Detection of Highly Poisonous Nerium oleander Using Quantitative Real-Time PCR with Specific Primers

An experimental study on the visual identification of Fritillaria ussuriensis based on LAMP and nucleic acid colloidal gold technique

Fritillaria ussuriensis Maxim is one of the traditional Chinese valuable herbs, which is the dried bulb of Fritillaria, a plant of the lily family. The identification of authenticity about F. ussuriensis is still technically challenging. In this study, visual identification was performed by ring-mediated isothermal amplification and nucleic acid colloidal gold techniques. Firstly, multiple sequence comparative analysis was performed by DNAMAN to find the differential sites of F. ussuriensis and its mixed pseudo-products, and the specific identification primers of F. ussuriensis were designed. Genomic DNA was extracted by the modified CTAB method, and the reaction system and reaction conditions were optimized to construct LAMP for the visual detection of F. ussuriensis, meanwhile, the genuine product was cloned and the extracted plasmid was sequenced. The specificity and sensitivity were detected, and also verified by nucleic acid colloidal gold method, and 20 commercially available samples were tested. The extracted DNA met the requirements of the experiment, and the genuine F. ussuriensis PCR product titrated on a test strip showed two bands on the T and C lines, while the counterfeit and negative control showed only one band on the C line, which matched the LAMP results. The specificity was 100 %, and the sensitivity of LAMP assay was up to 0.01 ng μL-1, while that of colloidal gold assay was 0.1 ng μL-1, thus the LAMP assay had high sensitivity. 14 out of 20 commercially available samples of F. ussuriensis were qualified, and 6 were unqualified, and the results of the two methods of identification were consistent. In this study, the combined detection method of LAMP and colloidal gold for nucleic acid was established to be specific, rapid, precise and visualized, which can provide a new technical idea for the detection of F. ussuriensis.

Identification of toxic Gelsemium elegans in processed food and honey based on real-time PCR analysis

Gelsemium elegans (GE) is a widely distributed hypertoxic plant that has caused many food poisoning incidents. Its pollen can also be collected by bees to produce toxic honey, posing a great threat to the health and safety of consumers. However, for the complex matrices such as cooked food and honey, it is challenging to perform composition analysis. It is necessary to establish more effective strategies for investigating GE contamination. In this study, the real-time PCR (qPCR) analysis combined with DNA barcode matK was proposed for the identification and detection of GE. Fifteen honey samples along with twenty-eight individuals of GE and the common confusable objects Lonicera japonica, Ficus hirta, Stellera chamaejasme and Chelidonium majus were gathered. Additionally, the food mixtures treated with 20-min boiling and 30-min digestion were prepared. Specific primers were designed, and the detection capability and sensitivity of qPCR in honey and boiled and digested food matrices were tested. The results demonstrated that the matK sequence with sufficient mutation sites was an effective molecular marker for species differentiation. GE and the confusable species could be clearly classified by the fluorescence signal of qPCR assay with a high sensitivity of 0.001 ng/μl. In addition, this method was successfully employed for the detection of deeply processed food materials and honey containing GE plants which even accounted for only 0.1 %. The sequencing-free qPCR approach undoubtedly can serve as a robust support for the quality supervision of honey industry and the prevention and diagnosis of food poisoning.

Development of nucleotide signatures for common poisonous organisms provides a new strategy for food poisoning diagnosis

DNA barcoding is widely used in toxic species authentication, but due to serious DNA degradation of forensic materials, the application of full-length barcode sequences in food poisoning diagnosis is greatly limited. Nucleotide signature, a shorter specific molecular marker, derived from traditional DNA barcoding has been proposed as an emerging tool of toxic species detection in deeply processed materials. In this study, to resolve the frequent food poisoning accidents with unknown origin, we envisioned developing a nucleotide signature data set of common poisonous organisms and combining high-throughput sequencing (HTS) to reveal the poisoning cause. Ninety-three individuals and 1093 DNA barcode sequences of twelve common poisonous plants, fish, mushrooms and their related species were collected. Through sequence alignment and screening, the nucleotide signatures were respectively developed and validated as their specific molecular markers. The sequence length varied from 19 bp to 38 bp. These fragments were conserved within the same species or genera, and the specificity between related species has been also demonstrated. To further evaluate the application potential of nucleotide signature in forensic diagnosis, simulated forensic specimens (SFS) containing different poisonous ingredients were sequenced by HTS with PCR-free libraries. As a result, the nucleotide signature was successfully captured from original HTS data without assembly and annotation, accompanied by a high detection sensitivity of 0.1 ng/µl in mixture system. Therefore, this method was suitable for the assay of forensic materials with serious DNA degradation. The present study undoubtedly provides a new perspective and strong support for the detection of toxic ingredients and the diagnosis of food poisoning.

Data Science and Plant Metabolomics

The study of plant metabolism is one of the most complex tasks, mainly due to the huge amount and structural diversity of metabolites, as well as the fact that they react to changes in the environment and ultimately influence each other. Metabolic profiling is most often carried out using tools that include mass spectrometry (MS), which is one of the most powerful analytical methods. All this means that even when analyzing a single sample, we can obtain thousands of data. Data science has the potential to revolutionize our understanding of plant metabolism. This review demonstrates that machine learning, network analysis, and statistical modeling are some techniques being used to analyze large quantities of complex data that provide insights into plant development, growth, and how they interact with their environment. These findings could be key to improving crop yields, developing new forms of plant biotechnology, and understanding the relationship between plants and microbes. It is also necessary to consider the constraints that come with data science such as quality and availability of data, model complexity, and the need for deep knowledge of the subject in order to achieve reliable outcomes.

Forensic botany: who?, how?, where?, when?

Plants are a good source of biological forensic evidence; this is due to their ubiquity, their ability to collect reference material, and their sensitivity to environmental changes. However, in many countries, botanical evidence is recognised as being scientifically. Botanical evidence is not mostly used for perpertration, instead it tends to serve as circumstantial evidence. Plant materials constitute the basis, among others, for linking a suspect or object to a crime scene or a victim, confirming or not confirming an alibi, determining the post-mortem interval, and determining the origin of food/object. Forensic botany entails field work, knowledge of plants, understanding ecosystem processes, and a basis understaning of geoscience. In this study, experiments with mammal cadavers were conducted to determine the occurence of an event. The simplest criterion characterising botanical evidence is its size. Therefore, macroremains include whole plants or their larger fragments (e.g. tree bark, leaves, seeds, prickles, and thorns), whereas microscopic evidence includes palynomorphs (spores and pollen grains), diatoms, and tissues. Botanical methods allow for an analysis to be repeated multiple times and the test material is easy to collect in the field. Forensic botany can be supplemented with molecular analyses, which, although specific and sensitive, still require validation.