238 research outputs found
Edward R. Atwill, Toledo, Ohio [approximately 1880]
No full textTerms associated with the photograph are: Atwill, Edward R. | ministers | Trinity Episcopal Church (Toledo, Ohio) | church vestment
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Antimicrobial resistance and genomic epidemiology of enteric bacteria on the farm-to-fork interface
No full textAntimicrobial resistance (AMR) is one of the most serious public health threats of the century. Resistant bacteria and AMR genes (ARGs) can spread through human and animal populations through pathways such that selective pressures in one population inextricably impacts others on the One Health continuum. This dissertation takes a farm-to-fork approach on AMR by evaluating the distribution and risk factors for AMR in retail products, AMR co-selection in food-producing animals, and genomic profiles of these bacteria.In Chapter 1, a cross-sectional study was conducted to assess the distribution and AMR profiles of Salmonella from retail meat products in California. From multivariable logistic regression, season of purchase and meat type were significantly associated with the isolation of Salmonella. Whole genome sequencing (WGS) characterized Salmonella isolates into 14 distinct serotypes corresponding to 17 MLST patterns. Diverse ARGs including those of high public health significance and putative plasmids were identified. The IncFIB(pN55391) replicon previously reported in connection to the worldwide dissemination of pESI-like mega plasmid carriage in an emerged S. Infantis clone was detected in four of the six multidrug-resistant (MDR) isolates.
In Chapter 2, Escherichia coli from samples in Chapter 1 were assessed to gain further insight on the clinical and epidemiologic risks associated with AMR in retail meat products from California. Phenotypic resistance to ampicillin, gentamicin, streptomycin, and tetracycline were significantly associated with meat type, with poultry counterparts (chicken or ground turkey) exhibiting higher odds for resistance compared to non-poultry meats (beef and pork). Clustering analysis and co-occurrence networks revealed that genomic AMR determinants of E. coli from retail meat were highly heterogeneous with sparsity of shared gene networks and minimally driven by retail-level factors of meat type, season of
purchase, packaging, and antibiotic label claims.
In Chapter 3, the impact of dietary zinc supplementation in pre-weaned dairy calves on phenotypic AMR of fecal Enterococcus spp. and E. coli was investigated. Accelerated failure time (AFT) models were constructed to determine the association between zinc treatment and AMR, with exponentiated coefficients adapted for minimum inhibitory concentration (MIC) values instead of time representing the degree of change in AMR (MIC Ratio, MR). Zinc supplementation did not significantly alter the MIC in Enterococcus spp. for 13 tested antimicrobials and in E. coli for azithromycin and ceftriaxone. However, a significant reduction in E. coli MIC values was observed for ciprofloxacin (MR= 0.17, 95% CI 0.03–0.97) and nalidixic acid (MR= 0.28, 95% CI 0.15–0.53) for zinc-treated compared to placebo-treated calves.
In Chapter 4, whole-genome comparative analysis was conducted to investigate the host-microbe interface of MDR E. coli from dairy calves. The pangenome of E. coli was open, with all-by-all genome similarity comparisons clustering primarily by sequence type (ST) rather than host factors of diarrheal disease, zinc supplementation, and antimicrobial exposure. E. coli lacked the typical virulence factors of diarrheagenic strains, however virulence factors overlapping with those in major pathotypes were identified, with the most prevalent genes corresponding to iron acquisition. Dietary zinc exposure was not associated with the selection of individual ARGs, however significant associations between the occurrence of certain ARGs and metal resistance genes were identified.
Collectively, this dissertation provides greater insight into the epidemiology of AMR in enteric bacteria of public health significance. This improved understanding of the distribution and drivers of AMR in food products and food-producing animals will inform future AMR monitoring and control strategies by supporting more targeted approaches to mitigate AMR from farm-to-fork
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Quantifying background levels of airborne bacteria and microbiome in proximity of beef cattle feedlot, and identifying associated environmental and anthropogenic risk factors
No full textBackground. California Leafy Green Products Handler Marketing Agreement (LGMA) established food safety metrics for producing leafy greens, with guidance recommendations of 400 feet, 1200 feet, and one-mile distances between production fields and either a composting facility utilizing animal products, or a feedlot (or concentrated animal feeding operations (CAFO)) containing >1000 or >80,000 head of cattle, respectively. Aim. The purpose of the three chapters was to: (1) evaluate the effect of these distance metrics, (2) identify key environmental risk factors associated with airborne bacterial pathogens (E. coli O157, non-O157 Shiga-toxin–producing E. coli (STEC), Salmonella) and indicator E. coli in proximity to beef cattle CAFOs, and (3) compare the cultural methods of airborne E. coli and the sequence of uspA gene from airborne E. coli isolated in each feedlot.
Methods. For chapter 1, each sample contained 1000 liters of air at a 1.2-m elevation over 10 minutes using MAS-100 Eco microbial air samplers. Airborne E. coli was tested based on direct count. Meteorological data in situ (air temperature, wind speed, wind direction, and relative humidity) was collected. Logistic regression was used to identify the association between risk factors and the odds of airborne E. coli detection. For chapter 2, each sample comprised 6000 liters of air collected at 1.2-m elevation using the same air samplers, with TSB-enriched air filters qPCR-screened for E. coli O157, STEC, Salmonella, and indicator E. coli; suspect positive colonies were further qPCR-confirmed. A separate air sample was collected for direct enumeration of the concentration of indicator E. coli. Local meteorological data was collected in situ and from a nearby weather station, along with the line-of-sight distance from the feedlot and events of dust-generating activity, with logistic regression used to identify which of these factors were associated with the odds of bacterial detection. For chapter 3, McNemar’s test was applied to compare the two methods (direct count and TSB-enrichment) of detecting airborne E. coli. The sequence similarity of the uspA gene from airborne E. coli tested positive based on both direct count and TSB-enrichment was calculated based on neighbors-joining methods. Wilcoxon rank-sum test was used for the association between the land occupation of feedlot and the occurrence of airborne E. coli. The sequence of the uspA gene from airborne E. coli in each feedlot was analyzed based on phylogenetic analysis.
Results. For chapter 1, a total of 168 air samples were collected from seven beef cattle feedlots in March and April 2020. The distance away from the edge of the feedlot ranged from 0 to around 2200 m (1.3 miles). The prevalence of airborne E. coli is 6.5% (11/168). The concentration of the airborne E. coli ranged from 1 to 2 colony-forming unit (CFU) per 1000 L of air. All positive samples are 37 m (120 ft) from the edge of the feedlot. As the distance between the feedlot edge and the air sampler increases 100 ft (30 m), the odds of detecting E. coli decrease by 95% (OR=0.05). For chapter 2, during the 6-month period (11/2020 to 4/2021) for leafy green production in Imperial Valley, California, 150 air samples were collected at LGMA-guidance distances of ~400 feet, ~1200 feet, and ~1 mile from five cattle feedlots. In addition, 150 samples were collected at randomized distances from the five feedlots ranging from 30 to 2000 feet in all directions. No bacterial pathogens were qPCR-confirmed for the 300 samples totaling 1.8 million L of processed air, which suggests a maximum concentration for E. coli O157, non-O157 STEC, and Salmonella of less than ~1 CFU per million L of ambient air. Indicator E. coli was detected in 16.7% (50/300) of samples, with positives found at all distance categories and a concentration ranging from 0 to 19 CFU/6000 L. Although E. coli detection was not significantly different between air samples taken at LGMA-guidance distances of 400 ft, 1200 ft, and 1 mile (8.3%, 15.0%, 10.0%, respectively), logistic regression on all 300 air samples (n=150 random plus n=150 LGMA-fixed distances) found significantly higher odds of E. coli for samples taken in close proximity compared to >2000-ft distance from a feedlot. Environmental factors associated with E. coli detection included wind speed, wind direction, relative humidity, sampling hour of day and month, and the presence of activities that created fugitive dust (feedlot cattle activity, vehicular traffic, plowing fields) during the sampling period. For chapter 3, statistically, there is a significant difference between the two test methods (direct count and TSB-enrichment) for airborne E. coli (p<0.001). For the 12 samples, which were positive for airborne E. coli based on both direct count and enrichment cultural methods, the sequence similarity of the uspA gene ranged from 88.6% to 100% with a mean of 93.1%. With comparable data, the prevalence of airborne E. coli for the first and second studies is 1.99% and 7.69%, respectively. Statistically, the occurrence of airborne E. coli is greater in the second study compared to the first one (p=0.04). The difference is from the volume of air collected, the duration of sampling, and the air filter placed on top of the media. Land occupancy of feedlots (an ordinal variable) is not associated with the occurrence of airborne E. coli for the first (p=0.07) and the second study (p=0.28) within 1 mile of feedlots. The sequence similarity of the uspA gene from all the airborne E. coli isolates ranged from 88.6% to 100% in each feedlot. If treating E. coli isolated from ≤50 ft and intensively exposed to a feedlot as reference isolates, 1400 ft is the furthest distance for E. coli isolates that shared identical uspA gene with reference isolates. For all the airborne E. coli isolated from >50 ft from the edge of each feedlot, ~6% to ~60% of the isolates shared identical sequence of the uspA gene with the reference isolates.
Conclusion. Lack of bacterial pathogen detection within these sampled distances suggests airborne deposition from nearby feedlots may not be a significant source of leafy green bacterial pathogen contamination; detection of very low concentrations of indicator E. coli as a function of distance, wind speed, and direction provides data to inform future revisions of produce safety guidance documents such as the current version of the California LGMA
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Risks of Adverse Outcomes for End-Stage Renal Disease Patients Hospitalized with COVID-19. A Retrospective Study in 5 California Medical Centers.
No full textAbstract Since December of 2019, infection with SARS-CoV-2, the virus that causes COVID-19, has led to the most serious infectious disease pandemic since the influenza pandemic of 1918-1920. In the United States, over 49.2 million cases of COVID-19 were diagnosed from February 2020 to December 6, 2021, resulting in 788,315 deaths. In the state of California, over 5.1 million cases of COVID-19 were diagnosed in the same time period, resulting in 75,102 deaths and 3,562 individuals presently hospitalized. While the majority of individuals affected by COVID-19 exhibit only mild symptoms that do not require hospitalization, many require hospitalization, with the most ill patients needing intensive care unit admission, mechanical ventilation, and extracorporeal membrane oxygenation (ECMO) treatment. End stage renal disease (ESRD) is caused when nephrons in the kidneys are damaged over time, the kidneys lose their ability to remove impurities in the blood, and kidney dialysis is required on a regular basis. Infection is the second most reported cause of death in the ESRD population. Annual death rates from pneumonia and sepsis are substantially higher among ESRD patients than among the general population. ESRD patients have a compromised and poorly regulated immune system, which may increase susceptibility to bacterial and viral infections, including the SARS-COV-2 virus. Research studies of ESRD patients who are hospitalized with Covid-19 are needed so that these patients can be risk stratified to appropriate therapeutic treatment regimens and receive the best possible in-hospital care.A retrospective cohort study was conducted to explore 6 clinical outcomes for individuals with and without ESRD, hospitalized with Covid-19 at one of the 5 tertiary care, academic hospitals of the University of California (UC Davis, UC Irvine, UC Los Angeles, UC San Diego, and UC San Francisco). The University of California COVID Research Database (UC CORDS), a large, harmonized database provided by the UC Health Data Warehouse (UCHDW), was utilized for this purpose. In Chapter 1, logistic regression analysis was used to investigate the risks for in-hospital death and hospital length of stay of 7 days or longer. In Chapter 2, the risks of ICU admission and ICU length of stay of 7 days or longer were also explored using logistic regression analysis. In Chapter 3, Cox proportional hazards regression analysis was used to investigate the risks for death and readmission within 30 days post-hospitalization for COVID-19. Factors associated with each of the above clinical outcomes were also explored in separate analyses
Modelling of Indicator Escherichia coli Contamination in Sentinel Oysters and Estuarine Water
No full textThis study was performed to improve the ability to predict the concentrations of Escherichia coli in oyster meat and estuarine waters by using environmental parameters, and microbiological and heavy metal contamination from shellfish growing area in southern Thailand. Oyster meat (n = 144) and estuarine waters (n = 96) were tested for microbiological and heavy metal contamination from March 2016 to February 2017. Prevalence and mean concentrations of E. coli were 93.1% and 4.6 × 103 most probable number (MPN)/g in oyster meat, and 78.1% and 2.2 × 102 MPN/100 mL in estuarine water. Average 7-day precipitation, ambient air temperature, and the presence of Salmonella were associated with the concentrations of E. coli in oyster meat (p < 0.05). Raw data (MPN/g of oyster meat and MPN/100 mL of estuarine water) and log-transformed data (logMPN/g of oyster meat and logMPN/100 mL of estuarine water) of E. coli concentrations were examined within two contrasting regression models. However, the more valid predictions were conducted using non-log transformed values. These findings indicate that non-log transformed data can be used for building more accurate statistical models in microbiological food safety, and that significant environmental parameters can be used as a part of a rapid warning system to predict levels of E. coli before harvesting oysters
Cryptosporidium parvum and cattle: implications for public health and land use restrictions
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Assessing the Link Between Rangeland Cattle and Waterborne Cryptosporidium Parvum Infection in Humans
No full textThis material was digitized as part of a cooperative project between the Society for Range Management, the National Agricultural Library, and the University of Arizona Libraries.The Rangelands archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform March 202
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Implications of Wildlife in E. coli Outbreaks Associated with Leafy Green Produce
No full textOutbreaks of E. coli O157:H7 associated with the consumption of leafy green produce from different regions within California have initiated a series of food safety management practices regarding wildlife access to the produce production environment and potential contamination of irrigation water supplies. Recent surveys of feral swine that document fecal shedding of E. coli O157:H7 underscore the potential for wildlife contamination of fresh produce under appropriate environmental conditions. Collectively, these observations have motivated retailers, processors, and growers of leafy green products to develop that set of ambitious guidelines regarding buffer zones, set-back distances, and fencing requirements for restricting wildlife access to the production environment. These issues and their ramifications for food safety and environmental quality will be discussed
Microbial Groundwater Sampling Protocol for Fecal-Rich Environments
No full textInherently, confined animal farming operations (CAFOs) and other intense fecal-rich environments are potential sources of groundwater contamination by enteric pathogens. The ubiquity of microbial matter poses unique technical challenges in addition to economic constraints when sampling wells in such environments. In this paper, we evaluate a groundwater sampling protocol that relies on extended purging with a portable submersible stainless steel pump and Teflon((R)) tubing as an alternative to equipment sterilization. The protocol allows for collecting a large number of samples quickly, relatively inexpensively, and under field conditions with limited access to capacity for sterilizing equipment. The protocol is tested on CAFO monitoring wells and considers three cross-contamination sources: equipment, wellbore, and ambient air. For the assessment, we use Enterococcus, a ubiquitous fecal indicator bacterium (FIB), in laboratory and field tests with spiked and blank samples, and in an extensive, multi-year field sampling campaign on 17 wells within 2 CAFOs. The assessment shows that extended purging can successfully control for equipment cross-contamination, but also controls for significant contamination of the well-head, within the well casing and within the immediate aquifer vicinity of the well-screen. Importantly, our tests further indicate that Enterococcus is frequently entrained in water samples when exposed to ambient air at a CAFO during sample collection. Wellbore and air contamination pose separate challenges in the design of groundwater monitoring strategies on CAFOs that are not addressed by equipment sterilization, but require adequate QA/QC procedures and can be addressed by the proposed sampling strategy
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