for the prediction of HBV integration sites but also for the further study of HBV integration mechanism.

bioinformatics↗

bioRxiv2020

Evaluation of Postharvest Senescence in Broccoli Via Hyperspectral Imaging

Fresh fruits and vegetables are invaluable for human health, but their quality deteriorates before reaching consumers due to ongoing biochemical processes and compositional changes. The current lack of any objective indices for defining "freshness" of fruits or vegetables limits our capacity to control product quality leading to food loss and waste. It has been hypothesized that certain proteins and compounds such as glucosinolates can be used as an indicator to monitor the freshness of vegetables and fruits. However, it is challenging to "visualize" the proteins and bioactive compounds during the senescence processes. In this work, we propose machine learning hyperspectral image analysis approaches for estimating glucosinolates levels to detect postharvest senescence in broccoli. Therefore, we set out the research to quantify glucosinolates as "freshness-indicators" which aid in the development of an innovative and accessible tool to precisely estimate the freshness of produce. Such a tool would allow for significant advancement in postharvest logistics and supporting the availability for high-quality and nutritious fresh produce.

bioengineering↗