Evidence map›Paper›PMID 22492712›Full record

ArticleNucleic acids research2012

Combinatorial targeting of ribbon-helix-helix artificial transcription factors to chimeric recognition sites.

Massimiliano Zampini, Finbarr Hayes

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Massimiliano ZampiniFaculty of Life Sciences and Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.
Finbarr Hayes
University of Manchester · GB

Funding

Biotechnology and Biological Sciences Research Council BB/G003114/1
6 · The paper itself

Abstract

Artificial transcription factors (ATFs) are potent synthetic biology tools for modulating endogenous gene expression and precision genome editing. The ribbon-helix-helix (RHH) superfamily of transcription factors are widespread in bacteria and archaea. The principal DNA binding determinant in this family comprises a two-stranded antiparallel β-sheet (ribbons) in which a pair of eight-residue motifs insert into the major groove. Here, we demonstrate that ribbons of divergent RHH proteins are compact and portable elements that can be grafted into a common α-helical scaffold producing active ATFs. Hybrid proteins cooperatively recognize DNA sites possessing core tetramer boxes whose functional spacing is dictated by interactions between the α-helical backbones. These interactions also promote combinatorial binding of chimeras with different transplanted ribbons, but identical backbones, to synthetic sites bearing cognate boxes for each protein either in vitro or in vivo. The composite assembly of interacting hybrid proteins offers potential advantages associated with combinatorial approaches to DNA recognition compared with ATFs that involve binding of a single protein. Moreover, the new class of RHH ATFs may be utilized to re-engineer transcriptional circuits, or may be enhanced with affinity tags, fluorescent moieties or other elements for targeted genome marking and manipulation in bacteria and archaea.

Indexed as

Binding SitesDatabases, ProteinDNAProtein EngineeringProtein Structure, SecondaryRepressor ProteinsTranscription FactorsDNARepressor ProteinsTranscription Factors

Identifiers

PMID22492712
PMCPMC3413123
OpenAlexW2044073402

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.