Environmental DNA (eDNA) analysis has gained traction as a precise and cost-effective method for species and waterways management. To date, publications on eDNA protocol optimization have focused primarily on DNA yield. Therefore, it has not been possible to evaluate the cost and speed of specific components of the eDNA protocol, such as water filtration and DNA extraction method when designing or choosing an eDNA protocol. At the same time, these two parameters are essential for the experimental design of a project. Here we evaluate and rank 27 different eDNA protocols in the context of Chinook salmon (Oncorhynchus tshawytscha) eDNA detection in an estuarine environment. We present a comprehensive evaluation of multiple eDNA protocol parameters, balancing time, cost and DNA yield. We collected samples composed of 500 mL estuarine water from Deverton Slough (38˚11'16.7"N 121˚58'34.5"W) and 500 mL from tank water containing 1.3 juvenile Chinook Salmon per liter. Then, we compared extraction methods, filter types, use of inhibitor removal kit for DNA yield, processing time, and protocol cost. Lastly, we used an MCMC algorithm together with machine learning to understand the DNA yield of each step of the protocol as well as the interactions between those steps. Glass fiber filtration was to be the most resilient to high turbidites, filtering the samples in 2.32 ± 0.08 min instead of 14.16 ± 1.86 min and 6.72 ± 1.99 min for nitrocellulose and paper filter N1, respectively. The filtration DNA yield percentages for paper filter N1, glass fiber, and nitrocellulose were 0.00045 ± 0.00013, 0.00107 ± 0.00013, 0.00172 ± 0.00013. The DNA extraction yield percentage for QIagen, dipstick, NaOH, magnetic beads, and direct dipstick ranged from 0.047 ± 0.0388 to 0.475 ± 0.0357. For estuarine waters, which are challenging for eDNA studies due to high turbidity, variable salinity, and the presence of PCR inhibitors, we found that a protocol combining glass filters, magnetic beads, and an extra step for PCR inhibitor removal, is the method that best balances time, cost, and yield. In addition, we provide a generalized decision tree for determining the optimal eDNA protocol for other studies in aquatic systems. Our findings should be applicable to most aquatic environments and provide a clear guide for determining which eDNA protocol should be used under different study constraints.

Environmental DNA (eDNA) detection methods can complement traditional biomonitoring to yield new ecological insights in aquatic systems. However, the conceptual and methodological frameworks for aquatic eDNA detection and interpretation were developed primarily in freshwater environments and have not been well established for estuaries and marine environments that are by nature dynamic, turbid, and hydrologically complex. Environmental context and species life history are critical for successful application of eDNA methods, and the challenges associated with eDNA detection in estuaries were the subject of a symposium held at the University of California Davis on January 29, 2020 (https://marinescience.ucdavis.edu/engagement/past-events/edna). Here, we elaborate upon topics addressed in the symposium to evaluate eDNA methods in the context of monitoring and biodiversity studies in estuaries. We first provide a concise overview of eDNA science and methods, and then examine the San Francisco Estuary (SFE) as a case study to illustrate how eDNA detection can complement traditional monitoring programs and provide regional guidance on future potential eDNA applications. Additionally, we offer recommendations for enhancing communication between eDNA scientists and natural resource managers, which is essential for integrating eDNA methods into existing monitoring programs. Our intent is to create a resource that is accessible to those outside the field of eDNA, especially managers, without oversimplifying the challenges or advantages of these methods.

Tracking and quantifying the abundance and location of cells in the developing brain is essential in neuroscience research, enabling a greater understanding of mechanisms underlying nervous system morphogenesis. Widely used experimental methods to quantify cells labeled with fluorescent markers, such as immunohistochemistry (IHC),in situhybridization, and expression of transgenes via stable lines or transientin uteroelectroporations (IUEs), depend on accurate and consistent quantification of images. Current methods to quantify fluorescently-labeled cells rely on labor-intensive manual counting approaches, such as the Fiji pluginCell Counter, which requires custom macros to enable higher-throughput analyses. Here, we present RapID Cell Counter, a semi-automated cell-counting tool with an easy-to-implement graphical user interface (GUI), which facilitates quick and consistent quantifications of cell density within user-defined boundaries that can be divided into equally-partitioned segments. Compared with the standard manual counting approach, we show that RapID matched accuracy and consistency and only required ∼10% of user time relative to manual counting methods, when quantifying the distribution of fluorescently-labeled neurons in mouse IUE experiments. Using RapID, we recapitulated previously published work focusing on two genes,SRGAP2andCUL5, important for projection neuron (PN) migration in the neocortex and used it to quantify PN displacement in a mouse knock-out model ofRBX2. Moreover, RapID is capable of quantifying other cell types in the brain with complex cell morphologies, including astrocytes and dopaminergic neurons. We propose RapID as an efficient method for neuroscience researchers to process fluorescently-labeled brain images in a consistent, accurate, and mid-throughput manner.

The use of environmental DNA (eDNA) to monitor species in aquatic environments has rapidly increased over the past decade. eDNA has consistently outperformed other methods of detection, yet eDNA relies on an indirect measure to estimate the real distribution of a species. Therefore, understanding the environmental factors that disperse eDNA is of major importance. Here we modeled the use of transect sampling for eDNA studies and also model the impact of river advection on detection radius and the expected probability of detection. Our model suggests that transect sampling: 1) increases the detection probability for both rare and common species, thus reducing the frequency of false negatives, 2) diminishes the standard deviation of the detection probability, which in most cases means higher reproducibility of eDNA studies, 3) better estimates systemwide trends of fish population distinguishing zones of multiple fishes from zones where few fishes are present, and 4) diminishes the effects of eddies and river velocity on the detection probability and detection radius. We propose the use of transect sampling as an alternative method of eDNA sampling with benefits that surpass the disadvantages of not being able to pinpoint the exact fish location. Our model also suggests that even short transects (less than 100 m) can yield considerable benefits compared to point sampling.