Biology subjects

Cheng, Y.

Publications and source records attributed to Cheng, Y..

At least 145 records · Page 8Linked to original sources

bioRxiv2024

Development and IND-enabling studies of a novel Cas9 genome-edited autologous CD34+ cell therapy to induce fetal hemoglobin for sickle cell disease

Sickle cell disease (SCD) is a common severe blood disorder, caused by one major point mutation in the HBB gene. Current pharmacotherapies are only partially effective and potentially curative allogeneic hematopoietic stem cell transplantation (HSCT) is associated with immune toxicities. Genome editing of autologous patient hematopoietic stem cells (HSCs) to reactivate fetal hemoglobin (HbF) in erythroid progeny offers a potentially curative approach to treat SCD and circumvents some problems associated with allogeneic HSCT. Although the FDA has released guidelines for evaluating genome editing risks, it remains unclear how to best to assess the preclinical safety and efficacy of genome-edited cellular drug products to prepare for a clinical trial. Here we describe rigorous pre-clinical characterization and optimization of a therapeutic {gamma}-globin gene promoter editing strategy that supported an investigational new drug (IND) application cleared by the FDA. We compared targets in the {gamma}-globin promoter and BCL11A erythroid-specific enhancer, identified a lead candidate that potently induces HbF, and tested our approach in mobilized CD34+ HSPCs from normal donors and individuals with SCD. We observed efficient editing, induction of HbF to levels predicted to be therapeutic, and reduction of sickling in red blood cells derived from edited HSPCs. With single-cell western and RNA-seq analyses, we defined the heterogeneity and specificity of HbF induction and HBG1/HBG2 transcription. With CHANGE-seq for sensitive and unbiased genome-wide off-target discovery followed by multiplexed targeted sequencing, we did not detect off-target activity in edited HSPCs. Our study provides a blueprint for translating new discoveries on ex vivo genome editing of HSCs towards clinical trials for treating SCD and other blood disorders.

genomics↗

bioRxiv2024

Impacts of global warming on fertility of male fishes: evidence from meta-analysis of temperature effects on spermatozoa motility

Studies have demonstrated adverse effects of global warming on aquatic ecosystems from the abiotic to the biotic level. In the present work, a meta-analysis study was conducted to elucidate the effects of global warming on spermatozoa functions, which are key determinants of male fertility. We recruited 245 data records from a pool of empirical studies, which includes 20 studies spanning 20 cold- and warm-water fish species, to identify the effects of increased water temperature (IWT) on determinants of sperm fertility in fishes. Data were systematically re-processed and re-analyzed to determine the overall effects of IWT on sperm kinetics such as motility (MOT), duration of motility (DSM), curvilinear velocity (VCL), rectilinear velocity (VSL) and average path velocity (VAP), as well as on enzymatic activities for energy supply (EAES) and antioxidant enzyme activity (ANEA). The standardized mean difference was calculated for each study, with positive values indicating higher performance under IWT. Results showed that (a) the overall effect size for MOT was more negative in cold-water fishes (-1.22) than in warm-water fishes (-0.98). (b) Each 1 {degrees}C increase in the activation medium reduced MOT by 1.30% (cold-water fishes) and 3.47% (warm-water fishes). (c) The IWT negatively affected DSM, decreasing it by 10 s (cold-water species) and 5.64 s (warm-water species) per degree of IWT. (d) Spermatozoa velocity (VCL and VSL) was increased by IWT in warm-water species. In conclusion, this study shows that IWT negatively affects sperm motility kinetics, suggesting an impact of global warming on fish reproduction.

cell biology↗

bioRxiv2024

A Libra in the Brain: Neural Correlates of Error Awareness Predict Moral Wrongness and Guilt Proneness

Error awareness is a fundamental mechanism in humans. Through traditional psychological tasks, certain neural activities that represent errors in objective manners have been identified. However, there is limited knowledge on how humans subjectively determine right from wrong in moral contexts. In this study, participants (N=39) mentally simulated themselves as the agents of moral and immoral behaviors, while viewing a series of actions with EEG recording and MRI scanning, respectively. A significant difference in error-related negativity (ERN) was observed among morally wrong scenarios, accompanied by higher wrongfulness ratings. Additionally, individual differences in guilt-proneness could predict the subjects ERN amplitude. The ERN amplitude was correlated with the BOLD activity in the anterior mid-cingulate cortex and anterior insula to immoral scenarios, reflecting error awareness toward moral wrongfulness. The late potential component displayed greater negativity to immoral scenarios and was correlated with BOLD activities in the amygdala, ventromedial prefrontal cortex, and temporoparietal junction, indicating cognitive and affective evaluation in moral judgment. In line with the moral dynamic framework, our results demonstrated individual variability in moral judgments, as indicated by dispersed and overlapping cognitive neural networks. This suggests that subjective evaluations of wrongfulness are underpinned by neural mechanisms, associated with those involved in objective error awareness.

neuroscience↗

bioRxiv2024

Biophysical Profiling of Red Blood Cells from Thin-film Blood Smears using Deep Learning

Microscopic inspection of thin-film blood smears is widely used to identify red blood cell (RBC) pathologies, including malaria parasitism and hemoglobinopathies, such as sickle cell disease and thalassemia. Emerging research indicates that non-pathologic changes in RBCs can also be detected in images, such as deformability and morphological changes resulting from the storage lesion. In transfusion medicine, cell deformability is a potential biomarker for the quality of donated RBCs. However, a major impediment to the clinical translation of this biomarker is the difficulty associated with performing this measurement. To address this challenge, we developed an approach for biophysical profiling of RBCs based on cell images in thin-film blood smears. We hypothesize that subtle cellular changes are evident in blood smear images, but this information is currently undetectable by human cognition. To test this hypothesis, we developed a deep learning strategy to analyze Giemsa-stained blood smears to assess the subtle morphologies indicative of RBC deformability and storage-based degradation. Specifically, we prepared thin-film blood smears from 27 RBC samples (9 donors evaluated at 3 storage timepoints) and imaged them using high-resolution microscopy. Using this dataset, we trained a convolutional neural network to evaluate image-based morphological features related to cell deformability. The prediction of donor deformability is strongly correlated to the microfluidic scores and can be used to categorize images into specific deformability groups with high accuracy. We also used this model to evaluates differences in RBC morphology resulting from cold storage. Together, our results demonstrate that deep learning models can exceed the limits of human cognition to detect subtle cellular differences in morphology resulting from deformability and cold storage. This result suggests the potential to assess donor blood quality from thin-film blood smears, which can be acquired ubiquitously in clinical workflows.

bioengineering↗

bioRxiv2024

Structure and function of an intermediate GPCR-G protein complex

Unraveling the signaling roles of intermediate complexes is pivotal for G protein-coupled receptor (GPCR) drug development. Despite hundreds of GPCR-G{beta}{gamma} structures, these snapshots primarily capture the fully activated end-state complex. Consequently, a comprehensive understanding of the conformational transitions during GPCR activation and the roles of intermediate GPCR-G protein complexes in signaling remain elusive. Guided by a conformational landscape profiled by 19F quantitative NMR (19F-qNMR) and Molecular Dynamics (MD) simulations, we resolved the structure of an unliganded GPCR-G protein intermediate complex by blocking its transition to the fully activated end-state complex. More importantly, we presented direct evidence that the intermediate GPCR-Gs{beta}{gamma} complex initiates a rate-limited nucleotide exchange without progressing to the fully activated end-state complex, thereby bridging a significant gap in our understanding the complexity of GPCR signaling. Understanding the roles of individual conformational states and their complexes in signaling efficacy and bias will help us to design drugs that discriminately target a disease-related conformation.

biophysics↗

bioRxiv2024

p300/CBP degradation is required to disable the active AR enhanceosome in prostate cancer

Prostate cancer is an exemplar of an enhancer-binding transcription factor-driven disease. The androgen receptor (AR) enhanceosome complex comprised of chromatin and epigenetic coregulators assembles at enhancer elements to drive disease progression. The paralog lysine acetyltransferases p300 and CBP deposit histone marks that are associated with enhancer activation. Here, we demonstrate that p300/CBP are determinant cofactors of the active AR enhanceosome in prostate cancer. Histone H2B N-terminus multisite lysine acetylation (H2BNTac), which is exclusively reliant on p300/CBP catalytic function, marked active enhancers and was notably elevated in prostate cancer lesions relative to the adjacent benign epithelia. Degradation of p300/CBP rapidly depleted acetylation marks associated with the active AR enhanceosome, which was only partially phenocopied by inhibition of their reader bromodomains. Notably, H2BNTac was effectively abrogated only upon p300/CBP degradation, which led to a stronger suppression of p300/CBP-dependent oncogenic gene programs relative to bromodomain inhibition or the inhibition of its catalytic domain. In vivo experiments using an orally active p300/CBP proteolysis targeting chimera (PROTAC) degrader (CBPD-409) showed that p300/CBP degradation potently inhibited tumor growth in preclinical models of castration-resistant prostate cancer and synergized with AR antagonists. While mouse p300/CBP orthologs were effectively degraded in host tissues, prolonged treatment with the PROTAC degrader was well tolerated with no significant signs of toxicity. Taken together, our study highlights the pivotal role of p300/CBP in maintaining the active AR enhanceosome and demonstrates how target degradation may have functionally distinct effects relative to target inhibition, thus supporting the development of p300/CBP degraders for the treatment of advanced prostate cancer.

cancer biology↗

bioRxiv2024

CDK12 Loss Promotes Prostate Cancer Development While Exposing Vulnerabilities to Paralog-Based Synthetic Lethality

Biallelic loss of cyclin-dependent kinase 12 (CDK12) defines a unique molecular subtype of metastatic castration-resistant prostate cancer (mCRPC). It remains unclear, however, whether CDK12 loss per se is sufficient to drive prostate cancer development--either alone, or in the context of other genetic alterations--and whether CDK12-mutant tumors exhibit sensitivity to specific pharmacotherapies. Here, we demonstrate that tissue-specific Cdk12 ablation is sufficient to induce preneoplastic lesions and robust T cell infiltration in the mouse prostate. Allograft-based CRISPR screening demonstrated that Cdk12 loss is positively associated with Trp53 inactivation but negatively associated with Pten inactivation--akin to what is observed in human mCRPC. Consistent with this, ablation of Cdk12 in prostate organoids with concurrent Trp53 loss promotes their proliferation and ability to form tumors in mice, while Cdk12 knockout in the Pten-null prostate cancer mouse model abrogates tumor growth. Bigenic Cdk12 and Trp53 loss allografts represent a new syngeneic model for the study of androgen receptor (AR)-positive, luminal prostate cancer. Notably, Cdk12/Trp53 loss prostate tumors are sensitive to immune checkpoint blockade. Cdk12-null organoids (either with or without Trp53 co-ablation) and patient-derived xenografts from tumors with CDK12 inactivation are highly sensitive to inhibition or degradation of its paralog kinase, CDK13. Together, these data identify CDK12 as a bona fide tumor suppressor gene with impact on tumor progression and lends support to paralog-based synthetic lethality as a promising strategy for treating CDK12-mutant mCRPC.

cancer biology↗

bioRxiv2024

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized [~]250 disease-risk genes and drug targets with associated cell types. Summary Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/585576v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@70b24org.highwire.dtl.DTLVardef@6c9eddorg.highwire.dtl.DTLVardef@131fae2org.highwire.dtl.DTLVardef@4e0f1e_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

In vivo optogenetics using a Utah Optrode Array with enhanced light output and spatial selectivity

Optogenetics allows manipulation of neural circuits in vivo with high spatial and temporal precision. However, combining this precision with control over a significant portion of the brain is technologically challenging (especially in larger animal models). Here, we have developed, optimised, and tested in vivo, the Utah Optrode Array (UOA), an electrically addressable array of optical needles and interstitial sites illuminated by 181 {micro}LEDs and used to optogenetically stimulate the brain. The device is specifically designed for non-human primate studies. Thinning the combined {micro}LED and needle backplane of the device from 300 {micro}m to 230 {micro}m improved the efficiency of light delivery to tissue by 80%, allowing lower {micro}LED drive currents, which improved power management and thermal performance. The spatial selectivity of each site was also improved by integrating an optical interposer to reduce stray light emission. These improvements were achieved using an innovative fabrication method to create an anodically bonded glass/silicon substrate with through-silicon vias etched, forming an optical interposer. Optical modelling was used to demonstrate that the tip structure of the device had a major influence on the illumination pattern. The thermal performance was evaluated through a combination of modelling and experiment, in order to ensure that cortical tissue temperatures did not rise by more than 1{degrees}C. The device was tested in vivo in the visual cortex of macaque expressing ChR2-tdTomato in cortical neurons. It was shown that the strongest optogenetic response occurred in the region surrounding the needle tips, and that the extent of the optogenetic response matched the predicted illumination profile based on optical modelling - demonstrating the improved spatial selectivity resulting from the optical interposer approach. Furthermore, different needle illumination sites generated different patterns of low-frequency potential (LFP) activity.

neuroscience↗

bioRxiv2024

Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction

Structure-based machine learning algorithms have been utilized to predict the properties of protein-protein interaction (PPI) complexes, such as binding affinity, which is critical for understanding biological mechanisms and disease treatments. While most existing algorithms represent PPI complex graph structures at the atom-scale or residue-scale, these representations can be computationally expensive or may not sufficiently integrate finer chemical-plausible interaction details for improving predictions. Here, we introduce MCGLPPI, a novel geometric representation learning framework that combines graph neural networks (GNNs) with the MARTINI molecular coarse-grained (CG) model to predict overall PPI properties accurately and efficiently. This framework maps proteins onto a concise CG-scale complex graph, where nodes represent CG beads and edges encode chemically plausible interactions. The GNN-based encoder is tailored to extract high-quality representations from this graph, efficiently capturing the overall properties of the protein complex structure. Extensive experiments on three different downstream PPI property prediction tasks demonstrate that MCGLPPI achieves competitive performance compared with the counterparts at the atom- and residue-scale, but with only a third of the computational resource consumption. Furthermore, the CG-scale pre-training on protein domain-domain interaction structures enhances its predictive capabilities for PPI tasks. MCGLPPI offers an effective and efficient solution for PPI overall property predictions, serving as a promising tool for the large-scale analysis of biomolecular interactions.

bioinformatics↗

bioRxiv2024

Chronic Ethanol Exposure Produces Persistent Impairment in Cognitive Flexibility and Decision Signals in the Striatum

Lack of cognitive flexibility is a hallmark of substance use disorders and has been associated with drug-induced synaptic plasticity in the dorsomedial striatum (DMS). Yet the possible impact of altered plasticity on real-time striatal neural dynamics during decision-making is unclear. Here, we identified persistent impairments induced by chronic ethanol (EtOH) exposure on cognitive flexibility and striatal decision signals. After a substantial withdrawal period from prior EtOH vapor exposure, male, but not female, rats exhibited reduced adaptability and exploratory behavior during a dynamic decision-making task. Reinforcement learning models showed that prior EtOH exposure enhanced learning from rewards over omissions. Notably, neural signals in the DMS related to the decision outcome were enhanced, while those related to choice and choice-outcome conjunction were reduced, in EtOH-treated rats compared to the controls. These findings highlight the profound impact of chronic EtOH exposure on adaptive decision-making, pinpointing specific changes in striatal representations of actions and outcomes as underlying mechanisms for cognitive deficits.

neuroscience↗

bioRxiv2024

Protocatechuic acid induces endogenous oxidative stress in CR-hvKP by regulating the EMP-PPP pathway

BackgroundKlebsiella pneumoniae is an important opportunistic pathogen and zoonotic pathogen. The widespread use of antibiotics has led to the emergence of a large number of multidrug-resistant Klebsiella pneumoniae in clinical animal husbandry, posing a serious threat to global health security. Protocatechuic acid (PCA) is a phenolic acid substance naturally present in many vegetables and fruits. It is a safe and highly developed new type of antibacterial synergist. PurposeThis study explored the antibacterial and synergistic mechanisms of PCA against Carbapenem-resistant hypervirulent Klebsiella pneumoniae. Study designMetabolomic analysis using PCA to investigate the metabolic effects of CR-hvKP and further explore the antibacterial mechanisms resulting from this metabolic regulation. MethodsThe MIC of PCA was measured by microdilution, and its bactericidal effect was observed by DAPI staining. Resistance and hemolysis tests were performed to ensure safety. The synergy of PCA and meropenem was tested by checkerboard assay. The biofilm inhibition was assessed by crystal violet and EPS assays. The membrane morphology, permeability, and potential were examined by SEM, PI, NPN, and DiSC3(5). The metabolic changes were evaluated by AlamarBlue, metabolomics, enzyme activity, ELISA, molecular docking, and qRT-PCR. The oxidative stress and metabolic disorders were verified by NADP(H), ROS, MDA, and ATP assays. ResultsThe results showed that PCA can synergize with antibiotics and inhibit the biofilm and membrane functions of CR-hvKP at low concentrations. Metabolomics revealed that PCA affects the EMP and PPP pathways of CR-hvKP, causing oxidative stress. This involves the binding of PGAM and the downregulation of BPGM, leading to the accumulation of glycerate-3P. This results in the inhibition of G6PDH and the imbalance of NADPH/NADP+, disrupting the energy metabolism and increasing the oxidative stress, which impair the biofilm and membrane functions and enhance the antibiotic efficacy. ConclusionThe results demonstrate that PCA regulates the EMP-linked PPP pathway of CR-hvKP, inhibits biofilm and membrane functions, and synergizes with antibiotics to kill bacteria, providing new insights and candidates for natural antibacterial enhancers. Author SummaryKlebsiella pneumoniae is a common pathogenic bacterium that can infect both humans and animals, causing serious diseases such as pneumonia, meningitis, and sepsis. Due to the overuse of antibiotics, this bacterium has developed resistance to many drugs, posing a significant threat to global health security. Through our research, we have discovered a natural substance called protocatechuic acid (PCA) that can enhance the effectiveness of antibiotics against this bacterium. PCA is found in many vegetables and fruits and is a safe and non-toxic antibacterial adjuvant. Our analysis of the metabolomics of PCA on Klebsiella pneumoniae has revealed its antibacterial and synergistic mechanisms. The study found that PCA can affect the bacteriums sugar metabolism pathway, leading to the generation of endogenous oxidative stress. This disrupts their energy metabolism, damages their cell membranes and biofilms, making them more susceptible to being killed by antibiotics. Through this mechanism, PCA can synergize with common antibiotics such as meropenem, enhancing their bactericidal ability. Our research has demonstrated that PCA is an effective antibacterial adjuvant, providing new candidates and insights for the development of natural antibacterial agents. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/583678v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@2e2963org.highwire.dtl.DTLVardef@9f3c51org.highwire.dtl.DTLVardef@3125a8org.highwire.dtl.DTLVardef@9f39b7_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

High performance TadA-8e derived cytosine and dual base editors with undetectable off-target effects in plants

Cytosine base editors (CBEs) and adenine base editors (ABEs) are powerful tools to install precise C-to-T and A-to-G base edits in living organisms. In recently years, a highly efficient ABE based on engineered TadA-8e, known as ABE8e, has been developed to confer highly efficient A-to-G editing in mammalian cells and plants. Interestingly, TadA-8e can be further evolved and engineered to confer cytosine base editing. In this study, we compare in rice and tomato cells a serial of engineered CBEs derived from TadA-8e and identify TadCBEa, TadCBEd, and TadCBEd_V106W as efficient CBEs with high editing purity, while maintaining the relatively narrow editing window of ABE8e. Excitingly, we show TadDE is a new class of dual base editor where a single deaminase domain promotes simultaneous C-to-T and A-to-G base editing in plant cells. Multiplexed base editing is demonstrated in transgenic rice plants with TadCBEa and TadDE. Furthermore, no off-target effects of TadCBEa and TadDE can be detected by whole genome and transcriptome sequencing of the transgenic lines, suggesting high editing specificity. Finally, we demonstrate two gain-of-function crop engineering applications in rice by using the efficient dual base editor, TadDE. In the first case, herbicide resistance alleles of OsALS are introduced by TadDE. In the second case, synonymous mutations are generated in OsSPL14, making its transcript resistant to OsMIR156-mediated degradation. Together, this study reports TadA-8e derived CBEs and a dual base editor with high editing activity, purity, and specificity. They are valuable additions to the expanding plant base editing toolbox.

molecular biology↗

bioRxiv2024

Systematic mapping of MCU-mediated mitochondrial calcium signaling networks

The Mitochondrial Ca2+ Uniporter Channel (MCUC) allows calcium entry into the mitochondrial matrix to regulate energy metabolism but also cell death. Although, several MCUC components have been identified, the molecular basis of mitochondrial Ca2+ signaling networks and their remodeling upon changes in uniporter activity have not been systematically assessed. Using an unbiased and quantitative proteomic approach, we map the MCUC interactome in HEK293 cells under physiological conditions and upon chronic loss or gain of mitochondrial Ca2+ uptake. Besides all previously known subunits of the uniporter, we identify 89 high-confidence interactors linking MCUC to several mitochondrial complexes and pathways, half of which are currently linked to metabolic, neurological, and immunological diseases. As a proof-of-concept, we validate EFHD1 as a binding partner of MCU, EMRE and MCUB with a MICU1-dependent inhibitory effect on Ca2+ uptake. To investigate compensatory mechanisms and functional consequences of mitochondrial Ca2+ dyshomeostasis, we systematically survey the MCU interactome upon silencing of EMRE, MCUB, MICU1 or MICU2. We observe profound changes in the MCU interconnectivity, whereby downregulation of EMRE reduces the number of MCU interactors of over 10-fold, while silencing of MCUB leads to a wider functional network linking MCU to mitochondrial stress response pathways and cell death. Altogether our study provides a comprehensive map of MCUC protein-protein interactions and a rich, high-confidence resource that can be explored to gain insights into the players and mechanisms involved in calcium signal transduction cascades and their relevance in human diseases.

cell biology↗

bioRxiv2024

Fertilization by short-term stored sperm alters DNA methylation patterns in common carp (Cyprinus carpio) embryos at single-base resolution

Short-term storage of sperm in vitro is widely used for artificial fertilization in aquaculture. It has been shown that short-term storage affects sperm motility characteristics, resulting in diminished fertility. However, the detrimental effects of short-term sperm storage on embryos development have remained largely unexplored in single-base methylome resolution. The main aim of the present study was to investigate DNA methylation in the offspring of common carp (Cyprinus carpio) derived from short-term stored sperm. Sperm were stored in artificial seminal plasma on ice (0-2{degrees}C) for 0, 3 and 6 days in vitro, fertilization was performed using oocytes from a single female, and embryos were collected at the mid-blastula stage. Sperm and embryo DNA was extracted, analysed by liquid chromatography with tandem mass spectrometry (LC-MS/MS) and whole genome bisulfite sequencing (WGBS). DNA methylation was then assessed. Sperm storage showed negative effects on motility, viability and DNA integrity, but had no effect on global DNA methylation of spermatozoa and resulting embryos. Results from the WGBS showed that methylation of 3313 genes was affected in the embryos fertilized with the 6-day-stored sperm, and the differentially methylated regions (DMRs) identified were mainly involved in cell adhesion, calcium, mitogen-activated protein kinase and adrenergic signalling, melanogenesis, metabolism and RNA transport. Such results suggest that prolongation of storage time may have certain impacts on embryonic development. These initial results provide valuable information for future consideration of the DNA methylome in embryos generated from short-term stored sperm, which is widely used for genetic management of broodstock in aquaculture.

molecular biology↗

bioRxiv2024

Protein property prediction based on local environment by 3D equivariant convolutional neural networks

Predicting the properties of proteins is an important procedure in protein engineering. It determines the subspace of mutations for protein modifications, which is critical to the success of the project, but heavily relies on the knowledge and experience of scientists. In this study, we propose a novel deep 3D-CNN model, Eq3DCNN, specifically designed for local environment-related tasks in protein engineering. Eq3DCNN uses basic atom descriptors and their coordinates as inputs, utilizing customized data augmentations to enhance its training efficiency. To make the Eq3DCNN extracted features with more generalization capability, we incorporated a rotation equivariant module to get rotation invariant features. Using cross-validations with different data splitting strategies and under the scenarios of zero-shot predictions, we demonstrate that Eq3DCNN outperformed other 3D-CNN models in stability predictions, and also well-preformed on other prediction tasks, such as the binding pocket and the secondary structure predictions. Our results also identified the key factors that contribute to the models accuracy and the scope of its applications. These findings may help scientists in designing better mutation experiments and increasing the success rate in protein engineering.

bioinformatics↗

bioRxiv2024

Selective degradation of multimeric proteins via chemically induced proximity to TRIM21

Targeted protein degradation (TPD) has emerged as an effective strategy to eliminate disease-causing proteins by inducing their interactions with the protein degradation machinery. First-generation TPD agents exploit a limited set of broadly expressed E3 ubiquitin ligases with constitutive activity, forbidding their application to proteins requiring higher levels of targeting selectivity. Here, by phenotype-based screening, we discovered that the antipsychotic drug acepromazine possesses interferon-enhanced cytotoxicity towards cancer cell lines expressing high levels of aldo-keto reductases 1C. These enzymes convert acepromazine into its stereo-selective metabolite (S)-hydroxyl-acepromazine, which recruits the interferon-induced E3 ubiquitin ligase TRIM21 to the vicinity of the nuclear pore complex, resulting in the degradation of nuclear pore proteins. Co-crystal structures of acepromazine and derivatives in complex with the PRYSPRY domain of TRIM21 revealed a ligandable pocket, which was exploited for designing heterobifunctional degraders. The resulting chemicals selectively degrade multimeric proteins-- such as those in biomolecular condensates--without affecting monomeric proteins, consistent with the requirement of substrate-induced clustering for TRIM21 activation. As aberrant protein assemblies have been causally linked to diseases such as neurodegeneration, autoimmunity, and cancer, our findings highlight the potential of TRIM21-based multimer-selective degraders as a strategy to tackle the direct causes of these diseases.

pharmacology and toxicology↗

bioRxiv2024

A hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data

BackgroundMethylation Quantitative Trait Loci (meQTLs) are chromosomal regions that harbor genetic variants affecting DNA methylation levels. The identification of meQTLs can be accomplished through quantifying the effects of single nucleotide polymorphisms (SNPs) on DNA methylation levels, and these inferred meQTLs can shed light on the complex interplay between the genome and methylome. However, most meQTL studies to date utilize bulk methylation datasets composed of different cell types that may have distinct methylation patterns in each cell type. Current technological challenges hinder the comprehensive collection of large-scale, cell-type-specific (CTS) methylation data, which limits our understanding of CTS methylation regulation. To address this challenge, we propose a hierarchical Bayesian interaction model (HBI) to infer CTS meQTLs from bulk methylation data. ResultsOur HBI method integrates bulk methylations data from a large number of samples and CTS methylation data from a small number of samples to estimate CTS meQTLs. Through simulations, we show that HBI improves the estimation (accuracy and power) of CTS genetic effects on DNA methylation. To systematically characterize genome-wide SNP-methylation level associations in multiple cell types, we apply HBI to bulk methylation data measured in peripheral blood mononuclear cells (PBMC) from a cohort of 431 individuals together with flow-sorted cell-derived methylation sequencing (MC-seq) data measured in isolated white blood cells (CD4+ T-cells, CD8+ T-cells, CD16+ monocytes) for 47 individuals. We demonstrate that HBI can identify CTS meQTLs and improve the functional annotation of SNPs. ConclusionsHBI can incorporate strong and robust signals from MC-seq data to improve the estimation of CTS meQTLs. Applying HBI to link the methylome and genome data helps to identify biologically relevant cell types for complex traits.

genetics↗