Microorganisms Move a Short Distance into an Almond Orchard from an Adjacent Upwind Poultry Operation

Needles in haystacks: monitoring the potential escape of bioaerosolised antibacterial resistance genes from wastewater treatment plants with air and phyllosphere sampling

Wastewater treatment plants are well-known point sources of emissions of antibacterial resistance genes (ARGs) into the environment. Although most work to date has focused on ARG dispersal via effluent, aerial dispersal in bioaerosols is a poorly understood, but likely important vector for ARG dispersal. Recent evidence suggests that ARG profiles of the conifer needle phyllosphere could be used to measure bioaerosol dispersal from anthropogenic sources. Here, we assessed airborne dispersal of ARGs from wastewater treatment plants in Wales, UK and Quebec, Canada, using conifer needles as passive bioaerosol monitors. ARG profiles of wastewater were compared to those of conifer phyllosphere using high-throughput qPCR. ARG richness was significantly lower in conifer phyllosphere samples than wastewater samples, though no differences were observed across the dispersal gradients. Mean copy number of ARGs followed a similar trend. ARG profiles showed limited, but consistent patterns with increasing distance from wastewater treatment plants, but these did not align with those of wastewater samples. For example, proportional abundance of aminoglycosides decreased over the dispersal gradient in Wales, whereas mobile genetic elements showed the inverse relationship. In summary, while distinct ARG profiles exist along dispersal gradients, links to those of wastewater were not apparent.

Comparison of Three Air Sampling Methods for the Quantification of Salmonella, Shiga-toxigenic Escherichia coli (STEC), Coliforms, and Generic E. coli from Bioaerosols of Cattle and Poultry Farms

Recent fresh produce outbreaks potentially associated with bioaerosol contamination from animal operations in adjacent land highlighted the need for further study to better understand the associated risk. The purpose of this research was to evaluate three sampling methods for quantifying target bacterial bioaerosols from animal operations. A dairy cattle and poultry farm located in Georgia, U.S. were visited six times each. Air was collected for 10 min using: 2-stage Andersen impactor with and without mineral oil overlay and impingement samplers. Sampling devices were run concurrently at 0.1, 1, and 2 m heights (n = 36). Andersen samplers were loaded with CHROMagar™ Salmonella, CHROMagar™ STEC, or Brilliance™ coliforms/E. coli. The impingement sampler contained buffered peptone water (20 mL) which was vacuum filtered through a 0.45 µm filter and placed onto the respective media. Plates were incubated at 37 ℃ for 48 h. PCR confirmation followed targeting ttr for Salmonella and stx1, stx2, and eae genes for STEC. No significant differences were found among methods to quantify coliforms and E. coli. Salmonella and STEC bioaerosols were not detected by any of the methods (Limit of detection: 0.55 log CFU/m3). E. coli bioaerosols were significantly greater in the poultry (2.76-5.00 log CFU/m3) than in the cattle farm (0.55-2.82 log CFU/m3) (p < 0.05), and similarly distributed at both stages in the Andersen sampler (stage 1:>7 μm; stage 2: 0.65-7 μm particle size). Sampling day did not have a significant effect on the recovery of coliforms/E. coli bioaerosols in the poultry farm when samples were taken at the broiler house exhaust fan (p > 0.05). A greater and constant emission of coliforms and E. coli bioaerosols from the poultry farm warrants further investigation. These data will help inform bioaerosol sampling techniques which can be used for the quantification of bacterial foodborne pathogens and indicator organisms for future research.

A meta-analysis of the effect of Eimeria spp. and/or Clostridium perfringens infection on the microbiota of broiler chickens

Coccidiosis in chickens is caused by Eimeria spp. The infection provides a growth advantage to Clostridium perfringens (CP), frequently leading to necrotic enteritis. One approach to alleviate the negative impacts of the diseases is to improve the bacterial composition in chickens, and many experiments investigating chicken enteric health in recent years include the characterization of the bacterial microbiota. This meta-analysis synthesized the data of studies investigating the intestinal microbiota after infection with coccidia and/or CP to provide a basis for future research. Inclusion criteria were that experiments contained a group infected with one or both pathogens and an uninfected control group, the use of 16SrRNA Illumina sequencing and the availability of raw data. A total of 17 studies could be included. Meta-analyses of 3 different data sets were performed: 1 on data of 9 experiments on chickens infected with coccidia only; the second on data of 4 studies on chickens infected with CP only; the third on raw data of 8 experiments with chickens infected with coccidia and CP. The meta-analysis of relative abundance and alpha diversity of the data sets was performed in R using the SIAMCAT and metafor packages. The number of families of interest identified by the analyses of experiments with infection with coccidia only, CP only and the combined infection were 23, 2, and 29, respectively. There was an overlap of 13 families identified by analyses of experiments with infection with coccidia only and of experiments with the combined infections. Machine learning was not able to find a model to predict changes of the microbiota in either 1 of the 3 analyses. Meta-analyses of functional profiles showed a more uniform reaction to the infections with the relative abundance of many pathways significantly altered. Alpha diversity was not affected by infection with either pathogen or the combination. In conclusion, the heterogeneity of these microbiota studies makes recognizing common trends difficult, although it seems that coccidia infection affects the microbiota more than an infection with CP. Future studies should focus on the bacterial functions that are changed due to these infections using metagenome techniques.

Structural Equation Models Suggest That On-Farm Noncrop Vegetation Removal Is Not Associated with Improved Food Safety Outcomes but Is Linked to Impaired Water Quality

While growers have reported pressures to minimize wildlife intrusion into produce fields through noncrop vegetation (NCV) removal, NCV provides key ecosystem services. To model food safety and environmental tradeoffs associated with NCV removal, published and publicly available food safety and water quality data from the Northeastern United States were obtained. Because data on NCV removal are not widely available, forest-wetland cover was used as a proxy, consistent with previous studies. Structural equation models (SEMs) were used to quantify the effect of forest-wetland cover on (i) food safety outcomes (e.g., detecting pathogens in soil) and (ii) water quality (e.g., nutrient levels). Based on the SEMs, NCV was not associated with or had a protective effect on food safety outcomes (more NCV was associated with a reduced likelihood of pathogen detection). The probabilities of detecting Listeria spp. in soil (effect estimate [EE] = -0.17; P = 0.005) and enterohemorrhagic Escherichia coli in stream samples (EE = -0.27; P < 0.001) were negatively associated with the amount of NCV surrounding the sampling site. Larger amounts of NCV were also associated with lower nutrient, salinity, and sediment levels, and higher dissolved oxygen levels. Total phosphorous levels were negatively associated with the amount of NCV in the upstream watershed (EE = -0.27; P < 0.001). Similar negative associations (P < 0.05) were observed for other physicochemical parameters, such as nitrate (EE = -0.38). Our findings suggest that NCV should not be considered an inherent produce safety risk or result in farm audit demerits. This study also provides a framework for evaluating environmental tradeoffs associated with using specific preharvest food safety strategies. IMPORTANCE Currently, on-farm food safety decisions are typically made independently of conservation considerations, often with detrimental impacts on agroecosystems. Comanaging agricultural environments to simultaneously meet conservation and food safety aims is complicated because farms are closely linked to surrounding environments, and management decisions can have unexpected environmental, economic, and food safety consequences. Thus, there is a need for research on the conservation and food safety tradeoffs associated with implementing specific preharvest food safety practices. Understanding these tradeoffs is critical for developing adaptive comanagement strategies and ensuring the short- and long-term safety, sustainability, and profitability of agricultural systems. This study quantifies tradeoffs and synergies between food safety and environmental aims, and outlines a framework for modeling tradeoffs and synergies between management aims that can be used to support future comanagement research.

Xylella fastidiosa Infection Reshapes Microbial Composition and Network Associations in the Xylem of Almond Trees

Xylella fastidiosa represents a major threat to important crops worldwide including almond, citrus, grapevine, and olives. Nowadays, there are no efficient control measures for X. fastidiosa, and the use of preventive measures and host resistance represent the most practical disease management strategies. Research on vessel-associated microorganisms is gaining special interest as an innate natural defense of plants to cope against infection by xylem-inhabiting pathogens. The objective of this research has been to characterize, by next-generation sequencing (NGS) analysis, the microbial communities residing in the xylem sap of almond trees affected by almond leaf scorch disease (ALSD) in a recent X. fastidiosa outbreak occurring in Alicante province, Spain. We also determined community composition changes and network associations occurring between xylem-inhabiting microbial communities and X. fastidiosa. For that, a total of 91 trees with or without ALSD symptoms were selected from a total of eight representative orchards located in five municipalities within the X. fastidiosa-demarcated area. X. fastidiosa infection in each tree was verified by quantitative polymerase chain reaction (qPCR) analysis, with 54% of the trees being tested X. fastidiosa-positive. Globally, Xylella (27.4%), Sphingomonas (13.9%), and Hymenobacter (12.7%) were the most abundant bacterial genera, whereas Diplodia (30.18%), a member of the family Didymellaceae (10.7%), and Aureobasidium (9.9%) were the most predominant fungal taxa. Furthermore, principal coordinate analysis (PCoA) of Bray–Curtis and weighted UniFrac distances differentiated almond xylem bacterial communities mainly according to X. fastidiosa infection, in contrast to fungal community structure that was not closely related to the presence of the pathogen. Similar results were obtained when X. fastidiosa reads were removed from the bacterial data set although the effect was less pronounced. Co-occurrence network analysis revealed negative associations among four amplicon sequence variants (ASVs) assigned to X. fastidiosa with different bacterial ASVs belonging to 1174-901-12, Abditibacterium, Sphingomonas, Methylobacterium–Methylorubrum, Modestobacter, Xylophilus, and a non-identified member of the family Solirubrobacteraceae. Determination of the close-fitting associations between xylem-inhabiting microorganisms and X. fastidiosa may help to reveal specific microbial players associated with the suppression of ALSD under high X. fastidiosa inoculum pressure. These identified microorganisms would be good candidates to be tested in planta, to produce almond plants more resilient to X. fastidiosa infection when inoculated by endotherapy, contributing to suppress ALSD.

Genomic evidence of environmental and resident Salmonella Senftenberg and Montevideo contamination in the pistachio supply-chain

Pistachios have been implicated in two salmonellosis outbreaks and multiple recalls in the U.S. This study performed an in-depth retrospective data analysis of Salmonella associated with pistachios as well as a storage study to evaluate the survivability of Salmonella on inoculated inshell pistachios to further understand the genetics and microbiological dynamics of this commodity-pathogen pair. The retrospective data analysis on isolates associated with pistachios was performed utilizing short-read and long-read sequencing technologies. The sequence data were analyzed using two methods: the FDA's Center for Food Safety and Applied Nutrition Single Nucleotide Polymorphism (SNP) analysis and Whole Genome Multilocus Sequence Typing (wgMLST). The year-long storage study evaluated the survival of five strains of Salmonella on pistachios stored at 25 °C at 35% and 54% relative humidity (RH). Our results demonstrate: i) evidence of persistent Salmonella Senftenberg and Salmonella Montevideo strains in pistachio environments, some of which may be due to clonal resident strains and some of which may be due to preharvest contamination; ii) presence of the Copper Homeostasis and Silver Resistance Island (CHASRI) in Salmonella Senftenberg and Montevideo strains in the pistachio supply chain; and iii) the use of metagenomic analysis is a novel tool for determining the composition of serovar survival in a cocktail inoculated storage study.

Sources and Assembly of Microbial Communities in Vineyards as a Functional Component of Winegrowing

Microbiomes are integral to viticulture and winemaking – collectively termed winegrowing – where diverse fungi and bacteria can exert positive and negative effects on grape health and wine quality. Wine is a fermented natural product, and the vineyard serves as a key point of entry for quality-modulating microbiota, particularly in wine fermentations that are conducted without the addition of exogenous yeasts. Thus, the sources and persistence of wine-relevant microbiota in vineyards critically impact its quality. Site-specific variations in microbiota within and between vineyards may contribute to regional wine characteristics. This includes distinctions in microbiomes and microbiota at the strain level, which can contribute to wine flavor and aroma, supporting the role of microbes in the accepted notion of terroir as a biological phenomenon. Little is known about the factors driving microbial biodiversity within and between vineyards, or those that influence annual assembly of the fruit microbiome. Fruit is a seasonally ephemeral, yet annually recurrent product of vineyards, and as such, understanding the sources of microbiota in vineyards is critical to the assessment of whether or not microbial terroir persists with inter-annual stability, and is a key factor in regional wine character, as stable as the geographic distances between vineyards. This review examines the potential sources and vectors of microbiota within vineyards, general rules governing plant microbiome assembly, and how these factors combine to influence plant-microbe interactions relevant to winemaking.

The source and transport of bioaerosols in the air: A review

Recent pandemic outbreak of the corona-virus disease 2019 (COVID-19) has raised widespread concerns about the importance of the bioaerosols. They are atmospheric aerosol particles of biological origins, mainly including bacteria, fungi, viruses, pollen, and cell debris. Bioaerosols can exert a substantial impact on ecosystems, climate change, air quality, and public health. Here, we review several relevant topics on bioaerosols, including sampling and detection techniques, characterization, effects on health and air quality, and control methods. However, very few studies have focused on the source apportionment and transport of bioaerosols. The knowledge of the sources and transport pathways of bioaerosols is essential for a comprehensive understanding of the role microorganisms play in the atmosphere and control the spread of epidemic diseases associated with them. Therefore, this review comprehensively summarizes the up to date progress on the source characteristics, source identification, and diffusion and transport process of bioaerosols. We intercompare three types of diffusion and transport models, with a special emphasis on a widely used mathematical model. This review also highlights the main factors affecting the source emission and transport process, such as biogeographic regions, land-use types, and environmental factors. Finally, this review outlines future perspectives on bioaerosols.