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The Microbiome Surrounding Death and...
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Belk, Aeriel D.
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The Microbiome Surrounding Death and Decay: Microbial Ecology of Food Processing, Meat Spoilage, and Human Decomposition Environments.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
The Microbiome Surrounding Death and Decay: Microbial Ecology of Food Processing, Meat Spoilage, and Human Decomposition Environments./
作者:
Belk, Aeriel D.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
181 p.
附註:
Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Contained By:
Dissertations Abstracts International83-03B.
標題:
Animal sciences. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28411668
ISBN:
9798544289500
The Microbiome Surrounding Death and Decay: Microbial Ecology of Food Processing, Meat Spoilage, and Human Decomposition Environments.
Belk, Aeriel D.
The Microbiome Surrounding Death and Decay: Microbial Ecology of Food Processing, Meat Spoilage, and Human Decomposition Environments.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 181 p.
Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Thesis (Ph.D.)--Colorado State University, 2021.
This item must not be sold to any third party vendors.
The primary processes associated with spoilage and decomposition are driven by microorganisms present on and near the decomposing tissues. Therefore, to better understand the decomposition processes, it is critical that we evaluate the microbial ecology of these systems. In this dissertation, I apply questions related to the vertebrate decomposition environment to several systems: the built environment, meat spoilage, and human decomposition for forensic sciences. The overarching goal of this dissertation is to demonstrate the patterns with which microbial communities assemble and progress in these specific environments, and to show the applications of this knowledge to the larger industry and research fields.Given the diversity of these environments and systems, I begin this dissertation with a review of literature for each of the areas in the first chapter. This chapter summarizes the current knowledge of built environments with a specific focus on the sources of microorganisms in these environments, how the microbial communities assemble, and the ecology of the communities in food processing facilities specifically. Then, I describe the current knowledge related to meat spoilage-associated microorganisms, with specific focus on their role in poultry processing and spoilage. Finally, I introduce terrestrial, outdoor vertebrate decomposition environments. I specifically describe how vertebrate decomposition research can be applied to forensic science, as the patterns of microbial succession in these environments can be used to predict the postmortem interval (PMI).The second chapter, titled "The microbiome of a newly constructed meat processing facility establishes over time by room function and microbial source", describes a research project investigating the microbiome of the built environment of a meat processing facility. We conducted this study to investigate knowledge gaps surrounding how microbial communities initially form in a food processing environment. Specifically, we investigated three major research questions: (1) Is a stable microbiome established in a meat processing facility? (2) What factors are associated with the facility microbial composition? (3) What are the major sources of microbes present in the facility microbiome? To address these questions, we collected samples of the microbial communities from drains and door handles in the newly constructed meat processing facility at Colorado State University approximately monthly spanning the first 18 months of operation. We used 16S rRNA gene sequencing following Earth Microbiome Project protocols to elucidate the content of the microbial communities, and further investigated the patterns using QIIME2 and R. Results indicated that stable microbial communities begin to form throughout the processing facility within the first eight to nine months of consistent production. However, these communities appeared subject to perturbation when major conditions in the facility change, such as a large shift in production volume. Additionally, different communities form within spaces, likely selected for by microbial source, room temperature, general use, and nutrient availability. Interestingly, it also appeared that physical barriers within the facility prevented specific organisms from being transmitted between spaces. Overall, this study demonstrates the importance of deliberate facility design and regular cleaning and sanitation practices to control the microbial communities in the food processing space.Chapter 3, "Air versus water chilling of chicken: a pilot study of quality, shelf-life, microbial ecology, and economics", describes an experiment evaluating the microbial communities associated with chicken breasts that were chilled using two different methods and how the communities from these two treatments lead to different patterns in spoilage over time. In this study, we assessed the meat quality, shelf-life, microbial ecology, and techno-economic impacts of chilling methods on chicken broilers in a university meat laboratory setting. We discovered that air-chilling methods resulted in superior chicken odor and shelf-life, especially prior to 14 days of dark storage. Moreover, we demonstrated that air chilling resulted in a more diverse microbiome that we hypothesize may delay the dominance of the spoilage organism Pseudomonas. Finally, a techno-economic analysis highlighted potential economic advantages to air chilling when compared to water-chilling in facility locations where water costs are a more significant factor than energy costs. Overall, we demonstrated that the method used during chilling (air vs water chilling) influences the final product microbial community, quality, and physiochemistry. Notably, the use of air chilling appeared to delay the bloom of Pseudomonas spp that are the primary spoilers in packaged meat products. By using air chilling to reduce carcass temperatures instead of water chilling producers may extend the time until spoilage of the products and, depending on costs of water in the area, may have economic and sustainability advantages.The fourth and fifth chapters describe studies in which we used patterns in microbial succession in decomposition environments to investigate how decomposition changes the microbial ecology and methods by which these patterns can be used to predict PMI. In chapter four, "Microbiome data accurately predict the postmortem interval using random forest regression models", we explored how to build the most robust Random Forest regression models for prediction of PMI by testing models built on different sample types (gravesoil, skin of the torso, skin of the head), gene markers (16s rRNA, 18s rRNA, ITS), and taxonomic levels (Sequence Variants, Species, Genus). We also tested whether particular suites of indicator microbes were informative across different datasets. Generally, results indicate that the most accurate models for predicting PMI were built using grave soil and skin data using the 16s rRNA genetic marker at the taxonomic level of phyla. Additionally, several phyla consistently contributed highly to model accuracy and may be candidate indicators of PMI.In chapter five, "Patterns of microbial succession in skin and decomposition-associated soils are predictive of the postmortem interval of human remains", we sought to improve the understanding of microbial communities in postmortem human environments by evaluating the patterns of microbial succession associated with human remains at three geographically distinct locations. The primary objectives were to (1) identify patterns in microbial diversity and taxonomy during human decomposition in skin and decomposition-associated soils across distinct environments and (2) determine the utility of amplicon sequencing-derived microbiome data in predicting the postmortem interval within the first 21 days of decomposition. To achieve these, we decomposed a total of 36 donated human remains across three anthropological research facilities (three per season per facility for four seasons) in distinct climactic regions of the United States. We collected microbial samples from the skin of the face, skin of the hip, soil near the face, and soil near the hip daily for the first 21 days of decomposition. These were then sequenced for the 16S and 18S rRNA genes to evaluate the microbial community composition, and generated models to estimate PMI using the Random Forest algorithm with nested cross-validation. We showed that the microbial diversity of decomposition soils decreased over time, likely due to environmental selection for specific organisms such as Clostridiales, Pseudomonodales, and Xanthamonadales. The environmental conditions of the anthropological research facilities used in this study led to distinct differences in microbial communities by location, but patterns of succession were still present.
ISBN: 9798544289500Subjects--Topical Terms:
3174829
Animal sciences.
Subjects--Index Terms:
Built environment
The Microbiome Surrounding Death and Decay: Microbial Ecology of Food Processing, Meat Spoilage, and Human Decomposition Environments.
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The primary processes associated with spoilage and decomposition are driven by microorganisms present on and near the decomposing tissues. Therefore, to better understand the decomposition processes, it is critical that we evaluate the microbial ecology of these systems. In this dissertation, I apply questions related to the vertebrate decomposition environment to several systems: the built environment, meat spoilage, and human decomposition for forensic sciences. The overarching goal of this dissertation is to demonstrate the patterns with which microbial communities assemble and progress in these specific environments, and to show the applications of this knowledge to the larger industry and research fields.Given the diversity of these environments and systems, I begin this dissertation with a review of literature for each of the areas in the first chapter. This chapter summarizes the current knowledge of built environments with a specific focus on the sources of microorganisms in these environments, how the microbial communities assemble, and the ecology of the communities in food processing facilities specifically. Then, I describe the current knowledge related to meat spoilage-associated microorganisms, with specific focus on their role in poultry processing and spoilage. Finally, I introduce terrestrial, outdoor vertebrate decomposition environments. I specifically describe how vertebrate decomposition research can be applied to forensic science, as the patterns of microbial succession in these environments can be used to predict the postmortem interval (PMI).The second chapter, titled "The microbiome of a newly constructed meat processing facility establishes over time by room function and microbial source", describes a research project investigating the microbiome of the built environment of a meat processing facility. We conducted this study to investigate knowledge gaps surrounding how microbial communities initially form in a food processing environment. Specifically, we investigated three major research questions: (1) Is a stable microbiome established in a meat processing facility? (2) What factors are associated with the facility microbial composition? (3) What are the major sources of microbes present in the facility microbiome? To address these questions, we collected samples of the microbial communities from drains and door handles in the newly constructed meat processing facility at Colorado State University approximately monthly spanning the first 18 months of operation. We used 16S rRNA gene sequencing following Earth Microbiome Project protocols to elucidate the content of the microbial communities, and further investigated the patterns using QIIME2 and R. Results indicated that stable microbial communities begin to form throughout the processing facility within the first eight to nine months of consistent production. However, these communities appeared subject to perturbation when major conditions in the facility change, such as a large shift in production volume. Additionally, different communities form within spaces, likely selected for by microbial source, room temperature, general use, and nutrient availability. Interestingly, it also appeared that physical barriers within the facility prevented specific organisms from being transmitted between spaces. Overall, this study demonstrates the importance of deliberate facility design and regular cleaning and sanitation practices to control the microbial communities in the food processing space.Chapter 3, "Air versus water chilling of chicken: a pilot study of quality, shelf-life, microbial ecology, and economics", describes an experiment evaluating the microbial communities associated with chicken breasts that were chilled using two different methods and how the communities from these two treatments lead to different patterns in spoilage over time. In this study, we assessed the meat quality, shelf-life, microbial ecology, and techno-economic impacts of chilling methods on chicken broilers in a university meat laboratory setting. We discovered that air-chilling methods resulted in superior chicken odor and shelf-life, especially prior to 14 days of dark storage. Moreover, we demonstrated that air chilling resulted in a more diverse microbiome that we hypothesize may delay the dominance of the spoilage organism Pseudomonas. Finally, a techno-economic analysis highlighted potential economic advantages to air chilling when compared to water-chilling in facility locations where water costs are a more significant factor than energy costs. Overall, we demonstrated that the method used during chilling (air vs water chilling) influences the final product microbial community, quality, and physiochemistry. Notably, the use of air chilling appeared to delay the bloom of Pseudomonas spp that are the primary spoilers in packaged meat products. By using air chilling to reduce carcass temperatures instead of water chilling producers may extend the time until spoilage of the products and, depending on costs of water in the area, may have economic and sustainability advantages.The fourth and fifth chapters describe studies in which we used patterns in microbial succession in decomposition environments to investigate how decomposition changes the microbial ecology and methods by which these patterns can be used to predict PMI. In chapter four, "Microbiome data accurately predict the postmortem interval using random forest regression models", we explored how to build the most robust Random Forest regression models for prediction of PMI by testing models built on different sample types (gravesoil, skin of the torso, skin of the head), gene markers (16s rRNA, 18s rRNA, ITS), and taxonomic levels (Sequence Variants, Species, Genus). We also tested whether particular suites of indicator microbes were informative across different datasets. Generally, results indicate that the most accurate models for predicting PMI were built using grave soil and skin data using the 16s rRNA genetic marker at the taxonomic level of phyla. Additionally, several phyla consistently contributed highly to model accuracy and may be candidate indicators of PMI.In chapter five, "Patterns of microbial succession in skin and decomposition-associated soils are predictive of the postmortem interval of human remains", we sought to improve the understanding of microbial communities in postmortem human environments by evaluating the patterns of microbial succession associated with human remains at three geographically distinct locations. The primary objectives were to (1) identify patterns in microbial diversity and taxonomy during human decomposition in skin and decomposition-associated soils across distinct environments and (2) determine the utility of amplicon sequencing-derived microbiome data in predicting the postmortem interval within the first 21 days of decomposition. To achieve these, we decomposed a total of 36 donated human remains across three anthropological research facilities (three per season per facility for four seasons) in distinct climactic regions of the United States. We collected microbial samples from the skin of the face, skin of the hip, soil near the face, and soil near the hip daily for the first 21 days of decomposition. These were then sequenced for the 16S and 18S rRNA genes to evaluate the microbial community composition, and generated models to estimate PMI using the Random Forest algorithm with nested cross-validation. We showed that the microbial diversity of decomposition soils decreased over time, likely due to environmental selection for specific organisms such as Clostridiales, Pseudomonodales, and Xanthamonadales. The environmental conditions of the anthropological research facilities used in this study led to distinct differences in microbial communities by location, but patterns of succession were still present.
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Models constructed to predict PMI from the microbial community were accurate within 49 to 92.33 ADD, which is equivalent to 3 to 5.82 days. Models were more accurate when greater taxonomic resolution was used in training. Overall, these results demonstrate that the patterns of microbial succession are predictive of PMI, even across different environments.In summary, in this dissertation I present the results of a series of studies, all of which describe the microbial community development and succession in distinct environments. All of these environments have the potential to influence the decomposition patterns of vertebrate remains. In food processing and meat environments, the microbes present in the community are connected to meat spoilage, which can shorten the product shelf life and contribute to the global food waste problem. In human decomposition, these patterns can be used by forensic investigators to estimate PMI and gain crucial evidence about the death event. In this dissertation, I demonstrate real-world applications of microbial ecology that can protect human health and well-being, and potentially solve crimes.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28411668
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