The authors thank Matthias Peter and his group at the Institute of Biochemistry at the ETH in Z&uuml;rich where these methods have been developed. This work has been supported by the Swiss National Science Foundation.

1. Microscopy Measurements
<ol>
	<li>Inoculate 5 ml of synthetic medium with yeast.</li>
	<li>Grow cells at 30 &#176;C overnight.</li>
	<li>Measure the OD600 of the overnight culture the next morning.</li>
	<li>Dilute overnight culture in 5 ml synthetic medium to OD600 0.05.</li>
	<li>Grow the diluted culture at 30 &#176;C for at least 4 hr.</li>
	<li>Prepare 3-fold concentrated (0.6 M) NaCl solution in synthetic medium.</li>
	<li>Prepare a 1 mg/ml solution of Concanavalin A (ConA) in PBS.</li>
	<li>Filtrate ~200 &#956;l of ConA solution into the well slide.</li>
	<li>Let stand for 30 min.</li>
	<li>Remove ConA solution.</li>
	<li>Add 150 &#956;l H2O to the well.</li>
	<li>Remove H2O.</li>
	<li>Measure OD600 of cell culture.</li>
	<li>Prepare 300 &#956;l of cell culture at OD600 = 0.02 in a 1.5 ml microtube.</li>
	<li>Sonicate the cells in a water bath for 45 sec.</li>
	<li>Vortex briefly the microtube.</li>
	<li>Sonicate the cells in a water bath for 45 sec.</li>
	<li>Vortex briefly the microtube.</li>
	<li>Add 200 &#956;l of cell culture to the well.</li>
	<li>Wait 30 min to let the cells settle to the bottom of the well.</li>
	<li>Place the well slide on the microscope.</li>
	<li>Select the illumination settings for the fluorescent channel to be recorded.</li>
	<li>Select the illumination settings for two bright field images (one slightly out of focus: 3 &#956;m below the focal plane to allow for a proper segmentation of the cells).</li>
	<li>Select the time intervals for the time-lapse measurement</li>
	<li>Select the fields of view to image.</li>
	<li>Start the acquisition of a few frames.</li>
	<li>Pause the acquisition to add the 100 &#956;l of 0.6 M NaCl medium.</li>
	<li>Resume imaging.</li>
</ol>
2. Flow Cytometry Measurements
<ol>
	<li>Inoculate 5 ml of synthetic medium with yeast.</li>
	<li>Grow at 30 &#176;C overnight.</li>
	<li>Measure the OD600 of the overnight culture the next morning.</li>
	<li>Dilute overnight culture in 5 ml synthetic medium to OD600 0.1.</li>
	<li>Grow at 30 &#176;C for at least 4 hr to reach an OD600 of 0.2-0.4.</li>
	<li>Prepare cycloheximide solution 1 mg/ml in H2O.</li>
	<li>Prepare 3-fold concentrated (0.6 M) NaCl solution in synthetic medium.</li>
	<li>Prepare one 1.5 ml microtube with 100 &#956;l of 0.6 M NaCl medium for each time point to be measured.</li>
	<li>At time 0, add 200 &#956;l of cell culture to each microtube.</li>
	<li>Incubate with shaking at 30 &#176;C.</li>
	<li>At time T, add 30 &#956;l cycloheximide to a microtube.</li>
	<li>Repeat step 2.11 for all the desired time points.</li>
	<li>Incubate all microtubes for at least 45 min and up to 3 hr at 30 &#176;C with shaking.</li>
	<li>Prepare FACS tubes with 400 &#956;l PBS.</li>
	<li>Sonicate the cells in water bath for 1 min.</li>
	<li>Vortex briefly the microtubes.</li>
	<li>Sonicate the cells in water bath for 1 min.</li>
	<li>Vortex briefly the microtubes.</li>
	<li>Add 100 &#956;l cell culture from each microtube to its corresponding FACS tube.</li>
	<li>Select the 488 nm excitation laser and 530/30 nm bandpass filter for detection.</li>
	<li>Test non-expressing and fully expressing sample to verify if they fall in the detector sensitivity range.</li>
	<li>Measure 10,000 cells for each sample acquired.</li>
</ol>

<ol>
	<li>Gasch, A. P., Spellman, P. T., 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=Genomic+expression+programs+in+the+response+of+yeast+cells+to+environmental+changes.">Genomic expression programs in the response of yeast cells to environmental changes.</a> Molecular biology of the cell. 11 (12), 4241-4257 (2000).</li><li>de Nadal, E., Zapater, M., Alepuz, P. M., Sumoy, L., Mas, G., Posas, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+MAPK+Hog1+recruits+Rpd3+histone+deacetylase+to+activate+osmoresponsive+genes.">The MAPK Hog1 recruits Rpd3 histone deacetylase to activate osmoresponsive genes.</a> Nature. 427 (6972), 370-374 (2004).</li><li>Ghaemmaghami, S., Huh, W. -. K., 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=Global+analysis+of+protein+expression+in+yeast.">Global analysis of protein expression in yeast.</a> Nature. 425 (6959), 737-741 (2003).</li><li>Wu, J. -. Q., Pollard, T. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Counting+cytokinesis+proteins+globally+and+locally+in+fission+yeast.">Counting cytokinesis proteins globally and locally in fission yeast.</a> Science. 310 (5746), 310-314 (2005).</li><li>Colman-Lerner, A., Gordon, 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=Regulated+cell-to-cell+variation+in+a+cell-fate+decision+system.">Regulated cell-to-cell variation in a cell-fate decision system.</a> Nature. 437 (7059), 699-706 (2005).</li><li>Acar, M., Becskei, A., van Oudenaarden, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enhancement+of+cellular+memory+by+reducing+stochastic+transitions.">Enhancement of cellular memory by reducing stochastic transitions.</a> Nature. 435 (7039), 228-232 (2005).</li><li>Pelet, S., Rudolf, F., Nadal-Ribelles, M., de Nadal, E., Posas, F., Peter, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transient+activation+of+the+HOG+MAPK+pathway+regulates+bimodal+gene+expression.">Transient activation of the HOG MAPK pathway regulates bimodal gene expression.</a> Science. 332 (6030), 732-735 (2011).</li><li>de Nadal, E., Casadome, L., Posas, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeting+the+MEF2-like+transcription+factor+Smp1+by+the+stress-activated+Hog1+mitogen-activated+protein+kinase.">Targeting the MEF2-like transcription factor Smp1 by the stress-activated Hog1 mitogen-activated protein kinase.</a> Molecular and Cellular Biology. 23 (1), 229-237 (2003).</li><li>Elowitz, M. B., Levine, A. J., Siggia, E. D., Swain, P. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stochastic+gene+expression+in+a+single+cell.">Stochastic gene expression in a single cell.</a> Science. 297 (5584), 1183-1186 (2002).</li><li>Pelet, S., Dechant, R., Lee, S. S., van Drogen, F., Peter, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+integrated+image+analysis+platform+to+quantify+signal+transduction+in+single+cells.">An integrated image analysis platform to quantify signal transduction in single cells.</a> Integrative biology : quantitative biosciences from nano to macro. 4 (10), 1274-1282 (2012).</li><li>Carpenter, A. E., Jones, T. R., 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=CellProfiler:+image+analysis+software+for+identifying+and+quantifying+cell+phenotypes.">CellProfiler: image analysis software for identifying and quantifying cell phenotypes.</a> Genome biology. 7 (10), R100 (2006).</li><li>Chernomoretz, A., Bush, A., Yu, R., Gordon, A., Colman-Lerner, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+Cell-ID+1.4+with+R+for+microscope-based+cytometry.">Using Cell-ID 1.4 with R for microscope-based cytometry.</a> Current protocols in molecular biology. Chapter 14, Unit 14.18 (2008).</li><li>Dimopoulos, S., Mayer, C., Rudolf, F., Stelling, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+Single+Cell+Segmentation+in+a+Variety+of+Microscopy+Images.">Automatic Single Cell Segmentation in a Variety of Microscopy Images.</a> Current protocols in molecular biology. , (2012).</li><li>Miyawaki, A., Nagai, T., Mizuno, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+of+protein+fluorophore+formation+and+engineering.">Mechanisms of protein fluorophore formation and engineering.</a> Current Opinion in Chemical Biology. 7 (5), 557-562 (2003).</li><li>Hersen, P., McClean, M. N., Mahadevan, L., Ramanathan, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Signal+processing+by+the+HOG+MAP+kinase+pathway.">Signal processing by the HOG MAP kinase pathway.</a> Proceedings of the National Academy of Sciences of the United States of America. 105 (20), 7165-7170 (2008).</li><li>Pepperkok, R., Ellenberg, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+fluorescence+microscopy+for+systems+biology.">High-throughput fluorescence microscopy for systems biology.</a> Nature reviews Molecular cell biology. 7 (9), 690-696 (2006).</li></ol>

The authors declare that they have no competing financial interests.

Microscopy
The treatment of the well with ConA is an essential step to ensure a proper imaging of the cells. Because ConA has low solubility in PBS (5 mg/ml), the filtration process allows the removal of large aggregates that are present in the unfiltered solution and interfere with the imaging. Cells attach relatively strongly to the treated surface and the addition of the inducing solution should not disturb the localization of the cells, allowing for a continuous tracking before and after the ...

Signaling via transduction cascades often culminates in the expression of proteins. The characterization of this expression profile is a key element in understanding the function of biological pathways. The identification of the spectrum of up-regulated proteins and the dynamics of their activation can be achieved by various techniques such as micro-arrays, northern blots or western blots1-3. However, these techniques average the response of an entire population of cells. To understand the fine regulation of the expression of proteins, it is desirable to gather measurements at the single cell level. Ideally, these measurements should also provide quantitative data amenable to develop mathematical models of the underlying pathway.
Microscopy and flow cytometry are two techniques, which are ideally suited to deliver such quantitative single cell measurements. The endogenous tagging of proteins with a fluorescent protein can be used to quantify their expression level 4. However, since the addition of a large fluorescent moiety at the terminus of the protein can render it non-functional, it is often more desirable to generate specific expression reporters based on a promoter driving the expression of a fluorescent construct. This reporter protein is exogenous to the cellular system and therefore does not influence the signaling events that are taking place in the cell.
Both microscopy and flow cytometry have been widely used in the yeast signaling field. As examples; Colman-Lerner and co-workers correlated, in single cells, the expression of mating specific and constitutively expressed reporters by microscopy to quantify the noise in yeast mating signal transduction cascade5, Acar and colleagues used flow cytometry to study the regulatory network controlling the expression of the GAL genes6. In a previous study7, we have used a combination of these two techniques to study the expression output from the high osmolarity glycerol (HOG) pathway in budding yeast. This mitogen activated protein kinase (MAPK) pathway is triggered by hyper-osmotic stress. It results in the activation of the MAPK Hog1, which translocates to the nucleus of the cell to induce a transcriptional program resulting in the expression of roughly 300 genes. To study this process, we had engineered an expression reporter based on the STL1 promoter (a gene induced specifically in response to Hog1 activity8) driving the expression of a quadruple Venus fluorescent protein (pSTL1-qV). Flow cytometry measurements uncovered the presence of two populations of cells at intermediate stress level (0.1 M NaCl) with only a fraction of the population expressing the fluorescent reporter. We used microscopy to further investigate this behavior and discovered that this noise in protein expression was governed by intrinsic factors9. We could further observe that cells with a similar level of Hog1 activity could display strikingly different expression outcomes. The combination of these two techniques allowed us to demonstrate how the slow remodeling of stress response genes influenced the expression outcome at the single cell level7.
In this paper, we use the expression of the pSTL1-qV reporter induced by hyper-osmotic shock as an example of the quantification of protein expression by microscopy and flow cytometry. The same strain subjected to 0.2 M NaCl stress was studied with both techniques. This will allow us to highlight some key differences in these two highly complementary techniques.

<table border="1">
		<tbody>
		 <tr>
			 <td></td>
			 <td></td>
			 <td></td>
			 <td>Reagent</td>
		 </tr>
		 <tr>
			 <td>Yeast Nitrogen Base</td>
			 <td>ForMedium</td>
			 <td>CYN6202</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>CSM amino-acid mix</td>
			 <td>ForMedium</td>
			 <td>DCS0011</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>Concanavalin A</td>
			 <td>GE Healthcare</td>
			 <td>17-0450-01</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>Cycloheximide</td>
			 <td>Fluka Aldrich Sigma</td>
			 <td>C7698</td>
			 <td>Toxic</td>
		 </tr>
		 <tr>
			 <td>ySP9</td>
			 <td></td>
			 <td></td>
			 <td>W303Mata leu2::LEU2-pSTL1-quadrupleV enus</td>
		 </tr>
		 <tr>
			 <td>pSP34</td>
			 <td></td>
			 <td></td>
			 <td>pRS305 pSTL1 (-800 -0) - quadruple V enus</td>
		 </tr>
		 <tr>
			 <td></td>
			 <td></td>
			 <td></td>
			 <td>Material</td>
		 </tr>
		 <tr>
			 <td>Microscope</td>
			 <td>Nikon</td>
			 <td>Ti-Eclipse</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>Microscope control software</td>
			 <td>Micro-manager</td>
			 <td>Ver 1.4.11</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>Incubation chamber</td>
			 <td>LIS</td>
			 <td>The Box</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>Fluorescence light source</td>
			 <td>Lumencor</td>
			 <td>SpectraX</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>Camera</td>
			 <td>Hamamatsu</td>
			 <td>Flash 4.0</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>Flow cytometer</td>
			 <td>BD</td>
			 <td>FACS calibur</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>Sonicator bath</td>
			 <td>Telesonic</td>
			 <td>TUC-150</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>8-well-slide </td>
			 <td>Thermo Lab-tek</td>
			 <td>155409</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>96-well-plate</td>
			 <td>Matrical bioscience</td>
			 <td>MGB096-1-2-LG</td>
			 <td></td>
		 </tr>
		 <tr>
			 <td>FACS tube</td>
			 <td>BD Falcon</td>
			 <td>352054</td>
			 <td></td>
		 </tr>
		</tbody>
 </table>

temporal quantification of mapk induced expression in single yeast cells

The quantification of gene expression at the single cell level uncovers novel regulatory mechanisms obscured in measurements performed at the population level. Two methods based on microscopy and flow cytometry are presented to demonstrate how such data can be acquired. The expression of a fluorescent reporter induced upon activation of the high osmolarity glycerol MAPK pathway in yeast is used as an example. The specific advantages of each method are highlighted. Flow cytometry measures a large number of cells (10,000) and provides a direct measure of the dynamics of protein expression independent of the slow maturation kinetics of the fluorescent protein. Imaging of living cells by microscopy is by contrast limited to the measurement of the matured form of the reporter in fewer cells. However, the data sets generated by this technique can be extremely rich thanks to the combinations of multiple reporters and to the spatial and temporal information obtained from individual cells. The combination of these two measurement methods can deliver new insights on the regulation of protein expression by signaling pathways.

Microscopy
Yeast cells bearing the expression reporter pSTL1-qV (ySP97) were attached to the bottom of the well-slide and placed under the microscope. The cells were stimulated by the addition of stress medium directly into the well during the course of the imaging session. This allows us to acquire a few images of the cells before pathway induction and follow their fate after the stimulation. In the present case, the cells were followed for ~2 hr with a time interval of 10 mi...

Watch this Scientific Journal Video about Temporal Quantification of MAPK Induced Expression in Single Yeast Cells at JoVE.com

Temporal Quantification of MAPK Induced Expression in Single Yeast Cells

Two complementary methods based on flow cytometry and microscopy are presented which enable the quantification, at the single cell level, of the dynamics of gene expression induced by the activation of a MAPK pathway in yeast.

The quantification of gene expression at the  single cell level uncovers novel regulatory mechanisms obscured in measurements  performed at the population ...

temporal-quantification-mapk-induced-expression-single-yeast

Research

JoVE Journal

Biology

8.5K 次观看.  University of Lausanne. 基于流式细胞术和显微术的两个互补的方法给出，使定量基因表达的诱导通过MAPK途径在酵母的激活的动力学，在单细胞水平。 

视频: Temporal Quantification of MAPK Induced Expression in Single Yeast Cells

Vaccinia Virus Infection &amp; Temporal Analysis of Virus Gene Expression: Part 1

The family Poxviridae consists of large double-stranded DNA containing viruses that replicate exclusively in the cytoplasm of infected cells. Members of the orthopox genus include variola, the causative agent of human small pox, monkeypox, and vaccinia (VAC), the prototypic member of the virus family. Within the relatively large (~ 200 kb) vaccinia genome, three classes of genes are encoded: early, intermediate, and late. While all three classes are transcribed by virally-encoded RNA polymerases, each class serves a different function in the life cycle of the virus. Poxviruses utilize multiple strategies for modulation of the host cellular environment during infection. In order to understand regulation of both host and virus gene expression, we have utilized genome-wide approaches to analyze transcript abundance from both virus and host cells. Here, we demonstrate time course infections of HeLa cells with Vaccinia virus and sampling RNA at several time points post-infection. Both host and viral total RNA is isolated and amplified for hybridization to microarrays for analysis of gene expression.

Protocol for Vaccinia infection of HeLa cells and analysis of host and viral gene expression. Part 1 of 3.

The family Poxviridae consists of large double-stranded DNA containing viruses that replicate exclusively in the cytoplasm of infected cells.  Members of ...

Vaccinia Virus Infection &amp; Temporal Analysis of Virus Gene Expression: Part 2

The family Poxviridae consists of large double-stranded DNA containing viruses that replicate exclusively in the cytoplasm of infected cells. Members of the orthopox genus include variola, the causative agent of human small pox, monkeypox, and vaccinia (VAC), the prototypic member of the virus family. Within the relatively large (~ 200 kb) vaccinia genome, three classes of genes are encoded: early, intermediate, and late. While all three classes are transcribed by virally-encoded RNA polymerases, each class serves a different function in the life cycle of the virus. Poxviruses utilize multiple strategies for modulation of the host cellular environment during infection. In order to understand regulation of both host and virus gene expression, we have utilized genome-wide approaches to analyze transcript abundance from both virus and host cells. Here, we demonstrate time course infections of HeLa cells with Vaccinia virus and sampling RNA at several time points post-infection. Both host and viral total RNA is isolated and amplified for hybridization to microarrays for analysis of gene expression.

Protocol for Vaccinia infection of HeLa cells and analysis of host and viral gene expression. Part 2 of 3.

Vaccinia Virus Infection &amp; Temporal Analysis of Virus Gene Expression: Part 3

Protocol for Vaccinia infection of HeLa cells and analysis of host and viral gene expression. Part 3 describes the process of fluorescently labeling the amplified RNA from both host and viral samples by amino allyl coupling of dyes. Part 3 of 3.

Using the Gene Pulser MXcell Electroporation System to Transfect Primary Cells with High Efficiency

It is becoming increasingly apparent that electroporation is the most effective way to introduce plasmid DNA or siRNA into primary cells. The Gene Pulser MXcell electroporation system and Gene Pulser electroporation buffer (Bio-Rad) were specifically developed to easily transfect nucleic acids into mammalian cells and difficult-to-transfect cells, such as primary and stem cells. We will demonstrate how to perform a simple experiment to quickly identify the best electroporation conditions. We will demonstrate how to run several samples through a range of electroporation conditions so that an experiment can be conducted at the same time as optimization is performed. We will also show how optimal conditions identified using 96-well electroporation plates can be used with standard electroporation cuvettes, facilitating the switch from electroporation plates to electroporation cuvettes while maintaining the same electroporation efficiency. In the video, we will also discuss some of the key factors that can lead to the success or failure of electroporation experiments.

This procedure shows how to use the Gene Pulser MXcell electroporation system to rapidly and easily identify the best electroporation conditions for mouse embryonic fibroblasts (MEFs) or other primary cells. Considerations for troubleshooting are also discussed in the associated video.

It is becoming increasingly apparent that electroporation is the most effective way to introduce plasmid DNA or siRNA into primary cells. The Gene Pulser ...

Expression of Recombinant Proteins in the Methylotrophic Yeast Pichia pastoris

Protein expression in the microbial eukaryotic host Pichia pastoris offers the possibility to generate high amounts of recombinant protein in a fast and easy to use expression system.
As a single-celled microorganism P. pastoris is easy to manipulate and grows rapidly on inexpensive media at high cell densities. Being a eukaryote, P. pastoris is able to perform many of the post-translational modifications performed by higher eukaryotic cells and the obtained recombinant proteins undergo protein folding, proteolytic processing, disulfide bond formation and glycosylation [1].
As a methylotrophic yeast P. pastoris is capable of metabolizing methanol as its sole carbon source. The strong promoter for alcohol oxidase, AOX1, is tightly regulated and induced by methanol and it is used for the expression of the gene of interest. Accordingly, the expression of the foreign protein can be induced by adding methanol to the growth medium [2; 3].
Another important advantage is the secretion of the recombinant protein into the growth medium, using a signal sequence to target the foreign protein to the secretory pathway of P. pastoris. With only low levels of endogenous protein secreted to the media by the yeast itself and no added proteins to the media, a heterologous protein builds the majority of the total protein in the medium and facilitates following protein purification steps [3; 4].
The vector used here (pPICZ&alpha;A) contains the AOX1 promoter for tightly regulated, methanol-induced expression of the gene of interest; the &alpha;-factor secretion signal for secretion of the recombinant protein, a Zeocin resistance gene for selection in both E. coli and Pichia and a C-terminal peptide containing the c-myc epitope and a polyhistidine (6xHis) tag for detection and purification of a recombinant protein. We also show western blot analysis of the recombinant protein using the specific Anti-myc-HRP antibody recognizing the c-myc epitope on the parent vector.

Expression of Recombinant Proteins in the Methylotrophic Yeast Pichia pastoris

The protocol describes protein expression using the methylotrophic yeast Pichia pastoris. The preparation of electrocompetent yeast cells, transformation of the vector with the gene of interest into P. pastoris and yeast DNA purification are also performed. Western blot analysis and protein purification build the last steps in this protein expression protocol.

Protein expression in the microbial eukaryotic host Pichia pastoris offers the possibility to generate high amounts of recombinant protein in a fast and ...

Identification of Growth Inhibition Phenotypes Induced by Expression of Bacterial Type III Effectors in Yeast

Many Gram-negative pathogenic bacteria use a type III secretion system to translocate a suite of effector proteins into the cytosol of host cells. Within the cell, type III effectors subvert host cellular processes to suppress immune responses and promote pathogen growth. Numerous type III effectors of plant and animal bacterial pathogens have been identified to date, yet only a few of them are well characterized. Understanding the functions of these effectors has been undermined by a combination of functional redundancy in the effector repertoire of a given bacterial strain, the subtle effects that they may exert to increase virulence, roles that are possibly specific to certain infection stages, and difficulties in genetically manipulating certain pathogens. Expression of type III effectors in the budding yeast Saccharomyces cerevisiae may allow circumventing these limitations and aid to the functional characterization of effector proteins. Because type III effectors often target cellular processes that are conserved between yeast and other eukaryotes, their expression in yeast may result in growth inhibition phenotypes that can be exploited to elucidate effector functions and targets. Additional advantages to using yeast for functional studies of bacterial effectors include their genetic tractability, information on predicted functions of the vast majority of their ORFs, and availability of numerous tools and resources for both genome-wide and small-scale experiments. Here we discuss critical factors for designing a yeast system for the expression of bacterial type III effector proteins. These include an appropriate promoter for driving expression of the effector gene(s) of interest, the copy number of the effector gene, the epitope tag used to verify protein expression, and the yeast strain. We present procedures to induce expression of effectors in yeast and to verify their expression by immunoblotting. In addition, we describe a spotting assay on agar plates for the identification of effector-induced growth inhibition phenotypes. The use of this protocol may be extended to the study of pathogenicity factors delivered into the host cell by any pathogen and translocation mechanism.

In this video, we describe a procedure for the expression of bacterial type III effectors in yeast and the identification of effector-induced growth inhibition phenotypes. Such phenotypes can be subsequently exploited to elucidate effector functions and targets.

Many Gram-negative pathogenic bacteria use a type III secretion system to translocate a suite of effector proteins into the cytosol of host cells. Within ...

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

The use of siRNA mediated gene knockdown is continuing to be an important tool in studies of gene expression.  siRNA studies are being conducted not only to study the effects of downregulating single genes, but also to interrogate signaling pathways and other complex interaction networks.  These pathway analyses require both the use of relevant cellular models and methods that cause less perturbation to the cellular physiology.  Electroporation is increasingly being used as an effective way to introduce siRNA and other nucleic acids into difficult to transfect cell lines and primary cells without altering the signaling pathway under investigation. There are multiple critical steps to a successful siRNA experiment, and there are ways to simplify the work while improving the data quality at several experimental stages.  To help you get started with your siRNA mediated gene knockdown project, we will demonstrate how to perform a pathway study complete from collecting and counting the cells prior to electroporation through post transfection real-time PCR gene expression analysis.  The following study investigates the role of the transcriptional activator STAT6 in IL-4 dependent gene expression of CCL17 in a Burkitt lymphoma cell line (Namalwa).  The techniques demonstrated are useful for a wide range of siRNA-based experiments on both adherent and suspension cells.  We will also show how to streamline cell counting with the TC10 automated cell counter, how to electroporate multiple samples simultaneously using the MXcell electroporation system, and how to simultaneously assess RNA quality and quantity with the Experion automated electrophoresis system.

This procedure describes a quick and easy workflow to introduce siRNA into difficult to transfect cell lines and follow gene expression by real-time PCR. Use of an automated cell counter, multi-well electroporation plate, and automated electrophoresis station provide quick and reliable results without the need for expensive robotic handling.

The use of siRNA mediated gene knockdown is continuing to be an important tool in studies of gene expression.  siRNA studies are being conducted not only ...

Analysis of Global RNA Synthesis at the Single Cell Level following Hypoxia

Hypoxia or lowering of the oxygen availability is involved in many physiological and pathological processes. At the molecular level, cells initiate a particular transcriptional program in order to mount an appropriate and coordinated cellular response. The cell possesses several oxygen sensor enzymes that require molecular oxygen as cofactor for their activity. These range from prolyl-hydroxylases to histone demethylases. The majority of studies analyzing cellular responses to hypoxia are based on cellular populations and average studies, and as such single cell analysis of hypoxic cells are seldom performed. Here we describe a method of analysis of global RNA synthesis at the single cell level in hypoxia by using Click-iT RNA imaging kits in an oxygen controlled workstation, followed by microscopy analysis and quantification.&nbsp; Using cancer cells exposed to hypoxia for different lengths of time, RNA is labeled and measured in each cell. This analysis allows the visualization of temporal and cell-to-cell changes in global RNA synthesis following hypoxic stress.

We describe a technique for analysis of global RNA synthesis in hypoxia using imaging. Click-chemistry labeling of RNA has not previously been performed under hypoxia and allows visualization of global RNA changes at the single cell level. This approach complements the existing averaged RNA techniques, allowing direct visualization of cell-to-cell changes in global RNA synthesis.

Hypoxia or lowering of the oxygen availability is involved in many physiological and pathological processes. At the molecular level, cells initiate a ...

Imaging Spatial Reorganization of a MAPK Signaling Pathway Using the Tobacco Transient Expression System

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular fluorescent complementation (BiFC) assay in tobacco epidermal cells, from testing protein-protein interaction to monitoring spatial distribution of signal transduction in plant cells. In this protocol, we used the BiFC assay to show that the interaction and the signaling between the Arabidopsis MAPKKK YODA and MAPK6 occur at the plasma membrane. When the scaffold protein BASL was co-expressed, the YODA-MAPK interaction redistributed and spatially co-polarized with CFP-BASL. This modified tobacco expression system allows for quick examination of signaling localization and dynamic changes (less than 4 days) and can accommodate multiple of fluorescent protein colors (at least three). We also presented detailed methods to quantify protein distribution (asymmetric spatial localization, or &#34;polarization&#34;) in tobacco cells. This advanced tobacco expression system has a potential to be used widely for quick testing of dynamic signaling events in live plant cells.

At the subcellular level, signaling events are dynamically modulated by developmental and environmental cues. Here we describe a protocol that employs the tobacco transient expression system to monitor dynamic protein-protein interaction and to disclose spatial organization of signal transduction in plant cells.

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular ...

Using Microfluidic Devices to Measure Lifespan and Cellular Phenotypes in Single Budding Yeast Cells

Budding yeast Saccharomyces cerevisiae is an important model organism in aging research. Genetic studies have revealed many genes with conserved effects on the lifespan across species. However, the molecular causes of aging and death remain elusive. To gain a systematic understanding of the molecular mechanisms underlying yeast aging, we need high-throughput methods to measure lifespan and to quantify various cellular and molecular phenotypes in single cells. Previously, we developed microfluidic devices to track budding yeast mother cells throughout their lifespan while flushing away newborn daughter cells. This article presents a method for preparing microfluidic chips and for setting up microfluidic experiments. Multiple channels can be used to simultaneously track cells under different conditions or from different yeast strains. A typical setup can track hundreds of cells per channel and allow for high-resolution microscope imaging throughout the lifespan of the cells. Our method also allows detailed characterization of the lifespan, molecular markers, cell morphology, and the cell cycle dynamics of single cells. In addition, our microfluidic device is able to trap a significant amount of fresh mother cells that can be identified by downstream image analysis, making it possible to measure the lifespan with higher accuracy.

This article presents a protocol optimized for the production of microfluidic chips and the setup of microfluidic experiments to measure the lifespan and cellular phenotypes of single yeast cells.

Budding yeast Saccharomyces cerevisiae is an important model organism in aging research. Genetic studies have revealed many genes with conserved effects ...