Variations in Fungal Community and Diversity in Doushen With Different Flavors

Abstract

Doushen, a traditional Chinese fermented soybean product, may be spiced or spicy depending on whether pepper powder is added. While numerous studies have investigated the microbial communities of other fermented foods, little is known on the fungal diversity of Doushen. Therefore, in this study, we investigated the fungal community and diversity in both spiced and spicy Doushen. Our results revealed that fungal species richness significantly differed between the samples with different flavors. A total of nine phyla and 188 fungal genera were identified, and Ascomycota and Aspergillus were predominant in all samples. Based on linear discriminant analysis, a total of 57 OTUs were significantly different between the two samples. Results of non-metric multidimensional scaling and unweighted pair-group analysis suggested that the presence of pepper powder affects the microbial community in Doushen. Network analysis showed that microbial interactions between fungal communities in Doushen with different flavors were significantly different. The results on the enumeration and identification of fungi were consistent with the composition of the dominant genera in the samples with different flavors. This study provides a theoretical basis for future research on food ecology in Doushen.

High‐throughput sequencing‐based analysis of fungal diversity and taste quality evaluation of Douchi, a traditional fermented food

“…Although there were great differences in microbial community structure in different Douchi samples, the functional expression and fermentation characteristics of the same microorganism in Douchi samples are basically the same (Wang et al, 2012). In this study, Procrustes analysis was used to find that the taste quality and the flora in Douchi samples had the same trend (Luo et al, 2020).…”

“…Although there were great differences in microbial community structure in different Douchi samples, the functional expression and fermentation characteristics of the same microorganism in Douchi samples are basically the same (Wang et al., 2012). In this study, Procrustes analysis was used to find that the taste quality and the flora in Douchi samples had the same trend (Luo et al., 2020). At the same time, the results of correlation analysis showed that Debaryomyces and Trichosporon were positively correlated with the intensity of the excellent taste index of Douchi samples, while Cladosporium and Candida were positively correlated with the intensity of the defective taste index.…”

Exposure of Cryptococcus neoformans to Seven Commonly Used Agricultural Azole Fungicides Induces Resistance to Fluconazole as Well as Cross-Resistance to Voriconazole, Posaconazole, Itraconazole and Isavuconazole

“…In contrast, TBZ is very widely used on a large number of different types of cultures from potatoes, soya beans, bananas, mangoes, peas and grapes [ 64 ], increasing the risk of field contact between environmental fungi potentially pathogenic to humans and suboptimal or spray drift deposit concentrations, allowing an increase in the MIC of FCZ. This is particularly true for the C gattii species complex, which has already been isolated from mango trees [ 70 ], as well as C. neoformans , which has already been isolated from soybean-derived products [ 71 ]. BMZ is one of the three molecules that generated the highest number of colonies with elevated MIC of FCZ among all the pesticides tested.…”

Influence of Tissue Type on the Bacterial Diversity and Community in Pork Bacon

“…Different types of microbes, coexist in traditional foods, have different roles in food production ( Zhang et al, 2018 , 2021 ; Zhu et al, 2018 ; Luo et al, 2020 ). In the present study, we detected various kinds of bacteria in bacon, including nine dominant genera: Staphylococcus , Psychrobacter , Pseudomonas , Acinetobacter , Macrococcus , Brochothrix , Cupriavidus , Massilia , and Carnobacterium .…”

“…The SparCC algorithm was applied to investigate the correlation of all bacterial genera. Correlation networks and redundancy analysis (RDA) were made using the Biomarker biocloud tools ( Luo et al, 2020 ; Zhang et al, 2021 ). Data of the physicochemical characterization used for RDA was showed in our previous study ( Zhang et al, 2021 ).…”