Tag Archives: 16S

Don’t forget the controls!

Almost every day new data about the composition of microbiomes are published. Many of these studies analyse the human microbiome, but also environmental samples.

Today we have the ability to sequence microbiomes in much more depth than a couple of years ago. Looking deeper sheds light on an important point: Contamination! In the very interesting publication of Salter et al. they could show that contaminating DNA is present in DNA extraction kits and other lab reagents.

The researchers sent dilutions of pure cultures of Salmonella bongori to three different institutes for DNA extraction and PCR, followed by sequencing on Illumina MiSeq. While S. bongori was the only organism identified in the undiluted samples, contaminating bacteria increased in relative abundance with higher degrees of dilution, and finally became dominant after the fifth dilution.

They did a similar analysis performing shotgun metagenomics of a pure S. bongori culture. This time, they used four different DNA extraction kits. Again, they saw that contamination increased with the degree of dilution, with contamination being the predominant feature after the fourth dilution. Also, they could show that each kit gave a different bacterial profile.

They also report on a study on the nasopharyngeal microbiota of children, analyzed over 2 years. They could show that using 4 different DNA extraction kits over time led to the false conclusion that differences in the microbial spectrum were associated with age. When DNA extraction was repeated on original samples using a different kit lot, the OTUs previously identified as contaminants were no longer detected.

In conclusion, contamination affected both 16S and metagenomic shotgun sequencing projects and was especially critical for samples with low biomass. Salter et al. present a list of potential contaminating organisms, as well as recommendations on how to cope with this problem. One recommendation is very obvious, and very effective: use negative controls!

Altogether, we should be very careful in planning our experiments in order to deliver results instead of artefacts. Especially, we need to be very careful when interpreting the data!

16S Amplicon Experiments: Which Platform to Choose?

Since 2010 several studies have been published that analyze microbial community composition by amplicon sequencing on the Illumina Genome Analyzer (GA). However, direct adaption of these protocols for sequencing on the HiSeq 2000 – the currently predominant Illumina sequencer – is not possible as both systems use different basecalling pipelines. Therefore amplicon sequencing on Illumina HiSeq 2000 is still left to the very experienced users and only a few publications can be studied on this.

In the meanwhile Illumina has introduced the MiSeq as the optimal platform for this kind of projects. In this context they have published an application note presenting sequencing of the V4 region of 16S rRNA genes on the MiSeq system.

And I totally agree that the MiSeq is a very good tool for these studies. For me, the most important advantages of the MiSeq layout in comparison to the sequencing on Illumina HiSeq 2000 are as follows:

  • Shorter turnaround time: The sequencing run itself takes a bit more than one full day, while a HiSeq 2000 run takes up to 12 days.
  • More informational content: By overlapping two paired end reads of 150 bp, full-length reads of about 250 bp can be generated
  • Potential for even longer reads: Illumina has announced read length of 250 bp for the end of the year. Then reads of up to 450 bp should be possible.

Nevertheless Roche GS FLX+ sequencing is still able to generate much longer reads with an average of up to 500-600 bp. And the long read length will provide a deeper insight into the microbiome of interest or more precisely higher classification efficiency down to species level. However Roche sequencing goes along with higher costs per base, so it will always be a decision based on the individual experiment, whether read length or sequencing depth is the most important factor.