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Amplicon Metagenomics - 16S/ITS

 
 
Use amplicon metagenomics to:
  • Explore the taxonomic community composition – bacteria or fungi – of your samples
  • Compare taxonomic shifts within an experimental setup
  • Optimize your next sampling experiment

 

Overview

Considerations before starting a amplicon metagenomics project:

  • Which specific primer pair answers the questions?
  • What is the amplicon length?
  • Sequencing depth?
  • Amount of samples?
  • Sample complexity?
  • Experimental setup (replicates and conditions)?

Let us guide you – from design to analysis

Example projects using amplicon metagenomics:

  • Detect nutrition dependent gut bacterial community shifts
  • Investigate the genetic diversity of archaea in deep sea hydrothermal vent environments
  • Observe community shifts in a bioreactor setup
  • Characterize the fungi spores from air

Applications related to amplicon metagenomics:

  • Shotgun metagenomics
  • Shotgun metatranscriptomics

Workflow

 
A typical workflow for an amplicon metagenomics project is shown in the graphic below. Please note that our highly-modular processes allow you various entry and opting out options. If you outsource your entire NGS project to Microsynth or only parts of it is up to you.
 

For further reading and a detailed technical description, please download our Application 16S/ITS Metagenomics Sequencing (see related downloads).

Results

The analysis of microbial communities by amplicon sequencing of specific marker genes such as the prokaryotic 16S rRNA gene or fungal internal transcribed spacer regions (ITS) addresses the following major questions:

  1. How diverse is the microbial community including its richness and evenness (α-diversity)? (see Figure 1)
  2. Which organisms are present in the microbial community? (see Table 1)
  3. Are the communities in different samples or under certain conditions equal or are there differences and which organisms are differentially abundant (β-diversity)? (see Figure 2 and Table 2)

Our 16S/ITS metagenomics analysis module provides you with the answers to these main questions. Additionally our whole 16S/ITS metagenomics workflow has been validated starting from DNA extraction over library preparation and sequencing to the bioinformatics analysis. If you are interested in our validation process feel free to contact us.

Figure 1: Alpha diversity measures for the analyzed community including observed richness, Chao 1 indices representing the estimated richness and the Shannon diversity indices.

Figure 2: PCA based on UniFrac distances displaying inter-sample similarities. Samples were grouped by two conditions.

 
Table 1: This detail of a results table lists relative abundances and taxonomic identification of observed OTUs in the different samples. For taxonomic classification confidence values are calculated and OTUs are only classified in a specific rank if its confidence value is above a certain threshold to avoid dubious classifications and false-positive results.
 
Table 2: This detail of a results table shows differential abundance of OTUs between two conditions including statistical measures for differential abundance (log fold change) and significance (adjusted p-value).