Search bioRxiv⌕ Search

Biology subjects

Breitwieser, F. P.

Publications and source records attributed to Breitwieser, F. P..

3 recordsLinked to original sources

Metagenomic Next-Generation Sequencing of Rectal Swabs for the Surveillance of Antimicrobial Resistant Organisms on the Illumina Miseq and Oxford MinION Platforms

PurposeAntimicrobial resistance (AMR) is a public health threat where efficient surveillance is needed to prevent outbreaks. Existing methods for detection of gastrointestinal colonization of multidrug-resistant organisms (MDRO) are limited to specific organisms or resistance mechanisms. Metagenomic next-generation sequencing (mNGS) is a more rapid and agnostic diagnostic approach for microbiome and resistome investigations. We determined if mNGS can detect MDRO from rectal swabs in concordance with standard microbiology results. MethodsWe performed and compared mNGS performance on short-read Illumina MiSeq (N=10) and long-read Nanopore MinION (N=4) platforms directly from peri-rectal swabs to detect vancomycin-resistant enterococci (VRE) and carbapenem-resistant Gram-negative organisms (CRO). ResultsWe detected E. faecium (N=8) and E. faecalis (N=2) with associated van genes (9/10) in concordance with VRE culture-based results. We studied the microbiome and identified CRO organisms, P. aeruginosa (N=1), E. cloacae (N=1), and KPC-producing K. pneumoniae (N=1). Nanopore real-time detection detected the blaKPC gene in 2.5 minutes and provided genetic context (blaKPC harbored on pKPC_Kp46 IncF plasmid). Illumina sequencing provided accurate allelic variant determination (i.e., blaKPC-2) and strain typing of the K. pneumoniae (ST-15). Conclusions: We demonstrated an agnostic approach for surveillance of MDRO, examining advantages of both short and long-read mNGS methods for AMR detection.

microbiology↗

KrakenHLL: Confident and fast metagenomics classification using unique k-mer counts

False positive identifications are a significant problem in metagenomic classification. We present KrakenHLL, a novel metagenomic classifier that combines the fast k-mer based classification of Kraken with an efficient algorithm for assessing the coverage of unique k-mers found in each species in a dataset. On various test datasets, KrakenHLL gives better recall and F1-scores than other methods, and effectively classifies and distinguishes pathogens with low abundance from false positives in infectious disease samples. By using the probabilistic cardinality estimator HyperLogLog (HLL), KrakenHLL is as fast as Kraken and requires little additional memory.

bioinformatics↗

Pavian: Interactive analysis of metagenomics data for microbiomics and pathogen identification

SummaryPavian is a web application for exploring metagenomics classification results, with a special focus on infectious disease diagnosis. Pinpointing pathogens in metagenomics classification results is often complicated by host and laboratory contaminants as well as many non-pathogenic microbiota. With Pavian, researchers can analyze, display and transform results from the Kraken and Centrifuge classifiers using interactive tables, heatmaps and flow diagrams. Pavian also provides an alignment viewer for validation of matches to a particular genome.\n\nAvailability and implementationPavian is implemented in the R language and based on the Shiny framework. It can be hosted on Windows, Mac OS X and Linux systems, and used with any contemporary web browser. It is freely available under a GPL-3 license from http://github.com/fbreitwieser/pavian. Furthermore a Docker image is provided at https://hub.docker.com/r/florianbw/pavian.\n\nContactfbreitw1@jhu.edu\n\nSupplementary informationSupplementary data is available at Bioinformatics online.

bioinformatics↗