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Liang, J.

Publications and source records attributed to Liang, J..

At least 55 records · Page 3Linked to original sources

Chromatin compaction upon CDK12 inhibition drives long gene silencing and a combinatorial lethal dependency on PAF1

Loss-of-function mutations in cyclin-dependent kinase 12 (CDK12) define an aggressive subtype of metastatic castration-resistant prostate cancer (mCRPC) characterized by genomic instability, and depletion of CDK12 activity downregulates the expression of long DNA repair genes. While these transcriptional defects are well-documented, potential alterations in chromatin that may topologically affect this silencing and the subsequent adaptive survival mechanisms of tumor cells remain poorly understood. Here, we employ a dynamic multi-omics strategy to map the remodeling of the RNA Polymerase II (RNA Pol II) complex and chromatin landscape. We utilized 5-ethynyl uridine (5-EU) metabolic labeling combined with mass spectrometry (MS) to specifically capture the transcriptionally active RNA Pol II complex, distinguishing active elongation complexes from static background, and map how its interactome changes when the activity of the major transcriptional kinases CDK7, CDK9 or CDK12/13 is inhibited. These data are then integrated with ATAC-seq, transcriptomics, and targeted synthetic lethality screen to validate findings from the RNA Pol II capture. We show that, unlike CDK9 inhibition, CDK12/13 inhibition triggers a progressive chromatin compaction. This is characterized by the decrease in the binding activity of CTCF to chromosomes closing, which acts as a physical blockade specifically silencing long genes when CDK12 activity is lost. In response to this topological remodeling, cells launch an adaptive survival program by recruiting the transcription elongation factor PAF1 and the DNA damage sensor DDB1 to the stalled RNA Pol II. We identify PAF1 as a critical vulnerability in this context. Collectively, we identify CDK12 as a regulator of chromatin topology rather than merely an elongation kinase. The chromatin compaction upon CDK12/13 inhibition creates a unique dependency on the PAF1-mediated adaptive remodeling. Specifically, targeting PAF1 converts this stress response into a lethal trap, establishing a potent, kinase-selective combination lethal strategy for CDK12-deficient prostate cancer.

cancer biology↗

Prevalence and Actionability of MTAP Loss in Oncogene-Driven Lung Cancer

BackgroundMethylthioadenosine phosphorylase (MTAP) loss co-occurs with actionable genomic alterations in non-small cell lung cancer (NSCLC) and creates vulnerability to protein arginine methyltransferase 5 (PRMT5) inhibition. Estimates of prevalence of MTAP loss rely on next-generation sequencing which can underestimate copy losses. Moreover, the activity of PRMT5 inhibitors in oncogene-driven NSCLC is not well established. MethodsWe assessed MTAP expression by immunohistochemistry (IHC) in 243 NSCLCs (n=132 early stage, n=111 metastatic), including 33 specimens with paired lymph nodes. Antiproliferative activity of PRMT5 inhibitor monotherapy and in combination with tyrosine kinase inhibitors (TKIs) was evaluated in MTAP-deleted NSCLC cell lines harboring EGFR or KRAS mutations or ALK rearrangements. ResultsAmong 243 NSCLC specimens from 240 patients (72% with driver alterations, 90% adenocarcinoma), MTAP loss was identified in 43 (18%) specimens from 40 (17%) patients, including 18 (14%) early-stage and 22 (20%) metastatic tumors. MTAP loss occurred in 24% of stage 4 driver-positive NSCLCs versus 14% of driver-negative tumors (p=0.314). Twenty (61%) lung-nodal pairs demonstrated concordance; eight cases only exhibited decreased MTAP expression in nodes. Variable sensitivity to PRMT5 inhibitors was observed in 22 MTAP-deleted NSCLC cell lines (9 EGFR-mutant, 7 KRAS-mutant, 6 ALK-rearranged), with responses seen in TKI-sensitive and TKI-resistant lines. SDMA (symmetric dimethylarginine) expression did not predict PRMT5 inhibitor sensitivity. TKI + PRMT5 inhibitor combos had greater activity than monotherapy. ConclusionsMTAP loss occurs in 1-in-5 oncogene-driven metastatic NSCLCs. PRMT5 inhibitor activity is independent of TKI exposure, driver alteration, and SDMA expression and enhanced by addition of TKI. These findings support clinical evaluation of PRMT5 inhibitor + TKI combinations for advanced NSCLC.

cancer biology↗

On-virion structural dynamics reveal temperature- and receptor-coordinated activation of an alphacoronavirus spike

Human alphacoronaviruses primarily infect the human upper respiratory tract, yet how physiological temperature and receptor-binding coordinate viral spike (S) protein activation remain unclear. Using cryo-electron tomography and subtomogram averaging, we directly visualized the structural dynamics of S on human coronavirus 229E (HCoV-229E) virions under physiologically relevant temperatures and in the presence of the host receptor human aminopeptidase N (hAPN). We identified two prefusion S2 conformations, compact and loose, that interconvert reversibly by temperature, revealing intrinsic S2 "breathing" on virions. Receptor-binding domain (RBD)-up conformations are rare on apo virions but are promoted at physiological temperature and stabilized upon receptor binding. hAPN can bind bivalently to neighboring S, forming Gemini S-hAPN complexes. Receptor incubation further promotes conversion from prefusion to postfusion S, an effect enhanced at 33. Together, our results demonstrate an optimized temperature for the HCoV-229E viral fitness, establish temperature and receptor binding as synergistic regulators of alphacoronavirus S activation and define an integrated, on-virion model of S conformational transitions during viral entry. These findings provide a structural framework for understanding alphacoronavirus infectivity.

microbiology↗

Real-time single-molecule imaging in zebrafish embryos uncovers non-canonical translation

Precise spatiotemporal control of protein synthesis is essential during embryogenesis, yet directly measuring translation kinetics in vivo remains challenging in vertebrates. In particular, it remains unclear how translation efficiency is determined for key developmental regulators, and which kinetic steps limit their production. Here, we used ALFA array-based nascent chain labeling combined with lattice light-sheet microscopy to visualize bmp2b translation in real time and at single-molecule resolution in early zebrafish embryos. When combined with MS2/MCP labeling to visualize all bmp2b mRNAs, we found that only some of them are being actively translated, suggesting that limited mRNA translation competence contributes to overall translation efficiency. We found that bmp2b translation operates below a maximal initiation regime, as replacement of its UTRs with viral UTRs increases ribosome loading. Furthermore, the bmp2b, but not actb2, 5'UTR supports cap-independent translation with ribosome loading comparable to cap-dependent initiation. Altogether, this approach provides a quantitative in vivo framework to dissect translation kinetics during early vertebrate development.

developmental biology↗

Whole-Brain Convergence of Real-World Visual Expertise beyond Faces: Meta-Analytic Evidence for Core-Adaptive Neural Architecture

Visual expertise--the ability to discriminate highly similar exemplars quickly and accurately within a category--supports skilled performance across real-world domains and is supported by distributed neural systems. We focus on non-face expertise to test cross-domain convergence in acquired real-world visual skills, treating faces separately because socially embedded, sensitive-period-constrained processing could blur this inference. It remains unresolved whether non-face expertise across heterogeneous domains converges on a shared, domain-general whole-brain architecture, or instead recruits domain-contingent neural configurations that vary with task and stimulus demands. We conducted a coordinate-based meta-analysis of 22 task-fMRI studies spanning 11 real-world non-face expertise domains (579 participants, 210 peak-activation foci). Primary analysis revealed a robust, right-lateralized parieto-temporo-occipital circuit centered on the middle occipital gyrus, middle temporal gyrus, angular gyrus and adjoining inferior parietal lobule. We propose that this circuit constitutes a domain-general neural core that integrates fine-grained visual features with semantic associations while supporting attention-guided recognition of visually similar objects in expert performance. Subgroup and meta-regression analyses uncovered a complementary adaptive component, the engagement of which varied systematically with representational and contextual factors. Pictorial stimuli and expert-novice contrasts reliably strengthened recruitment of the right-hemisphere core, whereas symbolic stimuli engagement toward left temporal regions while selectively re-engaging right-core nodes. In addition, male-skewed samples showed attenuated left-hemisphere activation. Together, these findings delineate a stable right-hemisphere neural scaffold underlying non-face visual expertise, flexibly supplemented by left-hemisphere systems as a function of stimulus format, task demands, and demographic context, providing a whole-brain reference framework for future studies. HighlightsO_LIA coordinate-based meta-analysis integrates 22 whole-brain task-fMRI studies of real-world non-face visual expertise. C_LIO_LIResults delineate a core-adaptive architecture supporting non-face expertise across domains. C_LIO_LIA right-lateralized parieto-temporo-occipital core (AG, MOG, MTG, adjoining IPL) shows convergent recruitment across non-face domains. C_LIO_LIAdaptive left-hemisphere regions (MTG/STG/ITG/IFG; plus FG/IOG/insula) are flexibly engaged with task and stimulus demands. C_LIO_LIFindings refine neurocognitive accounts of perceptual expertise and provide a domain-spanning whole-brain reference framework for future studies. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/696823v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@14119a6org.highwire.dtl.DTLVardef@fb04cforg.highwire.dtl.DTLVardef@1f8cd35org.highwire.dtl.DTLVardef@168798a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

A K27-linked Ubiquitin Checkpoint Controls NOTCH Homeostasis

Cell surface receptors such as NOTCH1 must be tightly regulated to ensure developmental fidelity and prevent pathological activation. Although the proteolytic steps culminating in nuclear NOTCH1 signaling are established, how cells prevent excessive or uncontrolled activation has remained unresolved. Here we identify the autophagy-related protein UVRAG as a negative regulator of NOTCH1. Upon receptor activation, UVRAG, acting independently of autophagy, recruits and activates the E3-ligase ITCH to catalyze K27-linked ubiquitination of membrane-tethered NOTCH1, thereby licensing ESCRT-dependent lysosomal degradation. Disruption of the UVRAG-ITCH-ESCRT axis stabilizes activated NOTCH1 intermediates and amplifies oncogenic signaling. In T-cell leukemia models driven by constitutive NOTCH1 activity, restoring UVRAG expression reinstates receptor turnover, suppresses disease progression, and improves therapeutic response. These findings define a ubiquitin-directed safeguard circuit that enforces NOTCH1 signaling homeostasis and reveals a tunable axis for intervention in NOTCH1-driven cancers.

molecular biology↗

Dissecting sequence determinants of DNA methylation and in silico perturbation

DNA methylation shapes cellular identity and genome function, yet the sequence logic that governs its establishment remains largely unresolved. Here we present MethylAI, a cross-species-pretrained and human-specialized deep learning framework that predicts single-CpG methylation states directly from genomic sequence with high fidelity. Through quantitative attribution, MethylAI uncovers intrinsic cis-regulatory principles embedded in DNA, revealing conserved transcription factor (TF) motifs whose influence extends beyond CpG composition. Activated motifs demarcate gene-body CpG islands, encode lineage-defining methylation states, and align with TF occupancy and diverse histone modifications, thereby linking sequence syntax to local chromatin regulation. CTCF perturbation experiments validated MethylAI-predicted methylation shifts at activated motifs, showing strong concordance with in silico perturbations. Mapping genetic variants onto methylation-linked active motifs further uncovered widespread connections to zinc-finger TF families, providing mechanistic insight into how noncoding variation contributes to human traits and diseases. By transforming DNA sequence into interpretable methylation grammar, MethylAI establishes a generalizable framework for decoding the regulatory architecture of the human epigenome.

genomics↗

A Chromatin-Structure-Guided Framework for Predictive and Interpretable Regulatory Genomics

Chromatin organization shapes gene regulation by linking distal elements across megabase scales, yet most predictive genomics models still treat the genome as linear, without incorporating three-dimensional structure. Hi-C provides genome-wide chromatin conformation information, but its contact maps are population-averaged, distance-biased, and noisy, obscuring the biologically specific contacts. We present CHROME, a framework built on a self-avoiding polymer ensemble null model that identifies physically specific, non-random Hi-C contacts. By integrating these contacts into graph representations, CHROME enables efficient information transfer across spatially connected loci. It integrates sequence, chromatin accessibility, or pre-trained embeddings into a graph attention architecture to predict cell line-specific ChIP-seq profiles, consistently outperforming local encoder baselines and generalizing to an unseen cell line. The resulting graph embeddings also enhance prediction on tissue-specific eQTL and ClinVar variant pathogenicity, outperforming local sequence-based embeddings. Beyond predictive performance, CHROME provides interpretability through attention-derived neighbor-to-center contributions that reveal how spatially connected loci influence local regulatory activity over multi-megabase distances. Together, these results show that incorporating physically validated chromatin interactions enables more accurate and interpretable modeling of gene regulation and variant effects.

genomics↗

Network modularity reveals context and state-dependent reorganization of time-varying functional connectivity in single-cell resolved neural activity recordings

An important goal of neuroscience is to understand how biological neural networks organize activity at multiple scales to enable complex information processing and behavioral output. To address this challenge, large-scale neural activity datasets with increased resolution and wider coverage have become more prevalent across many model systems. However, bridging the gap in scale between changes in pairwise functional connectivity between neurons and changes in brain-wide organization of activity remains a key challenge. In this work, we demonstrate application of modularity-based community detection and network modularity to single-cell resolved recordings, for the first time, as a method to summarize complex changes in time-varying functional connectivity, facilitating comparisons across multiple time windows, recordings, and conditions. We apply these methods to both single-cell resolved multi-cell and whole-brain activity recordings. In the multi-cell recordings, we find that food odor changes functional connectivity between existing network modules in a C. elegans locomotory interneuron network, rather than reorganizing them. In spontaneous whole-brain activity, we identify several key hub neurons and combinations that significantly destabilize module assignments when silenced. Together, these results demonstrate community detection and modularity as a method for detecting context and network state-dependent changes in functional connectivity at the intermediate scale of network modules in single-cell resolved neural activity. Results from these analyses facilitate future investigation of mechanisms that mediate organization of neural activity at intermediate scales.

neuroscience↗

Aversive Learning Induces Context-Gated Global Reorganization of Neural Dynamics in Caenorhabditis elegans

Learning generates experience-dependent changes to the brain. However, how neurons of diverse functions and connectivity reorganize and modulate their activities to generate coherent changes while preserving essential functions is not well understood. Here, we address this question using an aversive olfactory learning paradigm whereby Caenorhabditis elegans learns to reduce its olfactory preference for pathogenic bacteria. Using functional imaging during olfactory stimulation in naive and trained animals, we show that, at brain-wide scale, cell type-by-cell type, learning induces context-gated reconfiguration of the organization of neural activity throughout the brain to alter neural responses only during bacteria-discrimination task, while leaving intact bacteria-sensing functions. We found that the context-gated encoding of learning is globally distributed across layers of the nervous system, composed of neurons carrying information of context or learning experience. In particular, aversive training modulates multiple functional connections within the nervous system, including those between sensory neurons and interneurons, as well as those among interneurons, in a context-gated manner. At the systems level, training modulates correlated activity of neural populations; we found that low-dimensional temporal patterns of population activity correlate well with locomotory gaits that express olfactory preferences. Upon training, the rotation and contraction of the low-dimensional neural manifolds shifts the brain into predisposed states for the context-gated display of learned behavior. Because animals encounter unpredictable environments in life, efficient learning about relevant cues while maintaining other functions is essential for survival. Our findings uncover network-level mechanisms that help explain how the brain reorganizes its activity patterns to both encode new experience and preserve essential functions.

neuroscience↗

PlantScience.ai: An LLM-Powered Virtual Scientist for Plant Science

The accelerating growth of plant science literature presents a major challenge for researchers seeking to extract accurate, up-to-date knowledge from an increasingly fragmented and domain-specific corpus. General-purpose large language models (LLMs), while powerful, often misinterpret plant science terminology and lack mechanisms for source traceability. We created PlantScience.ai, a virtual plant biology scientist powered by our automated scientific knowledge graph construction pipeline (AutoSKG). PlantScience.ai exhibits expert-level reasoning in plant biology and maintains scholarly rigour in its citations. Through continuous learning, it integrates the latest research, ensuring that its knowledge base remains current and scientifically robust. Apart from providing the answers to the scientific questions, PlantScience.ai can interact with human scientists, follow instructions, and retrieve information with citation awareness, grounding each response in primary sources to ensure accuracy and verifiability. PlantScience.ai marks a pivotal advance toward a collaborative scientific paradigm in which virtual and human plant scientists work synergistically to accelerate discovery while preserving the unique value of human insight. PlantScience.ai is available at https://plantscience.ai.

plant biology↗

Machine learning guided engineering of conditional split inteins for regulated protein splicing in mammalian cells

Inteins are proteins that excise themselves from precursor proteins and connect the flanking polypeptides with a peptide bond. Split inteins consist of two independently translated fragments that must associate to become splice-competent. They can be used for diverse post-translational protein modifications. Using the ML Int&in algorithm, we predicted unnatural split sites in two of the fastest and most efficient split inteins, gp41-1 and NrdJ-1, to generate functional variants with fragments of reduced mutual affinity. We harness this feature to create conditional versions of these inteins by controlling the physical proximity of the intein fragments with a light-inducible heterodimerization system. The resulting light-activatable gp41-1 and NrdJ-1 inteins enabled blue light-dependent control of Cre recombinase activity in mammalian cells, which we exploited to spatially control apoptosis via localized expression of truncated BID (tBID) and caspase-8. This work highlights the versatility of Int&in for designing conditional inteins for precise spatiotemporal protein regulation.

synthetic biology↗

Decoding with multivariate pattern analysis is superior for optically pumped magnetometer-based magnetoencephalography compared to superconducting quantum interference device-based systems

BackgroundMultivariate pattern analysis (MVPA) has become an increasingly important method for decoding distributed brain activity from neural electrophysiological recordings by leveraging both temporal and spatial features. These multivariate approaches have proven important for both cognitive neuroscience and brain-computer interfaces. MVPA might benefit from magnetoencephalography (MEG) systems based on optically pumped magnetometers (OPMs), as these sensors can be placed closer to the scalp, providing higher spatial resolution compared to conventional MEG systems that rely on superconducting quantum interference devices (SQUIDs). As OPM-based MEG systems become available at more institutions, it is essential to experimentally compare their performance with traditional SQUID-based systems using MVPA. MethodsWe adapted a visual object-word paradigm from a previous study, originally implemented on a TRIUX MEGIN SQUID system, to the FieldLine HEDscan OPM system. Participants were recruited and we recorded their ingoing brain activity while did the same task in both systems. Visual stimuli of different objects were presented alternately in two modalities: pictures and the corresponding written words. For each modality, MVPA was used to classify the objects from OPM and SQUID magnetometers data respectively. To further investigate the advantages of OPM, we evaluated the effect classification accuracy of two spatial factors by controlling the number of sensors included and the spatial frequency content of the sensor data. ResultsWe found higher time-resolved decoding accuracy for the OPM compared to the SQUID data. Moreover, OPMs show higher classification performance compared to SQUIDs when controlling for the same number of sensors; consistently, the OPM system required fewer sensors to reach the performance limit of the SQUID system. Our analysis considering the spatial frequency content of the signal revealed that decoding accuracy plateaued for the SQUID system at lower spatial frequencies while the performance of the OPM system continued to improve when higher-order spatial components were included. ConclusionOur OPM-MEG system outperformed the SQUID-MEG system on MVPA on decoding of visual processing. This advantage of OPM is driven by its higher spatial resolution, resulting from the sensors being positioned closer to the head and thus able to capture higher spatial frequency components of the brain signal. OPM may facilitate cognitive neuroscience research as well as brain-computer interfaces by providing higher sensitivity when employing paradigms using multi-variate data analysis.

neuroscience↗

Ecological constraints foster both extreme viral-host lineage stability and mobile element diversity in a marine community

Phages are typically viewed as very rapidly evolving biological entities. Little is known, however, about whether and how phages can establish long-term genetic stability. We addressed this eco-evolutionary question in an open marine animal associated system, through two longitudinal samplings years apart in an oyster farm, obtaining >1,000 virulent phages and >600 Vibrio crassostreae strains. Surprisingly, lineages of phage and bacteria were very persistent, with some phages remaining strictly identical after four years. The phage-vibrio infection network remained modular with multiple lineages co-habitating within individual oysters for long periods of time. Seasonal restriction of V. crassostreae, overwintering in wild oysters, and limited viral decay may explain phage stability. Oysters also act as hotspots of activity of diverse mobile genetic element (MGE), hosting plasmids, prophages, phage-plasmids and entirely new classes of satellite-plasmids. Our findings demonstrate how nested ecological constraints can stabilize viral lineages: oysters house vibrio populations that escape host immunity, vibrios restrict phages via receptors and defenses, and satellites parasitize their cognate helper phages. We suggest that ecological context can favor the long-term maintenance of viral lineages and stabilize MGE persistence in the ocean, even amid ongoing mutation and antagonistic co-evolution.

microbiology↗

Enhancing Volatile Fatty Acid Accumulation in Seaweed-Arrested Anaerobic Digestion via a Two-Tier Framework of Engineering Diagnostics and Microbial Surveillance

This study presents a two-tier framework for brown seaweed-arrested anaerobic digestion (SW-AAD) by coupling engineering diagnostics (tier-1) with microbial surveillance (tier-2) to transform conventional digesters into volatile fatty acid (VFAs) biorefineries. In 70-day lab-scale batch tests (volume: 2 L), engineering diagnostics revealed that sequential additions of brown seaweed elevated salinity to 3.3% ash content, stabilized pH at 5.8-6.1, collapsed the CH/CO2 ratio from 2.98 to <0.04, suppressed biogas by 96%, and boosted carbon-conversion efficiency from 10% to 52%. More than half of the influent carbon was redirected from methane to a liquid-phase VFAs pool, dominated by butyrate, hexanoate, and acetate, peaking at 14.5 g L-{superscript 1}. Microbial surveillance using 16S rRNA sequencing presented a 10-fold decline in methanogens, alongside an increase in salt- and acid-tolerant acidogenic microbial families, including Lachnospiraceae, Ruminococcaceae, and Clostridiaceae, as well as seaweed-derived microbial families, including Psychromonadaceae, and Marinomonadaceae. Temporal synchrony and asynchrony-resolved analysis confirmed a strong correlation between two tiers, revealing an operational window featured with two patterns: a rapid engineering parameter response (where changes in engineering parameters were followed by a decline in methanogens within 0-3 days) and a slower microbial restructuring (where the surge in VFA concentration lagged the enrichment of seaweed-derived acidogens by 1-5 days). Based on this operation window, feedback control strategies were simulated for SW-AAD, indicating that cumulative VFAs (cVFAs) yield could be bolstered from 11.38 to 16.13 g COD L-{superscript 1} (+41.8%). A techno-economic assessment (TEA) revealed that this VFA-targeted SW-AAD can reduce capital expenditure by [~]20% compared to conventional AD. This study underscores the promise of asynchrony-resolved analysis of SW-AAD systems for robust and economically viable VFAs production from organic waste. Graphics O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/680780v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1dc596dorg.highwire.dtl.DTLVardef@1731cadorg.highwire.dtl.DTLVardef@5fe025org.highwire.dtl.DTLVardef@74d8d3_HPS_FORMAT_FIGEXP M_FIG C_FIG Environmental synopsisBrown seaweed-arrested anaerobic digestion (SW-AAD) leverages seaweed-driven salinity, and acidification to suppress methanogenesis, diverting >50% of carbon to VFAs (14.5 g COD L-{superscript 1}) while cutting methane by 99%. A two-tier framework couples engineering diagnostics with microbial surveillance and asynchrony-resolved analysis, enabling feedback control and low-emission waste valorization in digesters.

bioengineering↗

Phosphatidylcholine Metabolism Controls Alveolar Progenitor Renewal and Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease marked by alveolar type 2 (AT2) stem cell dysfunction and excessive matrix deposition, with no effective treatments. Recent advances have recognized that AT2 cells act as stem cells, in addition to their role in the production of pulmonary surfactants in the distal alveolar space. We and others have reported a failure of AT2 regeneration and a loss of AT2 cells in IPF. We recently further reported that there is a defect in lipid metabolism in IPF AT2 cells and we discovered a selective loss of lysophosphatidylcholine acyltransferase 1 (LPCAT1) in AT2 cells from IPF, as well as in AT2 cells from bleomycin-injured mice. Pharmacological and genetic experiments confirm that LPCAT1 is required for AT2 cell renewal in 3D organoid assays. AT2 cell-specific Lpcat1 deletion resulted in reduced AT2 renewal, spontaneous lung fibrosis, and heightened susceptibility to bleomycin-induced fibrosis in mice in vivo. Expression-based high-content drug screening with an LPCAT1 knock-in cell line identified several drug families that upregulated LPCAT1 expression. We further confirmed that anti-malarial artesunate and PLA2 inhibitor ONO-RS-082 increased LPCAT1 mRNA expression, promoted AT2 renewal, and attenuated bleomycin-induced lung fibrosis in mice in vivo. Our findings establish LPCAT1 as a critical regulator of AT2 renewal and lipid metabolism in IPF, suggesting that reactivation of LPCAT1 could offer a novel therapeutic strategy for restoring alveolar progenitor function and mitigating lung fibrosis.

cell biology↗

ChromPolymerDB: A High-Resolution Database of Single-Cell 3D Chromatin Structures for Functional Genomics

The three-dimensional (3D) organization of chromatin plays a critical role in regulating gene expression and genomic processes like DNA replication, repair, and genome stability. Although these processes occur at the individual-cell level, most chromatin structure data are derived from population-averaged assays, such as Hi-C, obscuring the heterogeneity of single-cell conformations. To address this limitation, we developed a polymer physics-based modelling framework, the Sequential Bayesian Inference Framework (sBIF), that deconvolutes bulk Hi-C data to reconstruct single-cell 3D chromatin conformations. To support a broader use of sBIF, we created ChromPolymerDB, a publicly accessible, high-resolution database of single-cell chromatin structures inferred by sBIF. The database contains [~]108 reconstructed 5 kb-resolution single cell structures, spanning over 60,000 genomic loci across 50 human cell types and experimental conditions. ChromPolymerDB features an interactive web interface with tools for 3D structural analysis and multi-omics integration. Users can explore associations between chromatin conformation and gene expression, epigenetic modifications, and regulatory elements. The platform also supports comparative analyses to identify structural changes across cell types, developmental stages, or disease contexts. ChromPolymerDB offers a unique resource for researchers studying the relationship between genome architecture and gene regulation, and for advancing comparative 3D genomics. ChromPolymerDB is available online at https://chrompolymerdb.bme.uic.edu/. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/678816v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@110c807org.highwire.dtl.DTLVardef@bc713forg.highwire.dtl.DTLVardef@1af0ea9org.highwire.dtl.DTLVardef@1eba638_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Geographical variation drives adaptive equilibrium of the P. falciparum sickle-associated mutations

The recent discovery of genetic mutations in Plasmodium falciparum--the most lethal malaria parasite--that enable it to overcome the protective effects of sickle cell trait, raises fundamental questions about the underlying biological and evolutionary interactions. Here we develop a geostatistical model to compare sickle haemoglobin genotype frequencies to the Plasmodium falciparum sickle-associated alleles across global populations, and find a robust association at multiple geographical scales, implying that sickle drives positive selection for these parasite mutations. A model of parasite evolution and an analysis of local haplotype patterns suggest that key features of these mutations - that they are polymorphic in all African populations and are mutually correlated despite lying in different genome regions - are caused by geographical variation in selection pressure, and that the alleles may have been maintained by balancing selection over timescales comparable to the age of the sickle mutation itself. The predicted impact of this host-parasite interaction on disease outcomes varies widely across populations, and functional data are needed to discover the biological mechanisms involved.

genetics↗