Gebunden-freie Paarerzeugung in kombinierten Laser- und Coulombfeldern

In der vorliegenden Arbeit wird der Prozess der gebunden-freien Paarerzeugung von Elektronen und Positronen in kombinierten Laser- und Coulombfeldern untersucht. Es wird angenommen, dass ein relativistischer Ionenstrahl frontal mit einem intensiven Röntgenlaserstrahl kollidiert. Das Elektron-Positron-Paar wird durch simultane Absorption mehrerer Laserphotonen in einem nichtlinearen Prozess erzeugt. Der Einfang der Elektronen wird sowohl für den Grundzustand als auch für angeregte Zustände untersucht. Es wird die Prozesswahrscheinlichkeit im Rahmen der relativistischen Quantenmechanik berechnet. Für diesen nichtlinearen Prozess starker Laserfelder kann keine gewöhnliche Störungsentwicklung angewandt werden; stattdessen wird hier die Strong-Field-Approximation benutzt, welche den Einfluss des Coulombfelds auf das Positron vernachlässigt. Es werden ein analytisches Ergebnis für die Übergangsamplitude gefunden und numerische Ergebnisse für die Paarproduktionsraten mit Parametern des geplanten Röntgenlasers bei DESY vorgestellt. Hauptresultate sind, dass gebunden-freie Paarproduktion zu endlich hohen Raten führt, und diese von vergleichbarer Größenordnung wie für frei-freie Paarproduktion sind. In naher Zukunft wird die experimentelle Beobachtung des untersuchten Prozesses möglich sein

Translatability of WGS typing results can simplify data exchange for surveillance and control of Listeria monocytogenes

Where classical epidemiology has proven to be inadequate for surveillance and control of foodborne pathogens, molecular epidemiology, using genomic typing methods, can add value. However, the analysis of whole genome sequencing (WGS) data varies widely and is not yet fully harmonised. We used genomic data on 494 Listeria monocytogenes isolates from readyto- eat food products and food processing environments deposited in the strain collection of the German National Reference Laboratory to compare various procedures for WGS data analysis and to evaluate compatibility of results. Two different core genome multilocus sequence typing (cgMLST) schemes, different reference genomes in single nucleotide polymorphism (SNP) analysis and commercial as well as opensource software were compared. Correlation of allele distances from the different cgMLST approaches was high, ranging from 0.97 to 1, and unified thresholds yielded higher clustering concordance than schemespecific thresholds. The number of detected SNP differences could be increased up to a factor of 3.9 using a specific reference genome compared with a general one. Additionally, specific reference genomes improved comparability of SNP analysis results obtained using different software tools. The use of a closed or a draft specific reference genome did not make a difference. The harmonisation of WGS data analysis will finally guarantee seamless data exchange, but, in the meantime, knowledge on threshold values that lead to comparable clustering of isolates by different methods may improve communication between laboratories. We therefore established a translation code between commonly applied cgMLST and SNP methods based on optimised clustering concordances. This code can work as a first filter to identify WGS- based typing matches resulting from different methods, which opens up a new perspective for data exchange and thereby accelerates timecritical analyses, such as in outbreak investigations

Genetic and Phenotypic Virulence Potential of Non-O1/Non-O139 Vibrio cholerae Isolated from German Retail Seafood

Non-O1 and non-O139 Vibrio cholerae (NOVC) can cause gastrointestinal infections in humans. Contaminated food, especially seafood, is an important source of human infections. In this study, the virulence potential of 63 NOVC strains isolated from retail seafood were characterized at the genotypic and phenotypic levels. Although no strain encoded the cholera toxin (CTX) and the toxin-coregulated pilus (TCP), several virulence factors, including the HlyA hemolysin, the cholix toxin ChxA, the heat-stable enterotoxin Stn, and genes coding for the type 3 and type 6 secretion systems, were detected. All strains showed hemolytic activity against human and sheep erythrocytes: 90% (n = 57) formed a strong biofilm, 52% (n = 33) were highly motile at 37 °C, and only 8% (n = 5) and 14% (n = 9) could resist ≥60% and ≥40% human serum, respectively. Biofilm formation and toxin regulation genes were also detected. cgMLST analysis demonstrated that NOVC strains from seafood cluster with clinical NOVC strains. Antimicrobial susceptibility testing (AST) results in the identification of five strains that developed non-wildtype phenotypes (medium and resistant) against the substances of the classes of beta-lactams (including penicillin, carbapenem, and cephalosporin), polymyxins, and sulphonamides. The phenotypic resistance pattern could be partially attributed to the acquired resistance determinants identified via in silico analysis. Our results showed differences in the virulence potential of the analyzed NOVC isolated from retail seafood products, which may be considered for further pathogenicity evaluation and the risk assessment of NOVC isolates in future seafood monitoring

Outcome of Different Sequencing and Assembly Approaches on the Detection of Plasmids and Localization of Antimicrobial Resistance Genes in Commensal Escherichia coli

Antimicrobial resistance (AMR) is a major threat to public health worldwide. Currently, AMR typing changes from phenotypic testing to whole-genome sequence (WGS)-based detection of resistance determinants for a better understanding of the isolate diversity and elements involved in gene transmission (e.g., plasmids, bacteriophages, transposons). However, the use of WGS data in monitoring purposes requires suitable techniques, standardized parameters and approved guidelines for reliable AMR gene detection and prediction of their association with mobile genetic elements (plasmids). In this study, different sequencing and assembly strategies were tested for their suitability in AMR monitoring in Escherichia coli in the routines of the German National Reference Laboratory for Antimicrobial Resistances. To assess the outcomes of the different approaches, results from in silico predictions were compared with conventional phenotypic- and genotypic-typing data. With the focus on (fluoro)quinolone-resistant E.coli, five qnrS-positive isolates with multiple extrachromosomal elements were subjected to WGS with NextSeq (Illumina), PacBio (Pacific BioSciences) and ONT (Oxford Nanopore) for in depth characterization of the qnrS1-carrying plasmids. Raw reads from short- and long-read sequencing were assembled individually by Unicycler or Flye or a combination of both (hybrid assembly). The generated contigs were subjected to bioinformatics analysis. Based on the generated data, assembly of long-read sequences are error prone and can yield in a loss of small plasmid genomes. In contrast, short-read sequencing was shown to be insufficient for the prediction of a linkage of AMR genes (e.g., qnrS1) to specific plasmid sequences. Furthermore, short-read sequencing failed to detect certain duplications and was unsuitable for genome finishing. Overall, the hybrid assembly led to the most comprehensive typing results, especially in predicting associations of AMR genes and mobile genetic elements. Thus, the use of different sequencing technologies and hybrid assemblies currently represents the best approach for reliable AMR typing and risk assessment

Genetic characterization of a multidrug-resistant Salmonella enterica serovar Agona isolated from a dietary supplement in Germany

Salmonella enterica subsp. enterica serovar Agona has a history of causing food-borne outbreaks and any emergence of multidrug-resistant (MDR) isolates in novel food products is of concern. Particularly, in food products frequently consumed without sufficient heating prior to consumption. Here, we report about the MDR isolate, 18-SA00377, which had been isolated from a dietary supplement in Germany in 2018 and submitted to the German National Reference Laboratory for Salmonella. WGS-based comparative genetic analyses were conducted to find a potential reservoir of the isolate itself or mobile genetic elements associated with MDR. As a phylogenetic analysis did not yield any closely related S. Agona isolates, either globally or from Germany, a detailed analysis of the largest plasmid (295,499 bp) was performed as it is the main carrier of resistances. A combined approach of long-read and short-read sequencing enabled the assembly of the isolate’s chromosome and its four plasmids. Their characterization revealed the presence of 23 different antibiotic resistance genes (ARGs), conferring resistance to 12 different antibiotic drug classes, as well as genes conferring resistance to six different heavy metals. The largest plasmid, pSE18-SA00377-1, belongs to the IncHI2 plasmid family and carries 16 ARGs, that are organized as two distinct clusters, with each ARG associated with putative composite transposons. Through a two-pronged approach, highly similar plasmids to pSE18-SA00377-1 were identified in the NCBI database and a search for Salmonella isolates with a highly similar ARG resistance profile was conducted. Mapping and structural comparisons between pSE18-SA00377-1 and these plasmids and Salmonella isolates showed that both the plasmid backbone and identical or similar ARG clusters can be found not only in Salmonella isolates, originating mostly from a wide variety of livestock, but also in a diverse range of bacterial genera of varying geographical origins and isolation sources. Thus, it can be speculated that the host range of pSE18-SA00377-1 is not restricted to Salmonella and its spread already occurred in different bacterial populations. Overall, this hints at a complex history for pSE18-SA00377-1 and highlights the importance of surveilling multidrug-resistant S. enterica isolates, especially in novel food items that are not yet heavily regulated

Genomic Insights into the Mobilome and Resistome of Sentinel Microorganisms Originating from Farms of Two Different Swine Production Systems

[EN] Antimicrobial resistance (AMR) is a threat to public health due to long-term antimicrobial use (AMU), which promotes the bacterial acquisition of antimicrobial resistance determinants (ARDs). Within food-producing animals, organic and extensive Iberian swine production is based on sustainable and eco-friendly management systems, providing an excellent opportunity to evaluate how sustained differences in AMU impact the development and spread of AMR. Here, through a whole-genome sequencing approach, we provide an in-depth characterization of the resistome and mobilome and their interaction in 466 sentinel bacteria, namely, Escherichia coli, Enterococcus spp., Campylobacter coli, and Staphylococcus spp., recovered from 37 intensive and organic-extensive pig farms. Both ARDs and mobile genetic elements (MGEs) were primarily taxon-associated, with higher similarities among bacteria which were closely phylogenetically related. E. coli exhibited the most diverse resistome and mobilome, with 85.4% mobilizable ARDs, 50.3% of which were plasmid-associated. Staphylococcus spp. exhibited a broad repertoire of ARDs and MGEs, with 52.3% of its resistome being mobilizable. Although Enterococcus spp. carried the highest number of ARDs per isolate and its plasmidome was similar in size to that of E. coli, 43.7% of its resistome was mobilizable. A narrow spectrum of ARDs constituted the C. coli resistome, with point mutations as its main AMR driver. A constrained AMU, as observed in organic-extensive herds, determined a reduction in the quantitative composition of the resistome and the complexity of the resistome-mobilome interaction. These results demonstrate taxon-associated AMR-MGE interactions and evidence that responsible AMU can contribute to reducing AMR pressure in the food chainSIWe acknowledge the excellent technical assistance provided by Diana Molina, Lucía Pérez, and Clara Vega, the help with data management provided by Laura Uelze, and the help by Katharina Thomas and Beatrice Baumann in sequencing library preparation. We also thank the veterinary practitioners and farmers for their willingness to collaborate and, in particular, Álvaro Fernández-Blanco for his support in contacting the farms. O.M.-A. received a grant from the Spanish Government (Ministerio de Universidades), no. EST 19/00806, for a short stay at the German Federal Institute for Risk Assessment. O.M.-A. also holds a grant from the Spanish Government (Ministerio de Educación y Formación Profesional), no. FPU 16/03485. H.A. is financially supported by the “Beatriz Galindo” Program from the Spanish Government (Ministerio de Educación y Formación Profesional), no. BEAGAL-18-106. Study design was performed by A.C., H.A. and A.A.-O. Samples were prepared by O.M.-A. M.B. performed the whole-genome sequencing. C.D. performed the computational analyses, with contribution from J.F.C.-D. Statistical analyses were performed by O.M.-A. with contributions from C.D. and J.F.C.-D. B.M., H.A. and A.A.-O. provided technical and scientific support on the analysis. O.M.-A., H.A., A.C., A.A.-O., B.M., M.B. and C.D. participated in writing the manuscript or contributed to its revision. All authors revised the manuscript and approved the final versio

Transient Phenomena in Gene Expression after Induction of Transcription

When transcription of a gene is induced by a stimulus, the number of its mRNA molecules changes with time. Here we discuss how this time evolution depends on the shape of the mRNA lifetime distribution. Analysis of the statistical properties of this change reveals transient effects on polysomes, ribosomal profiles, and rate of protein synthesis. Our studies reveal that transient phenomena in gene expression strongly depend on the specific form of the mRNA lifetime distribution

Impact of wet-lab protocols on quality of whole-genome short-read sequences from foodborne microbial pathogens

For successful elucidation of a food-borne infection chain, the availability of high-quality sequencing data from suspected microbial contaminants is a prerequisite. Commonly, those investigations are a joint effort undertaken by different laboratories and institutes. To analyze the extent of variability introduced by differing wet-lab procedures on the quality of the sequence data we conducted an interlaboratory study, involving four bacterial pathogens, which account for the majority of food-related bacterial infections: Campylobacter spp., Shiga toxin-producing Escherichia coli, Listeria monocytogenes, and Salmonella enterica. The participants, ranging from German federal research institutes, federal state laboratories to universities and companies, were asked to follow their routine in-house protocols for short-read sequencing of 10 cultures and one isolated bacterial DNA per species. Sequence and assembly quality were then analyzed centrally. Variations within isolate samples were detected with SNP and cgMLST calling. Overall, we found that the quality of Illumina raw sequence data was high with little overall variability, with one exception, attributed to a specific library preparation kit. The variability of Ion Torrent data was higher, independent of the investigated species. For cgMLST and SNP analysis results, we found that technological sequencing artefacts could be reduced by the use of filters, and that SNP analysis was more suited than cgMLST to compare data of different contributors. Regarding the four species, a minority of Campylobacter isolate data showed the in comparison highest divergence with regard to sequence type and cgMLST analysis. We additionally compared the assembler SPAdes and SKESA for their performance on the Illumina data sets of the different species and library preparation methods and found overall similar assembly quality metrics and cgMLST statistics

PaPrBaG: A machine learning approach for the detection of novel pathogens from NGS data

The reliable detection of novel bacterial pathogens from next-generation sequencing data is a key challenge for microbial diagnostics. Current computational tools usually rely on sequence similarity and often fail to detect novel species when closely related genomes are unavailable or missing from the reference database. Here we present the machine learning based approach PaPrBaG (Pathogenicity Prediction for Bacterial Genomes). PaPrBaG overcomes genetic divergence by training on a wide range of species with known pathogenicity phenotype. To that end we compiled a comprehensive list of pathogenic and non-pathogenic bacteria with human host, using various genome metadata in conjunction with a rule-based protocol. A detailed comparative study reveals that PaPrBaG has several advantages over sequence similarity approaches. Most importantly, it always provides a prediction whereas other approaches discard a large number of sequencing reads with low similarity to currently known reference genomes. Furthermore, PaPrBaG remains reliable even at very low genomic coverages. CombiningPaPrBaG with existing approaches further improves prediction results