Clonal analyses and gene profiling identify genetic biomarkers of the thermogenic potential of human brown and white preadipocytes

Journal name:
Nature Medicine
Volume:
21,
Pages:
760–768
Year published:
DOI:
doi:10.1038/nm.3881
Received
Accepted
Published online

Abstract

Targeting brown adipose tissue (BAT) content or activity has therapeutic potential for treating obesity and the metabolic syndrome by increasing energy expenditure. However, both inter- and intra-individual differences contribute to heterogeneity in human BAT and potentially to differential thermogenic capacity in human populations. Here we generated clones of brown and white preadipocytes from human neck fat and characterized their adipogenic and thermogenic differentiation. We combined an uncoupling protein 1 (UCP1) reporter system and expression profiling to define novel sets of gene signatures in human preadipocytes that could predict the thermogenic potential of the cells once they were maturated. Knocking out the positive UCP1 regulators, PREX1 and EDNRB, in brown preadipocytes using CRISPR-Cas9 markedly abolished the high level of UCP1 in brown adipocytes differentiated from the preadipocytes. Finally, we were able to prospectively isolate adipose progenitors with great thermogenic potential using the cell surface marker CD29. These data provide new insights into the cellular heterogeneity in human fat and offer potential biomarkers for identifying thermogenically competent preadipocytes.

At a glance

Figures

  1. Generation and characterization of immortalized human brown and white fat progenitors.
    Figure 1: Generation and characterization of immortalized human brown and white fat progenitors.

    (a) Light microscopic images of immortalized human WAT progenitors (hWAT-SVF cells) and human BAT progenitors (hBAT-SVF cells) at day 0 and 18 (stained with Oil Red O) from four subjects (Sub1–4). Scale bar, 100 μm. (b) qRT-PCR analysis for UCP1 mRNA expression in differentiated adipocytes from hWAT-SVF cells and hBAT-SVF cells from four subjects (Sub1–4). Data are presented as fold changes relative to subject1–derived hWAs (n = 3 per group, biological replicates). (c) Western blot analysis of UCP1 protein level in hWAs and hBAs differentiated from progenitors of Sub1 and Sub2. α-Tubulin serves as a loading control. (d) qRT-PCR analysis for LEP mRNA expression as in b. Data are presented as fold changes relative to subject1–derived hWAs (n = 3 per group, biological replicates). (e) Oxygen consumption rate (OCR) was measured in the absence (basal respiration, Basal res.) or presence of oligomycin (Proton leak) or FCCP (maximal respiration, Max. res.) in hWAs and hBAs from Sub1 (left) and Sub2 (right). Data are presented as mean ± s.e.m. (n = 10 per group, biological replicates; hWAs versus hBAs). (f) Glucose uptake was measured using [3H]2-deoxy-glucose in hWAs and hBAs stimulated with (Ins100) or without (Ins0) 100 nM insulin from Sub1 (left) and Sub2 (right) (n = 3 per group, biological replicates). (g) Fatty acid uptake (FAU) and fatty acid oxidation (FAO) were measured using [14C]palmitic acid in hWAs and hBAs from Sub1 (left) and Sub2 (right). Data are presented as fold change compared to FAU or FAO from hWAs (n = 3 per group, biological replicates). AU, arbitrary unit. (h) qRT-PCR analysis for UCP1 and PPARG mRNA expression in hWAs and hBAs from Sub1 (left) and Sub2 (right). Data are presented as fold changes compared to mRNA expression in vehicle-treated (veh) hWAs for each subject (n = 3 per group, biological replicates; NS, not significant; Veh versus BMP7). Throughout, error bars represent mean ± s.e.m.; *P < 0.05, **P < 0.01, ***P < 0.001 by two-tailed Student's t-test. A representative experiment from a total of three independent studies is shown.

  2. Use of a UCP1 reporter system for in vitro and in vivo monitoring of UCP1 expression.
    Figure 2: Use of a UCP1 reporter system for in vitro and in vivo monitoring of UCP1 expression.

    (a) Schematic structure of the hUCP1 promoter reporter system. 4,148 bp of human UCP1 promoter drives the expression of bicistronic luciferase and GFP. T2A is the internal ribosomal entry site. (b) In hBAT-SVF and hWAT-SVF cells stably expressing the reporter construct, luciferase activity (right) strongly correlated with endogenous UCP1 gene expression (left) during the course of differentiation (see Fig. 1a and Online Methods). Data are presented as fold changes compared to hWAT-SVF cells on day 0 (mean ± s.e.m., n = 3 per group, biological replicates). A representative experiment from a total of two independent studies is shown. (c) Monitoring UCP1 expression by GFP in vitro using a time-lapse imaging system during differentiation of hBAT-SVF cells from subject 1 (Sub1). (d) Left, representative bioluminescent images of nude mice captured 22 d after transplantation of hWAT-SVF and hBAT-SVF cells described in b. Right, quantification of luciferase activity by total flux measured in millions of photons per second (error bars are mean ± s.e.m.). The experiments have been repeated twice (n = 2 for the hWAT-SVF group; n = 3 for the hBAT-SVF group). (e) qRT-PCR analysis for expression of FABP4, UCP1 and LEP in fat pads developed from the transplanted cells. Data are presented as fold changes compared to fat pads developed from hWAT-SVF cells with vehicle treatment (mean ± s.e.m.). *P < 0.05, **P < 0.01, ***P < 0.001 by two-tailed Student's t-test. A representative experiment from a total of two independent studies is shown.

  3. Clonal analysis of human brown and white fat progenitors.
    Figure 3: Clonal analysis of human brown and white fat progenitors.

    The clonal analysis strategy of hWAT-SVF and hBAT-SVF cell progenitors is shown as a dendrogram. 152 clones from hWAT-SVF cells and 128 clones from hBAT-SVF cells were derived by limiting dilution of pooled cells from four subjects. Adipogenic capacity was determined by Nile red staining and UCP1 levels were determined by luciferase activity on day 18. Detailed selection criteria are described in Supplementary Figures 6 and 7. Selected highly adipogenic clones (adipogenic++) were pretreated with 3.3 nM BMP7 for 6 d and then differentiated into mature adipocytes in a 96-well plate. Luciferase activity was measured on day 18 and the cells were divided into different groups on the basis of the level (negative, neg; low; medium, med; and high) of normalized (to protein content) luciferase activity. The positive response (resp. (+)) to BMP7 pretreatment was defined as >1.5-fold increase of luciferase activity in BMP7-pretreated versus vehicle groups.

  4. Gene expression profiles in adipose progenitors predict the thermogenic capacity of mature adipocytes.
    Figure 4: Gene expression profiles in adipose progenitors predict the thermogenic capacity of mature adipocytes.

    (a) A schematic presentation outlining the strategy used to identify the genes in preadipocytes with positive or negative correlation with UCP1 levels in mature adipocytes. Microarray analyses were done in 41 selected highly adipogenic clones from four subjects (8 clones from hWAT-SVF cells and 33 clones from hBAT-SVF cells). (b) Plot showing distribution of correlation coefficients between each gene's expression and UCP1 expression (as determined by luciferase activities). We used P < 0.001 as the cutoff to prioritize candidate genes (two-tailed alternative with function 'cor.test' in the R software), which is associated with a correlation coefficient of 0.5 or −0.5, and the number of genes that met this cutoff is indicated. The correlation coefficient (r) is shown on the x axis and gene density is shown on the y axis. (c) Log2 gene expression data from the 50 genes most associated with UCP1 were centered to have a mean of zero and restricted to the interval [−2,2] and are shown in a heatmap, along with a color bar representing UCP1 at the top, in which darker indicates higher UCP1 levels (as determined by luciferase activities in the reporter clones). Detailed information of genes is shown in Supplementary Table 4. (d) Scatter plots showing the positive and negative correlations between the UCP1-luciferase levels and expression levels of candidate genes from microarrays. The log2 gene expression levels from progenitor cells (day 0) are shown on the x axis. The y axis represents the log2 UCP1-luciferase levels from mature adipocytes (day 18).

  5. PREX1 and EDNRB are required for determining thermogenic competency.
    Figure 5: PREX1 and EDNRB are required for determining thermogenic competency.

    (a) Heatmap displaying correlations between UCP1 mRNA levels on day 18 (top row) and expression levels of candidate genes on day 0. Data were obtained from 10 independent hWAT-SVF and hBAT-SVF clones derived from the same four subjects that were not included in microarray analyses. Values were normalized within each row using a linear color scale. (b) mRNA levels of PREX1 and EDNRB were measured by qRT-PCR in PREX1- and EDNRB-knockout (KO) hBAT-SVF clones made using CRISPR-Cas9 technology. The results were verified in another progenitor clone. (c) Microscopic views of differentiated PREX1-KO and EDNRB-KO hBAT-SVF cells. Ctl, control cells. Scale bar, 100 μm. (d) qRT-PCR analysis for PPARG and brown fat–specific markers (UCP1, DIO2 and PPARGC1A) in differentiated PREX1-KO and EDNRB-KO hBAT-SVF cells. (e) SSTR1 level was detected by qRT-PCR in a SSTR1-KO hWAT-SVF clone that was made using CRISPR-Cas9. The results were verified in another progenitor clone. (f) Bright-field images of a differentiated SSTR1-KO hWAT-SVF clone. Scale bar, 100 μm. (g) qRT-PCR analysis for PPARG and brown fat–specific markers (UCP1 and DIO2) from a differentiated SSTR1-KO clone. qRT-PCR data are presented as fold change compared to control cells (Ctl) (mean ± s.e.m., n = 3 per group, biological replicates; two-tailed Student's t-test; *P < 0.05, **P < 0.01, ***P < 0.001). The Ct values are indicated to reflect the actual gene expression levels.

  6. Isolation of progenitors possessing thermogenic potential using a cell surface marker.
    Figure 6: Isolation of progenitors possessing thermogenic potential using a cell surface marker.

    (a) Scatter plots showing positive correlation between the UCP1-luciferase levels (shown as log2 levels on the y axis) on day 18 and expression levels of ITGA10 (left) and ITGB1 (right) (shown as log2 levels on the x axis) on day 0 from microarray analyses. (b) Correlation between the mRNA levels of ITGA10 and ITGB1 (shown as log2 levels on the x axis) on day 0 and UCP1 mRNA levels (shown as log2 levels on the y axis) on day 18 in ten independent hWAT-SVF and hBAT-SVF clones, as described in Figure 5a. (c) Histogram displaying subpopulations with differential levels of CD29 from pooled hWAT-SVF (blue) and hBAT-SVF (red) cells using FACS. Gray line represents unstained cells. (d) Images of sorted subpopulations with different levels of CD29 (CD29low, CD29med and CD29high) on days 0 and 18 are shown. Note that we could not sort enough numbers of CD29low cells from pooled hBAT-SVF cells, and thus results from this subpopulation are not shown. Scale bar, 100 μm. A representative experiment from two independent studies is shown. (e) qRT-PCR analysis for the adipocyte markers (FASN, PPARG and FABP4) and brown fat–specific markers (UCP1, PPARGC1A and DIO2) on the indicated differentiated populations. (f) To correct for the different degrees of adipogenesis shown in e, expression levels of UCP1 and DIO2 were normalized to the level of the mature adipocyte marker, FASN. Data are presented as mean ± s.e.m. (n = 3 per group, biological replicates; two-tailed Student's t-test; *P < 0.05, **P < 0.01, ***P < 0.001).

Videos

  1. Time lapse imaging of hBAT-SVF differentiation
    Video 1: Time lapse imaging of hBAT-SVF differentiation

Accession codes

Primary accessions

Gene Expression Omnibus

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Author information

Affiliations

  1. Section on Integrative Physiology and Metabolism, Research Division, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA.

    • Ruidan Xue,
    • Matthew D Lynes,
    • Farnaz Shamsi,
    • Tim J Schulz,
    • Hongbin Zhang,
    • Tian Lian Huang,
    • Kristy L Townsend,
    • Hirokazu Takahashi,
    • Lauren S Weiner,
    • Laurie J Goodyear,
    • Aaron M Cypess &
    • Yu-Hua Tseng
  2. Division of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

    • Ruidan Xue &
    • Yiming Li
  3. Bioinformatics Core, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA.

    • Jonathan M Dreyfuss
  4. Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA.

    • Jonathan M Dreyfuss
  5. Department of Orthopedic Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.

    • Andrew P White
  6. Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA.

    • Maureen S Lynes &
    • Lee L Rubin
  7. Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, USA.

    • Maureen S Lynes,
    • Lee L Rubin &
    • Yu-Hua Tseng
  8. Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA.

    • Aaron M Cypess

Contributions

The study was designed by Y.-H.T., R.X., M.D.L. and A.M.C. The manuscript was written by Y.-H.T., M.D.L., R.X. and J.M.D. R.X. performed the majority of the experiments. M.D.L. did the time-lapse imaging, IVIS scanning and FACS. J.M.D. analyzed microarray data. F.S. performed bioenergetics analyses in knockout cells. T.J.S. and H.Z. established the method of isolation, immortalization and differentiation of human fat progenitors. T.L.H. did the human cell implantation and gene expression microarrays. K.L.T. provided assistance with the Seahorse bioanalyzer. Y.L. provided research assistance. H.T. and L.J.G. helped with fuel utilization experiments. A.M.C., L.S.W. and A.P.W. collected human fat samples. M.S.L. and L.L.R. helped with the time-lapse imaging. All authors contributed to editing the manuscript.

Competing financial interests

A.M.C. and Y.-H.T. are recipients of a sponsored research grant and licensing payments from Chugai Pharmaceutical Co., Ltd through Joslin Diabetes Center.

Corresponding author

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Supplementary information

Video

  1. Video 1: Time lapse imaging of hBAT-SVF differentiation (31.13 MB, Download)

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  1. Supplementary Text and Figures (1,516 KB)

    Supplementary Figures 1–9 & Supplementary Tables 1–5

Additional data