Toward Gigabrain: Engineering Self-Perfusing Human Brain Organoids

1. Overview

Scientific Rationale and Importance

Brain organoids became increasingly complex over the last years. We and others could show that vascularized midbrain assembloids reduce hypoxia and improve neuronal maturation (Zimmermann et al., 2025; https://www.biorxiv.org/content/10.1101/2025.08.06.668815v1). Nevertheless, even in presence of endothelial tubes and lumen formation, these vessels remain passive. They contain medium, but there is no flow. Transport is still diffusion-driven.

Diffusion is sufficient only at small scale. Once organoids increase in size, oxygen gradients reappear, metabolic stress increases and central degeneration occurs. This diffusion barrier is the fundamental bottleneck preventing scaling toward gigabrain dimensions.

In vivo, brain vasculature is dynamic. Microvessels show vasomotion driven by smooth muscle contraction and mural cell activity. Even subtle rhythmic contractions support convective mixing and stabilize oxygen distribution. Current organoid systems reproduce vascular structure but not vascular function.

We therefore propose to engineer intrinsic vascular pacemakers into brain organoids. These pacemakers consist of organized contractile smooth muscle sleeves capable of generating low-amplitude pulsatility. The aim is not to recreate a heart, but to create distributed micro-contractions that induce intraluminal mixing.

This project represents a conceptual transition: from vascularized organoids to perfused organoids. Intrinsic pulsatility will overcome diffusion limits and allow scaling toward larger and metabolically more demanding constructs.

Confirmation of Funding, Facilities, and Ethics Approvals

The proposed work builds directly on established vascularized midbrain organoid platforms in our laboratory. All required infrastructure is already available, including:

Human iPSC and organoid culture facilities
Vascular and smooth muscle differentiation pipelines
Live imaging and calcium imaging systems
Confocal microscopy
Multi-electrode array electrophysiology
Flow cytometry and transcriptomic profiling platforms

The laboratory has ongoing funding covering personnel and core facilities. The proposed project extends an already operational system and does not require new infrastructure.

All experiments will be performed under existing ethical approvals for the use of human induced pluripotent stem cells and their differentiation into neural and mesodermal derivatives. No animal transplantation experiments are planned.

Estimated Timeline

This is a focused proof-of-principle project structured in three accelerated phases:

Months 1–3:
Optimization of contractile vascular organoids

Enhancement of smooth muscle differentiation
Validation of rhythmic contraction (calcium imaging, lumen deformation)
Quantification of contraction amplitude

Months 3–6:
Integration into midbrain organoids

Generation of pulsatile vascularized brain organoids
Tracer displacement assays inside vessels
Hypoxia reduction assessment

Months 6–9:
Scaling assessment and functional validation

Moderate size increase experiments
Viability and LDH analysis
Oxygen gradient mapping
Electrophysiological stability testing

The goal within 9 months is to demonstrate measurable intraluminal pulsatility and improved transport compared to diffusion-only controls.

Data Sharing Commitment

All datasets generated during this project will be shared openly:

Transcriptomic data will be deposited in public repositories (e.g., GEO).
Analysis scripts will be shared via public Git repositories.
Imaging datasets demonstrating pulsatility and tracer dynamics will be made available upon pre-publication and publication.
Detailed protocols for generation of contractile vascular organoids will be published to ensure reproducibility.

We are committed to rapid dissemination, as solving diffusion limitations is a central challenge for the entire organoid field.

2. Introduction

Theoretical Background

Organoids have changed how we think about human brain biology. Instead of studying dissociated neurons in flat plastic, we now generate self-organizing three-dimensional tissues that recapitulate aspects of development, cytoarchitecture and cell diversity. Region-specific midbrain organoids allow modeling of dopaminergic neuron biology and Parkinson’s disease phenotypes in a human context.

Over the past years, increasing complexity has been introduced into these systems. Microglia were integrated. Vascular organoids were fused. Neurovascular unit-like interactions could be observed. Hypoxia levels were reduced compared to non-vascularized controls. This was an important step.

But still, something fundamental is missing.

The vasculature inside organoids is structural. It forms lumen. It expresses endothelial markers. It organizes with pericyte-like cells. Yet it is passive. There is no active perfusion. The vessels are filled, but not flowing.

Transport remains diffusion-driven.

Diffusion is physically limited. According to Fick’s law, transport efficiency decreases dramatically with increasing distance. This means that as organoids grow larger, oxygen and nutrient gradients inevitably appear. Even if vascular-like tubes are present, without flow they do not overcome the diffusion barrier.

In vivo, brain vasculature is dynamic. Smooth muscle cells surrounding arterioles generate vasomotion. Pericytes regulate capillary tone. Rhythmic micro-contractions contribute to convective transport and metabolic stabilization. Even small amplitude oscillations can enhance mixing beyond pure diffusion.

Current organoid approaches solve architecture, but not physiology. Microfluidic perfusion systems exist, but they require external pumps, tubing and artificial scaffolds. These approaches break the concept of a self-contained, self-organizing system. They introduce engineering complexity rather than biological autonomy.

We argue that intrinsic biological pulsatility is missing in organoid biology.

Key Literature Context

Several groups demonstrated vascularization strategies in brain organoids, including co-culture with endothelial progenitors, scaffold-based diffusion enhancement, and transplantation-induced angiogenesis. These approaches improved oxygenation and maturation, but none established intrinsic flow.

Studies on vascular organoids showed formation of endothelial tubes with smooth muscle-like coverage. However, functional rhythmic contractility has not been exploited for perfusion purposes.

In developmental biology and vascular physiology, vasomotion is recognized as an important mechanism regulating tissue perfusion. Rhythmic contraction of smooth muscle cells contributes to distribution of blood flow and metabolic matching.

Despite this knowledge, organoid systems largely ignore the mechanical dimension of vascular function.

Thus, the field currently stands at a paradox: we have vascularized organoids without vascular function.

Key publications here are:

1. Zimmermann A-S., Sabate-Soler S., et al., Schwamborn J.
“Vascularized midbrain assembloids show neuroinflammation and dopaminergic neuron vulnerability in Parkinson’s Disease.” bioRxiv (posted Aug 7, 2025).

2. Wimmer RA, Leopoldi A, Aichinger M, Kerjaschki D, Penninger JM.
“Generation of blood vessel organoids from human pluripotent stem cells.” Nature Protocols (2019).

3. Cakir B, Xiang Y, Tanaka Y, et al.
“Engineering of human brain organoids with a functional vascular-like system.” Nature Methods (2019).

4. Pham MT, Pollock KM, Rose MD, et al.
“Generation of human vascularized brain organoids.” NeuroReport (2018).

5. Cai H, et al.
“Vascular network-inspired diffusible scaffolds for engineering functional midbrain organoids.” Cell Stem Cell (2025).

Research Questions

The present study addresses the following central questions:

Can smooth muscle cells in vascular organoids be organized and matured to generate measurable rhythmic contraction?
Can such contractile elements induce intraluminal micro-flow or convective mixing inside organoid vessels?
Does intrinsic pulsatility reduce hypoxia beyond diffusion-based vascularization alone?
Can pulsatile vascularization enable scaling toward larger organoid dimensions without central degeneration?

These questions target the fundamental scaling limitation of organoid biology.

Hypotheses

H1: Enhanced differentiation and organization of vascular smooth muscle cells will lead to spontaneous or inducible rhythmic contraction within vascular organoids.

H2: Rhythmic contraction of smooth muscle sleeves will generate measurable intraluminal displacement of tracers consistent with convective mixing beyond diffusion.

H3: Organoids containing contractile vascular pacemakers will show significantly reduced hypoxia and cytotoxicity compared to non-contractile vascularized controls.

H4: Pulsatile vascularization will permit growth of larger organoids while maintaining neuronal viability and electrophysiological stability.

H5: Even if convective flow remains modest, rhythmic mechanical stimulation alone will alter endothelial and neuronal maturation profiles.

Importance of the Study

The main bottleneck in scaling brain organoids is not differentiation efficiency. It is physics. Diffusion does not scale.

If we want gigabrain systems, we must introduce active transport.

This study proposes a biologically autonomous solution. Instead of external pumps and synthetic scaffolds, we integrate distributed micro-contractions directly into the tissue. This preserves the self-organizing nature of organoids while adding a missing physiological component.

The importance of this work does not depend solely on positive outcome.

If intrinsic pulsatility works, it will represent a conceptual shift from static vascularization to functional perfusion. This would open the possibility of generating larger, more metabolically stable brain constructs and allow more realistic modeling of neurovascular and neurodegenerative diseases.

If intrinsic pulsatility does not generate measurable flow, this is equally informative. It would define the mechanical limits of biological self-perfusion and clarify whether external perfusion systems are unavoidable for scaling. Such knowledge would guide the entire field toward more rational design of complex organoid systems.

Either outcome advances understanding.

Impact Statement

Scaling organoids toward gigabrain dimensions requires more than adding cells. It requires adding physiology.

By introducing intrinsic vascular pacemakers, this project challenges the current paradigm of passive vascularization. It proposes that organoids should not only look vascularized, but behave vascularized.

Regardless of outcome, this work will clarify whether biological pulsatility is sufficient to overcome diffusion limits in three-dimensional human brain tissue models. This question is central for the future of large-scale organoid engineering.

In simple words: if we want bigger brains in a dish, we need circulation. This project tests whether we can build it from within.

3. Methods

Participants/Sample

Target sample

This is not a clinical participant study, but a cell-line based experimental study. The “participants” are human iPSC lines (healthy control as primary) and derived organoids/assembloids.

We will generate four main experimental groups:

MO (midbrain organoids; non-vascular)
MOVO (midbrain + vascular organoid fusion; non-contractile control)
cMOVO (contractile MOVO; vascular pacemaker condition)
cMOVO + pacing (optional; induced/synchronized contractility, only if needed)

Primary endpoints are functional readouts of pulsatility and transport (not only marker expression).

Inclusion criteria (iPSC lines)

Valid informed consent for iPSC derivation and differentiation into neural/mesodermal lineages
Normal karyotype (or at least no gross abnormalities; we do basic QC)
Mycoplasma negative
Robust differentiation capacity into (i) midbrain neural progenitors and (ii) vascular lineages (endothelium + mural cells)
Stable growth and passaging behavior (no “crazy” slow growing lines)

Exclusion criteria (iPSC lines)

Karyotype abnormalities that correlate with differentiation artefacts
Recurrent contamination / mycoplasma
Lines that repeatedly fail to form organoids (high batch-to-batch collapse)
Lines that produce vascular organoids without lumen formation (we need lumen; otherwise no point)

Recruitment strategy

We will use existing in-house iPSC lines already established under approved consent. This is not “recruiting humans”, it is sourcing cell lines with correct consent. No patient recruitment is required for the 9-month proof-of-principle.

Sample size justification (incl. power analysis)

Because this is a proof-of-principle with multiple readouts (imaging-based functional endpoints), the unit of analysis is organoid/assembloid with batch as random effect. We will avoid pseudo-replication by doing ≥3 independent differentiation batches (biological replicates) per condition.

Planned n (core endpoints):

Batches: 3 independent batches (minimum), ideally 4 if timing allows
Organoids per batch per condition: 10–12
Total per condition: 30–36 organoids

Power logic (pragmatic):
We are expecting large effects if the concept works (tracer displacement detectable vs essentially none; hypoxia area reduction). For a conservative power estimate, we assume:

two-sided α = 0.05
target power 80%
effect size in the “medium-to-large” range (Cohen’s d ~0.8) for quantitative outcomes like hypoxia coverage, LDH normalization, lumen diameter oscillation amplitude.

With n ≈ 30 per group, a d~0.8 effect is typically detectable with adequate power in simple comparisons, and with mixed models (batch random effect) we still remain reasonably powered because within-batch n is high and variance is estimatable. If the true effect is smaller (d~0.5), the 9-month frame becomes a pilot anyway, but still informative.

We also apply a two-stage approach to prevent wasting months:

Stage 1 (Month 1–4): small pilot n=6 per condition per batch (x2 batches) to confirm feasibility and variance
Stage 2 (Month 4–9): expand to full n only if the pulsatility + tracer signal is measurable

So the “power analysis” is combined with feasibility gating, which is realistic for organoids where variance is sometimes not friendly.

Materials and Procedures

Overview of experimental workflow

Generate midbrain organoids (MO) using established protocol (NESC-based)
Generate vascular organoids (VO) from iPSCs
Engineer contractile VO (“vascular pacemaker units”) by enhancing mural smooth muscle differentiation and organization
Fuse MO + VO in ECM droplet to form MOVO
Quantify: pulsatility → tracer movement → hypoxia/viability → functional neuronal readouts

Cell culture and differentiation

Midbrain organoids (MO):

Start from NESCs derived from iPSCs
Aggregate 6,000 cells / well (ULA plates)
Patterning and maturation media changes as per established midbrain organoid workflows
Embedding in Matrigel at defined stage (day aligned to fusion)
Culture on orbital shaker after embedding (typical 70–80 rpm), because static culture will create non-comparable gradients

Vascular organoids (VO):

iPSC aggregates in vascular differentiation medium under hypoxic conditions early (5% O₂ typical)
Growth factor schedule to drive endothelial and mural lineages
VO are used at the time window where lumen-forming endothelial networks are present

Contractile vascular organoids (cVO):
This is the key engineering step. We will push mural differentiation toward smooth muscle-like contractile phenotype:

Adjust TGFβ / PDGF signaling to increase αSMA+ sleeve formation
Enrichment of circumferential organization by ECM composition tuning (Matrigel/collagen ratio, stiffness window)
Optional: metabolic maturation (longer culture, lactate selection if helpful)
Functional screening: calcium imaging + time-lapse brightfield to detect spontaneous oscillations

We do not claim “artery” formation. We claim contractile sleeves around lumen structures, enough to create low amplitude rhythmic constriction.

Fusion / assembloid generation

At defined days (aligned across MO and VO), one MO + one VO are co-embedded in ~30 µL ECM droplet
Polymerize at 37°C, then transfer to 24-well plates
Culture in midbrain maturation medium (or compatible co-culture medium if required for mural cell maintenance)
Shaker culture for standardization
For pacing condition: apply mild pacing trigger only if spontaneous contractility is too stochastic (see IF-THEN below)

Functional readouts (replication-ready detail)

(A) Pulsatility quantification (primary functional endpoint)

Live imaging: time-lapse (phase contrast or confocal if labeled)
Measure lumen diameter over time at multiple vessel segments (≥5 segments per organoid)
Output: oscillation amplitude, frequency, regularity index

(B) Intraluminal transport / micro-flow

Inject or soak fluorescent tracer (e.g., dextran 70kDa and/or 10kDa)
Optional microbeads (0.5–2 µm) to track displacement
Time-lapse imaging of tracer distribution inside lumen structures
Output: displacement velocity, mixing index, penetration depth vs time

(C) Hypoxia and viability

Hypoxia probe staining (pimonidazole-based)
LDH release assay normalized by organoid area/volume
Output: % hypoxic area, LDH/size, necrotic core fraction

(D) Neuronal functionality (secondary)

MEA recordings for spontaneous activity (mean firing rate, spikes, active electrodes)
Optional immunostaining for TH/MAP2/GFAP and vascular markers (CD31, VE-cadherin, αSMA) to confirm composition in the same batch

Data collection setting

All cultures maintained in standard incubators (37°C, 5% CO₂; defined O₂ where relevant)
Imaging on confocal + live-cell time-lapse station
Data stored immediately to structured lab server folders (batch → condition → organoid ID)

Planned Analyses

Analysis pipeline (preprocessing)

QC & exclusion at organoid level (pre-registered rules):
- If organoid collapses structurally before readout → exclude (technical failure)
- If no lumen structures are detectable in MOVO/cMOVO → exclude from flow analysis but keep for “failure rate” reporting
- If contamination detected → exclude entire batch, repeat batch (documented)
Image preprocessing:
- Drift correction for time-lapse
- Segmentation of lumen boundaries (semi-automated + manual QC)
- Extract diameter time series and tracer intensity profiles
- Compute oscillation parameters using FFT/peak detection with fixed settings across groups
Normalization:
- LDH normalized by organoid area/volume
- Hypoxia area as % of total section area
- Tracer/microbead measures normalized by imaging duration and pixel-to-µm calibration

Statistical models and tests

Primary comparisons use linear mixed-effects models with:
- fixed effect: condition (MO vs MOVO vs cMOVO)
- random effect: batch
- optional random effect: line (if >1 iPSC line used)
For non-normal distributions:
- transform (log or rank-based) or use generalized mixed models
Multiple comparisons:
- control using Tukey or FDR depending on endpoint family

Hypothesis-specific predictions

H1 (contractility): cVO and cMOVO show higher oscillation amplitude and frequency vs MOVO (near-baseline).
H2 (transport): tracer displacement/mixing index is significantly increased in cMOVO vs MOVO.
H3 (hypoxia): hypoxia area % and LDH/size decrease in cMOVO vs MOVO, and both better than MO.
H4 (scale proxy): cMOVO tolerates increased size (area/diameter) at comparable viability vs MOVO.

Contingent decisions (IF–THEN)

IF spontaneous pulsatility is absent in ≥70% of cVO in pilot batches, THEN we introduce synchronized stimulation (pharmacologic mild trigger or optogenetic pacing, depending what is already available).
IF lumen segmentation fails due to low contrast, THEN we switch to endothelial fluorescent labeling for live imaging (stable line or transient labeling), and repeat only the imaging step (not full differentiation).
IF tracer remains mostly extraluminal (leakage), THEN we quantify barrier integrity markers (VE-cadherin continuity) and adjust maturation window before measurement.
IF variance is high (CV > 40%) in key endpoint in Stage 1, THEN we increase number of batches rather than number of organoids per batch (because batch is the real biology).
IF cMOVO shows improved transport but no hypoxia benefit, THEN we interpret as “mixing without tissue penetration” and include additional oxygen-sensing readout near lumen-adjacent regions.

Ethics and Data Management

Ethical approval status / plan

All work is performed with human iPSC lines under existing institutional ethics approvals and consent for reprogramming and differentiation into neural and mesodermal lineages. No new donor recruitment is planned. No animal transplantation is included. If a new biobank line is added, we will ensure consent scope matches the planned differentiation and data sharing (de-identified).

Confidentiality measures

iPSC lines are coded with non-identifiable IDs
No directly identifying donor data is stored in project folders
Access restricted to authorized lab members
Any metadata shared publicly will be de-identified and consent-compatible

Data sharing / archiving plan

Raw and processed quantitative datasets (hypoxia %, LDH normalized values, pulsatility time series, tracer displacement metrics) will be deposited in a public repository at publication (or earlier if the call requests fast release).
Transcriptomics (if generated within 9 months) will go to GEO (or equivalent).
Analysis scripts (R/Python) will be shared via Git repository with versioning.
Imaging datasets: representative time-lapse videos and key stacks will be shared as curated subsets plus metadata to enable reuse (full raw imaging may be large, but we will provide enough for replication and re-analysis).

We will report negative outcomes also, because in organoids this is sometimes the most honest data.

4. Pilot Data (Optional)

The following pilot data are derived from our previously established vascularized midbrain assembloid system (preprint; Zimmermann, Sabate-Soler et al., 2025)

These data are not part of the present proposed study, but they demonstrate feasibility of the core biological components on which this project is built.

We clearly separate what is already shown and what is new.

Structural Vascularization Is Feasible and Reproducible

In Zimmermann et al., 2025, we demonstrated that fusion of vascular organoids with midbrain organoids results in:

CD31-positive endothelial networks
VE-cadherin-positive adherens junctions
Collagen IV-positive basement membrane structures
αSMA-positive mural cell elements
Tubular organization with lumen formation

Importantly, endothelial cells organize in a vessel-like manner and form interconnected networks

This establishes that:

Lumen structures can be formed reproducibly in vitro
Mural/smooth muscle-like cells are already present in the system
The structural prerequisites for introducing contractile sleeves are biologically realistic

This is crucial. We are not building something from zero. The vascular scaffold is already there.

Reduced Hypoxia in Vascularized Assembloids

Using hypoxia probe staining, we showed that vascularized midbrain organoids (MOVOs) display:

Significantly reduced hypoxic regions compared to non-vascularized controls
Reduced LDH release (lower cytotoxicity)
Increased overall size compared to MOs

This demonstrates that:

Even diffusion-based vascular structures improve metabolic conditions
The system tolerates increased tissue mass when vascularized

However, and this is central, the improvement occurs without active perfusion. Transport is still diffusion-driven.

Thus, the pilot data show partial solution. But diffusion limits remain.

This directly motivates the new step: add pulsatility.

Functional and Morphological Maturity

In the preprint, we further demonstrated:

Increased morphological complexity of microglia in vascularized assembloids
More elaborate endothelial processes
Enhanced neurotrophic signaling signatures
Detectable electrophysiological activity via MEA
Disease-relevant phenotypes in PD context

These results demonstrate that:

The vascular system is not inert decoration
It functionally interacts with neuronal and glial compartments
The system is sufficiently stable for advanced functional readouts

Therefore, adding contractile dynamics will be introduced into a system that is already biologically active and measurable, not a fragile prototype.

Evidence That Smooth Muscle Elements Are Present

αSMA-positive cells were detectable along vessel-like structures

While rhythmic contraction was not quantified in the preprint, the presence of mural elements indicates that:

Smooth muscle differentiation capacity exists
The system already contains a partial contractile machinery
Optimization of organization and maturation is realistic

This informs feasibility of Aim 1 (engineering contractile vascular pacemakers).

Variance Estimates Informing Power

From quantitative analyses in the preprint (hypoxia area, LDH release, electrophysiology), we observed:

Clear separation between MO and MOVO conditions
Batch-consistent effects across biological replicates
Variability in the moderate range typical for organoid systems

Effect magnitudes for hypoxia reduction and LDH normalization were in a range that would correspond to medium-to-large standardized effects.

This informed the current power assumptions (d ~0.8 for metabolic endpoints), and justifies the projected sample size of ~30 organoids per condition across ≥3 batches for the main study.

Thus, our power estimation is not speculative, it is grounded in actual prior variance behavior of this platform.

What Is NOT Yet Demonstrated (Gap Statement)

To be very clear:

The preprint does not demonstrate:

Rhythmic lumen diameter oscillation
Intraluminal tracer displacement
Convective transport beyond diffusion
Size expansion beyond current vascularized state

These are precisely the novel components of the present proposal.

The pilot data demonstrate:

Structural vascularization
Reduced hypoxia
Functional neurovascular interaction
Platform stability and scalability

The main study now tests whether adding organized contractile sleeves converts structural vascularization into functional micro-perfusion.

Feasibility Summary

The preprint provides strong feasibility evidence for:

Robust generation of vascularized midbrain assembloids
Reproducible metabolic and functional readouts
Presence of mural/smooth muscle-like elements
Quantifiable hypoxia and viability endpoints

Therefore, the proposed work is not speculative engineering. It is a logical extension of an already operational vascular organoid system.

In simple words:
We already built vessels.
Now we make them move.

5. Budget

All personnel costs (PI, postdoctoral researcher, technical staff, data analysis) will be fully covered in-kind by existing institutional funding. We are therefore requesting support exclusively for consumables required to execute the 9-month proof-of-principle phase.

The total requested budget is 25,000 €.

This amount is calculated conservatively and is sufficient to complete the core experiments required to test intrinsic vascular pulsatility and functional transport. The budget is flexible and may be adjusted internally depending on pilot-phase results.

Cell Culture and Organoid Generation

Approximately 11,000 € are allocated for stem cell maintenance and differentiation consumables.

This includes:

iPSC maintenance media and supplements
Neural and vascular differentiation media components
Growth factors required for midbrain patterning and vascular lineage induction (e.g., VEGF-A, FGF-2, BMP4, BDNF, GDNF, IL-34, GM-CSF)
Small molecules for developmental signaling control (e.g., CHIR, SB, LDN, DAPT, SAG)
ECM materials (Matrigel / Geltrex / collagen blends) for embedding and fusion
Ultra-low attachment plates, multiwell plates, and sterile plastics

Organoid work is media-intensive and growth-factor heavy. These costs reflect approximately three to four full biological batches across conditions.

Vascular Pacemaker Engineering

Approximately 3,000 € are allocated to optimize smooth muscle differentiation and assess contractility.

This includes:

Additional mural cell–promoting factors (PDGF-BB, TGFβ variants)
Calcium-sensitive dyes and live imaging reagents
Mild pharmacological modulators for testing inducible pulsatility

This budget is designed to allow iteration if initial differentiation does not yield sufficient contractile amplitude.

Functional Transport and Hypoxia Assays

Approximately 6,000 € are allocated for functional validation.

This includes:

Fluorescent tracers of different molecular weights (dextran variants)
Fluorescent microbeads for displacement tracking
Hypoxia probe kits
LDH cytotoxicity assays
Core antibodies for structural validation (CD31, VE-cadherin, αSMA, TH, MAP2, etc.)
Secondary antibodies and mounting reagents

Imaging and Electrophysiological Consumables

Approximately 3,000 € are allocated for imaging-compatible consumables and electrophysiology materials.

This includes:

Live-imaging culture dishes and chamber slides
Coatings and consumables for MEA recordings
Minor data storage expansion if required

No equipment purchase is requested. All microscopes, incubators, MEA systems, and computational infrastructure are already available in the laboratory.

Contingency Reserve

A modest 2,000 € internal buffer is embedded within the above allocations to account for repetition of a failed batch or replacement of unstable reagents. Organoid systems are biologically complex, and a small flexibility margin is necessary to maintain experimental continuity.

Summary

The requested 25,000 € will fully cover all consumables required to:

Engineer contractile vascular organoids
Integrate them into midbrain assembloids
Quantify pulsatility and intraluminal transport
Assess hypoxia and viability outcomes

All personnel and infrastructure are provided in-kind.

This is a focused, cost-efficient proof-of-principle study designed to determine whether intrinsic vascular pacemakers can convert structural vascularization into functional micro-perfusion within brain organoids.

6. References

1. Zimmermann AS et al., Vascularized midbrain assembloids show neuroinflammation and dopaminergic neuron vulnerability in Parkinson’s Disease.” bioRxiv

2. Morizane, R. et al. Nephron organoids derived from human pluripotent stem cells model kidney development and injury. Nat Biotechnol 33, 1193–1200 (2015).

3. Broutier, L. et al. Culture and establishment of self-renewing human and mouse adult liver and pancreas 3D organoids and their genetic manipulation. Nat Protoc 11, 1724–1743 (2016).

4. Lancaster, M. A. & Knoblich, J. A. Organogenesis in a dish: modeling development and disease using organoid technologies. Science 345, (2014).

5. Lindborg, B. A. et al. Rapid Induction of Cerebral Organoids From Human Induced Pluripotent Stem Cells Using a Chemically Defined Hydrogel and Defined Cell Culture Medium. Stem Cells Transl Med 5, 970–979 (2016).

6. Lancaster, M. A. et al. Cerebral organoids model human brain development and microcephaly. Nature 501, 373–379 (2013).

7. Birey, F. et al. Assembly of functionally integrated human forebrain spheroids. Nature 545, 54–59 (2017).

8. Monzel, A. S. et al. Derivation of Human Midbrain-Specific Organoids from Neuroepithelial Stem Cells. Stem Cell Reports 8, 1144–1154 (2017).

9. Smits, L. M., et al. Modeling Parkinson’s disease in midbrain-like organoids. NPJ Parkinsons Dis 5, (2019).

10. Modamio, J. et al. Synaptic decline precedes dopaminergic neuronal loss in human midbrain organoids harboring a triplication of the SNCA gene. bioRxiv 2021.07.15.452499 (2021) doi:10.1101/2021.07.15.452499.

11. Jo, J. et al. Midbrain-like Organoids from Human Pluripotent Stem Cells Contain Functional Dopaminergic and Neuromelanin-Producing Neurons. Cell Stem Cell 19, 248–257 (2016).

12. Sabate-Soler, S. et al. Microglia integration into human midbrain organoids leads to increased neuronal maturation and functionality. Glia 70, 1267–1288 (2022).

13. Stehbens, W., Wakefield, J. S., Gilbert-Barness, E. & Zuccollo, J. Histopathology and ultrastructure of human umbilical blood vessels. Fetal Pediatr Pathol 24, 297–315 (2005).

14. Pugsley, M. K. & Tabrizchi, R. The vascular system. An overview of structure and function. J Pharmacol Toxicol Methods 44, 333–340 (2000).

15. Ruhrberg, C. & Bautch, V. L. Neurovascular development and links to disease. Cellular and Molecular Life Sciences 70, 1675 (2013).

16. McConnell, H. L., Kersch, C. N., Woltjer, R. L. & Neuwelt, E. A. The translational significance of the neurovascular unit. Journal of Biological Chemistry 292, 762–770 (2017).

17. Bell, R. D. et al. Pericytes control key neurovascular functions and neuronal phenotype in the adult brain and during brain aging. Neuron 68, 409–427 (2010).

18. Cai, H. et al. Vascular network-inspired diffusible scaffolds for engineering functional midbrain organoids. Cell Stem Cell 32, 824–837.e5 (2025).

19. Wimmer, R. A., Leopoldi, A., Aichinger, M., Kerjaschki, D. & Penninger, J. M. Generation of blood vessel organoids from human pluripotent stem cells. Nature Protocols 2019 14:11 14, 3082–3100 (2019).

20. Nickels, S. L. et al. Reproducible generation of human midbrain organoids for in vitro modeling of Parkinson’s disease. Stem Cell Res 46, (2020).

21. von Bartheld, C. S., Bahney, J. & Herculano-Houzel, S. The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting. Journal of Comparative Neurology 524, 3865–3895 (2016).

22. Smajic, S. et al. Single-cell sequencing of human midbrain reveals glial activation and a Parkinson-specific neuronal state. Brain 145, 964–978 (2022).

23. Sierra, A. et al. The “Big-Bang” for modern glial biology: Translation and comments on Pío del Río-Hortega 1919 series of papers on microglia. Glia 64, 1801–1840 (2016).

24. Hamerman, J. A. et al. Cutting edge: inhibition of TLR and FcR responses in macrophages by triggering receptor expressed on myeloid cells (TREM)-2 and DAP12. J Immunol 177, 2051–2055 (2006).

25. Turnbull, I. R. et al. Cutting edge: TREM-2 attenuates macrophage activation. J Immunol 177, 3520–3524 (2006).

26. Ulrich, J. D. et al. Altered microglial response to Aβ plaques in APPPS1-21 mice heterozygous for TREM2. Mol Neurodegener 9, (2014).

27. Dzamk, N. Cytokine activity in Parkinson’s disease. Neuronal Signal 7, (2023).

28. Bergmann, S. et al. Blood-brain-barrier organoids for investigating the permeability of CNS therapeutics. Nat Protoc 13, 2827–2843 (2018).

29. Pham, M. T. et al. Generation of human vascularized brain organoids. Neuroreport 29, 588–593 (2018).

30. Miller, J. S. et al. Rapid casting of patterned vascular networks for perfusable engineered three-dimensional tissues. Nat Mater 11, 768–774 (2012).

31. Mansour, A. A. et al. An in vivo model of functional and vascularized human brain organoids. Nature Biotechnology 2018 36:5 36, 432–441 (2018).

32. Wörsdörfer, P. et al. Generation of complex human organoid models including vascular networks by incorporation of mesodermal progenitor cells. Sci Rep 9, 1–13 (2019).

33. Wörsdörfer, P., Rockel, A., Alt, Y., Kern, A. & Ergün, S. Generation of Vascularized Neural Organoids by Co-culturing with Mesodermal Progenitor Cells. STAR Protoc 1, (2020).

34. Nashimoto, Y. et al. Integrating perfusable vascular networks with a three-dimensional tissue in a microfluidic device. Integrative Biology (United Kingdom) 9, 506–518 (2017).

35. Sun, X. Y. et al. Generation of vascularized brain organoids to study neurovascular interactions. Elife 11, e76707 (2022).

36. Ahn, Y. et al. Human blood vessel organoids penetrate human cerebral organoids and form a vessel-like system. Cells 10, (2021).

37. Giannotta, M., Trani, M. & Dejana, E. VE-cadherin and endothelial adherens junctions: active guardians of vascular integrity. Dev Cell 26, 441–454 (2013).

38. Lancaster, M. A. et al. Cerebral organoids model human brain development and microcephaly. Nature 501, 373–379 (2013).

39. Beauchamp, P. et al. Development and Characterization of a Scaffold-Free 3D Spheroid Model of Induced Pluripotent Stem Cell-Derived Human Cardiomyocytes. Tissue Eng Part C Methods 21, 852–861 (2015).

40. Ramachandran, S. D. et al. In Vitro Generation of Functional Liver Organoid-Like Structures Using Adult Human Cells. PLoS One 10, (2015).

41. Qian, X. et al. Sliced Human Cortical Organoids for Modeling Distinct Cortical Layer Formation. Cell Stem Cell 26, 766 (2020).

42. Cakir, B. et al. Engineering of human brain organoids with a functional vascular-like system. Nat Methods 16, 1169–1175 (2019).

43. Leventhal, C., Rafii, S., Rafii, D., Shahar, A. & Goldman, S. A. Endothelial trophic support of neuronal production and recruitment from the adult mammalian subependyma. Mol Cell Neurosci 13, 450–464 (1999).

44. Rymo, S. F. et al. A two-way communication between microglial cells and angiogenic sprouts regulates angiogenesis in aortic ring cultures. PLoS One 6, (2011).

45. Li, J. et al. Astrocyte_to_astrocyte contact and a positive feedback loop of growth factor signaling regulate astrocyte maturation. Glia 67, 1571 (2019).

46. Klement, W. et al. A pericyte-glia scarring develops at the leaky capillaries in the hippocampus during seizure activity. Epilepsia 60, 1399–1411 (2019).

47. Chen, A. Q. et al. Microglia-derived TNF-α mediates endothelial necroptosis aggravating blood brain–barrier disruption after ischemic stroke. Cell Death Dis 10, (2019).

48. Yousef, H. et al. Aged blood impairs hippocampal neural precursor activity and activates microglia via brain endothelial cell VCAM1. Nat Med 25, 988 (2019).

49. Achyuta, A. K. H. et al. A modular approach to create a neurovascular unit-on-a-chip. Lab Chip 13, 542–553 (2013).

50. Pediaditakis, I. et al. Modeling alpha-synuclein pathology in a human brain-chip to assess blood-brain barrier disruption. Nat Commun 12, (2021).

51. Morrison, H., Young, K., Qureshi, M., Rowe, R. K. & Lifshitz, J. Quantitative microglia analyses reveal diverse morphologic responses in the rat cortex after diffuse brain injury. Scientific Reports 2017 7:1 7, 1–12 (2017).

52. Yang, R. et al. Regulation of microglial process elongation, a featured characteristic of microglial plasticity. Pharmacol Res 139, 286–297 (2019).

53. Cengiz, P. et al. Developmental differences in microglia morphology and gene expression during normal brain development and in response to hypoxia-ischemia HHS Public Access. Neurochem Int 127, 137–147 (2019).

54. Harry, G. J., Kraft, A. D., Harry, G. J. & Kraft, A. D. Microglia in the developing brain: a potential target with lifetime effects. Neurotoxicology 33, 191–206 (2012).

55. Tsuji-Tamura, K. & Ogawa, M. Morphology regulation in vascular endothelial cells. Inflammation and Regeneration 2018 38:1 38, 1–13 (2018).

56. Liang, J. et al. Endothelial Cell Morphology Regulates Inflammatory Cells Through MicroRNA Transferred by Extracellular Vesicles. Front Bioeng Biotechnol 8, 369 (2020).

57. Iadecola, C. & Anrather, J. The immunology of stroke: from mechanisms to translation. Nat Med 17, 796 (2011).

58. Perego, C., Fumagalli, S. & De Simoni, M.-G. Temporal pattern of expression and colocalization of microglia/macrophage phenotype markers following brain ischemic injury in mice. J Neuroinflammation 8, 174 (2011).

59. Gilks, W. P. et al. A common LRRK2 mutation in idiopathic Parkinson’s disease. Lancet 365, 415–416 (2005).

60. Usmani, A., Shavarebi, F. & Hiniker, A. The Cell Biology of LRRK2 in Parkinson’s Disease. Mol Cell Biol 41, e00660–20 (2021).

61. Chen, Y. et al. G2019S LRRK2 Mutation Enhances MPP+-Induced Inflammation of Human Induced Pluripotent Stem Cells-Differentiated Dopaminergic Neurons. Front Neurosci 16, 947927 (2022).

62. Walter, J. et al. The Parkinson’s-disease-associated mutation LRRK2-G2019S alters dopaminergic differentiation dynamics via NR2F1. Cell Rep 37, 109864 (2021).

63. Zagare, A. et al. Midbrain organoids mimic early embryonic neurodevelopment and recapitulate LRRK2-p.Gly2019Ser-associated gene expression. Am J Hum Genet 109, 311 (2022).

64. Skiteva, O., Yao, N., Sitzia, G. & Chergui, K. LRRK2-G2019S mice display alterations in glutamatergic synaptic transmission in midbrain dopamine neurons. J Neurochem 161, 158–172 (2022).

65. Lau, K., Kotzur, R. & Richter, F. Blood–brain barrier alterations and their impact on Parkinson’s disease pathogenesis and therapy. Transl Neurodegener 13, 37 (2024).

66. de Rus Jacquet, A., et al. The contribution of inflammatory astrocytes to BBB impairments in a brain-chip model of Parkinson’s disease. Nat Commun 14, (2023).

67. Rosh, I., et al. Synaptic dysfunction and extracellular matrix dysregulation in dopaminergic neurons from sporadic and E326K-GBA1 Parkinson’s disease patients. NPJ Parkinsons Dis 10, (2024).

68. Kamath, T. et al. Single-cell genomic profiling of human dopamine neurons identifies a population that selectively degenerates in Parkinson’s disease. Nature Neuroscience 2022 25:5 25, 588–595 (2022).

69. Erekat, N. S. Apoptosis and its Role in Parkinson’s Disease. Parkinson’s Disease: Pathogenesis and Clinical Aspects 65–82 (2018) doi:10.15586/CODONPUBLICATIONS.PARKINSONSDISEASE.2018.CH4.

70. J, S., et al. Erratum: Midbrain dopamine oxidation links ubiquitination of glutathione peroxidase 4 to ferroptosis of dopaminergic neurons (The Journal of Clinical Investigation (2023) 133: 10 (e165228) DOI: 10.1172/JCI165228). Journal of Clinical Investigation 133, (2023).

71. Liu, L., Cui, Y., Chang, Y. Z. & Yu, P. Ferroptosis-related factors in the substantia nigra are associated with Parkinson’s disease. Sci Rep 13, (2023).

72. Foliaki, S. T. et al. Neuronal excitatory-to-inhibitory balance is altered in cerebral organoid models of genetic neurological diseases. Mol Brain 14, 156 (2021).

73. Smajic, S. et al. Single-cell sequencing of human midbrain reveals glial activation and a Parkinson-specific neuronal state. Brain 145, 964 (2021).

74. Li, Y. et al. TREM2: Potential therapeutic targeting of microglia for Alzheimer’s disease. Biomedicine & Pharmacotherapy 165, 115218 (2023).

75. Reinhardt, P. et al. Derivation and Expansion Using Only Small Molecules of Human Neural Progenitors for Neurodegenerative Disease Modeling. PLoS One 8, e59252 (2013).

76. Haenseler, W. et al. A Highly Efficient Human Pluripotent Stem Cell Microglia Model Displays a Neuronal-Co-culture-Specific Expression Profile and Inflammatory Response. Stem Cell Reports 8, 1727–1742 (2017).

77. Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e29 (2021).

78. Becht, E. et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nature Biotechnology 2018 37:1 37, 38–44 (2018).

79. La Manno, G. et al. Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells. Cell 167, 566–580.e19 (2016).

80. Franzén, O., Gan, L. M. & Björkegren, J. L. M. PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data. Database 2019, 46 (2019).

81. Fuchs, S. B. A. et al. GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data. OMICS 20, 139–151 (2016).

Toward Gigabrain: Engineering Self-Perfusing Human Brain Organoids

Toward Gigabrain: Engineering Self-Perfusing Human Brain Organoids

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