Biology subjects

Luo, D.

Publications and source records attributed to Luo, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Scalable Enzyme Reaction Retrieval Enables Metagenomic Biocatalyst Discovery

Enzyme catalyzed reactions drive metabolism and enable diverse applications in biotechnology and sustainable synthesis, but assigning catalytic functions to uncharacterized enzymes and finding enzymes for target reactions remain major challenges. Despite recent advances in machine learning, translating enzyme function prediction into systematic discovery across the vast space of uncharacterized proteins and biochemical reactions remains challenging. Here we present EzHit, a lightweight framework for bidirectional enzyme reaction retrieval. Across enzyme annotation, orphan-reaction retrieval and family-specific fine-tuning benchmarks, EzHit achieved strong top-ranked performance and outperformed representative enzyme reaction matching baselines. We further show that Mahalanobis distance based geometric confidence provides more useful reliability estimates than probability-derived uncertainty metrics or evidential learning, enabling confidence-aware prioritization of high scoring candidates. Owing to its efficiency, EzHit was applied to a nearly trillion-scale OMG_Prot50 with RHEA screen, yielding 8.20 billion retained enzyme reaction associations across 30.27 million predicted enzyme sequences. Experimental validation further confirmed the activity of EzHit prioritized metagenomic enzyme candidates for a sparsely annotated reaction. Together, these results establish EzHit as a scalable framework for enzyme annotation, reaction-guided mining and biocatalyst discovery

bioinformatics↗

bioRxiv2026

Geothermal gradients restructure metabolism in hot spring microbial communities

Hot springs are employed as model systems for understanding how environmental stress structures microbial communities, yet the mechanisms by which geothermal stress reorganizes community metabolism remain poorly understood. Here we combined genome-resolved metagenomics, metatranscriptomics, aqueous geochemistry, and community metabolic modelling to investigate photosynthetic biofilms across the geothermal gradient of a hot spring in Singapore. We reconstructed community taxonomic and functional composition via metagenome-assembled genomes and identified three transcriptionally coordinated ecological guilds defined by convergent metabolic strategies rather than phylogeny. Community metabolic models revealed that increasing geothermal stress reorganized nutrient exchange networks, progressively reducing metabolic redundancy and increasing dependence on reciprocal interactions among thermophilic guilds. Increasing geothermal stress redirected relative modelled elemental demand from carbon-associated metabolism towards nitrogen and sulfur metabolism, highlighting nitrogen limitation and sulfur-linked bioenergetics as defining features of stress adaptation. Electron allocation modelling further demonstrated a systems-level transition from growth-oriented biosynthesis toward catabolic energy conservation, respiratory metabolism, and oxidative stress management under geothermal stress. These coordinated metabolic shifts indicate that hot spring communities become increasingly specialized and energetically constrained near their upper geothermal limits. Overall, the findings demonstrate how environmental stress restructures microbial ecosystems through guild-level metabolic partitioning and cooperative resource exchange and establishes an integrative systems biology framework for predicting microbial ecosystem function in extreme environments.

microbiology↗

bioRxiv2026

Spatially confined dopamine from locus coeruleus axons selectively shapes hippocampal dynamics and action timing

Neuromodulatory systems project broadly, yet computations engage specific neuronal populations. Whether neuromodulation can selectively influence task-engaged neurons remains unclear. During goal-directed navigation, neurons in the locus coeruleus (LC), the brain's principal norepinephrine source, responded at navigation onset. Concurrently, dopamine transients arose in micrometer-scale domains around LC axons in CA1. These transients preferentially enhanced nearby CA1 neurons with ramping dynamics, whose higher activity predicted later reward-anticipatory action. Brief LC activation evoked local dopamine, enhanced ramping dynamics, and delayed action initiation seconds later. Blocking D1-like, but not adrenergic, receptors weakened ramping dynamics and impaired reward anticipation. Modeling showed that selectivity can emerge when localized dopamine coincides with strong ongoing neuronal activity, without dedicated wiring. Thus, a widely projecting system can selectively modulate task-engaged neurons and shape behavior.

neuroscience↗

bioRxiv2026

Dynamics-aware geometric learning predicts disease-associated molecular perturbations

Missense mutations and post-translational modifications (PTMs) are major molecular perturbations that reshape protein function but are traditionally studied independently. Current computational approaches largely rely on sequence conservation or static structural features, limiting our understanding of how perturbations alter intrinsic protein dynamics. We present DynGeo-Pheno, a unified geometric deep learning framework that integrates protein language model representations with anisotropic network model-derived dynamics to jointly capture evolutionary, structural, and biophysical information. DynGeo-Pheno predicts disease-associated phosphosites and pathogenic missense mutations with high accuracy on independent test datasets. Ablation analyses indicate that protein dynamics provide complementary information beyond sequence evolution and structural topology for pathogenicity prediction. Beyond predictive performance, DynGeo-Pheno reveals that disease-associated perturbations preferentially localize to functional structural regions, including ligand-binding pockets and PPI interfaces. Mechanistically, phosphosites and missense mutations appear to exhibit distinct yet convergent dynamic signatures. Phosphosites preferentially occur in flexible regulatory regions, whereas pathogenic mutations are enriched in ordered structural elements. Despite these differences, both perturbation types display enhanced long-range coupling, increased perturbation responsiveness, and elevated mechanical stability, indicating that pathogenic residues preferentially occupy mechanically constrained and allosteric regulatory sites. This study provides compelling evidence that intrinsic protein dynamics is an important complementary determinant of pathogenicity and establishes a unified framework for interpretable AI predictions and mechanistic understanding of how genetic and regulatory perturbations may shape protein function.

biophysics↗

bioRxiv2026

Anti-Z-NA antibodies can distinguish accessible Z-form states across DNA, RNA, and DNA-RNA substrates

Left-handed (Z-form) double-stranded nucleic acid conformers (Z-DNA and Z-RNA, collectively called Z-NA) are molecular patterns recognized by ADAR1 and ZBP1, which are sensor proteins involved in innate immunity. Monoclonal antibodies raised against Z-DNA, such as Z22 and Z-D11, are employed as probes for the study of Z-NAs, but their substrate specificity and functional equivalence remain unclear. Here, we used biochemical, biophysical, and structural approaches to compare the binding modes and target specificies of Z22 and Z-D11, using Z-prone CG-rich dsDNA, dsRNA, and DNA-RNA hybrids as substrates. Both antibodies failed to form stable complexes with short CG-rich dsRNA under conditions compatible with antibody stability, which suggests that they are unable to induce A-to-Z transitions in dsRNA. In contrast, both antibodies robustly complexed with dsDNA and DNA-RNA hybrid substrates. Cryo-EM structural analysis confirmed that both antibodies interact with Z-NA through a conserved interaction network, and demonstrated that complexes between the antibodies and DNA-RNA hybrids adopted distinct higher-order organizations. Z22 retained binding to both Z-DNA and Z-RNA segments, whereas Z-D11 displayed substrate-dependent organization and was restricted to Z-DNA segments Molecular modelling provided mechanistic explanation for the differences in Z-RNA binding ability between the two antibodies, which was confirmed in situ with ADAR1-depleted, IAV- infected and JTE607-treated cells. We also demonstrate that Z-D11, in contrast to previously described Z22, is unable to induce B-to-Z-transitions in short d(CG)6 oligos under physiological conditions. Together, these results show that anti Z-NA monoclonal antibodies are not functionally interchangeable: whereas Z22 recognizes pre-formed Z-RNA, Z-DNA- RNA hybrids, and Z-DNA, Z-D11 recognizes Z-DNA, and DNA segments in Z-DNA-RNA hybrids. These differences are dictated by substrate composition, local geometry, and conformational accessibility, which also likely impact their ability to induce NA structural transitions. These findings have important implications for interpreting antibody-based detection of left-handed nucleic acids in biological systems.

biophysics↗

bioRxiv2026

Distinct RNA engagements define genome import and replication elongation in alphaviruses

Membrane-associated replication complexes (RCs) are a hallmark of alphaviruses, yet the mechanisms by which viral RNA is delivered into these compartments and coordinated with RNA synthesis remain incompletely understood. Here, we present a cryo-electron microscopy (cryo-EM) structure of the Chikungunya virus (CHIKV) RC core, consisting of nsP1, nsP2, and nsP4, in complex with the replicative RNA substrates, revealing two spatially distinct RNA-binding sites. A single-stranded RNA (ssRNA) engages the nsP2 helicase and extends toward a pore formed at the nsP1-nsP4 interface, whereas a double-stranded RNA (dsRNA) is accommodated within the central catalytic pocket of the nsP4 polymerase in an elongation configuration. Structural analysis suggests a helicase-assisted RNA threading model in which the 5' end of the viral genome is guided toward the spherule lumen through the RC pore. Concurrently, the nsP4 polymerase engages dsRNA in a manner consistent with RNA synthesis. This work provides a structural framework for understanding RNA trafficking and enzymatic coordination in viral replication organelles. Significance StatementLike many positive-sense RNA viruses, alphavirus replication occurs within membrane-bound spherules, but how viral RNA is delivered into these compartments and coupled to RNA synthesis has remained unclear. Here, we show that the CHIKV RC core contains two functionally distinct RNA-engagement modules: an nsP2-associated ssRNA path directed toward the nsP1-nsP4 pore, and an nsP4-bound duplex RNA positioned in an elongation-like polymerase channel. These observations support a model in which alphavirus RCs integrate genome import and RNA synthesis within a single membrane-associated molecular machine. This work provides a structural framework for understanding RNA trafficking, replication-organelle function, and potential antiviral targeting of alphavirus replication.

microbiology↗

bioRxiv2026

RNABag: A Generalizable Transcriptome Foundation Model for Precision Oncology across Biopsy Modalities

Transcriptomic data is highly sensitive to cancer state and progression, making transcriptome-based foundation models a great promise for diverse clinical ontological inference. However, analyses of transcriptome are conventionally hindered by technical batch effects and limited generalization across platforms. Here, we introduce RNABag, a foundation model designed to generalize well to external datasets. In particular, the model only focuses on highly variable genes to reduce noise; and extensive data augmentation was utilized to pretrain RNABag to learn robust representations, invariant to batch variations. We demonstrate that RNABag achieves superior performance in pan-cancer tissue-of-origin classification and cancer detection in internal validation sets, as well as in zero-shot generalization to external cohorts and in-house clinical samples. Furthermore, RNABag, after specialized finetuning, exhibits strong capabilities in a wide range of clinical applications. The model effectively stratifies patient survival and predicts relapse risks, highlighting key molecular pathways driving tumor progression. Crucially, we extend RNABags utility to liquid biopsies, achieving high diagnostic accuracy in plasma cfRNA and tumor-educated platelets (TEPs), thereby supporting its application in non-invasive cancer monitoring. Interpretability analysis revealed pivotal role of tumor immune escape in the cancer induced plasma cfRNA signals. In summary, our study indicates that cancer states and progression may be monitored in details and precision via comprehensive modeling of transcriptome across biopsy modalities.

bioinformatics↗

bioRxiv2026

Microbiome stability in wild and rehabilitated insectivorous bats revealed by shotgun metagenomics

BackgroundWildlife rehabilitation can influence host-associated microbiota, yet little is known about how the gut microbiome of insectivorous bats responds to rehabilitation during temporary managed care. This study applied shotgun metagenomics to evaluate the impact of temporary managed care on the gut microbiome of wild and rehabilitated bats in Yorkshire, UK. ResultsWe analysed 25 faecal metagenomes from Myotis daubentonii, Pipistrellus pipistrellus, Nyctalus noctula and N. leisleri, including wild baseline bats and bats sampled during temporary managed care (1-49 days in rehabilitation). Microbial communities clustered strongly by host species and roost location, but not by rehabilitation status. Bacterial alpha diversity did not differ between wild bats, and bats in care (H = 2.30, p = 0.32). Archaeal communities were highly uniform across samples, showing far lower interindividual variation than bacterial communities (12.2% vs. 41.8% coefficient of variation). Rehabilitated bats showed increased relative abundance of Yersiniaceae and Lactobacillaceae, while environmental families such as Pseudomonadaceae and Erwiniaceae decreased, indicating modest but non-disruptive changes consistent with a controlled diet and reduced environmental exposure. ConclusionsAcross temporary managed care, the core gut microbiome of insectivorous bats remained stable, demonstrating notable microbial resilience. These findings provide an important baseline for monitoring microbiome health in wildlife rehabilitation and supporting post-release conservation programmes in the UK and beyond.

microbiology↗

bioRxiv2025

Cryo-EM structures of anti Z-DNA antibodies in complex with antigen reveal distinct recognition modes of a left-handed geometry

Double-stranded nucleic acids can undergo transitions from canonical B/A-forms to alternate left-handed Z-DNA/Z-RNA (Z-NAs). Z-NAs are implicated in processes such as neuroinflammation in Alzheimers disease, Lupus Erythematosus, microbial biofilms, and type I interferon-mediated human pathologies. Since endogenous Z-NA sensors like the Z domain can induce B-to-Z transitions, monoclonal antibodies (mAbs) Z-D11 and Z22 have been regarded as conformation-specific tools to confirm Z-NA in situ, although high-resolution structural information is missing. Here, we employed single-particle cryo-electron microscopy to solve structures of Z-D11 and Z22 bound to synthetic d(CG)6 12mer Z-DNA duplex. Both mAbs form filamentous trimers around the Z-DNA axis, further stabilized by Fab-Fab interactions. The mAbs achieve specificity through extensive contacts to both Z-form backbone strands and the exposed guanine/cytosine bases in the major groove. This mode of recognition is dictated by shape complementarity rather than sequence specificity, sensing the alternating syn/anti backbone torsions and the phosphate zig-zag geometry unique to Z-DNA. Our data also suggest that these mAbs are not inducing B-to-Z transitions under normal physiological conditions. Finally, comparison to other double-stranded NA-binding mAbs defines a similar structural logic adapted to different helical geometry recognition patterns, thus providing a framework for engineering highly specific nucleic acid probes.

biochemistry↗

bioRxiv2025

Structural basis of Retron-Eco8-mediated anti-phage defense

Retrons represent a novel class of bacterial defense systems that employ reverse transcriptase (RT), non-coding RNA, and effector proteins to counteract phage infections. In this study, we elucidate the molecular mechanism of a retron system, Retron-Eco8. Biochemical experiments reveal that the Retron-Eco8 holocomplex, rather than the effector alone, exhibits double-stranded DNA cleavage activity in an ATP-independent manner, triggering abortive infection and effectively halting phage propagation. Cryo-electron microscopy (cryo-EM) analysis reveals a supramolecular assembly comprising four RT subunits, four msDNA (multicopy single-stranded DNA) molecules, and four OLD (overcoming lysogenization defect) nucleases--a configuration critical for anti-phage defense. Structural comparisons between apo and ATP-Mg2+-bound states demonstrate a local conformational change. Notably, we identify the phage SSB (single-stranded DNA-binding) protein as an activator of Retron-Eco8, and phylogenetic analysis of SSB proteins further elucidates the phage resistance specificity. Collectively, our findings delineate the structural architecture of the Retron-Eco8 defense complex and provide mechanistic insights into retron-mediated bacterial immunity.

biophysics↗

bioRxiv2025

Visualization of Bluetongue virus RNA segment networks in infected cells: multipartite genomic RNA assortment is independent of viral proteins NS2 and VP6

Bluetongue virus (BTV), with a genome of ten double-stranded RNA segments (S1-S10), is an emerging animal pathogen causing major economic losses in livestock worldwide. BTV replication involves RNA-RNA and RNA-protein interactions, with RNA-binding proteins, VP6 and NS2 playing key roles in genome assembly and RNA packaging. To explore the dynamics of RNA segment interactions and the roles of VP6 and NS2 in RNA complex formation, we used RNA fluorescence in-situ Hybridisation Chain Reaction (HCR), along with site-specific mutagenesis and reverse genetics. We found that RNA segments interact sequentially, from the smallest (S10) to the largest (S1), forming a single complex that includes the entire genome. This process is independent of VP6 or NS2, although NS2 enhances the assembly of larger segments. Additionally, we show that VP6 binds to +ssRNAs before their incorporation into viral assembly factory (inclusion bodies/VIBs). These findings reveal that RNA-RNA interactions, rather than primary replicase proteins, govern the sorting and recruitment of genome segments. Our data offer new insights into BTV RNA packaging, showing that genome segments destined for packaging and dsRNA synthesis are segregated through complex formation, distinct from +ssRNAs used in protein synthesis, including those encoding the replicase complex.

microbiology↗

bioRxiv2025

Evolutionary rewiring of host metabolism and interferon signalling by SARS-CoV-2 variants

SARS-CoV-2 variants differ in transmissibility and immune evasion, but their effects on host-cell metabolism and signalling remain less defined. Using integrated transcriptomic, phosphoproteomic, and amino acid profiling in primary nasal epithelial cells, we compared early and late host responses to pre-Omicron variants (Alpha, Beta), Delta, and Omicron subvariants (BA.1, BA.5). Pre-Omicron strains broadly suppressed antiviral interferon-stimulated gene expression and reprogrammed metabolism by reducing mitochondrial oxidative phosphorylation and {beta}-oxidation. Delta infection was associated with extensive transcriptional and metabolic remodelling, characterised by activation of stress- and growth-related kinases and selective retention of biosynthetic amino acids, consistent with a host response to stress and viral modulation of interferon-associated signalling. In contrast, Omicron infection elicited a more restrained response dominated by cytokine and survival pathways, with limited metabolic activation and interferon suppression. Together, these findings suggest SARS-CoV-2 has progressively evolved toward a strategy that maintains efficient upper-airway replication while minimising epithelial stress and inflammation.

systems biology↗

bioRxiv2025

Discovery of a potent anti-Zika virus benzamide series targeting the viral protein NS4B

1.Zika virus (ZIKV), a member of the Flaviviridae family, causes significant public health concerns through congenital Zika syndrome and Guillain-Barre syndrome, yet no effective anti-ZIKV drugs or vaccines are available. To address this critical need, we conducted phenotypic, cytopathic effect-based, high-throughput screening followed by medicinal chemistry optimization and discovered novel benzamide anti-ZIKV leads. Current best compounds demonstrated superior potency (EC50 values 40-400 nM, CC50 > 50 {micro}M) compared to NITD-008, the most potent known anti-ZIKV agent. Time-of-addition assays, resistant virus selection studies, and biophysical binding experiments confirmed that NS4B interference constitutes the primary antiviral mechanism. Notably, resistance mutations mapped to the C-terminus of NS4B, distinct from other flavivirus NS4B inhibitors targeting dengue or yellow fever viruses, revealing novel insights into a critical function of the region. These findings establish NS4B as an Achilles heel for flaviviruses and support the development of pan-flavivirus therapeutics targeting this essential viral protein. 2. AUTHOR SUMMARYSince its pandemic spread in 2015-2016, Zika virus infection remains a significant public health threat worldwide. The virus can cause severe brain damage in developing babies and serious neurological complications like Guillain-Barre syndrome in adults. Despite these devastating consequences, we currently lack effective medicines or vaccines to prevent the virus from spreading through communities or from mothers to their unborn children. To address this critical gap, we conducted a large-scale screening of chemical compounds and discovered a promising new class of molecules that can effectively stop Zika virus from replication. Using medicinal chemistry techniques, we were able to make these compounds even more potent against the virus. In follow-up studies, we found that our compounds work by interfering with a specific viral protein called NS4B, which the virus needs to replicate its genome within the cell. Remarkably, other research teams studying related other flaviviruses (e.g., dengue and yellow fever virus) have independently discovered that this same protein is a vulnerable target. Our findings suggest that NS4B represents a universal weakness across the entire flavivirus family, making it an attractive target for developing broad-spectrum antiviral treatments.

microbiology↗

bioRxiv2025

Modular platform for therapeutic drug delivery using trifunctional bio-orthogonal macromolecular conjugates

Targeted delivery of macromolecular therapeutics holds great promise for overcoming the limitations of conventional small molecules, enabling modulation of protein-protein interactions and precise genome editing. However, efficient, safe, and cell type-specific delivery remains a major challenge. To address this, we developed a modular platform for synthesizing heterotrifunctional bio-orthogonal macromolecular conjugates (BMCs) by engineering diverse combinations of targeting ligands, cell-penetrating peptides (CPPs), and bioactive cargos. We optimized facile bioconjugation chemistries to generate BMCs with improved yields, structural integrity, and activity. Modular BMCs accommodate diverse components, including antibodies and receptor ligands for targeting, CPPs for intracellular trafficking, and optical probes, therapeutic peptidomimetics, and CRISPR-Cas9 nuclease as cargos to confer specific biological activities. We assayed their utility across multiple applications: BMCs with fluorescently labeled cargo revealed endosomal escape and intracellular accumulation; peptidomimetic MYB transcription factor inhibitor BMCs exhibited potent anti-leukemic activity against acute myeloid leukemia cells; and Cas9 BMCs achieved rapid delivery and cell type-specific gene editing in human cells. The BMC approach enables customizable delivery of functional macromolecules, nominating BMCs as a broadly applicable platform for biomedical applications. One-Sentence SummaryThe establishment of modular platform for synthesizing bio-orthogonal macromolecular conjugates (BMC) enabled fast and targeted delivery of membrane-impermeant macromolecular drugs.

biochemistry↗

bioRxiv2025

Evolutionary Genomics Guides Scalable Coral Probiotics for Climate Resilience

A universal bottleneck limiting probiotic efficacy in medicine, aquaculture, agriculture, and wildlife conservation is uncertain long-term colonization, necessitating repeated administration. We present an evolution-guided framework for probiotic identification based on genomic hallmarks of emerging host dependency, including widespread pseudogenization and insertion sequence proliferation driving genomic restructuring. Applied to coral reefs, we screened over 1,200 coral-associated bacterial isolates and identified Ruegeria MC10 as exhibiting these signatures. Its presence was associated with increased thermal tolerance of a model cnidarian. Following nursery application, MC10 persisted in reef corals for an 8-month monitoring period through a natural bleaching event, improving color retention and retaining algal photosynthesis performance. This work establishes a predictive, scalable pipeline for selecting persistent probiotics, directly addressing a central constraint on microbiome-based interventions across host systems.

microbiology↗

bioRxiv2025

Catalytic pocket-informed augmentation of enzyme kinetic parameters prediction via hierarchical graph learning

Predicting enzyme kinetic parameters is crucial for enzyme engineering and mining, but development of accurate tools for this task is still challenging due to the complexity of influencing factors. Large language models (LLMs)-based deep learning methods show satisfactory performance in Kcat prediction by encoding substrate and enzyme sequence information, but this further enhancement of the performance can be largely limited by the ignorance of the substrate-binding information. Here, we introduce GraphKcat, a deep learning framework that integrates enzyme-substrate 3D binding conformations for precise kinetic parameter prediction. The method employs Chai-1 to generate enzyme-substrate complex conformations, followed by a developed multi-scale hierarchical graph neural network to systematically characterize active site features from all-atom (AA) level to coarse-grained (CG) level, which are subsequently fused with LLMs embedded substrate, sequence, and environmental related information for prediction. To enable efficient multimodal feature integration, we proposed a multi modal cross-attention fusion (MMCAF) module for feature alignment and update. Experimental evaluations demonstrate that GraphKcat can effectively identifying catalysis-critical residues, learning sequence similarity-independent features through its multi-scale graph architecture, and maintaining robust performance under low sequence similarity conditions. Critically, GraphKcat captures conserved structural and physicochemical patterns related to enzymatic activity, enabling accurate identification of high-activity enzyme variants and functional mutants even for low-homology targets. These capabilities highlight its potential as a transformative tool for enzymatic activity prediction, rational enzyme engineering, and enzyme mining in industrial applications.

bioinformatics↗

bioRxiv2025

Saddle Curvature Association of nsP1 Facilitates the Replication Complex Assembly of Chikungunya Virus in Cells

The replication of positive-sense RNA viruses, including the pathogenic SARS-CoV-1 and -2, DENV, and ZIKV, often takes place in curved cellular membrane compartments of tens to hundreds of nanometers in diameter within host cells. The non-structural proteins (nsPs) of viruses are found to critically control the formation and maintenance of such unique nanoscale membrane structures. However, the molecular mechanism underlying the association and assembly of nsPs around curved membranes has remained elusive, due to the technical difficulties of imaging the nanoscale interaction in live cells. In this study, we leveraged vertically aligned nanostructures to define membrane curvatures in live cells and investigated the assembly of viral nsPs on these curved membranes. Using Chikungunya virus as a model system, we found that its nsP1 was preferentially bound to and stabilized around positively curved membrane sites and the preference became more apparent as the radius of curvature decreased to 150 nm or smaller. This preferential accumulation was mainly attributed to the hydrophobic residues on recently identified membrane association loops (MA loops) of each nsP1 monomer. Molecular dynamics simulations further confirmed the improved binding kinetics and stability of nsP1 on positively curved membranes, especially when a 12-mer ring was formed by the nsP1 dodecamer. More interestingly, a saddle curvature association was enabled by the 3D coordination of nsP1 monomers along the dodecamer ring, where the MA loops of individual nsP1 monomers sensed a wide range of the positively curved membrane in the x-z plane while the rigid nsP1 dodecamer ring stabilized the negative curvature in the x-y plane. Its strong coupling to the saddle curvature fulfilled the need to constrain the neck of the membrane spherule for viral replication. Strikingly, productive CHIKV replication exhibited strong enrichment on patterned nanostructure array, proving the effectiveness of membrane curvature-guided assembly of the functional replication complex. Our findings revealed that the cell membrane facilitated the local enrichment of viral nsPs in a curvature- dependent manner. It opens up membrane curvature modulation as a new dimension to dissect the formation and regulation of membrane compartments for viral replication.

biophysics↗

bioRxiv2025

Structural basis for prohibitin-mediated regulation of mitochondrial m-AAA protease

Mitochondrial function critically dependents on protein quality control systems, with the m-AAA protease plays a key role at the inner mitochondrial membrane (IMM). The evolutionarily conserved prohibitins (PHBs) are essential modulators of this protease across species, yet the molecular mechanisms remain unclear. Here, we present the Cryo-EM structure of the Chaetomium thermophilum PHB (CtPHB) complex, revealing a cage-like assembly composed of 11 copies of PHB1/PHB2 heterodimers. Electron microscopic and biochemical analyses suggest that m-AAA proteases are enclosed within the PHB complex through interactions mediated by their SPFH-interacting motif (SIM) exposed in the intermembrane space. Further in situ cryo-ET directly visualizes these cage-protease assemblies in native mitochondria. Disruption of their interface leads to elevated m-AAA protease activity and diminished mitochondrial stress resistance. These data establish PHB complexes as spatial organizers that compartmentalize m-AAA proteases in membrane microdomains to fine tune proteolytic homeostasis. Our findings reveal the critical role of the PHB complex in maintaining mitochondrial proteostasis, providing a unified mechanistic model to explain and reconcile the pleiotropic, and often contradictive phenotypes of PHBs and m-AAA protease in mitochondrial physiology and various disease conditions.

molecular biology↗