Biology subjects

Li, Z.

Publications and source records attributed to Li, Z..

At least 361 records · Page 20Linked to original sources

bioRxiv2025

Co-Evolutionary Characterization of PBP2 as the Predominant Siderophore Recognizer in Diverse Gram-Positive Bacteria

Iron is a scarce yet essential nutrient for bacteria. Microbes often acquire iron by secreting siderophores, a diverse group of small molecules that form high-affinity complexes with iron for microbial uptake. Understanding microbial iron interaction networks requires detailed characterization of siderophore recognition specificity. In Gram-positive bacteria, substrate-binding proteins (SBPs) bind iron-siderophore complexes and deliver them to ABC transporters for import. However, the SBPs responsible for selective recognition remain poorly characterized, hindering large-scale data mining and network reconstruction. Here, we addressed this knowledge gap by systematically analyzing siderophore uptake systems, first in five representative genera and then across a comprehensive dataset of 16,232 Gram-positive genomes. Through a pipeline integrating genome mining, coevolutionary analysis, and structural modeling, we established PBP2 (Peripla_BP_2) subtype SBPs as the primary siderophore recognizer family. We revealed that, unlike the physically clustered systems in Gram-negative bacteria, synthetase and recognizer genes in Gram-positive bacteria are sometimes genomically decoupled yet display coordinated transcriptional regulation by iron-responsive transcription factors. Our findings underscore key differences between Gram-positive and Gram-negative iron acquisition systems, providing foundational knowledge for large-scale inference of siderophore-mediated microbial interactions. Impact StatementBacteria secrete siderophores to scavenge iron and import the siderophore-iron complex via specific receptors, a process that shapes microbial community dynamics. However, predicting these interactions has been challenging, because the specific siderophore receptors in Gram-positive bacteria remained largely uncharacterized. In this study, we opened this "black box" by analyzing a comprehensive dataset of 16,232 genomes spanning the majority of Gram-positive bacteria. Through coevolutionary analysis, we identified PBP2 proteins as the primary "locks" that recognize siderophore "keys." We further demonstrate that these receptors exhibit greater evolutionary flexibility than their Gram-negative counterparts, frequently decoupled genomically from siderophore biosynthesis genes yet linked by transcriptional regulation. This discovery fills a critical knowledge gap, providing the missing link needed to map the global landscape of siderophore uptake potential and enable "sequence-to-ecology" prediction of iron-interaction networks in Gram-positive bacteria.

microbiology↗

bioRxiv2025

A Controlled Test of Risk-Dependent Immune Investment in a Clonal Ant

Biological systems can benefit from distributing defensive investment unevenly, concentrating protection in parts of the system that face higher risk or hold greater strategic value. In social groups, individuals often face asymmetric infection risks based on their behavioural roles, raising the possibility that immune defences are plastically adjusted according to risk. In social insects, this idea has led to the hypothesis that individuals performing high-risk tasks, such as foraging, should invest more in constitutive immune defences to reduce transmission within the colony. However, testing this hypothesis has been hindered by confounding effects of genotype, age, and infection history. We use the clonal raider ant Ooceraea biroi to overcome these limitations. In this system, spontaneous behavioural specialisation between genetically identical, age-matched individuals creates variation in infection risk, while controlling for other sources of variation. We first annotated the O. biroi immune gene repertoire and sequenced the transcriptomes of 77 individuals that showed considerable behavioural variation. We then combined fine-scale individual behavioural tracking with three complementary measures of immune investment: immune-related gene expression, antibacterial activity, and survival following infection. Despite behavioural specialisation, we find no evidence that individuals engaging in higher-risk behaviours invest more in constitutive immune defences. These results contradict a long-standing hypothesis in the field and suggest limits to plastic immune allocation based on infection risk in social insect colonies.

ecology↗

bioRxiv2025

Mechanisms of surface and volume light scattering from Caenorhabditis elegans revealed by angle-resolved measurements

The use of the model roundworm Caenorhabditis elegans in has enabled pioneering discoveries in biology in part due to its optical accessibility. Optical imaging of C. elegans primarily relies on light scattering to generate contrast. However, the mechanisms of light scattering by C. elegans, and how they influence image contrast, are not well understood. We measured scattering and image contrast from C. elegans under varied illumination angles, wavelength, substrate composition, bacterial seeding, and index matching conditions. Combining experiments with ray-tracing simulations, we show that scattering arises from two interacting components: volume scattering within the body and surface scattering at interfaces between the worm and its surroundings. Surface scattering dominates at low angles and enhances animal boundaries, whereas volume scattering becomes more prominent at higher angles and improves visibility of internal structures. We identify practical conditions that optimize image contrast, including low-angle off-axis illumination, longer-wavelength (red) light, and low-scattering substrate media. Our work establishes a framework for understanding light scattering from small animals.

bioengineering↗

bioRxiv2025

Modeling tumor transport and growth with poroelastic biopolymer networks

The mechanical properties of the extracellular matrix (ECM) regulate tumor growth and invasion in the tumor microenvironment. Models of biopolymer networks have been used to investigate the impact of elasticity and viscoelasticity of ECM on tumor behavior. Under tumor compression, these networks also show poroelastic behavior that is governed by the resistance to water flow through their pores. This work investigates the hypothesis that poroelastic properties regulate tumor growth. Here, alginate hydrogels with tunable ionic and hybrid ionic/covalent crosslinking are used as a model biopolymer system. Hydrogel stiffness, viscoelasticity, and stress relaxation behavior were characterized using stepwise axial compression. Among these properties, we find poroelastic fluid outflow dominates ECM stress relaxation, as the measured water flux was significantly affected under compression. Continuum mechanics-based modeling was developed to formulate and calculate the chemical potential gradients of water (solvent) in the hydrogels under compression. This framework was extended into an advection-diffusion framework to quantify growth factor (solute) distribution under varying strengths of stress and diffusion indexed by the relative strength of convective to diffusive transport, characterized by the Peclet number. An agent-based computational simulation showed that tumor growth was affected by Peclet number. Together, these results highlight the role of the poroelastic properties of ECM on water flux and transport in the tumor microenvironment.

biophysics↗

bioRxiv2025

Mapping disease critical spatially variable gene programs by integrating spatial transcriptomics with human genetics

Spatial gene expression patterns underlie tissue organization, development, and disease, yet current methods for detecting spatially variable genes (SVGs) lack the flexibility to capture multi-scale structure, ensure robustness across platforms, and integrate with genetic data to assess disease relevance. We present Spacelink, a unified framework that models spatial variability of a gene at both whole-tissue and cell-type resolution using an adaptive mixture of data-driven spatial kernels and summarizes it using an Effective Spatial Variability (ESV) metric. Spacelink achieved up to 3.2x higher detection power over eight existing global SVG and cell-type SVG methods while showing consistently superior FDR control across 34 different simulation settings and also showed superior cross-platform concordance in matched tissue Visium and CosMx datasets. Applied to 3 healthy CosMx human tissues (brain cortex, lymph node, liver), Spacelink revealed that SVGs are highly informative for 113 complex traits and diseases (average GWAS sample size = 340,406). Spacelink showed up to 2.2x higher disease informativeness over competing methods in tissue-relevant complex diseases and traits, conditional on putative non-spatial expression-level confounders. Applied to a mouse organogenesis Stereo-seq atlas (8 developmental stages), Spacelink identified 145 genes with stage-associated ESV within brain independent of mean expression, that are enriched in pathways like Wnt signaling and Rap1 signaling characterizing early and late development, respectively. Integration with in vivo Perturb-seq targeting 35 de novo ASD risk genes revealed that perturbations in excitatory neurons and astrocytes preferentially altered spatially structured downstream gene programs (1.7-2.2x higher average ESV across stages than other cell types), many of which were enriched for polygenic autism GWAS loci. In neurodegeneration, analysis of 32 Visium dorsolateral prefrontal cortex samples spanning Alzheimers disease (AD) pathology stages identified 334 genes with decreasing ESV along amyloid burden (enriched for glycolysis) and 216 genes with decreasing ESV along tau tangle accumulation (enriched for apoptotic pathways). Several AD risk genes (PKM, CLU, GPI) showed conserved reductions in spatial variability with AD pathology in both human and 5xFAD mouse, with PKM linking to a colocalized splicing QTL and amyloid burden QTL variant. These results highlight the utility of Spacelink in decoding spatially variable gene programs that connect tissue architecture to disease genetics.

genomics↗

bioRxiv2025

In vivo genome-wide CRISPR screens in human T cells to enhance T cell therapy for solid tumors

Large-scale CRISPR screening in human T cells holds significant promise for identifying genetic modifications that can enhance cellular immunotherapy. However, many genetic regulators of T cell performance in solid tumors may not be readily revealed in vitro. In vivo screening in tumor-bearing mice offers greater physiological relevance, but has historically been limited by low intratumoral T cell recovery. Here, we developed a new model system that achieves significantly higher human T cell recovery from tumors, enabling genome-wide in vivo screens with small numbers of mice. Tumor-infiltrating T cells in this model exhibit hallmarks of dysfunction compared to matched splenic T cells, creating an ideal context for screening for genetic modifiers of T cell activity in the tumor microenvironment. Using this platform, we performed two genome-wide CRISPR knockout screens to identify genes regulating T cell intratumoral abundance and effector function (e.g., IFN-{gamma} production). The intratumoral abundance screen uncovered the P2RY8-G13 GPCR signaling pathway as a negative regulator of human T cell infiltration into tumors. The effector function screen identified GNAS (Gs), a central signaling mediator downstream of multiple GPCRs that sense different suppressive ligands, as a key regulator of T cell dysfunction in tumors. Targeted GNAS knockout rendered T cells resistant to multiple suppressive cues and significantly improved therapeutic performance across diverse solid tumor models. Moreover, combinatorial knockout of P2RY8 (trafficking) and GNAS (effector function) further enhanced overall tumor control, demonstrating that genetic modifications targeting distinct T cell phenotypes can be combined to improve therapeutic potency. This flexible and scalable in vivo screening platform can be adapted to diverse tumor models and pooled CRISPR libraries, enabling future discovery of genetic strategies that equip T cell therapies to overcome barriers imposed by solid tumors.

immunology↗

bioRxiv2025

PD-1 signaling is essential for the early accumulation of HBV-specific CD8+ T cells during HBV infection

Background & AimsProgrammed cell death Protein 1(PD-1) is one of the key inhibitory receptors that regulates CD8 T cell exhaustion during chronic viral infection. However, the role of PD-1 in modulating effector T cell differentiation and function during early phase of hepatitis B virus (HBV) infection remains poorly defined. MethodsUsing adoptive transfer of wild-type or PD-1 KO HBV-specific TCR transgenic (C93-TCRtg) CD8 T cells, flow cytometry, and transcriptome sequencing, we systematically profiled early PD-1 dynamics in splenic and intrahepatic T cells and evaluated how PD-1 deficiency shapes anti-HBV T cell responses in acute self-resolving (AR) and chronic (CH) HBV mouse models. ResultsAcute HBV infection induced sustained PD-1 upregulation on intrahepatic/splenic CD8 T cells, which predominantly exhibited an effector phenotype. PD-1 cells displayed enhanced proliferation, cytotoxicity, and effector cytokine production compared to PD-1- counterparts. Adoptive transfer of PD-1 KO C93-TCRtg CD8 T cells resulted in significantly impaired early expansion in both spleen and liver during acute infection, accompanied by reduced granzyme B expression while maintaining IFN-{gamma}, TNF-, or IL-2 production. Transcriptomic analysis revealed that PD-1 deficiency was associated with the upregulation of apoptosis gene signatures. In chronic HBV infection, PD-1 KO cells failed to expand long-term and exhibited exacerbated exhaustion evidenced by a loss of IFN-{gamma} production. ConclusionsPD-1 is essential for the early expansion and survival of HBV-specific CD8 T cells during acute infection and does not suppress their effector cytokine function. Its absence impairs proliferation and promotes exhaustion of HBV-specific CD8 T cell in chronic infections. Impact and implicationsOur study redefines PD-1s role in acute HBV infection. Rather than merely constraining effector function, PD-1 is essential for the early expansion and survival of HBV-specific CD8+ T cells, acting as a safeguard against activation-induced apoptosis. The context-dependent functions position PD-1 as a critical rheostat calibrating the magnitude and quality of the antiviral CD8+ T cell response, with significant implications for immunotherapeutic strategies targeting this pathway in hepatitis B.

immunology↗

bioRxiv2025

A cross model spatial and single-cell atlas reveals the conserved involvement of osteopontin in polycystic kidney disease

Polycystic kidney disease (PKD) arises from mutations in cilia-associated genes, such as PKD1 and PKD2, expressed in renal epithelial cells, leading to progressive kidney dysfunction and end- stage kidney disease (ESKD). PKD patients exhibit significant heterogeneity in disease progression, largely due to genetic and environmental modifiers. Like patients, mouse models of PKD also exhibit significant heterogeneity with regards to the gene mutated, age of disease onset, and rate of disease progression. To elucidate the cellular and molecular consequences of these variables, we constructed an integrated single-cell and spatial transcriptomics atlas across mouse models of PKD, mapping changes in cell type composition, gene expression, and intercellular signaling networks across the whole atlas and within individual models. Consistently across models, single cell RNA sequencing (scRNAseq) data revealed increased Spp1 (osteopontin) expression and signaling from PKD-enriched clusters to Ly6clo monocytes. Global deletion of Spp1 in Pkd1RC/RC mice resulted in reduced cyst severity, improved kidney function, and reduced Ly6clo monocyte numbers, suggesting that SPP1 signaling to Ly6clo monocytes promotes PKD progression. We also created a freely available, searchable website (https://bmblx.bmi.osumc.edu/scPKD/) that can be used to identify cross- and intra-model specific changes in gene expression, guiding researchers to new therapeutic targets for treating PKD.

bioinformatics↗

bioRxiv2025

Phosphorylation enables progressive microtubule-associated protein proteolysis and functionalisation during neural development

Neurological diseases are frequently characterised by dysregulation of the microtubule cytoskeleton, which is critical for neuronal integrity and functioning. However, the precise mechanisms by which microtubule dynamics are regulated during the development of the nervous system remain poorly understood. Here, we use global phosphoproteomic screening to identify cytoskeletal substrates of Ser-Arg Protein Kinase (SRPK), which is implicated in several neurodevelopmental and neurodegenerative conditions. We show that SRPK directly phosphorylates Microtubule Associated Protein (MAP)1S at multiple sites in a C-terminal region involved in proteolytic maturation and microtubule binding. SRPK-dependent MAP1S phosphorylation modulates the affinity of the MAP1S microtubule binding domain for microtubules and MAP1S proteolytic processing by the Calpain (CAPN)10 protease. Finally, we show that MAP1S proteolytic processing occurs progressively during neurodevelopment via a specific CAPN10 expression switch, corresponding with MAP1S acquisition of microtubule binding activity. Our results demonstrate a role for SRPK in coordinating processing and functionalisation of a key microtubule regulatory protein during neurodevelopment and provide insight into mechanisms by which the microtubule cytoskeleton may be dysregulated in neurological diseases.

biochemistry↗

bioRxiv2025

Restricted Retrieval Enhances Extinction Memory Generalization across Time and Context

During traditional extinction, the conditioned stimulus (CS) activates both the original fear memory and the newly formed extinction memory. Because fear memory is typically more robust, it interferes with the encoding, consolidation, and retrieval of extinction memory, resulting in a fragile and transient safety trace. Consequently, fear often returns after extinction. This pilot study examined whether repeated retrieval practice of the most recent nonreinforced CS during extinction could strengthen extinction memory and reduce fear relapse. Thirty-nine participants completed a four-day paradigm comprising fear acquisition (60% reinforcement rate), two extinction sessions, and a fear renewal test. The two groups (experimental vs. control) differed only during the extinction phase. Specifically, the experimental group received training identical to that of the Ctrl group during the first two and last two trials of the first extinction session, and the first and last two trials of the second session (for each CS type). During the intermediate trials, the experimental group recalled whether the preceding CS+/CS- trial was safe and then predicted the outcome of the current trial accordingly. Conditioned responses were assessed using skin conductance responses and subjective assessments (US expectancy, valence, and arousal). Both behavioral and physiological indices consistently suggested that restricted retrieval practice during extinction improved extinction memory retention and attenuated fear renewal. These findings suggest the potential benefits of incorporating restricted retrieval practice into extinction-based interventions to improve their long-term efficacy.

animal behavior and cognition↗

bioRxiv2025

Integrated Analysis of Glycosylation and Inflammation-Related Genes for Prognostic Risk Modeling and Immunotherapy Response Prediction in Gastric Cancer

BackgroundGastric cancer (GC) continues to be among the most commonly identified cancers worldwide. This study integrates glycosylation and inflammation-related gene features for the first time to construct a prognostic model for gastric cancer, providing new theoretical basis for revealing immune escape mechanisms and personalized treatment strategies. MethodsTranscriptomic and clinical data derived from GC samples were meticulously examined, utilizing resources from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Through differential expression analysis, we successfully identified glycosylation and inflammatory-related differentially expressed genes (GANDIRDEGs). To construct a prognostic gene signature, we applied least absolute shrinkage and selection operator (LASSO) analysis in conjunction with Cox regression analysis. Additionally, we performed somatic mutation (SM) along with copy number variation (CNV) analyses, alongside gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, we conducted gene set enrichment analysis (GSEA) along with a comprehensive evaluation of immune infiltration and drug sensitivity. ResultsWe identified and validated a six-gene (INHBA, OLR1, ROS1, EPHA5, TACR1, and IL6) signature, termed GANDIRDEGs, which showed excellent performance in distinguishing overall survival (OS) between high-risk (HR) and low-risk (LR) cohorts. Moreover, we developed a prognostic nomogram utilizing this six-gene signature that provides highly accurate predictions of GC patient outcomes.SM and CNV analyses revealed that MSR1 had the highest mutation rate among the GANDIRDEGs, with a mutation rate of 5%. GO, KEGG, and GSEA revealed significant associations of each pivotal gene with pathways, including cytokine signaling, the inflammatory response, and apoptosis mediated by CDKN1A through TP53, among various biological functions and signal transduction pathways. Our findings offer a novel gene signature, GANDIRDEGs, that correlated with prognosis, immune infiltration, and therapeutic sensitivity in patients with GC. ConclusionThis study establishes a prognostic signature integrating glycosylation and inflammatory pathways in GC, providing valuable insights into the mechanisms of immune evasion and potential personalized treatment approaches.

cell biology↗

bioRxiv2025

Sarbecovirus Rc-o319 S-Protein Structures Reveal Highly Specialized Adaptation to Rhinolophus cornutus ACE2

Bat sarbecoviruses often exhibit species-dependent ACE2 specificity. Understanding the determinants of receptor specificity enables better assessment of the cross-species transmission potential of sarbecoviruses. Here, we characterize the S-protein of Rc-o319, a sarbecovirus identified in Japanese Rhinolophus cornutus bats. Featuring an unusual 9-amino-acid deletion within its receptor binding motif (RBM), Rc-o319 S-protein utilizes its cognate R. cornutus ACE2 (bACE2R.cor) but not human ACE2 (hACE2), demonstrating highly restricted receptor specificity. Cryo-EM structures reveal two locked prefusion conformations of the Rc-o319 S-trimer and define a novel type-1b receptor-binding domain (RBD), featuring a distinct beta-loop (BL) within the RBM due to the RBM-deletion. The Rc-o319-RBD:bACE2R.cor complex structure reveals unique interactions mediated by the specialized BL and RBM-loop of Rc-o319-RBD and by a bACE2R.corglycan. Structure-guided mutagenesis demonstrates that changes in BL and RBM-loop within the Rc-o319 S-RBD must occur simultaneously to allow medium-to-high-affinity hACE2 binding. Comparative assays further show that the bACE2R.cor receptor supports only a subset of sarbecoviruses, highlighting its restricted sarbecovirus compatibility. Our findings establish the Rc-o319 S-protein as a structurally and functionally specialized adaptation to R. cornutus ACE2 and identify the structural constraints limiting its cross-species transmission potential. Author SummarySARS-related viruses are widely found in horseshoe bats. Some can bind the human ACE2 receptor with variable affinities, whereas others bind only bat ACE2 receptors. Understanding the basis for this difference is critical for assessing spillover risk. We studied the spike protein of a bat sarbecovirus, Rc-o319, isolated from Japanese Rhinolophus cornutus horseshoe bats. Although Rc-o319 is genetically related to SARS-CoV-2, it is unable to bind the human ACE2 receptor. Structural analyses and functional experiments revealed that the Rc-o319 spike protein possesses a distinct receptor-binding motif (RBM). This RBM features a specialized "beta-loop" that replaces the "large-loop" found in human-infecting sarbecoviruses. The beta-loop enables high-affinity binding to its cognate Rhinolophus cornutus bat ACE2 receptor while simultaneously preventing optimal interaction with human ACE2. We further found that acquisition of high affinity for the human ACE2 receptor would require coordinated changes across multiple regions of the RBM, including changing the beta-loop into a large-loop structure. Together, our findings demonstrate that the Rc-o319 spike protein is highly adapted to its cognate bat ACE2 receptor and faces substantial structural constraints that limit its ability to switch to binding human ACE2.

microbiology↗

bioRxiv2025

RhoV Promotes Proliferation, Migration, and MAPK Activation in Pancreatic Ductal Adenocarcinoma

Background and AimsPancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy characterized by diagnosis at advanced stages, limited therapeutic options, and frequent resistance to therapies. Although oncogenic KRAS mutations are central drivers of PDAC, alternative pathways indisputably contribute to its tumorigenesis and progression. RhoV, a member of the Rho family of small GTPases, has been implicated in tumor development in other cancer types, such as breast cancer and lung adenocarcinoma; however, its role in PDAC remains unclear. MethodsIn this study, we investigated the expression and functional impact of RhoV on PDAC. Analysis of publicly available datasets and immunohistochemical profiling of 114 PDAC patient specimens were used to evaluate the expression of RhoV in PDAC and its prognostic impact. Overexpression and CRISPR-Cas9-mediated knockout of RhoV were established in three pancreatic cancer cell lines. Functional analyses, such as cell proliferation, migration, invasion, colony formation, spheroid growth, and mouse xenograft, were used to evaluate the role of RhoV in PDAC cells. ResultsRhoV overexpression was associated with reduced overall and recurrence-free survival in public datasets and our own patient cohort. Functional assays demonstrated that RhoV overexpression promoted PDAC cell proliferation, colony formation, and spheroid growth, whereas knockout of RhoV suppressed these changes. Moreover, RhoV enhanced PDAC cell migration and invasion in vitro, accompanied by downregulation of E-cadherin and upregulation of N-cadherin and vimentin, indicating induction of epithelial-mesenchymal transition. Mechanistically, RhoV overexpression activated key MAPK pathway components, including phosphorylation of ERK, JNK, and p38. In vivo, xenograft models confirmed that RhoV drives tumor growth and increases tumor burden. ConclusionThese results establish RhoV as a novel oncogenic factor in PDAC progression and highlight its potential as a biomarker and therapeutic target, warranting further investigation into combinatorial targeting strategies to overcome KRAS inhibitor resistance.

cancer biology↗

bioRxiv2025

Transfer RNA modifications during rhizome development in Oryza longistaminata

The rhizome organ endows many clonal plants with the ability to reproduce under stressful climates. Such rhizome-mediated perenniality also underlies the recent success of perennial rice breeding. Despite the importance of this organ, its developmental regulation is poorly understood. Here, using Oryza longistaminata, an emerging model for rhizome biology, we explored the involvement of tRNA modification in rhizome development. Through comparative profiling of modified nucleotides in rhizome samples at different developmental stages and/or subjected to various treatments, we identified a number of key rhizome-related tRNA modifications and revealed that, akin to the observations in many non-plant organisms, tRNA modifications are associated with hormonal signalling to regulate rhizomes responses to environmental cues. Furthermore, genome-wide analysis of tRNA-modifying genes was performed to facilitate future functional studies. These results and analyses not only deepen our understanding of rhizome development but also underscore the regulatory roles of tRNA modification in plant organ development.

plant biology↗

bioRxiv2025

Dual-LLM Adversarial Framework for Information Extraction from Research Literature

Information Extraction (IE) is a fundamental task in Natural Language Processing (NLP) that aims to automatically identify relevant information from unstructured or semi-structured data. Information extraction from lengthy research literature, particularly in multi-omics studies, faces significant challenges due to their complex narratives and extensive context. To address this, we present a novel dual-LLM adversarial framework in which one large language model (LLM) performs the extraction and another provides iterative feedback to refine the results. This process systematically reduces errors, enhances consistency across heterogeneous data sources, and converges toward more accurate outputs. We evaluated our approach against manual and single-LLM extraction, using LLMs as evaluators. Experimental results show that our adversarial framework outperforms these baselines, highlighting its effectiveness for extracting structured information from lengthy scientific texts.

bioinformatics↗

bioRxiv2025

Fluorescent protein-based ticker tapes for multiplexed recordings of transcriptional histories in single cells in culture and in vivo

Recording and imaging of promoter activities in real time is critical for deciphering cellular states and dynamic signaling crosstalk, but technologies capable of simultaneously capturing multiple transient events in living cells are lacking. Here, we custom-design fluorescent protein-based ticker tapes (FPTT) for multiplexed and longitudinal recording of physiological activities in single cells. FPTT integrates multi-spectral monomeric fluorescent proteins with self-assembling protein fibers, enabling massively parallel analysis of signaling dynamics under varying cellular conditions. Using FPTT, we were able to log dose-dependent and reversible transcriptional histories of endogenous cFos signaling in primary hippocampus neurons at a 3-hour temporal resolution via biological timestamps and an extended recording time of over 8 days. Furthermore, we expanded the imaging toolset by engineering genetically encoded FPTT variants for human NF{kappa}B, JAK/STAT3, mTOR, NFAT and cAMP signaling, allowing for the quantification of potential crosstalk between cFos and NF{kappa}B pathways in neurons, multiplexed recording of STAT3- and cAMP-specific promoters during drug-induced liver injury in mice, as well as simultaneous analysis of up to four major signaling pathways involved in experimental T-cell activation. This platform advances single-cell analysis by providing a versatile tool to investigate transcriptional histories and signaling interplay across diverse biological contexts, with broad applications in developmental biology and disease modeling.

synthetic biology↗

bioRxiv2025

A Benchmark of Evo2 Genomic AI Models for Efficient and Practical Deployment

The rapid advancement of DNA foundation language models has brought about a transformative shift in genomics, allowing for the deciphering of intricate patterns and regulatory mechanisms embedded within DNA sequences. The genomic foundation model Evo2 demonstrates remarkable capabilities in decoding DNA functional patterns through cross-species pretraining. However, despite the great potential of Evo2 in basic genomics research, there is currently no clear and systematic guidance on its specific application scenarios, performance, and optimization directions in the field of tumor genomics, and its performance dependency on specialized hardware (such as FP8 precision on H800 GPUs) has not been empirically benchmarked. Here, we present a focused validation of Evo2 using two independent cancer genomic datasets (Bladder Urothelial Carcinoma and Ovarian Cancer), we tested the downstream tasks of Evo2, including the prediction of tumor pathogenic variants and the prediction of mutational effects, and compared its performance on A100 and H800 GPUs. The results show that critical importance of FP8 precision, enabling the H800 to achieve a 4x faster inference speed than the A100 with stable accuracy (AUC 0.88-0.95). The 7B-parameter model emerged as the top performer, whereas the 40B model experienced a severe performance drop (AUC to 0.48) on non-FP8 hardware like the A100. These findings empirically validated Evo2s hardware specifications and provided practical insights for researchers implementing the model with similar computational resources. Futhermore, our findings provide a framework for the application and optimization of downstream tasks of the DNA language model Evo2 in cancer, and can guide researchers in effectively applying it in genomic studies. Key PointsO_LIHardware Precision Impact: FP8 precision on H800 GPUs is critical for Evo 2s performance, enabling 4x faster inference than A100 (without FP8 support) while maintaining high accuracy (AUC 0.88-0.95). C_LIO_LIModel Scale Optimization: The 7B-parameter model outperformed larger variants (e.g., 40B), which suffered severe accuracy drops (AUC as low as 0.48) on non-FP8 hardware, highlighting a balance between efficiency and performance. C_LIO_LIPractical Guidelines: We provide a framework for deploying Evo 2 in cancer genomics, including hardware recommendations, dataset curation, and downstream task optimization--valuable for researchers with varied computational resources. C_LI

genomics↗

bioRxiv2025

Scaling Personalized TMS: A Scalp-Based MRI-guided Alternative to Neuronavigation

BackgroundPersonalized transcranial magnetic stimulation (TMS) has shown promise in treating psychiatric and neurological disorders, but its accessibility is limited by reliance on costly and complex neuronavigation systems, particularly in resource-constrained clinical settings. ObjectiveTo develop and validate a scalp-based alternative to neuronavigation for personalized TMS targeting. MethodsWe developed a Continuous Proportional Coordinate (CPC) system-based approach for personalized TMS targeting and validated its performance through three operators across ten participants, using individualized DLPFC-SGC targets as an example. The validation framework included targeting consistency assessment, reproducibility evaluation, and cross-cortical generalizability analysis. ResultsThe CPC-based approach demonstrated comparable performance to neuronavigation, achieving 99.4% of its electric field strength (74.80 vs. 75.14 V/m; r = 0.962) and 93.9% of DLPFC-SGC functional connectivity (-0.216 vs. -0.230; r = 0.949), with high inter-operator reliability (ICC [≥] 0.903). Reproducibility analysis showed strong correlation between sessions (r = 0.948-0.957) with high reliability. Further simulations across 1,125 uniformly distributed cortical targets supported generalizability of this approach, with stable electric field preservation (99.07 {+/-} 1.54%) across different brain regions. ConclusionsThe CPC-based approach offers a practical alternative to neuronavigation, maintaining targeting accuracy and providing a more accessible option for personalized TMS implementation.

neuroscience↗