Dataset Information

A directed evolution design of a GCG-specific DNA hemimethylase.

ABSTRACT: DNA cytosine-5 methyltransferases (C5-MTases) are valuable models to study sequence-specific modification of DNA and are becoming increasingly important tools for biotechnology. Here we describe a structure-guided rational protein design combined with random mutagenesis and selection to change the specificity of the HhaI C5-MTase from GCGC to GCG. The specificity change was brought about by a five-residue deletion and introduction of two arginine residues within and nearby one of the target recognizing loops. DNA protection assays, bisulfite sequencing and enzyme kinetics showed that the best selected variant is comparable to wild-type M.HhaI in terms of sequence fidelity and methylation efficiency, and supersedes the parent enzyme in transalkylation of DNA using synthetic cofactor analogs. The designed C5-MTase can be used to produce hemimethylated CpG sites in DNA, which are valuable substrates for studies of mammalian maintenance MTases.

SUBMITTER: Gerasimaite R

PROVIDER: S-EPMC2790894 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature

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A directed evolution design of a GCG-specific DNA hemimethylase.

Gerasimaite Ruta R Vilkaitis Giedrius G Klimasauskas Saulius S

Nucleic acids research 20091101 21

DNA cytosine-5 methyltransferases (C5-MTases) are valuable models to study sequence-specific modification of DNA and are becoming increasingly important tools for biotechnology. Here we describe a structure-guided rational protein design combined with random mutagenesis and selection to change the specificity of the HhaI C5-MTase from GCGC to GCG. The specificity change was brought about by a five-residue deletion and introduction of two arginine residues within and nearby one of the target reco ...[more]

PMID: 19783820

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Project description:Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes. A single enhancer, of a few hundred base pairs in length, can autonomously and independently of its location and orientation drive cell-type specific expression of a gene or transgene. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Recently, deep learning models have yielded unprecedented insight into the enhancer code, and well-trained models are reaching a level of understanding that may be close to complete. As a consequence, we hypothesized that deep learning models can be used to guide the directed design of synthetic, cell type specific enhancers, and that this process would allow for a detailed tracing of all enhancer features at nucleotide-level resolution. Here we implemented and compared three different design strategies, each built on a deep learning model: (1) directed sequence evolution; (2) directed iterative motif implanting; and (3) generative design. We evaluated the function of fully synthetic enhancers to specifically target Kenyon cells or glial cells in the fruit fly brain using transgenic animals. We then exploited this concept further by creating “dual-code” enhancers that target two cell types, and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the trajectories followed during state space searches towards functional enhancers, we could accurately define the enhancer code as the optimal strength, combination, and relative distance of TF activator motifs, and the absence of TF repressor motifs. Finally, we applied the same three strategies to successfully design human enhancers, finding highly similar design principles as in Drosophila. In conclusion, enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.

Dataset Information

A directed evolution design of a GCG-specific DNA hemimethylase.

Publications

A directed evolution design of a GCG-specific DNA hemimethylase.

Similar Datasets

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