scholarly journals Control of subunit stoichiometry in single-chain MspA nanopores

2021 ◽  
Author(s):  
Mikhail Pavlenok ◽  
Luning Yu ◽  
Dominik Herrmann ◽  
Meni Wanunu ◽  
Michael Niederweis
Keyword(s):  
Dna Sequencing ◽  
Transmembrane Protein ◽  
Nanopore Sequencing ◽  
Single Chain ◽  
Base Calling ◽  
Subunit Stoichiometry ◽  
Oligomeric Protein ◽  
Highly Sensitive ◽  
Stochastic Events ◽  
Nucleotide Resolution

Transmembrane protein channels enable fast and highly sensitive electrical detection of single molecules. Nanopore sequencing of DNA was achieved using an engineered Mycobacterium smegmatis porin A (MspA) in combination with a motor enzyme. Due to its favorable channel geometry, the octameric MspA pore exhibits the highest current level as compared to other pore proteins. To date, MspA is the only protein nanopore with a published record of DNA sequencing. While widely used in commercial devices, nanopore sequencing of DNA suffers from significant base-calling errors due to stochastic events of the complex DNA-motor-pore combination and the contribution of up to five nucleotides to the signal at each position. Asymmetric mutations within subunits of the channel protein offer an enormous potential to improve nucleotide resolution and sequencing accuracy. However, random subunit assembly does not allow control of the channel composition of MspA and other oligomeric protein pores. In this study, we showed that it is feasible to convert octameric MspA into a single-chain pore by connecting eight subunits using peptide linkers. We constructed single-chain MspA trimers, pentamers, hexamers and heptamers to demonstrate that it is feasible to alter the subunit stoichiometry and the MspA pore diameter. All single-chain MspA proteins formed functional channels in lipid bilayer experiments. Importantly, we demonstrated that single-chain MspA discriminated all four nucleotides identical to MspA produced from monomers. Thus, single-chain MspA constitutes a new milestone in its development and adaptation as a biosensor for DNA sequencing and many other applications.

scholarly journals The application of numerical estimates of base calling accuracy to DNA sequencing projects

1995 ◽  
Vol 23 (8) ◽  
pp. 1406-1410 ◽  
Author(s):  
James K. Bonfield ◽  
Rodger Staden
Keyword(s):  
Dna Sequencing ◽  
Base Calling

scholarly journals DeepSimulator: a deep simulator for Nanopore sequencing

2017 ◽  
Author(s):  
Yu Li ◽  
Renmin Han ◽  
Chongwei Bi ◽  
Mo Li ◽  
Sheng Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
De Novo ◽  
Real Data ◽  
Electrical Current ◽  
Complex Nature ◽  
Main Task ◽  
Nanopore Sequencing ◽  
Base Calling ◽  
Context Dependent ◽  
Sequencing Procedure

ABSTRACTMotivationOxford Nanopore sequencing is a rapidly developed sequencing technology in recent years. To keep pace with the explosion of the downstream data analytical tools, a versatile Nanopore sequencing simulator is needed to complement the experimental data as well as to benchmark those newly developed tools. However, all the currently available simulators are based on simple statistics of the produced reads, which have difficulty in capturing the complex nature of the Nanopore sequencing procedure, the main task of which is the generation of raw electrical current signals.ResultsHere we propose a deep learning based simulator, DeepSimulator, to mimic the entire pipeline of Nanopore sequencing. Starting from a given reference genome or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments performed across four species show that the signals generated by our context-dependent model are more similar to the experimentally obtained signals than the ones generated by the official context-independent pore model. In terms of the simulated reads, we provide a parameter interface to users so that they can obtain the reads with different accuracies ranging from 83% to 97%. The reads generated by the default parameter have almost the same properties as the real data. Two case studies demonstrate the application of DeepSimulator to benefit the development of tools in de novo assembly and in low coverage SNP detection.AvailabilityThe software can be accessed freely at: https://github.com/lykaust15/deep_simulator.

scholarly journals Genomic DNA preparation enabling multiple replicate reads for accurate nanopore sequencing

2015 ◽  
Author(s):  
Dimitra Tsavachidou
Keyword(s):  
Nucleic Acid ◽  
Error Rates ◽  
Nanopore Sequencing ◽  
Acid Molecule ◽  
Single Nucleotide ◽  
Nucleic Acid Molecule ◽  
Dna Strands ◽  
Nucleotide Resolution ◽  
Single Nucleotide Resolution ◽  
Sequencing Procedure

Sequencing at single-nucleotide resolution using nanopore devices is performed with reported error rates 10.5-20.7% (Ip et al., 2015). Since errors occur randomly during sequencing, repeating the sequencing procedure for the same DNA strands several times can generate sequencing results based on consensus derived from replicate readings, thus reducing overall error rates. The method presented in this manuscript constructs copies of a nucleic acid molecule that are consecutively connected to the nucleic acid molecule. Such copies are useful because they can be sequenced by a nanopore device, enabling replicate reads, thus improving overall sequencing accuracy.

scholarly journals Accurate detection of m6A RNA modifications in native RNA sequences

2019 ◽  
Author(s):  
Huanle Liu ◽  
Oguzhan Begik ◽  
Morghan C Lucas ◽  
Christopher E. Mason ◽  
Schraga Schwartz ◽  
...  
Keyword(s):  
Rna Modifications ◽  
Rna Sequences ◽  
Single Nucleotide ◽  
Rna Molecules ◽  
Base Calling ◽  
Oxford Nanopore ◽  
Nucleotide Resolution ◽  
The Universe ◽  
Oxford Nanopore Technologies ◽  
Single Nucleotide Resolution

ABSTRACTThe field of epitranscriptomics has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here we show that using Oxford Nanopore Technologies, N6-methyladenosine (m6A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Our results open new avenues to investigate the universe of RNA modifications with single nucleotide resolution, in individual RNA molecules.

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