Biology subjects

Camp, G.

Publications and source records attributed to Camp, G..

14 recordsLinked to original sources

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

Unified Generation of Regionalized Neural Organoids from Single-Lumen Neuroepithelium

Human brain development begins with the formation of the neural tube, a neuroepithelium organized around a single continuous lumen that is patterned to specify distinct brain regions. Human pluripotent stem cell (hPSC)-derived neural organoids offer powerful models to study this process and its disruption in disease. However, most existing protocols rely on stochastic self-organization of hPSC aggregates, leading to high variability in tissue architecture and cell type composition, which limits reproducibility and fidelity to natural development. This variability has also hindered the broader adoption of brain organoid technology in translational and pharmaceutical research, where robustness and standardization are critical. Here, we present a scalable and reproducible platform that uses uniform, single-lumen neuroepithelium (SLN) as a standardized starting point for generating diverse, regionally specified neural organoids. SLNs form with high efficiency and reproducibility, can be patterned along dorso-ventral and anterior-posterior axes, and mature in suspension culture into organoids representing forebrain, midbrain, hindbrain, and neural retina. This unified and scalable approach provides a reproducible foundation for modeling human brain development, offering broad translational potential for mechanistic studies, disease modeling, and drug discovery.

developmental biology↗

bioRxiv2025

Integrated Microfluidic Platform for High-Throughput Generation of Intestinal Organoids in Hydrogel Droplets

Organoid research offers valuable insights into human biology and disease, but reproducibility and scalability remain significant challenges, particularly for epithelial organoids. Here, we present an integrated microfluidic platform that addresses these limitations by enabling high-throughput generation of uniform hydrogel microparticles embedded with intestinal stem cells. Our platform includes a cell distribution system for homogenous cell encapsulation and a microfluidic oil removal module for efficient particle transfer to aqueous media. We demonstrate the successful culture and differentiation of both healthy and tumor-derived intestinal organoids within these microparticles, achieving high homogeneity and reproducibility. This integrated microfluidic approach holds promise for scalable and standardized organoid production, with potential applications in drug screening, disease modeling, and personalized medicine.

bioengineering↗

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

Multi-omic human neural organoid cell atlas of the posterior brain

Patterning of the neural tube establishes midbrain and hindbrain structures that coordinate motor movement, process sensory input, and integrate cognitive functions. Cellular impairment within these structures underlie diverse neurological disorders, and in vitro organoid models promise inroads to understand development, model disease, and assess therapeutics. Here, we use paired single-cell transcriptome and accessible chromatin sequencing to map cell composition and regulatory mechanisms in organoid models of midbrain and hindbrain. We find that existing midbrain organoid protocols generate ventral and dorsal cell types, and cover regions including floor plate, dorsal and ventral midbrain, as well as adjacent hindbrain regions, such as cerebellum. Gene regulatory network (GRN) inference and transcription factor perturbation resolve mechanisms underlying neuronal differentiation. A single-cell multiplexed patterning screen identifies morphogen concentration and combinations that expand existing organoid models, including conditions that generate medulla glycinergic neurons and cerebellum glutamatergic subtypes. Differential abundance of cell states across screen conditions enables differentiation trajectory reconstruction from region-specific progenitors towards diverse neuron types of mid- and hindbrain, which reveals morphogen-regulon regulatory relationships underlying neuronal fate specification. Altogether, we present a single-cell multi-omic atlas and morphogen screen of human neural organoid models of the posterior brain, advancing our understanding of the co-developmental dynamics of regions within the developing human brain.

developmental biology↗

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↗

bioRxiv2023

Human neuron subtype programming through combinatorial patterning with scSeq readouts

Human neurons programmed through transcription factor (TF) overexpression model neuronal differentiation and neurological diseases. However, programming specific neuron types remains challenging. Here, we modulate developmental signaling pathways combined with TF overexpression to explore the spectrum of neuron subtypes generated from pluripotent stem cells. We screened 480 morphogen signaling modulations coupled with NGN2 or ASCL1/DLX2 induction using a multiplexed single-cell transcriptomic readout. Analysis of 700,000 cells identified diverse excitatory and inhibitory neurons patterned along the anterior-posterior and dorsal-ventral axes of neural tube development. We inferred signaling and TF interaction networks guiding differentiation of forebrain, midbrain, hindbrain, spinal cord, peripheral sympathetic and sensory neurons. Our approach provides a strategy for cell subtype programming and to investigate how cooperative signaling drives neuronal fate.

bioengineering↗

bioRxiv2023

An integrated transcriptomic cell atlas of human neural organoids

Neural tissues generated from human pluripotent stem cells in vitro (known as neural organoids) are becoming useful tools to study human brain development, evolution and disease. The characterization of neural organoids using single-cell genomic methods has revealed a large diversity of neural cell types with molecular signatures similar to those observed in primary human brain tissue. However, it is unclear which domains of the human nervous system are covered by existing protocols. It is also difficult to quantitatively assess variation between protocols and the specific cell states in organoids as compared to primary counterparts. Single-cell transcriptome data from primary tissue and neural organoids derived with guided or un-guided approaches and under diverse conditions combined with large-scale integrative analyses make it now possible to address these challenges. Recent advances in computational methodology enable the generation of integrated atlases across many data sets. Here, we integrated 36 single-cell transcriptomics data sets spanning 26 protocols into one integrated human neural organoid cell atlas (HNOCA) totaling over 1.7 million cells. We harmonize cell type annotations by incorporating reference data sets from the developing human brain. By mapping to the developing human brain reference, we reveal which primary cell states have been generated in vitro, and which are under-represented. We further compare transcriptomic profiles of neuronal populations in organoids to their counterparts in the developing human brain. To support rapid organoid phenotyping and quantitative assessment of new protocols, we provide a programmatic interface to browse the atlas and query new data sets, and showcase the power of the atlas to annotate new query data sets and evaluate new organoid protocols. Taken together, the HNOCA will be useful to assess the fidelity of organoids, characterize perturbed and diseased states and facilitate protocol development in the future.

developmental biology↗

bioRxiv2023

Single-cell epigenomic reconstruction of developmental trajectories in human neural organoid systems from pluripotency

Human cell type diversity emerges through a highly regulated series of fate restrictions from pluripotent progenitors. Fate restriction is orchestrated in part through epigenetic modifications at genes and regulatory elements, however it has been difficult to study these mechanisms in humans. Here, we use organoid models of the human central nervous system and establish single-cell profiling of histone modifications (H3K27ac, H3K27me3, H3K4me3) in organoid cells over a time course to reconstruct epigenomic trajectories governing cell identity acquisition from human pluripotency. We capture transitions from pluripotency through neuroepithelium, to retinal and brain region specification, as well as differentiation from progenitors to neuronal and glial terminal states. We find that switching of repressive and activating epigenetic modifications can precede and predict decisions at each stage, providing a temporal census of gene regulatory elements and transcription factors that we characterize in a gene regulatory network underlying human cerebral fate acquisition. We use transcriptome and chromatin accessibility measurements in the same cell from a human developing brain to validate this regulatory mode in a primary tissue. We show that abolishing histone 3 lysine 27 trimethylation (H3K27me3) through inhibition of the polycomb group protein Embryonic Ectoderm Development (EED) at the neuroectoderm stage disrupts fate restriction and leads to aberrant cell fate acquisition, ultimately influencing cell type composition in brain organoids. Altogether, our single-cell genome wide map of histone modifications during human neural organoid development serves as a blueprint (https://episcape.ethz.ch) to explore human cell fate decisions in normal physiology and in neurodevelopmental disorders. More broadly, this approach can be used to study human epigenomic trajectory mechanisms in any human organoid system. SummaryUnguided neural organoids reveal widespread and dynamic switching of epigenetic modifications during development and recapitulate fate restriction from pluripotency to terminally differentiated cells of the human central nervous system.

developmental biology↗

bioRxiv2022

A Development-Inspired Niche for Homeostatic Human Mini-Intestines

Epithelial organoids derived from intestinal tissue, also referred to as mini-intestines or mini-guts, recapitulate many aspects of the organ in vitro and can be used for biological discovery, personalized medicine, and drug development. Murine intestinal organoids represent a homeostatic system that balances stem cell maintenance within a crypt-like compartment and differentiation within a villus-like compartment1-3. However, this homeostatic balance and spatial organization has not been achieved with human intestinal organoids4. Here, we leverage single cell RNA-seq data (scRNA-seq) and high-resolution imaging to interrogate the developing human intestinal stem cell niche. We identified an EGF-family member, EPIREGULIN (EREG), as uniquely expressed in the developing crypt, and found that EREG can take the place of EGF as an in vitro niche factor. Unlike EGF, which leads to growth of thin-walled cystic organoids, EREG-organoids are spatially resolved into budded and proliferative crypt domains and a differentiated villus-like central lumen. Transcriptomics and epigenomics showed that EREG-organoids are globally similar to the native intestine while EGF-organoids have an altered chromatin landscape, downregulate the master intestinal transcription factor CDX25,6, and ectopically express stomach genes.

developmental 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↗

bioRxiv2021

Maturation of human intestinal epithelium from pluripotency in vitro

Methods to generate human intestinal tissue from pluripotent stem cells (PSCs) open new inroads into modeling intestine development and disease. However, current protocols require organoid transplantation into an immunocompromised mouse to achieve matured and differentiated epithelial cell states. Inspired by developmental reconstructions from primary tissues, we establish a regimen of inductive cues that enable stem cell maturation and epithelial differentiation entirely in vitro. We show that the niche factor Neuregulin1 (NRG1) promotes morphological change from proliferative epithelial cysts to matured epithelial tissue in three-dimensional cultures. Single-cell transcriptome analyses reveal differentiated epithelial cell populations, including diverse secretory and absorptive lineages. Comparison to multi-organ developmental and adult intestinal cell atlases confirm the specificity and maturation state of cell populations. Altogether, this work opens a new direction to use in vitro matured epithelium from human PSCs to study human intestinal epithelium development, disease, and evolution in controlled culture environments.

cell biology↗

bioRxiv2020

Cluster similarity spectrum integration of single-cell genomics data

Technologies to sequence the transcriptome, genome or epigenome from thousands of single cells in an experiment provide extraordinary resolution into the molecular states present within a complex biological system at any given moment. However, it is a major challenge to integrate single-cell sequencing data across experiments, conditions, batches, timepoints and other technical considerations. New computational methods are required that can integrate samples while simultaneously preserving biological information. Here, we propose an unsupervised reference-free data representation, Cluster Similarity Spectrum (CSS), where each cell is represented by its similarities to clusters independently identified across samples. We show that CSS can be used to assess cellular heterogeneity and enable reconstruction of differentiation trajectories from cerebral organoid single-cell transcriptomic data, and to integrate data across experimental conditions and human individuals. We compare CSS to other integration algorithms and show that it can outperform other methods in certain integration scenarios. We also show that CSS allows projection of single-cell genomic data of different modalities to the CSS-represented reference atlas for visualization and cell type identity prediction. In summary, CSS provides a straightforward and powerful approach to understand and integrate challenging single-cell multi-omic data.

bioinformatics↗

bioRxiv2019

Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains

Identification of gene expression traits unique to the human brain sheds light on the mechanisms of human cognition. Here we searched for gene expression traits separating humans from other primates by analyzing 88,047 cell nuclei and 422 tissue samples representing 33 brain regions of humans, chimpanzees, bonobos, and macaques. We show that gene expression evolves rapidly within cell types, with more than two-thirds of cell type-specific differences not detected using conventional RNA sequencing of tissue samples. Neurons tend to evolve faster in all hominids, but non-neuronal cell types, such as astrocytes and oligodendrocyte progenitors, show more differences on the human lineage, including alterations of spatial distribution across neocortical layers.

evolutionary biology↗