Mycobiota contaminating some market cake samples with reference to their toxin and enzyme.

Fungi can spoil the majority of baked products. Spoilage of cake during storage is commonly associated with fungi. Therefore, this study aimed to assess the quality of different types of cakes sold in the market. The most predominant fungal genera in the tested cake samples (14 samples) were Aspergillus spp., and Penicillium spp. On Potato Dextrose Agar (PDA), the medium fungal total count was 43.3 colonies /g. Aspergillus was the most dominant genus and was isolated from six samples of cake. Aspergillus was represented by 3 species namely, A. flavus, A. niger, and A. nidulans, represented by 13.32, 19.99, and 3.33 colonies /g respectively. On Malt Extract Agar (MEA) Medium, the fungal total count was 123.24 colonies / g. Aspergillus was the most dominant isolated genus from 11 samples of cake and was represented by 5 species, namely, A. flavus, A. niger, A. ochraceous, A. terreus, and A. versicolor (26. 65, 63.29, 3.33, 6.66, and 3.33 colonies / g , respectively). Twenty-four isolates (88.88 %) of the total tested twenty-seven filamentous fungi showed positive results for amylase production. Ten isolates (37.03%) of the total tested filamentous fungi showed positive results for lipase production, and finally eleven isolates (40.74 %) of the total fungal isolates showed positive results for protease production. Aflatoxins B1, B2, G1, G2, and ochratoxin A were not detected in fourteen collected samples of cake. In this study, clove oil was the best choice overpeppermint oil and olive oil for preventing mold development when natural agents were compared. It might be due to the presence of a varietyof bioactive chemical compounds in clove oil, whose major bioactive component is eugenol, which acts as an antifungal reagent. Therefore, freshly baked cake should be consumed within afew days to avoid individuals experiencing foodborne illnesses.

A metabolomic approach to target antimalarial metabolites in the Artemisia annua fungal endophytes.

Fungal endophytes are a major source of anti-infective agents and other medically relevant compounds. However, their classical blinded-chemical investigation is a challenging process due to their highly complex chemical makeup. Thus, utilizing cheminformatics tools such as metabolomics and computer-aided modelling is of great help deal with such complexity and select the most probable bioactive candidates. In the present study, we have explored the fungal endophytes associated with the well-known antimalarial medicinal plant Artemisia annua for their production of further antimalarial agents. Based on the preliminary antimalarial screening of these endophytes and using LC-HRMS-based metabolomics and multivariate analyses, we suggested different potentially active metabolites (compounds 1-8). Further in silico investigation using the neural-network-based prediction software PASS led to the selection of a group of quinone derivatives (compounds 1-5) as the most possible active hits. Subsequent in vitro validation revealed emodin (1) and physcion (2) to be potent antimalarial candidates with IC50 values of 0.9 and 1.9 µM, respectively. Our approach in the present investigation therefore can be applied as a preliminary evaluation step in the natural products drug discovery, which in turn can facilitate the isolation of selected metabolites notably the biologically active ones.