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Updated: May 26, 2026

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays
Published on: January 16, 2018
High-throughput isotopic analysis of RNA microarrays to quantify microbial resource use
Xavier Mayali1, Peter K Weber, Eoin L Brodie
1Physical and Life Science Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA. mayali1@llnl.gov
Chip-stable isotope probing (SIP) directly measures uncultivated microbe functions using a microarray. This method quanties substrate use by diverse microbial taxa, revealing resource partitioning in natural environments.
Area of Science:
- Microbial Ecology
- Environmental Microbiology
- Molecular Ecology
Background:
- Most microorganisms are uncultivated, limiting understanding of their ecological roles.
- Current methods often infer microbial functions from diversity and genomic data.
- Direct functional measurements are crucial for uncultivated microbial communities.
Purpose of the Study:
- To develop a high-sensitivity, high-throughput method for directly measuring the functional roles of uncultivated microbes.
- To enable the quantification of substrate use by specific microbial taxa in complex communities.
- To test genomics-generated hypotheses about microbial biogeochemical functions.
Main Methods:
- Developed Chip-stable isotope probing (Chip-SIP), integrating stable isotope probing (SIP) with phylogenetic microarrays.
- Incubated microbial communities with isotopically labeled substrates.
- Hybridized extracted rRNA to a microarray and measured isotope incorporation using NanoSIMS.
Main Results:
- Chip-SIP detected low levels of isotopic enrichment (0.5 atom % 13C, 0.1 atom % 15N), allowing short incubations and low substrate concentrations.
- Applied to an estuarine community, Chip-SIP quantified substrate incorporation by 81 distinct microbial taxa.
- Demonstrated resource partitioning among microbes utilizing simple organic substrates like amino acids, nucleic acids, and fatty acids.
Conclusions:
- Chip-SIP is a sensitive and high-throughput method for directly assessing microbial functions.
- The approach allows for testing genomics-based predictions in natural microbial communities.
- Expands the toolkit for microbial ecologists studying biogeochemical processes in diverse environments.
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