Biology subjects

Zou, S.

Publications and source records attributed to Zou, S..

At least 19 recordsLinked to original sources

bioRxiv2026

The L-type voltage-gated Ca2+ channel CaV1.2 regulates fibroblast-like synoviocytes invasiveness during rheumatoid arthritis

Fibroblast-like synoviocytes (FLS) are major drivers of synovial tissue inflammation and damage during rheumatoid arthritis (RA). A hallmark of the aggressiveness of RA-FLS is their invasiveness but the molecular mechanisms that regulate this invasiveness remain poorly understood. The KCa1.1 (BK, Slo1, MaxiK, KCNMA1) potassium channel is a major regulator of RA-FLS pathogenicity and inhibiting KCa1.1 expression or its activity with selective blockers reduces RA-FLS invasiveness and reduces disease severity and joint damage in rat models of RA. KCa1.1 blockade induces a Ca2+ influx in RA-FLS whose intracellular signaling results in increased cell adhesion to the extracellular matrix and thus a reduction in cell migration. However, the identity of the Ca2+-permeable channel responsible for the Ca2+ influx has remained elusive. Here, we demonstrate the co-expression of KCa1.1 with the L-type voltage-gated CaV1.2 channels at the plasma membrane of primary human and rat FLS. Selective blocking of the CaV1.2 channel blunts the Ca2+ influx induced by KCa1.1 blockade and abrogates the effects of KCa1.1 blockade on RA-FLS invasiveness, migration, cell shape, and podoplanin expression. Whereas KCa1.1 blockers reduce disease severity in rat models of RA, treating rats with the collagen-induced arthritis model of RA with both blockers of KCa1.1 and CaV1.2 eliminates the therapeutic benefits of treatment with KCa1.1 blockers alone. Together, these data demonstrate a physical and functional coupling of KCa1.1 and CaV1.2 channels in FLS during RA and its rat model that regulate the invasive phenotype of the FLS through modulation of intracellular Ca2+ homeostasis.

cell biology↗

bioRxiv2026

Immune Reconstitution and Antigenic Exposure History Shape Virus-Specific Humoral Immunity in People with HIV

CD4+ T-cell recovery is widely used to assess immune reconstitution in people with HIV, but its relationship to virus-specific humoral immunity across pathogens remains unclear. We characterized neutralizing activity against SARS-CoV-2, HIV-1, and influenza viruses in ART-treated, virologically suppressed individuals spanning distinct CD4+ T-cell levels. BA.5 was the dominant SARS-CoV-2 neutralization target across CD4 strata, whereas D614G neutralization increased with greater immune reconstitution. This gradient was largely absent for the antigenically divergent NB.1.8.1 and XFG variants. HIV-1 neutralization was inversely associated with CD4+ T-cell count, while influenza showed strain-dependent patterns. Neutralization-to-protection bridging preserved a CD4-associated gradient for D614G but not for highly immune-evasive variants. These findings show that immune reconstitution does not translate uniformly into antiviral humoral function. Instead, antibody profiles reflect host immune status, prior antigenic exposure, and viral antigenic evolution, supporting pathogen-specific functional assessment alongside conventional immune monitoring.

immunology↗

bioRxiv2026

Community diversity and interaction of bacterial, cyanobacteria and protist among aquatic and soil micro-food chains

Microorganisms, found in every environment, play an important role in recycling matter and providing energy to the ecosystem. Here, we used 18S and 16S metabarcoding to study bacteria, cyanobacteria and protist community diversity and functional ecology among different environments of typical lake, river, marine and soil from the Yangtze Delta of China. The results showed that the similarity of cyanobacteria and protozoa communities in soil and aquatic environments was both higher than that of bacteria and microalgae communities. While the diversity of cyanobacteria and bacteria in lake was higher than that in river, marine and soil, the diversity of microalgae and protozoa in river was higher than that in lake, marine and soil. The {beta} diversity of cyanobacteria and bacteria marked differences in lake from other environments. But The distribution of dominant families of cyanobacteria, bacteria, microalgae and protozoa is similar to diversity. While significant positive correlations were found among dominant species of cyanobacteria, protozoa, bacteria and microalgae in lake the dominant species among bacteria, microalgae and protozoa in river, marine and soil all showed more negative correlations. Our study provides the basis for understanding the functional ecology of microbes in the micro-food webs of different environments.

ecology↗

bioRxiv2026

Seasonal Rebalancing of Assembly Processes and Cross-Domain Network Restructuring in Microbial Communities of a Large Eutrophic Lake

Harmful algal bloom (HAB) succession in eutrophic lakes arises from seasonal rebalancing of selection, dispersal, and drift across interacting microbial domains, yet process attribution remains limited due to the scarcity of cross-domain analyses. Using multi-marker eDNA metabarcoding (16S rRNA, 18S rRNA, 23S rRNA), we show that bacterioplankton, cyanobacteria, phytoplankton, and zooplankton in Lake Taihu undergo coordinated spring-summer transitions, with inter-seasonal turnover far exceeding spatial heterogeneity. Assembly regimes shifted coherently across domains: spring communities were dominated by strong homogeneous selection--especially among cyanobacteria and microeukaryotes--whereas summer communities moved toward drift- or neutrality-like dynamics under bloom-stage mixing that enhanced dispersal. Null- and neutral-model diagnostics supported these trends. Cross-domain co-occurrence networks restructured seasonally, with summer networks becoming more connected and substantially more robust, indicating that bloom conditions foster cohesive, robust interaction structures rather than destabilization. These findings provide evidence that bloom progression restructures aquatic microbiomes through a seasonal rebalance of selection, drift, and dispersal coupled with adaptive strengthening of cross-domain connectivity, providing a process-explicit framework for understanding community stability and ecosystem resilience in eutrophic lakes.

ecology↗

bioRxiv2026

Promoter architecture decodes response regulator phosphorylation into distinct transcriptional logics in Pseudomonas aeruginosa

Two-component systems convert environmental signals into transcriptional responses, but how one response-regulator phosphorylation state produces different outputs at different promoters remains unclear. Here we show that promoter architecture determines how the ParR response regulator in Pseudomonas aeruginosa interprets phosphorylation. Phenotypic, transcriptomic, biochemical and promoter-engineering analyses showed that phosphorylation of the conserved ParR receiver residue Asp57 lowered DNA-occupancy thresholds across target promoters. Individual promoters, however, converted this shared increase in binding into activation, repression or phosphorylation-dependent sign switching. Chromosomally D57 ParR variants reproduced these behaviours at endogenous loci and altered antibiotic susceptibility, biofilm formation and virulence-associated phenotypes. Mapping and engineering of representative promoters identified a two-tier cis-regulatory code: half-site sequence compatibility determines productive ParR engagement, whereas spacer length determines regulatory sign and magnitude. Spacer swaps were sufficient to reprogram promoter logic between regulatory modes. These findings separate regulator state from promoter decoding and show how bacterial promoter architecture can diversify the outputs of a shared phosphorylation signal. ImportancePseudomonas aeruginosa is an opportunistic pathogen that survives antimicrobial treatment and adapts to diverse host environments by rapidly changing gene expression. How a single sensory pathway generates different, and sometimes opposing, responses across many genes has remained unclear. We show that the regulatory protein ParR does not impose one fixed transcriptional program. Instead, the DNA architecture of each target promoter determines whether the same phosphorylation signal activates, represses, or reverses gene expression. The sequence and spacing of ParR recognition sites form a compact regulatory code, and changing spacer length alone can reprogram promoter behavior. Different ParR states were also associated with changes in antibiotic susceptibility, biofilm formation, and virulence-associated phenotypes. Our findings explain how one bacterial signaling pathway can generate diverse physiological outcomes without additional regulators and provide a framework for understanding regulatory flexibility in Pseudomonas aeruginosa and for engineering genetic circuits with multiple outputs. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/740031v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@1b6ec28org.highwire.dtl.DTLVardef@4a3f2eorg.highwire.dtl.DTLVardef@79e528org.highwire.dtl.DTLVardef@b3aa77_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2026

Promoter architecture diversifies ParR-dependent transcription in Pseudomonas aeruginosa

Two-component systems convert environmental signals into transcriptional responses, but how one response-regulator phosphorylation state produces different outputs at different promoters remains unclear. Here we show that promoter architecture determines how the ParR response regulator in Pseudomonas aeruginosa interprets phosphorylation. Phenotypic, transcriptomic, biochemical and promoter-engineering analyses showed that phosphorylation of the conserved ParR receiver residue Asp57 lowered DNA-occupancy thresholds across target promoters. Individual promoters, however, converted this shared increase in binding into activation, repression or phosphorylation-dependent sign switching. Chromosomally D57 ParR variants reproduced these behaviours at endogenous loci and altered antibiotic susceptibility, biofilm formation and virulence-associated phenotypes. Mapping and engineering of representative promoters identified a two-tier cis-regulatory code: half-site sequence compatibility determines productive ParR engagement, whereas spacer length determines regulatory sign and magnitude. Spacer swaps were sufficient to reprogram promoter logic between regulatory modes. These findings separate regulator state from promoter decoding and show how bacterial promoter architecture can diversify the outputs of a shared phosphorylation signal. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/738673v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1a0a26forg.highwire.dtl.DTLVardef@10836a8org.highwire.dtl.DTLVardef@3c6cd8org.highwire.dtl.DTLVardef@10dfefb_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsParR coordinates antibiotic resistance, biofilm formation and virulence-linked phenotypes in P. aeruginosa. Promoters convert ParR phosphorylation into activation, repression or sign switching. Half-site compatibility and spacer length form a cis-regulatory code for ParR output.

biochemistry↗

bioRxiv2026

A CRISPR/Cas9-induced blunt-end telomere system in S. pombe reveals RNase H2-dependent RNA primer removal at the terminal Okazaki fragment of lagging telomeres

Studying the fine-scale dynamics of telomere replication has been hindered by the heterogeneity of native telomeres and the limitations of existing tools. Here, we report a highly efficient and inducible CRISPR/Cas9-mediated system for generating de novo telomeres with defined blunt ends in S. pombe. This fine setting allows for the precise dissection of post-replicative telomere end structures at near single-nucleotide resolution. Using this system, we show that the replicated leading-strand telomere is blunt-ended, while the lagging-strand counterpart contains a [~]10-nt 3 overhang resulting from RNA primer removal. By analyzing mutants deficient in ribonucleases, we found that the removal of this terminal RNA primer is specifically dependent on RNase H2, but not RNase H1. This RNase H2-dependent mechanism is essential for defining the mature structure of the lagging-strand telomere with authentic telomeric sequences. Our findings reveal a fundamental asymmetry in telomere end processing after replication and establish RNase H2 as the key enzyme responsible for resolving the terminal RNA primer in lagging-strand telomeres. This mechanism, conserved from budding to fission yeast, underscores the critical and evolutionarily ancient role of RNase H2 in defining eukaryotic telomere architecture. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/738813v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1991a5eorg.highwire.dtl.DTLVardef@924467org.highwire.dtl.DTLVardef@c8f39eorg.highwire.dtl.DTLVardef@f240d7_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2026

UBE3C retrofits the proteasome to enforce degradation of ultra-stable folds

Neurodegeneration and proteinopathies arise from mutated or misfolded proteins that form ultra-stable, proteotoxic aggregates that evade proteasomal degradation despite ubiquitylation1-8. These conditions are exacerbated by the deubiquitylase USP14 that can prematurely rescue substrates9-11. To counter these obstacles to effective proteolysis, eukaryotes evolved the highly conserved HECT-type E3 ligase UBE3C--dysregulated in neurodegeneration12,13 and overexpressed in cancers14-17--to reprogram the 26S proteasome toward heightened activity via unknown mechanisms18-25. Here we visualized functional dynamics of the human UBE3C-retrofitted proteasome enforcing degradation of a re-engineered superfolder GFP that normally escapes proteolysis, using time-resolved cryo-electron microscopy. A continuum of non-equilibrium conformations, comprising fourteen proteasome conformers orthogonally combined with four UBE3C states or three USP14 states, reveals a cryptic UBE3C-receptor site in the proteasomal lid and captures key intermediates of ubiquitin-chain elongation and branching at four linkage-specific ubiquitin-binding sites. Remarkably, UBE3C creates an extreme shortcut for ubiquitin shuttling that bypasses USP14, promotes USP14 recycling and allosterically strengthens substrate-unfolding forces of the AAA-ATPase unfoldase to ultimately surmount the unfolding energy barrier of ultra-stable proteins. These findings define the complete functional cycle of the UBE3C-reprogrammed proteasome, illuminating how UBE3C simultaneously controls USP14 and the proteasome to enforce clearance of ultra-stable folds, and establish crucial mechanistic foundations for proteolysis-targeting therapeutic discovery.

biochemistry↗

bioRxiv2026

Differential higher-order superassembly of HECT-type UBE3 ligases controlled by calcium signals

The yeast E4 ligase Hul5 transiently associates with the proteasome during heat shock and proteotoxic stress to maintain cytosolic protein quality control. Two of its human orthologs, UBE3B and UBE3C, have specialized to safeguard mitochondria and inherit Hul5 function, respectively. We determined cryo-electron microscopy structures of full-length human UBE3B and UBE3C in complex with calmodulin at 2.9-3.5 [A] in calcium-free and calcium-saturated conditions. Calmodulin acts as an inter-protomer molecular glue clamping UBE3B into ring-shaped anti-parallel homodimers or asymmetric trimers, and remodels UBE3C into a conformation competent for proteasome association. Calcium binding to calmodulin promotes disassembly of these higher-order complexes, toggling UBE3B/C from E4 to E3 activity. These findings reveal how calmodulin regulates higher-order architectures of E3/E4 ligases to rewire the ubiquitin-proteasome system via calcium signaling.

biochemistry↗

bioRxiv2025

Template-based RNA structure prediction advanced through a blind code competition

Automatically predicting RNA 3D structure from sequence remains an unsolved challenge in biology and biotechnology. Here, we describe a Kaggle code competition engaging over 1700 teams and 43 previously unreleased structures to tackle this challenge. The top three submitted algorithms achieved scores within statistical error of the winners of the recent CASP16 competition. Unexpectedly, the top Kaggle strategy involved a pipeline for discovering 3D templates, without the use of deep learning. We integrated this template-modeling pipeline and other Kaggle strategies to develop a single model RNAPro that retrospectively outperformed individual Kaggle models on the same test set. These results suggest a growing importance of template-based modeling in RNA structure prediction.

biophysics↗

bioRxiv2025

Rapid and Reproducible Multimodal Biological Foundation Model Development with AIDO.ModelGenerator

Foundation models (FMs) for DNA, RNA, proteins, cells, and tissues have begun to close long-standing performance gaps in biological prediction tasks, yet each modality is usually studied in isolation. Bridging them requires software that can ingest heterogeneous data, apply large pre-trained backbones from various sources, and perform multimodal benchmarking studies at scale. We present AIDO.ModelGenerator, an open-source toolkit that turns these needs into declarative experiment recipes through a structured experimental framework. AIDO.ModelGenerator provides (i) 300+ datasets covering DNA, RNA, protein, cell, spatial, and multimodal data types; (ii) 30+ pretrained FMs ranging from 3M to 16B parameters; (iii) 10+ plug-and-play use-cases covering inference, adaptation, prediction, generation, and zero-shot evaluation; and (iv) YAML-driven experiment recipes that enable exact reproducibility. On a sequence-to-expression prediction task, AIDO.ModelGenerator systematically builds and tests unimodal and multimodal models, achieving a new SOTA by combining DNA and RNA FMs that outperforms unimodal baselines by over 10%. In a Crohns disease case-study, the frameworks simulated knockout protocol ranks the clinically implicated target SOX4 6,000 positions higher than differential-expression baselines, illustrating its utility for therapeutic target discovery. We release code, tutorials, checkpoints, datasets, and API reference to accelerate multimodal FM research in the life sciences1.

bioinformatics↗

bioRxiv2025

Chromosomal-level genome of the Pinus massoniana 'Minlin WY36'

Owing to conifers complex and large genomes, it is challenging to construct a comprehensive reference genome and conduct evolutionary and genomic research. Here, we present the chromosome-level assembly of Pinus massoniana Minlin WY36, a pioneering conifer species used for afforestation, timber production, and oleoresin extraction. The genome size was determined to be 23.41 Gb, with a contig N50 value of 1.15 Mb and a scaffold N50 value of 2.02 Gb. A total of 23.16 Gb of reads (98.93% of the assembled genome) were anchored and oriented onto 12 pseudochromosomes, with chromosome lengths from 1.47 to 2.29 Gb. A total of 32,144 protein-coding genes were predicted, of which 27,173 (84.54%) were functionally annotated. The P. massoniana Minlin WY36 genome consists of 79.41% (18.57 Gb) repetitive sequences, among which long terminal repeat sequences (LTR) were the most abundant. Through comparative genomic analysis, we found that the unique and significantly expanded genes in P. massoniana Minlin WY36 were enriched in the metabolism related to resin synthesis. This study offers valuable insights into conifer evolution and contributes resources for further investigations of conifer adaptation and developmental processes.

genomics↗

bioRxiv2025

Super-giga and tiny orchid genomes illuminate evolution of Orchidaceae

Orchidaceae (orchids) is commonly known as one of the largest families of seed plants, and grow in an extensive range of habitats worldwide. In the present study, we generated chromosome-level reference genomes for two orchids using a combination of PacBio, Illumina, and Hi-C sequencing, Cypripedium singchii has the largest genome and chromosomes among the sequenced species so far, with a genome size of 43.19 Gb (1C) with ten chromosomes, and Apostasia fujianica has the smallest known genome and chromosomes in Orchidaceae, with a genome size of 340.90 Mb (1C) with 35 chromosomes. We predicted a total of 32,412 and 21,724 protein-coding genes for C. singchii and A. fujianica, respectively. The overall BUSCO score was 85.01% for C. singchii and 91.80% in A. fujianica. Based on protein-coding sequences from 55 conserved single-copy families across 21 plant species, we constructed a high-confidence phylogenetic tree and estimated the divergence times. The high-quality genomes of super-giga and tiny orchids offer key insight for future evolutionary researches.

genomics↗

bioRxiv2025

Rapaprotin is Activated by an Endopeptidase to Disassemble 26S Proteasome

The 19S regulatory particle (RP) associates with the 20S core particle (CP) to form the 26S proteasome, an evolutionarily conserved holoenzyme that plays key roles in both physiological and pathological processes. Proteasome inhibitors that target the catalytic subunits within the 20S have proven to be valuable research tools and therapeutics for various cancers. Herein we report the discovery of rapaprotin, a 26S proteasome assembly inhibitor from our natural product-inspired hybrid macrocycle rapafucin library. Rapaprotin induces apoptosis in both myeloma and leukemia cell lines. Genome-wide CRISPR-Cas9 screen identified a cytosolic enzyme, prolyl endopeptidase (PREP) that is required for the pro-apoptotic activity of rapaprotin. Further mechanistic studies revealed that rapaprotin acts as a molecular transformer, changing from an inactive cyclic form into an active linear form, rapaprotin-L, upon PREP cleavage, to block 26S proteasome activity. Time-resolved cryogenic electron microscopy (cryo-EM) revealed that rapaprotin-L induces dissociation of the 19S RP from the 26S holoenzyme, which was verified in cells. Furthermore, rapaprotin exhibits a marked synergistic effect with FDA-approved proteasome inhibitors and resensitizes drug-resistant multiple myeloma cells from patients to bortezomib. Taken together, these results suggest that rapaprotin is a new chemical tool to probe the dynamics of the 26S proteasome assembly and a promising anticancer drug lead.

pharmacology and toxicology↗

bioRxiv2024

Peptide Information Compression Technology (PICT): A New Frontier in Therapeutic Peptide Discovery

Therapeutic peptides hold tremendous market potential, yet the discovery methods for active peptides lag considerably behind those for small molecules and biological macromolecule drugs. Due to their respective limitations, traditional peptide compound synthesis and display libraries fail to meet the growing demands of the peptide drug market. Here, we introduce a novel Peptide Information Compression Technology (PICT) and, based on this technology, a large-scale physical peptide library and its accompanying high-throughput screening (HTS) platform. By screening for inhibitors of TSLP/TSLPR/IL7R and antagonists of MC3R at both the molecular and cellular levels, we have identified active molecules in the single-digital micromolar and nanomolar ranges, respectively. This demonstrates the immense application value of Peptide Information Compression Technology in the efficient discovery of peptide drugs.

molecular biology↗

bioRxiv2024

Mixture of Experts Enable Efficient and Effective Protein Understanding and Design

Proteins play a fundamental role in life. Understanding the language of proteins offers significant potential for gaining mechanistic insights into biological systems and introduces new avenues for treating diseases, enhancing agriculture, and safeguarding the environment. While large protein language models (PLMs) like ESM2-15B and xTrimoPGLM-100B have achieved remarkable performance in diverse protein understanding and design tasks, these models, being dense transformer models, pose challenges due to their computational inefficiency during training and deployment. In this work, we introduce AIDO.Protein, a pretrained module for protein representation in an AI-driven Digital Organism [1]. AIDO.Protein is also the first mixture-of-experts (MoE) model in the protein domain, with model size scales to 16 billion parameters. Leveraging a sparse MoE architecture with 8 experts within each transformer block and selectively activating 2 experts for each input token, our model is significantly more efficient in training and inference. Through pre-training on 1.2 trillion amino acids collected from UniRef90 and ColabfoldDB, our model achieves state-of-the-art results across most tasks in the xTrimoPGLM benchmark. Furthermore, on over 280 ProteinGym Deep Mutational Scanning (DMS) assays, our model achieves nearly 99% of the overall performance of the best MSA-based model and significantly outperforms the previously reported state-of-the-art models that do not utilize MSA. We also adapted this model for structure-conditioned protein sequence generation tasks and achieved new SOTA in this domain. These results indicate that AIDO.Protein can serve as a strong foundation model for protein understanding and design. Models and codes are available through ModelGenerator in https://github.com/genbio-ai/AIDO and on Hugging Face.

bioinformatics↗

bioRxiv2024

A Large-Scale Foundation Model for RNA Function and Structure Prediction

Originally marginalized as an intermediate in the information flow from DNA to protein, RNA has become the star of modern biology, holding the key to precision therapeutics, genetic engineering, evolutionary origins, and our understanding of fundamental cellular processes. Yet RNA is as mysterious as it is prolific, serving as an information store, a messenger, and a catalyst, spanning many underchar-acterized functional and structural classes. Deciphering the language of RNA is important not only for a mechanistic understanding of its biological functions but also for accelerating drug design. Toward this goal, we introduce AIDO.RNA, a pre-trained module for RNA in an AI-driven Digital Organism [1]. AIDO.RNA contains a scale of 1.6 billion parameters, trained on 42 million non-coding RNA (ncRNA) sequences at single-nucleotide resolution, and it achieves state-of-the-art performance on a comprehensive set of tasks, including structure prediction, genetic regulation, molecular function across species, and RNA sequence design. AIDO.RNA after domain adaptation learns to model essential parts of protein translation that protein language models, which have received widespread attention in recent years, do not. More broadly, AIDO.RNA hints at the generality of biological sequence modeling and the ability to leverage the central dogma to improve many biomolecular representations. Models and code are available through ModelGenerator in https://github.com/genbio-ai/AIDO and on Hugging Face.

bioinformatics↗

bioRxiv2024

Salt-dependent non-catalytic allostery of human USP14-regulated 26S proteasome

USP14, a deubiquitylating enzyme, regulates 26S proteasome function both catalytically and non-catalytically through multiple checkpoints. How USP14 non-catalytically regulates the proteasome activity remains elusive. Here, we combined genetic engineering and cryo-EM to disentangle how USP14 non-catalytically regulates proteasome activity in a salt-dependent manner. By solving 16 high-resolution cryo-EM structures of substrate-engaged human 26S proteasome complexed with a catalytically deficient mutant USP14, we demonstrate that USP14s non-catalytic activity alone can induce parallel pathways of proteasome state transitions, leading to opposing substrate fates. The USP14 mutant allosterically reprograms the AAA-ATPase motor, inducing novel substrate-engaged conformations and filling major gaps in understanding asymmetric ATP-hydrolysis cycling around the ATPase ring. Time-resolved cryo-EM and functional analysis reveal that sodium or potassium promotes substrate-engaged pathways and suppresses USP14 activity for enhanced degradation, uncovering another layer of complexity in proteasome regulation.

biochemistry↗