Biology subjects

Wang, K.

Publications and source records attributed to Wang, K..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

Characterization of the Gut Microbiota and Serum Metabolomics in Patients with Type 2 Diabetes Mellitus and Newly Diagnosed Acute Coronary Syndrome

Biomarkers for the early identification of acute coronary syndrome (ACS) risk remain inadequately investigated, particularly in patients with type 2 diabetes mellitus (T2DM), for whom timely clinical intervention may substantially enhance prognostic outcomes. The gut microbiota and serum metabolites may serve as pivotal mediators in the occurrence and progression of ACS among patients with T2DM, and whether these factors can be used for the precise discrimination of patients with T2DM complicated by ACS remains to be explored. Overall, 76 participants were enrolled (38 patients diagnosed with T2DM complicated by ACS and another 38 with T2DM without ACS). 16S rRNA sequencing combined with untargeted LC-MS metabolomics revealed a dysregulated gut-serum axis in patients with T2DM complicated by ACS: enrichment of proinflammatory microorganisms (Enterococcus spp.), reduction of butyrate producers (Butyricimonas spp.) and concomitant dysregulation of circulating lipid metabolites-upregulation of PC(16:0/9:0 (CHO)) and arachidonic acid alongside downregulation of cholesterol sulfate. By integrating multiomics data and applying various feature selection methods, we subsequently identified six key biomarkers. The final constructed combined model robustly distinguished patients with T2DM complicated by ACS from those with T2DM alone (AUC = 0.983), outperforming the other single omics models. Our study revealed that the gut microbiota and related serum metabolites serve as key mediators in the onset and progression of ACS among patients with T2DM, and demonstrated their potential value as noninvasive biomarkers for the early diagnosis of T2DM complicated by ACS. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSWe combined 16S rRNA sequencing with untargeted LC-MS metabolomics to dissect the gut-serum axis in patients with T2DM complicated by newly diagnosed ACS. We identified distinct gut microbial and serum metabolic signatures that distinguish ACS progression within the T2DM population. A multiomics classifier integrating clinical, microbial, and metabolic variables achieved robust diagnostic performance (AUC = 0.983) and outperformed single omics models. What Are the Clinical Implications?Integrated multiomics biomarkers facilitate the early identification of ACS progression in patients with T2DM, offering novel avenues for precision prevention, dynamic clinical surveillance, and individualized therapeutic strategies. Dysregulations of the gut microbiota and serum metabolome may play an important role in the development and progression of ACS in patients with T2DM.

microbiology↗

bioRxiv2026

A spatiotemporal immune atlas of subarachnoid hemorrhage from single-cell and spatial transcriptomics

Background and PurposeSubarachnoid hemorrhage (SAH) triggers a complex immune response that critically influences early brain injury (EBI) and long-term outcomes. However, the precise spatiotemporal dynamics and heterogeneity of immune cell infiltration and microglial reprogramming remain poorly understood. We aimed to construct a high-resolution immune atlas to delineate cell states, lineage trajectories, and spatial niches following SAH. MethodsWe integrated single-cell RNA sequencing (scRNA-seq) of CD45+ immune cells with spatial transcriptomics (ST) in a murine endovascular perforation SAH model. Immune landscapes were profiled at 24 hours (acute phase) and 72 hours (subacute phase) post-injury, compared with sham controls. Advanced bioinformatics integrated transcriptional signatures with spatial localization to map macrophage, neutrophil, and microglial dynamics. ResultsOur atlas reveals a coordinated immune transition from acute inflammation to reparative processing. We identified five macrophage, four neutrophil, and eight microglial subsets with distinct spatiotemporal patterns. Notably, we discovered a SAH-specific inflammatory microglial population (MG_03; Spp1+/Lpl+) that clusters at the rupture site during the acute phase. This subset is transcriptionally distinct from disease-associated microglia (DAM) in other neurodegenerative conditions. Trajectory analysis suggests MG_03 acts as a signaling hub for immune recruitment before transitioning toward proliferative and reparative states (MG_06-08) that disperse into the parenchyma by 72 hours. ConclusionsThis study provides the first comprehensive spatiotemporal immune atlas of SAH, highlighting the distinct role of the Spp1+ MG_03 subpopulation in early injury sensing. These findings offer a roadmap for identifying precise therapeutic windows and targeting specific immune subsets to mitigate EBI. Graphical AbstractExperimental workflow for single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) in a mouse SAH model induced by endovascular perforation. Brain tissue from the ipsilateral (injured) hemisphere was collected from sham and at 24 h and 72 h post-SAH. For scRNA-seq, CD45 immune cells were isolated prior to library preparation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/703421v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@4a1bc9org.highwire.dtl.DTLVardef@16664c4org.highwire.dtl.DTLVardef@1619725org.highwire.dtl.DTLVardef@a0d34_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

The effects of breeding timing, clutch size, and nesting strategy on reproductive success in the crested ibis (Nipponia nippon)

O_LIStudying the reproduction process, which is a key determinant of individual and population fitness in endangered species, is challenging but urgently needed. The crested ibis (Nipponia nippon), a flagship endangered species recovering from an extreme population bottleneck, provides a valuable opportunity to examine how life-history strategies shape reproductive success and inform future conservation practices. C_LIO_LIWe monitored 176 breeding pairs of crested ibis over three consecutive breeding seasons and investigated the effects of three key life-history traits, namely breeding timing, clutch size, and nesting strategy (solitary versus colonial), on reproductive success (hatching and fledging success). C_LIO_LIOur analysis found that both hatching and fledging success declined significantly as breeding initiated later, and a positive association between clutch size and reproductive success in this species. These patterns were robust and repeatable across three years. Unlike other closely related species in this family, sibling competition is generally non-lethal, leading to large clutch sizes fledged in this endangered species. We consider this pattern to be a main reason underlying the rapid population recovery observed in the crested ibis. On the other hand, nesting strategy (colonial vs. solitary breeding) had no detectable effect on reproductive success. This pattern indicates the crested ibis can adopt different breeding strategies across habitats, highlighting its capacity to flexibly adjust breeding behavior in response to local environmental conditions. C_LIO_LIOur results provide an integrative assessment of how key life-history traits shape reproductive outcomes in a wild population of the crested ibis, serving as a foundation for evaluating its current status of population recovery and refining future conservation strategies for endangered avian species sharing similar life-history characteristics. C_LI

zoology↗

bioRxiv2026

Integrative Single-Cell Epigenomic Atlas Annotates the Regulatory Genome of the Adult Mouse Brain

Histone modifications underpin the cell-type-specific gene regulatory programs that drive the remarkable cellular diversity of the mammalian brain. Here, we jointly profiled four histone modifications and the transcriptome in 2.5 million nuclei from the adult mouse brain. By integrating these data with chromatin accessibility, DNA methylation, and three-dimensional genome organization, we constructed a unified epigenomic atlas spanning over 100 brain cell subclasses, and assigned active, primed, and repressive chromatin states across 81% of the genome. Active chromatin states marked by combinatorial histone modifications better nominate candidate enhancers with functional support than chromatin accessibility alone, while H3K27me3- and H3K9me3-marked chromatin states delineate distinct modes of cell-type-specific gene repression. Finally, this multimodal resource enables deep learning models that predict cell-type-specific epigenomic features and gene expression from DNA sequence, providing a comprehensive framework for annotating the brain regulatory genome and interpreting non-coding disease risk variants. HIGHLIGHTS- A single-cell epigenome atlas of transcription and four histone modifications across 2.5M mouse brain cells - Multimodal integration maps chromatin states across [~]81% of the adult mouse brain genome - Cell-type-resolved chromatin landscapes reveal regulatory programs mediated by enhancers, Polycomb and H3K9me3 - Deep learning models predict cell-type-specific epigenomic features and gene expression from DNA sequence

genomics↗

bioRxiv2026

A CRISPR-Based Humanized Model Reveals Cooperative Role of STAG2 Loss in Familial GATA2-Deficient MDS Progression

Myelodysplastic syndrome (MDS) is a heterogeneous myeloid malignancy driven by hematopoietic stem cell dysfunction, leading to ineffective hematopoiesis and cytopenias. Familial GATA2 deficiency is the most common cause of Myelodysplastic syndrome in adolescents, with progression often accelerated by co-occurring mutations, notably STAG2 loss-of-function. Using CRISPR/Cas9-mediated genome engineering in primary human fetal liver-derived hematopoietic stem cells and xenotransplantation in mice, we modeled GATA2-deficient Myelodysplastic syndrome with acquired STAG2 loss to investigate disease initiation and progression. While GATA2 deficiency alone had minimal short-term impact in our model, combined GATA2 and STAG2 loss increased hematopoietic stem cell maintenance and self-renewal, induced a myeloid-lineage bias, and expanded primitive progenitors. Single-cell transcriptional profiling revealed upregulation of stemness genes and inflammatory pathways. This humanized model faithfully recapitulates high-risk GATA2-deficient Myelodysplastic syndrome, providing mechanistic insight into how cooperative mutations drive stem cell expansion, inflammatory signaling, and myeloid skewing. Visual Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/702879v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1972beforg.highwire.dtl.DTLVardef@1c57886org.highwire.dtl.DTLVardef@16bd582org.highwire.dtl.DTLVardef@8e728a_HPS_FORMAT_FIGEXP M_FIG C_FIG Key PointsO_LIHumanized model of familial GATA2-deficiency requires the loss of STAG2 for progression to an MDS disease phenotype C_LIO_LIGATA2-ko+STAG2-ko increase HSC self-renewal, induce a myeloid-lineage bias, and trigger an inflammatory transcriptional program C_LI

cancer biology↗

bioRxiv2026

An Advanced Humanized Systemic Lupus Erythematosus Model Enables Parallel Profiling of B Cell-Targeted Therapies

B cell-targeted therapies represent a transformative frontier for systemic lupus erythematosus (SLE) intervention, yet clinical recommendation of specific treatment is hampered by the challenge to perform head-to-head comparisons of efficacy-toxicity trade-offs and tissue-specific impacts in patients. To address this gap, an advanced Toll-like receptor 7 (TLR7) agonist-induced SLE model is developed in a NCG-M (NOD-Prkdcem26Cd52Il2rgem26Cd22Rosa26em1Cin(hCSF2&IL3&KITLG)/Gpt) human immune system (HIS) mice. This model enables parallel evaluation of multiple B cell-directed therapies within a controlled cohort study. It recapitulates core SLE pathologies--including immune effector cell augmentation, autoantibody production and glomerulonephritis--within 2 months, demonstrating greater severity and clinical fidelity than conventional pristane-induced systems. Validated through replication of clinical responses to rituximab and belimumab, the platform directly compares two emerging modalities: universal chimeric antigen receptor-T cells (UCAR-T) elicits delayed but profound B-cell reset correlating with superior reduction in renal pathology and autoantibodies, while T cell engagers (TCEs) mediate rapid yet partial B-cell depletion and transient efficacy. UCAR-T concurrently induces greater acute inflammatory responses, aligning with its distinct toxicity profile. By resolving therapy-specific effects on human immune dynamics and symptom control, this study empowers context-specific therapeutic selection for SLE, advancing tailored management strategies.

immunology↗

bioRxiv2026

Programmable artificial RNA condensates in mammalian cells

Artificial biomolecular condensates have emerged as powerful tools to control cellular behaviors. Here we introduce a method to build artificial condensates within living mammalian cells through the design of modular RNA motifs formed by a single, short strand of RNA. These condensates emerge spontaneously, creating RNA-rich compartments that remain separated from their surrounding environment. The RNA sequences include stem-loop domains that fold as the RNA is transcribed, and then condense in the nucleus and cytoplasm through loop-loop interactions. These sequences can be optimized and diversified, enabling the generation of distinct, non-mixing condensate populations and the programmable control of their subcellular localization. The RNA motifs can also be modified to recruit small molecules, proteins, and RNA molecules in a sequence-specific manner to the RNA-rich phase. By introducing additional RNAs that link two distinct types of condensates, we can create droplets with multiple subcompartments, whose organization can be controlled by tuning the stoichiometry of different RNA sequences. These artificial condensates provide a versatile platform for studying and manipulating molecular functions inside living cells.

synthetic biology↗

bioRxiv2026

VAETracer: Mutation-Guided Lineage Reconstruction and Generational State Inference from scRNA-seq

Somatic mutations accumulate with cell division and are key to understanding tumor evolution. While single-cell RNA sequencing (scRNA-seq) can effectively capture somatic mutations in the 3' untranslated region (3' UTR), enabling its use for lineage tracing, these data are inherently noisy and exhibit high false-positive rates. To address this limitation, we propose VAETracer, a deep learning framework that is able to reconstruct cellular lineages by extracting cellular generation index (CGI) from mutation profiles of 3' UTR in scRNA-seq data, thus enabling the inference of developmental trajectories without relying on noisy mutation signals (https://github.com/Kaiyu-W/VAETracer). There are two core components for VAETracer: (1) scMut module, which infers the CGI directly from sparse and noisy mutation matrices using our cumulative mutation model (CMM), effectively bypassing error-prone phylogenetic tree topologies caused by mutation noise, and (2) MutTracer module, which predicts ancestral and future latent cellular states or gene expressions at the single-cell level by integrating CGI information with measured transcriptomes. Validation on simulated and real tumor datasets shows that this method can accurately reconstruct clonal relationships, quantify tumor progression, and effectively infer unmeasured cellular states using only the measured scRNA-seq data. This work provides a new computational tool for extracting lineage information and revealing tumor evolution directly from widely available RNA-seq data.

bioinformatics↗

bioRxiv2026

TSTScope Unifies Single-Cell Multi-Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

Immune checkpoint blockade (ICB) can produce durable responses in cancer, but reliable predictors of benefit are still lacking. CD8 tumor-specific T cells are essential for ICB efficacy, yet it remains unclear which functional states of these cells determine therapeutic success. To address this, we developed TSTScope, an interpretable deep learning framework that integrates single-cell transcriptomic and T-cell receptor sequencing data to generate unified representations of CD8 T-cell identity. By applying TSTScope to non-small cell lung cancer (NSCLC) datasets, we characterized the gene programs defining tumor specificity and computationally inferred a population of potential TSTs. Crucially, we demonstrate that clinical response is not a product of TST abundance, but is instead governed by their functional state. We derived the MPR score, a metric capturing this functional potential, which proved to be a robust predictor of treatment outcomes. In an independent validation cohort, the MPR score significantly outperformed established biomarkers. Collectively, TSTScope identifies a distinct functional state of tumor-specific T cells as a primary determinant of ICB efficacy, providing both a mechanistic framework and a potent tool for precision immunotherapy.

bioinformatics↗

bioRxiv2026

Genomic and pan-genomic insight into longan domestication and improvement

Longan (Dimocarpus longan) is a tropical tree in Sapindaceae family with economic importance known for its nutritous fruits. Genetic improvement of longan requires knowledge of reliable molecular markers and functional genes associated with key traits. However, it is largely impeded by lacking a complete genome and pangenome reference encompassing the broad genetic diversity in diverse longan germplasms. Here, we present a telomere-to-telomere (T2T) gap-free genome of longan cultivar Shixia and a graph-based pangenome constructed using newly assembled chromosome-level genomes of 101 accessions. We completely assemble the longan centromere regions primarily composed of Gypsy-CRM retrotransposons. The pan-genome analysis reveals 58,978 non-redundant structural variants (SVs) that exhibit signs of genomic selective sweep during longan domestication and breeding. Additionally, haplotype-resolved genome analysis suggests allele-specific gene expression associated with SV-driven changes in 3D genome architecture. Importantly, the graph-based pan-genome empowers population-scale SV genotyping and genomewide association with various longan traits. SV-GWAS revealed 12 QTLs significantly linked with longan maturity period. Among them, a 758bp insertion is located downstream of the DlDAZ gene encoding a C2H2 zinc-finger transcription factor, and DIDAZ-transgenic tomatoes showed delayed maturity. Together, our T2T genome and pan-genome provide valuable resources to facilitate longan genetic research and precise improvement.

genomics↗

bioRxiv2026

Glucose is a ligand-like trigger for secretion of postprandial GLP-1

Glucagon-like peptide 1 (GLP-1) is secreted from the intestinal L cells in a glucose-dependent manner. However, the mechanism underlying how glucose stimulates the secretion remains unclear. Here, we found that glucose at postprandial concentrations near the Km of GK for glucose ([~]10 mM), as well as nonmetabolizable glucose analogs, triggers GLP-1 secretion by intestinal L cells through directly binding to glucokinase (GK), without increasing intracellular ATP levels. We also show that in postprandially high glucose, glucose-bound GK interacts and inhibits KATP, as assessed by immunoprecipitation and FRET-FLIM analyses, as well as patch clamping. In addition, we have utilized GK mutants identified in diabetics, demonstrating that those mutants defective in binding to glucose impair GLP-1 secretion in however high glucose, whereas mutants constitutively bound to glucose with defects in catalysis, promote GLP-1 secretion even in low glucose. Furthermore, the KATP mutant unable to bind to GK blocks GLP-1 secretion in high glucose. We have also provided evidence showing that sodium-glucose cotransporter 1 (SGLT1) plays an important role in the basal secretion of GLP-1, but not in high glucose. We have thus revealed that glucose the molecule itself and GK act as a ligand and the receptor, respectively, to induce GLP-1 secretion in response to high glucose, providing new therapeutic avenues targeting metabolic diseases.

biochemistry↗

bioRxiv2026

Abalone genomics reveals an ancient asymmetry axis and the multifunctionality of the mantle

Gastropod diversification represents one of the most spectacular evolutionary radiations, underpinned by a fundamentally asymmetric body plan and diverse pigmentation patterns. To understand the genetic underpinnings of these cardinal traits, we constructed a chromosome-level genome assembly for the rainbow abalone, Haliotis iris. Integrating systematic genomics, histoembryology, and molecular assays, we uncover an ancient regulatory axis, conserved for over 544 million years, in which the long non-coding RNA lncRNA1 functions as a competing endogenous RNA to shield pitx transcripts from miRNA-mediated degradation, thereby driving the establishment of asymmetric body patterning, including the mantle. Furthermore, we identify a wnt-mitf-tyr cascade as the driver of melanogenesis and demonstrate that the mantle is the primary site of melanin synthesis. Concurrently, we reveal the mantle as a multifunctional organ possessing mechanosensory capabilities. These findings elucidate the ancient genetic toolkit governing trait evolution in gastropods. TeaserA deeply conserved RNA switch directs gastropod body plans and reveals the mantles hidden talents.

genomics↗

bioRxiv2025

A Solanoeclepin A precursor functions as a new rhizosphere signaling molecule recruiting growth-promoting microbes under nitrogen deficiency

Solanoeclepin A (SolA) is a triterpenoid exuded from the roots of Solanaceae plants, originally identified as hatching stimulant for plant parasitic cyst nematodes. Assuming that evolution would have selected against the production of such a fitness lowering molecule, we postulated that SolA must serve another, beneficial, role for the plant. In this study, we demonstrate that nitrogen (N) deficiency strongly increases the SolA concentration in tomato root exudate. Moreover, SolA is produced only under non-sterile conditions, indicating that soil microbiota are involved in its production. Time-resolved RNAseq analysis revealed several candidate genes for SolA biosynthesis, which were all upregulated under N deficiency. Transient silencing of two SolA biosynthetic genes (e.g., CYP749A19 and CYP749A20) significantly reduced SolA production. Microbiome analysis on the rhizosphere of these plants demonstrated that the recruitment of beneficial Massilia spp. was inhibited in the transiently silenced plants. Isolation of a Massilia strain, identified as Massilia cellulosiltytica, allowed us to show that it has growth-promoting activity under N deficiency, likely via indole-3-acetic acid production and enhanced N acquisition. Root exudate of N-starved tomato displayed strong chemotactic activity towards this strain. Together, these findings demonstrate that SolA production under N deficiency relies on the interaction between tomato and soil microbiota that convert a plant-produced precursor that is a recruitment signal for beneficial, growth-promoting microbes to SolA, which was hijacked by cyst nematodes as a reliable host presence cue. This dual functionality resembles the microbial transformation of primary into secondary bile acids, important signalling molecules, in the gut of animals, and suggests convergent evolution in host-microbe co-metabolism. Overall, our study positions SolA as a multifunctional signaling molecule in rhizosphere interactions, with potential application for enhancing crop resilience and sustainable pest management.

plant biology↗

bioRxiv2025

A novel dephosphorylation peptide inhibits 17β-HSD1 enzyme activity in ovarian granulosa cells and breast cancer cells

Estradiol (E2), a pivotal mammalian reproductive hormone, is closely associated with estrogen-dependent diseases. 17{beta}-hydroxysteroid dehydrogenase type 1 (17{beta}-HSD1), a critical E2 synthesis enzyme, has been understudied for its post-translational regulation-despite its potential as a therapeutic target, no clinically approved inhibitors are currently available. In our investigation of porcine follicular atresia mechanisms, we identified five differentially phosphorylated residues in 17{beta}-HSD1. Using in vitro site-directed mutagenesis and transgenic mouse models carrying point mutations, we established that Ser30 and Ser274 are critical phosphorylation sites that robustly modulate 17{beta}-HSD1 enzymatic activity. We further demonstrated that activin A and insulin-like growth factor 1 (IGF-1) enhance 17{beta}-HSD1 activity by promoting its phosphorylation at these two sites. To target these regulatory residues, we designed and synthesized cell-penetrating peptides (CPPs) that specifically suppress 17{beta}-HSD1 phosphorylation. Functional assays conclusively demonstrated that these CPPs significantly suppressed 17{beta}-HSD1 activity in vitro. Notably, they also inhibited the proliferation, migration and invasion of MCF-7 cells, as well as tumor growth in a mouse model of breast cancer. Our study provides novel mechanistic insights into the regulation of 17{beta}-HSD1 and E2 synthesis, addressing a critical gap in steroid hormone biology. The identification of Ser30/Ser274 as functional phosphorylation sites and the development of CPP-based inhibitors offer both theoretical advances and translational potential, opening new avenues for the treatment of estrogen-dependent breast cancer.

cell biology↗

bioRxiv2025

TUPAD: A Tn5-Mediated, Pre-amplification/Adapter-Dimer-Free Platform for Ultra-Uniform, One-Step PGT Profiling with High Stability and Broad Compatibility

High-throughput sequencing stands as a cornerstone of clinical molecular diagnostics, particularly in preimplantation genetic testing (PGT)--a key application where the selection of chromosomally normal embryos is critical to enhancing in vitro fertilization (IVF) success rates. A fundamental challenge inherent to PGT, however, lies in the ultra-low gDNA input (typically <100 pg) from embryo biopsies. To mitigate this limitation, traditional workflows rely on whole genome amplification (WGA) technologies, such as MDA, PicoPlex, and MALBAC. Yet these WGA-based protocols inherently entail pre-amplification of gDNA prior to standard library construction---a step that introduces significant coverage bias and compromised uniformity. These are intrinsic flaws irreparable by downstream library preparation or bioinformatics analysis, ultimately leading to clinical uncertainty in the interpretation of copy number variations (CNVs). In this study, we developed TUPAD (Tn5-Mediated, Uniform Pre-amplification-free and Adapter-Dimer-Free Library preparation), a transformative technology that bypasses the limitations of traditional WGA. By engineering a novel adapter-dimer-free transposon system, TUPAD enables high-efficiency library construction from as little as 1 picogram (pg) of gDNA. This breakthrough allows for a pre-amplification-free workflow, effectively eliminating the primary source of amplification bias. Compared to existing WGA standards, these advantages are fully retained in embryo biopsy and positive sample testing, TUPAD consistently generates highly uniform library data, significantly enhancing the detection limit and accuracy of CNVs and other genomic variants. Beyond these performance advantages, TUPAD also cuts wet-lab processing time by 50%. Practical validation confirms TUPAD results are stable, reliable, with proven practical utility in PGT testing.

molecular biology↗

bioRxiv2025

Polus: a Transformer-based Soft-decision Codec Enhancement Platform for DNA Storage

DNA storage offers exceptional information density and archival longevity, but is constrained by the complex, heterogeneous errors inherent to synthesis, storage, and sequencing. Conventional error-correction schemes often rely on excessive logical redundancy to mitigate these biochemical imperfections, thereby compromising storage efficiency. Here, we introduce Polus, a deep-learning-enabled platform that bridges the gap between biochemical constraints and digital reliability through soft-decision decoding. At its core is SeqFormer, a Transformer-based channel model that synergizes sequence context with quality signals to characterize platform-specific error profiles, generating calibrated per-base confidence scores. This mechanism transforms uncertain biochemical noise into informative "soft" erasures. In in silico benchmarks, Polus significantly enhances mainstream codecs: it reduces the sequencing coverage required for DNA Fountain by 38.9% --increasing effective physical density by [~]80%--and eliminates persistent indel-induced errors in the Yin-Yang codec. Furthermore, it enables a targeted resequencing strategy that achieves full recovery with 99.9% less overhead than brute-force deepening. To formalize these gains and address the lack of systematic benchmarking in the field, Polus establishes a standardized nine-metric evaluation framework that rigorously quantifies the trade-offs between reliability, density, and cost. This work provides a reproducible, quantitative foundation for next-generation, context-aware DNA storage systems.

bioinformatics↗

bioRxiv2025

RM1mAb avoids Intracellular degradation to Synergistically inhibit NLRP3 Inflammasome Activation in Familial Cold Autoinflammatory Syndrome

The NLRP3 inflammasome enables release of mitochondrial DNA to circulation. Circulating oxidized mitochondrial DNA generated in response to NLRP3 inflammasome activation functions as an alarmin that contributes to the maintenance of systemic inflammation. The discovery that NLRP3 could cleave oxidized mtDNA led to repurposed chemical inhibitors that dually target NLRP3 and DNA glycosylase OGG1, resulting in pro-survival type-1 interferon. Using molecular dynamics and immunology we show that RM1mAb, a full-length monoclonal antibody targeting the NLRP3 pyrin domain, can prevent NLRP3 from interacting with mitochondrial DNA. We further illustrate RM1mAb can exploit FC{gamma}Rs for cell entry and avoid destruction by the lysosomal pathway to inhibit IL-1{beta} secretion in peripheral mononuclear blood cells (PBMCs) isolated from patients with Familial Cold Autoinflammatory Syndrome harboring NLRP3 L353P gain of function mutation. We show RM1mAb and repurposed inhibitor TH5487 synergistically inhibit inflammasome activation. These findings illustrate the promise of exploiting FC{gamma}Rs as a means of IgG entry to target cytosolic proteins and improve human health. One-Sentence SummaryRM1mAb and TH5487 synergistically inhibit inflammasome activation in human FCAS PBMCs.

immunology↗

bioRxiv2025

HINS: HLA-mediated immunogenic neoantigen score for robust prediction of immune checkpoint blockade response

Immune checkpoint blockade (ICB) therapy response prediction provides remarkable genomic and transcriptomic gains and has successfully understood the molecular mechanisms underlying various cancers. However, only a subset of patients with advanced tumors currently benefits from ICB therapies, which at times incur considerable side effects and costs. Developing predictive tools for ICB response has remained a serious challenge because of the complexity of the immune response and the shortage of large cohorts of ICB-treated patients that include both omics and response data. Here, based on a pooled genomic dataset of 919 patients across multiple solid tumors treated with anti-PD-(L)1 or anti-CTLA-4, we constructed human leukocyte antigen class I (HLA-I)-mediated immunogenic neoantigen score (HINS). HINS is a predictor of ICB response using neoantigen quality and HLA evolutionary divergence to integrate the factors associated with immune activation and evasion. It yielded an overall accuracy of AUC=0.853, outperforming existing predictors and capturing more than 75% true responders. Experimental analysis indicated that patients with higher HINS were more likely to undergo survival benefits following ICB therapy. Our results highlighted the transcriptional and genomic correlations between HINS-identified molecule features and ICB response, such as immunoresponsive gene enrich pathways, favorable and unfavorable genomic subgroups, and hotspot somatic events in driver genes. This study presented an interpretable, accurate deep-learning method using meaningful predictive features to predict the response to ICB, providing biological insights into the complexity of the determinants underlying immunotherapy.

bioinformatics↗