Primer biases and implications
Most known primers used in amplifying microbial eukaryotic communities
are those reported by Stoeck et al. (2010) and Bradley et al. (2016) but
also suffer in their biases, which has implications in inferring
ecological insights on microbial communities. We then generated new
primer sets (Wolf 938 and Wolf 964) to complement the limitations of the
existing ones and evaluated their efficiency in silico using
known reference sequences, in vitro amplification using mock
communities, and their applicability in situ using environmental
samples.
Consistently, the different primer sets we tested (Wolf 938, Stoeck,
Wolf 964) were not able to amplify or provide high resolving power in
all target taxonomic groups, although all sets amplified some if not all
abundant taxa we expected based on microscopy (Lalande et al., 2016;
Nöthig et al., 2015). Relative to the three most dominant and
significant phytoplankton groups in the Arctic, the Stoeck and Wolf938
primers seemed to be good in detecting all three groups, but differences
were found at the sequence level. For example, while primers Stoeck and
Wolf938 were able to show ecotype-level variations in chlorophytes, they
did not exhibit sensitivity to the haptophytes. In contrast, Wolf964
demonstrated the alternating abundances between Emiliania andPhaeocystis but did not perform well in detecting the
chlorophytes. These results suggest that although we might come close to
generating a broader taxonomy-binding primer, a ‘universal one’ is still
not available. Primer usage then will ultimately depend on the questions
being asked and the groups being targeted, or a combination of primer
sets in case of exploratory work. This is especially true for the marine
environment, which possesses one of the highest microbial eukaryotic
diversities (see de Vargas et al., 2015).
We further observed disparity between in silico and in
situ tests. For example, Wolf938 did not perform well in silicoespecially in detecting diatoms but was able to amplify sequences and
even revealed patterns between Chaetoceros phylotypes from
environmental samples. This indicates that what works in silicomight not necessarily readily work in environmental samples and
vice-versa. These could be due to efficiency of nucleic acid extraction,
priming specificity, PCR biases, and sequencing-related issues, PCR
inhibition due to the presence of humic and fulvic acids, preservation
of the samples (Lever et al., 2015; Metfies et al., 2017), and
competition reaction between known and unknown taxa. It is important to
note however that limitations of currently used primers do not render
previous and ongoing efforts in investigating eukaryotic microbes wrong
or inaccurate. On the contrary, knowing such limitations provide new
insights, perspectives, and contexts in analyzing and interpreting
HTS-generated data. It is certain however that in some cases, these
biases in primers could limit our understanding of natural ecosystems or
even provide wrongful conclusions in interpreting data by missing out
certain taxa if not considered during analysis.