ACIDES: on-line monitoring of forward genetic screens for protein engineering
Abstract Forward genetic screens of mutated variants are a versatile strategy for protein engineering and investigation, which has been successfully applied to various studies like directed evolution (DE) and deep mutational scanning (DMS). While next-generation sequencing can track millions of vari...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-12-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-43967-9 |
| _version_ | 1797371170005188608 |
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| author | Takahiro Nemoto Tommaso Ocari Arthur Planul Muge Tekinsoy Emilia A. Zin Deniz Dalkara Ulisse Ferrari |
| author_facet | Takahiro Nemoto Tommaso Ocari Arthur Planul Muge Tekinsoy Emilia A. Zin Deniz Dalkara Ulisse Ferrari |
| author_sort | Takahiro Nemoto |
| collection | DOAJ |
| description | Abstract Forward genetic screens of mutated variants are a versatile strategy for protein engineering and investigation, which has been successfully applied to various studies like directed evolution (DE) and deep mutational scanning (DMS). While next-generation sequencing can track millions of variants during the screening rounds, the vast and noisy nature of the sequencing data impedes the estimation of the performance of individual variants. Here, we propose ACIDES that combines statistical inference and in-silico simulations to improve performance estimation in the library selection process by attributing accurate statistical scores to individual variants. We tested ACIDES first on a random-peptide-insertion experiment and then on multiple public datasets from DE and DMS studies. ACIDES allows experimentalists to reliably estimate variant performance on the fly and can aid protein engineering and research pipelines in a range of applications, including gene therapy. |
| first_indexed | 2024-03-08T18:15:58Z |
| format | Article |
| id | doaj.art-ca14d5d691344b0d9cf2055c415a56e5 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-08T18:15:58Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-ca14d5d691344b0d9cf2055c415a56e52023-12-31T12:11:33ZengNature PortfolioNature Communications2041-17232023-12-0114111110.1038/s41467-023-43967-9ACIDES: on-line monitoring of forward genetic screens for protein engineeringTakahiro Nemoto0Tommaso Ocari1Arthur Planul2Muge Tekinsoy3Emilia A. Zin4Deniz Dalkara5Ulisse Ferrari6Institut de la Vision, Sorbonne Université, INSERM, CNRSInstitut de la Vision, Sorbonne Université, INSERM, CNRSInstitut de la Vision, Sorbonne Université, INSERM, CNRSInstitut de la Vision, Sorbonne Université, INSERM, CNRSInstitut de la Vision, Sorbonne Université, INSERM, CNRSInstitut de la Vision, Sorbonne Université, INSERM, CNRSInstitut de la Vision, Sorbonne Université, INSERM, CNRSAbstract Forward genetic screens of mutated variants are a versatile strategy for protein engineering and investigation, which has been successfully applied to various studies like directed evolution (DE) and deep mutational scanning (DMS). While next-generation sequencing can track millions of variants during the screening rounds, the vast and noisy nature of the sequencing data impedes the estimation of the performance of individual variants. Here, we propose ACIDES that combines statistical inference and in-silico simulations to improve performance estimation in the library selection process by attributing accurate statistical scores to individual variants. We tested ACIDES first on a random-peptide-insertion experiment and then on multiple public datasets from DE and DMS studies. ACIDES allows experimentalists to reliably estimate variant performance on the fly and can aid protein engineering and research pipelines in a range of applications, including gene therapy.https://doi.org/10.1038/s41467-023-43967-9 |
| spellingShingle | Takahiro Nemoto Tommaso Ocari Arthur Planul Muge Tekinsoy Emilia A. Zin Deniz Dalkara Ulisse Ferrari ACIDES: on-line monitoring of forward genetic screens for protein engineering Nature Communications |
| title | ACIDES: on-line monitoring of forward genetic screens for protein engineering |
| title_full | ACIDES: on-line monitoring of forward genetic screens for protein engineering |
| title_fullStr | ACIDES: on-line monitoring of forward genetic screens for protein engineering |
| title_full_unstemmed | ACIDES: on-line monitoring of forward genetic screens for protein engineering |
| title_short | ACIDES: on-line monitoring of forward genetic screens for protein engineering |
| title_sort | acides on line monitoring of forward genetic screens for protein engineering |
| url | https://doi.org/10.1038/s41467-023-43967-9 |
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