Emerging Scholar Year-End Report - Jessica Nichols
Mild traumatic brain injury (mTBI) accounts for the majority (75%) of the 2.5 million brain injuries estimated to occur in the United States each year. Individuals that acquire a mTBI can experience a range of complications including cognitive deficits, sleep disturbances, and neuropsychiatric changes, with repeated mTBIs (rmTBI) resulting in a worse prognosis. Utilizing a clinically relevant mouse model of mTBI and rmTBI, I was able to recapitulate some of functional alterations experienced by the human population. My data reveled that while sustaining a single mTBI results in slight and acute impairments, mice receiving repeated mTBIs experience more robust and longer lasting deficits in learning and memory, sleep disturbances, and lack of motivation to perform activities of daily living. This mouse model was used in my subsequent studies and will be used in future research to evaluate injury mechanisms and therapeutics.
Following initial insult to the brain, alterations in the neurochemical, cellular, and metabolic environment occur which elicit a secondary injury cascade and ultimately lead to the functional deficits described previously. Neuroinflammation plays a key role in secondary injury, with the activation of transcription factor nuclear factor kappa B (NF-κB) and an increase in production of reactive species being two contributing factors. I investigated the efficacy of a drug, a catalytic oxidoreductant, in targeting these factors and thereby reducing inflammation post-rmTBI. My research demonstrated that drug administration post-rmTBI could decrease reactive species and NF-κB activation acutely and sub-acutely after injury. Current studies are looking at additional markers to determine the inflammatory state of the mouse brain post-rmTBI and drug administration; while, future studies plan to evaluate the effect of this drug on functional outcome.
After a single mTBI, 80-90% of individuals recover in approximately 1 week without intervention. The same does not hold true for repeated mTBIs. One aspect of my research sought to explore the mechanism behind this spontaneous recovery. Utilizing a transgenic mouse line with selectively labelled newborn granule cells, I evaluated the effect of mTBI and rmTBI on neurogenesis. No significant differences between groups were observed when I looked at the number of newborn neurons. However, future experiments plan to examine neurogenesis further by looking at how these newborn neurons are integrating into the CNS circuitry to determine if there are differences which could be contributing to the functional impairments seen after rmTBIs.
Emerging Scholar Year-End Report - Jada Vaden
The extensive synaptic networks between neurons allow information to flow throughout the brain, enabling consciousness, perception, movement, and learning. Breakdown of this transfer of information contributes to complex neurodevelopmental disorders ranging from autism to schizophrenia. Understanding the factors that enable reliable communication between neurons is therefore a critical goal of neuroscience.
Synaptic transmission occurs when an action potential invades a presynaptic terminal and causes the release of a vesicle of neurotransmitter. The neurotransmitter then binds to receptors in the postsynaptic cell, causing an electrical signal. It was believed, until fairly recently, that a presynaptic terminal could release, at most, one vesicle per action potential, and that the probability that any vesicles would be released was fairly low. However, evidence is mounting that a single terminal can release multiple vesicles under some circumstances. This process, termed multivesicular release (MVR), greatly enhances the reliability of neuronal communication, but the molecular events that allow it to occur remain unknown.
I investigated this question at the synapse between the climbing fiber and Purkinje cell in the cerebellar cortex. Previous work has established that MVR is prominent at this synapse; in fact, a single presynaptic terminal is thought to release 3-5 vesicles per action potential. My initial experiments suggested that protein kinase A (PKA), a molecular machine that modifies the activity of other proteins, was prominent at this synapse, so I asked whether PKA contributes to MVR. In my experiments, activating PKA increased MVR and, conversely, inhibiting PKA decreased MVR.
Because PKA regulates the activity of other proteins, the next challenge was to identify which of PKA’s targets is critical for MVR. I did this by testing whether activation of PKA still increased MVR in mice lacking the genes for various PKA targets. The prediction was that, in a mouse lacking PKA’s primary MVR-stimulating target, PKA activation would no longer enhance MVR. After performing these experiments in several lines of mice, I found that PKA activation did not enhance MVR in mice lacking the gene for synapsin. This suggests that PKA stimulates MVR by modifying the activity of synapsin. Moreover, because mutations in synapsin have been identified in human patients with autism, my results may shed some light on the deficits in neuronal communication observed in this disorder.
Ongoing experiments are focused on uncovering the mechanism by which PKA and synapsin increase MVR. Specifically, I’m testing whether activation of PKA increases the probability that a vesicle of neurotransmitter is released in response to an action potential or, instead, increases the number of vesicles available for release. While preliminary results support the latter explanation, I have planned several additional experiments to strengthen this conclusion.
The Whit Mallory Fellowship has been instrumental in my progress during the past year. Funds from the fellowship allowed me to obtain genetically modified mice and the mission of Civitan International inspired me to choose PKA targets that had previously been implicated in intellectual disorders. The fellowship also allowed me to visit a lab at the University of Texas to learn a new surgical technique and travel to a premier conference to present my results. Discussions with leading scientists at this conference helped me to design experiments to better understand the mechanism by which PKA increases MVR. Finally, I have been able to hire two talented pre-med students to assist with these experiments. The time they spend in lab will help to further my research, prepare them for success in medical school, and allow me to hone my mentoring abilities for the next step in my career.
Raise the Roof for Rett
Visscher Lab Makes News
Computing challenges are found across the UAB campus, from physics and neurology to genetics and the microbiome. Alabama’s most advanced supercomputer is now at UAB, making it possible to solve these challenges.
Kristina Visscher is using fMRI images from several hundred brains to learn how the brain adapts after long-term changes in vision.What do the human brain, the 3 billion base-pair human genome and a tiny cube of 216 atoms have in common?
All of them, from the tiny cube to the 3-pound human brain, create incredibly complex computing challenges for University of Alabama at Birmingham researchers, and aggressive investments in UAB’s IT infrastructure have opened new possibilities in innovation, discovery and patient care.
For example, Kristina Visscher, Ph.D., assistant professor of neurobiology, UAB School of Medicine, uses fMRI images from several hundred human brains to learn how the brain adapts after long-term changes in visual input, such as macular degeneration. Frank Skidmore, M.D., an assistant professor of neurology in the School of Medicine, studies hundreds of brain MRI images to see if they can predict Parkinson’s disease.
David Crossman, Ph.D., bioinformatics director in UAB’s Heflin Center for Genomic Science, deciphers the sequences of human genomes for patients seeking a diagnosis in UAB’s Undiagnosed Diseases Program, and he processes DNA sequencing for UAB researchers who need last-minute data for their research grant applications.
Ryoichi Kawai, Ph.D., an associate professor of physics in the UAB College of Arts and Sciences, is laying the groundwork for a better infrared laser by calculating the electronic structure for a cube made up of just 216 atoms of zinc sulfide doped with chromium or iron.
Each researcher faces a mountain range of computational challenges. Those mountains are now easier to scale with UAB’s new supercomputer — the most advanced in Alabama for speed and memory.
The tiny cubeThe 216-atom electronic structure problem “is the largest calculation on campus, by far,” Kawai said. “If you give me 2,000 cores, I can use them. If you give me 10,000 cores, I can use them all without losing efficiency.” (UAB's new supercomputer has 2,304 cores.)
| Learn more about UAB’s new supercomputer in this story
BrainsIn their research, both Skidmore and Visscher have to compare brains with other brains. Because each brain differs somewhat in size, shape and surface folds, every brain has to be mapped onto a template to allow comparisons.
Physicist Kawai describes his computations as the most intensive on campus.“We want to capture information in an image, such as information on an individual’s brain condition,” Skidmore said. “The information we are trying capture, however, can often be difficult to see in the sea of data we collect. One brain may contain millions of bits of data in the form of ‘voxels,’ which are a bit like the pixels on your TV but in three dimensions.”
“When we map to a template,” Skidmore said, “we quadruple the data. When we ask, ‘How does this compare to a healthy brain?’ we double the data again. Then if we look across one brain or across multiple kinds of brain images, the amount of data truly explodes.”
Physicist Ryoichi Kawai's complex calculations of the electronic structure of a cube of atoms are laying the groundwork for better lasers.“This is made even more complex by the fact that a given image can include more than three dimensions of information,” he said. “One type of image we use generates 5-dimensional brain maps. Since we can’t see in five dimensions, we ask the computer to work in these higher-dimensional spaces to help us pull the information out of the data.”
To look at the adult brain’s plasticity — the ability to change function and structure through new synaptic connections — Visscher studies visual processing.
“Because we look at spatial and temporal data, the number of pieces of information is huge — gigabytes per subject,” she said. “We need to do correlations on all the data points at the same time. To get faster, we optimize the data analysis with a lot of feedback. Then we run what we learned from one brain on a hundred brains.”
UAB customersCrossman deciphers the sequences of human genomes for patients seeking a diagnosis, and he processes DNA sequencing for UAB researchers. Providing excellent customer service to his clients is vital, Crossman says, and it takes computer power to crunch genome sequencing data for those researchers, physicians and patients.
Managing traffic on the new UAB computer clusterSize:
The data floodgates of genomics burst open about a dozen years ago with the arrival of next-generation, high-throughput sequencing, says Elliot Lefkowitz, Ph.D., director of Informatics for the UAB Center for Clinical and Translational Science. Lefkowitz has been serving the bioinformatics needs of the UAB Center for AIDS Research for 25 years, and now also handles bioinformatics for the UAB Microbiome Facility. His team has grown to five bioinformaticians and several programmers.
“We deal with billions of sequences when we do a run through the DNA sequencing machine,” Lefkowitz said. “We need to compare every one of the billion ‘reads’ (the 50- to 300-base sequence of a short piece of DNA) to every other one. With high-performance computing and thousands of nodes, each one does part of the job.”
“In not too many years,” Lefkowitz speculated, “we will be sequencing every patient coming into University Hospital.”
Changes like that mean ever-increasing computer demands.
“Biomedical research,” Crossman said, “now is big data.”