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2023-1-BG01-KA220-HED-000155777 – DigiOmica

Welcome to CLP3 “Environmental genomics and metabolomics – air pollution”

In Brief

 

CLP3 is foreseen for:

  • Undergraduates: B.Sc. students; EQF 6
  • Graduates: M.Sc. students; EQF 7

CLP3 Summary

The advancement of DNA-based approaches for genome data generation and interpretation encompasses, among others, the study of the genomes at an environmental scale using environmental DNA (eDNA). eDNA is the genetic material of nuclear and mitochondrial origin released from an organism in the environment. It is obtained directly from environmental samples (terrestrial or aquatic) without the necessity of biomaterial availability and used as an efficient, easy-to-manipulate, and standardized, non-invasive sampling approach. Thus, eDNA sampling is applied for species distribution monitoring and operates through sensitive and cost-effective protocols. Although the current technical challenges and drawbacks that scientists face are related mainly to the pitfalls in eDNA obtaining, sequencing, and data interpretation, the potential of eDNA applications is undoubtful. The perspectives on eDNA applications cover the field methods and laboratory protocols improvement for its detection and technical advancements in eDNA application as a biodiversity inventory and monitoring tool.

Omics approaches to study the air pollutant exposure’s health effects comprise systematic investigations at the genomic level. Genomics and epigenomics contribute to the assessment of the response to air pollutant exposure through studies based on single-nucleotide polymorphisms (SNP) in DNA (genome-wide) and epigenomic changes like differences in DNA methylation and post-translational histones modifications (epigenome-wide). The genome/epigenome changes that result from gene-environment interaction influence protein expression and function at the metabolic level, thus impacting cellular functions in response to air pollution. The appraisal of these changes through genomics/epigenomics tools facilitates the adverse effects of air pollutants’ understanding. This case study presents data about the state-of-the-art in genome-wide association studies of SNP, changes in DNA methylation, and post-translational histone modifications that occur with air pollutant exposure. The material also reveals GWIS and conceptual models for air pollution epigenetic epidemiologic studies as advantageous research perspectives.

Metabolomics provides qualitative and quantitative analysis of thousands of naturally occurring small molecules (metabolites) required for maintenance, growth, and normal cellular function. Despite their size, they can cause severe disease, clean up contaminated soil and water, and drive biogeochemical cycles that shape the global climate. Microbial Metabolomics finds application in environmental, medical, and biotechnological fields. Environmental metabolomics studies the effects of the growth environment on the development of an organism in natural, uncontrolled conditions. Environmental metabolomics studies also the impact of environmental stress (pollution and climate change) on the health of organisms that live in our natural environment. Application areas of environmental metabolomics include aquatic and terrestrial toxicology, organism diseases, environmental monitoring, and ecological risk assessment. Tools used to measure metabolite levels include nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry. Due to the huge amount of data collected from the experiments, mathematics and computer science are applied to analyze them.

Environmental biotechnology is the application of biotechnology principles and techniques to study and manage the natural environment. It involves microorganisms and other biological agents’ usage for the performance of environmentally beneficial tasks such as cleaning up contaminated sites, enhancing soil health, and reducing greenhouse gas emissions. Examples of environmental biotechnology applications include the use of bacteria to break down pollutants in water and soil, the use of algae to absorb excess nutrients from wastewater, and the use of fungi to decompose organic matter in landfills. Environmental biotechnology has the potential to contribute to finding sustainable solutions to environmental problems, and it is an area of active research and development. Environmental database provides access to international scientific literature relating to all aspects of environmental quality, monitoring, resource management, and conservation. Bioinformatics is essential for understanding ecological processes, managing data, and developing tools to address global challenges

Authors

  • Aleksandar Dolashki, IOCCP-BAS
  • Alexander Savov, R&D Center Biointech Ltd.
  • Boryana Angelova, R&D Center Biointech Ltd.
  • Lyudmila Velkova, IOCCP-BAS
  • Maria Vassileva,University of Granada
  • Nikolay Vassilev, University of Granada
  • Pavlina Dolashka, IOCCP-BAS
  • Trayana Nedeva, Sofia University “St. Kliment Ohridski”
  • Valentin Savov, R&D Center Biointech Ltd.

Educational Goals

This CLP3 offers new knowledge and skills about:

  • eDNA as a tool for monitoring species, populations and communities at molecular level
  • eDNA sampling and its technical challenges and drawbacks
  • eDNA application areas and future potential
  • ‘Omics’ (especially, genomics and epigenomics) approaches to study the negative effects of air pollutant exposure
  • Genome-wide association studies (GWAS) Genome-wide interaction studies (GWIS) of air pollution exposure
  • Impact of epigenomic modifications in air pollution research
  • Environmental Metabolomics
  • Major categories of environmental metabolomics and related methodological and technical innovations
  • Challenges and prospects of ecological metabolomic applications
  • Data science – environmental databases that provide access to a wealth of information related to environmental science
  • Environmental science – field that study the environment and solve environmental problems
  • Challenges and perspective of environmental bioinformatics

Learning Outcomes

Upon completion of this CLP the learners will be able to:

  • Define eDNA as a tool for monitoring species, populations and communities at molecular level
  • Explain the application areas of eDNA of microbial origin and macro-organisms in different habitats and time frames
  • Recognize and apply eDNA sampling protocols for monitoring species distribution
  • Explain the technical challenges and drawbacks of eDNA sampling and data interpretation
  • Understand the eDNA applications potential
  • Describe how the genome-wide association studies can improve our understanding of the adverse effects of air pollutants
  • Understand the links between air pollutant exposure and the epigenome
  • Present the principles of ‘candidate gene’ and the ‘genome-wide’ (‘hypothesis-independent’) approaches as tools for assessment of the biological response to air pollutants exposure
  • Examine the causative role for the epigenome in the adverse effects of environmental exposures, using air pollution as a model
  • Know the essence of the approach for use of GWAS to measure controlled air pollutants exposures in healthy individuals.
  • Describe the principles of metabolomics/environmental metabolomics
  • Apply metabolomics studies to assess metabolites and ecosystems and communities’ diversity
  • Define the major categories of environmental metabolomics research
  • Explain the environmental metabolomics application for metabolic engineering, microbial ecology, and environmental research
  • Define the challenges, limits, and perspective of environmental metabolomics
  • Describe the principles and key aspects of environmental bioinformatics and its methods and software tools
  • Use different environmental databases that cover all aspects of human impact on the environment.
  • Define the major categories of environmental science
  • Explain the application of environmental bioinformatics
  • Define the challenges, limits and perspective of environmental bioinformatics

Composition

This CLP3 comprises two Units of Learning Outcomes (ULO3 & ULO 7)

  • ULO 3:
    • Module 1 Genomics: environmental DNA and sampling
    • Module 10 Air pollution genomics
  • ULO 7
    • Module 4 Metabolomics: study microorganisms’ response to environmental stressors
    • Module 6 Environmental database and bioinformatics

Learning Content

Access here the CLP3 learning content!

>> Genomics: environmental DNA and sampling

>> Air pollution genomics

>> Metabolomics: study microorganisms’ response to environmental stressors

>> Environmental database and bioinformatics

Knowledge Assessment

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