Biology subjects

Nan, F.

Publications and source records attributed to Nan, F..

9 recordsLinked to original sources

bioRxiv2026

Circular RNA aptamers act as superb sub-stoichiometric chaperones to prevent cytosolic TDP-43 condensation

Pathological protein misfolding and aggregation underlie many devastating human diseases, yet strategies to selectively neutralize aggregation-prone protein states without perturbing their normal functions remain limited. Here we identify loosely structured circular RNA (cRNA) aptamers, circT3 and its minimized 116-nt variant circT3-M3, as superb sub-stoichiometric RNA chaperones that suppress pathological assembly of TAR DNA-binding protein 43 (TDP-43), a defining feature of amyotrophic lateral sclerosis and frontotemporal dementia, in vitro and in cells. Rather than acting through simple stoichiometric sequestration, these cRNA aptamers engage TDP-43 transiently and iteratively through functionally and pathologically important residues in the RRM1 domain. Such interaction enables a single cRNA aptamer to promote rapid and multiple RRM1-dependent homomeric assembly, thereby stabilizing TDP-43 in a soluble oligomeric state to outcompete the C-terminal prion-like domain-driven condensation and supersaturation. Together, our findings establish cRNA aptamers as highly efficient subcellular RNA chaperones with exceptionally potent low-dose activity and highlight their promise as next-generation RNA therapeutics for certain protein-aggregation disorders.

molecular biology↗

bioRxiv2026

Partitioning Fraction of Variance Explained into Strong Localized Effects and Weak Diffuse Effects

High-dimensional genetic data present substantial challenges for estimating the fraction of variance explained (FVE) by genome-wide single-nucleotide polymorphisms (SNPs). In the context of genetics the VFE is called SNP heritability. Standard approaches for FVE estimation, such as GWAS heritability (GWASH) and linkage disequilibrium score (LDSC) regression, typically assume Gaussian distributions for SNP effect sizes. However, empirical evidence indicates that SNP effects are often heavy-tailed, with a small subset of variants exerting disproportionately large influence. Such settings violate the recently established bounded-kurtosis effect (BKE) condition, under which these FVE estimators are consistent. Consequently, widely used methods may yield severely biased estimates when strong effects are present. We introduce a decomposed FVE estimation framework that accommodates heavy-tailed and heterogeneous SNP effect distributions. The proposed approach partitions total heritability into contributions from strong and weak genetic effects, estimating the former using low-dimensional adjusted R2 and the latter using an extension of FVE estimation methodology that remains valid under BKE compliance. We further develop a test for detecting violations of the BKE condition and compare several high-dimensional screening procedures for identifying strong-effect SNPs when they are not known in advance. Simulation studies show that the proposed decomposition substantially improves estimation accuracy over existing approaches in the presence of heavy-tailed effects. Application to the Adolescent Brain Cognitive Development (ABCD) Study demonstrates the practical utility of the method, yielding more reliable heritability estimates for the PolyVoxel Score, a neuroimaging-based biomarker linked to iron accumulation. Our results highlight the importance of accommodating effect heterogeneity in large-scale genomic studies.

genetics↗

bioRxiv2025

Dual Transcriptional Drivers of Immune Suppression in SACC: NOTCH1 for Cellular and MYB for Humoral Immunity

As a classic immune-"cold" tumor, salivary adenoid cystic carcinoma (SACC) represents a significant clinical challenge. Through sequencing analyses, we identify profound systemic immune dysregulation in SACC, characterized by suppressed hematopoiesis, T-cell exhaustion, compensatory myelopoiesis, and an expanded immature B-cell compartment. While lung metastases exhibit a relatively immune-engaged microenvironment enriched in tissue-resident T cells, these sites remain dominated by immature B cells. Mechanistically, this hematopoietic dysfunction originates from direct disruption of tumor-derived signaling entering the circulation, supported by detection of the SACC-signature MYB-NFIB fusion gene in peripheral plasma and blood cells. At the molecular level, we discover that IL17RB/OLIG1/NOTCH1 signaling pathways engage in multicellular crosstalk via IL33 or TP53 to suppress T-cell activation in primary tumors. Moreover, at lung metastatic sites, the MYB/MYBL2-NOTCH1-CXCL13-CXCR5 axis is blocked through CD24 or IL17RB, thereby inhibiting B-cell maturation. Single-cell transcriptomic profiling further identifies cancer stem cells (CSCs) exhibiting dual characteristics of cell-cycle activity and immune progenitor features, a finding that clarifies the fundamental mechanism by which these cells evade immune surveillance. In conclusion, we propose that stem cell camouflage constitutes the core mechanism underlying bone marrow hematopoietic dysfunction and drives immune evasion in SACC. These findings highlight the IL17RB-NOTCH1 signaling axis as a promising therapeutic target, offering potential to overcome the long-standing challenges associated with NOTCH1-targeted therapies in this malignancy. SignificanceOur novel transcriptomic analysis revealed a key G2M/CLP dual-progenitor state in SACC immunocold tumors. Tracing its origin to hematopoietic differentiation, we uncovered a NOTCH1-mediated dual-hit mechanism: restricting antigen presentation to silence T cells while partnering with MYB to block B-cell maturation. This finding pinpoints a root cause of immune evasion and establishes this pathway as a central therapeutic target. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/688163v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@18c22a2org.highwire.dtl.DTLVardef@135e381org.highwire.dtl.DTLVardef@eb4eadorg.highwire.dtl.DTLVardef@7a51c4_HPS_FORMAT_FIGEXP M_FIG C_FIG Dichotomous gene mapping and single-cell interactome reveal the microenvironmental specificity of NOTCH1/MYB regulation of T/B-cell differentiation and its distinct signaling flows.

immunology↗

bioRxiv2025

Transcriptional Subtypes on Immune Microenvironment and Predicting Postoperative Recurrence and Metastasis in Pheochromocytoma and Paraganglioma

Pheochromocytomas and paragangliomas (PPGLs) exhibit substantial molecular and immune heterogeneity, complicating risk assessment and treatment. Here, we define three distinct transcriptional subtypes (C1, C2, C3) through integrative transcriptomic and immunogenomic profiling. C1 is characterized by hypoxia-driven pathways and an immunosuppressive microenvironment, correlating with poor prognosis. C2 exhibits a highly inflamed immune landscape with robust CD8+ T cell infiltration, suggesting potential sensitivity to immunotherapy. C3 is enriched in metabolic reprogramming pathways and displays intermediate clinical outcomes. Genetic analysis reveals subtype-specific mutational patterns, with pseudohypoxic driver mutations (SDHB, VHL, SDHA, SDHD) predominant in C1 and C3, while kinase pathway alterations (NF1, RET) define C2. Single-nucleus RNA sequencing further delineates immune ecosystem diversity. Notably, we identify ANGPT2, PCSK1N, and GPX3 as key subtype-specific biomarkers, with ANGPT2 driving tumor progression in C1 and emerging as a potential therapeutic target. Our findings provide a refined molecular classification integrating immune and genomic features, offering a framework for improved prognostication and precision therapies in PPGLs.

cancer biology↗

bioRxiv2024

Development of a novel peripherally acting alpha2A-adrenergic receptor antagonist for anti-diabetic

Yohimbine, a potent alpha2A-adrenergic receptor (2AAR) antagonist, was found therapeutic potential for type 2 diabetes through improving insulin release. However, the adverse side effects mediated by its actions in the brain hampered its use. Here, based on molecular docking analysis and structural modification, we have developed a novel peripherally acting yohimbine derivative (CDS479-2). CryoEM data found that yohimbine and CDS479-2 have similar interactions with the structure of 2AAR. Importantly, CDS479-2 shows similar 2AAR antagonist activity as yohimbine, but with very limited access to the brain, and thus avoiding the unwanted central effects such as hypertension and anxiety. Acute administration of CDS479-2 by injection or gavage lowered blood glucose levels and improved glucose tolerance in the high-fat diet-induced obesity (DIO) mice, an animal model for human type 2 diabetes. Remarkably, DIO mice received 2 weeks of daily administration of CDS479-2, but not yohimbine, exhibited sustained normoglycaemia, and increased density of the insulin-producing beta cells, in which important proliferation genes were found upregulated. Moreover, the overall protein expression levels of their pancreas were more similar to that of the healthy chow-fed mice. Thus, CDS479-2 may indicate a new direction for type 2 diabetes treatment. Importantly, the strategy we employed in this study will inspire the optimization for drugs that with both peripheral and central targets. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/628818v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1d3d7corg.highwire.dtl.DTLVardef@1afbad3org.highwire.dtl.DTLVardef@12a1aborg.highwire.dtl.DTLVardef@1341a02_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2023

A deep learning model embedded framework to distinguish DNA and RNA mutations directly from RNA-seq

We develop a stepwise computational framework, called DEMINING, to directly detect expressed DNA and RNA mutations in RNA deep sequencing data. DEMINING incorporates a deep learning model named DeepDDR, which facilitates the separation of expressed DNA mutations from RNA mutations after RNA-seq read mapping and pileup. When applied in RNA-seq of acute myeloid leukemia patients, DEMINING uncovered previously-underappreciated DNA and RNA mutations, some associated with the upregulated expression of host genes or the production of neoantigens. Finally, we demonstrate that DEMINING could precisely classify DNA and RNA mutations in RNA-seq data from non-primate species through the utilization of transfer learning.

bioinformatics↗

bioRxiv2021

Complexin-1 regulated transition in the assembly of single neuronal SNARE complex

Neurotransmitter release is mediated by the synaptic vesicle exocytosis. Important proteins in this process have been identified including the molecular machine Synaptic-soluble N-ethylmaleimide-sensitive factor attachment receptor (SNARE) proteins, and other regulators. Complexin (Cpx) is one of the vital regulators in this process. The functions of Cpx are proposed to maintain a proper primed vesicle pool by preventing its premature depletion, which facilitates the vesicle fusion in the presence of Ca2+. However, the molecular mechanism remains unclear. Using dual-trap optical tweezers, we detected the interaction of complexin-1 (CpxI) with SNARE. We found that the CpxI stabilizes partially folded SNARE complexes by competing with C-terminal of Vamp protein and interacting with the C-terminal of t-SNARE complex.

biophysics↗

bioRxiv2021

SCAPTURE: a deep learning-embedded pipeline that captures polyadenylation information from 3' tag-based RNA-seq of single cells

Single-cell RNA-seq (scRNA-seq) profiles gene expression with a resolution that empowers depiction of cell atlas in complex systems. Here, we developed a stepwise computational pipeline SCAPTURE to identify, evaluate, and quantify cleavage and polyadenylation sites (PASs) from 3 tag-based scRNA-seq. SCAPTURE detects PASs de novo in single cells with high sensitivity and accuracy, enabling detection of previously unannotated PASs. Quantified alternative PAS transcripts refine cell identities, enriching information extracted from scRNA-seq.

bioinformatics↗

bioRxiv2020

Structural basis of bile acid receptor activation and Gs coupling

G protein-coupled bile acid receptor (GPBAR) is a membrane receptor that senses bile acids to regulate diverse functions through Gs activation. Here, we report the cryo-EM structures of GPBAR-Gs complexes stabilized by either high-affinity P395 or the semisynthesized bile acid derivative INT-777 at 3-[A] resolution. These structures revealed a large oval-shaped ligand pocket with several sporadic polar groups to accommodate the amphipathic cholic core of bile acids. A fingerprint of key residues recognizing diverse bile acids in the orthosteric site, a putative second bile acid binding site with allosteric properties and structural features contributing to bias property were identified through structural analysis and mutagenesis studies. Moreover, structural comparison of GPBAR with other GPCRs uncovered an atypical mode of receptor activation and G-protein- coupling, featuring a different set of key residues connecting the ligand binding pocket to the Gs coupling site, and a specific interaction motif localized in intracellular loop 3. Overall, our study not only provides unique structural features of GPBAR in bile acid recognition, allosteric effects and biased signaling, but also suggests that distinct allosteric connecting mechanisms between the ligand binding pocket and the G protein binding site exist in the GPCR superfamily.

biochemistry↗