Putting computational models of immunity to the test - an invited challenge to predict vaccination outcomes.

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting booster responses and generate experimental data for the explicit purpose of model evaluation.

IgG glycosylation associates with risk of progression from latent to active tuberculosis.

Objectives: Glycosylation motifs shape antibody structure, stability and antigen affinity and play an important role in antibody localization and function. Serum IgG glycosylation profiles are significantly altered in infectious diseases, including tuberculosis (TB), but have not been studied in the context of progression from latent to active TB.

Methods: We performed a longitudinal study of paired bulk IgG glycosylation and transcriptomic profiling in blood from individuals with active TB (ATB) or latent TB infection (LTBI) before and after treatment.

Antigen-specificity measurements are the key to understanding T cell responses.

Antigen-specific T cells play a central role in the adaptive immune response and come in a wide range of phenotypes. T cell receptors (TCRs) mediate the antigen-specificities found in T cells. Importantly, high-throughput TCR sequencing provides a fingerprint which allows tracking of specific T cells and their clonal expansion in response to particular antigens.

Single-cell profiling reveals distinct subsets of CD14+ monocytes drive blood immune signatures of active tuberculosis.

Introduction: Previous studies suggest that monocytes are an important contributor to tuberculosis (TB)-specific immune signatures in blood.

Methods: Here, we carried out comprehensive single-cell profiling of monocytes in paired blood samples of active TB (ATB) patients at diagnosis and mid-treatment, and healthy controls.

Results: At diagnosis, ATB patients displayed increased monocyte-to-lymphocyte ratio, increased frequency of CD14+CD16- and intermediate CD14+CD16+ monocytes, and upregulation of interferon signaling genes that significantly overlapped with previously reported blood TB signatures in both CD14+ subsets.

Distinguishing cell-cell complexes from dual lineage cells using single-cell transcriptomics is not trivial.

In their recent correspondence, Jie et al. strongly defend that the DE cell population they discovered are always dual lineage co-expressing cells and not complexes of B cells and T cells, which we have previously described as frequently present in single-cell RNA sequencing data. Here, we respond to the specific arguments made in their correspondence.

Host Immune-Metabolic Adaptations Upon Mycobacterial Infections and Associated Co-Morbidities.

Mycobacterial diseases are a major public health challenge. Their causative agents include, in order of impact, members of the complex (causing tuberculosis), (causing leprosy), and non-tuberculous mycobacterial pathogens including Macrophages are mycobacterial targets and they play an essential role in the host immune response to mycobacteria. This review aims to provide a comprehensive understanding of the immune-metabolic adaptations of the macrophage to mycobacterial infections.

Distinct blood transcriptomic signature of treatment in latent tuberculosis infected individuals at risk of developing active disease.

Although only a small fraction will ever develop the active form of tuberculosis (ATB) disease, chemoprophylaxis treatment in latent TB infected (LTBI) individuals is an effective strategy to control pathogen transmission. Characterizing immune responses in LTBI upon chemoprophylactic treatment is important to facilitate treatment monitoring, and thus improve TB control strategies. Here, we studied changes in the blood transcriptome in a cohort of 42 LTBI and 8 ATB participants who received anti-TB therapy.

HLA-DR Marks Recently Divided Antigen-Specific Effector CD4 T Cells in Active Tuberculosis Patients.

Upon Ag encounter, T cells can rapidly divide and form an effector population, which plays an important role in fighting acute infections. In humans, little is known about the molecular markers that distinguish such effector cells from other T cell populations. To address this, we investigated the molecular profile of T cells present in individuals with active tuberculosis (ATB), where we expect Ag encounter and expansion of effector cells to occur at higher frequency in contrast to -sensitized healthy IGRA individuals.

A population of CD4CD38 T cells correlates with disease severity in patients with acute malaria.

Objective: CD4 T cells are critical mediators of immunity to spp. infection, but their characteristics during malarial episodes and immunopathology in naturally infected adults are poorly defined. Flow cytometric analysis of PBMCs from patients with either or malaria revealed a pronounced population of CD4 T cells co-expressing very high levels of CD4 and CD38 we have termed CD4CD38 T cells.

Quantitative and Qualitative Perturbations of CD8 MAITs in Healthy -Infected Individuals.

CD8 T cells are considered important contributors to the immune response against , yet limited information is currently known regarding their specific immune signature and phenotype. In this study, we applied a cell population transcriptomics strategy to define immune signatures of human latent tuberculosis infection (LTBI) in memory CD8 T cells. We found a 41-gene signature that discriminates between memory CD8 T cells from healthy LTBI subjects and uninfected controls.

The Challenge of Distinguishing Cell-Cell Complexes from Singlet Cells in Non-Imaging Flow Cytometry and Single-Cell Sorting.

Our recent work has highlighted that care needs to be taken when interpreting single cell data originating from flow cytometry acquisition or cell sorting: We found that doublets of T cells bound to other immune cells are often present in the live singlet gate of human peripheral blood samples acquired by flow cytometry. This hidden "contamination" generates atypical gene signatures of mixed cell lineage in what is assumed to be single cells, which can lead to data misinterpretation, such as the description of novel immune cell types. Here, based on the example of T cell-monocyte complexes, we identify experimental and data analysis strategies to help distinguishing between singlets and cell-cell complexes in non-imaging flow cytometry and single-cell sorting.

Reporting and connecting cell type names and gating definitions through ontologies.

Background: Human immunology studies often rely on the isolation and quantification of cell populations from an input sample based on flow cytometry and related techniques. Such techniques classify cells into populations based on the detection of a pattern of markers. The description of the cell populations targeted in such experiments typically have two complementary components: the description of the cell type targeted (e.

Circulating T cell-monocyte complexes are markers of immune perturbations.

Our results highlight for the first time that a significant proportion of cell doublets in flow cytometry, previously believed to be the result of technical artifacts and thus ignored in data acquisition and analysis, are the result of biological interaction between immune cells. In particular, we show that cell:cell doublets pairing a T cell and a monocyte can be directly isolated from human blood, and high resolution microscopy shows polarized distribution of LFA1/ICAM1 in many doublets, suggesting in vivo formation. Intriguingly, T cell-monocyte complex frequency and phenotype fluctuate with the onset of immune perturbations such as infection or immunization, reflecting expected polarization of immune responses.

Host Transcriptomics as a Tool to Identify Diagnostic and Mechanistic Immune Signatures of Tuberculosis.

Tuberculosis (TB) is a major infectious disease worldwide, and is associated with several challenges for control and eradication. First, more accurate diagnostic tools that better represent the spectrum of infection states are required; in particular, identify the latent TB infected individuals with high risk of developing active TB. Second, we need to better understand, from a mechanistic point of view, why the immune system is unsuccessful in some cases for control and elimination of the pathogen.

DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data.

Computational methods for identification of cell populations from polychromatic flow cytometry data are changing the paradigm of cytometry bioinformatics. Data clustering is the most common computational approach to unsupervised identification of cell populations from multidimensional cytometry data. However, interpretation of the identified data clusters is labor-intensive.

Discovering transcriptional signatures of disease for diagnosis versus mechanism.

Transcriptional signatures of disease can be used for diagnosis or to gain insight into disease mechanisms. This Comment article discusses the different sets of criteria that should be considered for the optimal design of investigations addressing these two purposes, using examples from the study of tuberculosis.

Transcriptomic Analysis of CD4 T Cells Reveals Novel Immune Signatures of Latent Tuberculosis.

In the context of infectious diseases, cell population transcriptomics are useful to gain mechanistic insight into protective immune responses, which is not possible using traditional whole-blood approaches. In this study, we applied a cell population transcriptomics strategy to sorted memory CD4 T cells to define novel immune signatures of latent tuberculosis infection (LTBI) and gain insight into the phenotype of tuberculosis (TB)-specific CD4 T cells. We found a 74-gene signature that could discriminate between memory CD4 T cells from healthy latently -infected subjects and noninfected controls.

Dichotomous miR expression and immune responses following primary blood-stage malaria.

Clinical responses to infection or vaccination and the development of effective immunity are characterized in humans by a marked interindividual variability. To gain an insight into the factors affecting this variability, we used a controlled human infection system to study early immune events following primary infection of healthy human volunteers with blood-stage Plasmodium falciparum malaria. By day 4 of infection, a dichotomous pattern of high or low expression of a defined set of microRNAs (miRs) emerged in volunteers that correlated with variation in parasite growth rate.

Early Immune Regulatory Changes in a Primary Controlled Human Plasmodium vivax Infection: CD1c Myeloid Dendritic Cell Maturation Arrest, Induction of the Kynurenine Pathway, and Regulatory T Cell Activation.

malaria remains a major public health problem. The requirements for acquisition of protective immunity to the species are not clear. Dendritic cells (DC) are essential for immune cell priming but also perform immune regulatory functions, along with regulatory T cells (Treg).

Polyfunctional and IFN- monofunctional human CD4 T cell populations are molecularly distinct.

Pathogen-specific polyfunctional T cell responses have been associated with favorable clinical outcomes, but it is not known whether molecular differences exist between polyfunctional and monofunctional cytokine-producing T cells. Here, we report that polyfunctional CD4 T cells induced during (. ) blood-stage infection in humans have a unique transcriptomic profile compared with IFN-γ monofunctional CD4 T cells and, thus, are molecularly distinct.

An Integrated Workflow To Assess Technical and Biological Variability of Cell Population Frequencies in Human Peripheral Blood by Flow Cytometry.

In the context of large-scale human system immunology studies, controlling for technical and biological variability is crucial to ensure that experimental data support research conclusions. In this study, we report on a universal workflow to evaluate both technical and biological variation in multiparameter flow cytometry, applied to the development of a 10-color panel to identify all major cell populations and T cell subsets in cryopreserved PBMC. Replicate runs from a control donation and comparison of different gating strategies assessed the technical variability associated with each cell population and permitted the calculation of a quality control score.

Plasmodium vivax but Not Plasmodium falciparum Blood-Stage Infection in Humans Is Associated with the Expansion of a CD8+ T Cell Population with Cytotoxic Potential.

Unlabelled: P. vivax and P. falciparum parasites display different tropism for host cells and induce very different clinical symptoms and pathology, suggesting that the immune responses required for protection may differ between these two species.