Biology subjects

Lin, R.

Publications and source records attributed to Lin, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Liver sinusoid constraints make random search of CD8 T cells for Plasmodium parasites efficient

A relatively small number of liver-localized CD8 T cells can provide sterilizing protection against exposure to Plasmodium sporozoites. Previously published mathematical model-based simulations of randomly searching for an infection T cells, assuming that T cells move in open (3D) space or on a regular lattice, suggested that some degree of attraction is needed for cells to find the infection. Yet, in our previous experiments we failed to find evidence of attraction towards the infection in most T cells. Because the movement of liver-localized T cells is confined to sinusoids, the blood vessels of the liver, T cells may in fact be attracted to the infection site via the sinusoids. In new experiments we imaged Plasmodium-specific CD8 T cells, sporozoites, and liver sinusoids simultaneously. We also developed a new method to model imaged sinusoids as graphs and to simulate movement of T cells on graphs, and new tests to detect biased cell movement on graphs. As before, our previously published open space/3D-based metric suggested that few T cells are attracted to the infection site in presence of moderate cluster of T cells. However, with our new graph-based metric we could not detect attraction when constraining T cell movement to sinusoids. Surprisingly, simulations of T cells searching for an infection via liver sinusoids showed that a relatively small number of T cells (1 cell/imaging volume or <10^5 cell/liver), moving without attraction at experimentally observed speeds, is sufficient to find the infection within 24 hours, well below the expected lifespan of the Plasmodium liver stage in mice. Our results suggest that the constrained environment of the tissue structure makes a random search more effective, and that detecting T cell attraction towards specific areas may arise as an artifact of metrics designed for open space/3D. Our results thus call for a re-evaluation of the implicit assumption that attraction is necessary for T cells to find infections in tissues.

immunology↗

bioRxiv2025

Detection of protein symmetry and structural rearrangements using secondary structure elements

Many proteins exhibit a degree of internal symmetry in their tertiary structure, including circular permutations. These characteristics play an important role in terms of the functional robustness of proteins against mutations, and are pivotal for the study of protein function and evolution. Proteins exhibiting internal symmetry often demonstrate enhanced functional benefits, such as increased binding affinity due to repeated structural motifs, and evolutionary advantages that may result from gene duplication or fusion events, leading to more robust and adaptable molecular architectures. Similarly, circular permutations have been linked to improved catalytic activity and enhanced thermostability, opening new avenues in the design of enzymes and other functional proteins. In this study, we introduce a novel computational pipeline that leverages secondary structure elements (SSEs) as a compressed yet informative representation of protein structure to detect both symmetry and structural rearrangements effectively. Our method shows strong advantages against the Combinatorial Extension with Circular Permutations (CECP) for computational cost and identifies 17,130 circularly related proteins. Additionally, it detects 26,739 proteins associated with indel mutations. Notably, 8,855 of these exhibit both circular permutation and indel mutations-highlighting a potential co-evolutionary relationship between these two types of structural variation. We also recovered most symmetric proteins identified by the CE-symm tool and revealed more than 2.5 times as many symmetric proteins in the same dataset. By integrating precise boundary detection, clustering analysis, and rigorous cross-validation against established tools, our framework robustly maps internal structural features. These insights deepen our understanding of protein architecture and evolution, and can also inform de novo protein design and engineering.

bioinformatics↗

bioRxiv2025

Compression of protein secondary structures enables ultra-fast and accurate structure searching

Protein structure prediction has undergone a revolution with the advent of AI-based algorithms, such as AlphaFold and RoseTTAFold. As a result, over 200 million predicted protein structures have been published. This wealth of structural data has created a need for rapid structure comparison algorithms, such as Foldseek, which enable efficient searches across this vast space of protein structures. Here we introduce a new ultra-compact representation of protein structure in the form of Secondary Structure Elements (SSEs). These are short sequences around 8% of the length and with 10% of the information content of full amino acid sequences and 3Di sequences. We show that, despite this compression factor, SSEs can be used as a highly effective tertiary structure comparison tool, with accuracy that approaches that of Foldseek, while offering a 200-fold speedup. In addition SSEs offer comparable performance to Foldseek in domain boundary retrieval. Furthermore we show that the particular way in which SSEs encode structure can also be used to specifically detect proteins that differ due to conformational change. These findings demonstrate that SSEs offer a valuable complementary approach for protein structure characterisation.

bioinformatics↗

bioRxiv2025

Genetics-to-structure multiscale analysis identifies disrupted calcium homeostasis as a mechanism of psychiatric disease

Neuropsychiatric disorders are highly heritable, but the molecular mechanisms linking risk variants to disease remain unclear1. Linking genetics to biological mechanisms requires integrating evidence across scales, from sequence variation to gene regulation to protein function. Here we integrate genetic, transcriptomic, and structural evidence to identify dysregulation of neuronal Ca2+ dynamics as a contributing mechanism. We analyzed single-nucleus neuronal RNA-seq data together with genome-wide association study (GWAS) heritability in a new way to identify gene expression programs enriched for psychiatric risk; genes encoding Ca2+ flux pathway genes were implicated by this analysis, a result that was then confirmed by concentrations of rare coding variants in these same genes in persons with psychiatric disorders. A critical gene in this biology, ATP2B2, encodes a Ca2+-extruding ATPase pump2 linked to neuropsychiatric disorders primarily through missense variants. To recognize specific molecular functions affected by these missense variants, we developed a 3D-neighborhood-based method that maps missense variants onto AlphaFold3-predicted protein structures and tests clustering of protein-altering variants in three-dimensional space. This approach revealed clustering of these missense changes in the Ca2+ pore and ATP:Mg2+ coordination site of ATP2B2. To validate the structural predictions arising from the genetic analysis, we determined the structure of human Ca2+-bound ATP2B2 at 2.64 [A] resolution by cryogenic electron microscopy. The structure replicated the 3D mutational hotspots identified by the genetic analysis, supporting the observation that neuropsychiatric variants cluster near specific catalytic sites of ATP2B2. In vitro experiments revealed that missense variants prioritized by the structural clustering analysis impaired ATP2B2-mediated Ca2+ extrusion in cellular and biochemical assays. Together, these findings suggest that precise regulation of Ca2+ dynamics is a contributing mechanism in neuropsychiatric disorders and establish a structure-based framework for predicting the mechanistic impact of missense variants.

genetics↗

bioRxiv2025

A new dual-affinity peptide nucleic acid for targeting miRNA-21 precursor rescues tumor repressor PTEN expression

MicroRNAs (miRNAs) have multiple functions in cells and are related to many diseases including cancer by regulating posttranscriptional gene expression. The microRNA precursors (pre-miRs), which can be cleaved by Dicer endonuclease to produce mature miRNAs, often have a cleavage site consisting of both double-stranded (ds) and single-stranded (ss) RNA structures. Peptide nucleic acid (PNA) is a kind of analogue of DNA which can hybridize to DNA or RNA through Watson-Crick and Hoogsteen pairing. We previously reported a novel dual-affinity PNA (daPNA) platform that can simultaneously form a duplex and a triplex with a target RNAs ssRNA-dsRNA junction region. The PNA-RNA complex structure is stabilized by forming antisense PNA (asPNA)-ssRNA duplex immediately adjacent to a chemically modified dsRNA-binding PNA (dbPNA)-dsRNA triplex. In this study, we further explored the application of the daPNA platform to target the precursor of miR-21, which is considered an oncogene. We have designed a set of PNAs including asPNAs, dbPNAs, and daPNAs. The nondenaturing polyacrylamide gel electrophoresis (PAGE) and biolayer interferometry (BLI) data reveal that daPNA-21-10 can strongly bind to pre-miR-21 with high specificity. The data show that pre-miR-21 is easily targeted by traditional antimir, asPNA or dbPNA and optimization of the dsRNA-ssRNA junction position is needed for identifying a tightly binding daPNA. Furthermore, daPNA-21-10 not only inhibits the Dicer activity on pre-miR-21 in cell-free assays, but also down-regulates the expression of miR-21, rescuing PTEN protein expression in cells. Taken together, the biofunction and programmability of daPNA make it a promising platform for probing and regulating miRNA biogenesis and many other RNA-involved biological processes. HighlightsO_LISimultaneous recognition of dsRNA and ssRNA regions C_LIO_LIRNA targeting by dividing and conquering through a dsRNA-ssRNA junction construction C_LIO_LISubstrate-specific inhibition of Dicer acting on pre-miR-21 C_LIO_LIDerepressing PTEN expression by inhibiting miR-21 maturation C_LI O_FIG O_LINKSMALLFIG WIDTH=170 HEIGHT=200 SRC="FIGDIR/small/668835v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@c8af64org.highwire.dtl.DTLVardef@172d2bdorg.highwire.dtl.DTLVardef@1698ea1org.highwire.dtl.DTLVardef@112fa16_HPS_FORMAT_FIGEXP M_FIG C_FIG eToc BlurbLian et al. show that the miR-21 precursor structure containing the Dicer cleavage site can be targeted by a new type of dual-affinity peptide nucleic acids (daPNAs) through the creation of a dsRNA-ssRNA junction, energetically optimized for the simultaneous duplex and triplex formation. Pre-miR-21 structure, which is hardly accessible to traditional antisense strategies and triplex formation alone, can be targeted by a daPNA with high sequence/structure specificity and strong binding affinity. daPNA platform has a great potential in probing many other RNA structures and broad therapeutic applications.

molecular biology↗

bioRxiv2025

Towards the Development of Isoenergetic Peptide Nucleic Acid Based Probes Targeting Double-Stranded RNAs Through Enhancing Sequence-Specific Stacking Interactions

Peptide nucleic acid (PNA), a synthetic nucleic acid analog, exhibits substantial potential in biotechnology and therapeutic applications due to its high binding affinity and nuclease/protease resistance. Chemically modified PNAs capable of forming stable triplex structures with double-stranded RNAs (dsRNAs) under near-physiological conditions further expand their utility by enabling sequence-specific precise targeting and probing of functional RNA structural motifs. However, the presence of inverted Watson-Crick pairs (C-G and U-A) may significantly weaken the triplex formation of the dsRNA-binding PNAs (dbPNAs). Our previous work demonstrated that dbPNA P3 (composed of L, T, and Q monomers for the recognition of G-C, A-U, and C-G base pairs, respectively) can stimulate ribosomal frameshifting by binding to rHP2, a model RNA hairpin structure in an mRNA, albeit with suboptimal efficiency, due to its significantly weakened Q*C-G triple formation. We hypothesize that incorporating s2U adjacent to Q may offer unique stacking and hydrogen bonding interactions facilitating the development of isoenergetic dbPNA-based probes binding toward dsRNAs with varied sequences. In this study, we investigate how incorporating s2U adjacent to Q residues in P3 influences its binding to rHP2. Bio-layer interferometry (BLI) and non-denaturing polyacrylamide gel electrophoresis (PAGE) analyses demonstrate that substituting T with s2U at the N-terminal position adjacent to Q (P3-2QT) enhances binding affinity by [~]10-fold compared to unmodified P3, whereas C-terminal substitution (P3-TQ2) yields only a 2-fold improvement. Consistent with these findings, a cell-free dual-luciferase reporter assay reveals that P3-2QT significantly increases ribosomal frameshifting efficiency compared to P3 and P3-TQ2. Molecular dynamics simulations further indicate that P3-2QT maintains enhanced PNA-PNA stacking stability, particularly between s2U3 and Q4, suggesting a structural basis for its superior activity. Intriguingly, analogous s2U substitution in the P5 oligomer with the Q replaced by L does not confer a comparable enhancement in binding to the target RNA (rHP1) and frameshifting stimulation, highlighting the context-dependent nature of this modification. To assess the broader applicability of the s2U-Q motif, we examined its effect in dbPNAs targeting the RNA panhandle structure of influenza virus A and precursor microRNA-21, respectively. Both PAGE and BLI data confirm that s2U incorporation improves binding affinity, reinforcing the generality of this strategy. These findings underscore the potential of sequence-dependent uracil thiolation in optimizing triplex-forming dsRNA-binding PNAs, warranting further exploration of modified nucleobase designs to enhance their binding and functional properties. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/662161v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@15d86aborg.highwire.dtl.DTLVardef@1347369org.highwire.dtl.DTLVardef@852040org.highwire.dtl.DTLVardef@84b0a_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThiolation of uracil upstream of Q base in PNA markedly enhances triplex binding affinity and enables isoenergetic and orthogonal targeting/activation. C_LIO_LIN-terminal s2U modification adjacent to Q residues increases PNA-dsRNA binding by [~]10-fold and significantly boosts ribosomal frameshifting efficiency. C_LIO_LIBiophysical assays and molecular dynamics simulations reveal that thiolation improves PNA stacking stability and slows dissociation, thereby enhancing functional activity toward structured RNA targets. C_LIO_LIThe general applicability of s2U modification is demonstrated with influenza A virus RNA panhandle structure and precursor micoRNA-21 targets, underscoring its broad potential for optimizing PNA-based therapeutics and biotechnological tools. C_LI

biochemistry↗

bioRxiv2025

The effects of E. granulosus PSCs proteins on host immune cells were elucidated through Transcriptomic and Metabolomic analyses

BackgroundEchinococcus granulosus (E. granulosus), a causative agent of zoonotic diseases, is widely prevalent across most regions and primarily affects vital organs such as the liver and lungs. The parasite secretes immunomodulatory substances, and its protoscolex proteins (PSCs) have been identified as potential diagnostic antigens and vaccine candidates. Although transcriptomics and metabolomics approaches have been employed to investigate echinococcosis, the impact of PSCs on the functionality of host immune cells and the expression of immunomodulatory-related genes remains largely unexplored. MethodsIn this study, immunofluorescence analysis was employed to determine the binding of PSCs to lymphocytes. The CCK-8 assay was utilized to evaluate the impact of varying concentrations of PSCs on cell viability, while ELISA was performed to quantify the levels of cytokines such as IL-9 and IL-4. Furthermore, by integrating LC-MS/MS-based metabolomics and RNA-Seq-based transcriptomics technologies, a systematic analysis was conducted to investigate the metabolic reprogramming and differential gene expression in lymphocytes following PSCs treatment, thereby elucidating the molecular mechanisms underlying its immune regulatory effects. ResultsPSCs proteins inhibited lymphocyte proliferation in a concentration-dependent manner, promoted IL-9 secretion at low concentrations, enhanced IL-4 expression at medium concentrations, and continuously up-regulated TGF-{beta} with increasing concentrations. Transcriptomic analysis identified 1,840 differentially expressed genes (991 up-regulated and 849 down-regulated), and KEGG enrichment analysis highlighted metabolic pathways, including phenylalanine metabolism. Gene Ontology (GO) analysis revealed that the functions of these genes were primarily associated with immunometabolic reprogramming and regulation of the intestinal barrier. Metabonomic profiling detected 12 significantly altered metabolites (8 up-regulated and 4 down-regulated). These findings suggest that PSCs reshape the host immune microenvironment via a metabolic-gene network. This study systematically elucidates how PSCs regulate immune cell function and metabolic homeostasis through multiple targets, providing novel insights into the immune escape mechanisms of parasites. ConclusionPSCs can induce host immune metabolic reprogramming, characterized by the activation of pyrimidine metabolism and the inhibition of bilirubin-mediated oxidative stress, through concentration-dependent regulation of Th9 cytokines (IL-9, IL-4/TGF-{beta}) and suppression of the PI3K-Akt signaling pathway. This process remodels the immune tolerance microenvironment. The aim is to elucidate the molecular mechanisms underlying parasite escape via multi-dimensional immunometabolic regulation, thereby providing a novel direction for the targeted treatment of echinococcosis. Author summaryE. granulosus is a zoonotic disease that can cause space-occupying lesions in the liver, lung and other organs, seriously threaten human health and cause economic losses in animal husbandry. It evades immune attack through a variety of mechanisms.This study investigates the regulatory effects of E. granulosus PSCs on host immune cell function, with a focus on their concentration-dependent influence on Th9 cell differentiation and cytokine expression, including IL-9. Through integrative analyses of transcriptomics and metabolomics, we elucidate the molecular mechanisms underlying immunometabolic reprogramming induced by PSCs. Our findings demonstrate that at low concentrations, PSCs promote the secretion of IL-9 associated with Th9 cells, upregulate IL-4/TGF-{beta} signaling, activate pyrimidine metabolism (leading to thymidine accumulation), enhance bile secretion pathways, and increase bilirubin levels to suppress oxidative stress and T-cell function, thereby establishing an immune-tolerant microenvironment. This research provides the first comprehensive illustration of immune microenvironment remodeling mediated by PSCs via multi-omics network regulation, offering novel insights into the treatment of cystic echinococcosis and host-parasite interactions.

immunology↗

bioRxiv2025

Domain shifts in infant brain diffusion MRI: Quantification and mitigation for fODF estimation

The accurate estimation of fiber orientation distributions (fODFs) in diffusion magnetic resonance imaging (MRI) is crucial for understanding early brain development and its potential disruptions. While deep learning (DL) models have shown promise in fODF estimation from neonatal diffusion MRI (dMRI) data, the out-of-domain (OOD) performance of these models remains largely unexplored, especially under diverse domain shift scenarios. This study evaluated the robustness of three state-of-the-art DL architectures--MLP-based, Transformer-based, and U-Net/CNN-based--on fODF predictions derived from diffusion MRI data. Using 488 subjects from the developing Human Connectome Project (dHCP) and the Baby Connectome Project (BCP) datasets, we reconstructed reference fODFs from the full dMRI series using single-shell three-tissue constrained spherical deconvolution (SS3T-CSD) and multi-shell multi-tissue CSD (MSMT-CSD) to generate reference fODF reconstructions for model training, and systematically assessed the impact of age, scanner/protocol differences, and input dimensionality on model performance. Our findings reveal that U-Net consistently outperformed other models when fewer diffusion gradient directions were used, particularly with the SS3T-CSD-derived ground truth, which showed superior performance in capturing crossing fibers. However, as the number of input diffusion gradient directions increased, MLP and the transformer-based model exhibited steady gains in accuracy. Nevertheless, performance nearly plateaued from 28 to 45 input directions in all models. Age-related domain shifts were found to be less pronounced in late developmental stages (late neonates, and babies), with SS3T-CSD demonstrating greater robustness to variability compared to MSMT-CSD. To address inter-site domain shifts, we implemented two adaptation strategies: the Method of Moments (MoM) and fine-tuning. Fine-tuning consistently yielded superior results, with U-Net benefiting the most from increased target subjects. This study represents the first systematic evaluation of OOD settings in deep learning applications to fODF estimation, providing critical insights into model robustness and adaptation strategies for diverse clinical and research applications.

bioinformatics↗

bioRxiv2025

Dynamic and Heterogeneous Distribution of Trichomonasvirus Species in Trichomonas vaginalis

Trichomonasvirus (TVV) is a double-stranded RNA virus from the Pseudototiviridae family that exclusively infects Trichomonas vaginalis, the protozoan responsible for the most common non-viral sexually transmitted infection. Within the Trichomonasvirus genus, five distinct viral species have been identified, and intriguingly, a single T. vaginalis isolate can simultaneously harbor multiple TVV species. Previous studies have explored the impact of TVV infection on the physiology and virulence of T. vaginalis, yet findings remain inconsistent and often contradictory. We propose that these discrepancies stem from the heterogeneous intracellular distribution of TVV within individual cells of the same T. vaginalis isolate. To investigate this, we employed ultra-deep single-cell RNA sequencing and immunofluorescence assays to examine multiple T. vaginalis isolates. Our results revealed striking variability in the proportion of infected cells carrying the same viral species, even within a single isolate. The present study is the first to demonstrate the dynamic and non-uniform intracellular distribution of TVV at the single-cell level. These findings challenge previous assumptions and provide a new perspective on the intricate virus-host interactions between TVV and T. vaginalis, offering new avenues for further research into their complex relationship. Author SummaryTrichomonas vaginalis is a parasitic protozoan responsible for the most prevalent non-viral sexually transmitted infection worldwide. In 1985, researchers discovered a double-stranded RNA (dsRNA) virus within T. vaginalis, which was later named Trichomonasvirus (TVV). This virus is believed to influence the hosts gene expression, impacting cytoadherence, drug susceptibility, and virulence proteins. However, studies on TVV-host interaction have produced conflicting results, with some genes appearing upregulated in one experiment but downregulated in another or vice versa. We hypothesize that these inconsistencies stem from the non-uniform distribution of TVV among individual cells within the same T. vaginalis isolate. Based on the experimental data from ultra-deep single-cell sequencing and immuno-localization, our study reveals that TVVs intracellular distribution is highly heterogeneous and dynamic. These findings challenge the prevailing assumption that TVV is uniformly and statically distributed. This heterogeneity underscores the need to reassess previous research on TVV-T. vaginalis interactions, as earlier studies may have overlooked this crucial factor.

microbiology↗

bioRxiv2025

Salient objects in a scene trigger enhanced perceptual selection and memory encoding

Rapidly detecting salient objects from surrounding environments is crucial for survival. Our study demonstrates that salient objects in visual search arrays trigger von Restorff-like effects. In a search task, participants detected a tilted target bar among distractors with EEG recordings. The results revealed that salient objects elicited the largest and earliest N2pc component, reflecting early attentional selection, which enhanced multivariate decoding of target location. Importantly, early selection of highly salient targets (25{degrees} tilt) triggered a cascade of preferential processing downstream, marked by stronger P3b components, neural synchronization, and phase-amplitude coupling between low- and high-frequency activity, along with better recall performance of target orientation. The strength of memory-related activity on the current trial predicted the vigor of the next selection event, indicating that salience-driven learning influences future attentional control. Overall, object salience in spatial arrays drives a cascade of processing, facilitating rapid learning of object relevance while humans search their environment, similar to the classic demonstrations of the von Restorff effect, except the objects are distributed in space rather than time.

neuroscience↗

bioRxiv2025

Inhibition of DHODH Activates Pyroptosis and cGAS-STING Pathways to Enhance NK cell Infiltration Mediated Anti-tumor Immunity in Melanoma

Cancer cells are heavily reliant on de novo pyrimidine synthesis. Suppression of pyrimidine metabolism directly inhibits tumor growth and fosters immune activation within the tumor microenvironment. Dihydroorotate dehydrogenase (DHODH), a crucial enzyme governing de novo pyrimidine synthesis, is a critical player in this context. Inhibition of DHODH not only reverses immunosuppression but also instigates a mild innate immune response. However, the impact of DHODH inhibition on natural killer (NK) cells remains unexplored. In this study, we found that inhibition of DHODH efficiently promotes NK cells infiltration in tumors. Suppression of DHODH led to increased oxidative stress in mitochondria, the release of mtDNA, and activation of caspase 3, which in turn activated the cGAS-STING pathway and pyroptosis in cancer cells, respectively, contributing to NK cells induced antitumor immune responses in melanoma. Additionally, we developed EA6, a novel DHODH inhibitor with higher efficacy in promoting NK cells infiltration. In summary, this study underscores that modulation of pyrimidine metabolism can effectively trigger antitumor immune responses, with a specific emphasis on NK cells. This finding opens new avenues for enhancing the efficacy of targeted nucleotide metabolism in cancer therapy. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/644471v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@88d4fcorg.highwire.dtl.DTLVardef@156fe1aorg.highwire.dtl.DTLVardef@448086org.highwire.dtl.DTLVardef@152079c_HPS_FORMAT_FIGEXP M_FIG C_FIG The anti-tumor mechanisms of DHODH inhibition. Inhibition of DHODH activates cGAS-STING pathways to enhance NK cell infiltration. And the tumor-infiltrating NK cells facilitate melanoma cells pyroptosis which providing a positive feedback mechanism for DHODH-mediated anti-tumor immunity.

cancer biology↗

bioRxiv2025

CellScope: High-Performance Cell Atlas Workflow with Tree-Structured Representation

Single-cell sequencing enables comprehensive profiling of individual cells, revealing cellular heterogeneity and function with unprecedented resolution. However, current analysis frameworks lack the ability to simultaneously explore and visualize cellular hierarchies at multiple biological levels. To address these limitations, we present CellScope, an innovative framework for constructing high-resolution cell atlases at multiple clustering levels. CellScope employs a two-step manifold fitting process for gene selection and noise reduction, followed by agglomerative clustering, and uniquely integrates UMAP visualization with hierarchical clustering to intuitively represent cellular relationships simultaneously at multiple levels--such as cell lineage, cell type, and cell subtype levels. Compared to established pipelines such as Seurat and Scanpy, CellScope comprehensively improves clustering performance, visualization clarity, computational efficiency, and algorithm interpretability, while reducing dependence on hyperparameters across a multitude of single-cell datasets. Most importantly, it can reveal new biological insights that other contemporary methods are unable to detect, thereby deepening our understanding of cellular heterogeneity and function, and potentially informing disease research.

bioinformatics↗

bioRxiv2025

ViFIT-assisted Histopathology: From H&E Style Standardization to Virtual Fiber Image Transformation

Deep learning-based virtual fiber staining provides a promising complement to routine H&E pathology. However, the reliance on predefined staining style inputs and manual intervention limits the clinical applicability of existing methods. To address these challenges, we introduce ViFIT-assisted histopathology, a two-stage diagnostic approach that integrates our proposed unsupervised deep learning-based virtual fiber transformation model (ViFIT). This approach enables the conversion of H&E-stained images with diverse styles into pathologist-preferred H&E images, while simultaneously generating content-consistent virtual fiber images containing label-free collagen fibers and stained reticular and elastic fibers. ViFIT-assisted histopathology reveals tumor-associated fibers and provides quantitative metrics across multiple intraoperative and postoperative cases. Experimental results demonstrate that ViFIT significantly outperforms state-of-the-art unsupervised methods in both style standardization and virtual staining, across various downstream tasks and cancer types. By eliminating the need for staining variation and manual annotation, ViFIT-assisted histopathology streamlines histopathology workflows, making it well-suited for multi-center consultations and differential diagnosis.

pathology↗

bioRxiv2025

Modular DNA Barcoding of Nanobodies Enables Multiplexed in situ Protein Imaging and High-throughput Biomolecule Detection

Current immunodetection methods using antibody-DNA conjugates enable multiplexed target detection through orthogonal DNA barcodes, but existing conjugation approaches are labor-intensive and often compromise antibody function. Here we present a modular, site-specific, and cost-efficient DNA tagging strategy -- multiplexed and modular barcoding of antibodies (MaMBA). Utilizing nanobodies as modular adaptors, MaMBA enables direct site-specific labeling of off-the-shelf IgG antibodies with a one-component design. We first applied MaMBA to develop the misHCR method for highly multiplexed in situ protein imaging via orthogonal hybridization chain reaction (HCR). Its cleavable variant, misHCRn, achieves simultaneous visualization of 12 different targets within the same mouse brain sections through iterative probe use. We further extended the cleavable MaMBA to develop the barcode-linked immunosorbent assay (BLISA) for multiplexed and high-throughput biomolecule detections. By combining BLISA with next-generation sequencing, we successfully measured SARS-CoV-2 IgG and HBV-associated antigens in a large number of human serum samples. Additionally, we demonstrated a small-scale drug screen by using BLISA to simultaneously detect eight protein targets. In conclusion, MaMBA offers a highly modular and easily adaptable approach for antibody DNA-barcoding, which can be broadly applied in basic research and clinical diagnostics.

bioengineering↗

bioRxiv2024

Covalent inhibitors of the RAS binding domain of PI3Ka impair tumor growth driven by RAS and HER2

Genetic disruption of the RAS binding domain (RBD) of PI 3-kinase (PI3K) prevents the growth of mutant RAS driven tumors in mice and does not impact PI3Ks role in insulin mediated control of glucose homeostasis. Selectively blocking the RAS-PI3K interaction may represent an attractive strategy for treating RAS-dependent cancers as it would avoid the toxicity associated with inhibitors of PI3K lipid kinase activity such as alpelisib. Here we report compounds that bind covalently to cysteine 242 in the RBD of PI3K p110 and block the ability of RAS to activate PI3K activity. These inhibitors have a profound impact on the growth of RAS mutant and also HER2 over-expressing tumors, particularly when combined with other inhibitors of the RAS/MAPK pathway, without causing hyperglycemia.

cancer biology↗

bioRxiv2024

Multimodal CRISPR screens uncover DDX39B as a global repressor of A-to-I RNA editing

Adenosine-to-Inosine (A-to-I) RNA editing is a critical post-transcriptional modification that diversifies the transcriptome and influences various cellular processes. Despite its significance, the regulatory mechanisms controlling A-to-I editing remain largely unknown. In this study, we present two complementary CRISPR-based genetic screening platforms: CREDITS (CRISPR-based RNA EDITing regulator Screening), which enables genome-scale identification of editing regulators using an RNA recorder-based reporter system, and scCREDIT-seq (single-cell CRISPR-based RNA EDITing sequencing), which provides multiplexed single-cell characterization of transcriptome and editome changes for pooled perturbations on dozens of selected genes. Through screening 1,350 RNA-binding proteins, we identified a series of known and novel A-to-I editing regulators. Detailed mechanistic investigation revealed DDX39B as a global repressor of A-to-I editing, which functions by preventing double-stranded RNA accumulation through its helicase and ATPase activities. We demonstrate that targeting DDX39B significantly enhances the efficiency of RNA editing-based tools like CellREADR and LEAPER, and represents a promising strategy for anti-HDV therapy by modulating viral genome editing. These technological advances not only expand our understanding of RNA editing regulation but also provide powerful tools for exploring tissue-specific and context-dependent RNA modification mechanisms, with broad implications for therapeutic development.

molecular biology↗

bioRxiv2024

Endogenous retrovirus-like proteins recruit UBQLN2 to stress granules and alter their functional properties

The human genome is replete with sequences derived from foreign elements including endogenous retrovirus-like proteins of unknown function. Here we show that UBQLN2, a ubiquitin-proteasome shuttle factor implicated in neurodegenerative diseases, is regulated by the linked actions of two retrovirus-like proteins, RTL8 and PEG10. RTL8 confers on UBQLN2 the ability to complex with and regulate PEG10. PEG10, a core component of stress granules, drives the recruitment of UBQLN2 to stress granules under various stress conditions, but can only do so when RTL8 is present. Changes in PEG10 levels further remodel the kinetics of stress granule disassembly and overall composition by incorporating select extracellular vesicle proteins. Within stress granules, PEG10 forms virus-like particles, underscoring the structural heterogeneity of this class of biomolecular condensates. Together, these results reveal an unexpected link between pathways of cellular proteostasis and endogenous retrovirus-like proteins.

neuroscience↗

bioRxiv2024

Three cytochrome P450 enzymes catalyse the formation of furanoclerodane precursors in Salvia spp.

Salvia species native to the Americas are rich in valuable bioactive furanoclerodanes, like the psychoactive salvinorin A found in Salvia divinorum, which is used in treatment of opioid addiction. However, there is relatively little known about their biosynthesis. To address this, we investigated the biosynthesis of salviarin, the simplest furanoclerodane structure in the ornamental sage Salvia splendens. Using a self-organizing map and mutual rank analysis of RNA-seq co-expression data, we identified three cytochrome P450 enzymes responsible for converting kolavenol into salviarin precursors, consecutively: annonene, hardwickiic acid and hautriwaic acid. As annonene and hardwickiic acid have also been proposed as intermediates in the biosynthesis of salvinorin A, and to examine our hypothesis for common evolutionary origin of the furanoclerodane pathway between the two Salvia species, we searched for homologous genes in available data for S. divinorum. The enzymes encoded by orthologous genes from S. divinorum displayed kolavenol synthase (SdKLS), annonene synthase (SdANS), and hardwickiic acid synthase (SdHDAS) activity respectively, supporting the view that these are intermediate steps in the biosynthesis of salvinorin A. We investigated the origin of annonene synthase and the role of gene duplication in the evolution of this specific activity. Our work shows how S. splendens can serve as a model species for studying furanoclerodanes biosynthesis in Salvia species, contributes to understanding the evolution of specialized metabolism in plants, and provides new tools to produce salvinorin A in biotechnological chassis.

plant biology↗