School of Molecular & Cell Biology (ETDs)

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Browsing School of Molecular & Cell Biology (ETDs) by Author "Gentle, Nikki"

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    Differential expression analysis of PMA and 1,25(OH)2D3-induced monocyte-to-macrophage differentiation in THP-1 cells
    (University of the Witwatersrand, Johannesburg, 2023-09) Perumal, Kelda Chloe; Meyer, Vanessa; Gentle, Nikki
    The process of monocyte-to-macrophage differentiation is studied in vitro through the use of promonocytic model cell lines, such as the THP-1 cell line, where commonly used differentiation inducing agents include phorbol-12-myristate-13-acetate (PMA) and the active metabolite of vitamin D3, (1,25(OH)2D3; VD3). While both induce differentiation, differences in their mechanisms of action, as well as how the end states of the differentiation process differ, are not well understood. Therefore, this study used computational approaches to compare the effects of PMA and VD3 on the differentiation of monocytes into macrophages, using the promonocytic THP-1 cell line. Through the use of RNA-sequencing, gene expression was quantified in differentiated and undifferentiated THP-1 cells, treated with both PMA and VD3. Differential gene expression analysis was performed to determine genes that were differentially expressed as a result of either treatment relative to the untreated cells. This was followed by over-representation analysis to determine the pathways and processes in which the differentially expressed genes (DEGs) were involved. PMA treatment (3 989 DEGs) resulted in more changes in expression relative to VD3 treatment, where only 384 genes were found to be differentially expressed in response to treatment with VD3. Only TFE3, KIT and TRIB1 were observed to be crucial to the process of differentiation, irrespective of treatment. Apart from this, the treatments were observed to largely involve different biological pathways, resulting in cells that were phenotypically distinct from each other at the transcriptional level. This included changes observed in the expression of genes encoding transcription factors known to be involved in the differentiation process, such as CEBPA, GATA2, IRF8 and PU.1, as well as those encoding surface markers representative of monocytes and macrophages, such as CD14, CD64 and CD11b. The expression patterns observed here indicate that, at least at the concentrations and time points included in this study, PMA and VD3 induce macrophage-like cells that are at different stages of differentiation and are not comparable to either each other or primary macrophages. Furthermore, key differences observed in the expression of genes encoding pathogen recognition receptors and cytokines suggest that which differentiation inducing agent is used may have important implications for these cells’ capacity to recognise pathogens and produce cytokines. The findings of this study therefore emphasise that it is crucial to carefully consider the choice of differentiation-inducing agent when using THP-1 cells as an experimental system for studying monocyte-to-macrophage differentiation.
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    Differential Gene Expression Analysis of PMA Treated Pro-monocytic Cell Lines
    (University of the Witwatersrand, Johannesburg, 2023) Kama, Asavela Olona; Meyer, Vanessa; Gentle, Nikki
    HL-60, THP-1, and U937 are model cell lines that can undergo myeloid differentiation in vitro, allowing the study of myeloid cell function in drug metabolism, cytotoxicity, and the aetiology of infections. However, the differentiated end-state of these cells is not well characterised. Moreover, cell line-specific differences in the level of gene expression may confound results obtained from such studies. The aim of this study was thus to compare changes in gene expression between HL-60, THP-1, and U937 cells in response to the differentiation agent, phorbol 12-myristate 13-acetate (PMA), 48 hours after treatment. Gene expression profiles were compared across all three cell lines prior to and post-PMA treatment. Differential gene expression analysis between treated and untreated cells was performed using DESeq2 (v 4.2). Gene over-representation analysis was performed using cluster Profiler (v 4.0). HL-60, THP-1, and U937 cells had similar expression profiles prior to PMA treatment, but different sets of genes were significantly differentially expressed in these cell lines 48 h after treatment with PMA. A total of 475 genes were consistently differentially expressed across all cell lines. These genes were found to be involved in phagosome formation and cell cycle transition. HL-60, THP-1, and U937 cells had 944, 1231, and 624 uniquely differentially expressed genes, respectively. These genes were predominantly involved in energy metabolism and pathogen recognition. Overall, THP-1 cells showed greater potential to detect viruses, while U937 cells showed greater potential to detect bacteria. From this, it can be concluded that while all three cell lines did indeed undergo myeloid differentiation, the macrophage-like cell state produced in each case differed between cell lines.
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    Using ChIP-seq and Gene Expression Microarray data to explore transcriptional dysregulation of PXDN and PXDNL in cardiovascular diseases
    (University of the Witwatersrand, Johannesburg, 2024) Naidoo, Shiven; Gentle, Nikki; Mavri-Damelin, Demetra
    Background: Cardiovascular diseases (CVDs) remain one of the leading causes of death globally. The genes PXDN and PXDNL are both expressed in the cardiovascular system, and their dysregulation has been linked to various disorders, including CVDs, but little is known of their transcriptional regulation in the cardiovascular system or their roles in CVD pathogenesis. Methods: This study developed two custom bioinformatics pipelines in R to mine and analyse ChIP-seq data from ChIP-Atlas and gene expression microarray data from the Gene Expression Omnibus (GEO). The first pipeline used ChIPseeker to identify regulatory transcription factors (TFs) of PXDN and PXDNL in cardiovascular cells and tissues. ChIP-seq data from 400 experiments across 63 TFs was filtered to isolate TFs with high confidence binding peaks in the promoter and first intron of PXDN and PXDNL. The second pipeline used R Bioconductor packages to explore the expression profiles of PXDN, PXDNL, and their TFs in seven microarray datasets across three CVD-related contexts: cardiomyopathies, heart failure and TNF-α stimulation. Results and discussion: This study identified 27 TFs binding to PXDN and 18 TFs binding to PXDNL in cardiovascular cells. Sixteen of these TFs were shared by both PXDN and PXDNL, suggesting potential coregulatory mechanisms in cardiovascular cells where they are both expressed. Unique TFs were also identified for PXDN (11) and PXDNL (2). Differential gene expression analysis revealed no significant change in expression (log2FC > 0.5; p.adj < 0.05) for PXDN, PXDNL and many of their identified TFs in the CVD-related conditions investigated, suggesting that changes at the transcript level may not contribute to the progression of these conditions. Conclusions: This study advances our understanding of the transcriptional regulation of PXDN and PXDNL in healthy cardiovascular cells as well as their expression levels in the investigated CVD-related contexts. This study also contributes a bioinformatics pipeline which can be further developed and applied to analysing data from ChIP-Atlas and GEO. Future research can elucidate the roles of each TF in regulating PXDN and PXDNL in healthy and diseased cell lines