Biology subjects

Liu, F.

Publications and source records attributed to Liu, F..

At least 181 records · Page 10Linked to original sources

bioRxiv2024

Modular structure of RNA 3' processing condensates involving the Arabidopsis RNA binding protein FCA

Our understanding of the functional requirements underpinning biomolecular condensation in vivo is still relatively poor. The Arabidopsis RNA binding protein FCA is found in liquid-like nuclear condensates that function in transcription termination, promoting proximal polyadenylation at many targets in the Arabidopsis genome. To further understand the properties of these condensates in vivo we used single particle tracking experiments on FCA reporters stably expressed at endogenous levels in plant nuclei. These revealed FCA forms a core oligomer of [~]4 molecules that multimerizes into higher-order particles. This assembles into macromolecular condensates through the function of the coiled-coil protein FLL2, which is genetically required for FCA function. FLL2 predominately co-localizes with FCA in larger sized condensates. A missense mutation in the FCA RRM domain, also genetically required for FCA function, reduced both average FCA particle and condensate size but did not perturb the core oligomer. Our work points to a modular structure for FCA condensates involving multimerization of core oligomers that assemble into functional macromolecular condensates via associated RNA and FLL2 interactions.

molecular biology↗

bioRxiv2024

Probe-dependent Proximity Profiling (ProPPr) Uncovers Similarities and Differences in Phospho-Tau-Associated Proteomes Between Tauopathies

Tauopathies represent a diverse group of neurodegenerative disorders characterized by the abnormal aggregation of the microtubule-associated protein tau. Despite extensive research, the precise mechanisms underlying the complexity of different types of tau pathology remain incompletely understood. Here we describe an approach for proteomic profiling of aggregate-associated proteomes on slides with formalin-fixed, paraffin-embedded (FFPE) tissue that utilizes proximity labelling upon high preservation of aggregate morphology, which permits the profiling of pathological aggregates regardless of their size. To comprehensively investigate the common and unique protein interactors associated with the variety of tau lesions present across different human tauopathies, Alzheimers disease (AD), corticobasal degeneration (CBD), Picks disease (PiD), and progressive supranuclear palsy (PSP), were selected to represent the major tauopathy diseases. Implementation of our widely applicable Probe-dependent Proximity Profiling (ProPPr) strategy, using the AT8 antibody, permitted identification and quantification of proteins associated with phospho-tau lesions in well-characterized human post-mortem tissue. The analysis revealed both common and disease-specific proteins associated with phospho-tau aggregates, highlighting potential targets for therapeutic intervention and biomarker development. Candidate validation through high-resolution co-immunofluorescence of distinct aggregates across disease and control cases, confirmed the association of retromer complex protein VPS35 with phospho-tau lesions across the studied tauopathies. Furthermore, we discovered disease-specific associations of proteins including ferritin light chain (FTL) and the neuropeptide precursor VGF within distinct pathological lesions. Notably, examination of FTL-positive microglia in CBD astrocytic plaques indicate a potential role for microglial involvement in the pathogenesis of these tau lesions. Our findings provide valuable insights into the proteomic landscape of tauopathies, shedding light on the molecular mechanisms underlying tau pathology. This first comprehensive characterization of tau-associated proteomes across different tauopathies enhances our understanding of disease heterogeneity and provides a resource for future functional investigation, as well as development of targeted therapies and diagnostic biomarkers.

neuroscience↗

bioRxiv2024

The impact of Arctic environments on human cerebral blood flow

BackgroundThe Arctic environment represents an extreme living condition that has significant impact on life. But research on alterations of human cerebral blood flow (CBF) in a high-latitude and low-temperature environment in the Arctic is still lacking. MethodsMembers of the 12th Chinese National Arctic Research Expedition team who took the icebreaker R/V Xuelong 2 to the Arctic were recruited. Transcranial colour doppler (TCD) examination was performed at the beginning of the voyage (lower latitude and higher temperature, LLHT) and during the Arctic scientific expedition period (higher latitude and lower temperature, HLLT) respectively. The spectral pattern and parameters of cerebral arteries were compared. ResultsAmong 16 healthy individuals, 13 completed the TCD examination twice. They had a significantly lower mean velocity (Vm) (63.5 cm/s HLLT vs. 68.4cm/s LLHT; P=0.028) and peak systolic velocity (PSV) (94.6cm/s HLLT vs. 107.0cm/s LLHT; P=0.038) of the left middle cerebral artery (LMCA) and higher pulsatility index (PI) of the right middle cerebral artery (RMCA) (0.83 HLLT vs. 077 LLHT; P=0.011) in the HLLT environment compared to the LLHT one. ConclusionsChanges in human CBF may occur in higher-latitude and lower-temperature environments in the Arctic.

physiology↗

bioRxiv2024

Single-cell multiomics reveals a gene regulatory circuit promoting leukemia cell differentiation

Cancer differentiation therapy aims to induce maturation of neoplastic cells, yet how cell fate is determined in oncogenic cellular contexts is poorly understood. Here we integrate chromatin accessibility and transcriptome analysis at single-cell levels to investigate the mechanism driving the differentiation trajectory of the PML/RAR+ acute promyeloid leukemia (APL) cell line model, NB4, under the induction of all-trans-retinoid acid (ATRA). We show that differentiating NB4 cells navigate through an intermediate cell fate decision point that leads to either terminal granulopoiesis or a transient immature-lymphocyte-like state. Functional perturbation studies indicate that ATRA signaling activates discrete PML/RAR-target enhancers to induce a positive feedforward gene regulatory circuit involving two myeloid-lineage transcription factors, SPI1 and CEBPE, which is both necessary and sufficient to activate a myelocytic gene expression program in NB4. Further, ectopic expression of SPI1 and CEBPE also promotes myelocytic differentiation in non-APL leukemia cell lines HL60 and K562. Together, these results shed light on the differentiation trajectory of therapy-induced cell decisions of APL and suggest a gene regulatory circuit that may be broadly exploited to promote terminal differentiation of leukemia.

cancer biology↗

bioRxiv2024

High-dimensional mass cytometry reveals stemness state heterogeneity in pancreatic ductal adenocarcinoma

Stem-like cancer cells harbour high self-renewal capacity, exhibit enhanced tumourigenicity and have been associated with therapy resistance, metastasis and tumour relapse. Therefore, understanding the molecular features of stem-like cells is critical for targeting them effectively and improving treatment outcomes for cancer patients. Several markers have been used to isolate and study the putative stem-like cells of pancreatic ductal adenocarcinoma (PDAC), but the patterns of marker co-expression and overlap between identified individual subpopulations are yet to be comprehensively studied. Here we developed a mass cytometry antibody panel for simultaneous analysis of 33 stemness-associated markers at single-cell resolution. High-dimensional mass cytometry analysis of PDAC cell lines revealed molecularly heterogeneous stemness states and highlighted the role of genotype in determining the cell line-specific stemness signature. Stemness marker expression lie along a continuum in PDAC cell lines and patient samples indicative of stepwise phenotypic transitions. We also identified a subset of PDAC cells co-expressing high levels of Musashi-2, DCLK1 and CXCR4, and harbouring basal-like and EMT transcriptional programmes associated with highly plastic phenotype. This multiplexed analysis uncovers nuance and complexities of the stemness state in the PDAC.

cancer biology↗

bioRxiv2024

Metabolic control of adaptive β-cell proliferation by the protein deacetylase SIRT2

Selective and controlled expansion of endogenous {beta}-cells has been pursued as a potential therapy for diabetes. Ideally, such therapies would preserve feedback control of {beta}-cell proliferation to avoid excessive {beta}-cell expansion and an increased risk of hypoglycemia. Here, we identified a regulator of {beta}-cell proliferation whose inactivation results in controlled {beta}-cell expansion: the protein deacetylase Sirtuin 2 (SIRT2). Sirt2 deletion in {beta}-cells of mice increased {beta}-cell proliferation during hyperglycemia with little effect in homeostatic conditions, indicating preservation of feedback control of {beta}-cell mass. SIRT2 restrains proliferation of human islet {beta}-cells cultured in glucose concentrations above the glycemic set point, demonstrating conserved SIRT2 function. Analysis of acetylated proteins in islets treated with a SIRT2 inhibitor revealed that SIRT2 deacetylates enzymes involved in oxidative phosphorylation, dampening the adaptive increase in oxygen consumption during hyperglycemia. At the transcriptomic level, Sirt2 inactivation has context-dependent effects on {beta}-cells, with Sirt2 controlling how {beta}-cells interpret hyperglycemia as a stress. Finally, we provide proof-of-principle that systemic administration of a GLP1-coupled Sirt2-targeting antisense oligonucleotide achieves {beta}-cell selective Sirt2 inactivation and stimulates {beta}-cell proliferation under hyperglycemic conditions. Overall, these studies identify a therapeutic strategy for increasing {beta}-cell mass in diabetes without circumventing feedback control of {beta}-cell proliferation.

physiology↗

bioRxiv2024

Lysis buffer selection guidance for mass spectrometry-based global proteomics including studies on the intersection of signal transduction and metabolism

Prerequisite for a successful proteomics experiment is a high-quality lysis of the sample of interest, resulting in a large number of identified proteins as well as a high coverage of protein sequences. Therefore, the choice of suitable lysis conditions is crucial. Many buffers were previously employed in proteomics studies, yet a comprehensive comparison of lysate preparation conditions was so far missing. In this study, we compared the efficiency of four commonly used lysis buffers, containing the agents NP40, SDS, urea or GdnHCl, in four different types of biological samples (suspension and adherent cell lines, primary mouse cells and mouse liver tissue). After liquid chromatography-mass spectrometry (LC-MS) measurement and MaxQuant analysis, we compared chromatograms, intensities, number of identified proteins and the localization of the identified proteins. Overall, SDS emerged as the most reliable reagent, ensuring stable performance and reproducibility across diverse samples. Furthermore, our data advocated for a dual-sample lysis approach, including that the resulting pellet is lysed again after the initial lysis with a urea lysis buffer and subsequently both lysates are combined for a single LC-MS run to maximize the proteome coverage. However, none of the investigated lysis buffers proved to be superior in every category, indicating that the lysis buffer of choice depends on the proteins of interest and on the biological question. Further, we demonstrated with our systematic studies the establishment of conditions that allows to perform global proteomics and affinity purification-based interactome characterization from the same lysate. In sum our results provide guidance for the best-suited lysis buffer for mass spectrometry-based proteomics depending on the question of interest.

systems biology↗

bioRxiv2024

IL-1beta-induced epithelial cell and fibroblast transdifferentiation fuels neutrophil recruitment in chronic rhinosinusitis with nasal polyps

Neutrophilic inflammation contributes to multiple chronic inflammatory airway diseases, including asthma and chronic rhinosinusitis with nasal polyps (CRSwNP), and is associated with an unfavorable prognosis. Here, using single-cell RNA sequencing (scRNA-seq) to profile human nasal mucosa obtained from the inferior turbinates, middle turbinates, and nasal polyps of CRSwNP patients, we identified two IL-1 signaling-induced cell subsets--LY6D+ club cells and IDO1+ fibroblasts--that promote neutrophil recruitment by respectively releasing S100A8/A9 and CXCL1/2/3/5/6/8 into inflammatory regions. IL-1{beta}, a pro-inflammatory cytokine involved in IL-1 signaling, induces the transdifferentiation of LY6D+ club cells and IDO1+ fibroblasts from primary epithelial cells and fibroblasts, respectively. In an LPS-induced neutrophilic CRSwNP mouse model, blocking IL-1{beta} activity with a receptor antagonist significantly reduced the numbers of LY6D+ club cells and IDO1+ fibroblasts and mitigated nasal inflammation. This study reveals the roles of two cell subsets in neutrophil recruitment and demonstrates an IL-1-based intervention for mitigating neutrophilic inflammation in CRSwNP.

immunology↗

bioRxiv2024

BAMBI: Integrative biostatistical and artificial-intelligence method discover coding and non-coding RNA genes as biomarkers

Accurate disease diagnosis and prognosis are crucial for effective treatment management and improving patient outcomes. However, accurately detecting early signs of certain diseases or recurrence remains challenging. Existing machine-learning methods for identifying gene expression biomarkers have several limitations, including poor performance on independent test datasets, inability to directly process omics data, and difficulty in identifying noncoding RNA genes as biomarkers. Additionally, these methods may not provide sufficient biological interpretation of their results, and the panel biomarkers they identify may not be suitable for clinical application. To address these limitations, we have developed a new computational method called BAMBI, which integrates multiple machine-learning algorithms and statistical approaches to identify putative coding and noncoding genes as biomarkers for disease diagnosis and prognosis. We evaluated BAMBI ability to identify diagnostic and prognostic biomarkers by analyzing multiple RNA-seq datasets from cancerous and non-cancerous diseases at population levels. The results from BAMBI demonstrate significant biological interpretability and state-of-the-art prediction performance. When the singular gene identified by BAMBI is used as a diagnostic biomarker, it achieves a balance accuracy exceeding 95% in studies of both breast cancer and psoriasis. Additionally, the prognostic biomarkers that BAMBI identifies from RNA-seq data of Acute Myeloid Leukemia (AML) patients significantly correlate with the survival rates in an independent AML patient cohort. Additionally, BAMBI outperforms existing methods by delivering more robust results, identifying biomarkers with fewer genes, and simultaneously achieving superior prediction accuracy. We have implemented BAMBI into user-friendly software for the research community. In summary, BAMBI serves as a more reliable pipeline for identifying both coding and noncoding genes as biosignature markers, enhancing the accuracy of disease diagnosis and prognosis. BAMBI is available via https://github.com/CZhouLab/BAMBI.

bioinformatics↗

bioRxiv2023

Aberrant connective tissue sheath contraction drives premature hair follicle regression by inducing progenitor cell depletion in androgenetic alopecia

Androgenetic alopecia (AGA) is characterized by progressive miniaturization of hair, forming a distinctive patterned baldness in the scalp; yet, the mechanisms for hair miniaturization in this disease remain largely unknown. Here by single-cell transcriptome analysis, we describe a concise single-cell atlas, and identify the early changes in cell subpopulations, hair follicle (HF) stem cell fate determination and cell-cell communications in AGA anagen HF units. Thereinto, apoptotic loss of HF progenitor cells is significantly increased, correlated with HF miniaturization in AGA. Mechanistically, enhanced contraction of connective tissue sheath (CTS) activates the mechanosensitive channel PIEZO1, which triggers ectopic apoptosis of progenitor cells in human anagen HFs. Continuous CTS contraction during AGA causes long-term loss of progenitor cells via inducing persistent ectopic apoptosis through PIEZO1, eventually leading to premature hair regression. Most importantly, we show that targeting CTS contraction by ML-7, a selective myosin light chain kinase (MLCK) inhibitor, can obviously improve the growth of HFs from balding scalps of AGA patients. Our study reveals the cellular hierarchies and identifies CTS with increased muscle contraction activity as a driver of premature hair regression in AGA, highlighting CTS surrounding human HF as the therapeutic target for treating this disorder.

pathology↗

bioRxiv2023

Structure-based discovery of positive allosteric modulators for the calcium sensing receptor

Drugs acting as positive allosteric modulators (PAMs) to enhance the activation of the calcium sensing receptor (CaSR) and to suppress parathyroid hormone (PTH) secretion can treat hyperparathyroidism but suffer from side effects including hypocalcemia and arrhythmias. Seeking new CaSR modulators, we docked libraries of 2.7 million and 1.2 billion molecules against transforming pockets in the active-state receptor dimer structure. Consistent with simulations suggesting that docking improves with library size, billion-molecule docking found new PAMs with a hit rate that was 2.7-fold higher than the million-molecule library and with hits up to 37-fold more potent. Structure-based optimization of ligands from both campaigns led to nanomolar leads, one of which was advanced to animal testing. This PAM displays 100-fold the potency of the standard of care, cinacalcet, in ex vivo organ assays, and reduces serum PTH levels in mice by up to 80% without the hypocalcemia typical of CaSR drugs. Cryo-EM structures with the new PAMs show that they induce residue rearrangements in the binding pockets and promote CaSR dimer conformations that are closer to the G-protein coupled state compared to established drugs. These findings highlight the promise of large library docking for therapeutic leads, especially when combined with experimental structure determination and mechanism. One sentence summaryStructure-based virtual screening uncovers novel CaSR allosteric modulators with enhanced efficacy and less side effects.

biophysics↗

bioRxiv2023

Engineered Skin Microbiome Reduces Mosquito Attraction to Mice

The skin microbiome plays a pivotal role in the production of attractive cues detected by mosquitoes. Here we leveraged recent advances in genetic engineering to significantly reduce the production of L-(+)-lactic acid as a strategy to reduce mosquito attraction to the highly prominent skin commensals Staphylococcus epidermidis and Corynebacterium amycolatum. Engraftment of these engineered bacteria onto the skin of mice reduced mosquito attraction and feeding for up to 11 uninterrupted days, which is considerably longer than the several hours of protection conferred by the leading chemical repellent DEET. Taken together, our findings demonstrate engineering the skin microbiome to reduce attractive volatiles represents an innovative untapped strategy to reduce vector attraction, preventing bites, and pathogen transmission setting the stage for new classes of long-lasting microbiome-based repellent products. One-Sentence SummaryModified microbes make skin less attractive to mosquitoes

microbiology↗

bioRxiv2023

The activated plant NRC4 immune receptor forms a hexameric resistosome

Innate immune responses against microbial pathogens in both plants and animals are regulated by intracellular receptors known as Nucleotide-binding Leucine-rich Repeats (NLR) proteins. In plants, these NLRs play a crucial role in recognizing pathogen effectors, thereby initiating the activation of immune defense mechanisms. Notably, certain NLRs serve as "helper" NLR immune receptors (hNLR), working in tandem with "sensor" NLR immune receptors (sNLR) counterparts to orchestrate downstream signaling events to express disease resistance. In this study, we reconstituted and determined the cryo-EM structure of the hNLR required for cell death 4 (NRC4) resistosome. The auto-active NRC4 formed a previously unanticipated hexameric configuration, triggering immune responses associated with Ca2+ influx into the cytosol. Furthermore, we uncovered a dodecameric state of NRC4, where the coil-coil (CC) domain is embedded within the complex, suggesting an inactive state, and expanding our understanding of the regulation of plant immune responses. One Sentence SummaryThe hexameric NRC4 resistosome mediates cell death associated with cytosolic Ca2+ influx.

plant biology↗

bioRxiv2023

A comprehensive overview and benchmarking analysis of fast algorithms for genome-wide association studies

Genome-wide association studies (GWAS) are a ubiquitous tool for identifying genetic variants associated with complex traits in structured populations. During the past 15 years, many fast GWAS algorithms based on a state-of-the-art model, namely the linear mixed model, have been published to cope with the rapidly growing data size. In this study, we provide a comprehensive overview and benchmarking analysis of 33 commonly used GWAS algorithms. Key mathematical techniques implemented in different algorithms were summarized. Empirical data analysis with 12 selected algorithms showed differences regarding the identification of quantitative trait loci (QTL) in several plant species. The performance of these algorithms evaluated in 10,800 simulated data sets with distinct population size, heritability and genetic architecture revealed the impact of these parameters on the power of QTL identification and false positive rate. Based on these results, a general guide on the choice of algorithms for the research community is proposed.

genetics↗

bioRxiv2023

Phenotype Heterogeneity Warrants Trizonal Feedback between Intracellular Contractility and Extracellular stiffening

The intricate interplay between actomyosin contractility and extracellular matrix (ECM) strain stiffening is pivotal in cancer invasion. Despite the admitted impact of such feedback, current models are inadequate in predicting the largely overlapping ranges of cell shapes and their corresponding motility levels at intermediate ranges of collagen density. To address this gap, we introduce a free energy-based, trizonal model for cell shape transition under ECM stiffening, which delineates two distinct and one overlapping motility zones entitled with their implications for cancer progression: a low-motility zone with minimal invasiveness, a high-motility zone indicative of significantly invasive cells, and a mesoregion which harbors cells at crossroads of both states. This model integrates critical factors influencing the bidirectional interaction between the cell and ECM, thereby offering a deeper grasp of cancer cell behavior. Our findings reveal that the combined effects of ECM strain stiffening and cellular contractility are key drivers of cell population heterogeneity and invasiveness. This model goes beyond existing paradigms by accurately determining the optimal cell elongation at matrix-driven steady-state equilibrium, factoring in collagen density, contractility density, stress polarization, membrane-cortical tension, and integrin dynamics through the lens of total free energy minimization. The models predictive capability is further validated against measured cell shapes from histological sections. Altogether, this research not only bridges a crucial knowledge gap, but also provides a robust computational framework for predicting and replicating cell shape transitions observed in human functional tissue assays, thereby enhancing our ability to understand and potentially combat cancer invasion. SignificanceECM stiffening is crucial in prompting metastatic phenotypes, with the interaction between cell contractility and ECM stiffening heavily influenced by cell motility level and reflected in distinct cell shapes [1-3]. This research introduces a free-energy-based model that, based on sound physics, not only distinguishes among different cell populations by their motility levels, but also truly replicates the recently observed trizonal cell response to ECM stiffness. This predictive model, validated by experiment, bridges a critical gap in our understanding of cellular dynamics in cancer progression, offering profound insight into the physical concepts driving these complex interactions. Thereupon, this work provides a powerful computational tool, potentially leading to new strategies in diagnosing and treating cancer by targeting specific cell behavioral traits and interactions within the tumor microenvironment.

cell biology↗

bioRxiv2023

Structural Host-Virus Interactome Profiling of Intact Infected Cells

Virus-host protein-protein interactions (PPIs) are fundamental to viral infections, yet high-resolution identification within the native context of intact infected cells has remained an unsolved challenge. Here, we developed structural host-virus interactome profiling (SHVIP) that combines in situ cross-linking mass spectrometry with the enrichment of newly synthesized viral proteins from infected cells. We established SHVIP using herpes simplex virus type 1 and obtained 739 PPIs based on 6,194 cross-links from productively infected cells. SHVIP captures PPIs across intracellular compartments and at the intact host endomembrane system. It resolves PPIs to the protein domain level and seamlessly integrates with AlphaFold-based structural modeling, facilitating detailed predictions of PPI sites within structured and intrinsically disordered regions. We show that SHVIP captures parts of the virus-host PPI space that are elusive to traditional interaction proteomics approaches. By selectively disrupting several newly identified virus-host PPIs, we confirm SHVIPs ability to uncover genuine virus-host PPIs in the intact complex environment of infected cells.

microbiology↗

bioRxiv2023

PROTEOME-SCALE RECOMBINANT STANDARDS AND A ROBUST HIGH-SPEED SEARCH ENGINE TO ADVANCE CROSS-LINKING MS-BASED INTERACTOMICS

AO_SCPLOWBSTRACTC_SCPLOWAdvancing data analysis tools for proteome-wide cross-linking mass spectrometry (XL-MS) requires ground-truth standards that mimic biological complexity. Here, we develop wellcontrolled XL-MS standards comprising hundreds of recombinant proteins that are systematically mixed for cross-linking. We use one standard dataset to guide the development of Scout, a search engine for XL-MS with MS-cleavable cross-linkers. Using other, independent datasets from our standards as well as published datasets, we benchmark the performance of Scout and existing XL-MS software. This demonstrates that Scout offers the best combination of speed, sensitivity, and false-discovery rate control. These results illustrate how our large recombinant standards can support the development of XL-MS analysis tools and evaluation of XL-MS results.

bioinformatics↗

bioRxiv2023

Head Direction Cells and Grid Cells as the Core Components of the Core-periphery Structure

Head direction cells and grid cells are neuron types defined by their regular firing patterns in standard experimental arenas. As technology advances, we can record extensive neuronal firing activity over time using electrophysiological or calcium imaging methods. The covariance matrix is a critical measure of this neural populations discharge activity. We developed a method to identify a core-periphery structure in the covariance matrix, highlighting the central role of grid cells and head direction cells in firing correlations. This method effectively redefines these cell types in terms of firing activity correlations, with core nodes exhibiting a higher mutual information rate for spatial variables. Additionally, we developed a periodic spring network algorithm, which uses the covariance matrix alone to estimate the spatial phases of both head direction cells and grid cells due to their periodic properties. This approach offers a new perspective on utilizing the covariance matrix of the neural population to better understand and identify these specialized cell types, even when traditional firing pattern-based definitions are challenging to apply.

neuroscience↗