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Abstract
The dosage compensation complex (DCC) binds to single X chromosomes in
Drosophila males and increases the transcription level of X-linked genes by approximately twofold.
Male-specific lethal 2 (MSL2) together with MSL1 mediates the initial recruitment
of the DCC to high-affinity sites in the X chromosome. MSL2 contains a DNA-binding
cysteine-rich CXC domain that is important for X targeting. In this study, we determined
the solution structure of MSL2 CXC domain by NMR spectroscopy. We identified three
zinc ions in the CXC domain and determined the metal-to-cysteine connectivities from
1H-
113Cd correlation experiments. The structure reveals an unusual zinc-cysteine cluster
composed of three zinc ions coordinated by six terminal and three bridging cysteines.
The CXC domain exhibits unexpected structural homology to pre-SET motifs of histone
lysine methyltransferases, expanding the distribution and structural diversity of
the CXC domain superfamily. Our findings provide novel structural insight into the
evolution and function of CXC domains.
Combined automated NOE assignment and structure determination module (CANDID) is a new software for efficient NMR structure determination of proteins by automated assignment of the NOESY spectra. CANDID uses an iterative approach with multiple cycles of NOE cross-peak assignment and protein structure calculation using the fast DYANA torsion angle dynamics algorithm, so that the result from each CANDID cycle consists of exhaustive, possibly ambiguous NOE cross-peak assignments in all available spectra and a three-dimensional protein structure represented by a bundle of conformers. The input for the first CANDID cycle consists of the amino acid sequence, the chemical shift list from the sequence-specific resonance assignment, and listings of the cross-peak positions and volumes in one or several two, three or four-dimensional NOESY spectra. The input for the second and subsequent CANDID cycles contains the three-dimensional protein structure from the previous cycle, in addition to the complete input used for the first cycle. CANDID includes two new elements that make it robust with respect to the presence of artifacts in the input data, i.e. network-anchoring and constraint-combination, which have a key role in de novo protein structure determinations for the successful generation of the correct polypeptide fold by the first CANDID cycle. Network-anchoring makes use of the fact that any network of correct NOE cross-peak assignments forms a self-consistent set; the initial, chemical shift-based assignments for each individual NOE cross-peak are therefore weighted by the extent to which they can be embedded into the network formed by all other NOE cross-peak assignments. Constraint-combination reduces the deleterious impact of artifact NOE upper distance constraints in the input for a protein structure calculation by combining the assignments for two or several peaks into a single upper limit distance constraint, which lowers the probability that the presence of an artifact peak will influence the outcome of the structure calculation. CANDID test calculations were performed with NMR data sets of four proteins for which high-quality structures had previously been solved by interactive protocols, and they yielded comparable results to these reference structure determinations with regard to both the residual constraint violations, and the precision and accuracy of the atomic coordinates. The CANDID approach has further been validated by de novo NMR structure determinations of four additional proteins. The experience gained in these calculations shows that once nearly complete sequence-specific resonance assignments are available, the automated CANDID approach results in greatly enhanced efficiency of the NOESY spectral analysis. The fact that the correct fold is obtained in cycle 1 of a de novo structure calculation is the single most important advance achieved with CANDID, when compared with previously proposed automated NOESY assignment methods that do not use network-anchoring and constraint-combination.
The Drosophila MSL complex associates with active genes specifically on the male X chromosome to acetylate histone H4 at lysine 16 and increase expression approximately 2-fold. To date, no DNA sequence has been discovered to explain the specificity of MSL binding. We hypothesized that sequence-specific targeting occurs at "chromatin entry sites," but the majority of sites are sequence independent. Here we characterize 150 potential entry sites by ChIP-chip and ChIP-seq and discover a GA-rich MSL recognition element (MRE). The motif is only slightly enriched on the X chromosome ( approximately 2-fold), but this is doubled when considering its preferential location within or 3' to active genes (>4-fold enrichment). When inserted on an autosome, a newly identified site can direct local MSL spreading to flanking active genes. These results provide strong evidence for both sequence-dependent and -independent steps in MSL targeting of dosage compensation to the male X chromosome.
Dosage compensation is the crucial process that equalizes gene expression from the X chromosome between males (XY) and females (XX). In Drosophila, the male-specific lethal (MSL) ribonucleoprotein complex mediates dosage compensation by upregulating transcription from the single male X chromosome approximately twofold. A key challenge is to understand how the MSL complex distinguishes the X chromosome from autosomes. Recent studies suggest that this occurs through a multi-step targeting mechanism that involves DNA sequence elements and epigenetic marks associated with transcription. This review will discuss the relative contributions of sequence elements and transcriptional marks to the complete pattern of MSL complex binding.
Publisher:
Public Library of Science
(San Francisco, USA
)
ISSN
(Electronic):
1932-6203
Publication date Collection: 2012
Publication date
(Electronic):
20
September
2012
Volume: 7
Issue: 9
Electronic Location Identifier: e45437
Affiliations
[1
]Department of Biochemistry and Molecular Biology, College of Life Sciences, Beijing
Normal University, Beijing, China
[2
]National Institute of Biological Sciences, Beijing, China
[3
]Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy
and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shangdong, China
[4
]National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy
of Sciences, Beijing, China
George Washington University, United States of America
Competing Interests: The authors have declared that no competing interests exist.
Conceived and designed the experiments: YF JFW KY. Performed the experiments: SZ JW
YF. Analyzed the data: SZ JW YF KY. Wrote the paper: SZ YF KY.
Article
Publisher ID:
PONE-D-12-19431
DOI: 10.1371/journal.pone.0045437
PMC ID: 3447885
PubMed ID: 23029009
SO-VID: 3fbb3546-6007-4ea1-a42d-489e14c6e5ba
Copyright statement:
Copyright @
2012
License:
This is an open-access article distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction
in any medium, provided the original author and source are credited.
History
Date
received
: 5
July
2012
Date
accepted
: 17
August
2012
Page count
Pages: 13
Funding
K.Y. was supported by the National Basic Research Program of China (973 Program) (2010CB835402
and 2012CB910900) and Beijing Municipal Government. Y.F. was supported by the National
Natural Science Foundation of China (30970571). The funders had no role in study design,
data collection and analysis, decision to publish, or preparation of the manuscript.
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