Biology subjects

Nie, C.

Publications and source records attributed to Nie, C..

15 recordsLinked to original sources

bioRxiv2026

Spatial engineering of posterior organizers in cerebral organoids via controlled morphogen exposure within hydrogels

Cerebral cortex organoids are powerful in vitro models that recapitulate key features of human development. However, conventional methods produce cortical organoids with spontaneous, spatially disorganized cortical regions due to limited control over morphogen distribution within local environments. Here, we present a spatially engineered hydrogel platform that drives localized posterior organizer formation in cortical organoids through controlled, localized exposure to morphogens. Using a combination of bulk photopolymerization, thermal crosslinking, and digital light processing (DLP) approaches, we fabricated hydrogels with stiffness-controlled layers that preferentially deliver morphogens to one side of the organoid, selectively inducing posterior organizer formation on the exposed face. We further validated this platform by delivering fluorescently tagged dextran, used as molecular weight-matched model morphogens, to visualize spatiotemporal delivery dynamics at the organoid interface. As a proof of principle, we also demonstrated that DLP fabrication enables the printing of dual morphogen hubs, serving as a model for establishing two opposing gradients within a single organoid. Together, this hydrogel platform enables systematic spatial patterning of cell populations in organoids, more faithfully recapitulating the spatial organization and cellular diversity of native tissues and advancing higher-fidelity models for studying human development and disease.

bioengineering↗

bioRxiv2025

Morphogen-guided neocortical organoids recapitulate regional areal identity and model neurodevelopmental disorder pathology

The human neocortex exhibits characteristic regional patterning (arealization) critical for higher-order cognitive function. Disrupted arealization is strongly implicated in neurodevelopmental disorders (NDDs), but current neocortical organoid models largely fail to recapitulate this patterning, limiting mechanistic understanding. Here, we establish a straightforward method for generating arealized organoids through short-term early exposure to anterior (FGF8) or posterior (BMP4/CHIR-99021) morphogens. These treatments created distinct anterior and posterior signaling centers, supporting long-lasting polarization, which we validated with single-cell RNA sequencing that revealed area-specific molecular signatures matching prenatal human cortex. To demonstrate the utility of this platform, we modeled Fragile X Syndrome (FXS) in organoids with distinct anterior and posterior regional identities. FXS organoids showed highly disrupted SOX4/SOX11 expression gradients along the anterior-posterior axis, consistent with alterations found in autism spectrum disorder (ASD) and demonstrate how regional patterning defects may contribute to NDD pathology. Together, our study provides a robust platform for generating neocortical organoids with anterior-posterior molecular signatures and highlights the importance of modeling NDDs using experimental platforms with neuroanatomic specificity.

developmental biology↗

bioRxiv2025

A Comprehensive Reference Catalog of Human Skin DNA Virome Reveals Novel Viral Diversity and Microenvironmental Influences

IntroductionHuman skin serves as a dynamic habitat for a diverse microbiome, including a complex array of viruses whose diversity and roles are not fully understood. ObjectivesThis study aims to enhance our understanding of this skin viral diversity through the construction of a detailed, non-redundant DNA viral reference catalog. MethodsA total of 2,760 skin metagenomes from six published skin studies were collected. A skin virome catalog was constructed using methods independent of reference databases. Viral characteristics were identified through cross-cohort meta-analysis and used to characterize viral features across different skin environments. ResultsWe identified 20,927 viral sequences, which clustered into 2,873 viral operational taxonomic units (vOTUs). Among these, 2,610 represent previously unrecorded viral sequences, uncovering a substantial breadth of viral diversity on human skin. The results also highlight significant differences in viral communities that are associated with varying skin microenvironments. The oily skin is enriched in Papillomaviridae; the dry skin area is enriched in Autographiviridae, Inoviridae and Mitoviridae; and the moist skin is enriched in Herelleviridae, indicating the adaptive nature of viruses. We also investigated the relationship between bacteriophages and bacteria on the skin surface. We found that skin bacteria such as Pseudomonas, Klebsiella, and Staphylococcus are infected by phages from the class Caudoviricetes. ConclusionThis comprehensive skin DNA viral catalog significantly advances our understanding of the viromes role within the skin ecosystem. The findings highlight the adaptive nature of viruses to different skin microenvironments and their interactions with resident bacteria. This catalog serves as a valuable resource for further epidemiological and therapeutic research, potentially leading to better management and treatment of skin conditions influenced by the skins virome.

microbiology↗

bioRxiv2024

Modeling metastatic progression from cross-sectional cancer genomics data

Metastasis formation is a hallmark of cancer lethality. Yet, metastases are generally unobservable during their early stages of dissemination and spread to distant organs. Genomic datasets of matched primary tumors and metastases may offer insights into the underpinnings and the dynamics of metastasis formation. We present metMHN, a cancer progression model designed to deduce the joint progression of primary tumors and metastases using cross-sectional cancer genomics data. The model elucidates the statistical dependencies among genomic events, the formation of metastasis, and the clinical emergence of both primary tumors and their metastatic counterparts. metMHN enables the chronological reconstruction of mutational sequences and facilitates estimation of the timing of metastatic seeding. In a study of nearly 5000 lung adenocarcinomas, metMHN pinpointed TP53 and EGFR as mediators of metastasis formation. Furthermore, the study revealed that post-seeding adaptation is predominantly influenced by frequent copy number alterations. All datasets and code are available on GitHub at https://github.com/cbg-ethz/metMHN.

bioinformatics↗

bioRxiv2022

DHHC3 mediated Cadm4 palmitoylation regulates myelination in CNS

Cell adhesion molecule 4 (Cadm4) plays important roles on plasma membrane (PM) to regulate myelin formation and the downregulation of Cadm4 is a prominent feature in many demyelination diseases. However, how Cadm4 maintains its level on PM has been elusive. Here, we identify that Cadm4 is palmitoylated at cysteine-347 (C347) and palmitoylation regulates the stable localization of Cadm4 on PM, as blocking palmitoylation by mutating C347 into alanine (C347A) results in the dissociation of Cadm4 from PM and targeting for degradation. Intriguingly, blocking Cadm4 palmitoylation by introducing C347A (Cadm4-KI) causes myelin abnormalities in CNS, characterized by loss of myelination, myelin infoldings and hypermyelination. Moreover, it is uncovered that Cadm4 palmitoylation is catalyzed by DHHC3, reducing Cadm4 palmitoylation by the deletion of DHHC3 renders the redistribution of Cadm4 for degrading. Consistently, the genetic deletion of DHHC3 leads to downregulated Cadm4 palmitoylation and defects in CNS myelination, virtually phenocopies that of the Cadm4-KI mice. Our findings suggest a mechanism that the stable localization of Cadm4 on PM regulated by protein palmitoylation is vital for myelination in CNS.

neuroscience↗

bioRxiv2022

Reconstruction and analysis of thermodynamically-constrained models reveal metabolic responses of a deep-sea bacterium to temperature perturbations

Microbial acclimation to different temperature conditions can involve broad changes in cell composition and metabolic efficiency. A systems-level view of these metabolic responses in non-mesophilic organisms, however, is currently missing. In this study, thermodynamically-constrained genome-scale models were applied to simulate the metabolic responses of a deep-sea psychrophilic bacterium, Shewanella psychrophila WP2, under suboptimal (4{degrees}C), optimal (15{degrees}C), and supraoptimal (20{degrees}C) growth temperatures. The models were calibrated with experimentally determined growth rates of WP2. Gibbs free energy change of reactions ({Delta}rG), metabolic fluxes, and metabolite concentrations were predicted using random simulations to characterize temperature-dependent changes in the metabolism. The modeling revealed the highest metabolic efficiency at the optimal temperature, and it suggested distinct patterns of ATP production and consumption that could lead to the lower metabolic efficiency under suboptimal or supraoptimal temperatures. The modeling also predicted rearrangement of fluxes through multiple metabolic pathways, including the glycolysis pathway, Entner-Doudoroff pathway, tricarboxylic acid (TCA) cycle, and the electron transport system, and these predictions were corroborated through comparisons to WP2 transcriptomes. Furthermore, predictions of metabolite concentrations revealed the potential conservation of reducing equivalents and ATP in the suboptimal temperature, consistent with experimental observations from other psychrophiles. Taken together, the WP2 models provided mechanistic insights into the metabolism of a psychrophile in response to different temperatures. ImportanceMetabolic flexibility is a central component of any organisms ability to survive and adapt to changes in environmental conditions. This study represents the first application of thermodynamically-constrained genome-scale models in simulating the metabolic responses of a deep-sea psychrophilic bacterium to varying temperatures. The models predicted differences in metabolic efficiency that were attributed to changes in metabolic pathway utilization and metabolite concentration during growth under optimal and non-optimal temperatures. Experimental growth measurements were used for model calibration, and temperature-dependent transcriptomic changes corroborated the model-predicted rearrangement of metabolic fluxes. Overall, this study highlights the utility of modeling approaches in studying the temperature-driven metabolic responses of an extremophilic organism.

systems biology↗

bioRxiv2021

IMPDH1 retinal variants control filament architecture to tune allosteric regulation

IMP dehydrogenase (IMPDH), a key regulatory enzyme in purine nucleotide biosynthesis, dynamically assembles filaments in response to changes in metabolic demand. Humans have two isoforms: IMPDH2 filaments reduce sensitivity to feedback inhibition by the downstream product GTP, while IMPDH1 assembly remains uncharacterized. IMPDH1 plays a unique role in retinal metabolism, and point mutants cause blindness and disrupt GTP regulation. Here, in a series of cryo-EM structures we show that IMPDH1 assembles polymorphic filaments with different assembly interfaces in active and inhibited states. Retina-specific splice variants introduce structural elements that reduce sensitivity to GTP inhibition, including stabilization of the active filament form. Finally, we show that IMPDH1 disease mutations fall into two classes: one disrupts GTP regulation and the other has no in vitro phenotype. These findings provide a foundation for understanding the role of IMPDH1 in retinal function and disease and demonstrate the diverse mechanisms by which metabolic enzyme filaments are allosterically regulated.

biochemistry↗

bioRxiv2021

Plasma exosomal miRNA analysis of Alzheimer's disease reveals the dysfunction of a neural network

Exosomal microRNA (miRNA) is an emerging source for biomarkers of Alzheimers disease (AD). Here, we profiled miRNA expression in AD, mild cognitive impairment (MCI), and controls. The assessment and validation of differentially expressed miRNA represented their potential to be novel biomarkers for AD and MCI. We conducted 13 co-expression networks and a miRNA network module linked to neural function emerged as the most significantly associated with AD diagnosis. The conservation analysis revealed the M1 was highly preserved in controls but dysfunction in AD and MCI. The module pattern between MCI and NC was similar, but significantly differed from AD, suggesting that the neural network regulated by miRNA changed during the mild cognitive stage, and the total miRNA expression altered in AD stage. Additionally, 24 out of 26 M1 hub-miRNAs were derived from brain tissue, and 15 had been reported as AD biomarkers. We consequently proposed the other 11 miRNAs could play important roles in AD. Our study highlights that co-expression network analysis can provide a new path for finding novel biomarkers.

bioinformatics↗

bioRxiv2021

Responding kinetic of B-cell receptor repertoire to the Toll-like receptor 7/8 stimulation in non-human primates

TLR7 and 8 regulate B cell immunity, but the precise details of the mechanism are still unclear. Here, we studied the kinetics of both heavy and light chains (IgKL) of B-cell receptor (BCR) repertoire responding to the TLR7/8 stimulation in two geniuses of non-human primates (NHPs), African green monkeys (AGMs) and rhesus macaques (RMs). We evaluated the activation of lymphocytes by flow cytometry, and studied characteristics of BCR repertoire in terms of gene usage, repertoire diversity, and the number of lineages. Although AGMs had a weaker activation than RMs, and a different responding kinetic, both AGMs and RMs presented an increased IgKL repertoire diversity and lineages expansion. It suggested that the responding time rather than initiation of TLR7/8-induced IgKL repertoire response related to B cell activation. Expanded IgKL lineages with frequency from 0.001% to 1% had an elevated mutation rate and expanded IgH lineages used more IgA/G/E, suggesting that the TLR7/8 stimulation expanded low-frequent but high-mutated lineages. Besides, most of expanded IgKL lineages were {lambda} isotype. In conclusion, TLR7/8 selectively expands IgKL lineages with a high mutation rate, low frequency, and {lambda} isotype. The selective effect of TLR7/8 on BCR repertoire allows TLR7/8 agonists to be adjuvant for selectively accelerating antibody maturation.

immunology↗

bioRxiv2021

In vitro efficacy of Artemisia extracts against SARS-CoV-2

Traditional medicines based on herbal extracts have been proposed as affordable treatments for patients suffering from coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Teas and drinks containing extracts of Artemisia annua and Artemisia afra have been widely used in Africa in efforts to prevent and fight COVID-19 infections. We sought to study the ability of different A. annua and A. afra extracts and the Covid-Organics drink produced in Madagascar to inhibit SARS-CoV-2 and feline coronavirus (FCoV) replication in vitro. Several extracts as well as Covid-Organics inhibit SARS-CoV-2 and FCoV replication at concentrations that did not affect cell viability. It remains unclear whether peak plasma concentrations in humans can reach levels needed to inhibit viral replication following consumption of teas or Covid-Organics. Clinical studies are required to evaluate the utility of these drinks for COVID-19 prevention or treatment in patients.

pharmacology and toxicology↗

bioRxiv2019

Evaluation of Commercially Available Exosomal Isolation Kits from Human Plasma

Exosomes are cell-derived lipid bilayer particles which are abundant in biological fluids. Exosome is an emerging source of biomarkers to diagnose various human diseases. Sequencing based exosomal studies could provide a comprehensive view of exosomal RNA and protein. To extracted these inclusions, exosomes should be isolated from the plasma first. Several exosome isolation methods were introduced since the discover of exosome. To promote the clinical application of exosomal inclusions, different isolation methods should be compared. We isolated exosomes from human plasma by using user-friendly and commercially available kits, SBI ExoQuick and QIAGEN exoRNeasy. Subsequently, small RNA sequencing was performed with two groups of isolated exosome samples and one group of plasma samples. No fundamental differences of exRNA yield between SC and EQ were found. In RNA profile analysis, the small RNA aligned reads, miRNA pattern, sample clustering varied as a result of methodological differences. Small RNA isolated by ExoQuick presented better data quality and RNA profile than exoRNeasy. This study compared sRNA sequencing data generated from two exosome isolation kits, it provides a reference for future small RNA studies and biomarker prediction in human plasma exosome.

bioinformatics↗

bioRxiv2019

LFMD: a new likelihood-based method to detect low-frequency mutations without molecular tags

As next-generation sequencing (NGS) and liquid biopsy become more prevalent in research and in the clinic, there is an increasing need for better methods to reduce cost and improve sensitivity and specificity of low-frequency mutation detection (where the Alternative Allele Frequency, or AAF, is less than 1%). Here we propose a likelihood-based approach, called Low-Frequency Mutation Detector (LFMD), which combines the advantages of duplex sequencing (DS) and the bottleneck sequencing system (BotSeqS) to maximize the utilization of duplicate reads. Compared with the existing state-of-the-art methods, DS, Du Novo, UMI-tools, and Unified Consensus Maker, our method achieves higher sensitivity, higher specificity (< 4 x 10-10 errors per base sequenced) and lower cost (reduced by ~70% at best) without involving additional experimental steps, customized adapters or molecular tags. LFMD is useful in areas where high precision is required, such as drug resistance prediction and cancer screening. As an example of LFMDs applications, mitochondrial heterogeneity analysis of 28 human brain samples across different stages of Alzheimers Disease (AD) showed that the canonical oxidative damage related mutations, C:G>A:T, are significantly increased in the mid-stage group. This is consistent with the Mitochondrial Free Radical Theory of Aging, suggesting that AD may be linked to the aging of brain cells induced by oxidative damage.

bioinformatics↗

bioRxiv2018

Value-based Decision Making Takes Place in the Action Domain in the Prefrontal Cortex

Value-based decision making is a process in which humans or animals maximize their gain by selecting appropriate options and performing the corresponding actions to acquire them. Whether the evaluation process of the options in the brain can be independent from their action contingency has been hotly debated. To address the question, we trained rhesus monkeys to make decisions by integrating evidence and studied whether the integration occurred in the stimulus or the action domain in the brain. After the monkeys learned the task, we recorded both from the orbitofrontal (OFC) and dorsolateral prefrontal (DLPFC) cortices. We found that the OFC neurons encoded the value associated with the single piece of evidence in the stimulus domain. Importantly, the representations of the value in the OFC was transient and the information was not integrated across time for decisions. The integration of evidence was observed only in the DLPFC and only in the action domain. We further used a neural network model to show how the stimulus-to-action transition of value information may be computed in the DLPFC. Our results indicated that the decision making in the brain is computed in the action domain without an intermediate stimulus-based decision stage.

neuroscience↗

bioRxiv2017

Covert Shift of Attention Modulates the Value Encoding in the Orbitofrontal Cortex

During value-based decision making, we often evaluate the value of each option sequentially by shifting our attention, even when the options are presented simultaneously. The orbitofrontal cortex (OFC) has been suggested to encode value during value-based decision making. Yet it is not known how its activity is modulated by attention shifts. We investigated this question by employing a passive viewing task that allowed us to disentangle effects of attention, value, choice and eye movement. We found that the attention modulated OFC activity through a winner-take-all mechanism. When we attracted the monkeys attention covertly, the OFC neuronal activity reflected the reward value of the newly attended cue. The shift of attention could be explained by a normalization model. Our results strongly argue for the hypothesis that the OFC neuronal activity represents the value of covertly attended item. They provide important insights toward the neural mechanism of value-based decision making.

neuroscience↗

bioRxiv2017

A Neural Network Framework For The Orbitofrontal Cortex During Model-Based Reinforcement Learning

Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and use the knowledge to choose actions and acquire desired outcomes. It has been proposed that the orbitofrontal cortex (OFC) encodes the task state space during reinforcement learning. However, it is not well understood how the OFC acquires and stores task state information. Here, we propose a neural network model based on reservoir computing. Reservoir networks exhibit heterogeneous and dynamic activity patterns that are suitable to encode task states. The information can be extracted by a linear readout trained with reinforcement learning. We demonstrate how the network acquires and stores the task structures. The network exhibits reinforcement learning behavior and its aspects resemble experimental findings of the OFC. Our study provides a theoretical explanation of how the OFC may contribute to reinforcement learning and a new approach to understanding the neural mechanism underlying reinforcement learning.

neuroscience↗