Autofluorescence of NADH is a new biomarker for sorting and characterizing cancer stem cells in human glioma
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The existing cell surface markers used for sorting glioma stem cells (GSCs) have obvious limitations, such as vulnerability to the enzymatic digestion and time-consuming labeling procedure. Reduced nicotinamide adenine dinucleotide (NADH) as a cellular metabolite with property of autofluorescence has the potential to be used as a new biomarker for sorting GSCs.
A method for sorting GSCs was established according to the properties of the autofluorescence of NADH. Then, the NADHhigh and NADHlow subpopulations were sorted. The stem-like properties of the subpopulations were evaluated by qRT-PCR, western blot analyses, limiting dilution assay, cell viability assay, bioluminescence imaging, and immunofluorescence analysis in vitro and in vivo. The relationship between CD133+/CD15+ cells and NADHhigh subpopulation was also assessed.
NADHhigh cells expressed higher stem-related genes, formed more tumor spheres, and harbored stronger pluripotency in vitro and higher tumorigenicity in vivo, compared to NADHlow subpopulation. NADHhigh glioma cells had the similar stemness with CD133+ or CD15+ GSCs, but the three subpopulations less overlaid each other. Also, NADHhigh glioma cells were more invasive and more resistant to chemotherapeutic drug temozolomide (TMZ) than NADHlow cells. In addition, the autofluorescence of NADH might be an appropriate marker to sort cancer stem cells (CSCs) in other cancer types, such as breast and colon cancer.
Our findings demonstrate that intracellular autofluorescence of NADH is a non-labeling, sensitive maker for isolating GSCs, even for other CSCs.
KeywordsGlioma stem cells Autofluorescence NADH FACS Biomarker
Basic fibroblast growth factor
Cancer stem cells
Epidermal growth factor
Fluorescence-activated cell sorting
Flavin adenine dinucleotide
Fluorescence lifetime microscopy
Glioma stem cells
Nicotinamide adenine dinucleotide
World Health Organization
Glioma stem cells (GSCs) are believed to be responsible for tumor initiation, progression, chemo- and radioresistance, and recurrence of gliomas [1, 2, 3, 4]. The identification and isolation of GSCs are crucial for a better understanding of their properties and developing GSC-targeting therapies. GSCs are usually identified and isolated from primary tumors or glioma cell lines by fluorescence-activated cell sorting (FACS) based on the cell surface makers, such as CD133 and CD15. Early studies reported that only 100 CD133-positive cells of glioma could produce a phenocopy of parent tumor in NOD-SCID mice, whereas 105 CD133-negative cells could not [1, 5]. CD15 has also been considered as another reliable surface marker for isolating GSCs . However, recent studies indicated that CD133- or CD15-negative glioma cells also possessed some GSC characteristics [6, 7, 8]. It is unclear whether partial CD133/CD15-negative cells have the properties of CSCs per se or partial CD133/CD15-negative GSCs are derived from CD133/CD15-positive subpopulation missing the markers by enzymatic digestion [9, 10]. In addition, the antibodies of CD133/CD15 are expensive and the labeling process is time-consuming. Therefore, it is necessary to find alternative strategies, which are more specific, simple, and economic for the isolation of GSCs.
Energy metabolism is involved in the self-renewal, reprogramming, and differentiation of regular stem cells and cancer stem cells (CSCs) [11, 12]. Reduced nicotinamide adenine dinucleotide (NADH) is a key carrier of electrons in cellular energy metabolism. It possesses a property of autofluorescence with an excitation wavelength at 340 ± 30 nm and an emission wavelength within the 460 ± 50 nm range [13, 14], and has been used as an important intracellular autofluorescence component to non-invasively monitor and analyze metabolic activity of living cells and tissues [15, 16]. Recently, NADH fluorescence intensity and fluorescence lifetime of bound and free NADH have been used to distinguish stem cells from their differentiated progeny [17, 18, 19]. Besides, NADH has been used to screen or monitor GSC metabolic state by using fluorescence lifetime microscopy (FLIM) . However, the usability of NADH autofluorescence in the isolation and purification of GSCs by FACS has not been evaluated.
In the present study, we applied the autofluorescence of NADH as a non-labeling marker to isolate GSCs by FACS. Compared to NADHlow subpopulation, NADHhigh subpopulation exhibited higher stem-like properties, including abilities of self-renewal, multilineage differentiation, and tumorigenesis, as well as higher invasive ability and resistance to chemotherapeutic temozolomide (TMZ). Besides, NADHhigh as a biomarker could be used to isolate breast and colon CSCs. Therefore, NADH is a suitable biomarker for the isolation of GSCs or other CSCs.
Materials and methods
Human glioma specimens and the preparation of single cell suspension
A total of 13 fresh surgical glioma specimens were collected from patients enrolled in the Southwest Hospital, Third Military Medical University, Chongqing, China, after signing an informed consent from patients or their guardian. All patients had not received chemoradiotherapy before surgery. The histopathological grading was in accordance with the World Health Organization (WHO) classification (2016). The clinicopathologic information of these patients is summarized in Additional file 1: Table S1. This study was approved by the Ethics Committee of Southwest Hospital.
To prepare the single cell suspension, fresh surgical glioma tissues were collected and cut into small pieces immediately, and then, glioma cells were isolated using the Papain Dissociation System (Worthington Biochemical, Lakewood, NJ, USA) as previously reported [21, 22] and suspended in PBS at 1–5 × 106 cells/mL.
Cell lines and culture
Glioma cell lines (T98G, LN229), breast cancer cell line (MDA-MB-231), and colon cell line (HT-29) were purchased from ATCC (VA, USA). Primary glioma cells GBM1 and GBM2 were respectively isolated from two human glioma surgical specimens in our laboratory [23, 24]. All the cell lines were maintained in DMEM (HyClone, USA) supplemented with 10% fetal bovine serum (FBS) (HyClone, USA). The medium for tumorsphere culture was composed of F12 medium containing 20 μL/mL B27 supplement (Gibco, USA), 20 ng/mL basic fibroblast growth factor (bFGF), and 20 ng/mL epidermal growth factor (EGF) (both from PeproTech, USA) without serum. All the cells were cultured at 37 °C in 5% CO2 and 100% humidity.
FACS analysis and cell sorting
The cultured glioma cells were digested by trypsin or accutase and resuspended with PBS. The fresh glioma specimens were transferred to laboratory on ice in half hour after surgery, then washed and enzymatically dissociated into single cells and resuspended in PBS. The staining procedures for CD133 and CD15 markers were performed as previously described [6, 8]. The labeling antibodies were anti-CD133-APC antibody (Clone REA816; Miltenyi Biotec, Germany) and anti-CD15-FITC antibody (Biolegend, USA) with REA Control (S)-APC (Miltenyi Biotec, Germany) and FITC Mouse IgM (Biolegend, USA) as controls, respectively.
The FACS analysis and cell sorting were performed on BD FACS Aria II cytometer (USA) or Beckman moflo XDP (USA). For analyzing and sorting with NADH autofluorescence intensity as a marker, an excitation wavelength of 375 nm or 355 nm and an emission wavelength of 450/50BP filter were used. For analyzing and sorting with CD133 and CD15 as markers, labeled cells were analyzed and sorted with corresponding excitation and emission wavelengths of the fluorochrome. All data were analyzed with BD FACSDiva software version 8 or Beckman moflo XDP submmit 5.2.
Limiting dilution assay
Limiting dilution assay was performed as previously described . Briefly, serial twofold dilutions (from 40 to 0 cells) of different glioma, breast cancer, and colon cells were seeded into ultra-low adhesion 96-well plates (10 wells per dilution) (Costar, USA) and cultured in tumorsphere medium. After incubation for 2 weeks, wells without spheres (log2, Y-axis) were counted and plotted against the number of cells plated per well (X-axis) to calculate the sphere formation efficiency.
RNA preparation and qRT-PCR
Total RNAs from sorted cells by FACS were extracted with RNA extracting Kit (Fastagen, China) according to the manufacturer’s instructions. One microgram of total RNA was reverse transcribed with the Reverse Transcription Kit (Takara, Dalian, China). Quantitative real-time PCR was carried out using the SYBR PrimeScript PCR kit II (TaKaRa, Japan). The level of β-tubulin mRNA was used as the internal control. The primers used in this study are listed in Additional file 1: Table S2.
Cell viability assay and IC50 evaluation
Different subpopulations of GBM1 and LN229 cells were seeded in 96-well plates at 2 × 103 cells/well and treated with TMZ at the indicated concentrations for 48 h. The viability of glioma cells was measured by using a Cell Counting Kit-8 (Beyotime, China) according to the manufacturer’s instructions. The OD values at 450 nm were recorded by fluoroanalyzer (Floskan Ascent, USA).
For induction of differentiation, NADHhigh cells were cultured in DMEM with 10% FBS for 7 days. The NADHhigh cells cultured in same conditions within 6 h were used as controls. Both differentiated and control cells were fixed in 4% paraformaldehyde for 30 min, washed three times with PBS at room temperature, and incubated with blocking buffer containing 10% normal goat serum and 0.3% Triton. The samples were incubated with primary antibodies anti-Sox2 (#3579, 1:400, CST), anti-Nestin (#33475, 1:400, CST), and anti-GFAP (#12389, 1:400, CST) overnight at 4 °C. Hoechst 33342 was used to counterstain the cell nuclei. After washing with PBS, the samples were mounted with Immuno-Mount™ (Thermo Scientific, USA) and then examined on a LEICA TCS-SP5 confocal microscope (× 63 objective).
Xenograft in NOD-SCID mice and bioluminescence imaging
The animal study was performed in accordance with the protocol approved by the Institutional Animal Care and Use Committee of Southwest Hospital, Third Military Medical University (TMMU). NOD/SCID female mice (5 weeks old) were purchased from the Laboratory Animal Center of TMMU. Different treated GBM cells were washed and resuspended in PBS and mixed with Matrigel (1:1, BD Biosciences), then subcutaneously injected into NOD/SCID mice at 4 × 103, 4 × 104, and 4 × 105 cells (100 μL/site) with the left flank as the test group and right flank as the control group. Tumor growth was monitored by bioluminescence imaging using In Vivo Imaging System (IVIS) Spectrum (Perkin Elmer, USA) and Living Image Software for IVIS (Perkin Elmer). At the end of 6 weeks after the injection, the mice were killed. Xenograft tumors were removed and weighted.
Western blotting was performed as previously described . The primary antibodies used in western blot were anti-Sox2 (#3579, 1:1000, CST), anti-CD133 (#64326, 1:1000, CST), anti-Nanog (#8822, 1:1000, CST, USA), and anti-β-tubulin (#2128, 1:10000, CST).
Transwell invasion analysis
Glioma cells were seeded into the upper chambers (Millipore, 8.0 μm, 24 well) that were coated with 15 μL/well of Matrigel in advance (Corning, USA) at the density of 3 × 104 cells/well in 200 μL of serum-free DMEM, and then, the upper chambers were placed in a 24-well plate added with 600 μL/well DMEM supplemented with 10% FBS. After incubation for 24 h, the cells were fixed with 4% paraformaldehyde followed by crystal violet staining. Non-invading cells were removed with a cotton swab, and the images of stained cells were collected by microscope (Olympus, Japan).
All experiments were performed at least three times. Statistical analysis was performed by using SPSS statistical software (SPSS16.0, Chicago, CA, USA) and GraphPad Prism 6 software (GraphPad, La Jolla, CA, USA). The unpaired two-group comparison and multiple comparisons were made with Student’s t test or one-way ANOVA, respectively. Data were presented as the mean ± SD. Statistical significance was set at *p < 0.05, **p < 0.01, and ***p < 0.001.
NADHhigh and NADHlow subpopulations can be sorted from glioma cells by FACS in vitro
NADHhigh glioma cells exhibit GSC traits in vitro
Previous studies showed that GSCs harbored multipotency to differentiate into neurons, astrocytes, and oligodendrocytes, and stem cell markers disappeared with the differentiation [28, 29]. Hence, we evaluated whether the NADHhigh subpopulation had multiple differentiation potential by a differentiation assay. As expected, the differentiated NADHhigh cells almost lost not only autofluorescence of NADH but also neural stem/progenitor markers Sox2 and Nestin and re-expressed astroglial marker GFAP (Fig. 2d). Thus, these data strongly indicate that NADHhigh glioma cells have the characteristics of GSCs in vitro.
NADHhigh glioma cells show high tumorigenicity in vivo
NADHhigh glioma subpopulation possesses similar stem-like properties with CD133+ or CD15+ cells, but only partially overlaps with them
The percentage of CD133+ and CD15+ cells in NADHhigh/low subpopulations of glioma cell lines
Percentage of CD133+ cells
Percentage of CD15+ cells
0.73 ± 0.04
2.10 ± 0.13
0.60 ± 0.13
0.50 ± 0.07
2.47 ± 0.44
0.43 ± 0.09
0.47 ± 0.04
2.63 ± 0.24
0.43 ± 0.11
0.40 ± 0.13
1.37 ± 0.22
2.27 ± 0.22
0.63 ± 0.31
4.77 ± 0.24
6.40 ± 0.07
6.23 ± 0.51
0.53 ± 0.04
1.83 ± 0.18
0.80 ± 0.13
0.13 ± 0.04
0.67 ± 0.04
0.27 ± 0.04
The invasion ability and temozolomide resistance of NADHhigh subpopulation are comparable with CD133+ and CD15+ subpopulations in glioma cells
The intensity of NADH autofluorescence can be used as a biomarker to sort other CSCs
Many endogenous ingredients of cells and tissues, such as some amino acids, collagen, elastin, NAD(P) H, flavin adenine dinucleotide (FAD), vitamins, lipids, and porphyrins, possess natural autofluorescence [36, 37]. Because these endogenous autofluorescence ingredients are the metabolites of cells or tissues, their autofluorescence intensity may directly reflect the physiological and/or pathological status of cells and tissues. So far, only the autofluorescence of NAD(P) H and FAD has been widely studied, mainly to be used in monitoring alteration of metabolic profiles and cellular oxidation-reduction status [38, 39, 40]. Moreover, the autofluorescence of NAD(P) H and FAD has been studied in normal stem cells and CSCs. Quinn et al. reported that the quantitative metabolic imaging using the endogenous fluorescence of NADH and FAD could monitor human mesenchymal stem cell differentiation into adipogenic and osteoblastic lineages . Fluorescence of free and protein-bound NADH could discriminate different differentiation stages of neuronal progenitor stem cells . Buschke et al. used multiphoton flow cytometry to non-invasively characterize and purify populations of intact stem cell aggregates based on NADH intensity and assessed the differentiation capacity of sorted populations . Bonuccelli et al. demonstrated that NAD(P) H autofluorescence was a new metabolic biomarker for CSCs in MCF-7 breast cancer cell line and sorted high NAD(P) H autofluorescence intensity cells exhibited CSC phenotype . Miranda-Lorenzo et al. used FAD autofluorescence as a novel tool to isolate and characterize epithelial CSCs, but it had obvious limitations, such as exogenous riboflavin needed to be added to enhance the sensitivity, and the experimental results varied with the concentrations of riboflavin, incubation times, and cell concentrations . Therefore, in comparison with FAD, NADH autofluorescence is a more reliable and promising biomarker to be used to sort CSCs without exogenous substances to be added. In the present study, we sorted NADHhigh subpopulation from glioma cells and further demonstrated that this subpopulation possessed the properties of CSCs, featured with significant increase of stemness-related gene expression, tumorsphere formation, invasiveness, resistance to TMZ in vitro, and tumorigenicity in vivo.
Herein, we used a wavelength of 355 nm or 375 nm for the autofluorescence of NADH. However, under our experimental conditions, the sorted NADHhigh subpopulation actually also contained NADPHhigh cells because NADH and NADPH are spectrally identical. Nevertheless, despite the two co-enzymes exert different functions with NAD/NADH as a key determinant of cellular energy metabolism and NADP/NADPH as a central role in biosynthetic pathways and antioxidant defense, both of them may be important for stemness maintenance of CSCs. Several other studies have suggested that the concentration of NADH is higher (up to 5 times) than the NADPH in mammalian and the quantum yield of NADH is 1.25 to 2.5 times higher than that of NADPH . Since NADH is the main source of the autofluorescence, we used NADHhigh but not NAD(P) Hhigh subpopulation as GSCs.
CD133 and CD15 have been regarded as reliable maker for enriching GSCs. In our studies, we compared the relationship of CD133+, CD15+, and NADHhigh subpopulations and found that CD133/CD15 defines distinct cell subpopulations and both CD133+ and CD15+ cells were only partially overlapped with NADHhigh subpopulation in glioma cells. Thus, NADHhigh may define a subset of GSCs independent of CD133+ and CD15+ subsets. As for the relationship between CD133+ and CD15+ cells, Son et al. reported that most CD133+ tumor cells freshly isolated from glioma specimens were CD15+ , but a less overlap between CD133+ and CD15+ subsets was observed in GBM1 and LN229 cells (Additional file 1: Figures S6 and S7).
As a basic metabolite, NADH is ubiquitously distributed in cells. Therefore, NADH autofluorescence could be a biomarker not only for GSCs, but also for other CSCs. Indeed, we found that NADHhigh/ALDH+, NADHhigh/ALDH−, and NADHlow/ALDH+ subpopulations had higher self-renewal ability than NADHlow/ALDH− subpopulation in breast cancer and colon cancer cells, implying that the autofluorescence of NADH might serve as a biomarker for CSCs of these cancers.
Our findings demonstrate that intracellular autofluorescence of NADH is a non-labeling, sensitive maker for isolating GSCs, even for other CSCs.
We would like to thank the specimen bank of Southwest Hospital for the specimens.
YC, XB, and QM contributed to the study conception and design. YC, XB, and QM contributed to the development of methodology. YY, YZ, JM, RC, and MZ contributed to the acquisition of data. QM, YY, YW, and LW contributed to the analysis and interpretation of data. WD, DW, and DX were involved in the administrative, technical, or material support. QM, YW, PZ, YC, and XB contributed to the writing, review, and/or revision of the manuscript. YC and XB were involved in the study supervision. All authors read and approved the final manuscript.
This work was supported by grants from the National Natural Science Foundation of China (innovative research group projects, 81821003 to XW Bian), Chongqing Science and Technology Commission (cstc2017jcyjA0544 to QH Ma), and Southwest Hospital Foundation (SWH2016JCZD-09 to DY Guo).
Ethics approval and consent to participate
This study was approved by the Ethical/Scientific Committee of Southwest Hospital.
Consent for publication
The authors declare that they have no competing interests.
- 10.Barteneva NS, Ketman K, Fasler-Kan E, Potashnikova D, Vorobjev IA. Cell sorting in cancer research--diminishing degree of cell heterogeneity. Biochim Biophys Acta. 1836;2013:105–22.Google Scholar
- 40.Skala MC, Riching KM, Gendron-Fitzpatrick A, Eickhoff J, Eliceiri KW, White JG, et al. In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proc Natl Acad Sci U S A. 2007;104:19494–9.PubMedPubMedCentralCrossRefGoogle Scholar
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