Current challenges and best-practice protocols for microbiome analysis

Abstract

Analyzing the microbiome of diverse species and environments using next-generation sequencing techniques has significantly enhanced our understanding on metabolic, physiological and ecological roles of environmental microorganisms. However, the analysis of the microbiome is affected by experimental conditions (e.g. sequencing errors and genomic repeats) and computationally intensive and cumbersome downstream analysis (e.g. quality control, assembly, binning and statistical analyses). Moreover, the introduction of new sequencing technologies and protocols led to a flood of new methodologies, which also have an immediate effect on the results of the analyses. The aim of this work is to review the most important workflows for 16S rRNA sequencing and shotgun and long-read metagenomics, as well as to provide best-practice protocols on experimental design, sample processing, sequencing, assembly, binning, annotation and visualization. To simplify and standardize the computational analysis, we provide a set of best-practice workflows for 16S rRNA and metagenomic sequencing data (available at https://github.com/grimmlab/MicrobiomeBestPracticeReview).

Keywords: 16S rRNA sequencing; amplicon sequencing; assembly; functional and taxonomic classification; metagenomics; microbiome.

Figure 1

An illustration of targeted amplicon and metagenomic sequencing approaches. A schematic overview demonstrating diverse sample types along with commonly utilized sequencing platforms, as well as systematic and stepwise data processing steps.

Figure 2

A schematic overview outlining various experimental and computational challenges associated with 16S rRNA-based and shotgun metagenomic sequencing.

Figure 3

Major short-read and long-read sequencing technologies. (A) Illumina sequencing involves initial trimming, adenylation of the blunt ends and ligation of specific adapters to DNA molecules. Following this library, fragments are amplified in situ on flow cell surfaces through bridge amplification and produce sequencing clusters. Finally, reversible dye terminator sequencing step is implemented where single-nucleotide addition reactions and presence of blocking group at the 3′-OH (of the ribose moiety) help to identify sequencing clusters through a reporter fluorescent signal. (B) PacBio sequencing involves a circular consensus sequencing (CCS) SMRTbell technique. Herein, ligation of hairpin adapters to each end of a duplex DNA molecule forms a closed loop, which is sequenced in a zero-mode waveguide (ZMW), fluorescence-based readout of nucleotide incorporation. Each strand in the duplex DNA is sequenced together in multiple passes, and the consensus sequences from both strands are incorporated. (C) Nanopore sequencing involves ligation of hairpin adapters at one end of duplex DNA molecule before initiating nanopore sequencing of the linked original DNA strands. The blockades in ionic current through the nanopore are optimally quantified as DNA base sequences.

Figure 4

Best-practice protocol for the acquisition and analysis of targeted amplicon and shotgun metagenomics data from sequencing to functional annotation. The basic flow of experimental steps followed by downstream preprocessing and analysis steps is shown. At each step, the optimal tools utilized during the process are shown as well. All scripts are available at https://github.com/grimmlab/MicrobiomeBestPracticeReview.