The first complete bacterial genome was decoded in 1995 using whole-genome sequencing. Once very expensive and time-consuming, costs for whole-genome sequencing have dropped dramatically since, and nowadays a bacterial genome can be sequenced within a few hours. Especially the latest generation of whole-genome sequencing technology, long-read sequencing (LRS), is making all the difference in revealing plasmid-encoded antimicrobial resistance genes. The review “Long-read sequencing for bacterial plasmid analysis: a brief overview” in FEMS Microbiology Letters describes the advantages of LRS and outlines important bioinformatic tools used for plasmid analysis, as summarized by Annika Sobkowiak in this #FEMSmicroBlog. #MicrobiologyIsEverywhere
Why do we need long-read sequencing?
Most antimicrobial resistance genes are located on small, extrachromosomal plasmids. However, to fully understand how these resistance genes are organized, transferred, and maintained within bacterial populations, it is not sufficient to sequence plasmids in isolation.
Sequencing both the bacterial chromosome and its plasmids is essential to reconstruct the complete genetic architecture of multidrug-resistant bacteria. This helps identify where resistance genes are located, how they are connected to mobile genetic elements, and how they may contribute to the spread of antimicrobial resistance.
Traditionally, short-read sequencing technologies generate only small DNA fragments, producing many tiny puzzle pieces that must be assembled to reconstruct the bacterial genome and its plasmids. This is particularly problematic for plasmid detection, because plasmids often contain repetitive sequences, mobile genetic elements, and antimicrobial resistance genes that may also occur elsewhere in the genome. As a result, short reads frequently cannot determine whether a resistance gene is located on a plasmid or on the chromosome, nor can they reliably reconstruct complete plasmid structures.
In contrast, long-read sequencing captures much larger DNA segments, often spanning repetitive regions and linking resistance genes to their surrounding genetic context. This makes genome and plasmid assembly simpler, more accurate, and less fragmented. From these assemblies, we can generate circular bacterial chromosomes and plasmids without gaps, allowing us to identify plasmid-borne antimicrobial resistance genes more reliably.
Choosing the right tool for the long-read sequencing workflow
Analysing long-read whole-genome sequencing data requires specialised bioinformatic software. Depending on the research question, these tools are used for distinct tasks: detecting plasmid sequences, reconstructing complete plasmids, typing and characterising plasmid backbones, annotating genes including antimicrobial resistance genes, comparing plasmids between isolates, and grouping related plasmids into clusters.
So far, no single tool performs all steps equally well. In practice, we need to combine multiple software programs into one workflow, with each tool covering only one part of the analysis.
As a result, analysing long-read sequencing data is not only a technical challenge but also an interpretative one. Hence, users need to understand the strengths and limitations of each tool to fully take advantage of the power of long-read sequencing and interpret data correctly. This is why the review “Long-read sequencing for bacterial plasmid analysis: a brief overview” in FEMS Microbiology Letters provides an overview of currently available tools for each of these analytical steps.
Applying long-read sequencing data in clinics
The long-read sequencing workflow has the potential to ensure that antibiotics remain effective in the future. An accurate blueprint of bacteria and their plasmids is the first step towards a better and more targeted use of antibiotics. Fortunately, in hospital environments, long-read sequencing is already frequently used to help monitor and contain the spread of multidrug-resistant pathogens. In further clinical diagnostics, long-read sequencing would mean faster and more precise results once the technology finds routine application.
Overall, this review aims to support this development by providing a concise overview of current bioinformatic tools needed to interpret long-read sequencing data and plasmid data effectively.
- Read the minireview“Long-read sequencing for bacterial plasmid analysis: a brief overview“ by van Almsick et al. in FEMS Microbiology Letters (2026).
Annika Sobkowiak is a research assistant at the University Hospital Münster (GER) at the Institute of Hygiene, mentored by PD Dr. Dr. Vera Schwierzeck. She completed her MSc in Interdisciplinary Biomedicine at the University Bielefeld (GER) in 2022 with her Master thesis about staphyloccocal biofilms, when she got fascinated by bacteria. She finished her PhD in 2026 which focussed on antimicrobial resistance encoding plasmids in bacteria. Her work is committed to better understanding multidrug-resistant bacterial dissemination and infections to improve patient treatment and infection prevention.
About this blog section
The section #MicrobiologyIsEverywhere highlights the global relevance of microbiology. The section acknowledges that microbiology knows no borders, as well as the fact that microbiologists are everywhere and our FEMS network extends well beyond Europe. This blog entry type accepts contributions from excellent blogs translated into English. Regional stories with global relevance are welcomed. National or international events sponsored, organised or connected to FEMS are also covered.
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