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Updated: Apr 30, 2026

Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy
Published on: May 29, 2012
Phenotypic discrimination and characterization of microbial populations in enhanced biological phosphorus removal
Jiayu Bi1, Ricardo Marques2, Dongqi Wang3
1Department of Municipal and Environmental Engineering, School of Water Resources and Hydro-Electric Engineering, Xi'an University of Technology, Xi'an, Shaanxi 710048, China.
Abstract:
Single-cell Raman spectroscopy (SCRS) represents a non-invasive, expedient, and label-free strategy for investigating the molecular composition of individual cells. In this study, we applied SCRS to perform qualitative and quantitative analyses of polyphosphate (polyP) accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) within enhanced biological phosphorus removal (EBPR) systems, enabling their metabolic trait-based profiling and phenotypic classification. SCRS analysis revealed diverse metabolic profiles of metabolically active EBPR populations including unknown GAOs and PAOs performing GAO metabolism. The dynamics of intracellular polymers quantified by SCRS were highly correlated with bulk measurements, while also providing additional metabolic information. SCRS analysis, combined with carbon feeding batch tests and hierarchical clustering analysis (HCA), could phenotypically classify clade-level PAO/GAO subpopulations with distinct carbon metabolisms and Raman spectral features (e.g., shift in signature peak, whole fingerprint region). The combination of fluorescence in situ hybridization (FISH) with Raman (FISH-Raman) and HCA, for the first time, revealed higher phenotypic microdiversity for Tetrasphaera and substantial differences in polyP peak position between Tetrasphaera and Accumulibacter cells. Tetrasphaera PG1, characterized by high polyP content and potentially belonging to members of clade 2 or 3, was identified as a primary contributor in a side-stream EBPR system. These findings offer novel insights into the metabolic processes and growth dynamics of microorganisms within EBPR systems, providing a critical tool for deciphering the microdiversity and metabolic behaviors of PAO/GAO populations in complex EBPR communities.
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