A new role for PGRP-S (Tag7) in immune defense: lymphocyte migration is induced by a chemoattractant complex of Tag7 with Mts1

PGRP-S (Tag7) is an innate immunity protein involved in the antimicrobial defense systems, both in insects and in mammals. We have previously shown that Tag7 specifically interacts with several proteins, including Hsp70 and the calcium binding protein S100A4 (Mts1), providing a number of novel cellular functions. Here we show that Tag7–Mts1 complex causes chemotactic migration of lymphocytes, with NK cells being a preferred target. Cells of either innate immunity (neutrophils and monocytes) or acquired immunity (CD4⁺ and CD8⁺ lymphocytes) can produce this complex, which confirms the close connection between components of the 2 branches of immune response.     

The genus Luppovia and the phylogeny of Cretaceous heteromorphic ammonoids

The unique preservation of heteromorphic shells of Luppovia Kakabadze, Bogdanova & Mikhailova 1978 from the Aptian deposits of Bolshoj Balkhan (western Turkmenia) made it possible to study the microstructure, internal shell characteristics and suture ontogeny of this genus. Microstructural investigations revealed that the dorsal shell wall in Luppovia is composed of three layers in contrast to that of monomorphic ammonoids, which is single-layered. This ability of secreting different numbers of layers in monomorphs and heteromorphs demonstrates plasticity of secreting activity of the mantle epithelium. Data obtained from the study of internal shell structure and suture ontogeny have been compared. Both these methods of investigation lead to the conclusion that the genus Luppovia belongs to the order Ammonitida. The results obtained confirm the viewpoint that the Cretaceous heteromorphic superfamilies Turrilitaceae and Ancylocerataceae have independent origins and belong to two different orders, Lytoceratida and Ammonitida, respectively. □ Ammonoidea , Luppovia, shell structure, ontogeny, phylogeny, Cretaceous.     

AmylPepPred: Amyloidogenic Peptide Prediction tool

We present an efficient computational architecture designed using supervised machine learning model to predict amyloid fibril forming protein segments, named AmylPepPred. The proposed prediction model is based on bio-physio-chemical properties of primary sequences and auto-correlation function of their amino acid indices. AmylPepPred provides a user friendly web interface for the researchers to easily observe the fibril forming and non-fibril forming hexmers in a given protein sequence. We expect that this stratagem will be highly encouraging in discovering fibril forming regions in proteins thereby benefit in finding therapeutic agents that specifically aim these sequences for the inhibition and cure of amyloid illnesses.

Availability

AmylPepPred is available freely for academic use at www.zoommicro.in/amylpeppred