Biology subjects

Sun, H.

Publications and source records attributed to Sun, H..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

The Par complex regulates apical-basal cell polarity through modulation of FAK signaling homeostasis

Cell polarity complexes are essential for embryogenesis, but their regulatory mechanisms during early developmental transitions remain incompletely understood. Here, we individually deleted the Crumbs, Par, and Scrib polarity complexes in mouse embryonic stem cells (mESCs). While loss of any single complex did not affect pluripotency or proliferation, deletion of Par complex disrupted the naive-to-primed transition and impaired subsequent differentiation, particularly lumen formation in neural tube organoids. Mechanistically, Par complex deficiency led to hyperphosphorylation of focal adhesion kinase (FAK) at the primed stage, driving a morphological shift from flat monolayer clusters to dome-shaped colonies. FAK inhibition rescued the aberrant morphology. Upstream, Par complex loss increased AKT phosphorylation, which remodeled extracellular matrix (ECM) and regulated integrin signaling via FURIN-LEFTY, ultimately modulating FAK activity. In addition, conditioned medium from wild-type cells partially rescued differentiation defects in Par knockout cells in a LEFTY-dependent manner. These phenotypes were consistently observed in naive-to-primed transition, neural stem cell differentiation, embryoid body formation, teratoma assays, and neural tube organoid differentiation. Together, these findings establish a Par complex-AKT-FURIN-LEFTY-ECM-integrin-FAK signaling cascade that links apical-basal polarity to early lineage specification and morphogenesis, providing a mechanistic framework for how polarity cues are translated into developmental outcomes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/722465v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@179e0adorg.highwire.dtl.DTLVardef@8d83bdorg.highwire.dtl.DTLVardef@c425fforg.highwire.dtl.DTLVardef@19a8ee5_HPS_FORMAT_FIGEXP M_FIG C_FIG Significance StatementThis study elucidates the molecular mechanism by which the Par complex regulates the establishment of cell polarity. The authors demonstrate that the Par complex promotes the expression of the protein convertase FURIN via AKT signaling, thereby enhancing the maturation and secretion of LEFTY protein. This process remodels the ECM and modulates integrin signaling, ultimately regulating FAK activity and controlling the establishment of cell polarity. These findings reveal how polarity cues govern early lineage specification and morphogenesis, with implications across multiple developmental contexts.

developmental biology↗

bioRxiv2026

Cell membrane proteome profiling uncovers molecular signatures and GPCR regulators underlying diet-induced obesity and exercise-mediated adaptation

Cell membrane proteins (CMPs), notably G protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs), represent the largest class of druggable targets. Despite their therapeutic importance, how the CMP landscape is systemically remodeled during metabolic disease progression and in response to exercise remains poorly understood. Here, we constructed the most comprehensive CMP proteome atlas to date across 22 male mouse tissues and established the first multi-tissue map of GPCR-associated protein hormones/prohormones. Integrated CMP proteomic and transcriptomic analysis revealed that diet-induced obesity and its progression to type 2 diabetes remodel the CMP repertoire in patterns distinct from those induced by exercise. We found that numerous GPCRs and RTKs critical for energy homeostasis are dysregulated during obesity in a tissue-specific manner, and these alterations are reversed to varying extents by exercise training. Importantly, our CMP-centric omics study identified two parathyroid hormone receptors (PTHRs) in the hypothalamus as negative regulators of feeding and body weight. Genetically silencing these hypothalamic PTHRs led to severe obesity even on a chow diet and markedly blunted exercise-induced weight loss. Collectively, our study provides not only new insights into systematic CMP regulation underlying metabolic deterioration versus exercise adaptation, but also nominates potential receptor targets for obesity management.

biochemistry↗

bioRxiv2026

Origin and evolution of grapevine genomes

Grapevines (Vitis) belonging to grape family (Vitaceae) are symbolic fruit crops pivotal to human civilization. The evolutionary history of grapevines divergent from other Vitaceae plants remains mysterious, requiring a family-wide whole-genome phylogenomic analysis. Here, we conduct chromosome-level phylogenomics to investigate the origin and evolution of grapevines using 29 genome assemblies of five genera Vitis, Parthenocissus, Ampelopsis, Tetrastigma, and Cissus, 27 of which are newly released in this study. Phylogenomic and macrosynteny analysis unanimously support Ampelopsis as a sister lineage to Parthenocissus, placing both closer to Vitis, with introgression and incomplete lineage sorting contributing to these relationships. Ancestral genome reconstruction delineates the major chromosome rearrangement events in Vitaceae karyotype evolution, highlighting the conserved karyotype in Vitis and the extensive karyotypic reorganization in Tetrastigma and Cissus. Pan-3D genome analysis highlights the contributions of structural variants (SVs) to the variation of A/B compartments and topologically associated domains (TADs), revealing a strong purifying selection of SVs at TAD boundaries. We further demonstrate that Helitron transposons drive the expansion and expression regulation of NLR immune-receptor genes in Vitis. Importantly, we discovered an NLR gene VbRpv35 from wild grapevine V. bellula resistant to downy mildew (DM), whose heterologous expression in V. vinifera confers enhanced DM resistance. Taken together, we provide phylogenomic insight into the origin and evolution of grapevines and valuable resources for grapevine improvement and understanding angiosperm evolution.

genomics↗

bioRxiv2026

Canalized gene regulatory networks stabilize floral polymorphism and enable modular transgressive expression

O_LIFloral polymorphisms frequently persist across heterogeneous environments despite ongoing gene flow, yet the regulatory mechanisms maintaining discrete phenotypes remain unclear. We tested whether alternative flower-colour morphs in Stellera chamaejasme L. are maintained by canalized gene regulatory architectures that stabilize expression around morph-specific optima. C_LIO_LIWe used a pan-transcriptomic and eco-evolutionary framework integrating genome-wide gene expression profiling, co-expression network analysis, functional enrichment, ortholog-based phylogenomics, and variance-based modeling of regulatory canalization and transgressive expression to quantify regulatory variation across morphs. C_LIO_LITranscriptomic variation was structured primarily by morph identity rather than geography, indicating consistent morph-associated regulatory programs. Parental morphs showed reduced within-morph variance in gene co-expression modules, consistent with strong regulatory constraint at the network level. In contrast, a naturally occurring mosaic morph exhibited extensive non-additive and predominantly transgressive expression, with most genes falling outside the parental range. This transgressive signal was modular, with most networks remaining stable while a subset showed elevated variance and disrupted inheritance. Functional analyses further reveal that floral pigmentation is embedded within broader metabolic and stress-response pathways, linking color polymorphism to coordinated physiological states and ecological differentiation. C_LI

plant biology↗

bioRxiv2026

Atomic structure and dynamics of the mechanosensitive channel MscL from E. coli by cryo-EM and solid-state NMR

Mechanosensitive channels are central to cellular responses to membrane tension, yet the structural basis of their gating remains incompletely understood. Here, we determine the structures of wild-type and G22S mutants of MscL from E. coli (EcMscL) by cryo-EM in peptide-based lipid nanodiscs and complement them with solid-state NMR measurements in liposomes to capture their dynamics in a native-like membrane environment. The cryo-EM structures reveal a closed conformation, whereas analysis of the low-threshold G22S mutant by NMR uncovers widespread conformational changes in both cytoplasmic and periplasmic regions. These data indicate enhanced dynamics and conformational heterogeneity in the mutant, revealing the early transitions from the closed towards the open state. Together, our results establish a synergistic framework integrating cryo-EM and NMR to resolve both structure and dynamics of mechanosensitive channels, and identify lipid-protein interactions as key determinants of MscL gating and mechanosensitivity. Our study further provides a quantitative benchmark for computational investigations of mechanogating and lays the foundation for the rational design of channels with tunable gating kinetics. TeaserBy integrating cryo-EM and solid-state NMR, we reveal how lipid-coupled dynamics prime MscL for opening, capturing the earliest transitions from closed to active states.

biophysics↗

bioRxiv2026

Structure-aware geometric graph learning for modeling protease-substrate specificity at scale

Protease-substrate specificity is central to cellular regulation and disease pathogenesis, and accurately modeling its structural determinants remains challenging. Substrate recognition is governed by spatial constraints and higher-order relationships that extend beyond local sequence motifs. Most computational approaches rely predominantly on motif-centric or sequence-based representations, limiting their ability to capture the geometric and relational structure underlying enzymatic specificity. Here, we introduce OmniCleave, a structure-aware geometric graph learning framework for modeling protease-substrate specificity at scale. OmniCleave is trained on 57,278 structure-informed protease-substrate pairs derived from 9,651 substrates spanning over 100 proteases across six distinct families. The framework integrates multi-scale structural graphs with higher-order protease relational topology, explicitly encoding spatial context and inter-protease dependencies within a unified geometric representation. This formulation moves beyond local pattern recognition and enables transferable modelling across six protease families. Across large-scale benchmarks, the framework consistently outperforms existing approaches and reveals interpretable geometric determinants underlying substrate recognition. Experimental validation confirms three novel caspase-3 substrates and 21 cleavage sites predicted by OmniCleave, supporting the biological relevance of the learned representations. Together, OmniCleave provides a scalable geometric framework for modeling protease-substrate specificity, with practical utility for systematic analysis of protease biology.

bioinformatics↗

bioRxiv2026

Role of Nonneutralizing Antibodies and Fc Effector Functions in Inhibiting SARS-CoV-2 Infection

Neutralizing monoclonal antibodies (mAbs) are a key component of antiviral therapeutics against SARS-CoV-2; however, the contribution of Fc-mediated effector functions remains underexplored. Here, we compare the antiviral activities of the neutralizing and non-neutralizing mAbs CB6 and CR3022, respectively. The Fc regions of both plant-produced mAbs carried nonfucosylated, non-galactosylated complex glycans (pCB6 and pCR3022), and CR3022 was also produced with mammalian-typical galactosylated, fucosylated glycans (mCR3022). pCR3022 exhibited markedly enhanced antibody-dependent cellular cytotoxicity (ADCC) and antibody-dependent cell-mediated virus inhibition (ADCVI) compared to mCR3022, indicating a significant impact of Fc glycosylation on antiviral activity despite the lack of neutralization. pCB6 exhibited potent neutralization while further enhancing virus clearance through synergistic Fc effector activity. Our findings suggest that Fc-mediated mechanisms, especially ADCC and ADCVI, can contribute substantially to viral control and may be particularly valuable against immune-evasive variants. These results advance our understanding of the functional roles that non-neutralizing antibodies can play in SARS-CoV-2 infection and highlight the potential of Fc glycoengineering to modulate the antiviral efficacy of both neutralizing and non-neutralizing mAbs.

immunology↗

bioRxiv2026

From nucleotides to semantics: genomic representation learning via joint-embedding predictive architecture

Decoding the regulatory syntax encoded in genomic sequences is a central objective in computational biology. Most existing genomic foundation models treat DNA as a language and adopt pretraining objectives from natural language processing. DNA sequences, however, lack explicit semantic boundaries and contain substantial evolutionary noise. Nucleotide-level reconstruction in a low-dimensional input space can therefore increase computational overhead and may yield representations with limited discriminative capacity. Downstream tasks often depend on expensive finetuning, which restricts practical use in many biology laboratories. Here we present GenoJEPA, a genomic representation learning framework based on joint-embedding predictive architecture. GenoJEPA combines continuous patching with semantic alignment, shifting the optimization from local base reconstruction to semantic alignment in latent space. Across 55 downstream tasks, GenoJEPA shows strong representational capacity and robust generalization while reducing parameter count and computational cost. The resulting semantic vectors from frozen GenoJEPA support lightweight GPU-free classifiers to achieve competitive accuracy. These results suggest a practical route towards efficient training and broad application of larger-scale genomic foundation models.

bioinformatics↗

bioRxiv2026

MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization

Computational drug discovery, particularly the complex workflows of drug molecule screening and optimization, requires orchestrating dozens of specialized tools in multi-step workflows, yet current AI agents struggle to maintain robust performance and consistently underperform in these high-complexity scenarios. Here we present MolClaw, an autonomous agent that leads drug molecule evaluation, screening, and optimization. It unifies over 30 specialized domain resources through a three-tier hierarchical skill architecture (70 skills in total) that facilitates agent long-term interaction at runtime: tool-level skills standardize atomic operations, workflow-level skills compose them into validated pipelines with quality check and reflection, and a discipline-level skill supplies scientific principles governing planning and verification across all scenarios in the field. Additionally, we introduce MolBench, a benchmark comprising molecular screening, optimization, and end-to-end discovery challenges spanning 8 to 50+ sequential tool calls. MolClaw achieves state-of-the-art performance across all metrics, and ablation studies confirm that gains concentrate on tasks that demand structured workflows while vanishing on those solvable with ad hoc scripting, establishing workflow orchestration competence as the primary capability bottleneck for AI-driven drug discovery.

bioinformatics↗

bioRxiv2026

Generative machine learning unlocks the first proteome-wide image of human cells

The spatial organization of proteins within cells governs virtually all cellular functions, yet current imaging can simultaneously visualize only tens of proteins, orders of magnitude below the thousands populating a single human cell. Here we present ProtiCelli, a deep generative model that simulates microscopy images for 12,800 human proteins from just three cellular landmark stains. Trained on 1.23 million Human Protein Atlas images, ProtiCelli outperforms existing methods in reconstruction accuracy and textural fidelity, and generalizes to unseen cell types and drug perturbations. Simulated images preserve hierarchical subcellular organization, recapitulate known protein protein interaction landscapes, and resolve compartment-specific functions of moonlighting proteins at single cell resolution. Remarkably, the model infers drug-induced changes in protein expression and localization from cell morphology alone, predicts cell cycle stage without dedicated markers, and enables unsupervised segmentation of subcellular compartments and spatial decomposition of gene sets into functional regions. We leverage ProtiCelli to generate Proteome2Cell, a dataset of 30.7 million simulated images spanning 2,400 virtual cells across 12 human cell lines, enabling hierarchical single-cell models that distinguish conserved from dynamic protein architectures. Integrated into the Human Protein Atlas, Proteome2Cell democratizes exploration of these virtual cells. By computationally bridging the experimental scalability gap, ProtiCelli establishes a foundation for spatial virtual cell modeling.

cell biology↗

bioRxiv2026

RNASTOP: A Deep Learning Framework for mRNA Chemical Stability Prediction and Optimization

Messenger RNA (mRNA) vaccines offer promising therapeutics for combating various diseases, yet their inherent chemical instability hampers their long-term efficacy. Although several methods have been developed to predict mRNA degradation, they exhibit limited accuracy and lack the capability for rational sequence optimization. Here, we propose RNASTOP, a novel framework integrating deep learning with heuristic search to simultaneously predict and optimize mRNA chemical stability. RNASTOP achieves a 13% accuracy improvement over the top-performing model on the Stanford OpenVaccine competition dataset and demonstrates robust generalization in predicting full-length mRNA degradation. Applied to mRNA codon optimization, RNASTOP reduces the minimum free energy of the Varicella-Zoster Virus vaccine sequence by 75.73% while maintaining high translation efficiency. Overall, RNASTOP serves as a powerful tool for predicting and optimizing mRNA chemical stability, poised to expedite the development of mRNA therapeutics. The source code of RNASTOP can be accessed at https://github.com/xlab-BioAI/RNASTOP.

bioinformatics↗

bioRxiv2026

Stage-resolved dynamics of antibiotic resistance genes and mobile genetic elements in full-scale anaerobic digestion systems

Anaerobic digestion (AD) has the potential to reduce antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) during waste treatment, yet evidence from full-scale plants remains limited and the relative importance of operational and physicochemical drivers is poorly resolved. Here, we profiled stage-resolved resistome and mobilome dynamics across substrates, digestates, and post-digestion storages from ten Swedish farm-scale AD plants (42 samples). High-throughput qPCR (ResistoMap) was combined with absolute 16S rRNA gene quantification and 16S rRNA gene amplicon sequencing to quantify ARG/MGE abundances and characterise bacterial community structure. ARGs and MGEs showed heterogeneous changes during digestion and subsequent storage, with both increases and decreases across plants. Non-metric multidimensional scaling (NMDS) suggested that higher pH and free ammonia were associated with decreasing trends in ARG and MGE relative abundance. Stage-resolved correlation networks revealed a dominant ARG-MGE association backbone that remained largely conserved from substrates to digestates and storage, whereas host-ARG and host-MGE associations were extensively restructured across processing stages. Collectively, these results show that stage-resolved, network-informed analyses offer a more informative framework than pooled, static approaches for evaluating resistance persistence and potential environmental risks associated with digestate application.

microbiology↗

bioRxiv2026

Cellular protein delivery through membrane potential driven water pores

Providing immediate access for functional proteins inside living cells would unlock unprecedented control over cellular processes; however, commonly used endocytic delivery suffers from endosomal trapping and degradation. One of the most powerful non-endosomal delivery methods uses cell surface anchored cell penetrating peptide (CPP)-additives that allow proteins to enter cells directly. Nevertheless, the underlying molecular mechanism involved in direct entry via crossing the cell membrane (protein translocation through the cell) and the major driving forces remain controversially discussed. Here, we provide a stepwise molecular picture on how CPP-additives enable uptake of protein cargoes through direct membrane translocation. CPP-additives accumulate on the cell surface in nucleation zones, locally hyperpolarizing the membrane, and induce transient water pores that allow selective CPP-protein entry without compromising membrane integrity. These fundamental mechanistic insights provide a firm basis for rationally optimizing delivery strategies using highly cationic CPPs, ultimately resulting in innovative and smart protein delivery strategies to advance therapeutic protein applications. Abstract Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/707441v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@14c1386org.highwire.dtl.DTLVardef@195f765org.highwire.dtl.DTLVardef@a52258org.highwire.dtl.DTLVardef@171dd7c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

Gut Microbiota Dysbiosis-Mediated Gut NLRP3 Inflammasome Activation Exacerbates Corticospinal Tract Injury After Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) causes severe neurological deficits, largely attributable to corticospinal tract (CST) injury. However, the underlying mechanism remains unclear, which hinders the development of effective treatment methods. Here, we found that CST injury is not only associated with the activation of NLRP3 inflammasome in the surrounding area of the hematoma as expected, and dysfunction of the blood-brain barrier, but also related to the severe imbalance of the gut microbiota, the activation of NLRP3 inflammasome in the gut and the impairment of gut barrier function after ICH. We therefore systematically investigated how the gut NLRP3 inflammasome and gut dysbiosis exacerbate CST injury after ICH. Knockdown of colon NLRP3 significantly attenuated CST injury and downregulated inflammasome signaling in both the peripheral circulation and the peri-hematomal brain. Consistently, antibiotic-mediated gut microbiota depletion suppressed NLRP3 activation in the gut and brain, improved neurological function, and reduced CST damage. Crucially, fecal microbiota transplantation (FMT) from ICH donors established that the exacerbation of CST injury is dependent on gut dysbiosis. While FMT induced severe pathology in control mice, this effect was improved in gut NLRP3 knockdown recipients, demonstrating that gut NLRP3 is essential for mediating the harmful effects of microbiota dysbiosis. Our findings described a causal gut-brain axis in ICH, wherein microbiota dysbiosis activates the gut NLRP3 inflammasome to exacerbate CST injury, thereby identifying the gut NLRP3 inflammasome as a promising therapeutic target.

neuroscience↗

bioRxiv2026

Graph-based RNA structural representation reveals determinants of subcellular localization

RNA subcellular localization is a key determinant of RNA function and regulation, yet existing computational approaches rely primarily on sequence or simplified structural descriptors, limiting their scalability to long transcripts, their ability to model inter-label dependencies, and their applicability across RNA types. Here, we present GRASP, a unified graph neural network framework for predicting RNA subcellular localization using a heterogeneous graph representation that is RNA substructure-aware. GRASP presents each RNA as a multi-scale graph comprising nucleotide nodes and secondary-structure-derived substructure nodes, connected by relational edges, enabling joint modeling of base-level interactions and regional structural context. The model further incorporates multi-label dependency learning to capture co-localization patterns across cellular compartments within a unified framework. Across multiple benchmark datasets and RNA types, GRASP consistently outperforms state-of-the-art sequence-based and structure-informed methods, achieving substantial improvements in accuracy, F1 score, and AUC while maintaining strong scalability to long transcripts. In addition, the graph-based representation provides biologically interpretable insights into structural determinants of RNA localization. The source code and data are available at https://github.com/ABILiLab/GRASP, and the web server is accessible at http://grasp.biotools.bio.

bioinformatics↗

bioRxiv2026

Vagus Nerve Stimulation Ameliorates Epilepsy via a Gut Microbiota-Butyrate-Vagus Nerve-Brain Axis

Vagus nerve stimulation (VNS) is an established therapy for drug-resistant epilepsy, yet its mechanism remains partially understood. Here, through an integrated clinical-translational approach, we demonstrate that VNS modulates the gut microbiome and alter the level of butyrate to reduce seizure susceptibility via vagus nerve-dependent signaling. In a longitudinal cohort of epilepsy patients, VNS enriched short-chain fatty acid-producing bacteria, including Akkermansia muciniphila, Prevotella, Alistipes, and Odoribacter. Among clinical responders, fecal butyrate levels decreased concomitantly with an increase in plasma butyrate concentrations. Fecal microbiota transplantation from post-VNS patients into mice reduced seizure severity and improved gut barrier integrity. In a murine model of epilepsy, VNS similarly increased the abundance of Akkermansia and plasma butyrate concentrations, decreased fecal butyrate levels, and abolished its antiseizure effects upon vagotomy. Either colonization with Akkermansia muciniphila or exogenous butyrate supplementation was sufficient to reduce seizures and anxiety-like behavior, effects that also required intact vagal signaling. Our findings define a microbiota-butyrate-vagal pathway essential for the therapeutic effects of VNS, highlighting the gut-brain axis as a target for epilepsy treatment. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/707138v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@8243e6org.highwire.dtl.DTLVardef@37f0e6org.highwire.dtl.DTLVardef@a8b321org.highwire.dtl.DTLVardef@1887342_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIVagus nerve stimulation (VNS) remodels the gut microbiota and alter the level of butyrate. C_LIO_LIVNS enriches short-chain fatty acids-producing bacteria, specifically Akkermansia muciniphila, in both humans and mice. C_LIO_LITransplantation of VNS-conditioned microbiota confers seizure protection and restores gut barrier integrity. C_LIO_LIAkkermansia muciniphila or exogenous butyrate is sufficient to reduce seizures via a vagus nerve-dependent pathway. C_LI

neuroscience↗

bioRxiv2026

Atomic structure and plasticity of the MthK-CTX complex investigated by cryo-EM, NMR, and MD simulations

Scorpion toxins block potassium channels, disrupting cellular excitability and causing symptoms such as pain, muscle spasms, or paralysis. Here, we use an integrated structural biology approach to uncover the binding mode of the scorpion toxin charybdotoxin (CTX) to the MthK channel, a model system for human large-conductance potassium (BK) channels. Cryo-EM defines the overall architecture of the MthK-CTX complex, while complementary solution- and solid-state NMR experiments identify key binding residues and show that toxin engagement alters the selectivity filter (SF) ion configuration without rearranging the filter itself. NMR and MD simulations further reveal an anchoring lysine residue stably inserted into the SF, while other contacts undergo fast NMR timescale dynamics. Together, these findings explain how CTX-like toxins maintain exceptionally high affinity while tolerating binding across multiple K+ channel subtypes, paving the way for site-specific extracellular modulation.

molecular biology↗

bioRxiv2026

Fine-tuning STEAP1 protein expression and purification to preserve its conformation and function

Six-transmembrane Epithelial Antigen of the Prostate 1 (STEAP1) has emerged as a promising therapeutic target for prostate cancer. We have optimized the expression and purification conditions of human STEAP1 to maximize the production of its homotrimeric form, which is crucial for metal ion reduction and maintaining cellular redox balance. Proteins obtained from these optimized conditions were complexed with both heme and flavin-adenine dinucleotide (FAD), two cofactors that are fundamental to STEAP functionality, suggesting native folding and interactions of the protein. In addition, we compared the impact of stable and transient expression systems on the protein quality of STEAP1. We found that stable expression promoted heme incorporation, improved expression homogeneity, and ensured correct protein orientation on cell surfaces. Our findings present effective strategies for optimizing the recombinant production of STEAP1, with potential applicability to other STEAP family proteins to facilitate therapeutic discovery.

biochemistry↗