Immune Responses Elicited in Tertiary Lymphoid Tissues Display Distinctive Features

During chronic inflammation, immune effectors progressively organize themselves into a functional tertiary lymphoid tissue (TLT) within the targeted organ. TLT has been observed in a wide range of chronic inflammatory conditions but its pathophysiological significance remains unknown. We used the rat aortic interposition model in which a TLT has been evidenced in the adventitia of chronically rejected allografts one month after transplantation. The immune responses elicited in adventitial TLT and those taking place in spleen and draining lymph nodes (LN) were compared in terms of antibody production, T cell activation and repertoire perturbations. The anti-MHC humoral response was more intense and more diverse in TLT. This difference was associated with an increased percentage of activated CD4+ T cells and a symmetric reduction of regulatory T cell subsets. Moreover, TCR repertoire perturbations in TLT were not only increased and different from the common pattern observed in spleen and LN but also “stochastic,” since each recipient displayed a specific pattern. We propose that the abnormal activation of CD4+ T cells promotes the development of an exaggerated pathogenic immune humoral response in TLT. Preliminary findings suggest that this phenomenon i) is due to a defective immune regulation in this non-professional inflammatory-induced lymphoid tissue, and ii) also occurs in human chronically rejected grafts.     

From Cellular Characteristics to Disease Diagnosis: Uncovering Phenotypes with Supercells

Cell heterogeneity and the inherent complexity due to the interplay of multiple molecular processes within the cell pose difficult challenges for current single-cell biology. We introduce an approach that identifies a disease phenotype from multiparameter single-cell measurements, which is based on the concept of “supercell statistics”, a single-cell-based averaging procedure followed by a machine learning classification scheme. We are able to assess the optimal tradeoff between the number of single cells averaged and the number of measurements needed to capture phenotypic differences between healthy and diseased patients, as well as between different diseases that are difficult to diagnose otherwise. We apply our approach to two kinds of single-cell datasets, addressing the diagnosis of a premature aging disorder using images of cell nuclei, as well as the phenotypes of two non-infectious uveitides (the ocular manifestations of Behçet''s disease and sarcoidosis) based on multicolor flow cytometry. In the former case, one nuclear shape measurement taken over a group of 30 cells is sufficient to classify samples as healthy or diseased, in agreement with usual laboratory practice. In the latter, our method is able to identify a minimal set of 5 markers that accurately predict Behçet''s disease and sarcoidosis. This is the first time that a quantitative phenotypic distinction between these two diseases has been achieved. To obtain this clear phenotypic signature, about one hundred CD8⁺ T cells need to be measured. Although the molecular markers identified have been reported to be important players in autoimmune disorders, this is the first report pointing out that CD8⁺ T cells can be used to distinguish two systemic inflammatory diseases. Beyond these specific cases, the approach proposed here is applicable to datasets generated by other kinds of state-of-the-art and forthcoming single-cell technologies, such as multidimensional mass cytometry, single-cell gene expression, and single-cell full genome sequencing techniques.     

Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling

Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10) to increase sensitivity, followed by computational “deconvolution” of cellular heterogeneity parameters (CHPs), such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of ‘ON’ versus ‘OFF’ cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies.     

Single-cell analysis of skin immune cells reveals an Angptl4-ifi20b axis that regulates monocyte differentiation during wound healing

The persistent inflammatory response at the wound site is a cardinal feature of nonhealing wounds. Prolonged neutrophil presence in the wound site due to failed clearance by reduced monocyte-derived macrophages delays the transition from the inflammatory to the proliferative phase of wound healing. Angiopoietin-like 4 protein (Angptl4) is a matricellular protein that has been implicated in many inflammatory diseases. However, its precise role in the immune cell response during wound healing remains unclear. Therefore, we performed flow cytometry and single-cell RNA sequencing to examine the immune cell landscape of excisional wounds from Angptl4^+/+ and Angptl4^−/− mice. Chemotactic immune cell recruitment and infiltration were not compromised due to Angptl4 deficiency. However, as wound healing progresses, Angptl4^−/− wounds have a prolonged neutrophil presence and fewer monocyte-derived macrophages than Angptl4^+/+ and Angptl4^LysM−/− wounds. The underlying mechanism involves a novel Angptl4-interferon activated gene 202B (ifi202b) axis that regulates monocyte differentiation to macrophages, coordinating neutrophil removal and inflammation resolution. An unbiased kinase inhibitor screen revealed an Angptl4-mediated kinome signaling network involving S6K, JAK, and CDK, among others, that modulates the expression of ifi202b. Silencing ifi202b in Angptl4^−/− monocytes, whose endogenous expression was elevated, rescued the impaired monocyte-to-macrophage transition in the in vitro reconstituted wound microenvironment using wound exudate. GSEA and IPA functional analyses revealed that ifi202b-associated canonical pathways and functions involved in the inflammatory response and monocyte cell fate were enriched. Together, we identified ifi202b as a key gatekeeper of monocyte differentiation. By modulating ifi202b expression, Angptl4 orchestrates the inflammatory state, innate immune landscape, and wound healing process.Subject terms: Acute inflammation, Acute inflammation     

Inflammatory and immune markers in HIV‐infected older adults on long‐term antiretroviral therapy: Persistent elevation of sCD14 and of proinflammatory effector memory T cells

HIV‐positive patients whose viral loads are successfully controlled by active antiretroviral therapy (ART) show no clinical signs of AIDS. However, their lifespan is shorter compared with individuals with no HIV infection and they prematurely exhibit a multitude of chronic diseases typically associated with advanced age. It was hypothesized that immune system aging may correlate with, and provide useful biomarkers for, this premature loss of healthspan in HIV‐positive subjects. Here, we tested whether the immune correlates of aging, including cell numbers and phenotypes, inflammatory status, and control of human cytomegalovirus (hCMV) in HIV‐positive subjects on long‐term successful ART (HIV+) may reveal increased “immunological age” compared with HIV‐negative, age‐matched cohort (HIV−) in participants between 50 and 69 years of age. Specifically, we expected that younger HIV+ subjects may immunologically resemble older individuals without HIV. We found no evidence to support this hypothesis. While T cells from HIV+ participants displayed differential expression in several differentiation and/or inhibitory/exhaustion markers in different T cell subpopulations, aging by a decade did not pronounce these changes. Similarly, while the HIV+ participants exhibited higher T cell responses and elevated inflammatory marker levels in plasma, indicative of chronic inflammation, this trait was not age‐sensitive. We did find differences in immune control of hCMV, and, more importantly, a sustained elevation of sCD14 and of proinflammatory CD4 and CD8 T cell responses across age groups, pointing towards uncontrolled inflammation as a factor in reduced healthspan in successfully treated older HIV+ patients.     

The Potential Regulatory Mechanisms of miR-196a in Huntington’s Disease through Bioinformatic Analyses

High throughput screening is a powerful tool to identify the potential candidate molecules involved during disease progression. However, analysis of complicated data is one of the most challenging steps on the way to obtaining useful results from this approach. Previously, we showed that a specific miRNA, miR-196a, could ameliorate the pathological phenotypes of Huntington’s disease (HD) in different models, and performed high throughput screening by using the striatum of transgenic mice. In this study, we further tried to identify the potential regulatory mechanisms using different bioinformatic tools, including Database for Annotation, Visualization and Integrated Discovery (DAVID), Molecular Signatures Database (MSigDB), TargetScan and MetaCore. The results showed that miR-196a dominantly altered “ABC transporters”, “RIG-I-like receptor signaling pathway”, immune system”, “adaptive immune system”,“tissue remodeling and wound repair” and “cytoskeleton remodeling”. In addition, miR-196a also changed the expression of several well-defined pathways of HD, such as apoptosis and cell adhesion. Since these analyses showed the regulatory pathways are highly related to the modification of the cytoskeleton, we further confirmed that miR-196a could enhance the neurite outgrowth in neuroblastoma cells, suggesting miR-196a might provide beneficial functions through the alteration of cytoskeleton structures. Since impairment of the cytoskeleton has been reported in several neuronal diseases, this study will provide not only the potential working mechanisms of miR-196a but also insights for therapeutic strategies for use with different neuronal diseases.     

Construction of disease-specific cytokine profiles by associating disease genes with immune responses

The pathogenesis of many inflammatory diseases is a coordinated process involving metabolic dysfunctions and immune response—usually modulated by the production of cytokines and associated inflammatory molecules. In this work, we seek to understand how genes involved in pathogenesis which are often not associated with the immune system in an obvious way communicate with the immune system. We have embedded a network of human protein-protein interactions (PPI) from the STRING database with 14,707 human genes using feature learning that captures high confidence edges. We have found that our predicted Association Scores derived from the features extracted from STRING’s high confidence edges are useful for predicting novel connections between genes, thus enabling the construction of a full map of predicted associations for all possible pairs between 14,707 human genes. In particular, we analyzed the pattern of associations for 126 cytokines and found that the six patterns of cytokine interaction with human genes are consistent with their functional classifications. To define the disease-specific roles of cytokines we have collected gene sets for 11,944 diseases from DisGeNET. We used these gene sets to predict disease-specific gene associations with cytokines by calculating the normalized average Association Scores between disease-associated gene sets and the 126 cytokines; this creates a unique profile of inflammatory genes (both known and predicted) for each disease. We validated our predicted cytokine associations by comparing them to known associations for 171 diseases. The predicted cytokine profiles correlate (p-value<0.0003) with the known ones in 95 diseases. We further characterized the profiles of each disease by calculating an “Inflammation Score” that summarizes different modes of immune responses. Finally, by analyzing subnetworks formed between disease-specific pathogenesis genes, hormones, receptors, and cytokines, we identified the key genes responsible for interactions between pathogenesis and inflammatory responses. These genes and the corresponding cytokines used by different immune disorders suggest unique targets for drug discovery.     

Immune repertoire analysis of normal Chinese donors at different ages

ObjectivesThis study investigated the characteristics of the immune repertoire in normal Chinese individuals of different ages.Materials and MethodsIn this study, all seven receptor chains from both B and T cells in peripheral blood of 16 normal Chinese individuals from two age groups were analyzed using high‐throughput sequencing and dimer‐avoided multiplex PCR amplification. Normal in this study is defined as no chronic, infectious or autoimmune disease within 6 months prior to blood draw.ResultsWe found that compared with the younger group, the clonal expression of T‐cell receptor repertoire increased in the older group, while diversity decreased. In addition, we found that the T‐cell receptor repertoire was more significantly affected by age than the B‐cell receptor repertoire, including significant differences in the use of the unique TCR‐alpha and TCR‐beta V‐J gene combinations, in the two groups of normal participants. We further analyzed the degree of complementarity determining region 3 sequence sharing between the two groups, and found shared TCR‐alpha, TCR‐gamma, immunoglobulin‐kappa and immunoglobulin‐lambda chain complementarity determining region 3 sequences in all subjects.ConclusionTaken together, our study gives us a better understanding of the immune repertoire of different normal Chinese people, and these results can be applied to the treatment of age‐related diseases. Immune repertoire analysis also allows us to observe participant''s wellness, aiding in early‐stage diagnosis.

With aging, the body''s thymus involution, T and B cells senescence, T cell clones expand, the diversity of the TCR repertoire decreases, and the immunity of the body''s immune system decreases.     

Induction of Murine Intestinal Inflammation by Adoptive Transfer of Effector CD4+CD45RBhigh T Cells into Immunodeficient Mice

There are many different animal models available for studying the pathogenesis of human inflammatory bowel diseases (IBD), each with its own advantages and disadvantages. We describe here an experimental colitis model that is initiated by adoptive transfer of syngeneic splenic CD4⁺CD45RB^high T cells into T and B cell deficient recipient mice. The CD4⁺CD45RB^high T cell population that largely consists of naïve effector cells is capable of inducing chronic intestinal inflammation, closely resembling key aspects of human IBD. This method can be manipulated to study aspects of disease onset and progression. Additionally it can be used to study the function of innate, adaptive, and regulatory immune cell populations, and the role of environmental exposures, i.e., the microbiota, in intestinal inflammation. In this article we illustrate the methodology for inducing colitis with a step-by-step protocol. This includes a video demonstration of key technical aspects required to successfully develop this murine model of experimental colitis for research purposes.     

Nodular Inflammatory Foci Are Sites of T Cell Priming and Control of Murine Cytomegalovirus Infection in the Neonatal Lung

Neonates, including mice and humans, are highly susceptible to cytomegalovirus (CMV) infection. However, many aspects of neonatal CMV infections such as viral cell tropism, spatio-temporal distribution of the pathogen as well as genesis of antiviral immunity are unknown. With the use of reporter mutants of the murine cytomegalovirus (MCMV) we identified the lung as a primary target of mucosal infection in neonatal mice. Comparative analysis of neonatal and adult mice revealed a delayed control of virus replication in the neonatal lung mucosa explaining the pronounced systemic infection and disease in neonates. This phenomenon was supplemented by a delayed expansion of CD8⁺ T cell clones recognizing the viral protein M45 in neonates. We detected viral infection at the single-cell level and observed myeloid cells forming “nodular inflammatory foci” (NIF) in the neonatal lung. Co-localization of infected cells within NIFs was associated with their disruption and clearance of the infection. By 2-photon microscopy, we characterized how neonatal antigen-presenting cells (APC) interacted with T cells and induced mature adaptive immune responses within such NIFs. We thus define NIFs of the neonatal lung as niches for prolonged MCMV replication and T cell priming but also as sites of infection control.     

The Suppression of Immune System Disorders by Passive Attrition

Exposure to infectious diseases has an unexpected benefit of inhibiting autoimmune diseases and allergies. This is one of many fundamental fitness tradeoffs associated with immune system architecture. The immune system attacks pathogens, but also may (inappropriately) attack the host. Exposure to pathogens can suppress the deleterious response, at the price of illness and the decay of immunity to previous diseases. This “hygiene hypothesis” has been associated with several possible underlying biological mechanisms. This study focuses on physiological constraints that lead to competition for survival between immune system cell types. Competition maintains a relatively constant total number of cells within each niche. The constraint implies that adding cells conferring new immunity requires loss (passive attrition) of some cells conferring previous immunities. We consider passive attrition as a mechanism to prevent the initial proliferation of autoreactive cells, thus preventing autoimmune disease. We see that this protection is a general property of homeostatic regulation and we look specifically at both the IL-15 and IL-7 regulated niches to make quantitative predictions using a mathematical model. This mathematical model yields insight into the dynamics of the “Hygiene Hypothesis,” and makes quantitative predictions for experiments testing the ability of passive attrition to suppress immune system disorders. The model also makes a prediction of an anti-correlation between prevalence of immune system disorders and passive attrition rates.     

Annexin A1 on the Surface of Early Apoptotic Cells Suppresses CD8+ T Cell Immunity

Prevention of an immune response against self-antigens derived from apoptotic cells is essential to preclude autoimmune and chronic inflammatory diseases. Here, we describe apoptosis induced externalization of endogenous cytosolic annexin 1 initiating an anti-inflammatory effector mechanism that suppresses the immune response against antigens of apoptotic cells. Cytosolic annexin 1 rapidly translocated to the apoptotic cell surface and inhibited dendritic cell (DC) activation induced by Toll like receptors (TLR). Annexin 1-inhibited DC showed strongly reduced secretion of pro-inflammatory cytokines (e.g. TNF and IL-12) and costimulatory surface molecules (e.g. CD40 and CD86), while anti-inflammatory mediators like PD-L1 remained unchanged. T cells stimulated by such DC lacked secretion of interferon-γ (IFN-γ) and TNF but retained IL-10 secretion. In mice, annexin 1 prevented the development of inflammatory DC and suppressed the cellular immune response against the model antigen ovalbumin (OVA) expressed in apoptotic cells. Furthermore, annexin 1 on apoptotic cells compromised OVA-specific tumor vaccination and impaired rejection of an OVA-expressing tumor. Thus, our results provide a molecular mechanism for the suppressive activity of apoptotic cells on the immune response towards apoptotic cell-derived self-antigens. This process may play an important role in prevention of autoimmune diseases and of the immune response against cancer.     

Modeling the impact of single-cell stochasticity and size control on the population growth rate in asymmetrically dividing cells

Microbial populations show striking diversity in cell growth morphology and lifecycle; however, our understanding of how these factors influence the growth rate of cell populations remains limited. We use theory and simulations to predict the impact of asymmetric cell division, cell size regulation and single-cell stochasticity on the population growth rate. Our model predicts that coarse-grained noise in the single-cell growth rate λ decreases the population growth rate, as previously seen for symmetrically dividing cells. However, for a given noise in λ we find that dividing asymmetrically can enhance the population growth rate for cells with strong size control (between a “sizer” and an “adder”). To reconcile this finding with the abundance of symmetrically dividing organisms in nature, we propose that additional constraints on cell growth and division must be present which are not included in our model, and we explore the effects of selected extensions thereof. Further, we find that within our model, epigenetically inherited generation times may arise due to size control in asymmetrically dividing cells, providing a possible explanation for recent experimental observations in budding yeast. Taken together, our findings provide insight into the complex effects generated by non-canonical growth morphologies.     

AIC649 Induces a Bi-Phasic Treatment Response in the Woodchuck Model of Chronic Hepatitis B

AIC649 has been shown to directly address the antigen presenting cell arm of the host immune defense leading to a regulated cytokine release and activation of T cell responses. In the present study we analyzed the antiviral efficacy of AIC649 as well as its potential to induce functional cure in animal models for chronic hepatitis B. Hepatitis B virus transgenic mice and chronically woodchuck hepatitis virus (WHV) infected woodchucks were treated with AIC649, respectively. In the mouse system AIC649 decreased the hepatitis B virus titer as effective as the “gold standard”, Tenofovir. Interestingly, AIC649-treated chronically WHV infected woodchucks displayed a bi-phasic pattern of response: The marker for functional cure—hepatitis surface antigen—first increased but subsequently decreased even after cessation of treatment to significantly reduced levels. We hypothesize that the observed bi-phasic response pattern to AIC649 treatment reflects a physiologically “concerted”, reconstituted immune response against WHV and therefore may indicate a potential for inducing functional cure in HBV-infected patients.     

Synergic Activation of Toll-Like Receptor (TLR) 2/6 and 9 in Response to Ureaplasma parvum & urealyticum in Human Amniotic Epithelial Cells

Ureaplasma species are the most frequently isolated microorganisms inside the amniotic cavity and have been associated with spontaneous abortion, chorioamnionitis, premature rupture of the membranes (PROM), preterm labour (PL) pneumonia in neonates and bronchopulmonary dysplasia in neonates. The mechanisms by which Ureaplasmas cause such diseases remain unclear, but it is believed that inappropriate induction of inflammatory responses is involved, triggered by the innate immune system. As part of its mechanism of activation, the innate immune system employs germ-lined encoded receptors, called pattern recognition receptors (PRRs) in order to “sense” pathogens. One such family of PRRs are the Toll like receptor family (TLR). In the current study we aimed to elucidate the role of TLRs in Ureaplasma-induced inflammation in human amniotic epithelial cells. Using silencing, as well as human embryonic kidney (HEK) transfected cell lines, we demonstrate that TLR2, TLR6 and TLR9 are involved in the inflammatory responses against Ureaplasma parvum and urealyticum serovars. Ureaplasma lipoproteins, such as Multiple Banded antigen (MBA), trigger responses via TLR2/TLR6, whereas the whole bacterium is required for TLR9 activation. No major differences were observed between the different serovars. Cell activation by Ureaplasma parvum and urealyticum seem to require lipid raft function and formation of heterotypic receptor complexes comprising of TLR2 and TLR6 on the cell surface and TLR9 intracellularly.     

Practical,Microfabrication-Free Device for Single-Cell Isolation

Microfabricated devices have great potential in cell-level studies, but are not easily accessible for the broad biology community. This paper introduces the Microscale Oil-Covered Cell Array (MOCCA) as a low-cost device for high throughput single-cell analysis that can be easily produced by researchers without microengineering knowledge. Instead of using microfabricated structures to capture cells, MOCCA isolates cells in discrete aqueous droplets that are separated by oil on patterned hydrophilic areas across a relatively more hydrophobic substrate. The number of randomly seeded Escherichia coli bacteria in each discrete droplet approaches single-cell levels. The cell distribution on MOCCA is well-fit with Poisson distribution. In this pioneer study, we created an array of 900-picoliter droplets. The total time needed to seed cells in ∼3000 droplets was less than 10 minutes. Compared to traditional microfabrication techniques, MOCCA dramatically lowers the cost of microscale cell arrays, yet enhances the fabrication and operational efficiency for single-cell analysis.     

Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization

Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17–31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data.