Metagenomics
Technologies
Genomics on a huge scale
discover new organisms and explore the dynamic nature of microbial populations
Microbes affect human and animal health, support the growth of plants, are critical components of all terrestrial and aquatic ecosystems and can be exploited to produce food, fuels or chemicals. Estimating the presence and abundance of small animals, phytoplankton and zooplankton, metegenomics has proven a powerful tool to assess biodiversity and be used to monitor health of terrestrial and aquatic ecosystems.
Next-Generation Sequencing, with its ability to sequence thousands of organisms in parallel, has revolutionized microbiology by allowing concurrent analysis of whole microbial communities from complex samples and identification of strains that may not be found using other methods.
Advanced Bioinformatics Pipeline: Our comprehensive workflow ensures accurate assembly, annotation, and analysis of metagenomic data.
Customized Solutions: Tailored services to meet the unique needs of your project.
Applications of Metagenomics
- Environmental Microbiology: Explore soil, water, and air microbiomes.
- Human and Animal Health: Study gut microbiota and their impact on health.
- Agricultural Science: Improve crop yield by understanding soil microbes.
- Biotechnology: Discover new enzymes and biochemical pathways.
- Ecology and Conservation: Assess biodiversity and ecosystem health.
Shotgun metagenomic sequencing
Shotgun metagenomics allows researchers to comprehensively sample all genes in all organisms present in a given complex sample. The method provides information both about which organisms are present and what metabolic processes are possible in the community.
Since the collection of DNA from an environment is largely uncontrolled, it is important to remember that the most abundant organisms in an environmental sample are most highly represented in the resulting sequence data. Thus, large sequencing efforts are required to achieve the high coverage needed to fully resolve the genomes of under-represented community members. However, the random nature of shotgun sequencing ensures that many of these organisms, which would otherwise go unnoticed using traditional culturing techniques, will be represented by at least some small sequence segments.
Tailored consultancy
For every project we want to make sure that the outcome will meet your expectations
Key Deliverables
- Quality Control Reports: Detailed HTML reports on read quality and preprocessing steps.
- Assembled Metagenomes: High-quality contigs and scaffolds for each sample.
- Metagenome-Assembled Genomes (MAGs): Reconstructed genomes with completeness and contamination metrics.
- Functional Annotations:
- Annotations Tables: Comprehensive data on gene functions and pathways.
- Metabolic Summaries: Excel spreadsheets summarizing metabolic capabilities.
- Taxonomic Classifications: Accurate assignments from domain to species level.
- Phylogenetic Trees: Newick format trees illustrating microbial relationships.
- Abundance Profiles: Quantitative data on genome abundance across samples.
- Gene and Protein Catalogs: Non-redundant collections for further research.
- Alignment Files: Mapped reads to contigs, MAGs, and predicted genes.
profiling of community-wide gene expression
RNA-seq for identification of both taxonomic composition and active biochemical functions.
Our Metagenomic Analysis Workflow
Quality Control and Preprocessing
- Removal of Duplicates and Contaminants: Eliminate PCR duplicates and common contaminants like PhiX to ensure data purity.
- Trimming and Filtering: Discard low-quality bases and short reads to improve dataset reliability.
- Error Correction: Correct sequencing errors using overlapping paired-end reads and k-mer analysis.
De Novo Metagenome Assembly
- Assembly of High-Quality Reads: Construct contigs and scaffolds without a reference genome to discover novel sequences.
- Validation and Filtering: Map reads back to contigs, retaining only those with sufficient length and coverage.
Metagenome-Assembled Genomes (MAGs) Reconstruction
- Genome Binning: Group contigs into bins representing individual microbial genomes.
- Quality Assessment: Evaluate completeness and contamination; check for chimerism to ensure high-quality MAGs.
- Dereplication: Generate a non-redundant set of genomes by clustering similar MAGs based on average nucleotide identity (ANI).
Abundance Profiling
- Quantification Across Samples: Map reads to MAGs and calculate median coverage to estimate genome abundance in each sample.
Functional and Taxonomic Annotation
- Gene Prediction: Identify open reading frames (ORFs) within MAGs to predict potential genes.
- Functional Annotation:
- eggNOG Catalog: Assign orthologous groups and functional descriptions.
- KEGG Modules: Identify metabolic pathways and functional modules.
- Pfam-A, CAZy, VOGDB: Annotate protein families, carbohydrate-active enzymes, methanogenic and methanotrophic, SCFA, nitrogen metabolism, nitrogen and sulfur metabolism, electrons transport pathways and viral sequences.
- Taxonomic Classification: Use the Genome Taxonomy Database (GTDB) for standardized nomenclature and phylogenetic placement.
- Phylogenetic Analysis: Construct trees based on conserved marker genes to illustrate evolutionary relationships.