Biology subjects

Okuda, R.

Publications and source records attributed to Okuda, R..

9 recordsLinked to original sources

bioRxiv2026

Biological control of ion transport, redox activity, and nucleation during biogenic synthesis of CdS nanoparticles

Cells have the potential to utilize biological pathways to synthesize semiconductor nanomaterials, such as CdS quantum dots. As in chemical reaction schemes, biogenic synthesis requires control of the concentration and redox state of starting materials during the nucleation and growth of nanoparticles. Biological pathways regulate these key processes of particle synthesis, and manipulation of such pathways enables biological control of multiple aspects of nanoparticle synthesis. Here, strains of Escherichia coli were engineered to biosynthesize cadmium sulfide (CdS) quantum dots through the coordinated action of three pathways controlling sulfide generation, cadmium uptake, and nanoparticle nucleation. When exposed to low, micromolar concentrations of external cadmium, strains combining all three pathways produced CdS quantum dots. The synthesis of nanoparticles, nanoparticle yield, and nanoparticle size depended on the combination of pathways found in each strain. Cells lacking all three pathways produced no detectable nanomaterials, cells with specific combinations of one or two pathways produced small particles in the range of 1.95 to 7.9 nm, and cells with all three pathways produced the largest particles with average diameters of 11.78 nm. These results demonstrate that cells can be engineered to control multiple aspects of biogenic nanoparticle synthesis and that these pathways act together to tune the biosynthesis of semiconductor nanomaterials within cells. ImportanceMicrobes synthesize materials, including metallic and semiconductor nanomaterials. This capability stems from the natural ability of microbes to interact with and precisely manipulate metal atoms. Here, multiple biological pathways were combined within a single strain of Escherichia coli, creating a cell capable of producing CdS nanoparticles. This engineered cell controls multiple steps of particle synthesis, including metal uptake, reduction of starting materials, and binding cadmium and sulfide ions to initiate particle formation. Metal uptake by the cells was improved through the modification of a metal ion transport protein, improving cadmium uptake across the outer membrane and creating higher concentrations of cadmium within the cell. Cells with all three pathways were able to produce CdS nanoparticles, called quantum dots, even when exposed to low concentrations of external cadmium. This biotechnology enables nanomaterial synthesis under environmentally friendly conditions and may improve technologies using bacteria to clean up toxic metals.

bioengineering↗

bioRxiv2026

Chromatin landscape and epigenetic heterogeneity of acute myeloid leukemia

Acute myeloid leukemia (AML) is an aggressive hematologic cancer characterized by proliferation of immature myeloblasts. It shows profound molecular heterogeneity, which has been primarily studied through genetic abnormalities, providing the basis for disease classification, prognostication, and therapeutic choice. However, genetic factors alone may not fully explain AML pathogenesis and diversity, while leaving the role of abnormal epigenome, particularly chromatin state, largely unexplored in a large cohort of patients. Here we show that AML is classified into 16 subgroups with distinct chromatin accessibility profiles based on ATAC-seq in 1,563 AML cases, including novel AML subgroups not previously recognized in conventional genomic classifications. By integrating multi-omics analyses of genome, transcriptome, and major histone marks, we show that these epigenetic subgroups exhibit unique features in clinical presentation, gene mutations, differentiation states, gene expression, and super-enhancer profiles, which are validated across independent cohorts. Single-cell sequencing demonstrates the presence of subgroup-specific ATAC signatures that are shared by all leukemic cells, confirming the definitive role of the epigenome in the ATAC-based classification. Mechanistically, each subgroup is associated with a distinct gene regulatory network centered on key transcription factors, where subgroup-specific super-enhancers play a pivotal role. These ATAC subgroups also have prognostic significance independent of genomic classification, and help reveal unexpected drug sensitivities. In summary, ATAC-based chromatin profiling in this large sample set, combined with multi-omics data, provides new insights into AML pathogenesis beyond genomic profiling and also serves as an invaluable resource for AML research.

cancer biology↗

bioRxiv2025

An integrated platform for high-throughput phenospace learning of 3D multilineage organoid systems

Complex multilineage organoid systems lack quantitative phenotyping methods preserving spatial architecture at high throughput. Current approaches compromise biological complexity, spatial resolution, or robust homogeneous multilineage assembly. We establish an integrated experimental-computational platform for high-throughput spatial phenotyping of multilineage organoids through developing a modular tumoroid culture system incorporating pancreatic ductal adenocarcinoma (PDAC) cells and cancer-associated fibroblasts (CAFs) in 384-well format with multiplexed whole-mount imaging. We developed Phenocoder, a machine learning framework combining conditional variational autoencoders with spatial graph analysis to extract multiscale organoid features. Rigorous validation demonstrates robust performance in PDAC tumoroids. The platform identifies pathway modulators that disrupt the fibrotic microenvironment and discovers stroma-dependent vulnerabilities, undetectable in monocultures. Extending to immuno-competent tumoroids, we assess fibrosis modulators in combination with T cell bispecific antibodies, identifying treatments that enhance immune cell proliferation and infiltration inducing cancer cell death, validated in patient-derived explants. This platform establishes a generalizable framework for multilineage organoid phenotyping.

cancer biology↗

bioRxiv2025

Integrated cell atlas and tumoroids chart pancreatic cancer therapeutic targets

Pancreatic ductal adenocarcinoma (PDAC) is characterized by dense, fibroblast-rich stroma that actively shapes the tumor microenvironment. Most PDAC cases arise from conserved genetic transformations initiated by oncogenic KRAS mutations, developing into metastatic disease with high mortality rates. To chart universal PDAC cell states and identify therapeutic inroads, we integrated published single-cell transcriptomes from 200 patient samples, and used the atlas to define prevalent cancer cell and cancer-associated fibroblast (CAF) states, gene expression programs, and ligand-receptor interactions. We established modular tumoroids incorporating patient-derived cancer cells and CAFs that recapitulate aspects of ductal architecture and desmoplastic stroma. Single-cell and spatial transcriptomic profiling confirmed preservation of key cellular states and signaling networks in vitro. We identified Syndecan-1 (SDC1) as a CAF-responsive cancer cell receptor correlating with poor patient survival. Functional SDC1 blockade disrupted cancer growth in tumoroids, highlighting therapeutic relevance. This study provides a framework for dissecting cancer-stroma dynamics and identifying actionable targets using patient-derived tumoroid models.

cancer biology↗

bioRxiv2025

Rare k-mers reveal centromere haplogroups underlying human diversity and cancer translocations

Centromeres are among the most diverse and dynamically evolving regions of the human genome and are commonly affected in various human cancers. However, organized into highly repetitive -satellite higher-order repeats (HORs), human centromere sequences have long resisted detailed genomic analysis. Although the development of long-read sequencing platforms has enabled the analysis of complete centromere sequences, their application to a large set of samples is still largely limited, preventing our understanding of centromere variation and haplotype structures across large human populations and the structural basis of centromere-involving translocations in cancer. Here we show that rare k-mers present in centromeric regions can serve as effective markers for dissecting the complexity of centromere structure, particularly that of active -satellite HOR arrays (aHOR arrays), across human populations and for understanding centromere-involving abnormalities in cancer. Based on rare k-mer-based clustering, centromere aHOR arrays are clustered into discrete haplogroups (aHOR-HGs) with distinct structural features. These k-mers were also used to develop a framework that enables the inference of haplogroups in a given sample based on short-read whole genome sequencing (WGS) data (ascairn). By applying ascairn to large-scale human population datasets (n > 3,300), we revealed the diversity of aHOR-HGs and their geographic histories across populations. The rare k-mer-based approach was also applied to investigate the structure of 1p/19q co-deletion, a highly recurrent centromere-involving translocation in IDH-mutated oligodendrogliomas. Analyzing short-read WGS data from 142 cases with 1p/19q co-deletion using rare k-mers, we showed that breakpoints of 1p/19q co-deletion were mapped to aHOR arrays in chromosomes 1 (D1Z7) and 19 (D19Z3), which was validated by long-read sequencing of two 1p/19q co-deletion-positive cases. Notably, the translocation preferentially involved haplogroups composed of haplotypes containing larger regions susceptible to rearrangement. These results highlight the role of rare k-mers in dissecting the complexity of centromere sequences and their evolutionary history as well as understanding centromere-involving abnormalities associated with human diseases.

genomics↗

bioRxiv2025

High-throughput histopathology for complex in vitro models

Human complex in vitro models (CIVMs) have demonstrated remarkable potential to study tissue development, physiology and disease at high-throughput. To effectively employ these miniaturized systems in translational preclinical research, their in-depth benchmarking is pivotal. Histology has been the core of tissue characterization for centuries and the foundation of spatial phenotyping. However, standard histology workflows are inherently low-throughput and centered on large tissue pieces. This does not match the high sample volumes and small sample sizes in CIVM research. Here, we introduce a holistic histo-workflow, utilizing 3D-printed histomolds that facilitate co-planar embedding of CIVMs at high-throughput, resulting in up to 48 samples in one section. We developed a variety of model-specific histomold designs that enable spatially controlled histological sectioning and downstream analyses. We describe these workflows, including mold generation, highplex staining and image analysis, and exemplify their application to histological analyses of various CIVMs. Altogether, the histomolds introduced here afford opportunities for CIVM processing and analysis, while significantly reducing labor and reagent resources, thereby democratizing high-throughput CIVM in histopathology.

pathology↗

bioRxiv2025

Human Lung Alveolar Model with an Autologous Innate and Adaptive Immune Compartment

Lung-resident immune cells, spanning both innate and adaptive compartments, preserve the integrity of the respiratory barrier, but become pathogenic if dysregulated1. Current in vitro organoid models aim to replicate interactions between the alveolar epithelium and immune cells but have not yet incorporated lung-specific immune cells critical for tissue residency2. Here we address this shortcoming by describing human lung alveolar immuno-organoids (LIO) that contain an autologous tissue-resident lymphoid compartment, primarily composed of tissue-resident memory T cells (TRMs). Additionally, we introduce lung alveolar immuno-organoids with myeloid cells (LIOM), which include both TRMs and a macrophage-rich alveolar myeloid compartment. The resident immune cells formed a stable immune-epithelial system, frequently interacting with the epithelium and promoting a regenerative alveolar transcriptomic profile. To understand how dysregulated inflammation perturbed the respiratory barrier, we simulated T-cell-mediated inflammation in LIOs and LIOMs and used single-cell transcriptomic analyses to uncover the molecular mechanisms driving immune responses. The presence of innate cells induced a shift in T cell identity from cytotoxic to immunosuppressive, reducing epithelial cell killing and inflammation. Based on insights obtained with bulk RNA-seq data from the phase 3 IMpower150 trial, we tested whether LIOM cultures could model clinically-relevant but poorly understood pulmonary side effects caused by immunotherapies such as the checkpoint inhibitor atezolizumab3. We observed a decrease in immunosuppressive T cells and identified gene signatures that matched the transcriptomic profile of patients with drug-induced pneumonitis. Given its effectiveness in capturing outcomes and mechanisms associated with a prevalent pulmonary disease, this system unlocks opportunities for studying a wide range of immune-related pathologies in the lung.

cell biology↗

bioRxiv2024

Improvement of Antibody Affinity and Using PURE Ribosome Display and Microbial Secretion System

A method has been developed for efficiently enriching and analyzing high-affinity antibody variants by combining the PURE ribosome display (ribosome display using purified cell-free protein synthesis components) with next-generation sequencing (NGS) and the Brevibacillus choshinensis secretion system, using the NZ-1 antibody, which targets the PA tag peptide (GVAMPGAEDDVV), as a model antibody. An artificial DNA encoding the single-chain fragment of binding (scFab) of the NZ-1 antibody was synthesized and actively expressed by cell-free protein synthesis system (CFPS). Region-specific saturation mutations were introduced into the scFab gene based on its structural information. The resulting scFab library was selected against the PA tag through two rounds of PURE ribosome display, followed by Illumina sequencing to identify potential scFab variants with higher affinity. The candidates were expressed as Fab fragments using the B. choshinensis secretion system. These Fab fragments were then purified from the culture supernatant using two-step column chromatography. The binding affinity of the purified Fab was evaluated using a biolayer interferometry assay, revealing a variant Fab with higher affinity than the wild-type Fab. These results demonstrate that integrating PURE ribosome display with NGS analysis and the B. choshinensis secretion expression system enables the rapid identification and analysis of high-affinity antibody variants.

synthetic biology↗

bioRxiv2022

Reconstructing cell interactions and state trajectories in pancreatic cancer stromal tumoroids

Interlineage communication within a cancer microenvironment can augment cancer cell behaviour and impact response to therapy. Patient-derived cancer organoids provide an opportunity to explore cancer cell biology, however it is a major challenge to generate a complex cancer microenvironment in vitro. Here, we established a stromal tumoroid culture system modeling pancreatic ductal adenocarcinoma (PDAC) that reconstitutes multilineage interactions between cancer, endothelial, and fibroblast cells and recapitulates several aspects of primary tumors. Whole-mount immunohistochemistry on cleared tumoroids reveals organized vessel, desmoplastic fibroblast, and glandular cancer cell phenotypes that emerge over time. Time-course scRNA-seq measurements show that tumoroid formation activates fibroblasts, altering the extracellular matrix (ECM) composition and inducing cancer cell signal-response signatures and metabolic state change. Comparison between tumoroids with normal or cancer associated fibroblasts (CAFs) reveals different ECM compositions, as well as differential effects on cancer cell behaviors and metabolism. We identify Syndecan 1 (SDC1) and Peroxisome proliferator-activated receptor gamma (PPARG) as receptor and metabolic nodes involved in cancer cell response to CAF signals, and blocking SDC1 disrupts cancer cell growth within the tumoroid. Tumoroids from multiple PDAC patients revealed co-existence of subpopulations associated with classical and basal phenotypes, and CAF-induced migration behaviors emerged in certain patient tumoroids. Comparisons between patient tumoroids revealed a multigene migration signature that develops over time reflecting a stress response mechanism that correlates with worse clinical outcome. Altogether, stromal tumoroids can be used to explore dynamic and reciprocal interactions between cancer, CAF and endothelial cell states, and our data provides new inroads into the discovery of personalized pancreatic cancer therapies.

cancer biology↗