Mannan-binding lectin-associated serine protease 1 (MASP-1), the most abundant enzyme of the complement lectin pathway, is able to stimulate human umbilical vein endothelial cells (HUVECs) to alter the expression of several cytokines and adhesion molecules. This study has assessed to what extent MASP-1 is able to modify the transcriptional pattern of inflammation-related (IR) genes in HUVECs. We utilized Agilent microarray to analyse the effects of recombinant MASP-1 (rMASP-1) in HUVECs, on a set of 884 IR genes. Gene Set Enrichment Analysis showed an overall activation of inflammation-related genes in response to rMASP-1. rMASP-1 treatment up- and down-regulated 19 and 11 IR genes, respectively. Most of them were previously unidentified, such as genes of chemokines (CXCL1, CXCL2, CXCL3), inflammatory receptors (TLR2, BDKRB2) and other inflammatory factors (F3, LBP). Expression of IR genes changed early, during the first 2 hours of activation. Both p38-MAPK inhibitor and NFκB inhibitor efficiently suppressed the effect of rMASP-1. We delineated 12 transcriptional factors as possible regulators of rMASP-1-induced IR genes. Our microarray-based data are in line with the hypothesis that complement lectin pathway activation, generating active MASP-1, directly regulates inflammatory processes by shifting the phenotype of endothelial cells towards a more pro-inflammatory type.

ABC (ATP-Binding Cassette) proteins with altered function are responsible for numerous human diseases. To aid the selection of positions and amino acids for ABC structure/function studies we have generated a database, ABCMdb (Gyimesi et al., ABCMdb: a database for the comparative analysis of protein mutations in ABC transporters, and a potential framework for a general application. Hum Mutat 2012; 33:1547–1556.), with interactive tools. The database has been populated with mentions of mutations extracted from full text papers, alignments and structural models. In the new version of the database we aimed to collect the effect of mutations from databases including ClinVar. Because of the low number of available data, even in the case of the widely studied disease-causing ABC proteins, we also included the possible effects of mutations based on SNAP2 and PROVEAN predictions. To aid the interpretation of variations in non-coding regions, the database was supplemented with related DNA level information. Our results emphasize the importance of in silico predictions because of the sparse information available on variants and suggest that mutations at analogous positions in homologous ABC proteins have a strong predictive power for the effects of mutations. Our improved ABCMdb advances the design of both experimental studies and meta-analyses in order to understand drug interactions of ABC proteins and the effects of mutations on functional expression. Database URL: http://abcm2.hegelab.org