Automated Phospholipid Fatty Acid (PLFA) Analysis using MIDI’s Sherlock PLFA Analysis Software

Significance of Topic

Phospholipid fatty acid analysis offers a direct measure of living microbial biomass and community composition in soils. By targeting membrane lipids that degrade rapidly after cell death, PLFA profiling provides a real-time snapshot of soil microbiota. This information is essential for understanding nutrient cycling, plant growth support, pollutant degradation, and the impacts of conservation or remediation interventions.

Objectives and Study Overview

The primary aim is to demonstrate an automated, high-throughput workflow for soil PLFA analysis using a streamlined extraction protocol coupled with MIDI’s Sherlock PLFA Analysis Software and Agilent GC instrumentation. This approach seeks to reduce manual labor, decrease reagent consumption, improve consistency, and minimize errors in peak identification and data processing.

Methodology and Instrumentation

Sample preparation and analysis followed these key steps:

• High-throughput PLFA extraction with addition of a known amount of 19:0 PC internal standard
• Automated sample loading via the Sherlock Sample Processor selecting the PLFAD2 method
• Agilent GC ChemStation control with predefined method parameters
• Sequence: calibration standard → hexane blank → soil extract
• Peak naming and quantification by Sherlock PLFA Analysis Software converting retention times to Equivalent Chromatographic Locales™
• Data normalization to mole percent, scaling to the internal standard, biomass calculation (nmol/g), and ratio computation via Sherlock PLFA Tools

Main Results and Discussion

The workflow identified 52 distinct fatty acids and automatically named 97.47% of detectable peaks. Biomass distribution by microbial origin revealed:

• Gram-negative bacteria as the dominant group (56.3 nmol/g)
• Significant contributions from Gram-positive bacteria, actinomycetes, arbuscular mycorrhizal fungi, and other eukaryotes
• User-defined PLFA ratios such as fungi to bacteria (0.10) and saturated to unsaturated fatty acids (0.84) provided insights into community stress and functional balance

This high naming success rate and detailed profiling demonstrate the method’s sensitivity and reliability for detecting subtle shifts in soil microbial communities.

Benefits and Practical Applications

Automating PLFA naming and categorization delivers:

• Consistency across runs by eliminating manual peak assignment
• Faster turnaround and reduced reagent use
• Customizable grouping of PLFAs to specific microbial types for tailored ecological studies
• Exportable data formats for visualization, statistical analysis, and publication

These advantages make the approach suitable for agricultural monitoring, environmental assessment, and quality control in soil research laboratories.

Future Trends and Applications

Emerging directions include:

• Integration with metagenomic and metabolomic datasets to link PLFA profiles with functional gene expression
• Machine learning models trained on large PLFA databases for automated community classification and anomaly detection
• Miniaturized and field-deployable GC platforms for on-site soil health monitoring
• Expanded PLFA libraries covering diverse ecosystems to improve biomarker specificity

Conclusion

The combination of a high-throughput extraction protocol, Agilent GC instrumentation, and MIDI’s Sherlock PLFA Analysis Software establishes a robust, standardized workflow for soil microbial community analysis. The process delivers rapid, accurate, and customizable profiling of living soil microbiota, supporting both research and applied environmental management.

Used Instrumentation

• Gas chromatograph: Agilent 7890B Series
• Autosampler: Agilent 7683 Injector with sample tray
• Software: MIDI Sherlock Software v6.3 with PLFA Package and Agilent OpenLab CDS ChemStation
• Column: Agilent Ultra 2 (25 m × 0.2 mm, 0.33 µm film)
• Carrier gas: Hydrogen at 1.3 mL/min
• Oven program: 190 °C hold, ramp to 285 °C at 10 °C/min, then to 310 °C at 60 °C/min
• Split ratio: 30:1; Injection volume: 2.0 µL; Inlet temp: 250 °C; FID temp: 300 °C

References

• Buyer JS and Sasser M High throughput phospholipid fatty acid analysis of soils Applied Soil Ecology 61 127–130 2012