Automatic tracking of cells for video microscopy in patch clamp experiments

Detalhes bibliográficos
Autor(a) principal: Peixoto, Helton M
Data de Publicação: 2014
Outros Autores: Munguba, Hermany, Cruz, Rossana MS, Guerreiro, Ana MG, Leão, Richardson Naves
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRN
Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/23218
Resumo: Background Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons. Methods Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness). Results We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy. Conclusion The techniques of digital image processing used in this work are an important addition to the set of microscopy tools used in modern electrophysiology, specially in experiments with neuron cultures and brain slices.
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spelling Peixoto, Helton MMunguba, HermanyCruz, Rossana MSGuerreiro, Ana MGLeão, Richardson Naves2017-05-30T12:46:34Z2017-05-30T12:46:34Z2014-06-20https://repositorio.ufrn.br/jspui/handle/123456789/2321810.1186/1475-925X-13-78engNeuronsFluorescent proteinsPhotodamagePatch-clampImage trackingMask overlayAutomatic tracking of cells for video microscopy in patch clamp experimentsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleBackground Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons. Methods Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness). Results We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy. Conclusion The techniques of digital image processing used in this work are an important addition to the set of microscopy tools used in modern electrophysiology, specially in experiments with neuron cultures and brain slices.info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.ufrn.br/bitstream/123456789/23218/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52ORIGINALAutomatic tracking of cells for video microscopy in patch clamp experiments.pdfAutomatic tracking of cells for video microscopy in patch clamp experiments.pdfRichardsonLeao_ICe_Automatic tracking of cells_2014application/pdf2229387https://repositorio.ufrn.br/bitstream/123456789/23218/1/Automatic%20tracking%20of%20cells%20for%20video%20microscopy%20in%20patch%20clamp%20experiments.pdfd7b15c45b51af0c7455caf565ffa9875MD51TEXTAutomatic tracking of cells for video microscopy in patch clamp experiments.pdf.txtAutomatic tracking of cells for video microscopy in patch clamp experiments.pdf.txtExtracted texttext/plain40629https://repositorio.ufrn.br/bitstream/123456789/23218/5/Automatic%20tracking%20of%20cells%20for%20video%20microscopy%20in%20patch%20clamp%20experiments.pdf.txte101ce92b74b018e59edb919b4781e60MD55THUMBNAILAutomatic tracking of cells for video microscopy in patch clamp experiments.pdf.jpgAutomatic tracking of cells for video microscopy in patch clamp experiments.pdf.jpgIM Thumbnailimage/jpeg9203https://repositorio.ufrn.br/bitstream/123456789/23218/6/Automatic%20tracking%20of%20cells%20for%20video%20microscopy%20in%20patch%20clamp%20experiments.pdf.jpg61689e17322220e76d591027821e3d3fMD56123456789/232182021-07-09 18:13:51.493oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2021-07-09T21:13:51Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.pt_BR.fl_str_mv Automatic tracking of cells for video microscopy in patch clamp experiments
title Automatic tracking of cells for video microscopy in patch clamp experiments
spellingShingle Automatic tracking of cells for video microscopy in patch clamp experiments
Peixoto, Helton M
Neurons
Fluorescent proteins
Photodamage
Patch-clamp
Image tracking
Mask overlay
title_short Automatic tracking of cells for video microscopy in patch clamp experiments
title_full Automatic tracking of cells for video microscopy in patch clamp experiments
title_fullStr Automatic tracking of cells for video microscopy in patch clamp experiments
title_full_unstemmed Automatic tracking of cells for video microscopy in patch clamp experiments
title_sort Automatic tracking of cells for video microscopy in patch clamp experiments
author Peixoto, Helton M
author_facet Peixoto, Helton M
Munguba, Hermany
Cruz, Rossana MS
Guerreiro, Ana MG
Leão, Richardson Naves
author_role author
author2 Munguba, Hermany
Cruz, Rossana MS
Guerreiro, Ana MG
Leão, Richardson Naves
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Peixoto, Helton M
Munguba, Hermany
Cruz, Rossana MS
Guerreiro, Ana MG
Leão, Richardson Naves
dc.subject.por.fl_str_mv Neurons
Fluorescent proteins
Photodamage
Patch-clamp
Image tracking
Mask overlay
topic Neurons
Fluorescent proteins
Photodamage
Patch-clamp
Image tracking
Mask overlay
description Background Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons. Methods Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness). Results We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy. Conclusion The techniques of digital image processing used in this work are an important addition to the set of microscopy tools used in modern electrophysiology, specially in experiments with neuron cultures and brain slices.
publishDate 2014
dc.date.issued.fl_str_mv 2014-06-20
dc.date.accessioned.fl_str_mv 2017-05-30T12:46:34Z
dc.date.available.fl_str_mv 2017-05-30T12:46:34Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv https://repositorio.ufrn.br/jspui/handle/123456789/23218
dc.identifier.doi.none.fl_str_mv 10.1186/1475-925X-13-78
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dc.language.iso.fl_str_mv eng
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