Biology subjects

Gao, J.

Publications and source records attributed to Gao, J..

At least 217 records · Page 12Linked to original sources

bioRxiv2021

Class I Histone Deacetylases (HDAC1-3) are Histone Lysine Delactylases

Lysine O_SCPLOWLC_SCPLOW-lactylation [K(O_SCPLOWLC_SCPLOW-la)] is a newly discovered histone mark that can be stimulated under conditions of high glycolysis, such as the Warburg effect. K(O_SCPLOWLC_SCPLOW-la) is associated with functions that are different from the widely studied histone acetylation. While K(O_SCPLOWLC_SCPLOW-la) can be introduced by the acetyltransferase p300, histone delactylase enzymes remain unknown. Here, we report the systematic evaluation of zinc- and NAD+-dependent HDACs for their ability to cleave {varepsilon}-N-O_SCPLOWLC_SCPLOW-lactyllysine marks. Our screens identified HDACs 1-3 and SIRT1-3 as delactylases in vitro. HDACs 1-3 show robust activity toward not only K(O_SCPLOWLC_SCPLOW-la) but also K(O_SCPLOWDC_SCPLOW-la) and diverse short-chain acyl modifications. We further confirmed the de-O_SCPLOWLC_SCPLOW-lactylase activity of HDACs 1 and 3 in cells. Identification of p300 and HDAC3 as regulatory enzymes suggests that histone lactylation is installed and removed by enzymes as opposed to spontaneous chemical reactivity. Our results therefore represent an important step toward full characterization of this pathways regulatory elements.

biochemistry↗

bioRxiv2021

GRAMMAR-Lambda: An Extreme Simplification for Genome-wide Mixed Model Association Analysis

A highly efficient genome-wide association method, GRAMMAR-Lambda is proposed to make simple genomic control for the test statistics deflated by GRAMMAR, producing statistical power as high as exact mixed model association method. Using the simulated and real phenotypes, we show that at a moderate or above genomic heritability, polygenic effects can be estimated using a small number of randomly selected markers, which extremely simplify genome-wide association analysis with an approximate computational complexity to naive method in large-scale complex population. Upon a test at once, joint association analysis offers significant increase in statistical power over existing methods.

bioinformatics↗

bioRxiv2021

Efficient Genomic Control for Mixed Model Associationsin Large-scale Population

Among linear mixed model-based association methods, GRAMMAR has the lowest computing complexity for association tests, but it produces a high false-negative rate due to the deflation of test statistics for complex population structure. Here, we present an optimized GRAMMAR method by efficient genomic control, Optim-GRAMMAR, that estimates the phenotype residuals by regulating downward genomic heritability in the genomic best linear unbiased prediction. Even though using the fewer sampling markers to evaluate genomic relationship matrices and genomic controls, Optim-GRAMMAR retains a similar statistical power to the exact mixed model association analysis, which infers an extremely efficient approach to handle large-scale data. Moreover, joint association analysis significantly improved statistical power over existing methods.

bioinformatics↗

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

Modulating the voltage sensor of a cardiac potassium channel shows antiarrhythmic effects

Cardiac arrhythmias are the most common cause of sudden cardiac death worldwide. Lengthening the ventricular action potential duration (APD) either congenitally or via pathologic or pharmacologic means, predisposes to a life-threatening ventricular arrhythmia, Torsade de Pointes. IKs, a slowly activating K+ current plays a role in action potential repolarization. In this study, we screened a chemical library in silico by docking compounds to the voltage sensing domain (VSD) of the IKs channel. Here we show that C28 specifically shifted IKs VSD activation in ventricle to more negative voltages and reversed drug-induced lengthening of APD. At the same dosage, C28 did not cause significant changes of the normal APD in either ventricle or atrium. This study provides evidence in support of a computational prediction of IKs VSD activation as a potential therapeutic approach for all forms of APD prolongation. This outcome could expand the therapeutic efficacy of a myriad of currently approved drugs that may trigger arrhythmias. Significance statementC28, identified by in silico screening, specifically facilitated voltage dependent activation of a cardiac potassium ion channel, IKs. C28 reversed drug-induced prolongation of action potentials, but minimally affected the normal action potential at the same dosage. This outcome supports a computational prediction of modulating IKs activation as a potential therapy for all forms of action potential prolongation, and could expand therapeutic efficacy of many currently approved drugs that may trigger arrhythmias.

biophysics↗

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

FGF21 Normalizes Plasma Glucose in Mouse Models of Type 1 Diabetes and Insulin Receptor Dysfunction

Fibroblast growth factor 21 (FGF21) is a member of the fibroblast growth factor (FGF) family of proteins. The biological activity of FGF21 was first shown to induce insulin independent glucose uptake in adipocytes through the GLUT1 transporter. Subsequently, it was shown to have effects on the liver to increase fatty acid oxidation. FGF21 treatment provides beneficial metabolic effects in both animal models and patients with obesity, type 2 diabetes mellitus (T2D) and/or fatty liver disease. In this paper, we revisited the original finding and found that insulin independent glucose uptake in adipocytes is preserved in the presence of an insulin receptor antagonist. Using a 40 kDa PEGylated (PEG) and half-life extended form of FGF21 (FGF21-PEG), we extended these in vitro results to two different mouse models of diabetes. FGF21-PEG normalized plasma glucose in streptozotocin-treated mice, a model of type 1 diabetes (T1D), without restoring pancreatic {beta}-cell function. FGF21-PEG also normalized plasma glucose levels and improved glucose tolerance in mice chronically treated with an insulin competitive insulin receptor antagonist, a model of autoimmune/Type-B insulin resistance. These data extend the pharmacological potential of FGF21 beyond the settings of T2D, fatty liver and obesity.

pharmacology and toxicology↗

bioRxiv2021

Machine Learning to Summarize and Provide Context for Sleep and Eating Schedules.

The relative timing of sleep and of eating within the circadian day is important for human health. Despite much data on sleep, and a growing data set for eating, there remains a need for an interpretative framework for the understanding of this data for health decisions. This study provides a new statistical and machine learning analysis of more than 500 participants in the Daily24 project. From their data, and the analysis, we propose a framework for determining the classification of participants into different chronotypes and with that the ability to realize the potential impact of daily circadian habits on health. We propose that our resulting distribution curves could be used, similar to NHANES (National Health and Nutrition Examination Survey) data for pediatric growth, as a measure for circadian misalignment and used to help guide re-entrainment schedules. Author summaryDaily habits can be positive, negative or neutral for human health. Generally sleep and eating schedules are assumed without thought for their potential to help or interfere with health. In this study we propose a framework, based on data from more than 500 participants, for evaluating the relative timing of meals and sleep schedules. This evaluation, similar to pediatric growth charts, can guide clinical suggestions for those at the extremes, while helping others to realize that they are unusual relative to the population average

bioinformatics↗

bioRxiv2020

Balancing the influenza neuraminidase and hemagglutinin responses by exchanging the vaccine virus backbone

Virions are a common antigen source for many viral vaccines. One limitation to using virions is that the antigen abundance is determined by the content of each protein in the virus. This caveat especially applies to viral-based influenza vaccines where the low abundance of the neuraminidase (NA) surface antigen remains a bottleneck for improving the NA antibody response. Here, we used the WHO recommended H1N1 antigens (2019-2020 season) in a systematic analysis to demonstrate that the NA to hemagglutinin (HA) ratio in virions can be improved by exchanging the viral backbone internal genes, thereby preserving the antigens. The purified inactivated virions with higher NA content show a more spherical morphology, a different balance between the HA receptor binding and NA receptor release functions, and induce a better NA inhibitory antibody response in mice. These results indicate that influenza viruses support a range of ratios for a given NA and HA pair that can be utilized to produce viral-based influenza vaccines with increased NA content which can elicit more balanced inhibitory antibody responses to NA and HA.

microbiology↗

bioRxiv2020

Light spectra modify nitrogen assimilation and nitrogen content in Quercus variabilis Blume seedling components: A bioassay with 15N pulses

The light spectra that reach plants change across different shading conditions, may alter the pattern of nitrogen (N) uptake and assimilation by understory regenerations that are also exposed to N deposition. We conducted a bioassay on Chinese cork oak (Quercus variabilis Blume) seedlings subjected to five-month N pulsing with 15NH4Cl (10.39 atom %) at 120 mg 15N plant-1 under the blue (48.5% blue, 33.7% green, and 17.8% red), red (14.6% blue, 71.7% red, 13.7% green), and green (17.4% blue, 26.2% red, 56.4% green) spectra provided by light-emitting diodes (LEDs). Half of the seedlings were fed twice a week using a 250 ppm N solution with added phosphorus, potassium, and micro-nutrients, while the other half received only distilled water. Neither treatment affected growth of height, diameter, or leaf area. Compared to the red light spectrum, the blue light treatment increased chlorophyll and soluble protein contents and glutamine synthetase (GS) activity, root N concentration, and N derived from the pulses. The green light spectrum induced more biomass to allocate to the roots and a higher percentage of N derived from internal reserves compared to the other two spectra. The 15N pulses demonstrated no interaction with spectra but weakened the reliance on N remobilization from acorns, strengthened biomass allocation to shoots, and induced higher chlorophyll content, GS activity, and N concentration. In conclusion, the red light spectrum should be avoided for Q. variabilis regenerations whose biomass allocation to underground organs are weakened under this condition.

ecology↗

bioRxiv2020

Discovering a less-is-more effect to select transcription factor binding sites informative for motif inference

Many statistical methods have been developed to infer the binding motifs of a transcription factor (TF) from a subset of its numerous binding regions in the genome. We refer to such regions, e.g. detected by ChIP-seq, as binding sites. The sites with strong binding signals are selected for motif inference. However, binding signals do not necessarily indicate the existence of target motifs. Moreover, even strong binding signals can be spurious due to experimental artifacts. Here, we observe that such uninformative sites without target motifs tend to be "crowded" -- i.e. have many other TF binding sites present nearby. In addition, we find that even if a crowded site contains recognizable target motifs, it can still be uninformative for motif inference due to the presence of interfering motifs from other TFs. We propose using less crowded and shorter binding sites in motif interference and develop specific recommendations for carrying this out. We find our recommendations substantially improve the resulting motifs in various contexts by 30%-70%, implying a "less-is-more" effect.

bioinformatics↗

bioRxiv2020

Regulating enzymatic reactions in Escherichia coli utilizing light-responsive cellular compartments based on liquid-liquid phase separation

Enzymatic reactions in cells are well organized into different compartments, among which protein-based membraneless compartments formed through liquid-liquid phase separation (LLPS) are believed to play important roles1,2. Hijacking them for our own purpose has promising applications in metabolic engineering3. Yet, it is still hard to precisely and dynamically control target enzymatic reactions in those compartments4. To address those problems, we developed Photo-Activated Switch in E. coli (PhASE), based on phase separating scaffold proteins and optogenetic tools. In this system, a protein of interest (POI) can be enriched up to 15-fold by LLPS-based compartments from cytosol within only a few seconds once activated by light, and become fully dispersed again within 15 minutes. Furthermore, we explored the potentiality of the LLPS-based compartment in enriching small organic molecules directly via chemical-scaffold interaction. With enzymes and substrates co-localized under light induction, the overall reaction efficiency could be enhanced. Using luciferin and catechol oxidation as model enzymatic reactions, we found that they could accelerate 2.3-fold and 1.6-fold, respectively, when regulated by PhASE. We anticipate our system to be an extension of the synthetic biology toolkit, facilitating rapid recruitment and release of POIs, and reversible regulation of enzymatic reactions.

synthetic biology↗

bioRxiv2020

A comparative study of data integration methods, integrating genetic association and functional annotation summary statistics

Functional annotations have the potential to increase the power of genome-wide association studies (GWAS) by prioritizing variants according to their biological function. Focusing on variant-specific annotation meta-scores including CADD (Kircher et al., 2014) and Eigen (Ionita-laza et al., 2016), we broadly examined GWAS summary statistics of 1,132 traits from the UK Biobank (Sudlow et al., 2015) using the weighted p-value approach (Genovese et al., 2006) and stratified false discovery control (sFDR) method (Sun et al., 2006). These 1,132 traits were rated by Benjamin Neales lab from the Broad Institute as having medium to high confidence for their heritability estimates. Averaged across the 1,132 UK Biobank traits, sFDR was more robust to uninformative meta-scores, but the weighted p-value method identified more variants using CADD or Eigen, based on performance measures that included type I error control, recall, precision, and relative efficiency. Our application results were consistent with those from an extensive simulation study using three different designs, including leveraging the real genetic data combined with simulated genomic data and vice versa. We also considered the recent FINDOR method (Kichaev et al., 2019), which leverages a set of individual 75 functional annotations into GWAS. An earlier application of FINDOR to 27 traits selected from the z7 category (SNP-heritability p-value < 1.27 x 10-12 by Nealelab) detected 13%-20% additional genome-wide significant loci as compared to the standard annotation-free GWAS, which we confirmed. Moreover, across all 438 traits in the z7 category, 46,631 out 59,764 (80%) significant loci discovered are common across the three data-integration methods. However, across all the 1,132 UK Biobank traits examined, the median [Q1,Q3] of the total numbers of new, genome-wide significant independent loci were 0 [0, 3] by FINDOR, 0 [0, 2] by weighted p-value, and 0 [0, 0] by sFDR. Notably, 162 traits (89%) in the nonsig trait category (SNP-heritability p-value > 0.05, "likely reflecting limited statistical power rather than a true lack of heritability" by Nealelab) had no new discoveries after data-integration by any of the three methods. Our findings suggest that more informative scores or new data integration methods are warranted to further improve the power of GWAS by leveraging the variant functional annotations.

genetics↗

bioRxiv2020

Pulmonary B cells ameliorate Alzheimer's disease-like neuropathology

Increasing evidence shows that the peripheral immune system is involved in the pathogenesis of Alzheimers disease (AD). Here, we report that pulmonary B cells mitigate beta-Amyloid (A{beta}) pathology in 5xFAD mice. The proportion of B cells rather than T cells increases in brain, meningeal and lung tissues in 3-month-old 5xFAD mice. Deletion of B cells aggravates A{beta} load and memory deficits of 5xFAD mice. Mechanimsly, pulmonary B cells can migrate to the brain parenchyma and produce interleukin-35 that inhibits neuronal {beta}-site APP-cleaving enzyme 1 expression, subsequently reducing the production of A{beta}. In turn, proliferation of pulmonary B cells is associated with activation of toll-like receptor/nuclear factor kappa-B pathway by elevated A{beta} that is drained from the brain parenchyma to the lungs via meningeal lymphatics. Furthermore, promoting pulmonary B cell proliferation via overexpression of B-cell-activating factor ameliorates brain A{beta} load and improves cognitive functions of 10-month-old 5xFAD mice. Together, these results highlight the lungs as both immune targets and effector organs in A{beta} pathogenesis. Pulmonary B cells might be a potential target against AD.

neuroscience↗

bioRxiv2020

Enteric glial cells respond to a dietary change in the lamina propria in a MyD88-dependent manner

Immune and nervous system sensing are two important ways of detecting inner and outer environmental changes. Immune cell activation in the gut can promote metabolic disorders. However, whether enteric nervous system sensing and activities are also important in metabolic syndromes is not clear. Enteric glial cells (EGCs) are thought to have sensing ability, but little is known about the potential connections between EGC and metabolic disorders. Consuming a modern Western-type high-fat low-fiber diet increases the risk of obesity. Here, we reported that dietary shift from a normal chow diet to a high-fat diet in wild-type (WT) C57BL/6 mice induced a transient emergence of glial fibrillary acidic protein (GFAP)-positive EGC network in the ileal lamina propria, accompanied by an increase of glial-derived neurotrophic factors production. Inhibition of EGC metabolic activity via gliotoxin fluorocitrate or glial-intrinsic deletion of myeloid differentiation factor 88 (Myd88) in mice blocked this dietary change-induced activity. Furthermore, we found a different role of MYD88 in glial cells versus adipocyte in diet-induced obesity. The glial Myd88 knockout mice gained less body weight after HFD feeding compared to the littermate controls. In contrast, adipocyte deletion of Myd88 in mice had no impact on the weight gain but had exacerbated glucose metabolic disorders. Pharmacological interventions of glial activities by fluorocitrate prevented body weight gain in a dietary type- and glial MYD88-independent manner. Collectively, our data reveal a previously unappreciated function of EGC in sensing a dietary shift-induced perturbation and glial activities as a whole may play roles in diet-induced obesity. New & NoteworthyIt is known that obesity and its related metabolic syndrome can damage the neuronal system. However, whether the neuronal system also participates in the development of obesity is unclear. Diet is an important contributing factor to obesity. Our study reveals that consuming a high-fat diet can induce a transient enteric glial cell response via its intrinsic sensing molecule(s). Inhibiting overall glial cell activities may have an impact on the development of the metabolic syndrome.

neuroscience↗

bioRxiv2020

Cell wall damage attenuates root hair cell patterning and tissue morphogenesis mediated by the Arabidopsis receptor kinase STRUBBELIG.

Cell wall remodeling is essential for the control of growth and development as well as the regulation of stress responses. However, the underlying cell wall monitoring mechanisms remain poorly understood. Regulation of root hair fate and flower development in Arabidopsis thaliana requires signaling mediated by the atypical receptor kinase STRUBBELIG (SUB). Furthermore, SUB is involved in cell wall integrity signaling and regulates the cellular response to reduced levels of cellulose, a central component of the cell wall. Here, we show that continuous exposure to sub-lethal doses of the cellulose biosynthesis inhibitor isoxaben results in altered root hair patterning and floral morphogenesis. Genetically impairing cellulose biosynthesis also results in root hair patterning defects. We further show that isoxaben exerts its developmental effects through the attenuation of SUB signaling. Our evidence indicates that down-regulation of SUB is a multi-step process and involves changes in SUB complex architecture at the plasma membrane, enhanced removal of SUB from the cell surface, and downregulation of SUB transcript levels. The results provide molecular insight into how the cell wall regulates cell fate and tissue morphogenesis.

plant biology↗

bioRxiv2020

9p21 Loss Defines the Evolutionary Patterns of Aggressive Renal Cell Carcinomas

Dedifferentiation and acquisition of chromosomal instability in renal cell carcinoma portends dismal prognosis and aggressive clinical behavior. However, the absence of reliable experimental models dramatically impacts the understanding of mechanisms underlying malignant progression. Here we established an in vivo genetic platform to rapidly generate somatic mosaic genetically engineerd immune-competent mouse models of renal tumors, recapitulating the genomic and phenotypic features of these malignancies. Leveraging somatic chromosomal engineering, we demonstrated that ablation of the murine locus syntenic to human 9p21 drives the rapid expansion of aggressive mesenchymal clones with prominent metastatic behavior, characterized by early emergence of chromosomal instability, whole-genome duplication, and conserved patterns of aneuploidy. This model of punctuated equilibrium provides a remarkable example of cross-species convergent evolution. SignificanceTo better understand the role of 9p21 in malignant progression, we generated a somatic mosaic GEMM of renal cancer, capturing the histological, genomic and evolutionary features of human disease. With this technology we demonstrated a critica role of 9p21 loss in metastatic evolution of RCC and provide a unique tool for testing new therapeutic treatments.

cancer biology↗

bioRxiv2020

CharPlant: A De Novo Open Chromatin Region (OCR) Prediction Tool for Plant Genomes

Chromatin accessibility is a highly informative structural feature for understanding gene transcription regulation because it indicates the degree to which nuclear macromolecules such as proteins and RNA can access chromosomal DNA. Studies show that chromatin accessibility is highly dynamic during stress response, stimulus response, and developmental transition. Moreover, physical access to chromosomal DNA in eukaryotes is highly cell-specific. Therefore, current technologies such as DNase-seq, ATAC-seq, and FAIRE-seq reveal only a portion of the open chromatin regions (OCRs) present in a given species. Thus, the genome-wide distribution of OCRs remains unknown. In this study, we developed a bioinformatics tool called CharPlant for the de novo prediction of chromatin accessible regions in plant genomes. To develop this tool, we constructed a three-layer convolutional neural network (CNN) and subsequently trained the CNN using DNase-seq and ATAC-seq datasets of four plant species. The model simultaneously learns the sequence motifs and regulatory logics, which are jointly used to determine DNA accessibility. All of these steps are integrated into CharPlant, which can be run using a simple command line. The results of data analysis using CharPlant in this study demonstrate its prediction power and computational efficiency. To our knowledge, CharPlant is the first de novo prediction tool that can identify potential OCRs in the whole genome. The source code of CharPlant and supporting files are freely downloadable from https://github.com/Yin-Shen/CharPlant.

bioinformatics↗