T-cell receptor retrogenic mice: a rapid, flexible alternative to T-cell receptor transgenic mice


D. A. A. Vignali, Department of Immunology, 262 Danny Thomas Place, St Jude Children’s Research Hospital, Memphis, TN 38105, USA. Email: vignali.lab@stjude.org
Senior author: D. A. A. Vignali


The T-cell receptor (TCR) is unique in its complexity. It determines not only positive (life) and negative (death) selection in the thymus, but also mediates proliferation, anergy, differentiation, cytotoxicity and cytokine production in the periphery. Through its association with six CD3 signalling chains (εγ, δε and ζζ), the TCR is capable of recognizing an extensive variety of antigenic peptides, from both pathogens and self-antigens, and translating these interactions into multiple signalling pathways that mediate diverse T-cell developmental and functional responses. The analysis of TCR biology has been revolutionized by the development of TCR transgenic mice, which express a single clonotypic T-cell population, with diverse specificities and genetic backgrounds. However, they are time consuming to generate and characterize, limiting the analysis of large numbers of TCR over a short period of time in multiple genetic backgrounds. The recent development of TCR retrogenic technology resolves these limitations and could in time have a similarly important impact on our understanding of T-cell development and function. In this review, we will discuss the advantages and limitations of retrogenic technology compared with the generation and use of TCR transgenic mice for studying all aspects of T-cell biology.

The impact of TCR transgenic mice

The T-cell receptor (TCR) repertoire is composed of T cells that are able to escape negative selection and develop through positive selection in the thymus. High-affinity/avidity recognition of self-peptide : major histocompatibility complex (MHC) by the TCR will mediate controlled apoptosis and deletion of immature thymocytes.1–3 Less than 1% are capable of recognizing self-peptide with optimal affinity/avidity to receive a survival signal yet avoid an activation threshold that would lead to apoptosis. This process of thymic education, referred to as central tolerance, prevents the majority of potentially autoreactive T cells entering the periphery. A variety of peripheral tolerance mechanisms, including cell intrinsic induction of anergy and antigenic unresponsiveness and cell extrinsic suppression by various regulatory T-cell populations, are employed to control autoreactive T cells that escape deletion in the thymus.1,4,5 Hence, a wide variety of central and peripheral tolerance mechanisms regulate T-cell development and prevent autoimmunity.

The TCR signalling also controls peripheral T-cell proliferation and shapes T-cell differentiation. Initial activation of antigen reactive CD4+ and CD8+ T cells can occur over a wide range of TCR affinities.6–8 However, further differentiation into effector and memory compartments is strongly influenced by TCR avidity in the case of CD4+ T cells, whereas a relatively wide range of affinities can support CD8+ T-cell differentiation.8,9 T helper phenotypes within the effector response of CD4+ T cells can potentially be influenced by the availability of antigen and TCR affinity.10,11 Furthermore, thymically derived T regulatory cells have been postulated to exhibit high TCR affinity to self-antigens compared with effector T cells.12,13 The role of TCR affinity in peripheral T-cell fate decisions remains to be fully elucidated.

The TCR is composed of two polypeptides (αβ or γδ) that contain variable regions and recognize peptide-bound MHC molecules; however, these chains are unable to transmit any intracellular signals from external stimulation because of short cytoplasmic tails. The CD3 complex (εγ, δε and ζζ chains), which is associated with TCR, allows for the signal transduction initiated after TCR ligation.14 Each of the four CD3 chains (ε, γ, δ, ζ) in the TCR complex contain immunotyrosine activation motifs (ITAMs) that are phosphorylated by protein tyrosine kinases to recruit downstream signalling molecules. The TCR : peptide : MHC recognition paradigm regulates thymic selection and, once T cells enter the periphery, will also determine anergy, activation, differentiation, apoptosis, cytokine production or cytotoxicity.

However, as a consequence of the large TCR diversity (1 × 1013) of a naive T-cell population,15 complete analysis of the T-cell response to any particular antigen is almost impossible. This impasse led scientists to develop transgenic mice, enabling them to study a particular TCR and how it responds to negative/positive selection pressures. This method was first accomplished with the generation of the HY transgenic mouse that enabled the study of negative selection in vivo.16 Other TCR transgenic mice followed, allowing for in vivo analysis of positive selection,17 and later the role of altered peptide ligands in establishing the kinetic signalling model.18 However, there are disadvantages to using the TCR transgenic system, such as the time it takes to generate and backcross each founder line onto the appropriate genetic background (Table 1). It is also important to note that random integration of the TCR transgene into germline DNA may have unwanted consequences, possibly leading to the analysis of a founder effect instead of the true function of the transgene. The advent of retrogenic mice (‘retro’ from retrovirus and ‘genic’ from transgenic) allowed for rapid generation and screening of multiple TCR combinations simultaneously.19,20 Importantly, each retrogenic mouse is individually generated, limiting the potential bias introduced by a founder effect. Here we discuss the utility of retrogenic mice as both a screening tool and a viable alternative to conventional transgenic mice.

Table 1.   T-cell receptor (TCR) transgenic versus retrogenic mice: advantages and disadvantages
IssueTCR transgenic1TCR retrogenic1
  1. 1Advantages are in bold.

  2. 2Excluding the time to clone the TCR, make transgenic or retroviral construct and producers.

PropagationContinuous – can breedLimited – need to remake each time
TCR expression – mean fluorescence intensityNormal (TCR-specific)Somewhat lower (TCR-specific)
TCR expression – regulationNormalNormal
Cell number (spleen)Normal (1 × 106 to 2 × 106)Lower (1 × 104 to 2 × 106)
Time to generate6 months plus25–6 weeks2
CostRelatively highRelatively low
Founder effectPotentialEach mouse is a new founder
Ability to compare multiple TCRs within same experimentLimited – potential strain variability; limited TCR transgenics availableExtensive – can compare numerous TCRs generated within the same colony and experiment
Complexity/time required to analyse TCRs on multiple genetic backgroundsDifficult/Long – complex breeding required – can be > 6 monthsEasy/Short – can express TCR on any chosen background within the same experiment

Multicistronic ‘self-cleaving’ 2A peptide-based retroviral vectors

Given that the TCR is a heterodimer, it is clearly important to use an expression system that gives rise to stoichiometric expression of the TCR-α and TCR-β chains. Several viruses use 2A peptides, or 2A-like sequences, to mediate protein cleavage, which we and others have used to develop multi-cistronic expression vectors.21–23 Multiple genes can be linked via the 2A peptide consensus motif (2A, Asp-Val/Ile-Glut-X-Asn-Pro-Gly; 2B,Pro) whereby cleavage activity occurs between the 2A glycine and the 2B proline (Fig. 1). The ‘cleavage’ observed is not a proteolytic event but is rather the result of cis-acting hydrolase activity, which causes ribosomal ‘skipping’ during translation.21,24,25 Specifically, the ribosome ‘skips’ the synthesis of the glycyl-prolyl peptide bond at the C-terminus of 2A.26 This allows for the previously translated protein to be released and for the ribosome to continue translation of the downstream cistron. Hence, two or more cistrons can be linked via the 2A peptide consensus motif but still be translated from a single open-reading frame. This allows for stoichiometric translation of multiple 2A-linked cistrons within a single vector in contrast to other approaches that result in uneven expression or are problematic to multimerize beyond two cistrons (e.g. using internal ribosomal entry sites).27 By harnessing this viral ‘skipping’ mechanism, stoichiometric expression of cytokines, cytokine receptors, immunoglobulins, TCR complex and many other multimeric complexes can be achieved in vitro and in vivo.26,28

Figure 1.

 Picornavirus-like ‘self-cleaving’ 2A peptide-linked, multi-cistronic retroviral vector. (a) Schematic of the retroviral vector and 2A-linked T-cell receptor (TCR) -α : TCR-β construct. The murine stem cell virus long terminal repeat (MSCV LTR) promoter is used to express the 2A-linked construct. The internal ribosomal entry site (IRES) is used to direct translation of the fluorescent protein. (b) Amino acid sequence of the 2A regions of foot-and-mouth disease virus (F2A), equine rhinitis A virus (E2A), Thosea asigna virus (T2A) and porcine teschovirus-1 (P2A). Conserved residues are boxed. The cleavage point between the 2A and 2B peptides, and hence the N- and C-terminal cistrons, is indicated by the arrow.

TCR retrogenic mouse as an alternative to TCR transgenic mouse

Initially, 2A peptide sequences were used to co-express genes related to the study of influenza, the cell cycle and cytokine expression.29–33 However, more recently we and others have used the 2A-linked multi-cistronic vectors to study complex multimeric structures such as the TCR : CD3 complex.19,20,28,34–38 The TCR retrogenic approach combines 2A-linked multi-cistronic retroviral vectors with retroviral-mediated stem cell gene transfer (Fig. 2).19,20,28,39–43 This approach offers a more efficient alternative to more commonly used internal ribosomal entry site-based vectors, which can lead to non-stoichiometric production of the TCR chains.44,45 The TCR retrogenic mice offer multiple advantages over conventional transgenic approaches (Table 1). The major advantage of this new approach is the ability to generate mice expressing multiple, distinct TCRs in a short amount of time on any background. Whereas transgenic mice may take 6 months or more to generate, TCR retrogenic mice take 6 weeks (and additional 2 months for vector construction and generation of retroviral producers). Generation and direct comparison of multiple TCRs essentially eliminate the founder effect because each mouse is generated separately.19,20,40,41,43

Figure 2.

 Flow chart of steps required to create T-cell receptor retrogenic mice. The standard time required for each step is indicated. 5FU, 5-fluorouracil; IL-3, interleukin-3; i.p., intraperitoneal; i.v., intravenous; SCF, stem cell factor.

The use of TCR retrogenic mice has facilitated the analysis of specific T-cell populations in vivo in a variety of areas, particularly autoimmunity (Table 2).19,20,40–43,46–57 Initially, we performed proof-of-principle experiments to demonstrate that the development and function of antigen-specific T cells, such as the ovalbumin-specific TCR OT-I and OT-II, were comparable between TCR retrogenic and transgenic mice.19,20 Retroviral expression of both TCRs resulted in the expected skewing to either the CD8+ or CD4+ lineage, and peripheral T-cell accumulation as early as 5 weeks after bone marrow transfer. Both OT-I and OT-II T cells were functional, as assessed by their proliferation and interleukin-2 production in response to peptide stimulation. Thymic selection in retrogenic mice was further analysed with TCR specific for male minor histocompatibility antigens, HY, MataHari and Marilyn, as well as expression of OT-I, OT-II and TEa TCR recombinantly linked to a protein or peptide that can modify their thymic selection (Table 2). This approach facilitated the rapid analysis of positive and negative selection.19,20

Table 2.   T-cell receptors that have been expressed in retrogenic mice
T-cell receptorAntigenPeptide epitopeMHCReference
  1. 1Expression of a single chain of a T-cell receptor (TCR-α or TCR-β).

  2. iNKT, invariant natural killer T.

Thymic selection/model antigen
 OT-IOvalbuminOVA257–264KbHolst 2006; Yang 200520,45
 OT-IIOvalbuminOVA323–339AbHolst 2006; Holst 2006; Yang 200520,45
 HYMale antigenSmcy738–746DbHolst 200620
 MataHariMale antigenHYUtyDbHolst 2006; Holst 200820,39
 MarilynMale antigenHYDbyDbHolst 200620
 C61Male antigenHYKKSmcyKkFurmanski 2010; Bartok 201037,38
 C6 (CDR mut)1Male antigen KkFurmanski 201037
 PA21.14H4Heg egg lysozymeHEL11–25Ag7Holst 2006; Burton 2008; Lennon 200919,41,43
 PA21.5F2Heg egg lysozymeHEL11–25Ag7Arnold 200440
 TeaI-Eα chain52–68AbHolst 200620
 ANDMoth cytochrome cMCC88–103EkHolst 200620
 NR23.4C. trachomatisCrpA63–71DbRoan 200650
 Clone 4InfluenzaHA518–526KbBurton A., Vignali D.A.A. unpublished–372DbBurton A., Vignali D.A.A. unpublished
 1803.D23.18HIVSL977–85HLA-2.1Joseph 200857
 BDC2..5ChromograninChgA359–372Ag7Arnold 2004; Burton 200840,41
 BDC10.1ChromograninChgA359–372Ag7Burton 200841
 PA15.14B12Glutamate decarboxylaseGAD206–220Ag7Arnold 2004; Burton 200840,41
 PA19.5E11Glutamate decarboxylaseGAD206–220Ag7Burton 2008; Viret 201141,49
 1A4Glutamate decarboxylaseGAD217–236Ag7Burton 200841
 PA17.9G7Glutamate decarboxylaseGAD284–300Ag7Burton 2008; Lennon 2009; Burton 201041–43
 PA18.10F10Glutamate decarboxylaseGAD510–524Ag7Burton 200841
 PA18.9H7Glutamate decarboxylaseGAD524–538Ag7Burton 200841
 530.45.19Glutamate decarboxylaseGAD530–543Ag7Burton 200841
 PA19.9G11Glutamate decarboxylaseGAD221–237Ag7Burton 2010; Lennon 200942,43
 PA18.10E1Glutamate decarboxylaseGAD524–538Ag7Arnold 200440
 4B5Glutamate decarboxylase Ag7Burton 201042
 10.23Protein tyrosine phosphatase-like IA2IA2676–688Ag7Lennon 200943
 Phogrin13Protein tyrosine phosphatase-like IA2IA2640–659Ag7Burton 200841
 Phogrin18Protein tyrosine phosphatase-like IA2IA2755–777Ag7Burton 2008; Lennon 2009; Viret 201141,43,49
 BDC6.9Islet antigen Ag7Burton 200841
 NY4.1Islet antigen Ag7Arnold 2004; Burton 2008; Lennon 200940,41,43
 12.4-1InsulinIns B9–23Ag7Burton 2008; Lennon 200941,43
 12.4-4InsulinIns B9–23Ag7Kobayashi 2008; Zhang 2009; Zhang 201048,53,54
 12.4-4v1InsulinIns B9–23Ag7Burton 2008; Lennon 200941,43
 12.1-19InsulinIns B9–23Ag7Burton A., Vincent E., Vignali D.A.A. unpublished
 G9.C8InsulinIns B9–23Kd/DbBurton A., Vignali D.A.A. unpublished
 AI4Islet antigen DbChaparro 200847
 6I1Unknown Ag7Lennon 200943
 6I6Unknown Ag7Lennon 200943
 6I9Unknown Ag7Lennon 200943
 6I16Unknown Ag7Lennon 200943
 6I22Unknown Ag7Lennon 200943
 6I26Unknown Ag7Lennon 200943
 6I36Unknown Ag7Lennon 200943
 6I37Unknown Ag7Lennon 200943
 6I38Unknown Ag7Lennon 200943
 10I1Unknown Ag7Lennon 200943
 10I14Unknown Ag7Lennon 200943
 10I35Unknown Ag7Lennon 200943
 6S12Unknown Ag7Lennon 200943
 6S22Unknown Ag7Lennon 200943
 10S2Unknown Ag7Lennon 200943
 10S10Unknown Ag7Lennon 200943
 10S21Unknown Ag7Lennon 200943
 1MOG9Myelin oligodendrocyte glycoproteinMOG35–55AbAlli 200846
 1MOG23Myelin oligodendrocyte glycoproteinMOG35–55AbAlli 200846
 1MOG244.2Myelin oligodendrocyte glycoproteinMOG35–55AbAlli 200846
 2MOG10Myelin oligodendrocyte glycoproteinMOG35–55AbAlli 200846
 5MOG113Myelin oligodendrocyte glycoproteinMOG35–55AbAlli 200846
 Tyrp1Melanosomal antigenTryp1277–297HLA-DR4Ha 201056
 F5 MART-1Melanoma-associated antigenMART-126–35HLA-A2.1Vatakis 201155
Other cell types
 iNKT TCRβ61   Mallevaey 200951
 iNKT TCRβ61 (CDR2 8.2)CD1d-glycolipid  Mallevaey 200951

So far, we have expressed 23 pancreatic islet antigen-specific TCRs on the non-obese diabetic (NOD) background (Table 2).40–43 BDC2.5, 12.4-1 and NY4.1, TCRs that have been previously expressed in transgenic mice, caused spontaneous diabetes in TCR retrogenic mice on NOD.scid or Rag−/− NOD backgrounds in a manner comparable to their TCR transgenic counterparts.40,41,58–60 The ability to express a large panel of TCRs at the same time, on the same background, allowed us to directly compare their insulitogenic and diabetogenic potential. The majority of available islet antigen-specific TCRs induced islet infiltration and some of these induced diabetes.40,41 Interestingly, largely independent of antigenic specificity, we observed a vast difference among the pathogenic potentials of these TCRs.41 Although antigen availability and levels of expression in the islets can affect the level of pathogenicity of the islet antigen-specific TCR, it is possible that within a single antigenic specificity TCR affinity may be the key factor that defines their diabetogenicity. The study of the functional relevance of TCR affinity, or any other parameter, can be greatly facilitated by the ability to express multiple TCRs specific to the same or different antigens via the TCR retrogenic approach. Indeed, this was recently performed in the experimental autoimmune encephalomyelitis model of multiple sclerosis.46 The authors did not observe an obvious correlation between TCR functional affinity and pathogenicity. Nevertheless, several questions remain. Thymic selection of myelin oligodendrocyte glycoprotein-reactive TCRs led to variability in the number of T cells exiting into the periphery. Isolating and transferring similar numbers of T cells could result in a different disease outcome. Additional biophysical analysis of TCR affinity combined with an in vitro response to antigen would provide a more complete analysis of peptide : MHC recognition by a given TCR.

The retrogenic approach can also be used to express several TCRs in the same animal at a selected ratio by mixing bone marrow transduced with different TCR-encoding retroviruses.43 We have employed this approach to show that antigen specificity is required for entry and accumulation of T cells in the pancreatic islets, as only T cells expressing islet antigen-specific TCRs accumulated in the islets, whereas in the same animals T cells expressing TCRs specific for irrelevant antigens were not able to infiltrate the islets. To take full advantage of the rapid analysis of TCR function in vivo via the TCR retrogenic approach, we cloned the TCR-αβ chains from 17 single cell-sorted Vα2+ Vβ6+ or Vα2+ Vβ10+ T cells from either the islets or spleen of female NOD mice and re-expressed these TCRs in vivo using the TCR retrogenic approach.43 The majority of TCRs cloned from the islets of NOD mice infiltrated the islets and some also caused diabetes, whereas none of the splenic TCRs were able to do so. Although, we simplified the cloning process by selecting specific VαVβ combinations, a recent publication has reported a method for paired analysis of Vα and Vβ chains based on PCR amplification of single cell sorted T cells with a pool of primers.61 The combination of this approach with the generation of TCR retrogenic mice could potentially revolutionize the analysis of T-cell specificity and function in a non-biased fashion in vivo.

Other uses for multi-cistronic vectors and the generation of retrogenic mice

The combination of 2A-linked multi-cistronic vectors and retrovirus-mediated stem cell transfer has facilitated our analysis of TCR function in vivo. However, this powerful combination need not be restricted to the in vivo analysis of the TCR. For example, we have used a similar approach to elucidate the role and impact of individual CD3 ITAMs on TCR signal transduction and T-cell development.34–36,39 We generated 25 groups of mice expressing various combinations of wild-type and mutant (inactive) ITAMs within the TCR : CD3 complex.39 To manipulate the number of functional ITAMs in the CD3 complex, cDNAs encoding the four CD3 chains were connected by 2A sequences and expressed in a single retrogenic vector. Using this approach, we developed a scalable signalling model in which the TCR : CD3 complex modulates proliferation, cytokine production, negative selection and the prevention of autoimmune disease based on the differential use of different numbers of CD3 ITAMs.

The use of TCR retrogenic mice is not limited to αβ T cells; it has also been used to study natural killer T cells. A recent study using invariant natural killer TCR retrogenic mice has shown that specific residues within the Vβ CDR3 and CDR2 loops are important in natural killer T-cell recognition of glycolipid : CD1 complexes and thymic selection.51 This approach could also be used to study TCR-γδ and perhaps the B-cell receptor in vivo.

It is possible that a more discriminating approach could be developed that would allow for the temporal or cell-type-restricted expression of the proteins under examination. For instance, the protein expression could be restricted to a particular haematopoietic compartment by flanking the protein of interest with loxP sites in the retroviral vector and using bone marrow from mice expressing Cre recombinase driven by a cell-type-specific promoter.62

Gene therapy has the potential to alleviate many forms of disease including genetic deficiencies, cancer and autoimmunity. However, in some instances treatment has been unreliable because a single gene is not always responsible for or required to alleviate disease. The stoichiometric co-expression of multiple genes may be necessary. Recently, 2A-based vectors have been used to express several multi-protein complexes including interleukin-12, interleukin-35 and the trans-Golgi network golgin (tumour necrosis factor transport molecule).30,63,64 There has been significant interest in the potential benefits of antigen-specific T-cell immunotherapy for the treatment of cancer, chronic viral infections and autoimmune diseases.45,55–57,65,66 Some studies have achieved optimal TCR-αβ expression and potent immunogenicity in human and mouse studies by using the 2A-linked vector system, which could expand in the future.44,55–57

Concluding remarks

In the past 7 years, 64 different TCRs have been expressed in vivo using the TCR retrogenic approach (Table 2). The rapid adoption of this approach can be explained by the relatively low cost and wide availability of reagents, rapid generation of mice, and ability to compare multiple TCRs within the same mouse colony compared with traditional TCR transgenic mice. Retrogenic mice may also be used as a pre-screening tool for TCRs before committing to the considerable cost of TCR transgenic mouse generation. The TCR retrogenic approach has already made an important contribution to our understanding of autoimmune diabetes, and could provide a powerful alternative to more traditional strategies for the in vivo analysis of T-cell development and function in a wide variety of disease models.


MB is supported by a JDRF Postdoctoral Fellowship (3-2009- 594). DAAV is supported by the National Institutes of Health (AI072239, AI39480, AI091977, DK089125), a National Cancer Institute Comprehensive Cancer Center Support CORE grant (CA21765), and the American Lebanese Syrian Associated Charities (ALSAC).


The authors have no conflicts of interest.