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CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

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RETRACTED: Reactome array: forging a link between metabolome and genome.

Ana Beloqui¹, María-Eugenia Guazzaroni, Florencio Pazos

¹CSIC, Institute of Catalysis, 28049 Madrid, Spain.

Science (New York, N.Y.)

|October 10, 2009

Summary

This summary is machine-generated.

This study introduces a novel metabolite array for analyzing metabolic functions in cells and communities, regardless of genome sequence. This tool enables the reconstruction of metabolic networks for both known and unsequenced organisms.

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High-Throughput Metabolic Profiling for Model Refinements of Microalgae

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

Area of Science:

Metabolomics
Systems Biology
Biochemistry

Background:

Understanding cellular metabolism is crucial for various biological and medical applications.
Current methods for metabolic analysis often require prior genome sequencing, limiting their application to unsequenced organisms.
A genome-independent approach is needed to comprehensively analyze metabolic phenotypes and networks.

Purpose of the Study:

To develop and validate a sensitive metabolite array for functional analysis of metabolic phenotypes and networks (reactomes) in cell populations and communities.
To demonstrate the array's utility for both sequenced and unsequenced organisms.
To enable the reconstruction of global metabolic pathways and identification of key enzymes.

Main Methods:

Development of a metabolite array containing 1676 dye-linked substrate compounds representing central metabolic pathways.
Application of cell extracts to the array, leading to enzyme-substrate binding, transformation, and signal activation.
Reconstruction of metabolic maps using data from the array.
Enzyme capture on nanoparticles, sequencing, and functional establishment for specific enzymes.

Main Results:

Successful reconstruction of metabolic maps for model bacteria.
Demonstrated utility for unsequenced organisms by reconstructing global metabolisms of microbial communities from diverse environments (acidic volcanic pool, deep-sea brine lake, hydrocarbon-polluted seawater).
Unequivocal establishment of enzyme functions captured on nanoparticles.

Conclusions:

The metabolite array provides a sensitive, genome sequence-independent platform for functional analysis of metabolic networks.
This technology significantly advances the study of microbial metabolomics, especially for unsequenced organisms and complex communities.
The array facilitates the reconstruction of metabolic pathways and the characterization of enzyme functions, opening new avenues in systems biology.