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The opportunistic pathogen Legionella is the leading cause of reported waterborne disease outbreaks in the United States. Legionella can thrive under the warm, stagnant, low-disinfectant conditions characteristic of premise (i.e., building) plumbing systems, making it challenging to identify effective interventions for its control. Copper (Cu) is a promising antimicrobial that can be dosed directly to water via copper-silver ionization systems or released naturally via corrosion of Cu pipes to help control growth of Legionella and other pathogens. However, prior research has shown that Cu does not always reliably control Legionella and sometimes seems to even stimulate its growth. A deeper understanding of the mechanistic effects of Cu on Legionella, at both pure-culture and real-world scales, is critical in order to inform effective controls for Legionella. The overarching objective of the research embodied by this dissertation was aimed at elucidating the chemical and microbial interactions in premise plumbing that govern efficacy of Cu for Legionella control through a series of complementary bench-, pilot-, and field-scale studies. A critical review and synthesis of the literature identified important knowledge gaps in relation to antimicrobial effects of Cu. In particular, changes in the pH, phosphate corrosion control, and rising levels of natural organic matter (NOM) in distributed water are predicted to be important controlling factors. The type of sacrificial anode rod material employed in water heaters was also identified as an underappreciated factor, which directly affects pH, evolution of hydrogen gas as a microbial nutrient, and release of metals (such as aluminum) that bind copper. Microbiological factors: including growth phase of Legionella (e.g., exponential or stationary), strain-specific Cu tolerance, background microbiome composition, and the possibility that viable but non-culturable (VBNC) Legionella might still cause human disease, were also identified as major confounding factors. These knowledge gaps are addressed from various dimensions across each chapter of the dissertation. The effects of pH, orthophosphate corrosion inhibitor concentration, and NOM were examined in bench-scale pure culture experiments over a range of conditions relevant to drinking water. Cupric ions and antimicrobial effects were drastically reduced at pH >7.5, especially in the presence of phosphate, which precipitates copper, or NOM, which complexes the Cu in a form that is less bioavailable. Chick-Watson disinfection models indicated that soluble Cu was the most robust correlate with observed Cu antimicrobial effects across a range of tested waters. This new knowledge suggests that measuring soluble rather than total Cu would be much more informative to guide practitioners in dosing. The research also demonstrated that changes in pH or orthophosphate that have been made to control corrosion over the last few decades, have significantly altered Cu chemistry in buildings, undermining antimicrobial capacity and increasing likelihood of Legionella growth. Pilot-scale experiments confirmed that soluble Cu is an effective indicator of Cu antimicrobial capacity, even in more complex environments represented by realistic hot water plumbing systems. In particular, dosing of orthophosphate, which is widely added by drinking water utilities to control corrosion, directly reduces soluble copper and overall antimicrobial capacity. In some cases, Cu added together with orthophosphate apparently promoted the growth of Legionella, providing an example of at least one circumstance where Cu addition can induce interactive effects that elevate Legionella compared to a control system with trace Cu. It was also demonstrated for the first time that different water heater sacrificial anode types are subject to different corrosion processes, which indirectly influence Cu antimicrobial capacity. Specifically, aluminum ions released from aluminum anode corrosion at 1 mg/L can form an Al(OH)3 gel, which can remove >80% of the soluble Cu from water and reduce Cu antimicrobial effects by >2-log at pH=7. Corrosion from magnesium anodes was found to dramatically increase the pH from 6.8 to >8, which correspondingly reduces Cu antimicrobial capacity. Cu deposition further increased the anode corrosion rate and promoted evolution of hydrogen gas, which is a potent electron donor that stimulates autotrophic microbial growth especially with a magnesium anode. Electric powered anodes did not release metals or alter pH and thus did not diminish Cu antimicrobial capacity. Still, across the pilot-scale experiments, even very high levels of Cu (>1.2 mg/L) at low pH (<7) failed to fully eradicate culturable Legionella. The much lower than expected antimicrobial efficacy of Cu in the pilot-scale hot water plumbing systems was found to be partially explained by the properties of the strain that colonized the systems. Based on fitting the data to a Chick-Watson disinfection model, the outbreak-associated strain that was inoculated into the systems was estimated to be 7 times more tolerant to Cu compared to the common lab strain applied in the bench-scale tests. Further, exponential growth phase L. pneumophila were found to be 2.5 times more susceptible to Cu relative to early stationary phase cultures. It is important to also recognize that, in the pilot-scale systems, drinking water biofilms and the amoeba hosts that colonize them can further shield Legionella from the antimicrobial effects of Cu. Application of shotgun metagenomic sequencing offered the opportunity to more deeply examine the response of Legionella and other pathogens to Cu dosed to the pilot-scale hot water systems in the context of the broader microbiome. It was found that metagenomic analysis provided a sensitive indication of the bioavailability of Cu to the broader microbial community inhabiting the hot water systems, further confirming that the outbreak-associated strain of Legionella that colonized the rigs was relatively tolerant of Cu. Functional gene analysis provided further insight into the mechanistic action of Cu, suggesting multi-modal action of both membrane damage and interruption of nucleic acid replication. The metagenomic analysis further revealed that protozoan host numbers tended to increase in the pilot-scale systems with time, and this could also increase the potential for Legionella proliferation with time. Additional pure culture studies aiming to further assess the mechanistic action of Cu provided strong evidence that Cu can induce a VBNC state for Legionella. This is a concern, given that other studies have indicated that VBNC Legionella are still capable of causing legionellosis. However, VBNC cells are not detected by conventional culturing. Multiple lines of evidence supported the conclusion that Cu induced a VBNC state for Legionella, including membrane integrity, enzyme activity, ATP generation, and Amoebae resuscitation assays applied to two different strains of L. pneumophila. After exposure to Cu, up to a 5-log (99.999%) reduction in culturable Legionella was observed, whereas corresponding reductions in the various viability measures were only by <1-log (90%). In other words, conventional culturing may miss up to 99.99% of the Legionella that is still capable of causing disease. To our knowledge, this is the first study that has assessed the potential for Cu-induced VBNC Legionella. Additional research is needed to further quantify the contribution of VBNC status to challenges in effective Cu-based control of Legionella in premise plumbing. This research further examines, for the first time, the proteomic response of Legionella to Cu, comparing both presumably VBNC and culturable cells. Functional annotation of proteins that were differentially produced by the cells in response to Cu addition revealed that VBNC L. pneumophila modulated its proteome to favor cell membrane- and motility-related proteins, while reducing production of other proteins related to primary metabolism compared to culturable cells. These observations are consistent with the metagenomic-based observations and support the hypothesis that Cu inactivates cells by damaging the cell membrane. The findings also confirmed reduced general cell metabolism that is characteristic of a VBNC state. This dissertation highlights the important and complex effects of Cu on Legionella growth in potable water systems as modified by water chemistry, water heater anode type, characteristics of the surrounding microbiome, and Legionella strain characteristics and growth status. The findings raise important questions about how to measure disinfectant efficacy and provide fundamental new knowledge that can help to better optimize the application of Cu as an antimicrobial to drinking water systems and better protect public health. / Doctor of Philosophy / The opportunistic pathogen Legionella is the leading cause of reportable waterborne disease outbreaks in the United States. Legionella is capable of growing in drinking water plumbing systems in homes, hospitals, hotels, and other buildings. Legionella is spread by inhaling tiny droplets of water that are suspended in the air when using the water, for example when showering, resulting in a severe and deadly form of pneumonia called Legionnaires' Disease. Copper is a promising antimicrobial that can be dosed directly into a building's water system by installing a copper-silver ionization system. There is also interest in understanding whether copper released naturally from copper pipes could help control Legionella. However, prior research indicates that copper sometimes inhibits, sometimes has no effect, and sometimes even seems to stimulate Legionella growth. The purpose of this dissertation was to better understand how the chemical properties of the drinking water, such as pH, presence of corrosion inhibitors that are commonly added to the water by utilities, and natural organic matter impact the ability of copper to kill Legionella. Impacts of the design of the drinking water system were also examined, for example, the material used in the anodes of water heaters to prevent corrosive damage to other system components was hypothesized to change the water chemistry in such a way that could also interfere with copper disinfection. Finally, the effect of the strain of Legionella, its growth phase (exponential or stationary), and culturability status (culturable versus viable but non-culturable) was also examined. Experiments were conducted over a wide range of conditions, from bench-scale pure culture experiments of a few days to full-scale plumbing systems over a period of 3.5 years. The complementary approaches maximize the strength of scientific conclusions about approaches that can more effectively control Legionella. Several discoveries were made as a result of this research that can help to improve the use of copper for controlling Legionella in drinking water systems. In particular, it was found that it is best to keep the pH less than 7.5, because above pH 7.5 copper reacts with orthophosphate corrosion inhibitor or natural organic matter in the water in a manner that makes it less potent to microbes. Through disinfection modeling it was found that soluble copper was the best predictor of the ability to kill Legionella. Therefore, it is recommended from this research that practitioners should monitor soluble copper instead of total copper for the purpose of assessing Legionella control. From the pilot-scale experiments, it was further found that the type of anode installed in the water heater can affect the ability of copper to kill Legionella. Magnesium anodes performed the worst, likely because they raised the pH above the recommended level of 7.5. Aluminum anodes were also a problem because aluminum ions released form an aluminum hydroxide gel that can remove more than 80% of the soluble copper from water. Electric powered anodes did not reduce copper antimicrobial effects by raising pH or forming a gel, but they are much less commonly used. A surprising finding throughout this study was that very high levels of copper (>1.2 mg/L) were required to measurably reduce Legionella in the pilot-scale systems. In the pure culture experiments, it was found that the outbreak-associated strain from Quincy, IL, that was inoculated into the system was highly copper tolerant. This demonstrated that the strain of Legionella that colonizes a particular drinking water system could be the reason why copper is sometimes less effective. Pure culture experiments also found that stationary phase Legionella are more difficult to kill than exponential phase Legionella, which could explain some discrepancies among lab studies reported in the literature. A particularly noteworthy discovery of this research was that copper can make it appear as if Legionella have been killed, because the traditional culture media indicate that there is no growth on the Petri dish; however, they are in fact still alive and capable of causing human disease. This is referred to as a "viable but non-culturable (VBNC)" state. The VBNC state of Legionella was confirmed using an array of techniques (membrane integrity, enzyme activity, ATP generation, and amoebae resuscitation) for two strains of L. pneumophila. We also examined how VBNC Legionella cellular functions were impacted by copper using whole cell proteome, i.e., analysis of all of the proteins extracted from Legionella. Copper induced VBNC Legionella modulated its proteome to favor cell membrane and motility related proteins, and reduced others related to primary metabolism compared with culturable cells. These results were consistent with those obtained via shotgun metagenomic analysis of the microbial community DNA in the pilot-scale water systems. Given the potential for VBNC organisms to prevail in systems disinfected with copper, it is recommended to supplement culture-based monitoring with molecular-based monitoring, e.g., with quantitative polymerase chain reaction. This dissertation highlights the important and complex effects of copper on Legionella growth in potable water systems. The findings help to inform guidance on how to improve the antimicrobial effect of copper, through adjusting the water chemistry, selecting appropriate water heater anodes, and optimizing the overall hot water system design. The dissertation also helps to inform improved strategies for monitoring the efficacy of copper for killing Legionella in real-world systems. Overall, the findings can help to improve policy and practice aimed at reducing the incidence of Legionnaires' Disease and protecting public health.

Fungi play important roles in various environments. Some of them infect plants and cause economically important diseases. However, many fungal pathogens cause similar symptoms or are even spread asymptomatically, making it difficult to identify them morphologically. Therefore, culture-independent, sequence-based diagnostic methods that can detect and identify fungi independently of the symptoms that they cause are desirable. Whole genome metagenomic sequencing has the potential to enable rapid diagnosis of plant diseases without culturing pathogens and designing pathogen-specific probes. In my study, the MinION nanopore sequencer, a portable single‐molecule sequencing platform developed by Oxford Nanopore Technologies, was employed to detect the fungus Calonectria pseudonaviculata (Cps), the causal agent of the devastating boxwood blight disease of the popular ornamental boxwood (Buxus spp.). Various DNA extraction methods and computational tools were compared. Detection was sensitive with an extremely low false positive rate for most methods. Therefore, metagenomic sequencing is a promising technology that could be implemented in routine diagnostics of fungal diseases. Other fungi may play important roles in the atmosphere because of their ice nucleation activity (INA). INA is the capacity of some particles to induce ice formation above the temperature that pure water freezes (-38°C). Importantly, INPs affect the ratio of ice crystals to liquid droplets in clouds, which in turn affects Earth's radiation balance and the intensity and frequency of precipitation. A few fungal species can produce ice nucleating particles (INPs) that cause ice formation at temperatures ≥ –10°C and they may be present in clouds. Two such fungal genera are Fusarium and Mortierella but little is known about their INPs and the genetic basis of their INA. In my study, F. avenaceum and M. alpina were examined in detail. INPs of both species were characterized and it was found that strains within both species varied in regards to the strength of INA. Whole genome sequencing and comparative genomic studies were then performed to identify putative INA genes. Differential expression analyses at different growth temperatures were also performed. INP properties of the two species shared similarities, both appearing to consist of secreted aggregates larger than 30 kDa. Low temperatures induced INA in both species. Lists of candidate INA genes were identified based on their presence in the strains with the strongest INA and/or induction of their expression at low temperatures and because they either encode secreted proteins or enzymes that produce other molecules known to have INA in other organisms. These genes can now be characterized further to help identify the fungal INA genes in both species. This can be expected to help increase our understanding of the role of fungal INA in the atmosphere. / Doctor of Philosophy / Fungi are important to life on Earth and play roles in the environments that surround us. On the one hand, fungi can make plants sick and some plant diseases may even cause economic losses to farmers. If the cause of a disease can be identified accurately in an early stage before symptoms develop, disease transmission may be prevented and plants may be protected from disease. However, it is a challenge to find out which fungus causes which disease since symptoms of different fungal diseases look very similar. Typically, we have to wait for plants to become very sick or we have to isolate the fungus that causes a disease to identity it, which may be time-consuming and not lead to precise identification. DNA sequencing technologies have the potential to lead to more sensitive, faster, and more accurate disease diagnosis and, therefore, may help prevent disease outbreaks. In my study, the MinION nanopore sequencer, a small portable device, was used to detect the fungus causing boxwood blight on boxwood. By loading the DNA of unhealthy boxwood on the device, the boxwood blight pathogen was identified within a very short time. Thus, this method is a promising diagnostic method that may be applied to detect other plant fungal diseases as well. On the other hand, fungi may affect Earth's climate by affecting how many water droplets in clouds are frozen, which in turn affects Earth's temperature and how often and how much it rains and snows. Fungi may affect the freezing of water droplets in clouds since some of them have ice nucleation activity (INA), which is the capacity to catalyze ice formation at a higher temperature than the temperature at which pure water freezes (-38°C), and they may be present in clouds. So far, INA has only been found in a few fungi, including the species Fusarium avenaceum and Mortierella alpina, but the mechanism of their INA is poorly understood. In my study, multiple F. avenaceum and M. alpina strains were examined in detail. Two approaches were used. First, strains in each species were compared with each other to find out how strong their INA is. Once it was found that they differed in their strength of INA, their genomes were sequenced and compared to find genes present in the most active strains and missing from the least active strains since it is these genes that may contribute to INA. It was also found that both fungal species had stronger INA when they were grown at lower temperatures. Therefore, the expression of their genes between higher and lower temperatures was compared to find the genes that were more highly expressed at lower temperatures since it is these genes that may cause INA. Based on previous studies, fungal INPs may either consist of secreted proteins or be the products of biosynthetic gene clusters. Therefore, the list of potential genes was reduced by looking for genes encoding either secreted proteins or biosynthetic gene clusters. The list of these potential INA genes will make it easier to identify the INA genes in F. avenaceum and M. alpina and determine the role of fungi in affecting the weather and climate on Earth.

Plant pathogens are one of the biggest threats to plant health and food security worldwide. To effectively contain plant disease outbreaks, classification and precise identification of pathogens is crucial to determine treatment and preventive measurements. Conventional methods of detection such as PCR may not be sufficient when the pathogen in question is unknown. Advances in sequencing technology have made it possible to sequence entire genomes and metagenomes in real-time and at a relatively low cost, opening an opportunity for the development of alternative methods for detection of novel and unknown plant pathogens. Within this dissertation, an integrated approach is used to reclassify a high-impact group of plant pathogens. Additionally, the application of metagenomics and nanopore sequencing using the Oxford Nanopore Technologies (ONT) MinION for fungal and bacterial plant pathogen detection and precise identification are demonstrated. To improve the classification of the strains belonging to the Ralstonia solanacearum species complex (RSSC), we performed a meta-analysis using a comparative genomics and a reverse ecology approach to accurately portray and refine the understanding of the diversity and evolution of the RSSC. The groups identified by these approaches were circumscribed and made publicly available through the LINbase web server so future isolates can be properly classified. To develop a culture-free detection method of plant pathogens, we used metagenomes of various plants and long-read nanopore sequencing to precisely identify plant pathogens to the strain-level and performed phylogenetic analysis with SNP resolution. In the first paper, we used tomato plants to demonstrate the detection power of bacterial plant pathogens. We compared bioinformatics tools for detection at the strain-level using reads and assemblies. In the second paper, we used a read-based approach to test the feasibility of the methodology to precisely detect the fungal pathogen causing boxwood blight. Lastly, with the improvement in nanopore sequencing, we used grapevine petioles to investigate whether we can go beyond detection and identification and do a phylogenetic analysis. We assembled a metagenome-assembled genome (MAG) of almost the same quality as the genomes obtained from cultured isolates and did a phylogenetic analysis with SNP resolution. Finally, for the cases where there may be no related genome in the database like the pathogen in question, we used machine learning and metagenomics to develop a reference-free approach to detection of plant diseases. We trained eight different machine learning models with reads from healthy and infected plant metagenomes and compared the classification accuracy of reads as belonging to a healthy or infected plant. From the comparison, random forest was the best model in terms of computational resources needed while maintaining a high accuracy (> 0.90). / Doctor of Philosophy / Microbes are present in every environment on the planet and have been on Earth for billions of years. While some microbes are beneficial, others can cause diseases. To differentiate the ones causing diseases from those who do not, looking into the evolutionary forces making them different is crucial to classify and identify them correctly. Although microorganisms cause diseases in humans and animals, the ones causing diseases in plants are one of the biggest threats to plant health and food security worldwide. In a perfect world, plant diseases would be diagnosed by eye or simple procedures. However, when a plant disease is present, it is not always obvious which organism, if any, is causing the disease making it hard for outbreaks to be detected and contained promptly. With technological advances, it is now possible to obtain all the genetic information of not only one organism but all the organisms living in an environment at a time. This genetic information can then be used to precisely identify what organism is causing a disease in a plant for faster disease diagnosis and, consequently, more efficient disease prevention and control. In this dissertation, we used the bacterial group, called Ralstonia solanacearum species complex, which can cause different diseases in more than 200 crops, to investigate and understand the evolution and diversity of the members of this group. We also used newly developed technologies to obtain the genetic material of all the organisms living in multiple important plants including tomato, grapevine, and the ornamental bush, boxwood. Using this genetic material, we developed a methodology for the detection of bacteria and a fungus causing plant diseases. While this works well when the suspected organism or a similar one is available for comparison, the detection of plant diseases in cases where this information is not available is challenging. Machine learning models, where computers can learn complex patterns from data, have the potential to detect pathogens without the need to compare the sequences to sequences of other pathogens. Here we also used the genetic material to train and compare different machine learning models to classify plants as either being infected or healthy.

History teaches us that novel materials, such as chlorofluorocarbon and asbestos, can have dire unintended consequences to human and environmental health. The exponential growth of the field of nanotechnology and the products developed along the way provide the opportunity for a new paradigm of design thinking, in which human and environmental impacts are considered early on in product development. In particular, nanocellulose is touted as a promising green nanomaterial, as it is sourced from an effectively inexhaustible feedstock of wood-based cellulose and is assumed to be harmless to the environment since it is derived from a natural material and assumed to be biodegradable. The various forms of nanocellulose possess an impressive diversity of properties, making it suitable for a wide variety of applications such as drug delivery, reinforcement, food additives, and iridescent make-up. However, as nanomaterials can have different properties relative to their bulk form, it is questionable whether they are truly environmentally friendly, particularly in terms of their biodegradability and potential impacts to receiving environments. Given the projected mass-scale application of nanocellulose and the inevitability of its subsequent release into environment, the purpose of this study was to determine the biodegradability of nanocellulose and the response of environmentally-relevant microbial communities. Specifically, it was hypothesized that cellulose in the nano size range would display distinct biodegradation patterns and rates, relative to larger forms of cellulose. Further, it was hypothesized that modification of nanocellulose, in terms of morphology and surface properties (e.g., charge), would further influence its biodegradability. Wetlands and anaerobic digesters were selected as two environmentally-relevant receiving environments that also play critical roles in global carbon turnover. To examine the biodegradability of nanocellulose, two distinct microbial consortia were enriched from wetland (W) and anaerobic digester (AD) inocula and applied in parallel experiments. The consortia were grown under anaerobic conditions with microcrystalline cellulose as the sole carbon substrate over a period of 246 days before being aliquoted to microcosms for subsequent biodegradation assays. Various forms of nanocellulose were spiked into the microcosms and compared with microcrystalline cellulose as a non nano reference. Microcosms were sacrificed in triplicate with time to monitor cellulose degradation as well as various measures of microbial community response. Microbial communities were characterized in terms of gene markers for total bacteria (16S rRNA genes) and anaerobic cellulose degraders (glycoside hydrolase family 48 genes, i.e., cel48) as well as high throughput amplicon sequencing of 16S rRNA genes (V4 region). A series of three studies examined: 1) the effect of nanocrystalline versus microcrystalline cellulose; 2) the effects of nanocellulose morphology (crystalline rod versus filament) and surface functionalization (cationic and anionic); and 3) metagenomic characterization of cellulose degrading communities using next-generation DNA sequencing. It was found that the nano- size range did not hinder cellulose degradation, in fact, nanocrystalline cellulose degraded slightly faster than microcrystalline cellulose according to 1st order kinetics (1st order decay constants: 0.62±0.08 wk-1 for anionic nanocrystalline cellulose versus 0.39±0.05 wk-1 for microcrystalline cellulose exposed to AD culture; 0.69±0.04 wk-1 for anionic nanocrystalline cellulose versus 0.58±0.05 wk-1 for microcrystalline cellulose exposed to W). Experiments comparing the effects of surface functionalization indicated that anionic nanocellulose degraded faster than cationic cellulose (1st order decay constants for cationic nanocrystalline cellulose: 0.48±0.06 wk-1 and 0.58±0.07 wk-1 on exposure to AD and W cultures respectively). Measurements of 16S rRNA and cel48 genes were consistent with this trend of greater biological growth and cellulose-degrading potential in the anionic nanocellulose condition, suggesting that surface properties can influence biodegradation patterns. Taxonomic characterization of 16S rRNA gene amplicons suggested that taxa known to contain anaerobic cellulose degraders were enriched in both W and AD consortia, which shifted in a distinct manner in response to exposure to the different cellulosic materials. This suggests that distinct groups of microbes may drive the biodegradation of different forms of cellulose. Further, metagenomic investigation provided new insight into taxonomic and functional aspects of anaerobic cellulose degradation, including identification of enzymatic families associated with degradation of the various forms of cellulose. Overall, the findings of this study advance understanding of anaerobic cellulose degradation and indicate that nanocellulose is likely to readily degrade in receiving environments and not pose an environmental concern. / Ph. D.

Many plants, especially grasses, have Nitrogen (N) as their growth-limiting nutrient. Large amounts of N fertilizer (>100 kg N ha-1) are used in managed systems to maximize crop productivity. However, the plant captures less than 50% of the (~12 million tons per year, U.S.) applied N-fertilizer. The remaining mobile N lost through leaching and denitrification accumulates in waterways and the atmosphere, respectively. Losses of fertilizers create environmental and economic concerns globally and create conditions that support the invasion of exotic plants in the natural landscapes. There is thus a need to come up with biological solutions to better manage nitrogen for plant growth and ecosystem sustainability. Microbial communities in the rhizosphere are known to potentially have beneficial effects on plant growth. Diazotrophs, for example, are bacteria that can convert the atmospheric nitrogen to ammonia, a process called 'nitrogen fixation.' Utilizing the natural process of associative nitrogen fixation to support most of the plant's N needs would substantially reduce fertilizer use and thus reduce production and environmental costs. The goal of this dissertation was to determine the structure and function of root-zone microbial communities for increasing productivity of native plants. Towards this end, we study the root-zone bacterial and fungal communities of native and exotic invasive plants. This study identifies that shifts in rhizosphere microbial communities are associated with invasion and highlights the importance of rhizosphere associated structure and function of microbes. A study of root-zone associated microbes in switchgrass (Panicum virgatum L.) - a U.S. native, warm-season, perennial, bioenergy crop indicates that high biomass yield and taller growth are associated with increased plant N-demand and supportive of bacteria with greater rates of N2-fixation in the rhizosphere. Another crucial outcome of the thesis is a better description of the core and cultivar-specific taxa that comprise the switchgrass root-zone associated microbiome. The work in this dissertation has brought us closer to designing N supply strategies by utilizing the natural microbial communities to balance the N-cycle in agroecosystems and support a sustainable environment. / Ph. D.

Cattle are commonly treated with antibiotics that may survive digestion and promote antibiotic resistance when manure or composted manure is used as a soil amendment for crop production. This study was conducted to determine the effects of antibiotic administration and soil amendment practices on microbial diversity and antibiotic resistance of bacteria recovered from the surfaces of lettuce and radishes grown using recommended application rates. Vegetables were planted in field plots amended with raw manure from antibiotic-treated dairy cows, composted-manure from cows with different histories of antibiotic administration, or a chemical fertilizer control (12 plots, n=3). Culture-based methods, 16SrDNA amplicon sequencing, qPCR and shot-gun metagenomics were utilized to profile bacteria and characterize the different gene markers for antibiotic resistance. Culture-based methodologies revealed that lettuce grown in soils amended with BSAs had significantly larger clindamycin resistant populations compared to control conditions. Growth in BSAs was associated with significant changes to the bacterial community composition of radish and lettuce. Total sul1 copies were 160X more abundant on lettuce grown in manure and total tet(W) copies were 30X more abundant on radishes grown in manure. Analysis of shotgun metagenomic data revealed that lettuce grown in manure-amended soils possessed resistance genes for three additional antibiotic classes compared to other treatments. This study demonstrates that raw, antibiotic-exposed manure may alter microbiota and the antibiotic resistance genes present on vegetables. Proper composting of BSAs as recommended by the U.S. Department of Agriculture and Environmental Protection Agency is recommended to mitigate the spread of resistance to vegetable surfaces. / MSLFS

Bacteria are ubiquitously present in every ecosystem on earth. While bacterial communities that reside in specific habitats, called the microbiota, have characteristic compositions, their constituents are exchanged between habitats. To understand the assembly processes and function of a microbial community in an ecosystem, it is thus important to identify its putative sources and sinks. The sources and sinks of the plant leaf microbiome, also called the phyllosphere microbiome, are still under debate. Here, I hypothesized that precipitation is a so far neglected source of the phyllosphere microbiome. Using 16S rRNA amplicon and metagenomic sequencing, I identified the genera Massilia, Sphingomonas, Methylobacterium, Pseudomonas, Acidiphilium, and Pantoea as members of the core rain microbiome in Blacksburg, VA. Further, I used rainwater as a bacterial inoculum to treat tomato plants. I showed that rain-borne bacteria of the genera Chryseobacterium, Enterobacter, Pantoea, Paenibacillus, Duganella, Streptomyces, Massilia, Shinella, Janthinobacterium, Erwinia, and Hyphomicrobium were significantly more abundant in the tomato phyllosphere 7 days post-inoculation, suggesting that these rain-borne bacteria successfully colonized the tomato phyllosphere and had a direct impact on the composition of its microbiome. These results were confirmed by comparing the phyllosphere microbiota of tomato plants grown under greenhouse conditions, and thus never exposed to rain, compared to plants grown outside under environmental conditions, including precipitation. Since a large diversity of bacteria is associated with rain, I also hypothesized that rain-borne bacteria are well adapted to environmental stresses, similar to the stressors microbial biopesticides are exposed to in the field. I thus explored rain as a source of resilient biopesticides to control fire blight, caused by the bacterial pathogen Erwinia amylovora, on apple. In an in-vitro dual culture assay, I identified rain-borne isolates displaying broad-range inhibition against E. amylovora and several other plant pathogens. Two rain-borne isolates, identified as Pantoea agglomerans and P. ananatis, showed the strongest inhibition of E. amylovora. Further experiments showed that these two Pantoea isolates survive under environmental conditions and have a strong protective effect against E. amylovora. However, protection from disease in an orchard was inconsistent, suggesting that the timing of application and formulations must be improved for field applications. Using a UV-mutagenesis screen and whole-genome sequencing, I found that a phenazine antibiotic produced by the P. agglomerans isolate was the likely active molecule that inhibited E. amylovora. Bacterial communities are constantly released as aerosols into the atmosphere from plant, soil, and aquatic sources. When in the atmosphere, bacteria may play crucial roles in geochemical processes, including the formation of precipitation. To understand the potential role of decaying vegetation as a source of atmospheric Ice Nucleation Particles (INPs), I analyzed a historic leaf litter sample collected in 1970 that had maintained Ice Nucleation Activity (INA) for 48 years. A culture-dependent analysis identified the bacterial species Pantoea ananatis and the fungal species Mortierella alpina to have INA and to be present in the leaf litter sample. Further, I determined that both P. ananatis and M. alpina produced heat-sensitive sub-micron INPs that may contribute to atmospheric INPs. The development of new sequencing technologies has facilitated our understanding of microbial community composition, assembly, and function. Most research in bacterial community composition is based on the sequencing of a single region of the 16S rRNA gene. Here, I tested the potential of culture-independent 16S rRNA sequencing of the phyllosphere microbiome for disease diagnosis. I compared the community composition of the microbiome of the aerial parts of cheddar pinks (Dianthus gratianopolitanus) that showed disease symptoms with the microbiome of healthy plants to identify the causative agent. However, I found that the pathogen is probably ubiquitous on cheddar pinks since it was present at similar abundance levels in symptomatic as well as healthy plants. Moreover, the low-resolution of 16S rRNA sequencing did not allow to identify the pathogen at the species or strain level. In summary, in this thesis, I found support for the hypothesis that rain is one of the sources of the phyllosphere microbiome, that rain is a promising source of biopesticides to control plant diseases in the field, that leaf litter is a source of atmospheric INPs, and that 16S rRNA sequencing is not well suited for pathogen identification in support of plant disease diagnosis. Finally, in additional research to which I contributed but that is not included in this thesis, I found that metagenomic sequencing can identify pathogens at the species and strain level and can overcome the limitations of 16S rRNA sequencing. / Doctor of Philosophy / Bacteria are present in nearly every ecosystem on earth. Bacterial communities that reside in a specific habitat are known as microbiota and have characteristic compositions and functions that directly impact the health of ecosystems. Microbiota associated with plants, the so-called plant microbiota, play a crucial role in plant fitness. Thus, it is important to study the assembly and diversity of plant microbiota and their impact on the ecosystem. The sources of leaf microbiota remain to be elucidated. Here, I have studied the contribution of rainfall to the bacteria that live on and in plant leaves. First, using DNA sequencing, I identified the bacteria present in rainfall in Blacksburg, VA. Then, using rain as bacterial inoculum, I found that some rain-borne bacteria, including members of the genera Pantoea, Massilia, Janthinobacterium, and Enterobacter, are efficient colonizers of tomato leaves. Either absence or low abundance of rain-borne bacteria from tomato leaves never exposed to rainfall confirmed further that bacteria in rain contribute to the assembly of plant leaf microbiota. The identification of all putative sources and sinks of leaf microbiota is important when trying to manipulate them to improve plant health and crop yield. Since I found that rainfall contains many different bacteria, I also studied the potential application of rain-borne bacteria in agriculture. The main limitations of commercial bio-pesticides are their poor survival and limited efficacy in the field. Here, I speculated that rain-borne bacteria are well adapted to environmental stressors and could represent efficient bio-pesticides under field conditions. In fact, I isolated two rain-borne bacteria from the genus Pantoea that strongly inhibited Erwinia amylovora, the causal agent of the fire blight disease of apple, in the laboratory under controlled conditions. However, I observed inconsistent results in a 2-year field trial in an orchard. Using mutagenesis and DNA sequencing, I found the active molecule that likely inhibited E. amylovora, in one of the rain-borne isolates. Finally, the access to newer and cheaper sequencing technologies has recently facilitated the study of bacteria at large scale. Most research of microbiota is based on the sequencing of a single region of one gene, the 16S rRNA gene. Here, I tested the potential of 16S rRNA sequencing of leaf microbiota for disease diagnosis. However, I identified the pathogen in healthy and diseased plants, suggesting its ubiquitous presence. Further, due to the low-resolution of 16S rRNA sequencing, it was impossible to identify the pathogen at the species level. In summary, I found that rain is a source that contributes to leaf microbiota, that rain is a promising source of bio-pesticides to control plant diseases, and that 16S rRNA sequencing is not recommended as a tool to diagnose plant diseases.