Background: Reduced representation genomic datasets are increasingly becoming available from a variety of organisms. These datasets do not target specific genes, and so may contain sequences from parasites and other organisms present in the target tissue sample. In this paper, we demonstrate that (1) RADseq datasets can be used for exploratory analysis of tissue-specific metagenomes, and (2) tissue collections house complete metagenomic communities, which can be investigated and quantified by a variety of techniques.
Methods: We present an exploratory method for mining metagenomic "bycatch" sequences from a range of host tissue types. We use a combination of the pyRAD assembly pipeline, NCBI's blastn software, and custom R scripts to isolate metagenomic sequences from RADseq type datasets.
Results: When we focus on sequences that align with existing references in NCBI's GenBank, we find that between three and five percent of identifiable double-digest restriction site associated DNA (ddRAD) sequences from host tissue samples are from phyla to contain known blood parasites. In addition to tissue samples, we examine ddRAD sequences from metagenomic DNA extracted snake and lizard hind-gut samples. We find that the sequences recovered from these samples match with expected bacterial and eukaryotic gut microbiome phyla.
Discussion: Our results suggest that (1) museum tissue banks originally collected for host DNA archiving are also preserving valuable parasite and microbiome communities, (2) that publicly available RADseq datasets may include metagenomic sequences that could be explored, and (3) that restriction site approaches are a useful exploratory technique to identify microbiome lineages that could be missed by primer-based approaches.
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http://dx.doi.org/10.7717/peerj.4662 | DOI Listing |
Food Environ Virol
January 2025
Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA.
Wastewater-based surveillance has emerged as a powerful approach to monitoring infectious diseases within a community. Typically, wastewater samples are concentrated before viral analyses to improve sensitivity. Current concentration methods vary in time requirements, costs, and efficiency.
View Article and Find Full Text PDFPhytopathology
January 2025
Virginia Polytechnic Institute and State University, School of Plant and Environmental Science, Blacksburg, Virginia, United States;
Microb Genom
January 2025
Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
A diverse array of micro-organisms can be found on food, including those that are pathogenic or resistant to antimicrobial drugs. Metagenomics involves extracting and sequencing the DNA of all micro-organisms on a sample, and here, we used a combination of culture and culture-independent approaches to investigate the microbial ecology of food to assess the potential application of metagenomics for the microbial surveillance of food. We cultured common foodborne pathogens and other organisms including , spp.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of Massachusetts Chan Medical School, Worcester, MA, USA.
Background: Alzheimer's disease (AD) is the most common type of dementia which results in debilitating memory loss as the disease advances. However, among older adults with AD, some may experience rapid cognitive decline while others may maintain a stable cognitive status for years. In addition to the amyloid plaques, tau tangles, and neuronal inflammation characteristic of AD, there is strong evidence of dysregulation in the peripheral immune system, including decreased naïve T cells and increased memory T cells among older adults with AD.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of Massachusetts Chan Medical School, Worcester, MA, USA.
Background: Several studies have found that oral and gut microbiome and their byproducts can impact Alzheimer's Disease (AD). The objective of our study is to analyze metagenomic sequencing data from paired oral and fecal microbiomes, along with clinical variables, to identify communities of bacteria associated with AD. This research aims to improve our understanding of the microbiome community matrix, and how these communities interact and correlate with AD status compared to healthy controls (HC) through an oral-gut microbial axis.
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