E. coli Nissle 1917 Affects Salmonella Adhesion to Porcine Intestinal Epithelial Cells

BACKGROUND: The probiotic Escherichia coli strain Nissle 1917 (EcN) has been shown to interfere in a human in vitro model with the invasion of several bacterial pathogens into epithelial cells, but the underlying molecular mechanisms are not known. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we investigated the inhibitory effects of EcN on Salmonella Typhimurium invasion of porcine intestinal epithelial cells, focusing on EcN effects on the various stages of Salmonella infection including intracellular and extracellular Salmonella growth rates, virulence gene regulation, and adhesion. We show that EcN affects the initial Salmonella invasion steps by modulating Salmonella virulence gene regulation and Salmonella SiiE-mediated adhesion, but not extra- and intracellular Salmonella growth. However, the inhibitory activity of EcN against Salmonella invasion always correlated with EcN adhesion capacities. EcN mutants defective in the expression of F1C fimbriae and flagellae were less adherent and less inhibitory toward Salmonella invasion. Another E. coli strain expressing F1C fimbriae was also adherent to IPEC-J2 cells, and was similarly inhibitory against Salmonella invasion like EcN. CONCLUSIONS: We propose that EcN affects Salmonella adhesion through secretory components. This mechanism appears to be common to many E. coli strains, with strong adherence being a prerequisite for an effective reduction of SiiE-mediated Salmonella adhesion

High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria

Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of “alien” elements which probably undergo special temporal–spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these “exotic” regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for “alien” regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions

Salmonella bongori provides insights into the evolution of the Salmonellae.

The genus Salmonella contains two species, S. bongori and S. enterica. Compared to the well-studied S. enterica there is a marked lack of information regarding the genetic makeup and diversity of S. bongori. S. bongori has been found predominantly associated with cold-blooded animals, but it can infect humans. To define the phylogeny of this species, and compare it to S. enterica, we have sequenced 28 isolates representing most of the known diversity of S. bongori. This cross-species analysis allowed us to confidently differentiate ancestral functions from those acquired following speciation, which include both metabolic and virulence-associated capacities. We show that, although S. bongori inherited a basic set of Salmonella common virulence functions, it has subsequently elaborated on this in a different direction to S. enterica. It is an established feature of S. enterica evolution that the acquisition of the type III secretion systems (T3SS-1 and T3SS-2) has been followed by the sequential acquisition of genes encoding secreted targets, termed effectors proteins. We show that this is also true of S. bongori, which has acquired an array of novel effector proteins (sboA-L). All but two of these effectors have no significant S. enterica homologues and instead are highly similar to those found in enteropathogenic Escherichia coli (EPEC). Remarkably, SboH is found to be a chimeric effector protein, encoded by a fusion of the T3SS-1 effector gene sopA and a gene highly similar to the EPEC effector nleH from enteropathogenic E. coli. We demonstrate that representatives of these new effectors are translocated and that SboH, similarly to NleH, blocks intrinsic apoptotic pathways while being targeted to the mitochondria by the SopA part of the fusion. This work suggests that S. bongori has inherited the ancestral Salmonella virulence gene set, but has adapted by incorporating virulence determinants that resemble those employed by EPEC.We thank the core sequencing and informatics teams at the Sanger Institute for their assistance and The Wellcome Trust for its support of the Sanger Institute Pathogen Genomics and Biology groups and the MRC for their support of GF, KSR and GNS. MCF, GCL, TRC, HSS, GSV, MS, NKP, RAK, JP, GD and NRT were supported by Wellcome Trust grant 076964 and MICROME, an EU Framework Programme 7 Collaborative Project, Grant Agreement Number 222886-2. Work was also supported by Grant ADI-08/2006 from Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) and The World Bank, and grant 1100092 from Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT). CJB was supported by fellowships from CONICYT (21080373 and AT-24091015)

A Strand-Specific RNA–Seq Analysis of the Transcriptome of the Typhoid Bacillus Salmonella Typhi

High-density, strand-specific cDNA sequencing (ssRNA–seq) was used to analyze the transcriptome of Salmonella enterica serovar Typhi (S. Typhi). By mapping sequence data to the entire S. Typhi genome, we analyzed the transcriptome in a strand-specific manner and further defined transcribed regions encoded within prophages, pseudogenes, previously un-annotated, and 3′- or 5′-untranslated regions (UTR). An additional 40 novel candidate non-coding RNAs were identified beyond those previously annotated. Proteomic analysis was combined with transcriptome data to confirm and refine the annotation of a number of hpothetical genes. ssRNA–seq was also combined with microarray and proteome analysis to further define the S. Typhi OmpR regulon and identify novel OmpR regulated transcripts. Thus, ssRNA–seq provides a novel and powerful approach to the characterization of the bacterial transcriptome

Evolutionary causes and consequences of bacterial antibiotic persistence

Antibiotic treatment failure is of growing concern. Genetically encoded resistance is key in driving this process. However, there is increasing evidence that bacterial antibiotic persistence, a non-genetically encoded and reversible loss of antibiotic susceptibility, contributes to treatment failure and emergence of resistant strains as well. In this Review, we discuss the evolutionary forces that may drive the selection for antibiotic persistence. We review how some aspects of antibiotic persistence have been directly selected for whereas others result from indirect selection in disparate ecological contexts. We then discuss the consequences of antibiotic persistence on pathogen evolution. Persisters can facilitate the evolution of antibiotic resistance and virulence. Finally, we propose practical means to prevent persister formation and how this may help to slow down the evolution of virulence and resistance in pathogens