Biology subjects

Xie, X.

Publications and source records attributed to Xie, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Agentic systems are adept at solving well-scoped, verifiable problems in computational biology

We introduce CompBioBench, a benchmark of 100 diverse tasks for evaluating agentic systems in computational biology. Unlike mathematics and programming, which more readily admit systematic verification, biological data are inherently noisy and open to interpretation. To enable objective evaluation without reducing tasks to prescriptive checklists, we propose a new benchmark construction strategy based on synthetic/augmented data and metadata scrambling/scrubbing of real datasets to create challenging problems that have a single ground-truth answer and require multi-step reasoning, tool use, bespoke code, and interaction with real-world external resources. The benchmark spans genomics, transcriptomics, epigenomics, single-cell analysis, human genetics, and machine learning workflows. Questions are curated by domain experts to cover a broad range of skills with varying difficulty. We evaluate leading general-purpose agentic systems starting from a bare-minimum environment, requiring them to fetch data and tools as needed to solve each problem. We find strong end-to-end performance, with Codex CLI (GPT 5.4) reaching 83% accuracy, Gemini CLI (3.1 Pro) reaching 82%, Claude Code (Opus 4.6) reaching 81%, and Claude Code (Opus 4.7) reaching 78%. On the hardest questions, Claude Code (Opus 4.6) reaches 69%, Codex CLI (GPT 5.4) reaches 59%, and Gemini CLI (3.1 Pro) reaches 49%. CompBioBench provides a practical testbed for measuring the progress of agentic systems in computational biology and for guiding future benchmark design. Data and a public leaderboard are available at https://huggingface.co/collections/Genentech/compbiobench-v1.

bioinformatics↗

bioRxiv2026

Biohybrid Robots with Embedded Conductive Fibers for Actuation, Sensing, and Closed-loop Control

Living organisms achieve adaptive actuation through the seamless integration of neural motor control circuitry and proprioceptive feedback. While biohybrid robotics aims to replicate these capabilities by merging engineered muscle with synthetic scaffolds, the field remains limited by interfaces that lack the efficiency and closed-loop regulation of natural neuromuscular systems. Here, we introduce a biohybrid muscle actuator system featuring a bioelectronic interface based on soft poly(3,4-ethylenedioxythiophene) (PEDOT) fibers for stimulation and sensing. These fibers conformally couple to muscle tissues, eliciting robust contractions at voltages as low as 1 V--requiring ultra-low power (0.376 {+/-} 0.034 mW) and preserving long-term tissue viability. By leveraging the independent addressability of these fibers, we demonstrate selective actuation of individual muscle units to achieve precise spatiotemporal control of a two-muscle-powered walking biohybrid robot, reaching a locomotion speed of 5.43 {+/-} 0.79 mm/min. When configured as strain sensors, the fibers exhibit a high gauge factor of 155.45 {+/-} 6.59 and resolve contractile displacements within tens of micrometers. We demonstrate that this sensing modality can be integrated into a closed-loop controller to autonomously modulate stimulation based on real-time feedback, significantly mitigating muscle fatigue (p = 0.038) during continuous operation. This work establishes a versatile platform for efficient actuation and intrinsic feedback sensing, providing a blueprint for efficient, autonomous, and adaptive biohybrid machines. SummarySoft conductive fibers enable a bioelectronic interface for low-power actuation and closed-loop control in biohybrid robots.

bioengineering↗

bioRxiv2026

A minimally invasive EEG recording method in mice using thin needle electrodes

Currently, implantation of electroencephalogram (EEG) electrodes in laboratory animals is time-consuming and requires specialized equipment. We present a novel method for EEG recordings in mice that utilizes thin needle electrodes. These electrodes are inserted into the skull at predetermined locations by gently pressing them against the bone surface. To ensure stable fixation of the implant, hook-shaped needles are positioned along the lateral aspects of the skull. The electrodes are connected to a multipin connector and secured to the skull using dental composite, after which the animal is allowed to recover from anesthesia. Importantly, procedures such as skull drilling and screw placement are not required, allowing the entire surgery to be completed in less than 15 minutes. Consequently, this EEG implantation approach is rapid and minimally invasive. Results of our studies indicate that EEG recordings obtained with needle electrodes are not inferior to those obtained with screw electrodes. Overall, the method is designed to enhance the accuracy and efficiency of EEG recording studies while improving animal welfare. O_LISimplifies the placement of EEG electrodes. C_LIO_LIReduces the time required for electrode implantation. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=67 SRC="FIGDIR/small/715731v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@e5608org.highwire.dtl.DTLVardef@1325ea4org.highwire.dtl.DTLVardef@1e37202org.highwire.dtl.DTLVardef@1521bb8_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Deep Learning Reveals Persistent Individual Signatures in Bat Echolocation Calls of the Greater Leaf-nosed Bat

Intraspecific variation is a prerequisite for natural selection and can manifest in various phenotypic traits, including vocal signals. However, classifying individuals based on their vocalizations, or acoustic individual identification (AIID), remains a significant challenge. This is particularly true for species that use rapidly varying echolocation calls for orientation. Here, we demonstrate that deep learning can overcome the limitation of traditional methods and reveal persistent individual signatures within bat echolocation calls. We recorded echolocation calls from 34 individuals of the greater leaf-nosed bat (Hipposideros armiger) under controlled laboratory conditions, with 19 individuals recorded repeatedly over three months. We show that a convolutional neural network (CNN) dramatically outperforms a traditional method, achieving an average identification accuracy of 84% for single calls and 91% for call sequences. In contrast, the traditional Discriminant Functional Analysis method achieved accuracies of only 39% and 47%, respectively. Through systematically altering the temporal structure of echolocation calls in input sequences, we found that temporal patterning enhances individual classification accuracy, suggesting it contributes to the encoding of individual-specific information. This study revealed that echolocation calls of H. armiger can contain stable, individual identity that were previously undetectable. Our findings highlight the potential of deep learning for non-invasive AIID and provide a methodological basis for future studies aiming to monitor animals in more dynamic environments.

zoology↗

bioRxiv2026

Chiral methionine oxidation reagents reveal stereospecific proteome modifications

Life is predicated on chirality, a molecular asymmetry akin to the left and right versions of human hands. Here we show that privileged protein residues are predisposed for chiral regulation. We developed enantiomeric oxaziridine reagents that systematically identify pro-(S) and pro-(R) methionine oxidation sites across proteomes that can be erased by stereospecific methionine sulfoxide reductase enzymes A and B, respectively. These probes reveal that chiral regulation of methionine oxidation-reduction processes can allosterically regulate protein function, as shown in cell and murine models of oxidative stress where selective (R)-methionine sulfoxide formation on M69 of biphenyl hydrolase-like protein leads to hydrolase inhibition and amplification of proteome N-homocysteinylation modifications. This work introduces a platform for characterizing sites of asymmetric methionine oxidation and the functional consequences concomitant with an individual chiral single-atom modification.

biochemistry↗

bioRxiv2026

Multi-component functionalized Bifidobacterium longum hydrogel for multi-target integrated therapy of colitis-associated anxiety and depression

Inflammatory bowel diseases (IBDs) are frequently accompanied by anxiety and depression, largely driven by perturbed gut-brain axis signaling. However, current oral therapies remain constrained by the spatial and functional separation between intestinal inflammation and central nervous system dysfunction. Here, we present a comprehensive gut-brain dual region integrated therapeutic strategy based on functionalized Bifidobacterium longum hydrogel (INPs@BL@Gel), in which baicalin and tyrosine are coordinated with Fe(III) to form infinite coordination polymers (ICPs), coated with inulin, assembled onto Bifidobacterium longum (BL), and subsequently encapsulated within a pH- and matrix metalloproteinase-responsive silk fibroin-gelatin hydrogel. INPs@BL@Gel exhibits high drug-loading, effective gastric protection, inflammation-triggered release, and long-term intestinal colonization. Within the inflamed intestine, BL and components synergistically suppress inflammatory responses, restore gut microbiota homeostasis, and promote intestinal barrier repair through multi-target integrated therapy. Importantly, BL combined with components markedly enhances the production of beneficial neuroactive metabolites such as homovanillic acid and short-chain fatty acids, which integrated regulate neuroinflammation, preserve synaptic function, and facilitate blood-brain barrier repair via the gut-brain axis. In vivo studies demonstrate that INPs@BL@Gel not only exert potent therapeutic efficacy against colitis and effectively alleviate associated depression, but also reshape the gut microbiota and restore barrier integrity, achieving an remarkable comprehensive therapeutic effect. O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/710940v1_fig1a.gif" ALT="Figure 11"> View larger version (59K): org.highwire.dtl.DTLVardef@1a831f3org.highwire.dtl.DTLVardef@1676617org.highwire.dtl.DTLVardef@15f99c1org.highwire.dtl.DTLVardef@1677cc4_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOScheme 1.C_FLOATNO (a) Schematic diagram of the design and preparation of functionalized Bifidobacterium longum hydrogel. (b) Exploration of the mechanism of INPs@BL@Gel in treating colitis-associated anxiety and depression through a dual-site multi-target synergistic strategy. C_FIG

pathology↗

bioRxiv2026

Therapeutic targeting inflammation linking periodontitis and atherosclerotic comorbidities using cell-free DNA-capturing nanomaterials

Periodontitis-associated systemic inflammation makes it a great challenge to explore therapeutic options applicable to periodontitis and atherosclerotic comorbidities. Here, we identify the crucial role of cell-free DNA (cfDNA) that underlies these comorbidities. Hypothesizing cfDNA as a therapeutic target, we engineer polyamidoamine dendrimer-functionalized nanomaterials to modulate such local-systemic inflammatory crosstalk. Periodontium-originated DNA can be systemically captured by cationic nanomaterials, and capturing cfDNA, whether locally or systemically, alleviates both periodontitis and atherosclerosis prior to severe atherosclerotic development in vivo. The transcriptomic and single-cell RNA sequencing analyses together reveal that cfDNA-capturing nanomaterials regulate inflammatory foam cell transformation in macrophages by modulating the expression of lipid-related foamy markers Spp1 and Fabp4. This study provides a proof of concept for cfDNA-driven periodontitis-atherosclerosis crosstalk, and offers a cfDNA-capturing nanoplatform for therapeutic intervention targeting periodontitis and atherosclerotic comorbidities in a holistic fashion.

immunology↗

bioRxiv2026

ALKBH5 Promotes Hepatic Gluconeogenesis via m6A-mediated Stabilization of Ogt mRNA

Excessive hepatic glucose production is a hallmark of fasting hyperglycemia in type 2 diabetes mellitus, yet the epitranscriptomic mechanisms that sustain this dysregulation remain incompletely understood. Here, we show that dexamethasone/forskolin-induced gluconeogenic activation triggers widespread remodeling of RNA m6A methylation in mouse primary hepatocytes. Among the m6A regulators examined, the demethylase ALKBH5 is robustly induced both in vitro and in fasted livers. This induction is mediated by the glucocorticoid receptor, which binds to the Alkbh5 promoter and activates its transcription. Functionally, ALKBH5 overexpression enhances gluconeogenic gene expression and glucose production, whereas both global and hepatocyte-specific Alkbh5 knockout mice exhibit suppressed hepatic gluconeogenesis. Mechanistically, we identify Ogt as a primary downstream target, defining an ALKBH5-OGT epitranscriptomic axis in hepatocytes. ALKBH5 demethylates and stabilizes Ogt mRNA, thereby elevating OGT expression and promoting gluconeogenic gene expression. Consistently, the pro-gluconeogenic effects of ALKBH5 are largely abrogated by OGT knockdown. Finally, pharmacological inhibition of ALKBH5 with 18l effectively improves glucose tolerance and suppresses hepatic gluconeogenesis in both wild-type and db/db mice. Together, these findings reveal a glucocorticoid-responsive epitranscriptomic mechanism whereby ALKBH5 stabilizes Ogt mRNA to drive gluconeogenesis and highlight ALKBH5 as a promising therapeutic target for type 2 diabetes mellitus.

molecular biology↗

bioRxiv2026

Functional and Structural Basis of Omicron BA.3.2.1 Spike

SARS-CoV-2 Omicron descendant BA.3.2, derived from BA.3 and carrying 39 additional spike substitutions, prompts concerns about altered fitness and antigenicity. Using BA.3.2.1 as a representative sublineage, we have engineered live-attenuated mNeonGreen SARS-CoV-2 encoding spikes from BA.3.2.1 and the JN.1-derived LP.8.1 and XEC, and benchmarked them against BA.3 and KP.3 in Calu-3 cells and primary human airway epithelium. BA.3.2.1 outcompetes BA.3 yet replicates more slowly than JN.1-descendants. Despite increased RBD-hACE2 affinity, BA.3.2.1 spike binds hACE2 less efficiently than LP.8.1, and shows the greatest resistance to neutralization by sera from KP.2/KP.3 infections. Cryo-EM reveals a predominantly closed, compact, asymmetric trimeric spike with a remodeled N-terminal domain, a distinct fusion-peptide-proximal region and altered N-glycosylation. BA.3.2.1 spike adopts a fine-tuned receptor-binding interface and shifted monoclonal-antibody footprints. These findings identify a trade-off between immune evasion and replication fitness driven by closed spike conformation, rationalizing BA.3.2s limited prevalence and underscoring the necessity for continued variant surveillance.

microbiology↗

bioRxiv2026

Near completely reversing the γ- to β-globin switch by enhancer release, retargeting and reinforcing

The {gamma}- to {beta}-globin switch is intricately regulated during human ontogeny, and this process is manipulated for therapeutic approaches to treat {beta}-hemoglobinopathies by activating {gamma}-globin expression. Several genetic strategies to reactivate HbF have partially reversed the {gamma}- to {beta}-globin switch and ameliorated the clinical symptoms of {beta}-hemoglobinopathies. However, whether the {gamma}- to {beta}-globin switch can be completely reversed remains unknown. Completely reversing the {gamma}- to {beta}-globin switch requires a thorough redirection of the locus control region (LCR) from interacting with the {beta}-globin gene (HBB) to interacting with the {gamma}-globin gene (HBG). Here, we found that disrupting the KLF1-mediated HBB-LCR interaction by mutating the CACCC motif in HBB leads to the release of the LCR and its retargeting to other {beta}-like globin genes. Moreover, simultaneously disrupting the KLF1-mediated HBB-LCR interaction and the epigenetic repression of HBG by combined editing of the CACCC motif in HBB and the TGACCA motif in HBG reinforces the HBG-LCR interaction, resulting in almost exclusive {gamma}-globin expression while nearly absent {beta}-globin expression, achieving near complete reversal of the {gamma}- to {beta}-globin switch. This finding demonstrates the comprehensive regulation of the {gamma}- to {beta}-globin switch by gene competition and gene silencing mechanisms. This finding also suggests that silenced genes can be fully activated through the redirection of enhancer-promoter contacts and that the specificity of enhancer-promoter contact within chromosomal domains is achieved through the transcription factor clusters binding to enhancers and promoters. Combined editing of the CACCC&TGACCA motifs also offer a more optimal therapeutic strategy for {beta}-hemoglobinopathies.

molecular biology↗

bioRxiv2026

Covalent Leader Peptide Probes Enable Proteome-Level Mapping of RiPP Enzymes beyond Biosynthetic Gene Clusters

Genome-based analyses have enabled widespread discovery and biosynthetic annotation of ribosomally synthesized and post-translationally modified peptides (RiPPs) pathways, yet often fail to capture all participating enzymes, particularly those encoded outside canonical biosynthetic gene clusters. In this study, leveraging the central role of leader peptides (LPs) in RiPP enzyme-substrate recognition, we developed a substrate-guided chemical-proteomic strategy using covalent LP probes to directly identify LP-binding enzymes from native proteomes. Using the LctA-LctM and PatE-LynD systems, we demonstrate that LP probes carrying a photocrosslinker engage enzymes at their authentic LP-recognition sites while preserving full catalytic competence. Application of this strategy to a model strain Streptomyces sparsogenes uncovered lanthipeptide synthetases encoded outside canonical biosynthetic gene clusters and revealed graded cross-cluster activities among multiple RiPP pathways. This work establishes a proof-of-concept model platform for proteome-level discovery of LP-binding RiPP enzymes and highlights cross-cluster enzymatic crosstalk as a latent mechanism for structural diversification.

biochemistry↗

bioRxiv2026

Striatal Acetylcholine Dip-Rebound Is Induced by Direct Pathway Neurons and Encodes Action-Outcome Contingency

Learning contingencies between actions and outcomes is pivotal in adaptive behavior and requires ongoing flexible sensory, motor, and reward information integration. The striatum is central to the integration. However, it remains unclear how the striatal neurons interact with each other to facilitate learning. Here we show that in the dorsomedial striatum, direct-pathway medium spiny neurons (dMSNs), but not dopamine (DA), inhibit cholinergic interneurons, inducing a characteristic acetylcholine (ACh) dip-rebound, encoding action-outcome (A-O) contingency. Using genetically encoded sensors and in vivo fiber photometry, we find that dMSN activation, ACh dip-rebound, and DA transients emerge only after mice acquire the contingency. dMSN activity and ACh dynamics persist even when rewards are probabilistic, adapt in time as the learned relationship between action and reward evolves, and vanish when the contingency is degraded. Ex vivo recordings and in vivo optogenetics further show that dMSN activity is both sufficient and required to generate the ACh dip-rebound through GABAergic inhibition of cholinergic interneurons. Disrupting the dip-rebound slows acquisition and accelerates extinction. Together, these findings reveal a previously unrecognized dMSN-ACh circuit mechanism that encodes contingency during instrumental learning, operating alongside DA signals that track reward outcomes.

neuroscience↗

bioRxiv2026

Dual Engram Architecture within a Single Striatal Cell Type Distinctly Controls Alcohol Relapse and Extinction

Relapse is a major obstacle in the treatment of alcohol and drug addiction and is thought to be driven by persistent drug-associated memories formed during their use. Behavioral therapies such as extinction training can reduce relapse and are proposed to work by creating a competing memory trace. However, where and how these opposing memories are stored in the brain is unknown. Here, we show that two anatomically and functionally distinct engram ensembles within the same genetically defined striatal cell type, direct-pathway medium spiny neurons (dMSNs), encode these opposing memories. Using engram-tagging tools in mice, we found that the acquisition of operant alcohol learning recruits a dMSN ensemble enriched in the striatal matrix compartment that stores alcohol-associated memories and whose activation selectively promotes relapse. Conversely, extinction of alcohol seeking recruits a dMSN ensemble enriched in the striosome compartment that stores extinction-related memories and whose activation suppresses relapse. Furthermore, we reveal that the physical memory trace storing the relapse-promoting memory is embedded within persistently strengthened corticostriatal synapses engaged during learning, and that artificially reproducing this plasticity is sufficient to trigger relapse-like behavior. These findings uncover a dual-engram architecture within dMSNs that governs relapse and extinction, providing a mechanistic framework for understanding how competing memories regulate drug-seeking behavior. HighlightsO_LIAcquisition and extinction of alcohol learning recruits distinct dMSN ensembles. C_LIO_LIAcquisition recruits matrix-enriched dMSN ensembles to promote relapse. C_LIO_LIExtinction recruits striosome-enriched dMSN ensembles to suppress relapse. C_LIO_LIEngram dMSNs show lasting synaptic potentiation and mimicking this potentiation triggers relapse. C_LI

neuroscience↗

bioRxiv2026

Early-Stage Corticostriatal Circuit Hyperactivity Impairs Cholinergic Function and Cognitive Flexibility in an Alzheimer's Model

Cognitive flexibility deficits are a hallmark of early-stage Alzheimers disease (AD), but the underlying circuit mechanisms remain poorly understood. Here, we show that the 5xFAD mouse model of AD neuropathology exhibited early deficits in instrumental reversal learning, indicating cognitive inflexibility preceding spatial memory deficits. This impairment was associated with excessive neuronal reactivation in the medial prefrontal cortex (mPFC) and dorsomedial striatum (DMS), key regions for goal-directed behavior. Electrophysiological recordings revealed that mPFC neurons in young 5xFAD mice were hyperexcitable and received elevated excitatory input. Moreover, the mPFC-to-direct pathway medium spiny neuron (dMSN) circuit and the dMSNs themselves were selectively hyperactive. These hyperactive dMSNs exerted increased inhibitory control over cholinergic interneurons (CINs) in the DMS, coinciding with reduced CIN firing and diminished striatal acetylcholine (ACh) release. Critically, sustained chemogenetic inhibition of the mPFC-to-DMS circuit in 5xFAD mice reduced cortical A{beta} accumulation, normalized glutamatergic transmission in both the mPFC and DMS, restored striatal ACh levels, and rescued reversal learning deficits. Together, these findings identify a hyperactive mPFC-to-DMS circuit that disrupts corticostriatal and cholinergic signaling, contributing to cognitive inflexibility in 5xFAD mice. Targeting this circuit may offer a therapeutic strategy to preserve cognitive function in the early stages of AD. HighlightsO_LI5xFAD mice exhibit early cognitive deficits in instrumental reversal learning. C_LIO_LImPFC neurons and corticostriatal circuits are hyperactive, while cholinergic neurons are hypoactive in 5xFAD mice. C_LIO_LISustained inhibition of mPFC-to-DMS circuit hyperactivity normalizes glutamatergic transmission and slows A{beta} accumulation in 5xFAD mice. C_LIO_LISustained inhibition of the mPFC-to-DMS circuit rescues reversal learning deficits in 5xFAD mice. C_LI

neuroscience↗

bioRxiv2026

BiLO: Bilevel Local Operator Learning for PDE Inverse Problems

We propose a new neural network based method for solving inverse problems for partial differential equations (PDEs) by formulating the PDE inverse problem as a bilevel optimization problem. At the upper level, we minimize the data loss with respect to the PDE parameters. At the lower level, we train a neural network to locally approximate the PDE solution operator in the neighborhood of a given set of PDE parameters, which enables an accurate approximation of the descent direction for the upper level optimization problem. The lower level loss function includes the least-square penalty of both the residual and its derivative with respect to the PDE parameters. We apply gradient descent simultaneously on both the upper and lower level optimization problems, leading to an effective and fast algorithm. The method, which we refer to as BiLO (Bilevel Local Operator learning), is also able to efficiently infer unknown functions in the PDEs through the introduction of an auxiliary variable. We provide a theoretical analysis that justifies our approach. Through extensive experiments over multiple PDE systems, we demonstrate that our method enforces strong PDE constraints, is robust to sparse and noisy data, and eliminates the need to balance the residual and the data loss, which is inherent to the soft PDE constraints in many existing methods.

systems biology↗

bioRxiv2026

Bayesian BiLO: Bilevel Local Operator Learning for Efficient Uncertainty Quantification of Bayesian PDE Inverse Problems with Low-Rank Adaptation

Uncertainty quantification in PDE inverse problems is essential in many applications. Scientific machine learning and AI enable data-driven learning of model components while preserving physical structure, and provide the scalability and adaptability needed for emerging imaging technologies and clinical insights. We develop a Bilevel Local Operator Learning framework for Bayesian inference in PDEs (B-BiLO). At the upper level, we sample parameters from the posterior via Hamiltonian Monte Carlo, while at the lower level we fine-tune a neural network via low-rank adaptation (LoRA) to approximate the solution operator locally. B-BiLO enables efficient gradient-based sampling without synthetic data or adjoint equations and avoids sampling in high-dimensional weight space, as in Bayesian neural networks, by optimizing weights deterministically. We analyze errors from approximate lower-level optimization and establish their impact on posterior accuracy. Numerical experiments across PDE models, including tumor growth, demonstrate that B-BiLO achieves accurate and efficient uncertainty quantification. MSC Classification: 65M32, 62F15, 68T07

systems biology↗

bioRxiv2026

Impacts of mutation accumulation and order on tumor initiation revealed by engineered murine colorectal cancer organoids

Tumorigenesis typically follows a multi-hit trajectory, driven by accumulating oncogenic mutations. Colorectal cancer (CRC) has long served as a paradigmatic model of multi-hit tumorigenesis, characterized by adenoma-carcinoma transition accompanied by acquisition of specific oncogene and tumor suppressor mutations. However, how the temporal order of early mutations influences CRC initiation remains poorly understood. To address this, we established a CRC tumorigenesis model using murine intestinal organoids. By introducing defined combinations of key CRC driver mutations (Kras, Apc, and Trp53) in distinct orders, we systematically investigated how the order of mutation accumulation affects tumor initiation. Our results reveal that the mutation accumulation confers growth advantages in both in vitro and in vivo models. Strikingly, mutation order also influenced the tumorigenic properties of the organoids. Whereas organoids with Trp53 loss before or after Apc loss similarly affected organoid phenotypes in vitro or tumorigenicity in immunodeficient mice, organoids with Trp53 loss preceding Apc inactivation exhibited reduced tumor-forming potential in immunocompetent mice, likely due to their distinct immunological features. Collectively, our study reveals a critical role of ordered mutation accumulation in CRC initiation, an insight that may hold clinical relevance.

cancer biology↗

bioRxiv2025

Inducible CreERT2 mouse lines for characterization of retinal bipolar cell subtypes

Bipolar cells relay visual signals from photoreceptor cells to ganglion cells in the retina. Fifteen bipolar cell subtypes have been identified in the mouse retina. These subtypes are classified as ON and OFF bipolar cells based on their response to light stimulus or rod and cone bipolar cells based on their connection to photoreceptor cells. However, the unique structural and functional role of these subtypes in the processing of visual information is not fully known due to the inadequate tools and models available for their characterization. In this study, to trace the lineage and characterize Vsx1, Lhx3, and Lhx4 - expressing bipolar cell subtypes in developing and adult mouse retina, we developed inducible Cre lines under the promoter of Vsx1, Lhx3, and Lhx4 and crossed them with ChR2EYFP reporter mice. Lineages of cells expressing Vsx1, Lhx3, and Lhx4 after Cre induction in the adult and postnatal mouse retina were then characterized. ChR2EYFP expression driven by Vsx1-CreERT2 was detected in type 2, 6, and 7 bipolar cells, Lhx3-CreERT2 in type 1b, 2, and 6 bipolar cells, and Lhx4-CreERT2 in type 2, 3, 4, and 5 bipolar cells as well as cone photoreceptor cells in the adult mouse retina. These bipolar cell subtype-specific inducible Cre mouse lines serve as efficient tools for elucidation of the mechanisms that control bipolar cell subtype development and function in the retina. Significance StatementBipolar cells are central connectors of the outer and inner retina and initiate processing of complex visual information. Bipolar cells differentiate into more than fifteen subtypes during development, and their structural diversity has been well studied. However, the unique contribution of these subtypes to the processing of visual information is poorly understood due to inadequate tools. In this study, we develop and characterize three inducible Cre mouse models for in vivo and temporally defined genetic manipulation in bipolar cell subtypes in the developing and adult mouse retina. These models serve as tools to elucidate the mechanisms that regulate the development and function of bipolar cell subtypes in the mouse retina.

neuroscience↗