Skip to main content
AIDS Research and Human Retroviruses logoLink to AIDS Research and Human Retroviruses
. 2020 Nov 25;36(12):969–972. doi: 10.1089/aid.2020.0116

Skipped Over: Tuning Natural Killer Cells Toward HIV Through Alternative Splicing

Daniel R Ram 1,✉, Kyle Kroll 1, R Keith Reeves 1,,2,✉
PMCID: PMC7703092  PMID: 32862656

Abstract

Natural killer (NK) cells provide some of the earliest immune responses to infection, but when viruses manipulate or perturb the immune environment to alter NK cell function, this places the host at a disadvantage. Indeed, others and we observe that in the context of HIV/simian immunodeficiency virus (SIV) infection, although NK cells are not infected, they can become dysfunctional over time. Several studies have characterized protein and transcriptional profiles of NK cells during HIV/SIV infection, but none have examined whether the production of alternative transcripts and corresponding isoforms is modulated. This phenomenon occurs broadly in normal biology and in other disease states, and could provide a novel avenue of investigation that may yield better targets to restore or augment NK cell responses to HIV/SIV. Herein, we briefly summarize published and new data that may provide a perspective on how to target NK cell splice variants.

Keywords: natural killer cell, alternative splicing, HIV/SIV


Alternative splicing is a mechanism used by cells to maximize the available genetic code by producing several potentially viable transcripts from a single multiexon gene. Although the process of gene splicing has been known for several decades, how splicing is regulated and how the splicing machinery could be coopted therapeutically are still largely underexplored. It is well established that the spliceosome complex is important in regulating gene splicing1 and several studies have suggested the role of splicing in cancers,2 but how these components are altered during situations of cellular stress, infections, or other disease states is largely unexplored.3,4

Recent study by Rotival et al. clearly demonstrates that treating human monocytes with several toll-like receptor agonists (proxies for viral, bacterial, or fungal infections) resulted in varying gene isoform expression profiles, including the production of putatively dysfunctional isoforms.5 It has also been shown that macrophage function is altered in the context of Mycobacterium tuberculosis infection through modulation of the splicing patterns of several genes, diminishing the ability of macrophages from clearing infection.6 Viral infection with, but not limited to, dengue,7 ZIKV,8 poliovirus,9 and HIV10 has also been shown to result in changes to the splicing patterns of host cells.

Although obviously not the only cause, it is possible that modulation of the host splicing patterns contributes to the pathology of infection.11 For example, during HIV infection, trans-activator of transcription (TAT) seems to be associated with neurocognitive effects through modulation of the host splicing machinery.10 Changes in alternative splicing are not limited to disease states, but also occur naturally during aging. Several studies have shown that in aged patient cohorts, there are fewer gene isoforms produced in immune cells, and this is correlated with weaker immune responses and poorer disease outcomes.12,13

Natural killer (NK) cells are potent antiviral and antitumor immune cells that play a crucial role in regulating HIV/SIV disease, particularly during acute infection.14 Interestingly, chronic infection with HIV/SIV leads to a premature immune aging phenotype,15 including a decline in NK cell functions, perhaps through exhaustion mechanisms that resemble those observed in T cells.16 This is evident through NK cell acquisition of exhaustion markers such as Tim-3, or decreased expression of transcription factors such as Eomes, both of which when blocked (Tim-3) or reversed (through Eomes overexpression) result in the restoration of NK cell function.16

Interestingly, genes encoding both Eomes and Tim-3 have multiple isoforms that may be differentially regulated during disease. It is well established that infection and disease lead to immune modulation through release of various cytokines and mobilizing various cell types, yet a comprehensive undertaking looking at how infection or disease results in an altered isoform landscape does not currently exist. Previous study from the Poltorak laboratory has shown that genetic contribution of specific gene isoforms of the apoptosis regulator cellular FLICE (FADD-like IL-1-converting enzyme)-inhibitory protein (cFLIP) leads to improved outcomes toward septic shock in a mouse model and that this can be transferred to nonresistant mice through genetic modulation of a single gene isoform.17 This study suggests that targeting gene isoform expression may be a viable therapeutic approach that may also be able to overcome issues arising from a complete knockdown of gene expression.

We posit that a similar approach can be employed in reversing the immunoregulatory effects after retroviral infection with HIV/SIV. Indeed analysis of data from our group in rhesus macaque NK cells18 has identified several genes that exist as splice variants at preinfection time points, including elevated short cFLIP isoforms, and NKp46 and NKp30. As a test case and proof of concept for this perspective, we more closely evaluated our own data (Fig. 1A) as well as published data on NKp30 (Fig. 1B–F). Data from human uterine NK cells revealed that NKp30 isoform expression was modulated by exposure to different cytokines and that isoform expression seemed to also be associated with disparate functional properties.19

FIG. 1.

FIG. 1.

NKp30 isoform-specific characterization in rhesus macaque and human NK cells. Transcripts per million read counts showing NKp30 isoforms in NK cells from (A) naive rhesus macaques (GSE148290); reanalysis of publicly available human RNA-Seq cohorts from (B) heterogeneous patient samples (GSE60424); (C) samples stimulated with or without adenosine (GSE119705); (D) samples after withdrawal of (No) or stimulation with IL-2 (+IL-2) or IL-15 (+IL-15), assessing RNA from the polysomal fraction (Polysomal) or cytoplasmic fraction (Cyto)(GSE77808); (E) samples unstimulated (Unstim) or stimulated with PMA and ionomycin (+PMA) from normal or DOCK8 knockout (DOCK8 KO) KHYG1 NK cell line (GSE101467); (F) patient samples after injection with the trivalent inactivated influenza vaccine from preinfection (day 0) to day 7 postinoculation (GSE64655). In the rhesus (A), the 201aa isoform corresponds with (ENSMMUP00000011616.3) and the 220aa isoform corresponds with (ENSMMUP00000011617.4). In the human samples (B–F), the 165aa isoform corresponds with (ENSP00000365239.4), the 190aa isoform corresponds with (ENSP00000365240.3), the 177aa isoform corresponds with (ENSP00000365241.4), and the 201aa isoform corresponds with (ENSP00000342156.5). The isoform-specific analyses of rhesus macaque naive samples were done using salmon32 and IsoformSwitchAnalyzeR,33 reanalysis of the human data was done using Grein.20 NK, natural killer.

Reanalysis of several publicly available data sets from Gene Expression Omnibus (GEO) using GREIN20 reveals that in human NK cells, isoform-specific expression of NKp30 isoforms varies in a heterogeneous population (GSE60424, Fig. 1B) with a preference for expression of a 177 amino acid variant (ENST00000376073.8). Isoform-specific NKp30 modulations also occur after ex vivo or in vitro stimulation (GSE77808, GSE101467, and GSE119705; Fig. 1C–E) or even after vaccination against influenza (GSE64655; Fig. 1F).

In our rhesus macaque data, we see expression of two NKp30 gene isoforms with a higher expression of a longer variant (220 amino acids, ENSMMUT00000012387.4) over a shorter variant (201 amino acids, ENSMMUT00000012386), Figure 1A. There is a 90% overlap between the predominant human and rhesus isoforms with the major differences in the signal peptide sequences. Whether or not these isoforms are functionally different or expression levels of these isoforms are altered during retroviral infection will require further investigation. NKp30 is just one example of many genes that are expressed as alternative transcripts; indeed, this deserves a more thorough investigation. In particular, it may be useful to assess the role that alternative splicing has on killer Ig-like receptor (KIR) selection in NK cells as described by Bruijnesteijn et al.21 especially in the context of disease states given the role that KIR plays in MHC antigen recognition by NK cells.

Since NK cells themselves are not infected with HIV/SIV, global immune modulation by the virus may lead to changes in NK cell alternative gene splicing—which can result in altered NK cell responses. It has already been shown that NK cells utilize alternative splicing mechanisms to modulate HLA-C expression, possibly leading to varying degrees of self-recognition,22 so it is possible that NK cells may also fine-tune antiviral responses through alternative splicing events. If we can understand the changes in splicing patterns, as well as identify key genes leading to NK cell dysfunction, we may be able to reverse the consequences of retroviral-induced immunosuppression observed during chronic HIV/SIV infection. Furthermore, NK cells can also generate memory-like immune responses against SIV epitopes.23 Since NK cells do not utilize RAG recombinase, it is possible that alternative splicing mechanisms may provide an opportunity to modify genes of other antigen recognition molecules in NK cells to provide epitope-specific responses.

Most RNA intervention programs are aimed at targeting the infection, disrupting the immune response through dampening of cytokine signaling, or inhibition of immunosuppressive molecules leading to enhanced immune responses.24 Sometimes, as in the case of gene therapy, the intent is to have a long-lasting effect through introduction of desired genes through viral vectors, or suppression of desired genes through mechnanisms such as RNA interference. In other instances, gene therapy can lead to the removal or repair of a dysfunctional gene through use of nuclease systems such as CRISPR/Cas-9 as is being attempted with CCR5 disruption in HIV.25

A particular difficulty in developing RNA-based therapies lies in the ability to deliver it to the target cells, in part, because the highly negative charge of siRNA or miRNA makes it difficult to transport across cell membranes. Several groups are developing a variety of methods including lipid particle-based delivery modalities that are able to overcome this problem,26 though cell-specificity continues to pose a challenge to drug delivery in general. Interestingly, some strategies involve targeting alternative gene isoforms, usually for genetic diseases such as congenital muscular dystrophy or others,27,28 and as a result this creates a substantial opportunity for innovation, not only in the development of therapies for HIV but also for how RNA-targeting therapies are implemented in general.

Current therapeutic approaches tend to be keenly focused on the disease agent and its immediate target, for instance focusing on CD4+ T cells in the case of HIV. Although it is certainly correct to focus on CD4+ T cells since HIV preferentially targets this immune subset leading to their depletion, a disease state such as HIV infection has systemic consequences. As a result, to develop a more appropriate response, we need to consider these broader consequences of viral infection. With such readily available access to RNA-sequencing technologies, it is now possible to investigate longitudinal effects of SIV/HIV infection in a broad range of immune cells and tissues.

Current practice for publishing studies with large genomic data sets often involves deposition of these data sets in publicly accessible databases. However, most of the currently available RNA-Seq data sets on repositories such as GEO, for instance, are missing the crucial dimension of preferential gene isoform expression, in part, because of how the studies were designed. Despite this, although not all RNA-Seq data sets will provide adequate sequencing depth, it may still be informative to revisit these vast repositories to glean insights into alternative gene splicing.

Including appropriate methodologies such as direct RNA-sequencing technologies or deep-sequencing technologies from Illumina or 10x Genomics29 to quantify alternative splicing in various cell types, tissues, and in longitudinal monitoring throughout HIV/SIV infection may inform on how alternative splicing is influenced by disease state and interventions in humans and other animal models. Furthermore, understanding how alternative splicing is modulated in crucial early responding cells, such as NK cells, may provide us with a more comprehensive understanding of how HIV infection is modulating the global immune response. Perhaps HIV proteins such as TAT may also play a direct role in modulating gene splicing in NK cell since TAT has been shown to be secreted from infected cells30,31 or perhaps yet to be discovered immune disruptions caused by CD4+ T cell targeting by HIV lead to indirect NK modulations. Understanding modulation of alternative splicing during HIV infection and developing RNA-based interventions to target relevant alternative transcripts may provide us with a novel approach to treat and ultimately cure HIV/AIDS.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This study was supported by National Institutes of Health grant no. R01 AI120828 (to R.K.R.) and a Harvard Center for AIDS Research (P30 AI060354) Developmental Award (to D.R.R). D.R.R. was also supported, in part, by NIH training grant no. T32 AI007387.

References

  • 1. Wang Z, Burge CB: Splicing regulation: From a parts list of regulatory elements to an integrated splicing code. RNA 2008;14:802–813 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Oltean S, Bates DO: Hallmarks of alternative splicing in cancer. Oncogene 2014;33:5311–5318 [DOI] [PubMed] [Google Scholar]
  • 3. Xiong HY, Alipanahi B, Lee LJ, et al. : RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease. Science 2015;347:1254806. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Schaub A, Glasmacher E: Splicing in immune cells-mechanistic insights and emerging topics. Int Immunol 2017;29:173–181 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Rotival M, Quach H, Quintana-Murci L: Defining the genetic and evolutionary architecture of alternative splicing in response to infection. Nat Commun 2019;10:1671. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Kalam H, Fontana MF, Kumar D: Alternate splicing of transcripts shape macrophage response to Mycobacterium tuberculosis infection. PLoS Pathog 2017;13:e1006236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. De Maio FA, Risso G, Iglesias NG, et al. : The dengue virus NS5 protein intrudes in the cellular spliceosome and modulates splicing. PLoS Pathog 2016;12:e1005841. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Hu B, Huo Y, Yang L, et al. : ZIKV infection effects changes in gene splicing, isoform composition and lncRNA expression in human neural progenitor cells. Virol J 2017;14:217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Alvarez E, Castello A, Carrasco L, Izquierdo JM: Poliovirus 2A protease triggers a selective nucleo-cytoplasmic redistribution of splicing factors to regulate alternative pre-mRNA splicing. PLoS One 2013;8:e73723. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Kadri F, Pacifici M, Wilk A, et al. : HIV-1-Tat protein inhibits SC35-mediated Tau Exon 10 inclusion through up-regulation of DYRK1A kinase. J Biol Chem 2015;290:30931–30946 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Chauhan K, Kalam H, Dutt R, Kumar D: RNA splicing: A new paradigm in host-pathogen interactions. J Mol Biol 2019;431:1565–1575 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Deschenes M, Chabot B: The emerging role of alternative splicing in senescence and aging. Aging Cell 2017;16:918–933 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Balliu B, Durrant M, Goede O, et al. : Genetic regulation of gene expression and splicing during a 10-year period of human aging. Genome Biol 2019;20:230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Alter G, Altfeld M: NK cells in HIV-1 infection: Evidence for their role in the control of HIV-1 infection. J Intern Med 2009;265:29–42 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Deeks SG: HIV infection, inflammation, immunosenescence, and aging. Annu Rev Med 2011;62:141–155 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Schafer JL, Muller-Trutwin MC, Reeves RK: NK cell exhaustion: Bad news for chronic disease? Oncotarget 2015;6:21797–21798 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Ram DR, Ilyukha V, Volkova T, et al. : Balance between short and long isoforms of cFLIP regulates Fas-mediated apoptosis in vivo. Proc Natl Acad Sci U S A 2016;113:1606–1611 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Aid M, Ram DR, Bosinger SE, Barouch DH, Reeves RK: Delineation and modulation of the natural killer cell transcriptome in rhesus macaques during ZIKV and SIV infections. Front Cell Infect Microbiol 2020;10:194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Siewiera J, Gouilly J, Hocine HR, et al. : Natural cytotoxicity receptor splice variants orchestrate the distinct functions of human natural killer cell subtypes. Nat Commun 2015;6:10183. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Mahi NA, Najafabadi MF, Pilarczyk M, Kouril M, Medvedovic M: GREIN: An interactive web platform for re-analyzing GEO RNA-seq data. Sci Rep 2019;9:7580. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Bruijnesteijn J, van der Wiel MKH, de Groot N, et al. : Extensive alternative splicing of KIR transcripts. Front Immunol 2018;9:2846. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Goodson-Gregg FJ, Rothbard B, Zhang A, et al. : Tuning of NK-Specific HLA-C Expression by Alternative mRNA Splicing. Front Immunol 2019;10:3034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Reeves RK, Li H, Jost S, et al. : Antigen-specific NK cell memory in rhesus macaques. Nat Immunol 2015;16:927–932 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Chakraborty C, Sharma AR, Sharma G, Doss CGP, Lee SS: Therapeutic miRNA and siRNA: Moving from bench to clinic as next generation medicine. Mol Ther Nucleic Acids 2017;8:132–143 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Anguela XM, High KA: Entering the modern era of gene therapy. Annu Rev Med 2019;70:273–288 [DOI] [PubMed] [Google Scholar]
  • 26. Lostalé-Seijo I, Montenegro J: Synthetic materials at the forefront of gene delivery. Nat Rev Chem 2018;2:258–277 [Google Scholar]
  • 27. Azibani F, Brull A, Arandel L, et al. : Gene therapy via trans-splicing for LMNA-related congenital muscular dystrophy. Mol Ther Nucleic Acids 2018;10:376–386 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Sune-Pou M, Prieto-Sanchez S, Boyero-Corral S, et al. : Targeting Splicing in the Treatment of Human Disease. Genes (Basel) 2017;8:87. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Arzalluz-Luque A, Conesa A: Single-cell RNAseq for the study of isoforms-how is that possible? Genome Biol 2018;19:110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Ensoli B, Barillari G, Salahuddin SZ, Gallo RC, Wong-Staal F: Tat protein of HIV-1 stimulates growth of cells derived from Kaposi's sarcoma lesions of AIDS patients. Nature 1990;345:84–86 [DOI] [PubMed] [Google Scholar]
  • 31. Yezid H, Konate K, Debaisieux S, Bonhoure A, Beaumelle B: Mechanism for HIV-1 Tat insertion into the endosome membrane. J Biol Chem 2009;284:22736–22746 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C: Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 2017;14:417–419 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Vitting-Seerup K, Sandelin A. IsoformSwitchAnalyzeR: Analysis of changes in genome-wide patterns of alternative splicing and its functional consequences. Bioinformatics 2019;35:4469–4471 [DOI] [PubMed] [Google Scholar]

Articles from AIDS Research and Human Retroviruses are provided here courtesy of SAGE Publications

RESOURCES