No description available.

Despite the lack of robust clinical response, treatment strategies for cancer-induced depression (CID) are currently limited to those developed for non-cancer-related depression. The work presented in this dissertation conceptualizes CID as a pathophysiologically distinct form of depression. To investigate CID at the most basic level, we first developed a preclinical model that was validated by comparison to an established model of stress-induced depressive-like behaviours. The positive control model was developed by chronically treating female BALB/c mice with oral corticosterone (CORT). The CID model was developed using subcutaneous inoculation with 4T1 mammary carcinoma cells. Anhedonia, behavioural despair, and dendritic atrophy in the medial prefrontal cortex (mPFC) were observed in both models. Similar to many human cancer cell lines, 4T1 cells were shown to secrete significant amounts of glutamate, which was markedly attenuated using the system xc- inhibitor sulfasalazine (SSZ). In CID mice, oral treatment with SSZ was at least as effective as fluoxetine, a popular clinical antidepressant, at preventing depressive-like behaviours. This effect was primarily attributable to intact SSZ, rather than its anti-inflammatory metabolite. RNA-sequencing was performed on hippocampal samples from CID and CORT animals. Analysis of differential expressed genes (DEGs) revealed significant overlap between the two models. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and biological process gene ontologies (GO:BP) terms related to ion homeostasis and neuronal communication were enriched for both models. CID was associated with additional DEGs that were not identified in the CORT model. These DEGs were enriched in KEGG pathways and GO:BP terms related to neuronal development, intracellular signalling cascade, learning, and memory. These studies suggest that CID may involve a distinct aetiology, and that glutamate secretion by cancer cells presents a viable target for antidepressant treatment. The development of mechanism-based therapeutics for CID will dramatically improve the quality of life for cancer patients. / Thesis / Doctor of Philosophy (PhD) / Cancer patients are at a high risk of developing depression. In addition to the psychological stress caused by a cancer diagnosis, there is evidence that cancer causes depression through biological pathways. To investigate these pathways, a mouse model of cancer-induced depression (CID) was developed. This model showed comparable behavioural and structural brain deficits to those observed in a stress model of depression. Cancer cells secrete elevated levels of glutamate, a signalling molecule that is involved in depression. In CID mice, inhibiting glutamate release had an antidepressant effect similar to that of fluoxetine, a standard clinical antidepressant. A genetic analysis on brain samples from the CID model revealed significant overlap with the stress model of depression. CID mice had additional changes relevant to learning, memory, and brain cell development that were not detected in the stress model. A better understanding of CID will lead to better treatment strategies developed specifically for cancer patients.

Upland cotton, Gossypium hirsutum L., is a natural source of fiber and a major row crop in the US with an estimated $7 billion raw product value in 2019. However, it is extremely sensitive to the broadleaf herbicide 2,4-dichlorophenoxyacetic acid (2,4-D). With the evolution of herbicide-resistant weeds compounded by off-target spray damage on conventional cotton varieties outside the transgenic Enlist technology (Dow Agrosciences) of herbicide-tolerant cotton varieties (Dow Agrosciences), there is a need to identify and develop novel sources of herbicide tolerance gene for upland cotton genetic improvement. Cotton chromosome substitution (CS) lines carry introgressions from other cultivated and wild allotetraploid Gossypium species that could be sources of novel and exotic alleles for herbicide tolerance. A total of 50 CS lines of G. barbadense L. (CS-B), G. tomentosum Nuttal ex Seeman (CS-T), and G. mustelinum Meers ex Watt (CS-M), in the genetic background of G. hirsutum L. Texas Marker-1 (TM-1) were screened for resistance to a field-recommended rate (1.12 kg ae ha-1) of 2,4-D in the greenhouse. Seven CS lines, CS-T04-15, CS-B12, CS-B15sh, CS-T04, CS-B22sh, CS-T07, and CS-B04-15 with the lowest injury were evaluated for tolerance at four and seven weeks after seedling emergence under field conditions. Progeny tests conducted in the greenhouse validated 2,4-D tolerance of CS-B15sh, showing 41% lower injury than TM-1. Novel variants of CS-T04-15 and CS-T07 were identified with complete tolerance to the herbicide but are segregating. Uptake and translocation of 14C-labeled 2,4-D indicated that reduced translocation of 2,4-D may be the 2,4-D tolerance mechanism in CS-T04-15 and CS-T07, while gene(s) associated with metabolism and reduced auxin transport appeared associated with the 2,4-D tolerance in CS-B15sh. Transcriptome analysis revealed differential expression of genes in 2,4-D-treated CS-B15sh and TM-1 with several components of the 2,4-D/auxin response pathway, including ubiquitin E3 ligase, PB1|AUX/IAA, ARF transcription factors, and F box proteins of the SCFTIR1/AFB complex being up-regulated. Functional annotation of differentially expressed genes revealed down-regulation of auxin transport, suggesting a potential linkage with tolerance mechanism involving altered movement of 2,4-D in CS-B15sh. The selected highly tolerant cotton CS lines will need to be confirmed further using molecular assays.

Psychiatric disorders are believed to result from the combination of genetic predisposition and many environmental triggers. While the large number of disease-associated genetic variations have been recognized by previous genome-wide association studies (GWAS), the role of epigenetic mechanisms that mediate the effects of environmental factors on CNS gene activity in the etiology of most mental illnesses is still largely unclear. A growing body of evidence suggested that the abnormalities (changes in gene expression, formation of neural circuits, and behavior) involved in most psychiatric syndromes are preserved by epigenetic modifications identified in several specific brain regions. In this thesis, we developed the second generation of one of our microfluidic technologies (MOWChIP-seq) and used it to profile genome-wide histone modifications in three mental illness-related biological studies: the effect of psychedelics in mice, schizophrenia, and the effect of maternal immune activation in mice offspring. The second generation of MOWChIP-seq was designed to generate histone modification profiles from as few as 100 cells per assay with a throughput as high as eight assays in each run. Then, we applied the new MOWChIP-seq and SMART-seq2 to profile the histone modification H3K27ac and transcriptome, respectively, using NeuN+ neuronal nuclei from the mouse frontal cortex after a single dose of psychedelic administration. The epigenomic and transcriptomic changes induced by 2,5-Dimethoxy-4-iodoamphetamine (DOI), a subtype of psychedelics, in mouse neuronal nuclei at various time points suggest that the long-lasting effects of the psychedelic are more closely related to epigenomic alterations than the changes in transcriptomic patterns. Next, we comprehensively characterized epigenomic and transcriptomic features from the frontal cortex of 29 individuals with schizophrenia and 29 individually matched controls (gender and age). We found that schizophrenia subjects exhibited thousands of neuronal vs. glial epigenetic differences at regions that included several susceptibility genetic loci, such as NRXN1, RGS4 and GRIN3A. Finally, we investigated the epigenetic and transcriptomic alterations induced by the maternal immune activation (MIA) in mice offspring's frontal cortex. Pregnant mice were injected with influenza virus at GD 9.5 and the frontal cortex from mice pups (10 weeks old) were examined later. The results offered us some insights into the contribution of MIA to the etiology of some mental disorders, like schizophrenia and autism. / Doctor of Philosophy / While this field is still in its early stage, the epigenetic studies of mental disorders present promise to expand our understanding about how environmental stimulates, interacting with genetic factors, contribute to the etiology of various psychiatric syndromes, like major depression and schizophrenia. Previous clinical trials suggested that psychedelics may represent a promising long-lasting treatment for patients with depression and other psychiatric conditions. These research presented the therapeutic potential of psychedelic compounds for treating major depression and demonstrated the capability of psychedelics in increasing dendritic density and stimulating synapse formation. However, the molecular mechanism mediating the clinical effectiveness of psychedelics remain largely unexplored. Our study revealed that epigenomic-driven changes in synaptic plasticity sustain psychedelics' long-lasting antidepressant action. Another serious mental illness is schizophrenia, which could affect how an individual feels, thinks, and behaves. Like most other mental disorders, schizophrenia results from a combination of genetic and environmental causes. Epigenetic marks allow a dynamic impact of environmental factors, including antipsychotic medications, on the access to genes and regulatory elements. Despite this, no study so far has profiled cell-type-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects or the effect of antipsychotic treatment on such epigenetic marks. Here we show the first comprehensive epigenomic characterization of the frontal cortex of 29 individuals with schizophrenia and 29 matched controls. The process of brain development is surprisingly sensitive to a lot of environmental insults. Epidemiological studies have recognized maternal immune activation as a risk factor that may change the normal developmental trajectory of the fetal brain and increase the odds of developing a range of psychiatric disorders, including schizophrenia and autism, in its lifetime. Given the prevalence of the coronavirus, uncovering the molecular mechanism underlie the phenotypic alterations has become more urgent than before, for both prevention and treatment.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第25491号 / 医博第5091号 / 新制||医||1073(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 浅野 雅秀, 教授 篠原 隆司, 教授 近藤 玄 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Switchgrass is a C4 perennial grass that is currently being developed for use as a second generation lignocellulosic biofuel crop. For switchgrass to be fully utilized as a bioenergy crop, large-scale plantings of elite switchgrass germplasm, possibly in monoculture, are likely to occur. This practice may increase the selection pressure on plant pathogens, such as switchgrass rust, which could result in devastating disease epidemics. The identification and deployment of quantitative trait loci (QTLs) and major plant disease resistance genes (R) in switchgrass breeding programs could offer broad spectrum and durable disease resistance in commercial switchgrass cultivars. 'Alamo', a lowland cultivar, is generally resistant to switchgrass rust whereas 'Dacotah', an upland cultivar, is highly susceptible. I hypothesized that major R genes and/or QTLs were contributing to the differences in disease phenotypes of these two cultivars. In this dissertation, bioinformatics and molecular biology approaches were employed to dissect the genetic mechanisms underlying switchgrass rust disease resistance. Novel pseudo-F2 mapping populations were created from a cross derived from 'Alamo' and 'Dacotah'. RNA-sequencing of the pseudo-F2 progenies of 'Alamo' x 'Dacotah' was used to construct a genetic linkage map and to identify potential QTLs correlating with disease resistance. In addition, a homology-based computational method was used to identify 1,011 potential NB-LRR R genes in the switchgrass genome (v 1.1). These potential R genes were characterized for polymorphism and expression differences between 'Alamo' and 'Dacotah'. Moreover, I found that some NB-LRR genes are developmentally regulated in switchgrass. One of the major objectives of switchgrass breeding programs is to develop cultivars with improved feedstock quality; however, changes in the components of the plant cell wall may affect disease resistance. I hypothesized that genetically modified switchgrass plants with altered cell wall components will respond differently than the wild-type to switchgrass rust. Transgenic switchgrass plants overexpressing AtSHN3, a transcription factor with known functions in epicuticular wax accumulation and cell wall deposition, were created. I found that AtSHN3-overexpressing transgenic switchgrass lines were more susceptible than wild-type plants in their response to switchgrass rust. Overall, the results of this dissertation provide a platform for elucidating the molecular mechanisms underlying resistance of switchgrass to switchgrass rust. These findings will help breeders create switchgrass cultivars with improved disease resistance, and will ultimately allow switchgrass to be used for sustainable biomass production. / Ph. D.

Räumliche Transkriptomik-Sequenzierungstechniken werden bei der Untersuchung von RNA in komplexen Geweben immer populärer. Mit diesen neuartigen Ansätze wird die Häufigkeit von Transkripten unter Beibehaltung ihrer räumlichen Lage gemessen, und ermöglichen so die Untersuchung der Genexpression in einem unvoreingenommen, raumzeitlichen Kontext. Angesichts der Vielfalt der zugrunde liegenden experimentellen Techniken, die Datensätze, die von verschiedenen Transkriptomik-Assays erstellt werden, variieren stark. Diese Datensätze werden von Pipelines verarbeitet und analysiert, die speziell für die jeweilige Methode entwickelt sind. Sie sind weder einfach modifizierbar, noch erweiterbar, dadurch sind sie nicht mit Inputs anderer Technologien kompatibel. Hier wird spacemake vorgestellt, eine bioinformatische Software, die darauf abzielt, die Lücke zwischen den verschiedenen räumlichen transkriptomischen Sequenzierungsansätzen zu schließen, durch sie einheitliches, schnelles, modulares, reproduzierbares und erweiterbares Rahmenwerk für die Verarbeitung und Analyse groß angelegter räumlicher transkriptomischer Daten bietet. Spacemake verarbeitet erfolgreich Daten aus den neuesten räumlichen Transkriptomik-Assays, unabhängig von ihrer Inputs. Spacemake ist parallel und läuft im Vergleich zu anderen vergleichbaren Techniken schneller. Spacemake ist modular entwickelt, und bietet verschiedene Module wie automatisiertes Clustering und Analyse, Quality Control, Saturation Analyse durch Downsampling, Zusammenführung technischer Replikate, Integration von scRNA-seq-Daten und Alignment von Mikroskopiebildern. Um ein Höchstmaß an Flexibilität zu bieten, ermöglicht spacemake benutzerkonfigurierbare Einstellungen\textit{run-mode} Einstellungen, wodurch die Unterstützung einer breiten Palette experimenteller Designs gewährleistet wird. Da spacemake in Python geschrieben ist, lässt es sich gut mit anderen Computational Biologie Methoden integrieren. Insgesamt hat spacemake das Potenzial, ein wichtiger Bestandteil der räumlichen Transkriptomik-Toolbox der Gegenwart und Zukunft zu sein. / Spatial transcriptomics sequencing techniques are increasingly popular when studying RNA in complex tissues. These novel approaches measure the abundance of transcripts while retaining their spatial location information, thus allowing the study of gene expression in an unbiased, spatiotemporal context. Given the variety of the underlying experimental techniques, the datasets which are produced by each spatial transcriptomic assay also vary greatly. These datasets are processed and analyzed by pipelines tailored specifically for each method, and are not easily modifiable nor extendable, thus making them incompatible to work with inputs from other technologies. Here spacemake is introduced, a bioinformatic software that aims to close the gap between the various spatial transcriptomic sequencing approaches, by providing a unified, fast, modular, reproducible, and extendable framework for large-scale spatial transcriptomic data processing and analysis. Spacemake successfully processes data from the latest spatial transcriptomics assays, regardless of their input data structure. Spacemake is parallel and runs faster when compared with other similar methods. It has a modular design and offers several modules such as automated clustering and analysis, quality control, saturation analysis through downsampling, technical replicate merging, scRNA-seq data integration, and microscopy image alignment. To offer maximum flexibility, spacemake allows for user-configurable \textit{run-mode} settings, ensuring support for a wide range of experimental designs. Written in Python, spacemake integrates well with other computational biology solutions. Overall spacemake has the potential to be an important part of the spatial transcriptomics toolbox of the present and future.

Lampreys are primitive jawless fishes that diverged over 550 million years ago. As adults, they are either parasitic or non-parasitic. In non-parasitic species, sexual differentiation and oocyte development generally occur earlier than in parasitic species; fecundity is reduced and sexual maturation is accelerated following metamorphosis. The genes controlling ovarian differentiation and maturation in lampreys are poorly understood. This study used RNA-Seq data in the parasitic chestnut lamprey Ichthyomyzon castaneus and non-parasitic northern brook lamprey Ichthyomyzon fossor to identify suites of genes expressed during different stages of ovarian development that show different developmental trajectories with respect to ovarian differentiation and sexual maturation. For this, reference-guided and de novo assembly pipelines were designed for studying a non-model species. To test and explore the relative advantages of the pipelines, expression of insulin superfamily genes was used. This research helps to identify genes involved in lamprey ovarian development and provides insight into evolution of the insulin superfamily in vertebrates. / May 2017

Prostate cancer is the most common noncutaneous cancer among men, yet current diagnostic methods are insufficient and more reliable diagnostic markers need to be developed. The answer that can bridge this gap and enable more efficient diagnoses may lie in microRNAs. These small, single stranded RNA molecules impact protein expression at the translational level and regulate important cellular pathways. Dysregulation of these small RNA molecules can have tumorigenic effects on cells and lead to many types of cancers. Currently the Prostate-Stimulating Antigen (PSA) is used as a diagnostic marker for prostate cancer. However, many factors can elevate PSA levels such as infections and certain medications, consequently leading to false positive diagnoses and unnecessary concern and over treatment with dire outcomes for the patient. Even worse, are the chances of false negative diagnoses, which result in prostate cancer not being diagnosed until its later stages. Therefore, although the use of the PSA level has had its uses in the clinic, it has failed to sufficiently bridge the gap or to distinguish indolent from aggressive disease. It has long been suggested in the literature that microRNAs are drastically altered throughout the course of cancer progression. Here, RNA sequencing was used to identify changes in miR expression profiles diagnostic for prostate cancer patients compared to non-patient controls. The RNA sequencing results were also used to identify normalization miRs to be used as endogenous controls. Confirmatory qRT-PCR was then used to corroborate these results for the top seven dysregulated miRs found from the RNA sequencing data. Data analysis of the Area Under the Curve (AUC) of the Receiver Operating Curves (ROC) of the selected miRs exhibited a better correlation with prostate cancer (AUC Range= 0.819- 0.950) than PSA (AUC of PSA=0.667). In summary, a panel of seven miRs are proposed, many of which have prostate specific targets, which would represent a significant improvement over current testing methods.

Les impacts environnementaux dues à l'extraction minière sont considérables. C'est l'action des microorganismes, en utilisant leur métabolisme du soufre sur les déchets miniers, qui engendre les plus grands défis. Jusqu'à présent, peu de recherches ont été effectués sur les microorganismes environnementaux pour la compréhension globale de l'action du métabolisme du soufre dans une optique de prévention et de rémédiation des impacts environnementaux de l'extraction minière. Dans cette étude, nous avons étudié une bactérie environnementale, Acidithiobacillus thiooxidans, dans le but de comprendre le métabolisme du soufre selon le milieu de culture et le niveau d'acidité du milieu. Nous avons utilisé la transcriptomique à haut débit, RNA-seq, en association avec des techniques de biogéochimie et de microscopie à électrons pour déterminer l'expression des gènes codants les enzymes du métabolisme du soufre. Nous avons trouvé que l'expression des gènes des enzymes du métabolisme du soufre chez ce microorganisme sont dépendantes du milieu, de la phase de croissance et du niveau d'acidité présent dans le milieu. De plus, les analyses biogéochimiques montrent la présence de composés de soufre réduits et d'acide sulfurique dans le milieu. Finalement, une analyse par microscopie électronique révèle que la bactérie emmagasine des réserves de soufre dans son cytoplasme. Ces résultats permettent une meilleure compréhension de son métabolisme et nous rapprochent de la possibilité de développer une technique de prédiction des réactions ayant le potentiel de causer des impacts environnementaux dus à l'extraction minière. / The environmental impact of mining extraction is important. The action of microorganisms using their sulfur metabolism to metabolise compounds in mining waste contributes to reactions that may impact water quality and the environment. Few studies have been conducted on environmental microorganisms to advance the global comprehension of their sulfur metabolism in an attempt to study their impact on the environment. In this study, we cultivate an environmental bacterium, Acidithiobacillus thiooxidans, in an attempt to understand its sulfur metabolism in different growth media and at different levels of acidity. We used high-throughput RNA sequencing in association with sulfur biogeochemistry and electron microscopy to determine the expression of the genes encoding sulfur metabolism enzymes. The expression of genes encoding sulfur metabolism enzymes was media and pH-dependent. Also, the biogeochemical analysis showed the presence of reduced sulfur intermediates and of sulfuric acid in the medium. Finally, an electron microscopic analysis revealed that the bacteria stock sulfur in the cytoplasm. These results resulted in a better comprehension of its sulfur metabolism and it opens the possibility to predict reactions in mining operations that have impact on the environment.