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"Johnson, S"
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Metagenomics: a path to understanding the gut microbiome
The gut microbiome is a major determinant of host health, yet it is only in the last 2 decades that the advent of next-generation sequencing has enabled it to be studied at a genomic level. Shotgun sequencing is beginning to provide insight into the prokaryotic as well as eukaryotic and viral components of the gut community, revealing not just their taxonomy, but also the functions encoded by their collective metagenome. This revolution in understanding is being driven by continued development of sequencing technologies and in consequence necessitates reciprocal development of computational approaches that can adapt to the evolving nature of sequence datasets. In this review, we provide an overview of current bioinformatic strategies for handling metagenomic sequence data and discuss their strengths and limitations. We then go on to discuss key technological developments that have the potential to once again revolutionise the way we are able to view and hence understand the microbiome.
Journal Article
Epistasis and evolution: recent advances and an outlook for prediction
As organisms evolve, the effects of mutations change as a result of epistatic interactions with other mutations accumulated along the line of descent. This can lead to shifts in adaptability or robustness that ultimately shape subsequent evolution. Here, we review recent advances in measuring, modeling, and predicting epistasis along evolutionary trajectories, both in microbial cells and single proteins. We focus on simple patterns of global epistasis that emerge in this data, in which the effects of mutations can be predicted by a small number of variables. The emergence of these patterns offers promise for efforts to model epistasis and predict evolution.
Journal Article
Constraint on net primary productivity of the global ocean by Argo oxygen measurements
The biological transformation of dissolved inorganic carbon to organic carbon during photosynthesis in the ocean, marine primary production, is a fundamental driver of biogeochemical cycling, ocean health and Earth’s climate system. The organic matter created supports oceanic food webs, including fisheries, and is an essential control on atmospheric carbon dioxide levels. Marine primary productivity is sensitive to changes due to climate forcing, but observing the response at the global scale remains a major challenge. Sparsely distributed productivity measurements are made using samples collected and analysed on research vessels. However, there are never enough ships and scientists to enable direct observations at the global scale with seasonal to annual resolution. Today, global ocean productivity is estimated using remote-sensing ocean-colour observations or general circulation models with coupled biological models that are calibrated with the sparse shipboard measurements. Here we demonstrate the measurement of gross oxygen production by photosynthesis using the diel cycle of oxygen concentration detected with the array of Biogeochemical-Argo profiling floats. The global ocean net primary productivity computed from this data is 53 Pg C y
−1
, which will be an important constraint on satellite and general circulation model-based estimates of the ocean productivity.
Argo measurements provide a constrained estimate of net primary productivity of the global ocean of 53 Pg C y
–1
, according to a global analysis of diel oxygen variations.
Journal Article
Stage at diagnosis and early mortality from cancer in England
Background:
Stage at diagnosis is a key predictor of overall cancer outcome. For the first time, stage completeness is high enough for robust analysis for the whole of England.
Methods:
We analysed data from the National Cancer Registration Service’s (NCRS) Cancer Analysis System on persons diagnosed with breast, colorectal, lung, prostate or ovarian cancers in England in 2012. One-year relative survival (followed-up to the end of 2013) was calculated along with adjusted excess rate ratios, for mortality within 1 year.
Results:
One-year relative survival decreased with increasing stage at diagnosis. For breast, prostate and colorectal cancers survival showed a major reduction for stage 4 cancers, whereas for lung and ovarian cancers there were substantial decreases in relative survival for each level of increase in stage. Excess rate ratios for mortality within 1 year of diagnosis showed that stage and age were the most important cofactors, but they also identified the statistically significant effects of sex, income deprivation and geographic area of residence.
Conclusions:
Further reductions in mortality may be most effectively achieved by diagnosing all cancers before they progress to stage 4, but for lung and ovarian cancers there is also a need for a stage shift to earlier stages together with efforts to improve stage-specific survival at all stages.
Journal Article
Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis
The 16S rRNA gene has been a mainstay of sequence-based bacterial analysis for decades. However, high-throughput sequencing of the full gene has only recently become a realistic prospect. Here, we use in silico and sequence-based experiments to critically re-evaluate the potential of the 16S gene to provide taxonomic resolution at species and strain level. We demonstrate that targeting of 16S variable regions with short-read sequencing platforms cannot achieve the taxonomic resolution afforded by sequencing the entire (~1500 bp) gene. We further demonstrate that full-length sequencing platforms are sufficiently accurate to resolve subtle nucleotide substitutions (but not insertions/deletions) that exist between intragenomic copies of the 16S gene. In consequence, we argue that modern analysis approaches must necessarily account for intragenomic variation between 16S gene copies. In particular, we demonstrate that appropriate treatment of full-length 16S intragenomic copy variants has the potential to provide taxonomic resolution of bacterial communities at species and strain level.
Here, the authors explore the potential of the 16S gene for discriminating bacterial taxa and show that full-length sequencing combined with appropriate clustering of intragenomic sequence variation can provide accurate representation of bacterial species in microbiome datasets.
Journal Article