Biology subjects

Li, K.

Publications and source records attributed to Li, K..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Vegetation change and functional composition shifts in southwestern China during late MIS 3 to LGM

The climatic transition from Marine Isotope Stage 3 (MIS3) to the Last Glacial Maximum (LGM) had caused widespread vegetation change. Despite the dynamic equilibrium between vegetation and climate, the specific role of functional composition in vegetations response to climate change was inadequately understood. Here, we analyzed the long-term trajectories of palynological diversity, vegetation coverage and community-weighted-mean (CWM) functional traits based on EH22 pollen record (35-18 cal ka BP) from Erhai Lake, southwestern China. The results disclosed a vegetation transition from temperate deciduous broadleaf forest dominance in late MIS3 to cold coniferous and mixed broadleaved/coniferous forests in LGM. This vegetation dynamic involved functional composition shifts from competitive-driven functional convergence to partial recovery via niche differentiation during the late MIS3, and finally to a low-diversity but functional differentiation state through trait complementarity and diversification strategies during the cold LGM. Our results likely support a function-mediated climate filtering process whereby climate change regulated long-term vegetation dynamics during the MIS3-LGM transition primarily through shifts in CWM functional composition. These findings underscore the potential of pollen-based trait approaches to reconstruct ecosystem properties and advance our understanding of ecosystem change over decadal to millennial time-scales.

ecology↗

bioRxiv2026

Rapid vegetation reorganization in Hengduan Mountains driven by high climatic oscillations

The accelerating global climate change has been triggering large-scale vegetation reorganizations, yet our understanding of how mountain ecosystems respond to rapid climatic oscillations is critically constrained. Here, we present a high-resolution palynological record from Erhai Lake, southwestern China, revealing eight episodes of rapid vegetation reorganizations in the Hengduan Mountains (HMs) over the past 35,200 years. These reorganizations closely tracked the rhythms of rapid climate oscillations, particularly during the Last Glacial Maximum and the Last Deglacial Period. We find that while the timing of rapid vegetation reorganizations were synchronous with Atlantic Meridional Overturning Circulation (AMOC) anomalies that modulated global climate variability, the magnitude of these reorganizations did not exhibit a linear correlation with AMOC strength; instead, they were governed by local heat and moisture availability mediated through teleconnections. This demonstrates a strong natural regulatory capacity of mountain vegetation in HMs, enabling resilience to intense climatic fluctuations. However, when using the Erhai record as a benchmark, we project that rapid reorganizations under the high-emission pathway (SSP585) will likely surpass the intensities observed during historical events. These findings reveal the high climatic sensitivity and strong natural regulatory capacity of mountain ecosystems, highlighting the critical necessity of climate mitigation actions and nature-based solutions to safeguard subalpine and alpine biodiversity against unprecedented future climate change.

ecology↗

bioRxiv2026

Decoding Spatial Programs in Human Glioblastoma Through Surprisal Information-Theoretical Analysis

Glioblastoma (GBM) is a highly heterogeneous and invasive brain tumor in which complex interactions among tumor cells, immune cells, and neurons shape disease progression and therapeutic resistance. Resolving spatial patterns programs in glioblastoma (GBM) requires analytical approaches that go beyond variance-driven embeddings. Here, we applied thermodynamic surprisal analysis, an information-theoretic decomposition framework, to spatial transcriptomic sequencing from human GBM specimens to identify orthogonal constraint modes that capture dominant and previously hidden spatial programs. Surprisal analysis revealed structured patterns in the data that are not highlighted by standard approaches such as PCA or cell type deconvolution, including immune-activation-associated signatures as well as spatial programs consistent with synapse remodeling. Coupling surprisal decomposition with spatial ligand-receptor interaction analysis, NICHES, along with multiplexed protein imaging connected these spatial hidden modes to reveal potential communication networks. Together, these results position surprisal analysis as a powerful, complementary strategy for interrogating spatial tumor architecture, enabling discovery of non-obvious spatial programs and interactions that are obscured by variance-based methods.

systems biology↗

bioRxiv2026

HoloCell: A Generative Foundation Model for Holistic Cellular Modeling

Single-cell multi-omics technologies have recently advanced to enable the profiling of epigenomic, transcriptomic, and proteomic layers within individual cells, offering new opportunities to characterize cellular states as integrated biological systems. However, developing a unified framework that can seamlessly integrate diverse omics modalities and remain robust to heterogeneous modality missingness remains challenging. Existing methods are often designed for specific modalities or modality pairs, relying on dataset-specific training or paired measurements. Here we present HoloCell, to our knowledge the first generative foundation model for joint representation learning and generative modeling across all three major single-cell omics modalities, i.e., epigenomics, transcriptomics, and proteomics. HoloCell contains over 860 million parameters and is pretrained on the Human-Multi-Omics-Corpus, which comprises approximately 468 million single-cell profiles across these three omics layers, corresponding to over 425 billion tokens. HoloCell introduces a a simple yet biologically motivated hierarchical tokenization strategy that encodes cis-regulatory elements, genes, and proteins as structured tokens within a shared modeling framework. We evaluated HoloCell across single-omics representation learning, paired multi-omics integration, unpaired multi-omics alignment, and cross-modal generation via iterative diffusion and remasking, demonstrating its superior performance and flexibility across diverse omics tasks. From a representation perspective, HoloCell provides a unified digital mapping of cellular states across multiple omics layers, capturing cell heterogeneity as an integrated system. From a generation perspective, its iterative diffusion and remasking frame-work permits flexible generation orders beyond fixed left-to-right causality, enabling in silico simulation of multi-omics information flow. Together, these capabilities position HoloCell as a versatile foundation model toward the emerging concept of a virtual cell, offering both systematic characterization and generative simulation of cellular systems within a unified framework.

bioinformatics↗

bioRxiv2026

Suboptimal human inference reflects an efficient and flexible information bottleneck

Human inference is often suboptimal in ways that vary across individuals and tasks. We propose that at least some of this variability reflects information-processing limits. To test this idea, we developed a task-general application of the information-bottleneck framework to quantify how much information individuals use (information capacity) and how effectively they use it (information efficiency). We applied this framework to human choice behavior on two distinct inference tasks and found that individual differences in performance were driven largely by variation in information capacity, while information efficiency remained consistently high. This pattern of variable capacity and high efficiency also applied to a subset of participants who appeared inefficient overall, but were efficient when evaluated relative to a simplified (heuristic) encoding of the observations. Regardless of whether participants based their strategies on full or simplified encodings, they tended to adjust their performance to different task demands by changing their information capacity while maintaining efficiency. We interpret these findings in terms of new analytical results linking optimal inference under information-capacity constraints to evidence-based choice noise, suggesting that a key driver of human behavioral variability is rational adaptation to flexible information-processing limits.

neuroscience↗

bioRxiv2026

The engulfment receptor CED-1/MEGF10 activates the GPCR LAT-1/ADGRL3 for apoptotic cell degradation

Efferocytosis, the clearance of apoptotic cells, is crucial for tissue homeostasis, inflammation suppression, and repair. While several G protein-coupled receptors (GPCRs) are involved, the broader role of GPCRs in efferocytosis remains unexplored. Through a genome-wide RNAi screen in Caenorhabditis elegans, we identified the adhesion GPCR LAT-1 as a key regulator of apoptotic cell degradation through the promotion of phagosome maturation. Our secondary RNAi scrween for transcriptional regulators revealed that the transcription factor AST-1 acts downstream of LAT-1 to mediate apoptotic cell degradation. We show that the engulfment receptor CED-1 functions as a ligand for LAT-1, activating a Gs protein/adenylyl cyclase/PKA/AST-1 signaling cascade and inducing the transcription of vps-34 and piki-1, which encode phosphatidylinositol 3-kinases essential for PtdIns3P generation on phagosomes. This pathway maintains appropriate VPS-34 and PIKI-1 levels for efficient efferocytosis. Notably, LAT-1 is evolutionarily conserved, with homologs in Drosophila (CIRL) and mammals (ADGRL3) performing similar functions. These findings reveal a conserved CED-1/MEGF10-LAT-1/ADGRL3 axis that orchestrates apoptotic cell clearance via a novel transcriptional regulatory pathway, providing new insight into the molecular mechanisms underlying tissue homeostasis and diseases associated with defective efferocytosis, including autoimmunity and neurodegeneration.

cell biology↗

bioRxiv2026

Scalable in vivo cardiac functional genomics with compressed AAV-Perturb-seq reveals a common mitochondrial response to perturbation

Efficient identification of new targets to treat human disease requires a scalable way to link genotype to phenotype directly in the target organ. Pooled CRISPR screening with single-cell RNA sequencing as a readout (Perturb-seq) has emerged as a method for functional genomics but is typically applied in vitro and is limited in scale. Here, we combine in vivo Perturb-seq via adeno-associated virus (AAV)-mediated delivery with a statistical framework allowing for signal deconvolution after multiple random perturbations per cell (compressed Perturb-seq), to develop in vivo compressed AAV-Perturb-seq, a scalable way to perform high-throughput, cell-autonomous functional genomics in a desired target organ. We apply this approach to study the effect of 585 gene knockouts on the cardiomyocyte transcriptome. We identify that alterations in the mitochondrial transcriptome are a common response to genetic perturbation, a finding independently validated across species and perturbation modalities. We identify very few synergistic perturbations, despite observing frequent combinatorial effects. Broadly, our work establishes a platform to facilitate in vivo functional genomics in a target organ with direct applicability to identifying therapeutic targets for the treatment of human disease.

genomics↗

bioRxiv2026

Inhibition of hexokinase 2 undermines cartilage health and accelerates osteoarthritis

ObjectiveEnhanced glycolysis is a metabolic hallmark of chondrocytes in osteoarthritis (OA); however, the roles of the glycolytic rate-limiting enzyme hexokinase 2 (HK2) in cartilage remain poorly understood. MethodsPharmacological approach (3-bromopyruvate (3-BrPA) treatment) and mice model involving HK2 knockout in Col2a1-expressing chondrocytes are utilized to access the impact of HK2 blockage on cartilage ex vivo and in vivo. The in vivo effects of HK2 inhibition on OA progression were evaluated using a destabilization of the medial meniscus (DMM)-induced OA mouse model, through both intra-articular 3-BrPA administration and chondrocyte HK2 deletion. Additionally, we analyzed published single-cell RNA sequencing (scRNA-seq) datasets from human articular cartilage and integrated these with bulk RNA-seq data from HK2-deficient chondrocytes to characterize HK2 expression features across conditions. ResultsBoth pharmacological inhibition and genetic deletion of HK2 impair cartilage formation ex vivo. Bulk RNA-seq analysis and ex vivo studies demonstrated a promoted ossification-like process due to HK2 ablation in chondrocytes. Through pseudotime analysis of published single-cell RNA sequencing (scRNA-seq) datasets from human articular cartilages, we further identified that HK2 is differentially expressed across conditions, with a feature of a relatively high expression level at terminal stages of chondrocyte differentiation in the context of OA. We next confirmed HK2 deficiency in chondrocytes significantly exacerbated OA progression but having no impact on skeletal development in mice. ConclusionsHK2 plays a critical role in maintaining cartilage health, likely through the regulation of calcification, thereby highlighting the potential risks associated with targeting glycolytic enzymes as a therapeutic strategy for OA.

pathology↗

bioRxiv2026

An AI-agent-orchestrated grey-box Transformer framework for sparse pharmacokinetic curve reconstruction and pharmacometric model initialization

Clinical pharmacokinetic (PK) modelling is constrained by sparse sampling, limited general-isability of single-drug models, and labour-intensive workflows, making it difficult to infer complete drug exposure from limited concentration observations. We present the Pharmacokinetic Foundation Model (PKFM), a grey-box Transformer framework pre-trained across 32 drugs that reconstructs concentration-time profiles from sparse concentration observations, dosing events, molecular descriptors, and physiological covariates while preserving output interpretability. In representative oral PK curves, three sparse input points recovered the principal absorption-elimination trajectory, achieving coefficient of determination (R2) = 0.992 for Midazolam oral and R2 = 0.990 for Verapamil oral. Using reconstructed curves in NONMEM (nonlinear mixed-effects modelling) improved covariance stability and individual prediction accuracy. Contrastive-learning embeddings supported Top-10 physiologically based pharmacokinetic (PBPK) candidate retrieval, with 75.6% of observations within the 2-fold range. A pharmacometrics-informed AI Agent (PM Agent) outperformed general-purpose programming tools in stability and pairwise win rate on a standardised modelling benchmark, with each run requiring human pharmaco-metrician confirmation before downstream use. These results support cross-drug pre-trained PK models as an information-completion layer for sparse PK evidence and a structured scaffold for the modelling workflow; clinical or regulatory use requires prospective validation, broader external benchmarking, and independent expert assessment.

pharmacology and toxicology↗

bioRxiv2026

Cell-type-resolved RNP topologies reveal dynamic structural mechanisms of splicing and therapeutic targets

Resolving RNA conformations in native ribonucleoprotein (RNP) complexes remains a fundamental challenge. Here, we introduce spatial hydroxyl acylation reversible crosslinking with immunoprecipitation (SHARCLIP) to simultaneously capture RNA-RNA, RNA-protein and protein-protein contacts in cells. SHARCLIP profiling of HNRNPC-associated RNA conformations established a global phased map of ribonucleosomes, resolving a decades-old debate on heterogenous nuclear (hn)RNP assembly. We built a dynamic structural atlas across seven cell lineages for >10,000 RNAs, generating ~200 million contacts, and identifying millions of dynamic loops, steric blockers and conformational switches that control splicing outcome. Deciphering the structural logic of mutually exclusive exons (MXEs) enabled rational design of structure-breaking and stabilizing antisense oligonucleotides (ASOs). We demonstrate effective isoform swapping in 12 genes linked to genetic disorders. SHARCLIP provides a comprehensive roadmap for cellular RNA structural biology and structure-guided RNA therapeutics.

molecular biology↗

bioRxiv2026

PARP1-mediated 5' flap dynamics facilitate Okazaki fragment maturation

Abstract/SummaryPrecise regulation of enzyme recruitment during Okazaki fragment maturation (OFM) is essential for faithful and efficient lagging-strand DNA synthesis. Emerging evidence suggests that PARP1 contributes to OFM yet its specific functions remain unclear. Here, we define context-dependent functions of PARP1 during OFM. Under physiological conditions, PARP1 co-localizes with PCNA in early S phase and restrains Pol {delta}-PCNA- mediated strand-displacement DNA synthesis, thereby preventing the formation of long 5' flaps, which is refractory to FEN1 cleavage. On the other hand, in LIG1-deficient cells, in which DNA nicks and unexpectedly long 5' flaps accumulate, PARP1 promotes the recruitment of LIG3 to catalyze OF ligation and DNA2 to facilitate long 5' flap processing. Collectively, our findings uncover previously unrecognized roles of PARP1 in regulating 5' flap dynamics to ensure efficient OFM and cell viability. HighlightsO_LIPARP1 plays context-dependent regulatory functions in Okazaki fragment maturation (OFM). C_LIO_LIPARP1 controls strand displacement DNA synthesis by the PCNA-Pol{delta} complex to dictate generation of short over long RNA-DNA flaps during canonic OFM. C_LIO_LIPARP1 senses unligated Okazaki fragments in DNA Ligase 1 deficient cells and suppresses unwanted conversion of DNA nicks into 5 flaps. C_LIO_LIProcessing of unligated nicks or flaps by DNA ligase 3 or DNA2, respectively in LIG1 deficient cells depends on PARP1. C_LIO_LIPARP1 inhibitors induce synthetic lethality with DNA ligase 1 or DNA2 inhibition. C_LI

molecular biology↗

bioRxiv2026

Fibroblast-encoded inflammatory memory orchestrates recurrent skin inflammation via NNMT-dependent metabolic remodeling

Chronic skin inflammation frequently recurs at the same anatomical sites after therapy withdrawal, implying stromal cells may encode local inflammatory memory. Here, we identified nicotinamide N-methyltransferase (NNMT) as a central metabolic-epigenetic regulator of fibroblast inflammatory memory enabling psoriasis relapse. Single-cell and spatial transcriptomics revealed that dermal fibroblasts acquire a persistent senescence-associated secretory phenotype (SASP) during inflammation, maintaining pro-inflammatory niche in resolved skin that supports CD 8+CD 103+ tissue-resident memory T cell (Trm) differentiation. Multi-omics profiling demonstrated that NNMT depletes S-adenosylmethionine (SAM), reduces H 3K 27me3 deposition, and permits sustained AP-1 occupancy at SASP gene promoters. Fibroblast-specific NNMT ablation or pharmacologic inhibition suppressed SASP activity, limited Trm accumulation, and prevented both initiation and relapse of skin inflammation in mice. These findings establish NNMT as a stromal regulator linking fibroblast metabolism to durable epigenetic memory and propose its targeting to erase inflammatory memory and achieve long-term remission in psoriasis and related immune-mediated diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/721223v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@34b2f4org.highwire.dtl.DTLVardef@1d0bb89org.highwire.dtl.DTLVardef@c8277borg.highwire.dtl.DTLVardef@9825ac_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic Abstract:C_FLOATNO Proposed mechanism through which NNMT-driven fibroblast SASP facilitates the initiation and recurrence of psoriasis C_FIG

immunology↗

bioRxiv2026

Development of a Fully Non-Viral 1XX-enhanced BCMA CAR-T Cell Therapy for Multiple Myeloma

Multiple myeloma (MM) is a clonal plasma cell malignancy characterized by bone marrow infiltration, monoclonal immunoglobulin production, and microenvironmental dysregulation that leads to systemic organ damage. The advent of B-cell maturation antigen (BCMA)-directed chimeric antigen receptor (CAR) T-cell therapy has induced unprecedented responses and durability for patients with relapsed/refractory MM. These outcomes are rarely observed with prior salvage strategies, although relapse remains the predominant long-term challenge for most patients. The two currently approved BCMA CAR-T cell products use viral vectors to semi-randomly insert the CAR gene, which results in heterogeneous genomic composition and variability in efficacy, safety, and product consistency. To address these challenges, we integrated targeted CRISPR genome engineering with precise CAR transgene insertion at the T-cell receptor alpha constant (TRAC) locus, 1XX CAR signaling architecture to enhance potency and durability, and non-viral manufacturing with a single-stranded DNA repair template to improve efficiency and yield. This approach confers physiological CAR expression, reduces insertional mutagenesis, and improves persistence by mitigating tonic signaling and exhaustion. Our GMP manufacturing process consistently achieved high CAR integration (37.7-72.7%) and yields across all full-scale runs and met predefined release criteria for identity, purity, safety, and quality. In NSG mouse models of MM, the UCCT-BCMA-1 product exhibited exceptionally potent tumor control, CAR-T cell expansion 100-1000-fold greater than that of lentiviral constructs, and durable clearance of myeloma cells after multiple rechallenges. These findings establish a CRISPR-edited, fully non-viral manufacturing platform for next-generation 1XX-BCMA CAR-T therapies with enhanced persistence, safety, and efficacy. One Sentence SummaryCRISPR-engineered, TRAC-targeted 1XX-BCMA CAR-T therapy with improved safety, potency, and persistence in relapsed and refractory multiple myeloma.

cancer biology↗

bioRxiv2026

Single injection of modified self-amplifying RNA encoding a CD19 bispecific T cell engager mediates long-term malignant B cell clearance

Bispecific T cell engagers (BiTEs) are a novel cancer immunotherapy modality that achieves significant clinical success. However, conventional single-chain variable fragment (scFv)-based BiTE therapy requires continuous intravenous infusion due to BiTEs short half-life, limiting patient access and increasing healthcare cost. Self-amplifying RNA (saRNA), an emerging RNA technology, enables durable protein production in situ. Here, we report a 5-methylcytidine (m5C)-modified saRNA encoded BiTE system (saRNA-BiTE) targeting CD19. saRNA-BiTE induces prolonged, antigen-specific target cell lysis in vitro. In an acute lymphoblastic leukemia rechallenge model, a single intravenous injection of saRNA-BiTE formulated in lipid nanoparticles eradicates malignant cells and prevents disease recurrence for 3 months. saRNA-BiTE maintains more stable systemic level than protein BiTE or mRNA-BiTE without generating an initial burst BiTE exposure and affords functional BiTE expression for 6 weeks post administration. This work establishes saRNA-BiTE as a robust platform for extended in situ BiTE expression with enhanced long-term efficacy and facile production.

bioengineering↗

bioRxiv2026

Heterogeneous transmission estimation and strategy optimization for Chikungunya: a vector-borne modeling study differentiating age and sex

Against the backdrop of global climate change and accelerating population mobility in 2025, chikungunya fever (CHIKF) exhibited a trend of worldwide spread, significantly increasing the difficulty of controlling tropical mosquito-borne diseases. To enhance the precision of intervention strategies, this study developed an age- and sex-structured human-mosquito interaction dynamic model based on data from the largest CHIKF outbreak ever recorded in China, and conducted a targeted analysis of prevention and control strategies. By decomposing the basic reproduction number and examining population heterogeneity, asymptomatic males aged 15-59 years were identified as the core transmission group. Optimal control analysis revealed that the synergistic implementation of three measures-- reducing the effective human-to-mosquito transmission rate, reducing the effective mosquito-to-human transmission rate, and suppressing mosquito population density--could reduce the overall infection rate by 95.7586%. Among these, mosquito population suppression should be prioritized as a universal core strategy; however, its protective effect on females aged 60 years and above was relatively weak, warranting particular attention. The study further demonstrated that asymmetric intensity combinations targeting these three intervention pathways--such as intensity profiles of "10%, 90%, 90%" or "60%, 80%, 90%"--could achieve effective outbreak control. This research elucidates population-specific transmission patterns and key pathways for intervention intensity, providing a theoretical and strategic foundation for the precise control of mosquito-borne diseases. It also provides actionable operational insights to support rapid response and strategy optimization for future emerging outbreaks. Author summaryCHIKF is a mosquito-borne viral disease that is gradually spreading from tropical regions to other areas. To achieve more precise control of this disease, we developed an age- and sex-structured analytical model based on the largest CHIKF outbreak in China, aiming to provide a scientific basis for responding to potential future outbreaks with inherent uncertainties. The study found that asymptomatic males aged 15-59 years were the primary drivers of transmission and should be prioritized as a key population for reducing viral spread in prevention efforts. When evaluating the effectiveness of different intervention strategies, females aged 60 years and above were the least affected by the implemented measures, indicating that this group should strengthen personal protection to lower their infection risk. Among all control measures, mosquito suppression was the most effective, suggesting that vector control strategies should be prioritized in future outbreak responses.

pathology↗

bioRxiv2026

The UV potentiated mutational signature of clinical stage G-quadruplex binder CX5461.

Drug-related UVA-induced photoreactions have been reported for several therapeutic compounds, including fluoroquinolones. CX5461 is a clinically relevant quinolone-derived anti-cancer small molecule with documented UVA-sensitising activity. Here we compared, by bulk and clonal whole genome sequencing (WGS) under light-protected conditions, the mutational signatures in human retinal pigment epithelial cells (RPE1) exposed to UVA, CX5461, or co-exposed to UVA and CX5461. Treatment with CX5461 or UVA alone resulted in a low SNV burden and background-like mutational profiles. In contrast, bulk sequencing of human cells co-exposed to UVA and CX5461 had a markedly higher SNV burden characterized by T>A and T>C substitutions. Furthermore, single-cell clonal expansion and sequencing of CX5461 alone, UVA alone or CX5461+UVA treatments confirmed that the pattern was only observed when cells were exposed to both UVA and CX5461. The CX5461+UVA-associated SNV signature we report arises only when CX5461-treated cells are exposed to UVA, and is not observed when CX5461-treated cells are shielded from light. We do not observe strong single base mutagenic activity of CX5461 alone, under light protected conditions. Our data emphasise the need for appropriate controls and light-exposure precautions when studying base mutagenesis activity of known photosensitiser molecules.

cancer biology↗

bioRxiv2026

Ultra-large targeted DNA integrations in primary human cells

Genetic engineering experiments and therapies are constrained by the size of DNA integrations into human cells genomes. Existing AAV, lentiviral, and non-viral methods rapidly decrease in integration efficiency beyond [~]5kb of sequence. Through systematic evaluation of non-viral DNA template formats, we identified circular ssDNA and dsDNA as capable of mediating >5kb integrations. Large circular DNA delivery efficiency and its impacts on cell viability and payload expression could be significantly improved with small DNA "helper" plasmids, mRNA-encoded nucleases, and sequence design optimizations. Collectively, these modifications enabled ultra-large--up to 10 kb DNA--integrations at >20% efficiency in primary human T cells at the TRAC locus and at >60% efficiency in human iPSCs at the AAVS1 locus. Finally, we demonstrate that GMP clinical-manufactured T cells with ultra-large integrations are functional in vitro and in vivo. Overall, we identified optimal template architectures, delivery modes, and sequence design rules for ultra-large DNA integrations in both research and clinical settings to accelerate basic genetic research and next-generation cellular therapies.

genetics↗

bioRxiv2026

Understanding the impact of sodium sulfide on the invasive growth of wine yeast

Yeasts ability to invade surfaces has important implications for infections and food contamination. Invasive growth in yeast is influenced by genetic and environmental factors. In this exploratory study, we used a systematic experimental design to identify conditions under which sulfide-induced invasive growth can be reliably observed and quantified and investigated the effects of sulfide, gene deletions, and environmental conditions on the invasive behaviour of the wine yeast strain AWRI 796. Sulfide enhanced invasion in the (parent) AWRI 796 strain under nitrogen-limiting conditions, although its effect was obscured by experimental variability and pre-culture conditions. Genetic factors had a major effect on the overall invasive phenotype, with deletion of key genes suppressing invasion. Most gene-deletion mutants did not significantly affect how the colony responded to sulfide. In addition to sulfide and genotype, environmental conditions also influenced invasive behaviour. The pre-2xSLAD pre-culture condition was best for detecting sulfide-induced growth, and later plate washing time and decreased nutrient levels enhanced invasiveness. Our experimental design and findings provide a framework for understanding the determinants of yeast invasiveness, which may inform future studies on filamentous yeast behaviour.

microbiology↗