What Do Day-Night Cycles Have to Do With Stroke Treatment?

Post by Anastasia Sares

What's the science?

Rats and mice are nocturnal: they are active during the night-time and sleep during the day. Human researchers, on the other hand, are diurnal; active in the day and sleeping at night. This simple fact means that a lot of pre-clinical trials (testing medication or treatment on an animal before it is tested in humans) happen during an animal’s sleep cycle, while most human stroke cases occur while the individual is awake. Sometimes a treatment’s effectiveness can vary depending on what point in the sleep cycle, or circadian rhythm, it is administered. This has recently proven to be the case with stroke, which happens when blood flow is blocked from one region of the brain (for example, by a blood clot). This week in Journal of Cerebral Blood Flow & Metabolism, Boltze and colleagues published a commentary about why circadian cycles matter for stroke treatment, signaling that we may have to adapt our methods for clinical and pre-clinical trials to accommodate these day-night cycles.

What do we already know?

In June of 2020, another team of researchers (Esposito and colleagues) examined a number of new stroke treatments that had passed the pre-clinical phase but failed at the clinical phase. In other words, these treatments seemed to work in rats or mice, but they didn’t benefit humans in the same way. The team showed that when the rodents were tested during their “active” phase (night-time) instead of their “inactive phase” (daytime), many of the treatments were not effective, just as they had seen in humans during the day.

Esposito and colleagues found that the penumbra, the brain tissue at the edge of the zone affected by a stroke, was smaller if the animals were awake at the time of injury. The neurons in the middle of the stroke zone will almost certainly die off, but the penumbra is alive for a little longer. It too, however, can die off in the hours following a stroke if treatment is not delivered quickly. The team suspected that the pre-clinical treatments didn’t work during the animal’s active time of day because the penumbra was smaller and there simply wasn’t much brain tissue left to treat.

What’s new?

Boltze proposed some ways of addressing circadian rhythm in future experiments. Some ways forward include testing diurnal animals like dogs or testing nocturnal animals during their active cycle (reversing the light/dark cycle in animal facilities so that human and rodent cycles align). Stroke treatments may also need to differ depending on the time of day the stroke occurs. The authors suggest that, for pre-clinical trials of new treatments, “the effect of intervention time should be systematically investigated,” documenting how well the treatment works during different times of the day. Then, during the clinical phase, a patient who presents with a stroke at night-time could be assigned to a different clinical trial than someone who comes in during the day, making sure that circadian rhythm is accounted for.

What's the bottom line?

Though humans share many features with our mammal cousins, it is important to remember that no animal model is perfect. This work provides an example of how small differences between human and rodent physiology can result in different responses to treatment. This recent research brings awareness to circadian rhythms as an important factor in pre-clinical trial development.

Boltze et al. Circadian effects on stroke outcome – Did we not wake up in time for neuroprotection? Journal of Cerebral Blood Flow & Metabolism (2020). Access the recent commentary here, and theoriginal Nature article by Esposito et al. here.

How the Hippocampus Builds Predictive Spatial Maps

Post by Giulia Baracchini

What’s the science?

Place cells, a type of neuron in the brain’s hippocampus, are involved in recreating spatial maps of the external world and thus play a key role in spatial learning and memory. Spatial learning requires the reactivation of place cells after spatial encoding has occurred, a phenomenon called place cell replay. However, place cells’ spatial representations are not static. Rodent studies have shown how place cells’ spatial representations are formed as animals learn and adapt to their changing environments. How place cell replay processes dynamically evolve during spatial learning remains unexplored. This week, in PNAS, Igata and colleagues tested how place cell replays change as rats learn a spatial task. 

How did they do it?

Rats were trained to run from a starting area to a checkpoint where they were given an intermediate reward, and then to a goal area where they received a final reward (pre-learning phase). After a few trials, the authors changed the location of the intermediate checkpoint and reward, requiring the rats to update their navigation strategies in order to obtain the reward (replacement phase). The animals eventually learned to run along the new path where they would receive a reward (post-learning phase). 

While the rats were performing the task, the authors recorded the spiking activity and theta-sequences (a measure of the spatial organization of the place cells) of multiple place cells located in the dorsal hippocampal CA1 region. They quantified the presence, frequency, directionality and sequence strength of sharp-wave ripple (SWR)-associated synchronous spikes, which are bursts of activity during which hippocampal place cells are activated. These reactivations of hippocampal place cells are referred to as place cell replays. They then used a statistical model (Bayesian decoding) to estimate how the rats’ spatial behaviour was represented by place cell replays. Lastly, to provide evidence for a causal link between learning-related replays, and animal behaviour during spatial learning, the authors transiently suppressed SWR-associated synchronous spikes after the replacement phase. They did so by selectively stimulating the ventral hippocampal commissure and delivering closed-loop feedback electrical stimulation.

What did they find?

The authors found that throughout the different learning stages, rats built a spatial representation of the environment by primarily recruiting (i) stable (i.e., similar across stages) sets of hippocampal place cells along with (ii) sets of place cells showing context-dependent properties (i.e., encoding specific locations). By feeding information about these cells’ preferred locations into their Bayesian model, the authors could successfully reconstruct an animal’s position in space. These findings demonstrate the role of the hippocampus in creating abstract, generalized memory maps.

As the rats were updating their navigational strategies, the authors found a significant increase in hippocampal theta-sequences and sequential SWR-associated synchronous spikes, compared to other learning phases. Interestingly, sequential place cell replays occurred for prioritized experiences only, in other words only salient and reward-related locations were replayed by separate synchronous events. Such preferential replay events were found to be greater for newly rewarded locations. While the rats learned about the new intermediate checkpoint area, most of these replay events represented the new path in the later phase of learning, even before the animals started taking the new path. The authors also found that the content and the directionality of the place cell replays changed as a function of learning over time. Together, these findings highlight the role of the hippocampus in building predictive maps of the environment that dynamically evolve as learning takes place. Finally, the authors reported that suppressing SWR-associated synchronized events impaired learning, suggesting that place cell replays are causally involved in the stabilization of newly learned behaviours.

What’s the impact?

This study highlights the key role of hippocampal place cell replays in building predictive, dynamic maps of the external environment. Importantly, the hippocampus replays salient or prioritized experiences to effectively encode them into memory. Further, such maps change as a function of learning and predict future behaviour.

Igata et al. Prioritized experience replays on a hippocampal predictive map for learning. Proceedings of the National Academy of Sciences (2020). Access the original scientific publication here.

A Coronavirus Protein Crosses the Blood-Brain-Barrier in Mice

Post by Leigh Christopher

What's the science?

COVID-19 has been associated with a number of central nervous system (CNS) symptoms including the loss of taste and smell, headaches, impaired consciousness, and even stroke. One reason for these symptoms could be that the SARS-CoV-2 virus (i.e., the virus responsible for COVID-19) enters the brain and acts directly on the CNS. Another possibility is those immune molecules known as cytokines (inflammatory molecules) associated with the virus cross the blood-brain-barrier, resulting in CNS symptoms. Yet a third possibility is that the virus sheds various proteins, which then cross the blood-brain-barrier and enter the brain. This week in Nature Neuroscience, Rhea and colleagues test whether the SARS-CoV-2 spike 1 protein (S1) can cross the blood-brain-barrier in mice.

How did they do it?

The authors radio-labelled S1 proteins from the SARS-CoV-2 virus, injected them intravenously into mice, and measured the blood-to-brain influx constant (a measure of the influx of S1 protein across the blood-brain-barriers). They did this using a method called multiple time regression analysis which allows for the measurement of protein influx to the brain while correcting for clearance of the protein out of the brain over time. They co-injected another radio-labelled protein along with the S1 protein that is known to have poor brain uptake, as a reference for how much S1 was crossing the blood-brain-barrier into the brain. The authors tested whether the S1 protein cleared the brain and entered other peripheral tissues and organs. A series of experiments were also performed to assess the mechanism of transport of the S1 protein across the blood-brain-barrier and into other tissues.

What did they find?

Radio-labelled S1 protein influx levels were significantly higher than the control protein, demonstrating that S1 does pass through the blood-brain-barrier and into the brain. They found that the virus entered a number of brain regions, and was also cleared from the brain through the blood, entering peripheral tissues, including the liver, kidney, and spleen. The authors attempted to understand the mechanism through which the S1 protein was transported across the blood-brain-barrier and into other tissues. When investigating the mechanism of transport of S1, they found evidence of blood-brain-barrier passage through adsorptive transcytosis, a mechanism where molecules bind to glycoproteins on endothelial cells and enter the brain through vesicle transport.

SARS-CoV-2 is thought to enter cells by binding to a protein called ACE2. The authors found that co-injection of ACE2 and radio-labelled S1 protein increased the influx of S1 protein into the brain and lungs, suggesting that S1 uptake into these tissues was mediated by ACE2. They also found strong evidence of the involvement of other receptors. Next, the authors wanted to assess whether S1 uptake is increased during an inflammatory state, which is typically induced by the virus. Upon injection of lipopolysaccharide (a substance inducing an inflammatory state), the influx of S1 protein to the lungs (via adsorptive transcytosis) was higher, and the influx of S1 protein to the brain was also higher (via blood-brain-barrier disruption). These findings suggest that inflammation further increases S1 protein entry into the brain and lungs.

What's the impact?

This study is the first to show that the S1 protein of SARS-CoV-2 crosses the blood-brain-barrier and enters the brain in mice. This research sheds light on the potential mechanisms by which the S1 protein enters the brain and other tissues. Further understanding the mechanism of uptake, and whether the virus itself can also pass into the brain will be an important question for future research. As this study was performed in mice, it will also be crucial to investigate whether S1 passes through the blood-brain-barrier in humans.

Rhea et al. The S1 protein of SARS-CoV-2 crosses the blood–brain barrier in mice. Nature Neuroscience (2020). Access the original scientific publication here.