Streptococcus pneumoniae Proteins AmiA, AliA, and AliB Bind Peptides Found in Ribosomal Proteins of Other Bacterial Species

Background We present an overview of bacterial non-classical secretion and a prediction method for identification of proteins following signal peptide independent secretion pathways. We have compiled a list of proteins found extracellularly despite the absence of a signal peptide. Some of these proteins also have known roles in the cytoplasm, which means they could be so-called "moon-lightning" proteins having more than one function. Results A thorough literature search was conducted to compile a list of currently known bacterial non-classically secreted proteins. Pattern finding methods were applied to the sequences in order to identify putative signal sequences or motifs responsible for their secretion. We have found no signal or motif characteristic to any majority of the proteins in the compiled list of non-classically secreted proteins, and conclude that these proteins, indeed, seem to be secreted in a novel fashion. However, we also show that the apparently non-classically secreted proteins are still distinguished from cellular proteins by properties such as amino acid composition, secondary structure and disordered regions. Specifically, prediction of disorder reveals that bacterial secretory proteins are more structurally disordered than their cytoplasmic counterparts. Finally, artificial neural networks were used to construct protein feature based methods for identification of non-classically secreted proteins in both Gram-positive and Gram-negative bacteria. Conclusion We present a publicly available prediction method capable of discriminating between this group of proteins and other proteins, thus allowing for the identification of novel non-classically secreted proteins. We suggest candidates for non-classically secreted proteins in Escherichia coli and Bacillus subtilis. The prediction method is available online.

Recently, several laboratories identifying proteins involved in the complex processes of replication, transcription and tumor suppression found that the 'new' protein they discovered had another, previously identified, function. A single protein with multiple functions might seem surprising, but there are actually many cases of proteins that 'moonlight', or have more than one role in an organism. As well as adding to the number and types of proteins that are known to moonlight, these new examples add to our understanding of the potential importance of moonlighting proteins.

The composition of the upper respiratory tract microbial community may influence the risk for colonization by the acute otitis media (AOM) pathogens Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis. We used culture-independent methods to describe upper respiratory tract microbial communities in healthy children and children with upper respiratory tract infection with and without concurrent AOM. Nasal swabs and data were collected in a cross-sectional study of 240 children between 6 months and 3 years of age. Swabs were cultured for S. pneumoniae, and real-time PCR was used to identify S. pneumoniae, H. influenzae, and M. catarrhalis. The V1-V2 16S rRNA gene regions were sequenced using 454 pyrosequencing. Microbial communities were described using a taxon-based approach. Colonization by S. pneumoniae, H. influenzae, and M. catarrhalis was associated with lower levels of diversity in upper respiratory tract flora. We identified commensal taxa that were negatively associated with colonization by each AOM bacterial pathogen and with AOM. The balance of these relationships differed according to the colonizing AOM pathogen and history of antibiotic use. Children with antibiotic use in the past 6 months and a greater abundance of taxa, including Lactococcus and Propionibacterium, were less likely to have AOM than healthy children (odds ratio [OR], 0.46; 95% confidence interval [CI], 0.25 to 0.85). Children with no antibiotic use in the past 6 months, a low abundance of Streptococcus and Haemophilus, and a high abundance of Corynebacterium and Dolosigranulum were less likely to have AOM (OR, 0.51; 95% CI, 0.31 to 0.83). An increased understanding of polymicrobial interactions will facilitate the development of effective AOM prevention strategies.