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

Xue R, Lynes MD, Dreyfuss JM, Shamsi F, Schulz TJ, Zhang H, Huang TL, Townsend KL, Li Y, Takahashi H, Weiner LS, White AP, Lynes MS, Rubin LL, Goodyear LJ, Cypess AM, Tseng YH - Nat. Med. (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: 1] Section on Integrative Physiology and Metabolism, Research Division, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA. [2] Division of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

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.

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PREX1 and EDNRB are required for determining thermogenic competency. (a) 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 4 subjects that were not included in microarray analyses. Values were normalized within each row using a linear color scale. (b) Levels of PREX1 and EDNRB mRNA were measured by Q-RT-PCR in PREX1 (PREX1 KO) and EDNRB (EDNRB KO) knockout hBAT-SVF clone using CRISPR/Cas9. The experiments were verified in another progenitor clone. (c) Microscopic views of differentiated PREX1 KO and EDNRB KO hBAT-SVF cells. Scale bar, 100 μm. (d) Q-RT-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 Q-RT-PCR in a SSTR1 knockout (SSTR1 KO) hWAT-SVF clone using CRISPR/Cas9. The experiments were verified in another progenitor clone. (f) Microscope views of differentiated SSTR1 KO hWAT-SVF clone. Scale bar, 100 μm. (g) Q-RT-PCR analysis for PPARG and brown-fat-specific markers (UCP1 and DIO2) in differentiated SSTR1 KO clone. Q-RT-PCR data are presented as fold changes compared to control vector transfected cells (Ctl) (mean ± s.e.m., n=3; two-tailed Student’s t-test; * P < 0.05, ** P < 0.01, *** P < 0.001). The Ct values (Ct) are indicated to reflect the actual levels of gene expression.
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Figure 5: PREX1 and EDNRB are required for determining thermogenic competency. (a) 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 4 subjects that were not included in microarray analyses. Values were normalized within each row using a linear color scale. (b) Levels of PREX1 and EDNRB mRNA were measured by Q-RT-PCR in PREX1 (PREX1 KO) and EDNRB (EDNRB KO) knockout hBAT-SVF clone using CRISPR/Cas9. The experiments were verified in another progenitor clone. (c) Microscopic views of differentiated PREX1 KO and EDNRB KO hBAT-SVF cells. Scale bar, 100 μm. (d) Q-RT-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 Q-RT-PCR in a SSTR1 knockout (SSTR1 KO) hWAT-SVF clone using CRISPR/Cas9. The experiments were verified in another progenitor clone. (f) Microscope views of differentiated SSTR1 KO hWAT-SVF clone. Scale bar, 100 μm. (g) Q-RT-PCR analysis for PPARG and brown-fat-specific markers (UCP1 and DIO2) in differentiated SSTR1 KO clone. Q-RT-PCR data are presented as fold changes compared to control vector transfected cells (Ctl) (mean ± s.e.m., n=3; two-tailed Student’s t-test; * P < 0.05, ** P < 0.01, *** P < 0.001). The Ct values (Ct) are indicated to reflect the actual levels of gene expression.

Mentions: To select promising candidate genes for further analyses, we applied the following three criteria. First, the primary selection criterion was based on their correlation coefficients, P-values and FDR values (Fig. 4c and Supplementary Table 4). Second, the top-ranking candidate genes were further verified by Q-RT-PCR assay in a set of 10 independent single cell clones derived from the same four subjects (but not included in the original microarray analysis) for positive or negative correlations between the expression levels of selected candidate genes in preadipocytes and UCP1 mRNA levels in mature adipocytes (Fig. 5a). Third, they were also validated in 7 pairs of the human neck brown and white adipose tissues (Supplementary Fig. 8).


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

Xue R, Lynes MD, Dreyfuss JM, Shamsi F, Schulz TJ, Zhang H, Huang TL, Townsend KL, Li Y, Takahashi H, Weiner LS, White AP, Lynes MS, Rubin LL, Goodyear LJ, Cypess AM, Tseng YH - Nat. Med. (2015)

PREX1 and EDNRB are required for determining thermogenic competency. (a) 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 4 subjects that were not included in microarray analyses. Values were normalized within each row using a linear color scale. (b) Levels of PREX1 and EDNRB mRNA were measured by Q-RT-PCR in PREX1 (PREX1 KO) and EDNRB (EDNRB KO) knockout hBAT-SVF clone using CRISPR/Cas9. The experiments were verified in another progenitor clone. (c) Microscopic views of differentiated PREX1 KO and EDNRB KO hBAT-SVF cells. Scale bar, 100 μm. (d) Q-RT-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 Q-RT-PCR in a SSTR1 knockout (SSTR1 KO) hWAT-SVF clone using CRISPR/Cas9. The experiments were verified in another progenitor clone. (f) Microscope views of differentiated SSTR1 KO hWAT-SVF clone. Scale bar, 100 μm. (g) Q-RT-PCR analysis for PPARG and brown-fat-specific markers (UCP1 and DIO2) in differentiated SSTR1 KO clone. Q-RT-PCR data are presented as fold changes compared to control vector transfected cells (Ctl) (mean ± s.e.m., n=3; two-tailed Student’s t-test; * P < 0.05, ** P < 0.01, *** P < 0.001). The Ct values (Ct) are indicated to reflect the actual levels of gene expression.
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Figure 5: PREX1 and EDNRB are required for determining thermogenic competency. (a) 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 4 subjects that were not included in microarray analyses. Values were normalized within each row using a linear color scale. (b) Levels of PREX1 and EDNRB mRNA were measured by Q-RT-PCR in PREX1 (PREX1 KO) and EDNRB (EDNRB KO) knockout hBAT-SVF clone using CRISPR/Cas9. The experiments were verified in another progenitor clone. (c) Microscopic views of differentiated PREX1 KO and EDNRB KO hBAT-SVF cells. Scale bar, 100 μm. (d) Q-RT-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 Q-RT-PCR in a SSTR1 knockout (SSTR1 KO) hWAT-SVF clone using CRISPR/Cas9. The experiments were verified in another progenitor clone. (f) Microscope views of differentiated SSTR1 KO hWAT-SVF clone. Scale bar, 100 μm. (g) Q-RT-PCR analysis for PPARG and brown-fat-specific markers (UCP1 and DIO2) in differentiated SSTR1 KO clone. Q-RT-PCR data are presented as fold changes compared to control vector transfected cells (Ctl) (mean ± s.e.m., n=3; two-tailed Student’s t-test; * P < 0.05, ** P < 0.01, *** P < 0.001). The Ct values (Ct) are indicated to reflect the actual levels of gene expression.
Mentions: To select promising candidate genes for further analyses, we applied the following three criteria. First, the primary selection criterion was based on their correlation coefficients, P-values and FDR values (Fig. 4c and Supplementary Table 4). Second, the top-ranking candidate genes were further verified by Q-RT-PCR assay in a set of 10 independent single cell clones derived from the same four subjects (but not included in the original microarray analysis) for positive or negative correlations between the expression levels of selected candidate genes in preadipocytes and UCP1 mRNA levels in mature adipocytes (Fig. 5a). Third, they were also validated in 7 pairs of the human neck brown and white adipose tissues (Supplementary Fig. 8).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: 1] Section on Integrative Physiology and Metabolism, Research Division, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA. [2] Division of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

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.

Show MeSH
Related in: MedlinePlus