Single-Cell Detection and Quantification of Metabolically Active Bacteria in Soil Using Heavy-Water Labeling and Raman Microspectroscopy.

Authors

Jiazhi Ding, Junqi Gao, Hongzhe Li, Li Cui

Published in

Journal of visualized experiments : JoVE. Issue 236. Oct 16, 2026. Epub Oct 16, 2026.

Abstract

Only microorganisms that are metabolically active during a defined observation window contribute directly to ongoing soil processes, yet this active fraction is difficult to quantify. Cultivation excludes uncultured taxa, deoxyribonucleic acid (DNA)-based methods primarily describe community membership and functional potential, and bulk assays obscure cell-to-cell variation. This protocol combines heavy-water (D₂O) labeling with single-cell Raman microspectroscopy, here termed Raman-deuterium isotope probing (Raman-DIP), to detect and quantify bacterial anabolic activity during labeling in soil. Matched soil samples are incubated under identical conditions with H₂O or D₂O. Microbial cells are then recovered by Nycodenz density separation, deposited on aluminum-coated slides, and analyzed individually. Deuterium incorporation into newly synthesized biomass produces a carbon-deuterium (C-D) band at 2,040-2,300 cm⁻¹. A cell is classified as detectably active when its C-D ratio exceeds a threshold derived from the matched H₂O control, and the active-cell fraction is calculated for each biological replicate. The method retains soil-matrix effects during labeling, does not require cultivation or a fluorescent activity probe, and reveals physiological heterogeneity that is lost in community-averaged measurements. Because D₂O supplies an isotopic label rather than an exogenous organic substrate, it can label diverse anabolic processes while limiting selection for a particular carbon source. The workflow is therefore suited to standardized comparisons of bacterial activity across soils and environmental treatments. It reports anabolic incorporation during the labeling interval rather than overall viability; nonlabeled cells should not automatically be interpreted as dead.

PMID:
42891611
Bibliographic data and abstract were imported from PubMed on 18 Oct 2026.

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