Trotter, E. | Search bioRxiv

bioRxiv2023

Uropathogenic Escherichia coli population structure and antimicrobial susceptibility in Norfolk, UK

SynopsisO_ST_ABSBackgroundC_ST_ABSHalf of all women have experienced a urinary tract infection (UTI) in their lifetime and this remains a persistent issue in rural counties like Norfolk, UK. In alignment globally, Uropathogenic E. coli (UPEC) are the main etiological agent for UTIs in Norfolk and are increasingly difficult to treat due to multi-drug resistance (MDR). ObjectiveWe set out to identify which clonal groups and resistance genes are disseminating in the community and hospitals in Norfolk, the first study of its kind for UPEC in this region. MethodsWe collected 217 clinical E. coli isolates causing UTIs in the community and hospital from the Clinical Microbiology laboratory at Norfolk and Norwich University Hospital. These were whole genome sequenced using the Illumina and MinION platforms for in silico multi-locus sequence typing and antibiotic resistance determinant detection. ResultsThe isolates were composed of 74 sequence types (STs); 8 lineages represented 57% of this population: ST73, ST12, ST69, ST131, ST404, ST95, ST127, and ST1193. Importantly, primary UTI screening deemed 8% of isolates to be MDR, with high rates of resistance to ampicillin (52.1%) and trimethoprim (36.2%) in hospitals. Of concern is the probable clonal expansion of MDR groups ST131 and ST1193 in hospitals and community settings with chromosomally encoded blaCTX-M-15, blaOXA-1, and aac(6)-Ib-cr5. ConclusionsThe burden of reported UTIs in Norfolk is largely caused by non-MDR isolates. The UPEC population is continually evolving, and monitoring samples with consideration of sources will help reduce burden of disease.

microbiology↗

bioRxiv2018

Truncation and Motif Based Pan-Cancer Analysis Highlights Novel Tumor Suppressing Kinases.

A major challenge in cancer genomics is identifying driver mutations from the large number of neutral passenger mutations within a given tumor. Here, we utilize motifs critical for kinase activity to functionally filter genomic data to identify driver mutations that would otherwise be lost within mutational noise. In the first step of our screen, we define a putative tumor suppressing kinome by identifying kinases with truncation mutations occurring within or before the kinase domain. We aligned these kinase sequences and, utilizing data from the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas databases, identified amino acids that represent predicted hotspots for loss-of-function mutations. The functional consequences of new LOF mutations were validated and the top 15 hotspot LOF residues were used in a pan-cancer analysis to define the tumor-suppressing kinome. A ranked list revealed MAP2K7 as a candidate tumor suppressor in gastric cancer, despite the mutational frequency of MAP2K7 falling within the mutational noise for this cancer type. The majority of mutations in MAP2K7 abolished catalytic activity compared to the wild type kinase, consistent with a tumor suppressive role for MAP2K7 in gastric cancer. Furthermore, reactivation of the JNK pathway in gastric cancer cells harboring LOF mutations in MAP2K7 or JNK1 suppresses clonogenicity and growth in soft agar, demonstrating the functional importance of inactivating the JNK pathway in gastric cancer. In summary, our data highlights a broadly applicable strategy to identify functional cancer driver mutations leading us to define the JNK pathway as tumor suppressive in gastric cancer.\n\nSummaryA unique computational pan-cancer analysis pinpoints novel tumor suppressing kinases, and highlights the power of functional genomics by defining the JNK pathway as tumor suppressive in gastric cancer.

cancer biology↗