Sequencing, Fast and Slow: Profiling Microbiomes in Human Samples with Nanopore Sequencing

Abstract

Rapid and accurate pathogen identification is crucial in effectively combating infectious diseases. However, the current diagnostic tools for bacterial infections predominantly rely on century-old culture-based methods. Furthermore, recent research highlights the significance of host–microbe interactions within the host microbiota in influencing the outcome of infection episodes. As our understanding of science and medicine advances, there is a pressing need for innovative diagnostic methods that can identify pathogens and also rapidly and accurately profile the microbiome landscape in human samples. In clinical settings, such diagnostic tools will become a powerful predictive instrument in directing the diagnosis and prognosis of infectious diseases by providing comprehensive insights into the patient’s microbiota. Here, we explore the potential of long-read sequencing in profiling the microbiome landscape from various human samples in terms of speed and accuracy. Using nanopore sequencers, we generate native DNA sequences from saliva and stool samples rapidly, from which each long-read is basecalled in real-time to provide downstream analyses such as taxonomic classification and antimicrobial resistance through the built-in software (<12 h). Subsequently, we utilize the nanopore sequence data for in-depth analysis of each microbial species in terms of host–microbe interaction types and deep learning-based classification of unidentified reads. We find that the nanopore sequence data encompass complex information regarding the microbiome composition of the host and its microbial communities, and also shed light on the unexplored human mobilome including bacteriophages. In this study, we use two different systems of long-read sequencing to give insights into human microbiome samples in the ‘slow’ and ‘fast’ modes, which raises additional inquiries regarding the precision of this novel technology and the feasibility of extracting native DNA sequences from other human microbiomes.

NAD: Noise-augmented direct sequencing of target nucleic acids by augmenting with noise and selective sampling

“…The second replicate has a better experimental output with twice more bases sequenced (4.79 Gb) as compared to the first replicate (2.14 Gb). This data output was below the theoretical output of MinION flow cells at 50 Gb, but achieving 10% of the theoretical capacity was typical data sizes generated with nanopore sequencing in the previous experiments [16]. The second replicate also has a better N50 estimate (40,320 b) which was around 5 times longer than that of the first replicate (Figure S2).…”

“…Moreover, it necessitates the quantification of DNA/RNA during each sequencing experiment, typically with a stringent quantity threshold. These experimental criteria often lead to the abandonment of direct sequencing or long-read sequencing in numerous studies [16].…”

A pangenome analysis of ESKAPE bacteriophages: the underrepresentation may impact machine learning models

“…Addressing these challenges in bacteriophage sequencing requires the development of specialized protocols, bioinformatics tools, and reference databases tailored to the unique characteristics of these viral entities. Recent advances in sequencing technologies and methodologies are continually improving our ability to overcome these obstacles and unravel the genetic intricacies of bacteriophages [58].…”

A pangenome analysis of ESKAPE bacteriophages: the underrepresentation may impact machine learning models

“…This shift in perspective is primarily attributed to a deeper understanding of the intricate relationships between bacteriophages and their bacterial hosts. Recent advances in sequencing technologies and methodologies are continually improving our ability to overcome these obstacles and unravel the genetic intricacies of bacteriophages (Park et al, 2023). In our future research endeavors, we are dedicated to tackling the issue of underrepresentation of phage-related data through comprehensive genome sampling initiatives, leveraging the latest advancements in long-read sequencing technology.…”