Seawater metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA777059 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR16700200_1.fastq.gz | Fastqsanger.gz | |||
| SRR16700200_2.fastq.gz | Fastqsanger.gz | |||
| SRR16700201_1.fastq.gz | Fastqsanger.gz | |||
| SRR16700201_2.fastq.gz | Fastqsanger.gz | |||
| SRR16700202_1.fastq.gz | Fastqsanger.gz |
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Experimental data description:
- 12 h restoration (corresponding to EDFig2 b, EDFig5 b,c,h), E14 mESCs, labelled samples and followed for 12h, total DNA and stranded, 4 biological replicates (rep1, rep2, rep3 and rep4) and 2 technical replicates (_1, _2).
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Project description:The variety of metagenomes in current databases provides a rapidly growing source of information for comparative studies. However, the quantity and quality of supplementary metadata is still lagging behind. It is therefore important to be able to identify related metagenomes by means of the available sequence data alone. We have studied efficient sequence-based methods for large-scale identification of similar metagenomes within a database retrieval context. In a broad comparison of different profiling methods we found that vector-based distance measures are well-suitable for the detection of metagenomic neighbors. Our evaluation on more than 1700 publicly available metagenomes indicates that for a query metagenome from a particular habitat on average nine out of ten nearest neighbors represent the same habitat category independent of the utilized profiling method or distance measure. While for well-defined labels a neighborhood accuracy of 100% can be achieved, in general the neighbor detection is severely affected by a natural overlap of manually annotated categories. In addition, we present results of a novel visualization method that is able to reflect the similarity of metagenomes in a 2D scatter plot. The visualization method shows a similarly high accuracy in the reduced space as compared with the high-dimensional profile space. Our study suggests that for inspection of metagenome neighborhoods the profiling methods and distance measures can be chosen to provide a convenient interpretation of results in terms of the underlying features. Furthermore, supplementary metadata of metagenome samples in the future needs to comply with readily available ontologies for fine-grained and standardized annotation. To make profile-based k-nearest-neighbor search and the 2D-visualization of the metagenome universe available to the research community, we included the proposed methods in our CoMet-Universe server for comparative metagenome analysis.
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Project description:In the collective genomes (the metagenome) of the microorganisms inhabiting the Earth's diverse environments is written the history of life on this planet. New molecular tools developed and used for the past 15 years by microbial ecologists are facilitating the extraction, cloning, screening, and sequencing of these genomes. This approach allows microbial ecologists to access and study the full range of microbial diversity, regardless of our ability to culture organisms, and provides an unprecedented access to the breadth of natural products that these genomes encode. However, there is no way that the mere collection of sequences, no matter how expansive, can provide full coverage of the complex world of microbial metagenomes within the foreseeable future. Furthermore, although it is possible to fish out highly informative and useful genes from the sea of gene diversity in the environment, this can be a highly tedious and inefficient procedure. Microbial ecologists must be clever in their pursuit of ecologically relevant, valuable, and niche-defining genomic information within the vast haystack of microbial diversity. In this report, we seek to describe advances and prospects that will help microbial ecologists glean more knowledge from investigations into metagenomes. These include technological advances in sequencing and cloning methodologies, as well as improvements in annotation and comparative sequence analysis. More significant, however, will be ways to focus in on various subsets of the metagenome that may be of particular relevance, either by limiting the target community under study or improving the focus or speed of screening procedures. Lastly, given the cost and infrastructure necessary for large metagenome projects, and the almost inexhaustible amount of data they can produce, trends toward broader use of metagenome data across the research community coupled with the needed investment in bioinformatics infrastructure devoted to metagenomics will no doubt further increase the value of metagenomic studies in various environments.
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Project description:Microbes are increasingly being implicated in autoimmune disease. This calls for a re-evaluation of how these chronic inflammatory illnesses are routinely treated. The standard of care for autoimmune disease remains the use of medications that slow the immune response, while treatments aimed at eradicating microbes seek the exact opposite-stimulation of the innate immune response. Immunostimulation is complicated by a cascade of sequelae, including exacerbated inflammation, which occurs in response to microbial death. Over the past 8 years, we have collaborated with American and international clinical professionals to research a model-based treatment for inflammatory disease. This intervention, designed to stimulate the innate immune response, has required a reevaluation of disease progression and amelioration. Paramount is the inherent conflict between palliation and microbicidal efficacy. Increased microbicidal activity was experienced as immunopathology-a temporary worsening of symptoms. Further studies are needed, but they will require careful planning to manage this immunopathology.
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