A nested leucine rich repeat (LRR) domain: The precursor of LRRs is a ten or eleven residue motif

<p>Abstract</p> <p>Background</p> <p>Leucine rich repeats (LRRs) are present in over 60,000 proteins that have been identified in viruses, bacteria, archae, and eukaryotes. All known structures of repeated LRRs adopt an arc shape. Most LRRs are 20-30 residues long. All LRRs contain LxxLxLxxNxL, in which "L" is Leu, Ile, Val, or Phe and "N" is Asn, Thr, Ser, or Cys and "x" is any amino acid. Seven classes of LRRs have been identified. However, other LRR classes remains to be characterized. The evolution of LRRs is not well understood.</p> <p>Results</p> <p>Here we describe a novel LRR domain, or nested repeat observed in 134 proteins from 54 bacterial species. This novel LRR domain has 21 residues with the consensus sequence of LxxLxLxxNxLxxLDLxx(N/L/Q/x)xx or LxxLxCxxNxLxxLDLxx(N/L/x)xx. This LRR domain is characterized by a nested periodicity; it consists of alternating 10- and 11- residues units of LxxLxLxxNx(x/-). We call it "IRREKO" LRR, since the Japanese word for "nested" is "IRREKO". The first unit of the "IRREKO" LRR domain is frequently occupied by an "SDS22-like" LRR with the consensus of LxxLxLxxNxLxxLxxLxxLxx or a "Bacterial" LRR with the consensus of LxxLxLxxNxLxxLPxLPxx. In some proteins an "SDS22-like" LRR intervenes between "IRREKO" LRRs.</p> <p>Conclusion</p> <p>Proteins having "IRREKO" LRR domain are almost exclusively found in bacteria. It is suggested that IRREKO@LRR evolved from a common ancestor with "SDS22-like" and "Bacterial" classes and that the ancestor of IRREKO@LRR is 10 or 11 residues of LxxLxLxxNx(x/-). The "IRREKO" LRR is predicted to adopt an arc shape with smaller curvature in which β-strands are formed on both concave and convex surfaces.</p

Effect of Specimen Thickness on Aging and Fatigue Strength of Al-Zn Alloys

Repeated tensile fatigue strength of the low temperature age-hardened Al-Zn alloys is investigated varying the specimen thickness. Fatigue strength of the age-hardened specimens decreases with the specimen thickness when the specimen is thinner than a certain thickness, whereas fatigue strength of non age-hardened specimens, i.e., pure aluminum and dilute Al-Zn alloy, does not depend the specimen thickness. The dependence of fatigue strength on the thickness of age-hardened specimen is considered to be caused by the decrease of the strength of specimen as a whole, as a result of increase in volume ratio of the soft surface layer formed after age-hardening with decreasing specimen thickness

Logical Operation Based Literature Association with Genes and its application, PosMed.

PosMed prioritizes candidate genes for positional cloning by employing our original database search engine GRASE, which uses an inferential process similar to an artificial neural network comprising documental neurons (or &#x27;documentrons&#x27;) that represent each document contained in databases such as MEDLINE and OMIM (Yoshida, _et al_. 2009, Makita, _et al_. 2009). PosMed immediately ranks the candidate genes by connecting phenotypic keywords to the genes through connections representing gene&#x2013;gene interactions other biological relationships, such as metabolite&#x2013;gene, mutant mouse&#x2013;gene, drug&#x2013;gene, disease&#x2013;gene, and protein&#x2013;protein interactions, ortholog data, and gene&#x2013;literature connections.&#xd;&#xa;&#xd;&#xa;To make proper relationships between genes and literature, we manually curate queries, which are defined by logical operation rules, against MEDLINE. For example, to detect a set of MEDLINE documents for the AT1G03880 gene in _A. thaliana_, we applied the following logical query: (&#x2018;AT1G03880&#x2019; OR &#x2018;CRU2&#x2019; OR &#x2018;CRB&#x2019; OR &#x2018;CRUCIFERIN 2&#x27; OR &#x2018;CRUCIFERIN B&#x2019;) AND (&#x2018;Arabidopsis&#x2019;) NOT (&#x2018;chloroplast RNA binding&#x2019;). Curators refined these queries in mouse, rice and _A. thaliana_. For human and rat genes, we use mouse curation results via ortholog genes in PosMed.&#xd;&#xa;&#xd;&#xa;PosMed is available at &#x22;http://omicspace.riken.jp/PosMed&#x22;:http://omicspace.riken.jp/PosMed&#xd;&#xa;&#xd;&#xa;References:&#xd;&#xa;Yoshida Y, et al. _Nucleic Acids Res_. 37(Web Server issue):W147-52. 2009. &#xd;&#xa;Makita Y, et al. _Plant Cell Physiol_. 2009 Jul;50(7):1249-59.&#xd;&#xa

Comparative sequence analysis of leucine-rich repeats (LRRs) within vertebrate toll-like receptors

<p>Abstract</p> <p>Background</p> <p>Toll-like receptors (TLRs) play a central role in innate immunity. TLRs are membrane glycoproteins and contain leucine rich repeat (LRR) motif in the ectodomain. TLRs recognize and respond to molecules such as lipopolysaccharide, peptidoglycan, flagellin, and RNA from bacteria or viruses. The LRR domains in TLRs have been inferred to be responsible for molecular recognition. All LRRs include the highly conserved segment, LxxLxLxxNxL, in which "L" is Leu, Ile, Val, or Phe and "N" is Asn, Thr, Ser, or Cys and "x" is any amino acid. There are seven classes of LRRs including "typical" ("<b><it>T</it></b>") and "bacterial" ("<b><it>S</it></b>"). All known domain structures adopt an arc or horseshoe shape. Vertebrate TLRs form six major families. The repeat numbers of LRRs and their "phasing" in TLRs differ with isoforms and species; they are aligned differently in various databases. We identified and aligned LRRs in TLRs by a new method described here.</p> <p>Results</p> <p>The new method utilizes known LRR structures to recognize and align new LRR motifs in TLRs and incorporates multiple sequence alignments and secondary structure predictions. TLRs from thirty-four vertebrate were analyzed. The repeat numbers of the LRRs ranges from 16 to 28. The LRRs found in TLRs frequently consists of LxxLxLxxNxLxxLxxxxF/LxxLxx ("<b><it>T</it></b>") and sometimes short motifs including LxxLxLxxNxLxxLPx(x)LPxx ("<b>S</b>"). The <it>TLR7 </it>family (TLR7, TLR8, and TLR9) contain 27 LRRs. The LRRs at the N-terminal part have a super-motif of <b><it>STT </it></b>with about 80 residues. The super-repeat is represented by <b><it>STTSTTSTT </it></b>or <b><it>_TTSTTSTT</it></b>. The LRRs in TLRs form one or two horseshoe domains and are mostly flanked by two cysteine clusters including two or four cysteine residue.</p> <p>Conclusion</p> <p>Each of the six major TLR families is characterized by their constituent LRR motifs, their repeat numbers, and their patterns of cysteine clusters. The central parts of the <it>TLR1 </it>and <it>TLR7 </it>families and of TLR4 have more irregular or longer LRR motifs. These central parts are inferred to play a key role in the structure and/or function of their TLRs. Furthermore, the super-repeat in the <it>TLR7 </it>family suggests strongly that "bacterial" and "typical" LRRs evolved from a common precursor.</p

Increased amyloidogenic processing of transgenic human APP in X11-like deficient mouse brain

<p>Abstract</p> <p>Background</p> <p>X11-family proteins, including X11, X11-like (X11L) and X11-like 2 (X11L2), bind to the cytoplasmic domain of amyloid β-protein precursor (APP) and regulate APP metabolism. Both X11 and X11L are expressed specifically in brain, while X11L2 is expressed ubiquitously. X11L is predominantly expressed in excitatory neurons, in contrast to X11, which is strongly expressed in inhibitory neurons. <it>In vivo </it>gene-knockout studies targeting X11, X11L, or both, and studies of X11 or X11L transgenic mice have reported that X11-family proteins suppress the amyloidogenic processing of endogenous mouse APP and ectopic human APP with one exception: knockout of X11, X11L or X11L2 has been found to suppress amyloidogenic metabolism in transgenic mice overexpressing the human Swedish mutant APP (APPswe) and the mutant human PS1, which lacks exon 9 (PS1dE9). Therefore, the data on X11-family protein function in transgenic human APP metabolism <it>in vivo </it>are inconsistent.</p> <p>Results</p> <p>To confirm the interaction of X11L with human APP ectopically expressed in mouse brain, we examined the amyloidogenic metabolism of human APP in two lines of human APP transgenic mice generated to also lack X11L. In agreement with previous reports from our lab and others, we found that the amyloidogenic metabolism of human APP increased in the absence of X11L.</p> <p>Conclusion</p> <p>X11L appears to aid in the suppression of amyloidogenic processing of human APP in brain <it>in vivo</it>, as has been demonstrated by previous studies using several human APP transgenic lines with various genetic backgrounds. X11L appears to regulate human APP in a manner similar to that seen in endogenous mouse APP metabolism.</p

Nurturing a gender-responsive approach to climate-smart agriculture in Guinayangan, Quezon

Coconut-based farming systems in Guinayangan, Quezon offer special opportunities for achieving multiple objectives, including carbon sequestration, economic empowerment of women and reduction of risks from variable and extreme weather. This info note discusses the gender-based role inequalities within coconut-based farming systems that can be addressed through agroforestry-based, climate-smart agriculture that features small livestock, fruit trees and root and tuber crops as understory crops. Numerous Climate-Smart Villages, spread across the municipality of Guinayangan, now serve as proof of concept, providing evidence that climate-smart agriculture based on agroforestry interventions are gender sensitive

Crystal Structure of the TLR4-MD-2 Complex with Bound Endotoxin Antagonist Eritoran

SummaryTLR4 and MD-2 form a heterodimer that recognizes LPS (lipopolysaccharide) from Gram-negative bacteria. Eritoran is an analog of LPS that antagonizes its activity by binding to the TLR4-MD-2 complex. We determined the structure of the full-length ectodomain of the mouse TLR4 and MD-2 complex. We also produced a series of hybrids of human TLR4 and hagfish VLR and determined their structures with and without bound MD-2 and Eritoran. TLR4 is an atypical member of the LRR family and is composed of N-terminal, central, and C-terminal domains. The β sheet of the central domain shows unusually small radii and large twist angles. MD-2 binds to the concave surface of the N-terminal and central domains. The interaction with Eritoran is mediated by a hydrophobic internal pocket in MD-2. Based on structural analysis and mutagenesis experiments on MD-2 and TLR4, we propose a model of TLR4-MD-2 dimerization induced by LPS

Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases

Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org

ジコウ コウカ AL 12MASS% ZN ゴウキン ノ ヒロウ キョウド ニ オヨボス フクゲン ショリ ノ エイキョウ

Effect of reversion treatment on the fatigue strength of age hardened Al-12mass% Zn alloy was studied by measurements of Vickers micro-hardness and number of cycles to failure under repeated tensile loading. The results obtained are summarized as follows. 1) Rate of reversion was faster in the surface layer than in the interior when the age hardened specimen annealed at 353K. That is, soft surface layer was formed, again. 2) In this case, the presence of soft surface layer strengthens fatigue resistance of the age hardened Al-12mass%Zn alloy

PosMed: ranking genes and bioresources based on Semantic Web Association Study

ABSTRACT Positional MEDLINE (PosMed; http://biolo