Metagenome Sequencing

Microbiomes contain diverse microbial communities whose interactions not only impact the system residents, but also have profound effects on the ecology, chemistry, and health of their shared host or environment. Capturing the interactions among microbes is essential as we expand our understanding of host-microbe dynamics, evaluate environmental degradation or remediation, and develop post-antibiotic-era therapies. Current insights in these fields are driven by genomic data which can classify taxa, report the abundances of metabolic pathways in a system, and define the microbial community structures that may differentiate health and disease states.

At SeqCenter, we aim to facilitate this research through our 16S/ITS amplicon services and our shotgun metagenomics services.

  • Metagenome Icon

    16S/ITS Sequencing

    The 16S/ITS amplicon approach uses targeted PCR amplification and sequencing of the hypervariable regions of rRNA genes. The results are then binned and queried against a database to provide a taxonomic abundance profile.

  • Metagenome Icon

    Shotgun Metagenomics

    Our Shotgun Metagenomics packages sequence randomly spread eDNA fragments within a sample and attempt to create metagenomic assemblies for the members of the community. This can provide a survey of functional genes within the community and a plethora of analytical opportunities.

We strongly encourage you to consult individual service pages for full details of the 16S/ITS amplicon sequencing services and the shotgun metagenomic services. Additionally, below is a brief comparison of the two approaches and a listing of example projects for various community types as a launch point for considering your options.

Comparison of 16S Amplicon and Shotgun Metagenomic Approaches

16S/ITS Shotgun Metagenomics
  • Volume: at least 20µL
  • Concentration: at least 10ng/µL recommended (any method)
  • Sample eluted into water or Tris/TE buffer
  • Volume: 30µL or more
  • Concentration: at least 10ng/µL (Qubit) or at least 20ng/µL (Nanodrop)
  • Sample eluted into water or Tris/TE buffer
  • ASV Classification
  • Identification (can be limited)
  • Functional gene content & function
  • Microbial community characterization
    • Novel organism discovery
    • Novel gene discovery
    • Metabolic function profiling
    • Resistance gene profiling
    • Phylogeny construction
  • More forgiving to low input
  • Lower cost for high throughput at a given depth
  • Low complexity analyses (simple interpretation)
  • Well-established references readily available
  • Provides information to characterize functional gene content of microbiome
  • Greater bioinformatics capabilities
  • Sequences organisms present at high read depth
  • Poorly classified communities lack adequate representation in queried databases
  • No functional gene content info
  • PCR amplification bias
  • Not as forgiving to low DNA concentration
  • Higher cost for given depth
  • High complexity bioinformatics applications
  • Susceptibility to host DNA contamination
  • Less developed, but rapidly evolving databases (requires well-developed references)
  • Zymo Quick-16S plus library prep
  • QIIME2 microbial analysis and comparison
  • Illumina DNA library prep (same as Illumina WGS packages)
  • Analysis utilizing Bowtie2, Samtools, NCBI database, and more
Data Received
  • Raw paired-end reads (2x301bp) as pairs of fastq files
  • Species Abundance Tables
  • Alpha and Beta Diversity
  • Taxonomic Assignment
  • Diversity Barplots by Taxonomic Rank
  • Raw paired-end reads (2x151bp) as pairs of fastq files
  • De novo metagenomic assembly and annotation
  • Taxonomic Assignment

Example Projects

The table below provides example projects, their applications, and potential limitations of each technology, which may serve as a guide when selecting a service appropriate for your project. Please note that applications listed are only recommendations. Always consult the most current literature in your field to determine an appropriate experimental design.

Community Description Recommended Approach Recommended Depth Rationale
Stool 16S/ITS 100k reads Since there is a high amount of diversity in this sample, we want many reads to ensure good coverage. The presence of host genomic material makes stool samples a poor candidate for shotgun metagenomics without a depletion step. Stool samples and stool pathogens are well represented in curated 16S/ITS databases.
Environmental swab (dry) 16S/ITS 20k-50k reads Dry swabs may not collect many microbes depending on the surface tested. Surfaces like cell phones, doorknobs, and public access tactile items are good candidates for dry swabs.
Environmental swab (wet) 16S/ITS or Shotgun Metagenomics 20k-50k reads or the small metagenome package Exogenous viruses are easily captured from wet swabs but will be missed in 16S analyses. The addition of water also allows more microbes to be collected from a surface.
Saliva 16S/ITS or Shotgun Metagenomics 50k-100k reads or the small metagenome package Saliva may encounter the same issues as a stool sample where high amounts of host DNA are carried through metagenomic preps. However, since the oral microbiome is not as well characterized as the gut microbiome, it presents as a good candidate for metagenomic sequencing if sequenced to a high enough depth.
Water (low biomass) 16S/ITS 20k reads With a low biomass, it is unlikely that a metagenome will assemble very well and may instead generate small noncontiguous sequenced fragments.
Water (high biomass) Shotgun Metagenomics Medium metagenome package High volumes of water can be passed through a two-micron filter to capture cells and enter extraction. These types of samples are good candidates for metagenomic sequencing as they likely contain organisms not previously described. The data may also present an opportunity to look for specific gene sets like bioremediatory metabolic pathways.
Clay/Soil 16S/ITS or Shotgun Metagenomics 50k-100k reads or the medium or large metagenome packages Soil is a commonly sequenced microbial sample. If looking for plant pathogens, chemical degrading microbes or gene set, or attempting to discern microbial-fungal interactions, shotgun metagenomics may be most appropriate.

If comparing taxa at different sampling sites, 16S or ITS may be a suitable approach.

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