Building of an Internal Transcribed Spacer (ITS) Gene Dataset to Support the Italian Health Service in Mushroom Identification

Summary

This research developed a genetic database to help quickly and accurately identify mushroom species, particularly those that can cause poisoning. This work is crucial for public health as mushroom poisoning affects thousands of people annually. The database helps healthcare providers identify toxic mushrooms faster to provide appropriate treatment. Impacts on everyday life: – Helps prevent mushroom poisoning by improving species identification – Enables faster medical response when poisoning occurs – Protects consumers from fraudulent mushroom products in markets – Supports safe wild mushroom foraging practices – Improves food safety monitoring systems

Background

Fungi represent a vast group of organisms with significant ecological and economic impact. Some produce mushrooms which are consumed worldwide, both wild-collected and cultivated. While mushrooms have nutritional value and fit current food trends, consumption carries risks of poisoning due to species misidentification. In Italy, mushroom poisoning is a public health concern with thousands of cases reported. DNA analysis using the Internal Transcribed Spacer (ITS) region has become a key method for mushroom identification, but requires comprehensive validated reference sequence datasets.

Objective

This study aimed to build and validate an ITS gene dataset to support the Italian Health Service in mushroom species identification, particularly focusing on species responsible for poisoning cases in the Tuscany region.

Results

From 7,270 initial sequences found in databases, 1,293 (17.8%) were discarded through filtering, resulting in 5,977 validated sequences. The researchers collected 97 specimens from 76 species and produced new reference sequences. The final dataset achieved 96.7% taxonomic coverage of target species. Validation showed 86.6% of reference sequences properly matched corresponding species with high identity values. The dataset proved particularly effective at identifying species commonly involved in poisoning cases.

Conclusion

The ITS gene dataset represents the first comprehensive attempt to collect reliable data supporting mushroom species identification, especially for poisoning cases. Its versatility and ability to be updated make it a valuable tool for the National Health Service in responding to poisoning incidents and supporting official control activities. The dataset can help guide appropriate medical treatment and detect fraud in commercial mushroom products.
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