Multi-Exposure Pathway Model to Compare Escherichia coli O157 Risks and Interventions

Shotgun Metagenomics-Guided Prediction Reveals the Metal Tolerance and Antibiotic Resistance of Microbes in Poly-Extreme Environments in the Danakil Depression, Afar Region

The occurrence and spread of antibiotic resistance genes (ARGs) in environmental microorganisms, particularly in poly-extremophilic bacteria, remain underexplored and have received limited attention. This study aims to investigate the prevalence of ARGs and metal resistance genes (MRGs) in shotgun metagenome sequences obtained from water and salt crust samples collected from Lake Afdera and the Assale salt plain in the Danakil Depression, northern Ethiopia. Potential ARGs were characterized by the comprehensive antibiotic research database (CARD), while MRGs were identified by using BacMetScan V.1.0. A total of 81 ARGs and 39 MRGs were identified at the sampling sites. We found a copA resistance gene for copper and the β-lactam encoding resistance genes were the most abundant the MRG and ARG in the study area. The abundance of MRGs is positively correlated with mercury (Hg) concentration, highlighting the importance of Hg in the selection of MRGs. Significant correlations also exist between heavy metals, Zn and Cd, and ARGs, which suggests that MRGs and ARGs can be co-selected in the environment contaminated by heavy metals. A network analysis revealed that MRGs formed a complex network with ARGs, primarily associated with β-lactams, aminoglycosides, and tetracyclines. This suggests potential co-selection mechanisms, posing concerns for both public health and ecological balance.

Characteristics of Wild Bird Resistomes and Dissemination of Antibiotic Resistance Genes in Interconnected Bird-Habitat Systems Revealed by Similarity of blaTEM Polymorphic Sequences

Wild birds are known to harbor and discharge antibiotic-resistant bacteria (ARB) and their associated antibiotic resistance genes (ARGs). However, assessments of their contribution to the dissemination of antibiotic resistance in the environment are limited to culture-dependent bacterial snapshots. Here, we present a high-throughput sequencing study that corroborates extensive ARG exchange between wild bird feces and their habitats and implies the need to scrutinize high-mobility birds as potential vectors for global propagation of ARGs. We characterized the resistome (281 ARGs) and microbiome of seven wild bird species and their terrestrial and aquatic habitats. The resistomes of bird feces were influenced by the microbial community structure, mobile genetic elements (MGEs), and residual antibiotics. We designated 33 ARGs found in more than 90% of the bird fecal samples as core ARGs of wild bird feces, among which 16 ARGs were shared as core ARGs in both wild bird feces and their habitats; these genes represent a large proportion of both the bird feces (35.0 ± 15.9%) and the environmental resistome (29.9 ± 21.4%). One of the most detected β-lactam resistance genes (bla_TEM, commonly harbored by multidrug resistant "superbugs") was used as molecular marker to demonstrate the high interconnectivity of ARGs between the microbiomes of wild birds and their habitats. Overall, this work provides a comprehensive analysis of the wild bird resistome and underscores the importance to consider genetic exchange between animals and the environment in the One Health approach.

A Farm-to-Fork Quantitative Microbial Exposure Assessment of β-Lactam-Resistant Escherichia coli among U.S. Beef Consumers

Integrated quantitative descriptions of the transmission of β-lactam-resistant Escherichia coli (BR-EC) from commercial beef products to consumers are not available. Here, a quantitative microbial exposure assessment model was established to simulate the fate of BR-EC in a farm-to-fork continuum and provide an estimate of BR-EC exposure among beef consumers in the U.S. The model compared the per-serving exposures from the consumption of intact beef cuts, non-intact beef cuts, and ground beef. Additionally, scenario analysis was performed to evaluate the relative contribution of antibiotic use during beef cattle production to the level of human exposure to BR-EC. The model predicted mean numbers of BR-EC of 1.7 × 10⁻⁴, 8.7 × 10⁻⁴, and 6.9 × 10⁻¹ CFU/serving for intact beef cuts, non-intact beef cuts, and ground beef, respectively, at the time of consumption. Sensitivity analyses using the baseline model suggested that factors related to sectors along the supply chain, i.e., feedlots, processing plants, retailers, and consumers, were all important for controlling human exposure to BR-EC. Interventions at the processing and post-processing stages are expected to be most effective. Simulation results showed that a decrease in antibiotic use among beef cattle might be associated with a reduction in exposure to BR-EC from beef consumption. However, the absolute reduction was moderate, indicating that the effectiveness of restricting antibiotic use as a standalone strategy for mitigating human exposure to BR-EC through beef consumption is still uncertain. Good cooking and hygiene practices at home and advanced safety management practices in the beef processing and post-processing continuum are more powerful approaches for reducing human exposure to antibiotic-resistant bacteria in beef products.

Stockpiling versus Composting: Effectiveness in Reducing Antibiotic-Resistant Bacteria and Resistance Genes in Beef Cattle Manure

Manure storage methods can affect the concentration and prevalence of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in cattle manure prior to land application. The objective of this study was to compare stockpiling and composting with respect to their effectiveness in reducing ARB and ARGs in beef cattle manure in a field-scale study. Field experiments were conducted in different seasons with different bulking agents for composting. For both the winter-spring cycle and the summer-fall cycle, ARB concentrations declined below the limit of quantification rapidly in both composting piles and stockpiles; however, ARB prevalence was significantly greater in the composting piles than in the stockpiles. This was likely due to the introduction of ARB from bulking agents. There was no significant change in ARG concentrations between initial and final concentrations for either manure storage treatment during the winter-spring cycle, but a significant reduction of the ARGs erm(B), tet(O), and tet(Q) over time was observed for both the composting pile and stockpile during the summer-fall cycle. Results from this study suggest that (i) bulking agent may be an important source of ARB and ARGs for composting; (ii) during cold months, the heterogeneity of the temperature profile in composting piles could result in poor ARG reduction; and (iii) during warm months, both stockpiling and composting can be effective in reducing ARG abundance. IMPORTANCE Proper treatment of manure is essential to reduce the spread of antibiotic resistance and protect human health. Stockpiling and composting are two manure storage methods which can reduce antibiotic-resistant bacteria and resistance genes, although few field-scale studies have examined the relative efficiency of each method. This study examined the ability of both methods in both winter-spring and summer-fall cycles, while also accounting for heterogeneity within field-scale manure piles. This study determined that bulking agents used in composting could contribute antibiotic-resistant bacteria and resistance genes. Additionally, seasonal variation could hinder the efficacy of composting in colder months due to heterogeneity in temperature within the pile; however, in warmer months, either method of manure storage could be effective in reducing the spread of antibiotic resistance.

Resurrection of inactive microbes and resistome present in the natural frozen world: Reality or myth?

The present world faces a new threat of ancient microbes and resistomes that are locked in the cryosphere and now releasing upon thawing due to climate change and anthropogenic activities. The cryosphere act as the best preserving place for these microbes and resistomes that stay alive for millions of years. Current reviews extensively discussed whether the resurrection of microbes and resistomes existing in these pristine environments is true or just a hype. Release of these ancient microorganisms and naked DNA is of great concern for society as these microbes can either cause infections directly or they can interact with contemporary microorganisms and affect their fitness, survival, and mutation rate. Moreover, the contemporary microorganisms may uptake the unlocked naked DNA, which might transform non-pathogenic microorganisms into deadly antibiotic-resistant microbes. Additionally, the resurrection of glacial microorganisms can cause adverse effects on ecosystems downstream. The release of glacial pathogens and naked DNA is real and can lead to fatal outbreaks; therefore, we must prepare ourselves for the possible reemergence of diseases caused by these microbes. This study provides a scientific base for the adoption of actions by international cooperation to develop preventive measures.

The application of quantitative microbial risk assessment to natural recreational waters: A review

This review examines the aims of and approaches to the Quantitative Microbial Risk Assessment (QMRA) of untreated recreational waters. The literature search was conducted on four databases and yielded 54 papers, which were analyzed on a quantitative (time-trend, geographical distribution, water type) and qualitative (aims, source of microbial data, pathogens and their measurement or estimation, ways to address variability and uncertainty, sensitivity analysis) basis. In addition, the parameters, implications, and limitations were discussed for each QMRA step. Since 2003, the number of papers has greatly increased, highlighting the importance of QMRA for the risk management of recreational waters. Nevertheless, QMRA still exhibits critical issues, above all regarding contamination data and dose-response relationships. To our knowledge, this is the first review to give a wide panoramic view on QMRA in relation to recreational exposure to untreated waters. This could be useful in identifying the current knowledge gaps and research needs.

Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of 'omics' techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR.

Postharvest Supply Chain with Microbial Travelers: a Farm-to-Retail Microbial Simulation and Visualization Framework

Fresh produce supply chains present variable and diverse conditions that are relevant to food quality and safety because they may favor microbial growth and survival following contamination. This study presents the development of a simulation and visualization framework to model microbial dynamics on fresh produce moving through postharvest supply chain processes. The postharvest supply chain with microbial travelers (PSCMT) tool provides a modular process modeling approach and graphical user interface to visualize microbial populations and evaluate practices specific to any fresh produce supply chain. The resulting modeling tool was validated with empirical data from an observed tomato supply chain from Mexico to the United States, including the packinghouse, distribution center, and supermarket locations, as an illustrative case study. Due to data limitations, a model-fitting exercise was conducted to demonstrate the calibration of model parameter ranges for microbial indicator populations, i.e., mesophilic aerobic microorganisms (quantified by aerobic plate count and here termed APC) and total coliforms (TC). Exploration and analysis of the parameter space refined appropriate parameter ranges and revealed influential parameters for supermarket indicator microorganism levels on tomatoes. Partial rank correlation coefficient analysis determined that APC levels in supermarkets were most influenced by removal due to spray water washing and microbial growth on the tomato surface at postharvest locations, while TC levels were most influenced by growth on the tomato surface at postharvest locations. Overall, this detailed mechanistic dynamic model of microbial behavior is a unique modeling tool that complements empirical data and visualizes how postharvest supply chain practices influence the fate of microbial contamination on fresh produce.IMPORTANCE Preventing the contamination of fresh produce with foodborne pathogens present in the environment during production and postharvest handling is an important food safety goal. Since studying foodborne pathogens in the environment is a complex and costly endeavor, computer simulation models can help to understand and visualize microorganism behavior resulting from supply chain activities. The postharvest supply chain with microbial travelers (PSCMT) model, presented here, provides a unique tool for postharvest supply chain simulations to evaluate microbial contamination. The tool was validated through modeling an observed tomato supply chain. Visualization of dynamic contamination levels from harvest to the supermarket and analysis of the model parameters highlighted critical points where intervention may prevent microbial levels sufficient to cause foodborne illness. The PSCMT model framework and simulation results support ongoing postharvest research and interventions to improve understanding and control of fresh produce contamination.