Related Experiment Video
Updated: Jun 13, 2026

Monitoring Plasmid Replication in Live Mammalian Cells over Multiple Generations by Fluorescence Microscopy
Published on: December 13, 2012
Real-time plasmid transmission detection pipeline
Natalie Scherff1,2, Jörg Rothgänger2, Thomas Weniger2
11Institute of Hygiene, University Hospital Münster, Münster, Germany.
Abstract:
The spread of antimicrobial resistance among bacteria by horizontal plasmid transmissions poses a major challenge for clinical microbiology. Here, we evaluate a new real-time plasmid transmission detection pipeline implemented in the SeqSphere+ (Ridom GmbH, Münster, Germany) software. Within the pipeline, a local Mash plasmid database is created, and Mash searches with a distance threshold of 0.001 are used to trigger plasmid transmission early warning alerts (EWAs). Clonal transmissions are detected using core-genome multi-locus sequence typing allelic differences. The tools MOB-suite, NCBI AMRFinderPlus, CGE MobileElementFinder, pyGenomeViz, and MUMmer, integrated in SeqSphere+, are used to characterize plasmids and for visual pairwise plasmid comparisons, respectively. We evaluated the pipeline using published hybrid assemblies (Oxford Nanopore Technology/Illumina) of a surveillance and outbreak data set with plasmid transmissions. To emulate prospective usage, samples were imported in chronological order of sampling date. Different combinations of the user-adjustable parameters sketch size (1,000 vs 10,000) and plasmid size correction were tested, and discrepancies between resulting clusters were analyzed with Quast. When using a sketch size of 1,000 with size correction turned on, the SeqSphere+ pipeline agreed with the published data and produced the same clonal and carbapenemase-carrying plasmid clusters. EWAs were in the correct chronological order. In summary, the developed pipeline presented here is suitable for integration into clinical microbiology settings with limited bioinformatics knowledge due to its automated analyses and alert system, which are combined with the GUI-based SeqSphere+ platform. Thus, with its integrated sample database, (near) real-time plasmid transmission detection is within reach in bacterial routine-diagnostic settings when long-read sequencing is employed.
Importance:
Plasmid-mediated spread of antimicrobial resistance is a major challenge for clinical microbiology, and monitoring of potential plasmid transmissions is essential to combat further dissemination. Whole-genome sequencing is often used to surveil nosocomial transmissions but usually limited to the detection of clonal transmissions (based on chromosomal markers). Recent advances in long-read sequencing technologies enable full reconstruction of plasmids and the detection of very similar plasmids, but so far, easy-to-use bioinformatic tools for this purpose have been missing. Here, we present an evaluation of an innovative real-time plasmid transmission detection pipeline. It is integrated into the GUI-based SeqSphere+ software, which already offers core-genome multi-locus sequence typing-based pathogen outbreak detection. It requires very limited bioinformatics knowledge, and its database, automated analyses, and alert system make it well suited for prospective clinical application.
Insights
This study introduces a new pipeline for real-time detection of plasmid transmission in clinical microbiology. The developed system effectively identifies antimicrobial resistance spread, aiding in infection control.
Area of Science:
- Microbiology
- Bioinformatics
- Genomics
Background:
- Antimicrobial resistance spread via plasmids is a significant clinical challenge.
- Current methods often miss plasmid-mediated transmissions, focusing mainly on clonal spread.
- Advances in long-read sequencing allow plasmid reconstruction but lack user-friendly tools.
Purpose of the Study:
- To evaluate a novel real-time plasmid transmission detection pipeline integrated into SeqSphere+ software.
- To assess the pipeline's utility for early warning alerts (EWAs) of plasmid spread.
- To determine the pipeline's suitability for clinical microbiology settings.
Main Methods:
- Utilized a local Mash plasmid database for early warning alerts (EWAs) with a distance threshold of 0.001.
- Employed core-genome multi-locus sequence typing for clonal transmission detection.
- Integrated tools like MOB-suite, AMRFinderPlus, and MUMmer for plasmid characterization and comparison.
Main Results:
- The SeqSphere+ pipeline successfully identified clonal and carbapenemase-carrying plasmid clusters, matching published data.
- Early warning alerts (EWAs) were generated in the correct chronological order.
- Optimal performance was achieved using a sketch size of 1,000 with plasmid size correction enabled.
Conclusions:
- The developed pipeline is suitable for clinical microbiology due to automated analyses and an alert system.
- Its integration into the GUI-based SeqSphere+ platform requires limited bioinformatics knowledge.
- The pipeline enables (near) real-time plasmid transmission detection in routine diagnostics using long-read sequencing.

