Found three OTUs/ASV that are highly abundant in my sample. How likely are they to be true OTUs/ASVs?

[Diki (Diki P)]

I found three OTUs that are highly abundant in my sample. I have eight unique stool samples from eight laboratory mice. We want to look microbiome dynamics from three timepoints (three sequencing preparation batches of these mice).

We got results from second batch not long ago, and found above-mentioned three highly abundant OTUs in the second batch. We observe very small number of them in the previous first batch.
I noticed we used different thermal cycler between batches for PCR. We suspect that the second batch thermal cycler is in a very questionable condition, how likely are these OTUs to be a true results and not an artifact caused by faulty PCR process?

Details:

1. We measure V3-V4 16s region.
2. The OTUs taxa is d__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacterales;f__Morganellaceae;g__Proteus;__
3. This is the frequency according to table.qzv,
   

Thank you very much.

[Diki (Diki P)]

Hi, please let me know if I am not allowed to put some PCR bias amplification reference for my question above. Supposedly considered as spam for example.

• Aird, Daniel, et al. “Analyzing and Minimizing PCR Amplification Bias in Illumina Sequencing Libraries.” Genome Biology, vol. 12, no. 2, Feb. 2011, p. R18. BioMed Central, https://doi.org/10.1186/gb-2011-12-2-r18.

• Dabney, Jesse, and Matthias Meyer. “Length and GC-Biases during Sequencing Library Amplification: A Comparison of Various Polymerase-Buffer Systems with Ancient and Modern DNA Sequencing Libraries.” BioTechniques, vol. 52, no. 2, Feb. 2012, pp. 87–94. future-science.com (Atypon), https://doi.org/10.2144/000113809.

• Kanagawa, Takahiro. “Bias and Artifacts in Multitemplate Polymerase Chain Reactions (PCR).” Journal of Bioscience and Bioengineering, vol. 96, no. 4, Jan. 2003, pp. 317–23. ScienceDirect, https://doi.org/10.1016/S1389-1723(03)90130-7.

• Krehenwinkel, Henrik, et al. “Estimating and Mitigating Amplification Bias in Qualitative and Quantitative Arthropod Metabarcoding.” Scientific Reports, vol. 7, no. 1, Dec. 2017, p. 17668. www.nature.com, https://doi.org/10.1038/s41598-017-17333-x.

• Library Preparation for Next-Generation Sequencing: Dealing with PCR Bias. https://sequencing.roche.com/content/rochesequence/en/blog/library-preparation-for-next-generation-sequencing-dealing-with-pcr-bias.html. Accessed 27 Dec. 2021.

• PCR Amplification Bias. PCR amplification bias. Accessed 27 Dec. 2021.

• Silverman, Justin D., et al. “Measuring and Mitigating PCR Bias in Microbiota Datasets.” PLOS Computational Biology, vol. 17, no. 7, July 2021, p. e1009113. PLoS Journals, https://doi.org/10.1371/journal.pcbi.1009113.

• Warnecke, P. M., et al. “Detection and Measurement of PCR Bias in Quantitative Methylation Analysis of Bisulphite-Treated DNA.” Nucleic Acids Research, vol. 25, no. 21, Nov. 1997, pp. 4422–26. DOI.org (Crossref), https://doi.org/10.1093/nar/25.21.4422.

Thank you all.

[colinbrislawn (Colin J Brislawn)]

@Diki

how likely are these OTUs to be a true results and not an artifact caused by faulty PCR process?

Did you run any positive or negative controls on these runs? Were the positive controls axenic / monoculture, or multi-taxa communities?

[Diki (Diki P)]

@colinbrislawn

Did you run any positive or negative controls on these runs? Were the positive controls axenic / monoculture, or multi-taxa communities?

Hi! Thank you for your reply.

Unfortunately, we did not run any positive or negative controls.
However, I am curious with the follow up if we had run the controls. Suppose negative control was monoculture and it was these Proteus above. Can we quickly assume that Proteus is contaminant and therefore justifiable to be removed?

Thank you.

[colinbrislawn (Colin J Brislawn)]

Good afternoon!

@Diki

Unfortunately, we did not run any positive or negative controls.

That's a shame. But, now you know for next time!

@Diki

However, I am curious with the follow up if we had run the controls. Suppose negative control was monoculture and it was these Proteus above. Can we quickly assume that Proteus is contaminant and therefore justifiable to be removed?

Yes. Because you know the composition of positive controls, you can use them to calibrate other parts of the process. Just like you said, if these three mystery OTUs appears in your second batch of samples, including your monoculture control sample you ran on both Illumina runs, you could argue it's artificial and remove it.

It's possible that the second batch really does have a highly abundant g__Proteus in it.

Here's some more discussions of positive controls and filtering out strange microbes, if you are interested:

Tutorial for filtering controls

Hi, as different controls (sequencing controls, DNA extraction controls, sample blanks, field blanks etc.) become more and more common in amplicon studies I thought it might be helpful to provide a QIIME2 tutorial specifically dealing with filtering sequences/features of controls. Here, I would suggest additional filtering options: e.g. subtraction of control read counts from counts in feature tables, filtering of RSVs coming from DADA2 in a similar fashion as the exclude_seqs_by_blast.py scrip…

Discussion: methods for removing contaminants and cross-talk

Just to add further to this discussion, I've previously used decontam prior to it being incorporated into QIIME 2, and whilst I'm a huge fan of the principles it's built around, it didn't work fantastically for my samples. I will caveat that as I did only attempt the prevalence method with 2 negative controls (one kit negative and one sequencing negative) for around 20 samples, which is likely too low a number of controls to have any real statistical power, I'm not sure what the ideal number of …