Deep integrative models for large-scale human genomics.

Polygenic risk scores (PRSs) are expected to play a critical role in precision medicine. Currently, PRS predictors are generally based on linear models using summary statistics, and more recently individual-level data. However, these predictors mainly capture additive relationships and are limited in data modalities they can use. We developed a deep learning framework (EIR) for PRS prediction which includes a model, genome-local-net (GLN), specifically designed for large-scale genomics data. The framework supports multi-task learning, automatic integration of other clinical and biochemical data, and model explainability. When applied to individual-level data from the UK Biobank, the GLN model demonstrated a competitive performance compared to established neural network architectures, particularly for certain traits, showcasing its potential in modeling complex genetic relationships. Furthermore, the GLN model outperformed linear PRS methods for Type 1 Diabetes, likely due to modeling non-additive genetic effects and epistasis. This was supported by our identification of widespread non-additive genetic effects and epistasis in the context of T1D. Finally, we constructed PRS models that integrated genotype, blood, urine, and anthropometric data and found that this improved performance for 93% of the 290 diseases and disorders considered. EIR is available at https://github.com/arnor-sigurdsson/EIR.

Sequencing and de novo assembly of 150 genomes from Denmark as a population reference.

Hundreds of thousands of human genomes are now being sequenced to characterize genetic variation and use this information to augment association mapping studies of complex disorders and other phenotypic traits. Genetic variation is identified mainly by mapping short reads to the reference genome or by performing local assembly. However, these approaches are biased against discovery of structural variants and variation in the more complex parts of the genome. Hence, large-scale de novo assembly is needed. Here we show that it is possible to construct excellent de novo assemblies from high-coverage sequencing with mate-pair libraries extending up to 20 kilobases. We report de novo assemblies of 150 individuals (50 trios) from the GenomeDenmark project. The quality of these assemblies is similar to those obtained using the more expensive long-read technology. We use the assemblies to identify a rich set of structural variants including many novel insertions and demonstrate how this variant catalogue enables further deciphering of known association mapping signals. We leverage the assemblies to provide 100 completely resolved major histocompatibility complex haplotypes and to resolve major parts of the Y chromosome. Our study provides a regional reference genome that we expect will improve the power of future association mapping studies and hence pave the way for precision medicine initiatives, which now are being launched in many countries including Denmark.

Chenopodium quinoa, a New Host for Alternaria Section Alternata and Alternaria Section Infectoriae Causing Yellow Leaf Blotch Disease.

Quinoa (Chenopodium quinoa Willd.) is a native American crop mainly grown in the Andes of Bolivia and Peru. During the last decades, the cultivation of quinoa has expanded to more than 125 countries. Since then, several diseases of quinoa have been characterized. A leaf disease was observed on quinoa plants growing in an experimental plot in Eastern Denmark in 2018. The symptoms produced by the associated fungi consisted of small yellow blotches on the upper surface of leaves with a pale chlorotic halo surrounding the lesion. These studies used a combination of morphology, molecular diagnostics, and pathogenicity tests to identify two different Alternaria species belonging to Alternaria sections Infectoriae and Alternata as the causal agent of observed disease symptoms. To the best of our knowledge, this is the first report of Alternaria spp. as foliar pathogens of quinoa. Our findings indicate the need for additional studies to determine potential risks to quinoa production.

Automated download and clean-up of family-specific databases for kmer-based virus identification.

SUMMARY: Here, we present an automated pipeline for Download Of NCBI Entries (DONE) and continuous updating of a local sequence database based on user-specified queries. The database can be created with either protein or nucleotide sequences containing all entries or complete genomes only. The pipeline can automatically clean the database by removing entries with matches to a database of user-specified sequence contaminants. The default contamination entries include sequences from the UniVec database of plasmids, marker genes and sequencing adapters from NCBI, an E.coli genome, rRNA sequences, vectors and satellite sequences. Furthermore, duplicates are removed and the database is automatically screened for sequences from green fluorescent protein, luciferase and antibiotic resistance genes that might be present in some GenBank viral entries, and could lead to false positives in virus identification. For utilizing the database, we present a useful opportunity for dealing with possible human contamination. We show the applicability of DONE by downloading a virus database comprising 37 virus families. We observed an average increase of 16 776 new entries downloaded per month for the 37 families. In addition, we demonstrate the utility of a custom database compared to a standard reference database for classifying both simulated and real sequence data. AVAILABILITYAND IMPLEMENTATION: The DONE pipeline for downloading and cleaning is deposited in a publicly available repository (https://bitbucket.org/genomicepidemiology/done/src/master/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic variation for tolerance to the downy mildew pathogen Peronospora variabilis in genetic resources of quinoa (Chenopodium quinoa).

BACKGROUND: Quinoa (Chenopodium quinoa Willd.) is an ancient grain crop that is tolerant to abiotic stress and has favorable nutritional properties. Downy mildew is the main disease of quinoa and is caused by infections of the biotrophic oomycete Peronospora variabilis Gaüm. Since the disease causes major yield losses, identifying sources of downy mildew tolerance in genetic resources and understanding its genetic basis are important goals in quinoa breeding. RESULTS: We infected 132 South American genotypes, three Danish cultivars and the weedy relative C. album with a single isolate of P. variabilis under greenhouse conditions and observed a large variation in disease traits like severity of infection, which ranged from 5 to 83%. Linear mixed models revealed a significant effect of genotypes on disease traits with high heritabilities (0.72 to 0.81). Factors like altitude at site of origin or seed saponin content did not correlate with mildew tolerance, but stomatal width was weakly correlated with severity of infection. Despite the strong genotypic effects on mildew tolerance, genome-wide association mapping with 88 genotypes failed to identify significant marker-trait associations indicating a polygenic architecture of mildew tolerance. CONCLUSIONS: The strong genetic effects on mildew tolerance allow to identify genetic resources, which are valuable sources of resistance in future quinoa breeding.

In Silico Genotyping of Escherichia coli Isolates for Extraintestinal Virulence Genes by Use of Whole-Genome Sequencing Data.

Extraintestinal pathogenic Escherichia coli (ExPEC) is the leading cause in humans of urinary tract infection and bacteremia. The previously published web tool VirulenceFinder (http://cge.cbs.dtu.dk/services/VirulenceFinder/) uses whole-genome sequencing (WGS) data for in silico characterization of E. coli isolates and enables researchers and clinical health personnel to quickly extract and interpret virulence-relevant information from WGS data. In this study, 38 ExPEC-associated virulence genes were added to the existing E. coli VirulenceFinder database. In total, 14,441 alleles were downloaded. A total of 1,890 distinct alleles were added to the database after removal of redundant sequences and analysis of the remaining alleles for open reading frames (ORFs). The database now contains 139 genes-of which 44 are related to ExPEC-and 2,826 corresponding alleles. Construction of the database included validation against 27 primer pairs from previous studies, a search for serotype-specific P fimbriae papA alleles, and a BLASTn confirmation of seven genes (etsC, iucC, kpsE, neuC, sitA, tcpC, and terC) not covered by the primers. The augmented database was evaluated using (i) a panel of nine control strains and (ii) 288 human-source E. coli strains classified by PCR as ExPEC and non-ExPEC. We observed very high concordance (average, 93.4%) between PCR and WGS findings, but WGS identified more alleles. In conclusion, the addition of 38 ExPEC-associated genes and the associated alleles to the E. coli VirulenceFinder database allows for a more complete characterization of E. coli isolates based on WGS data, which has become increasingly important considering the plasticity of the E. coli genome.

ResFinder 4.0 for predictions of phenotypes from genotypes.

OBJECTIVES: 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. METHODS: The ResFinder code was re-written to process raw reads and use Kmer-based alignment. The existing ResFinder and PointFinder databases were revised and expanded. Additional databases were developed including a genotype-to-phenotype key associating each AMR determinant with a phenotype at the antimicrobial compound level, and species-specific panels for in silico antibiograms. ResFinder 4.0 was validated using Escherichia coli (n = 584), Salmonella spp. (n = 1081), Campylobacter jejuni (n = 239), Enterococcus faecium (n = 106), Enterococcus faecalis (n = 50) and Staphylococcus aureus (n = 163) exhibiting different AST profiles, and from different human and animal sources and geographical origins. RESULTS: Genotype-phenotype concordance was ≥95% for 46/51 and 25/32 of the antimicrobial/species combinations evaluated for Gram-negative and Gram-positive bacteria, respectively. When genotype-phenotype concordance was <95%, discrepancies were mainly linked to criteria for interpretation of phenotypic tests and suboptimal sequence quality, and not to ResFinder 4.0 performance. CONCLUSIONS: WGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.

High-Throughput Sequencing-Based Investigation of Viruses in Human Cancers by Multienrichment Approach.

BACKGROUND: Viruses and other infectious agents cause more than 15% of human cancer cases. High-throughput sequencing-based studies of virus-cancer associations have mainly focused on cancer transcriptome data. METHODS: In this study, we applied a diverse selection of presequencing enrichment methods targeting all major viral groups, to characterize the viruses present in 197 samples from 18 sample types of cancerous origin. Using high-throughput sequencing, we generated 710 datasets constituting 57 billion sequencing reads. RESULTS: Detailed in silico investigation of the viral content, including exclusion of viral artefacts, from de novo assembled contigs and individual sequencing reads yielded a map of the viruses detected. Our data reveal a virome dominated by papillomaviruses, anelloviruses, herpesviruses, and parvoviruses. More than half of the included samples contained 1 or more viruses; however, no link between specific viruses and cancer types were found. CONCLUSIONS: Our study sheds light on viral presence in cancers and provides highly relevant virome data for future reference.

Using WGS to identify antibiotic resistance genes and predict antimicrobial resistance phenotypes in MDR Acinetobacter baumannii in Tanzania.

BACKGROUND: Reliable phenotypic antimicrobial susceptibility testing can be a challenge in clinical settings in low- and middle-income countries. WGS is a promising approach to enhance current capabilities. AIM: To study diversity and resistance determinants and to predict and compare resistance patterns from WGS data of Acinetobacter baumannii with phenotypic results from classical microbiological testing at a tertiary care hospital in Tanzania. METHODS AND RESULTS: MLST using Pasteur/Oxford schemes yielded eight different STs from each scheme. Of the eight, two STs were identified to be global clones 1 (n = 4) and 2 (n = 1) as per the Pasteur scheme. Resistance testing using classical microbiology determined between 50% and 92.9% resistance across all drugs. Percentage agreement between phenotypic and genotypic prediction of resistance ranged between 57.1% and 100%, with coefficient of agreement (κ) between 0.05 and 1. Seven isolates harboured mutations at significant loci (S81L in gyrA and S84L in parC). A number of novel plasmids were detected, including pKCRI-309C-1 (219000 bp) carrying 10 resistance genes, pKCRI-43-1 (34935 bp) carrying two resistance genes and pKCRI-49-1 (11681 bp) and pKCRI-28-1 (29606 bp), each carrying three resistance genes. New ampC alleles detected included ampC-69, ampC-70 and ampC-71. Global clone 1 and 2 isolates were found to harbour ISAba1 directly upstream of the ampC gene. Finally, SNP-based phylogenetic analysis of the A. baumannii isolates revealed closely related isolates in three clusters. CONCLUSIONS: The validity of the use of WGS in the prediction of phenotypic resistance can be appreciated, but at this stage is not sufficient for it to replace conventional antimicrobial susceptibility testing in our setting.

LRE-Finder, a Web tool for detection of the 23S rRNA mutations and the optrA, cfr, cfr(B) and poxtA genes encoding linezolid resistance in enterococci from whole-genome sequences.

OBJECTIVES: In enterococci, resistance to linezolid is often mediated by mutations in the V domain of the 23S rRNA gene (G2576T or G2505A). Furthermore, four genes [optrA, cfr, cfr(B) and poxtA] encode linezolid resistance in enterococci. We aimed to develop a Web tool for detection of the two mutations and the four genes encoding linezolid resistance in enterococci from whole-genome sequence data. METHODS: LRE-Finder (where LRE stands for linezolid-resistant enterococci) detected the fraction of Ts in position 2576 and the fraction of As in position 2505 of the 23S rRNA and the cfr, cfr(B), optrA and poxtA genes by aligning raw sequencing reads (fastq format) with k-mer alignment. For evaluation, fastq files from 21 LRE isolates were submitted to LRE-Finder. As negative controls, fastq files from 1473 non-LRE isolates were submitted to LRE-Finder. The MICs of linezolid were determined for the 21 LRE isolates. As LRE-negative controls, 26 VRE isolates were additionally selected for linezolid MIC determination. RESULTS: LRE-Finder was validated and showed 100% concordance with phenotypic susceptibility testing. A cut-off of 10% mutations in position 2576 and/or position 2505 was set in LRE-Finder for predicting a linezolid resistance phenotype. This cut-off allows for detection of a single mutated 23S allele in both Enterococcus faecalis and Enterococcus faecium, while ignoring low-level sequencing noise. CONCLUSIONS: A Web tool for detection of the 23S rRNA mutations (G2576T and G2505A) and the optrA, cfr, cfr(B) and poxtA genes from whole-genome sequences from enterococci is now available online.

Proof of concept: used malaria rapid diagnostic tests applied for parallel sequencing for surveillance of molecular markers of anti-malarial resistance in Bissau, Guinea-Bissau during 2014-2017.

BACKGROUND: Large-scale surveillance of molecular markers of anti-malarial drug resistance is an attractive method of resistance monitoring, to complement therapeutic efficacy studies in settings where the latter are logistically challenging. METHODS: Between 2014 and 2017, this study sampled malaria rapid diagnostic tests (RDTs), used in routine clinical care, from two health centres in Bissau, Guinea-Bissau. In order to obtain epidemiological insights, RDTs were collected together with patient data on age and sex. A subset of positive RDTs from one of the two sites (n = 2184) were tested for Plasmodium DNA content. Those testing positive for Plasmodium DNA by PCR (n = 1390) were used for library preparation, custom designed dual indexing and next generation Miseq targeted sequencing of Plasmodium falciparum genes pfcrt, pfmdr1, pfdhfr, pfdhps and pfk13. RESULTS: The study found a high frequency of the pfmdr1 codon 86N at 88-97%, a significant decrease of the pfcrt wildtype CVMNK haplotype and elevated levels of the pfdhfr/pfdhps quadruple mutant ranging from 33 to 51% between 2014 and 2017. No polymorphisms indicating artemisinin tolerance were discovered. The demographic data indicate a large proportion of young adults (66%, interquartile range 11-28 years) presenting with P. falciparum infections. While a total of 5532 gene fragments were successfully analysed on a single Illumina Miseq flow cell, PCR-positivity from the library preparation varied considerably from 13 to 87% for different amplicons. Furthermore, pre-screening of samples for Plasmodium DNA content proved necessary prior to library preparation. CONCLUSIONS: This study serves as a proof of concept for using leftover clinical material (used RDTs) for large-scale molecular surveillance, encompassing the inherent complications regarding to methodology and analysis when doing so. Factors such as RDT storage prior to DNA extraction and parasitaemia of the infection are likely to have an effect on whether or not parasite DNA can be successfully analysed, and are considered part of the reason the data yield is suboptimal. However, given the necessity of molecular surveillance of anti-malarial resistance in settings where poor infrastructure, poor economy, lack of educated staff and even surges of political instability remain major obstacles to performing clinical studies, obtaining the necessary data from used RDTs, despite suboptimal output, becomes a feasible, affordable and hence a justifiable method.

Rapid and precise alignment of raw reads against redundant databases with KMA.

BACKGROUND: As the cost of sequencing has declined, clinical diagnostics based on next generation sequencing (NGS) have become reality. Diagnostics based on sequencing will require rapid and precise mapping against redundant databases because some of the most important determinants, such as antimicrobial resistance and core genome multilocus sequence typing (MLST) alleles, are highly similar to one another. In order to facilitate this, a novel mapping method, KMA (k-mer alignment), was designed. KMA is able to map raw reads directly against redundant databases, it also scales well for large redundant databases. KMA uses k-mer seeding to speed up mapping and the Needleman-Wunsch algorithm to accurately align extensions from k-mer seeds. Multi-mapping reads are resolved using a novel sorting scheme (ConClave scheme), ensuring an accurate selection of templates. RESULTS: The functionality of KMA was compared with SRST2, MGmapper, BWA-MEM, Bowtie2, Minimap2 and Salmon, using both simulated data and a dataset of Escherichia coli mapped against resistance genes and core genome MLST alleles. KMA outperforms current methods with respect to both accuracy and speed, while using a comparable amount of memory. CONCLUSION: With KMA, it was possible map raw reads directly against redundant databases with high accuracy, speed and memory efficiency.

RUCS: rapid identification of PCR primers for unique core sequences.

MOTIVATION: Designing PCR primers to target a specific selection of whole genome sequenced strains can be a long, arduous and sometimes impractical task. Such tasks would benefit greatly from an automated tool to both identify unique targets, and to validate the vast number of potential primer pairs for the targets in silico. RESULTS: Here we present RUCS, a program that will find PCR primer pairs and probes for the unique core sequences of a positive genome dataset complement to a negative genome dataset. The resulting primer pairs and probes are in addition to simple selection also validated through a complex in silico PCR simulation. We compared our method, which identifies the unique core sequences, against an existing tool called ssGeneFinder, and found that our method was 6.5-20 times more sensitive. We used RUCS to design primer pairs that would target a set of genomes known to contain the mcr-1 colistin resistance gene. Three of the predicted pairs were chosen for experimental validation using PCR and gel electrophoresis. All three pairs successfully produced an amplicon with the target length for the samples containing mcr-1 and no amplification products were produced for the negative samples. The novel methods presented in this manuscript can reduce the time needed to identify target sequences, and provide a quick virtual PCR validation to eliminate time wasted on ambiguously binding primers. AVAILABILITY AND IMPLEMENTATION: Source code is freely available on https://bitbucket.org/genomicepidemiology/rucs. Web service is freely available on https://cge.cbs.dtu.dk/services/RUCS. CONTACT: mcft@cbs.dtu.dk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Direct whole-genome sequencing of Plasmodium falciparum specimens from dried erythrocyte spots.

BACKGROUND: Plasmodium falciparum malaria remains a major health burden and genomic research represents one of the necessary approaches for continued progress towards malaria control and elimination. Sample acquisition for this purpose is troublesome, with the majority of malaria-infected individuals living in rural areas, away from main infrastructure and the electrical grid. The aim of this study was to describe a low-tech procedure to sample P. falciparum specimens for direct whole genome sequencing (WGS), without use of electricity and cold-chain. METHODS: Venous blood samples were collected from malaria patients in Bandim, Guinea-Bissau and leukocyte-depleted using Plasmodipur filters, the enriched parasite sample was spotted on Whatman paper and dried. The samples were stored at ambient temperatures and subsequently used for DNA-extraction. Ratios of parasite:human content of the extracted DNA was assessed by qPCR, and five samples with varying parasitaemia, were sequenced. Sequencing data were used to analyse the sample content, as well as sample coverage and depth as compared to the 3d7 reference genome. RESULTS: qPCR revealed that 73% of the 199 samples were applicable for WGS, as defined by a minimum ratio of parasite:human DNA of 2:1. WGS revealed an even distribution of sequence data across the 3d7 reference genome, regardless of parasitaemia. The acquired read depths varied from 16 to 99×, and coverage varied from 87.5 to 98.9% of the 3d7 reference genome. SNP-analysis of six genes, for which amplicon sequencing has been performed previously, confirmed the reliability of the WGS-data. CONCLUSION: This study describes a simple filter paper based protocol for sampling P. falciparum from malaria patients for subsequent direct WGS, enabling acquisition of samples in remote settings with no access to electricity.

Molecular epidemiology of virulence and antimicrobial resistance determinants in Klebsiella pneumoniae from hospitalised patients in Kilimanjaro, Tanzania.

This study aimed to use whole-genome sequencing to determine virulence and antimicrobial resistance genes in K. pneumoniae isolated from patients in a tertiary care hospital in Kilimanjaro. K. pneumoniae isolates from patients attending Kilimanjaro Christian Medical Centre between August 2013 and August 2015 were fully genome-sequenced and analysed locally. Sequence analysis was done for identification of virulence and AMR genes. Plasmid and multi-locus sequence typing and capsular or capsular (K) typing were performed and phylogeny was done to ascertain K. pneumoniae relatedness. Stata 13 (College Station, TX, 77845, USA) was used to determine Cohen's kappa coefficient of agreement between the phenotypically tested and sequence-predicted resistance. A total of 16 (47.1%) sequence types (STs) and 10 (29.4%) K types were identified in 30 (88.2%) and 17 (50.0%) of all analysed isolates, respectively. K. pneumoniae ST17 were 6 (17.6%). The commonest determinants were blaCTX-M-15 in 16 (47.1%) isolates, blaSHV in 30 (88.2%), blaOXA-1 in 8 (23.5%) and blaTEM-1 in 18 (52.9%) isolates. Resistance genes for aminoglycosides were detected in 21 (61.8%) isolates, fluoroquinolones in 13 (38.2%) and quinolones 34 (100%). Ceftazidime and ceftriaxone showed the strongest agreement between phenotype- and sequence-based resistance results: 93.8%, kappa = 0.87 and p = 0.0002. Yersiniabactin determinant was detected in 12 (35.3%) of K. pneumoniae. The proportion of AMR and virulence determinants detected in K. pneumoniae is alarming. WGS-based diagnostic approach has showed promising potentials in clinical microbiology, hospital outbreak source tracing virulence and AMR detection at KCMC.

Prevalence and risk factors for CTX-M gram-negative bacteria in hospitalized patients at a tertiary care hospital in Kilimanjaro, Tanzania.

Emergence and spread of extended spectrum beta-lactamase (ESBL)-producing gram-negative bacteria, mainly due to CTX-M, is a major global public health problem. Patients infected with ESBL-producing gram-negative bacteria have an increased risk of treatment failure and death. We investigated the prevalence and risk factors for CTX-M gram-negative bacteria isolated from clinical specimens of patients hospitalized at a tertiary care hospital in Kilimanjaro, Tanzania. Isolated gram-negative bacteria from inpatients admitted at Kilimanjaro Christian Medical Centre (KCMC) between August 2013 and August 2015 were fully genome sequenced. The prevalence of ESBL-producing gram-negative bacteria was determined based on the presence of blaCTX-M. The odds ratio (OR) and risk factors for ESBL-producing gram-negative bacteria due to CTX-M were assessed using logistic regression models. The overall CTX-M prevalence (95% CI) was 13.6% (10.1-18.1). Adjusted for other factors, the OR of CTX-M gram-negative bacteria for patients previously hospitalized was 0.26 (0.08-0.88), p = 0.031; the OR for patients currently on antibiotics was 4.02 (1.29-12.58), p = 0.017; the OR for patients currently on ceftriaxone was 0.14 (0.04-0.46), p = 0.001; and the OR for patients with wound infections was 0.24 (0.09-0.61), p = 0.003. The prevalence of ESBL-producing gram-negative bacteria due to CTX-M in this setting is relatively low compared to other previous reports in similar settings. However, to properly stop further spread in the hospital, we recommend setting up a hospital surveillance system that takes full advantage of the available next-generation sequencing facility to routinely screen for all types of bacterial resistance genes.

Qualitative analysis of MMI raters' scorings of medical school candidates: A matter of taste?

Recent years have seen leading medical educationalists repeatedly call for a paradigm shift in the way we view, value and use subjectivity in assessment. The argument is that subjective expert raters generally bring desired quality, not just noise, to performance evaluations. While several reviews document the psychometric qualities of the Multiple Mini-Interview (MMI), we currently lack qualitative studies examining what we can learn from MMI raters' subjectivity. The present qualitative study therefore investigates rater subjectivity or taste in MMI selection interview. Taste (Bourdieu 1984) is a practical sense, which makes it possible at a pre-reflective level to apply 'invisible' or 'tacit' categories of perception for distinguishing between good and bad. The study draws on data from explorative in-depth interviews with 12 purposefully selected MMI raters. We find that MMI raters spontaneously applied subjective criteria-their taste-enabling them to assess the candidates' interpersonal attributes and to predict the candidates' potential. In addition, MMI raters seemed to share a taste for certain qualities in the candidates (e.g. reflectivity, resilience, empathy, contact, alikeness, 'the good colleague'); hence, taste may be the result of an ongoing enculturation in medical education and healthcare systems. This study suggests that taste is an inevitable condition in the assessment of students' performance. The MMI set-up should therefore make room for MMI raters' taste and their connoisseurship, i.e. their ability to taste, to improve the quality of their assessment of medical school candidates.

Bacterial whole genome-based phylogeny: construction of a new benchmarking dataset and assessment of some existing methods.

BACKGROUND: Whole genome sequencing (WGS) is increasingly used in diagnostics and surveillance of infectious diseases. A major application for WGS is to use the data for identifying outbreak clusters, and there is therefore a need for methods that can accurately and efficiently infer phylogenies from sequencing reads. In the present study we describe a new dataset that we have created for the purpose of benchmarking such WGS-based methods for epidemiological data, and also present an analysis where we use the data to compare the performance of some current methods. RESULTS: Our aim was to create a benchmark data set that mimics sequencing data of the sort that might be collected during an outbreak of an infectious disease. This was achieved by letting an E. coli hypermutator strain grow in the lab for 8 consecutive days, each day splitting the culture in two while also collecting samples for sequencing. The result is a data set consisting of 101 whole genome sequences with known phylogenetic relationship. Among the sequenced samples 51 correspond to internal nodes in the phylogeny because they are ancestral, while the remaining 50 correspond to leaves. We also used the newly created data set to compare three different online available methods that infer phylogenies from whole-genome sequencing reads: NDtree, CSI Phylogeny and REALPHY. One complication when comparing the output of these methods with the known phylogeny is that phylogenetic methods typically build trees where all observed sequences are placed as leafs, even though some of them are in fact ancestral. We therefore devised a method for post processing the inferred trees by collapsing short branches (thus relocating some leafs to internal nodes), and also present two new measures of tree similarity that takes into account the identity of both internal and leaf nodes. CONCLUSIONS: Based on this analysis we find that, among the investigated methods, CSI Phylogeny had the best performance, correctly identifying 73% of all branches in the tree and 71% of all clades. We have made all data from this experiment (raw sequencing reads, consensus whole-genome sequences, as well as descriptions of the known phylogeny in a variety of formats) publicly available, with the hope that other groups may find this data useful for benchmarking and exploring the performance of epidemiological methods. All data is freely available at: https://cge.cbs.dtu.dk/services/evolution_data.php .

Development of a Web Tool for Escherichia coli Subtyping Based on fimH Alleles.

The aim of this study was to construct a valid publicly available method for in silico fimH subtyping of Escherichia coli particularly suitable for differentiation of fine-resolution subgroups within clonal groups defined by standard multilocus sequence typing (MLST). FimTyper was constructed as a FASTA database containing all currently known fimH alleles. The software source code is publicly available at https://bitbucket.org/genomicepidemiology/fimtyper, the database is freely available at https://bitbucket.org/genomicepidemiology/fimtyper_db, and a service implementing the software is available at https://cge.cbs.dtu.dk/services/FimTyper FimTyper was validated on three data sets: one containing Sanger sequences of fimH alleles of 42 E. coli isolates generated prior to the current study (data set 1), one containing whole-genome sequence (WGS) data of 243 third-generation-cephalosporin-resistant E. coli isolates (data set 2), and one containing a randomly chosen subset of 40 E. coli isolates from data set 2 that were subjected to conventional fimH subtyping (data set 3). The combination of the three data sets enabled an evaluation and comparison of FimTyper on both Sanger sequences and WGS data. FimTyper correctly predicted all 42 fimH subtypes from the Sanger sequences from data set 1 and successfully analyzed all 243 draft genomes from data set 2. FimTyper subtyping of the Sanger sequences and WGS data from data set 3 were in complete agreement. Additionally, fimH subtyping was evaluated on a phylogenetic network of 122 sequence type 131 (ST131) E. coli isolates. There was perfect concordance between the typology and fimH-based subclones within ST131, with accurate identification of the pandemic multidrug-resistant clonal subgroup ST131-H30. FimTyper provides a standardized tool, as a rapid alternative to conventional fimH subtyping, highly suitable for surveillance and outbreak detection.

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

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.