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Sun, Y.

Publications and source records attributed to Sun, Y..

At least 127 records · Page 7Linked to original sources

Protocol-dependent cardiomyocyte states determine disease modelling capacity of human iPSCs

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are widely used to model cardiovascular disease, yet numerous differentiation protocols generate cardiomyocytes with heterogeneous molecular and functional properties, complicating experimental design. Here we systematically compare sixteen commonly used cardiomyocyte differentiation protocols and characterize their resulting cell states using single-nucleus RNA sequencing, functional phenotyping and computational integration with human genetic data. Despite similar cardiomyocyte yields, protocols produced distinct transcriptional programs, subtype compositions and physiological properties. By integrating protocol-specific gene expression signatures with genome-wide association studies of cardiovascular traits, we identify cardiomyocyte states enriched for genetic architectures underlying specific diseases. These analyses accurately predict protocols most suitable for modelling particular disease contexts, including electrophysiological defects associated with Brugada syndrome and metabolic vulnerability relevant to myocardial infarction. Our results demonstrate that differentiation protocols encode biologically distinct cardiomyocyte states with differential disease relevance and establish a framework for aligning stem-cell differentiation strategies with human complex trait genetics to guide model selection. This approach enables rational design of iPSC-based disease models and highlights how population-scale genetic data can inform experimental systems in stem cell biology.

systems biology↗

Integrative Omics and Network Biology Reveal Transcriptional Changes of Amino Acid Transport in Arabidopsis Susceptibility to Pseudomonas syringae

Plant amino acids function as both pathogen nutrients and essential drivers of systemic immunity. The regulation of amino acid homeostasis through transporters is a essential for mounting a robust and coordinated immune response in plants during pathogen infection. Using systems biology and integrative network science, we investigated bacterial virulence in Arabidopsis. By comparing gene coexpression networks of effector-triggered susceptibility (ETS) and pattern-triggered immunity (PTI), we uncovered a plant amino acid-related processes specifically linked to ETS. Integrating time-series transcriptomics, protein-DNA interactions, and mathematical simulations, we identified ANAC046 as a transcriptional regulator of amino acid processes during ETS. Single-cell RNA-Seq revealed that amino acid transporters are primarily expressed in companion and mesophyll cells, while functional validation confirmed ANAC046s roles in promoting susceptibility. Further integration of transcriptome and interactome data showed that amino acid-related genes interact with key immune hub proteins. Network topology analysis enabled the characterization of seven additional genes involved in plant defense. To support community-wide research, we developed MIData, an open-access platform for pre-analyzed Arabidopsis networks. Together, our findings demonstrate the power of systems-level approaches in uncovering hierarchical regulatory mechanisms underlying plant susceptibility to bacterial pathogens.

plant biology↗

Topographic CA1 input shapes subicular spatial coding

Precise anatomical topographic mapping in the brain supports high-fidelity information transfer for computations such as sensory alignment and motor coordination1,2. As a brain structure central to learning, memory, and navigation, the hippocampal formation is likewise organized with striking topographic precision3-8. Within this circuit, the subiculum plays a critical role in forming the cognitive map by integrating spatial and non-spatial information from both CA1 and the entorhinal cortex (EC)9-17. Inputs from these regions follow a continuous topography such that distal subiculum receives projections from proximal CA1 (pCA1) and medial EC (MEC), whereas proximal subiculum receives projections from distal CA1 (dCA1) and lateral EC (LEC)3-5,7,8. This anatomical architecture suggests that subicular computations may depend critically on the fidelity of these circuit topographies. However, because CA1 and EC provide partially overlapping spatial information, it remains unclear to what extent CA1-to-subiculum topography, independent of ECs contribution, shapes the physiological properties of subicular neurons. Here, by selectively disrupting CA1-to-subiculum topographic projections in latrophilin-2 conditional knockout mice, we show that precise topography shapes the anatomical distribution of subicular spatial coding while preserving single-cell tuning. Disrupted CA1 input topography also selectively impairs subicular boundary vector coding and long-term network stability. Thus, CA1 input topography is critical for organizing subicular spatial coding and network dynamics. HighlightsO_LICA1[->]subiculum topography organizes spatial coding distribution in the subiculum. C_LIO_LIDisrupted CA1 input topography spares individual subicular place cell tuning. C_LIO_LIDisrupted CA1 input topography selectively impairs subicular boundary vector coding. C_LIO_LILong-term subicular ensemble reactivation requires precise CA1 input topography. C_LI

neuroscience↗

Complete genome-derived metabolic interactions reveal impact of gut ecology on human health

Metabolic interactions govern gut microbiome assembly, yet functional rules remain obscured by genomic incompleteness and fragmentation. Here, we leverage 1,150 complete genomes to construct genome-scale metabolic models, demonstrating that draft genomes introduce systemic artifacts missing critical transport functions. We observe that metabolic interactions are intrinsically driven by genomic traits and niche specialization rather than random association. We stratifies strains into four ecological groups, including active players, resource predators, utilizers, and contributors, each of which exhibits distinct metabolite exchange/competition signatures. This functional architecture is strongly coupled to secondary metabolism. Applying this framework to inflammatory bowel disease revealed distinct temporal dynamics of ecological groups across disease subtypes, where group-specific dysbiosis predicted clinical phenotypes better than whole community profiles. Furthermore, integrating metabolic and co-occurrence networks to identify keystone for classifiers as features significantly improved disease diagnosis. Our study provides novel insights into gut metabolic interaction landscape, bridging the gap between genomic potential and clinical utility for precision microbiome therapeutics.

microbiology↗

SARS-CoV-2 Defective Viral Genomes from Distinct Genomic Regions Drive Divergent Interferon Responses

Defective viral genomes (DVGs) are naturally generated during genomic replication of many RNA viruses. When produced early in infection or supplemented at the onset of infection, DVGs can attenuate viral pathogenesis by stimulating IFN responses and antagonizing wild type (WT) virus replication, highlighting their potential as antiviral therapeutics. However, during natural infection DVGs can exert both antiviral and proviral effects depending on their generation kinetics, species, and abundance, underscoring the need to better understand their roles in viral pathogenesis. Coronaviruses (CoVs) remain a major global health threat and ubiquitously generate DVGs, yet DVGs roles during CoV infection are largely unknown. Using SARS-CoV-2 as a model, we previously identified DVGs in vitro and in patient samples and discovered two major genomic hotspots (A and B) for their generation. Here, we first showed that overall DVG abundance tended to positively correlate with COVID-19 severity, with approximately 40% of DVGs originating from a specific genomic region designated hotspot B. Analysis of a publicly available single-cell RNA-seq datasets revealed that DVGs from hotspot B, but not hotspot A, were associated with elevated IFN responses, suggesting that DVGs derived from different genomic regions vary in their ability to stimulate innate immunity. To test this directly, we constructed two representative DVGs corresponding to hotspots A and B. Both DVGs suppressed the replication of co-infecting WT virus; however, only DVG-B induced robust IFN responses, exceeding those triggered by WT virus alone. This was further confirmed in human precision-cut lung slices. Mechanistically, DVG-B-derived dsRNA exhibited a distinct subcellular distribution compared with WT virus. Complementation with the nucleocapsid (N) partially restored dsRNA organization but did not alter the IFN response. Together, our findings demonstrate that DVGs arising from distinct genomic hotspots differentially regulate IFN responses, potentially contributing to varied pathogenic outcomes during SARS-CoV-2 infection. Author summaryDefective viral genomes (DVGs) are naturally produced during RNA virus infection and can suppress viral pathogenesis by stimulating innate immune responses. However, their roles in coronavirus infection, particularly SARS-CoV-2, remain poorly understood. This study investigated the species-specific function of DVGs generated during SARS-CoV-2 infection and their impact on disease outcomes. Cohort analysis revealed that overall DVG abundance tended to positively correlate with COVID-19 severity, with approximately 40% of DVGs originating from a specific genomic region designated hotspot B. Single-cell RNA sequencing showed that DVGs from hotspot B, but not hotspot A, were associated with elevated IFN responses, suggesting that DVGs from different genomic regions vary in their immunostimulatory capacity. To directly test this, we constructed representative DVGs from both hotspots. While both suppressed wild-type virus replication, only DVG-B induced robust IFN responses both in vitro and ex vivo. Mechanistically, DVG-B produced dsRNA with distinct subcellular distribution compared to wild-type virus. Interestingly, complementation with the viral nucleocapsid protein partially restored dsRNA organization but did not alter IFN responses. These findings demonstrate that SARS-CoV-2 DVGs arising from different genomic hotspots differentially regulate innate immunity, potentially contributing to varied pathogenic outcomes during infection.

microbiology↗

The Effects of Different Gait Patterns on Knee Joint Biomechanics and Dynamic Stability during Stair Walking in Healthy Adults

ObjectiveTo investigate the effects of different gait patterns on knee joint biomechanics and dynamic stability during stair ascent. MethodsFourteen healthy males were recruited to ascend stairs using two distinct gait patterns: the "single-step" (leading with the same leg) and "cross-step" (alternating legs) strategies. Kinematic and kinetic data were collected synchronously using a Qualisys infrared motion capture system and a Kistler 3D force plate. Dynamic stability was quantified using the Margin of Stability (MOS), and knee joint biomechanics were evaluated using Patellofemoral Joint Stress (PFJS) and other relevant metrics. ResultsThroughout the gait cycle, there was no significant difference in the Medio-Lateral (ML) MOS between the single-step and cross-step patterns (P=0.318). However, in the Anterior-Posterior (AP) direction, the MOS for both patterns remained negative and decreased over time, with the cross-step pattern exhibiting significantly lower AP MOS values than the single-step pattern (P=0.002). At the moment of left foot-off, significant differences were observed in the right knee joint angle, right knee joint moment, net joint moment, effective quadriceps muscle lever arm, Quadriceps Force (QF), the angle between the quadriceps tendon and patellar ligament, Patellofemoral Joint Force (PFJF), patellofemoral joint stress, and patellofemoral contact area (all P<0.001). ConclusionsDuring stair ascent, the cross-step pattern reduces body stability, thereby increasing the risk of backward falls. Furthermore, this pattern increases patellofemoral joint stress, subjecting the knee to greater loading. Therefore, it is recommended to enhance lower limb muscle strength through targeted training to reduce fall risk. Additionally, adopting a more cautious gait strategy (such as the single-step pattern) can help minimize patellofemoral joint loading and mitigate the risk of patellofemoral pain.

biophysics↗

A feed-forward loop between niche adenosine and Gzmk⁺ CD8 T cells propagates systemic inflammaging

The causal link between the aging microenvironment and T cell aging remains elusive. Here, we demonstrate that adenosine within aging tissues actively reprograms CD8+ T cells into a pro-aging Granzyme K+ (Gzmk+) population. Mechanistically, senescent cells create an adenosine-rich niche via p16-dependent CD39 upregulation, triggering A2aR signaling to induce Gzmk+ T cell differentiation. Once released, Gzmk promotes systemic inflammaging through PAR1 and complement activation. Crucially, targeting this axis--either via genetic Gzmk ablation or pharmacological A2aR blockade--reverses multi-organ aging phenotypes and significantly extends healthy lifespan in mice. Human analysis reveals age-dependent Gzmk+ T cell accumulation in multi organs, while coffee intake (an A2aR antagonist) inversely correlates with plasma Gzmk levels. Our findings uncover how metabolic niche changes drive T cell aging and establish the adenosine-Gzmk axis as a pivotal therapeutic target for combating age-related diseases.

immunology↗

A CRISPR-Cas9 screen Reveals STEEP1 as a Key Host Dependency Factor for Epstein-Barr Virus Latent Membrane Protein 1 Trafficking and Signaling

The Epstein-Barr virus (EBV) oncogene Latent membrane protein 1 (LMP1) is essential for B-cell transformation into continuously growing lymphoblastoid cell lines. LMP1 traffics to plasma membrane and intracellular signaling sites to mimic aspects of signaling by the B cell co-receptor CD40. LMP1 is expressed in many EBV-associated cancers, including post-transplant lymphoma, Hodgkin lymphoma, T/NK lymphoma and nasopharyngeal carcinoma, where it activates key growth and survival pathways. LMP1 signaling is also implicated in multiple sclerosis pathogenesis. To identify host dependency factors that support LMP1 trafficking and signaling, we performed a human genome-wide CRISPR-Cas9 screen in B cells. The screen identified both known and previously uncharacterized mediators of LMP1 signaling. The ER resident protein STEEP1, implicated in DNA sensor STING trafficking and signaling, was a top screen hit. Importantly, STEEP1 did not score in our prior B cell CRISPR screen for factors that support CD40 signaling, suggesting specificity. STEEP1 depletion strongly impaired LMP1 signaling, including activation of NF-kB and MAP kinase pathways. Mechanistically, STEEP1 associated with LMP1 in a manner dependent on the N-terminal cytoplasmic tail and supported LMP1 egress from the ER to signaling sites in both B and epithelial cells. Collectively, these findings reveal STEEP1 as a key host factor that supports trafficking of newly synthesized LMP1 molecules to intracellular signaling sites and highlights LMP1/STEEP1 interaction as a novel therapeutic target. ImportanceEpstein-Barr virus (EBV) infects most people worldwide. While infection is often benign, it causes infectious mononucleosis, is associated with a range of lymphomas, nasopharyngeal and gastric carcinoma and is a major trigger for autoimmune disease, including multiple sclerosis. The EBV encoded oncogene LMP1 is a key driver of EBV pathogenesis, and its signaling is necessary for viral immortalization of B lymphocytes into continuously growing lymphoblasts (LCLs). Here, we performed a CRISPR genetic screen to identify host factors that support continuous, ligand-independent signaling by LMP1. This analysis identified an ER-resident protein called STEEP1, previously implicated in support of trafficking of the DNA sensor STING, as a key LMP1 partner. We found that STEEP1 associates with LMP1 and supports LMP1 trafficking out of the endoplasmic reticulum to cellular signaling sites. As STEEP1 knockout impaired LMP1 function and LCL survival, our study identifies the STEEP1/LMP1 complex as a therapeutic target.

microbiology↗

Principles of subclonal gene dosage across human cancer

Intratumor heterogeneity drives disease progression, but even though subclonal copy number variation (CNV) is a major contributor to this heterogeneity1, its impact on cell phenotype is not fully understood. Here, by applying high-quality joint whole genome sequencing and mRNA profiling in single cells (DNTR-seq2) to solid tumors and leukemias from 57 patients, we have analyzed the in vivo transcriptional effect of subclonal CNVs within a tumor. We found that gene dosage is generally additive in low and moderate copy states, but that cancer-type-specific compensation is common, and core promoter elements are associated with reduced additivity. We find that different classes of subclonal CNV impose varying degrees of transcriptional constraints on a cell, with highly amplified megabase-size regions associated with a strong effect both in cis and trans, while arm level CNVs generally exert a milder effect. We also describe a previously unappreciated class of tumors with transient clonality, where every cell is genetically highly distinct. We find that transient clonality is common in ovarian cancer and soft tissue sarcoma, that it is preceded by a whole genome duplication event, and that gene dosage in these tumors affects transcript abundance to a similar degree as in cancer with stable subclones.

cancer biology↗

Mechanistic insight into the phosphorylation of ERK by MEK

The RAS-RAF-MEK-ERK cascade regulates critical cellular processes such as cell proliferation and differentiation, with its dysregulation driving over 30% of human cancers. However, the active state of MEK and molecular mechanisms of ERK phosphorylation remain unclear. Here, we report the cryo-EM structures of phosphorylated MEK1 (pMEK1) bound to unphosphorylated and monophosphorylated ERK1. These structures reveal that pMEK1 interacts with ERK1 via three interfaces: first between MEK1 N-terminal peptide and ERK1 D-site recruitment site (DRS), second between MEK1 C-lobe and ERK1 F-site recruitment site (FRS), and third between MEK1 activation loop and ERK1 activation loop. Notably, we identify an unexpected phosphorylation mechanism: pMEK1 catalyzes ERK1 T202 phosphorylation through phosphate transfer from ERK1 Y204. In addition, pMEK1 exhibits phosphatase activity, catalyzing the dephosphorylation of ERK1 Y204. These findings allow us to delineate the catalytic cycle of MEK-catalyzed ERK phosphorylation and provide insights for targeting this oncogenic pathway.

molecular biology↗

Interactome mapping in human excitatory neurons reveals novel risk genes and pathways in Alzheimer's disease

Alzheimers disease (AD) is an irreversible neurodegenerative disease defined by its molecular hallmarks - amyloid beta peptide plaques and neurofibrillary Tau tangles. Despite significant progress that has been made in uncovering a large number of genetic risk factors through extensive genomic sequencing and genetic studies, the molecular mechanisms driving AD-associated pathology and cognitive decline remain poorly understood. Therefore, alongside the identification of more risk genes, it is also paramount to study how these genes function and influence each other within the cellular pathways and overall molecular networks in AD-relevant brain cell types. However, current human protein-protein interactome datasets were all generated in either yeast or generic human cell lines. Consequently, many important neuronal interactions, especially neuron-specific ones, have yet been discovered. To address this critical gap, we developed a highly scalable, high-quality interactome mapping pipeline in human excitatory neurons derived from induced pluripotent stem cells (iPSC), and generated a comprehensive, neuron-specific interactome map, named ADNeuronNet, for key AD risk genes. ADNeuronNet consists of 1,767 high-confidence interactions among 1,189 proteins and is the only dataset enriched with neuron-specific genes when compared to known protein interactions, including previous large-scale interactome maps, for the same baits in the literature. Within ADNeuronNet, we identified 1,375 novel interactions, many of which are likely neuron specific. For example, we identified a neuron-specific interactor, RIN2, for major AD risk factor BIN1 and confirmed RIN2s function in recruiting BIN1 to RAB5 positive early endosomes, a process that has been well-associated with AD etiology. Additionally, we performed quantitative interaction perturbation analyses on AD risk genes with AD-associated mutations or isoforms and identified significant changes in 99 protein interactions among 11 different protein variants. Finally, we found that subunits from the anaphase-promoting complex/cyclosome (APC/C), another novel BIN1 interactors identified by ADNeuronNet, mediated modulation of Tau-aggregation in neurons via regulation of APOE expression, uncovering a previously unrecognized BIN1-APC/C-APOE regulatory axis in AD pathobiology. In summary, these findings illustrate how our neuron-specific ADNeuronNet can be leveraged to uncover new risk gene candidates and cellular pathways that help advance our understanding of molecular mechanisms underlying AD etiology.

systems biology↗

In vivo-directed evolution identifies AAV-WM04 as a next-generation vector for potent and durable hearing restoration in DFNB9

Efficient and cell-specific gene delivery to cochlear inner hair cells (IHCs) remains a major challenge for inner ear gene therapy. Here, we identify and characterize a novel AAV2-derived capsid, AAV-WM04, that enables highly efficient and selective IHC transduction at low doses. Using an in vivo-directed evolution strategy, we generated a randomized AAV2 capsid library with 9-amino acid insertions and performed iterative selection in the adult mouse cochlea. Next-generation sequencing revealed enrichment of several variants, among which AAV-WM04 exhibited superior packaging efficiency and pronounced IHC tropism. AAV-WM04 achieved near-complete IHC transduction throughout the cochlear axis in adult mice, outperforming clinically relevant vectors with minimal off-target expression and no detectable ototoxicity. Robust and exclusive IHC transduction was further validated in non-human primates following round window membrane delivery, underscoring translational potential. Therapeutically, AAV-WM04 enabled efficient dual-AAV trans-splicing delivery of the large OTOF gene, resulting in uniform full-length otoferlin expression in IHCs. In a humanized Otof Q829X/Q829X mouse model, AAV-WM04 restored auditory function across a broad frequency range at relatively low doses and achieved durable hearing recovery. Collectively, these findings establish AAV-WM04 as a next-generation IHC-targeted vector with high efficiency, safety, and cross-species applicability for precision gene therapy of hereditary hearing loss.

genetics↗

4-methyl-3-aminopyridine: A novel active blocker of voltage-gated potassium ion channels in the central nervous system.

Aminopyridines, including 4-aminopyridine (4AP), 3,4-diaminopyridine, and [18F]3-fluoro-4-aminopyridine, are voltage-gated potassium (KV) channel blockers used clinically to enhance conduction in neurological disorders and to image demyelination by PET. Developing new aminopyridines may yield improved therapeutics or imaging agents. Here, we characterized the physicochemical properties (pKa, log D), KV channel-blocking activity, toxicity (LD50), and pharmacokinetics of a novel compound, 4-methyl-3-aminopyridine (4Me3AP). 4Me3AP was less basic and more lipophilic than 4AP and showed greater blocking potency across multiple KV channels expressed in Xenopus oocytes. In mice, 4Me3AP exhibited lower acute toxicity (LD50= 29.3 mg/kg) than 4AP (LD50= 12.7 mg/kg) and a longer plasma half-life. These findings indicate that 4Me3AP is a potent KV channel blocker with favorable pharmacological properties, supporting its potential for symptomatic treatment of demyelinating diseases.

biochemistry↗

Molecular Glue-Induced Homodimerization Drives Targeted CRBN Autodegradation

Molecular glue degraders (MGDs) offer a sophisticated, proximity-based approach to protein modulation. In this study, we introduce LJY-3-60, a novel proximity-inducing agent that unexpectedly triggers the potent and selective autodegradation of CRBN. Evidence from CRISPR-Cas9 screening and IP-MS reveals that this degradation process is strictly governed by the intrinsic CRL4CRBN machinery, independent of any extrinsic E3 recruitment. Through a combination of cellular and biophysical characterizations, we demonstrate that LJY-3-60 acts as a molecular bridge to template CRBN homodimerization. This mechanism is unequivocally elucidated by the atomic-resolution co-crystal structure of the CRBNMidi-LJY-3-60 complex. The structure explicitly delineates the homodimerization interface, revealing how the ligand reorganizes the protein surface to stabilize a non-canonical architecture that drives trans-autoubiquitination and subsequent proteasomal degradation. Furthermore, LJY-3-60 serves as a highly effective, controllable off-switch to mitigate PROTAC-induced toxicity. Ultimately, this work delivers a robust chemical tool for modulating CRBN stability. By demonstrating how a small molecule can functionally mimic an endogenous E3 substrates degron to catalyse targeted autodegradation, this study establishes a rational structural framework for designing the next generation of self-destructive modulators in targeted protein degradation (TPD) therapeutics.

biochemistry↗

Multi-omic responses to acute exercise in abdominal subcutaneous adipose tissue of sedentary adults: findings from MoTrPAC

Exercise induces widespread health benefits across multiple tissues, yet the acute molecular responses in human adipose tissue remain poorly defined. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) profiled temporal molecular changes in abdominal subcutaneous adipose tissue (ASAT) following a single bout of exercise. Healthy sedentary adults were randomized to endurance (EE), resistance (RE), or control (CON) groups. ASAT biopsies were collected pre-exercise and at 45min, 4hr, and 24hr post-exercise, followed by transcriptomic, proteomic, phosphoproteomic, and metabolomic analyses. EE and RE elicited distinct, time-resolved molecular programs involving angiogenesis, extracellular matrix remodeling, mitochondrial metabolism, substrate utilization, and circadian regulation. Phosphoproteomics revealed acute changes in cytoskeletal and branched-chain amino acid metabolism proteins associated with glycemic control. Temporal metabolomic shifts were cell-type-specific. Finally, we identified candidate adipose-derived exerkines with predicted endocrine actions. This multi-omic map of acute ASAT responses offers insight into adipose-specific mechanisms by which exercise promotes metabolic health.

systems biology↗

MERFISH 2.0, an ultra-sensitive single-cell spatial transcriptomics imaging chemistry across diverse tissue types

Spatial transcriptomics has emerged as a transformative approach for elucidating tissue architecture, cellular heterogeneity, and disease mechanisms by preserving the spatial context of gene expression in cells. Despite these advances, many spatial transcriptomic methods underperform in archival or clinically relevant specimens, particularly formalin-fixed, paraffin-embedded (FFPE) tissues, where RNA degradation and crosslinking hinder transcript detection. To address these challenges, we developed Multiplexed Error Robust Fluorescence In Situ Hybridization 2.0 (MERFISH 2.0), an optimized spatial transcriptomic imaging chemistry to enhance profiling of fragmented and highly crosslinked RNA. Across diverse human and mouse tissues preserved as fresh-frozen, fixed-frozen, and FFPE specimens, MERFISH 2.0 substantially increased transcript detection sensitivity by up to [~]8-fold relative to MERFISH 1.0 while preserving quantitative concordance (Pearson r [&ge;] 0.8 across tissues). In archived fresh-frozen human brain samples, MERFISH 2.0s enhanced sensitivity improved transcript recovery, enhanced cell type resolution and spatial analyses. In low quality archival FFPE human breast cancer specimen, MERFISH 2.0 revealed additional cell populations, novel cell clusters, refined tumor-immune architecture, and increased detection of gene-gene and cell-cell interactions relative to MERFISH 1.0, underscoring the impact of improved sensitivity on downstream spatial analysis. By substantially expanding robust transcript detection to degraded and archival samples, MERFISH 2.0 enables scalable, cohort-level spatial transcriptomic analysis across clinically relevant tissue collections.

genomics↗

Phenotypic Bioactivity Prediction as Open-set Biological Assay Querying

The traditional drug discovery pipeline is severely bottlenecked by the need to design and execute bespoke biological assays for every new target and compound--a process that is both time-consuming and prohibitively expensive. While machine learning has accelerated virtual screening, current models remain confined to "closed-set" paradigms, unable to generalize to entirely novel biological assays without target-specific experimental data. Here, we present OpenPheno, a groundbreaking multimodal foundation model that fundamentally redefines bioactivity prediction as an open-set, visual-language question-answering (QA) task. By integrating chemical structures (SMILES), universal phenotypic profiles (Cell Painting images), and natural language descriptions of biological assays, OpenPheno unlocks the highly coveted "profile once, predict many" paradigm. Instead of conducting countless target-specific wet-lab experiments, researchers only need to capture a single, low-cost Cell Painting image of a novel compound. OpenPheno then evaluates this universal phenotypic "fingerprint" against the text-based description of any unseen assay, predicting bioactivity in a zero-shot manner. On 54 entirely unseen assays, it achieves strong zero-shot performance (mean AUROC 0.75), exceeding supervised baselines trained with full labeled data, and few-shot adaptation further improves predictions. In the most stringent setting where both compounds and assays are novel, OpenPheno maintains robust generalization (mean AUROC 0.66), opening up a new paradigm for a highly scalable, cost-effective, and universal engine for next-generation drug discovery.

bioinformatics↗

A full-length single nuclei transcriptomic atlas of human skeletal muscle insulin resistance

Skeletal muscle (SkM) insulin resistance is a central defect in T2D, yet cell specific molecular determinants remain incompletely understood. Here, we integrate full-length single-nucleus transcriptomics with gold-standard stable isotope-labeled hyperinsulinemic-euglycemic clamps to generate a nucleus-resolved transcriptomic atlas of SkM insulin resistance. We identify previously unrecognized myonuclear populations whose proportions associate with insulin sensitivity across independent cohorts, revealing MYH7B+ myonuclei are metabolically favorable over EGF+ myonuclei. Modeling transcriptional variation against tracer-derived glucose disposal uncovers highly nucleus-specific molecular programs that are obscured when using surrogate fasting indices. Mechanistically, we identify zinc transporter ZIP14 as a positive regulator of insulin-stimulated glucose uptake and implicate EGF signaling in impaired branched-chain amino acid catabolism and inflammatory cross-talk within the SkM niche. Together, these findings redefine SkM insulin resistance as a multicellular, nucleus-resolved process and highlight new cell type specific targets for metabolic intervention.

molecular biology↗