国立情報学研究所で電子化したコンテンツを使用している。

国立情報学研究所で電子化したコンテンツを使用している。

In freshwater fish, such as the rainbow trout (Oncorhynchus mykiss), higher ion concentrations in the body fluids relative to the dilute surrounding environment lead to diffusive ion loss that is countered by active ion uptake. Active ion uptake is achieved via specialised cells in the gill epithelium known as ionocytes, with the species studied to date exhibiting multiple ionocyte subtypes with specific complements of ion transport proteins. To better understand the functions and responses of each ionocyte subtype, methods are needed to isolate specific ionocyte subtypes. This thesis developed a method to use fluorescence-activated cell sorting (FACS) to isolate the peanut lectin agglutinin-positive (PNA+) ionocyte subtype of the trout gill, which is posited to be a base-secreting cell that takes up Cl- ions. A suspension of gill cells dissociated using ethylenediaminetetraacetic acid (EDTA) was labelled with biotinylated PNA that was detected using streptavidin conjugated to a fluorophore, and subjected to FACS to yield a population of PNA+ ionocytes of high viability and purity. To validate the utility of the approach, it was used in a proof-of-principle experiment to evaluate transcript abundance of cytosolic carbonic anhydrase (CAc) in PNA+ ionocytes in trout that were subjected to metabolic alkalosis. This experiment revealed that the relative transcript abundance of CAc was significantly elevated in PNA+ ionocytes of alkalotic trout relative to that of control trout (P = 0.001; N = 7), a response that is consistent with the expected role of PNA+ ionocytes in compensation for systemic alkalosis.

Philosophiae Doctor - PhD / The estimated 5 × 10³⁰ prokaryotic cells inhabiting our planet sequester some 350–550 Petagrams (1 Pg = 1015 g) of carbon, 85–130 Pg of nitrogen, and 9–14 Pg of phosphorous, making them the largest reservoir of those nutrients on Earth (Whitman et al. 1998). However, reports suggest that only less than 1% of these microscopic organisms are cultivable (Torsvik et al. 1990; Sleator et al. 2008). Until recently with the development of metagenomic techniques, the knowledge of microbial diversity and their metabolic capabilities has been limited to this small fraction of cultivable organisms (Handelsman et al. 1998). While metagenomics has undoubtedly revolutionised the field of microbiology and biotechnology it has been generally acknowledged that the current approaches for metagenomic bio- rospecting / screening have limitations which hinder this approach to fully access the metabolic potentials and genetic variations contained in microbial genomes (Beloqui et al. 2008). In particular, the construction of metagenomic libraries and heterologous expression are amongst the major obstacles. The aim of this study was to develop an ultra-high throughput approach for screening enzyme activities using uncloned metagenomic DNA, thereby eliminating cloning steps, and employing in vitro heterologous expression. To achieve this, three widely used techniques: cell-free transcription-translation, in vitro compartmentalisation (IVC) and Fluorescence Activated Cell Sorting (FACS) were combined to develop this robust technique called metagenomic in vitro compartmentalisation (mIVC-FACS). Moreover, the E. coli commercial cell-free system was used in parallel to a novel, in-house Rhodococcus erythropolis based cell-free system. The versatility of this technique was tested by identifying novel beta-xylosidase encoding genes derived from a thermophilic compost metagenome. In addition, the efficiency of mIVC-FACS was compared to the traditional metagenomic approaches; function-based (clone library screening) and sequence-based (shotgun sequencing and PCR screening). The results obtained here show that the R. erythropolis cell-free system was over thirty-fold more effective than the E. coli based system based on the number of hits obtained per million double emulsions (dE) droplets screened. Six beta-xylosidase encoding genes were isolated and confirmed from twenty-eight positive dE droplets. Most of the droplets that were isolated from the same gate encoded the same enzyme, indicating that this technique is highly selective. A comparison of the hit rate of this screening approach with the traditional E. coli based fosmid library method shows that mIVC-FACS is at least 2.5 times more sensitive. Although only a few hits from the mIVC-FACS screening were selected for confirmation of beta-xylosidase activity, the proposed hit rate suggests that a significant number of positive hits are left un-accessed through the traditional clone library screening system. In addition, these results also suggest that E. coli expression system might be intrinsically sub-optimal for screening for hemicellulases from environmental genomes compared to R. erythropolis system. The workflow required for screening one million clones in a fosmid library was estimated to be about 320 hours compared to 144 hours required via the mIVC-FACS screening platform. Some of the gene products obtained in both screening platforms show multiple substrate activities, suggesting that the microbial consortia of composting material consist of microorganisms that produce enzymes with multiple lignocellulytic activities. While this platform still requires optimisation, we have demonstrated that this technique can be used to isolate genes encoding enzymes from mixed microbial genomes. mIVC-FACS is a promising technology with the potential to take metagenomic studies to the second generation of novel natural products bio-prospecting. The astonishing sensitivity and ultra-high throughput capacity of this technology offer numerous advantages in metagenomic bio-prospecting. / National Research Foundation (NRF)

Neben chemotherapeutischen und chirurgischen Maßnahmen ist die Bestrahlung integraler Bestandteil multimodaler Therapiekonzepte bei malignen Tumorerkrankungen. In diesem Zusammenhang spielt der Einblick in physiologische und pathophysiologische Abläufe in menschlichen Zellen und auf molekularer Ebene  eine zunehmende Rolle. Auf diese Weise werden komplexe Stoffwechselwege mit ihren unterschiedlichen Funktionen und ihren aus einzelnen Proteinen bestehenden Komponenten immer besser verstanden. Allerdings entstehen durch die Kenntnis dieser Stoffwechselwege neue Fragen, die Gegenstand medizinischer Forschung sind.  Der TGFβ-Signalweg ist ein wesentlicher intrazellulärer Signalweg, der neben zahlreichen anderen Funktionen einen Einfluss auf die Entstehung bestimmter Tumorerkrankungen hat. Eine Vielzahl an Einzelnukleotid-Polymorphismen (single nucleotide polymorphisms, SNP) ist bekannt sowie die Erkenntnis darüber, dass die Anwesenheit von verschiedenen Varianten eines SNP einen Einfluss auf die Zellvitalität hat je nach Behandlungsbedingung. Ziel dieser Arbeit war es den Einfluss von Keimbahn-Polymorphismen in Genen des TGFβ-Signalwegs und der DNA-Reparatur auf die Strahlenempfindlichkeit lymphoblastoider Zellen zu untersuchen. Hierzu wurden 54 käuflich erworbene lymphoblastoide Zellen angezüchtet. Jede dieser Zelllinien wurde sechs parallelen Behandlungsbedingungen unterworfen. Neben der unbehandelten Kontrolle und einer mit anti-TGFβ behandelten Kontrolle wurden Zellen einer alleinigen Bestrahlung mit 3 Gy ausgesetzt. Darüber hinaus wurden Zellen 16 Stunden vor der Bestrahlung mit TGFβ1 oder anti-TGFβ vorinkubiert oder unmittelbar nach der Bestrahlung mit TGFβ1 behandelt.  Nach Ablauf einer 24-stündigen Inkubationszeit erfolgte die Zellvitalitätsmessung mittels FACS (fluorescence activated cell sorting)–Analyse. Die Ergebnisse wurden mit Daten von insgesamt 1656 polymorphen Positionen (aus HapMap Datenbank) aus 21 Kandidatengenen korreliert. Auf diese Weise sollte der Einfluss dieser Polymorphismen auf die Zellvitalität ermittelt werden. Sowohl bei SMAD3 als auch bei SMAD7 fanden sich jeweils 2 SNP, die ein perfektes bzw hohes Kopplungsungleichgewicht (linkage disequilibrium) aufwiesen. Insgesamt waren zwölf Polymorphismen aus acht Genen (TGFBR1, SMAD2, SMAD3, SMAD7, BRCA2, MSH2, MSH6 und XRCC1) mit signifikanten Veränderungen der Zellvitalität assoziiert. Das Variantenallel scheint bis auf wenige Ausnahmen einen zytoprotektiven Effekt zu haben. Ausnahmen sind 3 SNP der Gene BRCA2, SMAD3 und SMAD 7, bei denen der Wildtyp mit höherer Zellvitalität einhergeht. Bei alleiniger Bestrahlung wirkten sich SNP aus SMAD3, SMAD7, MSH2 und MSH6 modulierend auf die Zytotoxizität aus, wenn auch statistisch nicht signifikant. Interessanterweise zeigten sich bei Betrachtung der Auswirkung einer Stimulation mit TGFβ1 vor und nach Bestrahlung mit 3 Gy dieselben SNP als statistisch signifikante Modellprädiktoren wie auch bei alleiniger Bestrahlung mit Ausnahme eines SNP aus SMAD3.  Bei Vorinkubation mit TGFβ1 wirkte sich die MSH2-Variante stärker aus. Hier entstand beim Wildtyp ein zusätzlich zytotoxischer Einfluss im Vergleich zur Stimulation nach Bestrahlung. Bei Inhibition durch anti-TGFβ vor der Bestrahlung zeigte noch ein SNP aus MSH6 und ein SNP aus SMAD7 einen zytoprotektiven Effekt.  Einige Ergebnisse dieser Arbeit könnten, sofern sie im Verlauf durch nachfolgende Studien bestätigt bzw. erweitert werden helfen Therapiekonzepte maligner Tumoren zu optimieren und eine individuelle Radiotherapie zu ermöglichen.

The Diploma Thesis deals with an implementation of the new method for an assessment of a cloning efficiency of the cancer stem cells separated by a high speed cell sorter. The cell-sowing on the microtitration plates was performed by the flow cytometry method in a combination with the high speed cell sorter. In the first part of the Diploma Thesis the new method was introduced and tested on the selected cell lines. The obtained results were compared with the results of the limiting dilution assay within four cell lines. As for the second part of my Diploma Thesis, the method was practically applied to analysis of the cloning capacity of two subpopulations of cE2 cells based on the expressions of characteristic markers of stem and cancer stem cells - CD44 and CD 133. Based on the findings, the new method can be introduced as an approved proceeding for the cloning capacity assessment of cancer stem cells in other workplaces that possess analogical device equipment.

Many normal and cancerous cell lines exhibit a stable composition of cells in distinct states which can, e.g., be defined on the basis of cell surface markers. There is evidence that such an equilibrium is associated with stochastic transitions between distinct states. Quantifying these transitions has the potential to better understand cell lineage compositions. We introduce CellTrans, an R package to quantify stochastic cell state transitions from cell state proportion data from fluorescence-activated cell sorting and flow cytometry experiments. The R package is based on a mathematical model in which cell state alterations occur due to stochastic transitions between distinct cell states whose rates only depend on the current state of a cell. CellTrans is an automated tool for estimating the underlying transition probabilities from appropriately prepared data. We point out potential analytical challenges in the quantification of these cell transitions and explain how CellTrans handles them. The applicability of CellTrans is demonstrated on publicly available data on the evolution of cell state compositions in cancer cell lines. We show that CellTrans can be used to (1) infer the transition probabilities between different cell states, (2) predict cell line compositions at a certain time, (3) predict equilibrium cell state compositions, and (4) estimate the time needed to reach this equilibrium. We provide an implementation of CellTrans in R, freely available via GitHub (https://github.com/tbuder/CellTrans).

Many normal and cancerous cell lines exhibit a stable composition of cells in distinct states which can, e.g., be defined on the basis of cell surface markers. There is evidence that such an equilibrium is associated with stochastic transitions between distinct states. Quantifying these transitions has the potential to better understand cell lineage compositions. We introduce CellTrans, an R package to quantify stochastic cell state transitions from cell state proportion data from fluorescence-activated cell sorting and flow cytometry experiments. The R package is based on a mathematical model in which cell state alterations occur due to stochastic transitions between distinct cell states whose rates only depend on the current state of a cell. CellTrans is an automated tool for estimating the underlying transition probabilities from appropriately prepared data. We point out potential analytical challenges in the quantification of these cell transitions and explain how CellTrans handles them. The applicability of CellTrans is demonstrated on publicly available data on the evolution of cell state compositions in cancer cell lines. We show that CellTrans can be used to (1) infer the transition probabilities between different cell states, (2) predict cell line compositions at a certain time, (3) predict equilibrium cell state compositions, and (4) estimate the time needed to reach this equilibrium. We provide an implementation of CellTrans in R, freely available via GitHub (https://github.com/tbuder/CellTrans).

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