Immune Cell Profiling
Immune Cell Profiling - Related Videos
15:39
Studying Organelle Dynamics in B Cells During Immune Synapse Formation
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Cited by 8 •
2019
Herein we describe two approaches to characterize cell polarization events in B lymphocytes during the formation of an IS. The first, involves quantification of organelle recruitment and cytoskeleton rearrangements at the synaptic membrane. The second is a biochemical approach, to characterize changes in composition of the centrosome, which undergoes polarization to the immune synapse.
07:26
Isolation of Functional Cardiac Immune Cells
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Cited by 9 •
2011
This method for isolating functional immune cells from the heart provides an alternative to the conventional methods of collagenase digestion, which causes unwanted immune cell activation, resulting in a decreased responsiveness of these cells. Our method of isolation yields functional cardiac immune cells by avoiding problems associated with enzymatic digestion.
06:28
Isolating Immune Cells from Mouse Brain and Skull
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Cited by 1 •
2024
To investigate the immune response to brain disorders, one common approach is to analyze changes in immune cells. Here, two simple and effective protocols are provided for isolating immune cells from murine brain tissue and skull bone marrow.
05:07
Isolation, Characterization and Functional Examination of the Gingival Immune Cell Network
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Cited by 30 •
2016
We have established a technique for the isolation, phenotypic characterization and functional analysis of immune cells from murine gingiva.
10:20
Single-cell Profiling of Developing and Mature Retinal Neurons
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Cited by 13 •
2012
A method for the isolation of single retinal cells and subsequent amplification of their cDNAs is described. Single-cell transcriptomics reveals the degree of cellular heterogeneity present in a tissue and uncovers new marker genes for rare cell populations. The accompanying protocol can be adjusted to suit many different cell types.
FAQs
Marker combinations distinguish closely related immune populations by examining cell-surface features together with intracellular signals. This layered view can indicate whether cells are activated, functionally altered, or responding differently within the same sample. As a result, profiling can connect changes in specific cellular states with infection, cancer, autoimmune disorders, or inflammatory disease.
These approaches emphasize different kinds of measurements. Flow cytometry and mass cytometry can characterize populations through combinations of cell-surface and intracellular markers, whereas single-cell sequencing can reveal cell-by-cell differences in gene expression. Choosing among them depends on whether the investigation prioritizes marker-defined populations, signaling-related features, or transcriptional variation.
A sample may contain multiple immune populations with distinct activation states and functional properties, so an overall measurement can conceal meaningful differences between cells. Resolving this heterogeneity helps researchers determine which populations change in disease and whether those changes relate to diagnosis, prognosis, treatment response, or the biological effects of an immunotherapy.
A typical workflow identifies relevant immune populations, measures cell-surface or intracellular markers, and evaluates activation or functional characteristics. Depending on the platform, investigators may also examine gene-expression changes or signaling patterns at the single-cell level. The resulting profile is then compared across health, disease, treatment conditions, or patient groups to identify informative differences.
Its uses extend across infection, cancer, autoimmune disorders, and inflammatory disease. Investigators can apply profiles to discover biomarkers, divide patients into biologically meaningful groups, monitor changes during treatment, and evaluate immunotherapies. These applications are valuable because cellular measurements can link immune-system variation with diagnosis, prognosis, and therapeutic outcomes.
Repeated or comparative profiles can show whether immune populations, activation states, or functional properties change in association with treatment. In immunotherapy studies, these measurements help assess the cellular response to the intervention and identify patterns associated with therapeutic outcomes. Such evidence can contribute to treatment monitoring, biomarker discovery, and patient stratification.