As Tolstoy wrote in Anna Karenina, “Happy families are all alike; every unhappy family is unhappy in its own way.” The same might be said of the brain. Normal brains look and behave similarly, but those affected by different neurodegenerative diseases are unique, since each disease targets a select subset of cells. In Parkinson disease, for example, dopaminergic neurons in the substantia nigra suffer, while their neighbors in the tegmentum remain relatively unscathed. In amyotrophic lateral sclerosis, lower motor neurons bear the brunt of disease, while upper motor neurons are less likely to be affected. This selective cell vulnerability presents a puzzle, particularly in the case of disease caused by inherited mutations: If the mutation is present in every cell in the body, what leads some neurons to resist its effects while others degenerate?
Analyzing differences between affected and unaffected cells might provide the answer, but separating them has not always been easy. Increasingly, researchers have taken advantage of modern technology, such as laser capture microscopy, to isolate individual cells and compare their gene expression patterns. The mRNAs expressed in each cell type may hint at their vulnerabilities. Microarrays and other screening tools, researchers hope, will help determine why some cells falter, and others survive particular disease onslaughts.
How are these types of analyses advancing our understanding of selective cell vulnerability? A Webinar led on 14 September 2010 by Eva Hedlund of the Karolinska Institute in Stockholm, Sweden, explored the value of microdissection and microarray analysis in studying neurodegenerative diseases. Hedlund discussed her latest results on ALS, and Chee-Yeun Chung of MIT’s Whitehead Institute shared her data on selective cell vulnerability in Parkinson disease. Rickard Sandberg, also from the Karolinska Institute, presented a new technique—RNA deep sequencing—that allows him to discover not only which mRNAs are present in tissues, cell lines, or single cells, but which splice forms they represent. Joining these presenters for a panel discussion were Stanislav Karsten of the University of California in Los Angeles, and Stephen Ginsberg of the Nathan Kline Institute in Orangeburg, New York.
Given some technical difficulties experienced during the first presentation, we had re-recorded Dr. Eva Hedlund’s talk, which is available here below. The following talk, that of Chee-Yeun Chung, starts at minute 30, while that of Rickard Sandberg, begins at minute 48.
- View a larger version of Eva Hedlund's slides.
- View a larger version of Chee-Yeun Chung's slides.
- View a larger version of Rickard Sandberg's slides.
By Amber Dance
In general, neurodegenerative diseases target specific cells, leaving many of their closest neighbors relatively unscathed. What makes some cells so susceptible to disease while others are tough enough to withstand the same insults? Using laser capture microdissection and microarrays, researchers are starting to answer that question by comparing gene expression profiles among cells.
Eva Hedlund, of the Karolinska Institute in Stockholm, Sweden, recently reported on selective cell vulnerability in motor neuron diseases (Hedlund et al., 2010). She and her colleagues noted that although motor neurons degenerate in ALS, spinal muscular atrophy (SMA), and spinobulbar muscular atrophy (SBMA), each disease hits specific cell populations. All three conditions sicken ventral motor neurons, while only ALS and SBMA affect lower cranial nerves. Upper cranial nerves are usually spared.
To determine the differences among these three neural populations, Hedlund and colleagues used laser capture microdissection (LCM) to isolate motor neurons from different areas—midbrain cranial nerves, brain stem, and cervical spinal cord—of normal rats. They then used microarray analysis to look for differences in gene expression between single cells. The data indicate that IGF-1 and IGF-II, which can be neuroprotective, are highly expressed in upper cranial neurons—perhaps explaining how they resist degeneration. On the other hand, members of the ubiquitin-based proteolysis system are more strongly expressed in spinal motor neurons. Ubiquitin-mediated proteolysis has been implicated in motor neuron disease.
Chee-Yeun Chung of MIT’s Whitehead Institute has adopted a similar LCM strategy to study Parkinson disease (Chung et al., 2005). Chung and colleagues found that in mice, vulnerable A9 dopaminergic neurons, compared to A10s, express more of the pro-apoptotic genes caspase-7 and Bcl2-like 11, perhaps explaining why A9 neurons are more susceptible to neurodegeneration. More recently, the researchers found that in mice, primates, and humans, the transcription factor orthodenticle homeobox 2 is highly expressed in A10 neurons compared to A9 (Chung et al., 2010), raising the possibility that this protein might be neuroprotective. Further, they found that overexpressing this transcription factor in cultured neurons protected the cells from the toxin MPP+, which induces Parkinson disease in rodents. The work has also led them to examine the protein phosphatase inhibitor G-substrate and the ras-related protein RAB3B as protective factors in A10 neurons (Chung et al., 2009; Chung et al., 2007).
One shortcoming in standard microarray analysis is that while it can determine which genes are transcribed when and where, it does not always inform on alternative splicing patterns. To study transcriptomes at this level of detail, Rickard Sandberg, also at the Karolinska Institute, applies a new technique: deep RNA sequencing, also known as RNA-seq (reviewed in Wang et al., 2009; Ramsköld et al., 2009). For RNA-seq, researchers fragment and reverse transcribe whole RNA samples from tissues, cell lines, or single cells, then sequence all the cDNAs. Common splice forms will show up many times in the sequencing results, while rarer forms will not appear as often, allowing scientists to quantify splice form levels (Wang et al., 2008). RNA-seq is more sensitive than microarrays.
Alzforum is pleased to have Hedlund and her co-panelists share their data and expertise during this Webinar. As always, we welcome your comments both prior to and during the event.
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- Chung CY, Licznerski P, Alavian KN, Simeone A, Lin Z, Martin E, Vance J, Isacson O. The transcription factor orthodenticle homeobox 2 influences axonal projections and vulnerability of midbrain dopaminergic neurons. Brain. 2010 Jul;133(Pt 7):2022-31. PubMed.
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