Identify the functional potential of microbial communities through advanced metagenome assembly, gene annotation, pathway analysis, and microbiome-wide statistical modeling.
Functional metagenomics analysis goes beyond identifying which microorganisms are present in a sample by revealing what those microorganisms are capable of doing. Using shotgun metagenomic sequencing data, BaseClear reconstructs metagenomes, predicts genes, and annotates biological functions to characterize the metabolic potential of microbial communities. This enables researchers to investigate functional pathways, carbohydrate metabolism, antimicrobial resistance genes, virulence factors, and other biological mechanisms that may influence health, disease, product performance, or environmental processes.
This service is designed for pharmaceutical companies, biotechnology organizations, consumer health and personal care companies, academic researchers, and microbiome innovators conducting clinical studies, intervention trials, product development programs, or large-scale microbiome research projects. It is particularly valuable when understanding microbial function is more important than taxonomic composition alone, such as studies investigating treatment effects, host-microbiome interactions, disease mechanisms, antimicrobial resistance, skin health, gut health, or microbiome-based product claims.
BaseClear applies validated and industry-benchmarked assembly-based bioinformatics workflows to analyze shotgun metagenomic sequencing data. Sequencing reads are assembled into contigs, followed by dedicated gene prediction workflows supporting prokaryotic, eukaryotic, viral, and phage genomes. Predicted genes are functionally annotated using state-of-the-art databases including eggNOG, UniRef90, KEGG, COG, CAZy, CARD, ResFinder, ARG-ANNOT, and VFDB. Statistical analyses are performed using established methods such as MaAsLin 2 to identify significant associations between functional gene abundances, microbial diversity metrics, and study metadata. The workflow supports both small research projects and large clinical studies involving hundreds of samples.
Clients receive a comprehensive package of functional metagenomics deliverables, including metagenome assemblies, gene predictions, functional annotations, pathway abundance tables, antimicrobial resistance profiles, virulence factor analyses, and metadata-driven statistical results. Outputs include publication-ready visualizations such as heatmaps, box plots, diversity analyses, and multivariate association plots, together with a detailed scientific report interpreting the results in the context of the study objectives. This integrated approach transforms raw shotgun metagenomics data into actionable biological insights that support research, product development, and scientific decision-making.
End-to-end microbial safety assessment capabilities
Regulatory-ready data generation and interpretation
Integrated wet-lab and bioinformatics expertise
Structured support for EFSA and global submissions
Functional metagenomics reveals the biological capabilities of a microbial community rather than only identifying which organisms are present. While taxonomic profiling provides information about microbial composition, functional analysis identifies genes, pathways, carbohydrate-active enzymes, antimicrobial resistance markers, and virulence factors that may directly influence health outcomes, treatment responses, product performance, or environmental processes. This allows researchers to move from describing microbial communities to understanding their biological function.
BaseClear identifies antimicrobial resistance and virulence genes using validated annotation workflows and multiple specialized reference databases. Predicted genes from assembled metagenomes are compared against databases including CARD, ResFinder, ARG-ANNOT, and VFDB, enabling comprehensive characterization of resistance mechanisms and virulence-associated functions. Using multiple databases increases coverage and confidence in the detection of clinically and biologically relevant markers.
Functional gene abundances can be statistically associated with clinical, phenotypic, environmental, or treatment-related metadata. BaseClear applies Microbiome Multivariable Associations with Linear Models (MaAsLin 2) to identify significant relationships between functional features and metadata variables while accounting for complex study designs. This enables researchers to identify microbial functions that are associated with treatment effects, disease states, demographic factors, or other variables of interest.
Functional metagenomics analyses are performed using multiple state-of-the-art databases that capture different aspects of microbial biology. BaseClear annotates genes against resources such as eggNOG, UniRef90, KEGG, COG, and CAZy to characterize metabolic pathways, molecular functions, and carbohydrate-active enzymes. This multi-database approach provides a comprehensive view of microbiome functionality across diverse sample types and research applications.
A functional metagenomics project delivers both detailed bioinformatics outputs and client-friendly scientific reporting. Clients receive metagenome assemblies, gene prediction files, functional annotation tables, pathway abundance matrices, antimicrobial resistance and virulence gene analyses, metadata association results, and publication-ready visualizations including heatmaps, diversity plots, box plots, and multivariate analyses. These deliverables provide both the raw analytical outputs required for advanced research and the interpreted insights needed for decision-making and publication.
SERVICES
Phenotypic assessment of antimicrobial resistance aligned with EFSA guidelines
SERVICES
Phenotypic assessment of antimicrobial and cytotoxic production
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