Browsing by Author "Alvesalo, Joni"

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  • Alvesalo, Joni (Helsingin yliopisto, 2007)
    Chlamydia pneumoniae is a common obligate intracellular bacterium that causes upper and lower respiratory infections worldwide. C. pneumoniae infections are persistence by nature, and an acute infection sometimes turn into chronic. The treatment of acute infections can be problematic. High doses and prolonged treatment with currently used antibiotics are often needed in order to achieve a clinical cure. In addition, more serious diseases such as atherosclerosis have recently been associated with chronic C. pneumoniae infection, which has proven to be extremely difficult to diagnose and impossible to treat with current antibiotics. In the present study, new antichlamydial compounds were searched among synthetic, natural and natural-derived compounds. A library of structurally diverse natural compounds, which were known to have a variety of health promoting effect in humans, was tested against C. pneumoniae. A library of synthetic compounds was pre screened in silico, in order to create smaller and more active targeted library, which was tested against C. pneumoniae. Antichlamydial compounds were found from both libraries, nature based compounds showing higher activity. A new high-throughput screening (HTS) assay was developed in order to search antichlamydial compound more efficiently. After optimizations of this partly automated time-resolved fluorometric immunoassay (TR-FIA) we were able to obtain results that were reliable, reproducible and consistent with mostly used assays in chlamydia susceptibility testing. Host cell response to acute C. pneumoniae infection was monitored in a gene and protein level. We were able to find four different human proteins with a significant difference in their expression, caused by the C. pneumoniae infection. All of these identified proteins were structural proteins, which supports earlier observations about the structural rearrangement that are requirement for a successful infection. In the genome level we were able to identify hundreds of genes that were significantly affected by the infection. In order to get more information out of the microarray data we used gene ontology (GO) classification, which group genes according to biological processes, cellular components and molecular functions. One set of potential drug target genes, was selected using GO classification data and another set of was selected using gene-wise analysis data, where data from the infected cells is compared against the control cell data. Expression changes of all target genes were confirmed with q-PCR, validated genes were silenced with the corresponding small interfering RNA (siRNA) molecule and the effect of silencing to C. pneumoniae infection was monitored. The greatest reduction in the number of C. pneumoniae inclusions was due to the silencing of the gene coding for the transcription factor EGR1, which decreased the number of inclusions by 38.6 %. Both data analysis methods revealed genes whose silencing reduced the number of C. pneumoniae particles more than 25 %, but GO-classified data proved to be more accurate and much more informative, compared to gene-wise analysis data.