Healthcare-associated infections (HCAIs) represent an enormous burden for patients, healthcare workers, relatives and society worldwide, including Germany. The central tasks of infection prevention are recording and evaluating infections with the aim of identifying prevention potential and risk factors, taking appropriate measures and finally evaluating them. From an infection prevention perspective, it would be of great value if (i) the recording of infection cases was automated and (ii) if it were possible to identify particularly vulnerable patients and patient groups in advance, who would benefit from specific and/or additional interventions.To achieve this risk-adapted, individualized infection prevention, the RISK PRINCIPE research project develops algorithms and computer-based applications based on standardised, large datasets and incorporates expertise in the field of infection prevention.The project has two objectives: a) to develop and validate a semi-automated surveillance system for hospital-acquired bloodstream infections, prototypically for HCAI, and b) to use comprehensive patient data from different sources to create an individual or group-specific infection risk profile.RISK PRINCIPE is based on bringing together the expertise of medical informatics and infection medicine with a focus on hygiene and draws on information and experience from two consortia (HiGHmed and SMITH) of the German Medical Informatics Initiative (MII), which have been working on use cases in infection medicine for more than five years.
Rapid screening of hospital admissions to detect asymptomatic carriers of resistant bacteria can prevent pathogen outbreaks. However, the resulting isolates rarely have their genome sequenced due to cost constraints and long turn-around times to get and process the data, limiting their usefulness to the practitioner. Here we used real-time, on-device target enrichment ("adaptive") sequencing as a highly multiplexed assay covering 1,147 antimicrobial resistance genes. We compared its utility against standard and metagenomic sequencing, focusing on an isolate of Raoultella ornithinolytica harbouring three carbapenemases (NDM, KPC, VIM). Based on this experimental data, we then modelled the influence of several variables on the enrichment results and predicted the large effect of nucleotide identity (higher is better) and read length (shorter is better). Lastly, we showed how all relevant resistance genes are detected using adaptive sequencing on a miniature ("Flongle") flow cell, motivating its use in a clinical setting to monitor similar cases and their surroundings.
Phages are among the most abundant and diverse biological entities on earth. Phage prediction from sequence data is a crucial first step to understanding their impact on the environment. A variety of bacteriophage prediction tools have been developed over the years. They differ in algorithmic approach, results, and ease of use. We, therefore, developed "What the Phage" (WtP), an easy-to-use and parallel multitool approach for phage prediction combined with an annotation and classification downstream strategy, thus supporting the user's decision-making process by summarizing the results of the different prediction tools in charts and tables. WtP is reproducible and scales to thousands of datasets through a workflow manager (Nextflow). WtP is freely available under a GPL-3.0 license (https://github.com/replikation/What_the_Phage).
Bacteriophages , Bacteriophages/genetics , Workflow
[This corrects the article DOI: 10.3389/fgene.2021.711437.].
Metagenomic sequencing is promising for clinical applications to study microbial composition concerning disease or patient outcomes. Alterations of the vaginal microbiome are associated with adverse pregnancy outcomes, like preterm premature rupture of membranes and preterm birth. Methodologically these samples often have to deal with low relative amounts of prokaryotic DNA and high amounts of host DNA (> 90%), decreasing the overall microbial resolution. Nanopore's adaptive sampling method offers selective DNA depletion or target enrichment to directly reject or accept DNA molecules during sequencing without specialized sample preparation. Here, we demonstrate how selective 'human host depletion' resulted in a 1.70 fold (± 0.27 fold) increase in total sequencing depth, providing higher taxonomic profiling sensitivity. At the same time, the microbial composition remains consistent with the control experiments. The complete removal of all human host sequences is not yet possible and should be considered as an ethical approval statement might still be necessary. Adaptive sampling increased microbial sequencing yield in all 15 sequenced clinical routine vaginal samples, making it a valuable tool for clinical surveillance and medical-based research, which can be used in addition to other host depletion methods before sequencing.
Microbiota , Nanopores , Premature Birth , DNA , Female , High-Throughput Nucleotide Sequencing/methods , Humans , Infant, Newborn , Microbiota/genetics , Pregnancy
In response to the SARS-CoV-2 pandemic, a highly increased sequencing effort has been established worldwide to track and trace ongoing viral evolution. Technologies, such as nanopore sequencing via the ARTIC protocol are used to reliably generate genomes from raw sequencing data as a crucial base for molecular surveillance. However, for many labs that perform SARS-CoV-2 sequencing, bioinformatics is still a major bottleneck, especially if hundreds of samples need to be processed in a recurring fashion. Pipelines developed for short-read data cannot be applied to nanopore data. Therefore, specific long-read tools and parameter settings need to be orchestrated to enable accurate genotyping and robust reference-based genome reconstruction of SARS-CoV-2 genomes from nanopore data. Here we present poreCov, a highly parallel workflow written in Nextflow, using containers to wrap all the tools necessary for a routine SARS-CoV-2 sequencing lab into one program. The ease of installation, combined with concise summary reports that clearly highlight all relevant information, enables rapid and reliable analysis of hundreds of SARS-CoV-2 raw sequence data sets or genomes. poreCov is freely available on GitHub under the GNUv3 license: github.com/replikation/poreCov.
Infections with SARS-CoV-2 can be asymptomatic, but they can also be accompanied by a variety of symptoms that result in mild to severe coronavirus disease-19 (COVID-19) and are sometimes associated with systemic symptoms. Although the viral infection originates in the respiratory system, it is unclear how the virus can overcome the alveolar barrier, which is observed in severe COVID-19 disease courses. To elucidate the viral effects on the barrier integrity and immune reactions, we used mono-cell culture systems and a complex human chip model composed of epithelial, endothelial, and mononuclear cells. Our data show that SARS-CoV-2 efficiently infected epithelial cells with high viral loads and inflammatory response, including interferon expression. By contrast, the adjacent endothelial layer was neither infected nor did it show productive virus replication or interferon release. With prolonged infection, both cell types were damaged, and the barrier function was deteriorated, allowing the viral particles to overbear. In our study, we demonstrate that although SARS-CoV-2 is dependent on the epithelium for efficient replication, the neighboring endothelial cells are affected, e.g., by the epithelial cytokines or components induced during infection, which further results in the damage of the epithelial/endothelial barrier function and viral dissemination.IMPORTANCESARS-CoV-2 challenges healthcare systems and societies worldwide in unprecedented ways. Although numerous new studies have been conducted, research to better understand the molecular pathogen-host interactions are urgently needed. For this, experimental models have to be developed and adapted. In the present study we used mono cell-culture systems and we established a complex chip model, where epithelial and endothelial cells are cultured in close proximity. We demonstrate that epithelial cells can be infected with SARS-CoV-2, while the endothelium did not show any infection signs. Since SARS-CoV-2 is able to establish viremia, the link to thromboembolic events in severe COVID-19 courses is evident. However, whether the endothelial layer is damaged by the viral pathogens or whether other endothelial-independent homeostatic factors are induced by the virus is essential for understanding the disease development. Therefore, our study is important as it demonstrates that the endothelial layer could not be infected by SARS-CoV-2 in our in vitro experiments, but we were able to show the destruction of the epithelial-endothelial barrier in our chip model. From our experiments we can assume that virus-induced host factors disturbed the epithelial-endothelial barrier function and thereby promote viral spread.
The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8-9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online. On the other hand, the pandemic has made us even more aware of the importance of accelerating research in viral bioinformatics. Advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks. The International Virus Bioinformatics Meeting 2020 has attracted approximately 120 experts in virology and bioinformatics from all over the world to join the two-day virtual meeting. Despite concerns being raised that virtual meetings lack possibilities for face-to-face discussion, the participants from this small community created a highly interactive scientific environment, engaging in lively and inspiring discussions and suggesting new research directions and questions. The meeting featured five invited and twelve contributed talks, on the four main topics: (1) proteome and RNAome of RNA viruses, (2) viral metagenomics and ecology, (3) virus evolution and classification and (4) viral infections and immunology. Further, the meeting featured 20 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting.
Computational Biology , RNA Viruses/genetics , Virology , COVID-19 , Congresses as Topic , Evolution, Molecular , Genome, Viral , Humans , Metagenomics , RNA Viruses/pathogenicity
The SHV ß-lactamases (BLs) have undergone strong allele diversification that has changed their substrate specificities. Based on 147 NCBI entries for SHV alleles, in silico mathematical models predicted 5 positions as relevant for the ß-lactamase inhibitor (BLI)-resistant (2br) phenotype, 12 positions as relevant for the extended-spectrum BL (ESBL) (2be) phenotype, and 2 positions as related solely to the narrow-spectrum (2b) phenotype. These positions and six additional positions described in other studies (including one promoter mutation) were systematically substituted and investigated for their substrate specificities in a BL-free Escherichia coli background, representing, to our knowledge, the most comprehensive substrate and substitution analysis for SHV alleles to date. An in vitro analysis confirmed the essentiality of positions 238 and 179 for the 2be phenotype and of position 69 for the 2br phenotype. The E240K and E240R substitutions, which do not occur alone in known 2br SHV variants, led to a 2br phenotype, indicating a latent BLI resistance potential of these substitutions. The M129V, A234G, S271I, and R292Q substitutions conferred latent resistance to cefotaxime. In addition, seven positions that were found not always to be associated with the ESBL phenotype resulted in increased resistance to ceftaroline. We also observed that coupling of a strong promoter (IS26) to an A146V mutant with the 2b phenotype resulted in highly increased resistance to BLIs, cefepime, and ceftaroline but not to third-generation cephalosporins, indicating that SHV enzymes represent an underestimated risk for empirical therapies that use piperacillin-tazobactam or cefepime to treat different infectious diseases caused by Gram-negative bacteria.
beta-Lactam Resistance , beta-Lactamases , Genetic Association Studies , Microbial Sensitivity Tests , beta-Lactamase Inhibitors , beta-Lactamases/genetics
