Dataset Information

Mining Public Metagenomes for Environmental Surveillance of Parasites: A Proof of Principle.

ABSTRACT: Parasites often have complex developmental cycles that account for their presence in a variety of difficult-to-analyze matrices, including feces, water, soil, and food. Detection of parasites in these matrices still involves laborious methods. Untargeted sequencing of nucleic acids extracted from those matrices in metagenomic projects may represent an attractive alternative method for unbiased detection of these pathogens. Here, we show how publicly available metagenomic datasets can be mined to detect parasite specific sequences, and generate data useful for environmental surveillance. We use the protozoan parasite Cryptosporidium parvum as a test organism, and show that detection is influenced by the reference sequence chosen. Indeed, the use of the whole genome yields high sensitivity but low specificity, whereas specificity is improved through the use of signature sequences. In conclusion, querying metagenomic datasets for parasites is feasible and relevant, but requires optimization and validation. Nevertheless, this approach provides access to the large, and rapidly increasing, number of datasets from metagenomic and meta-transcriptomic studies, allowing unlocking hitherto idle signals of parasites in our environments.

SUBMITTER: Franssen FFJ

PROVIDER: S-EPMC8278238 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Mining Public Metagenomes for Environmental Surveillance of Parasites: A Proof of Principle.

Franssen Frits F J FFJ Janse Ingmar I Janssen Dennis D Caccio Simone M SM Vatta Paolo P van der Giessen Joke W B JWB van Passel Mark W J MWJ

Frontiers in microbiology 20210630

Parasites often have complex developmental cycles that account for their presence in a variety of difficult-to-analyze matrices, including feces, water, soil, and food. Detection of parasites in these matrices still involves laborious methods. Untargeted sequencing of nucleic acids extracted from those matrices in metagenomic projects may represent an attractive alternative method for unbiased detection of these pathogens. Here, we show how publicly available metagenomic datasets can be mined to ...[more]

PMID: 34276576

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Project description:In this work we demonstrate a novel method of methylation detection that utilises immunoaffinity to detect the presence of methylated DNA hybridised to a cDNA microarray. We use a monoclonal antibody specific to 5 methylcytosine to detect the presence of 5 methylcytosine in genomic DNA from human fibroblasts bearing the karyotype 45 XO. We report that over 2900 genes show the presence of methylation in this condition. We also report that 165 genes are consistently methylated in all replicates of these experiments. The methylated genes show a uniform distribution over all the chromosomes. The gene ontology of these also indicates no functional correlation between the genes that are methylated. We detect the presence of methylation in IGF2, an imprinted gene and thus known to harbour DNA methylation. The method is extremely specific and offers a quick and efficient way to analyse the methylation landscape on a high throughput scale. This method uses existing technology to assess methylation and thus can integrate very efficiently into any platform used. A method that detects DNA methylation that is not restricted to specific sequences would provide a useful platform to analyse methylation distribution among the genes in any given phenotypic condition.Availability of additional approaches to examine DNA methylation would lead to increase in our understanding of the methylome and would help define the intrinsic and extrinsic factors which govern it. Microarray based high throughput methods have been extensively used for gene expression analysis. The method described uses a microarray to analyse DNA methylation levels in a gene/cDNA/oligo specific manner. Here, genomic DNA is fragmented and used for hybridization to microarray slides. The presence of DNA cytosine methylation in the hybridized DNA is detected by employing Cy3 labelled anti 5mC( 5-methyl cytidine) antibody (monoclonal). The resolution provided by this method is dependent upon the microarray platform used. This method can be adapted to any platform thus enabling seamless integration with existing technology of gene expression analysis

Dataset Information

Mining Public Metagenomes for Environmental Surveillance of Parasites: A Proof of Principle.

Publications

Mining Public Metagenomes for Environmental Surveillance of Parasites: A Proof of Principle.

Similar Datasets

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