Fumarate induces vesicular release of mtDNA to drive innate immunity.

Mutations in fumarate hydratase (FH) cause hereditary leiomyomatosis and renal cell carcinoma1. Loss of FH in the kidney elicits several oncogenic signalling cascades through the accumulation of the oncometabolite fumarate2. However, although the long-term consequences of FH loss have been described, the acute response has not so far been investigated. Here we generated an inducible mouse model to study the chronology of FH loss in the kidney. We show that loss of FH leads to early alterations of mitochondrial morphology and the release of mitochondrial DNA (mtDNA) into the cytosol, where it triggers the activation of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING)-TANK-binding kinase 1 (TBK1) pathway and stimulates an inflammatory response that is also partially dependent on retinoic-acid-inducible gene I (RIG-I). Mechanistically, we show that this phenotype is mediated by fumarate and occurs selectively through mitochondrial-derived vesicles in a manner that depends on sorting nexin 9 (SNX9). These results reveal that increased levels of intracellular fumarate induce a remodelling of the mitochondrial network and the generation of mitochondrial-derived vesicles, which allows the release of mtDNAin the cytosol and subsequent activation of the innate immune response.

Listeria motility increases the efficiency of epithelial invasion during intestinal infection.

Listeria monocytogenes (Lm) is a food-borne pathogen that causes severe bacterial gastroenteritis, with high rates of hospitalization and mortality. Lm is ubiquitous in soil, water and livestock, and can survive and proliferate at low temperatures. Following oral ingestion of contaminated food, Lm crosses the epithelium through intestinal goblet cells in a mechanism mediated by Lm InlA binding host E-cadherin. Importantly, human infections typically occur with Lm growing at or below room temperature, which is flagellated and motile. Even though many important human bacterial pathogens are flagellated, little is known regarding the effect of Lm motility on invasion and immune evasion. Here, we used complementary imaging and computer modeling approaches to test the hypothesis that bacterial motility helps Lm locate and engage target cells permissive for invasion. Imaging explanted mouse and human intestine, we showed that Lm grown at room temperature uses motility to scan the epithelial surface and preferentially attach to target cells. Furthermore, we integrated quantitative parameters from our imaging experiments to construct a versatile "layered" cellular Potts model (L-CPM) that simulates host-pathogen dynamics. Simulated data are consistent with the hypothesis that bacterial motility enhances invasion by allowing bacteria to search the epithelial surface for their preferred invasion targets. Indeed, our model consistently predicts that motile bacteria invade twice as efficiently over the first hour of infection. We also examined how bacterial motility affected interactions with host cellular immunity. In a mouse model of persistent infection, we found that neutrophils migrated to the apical surface of the epithelium 5 hours post infection and interacted with Lm. Yet in contrast to the view that neutrophils "hunt" for bacteria, we found that these interactions were driven by motility of Lm-which moved at least ~50x faster than neutrophils. Furthermore, our L-CPM predicts that motile bacteria maintain their invasion advantage even in the presence of host phagocytes, with the balance between invasion and phagocytosis governed almost entirely by bacterial motility. In conclusion, our simulations provide insight into host pathogen interaction dynamics at the intestinal epithelial barrier early during infection.

Interpreting T-cell search "strategies" in the light of evolution under constraints.

Two decades of in vivo imaging have revealed how diverse T-cell motion patterns can be. Such recordings have sparked the notion of search "strategies": T cells may have evolved ways to search for antigen efficiently depending on the task at hand. Mathematical models have indeed confirmed that several observed T-cell migration patterns resemble a theoretical optimum; for example, frequent turning, stop-and-go motion, or alternating short and long motile runs have all been interpreted as deliberately tuned behaviours, optimising the cell's chance of finding antigen. But the same behaviours could also arise simply because T cells cannot follow a straight, regular path through the tight spaces they navigate. Even if T cells do follow a theoretically optimal pattern, the question remains: which parts of that pattern have truly been evolved for search, and which merely reflect constraints from the cell's migration machinery and surroundings? We here employ an approach from the field of evolutionary biology to examine how cells might evolve search strategies under realistic constraints. Using a cellular Potts model (CPM), where motion arises from intracellular dynamics interacting with cell shape and a constraining environment, we simulate evolutionary optimization of a simple task: explore as much area as possible. We find that our simulated cells indeed evolve their motility patterns. But the evolved behaviors are not shaped solely by what is functionally optimal; importantly, they also reflect mechanistic constraints. Cells in our model evolve several motility characteristics previously attributed to search optimisation-even though these features are not beneficial for the task given here. Our results stress that search patterns may evolve for other reasons than being "optimal". In part, they may be the inevitable side effects of interactions between cell shape, intracellular dynamics, and the diverse environments T cells face in vivo.

Computational modelling of cell motility modes emerging from cell-matrix adhesion dynamics.

Lymphocytes have been described to perform different motility patterns such as Brownian random walks, persistent random walks, and Lévy walks. Depending on the conditions, such as confinement or the distribution of target cells, either Brownian or Lévy walks lead to more efficient interaction with the targets. The diversity of these motility patterns may be explained by an adaptive response to the surrounding extracellular matrix (ECM). Indeed, depending on the ECM composition, lymphocytes either display a floating motility without attaching to the ECM, or sliding and stepping motility with respectively continuous or discontinuous attachment to the ECM, or pivoting behaviour with sustained attachment to the ECM. Moreover, on the long term, lymphocytes either perform a persistent random walk or a Brownian-like movement depending on the ECM composition. How the ECM affects cell motility is still incompletely understood. Here, we integrate essential mechanistic details of the lymphocyte-matrix adhesions and lymphocyte intrinsic cytoskeletal induced cell propulsion into a Cellular Potts model (CPM). We show that the combination of de novo cell-matrix adhesion formation, adhesion growth and shrinkage, adhesion rupture, and feedback of adhesions onto cell propulsion recapitulates multiple lymphocyte behaviours, for different lymphocyte subsets and various substrates. With an increasing attachment area and increased adhesion strength, the cells' speed and persistence decreases. Additionally, the model predicts random walks with short-term persistent but long-term subdiffusive properties resulting in a pivoting type of motility. For small adhesion areas, the spatial distribution of adhesions emerges as a key factor influencing cell motility. Small adhesions at the front allow for more persistent motility than larger clusters at the back, despite a similar total adhesion area. In conclusion, we present an integrated framework to simulate the effects of ECM proteins on cell-matrix adhesion dynamics. The model reveals a sufficient set of principles explaining the plasticity of lymphocyte motility.

Local actin dynamics couple speed and persistence in a cellular Potts model of cell migration.

Cell migration is astoundingly diverse. Molecular signatures, cell-cell interactions, and environmental structures each play their part in shaping cell motion, yielding numerous morphologies and migration modes. Nevertheless, in recent years, a simple unifying law was found to describe cell migration across many different cell types and contexts: faster cells turn less frequently. This universal coupling between speed and persistence (UCSP) was explained by retrograde actin flow from front to back, but it remains unclear how this mechanism generalizes to cells with complex shapes and cells migrating in structured environments, which may not have a well-defined front-to-back orientation. Here, we present an in-depth characterization of an existing cellular Potts model, in which cells polarize dynamically from a combination of local actin dynamics (stimulating protrusions) and global membrane tension along the perimeter (inhibiting protrusions). We first show that the UCSP emerges spontaneously in this model through a cross talk of intracellular mechanisms, cell shape, and environmental constraints, resembling the dynamic nature of cell migration in vivo. Importantly, we find that local protrusion dynamics suffice to reproduce the UCSP-even in cases in which no clear global, front-to-back polarity exists. We then harness the spatial nature of the cellular Potts model to show how cell shape dynamics limit both the speed and persistence a cell can reach and how a rigid environment such as the skin can restrict cell motility even further. Our results broaden the range of potential mechanisms underlying the speed-persistence coupling that has emerged as a fundamental property of migrating cells.

Eight-Color Multiplex Immunohistochemistry for Simultaneous Detection of Multiple Immune Checkpoint Molecules within the Tumor Microenvironment.

Therapies targeting immune checkpoint molecules CTLA-4 and PD-1/PD-L1 have advanced the field of cancer immunotherapy. New mAbs targeting different immune checkpoint molecules, such as TIM3, CD27, and OX40, are being developed and tested in clinical trials. To make educated decisions and design new combination treatment strategies, it is vital to learn more about coexpression of both inhibitory and stimulatory immune checkpoints on individual cells within the tumor microenvironment. Recent advances in multiple immunolabeling and multispectral imaging have enabled simultaneous analysis of more than three markers within a single formalin-fixed paraffin-embedded tissue section, with accurate cell discrimination and spatial information. However, multiplex immunohistochemistry with a maximized number of markers presents multiple difficulties. These include the primary Ab concentrations and order within the multiplex panel, which are of major importance for the staining result. In this article, we report on the development, optimization, and application of an eight-color multiplex immunohistochemistry panel, consisting of PD-1, PD-L1, OX40, CD27, TIM3, CD3, a tumor marker, and DAPI. This multiplex panel allows for simultaneous quantification of five different immune checkpoint molecules on individual cells within different tumor types. This analysis revealed major differences in the immune checkpoint expression patterns across tumor types and individual tumor samples. This method could ultimately, by characterizing the tumor microenvironment of patients who have been treated with different immune checkpoint modulators, form the rationale for the design of immune checkpoint-based immunotherapy in the future.

Adjuvant dendritic cell therapy in stage IIIB/C melanoma: the MIND-DC randomized phase III trial.

Autologous natural dendritic cells (nDCs) treatment can induce tumor-specific immune responses and clinical responses in cancer patients. In this phase III clinical trial (NCT02993315), 148 patients with resected stage IIIB/C melanoma were randomized to adjuvant treatment with nDCs (n = 99) or placebo (n = 49). Active treatment consisted of intranodally injected autologous CD1c+ conventional and plasmacytoid DCs loaded with tumor antigens. The primary endpoint was the 2-year recurrence-free survival (RFS) rate, whereas the secondary endpoints included median RFS, 2-year and median overall survival, adverse event profile, and immunological response The 2-year RFS rate was 36.8% in the nDC treatment group and 46.9% in the control group (p = 0.31). Median RFS was 12.7 months vs 19.9 months, respectively (hazard ratio 1.25; 90% CI: 0.88-1.79; p = 0.29). Median overall survival was not reached in both treatment groups (hazard ratio 1.32; 90% CI: 0.73-2.38; p = 0.44). Grade 3-4 study-related adverse events occurred in 5% and 6% of patients. Functional antigen-specific T cell responses could be detected in 67.1% of patients tested in the nDC treatment group vs 3.8% of patients tested in the control group (p < 0.001). In conclusion, while adjuvant nDC treatment in stage IIIB/C melanoma patients generated specific immune responses and was well tolerated, no benefit in RFS was observed.

Machine learning analysis of the T cell receptor repertoire identifies sequence features of self-reactivity.

The T cell receptor (TCR) determines specificity and affinity for both foreign and self-peptides presented by the major histocompatibility complex (MHC). Although the strength of TCR interactions with self-pMHC impacts T cell function, it has been challenging to identify TCR sequence features that predict T cell fate. To discern patterns distinguishing TCRs from naive CD4+ T cells with low versus high self-reactivity, we used data from 42 mice to train a machine learning (ML) algorithm that identifies population-level differences between TCRß sequence sets. This approach revealed that weakly self-reactive T cell populations were enriched for longer CDR3ß regions and acidic amino acids. We tested our ML predictions of self-reactivity using retrogenic mice with fixed TCRß sequences. Extrapolating our analyses to independent datasets, we predicted high self-reactivity for regulatory T cells and slightly reduced self-reactivity for T cells responding to chronic infections. Our analyses suggest a potential trade-off between TCR repertoire diversity and self-reactivity. A record of this paper's transparent peer review process is included in the supplemental information.

Tumor microenvironment shows an immunological abscopal effect in patients with NSCLC treated with pembrolizumab-radiotherapy combination.

BACKGROUND: Immunotherapy is currently part of the standard of care for patients with advanced-stage non-small cell lung cancer (NSCLC). However, many patients do not respond to this treatment, therefore combination strategies are being explored to increase clinical benefit. The PEMBRO-RT trial combined the therapeutic programmed cell death 1 (PD-1) antibody pembrolizumab with stereotactic body radiation therapy (SBRT) to increase the overall response rate and study the effects on the tumor microenvironment (TME). METHODS: Here, immune infiltrates in the TME of patients included in the PEMBRO-RT trial were investigated. Tumor biopsies of patients treated with pembrolizumab alone or combined with SBRT (a biopsy of the non-irradiated site) at baseline and during treatment were stained with multiplex immunofluorescence for CD3, CD8, CD20, CD103 and FoxP3 for lymphocytes, pan-cytokeratin for tumors, and HLA-ABC expression was determined. RESULTS: The total number of lymphocytes increased significantly after 6 weeks of treatment in the anti-PD-1 group (fold change: 1.87, 95% CI: 1.06 to 3.29) and the anti-PD-1+SBRT group (fold change: 2.29, 95% CI: 1.46 to 3.60). The combination of SBRT and anti-PD-1 induced a 4.87-fold increase (95% CI: 2.45 to 9.68) in CD103+ cytotoxic T-cells 6 weeks on treatment and a 2.56-fold increase (95% CI: 1.03 to 6.36) after anti-PD-1 therapy alone. Responders had a significantly higher number of lymphocytes at baseline than non-responders (fold difference 1.85, 95% CI: 1.04 to 3.29 for anti-PD-1 and fold change 1.93, 95% CI: 1.08 to 3.44 for anti-PD-1+SBRT). CONCLUSION: This explorative study shows that that lymphocyte infiltration in general, instead of the infiltration of a specific lymphocyte subset, is associated with response to therapy in patients with NSCLC.Furthermore, anti-PD-1+SBRT combination therapy induces an immunological abscopal effect in the TME represented by a superior infiltration of cytotoxic T cells as compared with anti-PD-1 monotherapy.

Testing Graphical Causal Models Using the R Package "dagitty".

Causal diagrams such as directed acyclic graphs (DAGs) are used in several scientific fields to help design and analyze studies that aim to infer causal effects from observational data; for example, DAGs can help identify suitable strategies to reduce confounding bias. However, DAGs can be difficult to design, and the validity of any DAG-derived strategy hinges on the validity of the postulated DAG itself. Researchers should therefore check whether the assumptions encoded in the DAG are consistent with the data before proceeding with the analysis. Here, we explain how the R package 'dagitty', based on the web tool dagitty.net, can be used to test the statistical implications of the assumptions encoded in a given DAG. We hope that this will help researchers discover model specification errors, avoid erroneous conclusions, and build better models. © 2021 The Authors. Basic Protocol 1: Constructing and importing DAG models from the dagitty web interface Support Protocol 1: Installing R, RStudio, and the dagitty package Basic Protocol 2: Testing DAGs against categorical data Basic Protocol 3: Testing DAGs against continuous data Support Protocol 2: Testing DAGs against continuous data with non-linearities Basic Protocol 4: Testing DAGs against a combination of categorical and continuous data.

CelltrackR: An R package for fast and flexible analysis of immune cell migration data.

Visualization of cell migration via time-lapse microscopy has greatly advanced our understanding of the immune system. However, subtle differences in migration dynamics are easily obscured by biases and imaging artifacts. While several analysis methods have been suggested to address these issues, an integrated tool implementing them is currently lacking. Here, we present celltrackR, an R package containing a diverse set of state-of-the-art analysis methods for (immune) cell tracks. CelltrackR supports the complete pipeline for track analysis by providing methods for data management, quality control, extracting and visualizing migration statistics, clustering tracks, and simulating cell migration. CelltrackR supports the analysis of both 2D and 3D cell tracks. CelltrackR is an open-source package released under the GPL-2 license, and is freely available on both GitHub and CRAN. Although the package was designed specifically for immune cell migration data, many of its methods will also be of use in other research areas dealing with moving objects.

Is T Cell Negative Selection a Learning Algorithm?

Our immune system can destroy most cells in our body, an ability that needs to be tightly controlled. To prevent autoimmunity, the thymic medulla exposes developing T cells to normal "self" peptides and prevents any responders from entering the bloodstream. However, a substantial number of self-reactive T cells nevertheless reaches the periphery, implying that T cells do not encounter all self peptides during this negative selection process. It is unclear if T cells can still discriminate foreign peptides from self peptides they haven't encountered during negative selection. We use an "artificial immune system"-a machine learning model of the T cell repertoire-to investigate how negative selection could alter the recognition of self peptides that are absent from the thymus. Our model reveals a surprising new role for T cell cross-reactivity in this context: moderate T cell cross-reactivity should skew the post-selection repertoire towards peptides that differ systematically from self. Moreover, even some self-like foreign peptides can be distinguished provided that the peptides presented in the thymus are not too similar to each other. Thus, our model predicts that negative selection on a well-chosen subset of self peptides would generate a repertoire that tolerates even "unseen" self peptides better than foreign peptides. This effect would resemble a "generalization" process as it is found in learning systems. We discuss potential experimental approaches to test our theory.

Site-specific functionality and tryptophan mimicry of lipidation in tetraspanin CD9.

Lipidation of transmembrane proteins regulates many cellular activities, including signal transduction, cell-cell communication, and membrane trafficking. However, how lipidation at different sites in a membrane protein affects structure and function remains elusive. Here, using native mass spectrometry we determined that wild-type human tetraspanins CD9 and CD81 exhibit nonstochastic distributions of bound acyl chains. We revealed CD9 lipidation at its three most frequent lipidated sites suffices for EWI-F binding, while cysteine-to-alanine CD9 mutations markedly reduced binding of EWI-F. EWI-F binding by CD9 was rescued by mutating all or, albeit to a lesser extent, only the three most frequently lipidated sites into tryptophans. These mutations did not affect the nanoscale distribution of CD9 in cell membranes, as shown by super-resolution microscopy using a CD9-specific nanobody. Thus, these data demonstrate site-specific, possibly conformation-dependent, functionality of lipidation in tetraspanin CD9 and identify tryptophan mimicry as a possible biochemical approach to study site-specific transmembrane-protein lipidation.

Surviving Stress: Modulation of ATF4-Mediated Stress Responses in Normal and Malignant Cells.

Activating transcription factor 4 (ATF4) is a stress-induced transcription factor that is frequently upregulated in cancer cells. ATF4 controls the expression of a wide range of adaptive genes that allow cells to endure periods of stress, such as hypoxia or amino acid limitation. However, under persistent stress conditions, ATF4 promotes the induction of apoptosis. Recent advances point to a role for post-translational modifications (PTMs) and epigenetic mechanisms in balancing these pro- and anti-survival effects of ATF4. We review here how PTMs and epigenetic modifiers associated with ATF4 may be exploited by cancer cells to cope with cellular stress conditions that are intrinsically associated with tumor growth. Identification of mechanisms that modulate ATF4-mediated transcription and its effects on cellular metabolism may uncover new targets for cancer treatment.

Human CD1c(+) DCs are critical cellular mediators of immune responses induced by immunogenic cell death.

Chemotherapeutics, including the platinum compounds oxaliplatin (OXP) and cisplatin (CDDP), are standard care of treatment for cancer. Although chemotherapy has long been considered immunosuppressive, evidence now suggests that certain cytotoxic agents can efficiently stimulate antitumor responses, through the induction of a form of apoptosis, called immunogenic cell death (ICD). ICD is characterized by exposure of calreticulin and heat shock proteins (HSPs), secretion of ATP and release of high-mobility group box 1 (HMGB1). Proper activation of the immune system relies on the integration of these signals by dendritic cells (DCs). Studies on the crucial role of DCs, in the context of ICD, have been performed using mouse models or human in vitro-generated monocyte-derived DCs (moDCs), which do not fully recapitulate the in vivo situation. Here, we explore the effect of platinum-induced ICD on phenotype and function of human blood circulating DCs. Tumor cells were treated with OXP or CDDP and induction of ICD was investigated. We show that both platinum drugs triggered translocation of calreticulin and HSP70, as well as the release of ATP and HMGB1. Platinum treatment increased phagocytosis of tumor fragments by human blood DCs and enhanced phenotypic maturation of blood myeloid and plasmacytoid DCs. Moreover, upon interaction with platinum-treated tumor cells, CD1c(+) DCs efficiently stimulated allogeneic proliferation of T lymphocytes. Together, our observations indicate that platinum-treated tumor cells may exert an active stimulatory effect on human blood DCs. In particular, these data suggest that CD1c(+) DCs are critical mediators of immune responses induced by ICD.