Innate Immune Recognition of RNA-virus infection in human macrophages

Innate immunity and host defence are rapidly evoked by structurally invariant molecular motifs common to microbial world, called pathogen associated molecular patterns (PAMPs). In addition to PAMPs, endogenous molecules released in response to inflammation and tissue damage, danger associated molecular patterns (DAMPs), are required for eliciting the response. The most important PAMPs of viruses are viral nucleic acids, their genome or its replication intermediates, whereas the identity and characteristics of virus infection-induced DAMPs are poorly defined. PAMPs and DAMPs engage a limited set of germ-line encoded pattern recognition receptors (PRRs) in immune and non-immune cells. Membrane-bound Toll-like receptors (TLRs), cytoplasmic retinoic acid inducible gene-I (RIG-I)-like receptors (RLRs) and nucleotide-binding oligomerization domain-like receptor (NLRs) are important PRRs involved in the recognition of the molecular signatures of viral infection, such as double-stranded ribonucleic acids (dsRNAs). Engagement of PRRs results in local and systemic innate immune responses which, when activated against viruses, evoke secretion of antiviral and pro-inflammatory cytokines, and programmed cell death i.e., apoptosis of the virus-infected cell. Macrophages are the central effector cells of innate immunity. They produce significant amounts of antiviral cytokines, called interferons (IFNs), and pro-inflammatory cytokines, such as interleukin (IL)-1β and IL-18. IL-1β and IL-18 are synthesized as inactive precursors, pro-IL-1β and pro-IL-18, that are processed by caspase-1 in a cytoplasmic multiprotein complex, called the inflammasome. After processing, these cytokines are biologically active and will be secreted. The signals and secretory routes that activate inflammasomes and the secretion of IL-1β and IL-18 during virus infections are poorly characterized. The main goal of this thesis was to characterize influenza A virus-induced innate immune responses and host-virus interactions in human primary macrophages during an infection. Methodologically, various techniques of cellular and molecular biology, as well as proteomic tools combined with bioinformatics, were utilized. Overall, the thesis provides interesting insights into inflammatory and antiviral innate immune responses, and has characterized host-virus interactions during influenza A virus-infection in human primary macrophages.

Sikainfluenssan epidemiologia Suomen näkökulmasta

Kirjallisuuskatsauksen aihe on ajankohtainen Suomessa ja muualla maailmassa. Sikainfluenssa on sikojen tarttuva hengitystiesairaus, jonka aiheuttaja on herkästi kärsäkontaktissa leviävä influenssa A – virus. Siat sairastuvat usein yllättäen ja samanaikaisesti. Sikainfluenssa voi olla oireeton tai vähäoireinen, mikä hankaloittaa taudin havaitsemista. Sikainfluenssa aiheuttaa sikatiloille tuotantotappioita ja sioille hyvinvointiongelmia. Sikainfluenssa on maailmalla yleinen sikojen hengitystiesairaus. Suomi oli sikainfluenssasta vapaa maa vuoteen 2007 saakka ja vuonna 2009 noin kolmasosa suomalaisista sikaloista oli seropositiivisia sikainfluenssan suhteen. Influenssa A – viruksia esiintyy yleisesti eläimillä ja ihmisillä. Influenssa A – virusten kantajia luonnossa ovat vesilinnut, jotka levittävät influenssaviruksia ulosteissaan. Influenssa A – virukset pystyvät muuntumaan uusiksi alatyypeiksi ja sikaa pidetään eläinlajina, jossa influenssa A – virukset muuntuvat lajista toiseen tarttuviksi. Sikainfluenssa on zoonoosi. Sikainfluenssaviruksia on useita eri alatyyppejä. Maailmalla esiintyvien sikainfluenssavirusten alkuperä ja ominaisuudet vaihtelevat maantieteellisen sijainnin mukaan. Euroopassa, Pohjois-Amerikassa ja Aasiassa nykyään esiintyvät sikainfluenssavirukset ovat kehittyessään eriytyneet geneettisesti ja antigeenisesti toisistaan. Sikapopulaatioissa kiertää yleensä useita eri sikainfluenssavirustyyppejä yhtä aikaa. Tärkeimpiä ja useimmiten eristettyjä sikainfluenssavirusten alatyyppejä ovat H1N1, H1N2 ja H3N2. Sikainfluenssan diagnosointi on tärkeää, jotta virusten leviämistä voidaan ehkäistä ja tautitilanne pysyy ajantasaisena. Sikainfluenssa diagnosoidaan osoittamalla sikainfluenssavirus 1-3 vuorokautta kliinisten oireiden alkamisen jälkeen otetuista virusnäytteistä tai virusvasta-aineet serologisin testein pariseeruminäytteistä. Viruksen osoitusmenetelmät (viruseristys ja RT-PCR) ovat luotettavia ja niillä sikainfluenssavirukset voidaan tyypittää. Serologisten testien (hemagglutinaation inhibitio ja ELISA) luotettavuudessa on puutteita ja etenkin ELISA-testien luotettavuus perustuu tietoon sikapopulaatiossa liikkuvien sikainfluenssavirusten alatyypeistä. Sikainfluenssan jatkuva ja tehokas tautiseuranta on oleellista, jotta serologiset testit saadaan optimoitua. Alueellisesti sikainfluenssan esiintyvyyttä lisäävät suuri sikatiheys, tilojen lyhyet välimatkat, eläinkuljetukset sekä sikojen kontaktit ulkopuolisiin henkilöihin ja tavaroihin. Sikalan bioturvallisuus on tärkein tekijä estettäessä sikainfluenssavirusten pääsy sikalaan. Sikainfluenssan vastustaminen on tärkeää, koska se on osa sikojen hengitystiesairauskompleksia sekä predisponoiva tekijä muiden sikapatogeenien aiheuttamille hengitystiesairauksille. Sikainfluenssan vastustuksessa voidaan suurilla sikatiloilla käyttää apuna kahta tai kolmea virustyyppiä sisältäviä rokotteita, jotka vähentävät sikainfluenssan kliinisiä oireita ja viruksen eritystä ympäristöön.

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Geographic Variation of Notified Ross River Virus Infections in Queensland, Australia, 1985-1996

The spatial and temporal variations of Ross River virus infections reported in Queensland, Australia, between 1985 and 1996 were studied by using the Geographic Information System. The notified cases of Ross River virus infection came from 489 localities between 1985 and 1988, 805 between 1989 and 1992, and 1,157 between 1993 and 1996 (chi2(df = 2) = 680.9; P < 0.001). There was a marked increase in the number of localities where the cases were reported by 65 percent for the period of 1989-1992 and 137 percent for 1993-1996, compared with that for 1985-1988. The geographic distribution of the notified Ross River virus cases has expanded in Queensland over recent years. As Ross River virus disease has impacted considerably on tourism and industry, as well as on residents of affected areas, more research is required to explore the causes of the geographic expansion of the notified Ross River virus infections.

Experimental Infection of Culex Annulirostris, Culex Gelidus, and Aedes Vigilax With a Yellow Fever/Japanese Encephalitis Virus Vaccine Chimera (Chimerivax TM-JE)

Australian mosquitoes from which Japanese encephalitis virus (JEV) has been recovered (Culex annulirostris, Culex gelidus, and Aedes vigilax) were assessed for their ability to be infected with the ChimeriVax-JE vaccine, with yellow fever vaccine virus 17D (YF 17D) from which the backbone of ChimeriVax-JE vaccine is derived and with JEV-Nakayama. None of the mosquitoes became infected after being fed orally with 6.1 log(10) plaque-forming units (PFU)/mL of ChimeriVax-JE vaccine, which is greater than the peak viremia in vaccinees (mean peak viremia = 4.8 PFU/mL, range = 0-30 PFU/mL of 0.9 days mean duration, range = 0-11 days). Some members of all three species of mosquito became infected when fed on JEV-Nakayama, but only Ae. vigilax was infected when fed on YF 17D. The results suggest that none of these three species of mosquito are likely to set up secondary cycles of transmission of ChimeriVax-JE in Australia after feeding on a viremic vaccinee.

Exploratory spatial analysis of social and environmental factors associated with the incidence of Ross River Virus in Brisbane, Australia

We used geographic information systems and a spatial analysis approach to explore the pattern of Ross River virus (RRV) incidence in Brisbane, Australia. Climate, vegetation and socioeconomic data in 2001 were obtained from the Australian Bureau of Meteorology, the Brisbane City Council and the Australian Bureau of Statistics, respectively. Information on the RRV cases was obtained from the Queensland Department of Health. Spatial and multiple negative binomial regression models were used to identify the socioeconomic and environmental determinants of RRV transmission. The results show that RRV activity was primarily concentrated in the northeastern, northwestern, and southeastern regions in Brisbane. Multiple negative binomial regression models showed that the spatial pattern of RRV disease in Brisbane seemed to be determined by a combination of local ecologic, socioeconomic, and environmental factors.