We present a protocol for growing high-reproducible spheroids and their phenotypic characterization using image capture and proteomics.
We present a protocol that describes the properties and advantages of using a standalone clinostat incubator for growing, treating, and monitoring 3D cell cultures. The clinostat mimics an environment where cells can assemble as highly reproducible spheroids with low shear forces and active nutrient diffusion. We demonstrate that both cancer and non-cancer hepatocytes (HepG2/C3A and THLE-3 cell lines) require 3 weeks of growth prior to achieving functionalities comparable to liver cells. This protocol highlights the convenience of utilizing incubators for 3D cells with cameras monitoring the cell growth, as snapshots can be taken to count and measure spheroids upon treatment. We describe the comparison of THLE-3 and HepG2/C3A cell lines, showing how non-cancerous cell lines can be grown as well as immortalized cancer cells. We demonstrate and illustrate how proteomics experiments can be conducted from a few spheroids, which can be collected without perturbing cell signaling, i.e., no trypsinization required. We show that proteomics analysis can be used to monitor the typical liver phenotype of respiratory chain metabolism and the production of proteins involved in metal detoxification and describe a semi-automated system to count and measure the spheroid’s area. Altogether, the protocol presents a toolbox that comprises a phenotypic characterization via image capture and a proteomics pipeline to experiment on 3D cell culture models.
In vitro cell cultures have been proven to be necessary and invaluable in establishing fundamental knowledge in biology. Much of the scientific understanding in biology and cancer specifically has come from the 2D culture system that is cells growing in a monolayer. Although 2D culture has been the dominant cell culture system, it has many disadvantages that can potentially stifle further biological progress. For example, 2D cultures lack cell-cell interactions important for cell signaling and proliferation1. To date, 3D culture systems have been shown to better model differentiation, drug response, tumor invasion, and biology2,3,4,5. 3D modeling of malignant cancers is especially vital due to the rise in the aging population and cancer mortality. Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide and frequently has an abysmal prognosis6. HCC is known to have a low cure rate, poor drug response, and high rate of reoccurrence6,7,8. Several 3D models for normal liver and HCC have been developed that mimic the physiology of in vivo normal and malignant liver tissue9,10.
Some of the current 3D systems include liquid overlays, bioreactors, hydrogel, scaffolds, and 3D-printed structures. Spheroids generated in bioreactors specifically provide unique advantages because they mimic tumor distribution of nutrient exposure, gas exchange, and cell proliferation/quiescence11. Bioreactors are especially suitable for cancer models due to their ease of use, large scalability, nutrient diffusion, and accessibility11. In addition, bioreactors can allow for high throughput experiments, greater reproducibility, and decreased human error. The bioreactor used in this study is unique because it simulates a system of reduced gravity, which minimizes disruptive shearing forces applied in typical bioreactors allowing for better reproducibility12. The omnidirectional gravity and reduction in shearing forces allow for the cells to develop in a more physiological manner. As evidence, HepG2/C3A cells grown under this methodology develop spherical organelles that produce in vivo levels of ATP, adenylate kinase, urea, and cholesterol13,14. In addition, drug treatments in this 3D system are more advanced and automated in comparison to 2D cultures. In 2D cultures, drug treatments must often have a short time course due to the need to trypsinize and maintain cell health. Yet, in our case, we can perform long-term drug treatments of spheroids without the need to disrupt the structure and physiology of the cells. Therefore, a shift from 2D to 3D cultures is necessary to better model in vivo biological phenomena and further scientific development.
This paper presents a methodology for growing high-reproducible spheroids (Figure 1 and Figure 2) and shows a semi-automated system to phenotypically characterize 3D structures (Figure 3). At the image level, we provide information on counting and measuring spheroids' area (Figure 3). By using mass spectrometry methods, we show how proteomics can be used to assess specific biological functions (Figure 4). By collecting and analyzing this data, we hope to improve the understanding of the biology behind 3D cell culture systems.
Understanding the biology behind three-dimensional (3D) cellular structures is extremely important for a more comprehensive knowledge of their functionalities. There is a growing interest in using 3D models for studying complex biology and performing toxicity screening. When cultivating cells in 3D many factors need to be considered, including the phenotypic assessment of the model system. A phenotype is defined as a group of observable characteristics of a specific organism, such as morphology, behavior, physiological and biochemical properties20.
In this protocol, we demonstrate how proteomics experiments can be conducted from a few spheroids and can be used to monitor the typical liver phenotype. Mass spectrometry has become an extensively applied method for 3D cell characterization, allowing the investigation of a variety of biological questions12,16,21,22. For a comprehensive proteome analysis, it is recommended to use at least 20 µg of protein starting material, from which 1 µg is injected into the mass spectrometer. It is important to mention that adding less sample might lead to loss of sensitivity, and adding more would gradually worsen the quality of the chromatography and eventually lead to blocking the column. In this study, we showed that the HepG2/C3A and THLE-3 spheroids are enriched with important proteins from glycolysis and TCA cycle, which are specific liver pathways and are critical for maintaining blood glucose levels and for energy production23,24. Actually, mass spectrometry analysis provides not only information at the protein level but also allows the investigation of protein post-translational modifications, as shown previously by our group16.
Another aspect to be considered in 3D phenotypic studies is the number and size of spheroids. Besides making experiments more reproducible, counting the number of spheroids and determining their size is essential to determine when to split the culture into multiple bioreactors, as the number of 3D structures within a vessel can impact spheroids' size and metabolic activity levels. However, it is important to highlight that the number and size of spheroids depend on the cell line, starting number of cells, splitting process, and time of collection. Details of HepG2/C3A spheroid culture, such as number of cells per spheroids, protein content, and size as a function of age, were provided by Fey, Korzeniowska, and Wrzesinski25. For accurate and successful analysis using the semi-automated method described here, the most critical step is a good spheroids' picture. For simplicity, the picture can be taken with a phone or tablet, but its resolution should be kept as high as possible. As images are quick to acquire, they allow large-scale screening experiments to visualize specific phenotypic features or investigate responses to drug treatment. Therefore, due to the increasing number of cell-based assays, a number of open-source software have been developed over the past 10 years for image analysis26. In this protocol, we describe a semi-automated system using the software FIJI18 to count and measure spheroids' size. We presented scripts (simple programming commands) to define a sequence of algorithmic operations that can be applied to an image collection, making the analysis an easy and quick process. However, depending on the characteristic of the spheroid, a manual measurement should be employed. For instance, if the spheroids are too translucent, the FIJI script will be imprecise. By the way, one of the most important criteria for this method to work is the compactness of the spheroids. This characteristic will contribute to a more enhanced color contrast between the spheroids and the background, which is necessary for the method to be accurate.
In summary, besides presenting a methodology for growing high-reproducible spheroids, a semi-automated system coupled with phenotypic characterization via image capture and proteomics was also described. We expect this toolbox for analyzing 3D cells to become more robust with full-automated image analysis software and next-generation mass spectrometers.
The authors have nothing to disclose.
The Sidoli lab gratefully acknowledges the Leukemia Research Foundation (Hollis Brownstein New Investigator Research Grant), AFAR (Sagol Network GerOmics award), Deerfield (Xseed award), Relay Therapeutics, Merck, and the NIH Office of the Director (1S10OD030286-01).
1.5 mL microcentrifuge tubes | Bio-Rad | 2239480 | |
10 mL syringe | Fisher Scientific | 1481754 | Luer lock tip, graduated to 12 mL |
1000 µL wide bore pipet tips | Fisher Scientific | 14222703 | |
200 µL wide bore pipet tips | Fisher Scientific | 14222730 | |
96-well Orochem filter plate | Orochem | OF1100 | |
96-well skirted plate | Axygen | PCR-96-FS-C | |
96-well vacuum manifold | Millipore | MAVM0960R | |
Ammonium bicarbonate | Sigma | A6141-25G | |
Bronchial Epithelial Cell Growth Medium (BEGM) | Lonza | CC-3170 | |
Cell culture grade water | Corning | 25-055-CV | |
ClinoReactor | CelVivo | N/A | Bioreactor for 3D cell culture |
ClinoStar incubator | CelVivo | N/A | CO2 incubator for 3D cell culture |
DTT | Sigma | D0632-5G | |
Dulbecco's Modified Eagle's Medium (DMEM) | Fisher Scientific | MT17205CV | |
Elplasia 24-well round bottom ultra-low attachment plate containing microwells | Corning | 4441 | |
Fetal Bovine Serum | Fisher Scientific | MT35010CV | |
Formic acid | Thermo | 28905 | |
Hank's Balanced Salt Solution (HBSS) | Fisher Scientific | MT21022CV | |
hEGF | Corning | 354052 | |
HERAcell vios 160i | Thermo | 51033557 | CO2 incubator for 2D cell culture |
HPLC grade acetonitrile | Fisher Scientific | A955-4 | |
HPLC grade methanol | Fisher Scientific | A452-1 | |
HPLC grade water | Fisher Scientific | W5-4 | |
Iodoacetamide | Sigma | I1149-5G | |
L-glutamine | Fisher Scientific | MT25015CI | |
Non-essential amino acids | Fisher Scientific | MT25025CI | |
Oasis HLB Resin 30 µm | Waters | 186007549 | |
Orbitrap Fusion Lumos Tribrid mass spectrometer | Thermo | IQLAAEGAAPFADBMBHQ | High resolution mass spectrometer |
PAULA microscope | Leica | ||
Penicillin-Streptomycin | Fisher Scientific | MT3002CI | |
PerkinElmer Victor X2 multilabel microplate reader | PerkinElmer | ||
pH paper | Hydrion | 93 | |
Phosphoetanolamine | Sigma | P0503 | |
Phosphoric acid | Fisher Scientific | A260-500 | |
Pipette gun | Eppendorf | Z666467 (Milipore Sigma) | |
Refrigerated centrifuge | Thermo | 75-217-420 | |
Reprosil-Pur resin | MSWIL | R13.AQ.003 | 120 Å pore size, C18-AQ phase, 3 μM bead size |
SDS | Bio-Rad | 1610301 | |
Sequencing grade modified trypsin | Promega | V511A | |
SpeedVac vacuum concentrator (96-well plates) | Thermo | 15308325 | Savant SPD1010 |
Sterile hood | Thermo | 1375 | |
Sterile serological pipettes | Fisher Scientific | 1367549 | |
S-trap | Protifi | C02-micro-80 | |
Syringe needle (18 G) | Fisher Scientific | 14817100 | 3" length, 0.05" diameter |
Trifluoroacetic acid (TFA) | Thermo | 28904 | |
Trypsin-EDTA | Gibco | 25300-054 | |
Vortex | Sigma | Z258415 | |
Water bath | Fisher Scientific | FSGPD10 |