DOI: 10.5061/dryad.8pk0p2nvh
title: Transcriptional determinants of lipid mobilization in human adipocytes

description: Defects in adipocyte lipolysis drive multiple aspects of cardiometabolic
 disease but the transcriptional framework controlling this process has not
 been established. To address this, we performed a targeted perturbation
 screen in primary human adipocytes. Our analyses identified 37
 transcriptional regulators of lipid mobilization, which we classified as:
 i) transcription factors, ii) histone chaperones, and iii) mRNA processing
 proteins. Based on its strong relationship with multiple readouts of
 lipolysis in patient samples, we performed mechanistic studies on one hit,
 ZNF189, which encodes the Zinc Finger Protein 189. Using mass-spectrometry
 and chromatin profiling techniques, we show that ZNF189 interacts with the
 tripartite motif family member TRIM28 and represses the transcription of
 an adipocyte-specific isoform of Phosphodiesterase 1B (PDE1B2). The
 regulation of lipid mobilization by ZNF189 requires PDE1B2 and
 overexpression of PDE1B2 is sufficient to attenuate hormone-stimulated
 lipolysis. Thus, our work identifies the ZNF189-PDE1B2 axis as a
 determinant of human adipocyte lipolysis and highlights a link between
 chromatin architecture and lipid mobilization.
description: <strong>RNAi Screen - Glycerol Release:
 </strong>RNA interference screening experiment, in adipocytes
 differentiated from CD55+/DPP4+ progenitor cells, was performed with the
 siGENOME® SMARTpool® siRNA Human Transcription Factor Library (Dharmacon,
 Lafayette, CO, USA). Lipolysis was assessed by fluorometric detection of
 glycerol in phenol-red-free media (ThermoFisher Scientific, 21041-033)
 collected from cells after 72 hours after siRNA transfection. Cytotoxicity
 was assessed by measuring LDH activity using the Cytotoxicity Detection
 KitPLUS 548 (Roche, 4744926001) according to the manufacturer’s
 instructions. Glycerol release and LDH data were analyzed using R v4.2.2.
 Outliers were identified using the IQR method, additionally triplicates
 with CV &gt; 20% were excluded from further analysis. The
 reproducibility of the glycerol release assays was assessed by calculation
 of the Pearson correlation coefficient between the experimental
 replicates. Data were normalized and scaled using the robust z-score
 method. Replicates with LDH release with rz-score &gt; |5| were
 excluded from the statistical analysis. Targets that significantly affect
 glycerol release (“hits”) were identified using a One-way ANOVA with
 Dunnet’s post-hoc test. <strong> Meta-analysis
 of the relationship between ZNF189 mRNA clinical
 parameters<br></strong>To assess the relationship
 between ZNF189 mRNA levels and metabolic parameters, we performed a
 meta-analysis of its expression in subcutaneous WAT samples across nine
 published clinical cohorts. For the meta-analysis of the relationship
 between ZNF189 mRNA and clinical parameters, both random and common
 effects from Spearman correlations are
 presented.<strong><br></strong> 
 <strong>Lipidomics<br></strong>Samples were analyzed in
 both positive and negative ion modes with a resolution of Rm/z=200=500000
 for MS and Rm/z=200=30000 for MS/MS experiments. MS/MS was triggered by an
 inclusion list encompassing corresponding MS mass ranges scanned in 1Da
 increments. Both MS and MS/MS data were combined to monitor CE, DAG, and
 TAG ions as ammonium adducts; PC, PC O-, as acetate adducts; and CL, PA,
 PE, PE O-, PG, PI, and PS as deprotonated anions. MS only was used to
 monitor LPA, LPE, LPE O-,LPI, and LPS as deprotonated anions; Cer, HexCer,
 SM, LPC, and LPC O- as acetate adducts. Data were analyzed with in-house
 developed lipid identification software, based on LipidXplorer. Data
 post-processing and normalization were performed using an in-house
 developed data management system. Only lipid identifications with a
 signal-to-noise ratio &gt;and a signal intensity five-fold higher than
 in corresponding blank samples were considered for further data analysis.
 Lipid species were included in statistical analysis if they had detectable
 values across all 6 replicates for both siRNA conditions. Principal
 components analysis was performed with the FactoMineR package in R.
 Confidence ellipses were calculated for a 0.95 confidence level.
 Species-level differences in lipids were assessed by pairwise comparisons
 using eBayes with the limma package in R, with FDR
 correction.<strong><br></strong>
description: # Transcriptional determinants of lipid mobilization in human adipocytes
 This data set contains the
 following: 1. **RNAi Screen - Glycerol Release:** RNA interference
 screening experiment, in adipocytes differentiated from CD55+/DPP4+
 progenitor cells, was performed with the siGENOME® SMARTpool® siRNA Human
 Transcription Factor Library (Dharmacon, Lafayette, CO, USA). Lipolysis
 was assessed by fluorometric detection of glycerol in phenol-red-free
 media (ThermoFisher Scientific, 21041-033) collected from cells after 72
 hours after siRNA transfection. Cytotoxicity was assessed by measuring LDH
 activity using the Cytotoxicity Detection KitPLUS 548 (Roche, 4744926001)
 according to the manufacturer’s instructions. Glycerol release and LDH
 data were analyzed using R v4.2.2. Outliers were identified using the IQR
 method, additionally triplicates with CV &gt; 20% were excluded from
 further analysis. The reproducibility of the glycerol release assays was
 assessed by calculation of the Pearson correlation coefficient between
 the experimental replicates. Data were normalized and scaled using the
 robust z-score method. Replicates with LDH release with rz-score &gt; |5|
 were excluded from the statistical analysis. Targets that significantly
 affect glycerol release (“hits”) were identified using a One-way ANOVA
 with Dunnet’s post-hoc test. 2. **Meta-analysis of the relationship
 between ZNF189 mRNA clinical parameters** \ To assess the relationship
 between ZNF189 mRNA levels and metabolic parameters, we performed a
 meta-analysis of its expression in subcutaneous WAT samples across nine
 published clinical cohorts. For the meta-analysis of the relationship
 between ZNF189 mRNA and clinical parameters, both random and common
 effects from Spearman correlations are presented. 3. **Lipidomics**\
 Samples were analyzed in both positive and negative ion modes with a
 resolution of Rm/z=200=500000 for MS and Rm/z=200=30000 for MS/MS
 experiments. MS/MS was triggered by an inclusion list encompassing
 corresponding MS mass ranges scanned in 1Da increments. Both MS and MS/MS
 data were combined to monitor CE, DAG, and TAG ions as ammonium adducts;
 PC, PC O-, as acetate adducts; and CL, PA, PE, PE O-, PG, PI, and PS as
 deprotonated anions. MS only was used to monitor LPA, LPE, LPE O-,LPI, and
 LPS as deprotonated anions; Cer, HexCer, SM, LPC, and LPC O- as acetate
 adducts. Data were analyzed with in-house developed lipid identification
 software, based on LipidXplorer. Data post-processing and normalization
 were performed using an in-house developed data management system. Only
 lipid identifications with a signal-to-noise ratio &gt;and a signal
 intensity five-fold higher than in corresponding blank samples were
 considered for further data analysis. Lipid species were included in
 statistical analysis if they had detectable values across all 6 replicates
 for both siRNA conditions. Principal components analysis was performed
 with the FactoMineR package in R. Confidence ellipses were calculated for
 a 0.95 confidence level. Species-level differences in lipids were assessed
 by pairwise comparisons using eBayes with the limma package in R, with FDR
 correction. ## Description of the data and file structure 1.**RNAi Screen
 - Glycerol Release:** Data for glycerol release levels and LDH activity,
 as well as the corresponding standard curves are stored as csv files. R
 Scripts are available for analyzing the data. **Description of csv
 files:** * a. data_samples.csv: file containing raw relative flawrescence
 unit (RFU) values from glycerol release of the screen. This file can be
 used to extrapolate glycerol concentration levels (ug/ml) using a standard
 curve that is provided in the file described below. Rows correspond to
 different samples. Columns describe an index number, a GeneID for the gene
 Knock-down, the plate of the sample, the well of the sample within that
 plate, and the RFU values (Signal). Missing values are presented as empty
 cells and derive from the signal measurement, these values are recognized
 as NA values by the R script provided and handled accordingly during the
 analysis pipeline. * b. data_standard_curves.csv: file containing raw
 relative flawrescence unit (RFU) values from the standard samples for the
 glycerol release of the screen. This file can be used to construct the
 standard curves needed for calculating glyceros release concentrations of
 the samples. These standard samples are from the same plates used in the
 data_samples.csv file. Rows correspond to different samples. Columns
 describe an index number, the well of the sample, the measured RFU signal,
 the respective plate, the patient, and the concentration of the standard
 sample (ug/mL). Missing values are presented as empty cells and derive
 from the signal measurement, these values are recognised as NA values by
 the R script provided and handled accordingly during the analysis
 pipeline. * c. data_samples_screen2.csv: file containing raw relative
 flawrescence unit (RFU) values from glycerol release of the secondary RNAi
 screen and with the same structure as data_samples.csv. This file can be
 used to extrapolate glycerol concentration levels using a standard curve
 that is provided in the file described below. Missing values are presented
 as empty cells and derive from the signal measurement, these values are
 recognised as NA values by the R script provided and handled accordingly
 during the analysis pipeline. * d. data_standard_curves_screen2.csv: data
 table with the same structure as data_samples.csv for a number of samples
 from the same experiment that were re-measured. This file can be used to
 construct the standard curves needed for calculating glyceros release
 concentrations of the samples. Missing values are presented as empty cells
 and derive from the signal measurement, these values are recognised as NA
 values by the R script provided and handled accordingly during the
 analysis pipeline. * e. data_samples_remeasured.csv : data table with the
 same structure as data_samples.csv for a number of samples from the
 secondary screen experiment that were re-measured. This file can be used
 to extrapolate glycerol concentration levels using a standard curve that
 is provided in the file described below. Missing values are presented as
 empty cells and derive from the signal measurement, these values are
 recognised as NA values by the R script provided and handled accordingly
 during the analysis pipeline. * f. data_standard_curves_remeasured.csv:
 data table with the same structure as data_standard_curves.csv for a
 number of samples from the same experiment that were re-measured. This
 file can be used to construct the standard curves needed for calculating
 glyceros release concentrations of the samples. Missing values are
 presented as empty cells and derive from the signal measurement, these
 values are recognised as NA values by the R script provided and handled
 accordingly during the analysis pipeline. * g. ldh_screen2.csv: raw data
 from the LDH experiment for the secondary screen. Rows correspond to
 different samples. This file can be used to assess the cell viability
 after RNAi in the secondary screen. Columns describe an index number, a
 GeneID for the gene Knock-down, the plate of the sample, the well of the
 sample within that plate, and the absorbance values (Abs). Missing values
 are presented as empty cells and derive from the signal measurement, these
 values are recognised as NA values by the R script provided and handled
 accordingly during the analysis pipeline. **Description of R script
 files:** * a. Glycerol_analysis_Screen1: Open the file and install the
 libraries needed for the analysis as indicated in the first section of the
 code. In the import files, choose the corresponding csv as indicated by
 the comments in the code. The linear regression and standard fit section
 of the code are used to create the standard curves for the glycerol
 release measurements using a linear regression model and to fit the
 unknown samples to those curves to obtain concentration values (ug/ml). In
 the next section, descriptive statistics are used to describe the samples
 and identify outliers and batch effects. Next, data are normalized using
 robust z-scores, and descriptive statistics are used again to exclude
 outliers using IQR outlier elimination and identify samples with high CV.
 Replicate correlation is used as a quality control for the measurements.
 In the final section, once outliers are removed, one-way ANOVA followedby
 Dunnett's post-hoc test is performed. * b. Glycerol_analysis_Screen2:
 Open the file and install the libraries needed for the analysis as
 indicated in the first section of the code. In the import files, choose
 the corresponding csv as indicated by the comments in the code. The linear
 regression and standard fit section of the code are used to create the
 standard curves for the glycerol release measurements using a linear
 regression model and to fit the unknown samples to those curves to obtain
 concentration values (ug/ml). In the next section, descriptive statistics
 are used to describe the samples and identify outliers and batch effects,
 and to compare the samples with screen1. Next, data are normalized using
 robust z-scores, and descriptive statistics are used again to exclude
 outliers using IQR outlier elimination and identify samples with high CV.
 In the next section LDH data are fitted using linear regression and
 samples with high LDH release are removed from further analysis. In the
 final section, once outliers are removed, one-way ANOVA followed by
 Dunnett's post-hoc test is performed. * Important note: Although the
 two scripts follow the same analysis pipeline, the script for the
 secondary screen includes measurement of glycerol release levels for a
 number of samples, as well as an additional analysis of LDH release levels
 that is used to exclude samples from further analysis. 2\. **Meta-analysis
 of the relationship between ZNF189 mRNA clinical parameters** Data tables
 from each clinical dataset used in the meta-analysis are provided as txt
 file. A README file is included with further information about its
 dataset. In every txt file, columns 1 and 2 correspond to PDE1B and ZNF189
 gene expression. The rest of the columns correspond to clinical parameters
 available in the dataset. These clinical parameter can be weight-to-hip
 ratio (WHR) and/or the HOMA-Insulin Resistance index (HOMA-IR). Rows
 correspond to different samples. 3\. **Lipidomics** Lipidomics data are
 provided as csv files. Rows correspond to different lipid species and they
 are described by the first column. The rest of the columns correspond to
 different samples measured. Missing values are presented as empty cells
 and derive from the signal measurement, these values are recognised as NA
 values by the R script provided and handled accordingly during the
 analysis pipeline. R Scripts are available for analyzing the data. Open
 the file and install the libraries needed for the analysis as indicated in
 the first section of the code. Import the file as indicated by the file
 path at the beginning of the code. In every step follow the instructions
 as indicated by the comments. The code can be used to perform descriptive
 statistics, PCA, and replicate correlation as quality control measures. In
 the final section, LIMMA is used to identify differentially altered lipid
 species. T ## Sharing/Access information Links to other publicly
 accessible locations of the data: *
 * Genomics data
 related to this publication are deposited in NCBI's Gene Expression
 Omnibus with the accession number GSE247818 * Proteomic 1172 data are
 deposited in the PRIDE database with the accession number PXD046964