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PreprintCited by 149Single-cell and spatial transcriptomicsNeuroinflammation and Neurodegeneration MechanismsMolecular Biology Techniques and Applications

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Enzymatic dissociation induces transcriptional and proteotype bias in brain cell populations

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Mattei, Daniele, Ivanov, Andranik, van Oostrum, Marc, Pantelyushin, Stanislav, Richetto, Juliet, Mueller, Flavia, Beffinger, Michal Matheus, Schellhammer, Linda, vom Berg, Johannes, Wollscheid, Bernd, Beule, Dieter, Paolicelli, Rosa Chiara, Meyer, Urs·2020·International Journal of Molecular Sciences
DOI 10.1101/2020.05.14.095422PMC PMC7663484

Preprint — published as 10.3390/ijms21217944 · Paper page

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Abstract

Different cell isolation techniques exist for transcriptomic and proteotype profiling of brain cells. Here, we provide a systematic investigation of the influence of different cell isolation protocols on transcriptional and proteotype profiles in mouse brain tissue by taking into account single-cell transcriptomics of brain cells, proteotypes of microglia and astrocytes, and flow cytometric analysis of microglia. We show that standard enzymatic digestion of brain tissue at 37°C induces profound and consistent alterations in the transcriptome and proteotype of neuronal and glial cells, as compared to an optimized mechanical dissociation protocol at 4°C. These findings emphasize the risk of introducing technical biases and biological artefacts when implementing enzymatic digestion-based isolation methods for brain cell analyses.

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Figure 1 The cell isolation method affects the proportions of murine hippocampal cell populations. (a) Schematic illustration of the two cell isolation methods. Adult murine hippocampi were mechanically dissociated at 4 °C (MD4°) or digested enzymatically for 30-min at 37 °C (ED37°). After myelin removal, total hippocampal cells from both conditions were subjected to scRNA-seq. The photomicrographs show the shape of cells isolated via MD4° or ED37°. Note that cells isolated via MD4° appear larger and display discernible nuclei and cytoplasm (Scale bar: 25 µm). (b) Uniform manifold approximation and projection (UMAP) scores showing the clustering of cells isolated via ED37° (4448 cells) or MD4° (11868 cells). (c) Colored legends (left) represent the identities and total fractions for each cell type and the violin plots (right) show the cell identity based on the enriched expression of specific genes.
Figure 1 The cell isolation method affects the proportions of murine hippocampal cell populations. (a) Schematic illustration of the two cell isolation methods. Adult murine hippocampi were mechanically dissociated at 4 °C (MD4°) or digested enzymatically for 30-min at 37 °C (ED37°). After myelin removal, total hippocampal cells from both conditions were subjected to scRNA-seq. The photomicrographs show the shape of cells isolated via MD4° or ED37°. Note that cells isolated via MD4° appear larger and display discernible nuclei and cytoplasm (Scale bar: 25 µm). (b) Uniform manifold approximation and projection (UMAP) scores showing the clustering of cells isolated via ED37° (4448 cells) or MD4° (11868 cells). (c) Colored legends (left) represent the identities and total fractions for each cell type and the violin plots (right) show the cell identity based on the enriched expression of specific genes.CC BY · PubMed Central
Figure 2 The cell isolation protocol alters the transcriptional profile of mouse hippocampal glia and neuronal cells. (a) Scatter plots of the differential gene expression in microglia, astrocytes, and neurons obtained via ED37° relative to MD4°. Some examples of up- and downregulated genes following ED are highlighted in red in the scatterplots. (b) Feature plot magnification of the microglial population from adult mouse hippocampi displaying the expression of the immediate-early genes Jun and Fos. ED37 °C induces the appearance of a microglial population characterized by increased expression of immediate early genes (upper panel) which is barely present in microglia from hippocampi processed via MD4° (lower panel). (c) Selected gene ontology (GO) terms associated with significantly deregulated genes in microglia, astrocytes, and neurons (ED37° relative to MD4°). The bar color represents downregulation in ED37° relative to MD4° (blue) and upregulation in ED37° relative to MD4° (red). The intensity of the respective color indicates the adjusted p-value, while the size of the bars denotes the effect size, i.e., the area under the curve (AUC, see Figure S3b). Significantly different genes were determined by the threshold: log-fold change > 0.5, adjusted p-value cut-off < 0.01.
Figure 2 The cell isolation protocol alters the transcriptional profile of mouse hippocampal glia and neuronal cells. (a) Scatter plots of the differential gene expression in microglia, astrocytes, and neurons obtained via ED37° relative to MD4°. Some examples of up- and downregulated genes following ED are highlighted in red in the scatterplots. (b) Feature plot magnification of the microglial population from adult mouse hippocampi displaying the expression of the immediate-early genes Jun and Fos. ED37 °C induces the appearance of a microglial population characterized by increased expression of immediate early genes (upper panel) which is barely present in microglia from hippocampi processed via MD4° (lower panel). (c) Selected gene ontology (GO) terms associated with significantly deregulated genes in microglia, astrocytes, and neurons (ED37° relative to MD4°). The bar color represents downregulation in ED37° relative to MD4° (blue) and upregulation in ED37° relative to MD4° (red). The intensity of the respective color indicates the adjusted p-value, while the size of the bars denotes the effect size, i.e., the area under the curve (AUC, see Figure S3b). Significantly different genes were determined by the threshold: log-fold change > 0.5, adjusted p-value cut-off < 0.01.CC BY · PubMed Central
Figure 3 The cell isolation method affects the proteotype profiles of mouse microglia and astrocytes. (a) Schematic illustration of the main experimental procedure. Adult murine hippocampi were mechanically dissociated at 4 °C (MD4°) or digested enzymatically for 30 min at 37 °C (ED37°). After myelin removal, microglia or astrocytes where freshly isolated via magnetic associated cell sorting (MACS) for cell-specific proteotype analysis. (b,c) Volcano plots (top) and select gene ontology (GO) terms (bottom) of deregulated proteins in (b) microglia and (c) astrocytes obtained via ED37° relative to MD4°. N = 4 biological replicates/group. Significantly different proteins were determined by the threshold: fold-change > 2 and adjusted p-value < 0.01. Benjamini–Hochberg method was used to account for multiple testing. (d,e) Comparison of (d) microglial and (e) astrocytic RNA and protein expression differences between the two protocols. The top 50 differentially expressed genes (sorted by RNA adj. p-value), which were detected at both RNA and protein levels, are highlighted in the scatterplots. A significant correlation was detected for both microglia (R = 0.49, p = 0.00027) and astrocytes (R = 0.29, p = 0.043).
Figure 3 The cell isolation method affects the proteotype profiles of mouse microglia and astrocytes. (a) Schematic illustration of the main experimental procedure. Adult murine hippocampi were mechanically dissociated at 4 °C (MD4°) or digested enzymatically for 30 min at 37 °C (ED37°). After myelin removal, microglia or astrocytes where freshly isolated via magnetic associated cell sorting (MACS) for cell-specific proteotype analysis. (b,c) Volcano plots (top) and select gene ontology (GO) terms (bottom) of deregulated proteins in (b) microglia and (c) astrocytes obtained via ED37° relative to MD4°. N = 4 biological replicates/group. Significantly different proteins were determined by the threshold: fold-change > 2 and adjusted p-value < 0.01. Benjamini–Hochberg method was used to account for multiple testing. (d,e) Comparison of (d) microglial and (e) astrocytic RNA and protein expression differences between the two protocols. The top 50 differentially expressed genes (sorted by RNA adj. p-value), which were detected at both RNA and protein levels, are highlighted in the scatterplots. A significant correlation was detected for both microglia (R = 0.49, p = 0.00027) and astrocytes (R = 0.29, p = 0.043).CC BY · PubMed Central
Figure 4 Cell isolation method affects microglial surface and intracellular marker expression in flow cytometric analysis. Flow cytometric analysis of surface and intracellular marker expression levels on microglia after ED37° versus MD4°. (a) Representative 2D-flow cytometric plot overlay with adjunct histograms and (b) scatterplots comparing forward scatter (FSC-A, t8 = 5.439, p = 0.0006) and side scatter (SSC-A, t8 = 18, p < 0.0001). (c) Photomicrographs illustrating the cell shape after MD4° or ED4° (20x magnification). (d–g) Representative 2D-flow cytometric plot overlays with adjunct histograms and scatter plots comparing geometric mean fluorescence intensities (gMFIs) of surface and intracellular expression of (d) CD45 (t8 = 13.28, p < 0.0001), (e) CD11b (t8 = 5.288, p = 0.0007), (f) SIRPα (t8 = 5.213, p = 0.0004) and (g) FcγRI, (t8 = 1.030, p = 0.3). (h) A t-SNE clustering algorithm was used to depict CD11b expression in different populations of microglia. Left row showing relative intracellular CD11b expression levels for both conditions. The right row shows an overlay of the two conditions, as well as all populations overlaid with high CD11b ICS expression. (i) Scatterplot for the quantification of the CD11b intracellular signal for microglia isolated via MD4° versus ED37° (t8 = 24.43, p < 0.0001) Summary of two independent experiments, n = 4 and 5 biological replicates/group respectively. Unpaired two-tailed Student t-tests were used to compare the means. *** p < 0.001, **** p < 0.0001. Error bars represent the mean ± standard deviation.
Figure 4 Cell isolation method affects microglial surface and intracellular marker expression in flow cytometric analysis. Flow cytometric analysis of surface and intracellular marker expression levels on microglia after ED37° versus MD4°. (a) Representative 2D-flow cytometric plot overlay with adjunct histograms and (b) scatterplots comparing forward scatter (FSC-A, t8 = 5.439, p = 0.0006) and side scatter (SSC-A, t8 = 18, p < 0.0001). (c) Photomicrographs illustrating the cell shape after MD4° or ED4° (20x magnification). (d–g) Representative 2D-flow cytometric plot overlays with adjunct histograms and scatter plots comparing geometric mean fluorescence intensities (gMFIs) of surface and intracellular expression of (d) CD45 (t8 = 13.28, p < 0.0001), (e) CD11b (t8 = 5.288, p = 0.0007), (f) SIRPα (t8 = 5.213, p = 0.0004) and (g) FcγRI, (t8 = 1.030, p = 0.3). (h) A t-SNE clustering algorithm was used to depict CD11b expression in different populations of microglia. Left row showing relative intracellular CD11b expression levels for both conditions. The right row shows an overlay of the two conditions, as well as all populations overlaid with high CD11b ICS expression. (i) Scatterplot for the quantification of the CD11b intracellular signal for microglia isolated via MD4° versus ED37° (t8 = 24.43, p < 0.0001) Summary of two independent experiments, n = 4 and 5 biological replicates/group respectively. Unpaired two-tailed Student t-tests were used to compare the means. *** p < 0.001, **** p < 0.0001. Error bars represent the mean ± standard deviation.CC BY · PubMed Central

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Metadata

Authors
Mattei, D., Ivanov, A., van Oostrum, M., Pantelyushin, S., Richetto, J., Mueller, F., Beffinger, M. M., Schellhammer, L., vom Berg, J., Wollscheid, B., Beule, D., Paolicelli, R. C., & Meyer, U.
Affiliations
  • University of Zurich (CH)
  • Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
  • ETH Zurich (CH)
  • Max Delbrück Center (DE)
  • University of Lausanne (CH)
Corresponding author
  • Mattei, Daniele
  • Ivanov, Andranik
ORCID
Venue
International Journal of Molecular Sciences
Publisher
openRxiv
Published
2020-05-16
Volume
21
Issue
21
Pages
7944-7944
ISSN
1422-0067 (ISSN-L)
DOI
10.1101/2020.05.14.095422
PMC
PMC7663484
OpenAlex
W3097563614
Cited by
143
References
39
Citations by year
2026: 18 · 2025: 19 · 2024: 25 · 2023: 28 · 2022: 32 · 2021: 21
FWCI
6.65
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Molecular Sciences (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • SERVAL (Université de Lausanne) (publishedVersion, cc-by)
  • MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (acceptedVersion)
  • IRIS (submittedVersion, cc-by)
  • Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
  • ETH Zürich Research Collection (cc-by)
  • Zurich Open Repository and Archive (University of Zurich)
Funders
  • National Science Foundation
  • Novartis Foundation
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (160259, 188524, 180099, 310030)
  • Eidgenössische Technische Hochschule Zürich (grant ETH-25 15-2)
  • Novartis Stiftung für Medizinisch-Biologische Forschung (#16C231)
  • Universität Zürich
  • Swiss Cancer Research Foundation (KFS-3852-02-2016, KFS‐4146‐02‐2017)
  • European Research Council (804949)
  • Functional Genomics Center Zurich
  • H2020 European Research Council (804949)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
Keywords
enzymatic tissue dissociation, technical bias, microglia, astrocytes, neurons, mechanical dissociation, single-cell transcriptomics, flow cytometry, mouse brain
MeSH terms
Animals, Astrocytes, Brain Neoplasms, Cell Separation, Chromatography, Liquid, Enzymes, Flow Cytometry, Glioma, Humans, Male, Neoplasm Transplantation, Sequence Analysis, RNA, Microglia, Gene Expression Profiling, Proteomics, Cell Line, Tumor, Mice, Tandem Mass Spectrometry, Single-Cell Analysis

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