Real-time diagnostic analysis of MinION™-based metagenomic sequencing in clinical microbiology evaluation: a case report

Optimized bacterial community characterization through full-length 16S rRNA gene sequencing utilizing MinION nanopore technology

BACKGROUND

Accurate identification of bacterial communities is crucial for research applications, diagnostics, and clinical interventions. Although 16S ribosomal RNA (rRNA) gene sequencing is a widely employed technique for bacterial taxonomic classification, it often results in misclassified or unclassified bacterial taxa. This study sought to refine the full-length 16S rRNA gene sequencing protocol using the MinION sequencer, focusing on the V1-V9 regions. Our methodological enquiry examined several factors, including the number of PCR amplification cycles, choice of primers and Taq polymerase, and specific sequence databases and workflows employed. We used a microbial standard comprising eight bacterial strains (five gram-positive and three gram-negative) in known proportions as a validation control.

RESULTS

Based on the MinION protocol, we employed the microbial standard as the DNA template for the 16S rRNA gene amplicon sequencing procedure. Our analysis showed that an elevated number of PCR amplification cycles introduced PCR bias, and the selection of Taq polymerase and primer sets significantly affected the subsequent analysis. Bacterial identification at genus level demonstrated Pearson correlation coefficients ranging from 0.73 to 0.79 when assessed using BugSeq, Kraken-Silva and EPI2ME-16S workflows. Notably, the EPI2ME-16S workflow exhibited the highest Pearson correlation with the microbial standard, minimised misclassification, and increased alignment accuracy. At the species taxonomic level, the BugSeq workflow was superior, with a Pearson correlation coefficient of 0.92.

CONCLUSIONS

These findings emphasise the importance of careful selection of PCR settings and a well-structured analytical framework for 16S rRNA full-length gene sequencing. The results showed a robust correlation between the predicted and observed bacterial abundances at both the genus and species taxonomic levels, making these findings applicable across diverse research contexts and with clinical utility for reliable pathogen identification.

Using nanopore sequencing to identify fungi from clinical samples with high phylogenetic resolution

The study of microbiota has been revolutionized by the development of DNA metabarcoding. This sequence-based approach enables the direct detection of microorganisms without the need for culture and isolation, which significantly reduces analysis time and offers more comprehensive taxonomic profiles across broad phylogenetic lineages. While there has been an accumulating number of researches on bacteria, molecular phylogenetic analysis of fungi still remains challenging due to the lack of standardized tools and the incompleteness of reference databases limiting the accurate and precise identification of fungal taxa. Here, we present a DNA metabarcoding workflow for characterizing fungal microbiota with high taxonomic resolution. This method involves amplifying longer stretches of ribosomal RNA operons and sequencing them using nanopore long-read sequencing technology. The resulting reads were error-polished to generate consensus sequences with 99.5-100% accuracy, which were then aligned against reference genome assemblies. The efficacy of this method was explored using a polymicrobial mock community and patient-derived specimens, demonstrating the marked potential of long-read sequencing combined with consensus calling for accurate taxonomic classification. Our approach offers a powerful tool for the rapid identification of pathogenic fungi and has the promise to significantly improve our understanding of the role of fungi in health and disease.

Full-Length 16S rRNA Gene Analysis Using Long-Read Nanopore Sequencing for Rapid Identification of Bacteria from Clinical Specimens

Amplicon sequencing of the 16S ribosomal RNA (rRNA) gene is a practical and reliable measure for taxonomic profiling of bacterial communities. This chapter describes the detailed workflow for full-length 16S rRNA gene amplicon analysis using nanopore sequencing and bioinformatics pipelines to analyze nanopore sequencing data for taxonomic assignment. This approach offers a higher taxonomic resolution for bacterial identification from clinical specimens with a markedly reduced timeframe and improved versatility.

Nanopore Sequencing Data Analysis of 16S rRNA Genes Using the GenomeSync-GSTK System

With the development of nanopore sequencing technology, long reads of DNA sequences can now be determined rapidly from various samples. This protocol introduces the GenomeSync-GSTK system for bacterial species identification in a given sample using nanopore sequencing data of 16S rRNA genes as an example. GenomeSync is a collection of genome sequences designed to provide easy access to genomic data of the species as demanded. GSTK (genome search toolkit) is a set of scripts for managing local homology searches using genomes obtained from the GenomeSync database. Based on this protocol, nanopore sequencing data analyses of metagenomes and amplicons could be efficiently performed. We also noted reanalysis in conjunction with future developments in nanopore sequencing technology and the accumulation of genome sequencing data.

Rapid detection of single nucleotide polymorphisms using the MinION nanopore sequencer: a feasibility study for perioperative precision medicine

Introduction

Precision medicine is a phrase used to describe personalized medical care tailored to specific patients based on their clinical presentation and genetic makeup. However, despite the fact that several single nucleotide polymorphisms (SNPs) have been reported to be associated with increased susceptibility to particular anesthetic agents and the occurrence of perioperative complications, genomic profiling and thus precision medicine has not been widely applied in perioperative management.

Methods

We validated six SNP loci known to affect perioperative outcomes in Japanese patients using genomic DNA from saliva specimens and nanopore sequencing of each SNP loci to facilitate allele frequency calculations and then compared the nanopore results to those produced using the conventional dideoxy sequencing method.

Results

Nanopore sequencing reads clustered into the expected genotypes in both homozygous and heterozygous cases. In addition, the nanopore sequencing results were consistent with those obtained using conventional dideoxy sequencing and the workflow provided reliable allele frequency estimation, with a total analysis time of less than 4 h.

Conclusion

Thus, our results suggest that nanopore sequencing is a promising and versatile tool for SNP genotyping, allowing for rapid and feasible risk prediction of perioperative outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40981-022-00506-7.

Nanopore sequencing and its application to the study of microbial communities

Since its introduction, nanopore sequencing has enhanced our ability to study complex microbial samples through the possibility to sequence long reads in real time using inexpensive and portable technologies. The use of long reads has allowed to address several previously unsolved issues in the field, such as the resolution of complex genomic structures, and facilitated the access to metagenome assembled genomes (MAGs). Furthermore, the low cost and portability of platforms together with the development of rapid protocols and analysis pipelines have featured nanopore technology as an attractive and ever-growing tool for real-time in-field sequencing for environmental microbial analysis. This review provides an up-to-date summary of the experimental protocols and bioinformatic tools for the study of microbial communities using nanopore sequencing, highlighting the most important and recent research in the field with a major focus on infectious diseases. An overview of the main approaches including targeted and shotgun approaches, metatranscriptomics, epigenomics, and epitranscriptomics is provided, together with an outlook to the major challenges and perspectives over the use of this technology for microbial studies.

Full-length 16S rRNA gene amplicon analysis of human gut microbiota using MinION™ nanopore sequencing confers species-level resolution

Background

Species-level genetic characterization of complex bacterial communities has important clinical applications in both diagnosis and treatment. Amplicon sequencing of the 16S ribosomal RNA (rRNA) gene has proven to be a powerful strategy for the taxonomic classification of bacteria. This study aims to improve the method for full-length 16S rRNA gene analysis using the nanopore long-read sequencer MinION™. We compared it to the conventional short-read sequencing method in both a mock bacterial community and human fecal samples.

Results

We modified our existing protocol for full-length 16S rRNA gene amplicon sequencing by MinION™. A new strategy for library construction with an optimized primer set overcame PCR-associated bias and enabled taxonomic classification across a broad range of bacterial species. We compared the performance of full-length and short-read 16S rRNA gene amplicon sequencing for the characterization of human gut microbiota with a complex bacterial composition. The relative abundance of dominant bacterial genera was highly similar between full-length and short-read sequencing. At the species level, MinION™ long-read sequencing had better resolution for discriminating between members of particular taxa such as Bifidobacterium, allowing an accurate representation of the sample bacterial composition.

Conclusions

Our present microbiome study, comparing the discriminatory power of full-length and short-read sequencing, clearly illustrated the analytical advantage of sequencing the full-length 16S rRNA gene.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02094-5.

A lab in the field: applications of real-time, in situ metagenomic sequencing

High-throughput metagenomic sequencing is considered one of the main technologies fostering the development of microbial ecology. Widely used second-generation sequencers have enabled the analysis of extremely diverse microbial communities, the discovery of novel gene functions, and the comprehension of the metabolic interconnections established among microbial consortia. However, the high cost of the sequencers and the complexity of library preparation and sequencing protocols still hamper the application of metagenomic sequencing in a vast range of real-life applications. In this context, the emergence of portable, third-generation sequencers is becoming a popular alternative for the rapid analysis of microbial communities in particular scenarios, due to their low cost, simplicity of operation, and rapid yield of results. This review discusses the main applications of real-time, in situ metagenomic sequencing developed to date, highlighting the relevance of this technology in current challenges (such as the management of global pathogen outbreaks) and in the next future of industry and clinical diagnosis.

Rapid sequencing-based diagnosis of infectious bacterial species from meningitis patients in Zambia

OBJECTIVES

We have developed a portable system for the rapid determination of bacterial composition for the diagnosis of infectious diseases. Our system comprises of a nanopore technology-based sequencer, MinION, and two laptop computers. To examine the accuracy and time efficiency of our system, we provided a proof-of-concept for the detection of the causative bacteria of 11 meningitis patients in Zambia.

METHODS

We extracted DNA from cerebrospinal fluid samples of each patient and amplified the 16S rRNA gene regions. The sequencing library was prepared, and the sequenced reads were simultaneously processed for bacterial composition determination using the minimap2 software and the representative prokaryote genomes.

RESULTS

The sequencing results of four of the six culture-positive samples were consistent with those of conventional culture-based methods. The dominant bacterial species in each of these samples were identified from the sequencing data within only 3 min. Although the major bacterial species were also detected from the other two culture-positive samples and five culture-negative samples, their presence could not be confirmed. Moreover, as a whole, although the number of sequencing reads obtained within a short sequencing run was small, there was no change in the major bacterial species over time with prolonged sequencing. In addition, the processing time strongly correlated with the number of sequencing reads used for the analysis.

CONCLUSION

Our results suggest that time-effective analysis could be achieved by determining the number of sequencing reads required for the rapid diagnosis of infectious bacterial species depending on the complexity of bacterial species in a sample.