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Identification of neural oscillations and epileptiform changes in human brain organoids

Ranmal A. Samarasinghe, Osvaldo A. Miranda, Simon Mitchell, Isabella Ferando, Momoko Watanabe, Jessie E. Buth, Arinnae Kurdian, Peyman Golshani, Kathrin Plath, William E. Lowry, Jack M. Parent, Istvan Mody, Bennett G. Novitch

Preprint posted on 28 October 2019 https://www.biorxiv.org/content/10.1101/820183v1

Article now published in Nature Neuroscience at http://dx.doi.org/10.1038/s41593-021-00906-5

Excitatory/inhibitory fusion organoids OSCILLATE! In combination with iPSC technology this allows patient specific drug tailoring, as exemplified by Rett Syndrome in this preprint.

Selected by Theresa Pohlkamp

Categories: cell biology, developmental biology, neuroscience, physiology

Background

In the past decade, human fibroblast-derived induced pluripotent stem cells (iPSCs) changed the landscape of preclinical research. Patient derived iPSCs are now utilized by researchers to grow organoids of different kind to study disease mechanisms and for personalized drug tailoring. Modeling the brain in form of an organoid is a particular challenge due to the diversity of neurons and other brain cell types that inhabit the most complex human organ. Networks of inhibitory and excitatory neurons are required to generate rhythmic brain activity in the range of gamma-oscillations (30-100 Hz), a modality of cognitive operations. Until very recently, brain organoids did not develop these rhythmic patterns, mostly due to an underrepresentation of GABAergic interneurons. However, in August a first study reported gamma oscillations in 6-10 months aged organoids (Trujillo et al., 2019).

During brain development GABAergic interneuron precursors migrate from a transitory structure, the ganglionic eminence (GE), to populate the maturing cortex and intermingle with excitatory neurons. Once neurons are positioned they establish a complex network across different brain structures to allow high cognitive function. Network malfunctioning can cause a variety of different neurological disorders, including schizophrenia, autism, and epilepsy. Rett syndrome is a rare neurological disorder in women, in which heterozygous disruption of the X-chromosomal gene MECP2 leads to coordination problems, repetitive movements, language deficits, and commonly epileptic seizures, which are caused by excessive and hypersynchronous activity of neural networks. In this study, the authors explore whether network-level functions of the brain, and their disruption in disease, can be studied using organoid models.

 

Findings

To generate brain organoids that are assembled as a network of excitatory and inhibitory neurons the authors fused human stem cell derived cortical (Cx) and GE organoids, similar as described before (Xiang et al., 2017). Organoids were treated with or without Sonic hedgehog pathway agonists to induce the growth of GE or Cx organoids, respectively. Once specified, organoids were fused and their joint development resulted in the integration of GE interneurons into the cortex. With calcium imaging and local field potential recordings (LFP), the physiological activity at single cell, microcircuit, and network level was characterized. After less than a month of co-culture the administration of GABAA receptor antagonists evoked repetitive waves of synchronized calcium transients. Moreover, during LFP recording the authors found interneuron-dependent multi-frequency oscillations (<100 Hz), comparable to what is found in mature neural networks in vivo.

Next, the authors took advantage of the human iPSC technology to grow brain organoids of fibroblasts obtained from an individual with Rett syndrome. To obtain isogenic control organoids they took advantage of random X-chromosomal inactivation that lead to a mosaic distribution of cells that express either the functional or the mutated MECP2 allele. X-chromosomal inactivation is not reversed during iPSC reprogramming or differentiation. Whereas no obvious differences in cytoarchitecture and cell composition were detected, the number of excitatory synapses was increased in the MECP2 deficient organoids. In addition, they recorded spontaneous epochs of synchronized calcium transients similar to what was observed after GABAA receptor treatment in controls. Moreover, whereas low-frequency (<100 Hz) oscillations were not produced by MECP2-lacking organoids, they exhibited high-frequency events.

Next, the authors performed an elegant exchange experiment in which MECP2-deficient GE organoids were fused with control Cx organoids, or vice versa. By doing this, they demonstrated that the observed differences in oscillations are caused by MECP2 lacking GE interneurons, rather than Cx derived neurons. In a drug rescue approach they found that the broad-spectrum anti-seizure medication sodium valproate reduced the events of spontaneous high-frequency firing but did not restore the oscillation pattern of MECP2-deficient mixed brain organoids. In contrast, the putative TP53 inhibitor Pifithrin-α restored gamma oscillations.

 

Why I chose this preprint

At the Society for Neuroscience meeting in Chicago this past October I “accidentally” learned a lot about brain organoids. The presidential lecture, held by Dr. Paola Arlotta, was so inspiring that I went to the following “Brain and Retina Organoid Social” to take my chance to fire questions at some very friendly and excited specialists in this field. I realized that in biomedical research human brain organoids provide great benefits over animal models but that this new technology also faces challenges: whereas the genetics are right, the complexity is not. Animal models designed to study human brain disorders have enhanced our molecular understanding, but their translatability usually fails once it comes to clinical trials. Now brain organoids derived from iPSCs of patients with neuronal disorders are on the forefront of efforts to model preclinical studies. Due to reduced complexity organoids will not replace animal models, but are a unique opportunity to study human genetics in a brain model. They develop a comparable neurodiversity to embryonic brains (Gotz, 2018). Recent progress in brain organoid technology allows vascularization (Pham et al., 2018), ventricle formation (Lancaster et al., 2013), organization of cortical regions (Kanton et al., 2019), and the differentiation of glia into astrocytes (Dezonne et al., 2017), microglia, and myelinating oligodendrocytes (Marton et al., 2019). To me as a scientist who characterized interneurons as a graduate student, the progress of interneuronal innervation to generate oscillatory networks was one of the most exciting aspects. Vascularization supports the nutritional supply of the brain organoids and may further promote their growth and complexity. The neuron-glia interaction is of importance to study microglial inflammatory responses that contribute to neurodegeneration and neuroprotection. Overall, there is an urgent need of a human in vitro model in which neurons, glia, and vascularization develop conjointly. The preprint highlighted here provides a pioneering and very valuable example of utilizing brain organoids for patient specific drug tailoring as a translatable tool to find a cure for human diseases of the brain.

 

Questions for the authors

  1. Rett syndrome is X-linked, and MECP2-loss follows a mosaic pattern. Is it possible to produce mosaic brain organoids in culture? What would you expect if the organoids would be mosaic?
  2. How would Pifithrin-α affect the oscillation in control brain organoids?
  3. Trujillo et al. (Trujillo et al., 2019) grew brain organoids for up to 10 months to obtain oscillations. Your method generates oscillations after less than three months of total culture time. In addition your method allows an elegant swip-swap approach. How do you think these different methods will serve different questions in the future?
  4. How would you compare your results to the findings published by Trujillo et al. on BioRxiv last year, where they also describe oscillation deficits in MECP2 deficient brain organoids (Trujillo et al., 2018)?

 

References

Dezonne, R.S., Sartore, R.C., Nascimento, J.M., Saia-Cereda, V.M., Romao, L.F., Alves-Leon, S.V., de Souza, J.M., Martins-de-Souza, D., Rehen, S.K., and Gomes, F.C. (2017). Derivation of Functional Human Astrocytes from Cerebral Organoids. Scientific reports 7, 45091.

Gotz, M. (2018). Revising concepts about adult stem cells. Science 359, 639-640.

Kanton, S., Boyle, M.J., He, Z., Santel, M., Weigert, A., Sanchis-Calleja, F., Guijarro, P., Sidow, L., Fleck, J.S., Han, D., et al. (2019). Organoid single-cell genomic atlas uncovers human-specific features of brain development. Nature 574, 418-422.

Lancaster, M.A., Renner, M., Martin, C.A., Wenzel, D., Bicknell, L.S., Hurles, M.E., Homfray, T., Penninger, J.M., Jackson, A.P., and Knoblich, J.A. (2013). Cerebral organoids model human brain development and microcephaly. Nature 501, 373-379.

Marton, R.M., Miura, Y., Sloan, S.A., Li, Q., Revah, O., Levy, R.J., Huguenard, J.R., and Pasca, S.P. (2019). Differentiation and maturation of oligodendrocytes in human three-dimensional neural cultures. Nature neuroscience 22, 484-491.

Pham, M.T., Pollock, K.M., Rose, M.D., Cary, W.A., Stewart, H.R., Zhou, P., Nolta, J.A., and Waldau, B. (2018). Generation of human vascularized brain organoids. Neuroreport 29, 588-593.

Trujillo, C.A., Gao, R., Negraes, P.D., Chaim, I.A., Domissy, A., Vandenberghe, M., Devor, A., Yeo, G.W., Voytek, B., and Muotri, A.R. (2018). Nested oscillatory dynamics in cortical organoids model early human brain network development. BioRxiv.

Trujillo, C.A., Gao, R., Negraes, P.D., Gu, J., Buchanan, J., Preissl, S., Wang, A., Wu, W., Haddad, G.G., Chaim, I.A., et al. (2019). Complex Oscillatory Waves Emerging from Cortical Organoids Model Early Human Brain Network Development. Cell stem cell 25, 558-569 e557.

Xiang, Y., Tanaka, Y., Patterson, B., Kang, Y.J., Govindaiah, G., Roselaar, N., Cakir, B., Kim, K.Y., Lombroso, A.P., Hwang, S.M., et al. (2017). Fusion of Regionally Specified hPSC-Derived Organoids Models Human Brain Development and Interneuron Migration. Cell stem cell 21, 383-398 e387.

 

Tags: brain organoids, epilepsy, gamma oscillation, ganglionic eminence, interneurons, ipscs, mecp2, oscillation, rett syndrome

Posted on: 25 November 2019

doi: https://doi.org/10.1242/prelights.15281

Read preprint (1 votes)

Author's response

Bennett Novitch and Ranmal Samarasinghe shared

Hi Theresa,

Thank you for selecting our study for discussion!  Below are are our responses to your questions.  Our response is in bold text.

  1. Rett syndrome is X-linked, and MECP2-loss follows a mosaic pattern. Is it possible to produce mosaic brain organoids in culture? What would you expect if the organoids would be mosaic?

It is theoretically possible to create a mosaic organoid by combining the mutant and isogenic control stem cells in pre-defined proportions at the time of organoid generation. For example, we typically start with ~9000 stem cells at the beginning of the organoid plating process (Day 0).  To create a 50/50 mosaic (50% cells have mutant MECP2 and 50% express the functional protein), we would initiate the organoid plating process with a mix of 4500 mutant and 4500 isogenic control stem cells. 

It is difficult to exactly predict how this will play out once the organoid matures, but we predict that we should end up with a hybrid phenotype similar to the mixed fusion results from the paper. In other words, something less severe than the non-mosaic mutant, but exhibiting a range of network defects.  Stay tuned….

  1. How would Pifithrin-α affect the oscillation in control brain organoids?

It is unlikely that this would have much effect in controls. Prior studies from our collaborator Bill Lowry’s group (Ohashi et al. Stem Cell Reports 2018 https://doi.org/10.1016/j.stemcr.2018.04.001) found that a characteristic feature of MECP2 mutant cells is activation of p53-associated cell senescence pathways.  We have no evidence that control organoids exhibit this senescence response, so we have no reason to expect that Pifithrin would have any significant impact on neural activities in these samples.

  1. Trujillo et al. grew brain organoids for up to 10 months to obtain oscillations. Your method generates oscillations after less than three months of total culture time. In addition your method allows an elegant swip-swap approach. How do you think these different methods will serve different questions in the future?

Our approaches are different in multiple ways. We likely see oscillations earlier due to a combination of factors including (1) increased sensitivity with use of traditional microelectrodes that penetrate the organoids and (2) because we intentionally generated “fusion” organoids with a mix of inhibitory and excitatory neurons from the start.  We have found that interneuron-excitatory cell integration is critical for generating complex oscillatory activity. Trujillo et al report that interneurons in their organoids spontaneously arise much later in development in their protocol than our protocol where we generate cortex and ganglionic eminence structures separately. They also use multi-electrode array methods (MEA), where the organoids lay on top of surface electrodes embedded in culture plates. This approach likely picks up activity from neurons at the outer surface of the organoid that end up in contact with the electrodes.  The organoids also require prolonged plating on these MEAs, which also likely impacts their 3D structure compared to our approach where we are measuring from intact 3D samples.

As a result of these differences, we think that our approach using fusion organoids may be better suited to identify oscillatory activity at earlier time points, for isolating interneuron vs excitatory neuron contributions to oscillations, and for sampling LFPs from deeper components of the organoid. The MEA approach is better suited for chronic recordings where the same organoid can be measured a number of times over an extended period of time. In addition, to the extent that the MEA picks up activity, this approach allows one to sample with more electrodes (multiple) than what we currently employ.  However, the density of electrodes can be modified in our system as well.

  1. How would you compare your results to the findings published by Trujillo et al. on BioRxiv last year, where they also describe oscillation deficits in MECP2 deficient brain organoids (Trujillo et al., 2018)?

Please note that the Trujillo et al. removed their MECP2 mutant organoid results from their published paper. With this caveat, our LFP results are generally in agreement in that we also find deficits in oscillatory activity in MECP2 mutant brain organoids, though what we see is distinct from their analysis.  For example, they show a general reduction in spiking whereas we see a marked increase which is associated with epileptiform activities. Trujillo et al. also reported deficits in overall organoid size and production of upper layer neurons (CTIP2, SATB2) in MECP2 KO organoids using single cell analysis, which we did not observe in our immunohistochemical analysis. Using our mix and match fusion organoid approach, we also found the oscillatory defects that we observe appear to stem in large part from MECP2 deficiency in the ganglionic eminence-derived cells (i.e. the interneurons that integrate into the cortical circuitry).

With best wishes,

Ben Novitch and Ranmal Samarasinghe

 

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