- Characterized lines sourced from established biobanks, typically with existing genotype and clinical annotation
- Indicative Lead Time: 4–8 weeks to receipt and QC, subject to repository terms
iPSC-Derived Serotonergic Hindbrain Microtissue & EV Screening
ProNAMs provides screening services using iPSC-derived serotonergic hindbrain 3D microtissues and their secreted extracellular vesicles (EVs). The platform is directed at the serotonergic component of neurodegenerative disease using human genetic backgrounds rather than transgenic animal models.
Serotonergic neurons of the raphe nuclei and their function under disease-associated genetic backgrounds. Degeneration of this population occurs early in AD and is associated with neuropsychiatric symptoms including agitation, depression and sleep disturbance, which affect a substantial proportion of patients and remain an area of unmet therapeutic need. The platform supports evaluation of compounds directed at this system, and biomarker discovery from EVs secreted by these microtissues.
The Challenge
The Need for Human Models in Neuropsychiatric Symptom Research
Animal Models and Genetic Architecture: Most AD models rely on single-gene mutations drawn from familial disease. Sporadic AD, which accounts for the large majority of cases, has a polygenic architecture that these models do not represent. For neuropsychiatric endpoints specifically, cross-species translation is further complicated by the difficulty of modelling the relevant behavioral phenotypes.
2D Cultures and Neuronal Architecture: Monolayer cultures lack the three-dimensional organization and intercellular interactions that shape neuronal maturation and network formation.
Inter-Individual Heterogeneity: Patient populations vary in disease progression and in the presence and severity of neuropsychiatric symptoms. Models based on a single genetic background cannot report on that variation.
Biomarker Discovery: Non-invasive markers reflecting early CNS changes remain scarce. EVs secreted by neuronal microtissues offer one route to candidate discovery, with the important qualification set out in the EV section below.
The Platform
Microtissue–EV Dual Proteomics Platform
The platform generates iPSC-derived 5-HT hindbrain 3D microtissues from defined human genetic backgrounds, then analyses both the microtissue and its secreted EVs by proteomics. Where a cohort design is used, backgrounds can include AD donors with and without documented neuropsychiatric symptoms, alongside age-matched controls.
iPSC Line Sourcing Options
Three routes are available; the choice materially affects timeline and is made at study design.
Third-Party Repository Lines
Client-Supplied Lines
- Client's own iPSC lines, received with existing characterization
- Indicative Lead Time: 2–4 weeks for receipt, recovery and QC
Reprogramming From Donor Blood
- PBMC isolation, episomal or Sendai reprogramming, clone selection and full characterization
- Indicative Lead Time: Approx. 7–9 months to characterized line (limited to Max. 4 lines per project)
Reprogramming efficiency varies by donor, clones with karyotypic abnormalities must be discarded, and parallel differentiation of larger numbers introduces batch effects that undermine cohort comparisons. Cohort studies requiring ten or more backgrounds are better served by repository routes, which arrive with existing characterization and clinical annotation.
Differentiation and Characterization
Line QC
- Pluripotency marker expression, karyotype assessment, mycoplasma testing, and reprogramming vector clearance for lines we generate
- Indicative Duration: 3–4 weeks
Directed Differentiation
- Patterning toward hindbrain identity and serotonergic specification, followed by 3D microtissue formation and maturation
- Indicative Duration: 8–12 weeks
Microtissue Characterization
- Serotonergic identity markers including TPH2, SERT and FEV/PET-1; regional identity markers; assessment of the serotonergic fraction; morphological and viability assessment
- Indicative Duration: 3–4 weeks
Characterization results for the batches used in a study are reported alongside the data. The serotonergic fraction achieved varies between lines and batches. Inter-batch variation is a recognized constraint in iPSC-derived models. Study designs address this by differentiating comparison arms in parallel from the same reagent lots where feasible, by including a reference line across batches, and by recording batch identity in the analysis so that batch effects can be assessed rather than absorbed into the biological result.
Extracellular Vesicle Analysis
Characterization
EVs isolated from microtissue culture supernatant are characterized against the reporting framework set out in the MISEV guidelines.
| Assessment | Method | Purpose |
|---|---|---|
| Particle Concentration and Size Distribution | Nanoparticle tracking analysis (NTA) | Quantifies yield and size profile of the preparation |
| EV Protein Markers | Western blot for tetraspanins CD9, CD63 and CD81 | Confirms presence of expected EV membrane proteins |
| Negative Markers | Western blot for a non-EV cellular marker | Assesses co-isolation of non-vesicular material |
| Morphology | Transmission electron microscopy (TEM) | Confirms vesicular morphology and size range |
| Isolation Method Disclosure | Reported with the data | Isolation method affects preparation composition and must be stated for the data to be interpretable |
Scope of EV Biomarker Work
EVs secreted by these microtissues reflect the state of the cells that produced them, and comparative proteomics between disease-background and control microtissue EVs can generate candidate markers. EVs collected from culture supernatant are not equivalent to EVs in patient plasma. Plasma EVs derive from many tissues, brain-derived EVs represent a small fraction of the total, and detection requires that the marker survive transit and remain distinguishable against that background.
Candidates identified in this platform are discovery-stage candidates requiring independent validation in clinical samples - a separate program with its own methodological requirements. We describe this work as candidate biomarker discovery rather than as liquid biopsy development, because the two are separated by a validation step this platform does not perform.
Services
Service Offerings
Target and Biomarker Discovery
Comparative proteomics across disease-background and control microtissues and their secreted EVs, to identify differentially abundant proteins associated with the genetic backgrounds under study.
Phenotypic Screening
Testing of small molecules or biologics in 5-HT hindbrain microtissues against defined functional and molecular endpoints.
Mechanism of Action Studies
Mass spectrometry–based proteomic profiling of microtissues and EVs to characterize pathway-level responses to compound exposure.
Multi-Background Comparison Studies
Testing across microtissues derived from multiple genetic backgrounds, to assess whether a compound response varies with background. Where cohort composition allows, this can inform hypotheses about response heterogeneity for later evaluation in appropriately powered clinical work.
Assay Parameters
| Parameter | Typical configuration |
|---|---|
| Genetic Backgrounds per Study | Determined by the question; exploratory studies commonly use a small number of backgrounds, comparison studies more. Statistical power is discussed at design, since the number of independent backgrounds - not the number of technical replicates - governs what conclusions the data can support |
| Replicates | Multiple independent microtissues per background per condition, in addition to independent backgrounds |
| Compound Exposure | Concentration series with duration fixed at design; vehicle control and, where available, a reference compound with known activity at the target |
| Microtissue Endpoints | Viability; serotonergic marker expression; synaptic markers; proteomic profiling; additional functional endpoints by agreement |
| EV Endpoints | Yield and size distribution; marker characterization; comparative proteomics |
| Proteomics | Acquisition mode, quantification approach, and statistical thresholds for differential abundance are fixed in the protocol before analysis and stated in the report |
Workflow
Service Workflow
We ensure high-efficiency delivery from initial sample processing to final data analysis.
1
Scoping
We begin with a technical consultation to establish what the program needs the data to show. This covers the research question and endpoints, which genetic backgrounds are required and why, and which iPSC sourcing route fits the design and the timeline. Where the endpoints extend beyond what a hindbrain-derived model addresses, we say so at this point and discuss how the study might be structured across model types.
Indicative duration: 3–5 business days
2
Design & Quotation
A written protocol is prepared covering line sourcing, the differentiation plan, batch structure, concentration series, controls, endpoint selection, and the statistical approach. Statistical power is addressed here rather than at analysis, since the number of independent genetic backgrounds - not the number of microtissues per background - governs what the study can conclude. The protocol is issued for client review and proceeds on sign-off.
Indicative duration: 5–10 business days
3
Line Sourcing & QC
iPSC lines are obtained by the route agreed at design: sourced from a third-party repository, received from the client, or generated by reprogramming from donor blood. All lines are assessed on receipt or derivation for pluripotency marker expression, karyotype, and mycoplasma, with reprogramming vector clearance verified for lines we generate. This stage is normally the principal determinant of overall timeline.
Indicative duration: 2–8 weeks / approx. 7–9 months
4
Differentiation & Characterization
Qualified lines are taken through directed differentiation toward hindbrain identity and serotonergic specification, followed by 3D microtissue formation and maturation. Each batch is then characterized for serotonergic identity markers, regional identity, serotonergic fraction, morphology and viability, and assessed against pre-defined release criteria before entering the study. Comparison arms are differentiated in parallel from common reagent lots where feasible, with batch identity recorded for the analysis.
Indicative duration: 11–16 weeks
5
Study Execution
Microtissues are exposed to the test article across the agreed concentration series alongside vehicle and reference controls. Microtissues and culture supernatant are collected at the defined timepoints, EVs are isolated and characterized, and analytical acquisition proceeds for both microtissue and EV samples.
Indicative duration: 4–8 weeks, depending on design
6
Analysis & Reporting
Proteomic data is processed and evaluated against the statistical thresholds fixed in the protocol. A draft report is issued for client review, covering methods, line and batch characterization, results, statistical treatment, and the applicability domain of the data. The final report is issued following one round of client comments.
Indicative duration: 15–20 business days
Browse Deliverables & Timelines
NOTE: All timelines, replicate numbers and deliverables described on this page are indicative.
Case Study
Illustrative Case Study
A hypothetical neuromodulator, Compound X, is directed at the 5-HT pathway for neuropsychiatric symptoms in AD. It shows activity in transgenic models, but the development team needs to understand whether response varies across human genetic backgrounds before committing to trial design.
iPSC lines representing multiple backgrounds - control and sporadic AD donors, including donors with documented neuropsychiatric symptoms - are differentiated into 5-HT hindbrain microtissues under a common protocol, with serotonergic fraction characterized per line. Microtissues are exposed to Compound X across a concentration series alongside vehicle and reference controls. Microtissues and secreted EVs are collected and analyzed by LC-MS/MS.
EV Proteomic Signal
Comparative analysis of EV proteomes between backgrounds identifies proteins differing in abundance. Candidates relating to synaptic function or cellular stress responses would be taken forward as discovery-stage candidates, requiring the clinical validation step described above before any diagnostic application could be contemplated.
Response Variation Across Backgrounds
Unsupervised analysis such as principal component analysis is used to explore structure in the proteomic data and to generate hypotheses about which backgrounds group together. Whether a given background constitutes a non-responder is then assessed against endpoints and statistical criteria defined before the analysis - PCA visualizes structure, it does not test it.
Pathway-Level Interpretation
Network analysis tools such as STRING can indicate which pathways are enriched among differentially abundant proteins, and whether that enrichment is consistent with the intended mechanism. These tools annotate against known and predicted interactions; they support interpretation rather than confirm mechanism, and orthogonal experimental evidence is needed for that.
FAQ
Frequently Asked Questions
Why a hindbrain model for an Alzheimer's program?
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Because the endpoint determines the model. Serotonergic neurons of the raphe nuclei degenerate early in AD and are associated with neuropsychiatric symptoms, which affect a large proportion of patients and remain poorly served therapeutically. A hindbrain-derived model addresses that dimension directly. It does not address amyloid or tau pathology, which are forebrain phenomena - programs with those endpoints need cortical or hippocampal models.
How do you confirm the microtissues are serotonergic?
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Identity is characterized per batch by marker expression including TPH2, SERT and FEV/PET-1, together with regional identity markers. The serotonergic fraction is measured rather than assumed, and reported as a study parameter, because functional readouts are interpreted relative to how much of the tissue is the population of interest. Characterization results for the batches used in a study are supplied with the data.
How is batch-to-batch variability handled?
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It is designed around rather than eliminated. Comparison arms are differentiated in parallel from the same reagent lots where feasible, a reference line is included across batches, and batch identity is retained in the analysis so batch effects can be assessed. Where a study spans batches, this is stated in the report and reflected in the statistical approach.
Can the EV markers you identify be used as a blood test?
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Not directly. Markers identified here are discovery-stage candidates from culture supernatant. Plasma EVs come from many tissues, brain-derived EVs are a small fraction, and translation requires independent validation in clinical samples - a separate program with its own requirements. We can identify and characterize candidates, and establishing clinical detectability and specificity is downstream work this platform does not perform.
Do you follow reporting standards for EV work?
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Characterization is aligned to the MISEV reporting framework: particle concentration and size by NTA, tetraspanin markers (CD9, CD63, CD81) and a negative marker by Western blot, and morphology by TEM, with the isolation method disclosed. Characterization is performed on preparations from each study rather than referenced from historical platform data, since isolation performance varies with input material.
Can you reprogram iPSC lines from our donor samples?
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Yes, up to four lines per project, at approximately 7–9 months to a characterized line. We limit the scale deliberately: reprogramming efficiency varies by donor, karyotypically abnormal clones must be discarded, and differentiating many freshly derived lines in parallel introduces batch effects that undermine cohort comparisons. For studies needing ten or more backgrounds, repository lines are faster and arrive with existing characterization and clinical annotation.
How many genetic backgrounds does a comparison study need?
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It depends on the effect size and the question, and it is discussed at design. The relevant unit for statistical power is the number of independent backgrounds, not the number of microtissues per background - additional technical replicates improve precision within a background but do not increase the number of independent observations. We would rather set this expectation at Stage 1 than deliver a study that cannot support the conclusion the program needs.
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