A High-Throughput Screen for Transcription Activation Domains Reveals Their Sequence Features and Permits Prediction by Deep Learning

Erijman, Ariel; Kozłowski, Łukasz P.; Sohrabi-Jahromi, Salma; Fishburn, James; Warfield, Linda; Schreiber, Jacob; Noble, William Stafford; Söding, Johannes; Hahn, Steven

doi:10.1016/j.molcel.2020.04.020

Cited by 89 publications

(170 citation statements)

References 83 publications

(134 reference statements)

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“…The Acidic Exposure Model extends from yeast to human cells with one elaboration: a larger role for leucine residues in human cells. In yeast, we focused on the central AD of Gcn4, where aromatic residues made large contributions to activity while leucine and methionine made smaller contributions (Erijman et al, 2020; Jackson et al, 1996; Ravarani et al, 2018; Staller et al, 2018). In human cells, we found three pieces of evidence that leucine residues make large contributions to AD activity.…”

Section: Resultsmentioning

confidence: 99%

“…Developing analogous high throughput methods for studying ADs will help close the understanding gap with DBDs. We and others have recently developed high-throughput methods for studying ADs in yeast, fly cells and human cells (Arnold et al, 2018; Erijman et al, 2020; Ravarani et al, 2018; Staller et al, 2018; Tycko et al, 2020). Building upon our work in yeast, here, we present a high-throughput method for studying AD variants in human cell culture.…”

Section: Introductionmentioning

confidence: 99%

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Design principles of acidic transcriptional activation domains

Staller

Ramirez

Holehouse

et al. 2020

Preprint

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Transcription factors activate gene expression with separable DNA binding domains and activation domains (Latchman, 2008). High-throughput studies have uncovered rules for how DNA binding domains recognize their cognate DNA motifs, but the design principles of activation domains remain opaque. For over thirty years it has been a mystery why activation domains are acidic and unstructured (Sigler, 1988). Activation domains require hydrophobic motifs to bind coactivators and join transcriptional condensates, but low evolutionary conservation and intrinsic disorder have made it difficult to identify the design principles that govern the sequence to function relationship (Boija et al., 2018; Chong et al., 2018; Cress and Triezenberg, 1991; Dyson and Wright, 2016). Consequently, activation domains cannot be predicted from amino acid sequence (Finn et al., 2016). Here, we resolve the functional roles of acidity and disorder in activation domains and use these insights to build a new predictor. We designed sequence variants in seven acidic activation domains and measured their activities in parallel with a high-throughput assay in human cell culture. Our results support a flexible model in which acidic residues solubilize hydrophobic motifs so that they can interact with coactivators. This model accurately predicts activation domains in the human proteome. We identify three general rules for activation domain function: hydrophobic motifs must be balanced by acidic residues; acidic residues make large contributions to activity when they are adjacent to motifs; and within motifs, the presence of aromatic or leucine residues reflects the structural constraints of coactivator interactions. We anticipate these design principles will aid efforts to predict activations from amino acid sequence and to engineer new domains.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design principles of acidic transcriptional activation domains

Staller

Ramirez

Holehouse

et al. 2020

Preprint

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“…It expands the catalog of functional transcriptional effector domains but is certainly still incomplete. We envision new library designs that tile transcription factors or focus on regions with activator-like signatures will identify additional human activator domains, as such designs have uncovered activators in yeast and Drosophila experiments (Arnold et al, 2018;Erijman et al, 2020;Ravarani et al, 2018). Without major modifications, HTrecruit should be compatible with any cell type that is transfectable (to integrate the reporter) and transducible by lentivirus (to deliver the library).…”

Section: High-throughput Protein Domain Functional Screens In Human Cmentioning

confidence: 99%

“…The recruitment assay has been applied extensively to characterize individual proteins and some fusions of multiple effectors (Amabile et al, 2016;Konermann et al, 2014), but the throughput of this assay is limited because each effector protein is individually cloned, delivered into cells, and measured. Recently, systematic recruitment of hundreds of chromatin regulators was achieved in yeast in an arrayed screen (Keung et al, 2014), and, in the last few years, pooled strategies for recruitment assays of activator domains were fruitfully implemented in yeast (Erijman et al, 2020;Staller et al, 2018) and Drosophila cells (Arnold et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

High-throughput discovery and characterization of human transcriptional effectors

Tycko¹,

DelRosso²,

Hess³

et al. 2020

Preprint

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SummaryThousands of proteins localize to the nucleus; however, it remains unclear which contain transcriptional effectors. Here, we develop HT-recruit - a pooled assay where protein libraries are recruited to a reporter, and their transcriptional effects are measured by sequencing. Using this approach, we measure gene silencing and activation for thousands of domains. We find a relationship between repressor function and evolutionary age for the KRAB domains, discover Homeodomain repressor strength is collinear with Hox genetic organization, and identify activities for several Domains of Unknown Function. Deep mutational scanning of the CRISPRi KRAB maps the co-repressor binding surface and identifies substitutions that improve stability/silencing. By tiling 238 proteins, we find repressors as short as 10 amino acids. Finally, we report new activator domains, including a divergent KRAB. Together, these results provide a resource of 600 human proteins containing effectors and demonstrate a scalable strategy for assigning functions to protein domains.

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“…Recent evidence hints at how this may be achieved. Mediator subunits in its tail sub-module have been shown to engage in a high number of low specificity and weak interactions via phase separation, thereby achieving a “fuzzy” interaction between Mediator and the activation domains of many different transcription factors [ [24] , [25] , [26] , [27] ]. The second arm of the Mediator bridge extends to interact with the pre-initiation complex, inducing the recruitment of RNA Pol II at target promoters [ 20 ] ( Fig.…”

Section: Mediator: a Bridge Between Enhancers And Promotersmentioning

confidence: 99%

Manipulating the Mediator complex to induce naïve pluripotency

Lynch

Bernad

Calvo

et al. 2020

Experimental Cell Research

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Human naïve pluripotent stem cells (PSCs) represent an optimal homogenous starting point for molecular interventions and differentiation strategies. This is in contrast to the standard primed PSCs which fluctuate in identity and are transcriptionally heterogeneous. However, despite many efforts, the maintenance and expansion of human naïve PSCs remains a challenge. Here, we discuss our recent strategy for the stabilization of human PSC in the naïve state based on the use of a single chemical inhibitor of the related kinases CDK8 and CDK19. These kinases phosphorylate and negatively regulate the multiprotein Mediator complex, which is critical for enhancer-driven recruitment of RNA Pol II. The net effect of CDK8/19 inhibition is a global stimulation of enhancers, which in turn reinforces transcriptional programs including those related to cellular identity. In the case of pluripotent cells, the presence of CDK8/19i efficiently stabilizes the naïve state. Importantly, in contrast to previous chemical methods to induced the naïve state based on the inhibition of the FGF-MEK-ERK pathway, CDK8/19i-naïve human PSCs are chromosomally stable and retain developmental potential after long-term expansion. We suggest this could be related to the fact that CDK8/19 inhibition does not induce DNA demethylation. These principles may apply to other fate decisions.

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A High-Throughput Screen for Transcription Activation Domains Reveals Their Sequence Features and Permits Prediction by Deep Learning

Cited by 89 publications

References 83 publications

Design principles of acidic transcriptional activation domains

Design principles of acidic transcriptional activation domains

High-throughput discovery and characterization of human transcriptional effectors

Manipulating the Mediator complex to induce naïve pluripotency

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