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[Preprint]. 2024 Sep 19:2024.09.17.613333.
doi: 10.1101/2024.09.17.613333.

Human Neural Organoid Microphysiological Systems Show the Building Blocks Necessary for Basic Learning and Memory

Affiliations

Human Neural Organoid Microphysiological Systems Show the Building Blocks Necessary for Basic Learning and Memory

Dowlette-Mary Alam El Din et al. bioRxiv. .

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Abstract

Brain Microphysiological Systems including neural organoids derived from human induced pluripotent stem cells offer a unique lens to study the intricate workings of the human brain. This paper investigates the foundational elements of learning and memory in neural organoids, also known as Organoid Intelligence by quantifying immediate early gene expression, synaptic plasticity, neuronal network dynamics, and criticality to demonstrate the utility of these organoids in basic science research. Neural organoids showed synapse formation, glutamatergic and GABAergic receptor expression, immediate early gene expression basally and evoked, functional connectivity, criticality, and synaptic plasticity in response to theta-burst stimulation. In addition, pharmacological interventions on GABAergic and glutamatergic receptors, and input specific theta-burst stimulation further shed light on the capacity of neural organoids to mirror synaptic modulation and short-term potentiation, demonstrating their potential as tools for studying neurophysiological and neurological processes and informing therapeutic strategies for diseases.

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Conflict of interest statement

Declaration of interests T.H. is named inventor on a patent by Johns Hopkins University on the production of organoids, which is licensed to Axo-Sim, New Orleans, LA, USA. T.H. and L.S. are consultants for AxoSim, New Orleans, and T.H. is also a consultant for AstraZeneca and American Type Culture Collection (ATCC) on advanced cell culture methods. B.J.K. is a named inventor on patents by CCLabs Pty Ltd trading as Cortical Labs on the use of biological neural systems for intelligent purposes. B.J.K., F.H, and A.L are employees of Cortical Labs. B.J.K. and A.L. are shareholders of Cortical Labs. J.L is a data science consultant for Vindhya Data Science specializing in bioinformatics analysis. The rest of the authors declare no conflict of interest.

Figures

Figure 1.
Figure 1.
Schematic overview of the experimental approach. A) Experimental timeline. B) Overview of avalanche and network connectivity analysis for time series electrophysiology data from organoids plated on HD-MEAs. C) Schematic representation of synaptic transmission modulation by pharmacological and electrical stimuli to induce synaptic plasticity. Figure created using BioRender.com.
Figure 2.
Figure 2.
Expression of glutamatergic and GABAergic receptor and synaptic plasticity related genes in neural organoids over course of differentiation. A) Representative immunocytochemistry images of organoids showing postsynaptic marker (HOMER1) and presynaptic marker (SYP) in 8- and 12-week cultures. In composite images, HOMER1 is shown in blue, and SYP is shown in yellow. Scale bars are 100 μm, 50 μm, and 10 μm respectively. B) Presence of inhibitory post-synaptic marker (Gephyrin), presynaptic marker (SYN1) and dendrites (MAP2) in 8- and 12-week organoids. In composite images, Gephyrin is shown in blue, SYN1 in yellow, and MAP2 in grey. Scale bars are 100 μm and 50 respectively. For panels A-B) All images were taken at 20x, 100x, and 100x + 4x zoom and processed with ImageJ for visualization. C) Gene expression of Gamma-Aminobutyric Acid Type A Receptor Subunit Alpha1 (GABRA1), Glutamate Ionotropic Receptor NMDA Type Subunit 1 (GRIN1), Glutamate [NMDA] Receptor Subunit Epsilon-1 (GRIN2A), and Glutamate [NMDA] Receptor Subunit Epsilon-2 (GRIN2B), Glutamate Ionotropic Receptor AMPA Type Subunit 1 (GRIA1), homer scaffold protein 1 (HOMER1) in organoids over the course of differentiation. D) Representative immunocytochemistry images of weeks 8 and 12 organoids stained for Neuronal Pentraxin 2 (NPTX2), Activity -Regulated Cytoskeleton-associated protein (ARC), cAMP response element-binding protein (CREB), and Brain-Derived Neurotrophic Factor (BDNF). Scale bar is 100 μm. E) Gene expression over the course of differentiation of immediate early genes (IEG) ARC, BDNF, Neuronal PAS Domain Protein 4 (NPA54), NPTX2, and Fos proto-oncogene AP-1 transcription factor subunit (FOS), and Early Growth Response 1 (EGR1). F) Gene expression of Synaptic Plasticity Related Genes CREB, calcium/calmodulin-dependent protein kinase II A (CAMK2A), Synaptic Ras GTPase-activating protein 1 (SYNGAP1). G) Gene expression of Synaptic Plasticity Related miRNA. For all gene expression plots, data is shown as box and whiskers plot (extending from the 25th to 75th percentiles) and represented as log2(FC) normalized to NPCs from 2-3 independent experiments with 3 technical replicates each. In all qPCR experiments, ACTB was used as a reference gene.
Figure 3.
Figure 3.
Neural organoid calcium oscillatory dynamics across different time points to show maturation of spontaneous network bursting. A) Representative changes in fluorescence over resting fluorescence (ΔF/F) graphs across 360 seconds for each time point. B) Average rise time, peak amplitude, firing rate, decay time, burst duration, number of peaks, and percentage of active organoids shown across different time points. At least 8 individual organoids across at least 3 independent experiments were imaged and quantified for each time point. Statistics was performed using One-way ANOVA and a Tukey post-hoc test. Changes over time were significant for rise time (p < 0.05), burst firing rate (p<0.0001), peak amplitude (p<0.0001), decay time (p < 0.01), burst duration (p < 0.001), and total number of peaks per organoid (p<0.0001). Pairwise comparisons are shown on the figure: # = Significant difference from week 4, Ŧ = Significant difference from week 6, $ = Significant difference from week 8, \ = Significant difference from week 10, ⍰ = Significant difference from week 12, • = Significant difference from week 14, * = Significant difference from all weeks. For exact p values see supplementary tables 4-8. See also Figure S2 for single neuron calcium imaging analysis.
Figure 4.
Figure 4.
Changes in spontaneous electrical activity in neural organoids throughout development. Representative raster plots and Active Area plots from HD-MEAs recording showing spontaneous electrical activity over time during (A) weeks 6-9 and (B) weeks 10-13 of differentiation. DOM: Days on MEAs. C) Network dynamic metrics from both organoid age groups seeded on HD-MEA over time. Data shown represents mean and standard deviation plotted from 2 independent experiments with 5 to 6 HD-MEA wells per group per experiment with 2-5 organoids per well. Statistics was performed using a mixed-effects model with matching and a Tukey post-hoc test. P<0.05 was considered significant. For exact p values from pairwise comparisons see supplementary documents. ISI: Interspike Interval. IBI: Interburst Interval.
Figure 5.
Figure 5.
Neural organoids show highly interconnected neuronal networks and criticality throughout development. A) Representative plots of functional connectivity at DOM 3, 9, 15, and 21 for the week 6-9 and week 10-13 old organoids. For clarity of visualization, only the 200 connections (edges) with the highest mutual information are shown. Each red dot represents an electrode, and the lines indicate the connections between electrodes. The thickness of the line indicates the weight of connectivity. See also Figure S4 for an expanded version of network connectivity across all days on the MEA. B) Average number of nodes; C) Average Fraction of Total Possible Edges; D) Average modularity over time in week 6-9 and week 10-13 organoids. E) Number of criticality coefficient (DCC) F) Branching ratio (BR) G) Shape collapse error (SCe) over time in 6-9 week and 10-13 week old organoids. Panels B-D show mean and standard deviation. Panels D–G show regression lines with a 95% confidence interval. Data plotted is from 2 independent experiments with 5-6 HD-MEA wells per group per experiment. Statistics were performed using a 2-way ANOVA and a Tukey post-hoc test. P<0.05 was considered significant. For exact p values from pairwise comparisons see supplementary documents.
Figure 6.
Figure 6.
Pharmacological characterization of synaptic transmission changes of neuronal spiking and bursting activity and Immediate Early Gene expression. Expression of ARC, NPAS4, FOS, and EGR1 after 2 hours of exposure to 20 μM AP5+20 μM NBQX, 10 μM bicuculline and 100 μM 4-AP in (A) 8-week and (B) 13-week old organoids, represented as box and whisker plots (25th to 75th percentiles) and as log2(Fold Change) normalized to negative control (organoids with no chemical treatment = 2h Control). ACTB was used as a reference gene. Data represents 3 independent experiments with 2 technical replicates each for 8-weeks and 4-5 independent experiments with 2 technical replicates each for 13-week time point. Statistics were calculated based on the technical replicate average from each independent experiment, with one-way ANOVA and post-hoc Dunnett’s tests *p < 0.05, ***p < 0.001, ****p < 0.0001 C). Representative Raster Plots from MEA recordings in week 13 old organoids (from 6 wells per condition) before and after treatment with bicuculline, 4-AP, and NBQX+AP5. D). Burst Frequency, Interburst interval coefficient of variation, burst duration, and percentage of spikes within bursts plotted for Bicuculline, 4-AP, and NBXQ+AP5 treated wells before, 0 mins, 2 hours, and 4 hours after exposure. Data represents 3 independent experiments with 2 HD-MEA wells per experiment per chemical (n=6). Statistical significance was calculated with repeated measures ANOVA with post-hoc Dunnett tests. p<0.05 was considered significant. Pairwise comparisons can be seen in the supplementary tables 9-19 and significant groups are shown in the figure.
Figure 7.
Figure 7.
Theta-Burst Stimulation Modulated Short-Term Plasticity. A) Graphical summary of TBS protocol. i-The TBS was performed four times spaced by 13 minutes. ii-Within each TBS there are 10 trails with four spikes per trial. iii-The schematic of each trial. B) Percent active area before and after stimulation across all 6 wells. Wells 4-6 show consistent increase or decrease in active area in response to stimulation while wells 1-3 show little change. C) Representative heat map evoked activity response for wells 4-6. Bin size is equal to 10 ms. The stimulation pulses are the light grey vertical lines, and the dashed orange lines indicate the start/stop time of the analysis window for calculating evoked activity. D) Active electrodes, total spikes, and evoked activity for wells 1-3 and then 4-6. The 90th percentile response of a well treated with NBQX/AP5 before and during stimulation is shown in blue overlayed on all graphs. The mean response of a well treated with NBQX/AP5 before and during stimulation is shown in black overlayed on all graphs. The 10th percentile response of a well treated with NBQX/AP5 before and during stimulation is shown in red overlayed on all graphs. Responses above this NBQX/AP5 region indicate responses generated by glutamatergic receptors. E) Histograms of total evoked activity per bin (bin size of 10 ms), total spikes, and total active area. The top three graphs show data aggregated across all electrodes for all 4 TBS for wells 1-3 and the bottom three graphs show data aggregated across all electrodes for all 4 TBS for wells 4-6. Wells 1-3 show little to no response while wells 4-6 indicate evoked responses on the millisecond timescale.

References

    1. Smirnova L. & Hartung T. The Promise and Potential of Brain Organoids. Adv. Healthc. Mater. e2302745 (2024) doi: 10.1002/adhm.202302745. - DOI - PubMed
    1. Acharya P., Choi N. Y., Shrestha S., Jeong S. & Lee M.-Y. Brain organoids: A revolutionary tool for modeling neurological disorders and development of therapeutics. Biotechnol. Bioeng. 121, 489–506 (2024). - PMC - PubMed
    1. Birey F. et al. Assembly of functionally integrated human forebrain spheroids. Nature 545, 54–59 (2017). - PMC - PubMed
    1. Qian X. et al. Brain Region-specific Organoids using Mini-bioreactors for Modeling ZIKV Exposure. Cell 165, 1238–1254 (2016). - PMC - PubMed
    1. Quadrato G. et al. Cell diversity and network dynamics in photosensitive human brain organoids. Nature 545, 48–53 (2017). - PMC - PubMed

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