Why Are Long-Read Sequencing Methods Revolutionizing Microbiome Analysis?

Abstract

Most of the knowledge available on the composition and functionality of microbial communities in different ecosystems comes from short-read sequencing methods. It implies limitations regarding taxonomic resolution, variant detection, and genome assembly contiguity. Long-read sequencing technologies can overcome these limitations, transforming the analysis of microbial community composition and functionality. It is essential to understand the characteristics of each sequencing technology to select the most suitable one for each microbiome study. This review aims to show how long-read sequencing methods have revolutionized microbiome analysis in ecosystems and to provide a practical tool for selecting sequencing methods. To this end, the evolution of sequencing technologies, their advantages and disadvantages for microbiome studies, and the new dimensions enabled by long-read sequencing technologies, such as virome and epigenetic analysis, are described. Moreover, desirable characteristics for microbiome sequencing technologies are proposed, including a visual comparison of available sequencing platforms. Finally, amplicon and metagenomics approaches and the sequencing depth are discussed when using long-read sequencing technologies in microbiome studies. In conclusion, although no single sequencing method currently possesses all the ideal features for microbiome analysis in ecosystems, long-read sequencing technologies represent an advancement in key aspects, including longer read lengths, higher accuracy, shorter runtimes, higher output, more affordable costs, and greater portability. Therefore, more research using long-read sequencing is recommended to strengthen its application in microbiome analysis.

Keywords: 16S; ecosystems; genome assembly; long-read sequencing; metagenomics; microbiome; taxonomic resolution; variants.

Figure 1

(a) Timeline with the introduction of sequencing technologies employed in microbiome research. (b) Schematic classification of first-, second-, and third-generation sequencing technologies employed in microbiome research. The key sequencing points for each sequencing technology amplification strategy are indicated (if utilized). In addition, the current use of each technology in microbiome research is provided below each technology. Abbreviations: bp, base pair; CRT, cyclic reversible termination; SBS, sequencing by synthesis; SBL, sequencing by ligation; SNA, single-nucleotide addition; SMRT, single-molecule real-time sequencing.

Figure 2

Comparison runtime (hours) for different ONT, PacBio, and Illumina sequencing platforms. Abbreviations: ONT, Oxford Nanopore Technologies; PacBio, Pacific Biosciences.

Figure 3

Comparison of maximum theoretical output per cell (Gb), total output/run (Gb), and sequencing speed (Gb/hour) across different ONT, PacBio, and Illumina sequencing platforms. Abbreviations: ONT, Oxford Nanopore Technologies; PacBio, Pacific Biosciences; P1, P1 flow cell; P2, P2 flow cell.

Figure 4

Comparison of sequencing instrument and cell prices for different ONT, PacBio, and Illumina sequencing platforms. (a) Instrument price ($). (b) Cell price ($). Abbreviations: ONT, Oxford Nanopore Technologies; PacBio, Pacific Biosciences; P1, P1 flow cell; P2, P2 flow cell.

Figure 5

Integrated overview of characteristics for microbiome analysis in ecosystems of commonly used sequencing platforms: ONT, PacBio, and Illumina. (a) Comparison of desirable characteristics among the different sequencing platforms: read length (bp), accuracy, runtime (hours), total output (Gb/run), instrument price ($), instrument portability, and bioinformatics expertise. (b) Global ranking of the different sequencing platforms, calculated by summing the scores assigned to each desirable characteristic.