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- My lab has been working with brain organoids
for a while now.
And they recapitulate, or they mimic human development
at the molecular level, as well as the cellular level.
The organization of the cells resemble some of the
organizations that we see during development.
So, in our case, we are focusing on the cortex.
As these organoids mature, we can identify different
cortical layers being formed.
So that was a great and very attractive model to study
disorders that affect cell proliferation,
gene expression, visually more foliage of the brain ,
but there are several neurological conditions
in psychiatric conditions where the brain is just intact.
The problem relies on network
and we have been trying to push this field
to create brain organoids that are functional
in a way that they can create sophisticated networks.
That was the original motivation
to optimize these novel protocol
so the networks can be formed.
So we have been measuring the activity of neuronal networks
by using microelectrode arrays or MEAs.
To be honest I was not expecting them
to increase too much over time.
After about four to six month of culturing these organoids,
Prescilla and Cleber form my lab they came to me and said
we have a big surprise.
- The whole well was synchronized
and there was like a lot of activity going on
and we've never seen that in today.
We were never able to see so high levels of activity,
so we were just very surprised.
- This was unprecedented tissue culture.
Initially my reaction was to be very skeptical.
So I thought that there was a short circuitry
or a bug into the system that was generating these spikes
from the microelectrode arrays.
So it was very unexpected result.
So that what motivate us to further investigate
what was going on.
- To generate the cortical organoids
we dissociated the iPSC colonies into single cells
and we keep these cells in suspension,
under rotation to form free floating spheres.
We promote neural induction by dual SMAD inhibition.
And for the proliferation of neural progenitor cells
we add growth factors into the media,
such as FGF and NGF.
Then we remove this growth factor
and we add some small molecules to promote
the neural differentiation and maturation.
However, these small molecules
they are kept only for a short period of time.
In the long term maintenance of the organoids
occurs in a more basal media.
- We turn to a single cell analysis
to see if the diversity of the cellular populations
were actually contributing to these level of activity.
- To characterize the cellular diversity
of cortical organoids during development,
we perform single cell RNA-seq
on one, three, six, and 10 months organoids.
We use unsupervised clustering on the combined data set
with almost 20, 000 cells
between five clusters and they're relative proportions.
Based on the express of genes,
we combine them into five major cell classes:
progenitors, intermediated progenitors,
glia cells, glutamatergic neurons, and GABAergic neurons.
At one month, organoids consist of
more than 70% of progenitor cells.
At three and six months, cortical organoids
consist of glia and glutamatergic neurons.
The glia cells start with a small population
and increase to around 40% of cells present
in the cortical organoids.
Remaining population of progenitors around 5%
and intermediate progenitors around 10%
were present during maturation.
GABAergic neurons were mainly restricted
to six to 10 months, as indicated
by the expression of specific markers,
eventually reaching around 15% of total neuronal population.
To further demonstrate the biosynthesis of GABA
we employed mass spectrometry.
The neurotransmitter GABA was detected in the culture media
after six months of maturation
in a physiological relevant concentration.
These results suggest the presence
of the basic complements for degeneration
of a neural network in a developing human cortical model.
- So by growing these organoids,
by giving them the right environment,
we can stimulate the progenitor cells
to produce a more diverse type of cell population.
- To interrogate the functional activity
of the cortical organoids,
we start at the single cell level
using patch clamp in individual neurons.
And we observe the repetitive action potential firing
in response to corinth injection.
These action potential firing
and also voltage dependent currents
they were abolished in the presence of TTX.
Then we decide to challenge the organoid
and see if we could modulate the neuronal activity.
And in the presence of glutamate receptor antagonist
the post-synaptic current was also abolished,
confirming that we had functional excitatory neurons
in the organoid.
The viability between replicates and the organoids
was very low compared to the cultures,
which is also really important for research.
Then we decide to do investigation
in a more mesoscopic scale
and we perform weekly recordings
using a multielectrode array over the course of 10 months.
In this approach we were able to collect single channel
and population firing features from time wise,
spike times, and the local field potential.
And in this case the spikes
they represent motor unit activity
due to the spatial and temporal resolution of DMA
which is not sufficient for single unit detection.
We could clearly see an increasing activity.
This activity was very robust,
switching from pure soft gases
and burst synchronized networks spikes.
And the increase of this network burst was not only number,
but also in complexity,
reflecting the maturation of the organoids.
- We further evaluated the role of glutamatergic
and GABAergic synapse transmission
in forming oscillations by pharmacological intervention.
Neural networks were effected
by both glutamate receptor antagonists
and GABA receptor agonists.
These drugs reduced the number of spikes and bursts
with a subsequential nation of synchronized activity.
The blockage of GABAergic transmission by bicuculline
increased then number of networks synchronized events
and did not effect big population firing rate,
but abolish message oscillatory achievement
by raising subsequent peaks.
In other words glutamatergic signaling
is important for starting oscillatory activity,
while GABA is important for keeping them going.
- The other thing that we decided to investigate
was if we have that much activity
it is possible that these networks will generate brain waves
similar to the ones captured by EEGs.
So that's when we turn at our collaborators
in the Voytek Lab,
this is Brad Voytek at a cognitive neurosciences
here at USCG.
- In the Voytek Lab we look at a lot of
the human electrophysiology.
So signals like EEG, ECoG, and MEG.
And the reason why these oscillating organoids
are interesting is because oscillations are
a ubiquitous feature in animals as well as humans.
You'll see a alpha oscillation at 10 Hz.
So that's why we think the organoids
that are oscillating are special.
There wasn't any 2D culture or other organoid work
that was showing oscillating cultures.
So what you're seeing in these traces
are the total number of neurons
that are firing at that time.
A higher peak means there are more neurons
or more action potentials that are emitted.
At six weeks the neurons don't really synchronize,
they fire sparsely and randomly.
Starting at 2 months they start to synchronize
in these burst events.
They have these periods where all neurons in a network
activate at the same time, then it just decays slowly.
Starting at four months they spike really quickly once
and then they spike again
within couple hundred milliseconds.
So that's what we call an oscillation.
And than at six months
there are ore and more cycles in this oscillation.
It's very regular, you see the same oscillation.
By eight months the trajectories become less third ripple.
We don't only see oscillation at a single time scale,
there are multiple frequencies
that are nested in each other,
but the slowest scale these bursts happen
every 10 to 20 seconds and is fairly regular.
But within a single burst you see this oscillation
at the second scale
which is what we call the nested oscillation.
And then there's even a faster oscillation at 100 Hz
and that's nested within that one.
So this nestedness or cross frequency coupling
is another feature that we see in human
as well as animal electrophysiology.
So the transition from six to eight months
in the functional activity we think is a product
of a more complex physical network in the organoid.
As we saw in the anatomical data
there are more GABergic neurons
as well as more glial cells that grow in this time span.
That's one possibility for how these organoids
at eight months are able to
have these more complex activities.
- More importantly they were able to compare the EEG
from preterm babies at different stages in the development
to our brain organoids.
- After seeing these organoids starting to exhibit
these more complex electrical features
we thought maybe we could compare it to EEG data
from very early development.
Sp we were able to find this clinical data set actually
of preterm infant EEG data.
And so this regression model is basically saying
if we just trained a very simple machine learning model
on the baby's EEG features to predict how old the babies are
can we then use that to predict directly using the organoids
features how old the organoids are in culture time.
So the regression model was trained on
data from 25 to 38 weeks.
The preterm EEGs are wildly different
from the organoid MEAs and the EEG signal
with the submation of a lot of brain areas
on the other side of the skull
which also smears the electrical signal.
In the organoid MEA the electrodes
are directly in contact with the organoids,
so you can pick up action potentials
as well as local field potentials
at a much better resolution.
That being said, the features we compare
across these two data sets
are things that are agnostic to the modality.
Which for example, are things like
how often these bursts of activity occurred.
In the time span where the model hasn't seen the EEG data,
so before 25 weeks, it predicted really poorly
for the organoids,
whereas starting from about 25 weeks
the prediction became a lot more correlative
with the actual developmental time of the organoids.
Therefore from the model's perspective
there are similar features in the EEG data
from the preterm babies which it has seen
compared to the organoid data which it hasn't.
When we use only those features
this model was able to predict
what the actual culture age was.
Coming back to the organoid as developmental model
this suggests that the network in the organoids
are a little bit more complex than we've seen before,
so it's able to give rise to activity
that you can record with MEA that's similar
to features in, for example, preterm infant EEGs.
It might suggest that we can use them
as models of neurodevelopment, for example,
or patient specific models to test out drugs
or disease interventions.
- Many people have been using this molecular arrays
to measure the overall network activity
mostly in 2D cultures.
Most of the time these 2D cultures
they generate a level of activity
that is below 5 Hz as a mean firing rate
and overall brain activity or network activity.
Even though you can keep them for longer periods of time
the maturation of those neurons reaches a plateau.
If you measure a mouse brain's lives
using the same technology you get something close to 18 Hz.
In a primate brain you get something close to 20 Hz.
Form our novel protocol for brain organoids
by the end of 40 weeks or about nine months
the level os activity is getting close to 20 Hz,
the level of maturation that's similar to
a more intact network such as the primate brain.
Even though these brain organoids recapitulate
some of the features that we see on EEGs from preterms
and even post-natal human brains,
it does not recapitulate the entire cortex.
It's a model and as any other models
it has intrinsic limitations,
such as the number of cell types, it's not vascularized.
We don't even know if the culture conditions
are the ideal culture conditions,
but they are an attractive model to start exploring
these early stages of human development.
The inability to study the embryonic human brain
makes this model even more relevant.
There are several conditions, for example autism,
where the genes that are implicated in autism
actually are very active in these very early stages
of fetal brain development.
Next steps on these research would include
external stimulation, hoping for further maturation
of these networks.
The other thing that we are also preparing
is to connect these brain networks with other brain regions
that we can independently generate and put them together
to see if they start forming these more circuits in a dish.
As we improve these model and as the work advances
the model is getting more and more complex
perhaps more and more close to the real brain
and that might raise some potential concerns
about the ethical applications of this too.
- Based on what I know of neurobiology and science
I'm pretty sure that what we have now,
what anybody working this field has so far
is very far from anything like self-awareness or sentience,
but the plan is to continue pushing further and further,
more and more development, more and more structure,
and what will that mean?
The key here is that the science is extraordinarily exciting
and extraordinarily important.
To understand various human neurological diseases
is crucial because there's a lot of human suffering
that goes with that.
But just because the goal is so great
doesn't mean any means are acceptable.
We should be thinking about that
and ideally erring on the side of caution
rather than pushing too far.
No committee is normally going to be looking at
what is that thing you're creating
when you differentiate the cells into human neurons
and allow them to form these networks.
We don't have the structure in place yet
and case could be made that it's
the sign of the community should
not wait for someone else to impose on us
rules and regulations and new approaches but ourselves.
Think about what sort of a review process
could we develop to make sure
we're looking at this step-by-step
and we should be engaging the general public
both to get their perspectives
and also to help them be onboard with where it's going.
- We scientists need to be very open
to these kind of discussion and always in keep in mind
that we are using these brain organoids
to really help people with neurological conditions,
conditions that effect millions of people
in the entire world.
So having a model to experimentally manipulate
the human brain as we do with these organoids
is instrumental if you wanna create better quality of life
for these individuals.
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