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Structural disorder in eukaryotes.

ABSTRACT: Based on early bioinformatic studies on a handful of species, the frequency of structural disorder of proteins is generally thought to be much higher in eukaryotes than in prokaryotes. To refine this view, we present here a comparative prediction study and analysis of 194 fully described eukaryotic proteomes and 87 reference prokaryotes for structural disorder. We found that structural disorder does distinguish eukaryotes from prokaryotes, but its frequency spans a very wide range in the two superkingdoms that largely overlap. The number of disordered binding regions and different Pfam domain types also contribute to distinguish eukaryotes from prokaryotes. Unexpectedly, the highest levels--and highest variability--of predicted disorder is found in protists, i.e. single-celled eukaryotes, often surpassing more complex eukaryote organisms, plants and animals. This trend contrasts with that of the number of domain types, which increases rather monotonously toward more complex organisms. The level of structural disorder appears to be strongly correlated with lifestyle, because some obligate intracellular parasites and endosymbionts have the lowest levels, whereas host-changing parasites have the highest level of predicted disorder. We conclude that protists have been the evolutionary hot-bed of experimentation with structural disorder, in a period when structural disorder was actively invented and the major functional classes of disordered proteins established.

SUBMITTER: Pancsa R

PROVIDER: S-EPMC3320622 | biostudies-other | 2012

REPOSITORIES: biostudies-other

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Structural disorder in eukaryotes.

Pancsa Rita R Tompa Peter P

PloS one 20120405 4

Based on early bioinformatic studies on a handful of species, the frequency of structural disorder of proteins is generally thought to be much higher in eukaryotes than in prokaryotes. To refine this view, we present here a comparative prediction study and analysis of 194 fully described eukaryotic proteomes and 87 reference prokaryotes for structural disorder. We found that structural disorder does distinguish eukaryotes from prokaryotes, but its frequency spans a very wide range in the two sup ...[more]

PMID: 22496841

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Project description:BackgroundWith the development of high-throughput sequencing techniques, more and more genomes were sequenced and assembled. However, annotating a genome's structure rapidly and expressly remains challenging. Current eukaryotic genome annotations require various, abundant supporting data, such as: species-specific and cross-species protein sequences, ESTs, cDNA and RNA-Seq data. Collecting those data and merging their analytical results to achieve a consistent complete annotation is a complex, time and cost consuming task.ResultsIn our study, we proposed a fast and easy-to-use computational tool: GASS (Genome Annotation based on Species Similarity). It annotates a eukaryotic genome based on only the annotations from another similar species. With aligning the exons' sequences of an annotated similar species to the un-annotated genome, GASS detects the optimal transcript annotations with a shortest-path model. In our study, GASS was used to achieve the rhesus annotations based on the human annotations. The produced annotations were evaluated by comparing them to the two existing rhesus annotation databases (RefSeq and Ensembl) directly and being aligned with three RNA-Seq data of rhesus. The experiment results showed that more than 65% RefSeq exons and splicing junctions were exactly found by GASS. GASS's sensitivity was higher than RefSeq's, and was close to Ensembl's. GASS had higher specificities than Ensembl at gene, transcript, exon and splicing junction levels. We also found the mis-assemblies of rheMac3 genome, which led to the 2 bp shifts in annotating position on exons' boundary and then the incomplete splicing canonical sites in Refseq annotations. These detections were further supported by various data sources.ConclusionsGASS quickly produces structural genome annotations in sufficient abundance and accuracy. With simple and rapid running of GASS, small labs can create quick views of genome annotations for an un-annotated species, without the necessity to create, collect, analyze and synthesize extra various data sources, or wait several months for the annotations from professional organizations. GASS can be applied to many study occasions, such as the analysis of RNA-Seq datasets from the unannotated species whose genome drafts are available but the annotations are not.

Project description:The first step of iron biomineralization mediated by ferritin is the oxidation at the ferroxidase active site of two ferrous ions to a diferric oxo/hydroxo species. Metal-loaded ferritin crystals obtained by soaking crystals of frog ferritin in FeSO(4) and CuSO(4) solutions followed by flash freezing provided X-ray crystal structures of the tripositive iron and bipositive copper adducts at 2.7 and 2.8 Å resolution, respectively. At variance with the already available structures, the crystal form used in this study contains 24 independent subunits in the asymmetric unit permitting comparison between them. For the first time, the diferric species at the ferroxidase site is identified in ferritins from higher eukaryotes. Anomalous difference Fourier maps for crystals (iron crystal 1) obtained after long soaking times in FeSO(4) solution invariantly showed diferric species with a Fe-Fe average distance of 3.1 ± 0.1 Å, strongly indicative of the presence of a ?-oxo/hydroxo bridge between the irons; protein ligands for each iron ion (Fe1 and Fe2) were also unequivocally identified and found to be the same in all subunits. For copper bound ferritin, dicopper(II) centers are also observed. While copper at site 1 is essentially in the same position and has the same coordination environment as Fe1, copper at site 2 is displaced toward His54, now acting as a ligand; this results in an increased intermetal distance (4.3 ± 0.4 Å). His54 coordination and longer metal-metal distances might represent peculiar features of divalent cations at the ferroxidase site. This oxidation-dependent structural information may provide key features for the mechanistic pathway in ferritins from higher eukaryotes that drive uptake of bivalent cation and release of ferric products at the catalytic site. This mechanism is supported by the X-ray picture obtained after only 1 min of soaking in FeSO(4) solutions (iron crystal 2) which reasonably contain the metal at different oxidation states. Here two different di-iron species are trapped in the active site, with intermetal distances corresponding to those of the ferric dimer in crystal 1 and of the dicopper centers and corresponding rearrangement of the His54 side chain.

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Structural disorder in eukaryotes.

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Structural disorder in eukaryotes.

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