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Wednesday, April 1st, 2020
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| 10:59a |
How dopamine drives brain activity Using a specialized magnetic resonance imaging (MRI) sensor, MIT neuroscientists have discovered how dopamine released deep within the brain influences both nearby and distant brain regions.
Dopamine plays many roles in the brain, most notably related to movement, motivation, and reinforcement of behavior. However, until now it has been difficult to study precisely how a flood of dopamine affects neural activity throughout the brain. Using their new technique, the MIT team found that dopamine appears to exert significant effects in two regions of the brain’s cortex, including the motor cortex.
“There has been a lot of work on the immediate cellular consequences of dopamine release, but here what we’re looking at are the consequences of what dopamine is doing on a more brain-wide level,” says Alan Jasanoff, an MIT professor of biological engineering, brain and cognitive sciences, and nuclear science and engineering. Jasanoff is also an associate member of MIT’s McGovern Institute for Brain Research and the senior author of the study.
The MIT team found that in addition to the motor cortex, the remote brain area most affected by dopamine is the insular cortex. This region is critical for many cognitive functions related to perception of the body’s internal states, including physical and emotional states.
MIT postdoc Nan Li is the lead author of the study, which appears today in Nature.
Tracking dopamine
Like other neurotransmitters, dopamine helps neurons to communicate with each other over short distances. Dopamine holds particular interest for neuroscientists because of its role in motivation, addiction, and several neurodegenerative disorders, including Parkinson’s disease. Most of the brain’s dopamine is produced in the midbrain by neurons that connect to the striatum, where the dopamine is released.
For many years, Jasanoff’s lab has been developing tools to study how molecular phenomena such as neurotransmitter release affect brain-wide functions. At the molecular scale, existing techniques can reveal how dopamine affects individual cells, and at the scale of the entire brain, functional magnetic resonance imaging (fMRI) can reveal how active a particular brain region is. However, it has been difficult for neuroscientists to determine how single-cell activity and brain-wide function are linked.
“There have been very few brain-wide studies of dopaminergic function or really any neurochemical function, in large part because the tools aren’t there,” Jasanoff says. “We’re trying to fill in the gaps.”
About 10 years ago, his lab developed MRI sensors that consist of magnetic proteins that can bind to dopamine. When this binding occurs, the sensors’ magnetic interactions with surrounding tissue weaken, dimming the tissue’s MRI signal. This allows researchers to continuously monitor dopamine levels in a specific part of the brain.
In their new study, Li and Jasanoff set out to analyze how dopamine released in the striatum of rats influences neural function both locally and in other brain regions. First, they injected their dopamine sensors into the striatum, which is located deep within the brain and plays an important role in controlling movement. Then they electrically stimulated a part of the brain called the lateral hypothalamus, which is a common experimental technique for rewarding behavior and inducing the brain to produce dopamine.
Then, the researchers used their dopamine sensor to measure dopamine levels throughout the striatum. They also performed traditional fMRI to measure neural activity in each part of the striatum. To their surprise, they found that high dopamine concentrations did not make neurons more active. However, higher dopamine levels did make the neurons remain active for a longer period of time.
“When dopamine was released, there was a longer duration of activity, suggesting a longer response to the reward,” Jasanoff says. “That may have something to do with how dopamine promotes learning, which is one of its key functions.”
Long-range effects
After analyzing dopamine release in the striatum, the researchers set out to determine this dopamine might affect more distant locations in the brain. To do that, they performed traditional fMRI imaging on the brain while also mapping dopamine release in the striatum. “By combining these techniques we could probe these phenomena in a way that hasn’t been done before,” Jasanoff says.
The regions that showed the biggest surges in activity in response to dopamine were the motor cortex and the insular cortex. If confirmed in additional studies, the findings could help researchers understand the effects of dopamine in the human brain, including its roles in addiction and learning.
“Our results could lead to biomarkers that could be seen in fMRI data, and these correlates of dopaminergic function could be useful for analyzing animal and human fMRI,” Jasanoff says.
The research was funded by the National Institutes of Health and a Stanley Fahn Research Fellowship from the Parkinson’s Disease Foundation. | | 1:59p |
New sensors could offer early detection of lung tumors People who are at high risk of developing lung cancer, such as heavy smokers, are routinely screened with computed tomography (CT), which can detect tumors in the lungs. However, this test has an extremely high rate of false positives, as it also picks up benign nodules in the lungs.
Researchers at MIT have now developed a new approach to early diagnosis of lung cancer: a urine test that can detect the presence of proteins linked to the disease. This kind of noninvasive test could reduce the number of false positives and help detect more tumors in the early stages of the disease.
Early detection is very important for lung cancer, as the five-year survival rates are at least six times higher in patients whose tumors are detected before they spread to distant locations in the body.
“If you look at the field of cancer diagnostics and therapeutics, there’s a renewed recognition of the importance of early cancer detection and prevention. We really need new technologies that are going to give us the capability to see cancer when we can intercept it and intervene early,” says Sangeeta Bhatia, who is the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, and a member of MIT’s Koch Institute for Integrative Cancer Research and the Institute for Medical Engineering and Science.
Bhatia and her colleagues found that the new test, which is based on nanoparticles that can be injected or inhaled, could detect tumors as small as 2.8 cubic millimeters in mice.
Bhatia is the senior author of the study, which appears today in Science Translational Medicine. The paper’s lead authors are MIT and Harvard University graduate students Jesse Kirkpatrick and Ava Soleimany, and former MIT graduate student Andrew Warren, who is now an associate at Third Rock Ventures.
Targeting lung tumors
For several years, Bhatia’s lab has been developing nanoparticles that can detect cancer by interacting with enzymes called proteases. These enzymes help tumor cells to escape their original locations by cutting through proteins of the extracellular matrix.
To find those proteins, Bhatia created nanoparticles coated with peptides (short protein fragments) that are targeted by cancer-linked proteases. The particles accumulate at tumor sites, where the peptides are cleaved, releasing biomarkers that can then be detected in a urine sample.
Her lab has previously developed sensors for colon and ovarian cancer, and in their new study, the researchers wanted to apply the technology to lung cancer, which kills about 150,000 people in the United States every year. People who receive a CT screen and get a positive result often undergo a biopsy or other invasive test to search for lung cancer. In some cases, this procedure can cause complications, so a noninvasive follow-up test could be useful to determine which patients actually need a biopsy, Bhatia says.
“The CT scan is a good tool that can see a lot of things,” she says. “The problem with it is that 95 percent of what it finds is not cancer, and right now you have to biopsy too many patients who test positive.”
To customize their sensors for lung cancer, the researchers analyzed a database of cancer-related genes called the Cancer Genome Atlas and identified proteases that are abundant in lung cancer. They created a panel of 14 peptide-coated nanoparticles that could interact with these enzymes.
The researchers then tested the sensors in two different mouse models of cancer, both of which are engineered with genetic mutations that lead them to naturally develop lung tumors. To help prevent background noise that could come from other organs or the bloodstream, the researchers injected the particles directly into the airway.
Using these sensors, the researchers performed their diagnostic test at three time points: 5 weeks, 7.5 weeks, and 10.5 weeks after tumor growth began. To make the diagnoses more accurate, they used machine learning to train an algorithm to distinguish between data from mice that had tumors and mice that did not.
With this approach, the researchers found that they could accurately detect tumors in one of the mouse models as early as 7.5 weeks, when the tumors were only 2.8 cubic millimeters, on average. In the other strain of mice, tumors could be detected at 5 weeks. The sensors’ success rate was also comparable to or better than the success rate of CT scans performed at the same time points.
Reducing false positives
The researchers also found that the sensors have another important ability — they can distinguish between early-stage cancer and noncancerous inflammation of the lungs. Lung inflammation, common in people who smoke, is one of the reasons that CT scans produce so many false positives.
Bhatia envisions that the nanoparticle sensors could be used as a noninvasive diagnostic for people who get a positive result on a screening test, potentially eliminating the need for a biopsy. For use in humans, her team is working on a form of the particles that could be inhaled as a dry powder or through a nebulizer. Another possible application is using these sensors to monitor how well lung tumors respond to treatment, such as drugs or immunotherapies.
“A great next step would be to take this into patients who have known cancer, and are being treated, to see if they're on the right medicine,” Bhatia says.
She is also working on a version of the sensor that could be used to distinguish between viral and bacterial forms of pneumonia, which could help doctors to determine which patients need antibiotics and may even provide complementary information to nucleic acid tests like those being developed for Covid-19. Glympse Bio, a company co-founded by Bhatia, is also working on developing this approach to replace biopsy in the assessment of liver disease.
The research was funded by the Koch Institute Support (core) Grant from the National Cancer Institute, the National Institute of Environmental Health Sciences, the National Science Foundation, the Ludwig Center for Molecular Oncology at MIT, the Koch Institute’s Marble Center for Cancer Nanomedicine, the Koch Institute Frontier Research Program through a gift from Upstage Lung Cancer, and Johnson and Johnson. | | 11:59p |
Technique reveals how crystals form on surfaces The process of crystallization, in which atoms or molecules line up in orderly arrays like soldiers in formation, is the basis for many of the materials that define modern life, including the silicon in microchips and solar cells. But while many useful applications for crystals involve their growth on solid surfaces (rather than in solution), there has been a dearth of good tools for studying this type of growth.
Now, a team of researchers at MIT and Draper has found a way to reproduce the growth of crystals on surfaces, but at a larger scale that makes the process much easier to study and analyze. The new approach is described in a paper in the journal Nature Materials, by Robert Macfarlane and Leonardo Zomberg at MIT, and Diana Lewis PhD ’19 and David Carter at Draper.
Rather than assembling these crystals from actual atoms, the key to making the process easy to observe and quantify was the use of “programmable atom equivalents,” or PAEs, Macfarlane explains. This works because the ways atoms line up into crystal lattices is entirely a matter of geometry and doesn’t rely on the specific chemical or electronic properties of its constituents.
The team used spherical nanoparticles of gold, coated with specially selected single strands of genetically engineered DNA, giving the particles roughly the appearance of Koosh balls. Single DNA strands have the inherent property of attaching themselves tightly to the corresponding reciprocal strands, to form the classic double helix, so this configuration provides a surefire way of getting the particles to align themselves in precisely the desired way.
“If I put a very dense brush of DNA on the particle, it’s going to make as many bonds with as many nearest neighbors as it can,” Macfarlane says. “And if you design everything appropriately and process it correctly, they will form ordered crystal structures.” While that process has been known for some years, this work is the first to apply that principle to study the growth of crystals on surfaces.
“Understanding how crystals grow upward from a surface is incredibly important for a lot of different fields,” he says. The semiconductor industry, for example, is based on the growth of large single-crystal or multi-crystalline materials that must be controlled with great precision, yet the details of the process are difficult to study. That’s why the use of oversized analogs such as the PAEs can be of such benefit.
The PAEs, he says, “crystallize in exactly the same pathways that molecules and atoms do. And so they are a very nice proxy system for understanding how crystallization occurs.” With this system, the properties of the DNA dictate how the particles assemble and the 3D configuration they end up in.
They designed the system such that the crystals nucleate and grow starting from a surface and “by tailoring the interactions both between particles, and between the particles and the DNA-coated surface, we can dictate the size, the shape, the orientation and the degree of anisotropy (directionality) in the crystal,” Macfarlane says.
“By understanding the process this is going through to actually form these crystals, we can potentially use that to understand crystallization processes in general,” he adds.
He explains that not only are the resulting crystal structures about 100 times larger than the actual atomic ones, but their formation processes are also much slower. The combination makes the process much easier to analyze in detail. Earlier methods of characterizing such crystalline structures only showed their final states, thus missing complexities in the formation process.
“I could change the DNA sequence. I can change the number of DNA strands in the particle. I can change the size of the particle and I can tweak each of these individual handles independently,” Macfarlane says. “So if I wanted to be able to say, OK, I hypothesize that this particular structure might be favored under these conditions if I tuned the energetics in such a way, that’s a much easier system to study with the PAEs than it would be with atoms themselves.”
The system is very effective, he says, but DNA strands modified in a manner that allows for attachment to nanoparticles can be quite expensive. As a next step, the Macfarlane lab has also developed polymer-based building blocks that show promise in replicating these same crystallization processes and materials, but can be made inexpensively at a multigram scale.
The work was partly supported by a Draper fellowship and the National Science Foundation and used facilities of the Materials Technology Laboratory at MIT. |
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