metaQuantome

metaQuantome performs quantitative analysis of mass-spectrometry-based metaproteomics data by integrating peptide-level taxonomic and functional hierarchies to resolve microbial community roles and functions.

Key Features:

• Peptide-level taxonomic and functional integration: Integrates taxonomic and functional hierarchies at the peptide level to attribute biological processes to specific taxa.
• Quantitative analysis: Leverages label-free intensity-based methods to summarize peptide-level quantitative information.
• Differential abundance analysis: Performs differential abundance testing across multiple experimental conditions to identify significant changes in microbial protein expression.
• Multivariate visualization: Provides principal components analysis and clustered heat map visualizations for exploration of complex metaproteomic datasets.
• Exploratory and hypothesis testing: Supports both exploratory analysis of single samples or conditions and formal hypothesis-testing workflows.
• Multiomics integration: Integrates metatranscriptomics via the MT2MQ tool and ingests outputs from the ASaiM workflow for comparative multiomic analyses.
• Statistical evaluation across conditions: Enables statistical analyses across multiple conditions, including time-course studies.

Scientific Applications:

• Benchmarking and accuracy assessment: Benchmarks metaproteomic quantification using artificially assembled microbial communities and recombinant human proteins spiked into an Escherichia coli background to evaluate taxonomic and functional quantification accuracy.
• Microbiome functional analysis: Applies to published human oral microbiome datasets to attribute taxonomic contributors to biological processes and generate publication-quality figures.

Methodology:

Label-free intensity-based peptide summarization; integration of taxonomic and functional hierarchies at the peptide level; differential abundance analysis; principal components analysis and clustered heat maps; statistical analyses across multiple conditions; MT2MQ integration of ASaiM workflow outputs.