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The Beijing strain is one of the most successful genotypes of Mycobacterium tuberculosis worldwide and appears to be highly homogenous according to existing genotyping methods. To type Beijing strains reliably we developed a robust typing scheme using single nucleotide polymorphisms (SNPs) and regions of difference (RDs) derived from whole-genome sequencing data of eight Beijing strains. SNP/RD typing of 259 M. tuberculosis isolates originating from 45 countries worldwide discriminated 27 clonal complexes within the Beijing genotype family. A total of 16 Beijing clonal complexes contained more than one isolate of known origin, of which two clonal complexes were strongly associated with South African origin. The remaining 14 clonal complexes encompassed isolates from different countries. Even highly resolved clonal complexes comprised isolates from distinct geographical sites. Our results suggest that Beijing strains spread globally on multiple occasions and that the tuberculosis epidemic caused by the Beijing genotype is at least partially driven by modern migration patterns. The SNPs and RDs presented in this study will facilitate future molecular epidemiological and phylogenetic studies on Beijing strains.

Whole genome sequencing (WGS) is widely used for outbreak analysis of bacteriology and virology but is scarcely used in mycology. Here, we used WGS for genotyping Aspergillus fumigatus isolates from a potential Aspergillus outbreak in an intensive care unit (ICU) during construction work. After detecting the outbreak, fungal cultures were performed on all surveillance and/or patient respiratory samples. Environmental samples were obtained throughout the ICU. WGS was performed on 30 isolates, of which six patient samples and four environmental samples were related to the outbreak, and twenty samples were unrelated, using the Illumina NextSeq 550. A SNP-based phylogenetic tree was created from outbreak samples and unrelated samples. Comparative analysis (WGS and short tandem repeats (STRs), microsatellite loci analysis) showed that none of the strains were related to each other. The lack of genetic similarity suggests the accumulation of Aspergillus spores in the hospital environment, rather than a single source that supported growth and reproduction of Aspergillus fumigatus. This supports the hypothesis that the Aspergillus outbreak was likely caused by release of Aspergillus fumigatus spores during construction work. Indeed, no new Aspergillus cases were observed in the ICU after cessation of construction. This study demonstrates that WGS is a suitable technique for examining inter-strain relatedness of Aspergillus fumigatus in the setting of an outbreak investigation.

Abstract Background We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the methods used, the genetic differences between the genera Shigella and Escherichia were used as control. Results The isolates obtained were representative of the population structure encountered in other Western European countries. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. Our benchmark characteristic, genus, resulted in eight associated genes and > 3,000,000 k-mers, indicating adequate performance of the algorithms used. Conclusions To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC.

Francisella tularensis is a zoonotic bacterium that is endemic in large parts of the world. It is absent in the standard library of the most applied matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) systems: the Vitek MS and the Bruker Biotyper system. The additional Bruker MALDI Biotyper Security library contains F. tularensis without subspecies differentiation. The virulence of F. tularensis differs between the subspecies. The F. tularensis subspecies (ssp.) tularensis is highly pathogenic, whereas the subspecies holarctica displays lower virulence and subspecies novicida and F. tularensis ssp. mediasiatica are hardly virulent. To differentiate the Francisellaceae and the F. tularensis-subspecies, an in-house Francisella library was built with the Bruker Biotyper system and validated together with the existing Bruker databases. In addition, specific biomarkers were defined based on the main spectra of the Francisella strains supplemented with in silico genome data. Our in-house Francisella library accurately differentiates the F. tularensis subspecies and the other Francisellaceae. The biomarkers correctly differentiate the various species within the genus Francisella and the F. tularensis subspecies. These MALDI-TOF MS strategies can successfully be applied in a clinical laboratory setting as a fast and specific method to identify F. tularensis to subspecies level.