Newly emerging technologies are rapidly changing conventional approaches to organ transplantation. In the modern era, the key challenges to transplantation include (1) how to best individualize and possibly eliminate the need for life-long immunosuppression and (2) how to expand the donor pool suitable for human transplantation. This article aims to provide readers with an updated review of three new technologies that address these challenges. First, single-cell RNA sequencing technology is rapidly evolving and has recently been employed in settings related to transplantation. The new sequencing data indicate an unprecedented cellular heterogeneity within organ transplants, as well as exciting new molecular signatures involved in alloimmune responses. Second, sophisticated nanotechnology platforms provide a means of therapeutically delivering immune modulating reagents to promote transplant tolerance. Tolerogenic nanoparticles with regulatory molecules and donor antigens are capable of targeting host immune responses with tremendous precision, which, in some cases, results in donor-specific tolerance. Third, CRISPR/Cas9 gene editing technology has the potential to precisely remove immunogenic molecules while inserting desirable regulatory molecules. This technology is particularly useful in generating genetically modified pigs for xenotransplantation to solve the issue of the shortage of human organs. Collectively, these new technologies are positioning the transplant community for major breakthroughs that will significantly advance transplant medicine.
Transplantation has undoubtedly made substantial progress in the past half a century. In the era of modern immunosuppression, acute rejection is no longer an immediate threat to the transplanted organs. In this setting, however, there are two new challenges facing the transplantation community, namely, (1) how best to individualize, minimize, and possibly eliminate indefinite immunosuppression, as broad immunosuppression is associated with powerful side effects in transplant patients, and (2) how to expand the donor pool suitable for human transplantation to resolve the growing shortage of human organs needed for transplantation. Recent advances in single-cell sequencing, nanotechnology, and CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR-associated protein 9) have enabled these novel technologies to be used to effectively address these issues in transplantation.1,2,3 Single-cell RNA sequencing (scRNA-seq) in particular provides comprehensive information about genetic variability and heterogeneity at a the level of an individual cell.4 Such genetic and molecular profiling can provide novel insights into ongoing alloimmune responses in grafts, which can be explored for prognostic, diagnostic, or therapeutic purposes. The development of strategies to promote immunosuppression-free allograft survival via the induction of donor-specific tolerance is a goal that has long been sought after in transplantation.5 The recent development of highly sophisticated nanotechnology platforms has shown promise with regard to inducing transplantation tolerance. Nanotechnology platforms can deliver specific therapeutics to targeted cell types and/or tissue sites and thus have the potential to engineer immune responses that are tailored to the particular organ type transplanted.6 Lastly, the acute shortage of donor organs is a growing problem in transplantation. Although the new organ allocation system has resulted in a significant decrease in disparities in organ allocation,7 an alternative source of donor organs is urgently needed to address the fundamental issue of organ shortage. Porcine organs are a potentially suitable alternative for use in human transplantation. In this regard, CRISPR/Cas9 gene editing technology has been an extremely powerful tool used to generate pigs with improved compatibility and greater potential for successful human transplantation.8
In the present review, we provide a comprehensive overview of recent advances in these technologies and their potential implications for transplantation.
Despite having identical genetic material, each cell type in the human body is distinct from each other in terms of size, morphology, phenotype, intracellular content, and metabolic activity and functions. Much of this heterogeneity is induced by external factors, which precisely regulate cellular gene expression and subsequent cellular activation, proliferation, differentiation, resulting in diverse cell types and distinct functional states.9 In homeostatic conditions, each tissue or organ is capable of performing a designated function as a consequence of the collective effort of its cellular consortium. Impairments of the contributions of one or more of the constituents can lead to a diseased condition. Thus, a comprehensive and temporal assessment of a tissue or organ in a diseased state at the level of a single-cell can provide valuable information from which therapeutic, diagnostic, or prognostic tools can be devised.
Several traditional approaches, such as flow cytometry, in situ hybridization, and immunohistochemistry, can provide information at a the level of a single cell. These approaches have substantially expanded our understanding of the pathogenesis of various diseases. However, a major limitation of these approaches is that the expression of only a very limited number of genes can be interrogated simultaneously. On the other hand, microarray and next-generation sequencing techniques can provide information about the expression of thousands of genes at once, but only for pooled cell samples, thereby averaging and offsetting the contributions of individual cells in the process. Thus, these approaches all have fundamental limitations with regard to providing comprehensive information about individual cells.10 With recent advances in scRNA-seq, profiling gene expression at the individual cell level and describing the dynamic functions of a single-cell based on its gene expression profile have now become possible.11,12 This powerful technology has been rapidly adopted for use in a broad range of biological specialties, including neuroscience, cancer, and developmental biology.13,14,15,16,17 Only recently has this approach been employed to study transplantation immunobiology. In this section, we will discuss the major steps of this technique as they pertain to transplant research and summarize recent landmark transplant studies employing this technology.
Platforms for scRNA-seq
In 2009, Tang et al.18 developed an mRNA sequencing assay with single-cell sensitivity. Employing this new technique, they revealed the expression profiles of thousands of genes at a single-cell resolution. Since then, this technique has been significantly improved. Figure 1 illustrates the schematic flow of scRNA-seq technology. Generating single-cell preparations from any tissue for scRNA-seq is one of the most critical steps for achieving consistency between different experiments.19 Single-cell suspensions from any tissue are generally prepared using enzymatic digestion and mechanical dissociation. The composition of the extracellular matrix varies among different tissues; therefore, protocols for cell dissociation require careful optimization for different tissues with appropriate quality control steps that must validate the viability of the cells and an accurate representation of the individual cell populations from a given tissue.
Individual cells often contain extremely low amounts of mRNA (~10 pg),20 and the preparation of a cDNA library from such a minute quantity of mRNA can be challenging. Originally, Tang et al.18 developed a manual method to separate individual cells into individual tubes that are then used for the construction of single-cell cDNA libraries. Islam et al.21 used Single-Cell Tagged Reverse Transcription sequencing (STRT-seq), which employs 96-well plates wherein each individual well contains one cell along with 6 base-pair oligos of known sequences (for barcoding mRNA transcripts) that are then used for the preparation of cDNA libraries. Barcoded libraries from individual cells can then be pooled for multiplexed sequencing. More recently, automated microfluidic droplet technology has been introduced for the parallel processing of a large number of cells simultaneously for single-cell encapsulation, mRNA transcript release, and barcoding of the mRNA for reverse transcription. This platform uses an extremely small volume of buffer (2 nL), thereby significantly reducing the costs associated with scRNA-seq.22,23 Macosko et al.23 developed a more streamlined DropSeq technique to form droplets using microfluidic chips. The simultaneous flow of oil, cells, and barcoded beads on the microfluidic chip facilitates droplet formation. The beads used in this microfluidic chip system contain the components essential for cDNA preparation, barcodes to tag individual transcripts from the cells, a Unique Molecular Identifier (UMI) to identify PCR duplicates, and primers for the PCR amplification of cDNA in a later step. In 2015, Klein et al.22 introduced another microfluidic-based scRNA-seq platform called InDrop. This platform utilizes deformable hydrogel beads containing barcode oligos. The major advantage of this platform, in comparison to DropSeq, is a significant enhancement of the encapsulation efficiency of the total input cells from ~5% in DropSeq to 60–90% in InDrop.22
As mentioned above, the quantity of mRNA in individual cells is minute. In addition, only 5–50% of the total mRNA can be reverse-transcribed to cDNA.18 Therefore, all scRNA-seq platforms need to amplify the cDNA by either PCR or in vitro transcription (IVT; the amplification of mRNA transcripts prior to reverse transcription to cDNA). A major drawback of amplifying extremely low amounts of mRNA is the artificial overamplification of selective mRNAs that inevitably occurs. These amplification-associated artifacts can be minimized by adding a UMI.24 UMIs are random barcodes that tag each transcript before the amplification of cDNA. This approach has been integrated into the STRT-seq, CELL-Seq2, DropSeq, InDrop, and SeqWell platforms. Following amplification and sequencing, two or more reads that align at the same location and have the same UMI are considered to be true PCR duplicates, and only then will they be tracked and collapsed during bioinformatics analysis. Consequently, reads with low quality scores are removed using the Phred algorithm, and the remaining sequencing reads are mapped against a reference genome data set for gene identification purposes. The identified reads are then counted and assigned to specific cells by their cell-specific barcodes. The enormous data set generated in this way is a digital expression matrix with extremely high dimensionalities. To appropriately interpret such data in a meaningful way and to detect relevant variables, dimensionality reduction and clustering programs are needed.25,26,27 Furthermore, the use of machine learning tools such as Wanderlust, Monocle, and Wishbone can order various clustered cell populations along specific trajectories corresponding to distinct biological processes present in the sample studied.28,29,30 Such in-depth information at a single-cell resolution has been revolutionary in advancing our understanding of cellular heterogeneity and the regulatory mechanisms that operate in homeostatic conditions as well as during disease progression.
Implications for transplantation
The power of scRNA-seq analysis can be exemplified by a recent study performed by Villani et al.11 that revealed heterogeneity among circulating dendritic cells and monocytes. The authors investigated the gene expression profiles of ~2400 cells isolated from human blood. Using unbiased clustering analysis, they identified six different dendritic cell (DC) subtypes and four different monocyte subtypes. Most intriguingly, a new subtype of DCs that are double positive for AXL and SIGLEC6 was discovered and named ‘AS DCs’. These cells closely resembled plasmacytoid DCs and were found to be potent stimulators of allogeneic T cells in vitro.11 Owing to their potent T-cell stimulation capability, it is conceivable that circulating AS DCs may promote or be indicative of allograft rejection in transplant recipients. Therefore, monitoring these cells in circulation may have a predictive value for detecting ongoing or pending allograft rejection.
Recently, Park et al.31 performed scRNA-seq analysis of cells from murine kidneys and identified 18 previously defined kidney and resident immune cells and 3 previously unidentified cell types. This study reveals that the collecting ducts in the kidneys of adult mice contain a previously unidentified transitional cell population that can differentiate into two different cell types, namely, intercalated cells and principal cells. Interestingly, in chronic kidney diseases, increased Notch signaling skews this transition towards principal cells, resulting in metabolic acidosis.31 These data provide a comprehensive resource for the future understanding of normal kidney function and kidney disease development. Humphreys and colleagues recently performed scRNA-seq analysis on kidney allograft biopsies from a recipient experiencing mixed cellular and antibody-mediated rejection.32 Cell clustering identified two monocyte populations (FCGR3A+ and FCGR3A−) with distinct gene expression profiles. Interestingly, despite their distinct phenotypes, both monocyte populations were found to be associated with mixed cellular and antibody-mediated allograft rejection. Cell trajectory analysis revealed a pro-inflammatory gene signature of proximal tubule cells. Although this study only included one healthy control and one allograft biopsy sample, the authors were able to identify 16 different kidney and infiltrating immune cell types, thus demonstrating the power and feasibility of this approach to comprehensively characterize cell-specific gene expression profiles from kidney allograft biopsy samples.32 However, fresh kidney biopsy samples may not be routinely available for such analyses. Considering this constraint, the researchers then compared scRNA-seq with single nuclear RNA sequencing (snRNA-seq) of frozen rather than fresh specimens. Their studies revealed the following important findings: (i) the cell types identified on the basis of gene expression by snRNA-seq were comparable to those identified by scRNA-seq analysis; (ii) the snRNA-seq and scRNA-seq platforms show equivalent sensitivity for gene detection; (iii) snRNA-seq analysis does not include stress-response genes, which are routinely present in scRNA-seq due to tissue processing at 37 °C; and (iv) snRNA-seq analysis allows the detection of more cell clusters than scRNA-seq. These findings were reproducible on all three platforms used in their studies. These data thus support the qualitative superiority of using the snRNA-seq approach over the scRNA-seq technique, a finding that will undoubtedly enhance the feasibility and clinical relevance of this technology.1
Recently, Gladka et al.33 employed scRNA-seq to investigate the gene expression profiles of FACS-sorted cells (SORT-seq) from injured mouse hearts after ischemia reperfusion injury (IRI). Using cluster analysis, the authors identified 17 different cell types in injured hearts. Two fibroblast-specific clusters post-IRI had activation-related differential gene expression. Of the genes with changed expression levels, cytoskeleton-associated protein 4 (CKAP4) has been identified as being a novel marker of activated cardiac fibroblasts; CKAP4, in turn, suppresses a set of genes in this population implicated in their differentiation to myofibroblasts post-IRI.33 More recently, another scRNA-seq analysis of murine hearts revealed 11 transcriptionally distinct macrophage and DC populations.34 Among these, the authors identified one population of self-renewing tissue-resident macrophages characterized as TIMD4+LYVE1+MHC-IIloCCR2− cells. Post-ischemic injury, these unique tissue-resident macrophages play a nonredundant cardioprotective role.34
Despite technical challenges, scRNA-seq technology has been rapidly adopted by several other fields, including cancer, developmental biology, and neuroscience. scRNA-seq analysis allows unbiased transcriptional comparisons at a single-cell resolution. Such in-depth investigation allows unraveling of the dynamic processes (functional or related to differentiation stages) of individual cells. The major impact of scRNA-seq has been to elucidate functional heterogeneity among cells conventionally assumed to be homogeneous based on traditional approaches.12,35 Similarly, transcriptional differences between individual cells also allow the identification of rare and/or novel cell types that would otherwise escape detection in analyses of pooled cells.36 Therefore, this technology is the best tool we currently have for building a dynamic cell atlas of kidney biopsy samples that can be used to elucidate the evolving immune responses to the kidney allograft in a given transplant patient.
Looming over its multitude of alluring benefits are several technical limitations of scRNA-seq technology. Due to the extremely small quantity of mRNA present and the dynamic states of individual cells, biological noise is challenging to avoid in this highly sensitive technology.37 Furthermore, as only 5–50% of the mRNA can be reverse-transcribed,38 the data obtained by this technology may only represent a partial picture of the biological processes of a single cell. The process of generating single-cell preparations from different tissues is of critical importance to data quality and should therefore be carefully optimized for each tissue studied. Furthermore, caution should be exerted when interpreting reads related to cellular stress responses, which may be artificially generated during the process of samples, rather than being innate to the cells examined, although these can be carefully removed by bioinformatics analyses. Encouragingly, Wu et al.1 demonstrated that it may be advantageous to replace scRNA-seq with snRNA-seq, which allows the preparation of samples from frozen tissues, thereby significantly minimizing this issue. Although applying scRNA-seq to investigating immune responses and dissecting the potential mechanisms of graft injury in transplantation has only just begun, recent landmark studies have formed a solid foundation for rapid advances in this field.
Nanotechnology for promoting long-term transplant survival
The use of nanotechnology, especially micro- and nanoparticles, has been investigated for decades for the therapeutic purposes of delivering various drugs and vaccines. In recent years, a number of nanoplatforms have been integrated into medical practice (“nanomedicine”) for tissue imaging, immune monitoring and immunomodulation. Nanomedicine is a rapidly advancing research field with promising applications in cancer therapies, neuroscience, vaccination, autoimmunity, and transplantation.39 In transplantation in particular, these approaches have been employed to modulate alloimmune responses by treating allografts pre- and post-transplantation to prevent graft injury and induce donor-specific tolerance (Fig. 2). In this section, we highlight and discuss recent applications of nanoplatforms in transplantation.
Pre-transplant targeting to reduce ischemic reperfusion injuries
Endothelial cells form the innermost layer of all vascularized organs. Following the implantation and reperfusion of a donor organ in the recipient, endothelial cells constitute the first interface between self and nonself that is encountered by the recipient lymphocytes.40 The endothelial cells of donor organs express several nonself molecules (predominantly donor MHC molecules); thus, they are a preferential trigger for allorecognition and immune responses.41 Furthermore, endothelial cells also express intercellular adhesion molecule (ICAM)-1 and vascular cell adhesion molecule (VCAM)-1,42 which are significantly upregulated following IRI and function to potentiate the antigen-presenting capacity of endothelial cells, as well as to recruit leukocytes to further exacerbate immune-mediated injuries.43 These parallel mechanisms by which endothelial cells can initiate allograft injury are therefore also potential therapeutic targets.44,45
Vascular endothelial cells are highly accessible through ex vivo perfusion; therefore, they are a good target for nanotherapeutics. ICAM-1 expressed by vascular endothelial cells during inflammation plays an important role in leukocyte recruitment and the activation of innate and adaptive immunity. Therefore, targeting endothelial cells with anti-ICAM-1 conjugated poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) through ex vivo perfusion could antagonize ICAM-1 and prevent leukocyte recruitment.46 Similarly, the expression of major histocompatibility complex (MHC) II on allograft endothelial cells can activate circulating memory T cells and initiate rejection.40 NPs (poly (amine-co-ester)) loaded with MHC II-specific siRNA delivered through ex vivo perfusion was found to attenuate MHC II expression on endothelial cells for up to 6 weeks,47 correlating with reduced T cell infiltration and activation in the graft, and, subsequently, with improved allograft histology. Therefore, it has been proposed that NP-based targeting of endothelial cells can potentially be adapted for use in human transplantation via ex vivo normothermic machine perfusion of harvested human organs.47 Employing normothermic machine perfusion of human kidneys, Tietjen et al.48 demonstrated that endothelial cells could be targeted by an anti-CD31 antibody conjugated to poly(lactic acid)–poly(ethylene) glycol NPs. In another recent study, Zhu et al.49 demonstrated that incubating mouse tracheal and aortic allografts with rapamycin-loaded polyethylene glycol micelles (10 nM in size) in standard hypothermic University of Wisconsin (UW) solution significantly prevents the chronic rejection of these allografts post-transplantation. This study further demonstrated that during cold preservation for 4–6 h, receptor-mediated endocytosis of rapamycin-loaded micelles can potentially reduce the secretion of inflammatory cytokines.49 Collectively, these studies demonstrate that during standard allograft procurement procedures, endothelial cells of the allografts can be readily targeted by NPs to reduce post-transplant allograft injury and potentially promote long-term allograft survival.
Post-transplant targeting to induce donor-specific tolerance
The induction of donor-specific tolerance is the ‘holy grail’’ of transplantation research.50 In recent years, NP-based platforms have been developed to induce antigen-specific tolerance. These platforms are called tolerogenic NPs.51 Typically, tolerogenic NPs carry specific antigens or peptides along with additional immunomodulatory therapeutics. Generally, myeloid cells are the primary target of tolerogenic NPs due to their capacity for antigen uptake and presentation and their activity in regulating innate and adaptive immune responses.52 However, diverse tolerogenic NPs have also been developed to target cell types other than myeloid cells via the conjugation of NPs with the ligands for cell-specific receptors.
An example of NP-mediated cell-specific targeting is the treatment for Hemophilia A. Hemophilia A is an inherited bleeding disorder, and patients with this disorder lack blood clotting factor VIII (FVIII). An effective therapy for hemophilia A is to provide the missing FVIII. However, a major obstacle to the long-term efficacy of this therapy is the development of antibodies against exogenous FVIII. Employing hemophilia A mice, Zhang et al.53 demonstrated that multiple injections of tolerogenic PLGA NPs containing rapamycin and FVIII protein induce stable antigen-specific tolerance and effectively prevent the generation of FVIII-specific antibodies. These data suggest the potential utility and efficacy of this approach for targeting B-cell antibody responses. Later, Pang et al.54 developed a sophisticated liposomal platform to specifically target B cells. In their approach, the investigators fabricated liposomal carriers carrying an antigen (OVA) and the B cell targeting ligand CD22 (Siglec-G), with rapamycin trapped in the lipid layer, and they demonstrated that stable B-cell tolerance to OVA can be achieved by treatment with this liposome formulation.54 In another study, Stead et al.55 developed porous silicon-based NPs targeting dendritic cells (DCs). These NPs were conjugated with DC-specific intercellular adhesion molecule-3-grabbing nonintegrin (DC-SIGN), CD11c monoclonal antibodies and rapamycin. The authors showed that injecting this formulation into mice specifically targets the NPs to DCs in the spleen as well as in the kidney, liver, and lungs and significantly promotes the generation of Tregs in the spleens of the treated animals. Though the results have not been demonstrated in transplant models, these studies provide a useful toolbox for constructing various tolerogenic NPs that can induce donor-specific transplantation tolerance.
Employing a fully MHC-mismatched mouse pancreatic islet transplant model, we previously tested the efficacy of PLGA NPs conjugated with donor cell lysate for the induction of donor-specific tolerance.56 We demonstrated that this strategy is effective at preventing the activation of donor-specific CD4 T cells and partially protects the islet allograft. Furthermore, combining the NP treatment with a short course of rapamycin results in a significant synergy in terms of the prolongation of islet allograft survival.56 In another study, Shahzad et al.57 developed PLGA NPs conjugated with H-2Kb-Ig dimer, CD47-Fc, and PD-L1-Fc, with encapsulated recombinant TGF-β, to specifically target and silence antigen-specific CD8 T cells. The authors applied this formulation in a single MHC-mismatched murine model of skin transplantation and demonstrated that three injections of this formulation on days 9, 11, and 13 post-transplant significantly reduced the numbers of antigen-specific CD8 T cells in the graft, blood, and spleen by inducing their apoptosis; consequently, the survival of the skin allograft was significantly prolonged.57
Currently, the only experimental protocols that have successfully achieved transplantation tolerance in human kidney recipients require donor bone marrow transplantation (BMT) and the induction of recipient mixed chimerism.58,59,60 Using a minor histocompatibility antigen (Hy)-mismatched C57BL/6 model of BMT, Hlavaty et al.61 tested the efficacy of a nanoparticle-based approach for the induction of mixed chimerism. In this model, the peptide antigens Dby and Uty of the Hy protein readily mediate the rejection of male bone marrow cells by female CD4 and CD8 T cells, respectively. Investigators have shown that a single injection of Dby-conjugated PLGA NPs on day + 1 post-transplant without any immunosuppressive therapy is sufficient to establish mixed chimerism and prevent rejection of the male bone marrow cells up to 20 weeks post-transplantation. In that study, the induction of mixed chimerism was found to be partially dependent on the PD1-PD-L1 interaction. The authors suggest that such a platform has promising potential to be applied to the development of translatable donor-specific tolerance strategies.61 Recently, Braza et al.62 showed that targeting the innate immune system at the time of transplantation can promote the acceptance of fully MHC-mismatched murine cardiac allografts. In their study, the authors demonstrated that high-density lipoprotein (HDL) nanobiologics made of natural phospholipids and apolipoprotein specifically target recipient macrophages. The delivery of rapamycin and TNF receptor-associated factor 6 (TRAF6) inhibitors via these nanobiologics blunts the inflammatory cytokine responses of macrophages. Mechanistically, such nanobiologics are capable of inducing Ly6Clo regulatory macrophages, which promote allograft acceptance via inhibiting T-cell activation.62
Collectively, these studies provide promising evidence that tailored tolerogenic NPs can be manufactured for the purpose of inducing transplantation tolerance. These studies further reveal the following essential components of efficient tolerogenic NP formulations (Fig. 2): (1) a biocompatible carrier; (2) the conjugation of ligand(s) for targeted delivery; (3) the inclusion of immune modulatory therapeutics such as rapamycin; and (4) the inclusion of the antigens of interest. The timing and frequency of the treatment are additional important variables that will require careful optimization. Furthermore, the propensity for tolerance induction will likely also depend on the type of organ transplanted.63 Therefore, future studies will be needed to examine each individual factor to optimize the therapeutic efficacy of NP formulations for inducing transplantation tolerance with specific transplanted organ types.
CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR-associated protein 9) technology is a revolutionary gene editing technology developed in 2012.64 CRISPR/Cas9 is an enzyme complex derived from bacteria that can be harnessed to precisely and efficiently remove or insert genes in a large range of organisms from yeasts to mammals.64,65 Due to its simplicity, efficiency, and accuracy, it has been widely used to generate genetically modified animal models that are used in the study of many diseases including cancers, viral infections, and neurologic disorders.66 In the field of transplantation, this technology has mainly been explored for its potential to facilitate the creation of genetically modified pigs with an increased compatibility with humans to improve porcine xenograft survival in humans.8,67 In this section, we aim to briefly summarize the gene modification mechanism of CRISPR/Cas9 and introduce current gene modification strategies by CRISPR/Cas9 used in xenotransplantation.
Overview of CRISPR/Cas9 applications in xenotransplantation
Xenotransplantation using porcine organs is a promising means of overcoming the constant shortages of human organs for an ever-growing waitlist of patients in need of organ transplantation. Porcine organs are ideal for xenotransplantation in humans because pigs are physiologically similar to humans, are easily modified and cloned and have a large number of offspring, as well as a relatively short reproduction cycle.68 The main barrier to successful transplantation of porcine organs into human recipients is aggressive graft rejection caused by both humoral and cellular immune responses triggered by xenoantigens on porcine cells.8 In addition, the risk of the transmission of zoonotic pathogens from pigs to humans also poses a potential threat to public health.69,70,71 Recent advances in CRISPR/Cas9 hold great promise for overcoming these barriers by decreasing the xenogenicity of porcine organs and increasing their physiological compatibility with humans.67,72
The CRISPR/Cas family was identified as an RNA-guided defense system protecting bacteria and archaea from invading viruses and plasmids; of the members of the CRISPR/Cas family, CRISPR/Cas9 has been the most widely studied due to its simple structure and high degree of specificity.64,73 Guided by RNA, CRISPR/Cas9 can bind to and cleave DNA sequences at specific locations and thus can be used to make precise gene modifications.66 The CRISPR/Cas9 system consists of the following three main components: the endonuclease Cas9 protein, the CRISPR RNA (crRNA), and a trans-activating crRNA (tracrRNA). The 5ʹ end of the crRNA is a 20-nucleotide guide sequence, which is complementary and can bind to the target DNA sequence (also known as a protospacer); the invariant tracrRNA sequence, partially complementary to the 3ʹ end of crRNA, is required for targeted DNA binding and the activation of Cas9. In addition to complementary binding between the target DNA sequence and the guide crRNA sequence, the target DNA must contain a protospacer adjacent motif (PAM) consisting of the 3-nucleotide sequence NGG, which is recognized by the PAM-interacting domain of Cas9 before executing the cleavage.64 The activation of Cas9 induces the cleavage of the target DNA sequence and generates a double-strand DNA break (DSB), which can then be repaired by either nonhomologous end joining (NHEJ) or homology-directed repair (HDR), resulting in targeted gene editing.74 Originally, NHEJ was thought to be error-prone, leading to insertion and deletion mutations. HDR is an alternative DNA repair mechanism, and in the presence of a repair template, precise and defined modifications can be generated at the DNA target sites.2 Later, research discovered that NHEJ is, however, the primary pathway by which CRISPR-induced lesions are repaired even in the presence of template DNA,75,76 and that NHEJ is in fact inherently accurate in the repair of Cas9-induced DSBs, leading to a high frequency of accurate modifications.77 Owing to further improvements, it is currently possible to make multiple gene modifications at several specific sites in the mammalian genome simultaneously, leading to the easy programmability and wide applicability of this RNA-guided gene editing technology.76
The discovery and development of CRISPR/Cas9 technology have allowed important breakthroughs in xenotransplantation. Transferring the nucleus from a genetically modified cell into an enucleated oocyte can create genetically modified embryos, which can then be surgically implanted into the oviducts of hormonally synchronized recipients to eventually produce piglets with the desired gene modifications.78 Bjoern further streamlined the process, directly injecting the components of CRISPR/Cas9 into porcine zygotes to create genetically modified embryos, thereby obviating the need for somatic cell nuclear transfer (SCNT) altogether. This advance significantly facilitates the production of genetically modified pigs suitable for xenotransplantation (Fig. 3).79 Employing this technology, researchers can now precisely inactivate or insert multiple genes in the porcine genome, generating pigs that are potential organ donors with multiple xenoantigen knockouts, as well as the simultaneous expression of multiple protective human transgenes.76,80 Here, we will also review current porcine genome modification strategies for the prevention of the transmission of PERV (Porcine Endogenous Retrovirus) during xenotransplantation.
Deletion of carbohydrate xenoantigens
Early graft failure due to hyperacute rejection (HAR) has always been a major challenge in xenotransplantation, particularly before the introduction of genetic modification technologies.81 Preformed human natural antibodies against specific porcine carbohydrate xenoantigens are the initiators of HAR. These antibodies activate the complement system, leading to the formation of a membrane attack complex that results in rapid graft destruction.2,8,82 The main carbohydrate xenoantigens expressed on porcine cells are alpha-1,3-galactose (α-Gal) produced by α-1,3-galactosyl-transferase, N-glycolylneuraminic acid (Neu5Gc) produced by cytidine monophosphate-N-acetylneuraminic acid hydroxylase, and non-gal glycan produced by β-1,4-N-acetylgalactosaminyltransferase. The genes encoding these three key enzymes are GGTA1, CMAH and B4GALNT2, respectively.83 GGTA1 gene deletion in porcine cells by CRISPR/Cas9 was first reported in 2014 by Sato et al.84 Porcine embryonic fibroblasts were transfected with a Cas9 expression vector and guide RNA specifically designed to target the GGTA1 gene, and GGTA1 biallelic knockout (KO) cells were successfully generated by this technique with high efficiency.84 In 2015, pigs lacking single GGTA1 (GTKO), dual GGTA1/CMAH (DKO), or triple GGTA1/CMAH/B4GALNT2 (TKO) genes were generated using CRISPR/Cas9 in a study by Estrada.78 Peripheral blood mononuclear cells (PBMCs) were isolated from these pigs and examined for binding with IgM and IgG from humans, rhesus macaques, and baboons. As expected, PBMCs from GGTA1−/−CMAH−/−B4GALNT2−/− TKO pigs showed diminished xenoantigenicity with both human and monkey sera. Interestingly, when incubated with monkey sera, GGTA1−/−CMAH−/− DKO PBMCs had a higher degree of xenoantigenicity than GGTA1−/− GTKO PBMCs.78 However, in the study by Gao et al.85 published in 2017 using human sera, antibody binding and antibody-mediated complement-dependent cytotoxicity were significantly reduced in cells from DKO pigs compared to cells from GTKO pigs. These studies suggest that antibody barriers to xenotransplantation can be minimized by CRISPR/Cas9 genetic modifications; however, the use of nonhuman primate models for examining certain genetic modifications may have limitations. Later, Zhang et al.86 also demonstrated that TKO pigs could be an ideal source of bioprosthetic heart valves (BHVs), as the BHVs from TKO pigs show minimal human IgG/IgM binding activity and no discernable differences in valvular properties compared with wild-type BHVs. Most recently, a preclinical study of pig-to-monkey kidney xenotransplantation using CRISPR/Cas9-modified pigs as donors and rhesus macaques as recipients was published in which long-term renal xenograft survival (435 days) was observed using pig donors with double xenoantigen (Gal and Sda) knockout.87 In their study, however, in addition to the xenoantigen deletion, T-cell depletion with anti-CD4 and anti-CD8, as well as anti-CD154, mycophenolic acid and steroids were also employed.87 Nonetheless, these findings collectively underscore the promising potential of the application of CRISPR/Cas9 technology to xenotransplantation.
MHC class-I deletion
Swine Leukocyte Antigen (SLA)-null pigs were created using CRISPR/Cas9 in 2014 by Reyes et al.88 Seven alleles of classic MHC class-I SLA genes were disrupted simultaneously to remove all MHC class I molecules. Though there was a decrease in the number of peripheral CD8 cells, these pigs otherwise appeared healthy and developed normally.88 In clinical transplantation, it is well known that antibody-mediated rejection can be particularly aggressive if patients are presensitized to the donor; presensitization means that the sera of the recipient will contain preformed antibodies towards donor human leukocyte antigens (HLAs).89 Interestingly, a study evaluating the ability of antibodies from waitlisted renal transplant patients to bind pig cells from TKO donors or from class I SLA-null donors revealed that many waitlisted patients have minimal xenoreactive antibodies to TKO pig cells, but some anti-HLA antibodies in sensitized patients can cross-react with class I SLAs.90 Moreover, human T-cell receptors can directly bind to SLA complexes, triggering human T-cell activation.91 Therefore, class I SLA deletion in addition to TKO will potentially be beneficial in xenotransplantation.
Complement C3 deletion
C3 is a pivotal component of the complement system that plays essential roles in xenograft rejection.92 Activation of the complement system leads to the formation of the membrane attack complex and, consequent, to xenograft damage; complement system activation is required for both hyperacute rejection (HAR) and acute vascular rejection (AVR) of the xenograft.82 Pig donors transgenically expressing human complement regulatory protein CD46 (hCD46) were generated to regulate complement activation in the porcine xenograft after xenotransplantation. This gene modification, combined with GGTA1 knockout, human thrombomodulin transgene and immunosuppression treatment, has achieved the longest survival so far of heterotopic cardiac xenografts (945 days) and kidney xenografts (> 310 days).93,94 Therefore, C3 deletion could be beneficial for xenograft survival. C3-deficient pigs have now been created by CRISPR/Cas9 by Zhang et al.92 In their study, the C3 gene in porcine fetal fibroblasts was cleaved by CRISPR/Cas9, and the biallelic knockout nuclei were then used for somatic cell nuclear transfer to generate C3KO piglets. In total, 19 C3KO piglets were produced, and their plasma C3 protein level was confirmed to be undetectable by Western blot and ELISA.92 These pigs are now available to be tested as potential donors for xenotransplantation.
Inactivation of porcine endogenous retroviruses (PERVs)
In addition to xenograft rejection, the risk of the transmission of infectious pathogens from pig donors to humans has been a concern in the xenotransplantation field. Porcine endogenous retroviruses (PERVs) are potentially infectious pathogens that could be transmitted to humans through pig xenografts. PERVs released from normal pig cells remain active in vivo, which is different from inactive human endogenous retroviruses. PERV-A and PERV-B are polytropic viruses that can infect cells of several species, including humans, posing a risk for xenotransplant recipients; in contrast, PERV-C is an ecotropic virus infecting only pig cells.95,96 Although PERV transmission to nonhuman primate or human recipients of porcine xenografts has not been reported, it has been shown that PERVs can infect human cells in vitro.97 Yang et al.98 reported using CRISPR/Cas9 to inactivate PERVs by targeting the retroviral gene pol, a reverse transcriptase universal to all PERVs. This approach led to a 1000-fold decrease in the ability of PERVs in porcine kidney cells to infect human kidney cells in vitro. However, in their study, the maximal efficiency of PERV inactivation in cell lines targeted by CRISPR/Cas9 was ~35–40%; within a given cell, the degree of pol inactivation also varied greatly, from < 10 to 100%. Furthermore, cell clones with > 90% pol inactivation grew poorly. Thus, simultaneous DNA cleavage by Cas9 at multiple pol sites of various PERV genes in a single cell may trigger DNA damage-induced cell senescence or apoptosis. To circumvent this issue, investigators used a cocktail containing a p53 inhibitor, pifithrin alpha (PFTa), and basic fibroblast growth factor (bFGF) to counter this effect during gene editing and have successfully grown cells with 100% PERV inactivation. Following SCNT, PERV-inactivated pig fetuses with 100% inactivated PERVs were generated.70,98 These PERV-inactivated pigs will now eliminate potential concerns of PERV transmission from pigs to humans during xenotransplantation.
Limitations and perspectives
The development of CRISPR/Cas9 is undoubtedly a seminal breakthrough that has ushered in an era of new progress in xenotransplantation. Previous studies in xenotransplantation have already identified numerous valuable target genes implicated in xenogeneic immune responses. With CRISPR/Cas9, it is now possible to accurately and efficiently modify those targets to promote long-term xenograft survival. However, although the specificity and efficiency of CRISPR/Cas9 have significantly improved compared with previous gene editing technologies, such as zinc finger nucleases and transcription activator-like effector nucleases, it is of paramount importance to ensure its absolute safety by eliminating off-target effects from unexpected genomic rearrangements, which may have detrimental consequences in humans. Further advancements in this powerful technology are still needed.
The past decade has seen tremendous advances in new technologies, such as single-cell RNA sequencing, nanobiotechnology, and CRISPR-Cas9 gene editing. However, creative applications of such novel and powerful technologies to improve clinical transplantation have only just begun. Armed with such tools, we are now well positioned to make major breakthroughs in defining and providing optimized and personalized care for all transplant recipients.
Wu, H., Kirita, Y., Donnelly, E. L. & Humphreys, B. D. Advantages of single-nucleus over single-cell RNA sequencing of adult kidney: Rare cell types and novel cell states revealed in fibrosis. J. Am. Soc. Nephrol. 30, 23–32 (2019).
Naeimi Kararoudi, M. et al. Clustered regularly interspaced short palindromic repeats/Cas9 gene editing technique in xenotransplantation. Front. Immunol. 9, 1711 (2018).
Tasciotti, E. et al. The emerging role of nanotechnology in cell and organ transplantation. Transplantation 100, 1629–1638 (2016).
Wang, J. & Song, Y. Single cell sequencing: a distinct new field. Clin. Transl. Med. 6, 10 (2017).
Kitchens, W. H. & Adams, A. B. Nonhuman primate models of transplant tolerance: closer to the holy grail. Curr. Opin. Organ Transplant. 21, 59–65 (2016).
Xie, J., Lee, S. & Chen, X. Nanoparticle-based theranostic agents. Adv. Drug Deliv. Rev. 62, 1064–1079 (2010).
Chopra, B. & Sureshkumar, K. K. Changing organ allocation policy for kidney transplantation in the United States. World J. Transplant. 5, 38–43 (2015).
Meier, R. P. H. et al. Xenotransplantation: back to the future? Transpl. Int. 31, 465–477 (2018).
Altschuler, S. J. & Wu, L. F. Cellular heterogeneity: do differences make a difference? Cell 141, 559–563 (2010).
Wu, H. & Humphreys, B. D. The promise of single-cell RNA sequencing for kidney disease investigation. Kidney Int. 92, 1334–1342 (2017).
Villani, A. C., et al. Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science. 2017; 356. https://doi.org/10.1126/science.aah4573.
Shalek, A. K. et al. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 510, 363–369 (2014).
Chu, L. F. et al. Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm. Genome Biol. 17, 173 (2016).
Lambrechts, D. et al. Phenotype molding of stromal cells in the lung tumor microenvironment. Nat. Med. 24, 1277–1289 (2018).
Lee, M. C. et al. Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing. Proc. Natl Acad. Sci. USA 111, E4726–E4735 (2014).
Sun, Z. et al. Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells. Oncotarget 9, 10945–10961 (2018).
Zhao, T. et al. Single-cell RNA-seq reveals dynamic early embryonic-like programs during chemical reprogramming. Cell Stem Cell 23, 31–45.e7 (2018).
Tang, F. et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat. Methods 6, 377–382 (2009).
Tung, P. Y. et al. Batch effects and the effective design of single-cell gene expression studies. Sci. Rep. 7, 39921 (2017).
Wang, Y. & Navin, N. E. Advances and applications of single-cell sequencing technologies. Mol. Cell 58, 598–609 (2015).
Islam, S. et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res. 21, 1160–1167 (2011).
Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
Islam, S. et al. Quantitative single-cell RNA-seq with unique molecular identifiers. Nat. Methods 11, 163–166 (2014).
Pierson, E. & Yau, C. ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis. Genome Biol. 16, 241 (2015).
Wang, Y. J. et al. Single-cell transcriptomics of the human endocrine pancreas. Diabetes 65, 3028–3038 (2016).
Xu, C. & Su, Z. Identification of cell types from single-cell transcriptomes using a novel clustering method. Bioinformatics 31, 1974–1980 (2015).
Bendall, S. C. et al. Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell 157, 714–725 (2014).
Setty, M. et al. Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat. Biotechnol. 34, 637–645 (2016).
Trapnell, C. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat. Biotechnol. 32, 381–386 (2014).
Park, J. et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 360, 758–763 (2018).
Wu, H. et al. Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response. J. Am. Soc. Nephrol. 29, 2069–2080 (2018).
Gladka, M. M. et al. Single-cell sequencing of the healthy and diseased heart reveals cytoskeleton-associated protein 4 as a new modulator of fibroblasts activation. Circulation 138, 166–180 (2018).
Dick, S. A. et al. Self-renewing resident cardiac macrophages limit adverse remodeling following myocardial infarction. Nat. Immunol. 20, 29–39 (2019).
Deng, Q., Ramskold, D., Reinius, B. & Sandberg, R. Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science 343, 193–196 (2014).
Miyamoto, D. T. et al. RNA-Seq of single prostate CTCs implicates noncanonical Wnt signaling in antiandrogen resistance. Science 349, 1351–1356 (2015).
Ross, I. L., Browne, C. M. & Hume, D. A. Transcription of individual genes in eukaryotic cells occurs randomly and infrequently. Immunol. Cell Biol. 72, 177–185 (1994).
Svensson, V. et al. Power analysis of single-cell RNA-sequencing experiments. Nat. Methods 14, 381–387 (2017).
Soares, S., Sousa, J., Pais, A. & Vitorino, C. Nanomedicine: Principles, properties, and regulatory issues. Front. Chem. 6, 360 (2018).
Pober, J. S. & Tellides, G. Participation of blood vessel cells in human adaptive immune responses. Trends Immunol. 33, 49–57 (2012).
Piotti, G., Palmisano, A., Maggiore, U. & Buzio, C. Vascular endothelium as a target of immune response in renal transplant rejection. Front. Immunol. 5, 505 (2014).
van Buul, J. D. et al. ICAM-1 clustering on endothelial cells recruits VCAM-1. J. Biomed. Biotechnol. 2010, 120328 (2010).
Tietjen, G. T., Bracaglia, L. G., Saltzman, W. M. & Pober, J. S. Focus on fundamentals: Achieving effective nanoparticle targeting. Trends Mol. Med. 24, 598–606 (2018).
Glotz, D., Lucchiari, N., Pegaz-Fiornet, B. & Suberbielle-Boissel, C. Endothelial cells as targets of allograft rejection. Transplantation 82, S19–S21 (2006).
Al-Lamki, R. S., Bradley, J. R. & Pober, J. S. Endothelial cells in allograft rejection. Transplantation 86, 1340–1348 (2008).
Muro, S. et al. Endothelial targeting of high-affinity multivalent polymer nanocarriers directed to intercellular adhesion molecule 1. J. Pharmacol. Exp. Ther. 317, 1161–1169 (2006).
Cui, J. et al. Ex vivo pretreatment of human vessels with siRNA nanoparticles provides protein silencing in endothelial cells. Nat. Commun. 8, 191 (2017).
Tietjen, G. T. et al. Nanoparticle targeting to the endothelium during normothermic machine perfusion of human kidneys. Sci. Transl. Med. 9 (2017). https://doi.org/10.1126/scitranslmed.aam6764.
Zhu, P. et al. Organ preservation with targeted rapamycin nanoparticles: a pre-treatment strategy preventing chronic rejection in vivo. RSC Adv. 8, 25909–25919 (2018).
Schroeder, R. A., Marroquin, C. E. & Kuo, P. C. Tolerance and the “Holy Grail” of transplantation. J. Surg. Res. 111, 109–119 (2003).
Kishimoto, T. K. & Maldonado, R. A. Nanoparticles for the induction of antigen-specific immunological tolerance. Front. Immunol. 9, 230 (2018).
Steinman, R. M. & Hemmi, H. Dendritic cells: translating innate to adaptive immunity. Curr. Top. Microbiol. Immunol. 311, 17–58 (2006).
Zhang, A. H., Rossi, R. J., Yoon, J., Wang, H. & Scott, D. W. Tolerogenic nanoparticles to induce immunologic tolerance: Prevention and reversal of FVIII inhibitor formation. Cell. Immunol. 301, 74–81 (2016).
Pang, L., Macauley, M. S., Arlian, B. M., Nycholat, C. M. & Paulson, J. C. Encapsulating an immunosuppressant enhances tolerance induction by siglec-engaging tolerogenic liposomes. Chembiochem 18, 1226–1233 (2017).
Stead, S. O. et al. Murine and non-human primate dendritic cell targeting nanoparticles for in vivo generation of regulatory T-cells. ACS Nano 12, 6637–6647 (2018).
Bryant, J. et al. Nanoparticle delivery of donor antigens for transplant tolerance in allogeneic islet transplantation. Biomaterials 35, 8887–8894 (2014).
Shahzad, K. A. et al. On-target and direct modulation of alloreactive T cells by a nanoparticle carrying MHC alloantigen, regulatory molecules and CD47 in a murine model of alloskin transplantation. Drug Deliv. 25, 703–715 (2018).
Leventhal, J. et al. Chimerism and tolerance without GVHD or engraftment syndrome in HLA-mismatched combined kidney and hematopoietic stem cell transplantation. Sci. Transl. Med. 4, 124ra28 (2012).
Scandling, J. D. et al. Tolerance and chimerism after renal and hematopoietic-cell transplantation. N. Engl. J. Med. 358, 362–368 (2008).
Kawai, T. et al. HLA-mismatched renal transplantation without maintenance immunosuppression. N. Engl. J. Med. 358, 353–361 (2008).
Hlavaty, K. A. et al. Tolerance induction using nanoparticles bearing HY peptides in bone marrow transplantation. Biomaterials 76, 1–10 (2016).
Braza, M. S. et al. Inhibiting inflammation with myeloid cell-specific nanobiologics promotes organ transplant acceptance. Immunity 49, 819–28.e6 (2018).
Dangi, A., Yu, S. & Luo, X. Apoptotic cell-based therapies for promoting transplantation tolerance. Curr. Opin. Organ Transplant. 23, 552–558 (2018).
Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).
Lander, N., Chiurillo, M. A. & Docampo, R. Genome editing by CRISPR/Cas9: A game change in the genetic manipulation of protists. J. Eukaryot. Microbiol. 63, 679–690 (2016).
Doudna, J. A. & Charpentier, E. Genome editing. The new frontier of genome engineering with CRISPR-Cas9. Science 346, 1258096 (2014).
Cowan, P. J. & Tector, A. J. The resurgence of xenotransplantation. Am. J. Transplant. 17, 2531–2536 (2017).
Denner, J. Paving the path toward porcine organs for transplantation. N. Engl. J. Med. 377, 1891–1893 (2017).
Fung, R. K. & Kerridge, I. H. Gene editing advance re-ignites debate on the merits and risks of animal to human transplantation. Intern. Med. J. 46, 1017–1022 (2016).
Niu, D. et al. Inactivation of porcine endogenous retrovirus in pigs using CRISPR-Cas9. Science 357, 1303–1307 (2017).
Salomon, D. R. A CRISPR way to block PERVs--engineering organs for transplantation. N. Engl. J. Med. 374, 1089–1091 (2016).
Shrock, E. & Guell, M. CRISPR in animals and animal models. Prog. Mol. Biol. Transl. Sci. 152, 95–114 (2017).
Wiedenheft, B., Sternberg, S. H. & Doudna, J. A. RNA-guided genetic silencing systems in bacteria and archaea. Nature 482, 331–338 (2012).
Lau, R. W., Wang, B. & Ricardo, S. D. Gene editing of stem cells for kidney disease modelling and therapeutic intervention. Nephrology 23, 981–990 (2018).
Cruz, N. M. & Freedman, B. S. CRISPR gene editing in the kidney. Am. J. Kidney Dis. 71, 874–883 (2018).
Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).
Guo, T. et al. Harnessing accurate non-homologous end joining for efficient precise deletion in CRISPR/Cas9-mediated genome editing. Genome Biol. 19, 170 (2018).
Estrada, J. L. et al. Evaluation of human and non-human primate antibody binding to pig cells lacking GGTA1/CMAH/beta4GalNT2 genes. Xenotransplantation 22, 194–202 (2015).
Petersen, B. et al. Efficient production of biallelic GGTA1 knockout pigs by cytoplasmic microinjection of CRISPR/Cas9 into zygotes. Xenotransplantation 23, 338–346 (2016).
Fischer, K., Kind, A. & Schnieke, A. Assembling multiple xenoprotective transgenes in pigs. Xenotransplantation 25, e12431 (2018).
Lambrigts, D., Sachs, D. H. & Cooper, D. K. Discordant organ xenotransplantation in primates: world experience and current status. Transplantation 66, 547–561 (1998).
Fischer, K. et al. Efficient production of multi-modified pigs for xenotransplantation by ‘combineering’, gene stacking and gene editing. Sci. Rep. 6, 29081 (2016).
Byrne, G. W., McGregor, C. G. A. & Breimer, M. E. Recent investigations into pig antigen and anti-pig antibody expression. Int. J. Surg. 23, 223–228 (2015).
Sato, M. et al. The combinational use of CRISPR/Cas9-based gene editing and targeted toxin technology enables efficient biallelic knockout of the alpha-1,3-galactosyltransferase gene in porcine embryonic fibroblasts. Xenotransplantation 21, 291–300 (2014).
Gao, H. et al. Production of alpha1,3-galactosyltransferase and cytidine monophosphate-N-acetylneuraminic acid hydroxylase gene double-deficient pigs by CRISPR/Cas9 and handmade cloning. J. Rreprod. Dev. 63, 17–26 (2017).
Zhang, R. et al. Reducing immunoreactivity of porcine bioprosthetic heart valves by genetically-deleting three major glycan antigens, GGTA1/beta4GalNT2/CMAH. Acta Biomater. 72, 196–205 (2018).
Adams, A. B. et al. Xenoantigen deletion and chemical immunosuppression can prolong renal xenograft survival. Ann. Surg. 268, 564–573 (2018).
Reyes, L. M. et al. Creating class I MHC-null pigs using guide RNA and the Cas9 endonuclease. J. Immunol. 193, 5751–5757 (2014).
Kemter, E., Denner, J. & Wolf, E. Will genetic engineering carry xenotransplantation of pig islets to the clinic? Curr. Diab. Rep. 18, 103 (2018).
Martens, G. R. et al. Humoral reactivity of renal transplant-waitlisted patients to cells from GGTA1/CMAH/B4GalNT2, and SLA class I knockout pigs. Transplantation 101, e86–e92 (2017).
Hara, H. et al. Human dominant-negative class II transactivator transgenic pigs—effect on the human anti-pig T-cell immune response and immune status. Immunology 140, 39–46 (2013).
Zhang, W. et al. Generation of complement protein C3 deficient pigs by CRISPR/Cas9-mediated gene targeting. Sci. Rep. 7, 5009 (2017).
Iwase, H. et al. Immunological and physiological observations in baboons with life-supporting genetically engineered pig kidney grafts. Xenotransplantation. 24 (2017). https://doi.org/10.1111/xen.12293.
Mohiuddin, M. M. et al. Chimeric 2C10R4 anti-CD40 antibody therapy is critical for long-term survival of GTKO.hCD46.hTBM pig-to-primate cardiac xenograft. Nat. Commun. 7, 11138 (2016).
Denner, J. How active are porcine endogenous retroviruses (PERVs)? Viruses 8 (2016). https://doi.org/10.3390/v8080215.
Ross, M. J. & Coates, P. T. Using CRISPR to inactivate endogenous retroviruses in pigs: an important step toward safe xenotransplantation? Kidney Int. 93, 4–6 (2018).
Patience, C., Takeuchi, Y. & Weiss, R. A. Infection of human cells by an endogenous retrovirus of pigs. Nat. Med. 3, 282–286 (1997).
Yang, L. et al. Genome-wide inactivation of porcine endogenous retroviruses (PERVs). Science 350, 1101–1104 (2015).
This work was supported by grants from the National Institutes of Health (R01 EB009910) (A.D. and X.L.) and the Chinese Scholarship Council (S.Y.).
The authors declare no competing interests.
About this article
Cite this article
Dangi, A., Yu, S. & Luo, X. Emerging approaches and technologies in transplantation: the potential game changers. Cell Mol Immunol 16, 334–342 (2019). https://doi.org/10.1038/s41423-019-0207-3
- Single cell sequencing
- Crisper Cas9
Safeguards for Using Viral Vector Systems in Human Gene Therapy: A Resource for Biosafety Professionals Mitigating Risks in Health Care Settings
Applied Biosafety (2020)
Cellular Immunology (2020)