Search form

UZ Gent, medische microbiologie

Contact details
Traineeship proposition
Abstract
Testimony
Admin
Abstract advanced bachelor of bioinformatics 2019-2020: Establishing a diagnostic pipeline for cgMLST analysis of outbreak samples
 
One of the most threatening concerns for hospitals is the outbreak of multidrug resistant organisms. Colonized patients need to be kept in isolation to prevent the spreading of the bacteria and are at risk of developing infections such as bacteremia. Outbreak analysis is essential for risk assessment, outbreak management and forecasting in the hospital. Using Whole Genome Sequencing (WGS) the bacterial isolates can be characterized and the sequencing data (fastqs) can be used to determine the relation between different patient or environmental samples. This is done with core genome or whole genome multilocus sequence typing (cgMLST or wgMLST). Commercially available platforms to do the analysis come at great expenses and are often a black box. By generating an own pipeline the UZ Gent hospital can lower the expenses and acquire relevant knowhow. To perform cgMLST analysis and minimum spanning tree (MST) generation the analysis pipeline (“OUTB8-analysis v1.0”) was created in Nextflow (v20.01.0.5264), see figure 1. OUTB8-analysis accepts paired and single end fastq files and requires a chewBBACA compatible cgMLST scheme as input. The pipeline starts with a quality control step of the raw data (FastQC v0.11.9, MultiQC v1.8) and continues with adaptor and quality trimming (fastp v0.20.0) and subsequent quality analysis. A de novo assembly is generated (megahit v1.2.9) and checked for quality (MetaQUAST v5.0.2). The simple MLST-type is determined using the PubMLST database (mlst v2.19.0). Extra assemblies can be added to the analysis with the “assem” option. Optionally (option “x”) the pipeline is ran with the given assemblies only without executing previous prepping steps. Actual cgMLST analysis is performed with the chewBBACA software (v2.5.4). The resulting table (tsv-file) is cleaned up and send to an R script for the generation of a minimum spanning tree. This tree enables quick visual detection of outbreaks within the analyzed samples. cgMLST schemes are not freely available for all bacteria, accordingly the scheme pipeline “OUTB8-scheme v1.0” was developed. This pipeline created in Nextflow (v20.01.0.5264) generates a prodigal training file and an chewBBACA compatible wgMLST and cgMLST scheme based on a given txid. Because a set of reference assemblies is needed to perform cg/wgMLST scheme creation, the pipeline searches for an existing accession file in the local MLST-database or generates a new file from NCBI using esearch (v13.3). The number of assemblies used to generate the scheme can be limited with the option “count” if desired. Selected fasta files are downloaded with bit-dl-ncbi-assemblies. A prodigal (v2.6.3) training file is created from a generated multifasta. Next the wgMLST scheme is created using the reference assemblies with chewBBACA software (v2.5.4). After allele calling, paralogs are removed and quality is checked. The cgMLST scheme can be generated with all loci present in a chosen percentage of the reference assemblies (option “perc”, default 95%). The same pipeline can also be used to determine the txid of several fastq files. This is done with kraken2 (v2.0.8-beta) on mini-fastq files of 10,000 reads to reduce computational power. Both pipelines were tested on freely available data of Klebsiella pneumonia outbreaks. The pipelines have shown to be adaptable and easy to use. In short these two pipelines provide an easy an adaptable way of analyzing outbreak samples starting from raw fastq files. In the future the OUTB8-analysis pipeline will be improved by choice of assembler and addition of a scaffolder. Also the OUTB8-scheme pipeline will include the adaption of already existing schemes to chewBBACA compatible schemes. After further validation with locally available data of several bacteria species and version control the pipeline will be used in UZGent for bacterial outbreak management.
 
Samenvatting eindwerk 2014-2015: The Ex Vivo Sputum Model: evaluation of the eradication of Pseudomonas aeruginosa by testing antibacterial agents
Cystic Fibrosis (CF) is a severe autosomal recessive disease most common in Causasian populations. CF affects multiple organs and leads to a fatal prognosis due to a dysfunction of the Cystic Fibrosis Transmembrane conductance Regulator (CFTR) protein. Some mutations that affect the CFTR gene cause deregulation of ion transport and poor hydration of the airway surface liquid producing a viscous mucus layer on the airway surface of CF patients. This layer can easily be colonized by bacteria such as Pseudomonas aeruginosa due to a poor mucociliary clearance. The bacteria that colonize the lung of CF patients can acquire multidrug resistance due to genetic modifications and biofilm formation. In this experiment bacteriolysin, EDTA, pulmozyme and tobramycin were tested on the Ex Vivo Sputum Model to evaluate the effect of these agents on the biofilm destruction and eradication of P. aeruginosa. Culture of treated sputum, RT-qPCR and FISH were used to analyse the effect of these agents. A combination of EDTA and tobramycin was found to be most effective for the eradication of P. aerugniosa in the sputum of CF-patients. Sputum of several patients treated with bacteriolysin and pulmozyme had an increase in detected bacterial cells compared with the control sample (untreated sputum). Possibly these agents affect the biofilm structure and increase the metabolic activity of the more dormant bacteria deep within the biofilm. By adding bacteriolysin and pulmozyme to trigger the dormant bacteria to become more active, antibiotic treatments could be more effective. This is a hypothesis that needs to be further evaluated.
 

Address

C. Heymanslaan 10
9000 Gent
Belgium

Contacts

Traineeship supervisor
Mario Vaneeckhoute
Mario.Vaneechoutte@UGent.be
Traineeship supervisor
Bruno Verhasselt
09 332 22 26
bruno.verhasselt@uzgent.be
Zoekopdracht
Klassiek
Via Map