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Research at Mass General
The research efforts at the Advanced Tissue Resource Center, part of the Department of Neurology at Mass Gen Hospital, have led to significant contributions to the understanding of many types of neurologic and psychiatric diseases.
We have successfully employed the highly specialized technological process of laser capture microdissection, (micro dissecting brain tissue with an instrument called a laser-capture microscope) in order to determine which specific molecules are contained in individual cells and/or regions of the brain.
Historically, we have participated as members of neuroscience teams studying the following:
Our ongoing research projects focus on several areas of basic and clinical neuroscience, including:
Charles Vanderburg, PhDDirectorContact by email
Elizabeth BienTechnicianContact by email
Lisa Genevieve RycynaTechnicianContact by email
Maximillian StrunzGraduate StudentContact by email
Galit Frydman, DVMPostdoctoral FellowContact by email
Matthew Frosch, MD, PhDFaculty CoordinatorContact by email
The objective of this study is to profile microRNAs in brain tissue and biofluids of patients with various neurodegenerative and psychiatric diseases.
MicroRNAs (miRNA) are short, non-coding ribonucleic acids (RNAs) that control gene expression at the posttranscriptional level by binding to the 3' untranslated region of target messenger RNAs (mRNAs), causing their translational inhibition or degradation.
Each miRNA can regulate thousands of different mRNA targets, modifying an exceptionally large number of genes, whereas a single mRNA is translated into a single protein. Ergo, miRNA levels may provide a better indication of a cell’s physiological state in health and in disease.
A demonstration of the cell-selective accuracy of laser-capture microscopy (LCM). Shown are microdissections of human brain tissue down to the single cell level, allowing us to isolate individual neural, glial and vascular components. The upper panels show intact, appropriately immunostained brain tissue sections indicating the cellular targets (astrocytes, capillary endothelial cells, neurons or microglia) while the lower panels show the corresponding post-LCM cellular target microdissected onto the surface of a collection device.
Identifying miRNA expression signatures has thus become an attractive technique that can produce robust neurophysiological and neuropathological data. We and others have begun to assess the levels of microRNAs in brain tissue, blood and cerebrospinal fluid (CSF) of patients with various neurodegenerative and psychiatric diseases.
The importance of non-coding RNA based regulation has become even more apparent of late. A recent Cell review entitled “A ceRNA Hypothesis: The Rosetta Stone of a Hidden RNA Language” describes how non-coding RNAs (ncRNAs) may “talk” to each other in a unified way, hypothetically predicting a previously unimagined ncRNA-dependant regulatory network.
Also appearing recently is a report (Cell Research (2012) 22:107–126) that rice-specific miRNA 168a can transfer to the digestive system, circulating blood and the liver of mammals upon consumption, and directly regulate the low density lipoprotein receptor adaptor protein. This extraordinary finding implies that miRNA signaling is so important and conserved that its effects can even be transferred across kingdoms.
As such, miRNA’s role as signaling moieties (the signaling parts of a molecule) and master regulators of cellular processes is affirmed, making them excellent candidates for biomarkers of physiologic and pathologic states. miRNAs are also more stable and resistant to degradation and posttranslational modification than mRNAs and proteins, making them better candidates for biomarker studies. Additionally, miRNAs can be amplified from samples with rarified content, whereas proteins cannot.
By using sensitive and specific quantative reserve-transcriptase polymerase chain reaction (qRT-PCR) technology, it is possible to detect altered expression of regional and stage-specific miRNAs in the brains and biofluids of these patients. Many of the miRNAs have been linked to molecular pathways, including neuronal differentiation, glutamate metabolism, innate immunity and cell survival.
For example, miR-9 and miR-132 downregulation has been correlated to impaired neurogenesis and neuronal differentiation. These miRNA profile changes might be specific markers for sporadic Alzheimer’s disease (AD). In fact, any miRNA changes could be disease-causing or may exacerbate an underlying pathology.
Thus, linking miRNAs to their specific targets could reveal novel pathways for disease progression. By analogy, if any neurodegenerative disease is caused or exacerbated by altered miRNA(s), then these could potentially serve as sensitive and specific biomarkers and thereby reveal the underlying disease pathology.
However, we have come to realize that miRNA expression changes in brain tissue occur at relatively modest levels. Subtle fold-changes on the order of <1 to ~2 fold are enough to alter the balance of a cell’s expression of a given miRNA-regulated protein or ontological cassette. Therefore, detecting and accurately documenting such small changes in neuropathological samples presents a considerable technical challenge.
We have taken an approach which couples the cell-selective accuracy of laser-capture microscopy with the distinct assay sensitivity advantage of digital droplet PCR (ddPCR). Thanks to Poisson mathematics, no housekeeper miRNAs or DDCt calculations are needed for ddPCR, and the very small input requirement allows us to place the entire laser-captured cell contents into a single 20,000 nano-droplet ddPCR reaction. This allows us to assay individual neural cells using a multiplexed HEX/EVA assay in order to count the molecular numbers of candidate miRNA(s) and accurately assess comparative expression ratios.
Currently, we are building a repository of miRNA expression values in the various neural cellular components of non-diseased control samples.
We are looking forward to using this technique on various neurodegenerative disease samples for comparison.
The objective of this study is to confirm the participation of Secreted Protein Acidic and Rich in Cysteine (SPARC) and hevin in the neuroinflammatory processes associated with Alzheimer’s disease.
Alzheimer’s disease is an age-related progressive form of dementia that features neuronal loss caused by intracellular and extracellular protein deposition. Neurodegeneration is accompanied by neuroinflammation that mainly involves microglia, the resident innate immune cell population of the brain.
During Alzheimer’s disease microglia shift their phenotype, and it has been suggested that they express matricellular proteins (in particular SPARC and hevin) that facilitate migration of other immune cells, such as blood-derived dendritic cells. These proteins contribute to the neuroimmune response and play a crucial role in functional tissue repair.
By investigating post-mortem human brain tissue, we confirmed the participation of SPARC and hevin in neuroinflammatory processes and suggest an infiltration of myeloid-derived immune cells to the areas of diseased tissue. SPARC is highly expressed during Alzheimer’s disease and collocates to protein deposits, thus conducing actively to cerebral inflammation and subsequent tissue repair.
Secreted protein acidic and rich in cysteine (SPARC) is expressed by microglia found in close proximity to pathological protein aggregates. A: Positive SPARC staining, shown in green and auto-fluorescent lipofuscin in red. B: White-light image of Iba-1 positive microglia, immunoperoxidase stain. C: ThioS staining against amyloid plaques. D: Merged image of A and C at the exact same location as in B, allowing for the conclusion that microglia express SPARC and that there is an association in between SPARC expression and the pathological hallmarks of Alzheimer‘s disease.
The objective of this study is to demonstrate the importance of fiber type-specific expression profiling in understanding skeletal muscle biology, and provides a practical method of performing such research.
Skeletal muscle contains various myofiber types closely associated with satellite stem cells, vasculature and neurons. During injury, growth, atrophy or diseases of skeletal muscle, the myofiber types, ratios of these types within a given muscle, and recruitment/loss of myofibers from motor units change, which makes it necessary to view skeletal muscle not as a whole but rather as a collection of microscopic myofiber sub-populations.
Thus, when performing genetic or proteomic expression analysis in any of the neuromuscular diseases, it is difficult to obtain sufficient cellular specificity to resolve differences associated with individual myofiber or motor unit sub-types.
We are using a simple histochemical method (metachromatic staining) to simultaneously identify Type I, IIA, IIB and IIC myofibers in frozen muscle sections of control and atrophic muscle followed by laser-capture micro dissection (LCM) of individual fiber types, myonuclear domains and satellite cells. Quantitative real time polymerase Chain Reaction (qPCR) was used to verify the integrity of the cell-specific RNAs harvested, while qPCR and surface enhanced laser desorption ionization-time of flight mass spectromer (SELDI-TOFMS) were used to quantify atrophy-associated changes in mRNA and protein levels within individual fiber types that could not be resolved by expression analysis of whole muscle.
Laser capture microdissection (LCM) of a Type I myofiber from a control rat gastrocnemius muscle cross section stained with a metachromatic ATPase stain. A: Depicts the initial section illustrating differential staining of Type I, IIA and IIB myofibers. B: Depicts laser targeting of the Type I myofiber. C: Depicts the remaining section after microdissection of the laser-targeted region. D: Depicts the excised Type I myofiber sample located on the collection cap of the LCM instrument.
The objective of this study is to test the hypothesis that the exosomal miRNA content of the cerebrospinal fluid (CSF) of humans with Alzheimer's disease differs from the content of non-demented controls.
Alzheimer’s disease (AD), the most common type of aging-associated dementia, is characterized by progressive accumulation of intracellular neurofibrillary tangles that are composed of aggregates of abnormal hyperphosphorylated microtubule-associated protein tau, and extracellular amyloid plaques comprised of amyloid β-peptide (Aβ), which are produced by processing of amyloid precursor protein (APP).
Human CSF-derived exosomes purified by differential ultracentrifugation and prepared for electron microscopy show 50-60nm diameters. 30,000x magnification.
Plaques and tangles are accompanied by neuron degeneration and predominantly affect regions of the basal forebrain, hippocampus and association cortices.
To date, the only available treatments have modest effects on disease progression and on relieving symptoms,possibly due to delayed diagnosis and treatment initiation.
AD-related changes in the brain are well advanced by the time the symptoms of dementia appear. Thus, understanding the early pathogenesis of the disease and discovering a reliable early diagnostic test or biomarker for AD before the clinical symptoms occur might increase the likelihood to attenuate AD progression before there is a significant neuronal loss.
Recent evidence suggests that microRNAs (miRNAs), short non-coding RNA molecules that regulate gene expression, may play a critical role in AD, and that such miRNAs are present in exosomes (organelles in cells) and can be used as diagnostic markers.
Our ongoing study shows the presence of specific miRNAs in human CSF and differences in the CSF exosomal miRNA content between AD patients and non-demented controls. The profile of these AD-related CSF exosomal miRNAs could potentially be used to establish novel diagnostic biomarkers.
1. Metallosis in a dog as a long-term complication following total hip arthroplasty. Frydman GH, Bendapudi P, Vanderburg C, Marini B, Toner M, Fox JG, Tompkins RG. 2017. Veterinary Pathology (in press).
2. Exosomal miR-149 and miR-29c as Candidates for Bipolar Disorder Biomarkers.
Jason L. Choi, Patricia F. Kao, Elena Itriago, Yougen Zhan, James A. Kozubek,
Andrew G. Hoss, Meredith G. Banigan,Charles R. Vanderburg, Amir Rezvani, and Ivana Delalle. 2017. Neuropsychiatric Genetics (in press).
3. A Circulating microRNA Signature Predicts Age-Based Development of Lymphoma. Beheshti A, Vanderburg C, McDonald JT, Ramkumar C, Kadungure T, Zhang H, et al. 2017. PLoS ONE 12(1): e0170521 PMID: 28107482
4. Local and Systemic Changes Associated with Long-Term, Percutaneous, Static Implantation of Titanium Alloys in Rhesus Macaques (Macaca mulatta). Galit H Frydman, Robert P Marini, Vasudevan Bakthavatchalu, Biddle Kathleen, Sureshkumar Muthupalani, Charles R. Vanderburg, Barry Lai, Pavan K Bendapudi, Ronald G Tompkins, and James G Fox. 2017. JAALAS Comparative Medicine. Volume 67 (2)
5. Pathologic correlations of [F-18]-AV-1451 imaging in non-Alzheimer tauopathies. Marta Marquié, Marc D. Normandin, Avery C. Meltzer, Michael Siao, Nicolas V. Andrea, William E. Klunk, Chester Mathis, Milos D. Ikonomovic, Manik Debnath, Elizabeth A. Bien, Charles R. Vanderburg, Isabel Costantino, Sara Makaretz, Sarah L. DeVos, Derek Oakley, Stephen N. Gomperts, John H. Growdon, Bradford C. Dickerson, Matthew P. Frosch, Bradley T. Hyman, Keith A. Johnson, and Teresa Gómez-Isla. 2017. Annals of Neurology 81(1) 117-128 PMID: 27997036
6. The melanoma-linked “redhead” gene MC1R supports dopaminergic neuron survival. Xiqun Chen, Hongxiang Chen, Michael Maguire, Bailiu Ya, Waijiao Cai, Fuxing Zuo, Robert Logan, Maryam Rahimian, Katey Robinson, Charles R. Vanderburg, Yang Yu, Yinsheng Wang, David E. Fisher & Michael A. Schwarzschild. 2016. Annals of Neurology PMID: 28019657
7. Coagulation Biomarkers in Healthy Chinese-Origin Rhesus Macaques (Macaca mulatta). Frydman GH, Bendapudi P, Marini RP, Vanderburg CR, Tompkins RG, Fox JG. 2016. J Am Assoc Lab Anim Sci. 55(3):252-9. PMID: 27177557
8. The Impact of Age and Sex in DLBCL: Systems Biology Analyses Identify Distinct Molecular Changes and Signaling Networks. Afshin Beheshti, PhD, Donna Neuberg, ScD, J. Tyson McDonald, PhD, Charles R. Vanderburg, PhD and Andrew M. Evens, DO, MSc, FACP. 2015. Cancer Informatics 14 141-148. PMCID: PMC4676434
9. Validating novel tau PET tracer [F-18]-AV-1451 (T807) on postmortem brain tissue. Marta Marquie, Marc D. Normandin, Charles R. Vanderburg, Isabel Costantino, Matthew P. Frosch, Bradley T. Hyman, Keith A. Johnson, Teresa Gomez-Isla. 2015. Annals of Neurology, 78 (5): 787-800 PMID: 26344059.
10. Metal Exposure and Alzheimer’s Pathophysiology. Huang X, Rogers JT, Vanderburg CR, Lai B, Dedeoglu A. 2014. Biochem Pharmacol. (3) e156
11. A three dimensional tissue culture model of bone formation utilizing rotational co-culture of human adult osteoblasts and osteoclasts. Mark S.F. Clarke, Alamelu Sundaresan, Charles R. Vanderburg, Meredith G. Banigan, and Neal R. Pellis. 2013. Acta Biomaterialia (13)1742-7061 PMID: 23664885
12. De-repression of FOXO3a death axis by microRNA-132 causes neuronal apoptosis in Alzheimer’s disease. Hon-Kit, Andus Wong, Tatiana Veremeyko, Nehal Patel, Christine Esau, Charles R. Vanderburgand Anna M. Krichevsky. 2013. Human Molecular Genetics (10) 1064-73 PMID: 23585551
13. Analysis of exosomal microRNAs in cerebrospinal fluid from Alzheimer’s disease patients. O. Cagsal-Getkin and C.R. Vanderburg. 2013. Journal of Extracellular Vesicles 2: 20826
14. Laser microdissection of metachromatically stained skeletal muscle allows quantification of fiber type specific gene expression. Charles R. Vanderburg and Mark S.F. Clarke. 2013. Mol Cell Biochem. Mar; 375(1-2):159-70. PMID:23196635
15. Differential expression of exosomal miRNAs in prefrontal cortices of schizophrenia and bipolar disorder patients. Meredith G. Banigan, Patricia F. Kao, James A. Kozubek, Ashley R. Winslow, Ozge Cagsal-Getkin, Juan Medina, Joan Costa, Andrea Schmitt, Howard Cabral, Ivana Delalle and Charles R. Vanderburg. 2013. PloS One. 8(1):e48814 PMID: 23382797
16. Assessment of gene order computing methods for Alzheimer's disease. Hu B, Jiang G, Pang C, Wang S, Liu Q, Chen Z, Vanderburg CR, Rogers JT, Deng Y, Huang X. 2013. BMC Med Genomics. 6 Suppl 1:S8 PMID: 23369541
17. Exosomal cell-to-cell transmission of alpha synuclein oligomers. Danzer KM, Kranich LR, Ruf WP, Cagsal-Getkin O, Winslow AR, Zhu L, Vanderburg CR, and McLean PJ. Mol Neurodegener. 2012; 7(1):42. PMID: 2292085
18. Increased expression of TrkB and Capzb2 accompanies preserved cognitive status in early Alzheimer disease pathology. Kao PF. Banigan MG. Vanderburg CR. McKee AC. Polgar PR. Seshadri S. and Delalle I. 2012. J. Neuropathol Exp Neurol. 71(7):654-64 PMID: 22710966
19. Hypomorphic Notch 3 alleles link Notch signaling to ischemic cerebral small-vessel disease. Arboleda-Velasquez JF, Manent J, Lee JH, Tikka S, Ospina C, Vanderburg CR, Frosch MP, Rodríguez-Falcón M, Villena J, Gygi S, Loper F, Kalimo H, Moskowitz MA, Ayata C, Louvi A, and Artavanis-Tsakonas S. 2011. PNAS. May 9 PMID: 21555590
20. Studying protein degradation pathways in vivo using a cranial window-based approach. Vivek K. Unni, Darius Ebrahimi-Fakhari, Charles R. Vanderburg, Pamela J. McLean and Bradley T. Hyman. 2011. Methods. Volume 53, Issue 3, Pages 194-200 PMID 21187150
21. Modulators of cytoskeletal reorganization in CA1 hippocampal neurons show increased expression in patients at mid-stage Alzheimer's disease. Kao. P, Davis DA, Banigan MG, Vanderburg CR, Seshadri S, and Delalle I. 2010. PLoS One , Oct 13;5(10):e13337 PMID: 20967212
22. The Role of MicroRNA in the Pathogenesis Associated With Necrotizing Enterocolitis. Pilar Requena, Jacqueline Beaupré, Allan M. Goldstein, Charles R. Vanderburg, N. Nanda Nanthakumar. 2010. Gastroenterology, 138:S-301.
23. Selective translational control of the Alzheimer amyloid precursor protein transcript by iron regulatory protein. Cho HH, Cahill CM, Vanderburg CR, Scherzer CR, Wang B, Huang X, Rogers JT. 2010. J. Biol.Chem. 285: 31217-31232. PMID: 20558735 24. Capzb2 mRNA and protein expression in the brains of patients diagnosed with Alzheimer’s disease and Huntington’s disease. Vanderburg CR, Davis DA, Diamond RE, Kao P and Delalle I. 2010. Translational Neuroscience. 1: 55-68.
25. A special clustering algorithm for identifying the genes associated with Alzheimer’s disease. Pang CY, Hu W, Hu BQ, Shi Y, Vanderburg CR, Rogers JT, and Huang X. 2010. IEEE Transactions on Nanobioscience. 9:44-50. PMID: 20089478 26. Mutations in the FUS/TLS Gene in Chromosome-16-Linked Familial Amyotrophic Lateral Sclerosis. Kwiatkowski TJ, Jr., Bosco D , LeClerc AL, Tamrazian E, Vanderburg CR, Russ C, Davis A, Gilchrist J, Kasarskis E, Munsat T, Hosler B, Haines J, Pericak-Vance M, Siddique T, McKenna-Yasek D, Sapp, PC , Horvitz HR, Landers JE, and Brown RH, Jr. 2009. Science, Volume 323:5198.
27. Independent component analysis of Alzheimer's DNA microarray gene expression data. Kong W, Mou X, Liu Q, Vanderburg CR, Rogers JT, Huang X. 2009. Molecular Neurodegeneration. 4:1-34.
28. Disruption of neural progenitors along the ventricular and subventricular zones in periventricular heterotopias. Ferland RJ, Batiz LF, Neal J, Lian G, Burdock E, Lu J, Hsiao Y-C, Diamond R, Mei D, Banham AH, Brown PJ, Vanderburg CR, Joseph J, Hecht JL, Folkerth R, Guerrini R, Walsh CA, Rodriguez EM, Sheen VL. 2009. Human Molecular Genetics, Volume 18:497-516.
29. A review of independent component analysis application to microarray gene expression data. Kong W, Vanderburg CR, Gunshin H, Rogers JT, Huang X. 2008. BioTechniques, Volume 45:501-520.
30. No alteration in tau exon 10 alternative splicing in tangle-bearing neurons of the Alzheimer’s disease brain. Martin Ingelsson, Karunya Ramasamy, Ippolita Cantuti-Castelvetri, Jennifer Orne, Susan Raju, Toshifumi Matsui, Charles R.Vanderburg, Jean C. Augustinack, Roberto de Silva, A.J.Lees, Lance Lannfelt, John H. Growdon, Matthew P. Frosch, David G. Standaert, Michael C. Irizarry, Bradley T. Hyman. 2006. Acta Neuropathologica, Volume 112, Pages 439-49.
31.Metal Exposure and Alzheimer's Pathogenesis. Xudong Huang, Guijian Liu, Weidong Huang, Robert D. Moir, Charles R. Vanderburg, Barry Lai, Zicheng Peng, Rudolph E. Tanzi, Jack T Rogers. 2006. Journal of Structural Biology, Volume 155, Pages 45-51.
32. Decreased levels of BDNF protein in Alzheimer temporal cortex are independent of BDNF polymorphisms. Jung Lee, Hiroaki Fukumoto, Jennifer Orne, Jochen Klucken, Susan Raju, Charles R. Vanderburg, Michael C. Irizarry, Bradley T. Hyman, Martin Ingelsson. 2005. Experimental Neurology, Volume 194, Pages 91-96.
33. A549 Lung Epithelial Cells Grown As 3-D Aggregates: Alternative Tissue Culture Model for P. aeruginosa Pathogenesis A.J. Carterson, C.M. Ott, M.S. Clarke, D. L Pierson, C.R. Vanderburg, C.A.Nickerson, K.L. Buchanan and M.J. Schurr. 2005. Infection and Immunity, Volume 73(2), Pages 1129-1140.
34. The effect of acute microgravity on mechanically-induced membrane damage and membrane-membrane fusion events. Clarke MS., Vanderburg CR., Feeback DL. McIntire LV. 2002. Journal of Gravitational Physiology. Volume 8, Pages 37-47.
35. Impact-mediated loading of large macromolecules into adherent mammalian cells. In Cell Biology: A Laboratory Handbook. ed. J.E. Celis (3rd Edition), Clarke, M.S.F. and Vanderburg, C.R. (2002). Academic Press.
36. Three-dimensional Tissue Assemblies: Novel Models for the Study of Salmonella Pathogenesis. Cheryl A. Nickerson, C. Mark Ott, Mark S. Clarke, Charles R. Vanderburg, and Duane L. Pierson. 2001. Infection and Immunity, Volume 69, Pages 7106-7120
37. In Situ localization of cholesterol in skeletal muscle by use of a monoclonal antibody. Mark S.F. Clarke, Charles R. Vanderburg, Marcas M. Bamman, Robert W. Caldwell, and Daniel L. Feeback. 2000. J. Appl. Physiol., Volume 89, Pages 731-741.
38. TGFb3 Promotes Transformation of Chicken Palate Medial Edge Epithelium to Mesenchyme in vitro. Dazhong Sun, Charles R. Vanderburg, Gregory S. Odierna and Elizabeth D. Hay. 1997. Development. Volume 125, Pages 95-105.
39. Exogenous E-Cadherin Expression in Primary Corneal Fibroblasts leads to the Formation of Stratified Epithelia. Charles R. Vanderburg and Elizabeth D. Hay. 1996. Acta Anatomica, Volume 157, Pages 87-104.
40. Impact Mediated Bead Loading as a Method of Inserting Macromolecules into Living Cells. Mark S.F. Clarke*, Charles R. Vanderburg, Elizabeth D. Hay, and Paul L. McNeil. 1994. Biotechniques. Volume 17, Pages 1118-1125. *First and second authors contributed equally.
41. Post transcriptional Control of Embryonic Rat Skeletal Muscle Protein Synthesis: Control at the Level of Translation by Endogenous RNA. Charles R. Vanderburg and Mark A. Nathanson. 1987. Journal of Cell Biology. Volume 107, Pages 1085-1098.
42. Transcriptional Translational Regulation of Muscle specific Protein Synthesis and Its Relationship to Chondrogenic Stimuli. Mark A. Nathanson, Elizabeth W. Bush, and Charles Vanderburg. 1986. Journal of Biological Chemistry. Volume 261, Pages 1477-1486.
Advanced Tissue Resource Center (ATRC)
Charlestown Navy Yard, B114-2725D
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