Characterization of a Legionella pneumophila gene encoding a lipoprotein antigen

A prominent 19kDa surface antigen of Legionella pneumophila , cloned in Escherichia coli , was found to be intimately associated with peptidoglycan. The DNA region encoding this antigen was mapped on an 11.9kb plasmid by means of deletion analysis and transposon mutagenesis. PhoA + gene fusions, generated by Tn phoA insertions into this region, confirmed the presence of a gene encoding a secreted protein. PhoA + transposon insertions were also associated with loss of the 19 kDa antigen in immunoassay s using a monoclonal antibody (mAb1E9) and the replacement of the 19kDa antigen with larger fusion proteins in immunoblots using Legionella immune serum. A 1540bp PstI fragment carrying the gene was sequenced, and the open reading frame encoding the antigen was identified. The gene encodes a polypeptide 176 amino acid residues long and 18913Da in size. The presence of a signal sequence of 22 amino acids with a consensus sequence for cleavage by signal peptidase II indicates that the antigen is a lipoprotein, and striking similarity with peptidoglycan-associated lipoproteins (PALs) from E. coli (51% amino acid homology) and Haemophilus influenzae (55% homology) is noted. We conclude that the 19kDa antigen of L. pneumophila is the structural equivalent of the PAL found in other Gram-negative species and suggest that its post-translational acylation may explain its potency as an immunogen.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75712/1/j.1365-2958.1991.tb00824.x.pd

A Maximum Entropy Formalism for Disentangling Chains of Correlated Sequence Positions

Covariation analysis of sets of aligned sequences of protein molecules is successful in certain instances in elucidating certain structural and functional links, but in general, pairs of sites displaying highly covarying mutations in protein sequences do not necessarily correspond to sites that are spatially close in the protein structure. In contrast, covariation analysis of sets of aligned sequences for RNA molecules is relatively successful in elucidating RNA secondary structure, as well as some aspects of tertiary structure. The goals of this paper are to (1) present the problem, (2) develop the mathematical formalism for solving the problem, and (3) validate the resulting algorithms on simulated data. Extensive application to biological sequences will be presented elsewhere