Mutational Scanning: Ion-ing out the genetic variants of Kir2.1

Deep mutational scanning provides new insights into how mutations alter the expression and activity of the potassium ion channel Kir2.1, which is associated with many diseases.
  1. Braden S Fallon
  2. Justin G English  Is a corresponding author
  1. Department of Biochemistry, University of Utah, United States

Every time a cell in your body divides, it copies the three billion letter message stored in its DNA. This process is prone to errors and can accidentally introduce mistakes into the genetic code. To counteract this, human cells proofread the copied DNA sequence and correct any inaccuracies (Kunkel, 2004). But typos sometimes fly under the radar, leading to mutations that can alter the overall meaning of the message encoded within the cell’s DNA.

Clinicians can rapidly and easily identify these errors using high-throughput DNA sequencing techniques. However, determining how individual mutations affect the message within DNA is more challenging. This is because some mutations will not change a gene’s activity, while others may substantially impact the function of the protein it encodes, potentially resulting in disease. Traditionally, the best way to study the impact of a mutation was to perform functional studies: researchers made a single mutation, tested it in different types of laboratory experiments, and reported the effect (Jackson et al., 2018). More recently, large-scale analysis techniques that can measure the consequences of all potential mutations in a specific gene have grown in popularity. These approaches (called deep mutational scanning, or DMS for short) allow researchers to make every typo the cell could make in a gene and determine the impact of all such errors in parallel (Fowler et al., 2010).

While DMS has been applied to several genes, these studies have typically only measured a singular output, such as how mutations impact a specific cell behavior or alter the protein encoded within the gene (Jones et al., 2020; Majithia et al., 2016; Starr et al., 2020). Now, in eLife, Willow Coyote-Maestas, David Nedrud, Yungui He and Daniel Schmidt report how they used DMS to characterize how mutations in the gene coding for an ion channel called Kir2.1 impact the function of this protein and its expression simultaneously (Coyote-Maestas et al., 2022).

Kir2.1 belongs to a family of proteins called inward-rectifying potassium channels (Kirs for short) that are studded throughout the cell surface and help stabilize the membrane potential of cells. Mutations in the genes encoding the Kir channels have been linked with various diseases, including diabetes, heart dysfunction, seizures and paralysis (Zangerl-Plessl et al., 2019). However, only a small number of mutations in Kir2.1 have been clinically reported, and how they affect the behavior of the channel is poorly understood.

Coyote-Maestas et al. therefore set out to employ DMS on the Kir2.1 channel, making this the largest disease-associated complex that DMS has ever been applied to. The team (who are based at the University of Minnesota) used this approach to introduce genetic mutations that altered the sequence of amino acids within Kir2.1. Each building block was swapped with every other possible amino acid to create a library of mutants that were then individually inserted into cells grown in the laboratory. To examine how many Kir2.1 channels were expressed at the cell surface, a marker that can be fluorescently labeled was inserted into the genetic sequence of the channel. For changes in functionality, a dye was used that measures membrane potential (Figure 1).

Schematic showing how deep mutational scanning was applied to Kir2.1.

Mutants of the potassium channel Kir2.1 were generated by modifying its DNA sequence so that every amino acid in the protein was swapped for every other possible amino acid. These genetic variants were then integrated and expressed in human cells (called HEK293T) grown in the laboratory. Further experiments were then carried out to determine whether the mutations altered the number of channels expressed on the cell surface, and/or the function of Kir2.1. Mutants were then categorized based on how they impacted the behavior of Kir2.1 and the results were compared to a clinical dataset (called ClinVar) containing mutations found in patients. Genetic variants in the database with no assigned clinical significance were then evaluated and given a pathogenicity score indicating how likely the mutation is to cause disease based on the results from the DMS experiment.

Image credit: Braden Fallon; Figure created using BioRender.

The data revealed that mutations that decreased the expression of Kir2.1 resided in parts of the genome that are responsible for trafficking the channel to the cell surface, or for folding the protein into the right shape. Furthermore, mutations that impacted the formation of the pore in the protein (which allows potassium ions to pass through) were detrimental to the overall expression of Kir2.1. The data also identified segments of Kir2.1 that prevent faulty channels from reaching the cell surface, some of which had already been detected in previous studies (Li et al., 2016; Ma et al., 2011).

Next, Coyote-Maestas et al. investigated changes in the activity of the channel. Interestingly, they found a distinct divide between mutations that impact expression and those that affect functionality. Indeed, many of the mutations that altered how the channel works had no effect on surface expression. This includes a mutation that has been shown to cause Anderson Tawil Syndrome, which is characterized by developmental defects, paralysis, and heart abnormalities (Plaster et al., 2001).

Coyote-Maestas et al. then compared their results to clinical datasets containing mutations in Kir2.1 that had been observed in patients (Figure 1). Each clinically reported mutation was compared to an identical mutation obtained by the group. If the expression or function of the DMS generated mutation was higher or lower than variants which are known to be benign, it was classified as being potentially pathogenic. This allowed Coyote-Maestas et al. to predict whether variants that have not yet been clinically observed are likely to cause disease, and determine how mutations with unclear or uncertain clinical effects may impact the function and expression of Kir2.1.

The comparison also revealed that most clinically reported mutations were associated with the protein’s function rather than its ability to successfully reach and embed itself into the cell surface. As Kir2.1 is needed for many aspects of physiology, mutations that significantly impact its expression are likely to be fatal (Zaritsky et al., 2001), which may be why these types of variants are less common in the general public.

Taken together, these findings suggest that DMS can provide various mutational insights. First, it can be used to predict the clinical significance of variants with previously unknown impacts. Second, it can be used to predict regions in DNA where mutations are more likely to occur and be clinically observed. Finally, this approach can predict how a mutation will impact a protein’s cellular role. However, while this study provides a significant breadth of new information, it is worth noting that only one experiment was performed to characterize the functional consequences of the mutations studied. Additional assays are needed, including in vivo studies, to validate the pathological effect of these genetic variants.

This work demonstrates how DMS can be used to study multiple parameters. Future DMS studies will benefit from mirroring this approach, and considering how mutations impact both expression and function simultaneously. The methodology established by Coyote-Maestas et al. can be broadly applied to other ion channels, and lays the groundworks for advancing DMS studies in many biochemical applications.

References

    1. Kunkel TA
    (2004) DNA replication fidelity
    The Journal of Biological Chemistry 279:16895–16898.
    https://doi.org/10.1074/jbc.R400006200

Article and author information

Author details

  1. Braden S Fallon

    Braden S Fallon is in the Department of Biochemistry, University of Utah, Salt Lake City, United States

    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8308-418X
  2. Justin G English

    Justin G English is in the Department of Biochemistry, University of Utah, Salt Lake City, United States

    For correspondence
    justin.english@biochem.utah.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1161-8928

Publication history

  1. Version of Record published: July 11, 2022 (version 1)

Copyright

© 2022, Fallon and English

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 355
    Page views
  • 86
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Braden S Fallon
  2. Justin G English
(2022)
Mutational Scanning: Ion-ing out the genetic variants of Kir2.1
eLife 11:e80718.
https://doi.org/10.7554/eLife.80718

Further reading

    1. Developmental Biology
    2. Genetics and Genomics
    Divya Khattar et al.
    Research Article

    The tips of the developing respiratory buds are home to important progenitor cells marked by the expression of SOX9 and ID2. Early in embryonic development (prior to E13.5), SOX9+ progenitors are multipotent, generating both airway and alveolar epithelium, but are selective progenitors of alveolar epithelial cells later in development. Transcription factors, including Sox9, Etv5, Irx, Mycn, and Foxp1/2 interact in complex gene regulatory networks to control proliferation and differentiation of SOX9+ progenitors. Molecular mechanisms by which these transcription factors and other signaling pathways control chromatin state to establish and maintain cell-type identity are not well-defined. Herein, we analyze paired gene expression (RNA-Seq) and chromatin accessibility (ATAC-Seq) data from SOX9+ epithelial progenitor cells (EPCs) during embryonic development in Mus musculus. Widespread changes in chromatin accessibility were observed between E11.5 and E16.5, particularly at distal cis-regulatory elements (e.g. enhancers). Gene regulatory network (GRN) inference identified a common SOX9+ progenitor GRN, implicating phosphoinositide 3-kinase (PI3K) signaling in the developmental regulation of SOX9+ progenitor cells. Consistent with this model, conditional ablation of PI3K signaling in the developing lung epithelium in mouse resulted in an expansion of the SOX9+ EPC population and impaired airway epithelial cell differentiation. These data demonstrate that PI3K signaling is required for epithelial patterning during lung organogenesis, and emphasize the combinatorial power of paired RNA and ATAC seq in defining regulatory networks in development.

    1. Developmental Biology
    2. Genetics and Genomics
    Ruhi Patel et al.
    Research Article

    Animal development requires coordination among cyclic processes, sequential cell fate specifications, and once-a-lifetime morphogenic events, but the underlying timing mechanisms are not well understood. Caenorhabditis elegans undergoes four molts at regular 8 to 10 hour intervals. The pace of the cycle is governed by PERIOD/lin-42 and other as-yet unknown factors. Cessation of the cycle in young adults is controlled by the let-7 family of microRNAs and downstream transcription factors in the heterochronic pathway. Here, we characterize a negative feedback loop between NHR-23, the worm homolog of mammalian retinoid-related orphan receptors (RORs), and the let-7 family of microRNAs that regulates both the frequency and finite number of molts. The molting cycle is decelerated in nhr-23 knockdowns and accelerated in let-7(−) mutants, but timed similarly in let-7(−) nhr-23(−) double mutants and wild-type animals. NHR-23 binds response elements (ROREs) in the let-7 promoter and activates transcription. In turn, let-7 dampens nhr-23 expression across development via a complementary let-7-binding site (LCS) in the nhr-23 3′ UTR. The molecular interactions between NHR-23 and let-7 hold true for other let-7 family microRNAs. Either derepression of nhr-23 transcripts by LCS deletion or high gene dosage of nhr-23 leads to protracted behavioral quiescence and extra molts in adults. NHR-23 and let-7 also coregulate scores of genes required for execution of the molts, including lin-42. In addition, ROREs and LCSs isolated from mammalian ROR and let-7 genes function in C. elegans, suggesting conservation of this feedback mechanism. We propose that this feedback loop unites the molting timer and the heterochronic gene regulatory network, possibly by functioning as a cycle counter.