, 2006; Wagner et al., 2007). However, the molecular mechanism by which

L. pneumophila Mip acts on these substrates remains unclear. The data obtained from Western blotting analysis show that MipXcc is localized in the periplasmic space. In contrast, the Mips and Mip-like proteins of L. pneumophila, N. gonorrhoeae, and C. trachomatis are located on the cell surface (Cianciotto et al., 1989; Leuzzi et al., 2005; Neff et al., 2007). The Mip-like proteins of T. cruzi and C. pneumoniae are secreted into the extracellular environment (Moro et al., 1995; Herrmann et al., 2006). It may be that Mips and Mip-like proteins that have different locations may influence virulence via different mechanisms. The role of the periplasmic MipXcc in pathogenesis may be quite different from those of the cell surface and extracellular Mips and Mip-like proteins. The find more latter may interact directly with host substrates in ways that a periplasmic protein could not. The results presented herein demonstrate that at least one of the major roles of the periplasmic Mip protein of Xcc in pathogenesis is assisting the maturation of proteins required for virulence. They also show that this process takes place in the periplasm. The Mip-like

protein FkpA is also located in the periplasm, and it has been suggested that it may be involved in the stress response or serve as a heat-shock protein that functions as a chaperone for envelope proteins (Missiakas et al., 1996; Arie et al., 2001). We are grateful

selleck chemicals to J. Maxwell Dow and Robert P. Ryan for helpful discussions and critical reading of the manuscript. This work was supported by the National Natural Science Foundation of China (30730004). Q.-L.M. and D.-J.T. contributed equally to this work. “
“The 16S rRNA gene has been widely used as a marker of gut bacterial diversity and phylogeny, yet we do not know the model of evolution that best explains the differences in its nucleotide composition within and among taxa. Over 46 000 good-quality near-full-length 16S rRNA gene sequences from five bacterial phyla were obtained from the ribosomal database project (RDP) by study and, when possible, by 4��8C within-study characteristics (e.g. anatomical region). Using alignments (RDPX and MUSCLE) of unique sequences, the FINDMODEL tool available at http://www.hiv.lanl.gov/ was utilized to find the model of character evolution (28 models were available) that best describes the input sequence data, based on the Akaike information criterion. The results showed variable levels of agreement (from 33% to 100%) in the chosen models between the RDP-based and the MUSCLE-based alignments among the taxa. Moreover, subgroups of sequences (using either alignment method) from the same study were often explained by different models. Nonetheless, the different representatives of the gut microbiota were explained by different proportions of the available models.