Microbe-induced activation of inflammatory cytokine response in human cells

Human body is in continuous contact with microbes. Although many microbes are harmless or beneficial for humans, pathogenic microbes possess a threat to wellbeing. Antimicrobial protection is provided by the immune system, which can be functionally divided into two parts, namely innate and adaptive immunity. The key players of the innate immunity are phagocytic white blood cells such as neutrophils, monocytes, macrophages and dendritic cells (DCs), which constantly monitor the blood and peripheral tissues. These cells are armed for rapid activation upon microbial contact since they express a variety of microbe-recognizing receptors. Macrophages and DCs also act as antigen presenting cells (APCs) and play an important role in the development of adaptive immunity. The development of adaptive immunity requires intimate cooperation between APCs and T lymphocytes and results in microbe-specific immune responses. Moreover, adaptive immunity generates immunological memory, which rapidly and efficiently protects the host from reinfection. Properly functioning immune system requires efficient communication between cells. Cytokines are proteins, which mediate intercellular communication together with direct cell-cell contacts. Immune cells produce inflammatory cytokines rapidly following microbial contact. Inflammatory cytokines modulate the development of local immune response by binding to cell surface receptors, which results in the activation of intracellular signalling and modulates target cell gene expression. One class of inflammatory cytokines chemokines has a major role in regulating cellular traffic. Locally produced inflammatory chemokines guide the recruitment of effector cells to the site of inflammation during microbial infection. In this study two key questions were addressed. First, the ability of pathogenic and non-pathogenic Gram-positive bacteria to activate inflammatory cytokine and chemokine production in different human APCs was compared. In these studies macrophages and DCs were stimulated with pathogenic Steptococcus pyogenes or non-pathogenic Lactobacillus rhamnosus. The second aim of this thesis work was to analyze the role of pro-inflammatory cytokines in the regulation of microbe-induced chemokine production. In these studies bacteria-stimulated macrophages and influenza A virus-infected lung epithelial cells were used as model systems. The results of this study show that although macrophages and DCs share several common antimicrobial functions, these cells have significantly distinct responses against pathogenic and non-pathogenic Gram-positive bacteria. Macrophages were activated in a nearly similar fashion by pathogenic S. pyogenes and non-pathogenic L. rhamnosus. Both bacteria induced the production of similar core set of inflammatory chemokines consisting of several CC-class chemokines and CXCL8. These chemokines attract monocytes, neutrophils, dendritic cells and T cells. Thus, the results suggest that bacteria-activated macrophages efficiently recruit other effector cells to the site of inflammation. Moreover, macrophages seem to be activated by all bacteria irrespective of their pathogenicity. DCs, in contrast, were efficiently activated only by pathogenic S. pyogenes, which induced DC maturation and production of several inflammatory cytokines and chemokines. In contrast, L. rhamnosus-stimulated DCs matured only partially and, most importantly, these cells did not produce inflammatory cytokines or chemokines. L. rhamnosus-stimulated DCs had a phenotype of "semi-mature" DCs and this type of DCs have been suggested to enhance tolerogenic adaptive immune responses. Since DCs have an essential role in the development of adaptive immune response the results suggest that, in contrast to macrophages, DCs may be able to discriminate between pathogenic and non-pathogenic bacteria and thus mount appropriate inflammatory or tolerogenic adaptive immune response depending on the microbe in question. The results of this study also show that pro-inflammatory cytokines can contribute to microbe-induced chemokine production at multiple levels. S. pyogenes-induced type I interferon (IFN) was found to enhance the production of certain inflammatory chemokines in macrophages during bacterial stimulation. Thus, bacteria-induced chemokine production is regulated by direct (microbe-induced) and indirect (pro-inflammatory cytokine-induced) mechanisms during inflammation. In epithelial cells IFN- and tumor necrosis factor- (TNF-) were found to enhance the expression of PRRs and components of cellular signal transduction machinery. Pre-treatment of epithelial cells with these cytokines prior to virus infection resulted in markedly enhanced chemokine response compared to untreated cells. In conclusion, the results obtained from this study show that pro-inflammatory cytokines can enhance microbe-induced chemokine production during microbial infection by providing a positive feedback loop. In addition, pro-inflammatory cytokines can render normally low-responding cells to high chemokine producers via enhancement of microbial detection and signal transduction.

Transfunctional living walls-designing living walls for environmental and social benefits

Greater attention is being directed towards incorporating greenery into the built environment as increasing global urbanisation drives the search for sustainable urbanism. This research takes a parametric approach to studying living wall dynamics using three methods to cover a diversity of design parameters and performance criteria. The findings led to a functional typology for living walls based on a range of design, context and performance parameters wider than previously identified. Such parametric studies offer valuable insights into 'transfunctional' living walls for homes, schools and public spaces.

Surface Proteins of Lactobacillus crispatus: Adhesive Properties and Cell Wall Anchoring

Bacterial surface-associated proteins are important in communication with the environment and bacteria-host interactions. In this thesis work, surface molecules of Lactobacillus crispatus important in host interaction were studied. The L. crispatus strains of the study were known from previous studies to be efficient in adhesion to intestinal tract and ECM. L. crispatus JCM 5810 possess an adhesive surface layer (S-layer) protein, whose functions and domain structure was characterized. We cloned two S-layer protein genes (cbsA; collagen-binding S-layer protein A and silent cbsB) and identified the protein region in CbsA important for adhesion to host tissues, for polymerization into a periodic layer as well as for attachment to the bacterial cell surface. The analysis was done by extensive mutation analysis and by testing His6-tagged fusion proteins from recombinant Escherichia coli as well as by expressing truncated CbsA peptides on the surface of Lactobacillus casei. The N-terminal region (31-274) of CbsA showed efficient and specific binding to collagens, laminin and extracellular matrix on tissue sections of chicken intestine. The N-terminal region also contained the information for formation of periodic S-layer polymer. This region is bordered at both ends by a conserved short region rich in valines, whose substitution to leucines drastically affected the periodic polymer structure. The mutated CbsA proteins that failed to form a periodic polymer, did not bind collagens, which indicates that the polymerized structure of CbsA is needed for collagen-binding ability. The C-terminal region, which is highly identical in S-layer proteins of L. crispatus, Lactobacillus acidophilus and Lactobacillus helveticus, was shown to anchor the protein to the bacterial cell wall. The C-terminal CbsA peptide specifically bound to bacterial teichoic acid and lipoteichoic acids. In conclusion, the N-terminal domain of the S-layer protein of L. crispatus is important for polymerization and adhesion to host tissues, whereas the C-terminal domain anchors the protein to bacterial cell-wall teichoic acids. Lactobacilli are fermentative organisms that effectively lower the surrounding pH. While this study was in progress, plasminogen-binding proteins enolase and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were identified in the extracellular proteome of L. crispatus ST1. In this work, the cell-wall association of enolase and GAPDH were shown to rely on pH-reversible binding to the cell-wall lipoteichoic acids. Enolase from L. crispatus was functionally compared with enolase from L. johnsonii as well as from pathogenic streptococci (Streptococcus pneumoniae, Streptococcus pyogenes) and Staphylococcus aureus. His6-enolases from commensal lactobacilli bound human plasminogen and enhanced its activation by human plasminogen activators similarly to, or even better than, the enolases from pathogens. Similarly, the His6-enolases from lactobacilli exhibited adhesive characteristics previously assigned to pathogens. The results call for more detailed analyses of the role of the host plasminogen system in bacterial pathogenesis and commensalism as well of the biological role and potential health risk of the extracellular proteome in lactobacilli.

Photobiological studies of Baltic Sea phytoplankton

Phytoplankton ecology and productivity is one of the main branches of contemporary oceanographic research. Research groups in this branch have increasingly started to utilise bio-optical applications. My main research objective was to critically investigate the advantages and deficiencies of the fast repetition rate (FRR) fluorometry for studies of productivity of phytoplankton, and the responses of phytoplankton towards varying environmental stress. Second, I aimed to clarify the applicability of the FRR system to the optical environment of the Baltic Sea. The FRR system offers a highly dynamic tool for studies of phytoplankton photophysiology and productivity both in the field and in a controlled environment. The FRR metrics obtain high-frequency in situ determinations of the light-acclimative and photosynthetic parameters of intact phytoplankton communities. The measurement protocol is relatively easy to use without phases requiring analytical determinations. The most notable application of the FRR system lies in its potential for making primary productivity (PP) estimations. However, the realisation of this scheme is not straightforward. The FRR-PP, based on the photosynthetic electron flow (PEF) rate, are linearly related to the photosynthetic gas exchange (fixation of 14C) PP only in environments where the photosynthesis is light-limited. If the light limitation is not present, as is usually the case in the near-surface layers of the water column, the two PP approaches will deviate. The prompt response of the PEF rate to the short-term variability in the natural light field makes the field comparisons between the PEF-PP and the 14C-PP difficult to interpret, because this variability is averaged out in the 14C-incubations. Furthermore, the FRR based PP models are tuned to closely follow the vertical pattern of the underwater irradiance. Due to the photoacclimational plasticity of phytoplankton, this easily leads to overestimates of water column PP, if precautionary measures are not taken. Natural phytoplankton is subject to broad-waveband light. Active non-spectral bio-optical instruments, like the FRR fluorometer, emit light in a relatively narrow waveband, which by its nature does not represent the in situ light field. Thus, the spectrally-dependent parameters provided by the FRR system need to be spectrally scaled to the natural light field of the Baltic Sea. In general, the requirement of spectral scaling in the water bodies under terrestrial impact concerns all light-adaptive parameters provided by any active non-spectral bio-optical technique. The FRR system can be adopted to studies of all phytoplankton that possess efficient light harvesting in the waveband matching the bluish FRR excitation. Although these taxa cover the large bulk of all the phytoplankton taxa, one exception with a pronounced ecological significance is found in the Baltic Sea. The FRR system cannot be used to monitor the photophysiology of the cyanobacterial taxa harvesting light in the yellow-red waveband. These taxa include the ecologically-significant bloom-forming cyanobacterial taxa in the Baltic Sea.

Functional genes and gene array analysis as tools for monitoring hydrocarbon biodegradation

Bioremediation, which is the exploitation of the intrinsic ability of environmental microbes to degrade and remove harmful compounds from nature, is considered to be an environmentally sustainable and cost-effective means for environmental clean-up. However, a comprehensive understanding of the biodegradation potential of microbial communities and their response to decontamination measures is required for the effective management of bioremediation processes. In this thesis, the potential to use hydrocarbon-degradative genes as indicators of aerobic hydrocarbon biodegradation was investigated. Small-scale functional gene macro- and microarrays targeting aliphatic, monoaromatic and low molecular weight polyaromatic hydrocarbon biodegradation were developed in order to simultaneously monitor the biodegradation of mixtures of hydrocarbons. The validity of the array analysis in monitoring hydrocarbon biodegradation was evaluated in microcosm studies and field-scale bioremediation processes by comparing the hybridization signal intensities to hydrocarbon mineralization, real-time polymerase chain reaction (PCR), dot blot hybridization and both chemical and microbiological monitoring data. The results obtained by real-time PCR, dot blot hybridization and gene array analysis were in good agreement with hydrocarbon biodegradation in laboratory-scale microcosms. Mineralization of several hydrocarbons could be monitored simultaneously using gene array analysis. In the field-scale bioremediation processes, the detection and enumeration of hydrocarbon-degradative genes provided important additional information for process optimization and design. In creosote-contaminated groundwater, gene array analysis demonstrated that the aerobic biodegradation potential that was present at the site, but restrained under the oxygen-limited conditions, could be successfully stimulated with aeration and nutrient infiltration. During ex situ bioremediation of diesel oil- and lubrication oil-contaminated soil, the functional gene array analysis revealed inefficient hydrocarbon biodegradation, caused by poor aeration during composting. The functional gene array specifically detected upper and lower biodegradation pathways required for complete mineralization of hydrocarbons. Bacteria representing 1 % of the microbial community could be detected without prior PCR amplification. Molecular biological monitoring methods based on functional genes provide powerful tools for the development of more efficient remediation processes. The parallel detection of several functional genes using functional gene array analysis is an especially promising tool for monitoring the biodegradation of mixtures of hydrocarbons.

Comparative and functional genome analysis of fungi for development of the protein production host Trichoderma reesei

Filamentous fungi of the subphylum Pezizomycotina are well known as protein and secondary metabolite producers. Various industries take advantage of these capabilities. However, the molecular biology of yeasts, i.e. Saccharomycotina and especially that of Saccharomyces cerevisiae, the baker's yeast, is much better known. In an effort to explain fungal phenotypes through their genotypes we have compared protein coding gene contents of Pezizomycotina and Saccharomycotina. Only biomass degradation and secondary metabolism related protein families seem to have expanded recently in Pezizomycotina. Of the protein families clearly diverged between Pezizomycotina and Saccharomycotina, those related to mitochondrial functions emerge as the most prominent. However, the primary metabolism as described in S. cerevisiae is largely conserved in all fungi. Apart from the known secondary metabolism, Pezizomycotina have pathways that could link secondary metabolism to primary metabolism and a wealth of undescribed enzymes. Previous studies of individual Pezizomycotina genomes have shown that regardless of the difference in production efficiency and diversity of secreted proteins, the content of the known secretion machinery genes in Pezizomycotina and Saccharomycotina appears very similar. Genome wide analysis of gene products is therefore needed to better understand the efficient secretion of Pezizomycotina. We have developed methods applicable to transcriptome analysis of non-sequenced organisms. TRAC (Transcriptional profiling with the aid of affinity capture) has been previously developed at VTT for fast, focused transcription analysis. We introduce a version of TRAC that allows more powerful signal amplification and multiplexing. We also present computational optimisations of transcriptome analysis of non-sequenced organism and TRAC analysis in general. Trichoderma reesei is one of the most commonly used Pezizomycotina in the protein production industry. In order to understand its secretion system better and find clues for improvement of its industrial performance, we have analysed its transcriptomic response to protein secretion stress conditions. In comparison to S. cerevisiae, the response of T. reesei appears different, but still impacts on the same cellular functions. We also discovered in T. reesei interesting similarities to mammalian protein secretion stress response. Together these findings highlight targets for more detailed studies.

Efficient probabilistic contingency analysis through a stability measure considering wind perturbation

The integration of stochastic wind power has accentuated a challenge for power system stability assessment. Since the power system is a time-variant system under wind generation fluctuations, pure time-domain simulations are difficult to provide real-time stability assessment. As a result, the worst-case scenario is simulated to give a very conservative assessment of system transient stability. In this study, a probabilistic contingency analysis through a stability measure method is proposed to provide a less conservative contingency analysis which covers 5-min wind fluctuations and a successive fault. This probabilistic approach would estimate the transfer limit of a critical line for a given fault with stochastic wind generation and active control devices in a multi-machine system. This approach achieves a lower computation cost and improved accuracy using a new stability measure and polynomial interpolation, and is feasible for online contingency analysis.