ACIDES: on-line monitoring of forward genetic screens for protein engineering

Takahiro Nemoto (), Tommaso Ocari, Arthur Planul, Muge Tekinsoy, Emilia A. Zin, Deniz Dalkara () and Ulisse Ferrari ()
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Takahiro Nemoto: Sorbonne Université, INSERM, CNRS
Tommaso Ocari: Sorbonne Université, INSERM, CNRS
Arthur Planul: Sorbonne Université, INSERM, CNRS
Muge Tekinsoy: Sorbonne Université, INSERM, CNRS
Emilia A. Zin: Sorbonne Université, INSERM, CNRS
Deniz Dalkara: Sorbonne Université, INSERM, CNRS
Ulisse Ferrari: Sorbonne Université, INSERM, CNRS

Nature Communications, 2023, vol. 14, issue 1, 1-11

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41467-023-43967-9

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