Creating De Novo Overlapped Genes.
Deep learning
Generative model
Genome compression
Machine learning
Markov random field
Multiple sequence alignments
Overlapping genes
Protein design
Synthetic biology
Synthetic genomes
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2023
2023
Historique:
entrez:
13
10
2022
pubmed:
14
10
2022
medline:
18
10
2022
Statut:
ppublish
Résumé
Future applications of synthetic biology will rely on deploying engineered cells outside of lab environments for long periods of time. Currently, a significant roadblock to this application is the potential for deactivating mutations in engineered genes. A recently developed method to protect engineered coding sequences from mutation is called Constraining Adaptive Mutations using Engineered Overlapping Sequences (CAMEOS). In this chapter we provide a workflow for utilizing CAMEOS to create synthetic overlaps between two genes, one essential (infA) and one non-essential (aroB), to protect the non-essential gene from mutation and loss of protein function. In this workflow we detail the methods to collect large numbers of related protein sequences, produce multiple sequence alignments (MSAs), use the MSAs to generate hidden Markov models and Markov random field models, and finally generate a library of overlapping coding sequences through CAMEOS scripts. To assist practitioners with basic coding skills to try out the CAMEOS method, we have created a virtual machine containing all the required packages already installed that can be downloaded and run locally.
Identifiants
pubmed: 36227541
doi: 10.1007/978-1-0716-2617-7_6
doi:
Substances chimiques
Proteins
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
95-120Informations de copyright
© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
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