STX17 Dynamically Regulated by Fis1 Induces Mitophagy Via Hierarchical Macroautophagic Mechanism
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A Minimum-Labeling Approach for Reconstructing Protein Networks Across Multiple Conditions
A Minimum-Labeling Approach for Reconstructing Protein Networks across Multiple Conditions Arnon Mazza1, Irit Gat-Viks2, Hesso Farhan3, and Roded Sharan1 1 Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. Email: [email protected]. 2 Dept. of Cell Research and Immunology, Tel Aviv University, Tel Aviv 69978, Israel. 3 Biotechnology Institute Thurgau, University of Konstanz, Unterseestrasse 47, CH-8280 Kreuzlingen, Switzerland. Abstract. The sheer amounts of biological data that are generated in recent years have driven the development of network analysis tools to fa- cilitate the interpretation and representation of these data. A fundamen- tal challenge in this domain is the reconstruction of a protein-protein sub- network that underlies a process of interest from a genome-wide screen of associated genes. Despite intense work in this area, current algorith- mic approaches are largely limited to analyzing a single screen and are, thus, unable to account for information on condition-specific genes, or reveal the dynamics (over time or condition) of the process in question. Here we propose a novel formulation for network reconstruction from multiple-condition data and devise an efficient integer program solution for it. We apply our algorithm to analyze the response to influenza in- fection in humans over time as well as to analyze a pair of ER export related screens in humans. By comparing to an extant, single-condition tool we demonstrate the power of our new approach in integrating data from multiple conditions in a compact and coherent manner, capturing the dynamics of the underlying processes. 1 Introduction With the increasing availability of high-throughput data, network biol- arXiv:1307.7803v1 [q-bio.QM] 30 Jul 2013 ogy has become the method of choice for filtering, interpreting and rep- resenting these data. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
The Schizophrenia Risk Gene Product Mir-137 Alters Presynaptic Plasticity
The schizophrenia risk gene product miR-137 alters presynaptic plasticity The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Siegert, S., J. Seo, E. J. Kwon, A. Rudenko, S. Cho, W. Wang, Z. Flood, et al. 2015. “The schizophrenia risk gene product miR-137 alters presynaptic plasticity.” Nature neuroscience 18 (7): 1008-1016. doi:10.1038/nn.4023. http://dx.doi.org/10.1038/nn.4023. Published Version doi:10.1038/nn.4023 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:24983896 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA HHS Public Access Author manuscript Author Manuscript Author ManuscriptNat Neurosci Author Manuscript. Author manuscript; Author Manuscript available in PMC 2016 January 01. Published in final edited form as: Nat Neurosci. 2015 July ; 18(7): 1008–1016. doi:10.1038/nn.4023. The schizophrenia risk gene product miR-137 alters presynaptic plasticity Sandra Siegert1,2, Jinsoo Seo1,2,*, Ester J. Kwon1,2,*, Andrii Rudenko1,2,*, Sukhee Cho1,2, Wenyuan Wang1,2, Zachary Flood1,2, Anthony J. Martorell1,2, Maria Ericsson4, Alison E. Mungenast1,2, and Li-Huei Tsai1,2,3,5 1Picower Institute for Learning and Memory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA 2Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA 3Broad Institute of MIT and Harvard, Cambridge, MA, USA 4Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA Abstract Non-coding variants in the human MIR137 gene locus increase schizophrenia risk at a genome- wide significance level. -
Supplementary Tables
Supplementary Tables Supplementary Table S1: Preselected miRNAs used in feature selection Univariate Cox proportional hazards regression analysis of the endpoint freedom from recurrence in the training set (DKTK-ROG sample) allowed the pre-selection of 524 miRNAs (P< 0.5), which were used in the feature selection. P-value was derived from log-rank test. miRNA p-value miRNA p-value miRNA p-value miRNA p-value hsa-let-7g-3p 0.0001520 hsa-miR-1304-3p 0.0490161 hsa-miR-7108-5p 0.1263245 hsa-miR-6865-5p 0.2073121 hsa-miR-6825-3p 0.0004257 hsa-miR-4298 0.0506194 hsa-miR-4453 0.1270967 hsa-miR-6893-5p 0.2120664 hsa-miR-668-3p 0.0005188 hsa-miR-484 0.0518625 hsa-miR-200a-5p 0.1276345 hsa-miR-25-3p 0.2123829 hsa-miR-3622b-3p 0.0005885 hsa-miR-6851-3p 0.0531446 hsa-miR-6090 0.1278692 hsa-miR-3189-5p 0.2136060 hsa-miR-6885-3p 0.0006452 hsa-miR-1276 0.0557418 hsa-miR-148b-3p 0.1279811 hsa-miR-6073 0.2139702 hsa-miR-6875-3p 0.0008188 hsa-miR-3173-3p 0.0559962 hsa-miR-4425 0.1288330 hsa-miR-765 0.2141536 hsa-miR-487b-5p 0.0011381 hsa-miR-650 0.0564616 hsa-miR-6798-3p 0.1293342 hsa-miR-338-5p 0.2153079 hsa-miR-210-5p 0.0012316 hsa-miR-6133 0.0571407 hsa-miR-4472 0.1300006 hsa-miR-6806-5p 0.2173515 hsa-miR-1470 0.0012822 hsa-miR-4701-5p 0.0571720 hsa-miR-4465 0.1304841 hsa-miR-98-5p 0.2184947 hsa-miR-6890-3p 0.0016539 hsa-miR-202-3p 0.0575741 hsa-miR-514b-5p 0.1308790 hsa-miR-500a-3p 0.2185577 hsa-miR-6511b-3p 0.0017165 hsa-miR-4733-5p 0.0616138 hsa-miR-378c 0.1317442 hsa-miR-4515 0.2187539 hsa-miR-7109-3p 0.0021381 hsa-miR-595 0.0629350 hsa-miR-3121-3p -
Syntaxin 16'S Newly Deciphered Roles in Autophagy
cells Perspective Syntaxin 16’s Newly Deciphered Roles in Autophagy Bor Luen Tang 1,2 1 Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore; [email protected]; Tel.: +65-6516-1040 2 NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 119077, Singapore Received: 19 November 2019; Accepted: 6 December 2019; Published: 17 December 2019 Abstract: Syntaxin 16, a Qa-SNARE (soluble N-ethylmaleimide-sensitive factor activating protein receptor), is involved in a number of membrane-trafficking activities, particularly transport processes at the trans-Golgi network (TGN). Recent works have now implicated syntaxin 16 in the autophagy process. In fact, syntaxin 16 appears to have dual roles, firstly in facilitating the transport of ATG9a-containing vesicles to growing autophagosomes, and secondly in autolysosome formation. The former involves a putative SNARE complex between syntaxin 16, VAMP7 and SNAP-47. The latter occurs via syntaxin 16’s recruitment by Atg8/LC3/GABARAP family proteins to autophagosomes and endo-lysosomes, where syntaxin 16 may act in a manner that bears functional redundancy with the canonical autophagosome Qa-SNARE syntaxin 17. Here, I discuss these recent findings and speculate on the mechanistic aspects of syntaxin 16’s newly found role in autophagy. Keywords: ATG9; autophagy; autophagosome; SNARE; syntaxin 16; syntaxin 17; VAMP7 1. Introduction Vesicular membrane trafficking [1] and macroautophagy [2] are two highly conserved cellular membrane remodeling processes in eukaryotes. The former mediates the transfer of materials between membrane compartments, while the latter serves to degrade and recycle cytosolic as well as membranous cellular materials. -
Mitochondrial Rab Gaps Govern Autophagosome Biogenesis During Mitophagy Koji Yamano1, Adam I Fogel1, Chunxin Wang1, Alexander M Van Der Bliek2, Richard J Youle1*
RESEARCH ARTICLE elife.elifesciences.org Mitochondrial Rab GAPs govern autophagosome biogenesis during mitophagy Koji Yamano1, Adam I Fogel1, Chunxin Wang1, Alexander M van der Bliek2, Richard J Youle1* 1Biochemistry Section, Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States; 2Department of Biological Chemistry, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, United States Abstract Damaged mitochondria can be selectively eliminated by mitophagy. Although two gene products mutated in Parkinson’s disease, PINK1, and Parkin have been found to play a central role in triggering mitophagy in mammals, how the pre-autophagosomal isolation membrane selectively and accurately engulfs damaged mitochondria remains unclear. In this study, we demonstrate that TBC1D15, a mitochondrial Rab GTPase-activating protein (Rab-GAP), governs autophagosome biogenesis and morphology downstream of Parkin activation. To constrain autophagosome morphogenesis to that of the cargo, TBC1D15 inhibits Rab7 activity and associates with both the mitochondria through binding Fis1 and the isolation membrane through the interactions with LC3/ GABARAP family members. Another TBC family member TBC1D17, also participates in mitophagy and forms homodimers and heterodimers with TBC1D15. These results demonstrate that TBC1D15 and TBC1D17 mediate proper autophagic encapsulation of mitochondria by regulating Rab7 activity at the interface between mitochondria and isolation membranes. DOI: 10.7554/eLife.01612.001 *For correspondence: [email protected] Introduction Competing interests: See page 21 Autophagosomes enclose seemingly random portions of the cytoplasm to supply nutrients during starvation or they can specifically engulf cellular debris to maintain quality control (Mizushima et al., Funding: See page 21 2011). -
Differential Redox-Regulation and Mitochondrial Dynamics in Normal and Leukemic Hematopoietic Stem Cells a Potential Window
Critical Reviews in Oncology / Hematology 144 (2019) 102814 Contents lists available at ScienceDirect Critical Reviews in Oncology / Hematology journal homepage: www.elsevier.com/locate/critrevonc Differential redox-regulation and mitochondrial dynamics in normal and leukemic hematopoietic stem cells: A potential window for leukemia T therapy ⁎ Katharina Mattes, Edo Vellenga, Hein Schepers Department of Hematology, Cancer Research Center Groningen, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands ARTICLE INFO ABSTRACT Keywords: The prognosis for many patients with acute myeloid leukemia (AML) is poor, mainly due to disease relapse HSC driven by leukemia stem cells (LSCs). Recent studies have highlighted the unique metabolic properties of LSCs, LSC which might represent opportunities for LSC-selective targeting. LSCs characteristically have low levels of re- Mitochondria active oxygen species (ROS), which apparently result from a combination of low mitochondrial activity and high ROS activity of ROS-removing pathways such as autophagy. Due to this low activity, LSCs are highly dependent on BCL-2 mitochondrial regulatory mechanisms. These include the anti-apoptotic protein BCL-2, which also has crucial Autophagy Venetoclax roles in regulating the mitochondrial membrane potential, and proteins involved in mitophagy. Here we review the different pathways that impact mitochondrial activity and redox-regulation, and highlight their relevance for the functionality of both HSCs and LSCs. Additionally, novel AML therapy strategies that are based on interference with those pathways, including the promising BCL-2 inhibitor Venetoclax, are summar- ized. 1. Introduction and scope of this review regulating ROS production and mitochondrial health. HSCs rely on glycolysis as their main energy source, which results in less oxidative Current treatment strategies for acute myeloid leukemia (AML) re- burden compared to mitochondrial oxidative phosphorylation (OX- sult in an initial reduction of leukemic blasts in the majority of patients. -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US). -
Appoptosin Interacts with Mitochondrial Outer-Membrane Fusion Proteins and Regulates Mitochondrial Morphology
© 2016. Published by The Company of Biologists Ltd | Journal of Cell Science (2016) 129, 994-1002 doi:10.1242/jcs.176792 RESEARCH ARTICLE Appoptosin interacts with mitochondrial outer-membrane fusion proteins and regulates mitochondrial morphology Cuilin Zhang1, Zhun Shi1, Lingzhi Zhang1, Zehua Zhou1, Xiaoyuan Zheng1, Guiying Liu1, Guojun Bu1, Paul E. Fraser2, Huaxi Xu1,3 and Yun-wu Zhang1,* ABSTRACT mitochondrial mobility, mitophagy, cell mitosis and apoptosis Mitochondrial morphology is regulated by fusion and fission (Youle and van der Bliek, 2012). – machinery. Impaired mitochondria dynamics cause various Mitochondrial fusion comprises two events outer-membrane diseases, including Alzheimer’s disease. Appoptosin (encoded by fusion and inner-membrane fusion. In mammalian cells, two SLC25A38) is a mitochondrial carrier protein that is located in the GTPases MFN1 and MFN2, which anchor on the outer mitochondrial inner membrane. Appoptosin overexpression causes membrane of mitochondria, are responsible for the outer- overproduction of reactive oxygen species (ROS) and caspase- membrane fusion (Chen et al., 2003; Koshiba et al., 2004). dependent apoptosis, whereas appoptosin downregulation abolishes However, compared to MFN2, MFN1 is relatively specific in β-amyloid-induced mitochondrial fragmentation and neuronal death regulating mitochondrial fusion (Shen et al., 2007). MFN1- during Alzheimer’s disease. Herein, we found that overexpression harboring mitochondria have a higher tethering efficiency than of appoptosin resulted in mitochondrial fragmentation in a manner those with MFN2, and purified MFN1 also possesses higher independent of its carrier function, ROS production or caspase GTPase activity than MFN2 (Ishihara et al., 2004). In contrast, activation. Although appoptosin did not affect levels of mitochondrial MFN2 is more tissue specific in its expression pattern than MFN1 outer-membrane fusion (MFN1 and MFN2), inner-membrane fusion (Liesa et al., 2009). -
Table S2.Up Or Down Regulated Genes in Tcof1 Knockdown Neuroblastoma N1E-115 Cells Involved in Differentbiological Process Anal
Table S2.Up or down regulated genes in Tcof1 knockdown neuroblastoma N1E-115 cells involved in differentbiological process analysed by DAVID database Pop Pop Fold Term PValue Genes Bonferroni Benjamini FDR Hits Total Enrichment GO:0044257~cellular protein catabolic 2.77E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 537 13588 1.944851 8.64E-07 8.64E-07 5.02E-07 process ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, USP17L5, FBXO11, RAD23B, NEDD8, UBE2V2, RFFL, CDC GO:0051603~proteolysis involved in 4.52E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 534 13588 1.93519 1.41E-06 7.04E-07 8.18E-07 cellular protein catabolic process ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, USP17L5, FBXO11, RAD23B, NEDD8, UBE2V2, RFFL, CDC GO:0044265~cellular macromolecule 6.09E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 609 13588 1.859332 1.90E-06 6.32E-07 1.10E-06 catabolic process ISG15, RBM8A, ATG7, LOC100046898, PSENEN, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, XRN2, USP17L5, FBXO11, RAD23B, UBE2V2, NED GO:0030163~protein catabolic process 1.81E-09 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 556 13588 1.87839 5.64E-06 1.41E-06 3.27E-06 ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, -
Regulation of Mitochondrial Dynamics and Cell Fate Rimpy Dhingra, Phd; Lorrie A
Advance Publication by-J-STAGE Circulation Journal REVIEW Official Journal of the Japanese Circulation Society http://www.j-circ.or.jp Regulation of Mitochondrial Dynamics and Cell Fate Rimpy Dhingra, PhD; Lorrie A. Kirshenbaum, PhD Though the mitochondrion was initially identified as a key organelle essentially required for energy production and oxidative metabolism, there is considerable evidence that mitochondria are intimately involved in regulating vital cellular processes, such as programmed cell death, proliferation and autophagy. Discovery of mitochondrial “shaping proteins” (Dynamin-related protein (Drp), mitofusins (Mfn) etc.) has revealed that mitochondria are highly dynamic organelles continually changing morphology by fission and fusion processes. Several human pathologies, including cancer, Parkinson’s disease, Alzheimer’s disease and cardiovascular diseases, have been linked to abnormalities in proteins that govern mitochondrial fission or fusion respectively. Notably, in the context of the heart, defects in mitochondrial dynamics resulting in too many fused and/or fragmented mitochondria have been associated with impaired cardiac development, autophagy, and contractile dysfunction. Understanding the mechanisms that govern mitochondrial fission/ fusion is paramount in developing new treatment strategies for human diseases in which defects in fission or fusion is the primary underlying defect. Here, we provide a comprehensive overview of the cellular targets and molecular signal- ing pathways that govern mitochondrial dynamics -
Mitochondrial Dynamic Abnormalities in Alzheimer's Disease Sirui Jiang Case Western Reserve University
MITOCHONDRIAL DYNAMIC ABNORMALITIES IN ALZHEIMER’S DISEASE by SIRUI JIANG Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Dissertation Advisor: Dr. Xiongwei Zhu Department of Pathology CASE WESTERN RESERVE UNIVERSITY January 2019 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of SIRUI JIANG Candidate for the degree of Doctor of Philosophy* Dr. Shu Chen (Committee Chair) Dr. Xiongwei Zhu Dr. Xinglong Wang Dr. George Dubyak Dr. Charles Hoppel August 15, 2018 *We also certify that written approval has been obtained for any proprietary material contained therein Table of Contents Table of Contents 1 List of Figures 3 Acknowledgements 5 List of Abbreviations 7 Abstract 10 Chapter 1. Introduction 12 Introduction to Alzheimer’s Disease 13 General Information 13 Pathology 14 Pathogenesis 15 Introduction to Mitochondrial Dynamics 20 Mitochondrial Function and Neuronal Health 20 Mitochondrial Dynamics 21 Mitochondrial Dynamics and Mitochondrial Function 23 Mitochondrial Dynamics and Mitochondrial Transport 24 Mitochondrial Deficits in AD 26 Mitochondrial Dysfunction in AD 26 Aβ and Mitochondrial Dysfunction 27 Mitochondrial Dynamic Abnormalities in AD: Recent Advances 28 Conclusion 34 1 Chapter 2. Mfn2 ablation causes an oxidative stress response and eventual neuronal death in the hippocampus and cortex 36 Abstract 37 Background 39 Methods 43 Results 47 Discussion 54 Figures 60 Chapter 3. DLP1 Cleavage by Calpain in Alzheimer’s Disease 71 Abstract 72 Background 73 Methods 77 Results 80 Discussion 85 Figures 89 Chapter 4. Summary, Discussion and Future Directions 96 References 108 2 List of Figures Figure 2.1 Cre-mediated ablation of Mfn2 expression in the hippocampus and cortex of Mfn2 cKO mice 60 Figure 2.2 Quantification of DLP1 and OPA1 in cKO mice 61 Figure 2.3 Mfn2 ablation caused mitochondrial fragmentation and ultrastructural damage in the hippocampus in vivo as evidenced by electron microscopic analysis.