Functional Features of Gene Expression

Functional linkages between genes.
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The Human Genome Project initiative provided researchers with an incredibly detailed blueprint for the building of each cell in the human body. The ultimate goal of scientists is to determine how genes (and the proteins they encode), function in the intact organism (1). This connection, from gene to function, is one that is studied in many different branches of science. Dr. Eswar Iyer, a member of the Cox Lab at George Mason University's Krasnow Institute for Advanced Study, and the numerous other faculty and lab members he works with take a systems neuroscience approach to better understand the concept.

Dr. Iyer presented part of the research he is currently involved in at Dr. Daniel Cox's lab. He began by clarifying exactly what is meant by a systems approach. The basic idea involves the use of reductionist methods while keeping the holistic view in mind.  This is all done without losing sight of the ultimate goal of the research - understanding gene function and determining how it fits into the bigger picture (2).

Dendrites are central to neuronal function.
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Neurons are highly polarized in their structure, having both axons and dendrites projecting outwards. Dr. Iyer and others at the Cox Lab focus mainly on dendrite morphology. Dendrites are the hallmark of neuronal identity and are central to neuronal function. They are also the primary site of synaptic and sensory input. They play a functional role in the establishment and maintenance of proper neuronal circuitry in a number of neuropathological disease states including autism and down syndrome (2). Dendrites have very unique and reproducible branching morphologies across species. This confirms that there are instructions being sent to the neurons that dictate its neuronal circuitry and branching morphologies. Understanding the mechanisms that control the acquisition and maintenance of neuronal class-specific dendritic morphology is a crucial part of the research being conducted at the Cox lab (2).

In order to attempt to make sense of this, a model system was needed. Dendritic arborization (da) neurons of the Drosophila Melanogaster (more commonly known as fruit flies) peripheral nervous system were used, as they provide an excellent model system for investigating class specific dendrite morphogenesis as well as sensory function (2, 3). Fruit flies are the perfect intermediate; they are a complex whole organism, yet simple enough for study. They possess about 85% of the genes of all the diseases studied in humans and thus, provide a fantastic system for studying a varying number of processes. Four classes of da neuron (Class I-IV), ordered by increasing dendritic complexity, are studied. Each class is involved in varying sensory modalities and behavioral studies can be conducted on these neurons. These neurons provide Dr. Iyer and others with the ability to analyze how neuronal diversity arises (2).

Development of different morphological classes of da neurons.
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Magnetic bead sorting.
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It was important to use a specific method to identify novel candidates involved in dendrite morphogenesis. Previously, the forward genetic screen method was used. This method proved to be slow, laborious, and random. A new approach known as reverse genetics was found to be more efficient. The reverse genetics method, when used alongside functional genomic analyses, provides a  faster and more directed approach for investigation of dendrite morphogenesis. Dr. Iyer, after explaining the specifics of this method, went on to outline the process. It begins with purification and isolation of da neuronal classes using an efficient technique known as 'magnetic bead sorting'. Gene expression profiling of classes is performed, followed by bioinformatics analyses to identify statistically enriched gene sets (2). The results of these analyses are functionally validated via a large scale in-vivo RNAi screen. Finally, the data provided by the RNAi screen is analyzed to identify the specific molecules involved in regulation of dendrite development (1). This process resulted in the team narrowing down approximately 750 transcription factors to a single gene that was found to have a perfect phenotype. The gene, named 'Bedwarfed', was analyzed by Dr. Iyer and his team in order to learn more about its function, behavior, and underlying molecular mechanisms (2).

A schematic association of forward and reverse genetic approaches for genetic association of phenotypes.
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Bedwarfed gene, after performing systemic characterization involving loss-of-function (LOF) and gain-of-function (GOF) analyses, was found to be essential in dendritic growth. It results in the shrinkage of dendritic branches, with no change in the total number of dendrites per neuron. Bedwarfed was also found to interact with a unique homeodomain transcription factor known as 'Cut' to regulate proper dendritic branching. The LOF and GOF studies conducted resulted in simplification of dendritic arbors. The knockdown (LOF) of the gene resulted in dwarfing and shrinking of dendrites. Dr. Iyer and his team expected overexpression (GOF) of the gene to result in a more complex morphology. However, the results of the findings were that the gene still simplified the neuron by removing fine dendritic branching (2). It was found that Bedwarfed plays a role in Cut-mediated dendritic branching. Turning down Cut in neurons was found to have similar effects as overexpression of Bedwarfed and a direct correlation was made between the two. Although Bedwarfed and Cut enhance each other's expression, they are not necessarily dependent on one another in order to be expressed. Bedwarfed also  interacts with ribosomal proteins to control growth and differentially regulate cytoskeletal proteins. The effect of Bedwarfed on the main cytoskeletal constituents of dendritic branches was also studied. It was found that the gene restricted tubulin levels while enhancing actin levels (2).

The research being conducted at the Cox lab is vital in developing a better understanding of the importance of dendritic morphogenesis and neuronal diversity. The work that has been done lays the groundwork for future research. Dr. Iyer mentioned the fact that the Bedwarfed gene is highly expressed in the human brain, retina, and in the nucleus and cytoplasm. A homolog of the gene is also involved in schizophrenia. Future work involves attempting to understand the underlying mechanism as well as testing the same hypothesis in the brain of rats and mice to see whether it is conserved across species. Mice and humans both have about 30,000 genes and share approximately 99% of them (4). Studying the genomic sequence of mice provides researchers with a powerful tool to improve their understanding of the role that genes play in human diseases. A relatively new area of study (and one that I am very interested in) is that of pharmacogenomics. This field involves the study of an individual's genetic inheritance to determine how that individual will respond to a certain drug. By better understanding dendrite morphogenesis and specific genes with a certain phenotype, would it be possible to determine the genes that play a role in alteration of drug metabolism and response? Pharmacogenomics is a promising field in that it might one day be possible to tailor drugs for the needs of each individual and adapted to each person's genetic makeup.

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References:

1. Alberts B, Johnson A, Lewis J, et al. Molecular Biology of the Cell. 4th edition. New York: Garland Science; 2002. Studying Gene Expression and Function. Available from: http://www.ncbi.nlm.nih.gov/books/NBK26818/

2. Iyer, Dr. Eswar. "From Gene to Function: A Systems Approach to Neuroscience", Cox Lab: Molecular Neuroanatomy and Developmental Neurogenetics, Krasnow Institute For Advanced Study. 25 October 2012. Seminar.

3. Jan, Y., Jan, L. Branching Out: Mechanisms of Dendritic Arborization. Nat Rev Neurosci. 2010 May;11(5):316-28. PMCID: PMC3079328. 

4. "Of Mice and Men - Striking Similarities at the DNA Level Could Aid Research." SFGate. Web. 28 Oct. 2012. 

<http://www.sfgate.com/news/article/of-mice-and-men-striking-similarities-at-the-2748350.php>.

Marching to the Beat of Calcium

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Calcium is one of the most important minerals found in our bodies and comprises approximately 1.5 to 2% of our body weight (1). Single-atom calcium ions are of the most versatile biological messengers known. Rapid, transient changes in calcium concentration directly control muscle contraction, cell locomotion, and neural transmission, among other things. Sustained, elevation of calcium signals is pivotal for numerous biological processes ranging from gene expression, to fertilization, to apoptosis or programmed cell death (2). Did you know that there is a functional linkage between intracellular calcium levels and cardiac arrhythmias? A better understanding of this relationship can very well lead to therapeutic prevention of life-threatening arrhythmias.

Dr. Saleet Jafri, a bioinformatics professor at George Mason University and a member of the Krasnow Institute of Advanced Study, has worked closely with faculty at GMU as well as at other universities. Their research efforts have culminated in the construction of a three-dimensional model simulation of the rat ventricular myocyte. The use of this stochastic model would allow them to make a connection between aberration in normal calcium homeostasis and how this can result in cardiac arrhythmias (3). In order to efficiently use this model, a numerical method was to be developed. Dr. Jafri and his team went on to develop the Ultrafast Monte Carlo Method, which was used to calculate the open probability of ryanodine receptors and the occurrence of a calcium leak. This GPU-enabled method is less expensive and more computationally efficient than other methods previously used for stochastic stimulations. The Ultrafast Monte Carlo Method employs the use of the Euler method, which is important for solving differential equations. By building this model, Dr. Jafri and his team attempt to answer fundamental questions regarding the mechanisms underlying arrhythmias that could not be answered with previous modeling efforts (2).

Process of excitation-contraction coupling in the cardiomyocte.
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Dr. Jafri clearly stressed the importance of understanding calcium dynamics and the mechanisms underlying it prior to understanding arrhythmias. Calcium acts as a signaling molecule in the excitation-contraction coupling of cardiac muscle. This physiological process relies predominantly on a mechanism known as calcium-induced calcium release (CICR). Central to this process are the calcium release units (CRUs). CRUs, consisting of t-tubules of cardiac muscle and the sarcoplasmic reticulum (SR) contain ryanodine receptors (RyRs) that, after detecting an influx of calcium, activate and result in the release of calcium from the SR to the cytoplasm (4). The release of calcium from the SR by activation of RyRs is triggered by the opening of L-type calcium channels or by the stochastic opening of a single RyR. These synchronized stochastic openings are referred to as calcium sparks (4).

Calcium sparks are the elementary release events that sum to produce a calcium transient, which is a term used to describe the increase in cytosolic calcium. Calcium sparks are visualized using confocal microscopy techniques. With regards to the termination of calcium release, many different elements come into play. According to Dr. Jafri, calcium sparks terminate because of the influence of three specific factors on RyRs gating: a large number of RyRs, coupled gating of RyRs, and finally, calcium concentration in the SR lumenal (2). Calcium sparks are important in maintaining calcium homeostasis via a mechanism known as 'calcium leak'. This calcium leak balances the SR calcium-ATPase flux. Increases in SR calcium means an increase in calcium leak (3). This results in calcium overload which causes membrane depolarization and leads to an arrhythmia. There is also an 'invisible leak', a certain amount of leak that has not been measured or accounted for. Dr. Jafri and his team address this issue using the 'sticky cluster model' (2).

Peaks of a calcium transient, action potential , and cardiac muscle contraction.
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Calcium sparks can be seen in this image as yellow and red spots. This cell was loaded with Fluo-3, a fluorescent  calcium indicator.
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Dr. Jafri and the team have implemented their three-dimensional stochastic model of calcium dynamics to better understand the primary mechanism underlying calcium wave generation. They examined the resting and individual calcium spark behavior using their 3D model and the Ultrafast Monte Carlo Method. They also simulated a SR calcium leak experiment in which caffeine was used. In addition, they examined the effects of phosphorylation on calcium spark generation. They have come to learn that the activation of a single RyR of the calcium release units would result in neighboring RyRs to become active as well, generating a synchronized influx of calcium from the SR to the cytoplasm (2). Once 6 or more RyRs open, the remaining channels open as well, resulting in a calcium spark. As for calcium release termination, it occurs by reduced calcium concentration in the SR which then results in stochastic closure, coupled gating, and reduced opening of RyRs (5).

The research that has been conducted by Dr. Jafri and others is pivotal in better understanding calcium entrained cardiac arrhythmias. Their work is invaluable in that it lays the groundwork on which future research can be built upon. Perhaps by using this model, in the future, researchers would be able to understand abnormalities in ryanodine receptors for example, or mutations associated with these receptors. New pharmacological or genetic strategies can be developed to treat disorders associated with the heart. There are certain rate and rhythm control medications that have been developed to help treat arrhythmias. Calcium channel blockers have been used as anti-arrhythmiac agents, but are associated with dangerous side effects and even death. Would it be possible to employ the Ultrafast Monte Carlo Method to simulate the effectiveness of medications to treat different heart conditions? Can the basic idea of stochastic stimulations be used in the treatment of other disorders?

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References:

1. http://www.crcnetbase.com/doi/abs/10.1201/9780203912393.ch6
2. Jafri, Dr. Saleet. "Understanding the Molecular Basis of Calcium-Entrained Cardiac Arrhythmia by GPU-Enabled Monte Carlo Simulation", Department of Molecular Neuroscience, Krasnow Institute For Advanced Study. 4 October 2012. Seminar.
3. Hoang-Trong, M. T., G. S. B. Williams, A. C. Chikando, E. A. Sobie, W. J. Lederer, and M. S. Jafri. 2011. Stochastic Simulation of Cardiac Calcium Dynamics and Waves.Conf Proc IEEE Eng Med Biol Soc. 2011: 4677-4680.
4. Williams, G. S. B., A. C. Chikando, T. M. Hoang-Trong, E. A. Sobie, W. J. Lederer, and M. S. Jafri. 2011. Dynamics of Calcium Sparks and Calcium Leak in Heart. Biophys. J.101:1287-1296.
5. Sobie, E. A., K. W. Dilly, J. d. S. Cruz, W. J. Lederer, and M. S. Jafri. 2002.Termination of cardiac of Ca²⁺ sparks: an investigative mathematical model of calcium-induced calcium release. Biophys. J. 83:59-78