Targeting of multiple tumor-associated antigens by individual T cell receptors during successful cancer immunotherapy.

The T cells of the immune system can target tumors and clear solid cancers following tumor-infiltrating lymphocyte (TIL) therapy. We used combinatorial peptide libraries and a proteomic database to reveal the antigen specificities of persistent cancer-specific T cell receptors (TCRs) following successful TIL therapy for stage IV malignant melanoma. Remarkably, individual TCRs could target multiple different tumor types via the HLA A∗02:01-restricted epitopes EAAGIGILTV, LLLGIGILVL, and NLSALGIFST from Melan A, BST2, and IMP2, respectively. Atomic structures of a TCR bound to all three antigens revealed the importance of the shared x-x-x-A/G-I/L-G-I-x-x-x recognition motif. Multi-epitope targeting allows individual T cells to attack cancer in several ways simultaneously. Such "multipronged" T cells exhibited superior recognition of cancer cells compared with conventional T cell recognition of individual epitopes, making them attractive candidates for the development of future immunotherapies.

Emergence of immune escape at dominant SARS-CoV-2 killer T cell epitope.

We studied the prevalent cytotoxic CD8 T cell response mounted against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike glycoprotein269-277 epitope (sequence YLQPRTFLL) via the most frequent human leukocyte antigen (HLA) class I worldwide, HLA A∗02. The Spike P272L mutation that has arisen in at least 112 different SARS-CoV-2 lineages to date, including in lineages classified as "variants of concern," was not recognized by the large CD8 T cell response seen across cohorts of HLA A∗02+ convalescent patients and individuals vaccinated against SARS-CoV-2, despite these responses comprising of over 175 different individual T cell receptors. Viral escape at prevalent T cell epitopes restricted by high frequency HLAs may be particularly problematic when vaccine immunity is focused on a single protein such as SARS-CoV-2 Spike, providing a strong argument for inclusion of multiple viral proteins in next generation vaccines and highlighting the need for monitoring T cell escape in new SARS-CoV-2 variants.

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network.

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those 'next users' of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

Structural Mechanism Underpinning Cross-reactivity of a CD8+ T-cell Clone That Recognizes a Peptide Derived from Human Telomerase Reverse Transcriptase.

T-cell cross-reactivity is essential for effective immune surveillance but has also been implicated as a pathway to autoimmunity. Previous studies have demonstrated that T-cell receptors (TCRs) that focus on a minimal motif within the peptide are able to facilitate a high level of T-cell cross-reactivity. However, the structural database shows that most TCRs exhibit less focused antigen binding involving contact with more peptide residues. To further explore the structural features that allow the clonally expressed TCR to functionally engage with multiple peptide-major histocompatibility complexes (pMHCs), we examined the ILA1 CD8+ T-cell clone that responds to a peptide sequence derived from human telomerase reverse transcriptase. The ILA1 TCR contacted its pMHC with a broad peptide binding footprint encompassing spatially distant peptide residues. Despite the lack of focused TCR-peptide binding, the ILA1 T-cell clone was still cross-reactive. Overall, the TCR-peptide contacts apparent in the structure correlated well with the level of degeneracy at different peptide positions. Thus, the ILA1 TCR was less tolerant of changes at peptide residues that were at, or adjacent to, key contact sites. This study provides new insights into the molecular mechanisms that control T-cell cross-reactivity with important implications for pathogen surveillance, autoimmunity, and transplant rejection.

HLA A*24:02-restricted T cell receptors cross-recognize bacterial and preproinsulin peptides in type 1 diabetes.

CD8+ T cells destroy insulin-producing pancreatic ß cells in type 1 diabetes through HLA class I-restricted presentation of self-antigens. Combinatorial peptide library screening was used to produce a preferred peptide recognition landscape for a patient-derived T cell receptor (TCR) that recognized the preproinsulin-derived (PPI-derived) peptide sequence LWMRLLPLL in the context of disease risk allele HLA A*24:02. Data were used to generate a strong superagonist peptide, enabling production of an autoimmune HLA A*24:02-peptide-TCR structure by crystal seeding. TCR binding to the PPI epitope was strongly focused on peptide residues Arg4 and Leu5, with more flexibility at other positions, allowing the TCR to strongly engage many peptides derived from pathogenic bacteria. We confirmed an epitope from Klebsiella that was recognized by PPI-reactive T cells from 3 of 3 HLA A*24:02+ patients. Remarkably, the same epitope selected T cells from 7 of 8 HLA A*24+ healthy donors that cross-reacted with PPI, leading to recognition and killing of HLA A*24:02+ cells expressing PPI. These data provide a mechanism by which molecular mimicry between pathogen and self-antigens could have resulted in the breaking of self-tolerance to initiate disease.

A targeted single mutation in influenza A virus universal epitope transforms immunogenicity and protective immunity via CD4+ T cell activation.

CD4+ T cells are central to adaptive immunity. Their role in cross-protection in viral infections such as influenza and severe acute respiratory syndrome (SARS) is well documented; however, molecular rules governing T cell receptor (TCR) engagement of peptide-human leukocyte antigen (pHLA) class II are less understood. Here, we exploit an aspect of HLA class II presentation, the peptide-flanking residues (PFRs), to "tune" CD4+ T cell responses within an in vivo model system of influenza. Using a recombinant virus containing targeted substitutions at immunodominant HLA-DR1 epitopes, we demonstrate limited weight loss and improved clinical scores after heterosubtypic re-challenge. We observe enhanced protection linked to lung-derived influenza-specific CD4+ and CD8+ T cells prior to re-infection. Structural analysis of the ternary TCR:pHLA complex identifies that flanking amino acids influence side chains in the core 9-mer peptide, increasing TCR affinity. Augmentation of CD4+ T cell immunity is achievable with a single mutation, representing a strategy to enhance adaptive immunity that is decoupled from vaccine modality.

Large differences in CO2 emissions from two dairy farms on a drained peatland driven by contrasting respiration rates during seasonal dry conditions.

Drained peatlands are major sources of CO2 to the atmosphere, yet the effects of land management and hydrological extremes have been little-studied at spatial scales relevant to agricultural enterprises. We measured fluxes of CO2 using the eddy covariance (EC) technique at two adjacent dairy farms on a drained peatland in Aotearoa New Zealand with remaining peat depths 5.5-8 m. One site (SD) had shallow surface drains and mean water table depth (WTD) -657 mm, while the other site (BD) had deep field border drains and mean WTD -838 mm. Net ecosystem CO2 production (NEP) was similar at the two sites when the soils were moist but diverged during late-summer drying, with site BD having 4.56 t C ha-1 greater CO2 emission than site SD over the four-month dry period. Soil drying reduced gross primary production (GPP) at both sites, while ecosystem respiration (ER) was reduced at site SD but not at site BD. The low dry season respiration rates at site SD contributed to near-zero annual NEP, while higher respiration rates at site BD led to annual CO2 loss of -4.95 ± 0.59 t C ha-1 yr-1. Accounting for other imports and exports of carbon, annual net ecosystem carbon balances were -2.23 and -8.47 t C ha-1 yr-1 at sites SD and BD, respectively. It is likely that the contrasting dry season respiration rates resulted from differences in soil physical properties affecting soil moisture vertical redistribution and availability to plants and microbes rather than from the relatively small differences in WTD. These differences could be caused by soil physical disturbances during pasture renewal or paddock recontouring, or time since initial drainage. Therefore, improved soil management might provide practical mitigation against excessive CO2 emissions during dry conditions, including droughts.

Modelling the effects of pasture renewal on the carbon balance of grazed pastures.

In New Zealand, pasture renewal is a routine management method for maintaining pasture productivity. However, knowledge of the renewal effects on soil organic carbon (SOC) stocks is still limited. Here we use a process-based model, CenW, to comprehensively assess the effects of pasture renewal on the carbon balance of a temperate pasture in the Waikato region of New Zealand. We investigated the effects of renewal frequency, length of fallow period, renewal timing, and the importance and quantification of age-related reductions in productivity. Our results suggest that SOC change depends on the combined effects of renewal on gross primary productivity (GPP), autotrophic and heterotrophic respiration, carbon removal by grazing and carbon allocation to roots. Pasture renewal reduces grazing removal proportionately more than GPP because newly established plants need to allocate more carbon to re-build their root system following renewal which limits foliage production. That lengthens the time before above-ground biomass has grown sufficiently to be grazed again. New plants have a lower ratio of autotrophic respiration to GPP, however, which partly compensates for the GPP loss during renewal. Our simulations suggested an average SOC loss of 0.16 tC ha-1 yr-1 if pastures were renewed every 25 years, but could gain an average of 0.3 tC ha-1 yr-1 if pastures were renewed every year. For maximizing pasture production, the optimal renewal frequency depends on the rate of pasture deterioration with more rapid deterioration rates favouring more frequent renewal. Additionally, the length of the fallow period, renewal timing, and associated environmental conditions are important factors that can affect SOC temporally, but the importance of those effects diminishes at the annual or longer time scales. A major uncertainty for a full understanding of the renewal effect on SOC lies in the rate of pasture deterioration with time since previous renewal.

Recovery of the CO2 sink in a remnant peatland following water table lowering.

Peatland biological, physical and chemical properties change over time in response to alterations in long-term water table position. Such changes complicate our ability to predict the response of peatland carbon stocks to sustained drying. In order to better understand the effect of sustained lowering of the water table on peatland carbon dynamics, we re-visited a drainage-affected bog, repeating eddy covariance measurements of CO2 flux after a 16-year interval. We found the ecosystem CO2 sink to have strengthened across the intervening period, despite a deep and fluctuating water table. This was mostly due to an increase in CO2 uptake through photosynthesis associated with increased shrub growth. We also observed a decline in CO2 loss through ecosystem respiration. These changes could not be attributed to environmental conditions. Air temperature was the only significant contemporaneous driver of monthly anomalies in CO2 fluxes, with higher temperatures decreasing the net CO2 sink via increased ecosystem respiration. However, the effect of air temperature was weak in comparison to the underlying differences between time periods. Therefore, we demonstrate that for drying peatlands, long-term changes within the ecosystem can be of primary importance as drivers of CO2 exchange. In this peatland, the ecosystem carbon sink has shown resilience to water table drawdown, with internal feedbacks leading to a recovery of the CO2 sink after a 16-year interval.

GPU-Accelerated Discovery of Pathogen-Derived Molecular Mimics of a T-Cell Insulin Epitope.

The strong links between (Human Leukocyte Antigen) HLA, infection and autoimmunity combine to implicate T-cells as primary triggers of autoimmune disease (AD). T-cell crossreactivity between microbially-derived peptides and self-peptides has been shown to break tolerance and trigger AD in experimental animal models. Detailed examination of the potential for T-cell crossreactivity to trigger human AD will require means of predicting which peptides might be recognised by autoimmune T-cell receptors (TCRs). Recent developments in high throughput sequencing and bioinformatics mean that it is now possible to link individual TCRs to specific pathologies for the first time. Deconvolution of TCR function requires knowledge of TCR specificity. Positional Scanning Combinatorial Peptide Libraries (PS-CPLs) can be used to predict HLA-restriction and define antigenic peptides derived from self and pathogen proteins. In silico search of the known terrestrial proteome with a prediction algorithm that ranks potential antigens in order of recognition likelihood requires complex, large-scale computations over several days that are infeasible on a personal computer. We decreased the time required for peptide searching to under 30 min using multiple blocks on graphics processing units (GPUs). This time-efficient, cost-effective hardware accelerator was used to screen bacterial and fungal human pathogens for peptide sequences predicted to activate a T-cell clone, InsB4, that was isolated from a patient with type 1 diabetes and recognised the insulin B-derived epitope HLVEALYLV in the context of disease-risk allele HLA A*0201. InsB4 was shown to kill HLA A*0201+ human insulin producing ß-cells demonstrating that T-cells with this specificity might contribute to disease. The GPU-accelerated algorithm and multispecies pathogen proteomic databases were validated to discover pathogen-derived peptide sequences that acted as super-agonists for the InsB4 T-cell clone. Peptide-MHC tetramer binding and surface plasmon resonance were used to confirm that the InsB4 TCR bound to the highest-ranked peptide agonists derived from infectious bacteria and fungi. Adoption of GPU-accelerated prediction of T-cell agonists has the capacity to revolutionise our understanding of AD by identifying potential targets for autoimmune T-cells. This approach has further potential for dissecting T-cell responses to infectious disease and cancer.

CD4+ T Cells Recognize Conserved Influenza A Epitopes through Shared Patterns of V-Gene Usage and Complementary Biochemical Features.

T cell recognition of peptides presented by human leukocyte antigens (HLAs) is mediated by the highly variable T cell receptor (TCR). Despite this built-in TCR variability, individuals can mount immune responses against viral epitopes by using identical or highly related TCRs expressed on CD8+ T cells. Characterization of these TCRs has extended our understanding of the molecular mechanisms that govern the recognition of peptide-HLA. However, few examples exist for CD4+ T cells. Here, we investigate CD4+ T cell responses to the internal proteins of the influenza A virus that correlate with protective immunity. We identify five internal epitopes that are commonly recognized by CD4+ T cells in five HLA-DR1+ subjects and show conservation across viral strains and zoonotic reservoirs. TCR repertoire analysis demonstrates several shared gene usage biases underpinned by complementary biochemical features evident in a structural comparison. These epitopes are attractive targets for vaccination and other T cell therapies.

Water table fluctuations control CO2 exchange in wet and dry bogs through different mechanisms.

High water tables (WT) stabilise peatland carbon (C) through regulation of biogeochemical processes. The impact of peatland WT on ecosystem function, including C exchange, alters over time, and the factors that cause some peatlands to display resilience and others to undergo degradation are poorly understood. Here we use CO2 flux measurements, measured by eddy covariance, to compare ecosystem function between two raised bogs; one drainage-affected, with a deep and fluctuating water table and the other near-natural, with a shallow and stable water table. The drainage-affected bog was found to be a moderate sink for CO2 (69 g C m-2 yr-1), which was 134 g C m-2 yr-1 less than the near-natural bog (203 g C m-2 yr-1). Greater ecosystem productivity has allowed the drainage-impacted bog to act as a CO2 sink despite higher ecosystem respiration; most likely due to an increase in photosynthetic capacity caused by expansion of ericaceous shrub cover. The tolerance of the vegetation community, particularly the main peat former Empodisma robustum (Restionaceae), to low and fluctuating WT appears to have been key in allowing the site to remain a sink. Despite the current resilience of the ecosystem CO2 sink, we found gross primary production to be limited under both high and low water tables, even in a year with typical rainfall. This is best explained by the limited physiological ability of ericaceous shrubs to tolerate a fluctuating WT. As such we hypothesise that if the WT continues to drop and become even more unstable, then without further vegetation change, a reduction in gross primary production is likely which may in turn cause the site to become a source for CO2.

Peptide Super-Agonist Enhances T-Cell Responses to Melanoma.

Recent immunotherapeutic approaches using adoptive cell therapy, or checkpoint blockade, have demonstrated the powerful anti-cancer potential of CD8 cytotoxic T-lymphocytes (CTL). While these approaches have shown great promise, they are only effective in some patients with some cancers. The potential power, and relative ease, of therapeutic vaccination against tumour associated antigens (TAA) present in different cancers has been a long sought-after approach for harnessing the discriminating sensitivity of CTL to treat cancer and has seen recent renewed interest following cancer vaccination successes using unique tumour neoantigens. Unfortunately, results with TAA-targeted "universal" cancer vaccines (UCV) have been largely disappointing. Infectious disease models have demonstrated that T-cell clonotypes that recognise the same antigen should not be viewed as being equally effective. Extrapolation of this notion to UCV would suggest that the quality of response in terms of the T-cell receptor (TCR) clonotypes induced might be more important than the quantity of the response. Unfortunately, there is little opportunity to assess the effectiveness of individual T-cell clonotypes in vivo. Here, we identified effective, persistent T-cell clonotypes in an HLA A2+ patient following successful tumour infiltrating lymphocyte (TIL) therapy. One such T-cell clone was used to generate super-agonist altered peptide ligands (APLs). Further refinement produced an APL that was capable of inducing T-cells in greater magnitude, and with improved effectiveness, from the blood of all 14 healthy donors tested. Importantly, this APL also induced T-cells from melanoma patient blood that exhibited superior recognition of the patient's own tumour compared to those induced by the natural antigen sequence. These results suggest that use of APL to skew the clonotypic quality of T-cells induced by cancer vaccination could provide a promising avenue in the hunt for the UCV "magic bullet."

Optimized Peptide-MHC Multimer Protocols for Detection and Isolation of Autoimmune T-Cells.

Peptide-MHC (pMHC) multimers have become the "gold standard" for the detection and isolation of antigen-specific T-cells but recent evidence shows that normal use of these reagents can miss fully functional T-cells that bear T-cell receptors (TCRs) with low affinity for cognate antigen. This issue is particularly pronounced for anticancer and autoimmune T-cells as self-reactive T-cell populations are enriched for low-affinity TCRs due to the removal of cells with higher affinity receptors by immune tolerance mechanisms. Here, we stained a wide variety of self-reactive human T-cells using regular pMHC staining and an optimized technique that included: (i) protein kinase inhibitor (PKI), to prevent TCR triggering and internalization, and (ii) anti-fluorochrome antibody, to reduce reagent dissociation during washing steps. Lymphocytes derived from the peripheral blood of type 1 diabetes patients were stained with pMHC multimers made with epitopes from preproinsulin (PPI), insulin-ß chain, glutamic acid decarboxylase 65 (GAD65), or glucose-6-phospate catalytic subunit-related protein (IGRP) presented by disease-risk allelles HLA A*02:01 or HLA*24:02. Samples from ankylosing spondylitis patients were stained with a multimerized epitope from vasoactive intestinal polypeptide receptor 1 (VIPR1) presented by HLA B*27:05. Optimized procedures stained an average of 40.5-fold (p = 0.01, range between 1.4 and 198) more cells than could be detected without the inclusion of PKI and cross-linking anti-fluorochrome antibody. Higher order pMHC dextramers recovered more cells than pMHC tetramers in parallel assays, and standard staining protocols with pMHC tetramers routinely recovered less cells than functional assays. HLA A*02:01-restricted PPI-specific and HLA B*27:05-restricted VIPR1-specific T-cell clones generated using the optimized procedure could not be stained by standard pMHC tetramer staining. However, these clones responded well to exogenously supplied peptide and endogenously processed and presented epitopes. We also showed that anti-fluorochrome antibody-conjugated magnetic beads enhanced staining of self-reactive T-cells that could not be stained using standard protocols, thus enabling rapid ex vivo isolation of autoimmune T-cells. We, therefore, conclude that regular pMHC tetramer staining is generally unsuitable for recovering self-reactive T-cells from clinical samples and recommend the use of the optimized protocols described herein.

Thermal Stability of Heterotrimeric pMHC Proteins as Determined by Circular Dichroism Spectroscopy.

T cell receptor (TCR) recognition of foreign peptide fragments, presented by peptide major histocompatibility complex (pMHC), governs T-cell mediated protection against pathogens and cancer. Many factors govern T-cell sensitivity, including the affinity of the TCR-pMHC interaction and the stability of pMHC on the surface of antigen presenting cells. These factors are particularly relevant for the peptide vaccination field, in which more stable pMHC interactions could enable more effective protection against disease. Here, we discuss a method for the determination of pMHC stability that we have used to investigate HIV immune escape, T-cell sensitivity to cancer antigens and mechanisms leading to autoimmunity.

Modelling carbon and water exchange of a grazed pasture in New Zealand constrained by eddy covariance measurements.

We used two years of eddy covariance (EC) measurements collected over an intensively grazed dairy pasture to better understand the key drivers of changes in soil organic carbon stocks. Analysing grazing systems with EC measurements poses significant challenges as the respiration from grazing animals can result in large short-term CO2 fluxes. As paddocks are grazed only periodically, EC observations derive from a mosaic of paddocks with very different exchange rates. This violates the assumptions implicit in the use of EC methodology. To test whether these challenges could be overcome, and to develop a tool for wider scenario testing, we compared EC measurements with simulation runs with the detailed ecosystem model CenW 4.1. Simulations were run separately for 26 paddocks around the EC tower and coupled to a footprint analysis to estimate net fluxes at the EC tower. Overall, we obtained good agreement between modelled and measured fluxes, especially for the comparison of evapotranspiration rates, with model efficiency of 0.96 for weekly averaged values of the validation data. For net ecosystem productivity (NEP) comparisons, observations were omitted when cattle grazed the paddocks immediately around the tower. With those points omitted, model efficiencies for weekly averaged values of the validation data were 0.78, 0.67 and 0.54 for daytime, night-time and 24-hour NEP, respectively. While not included for model parameterisation, simulated gross primary production also agreed closely with values inferred from eddy covariance measurements (model efficiency of 0.84 for weekly averages). The study confirmed that CenW simulations could adequately model carbon and water exchange in grazed pastures. It highlighted the critical role of animal respiration for net CO2 fluxes, and showed that EC studies of grazed pastures need to consider the best approach of accounting for this important flux to avoid unbalanced accounting.