An automated method for consistent helix assignment using turn information

A new automated helix assignment method is presented that leads to a more consistent definition of the helix termini, especially of the helix C-terminus. The method assigns a helix to segments of protein chain where adjacent helical turn structures are observed, capped by specific distorted turn types (e.g., open helical turns without a hydrogen bond) or capping motifs (e.g., the Schellman motif). Helix termini are detected by observing the behavior of the NH group in N-termini and the CO group in C-termini; in each case, the respective group must be free to interact with hydrogen bonding partners outside of the putative helix for a helix terminus to be assigned. The presented assignment method and SHAFT-assigned helices are part of Secbase and are made available with Relibase+ 3.0 and the free web version of Relibase 3.0. The method can also be used for the helix assignments of additional protein structures.     

NMR structure of the Bordetella bronchiseptica protein NP_888769.1 establishes a new phage-related protein family PF13554

The solution structure of the hypothetical phage-related protein NP_888769.1 from the Gram-negative bacterium Bordetella bronchoseptica contains a well-structured core comprising a five-stranded, antiparallel β-sheet packed on one side against two α-helices and a short β-hairpin with three flexibly disordered loops extending from the central β-sheet. A homology search with the software DALI identified two Protein Data Bank deposits with Z-scores > 8, where both of these proteins have less than 8% sequence identity relative to NP_888769.1, and one has been functionally annotated as a lambda phage tail terminator protein. A sequence-homology analysis then confirmed that NP_888769.1 represents the first three-dimensional structural representative of a new protein family that was previously predicted by the Joint Center for Structural Genomics, which includes so far about 20 prophage proteins encoded in bacterial genomes.     

Solution structure of the Escherichia coli protein ydhR: a putative mono-oxygenase

YdhR is a 101-residue conserved protein from Escherichia coli. Sequence searches reveal that the protein has >50% identity to proteins found in a variety of other bacterial genomes. Using size exclusion chromatography and fluorescence spectroscopy, we determined that ydhR exists in a dimeric state with a dissociation constant of approximately 40 nM. The three-dimensional structure of dimeric ydhR was determined using NMR spectroscopy. A total of 3400 unambiguous NOEs, both manually and automatically assigned, were used for the structure calculation that was refined using an explicit hydration shell. A family of 20 structures was obtained with a backbone RMSD of 0.48 A for elements of secondary structure. The structure reveals a dimeric alpha,beta fold characteristic of the alpha+beta barrel superfamily of proteins. Bioinformatic approaches were used to show that ydhR likely belongs to a recently identified group of mono-oxygenase proteins that includes ActVA-Orf6 and YgiN and are involved in the oxygenation of polyaromatic ring compounds.     

High-resolution aliphatic side-chain assignments in 3D HCcoNH experiments with joint H–C evolution and non-uniform sampling

We describe an efficient NMR triple resonance approach that correlates, at high resolution, protein side-chain and backbone resonances. It relies on the combination of two strategies: joint evolution of aliphatic side-chain proton/carbon coherences using a backbone N–H based HCcoNH reduced dimensionality (RD) experiment and non-uniform sampling (NUS) in two indirect dimensions. A typical data set containing such correlation information can be acquired in 2 days, at very high resolution unfeasible for conventional 4D HCcoNH-TOCSY experiments. The resonances of the aliphatic side-chain protons are unambiguously assigned to their attached carbons through the analysis of the ‘sum’ and ‘difference’ spectra. This approach circumvents the tedious process of manual resonance assignments using HCcH-TOCSY data, while providing additional resolving power of backbone N–H signals. A simple peak-list based algorithm has been implemented in the IBIS software for rapid automated backbone and side-chain assignments.     

FIRST HARMFUL DINOPHYSIS (DINOPHYCEAE,DINOPHYSIALES) BLOOM IN THE U.S. IS REVEALED BY AUTOMATED IMAGING FLOW CYTOMETRY1

Imaging FlowCytobot (IFCB) combines video and flow cytometric technology to capture images of nano‐ and microplankton (～10 to >100 μm) and to measure the chlorophyll fluorescence associated with each image. The images are of sufficient resolution to identify many organisms to genus or even species level. IFCB has provided >200 million images since its installation at the entrance to the Mission‐Aransas estuary (Port Aransas, TX, USA) in September 2007. In early February 2008, Dinophysis cells (1–5 · mL^?1) were detected by manual inspection of images; by late February, abundance estimates exceeded 200 cells · mL^?1. Manual microscopy of water samples from the site confirmed that D. cf. ovum F. Schütt was the dominant species, with cell concentrations similar to those calculated from IFCB data, and toxin analyses showed that okadaic acid was present, which led to closing of shellfish harvesting. Analysis of the time series using automated image classification (extraction of image features and supervised machine learning algorithms) revealed a dynamic phytoplankton community composition. Before the Dinophysis bloom, Myrionecta rubra (a prey item of Dinophysis) was observed, and another potentially toxic dinoflagellate, Prorocentrum, was observed after the bloom. Dinophysis cell‐division rates, as estimated from the frequency of dividing cells, were the highest at the beginning of the bloom. Considered on a daily basis, cell concentration increased roughly exponentially up to the bloom peak, but closer inspection revealed that the increases generally occurred when the direction of water flow was into the estuary, suggesting the source of the bloom was offshore.     

Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences

Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.