Environmental DNA and Metabarcoding Basics

Environmental DNA (eDNA)

• eDNA is genetic material from organisms found in environmental samples (water, soil, air)
• It's a non-invasive method to study biodiversity, complementing traditional methods
• The presence of eDNA indicates the presence of a specific organism
• Researchers can extract, amplify, and sequence DNA to identify species and their abundance
• This method revolutionizes ecological research, especially in detecting elusive species and monitoring populations

Metabarcoding

• A powerful tool for biodiversity analysis
• Uses DNA sequencing to identify multiple species simultaneously from a single sample
• Enables the analysis of the diversity of organism communities, current and past
• Uses genetic markers specific to a taxon (species, genus, or family) like 16S rDNA (bacteria), 18S rDNA, Cyt-b or COI (animals), rbcL and matk (plants), or ITS (fungi)

Metagenomics

• A powerful tool for studying biodiversity
• Identifies all organisms present in a sample, regardless of cultivatability
• Reveals functional potential of a community by identifying present genes and metabolic pathways
• Assembles complete genomes, even for uncultivated or extinct organisms, revealing insights into their evolution and adaptation

eDNA Metabarcoding Methodology

• Environmental Sampling: Collect samples (water, sediment, air)
• DNA Extraction: Isolate DNA from the sample
• Amplification: Amplify specific DNA regions using PCR
• Sequencing: Sequence the amplified DNA using next-generation sequencing
• Data Analysis: Analyze sequence data to identify species and assess biodiversity

Benefits of eDNA

• Non-Invasive Sampling: Avoids disturbing ecosystems during biodiversity monitoring.
• Cost-Effectiveness: Often cheaper than traditional sampling methods
• Taxonomic Resolution: Enables sampling of greater diversity and higher taxonomic resolution
• Detection of Rare Species: Effectively detects rare, invasive species, extinct, or elusive species

Drawbacks of eDNA

• Degradation: eDNA degrades in the environment, limiting the scope of studies, especially in warm, tropical regions
• Variability: Degradation time and travel distance vary with environmental conditions, impacting inferences on species distributions

Earth Microbiome Project

• Analyzes over 200,000 samples using metagenomics
• Creates a global atlas of genes, proteins, and microbial communities from diverse ecosystems

The Human Microbiome Project

• Coordinates research with ethical, legal, and social impact considerations
• Aims to improve disease prevention through microbiome study
• Revealed three distinct intestinal microbiome groups, independent of demographics or health status

Genomic Observatories

• Produces long-term, contextualized biodiversity observations at the genomic level
• Quantifies biotic interactions and constructs biodiversity models to predict ecosystem services
• Employs cutting-edge genomics to monitor genetic variation in human and natural ecosystems

PEGS (Integrating Genomic and Environmental Data)

• Systematically relates genetic data with biophysical and socio-economic metadata to produce comprehensive predictive modeling of ecosystems
• Creates models for biodiversity quality, distribution, and ecosystem services, considering future scenarios and human activity
• Establishes new genomic observation sites in developing countries to study biodiversity vulnerability across diverse ecosystems

Natural History Museums Role in Conservation

• Crucial for safeguarding biological collections (representing them accurately and reliably for future research)
• Preserve genetic materials (DNA) alongside physical specimens
• Foster global collaboration among researchers through international networks
• Contribute to the Barcode of Life initiative (e.g. plant and animal categorization)

challenges in managing biodiversity data

• Specimen-Data Link: Connecting genomic data to specific museum specimens is challenging
• Unidentified Organisms: Samples from diverse environments often contain numerous unknown organisms, requiring extensive taxonomic work
• Specialist Shortage: Analysis of enormous biodiversity data often requires specialized expertise

Ecoinformatics

• Advances new methodologies and software specifically for analyzing and managing biodiversity data
• Promotes the online sharing of data sets to broad scientific communities, facilitating cooperation.
• Emphasizes data standardisation, collaboration and data sharing

The Future of Biodiversity Data

• Integrated Data Systems: Seamlessly combine data from collections, genomics, and environmental sources
• Citizen Science Engagement: Encourage public participation in research and data collection
• Virtual and Augmented Reality: Create immersive experiences to enhance understanding of biodiversity and conservation
• Predictive Modeling and Conservation: Data-based forecasting, informing conservation strategies
• Ethical Considerations: Addressing ethical challenges related to data ownership, access, and responsible research

Omics Technologies

• Risk Assessment: "Omics" technologies are very promising in risk assessments as they analyze biochemical level information to evaluate chemicals, and identify toxicity levels more readily and accurately.
• Population Responses: These technologies give a deeper understanding of how populations respond to environmental changes (e.g. exposure to toxins), and allows to identify sensitive and insensitive species and phenotypes.