Journal: Molecular metabolism

Article Title: Adaptive gene expression of alternative splicing variants of PGC-1α regulates whole-body energy metabolism.

doi: 10.1016/j.molmet.2024.101968

Figure Lengend Snippet: Figure 1: Molecular structures and functions of mouse PGC-1a isoforms. (A) Gene and predicted protein structures of PGC-1a isoforms. (B) C2C12 myotubes infected with adenoviruses encoding individual PGC-1a isoforms or b-galactosidase (b-gal, control) were subjected to RT-qPCR analysis of carnitine palmitoyltransferase 1b (Cpt1b), PPARa (Ppara), mitochondrial ATP synthase subunit b (Atp5b), glucose transporter 4 (Glut4), mitochondrial transcription factor A (Tfam), and cytochrome c oxidase subunit II (Mt-Co2) mRNAs (n ¼ 8 independent experiments). The amount of each mRNA was normalized by that of 36B4 mRNA, and normalized values are expressed relative to the corresponding value for myotubes expressing b-gal. (C) COS7 cells transfected with expression vectors encoding each PGC-1a isoform (or with the corresponding empty vector, Control) and with an expression vector for mouse PPARa were subjected to immunoprecipitation (IP) with antibodies to PGC-1a, and the resulting precipitates were subjected to immunoblot analysis with antibodies to PPARa (upper panel) or to PGC-1a (lower panel). (D) Luciferase reporter assay with the reporter plasmid 3x-PPRE-luc for the transcriptional coactivator activity of PGC-1a isoforms expressed together with PPARa in C2C12 cells (n ¼ 4 independent experiments). (E, F) C2C12 myotubes infected with adenoviruses encoding PGC-1a isoforms or b-gal (control) were subjected to immunoblot analysis of PGC-1a and GAPDH as a loading control (E) as well as assayed both for respiration rate under basal conditions and in the presence of oligomycin or carbonyl cyanide p-trifluoromethoxyphenylhydrazone (FCCP) and for mitochondrial proton leak (F) (n ¼ 8 independent experiments). (G) Effects of clenbuterol on the promoter activity of PGC-1aa or PGC-1ab/c genes in C2C12 myoblasts. All quantitative data are means s.e.m. *P < 0.05 versus the corresponding value for b-gal (B) or for the indicated comparisons (D, F) by one-way (B, F) or two-way (D, G) ANOVA with Bonferroni’s post hoc test. NS, not significant.

Article Snippet: COS7 cells transfected with pcDNA3.1-based expression vectors encoding mouse PGC-1a isoforms and mouse PPARa were subjected to immunoprecipitation with antibodies to PGC-1a (ST1202, Calbiochem), and the resulting precipitates were subjected to immunoblot analysis with the same antibodies to PGC-1a and with those to PPARa (H-08, Santa Cruz Biotechnology).

Techniques: Infection, Control, Quantitative RT-PCR, Expressing, Transfection, Plasmid Preparation, Immunoprecipitation, Western Blot, Luciferase, Reporter Assay, Activity Assay

Journal: Molecular metabolism

Article Title: Adaptive gene expression of alternative splicing variants of PGC-1α regulates whole-body energy metabolism.

doi: 10.1016/j.molmet.2024.101968

Figure Lengend Snippet: Figure 2: Effects of exercise on the abundance of PGC-1a isoform mRNAs in mice and humans. (A) RT-qPCR analysis of PGC-1a isoform mRNAs in skeletal muscle of male C57BL/6J mice both under the static condition (Ex ()) and after exercise on a treadmill at 15 m/min for 120 min (Ex (þ)) (n ¼ 8 mice per group). EDL, extensor digitorum longus. (B) RT-qPCR analysis of PGC-1a isoform mRNAs in vastus lateralis skeletal muscle of human individuals with NGT (n ¼ 10) or T2D (n ¼ 10) both under the static condition (Ex ()) and after ergometer exercise for 30 min (Ex (þ)). PGC-1a isoform mRNAs were subjected to quantification with the use of standard curves determined with plasmids containing the corresponding cDNAs so as to allow comparison of their amounts, and copy number was determined by RT-qPCR. The relative copy number of the transcripts was normalized to that of 36B4. Data in (A) and (B) are means s.e.m. *P < 0.05, **P < 0.01, and NS by one-way ANOVA with Bonferroni’s post hoc test. (C) Correlation of log2[fold change] for the exercise-induced increase in the abundance of PGC-1a isoform mRNAs in human skeletal muscle and VO2 max (NGT, n ¼ 10; T2D, n ¼ 10). Spearman correlation R2 values and P values are indicated.

Article Snippet: COS7 cells transfected with pcDNA3.1-based expression vectors encoding mouse PGC-1a isoforms and mouse PPARa were subjected to immunoprecipitation with antibodies to PGC-1a (ST1202, Calbiochem), and the resulting precipitates were subjected to immunoblot analysis with the same antibodies to PGC-1a and with those to PPARa (H-08, Santa Cruz Biotechnology).

Techniques: Quantitative RT-PCR, Comparison

Journal: Molecular metabolism

Article Title: Adaptive gene expression of alternative splicing variants of PGC-1α regulates whole-body energy metabolism.

doi: 10.1016/j.molmet.2024.101968

Figure Lengend Snippet: Figure 3: Obesity and insulin resistance in PGC-1aAE1KO mice. (AeD) Body mass at the indicated ages (n ¼ 16) (A), tissue mass at 4 months of age (n ¼ 16) (B), as well as abdominal images and adipose tissue mass (n ¼ 4) (C) and lean body mass (n ¼ 4) (D) obtained by CT at 4 months of age for WT and KO mice. (EeG) Hematoxylineeosin staining of eWAT (E) as well as adipocyte diameter in epididymal or subcutaneous fat as determined either with a Coulter counter (F) or by histological analysis (G) for WT and KO mice at 3 months of age (n ¼ 4). (H) Food intake for 4-month-old WT and KO mice (n ¼ 10). (I, J) Violin plots for blood glucose (I) and plasma insulin (J) concentrations in the randomly fed state and at the indicated ages (n ¼ 16). Plot center lines denote the median. (K, L) Blood glucose (K) and plasma insulin (L) levels during an intraperitoneal GTT (left panels) as well as the corresponding area under the curve (AUC) values (right panels) for WT and KO mice at 7 months of age (n ¼ 11). (M, N) RT-qPCR analysis of total PGC-1a mRNA (n ¼ 8) (M) and qPCR analysis of mtDNA content (n ¼ 6) (N) for the indicated skeletal muscles of WT and KO mice at 4 months of age. (O) Function of mitochondria isolated from gastrocnemius muscle of WT and KO mice at 4 months of age (n ¼ 4). Quantitative data are means s.e.m. for the indicated numbers (n) of mice in (AeD, G, HeO). *P < 0.05, **P < 0.01, and NS versus the corresponding WT value or for the indicated comparisons by the two-tailed unpaired Student’s t test (BeD, HeJ; K,L (right panels)) or by one-way (A; K, L (left panels); M-O) or two-way (G) ANOVA with Bonferroni’s post hoc test.

Article Snippet: COS7 cells transfected with pcDNA3.1-based expression vectors encoding mouse PGC-1a isoforms and mouse PPARa were subjected to immunoprecipitation with antibodies to PGC-1a (ST1202, Calbiochem), and the resulting precipitates were subjected to immunoblot analysis with the same antibodies to PGC-1a and with those to PPARa (H-08, Santa Cruz Biotechnology).

Techniques: Staining, Clinical Proteomics, Quantitative RT-PCR, Muscles, Isolation, Two Tailed Test

Journal: Molecular metabolism

Article Title: Adaptive gene expression of alternative splicing variants of PGC-1α regulates whole-body energy metabolism.

doi: 10.1016/j.molmet.2024.101968

Figure Lengend Snippet: Figure 4: Oxygen consumption, heat production, and locomotor activity during the light and dark phases for PGC-1aAE1KO mice. (A) The circadian pattern of locomotor activity for WT and KO mice at 3 months of age was analyzed with an infrared sensor for 10 days (n ¼ 10). Locomotor activity is expressed as a percentage of the daily total: 100% (activity counts for each hour/total activity counts for 24 h). Each point corresponds to an individual mouse. (B) RT-qPCR analysis of PGC-1a isoform mRNAs in skeletal muscle of WT and KO mice during the light and dark phases in the absence or presence of a running wheel (n ¼ 4). (CeE, GeI) Circadian pattern of oxygen consumption (VO2) (C, G) as well as the levels of oxygen consumption (D, H) and heat production (E, I) during the light and dark phases in the absence (WT, n ¼ 7; KO, n ¼ 9) (CeE) or presence (WT, n ¼ 5; KO, n ¼ 7) (GeI) of a running wheel for 4-month-old WT and KO mice. (F, J) Locomotor activity for 4-month-old WT and KO mice during the light and dark phases was analyzed for 4 days in the absence (WT, n ¼ 7; KO, n ¼ 9) (F) or presence (WT, n ¼ 5; KO, n ¼ 7) (J) of a running wheel. The center lines of the violin plots indicate the median. Data are means s.e.m. in (BeE, GeI), and n values indicate the numbers of mice. *P < 0.05, **P < 0.01, and NS by the two-tailed unpaired Student’s t test (DeF, HeJ) or two-way ANOVA with Bonferroni’s post hoc test (B).

Article Snippet: COS7 cells transfected with pcDNA3.1-based expression vectors encoding mouse PGC-1a isoforms and mouse PPARa were subjected to immunoprecipitation with antibodies to PGC-1a (ST1202, Calbiochem), and the resulting precipitates were subjected to immunoblot analysis with the same antibodies to PGC-1a and with those to PPARa (H-08, Santa Cruz Biotechnology).

Techniques: Activity Assay, Quantitative RT-PCR, Two Tailed Test

Journal: Molecular metabolism

Article Title: Adaptive gene expression of alternative splicing variants of PGC-1α regulates whole-body energy metabolism.

doi: 10.1016/j.molmet.2024.101968

Figure Lengend Snippet: Figure 5: Impaired motor performance as well as attenuated exercise-induced energy expenditure and gene expression in PGC-1aAE1KO mice. (AeC) Motor per- formance of 3-month-old WT and KO mice (n ¼ 8) was assessed by an exercise endurance test with stepwise increases in treadmill rate (A). Exhaustion was defined as the inability of the animal to remain on the treadmill despite mechanical prodding. The average time (B) and distance (C) of running until exhaustion were determined. (DeG) Time course of oxygen consumption (n ¼ 8) (D), total oxygen consumption (n ¼ 8) (E), carbohydrate oxidation rate (n ¼ 6) (F), and lipid oxidation rate (n ¼ 6) (G) during the first 30 min of forced treadmill exercise (Ex) at 25 m/min for 4-month-old WT and KO mice. (H, I) Percentage change in body mass (n ¼ 14) after (H), and epididymal fat mass (n ¼ 4) before and after (I), forced treadmill exercise for 120 min at 15 m/min for 4-month-old WT and KO mice. (J) Intramuscular temperature of 4-month-old WT and KO mice during forced treadmill exercise at 15 m/min (n ¼ 5). (K, L) RT-qPCR analysis of PGC-1a isoform mRNAs in gastrocnemius muscle (n ¼ 6) (K) and immunoblot analysis of PGC-1a in EDL (n ¼ 3) (L) for 4-month-old WT and KO mice under the static condition (Ex ()) or after forced treadmill exercise at 15 m/min for 120 min (Ex (þ)). (M) RT-qPCR analysis of mRNAs for the indicated genes in gastrocnemius muscle of 4-month-old WT and KO mice under the static condition or after forced treadmill exercise at 15 m/min for 120 min (n ¼ 4). The amount of each mRNA was normalized by that of 36B4 mRNA, and normalized values are expressed relative to the corresponding value for WT Ex (). All quantitative data are means s.e.m. for the indicated numbers (n) or mice with the exception of those in (A) and (H), with the median being indicated in (H). *P < 0.05, **P < 0.01, and NS by the two-tailed unpaired Student’s t test (B, C, H) or two-way ANOVA with Bonferroni’s post hoc test (EeG, I, K, M).

Article Snippet: COS7 cells transfected with pcDNA3.1-based expression vectors encoding mouse PGC-1a isoforms and mouse PPARa were subjected to immunoprecipitation with antibodies to PGC-1a (ST1202, Calbiochem), and the resulting precipitates were subjected to immunoblot analysis with the same antibodies to PGC-1a and with those to PPARa (H-08, Santa Cruz Biotechnology).

Techniques: Gene Expression, Quantitative RT-PCR, Western Blot, Two Tailed Test

Journal: Molecular metabolism

Article Title: Adaptive gene expression of alternative splicing variants of PGC-1α regulates whole-body energy metabolism.

doi: 10.1016/j.molmet.2024.101968

Figure Lengend Snippet: Figure 6: Characterization of BAT and change in body temperature in response to cold exposure in PGC-1aAE1KO mice. (A, B) Hematoxylineeosin staining (A) and tissue mass (n ¼ 16) (B) for interscapular BAT of WT and KO mice at 8 weeks of age. (C, D) RT-qPCR analysis of PGC-1a isoform mRNAs (n ¼ 4) (C) and of UCP1 mRNA (n ¼ 4) (D) in BAT of 6-week-old WT and KO mice maintained either at 22 C or for the indicated times (C) or 3 h (D) at 4 C. The amount of UCP1 mRNA was normalized by that of 36B4 mRNA, and normalized values are expressed relative to the value for WT at 22 C. (E) Rectal temperature of 6-week-old WT and KO mice during exposure to 4 C for the indicated times (n ¼ 6). (F, G) RT-qPCR analysis of PGC-1a isoform mRNAs (F) and of expression of the indicated genes (G) in eWAT of 4-month-old WT and KO mice maintained at 22 C or for 3 h at 4 C (n ¼ 4). Gene expression in (G) was normalized by the amount of 36B4 mRNA, and normalized values are expressed relative to the value for WT at 22 C. All quantitative data are means s.e.m. for the indicated numbers (n) or mice. *P < 0.05, **P < 0.01, and NS versus the corresponding value for KO mice (E) or for the indicated comparisons (BeD, F, G) by the two-tailed unpaired Student’s t test (B) or two-way ANOVA with Bonferroni’s post hoc test (CeG).

Article Snippet: COS7 cells transfected with pcDNA3.1-based expression vectors encoding mouse PGC-1a isoforms and mouse PPARa were subjected to immunoprecipitation with antibodies to PGC-1a (ST1202, Calbiochem), and the resulting precipitates were subjected to immunoblot analysis with the same antibodies to PGC-1a and with those to PPARa (H-08, Santa Cruz Biotechnology).

Techniques: Staining, Quantitative RT-PCR, Expressing, Gene Expression, Two Tailed Test

Journal: Molecular metabolism

Article Title: Adaptive gene expression of alternative splicing variants of PGC-1α regulates whole-body energy metabolism.

doi: 10.1016/j.molmet.2024.101968

Figure Lengend Snippet: Figure 7: Effects of exercise training on skeletal muscle remodeling in PGC-1aAE1KO mice. (A, B) RT-qPCR analysis of MHC mRNAs (n ¼ 6) (A) and qPCR analysis of mtDNA (n ¼ 8) (B) in gastrocnemius of WT and KO mice maintained with or without exercise training for 6 weeks beginning at 3 months of age. The amount of each MHC mRNA was normalized by that of 36B4 mRNA, and normalized values are expressed relative to the corresponding value for training (). (C, D) Vascular density in EDL as determined by immunohistochemical staining with antibodies to CD31 (C) and represented by the average number of CD31-positive capillaries per high-power field (HPF) among four such HPFs (D) for WT and KO mice (n ¼ 4) maintained with or without exercise training for 6 weeks beginning at 3 months of age. Mice at 4 months of age subjected to forced treadmill exercise at 15 m/min for 120 min were also analyzed for comparison (Ex (þ), n ¼ 4). (E) RT-qPCR analysis of PGC-1a isoform mRNAs in gastrocnemius of WT and KO mice as in (A) (n ¼ 6). All quantitative data are means s.e.m. for the indicated numbers (n) of mice. *P < 0.05, **P < 0.01, and NS by two-way ANOVA with Bonferroni’s post hoc test. (F) Model for the roles of PGC-1a isoforms in skeletal muscle. Circle sizes indicate the relative abundance of PGC-1a isoforms.

Article Snippet: COS7 cells transfected with pcDNA3.1-based expression vectors encoding mouse PGC-1a isoforms and mouse PPARa were subjected to immunoprecipitation with antibodies to PGC-1a (ST1202, Calbiochem), and the resulting precipitates were subjected to immunoblot analysis with the same antibodies to PGC-1a and with those to PPARa (H-08, Santa Cruz Biotechnology).

Techniques: Quantitative RT-PCR, Immunohistochemical staining, Staining, Comparison

Journal: CNS Neuroscience & Therapeutics

Article Title: PGC ‐1α Transcriptionally Regulated by ChREBP Mitigates Neuropathic Pain Through Promoting Microglial Fatty Acid Oxidation and Anti‐Inflammatory Response

doi: 10.1002/cns.70744

Figure Lengend Snippet: Overexpression of ChREBP activates the fatty acid oxidation in microglia. (A) KEGG enrichment analysis of the 50 hub genes significantly associated with ChREBP. (B) This panel compares the oxygen consumption rate of HAPI cells in four groups: Empty vector plasmid (±Etomoxir) and ChREBP overexpression plasmid (±Etomoxir). (C–F) Effects of ChREBP overexpression on fatty acid oxidation rate (C), basal respiration (D), maximal respiration (E), and ATP production (F) in the HAPI cells. (G‐N) RT‐qPCR was used to detect the mRNA expression levels of PPARG (G), SCD (H), FASN (I), PGC‐1α (J), ACACA (K), PPARA (L), SREBF1 (M), and HMGCR (N) in HAPI cells. These eight hub genes were selected from the STRING‐derived candidate gene set based on their highest connectivity degrees in the Cytoscape PPI network. Data are presented as mean ± SD, n = 3, ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001.

Article Snippet: After blocking at room temperature for 1 h, the antibodies were prepared with QuickBlock primary antibody dilution buffer (P0262; Beyotime): goat polyclonal antibody to Iba‐1 (1:250, ab5076; Abcam), mouse monoclonal antibody to GFAP (1:400, 3670S; CST), mouse monoclonal antibody to NeuN (1:400; MAB377, Millipore), rabbit polyclonal antibody to ChREBP (1:200; NB400‐135, Novus Biologicals), mouse monoclonal antibody to PGC‐1α (1:200, 66369‐1‐Ig; Proteintech), rabbit polyclonal antibody to iNOS (1:200, BS1186; Bioworld) and rabbit polyclonal antibody to Arg‐1 (1:200, BS67738; Bioworld), and incubated at 4°C overnight.

Techniques: Over Expression, Plasmid Preparation, Quantitative RT-PCR, Expressing, Derivative Assay

Journal: CNS Neuroscience & Therapeutics

Article Title: PGC ‐1α Transcriptionally Regulated by ChREBP Mitigates Neuropathic Pain Through Promoting Microglial Fatty Acid Oxidation and Anti‐Inflammatory Response

doi: 10.1002/cns.70744

Figure Lengend Snippet: ChREBP directly regulates PGC‐1α expression by binding to its promoter region. (A) Both ChREBP and PGC‐1α colocalize with Iba‐1 in the spinal cord of NP rats. (B‐C) Representative immunofluorescence images of PGC‐1α after in vivo overexpression of ChREBP (B) and quantitative analysis of fluorescence intensity (C). (D) mRNA level of PGC‐1α after in vivo overexpression of ChREBP. (E, F) Effect of ChREBP overexpression on PGC‐1α protein level in HAPI cells (E) and quantitative analysis of protein bands (F). (G, H) mRNA levels of PGC‐1α (G) and ChREBP (H) after overexpression of PGC‐1α in HAPI cells. (I, J) Protein expression of PGC‐1α and ChREBP after overexpression of PGC‐1α in HAPI cells (I), and quantitative analysis of protein bands (J). (K) Two binding sites between ChREBP and the PGC‐1α promoter region were predicted using the JASPAR database. (L) Schematic diagram of the constructed luciferase reporter plasmids for the wild‐type (WT) and mutant (MUT1, MUT2, MUT3) PGC‐1α promoters. (M) Dual‐luciferase reporter assay showing the effect of ChREBP overexpression on luciferase activity of the WT PGC‐1α promoter plasmid. (N) Dual‐luciferase reporter assay comparing the effect of ChREBP overexpression on luciferase activity between the WT and three mutant (MUT1, MUT2, MUT3) PGC‐1α promoter plasmids. (O) ChIP‐qPCR showing the amplification of PGC‐1α promoter fragments in the ChREBP group compared with the IgG group. (P) The enrichment of PGC‐1α promoter fragments by ChREBP immunoprecipitation. Marker: DNA marker; Input: 2% input sample; IgG: Negative control; Histone H3: Positive control. ChREBP: Specific antibody for target detection. Data are represented as mean ± SD, n = 6 for in vivo experiments (A–D), n = 3 for in vitro experiments (E‐P), ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001.

Article Snippet: After blocking at room temperature for 1 h, the antibodies were prepared with QuickBlock primary antibody dilution buffer (P0262; Beyotime): goat polyclonal antibody to Iba‐1 (1:250, ab5076; Abcam), mouse monoclonal antibody to GFAP (1:400, 3670S; CST), mouse monoclonal antibody to NeuN (1:400; MAB377, Millipore), rabbit polyclonal antibody to ChREBP (1:200; NB400‐135, Novus Biologicals), mouse monoclonal antibody to PGC‐1α (1:200, 66369‐1‐Ig; Proteintech), rabbit polyclonal antibody to iNOS (1:200, BS1186; Bioworld) and rabbit polyclonal antibody to Arg‐1 (1:200, BS67738; Bioworld), and incubated at 4°C overnight.

Techniques: Expressing, Binding Assay, Immunofluorescence, In Vivo, Over Expression, Fluorescence, Construct, Luciferase, Mutagenesis, Reporter Assay, Activity Assay, Plasmid Preparation, ChIP-qPCR, Amplification, Immunoprecipitation, Marker, Negative Control, Positive Control, In Vitro

Journal: CNS Neuroscience & Therapeutics

Article Title: PGC ‐1α Transcriptionally Regulated by ChREBP Mitigates Neuropathic Pain Through Promoting Microglial Fatty Acid Oxidation and Anti‐Inflammatory Response

doi: 10.1002/cns.70744

Figure Lengend Snippet: PGC‐1α overexpression reverses the microglial metabolism–polarization–inflammation–excitability–pain axis induced by ChREBP knockdown in microglia. (A) Schematic diagram showing the role of key molecules in the fatty acid oxidation pathway. (B‐E) mRNA levels of key fatty acid oxidation molecules CPT1A (B), CPT2 (C), ACADM (D), and HADHA (E) in the spinal cord of rats in each group. (F, G) Representative immunofluorescence staining images for double‐labeled Iba‐1 and pro‐inflammatory microglial marker (iNOS), and double‐labeled Iba‐1 and anti‐inflammatory microglial marker (Arg‐1) in the spinal cord (F), and the ratio of Iba‐1 + iNOS + to Iba‐1 + Arg‐1 + cells (G). (H–J) mRNA levels of inflammatory factors TNF‐α (H), IL‐1β (I), and IL‐6 (J) in the spinal cord of rats in each group. (K) Patch‐clamp electrophysiological recordings performed at the L5 spinal cord segment. (L–N) Representative images of spontaneous excitatory postsynaptic currents (sEPSC) in the spinal cord of rats in each group (L), and statistical analysis of their frequency (M) and amplitude (N). (O, P) Mechanical pain thresholds on the ipsilateral (O) and contralateral (P) sides of rats in each group. Data are represented as mean ± SD; n = 6 for in vivo experiments (B–J, O, P), n = 3 for electrophysiological recordings (K–N), ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001.

Article Snippet: After blocking at room temperature for 1 h, the antibodies were prepared with QuickBlock primary antibody dilution buffer (P0262; Beyotime): goat polyclonal antibody to Iba‐1 (1:250, ab5076; Abcam), mouse monoclonal antibody to GFAP (1:400, 3670S; CST), mouse monoclonal antibody to NeuN (1:400; MAB377, Millipore), rabbit polyclonal antibody to ChREBP (1:200; NB400‐135, Novus Biologicals), mouse monoclonal antibody to PGC‐1α (1:200, 66369‐1‐Ig; Proteintech), rabbit polyclonal antibody to iNOS (1:200, BS1186; Bioworld) and rabbit polyclonal antibody to Arg‐1 (1:200, BS67738; Bioworld), and incubated at 4°C overnight.

Techniques: Over Expression, Knockdown, Immunofluorescence, Staining, Labeling, Marker, Patch Clamp, In Vivo

Journal: FEBS letters

Article Title: Structural activity relationship of flavonoids with estrogen-related receptor gamma.

doi: 10.1016/j.febslet.2009.11.026

Figure Lengend Snippet: Fig. 2. Effects of flavonoids on the activities of ERb and estrogen-related receptor c (ERRc). (A) HeLa cells were transfected with an expression plasmid of Gal4-DBD-ERb-LBD together with a luciferase reporter and a control Renilla luciferase plasmid. About 10 nM 17b-estradiol as a positive control or different flavonoids at 5 lM were added for 24 h before luciferase assays. Fold induction by compounds were calculated and shown compared to dimethyl sulfoxide (DMSO) as a vehicle. (B) HeLa cells were transfected with expression plasmids of Gal4-DBD control or Gal4-DBD-ERRc-LBD with or without pcDNA-peroxisome proliferators-activated receptor c coactivator-1a (PGC-1a) together with a luciferase reporter and a control Renilla luciferase plasmid. DMSO or 10 lM 4-hydroxytamoxifen (4-OHT) was added and assays performed as in (A). (C) Transfection were performed as in (B) with different flavonoids (1, 5, and 25 lM); % activity indicates the normalized activities of ERRc under the influences of flavonoids compared to DMSO control set at 100%. (A–C) Results represent mean ± S.E.M. **P < 0.01.

Article Snippet: Membranes were incubated with rabbit anti-human-PGC-1a antibody generated in house or mouse anti-b-actin antibody (Boster) followed by horseradish peroxidase-conjugated secondary antibody (Amersham) and developed with BeyoECL Plus reagent (Beyotime).

Techniques: Transfection, Expressing, Plasmid Preparation, Luciferase, Control, Positive Control, Activity Assay

Journal: FEBS letters

Article Title: Structural activity relationship of flavonoids with estrogen-related receptor gamma.

doi: 10.1016/j.febslet.2009.11.026

Figure Lengend Snippet: Fig. 3. Apigenin directly blocks the interaction between ERRc and PGC-1a. (A) 125 nM of purified ERRc-LBD was tested for its interaction with NR1, NR2, and NR3 motifs as described [6]. (B) DMSO, 1 lM 4-OHT, 5 lM DY-131, 25 lM daidzein, or 25 lM luteolin was incubated with 50 nM ERRc-LBD for 1 hr before interaction analysis with NR2 as in (A). (C) Different doses of apigenin were tested as in (B).

Article Snippet: Membranes were incubated with rabbit anti-human-PGC-1a antibody generated in house or mouse anti-b-actin antibody (Boster) followed by horseradish peroxidase-conjugated secondary antibody (Amersham) and developed with BeyoECL Plus reagent (Beyotime).

Techniques: Incubation

Journal: FEBS letters

Article Title: Structural activity relationship of flavonoids with estrogen-related receptor gamma.

doi: 10.1016/j.febslet.2009.11.026

Figure Lengend Snippet: Fig. 4. Effects of flavonoids on the activity of PGC-1a. (A) HeLa cells were transfected with an expression plasmid of Gal4-DBD or Gal4-DBD-PGC-1a together with a luciferase reporter and a control Renilla luciferase plasmid. DMSO or 1, 5, and 25 lM luteolin were added for 24 h; % activity indicates the normalized activities of PGC-1a compared to DMSO control set at 100%. (B) HeLa cell extracts pre-treated with DMSO or 25 lM luteolin was probed with anti-PGC-1a or b-actin antibodies for Western analysis. PGC-1a protein levels normalized to b-actin from three independent experiments were quantified. Results represent mean ± S.E.M. **P < 0.01.

Article Snippet: Membranes were incubated with rabbit anti-human-PGC-1a antibody generated in house or mouse anti-b-actin antibody (Boster) followed by horseradish peroxidase-conjugated secondary antibody (Amersham) and developed with BeyoECL Plus reagent (Beyotime).

Techniques: Activity Assay, Transfection, Expressing, Plasmid Preparation, Luciferase, Control, Western Blot

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 1. Meta-analysis of stemness programs and metabolic states in IPMN- and PanIN-mediated PDAC progression. NCBI GEO datasets (GSE19650 and GSE43288) were used to investigate the differential transcriptomic signatures of stemness and metabolic genes. The data analysis and processing were performed by quantile normalization and log2 transformation. A–N, Representation of the differentially expressed glycolysis genes (A–G), OXPhos genes (H–K), MYC (L), PPARGC1A (M), and CPT2 (N) in indicated samples: NP (N ¼ 7), IPMN-derived PDAC (IPMN-PDAC; n ¼ 3), IPMA or IPMN with low-grade dysplasia (n ¼ 6), and IPMC or IPMN with high- grade dysplasia (n ¼ 6). O–X, Representation of the differentially expressed glycolysis genes (O–U), fatty acid b-oxidation genes (V–W), and PPARGC1A (X) in indicated samples: NP (n ¼ 3), PanIN (n ¼ 13), and PDAC (n ¼ 4). Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (P < 0.05; , P < 0.05; , P < 0.01; P < 0.001.) Y, Venn diagram showing common and unique overexpressed stemness genes in PanIN and IPMN. Data represent mean SD. P valueswere calculated using ordinary one-way ANOVA (multiple comparisons; ,P < 0.05). Z, Network analysis of the differentially expressed stemness and metabolic genes from the GSE19650 dataset using IPA. The network shows that the PPARGC1A is central to stemness, FAO, and OXPhos pathways in IPMN.

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Transformation Assay, Derivative Assay

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 2. Differential expression of metabolic regulators, PGC1a and CPT1A, in different stages of PDAC development. A–F, IHC analysis of PGC1a (A–C) and CPT1A (D–F) in indicated samples. A histoscore was calculated by multiplying intensity and positivity. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (, P < 0.05; , P < 0.01; , P < 0.001). Scale bar 200 mm. C and F, Magnified PanIN2 and IPMN regions duplicated from the original PanIN2 and IPMN IHC images of A and D to show the subcellular localization of PGC1a (C) and CPT1A (F) were shown.

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Quantitative Proteomics

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 4. ADM/PanIN and IPMN show upregulation of PGC1a and display unique metabolic states. A and B, IHC analysis of PGC1a in PBS- or cerulean-treated KC pancreas samples. The histogram to the right shows the histoscore of PGC1a. Data represent mean SD (n ¼ 3). Scale bar 200 mm. C and D, qRT- PCR analysis of PPARGC1A and CPT1A in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). E and F, Maximal respiration and spare respiratory capacity reflected by OCR were measured using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). G and H, Glycolysis and glycolytic capacity reflected by ECAR was measured in indicated samples using Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). I, Maximal endogenous OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). J and K, Immunofluorescence images of pancreas harvested from PBS- or cerulean-treated KC mice stained with PNA-Rhodamine, DBA-FITC, UEA1-FITC, CD133, PGC1a, CPT1A, and DAPI (as indicated). Scale bar 100 mm. L and M, qRT- PCR analysis of indicated genes in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). N, Basal OCR was measured in acinar, AD, and ductal populations using XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). O, Immunofluorescence images of pancreas harvested from 10-week-old KC and WT mice stained with CD133, PGC1a, cKIT, and DAPI (as indicated). Scale bar 50 mm. P, qRT- PCR analysis of indicated genes in LGKC1 control and doxycycline (Dox)-induced samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). Q, OCR was measured following the addition of oligomycin (O; 1 mmol/L), FCCP (F; 0.5 mmol/L), and electron transport inhibitor rotenone/antimycin A (R/A; 0.5 mmol/L). Data are mean SD (n ¼ 6). R, ECAR was measured following the addition of glucose (Glc; 10 mmol/L), oligomycin (O; 1 mmol/L), and 2-deoxyglucose (2DG; 50 mmol/L). Data are mean SEM (n ¼ 6). S, Immunofluorescence images of human IPMN organoids stained with PGC1a, CPT1A, and DAPI (as indicated). Scale bar 50 mm.

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Quantitative RT-PCR, Staining, Control

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 5. ADM/PanIN and IPMN show the upregulation of unique PGC1a-interacting partners. A, Protein–protein interactions analysis of PPARGC1A using “STRING” software. B–I, A meta-analysis of genes that encode PGC1a-interacting proteins using the human IPMN progression dataset GSE19650. Datasets were processed using standard GEO2R analysis, followed by quantile normalization and log2 transformation. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP. J, qRT-PCR analysis of indicated genes in acinar and AD cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). K and L, Immunofluorescence images with PGC1a, PPARg, and DAPI staining on indicated samples. M and N, Immunofluorescence images. NRF1 staining along with DAPI on pancreatic tissues harvested from control (KC) and cerulean-treated KC (KCþCer) mouse (M). The KCþCer immunofluorescence image, which was shown for NRF1 staining in M (bottom image), was further showed for the co-expression of NRF1 with PGC1a (N, bottom images). The co-expression of NRF1 with PGC1a was shown in another KCþCer tissue section (N, top images). O, Immunofluorescence images with PGC1a, NRF1, and DAPI staining on indicated samples. Scale bar 50 mm. For all histograms, P values were calculated by Student t test (, P < 0.05; , P < 0.01; , P < 0.001.)

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Protein-Protein interactions, Software, Transformation Assay, Quantitative RT-PCR, Staining, Control, Expressing

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 6. PGC1a-mediated OXPhos and FAO-OXPhos regulate stemness in ADM/PanIN and IPMN, respectively. A, qRT-PCR analysis of Ppargc1a in the scramble and PGC1a KD in LGKC1 cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). B, LGKC1 SCR and PGC1a KD cells were injected subcutaneously into nude mice and maintained with doxycycline (DOX) in water. The subcutaneous tumors were excised 21 days after implantation, followed by the measurement of tumor volume and weight (bar graphs). Data are mean SD (n ¼ 4). The significance was determined by a t test (, P < 0.05; , P < 0.01; , P < 0.001). C, qRT-PCR analysis of indicated genes in the scramble and PGC1a KD LGKC1þDOX cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). D–F, Basal, maximal respiration, and spare respiratory capacity reflected by OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). G and H, Morphology of human IPMN organoids growing in the presence and absence of SR18292. (Continued on the following page.)

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Quantitative RT-PCR, Injection

Journal: Cells

Article Title: A Role for PGC-1a in the Control of Abnormal Mitochondrial Dynamics in Alzheimer’s Disease

doi: 10.3390/cells11182849

Figure Lengend Snippet: A remarkable reduction in PGC-1a expression is observed in AD patients, cells and 2×Tg-AD mice. Expression patterns and qualification of ( A , F ) PGC-1a and ( B , C , G ) Aβ deposits from the parietal cortex samples of AD and control (Ctr) humans were analyzed using immunofluorescence. N 2 A cells were transfected with pCDNA plasmid or plasmid-encoding APP ( APPswe ) for 48 h. ( E ) Expression patterns and ( J ) qualification of PGC-1a were studied with Western blot. ( D ) PCR products obtained from genomic DNA from APP/PS1 mice. The 608 and 350 bp bands resulted from the amplification of PS1 and APP alleles, respectively. Expression patterns and qualification of ( H , K ) PGC-1a and ( I , L , M ) Aβ deposits from the parietal cortex samples of APP/PS1 and WT mice (6 months) were studied with immunofluorescence. The qualification of % Area fraction of Aβ plaques was calculated using the formula [area fraction of Aβ plaques/total area fractions] × 100% between the two genotypes. Scale bars = 200 μm. For each group, n = 6–10. Significance levels were set at * p < 0.05, *** p < 0.001 for noted differences between Ctr and AD groups, pCDNA and APPswe groups or WT and APP/PS1 groups. Tubulin was used as the loading control.

Article Snippet: Primary antibodies against EGFP (1:1000, Beyotime, cat # AG281, Shanghai, China), Flag (1:1000, abm, cat # G188, Zhenjiang, China), OPA1 (1:1000, Boster, cat # PB0773, Wuhan, China), MFN1 (1:1000, Boster, cat # PB0263, Wuhan, China), MFN2 (1:800, Bioss, cat # bs-23685R, Beijing, China), DRP1 (1:1000, Wanleibio, cat # WL03028, Shenyang, China), FIS1 (1:1000, Boster, cat # A01932-2, Wuhan, China), BAX (1:5000, Abcam, cat # ab32503, Cambridge, MA, USA), Bcl-2 (1:2000, Abcam, cat # ab182858, Cambridge, MA, USA), PGC-1a (1:1000, Bioss, cat # bs-1832R, Beijing, China), KIF5A Flag (diluted 1:1000, Bioword, cat # BS71526, Nanjing, China), KIF5B (diluted 1:1000, Wanleibio, cat # WL04906, Shenyang, China), and the horseradish peroxidase-linked antibodies (1:5000, Beyotime, goat anti mouse IgG, cat # A0216 and goat anti rabbit IgG, cat # A0208, Shanghai, China) were used to probe these blots.

Techniques: Expressing, Immunofluorescence, Transfection, Plasmid Preparation, Western Blot, Amplification

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 1. Meta-analysis of stemness programs and metabolic states in IPMN- and PanIN-mediated PDAC progression. NCBI GEO datasets (GSE19650 and GSE43288) were used to investigate the differential transcriptomic signatures of stemness and metabolic genes. The data analysis and processing were performed by quantile normalization and log2 transformation. A–N, Representation of the differentially expressed glycolysis genes (A–G), OXPhos genes (H–K), MYC (L), PPARGC1A (M), and CPT2 (N) in indicated samples: NP (N ¼ 7), IPMN-derived PDAC (IPMN-PDAC; n ¼ 3), IPMA or IPMN with low-grade dysplasia (n ¼ 6), and IPMC or IPMN with high- grade dysplasia (n ¼ 6). O–X, Representation of the differentially expressed glycolysis genes (O–U), fatty acid b-oxidation genes (V–W), and PPARGC1A (X) in indicated samples: NP (n ¼ 3), PanIN (n ¼ 13), and PDAC (n ¼ 4). Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (P < 0.05; , P < 0.05; , P < 0.01; P < 0.001.) Y, Venn diagram showing common and unique overexpressed stemness genes in PanIN and IPMN. Data represent mean SD. P valueswere calculated using ordinary one-way ANOVA (multiple comparisons; ,P < 0.05). Z, Network analysis of the differentially expressed stemness and metabolic genes from the GSE19650 dataset using IPA. The network shows that the PPARGC1A is central to stemness, FAO, and OXPhos pathways in IPMN.

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Transformation Assay, Derivative Assay

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 2. Differential expression of metabolic regulators, PGC1a and CPT1A, in different stages of PDAC development. A–F, IHC analysis of PGC1a (A–C) and CPT1A (D–F) in indicated samples. A histoscore was calculated by multiplying intensity and positivity. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP (, P < 0.05; , P < 0.01; , P < 0.001). Scale bar 200 mm. C and F, Magnified PanIN2 and IPMN regions duplicated from the original PanIN2 and IPMN IHC images of A and D to show the subcellular localization of PGC1a (C) and CPT1A (F) were shown.

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Quantitative Proteomics

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 4. ADM/PanIN and IPMN show upregulation of PGC1a and display unique metabolic states. A and B, IHC analysis of PGC1a in PBS- or cerulean-treated KC pancreas samples. The histogram to the right shows the histoscore of PGC1a. Data represent mean SD (n ¼ 3). Scale bar 200 mm. C and D, qRT- PCR analysis of PPARGC1A and CPT1A in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). E and F, Maximal respiration and spare respiratory capacity reflected by OCR were measured using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). G and H, Glycolysis and glycolytic capacity reflected by ECAR was measured in indicated samples using Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 6). I, Maximal endogenous OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). J and K, Immunofluorescence images of pancreas harvested from PBS- or cerulean-treated KC mice stained with PNA-Rhodamine, DBA-FITC, UEA1-FITC, CD133, PGC1a, CPT1A, and DAPI (as indicated). Scale bar 100 mm. L and M, qRT- PCR analysis of indicated genes in indicated samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). N, Basal OCR was measured in acinar, AD, and ductal populations using XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). O, Immunofluorescence images of pancreas harvested from 10-week-old KC and WT mice stained with CD133, PGC1a, cKIT, and DAPI (as indicated). Scale bar 50 mm. P, qRT- PCR analysis of indicated genes in LGKC1 control and doxycycline (Dox)-induced samples. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). Q, OCR was measured following the addition of oligomycin (O; 1 mmol/L), FCCP (F; 0.5 mmol/L), and electron transport inhibitor rotenone/antimycin A (R/A; 0.5 mmol/L). Data are mean SD (n ¼ 6). R, ECAR was measured following the addition of glucose (Glc; 10 mmol/L), oligomycin (O; 1 mmol/L), and 2-deoxyglucose (2DG; 50 mmol/L). Data are mean SEM (n ¼ 6). S, Immunofluorescence images of human IPMN organoids stained with PGC1a, CPT1A, and DAPI (as indicated). Scale bar 50 mm.

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Quantitative RT-PCR, Staining, Control

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 5. ADM/PanIN and IPMN show the upregulation of unique PGC1a-interacting partners. A, Protein–protein interactions analysis of PPARGC1A using “STRING” software. B–I, A meta-analysis of genes that encode PGC1a-interacting proteins using the human IPMN progression dataset GSE19650. Datasets were processed using standard GEO2R analysis, followed by quantile normalization and log2 transformation. Data represent mean SD. P values were calculated using ordinary one-way ANOVA (multiple comparisons). The mean of each sample was compared with the mean of NP. Asterisks indicate a statistically significant difference between each sample and NP. J, qRT-PCR analysis of indicated genes in acinar and AD cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). K and L, Immunofluorescence images with PGC1a, PPARg, and DAPI staining on indicated samples. M and N, Immunofluorescence images. NRF1 staining along with DAPI on pancreatic tissues harvested from control (KC) and cerulean-treated KC (KCþCer) mouse (M). The KCþCer immunofluorescence image, which was shown for NRF1 staining in M (bottom image), was further showed for the co-expression of NRF1 with PGC1a (N, bottom images). The co-expression of NRF1 with PGC1a was shown in another KCþCer tissue section (N, top images). O, Immunofluorescence images with PGC1a, NRF1, and DAPI staining on indicated samples. Scale bar 50 mm. For all histograms, P values were calculated by Student t test (, P < 0.05; , P < 0.01; , P < 0.001.)

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Protein-Protein interactions, Software, Transformation Assay, Quantitative RT-PCR, Staining, Control, Expressing

Journal: Clinical Cancer Research

Article Title: PGC1α-Mediated Metabolic Reprogramming Drives the Stemness of Pancreatic Precursor Lesions

doi: 10.1158/1078-0432.ccr-20-5020

Figure Lengend Snippet: Figure 6. PGC1a-mediated OXPhos and FAO-OXPhos regulate stemness in ADM/PanIN and IPMN, respectively. A, qRT-PCR analysis of Ppargc1a in the scramble and PGC1a KD in LGKC1 cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). B, LGKC1 SCR and PGC1a KD cells were injected subcutaneously into nude mice and maintained with doxycycline (DOX) in water. The subcutaneous tumors were excised 21 days after implantation, followed by the measurement of tumor volume and weight (bar graphs). Data are mean SD (n ¼ 4). The significance was determined by a t test (, P < 0.05; , P < 0.01; , P < 0.001). C, qRT-PCR analysis of indicated genes in the scramble and PGC1a KD LGKC1þDOX cells. The PCR data were normalized with the Actb gene. Data represent mean SD (n ¼ 3). D–F, Basal, maximal respiration, and spare respiratory capacity reflected by OCR due to FAO measured by XF Palmitate-BSA FAO Substrate with the XF Cell Mito Stress Test kit using the Seahorse extracellular flux analyzer. Data are mean SEM (n ¼ 3). G and H, Morphology of human IPMN organoids growing in the presence and absence of SR18292. (Continued on the following page.)

Article Snippet: Generation of PGC1a stable KD cells The Colo357 pancreatic cancer cells with stable PGC1a KD and scrambled (SCR) control cells were generated using a PGC1a human shRNA plasmid kit (Origene, TG310260).

Techniques: Quantitative RT-PCR, Injection