Mouse Crhbp Knockout Project (CRISPR/Cas9)
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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. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Exploring the Relationship Between Gut Microbiota and Major Depressive Disorders
E3S Web of Conferences 271, 03055 (2021) https://doi.org/10.1051/e3sconf/202127103055 ICEPE 2021 Exploring the Relationship between Gut Microbiota and Major Depressive Disorders Catherine Tian1 1Shanghai American School, Shanghai, China Abstract. Major Depressive Disorder (MDD) is a psychiatric disorder accompanied with a high rate of suicide, morbidity and mortality. With the symptom of an increasing or decreasing appetite, there is a possibility that MDD may have certain connections with gut microbiota, the colonies of microbes which reside in the human digestive system. In recent years, more and more studies started to demonstrate the links between MDD and gut microbiota from animal disease models and human metabolism studies. However, this relationship is still largely understudied, but it is very innovative since functional dissection of this relationship would furnish a new train of thought for more effective treatment of MDD. In this study, by using multiple genetic analytic tools including Allen Brain Atlas, genetic function analytical tools, and MicrobiomeAnalyst, I explored the genes that shows both expression in the brain and the digestive system to affirm that there is a connection between gut microbiota and the MDD. My approach finally identified 7 MDD genes likely to be associated with gut microbiota, implicating 3 molecular pathways: (1) Wnt Signaling, (2) citric acid cycle in the aerobic respiration, and (3) extracellular exosome signaling. These findings may shed light on new directions to understand the mechanism of MDD, potentially facilitating the development of probiotics for better psychiatric disorder treatment. 1 Introduction 1.1 Major Depressive Disorder Major Depressive Disorder (MDD) is a mood disorder that will affect the mood, behavior and other physical parts. -
Mouse Crhbp Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Crhbp Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Crhbp conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Crhbp gene (NCBI Reference Sequence: NM_198408 ; Ensembl: ENSMUSG00000021680 ) is located on Mouse chromosome 13. 7 exons are identified, with the ATG start codon in exon 1 and the TGA stop codon in exon 7 (Transcript: ENSMUST00000221025). Exon 4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Crhbp gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-49J13 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for disruptions in this gene display behavior indicative of increased anxiety. Male mice also show reduced food intake resulting in reduced growth between ages 7 and 15 weeks. Exon 4 starts from about 34.58% of the coding region. The knockout of Exon 4 will result in frameshift of the gene. The size of intron 3 for 5'-loxP site insertion: 1458 bp, and the size of intron 4 for 3'-loxP site insertion: 1851 bp. The size of effective cKO region: ~711 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 2 3 4 5 7 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Crhbp Homology arm cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Biological Pathways, Candidate Genes, and Molecular Markers Associated with Quality-Of-Life Domains: an Update
Qual Life Res (2014) 23:1997–2013 DOI 10.1007/s11136-014-0656-1 REVIEW Biological pathways, candidate genes, and molecular markers associated with quality-of-life domains: an update Mirjam A. G. Sprangers • Melissa S. Y. Thong • Meike Bartels • Andrea Barsevick • Juan Ordon˜ana • Qiuling Shi • Xin Shelley Wang • Pa˚l Klepstad • Eddy A. Wierenga • Jasvinder A. Singh • Jeff A. Sloan Accepted: 19 February 2014 / Published online: 7 March 2014 Ó Springer International Publishing Switzerland 2014 Abstract (depressed mood) and positive (well-being/happiness) Background There is compelling evidence of a genetic emotional functioning, social functioning, and overall foundation of patient-reported quality of life (QOL). Given QOL. the rapid development of substantial scientific advances in Methods We followed a purposeful search algorithm of this area of research, the current paper updates and extends existing literature to capture empirical papers investigating reviews published in 2010. the relationship between biological pathways and molecu- Objectives The objective was to provide an updated lar markers and the identified QOL domains. overview of the biological pathways, candidate genes, and Results Multiple major pathways are involved in each molecular markers involved in fatigue, pain, negative QOL domain. The inflammatory pathway has the strongest evidence as a controlling mechanism underlying fatigue. Inflammation and neurotransmission are key processes On behalf of the GeneQol Consortium. involved in pain perception, and the catechol-O-methyl- transferase (COMT) gene is associated with multiple sorts Electronic supplementary material The online version of this article (doi:10.1007/s11136-014-0656-1) contains supplementary of pain. The neurotransmitter and neuroplasticity theories material, which is available to authorized users. -
Stress Susceptibility-Specific Phenotype Associated with Different
Lisowski et al. BMC Neuroscience 2013, 14:144 http://www.biomedcentral.com/1471-2202/14/144 RESEARCH ARTICLE Open Access Stress susceptibility-specific phenotype associated with different hippocampal transcriptomic responses to chronic tricyclic antidepressant treatment in mice Pawel Lisowski1*, Grzegorz R Juszczak2, Joanna Goscik3, Adrian M Stankiewicz2, Marek Wieczorek4, Lech Zwierzchowski1 and Artur H Swiergiel5,6 Abstract Background: The effects of chronic treatment with tricyclic antidepressant (desipramine, DMI) on the hippocampal transcriptome in mice displaying high and low swim stress-induced analgesia (HA and LA lines) were studied. These mice displayed different depression-like behavioral responses to DMI: stress-sensitive HA animals responded to DMI, while LA animals did not. Results: To investigate the effects of DMI treatment on gene expression profiling, whole-genome Illumina Expres- sion BeadChip arrays and qPCR were used. Total RNA isolated from hippocampi was used. Expression profiling was then performed and data were analyzed bioinformatically to assess the influence of stress susceptibility-specific phe- notypes on hippocampal transcriptomic responses to chronic DMI. DMI treatment affected the expression of 71 genes in HA mice and 41 genes in LA mice. We observed the upregulation of Igf2 and the genes involved in neuro- genesis (HA: Sema3f, Ntng1, Gbx2, Efna5, and Rora; LA: Otx2, Rarb, and Drd1a) in both mouse lines. In HA mice, we observed the upregulation of genes involved in neurotransmitter transport, the termination of GABA and glycine ac- tivity (Slc6a11, Slc6a9), glutamate uptake (Slc17a6), and the downregulation of neuropeptide Y (Npy) and cortico- tropin releasing hormone-binding protein (Crhbp). In LA mice, we also observed the upregulation of other genes involved in neuroprotection (Ttr, Igfbp2, Prlr) and the downregulation of genes involved in calcium signaling and ion binding (Adcy1, Cckbr, Myl4, Slu7, Scrp1, Zfp330). -
Zimmer Cell Calcium 2013 Mammalian S100 Evolution.Pdf
Cell Calcium 53 (2013) 170–179 Contents lists available at SciVerse ScienceDirect Cell Calcium jo urnal homepage: www.elsevier.com/locate/ceca Evolution of the S100 family of calcium sensor proteins a,∗ b b,1 b Danna B. Zimmer , Jeannine O. Eubanks , Dhivya Ramakrishnan , Michael F. Criscitiello a Center for Biomolecular Therapeutics and Department of Biochemistry & Molecular Biology, University of Maryland School of Medicine, 108 North Greene Street, Baltimore, MD 20102, United States b Comparative Immunogenetics Laboratory, Department of Veterinary Pathobiology, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, TX 77843-4467, United States a r t i c l e i n f o a b s t r a c t 2+ Article history: The S100s are a large group of Ca sensors found exclusively in vertebrates. Transcriptomic and genomic Received 4 October 2012 data from the major radiations of mammals were used to derive the evolution of the mammalian Received in revised form 1 November 2012 S100s genes. In human and mouse, S100s and S100 fused-type proteins are in a separate clade from Accepted 3 November 2012 2+ other Ca sensor proteins, indicating that an ancient bifurcation between these two gene lineages Available online 14 December 2012 has occurred. Furthermore, the five genomic loci containing S100 genes have remained largely intact during the past 165 million years since the shared ancestor of egg-laying and placental mammals. Keywords: Nonetheless, interesting births and deaths of S100 genes have occurred during mammalian evolution. Mammals The S100A7 loci exhibited the most plasticity and phylogenetic analyses clarified relationships between Phylogenetic analyses the S100A7 proteins encoded in the various mammalian genomes. -
CREB-Dependent Transcription in Astrocytes: Signalling Pathways, Gene Profiles and Neuroprotective Role in Brain Injury
CREB-dependent transcription in astrocytes: signalling pathways, gene profiles and neuroprotective role in brain injury. Tesis doctoral Luis Pardo Fernández Bellaterra, Septiembre 2015 Instituto de Neurociencias Departamento de Bioquímica i Biologia Molecular Unidad de Bioquímica y Biologia Molecular Facultad de Medicina CREB-dependent transcription in astrocytes: signalling pathways, gene profiles and neuroprotective role in brain injury. Memoria del trabajo experimental para optar al grado de doctor, correspondiente al Programa de Doctorado en Neurociencias del Instituto de Neurociencias de la Universidad Autónoma de Barcelona, llevado a cabo por Luis Pardo Fernández bajo la dirección de la Dra. Elena Galea Rodríguez de Velasco y la Dra. Roser Masgrau Juanola, en el Instituto de Neurociencias de la Universidad Autónoma de Barcelona. Doctorando Directoras de tesis Luis Pardo Fernández Dra. Elena Galea Dra. Roser Masgrau In memoriam María Dolores Álvarez Durán Abuela, eres la culpable de que haya decidido recorrer el camino de la ciencia. Que estas líneas ayuden a conservar tu recuerdo. A mis padres y hermanos, A Meri INDEX I Summary 1 II Introduction 3 1 Astrocytes: physiology and pathology 5 1.1 Anatomical organization 6 1.2 Origins and heterogeneity 6 1.3 Astrocyte functions 8 1.3.1 Developmental functions 8 1.3.2 Neurovascular functions 9 1.3.3 Metabolic support 11 1.3.4 Homeostatic functions 13 1.3.5 Antioxidant functions 15 1.3.6 Signalling functions 15 1.4 Astrocytes in brain pathology 20 1.5 Reactive astrogliosis 22 2 The transcription -
Molecular Characterization of Selectively Vulnerable Neurons in Alzheimer’S Disease
RESOURCE https://doi.org/10.1038/s41593-020-00764-7 Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease Kun Leng1,2,3,4,13, Emmy Li1,2,3,13, Rana Eser 5, Antonia Piergies5, Rene Sit2, Michelle Tan2, Norma Neff 2, Song Hua Li5, Roberta Diehl Rodriguez6, Claudia Kimie Suemoto7,8, Renata Elaine Paraizo Leite7, Alexander J. Ehrenberg 5, Carlos A. Pasqualucci7, William W. Seeley5,9, Salvatore Spina5, Helmut Heinsen7,10, Lea T. Grinberg 5,7,11 ✉ and Martin Kampmann 1,2,12 ✉ Alzheimer’s disease (AD) is characterized by the selective vulnerability of specific neuronal populations, the molecular sig- natures of which are largely unknown. To identify and characterize selectively vulnerable neuronal populations, we used single-nucleus RNA sequencing to profile the caudal entorhinal cortex and the superior frontal gyrus—brain regions where neurofibrillary inclusions and neuronal loss occur early and late in AD, respectively—from postmortem brains spanning the progression of AD-type tau neurofibrillary pathology. We identified RORB as a marker of selectively vulnerable excitatory neu- rons in the entorhinal cortex and subsequently validated their depletion and selective susceptibility to neurofibrillary inclusions during disease progression using quantitative neuropathological methods. We also discovered an astrocyte subpopulation, likely representing reactive astrocytes, characterized by decreased expression of genes involved in homeostatic functions. Our characterization of selectively vulnerable neurons in AD paves the way for future mechanistic studies of selective vulnerability and potential therapeutic strategies for enhancing neuronal resilience. elective vulnerability is a fundamental feature of neurodegen- Here, we performed snRNA-seq on postmortem brain tissue erative diseases, in which different neuronal populations show from a cohort of individuals spanning the progression of AD-type a gradient of susceptibility to degeneration. -
393LN V 393P 344SQ V 393P Probe Set Entrez Gene
393LN v 393P 344SQ v 393P Entrez fold fold probe set Gene Gene Symbol Gene cluster Gene Title p-value change p-value change chemokine (C-C motif) ligand 21b /// chemokine (C-C motif) ligand 21a /// chemokine (C-C motif) ligand 21c 1419426_s_at 18829 /// Ccl21b /// Ccl2 1 - up 393 LN only (leucine) 0.0047 9.199837 0.45212 6.847887 nuclear factor of activated T-cells, cytoplasmic, calcineurin- 1447085_s_at 18018 Nfatc1 1 - up 393 LN only dependent 1 0.009048 12.065 0.13718 4.81 RIKEN cDNA 1453647_at 78668 9530059J11Rik1 - up 393 LN only 9530059J11 gene 0.002208 5.482897 0.27642 3.45171 transient receptor potential cation channel, subfamily 1457164_at 277328 Trpa1 1 - up 393 LN only A, member 1 0.000111 9.180344 0.01771 3.048114 regulating synaptic membrane 1422809_at 116838 Rims2 1 - up 393 LN only exocytosis 2 0.001891 8.560424 0.13159 2.980501 glial cell line derived neurotrophic factor family receptor alpha 1433716_x_at 14586 Gfra2 1 - up 393 LN only 2 0.006868 30.88736 0.01066 2.811211 1446936_at --- --- 1 - up 393 LN only --- 0.007695 6.373955 0.11733 2.480287 zinc finger protein 1438742_at 320683 Zfp629 1 - up 393 LN only 629 0.002644 5.231855 0.38124 2.377016 phospholipase A2, 1426019_at 18786 Plaa 1 - up 393 LN only activating protein 0.008657 6.2364 0.12336 2.262117 1445314_at 14009 Etv1 1 - up 393 LN only ets variant gene 1 0.007224 3.643646 0.36434 2.01989 ciliary rootlet coiled- 1427338_at 230872 Crocc 1 - up 393 LN only coil, rootletin 0.002482 7.783242 0.49977 1.794171 expressed sequence 1436585_at 99463 BB182297 1 - up 393 -
Vast Human-Specific Delay in Cortical Ontogenesis Associated With
Supplementary information Extension of cortical synaptic development distinguishes humans from chimpanzees and macaques Supplementary Methods Sample collection We used prefrontal cortex (PFC) and cerebellar cortex (CBC) samples from postmortem brains of 33 human (aged 0-98 years), 14 chimpanzee (aged 0-44 years) and 44 rhesus macaque individuals (aged 0-28 years) (Table S1). Human samples were obtained from the NICHD Brain and Tissue Bank for Developmental Disorders at the University of Maryland, USA, the Netherlands Brain Bank, Amsterdam, Netherlands and the Chinese Brain Bank Center, Wuhan, China. Informed consent for use of human tissues for research was obtained in writing from all donors or their next of kin. All subjects were defined as normal by forensic pathologists at the corresponding brain bank. All subjects suffered sudden death with no prolonged agonal state. Chimpanzee samples were obtained from the Yerkes Primate Center, GA, USA, the Anthropological Institute & Museum of the University of Zürich-Irchel, Switzerland and the Biomedical Primate Research Centre, Netherlands (eight Western chimpanzees, one Central/Eastern and five of unknown origin). Rhesus macaque samples were obtained from the Suzhou Experimental Animal Center, China. All non-human primates used in this study suffered sudden deaths for reasons other than their participation in this study and without any relation to the tissue used. CBC dissections were made from the cerebellar cortex. PFC dissections were made from the frontal part of the superior frontal gyrus. All samples contained an approximately 2:1 grey matter to white matter volume ratio. RNA microarray hybridization RNA isolation, hybridization to microarrays, and data preprocessing were performed as described previously (Khaitovich et al. -
Meta-Analysis of Brain Gene Expression Data from Mouse Model Studies of Maternal Immune Activation Using Poly(I:C)
G C A T T A C G G C A T genes Article Meta-Analysis of Brain Gene Expression Data from Mouse Model Studies of Maternal Immune Activation Using Poly(I:C) Aodán Laighneach 1 , Lieve Desbonnet 2, John P. Kelly 2, Gary Donohoe 1 and Derek W. Morris 1,* 1 Centre for Neuroimaging, Cognition and Genomics, Discipline of Biochemistry and School of Psychology, National University of Ireland Galway, H91 TK33 Galway, Ireland; [email protected] (A.L.); [email protected] (G.D.) 2 Discipline of Pharmacology and Therapeutics, National University of Ireland Galway, H91 TK33 Galway, Ireland; [email protected] (L.D.); [email protected] (J.P.K.) * Correspondence: [email protected] Abstract: Maternal immune activation (MIA) is a known risk factor for schizophrenia (SCZ) and autism spectrum disorder (ASD) and is often modelled in animal studies in order to study the effect of prenatal infection on brain function including behaviour and gene expression. Although the effect of MIA on gene expression are highly heterogeneous, combining data from multiple gene expression studies in a robust method may shed light on the true underlying biological effects caused by MIA and this could inform studies of SCZ and ASD. This study combined four RNA-seq and microarray datasets in an overlap analysis and ranked meta-analysis in order to investigate genes, pathways and cell types dysregulated in the MIA mouse models. Genes linked to SCZ and ASD and crucial in neurodevelopmental processes including neural tube folding, regulation of cellular stress and neuronal/glial cell differentiation were among the most consistently dysregulated in these ranked analyses.