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.

Author Correction: Genome-wide CRISPR-Cas9 screening reveals ubiquitous T cell cancer targeting via the monomorphic MHC class I-related protein MR1.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genome-wide CRISPR-Cas9 screening reveals ubiquitous T cell cancer targeting via the monomorphic MHC class I-related protein MR1.

Human leukocyte antigen (HLA)-independent, T cell-mediated targeting of cancer cells would allow immune destruction of malignancies in all individuals. Here, we use genome-wide CRISPR-Cas9 screening to establish that a T cell receptor (TCR) recognized and killed most human cancer types via the monomorphic MHC class I-related protein, MR1, while remaining inert to noncancerous cells. Unlike mucosal-associated invariant T cells, recognition of target cells by the TCR was independent of bacterial loading. Furthermore, concentration-dependent addition of vitamin B-related metabolite ligands of MR1 reduced TCR recognition of cancer cells, suggesting that recognition occurred via sensing of the cancer metabolome. An MR1-restricted T cell clone mediated in vivo regression of leukemia and conferred enhanced survival of NSG mice. TCR transfer to T cells of patients enabled killing of autologous and nonautologous melanoma. These findings offer opportunities for HLA-independent, pan-cancer, pan-population immunotherapies.

Activation of naïve CD4+ T cells re-tunes STAT1 signaling to deliver unique cytokine responses in memory CD4+ T cells.

The cytokine IL-6 controls the survival, proliferation and effector characteristics of lymphocytes through activation of the transcription factors STAT1 and STAT3. While STAT3 activity is an ever-present feature of IL-6 signaling in CD4+ T cells, prior activation via the T cell antigen receptor limits IL-6's control of STAT1 in effector and memory populations. Here we found that phosphorylation of STAT1 in response to IL-6 was regulated by the tyrosine phosphatases PTPN2 and PTPN22 expressed in response to the activation of naïve CD4+ T cells. Transcriptomics and chromatin immunoprecipitation-sequencing (ChIP-seq) of IL-6 responses in naïve and effector memory CD4+ T cells showed how the suppression of STAT1 activation shaped the functional identity and effector characteristics of memory CD4+ T cells. Thus, tyrosine phosphatases induced by the activation of naïve T cells determine the way activated or memory CD4+ T cells sense and interpret cytokine signals.

Th1 Cells Alter the Inflammatory Signature of IL-6 by Channeling STAT Transcription Factors to Alu-like Retroelements.

Cytokines that signal via STAT1 and STAT3 transcription factors instruct decisions affecting tissue homeostasis, antimicrobial host defense, and inflammation-induced tissue injury. To understand the coordination of these activities, we applied RNA sequencing, chromatin immunoprecipitation sequencing, and assay for transposase-accessible chromatin with high-throughput sequencing to identify the transcriptional output of STAT1 and STAT3 in peritoneal tissues from mice during acute resolving inflammation and inflammation primed to drive fibrosis. Bioinformatics focused on the transcriptional signature of the immunomodulatory cytokine IL-6 in both settings and examined how profibrotic IFN-γ-secreting CD4+ T cells altered the interpretation of STAT1 and STAT3 cytokine cues. In resolving inflammation, STAT1 and STAT3 cooperated to drive stromal gene expression affecting antimicrobial immunity and tissue homeostasis. The introduction of IFN-γ-secreting CD4+ T cells altered this transcriptional program and channeled STAT1 and STAT3 to a previously latent IFN-γ activation site motif in Alu-like elements. STAT1 and STAT3 binding to this conserved sequence revealed evidence of reciprocal cross-regulation and gene signatures relevant to pathophysiology. Thus, we propose that effector T cells retune the transcriptional output of IL-6 by shaping a regulatory interplay between STAT1 and STAT3 in inflammation.

Responses of Salmonella biofilms to oxidizing biocides: Evidence of spatial clustering.

The spatial organization of biofilm bacterial communities can be influenced by several factors, including growth conditions and challenge with antimicrobials. Differential survival of clusters of cells within biofilms has been observed. In this work, we present a variety of methods to identify, quantify and statistically analyse clusters of live cells from images of two Salmonella strains with differential biofilm forming capacity exposed to three oxidizing biocides. With a support vector machine approach, we showed spatial separation between the two strains, and, using statistical testing and high-performance computing (HPC), we determined conditions which possess an inherent cluster structure. Our results indicate that there is a relationship between biocide potency and inherent biofilm formation capacity with the tendency to select for spatial clusters of survivors. There was no relationship between positions of clusters of live or dead cells within stressed biofilms. This work identifies an approach to robustly quantify clusters of physiologically distinct cells within biofilms and suggests work to understand how clusters form and survive is needed. SIGNIFICANCE STATEMENT: Control of biofilm growth remains a major challenge and there is considerable uncertainty about how bacteria respond to disinfection within a biofilm and how clustering of cells impacts survival. We have developed a methodological approach to identify and statistically analyse clusters of surviving cells in biofilms after biocide challenge. This approach can be used to understand bacterial behaviour within biofilms under stress and is widely applicable.

Single-Nucleus RNA Sequencing Identifies New Classes of Proximal Tubular Epithelial Cells in Kidney Fibrosis.

BACKGROUND: Proximal tubular cells (PTCs) are the most abundant cell type in the kidney. PTCs are central to normal kidney function and to regeneration versus organ fibrosis following injury. This study used single-nucleus RNA sequencing (snRNAseq) to describe the phenotype of PTCs in renal fibrosis. METHODS: Kidneys were harvested from naïve mice and from mice with renal fibrosis induced by chronic aristolochic acid administration. Nuclei were isolated using Nuclei EZ Lysis buffer. Libraries were prepared on the 10× platform, and snRNAseq was completed using the Illumina NextSeq 550 System. Genome mapping was carried out with high-performance computing. RESULTS: A total of 23,885 nuclei were analyzed. PTCs were found in five abundant clusters, mapping to S1, S1-S2, S2, S2-cortical S3, and medullary S3 segments. Additional cell clusters ("new PTC clusters") were at low abundance in normal kidney and in increased number in kidneys undergoing regeneration/fibrosis following injury. These clusters exhibited clear molecular phenotypes, permitting labeling as proliferating, New-PT1, New-PT2, and (present only following injury) New-PT3. Each cluster exhibited a unique gene expression signature, including multiple genes previously associated with renal injury response and fibrosis progression. Comprehensive pathway analyses revealed metabolic reprogramming, enrichment of cellular communication and cell motility, and various immune activations in new PTC clusters. In ligand-receptor analysis, new PTC clusters promoted fibrotic signaling to fibroblasts and inflammatory activation to macrophages. CONCLUSIONS: These data identify unrecognized PTC phenotype heterogeneity and reveal novel PTCs associated with kidney fibrosis.

Human leukocyte antigen (HLA) class II peptide flanking residues tune the immunogenicity of a human tumor-derived epitope.

CD4+ T-cells recognize peptide antigens, in the context of human leukocyte antigen (HLA) class II molecules (HLA-II), which through peptide-flanking residues (PFRs) can extend beyond the limits of the HLA binding. The role of the PFRs during antigen recognition is not fully understood; however, recent studies have indicated that these regions can influence T-cell receptor (TCR) affinity and pHLA-II stability. Here, using various biochemical approaches including peptide sensitivity ELISA and ELISpot assays, peptide-binding assays and HLA-II tetramer staining, we focused on CD4+ T-cell responses against a tumor antigen, 5T4 oncofetal trophoblast glycoprotein (5T4), which have been associated with improved control of colorectal cancer. Despite their weak TCR-binding affinity, we found that anti-5T4 CD4+ T-cells are polyfunctional and that their PFRs are essential for TCR recognition of the core bound nonamer. The high-resolution (1.95 Å) crystal structure of HLA-DR1 presenting the immunodominant 20-mer peptide 5T4111-130, combined with molecular dynamic simulations, revealed how PFRs explore the HLA-proximal space to contribute to antigen reactivity. These findings advance our understanding of what constitutes an HLA-II epitope and indicate that PFRs can tune weak affinity TCR-pHLA-II interactions.

Induction of influenza-specific local CD8 T-cells in the respiratory tract after aerosol delivery of vaccine antigen or virus in the Babraham inbred pig.

There is increasing evidence that induction of local immune responses is a key component of effective vaccines. For respiratory pathogens, for example tuberculosis and influenza, aerosol delivery is being actively explored as a method to administer vaccine antigens. Current animal models used to study respiratory pathogens suffer from anatomical disparity with humans. The pig is a natural and important host of influenza viruses and is physiologically more comparable to humans than other animal models in terms of size, respiratory tract biology and volume. It may also be an important vector in the birds to human infection cycle. A major drawback of the current pig model is the inability to analyze antigen-specific CD8+ T-cell responses, which are critical to respiratory immunity. Here we address this knowledge gap using an established in-bred pig model with a high degree of genetic identity between individuals, including the MHC (Swine Leukocyte Antigen (SLA)) locus. We developed a toolset that included long-term in vitro pig T-cell culture and cloning and identification of novel immunodominant influenza-derived T-cell epitopes. We also generated structures of the two SLA class I molecules found in these animals presenting the immunodominant epitopes. These structures allowed definition of the primary anchor points for epitopes in the SLA binding groove and established SLA binding motifs that were used to successfully predict other influenza-derived peptide sequences capable of stimulating T-cells. Peptide-SLA tetramers were constructed and used to track influenza-specific T-cells ex vivo in blood, the lungs and draining lymph nodes. Aerosol immunization with attenuated single cycle influenza viruses (S-FLU) induced large numbers of CD8+ T-cells specific for conserved NP peptides in the respiratory tract. Collectively, these data substantially increase the utility of pigs as an effective model for studying protective local cellular immunity against respiratory pathogens.

Peptide-MHC Class I Tetramers Can Fail To Detect Relevant Functional T Cell Clonotypes and Underestimate Antigen-Reactive T Cell Populations.

Peptide-MHC (pMHC) multimers, usually used as streptavidin-based tetramers, have transformed the study of Ag-specific T cells by allowing direct detection, phenotyping, and enumeration within polyclonal T cell populations. These reagents are now a standard part of the immunology toolkit and have been used in many thousands of published studies. Unfortunately, the TCR-affinity threshold required for staining with standard pMHC multimer protocols is higher than that required for efficient T cell activation. This discrepancy makes it possible for pMHC multimer staining to miss fully functional T cells, especially where low-affinity TCRs predominate, such as in MHC class II-restricted responses or those directed against self-antigens. Several recent, somewhat alarming, reports indicate that pMHC staining might fail to detect the majority of functional T cells and have prompted suggestions that T cell immunology has become biased toward the type of cells amenable to detection with multimeric pMHC. We use several viral- and tumor-specific pMHC reagents to compare populations of human T cells stained by standard pMHC protocols and optimized protocols that we have developed. Our results confirm that optimized protocols recover greater populations of T cells that include fully functional T cell clonotypes that cannot be stained by regular pMHC-staining protocols. These results highlight the importance of using optimized procedures that include the use of protein kinase inhibitor and Ab cross-linking during staining to maximize the recovery of Ag-specific T cells and serve to further highlight that many previous quantifications of T cell responses with pMHC reagents are likely to have considerably underestimated the size of the relevant populations.

Identification of human viral protein-derived ligands recognized by individual MHCI-restricted T-cell receptors.

Evidence indicates that autoimmunity can be triggered by virus-specific CD8(+) T cells that crossreact with self-derived peptide epitopes presented on the cell surface by major histocompatibility complex class I (MHCI) molecules. Identification of the associated viral pathogens is challenging because individual T-cell receptors can potentially recognize up to a million different peptides. Here, we generate peptide length-matched combinatorial peptide library (CPL) scan data for a panel of virus-specific CD8(+) T-cell clones spanning different restriction elements and a range of epitope lengths. CPL scan data drove a protein database search limited to viruses that infect humans. Peptide sequences were ranked in order of likelihood of recognition. For all anti-viral CD8(+) T-cell clones examined in this study, the index peptide was either the top-ranked sequence or ranked as one of the most likely sequences to be recognized. Thus, we demonstrate that anti-viral CD8(+) T-cell clones are highly focused on their index peptide sequence and that 'CPL-driven database searching' can be used to identify the inciting virus-derived epitope for a given CD8(+) T-cell clone. Moreover, to augment access to CPL-driven database searching, we have created a publicly accessible webtool. Application of these methodologies in the clinical setting may clarify the role of viral pathogens in the etiology of autoimmune diseases.

Modelling mechanical and chemical treatment of biofilms with two phenotypic resistance mechanisms.

Bacterial biofilms are notoriously difficult to eradicate owing to a number of tolerance mechanisms including physiological, physical, genotypic and phenotypic variations. Recent focus has shifted to phenotypic tolerance which is apparently the main defence mechanism that protects biofilms against long-term disinfection. Previous mathematical models have addressed phenotypic dynamics by considering adaptive response and persister formation separately. The aim of this manuscript is to consider a combined model to understand the interplay between these two defence mechanisms. We find that each mechanism protects the biofilm differently and hence responds differently to antibiotic challenge. We focus on on-off dosing that has been shown to eradicate each subpopulation alone. Our results indicate that the combined resistance exhibits qualitatively similar behavior to persister formation for short dosing times, and similar behavior to adaptive resistance for long dosing times. To further contrast the behavior of the model under different parameter regimes, we explore two classes of combination treatment that include mechanical and chemical treatments. The examples focus on different applications - pipe clearance and dental carrie prevention - and demonstrate the underlying conclusion that adaptive and persister mechanism provide protection for different challenges and are thus not redundant systems and each may require specific treatment plans.

Systems Approaches to Cell Culture-Derived Extracellular Vesicles for Acute Kidney Injury Therapy: Prospects and Challenges.

Acute kidney injury (AKI) is a heterogeneous syndrome, comprising diverse etiologies of kidney insults that result in high mortality and morbidity if not well managed. Although great efforts have been made to investigate underlying pathogenic mechanisms of AKI, there are limited therapeutic strategies available. Extracellular vesicles (EV) are membrane-bound vesicles secreted by various cell types, which can serve as cell-free therapy through transfer of bioactive molecules. In this review, we first overview the AKI syndrome and EV biology, with a particular focus on the technical aspects and therapeutic application of cell culture-derived EVs. Second, we illustrate how multi-omic approaches to EV miRNA, protein, and genomic cargo analysis can yield new insights into their mechanisms of action and address unresolved questions in the field. We then summarize major experimental evidence regarding the therapeutic potential of EVs in AKI, which we subdivide into stem cell and non-stem cell-derived EVs. Finally, we highlight the challenges and opportunities related to the clinical translation of animal studies into human patients.

Analysis of single nuclear chromatin accessibility reveals unique myeloid populations in human pancreatic ductal adenocarcinoma.

BACKGROUND: A better understanding of the pancreatic ductal adenocarcinoma (PDAC) immune microenvironment is critical to developing new treatments and improving outcomes. Myeloid cells are of particular importance for PDAC progression; however, the presence of heterogenous subsets with different ontogeny and impact, along with some fluidity between them, (infiltrating monocytes vs. tissue-resident macrophages; M1 vs. M2) makes characterisation of myeloid populations challenging. Recent advances in single cell sequencing technology provide tools for characterisation of immune cell infiltrates, and open chromatin provides source and function data for myeloid cells to assist in more comprehensive characterisation. Thus, we explore single nuclear assay for transposase accessible chromatin (ATAC) sequencing (snATAC-Seq), a method to analyse open gene promoters and transcription factor binding, as an important means for discerning the myeloid composition in human PDAC tumours. METHODS: Frozen pancreatic tissues (benign or PDAC) were prepared for snATAC-Seq using 10× Chromium technology. Signac was used for preliminary analysis, clustering and differentially accessible chromatin region identification. The genes annotated in promoter regions were used for Gene Ontology (GO) enrichment and cell type annotation. Gene signatures were used for survival analysis with The Cancer Genome Atlas (TCGA)-pancreatic adenocarcinoma (PAAD) dataset. RESULTS: Myeloid cell transcription factor activities were higher in tumour than benign pancreatic samples, enabling us to further stratify tumour myeloid populations. Subcluster analysis revealed eight distinct myeloid populations. GO enrichment demonstrated unique functions for myeloid populations, including interleukin-1b signalling (recruited monocytes) and intracellular protein transport (dendritic cells). The identified gene signature for dendritic cells influenced survival (hazard ratio = .63, p = .03) in the TCGA-PAAD dataset, which was unique to PDAC. CONCLUSIONS: These data suggest snATAC-Seq as a method for analysis of frozen human pancreatic tissues to distinguish myeloid populations. An improved understanding of myeloid cell heterogeneity and function is important for developing new treatment targets in PDAC.

Effect of periodic disinfection on persisters in a one-dimensional biofilm model.

It is well known that disinfection methods that successfully kill suspended bacterial populations often fail to eliminate bacterial biofilms. Recent efforts to understand biofilm survival have focused on the existence of small, but very tolerant, subsets of the bacterial population termed persisters. In this investigation, we analyze a mathematical model of disinfection that consists of a susceptible-persister population system embedded within a growing domain. This system is coupled to a reaction-diffusion system governing the antibiotic and nutrient. We analyze the effect of periodic and continuous dosing protocols on persisters in a one-dimensional biofilm model, using both analytic and numerical method. We provide sufficient conditions for the existence of steady-state solutions and show that these solutions may not be unique. Our results also indicate that the dosing ratio (the ratio of dosing time to period) plays an important role. For long periods, large dosing ratios are more effective than similar ratios for short periods. We also compare periodic to continuous dosing and find that the results also depend on the method of distributing the antibiotic within the dosing cycle.

Systems Biology Approaches for the Improvement of Oncolytic Virus-Based Immunotherapies.

Oncolytic virus (OV)-based immunotherapy is mainly dependent on establishing an efficient cell-mediated antitumor immunity. OV-mediated antitumor immunity elicits a renewed antitumor reactivity, stimulating a T-cell response against tumor-associated antigens (TAAs) and recruiting natural killer cells within the tumor microenvironment (TME). Despite the fact that OVs are unspecific cancer vaccine platforms, to further enhance antitumor immunity, it is crucial to identify the potentially immunogenic T-cell restricted TAAs, the main key orchestrators in evoking a specific and durable cytotoxic T-cell response. Today, innovative approaches derived from systems biology are exploited to improve target discovery in several types of cancer and to identify the MHC-I and II restricted peptide repertoire recognized by T-cells. Using specific computation pipelines, it is possible to select the best tumor peptide candidates that can be efficiently vectorized and delivered by numerous OV-based platforms, in order to reinforce anticancer immune responses. Beyond the identification of TAAs, system biology can also support the engineering of OVs with improved oncotropism to reduce toxicity and maintain a sufficient portion of the wild-type virus virulence. Finally, these technologies can also pave the way towards a more rational design of armed OVs where a transgene of interest can be delivered to TME to develop an intratumoral gene therapy to enhance specific immune stimuli.

Bifidobacterium affects antitumor efficacy of oncolytic adenovirus in a mouse model of melanoma.

Gut microbiota plays a key role in modulating responses to cancer immunotherapy in melanoma patients. Oncolytic viruses (OVs) represent emerging tools in cancer therapy, inducing a potent immunogenic cancer cell death (ICD) and recruiting immune cells in tumors, poorly infiltrated by T cells. We investigated whether the antitumoral activity of oncolytic adenovirus Ad5D24-CpG (Ad-CpG) was gut microbiota-mediated in a syngeneic mouse model of melanoma and observed that ICD was weakened by vancomycin-mediated perturbation of gut microbiota. Ad-CpG efficacy was increased by oral supplementation with Bifidobacterium, reducing melanoma progression and tumor-infiltrating regulatory T cells. Fecal microbiota was enriched in bacterial species belonging to the Firmicutes phylum in mice treated with both Bifidobacterium and Ad-CpG; furthermore, our data suggest that molecular mimicry between melanoma and Bifidobacterium-derived epitopes may favor activation of cross-reactive T cells and constitutes one of the mechanisms by which gut microbiota modulates OVs response.

Modeling the inhibition of breast cancer growth by GM-CSF.

M-CSF is overexpressed in breast cancer and is known to stimulate macrophages to produce VEGF resulting in angiogenesis. It has recently been shown that the growth factor GM-CSF injected into murine breast tumors slowed tumor growth by secreting soluble VEGF receptor-1 (sVEGFR-1) that binds and inactivates VEGF. This study presents a mathematical model that includes all the components above, as well as MCP-1, tumor cells, and oxygen. The model simulations are representative of the in vivo data through predictions of tumor growth using different protocol strategies for GM-CSF for the purpose of predicting higher degrees of treatment success. For example, our model predicts that once a week dosing of GM-CSF would be less effective than daily, twice a week, or three times a week treatment because of the presence of essential factors required for the anti-tumor effect of GM-CSF.

Systems Biology in ELIXIR: modelling in the spotlight.

In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR's future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.