Evidence map›Paper›PMID 35114111›Full record

ArticleCell2022

Structural basis for channel conduction in the pump-like channelrhodopsin ChRmine.

Koichiro E Kishi, Yoon Seok Kim, Masahiro Fukuda, Masatoshi Inoue, Tsukasa Kusakizako, Peter Y Wang, Charu Ramakrishnan, Eamon F X Byrne, Elina Thadhani, Joseph M Paggi and 17 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed
13.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

87 citing papers in PubMed, 143 citations in OpenAlex.

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  20. Serotonin modulates nucleus accumbens circuits to suppress aggression.bioRxiv : the preprint server for biology · 2025
    Article

27 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

27 authors at 8 institutions in 3 countries.

Koichiro E KishiKomaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan.
Yoon Seok KimDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Masahiro FukudaKomaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan.
Masatoshi InoueDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Tsukasa KusakizakoDepartment of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo, Tokyo, Japan.
Peter Y WangDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Charu RamakrishnanCNC Program, Stanford University, Palo Alto, CA, USA.
Eamon F X ByrneDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Elina ThadhaniDepartment of Bioengineering, Stanford University, Stanford, CA, USA; Department of Computer Science, Stanford University, Stanford, CA, USA.
Joseph M PaggiDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Toshiki E MatsuiKomaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan.
Keitaro YamashitaMRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge, UK.
Takashi NagataInstitute for Solid State Physics, The University of Tokyo, Kashiwa, Japan; PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan.
Masae KonnoInstitute for Solid State Physics, The University of Tokyo, Kashiwa, Japan; PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan.
Sean QuirinDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Maisie LoDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Tyler BensterDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Tomoko UemuraDepartment of Cell Biology, Graduate School of Medicine, Kyoto University, Kyoto, Sakyo, Japan.
Kehong LiuDepartment of Cell Biology, Graduate School of Medicine, Kyoto University, Kyoto, Sakyo, Japan.
Mikihiro ShibataWPI Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma, Kanazawa, Japan; High-Speed AFM for Biological Application Unit, Institute for Frontier Science Initiative, Kanazawa University, Kakuma, Kanazawa, Japan.
Norimichi NomuraDepartment of Cell Biology, Graduate School of Medicine, Kyoto University, Kyoto, Sakyo, Japan.
So IwataDepartment of Cell Biology, Graduate School of Medicine, Kyoto University, Kyoto, Sakyo, Japan; RIKEN SPring-8 Center, Kouto, Sayo-cho, Sayo-gun, Hyogo, Japan.
Osamu NurekiDepartment of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo, Tokyo, Japan.
Ron O DrorDepartment of Computer Science, Stanford University, Stanford, CA, USA; Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA.
Keiichi InoueInstitute for Solid State Physics, The University of Tokyo, Kashiwa, Japan.
Karl DeisserothDepartment of Bioengineering, Stanford University, Stanford, CA, USA; CNC Program, Stanford University, Palo Alto, CA, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA. Electronic address: deissero@stanford.edu.
Hideaki E KatoKomaba Institute for Science, The University of Tokyo, Meguro, Tokyo, Japan; Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo, Tokyo, Japan; PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan; FOREST, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan. Electronic address: hekato@bio.c.u-tokyo.ac.jp.
Stanford University · USThe University of Tokyo · JPKyoto University · JPJapan Science and Technology Agency · JPHoward Hughes Medical Institute · USKanazawa University · JPMRC Laboratory of Molecular Biology · GBPalo Alto University · US

Funding

Channel Structure-Based Tools for Precise Interrogation of Circuitry and BehaviorR37MH075957 · NIMH · STANFORD UNIVERSITY · PI DEISSEROTH, KARL A. · 2013 to 2022
$7.3M
Technology development for fast optical interrogation of living neural circuitryR01MH075957 · NIMH · STANFORD UNIVERSITY · PI DEISSEROTH, KARL A. · 2008 to 2012
$2.6M
Medical Research Council MC_UP_A025_1012NIMH NIH HHS R01 MH075957NIMH NIH HHS R37 MH075957
6 · The paper itself

Abstract

ChRmine, a recently discovered pump-like cation-conducting channelrhodopsin, exhibits puzzling properties (large photocurrents, red-shifted spectrum, and extreme light sensitivity) that have created new opportunities in optogenetics. ChRmine and its homologs function as ion channels but, by primary sequence, more closely resemble ion pump rhodopsins; mechanisms for passive channel conduction in this family have remained mysterious. Here, we present the 2.0 Å resolution cryo-EM structure of ChRmine, revealing architectural features atypical for channelrhodopsins: trimeric assembly, a short transmembrane-helix 3, a twisting extracellular-loop 1, large vestibules within the monomer, and an opening at the trimer interface. We applied this structure to design three proteins (rsChRmine and hsChRmine, conferring further red-shifted and high-speed properties, respectively, and frChRmine, combining faster and more red-shifted performance) suitable for fundamental neuroscience opportunities. These results illuminate the conduction and gating of pump-like channelrhodopsins and point the way toward further structure-guided creation of channelrhodopsins for applications across biology.

Indexed as

Ion Channel GatingAnimalsChannelrhodopsinsCryoelectron MicroscopyFemaleHEK293 CellsHumansMaleMiceMice, Inbred C57BLModels, MolecularOptogeneticsPhylogenyRatsRats, Sprague-DawleySchiff BasesChannelrhodopsinsSchiff Basesall-opticalchannelrhodopsinChRminecryo-EMmicrobial opsinoptogeneticsPLCRpump-like channelrhodopsinstructure-guided engineering

Identifiers

PMID35114111
PMCPMC7612760
OpenAlexW4221028201

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.