Exploring the genetic architecture of ecophysiological traits in microbial ecology using statistical analysis of the properties of protein sequences: application to the glycogen accumulating organism (GAO) phenotype
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Abstract
Nearly 50 years ago, King and Wilson introduced a key distinction between two types of genetic variation–named structural and regulatory variation–for exploring the molecular basis for phenotypic traits. Structural variation is genetic variation that will influence gene product structure via changes in coding sequence, whereas regulatory variation will influence the control of gene product expression. Here we repurpose these concepts to study the molecular basis of eco-physiological traits observed in microbial ecology, focusing on a specialized glycogen accumulating phenotype, known to be exhibited by a phylogenetically diverse group of microbes. We analyse the statistical properties of the protein sequence of the 1,4– α –glucan branching enzyme ( glgB ), a key enzyme responsible for formation of glycogen from linear glucans. We show that the glgB proteins in a subgroup of these organisms show unusual statistical properties of protein sequence length, sequence similarity and patterning of functional domains, compared to organisms that do not exhibit this phenotype. These findings suggest a role for structural genetic variation in determining this phenotype in some species. Our analysis holds implications for dissecting the genetic/genomic architecture of complex traits exhibited by microbial communities and also provides a complementary framework to presence–absence level analyses that are ubiquitous in microbial ecology.
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Collectively, our analysis supports the view that some GAO species harbour unusual structural variants of the glgB enzyme:
Could you use a tool like Foldseek to compare the structural similarity of these proteins further: https://search.foldseek.com/search? Or take these input proteins and either fetch the PDB files or fold with Alphafold/ESMfold and cast a wider net of comparisons beyond AS organisms? The ProteinCartography workflow could help with these additional analyses and insights: https://research.arcadiascience.com/pub/resource-protein-cartography/release/6 and github repo: https://github.com/Arcadia-Science/ProteinCartography
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connected in a clique
Maybe cluster is the better term here?
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Figure 1:
Not sure if you can modify the preprint submission to rotate this figure?
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Or in other words, is the GAO phenotype largely driven by superior metabolic capacity of the component proteins in glycogen storage pathways (the structural hypothesis) or is it a consequence of optimal regulation of those pathways in the specific environments where the phenotype is observed? (the regulatory hypothesis).
This is also a really interesting way to frame this question - my gut instinct says it's probably some combination of both the genetic/structural variation and regulatory mechanisms. Creating approaches/frameworks to combine all this information together for traits of interest will be really crucial!!
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a logical question to ask is whether the glycogen storage machinery of GAO species exhibit unusual or enhanced metabolic properties compared to those found in non-GAO species?
This is such a fascinating question, and very similar to the question we posed in related to polyphosphate accumulation: https://research.arcadiascience.com/pub/result-ppk1-homology/release/1. It's exciting to see other groups thinking about protein structural similarity and traits in this way!
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McDaniel and colleagues
Very small note - Joris van Steenbrugge and I were co-first authors so the way I refer to this is "McDaniel and van Steenbrugge and colleagues..." to give the correct credit here, even if it makes the sentence a bit longer
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statistical properties
Describing this as "statistical properties" is possibly confusing, I think I know what you mean is that this is a comparative approach of protein features connected to trait information, but possibly a better way of explaining this
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