C-Type Lectin in Chlamys farreri (CfLec-1) Mediating Immune Recognition and Opsonization

Background: C-type lectins are a superfamily of Ca 2+ dependent carbohydrate-recognition proteins that play significant diverse roles in nonself-recognition and clearance of invaders. Though they are well characterized in vertebrates, the study of the potential function and mechanism of C-type lectins in invertebrate immunity is still in its infancy. Methodology: A C-type lectin (CfLec-1) from scallop Chlamys farreri, a dominant cultured mollusk species in China, was selected to investigate its mRNA expression, localization and the possible functions in innate immunity in the present study. After scallop was stimulated by three typical PAMPs, the mRNA expression of CfLec-1 in hemocytes was poles apart. It was significantly up-regulated (p,0.01) after scallops were stimulated by LPS or b-glucan, but significantly down-regulated (p,0.01) after PGN stimulation. The binding ability of recombinant CfLec-1 (designated as rCfLec-1) towards eight PAMPs was investigated subsequently by PAMPs microarray, which revealed rCfLec-1 could bind LPS, PGN and mannan in vitro, indicating CfLec-1 served as a PRR involved in the pathogen recognition. Immunofluorescence assay with polyclonal antibody specific for CfLec-1 revealed that CfLec-1 was mainly located in the mantle and gill of the scallop. CfLec-1 could bind to the surface of scallop hemocytes and recruited hemocytes to enhance their encapsulation in vitro, and this process could be specifically blocked by anti-rCfLec-1 antibody. Meanwhile, rCfLec-1 could also enhance the phagocytic activity of scallop hemocytes against Escherichia coli

Enhancement of COPD biological networks using a web-based collaboration interface

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks