Metagenomics has redefined many areas of microbiology. However, metagenome-assembled genomes (MAGs) are often fragmented, primarily when sequencing was performed with short reads. Recent long-read sequencing technologies promise to improve genome reconstruction. However, the integration of two different sequencing modalities makes downstream analyses complex. We, therefore, developed MUFFIN, a complete metagenomic workflow that uses short and long reads to produce high-quality bins and their annotations. The workflow is written by using Nextflow, a workflow orchestration software, to achieve high reproducibility and fast and straightforward use. This workflow also produces the taxonomic classification and KEGG pathways of the bins and can be further used for quantification and annotation by providing RNA-Seq data (optionally). We tested the workflow using twenty biogas reactor samples and assessed the capacity of MUFFIN to process and output relevant files needed to analyze the microbial community and their function. MUFFIN produces functional pathway predictions and, if provided de novo metatranscript annotations across the metagenomic sample and for each bin. MUFFIN is available on github under GNUv3 licence: https://github.com/RVanDamme/MUFFIN.

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.

The global spread and diversification of multidrug-resistant Gram-negative (MRGN) bacteria poses major challenges to healthcare. In particular, carbapenem-resistant Klebsiella pneumoniae strains have been frequently identified in infections and hospital-wide outbreaks. The most frequently underlying resistance gene (bla_KPC) has been spreading over the last decade in the health care setting. bla_KPC seems to have rapidly diversified and has been found in various species and on different plasmid types. To review the progress and dynamics of this diversification, all currently available KPC plasmids in the NCBI database were analysed in this work. Plasmids were grouped into 257 different representative KPC plasmids, of which 79.4% could be clearly assigned to incompatibility (Inc) group or groups. In almost half of all representative plasmids, the KPC gene is located on Tn4401 variants, emphasizing the importance of this transposon type for the transmission of KPC genes to other plasmids. The transposons also seem to be responsible for the occurrence of altered or uncommon fused plasmid types probably due to incomplete transposition. Moreover, many KPC plasmids contain genes that encode proteins promoting recombinant processes and mutagenesis; in consequence accelerating the diversification of KPC genes and other colocalized resistance genes.

Our study investigates the effectiveness of Oxford Nanopore Technologies for accurate outbreak tracing by resequencing 33 isolates of a 3-year-longKlebsiella pneumoniaeoutbreak with Illumina short-read sequencing data as the point of reference. We detect considerable base errors through cgMLST and phylogenetic analysis of genomes sequenced with Oxford Nanopore Technologies, leading to the false exclusion of some outbreak-related strains from the outbreak cluster. Nearby methylation sites cause these errors and can also be found in other species besidesK. pneumoniae. Based on these data, we explore PCR-based sequencing and a masking strategy, which both successfully address these inaccuracies and ensure accurate outbreak tracing. We offer our masking strategy as a bioinformatic workflow (MPOA) to identify and mask problematic genome positions in a reference-free manner. Our research highlights limitations in using Oxford Nanopore Technologies for sequencing prokaryotic organisms, especially for investigating outbreaks. For time-critical projects that cannot wait for further technological developments by Oxford Nanopore Technologies, our study recommends either using PCR-based sequencing or using our provided bioinformatic workflow. We advise that read mapping–based quality control of genomes should be provided when publishing results.