Chapter 4 Testing RCR expression and antiviral response in Balb/cJ mice
4.2 Materials and Methods
Animal research ethics approval was obtained from the UCT Health Sciences Animal Ethics Committee (AEC) in accordance with the Faculty of Health Sciences rules and regulations (AEC approval # 017/016).
4.2.1 Animal husbandry, welfare and care of Balb/cJ mice
Animal research experiments used female Balb/cJ (Jaxson Labs; USA) mice, bred as strain UCT4 at the specific pathogen free (SPF) level 2 animal breeding facility at UCT. After 8-10 weeks they were transferred to the UCT Research Animal Facility (RAF) where they remained for the duration of the study. Here the mice were housed, fed and monitored by the trained and certified RAF staff using the specialised facilities and equipment within the facility according to their standard operating procedure (SOP). All inoculations and procedures were performed on the animals by an experienced animal technologist.
4.2.2 Handling and inoculations
Mice were kept in groups of three and acclimatised to their environment for one week before inoculations were performed. Each mouse received a single 50 µl inoculation in the anterior tibialis muscle of the right hind limb on Day 0. The inoculations for the groups are outlined in Table 4.2.2.
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Table 4.2.2. Inoculation dosages for murine eGFP quantification
Mouse Group DNA included in inoculum Total volume RCR+ eGFP RCR- eGFP pTHRep
Group 1 50 µg - - 50 µl
Group 2 - 50 µg - 50 µl
Group 3 50 µg - 10 µg 50 µl
Neg Control - - 10 µg 50 µl
4.2.2 Animal euthanasia procedure and tissue harvesting
The mice were euthanised by exsanguination under general anaesthesia with ketamine/xylazine (200 μl per 20 g mouse) administered via intraperitoneal injection. Pedal reflex was used to determine depth of anaesthesia. If insufficient after 20 minutes, an additional ½ dose of ketamine/xylazine was administered. No pedal withdrawal after stimulation indicated that the depth of anaesthesia was sufficient for cardiac puncture and exsanguination. Animals were placed in dorsal recumbency, and a 26G needle was inserted adjacent the xiphoid cartilage and into the heart. A maximum of 1.8 mL of blood was collected and stored at 4 °C (Diehl et al., 2001). Exsanguination lasted between 1-3 minutes and therefore no warming, ocular lubrication or any other protocol while under anaesthesia was required. Death was confirmed by cervical dislocation of the neck. Thereafter their spleens and the anterior tibialis muscle of the inoculation site were harvested, placed in RPMI media, and put on ice.
4.2.3 Muscle tissue preparation and sectioning
To preserve eGFP expression a published protocol (Liadaki et al., 2007) was used. The harvested anterior tibialis muscle was fixed in 4% paraformaldehyde in PBS at 4°C overnight and then saturated in sterile 20% sucrose in PBS (0.22 μm filtered), for 4-24 h. The sample was then embedded in Frozen Section Compound (FSC) 22 (Leica, Germany) and frozen at -80°C until sectioning.
Sectioning was performed on a CM 1850 cryostat (Leica) where two 10 µM and two 20 µM cross sections were made for each muscle tissue at a depth of ¼ and ½ way through the muscle tissue.
Longitudinal sections were also made for each sample, ½ way through the tissue collecting two 10 µM and two 20 µM (as before). Slides were treated with a drop of Mowiol containing ~10 mg per ml n- propyl gallate as an antifade reagent. Cover slips were added, and samples allowed to dry overnight at RT, and stored at 4°C until confocal microscopy.
4.2.4 Confocal microscopy of muscle sections
A ZEISS LSM 880 Airyscan confocal microscope was used to quantify eGFP fluorescence in sectioned mouse muscle samples using a similar method as described previously in (Section 3.2.3.). However, this time image capturing was done as a series of z-stacks run in tile scans of up to 8x8 images and merged into a single giant z-stack image file for the full muscle cross section. This was transformed
110 into a maximum intensity projection for fluorescence quantification in the manner previously described (Section 3.2.3). This was only done for muscle cross sections where individual muscle fibre bundles could be identified and selected. Data was then tabulated and analysed in MS Excel. All images taken were done so using identical exposure and capture settings calibrated to the brightest fluorescence found in the sample to prevent the possibility of overexposure. Positive fluorescence was identified as those muscle fibre bundles exhibiting fluorescence readouts at least 2σ higher than the average background autofluorescence level recorded for the negative control. Data was normalised by quantifying the relative background fluorescence of untransfected muscle fibre bundles for each sample and subtracting this from the average positive muscle fibre bundles readout to determine the fluorescence attributable to eGFP as the true readout.
For longitudinally sectioned samples, an entirely different method of data analysis and quantification was employed. This was done using ImageJ Fiji, public software suite, (Open Source, Github) to calculate the mean integrated density of eGFP fluorescence over the entire longitudinal sectioned Z- stack tile scan. A cut-off threshold of 2σ from the mean of the negative control was used to eliminate background and autofluorescence and this was applied to all images. This method was completely unbiased in nature and no normalization was used (Collins, 2007; Cruz, 2016; Gray et al., n.d.). This raw data was graphed for comparison with the analysis performed on the muscle cross sections.
4.2.5 Antiviral Response RT² Profiler PCR Array
To identify any unique alterations in gene expression, 84 key antiviral response genes were evaluated using Human Antiviral Response RT² Profiler PCR Arrays (Qiagen, USA). In this experiment, DNA transfections were carefully controlled so that the same amount of total DNA was transfected in each sample using the exact same amount of transfection reagent. To achieve this, pUC19 was used as a filler plasmid and as a non-expressing DNA transfection negative control. The RCR+ and RCR- Gag expression vectors, as well as the pTHRep and RCR+ eGFP vectors, were evaluated for their induction of antiviral response genes in comparison to the pUC19 plasmid (as the negative control). Plasmids were transfected into HeLa S3 cells seeded at ~20% confluency in six well plates that were then grown to ~70% confluency (~48 h) before transfections were performed using standard transfection protocols.
Each experimental plasmid was added in a 5:1 ratio with 5 sample plasmid DNA to 1 part pUC19 filler plasmid or 1 part pTHRep used to boost RCR, with a negative control that used only a pUC19 plasmid.
Cells were cultured under standard conditions for 48 h, after which RNA was extracted using RNEasy Plus mini kit (Qiagen). RT2 profiler array analysis was performed by the centre for proteomic and genomic research (CPGR, RSA) who also did quality control testing on the RNA samples before the arrays were run on an ABI QuantStudio 12K Flex qPCR (Invitrogen, USA). Data analysis was performed in MS Excel with the use of a template document developed specifically for RT2 profiler array and provided by Qiagen through their website. A cut-off threshold was set at 1.5 fold change in
111 gene expression for positive identification of relevant alteration in gene expression. This level was chosen to aid in the identification of altered gene expression profiles because FACS had identified that HeLa S3 transfections were ~20% efficient. This meant the true change in gene expression per cell should be ~5 times higher than that reported by the RT2 profiler array, which justified using the lower threshold. Furthermore, in terms of data normalization of the array, one of the best methods is to normalize RNA array data against, is to make use of a carefully selected set of housekeeping genes that are stably expressed in all cells (Jacobsen et al., 2009). The Qiagen gene arrays uses this method with five selected housekeeping genes for its arrays, to ensure high quality and accurate data normalization.
Because this method of normalization was used, it also helped justify the reduction of the cut-off threshold from the standard 2.0 to 1.5fold change. The data normalization is performed automatically when analysing the Qiagen MS Excel template for analysis of the array data. Analysis was done per manufacturer instructions, and all gene expression changes were recoded with relevant level of significance of each finding above the threshold (available in Appendix D).
Because these arrays work by benchmarking sample data against the control data, by normalizing the data with five known housekeeping genes, it becomes possible to run additional cross comparisons between data sets individually as well as against the negative control. This allows for additional semi- independent analyses of the array data to be made. They remain semi-independent because the sample data remains the same. Two of these additional analyses were done to provide additional supporting evidence and possibly identify new unique alterations in gene expression not detected by the primary comparisons. In the primary comparison all samples tested were evaluated against a pUC19 negative control. This was the perfect baseline negative control because the pUC19 vector is essentially the non- expressing backbone of all the other DNA vectors used. It contains the same core DNA sequence as all the plasmids tested with none of the mammalian expression genetics. Primary analyses with pUC19 used the same concentrations of DNA and transfection reagent. These components are known to be capable of influencing gene responses, which made pUC19 an ideal primary control. However, in terms of comparing RCR+ and RCR- vectors, pUC19 was not the ideal control. Here the use of additional cross comparisons between the RCR+ and RCR- vectors helped generate more usable data from the gene arrays. The first direct comparison was the RCR+ vs RCR- Gag vectors. This presented the ideal control data set for evaluating the effects of RCR while still controlling for any independent effects from Gag expression. Cross sample analysis was also performed with the combined RCR+ and pTHRep sample versus the RCR- Gag sample datasets. In this way differences detected in one analysis of sample datasets can be cross examined and ideally corroborated with the additional cross comparisons to strengthen overall findings. It is therefore important to keep in mind which samples are being compared and which sample was used as the reference control when discussing the array results.
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