Energy Gradients Structure Microbial Communities Across Sediment Horizons in Deep Marine Sediments of the South China Sea

The deep marine subsurface is a heterogeneous environment in which the assembly of microbial communities is thought to be controlled by a combination of organic matter deposition, electron acceptor availability, and sedimentology. However, the relative importance of these factors in structuring microbial communities in marine sediments remains unclear. The South China Sea (SCS) experiences significant variability in sedimentation across the basin and features discrete changes in sedimentology as a result of episodic deposition of turbidites and volcanic ashes within lithogenic clays and siliceous or calcareous ooze deposits throughout the basin\u27s history. Deep subsurface microbial communities were recently sampled by the International Ocean Discovery Program (IODP) at three locations in the SCS with sedimentation rates of 5, 12, and 20 cm per thousand years. Here, we used Illumina sequencing of the 16S ribosomal RNA gene to characterize deep subsurface microbial communities from distinct sediment types at these sites. Communities across all sites were dominated by several poorly characterized taxa implicated in organic matter degradation, including Atribacteria, Dehalococcoidia, and Aerophobetes. Sulfate-reducing bacteria comprised only 4% of the community across sulfate-bearing sediments from multiple cores and did not change in abundance in sediments from the methanogenic zone at the site with the lowest sedimentation rate. Microbial communities were significantly structured by sediment age and the availability of sulfate as an electron acceptor in pore waters. However, microbial communities demonstrated no partitioning based on the sediment type they inhabited. These results indicate that microbial communities in the SCS are structured by the availability of electron donors and acceptors rather than sedimentological characteristics

第885回千葉医学会例会・千葉大学第二外科例会

<p><b>A</b>. NMDS ordination of 16S rRNA gene-derived microbial community structure. Similarity profile analysis, an <i>a priori</i> statistical approach that uses permutation to identify groups of communities that are more dissimilar than expected by chance, identified two distinct clusters of communities. Ellipses represent the 95% confidence intervals around the centroid for each cluster (the spatial mean in NMDS space of the communities belonging to each cluster). Lines emanating from the centroids indicate to which cluster each community belongs. Bacterial families well-correlated with the ordination (r² > 0.40) are displayed; vector length is proportional to the Pearson correlation coefficient for each family and vector direction corresponds to the direction of increasing abundance relative to the ordinated communities. Legend indicates the dune from which each ordinated community originated. Final 2-dimensional stress of the ordination is 0.12. <b>B</b>. Linear discriminant analysis (LDA) of bacterial classes indicates that the two clusters of microbial communities identified by similarity profile analysis are driven by the disparity between a high abundance of <i>Gammaproteobacteria</i> in one set of communities and more diverse population in the other set of communities. Only classes with effect size > 2.0 are displayed. <b>C</b>. NMDS ordination is based only on samples for which environmental parameters were measured. Parameters with r² > 0.1 are displayed. Final 2-dimensional stress of the ordination is 0.07.</p

A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction

The developmental and physiological complexity of the auditory system is likely reflected in the underlying set of genes involved in auditory function. In humans, over 150 non-syndromic loci have been identified, and there are more than 400 human genetic syndromes with a hearing loss component. Over 100 non-syndromic hearing loss genes have been identified in mouse and human, but we remain ignorant of the full extent of the genetic landscape involved in auditory dysfunction. As part of the International Mouse Phenotyping Consortium, we undertook a hearing loss screen in a cohort of 3006 mouse knockout strains. In total, we identify 67 candidate hearing loss genes. We detect known hearing loss genes, but the vast majority, 52, of the candidate genes were novel. Our analysis reveals a large and unexplored genetic landscape involved with auditory function

Non-Visual Effects of Light on Melatonin, Alertness and Cognitive Performance: Can Blue-Enriched Light Keep Us Alert?

Light exposure can cascade numerous effects on the human circadian process via the non-imaging forming system, whose spectral relevance is highest in the short-wavelength range. Here we investigated if commercially available compact fluorescent lamps with different colour temperatures can impact on alertness and cognitive performance

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Different experimental approaches in modelling cataractogenesis: An overview of selenite-induced nuclear cataract in rats

Cataract, the opacification of eye lens, is the leading cause of blindness worldwide. At present, the only remedy is surgical removal of the cataractous lens and substitution with a lens made of synthetic polymers. However, besides significant costs of operation and possible complications, an artificial lens just does not have the overall optical qualities of a normal one. Hence it remains a significant public health problem, and biochemical solutions or pharmacological interventions that will maintain the transparency of the lens are highly required. Naturally, there is a persistent demand for suitable biological models. The ocular lens would appear to be an ideal organ for maintaining culture conditions because of lacking blood vessels and nerves. The lens in vivo obtains its nutrients and eliminates waste products via diffusion with the surrounding fluids. Lens opacification observed in vivo can be mimicked in vitro by addition of the cataractogenic agent sodium selenite (Na2SeO3) to the culture medium. Moreover, since an overdose of sodium selenite induces also cataract in young rats, it became an extremely rapid and convenient model of nuclear cataract in vivo. The main focus of this review will be on selenium (Se) and its salt sodium selenite, their toxicological characteristics and safety data in relevance of modelling cataractogenesis, either under in vivo or in vitro conditions. The studies revealing the mechanisms of lens opacification induced by selenite are highlighted, the representatives from screening for potential anti-cataract agents are listed

The Identification of Cable Bacteria Attached to the Anode of a Benthic Microbial Fuel Cell: Evidence of Long Distance Extracellular Electron Transport to Electrodes

Multicellular, filamentous, sulfur-oxidizing bacteria, known as cable bacteria, were discovered attached to fibers of a carbon brush electrode serving as an anode of a benthic microbial fuel cell (BMFC). The BMFC had been operated in a temperate estuarine environment for over a year before collecting anode samples for scanning electron microscopy and phylogenetic analyses. Individual filaments were attached by single terminus cells with networks of pilus-like nano-filaments radiating out from these cells, across the anode fiber surface, and between adjacent attachment locations. Current harvesting by the BMFC poised the anode at potentials of ~170–250 mV vs. SHE, and these surface potentials appear to have allowed the cable bacteria to use the anode as an electron acceptor in a completely anaerobic environment. A combination of catalyzed reporter deposition fluorescent in situ hybridization (CARD-FISH) and 16S rRNA gene sequence analysis confirmed the phylogeny of the cable bacteria and showed that filaments often occurred in bundles and in close association with members of the genera Desulfuromonas. However, the Desulfobulbaceae Operational Taxonomic Units (OTUs) from the 16S sequencing did not cluster closely with other putative cable bacteria sequences suggesting that the taxonomic delineation of cable bacteria is far from complete

Energy Gradients Structure Microbial Communities Across Sediment Horizons in Deep Marine Sediments of the South China Sea

The deep marine subsurface is a heterogeneous environment in which the assembly of microbial communities is thought to be controlled by a combination of organic matter deposition, electron acceptor availability, and sedimentology. However, the relative importance of these factors in structuring microbial communities in marine sediments remains unclear. The South China Sea (SCS) experiences significant variability in sedimentation across the basin and features discrete changes in sedimentology as a result of episodic deposition of turbidites and volcanic ashes within lithogenic clays and siliceous or calcareous ooze deposits throughout the basin's history. Deep subsurface microbial communities were recently sampled by the International Ocean Discovery Program (IODP) at three locations in the SCS with sedimentation rates of 5, 12, and 20 cm per thousand years. Here, we used Illumina sequencing of the 16S ribosomal RNA gene to characterize deep subsurface microbial communities from distinct sediment types at these sites. Communities across all sites were dominated by several poorly characterized taxa implicated in organic matter degradation, including Atribacteria, Dehalococcoidia, and Aerophobetes. Sulfate-reducing bacteria comprised only 4% of the community across sulfate-bearing sediments from multiple cores and did not change in abundance in sediments from the methanogenic zone at the site with the lowest sedimentation rate. Microbial communities were significantly structured by sediment age and the availability of sulfate as an electron acceptor in pore waters. However, microbial communities demonstrated no partitioning based on the sediment type they inhabited. These results indicate that microbial communities in the SCS are structured by the availability of electron donors and acceptors rather than sedimentological characteristics