SPECIES DETECTION: ECHINODERMS

SEA CUCUMBERS

Kang Y. A., Lee S. R., Kim E. B., Park S. U., Lim S. M., Andriyono S., Kim H. W. (2022): Optimized pretreatment conditions for the environmental DNA (eDNA) analysis of Apostichopus japonicus. Fisheries and Aquatic Sciences 25: 264-275.
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Abstract
A non-destructive environmental DNA protocol for the genetic analysis of sea cucumber (Apostichopus japonicus) resources DNA was established. Among the several commercial DNA extraction kits, the DNeasy^® Plant Mini Kit was selected as the best choice to obtain the high-quality genomic DNAs from the mucous sea cucumber. As the temperature and incubation time increased, the amount of extracted environmental DNA was also large, but it was judged that the increased amount did not affect as much as 2–3 times. Therefore, these conditions were not considered to be the main factors to consider in actual environmental DNA extraction. However, the amount of seawater relative to the size of the sample was judged as a major consideration, and a sufficient amount of environmental DNA for analysis was secured when stored within 1 min while stirring the volume of seawater corresponding to the total sea cucumber weight (g). In securing the environmental DNA of sea cucumbers, the mortality rate of sea cucumbers in all experiments was 0, and it was judged that the effects of sea cucumbers were not significant through this treatment. Through the results of this study, sea cucumber DNA research, which has been conducted in a destructive method, can be conducted non-destructively through environmental DNA analysis. Through this study, we have secured a standard protocol that can successfully extract the sea cucumber DNA through environmental DNA. It is not only excellent in terms of time and cost of traditional DNA analysis method currently used, but it is completely non-destructive in the ecosystem of the survey area. It is believed that the system can be transformed in a way that does not affect it. However, it is thought that various standard protocols should be established considering the characteristics of each type.

Zhang L., Xing B., Wang W., Xu J. (2022): Sea cucumber detection algorithm based on deep learning. Sensors 22: 5717.
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The traditional single-shot multiBox detector (SSD) for the recognition process in sea cucumbers has problems, such as an insufficient expression of features, heavy computation, and difficulty in application to embedded platforms. To solve these problems, we proposed an improved algorithm for sea cucumber detection based on the traditional SSD algorithm. MobileNetv1 is selected as the backbone of the SSD algorithm. We increase the feature receptive field by receptive field block (RFB) to increase feature details and location information of small targets. Combined with the attention mechanism, features at different depths are strengthened and irrelevant features are suppressed. The experimental results show that the improved algorithm has better performance than the traditional SSD algorithm. The average precision of the improved algorithm is increased by 5.1%. The improved algorithm is also more robust. Compared with YOLOv4 and the Faster R-CNN algorithm, the performance of this algorithm on the P-R curve is better, indicating that the performance of this algorithm is better. Thus, the improved algorithm can stably detect sea cucumbers in real time and provide reliable feedback information.

Luo P., Ren C., Cheng C., Pan W., Jiang X., Jiang F., Ma B., Yu S., Zhang X., Chen T., Hu C. (2023): Applications of environmental DNA (eDNA) in monitoring the endangered status and evaluating the stock enhancement effect of tropical sea cucumber Holothuria scabra. Marine Biotechnology 25: 778-789.
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The tropical sea cucumber Holothuria scabra is naturally found in the Indo-West Pacific. However, due to their commercial value, natural H. scabra populations have declined significantly in recent years, resulting in its status as an endangered species. Surveys of H. scabra resource pose a challenge due to its specific characteristics, such as sand-burrowing behavior. To overcome this problem, our study established a convenient and feasible method for assessing H. scabra resources using environmental DNA (eDNA) monitoring technology. First, H. scabra-specific TaqMan primers and probe were designed based on its cox1 gene, followed by the development of an eDNA monitoring method for H. scabra in two separate sea areas (Xuwen and Daya Bay). The method was subsequently employed to investigate the distribution of H. scabra and assess the effects of aquaculture stock enhancement through juvenile releasing in the Weizhou Island sea area. The H. scabra eDNA monitoring approach was found to be more appropriate and credible than traditional methods, and a positive impact of stocking on H. scabra populations was observed. In summary, this is the first report to quantify eDNA concentration in a Holothuroidea species, and it provides a convenient and accurate method for surveying H. scabra resources. This study introduces novel concepts for eDNA-based detection of endangered marine benthic animals and monitoring their population distribution and abundance.

STARFISH

Uthicke S., Lamare M., Doyle J. R. (2018): eDNA detection of corallivorous seastar (Acanthaster cf. solaris) outbreaks on the Great Barrier Reef using digital droplet PCR. Coral Reefs 37: 1229-1239.
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Coral loss through consumption by corallivorous crown-of-thorns seastars (CoTS, Acanthaster spp.) is a major contributor to the coral reef crisis in the Indo-Pacific region. The fourth wave of Acanthaster cf. solaris outbreaks since the 1960s started around 2010 on Australia’s Great Barrier Reef. Ecological monitoring failed to detect early outbreak stages, thus preventing timely intervention. Here, we develop a digital droplet PCR (ddPCR)-based method to detect environmental DNA (eDNA) of CoTS in 2-l water samples that can be compared with abundances of the species recorded by divers along 200-m² transects. Aquarium tests demonstrated that eDNA was readily detectable and increases proportional to the biomass of CoTS (R² = 0.99, p < 0.0001). Adaptation from a quantitative PCR technique developed for CoTS larvae (Doyle et al. in Marine Biology 164:176, 2017) to ddPCR improved the limit of quantification (LOQ) by a factor of 45. During field verification on 11 reefs, CoTS eDNA was detectable on all reefs suffering outbreaks. In contrast, CoTS eDNA was absent from ‘post-outbreak’ reefs after populations collapsed and from ‘pre-outbreak’ reefs. In linear models, CoTS densities explained a high amount of variance of eDNA concentrations, both for water samples taken at the depth of transects (R² = 0.60, p < 0.0001) and on the sea surface (R² = 0.46, p = 0.0004). The proportion of samples above LOQ was also correlated with CoTS densities, with a similar amount of variance explained as for the concentration (underwater R² = 0.68, p < 0.0001; surface R² = 0.49, p = 0.0004). We conclude that, after consideration of sampling locations and times, this method is promising for CoTS population monitoring and early detection of outbreaks and might supplement or replace traditional monitoring. Development of automated samplers and possibly on board PCR in the future will further improve early detection.

Doyle J., Uthicke S. (2021): Sensitive environmental DNA detection via lateral flow assay (dipstick) – A case study on corallivorous crown‐of‐thorns sea star (Acanthaster cf. solaris) detection. Environmental DNA 3: 323-342.
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Environmental DNA (eDNA) represents an emerging opportunity for species monitoring in the marine environment. One aspect that poses challenges is the ability to detect target DNA without the complexity of specialized laboratory equipment. Lateral flow is an analytical technique that has been adopted in point-of-care diagnostics for human, veterinary, and agricultural health. Here, we aim to use lateral flow assay as a detection method for eDNA monitoring using a commercially available nucleic acid lateral flow device (PCRD™) in combination with previously developed species-specific mtDNA primers. Episodic population explosions of coral-eating crown-of-thorns sea star (CoTS) contribute significantly to the coral reef crisis on tropical Pacific coral reefs. Laboratory testing revealed our lateral flow assay developed for CoTS was as sensitive as digital droplet PCR and able to detect < 10 copies of target DNA, per PCR. Furthermore, the lateral flow assay was completed in less than half the time compared with digital droplet PCR and cost less than half that of digital droplet PCR. We applied this method to eDNA water samples collected in field locations where CoTS were present in low (=nonoutbreak) population densities and found lateral flow assay to be sufficiently sensitive to detect these populations. Detection of low-density CoTS populations is critical for early warning of outbreaks and leads to early management interventions (e.g., culling). Importantly, we demonstrate that with species-specific primers, the development and application of lateral flow assay methods for eDNA detection are feasible, for example, for invasive or threatened species, or those with high conservation value.

Uthicke S., Robson B., Doyle J. R., Logan M., Pratchett M. S., Lamare M. (2022): Developing an effective marine eDNA monitoring: eDNA detection at pre-outbreak densities of corallivorous seastar (Acanthaster cf. solaris). Science of the Total Environment 851: 158143.
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Outbreaks of the corallivorous Crown-of-Thorns Seastar (CoTS) Acanthaster cf. solaris contribute significantly to coral reef loss. Control of outbreaks is hampered because standard monitoring techniques do not detect outbreaks at early (low density) stages, thus preventing early intervention. We previously demonstrated that eDNA monitoring can detect CoTS at intermediate densities. Here, we test whether detection probability can be improved by (i) targeted site selection or collection at specific times and (ii) moving from an average eDNA copy number approach (based on the limit of quantification) to a presence/absence approach (based on the limit of detection). Using a dataset collected over three years and multiple reef sites, we demonstrated that adding water residence age, sea surface level and temperature into generalized linear models explained low amounts of variance of eDNA copy numbers. Site specific CoTS density, by contrast, was a significant predictor for eDNA copy numbers. Bayesian multi-scale occupancy modelling of the presence/absence data demonstrated that the probability of sample capture (θ) on most reefs with intermediate or high CoTS densities was >0.8. Thus, confirming CoTS presence on these reefs would only require 2–3 samples. Sample capture decreased with decreasing CoTS density. Collecting ten filters was sufficient to reliably (based on the lower 95 % Credibility Interval) detect CoTS below nominal outbreak levels (3 Ind. ha−1). Copy number-based estimates may be more relevant to quantify CoTS at higher densities. Although water residence age did contribute little to our models, sites with higher residence times may serve as sentinel sites accumulating eDNA. The approach based on presence or absence of eDNA facilitates eDNA monitoring to detect CoTS densities below outbreak thresholds and we continue to further develop this method for quantification.

Li L., Liu T., Huang H., Song H., He S., Li P., Gu Y., Chen J. (2023): An early warning model for starfish disaster based on multi-sensor fusion. Frontiers in Marine Science 10: 1167191.
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Starfish have a wide range of feeding habits, including starfish, sea urchins, sea cucumbers, corals, abalones, scallops, and many other marine organisms with economic or ecological value. The starfish outbreak in coastal areas will lead to severe economic losses in aquaculture and damage the ecological environment. However, the current monitoring methods are still artificial, time-consuming, and laborious. This study used an underwater observation platform with multiple sensors to observe the starfish outbreak in Weihai, Shandong Province. The platform could collect the temperature, salinity, depth, dissolved oxygen, conductivity, other water quality data, and underwater video data. Based on these data, the paper proposed an early warning model for starfish prevalence (EWSP) based on multi-sensor fusion. A deep learning-based object detection method extracts time-series information on the number of starfish from underwater video data. For the extracted starfish quantity information, the model uses the k-means clustering algorithm to divide the starfish prevalence level into four levels: no prevalence, mild prevalence, medium prevalence, and high prevalence. Correlation analysis concluded that the water quality factors most closely related to the starfish prevalence level are temperature and salinity. Therefore, the selected water quality factor and the number of historical starfish are inputted. The future starfish prevalence level of the starfish outbreak is used as an output to train the BP (back propagation) neural network to build EWSP based on multi-sensor fusion. Experiments show that the accuracy rate of this model is 97.26%, whose precision meets the needs of early warning for starfish outbreaks and has specific application feasibility.

Wang L., Xu J., Liu H., Wang S., Ou W., Zhang M., Wei F., Luo S., Chen B., Zhang S., Yu K. (2023): Ultrasensitive and on-site eDNA detection for the monitoring of crown-of-thorns starfish densities at the pre-outbreak stage using an electrochemical biosensor. Biosensors and Bioelectronics 230: 115265.
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The coral reef crisis has significantly intensified over the last decades, mainly due to severe outbreaks of crown-of-thorns starfish (COTS). Current ecological monitoring has failed to detect COTS densities at the pre-outbreak stage, thus preventing early intervention. In this work, we developed an effective electrochemical biosensor modified by a MoO₂/C nanomaterial, as well as a specific DNA probe that could detect trace COTS environmental DNA (eDNA) at a lower detection limit (LOD = 0.147 ng/μL) with excellent specificity. The reliability and accuracy of the biosensor were validated against the standard methods by an ultramicro spectrophotometer and droplet digital PCR (p > 0.05). The biosensor was then utilized for the on-site analysis of seawater samples from SYM-LD and SY sites in the South China Sea. For the SYM-LD site suffering an outbreak, the COTS eDNA concentrations were 0.33 ng/μL (1 m, depth) and 0.26 ng/μL (10 m, depth), respectively. According to the ecological survey, the COTS density was 500 ind/hm² at the SYM-LD site, verifying the accuracy of our measurements. At the SY site, COTS eDNA was also detected at 0.19 ng/μL, but COTS was not found by the traditional survey. Hence, larvae were possibly present in this region. Therefore, this electrochemical biosensor could be used to monitor COTS populations at the pre-outbreak stages, and potentially serve as a revolutionary early warning method. We will continue to improve this method for picomolar or even femtomolar detection of COTS eDNA.