Affordable Access

deepdyve-link
Publisher Website

Charting the signal trajectory in a light-oxygen-voltage photoreceptor by random mutagenesis and covariance analysis.

Authors
  • Gleichmann, Tobias
  • Diensthuber, Ralph P
  • Möglich, Andreas
Type
Published Article
Journal
Journal of Biological Chemistry
Publisher
American Society for Biochemistry and Molecular Biology
Publication Date
Oct 11, 2013
Volume
288
Issue
41
Pages
29345–29355
Identifiers
DOI: 10.1074/jbc.M113.506139
PMID: 24003219
Source
Medline
Keywords
License
Unknown

Abstract

Modular signal receptors empower organisms to process environmental stimuli into adequate physiological responses. At the molecular level, a sensor module receives signals and processes the inherent information into changes of biological activity of an effector module. To better understand the molecular bases underpinning these processes, we analyzed signal reception and processing in the dimeric light-oxygen-voltage (LOV) blue light receptor YF1 that serves as a paradigm for the widespread Per-ARNT-Sim (PAS) signal receptors. Random mutagenesis identifies numerous YF1 variants in which biological activity is retained but where light regulation is abolished or inverted. One group of variants carries mutations within the LOV photosensor that disrupt proper coupling of the flavin-nucleotide chromophore to the protein scaffold. Another larger group bears mutations that cluster at the dyad interface and disrupt signal transmission to two coaxial coiled-coils that connect to the effector. Sequence covariation implies wide conservation of structural and mechanistic motifs, as also borne out by comparison to several PAS domains in which mutations leading to disruption of signal transduction consistently map to confined regions broadly equivalent to those identified in YF1. Not only do these data provide insight into general mechanisms of signal transduction, but also they establish concrete means for customized reprogramming of signal receptors.

Report this publication

Statistics

Seen <100 times