Dataset Information

FEAST: A flow cytometry-based toolkit for interrogating microglial engulfment of synaptic and myelin proteins.

ABSTRACT: Although engulfment is a hallmark of microglia function, fully validated platforms that facilitate high-throughput quantification of this process are lacking. Here, we present FEAST (Flow cytometric Engulfment Assay for Specific Target proteins), which enables interrogation of in vivo engulfment of synaptic material by brain resident macrophages at single-cell resolution. We optimize FEAST for two different analyses: quantification of fluorescent material inside live cells and of engulfed endogenous proteins within fixed cells. To overcome false-positive engulfment signals, we introduce an approach suitable for interrogating engulfment in microglia from perfusion-fixed tissue. As a proof-of-concept for the specificity and versatility of FEAST, we examine the engulfment of synaptic proteins after optic nerve crush and of myelin in two mouse models of demyelination (treatment with cuprizone and injections of lysolecithin). We find that microglia, but not brain-border associated macrophages, engulf in these contexts. Our work underscores how FEAST can be utilized to gain critical insight into functional neuro-immune interactions that shape development, homeostasis, and disease.

SUBMITTER: Dissing-Olesen L

PROVIDER: S-EPMC10533836 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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FEAST: A flow cytometry-based toolkit for interrogating microglial engulfment of synaptic and myelin proteins.

Dissing-Olesen Lasse L Walker Alec J AJ Feng Qian Q Barr Helena J HJ Walker Alicia C AC Xie Lili L Wilton Daniel K DK Das Indrani I Benowitz Larry I LI Stevens Beth B

Nature communications 20230927 1

Although engulfment is a hallmark of microglia function, fully validated platforms that facilitate high-throughput quantification of this process are lacking. Here, we present FEAST (Flow cytometric Engulfment Assay for Specific Target proteins), which enables interrogation of in vivo engulfment of synaptic material by brain resident macrophages at single-cell resolution. We optimize FEAST for two different analyses: quantification of fluorescent material inside live cells and of engulfed endoge ...[more]

PMID: 37758703

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Project description:Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

Dataset Information

FEAST: A flow cytometry-based toolkit for interrogating microglial engulfment of synaptic and myelin proteins.

Publications

FEAST: A flow cytometry-based toolkit for interrogating microglial engulfment of synaptic and myelin proteins.

Similar Datasets

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