Directives de soumission d'échantillons
Design the cell pairing, physical interaction, and readout package as one experiment.
Define the Interaction Before Selecting the Cells
"Organoid–immune co-culture" can describe several biologically different experiments. One project may ask whether lymphocytes recognize and damage a defined organoid model. Another may ask whether immune cells migrate through matrix and enter an organoid. A third may examine how macrophages alter epithelial state without requiring direct contact. These questions need different cell sources, culture geometries, controls, sampling times, and measurements.
For a solution-level view that places co-culture within a coordinated model, characterization, and sequencing workflow, see Organoid Research and Sequencing Solutions.
We begin by defining the interaction that the study must reveal. Is the primary event recognition, migration, infiltration, activation, sustained contact, target-cell injury, soluble signaling, or a change in cell state? We then define which compartment provides the evidence. Imaging can localize cells; flow-based or soluble-factor assays can characterize immune activation; organoid viability and death measurements can quantify injury; sequencing can distinguish the transcriptional response of each cell population. None of these readouts is treated as a substitute for all the others.
Best for
- Researching immune-cell recognition, migration, infiltration, activation, or cytotoxicity in a three-dimensional organoid context.
- Comparing autologous and controlled allogeneic pairings when donor source is part of the hypothesis.
- Evaluating T cells, peripheral blood mononuclear cells, natural killer cells, engineered immune cells, macrophages, or other project-qualified populations with compatible organoid models.
- Adding single-cell RNA sequencing when bulk measurements cannot separate organoid and immune-cell responses.
- Testing whether a defined stromal component changes interaction behavior under a controlled design.
Not for
- Inferring patient benefit, selecting a therapy, or making decisions for an individual.
- Calling an immune mechanism from organoid viability alone.
- Claiming successful infiltration from immune cells that are merely adjacent to an organoid in a two-dimensional image.
- Combining poorly documented cell sources, matrices, media, and activation procedures into an experiment that cannot be reproduced.
- Adding every available microenvironment component when the study lacks a specific comparison for each one.
Match Immune-Cell Source to the Evidence You Need
The immune-cell source changes what the experiment can mean. Autologous cells preserve donor matching and reduce the interpretive problem of alloreactivity, but they may be limited in availability, composition, expansion history, or baseline function. Allogeneic cells can support controlled donor comparisons or standardized discovery studies, yet observed activation may include recognition created by the mismatch. The page therefore does not present one source as universally better.
| Pairing route | Useful research question | Controls that matter | Interpretive boundary |
|---|---|---|---|
| Autologous organoid and immune cells | Does a matched immune population recognize or alter its corresponding organoid under the tested conditions? | Organoid-only, immune-only, baseline immune phenotype, activation control, and matched untreated or vehicle condition | Limited activity may reflect cell state, culture compatibility, antigen presentation, expansion history, or the tested window; it is not proof of biological absence. |
| Allogeneic pairing | How do qualified donor immune cells differ in migration, activation, or cytotoxicity against the same organoid model? | Multiple donor or lot records, organoid-only and immune-only controls, and a design that can expose mismatch-associated activation | Response cannot automatically be assigned to the intended target or pathway. |
| Enriched or engineered immune population | Does a defined T-cell, natural-killer-cell, macrophage, or engineered-cell preparation produce the expected functional pattern? | Identity and viability review, unmodified or reference cell control where available, organoid-only control, and a relevant positive control | Expansion, activation, transduction, storage, and recovery history can change cell state before co-culture begins. |
| Mixed immune population | Which immune subsets respond within a more complex input such as peripheral blood mononuclear cells or tumor-associated immune cells? | Input-composition profile, batch and donor metadata, subset-aware endpoints, and compartment-resolved analysis | A change in the mixture may reflect abundance shifts rather than a state change within one cell type. |
Cell type names are not sufficient intake information. The project record should capture tissue or blood source, collection and preservation route, isolation or enrichment method, activation and expansion history, engineered construct status where relevant, passage or culture history, viability, and available identity data. Ratios and cell numbers are then scoped to the assay; they are not advertised as fixed specifications because a useful effector-to-target range depends on organoid size, accessibility, growth, cell potency, and the observation window.
Choose the Physical Co-Culture Configuration
Physical configuration controls which interactions are possible. Direct contact can support recognition, synapse formation, infiltration, and cytotoxicity, but it also makes it harder to separate cell populations later. Matrix-embedded designs can test movement through a three-dimensional barrier, while compartmentalized systems can isolate soluble signaling or directional migration. The correct route follows the question rather than the visual appeal of the model.
Choose source, contact mode, matrix, and readout together; do not add complexity without a comparison it can answer.
| Configuration | Best for | What it cannot show by itself | Planning focus |
|---|---|---|---|
| Direct-contact co-culture | Recognition, sustained contact, degranulation, killing, and short-range signaling | Whether an effect requires migration through matrix or is driven only by soluble factors | Labeling strategy, imaging depth, dissociation route, cell recovery, and contact-dependent controls |
| Matrix-embedded immune cells and organoids | Three-dimensional migration, accumulation, penetration, and interaction under a defined matrix condition | Whether the same behavior persists in another matrix composition or tissue context | Matrix lot and concentration, pore and diffusion constraints, medium compatibility, and image segmentation |
| Compartmentalized or transwell configuration | Soluble-factor exchange, chemotaxis, directional migration, or comparison with direct contact | Cell–cell contact, true entry into the organoid, or local signaling at the interface | Membrane and pore selection, compartment volumes, sampling plan, and matched direct-contact comparator |
| Sequential exposure or conditioned-medium route | Separating an immune-secreted signal from concurrent physical interaction | The dynamics of reciprocal signaling during simultaneous co-culture | Collection window, normalization, carryover, storage, and a fresh-medium control |
A single project may compare two configurations when contact dependence is central to the hypothesis. It should not compare multiple geometries merely to expand the panel. Each added route consumes organoid and immune material, changes the interpretation, and requires its own controls.
Protect Both Compartments with Compatibility Controls
Organoid medium is optimized to preserve or expand the epithelial model; immune-cell medium is optimized for a different population. A compromise can change both compartments before the interaction of interest occurs. Matrix composition, cytokine supplementation, oxygen exposure, dissociation stress, and labeling procedures can introduce additional effects. A feasibility phase therefore tests whether both cell populations remain analyzable in the proposed shared condition.
- Organoid-only control: reveals medium, matrix, labeling, exposure, and time-dependent changes in the target compartment.
- Immune-only control: shows baseline survival, activation drift, aggregation, and soluble-factor release without organoids.
- Matched untreated or vehicle control: keeps handling and exposure comparable to the experimental condition.
- Immune-function control: demonstrates that the immune preparation can respond under an appropriate positive condition without assuming the organoid must trigger it.
- Organoid-injury control: confirms that the selected death, viability, or imaging endpoint can detect a meaningful change in that model.
- Contact-dependence control: uses a compartmentalized or conditioned-medium comparator when the hypothesis distinguishes direct interaction from soluble signaling.
- Donor and batch structure: prevents technical replication from being mistaken for independent biological replication.
Acceptance logic is project-defined. It can include cell recovery, organoid growth or morphology, immune-cell viability and phenotype, control separation, image quality, and the ability to recover enough analyzable cells for the planned endpoint. A pilot that fails a critical gate is documented and redesigned; it is not scaled simply because both materials are available.
Run a Gated Workflow from Feasibility to Resolution
The workflow protects scarce matched material by testing compatibility before the full condition matrix. Each stage has a review point and an agreed output.
Move from compatibility to interaction and molecular resolution through explicit gates.
- Question and pairing definition. Specify the organoid model, immune population, autologous or allogeneic logic, expected interaction, comparison unit, and RUO boundary.
- Material and identity review. Review organoid provenance and characterization, immune-cell source and preparation history, matrix and medium requirements, available quantities, and shipment or recovery constraints.
- Compatibility pilot. Test selected shared conditions, labeling or tracking route, basic recovery, imageability, control behavior, and whether both compartments can reach the intended endpoint.
- Design lock. Finalize contact configuration, ratios or cell-loading ranges, time points, treatments where applicable, biological and technical replication, controls, sampling, and predefined exclusion rules.
- Co-culture execution. Record cell lot or donor, organoid batch and passage, matrix, medium, plating, immune-cell addition, imaging, sampling, deviations, and any intermediate handling.
- Functional readout and QC. Quantify the agreed infiltration, immune activation, organoid injury, soluble-factor, or phenotype endpoints while retaining raw-image and sample-level traceability.
- Sequencing and integration. When included, process samples for single-cell or selected bulk sequencing, resolve compartment-specific states, integrate functional and molecular evidence, and report limits and next-study recommendations.
Measure Infiltration, Activation, and Organoid Injury Separately
A convincing co-culture study asks at least three different questions: Did immune cells reach or enter the organoid? Did their functional state change? Did the organoid experience measurable injury or another defined response? The answers may align, but they should not be assumed to do so.
Infiltration and Migration
Time-lapse or endpoint imaging can measure immune-cell distance from the organoid, accumulation at the boundary, entry into a defined three-dimensional region, persistence, and movement trajectories. Optical sectioning or three-dimensional reconstruction may be needed to distinguish surface attachment from internal localization. The segmentation and depth rule is established before group comparison, and fields that cannot be analyzed remain visible in the QC record.
Immune Activation
Activation may be assessed through project-selected cell-surface or intracellular markers, degranulation-associated measurements, proliferation, cell-state imaging, or soluble factors. Supernatant measurements can be useful, but they combine contributions from the entire well and may not identify the producing cell type. Immune-only controls help reveal activation caused by culture conditions, cell preparation, or a treatment rather than the organoid interaction.
Organoid Injury and Killing
Organoid response can be evaluated with longitudinal morphology, change in size or object number, membrane-integrity or apoptosis-associated signals, direct cell counts after dissociation, and compatible viability measurements. A terminal value should be interpreted with the baseline growth and control trajectory. Loss of signal may represent killing, growth arrest, detachment, segmentation failure, or assay interference; an orthogonal measurement can separate these possibilities.
The analysis preserves these endpoints as related but distinct evidence. A project-specific summary may integrate them for prioritization, but the report retains the underlying measurements and does not turn a composite score into an unsupported mechanism.
Resolve the Mixed System with Single-Cell RNA Sequencing
Bulk RNA sequencing of a co-culture blends changes in cell abundance with changes in gene expression. If immune cells accumulate while organoid cells decline, the mixed profile can shift even when the state of each remaining cell is unchanged. Single-cell RNA sequencing can separate the major compartments and selected subpopulations, provided the collection and dissociation plan preserves the cells needed to answer the question.
The sequencing design begins before co-culture. Experimental unit, biological replication, sampling time, sample multiplexing strategy, expected cell mixture, dissociation method, viability, and doublet risk all affect interpretability. The analysis can include cell-quality review, population annotation, abundance summaries, within-cell-type differential expression, state and pathway analysis, and project-defined comparisons between organoid and immune compartments. Putative ligand–receptor relationships are reported as interaction hypotheses derived from expression data, not proof of physical binding or causal signaling.
| Question | Single-cell output | Decision value | Limit |
|---|---|---|---|
| Which populations are present after co-culture? | Cell-quality metrics, annotated embedding, population abundance, and marker evidence | Shows whether the intended compartments were recovered and which subsets changed in representation | Recovery and dissociation can bias abundance; observed proportions are not automatically the original culture proportions. |
| How did immune cells respond? | Within-subset state comparison, differential expression, pathway summaries, and selected activation or exhaustion-associated programs | Separates a state change from a shift in subset composition | Expression programs require functional context and do not alone prove cytotoxic activity. |
| How did the organoid respond? | Epithelial-state annotation, stress and injury programs, antigen-presentation-associated expression, and differential pathways | Links organoid molecular response to matched imaging or injury endpoints | Sampling time and surviving-cell bias can hide earlier or terminal events. |
| Which interactions merit follow-up? | Project-defined ligand–receptor candidates and compartment-paired expression patterns | Prioritizes targeted perturbation or validation experiments | Co-expression supports a hypothesis, not directionality or causality. |
When clonotype behavior is central, immune repertoire sequencing or a compatible single-cell immune-receptor workflow can be considered. Engineered T-cell programs may also connect to our CAR-T single-cell multiomics solution. These are optional modules, not default additions. The broader organoid sequencing services page provides the available bulk, single-cell, and spatial sequencing routes when the primary question extends beyond the co-culture system.
Add Stromal Components Only When the Question Requires Them
Fibroblasts, macrophages, endothelial cells, or other stromal populations can change matrix organization, chemokine gradients, survival signals, and immune accessibility. Their inclusion can make a defined question more realistic, but every added population creates new sources of variability and new attribution problems.
A stromal component is therefore treated as a project option rather than a separate service page. We define what it is expected to change, which comparison isolates that contribution, how its identity and state will be reviewed, and whether the readout can distinguish it from organoid and immune cells. For example, adding fibroblasts may be justified when the hypothesis concerns an exclusion barrier or a stromal signaling program. Without a paired no-fibroblast condition and a way to identify fibroblast-derived signals, the extra complexity may make the result less interpretable rather than more informative.
The same principle applies to macrophage polarization, endothelial additions, and multi-cell assemblies. Labels such as "tumor microenvironment" do not remove the need for explicit cell sources, ratios, timing, controls, and compartment-aware analysis.
Receive a Compartment-Aware Evidence Package
The deliverable is organized around the study decision and the evidence contributed by each compartment. It does not end with a single percent-killing value.
- Final study design, cell-source and organoid metadata, pairing logic, culture configuration, matrix and medium records, control definitions, and deviation log.
- Organoid and immune-cell acceptance review, feasibility results, predefined analysis and exclusion rules, and sample manifest.
- Raw or agreed processed imaging references, object- and well-level summaries, infiltration or migration metrics, and image-analysis QC.
- Immune activation and soluble-factor outputs when included, with immune-only and appropriate positive-control context.
- Organoid injury, death, growth, morphology, or viability outputs with matched organoid-only controls and time information.
- Single-cell quality report, annotated cell populations, abundance summaries, within-population differential expression, pathway results, and interaction hypotheses when sequencing is included.
- Integrated condition-level summary that links functional measurements to molecular states without hiding discordant evidence.
- Limitations, unresolved observations, and project-specific recommendations for targeted validation or a next-stage sequencing study.
What We Need to Scope the Study
Provide the organoid type, source, derivation and passage history, current culture performance, matrix and medium, available characterization, and expected quantity. For immune cells, provide source, autologous or allogeneic status, isolation or enrichment method, activation or expansion history, engineered status where relevant, preservation and recovery history, available identity or phenotype data, and expected quantity. Also describe the interaction question, preferred comparison, any treatments, desired timing, and the evidence required from imaging, functional assays, sequencing, or a combination. We use this information to define the smallest design that can answer the question while preserving the material needed for confirmation.
Illustrative Organoid–Immune Co-Culture Results
These mock outputs show three complementary views of the same type of study. They contain no customer observations and establish no expected effect size or universal cutoff. Final plots depend on the cell pairing, configuration, controls, sampling plan, and measurements that pass feasibility review.
Illustrative example: distinguish approach, boundary accumulation, and internal localization.
Infiltration Trajectory Map
Matched time points can combine representative fields with cell trajectories, distance-to-organoid measurements, and a predefined depth distribution. The analysis distinguishes cells that approach the organoid from cells that remain at the boundary or enter the segmented three-dimensional region. Image quality and tracking failures remain part of the QC.
Illustrative example: interpret organoid injury beside, not instead of, immune function.
Interaction and Injury Matrix
Condition-level views can place organoid death or structural disruption beside immune activation and contact behavior. A response is advanced only with the evidence required by the question. Strong immune activation without organoid injury, or organoid injury without a matching immune signal, remains a biologically distinct result rather than being forced into one score.
Illustrative example: separate population abundance from within-population state.
Compartment-Resolved Cell Atlas
An annotated embedding can be linked to population abundance, within-cell-type differential expression, pathway summaries, and candidate interaction pairs. The report shows cell recovery and quality beside biological contrasts so a missing population is not mistaken for a true absence and a mixture shift is not mistaken for a state change.
Organoid Immune Cell Co-Culture FAQs
Can you use autologous organoids and immune cells?
Yes, when matched material and provenance are available and the proposed cell preparation is feasible. Autologous pairing reduces mismatch-associated interpretation but does not remove the need for organoid-only, immune-only, activation, and injury controls.
Can allogeneic immune cells be used?
Yes. Allogeneic cells can support donor comparisons or standardized discovery designs, but mismatch-associated activation must be considered. We document donor and lot, include appropriate controls, and avoid assigning every response to the intended target.
Which immune-cell types can be included?
Projects may consider peripheral blood mononuclear cells, enriched T or natural-killer cells, tumor-associated immune cells, engineered immune cells, macrophages, or another qualified population. Feasibility depends on source, preparation history, available amount, compatibility, and the readout needed.
Do immune cells have to touch the organoid?
No. Direct contact is appropriate for recognition, interaction, and killing questions. Compartmentalized or conditioned-medium designs are useful for soluble signaling, chemotaxis, or contact-dependence comparisons. The geometry is selected from the hypothesis.
How do you measure immune-cell infiltration?
Depending on the model, imaging can quantify distance, boundary accumulation, entry into a predefined three-dimensional region, persistence, and trajectories. Optical depth and segmentation rules are defined before comparison so surface association is not mislabeled as internal infiltration.
Is organoid viability enough to prove immune killing?
No. A viability change can reflect growth arrest, culture stress, detachment, assay interference, or direct injury. A stronger design combines organoid response with immune-function evidence, imaging, matched controls, and an orthogonal endpoint when justified.
Can single-cell RNA sequencing be added?
Yes. It is most useful when the study needs to distinguish organoid and immune-cell states, identify responding subsets, or examine changes in population composition. The collection, dissociation, replication, and sample design must be planned before co-culture.
Can you analyze immune clonotypes?
A compatible immune-repertoire or single-cell receptor workflow can be considered when clonotype expansion or persistence is central to the question and suitable material is available. It is an optional module rather than a default co-culture output.
Can fibroblasts or other stromal cells be added?
Yes, when a defined comparison tests their contribution and the analysis can distinguish their signals. Stromal cells are project-selected components; they are not added automatically or offered as separate subpages under this service.
Do you use fixed immune-cell-to-organoid ratios and time points?
No universal ratio or time point fits every system. We scope a project-defined range based on organoid size and growth, immune-cell source and potency, culture geometry, the event being measured, and material limits, then lock it after feasibility review.
Can an existing co-culture be submitted only for sequencing?
Potentially. We need the full design and sample history, cell mixture, treatments, time points, preservation route, expected viability, and biological replication. We then assess whether bulk or single-cell sequencing can answer the question without recreating the culture.
Can these results be used to choose a treatment for a patient?
No. The service supports controlled research on organoid–immune interactions and does not provide diagnosis, patient-level prediction, treatment selection, or testing for human studies.
Case Study: Direct and Indirect Organoid–Macrophage Co-Culture Separate Contact and Soluble Signaling
Source: Kakni P, Truckenmüller R, Habibović P, et al. International Journal of Molecular Sciences (2022), Figure 2.[1] This is an independent research example, not a CD Genomics customer case.
Background: Intestinal epithelial organoids reproduce important epithelial features but generally lack immune cells. The investigators needed a controllable system that could examine how macrophages and intestinal organoids influence one another while distinguishing direct cellular interaction from communication across separated compartments.
Methods: The study placed intestinal organoids and macrophages in a microwell-based platform and compared direct and indirect co-culture formats. The investigators assessed morphology and viability over time, varied macrophage input, and used inflammatory stimulation to probe interaction-dependent responses. Organoid-only and macrophage-related controls provided context for changes caused by the shared system.
Results: Figure 2 documented the direct co-culture configuration and showed organoid morphology across time and macrophage conditions. The work demonstrated that the physical arrangement and immune-cell loading were experimental variables rather than neutral details. Across the study, direct and indirect formats supported different access to cell-contact and soluble-factor questions, while longitudinal imaging helped reveal when culture compatibility changed.
Conclusion: The case supports a central design principle for service work: choose contact mode, cell input, time course, and controls before assigning meaning to an endpoint. It does not establish a universal macrophage ratio or response threshold. The independent results should be used to design project-specific feasibility and comparison logic.
Independent study figure: culture configuration, immune-cell loading, and time must stay visible when interpreting compatibility and interaction.