This work was supported by awards from HHMI 56006760 to JDV, the National Institutes of Health (NIH) (2 TL1 RR 24158-6) to DMAW, and from the Ellison Medical Foundation (AG-SS-2465) and the NIH (GM45735, GM45735S1 and GM096445) to LP. GM45735S1 was issued from the NIH under the American Recovery and Reinvestment Act of 2009. The microscopes used for these studies were supported in part through a NIH &frasl; NCI grant (5 P30 CA13696).

1. Transformation of Yeast Cells with the Biosensors
<ol>
 <li>Transform the desired yeast strain with plasmid bearing mito-roGFP or mitGO-ATeam2 using the lithium acetate method27.</li>
 <li>To confirm transformation with the plasmid-borne biosensor and to prevent loss of the plasmid, select and maintain transformants on the appropriate selective synthetic complete medium (SC-Ura for mito-roGFP, or SC-Leu for mitGo-ATeam2). If the fluorescent probe has been subcloned in a different plasmid than those described here, use the appropriate selective medium. Visualize transformants by fluorescence microscopy to confirm that they express the fluorescent biosensor and exhibit normal mitochondrial morphology.</li>
</ol>
2. Growth of Cells and Preparation for Imaging
Cell function and response to drug treatment are highly dependent on cell density and metabolic activity. Best results are obtained when cells are actively dividing (mid-log phase, ~0.5 - 1 x 107 cells/ml). The most reliable way to generate mid-log phase cultures of consistent density is to inoculate from a stationary-phase pre-culture.
<ol>
 <li>Prepare a stationary-phase pre-culture: pick a single colony of transformed cells from a plate and inoculate selective liquid media (5 ml in a 50 ml conical-bottom tube). Grow at 30 &deg;C with shaking at 225 rpm until the optical density of the culture at 600 nm (OD600) has reached a plateau (24-48 hr).</li>
 <li>Prepare a mid-log phase culture for observation: use the appropriate volume of pre-culture to inoculate 5 ml of selective media in a 50 ml conical-bottom tube. YPD media is autofluorescent and should not be used for these studies. Use synthetic complete, glucose based, dropout (SC-Ura) media. Grow cells at 30 &deg;C, shaking at 225 rpm, for 4-16 hr, until they reach mid-log phase (~0.5 - 1 x 107 cells/ml). Cell density can be determined by measuring OD600; calibrate the spectrophotometer to determine the correct OD600 reading. On our Beckman DU530 (Beckman Coulter, Indianapolis, IN), mid-log phase corresponds to an OD600 of 0.1-0.3.</li>
</ol>
Mito-roGFP1 senses fluctuations in the organelle in response to metabolic changes. For example, in this assay mitochondrial redox state changes when yeast grow on fermentable carbon sources (e.g. glucose, as in SC media) versus non-fermentable carbon sources (e.g. glycerol, as in SGlyc media), and even in different batches of the same media. Therefore, use the same batch of media for all experiments.
<ol start="3">
 <li>Cells are ready for concentration (see step 2.4) and imaging if no treatment is being performed. If cells are being treated, incubate cells with the appropriate treatment and continue to the next step.</li>
 <li>Concentrate 1 ml of culture by centrifugation at 6,000 x g for 15 sec and resuspension of the cell pellet in 20 &mu;l of media. These conditions maximize the number of distinguishable cells in the field of view.</li>
 <li>Apply 2 &mu;l of the resuspended cells to a slide. Cover with a coverslip (No. 1.5, preferably high-performance 170&plusmn;5 &mu;m thickness), and seal the edges of the coverslip with clear nail polish or valap (see Reagents). To seal with valap, melt a small amount on a metal spatula by holding it over a Bunsen burner flame, then spread a small amount along the edges of the coverslip.</li>
 <li>Maintain cells at 30 &deg;C during imaging. An objective heater on the 100x oil immersion lens used for imaging works well for this application. Under these conditions, mitochondrial morphology, redox state and ATP levels remain unchanged during imaging for 10-15 min.</li>
</ol>
3. Imaging Setup
<ol>
 <li>Setup for imaging mito-roGFP1 on a wide-field fluorescence microscope 
 The steps here are tailored to the AxioObserver.Z1 microscope equipped with a Colibri LED excitation source, a wide-field Orca ER camera and Axiovision acquisition software. Photobleaching of both channels and photoconversion of oxidized mito-roGFP1 is reduced significantly using LED illumination compared to mercury arc lamp illumination (see below). 
 To maximize signal and resolution, use the highest numerical aperture possible in the objective, and the lowest magnification that provides sufficient spatial resolution. In addition, for mito-roGFP imaging, verify that the objective transmits well at 365 nm. The 100x/1.3NA EC PlanNeofluar objective (Zeiss) works well for this application. 
 Configure the acquisition software to capture the oxidized and reduced mito-roGFP1 species. We use the following conditions.
 <ol>
 <li>Configure the channel for oxidized mito-roGFP to use excitation at 365 nm (100% LED power) and an emission filter suitable for GFP, such as the 38 HE filter set (Zeiss), with the included excitation filter removed from the cube. Removal of the excitation filter allows excitation at both 365 nm and 470 nm without the need to switch filters, thus increasing achievable time resolution.</li>
 <li>Configure the channel for reduced mito-roGFP to use excitation at 470 nm (100% LED power) and, as mentioned above, the same emission filter cube used for the oxidized mito-roGFP. Set the camera to 1x1 binning to optimize spatial resolution.</li>
 <li>Set software to acquire a z stack consisting of 11 slices with 0.5 &mu;m spacing, collecting both channels at each z position. This mode of acquisition is slower than acquiring each z stack in turn, but it prevents artifacts arising from mitochondrial motion between acquisition of the oxidized and reduced channels.</li>
 <li>Image several cells to determine an appropriate exposure time, producing a strong but not saturating signal. It is important to maintain the ratio of exposure times for oxidized and reduced mito-roGFP1 for all experiments. For example, if the exposure times for oxidized and reduced mito-roGFP1 are 300 and 100 msec, respectively, then the exposure time for oxidized mito-roGFP1 should be 3 times that for reduced mito-roGFP for all experiments.</li>
 </ol>
 </li>
 <li>Setup for imaging mitGO-ATeam2 on a spectral confocal microscope 
 To quantify ATP levels using mitGO-ATeam2, the fluorescence from GFP (emission maximum 510 nm) must be distinguished from that from OFP (emission maximum 560 nm). There are fluorescence filter sets that resolve the fluorescence emitted from these fluorophores. However, we find that a spectral detector, available on many laser scanning confocal microscopes, works best for this application. A spectral detector separates the fluorescence emission into many components (typically 32 or more) according to wavelength. Several adjacent wavelength bands can be combined into one image channel. The wavelengths to be combined are selected empirically so as to maximize signal from GFP and OFP while avoiding crossover of signal that would confound the FRET measurement. Use the highest numerical aperture lens available. We use a 100x/1.49 or 60x/1.49 Apo-TIRF lens. We use the Nikon A1R confocal microscope running NIS Elements software. Configure the acquisition software to capture the ATP-bound and ATP-unbound mitGO-ATeam2 species. We use the following conditions.
 <ol>
 <li>Set pinhole to 1.0 Airy units (AU), which on our system corresponds to a z resolution of about 0.42 &mu;m.</li>
 <li>Set scan zoom to approach the Nyquist sampling limit, which will maximize spatial information in the image. On our system the pixel size is 0.12 &mu;m.</li>
 <li>Because mitochondria may move during imaging, it can be helpful to increase imaging speed by cropping the field to 512 x 256 pixels. The total time required to image one frame in our system is 1.0 sec, including a 2-fold scan average. Depending on desired spatial resolution, the field can be further cropped to increase time resolution.</li>
 <li>Excite at 488 nm, and collect emission from 500 - 520 nm for GFP, and from 550 - 580 nm for OFP. Actual optimal values may vary with characteristics of the imaging system.</li>
 <li>The optimal laser power for our system is between 6.0 and 6.4%. The optimal laser power will vary for each microscope system, but will ideally be as low as possible while still producing an interpretable image. Use an internal or external power meter to monitor changes in the laser power, which occur normally over time in any optical system.</li>
 <li>Adjust detector gain and illumination light intensity to maximize the detected range of pixel values but avoid saturating the signal, for as many cells as possible. Do not analyze any cells containing more than 1% saturated pixels. Image all samples using the same objective, laser power, scan zoom, pixel size, gain, and offset.</li>
 </ol>
 </li>
</ol>
4. Image Acquisition
<ol>
 <li>Locate the focal plane of cells of interest using transmitted light to minimize bleaching the fluorescent probe.</li>
 <li>After locating one or more cells of interest, collect a z-series through the whole depth of a typical cell (approx. 7 &mu;m) using a step size of 0.5 &mu;m.</li>
 <li>Image other cells of interest on the slide, but do not image a single slide for longer than 15 min. After 15 min on the slide, cells lose viability.</li>
</ol>
5. Analysis
Mitochondrial ATP level is determined by measuring the ratio of the mitGO-ATeam2 emission at 560 nm to that at 510 nm.27 The redox state of the organelle is measured as the reduced to oxidized (R/O) ratio of mito-roGFP; i.e. emission at 510 nm upon excitation at 470 nm divided by emission at 510 nm upon excitation at 365 nm. Before calculating the ratio, we subtract background and determine a threshold value for pixels belonging to the fluorescent mitochondria.
Public domain (e.g. ImageJ30) or commercially available (e.g. Volocity, Perkin-Elmer) software can be used for analysis of mito-roGFP1 or mitGO-ATeam2. Depending on the software used for image acquisition and for analysis, the images may first need to be converted to another format, such as TIFF, before opening them in the analysis software. If images are converted, it is essential to verify that pixel values are not changed during the conversion. Analysis of mito-roGFP1 data, using both programs is described below. Program menus and options to select within each menu are highlighted in bold italics.
5.1 ImageJ analysis
<ol>
 <li>Open images and change type to 32 bit: Image&rarr; Type &rarr; 32 bit.</li>
 <li>Draw a region of interest (ROI) in an area where there are no cells. Calculate the mean intensity in this ROI: Analyze &rarr; Measure.</li>
 <li>Subtract the calculated mean background from the stack: Process &rarr; Math &rarr; Subtract.</li>
 <li>Using the subtracted z-stack, find the middle slice and threshold on mitochondria: Image &rarr; Adjust &rarr; Threshold and click Apply on the Threshold window. Apply to all slices in the stack. Check Set background pixels to NaN.</li>
 <li>Create the ratio z stack: Process &rarr; Image Calculator Divide the reduced stack by the oxidized z stack for mito-roGFP1 analysis. Divide the 560 nm (ATP bound) image by the 510 nm (ATP unbound) image for mitGO-ATeam2 analysis.</li>
 <li>Draw an ROI around the area of interest. Choose Analyze &rarr; Tools &rarr; ROI Manager, and click Add to record the ROI. Multiple regions may be stored in the manager. In ROI Manager, select all ROIs, then choose More &rarr; Multi-Measure to measure all stack slices. Export data to a spreadsheet for analysis.</li>
</ol>
5.2 Volocity analysis
<ol>
 <li>Import images into a Volocity library and create an image sequence with 2 channels.</li>
 <li>Draw a region of interest (ROI) in an area where there are no cells. Choose: Tools &rarr; Ratio.</li>
 <li>Use Volocity to calculate the background: Get From ROI.</li>
 <li>Adjust the threshold to include mitochondrial structures.</li>
 <li>Check the option to apply a rainbow LUT to the ratio channel. The intensity-modulated channel may produce a less noisy image for presenta-tion, but it should not be used for quantitation of average ratio.</li>
 <li>Select the Measurement tab, select the ratio channel and draw an ROI around the area of interest. Measure the ratio channel, excluding zero values. Multiple regions may be selected and measured at the same time. Export data to a spreadsheet for analysis.</li>
</ol>

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No conflicts of interest declared.

Here, we describe methods to use mito-roGFP1 and mitGO-ATeam2 as biosensors to assess mitochondrial redox state and ATP levels in living yeast cells. We find that expression of plasmid-borne mito-roGFP1 or mitGO-ATeam results in quantitative targeting to mitochondria, without any obvious effect on mitochondrial morphology or distribution or on cellular growth rates.3 Mito-roGFP1 can detect changes in mitochondrial redox state from highly oxidized to highly reduced states. Similarly, mitGO-ATeam can measure cha...

Mitochondria are essential organelles for ATP production, biosynthesis of amino acids, fatty acids, heme, iron sulfur clusters and pyrimidines. Mitochondria also play pivotal roles in calcium homeostasis, and in regulation of apoptosis.1 Increasing evidence links mitochondria to aging and age-related diseases including Parkinson's disease, Alzheimer's disease, amyotrophic lateral sclerosis, and Huntington's disease.2 While individuals live their entire lives with mutations in mitochondrial proteins that are associated with neurodegenerative diseases, the disease symptoms occur only later in life. This indicates that changes occur in mitochondria with age that allow disease pathology to emerge. Indeed, mitochondrial fitness is correlated with overall cell health and lifespan in yeast and mammalian cells.3,4 Here, we describe how to use genetically encoded, ratiometric fluorescent biosensors to assess two critical features of mitochondria in living yeast cells: redox state and ATP levels.
Mitochondrial function in aerobic energy mobilization is well established. Mitochondrial redox state is a product of reducing and oxidizing species in the organelle, including NAD+/NADH, FAD/FADH2, NADP+/NADPH, glutathione/glutathione disulfide (GSH/GSSG) and reactive oxygen species (ROS). Uncoupling mitochondria or hypoxia affects mitochondrial respiratory activity and alters the ratio of NAD+ to NADH in the organelle. ROS, which are produced from inefficient electron transfer between complexes of the electron transport chain in the inner mitochondrial membrane, as well as from the deamination of amines via monoamine oxidase in the outer mitochondrial membrane 5, damage lipids, proteins, and nucleic acids and have been linked to aging and age-associated neurodegenerative diseases 6,7,8. ROS also play a role in signal transduction in mitochondria, through oxidation of GSH. For example, NADH dehydrogenase not only contributes to ROS production but also is regulated through interactions with the glutathione pool 9,10. &alpha;-Ketoglutarate dehydrogenase and aconitase, components of the TCA cycle, exhibit reduced activity in oxidizing environments11,12.
Indeed, redox-dependent regulation of aconitase activity is conserved from bacteria to mammals13,14. Thus, monitoring the redox state and ATP levels of mitochondria is crucial to understanding their function and role in disease pathology.
Biochemical methods have been used to assess the redox state or ATP levels of whole cells or isolated mitochondria. Widely used methods to assess the redox state of whole cells or isolated mitochondria are based on measuring the levels of the redox pair GSH/GSSG15. The luciferin-luciferase system is commonly used to measure mitochondrial ATP levels in either permeabilized whole cells or isolated mitochondria.16,17,18,19,20 In this assay, luciferase binds to ATP and catalyzes the oxidation of and chemiluminescence from luciferin.21 The intensity of the emitted light is proportional to the amount of ATP in the reaction mixture.22
These methods have revealed fundamental information regarding mitochondrial function, including the finding that patients with neurodegenerative diseases, such as Alzheimer's disease, have abnormally low ATP levels.23 However, they cannot be used to image living, intact cells. Moreover, methods based on whole-cell analysis provide an average of redox state or ATP levels in all compartments of the cell. Measurements in isolated organelles are potentially problematic because mitochondrial redox state or ATP levels may change during subcellular fractionation. Finally, recent studies from our laboratory and others indicate that mitochondria within individual cells are heterogeneous in function, which in turn affects the lifespan of mother and daughter cells.3 Thus, there is a need to measure mitochondrial ATP levels and redox state in living cells with subcellular resolution.
The biosensors for mitochondrial function described here are both based on GFP. Redox-sensitive GFP (roGFP)24,25 is a GFP variant in which surface-exposed cysteines are added to the molecule. roGFP, like wild-type GFP, has two excitation peaks (at ~400 nm and ~480 nm) and one emission peak at ~510 nm. Oxidation of the cysteine residues in roGFP results in an increase in excitation at ~400 nm. Reduction of those cysteines favors excitation at ~480 nm. Thus, the ratio of 510 nm emission upon excitation of roGFP at 480 nm and 400 nm reveals the relative amount of reduced and oxidized roGFP, which reflects the redox state of the fluorophore's environment.
Two versions of roGFP are widely used: roGFP1 and roGFP2. Both contain the same cysteine insertions. roGFP1 is based on wild-type GFP and roGFP2 is based on S65T GFP, which has more efficient excitation at 480 nm and less efficient excitation at 400 nm compared to wtGFP24. roGFP1 is less pH sensitive than roGFP2 and its dynamic range extends further into the reduced range. Thus, roGFP1 may be more useful for monitoring more reducing compartments such as mitochondria or the cytosol, and compartments with variable pH, such as endosomes. roGFP2 offers brighter signal and, in some studies, a greater dynamic range than roGFP124,26. Studies in Arabidopsis thaliana indicate that the time required for response to changes in redox state is similar for both sensors (t&frac12; for oxidation, 65 and 95 sec and t&frac12; for reduction, 272 and 206 sec, for roGFP1 and roGFP2, respectively).26
MitGO-ATeam2 is a minimally invasive, reliable sensor that measures mitochondrial ATP in the budding yeast Saccharomyces cerevisiae. GO-ATeam is a F&ouml;rster resonance energy transfer (FRET) probe that consists of the &epsilon; subunit of the FoF1-ATP synthase sandwiched between FRET donor and acceptor fluorescent proteins (GFP and orange fluorescent protein (OFP), respectively). 27 Binding of ATP to the &epsilon; subunit results in conformational changes in the protein that bring the FRET donor in close proximity to the acceptor and allow for energy transfer from donor to acceptor. There are two variants of GO-ATeam, GO-ATeam1 and GO-ATeam2. GO-ATeam2 has a higher affinity for MgATP than GO-ATeam1, making it more suitable for measuring the typically lower [ATP] in mitochondria compared to the cytosol.27
To probe mitochondrial redox state, we constructed a fusion protein (mito-roGFP1) consisting of roGFP1 fused to the ATP9 leader sequence and expressed from a centromere-based (low copy number) yeast expression plasmid under control of the strong glyceraldehyde-3-phosphate dehydrogenase (GPD) promoter (p416GPD, Addgene). We used roGFP1 to probe the redox status of mitochondria in the context of aging of the model fungus Saccharomyces cerevisiae. We find that roGFP1 can detect changes in mitochondrial redox state that occur during aging and in response to nutrient availability but has no apparent detrimental effect on yeast cells. We also see variability in the redox state of mitochondria within individual living yeast cells, a finding that underscores the importance of a biosensor with subcellular spatial resolution.
MitGO-ATeam2 is a variant of GO-ATeam2, which has the mitochondrial signal sequence of cytochrome c oxidase subunit VIIIA inserted at the amino terminus of GO-ATeam2.27 We modified the mitGO-ATeam2 probe (kindly provided by the laboratory of H. Noji, Institute of Scientific and Industrial Research, Osaka University, Japan) for use in yeast by subcloning it, via Xba1 and HindIII sites, into the yeast expression vector pAG415GPD-ccdB (Addgene, Cambridge, MA, USA), which is a low-copy plasmid containing the strong constitutive GPD promoter. We expressed mitGO-ATeam2 in budding yeast, and find, by counterstaining with the DNA-binding dye DAPI, that it localizes exclusively to mitochondria, where it serves as an effective probe to measure physiological changes in mitochondrial ATP levels.
roGFP and GO-ATeam are both genetically encoded. As a result, they can be introduced and stably maintained in intact cells, and provide information on redox state or ATP levels in individual, living cells. Moreover, both biosensors monitor changes in redox state or ATP levels that occur under physiological conditions.28 Both probes are also ratiometric. As a result, measurements made with these probes are not affected by changes in biosensor concentration or sample illumination or thickness. Finally, both biosensors provide subcellular spatial resolution. Indeed, roGFP has been targeted to mitochondria, ER, endosomes and peroxisomes24, and can detect changes in redox state of each of these organelles, largely independent of pH.

<table border="1">
	<tbody>
		<tr>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Reagents</td>
		</tr>
		<tr>
			<td>Antimycin A</td>
			<td>Sigma-Aldrich (St. Louis, MO)</td>
			<td>1397-94-0</td>
			<td>Dissolved in ethanol to a 2 mg/ml stock solution.</td>
		</tr>
		<tr>
			<td>SGlyc (synthetic glycerol-based) yeast growth medium *omit for SGlyc-Ura 
			**omit for SGlyc-Leu</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Dissolve in H2O. Adjust pH to 5.5 with NaHCO3. Autoclave. 
			 
			Ingredients: 
			0.67% Yeast nitrogen base without amino acids 
			3% Glycerol 
			0.05% Glucose 
			2 mg/ml adenine 
			2 mg/ml uracil* 
			1 mg/ml L-arginine 
			1 mg/ml L-histidine 
			1 mg/ml L-leucine** 
			3 mg/ml L-lysine 
			2 mg/ml L-methionine 
			4 mg/ml L-phenylalanine 
			2 mg/ml L-tryptophan 
			3 mg/ml L-tyrosine</td>
		</tr>
		<tr>
			<td>SC (synthetic complete, glucose-based) yeast growth medium *omit for SGlyc-Ura 
			**omit for SGlyc-Leu</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Dissolve in H2O. Adjust pH to 5.5 with NaHCO3. Autoclave. Ingredients: 
			0.67% Yeast nitrogen base without amino acids 
			3% Glucose 
			2 mg/ml adenine 
			2 mg/ml uracil* 
			1 mg/ml L-arginine 
			1 mg/ml L-histidine 
			1 mg/ml L-leucine** 
			3 mg/ml L-lysine 
			2 mg/ml L-methionine 
			4 mg/ml L-phenylalanine 
			2 mg/ml L-tryptophan 
			3 mg/ml L-tyrosine</td>
		</tr>
		<tr>
			<td>Valap</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Combine ingredients in a 1:1:1 (w:w:w) ratio. Melt by submerging in a 70 &deg;C H2O bath. Aliquot into glass petri dishes. Store at room temperature. Ingredients: 
			Vaseline petroleum jelly, hard paraffin, lanolin</td>
		</tr>
		<tr>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>Equipment and Software</td>
		</tr>
		<tr>
			<td>Precleaned Gold Seal Rite-on Micro Slides</td>
			<td>Thomas Scientific (Swedesboro, NJ)</td>
			<td>3050</td>
			<td>Size: 25 x 75 mm; Thickness: 0.93 to 1.05 mm</td>
		</tr>
		<tr>
			<td>High-performance coverslips, No. 1.5, 18x18 mm</td>
			<td>Zeiss (Thornwood, NY)</td>
			<td>474030-9000-000</td>
			<td>These are less variable in thickness (170&plusmn;5 &mu;m) than standard coverslips, reducing spherical aberration and improving 3D imaging performance</td>
		</tr>
		<tr>
			<td>Fisherbrand Microscope Cover Glass, No. 1.5</td>
			<td>Fisher Scientific (Pittsburgh, PA)</td>
			<td>12-545E</td>
			<td>Size: 22 x 22 mm, No. 1.5 thickness (170 &mu;m)</td>
		</tr>
		<tr>
			<td>A1 laser scanning confocal microscope with spectral detector and 100x/1.49 NA Apo-TIRF objective</td>
			<td>Nikon (Melville, NY)</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>AxioObserver.Z1 microscope equipped with a 100x/1.3NA EC Plan-Neofluar objective (Zeiss) and Orca ER cooled CCD camera (Hamamatsu) and controlled by Axiovision software</td>
			<td>Zeiss (Thornwood, NY); Hamamatsu (Hamamatsu City, Japan)</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Volocity 3D Image Analysis software</td>
			<td>Perkin Elmer (Waltham, MA)</td>
			<td>&nbsp;</td>
			<td>Restoration module for deconvolution; Quantitation module for ratio calculation and measurement</td>
		</tr>
		<tr>
			<td>ImageJ software</td>
			<td>National Institutes of Health (Bethesda, MD)</td>
			<td>&nbsp;</td>
			<td><a href="http://rsb.info.nih.gov/ij/" target="_blank">http://rsb.info.nih.gov/ij/</a></td>
		</tr>
	</tbody>
</table>

ratiometric biosensors that measure mitochondrial redox state and atp in living yeast cells

Mitochondria have roles in many cellular processes, from energy metabolism and calcium homeostasis to control of cellular lifespan and programmed cell death. These processes affect and are affected by the redox status of and ATP production by mitochondria. Here, we describe the use of two ratiometric, genetically encoded biosensors that can detect mitochondrial redox state and ATP levels at subcellular resolution in living yeast cells. Mitochondrial redox state is measured using redox-sensitive Green Fluorescent Protein (roGFP) that is targeted to the mitochondrial matrix. Mito-roGFP contains cysteines at positions 147 and 204 of GFP, which undergo reversible and environment-dependent oxidation and reduction, which in turn alter the excitation spectrum of the protein. MitGO-ATeam is a F&ouml;rster resonance energy transfer (FRET) probe in which the &epsilon; subunit of the FoF1-ATP synthase is sandwiched between FRET donor and acceptor fluorescent proteins. Binding of ATP to the &epsilon; subunit results in conformation changes in the protein that bring the FRET donor and acceptor in close proximity and allow for fluorescence resonance energy transfer from the donor to acceptor.

Measuring mitochondrial redox state with mito-roGFP
Here, we show that mito-roGFP1 has the dynamic range to detect changes in mitochondrial redox state from fully oxidized to reduced in living yeast cells, without affecting yeast cell growth or mitochondrial morphology. First, we find cells expressing mitochondria-targeted GFP and roGFP1 grow at normal rates (Figure 1A). The maximum growth rate, as measured by maximum slope of the growth curve during log-phase growth and the time...

Watch this Scientific Journal Video about Ratiometric Biosensors that Measure Mitochondrial Redox State and ATP in Living Yeast Cells at JoVE.com

Ratiometric Biosensors that Measure Mitochondrial Redox State and ATP in Living Yeast Cells

We describe the use of two ratiometric, genetically encoded biosensors, which are based on GFP, to monitor mitochondrial redox state and ATP levels at subcellular resolution in living yeast cells.

Mitochondria have roles in many cellular processes, from energy metabolism and calcium homeostasis to control of cellular lifespan and programmed cell ...

ratiometric-biosensors-that-measure-mitochondrial-redox-state-atp

Research

JoVE Journal

Bioengineering

20.9K Views.  Columbia University. We describe the use of two ratiometric, genetically encoded biosensors, which are based on GFP, to monitor mitochondrial redox state and ATP levels at subcellular resolution in living yeast cells.

Video: Ratiometric Biosensors that Measure Mitochondrial Redox State and ATP in Living Yeast Cells

Fabrication of Electrochemical-DNA Biosensors for the Reagentless Detection of Nucleic Acids, Proteins and Small Molecules

As medicine is currently practiced, doctors send specimens to a central laboratory for testing and thus must wait hours or days to 
receive the results. Many patients would be better served by rapid, bedside tests. To this end our laboratory and others have developed a versatile, reagentless 
biosensor platform that supports the quantitative, reagentless, electrochemical detection of nucleic acids (DNA, RNA), proteins (including antibodies) and small 
molecules analytes directly in unprocessed clinical and environmental samples. In this video, we demonstrate the preparation and use of several biosensors in this 
"E-DNA" class. In particular, we fabricate and demonstrate sensors for the detection of a target DNA sequence in a polymerase chain reaction mixture, an HIV-specific antibody and the drug cocaine. The preparation procedure requires only three hours of hands-on effort followed by an overnight incubation, and their use requires only minutes.

"E-DNA" sensors, reagentless, electrochemical biosensors that perform well even when challenged directly in blood and other complex matrices, have been adapted to the detection of a wide range of nucleic acid, protein and small molecule analytes. Here we present a general procedure for the fabrication and use of such sensors.

As medicine is currently practiced, doctors send specimens to a central laboratory for testing and thus must wait hours or days to 
receive the results. ...

Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells

Diffusion is often an important rate-determining step in chemical reactions or biological processes and plays a role in a wide range of intracellular events. Viscosity is one of the key parameters affecting the diffusion of molecules and proteins, and changes in viscosity have been linked to disease and malfunction at the cellular level.1-3 While methods to measure the bulk viscosity are well developed, imaging microviscosity remains a challenge. Viscosity maps of microscopic objects, such as single cells, have until recently been hard to obtain. Mapping viscosity with fluorescence techniques is advantageous because, similar to other optical techniques, it is minimally invasive, non-destructive and can be applied to living cells and tissues.
Fluorescent molecular rotors exhibit fluorescence lifetimes and quantum yields which are a function of the viscosity of their microenvironment.4,5 Intramolecular twisting or rotation leads to non-radiative decay from the excited state back to the ground state. A viscous environment slows this rotation or twisting, restricting access to this non-radiative decay pathway. This leads to an increase in the fluorescence quantum yield and the fluorescence lifetime. Fluorescence Lifetime Imaging (FLIM) of modified hydrophobic BODIPY dyes that act as fluorescent molecular rotors show that the fluorescence lifetime of these probes is a function of the microviscosity of their environment.6-8 A logarithmic plot of the fluorescence lifetime versus the solvent viscosity yields a straight line that obeys the F&ouml;rster Hoffman equation.9 This plot also serves as a calibration graph to convert fluorescence lifetime into viscosity.
Following incubation of living cells with the modified BODIPY fluorescent molecular rotor, a punctate dye distribution is observed in the fluorescence images. The viscosity value obtained in the puncta in live cells is around 100 times higher than that of water and of cellular cytoplasm.6,7 Time-resolved fluorescence anisotropy measurements yield rotational correlation times in agreement with these large microviscosity values. Mapping the fluorescence lifetime is independent of the fluorescence intensity, and thus allows the separation of probe concentration and viscosity effects. 
In summary, we have developed a practical and versatile approach to map the microviscosity in cells based on FLIM of fluorescent molecular rotors.

Fluorescence Lifetime Imaging (FLIM) has emerged as a key technique to image the environment and interaction of specific proteins and dyes in living cells. FLIM of fluorescent molecular rotors allows mapping of viscosity in living cells.

Diffusion is often an important rate-determining step in chemical reactions or biological processes and plays a role in a wide range of intracellular ...

Spatio-Temporal Manipulation of Small GTPase Activity at Subcellular Level and on Timescale of Seconds in Living Cells

Dynamic regulation of the Rho family of small guanosine triphosphatases (GTPases) with great spatiotemporal precision is essential for various cellular functions and events1, 2. Their spatiotemporally dynamic nature has been revealed by visualization of their activity and localization in real time3. In order to gain deeper understanding of their roles in diverse cellular functions at the molecular level, the next step should be perturbation of protein activities at a precise subcellular location and timing. 
To achieve this goal, we have developed a method for light-induced, spatio-temporally controlled activation of small GTPases by combining two techniques: (1) rapamycin-induced FKBP-FRB heterodimerization and (2) a photo-caging method of rapamycin. With the use of rapamycin-mediated FKBP-FRB heterodimerization, we have developed a method for rapidly inducible activation or inactivation of small GTPases including Rac4, Cdc424, RhoA4 and Ras5, in which rapamycin induces translocation of FKBP-fused GTPases, or their activators, to the plasma membrane where FRB is anchored. For coupling with this heterodimerization system, we have also developed a photo-caging system of rapamycin analogs. A photo-caged compound is a small molecule whose activity is suppressed with a photocleavable protecting group known as a caging group. To suppress heterodimerization activity completely, we designed a caged rapamycin that is tethered to a macromolecule such that the resulting large complex cannot cross the plasma membrane, leading to virtually no background activity as a chemical dimerizer inside cells6. Figure 1 illustrates a scheme of our system. With the combination of these two systems, we locally recruited a Rac activator to the plasma membrane on a timescale of seconds and achieved light-induced Rac activation at the subcellular level6.

A method for spatio-temporal control of small GTPase activity by light is described. This method is based on rapamycin-induced FKBP-FRB heterodimerization and photo-caging systems. Optimization of light-irradiation enables the spatio-temporally controlled activation of small GTPases at the subcellular level.

Dynamic regulation of the Rho family of small guanosine triphosphatases (GTPases) with great spatiotemporal precision is essential for various cellular ...

Hollow Microneedle-based Sensor for Multiplexed Transdermal Electrochemical Sensing

The development of a minimally invasive multiplexed monitoring system for rapid analysis of biologically-relevant molecules could offer individuals suffering from chronic medical conditions facile assessment of their immediate physiological state. Furthermore, it could serve as a research tool for analysis of complex, multifactorial medical conditions. In order for such a multianalyte sensor to be realized, it must be minimally invasive, sampling of interstitial fluid must occur without pain or harm to the user, and analysis must be rapid as well as selective.
Initially developed for pain-free drug delivery, microneedles have been used to deliver vaccines and pharmacologic agents (e.g., insulin) through the skin.1-2 Since these devices access the interstitial space, microneedles that are integrated with microelectrodes can be used as transdermal electrochemical sensors. Selective detection of glucose, glutamate, lactate, hydrogen peroxide, and ascorbic acid has been demonstrated using integrated microneedle-electrode devices with carbon fibers, modified carbon pastes, and platinum-coated polymer microneedles serving as transducing elements.3-7,8
This microneedle sensor technology has enabled a novel and sophisticated analytical approach for in situ and simultaneous detection of multiple analytes. Multiplexing offers the possibility of monitoring complex microenvironments, which are otherwise difficult to characterize in a rapid and minimally invasive manner. For example, this technology could be utilized for simultaneous monitoring of extracellular levels of, glucose, lactate and pH,9 which are important metabolic indicators of disease states7,10-14 (e.g., cancer proliferation) and exercise-induced acidosis.15

This article details the construction of a multiplexed microneedle-based sensor. The device is being developed for in situ sampling and electrochemical analysis of multiple analytes in a rapid and selective manner. We envision clinical medicine and biomedical research uses for these microneedle-based sensors.

The development of a minimally invasive multiplexed monitoring system for rapid analysis of biologically-relevant molecules could offer individuals ...

Measuring the Mechanical Properties of Living Cells Using Atomic Force Microscopy

Mechanical properties of cells and extracellular matrix (ECM) play important roles in many biological processes including stem cell differentiation, tumor formation, and wound healing. Changes in stiffness of cells and ECM are often signs of changes in cell physiology or diseases in tissues. Hence, cell stiffness is an index to evaluate the status of cell cultures. Among the multitude of methods applied to measure the stiffness of cells and tissues, micro-indentation using an Atomic Force Microscope (AFM) provides a way to reliably measure the stiffness of living cells. This method has been widely applied to characterize the micro-scale stiffness for a variety of materials ranging from metal surfaces to soft biological tissues and cells. The basic principle of this method is to indent a cell with an AFM tip of selected geometry and measure the applied force from the bending of the AFM cantilever. Fitting the force-indentation curve to the Hertz model for the corresponding tip geometry can give quantitative measurements of material stiffness. This paper demonstrates the procedure to characterize the stiffness of living cells using AFM. Key steps including the process of AFM calibration, force-curve acquisition, and data analysis using a MATLAB routine are demonstrated. Limitations of this method are also discussed.

This paper demonstrates a protocol to characterize the mechanical properties of living cells by means of microindentation using an Atomic Force Microscope (AFM).

Mechanical  properties of cells and extracellular matrix (ECM) play important roles in many  biological processes including stem cell differentiation, ...

Optical Detection of E. coli Bacteria by Mesoporous Silicon Biosensors

A label-free optical biosensor based on a nanostructured porous Si is designed for rapid capture and detection of Escherichia coli K12 bacteria, as a model microorganism. The biosensor relies on direct binding of the target bacteria cells onto its surface, while no pretreatment (e.g.&#160;by cell lysis) of the studied sample is required. A mesoporous Si thin film is used as the optical transducer element of the biosensor. Under white light illumination, the porous layer displays well-resolved Fabry-P&#233;rot fringe patterns in its reflectivity spectrum. Applying a fast Fourier transform (FFT) to reflectivity data results in a single peak. Changes in the intensity of the FFT peak are monitored. Thus, target bacteria capture onto the biosensor surface, through antibody-antigen interactions, induces measurable changes in the intensity of the FFT peaks, allowing for a &#39;real time&#39; observation of bacteria attachment.
The mesoporous Si film, fabricated by an electrochemical anodization process, is conjugated with monoclonal antibodies, specific to the target bacteria. The immobilization, immunoactivity and specificity of the antibodies are confirmed by fluorescent labeling experiments. Once the biosensor is exposed to the target bacteria, the cells are directly captured onto the antibody-modified porous Si surface. These specific capturing events result in intensity changes in the thin-film optical interference spectrum of the biosensor. We demonstrate that these biosensors can detect relatively low bacteria concentrations (detection limit of 104 cells/ml) in less than an hour.

Optical Detection of E. coli Bacteria by Mesoporous Silicon Biosensors

A label-free optical biosensor for rapid bacteria detection is introduced. The biosensor is based on a nanostructured porous Si, which is designed to directly capture the target bacteria cells onto its surface. We use monoclonal antibodies, immobilized onto the porous transducer, as the capture probes. Our studies demonstrate the applicability of these biosensors for the detection of low bacterial concentrations within minutes with no prior sample processing (such as cell lysis).

A label-free optical biosensor based on a nanostructured porous Si is designed for rapid capture and detection of Escherichia coli K12 bacteria, as a ...

Optical Control of Living Cells Electrical Activity by Conjugated Polymers

Hybrid interfaces between organic semiconductors and living tissues represent a new tool for in-vitro and in-vivo applications. In particular, conjugated polymers display several optimal properties as substrates for biological systems, such as good biocompatibility, excellent mechanical properties, cheap and easy processing technology, and possibility of deposition on light, thin and flexible substrates. These materials have been employed for cellular interfaces like neural probes, transistors for excitation and recording of neural activity, biosensors and actuators for drug release. Recent experiments have also demonstrated the possibility to use conjugated polymers for all-optical modulation of the electrical activity of cells. Several in-vitro study cases have been reported, including primary neuronal networks, astrocytes and secondary line cells. Moreover, signal photo-transduction mediated by organic polymers has been shown to restore light sensitivity in degenerated retinas, suggesting that these devices may be used for artificial retinal prosthesis in the future. All in all, light sensitive conjugated polymers represent a new approach for optical modulation of cellular activity.
In this work, all the steps required to fabricate a bio-polymer interface for optical excitation of living cells are described. The function of the active interface is to transduce the light stimulus into a modulation of the cell membrane potential. As a study case, useful for in-vitro studies, a polythiophene thin film is used as the functional, light absorbing layer, and Human Embryonic Kidney (HEK-293) cells are employed as the biological component of the interface. Practical examples of successful control of the cell membrane potential upon stimulation with light pulses of different duration are provided. In particular, it is shown that both depolarizing and hyperpolarizing effects on the cell membrane can be achieved depending on the duration of the light stimulus. The reported protocol is of general validity and can be straightforwardly extended to other biological preparations.

A method for stimulation of in-vitro cell cultures electrical activity with visible light, based on the use of organic semiconducting polymers is described.

Hybrid interfaces between organic semiconductors and living tissues represent a new tool for in-vitro and in-vivo applications. In particular, conjugated ...

A Protocol for Using F&#246;rster Resonance Energy Transfer (FRET)-force Biosensors to Measure Mechanical Forces across the Nuclear LINC Complex

The LINC complex has been hypothesized to be the critical structure that mediates the transfer of mechanical forces from the cytoskeleton to the nucleus. Nesprin-2G is a key component of the LINC complex that connects the actin cytoskeleton to membrane proteins (SUN domain proteins) in the perinuclear space. These membrane proteins connect to lamins inside the nucleus. Recently, a F&#246;rster Resonance Energy Transfer (FRET)-force probe was cloned into mini-Nesprin-2G (Nesprin-TS (tension sensor)) and used to measure tension across Nesprin-2G in live NIH3T3 fibroblasts. This paper describes the process of using Nesprin-TS to measure LINC complex forces in NIH3T3 fibroblasts. To extract FRET information from Nesprin-TS, an outline of how to spectrally unmix raw spectral images into acceptor and donor fluorescent channels is also presented. Using open-source software (ImageJ), images are pre-processed and transformed into ratiometric images. Finally, FRET data of Nesprin-TS is presented, along with strategies for how to compare data across different experimental groups.

A Protocol for Using F&amp;#246;rster Resonance Energy Transfer (FRET)-force Biosensors to Measure Mechanical Forces across the Nuclear LINC Complex

A number of FRET-based force biosensors have recently been developed, enabling the protein-specific resolution of intracellular force. In this protocol, we demonstrate how one of these sensors, designed for the linker of the nucleoskeleton-cytoskeleton (LINC) complex protein Nesprin-2G can be used to measure actomyosin forces on the nuclear LINC complex.

The LINC complex has been hypothesized to be the critical structure that mediates the transfer of mechanical forces from the cytoskeleton to the nucleus. ...

Using Synthetic Biology to Engineer Living Cells That Interface with Programmable Materials

We have developed an abiotic-biotic interface that allows engineered cells to control the material properties of a functionalized surface. This system is made by creating two modules: a synthetically engineered strain of E. coli cells and a functionalized material interface. Within this paper, we detail a protocol for genetically engineering selected behaviors within a strain of E. coli using molecular cloning strategies. Once developed, this strain produces elevated levels of biotin when exposed to a chemical inducer. Additionally, we detail protocols for creating two different functionalized surfaces, each of which is able to respond to cell-synthesized biotin. Taken together, we present a methodology for creating a linked, abiotic-biotic system that allows engineered cells to control material composition and assembly on nonliving substrates.

This paper presents a series of protocols for developing engineered cells and functionalized surfaces that enable synthetically engineered E. coli to control and manipulate programmable material surfaces.

We have developed an abiotic-biotic interface that allows engineered cells to control the material properties of a functionalized surface. This system is ...

Measurement of Force-Sensitive Protein Dynamics in Living Cells Using a Combination of Fluorescent Techniques

Cells sense and respond to physical cues in their environment by converting mechanical stimuli into biochemically-detectable signals in a process called mechanotransduction. A crucial step in mechanotransduction is the transmission of forces between the external and internal environments. To transmit forces, there must be a sustained, unbroken physical linkage created by a series of protein-protein interactions. For a given protein-protein interaction, mechanical load can either have no effect on the interaction, lead to faster disassociation of the interaction, or even stabilize the interaction. Understanding how molecular load dictates protein turnover in living cells can provide valuable information about the mechanical state of a protein, in turn elucidating its role in mechanotransduction. Existing techniques for measuring force-sensitive protein dynamics either lack direct measurements of protein load or rely on the measurements performed outside of the cellular context. Here, we describe a protocol for the F&#246;rster resonance energy transfer-fluorescence recovery after photobleaching (FRET-FRAP) technique, which enables the measurement of force-sensitive protein dynamics within living cells. This technique is potentially applicable to any FRET-based tension sensor, facilitating the study of force-sensitive protein dynamics in variety of subcellular structures and in different cell types.

Here, we present a protocol for the simultaneous use of F&#246;rster resonance energy transfer-based tension sensors to measure protein load and fluorescence recovery after photobleaching to measure protein dynamics enabling the measurement of force-sensitive protein dynamics within living cells.

Cells sense and respond to physical cues in their environment by converting mechanical stimuli into biochemically-detectable signals in a process called ...