Urinary tract infections impose substantial health burdens on women worldwide. Urinary tract infections often incur a high risk of recurrence and antibiotic resistance, and uropathogenic E. coli accounts for approximately 80% of clinically acquired cases. The diagnosis of, treatment of, and drug development for urinary tract infections remain substantial challenges due to the complex pathogenesis of this condition. The clinically isolated UPEC 83972 strain was found to produce four siderophores: yersiniabactin, aerobactin, salmochelin, and enterobactin. The biosyntheses of some of these siderophores implies that the virulence of UPEC is mediated via the targeting of primary metabolism. However, the differential modulatory roles of siderophore biosyntheses on the differential metabolomes of UPEC and non-UPEC strains remain incompletely understood. In the present study, we sought to investigate how the differential metabolomes can be used to distinguish UPEC from non-UPEC strains and to determine the associated regulatory roles of siderophore biosynthesis. Our results are the first to demonstrate that the identified differential metabolomes strongly differentiated UPEC from non-UPEC strains. Furthermore, we performed metabolome assays of mutants with different patterns of siderophore deletions; the data revealed that the mutations of all four siderophores exerted a stronger modulatory role on the differential metabolomes of the UPEC and non-UPEC strains relative to the mutation of any single siderophore and that this modulatory role primarily involved amino acid metabolism, oxidative phosphorylation in the carbon fixation pathway, and purine and pyrimidine metabolism. Surprisingly, the modulatory roles were strongly dependent on the type and number of mutated siderophores. Taken together, these results demonstrated that siderophore biosynthesis coordinately modulated the differential metabolomes and thus may indicate novel targets for virulence-based diagnosis, therapeutics, and drug development related to urinary tract infections.

The high-pathogenicity island (HPI) is an important determinant of the pathogenicity of pathogenic Yersinia microbes. The HPI carries a cluster of virulence genes that chiefly account for the biosynthesis, transportation and regulation of a virulence-associated siderophore, yersiniabactin. This siderophore is also present in uropathogenic E. coli (UTI89) but not in non-uropathogenic E. coli. We sought to perform metabolic phenotyping and to understand how the presence of the HPI influences central carbon metabolism, which remains poorly understood, by combining targeted metabolomics with a genetic approach. Unexpectedly, our results revealed that uropathogenic E. coli (UPEC) with an HPI had superior metabolic homeostasis to a non-UPEC K12 strain without an HPI, thereby allowing UPEC with an HPI to flexibly adapt to a variety of growth environments. In this study, we elucidate the unrecognized regulatory effects of the HPI virulence genes on central carbon metabolism, in addition to their roles in directing yersiniabactin. These regulatory effects may be implicated in differentiating UPEC from non-UPEC.

Correction for ‘Discovery and characterization of functional modules and pathogenic genes associated with the risk of coronary artery disease’ by Wenna Nie et al., RSC Adv., 2015, 5, 26443–26451.

Coronary artery disease (CAD) involves a complex interplay between multiple pathogenic genes that leads to a complex pathogenesis; its diagnosis and treatment remain significantly challenging. Here, we developed an integrated network biology approach to identify disease risk functional modules and pathogenic genes associated with CAD risk. First, we selected 72 known disease genes from the OMIM, GAD, and DO databases as an initial set of seed genes. We retrieved PPI data from HPRD to expand this gene set into a CAD-PPI gene network based on direct interactions and then performed topology analysis for this CAD-PPI gene network. Second, we utilized an MCL algorithm to identify 49 susceptible modules with high modularity. Third, we used functional consistency analysis to further identify 23 risk functional modules. Finally, according to existing cascades of known disease genes in KEGG pathways, we identified 82 pathogenic genes that are either directly or indirectly associated with CAD risk. Based on previous reports, 37 of our identified genes are involved in the development of CAD, whereas the other 45 genes remain to be associated with CAD by experimental evidence. Taken together, our results will provide a better understanding of CAD pathogenesis as well as new insights into its prognosis and treatment.

Bacterial siderophores are a group of chemically diverse, virulence-associated secondary metabolites whose expression exerts metabolic costs. A combined bacterial genetic and metabolomic approach revealed differential metabolomic impacts associated with biosynthesis of different siderophore structural families. Despite myriad genetic differences, the metabolome of a cheater mutant lacking a single set of siderophore biosynthetic genes more closely approximate that of a non-pathogenic K12 strain than its isogenic, uropathogen parent strain. Siderophore types associated with greater metabolomic perturbations are less common among human isolates, suggesting that metabolic costs influence success in a human population. Although different siderophores share a common iron acquisition function, our analysis shows how a metabolomic approach can distinguish their relative metabolic impacts in E. coli.