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Huang, B.

Publications and source records attributed to Huang, B..

At least 91 records · Page 5Linked to original sources
bioRxiv2024

Multi-layered Network Analysis of Osteoking in the Treatment of Osteoporosis: Unraveling Mechanisms from Gene Expression to Molecular Docking

This study aimed to elucidate the therapeutic mechanisms of Osteoking in the treatment of osteoporosis through a comprehensive analysis of potential targets, active ingredients, and associated pathways. MethodThe study employed an integrated approach to understand the molecular mechanisms underlying Osteokings treatment of osteoporosis. The construction of the protein-protein interaction network involved analyzing data from GENEMANIA and STRING databases. KEGG enrichment analysis was performed to identify enriched pathways, focusing on the cAMP signaling and PI3K-AKT signaling pathways. Active ingredients, disease targets, and osteoporosis-related pathways were integrated into a comprehensive network diagram using Cytoscape. ResultThe Gene Expression Omnibus (GEO) database was employed to identify osteoporosis-related gene targets, revealing 3,578 downregulated and 1,204 upregulated genes. Simultaneously, Osteokings active ingredients and potential targets were investigated using the Traditional Chinese Medicine Integrated Database (ETCM). A protein-protein interaction network and KEGG pathway enrichment analysis were constructed, highlighting potential targets for Osteokings therapeutic effects on osteoporosis. The study also conducted molecular docking analysis, revealing the strong binding capacities of Kaempferol with key disease targets. The results suggest that Osteoking, particularly its active component Kaempferol, holds promise as a potential intervention for osteoporosis, providing insights for further exploration and development of osteoporosis treatments ConclusionsIn conclusion, despite some limitations, this study provides valuable information for the treatment of osteoporosis. Future research should make further progress by continually expanding data sources, conducting in-depth experimental validations, and broadening the scope of targets to better understand and address this common skeletal disorder. FundingThis work was supported by the Scientific Foundation of Fuzhou Municipal Health Commission (2021-S-wp3).

bioinformatics↗
bioRxiv2024

Bottlebrush polyethylene glycol nanocarriers translocate across human airway epithelium via molecular architecture enhanced endocytosis

Pulmonary drug delivery is critical to the treatment of respiratory diseases. However, the human airway surface presents multiscale barriers to efficient drug delivery. Here we report a bottlebrush polyethylene glycol (PEG-BB) nanocarrier that can translocate across all barriers within the human airway surface. Guided by the molecular theory, we design a PEG-BB molecule consisting of a linear backbone densely grafted by many ([~]1,000) low molecular weight ([~]1000 g/mol) PEG chains; this results in a highly anisotropic, wormlike nanocarrier featuring a contour length of [~]250 nm, a cross-section of [~]20 nm, and a hydrodynamic diameter of [~]40 nm. Using the classic air-liquid-interface culture system to recapitulate essential biological features of the human airway surface, we show that PEG-BB rapidly penetrates through endogenous airway mucus and periciliary brush layer (mesh size of 20-40 nm) to be internalized by cells across the whole epithelium. By quantifying the cellular uptake of polymeric carriers of various molecular architectures and manipulating cell proliferation and endocytosis pathways, we show that the translocation of PEG-BB across the epithelium is driven by bottlebrush architecture enhanced endocytosis. Our results demonstrate that large, wormlike bottlebrush PEG polymers, if properly designed, can be used as a novel carrier for pulmonary and mucosal drug delivery. Table of Contents O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/580508v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@191f141org.highwire.dtl.DTLVardef@7600f4org.highwire.dtl.DTLVardef@138c9c6org.highwire.dtl.DTLVardef@1471c22_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗
bioRxiv2024

A Germinal Center Checkpoint of AIRE in B Cells LimitsAntibody Diversification

In response to antigens, B cells undergo antibody diversification, including affinity maturation and class switching, mediated by activation-induced cytidine deaminase (AID) in secondary lymphoid organs, but uncontrolled AID activity can precipitate autoimmunity and cancer. The regulation of antibody diversification is of fundamental importance, though the mechanisms underlying these pathways are not well understood. We found that autoimmune regulator (AIRE), the molecule essential for T cell tolerance, is expressed in germinal center (GC) B cells in a CD40-dependent manner, interacts with AID and negatively regulates antibody affinity maturation and class switching by inhibiting AID function. AIRE deficiency in B cells caused altered antibody repertoire, increased somatic hypermutations, elevated autoantibodies to T helper 17 effector cytokines and defective control of skin Candida albicans. These results define a GC B cell checkpoint of humoral immunity and illuminate new approaches of generating high-affinity neutralizing antibodies for immunotherapy.

immunology↗
bioRxiv2023

Mantis: high-throughput 4D imaging and analysis of the molecular and physical architecture of cells

High-throughput dynamic imaging of cells and organelles is essential for understanding complex cellular responses. We report Mantis, a high-throughput 4D microscope that integrates two complementary, gentle, live-cell imaging technologies: remote-refocus label-free microscopy and oblique light-sheet fluorescence microscopy. Additionally, we report shrimPy, an open-source software for high-throughput imaging, deconvolution, and single-cell phenotyping of 4D data. Using Mantis and shrimPy, we achieved high-content correlative imaging of molecular dynamics and the physical architecture of 20 cell lines every 15 minutes over 7.5 hours. This platform also facilitated detailed measurements of the impacts of viral infection on the architecture of host cells and host proteins. The Mantis platform can enable high-throughput profiling of intracellular dynamics, long-term imaging and analysis of cellular responses to perturbations, and live-cell optical screens to dissect gene regulatory networks. Significance StatementUnderstanding the dynamics and interactions of cellular components is crucial for biological research and drug discovery. Current dynamic fluorescence microscopy methods can only image a few fluorescent labels, providing a limited view of these complex processes. We developed Mantis, a high-throughput 3D microscope that maps interactions among components of dynamic cell systems. Mantis combines light-sheet fluorescence imaging of multiple fluorophores with quantitative label-free microscopy and is complemented by shrimPy, our open-source software for high-throughput data acquisition and high-performance analysis. Mantis enabled simultaneous 3D time-lapse imaging of 20 cell lines and quantitative analysis of responses to perturbations like viral infection at single-cell resolution. This approach can accelerate the analysis of cellular dynamics and image-based drug discovery.

cell biology↗
bioRxiv2023

Geographic Distribution of a Missense Mutation in the KRT38 Gene and Its Association with Heat Tolerance in Chinese Indigenous Cattle Breeds

ContextChina has a vast area across many temperature zones and a variety of cattle breeds. These cattle resources are ideal models to research their adaptability to the environment. The KRT38 gene is an acidic protein, and its coding product can be used as a component of hair production. AimsThe objective of this study was to investigate the diversity of the KRT38 gene in Chinese local cattle and the association of different genotypes with mean temperature (T), relative humidity (RH) and temperature humidity index (THI). MethodsA missense mutation g.41650738 A > G in the KRT38 gene was screened from the database of bovine genomic variation (BGVD), was genotyped in a total of 246 samples from 15 local cattle breeds in China by PCR amplification and sequencing. Finally, the correlation between the locus and the three climatic factors was analysed. Key resultsWe successfully obtained the frequency of this SNP in three groups of cattle in northern, central and southern China. The frequency of allele A gradually declined from north to south, while the frequency of allele G showed the opposite trend with a clear geographic distribution. ConclusionsOur results indicate that KRT38 variation in Chinese indigenous cattle might be linked to heat tolerance. ImplicationsOur analysis may support in finding out its importance as a genetic signal for heat tolerance in cattle reproduction and genetics.

genomics↗
bioRxiv2023

CELL-E 2: Translating Proteins to Pictures and Back with a Bidirectional Text-to-Image Transformer

We present CELL-E 2, a novel bidirectional transformer that can generate images depicting protein subcellular localization from the amino acid sequences (and vice versa). Protein localization is a challenging problem that requires integrating sequence and image information, which most existing methods ignore. CELL-E 2 extends the work of CELL-E, not only capturing the spatial complexity of protein localization and produce probability estimates of localization atop a nucleus image, but also being able to generate sequences from images, enabling de novo protein design. We train and finetune CELL-E 2 on two large-scale datasets of human proteins. We also demonstrate how to use CELL-E 2 to create hundreds of novel nuclear localization signals (NLS). Results and interactive demos are featured at https://bohuanglab.github.io/CELL-E_2/.

bioinformatics↗
bioRxiv2023

NanoBERTa-ASP: Predicting Nanobody Binding Epitopes Based on a Pretrained RoBERTa Model

Nanobodies, also known as VHH or single-domain antibodies, are a unique class of antibodies that consist only of heavy chains and lack light chains. Nanobodies possess the advantages of both small molecule drugs and conventional antibodies, making them a promising class of therapeutic biopharmaceuticals. Studying the characteristics of nanobody sequences can aid the development and design of nanobodies. An important challenge in this field is accurately predicting the binding sites between nanobodies and antigens. The binding site is the region where the nanobody interacts with the antigen. The precise prediction of these binding sites is crucial for comprehending the interaction mechanism between the nanobody and the antigen, facilitating the design of effective nanobodies, as well as gaining valuable insights into the properties of nanobodies. Nanobodies typically have smaller and more flexible binding sites than traditional antibodies, however predictive models trained on traditional antibodies may not be suitable for nanobodies. Moreover, the limited availability of antibodyderived nanobody datasets for deep learning poses challenges in constructing highly accurate predictive models that can generalize well to unseen data. To address these challenges, we propose a novel nanobody prediction model, named NanoBERTa-ASP (Antibody Specificity Prediction), which is specifically designed for predicting nanobody-antigen binding sites. The model adopts a training strategy more suitable for nanobodies by leveraging an advanced natural language processing (NLP) model called BERT (Bidirectional Encoder Representations from Transformers). The model also utilizes a masked language modeling approach to learn the contextual information of the nanobody sequence and predict its binding site. The results obtained from training NanoBERTa-ASP on nanobodies highlight its exceptional performance in Precision and AUC, underscoring its proficiency in capturing sequence information specific to nanobodies and accurately predicting their binding sites. Furthermore, our model can provide insights into the interaction mechanisms between nanobodies and antigens, contributing to a better understanding of nanobodies, as well as accelerating the development and design of nanobodies with potential therapeutic applications. To the best of our knowledge, NanoBERTa-ASP is the first nanobody language model that achieved high accuracy in predicting the binding sites. Github repositoryhttps://github.com/WangLabforComputationalBiology/NanoBERTa-ASP

bioinformatics↗
bioRxiv2023

HybriSeq: Probe-based Device-free Single-cell RNA Profiling

We have developed the HybriSeq method for single-cell RNA profiling, which utilizes in situ hybridization of multiple probes for targeted transcripts, followed by split-pool barcoding and sequencing analysis of the probes. We have shown that HybriSeq can achieve high sensitivity for RNA detection with multiple probes and profile entire transcripts without an end bias. The utility of HybriSeq is demonstrated in characterizing cell-to-cell heterogeneities of a panel of 196 genes in peripheral blood mononuclear cells and the detection of missed annotations of transcripts.

bioengineering↗
bioRxiv2023

Nanotope: A Graph Neural Network-Based Model for Nanobody paratope prediction

Nanobodies are artificial antibodies derived from the immune system of camelid species, obtained through artificial processing and isolation of antigen-binding proteins. Their small molecular size and high specificity endow nanobodies with extensive potential applications in various fields. However, determining nanobody paratopes through experimental methods is both costly and time-consuming, while traditional computational approaches often lack sufficient accuracy. To enhance the prediction accuracy, we propose Nanotope, a structurebased model capable of efficiently and accurately predicting paratopes, utilizing graph neural networks and an antibody pretrained language model. Our approach primarily leverages sequence features obtained from the AntiBERTy antibody pretrained language model and three-dimensional spatial structure features of nanobodies as inputs. Employing one-dimensional convolution, EGConv graph convolution, and GATConv convolution, we predict the probability of nanobody paratopes with a much higher accuracy. Our method significantly improves the prediction of nanobody paratopes and requires only nanobody sequences and structural information, without the need for additional antigen information. Source code is freely available at https://github.com/WangLabforComputationalBiology/Nanotope

bioinformatics↗
bioRxiv2023

NanoLAS: a Comprehensive Nanobody Database with Data Integration, Consolidation, and Application

Nanobodies, a unique subclass of antibodies first discovered in camelid animals, are composed solely of a single heavy chains variable region (VHH). Their significantly reduced molecular weight, in comparison to conventional antibodies, confers numerous advantages in the treatment of various diseases. As research and applications involving nanobodies expand, the quantity of identified nanobodies is also rapidly growing. However, the existing antibody databases are deficient in type and coverage, failing to satisfy the comprehensive needs of researchers and thus, impeding progress in nanobody research. In response to this, we have amalgamated data from multiple sources to successfully assemble a new and comprehensive nanobody database. This database has currently included the latest nanobody data, provides researchers with an excellent search and data display interface, thus facilitating the progression of nanobody research and their application in disease treatment. In summary, the newly constructed Nanobody Library and Archive System (NanoLAS) may significantly enhance the retrieval efficiency and application potential of nanobodies. We envision that NanoLAS will serve as an accessible, robust, and efficient tool for nanobody research and development, propelling advancements in the field of biomedicine. Database URLhttps://www.nanolas.cloud

bioinformatics↗
bioRxiv2023

De novo designed Hsp70 activator dissolves intracellular condensates

Protein quality control (PQC) is carried out in part by the chaperone Hsp70, in concert with adapters of the J-domain protein (JDP) family. The JDPs, also called Hsp40s, are thought to recruit Hsp70 into complexes with specific client proteins. However, the molecular principles regulating this process are not well understood. We describe the de novo design of a set of Hsp70 binding proteins that either inhibited or stimulated Hsp70s ATPase activity; a stimulating design promoted the refolding of denatured luciferase in vitro, similar to native JDPs. Targeting of this design to intracellular condensates resulted in their nearly complete dissolution. The designs inform our understanding of chaperone structure-function relationships and provide a general and modular way to target PQC systems to condensates and other cellular targets.

biochemistry↗
bioRxiv2023

Designed Endocytosis-Triggering Proteins mediate Targeted Degradation and amplify signaling

Endocytosis and lysosomal trafficking of cell surface receptors can be triggered by interaction with endogenous ligands. Therapeutic approaches such as LYTAC1,2 and KineTAC3, have taken advantage of this to target specific proteins for degradation by fusing modified native ligands to target binding proteins. While powerful, these approaches can be limited by possible competition with the endogenous ligand(s), the requirement in some cases for chemical modification that limits genetic encodability and can complicate manufacturing, and more generally, there may not be natural ligands which stimulate endocytosis through a given receptor. Here we describe general protein design approaches for designing endocytosis triggering binding proteins (EndoTags) that overcome these challenges. We present EndoTags for the IGF-2R, ASGPR, Sortillin, and Transferrin receptors, and show that fusing these tags to proteins which bind to soluble or transmembrane protein leads to lysosomal trafficking and target degradation; as these receptors have different tissue distributions, the different EndoTags could enable targeting of degradation to different tissues. The modularity and genetic encodability of EndoTags enables AND gate control for higher specificity targeted degradation, and the localized secretion of degraders from engineered cells. The tunability and modularity of our genetically encodable EndoTags should contribute to deciphering the relationship between receptor engagement and cellular trafficking, and they have considerable therapeutic potential as targeted degradation inducers, signaling activators for endocytosis-dependent pathways, and cellular uptake inducers for targeted antibody drug and RNA conjugates.

synthetic biology↗
bioRxiv2023

Iterative In Silico Screening for Optimizing Stable Conformation of Anti-SARS-CoV-2 Nanobodies

Nanobodies (Nbs or VHHs) are single-domain antibodies (sdAbs) derived from camelid heavy-chain antibodies. The variable region of these nanobodies has special and unique characteristics, such as small size, good tissue penetration, and cost-effective production, making nanobodies a good candidate for the diagnosis and treatment of viruses. Identifying effective nanobodies against the COVID-19 would help us defeat this dangerous virus or other unknown variants in future. Herein, we introduce an in silico screening strategy for optimizing stable conformation of anti-SARS-CoV-2 nanobodies. Firstly, various complexes containing nanobodies were downloaded from the RCSB database, which were identified from immunized llamas. The primary docking between nanobodies and the SARS-CoV-2 spike protein receptor-binding domain was performed through ClusPro program, with the manually screening that leaving the reasonable conformation to the next step. Then, the binding distances of atoms between the antigen-antibody interfaces were measured through the NeighborSearch algorithm. Finally, filtered nanobodies were acquired according to HADDOCK scores through HADDOCK docking the COVID spike protein with nanobodies under restrictions of calculated molecular distance between active residues and antigenic epitopes less than 4.5 [A]. In this way, those nanobodies which with more reasonable conformation and with stronger neutralizing efficacy were acquired. To validate the efficacy ranking of the nanobodies we obtained, we calculated the binding affinities ({Delta}G) and dissociation constants (Kd) of all screened nanobodies using the PRODIGY web tool, and predicted the stability changes induced by all possible point mutations in nanobodies using the MAESTROWeb server. Furthermore, we examined the performance of the relationship between nanobodies ranking and their number of mutation-sensitive sites (Spearman correlation > 0.68), the results revealed a robust correlation, indicating that the superior nanobodies identified through our screening process exhibited fewer mutation hotspots and higher stability. This correlation analysis demonstrates the validity of our screening criteria, underscoring the suitability of these nanobodies for future development and practical implementation. In conclusion, this three-step screening strategy iteratively in silico greatly improved the accuracy of screening desired nanobodies compared to using only ClusPro docking or default HADDOCK docking settings. It provides new ideas for the screening of novel antibodies and computer-aided screening methods.

bioinformatics↗
bioRxiv2023

Biodecomposing Spirulina platensis by a de novo designed Bacillus subtilis-based method to develop a medium for the high cell-density cultivation of Escherichia coli in batch mode

High cell-density cultivation (HCDC) is fundamental to basic research and industrial applications, especially in batch mode. However, limited media are available for batch culture of HCDC, because the media for batch culture must contain extremely sufficient nutrients on the one hand and few or even no substrates to generate detrimental metabolite on the other hand to attain HCDC. Spirulina platensis (SP), a new media material, is considered ideal for the development of such media. Here, we develop a biolysis method for SP degradation based on the cultivation supernatant of Bacillus subtilis and extensively demonstrate its higher degradation (indicated by the production of more small peptides and free amino acids) and cultivation effectiveness with three other methods. Based on its SP hydrolysates, a modified SP-based broth (MSP) is then formulated. Tests on Escherichia coli K-12 show that MSP achieves HCDC with several benefits: (i) its maximum optical density at 600 nm is [~]16.67, significantly higher than that of Luria-Bertani (LB) broth (only [~]6.30); (ii) MSP requires only 36 h to reach peak growth, much faster than that of LB (48 h); (iii) its maximum growth (1.12 {+/-} 0.01 h-1) is significantly higher than that of LB (0.20 {+/-} 0.00 h-1); (v) MSP initiates growth immediately after inoculation (lag time <0), comparable to LB; (iv) the number of viable cells in MSP is high ([~]2.16 x 1011 ml-1), [~]10.19 times the amount in LB. Consequently, we envision MSP will become the first choice for E. coli HCDC batch culture in the future. ImportanceSo far, it is the first time to develop a high-efficiency method for transforming Spirulina platensis (SP) into medium ingredients. Based on its SP hydrolysates, a high cell-density cultivation (HCDC) medium for the batch culture of Escherichia coli is formulated for the first time, which is greatly beneficial for both basic research and industrial applications. In addition to HCDC, the SP hydrolysates can be extended to a wide range of applications, due to their rich nutrient content. Besides, this study demonstrates for the first time that SP is an ideal material to develop HCDC media. Furthermore, this study demonstrates that medium development and modification for batch culture can attain HCDC, without the development of new culture technologies. Therefore, this study highlights the importance of the rebirth of medium development and modification and supports the shift from developing new culture technologies to medium development and modification for HCDC in batch mode.

microbiology↗
bioRxiv2023

Modeling kidney development, disease, and plasticity with clonal expandable nephron progenitor cells and nephron organoids

Nephron progenitor cells (NPCs) self-renew and differentiate into nephrons, the functional units of the kidney. Here we report manipulation of p38 and YAP activity creates a synthetic niche that allows the long-term clonal expansion of primary mouse and human NPCs, and induced NPCs (iNPCs) from human pluripotent stem cells. Cultured iNPCs resemble closely primary human NPCs, generating nephron organoids with abundant distal convoluted tubule cells, which are not observed in published kidney organoids. The synthetic niche reprograms differentiated nephron cells into NPC state, recapitulating the plasticity of developing nephron in vivo. Scalability and ease of genome-editing in the cultured NPCs allow for genome-wide CRISPR screening, identi-fying novel genes associated with kidney development and disease. A rapid, efficient, and scala-ble organoid model for polycystic kidney disease was derived directly from genome-edited NPCs, and validated in drug screen. These technological platforms have broad applications to kidney development, disease, plasticity, and regeneration.

developmental biology↗
bioRxiv2023

Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening

The quest for more effective virtual screening algorithms is hindered by the scarcity of training data, calling for innovative approaches. This study presents the first use of experimental electron density (ED) data for improving active compound enrichment in virtual screening, supported by EDs ability to reflect the time-averaged behavior of ligands and solvents in the binding pocket. Experimental ED-based grid matching score (ExptGMS) was developed to score compounds by measuring the degree of matching between their binding conformations and a series of multi-resolution experimental ED grids. The efficiency of ExptGMS was validated using both in-silico tests with the Directory of Useful Decoys-Enhanced dataset and wet-lab tests on Covid-19 3CLpro-inhibitors. ExptGMS improved the active compound enrichment in top-ranked molecules by approximately 20%. Furthermore, ExptGMS helped identify four new and active inhibitors of 3CLpro, with the top showing an IC50 value of 1.9 {micro}M. To facilitate the use of ExptGMS, we developed an online database containing experimental ED grids for over 17,000 proteins.

bioinformatics↗
bioRxiv2023

A deep population reference panel of tandem repeat variation

Tandem repeats (TRs) represent one of the largest sources of genetic variation in humans and are implicated in a range of phenotypes. Here we present a deep characterization of TR variation based on high coverage whole genome sequencing from 3,550 diverse individuals from the 1000 Genomes Project and H3Africa cohorts. We develop a method, EnsembleTR, to integrate genotypes from four separate methods resulting in high-quality genotypes at more than 1.7 million TR loci. Our catalog reveals novel sequence features influencing TR heterozygosity, identifies population-specific trinucleotide expansions, and finds hundreds of novel eQTL signals. Finally, we generate a phased haplotype panel which can be used to impute most TRs from nearby single nucleotide polymorphisms (SNPs) with high accuracy. Overall, the TR genotypes and reference haplotype panel generated here will serve as valuable resources for future genome-wide and population-wide studies of TRs and their role in human phenotypes.

genomics↗