Cation and Anion Channelrhodopsins: Sequence Motifs and Taxonomic 2 Distribution
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Determinants of Channelrhodopsin Ion Selectivity
Structural foundations of optogenetics: Determinants of channelrhodopsin ion selectivity Andre Berndta,1, Soo Yeun Leea,1, Jonas Wietekb,1, Charu Ramakrishnana, Elizabeth E. Steinbergc,d, Asim J. Rashide, Hoseok Kimf, Sungmo Parke, Adam Santoroe, Paul W. Franklande, Shrivats M. Iyera, Sally Paka, Sofie Ährlund-Richterf, Scott L. Delpa, Robert C. Malenkac,d, Sheena A. Josselyne, Marie Carlénf, Peter Hegemannb, and Karl Deisserotha,c,g,2 aDepartment of Bioengineering, Stanford University, Stanford, CA 94305; bInstitute for Biology, Experimental Biophysics, Humboldt Universität zu Berlin, D-10115 Berlin, Germany; cDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305; dNancy Pritzker Laboratory, Stanford University, Stanford, CA 94305; eProgram in Neurosciences and Mental Health, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada M5G 1X8; fDepartment of Neuroscience, Karolinska Institutet, SE-171 77 Stockholm, Sweden; and gHoward Hughes Medical Institute, Stanford University, Stanford, CA 94305 This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2012. Contributed by Karl Deisseroth, November 30, 2015 (sent for review November 16, 2015; reviewed by Lily Yeh Jan and Anatol Kreitzer) The structure-guided design of chloride-conducting channelrhodop- Converging lines of work recently achieved the latter goal; resolving sins has illuminated mechanisms underlying ion selectivity of this the high-resolution structure of channelrhodopsin (7) allowed a remarkable family of light-activated ion channels. The first gener- principled structure-guided approach to engineering for chloride ation of chloride-conducting channelrhodopsins, guided in part by selectivity by testing an electrostatic model for pore function (8, 9). -
Number of Living Species in Australia and the World
Numbers of Living Species in Australia and the World 2nd edition Arthur D. Chapman Australian Biodiversity Information Services australia’s nature Toowoomba, Australia there is more still to be discovered… Report for the Australian Biological Resources Study Canberra, Australia September 2009 CONTENTS Foreword 1 Insecta (insects) 23 Plants 43 Viruses 59 Arachnida Magnoliophyta (flowering plants) 43 Protoctista (mainly Introduction 2 (spiders, scorpions, etc) 26 Gymnosperms (Coniferophyta, Protozoa—others included Executive Summary 6 Pycnogonida (sea spiders) 28 Cycadophyta, Gnetophyta under fungi, algae, Myriapoda and Ginkgophyta) 45 Chromista, etc) 60 Detailed discussion by Group 12 (millipedes, centipedes) 29 Ferns and Allies 46 Chordates 13 Acknowledgements 63 Crustacea (crabs, lobsters, etc) 31 Bryophyta Mammalia (mammals) 13 Onychophora (velvet worms) 32 (mosses, liverworts, hornworts) 47 References 66 Aves (birds) 14 Hexapoda (proturans, springtails) 33 Plant Algae (including green Reptilia (reptiles) 15 Mollusca (molluscs, shellfish) 34 algae, red algae, glaucophytes) 49 Amphibia (frogs, etc) 16 Annelida (segmented worms) 35 Fungi 51 Pisces (fishes including Nematoda Fungi (excluding taxa Chondrichthyes and (nematodes, roundworms) 36 treated under Chromista Osteichthyes) 17 and Protoctista) 51 Acanthocephala Agnatha (hagfish, (thorny-headed worms) 37 Lichen-forming fungi 53 lampreys, slime eels) 18 Platyhelminthes (flat worms) 38 Others 54 Cephalochordata (lancelets) 19 Cnidaria (jellyfish, Prokaryota (Bacteria Tunicata or Urochordata sea anenomes, corals) 39 [Monera] of previous report) 54 (sea squirts, doliolids, salps) 20 Porifera (sponges) 40 Cyanophyta (Cyanobacteria) 55 Invertebrates 21 Other Invertebrates 41 Chromista (including some Hemichordata (hemichordates) 21 species previously included Echinodermata (starfish, under either algae or fungi) 56 sea cucumbers, etc) 22 FOREWORD In Australia and around the world, biodiversity is under huge Harnessing core science and knowledge bases, like and growing pressure. -
The Plankton Lifeform Extraction Tool: a Digital Tool to Increase The
Discussions https://doi.org/10.5194/essd-2021-171 Earth System Preprint. Discussion started: 21 July 2021 Science c Author(s) 2021. CC BY 4.0 License. Open Access Open Data The Plankton Lifeform Extraction Tool: A digital tool to increase the discoverability and usability of plankton time-series data Clare Ostle1*, Kevin Paxman1, Carolyn A. Graves2, Mathew Arnold1, Felipe Artigas3, Angus Atkinson4, Anaïs Aubert5, Malcolm Baptie6, Beth Bear7, Jacob Bedford8, Michael Best9, Eileen 5 Bresnan10, Rachel Brittain1, Derek Broughton1, Alexandre Budria5,11, Kathryn Cook12, Michelle Devlin7, George Graham1, Nick Halliday1, Pierre Hélaouët1, Marie Johansen13, David G. Johns1, Dan Lear1, Margarita Machairopoulou10, April McKinney14, Adam Mellor14, Alex Milligan7, Sophie Pitois7, Isabelle Rombouts5, Cordula Scherer15, Paul Tett16, Claire Widdicombe4, and Abigail McQuatters-Gollop8 1 10 The Marine Biological Association (MBA), The Laboratory, Citadel Hill, Plymouth, PL1 2PB, UK. 2 Centre for Environment Fisheries and Aquacu∑lture Science (Cefas), Weymouth, UK. 3 Université du Littoral Côte d’Opale, Université de Lille, CNRS UMR 8187 LOG, Laboratoire d’Océanologie et de Géosciences, Wimereux, France. 4 Plymouth Marine Laboratory, Prospect Place, Plymouth, PL1 3DH, UK. 5 15 Muséum National d’Histoire Naturelle (MNHN), CRESCO, 38 UMS Patrinat, Dinard, France. 6 Scottish Environment Protection Agency, Angus Smith Building, Maxim 6, Parklands Avenue, Eurocentral, Holytown, North Lanarkshire ML1 4WQ, UK. 7 Centre for Environment Fisheries and Aquaculture Science (Cefas), Lowestoft, UK. 8 Marine Conservation Research Group, University of Plymouth, Drake Circus, Plymouth, PL4 8AA, UK. 9 20 The Environment Agency, Kingfisher House, Goldhay Way, Peterborough, PE4 6HL, UK. 10 Marine Scotland Science, Marine Laboratory, 375 Victoria Road, Aberdeen, AB11 9DB, UK. -
Fig.S1. the Pairwise Aligments of High Scoring Pairs of Recognizable Pseudogenes
LysR transcriptional regulator Identities = 57/164 (35%), Positives = 82/164 (50%), Gaps = 13/164 (8%) 70530- SNQAIKTYLMPK*LRLLRQK*SPVEFQLQVHLIKKIRLNIVIRDINLTIIEN-TPVKLKI -70354 ++Q TYLMP+ + L RQK V QLQVH ++I ++ INL II P++LK 86251- ASQTTGTYLMPRLIGLFRQKYPQVAVQLQVHSTRRIAWSVANGHINLAIIGGEVPIELKN -86072 70353- FYTLLRMKERI*H*YCLGFL------FQFLIAYKKKNLYGLRLIKVDIPFPIRGIMNNP* -70192 + E L + F L + +K++LY LR I +D IR +++ 86071- MLQVTSYAED-----ELALILPKSHPFSMLRSIQKEDLYRLRFIALDRQSTIRKVIDKVL -85907 70191- IKTELIPRNLN-EMELSLFKPIKNAV*PGLNVTLIFVSAIAKEL -70063 + + EMEL+ + IKNAV GL + VSAIAKEL 85906- NQNGIDSTRFKIEMELNSVEAIKNAVQSGLGAAFVSVSAIAKEL -85775 ycf3 Photosystem I assembly protein Identities = 25/59 (42%), Positives = 39/59 (66%), Gaps = 3/59 (5%) 19162- NRSYML-SIQCM-PNNSDYVNTLKHCR*ALDLSSKL-LAIRNVTISYYCQDIIFSEKKD -19329 +RSY+L +I + +N +YV L++ ALDL+S+L AI N+ + Y+ Q + SEKKD 19583- DRSYILYNIGLIYASNGEYVKALEYYHQALDLNSRLPPAINNIAVIYHYQGVKASEKKD -19759 Fig.S1. The pairwise aligments of high scoring pairs of recognizable pseudogenes. The upper amino acid sequences indicates Cryptomonas sp. SAG977-2f. The lower sequences are corresponding amino acid sequences of homologs in C. curvata CCAP979/52. Table S1. Presence/absence of protein genes in the plastid genomes of Cryptomonas and representative species of Cryptomonadales. Note; y indicates pseudogenes. Photosynthetic Non-Photosynthetic Guillardia Rhodomonas Cryptomonas C. C. curvata C. curvata parameciu Guillardia Rhodomonas FBCC300 CCAP979/ SAG977 CCAC1634 m theta salina -2f B 012D 52 CCAP977/2 a rps2 + + + + -
Optogenetic Investigation of Neural Circuits in Vivo
Review Optogenetic investigation of neural circuits in vivo Matthew E. Carter and Luis de Lecea Neurosciences Program and Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA The recent development of light-activated optogenetic probes are activated by light (‘opto-’) and are genetically- probes allows for the identification and manipulation of encoded (‘-genetics’), allowing for the direct control specific neural populations and their connections in of specific populations of cells in vitro and in vivo awake animals with unprecedented spatial and temporal (Figure 1) [19–23]. The unprecedented spatial and tempo- precision. This review describes the use of optogenetic ral precision of these tools has allowed substantial progress tools to investigate neurons and neural circuits in vivo. in elucidating the structure and function of previously We describe the current panel of optogenetic probes, intractable neural circuits. methods of targeting these probes to specific cell types This review highlights the use of optogenetic probes to in the nervous system, and strategies of photostimulat- investigate neural circuits in vivo. We survey the diversity of ing cells in awake, behaving animals. Finally, we survey optogenetic tools in behavioral neuroscience, discussing the application of optogenetic tools to studying func- common strategies of cell-type specific targeting and in vivo tional neuroanatomy, behavior and the etiology and light delivery. We also describe common and theoretical treatment of various neurological disorders. methods for investigating neural circuits in awake, behav- ing animals and review some of the optogenetic studies that Optogenetics represent important progress in our understanding of neu- The mammalian brain is composed of billions of neurons ral circuits in normal behavior and disease. -
Han-Optogenetic-Review-ACS-2012.Pdf
Review pubs.acs.org/chemneuro In Vivo Application of Optogenetics for Neural Circuit Analysis Xue Han Biomedical Engineering Department, Boston University, Boston, Massachusetts, United States ABSTRACT: Optogenetics combines optical and genetic methods to rapidly and reversibly control neural activities or other cellular functions. Using genetic methods, specific cells or anatomical pathways can be sensitized to light through exogenous expression of microbial light activated opsin proteins. Using optical methods, opsin expressing cells can be rapidly and reversibly controlled by pulses of light of specific wavelength. With the high spatial temporal precision, optogenetic tools have enabled new ways to probe the causal role of specific cells in neural computation and behavior. Here, we overview the current state of the technology, and provide a brief introduction to the practical considerations in applying optogenetics in vivo to analyze neural circuit functions. KEYWORDS: Channelrhodopsin, archaerhodopsin, halorhodopsin, cell type specificity ptogenetics is a new field being rapidly established upon algae), and others that mediate a variety of cellular functions O the first demonstration of precise activation of neurons (for reviews on opsin structure and function, see refs 9 and 10). expressing a light-activated microbial opsin, channelrhodopsin- Most sensory rhodopsins function through recruiting intra- 2, with pulses of blue light in 2005.1 Microbial (type I) opsins cellular signaling molecules without direct ion transport are classes of monolithic light activated proteins, encoded by function. However, channelrhodopsins can mediate phototaxis small genes of under a kilobase long. Three major classes of as a light-gated cation channel at high light intensity and as a microbial opsins have been adapted to optogenetically control calcium channel at low light intensity.11 cellular functions, channelrhodopsins, halorhodopsins, and Microbial opsins share sequence homology and are archaerhodopsins (Figure 1). -
Perfecting Chr2
RESEARCH HIGHLIGHTS NEUROSCIENCE Perfecting ChR2 Two new reports describe variants of chan- but in a typical neurobiology experiment nelrhodopsin 2 with improved properties. the channel is thought to transport mostly Channelrhodopsin 2 (ChR2) has been a sodium ions. If one were to slightly increase godsend tool to study brain function. This the number of calcium ions transported, protein—originally found in tiny algae— the group reasoned, this could result in is a membrane-ion channel that opens up improvements in the channel’s performance in response to pulses of light, producing a for neuronal activation. change in the membrane potential of charged By modifying one residue in wild-type cells. Algae use ChR2 to signal the presence ChR2, the group generated a mutant with of light and trigger their swimming away or higher calcium permeability, called ‘CatCh’ toward it in the pond; neuroscientists, after (Kleinlogel et al., 2011). In nonneuronal ‘transplanting’ ChR2 into neurons, use it to Image of a neuron expressing the TC mutant, and cells, CatCh’s modest preference for cal- provoke light-triggered action potentials in its spiking trace. Image courtesy of T. Oertner. cium ions elicits approximately three times cells embedded deep in brain tissue. Not sur- higher currents and a slight slowdown of its prisingly, some of ChR2’s natural properties As with previous higher-current ChR2 kinetics compared to wild-type ChR2. But are not exactly ideal for this purpose. mutants, however, the closure of the TC surprisingly, when expressed in neurons, In particular, the channel’s small cur- mutant’s ion channel after a light stimulus is the group saw a nearly 70-fold increase in rents and slow kinetics still limit the poten- slightly slowed down. -
Biovolumes and Size-Classes of Phytoplankton in the Baltic Sea
Baltic Sea Environment Proceedings No.106 Biovolumes and Size-Classes of Phytoplankton in the Baltic Sea Helsinki Commission Baltic Marine Environment Protection Commission Baltic Sea Environment Proceedings No. 106 Biovolumes and size-classes of phytoplankton in the Baltic Sea Helsinki Commission Baltic Marine Environment Protection Commission Authors: Irina Olenina, Centre of Marine Research, Taikos str 26, LT-91149, Klaipeda, Lithuania Susanna Hajdu, Dept. of Systems Ecology, Stockholm University, SE-106 91 Stockholm, Sweden Lars Edler, SMHI, Ocean. Services, Nya Varvet 31, SE-426 71 V. Frölunda, Sweden Agneta Andersson, Dept of Ecology and Environmental Science, Umeå University, SE-901 87 Umeå, Sweden, Umeå Marine Sciences Centre, Umeå University, SE-910 20 Hörnefors, Sweden Norbert Wasmund, Baltic Sea Research Institute, Seestr. 15, D-18119 Warnemünde, Germany Susanne Busch, Baltic Sea Research Institute, Seestr. 15, D-18119 Warnemünde, Germany Jeanette Göbel, Environmental Protection Agency (LANU), Hamburger Chaussee 25, D-24220 Flintbek, Germany Slawomira Gromisz, Sea Fisheries Institute, Kollataja 1, 81-332, Gdynia, Poland Siv Huseby, Umeå Marine Sciences Centre, Umeå University, SE-910 20 Hörnefors, Sweden Maija Huttunen, Finnish Institute of Marine Research, Lyypekinkuja 3A, P.O. Box 33, FIN-00931 Helsinki, Finland Andres Jaanus, Estonian Marine Institute, Mäealuse 10 a, 12618 Tallinn, Estonia Pirkko Kokkonen, Finnish Environment Institute, P.O. Box 140, FIN-00251 Helsinki, Finland Iveta Ledaine, Inst. of Aquatic Ecology, Marine Monitoring Center, University of Latvia, Daugavgrivas str. 8, Latvia Elzbieta Niemkiewicz, Maritime Institute in Gdansk, Laboratory of Ecology, Dlugi Targ 41/42, 80-830, Gdansk, Poland All photographs by Finnish Institute of Marine Research (FIMR) Cover photo: Aphanizomenon flos-aquae For bibliographic purposes this document should be cited to as: Olenina, I., Hajdu, S., Edler, L., Andersson, A., Wasmund, N., Busch, S., Göbel, J., Gromisz, S., Huseby, S., Huttunen, M., Jaanus, A., Kokkonen, P., Ledaine, I. -
Mannitol Biosynthesis in Algae : More Widespread and Diverse Than Previously Thought
This is a repository copy of Mannitol biosynthesis in algae : more widespread and diverse than previously thought. White Rose Research Online URL for this paper: https://eprints.whiterose.ac.uk/113250/ Version: Accepted Version Article: Tonon, Thierry orcid.org/0000-0002-1454-6018, McQueen Mason, Simon John orcid.org/0000-0002-6781-4768 and Li, Yi (2017) Mannitol biosynthesis in algae : more widespread and diverse than previously thought. New Phytologist. pp. 1573-1579. ISSN 1469-8137 https://doi.org/10.1111/nph.14358 Reuse Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. This is indicated by the licence information on the White Rose Research Online record for the item. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ 1 Mannitol biosynthesis in algae: more widespread and diverse than previously thought. Thierry Tonon1,*, Yi Li1 and Simon McQueen-Mason1 1 Department of Biology, Centre for Novel Agricultural Products, University of York, Heslington, York, YO10 5DD, UK. * Author for correspondence: tel +44 1904328785; email [email protected] Key words: Algae, primary metabolism, mannitol biosynthesis, mannitol-1-phosphate dehydrogenase, mannitol-1-phosphatase, haloacid dehalogenase, histidine phosphatase, evolution of metabolic pathways. -
Lateral Gene Transfer of Anion-Conducting Channelrhodopsins Between Green Algae and Giant Viruses
bioRxiv preprint doi: https://doi.org/10.1101/2020.04.15.042127; this version posted April 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 5 Lateral gene transfer of anion-conducting channelrhodopsins between green algae and giant viruses Andrey Rozenberg 1,5, Johannes Oppermann 2,5, Jonas Wietek 2,3, Rodrigo Gaston Fernandez Lahore 2, Ruth-Anne Sandaa 4, Gunnar Bratbak 4, Peter Hegemann 2,6, and Oded 10 Béjà 1,6 1Faculty of Biology, Technion - Israel Institute of Technology, Haifa 32000, Israel. 2Institute for Biology, Experimental Biophysics, Humboldt-Universität zu Berlin, Invalidenstraße 42, Berlin 10115, Germany. 3Present address: Department of Neurobiology, Weizmann 15 Institute of Science, Rehovot 7610001, Israel. 4Department of Biological Sciences, University of Bergen, N-5020 Bergen, Norway. 5These authors contributed equally: Andrey Rozenberg, Johannes Oppermann. 6These authors jointly supervised this work: Peter Hegemann, Oded Béjà. e-mail: [email protected] ; [email protected] 20 ABSTRACT Channelrhodopsins (ChRs) are algal light-gated ion channels widely used as optogenetic tools for manipulating neuronal activity 1,2. Four ChR families are currently known. Green algal 3–5 and cryptophyte 6 cation-conducting ChRs (CCRs), cryptophyte anion-conducting ChRs (ACRs) 7, and the MerMAID ChRs 8. Here we 25 report the discovery of a new family of phylogenetically distinct ChRs encoded by marine giant viruses and acquired from their unicellular green algal prasinophyte hosts. -
Neoproterozoic Origin and Multiple Transitions to Macroscopic Growth in Green Seaweeds
bioRxiv preprint doi: https://doi.org/10.1101/668475; this version posted June 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Neoproterozoic origin and multiple transitions to macroscopic growth in green seaweeds Andrea Del Cortonaa,b,c,d,1, Christopher J. Jacksone, François Bucchinib,c, Michiel Van Belb,c, Sofie D’hondta, Pavel Škaloudf, Charles F. Delwicheg, Andrew H. Knollh, John A. Raveni,j,k, Heroen Verbruggene, Klaas Vandepoeleb,c,d,1,2, Olivier De Clercka,1,2 Frederik Leliaerta,l,1,2 aDepartment of Biology, Phycology Research Group, Ghent University, Krijgslaan 281, 9000 Ghent, Belgium bDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, 9052 Zwijnaarde, Belgium cVIB Center for Plant Systems Biology, Technologiepark 71, 9052 Zwijnaarde, Belgium dBioinformatics Institute Ghent, Ghent University, Technologiepark 71, 9052 Zwijnaarde, Belgium eSchool of Biosciences, University of Melbourne, Melbourne, Victoria, Australia fDepartment of Botany, Faculty of Science, Charles University, Benátská 2, CZ-12800 Prague 2, Czech Republic gDepartment of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20742, USA hDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, 02138, USA. iDivision of Plant Sciences, University of Dundee at the James Hutton Institute, Dundee, DD2 5DA, UK jSchool of Biological Sciences, University of Western Australia (M048), 35 Stirling Highway, WA 6009, Australia kClimate Change Cluster, University of Technology, Ultimo, NSW 2006, Australia lMeise Botanic Garden, Nieuwelaan 38, 1860 Meise, Belgium 1To whom correspondence may be addressed. Email [email protected], [email protected], [email protected] or [email protected]. -
Activation of Distinct Channelrhodopsin Variants Engages Different Patterns of Network Activity
New Research Sensory and Motor Systems Activation of Distinct Channelrhodopsin Variants Engages Different Patterns of Network Activity Na Young Jun1 and Jessica A. Cardin2,3 https://doi.org/10.1523/ENEURO.0222-18.2019 1Department of Ophthalmology, Yale University, New Haven, CT 06520, 2Department of Neuroscience, Yale University, New Haven, CT 06520, and 3Kavli Institute for Neuroscience, Yale University, New Haven, CT 06520 Abstract Several recently developed Channelrhodopsin (ChR) variants are characterized by rapid kinetics and reduced desensitization in comparison to the widely used ChR2. However, little is known about how varying opsin properties may regulate their interaction with local network dynamics. We compared evoked cortical activity in mice expressing three ChR variants with distinct temporal profiles under the CamKII promoter: Chronos, Chrimson, and ChR2. We assessed overall neural activation by measuring the amplitude and temporal progres- sion of evoked spiking. Using ␥-range (30–80 Hz) local field potential (LFP) power as an assay for local network engagement, we examined the recruitment of cortical network activity by each tool. All variants caused light-evoked increases in firing in vivo, but each demonstrated different temporal patterning of evoked activity. In addition, the three ChRs had distinct effects on cortical ␥-band activity. Our findings suggest the properties of optogenetic tools can substantially affect their efficacy in vivo, as well their engagement of circuit resonance. Key words: Channelrhodopsin; Chrimson; Chronos; cortex; ␥ oscillations; optogenetics Significance Statement Genetically modified opsins are some of the most widely used experimental tools in modern neuroscience. However, although these tools are well characterized at the single-cell level, little is known about how the varying properties of the opsins affect their interactions with active neural networks in vivo.