黄曲霉毒素(AF)和曲霉毒素A(OTA)是具有致癌性的真菌代谢产物,致畸,胚胎毒性,基因毒性,神经毒性,以及对人类和动物的免疫抑制作用。植物性食品的消费增加和与气候变化相关的环境条件加剧了霉菌毒素中毒的风险。本研究旨在研究11个选定的乳酸菌菌株降低/抑制黄曲霉生长的能力,寄生曲霉,碳曲霉,黑曲霉,Welwitschiae曲霉,骨化曲霉,西季曲霉,不同温度条件下的灰青霉和AF和OTA产量。数据通过方差分析处理,建立了能够预测生长抑制率的机器学习(ML)模型,并对他们的表现进行了比较。所有因素LAB菌株,真菌物种,和温度显着影响真菌生长和霉菌毒素的产生。真菌生长抑制范围为0-100%。总的来说,对LAB处理最敏感的真菌是疣状芽胞杆菌和A。而最不敏感的是A.Niger和A.welwitschiae。具有最高抗真菌活性的LAB菌株是戊糖片球菌(菌株S11sMM和M9MM5b)。AF的降低范围为19.0%(黄曲霉毒素B1)-60.8%(黄曲霉毒素B2),OTA,7.3-100%,取决于细菌和真菌菌株和温度。具有最高抗AF活性的LAB菌株是戊糖假单胞菌和中肠明串珠菌的三个菌株。右旋糖酐(T2MM3),具有最高抗OTA活性的是副干酪明串珠菌。副干酪(3T3R1)和中肠曲霉菌。右旋糖酐(T2MM3)。预测真菌生长抑制的最佳ML方法是多层感知器神经网络,其次是随机森林。由于抗真菌和抗霉菌毒素的能力,本研究中使用的LABs菌株可能是针对黄曲霉毒素和曲霉毒素真菌以及AFL和OTA积累的生物防治剂。
Aflatoxins (AF) and ochratoxin A (OTA) are fungal metabolites that have carcinogenic, teratogenic, embryotoxic, genotoxic, neurotoxic, and immunosuppressive effects in humans and animals. The increased consumption of plant-based foods and environmental conditions associated with climate change have intensified the risk of mycotoxin intoxication. This study aimed to investigate the abilities of eleven selected LAB strains to reduce/inhibit the growth of Aspergillus flavus, Aspergillus parasiticus, Aspergillus carbonarius, Aspergillus niger, Aspergillus welwitschiae, Aspergillus steynii, Aspergillus westerdijkiae, and Penicillium verrucosum and AF and OTA production under different temperature regiments. Data were treated by ANOVA, and machine learning (ML) models able to predict the growth inhibition percentage were built, and their performance was compared. All factors LAB strain, fungal species, and temperature significantly affected fungal growth and mycotoxin production. The fungal growth inhibition range was 0-100%. Overall, the most sensitive fungi to LAB treatments were P. verrucosum and A. steynii, while the least sensitive were A. niger and A. welwitschiae. The LAB strains with the highest antifungal activity were Pediococcus pentosaceus (strains S11sMM and M9MM5b). The reduction range for AF was 19.0% (aflatoxin B1)-60.8% (aflatoxin B2) and for OTA, 7.3-100%, depending on the bacterial and fungal strains and temperatures. The LAB strains with the highest anti-AF activity were the three strains of P. pentosaceus and Leuconostoc mesenteroides ssp. dextranicum (T2MM3), and those with the highest anti-OTA activity were Leuconostoc paracasei ssp. paracasei (3T3R1) and L. mesenteroides ssp. dextranicum (T2MM3). The best ML methods in predicting fungal growth inhibition were multilayer perceptron neural networks, followed by random forest. Due to anti-fungal and anti-mycotoxin capacity, the LABs strains used in this study could be good candidates as biocontrol agents against aflatoxigenic and ochratoxigenic fungi and AFL and OTA accumulation.