SEARCH · bioRxiv Science

Results for “cancer biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

97 records · Page 2Linked to original sources

bioRxiv2026

Nuclear Myosin VI stabilises Ku-associated DNA ends during non-homologous end joining

DNA double-strand breaks (DSBs) require rapid signalling and physical stabilisation of broken DNA ends to preserve genome integrity. Here, we identify myosin VI (MVI) as an ATM-regulated component of the DSB response. DNA damage induces rapid nuclear accumulation and nanoscale reorganisation of MVI across multiple cell models, in an ATM-dependent manner. Pharmacological or genetic perturbation of MVI attenuates {gamma}H2AX signalling and disrupts Ku80 organisation, while DNA damage persists. This leads to increased sensitivity to cisplatin and bleomycin. Super-resolution imaging reveals spatial association of MVI with Ku80-containing repair structures, implicating MVI in non-homologous end joining (NHEJ). In a minimal reconstituted system, MVI and actin enhance the proximity of Ku70/80-bound DNA ends. Together, our findings identify MVI as a regulator of DSB repair that links ATM signalling to Ku-associated DNA-end stabilisation and suggest that targeting MVI may sensitise tumour cells to genotoxic therapy.

cancer biology↗

bioRxiv2026

Heterogeneous and conserved radiation responses reveal FOXM1-dependent regulation of microcephaly genes in glioblastoma

Glioblastoma (GBM) is characterized by marked heterogeneity, glioma stem-like cells (GSCs), and resistance to therapy. Because GSCs share features with neural progenitor cells (NPCs), we investigated whether neurodevelopmental programs contribute to their response to irradiation. Transcriptional profiling of four patient-derived GSC lines revealed cell line-specific responses, with radiosensitivity correlating with the magnitude of p53 activation and basal expression of its negative regulator, MDM2. Despite this heterogeneity, radiation consistently activated p53-dependent pathways and suppressed cell-cycle programs. Among these, genes associated with primary hereditary microcephaly (MCPH) that regulate NPC proliferation were coordinately repressed. Single-cell RNA sequencing localized this response to G2/M-cycling cells. FOXM1 was similarly reduced following irradiation, emerged as a candidate regulator of a subset of MCPH genes, and correlated with their expression in GBM tumors. Pharmacological inhibition of FOXM1 reduced expression of selected MCPH genes and enhanced radiosensitivity in U251 cells. Together, these findings identify coordinated suppression of a FOXM1-associated MCPH program as part of the GBM radiation response, while suggesting that the radiosensitizing effects of pharmacological FOXM1 inhibition extend beyond this transcriptional axis.

cancer biology↗

bioRxiv2026

A Microneurosurgical Survival Platform for Elucidating Mechanisms of Brain Tumor Recurrence and Metastasis

Brain tumor recurrence remains the leading cause of mortality in neuro-oncology, and there is a lack of preclinical models replicating the clinical cycle of surgical resection and relapse. To bridge this gap, we developed a novel microneurosurgical survival platform in mice using the NICO Myriad system. We orthotopically implanted pediatric medulloblastoma cells into the mouse cerebral cortex or cerebellum, followed by longitudinal microneurosurgical resection. Bioluminescence imaging and gross fluorescence verified successful resection, local and distal recurrence and metastasis. Comparative bulk RNA sequencing revealed extensive stage-specific transcriptomic divergence alongside conserved core gene sets (2,702 genes in the cerebral cortex and 3,240 genes in the cerebellum) across primary, locally recurrent, and distally recurrent stages. Pathway analysis shows activation of cellular growth, second messenger signaling, and cellular stress adaptation pathways. Targeted qPCR validation demonstrated that post-surgical relapse is driven by a distinct molecular program: recurrent tumors downregulate primary developmental drivers (PTCH1, MYCBP2), canonical suppressors (FOS, PTEN), and chromatin regulators (HDAC2), while selectively upregulating post-transcriptional machinery (RBM8A), endosomal trafficking regulators (RAB5C), acetyltransferases (NAA15), and the m6A RNA demethylase ALKBH5. These findings reveal that medulloblastoma shifts from a primary oncogenic state toward post-transcriptional and transcriptomic survival mechanisms following surgery. Identifying persistent candidates within this conserved core framework provides a roadmap for next-generation precision immunotherapies.

cancer biology↗

bioRxiv2026

Antibody co-administration robustly improves proton therapy with radiosensitizing nanoparticles: a mathematical modeling study

Radiosensitizing nanoparticles represent a promising approach for enhancing the efficacy of proton radiotherapy; however, their performance is constrained by restricted penetration into tumor tissue, resulting in preferential perivascular accumulation. Here, we develop a spatially distributed mathematical model of a growing tumor undergoing proton therapy with intravenously administered radiosensitizing nanoparticles to investigate treatment optimization strategies. Using physiologically plausible parameter ranges informed by our own experimental measurements and published data, we demonstrate that co-administration of targeted nanoparticles with antibodies binding to the same tumor receptors can overcome transport-induced localization and promote a more uniform intratumoral redistribution of nanoparticles before irradiation. Population-level simulations across heterogeneous parameter sets suggest that moderate antibody doses consistently prolong tumor regrowth time, whereas higher antibody doses produce a pronounced and robust increase in tumor cure probability under a single high-dose irradiation regimen representative of preclinical settings. A key conceptual result of our analysis is the asymmetric risk associated with antibody co-administration. In contrast to antibody--drug conjugates, for which excessive dosing of unconjugated antibodies may severely compromise therapeutic efficacy, co-administration of antibodies with nanoparticle-based radiosensitizers constitutes a "safe-by-design" strategy with respect to tumor cell kill in the modeled single high-dose irradiation setting: although excessive antibody doses may yield suboptimal outcomes, they cannot reduce tumor cell kill below that achieved with targeted nanoparticles administered without antibodies. These findings identify antibody-mediated spatial redistribution of radiosensitizing nanoparticles as a favorable strategy that is expected to provide robust therapeutic benefit despite substantial variability in tumor characteristics.

cancer biology↗

bioRxiv2026

A COJEC-chemotherapy resistant model of Th-ALK(F1174L)/MYCN neuroblastoma offers insights into tumour immune evasion and development of the bone marrow metastatic niche

Multi-agent COJEC chemotherapy is the main-stay of induction treatment for patients diagnosed with high-risk neuroblastoma. However, at least 10% of patients will be primary refractory to chemotherapy and only 50% achieve 5-year overall survival. The bone marrow is the most frequent site of metastasis in these patients. Novel approaches are required to improve response rates but the inter- and intra- patient tumour heterogeneity and dynamics of the neuroblastoma immune microenvironment makes anticipation of resistance phenotypes incredibly challenging. We present here a novel immunocompetent C57 Bl/6 model of Th-ALK(F1174L)/MYCN neuroblastoma, in which spontaneous abdominal tumours are driven by expression of mutant Anaplastic Lymphoma Kinase and over-expression of Mycn in the neural crest. We have used this model to generate a personalised dosing schedule inducing COJEC-chemotherapy resistance, in which individual mice receive chemotherapy cycles dependent upon the progression of their neuroblastoma tumours. Using both single cell RNA sequencing and spatial immunophenotyping gave us extraordinary precision in our comprehensive analysis of the tumour intrinsic and microenvironmental factors associated with COJEC resistance. We found that the resistance phenotype was driven by Cdk8 upregulation in adrenergic and mesenchymal tumour cells. Infiltration of immunosuppressive myeloid-derived immune cells and remodeling of the tumour-associated stroma further contributed to COJEC resistance. In the bone marrow we observed expansion of neutrophils and evidence of NETosis associated with micro-metastatic disease. Our results further endorse the development of CDK8-targeting therapeutics for neuroblastoma patients which might boost the anti-tumour immune response. Additional studies will be required to define the roles of neutrophils and neutrophil NETosis in neuroblastoma progression and metastasis. Our C57 Bl/6 model will be pivotal in future preclinical studies of immune-modulating therapeutics.

cancer biology↗

bioRxiv2026

Immune-metabolic-redox ecosystems define spatially organized tumor states in head and neck squamous cell carcinoma.

Background: Spatial organization is increasingly recognized as a key determinant of tumor-immune interactions in head and neck squamous cell carcinoma (HNSCC). The GSE300147 Xenium spatial transcriptomic resource generated by McCord and colleagues established a framework for mapping spatially coordinated T-cell states in HNSCC. However, how tumor-enriched epithelial immune states relate to metabolic, redox, and stress-adaptive transcript programs remains incompletely defined. Methods: A secondary, data-driven reanalysis of GSE300147 was performed, focusing on 17 confirmed HNSCC Xenium sections after exclusion of a non-HNSCC ameloblastoma specimen. A total of 1,148,244 cells were analyzed, including 558,867 EpCAM+ tumor-enriched epithelial cells. Tumor-enriched epithelial cells were classified into Hot, Intermediate, and Cold states using a Composite Hotness framework integrating T-cell inflammatory signature score, checkpoint-associated signaling, CD274 expression, IFN/antigen-presentation signature score (IFN/AP), and tumor-immune proximity. Six metabolic ecosystem states, neighborhood profiling, spatial permutation testing, and an integrated Immune-Metabolic-Redox Ecosystem Score (IMRES) were then applied. Results: Immune activation was spatially heterogeneous across HNSCC sections. Immune-hot tumor-enriched epithelial regions showed not only inflammatory, checkpoint-associated, and antigen-presentation signature scores, but also coordinated metabolic, oxidative-redox, and stress-response transcript programs. IMRES, derived from available immune, metabolic, redox, and stress-response transcript components represented in the Xenium panel, increased progressively from Cold to Intermediate to Hot tumor-enriched epithelial states and was associated with NFE2L2, GDF15, HLA-DRA, CD274, KEAP1, and MDM2. Integrating IMRES with Composite Hotness identified a distinct Hot+IMREShigh ecosystem comprising 106,874 tumor-enriched epithelial cells. This state showed the strongest immune-active and stress-adaptive features and was positioned closer to immune populations than expected by random assignment. An alternative rank-based robustness analysis reproduced the IMRES-associated ecosystem axis and correlated with the original module-based score (Spearman r = 0.597). Conclusions: This secondary reanalysis extends the original spatial T-cell framework by defining a complementary tumor-centered immune-metabolic-redox ecosystem in HNSCC. IMRES provides a transcript-derived framework for identifying Hot+IMREShigh neighborhoods where immune activation, checkpoint signaling, metabolic remodeling, and stress adaptation converge, providing a hypothesis-generating framework for studying immune resistance and therapeutic vulnerability.

cancer biology↗

bioRxiv2026

POU2AF2/OCA-T1 coactivates POU2F2 and defines a lineage-specific dependency in diffuse large B-cell lymphoma

Lineage-restricted transcriptional programs establish cell identity and can create selective dependencies in cancer. Here, we identify POU2AF2, encoding the transcriptional co-activator OCA-T1, as a critical lineage-specific dependency in a subset of diffuse large B-cell lymphoma (DLBCL). Pan-cancer dependency analyses and patient cohorts reveal elevated POU2AF2 expression in genetically aggressive DLBCL, where its depletion markedly suppresses tumor growth in vitro and in vivo. Mechanistically, POU2AF2 cooperates with the B-cell lineage-defining transcription factor POU2F2 (OCT2) to activate lymphocyte activation gene programs through direct chromatin engagement, thereby sustaining malignant transcriptional networks. We further identified a key epigenetic regulatory axis composed of the lineage-specific transcription factor TCF3 and the histone methyltransferase SET1A-COMPASS that drives POU2AF2 expression downstream of B-cell receptor signaling. Single-cell transcriptomic analysis reveals that POU2AF2 marks and sustains an innate-like B1 B-cell population in vivo, a candidate cell of origin for lymphoma. Together, these findings define a lineage-restricted POU2AF2/POU2F2 transcriptional module, controlled by a TCF3/SET1A epigenetic network, that sustains both innate-like B-cell identity and malignant fitness in DLBCL. Our study uncovers a previously unrecognized lineage-specific transcriptional dependency and highlights POU2AF2 and its associated regulatory circuitry as potential therapeutic targets in aggressive B-cell malignancies.

cell biology↗

bioRxiv2026

An agent-based 3D model of non-genetic adaptation in cancer tissues under electrical, mechanical, and hypoxic stress

Non-genetic adaptation enables cancer cells to alter their phenotype under stress without requiring new mutations. However, the mechanisms by which electrical, mechanical, and hypoxic cues combine to shape this process in 3D tissues remain poorly understood. This work presents an agent-based tumor model that integrates vascular oxygen supply, a globally imposed electric field, mechanically mediated crowding and compression cues, phenotype transitions, cell growth, mitosis, death, and inheritance of adaptive memory across division. The simulated tumors exhibit a three-stage trajectory consisting of necrosis onset, transient collapse of live mass, and partial regrowth accompanied by progressive accumulation of adapted cells. Continuous electrical stimulation produces a dose-dependent reduction in live mass while markedly increasing the adapted fraction, with comparatively limited changes in final necrotic burden. This response is strongly conditioned by mechanics and reshapes (and is reshaped by) adaptive capacity. Pulsed stimulation further shows that, in the model, electric field amplitude and temporal schedule jointly determine memory phenomena, phenotypic diversification, and growth recovery. These results show that coupling local oxygen availability, mechanical constraints, electrical forcing, and history-dependent phenotype transitions can generate distinct tissue-level patterns of phenotypic heterogeneity. Both stimulus magnitude and temporal protocol influenced the resulting population structure, suggesting that the history of physical stress may be an important determinant of adaptive dynamics in spatially organized tumor models.

biophysics↗

bioRxiv2026

Tumor γδ T-cell abundance is associated with favorable cancer treatment outcomes

Purpose: Clinical response to immune checkpoint blockade (ICB) remains variable. We asked whether immune-cell populations in the tumor microenvironment (TME) are associated with benefit across treatments and tumor types. Experimental Design: We analyzed pretreatment bulk tumor RNA-seq from ICB cohorts and TCGA. Gene-level effects associated with ICB response or TCGA survival were projected onto Human Primary Cell Atlas profiles of 157 cell types. Cox and mixed-effects models accounted for cancer type, cohort, and therapy, as appropriate. After {gamma}{delta} T cells emerged as a leading population, we adjusted their associations for eight CD8 estimators and evaluated them using TRUST4-based TRG/TRD reconstruction and single-cell RNA-seq. Results: {gamma}{delta} T-cell programs were among the signatures consistently associated with ICB response and favorable TCGA survival. Across ICB cohorts, {gamma}{delta} T-cell abundance was associated with response (n=1,356; OR, 1.38; 95% CI, 1.23-1.56) and overall survival (n=1,074; HR, 0.82; 95% CI, 0.76-0.88), with associations persisting after CD8 adjustment. ICB-response-associated cell-type profiles were strongly concordant with chemotherapy response (r=0.92) and moderately concordant with radiation response (r=0.58); targeted and hormone therapy analyses were underpowered. TRUST4 reconstruction and single-cell RNA-seq provided orthogonal support for the {gamma}{delta} signal. Conclusions: Pretreatment {gamma}{delta} T-cell abundance was associated with favorable ICB outcomes and survival across cancers, while related cell-type programs extended to selected non-immunotherapy response settings. Although associative and context dependent, these findings support prospective evaluation of {gamma}{delta} T-cell abundance as a candidate tumor-immune biomarker.

immunology↗

bioRxiv2026

Learning and forecasting shared evolutionary pathways to multi-drug resistance across global pathogens

Infections with bacteria which have evolved multi-drug resistance (MDR) cause millions of deaths worldwide. Large-scale efforts are gathering genotypic and phenotypic data on MDR bacteria, but methods for learning the structure, diversity, and predictors of evolutionary pathways to MDR have yet to take full advantage of these data. Here, we use evolutionary accumulation modelling (EvAM), an emerging class of machine learning methods with roots in cancer progression, to infer these evolutionary pathways across ESKAPEE pathogens (seven bacterial species that dominate health burdens), using a database of over 635k genotyped phenotypic observations from around the world. We identify global patterns in MDR evolutionary pathways, remarkably shared across multiple ESKAPEE species. Species-specific deviations from these stereotypical pathways are connected with geographical and demographic covariates, facilitating predictions of future MDR evolution. We verify these predictions with several hundred new phenotypes from ESKAPEE samples spanning decades of clinical infections in sub-Saharan Africa, demonstrating the capacity to forecast future MDR evolution from these inferred shared pathways.

evolutionary biology↗

bioRxiv2026

The trade-off between parsimony and model complexity for understanding biomedical mechanisms from mathematical models

Mechanistic mathematical models have been used extensively to provide a deeper understanding of biological mechanisms, including unveiling the regulation of tumour growth and its response to various treatments. However, given the breadth of biological regulatory mechanisms, these models are frequently large and thus prone to potential issues with parameter identifiability. Statistical metrics like the Akaike and Bayesian information criteria can help identify a parsimonious model by balancing goodness of fit against model complexity. Yet simple models may fail to provide sufficient biological insight if they do not adequately capture known physiological processes or mechanisms. A modeller must therefore balance hypothesis generation and biological learning with model tractability. Here, we illustrate this balance using models of ovarian cancer growth and treatment response to cisplatin and immune checkpoint blockade in homologous recombination (HR)-deficient and HR-proficient immunocompetent mouse models. We develop a hierarchy of mathematical models of increasing complexity to describe tumour growth, treatment response, and immune dynamics. Our results highlight the limits of relying purely on statistical metrics for model selection, particularly when the goal is to obtain biological insight and underscore the importance of balancing model complexity to avoid overfitting and parameter unidentifiability.

systems biology↗

bioRxiv2026

Replication stress at centromeres biases the segregation of DNA damage

Replication-associated errors can cause DNA damage to accumulate on the newly synthesized strand over time. In specific cases such as stem cells, retention of the immortal strand used as template preserves one daughter cell into pluripotency while correlating with terminal differentiation of the damage one. In somatic cells, DNA damage distribution after mitosis remains unclear. Here, we uncovered a mechanism of non-random segregation of the DNA damage marker gH2AX occurring during a single cell division cycle. Replication stress using hydroxyurea (HU) upon release into S phase in RPE-1, BJ, hCEC D29 and fibroblasts showed reproducible Non-Random Segregation (NRS) of gH2AX in the ensuing G1, a phenotype not observed in any of the cancer cell lines analyzed. Notably, removal of R-loops led to a reduction of cells with NRS, whether RNaseH1 was over-expressed globally or exclusively targeted to centromeres, indicating that centromeric DNA-RNA hybrids contribute to NRS of the damage. In line with our previous evidence of centromeric chromatin disruption leading to R-loops, rapid removal of the histone H3 variant CENP-A causes damage and NRS, although to a lower extent than HU alone. This implies that additional mechanisms contribute to centromeric R-loops and NRS of damage in the daughter cells upon mitotic exit. Mechanistically, chemical inhibition of the catalytic activity of Rad51 led to a significant drop in NRS without a change in the total amount of damaged cells, implying involvement of the Homologous Recombination (HR) pathway to accumulation of gH2AX to only one chromatid. In turn, this affects the spindle-kinetochore with a measurable length asymmetry, inducing mechanical and/or epigenetic signals that affect the orientation of the sister chromatids on the metaphase plate to bias segregation. Altogether, we found replication-induced asymmetric segregation of DNA damage during mitosis that is influenced by centromeric R-loops, Rad51 activity and spindle dynamics, with implications on cell fate, chromosome and genome stability in the daughter cells.

cell biology↗

bioRxiv2026

Accurate detection of metagenomic strain-level associations using average nucleotide identity with StrainSpy

Genetic variation among microbial strains of the same species can profoundly influence their phenotypes, ecological functions, and impacts on human health. Traditionally, the relative abundance of a species has been used to identify associations between the microbiome and disease. However, this approach overlooks intra-species genetic variation and is susceptible to spurious correlations arising from the compositional nature of abundance data and microbial load. Fast, k-mer-based algorithms can now accurately estimate strain-level Average Nucleotide Identity (ANI) in metagenomes. Despite its value as an orthogonal metric for strain-level analysis, methods for conducting ANI-based association studies remain limited. To address this, we developed StrainSpy, a statistical algorithm that identifies associations between containment ANI and variables of interest across a wide range of study designs, including longitudinal and multi-cohort designs. Re-analysis of a study examining gut microbiota recovery in 12 healthy adults following antibiotic exposure revealed novel strain-level associations, including a reduction in strain-level diversity despite species persistence. Applying StrainSpy to a multi-cohort analysis of 3,414 colorectal cancer metagenomes identified novel strain-level associations with colorectal cancer. However, in a separate collection of microbiome-immunotherapy studies, no individual strain was consistently associated across cohorts. Importantly, across both datasets, StrainSpy informed containment ANI-based machine learning models achieved comparable accuracy to traditional abundance-based methods. StrainSpy is publicly available as an R package github.com/gtonkinhill/strainspy.

microbiology↗

bioRxiv2026

Paternal regulation of H3K4 methylation supports tumor suppressor networks in mammals intergenerationally

Paternally-inherited epigenetic information can influence phenotype in offspring (1). Here, we identify a critical mechanistic contribution of KDM6A (UTX), an X-linked histone modifier and tumor suppressor, in regulating transmissible epigenetic information in mammalian sperm. Paternal loss of KDM6A increases cancer risk in genetically wild type offspring, but how Kdm6a knockout sperm transmit this effect at the molecular level is unknown (2). We find that KDM6A functions in spermatogenesis to promote methylation of histone H3 lysine 4 (H3K4) via selective interaction with the COMPASS complex methyltransferase KMT2C (MLL3). KMT2C and KDM6A are coordinately recruited to promoters of active genes in spermatogenic cells, contrasting with recruitment to intergenic enhancers in other cell types (3, 4). Loss of KDM6A disrupts H3K4 methylation at promoters of tumor suppressor genes in spermatogonia, and some of these defects persist in epididymal sperm and correspond to impaired expression in preimplantation embryos. These genes are also misregulated in normal and malignant hematopoietic tissue of genetically wild type offspring, indicating that impaired H3K4 methylation in KDM6A-deficient male germ cells may preferentially alter regulation of tumor suppressor gene networks in development across generations.

genetics↗

bioRxiv2026

Programmable Antibody-DNA Conjugation via HUH-Tags Enables Quantitative Measurement of Receptor-Specific Adhesion Dynamics

Antibody-DNA oligonucleotide conjugates (AOCs) are widely used for molecular assembly and cellular analysis, yet current approaches for generating these conjugates often rely on nonspecific chemistries that produce heterogeneous products. Here, we present two complementary strategies for generating site-specific AOCs using covalent DNA-linking HUH endonucleases. In one approach, recombinant antibodies are genetically fused to HUH-tags to enable direct, site-specific DNA conjugation. In the second, off-the-shelf antibodies are indirectly linked to HUH-tags using a photocrosslinkable Protein G-HUH fusion, enabling covalent Fc-directed attachment. Both strategies yield homogeneous AOCs while preserving antigen binding affinity. We apply these conjugates to a DNA-based mechanochemical assay, termed rupture-and-deliver tension gauge tethers (RAD-TGTs), which converts receptor-mediated adhesion forces into intracellular delivery of a fluorescent oligonucleotide payload. By tuning duplex stability, we define adhesion dynamics across multiple mechanical regimes. Using HER2- and beta1-integrin-targeting AOCs, we identify receptor-specific adhesion signatures and uncover cooperative interactions between receptor systems in a panel of cancer cell lines. Dual-color probes enable multiplexed single-cell mechanical phenotyping, and application to primary NK cells reveals dose-dependent responses to integrin modulators. These results establish a generalizable platform for site-defined AOC generation and for quantitative, high-throughput measurement of receptor-mediated adhesion dynamics.

bioengineering↗

bioRxiv2026

From Bile Acids to a Gas-Producing Microbiome Phenotype: A Novel Mechanism of Host-Microbiome Communication

Background Microbiome-derived metabolites regulate host physiology, yet bacterial gaseous metabolites remain largely overlooked. Traditionally regarded as fermentation end-products, bacterial gases may act as biologically active mediators of host-microbiome communication. We hypothesized that bile acids regulate bacterial gaseous metabolism and influence host epithelial responses. Methods A high gas-producing clinical Escherichia coli isolate from a patient with moderately severe acute pancreatitis was cultured with selected primary and secondary bile acids. Gas production was assessed by pressure measurements, GC-TCD and GC-MS. Biological activity was evaluated by indirect exposure of Caco-2 and PANC-1 epithelial cells, followed by apoptosis/necrosis assays and whole-transcriptome RNA sequencing. Results Bile acids markedly reshaped bacterial gaseous metabolism. Cholic acid and deoxycholic acid promoted intense gas production, whereas chenodeoxycholic acid almost completely abolished it. Despite minimal apoptosis and necrosis, bacterial gaseous metabolites induced extensive transcriptional remodeling. Caco-2 cells showed stronger responses than PANC-1 cells, particularly to deoxycholic acid-derived gases, involving inflammatory signaling, extracellular matrix remodeling, epithelial plasticity, stress responses, and cancer-associated genes including PTGS2, MMP1, PLAUR, NR4A2, and SERPINE1. PANC-1 cells exhibited a more restricted response involving oxidative stress, proteostasis, and autophagy-associated pathways. Conclusions Our findings indicate that bacterial gases are a previously underrecognized class of microbiome-derived signaling molecules capable of modulating host gene expression independently of direct bacterial contact. We identify a gas-producing microbiome phenotype regulated by bile acid composition, linking microbial metabolism with epithelial signaling. These findings expand the concept of host-microbiome communication and provide a framework for investigating bacterial gaseous metabolites in intestinal and pancreatic diseases.

microbiology↗

bioRxiv2026

Genetic Disruption at the CIP2A Locus Modulates T Cell Responses and Attenuates Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) driven by pathogenic T cell-mediated inflammation. Fingolimod (FTY720), an approved therapy for MS, is an established activator of protein phosphatase 2A (PP2A). However the contribution of PP2A in autoimmune neuroinflammation remains incompletely understood. Here, we addressed this question using experimental autoimmune encephalomyelitis (EAE), a murine model of MS, in mice carrying a genetic disruption of the locus encoding cancerous inhibitor of protein phosphatase 2A (CIP2A), an endogenous inhibitor of PP2A. Mice with disruption of the CIP2A locus, the knock out (KO) mice, exhibited attenuated EAE severity compared with wild-type (WT) controls. Histological and flow-cytometric analyses revealed markedly reduced infiltration of mononuclear cells, including CD4 and CD4CXCR6 encephalitogenic T cells, in the CNS of diseased KO mice. Reduced numbers of these T cell populations were also observed in peripheral lymphoid organs of the Cip2a-deficient mice during EAE, while T cell abundance was comparable under steady-state conditions, suggesting impaired activation-induced expansion rather than altered homeostasis or migration. Single-cell RNA sequencing of CNS and lymph node immune cells revealed changes in cell-type abundance and gene expression. Notably, Il17a expression was reduced in CNS CD8+ T cells and showed a similar trend in {gamma}{delta} T cells. Together, our findings reveal that genetic disruption at the CIP2A locus attenuates EAE, possibly by limiting the expansion and accumulation of encephalitogenic T cell populations in CNS. These results identify the CIP2A locus as a previously unrecognized regulator of T cell-driven autoimmune neuroinflammation and provide new insights into mechanisms that restrain pathogenic T cell responses during EAE.

immunology↗

bioRxiv2026

Harnessing Escherichia coli motility to engineer bacterial Voronoi patterns

Cell motility drives spatial pattern formation across diverse biological systems. Here, we engineer Escherichia coli motility in semi-solid agar to control Voronoi patterns in two and three dimensions, partitioning space into regions closest to their respective inoculation seeds. Consistent with our reaction-diffusion model, we observed that collisions between expansion fronts generate either biomass depletion (''gaps'') or accumulation (''anti-gaps''), governed by the relative diffusion rates of bacteria and nutrients. By engineering strains with distinct expansion rates and tuneable motility, and by integrating these experimental data into a dynamic Voronoi model, we achieved precise control over pattern geometry. This enabled the generation of gaps with varying widths, curved boundaries, asymmetric structures, seedless regions, and complex composite patterns. Together, these findings establish bacterial Voronoi patterns as a programmable platform for engineering multicellular spatial organization, with potential applications in synthetic biology and materials science.

synthetic biology↗