Recognizing false positives: synthetic oligonucleotide controls for environmental DNA surveillance

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Time to get real with qPCR controls: The frequency of sample contamination and the informative power of negative controls in environmental DNA studies

Environmental (e)DNA methods have enabled rapid, sensitive and specific inferences of taxa presence throughout diverse fields of ecological study. However, use of eDNA results for decision-making has been impeded by uncertainties associated with false positive tests putatively caused by sporadic or systemic contamination. Sporadic contamination is a process that is inconsistent across samples and systemic contamination occurs consistently over a group of samples. Here, we used empirical data and laboratory experiments to (i) estimate the sporadic contamination rate for each stage of a common, targeted eDNA workflow employing best practice quality control measures under simulated conditions of rare and common target DNA presence, (ii) determine the rate at which negative controls (i.e., "blanks") detect varying concentrations of systemic contamination, and (iii) estimate the effort that would be required to consistently detect sporadic and systemic contamination. Sporadic contamination rates were very low across all eDNA workflow steps, and, therefore, an intractably high number of negative controls (>100) would be required to determine occurrence of sporadic contamination with any certainty. Contrarily, detection of intentionally introduced systemic contamination was more consistent; therefore, very few negative controls (<5) would be needed to consistently alert to systemic contamination. These results have considerable implications to eDNA study design when resources for sample analyses are constrained.

The Elephant in the Lab (and Field): Contamination in Aquatic Environmental DNA Studies

The rapid evolution of environmental (e)DNA methods has resulted in knowledge gaps in smaller, yet critical details like proper use of negative controls to detect contamination. Detecting contamination is vital for confident use of eDNA results in decision-making. We conducted two literature reviews to summarize (a) the types of quality assurance measures taken to detect contamination of eDNA samples from aquatic environments, (b) the occurrence, frequency and attribution (i.e., putative sources) of unexpected amplification in these quality assurance samples, and (c) how results were interpreted when contamination occurred. In the first literature review, we reviewed 156 papers and found that 91% of targeted and 73% of metabarcoding eDNA studies reported inclusion of negative controls within their workflows. However, a large percentage of targeted (49%) and metabarcoding (80%) studies only reported negative controls for laboratory procedures, so results were potentially blind to field contamination. Many of the 156 studies did not provide critical methodological information and amplification results of negative controls. In our second literature review, we reviewed 695 papers and found that 30 targeted and 32 metabarcoding eDNA studies reported amplification of negative controls. This amplification occurred at similar proportions for field and lab workflow steps in targeted and metabarcoding studies. These studies most frequently used amplified negative controls to delimit a detection threshold above which is considered significant or provided rationale for why the unexpected amplifications did not affect results. In summary, we found that there has been minimal convergence over time on negative control implementation, methods, and interpretation, which suggests that increased rigor in these smaller, yet critical details remains an outstanding need. We conclude our review by highlighting several studies that have developed especially effective quality assurance, control and mitigation methods.

Sewage analysis as a tool for the COVID-19 pandemic response and management: the urgent need for optimised protocols for SARS-CoV-2 detection and quantification

COVID-19 is an ongoing global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of July 29th 2020, more than 16,6 million cases have been reported in more than 188 countries/territories, leading to more than 659000 deaths. One of the main challenges facing health authorities has been testing for the virus on a sufficiently comprehensive scale. The pandemic has been an impetus for the wastewater community as it has inspired scientists to look to wastewater to help fill in the gap of measuring the prevalence of SARS-CoV-2 within a given community. Testing the wastewater may serve as an early warning system allowing timely interventions. Although viral shedding varies among individuals and over the course of their infection, the sewage system can blend these variations into an average that represents the wider studied community. The urgent need has led to a lack of coherent reporting of data regarding the analysis, as these huge and remarkable efforts by the wastewater scientific community were made in a very short time. Important information on the analytical approach is often lacking, while there is still no optimisation of the methodology, including sampling, sample storage and concentration, RNA extraction and detection/quantification. This review aims at identifying the main issues for consideration, relating to the development of validated methodological protocols for the virus quantitative analysis in wastewater. Their inclusion will enable the methodological optimisation of SARS-CoV-2 wastewater analyses, transforming the wastewater infrastructure into a source of useful information for the health sector.

Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance

Trap-based surveillance strategies are widely used for monitoring of invasive insect species, aiming to detect newly arrived exotic taxa as well as track the population levels of established or endemic pests. Where these surveillance traps have low specificity and capture non-target endemic species in excess of the target pests, the need for extensive specimen sorting and identification creates a major diagnostic bottleneck. While the recent development of standardized molecular diagnostics has partly alleviated this requirement, the single specimen per reaction nature of these methods does not readily scale to the sheer number of insects trapped in surveillance programmes. Consequently, target lists are often restricted to a few high-priority pests, allowing unanticipated species to avoid detection and potentially establish populations. DNA metabarcoding has recently emerged as a method for conducting simultaneous, multi-species identification of complex mixed communities and may lend itself ideally to rapid diagnostics of bulk insect trap samples. Moreover, the high-throughput nature of recent sequencing platforms could enable the multiplexing of hundreds of diverse trap samples on a single flow cell, thereby providing the means to dramatically scale up insect surveillance in terms of both the quantity of traps that can be processed concurrently and number of pest species that can be targeted. In this review of the metabarcoding literature, we explore how DNA metabarcoding could be tailored to the detection of invasive insects in a surveillance context and highlight the unique technical and regulatory challenges that must be considered when implementing high-throughput sequencing technologies into sensitive diagnostic applications.

A Brief Review of Non-Avian Reptile Environmental DNA (eDNA), with a Case Study of Painted Turtle (Chrysemys picta) eDNA Under Field Conditions

Environmental DNA (eDNA) is an increasingly used non-invasive molecular tool for detecting species presence and monitoring populations. In this article, we review the current state of non-avian reptile eDNA work in aquatic systems, and present a field experiment on detecting the presence of painted turtle (Chrysemys picta) eDNA. Thus far, turtle and snake eDNA studies have shown mixed results in detecting the presence of these animals under field conditions. However, some instances of low detection rates and non-detection occur for these non-avian reptiles, especially for squamates. We explored non-avian reptile eDNA quantification by sampling four lentic ponds with different densities (0 kg/ha, 6 kg/ha, 9 kg/ha, and 13 kg/ha) of painted turtles over three months to detect differences in eDNA using a qPCR assay amplifying the COI gene of the mtDNA genome. Only one sample of the highest-density pond amplified eDNA for a positive detection. Yet, estimates of eDNA concentration from pond eDNA were rank-order correlated with turtle density. We present the “shedding hypothesis”—the possibility that animals with hard, keratinized integument do not shed as much DNA as mucus-covered organisms—as a potential challenge for eDNA studies. Despite challenges with eDNA inhibition and availability in water samples, we remain hopeful that eDNA can be used to detect freshwater turtles in the field. We provide key recommendations for biologists wishing to use eDNA methods for detecting non-avian reptiles.