Harvard Biophysics PhD candidate studying protein evolution with a focus on transporters in the Gaudet and Marks labs. Occasional fiction writer. Proud cat dad.
Sam Berry
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Transporters must use a limited set of structural scaffolds to accurately discriminate between arbitrary substrates, in the process undergoing major conformational change. Despite advances in machine learning, the "rules" by which transporter sequences encode these functions remain opaque.
Finally, I have to shout out everyone who made this possible, especially the endlessly patient @rachellegaudet.bsky.social but also my fearless mentee Camille and far more people than I can fit in this post who gave me neverending help and advice!
If you've read this kind of study before, some trends are obvious by now: mutations to the binding site tend to be deleterious, P/R/K are especially perturbative, the effects of many mutations when combined can be modeled as additive. But where it gets interesting is where those trends break down...
Why would this happen? At the end, we propose a simple model explaining why the same residues might influence both epistasis and specificity in terms of the energetic balance between the transporter's major conformations. Check out the paper and let me know what you think!
Second, we find only a small set of "core" mutations clustered around a key binding site methionine allow for Mg2+ import. However, many additional mutations can then finetune this specificity. What's more, these specificity modulator mutations correlate strongly with those epistatic hotspots (!)
We addressed this by developing new assays that allowed us to make thousands of different sequence changes to a model metal transporter and then quantify how those changes affect its import of a representative native metal substrate, Mn2+, as well as a non-transported ion, Mg2+.
To test more than single-mutant effects, we used structural and evolutionary information to guide the library toward combinations of mutations hypothesized to be more likely to alter specificity. This included a combinatorial library across 59 positions informed by natural sequence diversity:
First, even though many mutations combine additively, we see specific epistasis at non-contacting positions that clusters at epistatic hotspots around where the transporter protein opens and closes. We see much more of this than has been observed previously for folding or binding domains.
I'm excited to share our new preprint representing the bulk of my PhD work, along with @camillefreedman.bsky.social, @deboramarks.bsky.social and @rachellegaudet.bsky.social. How do transporter proteins control what molecules they bring across the membrane?
www.biorxiv.org/content/10.6...
