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Bacterial Community Sequences of Submerged Aquatic Vegetation in the Potomac River.
Here, we report results from PCR and sequencing of bacterial 16S rRNA genes from leaf and root surfaces from nine submerged aquatic vegetation (SAV) samples comprising five species. Samples were from four sites along the Potomac River
Draft Genome Sequence of Curtobacterium flaccumfaciens Strain UCD-AKU (Phylum Actinobacteria).
Here we present the draft genome of an actinobacterium, Curtobacterium flaccumfaciens strain UCD-AKU, isolated from a residential carpet. The genome assembly contains 3,692,614 bp in 130 contigs. This is the first member of the Curtobacterium genus to be sequenced
Draft Genome Sequence of Dietzia sp. Strain UCD-THP (Phylum Actinobacteria).
Here, we present the draft genome sequence of an actinobacterium, Dietzia sp. strain UCD-THP, isolated from a residential toilet handle. The assembly contains 3,915,613 bp. The genome sequences of only two other Dietzia species have been published, those of Dietzia alimentaria and Dietzia cinnamea
Draft Genome Sequence of Kocuria sp. Strain UCD-OTCP (Phylum Actinobacteria).
Here, we present the draft genome of Kocuria sp. strain UCD-OTCP, a member of the phylum Actinobacteria, isolated from a restaurant chair cushion. The assembly contains 3,791,485 bp (G+C content of 73%) and is contained in 68 scaffolds
Characterization of shifts of koala (Phascolarctos cinereus) intestinal microbial communities associated with antibiotic treatment.
Koalas (Phascolarctos cinereus) are arboreal marsupials native to Australia that eat a specialized diet of almost exclusively eucalyptus leaves. Microbes in koala intestines are known to break down otherwise toxic compounds, such as tannins, in eucalyptus leaves. Infections by Chlamydia, obligate intracellular bacterial pathogens, are highly prevalent in koala populations. If animals with Chlamydia infections are received by wildlife hospitals, a range of antibiotics can be used to treat them. However, previous studies suggested that koalas can suffer adverse side effects during antibiotic treatment. This study aimed to use 16S rRNA gene sequences derived from koala feces to characterize the intestinal microbiome of koalas throughout antibiotic treatment and identify specific taxa associated with koala health after treatment. Although differences in the alpha diversity were observed in the intestinal flora between treated and untreated koalas and between koalas treated with different antibiotics, these differences were not statistically significant. The alpha diversity of microbial communities from koalas that lived through antibiotic treatment versus those who did not was significantly greater, however. Beta diversity analysis largely confirmed the latter observation, revealing that the overall communities were different between koalas on antibiotics that died versus those that survived or never received antibiotics. Using both machine learning and OTU (operational taxonomic unit) co-occurrence network analyses, we found that OTUs that are very closely related to Lonepinella koalarum, a known tannin degrader found by culture-based methods to be present in koala intestines, was correlated with a koala's health status. This is the first study to characterize the time course of effects of antibiotics on koala intestinal microbiomes. Our results suggest it may be useful to pursue alternative treatments for Chlamydia infections without the use of antibiotics or the development of Chlamydia-specific antimicrobial compounds that do not broadly affect microbial communities
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Dynamic multifactor hubs interact transiently with sites of active transcription in Drosophila embryos.
The regulation of transcription requires the coordination of numerous activities on DNA, yet how transcription factors mediate these activities remains poorly understood. Here, we use lattice light-sheet microscopy to integrate single-molecule and high-speed 4D imaging in developing Drosophila embryos to study the nuclear organization and interactions of the key transcription factors Zelda and Bicoid. In contrast to previous studies suggesting stable, cooperative binding, we show that both factors interact with DNA with surprisingly high off-rates. We find that both factors form dynamic subnuclear hubs, and that Bicoid binding is enriched within Zelda hubs. Remarkably, these hubs are both short lived and interact only transiently with sites of active Bicoid-dependent transcription. Based on our observations, we hypothesize that, beyond simply forming bridges between DNA and the transcription machinery, transcription factors can organize other proteins into hubs that transiently drive multiple activities at their gene targets.Editorial noteThis article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter)
Exposure-Lag-Response in Longitudinal Studies: Application of Distributed-Lag Nonlinear Models in an Occupational Cohort.
Prolonged exposures can have complex relationships with health outcomes, as timing, duration, and intensity of exposure are all potentially relevant. Summary measures such as cumulative exposure or average intensity of exposure may not fully capture these relationships. We applied penalized and unpenalized distributed-lag nonlinear models (DLNMs) with flexible exposure-response and lag-response functions in order to examine the association between crystalline silica exposure and mortality from lung cancer and nonmalignant respiratory disease in a cohort study of 2,342 California diatomaceous earth workers followed during 1942-2011. We also assessed associations using simple measures of cumulative exposure assuming linear exposure-response and constant lag-response. Measures of association from DLNMs were generally higher than those from simpler models. Rate ratios from penalized DLNMs corresponding to average daily exposures of 0.4 mg/m3 during lag years 31-50 prior to the age of observed cases were 1.47 (95% confidence interval (CI): 0.92, 2.35) for lung cancer mortality and 1.80 (95% CI: 1.14, 2.85) for nonmalignant respiratory disease mortality. Rate ratios from the simpler models for the same exposure scenario were 1.15 (95% CI: 0.89, 1.48) and 1.23 (95% CI: 1.03, 1.46), respectively. Longitudinal cohort studies of prolonged exposures and chronic health outcomes should explore methods allowing for flexibility and nonlinearities in the exposure-lag-response
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