Glutamine Flux Imaging Using Genetically Encoded Sensors

Summary

This article will demonstrate how to monitor glutamine dynamics in live cells using FRET. Genetically encoded sensors allow real-time monitoring of biological molecules at a subcellular resolution. Experimental design, technical details of the experimental settings, and considerations for post-experimental analyses will be discussed for genetically encoded glutamine sensors.

Abstract

Genetically encoded sensors allow real-time monitoring of biological molecules at a subcellular resolution. A tremendous variety of such sensors for biological molecules became available in the past 15 years, some of which became indispensable tools that are used routinely in many laboratories.

One of the exciting applications of genetically encoded sensors is the use of these sensors in investigating cellular transport processes. Properties of transporters such as kinetics and substrate specificities can be investigated at a cellular level, providing possibilities for cell-type specific analyses of transport activities. In this article, we will demonstrate how transporter dynamics can be observed using genetically encoded glutamine sensor as an example. Experimental design, technical details of the experimental settings, and considerations for post-experimental analyses will be discussed.

Introduction

Due to remarkable progress in technologies that allows examination of the transcriptome and the proteome at a cellular level, it has now become clear that the biochemistry and the resulting flux of metabolites and ions are highly cell-type specific. For example, in the mammalian liver, sequential glutamine degradation and synthesis are carried out simultaneously by periportal cells and perivenous cells respectively, feeding ammonium to the urea cycle in the former cell type while consuming excess ammonia in the latter ^1-3. In some cases, significant biochemical heterogeneity is detected even in a single “cell type” ^4,5. In addition to such spatial specificity, the cellular levels of metabolites and ions are highly dynamic (e.g., signaling molecules such as Ca²⁺ and cyclic nucleotides). The spatiotemporal patterns of metabolites and ions often play critical roles in signal transduction. Monitoring cellular dynamics of metabolites and ions, however, pose unique challenge. In many cases the change in concentrations are rapid and transient, exemplified by the case of signaling molecules such as Ca²⁺, which decays within ~20 msec in dendritic spines ⁶. In addition, compartmentalization of biochemical pathways within and among the cells makes it difficult to quantify the dynamics of metabolites and ions using extraction and column chromatography/mass spectrometry techniques.

Genetically encoded sensors for biological molecules are now widely used due to the high spatiotemporal resolution that allows the experimenter to study short-lived and/or compartmentalized molecular dynamics (reviewed in ^7,8). These genetically encoded sensors can roughly be divided into two categories; intensity-based sensors and ratiometic sensors. Intensity-based sensors typically consist of a binding domain and a fluorescent protein (FPs), and the solute binding to the binding domain changes the fluorescent intensity. Ratiometic sensors, on the other hand, often take advantage of Föster Resonance Energy Transfer (FRET) between two FPs that function as a FRET pair. These sensors consist of a binding domain and two FPs, and the solute binding induces the change in FRET efficiency between the two FPs. A large number of sensors for biologically important metabolites and ions have been developed in the past decade ^8,9.

One of the exciting possibility offered by such genetically encoded sensors is their use in the high-resolution analysis of membrane transport processes, which previously was not easy to detect at the cellular level. Genetically encoded sensors facilitate the analysis of transport mechanisms such as substrate specificity and pH dependence ^10,11. Moreover, in combination with the genetic resources such as the library of RNAi constructs for model organisms, it is now possible to conduct genome-wide searches for novel transport processes using genetically encoded sensors. Indeed, use of genetically encoded sensor lead to the discovery of previously uncharacterized transporters in multiple cases ^12,13.

Recently, our laboratory has developed a series of FRET-based sensor for glutamine. We have demonstrated that cellular glutamine levels can be visualized using such FRET glutamine sensors ¹⁰. These sensors consist of a FRET donor (mTFP1) inserted into a bacterial glutamine binding protein glnH, and a FRET acceptor (venus) at the C-termini of glnH (Figure 1). FRET efficiency of these sensors decrease upon binding of glutamine, resulting in the decrease of acceptor/donor intensity ratio. Fine regulation of glutamine transport processes is important in biological processes such as neurotransmission ^14,15 and the maintenance of urea cycle in the liver ^1,16,17.

Here we show the methodology of analyzing transport activities with FRET sensors for glutamine, using a wide-field fluorescence microscope set-up. The goal of experiments shown here are to detect transporter activities in a single cell and to examine substrate specificity of a transiently expressed transporter.

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Protocol

1. Sample Preparation

Note: In many cases perfusion experiments wash away a significant portion of cells, which can become a frustrating issue. Although not necessary for all cell lines, coating cover glass surfaces with poly-L-Lysine (add 1.0 ml/25 cm² of 0.01% solution to the surface, incubate >5 min, wash twice with cell culture grade water, and dry in the biosafety cabinet) enhances cell adhesion. Also, be aware of the biosafety level (BSL) of the cell line used, and follow the standard operating procedure approved by the local environmental health and safety office. In this experiment, cos7 cells were used due to low endogenous glutamine transport activity (see Figure 4).

1. Seed cos7 cells at ~70-80% confluency in Dulbecco’s Modified Eagle Medium (DMEM) + 10% cosmic calf serum and 100 U/ml penicillin/streptomycin, either on sterile 25 mm glass coverslips placed in the 6-well culture dish or 8-well glass-bottom slides. Incubate at 37 °C, 5% CO_2, 100% humidity for 24 hr.
2. Exchange the growth medium to DMEM +10% cosmic calf serum (no antibiotics), according to the manufacturer’s protocol. Grow O/N at 37 °C, 5% CO₂ at 100% humidity.
3. Add 0.4 mg each of plasmid DNA encoding the glutamine sensor (pcDNA3.1, carrying FLIPQTV3.0 sensor under CMV promoter ¹⁰) and the mCherry-tagged ASCT2 ¹⁰ to 50 ml serum-free media (OPTI-MEM) and mix gently.
4. Add 1 ml of transfection reagent to 50 ml serum-free media. Incubate at RT for 5 min.
5. Mix the two solutions containing DNA (step 1.3) and transfection reagent (step 1.4) and incubate for 20 min.
6. Gently add the transfection reagent on top of the cells and mix gently by rocking the chamber. Incubate for 24 hr at 37 °C, 5% CO₂, 100% humidity.
7. After 24 hr, exchange the medium to DMEM + 10% Cosmic Calf Serum (CCS) + 100 unit of penicillin/streptomycin.
8. Cells are imaged 48-72 hr post-transfection.

2. Perfusion Experiment

Note: For cos7 cells used in this experiment, perfusion media and chamber were kept at RT and ambient CO₂ concentration. However, if the cells being used require higher temperature and CO₂ concentration control for survival, heated microscope stage and/or an environmental chamber should be used.

1. Prepare perfusion buffer A-F (See List of Materials). Attach stopcocks to 50 ml syringes, close the stopcocks then fill them with the perfusion solutions. Open the stopcock for a brief period to fill the head space in the stopcock with the buffer.
2. Switch on the 8-channel, gravity-feed perfusion system with a perfusion pencil, and then select “Manual Mode” under Select Function option. Place a waste container under the perfusion pencil.
3. Manually activate the ports by pressing the corresponding numbers and fill the tubings using 10 ml syringe containing water, and then close the port. Once the ports are filled with water, set the syringes containing buffers A-F on the port 1-6 of perfusion system, and then open the stopcocks. Open the ports again to replace the water in the tubing with the buffers. The flow rate should be around 0.8 ml/min.
4. Press cancel once on the perfusion controller to go back to the “Select Function” menu. Toggle to “Edit Program” option, then type in the perfusion protocol indicated in Table 1. Save the perfusion program.
5. Take the cells out of the incubator. Wash twice with the perfusion buffer, and then set the cells on the stage. Connect the perfusion system to the chamber. If an open chamber is used, set up another pump that removes the perfusion solution from the chamber.
6. Open Slidebook software. Start a new slide.
   Note: The following procedure is specific to Slidebook software, but other software such as MetaFluor and Nis-Element can also be used for the type of imaging described here. Theoretically experiments can be performed using any software that allows time-course imaging, and the image sequences can be analyzed post-experimentally using software such as ImageJ (http://rsbweb.nih.gov/ij/) or Fiji (http://fiji.sc/Fiji). However, software that allows real-time monitoring of acceptor/donor ratio is highly useful.
7. Mount the slide onto the fluorescent microscope stage. Find the cells co-expressing the sensor and ASCT-mCherry using appropriate filter sets (see List of Materials) under “FOCUS” function. Adjust gain by clicking “Camera” tab and sliding the slide bar under “gain”. Also, adjust the neutral density filter setting from neutral density filter drop-down menu. Note: If the filter cube does not include an eye filter, do not use the eye pieces since short-wavelength excitation light is harmful to eyes. Use the computer screen to find the cells instead.
8. Acquire images of cells with donor (mTFP1)_exdonor(mTFP1)_em , donor(mTFP1)_exacceptor(venus)_em and acceptor(mTFP1)_exacceptor(venus)_{em m} channels (filters are specified in the List of Materials). Click “Image Capture”, and then in the acquisition window, specify the filters that are going to be used. Click “TEST” button to adjust the exposure time by typing the desired exposure time in the box next to the filter settings. Note: All three channels need to be exposed for the same length. When adjusting the imaging parameters, take the expected FRET efficiency change and fold increase into account: for example, if the FRET efficiency is expected to go up 2-fold during the experiment, imaging parameters should be adjusted so that the intensity of Donor_exAcceptor_em at the resting state should be <50% of the maximal value that can be recorded by the instrument, so that channel does not become saturated during the experiment. Signal from the labeled cells should be at least three-times higher than that in the background region.
9. Draw a region of interest using regions tool in the software. Alternatively, a software function to select pixels above certain intensity can be used, and then converted into regions. To do this, click Mask – Segment, then move the sliding bar to highlight the desired areas.
10. Select “time lapse” in the capture type box, then specify the interval (10 sec in this experiment) and time points for the experiment.
11. Draw a region in an area without any fluorescent cells. This area is used for background subtraction. Right click the region drawn, and then set it as a background. Note: Ideally, cells that are not expressing the sensors should be used as the background region to account for both the autofluorescence and the background florescence detected by the camera. If no such cells are available in the field of view, at least a region without the cells should be used to account for the background fluorescence.
12. Select the desired program under “Select Function - Run programs” option. Toggle to the saved program (see step 2.3), and then hit ENTER on the perfusion controller. Now the program is loaded, and hitting any key will start the perfusion.
13. Ensure perfusion and the imaging experiment start at the same time by clicking “Start” button in the capture window at the same time as pressing a key on the perfusion controller.
    Note: It is recommended to record the timepoint where the solutions were exchanged (this can be done using “NOTES” function, found within the acquisition tab).
14. Perform the same perfusion protocol using cells expressing a sensor that is expected to be either saturated or unbound under the experimental condition.
    Note: Here, FLIPQTV3.0_1.5μ, which is saturated under the experimental condition, is used as a control, Figure 6. Such control experiments are necessary to confirm that the FRET efficiency change is due to the actual change in the substrate and not due to the change in other parameters such as cellular pH.

3. Post-experiment Analysis

1. Examine if sample drift has occurred during the experiment. Draw Regions Of Interest (ROI)s on the image taken at timepoint 0, then move the sliding bar at the top of the imaging window and check if the cells fall out of the ROIs in images taken later in the experiment.
2. If yes, then use the tracking function to correct for the drift by first, creating masks around the cells by selecting Mask – Segment, then slide the line that specifies the cutoff to highlight the regions containing cells. Track the regions by clicking Mask – Particle tracking – Basic particle tracking.
3. Re-draw the ROIs and background region when necessary.
4. Export the mean intensity of the ROIs over the course of experiment. Click Statistics – Export – Ratio/timelapse data.
5. When FRET efficiency and quantification of substrate concentration is not necessary, plot the time course of the intensity ratio (Donor_exAcceptor_em, / Donor_exDonor_em) as a proxy of the dynamics of the substrate. To determine the cytosolic concentration, calculate the maximal and minimal ratio change (i.e., at the saturating and absence of the substrate, respectively), Δr_max - Δr_min, by non-linear regression of Δratio (Δr) with the following equation:
   Δr = [S]/(K_d+[S]) x (Δr_max - Δr_min) + Δr_min
   where [S] is the substrate concentration in the cytosol. Using the Δr_max - Δr_min values obtained, saturation (S) of the sensor at a given Δr is calculated as
   S = (Δr - Δr_min) / (Δr_max - Δr_min)
   S can further be converted into the substrate concentration [S] using the following equation:
   S = [S]/(K_d+[S])
   Note: the intensity of Acceptor_exAcceptor_em channel should be also plotted to examine whether the experimental condition influenced the fluorescence of the acceptor directly.
6. When a baseline drift due to photo-bleaching is observed, perform a baseline correction. To do this, plot the intensities of donor and acceptor over time (Figure 5A). Then identify the timepoints used for the baseline, according to the delay in the perfusion system and the transport activity of the particular cell (Figure 5B).
7. Calculate a polynominal fitting that best describes the baseline. Then, normalize the raw intensity from each timepoint to the baseline (Figure 5C). Calculate the intensity ratio (Donor_exAcceptor_em, / Donor_exDonor_em) from the normalized donor and acceptor intensities.

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Results

Typical time-course experiments are represented in Figure 2. In these experiments, FRET glutamine sensors with affinities of 8 mM (FLIPQTV3.0_8m, Figure 2A and 2B) and 100 μM (FlipQTV3.0_100 μ C and D) were co-expressed with an obligatory amino acid exchanger ASCT2 ¹⁸ in cos7 cells ¹⁰. Influx of glutamine is detected as the change in fluorescence intensity ratios between the donor (mTFP1) and the acceptor (venus) (Figure 2A

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Discussion

The success of imaging experiments depends upon a few critical factors. One of these factors is the affinity of sensors used, as discussed above. Absolute concentration of the substrate in the subcellular compartment of interest, however, is often unknown. Therefore we recommend trying multiple sensors with staggered affinities to find the one that works best under the desired experimental condition. For example, in our case we transfected the cos7 cells with glutamine sensors with 1.5μ, 100μ, 2m, and 8m (

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Materials

Name	Company	Catalog Number	Comments
Inverted fluorescent microscope	Olympus	IX81F-3-5	An equivalent inverted fluorescent microscope from other suppliers would also be appropriate.
Excitation filter (mTFP1)	Omega Optical	3RD450-460	Band width 450-460 nm
Excitation filter (Venus)	Chroma	ET500/20	Band width 490-510 nm
Emission filter (mTFP1)	Chroma	HQ495/30m	Band width 475-505 nm
Emission filter (Venus)	Chroma	ET535/30m	Band width 520-550 nm
Dichroic mirror (FRET channels)	Chroma	470dcxr	Long pass, 470 nm cut off
Dichroic mirror (YFP channel)	Chroma	89002bs	Passes 445-490 nm, 510-560 nm, 590-680 nm
mCherry filter set	Chroma	49008	Excitation 540-580 nm, long pass dichroic with 585 nm cut off, emission filter 595-695 nm
Light source	Olympus	U-LH100L-3-5	LED- or halogen light source that produces stable light intensity, mercury lamps are not recommended
CCD camera	Qimaging	Rolera-MGi EMCCD
Apochromatic fluorescence objective	Olympus
Perfusion system, ValveBank II	AutoMate Scientific	[01-08]	Other perfusion systems that allow fast solution exchange would also work
Laminar-flow chambers	C&L Instruments	VC-MPC-TW	Other larminar-flow chambers would also work.
Chambered slide	Lab-Tek	154534	For open-chamber experiments
Perfusion pump	Thermo Scientific	74-046-12131	For open-chamber experiments
Software supporting ratiometric measurements	Intellegenent Imaging Innovation	Slidebook 5.5
Laminar flow biosafety cabinet	ESCO	LA-3A2
Isotemp CO2 Incubator	Thermo Scientific	13-255-25
Dulbecco's MEM (DMEM)	Hyclone	SH30243.01
Cosmic calf serum	Hyclone	SH3008703
Penicillin/streptomycin	Hyclone	SV30010
Serum-free medium for transfection (OPTI-MEM I)	Invitrogen	31985	Used with Lipofectamine 2000
Poly-L-Lysine solution	Sigma	P4707
25 mm circular glass cover slips	Thermo Scientific	12-545-102	In case VC-MPC-TW is used
Lipofectamine 2000	Invitrogen	11668027	Other transfection reagents can also be used.
Solution A (Hank's buffer)			9.7 g HANK salt (Sigma H1387), 0.35 g NaHCO3, 5.96 g HEPES to 1 L, pH adjusted to 7.35 with NaOH
Solution B			Solution A + 0.04 mM Gln
Solution C			Solution A + 0.2 mM Gln
Solution D			Solution A + 1 mM Gln
Solution E			Solution A + 5 mM Gln
Solution F			Solution A + 5 mM Ala