Construction of aquaporin and GFP-expressing cell lines

Human AQP1 (NM_198098.1) and AQP4 (NM_001650.4) complementary DNAs were ordered from OriGene (Rockville, MD) and subcloned into a lentiviral vector downstream of a constitutive CMV or doxycycline-regulated CMV promoter (Clontech, Mountain View, CA) and an N-terminal FLAG tag. The doxycycline-regulated CMV was used specifically to place AQP1 or GFP under the control of doxycycline using a commercially available CHO cell line (Clontech) that expresses the rtTA transactivator. Enhanced GFP was fused downstream of aquaporin via an IRES sequence. Lentiviral packaging was performed in HEK 293T cells by transfecting 22 μg of packaging plasmid to expresses the capsid genes from a CMV promoter along with 22 μg of insert plasmid harboring the gene of interest (AQP1-IRES-GFP, AQP4-IRES-GFP, or GFP) flanked by long terminal repeat sequences and 4.5 μg of VSV-G plasmid that expresses the vesicular stomatitis virus G protein to enable broad tropism of the lentiviral particles. Transfection was achieved using 25 kDa linear polyethyleneimine (Polysciences, Warrington, PA) at a concentration of 2.58 mg PEI per mg DNA. Approximately 24 h post transfection, the culture medium was supplemented with sodium butyrate at 10 mM concentration, to induce expression of the packaging genes. Virus production was allowed to proceed for 48–60 h following which the virus-laden supernatant was collected, centrifuged at 500 g to remove residual HEK 293T cells, mixed with one-tenth the volume of Lenti-X concentrator (Clontech) and incubated at 4 °C for at least 24 h. Lentiviral particles were subsequently sedimented by centrifugation at 1,500 g for 45 min at 4 °C and resuspended in 1–2 ml of DMEM medium. Resuspended viral particles were immediately used to transfect CHO, CHO-TetON, Neuro 2a or U87 cells, to generate stable cell lines. For this, the cells were first grown to 70–80% confluency in six-well plates. Spent medium was aspirated from the wells and replaced with 1 ml lentivirus suspension together with 8 μg ml−1 polybrene. The cells were spinfected at 2,000 g for 90 min at 30 °C, following which the plates were returned to the 37 °C incubator for 48 h to allow gene expression. Control cell lines were generated in the same way to express enhanced GFP from a constitutive or doxycycline-regulated CMV promoter. Cell lines were obtained from American Type Cell Culture Collection (U87, Neuro 2a, HEK 293T, CHO) or from Clontech (CHO-TetON) and used without further validation. Further, we note that none of the cell lines used in the study are listed in the database of cross-contaminated cell lines maintained by the International Cell Line Authentication Committee as of 10/26/2016. Some of the cell lines were periodically checked for Mycoplasma contamination using the MycoAlert detection kit from Lonza.

Determination of cell viability

Cell viability was determined using four different approaches including staining with ethidium homodimer-1 (Thermo Fisher) and measurement of resazurin reduction (CellTiter-Blue assay, Promega), ATP content (CellTiter-Glo assay, Promega) and lactate dehydrogenase release (CytoOne, Promega). For ethidium homodimer-1 staining, AQP1- and GFP-expressing cells were grown in six-well plates for 48 h, trypsinized and resuspended in 100 μl PBS supplemented with ethidium homodimer-1 at 4 μM final concentration. The cell-dye mixture was allowed to incubate at 4 °C for 1 h in a rotary shaker. Subsequently, 10 μl of the cell suspension was loaded in a disposable hemocytometer (C-chip DHC S02, Incyto) and total number of cells was estimated by imaging the hemocytometer chamber using bright field microscopy. Dead cells stained red and were estimated using fluorescence imaging with a Cy3 filter set. Viability was calculated as the fraction of cells that did not stain using ethidium homodimer-1. For the remaining cytotoxicity assays, AQP1- and GFP-expressing cells were grown in 96-well plates for 24–48 h and treated with the assay reagents as described by the manufacturer. Fluorescence (resazurin reduction and lactate dehydrogenase release) or luminescence (ATP content assay) readouts were measured using a SpectraMax fluorescence plate reader using an excitation wavelength of 560 nm and with the emission filter set to 590 nm for fluorescence, and with an open filter slot with a 1 s integration time for luminescence.

Quantification of AQP1 expression

AQP1 expression was quantified via western blotting and relative fluorescence measurements. AQP1 expression was induced in CHO cells by treating the cells with doxycycline for 48 h. Membrane fractions were isolated using ProteoExtract native membrane protein extraction kit (EMD Millipore, Billerica, MA) or MEM-PER Plus membrane protein extraction kit (Thermo Fisher) and concentrated ∼30-fold using a 10 kDa centrifugal filter. Alternatively, proteins were concentrated using trichloroacetic acid precipitation (ProteoExtract protein precipitation kit). Proteins were denatured at 37 °C for at least 1 h followed by 95 °C for 5 min and resolved on a denaturing SDS–PAGE gel, transferred to a polyvinylidene difluoride membrane and probed using mouse anti-FLAG primary antibodies ( 0.5 μg ml−1 final concentration) and horseradish peroxidase-conjugated goat anti-mouse IgG secondary antibodies (0.4 μg ml−1 final concentration). Primary and secondary antibodies were purchased from Sigma (catalogue number F1365) and Santa Cruz Biotech (catalogue number sc-2005). Signal detection was achieved using the Clarity chemiluminescent substrate (Biorad, Hercules, CA) using an exposure time of 1–10 s. AQP1 expression was quantified from a calibration curve of known quantities (100 to 400 ng) of FLAG-tagged bacterial alkaline phosphatase (Sigma Aldrich, St Louis, MO) that was simultaneously loaded, stained and imaged on the same blot (Supplementary Fig. 4a). As AQP1 expression in cells induced with 0.01 μg ml−1 doxycycline was below the chemiluminescence detection limit of our western blotting, we estimated AQP1 concentration in this case by quantifying doxycycline dependent fluorescence of IRES-linked GFP. In particular, we measured GFP fluorescence in cells induced using various concentrations of doxycycline to derive a dose-response curve for transcriptional regulation by doxycycline. Based on this, we estimated a relative response ratio of 0.18±0.03 (n=4) between GFP expression in low (0.01 μg ml−1) and high (1 μg ml−1) doxycycline conditions. As AQP1 and GFP are co-transcribed into a single polycistronic construct, we expect the doxycycline dose-response curve to be conserved for the AQP1 messenger RNA as well. This enabled us to extrapolate the concentration of AQP1 in the low doxycycline scenario by multiplying the measured AQP1 concentration at high doxycycline induction (2.54±0.46 μM based on western blotting, n=5) by the response ratio of 0.18. For the fluorescence measurements, doxycycline-treated cells were lysed using RIPA buffer and GFP fluorescence was measured in the cell lysates using a SpectraMax fluorescence plate reader with excitation wavelength set to 450 nm. Fluorescence emission was quantified by integrating the emission spectrum between 480 and 610 nm. Before fluorescence measurements, lysate concentrations were adjusted, to ensure equal total protein levels across samples.

Diffusion-weighted MRI of cell pellets

For diffusion-weighted MRI, cells were grown for 48 h, trypsinized, resuspended in 100 μl PBS and centrifuged at 500 g for 5 min in 0.2 ml PCR tubes, to produce a compact pellet. Subsequently, the tubes were loaded in wells molded in a 1% agarose phantom and imaged using a Bruker 7T horizontal bore MRI scanner equipped with a 7.2 cm diameter bore transceiver coil for radio frequency excitation and detection. Diffusion-weighted images were acquired on a 1.5 or 2 mm-thick horizontal slice through the cell pellets using a stimulated echo DWI sequence with the following parameters: echo time, T E =24.5 ms, repetition time, T R =2 s, number of excitations=1–3, gradient duration, δ=7 ms, matrix size=256 × 256, field of view (FOV)=3.5 × 6.5 cm2. The gradient interval (Δ) was varied from 20 to 400 ms to generate effective diffusion times (Δ eff =Δ−δ/3) of 18–398 ms in each experiment. Single-axis diffusion gradients were applied and gradient strength was varied to generate b-values in the range 0–800 s mm−2. For each value of Δ eff , ADC was calculated from the slope of the logarithmic decay in MRI signal intensity versus b-value. Images were analysed using custom macros in ImageJ (NIH). A linear 8-bit colour scale were used to facilitate the visualization of the relevant contrast in each figure. Least-squares regression fitting was performed using Origin 2016 or Matlab version 9 (2016).

T 1 - and T 2 -weighted MRI of cell pellets

T 1 -weighted images were acquired using a rapid acquisition with relaxation enhancement sequence with the following parameters: T E =9.6 ms, rapid acquisition with relaxation enhancement factor=4, N EX =2, matrix size=128 × 256, FOV=8 × 5 cm2, slice thickness=1.5 mm and receiver bandwidth=50,505.1 Hz. Variable T R times were used including 146.19, 321.47, 519.98, 748.83, 1018.9, 1348.72, 1771.99, 2363.81, 3355.44 and 7500, ms. T 1 -values were estimated from the following equation:

where S 0 is the equlibrium magnetization. T 2 -weighted images were acquired using a Car–Purcell–Meiboom–Gill pulse sequence with the following parameters: T E =11 ms, T R =1.5 s, number of echoes=63, number of excitations=4, matrix size=256 × 256, FOV=8 × 5 cm2, slice thickness=1.5 mm and receiver bandwidth=50,505.1 Hz. T 2 relaxation rates were estimated by fitting the first 19 echoes to the signal decay equation:

All images were analysed using custom macros in ImageJ (NIH) and least-squares regression fitting was performed using OriginLab. We report average T 1 and T 2 measurements for n=4.

Mouse xenograft model

To prepare cells for intracranial tumour implantation, AQP1- and GFP-expressing CHO-TetON cells were grown for 48 h, trypsinized, centrifuged at 500 g for 10 min and resuspended in 100 μl serum-free DMEM. Female NOD/SCID/γ-mice between 5 and 7 weeks of age (Jackson Laboratory, Bar Harbor, ME) were anaesthetized with 2.5% isoflurane and 105 AQP1-expressing CHO cells were injected stereotaxically into the right striatum. Coordinates of the injection sites with respect to bregma were as follows: 1 mm anterior, 2 mm lateral and 1–3 mm ventral from the surface of the calvaria. The same number of control GFP-expressing CHO cells were implanted in the left striatum of the same animal.

For longitudinal measurements of tumour volume, subcutaneous xenografts were established by injecting 3 × 106 AQP1 and GFP CHO cells (prepared as described above and resuspended in Matrigel) into the right and left hind limbs of female NOD/SCID/γ-mice. Gene expression was induced by intraperitoneal injection of 75 μg doxycycline 11 days following tumour inoculation. Tumour size was measured daily using callipers and tumour volume was calculated as 0.52 × (short axis)2 × (long axis). A sample size of n=4 biological replicates was deemed adequate for a power (expressed as 1−β) of 0.80, calculated based on the difference in AQP1 and GFP groups observed in vitro. In addition, the tumour models are well established and tumour growth is stable, which obviated the need for a larger sample size. No surviving animals were excluded from the final analysis. Tumour inoculation sites were not randomized and investigators were not blinded to the experiments. All animal experiments were approved by the Institutional Animal Care and Use Committee of the California Institute of Technology.

Diffusion-weighted MRI of brain tumour xenografts

Diffusion-weighted imaging of mouse xenografts was performed using a Bruker 7T horizontal bore MRI scanner. Radio frequency excitation was delivered by a 7.2 cm diameter bore volume coil and detection was achieved using a 3 cm diameter surface coil. Mice were anaesthetized using 1–2% isoflurane. Respiration and temperature were continuously monitored using a pressure transducer (Biopac Systems) and fibre optic rectal thermometer (Neoptix). Warm air was circulated to maintain body temperature at 30 °C. Tumour formation was confirmed by acquiring diffusion-weighted images 5 days following xenograft implantation, after which mice were intraperitoneally injected with 75 μg doxycycline to induce expression of AQP1 and GFP in the tumours. A second set of diffusion-weighted images was acquired 24–48 h following doxycycline injection. Preliminary diffusion-weighted images to locate the tumours were first acquired on horizontal slices using a three-dimensional echo planar imaging stimulated echo DWI sequence with the following parameters: T R =2.5 or 3 s, T E =25.7 ms, δ=7 ms, Δ=100 ms, b=1,000 s mm−2, number of excitations=9, matrix size=16 × 128 × 128 and FOV=1.59 × 1.29 × 0.74 cm3. After identifying an appropriate tumour-bearing slice, two-dimensional echo planar imaging diffusion-weighted images were acquired at the slice using similar parameters but with a slice thickness of 1–2 mm, T R =5 s, number of excitations=144–256.

Histological analyses of brain tissue

Mouse tumours were evaluated for gene expression and signs of necrosis via fluorescence imaging of 100 μm-thick histological sections and haematoxylin–eosin staining of 5 μm-thick paraffin-embedded sections. For histological analyses, mice were anaesthetized by intraperitoneal injection of ketamine (100 mg kg−1 of body weight) and xylazine (10 mg kg−1 of body weight), and transcardially perfused first with PBS containing heparin (10 units ml−1, Sigma Aldrich) and subsequently with 4% w/v paraformaldehyde (Sigma Aldrich). Following perfusion, the brain was harvested and fixed in 4% w/v paraformaldehyde for 2 h at room temperature and washed three times with PBS. Axial brain sections of 100 μm-thickness were obtained using a vibratome (Leica Biosystems, Buffalo Grove, IL). Free-floating sections were incubated for 30 min at room temperature with a 1 μM solution of TO-PRO-3 Iodide nuclear stain in PBS (Thermo Fisher Scientific, Waltham, MA). Stained sections were washed three times with PBS and mounted on glass slides with ProLong Diamond Antifade Mountant (Thermo Fisher Scientific) and imaged using a confocal microscope with GFP- and Cy5-specific filter sets. Haematoxylin–eosin staining was performed by the Translational Pathology Core Laboratory in the University of California, Los Angeles.

Monte Carlo simulations of water diffusion in cells

We developed a model for restricted water diffusion and exchange in cells, building on the previously described Karger and Szafer models of tissue water diffusion48,67,68. We modelled cell pellets as a face-centered cubic lattice packed with 108 spherical cells (Supplementary Fig. 1a) with water molecules distributed randomly throughout the lattice at t=0. Cell radii were sampled from a normal distribution with a mean of 6.8 μm and a s.d. of 1.2 μm. We set the simulation time step τ=50 μs and at each time step, water molecules were propagated in a three-dimensional random walk with step size given by in each direction. Here, N is sampled from a random normal distribution and D is the free diffusion coefficient of water at 12.9 °C (the bore temperature of our MRI scanner) in the intracellular compartment (554.7 μm2 s−1) or in the extracellular space (1664.2 μm2 s−1)69. If a water molecule encounters a membrane, the propagation step is recalculated and the molecule either transmitted or reflected off the membrane with a probability given by

wherein P is the membrane permeability and D is the free diffusion coefficient of water in the intracellular compartment. Diffusion paths were simulated in Python and the ADC was calculated using Matlab as described in the Szafer model48:

where Σx2 represents the sum square displacement of a water molecule from its starting position and q is given by (γδg)2, where γ is the gyromagnetic ratio, g is the gradient strength and δ is the duration of the pulsed diffusion gradient. We note that b-value is calculated as:

In the first set of simulations (ADC versus permeability), we varied the cell permeability from 0.034 to 0.39 μm ms−1 and calculated ADC(Δ) for each value of cell permeability. In the second set of simulations (ADC versus fraction of AQP1-expressing cells), the permeability of AQP1-expressing cells and control cells were fixed at 0.14 and 0.039 μm ms−1 respectively, in accordance with previously published values55. We incrementally varied the fraction of cells expressing AQP1 and for each composition, simulated 3 × 104 (nonunique) random arrangements of AQP1-expressing and control cells to exclude geometry or arrangement dependent bias in the results. ADC(Δ) was estimated corresponding to varying fractions of AQP1-expressing cells in the population.

Estimation of AQP1 expression from Monte Carlo simulations

Based on the simulated trend of ADC as a function of cell permeability, we calculated permeability values of CHO cells induced with various concentrations of doxycycline and for which ADC values had been experimentally measured. Permeability values calculated in this manner ranged from 0.074 to 0.55 μm ms−1 corresponding to 0.01 and 1 μg ml−1 doxycycline concentrations. Next, permeability values were converted to volumetric flow rates by taking their product with the average surface area of a CHO cell (380 μm2). AQP1 concentration was estimated based on the previously reported unit channel conductance of 6 × 10−5 μm3 ms−1 (refs 53, 55).

Statistical analysis

For statistical significance testing, we used two-sided homoscedastic t-tests with a significance level of type I error set at 0.05 for rejecting the null hypothesis. Paired-sample t-tests were used where indicated. Homogeneity of variances between data sets was verified using Bartlett’s test or F-test, although we note that the statistical significance of our results remains conserved on using the Welch’s t-test for heteroscedastic distributions. Normal distribution of data sets was verified using the Kolmogorov–Smirnov test with a significance level of 0.01.

Data availability

All data presented in support of the findings in this study and plasmids are available from the authors upon request.

Code availability

Python and MATLAB scripts for Monte Carlo simulations are available at http://shapirolab.caltech.edu/?page_id=525.