Intracellular Load Quantification
Intracellular Load Quantification - Related Videos
03:52
Quantification of Bacterial Load in Mouse Spleen and Liver After Systemic Infection
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2026
Source: Ahn, J. J., et al. Experimental Infection with Listeria monocytogenes as a Model for Studying Host Interferon-γ Responses. J. Vis. Exp. (2016)The video demonstrates bacterial load measurement in spleen and liver tissues isolated from mice infected with an intracellular bacterial pathogen. Bacteria, accumulated within tissue-resident phagocytes during systemic infection, are released using detergent-based lysis and mechanical disruption. Serial dilutions of the homogenates are plated on...
15:28
A Microscopic Phenotypic Assay for the Quantification of Intracellular Mycobacteria Adapted for High-throughput/High-content Screening
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Cited by 30 •
2014
Here, we describe a phenotypic assay applicable to the High-throughput/High-content screens of small-interfering synthetic RNA (siRNA), chemical compound, and Mycobacterium tuberculosis mutant libraries. This method relies on the detection of fluorescently labeled Mycobacterium tuberculosis within fluorescently labeled host cell using automated confocal microscopy.
11:54
Optical Quantification of Intracellular pH in Drosophila melanogaster Malpighian Tubule Epithelia with a Fluorescent Genetically-encoded pH Indicator
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Cited by 9 •
2017
Cellular ion transport can often be assessed by monitoring intracellular pH (pHi). Genetically Encoded pH-Indicators (GEpHIs) provide optical quantification of intracellular pH in intact cells. This protocol details the quantification of intracellular pH through cellular ex vivo live-imaging of Malpighian tubules of Drosophila melanogaster with pHerry, a pseudo-ratiometric genetically encoded pH-indicator.
02:49
Quantification of Helicobacter pylori Load in an Infected Mouse Stomach
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2025
In this video, we describe a protocol to quantify Helicobacter pylori load in mouse stomach tissues post-infection to confirm its colonization.
12:58
Visualisation and Quantification of Intracellular Interactions of Neisseria meningitidis and Human α-actinin by Confocal Imaging
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2010
Neisseria meningitidis (Nm), a gram negative human-specific respiratory pathogen, can bind to human α-actinin. Here we present a protocol for visualisation of colocalisation of the bacterium with intracellular α-actinin after bacterial entry into human brain microvascular endothelial cells (HBMECs).
FAQs
Removing or quenching extracellular material is the key control for separating internalization from surface association. A signal measured before that step can include cargo attached to the outside of cells, whereas the treated sample is intended to represent material retained inside. This distinction is essential when interpreting uptake measurements for nanoparticles, drugs, nucleic acids, or pathogens.
Measured load can vary with cell type, exposure dose, internalization, retention, and intracellular trafficking. Thus, two populations receiving the same treatment may produce different signals because they handle the cargo differently, while a changing signal across doses may reflect a dose-response relationship. Examining these variables helps connect assay output with cell biology rather than treating signal as uptake alone.
Microscopy, flow cytometry, and biochemical analysis are alternative readout platforms for the resulting signal. Their use can be matched to the experimental question, including whether the study examines individual cells or a cell population. Each approach can assess intracellular accumulation after extracellular material has been removed or quenched, allowing normalized comparisons across experimental conditions.
Normalization makes intracellular-load values more comparable between samples. Reporting signal relative to cell number, protein content, or cell volume helps account for differences in the amount of biological material analyzed. This is especially important when cell populations differ in size or abundance, because an unadjusted total signal could reflect sample quantity rather than a change in cargo accumulation.
A typical assay labels the cargo, applies the experimental exposure, removes or quenches material outside the cells, and then measures the remaining signal. Researchers express that signal relative to cell number, protein content, or volume. Applying the same sequence across cell types or conditions supports comparisons of internalization, retention, trafficking, and dose response.
Researchers apply these measurements to drug delivery, infection, toxicity, membrane transport, and nanomaterial performance. The assay can show whether a treatment reaches cells and whether pathogens or cargo accumulate differently across conditions. These outcomes help evaluate delivery systems and biological responses while distinguishing intracellular accumulation from material that remains associated with the cell surface.
For nanomaterial studies, intracellular load quantification links particle-associated signal to cellular accumulation rather than simply exposure outside the cells. Measurements across cell types or experimental conditions can reveal differences in uptake, retention, trafficking, and dose response. This makes the approach useful for comparing nanomaterial performance and investigating how cellular handling may influence biological outcomes.