Pathogens that invade into the soil cancontaminate food and water, andinfect animals and human beings. It is well documented that individual bacterial phyla are well correlated with the survival of E. coliO157 (EcO157), while the interaction betweenthe fungal communities and EcO157 survival remains largely unknown. In this study, soil samples from Tongliao, Siping, and Yanji in northeast China were collected and characterized. Total DNA was extracted for fungal and bacterial community characterization. EcO157 cells were spiked into the soils, and their survival behavior was investigated. Results showed that both fungal and bacterial communities were significantly correlated (p < 0.01) with the survival of EcO157 in soils, and the relative abundances of fungal groups (Dothideomycetes and Sordariomycetes) and some bacterial phyla (Acidobacteria, Firmicutes, gamma- and delta-Proteobacteria)weresignificantly correlated with ttds (p < 0.01). Soil pH, EC (electric conductance) salinity, and water-soluble nitrate nitrogen were significantly correlated with survival time (time to reach the detection limit, ttd) (p < 0.05). The structural equation model indicated that fungal communities could directly influence ttds, and soil properties could indirectly influence the ttds through fungal communities. The first log reduction time (δ) was mainly correlated with soil properties, while the shape parameter (p) was largely correlated with fungal communities. Our data indicated that both fungal and bacterial communities were closely correlated (p < 0.05)with the survival of EcO157 in soils, and different fungal and bacterial groups might play different roles. Fungal communities and bacterial communities explained 5.87% and 17.32% of the overall variation of survival parameters, respectively. Soil properties explained about one-third of the overall variation of survival parameters. These findings expand our current understanding of the environmental behavior of human pathogens in soils.

From the west to the east across Northeast China, there are three major land use types, ranging from agricultural-pastoral interlaced land, crop land, and forest land. The soil microbial community of each land use type has been reported; however, a thorough comparison of the soil microbial ecology of soils from each land use type has not been made. In the current study, soil samples from agricultural-pastoral land, crop land, and an artificial economic forest were collected from Tongliao, Siping, and Yanji, respectively. The structure and composition of bacterial and fungal communities was investigated by a next generation sequencing protocol, and soil physicochemical properties were also determined. Pair-wise analysis showed some soil parameters were significantly different between agricultural-pastoral land and crop land or forest land, while those soil parameters shared more similarities in crop land and forest land soils. Principal coordinates analysis and dissimilarity analyses jointly indicated that bacterial and fungal communities from each sampling site were quite different. Canonical correspondence analysis and a partial Mantel test showed that the community structures of bacteria and fungi were mainly affected by clay, pH, water soluble organic carbon (WSOC), and total soluble nitrogen (TN). Co-occurrence network analysis and the associated topological features revealed that the network of the bacterial community was more complex than that of the fungal community. Clay, pH, WSOC, and NH4+-N were major drivers and pH and WSOC were major factors in shaping the network of the bacterial community and the fungal community, respectively. In brief, our results indicated that microbial diversity, co-occurrence network patterns, and their shaping factors differed greatly among soils of distinct land use types in Northeast China. Our data also provided insights into the sustainable use of soils under different land use types.

Persistence of E. coli O157: H7 (EcO157) in 48 water samples (24 Spring samples and 24 Autumn samples) from 3 urban recreational waters in Changchun City was investigated, and multivariate statistical analysis was performed to correlate survival data with water physicochemical properties and bacterial communities. Our data showed that EcO157 survived longer in Spring samples than in Autumn samples regardless of the lakes. Results revealed that recreational water physicochemical properties and bacterial community in Spring samples were different from those in Autumn samples. Mantel and Partial Mantel tests, as well as co-occurrence network analysis illustrated that EC salinity, TOC and bacterial community were correlated with survival time (ttd) (p < 0.05). Variation partition analysis (VPA) indicated that bacterial community, EC, TOC and TN explained about 64.81% of overall ttd variation in Spring samples, and bacterial community, EC, pH and TP accounted for about 56.59% of overall ttd variation in Autumn samples. Structural equation model (SEM) illustrated that EC indirectly positively affected ttd through bacterial community. The correlation between bacterial community and ttd was negative in Spring samples and positive in Autumn samples. TN appeared a direct positive effect on ttd in Spring samples. TP displayed a direct negative effect on ttd in Autumn samples. Our results concluded that there was seasonal variation in environmental factors that directly or indirectly affected the survival of EcO157 in urban recreational waters.

Persistence of E. coli O157: H7 (EcO157) in 48 water samples (24 Spring samples and 24 Autumn samples) from 3 urban recreational waters in Changchun City was investigated, and multivariate statistical analysis was performed to correlate survival data with water physicochemical properties and bacterial communities. Our data showed that EcO157 survived longer in Spring samples than in Autumn samples regardless of the lakes. Results revealed that recreational water physicochemical properties and bacterial community in Spring samples were different from those in Autumn samples. Mantel and Partial Mantel tests, as well as co-occurrence network analysis illustrated that EC salinity, TOC and bacterial community were correlated with survival time (ttd) (p < 0.05). Variation partition analysis (VPA) indicated that bacterial community, EC, TOC and TN explained about 64.81% of overall ttd variation in Spring samples, and bacterial community, EC, pH and TP accounted for about 56.59% of overall ttd variation in Autumn samples. Structural equation model (SEM) illustrated that EC indirectly positively affected ttd through bacterial community. The correlation between bacterial community and ttd was negative in Spring samples and positive in Autumn samples. TN appeared a direct positive effect on ttd in Spring samples. TP displayed a direct negative effect on ttd in Autumn samples. Our results concluded that there was seasonal variation in environmental factors that directly or indirectly affected the survival of EcO157 in urban recreational waters.