Craig, Amanda, authorBrazile, William, advisorReynolds, Stephen, committee memberClark, Maggie, committee memberEllis, Bob, committee memberAutenrieth, Dan, committee member2023-08-282023-08-282023https://hdl.handle.net/10217/236989The dairy industry is vital to the American economy and impacts both the general population and the workers immediately involved in dairy production. The United States is a significant contributor to the global industry producing approximately 14.6% of the global milk supply. To accomplish this, large herd dairy operations (>1000 head of cattle) operate 24 hours a day, 365 days a year. The long production hours and large herd size result in an increase in the number of injuries and illness in dairy workers. One type of illness diagnosed in dairy farmers is respiratory disease. Multiple researchers have shown that some workers in modern dairy operations have pulmonary function cross-shift declines and lower pulmonary function as well as increased rates of obstructive respiratory conditions such as chronic bronchitis, organic dust toxicity syndrome, occupational asthma, chronic obstructive pulmonary disease, and hypersensitivity pneumonitis (Reynolds, Lundqvist et al. 2013, Reynolds, Nonnenmann et al. 2013).Respiratory disease is caused by exposure to bioaerosols that consist of bacteria, fungi (and the corresponding constituents), pollen, animal dander, feed, and manure. Although bioaerosol exposure can cause infection, the immunological response the body has to bioaerosols that result in decreased lung function is more prevalent in dairy workers. Although some researchers have examined culturable bacteria and fungi, the viable organisms only represent a small fraction of what is detected in the air at the dairies (Katja Radon and Jörg Hartung 2002). One method used to identify Gram-negative bacteria is the recombinant factor C (rFC) assay, a rapid diagnostic assay to identify concentrations of endotoxins present in dairy environments. While endotoxins have explained a portion of the respiratory problems in dairy workers, they do not explain all of the respiratory diseases (May, Romberger et al. 2012). Little research has been performed to determine concentrations of fungi at dairies. Some work has been done using GC/MS to identify fungal markers, but the current research is the first study to use the rapid diagnostic (Glucatell) assay to quantify worker exposure to fungi at dairies. The primary goal of this study was to better characterize dairy worker exposure to bioaerosols through two sample analysis techniques: next generation sequencing (NGS) and rapid diagnostic assays (rFC and Gluactell). The specific aims of this dissertation were to 1) identify similarities and differences in bacterial communities between button samplers and biosamplers co-located inside a cattle pen, 2) characterize worker exposure to the microbial community on dairy farms in comparison to environmental sources, and 3) characterize worker exposure to two bioaerosols constituents based on dairy worker task. For Specific Aim 1, area air samples were taken for five consecutive days to compare the button and biosamplers co-located inside a fresh cow pen and then analyzed using NGS to determine the identity and quantity of bacteria. The current study was the first to compare the biosamplers and button samplers for NGS analysis at a dairy. The results from this study will help researchers make better decisions on the type of sampler that should be employed for collecting airborne bacteria. The researchers found that the biosampler was more effective at collecting samples for NGS. The two samplers had significantly different microbial communities that were identified based on the Principle Coordinate Analysis (PCoA) plot. However, upon further analysis the alpha diversity plot showed relatively similar Shannon and Inverse Simpson indices suggesting both samplers were sampling from the same core microbiome. Therefore, the difference between the samplers is likely due to the high variance in the samples and not actual differences in the microbial community. The alpha diversity plot also had a high operational taxonomic units (OTU) count indicating that the dairy microbiome has a high count of rare bacteria and a low count of dominant bacteria. The biosampler had a higher relative abundance of bacteria across all five sampling days. The majority of the top identified bacteria were Gram-positive. Currently, little research has been done to assess the impact of Gram-positive bacteria on worker respiratory health. Based on these results, future research should focus on Gram-positive bacteria as they may substantially contribute to respiratory disease. Some of the identified bacterial genera have potentially pathogenic species, but data on the species level is needed to determine the potential for infection. Both viable and non-viable bacteria and their corresponding constituents can act as inflammagens, potentially causing cross-shift lung function decline and respiratory disease (May, Romberger et al. 2012). Both samplers collected bacterial communities that could be analyzed and used for NGS, but the biosampler was identified as the better sampler because of the higher OTU counts and greater bacterial diversity. However, depending on the type of sample information required, the button sampler may be advantageous because it can be used for personal samples and throughout the entire day. For Specific Aim 2, personal and area air, hand swabs, and soil samples were collected at one dairy for five consecutive days and analyzed using NGS. The sample sets were then compared to identify differences and similarities between the sample type, identity of the bacteria, and potential for worker exposure. The difference between sampler (button vs biosamplers) was significantly different. The sample type explained more than 50% of the differences seen in the microbial community. The biosampler compared to the button sampler had a lot of variation within their respective types which could explain some of the differences between the communities due to the differences in sampling length and time of day. The variation in the biosampler was mainly due to the second sample taken on each day. The area air samples had the highest relative abundance between the sample types. Soil was thought to have the highest relative abundance but because the number of samples were biased toward air samples (n=60 vs n=15) when the most prevalent top bacteria were chosen they were driven by the air samples. The majority of the bacteria were also found to be Gram-positive across all the samples. The most common source of the bacteria based on the genera information was soil which was expected based on the dusty nature of the dairy environment. Some genera identified have potential pathogenic species, but this dataset did not provide information on the species level. No conclusions can be made on the possibility of infection from the bacteria in these samples. For Specific Aim 3, four dairies were recruited to assess airborne concentrations of Gram-negative bacteria, fungi and dust. Workers were binned into eight different tasks, and the task samples were compared to identify differences in exposure between the tasks. Differences in site and season were not statistically significant and were not included in subsequent analyses. The concentration of dust over a full work shift ranged from 0.95-5.6 mg/m3 and were lower than expected. The highest dust concentration was below the Occupational Safety Health Administration Permissible Exposure Limit (OSHA PEL) of 10 mg/m3 but was not below the suggested Occupational Exposure Limit (OEL) from the American Conference of Governmental Industrial Hygienists (ACGIH) of 2.4 mg/m3 indicating that dust exposure may be a concern for some of the tasks. Machine operators and milkers had the highest geometric mean dust concentrations with concentrations of 0.356 and 0.305 mg/m3 respectively. The endotoxin concentrations ranged from 0.078-40 EU/m3 which was lower than other research observing endotoxins concentrations at dairies and below the suggested OEL of 90 EU/m3. Multi-task workers and milkers had the highest endotoxin concentrations (Donham 2000). The β-glucan concentrations ranged from 0.2-212 pg/m3 with the highest task concentrations found in multi-task workers and machine operators. There is not a suggested OEL for β-glucans but concentrations measured in this study were higher than other studies in waste processing facilities (Douwes 2005). Ultimately, there was not one task that was consistently higher between the different exposure variables and there were no significant differences between any of the tasks. No conclusions or recommendations could be made on the task-based exposures at the dairies. However, even at low concentrations, exposure to agricultural dusts have been shown to induce responses from cytokines (Poole, Dooley et al. 2010). The genetic polymorphism TLR4 has also been demonstrated to cause workers to be more predisposed to sensitization to endotoxins at extremely low concentrations (Reynolds 2012).born digitaldoctoral dissertationsengCopyright and other restrictions may apply. 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