Simultaneous transcriptional profiling of bacteria and their host cells

We developed an RNA-Seq-based method to simultaneously capture prokaryotic and eukaryotic expression profiles of cells infected with intracellular bacteria. As proof of principle, this method was applied to Chlamydia trachomatis-infected epithelial cell monolayers in vitro, successfully obtaining transcriptomes of both C. trachomatis and the host cells at 1 and 24 hours post-infection. Chlamydiae are obligate intracellular bacterial pathogens that cause a range of mammalian diseases. In humans chlamydiae are responsible for the most common sexually transmitted bacterial infections and trachoma (infectious blindness). Disease arises by adverse host inflammatory reactions that induce tissue damage & scarring. However, little is known about the mechanisms underlying these outcomes. Chlamydia are genetically intractable as replication outside of the host cell is not yet possible and there are no practical tools for routine genetic manipulation, making genome-scale approaches critical. The early timeframe of infection is poorly understood and the host transcriptional response to chlamydial infection is not well defined. Our simultaneous RNA-Seq method was applied to a simplified in vitro model of chlamydial infection. We discovered a possible chlamydial strategy for early iron acquisition, putative immune dampening effects of chlamydial infection on the host cell, and present a hypothesis for Chlamydia-induced fibrotic scarring through runaway positive feedback loops. In general, simultaneous RNA-Seq helps to reveal the complex interplay between invading bacterial pathogens and their host mammalian cells and is immediately applicable to any bacteria/host cell interaction. © 2013 Humphrys et al

Bestimmung der Groessenverteilung von Asbestfasern und Asbestpartikeln in der Abluft von Filteranlagen Teilvorhaben C

TIB: RN 8908 (85-031,3) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Comparative genomic analysis of human Chlamydia pneumoniae isolates from respiratory, brain and cardiac tissues

© 2015 Elsevier Inc. Chlamydia pneumoniae is an obligate intracellular bacterium implicated in a wide range of human diseases including atherosclerosis and Alzheimer's disease. Efforts to understand the relationships between C. pneumoniae detected in these diseases have been hindered by the availability of sequence data for non-respiratory strains. In this study, we sequenced the whole genomes for C. pneumoniae isolates from atherosclerosis and Alzheimer's disease, and compared these to previously published C. pneumoniae genomes. Phylogenetic analyses of these new C. pneumoniae strains indicate two sub-groups within human C. pneumoniae, and suggest that both recombination and mutation events have driven the evolution of human C. pneumoniae. Further fine-detailed analyses of these new C. pneumoniae sequences show several genetically variable loci. This suggests that similar strains of C. pneumoniae are found in the brain, lungs and cardiovascular system and that only minor genetic differences may contribute to the adaptation of particular strains in human disease

Empirical model for the assessment of climate change impacts on spatial pattern of water availability in Nigeria

Rising temperatures and changing rainfall patterns due to global warming would affect sustainability in water resources in many regions. This change would impact several sectors, particularly the agricultural and water resources. The major objective of the present study is to model the impacts of climate change on spatial variability in water sustainability of Nigeria. Gauge based gridded rainfall data of global precipitation climatology centre (GPCC) and temperature data of climate research unit (CRU) for the period 1901–2010 and total water storage (TWS) anomaly data of Gravity Recovery and Climate Experiment (GRACE) for the period 2002–2016 were used for this purpose. The concept of reliability-resiliency-vulnerability was used for the assessment of sustainability in water resources. Machine learning models were used for the development of empirical models for the simulation of TWS from GPCC rainfall and CRU temperature. Finally, the multi-model ensemble mean projections of rainfall and temperature of four GCMs namely MRI-CGCM3, HadGEM2-ES, CSIRO-Mk3-6-0 and CESM1-CAM5 were used in the model for the assessment of climate change impact on water sustainability. The results revealed the declination of TWS in Nigeria up to -12 m during the rainy periods in some parts. Spatial assessment of the changes in TWS for the future shows the northeast, southeast and south-south parts would mostly experience decreases in TWS. Water sustainability will be low in these areas and some other parts of the country for the future