Biology subjects

Ge, R.

Publications and source records attributed to Ge, R..

26 records · Page 2Linked to original sources

bioRxiv2022

Lysine acetylation regulates antibiotic resistance in Escherichia coli

Antibiotic resistance is increasingly becoming a serious challenge to public health. The regulation of metabolism by post-translational modifications (PTMs) has been widely studied; however, the comprehensive mechanism underlying the regulation of acetylation in bacterial resistance against antibiotics is unknown. Herein, with Escherichia coli as the model, we performed quantitative analysis of the acetylated proteome of wild-type sensitive strain (WT) and ampicillin- (Re-Amp), kanamycin- (Re-Kan), and polymyxin B-resistant (Re-Pol) strains. Based on bioinformatics analysis combined with biochemical validations, we found that a common regulatory mechanism exists between the different resistant strains. Acetylation negatively regulates bacterial metabolism to maintain antibiotic resistance, but positively regulates bacterial motility. Further analyses revealed that key enzymes in various metabolic pathways were differentially acetylated. Particularly, pyruvate kinase (PykF), a key glycolytic enzyme regulating bacterial metabolism, and its acetylated form were highly expressed in the three resistant types and were identified as reversibly acetylated by the deacetylase CobB and the acetyl-transferase PatZ, and also could be acetylated by non-enzyme AcP in vitro. Further, the deacetylation of Lys413 of PykF increased the enzyme activity by changing the conformation of ATP binding site of PykF, resulting in an increase in energy production, which in turn increased the sensitivity of drug-resistant strains to antibiotics. This study provides novel insights for understanding bacterial resistance and lays the foundation for future research on regulation of acetylation in antibiotic-resistant strains. ImportanceThe misuse of antibiotics has resulted in an emergence of a large number of antibiotic-resistant strains, which seriously threaten human health. Bacterial metabolism is tightly controlled by protein post-translational modifications, especially acetylation. However, the comprehensive mechanism underlying regulation of acetylation in bacterial resistance remains unexplored. Here, acetylation was found to positively regulate bacterial motility and negatively regulate energy metabolism, which was common in all the different antibiotic-resistant strains. Moreover, the acetylation and deacetylation process of PykF was uncovered, and deacetylation of the Lys 413 of PykF was found to contribute to bacterial sensitivity to antibiotics. This study provides a new direction for research on development of bacterial resistance through post-translational modifications and provides a theoretical basis for the development of antibacterial drugs.

microbiology↗

bioRxiv2022

Sex differences in predictors and regional patterns of brain-age-gap estimates

BackgroundThe brain-age-gap estimate (brainAGE) quantifies the difference between chronological age and age predicted by applying machine-learning models to neuroimaging data, and is considered a biomarker of brain health. Understanding sex-differences in brainAGE is a significant step toward precision medicine. MethodsGlobal and local brainAGE (G-brainAGE and L-brainAGE, respectively) were computed by applying machine learning algorithms to brain structural magnetic resonance imaging data from 1113 healthy young adults (54.45% females; age range: 22-37 years) participating in the Human Connectome Project. Sex-differences were determined in G-brainAGE and L-brainAGE. Random forest regression was used to determine sex-specific associations between G-brainAGE and non-imaging measures pertaining to sociodemographic characteristics and mental, physical, and cognitive functions. ResultsL-brainAGE showed sex-specific differences in brain ageing. In females, compared to males, L-brainAGE was higher in the cerebellum and brainstem and lower in the prefrontal cortex and insula. Although sex-differences in G-brainAGE were minimal, associations between G-brainAGE and non-imaging measures differed between sexes with the exception for poor sleep quality, which was common to both. The most important predictor of higher G-brainAGE was non-white race in males and systolic blood pressure in females. ConclusionsThe results demonstrate the value of applying sex-specific analyses and machine learning methods to advance our understanding of sex-related differences in factors that influence the rate of brain ageing and provide a foundation for targeted interventions.

neuroscience↗

bioRxiv2021

ME-ACP: Multi-view Neural Networks with Ensemble Model for Identification of Anticancer Peptides

Cancer remains one of the most threatening diseases, which kills millions of lives every year. As a promising perspective for cancer treatments, anticancer peptides (ACPs) overcome a lot of disadvantages of traditional treatments. However, it is time-consuming and expensive to identify ACPs through conventional experiments. Hence, it is urgent and necessary to develop highly effective approaches to accurately identify ACPs in large amounts of protein sequences. In this work, we proposed a novel and effective method named ME-ACP which employed multi-view neural networks with ensemble model to identify ACPs. Firstly, we employed residue level and peptide level features preliminarily with ensemble models based on lightGBMs. Then, the outputs of lightGBM classifiers were fed into a hybrid deep neural network (HDNN) to identify ACPs. The experiments on independent test datasets demonstrated that ME-ACP achieved competitive performance on common evaluation metrics.

bioinformatics↗

bioRxiv2021

DRUG-seq Provides Unbiased Biological Activity Readouts for Drug Discovery

Unbiased transcriptomic RNA-seq data has provided deep insights about biological processes. However, its impact in drug discovery has been narrow given high costs and low throughput. Proof-of-concept studies with Digital RNA with pertUrbation of Genes (DRUG)-seq demonstrated the potential to address this gap. We extended the DRUG-seq platform by subjecting it to rigorous testing and by adding an open-source analysis pipeline. The results demonstrate high reproducibility and ability to resolve the mechanism(s) of action for a diverse set of compounds. Overall, the protocol and open-source analysis pipeline are a step towards industrializing RNA-seq for high complexity transcriptomics studies performed at a saturating scale.

genomics↗

bioRxiv2021

Implementation of a TMS-fMRI system: A primer

Transcranial magnetic stimulation (TMS) is a non-invasive and non-pharmacological intervention, approved for the treatment of individuals diagnosed with treatment-resistant depression. This well-tolerated approach uses magnetic pulses to stimulate specific brain regions and induce changes in brain networks at multiple levels of human functioning. Combining TMS with other neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), offers new insights into brain functioning, and allows to map out the causal alterations brought on by TMS interventions on neural network connectivity and behaviour. However, the implemention of concurrent TMS-fMRI brings on a number of technical challenges that must be overcome to ensure good quality of functional images. The goal of this study was thus to investigate the impact of TMS pulses in an MR-environment on the quality of BRAINO phantom images, in terms of the signal of the images, the temporal fluctuation noise, the spatial noise and the signal to fluctuation noise ratio, at the University of British Columbia (UBC) Neuroimaging facility. The results of our analyses replicated those of previous sites, and showed that the present set-up for concurrent TMS-fMRI ensures minimal noise artefact on functional images obtained through this multimodal approach. This step was a key stepping stone for future clinical trials at UBC.

neuroscience↗

bioRxiv2020

SS-Detect: Development and Validation of a New Strategy for Source-Based Morphometry in Multi-Scanner Studies

Background and PurposeSource-based morphometry (SBM) has been used in multi-centre studies pooling magnetic resonance imaging (MRI) data across different scanners to advance the reproducibility of neuroscience research. In the present study, we developed an analysis strategy for Scanner-Specific Detection (SS-Detect) of SBPs in multi-scanner studies, and evaluated its performance relative to a conventional strategy. MethodsIn the first experiment, the SimTB toolbox was used to generate simulated datasets mimicking twenty different scanners with common and scanner-specific SBPs. In the second experiment, we generated one simulated SBP from empirical gray matter volume (GMV) datasets from two different scanners. Moreover, we applied two strategies to compare SBPs between schizophrenia patients and healthy controls GMV from two different scanners. ResultsThe outputs of the conventional strategy were limited to whole-sample-level results across all scanners; the outputs of SS-Detect included whole-sample-level and scanner-specific results. In the first simulation experiment, SS-Detect successfully estimated all simulated SBPs, including the common and scanner-specific SBPs whereas the conventional strategy detected only some of the whole-sample SBPs. The second simulation experiment showed that both strategies could detect the simulated SBP. Quantitative evaluations of both experiments demonstrated greater accuracy of the SS-Detect in estimating spatial SBPs and subject-specific loading parameters. In the third experiment, SS-Detect detected more significant between-group SBPs, and these SBPs corresponded with the results from voxel-based morphometry analysis, suggesting that SS-Detect has higher sensitivity in detecting between-group differences. ConclusionsSS-Detect outperformed the conventional strategy and can be considered advantageous when SBM is applied to a multi-scanner study.

bioinformatics↗

bioRxiv2020

Global Screening of Sentrin-Specific Protease Family Substrates in SUMOylation

Post-translational modification of proteins by the addition of small ubiquitin-related modifier (SUMO) is a dynamic process, in which deSUMOylation is carried out by members of the Sentrin/SUMO-specific protease (SENP) family. While identification of SUMOylation sites at global scale has made great progress, much less effort has been made on the SENP family-dependent deSUMOylation. Here we report a dataset of 3,763 high confident SUMO1 modification sites and their dependence on the 6 members of SENP proteins. Interrogation of the dataset led to the discovery that SENP3 regulates the innate immune response via deSUMOylation of DHX15 and PCBP2 and recruitment of inflammatory molecules. Collectively, this dataset presents a site-resolved network of the SUMO-SENP system, providing information for potential substrates of the SENP proteins.

biochemistry↗

bioRxiv2019

In-Depth Characterization and Validation in BRG1-Mutant Lung Cancers Define Novel Catalytic Inhibitors of SWI/SNF Chromatin Remodeling

Members of the ATP-dependent SWI/SNF chromatin remodeling complexes are among the most frequently mutated genes in cancer, suggesting their dysregulation plays a critical role. The synthetic lethality between SWI/SNF catalytic subunits BRM/SMARCA2 and BRG1/SMARCA4 has instigated great interest in targeting BRM. Here we have performed a critical and in-depth investigation of novel dual inhibitors (BRM011 and BRM014) of BRM and BRG1 in order to validate their utility as chemical probes of SWI/SNF catalytic function, while obtaining insights into the therapeutic potential of SWI/SNF inhibition. In corroboration of on-target activity, we discovered compound resistant mutations through pooled screening of BRM variants in BRG1-mut cancer cells. Strikingly, genome-wide transcriptional and chromatin profiling (ATAC-Seq) provided further evidence of pharmacological perturbation of SWI/SNF chromatin remodeling as BRM011 treatment induced specific changes in chromatin accessibility and gene expression similar to genetic depletion of BRM. Finally, these compounds have the capacity to inhibit the growth of tumor-xenografts, yielding important insights into the feasibility of developing BRM/BRG1 ATPase inhibitors for the treatment of BRG1-mut lung cancers. Overall, our studies not only establish the feasibility of inhibiting SWI/SNF catalytic function, providing a framework for SWI/SNF therapeutic targeting, but have also yielded successful elucidation of small-molecule inhibitors that will be of importance in probing SWI/SNF function in various disease contexts.

cancer biology↗