We thank Dr. Yuval Reiss and Dr. William Breuer for critically reviewing the manuscript and Omri Alfassy for helping in the development of the Ura3-GFP screen assay. We also thank Dr. M. Hochstrasser and Dr. R. Kulka for plasmids and strains. This work was funded by the Israeli Academy of Sciences (grant 786/08) and by the United States-Israel Binational Scientific foundation (grant 2011253).

1. Cell Culture
<ol>
	<li>Transform the appropriate auxotrophic yeast cells, such as Try467 (Table 2), with a plasmid containing (a) a URA3-degron fusion and (b) an additional metabolic marker for plasmid selection and maintenance. 
	NOTE: An example of a suitable plasmid is YDpK-MET25p-Deg1-FLAG-Vma12-Ura3 (LYS2) (Deg1-UV). This is a yeast integrative plasmid containing a fusion protein comprising of Deg1 &#8212; a degron derived from the yeast transcription factor Mat217, FLAG epitope &#8212; for detection by immunoblotting, Vma12 &#8212; a stable ER protein, and Ura315,18 (Figure 3A). (See Table 3 for plasmids used in this study and for additional examples of suitable plasmids.)</li>
	<li>For plasmid selection and maintenance, keep cells in agar plates under a suitable Synthetic Defined (SD) medium lacking amino acid selection markers19 (For example, Deg1-UV is selected and maintained under SD-LYS selective media).</li>
	<li>Grow cells O/N at 30 &#176;C in a suitable selective SD medium for plasmid maintenance until a stationary phase is reached. Grow the cells in test tubes or in a 96-well plate, depending on the number of samples to be examined (section 2).</li>
</ol>
2. Cell Preparation for Analysis
<ol>
	<li>When a small number of samples (N&#8804;15) are to be assayed, dilute the cells and replace the medium as follows:
	<ol>
		<li>Dilute 50 &#181;l of cells from an O/N culture with 150 &#181;l of SD medium per well in a 96-well plate (clear bottom). Note, the first sample is designated as blank contains medium only.</li>
		<li>Determine the OD600 values of the samples in the 96-well plate using a microplate reader.</li>
		<li>Calculate the actual OD600 in each well by multiplying the OD600 reading by the dilution factor (x4), from which the value of the blank reading is subtracted. Normalize the resulting values by dividing by 0.55 to obtain a calculated path-length of 1 cm according to the Beer-Lambert law. Note, this value is constant when measuring the OD600 of 200 &#181;l of cells in a standard 96-well plate.</li>
		<li>Calculate the exact volume needed for obtaining yeast cells at amount equivalent to OD600 of 0.25 and transfer it to an Eppendorf tube.</li>
		<li>Spin down the cells at high speed (12,000 x g) for 1 min.</li>
		<li>Remove the supernatant and resuspend the cells in 1 ml of the appropriate selective medium (see section 3.1) to obtain OD600 of 0.25.</li>
		<li>Transfer 200 &#181;l of the diluted strains to a new well in a 96-well plate.</li>
	</ol>
	</li>
	<li>When a large number of samples (N&#62;15) are to be tested, dilute the cells and replace the medium without prior OD600 measurement, as follows:
	<ol>
		<li>Transfer 10 &#956;l of stationary cells grown O/N in a 96-well plate into a new 96-well plate containing 190 &#956;l (dilution 1:20) of the appropriate selective media (see section 3.1).</li>
	</ol>
	</li>
</ol>
3. Growth Kinetics in Liquid Culture Under Selective Conditions (GiLS)
<ol>
	<li>Use the following media for growth measurements using the Ura3-degron reporter:
	<ol>
		<li>For positive controls of yeast growth under non-restrictive conditions, use plasmid selective SD media (see section 1.2). If no plasmid selection is required, for example, when using an integrative plasmid such as Deg1-UV, SD medium containing all necessary amino acids (SD complete) can be used.</li>
		<li>For experimental samples measuring growth under restrictive conditions, use SD-URA medium.</li>
	</ol>
	</li>
	<li>Set a multimode microplate reader to: an incubation temperature of 30 &#176;C, OD600 measurement intervals of 15 min, and an orbital and linear shaking cycles of 1 min every seven min. 
	NOTE: This dual-mode shaking was optimized to obtain homogenous distribution of cells; however, other shaking modes or even no shaking may work as well.</li>
	<li>Incubate the cells at 30 &#176;C in a microplate reader O/N or until cells have reached the stationary phase (12-24 hr).</li>
	<li>Export the raw data to a spreadsheet file.</li>
	<li>Determine yeast growth kinetics using MDTcalc, a customized software program that calculates the minimal time (in hr) for cells to double their population size (Minimal Doubling Time (MDT); for details see section 4).</li>
</ol>
4. Calculation of Minimal Doubling Time (MDT): Principles of the MDTcalc Algorithm

NOTE: Principles of the MDTcalc algorithm, using a representative sample of Try467 yeast cells (Table 2) grown in SD complete media, are illustrated in Table 1 and Figure 1, showing a data spreadsheet and growth plots, respectively.

<ol>
	<li>Subtract OD600 blank values, obtained in the respective well, from each of the readings obtained in the sample well. Divide the resulting differences by 0.55 (for 96-well plates) to correct for the light path length. Plot the final values (Table 1, Trans.) against time to produce the actual yeast growth curve (OD600/hr) (Figure 1A).</li>
	<li>Calculate log2 (OD600) for each of the transformed values to convert the logarithmic growth phase into a linear curve (Figure 1B).</li>
	<li>Calculate the slope of a 10 time-points interval (N=10) starting at time 0 and moving one time-point at a time until N&#60;10 (Table 1, Slope; Figure 1C).</li>
	<li>Calculate the inverse value of each slope to obtain the time required for the cell population to double (Table 1, 1/Slope; Figure 1C). Calculate the minimal 1/Slope value to determine the MDT (Table 1, black rectangle; Figure 1C). Extract the calculated MDT for cells in the sample (Table 1, 1/Slope, black rectangle) from the selected time interval (Table 1, outlined by red rectangle, Figures 1B, 1D). 
	NOTE: The rate of cell growth on SD-URA medium is inversely proportional to the MDT.</li>
</ol>
5. Using MDTcalc
<ol>
	<li>Copy the supplemented program files into a designated folder in the computer.</li>
	<li>Make sure the spreadsheet file containing the growth data is saved and closed. Open the MDTcalc application program to see the start screen appears.
	<ol>
		<li>Insert the required information, as demonstrated in Figure 2:
		<ol>
			<li>Under &#39;File path&#39;, click on the rectangle on the right to locate the spreadsheet file.</li>
			<li>Under &#39;Sheet name&#39;, write the spreadsheet name where the raw data is located.</li>
			<li>Under &#39;Starting position&#39;, insert the spreadsheet coordinate of time 0 of the first sample.</li>
			<li>Under &#39;Time column&#39;, insert the letter defining the location of the time point column (time should be provided in seconds).</li>
			<li>Under &#39;Blank column&#39;, insert the letter defining the location of the blank column (usually but not necessarily in well A1 of the 96-well plate).</li>
			<li>Under &#39;OD value&#39;, choose the minimal transformed OD600 value required for the initiation of MDT calculation (usually 0.15-0.25). Setting this value prevents calculations of MDT for cultures in lag phase due to excessive dilution so that MDT is calculated only for samples that reach the defined OD600 value or higher.</li>
		</ol>
		</li>
		<li>Once the last value has been entered, press the &#39;calculate&#39; button at the bottom of the screen. Ensure that the progress bar on the right gradually changes to green. Do not open the spreadsheet file during the calculation process.</li>
		<li>Export the two sets of data that appear automatically on the screen at the completion of the MDT calculation into a spreadsheet. Ensure that the data includes: (a) the MDT value for each well that passes the minimal OD value test (as set in section 5.2.1.6) and (b) the initial time point of the interval from which the MDT was calculated (Start time).</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

Here we describe an assay based on cell growth for determining relative protein degradation rates, termed &#39;Growth kinetics in Liquid culture under Selective conditions&#39; (GiLS). The GiLS assay has several advantages: It is simple to set up, data acquisition and analysis is straightforward and it is extremely modular. Consequently, GiLS can be applied simultaneously to multiple samples in a user friendly multi-well plate format that can be adapted to automation for high throughput applications. Most importantly, Gi...

The ubiquitin-proteasome degradation system is a major regulatory machine, which has been implicated in the maintenance of protein homeostasis in all eukaryotes. The UPS initially conjugates multiple ubiquitin molecules to a target protein after which the poly-ubiquitin-tagged protein is degraded by the 26S proteasome. In most cases, the rate limiting step for ubiquitin mediated degradation is substrate ubiquitylation, mediated by E2 conjugating enzymes and E3 ligating enzymes (E3 Ligases)1. Consequently, intracellular stability of specific proteins reflects their susceptibility to ubiquitin-conjugation and the activity of their cognate ubiquitylation enzymes.
E3 ligases are the principal substrate recognition components of the UPS. As such, these enzymes recognize degrons within their substrates that are either absent or not exposed in their stable counterparts 2. For example, many regulators of the cell cycle must be synthesized and degraded in a temporally specific manner in order to keep cell cycle progression in order. The degradation of these proteins is often controlled by phosphorylation, mediated by cell-signaling regulated kinases 3,4. On the other hand, aberrantly-folded proteins are recognized through cryptic degrons. These are regions that are normally hidden in the native structure and are exposed upon structure perturbation. Such degrons include hydrophobic domains 5-7 and&#160;intrinsically disordered segments8.&#160;
Since the seminal discovery of the ubiquitin-system for protein degradation and characterization of its fundamentals in reticulocyte lysates9, yeast genetics was instrumental in discovering many of the components of the ubiquitin system10. The success of yeast as a model organism for systematic analysis of protein degradation by the UPS is mainly due to the fact that the UPS is highly conserved in all eukaryotes4, coupled with their amenability as an experimental system. Indeed, yeast-based systems are commonly employed to decipher the mechanisms of action of the ubiquitylation machinery.
Studying protein degradation by biochemical means usually requires preparation of cell extracts. While animal cell proteins can be extracted under relatively mild conditions that preserve protein interactions and function, the presence of a robust cell wall in yeast11 requires considerably harsher disruption conditions which may affect protein recovery. Indeed, different procedures for yeast cell disruption vary considerably in their capacity to recover intact proteins in amounts that correctly represent their relative cellular abundance. Further inaccuracy is inherent in the different methods employed for determining degradation rates of specific proteins: Metabolic labeling-based &#39;pulse-chase&#39; experiments followed by immunoprecipitation, to isolate specific proteins12, is often not strictly quantitative. Thus, when protein degradation is compared by this method, extra caution should be exercised in interpreting the results. To circumvent this drawback, an alternative cycloheximide (CHX) chase assay can be employed12. In this assay, the translation inhibitor is added to cell cultures and temporal changes in protein steady-state levels are subsequently monitored. Nevertheless, the usage of CHX is limited to proteins with relatively short half-lives (&#60; 90 min), as long-term inhibition of protein synthesis is cytotoxic. Notably, both of the above-mentioned assays require the use of protein-specific antibodies, which are not always available.
To overcome these technical limitations, researchers have developed several approaches that do not require cell extraction and direct protein handling. One approach is based on the establishment of auxotrophic yeast strains, obtained by the deletion of genes encoding essential metabolic enzymes. Such genes include HIS3, LEU2, LYS2 and TRP1, encoding for enzymes required for amino acid biosynthesis, as well as URA3 that encodes OMP decarboxylase (Ura3), an essential enzyme of pyrimidine ribonucleotide biosynthesis. Ura3 has been widely used in protein degradation studies. In these assays, constitutive expression of Ura3 rescues growth of ura3 cells in uracil-deficient medium13. Consequently, destabilizing Ura3 through the fusion of a degron can diminish cell growth on minimal medium lacking uracil. This method has been used in various protein degradation studies, including the identification of degradation determinants5, E3 ligases14 and auxiliary ubiquitylation factors15 and the discovery of novel UPS degrons16. All of these methods employed cell growth on agar plates as assay readout. However, the growth criterion (positive/negative growth), while robust and efficient, is mostly qualitative and does not provide quantitative information that is important for evaluating a degron&#39;s potency or the relative contribution of various auxiliary degradation factors.
We have therefore developed and utilized yeast vectors and screening methods enabling systematic and quantitative analysis of protein degradation by the URA3-degron fusion system. The protocol is based on an easy-to-handle assay that measures Growth kinetics in Liquid culture under Selective conditions (GiLS) and on the generation of standard growth curves. Yeast growth kinetics are characterized by three main phases &#8212; the lag, the exponential (log) and the stationary phase. Calculation of yeast replication kinetics during the log phase under selective conditions, which is determined by the levels of expression of the Ura3-degron, provides an unbiased quantitative measurement of protein degradation. This method can be applied to measuring and comparing degradation rates of multiple UPS substrates simultaneously in multiple strains and under various conditions.

<table border="0" cellpadding="0" cellspacing="0" width="790">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:184px;">Name of Material/ Equipment</td>
			<td style="width:149px;">Company</td>
			<td style="width:119px;">Catalog Number</td>
			<td style="width:339px;">Comments/Description</td>
		</tr>
		<tr height="49">
			<td height="49" style="height:49px;width:184px;">Difco yeast nitrogen base w/o amino acids and ammonium sulfate</td>
			<td>BD Biosciences</td>
			<td>233520</td>
			<td rowspan="6" style="width:339px;">For yeast growth on SD minimal media.&#160; Amino acids to be supplied are: Arginine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ammonium sulfate</td>
			<td>Sigma - Aldrich</td>
			<td>A4418</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Glucose</td>
			<td>Sigma - Aldrich</td>
			<td>16325</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Adenine</td>
			<td>Sigma - Aldrich</td>
			<td>A8626</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Uracil</td>
			<td>Sigma - Aldrich</td>
			<td>U0750</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Amino acids</td>
			<td>Highest purity available&#160;</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:184px;">96 well plates</td>
			<td style="width:149px;">Nunc</td>
			<td style="width:119px;">167008</td>
			<td>Any other compatible brand can be used</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:184px;">Cyclohexamide&#160;</td>
			<td style="width:149px;">Sigma - Aldrich</td>
			<td style="width:119px;">C7698</td>
			<td>Working conc. 0.5 mg/ml</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:184px;">Infinite 200 PRO series</td>
			<td style="width:149px;">Tecan</td>
			<td style="width:119px;"></td>
			<td style="width:339px;">For yeast incubation and OD 600 measurements. Any other compatible temp-controled reader can be used</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:184px;">MDTcalc</td>
			<td style="width:149px;"></td>
			<td style="width:119px;"></td>
			<td>Experimental software</td>
		</tr>
	</tbody>
</table>

reporter-based growth assay for systematic analysis of protein degradation

Protein degradation by the ubiquitin-proteasome system (UPS) is a major regulatory mechanism for protein homeostasis in all eukaryotes. The standard approach to determining intracellular protein degradation relies on biochemical assays for following the kinetics of protein decline. Such methods are often laborious and time consuming and therefore not amenable to experiments aimed at assessing multiple substrates and degradation conditions. As an alternative, cell growth-based assays have been developed, that are, in their conventional format, end-point assays that cannot quantitatively determine relative changes in protein levels.
Here we describe a method that faithfully determines changes in protein degradation rates by coupling them to yeast cell-growth kinetics. The method is based on an established selection system where uracil auxotrophy of URA3-deleted yeast cells is rescued by an exogenously expressed reporter protein, comprised of a fusion between the essential URA3 gene and a degradation determinant (degron). The reporter protein is designed so that its synthesis rate is constant whilst its degradation rate is determined by the degron. As cell growth in uracil-deficient medium is proportional to the relative levels of Ura3, growth kinetics are entirely dependent on the reporter protein degradation.
This method accurately measures changes in intracellular protein degradation kinetics. It was applied to: (a) Assessing the relative contribution of known ubiquitin-conjugating factors to proteolysis (b) E2 conjugating enzyme structure-function analyses (c) Identification and characterization of novel degrons. Application of the degron-URA3-based system transcends the protein degradation field, as it can also be adapted to monitoring changes of protein levels associated with functions of other cellular pathways.

Investigating the role of enzymes of the Doa10 pathway in the degradation of a reporter substrate 
To test the validity of the GiLS method it was compared to a traditional degradation assay. This experiment assesses the relative contribution of components of the ER-membrane localized Doa10 E3-ligase complex20,21 to the degradation of the protein quality control reporter substrate Deg1-VU (Figure 3A). The Deg1-VU plasmid was integra...

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Reporter-based Growth Assay for Systematic Analysis of Protein Degradation

Here we describe a robust biological assay for quantifying the relative rate of proteolysis by the ubiquitin-proteasome system. The assay readout is yeast growth rate in liquid culture, which is dependent on the cellular levels of a reporter protein comprising a degradation signal fused to an essential metabolic marker.

Protein degradation by the ubiquitin-proteasome system (UPS) is a major regulatory mechanism for protein homeostasis in all eukaryotes. The standard ...

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10.6K vues.  The Hebrew University of Jerusalem. Here we describe a robust biological assay for quantifying the relative rate of proteolysis by the ubiquitin-proteasome system. The assay readout is yeast growth rate in liquid culture, which is dependent on the cellular levels of a reporter protein comprising a degradation signal fused to an essential metabolic marker.

Vidéo: Reporter-based Growth Assay for Systematic Analysis of Protein Degradation

Actin Co-Sedimentation Assay; for the Analysis of Protein Binding to F-Actin

The actin cytoskeleton within the cell is a network of actin filaments that allows the movement of cells and cellular processes, and that generates tension and helps maintains cellular shape.  Although the actin cytoskeleton is a rigid structure, it is a dynamic structure that is constantly remodeling.  A number of proteins can bind to the actin cytoskeleton.  The binding of a particular protein to F-actin is often desired to support cell biological observations or to further understand dynamic processes due to remodeling of the actin cytoskeleton. The actin co-sedimentation assay is an in vitro assay routinely used to analyze the binding of specific proteins or protein domains with F-actin.  The basic principles of the assay involve an incubation of the protein of interest (full length or domain of) with F-actin, ultracentrifugation step to pellet F-actin and analysis of the protein co-sedimenting with F-actin.  Actin co-sedimentation assays can be designed accordingly to measure actin binding affinities and in competition assays.

Proteins bind to filamentous actin (F-actin) through distinct actin binding modules. In this video we demonstrate the procedure of actin co-sedimentation, which is an in vitro assay routinely used to analyze proteins or specific domains that bind F-actin.

The actin cytoskeleton within the cell is a network of actin filaments that allows the movement of cells and cellular processes, and that generates ...

A Neuronal and Astrocyte Co-Culture Assay for High Content Analysis of Neurotoxicity

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing measurement of multiple cellular phenotypes within a single assay. In this study, we utilized HCA to develop a novel assay for neurotoxicity. Neurotoxicity assessment represents an important part of drug safety evaluation, as well as being a significant focus of environmental protection efforts. Additionally, neurotoxicity is also a well-accepted in vitro marker of the development of neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Recently, the application of HCA to neuronal screening has been reported. By labeling neuronal cells with &beta;III-tubulin, HCA assays can provide high-throughput, non-subjective, quantitative measurements of parameters such as neuronal number, neurite count and neurite length, all of which can indicate neurotoxic effects. However, the role of astrocytes remains unexplored in these models. Astrocytes have an integral role in the maintenance of central nervous system (CNS) homeostasis, and are associated with both neuroprotection and neurodegradation when they are activated in response to toxic substances or disease states. GFAP is an intermediate filament protein expressed predominantly in the astrocytes of the CNS. Astrocytic activation (gliosis) leads to the upregulation of GFAP, commonly accompanied by astrocyte proliferation and hypertrophy. This process of reactive gliosis has been proposed as an early marker of damage to the nervous system. The traditional method for GFAP quantitation is by immunoassay. This approach is limited by an inability to provide information on cellular localization, morphology and cell number. We determined that HCA could be used to overcome these limitations and to simultaneously measure multiple features associated with gliosis - changes in GFAP expression, astrocyte hypertrophy, and astrocyte proliferation - within a single assay. In co-culture studies, astrocytes have been shown to protect neurons against several types of toxic insult and to critically influence neuronal survival. Recent studies have suggested that the use of astrocytes in an in vitro neurotoxicity test system may prove more relevant to human CNS structure and function than neuronal cells alone. Accordingly, we have developed an HCA assay for co-culture of neurons and astrocytes, comprised of protocols and validated, target-specific detection reagents for profiling &beta;III-tubulin and glial fibrillary acidic protein (GFAP). This assay enables simultaneous analysis of neurotoxicity, neurite outgrowth, gliosis, neuronal and astrocytic morphology and neuronal and astrocytic development in a wide variety of cellular models, representing a novel, non-subjective, high-throughput assay for neurotoxicity assessment. The assay holds great potential for enhanced detection of neurotoxicity and improved productivity in neuroscience research and drug discovery.

This article describes a novel protocol and reagent set designed for sensitive measurement of neurotoxic effects of compounds and treatments on co-cultures of neurons and astrocytes using high content analysis. Results demonstrate that high content analysis represents an exciting novel technology for neurotoxicity assessment.

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing ...

Using the GELFREE 8100 Fractionation System for Molecular Weight-Based Fractionation with Liquid Phase Recovery

The GELFREE 8100 Fractionation System is a novel protein fractionation system designed to maximize protein recovery during molecular weight based fractionation. The system is comprised of single-use, 8-sample capacity cartridges and a benchtop GELFREE Fractionation Instrument. During separation, a constant voltage is applied between the anode and cathode reservoirs, and each protein mixture is electrophoretically driven from a loading chamber into a specially designed gel column gel. Proteins are concentrated into a tight band in a stacking gel, and separated based on their respective electrophoretic mobilities in a resolving gel. As proteins elute from the column, they are trapped and concentrated in liquid phase in the collection chamber, free of the gel. The instrument is then paused at specific time intervals, and fractions are collected using a pipette. This process is repeated until all desired fractions have been collected. If fewer than 8 samples are run on a cartridge, any unused chambers can be used in subsequent separations.
This novel technology facilitates the quick and simple separation of up to 8 complex protein mixtures simultaneously, and offers several advantages when compared to previously available fractionation methods. This system is capable of fractionating up to 1mg of total protein per channel, for a total of 8mg per cartridge. Intact proteins over a broad mass range are separated on the basis of molecular weight, retaining important physiochemical properties of the analyte. The liquid phase entrapment provides for high recovery while eliminating the need for band or spot cutting, making the fractionation process highly reproducible1.

The accompanying video describes the use of the GELFREE 8100 Fractionation System, which partitions complex protein samples on the basis of molecular weight and recovers the fractions in liquid phase. The video describes how the technology works, how it is used, and provides resultant data, with polyacrylamide gel electrophoresis analysis of fractionated bovine liver homogenate.

The GELFREE 8100 Fractionation System is a novel protein fractionation system designed to maximize protein recovery during molecular weight based ...

Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth

Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software.  Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT.  To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images.  To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time.  The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion.  

Video bioinformatics is the automated processing, analysis, understanding, and data mining of biological spatio-temporal data extracted from microscopic videos. The purpose of this article is to demonstrate a method for measuring human embryonic stem cell colony growth using a video bioinformatics method.

Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer ...

Growth-based Determination and Biochemical Confirmation of Genetic Requirements for Protein Degradation in Saccharomyces cerevisiae

Regulated protein degradation is crucial for virtually every cellular function. Much of what is known about the molecular mechanisms and genetic requirements for eukaryotic protein degradation was initially established in Saccharomyces cerevisiae. Classical analyses of protein degradation have relied on biochemical pulse-chase and cycloheximide-chase methodologies. While these techniques provide sensitive means for observing protein degradation, they are laborious, time-consuming, and low-throughput. These approaches are not amenable to rapid or large-scale screening for mutations that prevent protein degradation. Here, a yeast growth-based assay for the facile identification of genetic requirements for protein degradation is described. In this assay, a reporter enzyme required for growth under specific selective conditions is fused to an unstable protein. Cells lacking the endogenous reporter enzyme but expressing the fusion protein can grow under selective conditions only when the fusion protein is stabilized (i.e. when protein degradation is compromised). In the growth assay described here, serial dilutions of wild-type and mutant yeast cells harboring a plasmid encoding a fusion protein are spotted onto selective and non-selective medium. Growth under selective conditions is consistent with degradation impairment by a given mutation. Increased protein abundance should be biochemically confirmed. A method for the rapid extraction of yeast proteins in a form suitable for electrophoresis and western blotting is also demonstrated. A growth-based readout for protein stability, combined with a simple protocol for protein extraction for biochemical analysis, facilitates rapid identification of genetic requirements for protein degradation. These techniques can be adapted to monitor degradation of a variety of short-lived proteins. In the example presented, the His3 enzyme, which is required for histidine biosynthesis, was fused to Deg1-Sec62. Deg1-Sec62 is targeted for degradation after it aberrantly engages the endoplasmic reticulum translocon. Cells harboring Deg1-Sec62-His3 were able to grow under selective conditions when the protein was stabilized.

Growth-based Determination and Biochemical Confirmation of Genetic Requirements for Protein Degradation in Saccharomyces cerevisiae

This article describes a yeast growth-based assay for the determination of genetic requirements for protein degradation. It also demonstrates a method for rapid extraction of yeast proteins, suitable for western blotting to biochemically confirm degradation requirements. These techniques can be adapted to monitor degradation of a variety of proteins.

Regulated protein degradation is crucial for virtually every cellular function. Much of what is known about the molecular mechanisms and genetic ...

Cycloheximide Chase Analysis of Protein Degradation in Saccharomyces cerevisiae

Regulation of protein abundance is crucial to virtually every cellular process. Protein abundance reflects the integration of the rates of protein synthesis and protein degradation. Many assays reporting on protein abundance (e.g., single-time point western blotting, flow cytometry, fluorescence microscopy, or growth-based reporter assays) do not allow discrimination of the relative effects of translation and proteolysis on protein levels. This article describes the use of cycloheximide chase followed by western blotting to specifically analyze protein degradation in the model unicellular eukaryote, Saccharomyces cerevisiae (budding yeast). In this procedure, yeast cells are incubated in the presence of the translational inhibitor cycloheximide. Aliquots of cells are collected immediately after and at specific time points following addition of cycloheximide. Cells are lysed, and the lysates are separated by polyacrylamide gel electrophoresis for western blot analysis of protein abundance at each time point. The cycloheximide chase procedure permits visualization of the degradation kinetics of the steady state population of a variety of cellular proteins. The procedure may be used to investigate the genetic requirements for and environmental influences on protein degradation.

Cycloheximide Chase Analysis of Protein Degradation in Saccharomyces cerevisiae

Protein abundance reflects the rates of both protein synthesis and protein degradation. This article describes the use of cycloheximide chase followed by western blotting to analyze protein degradation in the model unicellular eukaryote, Saccharomyces cerevisiae (budding yeast).

Regulation of protein abundance is crucial to virtually every cellular process. Protein abundance reflects the integration of the rates of protein ...

Assays for the Degradation of Misfolded Proteins in Cells

Protein misfolding and aggregation are associated with various neurodegenerative diseases. Cellular mechanisms that recognize and degrade misfolded proteins may serve as potential therapeutic targets. To distinguish degradation of misfolding-prone proteins from other mechanisms that regulate their levels, one important method is to measure protein half-life in cells. However, this can be challenging because misfolding-prone proteins may exist in different forms, including the native form and misfolded forms of distinct characteristics. Here we describe assays to examine the half-life of misfolded proteins in mammalian cells using a highly aggregation-prone protein, Ataxin-1 with an extended polyglutamine (polyQ) stretch, and a conformationally unstable luciferase mutant as models. Cycloheximide chase is combined with cell fractionation to examine the turnover rate of misfolding-prone proteins in various cellular fractions. We further depict a fluorescence-based assay using an enhanced green fluorescence protein (EGFP)-fusion of the luciferase mutant, which can be adapted for high throughput screening on a microplate-reader.

This report describes protocols for measuring degradation rates of misfolded proteins by either western blot or fluorescence-based assays. The methods can be applied to analysis of other misfolded proteins and for high throughput screening.

Protein misfolding and aggregation are associated with various neurodegenerative diseases. Cellular mechanisms that recognize and degrade misfolded ...

A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling

An experimental design mimicking natural plant-microbe interactions is very important to delineate the complex plant-microbe signaling processes. Arabidopsis thaliana-Agrobacterium tumefaciens provides an excellent model system to study bacterial pathogenesis and plant interactions. Previous studies of plant-Agrobacterium interactions have largely relied on plant cell suspension cultures, the artificial wounding of plants, or the artificial induction of microbial virulence factors or plant defenses by synthetic chemicals. However, these methods are distinct from the natural signaling in planta, where plants and microbes recognize and respond in spatial and temporal manners. This work presents a hydroponic cocultivation system where intact plants are supported by metal mesh screens and cocultivated with Agrobacterium. In this cocultivation system, no synthetic phytohormone or chemical that induces microbial virulence or plant defense is supplemented. The hydroponic cocultivation system closely resembles natural plant-microbe interactions and signaling homeostasis in planta. Plant roots can be separated from the medium containing Agrobacterium, and the signaling and responses of both the plant hosts and the interacting microbes can be investigated simultaneously and systematically. At any given timepoint/interval, plant tissues or bacteria can be harvested separately for various &#34;omics&#34; analyses, demonstrating the power and efficacy of this system. The hydroponic cocultivation system can be easily adapted to study: 1) the reciprocal signaling of diverse plant-microbe systems, 2) signaling between a plant host and multiple microbial species (i.e.&#160;microbial consortia or microbiomes), 3) how nutrients and chemicals are implicated in plant-microbe signaling, and 4) how microbes interact with plant hosts and contribute to plant tolerance to biotic or abiotic stresses.

The described hydroponic cocultivation system supports intact plants with metal mesh screens and cocultivates them with bacteria. Plant tissue, bacteria, and secreted molecules can then be separately harvested for downstream analyses, simultaneously allowing for the molecular responses of both plant hosts and interacting microbes or microbiomes to be investigated.

An experimental design mimicking natural plant-microbe interactions is very important to delineate the complex plant-microbe signaling processes. ...

Precise, High-throughput Analysis of Bacterial Growth

Bacterial growth is a central concept in the development of modern microbial physiology, as well as in the investigation of cellular dynamics at the systems level. Recent studies have reported correlations between bacterial growth and genome-wide events, such as genome reduction and transcriptome reorganization. Correctly analyzing bacterial growth is crucial for understanding the growth-dependent coordination of gene functions and cellular components. Accordingly, the precise quantitative evaluation of bacterial growth in a high-throughput manner is required. Emerging technological developments offer new experimental tools that allow updates of the methods used for studying bacterial growth. The protocol introduced here employs a microplate reader with a highly optimized experimental procedure for the reproducible and precise evaluation of bacterial growth. This protocol was used to evaluate the growth of several previously described Escherichia coli strains. The main steps of the protocol are as follows: the preparation of a large number of cell stocks in small vials for repeated tests with reproducible results, the use of 96-well plates for high-throughput growth evaluation, and the manual calculation of two major parameters (i.e., maximal growth rate and population density) representing the growth dynamics. In comparison to the traditional colony-forming unit (CFU) assay, which counts the cells that are cultured in glass tubes over time on agar plates, the present method is more efficient and provides more detailed temporal records of growth changes, but has a stricter detection limit at low population densities. In summary, the described method is advantageous for the precise and reproducible high-throughput analysis of bacterial growth, which can be used to draw conceptual conclusions or to make theoretical observations.

Quantitative evaluation of bacterial growth is essential to understanding microbial physiology as a systems-level phenomenon. A protocol for experimental manipulation and an analytical approach are introduced, allowing for precise, high-throughput analysis of bacterial growth, which is a key subject of interest in systems biology.

Bacterial growth is a central concept in the development of modern microbial physiology, as well as in the investigation of cellular dynamics at the ...

Luciferase Complementation Imaging Assay in Nicotiana benthamiana Leaves for Transiently Determining Protein-protein Interaction Dynamics

Protein-protein interactions are fundamental mechanisms for relaying signal transduction in most cellular processes; therefore, identification of novel protein-protein interaction pairs and monitoring protein interaction dynamics are of particular interest for revealing how plants respond to environmental factors and/or developmental signals. A plethora of approaches have been developed to examine protein-protein interactions, either in vitro or in vivo. Among them, the recently established luciferase complementation imaging (LCI) assay is the simplest and fastest method for demonstrating in vivo protein-protein interactions. In this assay, protein A or protein B is fused with the amino-terminal or carboxyl-terminal half of luciferase, respectively. When protein A interacts with protein B, the two halves of luciferase will be reconstituted to form a functional and active luciferase enzyme. Luciferase activity can be recorded with a luminometer or CCD-camera. Compared with other approaches, the LCI assay shows protein-protein interactions both qualitatively and quantitatively. Agrobacterium infiltration in Nicotiana benthamiana leaves is a widely used system for transient protein expression. With the combination of LCI and transient expression, these approaches show that the physical interaction between COP1 and SPA1 was gradually reduced after jasmonate treatment.

Luciferase Complementation Imaging Assay in Nicotiana benthamiana Leaves for Transiently Determining Protein-protein Interaction Dynamics

This manuscript describes an easy and rapid experimental procedure for determining protein-protein interactions based on the measurement of luciferase activity.

Protein-protein interactions are fundamental mechanisms for relaying signal transduction in most cellular processes; therefore, identification of novel ...