24?h after seeding, transfection complexes were prepared using 50?ng per well of various DNA constructs, using 0

24?h after seeding, transfection complexes were prepared using 50?ng per well of various DNA constructs, using 0.13?l of TransIT-X2 (Mirus MIR6003) in a final reaction volume of 20?l OptiMEM. and organisation of the reticular network. Due to its complex morphology, image analysis methods to quantitatively describe this organelle, and importantly any changes to it, are lacking. Results In this work we detail a methodological approach that utilises automated high-content screening microscopy to NVP-BGT226 capture images of cells fluorescently-labelled for numerous ER markers, followed by their quantitative analysis. We propose that two important metrics, namely the area of dense ER and the area of polygonal regions in between the NVP-BGT226 reticular elements, together provide a basis for measuring the quantities of rough and easy ER, respectively. We demonstrate that a quantity of different pharmacological perturbations to the ER can be quantitatively measured and compared in our automated image analysis pipeline. Furthermore, we show that this method can be implemented in both commercial and open-access image analysis software with comparable results. Conclusions We propose that this method has the potential to be applied in the context of large-scale genetic and chemical Rabbit polyclonal to HYAL1 perturbations to assess the organisation of the ER in adherent cell cultures. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04334-x. ER marker. Similarly, we observed a high signal of the ER lipid-raft associated protein (ERLIN2) [54], the E3 ubiquitin-protein ligase synoviolin (SYVN1) [55], and a subunit of the oligosaccharyltransferase complex A (OST-A) Magnesium Transporter 1 (MAGT1) [56] YFP-tagged proteins on ER structures in U-2 OS cells (Fig.?6A). We adapted our previously explained pipeline designed for Sec61-mEmerald for each of these markers (Additional file 2: Appendix 1, Table 2) and successfully obtained metrics for ER polygon region area and % dense RER in proportion to cell area (Fig.?6B, C). Open in a separate windows Fig. 6 Analysis of ER distribution in U-2 OS cells using numerous ER markers. A Images of a single cell showing sequential analysis of SER polygon regions (columns 2 and 3) and dense RER (columns 4, 5 and 6) in U-2 OS cells expressing numerous constructs that label the ER (GOLT1B-YFP, ERIN2-YFP, SYVN1-YFP and MAGT1-YFP) (column 1). B Quantification of ER polygon region common size. C Quantification of % of dense ER in cell cytoplasm in U-2 OS cells expressing each ER-localising protein. D Representative images of U-2 OS cells showing sequential analysis of dense RER (columns 2, 3 and 4) labelled with anti-Reep5 antibody and ER Tracker? (column 1) and quantification of % of dense ER in cell cytoplasm (E). Data are expressed as mean??SEM (n?=?3C4 independent experiments comprising??50 cells each). All level bars?=?20?m Finally, we wanted to assess the applicability of our method beyond the use of over-expressed fluorescently-tagged proteins. To this end, we first used an immunofluorescence approach, applying our pipeline to immunolabelled ER-resident proteins. Several of the antibodies we tested only gave a low signal-to-noise ratio. We obtained the best results with an antibody against Reep5, although staining in the cell periphery was poor and did not show continuous tubules (Fig.?6D) precluding analysis of the polygon area. However, we were able to determine the proportion of dense RER in relation to cell area using the anti-Reep5 antibody, as it provided a strong stain in the perinuclear area (Fig.?6D, E). Similarly, the frequently used ER Tracker dye failed to strongly label SER tubules but enabled analysis of dense RER structures using our pipeline (Fig.?6D, E). Together, these results indicate that our analysis pipeline is compatible with a range of ER markers, while they also suggest caution in their choice, considering the advantages and limitations of each individual maker. Discussion In this study we present an automated image analysis pipeline for the quantitative assessment of the ER using high-content fluorescence microscopy. Until now, the majority of studies reporting on ER morphology have been qualitative; i.e. describing the organelle as normal or abnormal. Qualitative studies are limited to the visual detection of gross changes, such as may occur under high levels of stress or cell toxicity, but often fail to detect more delicate, yet NVP-BGT226 physiologically relevant, changes. When quantitative analysis has been undertaken, it has been manually applied [57], an approach which is so labour intensive that it precludes its application to high-throughput screening as would be required to identify novel targets which could change disease-associated ER alterations. Here we present two novel quantitative features that describe the ER, namely the SER tubule polygon area and the proportion of dense RER in the cell..

Categories p53