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Tan, Y.

Publications and source records attributed to Tan, Y..

At least 19 recordsLinked to original sources

Cancer cells hijack mitochondria from Bhlhe40+ T cells for immune evasion

Cancer cells hijack mitochondria from T cells via tunneling nanotubes (TNTs) to promote immune evasion, yet the underlying mechanisms of mitochondrial-loss remain poorly understood. Here, through targeted screening of relevant genes, we demonstrated that CD38 is a potent regulator of TNT formation through interaction with its cognate ligand, CD31. Conditional knockdown of Cd38 in murine models leads to CD8+ T cell-dependent tumor shrinkage. Single-cell RNA sequencing of tumor-infiltrating T cells revealed that cancer cells preferentially target the Bhlhe40+ effector subset. Bhlhe40 is a transcription factor that upregulates the expression of S100a4, a reported chemoattractant of nanotubes. Bhlhe40 upregulation creates mitochondrial-loss vulnerability for tumor neoantigen-specific T cells. Dual mitochondria transfer blockade with Cd38 knockdown and S100a4 inhibitor trifluoperazine markedly suppressed tumor growth. Collectively, our findings identified the Bhlhe40-S100a4 cascade as a critical regulator of cancer/T cell mitochondrial transfer, providing insights for the development of new cancer immunotherapies.

immunology↗

VenusGenome: Genome-Aware Masked Autoencoding for Microbial Genome Representation Learning

Genomic-context models have shown that contextualizing protein embeddings can improve predictions of microbial function. We observe that a gene's protein embedding is partially predictable from the embeddings of neighboring genes in the genome, motivating high-ratio masking that requires reconstruction from sparser genomic context. Genomic modeling must also distinguish biological relationships from assembly conventions, since the ordering of separate contigs does not imply adjacency and strand labels depend on the reference orientation. We therefore introduce VenusGenome, a gene-resolution masked autoencoder that combines visible-only encoding with genome-aware attention incorporating contig boundaries, relative strand orientations, and gene positions. We pretrain this model on a curated corpus of over 1.7 million microbial genome assemblies from isolate and metagenomic sources, using frozen protein embeddings as gene-level inputs. Across genome-level phenotype prediction and gene-level tasks, the resulting frozen representations achieve the highest mean performance among the evaluated models on nine of eleven primary metrics. An exploratory gene-input perturbation analysis further links representation sensitivity to experimentally measured fitness defects. Ablations support the contribution of genome-aware attention and show the benefits of masked autoencoding over BERT-style masked modeling, with further gains from higher masking ratios.

bioinformatics↗

Antigen-aware TCR embeddings reveal conserved immune patterns for personalized immune monitoring

T cell receptor (TCR) repertoires are highly individualized, while technical variation further complicates comparisons across individuals and cohorts. Here, we present TCRmeta, an antigen-aware framework that integrates population-scale repertoire relationships with experimentally defined antigen specificity to establish a shared space for repertoire analysis. TCRmeta predicted mutation-induced changes and captured antigen-related relationships in TCR specificity. Despite extensive sequence diversity, TCRmeta revealed a conserved repertoire landscape, enabling construction of a healthy reference for quantifying repertoire dispersal. Across cohorts, aging was associated with conserved V gene changes and progressive dispersal, with greater dispersal in CMV-positive individuals. Longitudinal analysis showed that repertoires progressively shifted toward the healthy reference following bone marrow transplantation or antiretroviral therapy. To directly compare repertoires in TCRmeta space, we developed Energy Shift, a pairwise measure robust to technical variation and HLA background while remaining sensitive to biological differences. Together, TCRmeta enables quantitative cross-individual and longitudinal immune monitoring.

bioinformatics↗

Targeting Cardiac Fibrosis with Chimeric Antigen Receptor Neutrophils Derived from Human Pluripotent Stem Cells

Heart failure remains a leading cause of global morbidity and mortality, with cardiac fibrosis contributing to disease progression. Following myocardial injury, activated cardiac fibroblasts orchestrate adverse extracellular matrix (ECM) remodeling, which leads to tissue stiffening and compromised contractility. Despite the clinical importance of cardiac fibrosis, current pharmacological interventions modulate disease progression without directly eliminating activated fibrogenic cells. To target these cells directly, we engineered human pluripotent stem cell (hPSC)-derived neutrophils expressing a chimeric antigen receptor (CAR) directed against fibroblast activation protein (FAP). In vitro, FAP CAR neutrophils exhibited increased reactive oxygen species-associated fluorescence during fibroblast co-culture and dose-dependent cytotoxicity in 2D cultures, while reducing fibroblast-associated fluorescence in 3D cardiac organoids without a significant reduction in cardiomyocyte-associated cardiac troponin T staining. FAP CAR neutrophils also showed increased iNOS and decreased Arginase-1 expression compared with unmodified neutrophils, consistent with a shift toward an N1-associated polarization profile. Analysis of public cardiac single-cell and single-nucleus RNA-sequencing datasets identified temporal patterns of immune-associated expression and fibroblast activation that informed treatment timing. In a murine myocardial infarction (MI) model, mice treated systemically with FAP CAR neutrophils showed higher day 7 left ventricular ejection fraction than PBS-treated mice in an exploratory comparison. Together, these findings support further evaluation of hPSC-derived FAP CAR neutrophils as an immunotherapeutic approach to cardiac fibrosis.

bioengineering↗

Systematic mapping of enhancers, silencers, and topological elements with prime editing deletion screens

Noncoding regulatory elements in the human genome can control gene expression through distinct mechanisms, including acting as enhancers, silencers, or topological elements. However, we lack tools to identify all such classes systematically and quantify their effects on gene expression in an endogenous genomic context. Here we develop Swap-seq, a method that combines pooled twin prime editing with flow-sorting to delete hundreds of endogenous regulatory sequences and measure their quantitative effects on the expression of a nearby gene. We apply Swap-seq to dissect the regulatory elements that control PPIF expression in THP-1 monocytes. We quantify the effects of distal and intronic enhancers, characterize CTCF insulators, and discover a silencer that regulates distal genes through histone deacetylase (HDAC)-mediated repression of neighboring enhancers. Hundreds of other genomic elements share its chromatin signatures and transcription factor binding sites, suggesting that this silencer represents a broader class of repressive elements. We leverage Swap-seq data to benchmark sequence-to-function models and show that they often capture the local activity of regulatory elements but fail to link them to distal target genes. Swap-seq thus provides a generalizable tool to discover regulatory elements across mechanistic classes, characterize their effects on gene expression, and generate large-scale datasets for evaluating sequence-to-function models.

genomics↗

Autophagosome-tethering compounds selectively lower mutant ataxin-3 in preclinical models of spinocerebellar ataxia type 3

Spinocerebellar ataxia type 3 (SCA3) is most common subtype of autosomal dominant spinocerebellar ataxia worldwide and the most prevalent CAG expansion disorder in the east Asian population, but disease-modifying therapies remain unavailable. SCA3 is caused by the accumulation of polyglutamine- (polyQ-) expanded mutant ataxin-3 (mAtxn3), while the wild-type ataxin-3 (wtAtxn3) plays an important cellular role. Thus, allele-selective clearance of mAtxn3 without affecting wtAtxn3 is highly desired for SCA3 treatment. To achieve this goal, we tested previously reported compounds that have been shown to selectively degrade the Huntingtons disease causing mutant HTT protein by tethering the expanded polyQ to the autophagosome protein LC3. Here, we demonstrated that two of these compounds, AN2 and GW5074, selectively reduced both soluble and aggregated mAtxn3 with expanded polyQ (84Q), but not wtAtxn3, in both cellular and mouse models of SCA3. Mechanistically, both compounds lowered mAtxn3 by enhancing its autophagic degradation without obvious activation of global autophagy. At the molecular level, both compounds increased mAtxn3-LC3 interaction and colocalization to enhance the allele-selectively autophagic degradation of mAtxn3. Phenotypically, both compounds rescued cell viability and ATP content of SCA3 cellular models. In SCA3 patient pluripotent stem cells (iPSCs) derived cortical neurons, both compounds allele-selectively reduced mAtxn3 and partially rescued neurite shortening. Importantly, in a well-established SCA3 transgenic mouse model (MJD84.2), intracerebroventricular, intraperitoneal, and oral administration allele-selectively reduced mAtxn3 in multiple brain regions and rescued motor function deficits. Oral dosing achieved nanomolar cerebellar exposure and showed no overt liver, kidney, or glial toxicity over 28 days. Analyses of 1303 Chinese patients with SCA3 and ATXN3 constructs of different polyglutamine lengths further supported the compounds polyQ length-dependent activity with relative sparing of normal-length ataxin-3. Together, these findings provide preclinical proof of concept that utilizing orally available small molecule compounds to allele-selectively enhance mAtxn3 autophagic degradation for SCA3 treatment. One-sentence summarySmall-molecule autophagosome-tethering compounds selectively lower mutant ataxin-3 through an LC3- and autophagy-dependent mechanism and improve disease-related phenotypes in preclinical models of SCA3.

neuroscience↗

REZCUE: Rescuing 3D spatial omics from archived FFPE tissue

Archived formalin-fixed, paraffin-embedded (FFPE) tissue represents a vast clinical resource, yet three-dimensional imaging and molecular profiling remain largely incompatible because current antigen retrieval and clearing can degrade nucleic acids. We developed REZCUE, a depth-invariant antigen retrieval chemistry based on in situ protein refolding that enables 3D multiplexed immunofluorescence imaging of intact FFPE tissue while preserving DNA, RNA, and protein for subsequent assays. REZCUE restores antigenicity in tissue archived for up to 30 years, supports 160 commercial antibodies across tissue types, and enables imaging to 4 mm depth. Imaging before destructive molecular profiling establishes a 3D spatial reference for registering molecular assays to intact tissue architecture. In a 25-year-archived breast cancer specimen, REZCUE integrated 3D image-guided clonal segmentation with spatial transcriptomics, mass spectrometry, miRNA sequencing, and whole-genome sequencing, identifying a luminalB/HER2-positive clone missed by conventional section-based spatial-omics. REZCUE transforms archived FFPE specimens into spatially registered substrates for sequential 3D multi-omic interrogation.

bioengineering↗

CardioChrom Reconstructs the Human Cardiac Virtual Epigenome from Single-Nucleus Transcriptomes

Background: Matched epigenomic profiling remains scarce in human heart failure, limiting regulatory interpretation of single-nucleus ribonucleic acid (RNA) sequencing data. We developed CardioChrom, a cardiac-specialized framework that reconstructs chromatin accessibility, histone H3 lysine 27 acetylation (H3K27ac), and histone H3 lysine 27 trimethylation (H3K27me3) from single-nucleus RNA profiles. Methods: CardioChrom was developed using same-nucleus human heart datasets jointly measuring RNA with chromatin accessibility by assay for transposase-accessible chromatin (ATAC), H3K27ac, or H3K27me3, with donor-separated development and leave-one-cell-type-out testing. Frozen models were evaluated in 10-donor and 23-sample external human heart cohorts. Histone reconstruction was benchmarked against measured profiles and a Transformer. The models were then applied without refitting to an RNA-only cohort of 43 donors with heart failure with preserved ejection fraction (HFpEF). Results: Across unseen cardiac cell types, CardioChrom increased area under the precision-recall curve by 0.0109 relative to within-cell-type RNA shuffling in 11 of 12 cell types and increased area under the receiver operating characteristic curve by 0.0179 in all 12. CardioChrom exceeded controls in both external cohorts and matched or exceeded the Transformer across 6 prespecified histone metrics. In HFpEF, 3,581 donor-level pathway-layer associations met global false discovery rate, sex-adjustment, and leave-one-donor-out robustness criteria. Endothelial cells showed prominent reconstructed histone-associated changes involving coagulation, inflammation, hypoxia, and profibrotic signaling. Von Willebrand factor expression and its reconstructed regulatory states were consistently reduced, and all 6 linked candidate cis-regulatory elements were classified as repressed. Motif-supported TF-cCRE-gene hypotheses were generated in endothelial cells and fibroblasts. Conclusions: CardioChrom extends RNA-only human heart failure cohorts toward cell-type-resolved virtual epigenomic and regulatory analysis while distinguishing predictions from direct measurements.

bioinformatics↗

Oral Actinobacteria sense and defend against parasitic epibionts

Bacteria contend with a wide range of antagonistic interactions from neighboring microbes. One widespread but poorly understood threat is posed by Patescibacteria, which proliferate by colonizing host bacteria surfaces and extracting cellular resources. Despite the ubiquity of Patescibacteria in the environment, how hosts defend against these epibionts remains unknown. Here we show that Actinomycetota fend off Patescibacteria using the Esx secretion system. We identify a secreted effector protein that mediates this defensive behavior and demonstrate that Esx induction is part of a multifaceted, epibiont-specific response that includes multiple predicted cell surface modifications. Finally, we show that this response occurs at the transcriptional level and is mediated by a previously undescribed threat sensing pathway whose activation leads to threonine phosphorylation of an FHA domain-containing output protein. Together with bioinformatic evidence linking this threat sensing pathway to Esx across Actinomycetales, our experimental findings establish a functional role for the elusive and broadly distributed Esx pathway in defense against epibionts. Furthermore, they help resolve the ecological relationship between Patescibacteria and their hosts as one of antagonism, not mutualism.

microbiology↗

From pose to behavior: SABER integrates identity-resolved multi-animal pose tracking with language-model-based behavioral factor discovery

Quantifying social behavior requires accurate assignment of posture and actions to individual animals, which is often hindered by close contact, occlusion, and identity switches. Meanwhile, current behavioral recognition pipelines still lack stable predictive accuracy. Here we developed SABER, a locally deployable framework that couples multianimal pose estimation with identity preserving tracking, interpretable behavioral factor mining, and multiscale temporal behavior prediction from a single overhead video stream. Across spontaneous two mice social interaction, mating, aggression, and four mice recordings, SABER improved pose estimation accuracy and tracking continuity relative to comparator pipelines. Its behavioral factor-mining procedure identified interpretable kinematic, postural, and social descriptors, and temporal integration improved classification of behavioral categories. SABER offers an intuitive, open-source interface to facilitate use. Applied to social defeat stress mice, SABER detected reduced approach behavior and a multivariate behavioral profile that distinguished depression susceptible from control animals. SABER outputs could also be synchronized with miniscope calcium recordings, enabling joint analysis of behavioral states and neuronal population activity. SABER therefore provides an accessible, identity resolved route from single view social interaction video to behavioral phenotyping and brain behavior analysis.

animal behavior and cognition↗

RECON infers regions of interest from H&E images and reconstructs whole-slide molecular profiles at single-cell resolution

Spatial omics technologies resolve molecular expression and spatial architecture at single-cell resolution, but profiling whole slides remains costly. In practice, only a few regions of interest (ROIs) are profiled, leaving the rest of the tissue unmeasured. S2-omics was the first framework to unify ROI selection with out-of-ROI prediction, but it operates on superpixels rather than individual cells and predicts discrete cell types rather than continuous molecular profiles. Superpixel-based representations do not explicitly preserve cell boundaries, while categorical cell-type labels cannot quantify molecular expression within cells. Here we present RECON, a two-stage framework that performs ROI inference and whole-slide molecular reconstruction at single-cell resolution, predicting both continuous molecular profiles and discrete cell-type labels. In the first stage, RECON extracts morphological and microenvironmental features from individual cells to identify a representative ROI for spatially resolved single-cell molecular profiling. In the second stage, RECON trains deep learning models on molecular measurements acquired within the selected ROI and reconstructs transcriptomic or proteomic profiles for all remaining cells on the slide. Benchmarked against pathologist annotations, RECONs ROI selection outperforms the superpixel-based S2-omics approaches (IoU: 0.75 versus 0.64). For transcriptomics, refining the modeling unit from superpixels to single cells improves per-gene Pearson correlation by 22%. For proteomics, RECON surpasses the current state-of-the-art method, ROSIE, across all 16 markers, with a median per-cell Pearson correlation of 0.91 versus 0.84. Moreover, RECON delineates tumour boundaries and regions with distinct immune-cell densities, and highlights candidate tertiary lymphoid structures. Together, these results demonstrate that RECON enables informative ROI selection and whole-slide molecular reconstruction at single-cell resolution for both spatial transcriptomics and spatial proteomics.

bioinformatics↗

An Open Benchmark for Systems Vaccinology: Insights from the CMI-PB Challenges

Systems vaccinology approaches have identified factors affecting vaccine responses in multiple studies, but the ability of computational models to generalize these findings to unseen data remains unclear. We established a community resource to create and compare models predicting B. pertussis booster vaccination responses and put such modeling approaches to the test. We compiled multi-modal experimental training data from three independent cohorts (n=117 individuals), and asked investigators to predict vaccine responses in a cohort of 54 newly recruited individuals using only their pre-booster vaccination data. We benchmarked a total of 107 computational models. Top-performing models were characterized by workflows that prioritized rigorous data preprocessing, robust imputation of missing data, and the use of multi-omics integration or non-linear machine learning. We identified pre-existing antigen-specific antibody titers and baseline monocyte frequencies as the most consistent predictors of post-vaccination immunity, highlighting the dominant role of individual immune setpoints. We established the resulting datasets and evaluation framework as a community resource to advance predictive immunology and facilitate personalized vaccination strategies.

immunology↗

Spatial multi-omics analysis reveals vimentin-high macrophages-endothelial cells niche shapes CAFs heterogeneity in colorectal cancer metastasis

The spatial architecture of the tumor microenvironment (TME) is pivotal in the progression of colorectal cancer (CRC) liver metastasis. By applying high-plex spatial multi-omic mapping and neighborhood analysis to a discovery cohort of colorectal cancer primary tumor (PT) and paired liver metastases (LM), we identified a specialized vimentin-high macrophages-endothelial cells niche that orchestrates cancer-associated fibroblast (CAF) phenotypes. Mechanistically, in primary tumors, vimentin-high macrophages secrete INHBA to activate the ACVR2/TGF-{beta} axis in endothelial cells, driving CAFs toward a myCAF phenotype. Conversely, in liver metastases, these macrophages secrete CXCL9 to trigger the PI3K-Akt/NF-[kcy]B/CXCL12 cascade in endothelial cells, directing CAFs toward an iCAF state. Clinically, high niche activity predicts poor survival. Divergent endothelial signaling in primary versus metastatic lesions exposes site-specific stromal vulnerabilities for therapeutic targeting, with architectural features discernible from routine histopathology. These findings reveal a site-specific regulatory mechanism of the macrophage-endothelial niche, offering a novel and clinically significant biomarker for CRC prognosis.

cancer biology↗

bgnorm: A Generative Statistical Framework for Background Correction, Normalisation, and Quality Control in Multiplex Spatial Proteomics

Multiplex spatial proteomics enables highly multiplexed in situ profiling but remains limited by technical variation arising from autofluorescence, non-specific antibody binding, instrument noise, and staining variability, affecting downstream biological tasks like cell typing. We present bgnorm, a statistical framework that describes fluorescence measurements using a generative mixture model of background, non-specific binding, and biological signal components. As natural statistical consequences, the model yielded three new methods: a background-correction method through probabilistic deconvolution of protein intensities, quality control metrics, and a quantile normalisation approach to unify measurements across markers, samples, and sequential slices. Across multiple multiplex imaging technologies, bgnorm improves signal separation and downstream marker positivity classification compared with existing preprocessing approaches. In expert-annotated datasets comprising over 406,000 marker positivity annotations, bgnorm achieved the highest classification performance and enabled accurate use of a single global positivity threshold across markers and samples. The method is implemented in the bgnormR and bgnormpy packages.

bioinformatics↗

Two-locus CRISPR toxin-antidote gene drive for confined population modification

Gene drive systems enable rapid spread of desired transgenes throughout populations. Advances in CRISPR technology have facilitated the construction of toxin-antidote gene drives, which utilize a CRISPR nuclease as the toxin to disrupt an essential wild-type gene alongside a recoded version of the same gene as the antidote. Because these systems propagate by eliminating wild-type alleles rather than directly copying themselves like homing drives, they typically exhibit introduction thresholds, allowing them to be confined to target populations. Previous work developed the efficient Toxin-Antidote Recessive Embryo (TARE) drive, but its threshold may be too low in challenging confinement scenarios. Here, we constructed a 2-locus TARE drive system. It has underdominance characteristics, yielding a higher introduction threshold, even when drive performance is ideal. It targets the essential but haplosufficient genes hairy and sim using two different drives at different genomic locations, each targeting the gene that the other rescues. Our system involved two linked elements together with rare homology-directed repair-mediated drive conversion, reducing the threshold to compensate for fitness costs. The system showed high efficiency in individual crosses. When released into multigenerational cage populations above the introduction threshold, the drive successfully and rapidly modified the entire population, and when below this threshold, it was eliminated. Our findings indicate that 2-locus TARE drives represent promising tools for effective and strongly confined population modification.

genetics↗

Development of a metabolomics-based index to monitor dietary effects on chronic inflammation: The Dietary Metabolomics Inflammation Index

BackgroundThe Dietary Inflammatory Index (DII) is widely used to assess the inflammatory potential of diet, but it relies on self-reported dietary assessment and does not directly capture individual differences in metabolism as an intermediate connection to inflammation. High-resolution metabolomics provides objective measurements that complement dietary assessment to support precision nutrition to control inflammation. ObjectiveWe developed, tested, and applied a Dietary Metabolite Inflammatory Index (DMII) to assess diet-related chronic inflammation using metabolites measured by liquid chromatography-high-resolution mass spectrometry. MethodsDII was calculated using dietaryindex R package with Block Food Frequency Questionnaire (FFQ) data. To develop the DMII, chronic inflammation-related dietary metabolites corresponding to the DII food parameters were found through a literature review. Dietary metabolites were identified and quantified by authentic standards by our established laboratory procedures. DMII uses the same inflammatory effect scores as the DII. Three DMII versions were developed: concentration-based, median-based, and quintile-based DMII. Mean and standard deviation of 29 dietary metabolites were calculated by using 3025 human plasma samples from 3 studies. DMII was tested in the Center for Health Discovery and Well-Being cohort (CHDWB) and the Atlanta African American Maternal and Child cohort (ATLAA) using chronic inflammation biomarkers, including high-sensitivity C-reactive protein (hs-CRP), CRP, and IL-6. The median-based DMII was further applied to four Alzheimers disease metabolomics datasets as a proof-of-concept application. ResultsIn the CHDWB study, concentration-based DMII had a weak positive correlation with Block FFQ-derived DII and strongly correlated with median-based and quintile-based DMII. In the same study, all three DMII versions had significant positive correlations with hs-CRP and IL-6. In the ATLAA study, only concentration-based DMII was positively associated with CRP and IL-6. Higher median-based DMII was associated with higher odds of Alzheimers disease. ConclusionsDMII provides a metabolomics-based framework for assessing diet-related chronic inflammation using metabolomics data. This metabolomics approach may complement self-reported dietary assessment to use diet and nutrition to help protect against chronic disease linked to inflammation.

biochemistry↗

Fault-tolerant 3D reconstruction from 2D spatial proteomics sections

Reconstructing 3D molecular volumes from sparsely sampled 2D tissue sections is limited by per-section marker dropout and tissue loss. We present 3D-Omics-Flow, a generative pipeline that jointly repairs damaged sections and interpolates between them at single-cell resolution. Across datasets spanning health and disease, 3D-Omics-Flow expands 3D spatial proteomics to practical sampling regimes, enabling atlas construction and downstream analysis from imperfect 2D section stacks.

bioinformatics↗

Intrinsic promoter responsiveness dictates sensitivity to transcriptional activation by enhancers

Enhancers activate specific target promoters, but whether intrinsic enhancer-promoter compatibility contributes to this specificity is debated. Recent studies using different reporter assays have reached contradictory conclusions. We compare six reporter assay designs, identify confounders that bias compatibility measurements, and apply improved assays to test 25,000 enhancer-promoter pairs. Promoters differ in their responsiveness to enhancers (>100-fold versus 1.1-fold activation) while enhancers activate all promoters in a similar rank order. Promoter output scales with enhancer activity following a power law, with the exponent varying across promoters. Incorporating this exponent into the Activity-by-Contact model improves prediction of endogenous enhancer effects, explaining why certain active genes are insensitive to distal perturbations and "skipped" by enhancers. Responsiveness is modulated by transcription factor motifs in the core promoter. This work establishes responsiveness as an intrinsic promoter property that enables specific promoters to be highly activated in a landscape of broadly compatible enhancers, while others remain unaffected.

genomics↗