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Alegria AD, Joshi AS, Mendana JB, Khosla K, Smith KT, Auch B, Donovan M, Bischof J, Gohl DM, Kodandaramaiah SB. High-throughput genetic manipulation of multicellular organisms using a machine-vision guided embryonic microinjection robot. Genetics 2024; 226:iyae025. [PMID: 38373262 PMCID: PMC10990426 DOI: 10.1093/genetics/iyae025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/02/2024] [Accepted: 01/08/2024] [Indexed: 02/21/2024] Open
Abstract
Microinjection is a technique used for transgenesis, mutagenesis, cell labeling, cryopreservation, and in vitro fertilization in multiple single and multicellular organisms. Microinjection requires specialized skills and involves rate-limiting and labor-intensive preparatory steps. Here, we constructed a machine-vision guided generalized robot that fully automates the process of microinjection in fruit fly (Drosophila melanogaster) and zebrafish (Danio rerio) embryos. The robot uses machine learning models trained to detect embryos in images of agar plates and identify specific anatomical locations within each embryo in 3D space using dual view microscopes. The robot then serially performs a microinjection in each detected embryo. We constructed and used three such robots to automatically microinject tens of thousands of Drosophila and zebrafish embryos. We systematically optimized robotic microinjection for each species and performed routine transgenesis with proficiency comparable to highly skilled human practitioners while achieving up to 4× increases in microinjection throughput in Drosophila. The robot was utilized to microinject pools of over 20,000 uniquely barcoded plasmids into 1,713 embryos in 2 days to rapidly generate more than 400 unique transgenic Drosophila lines. This experiment enabled a novel measurement of the number of independent germline integration events per successfully injected embryo. Finally, we showed that robotic microinjection of cryoprotective agents in zebrafish embryos significantly improves vitrification rates and survival of cryopreserved embryos post-thaw as compared to manual microinjection. We anticipate that the robot can be used to carry out microinjection for genome-wide manipulation and cryopreservation at scale in a wide range of organisms.
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Affiliation(s)
- Andrew D Alegria
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Amey S Joshi
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Jorge Blanco Mendana
- University of Minnesota Genomics Center, University of Minnesota, Minneapolis, MN 55455, USA
| | - Kanav Khosla
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Kieran T Smith
- Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota, St. Paul, MN 55108, USA
| | - Benjamin Auch
- University of Minnesota Genomics Center, University of Minnesota, Minneapolis, MN 55455, USA
| | - Margaret Donovan
- University of Minnesota Genomics Center, University of Minnesota, Minneapolis, MN 55455, USA
| | - John Bischof
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Daryl M Gohl
- University of Minnesota Genomics Center, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
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2
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Guo Z, Zuchowicz N, Bouwmeester J, Joshi AS, Neisch AL, Smith K, Daly J, Etheridge ML, Finger EB, Kodandaramaiah SB, Hays TS, Hagedorn M, Bischof JC. Conduction-Dominated Cryomesh for Organism Vitrification. Adv Sci (Weinh) 2024; 11:e2303317. [PMID: 38018294 PMCID: PMC10797434 DOI: 10.1002/advs.202303317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 10/20/2023] [Indexed: 11/30/2023]
Abstract
Vitrification-based cryopreservation is a promising approach to achieving long-term storage of biological systems for maintaining biodiversity, healthcare, and sustainable food production. Using the "cryomesh" system achieves rapid cooling and rewarming of biomaterials, but further improvement in cooling rates is needed to increase biosystem viability and the ability to cryopreserve new biosystems. Improved cooling rates and viability are possible by enabling conductive cooling through cryomesh. Conduction-dominated cryomesh improves cooling rates from twofold to tenfold (i.e., 0.24 to 1.2 × 105 °C min-1 ) in a variety of biosystems. Higher thermal conductivity, smaller mesh wire diameter and pore size, and minimizing the nitrogen vapor barrier (e.g., vertical plunging in liquid nitrogen) are key parameters to achieving improved vitrification. Conduction-dominated cryomesh successfully vitrifies coral larvae, Drosophila embryos, and zebrafish embryos with improved outcomes. Not only a theoretical foundation for improved vitrification in µm to mm biosystems but also the capability to scale up for biorepositories and/or agricultural, aquaculture, or scientific use are demonstrated.
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Affiliation(s)
- Zongqi Guo
- Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
| | - Nikolas Zuchowicz
- Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
| | - Jessica Bouwmeester
- Hawaii Institute of Marine BiologyUniversity of HawaiiKaneoheHI96744USA
- Smithsonian National Zoo and Conservation Biology InstituteFront RoyalVA22630USA
| | - Amey S. Joshi
- Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
| | - Amanda L. Neisch
- Department of GeneticsCell Biology and DevelopmentUniversity of MinnesotaMinneapolisMN55455USA
| | - Kieran Smith
- Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
| | - Jonathan Daly
- Taronga Conservation Society AustraliaMosmanNew South Wales2088Australia
- School of BiologicalEarth and Environmental SciencesUniversity of New South WalesKensingtonNew South Wales2033Australia
| | - Michael L. Etheridge
- Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
| | - Erik B. Finger
- Department of SurgeryUniversity of MinnesotaMinneapolisMN55455USA
| | - Suhasa B. Kodandaramaiah
- Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
- Department of Biomedical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
- Graduate Program in NeuroscienceUniversity of MinnesotaMinneapolisMN55455USA
| | - Thomas S. Hays
- Department of GeneticsCell Biology and DevelopmentUniversity of MinnesotaMinneapolisMN55455USA
| | - Mary Hagedorn
- Hawaii Institute of Marine BiologyUniversity of HawaiiKaneoheHI96744USA
- Smithsonian National Zoo and Conservation Biology InstituteFront RoyalVA22630USA
| | - John C. Bischof
- Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
- Department of Biomedical EngineeringUniversity of MinnesotaMinneapolisMN55455USA
- Institute for Engineering in MedicineUniversity of MinnesotaMinneapolisMN55455USA
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3
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Surinach D, Rynes ML, Saxena K, Ko E, Redish AD, Kodandaramaiah SB. Strategy dependent recruitment of distributed cortical circuits during spatial navigation. Res Sq 2023:rs.3.rs-2997927. [PMID: 37398469 PMCID: PMC10312965 DOI: 10.21203/rs.3.rs-2997927/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Spatial navigation is a complex cognitive process that involves neural computations in distributed regions of the brain. Little is known about how cortical regions are coordinated when animals navigate novel spatial environments or how that coordination changes as environments become familiar. We recorded mesoscale calcium (Ca2+) dynamics across large swathes of the dorsal cortex in mice solving the Barnes maze, a 2D spatial navigation task where mice used random, serial, and spatial search strategies to navigate to the goal. Cortical dynamics exhibited patterns of repeated calcium activity with rapid and abrupt shifts between cortical activation patterns at sub-second time scales. We used a clustering algorithm to decompose the spatial patterns of cortical calcium activity in a low dimensional state space, identifying 7 states, each corresponding to a distinct spatial pattern of cortical activation, sufficient to describe the cortical dynamics across all the mice. When mice used serial or spatial search strategies to navigate to the goal, the frontal regions of the cortex were reliably activated for prolonged durations of time (> 1s) shortly after trial initiation. These frontal cortex activation events coincided with mice approaching the edge of the maze from the center and were preceded by temporal sequences of cortical activation patterns that were distinct for serial and spatial search strategies. In serial search trials, frontal cortex activation events were preceded by activation of the posterior regions of the cortex followed by lateral activation of one hemisphere. In spatial search trials, frontal cortical events were preceded by activation of posterior regions of the cortex followed by broad activation of the lateral regions of the cortex. Our results delineated cortical components that differentiate goal- and non-goal oriented spatial navigation strategies.
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Affiliation(s)
- Daniel Surinach
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Mathew L Rynes
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - Kapil Saxena
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Eunsong Ko
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - A David Redish
- Department of Neuroscience, University of Minnesota, Twin Cities
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
- Department of Neuroscience, University of Minnesota, Twin Cities
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4
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Surinach D, Rynes ML, Saxena K, Ko E, Redish AD, Kodandaramaiah SB. Distinct mesoscale cortical dynamics encode search strategies during spatial navigation. bioRxiv 2023:2023.03.27.534480. [PMID: 37034682 PMCID: PMC10081171 DOI: 10.1101/2023.03.27.534480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Spatial navigation is a complex cognitive process that involves neural computations in distributed regions of the brain. Little is known about how cortical regions are coordinated when animals navigate novel spatial environments or how that coordination changes as environments become familiar. We recorded mesoscale calcium (Ca2+) dynamics across large swathes of the dorsal cortex in mice solving the Barnes maze, a 2D spatial navigation task where mice used random, serial, and spatial search strategies to navigate to the goal. Cortical dynamics exhibited patterns of repeated calcium activity with rapid and abrupt shifts between cortical activation patterns at sub-second time scales. We used a clustering algorithm to decompose the spatial patterns of cortical calcium activity in a low dimensional state space, identifying 7 states, each corresponding to a distinct spatial pattern of cortical activation, sufficient to describe the cortical dynamics across all the mice. When mice used serial or spatial search strategies to navigate to the goal, the frontal regions of the cortex were reliably activated for prolonged durations of time (> 1s) shortly after trial initiation. These frontal cortex activation events coincided with mice approaching the edge of the maze from the center and were preceded by temporal sequences of cortical activation patterns that were distinct for serial and spatial search strategies. In serial search trials, frontal cortex activation events were preceded by activation of the posterior regions of the cortex followed by lateral activation of one hemisphere. In spatial search trials, frontal cortical events were preceded by activation of posterior regions of the cortex followed by broad activation of the lateral regions of the cortex. Our results delineated cortical components that differentiate goal- and non-goal oriented spatial navigation strategies.
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Affiliation(s)
- Daniel Surinach
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Mathew L Rynes
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - Kapil Saxena
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
| | - Eunsong Ko
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
| | - A David Redish
- Department of Neuroscience, University of Minnesota, Twin Cities
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities
- Department of Biomedical Engineering, University of Minnesota, Twin Cities
- Department of Neuroscience, University of Minnesota, Twin Cities
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5
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Hu J, Hossain RF, Navabi ZS, Tillery A, Laroque M, Donaldson PD, Swisher SL, Kodandaramaiah SB. Fully desktop fabricated flexible graphene electrocorticography (ECoG) arrays. J Neural Eng 2023; 20:10.1088/1741-2552/acae08. [PMID: 36548995 PMCID: PMC10027363 DOI: 10.1088/1741-2552/acae08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022]
Abstract
Objective:Flexible Electrocorticography (ECoG) electrode arrays that conform to the cortical surface and record surface field potentials from multiple brain regions provide unique insights into how computations occurring in distributed brain regions mediate behavior. Specialized microfabrication methods are required to produce flexible ECoG devices with high-density electrode arrays. However, these fabrication methods are challenging for scientists without access to cleanroom fabrication equipment.Results:Here we present a fully desktop fabricated flexible graphene ECoG array. First, we synthesized a stable, conductive ink via liquid exfoliation of Graphene in Cyrene. Next, we established a stencil-printing process for patterning the graphene ink via laser-cut stencils on flexible polyimide substrates. Benchtop tests indicate that the graphene electrodes have good conductivity of ∼1.1 × 103S cm-1, flexibility to maintain their electrical connection under static bending, and electrochemical stability in a 15 d accelerated corrosion test. Chronically implanted graphene ECoG devices remain fully functional for up to 180 d, with averagein vivoimpedances of 24.72 ± 95.23 kΩ at 1 kHz. The ECoG device can measure spontaneous surface field potentials from mice under awake and anesthetized states and sensory stimulus-evoked responses.Significance:The stencil-printing fabrication process can be used to create Graphene ECoG devices with customized electrode layouts within 24 h using commonly available laboratory equipment.
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Affiliation(s)
- Jia Hu
- Department of Mechanical Engineering, University of Minnesota Twin Cities
| | | | - Zahra S. Navabi
- Department of Mechanical Engineering, University of Minnesota Twin Cities
| | | | - Michael Laroque
- Department of Mechanical Engineering, University of Minnesota Twin Cities
| | - Preston D. Donaldson
- Department of Electrical and Computer Engineering, University of Minnesota Twin Cities
| | - Sarah L. Swisher
- Department of Electrical and Computer Engineering, University of Minnesota Twin Cities
| | - Suhasa B. Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota Twin Cities
- Department of Biomedical Engineering, University of Minnesota Twin Cities
- Department of Neuroscience, University of Minnesota Twin Cities
- Send manuscript correspondence to: Suhasa B. Kodandaramaiah, Department of Mechanical Engineering, University of Minnesota, Twin Cities, Address: 111 Church St SE, Room 303, Minneapolis, MN 55455,
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6
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Cramer SW, Haley SP, Popa LS, Carter RE, Scott E, Flaherty EB, Dominguez J, Aronson JD, Sabal L, Surinach D, Chen CC, Kodandaramaiah SB, Ebner TJ. Wide-field calcium imaging reveals widespread changes in cortical functional connectivity following mild traumatic brain injury in the mouse. Neurobiol Dis 2023; 176:105943. [PMID: 36476979 PMCID: PMC9972226 DOI: 10.1016/j.nbd.2022.105943] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 11/29/2022] [Accepted: 12/02/2022] [Indexed: 12/12/2022] Open
Abstract
>2.5 million individuals in the United States suffer mild traumatic brain injuries (mTBI) annually. Mild TBI is characterized by a brief period of altered consciousness, without objective findings of anatomic injury on clinical imaging or physical deficit on examination. Nevertheless, a subset of mTBI patients experience persistent subjective symptoms and repeated mTBI can lead to quantifiable neurological deficits, suggesting that each mTBI alters neurophysiology in a deleterious manner not detected using current clinical methods. To better understand these effects, we performed mesoscopic Ca2+ imaging in mice to evaluate how mTBI alters patterns of neuronal interactions across the dorsal cerebral cortex. Spatial Independent Component Analysis (sICA) and Localized semi-Nonnegative Matrix Factorization (LocaNMF) were used to quantify changes in cerebral functional connectivity (FC). Repetitive, mild, controlled cortical impacts induce temporary neuroinflammatory responses, characterized by increased density of microglia exhibiting de-ramified morphology. These temporary neuro-inflammatory changes were not associated with compromised cognitive performance in the Barnes maze or motor function as assessed by rotarod. However, long-term alterations in functional connectivity (FC) were observed. Widespread, bilateral changes in FC occurred immediately following impact and persisted for up to 7 weeks, the duration of the experiment. Network alterations include decreases in global efficiency, clustering coefficient, and nodal strength, thereby disrupting functional interactions and information flow throughout the dorsal cerebral cortex. A subnetwork analysis shows the largest disruptions in FC were concentrated near the impact site. Therefore, mTBI induces a transient neuroinflammation, without alterations in cognitive or motor behavior, and a reorganized cortical network evidenced by the widespread, chronic alterations in cortical FC.
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Affiliation(s)
- Samuel W Cramer
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, USA
| | - Samuel P Haley
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Laurentiu S Popa
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Earl Scott
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Evelyn B Flaherty
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Judith Dominguez
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Justin D Aronson
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Luke Sabal
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Daniel Surinach
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Clark C Chen
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA.
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7
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Donaldson PD, Navabi ZS, Carter RE, Fausner SML, Ghanbari L, Ebner TJ, Swisher SL, Kodandaramaiah SB. Polymer Skulls With Integrated Transparent Electrode Arrays for Cortex-Wide Opto-Electrophysiological Recordings. Adv Healthc Mater 2022; 11:e2200626. [PMID: 35869830 PMCID: PMC9573805 DOI: 10.1002/adhm.202200626] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/23/2022] [Indexed: 01/27/2023]
Abstract
Electrophysiology and optical imaging provide complementary neural sensing capabilities - electrophysiological recordings have high temporal resolution, while optical imaging allows recording of genetically-defined populations at high spatial resolution. Combining these two modalities for simultaneous large-scale, multimodal sensing of neural activity across multiple brain regions can be very powerful. Here, transparent, inkjet-printed electrode arrays with outstanding optical and electrical properties are seamlessly integrated with morphologically conformant transparent polymer skulls. Implanted on transgenic mice expressing the Calcium (Ca2+ ) indicator GCaMP6f in excitatory neurons, these "eSee-Shells" provide a robust opto-electrophysiological interface for over 100 days. eSee-Shells enable simultaneous mesoscale Ca2+ imaging and electrocorticography (ECoG) acquisition from multiple brain regions covering 45 mm2 of cortex under anesthesia and in awake animals. The clarity and transparency of eSee-Shells allow recording single-cell Ca2+ signals directly below the electrodes and interconnects. Simultaneous multimodal measurement of cortical dynamics reveals changes in both ECoG and Ca2+ signals that depend on the behavioral state.
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Affiliation(s)
- Preston D Donaldson
- Department of Electrical and Computer Engineering, University of Minnesota Twin Cities, 200 Union St SE, Minneapolis, MN, 55455, USA
| | - Zahra S Navabi
- Department of Mechanical Engineering, University of Minnesota Twin Cities, 117 Pleasant St SE, Minneapolis, MN, 55455, USA
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, Twin Cities, 312 Church St. SE, 7-105 Nils Hasselmo Hall, Minneapolis, MN, 55455, USA
| | - Skylar M L Fausner
- Department of Mechanical Engineering, University of Minnesota Twin Cities, 117 Pleasant St SE, Minneapolis, MN, 55455, USA
| | - Leila Ghanbari
- Department of Mechanical Engineering, University of Minnesota Twin Cities, 117 Pleasant St SE, Minneapolis, MN, 55455, USA
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, Twin Cities, 312 Church St. SE, 7-105 Nils Hasselmo Hall, Minneapolis, MN, 55455, USA
| | - Sarah L Swisher
- Department of Electrical and Computer Engineering, University of Minnesota Twin Cities, 200 Union St SE, Minneapolis, MN, 55455, USA
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota Twin Cities, 117 Pleasant St SE, Minneapolis, MN, 55455, USA
- Department of Neuroscience, University of Minnesota, Twin Cities, 312 Church St. SE, 7-105 Nils Hasselmo Hall, Minneapolis, MN, 55455, USA
- Department of Biomedical Engineering, University of Minnesota Twin Cities, 321 Church St SE, Minneapolis, MN, 55455, USA
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8
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Joshi AS, Alegria AD, Auch B, Khosla K, Mendana JB, Liu K, Bischof J, Gohl DM, Kodandaramaiah SB. Multiscale, multi-perspective imaging assisted robotic microinjection of 3D biological structures. Annu Int Conf IEEE Eng Med Biol Soc 2021; 2021:4844-4850. [PMID: 34892294 PMCID: PMC8966898 DOI: 10.1109/embc46164.2021.9630858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Microinjection is a widely used technique employed by biologists with applications in transgenesis, cryopreservation, mutagenesis, labeling/dye injection and in-vitro fertilization. However, microinjection is an extremely laborious manual procedure, which makes it a critical bottleneck in the field and thus ripe for automation. Here, we present a computer-guided robot that automates the targeted microinjection of Drosophila melanogaster and zebrafish (Danio rerio) embryos, two important model organisms in biological research. The robot uses a series of cameras to image an agar plate containing embryos at multiple magnifications and perspectives. This imaging is combined with machine learning and computer vision algorithms to pinpoint a location on the embryo for targeted microinjection with microscale precision. We demonstrate the utility of this microinjection robot to successfully microinject Drosophila melanogaster and zebrafish embryos. Results obtained indicate that the robotic microinjection approach can significantly increase the throughput of microinjection as compared to manual microinjection while maintaining survival rates comparable to human operators. In the future, this robotic platform can be used to perform high throughput microinjection experiments and can be extended to automatically microinject a host of organisms such as roundworms (Caenorhabditis elegans), mosquito (Culicidae) embryos, sea urchins (Echinoidea) and frog (Xenopus) oocytes.
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Affiliation(s)
- Amey S. Joshi
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, USA
| | - Andrew D. Alegria
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, USA
| | - Benjamin Auch
- University of Minnesota Genomic Center, University of Minnesota Twin Cities, Minneapolis, USA
| | - Kanav Khosla
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, USA
| | - Jorge Blanco Mendana
- University of Minnesota Genomic Center, University of Minnesota Twin Cities, Minneapolis, USA
| | - Kunpeng Liu
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, USA
| | - John Bischof
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, USA
- Department of Biomedical Engineering, University of Minnesota Twin Cities, Minneapolis, USA
| | - Daryl M. Gohl
- University of Minnesota Genomic Center, University of Minnesota Twin Cities, Minneapolis, USA
- Department of Genetics, Cell Biology, and Development, University of Minnesota Twin Cities, Minneapolis, USA
| | - Suhasa B. Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, USA
- Department of Biomedical Engineering, University of Minnesota Twin Cities, Minneapolis, USA
- Department of Neuroscience, University of Minnesota Twin Cities, Minneapolis, USA
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9
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West SL, Aronson JD, Popa LS, Feller KD, Carter RE, Chiesl WM, Gerhart ML, Shekhar AC, Ghanbari L, Kodandaramaiah SB, Ebner TJ. Wide-Field Calcium Imaging of Dynamic Cortical Networks during Locomotion. Cereb Cortex 2021; 32:2668-2687. [PMID: 34689209 PMCID: PMC9201596 DOI: 10.1093/cercor/bhab373] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 09/10/2021] [Accepted: 09/11/2021] [Indexed: 01/04/2023] Open
Abstract
Motor behavior results in complex exchanges of motor and sensory information across cortical regions. Therefore, fully understanding the cerebral cortex’s role in motor behavior requires a mesoscopic-level description of the cortical regions engaged, their functional interactions, and how these functional interactions change with behavioral state. Mesoscopic Ca2+ imaging through transparent polymer skulls in mice reveals elevated activation of the dorsal cerebral cortex during locomotion. Using the correlations between the time series of Ca2+ fluorescence from 28 regions (nodes) obtained using spatial independent component analysis (sICA), we examined the changes in functional connectivity of the cortex from rest to locomotion with a goal of understanding the changes to the cortical functional state that facilitate locomotion. Both the transitions from rest to locomotion and from locomotion to rest show marked increases in correlation among most nodes. However, once a steady state of continued locomotion is reached, many nodes, including primary motor and somatosensory nodes, show decreases in correlations, while retrosplenial and the most anterior nodes of the secondary motor cortex show increases. These results highlight the changes in functional connectivity in the cerebral cortex, representing a series of changes in the cortical state from rest to locomotion and on return to rest.
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Affiliation(s)
- Sarah L West
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA.,Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Justin D Aronson
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Laurentiu S Popa
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Kathryn D Feller
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA.,Union College Biological Sciences Department, Schenectady, NY 12308, USA
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - William M Chiesl
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Morgan L Gerhart
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Aditya C Shekhar
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Leila Ghanbari
- Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Suhasa B Kodandaramaiah
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA.,Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.,Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA.,Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
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10
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Rynes ML, Surinach DA, Linn S, Laroque M, Rajendran V, Dominguez J, Hadjistamoulou O, Navabi ZS, Ghanbari L, Johnson GW, Nazari M, Mohajerani MH, Kodandaramaiah SB. Miniaturized head-mounted microscope for whole-cortex mesoscale imaging in freely behaving mice. Nat Methods 2021; 18:417-425. [PMID: 33820987 PMCID: PMC8034419 DOI: 10.1038/s41592-021-01104-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 02/18/2021] [Accepted: 02/26/2021] [Indexed: 12/28/2022]
Abstract
The advent of genetically encoded calcium indicators, along with surgical preparations such as thinned skulls or refractive index matched skulls, have enabled mesoscale cortical activity imaging in head-fixed mice. However, neural activity during unrestrained behavior substantially differs from neural activity in head-fixed animals. For whole-cortex imaging in freely behaving mice, we here present the “mini-mScope,” a wide-field, miniaturized, and head-mounted fluorescence microscope compatible with transparent polymer skull preparations. With a field of view of 8 mm x 10 mm and weighing less than 4 g, the mini-mScope can image most of the mouse dorsal cortex with resolution ranging from 39 to 56 μm. We have used the mini-mScope to record mesoscale calcium activity across the dorsal cortex during sensory-evoked stimuli, open field behaviors, social interactions, and transitions from wakefulness to sleep.
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Affiliation(s)
- Mathew L Rynes
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Daniel A Surinach
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Samantha Linn
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Michael Laroque
- Schools of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Vijay Rajendran
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Judith Dominguez
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Orestes Hadjistamoulou
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Zahra S Navabi
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Leila Ghanbari
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Gregory W Johnson
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Mojtaba Nazari
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada
| | - Majid H Mohajerani
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada
| | - Suhasa B Kodandaramaiah
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA. .,Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN, USA. .,Department of Neuroscience, University of Minnesota, Twin Cities, Minneapolis, MN, USA.
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11
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Cramer SW, Carter RE, Aronson JD, Kodandaramaiah SB, Ebner TJ, Chen CC. Through the looking glass: A review of cranial window technology for optical access to the brain. J Neurosci Methods 2021; 354:109100. [PMID: 33600850 DOI: 10.1016/j.jneumeth.2021.109100] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 02/07/2021] [Accepted: 02/09/2021] [Indexed: 02/07/2023]
Abstract
Deciphering neurologic function is a daunting task, requiring understanding the neuronal networks and emergent properties that arise from the interactions among single neurons. Mechanistic insights into neuronal networks require tools that simultaneously assess both single neuron activity and the consequent mesoscale output. The development of cranial window technologies, in which the skull is thinned or replaced with a synthetic optical interface, has enabled monitoring neuronal activity from subcellular to mesoscale resolution in awake, behaving animals when coupled with advanced microscopy techniques. Here we review recent achievements in cranial window technologies, appraise the relative merits of each design and discuss the future research in cranial window design.
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Affiliation(s)
- Samuel W Cramer
- Department of Neurosurgery, University of Minnesota, 420 Delaware St SE, Mayo D429, MMC 96, Twin Cities, Minneapolis, MN, 55455, USA
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, Twin Cities, Room 421, 2001 Sixth Street S.E., Minneapolis, MN, 55455 MN, USA
| | - Justin D Aronson
- Department of Neuroscience, University of Minnesota, Twin Cities, Room 421, 2001 Sixth Street S.E., Minneapolis, MN, 55455 MN, USA
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA; Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA; Graduate Program in Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, Twin Cities, Room 421, 2001 Sixth Street S.E., Minneapolis, MN, 55455 MN, USA.
| | - Clark C Chen
- Department of Neurosurgery, University of Minnesota, 420 Delaware St SE, Mayo D429, MMC 96, Twin Cities, Minneapolis, MN, 55455, USA.
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12
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Shull G, Haffner C, Huttner WB, Taverna E, Kodandaramaiah SB. Manipulation of Single Neural Stem Cells and Neurons in Brain Slices using Robotic Microinjection. J Vis Exp 2021. [PMID: 33554975 DOI: 10.3791/61599] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
A central question in developmental neurobiology is how neural stem and progenitor cells form the brain. To answer this question, one needs to label, manipulate, and follow single cells in the brain tissue with high resolution over time. This task is extremely challenging due to the complexity of tissues in the brain. We have recently developed a robot, that guide a microinjection needle into brain tissue upon utilizing images acquired from a microscope to deliver femtoliter volumes of solution into single cells. The robotic operation increases resulting an overall yield that is an order of magnitude greater than manual microinjection and allows for precise labeling and flexible manipulation of single cells in living tissue. With this, one can microinject hundreds of cells within a single organotypic slice. This article demonstrates the use of the microinjection robot for automated microinjection of neural progenitor cells and neurons in the brain tissue slices. More broadly, it can be used on any epithelial tissue featuring a surface that can be reached by the pipette. Once set up, the microinjection robot can execute 15 or more microinjections per minute. The microinjection robot because of its throughput and versality will make microinjection a broadly straightforward high-performance cell manipulation technique to be used in bioengineering, biotechnology, and biophysics for performing single-cell analyses in organotypic brain slices.
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Affiliation(s)
- Gabriella Shull
- Department of Biomedical Engineering, University of Minnesota; Department of Biomedical Engineering, Duke University
| | | | | | - Elena Taverna
- Max Planck Institute of Molecular Cell Biology and Genetics; Max Planck Institute for Evolutionary Anthropology;
| | - Suhasa B Kodandaramaiah
- Department of Biomedical Engineering, University of Minnesota; Department of Mechanical Engineering, University of Minnesota; Graduate Program in Neuroscience, University of Minnesota;
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13
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Alegria A, Joshi A, O'Brien J, Kodandaramaiah SB. Single neuron recording: progress towards high-throughput analysis. Bioelectron Med (Lond) 2020; 3:33-36. [PMID: 33169092 PMCID: PMC7604670 DOI: 10.2217/bem-2020-0011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 08/10/2020] [Indexed: 11/21/2022]
Affiliation(s)
- Andrew Alegria
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN 55455, USA
| | - Amey Joshi
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN 55455, USA
| | - Jacob O'Brien
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN 55455, USA
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN 55455, USA
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN 55455, USA
- Department of Neuroscience, University of Minnesota, Twin Cities, MN 55455, USA
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14
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Rynes ML, Ghanbari L, Schulman DS, Linn S, Laroque M, Dominguez J, Navabi ZS, Sherman P, Kodandaramaiah SB. Assembly and operation of an open-source, computer numerical controlled (CNC) robot for performing cranial microsurgical procedures. Nat Protoc 2020; 15:1992-2023. [PMID: 32405052 DOI: 10.1038/s41596-020-0318-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 03/03/2020] [Indexed: 12/14/2022]
Abstract
Cranial microsurgery is an essential procedure for accessing the brain through the skull that can be used to introduce neural probes that measure and manipulate neural activity. Neuroscientists have typically used tools such as high-speed drills adapted from dentistry to perform these procedures. As the number of technologies available for neuroscientists has increased, the corresponding cranial microsurgery procedures to deploy them have become more complex. Using a robotic tool that automatically performs these procedures could standardize cranial microsurgeries across neuroscience laboratories and democratize the more challenging procedures. We have recently engineered a robotic surgery platform that utilizes principles of computer numerical control (CNC) machining to perform a wide variety of automated cranial procedures. Here, we describe how to adapt, configure and use an inexpensive desktop CNC mill equipped with a custom-built surface profiler for performing CNC-guided microsurgery on mice. Detailed instructions are provided to utilize this 'Craniobot' for performing circular craniotomies for coverslip implantation, large craniotomies for implanting transparent polymer skulls for cortex-wide imaging access and skull thinning for intact skull imaging. The Craniobot can be set up in <2 weeks using parts that cost <$1,500, and we anticipate that the Craniobot could be easily adapted for use in other small animals.
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Affiliation(s)
- Mathew L Rynes
- Department of Biomedical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Leila Ghanbari
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Daniel Sousa Schulman
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Samantha Linn
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Michael Laroque
- Schools of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Judith Dominguez
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Zahra S Navabi
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Peter Sherman
- Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Suhasa B Kodandaramaiah
- Department of Biomedical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA. .,Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA.
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15
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An J, Flores FJ, Kodandaramaiah SB, Dalla Betta I, Nikolaeva K, Boyden ES, Forest CR, Brown EN. Automated Assessment of Loss of Consciousness Using Whisker And Paw Movements During Anesthetic Dosing in Head-Fixed Rodents. Annu Int Conf IEEE Eng Med Biol Soc 2019; 2018:730-733. [PMID: 30440500 DOI: 10.1109/embc.2018.8512377] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The precise identification of loss of consciousness (LOC) is key to studying the effects of anesthetic drugs in neural systems. The standard behavioral assay for identifying LOC in rodents is the Loss of Righting Reflex (LORR), assessed by placing the animal in the supine position every minute until it fails to right itself. However, this assay cannot be used when the rodents are head-fixed, which limits the use of powerful techniques such as multi-electrode recordings, in vivo patch clamp, and neuronal imaging. In these situations, an alternative way to assess LOC is needed. We propose that loss of movement (LOM) in whiskers and paws of head-fixed animals can be used as an alternative behavioral assay in head-fixed animals. Unlike LORR, LOM in whiskers and paws is much harder to detect by visual inspection. Therefore, we developed a method to automatically assess for LOM of whiskers and paws in head fixed rodents during in vivo patch clamp recordings. Our method uses an algorithm based on optical flow and point-process filtering which can be run on images acquired on regular cameras at low frame-rates. We show that the algorithm can achieve at least comparable accuracy in detecting LOC when compared with consensus among human observers, as well as improved precision when compared with individual observers. In the future, we aim to to expand the method to detect more behavioral end-points during anesthesia such as paradoxical excitation. Eventually, we hope to enable multi-modal anesthesia studies, which incorporates behavioral and neurophysiological data.
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16
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Shull G, Haffner C, Huttner WB, Kodandaramaiah SB, Taverna E. Robotic platform for microinjection into single cells in brain tissue. EMBO Rep 2019; 20:e47880. [PMID: 31469223 PMCID: PMC6776899 DOI: 10.15252/embr.201947880] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Revised: 07/23/2019] [Accepted: 08/07/2019] [Indexed: 01/02/2023] Open
Abstract
Microinjection into single cells in brain tissue is a powerful technique to study and manipulate neural stem cells. However, such microinjection requires expertise and is a low-throughput process. We developed the "Autoinjector", a robot that utilizes images from a microscope to guide a microinjection needle into tissue to deliver femtoliter volumes of liquids into single cells. The Autoinjector enables microinjection of hundreds of cells within a single organotypic slice, resulting in an overall yield that is an order of magnitude greater than manual microinjection. The Autoinjector successfully targets both apical progenitors (APs) and newborn neurons in the embryonic mouse and human fetal telencephalon. We used the Autoinjector to systematically study gap-junctional communication between neural progenitors in the embryonic mouse telencephalon and found that apical contact is a characteristic feature of the cells that are part of a gap junction-coupled cluster. The throughput and versatility of the Autoinjector will render microinjection an accessible high-performance single-cell manipulation technique and will provide a powerful new platform for performing single-cell analyses in tissue for bioengineering and biophysics applications.
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Affiliation(s)
- Gabriella Shull
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA.,Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Christiane Haffner
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Wieland B Huttner
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Suhasa B Kodandaramaiah
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA.,Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Elena Taverna
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.,Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
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17
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Holst GL, Stoy W, Yang B, Kolb I, Kodandaramaiah SB, Li L, Knoblich U, Zeng H, Haider B, Boyden ES, Forest CR. Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex. J Neurophysiol 2019; 121:2341-2357. [PMID: 30969898 DOI: 10.1152/jn.00738.2018] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques. NEW & NOTEWORTHY In vivo patch-clamp is the gold standard for intracellular recordings, but it is a very manual and highly skilled technique. The robot in this work demonstrates the most automated in vivo patch-clamp experiment to date, by enabling production of multiple, serial intracellular recordings without human intervention. The robot automates pipette filling, wire threading, pipette positioning, neuron hunting, break-in, delivering sensory stimulus, and recording quality control, enabling in vivo cell-type characterization.
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Affiliation(s)
- Gregory L Holst
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | - William Stoy
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | - Bo Yang
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | - Ilya Kolb
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | | | - Lu Li
- Allen Institute for Brain Science , Seattle, Washington
| | - Ulf Knoblich
- Allen Institute for Brain Science , Seattle, Washington
| | - Hongkui Zeng
- Allen Institute for Brain Science , Seattle, Washington
| | - Bilal Haider
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology , Atlanta, Georgia
| | - Edward S Boyden
- Media Arts and Sciences, Massachusetts Institute of Technology , Cambridge, Massachusetts.,McGovern Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts.,Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology , Atlanta, Georgia
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18
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Ghanbari L, Carter RE, Rynes ML, Dominguez J, Chen G, Naik A, Hu J, Sagar MAK, Haltom L, Mossazghi N, Gray MM, West SL, Eliceiri KW, Ebner TJ, Kodandaramaiah SB. Cortex-wide neural interfacing via transparent polymer skulls. Nat Commun 2019; 10:1500. [PMID: 30940809 PMCID: PMC6445105 DOI: 10.1038/s41467-019-09488-0] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 03/12/2019] [Indexed: 11/22/2022] Open
Abstract
Neural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating behaviors. Progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. We engineered ‘See-Shells’—digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (>300 days) optical access to 45 mm2 of the dorsal cerebral cortex in the mouse. We demonstrate the ability to perform mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm deep. See-Shells allow calcium imaging from multiple, non-contiguous regions across the cortex. Perforated See-Shells enable introducing penetrating neural probes to perturb or record neural activity simultaneously with whole cortex imaging. See-Shells are constructed using common desktop fabrication tools, providing a powerful tool for investigating brain structure and function. Imaging the mouse brain using glass cranial windows has limitations in terms of flexibility and long-term imaging. Here the authors engineer transparent polymer skulls that can fit various skull morphologies and can be implanted for over 300 days, enabling simultaneous high resolution brain imaging and electrophysiology across large cortical areas.
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Affiliation(s)
- Leila Ghanbari
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Russell E Carter
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Mathew L Rynes
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Judith Dominguez
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Gang Chen
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Anant Naik
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Jia Hu
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA
| | | | - Lenora Haltom
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA
| | - Nahom Mossazghi
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Madelyn M Gray
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Sarah L West
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Kevin W Eliceiri
- Department of Biomedical Engineering, University of Wisconsin, Madison, WI, USA
| | - Timothy J Ebner
- Department of Neuroscience, University of Minnesota, Twin Cities, MN, USA
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN, USA. .,Department of Biomedical Engineering, University of Minnesota, Twin Cities, MN, USA.
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19
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Ghanbari L, Rynes ML, Hu J, Schulman DS, Johnson GW, Laroque M, Shull GM, Kodandaramaiah SB. Craniobot: A computer numerical controlled robot for cranial microsurgeries. Sci Rep 2019; 9:1023. [PMID: 30705287 PMCID: PMC6355931 DOI: 10.1038/s41598-018-37073-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 11/30/2018] [Indexed: 12/11/2022] Open
Abstract
Over the last few decades, a plethora of tools has been developed for neuroscientists to interface with the brain. Implementing these tools requires precisely removing sections of the skull to access the brain. These delicate cranial microsurgical procedures need to be performed on the sub-millimeter thick bone without damaging the underlying tissue and therefore, require significant training. Automating some of these procedures would not only enable more precise microsurgical operations, but also facilitate widespread use of advanced neurotechnologies. Here, we introduce the “Craniobot”, a cranial microsurgery platform that combines automated skull surface profiling with a computer numerical controlled (CNC) milling machine to perform a variety of cranial microsurgical procedures on mice. The Craniobot utilizes a low-force contact sensor to profile the skull surface and uses this information to perform precise milling operations within minutes. We have used the Craniobot to perform intact skull thinning and open small to large craniotomies over the dorsal cortex.
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Affiliation(s)
- Leila Ghanbari
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minnesota, USA
| | - Mathew L Rynes
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, Minnesota, USA
| | - Jia Hu
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, Minnesota, USA
| | - Daniel S Schulman
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minnesota, USA
| | - Gregory W Johnson
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minnesota, USA
| | - Michael Laroque
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minnesota, USA
| | - Gabriella M Shull
- Department of Biomedical Engineering, University of Minnesota, Twin Cities, Minnesota, USA
| | - Suhasa B Kodandaramaiah
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minnesota, USA. .,Department of Biomedical Engineering, University of Minnesota, Twin Cities, Minnesota, USA.
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20
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Allen BD, Moore-Kochlacs C, Bernstein JG, Kinney JP, Scholvin J, Seoane LF, Chronopoulos C, Lamantia C, Kodandaramaiah SB, Tegmark M, Boyden ES. Automated in vivo patch-clamp evaluation of extracellular multielectrode array spike recording capability. J Neurophysiol 2018; 120:2182-2200. [PMID: 29995597 DOI: 10.1152/jn.00650.2017] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Much innovation is currently aimed at improving the number, density, and geometry of electrodes on extracellular multielectrode arrays for in vivo recording of neural activity in the mammalian brain. To choose a multielectrode array configuration for a given neuroscience purpose, or to reveal design principles of future multielectrode arrays, it would be useful to have a systematic way of evaluating the spike recording capability of such arrays. We describe an automated system that performs robotic patch-clamp recording of a neuron being simultaneously recorded via an extracellular multielectrode array. By recording a patch-clamp data set from a neuron while acquiring extracellular recordings from the same neuron, we can evaluate how well the extracellular multielectrode array captures the spiking information from that neuron. To demonstrate the utility of our system, we show that it can provide data from the mammalian cortex to evaluate how the spike sorting performance of a close-packed extracellular multielectrode array is affected by bursting, which alters the shape and amplitude of spikes in a train. We also introduce an algorithmic framework to help evaluate how the number of electrodes in a multielectrode array affects spike sorting, examining how adding more electrodes yields data that can be spike sorted more easily. Our automated methodology may thus help with the evaluation of new electrode designs and configurations, providing empirical guidance on the kinds of electrodes that will be optimal for different brain regions, cell types, and species, for improving the accuracy of spike sorting. NEW & NOTEWORTHY We present an automated strategy for evaluating the spike recording performance of an extracellular multielectrode array, by enabling simultaneous recording of a neuron with both such an array and with patch clamp. We use our robot and accompanying algorithms to evaluate the performance of multielectrode arrays on supporting spike sorting.
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Affiliation(s)
- Brian D Allen
- Media Lab and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, and Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts
| | - Caroline Moore-Kochlacs
- Media Lab and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, and Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts.,Department of Neuroscience, Boston University , Boston, Massachusetts
| | - Jacob G Bernstein
- Media Lab and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, and Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts
| | - Justin P Kinney
- Media Lab and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, and Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts.,Leaflabs, LLC, Cambridge, Massachusetts
| | - Jorg Scholvin
- Media Lab and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, and Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts
| | - Luís F Seoane
- Department of Physics and Kavli Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts
| | | | | | - Suhasa B Kodandaramaiah
- Media Lab and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, and Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts.,Department of Mechanical Engineering, University of Minnesota , Minneapolis, Minnesota
| | - Max Tegmark
- Department of Physics and Kavli Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts
| | - Edward S Boyden
- Media Lab and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, and Koch Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts
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21
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Kodandaramaiah SB, Flores FJ, Holst GL, Singer AC, Han X, Brown EN, Boyden ES, Forest CR. Multi-neuron intracellular recording in vivo via interacting autopatching robots. eLife 2018; 7:24656. [PMID: 29297466 PMCID: PMC5812718 DOI: 10.7554/elife.24656] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2016] [Accepted: 12/19/2017] [Indexed: 11/16/2022] Open
Abstract
The activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known about the intracellular processes that lead to spiking activity. We present a robotic system, the multipatcher, capable of automatically obtaining blind whole-cell patch clamp recordings from multiple neurons simultaneously. The multipatcher significantly extends automated patch clamping, or 'autopatching’, to guide four interacting electrodes in a coordinated fashion, avoiding mechanical coupling in the brain. We demonstrate its performance in the cortex of anesthetized and awake mice. A multipatcher with four electrodes took an average of 10 min to obtain dual or triple recordings in 29% of trials in anesthetized mice, and in 18% of the trials in awake mice, thus illustrating practical yield and throughput to obtain multiple, simultaneous whole-cell recordings in vivo.
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Affiliation(s)
- Suhasa B Kodandaramaiah
- Media Lab, Massachusetts Institute of Technology, Cambridge, United States.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States.,G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, United States
| | - Francisco J Flores
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, United States.,Picower Institute for Memory and Learning, Massachusetts Institute of Technology, Cambridge, United States
| | - Gregory L Holst
- G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, United States
| | - Annabelle C Singer
- Media Lab, Massachusetts Institute of Technology, Cambridge, United States.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, United States
| | - Emery N Brown
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, United States.,Picower Institute for Memory and Learning, Massachusetts Institute of Technology, Cambridge, United States.,Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, United States
| | - Edward S Boyden
- Media Lab, Massachusetts Institute of Technology, Cambridge, United States.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States
| | - Craig R Forest
- G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, United States
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22
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Piatkevich KD, Suk HJ, Kodandaramaiah SB, Yoshida F, DeGennaro EM, Drobizhev M, Hughes TE, Desimone R, Boyden ES, Verkhusha VV. Near-Infrared Fluorescent Proteins Engineered from Bacterial Phytochromes in Neuroimaging. Biophys J 2017; 113:2299-2309. [PMID: 29017728 DOI: 10.1016/j.bpj.2017.09.007] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Revised: 09/03/2017] [Accepted: 09/06/2017] [Indexed: 11/17/2022] Open
Abstract
Several series of near-infrared (NIR) fluorescent proteins (FPs) were recently engineered from bacterial phytochromes but were not systematically compared in neurons. To fluoresce, NIR FPs utilize an enzymatic derivative of heme, the linear tetrapyrrole biliverdin, as a chromophore whose level in neurons is poorly studied. Here, we evaluated NIR FPs of the iRFP protein family, which were reported to be the brightest in non-neuronal mammalian cells, in primary neuronal culture, in brain slices of mouse and monkey, and in mouse brain in vivo. We applied several fluorescence imaging modes, such as wide-field and confocal one-photon and two-photon microscopy, to compare photochemical and biophysical properties of various iRFPs. The iRFP682 and iRFP670 proteins exhibited the highest brightness and photostability under one-photon and two-photon excitation modes, respectively. All studied iRFPs exhibited efficient binding of the endogenous biliverdin chromophore in cultured neurons and in the mammalian brain and can be readily applied to neuroimaging.
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Affiliation(s)
- Kiryl D Piatkevich
- Media Lab, MIT, Cambridge, Massachusetts; MIT McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts
| | - Ho-Jun Suk
- Media Lab, MIT, Cambridge, Massachusetts; Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, Massachusetts
| | - Suhasa B Kodandaramaiah
- Media Lab, MIT, Cambridge, Massachusetts; MIT McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts
| | - Fumiaki Yoshida
- MIT McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts
| | - Ellen M DeGennaro
- MIT McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts; Department of Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts
| | - Mikhail Drobizhev
- Department of Cell Biology and Neuroscience, Montana State University, Bozeman, Montana
| | - Thomas E Hughes
- Department of Cell Biology and Neuroscience, Montana State University, Bozeman, Montana
| | - Robert Desimone
- MIT McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts; Department of Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts
| | - Edward S Boyden
- Media Lab, MIT, Cambridge, Massachusetts; MIT McGovern Institute for Brain Research, MIT, Cambridge, Massachusetts; Department of Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts; Department of Biological Engineering, MIT, Cambridge, Massachusetts; MIT Center for Neurobiological Engineering, MIT, Cambridge, Massachusetts.
| | - Vladislav V Verkhusha
- Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York; Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, New York.
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23
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Suk HJ, van Welie I, Kodandaramaiah SB, Allen B, Forest CR, Boyden ES. Closed-Loop Real-Time Imaging Enables Fully Automated Cell-Targeted Patch-Clamp Neural Recording In Vivo. Neuron 2017; 95:1037-1047.e11. [PMID: 28858614 DOI: 10.1016/j.neuron.2017.08.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Revised: 06/27/2017] [Accepted: 08/04/2017] [Indexed: 01/02/2023]
Abstract
Targeted patch-clamp recording is a powerful method for characterizing visually identified cells in intact neural circuits, but it requires skill to perform. We previously developed an algorithm that automates "blind" patching in vivo, but full automation of visually guided, targeted in vivo patching has not been demonstrated, with currently available approaches requiring human intervention to compensate for cell movement as a patch pipette approaches a targeted neuron. Here we present a closed-loop real-time imaging strategy that automatically compensates for cell movement by tracking cell position and adjusting pipette motion while approaching a target. We demonstrate our system's ability to adaptively patch, under continuous two-photon imaging and real-time analysis, fluorophore-expressing neurons of multiple types in the living mouse cortex, without human intervention, with yields comparable to skilled human experimenters. Our "imagepatching" robot is easy to implement and will help enable scalable characterization of identified cell types in intact neural circuits.
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Affiliation(s)
- Ho-Jun Suk
- Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ingrid van Welie
- Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Suhasa B Kodandaramaiah
- Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Brian Allen
- Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Craig R Forest
- G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Edward S Boyden
- Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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24
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Singer AC, Talei Franzesi G, Kodandaramaiah SB, Flores FJ, Cohen JD, Lee AK, Borgers C, Forest CR, Kopell NJ, Boyden ES. Mesoscale-duration activated states gate spiking in response to fast rises in membrane voltage in the awake brain. J Neurophysiol 2017; 118:1270-1291. [PMID: 28566460 PMCID: PMC5558023 DOI: 10.1152/jn.00116.2017] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 05/26/2017] [Accepted: 05/29/2017] [Indexed: 12/13/2022] Open
Abstract
Seconds-scale network states, affecting many neurons within a network, modulate neural activity by complementing fast integration of neuron-specific inputs that arrive in the milliseconds before spiking. Nonrhythmic subthreshold dynamics at intermediate timescales, however, are less well characterized. We found, using automated whole cell patch clamping in vivo, that spikes recorded in CA1 and barrel cortex in awake mice are often preceded not only by monotonic voltage rises lasting milliseconds but also by more gradual (lasting tens to hundreds of milliseconds) depolarizations. The latter exert a gating function on spiking, in a fashion that depends on the gradual rise duration: the probability of spiking was higher for longer gradual rises, even when controlled for the amplitude of the gradual rises. Barrel cortex double-autopatch recordings show that gradual rises are shared across some, but not all, neurons. The gradual rises may represent a new kind of state, intermediate both in timescale and in proportion of neurons participating, which gates a neuron's ability to respond to subsequent inputs.NEW & NOTEWORTHY We analyzed subthreshold activity preceding spikes in hippocampus and barrel cortex of awake mice. Aperiodic voltage ramps extending over tens to hundreds of milliseconds consistently precede and facilitate spikes, in a manner dependent on both their amplitude and their duration. These voltage ramps represent a "mesoscale" activated state that gates spike production in vivo.
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Affiliation(s)
- Annabelle C Singer
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia
- Media Laboratory and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Giovanni Talei Franzesi
- Media Laboratory and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Suhasa B Kodandaramaiah
- Media Laboratory and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, Minnesota
| | - Francisco J Flores
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Jeremy D Cohen
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, Virginia
| | - Albert K Lee
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, Virginia
| | | | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia; and
| | - Nancy J Kopell
- Department of Mathematics and Statistics, Boston University, Boston, Massachusetts
| | - Edward S Boyden
- Media Laboratory and McGovern Institute for Brain Research, Departments of Biological Engineering and Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts;
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25
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Grossman N, Bono D, Dedic N, Kodandaramaiah SB, Rudenko A, Suk HJ, Cassara AM, Neufeld E, Kuster N, Tsai LH, Pascual-Leone A, Boyden ES. Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields. Cell 2017; 169:1029-1041.e16. [PMID: 28575667 PMCID: PMC5520675 DOI: 10.1016/j.cell.2017.05.024] [Citation(s) in RCA: 371] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Revised: 02/22/2017] [Accepted: 05/12/2017] [Indexed: 12/22/2022]
Abstract
We report a noninvasive strategy for electrically stimulating neurons at depth. By delivering to the brain multiple electric fields at frequencies too high to recruit neural firing, but which differ by a frequency within the dynamic range of neural firing, we can electrically stimulate neurons throughout a region where interference between the multiple fields results in a prominent electric field envelope modulated at the difference frequency. We validated this temporal interference (TI) concept via modeling and physics experiments, and verified that neurons in the living mouse brain could follow the electric field envelope. We demonstrate the utility of TI stimulation by stimulating neurons in the hippocampus of living mice without recruiting neurons of the overlying cortex. Finally, we show that by altering the currents delivered to a set of immobile electrodes, we can steerably evoke different motor patterns in living mice.
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Affiliation(s)
- Nir Grossman
- Media Lab, MIT, Cambridge, MA 02139, USA; McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA; Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA; Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, SW7 0AZ London, UK
| | - David Bono
- Department of Materials Science and Engineering, MIT, Cambridge, MA 02139, USA
| | - Nina Dedic
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA
| | - Suhasa B Kodandaramaiah
- Media Lab, MIT, Cambridge, MA 02139, USA; Department of Mechanical Engineering, University of Minnesota, Twin Cities, Minneapolis, MN 55455, USA
| | - Andrii Rudenko
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Biology, City College of the City University of York, New York, NY 10031, USA
| | - Ho-Jun Suk
- McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA; Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, MA 02139, USA
| | - Antonino M Cassara
- IT'IS Foundation for Research on Information Technologies in Society, 8004 Zurich, Switzerland
| | - Esra Neufeld
- IT'IS Foundation for Research on Information Technologies in Society, 8004 Zurich, Switzerland
| | - Niels Kuster
- IT'IS Foundation for Research on Information Technologies in Society, 8004 Zurich, Switzerland; Swiss Federal Institute of Technology (ETHZ), 8092 Zurich, Switzerland
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Broad Institute of Harvard University and MIT, Cambridge, MA 02142, USA
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Edward S Boyden
- Media Lab, MIT, Cambridge, MA 02139, USA; McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA; Broad Institute of Harvard University and MIT, Cambridge, MA 02142, USA; Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Center for Neurobiological Engineering, MIT, Cambridge, MA 02139, USA.
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26
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Wu 吴秋雨 Q, Kolb I, Callahan BM, Su Z, Stoy W, Kodandaramaiah SB, Neve R, Zeng H, Boyden ES, Forest CR, Chubykin AA. Integration of autopatching with automated pipette and cell detection in vitro. J Neurophysiol 2016; 116:1564-1578. [PMID: 27385800 DOI: 10.1152/jn.00386.2016] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 07/04/2016] [Indexed: 11/22/2022] Open
Abstract
Patch clamp is the main technique for measuring electrical properties of individual cells. Since its discovery in 1976 by Neher and Sakmann, patch clamp has been instrumental in broadening our understanding of the fundamental properties of ion channels and synapses in neurons. The conventional patch-clamp method requires manual, precise positioning of a glass micropipette against the cell membrane of a visually identified target neuron. Subsequently, a tight "gigaseal" connection between the pipette and the cell membrane is established, and suction is applied to establish the whole cell patch configuration to perform electrophysiological recordings. This procedure is repeated manually for each individual cell, making it labor intensive and time consuming. In this article we describe the development of a new automatic patch-clamp system for brain slices, which integrates all steps of the patch-clamp process: image acquisition through a microscope, computer vision-based identification of a patch pipette and fluorescently labeled neurons, micromanipulator control, and automated patching. We validated our system in brain slices from wild-type and transgenic mice expressing channelrhodopsin 2 under the Thy1 promoter (line 18) or injected with a herpes simplex virus-expressing archaerhodopsin, ArchT. Our computer vision-based algorithm makes the fluorescent cell detection and targeting user independent. Compared with manual patching, our system is superior in both success rate and average trial duration. It provides more reliable trial-to-trial control of the patching process and improves reproducibility of experiments.
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Affiliation(s)
- Qiuyu Wu 吴秋雨
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana
| | - Ilya Kolb
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Brendan M Callahan
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Zhaolun Su
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana
| | - William Stoy
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Suhasa B Kodandaramaiah
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts; Department of Mechanical Engineering, University of Minnesota-Twin Cities, Minneapolis, Minnesota; and
| | - Rachael Neve
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, Washington
| | - Edward S Boyden
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Craig R Forest
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia
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27
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Baratta MV, Kodandaramaiah SB, Monahan PE, Yao J, Weber MD, Lin PA, Gisabella B, Petrossian N, Amat J, Kim K, Yang A, Forest CR, Boyden ES, Goosens KA. Stress Enables Reinforcement-Elicited Serotonergic Consolidation of Fear Memory. Biol Psychiatry 2016; 79:814-822. [PMID: 26248536 PMCID: PMC4698247 DOI: 10.1016/j.biopsych.2015.06.025] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2014] [Revised: 06/02/2015] [Accepted: 06/17/2015] [Indexed: 01/03/2023]
Abstract
BACKGROUND Prior exposure to stress is a risk factor for developing posttraumatic stress disorder (PTSD) in response to trauma, yet the mechanisms by which this occurs are unclear. Using a rodent model of stress-based susceptibility to PTSD, we investigated the role of serotonin in this phenomenon. METHODS Adult mice were exposed to repeated immobilization stress or handling, and the role of serotonin in subsequent fear learning was assessed using pharmacologic manipulation and western blot detection of serotonin receptors, measurements of serotonin, high-speed optogenetic silencing, and behavior. RESULTS Both dorsal raphe serotonergic activity during aversive reinforcement and amygdala serotonin 2C receptor (5-HT2CR) activity during memory consolidation were necessary for stress enhancement of fear memory, but neither process affected fear memory in unstressed mice. Additionally, prior stress increased amygdala sensitivity to serotonin by promoting surface expression of 5-HT2CR without affecting tissue levels of serotonin in the amygdala. We also showed that the serotonin that drives stress enhancement of associative cued fear memory can arise from paired or unpaired footshock, an effect not predicted by theoretical models of associative learning. CONCLUSIONS Stress bolsters the consequences of aversive reinforcement, not by simply enhancing the neurobiological signals used to encode fear in unstressed animals, but rather by engaging distinct mechanistic pathways. These results reveal that predictions from classical associative learning models do not always hold for stressed animals and suggest that 5-HT2CR blockade may represent a promising therapeutic target for psychiatric disorders characterized by excessive fear responses such as that observed in PTSD.
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MESH Headings
- Amygdala/drug effects
- Amygdala/metabolism
- Animals
- Association Learning/drug effects
- Association Learning/physiology
- Conditioning, Psychological/drug effects
- Conditioning, Psychological/physiology
- Disease Models, Animal
- Dorsal Raphe Nucleus/metabolism
- Electroshock
- Fear/drug effects
- Fear/physiology
- Male
- Memory Consolidation/drug effects
- Memory Consolidation/physiology
- Mice, Inbred C57BL
- Mice, Transgenic
- Models, Neurological
- Models, Psychological
- Neurons/drug effects
- Neurons/metabolism
- Optogenetics
- Receptor, Serotonin, 5-HT2C/metabolism
- Restraint, Physical
- Serotonin/metabolism
- Serotonin 5-HT2 Receptor Antagonists/pharmacology
- Serotonin Plasma Membrane Transport Proteins/genetics
- Serotonin Plasma Membrane Transport Proteins/metabolism
- Stress Disorders, Post-Traumatic/metabolism
- Stress, Psychological/physiopathology
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Affiliation(s)
- Michael V Baratta
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts; MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Suhasa B Kodandaramaiah
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; The George W. Woodruff School of Mechanical Engineering (SBK, CRF), Georgia Institute of Technology, Atlanta, Georgia
| | - Patrick E Monahan
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Junmei Yao
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Michael D Weber
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
| | - Pei-Ann Lin
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Barbara Gisabella
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Natalie Petrossian
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Jose Amat
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado
| | - Kyungman Kim
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Aimei Yang
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Craig R Forest
- The George W. Woodruff School of Mechanical Engineering (SBK, CRF), Georgia Institute of Technology, Atlanta, Georgia
| | - Edward S Boyden
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts; MIT Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Ki A Goosens
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts.
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28
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Kodandaramaiah SB, Holst GL, Wickersham IR, Singer AC, Franzesi GT, McKinnon ML, Forest CR, Boyden ES. Assembly and operation of the autopatcher for automated intracellular neural recording in vivo. Nat Protoc 2016; 11:634-54. [PMID: 26938115 DOI: 10.1038/nprot.2016.007] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Whole-cell patch clamping in vivo is an important neuroscience technique that uniquely provides access to both suprathreshold spiking and subthreshold synaptic events of single neurons in the brain. This article describes how to set up and use the autopatcher, which is a robot for automatically obtaining high-yield and high-quality whole-cell patch clamp recordings in vivo. By following this protocol, a functional experimental rig for automated whole-cell patch clamping can be set up in 1 week. High-quality surgical preparation of mice takes ∼1 h, and each autopatching experiment can be carried out over periods lasting several hours. Autopatching should enable in vivo intracellular investigations to be accessible by a substantial number of neuroscience laboratories, and it enables labs that are already doing in vivo patch clamping to scale up their efforts by reducing training time for new lab members and increasing experimental durations by handling mentally intensive tasks automatically.
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Affiliation(s)
- Suhasa B Kodandaramaiah
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Departments of Biological Engineering and Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts, USA
| | - Gregory L Holst
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Ian R Wickersham
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Departments of Biological Engineering and Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts, USA
| | - Annabelle C Singer
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Departments of Biological Engineering and Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts, USA
| | | | - Michael L McKinnon
- Department of Physiology, School of Medicine, Emory University, Atlanta, Georgia, USA
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Edward S Boyden
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Departments of Biological Engineering and Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts, USA
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29
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Harrison RR, Kolb I, Kodandaramaiah SB, Chubykin AA, Yang A, Bear MF, Boyden ES, Forest CR. Microchip amplifier for in vitro, in vivo, and automated whole cell patch-clamp recording. J Neurophysiol 2014; 113:1275-82. [PMID: 25429119 DOI: 10.1152/jn.00629.2014] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Patch clamping is a gold-standard electrophysiology technique that has the temporal resolution and signal-to-noise ratio capable of reporting single ion channel currents, as well as electrical activity of excitable single cells. Despite its usefulness and decades of development, the amplifiers required for patch clamping are expensive and bulky. This has limited the scalability and throughput of patch clamping for single-ion channel and single-cell analyses. In this work, we have developed a custom patch-clamp amplifier microchip that can be fabricated using standard commercial silicon processes capable of performing both voltage- and current-clamp measurements. A key innovation is the use of nonlinear feedback elements in the voltage-clamp amplifier circuit to convert measured currents into logarithmically encoded voltages, thereby eliminating the need for large high-valued resistors, a factor that has limited previous attempts at integration. Benchtop characterization of the chip shows low levels of current noise [1.1 pA root mean square (rms) over 5 kHz] during voltage-clamp measurements and low levels of voltage noise (8.2 μV rms over 10 kHz) during current-clamp measurements. We demonstrate the ability of the chip to perform both current- and voltage-clamp measurement in vitro in HEK293FT cells and cultured neurons. We also demonstrate its ability to perform in vivo recordings as part of a robotic patch-clamping system. The performance of the patch-clamp amplifier microchip compares favorably with much larger commercial instrumentation, enabling benchtop commoditization, miniaturization, and scalable patch-clamp instrumentation.
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Affiliation(s)
| | - Ilya Kolb
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Suhasa B Kodandaramaiah
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; McGovern Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | | | - Aimei Yang
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Mark F Bear
- Howard Hughes Medical Institute, The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts; and
| | - Edward S Boyden
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts; McGovern Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia
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Chuong AS, Miri ML, Busskamp V, Matthews GAC, Acker LC, Sørensen AT, Young A, Klapoetke NC, Henninger MA, Kodandaramaiah SB, Ogawa M, Ramanlal SB, Bandler RC, Allen BD, Forest CR, Chow BY, Han X, Lin Y, Tye KM, Roska B, Cardin JA, Boyden ES. Noninvasive optical inhibition with a red-shifted microbial rhodopsin. Nat Neurosci 2014; 17:1123-9. [PMID: 24997763 PMCID: PMC4184214 DOI: 10.1038/nn.3752] [Citation(s) in RCA: 346] [Impact Index Per Article: 34.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2014] [Accepted: 06/01/2014] [Indexed: 12/11/2022]
Abstract
Optogenetic inhibition of the electrical activity of neurons enables the causal assessment of their contributions to brain functions. Red light penetrates deeper into tissue than other visible wavelengths. We present a red-shifted cruxhalorhodopsin, Jaws, derived from Haloarcula (Halobacterium) salinarum (strain Shark) and engineered to result in red light-induced photocurrents three times those of earlier silencers. Jaws exhibits robust inhibition of sensory-evoked neural activity in the cortex and results in strong light responses when used in retinas of retinitis pigmentosa model mice. We also demonstrate that Jaws can noninvasively mediate transcranial optical inhibition of neurons deep in the brains of awake mice. The noninvasive optogenetic inhibition opened up by Jaws enables a variety of important neuroscience experiments and offers a powerful general-use chloride pump for basic and applied neuroscience.
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Affiliation(s)
- Amy S Chuong
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mitra L Miri
- 1] Department of Neurobiology, Yale School of Medicine, Yale University, New Haven, Connecticut, USA. [2]
| | - Volker Busskamp
- 1] Neural Circuit Laboratories, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. [2] Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA. [3]
| | - Gillian A C Matthews
- 1] Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2]
| | - Leah C Acker
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [4]
| | - Andreas T Sørensen
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Andrew Young
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Nathan C Klapoetke
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mike A Henninger
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Suhasa B Kodandaramaiah
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [4] George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Masaaki Ogawa
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Shreshtha B Ramanlal
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Rachel C Bandler
- Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Brian D Allen
- Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Brian Y Chow
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Yingxi Lin
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kay M Tye
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Botond Roska
- Neural Circuit Laboratories, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Jessica A Cardin
- 1] Department of Neurobiology, Yale School of Medicine, Yale University, New Haven, Connecticut, USA. [2] Kavli Institute for Neuroscience, Yale University, New Haven, Connecticut, USA
| | - Edward S Boyden
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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Abstract
Robotic and automation technologies have played a huge role in in vitro biological science, having proved critical for scientific endeavors such as genome sequencing and high-throughput screening. Robotic and automation strategies are beginning to play a greater role in in vivo and in situ sciences, especially when it comes to the difficult in vivo experiments required for understanding the neural mechanisms of behavior and disease. In this perspective, we discuss the prospects for robotics and automation to influence neuroscientific and intact-system biology fields. We discuss how robotic innovations might be created to open up new frontiers in basic and applied neuroscience and present a concrete example with our recent automation of in vivo whole-cell patch clamp electrophysiology of neurons in the living mouse brain.
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Affiliation(s)
- Suhasa B. Kodandaramaiah
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia
- MIT Media Lab, McGovern Institute, Department of Biological Engineering, and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Edward S. Boyden
- MIT Media Lab, McGovern Institute, Department of Biological Engineering, and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Craig R. Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia
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Kolb I, Holst G, Goldstein B, Kodandaramaiah SB, Boyden ES, Culurciello E, Forest CR. Automated, in-vivo, whole-cell electrophysiology using an integrated patch-clamp amplifier. BMC Neurosci 2013. [PMCID: PMC3704364 DOI: 10.1186/1471-2202-14-s1-p131] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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