Biology subjects

Xie, S.

Publications and source records attributed to Xie, S..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Integrated analysis and systematic characterization of the regulatory network for human germline development

Primordial germ cells (PGCs) are the precursors of germline that are specified at embryonic stage. Recent studies reveal that humans employ different mechanisms for PGC specification compared with model organisms such as mice. Moreover, the specific regulatory machinery is still largely unexplored, mainly due to the inaccessible nature of this complex biological process. Here, we collect and integrate multi-omics data, including 581 RNA-seq, 54 ATAC-seq, 45 ChIP-seq, and 69 single-cell RNA-seq samples from different stages of human PGC development to recapitulate the precisely controlled and stepwise process, presenting an atlas in the human PGC database (hPGCdb). With these uniformly processed data and integrated analyses, we characterize the potential key transcription factors and regulatory networks governing human germ cell fate. We validate the important roles of some of the key factors in germ cell development by CRISPRi knockdown. We also identify the soma-germline interaction network and discover the involvement of SDC2 and LAMA4 for PGC development, as well as soma-derived NOTCH2 signaling for germ cell differentiation. Taken together, we have built a database for human PGCs and demonstrate that hPGCdb enables the identification of the missing pieces of mechanisms governing germline development, including both intrinsic and extrinsic regulatory programs.

developmental biology↗

bioRxiv2023

Forest demography and biomass accumulation rates are associated with transient mean tree size vs density scaling relations

Linking individual and stand-level dynamics during forest development reveals a scaling relationship between mean tree size and tree density in forest stands, which integrates forest structure and function. However, the nature of this so-called scaling law and its variation across broad spatial scales remains unquantified and its linkage with forest demographic processes and carbon dynamics remains elusive. Here we develop a theoretical framework and compile a broad-scale dataset of long-term sample forest stands (n = 1433) from largely undisturbed forests to examine the association of temporal mean tree size vs density scaling trajectories (slopes) with biomass accumulation rates and the sensitivity of scaling slopes to environmental and demographic drivers. The results empirically demonstrate a large variation of scaling slopes, ranging from -4 to -0.2, across forest stands in tropical, temperate and boreal forest biomes. Steeper scaling slopes are associated with higher rates of biomass accumulation, resulting from a lower offset of forest growth by biomass loss from mortality. In North America, scaling slopes are positively correlated with forest stand age and rainfall seasonality, thus suggesting a higher rate of biomass accumulation in younger forests with lower rainfall seasonality. These results demonstrate the strong association of the transient mean tree size vs density scaling trajectories with forest demography and biomass accumulation rates, thus highlighting the promise of leveraging forest structure properties to predict forest demography, carbon fluxes and dynamics at broad spatial scales. Significance StatementMean tree size vs density scaling relationships are thought to predict forest function at broad spatial scales. Here we develop a theoretical framework based upon demographic processes and empirical evidence from forest inventory data to demonstrate a strong association of the transient mean tree size and density scaling trajectories (slopes) with forest demography and biomass accumulation rates. This strong association is pervasive across forest biomes and suggests a negative relationship between scaling slope and biomass accumulation rate (resource availability). Our results highlight the promise of leveraging forest structure (i.e., inferred from high resolution remote sensing data or fused into size-structured demographic models) to evaluate forest demography, carbon fluxes and dynamics at broad spatial scales.

ecology↗

bioRxiv2023

Epiregulon: Inference of single-cell transcription factor activity to dissect mechanisms of lineage plasticity and drug response

Transcription factors (TFs) and transcriptional coregulators represent an emerging class of therapeutic targets in oncology. Gene regulatory networks (GRNs) can be used to evaluate pharmacological agents targeting these factors and to identify drivers of disease and drug resistance. However, GRN methods that rely solely on gene expression often fail to account for post-transcriptional modulation of TF function. We present Epiregulon, a method that constructs GRNs from single-cell ATAC-seq and RNA-seq data for accurate prediction of TF activity. This is achieved by considering the co-occurrence of TF expression and chromatin accessibility at TF binding sites in each cell. We leverage ChIP-seq data to extend inference to transcriptional coregulators lacking defined motifs or TF harboring neomorphic mutations. Epiregulon accurately predicted the effects of AR inhibition across various drug modalities including an AR antagonist and an AR degrader, delineated the mechanisms of a SMARCA4 degrader by identifying context-dependent interaction partners and prioritized known and novel drivers of lineage reprogramming and tumorigenesis. By mapping gene regulation across various cellular contexts, Epiregulon can accelerate the discovery of therapeutics targeting transcriptional regulators.

bioinformatics↗

bioRxiv2023

Functional characterization of RNA profiles in processing bodies of human embryonic stem cells and mesodermal cells

Processing bodies (P-bodies) are the membraneless organelles that play critical roles in RNA storage and decay. Abnormalities in P-bodies contribute to diseases and developmental disorders. Huge efforts have been applied to the identification of the protein components in P-bodies, however, the dynamics of RNA components of P-bodies in human embryonic stem cells (hESCs) during maintenance and differentiation remain largely elusive. Here, we characterized the RNA profiles of P-bodies from HEK293T cells, hESCs, and hESC-derived mesodermal cells. The number of P-bodies decreases upon hESC differentiation towards mesodermal fate, accompanied with the decreased RNAs within P-bodies. By functional analysis of the P-body enriched and P-body depleted genes across different cell types, we discovered the cell type-specific enrichment of P-body-genes and the potential association with human diseases. We also captured the non-coding RNAs, including long intergenic non-coding RNAs and transposable elements in P-bodies in a cell type-specific manner. Furthermore, we verified the involvement P-bodies in regulating the differentiation of hESCs towards mesoderm by over-expression of LSM14A and knocking down of SPTAN1. In summary, we characterized the mRNAs and non-coding RNAs in P-bodies of hESCs and hESC-derived mesodermal cells, discovering the potential roles that P-bodies play for the precise differentiation of hESCs.

developmental biology↗

bioRxiv2023

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes

Genetic studies have associated thousands of enhancers with breast cancer. However, the vast majority have not been functionally characterized. Thus, it remains unclear how variant-associated enhancers contribute to cancer. Here, we perform single-cell CRISPRi screens of 3,512 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of >500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of variant-associated enhancers disrupts breast cancer gene programs. We observe variant-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple variant-associated enhancers indirectly regulate TP53. Comparative studies illustrate sub-type specific functions between enhancers in ER+ and ER- cells. Finally, we developed the pySpade package to facilitate analysis of single-cell enhancer screens. Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

genomics↗

bioRxiv2023

Dense Sampling of Taxa and Genomes Untangles the Phylogenetic Backbone of a Non-model Plant Lineage Rife with Deep Hybridization and Allopolyploidy

Phylogenetic networks, rather than purely bifurcating trees, more accurately depict the intricate evolutionary dynamics of most lineages, especially those characterized by extensive hybridization and allopolyploidization events. However, the challenges of achieving complete taxon sampling, and limited financial resources for studying non-model plant lineages, have hindered comprehensive and robust estimation of phylogenetic backbones with guidance from networks. The bellflower tribe, Campanuleae, characterized by a reticulate evolutionary history, serves as an ideal model to investigate how to diagnose nested ancient reticulation events. Here, by integrating multiple genomic data sources and a range of phylogenetic inference methods, we produced a robust phylogenetic backbone for the tribe Campanuleae. Our investigation of reticulate evolution indicates that hybridization and allopolyploidization were instrumental in shaping the diversity of the bellflower tribe, particularly during the initial diversification of the subtribe Phytematinae. Additionally, we ascertained that conflicting topologies resulting from distinct genomic datasets and inference methodologies significantly impact downstream estimates of divergence dating, ancestral area construction, and diversification rates. This study offers a universally relevant framework for deciphering how to use network-based phylogenetic structures using various genomic sources and inference methods. [Campanulaceae, Campanuleae, Cytonuclear discordance, paralog, phylogenomics, reticulate evolution]

plant biology↗

bioRxiv2023

Identifying summary statistics for approximate Bayesian computation in a phylogenetic island biogeography model

Estimation of parameters of evolutionary island biogeography models, such as colonization and diversification rates, is important for a better understanding of island systems. A popular statistical inference framework is likelihood-based estimation of parameters using island species richness and phylogenetic data. Likelihood approaches require that the likelihood can be computed analytically or numerically, but with the increasing complexity of island biogeography models, this is often unfeasible. Simulation-based estimation methods may then be a promising alternative. One such method is approximate Bayesian computation (ABC), which compares summary statistics of the empirical data with the output of model simulations. However, ABC demands the definition of summary statistics that sufficiently describe the data, which is yet to be explored in island biogeography. Here, we propose a set of summary statistics and use it in an ABC framework for the estimation of parameters of an island biogeography model, DAISIE (Dynamic Assembly of Island biota through Speciation, Immigration and Extinction). For this model, likelihood-based inference is possible, which gives us the opportunity to assess the performance of the summary statistics. DAISIE currently only allows maximum likelihood estimation (MLE), so we additionally develop a likelihood-based Bayesian inference framework using Markov Chain Monte Carlo (MCMC) to enable comparison with the ABC results (i.e., making the same assumptions on prior distributions). We simulated phylogenies of island communities subject to colonization, speciation, and extinction using the DAISIE simulation model and compared the estimated parameters using the three inference approaches (MLE, MCMC and ABC). Our results show that the ABC algorithm performs well in estimating colonization and diversification rates, except when the species richness or amount of phylogenetic information from an island are low. We find that compared to island species diversity statistics, summary statistics that make use of phylogenetic and temporal patterns (e.g., the number of species through time) significantly improve ABC inference accuracy, especially in estimating colonization and anagenesis rates, as well as making inference converge considerably faster and perform better under the same number of iterations. Island biogeography is rapidly developing new simulation models that can explain the complexity of island biodiversity, and our study provides a set of informative summary statistics that can be used in island biogeography studies for which likelihood-based inference methods are not an option.

evolutionary biology↗

bioRxiv2023

Inferring state-dependent diversification rates using approximate Bayesian computation (ABC)

State-dependent speciation and extinction (SSE) models provide a framework for quantifying whether species traits have an impact on evolutionary rates and how this shapes the variation in species richness among clades in a phylogeny. However, SSE models are becoming increasingly complex, limiting the application of likelihood-based inference methods. Approximate Bayesian computation (ABC), a likelihood-free approach, is a potentially powerful alternative for estimating parameters. One of the key challenges in using ABC is the selection of efficient summary statistics, which can greatly affect the accuracy and precision of the parameter estimates. In state-dependent diversification models, summary statistics need to capture the complex relationships between rates of diversification and species traits. Here, we develop an ABC framework to estimate state-dependent speciation, extinction and transition rates in the BiSSE (binary state dependent speciation and extinction) model. Using different sets of candidate summary statistics, we then compare the inference ability of ABC with that of using likelihood-based maximum likelihood (ML) and Markov chain Monte Carlo (MCMC) methods. Our results show the ABC algorithm can accurately estimate state-dependent diversification rates for most of the model parameter sets we explored. The inference error of the parameters associated with the species-poor state is larger with ABC than in the likelihood estimations only when the speciation rate is highly asymmetric between the two states ({lambda}1 /{lambda} 0 = 5). Furthermore, we find that the combination of normalized lineage-through-time (nLTT) statistics and phylogenetic signal in binary traits (Fitz and Purviss D) constitute efficient summary statistics for the ABC method. By providing insights into the selection of suitable summary statistics, our work aims to contribute to the use of the ABC approach in the development of complex state-dependent diversification models, for which a likelihood is not available.

evolutionary biology↗

bioRxiv2023

miRNA-encoded regulatory peptides modulate cadmium tolerance and accumulation in rice

MicroRNAs (miRNAs) are small non-coding RNAs that play a vital role in plant responses to abiotic and biotic stress. Recently, it has been discovered that some primary miRNAs (pri-miRNAs) encode regulatory short peptides called miPEPs. However, the presence of miPEPs in rice, and their functions in response to abiotic stress, particularly stress induced by heavy metals, remain poorly understood. Here, we identified a functional small peptide (miPEP156e) encoded by pri-miR156e that regulates the expression of miR156 and its target SPL genes, thereby affecting miR156-mediated cadmium (Cd) tolerance in rice. Overexpression of miPEP156e led to a reduction in the accumulation of reactive oxygen species (ROS) and Cd in plants under Cd stress, resulting in improved rice Cd tolerance, as observed in miR156-overexpressing lines and seedlings treated with exogenous miPEP156e. In contrast, miPEP156e mutants displayed sensitivity to Cd stress due to the elevated accumulation of ROS and Cd. Transcriptome analysis further revealed that miPEP156e improved rice Cd tolerance by modulating Cd transporter and ROS scavenging genes. Moreover, we identified five novel miPEPs involved in regulating Cd resistance through exogenous treatment of seedlings with synthetic corresponding miPEPs. Our study provides insights into the regulatory mechanism of miPEP156e in rice response to Cd stress and demonstrates the potential of miPEPs as an effective tool for improving crop abiotic stress tolerance.

plant biology↗

bioRxiv2023

ASD mutation of Katnal2 impairs ependymal ciliary motion and causes hydrocephalus

Katanin catalytic subunit A1 like 2 (KATNAL2) is a high-risk gene associated with autism spectrum disorders (ASD), however its impact on brain development and disease remains unclear. The present study revealed an unexpected role of KATNAL2 in regulating ependymal ciliary motion and cerebrospinal fluid flow during brain development, an important contributing factor for ASD. We discovered a distinct expression pattern of KATNAL2 in multiciliated ependymal cells of both human and mouse brains. Notably, an ASD-associated mutation of Katnal2 disrupted its molecular function and resulted in ASD-related behavioral deficits in mice. Additionally, this mutation affected the polarized organization and beating of ependymal cilia, leading to delayed cerebrospinal fluid flow and sustained ventricular enlargement from the early postnatal stage. Conditional ablation of Katnal2 specifically in the ependymal cells of neonatal mice is sufficient to cause ventricular dilation, whereas no such effect was observed in adult mice. Our findings highlight the importance of ependymal motile cilia and hydrocephalus in ASD, offering insights into its pathogenesis and potential intervention.

neuroscience↗

bioRxiv2023

Lysine vitcylation is a novel vitamin C-derived protein modification that enhances STAT1-mediated immune response

Vitamin C (vitC) is a vital nutrient for health and also used as a therapeutic agent in diseases such as cancer. However, the mechanisms underlying vitCs effects remain elusive. Here we report that vitC directly modifies lysine without enzymes to form vitcyl-lysine, termed "vitcylation", in a dose-, pH-, and sequence-dependent manner across diverse proteins in cells. We further discover that vitC vitcylates K298 site of STAT1, which impairs its interaction with the phosphatase PTPN2, preventing STAT1 Y701 dephosphorylation and leading to increased STAT1-mediated IFN pathway activation in tumor cells. As a result, these cells have increased MHC/HLA class-I expression and activate immune cells in co-cultures. Tumors collected from vitC-treated tumor-bearing mice have enhanced vitcylation, STAT1 phosphorylation and antigen presentation. The identification of vitcylation as a novel PTM and the characterization of its effect in tumor cells opens a new avenue for understanding vitC in cellular processes, disease mechanisms, and therapeutics.

biochemistry↗

bioRxiv2023

A non-image-forming visual circuit mediates the innate fear of heights

The neural basis of fear of heights remains largely unknown. In this study, we investigated the fear response to heights in mice and observed characteristic aversive behaviors resembling human height vertigo. We identified visual input as a critical factor in mouse reactions to heights, while peripheral vestibular input was found to be nonessential for fear of heights. Unexpectedly, we found that fear of heights in naive mice does not rely on image-forming visual processing by the primary visual cortex. Instead, a subset of neurons in the ventral lateral geniculate nucleus (vLGN), which connects to the lateral/ventrolateral periaqueductal gray (l/vlPAG), drives the expression of fear associated with heights. Additionally, we observed that a subcortical visual pathway linking the superior colliculus to the lateral posterior thalamic nucleus inhibits the defensive response to height threats. These findings highlight a rapid fear response to heights threat through a subcortical visual and defensive pathway from the vLGN to the l/vlPAG.

neuroscience↗

bioRxiv2023

Co-engagement of TIGIT+ immune cells to PD-L1+ tumours by a bispecific antibody potentiates T-cell response and tumour control

Co-targeting PD-1/PD-L1 and TIGIT/CD226 is being pursued to broaden the efficacy of current immunotherapy. Here we demonstrate that a bispecific antibody (BsAb) targeting PD-L1 and TIGIT, HB0036, shows major advantages over the combination of the two parental monoclonal Abs (mAbs). We demonstrated that HB0036 co-engages PD-L1+ tumour cells and TIGIT+ T cells, and thereby upregulates CD226 on T cells and induces a greater T-cell proliferative response compared to the combination of the parental antibodies in vitro. In vivo, HB0036 recruits greater amounts of TIGIT antibody in PD-L1+ tumours but not in PD-L1- tumours, compared with therapy using the two parental antibodies. We also observed improved tumour control and favourable immunological signatures with HB0036 in syngeneic and xenograft tumour models. Collectively, these findings demonstrate that bispecific antibodies targeting PD-L1 and TIGIT offer superior benefits in cancer immunotherapy compared with therapy using the two parental antibodies. Based on these studies, a phase I clinical trial with HB0036 has been initiated in patients with solid tumours (NCT05417321).

immunology↗

bioRxiv2023

Computational insights into the conformational transition of STING: mechanistic, energetic considerations, and the influence of crucial mutations

STING (stimulator of interferon genes) is a crucial protein in the innate immune systems response to viral and bacterial infections. In this study, we investigated the mechanistic and energetic mechanism of the conformational transition process of STING activated by cGAMP binding. We found that the STING connector region undergoes an energetically unfavorable transition during this process, which is compensated by the favorable interaction between cGAMP and the STING ligand binding domain. We utilized enhanced sampling methods to study STINGs rotation and finds that several disease-causing mutations, such as N154S and V155L, can result in a smoother transition process, while V147L exhibits unfavorable conformational transition energy. These findings indicate that V147L may not be a gain-of-function mutation, as previously thought, and are further supported by an evolutionary analysis of the STING connector region. Overall, our study provides detailed insights into the mechanism of STINGs rotation and has implications for the development of treatments for STING-related diseases.

biophysics↗

bioRxiv2023

Progesterone is an Inducement of Heritable Pulmonary Arterial Hypertension with BMPR2 Mutation

BackgroundBone morphogenetic protein type II receptor (BMPR2) gene mutation accounts for 80% of patients with heritable pulmonary artery hypertension (HPAH), and female mutation carriers have significantly higher penetrance rate than males. The inducement of HPAH penetrance and the mechanism of sex differential penetrance are still elusive. MethodsWe infected or transfected pulmonary artery smooth muscle cells (PASMCs) with shBMPR2 lentivirus or siBMPR2 to simulate the pathologic condition of BMPR2 heterozygous mutation and treated them with progesterone. The HPAH patient-derived induced pluripotent stem cells (iPSCs) were induced into vascular smooth muscle cells (VSMCs) to further verify the cellular phenotype. Wild-type flox+/- female mice and SM22-cre BMPR2 flox+/- female mice (CKO mice) were administered with 1-month progesterone, and their phenotype of PAH was evaluated by right heart catheterization and histopathological examination. ResultsProgesterone promoted the proliferation of PASMCs with BMPR2-knockdownby activating ERK pathway via progesterone receptor (PGR). Activated ERK not only upregulated the phosphorylation and elevation of cMYC, but also induced the transcription of endothelin (EDN1) by promoting the nuclear entry of c-JUN and combination on the its promoter region. Similar results were confirmed by iPSCs-VSMCs experiment. CKO mice developed PAH spontaneously and had increased expression of EDN1, which was further aggravated by exogenous progesterone. ConclusionsProgesterone might be an inducement of HPAH penetrance caused by BMPR2 mutation, accounting for sex differential penetrance.

molecular biology↗

bioRxiv2023

Inducible mismatch repair streamlines forward genetic approaches to target identification of cytotoxic small molecules

Orphan cytotoxins are small molecules for which the mechanism of action (MoA) is either unknown or ambiguous. Unveiling the mechanism of these compounds may lead to useful tools for biological investigation and in some cases, new therapeutic leads. In select cases, the DNA mismatch repair-deficient colorectal cancer cell line, HCT116, has been used as a tool in forward genetic screens to identify compound-resistant mutations, which have ultimately led to target identification. To expand the utility of this approach, we engineered cancer cell lines with inducible mismatch repair deficits, thus providing temporal control over mutagenesis. By screening for compound resistance phenotypes in cells with low or high rates of mutagenesis, we increased both the specificity and sensitivity of identifying resistance mutations. Using this inducible mutagenesis system, we implicate targets for multiple orphan cytotoxins, including a natural product and compounds emerging from a high-throughput screen, thus providing a robust tool for future MoA studies.

biochemistry↗

bioRxiv2023

High-throughput screening of functional neo-antigens and their specific TCRs via the Jurkat reporter system combine with droplet microfluidics

T-cell receptor (TCR)-engineered T cells can precisely recognize a broad repertoire of targets derived from both intracellular and surface proteins of tumor cells. TCR-T adoptive cell therapy has shown safety and promising efficacy in solid tumor immunotherapy. However, antigen-specific functional TCR screening is time-consuming and expensive, which limits its application clinically. Here, we developed a novel integrated antigen-TCR screening platform based on droplet microfluidics technology, enabling high-throughput peptide-major histocompatibility complex (pMHC) library-to-TCR library screening with high sensitivity and low background signal. We introduced DNA barcoding technology to label peptide antigen candidate-loaded antigen-presenting cells (APCs) and Jurkat reporter cells to check the specificity of pMHC-TCR candidates. Coupled with the next-generation sequencing pipeline, interpretation of the DNA barcodes and the gene expression level of the Jurkat T-cell activation pathway provided a clear peptide-MHC-TCR recognition relationship. Our proof-of-principle study demonstrates that the platform could achieve unbiased pMHC-TCR library-on-library screening, which is expected to be used in the cross-reactivity and off-target testing of candidate pMHC-TCR libraries in clinical applications.

bioengineering↗

bioRxiv2023

Probing the hierarchical dynamics of DNA-sperm nuclear transition protein complex through fuzzy interaction and mesoscale condensation

Nuclear transition protein TNP1 is a crucial player mediating histone-protamine exchange in condensing spermatids. A unique combination of intrinsic disorder and multivalent properties turns TNP1 into an ideal agent for orchestrating the formation of versatile TNP-DNA assembly and endows the protein with potent value for vaccine design. Despite its significance, the physicochemical property and the molecular mechanism taken by TNP1 for histone replacement and DNA condensation are still poorly understood. In this study, for the first time, we expressed and purified in vitro human TNP1. We investigated the hierarchical dynamics of TNP1: DNA interaction by combing computational simulations, biochemical assay, fluorescence imaging, and atomic force microscopy. We analyzed fuzzy interactions between TNP1 and DNA at the atomistic level and assessed the influence of TNP1 association on the electrostatic and mechanical properties of DNA. Furthermore, the alteration of the physicochemical properties of the TNP1-DNA complex modulates its molecular assembly and phase separation. Our study sets the foundation for understanding TNP1-mediated histone replacement and sheds light on the encapsulation of genetic material by TNP1 for vaccine development.

biophysics↗