Pros and cons of multi-omics strategies

Let’s begin by examining the pros and cons of using metabarcoding for biodiversity assessment compared to other omics strategies.

Pros of metabarcoding:

• Cost-effectiveness and speed: Metabarcoding is generally more affordable and faster than other omics approaches.
• Multiplexing capabilities: Thanks to advancements in barcoding and library preparation strategies (discussed earlier in this course), you can multiplex and sequence multiple samples simultaneously.
• Simplified computational costs: The computational requirements, including data storage and subsequent bioinformatics analyses, are relatively straightforward compared to multi-omics strategies.

Cons of metabarcoding:

• Limited taxonomic resolution: Metabarcoding often struggles with low taxonomic resolution, although this is gradually improving with the advent of long-read technologies. Additionally, since identifications rely on a single gene, this can affect the overall classification accuracy.
• Sequence artefacts: Random amplification via PCR can introduce sequence artefacts, leading to potential PCR-amplification bias.
• Dependency on extrapolation: Functional characterization of the microbiome based on single gene assays, like metabarcoding, relies on extrapolation, which can sometimes over- or under-estimate the functional aspects of the community.

In Contrast: pros of metagenomics (an omics approach)

Multi-omics approaches, especially metagenomics, can characterise a vast number of genomes in environmental samples through both taxonomic and functional analysis. Here are the benefits of using metagenomics for biodiversity studies:

• Comprehensive data: Metagenomics provides extensive information, including all genes in a community, their transcripts, enzymes, and metabolites.
• Functional profiling: It is particularly useful for functional profiling in microbial communities and can capture critical information related to viruses and other mobile genetic elements. Recent studies (Paoli et al. 2022) have demonstrated that multi-omic methodologies can recover novel genomes and functions from environmental systems, showcasing their advantages over amplicon-based strategies.

Cons of metagenomics:

• Time-consuming analysis: The analytical methods for metagenomics can be varied and time-intensive, with several methodologies currently under development, leading to potential inefficiencies in interoperability.
• High computational demands: Most analytical methods require significant computational resources and large data storage. The high costs associated with sequencing and analysis can make multi-omic approaches a considerable investment.

Moving forward

To fully understand and effectively integrate the omics strategies mentioned, it’s important to explore methods for combining various technologies. Extensive reviews on this topic are available, and we encourage you to check out the relevant literature (Arıkan and Muth 2023; and Martínez Arbas 2021) for more detailed information.

Take a moment to assess the strategy you’re using in your biodiversity project, focusing on its efficiency and cost-effectiveness. Consider whether a multi-omics approach is truly necessary, or if the metabarcoding approach is sufficient to answer your research question.

You can now continue to the next page to explore the advanced technologies used to study and understand diverse microbial communities.