Biology subjects

Zhao, P.

Publications and source records attributed to Zhao, P..

At least 91 records · Page 5Linked to original sources

bioRxiv2023

An eco-physiological model of forest photosynthesis and transpiration under combined nitrogen and water limitation

Although the separate effects of water and nitrogen (N) limitations on forest growth are well known, the question of how to predict their combined effects remains a challenge for modeling of climate change impacts on forests. Here, we address this challenge by developing a new eco-physiological model that accounts for plasticity in stomatal conductance and leaf N concentration. Based on an optimality principle, our model determines stomatal conductance and leaf N concentration by balancing carbon uptake maximization, hydraulic risk and cost of maintaining photosynthetic capacity. We demonstrate the accuracy of the model predictions by comparing them against gross primary production estimates from eddy covariance flux measurements and sap-flow scaled canopy transpiration in a long-term fertilized and an unfertilized Scots pine (Pinus sylvestris L.) forest in northern Sweden. The model also explains the response to N fertilization as a consequence of (i) reduced carbon cost of N uptake and (ii) increased leaf area per hydraulic conductance. The results suggest that leaves optimally coordinate N concentration and stomatal conductance both on short (weekly) time scales in response to weather conditions and on longer time scales in response to soil water and N availabilities.

ecology↗

bioRxiv2023

TIPRL1 and its ATM-dependent phosphorylation promote radiotherapy resistance in head and neck cancer

TIPRL1 (target of rapamycin signaling pathway regulator-like 1) is a known interactor and inhibitor of protein phosphatases PP2A, PP4 and PP6 - all pleiotropic modulators of the DNA Damage Response (DDR). Here, we describe a new role for TIPRL1 in the radiotherapy (RT) response of Head and Neck Squamous Cell Carcinoma (HNSCC). TIPRL1 expression was found increased in tumor versus non- tumor tissue, with high tumoral TIPRL1 expression associating with lower locoregional control and decreased survival of RT-treated patients. TIPRL1 deletion in HNSCC cells resulted in increased RT sensitivity, a faster but prolonged cell cycle arrest, increased micronuclei formation and an altered proteome-wide DDR. Upon irradiation, ATM phosphorylates TIPRL1 at Ser265, contributing to TIPRL1-mediated RT resistance. Mass spectrometry analysis identified DNA-PKcs, RAD51 and nucleosomal histones as novel TIPRL1 interactors. Histone binding, although stimulated by RT, was adversely affected by TIPRL1 Ser265 phosphorylation. Our findings underscore a clinically relevant role for TIPRL1 and its ATM-dependent phosphorylation in RT resistance through modulation of DNA damage checkpoint activation and repair.

cancer biology↗

bioRxiv2023

Genomic insights into post-domestication expansion and selection of body size in ponies

Horses domestication revolutionized human civilization by changing transportation, farming, and warfare patterns. Despite extensive studies on modern domestic horse origins, the intricate demographic history and genetic signatures of pony size demand further exploration. Here, we present a high-quality genome of the Chinese Debao pony and extensively analyzed 385 individuals from 49 horse breeds. We reveal the conservation of ancient components in East Asian horses and close relationships between Asian horses and specific European pony lineages. Genetic analysis uncovers Asian paternal origin for European pony breeds, and these pony-sized horses share a close genetic affinity due to the presence of a potential ancestral ghost pony population. Additionally, we identify promising cis-regulatory elements influencing horse withers height by regulating genes like RFLNA and FOXO1. Overall, our study provides insightful perspectives into the development history and genetic determinants underlying body size in ponies and offers broader implications for horse population management and improvement. TeaserDecoding pony genetics: exploring origins and size determinants sheds light on their historical and biological impacts.

genomics↗

bioRxiv2023

Promotion of tumor angiogenesis and growth induced by low-dose antineoplastic agents via bone-marrow-derived cells

More research is needed to solidify the basis for reasonable metronomic chemotherapy regimens due to the inconsistent clinical outcomes from studies on metronomic chemotherapy with antineoplastic agents, along with signs of a nonlinear dose-response relationship at low doses. The present study therefore explored the dose-response relationships of representative antineoplastic agents in low dose ranges and their underlying mechanisms. Cyclophosphamide (CPA) and 5-fluorouracil (5-Fu) were employed to observe the effects of the frequent administration of low-dose antineoplastic agents on tumor growth, tumor angiogenesis, and bone-marrow-derived cell (BMDC) mobilization in mouse models. The effects of antineoplastic agents on tumor and endothelial cell functions with or without BMDCs were analyzed in vitro. Tumor growth and metastasis were significantly promoted after the administration of CPA or 5-Fu at certain low dose ranges, and were accompanied by enhanced tumor angiogenesis and proangiogenic factor expression in tumor tissues, increased proangiogenic BMDC release in the circulating blood, and augmented proangiogenic BMDC retention in tumor tissues. Low concentrations of CPA or 5-Fu were found to significantly promote tumor cell migration and invasion, and enhance BMDC adhesion to endothelial cells in vitro. These results suggest that there are risks in empirical metronomic chemotherapy using low-dose antineoplastic agents.

pharmacology and toxicology↗

bioRxiv2023

Accelerated social representational drift in the nucleus accumbens in a model of autism

Impaired social interaction is one of the core deficits of autism spectrum disorder (ASD) and may result from social interactions being less rewarding. How the nucleus accumbens (NAc), as a key hub of reward circuitry, encodes social interaction and whether these representations are altered in ASD remain poorly understood. We identified NAc ensembles encoding social interactions by calcium imaging using miniaturized microscopy. NAc population activity, specifically D1 receptor-expressing medium spiny neurons (D1-MSNs) activity, predicted social interaction epochs. Despite a high turnover of NAc neurons modulated by social interaction, we found a stable population code for social interaction in NAc which was dramatically degraded in Cntnap2-/- mouse model of ASD. Surprisingly, non-specific optogenetic inhibition of NAc core neurons increased social interaction time and significantly improved sociability in Cntnap2-/- mice. Inhibition of D1- or D2-MSNs showed reciprocal effects, with D1 inhibition decreasing social interaction and D2 inhibition increasing interaction. Therefore, social interactions are preferentially, specifically and dynamically encoded by NAc neurons and social representations are degraded in this autism model.

neuroscience↗

bioRxiv2023

The Role and Mechanism of TEAD4 in Preimplantation Embryonic Development in Mice and Cattle

Tead4, a critical transcription factor expressed during preimplantation development, is essential for the expression of trophectoderm-specific genes in mice. However, the functional mechanism of Tead4 in mouse preimplantation development and its conservation across mammals remain unclear. Here, we report that Tead4 is a crucial transcription factor necessary for blastocyst formation in mice. Disruption of Tead4 through base editing results in developmental arrest at the morula stage. Additionally, RNA-seq analysis reveals dysregulation of 670 genes in Tead4 knockout embryos. As anticipated, Tead4 knockout leads to a decrease in trophectoderm genes Cdx2 and Gata3. Intriguingly, we observed a reduction in Krt8, suggesting that Tead4 influences the integrity of the trophectoderm epithelium in mice. More importantly, we noted a dramatic decrease in nuclear Yap in outside cells for Tead4-deficient morula, indicating that Tead4 directly regulates Hippo signaling. In contrast, bovine embryos with TEAD4 depletion could still develop to blastocysts with normal expression of CDX2, GATA3, and SOX2, albeit with a decrease in total cell number and ICM cell number. In conclusion, we propose that Tead4 regulates mouse blastocyst formation via Krt8 and Yap, both of which are critical regulators of mouse preimplantation development.

developmental biology↗

bioRxiv2023

Computational repurposing of oncology drugs through off-target drug binding interactions from pharmacological databases

PURPOSESystematic repurposing of approved medicine for another indication represents an attractive strategy to accelerating drug development in oncology. Herein we present a strategy of combining biomarker testing with drug repurposing to identify new treatments for patients with advanced cancer. METHODSTumours were sequenced with Illumina TruSight Oncology 500 (TSO-500) platform or the FoundationOne(R) CDx panel. Mutations were manually screened by two medical oncology clinicians and pathogenic mutations were categorised with reference to the literature. Variants of unknown significance were classified as potentially pathogenic if a plausible mechanism and computational prediction of pathogenicity existed. Gain of function mutations were evaluated through the repurposing databases Probe Miner, the Broad Institute Drug Repurposing Hub (Broad Institute DRH) and TOPOGRAPH. Gain of function mutations were classified as repurposing events if they were identified in Probe Miner, were not indexed in TOPOGRAPH which captures active clinical trial biomarkers and excluding mutations for which a known FDA-approved biomarker label exists. The performance of the computational repurposing approach was validated by evaluating its ability to identify known FDA-approved biomarkers. Exploratory functional analyses were performed with gene expression data and CRISPR-dependency data sourced from the DepMap portal. The total repurposable genome was identified by evaluating all possible gene-FDA drug approved combinations in the Probe Miner dataset. RESULTSThe computational repurposing approach was highly accurate at identifying FDA therapies with known biomarkers (94%). Using a real-world dataset of next-generation sequencing molecular reports (n = 94) and excluding the identification of mutations that would render patients eligible for FDA-licensed therapies or local clinical trials, it was found that a meaningful percentage of patients (14%) would have an off-label therapeutic identified through this approach. Exploratory analyses were performed, including the identification of drug-target interactions that have been previously described in the medicinal chemistry literature but are not well known, and the evaluation of the frequency of theoretical drug repurposing events in the TCGA pan-cancer dataset (73% of samples in the cohort). CONCLUSIONOverall, a computational drug repurposing approach may assist in identifying novel repurposing events in cancer patients with advanced tumours and no access to standard therapies. Further validation is needed to confirm the utility of a precision oncology approach using drug repurposing.

biochemistry↗

bioRxiv2023

AbFold -- an AlphaFold Based Transfer Learning Model for Accurate Antibody Structure Prediction

MotivationAntibodies are a group of proteins generated by B cells, which are crucial for the immune system. The importance of antibodies is ever-growing in pharmaceutics and biotherapeutics. Despite recent advancements pioneered by AlphaFold in general protein 3D structure prediction, accurate structure prediction of antibodies still lags behind, primarily due to the difficulty in modeling the Complementarity-determining regions (CDRs), especially the most variable CDR-H3 loop. ResultsThis paper presents AbFold, a transfer learning antibody structure prediction model with 3D point cloud refinement and unsupervised learning techniques. AbFold consistently produces state-of-the-art results on the prediction accuracy of the six CDR loops. The predictions of AbFold achieve an average RMSD of 1.51 [A] for both heavy and light chains and an average RMSD of 3.04 [A] for CDR-H3, bettering current models AlphaFold and IgFold. AbFold will contribute to antibody structure prediction and design processes.

bioinformatics↗

bioRxiv2023

Taste papilla cell differentiation requires tongue mesenchyme via ALK3-BMP signaling to regulate the production of secretory proteins

Taste papillae are specialized organs each of which is comprised of an epithelial wall hosting taste buds and a core of mesenchymal tissue. In the present study, we report that during the early stages of embryonic development, bone morphogenetic protein (BMP) signaling mediated by type 1 receptor ALK3 in the tongue mesenchyme is required for the epithelial Wnt/{beta}-catenin activity and taste papilla cell differentiation. Mesenchyme-specific knockout (cKO) of Alk3 using Wnt1-Cre and Sox10-Cre resulted in an absence of taste papillae at E12.0. Biochemical and cell differentiation analyses demonstrated that mesenchymal ALK3-BMP signaling governs the production of previously unappreciated secretory proteins, i.e., suppresses those that inhibiting and facilitates those promoting taste cell differentiation. Bulk RNA-Sequencing analysis revealed many more differentially expressed genes (DEGs) in the tongue epithelium than in the mesenchyme in Alk3 cKO vs control. Moreover, we detected a down-regulated epithelial Wnt/{beta}-catenin signaling, and taste papilla development in the Alk3 cKO was rescued by GSK3{beta} inhibitor LiCl, but not Wnt3a. Our findings demonstrate for the first time the requirement of tongue mesenchyme in taste papilla cell differentiation. Summary statementThis is the first set of data to implicate the requirement of tongue mesenchyme in taste papilla cell differentiation.

developmental biology↗

bioRxiv2023

Structure of a fungal 1,3-β-glucan synthase

1,3-{beta}-Glucan is the major component of the fungal cell wall and is synthesized by 1,3-{beta}-glucan synthase located in the plasma membrane, which is a molecular target of anti-fungal drugs echinocandins and the triterpenoid ibrexafungerp. In this study, we report the 3.0-[A] resolution cryo-EM structure of Saccharomyces cerevisiae 1,3-{beta}-glucan synthase, Fks1. The structure reveals a central catalytic region adopting a cellulose synthase fold with a cytosolic conserved GT-A type glycosyltransferase domain and a closed transmembrane glucan-transporting channel. We found that two extracellular disulfide bonds are crucial for Fks1 enzymatic activity. Structural comparison between Fks1 and cellulose synthases and structure-guided mutagenesis studies provided novel insights into the molecular mechanisms of the fungal 1,3-{beta}-glucan synthase.

biophysics↗

bioRxiv2023

PD1 is transcriptionally regulated by LEF1 in mature T cells

Programmed cell death 1 (PD1) plays a vital role in cancer immune evasion. So monoclonal antibodies targeting PD-1 to boost the immune system are being developed for the treatment of cancer. But the effect of PD1/PD-L1 blocking antibody only works in a subset of patients or some tumors. It is well established that PD-1 can affect the positive selection of T cells. Mice lacking PD1 or PD-L1 had more DP T cells in the thymus. However, how it affects the T-cell repertoire is not very clear. For T cell development and maturation, TCF1 and its homolog LEF1, act as indispensable factors and TCF1 has been most studied. In our work, we found that LEF1, not TCF1, positively regulated the transcription of PD1 by generating two mice models, including ERT2-CRE-LEF1flox/flox mice and concanavalin A (ConA)-mediated T activation mice model. We investigated LEF1 and PD1 expression in mature T cells, including CD4+ T cells, CD8+ T cells, and Treg cells in these two mice models. And we also evaluated the expression of PD1 in tumor-infiltrating lymphocytes in the tumor-implantation experiments. Furthermore, the regulation of PD1 by LEF1 was verified in LEF1 knockdown cells. Our conclusions provided a novel insight into PD1 regulation in immune responses and explored potential strategies for clinical anti-PD1 treatment.

immunology↗

bioRxiv2023

Matching Variants for functional characterization of genetic variants

Rapid and low-cost sequencing, as well as computer analysis, have facilitated the diagnosis of many genetic diseases, resulting in a substantial rise in the number of disease-associated genes. However, genetic diagnosis of many disorders remains problematic due to the lack of interpretation for many genetic variants, especially missenses, the infeasibility of high-throughput experiments on mammals, and the shortcomings of computational prediction technologies. Additionally, the available mutant databases are not well-utilized. Toward this end, we used Caenorhabditis elegans mutant resources to delineate the functions of eight missense variants (V444I, V517D, E610K, L732F, E817K, H873P, R1105K, and G1205E) and two stop codons (W937stop and Q1434stop), including several matching variants (MatchVar) with human in ciliopathy associated IFT-140 (also called CHE-11)//IFT140 (intraflagellar transport protein 140). Moreover, MatchVars carrying C. elegans mutants, including IFT-140(G680S) and IFT-140(P702A) for the human (G704S) (dbSNP: rs150745099) and P726A (dbSNP: rs1057518064 and a conflicting variation) were created using CRISPR/Cas9. IFT140 is a key component of IFT complex A (IFT-A), which is involved in the retrograde transport of IFT along cilia and the entrance of G protein-coupled receptors (GPCRs) into cilia. Functional analysis of all ten variants revealed that P702A and W937stop, but not others phenocopied the ciliary phenotypes (short cilia, IFT accumulations, mislocalization of membrane proteins, and cilia entry of non-ciliary proteins) of the IFT-140 null mutant, indicating that both P702A and W937stop are phenotypic in C. elegans. Our functional data offered experimental support for interpreting human variants, by using ready-to-use mutants carrying MatchVars and generating MatchVars with CRISPR/Cas9.

genetics↗

bioRxiv2023

m6A Demethylase FTO Stabilizes LINK-A to Exert Oncogenic Roles via MCM3-Mediated Cell Cycle Progression and HIF-1α Activation

RNA N6-methyladenosine (m6A) modification, balanced by methyltransferases and demethylases, has recently been shown to play critical roles in multiple cancers. However, the mechanism by which m6A modification regulates long noncoding RNA (lncRNA) stability and function during cancer progression remains unclear. Here, we show that m6A demethylase fat mass and obesity-associated protein (FTO) removes the m6A modification on long intergenic noncoding RNA for kinase activation (LINK-A) and stabilizes it to promote cell proliferation and cytotoxic chemotherapy resistance in esophageal squamous cell carcinoma (ESCC). Mechanistically, LINK-A enhances the interaction between minichromosome maintenance complex component 3 (MCM3) and cyclin-dependent kinase 1 (CDK1) to promote MCM3 phosphorylation by CDK1. MCM3 is a subunit of the hexameric protein complex and its phosphorylation facilitates loading of the MCM complex onto chromatin, which promotes cell cycle progression and subsequent cell proliferation. Meanwhile, LINK-A prevents the interaction of MCM3 and hypoxia-inducible factor 1 (HIF-1), abrogates MCM3-mediated transcriptional repression of HIF-1, and promotes glycolysis and chemoresistance of cancer cells. These results elucidate a mechanism whereby FTO-stabilized LINK-A plays oncogenic roles and present the FTO/LINK-A/MCM3/HIF-1 axis as a promising therapeutic target for ESCC.

cancer biology↗

bioRxiv2022

tFold-Ab: Fast and Accurate Antibody Structure Prediction without Sequence Homologs

Accurate prediction of antibody structures is critical in analyzing the function of antibodies, thus enabling the rational design of antibodies. However, existing antibody structure prediction methods often only formulate backbone atoms and rely on additional tools for side-chain conformation prediction. In this work, we propose a fully end-to-end architecture for simultaneous prediction of backbone and side-chain conformations, namely tFold-Ab. Pre-trained language models are adopted for fast structure prediction by avoiding the time-consuming search for sequence homologs. The model firstly predicts monomer structures of each chain, and then refines them into heavy-light chain complex structure prediction, which enables multi-level supervision for model training. Evaluation results verify the effectiveness of tFold-Ab for both antibody and nanobody structure prediction. In addition, we provide a public web service for antibody structure prediction at https://drug.ai.tencent.com/en.

bioinformatics↗

bioRxiv2022

Prospective isolation according to melanin pigment content of melanoma cells with heterogeneous potentials for disease propagation

Functional variation between cancer cells (intra-tumoral heterogeneity) poses a major challenge to treating and managing cancer patients. Melanomas are typically composed of cancer cells with heterogeneous content of melanin pigment. Pigment production is a hallmark of normal melanocytic differentiation, however the functional consequences of melanin production in melanoma cells remains poorly understood owing to a lack of experimental approaches for detection of pigment in unfixed cells. Here, we describe a novel flow cytometric method for high purity separation of viable melanoma cells based on their content of melanin pigment, exploiting the infrared light scattering properties of melanin. By fluorescence-activated cell sorting, we show that melanoma cells with low-pigment content (LPCs) in culture and in patient tumors are far more abundant than high-pigment cells (HPCs), and have substantially increased potentials for colony formation in vitro and for tumor formation in vivo. RNAseq analysis revealed activation of P53 in HPCs associated with perturbed cell cycling, whereas LPCs displayed upregulation of MYC-associated transcription and activated ribosome biogenesis. The latter was reduced by topoisomerase 2 beta targeting with CX-5461, which also induced senescent HPC phenotypes and irreversible loss of clonogenic activity. These data illuminate an inverted pyramid hierarchical model of melanoma cell propagation wherein abundant LPCs frequently renew their own malignant potential to propagate disease, but also rarely generate HPCs that lose this ability in a manner that may be promoted as an anti-melanoma strategy.

cancer biology↗

bioRxiv2022

A new polymodal gating model of the proton-activated chloride channel

The proton-activated chloride (PAC) channel plays critical roles in ischemic neuron death, but its activation mechanisms remain elusive. Here, we interrogated PAC channel gating using its unique bidirectional modulator C77304 as a pharmacological probe. C77304 activated the PAC channel by acting on its proton gating, while simultaneously inhibiting channel activity at higher doses, through interaction with two modulatory sites with different affinities and state-dependence. Excitingly, we revealed that PAC undergoes intrinsic proton gating-independent voltage activation, which was defined by an ion-flux gating mechanism. Scanning-mutagenesis and molecular dynamics simulation confirmed that E181, E257, and E261 in human PAC form the primary proton sensors, as alanine mutations eliminated the channels proton gating while sparing the voltage-dependent gating. This proton sensing mechanism was basically conserved among orthologous PAC channels. Collectively, our data unveils the polymodal gating and proton sensing mechanisms in the PAC channel which may inspire potential drug development.

neuroscience↗

bioRxiv2022

Contact Stiffness Governs Mechanoresponses of Living Cells to Extracellular Microenvironment

In interactions between cells and extracellular matrices (ECMs), contact mechanics theory indicates that local ECM deformation depends on both local and non-local forces imposed by cells. In the present study, we investigated the use of a comprehensive variable, contact stiffness (CS), to interpret cell-ECM interactions. CS defines the relationship between the local ECM deformation and the total force from a cell, integrating the effects of individual variables including ECM stiffness, ECM thickness, and cell adhesion area. Through assessments of ECM mechanosensing by human mesenchymal stem cells (hMSCs) under varied CS conditions, we showed that CS scaled well with both yes-associated protein (YAP) activity and the extent of stem cell differentiation. To reveal the cross-scale mechanism underlying mechanosensing, we propose a CS-based motor clutch model, which suggests that various mechanical stimuli affect cells by altering the CS, thus altering the reaction force from the ECM. Using the proposed model, we revealed the contributions of cell architecture evolution to stem cell differentiation and predicted the influence of a non-adjacent ECM layer on cellular mechanosensing. These results demonstrate that the use of CS provides a quantitative predictive framework that allows researchers to address longstanding questions about the effects of ECM mechanics on cell behaviors.

biophysics↗

bioRxiv2022

LncDLSM: Identification of Long Non-coding RNAs with Deep Learning-based Sequence Model

Long non-coding RNAs (LncRNAs) serve a vital role in regulating gene expressions and other biological processes. Differentiation of lncRNAs from protein-coding transcripts helps researchers dig into the mechanism of lncRNA formation and its downstream regulations related to various diseases. Previous works have been proposed to identify lncRNAs, including traditional bio-sequencing and machine learning approaches. Considering the tedious work of biological characteristic-based feature extraction procedures and inevitable artifacts during bio-sequencing processes, those lncRNA detection methods are not always satisfactory. Hence, in this work, we presented lncDLSM, a deep learning-based framework differentiating lncRNA from other protein-coding transcripts without dependencies on prior biological knowledge. lncDLSM is a helpful tool for identifying lncRNAs compared with other biological feature-based machine learning methods and can be applied to other species by transfer learning achieving satisfactory results. Further experiments showed that different species display distinct boundaries among distributions corresponding to the homology and the specificity among species, respectively. An online web server is provided to the community for easy use and efficient identification of lncRNA, available at http://39.106.16.168/lncDLSM.

bioinformatics↗