Human physiomimetic model integrating microphysiological systems of the gut, liver, and brain for studies of neurodegenerative diseases

Abstract

Slow progress in the fight against neurodegenerative diseases (NDs) motivates an urgent need for highly controlled in vitro systems to investigate organ-organ- and organ-immune-specific interactions relevant for disease pathophysiology. Of particular interest is the gut/microbiome-liver-brain axis for parsing out how genetic and environmental factors contribute to NDs. We have developed a mesofluidic platform technology to study gut-liver-cerebral interactions in the context of Parkinson's disease (PD). It connects microphysiological systems (MPSs) of the primary human gut and liver with a human induced pluripotent stem cell-derived cerebral MPS in a systemically circulated common culture medium containing CD4⁺ regulatory T and T helper 17 cells. We demonstrate this approach using a patient-derived cerebral MPS carrying the PD-causing A53T mutation, gaining two important findings: (i) that systemic interaction enhances features of in vivo-like behavior of cerebral MPSs, and (ii) that microbiome-associated short-chain fatty acids increase expression of pathology-associated pathways in PD.

Fig. 1. Human 3XGLB physiomimetic system of the gut-liver-brain axis.

(A) Schematic representation of the design rationale for the experimental approach and description of individual MPSs included in this study. (B) Top left: pneumatic plates machined in acrylic; top right: mesofluidic plate machined from monolithic polysulfone; bottom: 3X Gut-Liver-Brain (3XGLB) platform composed of pneumatic and fluidic plates with elastomeric polyurethane membrane in between them to form a pumping manifold with integrated fluid channels. The platform allows three-way interaction in three replicates where the center liver-specific MPS can be fluidically linked to two additional Transwell-based MPSs. Photo credit: Martin Trapecar, MIT. (C) Top view of the 3XGLB with identified fluidic and pumping properties as well as operational parameters (for more details, see fig. S1A).

Fig. 2. Physiomimetic interaction increases in vivo markers of cerebral MPSs.

(A) Schematic presentation of conditions compared in Fig. 1 (B to F) and tables S1 and S2. Top: Control PD-C cerebral MPS in isolation; middle: Control PD-C cerebral MPS in interaction with the gut and liver MPSs; bottom: Control PD-C MPS in interaction with the gut and liver MPSs and T_reg/T_H17 cells. (B to D) We jointly harvested neurons, astrocytes, and microglia of three separate replicates of control PD-C cerebral MPSs after a 4-day interaction with the gut and liver MPSs in the absence or presence of T_reg/T_H17 cells. (B) We compared DGE of neuron-, astrocyte-, and microglia-related genes between cerebral MPSs in isolation versus those in interaction. Significance is expressed as *P < 0.05, **P < 0.001, ****P < 0.00001. (C and D) PANTHER pathway enrichments in cerebral PD-C MPSs in interaction over those in isolation. Data represent averages of three replicates. Pathways are ranked on the basis of a combined z and P value score. (E) Concentrations of cytokines measured in the CM shared between MPSs after 96 hours of gut-liver-cerebral (PD-C) interaction studies with or without circulating T_reg/T_H17 cells and indicated reported values of the same proteins in human plasma (for exact values and references, see table S1). (F) Concentrations of cytokines and neuronal markers measured in the apical control PD-C MPS media after 96 hours in isolation or during the gut-liver-brain interaction studies with or without circulating T_reg/T_H17 cells and indicated reported values of the same proteins in human cerebrospinal fluid (for exact values and references, see table S2). Data represent averages of two to nine replicates after 4 days in culture. Error bars represent SEM. TNF-α, tumor necrosis factor–α; GFAP, glial fibrillary acidic protein.

Fig. 3. PD cerebral MPSs exhibit PD-associated transcriptional and metabolic features.

(A) Representative, 3D rendered confocal images of the PD (top) and control PD-C (bottom) cerebral MPSs composed of hiPSC-derived microglia (green), astrocytes (purple), and neurons (red) cocultured on 0.4-μm microporous 24-well Transwells. (B) Metabolic pathway enrichment in apical cerebral media after 4 days of culture of the PD cerebral MPSs when compared to the PD-C control MPS. (C) Volcano plot of DGE among neurons, astrocytes, and microglia in PD MPSs (red) over PD-C control MPSs (blue). (D) ClueGO Network of enriched (magenta) and suppressed (blue) WikiPathway pathways in PD cerebral MPSs based on DGE shown under (C). (E) Concentration (ng/ml) of multiplexed neuronal markers in apical media of the PD and PD-C MPSs after 4 days of culture in isolation. Data represent six to nine biological replicates from two to three independent experiments. Significance was determined with paired t test. Lines in violin plots denote distribution quartiles. (F) DGE pathway enrichments in PD cerebral MPSs as compared to control PD-C MPSs based on the GEO Diseases database. Diseases are ranked by combined P value and rank score. (B to D and F) Data represent averages of three replicates after 4 days in coculture.

Fig. 4. SCFA universally reduce inflammatory cytokines during physiomimetic interaction.

(A) Schematic presentation of conditions compared in Fig. 1 (B to D). (B) PCA of all multiplexed cytokines/chemokines after 4 days of interactions in the CM shared between the MPSs and apical cerebral MPS media. Samples primarily separate from top to bottom depending on the sampling site as indicated by the dotted line and from left to right depending on the presence of SCFA (empty markers) versus absence of SCFA (filled markers). Samples were z scored before PCA. (C) Presence of SCFA significantly reduces concentrations of most analytes regardless of PD or PD-C genotype, as illustrated in a heatmap showing log₂ fold changes (log₂FC) in cytokine, chemokine, and growth factor concentrations between SCFA-treated and untreated groups (see leftmost column). The log₂FC values are annotated for significance based on the false discovery rate (FDR) where •FDR < 0.05, ••FDR < 0.01. Heatmaps comparing actual concentrations can be found in fig. S3. (D) Concentration (ng/ml) of multiplexed neuronal markers in apical media of the interacting cerebral MPSs after 4 days of culture. Significance was determined with a paired t test where *P < 0.05, **P < 0.001. Each interacting condition had three replicates, and the results present their averages.

Fig. 5. SCFA increase pathology-related transcriptomic changes in PD MPSs.

(A) Left: Schematic representation of the interaction condition. Right: Comparison of enriched pathways based on WikiPathways between SCFA-exposed and non-exposed PD-C (left) as well as PD MPSs (right) in interactions with the gut and liver MPSs. (B) Left: Schematic representation of the interaction condition. Right: Comparison of enriched pathways based on WikiPathways between SCFA-exposed and non-exposed PD-C (left) as well as PD MPSs (right) in interactions with the gut and liver MPSs as well as circulating T_reg/T_H17 cells. (C) Volcano plots of differentially expressed genes in control PD-C and PD cerebral MPSs across all interaction conditions in the presence (red) or absence (blue) of SCFA. (D) Volcano plot of DGE in SCFA-exposed PD cerebral MPSs (red) over PD-C control MPSs (blue) during gut-liver-brain interactions in the presence of circulating T_reg/T_H17 cells and SCFA. (E) Pathway enrichments based on DGE shown under (D) in SCFA-exposed control PD-C cerebral MPSs (top) as compared to SCFA-exposed PD MPSs (bottom) according to WikiPathways. Pathways are ranked based on a combined z and P value score. (F) DGE of PD-associated genes comparing PD and PD-C MPSs in isolation or interaction with T_reg/T_H17 cells and SCFA. Interaction significantly increases the in vivo–like expression of PD-associated genes. (G) DGE of disease-associated microglia (DAM)–associated genes comparing PD and PD-C MPSs in isolation or interaction with T_reg/T_H17 cells and SCFA where the interaction in the presence of T_reg/T_H17 cells significantly increases expression of DAMs. (A to G) Data represent averages of three replicates after a 4-day interaction. Significance is indicated as *P < 0.05, **P < 0.001, ***P < 0.0001, ****P < 0.00001.

Fig. 6. PD MPS-unique transcriptional changes during interaction with SCFA.

(A) Venn diagram showing number of unique or shared DGE among SCFA-exposed PD and PD-C MPSs during interaction with the gut and liver in the presence or absence of circulating T_reg/T_H17 cells. Left: Up-regulated genes, right: down-regulated genes. On the basis of the number of altered genes, SCFA affect PD MPSs to a greater extent than PD-C MPSs. (B) Pathway enrichments based on DEG shown under (A) universally in all cerebral MPSs, regardless of genotype or the presence of T_reg/T_H17 cells, according to WikiPathways database. Pathways are ranked on the basis of a combined z and P value score. (C) Up-regulated pathways, identified with g:Profiler, exclusively in PD cerebral MPSs after interaction and the exposure to SCFA regardless of the presence of T_reg/T_H17 cells. (D) Down-regulated pathways, identified with g:Profiler, exclusively in PD cerebral MPSs after gut-liver interaction and the exposure to SCFA regardless of the presence of T_reg/T_H17 cells. (A to D) Data represent averages of three replicates after a 4-day interaction. (E) Schematic summary of unique and universal effects of SCFA during interaction with the PD-C and PD cerebral MPSs.