Fish and invertebrates
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA833406 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Seafood fraud has become a global emerging issue, threatening food security and safety. Adulteration, substitution, dilution, and incorrect labeling of seafood products are fraudulent practices that violate consumer safety. In this context, developing sensitive, robust, and high-throughput molecular tools for food and feed authentication is becoming crucial for regulatory purposes. Analytical approaches such as proteomics mass spectrometry have shown promise in detecting incorrectly labeled products. For the application of these tools, genome information is crucial, but currently, for marine species of commercial importance, such information is unavailable. However, when combining proteomic analysis with spectra library matching, commercially important fish species were successfully identified, differentiated, and quantified in pure muscle samples and mixtures, even when genome information was scarce. This study further tested the previously developed proteomic-based spectra library-based approach was further tested to differentiate 29 fish species from the North Sea in individual samples, laboratory-prepared mixtures, and commercial samples. For authenticating libraries generated from 29 fish species, fresh muscle samples from the fish samples were matched against the reference libraries. Species of the fresh fish samples were correctly authenticated using the spectra libraries generated from the 29 fish species. Furthermore, processed commercial products containing mixtures of two or three fish species were matched against these spectra libraries to test the accuracy and robustness of this method for authentication of fish species. The results indicated that the method is suitable for the authentication of fish species from highly processed samples such as fish cakes and burgers. Spectra libraries built from 29 fish species in the North Sea can efficiently tackle current and future challenges in feed and food authentication analyses when prospecting new resources in the Arctic.
2024-04-23 | MSV000094602 | MassIVE
Project description:As described in our paper "Aspm knockout ferret reveals an evolutionary mechanism governing cerebral cortical size" (Johnson et al., Nature 2018), we used the standard Drop-seq method and analysis of Macosko et al. (2015) to capture, sequence, and analyze mRNA from single cells from Aspm wild-type, heterozygous, and knock-out littermate ferrets at embryonic day 35. Bulk reference samples were processed using standard Illumina mRNA-seq library prep and sequencing protocols, and the samples were described previously (Johnson, Wang et al., Nature Neurosci 2015)
2018-04-18 | GSE110010 | GEO
Project description:Currently as of 29/05/2019:
https://www.cancerresearchuk.org/about-cancer/find-a-clinical-trial/a-trial-looking-aspirin-and-fish-oil-possible-way-preventing-small-growths-forming-bowel-seafood
Previously:
http://cancerhelp.cancerresearchuk.org/trials/a-trial-looking-aspirin-and-fish-oil-possible-way-preventing-small-growths-forming-bowel-seafood
| 2407543 | ecrin-mdr-crc
Project description:Ricin, a protein found in castor seeds, is a lethal toxin that is designated as a category 2 select agent. Because castor seeds are easy to obtain and the toxin can be easily extracted, cases of attempted ricin poisoning are relatively common. A shotgun proteomics method for ricin identification has recently been developed (manuscript in preparation), in which ricin peptides are identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by proteomics database search, and peptide-spectrum matches are verified and compared to standard spectra by a human expert. To make this process more reproducible, objective, and high-throughput, we have created a ricin spectral library for peptide identification to supplement the human review step. To construct these spectral libraries, two pure ricin samples (from a proposed standard reference material) and crude castor seed extracts were digested with trypsin and analyzed using a standard shotgun LC-MS/MS protocol. Spectral libraries were created from the filtered search results from four database search tools. The library was then used in a search using SpectraST on samples from castor seeds. Analysis showed that the spectral library search resulted in more peptides identified from crude castor seed samples compared to MS-GF+ and Sequest plus Percolator. These results suggest that computational comparison of putative ricin peptide spectra to library spectra can be an effective method of confirming the presence of ricin, and that spectral library search may be suitable to augment the more manual and subjective aspects of the currently recommended human expert review.
2019-10-02 | PXD013711 | Pride
Project description:The application of machine learning has recently gained interest from ecotoxicological fields for its ability to model and predict chemical and/or biological processes, such as the prediction of bioconcentration. However, comparison of different models and the prediction of bioconcentration in invertebrates has not been previously evaluated. A comparison of 24 linear and machine learning models is presented herein for the prediction of bioconcentration in fish and important factors that influenced accumulation identified. R2 and root mean square error (RMSE) for the test data (n = 110 cases) ranged from 0.23-0.73 and 0.34-1.20, respectively. Model performance was critically assessed with neural networks and tree-based learners showing the best performance. An optimised 4-layer multi-layer perceptron (14 descriptors) was selected for further testing. The model was applied for cross-species prediction of bioconcentration in a freshwater invertebrate, Gammarus pulex. The model for G. pulex showed good performance with R2 of 0.99 and 0.93 for the verification and test data, respectively. Important molecular descriptors determined to influence bioconcentration were molecular mass (MW), octanol-water distribution coefficient (logD), topological polar surface area (TPSA) and number of nitrogen atoms (nN) among others. Modelling of hazard criteria such as PBT, showed potential to replace the need for animal testing. However, the use of machine learning models in the regulatory context has been minimal to date and is critically discussed herein. The movement away from experimental estimations of accumulation to in silico modelling would enable rapid prioritisation of contaminants that may pose a risk to environmental health and the food chain.
| S-EPMC6234108 | biostudies-literature
Project description:Vibrio harveyi, which belongs to family Vibrionaceae of class Gammaproteobacteria, includes the species V. carchariae and V. trachuri as its junior synonyms. The organism is a well-recognized and serious bacterial pathogen of marine fish and invertebrates, including penaeid shrimp, in aquaculture. Diseased fish may exhibit a range of lesions, including eye lesions/blindness, gastro-enteritis, muscle necrosis, skin ulcers, and tail rot disease. In shrimp, V. harveyi is regarded as the etiological agent of luminous vibriosis in which affected animals glow in the dark. There is a second condition of shrimp known as Bolitas negricans where the digestive tract is filled with spheres of sloughed-off tissue. It is recognized that the pathogenicity mechanisms of V. harveyi may be different in fish and penaeid shrimp. In shrimp, the pathogenicity mechanisms involved the endotoxin lipopolysaccharide, and extracellular proteases, and interaction with bacteriophages. In fish, the pathogenicity mechanisms involved extracellular hemolysin (encoded by duplicate hemolysin genes), which was identified as a phospholipase B and could inactivate fish cells by apoptosis, via the caspase activation pathway. V. harveyi may enter the so-called viable but nonculturable (VBNC) state, and resuscitation of the VBNC cells may be an important reason for vibriosis outbreaks in aquaculture. Disease control measures center on dietary supplements (including probiotics), nonspecific immunostimulants, and vaccines and to a lesser extent antibiotics and other antimicrobial compounds.
| S-EPMC7223180 | biostudies-literature
Project description:Industrial-scale harvest of species at risk of extinction is controversial and usually highly regulated on land and for charismatic marine animals (e.g. whales). In contrast, threatened marine fish species can be legally caught in industrial fisheries. To determine the magnitude and extent of this problem, we analyze global fisheries catch and import data and find reported catch records of 91 globally threatened species. Thirteen of the species are traded internationally and predominantly consumed in European nations. Targeted industrial fishing for 73 of the threatened species accounts for nearly all (99%) of the threatened species catch volume and value. Our results are a conservative estimate of threatened species catch and trade because we only consider species-level data, excluding group records such as 'sharks and rays.' Given the development of new fisheries monitoring technologies and the current push for stronger international mechanisms for biodiversity management, industrial fishing of threatened fish and invertebrates should no longer be neglected in conservation and sustainability commitments.
| S-EPMC7506527 | biostudies-literature
Project description:Wild type and creatine kinase knock-out mice were subjected to a multi-organ metabolomic and proteomics comparative analysis using a streamline sample preparation method which allowed both metabolite and proteomic analysis of each organ. The metabolites were spiked with an heavy internal reference metabolite standards and analyzed using optimized reverse phase HPLC analysis in both positive and negative mode on a Q Exactive Classic. A reference standard library consisting of over 600 reference metabolite standards were analyzed on this system for extra confidence in the identification and quantification of this library of key metabolites. This repository solely contains the metabolomic data. A second repository will contain the matched proteomic data.
2025-05-05 | MSV000097802 | MassIVE
Project description:We performed a parallel analysis of commonly used pre- and post-bisulfite WGBS library preparation protocols for their performance and quality of sequencing outputs. Our results show that bisulfite conversion per se generates pronounced sequencing biases, and subsequent fragmentation and amplification steps lead to several-fold overrepresentation of these artefacts. Standard pre-bisulfite library preparation methods lead to a significantly biased genomic sequence representation and a marked overestimation of methylation levels. We have integrated a bias diagnostic tool in the Bismark package and propose that amplification-free and post-bisulfite procedures should become the gold standard for WGBS library preparation.
2017-02-16 | GSE77961 | GEO