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Yang, H.

Publications and source records attributed to Yang, H..

At least 307 records · Page 17Linked to original sources
bioRxiv2024

Development of deaminase-free T-to-S base editor and C-to-G base editor by engineered human uracil DNA glycosylase

DNA base editors could enable direct editing of adenine (A), cytosine (C), or guanine (G), but there is no base editor for direct thymine (T) editing currently. Here, by fusing Cas9 nickase (nCas9) with engineered human uracil DNA glycosylase (UNG) variants, we developed a deaminase-free glycosylase-based thymine base editor (gTBE) with the ability of direct T editing. By several rounds of UNG mutagenesis via rational screening, we demonstrated that gTBE with engineered UNG variants could achieve T editing efficiency by up to 81.5%. Furthermore, the gTBE exhibited high T-to-S (i.e., T-to-C or T-to-G) conversion ratio with up to 0.97 in cultured human cells. Using similar strategy, we developed a deaminase-free cytosine base editor (gCBE) facilitating specifically direct C editing by engineered UNG with mutations different from gTBE. Thus, we provide two novel base editors, gTBE and gCBE, with corresponding engineered UNG variants, broadening the targeting scope of base editors.

molecular biology↗
bioRxiv2023

Oblique Line Scan Illumination Enables Expansive, Accurate and Sensitive Single Protein Measurements in Solution and in Living Cells

Single-molecule localization microscopy (SMLM) techniques, such as single-molecule tracking (SMT), enable in situ measurements in cells from which data-rich metrics can be extracted. SMT has been successfully applied to a variety of biological questions and model systems, aiming to unravel the spatiotemporal regulation of molecular mechanisms that govern protein function, downstream pathway effects, and cellular function. While powerful, SMLM often suffers from low throughput and illumination inhomogeneity, along with microscope and user-induced technical biases. Due to technical limitations in scaling SMLM techniques, a tradeoff between spatiotemporal resolution and throughput has been made historically, restricting broad application of these technologies. Here we address these limitations using Oblique Line Scan (OLS), a robust single-objective light-sheet based illumination and detection modality that achieves nanoscale spatial resolution and sub-millisecond temporal resolution across a 250 x 190 m field of view. We demonstrate OLS-enabled SMT on Halo-Tagged proteins in living cells capturing protein motion up to 14 m2 /s. By exploiting the adaptability of the acquisition frame rate and the improved rejection of out of focus light, we extend the utility of OLS beyond cellular compartments with in-solution SMT (isSMT) for single-molecule measurement of ligand-protein interactions and disruption of protein-protein interactions (PPI). We illustrate the versatility of OLS by showcasing two-color SMT, STORM, and single molecule fluorescence recovery after photobleaching (FRAP). OLS expands the range of SMLM applications and paves the way for robust, high-throughput single-molecule investigations of protein dynamics required for drug screening and systems biology studies, both in cells and in solution.

biophysics↗
bioRxiv2023

De novo design of drug-binding proteins with predictable binding energy and specificity

The de novo design of small-molecule-binding proteins has seen exciting recent progress; however, the ability to achieve exquisite affinity for binding small molecules while tuning specificity has not yet been demonstrated directly from computation. Here, we develop a computational procedure that results in the highest affinity binders to date with predetermined relative affinities, targeting a series of PARP1 inhibitors. Two of four designed proteins bound with affinities ranging from < 5 nM to low M, in a predictable manner. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free-energy calculations performed directly on the designed models are in excellent agreement with the experimentally measured affinities, suggesting that the de novo design of small-molecule-binding proteins with tuned interaction energies is now feasible entirely from computation. We expect these methods to open many opportunities in biomedicine, including rapid sensor development, antidote design, and drug delivery vehicles. One Sentence SummaryWe use informatic sampling to design low nM drug-binding proteins, and physics-based calculations to accurately predict affinities.

biophysics↗
bioRxiv2023

Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors

The spread of cancer from organ to organ (metastasis) is responsible for the vast majority of cancer deaths; however, most current anti-cancer drugs are designed to arrest or reverse tumor growth without directly addressing disease spread. It was recently discovered that tumor cell-secreted interleukin-6 (IL-6) and interleukin-8 (IL-8) synergize to enhance cancer metastasis in a cell-density dependent manner, and blockade of the IL-6 and IL-8 receptors (IL-6R and IL-8R) with a novel bispecific antibody, BS1, significantly reduced metastatic burden in multiple preclinical mouse models of cancer. Bispecific antibodies (BsAbs), which combine two different antigen-binding sites into one molecule, are a promising modality for drug development due to their enhanced avidity and dual targeting effects. However, while BsAbs have tremendous therapeutic potential, elucidating the mechanisms underlying their binding and inhibition will be critical for maximizing the efficacy of new BsAb treatments. Here, we describe a quantitative, computational model of the BS1 BsAb, exhibiting how modeling multivalent binding provides key insights into antibody affinity and avidity effects and can guide therapeutic design. We present detailed simulations of the monovalent and bivalent binding interactions between different antibody constructs and the IL-6 and IL-8 receptors to establish how antibody properties and system conditions impact the formation of binary (antibody-receptor) and ternary (receptor-antibody-receptor) complexes. Model results demonstrate how the balance of these complex types drives receptor inhibition, providing important and generalizable predictions for effective therapeutic design.

systems biology↗
bioRxiv2023

Climate change impacts dryland multifunctionality: A cascade of precipitation variability to species replacement in multitrophic microbiota

In the Anthropocene, the pervasive impacts of climate change on arid ecosystems are increasingly evident, resulting in significant alterations in both biodiversity and functionality. Although soil microbes are anticipated to be sensitive to changes in precipitation regimes, the mechanisms through which multifaceted precipitation changes impair the delivery of multiple functions by multitrophic microbiota in soils remain largely unexplored. In the drylands of Northwestern China, we examined the direct effects of historical precipitation regimes on the soil multifunctionality of biocrusts, a model system, and their indirect impacts mediated by microbial communities. Among abiotic predictors, precipitation variability, rather than mean annual precipitation, emerged as the primary driver of multifunctionality, leading to a convergence of less functionally beneficial species. By utilizing a biodiversity-ecosystem function relationship framework, our results underscore the crucial roles of - and {beta}-diversity of heterotrophic bacteria, fungi, and phototrophic cyanobacteria in maintaining soil functionality. However, the underlying mechanisms are distinct. We found that the local richness of heterotrophs and phylogenetic dissimilarity of photoautotrophs exert positive influences on multifunctionality, while species replacement, a component of {beta}-diversity, primarily enhances the variance in soil multifunctionality. Importantly, the findings illuminate the cascading effect of precipitation variability on dryland ecosystems, amplified by microbial diversity, potentially triggering a silent collapse of vulnerable arid habitats. Our study highlights the importance of considering indirect climate impacts via soil microbiota, contributing to a deeper understanding of the real-world consequences of climate change on drylands, and offering valuable insights for the management of biodiversity theory-inspired ecosystem restoration.

ecology↗
bioRxiv2023

Prefrontal dynamics and encoding of flexible rule switching

Behavioral flexibility, the ability to adjust behavioral strategies in response to changing environmental contingencies and internal demands, is fundamental to cognitive functions. Despite a large body of pharmacology and lesion studies, the precise neurophysiological mechanisms that underlie behavioral flexibility are still under active investigations. This work is aimed to determine the role of a brainstem-to-prefrontal cortex circuit in flexible rule switching. We trained mice to perform a set-shifting task, in which they learned to switch attention to distinguish complex sensory cues. Using chemogenetic inhibition, we selectively targeted genetically-defined locus coeruleus (LC) neurons or their input to the medial prefrontal cortex (mPFC). We revealed that suppressing either the LC or its mPFC projections severely impaired switching behavior, establishing the critical role of the LC-mPFC circuit in supporting attentional switching. To uncover the neurophysiological substrates of the behavioral deficits, we paired endoscopic calcium imaging of the mPFC with chemogenetic inhibition of the LC in task-performing mice. We found that mPFC prominently responded to attentional switching and that LC inhibition not only enhanced the engagement of mPFC neurons but also broadened single-neuron tuning in the task. At the population level, LC inhibition disrupted mPFC dynamic changes and impaired the encoding capacity for switching. Our results highlight the profound impact of the ascending LC input on modulating prefrontal dynamics and provide new insights into the cellular and circuit-level mechanisms that support behavioral flexibility.

neuroscience↗
bioRxiv2023

Conformational Space Profile Enhances Generic Molecular Representation Learning

The molecular representation model is a neural network that converts molecular representations (SMILES, Graph) into feature vectors, that carries the potential to be applied across a wide scope of drug discovery scenarios. However, current molecular representation models have been limited to 2D or static 3D structures, overlooking the dynamic nature of small molecules in solution and their ability to adopt flexible conformational changes crucial for drug-target interactions. To address this limitation, we propose a novel strategy that incorporates the conformational space profile into molecular representation learning. By capturing the intricate interplay between molecular structure and conformational space, our strategy enhances the representational capacity of our model named GeminiMol. Consequently, when pre-trained on a miniaturized molecular dataset, the GeminiMol model demonstrates a balanced and superior performance not only on traditional molecular property prediction tasks but also on zero-shot learning tasks, including virtual screening and target identification. By capturing the dynamic behavior of small molecules, our strategy paves the way for rapid exploration of chemical space, facilitating the transformation of drug design paradigms.

bioinformatics↗
bioRxiv2023

Chaperone-mediated autophagy is an overlooked pathway for mutant α1 antitrypsin Z degradation

Chaperone-mediated autophagy (CMA) is a specific form of autophagy that selectively targets proteins containing a KFERQ-like motif and relies on the chaperone protein HSC70 for substrate recognition. In 1-antitrypsin deficiency (AATD), a disease characterized by the hepatic build-up of 1-Antitrypsin Z mutant (ATZ), CMAs role had been unclear. This work demonstrates the critical role that CMA plays in preventing ATZ accumulation; suppressing CMA worsens ATZ accumulation, whilst activating it through chemical stimulation or LAMP2A overexpression promotes ATZ breakdown. Specifically, ATZs 121QELLR125 motif is critical for HSC70 recognition and LAMP2As charged C-terminal cytoplasmic tail is vital for substrate binding, facilitating CMA-mediated degradation of ATZ. This selective activation of CMA operates independently from other autophagy pathways and alleviate ATZ aggregates caused cellular stress. These findings highlight CMAs critical function in cellular protein quality control of ATZ and place it as a novel target for AATD treatment approaches.

cell biology↗
bioRxiv2023

Group-common and individual-specific effects of structure-function coupling in human brain networks with graph neural networks

The human cerebral cortex is organized into functionally segregated but synchronized regions bridged by the structural connectivity of white matter pathways. While structure-function coupling has been implicated in cognitive development and neuropsychiatric disorders, it remains unclear to what extent the structure-function coupling reflects a group-common characteristic or varies across individuals, at both the global and regional brain levels. By leveraging two independent, high-quality datasets, we found that the graph neural network accurately predicted unseen individuals functional connectivity from structural connectivity, reflecting a strong structure-function coupling. This coupling was primarily driven by network topology and was substantially stronger than that of the correlation approaches. Moreover, we observed that structure-function coupling was dominated by group-common effects, with subtle yet significant individual-specific effects. The regional group and individual effects of coupling were hierarchically organized across the cortex along a sensorimotor-association axis, with lower group and higher individual effects in association cortices. These findings emphasize the importance of considering both group and individual effects in understanding cortical structure-function coupling, suggesting insights into interpreting individual differences of the coupling and informing connectivity-guided therapeutics.

neuroscience↗
bioRxiv2023

THER: Integrative Web Tool for Tumor Hypoxia Exploration and Research

Hypoxia is an important factor in the adaptation of tumor cells to their environment, contributes to their malignant progression, and affects tumor prognosis and drug sensitivity. Although there is a wealth of transcriptomic data stored in public databases, there is a lack of web-based tools for analyzing these data to explore the link between hypoxia and the mechanisms of tumorigenesis and progression. To this end, we have developed an interactive web-based tool called THER, which is designed to help users easily identify potential targets, mechanisms of action and effective drugs for treating hypoxic tumors. THER integrates 63 transcriptomic tumor hypoxia datasets from the Gene Expression Omnibus (GEO) database, covering 3 species, 18 tumor types and 42 cell line types. This web tool provides five modules that allow users to perform differential expression analysis, expression profiling analysis, correlation analysis, enrichment analysis and drug sensitivity analysis on different datasets based on different oxygen statuses. We expect that users will be able to use the tool to identify valuable biomarkers, further reveal the molecular mechanisms of tumor hypoxia, and identify effective drugs, thus providing a scientific basis for tumor diagnosis and treatment. THER is open to all users and can be accessed without login at https://smuonco.shinyapps.io/THER/.

cancer biology↗
bioRxiv2023

Structural basis for polyuridine tract recognition by SARS-CoV-2 Nsp15

SARS-CoV-2 non-structural protein 15 (Nsp15) is critical for productive viral replication and evasion of host immunity. The uridine-specific endoribonuclease activity of Nsp15 mediates the cleavage of the polyuridine [poly(U)] tract of the negative-strand coronavirus genome to minimize the formation of dsRNA that activates the host antiviral interferon signaling. However, the molecular basis for the recognition and cleavage of the poly(U) tract by Nsp15 is incompletely understood. Here, we present cryogenic electron microscopy (cryoEM) structures of SARS-CoV-2 Nsp15 bound to viral replication intermediate dsRNA containing poly(U) tract at 2.7-3.3 [A] resolution. The structures reveal one copy of dsRNA binds to the sidewall of an Nsp15 homohexamer, spanning three subunits in two distinct binding states. The target uracil is dislodged from the base-pairing of the dsRNA by amino acid residues W332 and M330 of Nsp15, and the dislodged base is entrapped at the endonuclease active site center. Up to 20 A/U base pairs are anchored on the Nsp15 hexamer, which explains the basis for a substantially shortened poly(U) sequence in the negative strand coronavirus genome compared to the long poly(A) tail in its positive strand. Our results provide mechanistic insights into the unique immune evasion strategy employed by coronavirus Nsp15.

molecular biology↗
bioRxiv2023

De novo Design of Peptides that Bind Specific Conformers of α-Synuclein

Insoluble amyloids rich in cross-{beta} fibrils are observed in a number of neurodegenerative diseases. Depending on the clinicopathology, the amyloids can adopt distinct supramolecular assemblies, termed conformational strains. However, rapid methods to study amyloid in a conformationally specific manner are lacking. We introduce a novel computational method for de novo design of peptides that tile the surface of -synuclein fibrils in a conformationally specific manner. Our method begins by identifying surfaces that are unique to the conformational strain of interest, which becomes a "target backbone" for the design of a peptide binder. Next, we interrogate structures in the PDB database with high geometric complementarity to the target. Then, we identify secondary structural motifs that interact with this target backbone in a favorable, highly occurring geometry. This method produces monomeric helical motifs with a favorable geometry for interaction with the strands of the underlying amyloid. Each motif is then symmetrically replicated to form a monolayer that tiles the amyloid surface. Finally, amino acid sequences of the peptide binders are computed to provide a sequence with high geometric and physicochemical complementarity to the target amyloid. This method was applied to a conformational strain of -synuclein fibrils, resulting in a peptide with high specificity for the target relative to other amyloids formed by -synuclein, tau, or A{beta}40. This designed peptide also markedly slowed the formation of -synuclein amyloids. Overall, this method offers a new tool for examining conformational strains of amyloid proteins.

biophysics↗
bioRxiv2023

Teaching transposon classification as a means to crowd source the curation of repeat annotation - a tardigrade perspective

The advancement of sequencing technologies results in the rapid release of hundreds of new genome assemblies a year providing unprecedented resources for the study of genome evolution. Within this context, the significance of in-depth analyses of repetitive elements, transposable elements (TEs) in particular, is increasingly recognized in understanding genome evolution. Despite the plethora of available bioinformatic tools for identifying and annotating TEs, the phylogenetic distance of the target species from a curated and classified database of repetitive element sequences constrains any automated annotation effort. Manual curation of raw repeat libraries is deemed essential due to the frequent incompleteness of automatically generated consensus sequences. However, manual curation and classification are time-consuming processes that offer limited short-term academic rewards and are typically confined to a few research groups where methods are taught through hands-on experience. Crowd sourcing efforts could offer a significant opportunity to bridge the gap between learning the methods of curation effectively and empowering the scientific community with high-quality, reusable repeat libraries. Here, we present an example of such crowd sourcing effort developed through both in-person and online courses built around a collaborative peer-reviewed teaching process that can be used as teaching reference guide for similar projects. The collaborative manual curation of TEs from two tardigrade species, for which there were no TE libraries available, resulted in the successful characterization of hundreds of new and diverse TEs: A hidden treasure awaits discovery within non-model organisms.

evolutionary biology↗
bioRxiv2023

Single cell transcriptional profiling of benign prostatic hyperplasia reveals a progenitor-like luminal epithelial cell state within an inflammatory microenvironment

Benign prostatic hyperplasia (BPH) is characterized by excessive cell proliferation and inflammation and affects most aging men. The development of new therapies for BPH requires a deeper understanding of the underlying pathophysiology and cellular components of BPH. Here, we characterize at single cell resolution the cellular states of BPH and identify cell populations enriched in BPH that contribute to cell proliferation and inflammation. Single-cell RNA-sequencing was performed on prostate tissue from 15 patients undergoing holmium laser enucleation of the prostate for treatment of BPH. Clustering and differential expression analysis on aligned single cell RNA-seq data was performed to annotate all cell types. Pseudotime, gene set enrichment, gene ontology, and ligand-receptor analyses were performed. 16,234 cells were analyzed and specific stromal, epithelial, and immune subgroups were found to be strongly associated with inflammation. A rare luminal subgroup was identified and pseudotime analysis indicated this luminal subgroup was more closely related to club and basal cells. Using a gene set derived from epithelial stem cells, we found that this luminal subgroup had a significantly higher stem cell signature score than all other epithelial subgroups, suggesting this subgroup is a luminal precursor state. Ligand-receptor interactions between stromal, epithelial, and immune cells were explored with CellPhoneDB. Unique interactions highlighting MIF, a pro-inflammatory cytokine that promotes epithelial cell growth and inflammation in the prostate, were found between fibroblasts and the progenitor luminal subgroup. This luminal subgroup also interacted with neutrophils and macrophages through MIF. Our single-cell profiling of BPH provides a roadmap for inflammation-linked cell subgroups and highlights a novel luminal progenitor subgroup interacting with other cell groups via MIF that may contribute to the inflammation and cell proliferation phenotype associated with BPH.

genomics↗
bioRxiv2023

Hypoxia inducible factors inhibit respiratory syncytial virus infection by modulation of nucleolin expression

Respiratory syncytial virus (RSV) is a global healthcare problem, causing respiratory illness in young children and elderly individuals. However, our knowledge of the host pathways that define susceptibility to RSV infection and disease severity is limited. Hypoxia inducible factors (HIFs) define cellular metabolic processes in response to low oxygen and are recognised to play a key role in regulating inflammatory responses in the lower respiratory tract. We demonstrate a role for hypoxia inducible factors (HIFs) to suppress RSV entry and RNA replication. We show that hypoxia and HIF prolyl-hydroxylase inhibitors significantly reduce expression of the RSV entry receptor nucleolin and inhibit viral driven cell-cell fusion. We identify a HIF regulated microRNA, miR-494, that regulates nucleolin expression. In RSV-infected mice, treatment with the clinically approved HIF prolyl-hydroxylase inhibitor, Daprodustat, reduced the level of infectious virus and infiltrating monocytes and neutrophils in the lung. This study highlights a role for HIF-signalling to limit multiple aspects of RSV infection and associated inflammation and informs future therapeutic approaches for treating this respiratory pathogen.

molecular biology↗
bioRxiv2023

Supramolecular Interactions of Teixobactin Analogues in the Crystal State

Teixobactin is a potent peptide antibiotic against Gram-positive bacteria that binds to lipid II and related peptidoglycan precursors and disrupts the cell membrane. This paper presents the X-ray crystallographic structure of the N-methylated teixobactin analogue N-Me-D-Gln4,Lys10-teixobactin (1). N-Methylation at position 4 prevents uncontrolled aggregation and enables the crystallization of the teixobactin analogue. Lysine at position 10 replaces the non-proteinogenic amino acid allo-enduracididine, which is not commercially available. Crystallization from aqueous solution with MgCl2 and PEG3350 afforded crystals suitable for X-ray crystallography. The crystallographic phases were solved using SAD phasing on data sets collected at 2.0663 [A]. Molecular replacement then enabled the determination of the structure at 1.50 [A] resolution using a data set collected at 0.9997[A] (PDB 8U78). Eight peptide molecules comprise the asymmetric unit, with each peptide molecule binding a chloride anion through hydrogen bonding with the amide NH group of residues 7, 8, 10, and 11. The peptide molecules form hydrogen-bonded antiparallel {beta}-sheet dimers in the crystal lattice, with residues 1-3 comprising the dimerization interface. The dimers further assemble end-to-end in the crystal lattice. The {beta}-sheet dimers are amphiphilic, with the side chains of the hydrophobic residues on one surface and the side chains of the hydrophilic residues on the other surface. The dimers pack in the lattice through hydrophobic interactions between the hydrophobic surfaces. The crystal structure of teixobactin analogue 1 recapitulates several aspects of the interaction of teixobactin with the cell membrane of Grampositive bacteria, including anion binding, supramolecular assembly through {beta}-sheet formation, and hydrophobic interactions.

microbiology↗
bioRxiv2023

Vascular abnormalities in heart and brain are associated with cardiovascular and neurological symptoms in a novel mouse model for Williams syndrome

Williams syndrome is a developmental disorder caused by a microdeletion entailing the loss of a single copy of 25-27 genes on chromosome 7q11.23. Patients suffer from cardiovascular and neuropsychological symptoms. Structural abnormalities of the cardiovascular system in Williams syndrome have been attributed to the hemizygous loss of the elastin (ELN) gene. In contrast, the neuropsychological consequences of Williams syndrome, including sensorimotor deficits, hypersociability and cognitive impairments, have been mainly attributed to altered expression of transcription factors like LIMK1, GTF2I and GTF2IRD1, while the potential impact of altered cerebrovascular function has been largely overlooked. To study the relationship between Williams syndrome mutations and vascularization of both the heart and brain, we generated a mouse model carrying a relatively long microdeletion (LD) that includes the Ncf1 gene, thereby minimizing the confounding impact of hypertension. LD mice had elongated and tortuous aortas but, unlike Eln haploinsufficient mice, showed no signs of structural cardiac hypertrophy. Remarkably, LD mice also displayed structural abnormalities in coronary and brain vessels, including disorganized extracellular matrices. Importantly, LD mice faithfully replicated both cardiovascular and neuropsychological symptoms observed in patients. The phenotype was even more comprehensive than former models, with structure-function correlations evident in aberrant auditory and motor behaviors resembling those in patients with Williams syndrome. Together, our findings suggest that not only cardiovascular but also neuropsychological symptoms in Williams syndrome may be driven in part by vascular abnormalities affecting both heart and brain. Significance StatementWilliams syndrome is caused by microdeletion of 25-27 genes on chromosome 7q11.23, resulting in cardiovascular and neuropsychological symptoms. It remains unclear how the affected genes interact and whether cardiovascular deficits influence brain function. We developed and characterized a mouse model with the longest Williams syndrome microdeletion to date. This model reveals interactions between genes that can be compensatory or additive: haploinsufficiency of Ncf1 may counteract the cardiac hypertrophy caused by Eln deletion, while vascular defects that are potentially due to Eln haploinsufficiency extend to the brain and may worsen neuropsychological symptoms. Our findings support the hypothesis that structural vascular deficits putatively contribute to both cardiac and cognitive phenotypes in Williams syndrome, opening new avenues for understanding and treating this syndrome.

systems biology↗