Biofilm formation by multidrug resistant Escherichia coli ST131 is dependent on type 1 fimbriae and assay conditions.

Escherichia coli sequence type 131 (ST131) have emerged as a pandemic lineage of important multidrug resistant pathogens worldwide. Despite many studies examining the epidemiology of ST131, only a few studies to date have investigated the capacity of ST131 strains to form biofilms. Some of these studies have reported contrasting findings, with no specific ST131 biofilm-promoting factors identified. Here we examined a diverse collection of ST131 isolates for in vitro biofilm formation in different media and assay conditions, including urine from healthy adult women. We found significant differences among strains and assay conditions, which offers an explanation for the contrasting findings reported by previous studies using a single condition. Importantly, we showed that expression of type 1 fimbriae is a critical determinant for biofilm formation by ST131 strains and that inhibition of the FimH adhesin significantly reduces biofilm formation. We also offer direct genetic evidence for the contribution of type 1 fimbriae in biofilm formation by the reference ST131 strain EC958, a representative of the clinically dominant H30-Rx ST131 subgroup. This is the first study of ST131 biofilm formation in biologically relevant conditions and paves the way for the application of FimH inhibitors in treating drug resistant ST131 biofilm infections.

Pheo-type: A diagnostic gene-expression assay for the classification of pheochromocytoma and paraganglioma

Context: Pheochromocytomas and paragangliomas (PPGLs) are heritable neoplasms that can be classified into gene-expression subtypes corresponding to their underlying specific genetic drivers. Objective: This study aimed to develop a diagnostic and research tool (Pheo-type) capable of classifying PPGL tumors into gene-expression subtypes that could be used to guide and interpret genetic testing, determine surveillance programs, and aid in elucidation of PPGL biology. Design: A compendium of published microarray data representing 205 PPGL tumors was used for the selection of subtype-specific genes that were then translated to the Nanostring gene-expression platform. A support vector machine was trained on the microarray dataset and then tested on an independent Nanostring dataset representing 38 familial and sporadic cases of PPGL of known genotype (RET, NF1, TMEM127, MAX, HRAS, VHL, and SDHx). Different classifier models involving between three and six subtypes were compared for their discrimination potential. Results: A gene set of 46 genes and six endogenous controls was selected representing six known PPGL subtypes; RTK1–3 (RET, NF1, TMEM127, and HRAS), MAX-like, VHL, and SDHx. Of 38 test cases, 34 (90%) were correctly predicted to six subtypes based on the known genotype to gene-expression subtype association. Removal of the RTK2 subtype from training, characterized by an admixture of tumor and normal adrenal cortex, improved the classification accuracy (35/38). Consolidation of RTK and pseudohypoxic PPGL subtypes to four- and then three-class architectures improved the classification accuracy for clinical application. Conclusions: The Pheo-type gene-expression assay is a reliable method for predicting PPGL genotype using routine diagnostic tumor samples.