Fungi are vital microbes present throughout the biosphere. Many species are essential decomposers in the ecosystem, breaking down organic materials and nourishing other lives. Moreover, some have directly influenced human civilization by providing beneficial products, such as edible mushrooms, brewer's yeast, baker's yeast, and antibiotics. However, it's important to note that this group of organisms can also have a "dark side". Each year, fungal pathogens cause approximately 150 million severe infections and 1.7 million deaths. The high rate of infection is compounded by the limited availability of antifungal drugs and the increasing prevalence of antifungal resistance. In response to the global burden of fungal diseases, the World Health Organization published a list of priority fungal pathogens in 2022 and highlighted strategies such as surveillance, sustainable research investments, and public health interventions to combat the increasing fungal threats. My PhD research has focused on surveillance and genomic analyses of several human fungal pathogens, particularly Candida auris. Candida auris is an emerging multidrug-resistant yeast that causes systemic infections with high mortality rates. While initially recognized as a nosocomial pathogen, our genomic analyses of strains isolated from clinical environments, tropical wetlands, fruit surfaces, and dog ears revealed potential transmission routes between diverse environments and patients, including a potential driver for the prevalence of antifungal resistance. Furthermore, our research indicated limited genetic exchange within and between lineages of Candida auris. Through genome-wide association analyses of global Candida auris strains, several known and novel genomic variants were identified associated with susceptibility to azoles, echinocandins, and amphotericin B. Overall, our studies underscore the importance of continuous surveillance to understand potential routes of Candida auris transmission and the urgent need for innovative approaches to treat multidrug-resistant Candida auris infections. / Thesis / Doctor of Philosophy (PhD)

<p dir="ltr">Romaine lettuce is a vegetable crop that is frequently contaminated with and often implicated in mass outbreaks of human-pathogenic <i>Escherichia coli</i>. To date, research has focused on the specific pathogens responsible for those outbreaks and consumer- and retail-level interventions to eliminate those pathogens or to mitigate their spread. However, in many cases, no singular food source can be identified. Food microbiomes, particularly those associated phylloplanes, are a growing interest area and may be key in identifying the conditions that allow for proliferation of pathogenic organisms like <i>E. coli</i> O157:H7. Further, examination of dominant components of the lettuce microbiome may reveal suitable candidates that can be encouraged or engineered to outcompete or indicate the presence of pathogens. Until recently, most microbiome studies focused on bacteria; less understood are the fungi of these microbiomes. Many fungi have myriad applications in the prevention and mitigation of both human and plant diseases. Thus, to effectively prevent pathogenic <i>E. coli </i>outbreaks, a fundamental understanding about the fungi that cohabit the lettuce microbiome is paramount. The most frequently isolated yeast in the romaine lettuce microbiome is an undescribed yeast, revealing the dearth of information regarding nonpathogenic fungi in food systems. First, the novel yeast <i>Sporobolomyces lactucae</i> is described using a multi-locus phylogeny through genealogical gene concordance, with a discussion on the potential ecological range. Second, the genome of <i>S. lactucae </i>strain HU9244 is assembled and annotated with transcriptomic information to help guide target gene selection for biotechnology, particularly in identifying candidates for reporter genes that may assist in the detection of <i>E. coli </i>O157:H7 via olfactory or visual cues. Third, the distribution of the yeast <i>S. lactucae</i> is determined, finding the organism in various climate types and potentially on other leafy greens as well, indicating its suitability for <i>in situ</i> detection of foodborne pathogens such as <i>E. coli</i> O157:H7 commonly found on romaine lettuce and other leafy greens.</p>

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京都大学 / 新制・課程博士 / 博士(農学) / 甲第24676号 / 農博第2559号 / 新制||農||1100(附属図書館) / 学位論文||R5||N5457(農学部図書室) / 京都大学大学院農学研究科応用生物科学専攻 / (主査)教授 寺内 良平, 教授 髙野 義孝, 教授 吉田 健太郎 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

Phylogenetics is transitioning from a history of deep-time analyses with few genes to a future of full-genome data that allows species-level resolutions at deep and shallow time scales. Accompanying this transition is a new focus on demographic parameters like ancestral population sizes and gene flow events in addition to the bifurcating trees that are the cornerstone of the field. As access to more data has highlighted some shortcomings of traditional phylogenetic methods that do not account for the processes of recombination, selection, population size changes, and inter-species gene flow, the field is exploring new theory and methods to catch up with the data. My thesis focuses on signals of demographic processes in genomic data. In exploring these processes, we attempt to avoid biases involved in simply extending old phylogenetic methods -- which have typically been applied to just a handful of genes -- to genomic datasets. Chapter 1 introduces a tool, ipcoal, for simulating genomic data on phylogenetic trees within a framework that includes recombination and the ability to specify effective population sizes, gene flow events, recombination maps, and differences in generation times. This tool enables, to varying degrees, all further chapters. Chapter 2 studies the effects of species tree demographic parameters on the resulting linkage among nearby local genealogies, including implications for gene tree and species tree inference. Chapter 3 examines turnover in local histories along the genome using a theoretical framework, the MS-SMC, which links topological heterogeneity along the genome to species tree model. Chapter 4 introduces simcat, a machine-learning method that uses genome-wide SNP data to infer admixture events on a phylogeny without relying on gene tree inference. This is an important step toward decreasing gene tree estimation error over deep evolutionary time scales. Behind the scenes, simcat uses ipcoal to train a machine learning model to map patterns in SNP data to the demographic scenarios that produced them. These chapters demonstrate new phylogenetic theory and methods for refining our ability to infer historical processes at phylogenetic scales, while also illuminating the importance of population-scale processes like gene flow and recombination for shaping genomes sampled in the present day.

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Pandemics of plague have reemerged multiple times throughout human history with tremendous mortality and extensive geographic spread. The First Pandemic (6th - 8th century) devastated the Mediterranean world, the Second Pandemic (14th - 19th century) swept across much of Afro-Eurasia, and the Third Pandemic (19th - 20th century) reached every continent except for Antarctica, and continues to persist in various endemic foci around the world. Despite centuries of historical research, the epidemiology of these pandemics remains enigmatic. However, recent technological advancements have yielded a novel form of evidence: ancient DNA of the plague bacterium Yersinia pestis. In this thesis, I explore how genomic data can be used to unravel the mysteries of when and where this disease appeared in the past. In particular, I focus on phylogenetic approaches to studying this 'small microbe' with 'big data' (i.e. 100s - 1000s of genomes). I begin by describing novel software I developed that supports the acquisition and curation of large amounts of DNA sequences in public databases. I then use this tool to create an updated global phylogeny of Y. pestis, which includes ~600 genomes with standardized metadata. I devise and validate a new approach for temporal modeling (i.e. molecular clock) that produces robust divergence dates in pandemic lineages of Y. pestis. In addition, I critically examine the questions that genomic evidence can and cannot address in isolation, such as whether the timing and spread of short-term epidemics can be confidently reconstructed. Finally, I apply this theoretical and methodological insight to a case study in which I reconstruct the appearance, persistence, and disappearance of plague in Denmark during the Second Pandemic. The three papers enclosed in this sandwich-thesis contribute to a larger body of work on the anthropology of plague, which seeks to understand how disease exposure and experience change over time and between human populations. Furthermore, this dissertation more broadly impacts both prospective studies of infectious disease, such as environmental surveillance and outbreak monitoring, and retrospective studies, which seek to date the emergence and spread of past pandemics. / Dissertation / Doctor of Philosophy (PhD) / The Plague is a disease that has profoundly impacted human history and is responsible for some of the most fatal pandemics ever recorded. It may surprise many to know that this disease is not a bygone of a past era, but in fact is still present in many regions of the world. Although researchers have been studying plague for hundreds of years, there are many aspects of its epidemiology that are enigmatic. In this thesis, I focus on how DNA from the plague bacterium can be used to estimate where and when this disease appeared in the past. To do so, I reconstruct the evolutionary relationships between modern and ancient strains of plague, using publicly available data and new DNA sequences retrieved from the skeletal remains of plague victims in Denmark. This work offers a new methodological framework for large-scale genetic analysis, provides a critique on what questions DNA evidence can and cannot answer, and expands our knowledge of the global diversity of plague.

Insect-human interactions are very complex; one example is the relationship between humans and the multicolored Asian lady beetle (ALB; Harmonia axyridis). ALB, a native to Asia, was introduced into North American agricultural fields and orchards as a biological control agent for aphids and other soft-bodied insects. However, it is considered a pest by some humans as it invades houses in the fall and winter months. Additionally, ALBs feed on fruits when aphids are scarce, and the hemolymph secreted by ALBs contaminates fruit and affects the taste of fruit products. ALBs invasive behavior has led to concern that this non-native species may be outcompeting native lady beetle species, perhaps leading toward the latter’s extinction. Our study aims to provide genomic and proteomic framework for further study and management of ALB. Insect genomes represent gateways into their complex physiological, behavioral, and structural characteristics, and consequently can be leveraged in the development of highly targeted strategies for the control of pests, the propagation/protection of beneficial species, and responsible stewardship of insect biodiversity. For this study, ALBs were collected on the Mississippi State University campus in Starkville, MS, and their DNA was sequenced using Illumina and Oxford Nanopore technologies. The data was assembled and annotated using multiple computational biology techniques. Over 40K protein-coding genes were predicted with high confidence from the ALB sequence assembly. To complement the genome assembly, the proteome of ALB was explored using LC-MSMS analysis and 2-D electrophoresis. Annotation was used to characterize and identify the proteins found in the proteomic analysis of ALB. Before completing our study, a Japanese H. axyridis genome assembly was published by the Beijing Institute of Science. The Japanese ALB genome had a higher assembly quality than ours, but it was not annotated. We annotated both the Japanese and Mississippi ALB genomes. Comparative analyses were performed to identify possible variations that could have resulted from adaptation, but the data revealed no significant differences between Japanese and Mississippi assemblies. Overall, the results from our study, including the annotation of the Japanese ALB assembly, provide a better understanding of the biology of the ALB and inform further research aimed at managing interactions of this species with humans, their crops, and the environment.

Identifying the forces responsible for driving genomic divergence during speciation is a major goal of research in evolutionary biology. Thus, many efforts have focused on disentangling these forces by modeling the evolutionary histories of interacting populations. Here, population genomic datasets and a diffusion approximation method is used to model the demographic scenarios that influence divergence between Heliconius erato and the incipient species Heliconius himera. The models support an isolation-with-migration scenario, with relatively low and heterogeneous rates of introgression between H. himera and H. erato cyrbia. Additionally, the models suggest a history of selection driving divergence and introgression patterns among H. himera and H. erato. Collectively, these results support H. himera’s status as an incipient species within the H. erato radiation and highlight the interplay of selection and demographic history in shaping heterogeneous patterns of genomic divergence between hybridizing species.

Water stress affects vine productivity, disease tolerance, and enological characteristics of grape. Florida Hybrid Bunch grape are developed through hybridization of local grape spp with Vitis vinifera. These cultivars are mostly grown in southeast region of United States. Water deficit conditions resulted due to failure of rains in the region has developed concern among Florida grape growers to increase water use efficiency of grape. The goal of this research is to identify genes and proteins differentially expressed in response to water stress and to correlate these changes with enological characteristics. Investigating transcripts and proteins will allow us to correlate them and confirm the involvement of specific genes responding to stress. Florida hybrid bunch ‘Suwannee’ grape plants were maintained under green house conditions. Water stress was induced by withholding irrigation. The leaf samples were collected from both irrigated and stressed plants at 5, 10, 15 and 20 day interval. We generated over 200 Subtractive Hybridization PCR products from control and water stressed leaf tissues. Cloning, sequencing and transcript analysis revealed that, 54 genes related to drought and defense regulated pathways out of 125 characterized transcripts. Proteins were extracted from leaf tissue with trichloroacetic acid /acetone and separated by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). The proteins were sequenced in LC/Mass Spectrophotometer. The most important differentially expressed genes include sucrose synthase, actin, isoprene synthase, ABF3, SNF1 related protein kinase, WRKY type transcription factors, AP2, ASR2, glyoxalase I and, cytochrome b which play significant role in cell permeability, transportation, photosynthesis and, maintenance in osmotic stress. We have found that ribulose bisphosphate carboxylase and phosphoribulokinase, which play major role in photosynthesis, were suppressed in response to water stress in Florida hybrid bunch. The results suggested that water stress affects expression of cDNAs associated with defense and drought regulated functions. Such profiling studies will be used to explicate specific pathways disconcerted by water deficit treatments, and in the identification of varietal differences.