Target Cell Topography and Cytoskeletal Reorganization in Natural Killer Cell Activity

The immune system has to recognize and destroy abnormal or infected cells to maintain homeostasis. Natural killer (NK) cells directly recognize and kill transformed or virus-infected cells without prior sensitization. We have studied both virus-infected and tumor cells in order to identify the target structures involved in triggering NK activity. Mouse/human cell hybrids containing various human chromosomes were used as targets. The human chromosome responsible for activating NK cell killing was identified to chromosome number 6. The results suggest that activated NK cells recognize ligands that are encoded on human chromosome 6. We showed that the ligand on the target cell side was intercellular adhesion molecule 2 (ICAM-2). There was no difference in the level of expression of ICAM-2, however, but a drastic difference was seen in the distribution of the molecule: ICAM-2 was evenly distributed on the surface of the NK-resistant cells, but almost totally redistributed to the tip of uropods, bud-like extensions, which were absent from the parental cells. Interestingly, the gene coding for cytoskeletal linker protein ezrin has been localized to human chromosome 6, and there was a colocalization of ezrin and ICAM-2 in the uropods. Furthermore, the transfected human ezrin into NK cell-resistant cells induced uropod formation, ICAM-2 and ezrin redistribution to newly formed uropods, and sensitized target cells to NK cell killing. These data reveal a novel form of NK cell recognition: target structures are already present on normal cells; they become detectable only after abnormal redistribution into hot spots on the target cell membrane. NK cells are central players in the defence against virus infections. They inhibit the spread of infection, allowing time for specific immune responses to develop. The virus-proteins that directly activate human NK cell killing are largely unknown. We studied the sensitivity of virus-specific early proteins of Semliki Forest virus (SFV) to NK killing. The viral non-structural proteins (nsP1-4) translated early in the virus cycle were transfected in NK-resistant cells. Viral early gene nsP1 alone efficiently sensitized target cells to NK activity, and the tight membrane association of nsP1 seems to be critical in the triggering of NK killing. NsP1 protein colocalized with (redistributed) ezrin in filopodia-like structures to which the NK cells were bound. The results suggest that also in viral infections NK cells react to rapid changes in membrane topography. Based on the results of this thesis, a new model of target cell recognition of NK cells can be suggested: reorganization of the cytoskeleton induces alterations in cell surface topography, and this new pattern of surface molecules is recognized as "altered-self".

Microbe-induced Innate Immune Responses in Human Dendritic Cells

Two types of antigen-presenting cells (APCs), macrophages and dendritic cells (DCs), function at the interface of innate and adaptive immunity. Through recognition of conserved microbial patterns, they are able to detect the invading pathogens. This leads to activation of signal transduction pathways that in turn induce gene expression of various molecules required for immune responses and eventually pathogen clearance. Cytokines are among the genes induced upon detection of microbes. They play an important role in regulating host immune responses during microbial infection. Chemotactic cytokines, chemokines, are involved in migratory events of immune cells. Cytokines also promote the differentiation of distinct T cell responses. Because of the multiple roles of cytokines in the immune system, the cytokine network needs to be tightly regulated. In this work, the induction of innate immune responses was studied using human primary macrophages or DCs as cell models. Salmonella enterica serovar Typhimurium served as a model for an intracellular bacterium, whereas Sendai virus was used in virus experiments. The starting point of this study was that DCs of mouse origin had recently been characterized as host cells for Salmonella. However, only little was known about the immune responses initiated in Salmonella-infected human DCs. Thus, cellular responses of macrophages and DCs, in particular the pattern of cytokine production, to Salmonella infection were compared. Salmonella-induced macrophages and DCs were found to produce multiple cytokines including interferon (IFN) -gamma, which is conventionally produced by T and natural killer (NK) cells. Both macrophages and DCs also promoted the intracellular survival of the bacterium. Phenotypic maturation of DCs as characterized by upregulation of costimulatory and human leukocyte antigen (HLA) molecules, and production of CCL19 chemokine, were also detected upon infection with Salmonella. Another focus of this PhD work was to unravel the regulatory events controlling the expression of cytokine genes encoding for CCL19 and type III IFNs, which are central to DC biology. We found that the promoters of CCL19 and type III IFNs contain similar regulatory elements that bind nuclear factor kappaB (NF-kappaB) and interferon regulatory factors (IRFs), which could mediate transcriptional activation of the genes. The regulation of type III IFNs in virus infection resembled that of type I IFNs a cytokine class traditionally regarded as antiviral. The induction of type I and type III IFNs was also observed in response to bacterial infection. Taken together, this work identifies new details about the interaction of Salmonella with its phagocytic host cells of human origin. In addition, studies provide information on the regulatory events controlling the expression of CCL19 and the most recently identified IFN family genes, type III IFN genes.

Interactions of natural products with β-lactoglobulins, members of the lipocalin family

Natural products constitute an important source of new drugs. The bioavailability of the drugs depends on their absorption, distribution, metabolism and elimination. To achieve good bioavailability, the drug must be soluble in water, stable in the gastrointestinal tract and palatable. Binding proteins may improve the solubility of drug compounds, masking unwanted properties, such as bad taste, bitterness or toxicity, transporting or protecting these compounds during processing and storage. The focus of this thesis was to study the interactions, including ligand binding and the effect of pH and temperature, of bovine and reindeer β-lactoglobulin (βLG) with such compounds as retinoids, phenolic compounds as well as with compounds from plant extracts, and to investigate the transport properties of the βLG-ligand complex. To examine the binding interactions of different ligands to βLG, new methods were developed. The fluorescence binding method for the evaluation of ligand binding to βLG was miniaturized from a quartz cell to a 96-well plate. A method of ultrafiltration sampling combined with high-performance liquid chromatography was developed to assess the binding of compounds from extracts. The interactions of phenolic compounds or retinoids and βLG were investigated using the 96-well plate method. The majority of flavones, flavonols, flavanones and isoflavones and all of the retinoids included were shown to bind to bovine and reindeer βLG. Phenolic compounds, contrary to retinol, were not released at acidic pH. Those results suggest that βLG may have more binding sites, probably also on the surface of βLG. An extract from Camellia sinensis (L.) O. Kunze (black tea), Urtica dioica L. (nettle) and Piper nigrum (black pepper) were used to evaluate whether βLG could bind compounds from plant extracts. Piperine from P. nigrum was found to bind tightly and rutin from U. dioica weakly to βLG. No components from C. sinensis bound to βLG in our experiment. The uptake and membrane permeation of bovine and reindeer βLG, free and bound with retinol, palmitic acid and cholesterol, were investigated using Caco-2 cell monolayers. Both bovine and reindeer βLG were able to cross the Caco-2 cell membrane. Free and βLG-bound retinol and palmitic acid were transported equally, whereas cholesterol could not cross the Caco-2 cell monolayer free or bound to βLG. Our results showed that βLG can bind different natural product compounds, but cannot enhance transport of retinol, palmitic acid or cholesterol through Caco-2 cells. Despite this, βLG, as a water-soluble binding protein, may improve the solubility of natural compounds, possibly protecting them from early degradation and transporting some of them through the stomach. Furthermore, it may decrease their bad or bitter taste during oral administration of drugs or in food preparations. βLG can also enhance or decrease the health benefits of herbal teas and food preparations by binding compounds from extracts.

Adenoviral gene therapy for non-small cell lung cancer

Adenoviral gene therapy is an experimental approach to cancer refractory to standard cancer therapies. Adenoviruses can be utilized as vectors to deliver therapeutic transgenes into cancer cells, while gene therapy with oncolytic adenoviruses exploits the lytic potential of viruses to kill tumor cells. Although adenoviruses demonstrate several advantages over other vectors - such as the unparalleled transduction efficacy and natural tropism to a wide range of tissues - the gene transfer efficacy to cancer cells has been limited, consequently restricting the therapeutic effect. There are, however, several approaches to circumvent this problem. We utilized different modified adenoviruses to obtain information on adenovirus tropism towards non-small cell lung cancer (NSCLC) cells. To enhance therapeutic outcome, oncolytic adenoviruses were evaluated. Further, to enhance gene delivery to tumors, we used mesenchymal stem cells (MSCs) as carriers. To improve adenovirus specificity, we investigated whether widely used cyclooxygenase 2 (Cox-2) promoter is induced by adenovirus infection in nontarget cells and whether selectivity can be retained by the 3 untranslated region (UTR) AU-rich elements. In addition, we investigated whether switching adenovirus fiber can retain gene delivery in the presence of neutralizing antibodies. Our results show that adenoviruses, whose capsids were modified with arginine-glycine-aspartatic acid (RGD-4C), the serotype 3 knob, or polylysins displayed enhanced gene transfer into NSCLC cell lines and fresh clinical specimens from patients. The therapeutic efficacy was further improved by using respective oncolytic adenoviruses with isogenic 24bp deletion in the E1A gene. Cox-2 promoter was also shown to be induced in normal and tumor cells following adenovirus infection, but utilization of 3 UTR elements can increase the tumor specificity of the promoter. Further, the results suggested that use of MSCs could enhance the bioavailability and delivery of adenoviruses into human tumors, although cells had no tumor tropism per se. Finally, we demonstrated that changing adenovirus fiber can allow virus to escape from existing neutralizing antibodies when delivered systemically. In conclusion, these results reveal that adenovirus gene transfer and specificity can be increased by using modified adenoviruses and MSCs as carriers, and fiber modifications simultaneously decrease the effect of neutralizing antibodies. This promising data suggest that these approaches could translate into clinical testing in patients with NSCLC refractory to current modalities.

Learning Nonlinear Visual Processing from Natural Images

The paradigm of computational vision hypothesizes that any visual function -- such as the recognition of your grandparent -- can be replicated by computational processing of the visual input. What are these computations that the brain performs? What should or could they be? Working on the latter question, this dissertation takes the statistical approach, where the suitable computations are attempted to be learned from the natural visual data itself. In particular, we empirically study the computational processing that emerges from the statistical properties of the visual world and the constraints and objectives specified for the learning process. This thesis consists of an introduction and 7 peer-reviewed publications, where the purpose of the introduction is to illustrate the area of study to a reader who is not familiar with computational vision research. In the scope of the introduction, we will briefly overview the primary challenges to visual processing, as well as recall some of the current opinions on visual processing in the early visual systems of animals. Next, we describe the methodology we have used in our research, and discuss the presented results. We have included some additional remarks, speculations and conclusions to this discussion that were not featured in the original publications. We present the following results in the publications of this thesis. First, we empirically demonstrate that luminance and contrast are strongly dependent in natural images, contradicting previous theories suggesting that luminance and contrast were processed separately in natural systems due to their independence in the visual data. Second, we show that simple cell -like receptive fields of the primary visual cortex can be learned in the nonlinear contrast domain by maximization of independence. Further, we provide first-time reports of the emergence of conjunctive (corner-detecting) and subtractive (opponent orientation) processing due to nonlinear projection pursuit with simple objective functions related to sparseness and response energy optimization. Then, we show that attempting to extract independent components of nonlinear histogram statistics of a biologically plausible representation leads to projection directions that appear to differentiate between visual contexts. Such processing might be applicable for priming, \ie the selection and tuning of later visual processing. We continue by showing that a different kind of thresholded low-frequency priming can be learned and used to make object detection faster with little loss in accuracy. Finally, we show that in a computational object detection setting, nonlinearly gain-controlled visual features of medium complexity can be acquired sequentially as images are encountered and discarded. We present two online algorithms to perform this feature selection, and propose the idea that for artificial systems, some processing mechanisms could be selectable from the environment without optimizing the mechanisms themselves. In summary, this thesis explores learning visual processing on several levels. The learning can be understood as interplay of input data, model structures, learning objectives, and estimation algorithms. The presented work adds to the growing body of evidence showing that statistical methods can be used to acquire intuitively meaningful visual processing mechanisms. The work also presents some predictions and ideas regarding biological visual processing.