Many experimental systems have been utilized to understand the mechanisms regulating T cell development and function in an immune response. Here a genetic approach using retroviral transduction is described, which is economic, time efficient, and most importantly, highly informative in identifying regulatory pathways.
Helper T cell development and function must be tightly regulated to induce an appropriate immune response that eliminates specific pathogens yet prevents autoimmunity. Many approaches involving different model organisms have been utilized to understand the mechanisms controlling helper T cell development and function. However, studies using mouse models have proven to be highly informative due to the availability of genetic, cellular, and biochemical systems. One genetic approach in mice used by many labs involves retroviral transduction of primary helper T cells. This is a powerful approach due to its relative ease, making it accessible to almost any laboratory with basic skills in molecular biology and immunology. Therefore, multiple genes in wild type or mutant forms can readily be tested for function in helper T cells to understand their importance and mechanisms of action. We have optimized this approach and describe here the protocols for production of high titer retroviruses, isolation of primary murine helper T cells, and their transduction by retroviruses and differentiation toward the different helper subsets. Finally, the use of this approach is described in uncovering mechanisms utilized by microRNAs (miRNAs) to regulate pathways controlling helper T cell development and function.
The immune response must be highly regulated to eliminate infections but prevent attacks on self-tissue that lead to autoimmunity. Helper T cells play an essential role in regulating the immune response, and a great deal of effort has been undertaken to understand their development and function (illustrated in several recent reviews 1-3). However, many questions remain, and many approaches have been utilized to study the mechanisms controlling helper T cell development and function. These have ranged from the use of in vitro cell culture systems to whole animals. Cell culture systems, especially those using cell lines, offer the benefit of ease of use and the ability to generate large amount of material to do sophisticated biochemical analyses. However, they suffer from their limited ability to reproduce the actual conditions occurring in an immune response. In contrast, whole animal experiments offer the benefit of relevance, but they can suffer from difficulties in manipulation and the ability to perform precise controls in addition to their large costs and ethical implications. Nevertheless, the vast majority of helper T cells studies today still require the use of whole animal experiments involving primary T cells because of the inability of cell lines to duplicate the exact steps occurring in the whole animal. Therefore, it is essential to utilize cost effective approaches that are highly informative.
Genetics is one powerful tool to study helper T cell development and function, yet traditional methods involving gene knockouts or transgenes are time consuming and expensive so they are often out of reach of small labs. However, retroviral transduction offers a powerful, rapid and, cost effective genetic approach to study the mechanisms of specific gene products. Therefore, it is commonly used in papers studying helper T cell development and function.
We have optimized a procedure for retroviral transduction of helper T cells. It utilizes the pMIG (Murine stem cell virus-Internal ribosomal entry site-Green fluorescent protein) retroviral expression vector, in which the gene of interest can be cloned and thereby expressed from the retrovirus long terminal repeat (LTR) 4. In addition, downstream of the inserted gene of interest is an internal ribosome entry sequence (IRES) followed by the green fluorescent protein (GFP) gene so transduced cells can easily be followed by their expression of GFP. The vector was originally derived from the Murine Stem Cell Virus (MSCV) vectors, which contain mutations in repressor binding sites in the LTRs making them resistant to silencing and thus, giving high expression in many cell types including helper T cells 5,6. Production of high titer retrovirus requires a simple transient transfection protocol of human embryonic kidney (HEK) 293T cells with the MIG vector and a helper virus vector that expresses the retroviral GAG, Pol, and Env genes. For this the pCL-Eco helper virus vector 7 works well in producing high titer replication incompetent retroviruses.
Here these protocols for retroviral production and transduction of primary murine T cells are described in addition to some of our results using this approach to study miRNA regulation of gene expression controlling helper T cell differentiation. miRNAs are small RNAs of approximately 22 nucleotides in length that post-transcriptionally regulate gene expression by targeting homologous sequences in protein encoding messenger RNAs and suppressing translation and inducing message instability 8,9. miRNAs play critical roles in developmental gene regulation. They are essential in the earliest stages of development, as embryos that cannot produce miRNAs die at a very early stage 10. In addition miRNAs are important later on in the development of many tissues. They are thought to function by fine-tuning the expression of genes required for developmental programs 1. In helper T cells miRNAs play multiple roles and are required for regulatory T cell (Treg) development 11-14. We used retroviral transduction as a means to dissect the mechanisms of miRNA regulation of Treg differentiation 15. Through such studies important individual miRNAs were determined by retroviral-mediated overexpression. Subsequently, relevant genes regulated by these miRNAs were identified in order to understand the molecular pathways regulated by miRNAs in helper T cell differentiation.
All mouse work performed in these protocols was undertaken according to the Animals Scientific Procedures Act, UK under the animal Project License 70/6965.
1. Retroviral Production
Prior to proceeding obtain all required approvals for producing genetically modified organisms and the use of retroviruses in mammalian cells.
2. Isolation of Primary Naïve CD4+ T Cells
3. Retroviral Transduction of Activated CD4+ T Cells and their Differentiation into Specific T Helper Subsets
The success of this experimental system requires highly pure populations of T cells and high titer retrovirus preparations. Representative results are shown here as examples of successful experiments. Figure 1 shows the typical purity of pre- and post-selected populations at each stage of the naïve helper T cell isolation protocol. Figure 2 and 3 illustrate the analysis of retrovirus production through GFP expression in the transfected HEK 293T cells (Figure 2) and transduced T cells (Figure 3). Transfection efficiencies of the HEK 293T cells can vary significantly with different retroviral constructs, but this often doesn't correlate with the level of retrovirus production observed with the number of GFP+ T cells. Also, the number of GFP+ T cells can vary depending on the polarization conditions. Furthermore, the mean expression level of GFP and the inserted gene can vary depending on the number of virus copies integrated, the effect of the integration site on transcription, and post-transcriptional regulatory mechanisms affecting the viral transcript.
Finally, Figure 4 shows some typical results we have observed with helper T cell differentiation when the miRNAs miR-15b/16 are overexpressed. These results show some of the variability that can occur within an individual experiment so true effects must be substantiated by statistical analysis of multiple repeat experiments using different preparations of helper T cells. In these experiments Th2 responses can be difficult to observe in the C57BL/6 line used here because they are prone to Th1 responses. Likewise, IL-9 staining can be difficult to detect above background. Therefore, it is imperative to do isotype controls and set up proper compensation to ensure correct gating of cytokine expression. In our results we have found that miR-15b/16 enhances iTreg induction by inhibiting the mTOR signaling pathway through suppressing the expression of the components Rictor and mTOR 15. miR-15b/16 can sometimes influence Th0, Th1, and Th17 differentiation in individual experiments, but there is no significant effect when examined in multiple repeat experiments. In contrast miR-15b/16 overexpression does significantly suppress Th9 differentiation (see reference 18).
Figure 1. Typical purity of helper T cells at each stage of isolation. Representative flow cytometry results of the indicated antigens are shown from the gate of live cells designated in the Forward Scatter (FSC) and Side Scatter (SSC) plots. (A) Pre- and post-CD4 negative selection. Expression profiles of CD4, CD8a, and MHCII are shown. These illustrate the enrichment of helper T cells and the loss of cytotoxic T cells and MHC class II expressing cells. A good purification should result in ~90% CD4+ T cells at this stage. (B) CD25 selection. On the left are the expression profiles of CD4, CD8a, and MHCII, and on the right are the CD4 and CD25 expression profiles pre and post selection. At this point >95% of CD25 negatively selected cells should be CD4+ CD25–. (C) CD62L selection. CD4, CD8a, and MHCII expression profiles are shown on the left. On the right the expression profiles for CD62L and CD44 are shown for pre- and post-CD62L selected cells along with CD4 and CD62L expression profile of post selected cells. After CD62L selection virtually all memory cells (CD44+) are removed leaving a highly enriched population of naïve helper T cells that contains 10-15% effector cells (CD62Llow). For all FACS profiles, equivalent settings and scales for a specific parameter were maintained throughout. Numbers represent the percentage of cells within a gated population. The slight decrease in size of the cells after the initial selection is presumably due to mechanical stress during the protocol. Please click here to view a larger version of this figure.
Figure 2. Analysis of retrovirus-transfected HEK 293T cells. GFP expression is shown in HEK 293T cells that were either untransfected or transfected and analyzed after collection of viral culture supernatants. GFP analysis was done on live cells from the gate on the FSC and SSC plot in the first panel. Numbers represent the percentage of GFP+ cells within the gated region. Typical transfection efficiencies range between 30-90%. Please click here to view a larger version of this figure.
Figure 3. Analysis of retrovirus transduced helper T cells. GFP expression is shown in retroviral-transduced helper T cells after differentiation in Th0, Th1, Th2, Th9, Th17, and Treg polarization conditions for three days. Analysis was gated on live and activated cells indicated in the FSC/SSC panel. Transduction efficiencies can vary between 10-75% depending on the construct and the polarization conditions. Likewise, the mean fluorescent intensity of GFP expression can vary. Please click here to view a larger version of this figure.
Figure 4. Effect of miR-15b/16 overexpression on helper T cell differentiation in different polarization conditions. Representative cytokine profiles are shown on the GFP+ population of cells from Figure 3. Please click here to view a larger version of this figure.
Table 1: Buffers used in these protocols. Please click here to download this table as an Excel spreadsheet.
Helper T cell polarization conditions | ||
Th0 | anti-IL-4 | 5 µg/ml |
anti-IFN-γ | 5 µg/ml | |
Th1 | recombinant-IL-12 | 20 ng/ml |
anti-IL-4 | 5 µg/ml | |
Th2 | recombinant IL-4 | 40 ng/ml |
anti-IFN-γ | 5 µg/ml | |
Th9 | recombinant TGF-β | 2.5 ng/ml |
recombinant IL-4 | 40 ng/ml | |
anti-IFN-γ | 10 µg/ml | |
Th17 | recombinant TGF-β | 2.5 ng/ml |
recombinant IL-6 | 50 ng/ml | |
anti-IFN-γ | 5 µg/ml | |
anti-IL-4 | 5 µg/ml | |
anti-IL-2 | 5 µg/ml | |
Tregs | recombinant TGF-β | 2.5 ng/ml |
recombinant IL-2 | 5 ng/ml |
Table 2: Helper T cell subset polarization conditions.
Retroviral mediated overexpression of genes is a powerful way to analyze function in helper T cells, as their development and function is often determined by the expression level of key regulators. However, cautious interpretation of the results is required because expression levels significantly above those of the endogenous gene can introduce many artifacts. Therefore, this technique should be combined with others to verify the relevance of function. For example, overexpression should be complemented by reduced expression using siRNAs or gene knockouts if available. With miRNAs, we complemented overexpression experiments with those of blocking by using viruses that overexpressed artificial miRNA targeting sites that acted as competitive inhibitors for a miRNA 15. Retroviral transduced cells can also be utilized in biochemical assays involving RNA and protein analysis. However, a major limitation of these experiments is efficiency of transduction resulting in a mixed population of transduced and untransduced cells. Therefore, these assays will most likely require sorting of the GFP+ population. Finally, in vitro differentiation assays should be combined with in vivo experiments, and one way this can be achieved is by adoptively transferring the transduced T cells into mice and following their differentiation and their effect on the immune response.
One of the key limitations to this system is the size of the RNA genome that can be packaged into the retroviral capsid. In our experience, the maximum insert size for MIG retroviral system that gives good virus production is 3-3.5 kb. Therefore, larger genes cannot be analyzed with this system, as they give poor virus titers. However, most genes are smaller than this size so this system is useful for a wide variety of gene studies.
With retroviral transduction, several alternatives within these protocols have been used. Many researchers have utilized packaging cell lines that stably express the retroviral genes (for example reference 16). However, we have obtained the highest titers using standard HEK 293T cells with co-transfection of the pCL-Eco helper virus vector. Isolation of naïve helper T cells can also be achieved through cell sorting rather than the magnetic bead and cell separation column protocol, but this requires access to a cell sorter, and the costs for sort time are typically higher than the bead reagents. Finally, there are variations on activation conditions used to differentiate helper T cells into the different subsets. For example, TCR stimulation of cells for too long before exposure to Treg inducing conditions can inhibit their induction 16. This can be a problem because retroviral expression requires cell division induced by stimulation of cells. Nevertheless, we have found efficient Treg induction using this protocol with O/N activation prior to retroviral transduction.
Within these protocols, successful application requires several factors. High titer retrovirus preparations need efficient transfection of the HEK 293T cells so high quality DNA and precisely prepared 2x HBS are important. In addition, the cell density of the HEK 293T cells needs to be roughly 50% at point of transfection because good expression of the transfected DNA requires that the cells are actively growing, and this will be inhibited if the cells are too sparse or dense. Cells at the optimal density during transfection should reach confluence at some point during the virus collection steps, but they will continue producing high titer virus stocks all the way through to the last collection. Efficient differentiation of the helper T cells requires good cell quality so ensure that isolated cells are to the purity illustrated in Figure 1. Likewise, the quality of the cells is dependent on the mice from which they were isolated. For these studies, we have used 6-8 week old C57BL/6 mice. Older mice can have less naïve cells, and other strains may differ in their differentiation. For example, BALB/c mice are more prone to Th2 responses than C57BL/6 mice 17 so as stated above, C57BL/6 T cells can be difficult to induce a Th2 response. In addition, any of the differentiation conditions may vary slightly from lab to lab, and the effect of gene overexpression may only become apparent in sub-optimal conditions so cytokine concentrations in the various polarization conditions may need to be titrated. Finally, effects of the overexpressed gene or the polarization conditions on cell proliferation can influence the transduction efficiency so measuring effects of the gene of interest may require optimizing the timing and concentration of polarizing reagents. Optimizing all these factors should lead to informative results with this system.
The authors have nothing to disclose.
This work was supported by a Biotechnology and Biological Sciences Research Council (BBSRC) grant (BB/H018573/1) and a BD Biosciences grant.
RPMI | Sigma | R8758 | |
DMEM | Sigma | D5671 | |
Penicillin Streptomycin solution | Sigma | P4333 | |
L-Glutamine | Sigma | G7513 | |
β-mercaptoethanol | Sigma | M3148 | |
DPBS | Sigma | D8537 | |
MIG vector | Addgene | Plasmid 9094 | |
pCL-Eco vector | Addgene | Plasmid 12371 | |
Cell strainer | BD Falcon | 352350 | |
Magnetic beads mouse CD4 cell kit | Invitrogen (Dynabeads) | 11415D | |
Streptavidin Beads | Miltenyi Biotech | 130-048-102 | |
MS cell separation columns | Miltenyi Biotech | 130-042-201 | |
LS cell separation columns | Miltenyi Biotech | 130-042-401 | |
CD25 Biotenylated MAb | BD Biosciences | 85059 | clone 7D4 |
CD62L Biotenylated MAb | BD Biosciences | 553149 | clone MEL-14 |
Polybrene (Hexadimethrine Bromide) | Sigma | 107689 | |
Anti-CD3 | eBiosciences | 16-0031-85 | clone 145-2C11 |
Anti-CD28 | eBiosciences | 16-0281-85 | clone 37.51 |
Anti-IL-4 | BD Biosciences | 559062 | clone 11B11 |
Anti-IFN-gamma | BD Biosciences | 559065 | clone XMG1.2 |
Anti-IL-2 | BD Biosciences | 554425 | cloneJES6-5H4 |
Recombinant IL-12 p70 | eBiosciences | 14-8121 | |
Recombinant IL-4 | BD Biosciences | 550067 | |
Recombinant TGF-beta | eBiosciences | 14-8342-62 | |
Recombinant IL-6 | eBiosciences | 14-8061 | |
Recombinant IL-2 | eBiosciences | 14-8021 | |
PMA | Sigma | P8139 | |
Ionomycin | Sigma | I0634 | |
Brefeldin A | eBiosciences | 00-4506 | |
Paraformaldehyde | Sigma | 16005 | Paraformaldehyde is toxic so use appropriate caution when handling |
Foxp3 staining buffer set | eBiosciences | 00-5523 | |
Anti-CD4 FITC | eBiosciences | 11-0041 | clone GK1.5 |
Anti-CD8a perCP-cy5.5 | eBiosciences | 45-0081-80 | clone 53-6.7 |
Anti-MHCII PE | eBiosciences | 12-0920 | clone HIS19 |
Anti-CD25 PE | eBiosciences | 12-0251-82 | clone PC61.5 |
Anti-CD62L PE | eBiosciences | 12-0621-82 | clone MEL-14 |
Anti-CD44 APC | eBiosciences | 17-0441 | clone IM7 |
Anti-IFN-gamma FITC | eBiosciences | 11-7311-81 | clone XMG1.2 |
Anti-IL-4 PE | BD Biosciences | 554435 | clone 11B11 |
Anti-IL-9 PE or APC | eBiosciences/Biolegend | 50-8091-82/514104 | clone RM9A4 |
Anti-IL-17a PE | BD Biosciences | 559502 | clone TC11-18H10 |
Anti-Foxp3 APC or PE | eBiosciences | 17-5773-82/12-5773-80 | clone FJK-16s |
NaCl | Sigma | S7653 | |
KCl | Sigma | P9333 | |
Na2HPO4-2H2O | Sigma | 71643 | |
Dextrose/Glucose | Sigma | G7021 | |
HEPES, free acid | Sigma | H3375 | |
NH4Cl | Sigma | A9434 | |
Disodium EDTA | Sigma | D2900000 | |
KHCO3 | Sigma | 237205 | |
CaCl2 | Sigma | C5670 |