Biology subjects

Han, W.

Publications and source records attributed to Han, W..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Exponential increase in QTL detection with increased sample size.

Power analyses are often used to determine the number of animals required for a genome wide association analysis (GWAS). These analyses are typically intended to estimate the sample size needed for at least one locus to exceed a genome-wide significance threshold. A related question that is less commonly considered is the number of significant loci that will be discovered with a given sample size. We used simulations based on a real dataset that consisted of 3,173 male and female adult N/NIH heterogeneous stock (HS) rats to explore the relationship between sample size and the number of significant loci discovered. Our simulations examined the number of loci identified in sub-samples of the full dataset. The sub-sampling analysis was conducted for four traits with low (0.15 {+/-} 0.03), medium (0.31 {+/-} 0.03 and 0.36 {+/-} 0.03) and high (0.46 {+/-} 0.03) SNP-based heritabilities. For each trait, we sub-sampled the data 100 times at different sample sizes (500, 1,000, 1,500, 2,000, and 2,500). We observed an exponential increase in the number of significant loci with larger sample sizes. Our results are consistent with similar observations in human GWAS and imply that future rodent GWAS should use sample sizes that are significantly larger than those needed to obtain a single significant result.

genetics↗

bioRxiv2023

Automated quantitative trait locus analysis (AutoQTL)

BackgroundQuantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complex decisions related to analysis of complex traits and generate diverse solutions to describe relationships that exist in genetic data. ResultsUsing a dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus, AutoQTL captures the phenotypic variance explained under a standard additive model while also providing evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions from simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL. ConclusionsThis proof-of-concept illustrates that automated machine learning techniques can be applied to genetic data and has the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection strategies.

genetics↗

bioRxiv2022

Maternal microbes and early brain development in mouse

The complex symbiotic relationship between the mammalian body and gut microbiome plays a critical role in the health outcomes of offspring later in life. The gut microbiome modulates virtually all physiological functions through direct or indirect interactions to maintain physiological homeostasis. Previous studies indicate a link between maternal/early-life gut microbiome, brain development, and behavioral outcomes relating to social cognition. Here we present direct evidence of the role of the gut microbiome in brain development. Through magnetic resonance imaging (MRI), we investigated the impact of the gut microbiome on brain organization and structure using germ-free (GF) mice and conventionalized mice, with the gut microbiome reintroduced after weaning. We found broad changes in brain volume in GF mice that persist despite the reintroduction of gut microbes at weaning. These data suggest a direct link between the maternal gut or early-postnatal microbe and their impact on brain developmental programming.

neuroscience↗

bioRxiv2022

Human mutations in SLITRK3 implicated in GABAergic synapse development in mice

We report on biallelic homozygous and monoallelic de-novo variants in SLITRK3 in 3 unrelated families presenting with epileptic encephalopathy associated with a broad neurological involvement characterized by microcephaly, intellectual disability, seizures, and global developmental delay. SLITRK3 encodes for a transmembrane protein that is involved in controlling neurite outgrowth and inhibitory synapse development and that has an important role in brain function and neurological diseases. Using primary cultures of hippocampal neurons carrying patients SLITRK3 variants and in combination with electrophysiology, we demonstrate that recessive variants are loss-of-function alleles. By analyzing the development and phenotype of SLITRK3 KO (SLITRK3-/-) mice, we bring additional evidence of enhanced susceptibility to pentylenetetrazole-induced seizure with the appearance of spontaneous epileptiform EEG, as well as developmental deficits such as higher motor activities and reduced parvalbumin interneurons. Taken together, our results exhibit impaired development of peripheral and central nervous system and support a conserved role of this transmembrane protein in neurological function. Our study delineates an emerging spectrum of human core synaptopathies caused by variants in genes that encode SLITRK proteins and essential regulatory components of the synaptic machinery. The hallmark of these disorders is impaired postsynaptic neurotransmission at nerve terminals; an impaired neurotransmission resulting in a wide array of (often overlapping) clinical features, including neurodevelopmental impairment, weakness, seizures, and abnormal movements. The genetic synaptopathy caused by SLITRK3 mutations highlights the key roles of this gene in human brain development and function.

genetics↗

bioRxiv2022

General stain deconvolution of histopathology images with physics-guided deep learning

Advances have been made in the use of deep learning to extract quantitative and predictive information from digital pathology slides, yet many barriers remain before clinical translation and deployment. In particular, models need to be generalizable despite the wide variations in image characteristics due to inter-scanner variability and differences in slide preparation protocols. This has led to an interest in stain deconvolution methods that could correct for the variability in image appearances. However, most existing stain deconvolution methods were developed and validated on specific datasets and perform poorly on unseen data. We developed Physics-Guided Deep Image Prior network for Stain deconvolution (PGDIPS), a method that combines a novel optical physics model and a self-supervised deep neural network to perform deconvolution for various classes and any number of stains, without the need of training data. PGDIPS outperformed state-of-the-art approaches for the deconvolution of conventional stain combinations, enabled analysis of previously unsupported special stains, and provided superior interpretability by explicitly encoding representations for stain properties and the light transmittance/absorbance process. PGDIPS is publicly available as an end-to-end off-the-shelf tool that does not require data curation, domain knowledge or high computation power.

bioinformatics↗

bioRxiv2022

Rapid and Signal Crowdedness-Robust In-Situ Sequencing through Hybrid Block Coding

Spatial transcriptomics technology has revolutionized our understanding of cell types and tissue organization, opening new possibilities for researchers to explore transcript distributions at subcellular levels. However, existing methods have limitations in resolution, sensitivity, or speed. To overcome these challenges, we introduce SPRINTseq (Spatially Resolved and signal-diluted Next-generation Targeted sequencing), an innovative in situ sequencing strategy that combines hybrid block coding and molecular dilution strategies. Our method enables fast and sensitive high-resolution data acquisition, as demonstrated by recovering over 142 million transcripts using a 108 gene panel from 453,843 cells from four mouse brain coronal slices in less than two days. Using this advanced technology, we uncover the cellular and subcellular molecular architecture of Alzheimers disease, providing additional information into abnormal cellular behaviors and their subcellular mRNA distribution. This improved spatial transcriptomics technology holds great promise for exploring complex biological processes and disease mechanisms.

genomics↗

bioRxiv2022

miR-148a-3p inhibits osteogenesis by targeting Itga11 via PI3K/Akt/GSK3/β-catenin pathway

In previous research, miR-148a-3p deficiency was observed in bone malformation in hemifacial microsomia. Nevertheless, the mechanism of miR-148a regulating osteogenesis remains unclear. Herein, in this article, we probed into the role of miR-148a-3p in bone physiology by utilizing miR-148a knock-out (KO) mice. Compared with wild-type (WT) or heterozygotic (HE) littermates, miR-148a knock-out mice manifested lower body weight, bone dysplasia with increased bone mass. Through in-vitro experiments, in terms of miR-148a-3p overexpression (miRNA mimic transfection) and knockout (primary cells from WT and KO littermates), we found that miR-148a-3p can suppress osteogenesis, either in the ALP activity or bone nodules formation. Afterward, by means of proteomics, combined with RNA-sequencing and prediction databases of microRNA targets (miRDB and TargetScan), nine candidate genes targeted by miR-148a-3p were identified. Among them, only Itga11 was regulated by mRNA degradation, while the others were modulated via post-transcriptional inhibition. Based on several online databases (GenePaint, BioGPS, STRING), Integrin Subunit Alpha 11 (Itga11) was suggested to play an essential role in osteogenesis and it was confirmed as one direct target of miR-148a-3p by dual-luciferase reporter assay. Meanwhile, gene set enrichment analysis (GSEA) indicated activation of PI3K-Akt signaling pathway and WNT signaling pathway in miR-148a KO mice. The thereafter western blot confirmed that PI3K/Akt/GSK3/{beta}-catenin signaling pathway was involved. Finally, with the help of esterase-response bone-affiliative liposome with the Itga11 siRNA delivery system, the enhanced osteogenesis in miR-148a KO mice was partly rescued. Taken together, we demonstrated that miR-148a-3p can inhibit osteogenesis by targeting Itga11 via PI3K/Akt/GSK3/{beta}-catenin pathway.

cell biology↗

bioRxiv2022

Extracellular matrix stiffness regulates fibroblast differentiation by influencing DNA methyltransferase 1 expression through microtubule polymerization

Cells sense physical cues, such as changes in extracellular matrix (ECM) stiffness, and translate these stimuli into biochemical signals that control various aspects of cellular behavior, thereby facilitating physiological and pathological processes in various organs. Evidence from multiple studies suggests that the anterior vaginal wall stiffness is higher in POP patients than in non-POP patients. Our experiments found that the expression of -smooth muscle actin (-SMA) in the anterior vaginal wall of patients with POP was increased, and the expression of DNMT1 was decreased. We used polyacrylamide gel to simulate matrix stiffening in vitro, and substrate stiffening induced the high expression of myofibroblast markers -SMA and CTGF in L929 cells. Inhibition of DNMT1 promotes fibroblast differentiation into myofibroblasts in vitro. The results of bioinformatics analysis showed that the expression of DNMT1 was significantly correlated with microtubule polymerization-related proteins. The experiment showed that the microtubule polymerization inhibitor nocodazole could eliminate the decrease of DNMT1 expression in fibroblasts induced by high stiffness. We conclude that fibroblasts sense an increase in the stiffness of the surrounding matrix and regulate fibroblast differentiation by regulating the expression of DNA methyltransferase 1 (DNMT1) through the regulation of microtubule polymerization. This study may help to elucidate the complex crosstalk between vaginal fibroblasts and their surrounding matrix in both healthy and pathological conditions, and provide new insights into the implications of potentially targeted phenotypic regulation mechanisms in material-related therapeutic applications.

cell biology↗

bioRxiv2022

Molecular and genetic mechanisms conferring dissolution of dioecy in Diospyros oleifera Cheng

Dioecy, a sexual system of single-sex (gynoecious/androecious) individuals, is rare in flowering plants. This rarity may be a result of the frequent transition from dioecy into systems with co-sex individuals. Here, we report potential molecular and genetic mechanisms that underlie the dissolution of dioecy to monoecy and andro(gyno)monoecy, based on multiscale genome-wide investigations of 150 accessions of Diospyros oleifera. All co-sex D. oleifera plants, including monoecious and andro(gyno)monoecious individuals, possessed the male determinant gene OGI, implying that genetic factors control gynoecia development in genetically male D. oleifera. In both single- and co-sex plants, female function was expressed in the presence of a genome-wide decrease in methylation levels, along with sexually distinct regulatory networks of smRNAs and their targets. Furthermore, a genome-wide association study (GWAS) identified a genomic region and a DUF247 gene cluster strongly associated with the monoecious phenotype, as well as several regions that may contribute to andromonoecy. Collectively, our findings imply stable breakdown of the dioecious system in D. oleifera, presumably a result of the genomic features of the sex-linked region.

plant biology↗

bioRxiv2022

Pathway and mechanism of tubulin folding mediated by TRiC/CCT conjugated with its ATPase cycle revealed by cryo-EM

The eukaryotic chaperonin TRiC/CCT assists the folding of about 10% of cytosolic proteins through an ATP-driven conformational cycle, and the essential cytoskeleton protein tubulin is the obligate substrate of TRiC. Here, we present an ensemble of cryo-EM structures of human TRiC throughout its ATPase cycle, with three of them revealing endogenously engaged tubulin in different folding stages. Our structural and XL-MS analyses suggested a gradual upward translocation and stabilization of tubulin within the TRiC chamber accompanying TRiC ring closure. Remarkably, in the closed TRiC-tubulin-S3 map resolved to 3.1-[A]-resolution, we captured a near-natively folded tubulin. We found the near-natively folded tubulin engaging through its N and C domains mainly with the A and I domains of the CCT3/6/8 subunits through electrostatic and hydrophilic interactions, while the tubulin I domain was found to remain dynamic. Moreover, we also showed the potential role of TRiC C-terminal tails in substrate stabilization and folding. Our study delineates the pathway and molecular mechanism of TRiC-mediated tubulin folding conjugated with TRiC ATPase cycle, and may also inform the design of therapeutic agents targeting TRiC-tubulin interactions.

biochemistry↗

bioRxiv2022

β1 integrin regulates alveolar epithelial cell differentiation following injury

During alveolar repair, alveolar type 2 (AT2) epithelial cell progenitors rapidly proliferate and differentiate into flat type 1 alveolar epithelial cells. Failure of normal alveolar repair mechanisms can lead to loss of alveolar structure (emphysema) or development of fibrosis, depending on the type and severity of injury. To test if {beta}1-containing integrins are required during repair following acute injury, we administered E. coli lipopolysaccharide (LPS) by intratracheal injection to mice with a post-developmental deletion of {beta}1 integrin in AT2 cells. While control mice recovered from LPS injury without structural abnormalities, {beta}1-deficient mice had more severe inflammation and developed emphysema. In addition, recovering alveoli were repopulated with an abundance of rounded epithelial cells co-expressing type 2, type 1, and mixed intermediate cell state markers, with few mature type 1 cells. {beta}1-deficient AT2 cells showed persistently increased proliferation after injury, which was blocked by inhibiting NF-{kappa}B activation in these cells. Lineage tracing experiments revealed that {beta}1-deficient AT2 cells failed to differentiate into mature type 1 alveolar epithelial cells. Together, these findings demonstrate that functional alveolar repair after injury with terminal alveolar epithelial differentiation requires {beta}1-containing integrins.

cell biology↗

bioRxiv2022

Structural basis of plp2-mediated cytoskeletal protein folding by TRiC/CCT

The eukaryotic chaperonin TRiC/CCT assists the folding of ~10% cytosolic proteins. The essential cytoskeletal proteins tubulin and actin are the obligate substrates of TRiC and their folding involves cochaperone and co-factors. Here, through cryo-EM analysis, we present a more complete picture of yeast TRiC-assisted tubulin and actin folding in the ATPase-cycle, under the coordination of cochaperone plp2. Our structures revealed that in the open C1 and C2 states, plp2 and substrates tubulin/actin engage with TRiC inside its chamber, one per ring. Noteworthy, we captured a ternary TRiC-plp2-tubulin complex in the closed C3 state, engaged with a full-length {beta}-tubulin in the native folded state even loaded with a GTP, and with a plp2 occupying the opposite ring, not reported before. Another closed C4 state revealed an actin in the intermediate state of folding and a plp2 occupying the other ring. Intriguingly, along with TRiC ring closure, we captured a large translocation of plp2 within TRiC chamber coordinating substrate translocation on the CCT6 hemisphere, potentially facilitating substrate stabilization and folding. Our findings provide structural insights into the folding mechanism of the major cytoskeletal proteins tubulin/actin under the coordination of the complex biogenesis machinery TRiC and plp2, and could extend our understanding on the links between cytoskeletal proteostasis and related human diseases.

biophysics↗

bioRxiv2022

Predicting the antigenic evolution of SARS-COV-2 with deep learning

The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) antigenic profile evolves in response to the vaccine and natural infection-derived immune pressure, resulting in immune escape and threatening public health. Exploring the possible antigenic evolutionary potentials improves public health preparedness, but it is limited by the lack of experimental assays as the sequence space is exponentially large. Here we introduce the Machine Learning-guided Antigenic Evolution Prediction (MLAEP), which combines structure modeling, multi-task learning, and genetic algorithm to model the viral fitness landscape and explore the antigenic evolution via in silico directed evolution. As demonstrated by existing SARS-COV-2 variants, MLAEP can infer the order of variants along antigenic evolutionary trajectories, which is also strongly correlated with their sampling time. The novel mutations predicted by MLAEP are also found in immunocompromised covid patients and newly emerging variants, like XBB1.5. The predictions of MLAEP were validated by conducting in vitro neutralizing antibody binding assay, which demonstrated that the model-generated variants displayed significantly increased immune evasion ability compared with the controls. In sum, our approach enables profiling existing variants and forecasting prospective antigenic variants, thus may help guide the development of vaccines and increase preparedness against future variants. Our model is available at https://mlaep.cbrc.kaust.edu.sa.

evolutionary biology↗

bioRxiv2022

PPML-Omics: a Privacy-Preserving federated Machine Learning system protects patients' privacy from omic data

Modern machine learning models towards various tasks with omic data analysis give rise to threats of privacy leakage of patients involved in those datasets. Despite the advances in different privacy technologies, existing methods tend to introduce too much computational cost (e.g. cryptographic methods) or noise (e.g. differential privacy), which hampers either model usefulness or accuracy in protecting privacy in biological data. Here, we proposed a secure and privacy-preserving machine learning method (PPML-Omics) by designing a decentralized version of the differential private federated learning algorithm. We applied PPML-Omics to analyze data from three sequencing technologies, and addressed the privacy concern in three major tasks of omic data, namely cancer classification with bulk RNA-seq, clustering with single-cell RNA-seq, and the integration of spatial gene expression and tumour morphology with spatial transcriptomics, under three representative deep learning models. We also examined privacy breaches in depth through privacy attack experiments and demonstrated that PPML-Omics could protect patients privacy. In each of these applications, PPML-Omics was able to outperform methods of comparison under the same level of privacy guarantee, demonstrating the versatility of the method in simultaneously balancing the privacy-preserving capability and utility in practical omic data analysis. Furthermore, we gave the theoretical proof of the privacy-preserving capability of PPML-Omics, suggesting the first mathematically guaranteed method with robust and generalizable empirical performance in protecting patients privacy in omic data.

bioinformatics↗

bioRxiv2022

222-nm far UVC exposure results in DNA damage and transcriptional changes to mammalian cells.

Ultraviolet (UV) germicidal tools have recently gained attention as a disinfection strategy against the COVID-19 pandemic but the safety profile arising from their exposure have been controversial and impeded larger scale implementation. We compare the emerging 222-nm far UVC and 277-nm UVC LED disinfection modules with the traditional UVC mercury lamp emitting at 254 nm to understand their effects on human retinal cell line ARPE-19 and HEK-A keratinocytes. Cells illuminated with 222-nm far UVC survived while those treated with 254-nm and 277-nm wavelengths underwent apoptosis via JNK/ATF2 pathway. However, cells exposed to 222-nm far UVC presented the highest degree of DNA damage as evidenced by yH2AX staining. Globally, these cells presented transcriptional changes in cell cycle and senescence pathways. Thus, the introduction of 222-nm far UVC lamps for disinfection purposes should be carefully considered and designed with the inherent dangers involved.

cell biology↗

bioRxiv2022

Whole-brain in vivo base editing reverses autistic-like behaviors in mice

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder associated with deficits in social communication and stereotypical behaviors. Numerous ASD-related genetic mutations have been identified and genome editing methods have been developed but successful genome editing in the whole-brain scale to alleviate autistic-like behaviors in animal models has not been achieved. Here we report the development of a new CRISPR-mediated cytidine base editor (CBE) system, which converts C{middle dot}G base pairs to T{middle dot}A. We demonstrate the effectiveness of this system by targeting an ASD-associated de novo mutation in the MEF2C gene (c.104T>C, p.L35P). We constructed a Mef2c L35P knock-in mouse and observed that Mef2c L35P heterozygous mice displayed autistic-like behaviors, including deficits in social behaviors and repetitive behaviors. We programmed the CBE to edit the C{middle dot}G base pairs of the mutated Mef2c gene (c.104T>C, p.L35P) to T{middle dot}A base pairs and delivered it via a single dose intravenous injection of blood brain barrier (BBB)-crossing AAV-PHP.eB vector into the mouse brain. This treatment restored MEF2C protein levels and reversed impairments in social interactions and repetitive behaviors in Mef2c L35P heterozygous mice. Together, this work presents an in vivo gene editing strategy in which correcting a single nucleotide mutation in the whole-brain scale could be successfully achieved, further providing a new therapeutic framework for neurodevelopmental disorders.

neuroscience↗

bioRxiv2022

Molecular basis of SARS-CoV-2 Omicron variant receptor engagement and antibody evasion and neutralization

The SARS-CoV-2 Omicron variant exhibits striking immune evasion and is spreading globally at an unprecedented speed. Understanding the underlying structural basis of the high transmissibility and greatly enhanced immune evasion of Omicron is of high importance. Here through cryo-EM analysis, we present both the closed and open states of the Omicron spike, which appear more compact than the counterparts of the G614 strain, potentially related to the Omicron substitution induced enhanced protomer-protomer and S1-S2 interactions. The closed state showing dominant population may indicate a conformational masking mechanism of immune evasion for Omicron spike. Moreover, we capture two states for the Omicron S/ACE2 complex with S binding one or two ACE2s, revealing that the substitutions on the Omicron RBM result in new salt bridges/H-bonds and more favorable electrostatic surface properties, together strengthened interaction with ACE2, in line with the higher ACE2 affinity of the Omicron relative to the G614 strain. Furthermore, we determine cryo-EM structures of the Omicron S/S3H3 Fab, an antibody able to cross-neutralize major variants of concern including Omicron, elucidating the structural basis for S3H3-mediated broad-spectrum neutralization. Our findings shed new lights on the high transmissibility and immune evasion of the Omicron variant and may also inform design of broadly effective vaccines against emerging variants.

biochemistry↗

bioRxiv2021

Variation of female pronucleus reveal oocyte or embryo abnormality: An expert experience deep learning of non-dark box analysis

BackgroundPronuclear assessment appears to have the ability to distinguish good and bad embryos in the zygote stage, but paradoxical results were obtained in clinical studies. This situation might be caused by the robust qualitative detection of the development of dynamic pronuclei. Here, we aim to establish a quantitative pronuclear measurement method by applying expert experience deep learning from large annotated datasets. MethodsConvinced handle-annotated 2PN images (13419) were used for deep learning then corresponded errors were recorded through handle check for subsequent parameters adjusting. We used 790 embryos with 52479 PN images from 155 patients for analysis the area of pronuclei and the pre-implantation genetic test results. Establishment of the exponential fitting equation and the key coefficient {beta} 1was extracted from the model for quantitative analysis for pronuclear(PN) annotation and automatic recognition. FindingsBased on the female original PN coefficient {beta}1, the chromosome-normal rate in the blastocyst with biggest PN area is much higher than that of the blastocyst with smallest PN area (58.06% vs. 45.16%, OR=1.68 [1.07-2.64]; P=0.031). After adjusting coefficient {beta}1 by the first three frames which high variance of outlier PN areas was removed, coefficient {beta}1 at 12 hours and at 14 hours post-insemination, similar but stronger evidence was obtained. All these discrepancies resulted from the female propositus in the PGT-SR subgroup and smaller chromosomal errors. Conclusion(s)The results suggest that detailed analysis of the images of embryos could improve our understanding of developmental biology. FundingNone

genetics↗