Current strategies for mobilome research

Mobile genetic elements (MGE) are pivotal for bacterial evolution and adaptation, allowing shuffling of genes even between distantly related bacterial species. The study of MGEs is biologically interesting as the mode of genetic propagation is kaleidoscopic and important, as MGEs are the main vehicles of the increasing bacterial antibiotic resistance that causes thousands of human deaths each year. The study of MGEs has previously focused on plasmids from individual isolates, but the revolution in sequencing technology has allowed the study of mobile genomic elements of entire communities using metagenomic approaches. The problem in using metagenomic sequencing for the study of MGEs is that plasmids and other mobile elements only comprise a small fraction of the total genetic content that are difficult to separate from chromosomal DNA based on sequence alone. Several different approaches have been proposed that specifically enrich plasmid DNA from community samples. Here, we review recent approaches used to study entire plasmid pools from complex environments, and point out possible future developments for and pitfalls of these approaches. Further, we discuss the use of the PacBio long-read sequencing technology for MGE discovery

COL4A3 is degraded in allergic asthma and degradation predicts response to anti-IgE therapy.

BACKGROUND Asthma is a heterogeneous syndrome substantiating the urgent requirement for endotype-specific biomarkers. Dysbalance of fibrosis and fibrolysis in asthmatic lung tissue leads to reduced levels of the inflammation-protective collagen 4 (COL4A3). OBJECTIVE To delineate the degradation of COL4A3 in allergic airway inflammation and evaluate the resultant product as a biomarker for anti-IgE therapy response. METHODS The serological COL4A3 degradation marker C4Ma3 (Nordic Bioscience, Denmark) and serum cytokines were measured in the ALLIANCE cohort (pediatric cases/controls: 134/35; adult cases/controls: 149/31). Exacerbation of allergic airway disease in mice was induced by sensitising to OVA, challenge with OVA aerosol and instillation of poly(cytidylic-inosinic). Fulacimstat (chymase inhibitor, Bayer) was used to determine the role of mast cell chymase in COL4A3 degradation. Patients with cystic fibrosis (CF, n=14) and CF with allergic broncho-pulmonary aspergillosis (ABPA, n=9) as well as severe allergic, uncontrolled asthmatics (n=19) were tested for COL4A3 degradation. Omalizumab (anti-IgE) treatment was assessed by the Asthma Control Test. RESULTS Serum levels of C4Ma3 were increased in asthma in adults and children alike and linked to a more severe, exacerbating allergic asthma phenotype. In an experimental asthma mouse model, C4Ma3 was dependent on mast cell chymase. Serum C4Ma3 was significantly elevated in CF plus ABPA and at baseline predicted the success of the anti-IgE therapy in allergic, uncontrolled asthmatics (diagnostic odds ratio 31.5). CONCLUSION C4Ma3 level depend on lung mast cell chymase and are increased in a severe, exacerbating allergic asthma phenotype. C4Ma3 may serve as a novel biomarker to predict anti-IgE therapy response

Writing in Britain and Ireland, c. 400 to c. 800

No abstract available

Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community

<div><p>As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.</p></div

Core metabolic modules shared by grasslands, deserts, and forest soils.

<p>Core metabolic modules shared by grasslands, deserts, and forest soils.</p