Biology subjects

Fan, J.

Publications and source records attributed to Fan, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Ratio-preserving super-resolution FLIM for quantitative live-cell lifetime imaging

Super-resolution (SR) fluorescence lifetime imaging promises nanoscale maps of molecular environment and function, but photon-limited acquisition and computational reconstruction can distort lifetime estimates, particularly for ratio-derived frequency-domain measurements under SR conditions. Here we introduce structured-illumination frequency-domain FLIM (SIM-fdFLIM), an SR lifetime imaging platform that combines commercial dual-tap fdFLIM detection with ratio-preserving reconstruction. SIM-fdFLIM uses direct-current (DC)-stabilized lifetime estimation to improve reconstruction robustness under low signal-to-noise conditions, followed by ratio-domain integrated variational estimation (RIVE) to correct channel misregistration and suppress noise amplification after SR reconstruction. The method achieves ~100 nm spatial resolution in lifetime maps and enables live-cell imaging at 2.8 Hz over a 56 x 56 {micro}m2 field of view. Across representative fluorophore standards, RIVE reduces lifetime standard deviation by approximately threefold relative to non-RIVE SIM-fdFLIM while preserving mean lifetime agreement with calibrated widefield fdFLIM. In living cells, SIM-fdFLIM resolves mitochondrial cristae-scale lifetime heterogeneity, mitochondrion-to-mitochondrion functional dynamics, nanoscale lipid-environment variations and perturbation-sensitive organelle-contact signatures. These results establish SIM-fdFLIM as a ratio-preserving platform for quantitative SR lifetime imaging, extending live-cell FLIM into a regime that combines nanoscale spatial resolution, Hz-rate acquisition, and preserved lifetime fidelity.

bioengineering↗

bioRxiv2026

CnidoSite: A Multi-Omics Database for Cnidarians

The phylum Cnidaria, encompassing reef-building corals, sea anemones, hydroids, and jellyfish, includes both ecological keystones of the marine biosphere and indispensable models for reconstructing early animal evolution. However, escalating ocean warming, recurrent mass coral bleaching events, and intensifying jellyfish blooms have underscored the urgent need to dissect the molecular underpinnings of cnidarian thermal tolerance, symbiosis, and environmental adaptation. Progress in cnidarian research is hindered by the lack of centralized, high-quality multi-omics resources. To address this, we present CnidoSite (https://CnidoSite.org), a comprehensive, analysis-ready multi-omics platform dedicated to Cnidaria. Spanning 327 species across 120 families, 23 orders, and 7 classes, it integrates 147 full-annotated genomes, 15,642 bulk transcriptomes, 50 single-cell datasets, 46 proteomes, 723 epigenomes, 1,650 metagenomic samples, and 180,652 phenotype records. Complemented by advanced toolkits for multidimensional functional and comparative analyses, CnidoSite provides extensive functional genomic resources, including genome assemblies, phylogenies, fossil entries, functional annotations, BUSCO assessments, and mitochondrial annotations. Key features include 29 co-expression networks with cross-tissue visualization and single-cell atlases to map developmental trajectories and stress responses. In summary, CnidoSite serves as a centralized platform that bridges cnidarian biology, marine conservation, and evolutionary genomics to investigate coral bleaching, symbiosis breakdown, jellyfish blooms, and the mechanisms driving environmental adaptation.

bioinformatics↗

bioRxiv2026

Interpretable machine learning coupled to gene regulatory networks uncovers subcircuits underlying cell fate decisions

Gene regulatory networks (GRNs) model causal linkages that control cell fate decisions and differentiation transitions. Prioritizing regulatory subnetworks underlying cell state differences is of critical importance, but current methods including those reliant on topological metrics introduce circularity as the metrics prioritizing TFs are computed from the same networks whose assumptions they inherit. Separately, interpretable machine learning methods can identify latent factors (LFs) that discriminate cellular states with formal statistical guarantees but do not model regulatory linkages. Here, we present FOCAL (Factor-Outcome Coupling for Assessment of Linkages), a paradigm to prioritize regulatory subnetworks by coupling state-specific and dynamic GRNs with outcome-supervised LFs learned using interpretable machine learning without reference to network topology. This shifts GRN focus from macroscopic TF nodes to state-specific and dynamic TF-gene linkages. In B and T cells, FOCAL identified GIFs (GRNs coupled to Interpretable latent Factors), prioritized regulatory subnetworks underlying established states as well as transient regulatory episodes preceding them. By coupling LFs learnt from perturbation experiments of lineage-defining TFs, FOCAL identified transcriptional predisposition to alternative fates within progenitor cell populations before overt differentiation. This uncovered a novel NFATC2-IRF8 interplay in activated B cells, that was validated by in-vitro and in-vivo genetic perturbations. The two transcription factors act cooperatively to restrain extrafollicular plasmablast differentiation and promote germinal center B cell fate.

systems biology↗

bioRxiv2026

Evolution of new cerebellar nuclei by excitatory progenitor diversification in the early rhombic lip

The cerebellar nuclei, the output regions of the cerebellum, have evolved via repeated duplication of a conserved cell type set to produce different numbers of nuclei across species. Here, we investigate the mechanism underlying this process using developmental single-cell and spatial transcriptomics time courses in mouse and chicken. We show that new nuclei formation is governed by excitatory neurons born from nucleus-specific progenitors in the early and late rhombic lip (RL), with inhibitory neurons incorporating into established nuclear territories. Evolutionarily newer canonical cerebellar nuclei with increasingly higher-order functions are produced by diversification of the early RL, where nuclear identity and spatial organization are established in part by co-option of border formation programs in conserved progenitor cell types. In contrast, the late RL generates the higher-order subnuclei of the medial nucleus and forms a non-canonical olivocerebellar circuit. Together, our findings suggest that new brain regions can evolve through developmental diversification of excitatory progenitors and spatial segregation of conserved sister cell types with generic inhibitory neurons filling in after.

neuroscience↗

bioRxiv2026

Risk factors and immunological characteristics of SARS-CoV-2 RNA re-positivity in convalescent COVID-19 Patients: A retrospective study

Purpose: To investigate the incidence, clinical features, and risk factors for SARS-CoV-2 nucleic acid re-positivity in recovered COVID-19 patients. Methods: We enrolled 441 convalescent COVID-19 patients from the rehabilitation ward of the Fifth Hospital of Shijiazhuang between January and April 2021. Based on nucleic acid test results, patients were categorized into repositive (n = 69) and non-repositive (n = 372) groups. Demographic, clinical, laboratory, and imaging data were compared between groups. Logistic regression was used to identify factors associated with re-positivity. Results: The overall re-positivity rate was 15.65%. Compared with the non-repositive group, the repositive group presented with a significantly higher proportion of moderate disease severity (72.46% vs. 50.54%) and a lower proportion of patients under 14 years old (7.25% vs. 23.66%). Additionally, multi-lobar involvement ([≥] 3 lobes) during the acute phase was more common in the repositive group (43.48% vs. 26.61%), with all differences being statistically significant (P < 0.001). Laboratory analysis revealed that repositive patients had significantly lower lymphocyte and eosinophil counts, as well as reduced albumin (ALB), aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio, and albumin/globulin (A/G) ratio. Furthermore, circulating CD3+, CD4+, and CD8+ T-cell counts were markedly decreased. In contrast, the neutrophil-to-lymphocyte ratio (NLR), immunoglobulin M (IgM), immunoglobulin A (IgA), and neutralizing antibody (NAb) levels were significantly elevated in re-positive patients (all P < 0.05). Multivariate logistic regression analysis identified the CD8+ as independent risk factors for re-positivity. Conclusion: In convalescent patients, SARS-CoV-2 RNA re-positivity correlates with distinct clinical and immunological characteristics. The CD8+ T-cell level is an independent predictor, highlighting that dysregulated immune and inflammatory responses contribute to delayed viral clearance.

immunology↗

bioRxiv2026

MMMAS: A Mendelian Mismatch Matrix Analysis System for Deterministic Pre-Screening of Germplasm Collections

Pedigree errors, duplicate accessions, and undocumented kinship limit the effective use of large genebank collections. Existing tools such as CERVUS and COLONY require allele-frequency estimates and return relationship-level assignments, providing no collection-wide view of Mendelian consistency. We developed the Mendelian Mismatch Matrix (MMM) framework and its open-source implementation, MMMAS (Mendelian Mismatch Matrix Analysis System). We applied MMM to apple (Malus x domestica; 1,085 accessions, 15 SSRs) and sweet cherry (Prunus avium; 383 accessions, 13 SSRs) datasets from the German Fruit Genebank. MMM converts pairwise Mendelian mismatch numbers (Mmn) into an N x N symmetric matrix, from which we derive four collection-scale indices (Mmin, the Mendelian minimum mismatch number; Mavg, the Mendelian average mismatch number; Mzmp, the Mendelian zero-mismatch partner number; Mmmd, the Mendelian mismatch-mode duplication index) and the Mendelian Exhaustive Stratification (MES) grading system. Apple showed a gradient-type structure (Mendelian Grade-gap Index, MGI = 0.125), sweet cherry a broken-type structure (MGI = 0.545). The Mmin-Mavg strategy identified 20 and 10 distinct accessions in apple and sweet cherry, including the scab-resistance donor Malus x floribunda 821 (Rvi6) and the fire-blight donor M. x robusta 5. The Mmmd index flagged one literature-confirmed pair of duplicate genotypes in sweet cherry. Of CERVUS-confirmed parent-offspring pairs, 97.31% in apple and 100% of high-confidence pairs in sweet cherry fell within Mmn <= 1. Mzmp rankings matched documented breeding history, with 'Cox Orange' (Mzmp = 57) and 'Luebecker Bunte' (Mzmp = 49) ranking first in each species. The complete end-to-end analysis of all 588,070 apple pairwise comparisons took 7.24 s on an ordinary workstation. This deterministic pre-screening framework, with a parameter-free core, supports routine quality assessment in germplasm collections.

genetics↗

bioRxiv2026

Repeated mild traumatic brain injury does not affect sleep or epileptiform activity one-month post-injury in a knock-in mouse model of Alzheimer's disease

Traumatic brain injuries (TBIs) are associated with increased risk of neurodegenerative disease, including Alzheimers disease (AD); however, the mechanisms by which TBI promotes AD pathogenesis remain poorly understood. It also remains unclear whether post-TBI sequelae, including sleep disturbances and seizures, play a role in driving disease progression. To investigate these relationships, we employed a translational approach using the Closed-Head Injury Model of Engineered Rotational Acceleration (CHIMERA) of repeated mild TBI (rmTBI) and an AD knock-in mouse model to assess sleep, power spectral density, epileptiform activity, and A{beta} pathology one month post-injury. RmTBI caused elevated neurofilament-light and glial fibrillary acidic protein, markers of neuronal damage. Sex differences were observed in acute injury outcomes, sleep measures, and A{beta} plaque size. Specifically, females exhibited longer recovery post-injury, higher mortality, decreased non-rapid eye movement sleep duration, and larger average plaque size than males at equivalent impact energy. These findings highlight the importance of including both sexes when establishing injury severity thresholds. Future studies should incorporate validated TBI biomarkers of neural injury to define equivalent injury parameters across sexes and examine the chronic effects of rmTBI on sleep, epileptiform activity and AD pathology.

neuroscience↗

bioRxiv2026

Hyaluronan and CD44 targeting reverses early matrix changes, proinflammatory signals and fibrosis in primary sclerosing cholangitis

Primary sclerosing cholangitis (PSC) is a rare, progressive liver disease characterized by biliary inflammation and bile duct strictures and no approved medical therapy. Despite its clinical severity, the pathological mechanisms underlying PSC remain poorly understood, largely due to early diagnostic challenges. Here we provide complementary evidence in human PSC samples, transcriptomic data, mouse models, and 3D cholangiocyte cultures that underscore the importance of hyaluronic acid (HA) and its cognate receptor CD44 in PSC pathogenesis. HA is a glycosaminoglycan abundant in the extracellular matrix in inflammatory disorders, yet its role in PSC has not been well characterized. We demonstrate that in early-stage PSC, cholangiocytes aberrantly produce high molecular weight HA that accumulates in the peribiliary matrix, increasing local tissue stiffness. This mechanical signal is transduced by a CD44/Integrin {beta}1 receptor complex in cholangiocytes, driving cell proliferation, YAP mechanosignaling, pro-inflammatory cytokine production with a transition to a ductular reactive phenotype. CD44 knockdown in cholangiocyte cell lines and mouse models significantly lowered stiffness, and attenuated inflammation. Together, these findings reveal a mechano-inflammatory axis in which HA-driven matrix stiffening perpetuates biliary inflammation and disease progression, identifying HA targeting and CD44 as promising therapeutic strategies. One Sentence SummaryHyaluronan and CD44 mediate matrix changes and progressive fibrosis in primary sclerosing cholangitis.

pathology↗

bioRxiv2026

Lineage recording reveals hijacked hepatic progenitor states as a common origin of HCC and ICC

HighlightsCERAMIC enables continuous and high-capacity lineage tracing of liver tumor initiation Fatty liver-associated hepatocytes acquire regenerative and premalignant cell states before malignant transformation Lineage reconstruction identifies Hep_Bi-zonal cells as the cellular origin of liver tumor initiation Transcriptional and regulatory programs distinguish tumor-fated hepatocytes from failed-to-transform lineages Peroxisomal metabolism is required for progenitor-state formation and liver tumor initiation Spatial remodeling identifies a macrophage niche associated with tumor-fated hepatocytes Dual ontogenies and functional specialization of lipid-associated macrophages shape the tumor-fated hepatocyte niche Fatty liver disease predisposes to primary liver cancer, yet the lineage routes and niche mechanisms that select rare tumor-fated hepatocytes remain unclear. Here we developed CERAMIC, a high-capacity CRISPR-Cas9 lineage recorder that co-recovers editing scars and transcriptomes from single cells, and applied it to an AKT/NRAS-driven model of MASLD-associated liver tumor initiation. Longitudinal lineage, single-cell and spatial analyses revealed a hierarchical trajectory in which bipotential bi-zonal hepatocytes (Hep_Bi-zonal), rather than pericentral-like hepatocytes (Hep_CVlike), generated regenerative and neoplastic hepatocyte progenitor states that progressed toward both hepatocellular carcinoma and intrahepatic cholangiocarcinoma lineages. Tumor-fated cells preferentially expanded along a remodeled midlobular-periportal axis and depended on ACOX1-mediated peroxisomal beta-oxidation to withstand lipotoxic and oxidative stress. Spatial and lineage analyses further identified a sequential lipid-associated macrophage niche, in which monocyte-derived LAMs engaged tumor-fated hepatocytes through an LGALS9-P4HB axis, and P4HB inhibition suppressed tumor expansion. These findings define liver tumor initiation as a lineage-restricted process licensed by peroxisomal metabolic adaptation and macrophage-derived niche signals.

cancer biology↗

bioRxiv2026

Reduced LANCL1-AS1 in old human skeletal muscle diminishes mitochondrial activity, shortens mt-mRNA poly(A) tails, and suppresses myogenesis

Regeneration of skeletal muscle preserves muscle mass and function, which decline with age. Here, we sought to identify long noncoding (lnc)RNAs involved in skeletal muscle myogenesis and potentially relevant to muscle aging. Cross-sectional analysis of skeletal muscle transcriptomes from healthy 22-through 89-year-old individuals revealed lncRNA LANCL1-AS1 among the top declining transcripts. Conversely, LANCL1-AS1 increased robustly during skeletal myogenesis and promoted myogenic differentiation in culture. Affinity pulldown by ChIRP followed by mass spectrometry revealed that LANCL1-AS1 associated with the mitochondrial protein LRPPRC, enhancing the formation of the chaperone complex LRPPRC-SLIRP, which maintains longer poly(A) tails of mitochondrial (mt-)mRNAs and stabilizes mt-mRNAs. Importantly, while myoblasts from old rhesus monkey muscle expressed lower levels of LANCL1-AS1 and mt-mRNAs, and displayed lower mitochondrial activity than young monkey myoblasts, overexpressing LANCL1-AS1 in old myoblasts restored mitochondrial activity and myogenesis. We propose that the age-associated reduction in LANCL1-AS1 contributes to impaired mitochondrial function and reduced myogenic capacity in aging skeletal muscle.

molecular biology↗

bioRxiv2026

A High-Confidence Atlas of Protein Methylation Enables AI-Driven Detection of Methylated Peptides

Lysine and arginine methylation regulate chromatin dynamics, transcription, and cellular signaling, however confident mass spectrometry (MS)-based detection and localization of this modification remain challenging. We reanalyzed eight public human methylation-enriched datasets using an open and standardized workflow that integrates database searching via the Trans-Proteomic Pipeline with a decoy-based statistical method for the independent estimation of false localization rates (FLR). This yielded a high-confidence Human Methylation Atlas of 1,828 sites (57 methyl-lysine, 1,771 methyl-arginine) across 1,021 proteins, classified into Gold, Silver, and Bronze confidence tiers. This is far fewer sites than reported in previous studies, reflecting the application of stringent FLR control, and what we hypothesise is potential high-false discovery in previous analyses. We then leveraged this resource to adapt a deep learning-based methodology for the improved detection of methylated peptides. Three mouse methylation-enriched datasets were reanalysed to augment training, and the phosphoproteomics-trained AHLF (ad hoc learning of peptide fragmentation) model was fine-tuned by transfer learning to create AHLF-Methylation. The model achieved mean ROC-AUC values of 0.824 on human spectra, and 0.829 on combined human-mouse spectra. The atlas is available through PTMeXchange and PRIDE, with curated site evidence integrated into UniProt and PeptideAtlas.

bioinformatics↗

bioRxiv2026

ProLoc: Text-guided Localization of Protein Functional Regions

MotivationProtein function is often mediated by specific sequence regions, such as domains, motifs and functional sites. Identifying these regions is important for understanding protein mechanisms, annotating newly sequenced proteins and prioritizing residues for experimental validation. However, existing protein function prediction and protein-text models mainly capture global protein-level associations, making it difficult to determine which residues support a given textual functional description. This limits their use for mechanistic interpretation and residue-level experimental prioritization. ResultsWe introduce text-guided protein functional region localization, a span-level grounding task that identifies residue regions corresponding to natural-language functional descriptions. We construct an InterPro-derived localization benchmark of explicit protein-text-region examples, covering both domain-level and functional-site annotations with sequence-similarity-aware splits and a unified span-level evaluation protocol. We further propose ProLoc, a text-conditioned localization model built on raw ESM2-650M and PubMedBERT with direct residue-level localization and anchor-free span proposal generation. On the held-out test set, ProLoc substantially outperforms window-based adaptations of representative protein and protein-text models. Its direct output achieves the strongest single-region localization performance, reaching 0.7730 IoU@1, while its anchor-free proposal output improves visible multi-site recovery, reaching 0.9671 VM R@10 IoU50 and 0.9489 VM All-Hit@50. Availability and ImplementationSource code and evaluation scripts are available at https://github.com/ShiDeng7rz/Proloc. The processed benchmark and data splits are archived at Zenodo: https://doi.org/10.5281/zenodo.20729714. Contactliupeishuo@nju.edu.cn

bioinformatics↗

bioRxiv2026

Sequential and coordinated control of human plasma cell differentiation by IRF4 and BLIMP1 utilizing a discriminating ISRE/EICE motif lexicon

The transcription factors IRF4 and BLIMP1 (PRDM1) promote plasma cell (PC) differentiation by repressing B cell identity genes while inducing the unfolded protein response, ER/Golgi biogenesis, and immunoglobulin secretion. How IRF4 and BLIMP1 partition and coordinate their genomic activities during plasma cell differentiation remains unresolved. Using naive human B cells and a stepwise in vitro differentiation system, we performed CRISPR/Cas9 perturbations of IRF4 or PRDM1 in plasma cell precursors followed by single-cell RNA sequencing. Despite their mutually reinforced expression and shared recognition of related IRF-family motifs (ISREs and EICEs), loss of IRF4, but not of BLIMP1, yielded a stunted intermediate with incomplete silencing of B cell identity genes and defective induction of the secretory program. Multiome profiling, base-pair-resolution motif modeling, CUT&RUN, and DNA-binding assays identified non-conserved nucleotides within ISRE/EICE motifs that discriminate IRF4 from BLIMP1 binding. These findings reveal a motif-lexicon-dependent IRF4-BLIMP1 interplay, in which IRF4 first acts independently and then in concert with BLIMP1. This regulatory logic may also underlie programming of additional lymphocyte effector states.

immunology↗

bioRxiv2026

GALILEO: Embodied AI scientist for autonomous therapeutic discovery in dynamic membrane systems

Generalizable Agentic Laboratory Intelligence for Learning, Experimentation, and Optimization (GALILEO) closes the prediction-to-intervention gap in therapeutic peptide discovery. Unlike prior AI-scientist systems, GALILEO couples an Observation-Thought-Action-Summary (OTAS) reasoning loop with robotic peptide synthesis and multimodal phenotyping. Candidate peptides are retrieved from a clinically informed peptide prior (CPP) and locally edited through auditable operations. GALILEO autonomously prioritized LRRC8C and SLC25A1 branches and used wet-lab feedback to update target beliefs, sequence policies, assay choices, and mechanism hypotheses. Peptides generated under this framework blocked LRRC8C currents, perturbed osmolyte/redox homeostasis, and promoted tumor-dependent T-cell activation, while SLC25A1 peptides disrupted citrate-export metabolism, reduced extracellular acidosis, and enhanced CD8+ T-cell function. These results establish retrieval-and-editing-based physical learning as a route for auditable, experimentally grounded interventions and transferable membrane-blocker rules.

Molecular Biology↗

bioRxiv2026

Decoding Multicellular Communication Motifs from Spatial Transcriptomics with ALARMIST

Cellular organization is driven by recurrent, coordinated interactions between multiple cell types, each sending and receiving multiple signals. Existing computational methods for spatial profiling data consider only individual ligand-receptor interactions and fail to capture the higher-order interactions governing the tissue microenvironment. To address this gap, we developed ALARMIST (Assessment of Ligand And Receptor Motifs And Impacts in Spatial Transcriptomics), a probabilistic framework that infers interpretable multicellular communication patterns from spatial data. ALARMIST decomposes neighborhood-level signaling patterns into motifs: recurrent communication subnetworks involving multiple cell types and sets of enriched ligand-receptor interactions. For each cell, ALARMIST identifies its active motifs and estimates the downstream phenotypic effects of each motif on active cells. We applied alarmist to spatial datasets of lung adenocarcinoma (LUAD) and glioblastoma (GBM) to identify microenvironmental drivers of tumor progression. In paired LUAD and adenocarcinoma-in-situ (AIS) samples, ALARMIST identified an immune-active vascular motif at the tumor-normal boundary and implicated motif-active plasmacytoid dendritic cells as drivers of inflammation in early carcinogenesis. In matched low- and high-grade glioma samples, ALARMIST identified a hub-and-spoke motif centered on a malignant macrophage subpopulation, implicating a GRN-SORT1 signaling axis with a downstream impact gene set predictive of survival in low-grade glioma patients. Code for ALARMIST is available at https://github.com/tansey-lab/alarmist.

bioinformatics↗

bioRxiv2026

Integration of immunomonitoring assays with PET/CT in TB patients identifies on-treatment biomarkers

Tuberculosis (TB) continues to pose a significant global public health challenge with substantial patient morbidity and mortality. Current TB patient biomarkers lack sufficient resolution to inform treatment response and patient stratification. This necessitates the development of sensitive and reliable host biomarkers. We previously demonstrated the efficacy of TruCulture whole blood stimulation for differentiating asymptomatic TB from active pulmonary TB disease patients in endemic regions. Our systems immunology study expands upon this previous work by evaluating the potential of TruCulture to monitor longitudinal responses to TB treatment in patients from the Predict-TB trial before, during, and after 6 months of antibiotic therapy. We stimulated whole blood from TB patients (n=40) using TruCulture under four conditions (Null, Mycobacterium tuberculosis-antigen, LPS, and IL-1{beta}) at baseline (week 0), during treatment (weeks 16 and 24), and one-year follow-up post- treatment (week 72). 20/25 measured cytokines exhibited significant changes throughout treatment, with several continuing to evolve during post-therapy follow-up. Machine learning based analysis identified Mtb-Ag-induced IL-1RA (AUC = 0.90, 0.92, 0.95 at weeks 16, 24, 72) and LPS-induced NLRP3 (AUC = 0.94 at week 16) as the best protein and transcriptional biomarkers for distinguishing treated from untreated patients, strongly implicating the inflammasome response. Combining these results with the extent of lung disease assessed by FDG PET/CT scans, we showed direct disease relevance for these blood-based biomarkers. The identified biomarker profiles hold promise for improving TB patient care through early prediction of treatment responses, real-time therapy monitoring, and informed development of host-directed therapeutic strategies for clinical decision-making. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=146 HEIGHT=200 SRC="FIGDIR/small/723467v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@15ae804org.highwire.dtl.DTLVardef@136939forg.highwire.dtl.DTLVardef@15ac58org.highwire.dtl.DTLVardef@e5d8f0_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO Predict-TB clinical study overview and summary of TB-specific biomarkers identified from TruCulture whole blood stimulation system. C_FIG

immunology↗

bioRxiv2026

Spatial imprints of emergent cardiomyocyte states in the pressure-overloaded heart

Resilience to cardiac stress is essential for health, yet the relationship between cardiomyocyte (CM) stress response and local microenvironment remains unclear. Here, we combined MERFISH spatial transcriptome profiling with Cellouette, an improved cell segmentation method, to determine CM-microenvironment relationships in a mouse model of ventricular pressure overload. We report the shape, transcription profile, spatial organization, and physical connectivity for >400,000 cells across stressed and healthy tissues. Under stress, CMs adopted a spectrum of emergent transcriptional states, with advanced states marked by a metabolic and pro-fibrotic shift. To discover CM-environment relationships, we performed a network analysis of physical cell connectivity combined with cell-type-specific profiling. We found that pro-fibrotic CM progression was tightly linked to distinct local microenvironments, and CM metabolic shifts could be inferred from transcriptional patterns in neighboring non-CM cells, revealing microenvironmental imprints of disease. We thus provide a resource for understanding the heterogeneity of outcome during cardiac pressure overload. HighlightsO_LICellouette provides accurate segmentation for single-cell spatial transcriptomics in cardiac tissue. C_LIO_LIPressure overload creates spatial gradients of cardiomyocyte pro-fibrotic states. C_LIO_LICardiomyocyte pro-fibrotic progression is linked to changes in local cell composition and gene expression. C_LIO_LITranscriptional states of non-muscle cells predict metabolic state of adjacent cardiomyocytes. C_LI

genomics↗

bioRxiv2026

Replication fork remodeling proteins, Smc5/6 and Rtt107, promote palindrome-mediated genome instability

Palindromic sequences are a potent source of genomic instability that can lead to cancer and hereditary diseases in humans. Molecular evidence shows that palindrome instability results from the formation of secondary structures, such as hairpins and cruciforms, which are cleaved by structure-specific nucleases. However, the mechanisms underlying cruciform formation and cleavage at palindromic sequences in eukaryotic cells remain incompletely understood. Here, we describe a pathway for secondary structure formation and chromosomal breakage at palindromes involving DNA helicase Mph1, Rad51 recombinase, Rad54 ATPase DNA strand remodeler, Rtt107 scaffold protein, and the multifunctional Smc5/6 complex. Deletion or mutation of any of these components results in a similar reduction in double-strand breaks at an Alu palindrome and a significant decrease in chromosomal rearrangements. We propose that Mph1, Rad51, and Rad54 work together at stalled replication forks to generate cruciform structures via fork remodeling, while Smc5/6 and Rtt107 mark the cruciforms, indicating an appropriate substrate for nuclease cleavage. As members of this pathway are conserved in humans, the uncovered mechanisms may underlie genomic instability at palindrome sites involved in disease etiology.

molecular biology↗