Spatial heterodyne observations of water (SHOW) from a high-altitude airplane: characterization, performance, and first results

The Spatial Heterodyne Observations of Water instrument (SHOW) is a limb-sounding satellite prototype that utilizes the Spatial Heterodyne Spectroscopy (SHS) technique, operating in a limb-viewing configuration, to observe limb-scattered sunlight in a vibrational band of water vapour within a spectral window from 1363 to 1366&thinsp;nm. The goal is to retrieve high vertical and horizontal resolution measurements of water vapour in the upper troposphere and lower stratosphere. The prototype instrument has been configured for observations from NASA's ER-2 high-altitude airborne remote science airplane. Flying at a maximum altitude of ∼21.34&thinsp;km with a maximum speed of ∼760&thinsp;km&thinsp;h−1, the ER-2 provides a stable platform to simulate observations from a low-earth orbit satellite. Demonstration flights were performed from the ER-2 during an observation campaign from 15 to 22 July 2017. In this paper, we present the laboratory characterization work and the level 0 to level 1 processing of flight data that were obtained during an engineering flight performed on 18 July 2017. Water vapour profile retrievals are presented and compared to in situ radiosonde measurements made of the same approximate column of air. These measurements are used to validate the SHOW measurement concept and examine the sensitivity of the technique.</p

Extending colonic mucosal microbiome analysis - Assessment of colonic lavage as a proxy for endoscopic colonic biopsies

This study was supported through GI Research funds and MRC Grant Ref: MR/M00533X/1 to GH.Peer reviewedPublisher PD

Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomes

Pseudomonas is a metabolically-diverse genus of bacteria known for its flexibility and leading free living to pathogenic lifestyles in a wide range of hosts. The Pseudomonas Genome Database (http://www.pseudomonas.com) integrates completely-sequenced Pseudomonas genome sequences and their annotations with genome-scale, high-precision computational predictions and manually curated annotation updates. The latest release implements an ability to view sequence polymorphisms in P. aeruginosa PAO1 versus other reference strains, incomplete genomes and single gene sequences. This aids analysis of phenotypic variation between closely related isolates and strains, as well as wider population genomics and evolutionary studies. The wide range of tools for comparing Pseudomonas annotations and sequences now includes a strain-specific access point for viewing high precision computational predictions including updated, more accurate, protein subcellular localization and genomic island predictions. Views link to genome-scale experimental data as well as comparative genomics analyses that incorporate robust genera-geared methods for predicting and clustering orthologs. These analyses can be exploited for identifying putative essential and core Pseudomonas genes or identifying large-scale evolutionary events. The Pseudomonas Genome Database aims to provide a continually updated, high quality source of genome annotations, specifically tailored for Pseudomonas researchers, but using an approach that may be implemented for other genera-level research communities

Satellite remote sensing data can be used to model marine microbial metabolite turnover

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10−6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology

The evolutionary signal in metagenome phyletic profiles predicts many gene functions

Background. The function of many genes is still not known even in model organisms. An increasing availability of microbiome DNA sequencing data provides an opportunity to infer gene function in a systematic manner. Results. We evaluated if the evolutionary signal contained in metagenome phyletic profiles (MPP) is predictive of a broad array of gene functions. The MPPs are an encoding of environmental DNA sequencing data that consists of relative abundances of gene families across metagenomes. We find that such MPPs can accurately predict 826 Gene Ontology functional categories, while drawing on human gut microbiomes, ocean metagenomes, and DNA sequences from various other engineered and natural environments. Overall, in this task, the MPPs are highly accurate, and moreover they provide coverage for a set of Gene Ontology terms largely complementary to standard phylogenetic profiles, derived from fully sequenced genomes. We also find that metagenomes approximated from taxon relative abundance obtained via 16S rRNA gene sequencing may provide surprisingly useful predictive models. Crucially, the MPPs derived from different types of environments can infer distinct, non-overlapping sets of gene functions and therefore complement each other. Consistently, simulations on &gt; 5000 metagenomes indicate that the amount of data is not in itself critical for maximizing predictive accuracy, while the diversity of sampled environments appears to be the critical factor for obtaining robust models. Conclusions. In past work, metagenomics has provided invaluable insight into ecology of various habitats, into diversity of microbial life and also into human health and disease mechanisms. We propose that environmental DNA sequencing additionally constitutes a useful tool to predict biological roles of genes, yielding inferences out of reach for existing comparative genomics approaches

Sequence of the hyperplastic genome of the naturally competent Thermus scotoductus SA-01

<p>Abstract</p> <p>Background</p> <p>Many strains of <it>Thermus </it>have been isolated from hot environments around the world. <it>Thermus scotoductus </it>SA-01 was isolated from fissure water collected 3.2 km below surface in a South African gold mine. The isolate is capable of dissimilatory iron reduction, growth with oxygen and nitrate as terminal electron acceptors and the ability to reduce a variety of metal ions, including gold, chromate and uranium, was demonstrated. The genomes from two different <it>Thermus thermophilus </it>strains have been completed. This paper represents the completed genome from a second <it>Thermus </it>species - <it>T. scotoductus</it>.</p> <p>Results</p> <p>The genome of <it>Thermus scotoductus </it>SA-01 consists of a chromosome of 2,346,803 bp and a small plasmid which, together are about 11% larger than the <it>Thermus thermophilus </it>genomes. The <it>T. thermophilus </it>megaplasmid genes are part of the <it>T. scotoductus </it>chromosome and extensive rearrangement, deletion of nonessential genes and acquisition of gene islands have occurred, leading to a loss of synteny between the chromosomes of <it>T. scotoductus and T. thermophilus</it>. At least nine large inserts of which seven were identified as alien, were found, the most remarkable being a denitrification cluster and two operons relating to the metabolism of phenolics which appear to have been acquired from <it>Meiothermus ruber</it>. The majority of acquired genes are from closely related species of the Deinococcus-Thermus group, and many of the remaining genes are from microorganisms with a thermophilic or hyperthermophilic lifestyle. The natural competence of <it>Thermus scotoductus </it>was confirmed experimentally as expected as most of the proteins of the natural transformation system of <it>Thermus thermophilus </it>are present. Analysis of the metabolic capabilities revealed an extensive energy metabolism with many aerobic and anaerobic respiratory options. An abundance of sensor histidine kinases, response regulators and transporters for a wide variety of compounds are indicative of an oligotrophic lifestyle.</p> <p>Conclusions</p> <p>The genome of <it>Thermus scotoductus </it>SA-01 shows remarkable plasticity with the loss, acquisition and rearrangement of large portions of its genome compared to <it>Thermus thermophilus</it>. Its ability to naturally take up foreign DNA has helped it adapt rapidly to a subsurface lifestyle in the presence of a dense and diverse population which acted as source of nutrients. The genome of <it>Thermus scotoductus </it>illustrates how rapid adaptation can be achieved by a highly dynamic and plastic genome.</p

High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria

Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of “alien” elements which probably undergo special temporal–spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these “exotic” regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for “alien” regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions