Biology subjects

Cui, Z.

Publications and source records attributed to Cui, Z..

At least 91 records · Page 5Linked to original sources

bioRxiv2021

Detection of Multiple Types of Cancer Driver Mutations Us-ing Targeted RNA Sequencing in NSCLC

Currently, DNA and RNA are used separately to capture different types of gene mutations. DNA is commonly used for the detection of SNVs, indels and CNVs; RNA is used for analysis of gene fusion and gene expression. To perform both DNA sequencing (DNA-seq) and RNA-seq, material is divided into two copies, and two different procedures are required for sequencing. Due to overconsumption of samples and experimental process complexity, it is necessary to create an experimental method capable of analyzing SNVs, indels, fusions and expression. We developed an RNA-based hybridization capture panel targeting actionable driver oncogenes in solid tumors and corresponding sample preparation and bioinformatics workflows. Analytical validation with an RNA standard reference containing 16 known fusion mutations and 6 SNV mutations demonstrated a detection specificity of 100.0% [95% CI 88.7%~100.0%] for SNVs and 100.0% [95% CI 95.4%~100.0%] for fusions. The targeted RNA panel achieved a 0.73-2.63 copies/ng RNA lower limit of detection (LOD) for SNVs and 0.21-6.48 copies/ng RNA for fusions. Gene expression analysis revealed a correlation greater than 0.9 across all 15 cancer-related genes between the RNA-seq results and targeted RNA panel. Among 1253 NSCLC FFPE tumor samples, multiple mutation types were called from DNA- and RNA-seq data and compared between the two assays. The DNA panel detected 103 fusions and 21 METex14 skipping events; 124 fusions and 26 METex14 skipping events were detected by the target RNA panel; 21 fusions and 4 METex14 skipping events were only detected by the target RNA panel. Among the 173 NSCLC samples negative for targetable mutations by DNA-seq, 15 (15/173, 8.67%) showed targetable gene fusions that may change clinical decisions with RNA-seq. In total, 226 tier I and tier II missense variants for NSCLC were analyzed at genomic (DNA-seq) and transcriptomic (RNA-seq) levels. The positive percent agreement (PPA) was 97.8%, and the positive predictive value (PPV) was 98.6%. Interestingly, variant allele frequencies were generally higher at the RNA level than at the DNA level, suggesting relatively dominant expression of mutant alleles. PPA was 97.6% and PPV 99.38% for EGFR 19del and 20ins variants. We also explored the relationship of RNA expression with gene copy number and protein expression. The RPKM of EGFR transcripts assessed by the RNA panel showed a linear relationship with copy number quantified by the DNA panel, with an R of 0.8 in 1253 samples. In contrast, MET gene expression is regulated in a more complex manner. In IHC analysis, all 3+ samples exhibited higher RPKM levels; IHC level of 2+ and below showed lower RNA expression. Parallel DNA- and RNA-seq and systematic analysis demonstrated the accuracy and robustness of the RNA sequencing panel in identifying multiple types of variants for cancer therapy. Contact: zhaojia0327@126.com

molecular biology↗

bioRxiv2021

Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth

The spatial layout of large-scale functional brain networks differs between individuals and is particularly variable in association cortex that has been implicated in a broad range of psychiatric disorders. However, it remains unknown whether this variation in functional topography is related to major dimensions of psychopathology in youth. Capitalizing on a large sample with 27-minutes of high-quality functional MRI data (n=790, ages 8-23 years) and advances in machine learning, we examined associations between functional topography and four correlated dimensions of psychopathology (fear, psychosis, externalizing, anxious-misery) as well as an overall psychopathology factor. We found that functional topography significantly predicted individual differences in dimensions of psychopathology, driven mainly by robust associations between topography and overall psychopathology. Reduced cortical representations of association networks were among the most important features of the model. Our results emphasize the value of considering systematic differences in functional neuroanatomy for personalized diagnostics and therapeutics in psychiatry.

neuroscience↗

bioRxiv2021

Developmental coupling of cerebral blood flow and fMRI fluctuations in youth

To support brain development during youth, the brain must balance energy delivery and consumption. Previous studies in adults have demonstrated high coupling between cerebral blood flow and brain function as measured using functional neuroimaging, but how this relationship evolves over adolescence is unknown. To address this gap, we studied a sample of 831 children and adolescents (478 females, ages 8-22) from the Philadelphia Neurodevelopmental Cohort who were scanned at 3T with both arterial spin labeled (ASL) MRI and resting-state functional MRI (fMRI). Local coupling between cerebral blood flow (CBF, from ASL) and the amplitude of low frequency fluctuations (ALFF, from fMRI) was first quantified using locally weighted regressions on the cortical surface. We then used generalized additive models to evaluate how CBF-ALFF coupling was associated with age, sex, and executive function. Enrichment of effects within canonical functional networks was evaluated using spin-based permutation tests. Our analyses revealed tight CBF-ALFF coupling across the brain. Whole-brain CBF-ALFF coupling decreased with age, largely driven by coupling decreases in the inferior frontal cortex, precuneus, visual cortex, and temporoparietal cortex (pfdr <0.05). Females had stronger coupling in the frontoparietal network than males (pfdr <0.05). Better executive function was associated with decreased coupling in the somatomotor network (pfdr <0.05). Overall, we found that CBF-ALFF coupling evolves in development, differs by sex, and is associated with individual differences in executive function. Future studies will investigate relationships between maturational changes in CBF-ALFF coupling and the presence of psychiatric symptoms in youth. SIGNIFICANCEThe functions of the human brain are metabolically expensive and reliant on coupling between cerebral blood flow and neural activity. Previous neuroimaging studies in adults demonstrate tight physiology-function coupling, but how this coupling evolves over development is unknown. Here, we examine the relationship between blood flow as measured by arterial spin labeling and the amplitude of low frequency fluctuations from resting-state magnetic resonance imaging across a large sample of youth. We demonstrate regionally specific changes in coupling over age and show that variations in coupling are related to biological sex and executive function. Our results highlight the importance of CBF-ALFF coupling throughout development; we discuss its potential as a future target for the study of neuropsychiatric diseases.

neuroscience↗

bioRxiv2021

Dissociable Multi-scale Patterns of Development in Personalized Brain Networks

The brain is organized into networks at multiple resolutions, or scales, yet studies of functional network development typically focus on a single scale. Here, we derived personalized functional networks across 29 scales in a large sample of youths (n=693, ages 8-23 years) to identify multi-scale patterns of network re-organization related to neurocognitive development. We found that developmental shifts in inter-network coupling systematically adhered to and strengthened a functional hierarchy of cortical organization. Furthermore, we observed that scale-dependent effects were present in lower-order, unimodal networks, but not higher-order, transmodal networks. Finally, we found that network maturation had clear behavioral relevance: the development of coupling in unimodal and transmodal networks dissociably mediated the emergence of executive function. These results delineate maturation of multi-scale brain networks, which varies according to a functional hierarchy and impacts cognitive development.

neuroscience↗

bioRxiv2021

Thin-Film Freeze-Drying of a Norovirus Vaccine Candidate

A bivalent Norovirus vaccine candidate has been developed that contains Norovirus strain GI.1 Norwalk-virus like particles (VLP) and strain GII.4 Consensus VLP adsorbed onto aluminum (oxy)hydroxide. In the present study, we tested the feasibility of converting the vaccine from a liquid suspension into dry powder by thin-film freeze-drying (TFFD). With the proper amount of trehalose and/or sucrose as cryoprotectant, TFFD can be applied to transform the Norovirus vaccine candidate into dry powders without causing antigen loss or particle aggregation, while maintaining the potency of the antigens within a specified acceptable range. In an accelerated stability study, the potency of the antigens was also maintained in the specified acceptable range after the dry powders were stored for eight weeks at 40{degrees}C, 75% relative humidity. The dry powder Norovirus vaccine offers the potential to eliminate the cold chain requirement for transport and/or storage of the vaccine.

pharmacology and toxicology↗

bioRxiv2021

Sex Differences in Functional Topography of Association Networks

Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here we leveraged an advanced machine learning method (sparsity-regularized nonnegative matrix factorization) to define individualized functional networks in 693 youth (ages 8-23 years) who underwent functional magnetic resonance imaging as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 83% accuracy (p<0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention and default mode networks. Mass-univariate analyses using generalized additive models with penalized splines provided convergent results. Comparative analysis using transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography correlated with the expression of genes on the X-chromosome. These results identify normative developmental sex differences in the functional topography of association networks and highlight the role of sex as a biological variable in shaping brain development in youth. SIGNIFICANCE STATEMENTWe identify normative developmental sex differences in the functional topography of personalized association networks including the ventral attention network and default mode network. Furthermore, chromosomal enrichment analyses revealed that sex differences in multivariate patterns of functional topography were spatially coupled to the expression of X-linked genes as well as astrocytic and excitatory neuronal cell-type signatures. These results highlight the role of sex as a biological variable in shaping functional brain development in youth.

neuroscience↗

bioRxiv2021

A Developmental Reduction of the Excitation:Inhibition Ratio in Association Cortex during Adolescence.

Adolescence is hypothesized to be a critical period for the development of association cortex. A reduction of the excitation:inhibition (E:I) ratio is a hallmark of critical period development; however it has been unclear how to assess the development of the E:I ratio using non-invasive neuroimaging techniques. Here, we used pharmacological fMRI with a GABAergic benzodiazepine challenge to empirically generate a model of E:I ratio based on multivariate patterns of functional connectivity. In an independent sample of 879 youth (ages 8-22 years), this model predicted reductions in the E:I ratio during adolescence, which were specific to association cortex and related to psychopathology. These findings support hypothesized shifts in E:I balance of association cortices during a neurodevelopmental critical period in adolescence. TeaserInhibitory maturation of the association cortex reflects an adolescent critical period.

neuroscience↗

bioRxiv2021

Mobile Footprinting: Linking Individual Distinctiveness in Mobility Patterns to Mood, Sleep, and Brain Functional Connectivity

Mapping individual differences in behavior is fundamental to personalized neuroscience. Here, we establish that statistical patterns of smartphone-based mobility features represent unique "footprints" that allow individual identification. Critically, mobility footprints exhibit varying levels of person-specific distinctiveness and are associated with individual differences in affective instability, circadian irregularity, and brain functional connectivity. Together, this work suggests that real-world mobility patterns may provide an individual-specific signature linking brain, behavior, and mood.

neuroscience↗

bioRxiv2021

The Impact of a Dynamic Working Environment on Human Gut Microbiota

Gut microbiota dysbiosis is associated with a variety of diseases, such as inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), metabolic diseases, allergic diseases, neurodevelopmental disorders and cancer. The human gut microbiota can be influenced by a variety of factors, including geography, dietary habits, living environment, age and altered lifestyle etc. This study was conducted to explore the gut microbiota compositions in officials who are in a stable working environment and train drivers who are in a dynamic working environment. Microbiota communities in the feces of 80 officials and 88 train drivers were analyzed using Illumina MiSeq sequencing targeting the V3-V4 region of 16S ribosomal RNA (rRNA) gene and ITS1 region of fungi. There were significant differences between the two groups in diversity and richness of gut microbiota, while the microbial community compositions of the two groups were similar. The relationship between gut microbiota and clinical characteristics was investigated. We found that more bacteria and fungi were positively correlated with clinical characteristics. Functional prediction analysis of the gut microbiota between the two groups by PICRUSt2 revealed significant differences between the official group and the train driver group. Elucidating these differences of the microbiome between the two groups will provide a foundation understanding of the impact of a dynamic environment on gut microbiota.

microbiology↗

bioRxiv2021

Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients

Glioblastoma widely affects brain structure and function, and remodels neural connectivity. Characterizing the neural connectivity in glioblastoma may provide a tool to understand tumor invasion. Here, using a structural connectome approach based on diffusion MRI, we quantify the global and regional connectome disruptions in individual glioblastoma patients and investigate the prognostic value of connectome disruptions and topological properties. We show that the disruptions in the normal-appearing brain beyond the lesion could mediate the topological alteration of the connectome (P <0.001), associated with worse patient performance (P <0.001), cognitive function (P <0.001), and survival (overall survival: HR: 1.46, P = 0.049; progression-free survival: HR: 1.49, P = 0.019). Further, the preserved connectome in the normal-appearing brain demonstrates evidence of remodeling, where increased connectivity is associated with better overall survival (log-rank P = 0.005). Our approach reveals the glioblastoma invasion invisible on conventional MRI, promising to benefit patient stratification and precise treatment.

neuroscience↗

bioRxiv2021

Super-delta2: An Enhanced Differential Expression Analysis Procedure for Multi-Group Comparisons of RNA-seq Data

BackgroundWe developed super-delta2, a differential gene expression analysis pipeline designed for multi-group comparisons for RNA-seq data. It includes a customized one-way ANOVA F-test and a post-hoc test for pairwise group comparisons; both are designed to work with a multivariate normalization procedure to reduce technical noise. It also includes a trimming procedure with bias-correction to obtain robust and approximately unbiased summary statistics used in these tests. We demonstrated the asymptotic applicability of super-delta2 to log-transformed read counts in RNA-seq data by large sample theory based on Negative Binomial Poisson (NBP) distribution. ResultsWe compared super-delta2 with three commonly used RNA-seq data analysis methods: limma/voom, edgeR, and DESeq2 using both simulated and real datasets. In all three simulation settings, super-delta2 not only achieved the best overall statistical power, but also was the only method that controlled type I error at the nominal level. When applied to a breast cancer dataset to identify differential expression pattern associated with multiple pathologic stages, super-delta2 selected more enriched pathways than other methods, which are directly linked to the underlying biological condition (breast cancer). ConclusionsBy incorporating trimming and bias-correction in the normalization step, super-delta2 was able to achieve tight control of type I error. Because the hypothesis tests are based on asymptotic normal approximation of the NBP distribution, super-delta2 does not require computationally expensive iterative optimization procedures used by methods such as edgeR and DESeq2, which occasionally have convergence issues.

bioinformatics↗

bioRxiv2021

Analysis of Spleen Histopathology, Splenocyte composition and Hematological Parameters in Mice Infected with Plasmodium berghei K173

Malaria is a fatal disease that presents clinically as a continuum of symptoms and severity, which are determined by complex host-parasite interactions. Clearance of infection is believed to be accomplished by the spleen and mononuclear phagocytic system (MPS), both in the presence and absence of artemisinin treatment. The spleen filters infected RBCs from circulation through immune-mediated recognition of the infected RBCs followed by phagocytosis. Using different strains of mice infected with P. berghei K173 (PbK173), the mechanisms leading to splenomegaly, histopathology, splenocyte activation and proliferation, and their relationship to control of parasitemia and host mortality were examined. Survival time of mice infected with PbK173 varied, although the infection was uniformly lethal. Mice of the C57BL/6 strain were the most resistant, while mice of the strain ICR were the most susceptible. BALB/c and KM mice were intermediate. In the course of PbK173 infection, both strains of mice experienced significant splenomegaly. Parasites were observed in the red pulp at 3 days post infection in all animals. All spleens retained late trophozoite stages as well as a fraction of earlier ring-stage parasites. The percentages of macrophages in infected C57BL/6 and KM mice were higher than uninfected mice on 8 dpi. Spleens of infected ICR and KM mice exhibited structural disorganization and remodeling. Furthermore, parasitemia was significantly higher in KM versus C57BL/6 mice at 8 dpi. The percentages of macrophages in ICR infected mice were lower than uninfected mice, and the parasitemia was higher than other strains. The results presented here demonstrate the rate of splenic mechanical filtration and the splenic macrophages likely contribute to an individuals total parasite burden. This in turn can influence the pathogenesis of malaria. Finally, different genetic backgrounds of mice have different splenic mechanisms for controlling malaria infection.

microbiology↗

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↗

bioRxiv2021

DenovoProfiling: a webserver for de novo generated molecule library profiling

With the advances of deep learning techniques, various architectures for molecular generation have been proposed for de novo drug design. Successful cases from academia and industrial demonstrated that the deep learning based de novo molecular design could efficiently accelerate the drug discovery process. The flourish of the de novo molecular generation methods and applications created great demand for the visualization and functional profiling for the de novo generated molecules. The rising of publicly available chemogenomic databases lays good foundations and create good opportunities for comprehensive profiling of the de novo library. In this paper, we present DenovoProfiling, a web server dedicated for de novo library visualization and functional profiling. Currently, DenovoProfiling contains six modules: (1) identification & visualization, (2) chemical space, (3) scaffold analysis, (4) molecular alignment, (5) target & pathways, and (6) drugs mapping. DenovoProfiling could provide structural identification, chemical space exploration, drugs mapping, and targets & pathways. The comprehensive annotated information could give user a clear picture of their de novo library and could provide guidance in the further selection of candidates for synthesis and biological confirmation. DenovoProfiling is freely available at http://denovoprofiling.xielab.net.

bioinformatics↗

bioRxiv2020

Intranasal administration of SARS-CoV-2 neutralizing human antibody prevents infection in mice

Prevention of SARS-CoV-2 infection at the point of nasal entry is a novel strategy that has the potential to help contain the ongoing pandemic. Using our proprietary technologies, we have engineered a human antibody that recognizes SARS-CoV-2 S1 spike protein with an enhanced affinity for mucin to improve the antibodys retention in respiratory mucosa. The modified antibody, when administered into mouse nostrils, was shown to block infection in mice that were exposed to high titer SARS-CoV-2 pseudovirus 10 hours after the initial antibody treatment. Our data show that the protection against SARS-CoV-2 infection is effective in both nasal and lung areas 7 days after viral exposure. The modified antibody is stable in a nasal spray formulation and maintains its SARS-CoV-2 neutralizing activity. Nasal spray of the modified antibody can be developed as an affordable and effective prophylactic product to protect people from infection by exposure to SARS-CoV-2 virus in the air. One-sentence summaryA Fc-modified human antibody prevents SARS-CoV-2 viral infection via nasal administration

bioengineering↗

bioRxiv2020

Double Lock of a Potent Human Monoclonal Antibody against SARS-CoV-2

Receptor recognition and subsequent membrane fusion are essential for the establishment of successful infection by SARS-CoV-2. Halting these steps can cure COVID-19. Here we have identified and characterized a potent human monoclonal antibody, HB27, that blocks SARS-CoV-2 attachment to its cellular receptor at sub-nM concentrations. Remarkably, HB27 can also prevent SARS-CoV-2 membrane fusion. Consequently, a single dose of HB27 conferred effective protection against SARS-CoV-2 in two established mouse models. Rhesus macaques showed no obvious adverse events when administrated with 10-fold of effective dose of HB27. Cryo-EM studies on complex of SARS-CoV-2 trimeric S with HB27 Fab reveal that three Fab fragments work synergistically to occlude SARS-CoV-2 from binding to ACE2 receptor. Binding of the antibody also restrains any further conformational changes of the RBD, possibly interfering with progression from the prefusion to the postfusion stage. These results suggest that HB27 is a promising candidate for immuno-therapies against COVID-19. HighlightsO_LISARS-CoV-2 specific antibody, HB27, blocks viral receptor binding and membrane fusion C_LIO_LIHB27 confers prophylactic and therapeutic protection against SARS-CoV-2 in mice models C_LIO_LIRhesus macaques showed no adverse side effects when administered with HB27 C_LIO_LICryo-EM studies suggest that HB27 sterically occludes SARS-CoV-2 from its receptor C_LI

biophysics↗

bioRxiv2020

Dynamic integration and segregation of amygdala subregional functional circuits linking to physiological arousal

The dynamical organization of brain networks is essential to support human cognition and emotion for rapid adaption to ever-changing environment. As the core nodes of emotion-related brain circuitry, the basolateral amygdala (BLA) and centromedial amygdala (CMA) as two major amygdalar nuclei, are recognized to play distinct roles in affective functions and internal states, via their unique connections with cortical and subcortical structures in rodents. However, little is known how the dynamical organization of emotion-related brain circuitry reflects internal autonomic responses in humans. Using resting-state functional magnetic resonance imaging (fMRI) with K-means clustering approach in a total of 79 young healthy individuals (cohort 1: 42; cohort 2: 37), we identified two distinct states of BLA- and CMA-based intrinsic connectivity patterns, with one state (integration) showing generally stronger BLA- and CMA-based intrinsic connectivity with multiple brain networks, while the other (segregation) exhibiting weaker yet dissociable connectivity patterns. In an independent cohort 2 of fMRI data with concurrent recording of skin conductance, we replicated two similar dynamic states and further found higher skin conductance level in the integration than segregation state. Moreover, machine learning-based Elastic-net regression analyses revealed that time-varying BLA and CMA intrinsic connectivity with distinct network configurations yield higher predictive values for spontaneous fluctuations of skin conductance level in the integration than segregation state. Our findings highlight dynamic functional organization of emotion-related amygdala nuclei circuits and networks and its links to spontaneous autonomic arousal in humans.

neuroscience↗

bioRxiv2020

Characterisation of bacteriophage JD419, a Staphylococcal phage with an unusual morphology and broad host range

As an antimicrobial therapy, therapeutic phages, also known as "Phage therapy" are able to inactivate multi-drug resistant bacteria such as methicillin and vancomycin resistant S. aureus and thus present a possible treatment for infections that are otherwise incurable. In this paper, we present a novel phage called JD419, which has a remarkably wide host-range. The virulent phage JD419 exhibits an elongated capsid and was able to infect and lyse 83 of all 129 tested clinical strains (64.3%) of multi-drug resistant S. aureus including MRSA. To evaluate the potential as a therapeutic phage, we tested the ability of phage JD419 to remain infectious after treatment exceeding physiological pH or temperature. The lytic activity of the phage was retained at pH values of 6.0-8.0 and at temperatures below 50{degrees}C. As phages sometimes contain virulence genes, we sequenced the complete genome of JD419. The 45509 bp genome contains a predicted 65 ORFs, none of which show homology to any known virulence or antibiotic resistance genes. Our study illustrates that Staphylococcus phage JD419 has the potential to be used for diagnostic, prophylaxic and therapeutic purposes.

microbiology↗