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Transcriptome sequencing reveals that LPS-triggered transcriptional responses in established microglia BV2 cell lines are poorly representative of primary microglia.

Das A, Kim SH, Arifuzzaman S, Yoon T, Chai JC, Lee YS, Park KS, Jung KH, Chai YG - J Neuroinflammation (2016)

Bottom Line: Established BV2 microglial cell lines have been the primary in vitro models used to study neuroinflammation for more than a decade because they reduce the requirement of continuously maintaining cell preparations and animal experimentation models.Importantly, we observed that previously unidentified TFs (i.e., IRF2, IRF5, IRF8, STAT1, STAT2, and STAT5A) and the epigenetic regulators KDM1A, NSD3, and SETDB2 were significantly and selectively expressed in primary microglia (PM).Collectively, these unprecedented findings demonstrate that established BV2 microglial cell lines are probably a poor representation of PM, and we establish a resource for future studies of neuroinflammation.

View Article: PubMed Central - PubMed

Affiliation: Institute of Natural Science and Technology, Hanyang University, Ansan, 15588, Republic of Korea.

ABSTRACT

Background: Microglia are resident myeloid cells in the CNS that are activated by infection, neuronal injury, and inflammation. Established BV2 microglial cell lines have been the primary in vitro models used to study neuroinflammation for more than a decade because they reduce the requirement of continuously maintaining cell preparations and animal experimentation models. However, doubt has recently been raised regarding the value of BV2 cell lines as a model system.

Methods: We used triplicate RNA sequencing (RNA-seq) to investigate the molecular signature of primary and BV2 microglial cell lines using two transcriptomic techniques: global transcriptomic biological triplicate RNA-seq and quantitative real-time PCR. We analyzed differentially expressed genes (DEGs) to identify transcription factor (TF) motifs (-950 to +50 bp of the 5' upstream promoters) and epigenetic mechanisms.

Results: Sequencing assessment and quality evaluation revealed that primary microglia have a distinct transcriptomic signature and express a unique cluster of transcripts in response to lipopolysaccharide. This microglial signature was not observed in BV2 microglial cell lines. Importantly, we observed that previously unidentified TFs (i.e., IRF2, IRF5, IRF8, STAT1, STAT2, and STAT5A) and the epigenetic regulators KDM1A, NSD3, and SETDB2 were significantly and selectively expressed in primary microglia (PM). Although transcriptomic alterations known to occur in BV2 microglial cell lines were identified in PM, we also observed several novel transcriptomic alterations in PM that are not frequently observed in BV2 microglial cell lines.

Conclusions: Collectively, these unprecedented findings demonstrate that established BV2 microglial cell lines are probably a poor representation of PM, and we establish a resource for future studies of neuroinflammation.

No MeSH data available.


Related in: MedlinePlus

RNA-seq analyses reveals LPS-induced inflammatory response-related genes and their downstream effectors in BV2 cell lines and PM. a A heat map representing the top 150 inflammatory genes that were up-regulated by 2- and 4-h LPS stimulation in BV2 cell lines and PM (P ≤ 0.01, and log2 fold change ≥1.5). Each row shows the relative expression level for a single gene, and each column shows the expression level of a single sample. Biological replicates (n = 3) for each condition were performed. b, c Pie chart displaying the number of up or down-regulated genes at 4-h LPS stimulation in BV2 cell lines and PM. d The area of overlap indicates the number of unique or shared up-regulated genes after 4 h of LPS stimulation in BV2 cell lines and PM. e, f Gene ontology analysis of the functional annotations that were associated with the top 150 up-regulated genes at 4 h after LPS stimulation in the BV2 cell lines and PM
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Fig2: RNA-seq analyses reveals LPS-induced inflammatory response-related genes and their downstream effectors in BV2 cell lines and PM. a A heat map representing the top 150 inflammatory genes that were up-regulated by 2- and 4-h LPS stimulation in BV2 cell lines and PM (P ≤ 0.01, and log2 fold change ≥1.5). Each row shows the relative expression level for a single gene, and each column shows the expression level of a single sample. Biological replicates (n = 3) for each condition were performed. b, c Pie chart displaying the number of up or down-regulated genes at 4-h LPS stimulation in BV2 cell lines and PM. d The area of overlap indicates the number of unique or shared up-regulated genes after 4 h of LPS stimulation in BV2 cell lines and PM. e, f Gene ontology analysis of the functional annotations that were associated with the top 150 up-regulated genes at 4 h after LPS stimulation in the BV2 cell lines and PM

Mentions: To gain a comprehensive understanding of the mechanisms involved and to directly compare how TLR4 stimulation alters the transcriptomic profile of BV2 cell lines and PM, RNA-seq experiments were performed. Next, we performed principal component analysis (PCA) using DESeq2 to examine congruency among biological replicates. PCA analysis showed a good separation and high level of consistency between biological replicates of the same population in BV2 cell lines and PM (Additional file 2: Figure S2). According to the above criteria, 237 genes for 2 h and 331 genes for 4 h were differentially regulated following LPS treatment BV2 cell lines. Of these, 205 and 299 genes were up-regulated, and 32 genes were down-regulated at 2 and 4 h, respectively, after LPS treatment in BV2 cell lines (Fig. 2b; Additional file 3: Figure S3). Surprisingly, we found significant generational differences in PM, in which 531 genes for 2 h and 1286 genes for 4 h were differentially regulated. Of these, 362 and 946 genes were up-regulated, and 169 and 340 genes were down-regulated at 2 and 4 h, respectively, after LPS treatment (Fig. 2c; Additional file 3: Figure S3), in contrast to our previous studies showing that differentially expressed genes in the BV2 cell lines were less pronounced at 2 and 4 h after LPS treatment [20, 31]. In this analysis, we have increased biological duplicate to biological triplicate RNA-seq as well as P value less than 0.01 for differential expression genes, which reduces the number of differential expression genes in the BV2 cell lines after 2- and 4-h LPS treatment. In addition, differences in the passage number and intrinsic variability of cells may lead to these discrepancies. The genes were grouped into several categories based on their biological processes and molecular gene ontology functions, and heat maps were generated to aid the visualization of the gene expression pattern. The top 150 inflammatory genes that were up-regulated at 2 and 4 h after LPS stimulation in BV2 and PM cells are shown in Fig. 2a. Next, we performed functional classification analyses of the up-regulated genes using DAVID Bioinformatics Resources [27] by classifying the results into gene ontology (GO) categories (FDR 0.05) using the biological process (BP) and molecular function (MF) categories. We observed that in both BV2 cell lines and PM, the top 150 genes that were up-regulated in response to 4-h LPS stimulation were mainly involved in the immune system process and multi-organism processes (Fig. 2e, f). Because the down-regulated genes were not associated with inflammation, only the up-regulated genes were further studied. We confirmed using GO analysis (FDR 0.05) and DAVID Bioinformatics Resources that the top 150 transcripts that were down-regulated by 4-h LPS stimulation in PM were associated with the developmental process and regulation of GTPase activity (Additional file 4: Figure S4).Fig. 2


Transcriptome sequencing reveals that LPS-triggered transcriptional responses in established microglia BV2 cell lines are poorly representative of primary microglia.

Das A, Kim SH, Arifuzzaman S, Yoon T, Chai JC, Lee YS, Park KS, Jung KH, Chai YG - J Neuroinflammation (2016)

RNA-seq analyses reveals LPS-induced inflammatory response-related genes and their downstream effectors in BV2 cell lines and PM. a A heat map representing the top 150 inflammatory genes that were up-regulated by 2- and 4-h LPS stimulation in BV2 cell lines and PM (P ≤ 0.01, and log2 fold change ≥1.5). Each row shows the relative expression level for a single gene, and each column shows the expression level of a single sample. Biological replicates (n = 3) for each condition were performed. b, c Pie chart displaying the number of up or down-regulated genes at 4-h LPS stimulation in BV2 cell lines and PM. d The area of overlap indicates the number of unique or shared up-regulated genes after 4 h of LPS stimulation in BV2 cell lines and PM. e, f Gene ontology analysis of the functional annotations that were associated with the top 150 up-regulated genes at 4 h after LPS stimulation in the BV2 cell lines and PM
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Fig2: RNA-seq analyses reveals LPS-induced inflammatory response-related genes and their downstream effectors in BV2 cell lines and PM. a A heat map representing the top 150 inflammatory genes that were up-regulated by 2- and 4-h LPS stimulation in BV2 cell lines and PM (P ≤ 0.01, and log2 fold change ≥1.5). Each row shows the relative expression level for a single gene, and each column shows the expression level of a single sample. Biological replicates (n = 3) for each condition were performed. b, c Pie chart displaying the number of up or down-regulated genes at 4-h LPS stimulation in BV2 cell lines and PM. d The area of overlap indicates the number of unique or shared up-regulated genes after 4 h of LPS stimulation in BV2 cell lines and PM. e, f Gene ontology analysis of the functional annotations that were associated with the top 150 up-regulated genes at 4 h after LPS stimulation in the BV2 cell lines and PM
Mentions: To gain a comprehensive understanding of the mechanisms involved and to directly compare how TLR4 stimulation alters the transcriptomic profile of BV2 cell lines and PM, RNA-seq experiments were performed. Next, we performed principal component analysis (PCA) using DESeq2 to examine congruency among biological replicates. PCA analysis showed a good separation and high level of consistency between biological replicates of the same population in BV2 cell lines and PM (Additional file 2: Figure S2). According to the above criteria, 237 genes for 2 h and 331 genes for 4 h were differentially regulated following LPS treatment BV2 cell lines. Of these, 205 and 299 genes were up-regulated, and 32 genes were down-regulated at 2 and 4 h, respectively, after LPS treatment in BV2 cell lines (Fig. 2b; Additional file 3: Figure S3). Surprisingly, we found significant generational differences in PM, in which 531 genes for 2 h and 1286 genes for 4 h were differentially regulated. Of these, 362 and 946 genes were up-regulated, and 169 and 340 genes were down-regulated at 2 and 4 h, respectively, after LPS treatment (Fig. 2c; Additional file 3: Figure S3), in contrast to our previous studies showing that differentially expressed genes in the BV2 cell lines were less pronounced at 2 and 4 h after LPS treatment [20, 31]. In this analysis, we have increased biological duplicate to biological triplicate RNA-seq as well as P value less than 0.01 for differential expression genes, which reduces the number of differential expression genes in the BV2 cell lines after 2- and 4-h LPS treatment. In addition, differences in the passage number and intrinsic variability of cells may lead to these discrepancies. The genes were grouped into several categories based on their biological processes and molecular gene ontology functions, and heat maps were generated to aid the visualization of the gene expression pattern. The top 150 inflammatory genes that were up-regulated at 2 and 4 h after LPS stimulation in BV2 and PM cells are shown in Fig. 2a. Next, we performed functional classification analyses of the up-regulated genes using DAVID Bioinformatics Resources [27] by classifying the results into gene ontology (GO) categories (FDR 0.05) using the biological process (BP) and molecular function (MF) categories. We observed that in both BV2 cell lines and PM, the top 150 genes that were up-regulated in response to 4-h LPS stimulation were mainly involved in the immune system process and multi-organism processes (Fig. 2e, f). Because the down-regulated genes were not associated with inflammation, only the up-regulated genes were further studied. We confirmed using GO analysis (FDR 0.05) and DAVID Bioinformatics Resources that the top 150 transcripts that were down-regulated by 4-h LPS stimulation in PM were associated with the developmental process and regulation of GTPase activity (Additional file 4: Figure S4).Fig. 2

Bottom Line: Established BV2 microglial cell lines have been the primary in vitro models used to study neuroinflammation for more than a decade because they reduce the requirement of continuously maintaining cell preparations and animal experimentation models.Importantly, we observed that previously unidentified TFs (i.e., IRF2, IRF5, IRF8, STAT1, STAT2, and STAT5A) and the epigenetic regulators KDM1A, NSD3, and SETDB2 were significantly and selectively expressed in primary microglia (PM).Collectively, these unprecedented findings demonstrate that established BV2 microglial cell lines are probably a poor representation of PM, and we establish a resource for future studies of neuroinflammation.

View Article: PubMed Central - PubMed

Affiliation: Institute of Natural Science and Technology, Hanyang University, Ansan, 15588, Republic of Korea.

ABSTRACT

Background: Microglia are resident myeloid cells in the CNS that are activated by infection, neuronal injury, and inflammation. Established BV2 microglial cell lines have been the primary in vitro models used to study neuroinflammation for more than a decade because they reduce the requirement of continuously maintaining cell preparations and animal experimentation models. However, doubt has recently been raised regarding the value of BV2 cell lines as a model system.

Methods: We used triplicate RNA sequencing (RNA-seq) to investigate the molecular signature of primary and BV2 microglial cell lines using two transcriptomic techniques: global transcriptomic biological triplicate RNA-seq and quantitative real-time PCR. We analyzed differentially expressed genes (DEGs) to identify transcription factor (TF) motifs (-950 to +50 bp of the 5' upstream promoters) and epigenetic mechanisms.

Results: Sequencing assessment and quality evaluation revealed that primary microglia have a distinct transcriptomic signature and express a unique cluster of transcripts in response to lipopolysaccharide. This microglial signature was not observed in BV2 microglial cell lines. Importantly, we observed that previously unidentified TFs (i.e., IRF2, IRF5, IRF8, STAT1, STAT2, and STAT5A) and the epigenetic regulators KDM1A, NSD3, and SETDB2 were significantly and selectively expressed in primary microglia (PM). Although transcriptomic alterations known to occur in BV2 microglial cell lines were identified in PM, we also observed several novel transcriptomic alterations in PM that are not frequently observed in BV2 microglial cell lines.

Conclusions: Collectively, these unprecedented findings demonstrate that established BV2 microglial cell lines are probably a poor representation of PM, and we establish a resource for future studies of neuroinflammation.

No MeSH data available.


Related in: MedlinePlus