Short-chain fatty acids (SCFAs) are fatty acids that contain fewer than six carbon atoms. Produced when friendly gut bacteria ferments fiber in the colon, SCFAs act as the main energy source for cells lining the colon (1). These substances have gained attention for their potential in bio-energy industry applications, specifically regarding their role in renewable energy generation from biological waste materials (2). SCFAs can be bio-synthesized from mixed waste, such as sewage sludge. As such, they can be used to develop local solutions, adding value to in part environmentally problematic waste products (3).
Various research efforts have been conducted to understand SCFAs, including recent efforts to quantify these substances using high-performance liquid chromatography coupled with a photodiode array detector (HPLC-PDA) (2). This research, helmed by scientists from the University of Maryland and published in the Journal of Chromatography Open, proved effective (4). The method was characterized by low detection limits, short analysis times, and being applicable to aqueous samples with complex matrices.
LCGC International recently spoke with Esther Olonimoyo, a graduate assistant at the University of Maryland, about her team’s research. In this interview, Olonimoyo speaks about the importance of analyzing SCFAs, challenges faced while conducting research, and potential research findings and developments that can be explored in the future.
What notable roles do short-chain fatty acids (SCFAs) play in scientific research?
SCFAs are naturally ubiquitous, occurring across diverse systems including soils, plants, human and animal microbiomes, wastewater, and the atmosphere. In environmental science, they play key roles in soil microbial ecology and carbon cycling. In energy research, SCFAs serve as intermediates or end-products in anaerobic digestion and biofuel production. In food science, they influence flavor development, preservation, and the quality of fermentation processes.
From an atmospheric perspective, SCFAs, particularly formic and acetic acids—are both directly emitted and secondarily formed through photochemical reactions involving biogenic and anthropogenic precursors. They are also abundant in wildfire plumes. Once in the atmosphere, these compounds contribute to acidity, participate in heterogeneous reactions, and influence oxidative capacity and overall atmospheric chemistry. These multifaceted roles make SCFAs important targets for investigation across environmental, clinical, and industrial research contexts.
What were the benefits of using HPLC-PDA to quantify the six short-chain fatty acids in your study?
High-performance liquid chromatography coupled with a photodiode array detector (HPLC-PDA) offered several advantages in SCFA quantification. A key benefit was achieving clean, reliable separation without requiring chemical derivatization, which is commonly needed in gas chromatography. This simplified the workflow, reduced preparation time, and eliminated potential artifacts, while also minimizing waste. The method was reproducible, cost-effective, and compatible with aqueous matrices, making it well-suited for our study.
To assess method efficiency, I introduced a metric called the Degree of Speciation (DoS), defined as the number of analytes resolved per minute of run time. Our method achieved a DoS of 0.7 analytes per minute, demonstrating high throughput. A cost-benefit analysis further highlighted the affordability of HPLC-PDA relative to more complex tools like nuclear magnetic resonance (NMR) or liquid chromatography-mass spectrometry (LC-MS). It proved especially advantageous for labs with limited access to high-end instrumentation, delivering solid analytical performance at a fraction of the cost.
What challenges or limitations did you face in your research that can still be explored?
A major challenge was applying the method to atmospheric samples such as rainwater, fog, and aerosols, where SCFAs exist at trace levels. Detecting these low concentrations required highly sensitive instrumentation and meticulous sample handling, pushing the limits of PDA-based detection.
Another limitation stemmed from the low UV absorbance of some SCFAs, which reduced sensitivity with PDA detectors. While the method met the needs of our study, future work could benefit from coupling HPLC with more sensitive detectors like mass spectrometers or exploring selective derivatization to enhance detection.
Method development itself was also repetitive and time-intensive, requiring multiple iterations to fine-tune parameters such as mobile phase composition, flow rate, and column temperature. Despite the effort, this iterative process was crucial to achieving consistency and reliability.
Lastly, matrix interferences occasionally affected peak resolution in complex environmental or biological samples. Incorporating more selective sample preparation strategies, like solid-phase extraction or advanced filtration, could further improve specificity and robustness. These challenges open new avenues for enhancing sensitivity and expanding method applicability to diverse real-world matrices.
In your opinion, what was the most exciting or compelling finding from your study?
The most exciting finding was the ability to achieve complete separation of 6 SCFAs in under 8 minutes, considerably faster than many existing methods, which often require 14 to 30 minutes. This high-throughput capability enhances efficiency without sacrificing resolution or accuracy.
Equally compelling was the elimination of derivatization. Many SCFA methods rely on this time-consuming and often hazardous step to improve detectability. Our method, through careful optimization of pH, flow rate, and temperature, maintained excellent sensitivity and precision without it, simplifying the workflow and reducing environmental impact.
The method also balanced performance and affordability. Our cost-benefit analysis showed that, compared to LC-MS or NMR-based techniques, the HPLC-PDA approach delivered a high DoS (analytes per minute) with significantly lower operational costs. This makes it a practical solution for routine SCFA analysis in smaller labs or resource-limited settings. The combination of speed, simplicity, and accessibility was a particularly exciting outcome of this work.
Are there any plans to expand upon your current findings? What might future research look like in this area?
Yes, I am currently expanding my research to optimize the separation of C₂ to C₆ dicarboxylic acids, such as oxalic and succinic acids. These compounds are increasingly important in environmental chemistry, atmospheric science, and biogeochemical cycling. They serve as markers for secondary organic aerosol formation and microbial activity, and improving their analytical resolution will enhance our understanding of both natural and anthropogenic processes.
I am also integrating green chemistry principles into method development, focusing on separation techniques that minimize or eliminate the use of toxic solvents. Future work will explore eco-friendly solvent systems, sustainable sample preparation methods, and robust analytical workflows that support both scientific innovation and environmental responsibility.
Was there anything that surprised you about this research that our readers should know?
What stood out most was how effective the method proved to be despite its simplicity and lack of derivatization. Traditionally, SCFA quantification in complex matrices has relied heavily on derivatization to enhance detection. This study showed that, with careful optimization, it’s possible to achieve high sensitivity, precision, and speed without that step.
Additionally, the method reduced analysis time by half compared to standard protocols while still detecting concentrations as low as 0.0003 mM. Achieving this level of performance with a low-cost, easy-to-implement platform is a significant advancement. It opens the door to faster, greener, and more accessible SCFA analysis for labs that may not have access to advanced instruments like mass spectrometers. This makes the method valuable for applications in environmental monitoring, food science, microbial studies, and biofuel research.
(1) Chin, K. How Short-Chain Fatty Acids Affect Health and Weight. Healthline 2021. https://www.healthline.com/nutrition/short-chain-fatty-acids-101#TOC_TITLE_HDR_2 (accessed 2025-6-30)
(2) Olonimoyo, E. A.; Amradi, N. K.; Lansing, S.; et al. An Improved Underivatized, Cost-Effective, Validated Method for Six Short-Chain Fatty Organic Acids by High-Performance Liquid Chromatography. J. Chromatogr. Open 2025, 7, 100193. DOI: 10.1016/j.jcoa.2024.100193
(3) Tomás-Pejó, E.; González-Fernández, C.; Greses, S.; Kennes, C.; et al. Production of Short-Chain Fatty Acids (SCFAs) as Chemicals or Substrates for Microbes to Obtain Biochemicals. Biotechnol. Biofuels Bioprod. 2023, 16, 96. DOI: 10.1186/s13068-023-02349-5
(4) Acevedo, A. University of Maryland Researchers Investigate HPLC-PDA Method for Fatty Acid Analysis. https://www.chromatographyonline.com/view/university-of-maryland-researchers-investigate-hplc-pda-method-for-fatty-acid-analysis (accessed 2025-6-30)
Esther A. Olonimoyo is a Ph.D. candidate in Atmospheric Chemistry at the University of Maryland, College Park. Her research focuses on the chemical characterization of organic acids, particularly short-chain fatty acids, in environmental and atmospheric systems. She specializes in method development using high-performance liquid chromatography (HPLC) and is passionate about integrating green chemistry principles into analytical workflows. Esther’s work bridges environmental sustainability and analytical science, with applications in air quality, atmospheric processes, and microbial metabolism. She is committed to advancing accessible, cost-effective methods for environmental monitoring and scientific discovery.
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