Biology subjects

Lee, J. S.

Publications and source records attributed to Lee, J. S..

At least 19 recordsLinked to original sources

bioRxiv2026

Inhibition of Pseudomonas aeruginosa-secreted protease IV reduces lung

The opportunistic pathogen Pseudomonas aeruginosa secretes numerous proteases that disrupt host defenses. Among them, the lysyl endopeptidase PrpL has been implicated in virulence, but its role in inflammatory responses has remained unclear. This study shows that purified PrpL activates the AP-1 transcription factors following instillation into mouse lungs, and drives robust production of IL-1{beta}, IL-6, and TNF, as well as clinical symptoms. A proteolytically inactive mutant of PrpL fails to elicit these responses. Structural analysis of the complex of PrpL and its natural inhibitory propeptide (PrpLPP) using X-ray crystallography revealed the inhibitory mechanism of PrpLPP, which guided the identification of a pre-existing dipeptide inhibitor (LasBi) that blocked PrpL activity and restricted AP-1-driven cytokine induction and clinical symptoms in vivo. This study shows that the alkaline protease AprA degrades PrpLPP and functions redundantly with LasB to liberate mature, active PrpL. Our findings: 1) establish PrpL as a key virulence factor that triggers AP-1-mediated inflammatory signaling, 2) provide structural and functional insights into PrpL inhibition, and 3) identify AprA as a novel upstream PrpL activator. Together, these results highlight PrpL as a promising anti-virulence therapeutic target. Given the functional redundancy of inflammatory effectors produced by P. aeruginosa, strategies aimed at mitigating P. aeruginosa-induced lung inflammation through PrpL inhibition would likely need to be combined with approaches targeting additional pro-inflammatory bacterial factors. Author SummaryWe identify PrpL as a critical Pseudomonas aeruginosa protease that activates the inflammatory transcription factor AP-1 and drives potent lung inflammation. Structural analysis of a natural PrpL inhibitor guided development of an existing dipeptide inhibitor that significantly reduced the production of proinflammatory cytokines and clinical responses in vivo. Moreover, discovery of the AprA protease as an additional PrpL activator refines the activation model and suggests potential upstream therapeutic strategies. These findings highlight PrpL as both a driver of pathogenesis and a promising therapeutic target for treating P. aeruginosa infections.

microbiology↗

bioRxiv2026

Language Modeling Materializes a World Model of Protein Biology

Proteins are fundamental to life. The full extent of their biology is beyond our ability to characterize with experimental approaches in the physical laboratory. Accurate digital representations could accelerate the discovery of protein biology through virtual experiments. We propose language modeling to learn unified and general representations that can be scaled to all of protein biology. Building on these representations, we develop a structure prediction model that exceeds the performance of established methods for biomolecular complex prediction across benchmarks, including for the interactions of antibodies with their targets. A simple search procedure yields high experimental success rates for the discovery of proteins with nanomolar binding affinities for both miniproteins and single-chain antibodies, a modality critical for therapeutic design. Study of the concepts in the language models representation space reveals a systematic organization aligned with the reductionist understanding of proteins developed through empirical science. Leveraging this organization, we generate a comprehensive map of protein biology encompassing over 6.8 billion sequences and 1.1 billion predicted structures, identifying connections across known and unknown biology. As a whole, this shows language modeling as a powerful substrate for representing the biology of proteins, operating across scales from the prediction and design of protein interactions at the atomic level, to identifying properties of proteins at different levels of granularity and abstraction, to the scale of mapping connections between proteins across billions of years of evolution.

bioinformatics↗

bioRxiv2026

Immunodominance Hierarchy of Endogenous BBN963 Bladder Cancer Antigens Remains Stable Under Anti-PD1 and Anti-CTLA4 Immunotherapy

Immune checkpoint inhibition (ICI) is clinically active against multiple cancers, including urothelial cancer at the non-muscle invasive, muscle-invasive, and metastatic stages. Despite this, large numbers of patients experience disease progression and relapse after treatment with ICI-containing regimens. Tumor antigen-specific T cells are critical to ICI response, however few studies have evaluated the breadth and magnitude of tumor antigen-specific T cell responses with ICI therapy. In this study, we mapped the tumor antigen immunodominance hierarchy in the BBN963 model of murine basal-like bladder cancer for endogenous tumor neoantigens expressed physiologically. We used a high-throughput matrixed ELISpot assay to detect CD8+ T cell responses to predicted BBN963 tumor antigens derived from multiple mutational genomic sources. We found CD8+ T cell responses were directed against a subset of tumor antigens forming a stable and reproducible immunodominance hierarchy across individual mice. Treatment with anti-PD-1 or anti-CTLA-4 did not substantially reshape this hierarchy or broadly shift dominant responses to previously defined subdominant epitopes. Predicted peptide MHC binding stability and affinity was associated with antigen immunogenicity. Cancer-testis antigens, endogenous retroviral antigens, and SNV-derived tumor antigens that were immunogenic were found across tumor subclones. By diversifying the immunogenic antigen repertoire beyond SNVs, we achieved nearly 100% tumor subclone coverage, suggesting that broader antigen selection could help immunotherapy target more tumor subclones. In conclusion, this study supports the stability of the immunodominance hierarchy under ICI therapy and a role for broadening antigen discovery to multiple expressional sources in immunotherapy design.

cancer biology↗

bioRxiv2026

Dual curvature sensing governs cell orientation and curvotaxis

Cells lying in a curved environment can respond to the surface curvature by reorienting their shape. However, whether cells respond to the mean curvature and/or the Gaussian curvature remains largely unexplored. Here, inspired by experimental observations of how ovarian theca cells (TCs) orient themselves on substrates with different curvatures, we propose a theoretical framework for active nematic layers on curved surfaces. In this model, we assume that the nematic directors of the cells respond to both the mean curvature and the Gaussian curvature of the underlying substrate surface. Our theory predicts specific cell orientation patterns on hemicylindrical, hourglass- and dome-like substrates, consistent with experimental observations. In addition, by incorporating a curvotaxis traction, our model successfully recapitulates the experimental observation of TC accumulation at convex regions of hemicylindrical substrates as well as saddle-shaped regions of more complex geometries. Overall, our work reveals the unexpected role of cell curvature sensing in driving collective migration and pattern formation on various substrate curvatures. SIGNIFICANCESubstrate surface curvature is a critical environmental cue that can influence multicellular organization and functions. Yet how cells collectively align and migrate on complex curved surfaces remains unclear. Here, we proposed a hydrodynamic theory of active nematic layers over curved surfaces for contractile theca cells (TCs), where we assume that the nematic directors of cells can respond to both the mean curvature and the Gaussian curvature of the underlying substrates. Our theory predicts distinct cell orientation patterns on hemicylindrical, hourglass- and dome-like substrates, consistent with experimental observations. Furthermore, by introducing curvotaxis traction, our model recapitulates experimentally observed accumulation of TCs at the convex regions of hemicylindrical substrates as well as saddle-shaped regions of more complex geometries. Together, our study provides a simple theoretical framework to unify our understanding of curvature sensing across complex topology, providing insights into geometric control of tissue pattern formation.

biophysics↗

bioRxiv2026

Distinct virus-derived circular RNA molecule influences host response during SARS-CoV-2 infection

Virus-derived circular RNA molecules (VcircRNAs) are expressed by many RNA viruses during infection. Putative functions include modulating viral replication and interacting with the host immune response. Some function as non-coding RNA fragments that regulate gene expression through binding to complementary RNA sequences, whereas others contain internal ribosomal entry site (IRES) sequences or non-canonical modifications that allow them to be translated. Here, we confirm the expression of a distinct SARS-CoV-2 VcircRNA molecule, circ7b8N, that has not been previously identified. We found that circ7b8N is expressed and detectable in cell culture infections and in acute infections across SARS-CoV-2 variants and shows promise for detection in post-acute clinical samples. Conservation of circ7b8N junctions is limited to the nearest phylogenetic relatives within the betacoronavirus genus but are present in other human and bat-infecting coronaviruses. Host cell gene expression is modulated by the treatment with circ7b8N agnostic of viral infection. The discovery and subsequent confirmation of circ7b8N expressed by SARS-CoV-2 provides a new biomarker for infection, and its conservation across variants suggests functional importance. Author SummaryCircular RNAs are a well-documented class of molecules expressed by mammalian cells. However, circular RNA molecules expressed by RNA viruses remain largely uncharacterized regarding their generation, specific functions, and roles in host-pathogen interactions. Our computational predictions discovered thousands of distinct circular RNA molecules expressed by SARS-CoV-2. Among these, we confirmed the presence of circ7b8N, the most abundant SARS-CoV-2-derived circular RNA identified in our sequencing data. We found that circ7b8N localizes outside the nucleus and is detectable in clinical samples collected both during and after acute SARS-CoV-2 infection. Although overexpression of circ7b8N was not found to alter viral titers, it modulated the expression of host genes related to immune response activation and membrane remodeling. This suggests that circ7b8N may simultaneously provide pro- and anti-viral functions independent of influencing viral replication. Phylogenetic analyses of coronaviruses suggest that the expression of circ7b8N is a relatively recent evolutionary event, and it is conserved across SARS-CoV-2 variants from the first five years of the pandemic. The abundant presence of circ7b8N across variants in both sequencing data and clinical samples implies it plays a multifaceted role in SARS-CoV-2 pathogenesis.

microbiology↗

bioRxiv2026

De novo design of a safe and potent respiratory syncytial virus immuno-focusing antigen

Respiratory syncytial virus (RSV) remains the leading cause of severe respiratory infections in infants, the elderly, and the immunocompromised. Although stabilized full-length pre-fusion (pre-F) protein vaccines are promising, enhanced respiratory disease (ERD) remains a critical safety concern. Here, we used artificial intelligence to design a de novo immuno-focused antigen that structurally preserves the RSV F head region containing critical neutralising epitopes-- site O, II and V-while replacing the non-neutralising stem with a computationally designed scaffold to minimise immunopathological risk. The lead candidate, aRF6, elicited robust protective immunity against RSV in mice and similar immunogenicity in non-human primates without detectable toxicity. Importantly, in stringent ERD-promoting models, aRF6 induced minimal pulmonary pathology and markedly attenuated Th2-biased cytokine responses, outperforming formalin-inactivated RSV and full-length-stabilized pre-F. The results of cryoelectron microscopy confirmed that the aRF6 structure precisely matched the computational predictions. These results demonstrated that computationally designed de novo immuno-focused antigens can yield safe and effective RSV vaccines, thereby providing a rational framework for next-generation vaccine development.

microbiology↗

bioRxiv2026

Fructose utilization by GM-CSF-differentiated macrophages aggravates autoimmune inflammation via MG-derived AGE-RAGE signaling

Excessive fructose intake is increasingly associated with metabolic and inflammatory pathologies; however, the direct impact of fructose metabolism on immune cell function remains insufficiently understood. Here, we demonstrate that GM-CSF-differentiated macrophages markedly upregulate the fructose-specific transporter GLUT5, enabling efficient fructose utilization through two complementary metabolic pathways. Using 13C-fructose tracing, we identified distinct carbon fluxes via a hexokinase (HK)-dependent glycolytic route and a ketohexokinase (KHK)-ALDOB-mediated fructolytic route. The HK-dependent pathway sustains glycolytic activity under glucose-limiting conditions, stabilizing HIF-1 and preserving pro-inflammatory gene expression. Conversely, the KHK-ALDOB axis increases dihydroxyacetone phosphate (DHAP) production, leading to methylglyoxal-derived advanced glycation end-products (MG-AGEs) that engage receptor for AGE (RAGE) signaling. This activation enhances MMP9 expression in macrophages and drives Th17 differentiation in CD4 T cells, amplifying inflammatory and tissue-remodeling processes. In vivo, fructose intake exacerbates autoimmune arthritis in SKG mice, and elevated fructose-driven glycolysis and MG-AGE accumulation are observed in monocytes from patients with rheumatoid arthritis. These results link fructose-driven carbonyl stress to macrophage effector programs and downstream T cell polarization. Collectively, these findings uncover a dual fructose metabolic program that integrates nutrient stress with persistent inflammation via the MG-AGE-RAGE axis and underscore the immunometabolic risks of excessive fructose exposure.

immunology↗

bioRxiv2025

Design and synthesis of mirror image fluorescent nucleotide reversible terminator, (L)-3'-O-azidomethyl-dGTP-N3-fluorophore, and (D)-9°N mutant DNA polymerase for mirror image (L)-DNA sequencing by synthesis

Functional DNA molecules such as aptamers, catalytic DNAzymes, and dynamic nanostructures have many promising applications in diagnostics and therapeutics yet suffer from limited utility due to immunogenicity and unwanted interactions with other biomolecules, leading to nuclease degradation and unintended sequence driven binding to native sample DNA. Bio-orthogonal, (L)-form or mirror image DNA overcome these challenges yet suffers from the inability to sequence these molecules in a high-throughput manner, a necessary step in the rapid creation of functional (L)-DNA. Here, we report for the first time, design, synthesis, and functional demonstration of (L)-DNA sequencing by synthesis (SBS) using a fluorescent nucleotide reversible terminator, (L)-3'-O-azidomethyl-dGTP-N3-fluorophore paired with a (D)-9{degrees}N mutant DNA polymerase, both enantiomers (i.e., mirror image) of their natural biologically active forms. TABLE OF CONTENTS (GRAPHICAL ABSTRACT) O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/692211v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@160650forg.highwire.dtl.DTLVardef@18add51org.highwire.dtl.DTLVardef@1c80104org.highwire.dtl.DTLVardef@1bad99b_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Making invisible excited state protein structures visible by combining NMR and machine learning

NMR relaxation studies of the precursor form of the pro-inflammatory cytokine interleukin-18, pro-IL-18, show that it adopts two sparsely populated (<0.5%) and transiently formed (ms lifetimes) excited state conformations in exchange with a highly populated ground state conformer. Although NMR data localize regions undergoing exchange to a pair of short {beta}-strands that are preserved in at least one of the excited states, additional structural information is not forthcoming. Here we develop a protocol whereby the NMR data is used to select alternative conformers of pro-IL-18 from ensembles predicted by the generative ML model AlphaFlow that are then evaluated through further NMR experiments. The approach identifies distinct excited state conformers and suggests a general method for combining experiment with computation to characterize protein energy landscapes.

biophysics↗

bioRxiv2025

Targeted degradation of pathologic tau aggregates via AUTOTAC ameliorates tauopathy

The pathogenesis of tauopathies including Alzheimers disease (AD) and progressive supranuclear palsy (PSP) involves the misfolding and aggregation of tau. Here, we employed AUTOTAC to induce the lysosomal degradation of intraneuronal tau aggregates. ATB2005A is a 734-Da chimera that simultaneously binds {beta}-sheet-rich tau aggregates and the autophagic receptor p62/SQSTM1, leading to autophagosomal sequestration and lysosomal co-degradation. In mouse models of tauopathies, orally administered ATB2005A lowered intraneuronal tau aggregates and exerted the therapeutic efficacy in neuroinflammation as well as cognition, behavior, and muscle movements. A Phase 2 clinical trial (U34401-4/2023/14) with companion dogs carrying canine cognitive dysfunction (CCD) demonstrated the efficacy of ATB2005A, as a veterinary medicine, to reverse the disease progression. ATB2005A is under Phase 1 clinical trial with human participants in Korea (202300697). These results validate AUTOTAC as a versatile platform for developing therapeutics to eradicate toxic protein aggregates in a wide range of proteinopathies.

neuroscience↗

bioRxiv2025

Multiscale 3D whole joint cellular and molecular mapping dissects the relationship between structure and pain

Understanding musculoskeletal joints from a 3D multiscale perspective, from molecular to anatomical levels, is essential for resolving the confounding relationships between structure and pain, elucidating the intricate mechanisms regulating joint health and diseases, and developing new treatment strategies. Here, we introduce a musculoskeletal joint immunostaining and clearing (MUSIC) method specifically designed to overcome key challenges of immunostaining and optical clearing of intact joints. Coupled with large-field light sheet microscopy, our approach enables 3D high-resolution, microscale neurovascular mapping within the context of whole-joint anatomy without the need for image coregistration across various joints, including temporomandibular joints, knees, and spines, and multiple species, including mouse, rat, and pig. Our findings reveal 3D heterogeneous distributions of neurovascular networks and previously uncharacterized neurovascular pathways within joints. Using the proteoglycan 4 knockout (Prg4-/-) mouse model of joint degeneration, we identified significant alterations in joint-wide neurovascular architecture, highlighting neurovascular changes along degenerative processes. Furthermore, in a traumatic joint injury mouse model, we observed long-lasting pain behavior and a time-course 3D neurovascular remodeling preceding detectable joint morphological change, bridging microscale alterations with potential pain mechanisms. This platform offers a powerful tool for multiscale 3D analysis, enabling new insights into joint pathophysiology and intricate interplay among joint tissues.

bioengineering↗

bioRxiv2025

Design of peptides with non-canonical amino acids using flow matching

The canonical vocabulary of twenty amino acids limits the chemical space available to proteins and peptides. Expanding this vocabulary to hundreds of non-canonical amino acids allows the engineering of proteins with novel function and activity, and is of great interest for the discovery of novel drugs such as macrocyclic peptides. Here we present NCFlow, a flow-based generative model capable of incorporating any arbitrary non-canonical amino acid into a given protein. To supplement sparse training data in the Protein Data Bank, NCFlow is pretrained on millions of small molecule structures and a large set of protein-ligand complexes before finetuning on native non-canonicals found within proteins in the Protein Data Bank. We show that NCFlow outperforms AlphaFold3-based methods in the structure prediction of unseen non-canonical amino acids. We present a peptide design pipeline akin to in silico deep mutational scanning, and propose a novel scoring strategy using a combination of deep learning-based and molecular dynamics-based alchemical binding free energy calculations to identify improved peptide variants. We apply the method on four protein-peptide complex test cases, and observe that incorporating non-canonicals can significantly improve binding affinity by up to -7.0 kcal/mol. Thus, NCFlow can be easily integrated into existing protein design platforms to further improve its properties outside of what is capable with standard amino acids.

bioinformatics↗

bioRxiv2025

An updated resource of 180K soybean SNP genotyping array based on the T2T reference genome

Single nucleotide polymorphism (SNP) genotyping has revolutionized crop improvement by enabling high-resolution genomic analyses and accelerating breeding programs. In soybean (Glycine max (L.) Merr.), a globally important legume crop, existing genotyping data for 180,961 SNP markers from the Korean soybean core collection were generated using the outdated Williams 82 reference genome version 1 (Wm82.v1), which contains numerous assembly gaps and misassemblies that limit genomic resolution. While high-quality reference genomes including Wm82.v4 and Wm82.v6 (telomere-to-telomere assembly) are now available, the valuable existing SNP array data have not been integrated with these improved genomic resources. Here we show successful remapping of the 180K SNP array data to both Wm82.v4 and Wm82.v6 reference genomes through sequence-based alignment of flanking regions. We extracted flanking sequences from SNP marker positions in Wm82.v1 and mapped them to the newer reference versions based on sequence similarity, excluding markers with mapping failures, allele mismatches, low-identity alignments, or multiple mappings, which resulted in successful mapping of 175,202 and 175,763 markers to Wm82.v4 and Wm82.v6, respectively. We also remapped genotype data from 927 soybean accessions (497 USDA-GRIN accessions and 430 Korean core collection accessions) to both reference versions. This updated SNP dataset provides the soybean research community with a comprehensive genomic resource that leverages both existing genotyping investments and state-of-the-art reference genome assemblies for enhanced crop improvement and genomic studies.

genomics↗

bioRxiv2025

Exploring Cellular Water Dynamics associated with Potassium Ion Changes Using Magnetic Resonance Imaging

Potassium ions play a critical role in modulating cellular physiology, but their direct effects on water dynamics have not been fully explored. Here, we investigated how elevated potassium ion concentrations ([K]) alter intracellular and extracellular water pools in comparison to hypoosmotic stress, using T2 and magnetization transfer (MT) parameters in a close-packed T-lymphocyte cell pellet model. Our findings reveal that the T2 increase primarily reflects an increase in intracellular free water concentration rather than a mere expansion of cell volume. Notably, [K] elevation produced distinct cell swelling profiles and a smaller relative rise in free water at comparable volumetric changes compared to hypoosmotic stress, highlighting more complex mechanisms than straightforward osmotic effects. While T2 proved sensitive to shifts in intracellular water content, the bound pool increased linearly with cell volume expansion. These results underscore that [K]-driven cell swelling diverges functionally from osmotic- driven cell swelling and demonstrate the viability of MRI-based approaches for probing K-dependent cellular events.

biophysics↗

bioRxiv2025

Proton motive force as a driver of persister sensitization by adenosine

Antibiotic tolerance and persistence contribute to the emergence of antimicrobial resistance, yet strategies to reverse these phenotypes remain limited. Our previous work revealed that the naturally occurring nucleoside adenosine can reverse antibiotic tolerance in diverse bacterial strains by modulating cellular energetics. Here, we define the mechanism underlying this potentiation, identifying adenosine metabolism as a driver of cytoplasmic alkalinization and proton motive force (PMF) generation. Using RNA sequencing, metabolite assays, and pH-sensitive fluorescent reporters, we show that adenosine is catabolized by purine nucleoside phosphorylase (deoD) to yield ribose-1-phosphate, which enters the pentose phosphate pathway. This metabolic flux stimulates the electron transport chain, leading to proton translocation, increased cytoplasmic pH, and enhanced PMF. Disruption of key metabolic enzymes (deoD, deoB, tktAB) or inhibition of enolase abolishes both alkalinization and antibiotic sensitization. Using a respiratory-deficient mutant, we demonstrate that aerobic respiration is the primary driver of alkalinization and gentamicin potentiation, though adenosine can partially increase membrane potential independently of oxidative phosphorylation. These findings support a model in which adenosine metabolism promotes aminoglycoside uptake via PMF-driven transport, sensitizing tolerant bacteria to killing. Our work implicates the ribose moiety of adenosine as a key metabolic lever for reversing tolerance. Broader exploration of nucleoside-based adjuvants across bacterial species and antibiotic classes may reveal generalizable strategies to enhance antibiotic efficacy against recalcitrant infections.

microbiology↗

bioRxiv2025

Regulation of Epithelial HIF by Probiotic Escherichia coli

The gastrointestinal tract is home to trillions of microorganisms that interact with their host in profound ways, including regulation of immune, endocrine, and neurological functions. One mechanism by which these microbes interact with their eukaryotic host is through the generation of short-chain fatty acids (SCFAs), which are metabolized by the intestinal epithelium creating a state of "physiologic hypoxia". This hypoxia, in turn, results in stabilization and activation of hypoxia-inducible factor (HIF), a transcription factor family shown to support gut barrier function and homeostasis, in the intestinal epithelium. The association between HIF and intestinal homeostasis has been long understood, as both genetic and pharmacologic potentiation of the HIF signaling pathway has been shown to promote barrier function both in vitro and in vivo. Although it has been previously established that pathogenic bacteria regulate HIF stabilization and activity in the intestinal epithelium independent of SCFA metabolism, it is not clear whether this property extends to noninfectious and/or commensal bacterial species. Here, we demonstrate that nonpathogenic, commensal strains of Escherichia coli stabilize HIF in intestinal epithelial cells in vitro. Further, we show that HIF is transcriptionally active in these cells and drives a "pro-barrier" transcriptional program. This property was found to be dependent on bacterial aerobic respiration, as genetic elimination of E. coli aerobic respiration abolished HIF stabilization and the subsequent transcriptional phenotype. Finally, we observed induction of tissue hypoxia in vivo using antibiotic-treated mice colonized with wild-type, but not respiration-deficient, E. coli. These findings demonstrate a novel ability for probiotic E. coli to regulate intestinal homeostasis through activation of HIF and suggest that this mechanism might be leveraged in as a novel therapeutic to combat intestinal inflammation, such as that observed during inflammatory bowel disease (IBD).

cell biology↗

bioRxiv2025

CyclicBoltz1, fast and accurately predicting structures of cyclic peptides and complexes containing non-canonical amino acids using AlphaFold 3 Framework

Cyclic peptides exhibit favourable properties making them promising candidates as therapeutics. While the design and modeling of peptides in general has seen rapid advances since the advent of modern machine learning methods, existing deep learning models cannot effectively predict cyclic peptide structures containing non-canonical amino acids (ncAAs), which are often crucial for peptide therapeutics. To address this limitation, we here extend the recent AF3-style model Boltz to cyclic peptides with ncAAs. In addition to the positional encoding offset, we used a simple yet effective extension of the cyclic offset encoding based on AlphaFold3s tokenization scheme that allows the modeling of cyclic peptides with modified residues. On a test set of peptides with ncAAs, our approach outperforms HighFold2 on 13/17 cases, with an average C RMSD of 1.877[A] and an average all-atom RMSD of 3.361[A]. Our results show that the cyclic offset encoding shown for AlphaFold2 generalizes to AlphaFold3-based models and can be extended to incorporate ncAAs, showing potential in the design of novel cyclic peptides with ncAAs for therapeutic applications.

bioinformatics↗

bioRxiv2024

Multimodal Spatial Profiling Reveals Immune Suppression and Microenvironment Remodeling in Fallopian Tube Precursors to High-Grade Serous Ovarian Carcinoma

High-Grade Serous Ovarian Cancer (HGSOC) originates from fallopian tube (FT) precursors. However, the molecular changes that occur as precancerous lesions progress to HGSOC are not well understood. To address this, we integrated high-plex imaging and spatial transcriptomics to analyze human tissue samples at different stages of HGSOC development, including p53 signatures, serous tubal intraepithelial carcinomas (STIC), and invasive HGSOC. Our findings reveal immune modulating mechanisms within precursor epithelium, characterized by chromosomal instability, persistent interferon (IFN) signaling, and dysregulated innate and adaptive immunity. FT precursors display elevated expression of MHC-class I, including HLA-E, and IFN-stimulated genes, typically linked to later-stage tumorigenesis. These molecular alterations coincide with progressive shifts in the tumor microenvironment, transitioning from immune surveillance in early STICs to immune suppression in advanced STICs and cancer. These insights identify potential biomarkers and therapeutic targets for HGSOC interception and clarify the molecular transitions from precancer to cancer. STATEMENT OF SIGNIFICANCEThis study maps the immune response in fallopian tube precursors of high-grade serous ovarian cancer, highlighting localized interferon signaling, CIN, and competing immune surveillance and suppression along the progression axis. It provides an explorable public spatial profiling atlas for investigating precancer mechanisms, biomarkers, and early detection and interception strategies.

cancer biology↗