With the rapid progress of next-generation sequencing (NGS) technologies, new tools and methods have emerged to investigate the transcriptomics of various organisms. RNA sequencing (RNA-seq) employs NGS to evaluate the presence and abundance of RNA transcripts in biological samples. This technique offers a comprehensive snapshot of the RNA dynamics within cells. With the ability to profile the entire transcriptome of organisms rapidly and accurately, RNA-seq has become the state-of-the-art method for transcriptome profiling, surpassing the traditional microarray approach. Single-cell RNA sequencing (scRNA-seq) was introduced in 2009 to profile the single-cell gene expression in highly heterogeneous samples such as brain tissue and tumors. The advancement of scRNA-seq technologies enables the in-depth transcriptomic study in each cell subtype. When selecting an scRNA-seq method, researchers must weigh the trade-off between profiling more single cells versus obtaining more comprehensive transcripts per cell, while considering the overall costs. The throughput of full-length scRNA-seq methods is usually lower, as each single cell needs to be processed separately to produce scRNA-seq libraries. However, full-length methods enable the researchers to investigate the splicing variants and allele-specific expression. Non-full-length methods only capture the 3' or 5' ends of transcripts, which limits their application in isoform detection, but as cells are pooled after barcoding for cDNA synthesis, the throughput is 2–3 orders of magnitude higher than full-length methods. We developed a droplet-based platform for full-length single-cell RNA-seq, which enabled the efficient recovery of full-length mRNA from individual cells in a high-throughput manner. The developed platform can process ~8,000 single cells within 2 days and detect ~20% more genes compared to Drop-seq. Besides scRNA-seq technology development, we also applied a low-input RNA-seq method to study the transcriptomics in different biological samples. When handling precious biological samples, a low-input method is necessary to profile the transcriptome of homogeneous cell populations. We first studied the epigenomic and transcriptomic regulations in colorectal cancer (CRC) using MOWChIP-seq, a low-input high-throughput method, in conjunction with our low-input RNA-seq approach. Fusobacterium nucleatum (Fnn) is closely related to the progression of cancers like CRC and pancreatic cancer. However, the molecular mechanisms of how Fnn adjusts the tumor microenvironment (TME) and leads to poor clinical outcomes are still unclear. In this in-vitro study, we characterized how hypoxia, an important TME ignored by previous research, facilitates Fnn infection of CRC and corresponding alterations of global epigenome and transcriptome. We infer that hypoxia has similar effects as Fnn infection alone on the CRC cells. The Fnn infection under hypoxia further boosts the proliferation and progression of CRC. We then applied our low-input RNA-seq method to study brain neuroscience and immunology. Psychedelics like DOI show promising clinical efficacy in patients with psychiatric conditions. Although psychedelics exhibit rapid antidepression action and long-lasting effectiveness compared to conventional treatment, their acute psychotic symptoms and potential for drug abuse discourage their application in clinical practice. In this case, it is important to comprehend the molecular mechanisms responsible for psychedelics' clinical efficacy. This understanding can pave the way for the development of improved treatments that do not rely on psychedelics. After profiling the transcriptome of mouse brain samples exposed to psychedelics with different post-exposure times, we concluded that the psychedelic-induced transcriptomic variations are more transient than epigenomic changes. In the second brain neuroscience project, we first applied 3-color FACS sorting to differentiate four neuron and non-neuron subtypes in human postmortem prefrontal cortex tissues. Then we profiled the gene expression of the four subtypes and validated the FACS sorting by examining the expression of marker genes. Differentially expressed genes between each subtype and the others were extracted and proceeded to gene ontology analysis. We identified unique altered biological pathways related to each subtype. The immunology research focuses on revealing the difference between low-grade inflammation and monocyte exhaustion, as well as the unique biological pathways they regulate. Therefore, we profiled the transcriptome of bone marrow-derived monocytes stimulated by PBS control, a low- or high-dose LPS. In addition to wild-type mice, we also included TRAM-deficient and IRAK-M-deficient mice. We concluded that low-dose LPS specifically regulates the TRAM-dependent pathway of TLR4 signaling, and high-dose LPS exclusively upregulates exhaustion markers by impacting metabolic and proliferative pathways. / Doctor of Philosophy / Transcriptomics is the comprehensive study of RNA transcripts derived from an organism's genome. RNA plays a vital role in maintaining the fundamental functions of cells and organisms. In eukaryotes, the genetic information stored in the DNA of cells is transferred to messenger RNA (mRNA) molecules through a process called transcription. These mRNA molecules serve as a bridge between DNA and proteins, as they carry the instructions encoded in genes to ribosomes for protein synthesis. Studying mRNA transcripts reveals various cellular mechanisms and their impact on overall organism function, gene regulation, and disease pathways. With the aid of next-generation sequencing, various RNA-seq approaches have been developed to study mRNA transcripts quantitatively in the past decades. To better understand the gene expression regulations in biological samples, we first applied bulk RNA-seq to profile the transcriptome of various samples under different conditions. Our in-house bulk RNA-seq protocol has been proven to be both high-performance and cost-effective compared to commercial kits. To better understand cellular diversity and uncover rare cell types in heterogeneous biological samples, we developed a droplet-based scRNA-seq platform that can recover full-length mRNA transcripts in a high throughput manner. It can profile the transcriptome of thousands of single cells within two days. It combines the advantages of the droplet-based scRNA-seq method (high throughput) and the well plate-based scRNA-seq method (full-length mRNA recovery).

For over thirty years, Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) has been a major contributor to morbidity and mortality in the commercial swine industry across the globe. This highly mutagenic RNA virus causes significant economic losses wherever it is prevalent, leading to $664 million in annual losses in the United States. Unfortunately, the current prevention and diagnostic techniques available have proven to be insufficient in controlling the spread of this disease. We describe an alternative diagnostic method exploiting the rapid turnaround time and long-read capacity of Oxford Nanopore Technology's MinION next-generation sequencer. We have developed a novel primer set designed to span Open Reading Frames 3 through 7 of the PRRSV genome, which has allowed for multiplexing of samples, thus reducing individual cost of testing, while yielding significantly more information than previously available. This novel primer pair and sequencing technique have distinguished mixed infections within individual animals and may be used to determine vaccination status. This new approach will help producers and veterinarians make better-informed decisions about co-mingling of animals and vaccination strategies, thus reducing the emergence of new, pathogenic strains of PRRSV. / Master of Science / Porcine reproductive and respiratory syndrome virus (PRRSV) is a common, economically important pathogen in commercial swine production. The virus was first identified in the late 1980's during outbreaks in the United States and Europe. In female pigs, the disease is characterized by abortion storms, and the delivery of mummified fetuses or very weak, ill piglets. Neonates often display signs of pneumonia, respiratory distress, and many die from hypoxia. Surviving piglets are highly susceptible to other diseases and are poor growers compared to other, unaffected piglets. Boars may show signs of respiratory disease and can also have decreased libido and reproductive success for months at a time. The virus is prone to mutating once a pig is infected, preventing herds from mounting sufficient immunity to protect against new, mutant strains. Identifying infected pigs early and accurately is crucial to managing PRRSV outbreaks. Currently available diagnostic tests for PRRSV have many limitations, thus we have developed a new diagnostic test using next-generation sequencing technology. Oxford Nanopore Technology provides a commercially available nanopore sequencer, the MinION, that can read long DNA strands in real-time. With this technology we have expanded the area of the PRRSV genome that can be sequenced, which allows us to better identify and distinguish strains of PRRSV in infected, and vaccinated pigs. This new testing method will allow veterinarians and practitioners across the country to better identify and predict outbreaks in their herds, helping them develop better management strategies against PRRSV.

京都大学 / 新制・課程博士 / 博士(農学) / 甲第24241号 / 農博第2520号 / 新制||農||1094(附属図書館) / 学位論文||R4||N5412(農学部図書室) / 京都大学大学院農学研究科応用生命科学専攻 / (主査)教授 宮川 恒, 教授 三芳 秀人, 教授 森 直樹 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

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Previous studies have shown that genes can be switched on or off by age, environmental factors, diseases, and lifestyles. The open or compact structures of chromatin is a crucial factor that affects gene expression. Epigenetics refers to hereditary mechanisms that change gene expression and regulations without changing DNA sequences. Epigenetic modifications, such as DNA methylation, histone modification, and non-coding RNA interaction, play critical roles in cell differentiation and disease processes. The conventional approach requires the use of a few million or more cells as starting material. However, such quantity is not available when samples from patients and small lab animals are examined. Microfluidic technology offers advantages to utilize low-input starting material and for high-throughput. In this thesis, I developed novel microfluidic technologies to study epigenomic regulations, including 1) profiling epigenomic changes associated with LPS-induced murine monocytes for immunotherapy, 2) examining cell-type-specific epigenomic changes associated with BRCA1 mutation in breast tissues for breast cancer treatment, and 3) developing a novel microfluidic oscillatory hybridized ChIRP-seq assay to profile genome-wide lncRNA binding for numerous human diseases. We used 20,000 and 50,000 primary cells to study histone modifications in inflammation and breast cancer of BRCA1 mutation, respectively. In the project of whole-genome lncRNA bindings, our microfluidic ChIRP-seq assay, for the first time, allowed us to probe native lncRNA bindings in mouse tissue samples successfully. The technology is a promising approach for scientists to study lncRNA bindings in primary patients. Our works pave the way for low-input and high-throughput epigenomic profiling for precision medicine development. / Doctor of Philosophy / Traditionally, physicians treat patients with a one-size-fits-all approach, in which disease prevention and treatment are designed for the average person. The one-size-fits-all approach fits many patients, but does not work on some. Precision medicine is launched to improve the low efficiency and diminish side effects, and all of these drawbacks are happening in the traditional approaches. The genomic, transcriptomic, and epigenomic data from patients is a valuable resource for developing precision medicine. Conventional approaches in profiling functional epigenomic regulation use tens to hundreds of millions cells per assay, that is why applications in clinical samples are restricted for several decades. Due to the small volume manipulated in microfluidic devices, microfluidic technology exhibits high efficiency in easy operation, reducing the required number of cells, and improving the sensitivity of assays. In order to examine functional epigenomic regulations, we developed novel microfluidic technologies for applications with the small number of cells. We used 20,000 cells from mice to study the epigenomic changes in monocytes. We also used 50,000 cells from patients and mice to study epigenomic changes associated with BRCA1 mutation in different cell types. We developed a novel microfluidic technology for studying lncRNA bindings. We used 100,000-500,000 cells from cell lines and primary tissues to test several lncRNAs. Traditional approaches require 20-100 million cells per assay, and these cells are infected by virus for over-producing specific lncRNA. However, our technology just needs 100,000 cells (non-over-producing state) to study lncRNA bindings. To the best of our knowledge, this is the first allowed us to study native lncRNA bindings in mouse samples successfully. Our efforts in developing microfluidic technologies and studying epigenomic regulations pave the way for precision medicine development.

Antibiotic resistance (AR) is a critical and looming threat to human health that requires action across the One Health continuum (humans, animals, environment). Coordinated surveillance within the environmental sector is largely underdeveloped in current National Action Plans to combat the spread of AR, and a lack of effective study approaches and standard analytical methods have led to a dearth of impactful environmental monitoring data on the prevalence and risk of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in aquatic environments. In this dissertation, integrated surveillance approaches of surface water and wastewater systems are demonstrated, and efforts are made towards standardizing both metagenomic- and culture-based techniques for globally comparable environmental monitoring. A field study of differentially-impacted watersheds on the island of Puerto Rico post-Hurricane Maria demonstrated the effectiveness of metagenomics in defining direct impact of anthropogenic stress and human fecal contamination on the proliferation of ARGs in riverine systems. The contribution of treated wastewater effluents to the dissemination of highly mobile and clinically-relevant ARGs and their connection to local clinical settings was also revealed. At the international scale, a transect of conventional activated sludge wastewater treatment plants (WWTPs), representing both US/European and Asian regions, were found to significantly attenuate ARG abundance through the removal of total bacterial load and human fecal indicators, regardless of influent ARG compositions. Strong structural symmetry between microbiome and ARG compositions through successional treatment stages suggested that horizontal gene transfer plays a relatively minor role in actively shaping resistomes during treatment. Risk assessment models, however, indicated high-priority plasmid-borne ARGs in final treated effluents discharged around the world, indicating potentially increased transmission risks in downstream environments. Advancements were also made toward standardizing methods for the generation of globally representative and comparable metagenomic- and culture-based AR monitoring data via two comprehensive and critical literature reviews. The first review provides guidance in next-generation sequencing (NGS) studies of environmental AR, proposing a framework for experimental controls, adequate sequencing depths, appropriate use of public databases, and the derivation of datatypes that are conducive for risk assessment. The second review focuses on antibiotic-resistant Enterococcus spp. as robust monitoring targets and an attractive alternative to more widely adopted Gram-negative organisms, while proposing workflows that generate universally equivalent datatypes. Finally, quantitative metagenomic (qMeta) techniques were benchmarked using internal reference standards for high-throughput quantification of ARGs with statistical reproducibility. / Doctor of Philosophy / Antimicrobials have contributed to the reduction of infectious diseases in humans and animals since the early 20th century, increasing productivity and saving countless lives. However, their industrial-scale application across human, animal, and agricultural sectors over the last several decades, especially the use of antibiotics, have engendered the proliferation of antibiotic resistance (AR). AR occurs when changes in bacteria cause the drugs used to treat infections to become less effective and has become one of the leading public health threats of the 21st century. The global spread of AR through the transmission and evolution of antibiotic resistant bacteria (ARB; known colloquially as "superbugs") and antibiotic resistance genes (ARGs) across the One Health continuum (i.e., humans, animals, and the environment) is resulting in increased hospitalization, length of hospital stays, suffering, death, and overall health-care associated costs globally. This dissertation demonstrates the use of metagenomics, the sequencing of all genetic material (e.g., DNA) recovered from a microbial community, for the comprehensive monitoring of ARB and ARGs in aquatic environments, a key pathway for the dissemination of AR into and out of human populations. In order to impede the proliferation of AR, surveillance systems are currently in place to track the spread and evolution of ARB and ARGs in humans and livestock, as well as agri-food sectors. However, the surveillance in natural and built environments (i.e., rivers and domestic sewage) has significantly lagged due to the lack of standard monitoring targets and methodologies. It is also a goal of this dissertation to suggest guidance for the collection of metagenomic- and culture-based AR monitoring data to generate universally comparable results that can be included in centralized databases. Riverine systems are ideal models for tracking input of antibiotic resistance to the natural environment by human activity. After Hurricane-Maria, many of Puerto Rico's wastewater treatment plants (WWTPs) went offline, discharging raw sewage to local surface waters. In a cross-sectional study of watersheds impacted by WWTPs, the abundance of ARGs was directly correlated to increases in local population density. Also, highly mobile and clinically-relevant ARGs were found directly downstream of WWTPs across the island. We found that many of these ARGs corresponded well to forms AR endemic to the region. WWTPs are the primary engineering controls put in place to curb the spread of human and animal waste streams and can help to reduce AR. An international transect of conventional activated sludge WWTPs representing US/Europe and Asia were sampled to garner a mechanistic understanding of the fate or ARGs through treatment. Although WWTPs remove total bacteria, human fecal indicators, and much of the abundance of ARGs, mobile and clinically-relevant ARGs are discharged around the world in large quantities. Consideration is needed in certain regions of iv the world where the managing of human waste streams is the first line of defense against the dissemination of resistance to local communities. Two comprehensive critical literature reviews were conducted to evaluate the various methodologies for generating and analyzing metagenomic- and culture-based AR monitoring data. These reviews address the need for experimental rigor and disclosure of extensive metadata for inclusion in future, centralized databases. The articles further provide guidance with respect to universally comparable datatypes and efficient workflows that will aid in the scale-up of the collection of environmental monitoring data within a global surveillance framework. Finally, a study was conducted to benchmark the use of internal DNA reference standards for the absolute quantification of ARGs (i.e., on a ARG copy per volume of sample basis). The statistical framework for ARG detection and its implications for wastewater-based surveillance systems of AR are also discussed.