Limits of detection and limits of quantification for Longfin Smelt (Hooligans/Hoolies)

Based on the reading: Reporting the limits of detection and quantification for environmental DNA assays Klymus et al., 2019

Environmental DNA (eDNA) is used to find rare species and is being used in fishery and wildlife conservation and management strategies (for a definition of eDNA see the previous blog post). There is a need for standardization of eDNA methods and reporting. Limit of detection (LOD) and limit of quantification (LOQ) are not fully established for eDNA studies. At the SSRC we use quantitative PCR (qPCR) to detect eDNA of Longfin Smelt (a.k.a. Hooligans (a.k.a. Hoolies)) to detect low concentrations of eDNA in the Nooksack River and Bellingham Bay.

However, we not only want to know of the Hoolies are present, we also want to quantify them. There is confusion about how to define LOD and LOQ for qPCR studies. Conventional definitions of LOD and LOQ do not fit qPCR data - because the previous definitions require linear response. Data from qPCR are not linear and negative samples do not produce signal distinguishable from background signal. Therefore, Klymus and others (2019) sought to refine and standardize LOD and LOQ for use with qPCR.

"Our goal is to help establish standard LOD and LOQ definitions and guidelines to improve communication, inform data interpretation, and facilitate cross‐study comparisons, all of which support conservation and management decisions." Klymus et al., 2019

LOD in qPCR can be defined as the lowest concentration of target analyte that can be detected with a defined level of confidence.

"The LOD is based on detection/nondetection criteria and describes an assay's ability to detect the target sequence at low levels." Klymus et al., 2019

LOQ is the lowest amount of analyte in a sample that can be quantitatively determined with stated experimental conditions.

"...measurement of concentration is addressed by the LOQ, which reflects the assay's capacity to precisely quantify copy number." Klymus et al., 2019

For qPCR, precision can be assessed using the coefficient of variations (CV) of the measured concentrations of standards. Data from the replicate standard curves are evaluated as the

binary, qualitative outcome for LOD (detection/nondetection) and as the CV for LOQ:

Klymus and others (2019) brought together data from seven different laboratories, each used synthetic DNA (except on group used plasmid) for their standard curves.

The SSRC is using synthetic DNA. We need to be certain of the amount of target molecules present in test reactions. With synthetic DNA, a known concentration of DNA can be tested. We recently designed a segment of DNA that will be used as our standard for Hoolies.

Side note: in a dream I had last night, I envisioned the synthetic DNA of the Hoolies as a hologram that appeared between my palms.

To determine LOD and LOQ for an assay, standard concentrations of DNA must be used in many qPCR experiments. For LOD, they must also include a mix of positive and negative replicates. The accuracy and precision of LOD and LOQ calculations increase with replication.

Klymus and others (2019) suggest either (1) discrete thresholds for determining the LOD and LOQ for an eDNA qPCR assay, or (2) calculations to determine LOD and LOQ based on curve fitting performed by an R script (drc).

To facilitate the evaluation of eDNA assays Klymus and others suggest, at a minimum, along with parameters by Bustin et al., 2009 and Goldberg et al., 2016, do the following:

Reported LOD and LOQ values should be accompanied by:

1. the concentration range and number of replicate standards per concentration used for calculating LOD and LOQ.

2. the determination approach used (either the discrete threshold or curve-fitting modeling method) and,

3. the specific criteria for LOD probability of detection and LOQ precision that were applied.

Environmental DNA (eDNA) review article

This is a synopsis of the article: "Past, present and future perspectives of environmental DNA (eDNA metabarcoding: A systematic review in methods, monitoring, and applications of global eDNA" Ruppert et al., 2019

Ruppert and others (2019) offer a comprehensive review of all the ways scientists have utilized eDNA in the last 10 years. Examples include marine sediments (Sinniger et al., 2016; Guardiola et al., 2016, 2015; Pawlowski et al., 2011), biofilms (Leray and Knowlton, 2015), estuarine monitoring (Avó et al., 2017; Chariton et al., 2010, 2015), freshwater monitoring, fecal matter or stomach contents (Buglione et al., 2018) .

They include two sections that describe what constitutes eDNA as well as a discussion on the different methods for different sample types.

eDNA is DNA captured from an environmental sample without first isolating any target organisms (Taberlet, Coissac, Hajibabaei, & Rieseberg,2012). Traces of DNA can be from feces, mucus, skin cells, organelles, gametes or even extracellular DNA. Environmental DNA can be sampled from modern environments (e.g., seawater, freshwater, soil or air) or ancient environments (e.g., cores from sediment, ice or permafrost, see Thomsen & Willerslev, 2015).

As a new fish biologist, currently using eDNA and qPCR to detect Hoolies in the Nooksack, I kept wondering about whether or not certain signals last longer than others from different species (if oils or organics in certain fish preserve their DNA). eDNA can remain viable from weeks to hundreds of years.

The article further reminds us though of the complications and the limitations of the current technology. In fact, there is a section that emphasizes the importance of primer design.

Image 1. Picture of Birch Bay State Park. While reading this article, I kept thinking of ways that this method could be used to examine ocean microbiome circulation.

The implementation of eDNA metabarcoding would benefit from optimized bioinformatics, improved database quality, and taxonomic resolution.

For soil and sediment samples, large volumes of sample over larger spatial scales are required from larger size classes of organisms.

“eDNA has the application of citizen science by engagement of citizen collection of eDNA using commercially available sampling kits, involving the public in biodiversity sampling in a way that could be complementary to already established methods.”

The articles has a great tie-in to community outreach and citizen science. It was unexpected and an will be interesting concept to try to tie into future research endeavors and grant proposals.

Example of deep-sea sediment eDNA metabarcoding results

Figure 1 from Pawlowski et al. (2011). They used metabarcoding on marine sediments in abyssal Arctic and Southern Ocean environmental to examine deep-sea eukaryotic richness. They detected 942-1756 taxa per sample, dominated by dinoflagellates, cercozoans, ciliates, and euglenozoans; even photosynthetic taxa were present.

Avó, Ana & Daniell, Tim & Neilson, Roy & Oliveira, Solange & Branco, Jordana & Adão, Helena. (2017). DNA Barcoding and Morphological Identification of Benthic Nematodes Assemblages of Estuarine Intertidal Sediments: Advances in Molecular Tools for Biodiversity Assessment. Frontiers in Marine Science. 4. 10.3389/fmars.2017.00066.

Buglione, Maria & Maselli, Valeria & Rippa, Daniela & de Filippo, Gabriele & Trapanese, Martina & Fulgione, Domenico. (2017). A pilot study on the application of DNA metabarcoding for non-invasive diet analysis in the Italian hare. Mammalian Biology. 88. 10.1016/j.mambio.2017.10.010.

Guardiola M, Uriz MJ, Taberlet P, Coissac E, Wangensteen OS, et al. (2016) Correction: Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons. PLOS ONE 11(4): e0153836.

Leray M, Knowlton N. DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity. Proc Natl Acad Sci U S A. 2015;112(7):2076-2081. doi:10.1073/pnas.1424997112.

Pawlowski J, Christen R, Lecroq B, Bachar D, Shahbazkia HR, Amaral-Zettler L, et al. (2011) Eukaryotic Richness in the Abyss: Insights from Pyrotag Sequencing. PLoS ONE 6(4): e18169. https://doi.org/10.1371/journal.pone.0018169.

Ruppert, K. M., Kline, R. J., & Rahman, M. S. (2019, January 1). Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: A systematic review in methods, monitoring, and applications of global eDNA. Global Ecology and Conservation. Elsevier B.V. https://doi.org/10.1016/j.gecco.2019.e00547.

Sinniger, F., Pawlowski, J., Harii, S., Gooday, A.J., Yamamoto, H., Chevaldonné, P., Cedhagen, T., Carvalho, G., & Creer, S. (2016). Worldwide Analysis of Sedimentary DNA Reveals Major Gaps in Taxonomic Knowledge of Deep-Sea Benthos. Frontiers in Marine Science, 3, 1-14.

Review of an article on Nanopore sequencing

The Application of Nanopore Sequencing Technology to the Study of Dinoflagellates: A Proof of Concept Study for Rapid Sequence-Based Discrimination of Potentially Harmful Algae

Hatfield et al., 2020

The aim of this study was to explore the suitability of the MinION platform for the detection and discrimination of dinoflagellates in environmental samples. This is the first study to prove the suitability of nanopore sequencing technology for taxonomic identification of harmful algal bloom organisms using ~ 3KB amplicon that encompassed multiple regions of the rDNA cassette.