Name: automated analysis of dynamic ca2+ signals in image sequences
Uploaded: 2014-06-16T15:00:00
Description: Watch this Scientific Journal Video about Automated Analysis of Dynamic Ca2+ Signals in Image Sequences at JoVE.com

This work was supported in part by National Institutes of Health Grants HL-085887, HL-092992, S10RR027535, and MOP-93676.

1. Vessel Dissection and Imaging
<ol>
	<li>Harvest tissue from domestic juvenile pigs as described in Martens et al27. Place harvested swine right ventricles into a polydimethylsiloxane (PDMS) bottom dissection dish containing HEPES buffered physiological saline solution (PSS).
	<ol>
		<li>With the aid of a stereomicroscope, dissect and remove a segment of the left anterior descending coronary artery (~8 mm length, 0.5 mm diameter) from surrounding tissue using forceps and spring scissors by removin...

<ol>
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Decoding complex Ca2+ signals at the cellular and multicellular level will require rigorous experimental and analytical approaches. Here, an approach is described in which time resolved confocal image sequences of Ca2+ dependent fluorescence are subjected to an automated analysis that identifies and quantifies statistically relevant Ca2+ signals within intact cellular fields In the specific case presented, an artery segment was isolated from pig heart, pinned opened to expose the endothel...

Ca2+ is a ubiquitous second messenger signaling molecule and cytosolic Ca2+ levels are highly regulated. Intracellular Ca2+ signals are complex and include isolated transients, oscillations, and propagating waves1-4. Spatial and temporal control of Ca2+ is thought to underlie physiological signal specificity, and therefore the analysis of Ca2+ signal patterns is of considerable interest to investigators in multiple fields5.
Ca2+ indicator dyes such as Fluo-4 and Fura-2 are commonly employed to measure intracellular Ca2+ signals with fluorescence microscopy5-12. Typically, temporal Ca2+ signals are evaluated as time-dependent changes in mean fluorescence within a user-defined area, or region of interest (ROI)5,6,13-16. Currently, manual ROI analysis is both time consuming and labor intensive because it requires users to identify many ROIs and perform repetitive computations17-19. These techniques may also be subject to considerable user error, including introduction of artificial signal modes and exclusion of low amplitude or diffuse signals18,20.
Automated ROI detection algorithms have previously been implemented using a variety of statistical approaches to determine optimal ROI placement, but they have generally been limited to analysis of line scan or pseudo-line scan images, which restricts analysis to a single spatial dimension in time17,19-22. Additionally, many existing algorithms are not adequate to encompass the diversity of Ca2+ release events which range from periodic, localized transients to propagating waves23,24. Comprehensive evaluation of physiological Ca2+ signals is often further complicated by the presence of significant image artifact that confounds signal to noise discrimination in many experimental systems.
Previously, an automated ROI detection algorithm solution to Ca2+ signal transient detection, implemented as a plugin for NIH ImageJ software (National Institutes of Health, Bethesda, MD), was developed and validated25,26. This algorithm, called LC_Pro, was designed to identify and analyze ROIs encompassing Ca2+ signal transients in two-dimensional time lapse image sequences. Here a practical experimental protocol and representative demonstration of an application of the algorithm in porcine coronary artery endothelium is provided, with additional postprocessing using the open source statistical processing software R to generate usable graphical output.

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			<td height="21" style="height:21px;width:216px;">dissection dish</td>
			<td style="width:71px;">Fisher Sci</td>
			<td style="width:119px;">#08-772-70</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">polydimethylsiloxane (PDMS)</td>
			<td style="width:71px;">Fisher Sci</td>
			<td style="width:119px;">#NC9644388</td>
			<td>elastomer kit, must be molded into dishes</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">HEPES-buffered PSS</td>
			<td style="width:71px;">Sigma</td>
			<td style="width:119px;">#H3375-250G</td>
			<td>HEPES acid</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">stereomicroscope</td>
			<td style="width:71px;">Nikon Inst.</td>
			<td style="width:119px;">#MNA42000</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">forceps</td>
			<td style="width:71px;">Fine Science Tools</td>
			<td style="width:119px;">#11223-20</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">spring scissors</td>
			<td style="width:71px;">Fine Science Tools</td>
			<td style="width:119px;">15003-08</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">tungsten wire</td>
			<td style="width:71px;">Scientific Inst Svcs</td>
			<td style="width:119px;">#406</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Fluo-4 AM</td>
			<td style="width:71px;">Life Tech.</td>
			<td style="width:119px;">#F-14201</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">pluronic F-127</td>
			<td style="width:71px;">Life Tech.</td>
			<td style="width:119px;">#P3000MP</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">metal pins</td>
			<td style="width:71px;">Fine Science Tools</td>
			<td style="width:119px;">#26002-10</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">cover-glass bottom chamber</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
			<td>Custom designed</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">spinning disc confocal microscope</td>
			<td style="width:71px;">Perkin Elmer</td>
			<td style="width:119px;">RS-3</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">imageJ software</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
			<td><a href="http://rsbweb.nih.gov/ij/download.html">download at: http://rsbweb.nih.gov/ij/download.html</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">LC_Pro plugin for imageJ</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
			<td><a href="http://rsbweb.nih.gov/ij/plugins/lc-pro/index.html">download at: http://rsbweb.nih.gov/ij/plugins/lc-pro/index.html</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">R software</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
			<td><a href="http://www.r-project.org/">download at: http://www.r-project.org/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">R traceplot script</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
			<td><a href="https://docs.google.com/file/d/0B-PSp1D9e2fjV3NIcGppUzkxdEk/edit?usp=sharing">download at: https://docs.google.com/file/d/0B-PSp1D9e2fjV3NIcGppUzkxdEk/edit?usp=sharing</a></td>
		</tr>
	</tbody>
</table>

automated analysis of dynamic ca2+ signals in image sequences

Intracellular Ca2+ signals are commonly studied with fluorescent Ca2+ indicator dyes and microscopy techniques. However, quantitative analysis of Ca2+ imaging data is time consuming and subject to bias. Automated signal analysis algorithms based on region of interest (ROI) detection have been implemented for one-dimensional line scan measurements, but there is no current algorithm which integrates optimized identification and analysis of ROIs in two-dimensional image sequences. Here an algorithm for rapid acquisition and analysis of ROIs in image sequences is described. It utilizes ellipses fit to noise filtered signals in order to determine optimal ROI placement, and computes Ca2+ signal parameters of amplitude, duration and spatial spread. This algorithm was implemented as a freely available plugin for ImageJ (NIH) software. Together with analysis scripts written for the open source statistical processing software R, this approach provides a high-capacity pipeline for performing quick statistical analysis of experimental output. The authors suggest that use of this analysis protocol will lead to a more complete and unbiased characterization of physiologic Ca2+ signaling.

A custom algorithm, LC_Pro, was developed and implemented in order to perform automated analysis of Ca2+ dynamics on confocal image sequences. As depicted in Figure 1, the algorithm utilizes sequential processing modules that A) detect and track sites of dynamic Ca2+ change above statistical (p &#60; 0.01) noise, B) define regions of interest (ROI) automatically at active site centers, and C) calculate average fluorescence intensities at ROIs to determine specific event parameters. ...

Watch this Scientific Journal Video about Automated Analysis of Dynamic Ca2+ Signals in Image Sequences at JoVE.com

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Here a novel region of interest analysis protocol based on sorting best-fit ellipses assigned to regions of positive signal within two-dimensional time lapse image sequences is demonstrated. This algorithm may enable investigators to comprehensively analyze physiological Ca2+ signals with minimal user input and bias.

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Intracellular Ca2+ signals are commonly studied with fluorescent Ca2+ indicator dyes and microscopy techniques. However, quantitative analysis of Ca2+ ...

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