Cell Discovery

Vaccination remains the most successful preventative measure against viral infection, but methods to stably deter rapidly-evolving pathogens have remained elusive. Vaccines capable of incorporating and anticipating viral evolution could address current challenges in seasonal vaccination efforts against SARS-CoV-2 and influenza where economic and disease burdens remain high despite decades of combined study. Rare epitope suppression (RES) is an underutilized concept within vaccine design, where humoral epitope targeting can be molded using complex antigen pools. Based in mRNA vaccine technology, 'wobble vaccines' represent the novel application of RES to human pathogens designed to anticipate and resist viral evolution. To establish this platform, public SARS-CoV-2 sequencing data was compiled from the first two years of the COVID-19 pandemic to identify high-diversity sites across the receptor binding domain (RBD) of the spike protein. Wobble RBD (WobbRBD) libraries reflecting that entropy were synthesized and incorporated into established self-amplifying (SA) vaccine constructs. Animals immunized with these complex antigen pools showed no obvious adverse effects. By three days-post vaccination, WobbRBD stimulated robust primary immune activation with distinctive characteristics compared to traditional single-strain vaccine modalities. By day 14, germinal centers, class switching, and antibody-secreting cells were induced, creating potent SARS-CoV-2 spike-binding IgG antibodies. Despite similar overall activation profiles, WobbRBD generated significantly increased breadth against SARS-CoV-2 variant spikes in comparison to single-strain controls -- even against future-emerging strains. Taken together, wobble vaccines represent a novel method for anticipating and preventing viral escape with promising applications in SARS-CoV-2, influenza, HIV, and beyond.

We developed an AI-guided design pipeline that generated and validated non-natural microbial rhodopsins with spectral properties not yet known in nature. The pipeline comprised a three-stage in silico design, a genetic algorithm (GA) for sequence generation, a stacked LASSO and XGBoost machine-learning (ML) regressor for spectral prediction and fitness ranking, and a Markov-based sequence plausibility filter to enforce proton pumping like characteristics. Four candidate rhodopsins (APR1, APR2, APR6, and APR7) targeting blue light absorption were designed and AlphaFold3 structural modelling predicted retinal binding pocket architecture consistent with outward proton-pumping function. Experimental characterisation confirmed that all four variants absorbed light at [~]410 nm and significantly promoted the growth of Cupriavidus necator under blue light illumination. This study demonstrates that AI-enabled design can engineer proteins with no natural precedent, generating light-harvesting rhodopsins with novel spectral properties while preserving biological function, marking a significant advance in programmable synthetic biology.

Glycosylation is a fundamental process regulating cellular function, tissue organization, and disease progression. However, comprehensive glycan profiling at single-cell spatial resolution remains largely inaccessible, particularly in clinical archival tissues. Here we develop spatial-GPT, a multimodal platform for simultaneous profiling of glycans, proteins, and/or transcripts in archival formalin-fixed paraffin-embedded (FFPE) tissues. Using a panel of 30 DNA-encoded lectins recognizing major mammalian glycan motifs and structural classes, sequencing-based spatial-GPT (DBiT-GPT) mapped the spatial glycome, proteome, and transcriptome across 16 human liver specimens encompassing steatosis, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC), leading to identification of spatial glyco-codes - combinatorial glycan states associated with distinct cellular identities, tissue features, and pathological processes. Unexpectedly, glyco-codes alone were sufficient to resolve major cell types, disease states, and HCC subtypes, revealing a previously unappreciated level of biological information encoded within the tissue glycome. Spatial glycomics uncovered tumor-like glyco-codes in premalignant regions, suggesting that glycan reprogramming may precede overt malignant transformation. Using imaging-based single-cell spatial glycan-protein profiling (CODEX-GP), we track glyco-codes across the whole-tissue architecture of 3 representative HCC samples. We further examined the glyco-codes across more than 300 patient specimens and quantified cell-type- and disease-specific glyco-codes as well as glycan-defined immune-evasion, T-cell-exhaustion, and steato-fibrotic niches. Together, these findings establish spatial glyco-codes as a previously unrecognized layer of tissue organization that encodes cellular identity, tissue function, and disease progression. The ability of glyco-codes to distinguish major liver pathologies across independent patient cohorts further highlights their potential as a new class of molecular histopathology biomarkers.

Current SARS-CoV-2 vaccines provide limited breadth of protection, underscoring the need for vaccine strategies that optimize immune responses. Virosomesoffer a modular vaccine platform that enables multivalent antigen display and incorporation of adjuvants which can steer immune responses. We evaluated the immune response in BALB/c mice with virosomes displaying SARS-CoV-2 Wuhan or Delta spike antigens and coupled with various distinct adjuvants. Adjuvant selection differentially influenced both humoral and cellular immune outcomes. The TLR7/8 agonist 3M -052 induced a strong Th1-biased response, characterized by elevated IgG2a/IgG1 ratios and robust type 1 cytokine induction with suppression of Th2-associated cytokines. In contrast, the saponin QS-21 enhanced antibody functional quality, illustrated by improved virus neutralization potency and breadth. Furthermore, the combined incorporation of both 3M-052 and QS-21 induced an elevated Th1-biased response without improving neutralization capacity. In conclusion, different adjuvants added onto our virosome-basedvaccine led to distinct antibody responses and splenic T-cell profiles, reflective of differences in immune programming. This information guides the selection of adjuvants for respiratory virus vaccines.

Prime editing enables the precise modification of genomes, thereby holding great potential for the treatment of genetic diseases. Despite substantial advancements in prime editing technology and the initiation of the first clinical trial for treating chronic granulomatous disease, further enhancement of editing efficiency across edit types is still urgently needed. Here, we developed a compact prime editor, PE2{Delta}R, by deleting the RNase H domain of the MMLV reverse transcriptase (MMLV-RT). We then conducted a saturated mutagenesis screen targeting two DNA interacting regions within the PE2{Delta}R-RT Fingers domain. By integrating three highly effective mutations (I61R, V101R, S67W) into PEmax lacking RNase H domain (termed PEmax{Delta}RM3), we achieved up to a 90% increase in editing efficiency across editing types compared to PEmax. Structural modelling using AlphaFold 3 suggests that these mutations enhance primer-template stabilization and guide the RNA/DNA hybrid into a catalytically favourable trajectory, providing a mechanistic explanation for the enhanced activity. Taken together, our study demonstrates proof-of-concept for the application of unbiased mutagenesis screen to identify novel mutations that enhance prime editor performance. Furthermore, we discovered that RT variants (I61R, V101R, S67W) synergize with PEmax and epegRNA to improve prime editing efficiency across edit types, with the strongest improvement observed in introducing small deletions.

Vaccination is one of the most effective public health interventions. However, vaccine efficacy varies widely among individuals, as immunity arises from complex interplay between genetic, pathogen, and immunological factors. To date, most systems vaccinology studies have remained pathogen-specific, precluding the discovery of potential shared immune architectures underlying durable antibody responses. To address this gap, we leveraged transcriptomic data from 1,032 participants receiving influenza, hepatitis B, or yellow fever vaccines to develop an interpretable machine learning framework for comparative analysis across diverse vaccine platforms. Pathogen-specific models using Blood Transcriptional Module-based feature aggregation accurately predicted high antibody responders and consistently outperformed gene-level models. Distinct predictive immune architectures identified across vaccines were further resolved for dominant hierarchical immune programs using surrogate decision trees. This approach identified the dominant decision boundaries underlying each vaccine model, highlighting leukocyte migration and Th2 differentiation in Hepatitis B, CD4+ T cells, M2 macrophages, and c-MYC signaling in Influenza, and B-cell receptor signaling with B-cell developmental pathways in Yellow Fever. Cross-pathogen concordance analyses further identified four shared transcriptional modules, suggesting partially conserved immune architectures across diverse vaccines. Together, these findings provide new insights into the immune mechanistic underpinnings of durable vaccine responses across vaccines and provide an interpretable framework for comparative systems vaccinology that may guide the rational design of next-generation vaccines. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/737303v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1b5be56org.highwire.dtl.DTLVardef@e323dborg.highwire.dtl.DTLVardef@470eb4org.highwire.dtl.DTLVardef@116759f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Personalized neoantigen vaccines are an emerging strategy for cancer immunotherapy, but their effectiveness depends on selecting tumor-specific antigens capable of inducing functional T-cell responses. The VACINUS AI-informed neoantigen prioritization framework previously identified and peptide-validated three immunogenic Tier 1 neoantigens in the B16F10 melanoma model. In this study, we extended that framework by translating these validated neoantigens into a multi-epitope messenger RNA vaccine formulated with lipid nanoparticles and evaluating its preclinical immunogenicity and antitumor activity. The three VACINUS-prioritized B16F10 neoantigens were encoded within a single multi-epitope construct, BF-V1_27-Ser, and formulated to generate BF-RNA-P. In B16F10 tumor-bearing mice, BF-RNA-P induced neoantigen-specific CD8+T-cell responses, with the strongest response directed against the B16F10-1-4 epitope. Combination with anti-PD-1 further enhanced vaccine-induced CD44+IFN-{gamma}+ CD8+ T-cell activation, whereas anti-PD-1 alone did not induce detectable peptide-specific responses. BF-RNA-P also suppressed tumor growth in vivo, and combination treatment produced the strongest antitumor effect, reflected by reduced tumor volume and lower endpoint tumor burden. Together, these findings demonstrate that VACINUS-prioritized and peptide-validated neoantigens can be reformatted into a multi-epitope messenger RNA/lipid nanoparticle vaccine while retaining antigen-specific immunogenicity and antitumor activity. This study provides preclinical proof-of-concept for integrating AI-informed, TCR-aware neoantigen prioritization with messenger RNA/lipid nanoparticle delivery as a translational strategy for personalized cancer vaccine development.

Discovering small molecules targeting proteins represents a major effort in drug development. RNA, however, as a class of macromolecule that carrying out important regulatory roles in the cell as drug target, only received attention recently. Although several methods have been proposed, an easy to operate, fast and robust method is still lacking. We designed a generic florescence screening method by fusing the target RNA with a florescent aptamer (fusion RNA) and then carried out screening using high-throughput format (Fluorescent Aptamer Screening, FAS). In this work, we chose SL5 on SARS-Cov-2 5’UTR as the test target. SL5 is a conserved motif across several corona virus family members whose core is not prone to mutation. We screened 9528 compounds, successfully identified four molecules (Sertraline (hydrochloride), Samuraciclib (hydrochloride), Minocycline (hydrochloride), JG-98 bind direct to the full-length SL5 at micromolar or higher affinity. The design of FAS could be easily adapted to structured RNA motifs without prior knowledge of its 3D structural information. In addition, this work showed the possibility of developing generic drugs for RNA virus by targeting the conserved viral RNA genome and paved a new way for the discovery of small molecule drugs in combating human diseases.

The human gut, containing 100 trillion microbes, is also considered the "second brain," having control over the different functions of the physiological system. With advancements in bioinformatics and the development of sequencing technologies, researchers are able to explore the diversity and functional implications of gut microbiota (GM), which have become strongly associated with a variety of diseases. Microbial imbalance, or dysbiosis, acts as a biomarker for early detection and prognosis of a disease. Artificial Intelligence and Machine Learning (AI/ML) methods, although extensively used in predicting GM associated diseases, are seldom translated to having practical real-world outcomes, necessitating the design of robust AI/ML models applicable in real-world scenario. We have therefore come up with designing stacking-based ensemble architectures (EM1 and EM2), developed by integrating multiple ML-based learning algorithms for improving disease prediction accuracy. The GM datasets, after split into training and test sets, were eventually fed into the proposed two-layer ensemble models, which combines the output from standardized base learners via a meta-classifier, strengthening classification robustness as well as ensuring consistency in optimized performance across diverse datasets. Both the proposed hybrid ensemble models have emerged to be superior performers over all baseline and deep learning models, with an average accuracy of 0.87 and 0.84 respectively. By combining multiple learners, the proposed ensemble models outperform traditional single-algorithm-based approaches to attain higher accuracy and robustness on complex GM datasets. Key messagesO_LIDevelopment of stacking-based hybrid ensemble models (EM), which can be employed to integrate different AI/ML algorithms with better prediction accuracy of gut microbiome (GM)-associated diseases. C_LIO_LIUse of independent GM datasets with preprocessing methods such as SMOTE and PCA to address class imbalance and high dimensionality. C_LIO_LIAll the proposed EM architectures are mostly superior to the existing state-of-the-art AI/ML methods (highest prediction accuracy: 0.87 and 0.84 with EM1 and EM2 models respectively) for GM diseases predictions. C_LIO_LIThe cross-cohort validation demonstrates high prediction accuracy and robustness, (AUC values close to 0.98 and 0.99, for EM1 and EM2). C_LIO_LIThese therefore demonstrate the effectiveness of EM frameworks for GM associated disease prediction, paving the way for corresponding applications in precision medicine. C_LI

Enterovirus D68 (EV-D68) is a non-polio picornavirus that has caused increasing rates of severe respiratory illness and acute flaccid myelitis in children worldwide this century. There are no approved vaccines or antivirals for EV-D68. Thus, we conducted a crystallographic fragment screening (CFS) and a high-throughput screening (HTS) biochemical assay against the EV-D68 RNA-dependent RNA polymerase 3D (3Dpol) to identify ligandable sites and non-nucleoside compounds that can spearhead anti-enteroviral drug discovery. The CFS, involving 650 fragments, identified 68 hit compounds (~10% hit rate) distributed across 3Dpol, including the functionally relevant sites RNA template channel, Active site, and RNA primer channel, and the previously unknown "Thumb site II" and "Index-middle finger pocket". Inhibition assays confirmed that compounds binding to each site can inhibit EV-D68 3Dpol activity. The HTS, a fluorescence-based PicoGreen biochemical assay, permitted screening 50,000 compounds of the ChemBridge Premium Library (0.77% hit rate). After a second-round dose-response screening, we identified 5-aminoindazole as a promising scaffold that inhibits EV-D68 3Dpol, including hit-to-lead compound 727590, which displayed an IC50 value of 25 M and preliminary structure-activity relationships. These hits offer amenable starting points for discovery and development of non-nucleoside inhibitors and provide opportunities for structure-based drug design against enteroviruses. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/737532v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@14a54a6org.highwire.dtl.DTLVardef@fb6621org.highwire.dtl.DTLVardef@ee2e2aorg.highwire.dtl.DTLVardef@118f91d_HPS_FORMAT_FIGEXP M_FIG Created with biorender.com and PyMOL Molecular Graphics System, version 2.5.0. Schrodinger, LLC. C_FIG

Filovirus outbreaks caused by Ebola virus (EBOV) and Marburg virus (MARV), pose severe global health threats characterized by high rates of fatal hemorrhagic fever. While species-specific vaccines and therapeutic monoclonal antibodies are approved for Zaire ebolavirus, broadly-active therapeutics remain unavailable, leaving populations vulnerable to MARV and other pathogenic Ebola species, such as Bundibugyo (BDBV) and Sudan (SUDV) ebolaviruses. Here we report a computationally guided, infectious virus validated screening platform for the rapid discovery of broad-spectrum filovirus antivirals. By leveraging quantitative structure-activity relationship (QSAR) models, we screened 142,382 compounds in silico to prioritize 125 high-potential candidates. Subsequent dose-response and viability profiling identified 23 compounds exhibiting potent, low-micromolar pan-filovirus activity and favorable cytotoxicity profiles. Molecular docking indicates these compounds target conserved structural and functional domains--primarily the VP35 and L proteins--which may disrupt essential viral replication and immune antagonism. Furthermore, systematic combinatorial screening revealed three highly synergistic compound pairs, notably NCGC00113249-01 and NCGC00118008-01, demonstrating robust cross-species efficacy. By targeting conserved vulnerabilities across the filovirus family, this integrated in silico and in vitro pipeline provides a scalable framework to rapidly nominate and optimize synergistic therapeutic regimens against both endemic and emerging viral threats including BDBV. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/737586v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1251baorg.highwire.dtl.DTLVardef@b3a2feorg.highwire.dtl.DTLVardef@191d314org.highwire.dtl.DTLVardef@b8f710_HPS_FORMAT_FIGEXP M_FIG C_FIG

IgG-degrading enzymes have emerged as innovative therapeutic agents for treating conditions driven by pathogenic antibodies. Here, we used structure-guided rational design to engineer IdeSM33, a double mutant (K167R/D226E) of the IgG-specific bacterial protease IdeS from Streptococcus pyogenes, with improved catalytic efficiency. Biolayer interferometry revealed a fourfold increase in binding affinity relative to wild-type IdeS (IdeSWT). This enhancement is likely attributable to mutations that strengthen hydrogen bonding at the enzyme-IgG Fc interface. In vitro, IdeSM33 has higher performance than IdeSWT in cleaving serum IgG. In vivo studies in rabbits demonstrated that IdeSM33 effectively depleted circulating IgG and showed better performance at a dose of 0.005 mg/kg than the IdeSWT. Although doses greater than 0.2 mg/kg demonstrated higher plasma concentrations of IdeS and a larger AUC 0 to last, they did not show a significant enhancement in the pharmacodynamics of IgG degradation. Importantly, a single dose of IdeSM33 (0.2 mg/kg) potently degraded binding and neutralizing antibodies against AAV9 within 1-2 days and restored hepatic AAV9 transduction in pre-immunized animals. Together, these findings highlight IdeSM33 as a potent and safe engineered enzyme with therapeutic potential for autoimmune disorders, transplant rejection, and overcoming pre-existing humoral immunity in gene therapy.

Objectives; The role of nuclear receptor subfamily 4, group A, member 3 (NR4A3) in hepatic steatosis, inflammation, and insulin resistance (IR) within the context of metabolic dysfunction-associated steatotic liver disease (MASLD) remains largely underexplored. Consequently, this study aimed to examine NR4A3's impact on MASLD and the potential underlying mechanisms. Methods; We aimed to elucidate the functional role of NR4A3 in MASLD through its knockdown in cell culture and animal models. To establish the cell culture model of MASLD, LO2 cells were treated with free fatty acids (FFAs), while male C57BL/6 mice were fed a high-fat diet (HFD) to create the animal model. NR4A3 knockdown was achieved using specific short hairpin RNA (NR4A3-shRNA) in the mice model and three small interfering RNAs (NR4A3-siRNAs) in the cell culture model. The lipids content, fatty acid synthesis, inflammatory factors, and IR were then assessed with and without NR4A3 knockdown. Furthermore, the underlying mechanism through which NR4A3 exerts its influence was explored by analyzing the interaction between NR4A3 and activating transcription factor 3 (ATF3). Results: In the cell culture experiments, the knockdown of NR4A3 significantly decreased the lipids content, fatty acid synthesis, and inflammatory factors in the LO2 cells treated with FFAs in the NR4A3-shRNA group compared with those in the NC-shRNA control group. In the animal model experiments, NR4A3 knockdown in the HFD male C57BL/6 mice significantly ameliorated HFD-induced hepatic steatosis, inflammation, and IR. Mechanistically, the knockdown of NR4A3 downregulated the expression and transcriptional activity of ATF3, resulting in an impaired ATF3 function. ATF3 overexpression significantly reversed lipid accumulation decline and reduced inflammation after NR4A3 knockdown. Conclusion: The downregulation of NR4A3 alleviates MASLD by modulating ATF3, suggesting this may be a promising therapeutic target.

Controlling protein glycosylation as a critical quality attribute of biopharmaceuticals remains challenging when glycosylation is coupled to cellular production systems. Here, we present a proof-of-concept glycosyltransferase immobilised enzyme reactor (IMER) housed within a 3D-printed column that enables directed post-production glycan modification of purified glycoproteins. Using {beta}-1,4-galactosyltransferase ({beta}4GalT1-IMER) and -2,6-sialyltransferase (ST6Gal1-IMER) immobilised on Ni-NTA resin, the IMER achieved near-complete galactosylation and substantial sialylation of partially deglycosylated bovine fetuin N-glycans with their respective substrates with a maximum substrate-enzyme contact time of four minutes. Isomeric-level analysis revealed arm-specific addition preferences for both enzymes, consistent with known specificities. The modular IMER design permits sequential connection of individual enzyme chambers, potentially offering a scalable, plug-and-play platform for constructing defined glycan structures on recombinant glycoprotein therapeutics.

Dietary methionine restriction has been shown to improve metabolic health and treat multiple diseases. Methionine metabolism regulates transmethylation reactions, including N6-methyladenosine (m6A) RNA methylation, by modulating the availability of S-adenosyl methionine (SAM). Both m6A RNA methylation and methionine metabolism are involved in the regulation of the circadian clock. However, it remains unclear whether dietary methionine influences circadian rhythms through the regulation of m6A RNA modification. In this study, we investigated the effects of short-term methionine deprivation on the diurnal oscillations of m6A RNA methylation in the mouse liver. We found that a methionine-deficient (MD) diet reprogrammed the cyclic expression patterns of m6A writers, erasers, and readers. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) revealed that the MD diet induced de novo diurnal m6A oscillations in genes associated with RNA processing, protein translation, protein ubiquitination, and mTORC1 signaling pathways. RNA-seq and quantitative proteomics analyses demonstrated that MD-induced changes in m6A RNA levels were linked to alterations in mRNA and protein abundance. We observed that dynamic m6A RNA methylation of the transcripts encoding two key enzymes, MAT2A and CBS, helps maintain methionine homeostasis in response to methionine starvation. These findings identify m6A RNA methylation as a key mechanism linking methionine metabolism to circadian regulation.

Although glycosylated small non-coding RNAs are emerging players in cancer, their functions in lung adenocarcinoma (LUAD) are largely unknown. We identify SNORA73B as a glycosylated small nucleolar RNA (glycol-snoRNA) that carries sialic acid-capped O-glycans in both normal lung epithelial and LUAD cells. SNORA73B is markedly elevated in LUAD, and its plasma levels distinguish early-stage LUAD from healthy controls with an area under the curve (AUC) of 0.7903. Subcellular fractionation reveals predominant nuclear localization. Functional assays demonstrate that SNORA73B depletion curbs LUAD cell proliferation, migration, and invasion, whereas its overexpression fosters these malignant phenotypes and accelerates tumor growth. Mechanistically, SNORA73B directly binds the T-cell-restricted intracellular antigen-related protein (TIAR), thereby enhancing TIAR protein abundance without affecting its mRNA levels. TIAR then recognizes the 3-untranslated region (3-UTR) of MYC mRNA to upregulate c-Myc, which subsequently augments AKT phosphorylation. Importantly, c-Myc knockdown largely rescues the oncogenic phenotypes and tumorigenesis induced by SNORA73B overexpression. Collectively, our data unveil a glycoRNA-dependent oncogenic axis SNORA73B-TIAR-c-Myc-AKT that drives LUAD progression. These findings position SNORA73B as a promising early diagnostic biomarker and a candidate therapeutic target in LUAD.

Mechanosensitive channels of large conductance (MscL) are essential bacterial safety valves that prevent osmotic lysis by releasing solutes in response to membrane tension. Despite extensive functional studies on Escherichia coli MscL (EcMscL), its high-resolution structure remained unknown. Using cryo-electron microscopy, we present an experimental structure of EcMscL reconstituted in nanodiscs at 3.1 [A] resolution. The structure reveals a pentameric assembly with a narrow hydrophobic gate at the cytosolic side and a periplasmic cavity, consistent with the canonical MscL-fold. Differences to earlier published crystal structures of MscL from other organisms are in the less conserved periplasmic loop. We observe a previously unreported dimeric association of EcMscL pentamers, mediated by residues 61-63 in the periplasmic loop. This dimeric interface is located at the periplasmic side and provides a structural basis for the formation of higher-order clusters. The observed arrangement enables a fluid-like, mosaic packing of channels with center-to-center distances of 5.9-9 nm, consistent with biophysical and imaging data. These findings provide a structural framework for understanding cluster organization of EcMscL that modulates its activity in cellular stress response.

Type 1 diabetes (T1D) involves immune-mediated destruction of pancreatic {beta}-cells, yet current disease-modifying therapies mainly target immunity without enhancing {beta}-cell resilience. We show selective neuropeptide Y4 receptor (Y4R) agonism protects {beta}-cells while reshaping islet immunity across T1D models. Multi-modal localisation using cell sorting, qPCR, RNAscope and fluorescent ligand competition demonstrated predominant Y4R expression and functional accessibility on mouse and human {beta}-cells. Selective Y4R agonism was non-toxic and did not impair islet network integrity, Ca{superscript 2} dynamics, glucose-stimulated insulin secretion or systemic glucose tolerance. Y4R activation conferred cytoprotection against inflammatory cytokines, streptozotocin, lipotoxicity and ER stress, reducing caspase-3/7 activation and {beta}-cell loss whilst sustaining insulin release and promoting proliferation in both mouse and human islets. Bulk RNA-seq revealed a coordinated {beta}-cell resilience programme characterised by reinforced identity and insulin processing, KEAP1-NFE2L2-driven antioxidative and proteostatic activation, and suppression of EIF2 signalling and associated biosynthetic and ER stress pathways. Concurrently, Y4R agonism dampened pathogenic chemokine and cytokine networks, including CXCL10, CCL3/4/7 and IL-6, while preserving IL-2 and Foxp3 signals, thereby limiting CD8 T cell, CD4 T cell and macrophage chemotaxis toward cytokine-stressed islets. Reduced immune-cell recruitment was conserved in a fully human immune-islet system, where Y4R activation significantly attenuated IL-2-activated human PBMC migration and invasion toward cytokine-stressed human islets. In a stringent NY8.3 CD8 T cell adoptive-transfer model, systemic Y4R agonism significantly delayed diabetes onset. These data position Y4R as a {beta}-cell-centric therapeutic target coupling intrinsic resilience with local immune modulation, offering a complementary approach for {beta}-cell preservation in T1D and islet replacement therapies. Graphical abstractThe selective Y4 receptor agonist K22 binds {beta}-cell-enriched NPY4R in mouse and human islets, activates a {beta}-cell resilience programme that preserves insulin secretion under inflammatory and metabolic stress, and simultaneously dampens islet chemokine output, thereby limiting innate and adaptive immune-cell recruitment and delaying autoimmune diabetes onset. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/736290v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@11af8d3org.highwire.dtl.DTLVardef@1c60d37org.highwire.dtl.DTLVardef@18dd142org.highwire.dtl.DTLVardef@1a56cdb_HPS_FORMAT_FIGEXP M_FIG C_FIG

Cas12a2 CRISPR nucleases, including SuCas12a2, have been shown to have extensive collateral activity towards RNA, ssDNA, and dsDNA. This collateral activity results in targeted cell elimination and has applications across biotechnology, agriculture, and human health. We explored the natural genetic diversity of Cas12a2 nucleases and characterized nine novel orthologs in a DNA damage kinetic assay in E. coli. Three new Cas12a2 orthologs (RsCas12a2, SdCas12a2, and HmCas12a2) were shown to have high collateral activity towards DNA. These nucleases are highly divergent from SuCas12a2, have conserved core RuvC catalytic residues, and have sequence diversity in the previously reported aromatic clamp residues required for nucleic acid positioning in the active site. We defined PFS preferences and mismatch tolerance for each high-activity Cas12a2 nuclease, expanding the available Cas12a2 toolbox, and discovered functional differences with obvious impacts on downstream applications.

Gastric insulin-secreting organoids (GINS) represent a promising source of {beta}-like cells for type 1 diabetes (T1D) therapy. In same-donor comparisons with induced pluripotent stem cell-derived islets (iPSC-islets), GINS displayed robust glucose responsiveness and reduced expression of key T1D autoantigens. Importantly, GINS exhibited decreased susceptibility to cytotoxicity mediated by engineered HLA-matched preproinsulin-specific effector T cells (Avatar Teffs) and a distinct transcriptional profile enriched for immune-modulatory and stress-adaptive gene programs. To enhance immune evasion, we engineered gastric stem cells to overexpress Programmed Death Ligand 1 (PD-L1) in an inducible manner. PD-L1+ GINS maintained normal functionality, while exhibiting improved survival under allogeneic Avatar Teff challenge in a MHC class I-independent fashion. We evaluated PD-L1-mediated protection against autologous Avatar Teff attack using an endothelialized microfluidic platform recapitulating physiologic immune interactions. T cells show reduced infiltration into PD-L1 GINS, resulting in significantly higher organoid viability compared to control GINS. Together, these findings identify GINS as a functional and engineerable {beta}-like cell platform with intrinsic hypoimmunogenic features, and support PD-L1 engineering as a strategy to enhance immune protection for both allogeneic and autologous transplantation in T1D.