We would like to thank Dr Hamish Campbell and Prof Antony Braithwaite for their help in developing the transduced MCF-7-LeGO cell lines. We would like to acknowledge our funding support by the Bloomfield Group Foundation through the Hunter Medical Research Institute. B.C.M is supported by an APA scholarship through the University of Newcastle and the MM Sawyer Scholarship through the Hunter Medical Research Institute.

1. Preparing Cells for Proliferation Assays
Note: Prepare the two cell lines in the same manner and seed in the same format for each method to be analyzed.
<ol>
	<li>Grow MCF-7-LeGO and MCF-7-&#916;40p53 7 cells to 75-80% confluence in T 75 cm2 tissue culture flasks using phenol-red free Dulbecco&#39;s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 200 mM L-glutamine, 2 &#181;g/ml insulin and 1 &#181;g/ml Puromycin at 37 &#176;C with 5% CO2. Handle cells in a sterile biosafety cabinet class II. 
	Note: The amount of time it takes to grow the cells to confluence varies depending on the seeding dilution. In preparation for plating the cells for the proliferation assays, seed the cells at a 1:3 dilution in supplemented DMEM and maintain in normal growth conditions for 3 days until 75-80% confluency.</li>
	<li>To remove the cells from the flask, pour off the media into a waste container. Immediately wash the cell layer with 2 ml of pre-warmed 2x trypsin. Aspirate trypsin. Add a further 2 ml of pre-warmed trypsin to the cell layer and place in an incubator for 5 min at 37 &#176;C with 5% CO2.
	<ol>
		<li>Once the cells detach, wash the cells with 10 ml warmed fresh supplemented DMEM. Transfer the cell suspension to a sterile 15 ml tube and centrifuge at 491 x g for 5 min at RT. Carefully aspirate and dispose of the supernatant.</li>
	</ol>
	</li>
	<li>Resuspend the cell pellet in 5 ml of fresh supplemented DMEM. Perform a cell count to determine the correct density to seed the cells in 96-well plates.
	<ol>
		<li>Dilute 100 &#181;l of the cell suspension in 900 &#181;l 1x Dulbecco&#39;s Phosphate Buffered Saline (DPBS). Place a new 60 &#181;m sensor onto the automated cell counter. Hold down the plunger and submerge the sensor in the diluted cell suspension. Slowly release the plunger on the cell counter. Remove the sensor from the cell counter when completed. 
		Note: The cell count will be displayed on the cell counter in cells/ml.</li>
	</ol>
	</li>
	<li>Seed cells at a final volume of 100 &#181;l (in DMEM) in a 96-well plate at ~20% confluency to allow room for cell growth and measurement of proliferation over 3-5 days (see Table 1). Seed all cell lines in triplicate. 
	Note: For this experiment, three different cell densities were assessed to determine the optimal cell density. The required cell numbers are summarized in Table 1. Seed cells at a lower density if measurement of more long-term growth is required.
	<ol>
		<li>For the hemocytometer and luminescence-based assays, prepare one plate per time point (i.e. 4 plates per assay). For the cell imager assay, prepare only one plate for the duration of the experiment.</li>
	</ol>
	</li>
	<li>Maintain cells at 37 &#176;C with 5% CO2 for 24 hr.</li>
</ol>
2. Determining Cell Count Using a Hemocytometer
<ol>
	<li>Pre-warm both medium and trypsin to 37 &#176;C in a cell culture incubator, oven or water bath. Aspirate media from cells into a waste container, wash once with 30 &#181;l of 2x trypsin, and aspirate the trypsin.</li>
	<li>Wash cells again with 30 &#181;l of 2x trypsin, and incubate for 5 minutes at 37 &#176;C. Gently tap edge of plate to dislodge cells from the plate. Add 50 &#181;l of supplemented DMEM and mix cells by pipetting until the cells form a single cell suspension.</li>
	<li>Prepare hemocytometer by cleaning surface and glass cover with 70% ethanol.</li>
	<li>Place the glass cover-slip over counting chambers and affix until &#39;Newton&#39;s refraction rings&#39; can be seen between the cover-slip edges and the hemocytometer. 
	Note: These indicate that the cover-slip has correctly adhered to the hemocytometer.</li>
	<li>Gently pipette 20 &#181;l of cell suspension under the cover-slip, filling the counting chamber by capillary motion. Place hemocytometer under 10x magnification of a microscope and visualize the counting chambers in the grid layout.</li>
	<li>Count cells in the 4 outer squares of the grid layout. To improve accuracy, repeat counts of additional outer squares if required, or until the count has reached 70 - 100 cells14,15.
	<ol>
		<li>Calculate cell concentration per ml as follows:Average cell count per square x dilution factor (if used) x 104</li>
	</ol>
	</li>
	<li>Repeat steps 2.1-2.8 every 24 hr for 96 hr post-seeding.</li>
</ol>
3. Determining Cell Proliferation Using a Luminescence-based Assay
Note: This is an endpoint measurement. Once the reagent is added to the cells, the plate can only be quantified once.
<ol>
	<li>Thaw luminescence reagent in a 22 &#176;C water bath for 30 min.</li>
	<li>Gently mix reagent by inverting the bottle to obtain a homogenous mix.</li>
	<li>Equilibrate one plate of seeded cells (from step 1.5) at RT for 30 min.</li>
	<li>Add 100 &#181;l of luminescence reagent to each well. Mix contents on an orbital shaker for 2 min. Allow plate to incubate for 10 min at RT.</li>
	<li>Setting up a luminescence experiment using the multi-mode plate reader software.
	<ol>
		<li>Turn on multi-mode plate reader and open the software. In the &#39;task manager&#39;, select &#39;experiments&#39; and &#39;create new&#39;.Select &#39;file&#39; from side toolbar, and under &#39;protocol&#39; tab, select &#39;procedure&#39;.</li>
		<li>Select &#39;Grenier 96 flat bottom&#39; plate type, and check the &#39;use lid&#39; box. Select &#39;read&#39; action under &#39;read method&#39; box. Select &#39;luminescence&#39; detection method. Click &#39;OK&#39;.</li>
		<li>In the read step box, select the wells to be scanned under the &#39;full plate&#39; tab, and select wells to act as blank wells.</li>
		<li>Set the filter set to empty filter (e.g., plug, Em: hole, mirror: none). Set the gain to 135, with an integration time of 0.5 sec per well and a read height of 6.5 mm. Click &#39;OK&#39; to save settings for the luminescence read.</li>
	</ol>
	</li>
	<li>Performing a Luminescent Read
	<ol>
		<li>Eject plate holder by selecting &#39;instrument control&#39; tab and click on &#39;plate out&#39;.Place 96-well plate onto the plate holder, ensuring the lid is on. Close the plate holder by clicking on &#39;plate in&#39; under &#39;instrument control&#39; tab. Click on &#39;read now&#39; from toolbar to perform luminescent read.</li>
		<li>Export the relative luminescent unit (RLU) measurements for each well to a spreadsheet for further analysis.</li>
	</ol>
	</li>
	<li>Repeat steps 3.1-3.6 to record proliferation every 24 hr up to 96 hr after seeding cells.</li>
</ol>
4. Determining Cell Count Using a Cell Imager
<ol>
	<li>Setting up a cell imaging experiment using the multi-mode cell imager software
	<ol>
		<li>Turn on multi-mode cell imager and open the software.</li>
		<li>In the &#39;task manager&#39;, select &#39;experiments&#39; tab and &#39;create new&#39;.On the &#39;file&#39; toolbar, click on &#39;protocol&#39; tab and open &#39;procedure&#39; tab.Select &#39;set temperature&#39; action. Set incubator to &#39;on&#39; and set temperature to 37 &#176;C and check &#39;preheat&#39; before continuing with next step&#39; box. Click &#39;OK&#39; to save settings.</li>
		<li>Select &#39;read&#39; action. Click on &#39;image&#39; detection method, select &#39;endpoint/kinetic&#39; read type and &#39;filters&#39; optics type. Click &#39;OK&#39;.Click on &#39;full plate&#39; tab and select wells on the plate to be imaged. Click &#39;OK&#39; to save the settings.</li>
		<li>Select the 2.5X objective from the drop down &#39;objectives&#39; options. Under &#39;channels&#39; tab, select two channels: GFP 469, 525 and Bright Field. Check &#39;auto&#39; exposure for both channels and select the auto-exposure well.</li>
		<li>To determine auto focus settings, select &#39;auto-focus&#39; and click on &#39;options&#39;. For the auto-focus options, select the &#39;scan and then auto focus&#39; method. Click &#39;OK&#39; to save settings.</li>
		<li>Set the horizontal and vertical offset from center of well (&#181;m) to 0.Select to scan multiple images per well in a 3 x 2 montage, with horizontal spacing (&#181;m) = 2,881 and vertical spacing (&#181;m) = 2,127. Click &#39;OK&#39; to save procedure settings. 
		Note: See Table 2 for read parameters.</li>
	</ol>
	</li>
	<li>Performing Read Experiment on Selected Plate
	<ol>
		<li>Click on the &#39;instrument control&#39; tab and select the &#39;plate out&#39; function.Place 96-well plate in plate holder, ensuring the lid is on. Under the &#39;instrument control&#39; tab, select the &#39;plate in&#39; function. Select &#39;read now&#39; from plate tab. Repeat read every 24 hr up to 96 hr post-seeding.</li>
	</ol>
	</li>
	<li>Analysis of Cell Count Using the Cell Imager Software.
	<ol>
		<li>To analyze an image, click on the &#39;data&#39; tab on the imaged plate, select &#39;picture [GFP 469, 525 + Bright field]&#39;. Double click on an imaged well.</li>
		<li>Click on a loaded image. Select &#39;analyze&#39; and select a single image of the montage to be analyzed. Click &#39;OK&#39;.Check the &#39;GFP&#39; channel only, and set parameters as outlined in Table 3. Click &#39;START&#39; to apply parameters to the imaged cells.</li>
		<li>Observe the cell counting mask placed over the imaged cells, which is used to determine the cell count per image. Click &#39;apply changes&#39; and maintain these settings for each plate imaged throughout the experiment.</li>
		<li>Once back at the imaged plate, click on the &#39;data&#39; drop down menu and select &#39;cell count&#39;. This will generate the total cell count per well.</li>
		<li>Export all data to a spreadsheet by clicking on the &#39;export&#39; tab for further analysis of the cell counts per well.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Lane, D. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cancer.+p53,+guardian+of+the+genome.">Cancer. p53, guardian of the genome.</a> Nature. 358 (6381), 15-16 (1992).</li><li>Olivier, M., Hollstein, M., Hainaut, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TP53+mutations+in+human+cancers:+origins,+consequences,+and+clinical+use.">TP53 mutations in human cancers: origins, consequences, and clinical use.</a> Cold Spring Harb Perspect Biol. 2 (1), a001008 (2010).</li><li>Olivier, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+clinical+value+of+somatic+TP53+gene+mutations+in+1,794+patients+with+breast+cancer.">The clinical value of somatic TP53 gene mutations in 1,794 patients with breast cancer.</a> Clin Cancer Res. 12 (4), 1157-1167 (2006).</li><li>Bourdon, J. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=p53+isoforms+can+regulate+p53+transcriptional+activity.">p53 isoforms can regulate p53 transcriptional activity.</a> Genes Dev. 19 (18), 2122-2137 (2005).</li><li>Avery-Kiejda, K. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Small+molecular+weight+variants+of+p53+are+expressed+in+human+melanoma+cells+and+are+induced+by+the+DNA-damaging+agent+cisplatin.">Small molecular weight variants of p53 are expressed in human melanoma cells and are induced by the DNA-damaging agent cisplatin.</a> Clin Cancer Res. 14 (6), 1659-1668 (2008).</li><li>Avery-Kiejda, K. A., Morten, B., Wong-Brown, M. W., Mathe, A., Scott, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+relative+mRNA+expression+of+p53+isoforms+in+breast+cancer+is+associated+with+clinical+features+and+outcome.">The relative mRNA expression of p53 isoforms in breast cancer is associated with clinical features and outcome.</a> Carcinogenesis. 35 (3), 586-596 (2014).</li><li>Weber, K., Bartsch, U., Stocking, C., Fehse, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+multicolor+panel+of+novel+lentiviral+&amp;#34;gene+ontology&amp;#34;+(LeGO)+vectors+for+functional+gene+analysis.">A multicolor panel of novel lentiviral &amp;#34;gene ontology&amp;#34; (LeGO) vectors for functional gene analysis.</a> Mol Ther. 16 (4), 698-706 (2008).</li><li>Riss, T. L., Moravec, R. A., Celis, J. 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The authors declare that they have no competing financial interests.

In this protocol three different methods of measuring cell proliferation in cultured cells were examined. Each method was capable of reproducible and accurate measurements of cell proliferation over 96 hr, and the results were comparable between each of the methods tested (Figure 2 and 3). Both the luminescence-based assay and cell imaging method produced the most robust results, showing linear increases in cell proliferation after 96 hr (Figure 2b, c). Additionally, cel...

The tumor suppressor gene, p53, is an essential regulator of a number of cellular processes, including cell cycle arrest, apoptosis and senescence1. It is responsible for maintaining genomic stability, and is therefore crucial for maintaining the balance of cell death and cell growth. Mutations in p53 are common in cancer and are the major cause of p53 inactivation leading to uncontrolled cancer cell proliferation2. Interestingly, mutations in p53 only account for approximately 25% of breast cancers3, suggesting that other mechanisms are responsible for the loss of p53 function. The recently discovered p53 isoforms have been shown to be overexpressed in a number of human cancers, and can modulate p53 function4,5. We have previously shown that the p53 isoform, &#916;40p53, is the most highly expressed isoform in breast cancer, and is significantly upregulated in breast cancer cells, when compared to normal adjacent tissue6. Following this, we stably transduced the human breast cancer cell line MCF-7 to overexpress &#916;40p53 using the LeGO-iG2-puro+ vector (GFP+)7. These cells were used to investigate if high &#916;40p53 expression increases cell proliferation rates in breast cancer cells.
There are many direct and indirect methods of measuring cell proliferation of cultured cells in vitro8,9. These can be performed either as continuous measurements over time, or as endpoint assays10. Conventional methods are still useful, such as cell counting using a hemocytometer. This assay is a low cost and direct measure of the cell number, but it does rely on large cell counts and highly skilled training to minimize error and large standard deviations from the counts. The need to perform measurements compatible with high-throughput formats has led to the development of multiwell-plate assays. These luminescence-based assays measure cell numbers based on a luminescent signal that is proportional to the metabolic activity of the cell11,12. More recently, the introduction of high content imaging platforms has allowed for new tools which monitor cell proliferation while providing quantitative and qualitative phenotypic data collection, and includes a variety of systems13. All of these methods provide avenues to measure cell growth, either by continuous measurement or endpoint assays, and each possess a range of advantages and disadvantages with regards to sensitivity, throughput of sample numbers, and cell information, all of which can be weighed accordingly depending on the research question.
This protocol describes three different methods for measuring cell proliferation in vitro, with each method utilizing different ranges of sensitivity, reproducibility and multi-well plate formats. This protocol aimed to compare the use of a hemocytometer counting chamber, a luminescence-based cell viability assay, and cell imager, in the measurement of cell proliferation over a 96 hour time course. To do this, the growth of vector-transduced cells (MCF-7-LeGO) was compared to cells transduced to overexpress &#916;40p53 (MCF-7-&#916;40p53), using three different cell densities. Cell proliferation was measured every 24 hr for up to 96 hr. Each method was found to have its own advantages and disadvantages, and depending on the aim of the experiment, each still is a valuable method for providing information on the rate of proliferation.

<table border="0" cellpadding="0" cellspacing="0" width="1031">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Dulbecco&#39;s Modified Eagle Medium, no phenol-red</td>
			<td style="width:99px;">ThermoFisher Scientific</td>
			<td style="width:119px;">21063-045</td>
			<td style="width:597px;">Supplemented with 10% FBS, 200mM L-glutamine, 2&#181;g/ml insulin and 1&#181;g/ml puromycin</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">L-glutamine solution (100x)</td>
			<td style="width:99px;">ThermoFisher Scientific</td>
			<td style="width:119px;">25030-081</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Insulin solution human</td>
			<td style="width:99px;">Sigma-Aldrich</td>
			<td style="width:119px;">I9278-5ML</td>
			<td style="width:597px;"></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Fetal bovine serum (FBS)</td>
			<td style="width:99px;">Bovogen Biologicals</td>
			<td style="width:119px;">SFBS-F-500ml</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Puromycin dihydrochloride</td>
			<td style="width:99px;">Sigma-Aldrich</td>
			<td style="width:119px;">P9620-10ML</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">0.5% trypsin-EDTA solution (10x)</td>
			<td style="width:99px;">ThermoFisher Scientific</td>
			<td style="width:119px;">15400-054</td>
			<td>Dilute to 2x in DPBS</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Dulbecco&#39;s Phosphate Buffered Saline (DPBS) (1x)</td>
			<td style="width:99px;">ThermoFisher Scientific</td>
			<td style="width:119px;">30028-02</td>
			<td></td>
		</tr>
		<tr height="45">
			<td height="45" style="height:45px;width:216px;">Tissue culture flask, 75cm2 growth area</td>
			<td style="width:99px;">Greiner Bio-One</td>
			<td align="right" style="width:119px;">658175</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Scepter 2.0 Cell Counter</td>
			<td style="width:99px;">Merck Millipore</td>
			<td style="width:119px;"></td>
			<td>Automated cell counter</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">96 well multiwell plate, flat bottom</td>
			<td style="width:99px;">Nunc</td>
			<td align="right" style="width:119px;">167008</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Improved Neubauer Hemocytometer</td>
			<td style="width:99px;">BOECO Germany</td>
			<td style="width:119px;">BOE 01</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Olympus IX51 inverted microscope</td>
			<td style="width:99px;">Olympus</td>
			<td style="width:119px;">IX51</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">CellTiter-Glo 2.0 Assay</td>
			<td style="width:99px;">Promega</td>
			<td style="width:119px;">G9242</td>
			<td>Luminescence-based assay</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Cytation 3 Cell Imaging Multi-Mode Reader</td>
			<td style="width:99px;">BioTek</td>
			<td style="width:119px;"></td>
			<td>Plate reader for luminescence, fluorescence and brightfield cell imaging</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Gen5 Data Analysis Software</td>
			<td style="width:99px;">BioTek</td>
			<td style="width:119px;">GEN5</td>
			<td></td>
		</tr>
	</tbody>
</table>

comparison of three different methods for determining cell proliferation in breast cancer cell lines

Measuring cell proliferation can be performed by a number of different methods, each with varying levels of sensitivity, reproducibility and compatibility with high-throughput formatting. This protocol describes the use of three different methods for measuring cell proliferation in vitro including conventional hemocytometer counting chamber, a luminescence-based assay that utilizes the change in the metabolic activity of viable cells as a measure of the relative number of cells, and a multi-mode cell imager that measures cell number using a counting algorithm. Each method presents its own advantages and disadvantages for the measurement of cell proliferation, including time, cost and high-throughput compatibility. This protocol demonstrates that each method could accurately measure cell proliferation over time, and was sensitive to detect growth at differing cellular densities. Additionally, measurement of cell proliferation using a cell imager was able to provide further information such as morphology, confluence and allowed for a continual monitoring of cell proliferation over time. In conclusion, each method is capable of measuring cell proliferation, but the chosen method is user-dependent.

To study different methods of measuring the proliferation of cultured cells, the cell proliferation of MCF-7-&#916;40p53 transduced cells was compared to the non-transduced MCF-7-LeGO breast cancer cell line. The three methods that were compared&#160;&#8211; the conventional hemocytometer method, cell viability luminescence assay, and cell imaging analysis- are outlined in the schematic diagram (Figure 1). Each method has advantages and disadvantages to accurately measure...

Watch this Scientific Journal Video about Comparison of Three Different Methods for Determining Cell Proliferation in Breast Cancer Cell Lines at JoVE.com

Comparison of Three Different Methods for Determining Cell Proliferation in Breast Cancer Cell Lines

This protocol describes the use of three different methods for analyzing cell proliferation in breast cancer cell lines. This includes the use of conventional cell counting, luminescence-based cell viability, and cell counting through the use of a cell imager. Each offers advantages for the reproducible measurement of cell proliferation.

Measuring cell proliferation can be performed by a number of different methods, each with varying levels of sensitivity, reproducibility and compatibility ...

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Biology

19.4K Views.  Hunter Medical Research Institute. This protocol describes the use of three different methods for analyzing cell proliferation in breast cancer cell lines. This includes the use of conventional cell counting, luminescence-based cell viability, and cell counting through the use of a cell imager. Each offers advantages for the reproducible measurement of cell proliferation.

Video: Comparison of Three Different Methods for Determining Cell Proliferation in Breast Cancer Cell Lines

Determining Cell Number During Cell Culture using the Scepter Cell Counter

Counting cells is often a necessary but tedious step for in vitro cell culture. Consistent cell concentrations ensure experimental reproducibility and accuracy. Cell counts are important for monitoring cell health and proliferation rate, assessing immortalization or transformation, seeding cells for subsequent experiments, transfection or infection, and preparing for cell-based assays. It is important that cell counts be accurate, consistent, and fast, particularly for quantitative measurements of cellular responses.
Despite this need for speed and accuracy in cell counting, 71% of 400 researchers surveyed1 who count cells using a hemocytometer. While hemocytometry is inexpensive, it is laborious and subject to user bias and misuse, which results in inaccurate counts. Hemocytometers are made of special optical glass on which cell suspensions are loaded in specified volumes and counted under a microscope. Sources of errors in hemocytometry include: uneven cell distribution in the sample, too many or too few cells in the sample, subjective decisions as to whether a given cell falls within the defined counting area, contamination of the hemocytometer, user-to-user variation, and variation of hemocytometer filling rate2.
To alleviate the tedium associated with manual counting, 29% of researchers count cells using automated cell counting devices; these include vision-based counters, systems that detect cells using the Coulter principle, or flow cytometry1. For most researchers, the main barrier to using an automated system is the price associated with these large benchtop instruments1.
The Scepter cell counter is an automated handheld device that offers the automation and accuracy of Coulter counting at a relatively low cost. The system employs the Coulter principle of impedance-based particle detection3 in a miniaturized format using a combination of analog and digital hardware for sensing, signal processing, data storage, and graphical display. The disposable tip is engineered with a microfabricated, cell- sensing zone that enables discrimination by cell size and cell volume at sub-micron and sub-picoliter resolution. Enhanced with precision liquid-handling channels and electronics, the Scepter cell counter reports cell population statistics graphically displayed as a histogram.

The Scepter Cell Counter is a handheld automated device that can be used to count cells, monitor cell diameter and volume, and be used to check the health and quality of cellular populations from one culture to the next.

Counting cells is often a necessary but tedious step for in vitro cell culture. Consistent cell concentrations ensure experimental reproducibility and ...

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Fluorescent cell tracking dyes, in combination with flow and image cytometry, are powerful tools with which to study the interactions and fates of different cell types in vitro and in vivo.1-5 Although there are literally thousands of publications using such dyes, some of the most commonly encountered cell tracking applications include monitoring of:
<ol>
	<li>stem and progenitor cell quiescence, proliferation and/or differentiation6-8</li>
	<li>antigen-driven membrane transfer9 and/or precursor cell proliferation3,4,10-18 and</li>
	<li>immune regulatory and effector cell function1,18-21.</li>
</ol>
Commercially available cell tracking dyes vary widely in their chemistries and fluorescence properties but the great majority fall into one of two classes based on their mechanism of cell labeling. "Membrane dyes", typified by PKH26, are highly lipophilic dyes that partition stably but non-covalently into cell membranes1,2,11. "Protein dyes", typified by CFSE, are amino-reactive dyes that form stable covalent bonds with cell proteins4,16,18. Each class has its own advantages and limitations. The key to their successful use, particularly in multicolor studies where multiple dyes are used to track different cell types, is therefore to understand the critical issues enabling optimal use of each class2-4,16,18,24.
The protocols included here highlight three common causes of poor or variable results when using cell-tracking dyes. These are:
<ol>
	<li>Failure to achieve bright, uniform, reproducible labeling. This is a necessary starting point for any cell tracking study but requires attention to different variables when using membrane dyes than when using protein dyes or equilibrium binding reagents such as antibodies.</li>
	<li>Suboptimal fluorochrome combinations and/or failure to include critical compensation controls. Tracking dye fluorescence is typically 102 - 103 times brighter than antibody fluorescence. It is therefore essential to verify that the presence of tracking dye does not compromise the ability to detect other probes being used.</li>
	<li>Failure to obtain a good fit with peak modeling software. Such software allows quantitative comparison of proliferative responses across different populations or stimuli based on precursor frequency or other metrics. Obtaining a good fit, however, requires exclusion of dead/dying cells that can distort dye dilution profiles and matching of the assumptions underlying the model with characteristics of the observed dye dilution profile.</li>
</ol>
Examples given here illustrate how these variables can affect results when using membrane and/or protein dyes to monitor cell proliferation.

Successful use of cell tracking dyes to monitor immune cell function and proliferation involves several critical steps. We describe methods for: 1) obtaining bright, uniform, reproducible label-ing with membrane dyes; 2) selecting fluorochromes and data acquisition conditions; and 3) choosing a model to quantify cell proliferation based on dye dilution.

Fluorescent cell tracking dyes, in combination with flow and image cytometry, are powerful tools with which to study the interactions and fates of ...

Generation of Stable Human Cell Lines with Tetracycline-inducible (Tet-on) shRNA or cDNA Expression

A major approach in the field of mammalian cell biology is the manipulation of the expression of genes of interest in selected cell lines, with the aim to reveal one or several of the gene's function(s) using transient/stable overexpression or knockdown of the gene of interest. Unfortunately, for various cell biological investigations this approach is unsuitable when manipulations of gene expression result in cell growth/proliferation defects or unwanted cell differentiation. Therefore, researchers have adapted the Tetracycline repressor protein (TetR), taken from the E. coli tetracycline resistance operon1, to generate very efficient and tight regulatory systems to express cDNAs in mammalian cells2,3. In short, TetR has been modified to either (1) block initiation of transcription by binding to the Tet-operator (TO) in the promoter region upon addition of tetracycline (termed Tet-off system) or (2) bind to the TO in the absence of tetracycline (termed Tet-on system) (Figure 1). Given the inconvenience that the Tet-off system requires the continuous presence of tetracycline (which has a half-life of about 24 hr in tissue cell culture medium) the Tet-on system has been more extensively optimized, resulting in the development of very tight and efficient vector systems for cDNA expression as used here.
Shortly after establishment of RNA interference (RNAi) for gene knockdown in mammalian cells4, vectors expressing short-hairpin RNAs (shRNAs) were described that function very similar to siRNAs5-11. However, these shRNA-mediated knockdown approaches have the same limitation as conventional knockout strategies, since stable depletion is not feasible when gene targets are essential for cellular survival. To overcome this limitation, van de Wetering et al.12 modified the shRNA expression vector pSUPER5 by inserting a TO in the promoter region, which enabled them to generate stable cell lines with tetracycline-inducible depletion of their target genes of interest.
Here, we describe a method to efficiently generate stable human Tet-on cell lines that reliably drive either inducible overexpression or depletion of the gene of interest. Using this method, we have successfully generated Tet-on cell lines which significantly facilitated the analysis of the MST/hMOB/NDR cascade in centrosome13,14 and apoptosis signaling15,16. In this report, we describe our vectors of choice, in addition to describing the two consecutive manipulation steps that are necessary to efficiently generate human Tet-on cell lines (Figure 2). Moreover, besides outlining a protocol for the generation of human Tet-on cell lines, we will discuss critical aspects regarding the technical procedures and the characterization of Tet-on cells.

Generation of Stable Human Cell Lines with Tetracycline-inducible Tet-on shRNA or cDNA Expression

A rapid and simple way to generate human cell lines with inducible and reversible cDNA overexpression or shRNA-mediated knock-down of the gene of interest. This method enables researchers to reliably and highly reproducibly manipulate cell lines that are difficult to alter by transient transfection methods or conventional knockdown/knockout strategies.

A major approach in  the field of mammalian cell biology is the manipulation of the expression of  genes of interest in selected cell lines, with the aim ...

Methods for Skin Wounding and Assays for Wound Responses in C. elegans

The C. elegans epidermis and cuticle form a simple yet sophisticated skin layer that can repair localized damage resulting from wounding. Studies of wound responses and repair in this model have illuminated our understanding of the cytoskeletal and genomic responses to tissue damage. The two most commonly used methods to wound the C. elegans adult skin are pricks with microinjection needles, and local laser irradiation. Needle wounding locally disrupts the cuticle, epidermis, and associated extracellular matrix, and may also damage internal tissues. Laser irradiation results in more localized damage. Wounding triggers a succession of readily assayed responses including elevated epidermal Ca2+ (seconds-minutes), formation and closure of an actin-containing ring at the wound site (1-2 hr), elevated transcription of antimicrobial peptide genes (2-24 hr), and scar formation. Essentially all wild type adult animals survive wounding, whereas mutants defective in wound repair or other responses show decreased survival. Detailed protocols for needle and laser wounding, and assays for quantitation and visualization of wound responses and repair processes (Ca dynamics, actin dynamics, antimicrobial peptide induction, and survival) are presented.

Methods for Skin Wounding and Assays for Wound Responses in C. elegans

The adult C. elegans skin is a tractable model for studies of epithelial wound responses, including wound closure, scar formation, and innate immunity.

The C. elegans epidermis and cuticle form a simple yet sophisticated skin layer that can repair localized damage resulting from wounding. Studies of wound ...

Generation of Genomic Deletions in Mammalian Cell Lines via CRISPR/Cas9

The prokaryotic clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) 9 system may be re-purposed for site-specific eukaryotic genome engineering. CRISPR/Cas9 is an inexpensive, facile, and efficient genome editing tool that allows genetic perturbation of genes and genetic elements. Here we present a simple methodology for CRISPR design, cloning, and delivery for the production of genomic deletions. In addition, we describe techniques for deletion, identification, and characterization. This strategy relies on cellular delivery of a pair of chimeric single guide RNAs (sgRNAs) to create two double strand breaks (DSBs) at a locus in order to delete the intervening DNA segment by non-homologous end joining (NHEJ) repair. Deletions have potential advantages as compared to single-site small indels given the efficiency of biallelic modification, ease of rapid identification by PCR, predictability of loss-of-function, and utility for the study of non-coding elements. This approach can be used for efficient loss-of-function studies of genes and genetic elements in mammalian cell lines.

CRISPR/Cas9 is a robust system to produce disruption of genes and genetic elements. Here we describe a protocol for the efficient creation of genomic deletions in mammalian cell lines using CRISPR/Cas9.

The prokaryotic clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) 9 system may be re-purposed for site-specific ...

Method for Measuring the Activity of Deubiquitinating Enzymes in Cell Lines and Tissue Samples

The ubiquitin-proteasome system has recently been implicated in various pathologies including neurodegenerative diseases and cancer. In light of this, techniques for studying the regulatory mechanism of this system are essential to elucidating the cellular and molecular processes of the aforementioned diseases. The use of hemagglutinin derived ubiquitin probes outlined in this paper serves as a valuable tool for the study of this system. This paper details a method that enables the user to perform assays that give a direct visualization of deubiquitinating enzyme activity. Deubiquitinating enzymes control proteasomal degradation and share functional homology at their active sites, which allows the user to investigate the activity of multiple enzymes in one assay. Lysates are obtained through gentle mechanical cell disruption and incubated with active site directed probes. Functional enzymes are tagged with the probes while inactive enzymes remain unbound. By running this assay, the user obtains information on both the activity and potential expression of multiple deubiquitinating enzymes in a fast and easy manner. The current method is significantly more efficient than using individual antibodies for the predicted one hundred deubiquitinating enzymes in the human cell.

The current protocol details a method for measuring the activity of functionally homologous deubiquitinating enzymes. Specialized probes covalently modify the enzyme and allow for detection. This method holds the potential to identify new therapeutic targets.

The ubiquitin-proteasome system has recently been implicated in various pathologies including neurodegenerative diseases and cancer. In light of this, ...

Employing Digital Droplet PCR to Detect BRAF V600E Mutations in Formalin-fixed Paraffin-embedded Reference Standard Cell Lines

ddPCR is a highly sensitive PCR method that utilizes a water-oil emulsion system. Using a droplet generator, an extracted nucleic acid sample is partitioned into ~20,000 nano-sized, water-in-oil droplets, and PCR amplification occurs in individual droplets. The ddPCR approach is in identifying sequence mutations, copy number alterations, and select structural rearrangements involving targeted genes. Here, we demonstrate the use of ddPCR as a powerful technique for precisely quantitating rare BRAF V600E mutations in FFPE reference standard cell lines, which is helpful in identifying individuals with cancer. In conclusion, ddPCR technique offers the potential to precisely profile the specific rare mutations in different genes in various types of FFPE samples.

The goal of this video is to demonstrate how to perform&#160;automated DNA extraction from formalin-fixed paraffin-embedded (FFPE) reference standard cell lines and digital droplet PCR&#160;(ddPCR) analysis to detect rare mutations in a clinical setting. Detecting mutations in FFPE samples demonstrates the clinical utility of ddPCR in FFPE samples.

ddPCR is a highly sensitive PCR method that utilizes a water-oil emulsion system. Using a droplet generator, an extracted nucleic acid sample is ...

Comparison of Tobacco Host Cell Protein Removal Methods by Blanching Intact Plants or by Heat Treatment of Extracts

Plants not only provide food, feed and raw materials for humans, but have also been developed as an economical production system for biopharmaceutical proteins, such as antibodies, vaccine candidates and enzymes. These must be purified from the plant biomass but chromatography steps are hindered by the high concentrations of host cell proteins (HCPs) in plant extracts. However, most HCPs irreversibly aggregate at temperatures above 60 &#176;C facilitating subsequent purification of the target protein. Here, three methods are presented to achieve the heat precipitation of tobacco HCPs in either intact leaves or extracts. The blanching of intact leaves can easily be incorporated into existing processes but may have a negative impact on subsequent filtration steps. The opposite is true for heat precipitation of leaf extracts in a stirred vessel, which can improve the performance of downstream operations albeit with major changes in process equipment design, such as homogenizer geometry. Finally, a heat exchanger setup is well characterized in terms of heat transfer conditions and easy to scale, but cleaning can be difficult and there may be a negative impact on filter capacity. The design-of-experiments approach can be used to identify the most relevant process parameters affecting HCP removal and product recovery. This facilitates the application of each method in other expression platforms and the identification of the most suitable method for a given purification strategy.

Three heat precipitation methods are presented that effectively remove more than 90% of host cell proteins (HCPs) from tobacco extracts prior to any other purification step. The plant HCPs irreversibly aggregate at temperatures above 60 &#176;C.

Plants not only provide food, feed and raw materials for humans, but have also been developed as an economical production system for biopharmaceutical ...

Inducible LAP-tagged Stable Cell Lines for Investigating Protein Function, Spatiotemporal Localization and Protein Interaction Networks

Multi-protein complexes, rather than single proteins acting in isolation, often govern molecular pathways regulating cellular homeostasis. Based on this principle, the purification of critical proteins required for the functioning of these pathways along with their native interacting partners has not only allowed the mapping of the protein constituents of these pathways, but has also provided a deeper understanding of how these proteins coordinate to regulate these pathways. Within this context, understanding a protein's spatiotemporal localization and its protein-protein interaction network can aid in defining its role within a pathway, as well as how its misregulation may lead to disease pathogenesis. To address this need, several approaches for protein purification such as tandem affinity purification (TAP) and localization and affinity purification (LAP) have been designed and used successfully. Nevertheless, in order to apply these approaches to pathway-scale proteomic analyses, these strategies must be supplemented with modern technological developments in cloning and mammalian stable cell line generation. Here, we describe a method for generating LAP-tagged human inducible stable cell lines for investigating protein subcellular localization and protein-protein interaction networks. This approach has been successfully applied to the dissection of multiple cellular pathways including cell division and is compatible with high-throughput proteomic analyses.

We describe a method for generating localization and affinity purification (LAP)-tagged inducible stable cell lines for investigating protein function, spatiotemporal subcellular localization and protein-protein interaction networks.

Multi-protein complexes, rather than single proteins acting in isolation, often govern molecular pathways regulating cellular homeostasis. Based on this ...

Anaerobic Growth and Maintenance of Mammalian Cell Lines

Most mucosal surfaces along with the midpoints in tumors and stem cell niches are geographic areas of the body that are anoxic. Previous studies show that the incubation in normoxic (5% CO2 in air) or hypoxic (low oxygen levels) conditions followed by an anoxic incubation (an absence of free oxygen) results in limited viability (2&#8211;3 days). A novel methodology was developed that enables an anoxic cell cultivation (for at least 17 days; the maximum time tested). The most critical aspect of this methodology is to ensure that no oxygen is introduced into the system. This is obtained by the degassing of media, and by flushing tubes, dishes, flasks, and pipettes with an anaerobic gas mixture (H2, CO2, N2) followed by permitting the materials to equilibrate to the anoxic (non-oxygen) environment prior to usage.&#160;Additional care must be exercised when acquiring photomicrographs to ensure that the micrographs obtained do not contain artifacts. In the absence of oxygen, cell morphology is significantly altered. Two distinct morphotypes are noted for all anaerobically-grown cells. The ability to grow and maintain mammalian cells in the absence of oxygen can be applied to the analysis of cell physiology, polymicrobial interactions, and the characterization of biosynthetic pathways for novel cancer drug development.

Here, we describe a new method that enables the anaerobic long-term cultivation of established cell lines. The maximum survival time that was tested is 17 days. This method is suitable for the testing of cytotoxic agents and exploring the physiology of anoxically replicating cells.

Most mucosal surfaces along with the midpoints in tumors and stem cell niches are geographic areas of the body that are anoxic. Previous studies show that ...