Defining metrics for whole-genome sequence analysis of MRSA in clinical practice.

Bacterial sequencing will become increasingly adopted in routine microbiology laboratories. Here, we report the findings of a technical evaluation of almost 800 clinical methicillin-resistant Staphylococcus aureus (MRSA) isolates, in which we sought to define key quality metrics to support MRSA sequencing in clinical practice. We evaluated the accuracy of mapping to a generic reference versus clonal complex (CC)-specific mapping, which is more computationally challenging. Focusing on isolates that were genetically related (50 bp apart to identify same-species contamination for MRSA. These metrics were combined into a quality-control (QC) flowchart to determine whether sequence runs and individual clinical isolates passed QC, which could be adapted by future automated analysis systems to enable rapid hands-off sequence analysis by clinical laboratories

Evaluation of a fully automated bioinformatics tool to predict antibiotic resistance from MRSA genomes.

OBJECTIVES: The genetic prediction of phenotypic antibiotic resistance based on analysis of WGS data is becoming increasingly feasible, but a major barrier to its introduction into routine use is the lack of fully automated interpretation tools. Here, we report the findings of a large evaluation of the Next Gen Diagnostics (NGD) automated bioinformatics analysis tool to predict the phenotypic resistance of MRSA. METHODS: MRSA-positive patients were identified in a clinical microbiology laboratory in England between January and November 2018. One MRSA isolate per patient together with all blood culture isolates (total n = 778) were sequenced on the Illumina MiniSeq instrument in batches of 21 clinical MRSA isolates and three controls. RESULTS: The NGD system activated post-sequencing and processed the sequences to determine susceptible/resistant predictions for 11 antibiotics, taking around 11 minutes to analyse 24 isolates sequenced on a single sequencing run. NGD results were compared with phenotypic susceptibility testing performed by the clinical laboratory using the disc diffusion method and EUCAST breakpoints. Following retesting of discrepant results, concordance between phenotypic results and NGD genetic predictions was 99.69%. Further investigation of 22 isolate genomes associated with persistent discrepancies revealed a range of reasons in 12 cases, but no cause could be found for the remainder. Genetic predictions generated by the NGD tool were compared with predictions generated by an independent research-based informatics approach, which demonstrated an overall concordance between the two methods of 99.97%. CONCLUSIONS: We conclude that the NGD system provides rapid and accurate prediction of the antibiotic susceptibility of MRSA

Ensembl’s 10th year

Ensembl (http://www.ensembl.org) integrates genomic information for a comprehensive set of chordate genomes with a particular focus on resources for human, mouse, rat, zebrafish and other high-value sequenced genomes. We provide complete gene annotations for all supported species in addition to specific resources that target genome variation, function and evolution. Ensembl data is accessible in a variety of formats including via our genome browser, API and BioMart. This year marks the tenth anniversary of Ensembl and in that time the project has grown with advances in genome technology. As of release 56 (September 2009), Ensembl supports 51 species including marmoset, pig, zebra finch, lizard, gorilla and wallaby, which were added in the past year. Major additions and improvements to Ensembl since our previous report include the incorporation of the human GRCh37 assembly, enhanced visualisation and data-mining options for the Ensembl regulatory features and continued development of our software infrastructure

Abstracts from the 20th International Symposium on Signal Transduction at the Blood-Brain Barriers

https://deepblue.lib.umich.edu/bitstream/2027.42/138963/1/12987_2017_Article_71.pd

Dynamics of Population Numbers and Biology of the White-tailed Eagle in Steppe Forests of the Tobol-Ishim Interfluve, Kazakhstan

The Naurzum forest was formerly the only place where nesting of White-tailed Eagles (Haliaeetus albicilla) was known in the northern half of Kazakhstan, apart from the valleys of Irtysh and Ural rivers. In 1978–1979, five breeding territories were found there. Since the early 1980’s, a slow but steady increase of the number of White-tailed Eagles was monitored in the Naurzum Nature Reserve. Eagles’ nests appeared in Sipsyn and in Tersek, in 1994 a second pair was found in Tersek, and by 1998, the population had increased to 13 pairs. Since 1999, new pairs have appeared every year, including the first pair nesting in birch groves on the slopes of the East Turgai plateau. In 2002, the number of known breeding territories in the Naurzum forest reached 22, of which 18 were occupied. Nests with nestlings were located at a distance of 0.7 to 2.8 km. Thus, the number of White-tailed Eagles in the Naurzum forest has become equal to the number of Imperial Eagles (Aquila heliaca)

Особенности размещения и численность орла-могильника в Костанайской области, Казахстан

Изучение распространения и численности орла-могильника (Aquila heliaca) в Костанайской области проводилось в течение 1998–2017 гг. С 1979 г. ведётся постоянный мониторинг гнездовой группировки в Наурзумском заповеднике

Machine-Learning Model for Prediction of Cefepime Susceptibility in Escherichia coli from Whole-Genome Sequencing Data.

The declining cost of performing bacterial whole-genome sequencing (WGS) coupled with the availability of large libraries of sequence data for well-characterized isolates have enabled the application of machine-learning (ML) methods to the development of nonlinear sequence-based predictive models. We tested the ML-based model developed by Next Gen Diagnostics for prediction of cefepime phenotypic susceptibility results in Escherichia coli. A cohort of 100 isolates of E. coli recovered from urine (n = 77) and blood (n = 23) cultures were used. The cefepime MIC was determined in triplicate by reference broth microdilution and classified as susceptible (MIC of ≤2 μg/mL) or not susceptible (MIC of ≥4 μg/mL) using the 2022 Clinical and Laboratory Standards Institute breakpoints. Five isolates generated both susceptible and not susceptible MIC results, yielding categorical agreement of 95% for the reference method to itself. Categorical agreement of ML to MIC interpretations was 97%, with 2 very major (false, susceptible) and 1 major (false, not susceptible) errors. One very major error occurred for an isolate with blaCTX-M-27 (MIC mode, ≥32 μg/mL) and one for an isolate with blaTEM-34 for which the MIC cefepime mode was 4 μg/mL. One major error was for an isolate with blaCTX-M-27 but with a MIC mode of 2 μg/mL. These preliminary data demonstrated performance of ML for a clinically important antimicrobial-species pair at a caliber similar to phenotypic methods, encouraging wider development of sequence-based susceptibility prediction and its validation and use in clinical practice