Mediator Subunit Med15 Dictates the Conserved “Fuzzy” Binding Mechanism of Yeast Transcription Activators Gal4 and Gcn4
This week, we profile a recent publication in Nature Communications from Steven Hahn (pictured, third from left),
Derek Pacheco (far left), and Linda Warfield (second from right) at Fred Hutch.
Can you provide a brief overview of your lab’s current research focus?
The focus of my lab is on mechanisms of transcriptional regulation. We use the yeast S. cerevisiae as our model system to investigate (i) the general protein machinery used for mRNA synthesis (RNA polymerase II and the general transcription factors), (ii) transcription factors, termed transcription activators, that upregulate transcription in response to various signaling pathways, and (iii) transcription coactivators – molecules that interact with transcription activators and then modulate transcription output by interaction with the general Pol II transcription machinery and/or modify chromatin. We are trying to understand how these three sets of factors work together to generate complex patterns of gene expression. Although we work on yeast, almost all these factors are conserved in eukaryotes, from yeasts to humans.
What is the significance of the findings in this publication?
This work is part of a longstanding collaboration between my lab and Rachel Klevit’s lab where we are investigating how transcription activators interact with one particular coactivator termed Mediator. Mediator is a conserved coactivator and a common activator target that is critical for nearly all mRNA transcription. Early work by others demonstrated that the transcription activators have very unusual properties such as intrinsic disorder (no stable 3D structure), unusual amino acid sequence composition, and no conserved amino acid sequence motifs. For example, comparing the sequence of one activator with another usually shows no sequence homology. Despite these properties, many activators of different sequences converge in cells to bind a small number of common coactivator targets. One of the important goals of the project is to understand the molecular mechanism of how the activators recognize and bind to the coactivators. Another more general objective is to understand how intrinsically disordered proteins interact with their binding partners.
Our two labs started collaborating in 2009 and have made many advances on these topics over the years. It’s been great collaborating with Rachel and her group because of their expertise in NMR and in the dynamic behavior of proteins and how they interact. This approach has been very important for this project because of the unusual mechanism of how the activators interact with the coactivators – by what Research Scientist Lisa Tuttle termed a “fuzzy free for all mechanism” (PMID: 29562181). This is very unlike what you might have learned in biochemistry class – where proteins specifically bind each other like a key in a lock. In the fuzzy binding mechanism, the activator peptide is rapidly binding and dissociating from the coactivator with many possible modes of interaction – in other words, there is no unique protein-protein interface.
Our earlier work showed that this mechanism holds for the well-studied activator named Gcn4. In this paper, we expanded our study to another well characterized activator Gal4. Gcn4 and Gal4 both have the ability to activate cellular transcription, yet very different primary amino acid sequences. One of the important objectives of the new work was to see if the fuzzy binding mechanism holds for activators of completely different sequences. As we predicted, Lisa Tuttle showed by NMR that the fuzzy mechanism holds for both Gal4 and Gcn4. Our findings show an amino acid sequence-independent mechanism for an activator-Mediator binding that is driven by hydrophobic amino acids within both the activator and the coactivator. This has important implications for how other activators and coactivators interact. Our work also showed another important principle – that the binding behavior of the activator is dependent on the target protein. Gal4 was already known to bind a repressor protein termed Gal80 using a conventional sequence-specific stable binding mechanism. A conclusion of our new work is that Gal4 can bind either by a conventional or a fuzzy mechanism and this binding mode is dictated by the protein target. All this work over the past decade was done by a fantastic team in Rachel’s lab and my lab that included: Lisa Tuttle, Derek Pacheco, Linda Warfield, and Peter Brzovic.
This biochemical work fits very nicely with our recent computational work where we selected a large number of functional activators from randomized sequences and developed a deep learning approach to predict activator function and to identify sequence features that specify what are termed “acidic” activators (Erijman et al 2020; PMID: 32416068). The sequence features we identified (clusters of hydrophobic residues in a generally acidic polypeptide) agree precisely with the NMR work showing dynamic sequence-independent interactions of the activators and coactivator.
What are the next steps for this research?
Our next step is to look for other types of activators that may work by different mechanisms and/or have different coactivator targets. Our computational work as well as other results in the field have suggested that there are other activator types but most of them have not been characterized. We are using a combination of experimental and computational approaches to identify these new types of activators and will then explore how their mechanisms are similar or different from the acidic activators.
This work was funded by:
The primary funding source has been NIH RO1 GM075114.