Long-Read Plasmid Sequencing and Assembly Using Nanopore Sequencing-Based Workflows
July 7th, 2026
46 views
The current study describes a workflow for nanopore sequencing of plasmids when the chromosomal sequence is already known or of no interest. An initial plasmid DNA enrichment step ensures optimal plasmid sequence depth and maximizes the number of samples that can be sequenced per flow cell.
Overview
This article presents a detailed workflow for nanopore sequencing aimed at maximizing plasmid DNA yield and sequencing accuracy. The protocol encompasses plasmid extraction, rapid barcoding, adapter ligation, sequencing, and sequence assembly, and is suitable for a wide range of plasmid sizes and levels of chromosomal contamination. The method is demonstrated using Escherichia coli as a model organism.
Key Study Components
Area of Science
- Molecular biology
- Genomics
- Microbiology
Background
- Plasmid sequencing is essential for genetic studies, recombinant gene expression, and plasmid capture experiments.
- Traditional sequencing methods may be limited by chromosomal contamination and low plasmid yield.
- Nanopore sequencing offers long-read capabilities and real-time data acquisition.
- Efficient workflows are needed to optimize plasmid sequencing throughput and accuracy.
Purpose of Study
- To develop and describe a robust workflow for nanopore-based plasmid sequencing.
- To maximize plasmid DNA yield and sequencing accuracy.
- To enable efficient parallel sequencing of multiple samples.
Methods Used
- Plasmid DNA extraction from clinical E. coli strains.
- Library preparation using rapid barcoding and adapter ligation.
- Loading libraries onto a nanopore flow cell for sequencing.
- Base calling performed in real time or post-hoc.
- Sequence assembly using Autocycler.
- Comparison of assemblies to gel mobility and short-read polished assemblies.
Main Results
- Plasmid assemblies matched sizes inferred from gel mobility.
- In two-thirds of cases, assemblies matched or closely resembled short-read polished assemblies (within 0.05% pairwise identity).
- Protocol supports plasmids from 4 to 174 kb in size.
- Up to 72% chromosomal contamination tolerated without loss of accuracy.
- Parallel sequencing of up to 24 samples achieved with optimal coverage.
Conclusions
- The workflow enables accurate and efficient plasmid sequencing using nanopore technology.
- It is suitable for plasmid verification, improving WGS-derived plasmid sequences, and sequencing plasmids captured by conjugation.
- The protocol is robust to chromosomal contamination and applicable to a range of plasmid sizes.
Frequently Asked Questions
What is the main advantage of this nanopore sequencing workflow for plasmids?
It maximizes plasmid DNA yield and sequencing accuracy, even in the presence of significant chromosomal contamination, and allows efficient parallel sequencing of multiple samples.
What organisms can this protocol be applied to?
While demonstrated with Escherichia coli, the protocol is applicable to other hosts commonly used for recombinant gene expression and plasmid capture.
How does the protocol handle chromosomal DNA contamination?
The workflow tolerates up to 72% chromosomal contamination without affecting plasmid sequencing accuracy.
What is the range of plasmid sizes that can be sequenced using this method?
The protocol is suitable for plasmids ranging from 4 to 174 kb.
How does the accuracy of nanopore assemblies compare to short-read assemblies?
In two-thirds of cases, nanopore assemblies matched or were within 0.05% pairwise sequence identity of short-read polished assemblies.
What are the computer requirements for this workflow?
Requirements depend on whether base calling is performed in real time or post-hoc, with more powerful hardware needed for real-time processing.
For what applications is this protocol particularly useful?
It is ideal for plasmid sequence verification, improving the accuracy of plasmid sequences from WGS, and sequencing plasmids captured by conjugation.
Executive Industry Relevance
Long-read nanopore plasmid sequencing enables high-confidence verification and assembly of plasmid constructs, supporting critical quality control and mechanistic de-risking in biopharma R&D. This workflow addresses the challenge of chromosomal contamination and variable plasmid yield, providing robust, scalable solutions for recombinant DNA and gene therapy vector development. Its parallelization and tolerance for mixed DNA inputs streamline early discovery and preclinical workflows, enhancing portfolio decision-making.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables precise verification of engineered plasmids for functional studies and target validation.
- Reduces ambiguity in construct identity, supporting mechanistic de-risking in discovery biology.
- Facilitates rapid triage of candidate constructs for downstream screening or expression.
Screening & Assay Development
- Provides validated sequence data for assay-ready plasmids, ensuring reproducibility in screening campaigns.
- Supports parallel sequencing of up to 24 samples, increasing throughput for construct libraries.
- Delivers quantitative sequence accuracy, enabling reliable comparison across engineered variants.
Translational & Preclinical Research
- Improves continuity from discovery to preclinical studies by confirming plasmid integrity in disease-relevant systems.
- Enables sequence verification for plasmids used in gene delivery or biomarker studies.
- Supports risk-adjusted advancement by minimizing sequence-related uncertainties in preclinical models.
Pipeline & Workflow Integration
This nanopore-based workflow integrates from early construct verification through screening and preclinical validation, supporting both hypothesis-driven and translational research pipelines.
- Discovery Biology: Confirms plasmid sequence fidelity, reducing risk of off-target effects in functional assays.
- Screening: Ensures assay-ready constructs are sequence-verified, supporting reproducible compound evaluation.
- Analytics: Provides high-accuracy, quantitative sequence data for cross-sample comparison and quality control.
- Translational Research: Aligns plasmid sequence verification with preclinical model requirements for gene expression studies.
- Enterprise Reuse: Offers a scalable, parallelizable sequencing capability adaptable across diverse R&D programs.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence in construct-driven studies and reduces mechanistic ambiguity.
- Operational Value: Standardizes plasmid verification, tolerates high chromosomal contamination, and supports high-throughput workflows.
- Strategic Value: Enables better go/no-go decisions by ensuring construct integrity before downstream investment.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of gene-based assets.
Implementation Considerations
- Requires expertise in plasmid extraction, library preparation, and nanopore sequencing workflows.
- Demands computational infrastructure scaled to real-time or post-hoc basecalling needs.
- Benefits from standardized protocols for cross-team reproducibility and data comparability.
- Adaptable to a range of plasmid sizes and host backgrounds, including high chromosomal DNA content.
- Best suited for applications where chromosomal sequence is known or not required.
Biopharma FAQs
Why does null hypothesis testing matter for plasmid sequence verification?
Null hypothesis testing ensures that observed plasmid sequence differences are statistically significant, supporting confident construct validation and reducing the risk of undetected errors in downstream applications.
How does independent variable isolation fit in plasmid conjugation sequencing?
By conjugating clinical strains with a common recipient, the workflow isolates plasmid-specific sequence variation, minimizing confounding host-cell effects and enabling accurate comparative analysis.
What do quantitative dependent variable measurements enable in nanopore assemblies?
Quantitative sequence identity metrics, such as pairwise identity within 0.05%, enable objective assessment of assembly accuracy and support reliable cross-sample comparisons for construct verification.
Why are replication requirements critical for parallel plasmid sequencing?
Replication across multiple samples and conditions ensures reproducibility and cross-functional confidence in sequence verification, supporting collaborative R&D and robust data integration.
What statistical analysis capabilities are required before implementing plasmid assembly workflows?
Robust statistical tools are needed to compare assembly outputs, assess sequence identity, and validate that plasmid assemblies match expected sizes and reference standards before advancing constructs in the pipeline.
