Biology subjects

Chen, C.

Publications and source records attributed to Chen, C..

At least 289 records · Page 16Linked to original sources

bioRxiv2024

A convenient single-cell newly synthesized transcriptome assay reveals gene expression dynamics during early-stage T-cell activation

Sequencing newly synthesized transcriptome alongside regular transcriptome in single cells enables the study of gene expression temporal dynamics during rapid chromatin and gene regulation processes. Existing assays for profiling single-cell newly synthesized transcriptome often require specialized technical expertise to achieve high cellular throughput, limiting their accessibility. Here, we developed NOTE-seq, a method for simultaneous profiling of regular and newly synthesized transcriptomes in single cells with high cellular throughput. NOTE-seq integrates 4-thiouridine labeling of newly synthesized RNA, thiol-alkylation-based chemical conversion, and a streamlined 10X Genomics workflow, making it accessible and convenient for biologists without extensive single-cell expertise. Using NOTE-seq, we investigated the temporal dynamics of gene expression during early-stage T-cell activation, identified transcription factors and regulons in Jurkat and naive T cells, and uncovered the down-regulation of FLI1 as a master transcription factor upon T-cell stimulation. Notably, topoisomerase inhibition led to the depletion of both topoisomerases and FLI1 in T cells through a proteasome-dependent mechanism driven by topoisomerase cleavage complexes, highlighting potential complications topoisomerase-targeting cancer chemotherapies could pose to the immune system.

genomics↗

bioRxiv2024

Transmission of Mixed Convergent Signals at the Mouse Retinogeniculate Synapse

There are two broad modes of information transfer in the brain: the labeled line model, where neurons relay inputs they receive, and the mixed tuning model, where neurons transform and integrate different inputs. In the visual pathway, information transfer between retinal ganglion cells (RGCs) and the dorsal lateral geniculate nucleus (dLGN) neurons is primarily viewed as a labeled line. However, recent work in mice has demonstrated that different RGC types, encoding distinct visual features, can converge onto a dLGN neuron, raising the fundamental question of whether the dLGN transforms visual information. Using optogenetics we activated distinct RGC populations and assessed spiking output of dLGN neurons by in vivo recordings. We found that visual response properties of dLGN neurons driven by a specific RGC population largely matched properties of the activated RGCs. Furthermore, in vitro dual-opsin experiments demonstrate that strong functional convergence from distinct RGC types rarely occurs. Thus, retinogeniculate information transfer in mice largely adheres to a labeled line model.

neuroscience↗

bioRxiv2024

Experience instructs the refinement of feature-selectivity in the mouse primary visual thalamus

Neurons exhibit selectivity for specific features: a property essential for extracting and encoding relevant information in the environment. This feature-selectivity is thought to be modifiable by experience at the level of the cortex. Here, we demonstrate that selective exposure to a feature during development can instruct the population representation for that feature in the primary visual thalamus. This thalamic plasticity is not simply inherited from the cortex because it is still observed when recordings were performed in the absence of cortical feedback. Moreover, plasticity is blocked in mutant mice that exhibit deficits in retinogeniculate refinement, indicating that alterations in feature-selectivity are a direct result of changes in feedforward connectivity. These experience-dependent changes persist into older ages--highlighting the importance of this developmental period in shaping population coding in the thalamus. Our results show that salient environmental features are hard-wired into thalamic circuits during a discrete developmental window.

neuroscience↗

bioRxiv2024

Stromal KITL/SCF promotes pancreas tissue homeostasis and restrains tumor progression

Components of normal tissue architecture serve as barriers to tumor progression. Inflammatory and wound-healing programs are requisite features of solid tumorigenesis, wherein alterations to immune and non-immune stromal elements enable loss of homeostasis during tumor evolution. The precise mechanisms by which normal stromal cell states limit tissue plasticity and tumorigenesis, and which are lost during tumor progression, remain largely unknown. Here we show that healthy pancreatic mesenchyme expresses the paracrine signaling molecule KITL, also known as stem cell factor, and identify loss of stromal KITL during tumorigenesis as tumor-promoting. Genetic inhibition of mesenchymal KITL in the contexts of homeostasis, injury, and cancer together indicate a role for KITL signaling in maintenance of pancreas tissue architecture, such that loss of the stromal KITL pool increased tumor growth and reduced survival of tumor-bearing mice. Together, these findings implicate loss of mesenchymal KITL as a mechanism for establishing a tumor-permissive microenvironment. Statement of significanceBy analyzing transcriptional programs in healthy and tumor-associated pancreatic mesenchyme, we find that a sub-population of mesenchymal cells in healthy pancreas tissue express the paracrine signaling factor KITL. Loss of mesenchymal KITL is an accompanying and permissive feature of pancreas tumor evolution, with potential implications for cancer interception.

cancer biology↗

bioRxiv2024

Single field evolution rule governs the dynamics of representational drift in mouse hippocampal dorsal CA1 region.

How the brain reconciles dynamism with stability to balance learning and reliable memory storage has not yet been fully understood. To address the critical question, we longitudinally recorded place cells in the hippocampal dorsal CA1 region over 7 to 56 days, utilizing multiple goal-oriented navigation paradigms across various environments. We found that over 80% of place cells displayed multiple fields, undergoing complex evolution events including field disappearance, formation, and retention. Place fields from the same neuron showed limited coordination ([~]5%), with a preference for synchronized changes. We further uncovered the single field evolution rule: the longer a field remains active, the more likely it is to continue being active; conversely, the longer a field remains inactive, the less likely it is to recover the future fate of a place field depends on its past activity. Mathematical modeling revealed that this rule sufficiently demonstrates the growing stability of the dCA1 spatial representation at the population level.

neuroscience↗

bioRxiv2024

Nuclear FAK aggravates CD8+ T cell exhaustion via the SP1-IL-6 axis in colorectal cancer

Nuclear abnormalities such as nuclear deformation are hallmarks of many diseases, including cancer. Accumulating evidence suggests that the dense and mechanically stiff tumor microenvironment promotes nuclear deformation in cancer cells. However, little is known about how nuclear deformation in neoplastic cells regulates immune exhaustion in the tumor microenvironment. Here, we found that lamin A/C-mediated nuclear stiffening in neoplastic cells promotes the nuclear translocation of phosphorylated focal adhesion kinase (pFAK), which is strongly correlated with the heterogeneity and exhaustion of CD8+ T cells within the spatial context of the tumor microenvironment in human colorectal cancer. Mechanistically, we revealed that increased nuclear tension within tumor cells promotes pFAK nuclear translocation, where nuclear pFAK was found to regulate SP1/IL-6-mediated T-cell exhaustion and the transcription of proinflammatory cytokines/chemokines. Pharmacological inhibition or disruption of pFAK nuclear translocation enhanced antitumor immune responses and synergistically potentiated PD-1 and TIM-3 immunotherapy by increasing CD8+ T-cell cytotoxicity and restoring exhaustion in preclinical models of colorectal cancer. These findings highlight the pivotal role of nuclear tension-mediated pFAK translocation into the tumor cell nucleus in regulating CD8+ T-cell exhaustion, suggesting that pFAK is a promising target for advancing cancer immunotherapy.

immunology↗

bioRxiv2024

VEHoP: A Versatile, Easy-to-use, and Homology-based Phylogenomic pipeline accommodating diverse sequences

Phylogenomics has emerged as a transformative approach in systematics, conservation biology, and biomedicine, enabling the inference of evolutionary relationships by leveraging hundreds to thousands of genes from genomic or transcriptomic data. However, acquiring high-quality genomes and transcriptomes necessitates samples with intact DNA and RNA, substantial sequencing investments, and extensive bioinformatic processing, such as genome/transcriptome assembly and annotation. This challenge is particularly pronounced for rare or difficult-to-collect species, such as those inhabiting the deep sea, where only fragmented DNA reads are often available due to environmental degradation or suboptimal preservation conditions. To address these limitations, we introduce VEHoP (Versatile, Easy-to-use Homology-based Phylogenomic pipeline), a tool designed to infer protein-coding regions from diverse inputs, including raw reads (short and long), draft genomes, transcriptomes, and annotated genomes. VEHoP automates the generation of orthologous sequence alignments, concatenated matrices, and phylogenetic trees, streamlining phylogenomic analyses for researchers across disciplines. The tool aims to (1) expand taxonomic sampling by accommodating a wide range of input data types and (2) simplify phylogenomic workflows, making them accessible to researchers with varying levels of bioinformatic expertise. We evaluated VEHoPs performance using datasets from oysters, catfish, and insects, demonstrating its ability to produce robust phylogenetic trees with strong bootstrap support, outperforming assembly-free methods. Additionally, we applied VEHoP to reconstruct the phylogeny of the enigmatic deep-sea gastropod order Neomphalida, successfully resolving a well-supported phylogenetic backbone for this poorly understood group. VEHoP is freely available on GitHub (https://github.com/ylify/VEHoP), with dependencies easily installable via Bioconda.

bioinformatics↗

bioRxiv2024

YTHDF2 upregulation and relocation dictate CD8 T cell polyfunctionality in tumor immunity

Epigenetic traits impact the antitumor function of CD8 T cells, yet whether and how RNA methylation programs engage in T cell immunity is poorly understood. Here we show that the N6-methyladenosine (m6A) RNA reader YTHDF2 is highly expressed in early effector or effector-like CD8 T cells and is partially distributed in the nucleus. YTHDF2 loss in T cells exacerbates tumor progression and confers unresponsiveness to PD-1 blockade in mice and humans. In addition to initiating RNA decay for mitochondrial fitness, YTHDF2 can orchestrate chromatin regulation to promote T cell polyfunctionality. YTHDF2-mediatd preservation of gene transcription arises from the interaction of YTHDF2 with IKZF1/3. Accordingly, immunotherapy-induced efficacy could be largely restored in YTHDF2-deficient T cells through combinational use of lenalidomide. Moreover, m6A recognition is fundamental for YTHDF2 translocation to the nucleus and autoregulation at the RNA level. Thus, YTHDF2 coordinates epitranscriptional and transcriptional networks to potentiate T cell immunity. HighlightsO_LIYTHDF2 expression and distribution underpin the threshold for bona fide CD8 T cell effector response C_LIO_LICanonical YTHDF2-mRNA decay pathway alleviates mitochondrial stress and CD8 T cell exhaustion C_LIO_LINuclear YTHDF2 sequesters IKZF1/3-mediated transcriptional repression to safeguard CD8 T cell polyfunctionality C_LIO_LIThe tumoricidal activity of YTHDF2-deficient CD8 T cells could be repaired through the synergy of anti-PD-1 and lenalidomide C_LI

immunology↗

bioRxiv2024

Olfactory basis for essential amino acid perception during foraging in Caenorhabditis elegans

Acquisition of essential nutrients through diet is crucial for the survival of animals. Dietary odors might enable animals to forage for nutrient-rich diets. We asked if Caenorhabditis elegans, a bacterivorous nematode, uses olfactory cues to forage for essential amino acid-rich (EAA) diets. Using the native microbiome of C. elegans, we show that worms rely on olfaction to select leucine (EAA)-enriched bacteria. Using gas chromatography, we find that leucine-enriched bacteria produce isoamyl alcohol (IAA) odor in the highest abundance. Prior adaptation of worms to IAA diminishes the diet preference of worms. Several wild isolates of C. elegans display robust responses to IAA emphasizing its ecological relevance. We find that foraging for a leucine-enriched diet is mediated via the AWC olfactory neurons. Finally, we identify SNIF-1 G protein-coupled receptor in AWC neurons as a receptor for IAA and a mediator of dietary decisions in worms. Our study identifies a receptor-ligand module underpinning foraging behavior in C. elegans.

animal behavior and cognition↗

bioRxiv2024

The microcephaly protein WDR62 regulates cellular purine metabolism through the HSP70/HSP90 chaperone machinery.

Inherited mutations in WD repeat-containing protein 62 (WDR62) are associated with microcephaly (MCPH2). While WDR62 plays important roles in mitosis and centriole biogenesis, additional WDR62 functions may cause abnormal brain growth. Here, we reveal a novel WDR62 role in the molecular chaperone network regulating purine metabolism. In response to hyperosmotic stress, WDR62 redistributes to purinosomes--phase-separated membraneless assemblies of purine metabolic enzymes and their chaperones. While WDR62 is not needed for purinosome formation, its loss disrupts purine homeostasis, resulting in the accumulation of purine nucleotide intermediates and a reduction in the levels of hypoxanthine-guanine phosphoribosyl transferase (HPRT), a key purine salvage enzyme. We link this to WDR62s interaction with Bcl2-associated athanogene 2 (BAG2), a co-chaperone that modulates the function of HSP70/90. In cells lacking WDR62, BAG2 levels are elevated and HPRT stability is reduced. Knocking down BAG2 in these cells restores HPRT levels, underscoring the crucial role of WDR62-BAG2 interactions in chaperone-mediated stability and turnover of metabolic pathway enzymes. Notably, common microcephaly-associated mutations in WDR62 alter its interaction with BAG2, suggesting that purine metabolic defects resulting from WDR62 mutations may underlie microcephaly in humans.

cell biology↗

bioRxiv2024

Integrin-deficient T cell leukemia accumulates in the central nervous system

T-cell acute lymphoblastic leukemia (T-ALL) spreads aggressively to the central nervous system (CNS), particularly the leptomeninges. Children with T-ALL are treated with high-dose, CNS-directed chemotherapy, which can cause lasting neurotoxicity and is not always effective. Little is known about how T-ALL enters and persists within the CNS. However, normal T cell migration into the CNS has been extensively studied. Two integrins--VLA-4 and LFA-1--mediate normal T cell entry to the CNS, and VLA-4 blockade effectively treats multiple sclerosis by excluding T cells from the brain. We hypothesized that these integrins would likewise be required for T-ALL CNS entry. Unexpectedly, not only were VLA-4 and LFA-1 dispensable for T-ALL to reach the CNS, integrin-deficient T-ALL accumulated in the CNS compared to control. Mechanistically, integrin loss accelerated T-ALL proliferation in the CNS, suggesting that integrin-mediated interactions may promote quiescence in this space. Integrin blockade synergized with chemotherapy targeting proliferating cells, raising the possibility that combination therapy might be a powerful strategy.

immunology↗

bioRxiv2024

Down regulation of Engase in Caenorhabditis elegans may improve its stresses adaptivity

Endo-beta-N-acetylglucosaminidase (ENGASE) is one of the key enzymes involved in the regulation of structure and function of glycoproteins. It is conserved from prokaryotic to eukaryotic cells. Although their activities in vitro and applications have been well studied, the biological function of ENGASE remains to be illustrated. In this study, we analyzed the molecular and physiological function of Engase from Caenorhabditis elegans homolog eng-1(CeEngase). We found that CeEngase knockout or knockdown increased the environmental stresses adaptability, such as heat stress and osmotic stress. Preliminary glycomics analysis showed that the basement membrane proteins of extracellular matrix may be the main targets of CeENGASE. In addition, CeENGASE may selectively prefer to N2H7 glycans on glycoproteins. In conclusion, our data illustrated that the defection and/or down regulation of CeEngase may provide a beneficially adaptation for stresses.

biochemistry↗

bioRxiv2024

Eco-evolutionary Guided Pathomic Analysis to Predict DCIS Upstaging

Cancers evolve in a dynamic ecosystem. Thus, characterizing cancers ecological dynamics is crucial to understanding cancer evolution and can lead to discovering novel biomarkers to predict disease progression. Ductal carcinoma in situ (DCIS) is an early-stage breast cancer characterized by abnormal epithelial cell growth confined within the milk ducts. In this study, we show that ecological analysis of hypoxia and acidosis biomarkers can significantly improve prediction of DCIS upstaging. First, we developed a novel eco-evolutionary designed approach to define habitats in the tumor intraductal microenvironment based on oxygen diffusion distance. Then, we identified cancer cells with metabolic phenotypes attributed to their habitats, including CA9 for hypoxia responding phenotype, and LAMP2b for acid adapted phenotype. Traditionally these markers have shown limited predictive capabilities for DCIS progression, if any. However, when analyzed from an ecological perspective, their power to differentiate between non-upstaged and upstaged DCIS increased significantly. Second, we discovered distinct niches with spatial patterns of these biomarkers and used the distribution of such niches to predict patient upstaging. The niches were characterized by pattern analysis of both cellular and spatial features. With a 5-fold validation on the biopsy cohort, we trained a random forest classifier to achieve the area under curve (AUC) of 0.74. Our results affirm the importance of tumor ecological features in eco-evolutionary-designed approaches for novel biomarkers discovery. SignificanceOur results affirm the importance of spatial and ecological features in eco-evolutionary-designed biomarkers discovery studies in the era of digital pathology.

cancer biology↗

bioRxiv2024

Bilingual language processing relies on shared semantic representations that are modulated by each language

Billions of people throughout the world are bilingual, and they can extract meaning from multiple languages. While some evidence suggests that there is a shared system in the human brain for processing semantic information from native and non-native languages, other evidence suggests that semantic processing is language-specific. We conducted a study to determine how semantic information for different languages is represented in the brains of bilinguals. Functional magnetic resonance imaging (fMRI) was used to record brain responses while participants read several hours of natural narratives in their native (Chinese) and non-native (English) languages. These data were then used to compare semantic representations between the two languages. We find that semantic representations are largely shared between languages, but that there are fine-grained differences in the representation of some semantic categories across languages. These results reconcile current competing theories of bilingual language processing. Significance StatementBilinguals understand the meaning of words in multiple languages. Whether this capacity reflects a shared brain system for processing both native and non-native languages, or whether processing is language-specific is still unclear. Here, we examine whether and how semantic representations in the brain support shared and/or language-specific processing. We recorded brain activity from participants reading narratives in their native (Chinese) and non-native (English) languages, and modeled how their brains represent word meaning in each language. We show that semantic representations are similar between the two language conditions, and that these representations are systematically modulated between native and non-native language comprehension.

neuroscience↗

bioRxiv2024

Digital Immunoassay for Rapid Detection of SARS-CoV-2 Infection in a Broad Spectrum of Animals

The ability of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) to infect a wide-range of species raises significant concerns regarding both human-to-animal and animal-to-human transmission. There is an increasing demand for highly sensitive, rapid, and simple diagnostic assays that can detect viral infection across various species. In this study, we developed a biosensor assay that adapted a monoclonal-antibody (mAb)-based blocking ELISA format into an Activate Capture + Digital Counting (AC + DC)-based immunoassay. The assay employs a photonic crystal (PC) biosensor, gold-nanoparticle (AuNP) tags, SARS-CoV-2 nucleocapsid (N) protein, and specific anti-N mAb to detect antibody responses in animals exposed with SARS-CoV-2. We demonstrated a simple 2-step 15-min test that was capable of detecting as low as 12.5 ng of antibody in controlled standard serum samples. Based on an evaluation of 176 cat serum samples with known antibody status, an optimal percentage of inhibition (PI) cut-off value of 0.588 resulted in a diagnostic sensitivity of 98.3% and a diagnostic specificity of 96.5%. The test is highly repeatable with low variation coefficients of 2.04%, 2.73%, and 4.87% across different runs, within a single run, and on a single chip, respectively. The test was further employed to detect antibody responses in multiple animal species as well as investigate dynamics of antibody response in experimentally infected cats. This test platform provides an important tool for rapid field surveillance of SARS-CoV-2 infection across multiple species.

microbiology↗

bioRxiv2024

Chemically induced cell plasticity enables the generation of high-fidelity embryo model

Embryo models open exciting opportunities for improving our understanding of development and advancing medicine. However, current models depend on intricate procedures and the integration of separately generated cell types. Here, we aimed to establish a chemical-only strategy to induce cellular plasticity and generate embryo founder-like cells. Within 60 hours, chemical-induced pluripotent stem cells activated early lineage specifiers, Cdx2 and Gata6, while maintaining Oct4/ Pou5f1 expression. Following a second 36-hour chemical treatment, founder-like cells developed into all blastocyst fates and self-assembled into embryo-like structures. These progressed into high-fidelity late-streak gastrulation stages within 4.5 days, displaying primitive streak formation via epithelial-to-mesenchymal transition, along with germ-layer tissues, amnion, and ectoplacental cone. Fate trajectories and molecular signatures from founder-like cells to chemically-induced embryo model (ci-MO) were defined, revealing remarkable similarity up to Embryonic day (E) 7.5 embryo. Summarily, ci-MO offers a straightforward, rapid, small-molecule-only, and high-fidelity approach to study embryonic development and cell fate specification. HighlightsO_LIGeneration of a direct, efficient, and sophisticated chemically induced embryo model (ci-MO) C_LIO_LITwo-pulse chemical induction reprograms ESCs into founder-like cells capable of developing all embryo fates C_LIO_LIGastrulating ci-MOs display high morphological and molecular accuracy C_LIO_LIci-MOs reconstruct embryo developmental trajectories C_LI

cell biology↗

bioRxiv2024

Comparative Analysis of Commercial Single-Cell RNA Sequencing Technologies

This study evaluates ten commercially available single-cell RNA sequencing (scRNA-seq) approaches across four technology groups: Emulsion-based kits from 10x Genomics and Fluent Biosciences; Microwell-based kits from Becton Dickinson, Honeycomb Technologies and Singerlon Technologies; Combinatorial-indexing kits from Parse Biosciences and Scale Biosciences; and a Matrigel-based kit from Scipio Biosciences. Peripheral blood mononuclear cells (PBMCs) from a single donor were used to assess analytical performance. Key features such as sample compatibility, cost, and experimental duration were also compared. Notably, superior analytical performance was demonstrated by the Chromium Fixed RNA Profiling kit from 10x Genomics, which uniquely features probe hybridization for transcript detection. Additionally, the Rhapsody WTA kit from Becton Dickinson provided a cost-effective balance of performance and expense per cell. With a rich dataset of 218,154 cells, this work provides a basis for differentiating commercial scRNA-seq technologies, which is intended to facilitate the effective application and further methodological development of single cell transcriptomics.

molecular biology↗

bioRxiv2024

node2vec2rank: Large Scale and Stable Graph Differential Analysis via Multi-Layer Node Embeddings and Ranking

1Advances in computational biology now enable the inference of increasingly accurate, genome-wide molecular interaction networks from multi-omic data collected across large cohorts. Comparing such networks across distinct biological states can identify biologically informative and potentially actionable higher-order interactions that differentiate these states. However, developing methods for effective graph differential analysis remains challenging as it requires capturing subtle structural changes within the context of complex, high-dimensional networks shaped by heterogeneous biological processes. We introduce node2vec2rank (n2v2r), a multi-layer spectral embedding algorithm that, in contrast to conventional feature-based approaches, compares graphs by inferring node representations that summarize network structure in a data-driven manner. Node2vec2rank is computationally efficient, stable, and provably recovers the correct ranking of differences between weighted graphs. We used n2v2r to compare networks from breast cancer subtypes, to analyze networks capturing single-cell dynamics, and to investigate sex differences in lung adenocarcinoma. The results of these analyses show that n2v2r is a versatile and powerful tool that can uncover biologically relevant insights from complex biological networks, distinguishing between states of health and disease.

bioinformatics↗