Predictive models of eukaryotic transcriptional regulation reveals changes in transcription factor roles and promoter usage between metabolic conditions

Transcription factors (TF) are central to transcriptional regulation, but they are often studied in relative isolation and without close control of the metabolic state of the cell. Here, we describe genome-wide binding (by ChIP-exo) of 15 yeast TFs in four chemostat conditions that cover a range of metabolic states. We integrate this data with transcriptomics and six additional recently mapped TFs to identify predictive models describing how TFs control gene expression in different metabolic conditions. Contributions by TFs to gene regulation are predicted to be mostly activating, additive and well approximated by assuming linear effects from TF binding signal. Notably, using TF binding peaks from peak finding algorithms gave distinctly worse predictions than simply summing the low-noise and high-resolution TF ChIP-exo reads on promoters. Finally, we discover indications of a novel functional role for three TFs; Gcn4, Ert1 and Sut1 during nitrogen limited aerobic fermentation. In only this condition, the three TFs have correlated binding to a large number of genes (enriched for glycolytic and translation processes) and a negative correlation to target gene transcript levels

A bioinformatic pipeline to analyze ChIP-exo datasets

The decrease of sequencing cost in the recent years has made genome-wide studies of transcription factor (TF) binding through chromatin immunoprecipitation methods like ChIP-seq and chromatin immunoprecipitation with lambda exonuclease (ChIP-exo) more accessible to a broader group of users. Especially with ChIP-exo, it is now possible to map TF binding sites in more detail and with less noise than previously possible. These improvements came at the cost of making the analysis of the data more challenging, which is further complicated by the fact that to this date no complete pipeline is publicly available. Here we present a workflow developed specifically for ChIP-exo data and demonstrate its capabilities for data analysis. The pipeline, which is completely publicly available on GitHub, includes all necessary analytical steps to obtain a high confidence list of TF targets starting from raw sequencing reads. During the pipeline development, we emphasized the inclusion of different quality control measurements and we show how to use these so users can have confidence in their obtained results

A simplified and defined serum-free medium for cultivating fat across species

Cultivated meat is a promising technology with the potential to mitigate the ethical and environmental issues associated with traditional meat. Fat plays a key role in the meat flavor; therefore, development of suitable adipogenic protocols for livestock is essential. The traditional adipogenic cocktail containing IBMX, dexamethasone, insulin and rosiglitazone is not food-compatible. Here, we demonstrate that of the four inducers only insulin and rosiglitazone are necessary in both serum-free (DMAD) and serum-containing media, with DMAD outperforming FBS. Two glucocorticoid receptor activators, progesterone and hydrocortisone, found in DMAD and FBS, affect differentiation homogeneity, without playing an essential role in activating adipogenic genes. Importantly, this protocol leads to mature adipocytes in 3D culture. This was demonstrated in both media types and in four species: ruminant and monogastric. We therefore propose a simplified one-step adipogenic protocol which, given the replacement of rosiglitazone by a food-compatible PPARγ agonist, is suitable for making cultivated fat

A simplified and defined serum-free medium for cultivating fat across species

Summary: Cultivated meat is a promising technology with the potential to mitigate the ethical and environmental issues associated with traditional meat. Fat plays a key role in the meat flavor; therefore, development of suitable adipogenic protocols for livestock is essential. The traditional adipogenic cocktail containing IBMX, dexamethasone, insulin and rosiglitazone is not food-compatible. Here, we demonstrate that of the four inducers only insulin and rosiglitazone are necessary in both serum-free (DMAD) and serum-containing media, with DMAD outperforming FBS. Two glucocorticoid receptor activators, progesterone and hydrocortisone, found in DMAD and FBS, affect differentiation homogeneity, without playing an essential role in activating adipogenic genes. Importantly, this protocol leads to mature adipocytes in 3D culture. This was demonstrated in both media types and in four species: ruminant and monogastric. We therefore propose a simplified one-step adipogenic protocol which, given the replacement of rosiglitazone by a food-compatible PPARγ agonist, is suitable for making cultivated fat