Katrine Grimstrup Joensen

Bio: Katrine Grimstrup Joensen is an academic researcher from Statens Serum Institut. The author has contributed to research in topics: Campylobacter jejuni & Campylobacter. The author has an hindex of 11, co-authored 18 publications receiving 1681 citations. Previous affiliations of Katrine Grimstrup Joensen include Technical University of Denmark.

Real-Time Whole-Genome Sequencing for Routine Typing, Surveillance, and Outbreak Detection of Verotoxigenic Escherichia coli

Abstract: Fast and accurate identification and typing of pathogens are essential for effective surveillance and outbreak detection. The current routine procedure is based on a variety of techniques, making the procedure laborious, time-consuming, and expensive. With whole-genome sequencing (WGS) becoming cheaper, it has huge potential in both diagnostics and routine surveillance. The aim of this study was to perform a real-time evaluation of WGS for routine typing and surveillance of verocytotoxin-producing Escherichia coli (VTEC). In Denmark, the Statens Serum Institut (SSI) routinely receives all suspected VTEC isolates. During a 7-week period in the fall of 2012, all incoming isolates were concurrently subjected to WGS using IonTorrent PGM. Real-time bioinformatics analysis was performed using web-tools (www.genomicepidemiology.org) for species determination, multilocus sequence type (MLST) typing, and determination of phylogenetic relationship, and a specific VirulenceFinder for detection of E. coli virulence genes was developed as part of this study. In total, 46 suspected VTEC isolates were characterized in parallel during the study. VirulenceFinder proved successful in detecting virulence genes included in routine typing, explicitly verocytotoxin 1 (vtx1), verocytotoxin 2 (vtx2), and intimin (eae), and also detected additional virulence genes. VirulenceFinder is also a robust method for assigning verocytotoxin (vtx) subtypes. A real-time clustering of isolates in agreement with the epidemiology was established from WGS, enabling discrimination between sporadic and outbreak isolates. Overall, WGS typing produced results faster and at a lower cost than the current routine. Therefore, WGS typing is a superior alternative to conventional typing strategies. This approach may also be applied to typing and surveillance of other pathogens.

Rapid and Easy In Silico Serotyping of Escherichia coli Isolates by Use of Whole-Genome Sequencing Data

Abstract: Accurate and rapid typing of pathogens is essential for effective surveillance and outbreak detection. Conventional serotyping of Escherichia coli is a delicate, laborious, time-consuming, and expensive procedure. With whole-genome sequencing (WGS) becoming cheaper, it has vast potential in routine typing and surveillance. The aim of this study was to establish a valid and publicly available tool for WGS-based in silico serotyping of E. coli applicable for routine typing and surveillance. A FASTA database of specific O-antigen processing system genes for O typing and flagellin genes for H typing was created as a component of the publicly available Web tools hosted by the Center for Genomic Epidemiology (CGE) (www.genomicepidemiology.org). All E. coli isolates available with WGS data and conventional serotype information were subjected to WGS-based serotyping employing this specific SerotypeFinder CGE tool. SerotypeFinder was evaluated on 682 E. coli genomes, 108 of which were sequenced for this study, where both the whole genome and the serotype were available. In total, 601 and 509 isolates were included for O and H typing, respectively. The O-antigen genes wzx , wzy , wzm , and wzt and the flagellin genes fliC , flkA , fllA , flmA , and flnA were detected in 569 and 508 genome sequences, respectively. SerotypeFinder for WGS-based O and H typing predicted 560 of 569 O types and 504 of 508 H types, consistent with conventional serotyping. In combination with other available WGS typing tools, E. coli serotyping can be performed solely from WGS data, providing faster and cheaper typing than current routine procedures and making WGS typing a superior alternative to conventional typing strategies.

PointFinder: a novel web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens.

Abstract: Background Antibiotic resistance is a major health problem, as drugs that were once highly effective no longer cure bacterial infections. WGS has previously been shown to be an alternative method for detecting horizontally acquired antimicrobial resistance genes. However, suitable bioinformatics methods that can provide easily interpretable, accurate and fast results for antimicrobial resistance associated with chromosomal point mutations are still lacking. Methods Phenotypic antimicrobial susceptibility tests were performed on 150 isolates covering three different bacterial species: Salmonella enterica, Escherichia coli and Campylobacter jejuni. The web-server ResFinder-2.1 was used to identify acquired antimicrobial resistance genes and two methods, the novel PointFinder (using BLAST) and an in-house method (mapping of raw WGS reads), were used to identify chromosomal point mutations. Results were compared with phenotypic antimicrobial susceptibility testing results. Results A total of 685 different phenotypic tests associated with chromosomal resistance to quinolones, polymyxin, rifampicin, macrolides and tetracyclines resulted in 98.4% concordance. Eleven cases of disagreement between tested and predicted susceptibility were observed: two C. jejuni isolates with phenotypic fluoroquinolone resistance and two with phenotypic erythromycin resistance and five colistin-susceptible E. coli isolates with a detected pmrB V161G mutation when assembled with Velvet, but not when using SPAdes or when mapping the reads. Conclusions PointFinder proved, with high concordance between phenotypic and predicted antimicrobial susceptibility, to be a user-friendly web tool for detection of chromosomal point mutations associated with antimicrobial resistance.

Applying the ResFinder and VirulenceFinder web-services for easy identification of acquired antibiotic resistance and E. coli virulence genes in bacteriophage and prophage nucleotide sequences

Abstract: Extensive research is currently being conducted on the use of bacteriophages for applications in human medicine, agriculture and food manufacturing. However, phages are important vehicles of horisontal gene transfer and play a significant role in bacterial evolution. As a result, concern has been raised that this increased use and dissemination of phages could result in spread of deleterious genes, e.g., antibiotic resistance and virulence genes. Meanwhile, in the wake of the genomic era, several tools have been developed for characterization of bacterial genomes. Here we describe how two of these tools, ResFinder and VirulenceFinder, can be used to identify acquired antibiotic resistance and virulence genes in phage genomes of interest. The general applicability of the tools is demonstrated on data sets of 1,642 phage genomes and 1,442 predicted prophages.

Redefining enteroaggregative Escherichia coli (EAEC): Genomic characterization of epidemiological EAEC strains.

Abstract: Although enteroaggregative E. coli (EAEC) has been implicated as a common cause of diarrhea in multiple settings, neither its essential genomic nature nor its role as an enteric pathogen are fully understood. The current definition of this pathotype requires demonstration of cellular adherence; a working molecular definition encompasses E. coli which do not harbor the heat-stable or heat-labile toxins of enterotoxigenic E. coli (ETEC) and harbor the genes aaiC, aggR, and/or aatA. In an effort to improve the definition of this pathotype, we report the most definitive characterization of the pan-genome of EAEC to date, applying comparative genomics and functional characterization on a collection of 97 EAEC strains isolated in the course of a multicenter case-control diarrhea study (Global Enteric Multi-Center Study, GEMS). Genomic analysis revealed that the EAEC strains mapped to all phylogenomic groups of E. coli. Circa 70% of strains harbored one of the five described AAF variants; there were no additional AAF variants identified, and strains that lacked an identifiable AAF generally did not have an otherwise complete AggR regulon. An exception was strains that harbored an ETEC colonization factor (CF) CS22, like AAF a member of the chaperone-usher family of adhesins, but not phylogenetically related to the AAF family. Of all genes scored, sepA yielded the strongest association with diarrhea (P = 0.002) followed by the increased serum survival gene, iss (p = 0.026), and the outer membrane protease gene ompT (p = 0.046). Notably, the EAEC genomes harbored several genes characteristically associated with other E. coli pathotypes. Our data suggest that a molecular definition of EAEC could comprise E. coli strains harboring AggR and a complete AAF(I-V) or CS22 gene cluster. Further, it is possible that strains meeting this definition could be both enteric bacteria and urinary/systemic pathogens.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Fast Tree: Computing Large Minimum-Evolution Trees with Profiles instead of a Distance Matrix

Abstract: Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement neighbor-joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest-neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N^2) space and O(N^2 L) time, but FastTree requires just O( NLa + N sqrt(N) ) memory and O( N sqrt(N) log(N) L a ) time. To estimate the tree's reliability, FastTree uses local bootstrapping, which gives another 100-fold speedup over a distance matrix. For example, FastTree computed a tree and support values for 158,022 distinct 16S ribosomal RNAs in 17 hours and 2.4 gigabytes of memory. Just computing pairwise Jukes-Cantor distances and storing them, without inferring a tree or bootstrapping, would require 17 hours and 50 gigabytes of memory. In simulations, FastTree was slightly more accurate than neighbor joining, BIONJ, or FastME; on genuine alignments, FastTree's topologies had higher likelihoods. FastTree is available at http://microbesonline.org/fasttree.

ResFinder 4.0 for predictions of phenotypes from genotypes.

Abstract: WGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output.

VFDB 2019: a comparative pathogenomic platform with an interactive web interface.

Abstract: The virulence factor database (VFDB, http://www.mgc.ac.cn/VFs/) is devoted to providing the scientific community with a comprehensive warehouse and online platform for deciphering bacterial pathogenesis. The various combinations, organizations and expressions of virulence factors (VFs) are responsible for the diverse clinical symptoms of pathogen infections. Currently, whole-genome sequencing is widely used to decode potential novel or variant pathogens both in emergent outbreaks and in routine clinical practice. However, the efficient characterization of pathogenomic compositions remains a challenge for microbiologists or physicians with limited bioinformatics skills. Therefore, we introduced to VFDB an integrated and automatic pipeline, VFanalyzer, to systematically identify known/potential VFs in complete/draft bacterial genomes. VFanalyzer first constructs orthologous groups within the query genome and preanalyzed reference genomes from VFDB to avoid potential false positives due to paralogs. Then, it conducts iterative and exhaustive sequence similarity searches among the hierarchical prebuilt datasets of VFDB to accurately identify potential untypical/strain-specific VFs. Finally, via a context-based data refinement process for VFs encoded by gene clusters, VFanalyzer can achieve relatively high specificity and sensitivity without manual curation. In addition, a thoroughly optimized interactive web interface is introduced to present VFanalyzer reports in comparative pathogenomic style for easy online analysis.

RefSeq: an update on prokaryotic genome annotation and curation.

Abstract: The Reference Sequence (RefSeq) project at the National Center for Biotechnology Information (NCBI) provides annotation for over 95 000 prokaryotic genomes that meet standards for sequence quality, completeness, and freedom from contamination. Genomes are annotated by a single Prokaryotic Genome Annotation Pipeline (PGAP) to provide users with a resource that is as consistent and accurate as possible. Notable recent changes include the development of a hierarchical evidence scheme, a new focus on curating annotation evidence sources, the addition and curation of protein profile hidden Markov models (HMMs), release of an updated pipeline (PGAP-4), and comprehensive re-annotation of RefSeq prokaryotic genomes. Antimicrobial resistance proteins have been reannotated comprehensively, improved structural annotation of insertion sequence transposases and selenoproteins is provided, curated complex domain architectures have given upgraded names to millions of multidomain proteins, and we introduce a new kind of annotation rule-BlastRules. Continual curation of supporting evidence, and propagation of improved names onto RefSeq proteins ensures that the functional annotation of genomes is kept current. An increasing share of our annotation now derives from HMMs and other sets of annotation rules that are portable by nature, and available for download and for reuse by other investigators. RefSeq is found at https://www.ncbi.nlm.nih.gov/refseq/.