A role of corazonin receptor in larval-pupal transition and pupariation in the oriental fruit fly Bactrocera dorsalis (Hendel) (Diptera: Tephritidae)

Corazonin (Crz) is a neuropeptide hormone, but also a neuropeptide modulator that is internally released within the CNS, and it has a widespread distribution in insects with diverse physiological functions. Here, we identified and cloned the cDNAs of Bactrocera dorsalis that encode Crz and its receptor CrzR. Mature BdCrz has 11 residues with a unique Ser11 substitution (instead of the typical Asn) and a His in the evolutionary variable position 7. The BdCrzR cDNA encodes a putative protein of 608 amino acids with 7 putative transmembrane domains, typical for the structure of G-protein-coupled receptors. When expressed in Chinese hamster ovary (CHO) cells, the BdCrzR exhibited a high sensitivity and selectivity for Crz (EC50 approximate to 52.5 nM). With qPCR, the developmental stage and tissue-specific expression profiles in B. dorsalis demonstrated that both BdCrz and BdCrzR were highly expressed in the larval stage, and BdCrzR peaked in 2-day-old 3rd-instar larvae, suggesting that the BdCrzR may play an important role in the larval-pupal transition behavior. Immunochemical localization confirmed the production of Crz in the central nervous system (CNS), specifically by a group of three neurons in the dorso-lateral protocerebrum and eight pairs of lateral neurons in the ventral nerve cord. qPCR analysis located the BdCrzR in both the CNS and epitracheal gland, containing the Inka cells. Importantly, dsRNA-BdCrzR-mediated gene-silencing caused a delay in larval-pupal transition and pupariation, and this phenomenon agreed with a delayed expression of tyrosine hydroxylase and dopa-decarboxylase genes. We speculate that CrzR-silencing blocked dopamine synthesis, resulting in the inhibition of pupariation and cuticular melanization. Finally, injection of Crz in head-ligated larvae could rescue the effects. These findings provide a new insight into the roles of Crz signaling pathway components in B. dorsalis and support an important role of CrzR in larval-pupal transition and pupariation behavior

4,4′-Bipyridine–cyano­acetic acid (1/2)

Crystals of the title adduct, C10H8N2·2C3H3NO2, were obtained from a methanol/water solution of cyano­acetic acid and 4,4′-bipyridine at room temperature. In the crystal structure, cyano­acetic acid and centrosymmetric 4,4′-bipyridine mol­ecules are linked by O—H⋯N hydrogen bonds to form three-component supra­molecular adducts. The acidic H atom is almost midway between the O and N atoms of the cyano­acetic acid and bipyridine mol­ecules, with O—H and N—H distances of 1.19 (3) and 1.39 (3) Å, respectively, so that the H-atom transfer is best regarded as partial. The three-component adducts are further inter­connected with neighboring mol­ecules by weak inter­molecular C—H⋯O and C—H⋯N hydrogen bonds and by π–π stacking inter­actions [centroid–centroid distance = 3.7200 (11) Å] to generate a three-dimensional supra­molecular structure

Modifying the DPClus algorithm for identifying protein complexes based on new topological structures

<p>Abstract</p> <p>Background</p> <p>Identification of protein complexes is crucial for understanding principles of cellular organization and functions. As the size of protein-protein interaction set increases, a general trend is to represent the interactions as a network and to develop effective algorithms to detect significant complexes in such networks.</p> <p>Results</p> <p>Based on the study of known complexes in protein networks, this paper proposes a new topological structure for protein complexes, which is a combination of subgraph diameter (or average vertex distance) and subgraph density. Following the approach of that of the previously proposed clustering algorithm DPClus which expands clusters starting from seeded vertices, we present a clustering algorithm IPCA based on the new topological structure for identifying complexes in large protein interaction networks. The algorithm IPCA is applied to the protein interaction network of Sacchromyces cerevisiae and identifies many well known complexes. Experimental results show that the algorithm IPCA recalls more known complexes than previously proposed clustering algorithms, including DPClus, CFinder, LCMA, MCODE, RNSC and STM.</p> <p>Conclusion</p> <p>The proposed algorithm based on the new topological structure makes it possible to identify dense subgraphs in protein interaction networks, many of which correspond to known protein complexes. The algorithm is robust to the known high rate of false positives and false negatives in data from high-throughout interaction techniques. The program is available at <url>http://netlab.csu.edu.cn/bioinformatics/limin/IPCA</url>.</p