Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning
A long-standing goal in protein science and clinical genetics is to develop quantitative models of sequence, structure, and function relationships to understand how mutations cause disease. Deep mutational scanning (DMS) is a promising strategy to map how amino acids contribute to protein structure...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2022-05-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/76903 |
| _version_ | 1811252423162855424 |
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| author | Willow Coyote-Maestas David Nedrud Yungui He Daniel Schmidt |
| author_facet | Willow Coyote-Maestas David Nedrud Yungui He Daniel Schmidt |
| author_sort | Willow Coyote-Maestas |
| collection | DOAJ |
| description | A long-standing goal in protein science and clinical genetics is to develop quantitative models of sequence, structure, and function relationships to understand how mutations cause disease. Deep mutational scanning (DMS) is a promising strategy to map how amino acids contribute to protein structure and function and to advance clinical variant interpretation. Here, we introduce 7429 single-residue missense mutations into the inward rectifier K+ channel Kir2.1 and determine how this affects folding, assembly, and trafficking, as well as regulation by allosteric ligands and ion conduction. Our data provide high-resolution information on a cotranslationally folded biogenic unit, trafficking and quality control signals, and segregated roles of different structural elements in fold stability and function. We show that Kir2.1 surface trafficking mutants are underrepresented in variant effect databases, which has implications for clinical practice. By comparing fitness scores with expert-reviewed variant effects, we can predict the pathogenicity of ‘variants of unknown significance’ and disease mechanisms of known pathogenic mutations. Our study in Kir2.1 provides a blueprint for how multiparametric DMS can help us understand the mechanistic basis of genetic disorders and the structure–function relationships of proteins. |
| first_indexed | 2024-04-12T16:34:21Z |
| format | Article |
| id | doaj.art-15c4d948595e4756b6a890ffb7da5841 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T16:34:21Z |
| publishDate | 2022-05-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-15c4d948595e4756b6a890ffb7da58412022-12-22T03:25:02ZengeLife Sciences Publications LtdeLife2050-084X2022-05-011110.7554/eLife.76903Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanningWillow Coyote-Maestas0https://orcid.org/0000-0001-9614-5340David Nedrud1Yungui He2Daniel Schmidt3https://orcid.org/0000-0001-7609-4873Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United StatesDepartment of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United StatesDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, United StatesDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, United StatesA long-standing goal in protein science and clinical genetics is to develop quantitative models of sequence, structure, and function relationships to understand how mutations cause disease. Deep mutational scanning (DMS) is a promising strategy to map how amino acids contribute to protein structure and function and to advance clinical variant interpretation. Here, we introduce 7429 single-residue missense mutations into the inward rectifier K+ channel Kir2.1 and determine how this affects folding, assembly, and trafficking, as well as regulation by allosteric ligands and ion conduction. Our data provide high-resolution information on a cotranslationally folded biogenic unit, trafficking and quality control signals, and segregated roles of different structural elements in fold stability and function. We show that Kir2.1 surface trafficking mutants are underrepresented in variant effect databases, which has implications for clinical practice. By comparing fitness scores with expert-reviewed variant effects, we can predict the pathogenicity of ‘variants of unknown significance’ and disease mechanisms of known pathogenic mutations. Our study in Kir2.1 provides a blueprint for how multiparametric DMS can help us understand the mechanistic basis of genetic disorders and the structure–function relationships of proteins.https://elifesciences.org/articles/76903deep mutational scanningion channelfoldinggatinghigh-throughputvariant effect prediction |
| spellingShingle | Willow Coyote-Maestas David Nedrud Yungui He Daniel Schmidt Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning eLife deep mutational scanning ion channel folding gating high-throughput variant effect prediction |
| title | Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning |
| title_full | Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning |
| title_fullStr | Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning |
| title_full_unstemmed | Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning |
| title_short | Determinants of trafficking, conduction, and disease within a K+ channel revealed through multiparametric deep mutational scanning |
| title_sort | determinants of trafficking conduction and disease within a k channel revealed through multiparametric deep mutational scanning |
| topic | deep mutational scanning ion channel folding gating high-throughput variant effect prediction |
| url | https://elifesciences.org/articles/76903 |
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