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Regulation of autophagy in development and disease

Goal: Studying the regulation of autophagy in development (adipocyte differentiation) and disease (cancer)

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Mahmoud Ahmed
added a research item
Ob/ob mice are leptin-deficient animals with uninhibited food intake and susceptibility to gain weight and develop type 2 diabetes. The mice have been used to study obesity and diabetes. We generated a dataset of different tissue gene expressions from wild-type and ob/ob mice with a normal diet (ND) or high-fat diet (HFD). The gene expression was profiled at a genome-scale using RNA-seq. We deposited the raw data to the short read archive and the processed data to the gene expression omnibus. In this manuscript, we describe generating the dataset and technical validation of the gene expression profiles. We assessed the quality of the reads, alignment, and the quantification of gene expression. We found that the tissue of origin explained the most variance between samples. Non-coding features differed in their contribution to the mice profiles. Gene expression profiles diverged between the experimental groups. To sum, this dataset can be used to study tissue-specific gene expression in weight gain susceptible mice and the response to HFD.
Mahmoud Ahmed
added a research item
We previously showed that some adipogenic transcription factors such as CEBPB and PPARG directly and indirectly regulate autophagy gene expression in adipogenesis. The order and effect of these events are undetermined. In this study, we modeled the gene expression, DNA-binding of transcriptional regulators, and histone modifications during adipocyte differentiation and evaluated the effect of the regulators on gene expression in terms of direction and magnitude. Then, we identified the overlap of the transcription factors and co-factors binding sites and targets. Finally, we built a chromatin state model based on the histone marks and studied their relation to the factors’ binding. Adipogenic factors differentially regulated autophagy genes as part of the differentiation program. Co-regulators associated with specific transcription factors and preceded them to the regulatory regions. Transcription factors differed in the binding time and location, and their effect on expression was either localized or long-lasting. Adipogenic factors disproportionately targeted genes coding for autophagy-specific transcription factors. In sum, a hierarchical arrangement between adipogenic transcription factors and co-factors drives the regulation of autophagy during adipocyte differentiation.
Mahmoud Ahmed
added 10 research items
Background Raf kinase inhibitor protein (RKIP) plays a critical role in many signaling pathways as a multi-functional adapter protein. In particular, the loss of RKIP's function in certain types of cancer cells results in ep-ithelial to mesenchymal transition (EMT) and the promotion of cancer metastasis. Also, RKIP inhibits autophagy by modulating LC3-lipidation and mTORC1. How the RKIP-dependent inhibition of autophagy is linked EMT and cancer progression is still under investigation.
Mahmoud Ahmed
added 3 research items
Autophagy is a highly conserved metabolic process involved in the degradation of intracellular components including proteins and organelles. Consequently, it plays a critical role in recycling metabolic energy for the maintenance of cellular homeostasis in response to various stressors. In cancer, autophagy either suppresses or promotes cancer progression depending on the stage and cancer type. Epithelial-mesenchymal transition (EMT) and cancer metastasis are directly mediated by oncogenic signal proteins including SNAI1, SLUG, ZEB1/2, and NOTCH1, which are functionally correlated with autophagy. In this report, we discuss the crosstalk between oncogenic signaling pathways and autophagy followed by possible strategies for cancer treatment via regulation of autophagy. Although autophagy affects EMT and cancer metastasis, the overall signaling pathways connecting cancer progression and autophagy are still illusive. In general, autophagy plays a critical role in cancer cell survival by providing a minimum level of energy via self-digestion. Thus, cancer cells face nutrient limitations and challenges under stress during EMT and metastasis. Conversely, autophagy acts as a potential cancer suppressor by degrading oncogenic proteins, which are essential for cancer progression, and by removing damaged components such as mitochondria to enhance genomic stability. Therefore, autophagy activators or inhibitors represent possible cancer therapeutics. We further discuss the regulation of autophagy-dependent degradation of oncogenic proteins and its functional correlation with oncogenic signaling pathways, with potential applications in cancer therapy.
Differentiating 3T3-L1 pre-adipocytes are a mixture of non-identical culture cells. It is vital to identify the cell types that respond to the induction stimulus to understand the pre-adipocyte potential and the mature adipocyte behavior. To test this hypothesis, we deconvoluted the gene expression profiles of the cell culture of MDI-induced 3T3-L1 cells. Then we estimated the fractions of the sub-populations and their changes in time. We characterized the sub-populations based on their specific expression profiles. Initial cell cultures comprised three distinct phenotypes. A small fraction of the starting cells responded to the induction and developed into mature adipocytes. Unresponsive cells were probably under structural constraints or were committed to differentiating into alternative phenotypes. Using the same population gene markers, similar proportions were found in induced human primary adipocyte cell cultures. The three sub-populations had diverse responses to treatment with various drugs and compounds. Only the response of the maturating sub-population resembled that estimated from the profiles of the mixture. We then showed that even at a low division rate, a small fraction of cells could increase its share in a dynamic two-populations model. Finally, we used a cell cycle expression index to validate that model. To sum, pre-adipocytes are a mixture of different cells of which a limited fraction become mature adipocytes.
Mahmoud Ahmed
added 2 research items
Approach. We modeled the gene expression, DNA-binding of transcriptional regulators, and histone modifications during adipocyte differentiation [1, preprint available]. We evaluated the effect of the binding of the regulators on gene expression in terms of direction and magnitude. Then, we identified the overlap of the transcription factors and co-factors binding sites and targets. Finally, we built a chromatin states model based on the histone marks and studied their relation with the factors’ binding. Findings. Adipogenic factors differentially regulated autophagy genes as part of the differentiation program. Co-regulators associated with specific transcription factors and preceded them to the regulatory regions. Transcription factors differed in the binding time and location, and their effect on expression was either localized or long-lasting. Adipogenic factors disproportionately targeted genes coding for autophagy-specific transcription factors.
We previously showed that some adipogenic transcription factors such as CEBPB and PPARG, directly and indirectly, regulate autophagy gene expression in adipogenesis. The order and the effect of these events are undetermined. In this study, we modeled the gene expression, DNA-binding of transcriptional regulators, and histone modifications during adipocyte differentiation and evaluated the effect of the regulators on gene expression in terms of direction and magnitude. Then, we identified the overlap of the transcription factors and co-factors binding sites and targets. Finally, we built a chromatin states model based on the histone marks and studied their relation with the factors’ binding. Adipogenic factors differentially regulated autophagy genes as part of the differentiation program. Co-regulators associated with specific transcription factors and preceded them to the regulatory regions. Transcription factors differed in the binding time and location, and their effect on expression was either localized or long-lasting. Adipogenic factors disproportionately targeted genes coding for autophagy-specific transcription factors. To sum, a hierarchical arrangement between adipogenic transcription factors and co-factors drives the regulation of autophagy during adipocyte differentiation.
Mahmoud Ahmed
added a research item
The 3T3-L1 cell line is used as an adipocyte differentiation model for the analysis of genes specifically expressed during the differentiation course. This cell model has several applications in obesity and insulin resistance research. We built a data resource to model gene expression of differentiating and mature adipocytes in response to several drugs and gene manipulations. We surveyed the literature survey for microarray datasets of differentiating 3T3-L1 cell line sampled at one or more time points under genetic or pharmacological perturbations. Data and metadata were obtained from the gene expression omnibus. The metadata were manually curated using unified language across the studies. Probe intensities were mapped and collapsed to genes using a reproducible pipeline. Samples were classified into none, genetically or pharmacologically modified. In addition to the clean datasets, two aggregated sets were further homogenized for illustration purposes. The curated datasets are available as an R/Bioconductor experimental data package curatedAdipoArray. The package documents the source code of the data collection, curation and processing. Finally, we used a subset of the data to effectively remove batch effects and reproduce biological observations. Database URL https://bioconductor.org/packages/curatedAdipoArray
Mahmoud Ahmed
added 10 research items
A curated dataset of publicly available ChIP-sequencing of transcription factors, chromatin remodelers, and histone modifications in the 3T3-L1 pre-adipocyte cell line. The package document the data collection, pre-processing, and processing of the data. In addition to the documentation, the package contains the scripts that were used to generate the data.
A curated dataset of RNA-Seq samples. The samples are MDI-induced pre-phagocytes (3T3-L1) at different time points/stages of differentiation. The package document the data collection, pre-processing, and processing. In addition to the documentation, the package contains the scripts that were used to generate the data.
A curated dataset of Microarrays samples. The samples are MDI- induced pre-adipocytes (3T3-L1) at different time points/stages of differentiation under different types of genetic (knockdown/overexpression) and pharmacological (drug treatment) perturbations. The package documents the data collection and processing. In addition to the documentation, the package contains the scripts that were used to generate the data.
Mahmoud Ahmed
added a research item
We previously showed that some adipogenic transcription factors such as CEBPB and PPARG directly and indirectly regulate autophagy gene expression in adipogenesis. The order and the effect of these events are undetermined. In this study, we modeled the gene expression, DNA-binding of transcriptional regulators, and histone modifications during adipocyte differentiation and evaluated the effect of the regulators on gene expression in terms of direction and magnitude. Then, we identified the overlap of the transcription factors and co-factors binding sites and targets. Finally, we built a chromatin states model based on the histone marks and studied their relation with the factors' binding. Adipogenic factors differentially regulated autophagy genes as part of the differentiation program. Co-regulators associated with specific transcription factors and preceded them to the regulatory regions. Transcription factors differed in the binding time and location, and their effect on expression was either localized or long-lasting. Adipogenic factors disproportionately targeted genes coding for autophagy-specific transcription factors. To sum, a hierarchical arrangement between adipogenic transcription factors and co-factors drives the regulation of autophagy during adipocyte differentiation.
Mahmoud Ahmed
added 2 research items
Autophagy is the cell self-eating mechanism to maintain cell homeostasis by removing damaged intracellular proteins or organelles. It has also been implicated in the development and differentiation of various cell types including the adipocyte. Several links between adipogenic transcription factors and key autophagy genes has been suggested. In this study, we tried to model the gene expression and their transcriptional regulation during the adipocyte differentiation using high-throughput sequencing datasets of the 3T3-L1 cell model. We applied the gene expression and co-expression analysis to all and the subset of autophagy genes to study the binding, and occupancy patterns of adipogenic factors, co-factors and histone modifications on key autophagy genes. We also analyzed the gene expression of key autophagy genes under different transcription factor knockdown adipocyte cells. We found that a significant percent of the variance in the autophagy gene expression is explained by the differentiation stage of the cell. Adipogenic master regulators, such as CEBPB and PPARG target key autophagy genes directly. In addition, the same factor may also control autophagy gene expression indirectly through autophagy transcription factors such as FOXO1, TFEB or XBP1. Finally, the binding of adipogenic factors is associated with certain patterns of co-factors binding that might modulate the functions. Some of the findings were further confirmed under the knockdown of the adipogenic factors in the differentiating adipocytes. In conclusion, autophagy genes are regulated as part of the transcriptional programs through adipogenic factors either directly or indirectly through autophagy transcription factors during adipogenesis.
The 3T3-L1 pre-adipocyte cell line is widely used to study the fat cell differentiation in vitro. Researchers also use this cell model to study obesity and insulin resistance. We surveyed the literature, the gene expression omnibus and the sequence read archive for RNA-Seq and ChIP-Seq datasets of MDI-induced 3T3-L1 differentiating cells sampled at one or more time points. The metadata of the relevant datasets were manually curated using unified language across the original studies. The raw reads were collected and pre-processed using a reproducible state-of-the-art pipeline. The final datasets are presented as reads count in genes for the RNA-Seq and reads count in peaks for the ChIP-Seq dataset. The curated datasets are available as two Bioconductor experimental data packages curatedAdipoRNA and curatedAdipoChIP. In addition, the packages document the source code of the data collection and the pre-processing pipelines. Here, we provide a descriptive analysis of the datasets with context and technical validation.
Mahmoud Ahmed
added a research item
Background Autophagy has been implicated in the development and differentiation of various cell types including the adipocyte [3, 5]. The 3T3-L1 mouse fibroblast is a key model for studying the adipocyte differentiation. When the pre-adipocyte is induced with a chemical cocktail containing MDI (1-Methyl-3-isobutylxanthine, Dexametha-sone and Insulin), the cell witnesses morphological and metabolic changes and is finally transformed into mature adipocyte [4]. In this study, we tried to model the gene expression and their transcriptional regulation during the adipocyte differentiation using public datasets [2, 1]. Methods We applied the gene expression and co-expression analysis to all and the subset of autophagy genes to study the binding, and occupancy patterns of adipogenic factors, co-factors and histone modications on key autophagy genes (Figure 1). Results We found that a signicant percent of the variance in the autophagy gene expression is explained by the differentiation stage of the cell (Figure 2). Changes in gene expression were also reflected on the gene set level where both lipogenic and autophagy related gene ontology terms were enriched (Table 1). Adipogenic master regulators such as CEBPB and PPARG target key autophagy genes directly (Figure 3). In addition, the same factor may also control autophagy gene expression indirectly through autophagy transcription factors such as Foxo1, Tfeb or Xbp1 (Figure 3). Finally, the binding of adipogenic factors is associated with certain patterns of co-factors binding that might modulate the functions (Figure 4). Some of the ndings were further conrmed under the knockdown of the adipogenic factors in the differentiating adipocytes (Figure 5). Conclusion In conclusion, autophagy genes are regulated as part of the transcriptional programs through adipogenic factors either directly or indirectly through autophagy transcription factors during adipogenesis (Figure 6).
Mahmoud Ahmed
added a research item
3T3-L1 preadipocytes undergo adipogenesis in response to treatment with dexamethaxone, 1-methyl-3-isobutylxanthine, and insulin (DMI) through activation of several adipogenic transcription factors. Many autophagy-related proteins are also highly activated in the earlier stages of adipogenesis, and the LC3 conjugation system is required for formation of lipid droplets. Here, we investigated the effect of overexpression of green fluorescent protein (GFP)-LC3 fusion protein on adipogenesis. Overexpression of GFP-LC3 in 3T3-L1 preadipocytes using poly-L-lysine-assisted adenoviral GFP-LC3 transduction was sufficient to produce intracellular lipid droplets. Indeed, GFP-LC3 overexpression stimulated expression of some adipogenic transcription factors (e.g., C/EBPα or β, PPARγ, SREBP2). In particular, SREBP2 was highly activated in preadipocytes transfected with adenoviral GFP-LC3. Also, phosphorylation of Raf kinase inhibitory protein (RKIP) at serine 153, consequently stimulating extracellular-signal regulated kinase (ERK)1 activity, was significantly increased during adipogenesis induced by either poly-L-lysine-assisted adenoviral GFP-LC3 transduction or culture in the presence of dexamethasone, 1-methyl-3-isobutylxanthine, and insulin. Furthermore, RKIP knockdown promoted ERK1 and PPARγ activation, and significantly increased the intracellular accumulation of triacylglycerides in DMI-induced adipogenesis. In conclusion, GFP-LC3 overexpression in 3T3-L1 preadipocytes stimulates adipocyte differentiation via direct modulation of RKIP-dependent ERK1 activity.
Mahmoud Ahmed
added 10 research items
Autophagy contributes to reorganizing intracellular components and forming fat droplets during the adipocyte differentiation. Here, we used public RNA-seq data to characterize the role of autophagy at different developmental stages of MDI-induced 3T3-L1 pre-adipocytes. Raw data of 4 different time points were obtained from the Short Read Archive. Salmon quasi-mapping based method was used to quantify the transcripts and the gene counts. DESeq2 package was used to model the gene counts for differential expression. Package goseq was used to apply the gene set enrichment analysis. Data were obtained, processed and annotated using R and Bioconductor. Several autophagy gene sets, as defined in the Gene Ontology, were activated during the course of the adipocyte differentiation. We further characterized these gene sets by clustering their members to a few distinct temporal profiles. Other potential functionally related genes were identified using a machine learning procedure. In summary, we characterized the autophagy gene sets and their members to biologically meaningful groups and elected several other genes to be functionally related based on their expression patterns, suggesting that they play critical roles in the adipogenesis.
3T3-L1 pre-adipocyte is a mouse fibroblast that can differentiate to a mature adipocyte when treated under a certain medium, therefore is often employed as a platform to study lipid metabolism in fat cells.Here, we use public available a gene expression microarray dataset from Gene Expression Omnibus (GEO) and transcription factors datasets from Cistrome Data Browser to explore the involvement of the autophagy and its potential regulation in differentiating adipocyte-like cell line. Gene Ontology (GO) was used to identify autophagyrelated genes in the dataset that were differentially expressed over time. Then, we coupled the gene expression with the ChIP-Seq datasets to explore the regulation patterns of the autophagy. Data were obtained, processed and annotated using Bioconductor tools. Six autophagy gene sets were significantly and differentially expressed in mature 3T3-L1 cells compared to the pre-adipocytes. Several genes were represented by multiple probes in the dataset and unlike expression levels. Many transcription factors modified the transcriptome of differentiating 3T3- L1 and had potential binding sites overlap with autophagy-related genes’ locations. Overall, autophagy-related genes were expressed alternatively, suggesting that autophagy role-plays accordingly and potentially is refashioned by alternative splicing.
Autophagy contributes to reorganizing intracellular components and forming fat droplets during the adipocyte differentiation. Here, we systematically describe the role of autophagy-related genes and gene sets during the differentiation of adipocytes. We used a public dataset from the European Nucleotide Archive from an RNA-seq experiment in which 3T3-L1 cells were induced by a differentiation induction medium, total RNA was extracted and sequenced at four different time points. Raw reads were aligned to the UCSC mouse reference genome (mm10) using HISAT2, and aligned reads were summarized at the gene or exon level using HTSeq. DESeq2 and DEXSeq were used to model the gene and exon counts and test for differential expression and relative exon usage, respectively. After applying the appropriate transformation, gene counts were used to perform the gene set and pathway enrichment analysis. Data were obtained, processed and annotated using R and Bioconductor. Several autophagy-related genes and autophagy gene sets, as defined in the Gene Ontology, were actively regulated during the course of the adipocyte differentiation. We further characterized these gene sets by clustering their members to a few distinct temporal profiles. Other potential functionally related genes were identified using a machine learning procedure. In summary, we characterized the autophagy gene sets and their members to biologically meaningful groups and elected a number of genes to be functionally related based on their expression patterns, suggesting that autophagy plays a critical role in removal of some intracellular components and supply of energy sources for lipid biogenesis during adipogenesis.
Mahmoud Ahmed
added a project goal
Studying the regulation of autophagy in development (adipocyte differentiation) and disease (cancer)