Regulation of natural killer cells: analog peptide handshake goes digital
Bibliographic record
Abstract
As an immunology graduate student, I fondly remember Tak Mak likening the T-cell receptor (TCR) to an outstretched hand interrogating each major histocompatibility complex (MHC) antigen it encountered for tactile evidence of viral subversion. Through many series of thoughtful experiments and ultimately, X-ray crystallography, the molecular basis for T-cell specificity and MHC restriction was revealed. This reinforced the distinction between natural killer (NK) cells and T cells and the sophistication of TCR selection and recognition processes elevated T cells into a more advanced evolutionary niche. Immunology texts referenced ‘missing self’ as key to NK cell function, a model which has expanded into integration of multiple positive and negative signals determining the outcome of NK cell engagement. Discovery of antigenic specificity for murine cytomegalovirus and possibly other antigens, evidence of memory and expanding knowledge of their regulation by killer cell immunoglobulin like receptors (KIR) has forced re-evaluation of NK cell nature [1]. Ironically, the longstanding illusion of MHC-independence segregating them from T cells has given way to indicate a surprisingly consistent focus on the same MHC molecules. Interaction between KIR and class I MHC molecules is offset from that of the TCR in such a way that NK cells experience thousands of distinct MHC molecules as only a handful of different subsets. Although this avoids the most polymorphic part of MHC molecules, affinities of KIR/class I MHC interactions within the same broad subsets vary for different allelic pairings. This variability creates a wide range of activating and inhibitory signal intensities through which KIR molecules influence NK cell activation and the epistatic interactions underlying susceptibility or resistance to certain pathogens. The proximity of KIR binding to the peptide binding site of MHC molecules led to speculation and demonstration that the strength of interaction between KIR and an MHC molecule could also be affected by the nature of peptide bound [2]. Decisive regulatory effects the cellular peptide repertoire can have on NK cell activation against viruses arose from identification of HIV and hepatitis C virus peptides that triggered higher levels of human histocompatibility-linked leukocyte antigen (HLA)-E expression [3,4]. Upregulation of HLA-E increases signaling through either negative (NKG2A) or positive (NKG2C) receptors, depending on what the NK cell expressed or in some cases, on the peptide itself. Human cytomegalovirus encodes several peptides that bind HLA-E and trigger preferential expansion of NKG2C-expressing NK cells [5,6]. Many examples of peptide dependent modulation of KIR affinity for MHC have been reported, thus, peptide specificity and MHC dependence, the very things thought to separate them from T cells, are now considered integral to NK cell regulation and adaptation through KIR and other regulatory receptors [7–9]. In this issue, Ziegler et al.[10] conduct an in depth comparison of the total peptide repertoire presented by class I HLA molecules on resting, activated and HIV-infected activated CD4+ T cells. As certain MHC class I/KIR epistatic interactions can influence the course of viral infections, including HIV infection, there is a strong rationale for investigating the effect of viral infection on the peptide repertoire expressed and the subsequent impact of changes in the peptide repertoire on KIR/HLA binding [9]. The authors prepared cell lysates, purified class I MHC molecules and analyzed peptides bound to the MHC class I molecules by liquid chromatography coupled with tandem mass spectrometry. The experiments were repeated 6 months apart with the same source of CD4+ T cells to demonstrate reproducibility. Over 12 000 peptides binding to HLA-A, B and C molecules were identified with 1369 unique to nonactivated CD4+ T cells, 4716 unique to activated CD4+ T cells and 3962 unique to HIV-infected CD4+ T cells. These data demonstrate broad lability in the expressed peptide repertoire and distinctive influences of activation and HIV infection. An interesting point the authors noted, confirming previous studies, was that less than 0.2% of the peptides expressed on HIV-infected cells came from HIV [11]. Thus, HIV infection affects peptide generation and or transport globally, mostly through mechanisms other than production of HIV-encoded peptides that compete with self peptides. To determine how this might affect NK cell recognition of HIV-infected cells, the authors focused on HLA-C∗03:04, the ligand for inhibitory KIR2DL3. Using HLA-C∗03:04-transfected 721 221 cells and KIR2DL3-Fc fusion protein, they showed that the most abundant peptide bound to HLA-C∗03:04 on uninfected cells mediated strong binding of KIR2DL3 while the most abundant peptide bound to HLA-C∗03:04 on HIV-infected cells mediated weaker binding. These results were confirmed using KIR2DL3γ Jurkat reporter cells and the molecular structural basis for the difference was modeled with atomistic molecular dynamics simulation. While their focus on a single inhibitory KIR/MHC ligand pair necessarily oversimplifies the impact on NK cell recognition, this reductionist approach provides an important illustration of another facet of the arms race between infectious agents and the immune system. In this case, NK cells are potentially skewed toward activation against HIV-infected cells by the dominant changes that occur in peptides presented by HLA-C∗03:04. If this imposed a strong selective effect against a highly mutating virus like HIV, there would be pressure for emergence of variants shifting the peptide (s) bound to HLA-C∗03:04 toward increasing the affinity of KIR2DL3. Significantly, this form of selection was reported in a previous study involving KIR2DL2 [12]. The article in this issue shows that escape is not necessarily through a mutant HIV peptide that itself binds to HLA-C, but potentially by an HIV variant influencing which host peptide dominates binding to HLA-C. Growing appreciation for the complexity of NK cell recognition and regulation strategies contrasts with the static picture of TCR specificity for a single peptide/HLA pairing. Although the idiosyncratic CD8+ T-cell response is often effective, interrogation of MHC molecules by a single TCR is unidimensional relative to an NK cell's use of a panel of receptors to interpret and integrate meaning from the entire array of different peptide/HLA molecules present on a target cell surface. The ability of single NK cells to process information on the nature of a target cell through multiple HLA/peptide interactions across a broad range of affinities empowers a versatility unavailable to adaptive immune cells governed by clonotypic receptors. Acknowledgements Conflicts of interest There are no conflicts of interest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".