Biology subjects

Zhang, Z.

Publications and source records attributed to Zhang, Z..

At least 487 records · Page 27Linked to original sources

bioRxiv2025

Deciphering the role of histone modifications in memory and exhausted CD8 T cells

Exhausted CD8 T cells (TEX) arising during chronic infections and cancer have reduced functional capacity and limited fate flexibility that prevents optimal disease control and response to immunotherapies. Compared to memory (TMEM) cells, TEX have a unique open chromatin landscape underlying a distinct gene expression program. How TEX transcriptional and epigenetic landscapes are regulated through histone post-translational modifications (hPTMs) remains unclear. Here, we profiled key activating (H3K27ac and H3K4me3) and repressive (H3K27me3 and H3K9me3) histone modifications in naive CD8 T cells (TN), TMEM and TEX. We identified H3K27ac-associated super-enhancers that distinguish TN, TMEM and TEX, along with key transcription factor networks predicted to regulate these different transcriptional landscapes. Promoters of some key genes were poised in TN, but activated in TMEM or TEX whereas other genes poised in TN were repressed in TMEM or TEX, indicating that both repression and activation of poised genes may enforce these distinct cell states. Moreover, narrow peaks of repressive H3K9me3 were associated with increased gene expression in TEX, suggesting an atypical role for this modification. These data indicate that beyond chromatin accessibility, hPTMs differentially regulate specific gene expression programs of TEX compared to TMEM through both activating and repressive pathways.

immunology↗

bioRxiv2025

Distinct Bomanins at the Drosophila 55C locus function in resistance and resilience to infections

Host defense against many Gram-positive bacteria and fungal pathogens is mainly provided by the Toll-dependent systemic immune response in Drosophila. While antimicrobial peptides active against these categories of pathogens contribute only modestly to protection, Bomanin peptides are major effectors of the Toll pathway. Remarkably, flies deleted for the 55C locus that contains 10 Bomanin genes are as sensitive as Toll pathway mutant flies to these infections. Yet, the exact functions of single Bomanins in resistance or resilience to infections remain poorly characterized. Here, we have extensively studied the role of these Bomanin genes. BomT1 functions in resistance to Enterococcus faecalis while playing a role in resilience against Metarhizium robertsii infection, like BomS2. BomT1 and BomT2 prevent the dissemination of Candida albicans throughout the host, even though they are not sufficient to confer protection to immunodeficient flies against this pathogen in survival experiments. Furthermore, BomT1 and BomBc1 mutants are sensitive to an Aspergillus fumigatus ribotoxin. We conclude that 55C Bomanins have defined albeit sometimes overlapping roles in the different facets of host defense against infections.

immunology↗

bioRxiv2025

RIP2 inhibits DOCK8-mediated platelet dense granule release and alleviates experimental myocardial infarction

ObjectiveReceptor-interacting protein 2 (RIP2) is an essential mediator of inflammation and innate immunity downstream of pattern recognition receptors (PRRs). Platelets express RIP2, while its role in platelet activation, thrombosis, and myocardial infarction (MI) is unknown. Approach and ResultsHere we show that RIP2 deficiency enhances platelet dense granule secretion in response to GPIb and GPVI activation; platelet aggregation in whole blood and adhesion under arterial shear are also increased. Consistently, RIP2 inhibitor WEHI-345 potentiates human platelet dense granule secretion and inhibits RIP2 phosphorylation induced by thrombin and collagen. These phenotypes are translated into shorter bleeding time, accelerated FeCl3-induced arterial thrombosis. Importantly, platelets from patients with coronary artery disease and mice with atherosclerosis express lower RIP2, and RIP2 deficiency deteriorates MI and cardiac function in a mouse ischemia/reperfusion model. Mechanistically, we found that platelets express dedicator of cytogenesis protein 8 (DOCK8), which is sequestered by phosphorylated RIP2 (p-RIP2), causing inhibition of Cdc42 activation and subsequent dense granule release. ConclusionsIn conclusion, RIP2 inhibits platelet activation, thrombosis, and ameliorates MI. Our results also suggest that a novel PRR-independent pathway, p-RIP2-DOCK8-Cdc42, negatively regulates platelet activation downstream of GPIb and GPVI. Platelet RIP2 pathway may be promising for therapeutic intervention of atherothrombotic diseases from early atherosclerosis stage to arterial thrombosis and MI. HighlightsO_LIRIP2 inhibits platelet dense granule release NOD2-independenly via pRIP2-DOCK8-Cdc42. C_LIO_LIThe negative regulation of RIP2 on platelet activation is translated into enhanced thrombosis, exacerbated myocardial infarction (MI). C_LIO_LIRIP2 pathway booster may be an approach for therapeutic intervention of atherothrombotic diseases. C_LI

molecular biology↗

bioRxiv2025

Deciphering of single-cell chromatin accessibility and transcriptome reveals the discrepancy for ex vivo human erythropoiesis

BackgroundErythroid cells can be generated from hematopoietic stem and progenitor cells (HSPC) derived from various sources; however, few studies decode ex vivo human erythropoiesis for the discrepancies at single-cell multi-omics resolution and uncover the underlying restraints for erythrocyte regeneration. ResultsWe deciphered ex vivo human erythropoiesis at two differentiation states from three sources at single-cell chromatin accessibility and transcriptomes level. We identified detrimental myeloid differentiation tendencies during early differentiation. These tendencies were linked to low glutamine activity in cord blood- and iPSC-derived erythropoiesis. The erythroid progenitor differentiation is restricted by cell cycle and hypoxia signaling deficiencies, which are pronounced in the iPSC-derived erythropoiesis. We delineated the erythroid differentiation trajectory of various ex vivo erythropoiesis systems, and revealed a distinct roadmap from HSC to orthochromatic erythroblast with unprecedented resolution. The integrative analysis of single-cell chromatin accessibility and transcriptome across developmental stages uncovered a dynamic coordination, and highlighted the pivotal role of chromatin accessibility and associated enhancers in regulating ex vivo erythropoiesis. Cell-cell communications in the ex vivo erythropoiesis system were not as well established as those in the BM, suggesting that modulating cell-cell communication signals in distinct ex vivo erythropoiesis system may facilitate erythrocyte regeneration. ConclusionsThis study comprehensively characterized the discrepancies and constraints in ex vivo human erythropoiesis at single-cell multi-omics resolution, offering novel strategies to overcome these constraints. These insights are critical for advancing functional erythrocyte generation and have significant implications for clinical applications.

developmental biology↗

bioRxiv2025

A biGWAS strategy reveals the genetic architecture of the interaction between wheat and Blumeria graminis f. sp. tritici

BackgroundWheat powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt) is one of the most significant diseases affecting global wheat production. Breeding for disease resistance (R) genes against Bgt often follows a boom-bust cycles, where cultivars with effective resistance are widely deployed on an expanding area until virulence emerges in the avirulence (Avr) pathogen population. While extensive effort has been devoted to identifying and cloning R genes, Avr genes remain relatively understudied, limiting our understanding of R-Avr interactions. That said, understanding R-Avr interactions is crucial for developing durable resistance strategies. ResultsWe conducted whole genome sequencing on 245 Bgt isolates collected from major wheat-growing regions in China, identifying 120 genetically unique isolates. Each of these unique isolates was inoculated and phenotyped on a diverse panel of wheat germplasm. Through Genome-Wide Association Analysis (GWAS) in both Bgt and wheat, we identified 65 Avr loci and 251 R loci overlapping with nine and eight cloned Avr or R genes, respectively. On average, each isolate carries eight Avr alleles, ranging from one to 17. Little geographical preference for Avr alleles or their combinations was observed, suggesting that disease resistance breeding against this pathogen should be coordinated at the national level. The level of resistance level is positively correlated with the number of R alleles carried by a wheat line, and the average frequency of an R allele is 2% among the wheat panel, indicating the potential for accumulating R alleles in breeding programs. We mapped 212 R-Avr interactions based on joint GWAS using both plant and pathogen genomes and cross-species epistasis, where a network of interactions was formed between wheat and Bgt. These interactions indicate that pyramiding five major R loci has the potential to confer resistance to half of the Avr loci. As a proof of concept, we successfully verified two previously described R-Avr pairs using tobacco experiments. Furthermore, we provided molecular validation evidence for three new Avr genes, including Bgt-50651, BgtE-5826 and BgtE-20009, and two new R-Avr interactions. Among them, Bgt-50651 interacts with Pm1a, Pm2a, and another unidentified R gene located near the Pm6/Pm52 interval. ConclusionOur study provides a framework for understanding the genetic interaction between plants and pathogens. The discovery of novel R/Avr loci and their complex interaction network underscores the need to integrate crop and pathogen genetic background, particularly the R/Avr allele composition, into breeding program design. These findings have significant implications for developing durable resistance strategies in wheat alongside offering valuable insights into the broader dynamics of plant-pathogen interactions.

genomics↗

bioRxiv2025

Molecular insights into early malignant transition of hepatocellular carcinoma

The molecular continuum of premalignant-to-malignant transition remains elusive in carcinogenesis, primarily due to the difficulty in sampling transitional lesions. Here, we present comprehensive genomic and immunological profiling of 21 very early hepatocellular carcinomas (veHCCs) arising within 17 cancer-prone DNs. Surprisingly, 82% of cancer-prone DNs harbored TERT alterations, suggesting a predisposing rather than causative role in malignancy transition. A substantial increase in CNA burden, rather than SNV, was noted, indicating a role of chromosome instability in malignancy transition. Additionally, veHCC-originating DNs showed immune inactivity, not falling into the prevailing paradigm that HCCs develop in a context of chronic inflammation. 43% of veHCCs showed an inflamed phenotype with relatively mild CNA burden but already exhibited immune evasion features. Two major evolutionary scenarios were thus proposed: 1) CNA-dominant progression and 2) early immune evasion of those with mild CNA burden. Collectively, our findings illustrate previously unexplored molecular paradigms in HCC initiation, highlighting the therapeutic potential of immunotherapy for early intervention.

cancer biology↗

bioRxiv2025

Brain Diffusion Transformer for Personalized Neuroscience and Psychiatry

Task-fMRI analyses typically focus on localized activation contrasts between stimuli, neglecting the brains dynamic hierarchy. We introduce Brain Diffusion Transformer (Brain-DiT), a deep generative model capturing recurrent processing underlying individualized neurocognitive state transitions via functional networks. Without prior assumptions, Brain-DiT identifies canonical cognitive regions in the brain and reveals replicable subgroups with distinct neural circuits in large cohorts, offering critical clinical insights overlooked by traditional methods: individuals exhibiting negative emotion bias, linked to language-related regions, had a 12-fold higher likelihood of major depression, and those with maladaptive inhibition strategies, associated with overactive medial frontal regions, showed a 9-fold increased risk of alcohol abuse. By bridging cognitive theory and psychiatric applications, Brain-DiT provides a unified analytical paradigm, paving the way for operational personalized medicine in psychiatry.

neuroscience↗

bioRxiv2025

Exploring Population Differences in the Human Gut Microbiome: from Microbial Abundance to Single Nucleotide Polymorphisms

The human gut microbiota exhibits significant diversity across populations, influenced by factors such as geography, diet, and lifestyle, particularly between the Han Chinese and non-Chinese populations. While previous studies have predominantly focused on the taxonomic abundance of the gut microbiome, the impact of single nucleotide polymorphisms (SNPs) in driving population-specific differences remains largely underexplored. In this study, we systematically investigated gut microbial differences between the Han Chinese and non-Chinese populations using the Human Gut Microbiome Reference Genome Catalog (HGMRGC). HGMRGC includes 271,480 non-redundant genomes from 5,785 prokaryotic species, which was generated by metagenomic sequencing data from 9,320 publicly available samples across 22 countries and 3,584 newly sequenced samples from Han Chinese individuals across 29 provinces and regions in China. We observed geography was the primary driver of microbial variation of abundance and SNPs. We identified 625 novel population-specific genome clusters from HGMRGC with functional differences in carbohydrate utilization and 126 species exhibiting distinct prevalence related to vitamin biosynthesis, antibiotic resistance, and carbohydrate metabolism. Beta diversity analysis highlighted significant inter-population differences in both microbial abundance and SNPs, while alpha diversity analysis revealed that non-Chinese populations exhibited higher diversity in microbial abundance, and Han Chinese populations displayed greater diversity in SNPs. These results provide valuable insights into population-specific microbial diversity, laying the groundwork for future research on its functional and health implications.

microbiology↗

bioRxiv2025

Palmdelphin facilitates R-spondin2 secretion to activate Wnt signaling and promote colorectal cancer stemness and tumorigenesis

The Wnt signaling pathway is a key driver of stemness and progression which contributes to mortality in colorectal cancer (CRC). R-spondins bind to LGR receptors to inhibit ubiquitin E3 ligases, thus protecting Frizzled from degradation and activating downstream Wnt signaling. Herein, we identify Palmdelphin (PALMD) as a functional marker of CRC stem cells, interspersed between intestinal and colonic crypt base epithelial cells, and predictive of aggressive CMS4 CRC and poor survival. Gene knockdown and overexpression studies revealed that PALMD initiates paracrine activation of Wnt/{beta}-catenin signaling via interacting with and facilitating the secretion of R-spondin2 (RSPO2), resulting in enhanced stemness and tumor growth in vitro and in vivo. Physiologic or pharmacologic inhibition of the PALMD-RSPO2 axis using R-spondin2-specific antibody or 6-methyl-1,3,8-trihydroxyanthraquinone (emodin), respectively, attenuates PALMD- mediated Wnt reporter activation, self-renewal, and tumorigenesis in cell and patient-derived organoid models. Together, these findings identify PALMD as a previously unknown player in Wnt signaling in CRC, and underscore the pro-tumorigenic role of R-spondin2 in this context.

cancer biology↗

bioRxiv2025

Capturing Natural Evolution in Function-guided RNA Design via Genomic Foundation Models

RNAs play critical roles in gene expression regulation, catalysis, genetic information transmission, and immune response. However, current RNA engineering approaches face limitations in designing RNA for efficient in vivo folding and functional execution. Here, we present a novel, zero-shot strategy that integrates genomic large language models (LLMs) with inverse folding models (IFMs) to generate RNA sequences that mirror natural evolutionary patterns while preserving the structural integrity of critical functional regions. Benchmarking 9 state-of-the-art genomic foundation models, we show that their unsupervised log-likelihood scores correlate strongly with RNA fitness, enabling zero-shot sequence design. Applied to fluorescent RNA aptamers, our approach yielded 20 Broccoli variants, over half of which achieved up to 155% in fluorescence and a twofold increase in binding affinity, with robust performance both in vitro and in vivo. For Pepper, two rounds of optimization produced 40 variants, 16 of which demonstrated up to 2.6 fold in fluorescence and a threefold boost in binding affinity, including five with superior in vivo brightness.This approach offers a scalable, efficient, and resource-light method for RNA design, with significant implications for RNA-based therapeutics and diagnostics. By leveraging general foundation models to facilitate RNA evolution in a zero-shot fashion, we believe our work represents a major advancement in the field of RNA engineering.

evolutionary biology↗

bioRxiv2025

ERK and PKA signaling drive the evolutionary expansion of the cortex

The human cerebral cortex, essential for intelligence, cognition, and language, evolved its uniqueness through mechanisms that drive neuronal expansion. Here, we demonstrate that ERK and PKA signaling cooperatively preserve the neurogenic capacity of cortical radial glia (RGs) by inhibiting gliogenic YAP/TAZ and SHH signaling. YAP/TAZ signaling drives cortical RGs toward ependymal fate, while SHH signaling facilitates the generation of cortical tripotential intermediate progenitor cells that produce cortical astrocytes, oligodendrocytes, and olfactory bulb interneurons. During evolution, cortical outer radial glia (oRGs) acquire dominant ERK/PKA signaling through a self-reinforcing feedback mechanism that suppresses both YAP and SHH pathways, thereby significantly enhancing oRG self-renewal capacity and extending the neurogenic period. These findings reveal that cortical neurogenesis, gliogenesis, and evolutionary expansion are coordinately regulated by an integrated ERK, PKA, YAP/TAZ, and SHH signaling, identifying a unifying principle of mammalian cortical development and evolution.

developmental biology↗

bioRxiv2025

Reshaping epistatic network modules enhances wheat yield potential

Increasing wheat yield is a key approach to ensuring global food security and an enduring focus in crop breeding. Here, we assembled a panel of 3,030 wheat lines to dissect the genetic mechanisms of yield improvement. We conducted large-scale field trials across five ecological environments over two consecutive years to evaluate yield performance and constructed a haplotype atlas using the Wheat 660K genotype array. 234 quantitative trait loci (QTLs) and 522 haplotype blocks (HBs) were identified for 14 traits through genome-wide association studies (GWAS), including 10 QTLs and 35 HBs associated with grain yield. Genomic analysis revealed that wheat yield improvement is primarily driven by changes in the epistatic network rather than the introduction of new haplotype segments. SNPs or HBs explain 53.3%-62.9% of the phenotypic variation in yield, whereas epistasis explains 70.4%, highlighting the role of epistasis in yield improvement. Moreover, yield improvement is significantly correlated with the accumulation of favorable epistatic modules. Pedigree-based analysis revealed that the modules remained relatively stable under the pressure of breeding selection, while new favorable modules were also created during hybrid breeding, highlighting that crop design breeding should be based on genetic modules. This study provides insights into genetic mechanism of wheat yield improvement and guidance for designing future wheat in the era of artificial intelligence.

genetics↗

bioRxiv2025

ATOMICA: Learning Universal Representations of Intermolecular Interactions

Molecular interactions underlie nearly all biological processes, yet most representation models describe isolated entities or specialize in a single molecular setting. Here, we introduce ATOMICA, an interaction-centered geometric deep learning model designed to learn transferable representations of intermolecular interfaces across proteins, small molecules, metal ions, and nucleic acids. Self-supervised pretraining on 2,037,972 interaction complexes yields representations spanning atoms, molecular building blocks, and complete interfaces. The latent space captures molecular identity and interaction context, supporting sequence recovery and zero-shot prioritization of residues involved in non-covalent interactions. ATOMICA provides structural information complementary to sequence representations on RNA and protein-pocket ligand classification. Across protein-pocket analyses, ATOMICA distinguishes ATP- and ADP-associated pocket states and retrieves ligand-matched pockets across proteins without detectable structural alignment. The latent space also enables cross-modal comparison, with orthosteric inhibitor embeddings retrieving regions proximal to native peptide and protein interfaces. Applied to the dark proteome, ATOMICA-Ligand predicts candidate ions or cofactors for 2,646 pockets, and five heme candidates show Soret-band shifts consistent with heme association. Together, these results show how interaction-centered molecular representations can transfer structural information across molecular interaction types and generate experimentally testable hypotheses.

bioinformatics↗

bioRxiv2025

The GSA Family in 2025: A Broadened Sharing Platform for Multi-Omics and Multimodal Data

The Genome Sequence Archive Family (GSA family) provides a suite of database resources for archiving, retrieving, and sharing multi-omics data for the global academic and industrial communities. It currently comprises four distinct database members: the Genome Sequence Archive (GSA, https://ngdc.cncb.ac.cn/gsa/), the Genome Sequence Archive for Human (GSA-Human, https://ngdc.cncb.ac.cn/gsa-human/), the open Archive for Miscellaneous Data (OMIX, https://ngdc.cncb.ac.cn/omix/), and the Open Biomedical Imaging Archive (OBIA, https://ngdc.cncb.ac.cn/obia). Compared to the 2021 version, the GSA family has significantly expanded by introducing a new database member, the OBIA, and through comprehensive upgrades to the existing ones. Notable enhancements to the existing members include broadening the range of accepted data types, enhancing the quality control systems, fine-tuning the data retrieval system, and refining the data-sharing management mechanisms.

genomics↗

bioRxiv2025

Enhancing variant detection in complex genomes: leveraging linked reads for robust SNP, Indel, and structural variant analysis

Accurate detection of genetic variants, including single nucleotide polymorphisms (SNPs), small insertions and deletions (INDELs), and structural variants (SVs), is essential for comprehensive genomic analysis. While short-read sequencing performs well for SNP and INDEL detection, it remains limited in resolving SVs, particularly in complex genomic regions, due to its short read length. Linked-read sequencing technologies, such as single-tube Long Fragment Read (stLFR), partially address this limitation by incorporating molecular barcodes to provide long-range information. In this study, we evaluate conventional paired-end linked reads (PE100_stLFR) and explore a conceptual extension: long single-end barcoded reads of 500 bp (SE500_stLFR) and 1000 bp (SE1000_stLFR). We developed_stLFR-sim, a Python-based simulator that reproduces the_stLFR workflow and enables realistic benchmarking. Using a high-quality T2T assembly of HG002, we generated multiple datasets across 12 sequencing configurations. SVs were called using Aquila_stLFR (v2) and benchmarked against the Genome in a Bottle (GIAB) HG002 SV truth set with Truvari. We show that simulated PE100_stLFR closely matches real data, validating the simulation framework. Increasing read length consistently improves SV detection accuracy, with SE1000_stLFR achieving the best performance and approaching long-read methods while outperforming short-read and pangenome-based approaches. Collectively, our results highlight the strong potential of long single-end barcoded reads for improving SV detection, and suggest that even modest increases in read length, when combined with barcode information, can provide a cost-effective and practical strategy for enhancing future sequencing technologies and SV discovery.

bioinformatics↗

bioRxiv2025

BoltzDesign1: Inverting All-Atom Structure Prediction Model for Generalized Biomolecular Binder Design

Deep learning in structure prediction has revolutionized protein research, enabling large-scale screening, novel hypothesis generation, and accelerated experimental design across biological domains. Recent advances, including RoseTTAFold-AA and AlphaFold3, have extended structure prediction models to work with small molecules, nucleic acids, ions, and covalent modifications. We present BoltzDesign1, which inverts the Boltz-1 model, an open source reproduction of AlphaFold3, to enable the design of protein binders for diverse molecular targets without requiring model finetuning. By utilizing only the Pairformer and Confidence modules, our method significantly reduces computational costs while achieving outstanding in silico success rates and diversity in binder generation. Optimizing directly on the distogram allows us to shape the probability distribution of atomic distances, rather than adjusting a single structure, steering the design toward sequences that yield robust structures with well-defined energy minima. By leveraging a fully atomic model trained on a wide variety of macromolecules, we can generate diverse heterocomplexes with flexible ligand conformations--a capability not currently matched by existing methods. This approach enables the design of novel protein interactions with potential applications in biosensors, enzyme engineering, therapeutic development, and biotechnological innovations.

molecular biology↗

bioRxiv2025

An unrecognized and crucial role of chloroplast division in leaf variegation in Arabidopsis thaliana

Leaf variegation provides a valuable model for elucidating the molecular mechanisms that underlie chloroplast biogenesis, including both chloroplast development and division. While there has been notable advancement in comprehending the role of the Arabidopsis Yellow Variegated2 (VAR2), which encodes the AtFtsH2 subunit of the thylakoid FtsH metalloprotease complex, the exact mechanism governing leaf variegation formation remains elusive. In this study, time-course microscopy analyses of chloroplast number per cell from the first leaf pair revealed that most var2 cells lack chloroplasts. Interestingly, chloroplast biogenesis in the green sector of var2 leaves is significantly delayed but prolonged compared to the wild type (WT), leading to increased heterogeneity in chloroplast number and size among cells. These results suggest that chloroplast biogenesis in the green sector can partially compensate for the defect in the white sector. Additionally, approximately 15% of cells in var2 white sectors are devoid of plastids, and chloroplast number in guard cells is significantly lower in var2 than in WT, indicating that VAR2 mutations impair chloroplast division. Consistently, the var2 phenotype is exacerbated by knocking out key plastid division genes, including Paralog of Accumulation and Replication of Chloroplasts6 (PARC6) and Plastid Division1 (PDV1), but is fully rescued by overexpressing PDV1 or PDV2. Furthermore, VAR2 mutations inhibit etioplast development, while accelerating chloroplast biogenesis by knocking out Constitutively Photomorphogenic1 (COP1) rescues the var2 phenotype. Together, our findings reveal a novel role for VAR2 in plastid division and its essential function in chloroplast biogenesis, providing new insights into the mechanism underlying variegated leaf formation.

plant biology↗

bioRxiv2025

Excitation Spectral Phasor Microscopy (ExSPM) unveils spatiotemporal heterogeneities in polarity of intracellular lipid droplets

Spatiotemporal heterogeneities in intracellular LD polarity are central to cellular homeostasis but remain largely unexplored. Here, we introduce Excitation Spectral Phasor Microscopy (ExSPM), which integrates high-throughput excitation spectral imaging with phasor analysis to map LD polarity with exceptional sensitivity and spatiotemporal resolution. Using the lipophilic dye Nile Red, ExSPM revealed extensive heterogeneity and dynamics of LD polarity within single cells, reflecting lipid metabolism and energy status. Notably, high-polarity LDs emerged dynamically at lysosome- and mitochondria-contact sites, revealing pathway-specific kinetics of LD catabolism that distinguish lipophagy from neutral lipolysis. ExSPM further uncovered a tightly interconnected regulatory network among lipolytic pathways, in which perturbation of one pathway reshapes others while preserving overall energy supply. ExSPM thus provides a versatile platform to dissect intracellular compositional heterogeneity and the coordinated regulation of lipid metabolism, offering new insights into organelle function and cellular homeostasis.

cell biology↗