Prolonged carriage of OXA-244-carbapenemase-producing Escherichia coli complicates epidemiological investigations.

The rapid increase of OXA-244-producing Escherichia coli, predominantly driven by genetically clustered isolates of sequence type (ST)38, has been observed in at least nine European countries, including Germany. However, the reasons for the spread of OXA-244-producing E. coli remain unclear. Here, we aim to evaluate the possibility of prolonged carriage. We identified a total of six different patients with repeated detection of OXA-244-producing E. coli isolates, which were subjected to both short and long-read whole-genome sequencing (WGS). Besides allelic differences using core genome multilocus sequence typing (cgMLST) analyses, we obtained numbers of single-nucleotide polymorphisms (SNPs) to calculate individual base-pair substitution (BPS) rates. To assess possible re-exposure and risk factors for prolonged carriage, case interviews were conducted. The time between detections ranged from eleven months to more than three years. Initial isolates originated in three+ out of six cases from clinical samples, whereas remaining samples were from screening, mostly in the inpatient setting. As expected, cgMLST analyses showed low numbers of allelic differences between isolates of each case ranging from 1 to 4, whereas numbers of SNPs were between 2 and 99 (mean = 36), thus clearly highlighting the discrepancy between these different bacterial typing approaches. For five out of six cases, observed BPS rates suggest that patients can be colonized with OXA-244-producing E. coli, including ST38 cluster isolates, for extensively long times. Thus, we may have previously missed the epidemiological link between cases because exposure to OXA-244-producing E. coli could have occurred in a time frame, which has not been evaluated in previous investigations. Our results may help to guide future epidemiological investigations as well as to support the interpretation of genetic diversity of OXA-244-producing E. coli, particularly among ST38 cluster isolates.

Surgical Experience Affects the Outcome of Central Venous Access Catheter Implantation in Children: A Retrospective Cohort Study.

INTRODUCTION: Surgical complications occur in up to third of children, limiting the benefits of tunneled central venous catheters (tCVCs) in children. We aimed to identify risk factors for complications related to catheter implantation. METHODS: All children and adolescents undergoing tCVC implantation at a single center over a period of 9 years were analyzed. Infection, thrombosis, dislocation, and catheter dysfunction were defined as complications. Both patient-related (ie, age, sex, vessel characteristics, revision surgery) and surgical factors (ie, sex of surgeon, surgical experience) were analyzed for their association with complications. RESULTS: A total of 1024 catheters were inserted, 887 ports and 137 broviac catheters. In terms of patient-related factors, Broviac catheters, and nononcological patients had a higher complication rate. The use of the internal jugular vein and revision surgery was associated with significantly increased complications in patients with port catheters. Experience of the surgeon correlated with various outcome parameters. Implantation performed by an attending were associated with lower complication rates in comparison to those performed by residents. Within the resident group, insertions performed by experienced residents had more complications compared with those performed by residents during their first years. CONCLUSION: The study suggests that the outcome of tCVCs insertion is affected by the type of catheter used, the utilized vessel and above all by surgical experience. Residents had significantly increased complication rates in comparison to board-certified surgeons and amongst resident's outcome got worse with increasing experience of the residents. The presence of an experienced attending did not compensate for this effect. To improve the outcome of tCVCs, strategies like direct feedback after every procedure to achieve proficiency should be implanted in residency programs.

A microscopy-based approach for determining growth probability and lag time of individual bacterial cells.

The development of relevant predictive models for single-cell lag time and growth probability near growth limits is of critical importance for predicting pathogen behavior in foods. The classical methods for data acquisition in this field are based on turbidity measurements of culture media in microplate wells inoculated with approximately one bacterial cell per well. Yet, these methods are labour intensive and would benefit from higher throughput. In this study, we developed a quantitative experimental method using automated microscopy to determine the single-cell growth probability and lag time. The developed method consists of the use of direct cell observation with phase-contrast microscopy equipped with a 100× objective and a high-resolution device camera. The method is not a time-lapse method but is based on the observation of high numbers of colonies for a given time. Automation of image acquisition and image analysis was used to reach a high throughput. The single-cell growth probabilities and lag times of four strains of Listeria monocytogenes were determined at 4 °C. The microscopic method was shown to be a promising method for the determination of individual lag times and growth probability at the single-cell level.

Insights from genome-wide approaches to identify variants associated to phenotypes at pan-genome scale: Application to L. monocytogenes' ability to grow in cold conditions.

Intraspecific variability of the behavior of most foodborne pathogens is well described and taken into account in Quantitative Microbial Risk Assessment (QMRA), but factors (strain origin, serotype, …) explaining these differences are scarce or contradictory between studies. Nowadays, Whole Genome Sequencing (WGS) offers new opportunities to explain intraspecific variability of food pathogens, based on various recently published bioinformatics tools. The objective of this study is to get a better insight into different existing bioinformatics approaches to associate bacterial phenotype(s) and genotype(s). Therefore, a dataset of 51 L. monocytogenes strains, isolated from multiple sources (i.e. different food matrices and environments) and belonging to 17 clonal complexes (CC), were selected to represent large population diversity. Furthermore, the phenotypic variability of growth at low temperature was determined (i.e. qualitative phenotype), and the whole genomes of selected strains were sequenced. The almost exhaustive gene content, as well as the core genome SNPs based phylogenetic reconstruction, were derived from the whole sequenced genomes. A Bayesian inference method was applied to identify the branches on which the phenotype distribution evolves within sub-lineages. Two different Genome Wide Association Studies (i.e. gene- and SNP-based GWAS) were independently performed in order to link genetic mutations to the phenotype of interest. The genomic analyses presented in this study were successfully applied on the selected dataset. The Bayesian phylogenetic approach emphasized an association with "slow" growth ability at 2 °C of the lineage I, as well as CC9 of the lineage II. Moreover, both gene- and SNP-GWAS approaches displayed significant statistical associations with the tested phenotype. A list of 114 significantly associated genes, including genes already known to be involved in the cold adaption mechanism of L. monocytogenes and genes associated to mobile genetic elements (MGE), resulted from the gene-GWAS. On the other hand, a group of 184 highly associated SNPs were highlighted by SNP-GWAS, including SNPs detected in genes which were already likely involved in cold adaption; hypothetical proteins; and intergenic regions where for example promotors and regulators can be located. The successful application of combined bioinformatics approaches associating WGS-genotypes and specific phenotypes, could contribute to improve prediction of microbial behaviors in food. The implementation of this information in hazard identification and exposure assessment processes will open new possibilities to feed QMRA-models.