Oligodendrocytes Provide Energy Reserves to Axons

Post by Laura Maile

The takeaway

When the brain is exposed to low glucose and decreased metabolism, as it is in diseases like Alzheimer’s, myelin slowly breaks down. Oligodendrocytes - cells that create myelin - can provide a reserve of energy for the axons of neurons, supporting them through periods of disease or other insults.   

What's the science?

Oligodendrocytes are the cells of the central nervous system that create myelin, the fatty substance that surrounds the axons of neurons and helps action potentials propagate down the axon. In addition to creating myelin, oligodendrocytes also support the production of ATP, the energy-associated molecule necessary for many cellular processes. This is important because myelin insulates axons, blocking their access to metabolic molecules in the extracellular space. As we age, myelin must be maintained by the constant turnover and production of new myelin proteins and fatty acids. Fatty acid oxidation is the process that occurs in the mitochondria and peroxisomes where fatty acids are broken down into acetyl-CoA, which can then be used in the production of ATP or of new fatty acids. In disorders associated with loss of myelin such as Alzheimer’s Disease, there is also reduced glucose metabolism in the brain. Scientists don’t yet know whether fatty acid and myelin production are connected to metabolism in oligodendrocytes. This week in Nature Neuroscience, Asadollahi and colleagues studied isolated optic nerves to determine whether axons depend on oligodendrocyte energy metabolism and whether myelin is disrupted when glucose is low.

How did they do it?

The authors studied the optic nerve of young adult mice because of its long, isolated axons. They used transgenic mice bred to express fluorescent proteins in oligodendrocytes. After isolating the optic nerves, they were exposed to different amounts of glucose, and fluorescent staining was used to analyze the total number and identity of surviving and dying cells. Next, they determined whether fatty acid metabolism provides an energy store by starving optic nerves of glucose and exposing them to a drug that blocks fatty acid oxidation in the mitochondria. They also used a high-resolution technique called electron microscopy to examine myelin structure in low glucose environments. 

Next, the authors sought to determine whether fatty acid metabolism in oligodendrocytes is important for axon function. They electrically stimulated isolated optic nerves while measuring the size of the evoked action potentials.  By increasing the frequency of stimulation, they could observe enhanced firing frequency of axons and measure the area of the resulting action potentials. They next disrupted fatty acid oxidation specifically in the peroxisomes of oligodendrocytes through a genetic mouse model that knocked out a specific gene. Using the same electrical stimulation experiment, they measured the action potential area of stimulated axons that were starved of glucose. Finally, to determine the role of oligodendrocytes in long-term glucose deprivation, the authors generated transgenic mice with an inducible knockout of the GLUT1 glucose transporter in oligodendrocytes. Using this model, they could disrupt glucose availability in oligodendrocytes in adult mice and then observe behavior and myelin structure using electron microscopy.  

What did they find?

The authors found that after 24 hours of low glucose exposure, oligodendrocytes and other glial cells suffered little to no cell death in the optic nerve, meaning they had access to some additional energy store.  When the optic nerve was exposed to an environment with no glucose and an inhibitor of fatty acid metabolism, 70% of cells died. After 24 hours of low glucose exposure, cells showed signs of cell death and loss of myelin integrity. When optic nerves were deprived of glucose and then electrically stimulated in the presence of a fatty acid oxidation blocker, their evoked action potentials decayed quicker than controls that had normal fatty acid oxidation. This shows that in low glucose environments, axonal function is supported by fatty acid metabolism. In transgenic mice that had a genetic block of fatty acid oxidation in oligodendrocyte peroxisomes, a similar decay in action potential area was observed, indicating that axonal function is supported specifically by oligodendrocytes. Finally, in mice that lacked the GLUT1 glucose transporter in oligodendrocytes, the authors observed loss of myelin even in the absence of behavioral deficits. This suggests that when glucose uptake by oligodendrocytes is low, normal myelin metabolism continues. 

What's the impact?

This study found that when neurons are exposed to low glucose, myelin loss, and oligodendrocyte fatty acid breakdown continues, providing support to axons and possibly avoiding permanent axon degeneration. This suggests that oligodendrocytes are important for providing energy reserves for neuronal axons and additionally, that in diseases associated with axonal degeneration and in normal aging, the imbalance between myelin production and degradation may be responsible for progressive loss of myelin.   

Access the original scientific publication here.

Heart Rhythms and the Perception of Time

Post by Anastasia Sares

The takeaway

This study shows that our general sensitivity to internal bodily states, our ability to reproduce time intervals accurately, and the strength of heartbeat-related signals in the brain are all related—consistent with the idea that our hearts may be key to anchoring our minds in time. 

What's the science?

Researchers have long known that the brain must have some sort of timekeeper or pacemaker that helps us estimate the passage of time. Increasingly, they are proposing that this timekeeper might be connected to the heart. A heartbeat influencing our perception of time is an example of embodied cognition, the concept that our mental processes are determined (at least in part) by our bodily states. A couple of papers made headlines in early 2023 showing that, on average, the beating of the heart affected moment-to-moment time estimation. However, individuals vary in their sensitivity to internal signals from their body (also known as interoception). Could this affect how good they are at estimating the passage of time and reproducing time intervals? And how exactly do the heart and the brain communicate this information?

This week in the Journal of Neuroscience, Khoshnoud and colleagues tracked the heart, the brain, and people’s conscious perception of time to understand the relationship between them during an interval-reproduction task.

How did they do it?

The authors first measured participants’ awareness of their own internal bodily states. They did this in two ways, the first being the Self-Awareness Questionnaire, where they rated their agreement with statements like: “I feel full and bloated after eating,” “I feel pain extremely,” or “I feel my heart thudding.” The second was a heartbeat counting task, where participants were asked to count their heartbeats for an indeterminate length of time without any physical aids like a finger on the wrist.

Next came the interval-timing task. In all trials, participants heard a sound that lasted either 4 seconds, 8 seconds, or 12 seconds, and when the sound ended, they had to press a button as soon as possible. Afterward, the participants had to reproduce the interval they had just heard by pressing another button 4, 8, or 12 seconds after the start of the next sound, or they did nothing. They knew ahead of time which type of trial it would be. In other words, while listening to the first sound, the only difference between trials was the knowledge that they would have to reproduce the interval later.

During the interval timing task, participants were hooked up to an electrocardiogram (measuring electrical signals from the heart) and an electroencephalogram (measuring electrical signals from the brain). Using these devices, the authors recorded the heartbeat-evoked potential, which is the brain signal occurring after a specific peak in the heartbeat (R peak). The authors also measured an electrical signal corresponding to timing in the brain called the contingent negative variation, because it is a long negative signal leading up to an anticipated event. 

What did they find?

On average, participants tended to produce shorter time intervals than the ones they had been presented with. However, there was a lot of variability between individuals—for example, in the 12-second condition, people produced intervals ranging from around 7 seconds to around 13 seconds. Scores on the Self-Awareness Questionnaire, changes in heartbeat-evoked potential, and the size of the contingent negative variation were all correlated to the length of interval a person produced in the reproduction task. Better self-awareness and less dramatic changes in the neural signals correlated to longer intervals, which were typically more accurate.

While participants listened to a new interval and intended to reproduce it, the heartbeat-evoked potential slowly increased from negative to positive. The bigger the change in heartbeat-evoked potential, the shorter the interval the person produced on average. On the other hand, accuracy on the heartbeat counting task did not seem to be related to accurate time production, which conflicted with previous studies.

What's the impact?

This study adds to the evidence for embodied time cognition. It suggests that during time estimation, signals from the heart to the brain accumulate, helping us to know how much time has passed, and that this signal is calibrated differently across individuals. However, there is still a lot we don’t know about the causal chain of events and more exploration is needed in this relatively new research field.  

Using Brain Organoids To Model Neurodevelopmental Disorders

Post by Lila Metko

The takeaway

Neurodevelopmental Disorders (NDDs) are characterized by improper brain development and deficits in cognition and behavior. Organoids are three-dimensional cellular structures, grown from human stem cells that may provide a solution for modeling NDDs for potential human therapeutics.   

What's the science?

Research using human-induced pluripotent stem cells (iPSC) is becoming increasingly sophisticated, as it is possible to differentiate these cells into many specialized cell types. Previously, most research with iPSCs has used two-dimensional culture systems, which cannot model complex cell processes such as cell migration and high-complexity cell-cell interactions. This week in Brain, Dionne and colleagues review the ability for three-dimensional, human iPSC derived brain organoids to model many of the NDDs that are difficult to translate from animal models to humans. They discuss how organoids are not without drawbacks: genomes may be altered in the process of cell reprogramming, and there are no standardized procedures to validate the quality of new iPSC lines. Organoids are, however, becoming increasingly more advanced and are a powerful tool for studying NDDs as an alternative to animal models or clinical research in humans.  

How did they do it?

The authors investigated the role of organoids in finding treatments for several common NDDs and summarized many of the advanced experiments that have been done with organoids in recent years. Many of these NDDs have pathology that makes them difficult to model in animals. For example, microlissencephaly, a disorder characterized by lower levels of brain gyrification, is difficult to model in animals because rodent brains are normally lissencephalic. Other disorders, such as Fragile X syndrome, may necessitate organoid models because treatments that have shown high success rates in animals have proven to be untranslatable to humans. Organoids have also proved useful for disorders that are believed to develop pathology in a particular stage of cellular differentiation. Further, there are limitations to studying rodent organs because they develop differently than human organs and the developmental timeline is different. Therefore, organoids give researchers the opportunity to more accurately mimic the developmental pathways of the human brain and apply interventions at particular stages. 

What did they find?

Among the organoid models used for disorders discussed, many produced new data that could not be found in animal models. For example, in research of Fragile X Syndrome, a NDD caused by abnormal translation regulation, animal models showed that mGluR5 inhibition (excitatory) or enhancement of GABAergic signaling (inhibitory) reversed cellular and behavioral deficits. However, these therapies did not show promising results in clinical trials. Organoid models of Fragile X syndrome showed that within targets of the primary protein that is absent in the disorder, FMRP, 66% were human specific. This means that the majority of the targets that the missing protein in Fragile X Syndrome acts on are found only in humans. 

Additionally, there are promising results for using organoid models to map out a more human-like developmental timescale. Angelman Syndrome (AS), is an NDD in which a mutation causes a loss of function in a specific protein, UBE3A, leading to intellectual disabilities and seizures. Organoid models developed from patients with AS, have shown that in these specific organoids, UBE3A localizes to the cytoplasm at a different developmental stage than in a typically developing human. Another instance of organoids better mimicking the development of humans is in Tuberous Sclerosis Complex (TSC). In this disorder, cortical tubers, malformed regions within the cortex, are a major part of the disease pathology but do not develop in mouse models. Research with human-based organoids showed that TSC organoids had a different ratio of glial (supporting) cells to neurons than those in a typically developing human. 

What's the impact?

This review highlights a technology that has the potential to make huge gains in expanding our translational knowledge of neurodevelopmental disorders. These findings suggest that human iPSC organoids have already made big strides towards developing therapeutics for NDDs and will likely continue to in the future. Based on these findings, there is a high likelihood that future neuroscience research will be increasingly dependent upon organoid models as a route to finding effective therapies. 

Access the original scientific publication here.