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Metabolic multireactor: Practical considerations for using simple oxygen sensing optodes for high-throughput batch
Matthew H Kaufman1, Joshua Torgeson2, James C Stegen1
1Pacific Northwest National Laboratory, Earth and Biological Sciences Division, Richland, WA, United States of America.
Plos One
|July 11, 2023
Summary
Researchers can now perform high-throughput, time-resolved oxygen consumption experiments on water and sediment samples using a cost-effective small batch reactor system. This approach enhances environmental research by enabling more comprehensive data collection from multiple samples simultaneously.
Area of Science:
- Environmental Science
- Analytical Chemistry
- Biogeochemistry
Background:
- Small batch reactor studies are crucial for understanding metabolic processes in aquatic and sediment environments.
- Existing methods often lack the throughput and temporal resolution needed for comprehensive analysis.
- High-quality, cost-effective experimental systems are needed to advance environmental research.
Purpose of the Study:
- To present a novel system for conducting small batch reactor oxygen consumption experiments.
- To provide practical guidance for constructing and operating a similar system for environmental research.
- To enable high-throughput, high time-resolution data collection from water and sediment samples.
Main Methods:
- Simultaneous measurement of oxygen concentrations in multiple small batch reactors.
- Adaptation of established fluorescent dye-based oxygen sensing technology.
- Detailed description of system construction, calibration, and operational procedures.
Main Results:
- The system allows for simultaneous monitoring of oxygen levels across multiple reactors.
- Achieves high throughput and high time-resolution data, overcoming limitations of previous studies.
- Provides a practical, cost-effective solution for environmental metabolic studies.
Conclusions:
- The presented system offers significant advantages for environmental research, including cost-effectiveness and high data quality.
- It empowers researchers to conduct more in-depth metabolic studies with increased sample numbers and time points.
- This work serves as a practical guide, minimizing challenges for others building similar experimental setups.

