Residue Analysis and Assessment of the Risk of Dietary Exposure to Domoic Acid in Shellfish from the Coastal Areas of China

Explainable machine learning for predicting the geographical origin of Chinese Oysters via mineral elements analysis

The traceability of geographic origin is essential for guaranteeing the quality, safety, and protection of oyster brands. However, the current outcomes of traceability lack credibility as they do not adequately explain the model's predictions. Consequently, we conducted a study to evaluate the efficacy of utilizing explainable machine learning combined with mineral elements analysis. The study findings revealed that 18 elements have the ability to determine regional orientation. Simultaneously, individuals should pay closer attention to the potential risks associated with oyster consumption due to the regional differences in essential and toxic elements they contain. Light gradient boosting machine (LightGBM) model exhibited indistinguishable performance, achieving flawless accuracy, precision, recall, F1 score and AUC, with values of 96.77%, 96.43%, 98.53%, 97.32% and 0.998, respectively. The SHapley Additive exPlanations (SHAP) method was used to evaluate the output of the LightGBM model, revealing differences in feature interactions among oysters from different provinces. Specifically, the features Na, Zn, V, Mg, and K were found to have a significant impact on the predictive process of the model. Consistent with existing research, the use of explainable machine learning techniques can provide insights into the complex connections between important product attributes and relevant geographical information.

Risk characteristics of shellfish toxins in Mytilus unguiculatus around the Zhoushan Islands, East China Sea

The Zhoushan Islands, are an important area for Mytilus unguiculatus aquaculture, and are threatened by potentially harmful algal blooms. However, a full understanding of the risks posed by their toxin residues is still lacking. M. unguiculatus samples were collected from the area between 2020 and 2021 and analyzed for their toxin profiles to assess the contamination status of shellfish toxins. The main toxins detected were the paralytic shellfish toxins (PSTs), gymnodimine (GYM), and domoic acid (DA). Nine PSTs components were detected, the dominant ones being C1, C2, and GTX5, with an overall detection rate of 85.7 %. The detection rate of DA was 55.05 %, and GYM was detected in all samples. The toxin levels in the samples were significantly lower than the European Union regulatory limits, but toxin contamination was generally universal.

Recombinase Polymerase Amplification Combined with Lateral Flow Dipstick Assay for the Rapid and Sensitive Detection of Pseudo-nitzschia multiseries

The harmful algal bloom (HAB) species Pseudo-nitzschia multiseries is widely distributed worldwide and is known to produce the neurotoxin domoic acid, which harms marine wildlife and humans. Early detection and preventative measures are more critical than late management. However, the major challenge related to early detection is the accurate and sensitive detection of microalgae present in low abundance. Therefore, developing a sensitive and specific method that can rapidly detect P. multiseries is critical for expediting the monitoring and prediction of HABs. In this study, a novel assay method, recombinase polymerase amplification combined with lateral flow dipstick (RPA-LFD), is first developed for the detection of P. multiseries. To obtain the best test results, several important factors that affected the amplification effect were optimized. The internal transcribed spacer sequence of the nuclear ribosomal DNA from P. multiseries was selected as the target region. The results showed that the optimal amplification temperature and time for the recombinase polymerase amplification (RPA) of P. multiseries were 37 °C and 15 min. The RPA products could be visualized directly using the lateral flow dipstick after only 3 min. The RPA-LFD assay sensitivity for detection of recombinant plasmid DNA (1.9 × 100 pg/μL) was 100 times more sensitive than that of RPA, and the RPA-LFD assay sensitivity for detection of genomic DNA (2.0 × 102 pg/μL) was 10 times more sensitive than that of RPA. Its feasibility in the detection of environmental samples was also verified. In conclusion, these results indicated that the RPA-LFD detection of P. multiseries that was established in this study has high efficiency, sensitivity, specificity, and practicability. Management measures made based on information gained from early detection methods may be able to prevent certain blooms. The use of a highly sensitive approach for early warning detection of P. multiseries is essential to alleviate the harmful impacts of HABs on the environment, aquaculture, and human health.

Online highly selective recognition of domoic acid by an aptamer@MOFs affinity monolithic column coupled with HPLC for shellfish safety monitoring

Enabling cost-effective safety monitoring of shellfish is an important measure for the healthy development of the coastal marine economy. Herein, a new aptamer@metal-organic framework (MOF)-functionalized affinity monolithic column was proposed and applied in selective in-tube solid-phase microextraction (IT-SPME) coupled with HPLC for the accurate recognition of domoic acid (DA) in shellfish. Using a surface engineering strategy, ZIF-8 MOF was grown in situ inside the poly(epoxy-MA-co-POSS-MA) hybrid monolith. A high BET surface area and abundant metal reactive sites of the MOF framework were obtained for anchoring massive aptamers with terminal-modified phosphate groups. Various characterizations, such as SEM, elemental mapping, XRD, and BET, were performed, and the affinity performance was also studied. The presence of a massive amount of aptamers with a super coverage density of 3140 μmol L-1 bound on ZIF-8 MOF activated a high-performance bionic-affinity interface, and perfect specificity was exhibited with little interference of tissue matrixes, thus assuring the highly selective capture of DA from the complex matrixes. Under the optimal conditions, DA toxins in shellfish were detected with the limit of detection (LOD) of 7.0 ng mL-1 (equivalent to 14.0 μg kg-1), representing a 5-28 fold enhancement in detection sensitivity over traditional SPE or MIP adsorbents reported previously. The recoveries of fortified mussel and clam samples were achieved as 91.8 ± 1.2%-94.1 ± 1.9% (n = 3) and 91.2 ± 1.1%-94.5 ± 3.6% (n = 3), respectively. This work sheds light on a cost-effective method for online selective IT-SPME and the accurate monitoring of DA toxins using an aptamer@MOF-mediated affinity monolith system coupled with the inexpensive HPLC-UV technique.

Age and Sex as Determinants of Acute Domoic Acid Toxicity in a Mouse Model

The excitatory neurotoxin domoic acid (DA) consistently contaminates food webs in coastal regions around the world. Acute exposure to the toxin causes Amnesic Shellfish Poisoning, a potentially lethal syndrome of gastrointestinal- and seizure-related outcomes. Both advanced age and male sex have been suggested to contribute to interindividual DA susceptibility. To test this, we administered DA doses between 0.5 and 2.5 mg/kg body weight to female and male C57Bl/6 mice at adult (7-9-month-old) and aged (25-28-month-old) life stages and observed seizure-related activity for 90 min, at which point we euthanized the mice and collected serum, cortical, and kidney samples. We observed severe clonic-tonic convulsions in some aged individuals, but not in younger adults. We also saw an association between advanced age and the incidence of a moderately severe seizure-related outcome, hindlimb tremors, and between advanced age and overall symptom severity and persistence. Surprisingly, we additionally report that female mice, particularly aged female mice, demonstrated more severe neurotoxic symptoms following acute exposure to DA than males. Both age and sex patterns were reflected in tissue DA concentrations as well: aged mice and females had generally higher concentrations of DA in their tissues at 90 min post-exposure. This study contributes to the body of work that can inform intelligent, evidence-based public health protections for communities threatened by more frequent and extensive DA-producing algal blooms.