New Insights Into the Immune System Using Dirty Mice Sara E

Total Page:16

File Type:pdf, Size:1020Kb

New Insights Into the Immune System Using Dirty Mice Sara E New Insights into the Immune System Using Dirty Mice Sara E. Hamilton, Vladimir P. Badovinac, Lalit K. Beura, Mark Pierson, Stephen C. Jameson, David Masopust and This information is current as Thomas S. Griffith of September 27, 2021. J Immunol 2020; 205:3-11; ; doi: 10.4049/jimmunol.2000171 http://www.jimmunol.org/content/205/1/3 Downloaded from References This article cites 100 articles, 17 of which you can access for free at: http://www.jimmunol.org/content/205/1/3.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 27, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2020 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. New Insights into the Immune System Using Dirty Mice ,†,‡,x {,‖,# Sara E. Hamilton,* Vladimirx P. Badovinac,x Lalit K. Beura,** Mark Pierson,*x xx Stephen C. Jameson,*,†,‡, David Masopust,†,‡, ,†† and Thomas S. Griffith†,‡, ,‡‡, The mouse (Mus musculus) is the dominant organism then is how to improve the value of experimental rodent re- used to investigate the mechanisms behind complex search to increase the success rate of translating preclinical immunological responses because of their genetic sim- findings to the clinic. One option is for experimental im- ilarity to humans and our ability to manipulate those munologists to supplement existing or developing new models genetics to understand downstream function. Indeed, with variables known or expected to influence the readout, our knowledge of immune system development, re- outcome, and/or conclusions. Unfortunately, it is also fair to sponse to infection, and ways to therapeutically manip- note that most of the envisioned improvements will likely increase the complexity, cost, and, in some cases, limit the ulate the immune response to combat disease were, in Downloaded from large part, delineated in the mouse. Despite the power number of researchers able to fulfill the new model require- of mouse-based immunology research, the translational ments. In this review, we will discuss new insights into im- efficacy of many new therapies from mouse to human munology research using models based on mice with a history is far from ideal. Recent data have highlighted how the of microbial exposure. Humans are exposed to pathogenic and commensal microbes naive, neonate-like immune system of specific pathogen– on a daily basis from birth, which (together with vaccination) http://www.jimmunol.org/ free mice differs dramatically in composition and mature the immune system to provide long-lasting protection function to mice living under barrier-free conditions against future microbial challenge. Immunological memory is (i.e., “dirty” mice). In this review, we discuss major minimal in most mice used in biomedical research because of findings to date and challenges faced when using specific pathogen–free (SPF) housing conditions in contrast to dirty mice and specific areas of immunology research the experienced immune systems of wild mice or mice obtained that may benefit from using animals with robust and from neighborhood pet stores [hereafter collectively referred to varied microbial exposure. The Journal of Immu- as “dirty” mice (4)]. The primary (and most obvious) feature of nology, 2020, 205: 3–11. dirty mice that distinguishes them from traditional SPF labo- ratory mice is that their exposure to multiple mouse pathogens by guest on September 27, 2021 aboratory mouse models represent an undeniable (which are normally excluded under SPF conditions) was asset in our understanding of immunology and hu- found to mature the murine immune system to more closely L man disease. Mice and humans share .90% ge- resemble that seen in adult humans (4–6). It is now appreciated netic homology (1), and their usage has led to the discovery that the baseline status of the immune system can have sig- of a significant number of genes and pathways fundamental nificant implications on the cellular composition and intensity for understanding disease processes and designing effective of subsequent immune responses. Our group published data treatment. Additionally, the power to transfer immune cells outlining the use of dirty mice to evaluate the composition and between hosts, ability to create genetic knockout strains, basic function of the immune system to challenge (compared conditional and inducible deletions, and transgenics are all with SPF mice), but additional work from a number of labo- important advantages to study disease processes within a fairly ratories has reinforced the concept and value of using dirty short timeline. However, many examples now exist whereby mice in preclinical investigation [Table I (4–10)]. Interest- use of the laboratory mouse has misdirected clinical ap- ingly, each publication has used slight variations in method- proaches, failing to positively impact humans and costing ology to generate the dirty mice used for study. The following millions of research dollars in the process (2, 3). The question information will be based on our experience with and data *Department of Laboratory Medicine and Pathology, University of Minnesota, Minne- This work was supported by National Institute of Allergy and Infectious Diseases, apolis, MN 55455; †Microbiology, Immunology, and Cancer Biology Ph.D. Program, National Institutes of Health (NIH) Grants AI116678 (to S.E.H.), AI147064 (to University of Minnesota, Minneapolis, MN 55455; ‡Center for Immunology, Univer- V.P.B.), and AI084913 (to D.M.); National Institute of General Medical Sciences, x sity of Minnesota, Minneapolis, MN 55455; Masonic Cancer Center, University of NIH Grants GM134880 (to V.P.B.) and GM115462 (to T.S.G.); and U.S. Department { Minnesota, Minneapolis, MN 55455; Department of Pathology, University of Iowa, of Veterans Affairs Merit Review Award I01BX001324 (to T.S.G.). ‖ Iowa City, IA 52242; Department of Microbiology and Immunology, University of Address correspondence and reprint requests to Dr. Thomas S. Griffith, Department of Iowa, Iowa City, IA 52242; #Interdisciplinary Graduate Program in Immunology, Uni- Urology, University of Minnesota, MMC 394 Mayo, 420 Delaware Street SE, Minne- versity of Iowa, Iowa City, IA 52242; **Department of Molecular Microbiology and †† apolis, MN 55455. E-mail address: tgriffi[email protected] Immunology, Brown University, Providence, RI 02912; Department of Microbiology and Immunology, University of Minnesota, Minneapolis, MN 55455; ‡‡Department of Abbreviations used in this article: CLP, cecal ligation and puncture; SPF, specific xx Urology, University of Minnesota, Minneapolis, MN 55455; and Minneapolis Vet- pathogen–free. erans Affairs Health Care System, Minneapolis, MN 55417 Ó ORCIDs: 0000-0002-3768-7622 (S.E.H.); 0000-0003-3180-2439 (V.P.B.); 0000- Copyright 2020 by The American Association of Immunologists, Inc. 0022-1767/20/$37.50 0001-9137-1146 (S.C.J.); 0000-0002-7205-9859 (T.S.G.). Received for publication February 13, 2020. Accepted for publication May 4, 2020. www.jimmunol.org/cgi/doi/10.4049/jimmunol.2000171 4 BRIEF REVIEWS: IMPACT AND FUTURE USE OF DIRTY MICE IN RESEARCH Table I. Mouse models of microbial exposure Model Strengths Weaknesses Human Genetic diversity (outbred) Significant regulations limit in vivo hypothesis-testing studies Experienced immune system Males and females can be used to address sex as a biological variable SPF mouse Can be inbred or outbred Naive immune system Infection history is controllable Microbiome is more uniform Numerous strains readily available to identify and interrogate Can be highly susceptible to pathogens immune cells Male and female mice can be used to address sex as a biological variable Wild mouse Natural pathogen exposure since birth Unknown infection history Diverse microbiome Unknown genetics and age Experienced immune system leads to enhanced protection to Increased cost for dedicated housing new infections Mice must be caught and may carry pathogens dangerous to humans (e.g., hantavirus) Cohoused with pet Can be inbred or outbred Increased cost for dedicated housing (e.g., BSL-3) store mice Can be age-matched with SPF mice Microbial exposure can vary with each cohort Downloaded from Natural pathogen exposure Cohousing can result in death depending on the pet store mouse used Conversion of the naive mouse immune system to a mature/ Unknown variation in microbiome composition effector phenotype is efficient (,10% of cohoused mice experience a poor conversion) and robust Restricted to female mice Sequential infection Infection history is known Requires prior selection of a “correct” set of pathogens http://www.jimmunol.org/ Using known pathogens draws on a larger pool of knowledge Uses laboratory defined routes of exposure instead of natural to interpret results routes Can be done with BSL1- and BSL2-level pathogens Milder conversion than observed with other methods
Recommended publications
  • Visual Exploration Across Biomedical Databases
    1 Visual Exploration Across Biomedical Databases Michael D. Lieberman∗†‡ Sima Taheri∗ Huimin Guo∗ Fatemeh Mir-Rashed∗ [email protected] [email protected] [email protected] [email protected] Inbal Yahav§ Aleks Aris∗ Ben Shneiderman∗† [email protected] [email protected] [email protected] Abstract—Though biomedical research often draws on knowl- mentioned in d. d may also have associations with other edge from a wide variety of fields, few visualization methods PubMed documents that cite d as a reference, as well as for biomedical data incorporate meaningful cross-database ex- associations to the PubMed documents that d itself cites. ploration. A new approach is offered for visualizing and explor- ∈ ing a query-based subset of multiple heterogeneous biomedical Furthermore, each gene g G could have associations with databases. Databases are modeled as an entity-relation graph the proteins for which g codes, or the DNA sequences in containing nodes (database records) and links (relationships which g’s code appears. Usually, the various types of records between records). Users specify a keyword search string to in these databases also have many attributes associated with retrieve an initial set of nodes, and then explore intra- and inter- them. For example, PubMed documents might be annotated database links. Results are visualized with user-defined semantic substrates to take advantage of the rich set of attributes usually with the date of publication, authors, and general topics, while present in biomedical data. Comments from domain experts gene records could be annotated with the relevant species, indicate that this visualization method is potentially advantageous location on chromosome, or function.
    [Show full text]
  • A Novel Transmembrane Glycoprotein Cancer Biomarker Present in the X Chromosome ANA PAULA DELGADO, SHEILIN HAMID, PAMELA BRANDAO and RAMASWAMY NARAYANAN
    CANCER GENOMICS & PROTEOMICS 11 : 81-92 (2014) A Novel Transmembrane Glycoprotein Cancer Biomarker Present in the X Chromosome ANA PAULA DELGADO, SHEILIN HAMID, PAMELA BRANDAO and RAMASWAMY NARAYANAN Department of Biological Sciences, Charles E. Schmidt College of Science, Florida Atlantic University, Boca Raton, FL, U.S.A. Abstract. Background: The uncharacterized proteins of the genome are of unknown nature (10). These proteins and the human proteome offer an untapped potential for cancer non-coding RNAs are called the ‘dark matter’ of the genome biomarker discovery. Numerous predicted open reading (11-13). Whereas in the past most gene discovery has frames (ORFs) are present in diverse chromosomes. The revolved around known genes due to the ease of follow-up mRNA and protein expression data, as well as the mutational studies (14-17), the dark matter of the genome offers an and variant information for these ORF proteins are available untapped potential (18). Realizing the importance of this area, in the cancer-related bioinformatics databases. Materials the US National Cancer Institute has recently announced a and Methods: ORF proteins were mined using bioinformatics major initiative called illuminating the dark matter for and proteomic tools to predict motifs and domains, and druggable targets (http://commonfund.nih.gov/idg/index). cancer relevance was established using cancer genome, Establishing cancer relevance for novel or uncharacterized transcriptome and proteome analysis tools. Results: A novel proteins is a crucial first step in lead discovery. The cancer testis-restricted ORF protein present in chromosome X called genomes of patients from around the world can be readily CXorf66 was detected in the serum, plasma and neutrophils.
    [Show full text]
  • BIOINFORMATICS ORIGINAL PAPER Doi:10.1093/Bioinformatics/Btu524
    CORE Metadata, citation and similar papers at core.ac.uk Provided by Open Repository and Bibliography - LuxembourgBioinformatics Advance Access published August 26, 2014 2014, pages 1–8 BIOINFORMATICS ORIGINAL PAPER doi:10.1093/bioinformatics/btu524 Data and text mining Advance Access publication August 6, 2014 BioTextQuest+: a knowledge integration platform for literature mining and concept discovery Nikolas Papanikolaou1,y, Georgios A. Pavlopoulos1,y, Evangelos Pafilis2, Theodosios Theodosiou1,ReinhardSchneider3, Venkata P. Satagopam3, Christos A. Ouzounis4,5, Aristides G. Eliopoulos1,6, Vasilis J. Promponas7 and Ioannis Iliopoulos1,* 1Division of Basic Sciences, University of Crete, Medical School, Heraklion 71110, Greece, 2Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece, 3Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7, avenue des Hauts-Fourneaux, L-4362 Esch sur Alzette, Luxembourg, 4Biological Computation & Process Laboratory (BCPL), Chemical Process & Energy Resources Institute (CPERI), Centre for Research & Technology Hellas (CERTH), PO Box 361, GR-57001 Downloaded from Thessalonica, Greece, 5Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, 6Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology Hellas, 70013 Heraklion, Crete, Greece and 7Department of Biological Sciences, Bioinformatics Research Laboratory, University of Cyprus, PO Box 20537, CY 1678, Nicosia, Cyprus http://bioinformatics.oxfordjournals.org/ Associate Editor: Alfonso Valencia ABSTRACT Contact: [email protected] or georgios.pavlopoulos@esat. Summary: The iterative process of finding relevant information in kuleuven.be biomedical literature and performing bioinformatics analyses might Supplementary information: Supplementary data are available at result in an endless loop for an inexperienced user, considering the Bioinformatics online.
    [Show full text]
  • Structure and Function of the Human Genome
    Downloaded from genome.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Perspective Structure and function of the human genome Peter F.R. Little School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney 2074, New South Wales, Australia The human genome project has had an impact on both biological research and its political organization; this review focuses primarily on the scientific novelty that has emerged from the project but also touches on its political dimensions. The project has generated both anticipated and novel information; in the later category are the description of the unusual distribution of genes, the prevalence of non-protein-coding genes, and the extraordinary evolutionary conservation of some regions of the genome. The applications of the sequence data are just starting to be felt in basic, rather than therapeutic, biomedical research and in the vibrant human origins and variation debates. The political impact of the project is in the unprecedented extent to which directed funding programs have emerged as drivers of basic research and the organization of the multidisciplinary groups that are needed to utilize the human DNA sequence. The past decade in biological research has surely been the decade If the biomedical goals of the HGP are in the future, the of genome research—from the scientific perspective, in the pub- immediate outcomes expected by the scientific community were lic imagination, and even in the minds of international politi- perhaps more pragmatic; a description of the gross structure of cians. It is therefore timely to use this 10th anniversary of Genome the human DNA sequence, the number of genes, and the pro- Research to take stock of where we are and where we might be in teins these might encode.
    [Show full text]
  • Protein Sequence Databases Rolf Apweiler1,, Amos Bairoch2 and Cathy H Wu3
    Protein sequence databases Rolf Apweiler1,Ã, Amos Bairoch2 and Cathy H Wu3 A variety of protein sequence databases exist, ranging from information provided by the genome projects and to a simple sequence repositories, which store data with little or no range of new technologies in protein science. For exam- manual intervention in the creation of the records, to expertly ple, mass spectrometry approaches are being used in curated universal databases that cover all species and in which protein identification and in determining the nature of the original sequence data are enhanced by the manual post-translational modifications [1]. These and other addition of further information in each sequence record. methods make it possible to quickly identify large num- As the focus of researchers moves from the genome to the bers of proteins, to map their interactions, to determine proteins encoded by it, these databases will play an even their location within the cell [2] and to analyse their more important role as central comprehensive resources of biological activities. Protein sequence databases play a protein information. Several the leading protein sequence vital role as a central resource for storing the data gen- databases are discussed here, with special emphasis on the erated by these and more conventional efforts, and mak- databases now provided by the Universal Protein ing them available to the scientific community. Knowledgebase (UniProt) consortium. To exploit the various resources fully, it is essential to Addresses distinguish between them
    [Show full text]
  • Convergent and Distributed Effects of the 3Q29 Deletion on the Human Neural Transcriptome ✉ Esra Sefik1,2,7, Ryan H
    Translational Psychiatry www.nature.com/tp ARTICLE OPEN Convergent and distributed effects of the 3q29 deletion on the human neural transcriptome ✉ Esra Sefik1,2,7, Ryan H. Purcell 3,4,7, The Emory 3q29 Project*, Elaine F. Walker2, Gary J. Bassell3,4 and Jennifer G. Mulle 1,5 © The Author(s) 2021 The 3q29 deletion (3q29Del) confers high risk for schizophrenia and other neurodevelopmental and psychiatric disorders. However, no single gene in this interval is definitively associated with disease, prompting the hypothesis that neuropsychiatric sequelae emerge upon loss of multiple functionally-connected genes. 3q29 genes are unevenly annotated and the impact of 3q29Del on the human neural transcriptome is unknown. To systematically formulate unbiased hypotheses about molecular mechanisms linking 3q29Del to neuropsychiatric illness, we conducted a systems-level network analysis of the non-pathological adult human cortical transcriptome and generated evidence-based predictions that relate 3q29 genes to novel functions and disease associations. The 21 protein-coding genes located in the interval segregated into seven clusters of highly co-expressed genes, demonstrating both convergent and distributed effects of 3q29Del across the interrogated transcriptomic landscape. Pathway analysis of these clusters indicated involvement in nervous-system functions, including synaptic signaling and organization, as well as core cellular functions, including transcriptional regulation, posttranslational modifications, chromatin remodeling, and mitochondrial metabolism. Top network-neighbors of 3q29 genes showed significant overlap with known schizophrenia, autism, and intellectual disability-risk genes, suggesting that 3q29Del biology is relevant to idiopathic disease. Leveraging “guilt by association”, we propose nine 3q29 genes, including one hub gene, as prioritized drivers of neuropsychiatric risk.
    [Show full text]
  • The Mouse Genome
    Downloaded from genome.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Perspective The mouse genome Jean Louis Guénet Département de Biologie du Développement, Institut Pasteur, 75724 Paris Cedex 15, France The house mouse has been used as a privileged model organism since the early days of genetics, and the numerous experiments made with this small mammal have regularly contributed to enrich our knowledge of mammalian biology and pathology, ranging from embryonic development to metabolic disease, histocompatibility, immunology, behavior, and cancer. Over the past two decades, a number of large-scale integrated and concerted projects have been undertaken that will probably open a new era in the genetics of the species. The sequencing of the genome, which will allow researchers to make comparisons with other mammals and identify regions conserved by evolution, is probably the most important project, but many other initiatives, such as the massive production of point or chromosomal mutations associated with comprehensive and standardized phenotyping of the mutant phenotypes, will help annotation of the ∼25,000 genes packed in the mouse genome. In the same way, and as another consequence of the sequencing, the discovery of many single nucleotide polymorphisms and the development of new tools and resources, like the Collaborative Cross, will contribute to the development of modern quantitative genetics. It is clear that mouse genetics has changed dramatically over the last 10–15 years and its future looks promising. Because of its many advantages as an animal model, geneticists sands of new mutations with chemicals or by gene trapping, the have used the house mouse since the early days of genetics.
    [Show full text]
  • Gocats: a Tool for Categorizing Gene Ontology Into Subgraphs of User-Defined Concepts
    University of Kentucky UKnowledge UKnowledge Molecular and Cellular Biochemistry Faculty Publications Molecular and Cellular Biochemistry 6-11-2020 GOcats: A Tool for Categorizing Gene Ontology into Subgraphs of User-Defined Concepts Eugene Waverly Hinderer III University of Kentucky, [email protected] Hunter N. B. Moseley University of Louisville, [email protected] Follow this and additional works at: https://uknowledge.uky.edu/biochem_facpub Part of the Biochemistry, Biophysics, and Structural Biology Commons, and the Cell and Developmental Biology Commons Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Repository Citation Hinderer, Eugene Waverly III and Moseley, Hunter N. B., "GOcats: A Tool for Categorizing Gene Ontology into Subgraphs of User-Defined Concepts" (2020). Molecular and Cellular Biochemistry Faculty Publications. 173. https://uknowledge.uky.edu/biochem_facpub/173 This Article is brought to you for free and open access by the Molecular and Cellular Biochemistry at UKnowledge. It has been accepted for inclusion in Molecular and Cellular Biochemistry Faculty Publications by an authorized administrator of UKnowledge. For more information, please contact [email protected]. GOcats: A Tool for Categorizing Gene Ontology into Subgraphs of User-Defined Concepts Notes/Citation Information Published in PLOS ONE, v. 15, no. 6, 0233311, p.1-29. © 2020 Hinderer III, Moseley. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Digital Object Identifier (DOI) https://doi.org/10.1371/journal.pone.0233311 This article is available at UKnowledge: https://uknowledge.uky.edu/biochem_facpub/173 PLOS ONE RESEARCH ARTICLE GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts 1 1,2,3,4,5 Eugene W.
    [Show full text]
  • An Overview of Synergistic Data Tools for Biological Scrutiny
    Review DOI: 10.1002/ijch.201200094 An Overview of Synergistic Data Tools for Biological Scrutiny Tsviya Olender,*[a] Marilyn Safran,[a] Ron Edgar,[b] Gil Stelzer,[a] Noam Nativ,[a] Naomi Rosen,[a] Ronit Shtrichman,[b] Yaron Mazor,[b] Michael D. West,[b] Ifat Keydar,[a] Noa Rappaport,[a] Frida Belinky,[a] David Warshawsky,[b] and Doron Lancet[a] Abstract: A network of biological databases is reviewed, the realm of disease scrutiny, we portray MalaCards, a novel supplying a framework for studies of human genes and the comprehensive database of human diseases and their anno- association of their genomic variations with human pheno- tations. Also shown is GeneKid, a tool aimed at generating types. The network is composed of GeneCards, the human novel kidney disease biomarkers using systems biology, as gene compendium, which provides comprehensive informa- well as Xome, a database for whole-exome next-generation tion on all known and predicted human genes, along with DNA sequences for human diseases in the Israeli popula- its suite members GeneDecks and GeneLoc. Two databases tion. Finally, we show LifeMap Discovery, a database of em- are shown that address genes and variations focusing on ol- bryonic development, stem cell research and regenerative factory reception (HORDE) and transduction (GOSdb). In medicine, which links to both GeneCards and MalaCards. Keywords: bioinformatics · databases · gene sequencing · genetic disease · olfaction 1 Introduction 2 GeneCards A main focus of our research is the use of genomics and The individual scientist, seeking research knowledge bioinformatics tools to obtain novel biological insights. about a gene of interest, can be overwhelmed by the These approaches involve the application of computation- deluge of data from worldwide genome projects.
    [Show full text]
  • Fundoscopy-Directed Genetic Testing to Re-Evaluate Negative Whole
    Cho et al. Orphanet Journal of Rare Diseases (2020) 15:32 https://doi.org/10.1186/s13023-020-1312-1 RESEARCH Open Access Fundoscopy-directed genetic testing to re- evaluate negative whole exome sequencing results Ahra Cho1,2,3, Jose Ronaldo Lima de Carvalho Jr1,3,4,5, Akemi J. Tanaka6, Ruben Jauregui1,3,7, Sarah R. Levi1,3, Alexander G. Bassuk8, Vinit B. Mahajan9,10 and Stephen H. Tsang1,3,6* Abstract Background: Whole exome sequencing (WES) allows for an unbiased search of the genetic cause of a disease. Employing it as a first-tier genetic testing can be favored due to the associated lower incremental cost per diagnosis compared to when using it later in the diagnostic pathway. However, there are technical limitations of WES that can lead to inaccurate negative variant callings. Our study presents these limitations through a re-evaluation of negative WES results using subsequent tests primarily driven by fundoscopic findings. These tests included targeted gene testing, inherited retinal gene panels, whole genome sequencing (WGS), and array comparative genomic hybridization. Results: Subsequent genetic testing guided by fundoscopy findings identified the following variant types causing retinitis pigmentosa that were not detected by WES: frameshift deletion and nonsense variants in the RPGR gene, 353- bp Alu repeat insertions in the MAK gene, and large exonic deletion variants in the EYS and PRPF31 genes. Deep intronic variants in the ABCA4 gene causing Stargardt disease and the GUCY2D gene causing Leber congenital amaurosis were also identified. Conclusions: Negative WES analyses inconsistent with the phenotype should raise clinical suspicion. Subsequent genetic testing may detect genetic variants missed by WES and can make patients eligible for gene replacement therapy and upcoming clinical trials.
    [Show full text]
  • Structural Variation in the Human Genome
    WHITEPAPER STRUCTURAL VARIATION IN THE HUMAN GENOME THE LEADER IN LONG-READ SEQUENCING The past quarter century has brought tremendous progress in the detection of single nucleotide variants (SNVs), but intermediate-sized (50 bp to 50 kb) structural variants (SV) remain a challenge. Such variants are too small to detect with cytogenetic methods, but too large to reliably discover HUMAN BIOMEDICAL RESEARCH with short-read DNA sequencing. Recent high-quality genome assemblies using PacBio long-read sequencing have revealed that each human genome has approximately 20,000 structural variants, spanning 10 million base pairs, more than twice the number of bases affected by SNVs1,2,3,4. Base pairs affected 5 Mb 3 Mb 10 Mb SNVs Indels Structural variants 1 bp <50 bp >50 bp Figure 1. Variation between two human genomes, by number of base pairs impacted. SNVs = Single nucleotide variants; indels = insertions and deletions4. www.pacb.com/sv Structural variants of all types are known to cause Mendelian disease and contribute to complex disease. All of these variants can be most robustly detected by PacBio Single Molecule, Real-Time (SMRT®) Sequencing. Genomics studies have shown that While these disorders are individually rare, the insertions, deletions, duplications, they collectively affect ~350 million people translocations, inversions, and tandem globally9, and the lengthy diagnostic repeat expansions in the structural variant odysseys these patients face has a size range can cause Mendelian disease, significant economic impact on society. 5 including Carney Complex , Potocki-Lupski Structural variants also contribute to 6 7 syndrome , and Smith-Magenis syndrome . complex disorders, including However, robust detection of structural autism10,11, cancer12,13, Alzheimer’s variants remains a hurdle.
    [Show full text]
  • Emerging Roles of Protein Kinase D1 in Cancer
    Published OnlineFirst June 16, 2011; DOI: 10.1158/1541-7786.MCR-10-0365 Molecular Cancer Subject Review Research Emerging Roles of Protein Kinase D1 in Cancer Vasudha Sundram1, Subhash C. Chauhan1,2,3, and Meena Jaggi1,2,3 Abstract Protein kinase D1 (PKD1) is a serine-threonine kinase that regulates various functions within the cell, including cell proliferation, apoptosis, adhesion, and cell motility. In normal cells, this protein plays key roles in multiple signaling pathways by relaying information from the extracellular environment and/or upstream kinases and converting them into a regulated intracellular response. The aberrant expression of PKD1 is associated with enhanced cancer phenotypes, such as deregulated cell proliferation, survival, motility, and epithelial mesenchymal transition. In this review, we summarize the structural and functional aspects of PKD1 and highlight the pathobiological roles of this kinase in cancer. Mol Cancer Res; 9(8); 985–96. Ó2011 AACR. Introduction ing pathways, and to disseminate information from the PKC signaling pathway as well. Further, PKD family Protein kinase D1 (PKD1) is a ubiquitous serine-threo- members exhibit diverse subcellular localizations (such as nine protein kinase that is involved in a multitude of cytosol, membrane, nucleus, Golgi, and mitochondria), functions in both normal and diseased states (1–3). This which allow them to influence different signaling pathways evolutionarily well-conserved protein, with homologs in (5–7). mice (Mus musculus), rats (Rattus norvegicus), flies (Droso- The PKD family contains 3 members that are homo- phila melanogaster), worms (Caenorhabditis elegans), and logous in structure and function, namely, PKD1, PKD2, yeast (Saccharomyces cerevisiae), was initially recognized as and PKD3 (5–9).
    [Show full text]