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Biology subjects

Yao, H.

Publications and source records attributed to Yao, H..

At least 55 records · Page 3Linked to original sources

De Novo Negatively Charged Binders Targeting MMLVRT Nucleic Acid Binding Sites Overcome Stability-Activity Trade-offs

The limited thermostability and storage-induced inactivation of Moloney murine leukemia virus reverse transcriptase (MMLV RT) have constrained its applications. In this study, a high-stability mutant, MMLV RT-SV, was generated through a multi-site mutagenesis strategy targeting the nucleic acid-binding pocket. Through de novo protein design, three highly negatively charged binders with affinities of 45 nM, 362 nM, and 829 nM were developed to specifically target the positively charged nucleic acid-binding region on the surface of MMLV RT-SV. Experimental results demonstrated that these binders formed complexes with the enzyme via electrostatic interaction, significantly enhancing the thermostability and long-term storage stability of MMLV RT-SV while not affecting its RNA- dependent DNA polymerase function. This work pioneers the rational design of negatively charged binders targeting strongly positively charged nucleic acid-binding sites, overcoming the traditional stability-activity trade-off inherent in site-directed mutagenesis and directed evolution. The proposed strategy not only provides an innovative solution to address the thermal sensitivity and storage instability of reverse transcriptase but also establishes a novel paradigm for De Novo-based precision engineering of enzyme functions, demonstrating significant potential in molecular diagnostics, gene editing, and related fields.

bioengineering↗

Hydroxychloroquine-functionalized Ionizable Lipids Mitigate Inflammatory Responses in mRNA Therapeutics

Lipid nanoparticle (LNP)-based mRNA therapeutics, highlighted by the success of SARS-CoV-2 vaccines, face challenges due to inflammation caused by ionizable lipids. These ionizable lipids can activate the immune system, particularly when co-delivered with nucleic acids, leading to undesirable inflammatory responses. We introduce a novel class of anti-inflammatory ionizable lipids functionalized with hydroxychloroquine (HCQ), which suppresses both lipid-induced and nucleic acid-induced immune activation. These HCQ-functionalized LNPs (HL LNPs) exhibit reduced proinflammatory responses while maintaining efficient mRNA delivery. Structural and physicochemical analyses revealed that HCQ-functionalization results in a distinct particle structure with significantly improved stability. The efficacy of HL LNPs was demonstrated across various therapeutic contexts, including a prophylactic vaccination model against varicella-zoster virus (VZV) and CRISPR-Cas9 gene editing targeting PCSK9. Notably, HL LNPs showed robust mRNA expression after repeated administration, addressing concerns of inflammation and ensuring sustained therapeutic effects. These findings highlight the potential of HCQ-functionalized LNPs in expanding the safe use of mRNA therapeutics, particularly for applications requiring repeated dosing and in scenarios where inflammation-induced side effects must be minimized.

bioengineering↗

Cryo-ET of IgG bivalent binding on SARS-CoV-2 provides structural basis for antibody avidity

The bivalent nature of IgG enhances its neutralization potency against enveloped viruses; however, on-virion structural details of IgG bivalent binding with antigens remain elusive. Here we used cryo-ET to investigate how two potent IgGs P17 and S309 interact with S-trimers on the SARS-CoV-2 surface. We found that these antibodies exploit the mobility of S-trimers to form diverse bivalent binding patterns. P17 stabilizes S-trimers in a one-RBD-up conformation and gathers S-trimer into linear multimers within minutes, whereas S309 primarily forms circular S-trimer assemblies that extend into lattice-like structures. Additionally, both IgGs can facilitate inter-virion coupling through bivalent binding of opposing S-trimers. These findings provide a structural basis for understanding IgG avidity and offer insights for antibody engineering and vaccine design.

biophysics↗

Capturing R-loops at base-pair resolution unveils clustered R-loops regulate gene expression in a number-dependent manner

R-loops are prevalent triplex nucleic strands found across various organisms, involved in numerous biological processes. However, the physiological and pathological functions of R-loops remain largely unknown due to a lack of effective and high-resolution detection methods. Here, using nuclease P1, T5 exonuclease, and lambda exonuclease mediated digestion of ssRNA, ssDNA, and dsDNA while preserving RNA:DNA hybrid, we report a method named R-loop identification assisted by nuclease and high-throughput sequencing (RIAN-seq) for genome-wide mapping of R-loops at base-pair resolution. RIAN-seq represents ultra-accuracy in position and size of R-loops and identifies an order of magnitude more R-loops than current methods. Notably, we find the majority of R-loops ranging from 60 bp to 130 bp and reveal previously unresolvable patterns of R-loops aggerated in clusters across the genome. Clustered R-loops at gene promoters recruit zinc finger transcription factors (VEZF1 and SP5) to promote transcription. The number of R-loops within a cluster positively correlates with the diversity of bound transcription factors. Furthermore, clustered R-loops are less susceptible to transcription perturbation as the number of R-loops within clusters increases. Overall, we demonstrate the ability to identify R-loops at unprecedented resolution and facilitate investigating the mechanisms of clustered R-loops in gene regulation in diverse biological processes.

molecular biology↗

A comprehensive comparison on clustering methods for multi-slide spatially resolved transcriptomics data analysis

Spatial transcriptomics (ST) data, by providing spatial information, enables simultaneous analysis of gene expression distributions and their spatial patterns within tissue. Clustering or spatial domain detection represents an essential methodology for ST data, facilitating the exploration of spatial organizations with shared gene expression or histological characteristics. Traditionally, clustering algorithms for ST have focused on individual tissue sections. However, the emergence of numerous contiguous tissue sections derived from the same or similar tissue specimens within or across individuals has led to the development of multi-slide clustering methods. In this study, we assess seven single-slide and three multi-slide clustering methods on two simulated datasets and three real datasets. Additionally, we investigate the effectiveness of pre-processing techniques, including spatial coordinate alignment (for example, PASTE) and gene expression batch effect removal (for example, Harmony), on clustering performance. Our study provides a comprehensive comparison of clustering methods for multi-slide ST data, serving as a practical guide for method selection in various scenarios.

bioinformatics↗

Variational Autoencoder-based Model Improves Polygenic Prediction in Blood Cell Traits

Genetic prediction of complex traits, enabled by large-scale genomic studies, has created new measures to understand individual genetic predisposition. Polygenic Risk Scores (PRS) offer a way to aggregate information across the genome, enabling personalized risk prediction for complex traits and diseases. However, conventional PRS calculation methods that rely on linear models are limited in their ability to capture complex patterns and interaction effects in high-dimensional genomic data. In this study, we seek to improve the predictive power of PRS through applying advanced deep learning techniques. We show that the Variational AutoEncoder-based model for PRS construction (VAE-PRS) outperforms currently state-of-the-art methods for biobank-level data in 14 out of 16 blood cell traits, while being computationally efficient. Through comprehensive experiments, we found that the VAE-PRS model offers the ability to capture interaction effects in high-dimensional data and shows robust performance across different pre-screened variant sets. Furthermore, VAE-PRS is easily interpretable via assessing the contribution of each individual marker to the final prediction score through the SHapley Additive exPlanations (SHAP) method, providing potential new insights in identifying trait-associated genetic variants. In summary, VAE-PRS presents a novel measure to genetic risk prediction by harnessing the power of deep learning methods, which could further facilitate the development of personalized medicine and genetic research.

bioinformatics↗

Engineered biological neural networks as basic logic operators

We present an in vitro neuronal network with controlled topology capable of performing basic Boolean computations, such as NAND and OR. Neurons cultured within polydimethylsiloxane (PDMS) microstructures on high-density microelectrode arrays (HD-MEAs) enable precise interaction through extracellular voltage stimulation and spiking activity recording. The architecture of our system allows for creating non-linear functions with two inputs and one output. Additionally, we analyze various encoding schemes, comparing the limitations of rate coding with the potential advantages of spike-timing-based coding strategies. This work contributes to the advancement of hybrid intelligence and biocomputing by offering insights into neural information encoding and decoding with the potential to create fully biological computational systems.

neuroscience↗

Structure-Based Design of Covalent Nanobody Binders for a Thermostable Green Fluorescence Protein

Green fluorescence protein (GFP) lights up almost every aspects of life sciences. An ultra thermostable GFP (TGP), engineered from a coral GFP, offers potential advantages over traditional jellyfish-derived GFP due to its high stability. However, owing to its later discovery, TGP lacks the extensive toolsets available for GFP, such as heavy chain-only antibody binders known as nanobodies. In this study, we have structurally characterized TGP in complex with Sb92, a synthetic nanobody identified from a previous in vitro screening, revealing its precise three-dimensional epitope. This structural insight, alongside the previously characterized Sb44-TGP complex, have allowed us to rationally design disulfide bonds between antigen and antibody for tighter interactions. Using biochemical analyses, we identify two bridged complexes (TGP A18C-Sb44 V100C, TGP E118C-Sb92 S57C), with the TGP-Sb92 disulfide pair showing high resistance to reducing agents. Our study expands the toolkit available for TGP and should encourage its wider applications.

biochemistry↗

C-Reactive Protein Drives Potent Clearance of Blood Bacteria in the Liver by Activating the Complement System

Plasma C-reactive protein (CRP) is widely used as a biomarker for bacterial infections due to its massive induction during infections, however, the precise function of CRP in bacterial infections remains undefined. Here we show that CRP enables Kupffer cells (liver macrophages) to capture and eliminate a wide range of encapsulated bacteria from the bloodstream of mice and thereby provides rapid and effective immunity. Mechanistically, CRP binds to the structurally diverse capsular polysaccharides of major Gram-positive and -negative pathogens, and thereby activates complement C3 at the bacterial surface. The C3-opsonized microbes are in turn captured by C3 receptors on the surface of Kupffer cells, and eliminated in the liver sinusoids. Since CRP principally shares the functional features of antibodies in pathogen recognition/execution, CRP-based defense combines the broad spectrum of the innate immunity with the swiftness, potency and specificity of the adaptive immunity, which helps explain massive rise of CRP during systemic bacterial infections.

immunology↗

MAST-Decon: Smooth Cell-type Deconvolution Method for Spatial Transcriptomics Data

AO_SCPLOWBSTRACTC_SCPLOWSpatial transcriptomics (ST) technologies have gained increasing popularity due to their ability to provide positional context of gene expressions in a tissue. One major limitation of current commercially available ST methods such as the 10X Genomics Visium platform is the lack of single cell resolution. Cell type deconvolution for ST data is critical in order to fully reveal underlying biological mechanisms. Existing ST data deconvolution methods share two common limitations: first, few of them utilize spatial neighborhood information. Existing methods such as RCTD and SPOTlight intrinsically treat each spatial spot as independent of neighboring spots, although we anticipate nearby spots to share similar cell type compositions based on clinical evidence of tissue structures. Such limitation could be amplified when sequencing depths at single spots are relatively low so that borrowing information from neighboring spots is necessary in order to obtain reliable deconvolution results. Second, although Visium data provide us with a histological image which could add additional information regarding spot heterogeneity, most existing methods do not utilize this H&E image. To solve these two limitations, we developed Multiscale Adaptive ST Deconvolution (MAST-Decon), a smooth deconvolution method for ST data. MAST-Decon uses a weighted likelihood approach and incorporates both gene expression data, spatial neighborhood information and H&E image features by constructing different kernel functions to obtain a smooth deconvolution result. We showcased the strength of MAST-Decon through simulations based on real data, including a single-cell dataset of mouse brain primary visual cortex, and real-world Visium datasets to demonstrate its robust and superior performance compared with other state-of-the-art methods.

genomics↗

Phosphate starvation stops bacteria digesting algal fucan that sequesters carbon

Algae provide a solar powered pathway to capture and sequester carbon by injecting stable fucan made from carbon dioxide into the ocean 1-4. Stability of the pathway is at odds with the presence of marine bacteria with genes of enzymes that can digest fucan and release the carbon dioxide 5. Biochemical explanations for stable fucan remain hypothetical 6. We assembled a biological carbon cycle model and found phosphate limitation enhanced fucan synthesis by algae, stopped digestion by bacteria and thereby stabilized the fucan carbon sequestration pathway. Marine microalgae Glossomastix sp. PLY432 increased synthesis of fucan, a part of its extracellular matrix, under nutrient-growth limiting conditions. Rate and extent of fucan digestion by a marine, isolated bacterium of the Akkermansiaceae family decreased with decreasing phosphate concentration. Phosphate starvation restricted bacterial growth rate, biomass yield and in turn increased the amount of stable fucan. Phosphate is universally required for growth but rare relative to glycan carbon in photosynthesis-derived ecosystems. The fact that phosphate is required for replication, transcription and translation explains why bacteria can digest gigatons of laminarin with a few enzymes, but not fucan during nutrient limited algal blooms. We conclude phosphate starvation constrains the ability of bacteria to digest fucan, which evolves to maintain stability around algal cells and consequentially also to keep carbon dioxide in the ocean.

microbiology↗

CTCF mutation at R567 causes developmental disorders via 3D genome rearrangement and abnormal neurodevelopment

The three-dimensional genome structure organized by CTCF is required for development. Clinically identified mutations in CTCF have been linked to adverse developmental outcomes. Nevertheless, the underlying mechanism remains elusive. In this investigation, we explored the regulatory roles of a clinically relevant R567W point mutation, located within the 11th zinc finger of CTCF, by introducing this mutation into both murine models and human embryonic stem cell-derived cortical organoid models. Mice with homozygous CTCFR567W mutation exhibited growth impediments, resulting in postnatal mortality, and deviations in brain, heart, and lung development at the pathological and single- cell transcriptome levels. This mutation induced premature stem-like cell exhaustion, accelerated the maturation of GABAergic neurons, and disrupted neurodevelopmental and synaptic pathways. Additionally, it specifically hindered CTCF binding to peripheral motifs upstream to the core consensus site, causing alterations in local chromatin structure and gene expression, particularly at the clustered protocadherin locus. Comparative analysis using human cortical organoids mirrored the consequences induced by this mutation. In summary, this study elucidates the influence of the CTCFR567W mutation on human neurodevelopmental disorders, paving the way for potential therapeutic interventions.

molecular biology↗

A torpor-like state (TLS) in mice slows blood epigenetic aging and prolongs healthspan

Torpor and hibernation are extreme physiological adaptations of homeotherms associated with pro-longevity effects. Yet the underlying mechanisms of how torpor affects aging, and whether hypothermic and hypometabolic states can be induced to slow aging and increase health span, remain unknown. We demonstrate that the activity of a spatially defined neuronal population in the avMLPA, which has previously been identified as a torpor-regulating brain region, is sufficient to induce a torpor like state (TLS) in mice. Prolonged induction of TLS slows epigenetic aging across multiple tissues and improves health span. We isolate the effects of decreased metabolic rate, long-term caloric restriction, and decreased core body temperature (Tb) on blood epigenetic aging and find that the pro-longevity effect of torpor-like states is mediated by decreased Tb. Taken together, our findings provide novel mechanistic insight into the pro-longevity effects of torpor and hibernation and support the growing body of evidence that Tb is an important mediator of aging processes.

physiology↗

LncRNA-Snhg3 Aggravates Hepatic Steatosis by Regulating PPARγ via SND1/H3K27me3

LncRNAs are involved in modulating the individual risk and the severity of progression in metabolic dysfunction-associated fatty liver disease (MASLD), but their precise roles remain largely unknown. This study aimed to investigate the role of lncRNA Snhg3 in the development and progression of MASLD, along with the underlying mechanisms. The result showed that Snhg3 was significantly downregulated in the liver of high-fat diet-induced obesity (DIO) mice. Notably, palmitic acid promoted the expression of Snhg3 and overexpression of Snhg3 increased lipid accumulation in primary hepatocytes. Furthermore, hepatocyte-specific Snhg3 deficiency decreased body and liver weight, alleviated hepatic steatosis and promoted hepatic fatty acid metabolism in DIO mice, whereas overexpression induced the opposite effect. Mechanistically, Snhg3 promoted the expression, stability and nuclear localization of SND1 protein via interacting with SND1, thereby inducing K63-linked ubiquitination modification of SND1. Moreover, Snhg3 decreased the H3K27me3 level and induced SND1-mediated chromatin loose remodeling, thus reducing H3K27me3 enrichment at the Ppar{gamma} promoter and enhancing Ppar{gamma} expression. The administration of PPAR{gamma} antagonist T0070907 improved Snhg3-aggravated hepatic steatosis. Our study revealed a new signaling pathway, Snhg3/SND1/H3K27me3/PPAR{gamma}, responsible for MASLD and indicates that lncRNA-mediated epigenetic modification has a crucial role in the pathology of MASLD.

molecular biology↗

Single-nucleus multiomics reveals the gene-regulatory networks underlying sex determination of murine primordial germ cells

Accurate specification of female and male germ cells during embryonic development is critical for sexual reproduction. Primordial germ cells (PGCs) are the bipotential precursors of mature gametes that commit to an oogenic or spermatogenic fate in response to sex-determining cues from the fetal gonad. The critical processes required for PGCs to integrate and respond to signals from the somatic environment in gonads are not understood. In this study, we developed the first single-nucleus multiomics map of chromatin accessibility and gene expression during murine PGC development in both XX and XY embryos. Profiling of cell-type specific transcriptomes and regions of open chromatin from the same cell captured the molecular signatures and gene networks underlying PGC sex determination. Joint RNA and ATAC data for single PGCs resolved previously unreported PGC subpopulations and cataloged a multimodal reference atlas of differentiating PGC clusters. We discovered that regulatory element accessibility precedes gene expression during PGC development, suggesting that changes in chromatin accessibility may prime PGC lineage commitment prior to differentiation. Similarly, we found that sexual dimorphism in chromatin accessibility and gene expression increased temporally in PGCs. Combining single-nucleus sequencing data, we computationally mapped the cohort of transcription factors that regulate the expression of sexually dimorphic genes in PGCs. For example, the gene regulatory networks of XX PGCs are enriched for the transcription factors, TFAP2c, TCFL5, GATA2, MGA, NR6A1, TBX4, and ZFX. Sex-specific enrichment of the forkhead-box and POU6 families of transcription factors was also observed in XY PGCs. Finally, we determined the temporal expression patterns of WNT, BMP, and RA signaling during PGC sex determination, and our discovery analyses identified potentially new cell communication pathways between supporting cells and PGCs. Our results illustrate the diversity of factors involved in programming PGCs towards a sex-specific fate.

developmental biology↗

Retrotransposon-mediated variation of a chitin synthase gene confers insect resistance to Bacillus thuringiensis Vip3Aa toxin

Bacillus thuringiensis (Bt) crops expressing Vip3Aa are highly efficacious in controlling major lepidopteran pests and delaying evolution of pest resistance. Although practical resistance to Vip3Aa in the field has not been reported, to proactively manage the pest resistance, there is an urgent need to better understand the genetic basis of resistance to Vip3Aa. This is particularly important for the fall armyworm (Spodoptera frugiperda), one of the most destructive pests around the world, which has evolved practical resistance to Bt crystal (Cry) toxins. Here, a highly Vip3Aa-resistant (resistance ratio: 5,562-fold) strain of S. frugiperda was selected in the laboratory. Results from bulked segregant analysis, fine-scale mapping, and genetic linkage analysis indicate that a mutation in the midgut-specific chitin synthase gene, SfCHS2, is strongly associated with high-level resistance to Vip3Aa. The resistance is ascribed to the transcriptional variation caused by retrotransposon insertion. The same variation of SfCHS2 was also detected in a field population. Importantly, knockout of SfCHS2 via CRISPR/Cas9 in susceptible S. frugiperda confers its complete resistance (>10,000-fold) to Vip3Aa. Also, we demonstrate that knockout of CHS2 can result in complete resistance to Vip3Aa in additional lepidopteran species, suggesting a general role of this gene in Vip3Aa resistance among lepidopteran pests. These results reported here would contribute to monitor and management of pest resistance to Vip3Aa.

genetics↗

Multi-ContrastiveVAE disentangles perturbation effects in single cell images from optical pooled screens

Optical pooled screens (OPS) enable comprehensive and cost-effective interrogation of gene function by measuring microscopy images of millions of cells across thousands of perturbations. However, the analysis of OPS data still mainly relies on hand-crafted features, even though these are difficult to deploy across complex data sets. This is because most unsupervised feature extraction methods based on neural networks (such as auto-encoders) have difficulty isolating the effect of perturbations from the natural variations across cells and experimental batches. Here, we propose a contrastive analysis framework that can more effectively disentangle the phenotypes caused by perturbation from natural cell-cell heterogeneity present in an unperturbed cell population. We demonstrate this approach by analyzing a large data set of over 30 million cells imaged across more than 5, 000 genetic perturbations, showing that our method significantly outperforms traditional approaches in generating biologically-informative embeddings and mitigating technical artifacts. Furthermore, the interpretable part of our model distinguishes perturbations that generate novel phenotypes from the ones that only shift the distribution of existing phenotypes. Our approach can be readily applied to other small-molecule and genetic perturbation data sets with highly multiplexed images, enhancing the efficiency and precision in identifying and interpreting perturbation-specific phenotypic patterns, paving the way for deeper insights and discoveries in OPS analysis.

bioinformatics↗

Paternal genomic resources from the YanHuang cohort suggested a Weakly-Differentiated Multi-source Admixture model for the formation of Hans founding ancestral lineages

The large-scale human genome revolution and rapidly advanced statistical innovation have updated our understanding of the fine-scale and complex genetic structure, the entire landscape of genetic diversity and the evolutionary trajectories of spatiotemporally different ancients and ethnolinguistically diverse modern populations. Recent ancient DNA research provided a detailed and complex admixture picture of ancient Europeans but limited insights into East Asians as the few available genomes. Y-chromosome variations in the male-specific regions, served as molecular archaeological tool, have unique evolutionary features that can be utilized to reconstruct the origin and subsequent interaction of ancient East Asian paternal lineages. We launched the YanHuang cohort using our designed highest-resolution capture sequencing panel to explore the detailed evolutionary trajectory of the Han Chinese, one of the largest ethnic groups in the world. We reported one of the largest uniparental genomic resources and observed multiple founding paternal lineages dominant in ancient western Eurasian, Siberian and East Asian participating in the formation of the gene pool of the Han Chinese. We identified fine-scale paternal genetic structure correlated with different patterns of ancient population interaction and geographical mountain barriers (Qinling-Huaihe line and Nanling Mountains), suggesting isolation-enhanced and admixture-introduced genetic differentiation enhanced the complexity of the Han Chinese genomic diversity. We observed a strong direct correlation between the frequency of multiple founding lineages of the Han Chinese and the proportion of subsistence-related ancestry sources related to western pastoralists, Holocene Mongolian Plateau people and ancient East Asians, reflecting the ancient migration events contributed to our identified patterns of Chinese paternal genomic diversity. We finally provided one novel and the most plausible admixture-by-admixture model, the Weakly-Differentiated Multi-Source Admixture model, as the major genetic mechanism to illuminate our observed pattern of complex interactions of multiple ancestral sources and landscape of the Han Chinese paternal genetic diversity. Generally, we presented one large-scale uniparental genomic resource from the YanHuang cohort, portrayed one novel admixture formation model and presented the entire genomic landscape with multiple ancestral sources related to ancient herders, hunter-gatherers and farmers who participated in the ancestral formation of the Han Chinese.

evolutionary biology↗