Abstract
Compared to two-dimensional (2D) cell culture, cellular aggregates or spheroids (3D) offer a more appropriate alternative in vitro system where individual cell-cell communication and micro-environment more closely represent the in vivo organ; yet we understand little of the physiological conditions at this scale. The relationship between spheroid size and oxygen microenvironment, an important factor influencing the metabolic capacity of cells, was first established using the fish intestine derived RTgutGC cell line. Subsequently, pharmaceutical metabolism (Propranolol), as determined by high performance liquid chromatography, in this intestinal model was examined as a function of spheroid size. Co-efficient of variation between spheroid size was below 12% using the gyratory platform method, with the least variation observed in the highest cell seeding density. The viable, high oxygen micro-environment of the outer rim of the spheroid, as determined by electron paramagnetic resonance (EPR) oximetry, decreased over time, and the hypoxic zone increased as a function of spheroid size. Despite a trend of higher metabolism in smaller spheroids, the formation of micro-environments (quiescent, hypoxic or anoxic) did not significantly affect metabolism or function of an environmentally relevant pharmaceutical in this spheroid model.
Introduction
The spheroid (three-dimensional or 3D) culture system is a model used increasingly in study function, metabolism and toxicological assessment of drugs and contaminants across a broad range of biological systems (; ; ; ; ; ; ; ; ). While microenvironment gradient formation has been well characterized in terms of oxygen diffusion in tumor based spheroid models (; ; ; ), questions still remain in terms of nutrient and xenobiotic diffusion/or metabolism in non-tumorous spheroid models. Beginning with the route of administration and uptake to the final site of action, a drug/toxicant encounters numerous barriers and transporters before reaching its target. Transporters play a key role in the uptake of toxicants and drugs by cells, with the largest family of transporters known as the ATP binding cassette (ABC) which include P-glycoprotein (Pgp). These proteins function as active transporters for multiple substrates across the cellular membrane and are highly conserved across animal taxa (). However, in cells cultivated as a 3D construct, oxygen is transported by diffusion and simultaneously consumed by cells (). In this context, a clear trend emerges where larger spheroids demonstrated markedly distinct diffusional gradients which do not provide sufficient nutrients into the core of the aggregate. As a consequence of limited nutrients, basic cellular activity such as waste removal is reduced resulting in eventual cell death. Any adjustment to this diffusion has clear impacts on energy and xenobiotic metabolism and subsequently can impact overall physiology and function of the spheroid. Typically, studies which address energy metabolism limitations in these models have used mathematical modeling of growth (; ) or cytotoxic changes in terms of quantitative changes in glucose, LDH or protein (; ) as a means of minimizing the degree of variation between predictions and reality. Regardless of the obvious connection, few studies address the differences in xenobiotic metabolism as impacted by spheroid size. Cytotoxic response to numerous pharmaceutical compounds using spheroids derived from both a primary source and a cell line was compared (), but no attempt was made to correlate metabolic rate with respect to spheroid cell seeding density, size and growth.
Significant differences in responsiveness of different 3D models following exposure to chemicals are difficult to interpret since there is no agreed or standardized spheroid size, or cell seeding protocol. Substantial advances in our knowledge about these 3D models have highlighted the potential impact of spheroid size in terms of their metabolic capability and responsiveness. For example, recent studies identified a maximum spheroid size where cells are exposed to sufficient oxygen in order to prevent or minimize hypoxia in their internal structure but did not quantify the metabolic differences between size categories (; ). It is unsurprising that reviews have focused on the incorporation of spheroid size in terms of responsiveness to treatment () and on opportunities and challenges associated with the use of this model to test drug delivery and efficacy (). However, development of high-throughput preparatory methodologies rarely addresses the impact of spheroid size and generally, the focus is drug penetration within a spheroid in relation to the molecular structure of the drug. Given that metabolic capacity of spheroids could depend on the size of spheroids, one might argue that the impact of size is important. If different size categories of spheroids are known to have variable zones of proliferating cells, necrosis or oxygen transport limitations, how can a single response be standardized or compared in vivo or in vitro in any animal or human system? Obviously, this has significant implications while extrapolating the information for fundamental biological or clinical understandings.
Previously we have addressed one of the fundamental unknowns for the widespread use of spheroid models by elucidating oxygen micro-environment in spheroids in fish cell line (i.e., RTG-2) derived spheroids of various sizes (). With precise cultivation of the spheroid size in terms of cell seeding density, zones of quiescence can be kept to a minimum and consequently unmodified metabolism can occur within the model. Yet, questions regarding fundamental characterization of how cell seeding density/spheroid size affects the oxygen micro-environment and the xenobiotic metabolism of the model system are still not available in the literature. Despite an acknowledged need, there is a lack of established cell lines derived from the gastrointestinal tract of fish to help understand dietary exposure to chemicals in the aquatic environment (). The use of the intestinal RTgutGC cell line to model metabolism in the form of a cellular aggregate therefore provides the opportunity to elucidate the metabolism of environmentally relevant contaminants in the gut environment in a more complex culture system. As described in later sections, this cell line cultured as spheroids demonstrates comparative morphology to the native intestine in the form of numerous polarized micro-villi formations on the edge of the spheroid structures which facilitates metabolism in this system and has been previously observed in the cell line when cultured on Transwell® inserts (). Staining for the presence of mucosubstances revealed strong staining for both acidic and neutral mucosubstances indicative of goblet cells which are comparable to expression of the intestine in vivo. Furthermore, available information also suggests an increasing use of intestinal spheroid cultures (; ; ), with increasing demand for teleost derived spheroids as the requirement for animal alternatives for fish ecotoxicological studies increases ().
Previous studies from our laboratories have demonstrated that the β-blocker propranolol, an environmentally relevant pharmaceutical, is actively metabolized both by hepatocytes and in spheroids derived from rainbow trout liver cells (; ). Despite the importance, as mentioned above, in vivo dietary uptake studies for chemicals in general and pharmaceuticals such as propranolol are not well reported in fish or aquatic models. Uptake of propranolol in the intestine has been reported to be less than half that of the liver in rabbit () and in murine systems (; ). Using the intestinal RTgutGC cell line cultured as spheroids and propranolol as our environmentally relevant test compound, we compared and contrasted different size classes of spheroids to test the hypothesis that the size of spheroids impact xenobiotic metabolism. To test this hypothesis, we used electron paramagnetic resonance (EPR) oximetry to determine oxygen gradients within this system as a function of spheroid size. We further characterized the functionality of the cell line using histochemical staining. To complement the determination of oxygen levels in different spheroid sizes, we used high performance liquid chromatography (HPLC) to determine the active metabolism of propranolol.
Materials and Methods
Reagent and Stock Preparation
All reagents were from Sigma-Aldrich (United Kingdom) unless otherwise indicated. Propranolol hydrochloride (99% pure, CAS 318-98-9, C16H22O2NCl) was supplied by industrial partner (AstraZeneca). Preparation of the oximetry probe LiPc (Lithium phthalocyanine) was carried out as previously described in detail ().
Cell Culture
The rainbow trout gastrointestinal cell line RTgutGC was a kind gift from Dr. Lucy Lee (University of Fraser Valley, Canada) (). The cell line was routinely cultured in our laboratory using 75 cm2 culture flasks at room temperature (21°C) in L-15 culture medium supplemented with 10% FBS (). Cells were seeded at a density of 5 × 104 cells/mL, and became confluent 7–8 days later. Spheroids were formed as previously outlined for another fish cell line (). Subsequent experiments were carried out on spheroids of three initial seeding densities (i.e., 12.5, 50 and 100 × 104 cells/mL), with a volume of 200 μL per spheroid well.
Morphological Characterization of the RTgutGC Spheroids
The growth of individual spheroids was calculated according to the methodology established previously in our laboratory (). Morphological characterization of the RTgutGC spheroid was observed under light microscopy over 14 days, with surface structure observed under Transmission Electron Microscopy (TEM) and histological staining of mucosubstances following previously established protocols ().
Electron Paramagnetic Resonance (EPR) Oximetry
Oxygen gradients across the spheroids were quantified as previously described by us (). Briefly, spectra were recorded on a Bruker EMX micro EPR spectrometer fitted with variable temperature accessory, operating at 9.4 GHz. Spheroids (2 per spectra recording) were drawn into the PTFE gas permeable tubing with ∼5 μL of medium per spheroid. The tube was folded once, and the spheroids allowed to sediment at the fold. Samples were maintained in the cavity at 292°K, which is equivalent to the incubation temperature (19°C). Oxygen saturation was quantified by measuring the peak to peak line width of the spectrum relative to a sample which contained only the probe and medium but not spheroids/cells. As per previous experiments (), the zone of hypoxic and anoxic cells was quantified based on mathematical calculations () following the identification of viable rim from EPR recordings.
Preparation of Spheroids for Exposure
Spheroids (7 days old) were pooled (for each separate experiment) from 96-well micro plates into a clean 96-well pHEMA-coated microplate at a seeding density of 12 spheroids per well of the 5 × 104 cells/mL seeding and 6 spheroids per well of the 10 × 104 cells/mL cell seeding density (in 75 μL L-15 medium; pH 7.4). These spheroid sizes were chosen as they adequately represent the range of spheroid radii typically reported in the non-tumor spheroid literature. For exposure, the spheroids were exposed to 75 μL of a solution of 200 μg/L of propranolol (final concentration 100 μg/L in well) reconstituted in L-15 medium and incubated at 15°C for 24 h. Control samples were quenched immediately after the addition of the exposure solution to samples using acetonitrile.
Metabolism of Propranolol in the Spheroids
Analyses were performed using Surveyor MS Pump Plus HPLC pump with HTC PAL autosampler coupled to TSQ Vantage triple quadrupole mass spectrometer equipped with heated electrospray (HESI II) source (all ThermoFisher Scientific, Hemel Hempstead, United Kingdom). Chromatographic separation was achieved using reversed-phase, 3 μm particle size, C18 Hypersil GOLD column 50 mm × 2.1 mm i.d. (Thermo Scientific, San Jose, CA, United States). Analytes were separated using a linear gradient of aqueous phase and Methanol both containing 0.1% of Formic Acid. Methanol content increased from 20% to 100% in 1.5 min and maintained for another 1.5 min before returning to the initial condition. The flow rate was 500 μL/min. Temperature of autosampler was set at 8°C while column was kept at a room temperature. HESI probe was operating in positive mode while an ion-spray voltage of +3.75 kV was applied. The heated capillary temperature was set at 270°C and the vaporizer temperature was 350°C. Nitrogen was employed as sheath and auxiliary gas at a pressure of 60 and 2 arbitrary units, respectively. The argon CID gas was used at a pressure of 1.5 mTorr. Quantification of propranolol was performed by monitoring characteristic multiple reaction monitoring (MRM) transitions 260.2→116.2 m/z (collision energy 17 eV). Internal standard method of quantification, using matrix matched standards was used in all samples analysis.
Additionally, CYP3A quantification in the intestinal spheroid model using the model inducer Testosterone was also examined (). CYP3A activity was quantified by measuring the extent of 6β-hydroxytestosterone (H2898, CAS: 62-99-7; Sigma) formation from testosterone using ultraperformance liquid chromatography systems (UltiMate 3000, ThermoScientific). Stock solutions were made up in HPLC grade methanol (Sigma, United Kingdom). Briefly, the cultured RTgutGC cells were seeded at varying densities and washing thrice with Hanks balanced salt solution and then incubated with 100 μM testosterone (T1500, CAS: 58-22-0; Sigma) for 2 h. At the end of incubation, 250 μL of the media was transferred into a glass vial with 250 μL of methanol and the 20 μL of the mixture injected onto the column. Samples, testosterone and 6β-hydroxytestosterone were chromatographed using Aquasil C18 column (150 mm × 4.6 mm, 3 μm; ThermoFisher) with a C18 security guard (Phenomenex, United Kingdom). The mobile phase consisted of diluted methanol in water with a gradient profile starting at 50% from 0 to 15 min, increasing to 60% until 20 min, increasing again to 85% until 22 min before decreasing back to 50%, all at a flow rate of 1 mL/min). The detection limits for testosterone and 6β-hydroxytestosterone metabolites was 0.1175 μM.
Statistical Analysis
Statistical analyses were preformed using R, Version 3.1.3 (). Data is given as mean values ± SEM, with n denoting the number of replicates per experiment unless otherwise indicated. These replicates are representative of non-parallel passages of the cell line, with each recording representative of 3-4 technical replicates. Data were first tested for normality and homogeneity of variance using the Anderson-Darling Normality test and Levene’s test respectively. Analysis of variance (ANOVA) was performed for multiple factor comparisons when assumptions were met. Due to non-normality and variable variance in micro-environment recordings, data was analyzed using a Friedman non-parametric test. A value of p < 0.05 was considered significant, with data presented as p < 0.001 demonstrating highly significant results.
Results
Morphological Characterization
Prior to the identification of micro-environment formation in the RTgutGC spheroid, it was critical that spheroid growth (across all cell seeding densities) was first established in order to identify the point at which spheroids were formed visually (Figure 1a) and to what size spheroids varied dependent on initial seeding (Figure 1b). This time point (day 7) was then used as the basis for assessment of micro-environment formation and later for the assessment of metabolism. During formation, the RTgutGC spheroid became significantly more compact, with a reduction in size of 30 – 40% observed irrespective of original seeding density. Transmission electron microscopy revealed microvilli (Figure 2A). Mucosubstances in the intestine are known to play an important role in the protection and uptake of xenobiotics from the ingested chyme, and their presence in the RTgutGC spheroid model was confirmed using histological staining (Figure 2B). Indeed, the intensity of staining is directly comparable to ex vivo adherent cultures of trout intestine (personal observation) and to cultures of the cell line grown on Transwell® inserts ().
FIGURE 1
FIGURE 2
Oxygen Micro-Environment Formation
Three experiments from non-parallel passages were recorded on day 7 and day 14 to elucidate variation in oxygen micro-environment formation as a function of seeding density. Diameters of the spheroids ranged from 143 to 444 μm (Table 1). Coefficient of variation between spheroids was recorded to denote comparability between experiments (and different passages) with an obvious trend toward minimization of variability in the larger size class (Table 1). Application of Friedman’s test revealed no significant changes in distribution of micro-environment formation over time or seeding density (χ2= 3, df = 2, p = 0.22) (Figure 3).
Table 1
| Seeding (Cells/Spheroid) | Sampling (Day) | Passage No. N = | Spectra No. N = | Δ 02 (%) | CV (%) | Diameter (μm) | Viable Rim (μm) | Hypoxic Zone (μm) |
|---|---|---|---|---|---|---|---|---|
| 2,500 | 7 | 3 | 14 | 68 ± 1.5 | 12 | 100 ± 5 | 68 | 13 |
| 14 | 14 | 68 ± 0.2 | 68 | 13 | ||||
| 10,000 | 7 | 3 | 13 | 51 ± 2.7 | 11 | 144 ± 4 | 73 | 41 |
| 14 | 10 | 60 ± 2.3 | 86 | 29 | ||||
| 20,000 | 7 | 4 | 10 | 54 ± 5.8 | 3 | 445 ± 3 | 269 | 113 |
| 14 | 10 | 41 ± 1.1 | 181 | 177 | ||||
Characteristics of the spheroids from the RTgutGC cell line with respect to variation in size as a function of initial cell seeding volume and the formation of micro-environments.
Data is presented as mean ± standard error of the mean. Data is representative of 3–4 passages with total spectra recordings (denoted by spectra) dependent on spheroid size and time. Clear spectra did not require extra sampling. This is due to 2–3 spheroids on average being used for the smaller size category to obtain a clear line width spectra, while 1–2 spheroids are required for the large size category (20,000 cells/spheroids). Seeding is representative of cells per spheroid (200 μL volume).
FIGURE 3

Impact of varying cell seeding densities on the formation of oxygen micro-environments. No significant differences were observed in the formation of oxygen microenvironment (p > 0.05). As denoted by the legend,
is representative of samples collected on day 7 where cells have become confluent in cell culture model and
is representative of samples collected on day 14.
Oxygen saturation was calculated as a percentage of narrowing line width in paramagnetic oximetry (
Metabolism of Propranolol in the Spheroids
All spheroid samples which underwent propranolol exposure were within the analytical limit of quantification, with exposure occurring on day 7 in order to investigate the relationship between metabolism and micro-environment formation. The depletion of propranolol was measured in four non-parallel individual passages (biological variability) of the RTgutGC cell line cultured as spheroids over 24 h, with each treatment in quadruplicate. A Shapiro–Wilk test revealed normal data (W = 0.9343, p = 0.29), while a Levene test revealed normal homogeneity of variance (df = 3, f = 0.064, p = 0.98), and so an ANOVA was applied to the data. This revealed significant differences between time (p < 0.001), but not between seeding densities (p = 0.81). Despite the non-significant differences between the two seeding densities, the degree of substrate depletion was different (Figure 4) between the lower seeding category of 50 × 104 cells/mL (n = 4, CV = 9.23%, 25% difference between 0 and 24 h) and the higher seeding category of 100 × 104 cells/mL (n = 4, CV = 2.38%, 15.25% difference between 0 and 24 h).
FIGURE 4

Substrate depletion of propranolol over time using two different cell seeding densities. Each treatment is repeated in quadruplicate over 4 non-parallel passages (n = 4). No significant difference in terms of metabolism was observed between the two seeding densities (p = 0.80; ns), but was found to be different over time (p < 0.001). As previously outlined in Figure 3,
is representative of samples collected immediately following exposure with no active metabolism of product,
while is indicative of samples collected after 24 h of metabolism by the spheroid model.
To investigate if the metabolism of propranolol occurred via the CYP3A pathway, standard curves were generated for testosterone and 6β-hydroxytestosterone as controls for measurement of CYP3A activity in the RTgutGC cell line (2D and 3D). No response was observed in cells seeded at any of the concentrations used, although numerous methodologies were tried including increasing seeding densities, incubation time, or indeed analytical chemistry by increasing injection volume from 20 to 100 μL, which caused no significant improvement in resulting peak (data not shown). In order to ascertain whether testosterone as a CYP3A inducer is cell line specific through a minimization of enzyme activity in cell line versus native tissue (via de-differentiation), primary cultures of rainbow trout intestine were used as controls, with cells exposed directly rather than allowed to attach to substrate (a suspension culture). Primary culture observations indicate that trout intestine does not directly metabolize testosterone to 6β-hydroxytestosterone as predicted in other tissue models (e.g., liver) (
Discussion
Propranolol metabolism is complex. In mammals we understand there are three hepatic pathways: hydroxylation of the naphthalene ring, and two processes focused on the decomposition of the side chain, that are glucuronidation and N-desisopropylation that together provide 14 potential metabolites (see Supplementary File for details and diagrams). In fish we understand little of which of these potential paths and processes are active. In this study, different sized spheroids initiated through augmentation of initial cell seeding were characterized. As previously observed using the RTG-2 cell line, spheroid diameter appears to stabilize after 7 days in culture over all seeding densities investigated (
The transport of compounds through cell membranes is a well-known feature in the determination of xenobiotic detoxification. This feature has a key impact on absorption potential, distribution, elimination, toxicity and especially efficacy of compounds as noted in cancer spheroid models (
As demonstrated in the current study, the RTgutGC cell line is capable of metabolizing propranolol (indicated through compound depletion) with metabolic rate being linked with spheroid size. The use of spheroids in uptake and diffusion studies is increasingly revealing new insights pertaining to drug metabolism and effects in the cellular environment (
The liver has long been considered the primary organ responsible for drug metabolism, with several studies addressing hepatic clearance of propranolol in both murine (
Studies evaluating and supporting the combined testing of both intestinal and hepatic metabolism, either in vivo or in vitro are increasing (
As previously outlined, most studies do not justify the use of small (or large) spheroids for drug uptake to investigate metabolism. The data indicates that spheroids with a size of less than 200 μm would be preferable to use when extreme micro-environments which can affect cellular metabolism should be kept to a minimum. To the our knowledge, the present study presents the first study addressing why the use of different sized spheroids may negatively/adversely impact uptake and xenobiotic metabolism through the formation of micro-environments which could be detrimental to cellular health and activity in a non-tumor spheroid model. In order to utilize the spheroid model, a thorough characterization of all spheroid models derived from different organs should be undertaken to establish baseline data to facilitate comparison. In this instance, we have begun this with the current study and previous work (
Statements
Author contributions
LL, SJ, WP, ND, and AJ conceived and designed the experiments. LL, ND, and MT performed the experiments. LL and MT analyzed the data. LL, SJ, SO, and AJ contributed to the writing of the manuscript. SO, ND, MT, SJ, and AJ critically reviewed and revised the manuscript.
Funding
The authors gratefully acknowledge funding from the Biotechnology and Biological Sciences Research Council (BBSRC) and Natural Environment Research Council (NERC) Industrial Partner Award with AstraZeneca; Grant BB/L01016X/1 to AJ (PI) and SJ. This work was conducted in part by LL whilst in receipt of a scholarship from University of Plymouth and the AstraZeneca Safety Health and Environment Research Program. Funding bodies did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. SO is an employee of AstraZeneca, a biopharmaceutical company specialized in the discovery, development, manufacturing and marketing of prescription medicines. SO’s work represents an AstraZeneca contribution in kind to the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115735 – iPiE: Intelligent-led Assessment of Pharmaceuticals in the Environment; resources of which are composed of financial contribution from the European Union’s Seventh Framework Program (FP7/2015-2018) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies’ in kind contribution.
Acknowledgments
We thank Glenn Harper for outstanding quality of electron microscopy (Plymouth Electron Microscopy Centre, University of Plymouth, United Kingdom). We would like to thank Dr. Malcolm Hetheridge (Exeter University) for his help facilitating the analytical chemistry.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer ORP and handling Editor declared their shared affiliation.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphar.2018.00947/full#supplementary-material
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Summary
Keywords
spheroids, EPR-oximetry, micro-environment, metabolism, intestine, β-blocker, propranolol
Citation
Langan LM, Owen SF, Trznadel M, Dodd NJF, Jackson SK, Purcell WM and Jha AN (2018) Spheroid Size Does not Impact Metabolism of the β-blocker Propranolol in 3D Intestinal Fish Model. Front. Pharmacol. 9:947. doi: 10.3389/fphar.2018.00947
Received
04 June 2018
Accepted
02 August 2018
Published
22 August 2018
Volume
9 - 2018
Edited by
Miia Turpeinen, University of Oulu, Finland
Reviewed by
Arturo Anadón, Complutense University of Madrid, Spain; Olavi R. Pelkonen, University of Oulu, Finland
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Copyright
© 2018 Langan, Owen, Trznadel, Dodd, Jackson, Purcell and Jha.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Awadhesh N. Jha, a.jha@plymouth.ac.uk
This article was submitted to Drug Metabolism and Transport, a section of the journal Frontiers in Pharmacology
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