Biology subjects

Gao, X.

Publications and source records attributed to Gao, X..

At least 271 records · Page 15Linked to original sources

bioRxiv2021

A new single-cell level R-index for EGFR-TKI resistance and survival prediction in LUAD

EGFR-TKIs achieved excellent efficacy in EGFR-mutated patients. Unfortunately, most patients would inevitably develop progressive disease within a median of 10 to 14 months. Predicting the resistance probability remains a challenge. Therefore, we created an R-index model trained by single-cell RNA data with the OCLR algorithm. This model can be applied to estimate the level of EGFR-TKI resistance in cell line and xenograft mice models and predict prognosis in multiple cohorts. Comparing the high and the low R-index group, we found that the glycolysis pathway and KRAS up-regulation pathway were related to resistance, and MDSC was the leading cause of immunosuppression in the tumor microenvironment. These results are consistent with previous studies indicating that the R-index provides an insight into resistance status and a new way to explore resistance mechanisms and clinical treatment by the combination of Glucose metabolism-targeted or MDSC-targeted therapies. This is the first quantification method of EGFR-TKI resistance based on single-cell sequencing data solving the problem of the mixed resistance state of tumor cells and helping explore transcriptome characteristics of drug-resistant cell populations.

bioinformatics↗

bioRxiv2021

Deep learning identifies and quantifies recombination hotspot determinants

Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related to the hotspots, their contributions to the recombination hotspots have not been quantified, and other determinants are yet to be elucidated. Here, we develop a computational method, RHSNet, based on deep learning and signal processing, to identify and quantify the hotspot determinants in a purely data-driven manner, utilizing datasets from various studies, populations, sexes, and species. In addition to being able to identify hotspot regions and the well-known determinants accurately, RHSNet is sensitive to the difference between different PRDM9 alleles and different sexes, and can generalize to PRDM9-lacking species. The cross-sex, cross-population, and cross-species studies suggest that the proposed method has the potential to identify and quantify the evolutionary determinant motifs. TeaserRHSNet can accurately identify and quantify recombination hotspot determinants across different studies, sexes, populations, and species.

bioinformatics↗

bioRxiv2021

Self-supervised contrastive learning for integrative single cell RNA-seq data analysis

Single-cell RNA-sequencing (scRNA-seq) has become a powerful tool to reveal the complex biological diversity and heterogeneity among cell populations. However, the technical noise and bias of the technology still have negative impacts on the downstream analysis. Here, we present a self-supervised Contrastive LEArning framework for scRNA-seq (CLEAR) profile representation and the downstream analysis. CLEAR overcomes the heterogeneity of the experimental data with a specifically designed representation learning task and thus can handle batch effects and dropout events. In the task, the deep learning model learns to pull together the representations of similar cells while pushing apart distinct cells, without manual labeling. It achieves superior performance on a broad range of fundamental tasks, including clustering, visualization, dropout correction, batch effect removal, and pseudo-time inference. The proposed method successfully identifies and illustrates inflammatory-related mechanisms in a COVID-19 disease study with 43,695 single cells from peripheral blood mononuclear cells. Further experiments to process a million-scale single-cell dataset demonstrate the scalability of CLEAR. This scalable method generates effective scRNA-seq data representation while eliminating technical noise, and it will serve as a general computational framework for single-cell data analysis.

bioinformatics↗

bioRxiv2021

DeeReCT-TSS: A novel meta-learning-based method annotates TSS in multiple cell types based on DNA sequences and RNA-seq data

The accurate annotation of transcription start sites (TSSs) and their usage is critical for the mechanistic understanding of gene regulation under different biological contexts. To fulfill this, on one hand, specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner. On the other hand, various computational tools have also been developed for in silico prediction of TSSs solely based on genomic sequences. Most of these computational tools cast the problem as a binary classification task on a balanced dataset and thus result in drastic false positive predictions when applied on the genome-scale. To address these issues, we present DeeReCT-TSS, a deep-learning-based method that is capable of TSSs identification across the whole genome based on both DNA sequences and conventional RNA-seq data. We show that by effectively incorporating these two sources of information, DeeReCT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types. Furthermore, we develop a meta-learning-based extension for simultaneous transcription start site (TSS) annotation on 10 cell types, which enables the identification of cell-type-specific TSS. Finally, we demonstrate the high precision of DeeReCT-TSS on two independent datasets from the ENCODE project by correlating our predicted TSSs with experimentally defined TSS chromatin states. Our application, pre-trained models and data are available at https://github.com/JoshuaChou2018/DeeReCT-TSS_release.

bioinformatics↗

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

FMRI multi-scale cortical spontaneous activity: 7T vs. 3T

This paper describes the use of the Human Connectome Project (HCP) data for mapping the distribution of spontaneous activity in the human brain across different spatial scales, magnets and individuals. Specifically, the resting-state functional MRI signals acquired under the HCP 3 tesla (T) and 7T magnet protocols were measured by computational methods at multiple spatial scales across the cerebral cortex using: 1) an amplitude metric on a single measuring unit (ALFF), 2) a functional homogeneity metric on a set of neighboring measuring units (ReHo) and 3) a homotopic functional connectivity metric on pairs of symmetric measuring units between the two hemispheres (VMHC). Statistical assessments on these measurements revealed that all the raw metrics were enhanced by the higher magnetic field, highlighting their dependence on magnet field strength. Measurement reliability of these global measurements were moderate to high and comparable between between 3T and 7T magnets. The differences in these measurements introduced by the higher magnetic field were spatially dependent and varied according to specific cortical regions. Specifically, the spatial contrasts of ALFF were enhanced by the 7T magnet within the anterior cortex while weakened in the posterior cortex. This is opposite for ReHo and VMHC. This scale-dependent phenomena also held true for measurement reliabilities, which were enhanced by the 7T magnet for ReHo and VMHC and weakened for ALFF. These reliability differences were primarily located in high-order associate cortex, reflecting the corresponding changes of individual differences: higher between-subject variability and lower within-subject variability for ReHo and VMHC, lower between-subject variability and higher within-subject variability for ReHo and VMHC with respect to higher magnetic field strength. Our work, for the first time, demonstrates the spatial-scale dependence of spontaneous cortical activity measurements in the human brain and their test-retest reliability across different magnet strengths, and discussed about the statistical implications for experimental design using resting-state fMRI.

neuroscience↗

bioRxiv2021

Somatic genetics analysis of sleep in adult mice

Classical forward and reverse mouse genetics approaches require germline mutations and, thus, are unwieldy to study sleep functions of essential genes or redundant pathways. It is also time-consuming to conduct electroencephalogram/electromyogram-based mouse sleep screening owning to labor-intensive surgeries and genetic crosses. Here, we describe a highly accurate SleepV (video) system and adeno-associated virus (AAV)-based adult brain chimeric (ABC)- expression/knockout (KO) platform for somatic genetics analysis of sleep in adult mice. A pilot ABC-expression screen identifies CREB and CRTC1, of which constitutive or inducible expression significantly reduces quantity and quality of non-rapid eye movement sleep. Whereas ABC-KO of exon 13 of Sik3 by AAV-Cre injection in Sik3-E13flox/flox adult mice phenocopies Sleepy (Sik3Slp/+) mice, ABC-CRISPR of Slp/Sik3 reverses hypersomnia of Sleepy mice, indicating a direct role of SLP/SIK3 kinase in sleep regulation. Multiplex ABC-CRISPR of both orexin/hypocretin receptors causes narcolepsy-like episodes, enabling one-step analysis of redundant genes in adult mice. Finally, ABC-expression/KO screen identifies Ankrd63 and NR1 as two potentially new sleep regulators. Therefore, this somatic genetics approach should facilitate high-throughput analysis of sleep regulatory genes, especially for essential or redundant genes, in adult mice by skipping the mouse development and genetic crosses.

neuroscience↗

bioRxiv2021

Integrative Clinical and Molecular Characterization of Translocation Renal Cell Carcinoma

ABSTRACTTranslocation renal cell carcinoma (tRCC) is an aggressive and poorly-characterized subtype of kidney cancer driven by MiT/TFE gene fusions. Here, we define the landmarks of tRCC through an integrative analysis of 152 tRCC patients identified across multiple genomic, clinical trial, and retrospective cohorts. Most tRCCs harbor few somatic alterations apart from MiT/TFE fusions and homozygous deletions at chromosome 9p21.3 (19.2% of cases). Transcriptionally, tRCCs display a heightened NRF2-driven antioxidant response that is associated with resistance to many targeted therapies. Consistently, we find that outcomes for tRCC patients treated with vascular endothelial growth factor receptor inhibitors (VEGFR-TKI) are worse than those treated with immune checkpoint inhibition (ICI). Multiparametric immunofluorescence confirmed the presence of CD8 + tumor-infiltrating T cells compatible with a clinical benefit from ICI and revealed an exhaustion immunophenotype distinct from clear cell RCC. Our findings comprehensively define the clinical and molecular features of tRCC and may inspire new therapeutic hypotheses.

cancer biology↗

bioRxiv2021

Reduced graphene oxide membrane as supporting film for high-resolution cryo-EM

Although single-particle cryogenic electron microscopy (cryo-EM) has been applied extensively for elucidating many crucial biological mechanisms at the molecular level, this technique still faces critical challenges, the major one of which is to prepare the high-quality cryo-EM specimen. Aiming to achieve a more reproducible and efficient cryo-EM specimen preparation, novel supporting films including graphene-based two-dimensional materials have been explored in recent years. Here we report a robust and simple method to fabricate EM grids coated with single- or few-layer reduced graphene oxide (RGO) membrane in large batch for high-resolution cryo-EM structural determination. The RGO membrane has decreased interlayer space and enhanced electrical conductivity in comparison to regular graphene oxide (GO) membrane. Moreover, we found that the RGO supporting film exhibited nice particle-absorption ability, thus avoiding the air-water interface problem. More importantly, we found that the RGO supporting film is particularly useful in cryo-EM reconstruction of sub-100 kDa biomolecules at near-atomic resolution, as exemplified by the study of RBD-ACE2 complex and other small protein molecules. We envision that the RGO membranes can be used as a robust graphene-based supporting film in cryo-EM specimen preparation.

biophysics↗

bioRxiv2021

ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation

Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers). Accurate identification of regulatory elements is fundamental for annotating genomes and understanding gene expression patterns. While there are many attempts to develop computational promoter and enhancer identification methods, reliable tools to analyze long genomic sequences are still lacking. Prediction methods often perform poorly on the genome-wide scale because the number of negatives is much higher than that in the training sets. To address this issue, we propose a dynamic negative set updating scheme with a two-model approach, using one model for scanning the genome and the other one for testing candidate positions. The developed method achieves good genome-level performance and maintains robust performance when applied to other species, without re-training. Moreover, the unannotated predicted regulatory regions made on the human genome are enriched for disease-associated variants, suggesting them to be potentially true regulatory elements rather than false positives. We validated high scoring "false positive" predictions using reporter assay and all tested candidates were successfully validated, demonstrating the ability of our method to discover novel human regulatory regions.

bioinformatics↗

bioRxiv2021

Decoding nucleosome positions with ATAC-seq data at single-cell level

As the basal bricks, the dynamics and arrangement of nucleosomes orchestrate the higher architecture of chromatin in a fundamental way, thereby affecting almost all nuclear biology processes. Thanks to its rather simple protocol, ATAC-seq has been rapidly adopted as a major tool for chromatin-accessible profiling at both bulk and single-cell level. However, to picture the arrangement of nucleosomes per se remains a challenge with ATAC-seq. In the present work, we introduce a novel ATAC-seq analysis toolkit, named deNOPA, to predict nucleosome positions. Assessments showed that deNOPA not only outperformed state-of-the-art tools, but it is the only tool able to predict nucleosome position precisely with ultrasparse ATAC-seq data. The remarkable performance of deNOPA was fueled by the reads from short fragments, which compose nearly half of sequenced reads and are normally discarded from nucleosome position detection. However, we found that the short fragment reads enrich information on nucleosome positions and that the linker regions were predicted by reads from both short and long fragments using Gaussian smoothing. We applied deNOPA to a single-cell ATAC-seq dataset and deciphered the intrapopulation heterogeneity of the human erythroleukemic cell line (K562). Last, using deNOPA, we showed that the dynamics of nucleosome organization may not directly couple with chromatin accessibility in the cis-regulatory regions when human cells respond to heat shock stimulation. Our deNOPA provides a powerful tool with which to analyze the dynamics of chromatin at nucleosome position level in the single-cell ATAC-seq age.

bioinformatics↗

bioRxiv2021

Key metabolic pathways involved in seed primary physiological dormancy maintenance of Korean pine seed

The metabolic changes that occurred during either cold stratification or after-ripen treatment, and in both dormant seeds and after-ripened seeds either under the dry state or during imbibition have been extensively explored. Much less is known about those present in both dormant seeds and cold stratified seeds during the same period of incubation under favorable germination conditions. Metabolite composition was investigated in both embryo and megagametophyte of primary physiological dormant seeds (PPDS) of Pinus Koreansis collected at 0 week, 1 week, 2 weeks, 4 weeks and 6 weeks of incubation, and of cold stratified seeds with released primary physiological dormancy (RPPDS) sampled at 0 week and 1 week of incubation, seed coat rupture stage and radicle protrusion stage. Embryo contained higher levels of most metabolites compared to megagametophyte. Strong metabolic changes occurred at 1 week and 4 weeks of incubation in PPDS, with most metabolites were significantly accumulated in 4-weeks-incubated PPDS. A larger metabolic switch was found in RPPDS between 1-week-incubation and seed coat rupture stage. Especially, there was a significant major decrease in the relative levels of most phosphorylated sugars and amino acids. The carbohydrate metabolism, especially pentose phosphate pathway and tricarboxylic acid cycle were more active pathways in the embryos of 4-weeks-incubated PPDS, but the operation rate of most amino acid metabolism was lower compared to 1-week-incubated RPPDS. We suggest that a larger metabolic switch in the embryo of PPDS after 4 weeks of incubation may assist in maintaining primary dormancy. One-sentence summaryA larger metabolic switch in dormant seeds after 4 weeks of incubation under favorable conditions for germination may maintain primary physiological dormancy of Korean pine seeds.

physiology↗

bioRxiv2021

Self-assembling SARS-CoV-2 nanoparticle vaccines targeting the S protein induces protective immunity in mice

The spike (S), a homotrimer glycoprotein, is the most important antigen target in the research and development of SARS-CoV-2 vaccine. There is no doubt that fully simulating the advanced structure of this homotrimer in the subunit vaccine development strategy is the most likely way to improve the immune protective effect of the vaccine. In this study, the preparation strategies of S protein receptor-binding domain (RBD) trimer, S1 region trimer, and ectodomain (ECD) trimer nanoparticles were designed based on ferritin nanoparticle self-assembly technology. The Bombyx mori baculovirus expression system was used to prepare these three nanoparticle vaccines with high expression levels in the silkworm. The immune results of mice show that the nanoparticle vaccine prepared by this strategy can not only induce an immune response by subcutaneous administration but also effective by oral administration. Given the stability of these ferritin-based nanoparticles vaccine, easy-to-use and low-cost oral immunization strategy can make up for the vaccination blind areas caused by the shortage of ultralow-temperature equipment and medical resources in underdeveloped areas. And the oral vaccine is also a very potential candidate to cut off the spread of SARS-CoV-2 in domestic and farmed animals, especially in stray and wild animals.

immunology↗

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

Cas9-cleavage sequences in minimal plasmids enhance non-viral genome targeting of CARs in primary human T cells

T cell genome editing holds great promise to advance a range of immunotherapies but is encumbered by the dependence on difficult-to-produce and expensive viral vectors. Here we have designed small double-stranded plasmid DNA modified to mediate high-efficiency homologous recombination. The resulting chimeric antigen receptor (CAR)-T cells display a similar phenotype, transcriptional profile and in vivo potency as CAR-T cells generated using adeno-associated viral (AAV) vector. This method should simplify and accelerate the use of precision engineering to produce edited T cells for research and clinical purposes.

bioengineering↗

bioRxiv2020

Precision mapping of the mouse brain metabolome

Metabolism is physiologically fundamental to a biological system. Understanding brain metabolism is critical for our comprehensive knowledge of brain function in health and disease. Combining a microarray collection system with targeted metabolomics analysis, here we performed precision mapping of the metabolome in the mouse brain and created maps for 79 metabolites with a resolution of 0.125mm3 per pixel (i.e., brain subregion). The metabolome atlas provides researchers with a useful resource to interpret the vulnerability of specific brain regions to various disease-relevant metabolic perturbations.

neuroscience↗

bioRxiv2020

A non-enzymatic acetylation of lysine residues adversely affects the Rubisco activase protein stability

The post-translational modifications of non-histone (PTMs) proteins functions are crucial for the plant adaption to the changing environment. The Rubisco activase (RCA) plays a key role in the CO2 fixation through the Rubisco activation process. We reported that the RCA from tobacco leaf could be acetylated at several lysine residues including K126 and K164. The acetylation level changes under different light conditions (night and day) as well as under heat stress (45 {degrees}C). We further showed that the RCA can be non-enzymatically acetylated in vitro, especially by the acetyl-CoA (Ac-CoA) through direct interaction between them. Our results of the in vitro assay with deuterium labeled Ac-CoA (D2-Ac-CoA) show that the two conserved RCA lysine residues (K126 and K164) were acetylated by Ac-CoA, entraining a dramatic decline in its ATPase activity and a slight effect on the Rubisco activation process. Furthermore, we revealed that the higher RCA acetylation level induced its faster degradation in the chloroplast, which was not a direct consequence of ubiquitination. Eventually, our findings unraveled a new prominent role for the protein acetylation in modulating the RCA stability, which could certainly regulate the carbon assimilation efficiency towards a different energy status of the plants.

plant biology↗

bioRxiv2020

ssc-micorRNA-132 suppresses the Clostridium perfringens beta2 toxin induced inflammation and apoptosis of IPEC-J2 cells via targeting DACH1

Clostridium perfringens (C. perfringens) beta2 (CPB2) is the main virulence factor secreted from C. perfringens type C, which caused diarrhea characterized by high mortality in pig, especially newborn piglets. Our previous research found that ssc-miR-132 displayed decreased expression in piglets diarrhea after infected with C. perfringens type C compared with normal piglets. We speculated that ssc-miR-132 may play an important role in the diarrhea. However, the function of ssc-miR-132 in the diarrhea is limited. Thus, we overexpressed and knocked down ssc-miR-132 in intestinal porcine epithelial (IPEC-J2) cells, and then treated the cells with recombinant CPB2 (rCPB2) toxin (20 g/mL). Our results showed that ssc-miR-132 was significantly decreased after treated with rCPB2 toxin. In addition, overexpression of ssc-miR-132 reduced the expression of lactate dehydrogenase (LDH) and tumor necrosis factor (TNF-), interleukin-6 (IL-6) and interleukin-8 (IL-8) caused by rCPB2 toxin. The CCK8, Edu and TUNEL staining showed that overexpression of ssc-miR-132 weakened the inhibition of rCPB2 toxin on cell proliferation and reduced the promotion of cell apoptosis; while inhibition of ssc-miR-132 had opposite results. The dual luciferase experiment showed that dachshund family transcription factor 1 (DACH1) was the target gene of ssc-miR-132. Silencing DACH1 was consistent with the results of overexpression of ssc-miR-132, and reversed the apoptosis and inflammation caused by rCPB2 toxin. Overexpression of DACH1 weakened the role of ssc-miR-132 in rCPB2 toxin -induced inflammation and apoptosis. In summary, ssc-miR-132 inhibited rCPB2 toxin-induced apoptosis and inflammation in IPEC-J2 cells by targeting DACH1.

cell biology↗