This research was supported by the Main Research Program (E0210702-03) of the Korea Food Research Institute (KFRI), funded by the Ministry of Science and ICT.

1. Preparation of bacterial inoculum
<ol>
	<li>Remove the glycerol stock vial stored at -80 &#176;C.</li>
	<li>Remove the bacterial strain (2-10 &#181;L) from the vial using a sterile pipette tip. 
	NOTE: Acinetobacter strains, A. bouvetii (13-1-1), A. junii (13-1-2), A. pittii (13-2-5), A. baumannii (13-2-9), A. radioresistens (20-1), and A. ursingii (24-1) are used in this protocol.</li>
	<li>Inoculate a commercially available blood agar plate (tryptic soy agar supplemented with 5% sheep blood, see Table of Materials) with the bacteria. 
	NOTE: Other media, such as nutrient agar or MacConkey agar, can also be used.</li>
	<li>Streak the agar surface using a sterile loop with intermittent flaming to thin it out.</li>
	<li>Place the agar plate upside down in an incubator and incubate at 30 &#176;C overnight for 20-24 h.</li>
	<li>Pick a single colony of the bacterial culture with a sterile needle and inoculate 5 mL sterile brain heart infusion broth (BHI, see Table of Materials) with the culture.</li>
	<li>Incubate the inoculated broth in a shaking incubator at 30 &#176;C overnight for 20-24 h at around 150 rpm.</li>
	<li>Transfer 1 mL of the overnight culture to a sterile microcentrifuge tube and centrifuge the overnight culture at 6,000 &#215; g for 10 min at room temperature (RT).</li>
	<li>Remove the supernatant with a pipette.</li>
	<li>Using a vortex, resuspend the pellet in 1 mL sterile phosphate-buffered saline (PBS).</li>
	<li>Centrifuge at 6,000 &#215; g for 10 min at RT and remove the supernatant.</li>
	<li>Resuspend the pellet in sterile ten-fold diluted BHI using vortex to an optical density of around 0.1 at 600 nm. 
	NOTE: The optical density of around 0.1 is equivalent to approximately 107 CFU/mL.</li>
</ol>
2. Biofilm quantification using crystal violet
<ol>
	<li>Add 200 &#181;L inoculum to each well of a sterile polystyrene 96-well plate (see Table of Materials) and add 200 &#181;L deionized water to each of the outermost wells to prevent the inner wells from drying out15.</li>
	<li>Add 200 &#181;L ten-fold diluted BHI to each well of the same plate as a negative control.</li>
	<li>Incubate the plate at 25 &#176;C for 24 h.</li>
	<li>Remove the supernatant with a pipette. 
	NOTE: Multichannel pipette is often more convenient for multiple samples.</li>
	<li>Carefully add 300 &#181;L PBS to each well and remove the supernatant with a pipette. 
	&#8203;NOTE: Multichannel pipette is often more convenient for multiple samples.</li>
	<li>Repeat step 2.5 two more times.</li>
	<li>Add 200 &#181;L crystal violet solution (1%) (see Table of Materials) to each well and incubate at RT for 30 min.</li>
	<li>Repeat steps 2.4-2.6.</li>
	<li>Add 200 &#181;L of absolute ethanol to each well and incubate for 15 min at RT. Mix thoroughly by pipetting up and down several times.</li>
	<li>Transfer 100 &#181;L elution from each well to a new 96-well plate.</li>
	<li>Measure the absorbance at 595 nm using a microplate reader (see Table of Materials).</li>
	<li>When the absorbance exceeds 2.0, make a proper dilution of the sample to the absorbance below 2.0 in absolute ethanol and measure it as in step 2.11. Then, calculate the absorbance of the sample (final value) by multiplying the observed value by the dilution factor.</li>
	<li>Calculate the true absorbance of the samples by subtracting the average value of the negative control from the value of each well of the test samples on the same well plate.</li>
</ol>
3. Biofilm viability count
<ol>
	<li>Add 1 mL inoculum (step 1) to each well of a sterile polystyrene 12-well plate15. Incubate the plate at 25 &#176;C for 24 h. Remove the supernatant with a pipette.</li>
	<li>Carefully add 1.5 mL sterile PBS to each well and remove the supernatant with a pipette. Add 1 mL sterile PBS to each well.</li>
	<li>Scrape off the bottom and wall surfaces of the well using fitted cell scrapers.</li>
	<li>Transfer the harvested cell suspension to a sterile plastic tube (10-1) containing 9 mL saline (0.85% NaCl) and 10-20 glass beads (see Table of Materials). 
	NOTE: To collect any residual biofilm debris left on the bottom surface of the well, it can be resuspended and transferred by pipette using saline from the 10-1 tube.</li>
	<li>Vortex the 10-1 tube for 60 s at a maximum speed.</li>
	<li>Make a 10-fold serial dilution by transferring 1 mL to the next sterile tube (10-2) containing 9 mL saline (0.85 % NaCl) up to 10-7.</li>
	<li>Spread 100 &#181;L from each dilution on Acinetobacter agar (see Table of Materials) and incubate the agar plates at 30 &#176;C for 24-42 h.</li>
	<li>Count the number of the typical red colonies on each plate manually in the range between 10 and 250.</li>
	<li>Calculate the number of viable cells in the biofilm of each well by using the equation below: 
	Viable cells = Number of colonies&#160;&#215; Dilution factors&#160;&#215; 10</li>
</ol>
4. Biofilm visualization using confocal laser scanning microscopy (CLSM)
<ol>
	<li>Add 200 &#181;L inoculum to each well of a sterile 96-well plate intended for microscopic analysis.</li>
	<li>Incubate the plate at 25 &#176;C for 24 h.</li>
	<li>Remove the supernatant with a pipette.</li>
	<li>Carefully add 300 &#181;L filter-sterilized deionized water to each well and remove the supernatant with a pipette.</li>
	<li>Repeat step 4.4.</li>
	<li>Prepare the mixture of SYTO 9 and propidium iodide (see Table of Materials) diluted in filter-sterilized deionized water to a final concentration of 10 &#181;M and 60 &#181;M, respectively.</li>
	<li>Add the mixture to each well at 200 &#181;L and incubate the plate for 20-30 min at RT in the dark.</li>
	<li>Repeat steps 4.3-4.4</li>
	<li>Visualize the bottom-surface attached biofilms using CLSM with the excitation wavelength of 488 nm and 561 nm and the emission wavelength range of 499-535 nm and 568-712 nm, respectively.</li>
</ol>

Assessment of Acinetobacter Biofilm Formation and Characterization of Biofilms

<ol>
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J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acinetobacter:+an+old+friend,+but+a+new+enemy.">Acinetobacter: an old friend, but a new enemy.</a> Journal of Hospital Infection. 73 (4), 355-363 (2009).</li><li>Weber, D. J., Rutala, W. A., Miller, M. B., Huslage, K., Sickbert-Bennett, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Role+of+hospital+surfaces+in+the+transmission+of+emerging+health+care-associated+pathogens:+Norovirus,+Clostridium+difficile,+and+Acinetobacter+species.">Role of hospital surfaces in the transmission of emerging health care-associated pathogens: Norovirus, Clostridium difficile, and Acinetobacter species.</a> American Journal of Infection Control. 38 (5), S25-S33 (2010).</li><li>Flemming, H. 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=The+biofilm+matrix:+multitasking+in+a+shared+space.">The biofilm matrix: multitasking in a shared space.</a> Nature Reviews Microbiology. 21 (2), 70-86 (2023).</li><li>Flemming, H. 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=Biofilms:+an+emergent+form+of+bacterial+life.">Biofilms: an emergent form of bacterial life.</a> Nature Reviews Microbiology. 14 (9), 563-575 (2016).</li><li>Yin, W., Wang, Y., Liu, L., He, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofilms:+the+microbial+&amp;#34;protective+clothing&amp;#34;+in+extreme+environments.">Biofilms: the microbial &amp;#34;protective clothing&amp;#34; in extreme environments.</a> International Journal of Molecular Sciences. 20 (14), 3423 (2019).</li><li>Gedefie, 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=Acinetobacter+baumannii+biofilm+formation+and+its+role+in+disease+pathogenesis:+a+review.">Acinetobacter baumannii biofilm formation and its role in disease pathogenesis: a review.</a> Infection and drug resistance. 14, 3711-3719 (2021).</li><li>Whiteway, C., Breine, A., Philippe, C., Van der Henst, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acinetobacter+baumannii.">Acinetobacter baumannii.</a> Trends in Microbiology. 30 (2), 199-200 (2022).</li><li>Longo, F., Vuotto, C., Donelli, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofilm+formation+in+Acinetobacter+baumannii.">Biofilm formation in Acinetobacter baumannii.</a> New Microbiologica. 37 (2), 119-127 (2014).</li><li>Azeredo, J., 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=Critical+review+on+biofilm+methods.">Critical review on biofilm methods.</a> Critical Reviews in Microbiology. 43 (3), 313-351 (2017).</li><li>Jia, J., Xue, X., Guan, Y., Fan, X., Wang, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofilm+characteristics+and+transcriptomic+profiling+of+Acinetobacter+johnsonii+defines+signatures+for+planktonic+and+biofilm+cells.">Biofilm characteristics and transcriptomic profiling of Acinetobacter johnsonii defines signatures for planktonic and biofilm cells.</a> Environmental Research. 213, 113714 (2022).</li><li>Yang, C., Su, P., Moi, S., Chuang, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofilm+formation+in+Acinetobacter+baumannii:+genotype-phenotype+correlation.">Biofilm formation in Acinetobacter baumannii: genotype-phenotype correlation.</a> Molecules. 24 (10), 1849 (2019).</li><li>Alamri, A. M., Alsultan, A. A., Ansari, M. A., Alnimr, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofilm-formation+in+clonally+unrelated+multidrug-resistant+Acinetobacter+baumannii+isolates.">Biofilm-formation in clonally unrelated multidrug-resistant Acinetobacter baumannii isolates.</a> Pathogens. 9 (8), 630 (2020).</li><li>Lim, E. S., Nam, S. J., Koo, O. K., Kim, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protective+role+of+Acinetobacter+and+Bacillus+for+Escherichia+coli+O157:H7+in+biofilms+against+sodium+hypochlorite+and+extracellular+matrix-degrading+enzymes.">Protective role of Acinetobacter and Bacillus for Escherichia coli O157:H7 in biofilms against sodium hypochlorite and extracellular matrix-degrading enzymes.</a> Food Microbiology. 109, 104125 (2023).</li><li>Stepanovi&#263;, S., &#262;irkovi&#263;, I., Ranin, L., Svabi&#263;-Vlahovi&#263;, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofilm+formation+by+Salmonella+spp.+and+Listeria+monocytogenes+on+plastic+surface.">Biofilm formation by Salmonella spp. and Listeria monocytogenes on plastic surface.</a> Letters in Applied Microbiology. 38 (5), 428-432 (2004).</li><li>Boone, R. L., 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=Analysis+of+virulence+phenotypes+and+antibiotic+resistance+in+clinical+strains+of+Acinetobacter+baumannii+isolated+in+Nashville,+Tennessee.">Analysis of virulence phenotypes and antibiotic resistance in clinical strains of Acinetobacter baumannii isolated in Nashville, Tennessee.</a> BMC Microbiology. 21 (1), 21 (2021).</li><li>Otter, J. 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=Surface-attached+cells,+biofilms+and+biocide+susceptibility:+implications+for+hospital+cleaning+and+disinfection.">Surface-attached cells, biofilms and biocide susceptibility: implications for hospital cleaning and disinfection.</a> Journal of Hospital Infection. 89 (1), 16-27 (2015).</li><li>Ravishankar, S., Juneja, V. K., Yousef, A. E., Juneja, V. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Adaptation+or+resistance+responses+of+microorganisms+to+stresses+in+the+food+processing+environment.">Adaptation or resistance responses of microorganisms to stresses in the food processing environment.</a> Microbial Stress Adaptation and Food Safety. , (2003).</li><li>Dewanti, R., Wong, A. C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+culture+conditions+on+biofilm+formation+by+Escherichia+coli+O157:H7.">Influence of culture conditions on biofilm formation by Escherichia coli O157:H7.</a> International Journal of Food Microbiology. 26 (2), 147-164 (1995).</li><li>McConnell, M. J., Actis, L., Pach&#243;n, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acinetobacter+baumannii:+human+infections,+factors+contributing+to+pathogenesis+and+animal+models.">Acinetobacter baumannii: human infections, factors contributing to pathogenesis and animal models.</a> FEMS Microbiology Reviews. 37 (2), 130-155 (2013).</li><li>McQueary, C. N., Actis, L. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acinetobacter+baumannii+biofilms:+variations+among+strains+and+correlations+with+other+cell+properties.">Acinetobacter baumannii biofilms: variations among strains and correlations with other cell properties.</a> The Journal of Microbiology. 49 (2), 243-250 (2011).</li></ol>

The authors have nothing to disclose.

Using the protocol described, the biofilm formation of Acinetobacter isolates with varying degrees was measured, visualized, and the viable cells in the biofilms were estimated (Figure 1, Figure 2, and Figure 3).
In this protocol, two different temperatures were used, 30 &#176;C for the growth and 25 &#176;C for the biofilm formation of Acinetobacter. 30 &#176;C was used because many stu...

Acinetobacter is known to cause nosocomial infections, and its human infection, especially in healthcare facilities, is increasingly reported1. It is widespread in hospitals, healthcare facilities, and food-associated environments2,3,4. It can survive for a long period in environments including hospital surfaces such as bed rails, bedside tables, the surface of ventilators, and sinks4. Such persistence on environmental surfaces may be one of the significant factors contributing to the nosocomial infections of Acinetobacter4.
Biofilm is a form of microbial life and is a microbial matrix composed of live microbial cells and extracellular polymeric substances (EPS) from the cells5. The microbial cells are embedded in the matrix and are often highly resistant to environmental stresses such as heat, salts, dryness, antibiotics, disinfectants, and shear forces6,7.
Acinetobacter can form biofilms on surfaces, suggesting that it may contribute to extended survival on environmental surfaces, including hospital surfaces, and enhanced resistance to antibiotic treatment8,9. In addition, the biofilm formation of Acinetobacter could be highly associated with human clinical outcomes8. Therefore, the biofilm formability of Acinetobacter strains could be one of the indicators in predicting environmental survival and human infections8,10.
The surface-attached biofilms can be quantified and visualized to assess biofilm formability. To quantify surface-attached biofilms, the biofilms are normally stained by biofilm-staining dyes such as crystal violet, and the dyes are eluted in solution and measured for optical density11. Visualization of biofilms is another good approach to assess biofilm formability11. Confocal Laser Scanning Microscopy (CLSM) visualization method employing specificity using fluorescent dyes could be more useful to characterize biofilm morphology compared to other techniques such as SEM12,13.
The viable cells in biofilms can be counted to estimate the number of viable cells in biofilms11. The viable cells embedded in biofilms are detached, diluted, spread on agar plates, incubated, and enumerated. Because the higher number of cells is likely to meet the infectious dose, it can provide more detailed information on biofilms, such as infection potentials associated with the number of cells13,14.
This article presents step-by-step protocols to (1) quantify surface-attached biofilms, (2) count viable cells in the biofilms, and (3) visualize the biofilms using CLSM of Acinetobacter. The presented protocols describe the methods to assess the biofilm formability of Acinetobacter isolates and characterize their biofilms.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>96-well cell culture plate</td>
			<td>SPL</td>
			<td>30096</td>
			<td>Polystyrene 96-well plate</td>
		</tr>
		<tr>
			<td>BHI (Brain Heart Infusion) broth</td>
			<td>Merck KGaA</td>
			<td>1.10493.0500</td>
			<td></td>
		</tr>
		<tr>
			<td>Blood Agar Base Plate</td>
			<td>KisanBio</td>
			<td>MB-B1005-P50</td>
			<td>Growth media for Acinetobacter</td>
		</tr>
		<tr>
			<td>CHROMagar Acinetobacter</td>
			<td>CHROMagar</td>
			<td>AC092</td>
			<td>Selective plate for Acinetobacter</td>
		</tr>
		<tr>
			<td>Crystal violet solution</td>
			<td>Sigma-Aldrich</td>
			<td>V5265</td>
			<td></td>
		</tr>
		<tr>
			<td>Filmtracer LIVE/DEAD biofilm viability kit</td>
			<td>Invitrogen</td>
			<td>L10316</td>
			<td>SYTO9 and propidium iodide</td>
		</tr>
		<tr>
			<td>Microplate reader</td>
			<td>Tecan</td>
			<td>Infinite M200 PRO NanoQuant</td>
			<td>Biofilm measurement</td>
		</tr>
		<tr>
			<td>RBC Glass Plating Beads</td>
			<td>RBC</td>
			<td>RG001</td>
			<td>Glass beads</td>
		</tr>
		<tr>
			<td>&#956;-Plate 96 Well Black</td>
			<td>ibidi</td>
			<td>89621</td>
			<td>Microplate intended for CLSM</td>
		</tr>
	</tbody>
</table>

quantification, viability assessment, and visualization strategies for acinetobacter biofilms

Acinetobacter causes nosocomial infections and its biofilm formation can contribute to the survival on dry surfaces such as hospital environments. Thus, biofilm quantification and visualization are important methods to assess the potential of Acinetobacter strains to cause nosocomial infections. The biofilms forming on the surface of the microplate can be quantified in terms of volume and cell numbers. Biofilm volumes can be quantified by staining using crystal violet, washing, destaining using ethanol, then measuring the solubilized dye using a microplate reader. To quantify the number of cells embedded in the biofilms, the biofilms are scrapped off using cell scrapers, harvested in the saline, vigorously agitated in the presence of glass beads, and spread on Acinetobacter agar. Then, the plates are incubated at 30 &#176;C for 24-42 h. After incubation, the red colonies are enumerated to estimate the number of cells in biofilms. This viable count method can also be useful for counting Acinetobacter cells in mixed-species biofilms. Acinetobacter biofilms can be visualized using fluorescent dyes. A commercially available microplate designed for microscopic analysis is employed to form biofilms. Then, the bottom-surface attached biofilms are stained with SYTO9 and propidium iodide dyes, washed, then visualized with confocal laser scanning microscopy.

Following the protocol, the biofilms of Acinetobacter isolates, originally isolated from kitchen surfaces, were formed on a polystyrene 96-well plate, stained with crystal violet, and the dyes were solubilized in ethanol and measured for biofilm mass (Figure 1). The number of biofilms greatly varied depending on the strains ranging from OD 0.04 to 1.69 (Figure 1). Based on the criteria established by Stepanovi&#263; et al.16, all...

Watch this Scientific Journal Video about A Comprehensive Protocol for Acinetobacter Biofilm Quantification, Assessment, and Visualization at JoVE.com

Author Spotlight: A Comprehensive Protocol for Acinetobacter Biofilm Quantification, Assessment, and Visualization 

This protocol describes the preparation of the inoculum, the biofilm quantification on microtiter plates using crystal violet dye, the viable count in biofilms, and the visualization of biofilms of Acinetobacter.

Quantification, Viability Assessment, and Visualization Strategies for Acinetobacter Biofilms

Acinetobacter causes nosocomial infections and its biofilm formation can contribute to the survival on dry surfaces such as hospital environments. Thus, ...

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2.7K Views.  Korea Food Research Institute. This protocol describes the preparation of the inoculum, the biofilm quantification on microtiter plates using crystal violet dye, the viable count in biofilms, and the visualization of biofilms of Acinetobacter.

Video: Author Spotlight: A Comprehensive Protocol for Acinetobacter Biofilm Quantification, Assessment, and Visualization 

Counting and Determining the Viability of Cultured Cells

Determining the number of cells in culture is important in standardization of culture conditions and in performing accurate quantitation experiments. A hemacytometer is a thick glass slide with a central area designed as a counting chamber. Cell suspension is applied to a defined area and counted so cell density can be calculated. 

Determining the number of cells in culture is important in standardization of culture conditions and in performing accurate quantitation experiments. In this video, we demonstrate how cells are counted using a hemacytometer.

Determining the number of cells in culture is important in standardization of culture conditions and in performing accurate quantitation experiments. A ...

Computer-assisted Large-scale Visualization and Quantification of Pancreatic Islet Mass, Size Distribution and Architecture

The pancreatic islet is a unique micro-organ composed of several hormone secreting endocrine cells such as beta-cells (insulin), alpha-cells (glucagon), and delta-cells (somatostatin) that are embedded in the exocrine tissues and comprise 1-2% of the entire pancreas. There is a close correlation between body and pancreas weight. Total beta-cell mass also increases proportionately to compensate for the demand for insulin in the body. What escapes this proportionate expansion is the size distribution of islets. Large animals such as humans share similar islet size distributions with mice, suggesting that this micro-organ has a certain size limit to be functional. The inability of large animal pancreata to generate proportionately larger islets is compensated for by an increase in the number of islets and by an increase in the proportion of larger islets in their overall islet size distribution. Furthermore, islets exhibit a striking plasticity in cellular composition and architecture among different species and also within the same species under various pathophysiological conditions. In the present study, we describe novel approaches for the analysis of biological image data in order to facilitate the automation of analytic processes, which allow for the analysis of large and heterogeneous data collections in the study of such dynamic biological processes and complex structures. Such studies have been hampered due to technical difficulties of unbiased sampling and generating large-scale data sets to precisely capture the complexity of biological processes of islet biology. Here we show methods to collect unbiased "representative" data within the limited availability of samples (or to minimize the sample collection) and the standard experimental settings, and to precisely analyze the complex three-dimensional structure of the islet. Computer-assisted automation allows for the collection and analysis of large-scale data sets and also assures unbiased interpretation of the data. Furthermore, the precise quantification of islet size distribution and spatial coordinates (i.e. X, Y, Z-positions) not only leads to an accurate visualization of pancreatic islet structure and composition, but also allows us to identify patterns during development and adaptation to altering conditions through mathematical modeling. The methods developed in this study are applicable to studies of many other systems and organisms as well.

Novel computer-assisted methods of large-scale procurement and analysis of immunohistochemically stained pancreatic specimens are described: (1) Virtual Slice capture of the entire section; (2) Mass analysis of large-scale data; (3) Reconstruction of 2D Virtual Slices; (4) 3D islet mapping; and (5) Mathematical analysis.

The pancreatic islet is a unique micro-organ composed of several hormone secreting endocrine cells such as beta-cells (insulin), alpha-cells (glucagon), ...

Assessment of GFP Expression and Viability Using the Tali Image-Based Cytometer

Single-cell and population information are commonly obtained either by flow cytometry or fluorescence microscopy. However, these two methods provide different information. Flow cytometry gives quantitative multi-parametric information about physical characteristics and staining or expression, but doesn't allow for visualization. Stand-alone fluorescence microscopy provides visual data, but doesn't allow for straightforward quantitative measurements1.
Image-based cytometry bridges the gap between these two methods, enabling the quick visualization and simultaneous quantitative analysis of thousands of cells in heterogeneous populations2. Here, we present a method for performing cell viability and green fluorescent protein (GFP) expression assays using the Tali Image-Based Cytometer3. The Tali instrument is a 3-channel (bright field, green fluorescence, red fluorescence) benchtop assay platform that offers several advantages over flow cytometry and fluorescence microscopy. The Tali cytometer is less expensive, takes up less bench space, requires less maintenance, and the work flow has been simplified so that the operation and analysis is much simpler and quicker. The Tali cytometer is capable of performing a range of suspension cell-based assays, including GFP and red fluorescent protein (RFP) expression, apoptosis4-6 and cell viability analysis with propidium iodide (PI)7-11.
Here, we demonstrate the use of the Tali instrument in performing a cell viability assay in cells expressing GFP. GFP-transduced cells are stained using the Tali Viability Kit - Dead Cell Red. The cells are then pipetted into a Tali Cellular Analysis Slide and loaded into the cytometer. Bright field, red fluorescence and green fluorescence images are captured and analyzed using assay specific algorithms. Histograms are then generated to display cell size, PI fluorescence intensity, and GFP fluorescence intensity. These parameters can then be thresholded to home in on a specific cell population.
A side-by side comparison of the Tali Image-Based Cytometer and traditional flow cytometry demonstrates that the two methods provide comparable data regarding cell viability and protein expression. However, the Tali instrument provides additional visual information about the cell population that cannot be obtained using a flow cytometer.

This protocol describes how to perform cell viability and fluorescence expression assays using the Tali Image-Based Cytometer.

Single-cell and population information are commonly obtained either by flow cytometry or fluorescence microscopy. However, these two methods provide ...

Assessment of Mitochondrial Functions and Cell Viability in Renal Cells Overexpressing Protein Kinase C Isozymes

The protein kinase C (PKC) family of isozymes is involved in numerous physiological and pathological processes. Our recent data demonstrate that PKC regulates mitochondrial function and cellular energy status. Numerous reports demonstrated that the activation of PKC-a and PKC-&epsilon; improves mitochondrial function in the ischemic heart and mediates cardioprotection. In contrast, we have demonstrated that PKC-&alpha; and PKC-&epsilon; are involved in nephrotoxicant-induced mitochondrial dysfunction and cell death in kidney cells. Therefore, the goal of this study was to develop an in vitro model of renal cells maintaining active mitochondrial functions in which PKC isozymes could be selectively activated or inhibited to determine their role in regulation of oxidative phosphorylation and cell survival. Primary cultures of renal proximal tubular cells (RPTC) were cultured in improved conditions resulting in mitochondrial respiration and activity of mitochondrial enzymes similar to those in RPTC in vivo. Because traditional transfection techniques (Lipofectamine, electroporation) are inefficient in primary cultures and have adverse effects on mitochondrial function, PKC-&epsilon; mutant cDNAs were delivered to RPTC through adenoviral vectors. This approach results in transfection of over 90% cultured RPTC.
Here, we present methods for assessing the role of PKC-&epsilon; in: 1. regulation of mitochondrial morphology and functions associated with ATP synthesis, and 2. survival of RPTC in primary culture. PKC-&epsilon; is activated by overexpressing the constitutively active PKC-&epsilon; mutant. PKC-&epsilon; is inhibited by overexpressing the inactive mutant of PKC-&epsilon;. Mitochondrial function is assessed by examining respiration, integrity of the respiratory chain, activities of respiratory complexes and F0F1-ATPase, ATP production rate, and ATP content. Respiration is assessed in digitonin-permeabilized RPTC as state 3 (maximum respiration in the presence of excess substrates and ADP) and uncoupled respirations. Integrity of the respiratory chain is assessed by measuring activities of all four complexes of the respiratory chain in isolated mitochondria. Capacity of oxidative phosphorylation is evaluated by measuring the mitochondrial membrane potential, ATP production rate, and activity of F0F1-ATPase. Energy status of RPTC is assessed by determining the intracellular ATP content. Mitochondrial morphology in live cells is visualized using MitoTracker Red 580, a fluorescent dye that specifically accumulates in mitochondria, and live monolayers are examined under a fluorescent microscope. RPTC viability is assessed using annexin V/propidium iodide staining followed by flow cytometry to determine apoptosis and oncosis.
These methods allow for a selective activation/inhibition of individual PKC isozymes to assess their role in cellular functions in a variety of physiological and pathological conditions that can be reproduced in in vitro.

The effects of activation of protein kinase C (PKC) isozymes on mitochondrial functions associated with respiration and oxidative phosphorylation and on cell viability are described. The approach adapts adenoviral technique to selectively overexpress PKC isozymes in primary cell culture and a variety of assays to determine mitochondrial functions and energy status of the cell.

The protein kinase C (PKC) family of isozymes is involved in numerous physiological and pathological processes. Our recent data demonstrate that PKC ...

Viability Assays for Cells in Culture

Manual cell counts on a microscope are a sensitive means of assessing cellular viability but are time-consuming and therefore expensive. Computerized viability assays are expensive in terms of equipment but can be faster and more objective than manual cell counts. The present report describes the use of three such viability assays. Two of these assays are infrared and one is luminescent. Both infrared assays rely on a 16&#160;bit Odyssey Imager. One infrared assay uses the DRAQ5 stain for nuclei combined with the Sapphire stain for cytosol and is visualized in the 700 nm channel. The other infrared assay, an In-Cell Western, uses antibodies against cytoskeletal proteins (&#945;-tubulin or microtubule associated protein 2) and labels them in the 800 nm channel. The third viability assay is a commonly used luminescent assay for ATP, but we use a quarter of the recommended volume to save on cost. These measurements are all linear and correlate with the number of cells plated, but vary in sensitivity. All three assays circumvent time-consuming microscopy and sample the entire well, thereby reducing sampling error. Finally, all of the assays can easily be completed within one day of the end of the experiment, allowing greater numbers of experiments to be performed within short timeframes. However, they all rely on the assumption that cell numbers remain in proportion to signal strength after treatments, an assumption that is sometimes not met, especially for cellular ATP. Furthermore, if cells increase or decrease in size after treatment, this might affect signal strength without affecting cell number. We conclude that all viability assays, including manual counts, suffer from a number of caveats, but that computerized viability assays are well worth the initial investment. Using all three assays together yields a comprehensive view of cellular structure and function.

Therapeutic compounds are often first examined in vitro with viability assays. Blind cell counts by a human observer can be highly sensitive to small changes in cell number but do not assess function. Computerized viability assays, as described here, can assess both structure and function in an objective manner.

Manual cell counts on a microscope are a sensitive means of assessing cellular viability but are time-consuming and therefore expensive. Computerized ...

Strategies for Tracking Anastasis, A Cell Survival Phenomenon that Reverses Apoptosis

Anastasis (Greek for &#8220;rising to life&#8221;) refers to the recovery of dying cells. Before these cells recover, they have passed through important checkpoints of apoptosis, including mitochondrial fragmentation, release of mitochondrial cytochrome c into the cytosol, activation of caspases, chromatin condensation, DNA damage, nuclear fragmentation, plasma membrane blebbing, cell shrinkage, cell surface exposure of phosphatidylserine, and formation of apoptotic bodies. Anastasis can occur when apoptotic stimuli are removed prior to death, thereby allowing dying cells to reverse apoptosis and potentially other death mechanisms. Therefore, anastasis appears to involve physiological healing processes that could also sustain damaged cells inappropriately. The functions and mechanisms of anastasis are still unclear, hampered in part by the limited tools for detecting past events after the recovery of apparently healthy cells. Strategies to detect anastasis will enable studies of the physiological mechanisms, the hazards of undead cells in disease pathology, and potential therapeutics to modulate anastasis. Here, we describe effective strategies using live cell microscopy and a mammalian caspase biosensor&#160;for identifying and tracking anastasis in mammalian cells.

The term anastasis refers to the phenomenon in which dying cells reverse a cell suicide process at a late stage, repair themselves, and ultimately survive. Here we demonstrate protocols for detecting and tracking cells that undergo anastasis.

Anastasis (Greek for &#8220;rising to life&#8221;) refers to the recovery of dying cells. Before these cells recover, they have passed through important ...

A Guide to Modern Quantitative Fluorescent Western Blotting with Troubleshooting Strategies

The late 1970s saw the first publicly reported use of the western blot, a technique for assessing the presence and relative abundance of specific proteins within complex biological samples. Since then, western blotting methodology has become a common component of the molecular biologists experimental repertoire. A cursory search of PubMed using the term &#8220;western blot&#8221; suggests that in excess of two hundred and twenty thousand published manuscripts have made use of this technique by the year 2014. Importantly, the last ten years have seen technical imaging advances coupled with the development of sensitive fluorescent labels which have improved sensitivity and yielded even greater ranges of linear detection. The result is a now truly Quantifiable Fluorescence based Western Blot (QFWB) that allows biologists to carry out comparative expression analysis with greater sensitivity and accuracy than ever before. Many &#8220;optimized&#8221; western blotting methodologies exist and are utilized in different laboratories. These often prove difficult to implement due to the requirement of subtle but undocumented procedural amendments. This protocol provides a comprehensive description of an established and robust QFWB method, complete with troubleshooting strategies.

The advancement of western blotting using fluorescence has allowed detection of subtle changes in protein expression enabling quantitative analyses. Here we describe a robust methodology for detection of a range of proteins across a variety of species and tissue types. A strategy to overcome common technical problems is also provided.

The late 1970s saw the first publicly reported use of the western blot, a technique for assessing the presence and relative abundance of specific proteins ...

Visualization and Quantification of the Cell-free Layer in Arterioles of the Rat Cremaster Muscle

The cell-free layer is defined as the parietal plasma layer in the microvessel flow, which is devoid of red blood cells. The measurement of the in vivo cell-free layer width and its spatiotemporal variations can provide a comprehensive understanding of hemodynamics in microcirculation. In this study, we used an intravital microscopic system coupled with a high-speed video camera to quantify the cell-free layer widths in arterioles in vivo. The cremaster muscle of Sprague-Dawley rats was surgically exteriorized to visualize the blood flow. A custom-built imaging script was also developed to automate the image processing and analysis of the cell-free layer width. This approach enables the quantification of spatiotemporal variations more consistently than previous manual measurements. The accuracy of the measurement, however, partly depends on the use of a blue filter and the selection of an appropriate thresholding algorithm. Specifically, we evaluated the contrast and quality of images acquired with and without the use of a blue filter. In addition, we compared five different image histogram-based thresholding algorithms (Otsu, minimum, intermode, iterative selection, and fuzzy entropic thresholding) and illustrated the differences in their determination of the cell-free layer width.

This study demonstrates the surgical preparation of the rat cremaster muscle for the visualization of the in vivo cell-free layer. Considerable factors affecting the accuracy of the cell-free layer width measurement are discussed in this study.

The cell-free layer is defined as the parietal plasma layer in the microvessel flow, which is devoid of red blood cells. The measurement of the in vivo ...

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Recent studies that compared transcriptomic datasets of human diseases with datasets from mouse models using traditional gene-to-gene comparison techniques resulted in contradictory conclusions regarding the relevance of animal models for translational research. A major reason for the discrepancies between different gene expression analyses is the arbitrary filtering of differentially expressed genes. Furthermore, the comparison of single genes between different species and platforms often is limited by technical variance, leading to misinterpretation of the con/discordance between data from human and animal models. Thus, standardized approaches for systematic data analysis are needed. To overcome subjective gene filtering and ineffective gene-to-gene comparisons, we recently demonstrated that gene set enrichment analysis (GSEA) has the potential to avoid these problems. Therefore, we developed a standardized protocol for the use of GSEA to distinguish between appropriate and inappropriate animal models for translational research. This protocol is not suitable to predict how to design new model systems a-priori, as it requires existing experimental omics data. However, the protocol describes how to interpret existing data in a standardized manner in order to select the most suitable animal model, thus avoiding unnecessary animal experiments and misleading translational studies.

We provide a standardized protocol for the use of gene set enrichment analysis of transcriptomic data to identify an ideal mouse model for translational research. 
This protocol can be used with DNA microarray and RNA sequencing data and can further be extended to other omics data if data are available.

Recent studies that compared transcriptomic datasets of human diseases with datasets from mouse models using traditional gene-to-gene comparison ...

Visualization and Quantification of Mesenchymal Cell Adipogenic Differentiation Potential with a Lineage Specific Marker

Several dyes are currently available for use in detecting differentiation of mesenchymal cells into adipocytes. Dyes, such as Oil Red O, are cheap, easy to use and widely utilized by laboratories analyzing the adipogenic potential of mesenchymal cells. However, they are not specific to changes in gene transcription. We have developed a gene-specific differentiation assay to analyze when a mesenchymal cell has switched its fate to an adipogenic lineage. Immuno-labelling against fatty acid binding protein-4 (FABP4), a lineage-specific marker of adipogenic differentiation, enabled visualization and quantification of differentiated cells. The ability to quantify adipogenic differentiation potential of mesenchymal cells in a 96 well microplate format has promising implications for a number of applications. Hundreds of clinical trials involve the use of adult mesenchymal stromal cells and it is currently difficult to correlate therapeutic outcomes within and especially between such clinical trials. This simple high-throughput FABP4 assay provides a quantitative assay for assessing the differentiation potential of patient-derived cells and is a robust tool for comparing different isolation and expansion methods. This is particularly important given the increasing recognition of the heterogeneity of the cells being administered to patients in mesenchymal cell products. The assay also has potential utility in high throughput drug screening, particularly in obesity and pre-diabetes research.

Traditional methods of assessing adipogenic differentiation are cheap and easy to use, but are not specific to changes in gene expression. We have developed an assay to quantify mesenchymal cell differentiation into mature adipocytes using a lineage specific marker. This assay has diverse applications across basic research and clinical medicine.

Several dyes are currently available for use in detecting differentiation of mesenchymal cells into adipocytes. Dyes, such as Oil Red O, are cheap, easy ...