Characterization of Microbial Communities in a Dairy Farm Matrix in Ningxia, China, by 16S rDNA Analysis

Identification of microbial communities and multi-species biofilms contamination in seafood processing environments with different hygiene conditions

Biofilms formed by spoilage and pathogenic bacteria increase microbial persistence, causing an adverse influence on the quality of seafood. The mono-species biofilms are widely reported, however, the contamination of multi-species biofilms and their matrix in food environments are still not fully understood. Here, we assessed the contamination of multi-species biofilms in three seafood processing environments with different hygiene levels by detecting bacterial number and three biofilm matrix components (carbohydrates, extracellular DNA (eDNA), and proteins). Samples comprising seven food matrix surfaces and eight food processing equipment surfaces were collected from two seafood processing plants (XY and XC) and one seafood market (CC). The results showed that the bacterial counts ranged from 1.89 to 4.91 CFU/cm2 and 5.68 to 9.15 BCE/cm2 in these surfaces by cultivation and real-time PCR, respectively. Six biofilm hotspots were identified, including four in CC and two in XY. Among the three processing environments, the amplicon sequence variants (ASVs) of Proteobacteria, Bacteroidetes, and Actinobacteria decreased with improved processing hygiene, while Firmicutes showed a decrease in the four most abundant phyla. The most prevalent bacteria belonged to genera Psychrobacter, Acinetobacter, and Pseudomonas, demonstrating the significant differences and alteration in bacterial community composition during different environments. From the biofilm hotspots, 15 isolates with strong biofilm forming ability were identified, including 7 Pseudomonas, 7 Acinetobacter, and 1 Psychrobacter. The Pseudomonas isolates exhibited the highest production of EPS components and three strong motilities, whose characteristics were positively correlated. Thus, this study verified the presence of multi-species biofilms in seafood processing environments, offering preliminary insights into the diversity of microbial communities during processing. It highlights potential contamination sources and emphasizes the importance of understanding biofilms composition to control biofilms formation in seafood processing environments.

Diarrheagenic Escherichia coli and Their Antibiotic Resistance Patterns in Dairy Farms and Their Microbial Ecosystems

Ruminants are the largest reservoir for all types of Escherichia coli, including the pathogenic ones, which can potentially be transmitted to humans via the food chain and environment. A longitudinal study was performed to estimate the prevalence and antibiotic-resistant pattern of pathogenic E. coli (pE.coli) strains in dairy farm environments. A total of 846 environmental samples (water, lagoon slurry, bedding, feed, feces, soil, and compost) were collected in summer over two years from five dairy farms in Maryland, USA. An additional 40 soil samples were collected in winter and summer seasons for evaluating microbiome composition. Collected environmental samples were screened for the presence of pE.coli, which was isolated using a selective culture medium, for later confirmation and virotyping using PCR with specific primers. The overall prevalence of pE.coli in dairy farms was 8.93% (71/846), with the most common virotype identified in isolates being ETEC, followed by STEC. The highest pE.coli prevalence were recorded in lagoon slurry (21.57%) while the lowest was in compost heap (2.99%). Among isolates, 95.87% of the virotypes were resistant to 9 classes of antibiotics whereas only 4.12% were sensitive. The highest proportion (68.04%) of resistance was found for quinolones (e.g., ciprofloxacin). The resulting metagenomic analysis at the phylum and genus levels of the grazing land soil suggests that climatic conditions actively influence the abundance of bacteria. Proteobacteria, which contains many Gram-negative foodborne pathogens (including pE.coli), was the most predominant phylum, accounting for 26.70% and 24.93% of soil bacteria in summer and winter, respectively. In addition to relative abundance, there was no significant difference in species diversity between seasons when calculated via Simpson (D) and Shannon (H) index. This study suggests that antibiotic-resistant E. coli virotypes are present in the dairy farm environment, and proper steps are warranted to control its transmission irrespective of seasonality.

Cow Farmers’ Homes Host More Diverse Airborne Bacterial Communities Than Pig Farmers’ Homes and Suburban Homes

Living on a farm has been linked to a lower risk of immunoregulatory disorders, such as asthma, allergy, and inflammatory bowel disease. It is hypothesized that a decrease in the diversity and composition of indoor microbial communities is a sensible explanation for the upsurge in immunoregulatory diseases, with airborne bacteria contributing to this protective effect. However, the composition of this potentially beneficial microbial community in various farm and suburban indoor environments is still to be characterized. We collected settled airborne dust from stables and the associated farmers’ homes and from suburban homes using electrostatic dust collectors (EDCs) over a period of 14 days. Then, quantitative PCR (qPCR) was used to assess bacterial abundance. The V3–V4 region of the bacterial 16S rRNA gene was amplified and sequenced using Ilumina MiSeq in order to assess microbial diversity. The Divisive Amplicon Denoising Algorithm (DADA2) algorithm was used for the inference of amplicon sequence variants from amplicon data. Airborne bacteria were significantly more abundant in farmers’ indoor environments than in suburban homes (p < 0.001). Cow farmers’ homes had significantly higher bacterial diversity than pig farmers’ and suburban homes (p < 0.001). Bacterial taxa, such as Firmicutes, Prevotellaceae, Lachnospiraceae, and Lactobacillus were significantly more abundant in farmers’ homes than suburban homes, and the same was true for beneficial intestinal bacterial species, such as Lactobacillus amylovorus, Eubacterium hallii, and Faecalibacterium prausnitzii. Furthermore, we found a higher similarity between bacterial communities in individual farmers’ homes and their associated cow stables than for pig stables. Our findings contribute with important knowledge on bacterial composition, abundance, and diversity in different environments, which is highly valuable in the discussion on how microbial exposure may contribute to the development of immune-mediated diseases in both children and adults.

Exploring prevalence of potential pathogens and fecal indicators in geographically distinct river systems through comparative metagenomics

Microbial communities are considered as vital members to reflect the health of a riverine system. Among them, pathogenic and fecal indicators imply health risks involved with potability of river water. The present study explores the diverse microbial communities, distribution pattern of potential pathogens, and fecal indicators between the geographically distinct Himalayan and Peninsular river systems of India. It also inquires into the environmental factors associated with community variance and distribution pattern of microbial indicators. The application of high-throughput amplicon sequencing approach unveiled significant demarcation (p < 0.004, Anosim R = 0.62) of samples suggesting unique microbial diversities in these two river sediments. Random forest analysis revealed Desulfobulbulus, PSB_M_3, and Opitutus in Himalayan, while DA101, Bacillus, and Streptomyces in the Peninsular as significant contributors to develop overall dissimilarity between the river systems. Permutational multivariate analysis of variance and co-occurrence network analysis were used to study the relationships between microbial taxa and environmental factors. Amongst the various studied environmental parameters, pH, K, Ca, Mg, Ba, and Al in the Himalayan and salinity, Na, temperature, and Th in the Peninsular significantly influenced shaping of distinct microbial communities. Furthermore, the potential pathogenic genera, including Flavobacterium, Clostridium, Arcobacter, Pseudomonas, and Bacillus were highly prevalent in both the river systems. Arcobacter, Clostridium, Acinetobacter, Bacteroides, and Caloramator were the prominent fecal indicators in these river systems. Our findings provide salient information about the crucial role and interplay between various environmental factors and anthropogenic influences in framing the microbiome of the distinct river systems in India. Moreover, assessing potential pathogenic and fecal indicators suggest the public health risk associated with untreated sewage discharge into these water sources. The detection of various F/S indicators and potentially pathogenic bacteria in Himalayan and Peninsular river systems emphasize the urgent need for future monitoring and management of major riverine systems in India.