We thank Emily Jackson, Joshua Zeidman, and Nicholas Wren for comments on the software. This work was funded by GM95733 (to N.M.), BBBE 103316 and MIT startup funds (to N.M.).

<ol>
	<li>Locke, J. C. W., Elowitz, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+movies+to+analyse+gene+circuit+dynamics+in+single+cells.">Using movies to analyse gene circuit dynamics in single cells.</a> Nature Reviews. Microbiology. 7 (5), 383-392 (2009).</li><li>Rosenfeld, N., Young, J. W., Alon, U., Swain, P. S., Elowitz, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+Regulation+at+the+Single-Cell+Level.">Gene Regulation at the Single-Cell Level.</a> Science. 307 (5717), 1962-1965 (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>Vega, N. M., Allison, K. R., Khalil, A. S., Collins, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Signaling-mediated+bacterial+persister+formation.">Signaling-mediated bacterial persister formation.</a> Nature Chemical Biology. 8 (5), 431-433 (2012).</li><li>Larson, D. R., Zenklusen, D., Wu, B., Chao, J. A., Singer, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-Time+Observation+of+Transcription+Initiation+and+Elongation+on+an+Endogenous+Yeast+Gene.">Real-Time Observation of Transcription Initiation and Elongation on an Endogenous Yeast Gene.</a> Science. 332 (6028), 475-478 (2011).</li><li>Golding, I., Paulsson, J., Zawilski, S., Cox, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+kinetics+of+gene+activity+in+individual+bacteria.">Real-time kinetics of gene activity in individual bacteria.</a> Cell. 123 (6), 1025-1061 (2005).</li><li>Suter, D. M., Molina, N., Gatfield, D., Schneider, K., Schibler, U., Naef, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mammalian+Genes+Are+Transcribed+with+Widely+Different+Bursting+Kinetics.">Mammalian Genes Are Transcribed with Widely Different Bursting Kinetics.</a> Science. 332 (6028), 472-474 (2011).</li><li>Cookson, N. A., Cookson, S. W., Tsimring, L. S., Hasty, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell+cycle-dependent+variations+in+protein+concentration.">Cell cycle-dependent variations in protein concentration.</a> Nucleic Acids Research. 38 (8), 2676-2681 (2010).</li><li>Zopf, C. J., Quinn, K., Zeidman, J., Maheshri, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell-cycle+dependence+of+transcription+dominates+noise+in+gene+expression.">Cell-cycle dependence of transcription dominates noise in gene expression.</a> , (2013).</li><li>Kaufmann, B. B., Yang, Q., Mettetal, J. T., 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=Heritable+stochastic+switching+revealed+by+single-cell+genealogy.">Heritable stochastic switching revealed by single-cell genealogy.</a> PLoS Biology. 5 (9), e239 (2007).</li><li>Cookson, S., Ostroff, N., Pang, W. L., Volfson, D., Hasty, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+dynamics+of+single-cell+gene+expression+over+multiple+cell+cycles.">Monitoring dynamics of single-cell gene expression over multiple cell cycles.</a> Molecular Systems Biology. 1 (1), 2005.0024 (2005).</li><li>Paliwal, S., Iglesias, P. A., Campbell, K., Hilioti, Z., Groisman, A., Levchenko, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MAPK-mediated+bimodal+gene+expression+and+adaptive+gradient+sensing+in+yeast.">MAPK-mediated bimodal gene expression and adaptive gradient sensing in yeast.</a> Nature. 446 (7131), 46-51 (2007).</li><li>Charvin, G., Cross, F. R., Siggia, E. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+microfluidic+device+for+temporally+controlled+gene+expression+and+long-term+fluorescent+imaging+in+unperturbed+dividing+yeast+cells.">A microfluidic device for temporally controlled gene expression and long-term fluorescent imaging in unperturbed dividing yeast cells.</a> PloS One. 3 (1), e1468 (2008).</li><li>Gordon, A., Colman-Lerner, A., Chin, T. E., Benjamin, K. R., Yu, R. C., Brent, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+quantification+of+molecules+and+rates+using+open-source+microscope-based+cytometry.">Single-cell quantification of molecules and rates using open-source microscope-based cytometry.</a> Nat. Meth. 4 (2), 175-181 (2007).</li><li>Otsu, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Threshold+Selection+Method+from+Gray-Level+Histograms.">A Threshold Selection Method from Gray-Level Histograms.</a> IEEE Trans. Sys. Man. Cyber. 9 (1), 62-66 (1979).</li><li>Goranov, A. I., Cook, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+rate+of+cell+growth+is+governed+by+cell+cycle+stage.">The rate of cell growth is governed by cell cycle stage.</a> Genes &amp; Development. 23 (12), 1408-1422 (2009).</li><li>To, T. -. L., Maheshri, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Noise+Can+Induce+Bimodality+in+Positive+Transcriptional+Feedback+Loops+Without+Bistability.">Noise Can Induce Bimodality in Positive Transcriptional Feedback Loops Without Bistability.</a> Science. 327 (5969), 1142-1145 (2010).</li><li>O'Neill, E. M., Kaffman, A., Jolly, E. R., O'Shea, E. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+PHO4+nuclear+localization+by+the+PHO80-PHO85+cyclin-CDK+complex.">Regulation of PHO4 nuclear localization by the PHO80-PHO85 cyclin-CDK complex.</a> Science. 271 (5246), 209-212 (1996).</li><li>Raser, J. M., O'Shea, E. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Control+of+stochasticity+in+eukaryotic+gene+expression.">Control of stochasticity in eukaryotic gene expression.</a> Science. 304 (5678), 1811-1814 (2004).</li></ol>

The authors declare that they have no competing financial interests.

The above protocol describes a simple method to obtain and analyze fluorescence time series data with limited experience in microfluidics or in software development. It allows one to obtain time-lapse fluorescence movies of single yeast cells; extract relevant cell size and expression measurements; curate tracking and lineage assignments; and analyze the behavior of whole cells over time using a commercially available microfluidic culture device and a versatile graphical user interface (GUI). While the experimental, segm...

Single-cell analysis of gene expression has furthered our understanding of many aspects of gene regulation. Static snapshots of fluorescent reporter expression using flow cytometry or microscopy provide useful information on the distribution of single-cell expression, but lack the history and evolution of time series data required to directly inform gene expression dynamics. Fluorescence time-lapse microscopy presents a means to obtain both single-cell measurements and their history. Various experimental and analytical techniques have been developed to obtain and quantify movies of fluorescent reporter expression, thus imparting insights into gene regulation features (see 1 for a review) such as cell-to-cell variation 2,3, bacterial persister formation 4, transcription initiation and elongation 5, transcriptional bursting 6,7, cell-cycle dependence 8,9, and heritability 10. However, obtaining quality single-cell fluorescence time series involves significant technical challenges in culturing a monolayer of cells in a controllable environment and in high-throughput quantification of the acquired fluorescence movies. Here, we describe a procedure to obtain and analyze fluorescence movies of S. cerevisiae with no required experience in cell culture device manufacture or in software development (Figure 1).
First, we detail an example protocol to generate fluorescence time series movies for budding yeast expressing one or more fluorescent reporters. Though customized microfluidic culture chambers have been built and successfully employed previously 11-13, we use a commercially available microfluidic device from CellAsic (Hayward, CA). The system confines cells to monolayer growth and allows continual control of the perfusion environment. The microscopy protocol we present is a simple means to obtain fluorescence movies of budding yeast, but any modified experimental protocol (a customized culture device, alternative media conditions, etc.) yielding similar fluorescence movie data of single yeast cells may be substituted.
Next, we outline the analysis of the movies using a graphical user interface (GUI) -based software package in MATLAB (Mathworks, Natick, MA), dubbed the GUI for Rapid Analysis of Fluorescence Time Series (GRAFTS), to extract time series data for single cells. GRAFTS has similar features to the versatile, open-source software package Cell-ID 14 in segmenting and tracking cells and in extracting fluorescence intensity and geometric information. However, GRAFTS provides important additional features. First, it offers easy interactive editing of segmentation and tracking results to verify data accuracy, rather than just statistical gating of outlier region traces after analysis. Moreover, it extends the analysis to automatically designate lineage and cell-cycle points of interest of budding yeast. Determining when mother and daughter divide to form two independent cell regions is crucial to determining whole cell (mother including any connected bud) measurements throughout the cell cycle 8. The suite consists of three modules to accomplish these tasks. The first segments cell regions based on the contrast between focused and unfocused bright field images, and allows the user to define and visually test segmentation parameters. The second tracks (using Blair and Dufresne's MATLAB implementation of the Crocker et al. IDL routine, available at: <a href="http://physics.georgetown.edu/matlab/" target="_blank">http://physics.georgetown.edu/MATLAB/</a>) and measures cell regions through time; automatically assigns lineages; and enables visual inspection and error correction. A simple plotting GUI is included to query single-cell properties. The third module ascribes bud emergence and division times, and outputs whole cell time series data as well as their first and second time derivatives (as discussed in 9). The analysis module outputs the data as a space-delimited text file for subsequent study in the statistical software of choice. Thus, the package enables the user to extract high quality time series data through a graphical interface. We have used this method to estimate real-time transcription rates in single budding yeast cells as a function of the cell cycle 9. While the modules have been optimized for budding yeast, the parameters or, if necessary, the freely available code may be adapted for other organisms and image types. Segmentation, tracking, and lineage assignment algorithms may be specific to types of imaging assigned and the organism in question. The existing algorithms could be replaced, but still retain the GUI interface that allows user-friendly visual inspection and correction of segmentation and tracking errors that invariably occur with any algorithm.

<table border="1">
	<tbody>
		<tr>
			<td>Name of Reagent/Material</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td>Y04C Yeast Perfusion Plate</td>
			<td>CellAsic</td>
			<td>Y04C-02</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>ONIX Microfluidic Perfusion Platform</td>
			<td>CellAsic</td>
			<td>EV-262</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Axio Observer.Z1 Microscope</td>
			<td>Zeiss</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Plan-Apochromat 63X/1.40 Oil DIC objective</td>
			<td>Zeiss</td>
			<td>440762-9904-000</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Cascade II EMCCD camera</td>
			<td>Photometrics</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Lumen 200 metal-halide arc lamp</td>
			<td>PRIOR Scientific</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Triple-bandpass dichroic filter cube and excitation and emission filter set</td>
			<td>Chroma Technology Corp</td>
			<td>set #89006</td>
			<td>Used for YFP (Venus/Citrine), CFP (Cerulean), RFP (mCherry/tdTomato)</td>
		</tr>
		<tr>
			<td>MAC 5000 controller and filter wheels</td>
			<td>Ludl Electronic Products</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>MATLAB R2011a</td>
			<td>Mathworks</td>
			<td>&nbsp;</td>
			<td>64-bit version handles large data files better than 32-bit</td>
		</tr>
	</tbody>
</table>

acquiring fluorescence time-lapse movies of budding yeast and analyzing single-cell dynamics using grafts

Fluorescence time-lapse microscopy has become a powerful tool in the study of many biological processes at the single-cell level. In particular, movies depicting the temporal dependence of gene expression provide insight into the dynamics of its regulation; however, there are many technical challenges to obtaining and analyzing fluorescence movies of single cells. We describe here a simple protocol using a commercially available microfluidic culture device to generate such data, and a MATLAB-based, graphical user interface (GUI) -based software package to quantify the fluorescence images. The software segments and tracks cells, enables the user to visually curate errors in the data, and automatically assigns lineage and division times. The GUI further analyzes the time series to produce whole cell traces as well as their first and second time derivatives. While the software was designed for S. cerevisiae, its modularity and versatility should allow it to serve as a platform for studying other cell types with few modifications.

A successfully performed and analyzed experiment will yield mostly continuous time series for single whole cells with realistically assigned bud emergence and division times. As an example, we performed the above protocol with a haploid yeast strain expressing an integrated copy of Cerulean fluorescent protein (CFP) driven by the constitutive ADH1 promoter to observe how growth and global expression may vary over time in single cells (Table 4, Y47). We ran the time series analysis to ob...

Watch this Scientific Journal Video about Acquiring Fluorescence Time-lapse Movies of Budding Yeast and Analyzing Single-cell Dynamics using GRAFTS at JoVE.com

Acquiring Fluorescence Time-lapse Movies of Budding Yeast and Analyzing Single-cell Dynamics using GRAFTS

We present a simple protocol to obtain fluorescence microscopy movies of growing yeast cells, and a GUI-based software package to extract single-cell time series data. The analysis includes automated lineage and division time assignment integrated with visual inspection and manual curation of tracked data.

Fluorescence time-lapse microscopy has become a powerful tool in the study of many biological processes at the single-cell level. In particular, movies ...

acquiring-fluorescence-time-lapse-movies-budding-yeast-analyzing

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Biology

12.7K Views.  Massachusetts Institute of Technology. Мы представляем простой протокол для получения флуоресцентного микроскопа фильмы растущих клеток дрожжей и на основе графического интерфейса программного пакета для извлечения одноклеточные данных временных рядов. Анализ включает в себя автоматизированн...

Video: Acquiring Fluorescence Time-lapse Movies of Budding Yeast and Analyzing Single-cell Dynamics using GRAFTS

Measuring Replicative Life Span in the Budding Yeast

Aging is a degenerative process characterized by a progressive deterioration of cellular components and organelles resulting in mortality. The budding yeast Saccharomyces cerevisiae has been used extensively to study the biology of aging, and several determinants of yeast longevity have been shown to be conserved in multicellular eukaryotes, including worms, flies, and mice 1. Due to the lack of easily quantified age-associated phenotypes, aging in yeast has been assayed almost exclusively by measuring the life span of cells in different contexts, with two different life span paradigms in common usage 2. Chronological life span refers to the length of time that a mother cell can survive in a non-dividing, quiescence-like state, and is proposed to serve as a model for aging of post-mitotic cells in multicellular eukaryotes. Replicative life span, in contrast, refers the number of daughter cells produced by a mother cell prior to senescence, and is thought to provide a model of aging in mitotically active cells. Here we present a generalized protocol for measuring the replicative life span of budding yeast mother cells. The goal of the replicative life span assay is to determine how many times each mother cell buds. The mother and daughter cells can be easily differentiated by an experienced researcher using a standard light microscope (total magnification 160X), such as the Zeiss Axioscope 40 or another comparable model. Physical separation of daughter cells from mother cells is achieved using a manual micromanipulator equipped with a fiber-optic needle. Typical laboratory yeast strains produce 20-30 daughter cells per mother and one life span experiment requires 2-3 weeks.

In this article we present a general protocol for measuring the replicative life span of yeast mother cells.

Aging is a degenerative process characterized by a progressive deterioration of cellular components and organelles resulting in mortality. The budding ...

Time-lapse Imaging of Mitosis After siRNA Transfection

Changes in cellular organization and chromosome dynamics that occur during mitosis are tightly coordinated to ensure accurate inheritance of genomic and cellular content. Hallmark events of mitosis, such as chromosome movement, can be readily tracked on an individual cell basis using time-lapse fluorescence microscopy of mammalian cell lines expressing specific GFP-tagged proteins. In combination with RNAi-based depletion, this can be a powerful method for pinpointing the stage(s) of mitosis where defects occur after levels of a particular protein have been lowered. In this protocol, we present a basic method for assessing the effect of depleting a potential mitotic regulatory protein on the timing of mitosis. Cells are transfected with siRNA, placed in a stage-top incubation chamber, and imaged using an automated fluorescence microscope. We describe how to use software to set up a time-lapse experiment, how to process the image sequences to make either still-image montages or movies, and how to quantify and analyze the timing of mitotic stages using a cell-line expressing mCherry-tagged histone H2B. Finally, we discuss important considerations for designing a time-lapse experiment. This strategy is complementary to other approaches and offers the advantages of 1) sensitivity to changes in kinetics that might not be observed when looking at cells as a population and 2) analysis of mitosis without the need to synchronize the cell cycle using drug treatments. The visual information from such imaging experiments not only allows the sub-stages of mitosis to be assessed, but can also provide unexpected insight that would not be apparent from cell cycle analysis by FACS.

Here we describe a basic protocol to image and quantify the mitotic timing of live mammalian tissue culture cells after siRNA transfection.

Changes in cellular organization and chromosome dynamics that occur during mitosis are tightly coordinated to ensure accurate inheritance of genomic and ...

Recording Multicellular Behavior in Myxococcus xanthus Biofilms using Time-lapse Microcinematography

A swarm of the &delta;-proteobacterium Myxococcus xanthus contains millions of cells that act as a collective, coordinating movement through a series of signals to create complex, dynamic patterns as a response to environmental cues. These patterns are self-organizing and emergent; they cannot be predicted by observing the behavior of the individual cells. Using a time-lapse microcinematography tracking assay, we identified a distinct emergent pattern in M. xanthus called chemotaxis, defined as the directed movement of a swarm up a nutrient gradient toward its source 1.
In order to efficiently characterize chemotaxis via time-lapse microcinematography, we developed a highly modifiable plate complex (Figure 1) and constructed a cluster of 8 microscopes (Figure 2), each capable of capturing time-lapse videos. The assay is rigorous enough to allow consistent replication of quantifiable data, and the resulting videos allow us to observe and track subtle changes in swarm behavior. Once captured, the videos are transferred to an analysis/storage computer with enough memory to process and store thousands of videos. The flexibility of this setup has proven useful to several members of the M. xanthus community.

Recording Multicellular Behavior in Myxococcus xanthus Biofilms using Time-lapse Microcinematography

To study Myxococcus xanthus swarm behavior, we have designed a time-lapse microcinematography protocol that can be modified for different assays. It employs standard growth conditions adapted for microscopy, and yields reproducible results by the use of inexpensive, reusable silicone gaskets. We have used this method to quantify multicellular chemotaxis.

A swarm of the &delta;-proteobacterium Myxococcus xanthus contains millions of cells that act as a collective, coordinating movement through a series of ...

Quantitative Analysis of Random Migration of Cells Using Time-lapse Video Microscopy

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During directional migration, cells move rapidly in response to an extracellular chemotactic signal, or in response to intrinsic cues 3 provided by the basic motility machinery. Random migration occurs when a cell possesses low intrinsic directionality, allowing the cells to explore their local environment.
Cell migration is a complex process, in the initial response cell undergoes polarization and extends protrusions in the direction of migration 2. Traditional methods to measure migration such as the Boyden chamber migration assay is an easy method to measure chemotaxis in vitro, which allows measuring migration as an end point result. However, this approach neither allows measurement of individual migration parameters, nor does it allow to visualization of morphological changes that cell undergoes during migration.
Here, we present a method that allows us to monitor migrating cells in real time using video - time lapse microscopy. Since cell migration and invasion are hallmarks of cancer, this method will be applicable in studying cancer cell migration and invasion in vitro. Random migration of platelets has been considered as one of the parameters of platelet function 4, hence this method could also be helpful in studying platelet functions. This assay has the advantage of being rapid, reliable, reproducible, and does not require optimization of cell numbers. In order to maintain physiologically suitable conditions for cells, the microscope is equipped with CO2 supply and temperature thermostat. Cell movement is monitored by taking pictures using a camera fitted to the microscope at regular intervals. Cell migration can be calculated by measuring average speed and average displacement, which is calculated by Slidebook software.

This method allows monitoring of cells in real time and quantitative measurements of different cell migration parameters such as speed, displacement, and velocity. Unlike the traditional methods, this real time approach is not based on endpoint quantitative migration measurements; instead it allows monitoring and calculating different parameters continuously.

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During ...

Budding Yeast Protein Extraction and Purification for the Study of Function, Interactions, and Post-translational Modifications

Homogenization by bead beating is a fast and efficient way to release DNA, RNA, proteins, and metabolites from budding yeast cells, which are notoriously hard to disrupt. Here we describe the use of a bead mill homogenizer for the extraction of proteins into buffers optimized to maintain the functions, interactions and post-translational modifications of proteins. Logarithmically growing cells expressing the protein of interest are grown in a liquid growth media of choice. The growth media may be supplemented with reagents to induce protein expression from inducible promoters (e.g. galactose), synchronize cell cycle stage (e.g. nocodazole), or inhibit proteasome function (e.g. MG132). Cells are then pelleted and resuspended in a suitable buffer containing protease and/or phosphatase inhibitors and are either processed immediately or frozen in liquid nitrogen for later use. Homogenization is accomplished by six cycles of 20 sec&#160;bead-beating (5.5 m/sec), each followed by one minute incubation on ice. The resulting homogenate is cleared by centrifugation and small particulates can be removed by filtration. The resulting cleared whole cell extract (WCE) is precipitated using 20% TCA for direct analysis of total proteins by SDS-PAGE followed by Western blotting. Extracts are also suitable for affinity purification of specific proteins, the detection of post-translational modifications, or the analysis of co-purifying proteins. As is the case for most protein purification protocols, some enzymes and proteins may require unique conditions or buffer compositions for their purification and others may be unstable or insoluble under the conditions stated. In the latter case, the protocol presented may provide a useful starting point to empirically determine the best bead-beating strategy for protein extraction and purification. We show the extraction and purification of an epitope-tagged SUMO E3 ligase, Siz1, a cell cycle regulated protein that becomes both sumoylated and phosphorylated, as well as a SUMO-targeted ubiquitin ligase subunit, Slx5.

The preparation of high quality yeast cell extracts is a necessary first step in the analysis of individual proteins or entire proteomes. Here we describe a fast, efficient, and reliable homogenization protocol for budding yeast cells that has been optimized to preserve protein functions, interactions, and post-translational modifications.

Homogenization by bead beating is a fast and efficient way to release DNA, RNA, proteins, and metabolites from budding yeast cells, which are notoriously ...

High-resolution Time-lapse Imaging and Automated Analysis of Microtubule Dynamics in Living Human Umbilical Vein Endothelial Cells

The physiological process by which new vasculature forms from existing vasculature requires specific signaling events that trigger morphological changes within individual endothelial cells (ECs). These processes are critical for homeostatic maintenance such as wound healing, and are also crucial in promoting tumor growth and metastasis. EC morphology is defined by the organization of the cytoskeleton, a tightly regulated system of actin and microtubule (MT) dynamics that is known to control EC branching, polarity and directional migration, essential components of angiogenesis. To study MT dynamics, we used high-resolution fluorescence microscopy coupled with computational image analysis of fluorescently-labeled MT plus-ends to investigate MT growth dynamics and the regulation of EC branching morphology and directional migration. Time-lapse imaging of living Human Umbilical Vein Endothelial Cells (HUVECs) was performed following transfection with fluorescently-labeled MT End Binding protein 3 (EB3) and Mitotic Centromere Associated Kinesin (MCAK)-specific cDNA constructs to evaluate effects on MT dynamics. PlusTipTracker software was used to track EB3-labeled MT plus ends in order to measure MT growth speeds and MT growth lifetimes in time-lapse images. This methodology allows for the study of MT dynamics and the identification of how localized regulation of MT dynamics within sub-cellular regions contributes to the angiogenic processes of EC branching and migration.

Protocols for Human Umbilical Vein Endothelial Cell (HUVEC) culture, transient transfection of fluorescently-labeled markers of microtubule growth, live-cell imaging and automated analysis of interphase microtubule growth dynamics are detailed.

The physiological process by which new vasculature forms from existing vasculature requires specific signaling events that trigger morphological changes ...

Applications of pHluorin for Quantitative, Kinetic and High-throughput Analysis of Endocytosis in Budding Yeast

Green fluorescent protein (GFP) and its variants are widely used tools for studying protein localization and dynamics of events such as cytoskeletal remodeling and vesicular trafficking in living cells. Quantitative methodologies using chimeric GFP fusions have been developed for many applications; however, GFP is somewhat resistant to proteolysis, thus its fluorescence persists in the lysosome/vacuole, which can impede quantification of cargo trafficking in the endocytic pathway. An alternative method for quantifying endocytosis and post-endocytic trafficking events makes use of superecliptic pHluorin, a pH-sensitive variant of GFP that is quenched in acidic environments. Chimeric fusion of pHluorin to the cytoplasmic tail of transmembrane cargo proteins results in a dampening of fluorescence upon incorporation of the cargo into multivesicular bodies (MVBs) and delivery to the lysosome/vacuole lumen. Thus, quenching of vacuolar fluorescence facilitates quantification of endocytosis and early events in the endocytic pathway. This paper describes methods using pHluorin-tagged cargos for quantification of endocytosis via fluorescence microscopy, as well as population-based assays using flow cytometry.

Accurate quantification of vesicular trafficking events often provides key insights into roles for specific proteins and the effects of mutations. This paper presents methods for using superecliptic pHluorin, a pH-sensitive GFP variant, as a tool for quantification of endocytic events in living cells using quantitative fluorescence microscopy and flow cytometry.

Green fluorescent protein (GFP) and its variants are widely used tools for studying protein localization and dynamics of events such as cytoskeletal ...

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 ...

High-resolution Imaging and Analysis of Individual Astral Microtubule Dynamics in Budding Yeast

Dynamic microtubules are fundamental to many cellular processes, and accurate measurements of microtubule dynamics can provide insight into how cells regulate these processes and how genetic mutations impact regulation. The quantification of microtubule dynamics in metazoan models has a number of associated challenges, including a high microtubule density and limitations on genetic manipulations. In contrast, the budding yeast model offers advantages that overcome these challenges. This protocol describes a method to measure the dynamics of single microtubules in living yeast cells. Cells expressing fluorescently tagged tubulin are adhered to assembled slide chambers, allowing for stable time-lapse image acquisition. A detailed guide for high-speed, four-dimensional image acquisition is also provided, as well as a protocol for quantifying the properties of dynamic microtubules in confocal image stacks. This method, combined with conventional yeast genetics, provides an approach that is uniquely suited for quantitatively assessing the effects of microtubule regulators or mutations that alter the activity of tubulin subunits.

Budding yeast is an advantageous model for studying microtubule dynamics in vivo due to its powerful genetics and the simplicity of its microtubule cytoskeleton. The following protocol describes how to transform and culture yeast cells, acquire confocal microscopy images, and quantitatively analyze microtubule dynamics in living yeast cells.

Dynamic microtubules are fundamental to many cellular processes, and accurate measurements of microtubule dynamics can provide insight into how cells ...

Examination of Mitotic and Meiotic Fission Yeast Nuclear Dynamics by Fluorescence Live-cell Microscopy

Live-cell imaging is a microscopy technique used to examine cell and protein dynamics in living cells. This imaging method is not toxic, generally does not interfere with cell physiology, and requires minimal experimental handling. The low levels of technical interference enable researchers to study cells across multiple cycles of mitosis and to observe meiosis from beginning to end. Using fluorescent tags such as Green Fluorescent Protein (GFP) and Red Fluorescent Protein (RFP), researchers can analyze different factors whose functions are important for processes like transcription, DNA replication, cohesion, and segregation. Coupled with data analysis using Fiji (a free, optimized ImageJ version), live-cell imaging offers various ways of assessing protein movement, localization, stability, and timing, as well as nuclear dynamics and chromosome segregation. However, as is the case with other microscopy methods, live-cell imaging is limited by the intrinsic properties of light, which put a limit to the resolution power at high magnifications, and is also sensitive to photobleaching or phototoxicity at high wavelength frequencies. However, with some care, investigators can bypass these physical limitations by carefully choosing the right conditions, strains, and fluorescent markers to allow for the appropriate visualization of mitotic and meiotic events.

Here, we present live-cell imaging which is a non-toxic microscopy method that allows researchers to study protein behavior and nuclear dynamics in living fission yeast cells during mitosis and meiosis.

Live-cell imaging is a microscopy technique used to examine cell and protein dynamics in living cells. This imaging method is not toxic, generally does ...