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Automatic tracking of cells for video microscopy in patch clamp experiments
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084571/ https://www.ncbi.nlm.nih.gov/pubmed/24946774 http://dx.doi.org/10.1186/1475-925X-13-78 |
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author | Peixoto, Helton M Munguba, Hermany Cruz, Rossana MS Guerreiro, Ana MG Leao, Richardson N |
author_facet | Peixoto, Helton M Munguba, Hermany Cruz, Rossana MS Guerreiro, Ana MG Leao, Richardson N |
author_sort | Peixoto, Helton M |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-4084571 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40845712014-07-18 Automatic tracking of cells for video microscopy in patch clamp experiments Peixoto, Helton M Munguba, Hermany Cruz, Rossana MS Guerreiro, Ana MG Leao, Richardson N Biomed Eng Online Research 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. BioMed Central 2014-06-20 /pmc/articles/PMC4084571/ /pubmed/24946774 http://dx.doi.org/10.1186/1475-925X-13-78 Text en Copyright © 2014 Peixoto et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Peixoto, Helton M Munguba, Hermany Cruz, Rossana MS Guerreiro, Ana MG Leao, Richardson N Automatic tracking of cells for video microscopy in patch clamp experiments |
title | 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_short | Automatic tracking of cells for video microscopy in patch clamp experiments |
title_sort | automatic tracking of cells for video microscopy in patch clamp experiments |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084571/ https://www.ncbi.nlm.nih.gov/pubmed/24946774 http://dx.doi.org/10.1186/1475-925X-13-78 |
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