In research, microscopy is not just a matter of beautiful images: it is a measurement. Localising a protein in a compartment, quantifying an intensity, measuring a colocalisation, counting cells or tracking a dynamic over time — so many numerical, reproducible readouts that quantitative imaging provides, from confocal to live-cell imaging.
Principle and workflow
Fluorescence microscopy illuminates specific markers (antibodies, fluorescent proteins, probes) and collects the light they emit. In confocal, a pinhole rejects light outside the focal plane: this yields optical sectioning that removes blur, allows high resolution in thick samples and 3D reconstruction by stacking planes (z-stacks). Analysis follows acquisition: object segmentation, then quantification — intensities, ratios (for example nucleo-cytoplasmic), colocalisation, counting, morphometry — using tools such as ImageJ/Fiji or QuPath.
In live-cell imaging, acquisition becomes temporal: time-lapse series capture migration, division, intracellular trafficking or transformation, at single-cell scale. The design of the protocol (markers, interval, light dose) then directly determines the reliability of the measurement.
Variants and options
Depending on the question, one deploys epifluorescence (fast, wide field), laser-scanning confocal (fine optical sectioning), spinning-disk confocal (fast and less phototoxic, suited to live-cell), or more specialised approaches: super-resolution (STED, PALM/STORM, SIM) below the diffraction limit, light-sheet for deep live imaging, whole-slide imaging for the entire slide, and in vivo imaging (fluorescence, bioluminescence). Analysis, for its part, ranges from manual counting to automated segmentation and reproducible pipelines.
When and why these techniques
Quantitative imaging is essential when the information is spatial or dynamic: subcellular localisation, colocalisation of partners, cell-to-cell heterogeneity, or tracking a process over time that “population-average” measurements (western blot, qPCR) could not capture. Confocal excels on thick samples and for 3D; spinning-disk and light-sheet, for fast live dynamics; super-resolution, for details below the optical limit.
These possibilities nonetheless come up against physical constraints. Classical fluorescence microscopy is bounded by the diffraction limit (lateral resolution of about 200 nm), which only super-resolution crosses. In live cells, illumination causes phototoxicity and photobleaching: each image “costs” light, hence a permanent trade-off between resolution, speed, depth and preservation of the sample (spinning-disk and light-sheet reduce this dose). Confocal has a limited penetration depth and remains slower in point-by-point scanning. Finally, any quantitative measurement requires standardised acquisition and controls: without constant settings, controlled segmentation and appropriate corrections, intensity is not comparable from one field or experiment to another.
Inovarion’s expertise
Inovarion treats microscopy as a measurement, from acquisition to quantification. Three published examples illustrate this: the quantification, by confocal imaging and micro-patterning, of the nucleo-cytoplasmic translocation of a mechanotransduction factor in muscle stem cells carrying mutations; the in vivo tracking, by longitudinal fluorescence imaging, of the malignant transformation of a single cell through to the development of a tumour; and single-cell time-lapse imaging of the growth status of intracellular bacteria within macrophages. Labelling, acquisition modality and image analysis under Fiji or QuPath are chosen here according to the quantity to be measured.
See also: Immunohistochemistry & multiplex immunofluorescence ; Flow cytometry ; In vivo & preclinical models.
Key publications
- Owens et al. Lamin Mutations Cause Increased YAP Nuclear Entry in Muscle Stem Cells. Cells, 2020. PubMed
- Scerbo et al. In vivo targeted and deterministic single-cell malignant transformation. eLife, 2025. Record → · PubMed
- Demarre et al. The Crohn’s disease-associated Escherichia coli strain LF82 relies on SOS and stringent responses to survive, multiply and tolerate antibiotics within macrophages. PLoS Pathogens, 2019. PubMed