Bioverkapselung lebender Bakterien (Escherichia coli) mit Poly-(Silicat) nach Transformation mit dem Silicatein-alpha-Gen

Die Bioverkapselung ist eine faszinierende Methode, um biologische Materialien einschließlich Zellen in Siliziumdioxid, Metalloxiden oder hybriden Sol-Gel-Polymeren zu immobilisieren. Bisher wurde nur die Sol-Gel-Vorläufertechnologie genutzt, um Bakterien- oder Hefezellen in Siliziumdioxid zu immobilisieren. Hierfür wurden verschiedene Reagenzien als wässrige Vorläufer getestet, um poly(Silicate) auf Biomolekülen (Bhatia et al., 2000) oder Zellen (Liu und Chen 1999; Coradin und Livage, 2007) zu bilden. Einer der erfolgreichsten bisherigen Methoden verwendet eine Mischung aus Silicaten und kolloidalem Silica. Diese initialen Vorläufer werden durch die Zugabe von Salzsäure neutralisiert, was die Gelbildung fortschreiten lässt und die Verkapselung von Bakterien in einem Silica-Netzwerk zur Folge hat (Nassif et al., 2003). Mit der Entdeckung von Silicatein, einem Enzym, das aus Demospongien isoliert wurde und die Bildung von poly(Silicat) katalysiert, wurde es möglich, poly(Silicat) unter physiologischen Bedingungen zu synthetisieren. Silicatein wurde rekombinant in E. coli hergestellt und ist in der Lage, bei Raumtemperatur, neutralem pH-Wert und in wässrigen Puffersystemen aus Siliziumalkoxiden poly(Silicat) zu bilden (Krasko et al., 2000; Müller et al., 2007b; Zhou et al., 1999). In vivo katalysiert Silicatein die Synthese der Silicathülle der Schwamm-Spiculae (Skelettelemente; Müller et al., 2005b; Müller et al., 2007a; Müller et al., 2007b; Schröder et al., 2007a). Dieses Biosilica wurde in Form von Silica-Nanospheren mit Durchmessern zwischen 100 nm und 250 nm organisiert vorgefunden (Pisera 2003; Tahir et al., 2005). Mit dieser Arbeit konnte gezeigt werden, dass Escherichia coli erfolgreich mit dem Silicatein-Gen transformiert werden kann. Das Level der Proteinexpression kann in Anwesenheit von Isopropyl-β-D-thiogalaktopyranosid (IPTG) effizient erhöht werden, indem man die Bakterienzellen gleichzeitig mit Kieselsäure inkubiert. Dieser Effekt konnte sowohl auf Ebene der Synthese des rekombinanten Proteins durch Western Blot als auch durch Immunfluoreszenzmikroskopie nachgewiesen werden. Das heterolog produzierte Silicatein besitzt enzymatische Aktivität und kann die Polymerisation von Kieselsäure katalysieren. Dies konnte sowohl durch Färbung mit Rhodamin123, als auch durch Reaktion der nicht polymerisierten, freien Kieselsäure mit dem ß-Silicomolybdato-Farbsystem (Silicomolybdänblau) nachgewiesen werden. Elektronenmikroskopische Untersuchungen zeigten, dass nur die silicateinexprimierenden Bakterien während des Wachstums in Anwesenheit von Kieselsäure eine viskose Hülle um Zelle herum bilden. Ebenfalls konnte gezeigt werden, dass Silicatein-α aus Suberites domuncula nach Transformation in E. coli an die Zelloberfläche dieser Zellen transportiert wurde und dort seine enzymatische Funktion beibehielt. Die Silicathülle wurde mittels Raster-Elektronenmikroskopie (REM) analysiert. Die Bakterien, die Silicatein exprimierten und poly(Silicat) an ihrer Oberfläche synthetisierten, zeigten die gleichen Wachstumsraten wie die Bakterien, die das Gen nicht enthielten. Schlussfolgernd lässt sich sagen, dass die silicateinvermittelte Verkapselung von Bakterien mit poly(Silicat) die Bandbreite der Anwendung von Bakterien für die Produktion von rekombinanten Proteinen verbessern, erweitern und optimieren könnte.

Ergodicity and regularity of invariant measure for branching Markov processes with immigration

In this thesis we consider systems of finitely many particles moving on paths given by a strong Markov process and undergoing branching and reproduction at random times. The branching rate of a particle, its number of offspring and their spatial distribution are allowed to depend on the particle's position and possibly on the configuration of coexisting particles. In addition there is immigration of new particles, with the rate of immigration and the distribution of immigrants possibly depending on the configuration of pre-existing particles as well. In the first two chapters of this work, we concentrate on the case that the joint motion of particles is governed by a diffusion with interacting components. The resulting process of particle configurations was studied by E. Löcherbach (2002, 2004) and is known as a branching diffusion with immigration (BDI). Chapter 1 contains a detailed introduction of the basic model assumptions, in particular an assumption of ergodicity which guarantees that the BDI process is positive Harris recurrent with finite invariant measure on the configuration space. This object and a closely related quantity, namely the invariant occupation measure on the single-particle space, are investigated in Chapter 2 where we study the problem of the existence of Lebesgue-densities with nice regularity properties. For example, it turns out that the existence of a continuous density for the invariant measure depends on the mechanism by which newborn particles are distributed in space, namely whether branching particles reproduce at their death position or their offspring are distributed according to an absolutely continuous transition kernel. In Chapter 3, we assume that the quantities defining the model depend only on the spatial position but not on the configuration of coexisting particles. In this framework (which was considered by Höpfner and Löcherbach (2005) in the special case that branching particles reproduce at their death position), the particle motions are independent, and we can allow for more general Markov processes instead of diffusions. The resulting configuration process is a branching Markov process in the sense introduced by Ikeda, Nagasawa and Watanabe (1968), complemented by an immigration mechanism. Generalizing results obtained by Höpfner and Löcherbach (2005), we give sufficient conditions for ergodicity in the sense of positive recurrence of the configuration process and finiteness of the invariant occupation measure in the case of general particle motions and offspring distributions.

Algoritmi e ricorsività: macchine di Turing e algoritmi di Markov

In questa questa tesi vengono presentate alcune delle più importanti definizioni di funzione computabile mediante un algoritmo: una prima descrizione è quella data tramite le funzioni ricorsive, un secondo approccio è dato in termini di macchine di Turing, infine, vengono considerati gli algoritmi di Markov. Si dimostra che tutte queste definizioni sono equivalenti. Completa la tesi un breve cenno al lambda-K-calcolo.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Catene di Markov nascoste e giochi stocastici.

In questa trattazione si introduce il concetto di catena di Markov nascosta: una coppia di processi stocastici (X,O), dove X è una catena di Markov non osservabile direttamente e O è il processo stocastico delle osservazioni, dipendente istante per istante solo dallo stato corrente della catena X. In prima istanza si illustrano i metodi per la soluzione di tre problemi classici, dato un modello di Markov nascosto e una sequenza di segnali osservati: valutare la probabilità della osservazione nel modello, trovare la sequenza nascosta di stati più probabile e aggiornare il modello per rendere più probabile l'osservazione. In secondo luogo si applica il modello ai giochi stocastici, nel caso in cui solo uno dei giocatori non è a conoscenza del gioco in ogni turno, ma può cercare di ottenere informazioni utili osservando le mosse dell'avversario informato. In particolare si cercano strategie basate sul concetto di catena di Markov nascoste e si analizzano i risultati ottenuti per valutare l'efficienza dell'approccio.

Catene di Markov reversibili e applicazioni al metodo Montecarlo basato sulle catene di Markov

Gli argomenti trattati in questa tesi sono le catene di Markov reversibili e alcune applicazioni al metodo Montecarlo basato sulle catene di Markov. Inizialmente vengono descritte alcune delle proprietà fondamentali delle catene di Markov e in particolare delle catene di Markov reversibili. In seguito viene descritto il metodo Montecarlo basato sulle catene di Markov, il quale attraverso la simulazione di catene di Markov cerca di stimare la distribuzione di una variabile casuale o di un vettore di variabili casuali con una certa distribuzione di probabilità. La parte finale è dedicata ad un esempio in cui utilizzando Matlab sono evidenziati alcuni aspetti studiati nel corso della tesi.

Caratterizzazione di sequenze di DNA mediante catene di Markov

Questa tesi si inserisce nell’ambito di studio dei modelli stocastici applicati alle sequenze di DNA. I random walk e le catene di Markov sono tra i processi aleatori che hanno trovato maggiore diffusione in ambito applicativo grazie alla loro capacità di cogliere le caratteristiche salienti di molti sistemi complessi, pur mantenendo semplice la descrizione di questi. Nello specifico, la trattazione si concentra sull’applicazione di questi nel contesto dell’analisi statistica delle sequenze genomiche. Il DNA può essere rappresentato in prima approssimazione da una sequenza di nucleotidi che risulta ben riprodotta dal modello a catena di Markov; ciò rappresenta il punto di partenza per andare a studiare le proprietà statistiche delle catene di DNA. Si approfondisce questo discorso andando ad analizzare uno studio che si ripropone di caratterizzare le sequenze di DNA tramite le distribuzioni delle distanze inter-dinucleotidiche. Se ne commentano i risultati, al fine di mostrare le potenzialità di questi modelli nel fare emergere caratteristiche rilevanti in altri ambiti, in questo caso quello biologico.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Classification of organisms previously reported as the SP and Stewart-Letscher groups, with descriptions of Necropsobacter gen. nov. and of Necropsobacter rosorum sp. nov. for organisms of the SP group

To allow classification of bacteria previously reported as the SP group and the Stewart-Letscher group, 35 isolates from rodents (21), rabbits (eight), a dog and humans (five) were phenotypically and genotypically characterized. Comparison of partial rpoB sequences showed that 34 of the isolates were closely related, demonstrating at least 97.4 % similarity. 16S rRNA gene sequence comparison of 20 selected isolates confirmed the monophyly of the SP group and revealed 98.5 %-100 % similarity between isolates. A blast search using the 16S rRNA gene sequences showed that the highest similarity outside the SP group was 95.5 % to an unclassified rat isolate. The single strain, P625, representing the Stewart-Letscher group showed the highest 16S rRNA gene similarity (94.9-95.5 %) to members of the SP group. recN gene sequence analysis of 11 representative strains resulted in similarities of 97-100 % among the SP group strains, which showed 80 % sequence similarity to the Stewart-Letscher group strain. Sequence similarity values based on the recN gene, indicative for whole genome similarity, showed the SP group being clearly separated from established genera, whereas the Stewart-Letscher group strain was associated with the SP group. A new genus, Necropsobacter gen. nov., with only one species, Necropsobacter rosorum sp. nov., is proposed to include all members of the SP group. The new genus can be separated from existing genera of the family Pasteurellaceae by at least three phenotypic characters. The most characteristic properties of the new genus are that haemolysis is not observed on bovine blood agar, positive reactions are observed in the porphyrin test, acid is produced from (+)-L-arabinose, (+)-D-xylose, dulcitol, (+)-D-galactose, (+)-D-mannose, maltose and melibiose, and negative reactions are observed for symbiotic growth, urease, ornithine decarboxylase and indole. Previous publications have documented that both ubiquinones and demethylmenaquinone were produced by the proposed type strain of the new genus, Michel A/76(T), and that the major polyamine of representative strains (type strain not included) of the genus is 1,3-diaminopropane, spermidine is present in moderate amounts and putrescine and spermine are detectable only in minor amounts. The major fatty acids of strain Michel A/76(T) are C(14 : 0), C(16 : 0), C(16:1)omega7c and summed feature C(14 : 0) 3-OH/iso-C(16 : 1) I. This fatty acid profile is typical for members of the family Pasteurellaceae. The G+C content of DNA of strain Michel A/76(T) was estimated to be 52.5 mol% in a previous investigation. The type strain is P709(T) ( = Michel A/76(T) = CCUG 28028(T) = CIP 110147(T) = CCM 7802(T)).

Proposal of Bisgaardia hudsonensis gen. nov., sp. nov. and an additional genomospecies, isolated from seals, as new members of the family Pasteurellaceae

Phenotypic and phylogenetic studies were performed on eight Gram-negative-staining, rod-shaped bacteria isolated from seals. Biochemical and physiological studies showed identical profiles for all of the isolates and indicated that they were related to the family Pasteurellaceae. 16S rRNA gene sequencing demonstrated that the organism represented a distinct cluster with two sublines within the family Pasteurellaceae with <96% sequence similarity to any recognized species. Multilocus sequence analysis (MLSA) including rpoB, infB and recN genes further confirmed these findings with the eight isolates forming a genus-like cluster with two branches. Genome relatedness as deduced from recN gene sequences suggested that the isolates represented a new genus with two species. On the basis of the results of the phylogenetic analysis and phenotypic criteria, it is proposed that these bacteria from seals are classified as Bisgaardia hudsonensis gen. nov., sp. nov. (the type species) and Bisgaardia genomospecies 1. The G+C content of the DNA was 39.5 mol%. The type strain of Bisgaardia hudsonensis gen. nov., sp. nov. is M327/99/2(T) (=CCUG 43067(T)=NCTC 13475(T)=98-D-690B(T)) and the reference strain of Bisgaardia genomospecies 1 is M1765/96/5 (=CCUG 59551=NCTC 13474).

Basfia succiniciproducens gen. nov., sp. nov., a new member of the family Pasteurellaceae isolated from bovine rumen

Gram-negative, coccoid, non-motile bacteria that are catalase-, urease- and indole-negative, facultatively anaerobic and oxidase-positive were isolated from the bovine rumen using an improved selective medium for members of the Pasteurellaceae. All strains produced significant amounts of succinic acid under anaerobic conditions with glucose as substrate. Phenotypic characterization and multilocus sequence analysis (MLSA) using 16S rRNA, rpoB, infB and recN genes were performed on seven independent isolates. All four genes showed high sequence similarity to their counterparts in the genome sequence of the patent strain MBEL55E, but less than 95 % 16S rRNA gene sequence similarity to any other species of the Pasteurellaceae. Genetically these strains form a very homogeneous group in individual as well as combined phylogenetic trees, clearly separated from other genera of the family from which they can also be separated based on phenotypic markers. Genome relatedness as deduced from the recN gene showed high interspecies similarities, but again low similarity to any of the established genera of the family. No toxicity towards bovine, human or fish cells was observed and no RTX toxin genes were detected in members of the new taxon. Based on phylogenetic clustering in the MLSA analysis, the low genetic similarity to other genera and the phenotypic distinction, we suggest to classify these bovine rumen isolates as Basfia succiniciproducens gen. nov., sp. nov. The type strain is JF4016(T) (=DSM 22022(T) =CCUG 57335(T)).