Multilocus Sequence Typing of Aggregatibacter actinomycetemcomitans Competently Depicts the Population Structure of the Species

We developed a multilocus sequence typing scheme (MLST) for Aggregatibacter actinomycetemcomitans based on seven housekeeping genes, adk , atpG , frdB , mdh , pgi , recA , and zwf . A total of 188 strains of seven serotypes were separated into 57 sequence types.

CALIPSO Aerosol-Typing Scheme Misclassified Stratospheric Fire Smoke: Case Study From the 2019 Siberian Wildfire Season

In August 2019, a 4-km thick wildfire smoke layer was observed in the lower stratosphere over Leipzig, Germany, with a ground-based multiwavelength Raman lidar. The smoke was identified by the smoke-specific spectral dependence of the extinction-to-backscatter ratio (lidar ratio) measured with the Raman lidar. The spaceborne CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) detected the smoke and classified it as sulfate aerosol layer (originating from the Raikoke volcanic eruption). In this article, we discuss the reason for this misclassification. Two major sources for stratospheric air pollution were active in the summer of 2019 and complicated the CALIPSO aerosol typing effort. Besides intense forest fires at mid and high northern latitudes, the Raikoke volcano erupted in the Kuril Islands. We present two cases observed at Leipzig, one from July 2019 and one from August 2019. In July, pure volcanic sulfate aerosol layers were found in the lower stratosphere, while in August, wildfire smoke dominated in the height range up to 4–5 km above the local tropopause. In both cases, the CALIPSO aerosol typing scheme classified the layers as sulfate aerosol layers. The aerosol identification algorithm assumes non-spherical smoke particles in the stratosphere as consequence of fast lifting by pyrocumulonimbus convection. However, we hypothesize (based on presented simulations) that the smoke ascended as a results of self-lifting and reached the tropopause within 2–7 days after emission and finally entered the lower stratosphere as aged spherical smoke particles. These sphercial particles were then classified as liquid sulfate particles by the CALIPSO data analysis scheme. We also present a successful case of smoke identification by the CALIPSO retrieval method.

Development of a multiplex PCR short tandem repeat typing scheme for Candida krusei

Candida krusei is a human pathogenic yeast that can cause candidemia with the lowest 90-day survival rate in comparison to other Candida species. Infections occur frequently in immunocompromised patients and several C. krusei outbreaks in health care facilities have been described. Here, we developed a short tandem repeat (STR) typing scheme for C. krusei to allow for fast and cost-effective genotyping of an outbreak and compared identified relatedness of ten isolates to SNP calling from whole-genome sequencing (WGS). From a selection of 14 novel STR markers, six were used to develop two multiplex PCRs. Additionally, three previously reported markers were selected for a third multiplex PCR. In total, 119 C. krusei isolates were typed using these nine markers and 79 different genotypes were found. STR typing correlated well with WGS SNP typing, as isolates with the same STR genotype varied by 8 and 19 SNPs, while isolates that differed in all STR markers varied at least tens of thousands of SNPs. The STR typing assay was found to be specific for C. krusei , stable in 100 subcloned generations, and comparable to SNP calling by WGS. In summary, this newly developed C. krusei STR typing scheme is a fast, reliable, easy-to-interpret and cost-effective method compared to other typing methods. Moreover, the two newly developed multiplexes showed the same discriminatory power as all nine markers combined, indicating that multiplexes M3-1 and M9 are sufficient to type C. krusei .

Large-scale comparative genomics of Salmonella enterica to refine the organization of the global Salmonella population structure

1.AbstractSince the introduction of the White-Kauffmann-Le Minor (WKL) scheme for Salmonella serotyping, the nomenclature remains the most widely used for reporting the disease prevalence of Salmonella enterica across the globe. With the advent of whole genome sequencing (WGS), traditional serotyping has been increasingly replaced by in-silico methods that couple the detection of genetic variations in antigenic determinants with sequence-based typing. However, despite the integration of genomic-based typing by in-silico serotyping tools such as SeqSero2 and SISTR, in-silico serotyping in certain contexts remains ambiguous and insufficiently informative due to polyphyletic serovars. Furthermore, in spite of the widespread acknowledgement of polyphyly from genomic studies, the serotyping nomenclature remains unaltered. To prompt refinements to the Salmonella typing nomenclature for disease reporting, we herein performed a systematic characterization of putative polyphyletic serovars and the global Salmonella population structure by comparing 180,098 Salmonella genomes (representing 723 predicted serovars) from GenomeTrakr and PubMLST databases. We identified a range of core genome MLST typing thresholds that result in stable population structure, potentially suitable as the foundation of a genomic-based typing nomenclature for longitudinal surveillance. From the genomic comparisons of hundreds of predicted serovars, we demonstrated that in-silico serotyping classifications do not consistently reflect the population divergence observed at the genomic level. The organization of Salmonella subpopulations based on antigenic determinants can be confounded by homologous recombination and niche adaptation, resulting in shared classification of highly divergent genomes and misleading distinction between highly similar genomes. In consideration of the pivotal role of Salmonella serotyping, a compendium of putative polyphyletic serovars was compiled and made publicly available to provide additional context for future interpretations of in-silico serotyping results in disease surveillance settings. To refine the typing nomenclatures used in Salmonella surveillance reports, we foresee an improved typing scheme to be a hybrid that integrates both genomic and antigenic information such that the resolution from WGS is leveraged to improve the precision of subpopulation classifications while preserving the common names defined by the WKL scheme. Lastly, we stress the importance of controlled vocabulary integration for typing information in open data settings in order for the global Salmonella population dynamics to be fully trackable.2.Impact StatementSalmonella enterica (S. enterica) is a major foodborne pathogen responsible for an annual incidence rate of more than 90 million cases of foodborne illnesses worldwide. To surveil the high order Salmonella lineages, compare disease prevalence across jurisdictions worldwide, and inform risk assessments, in-silico serotyping has been established as the gold standard for typing the bacteria. However, despite previous Salmonella genomic studies reporting discordance between phylogenomic clades and serovars, refinements have yet been made to the serotyping scheme. Here, we analyzed over 180,000 Salmonella genomes representing 723 predicted serovars to subdivide the population into evolutionarily stable clusters in order to propose a stable organization of the Salmonella population structure that can form the basis of a genomic-based typing scheme for the pathogen. We described numerous instances in which genomes between serotypes are more similar than genomes within a serotype to reflect the inconsistencies of subpopulation classifications based on antigenic determinants. Moreover, we found inconsistencies between predicted serovars and reported serovars which highlighted potential errors in existing in-silico serotyping tools and the need to implement controlled vocabularies for reporting Salmonella subtypes in public databases. The findings of our study aim to motivate the future development of a standardized genomic-based typing nomenclature that more accurately captures the natural populations of S. enterica.3.Data SummaryThe assembly accession numbers of the genomes analyzed in this study (n = 204,952) and the associated metadata (e.g. sampling location, collection date, FTP address for retrieval) are documented in Table S1. The GenomeTrakr genomes were retrieved from the National Center for Biological Information GenBank database. The PubMLST genomes were retrieved using the BIGSdb API.

Population structure analysis and laboratory monitoring of Shigella with a standardised core-genome multilocus sequence typing scheme: a validation study

Background The laboratory surveillance of bacillary dysentery is based on a Shigella typing scheme standardised in the late 1940s. This scheme classifies Shigella strains into four serogroups and more than 50 serotypes on the basis of biochemical tests and lipopolysaccharide O-antigen serotyping. Real-time genomic surveillance of Shigella infections has been implemented in several countries, but without the use of a standardised high-resolution typing scheme. Methods We studied over 4,000 clinical isolates and reference strains of Shigella, covering all serotypes, including provisional serotypes and atypical strains, with the current serotyping scheme. These strains and isolates were also subjected to whole-genome sequencing and analysis with the EnteroBase Escherichia/Shigella 2,513-locus core-genome multilocus sequence typing scheme (cgMLST). Findings The Shigella genomes were grouped into eight phylogenetically distinct clusters, within the E. coli species. Three of these clusters contained strains from different serogroups and serotypes, the remaining five each consisting of a single serotype. The cgMLST hierarchical clustering (HC) analysis at different levels of resolution (HC2000 to HC400) recognised the natural groupings for Shigella. By contrast, the serotyping scheme was affected by horizontal gene transfer, leading to a conflation of genetically unrelated Shigella strains and a separation of some genetically related strains. We also curated the various provisional serotypes reported in the literature and described five new Shigella serotypes for addition to the typing scheme. Interpretation The EnteroBase Escherichia/Shigella cgMLST is a standardised, robust, portable, and high-resolution scheme that will enhance the laboratory surveillance of Shigella infections, particularly for Shigella flexneri. However, cgMLST data should be considered together with in silico serotyping data, to maintain backward compatibility with the current Shigella serotyping scheme.

Development and validation of a Burkholderia pseudomallei core genome multilocus sequence typing scheme to facilitate molecular surveillance

Objectives: Burkholderia pseudomallei causes the severe disease melioidosis. Whole genome-sequencing (WGS) based typing methods currently offer the highest resolution for molecular investigations of this genetically diverse pathogen. Still, its routine application in diagnostic laboratories is limited by the need for high computing power, bioinformatic skills and variable bioinformatic approaches, the latter affecting the results. We therefore aimed to establish and validate a WGS-based core genome multilocus sequence typing (cgMLST) scheme, applicable in routine diagnostic settings. Methods: A soft defined core genome was obtained by challenging the B. pseudomallei reference genome K96243 with 469 environmental and clinical genomes, resulting in 4,221 core and 1,359 accessory targets. The scheme was validated with 320 WGS datasets. We compared our novel typing scheme with single nucleotide polymorphism based-approaches investigating closely and distantly related strains. Finally, we applied our scheme for tracking the environmental source of a recent infection. Results: The validation of the scheme detected >95% good cgMLST target genes in 98.4% of the genomes. Comparison with existing typing methods revealed very good concordance. Our scheme proved to be applicable to investigate not only closely related strains, but also the global B. pseudomallei population structure. We successfully utilized our scheme to identify a sugar cane field as the presumable source of a recent melioidosis case. Conclusion: We developed a robust cgMLST typing scheme which integrates high resolution, maximized standardization and fast analysis for the non-bioinformatician. Our typing scheme has the potential to serve as a routinely applicable classification system in B. pseudomallei molecular epidemiology.

Establishment of a publicly available core genome multilocus sequence typing scheme for Clostridium perfringens

Clostridium perfringens is a spore-forming anaerobic pathogen responsible for a variety of histotoxic and intestinal infections in humans and animals. High-resolution genotyping aiming to identify bacteria at strain level has become increasingly important in modern microbiology to understand pathogen transmission pathways and to tackle infection sources. This study aimed at establishing a publicly available genome-wide multilocus sequence-typing scheme for C. perfringens. 1,431 highly conserved core genes (1.34 megabases; 50% of the reference genome genes) were indexed for a core-genome-based MLST scheme for C. perfringens. As an example, we applied the scheme to 87 poultry and 73 non-poultry strains (total=160). The genotyping results of the 160 genomes were congruent in terms of resolution and tree topology between allele-based and single-nucleotide-polymorphism-based core-genome typing. For the analysis of poultry strains of C. perfringens concerning the country of isolation, NetB-toxin gene carriage and clinical disease, we used 60 allelic differences as a clustering threshold. The results showed that poultry strains from a single country formed a cluster (n=17 clusters including 46 strains). Two clusters included six strains from four different countries. These strains were netB-positive, as were seven strains from Denmark and two strains from Finland, possibly indicating common sources of netB-positive strains. In terms of clinical presentation, different clusters of strains were associated with cases of suspected necrotic enteritis. Strains from sick birds grouped with strains from healthy birds or meat samples showing that potentially virulent strains are widespread and that host-related factors contribute significantly to NE. In summary, a publicly available scheme and an allele nomenclature database for genomic typing of C. perfringens has been established and can be used for broad-based and standardised epidemiological studies.

Characterisation of Phage Susceptibility Variation in Salmonellaenterica Serovar Typhimurium DT104 and DT104b

The surge in mortality and morbidity rates caused by multidrug-resistant (MDR) bacteria prompted a renewal of interest in bacteriophages (phages) as clinical therapeutics and natural biocontrol agents. Nevertheless, bacteria and phages are continually under the pressure of the evolutionary phage–host arms race for survival, which is mediated by co-evolving resistance mechanisms. In Anderson phage typing scheme of Salmonella Typhimurium, the epidemiologically related definitive phage types, DT104 and DT104b, display significantly different phage susceptibility profiles. This study aimed to characterise phage resistance mechanisms and genomic differences that may be responsible for the divergent phage reaction patterns in S. Typhimurium DT104 and DT104b using whole genome sequencing (WGS). The analysis of intact prophages, restriction–modification systems (RMS), plasmids and clustered regularly interspaced short palindromic repeats (CRISPRs), as well as CRISPR-associated proteins, revealed no unique genetic determinants that might explain the variation in phage susceptibility among the two phage types. Moreover, analysis of genes coding for potential phage receptors revealed no differences among DT104 and DT104b strains. However, the findings propose the need for experimental assessment of phage-specific receptors on the bacterial cell surface and analysis of bacterial transcriptome using RNA sequencing which will explain the differences in bacterial susceptibility to phages. Using Anderson phage typing scheme of Salmonella Typhimurium for the study of bacteria-phage interaction will help improving our understanding of host–phage interactions which will ultimately lead to the development of phage-based technologies, enabling effective infection control.