Asma Ahmed

Immunotherapeutic efficacy of Mycobacterium indicus pranii in eliciting anti-tumor T cell responses: Critical roles of IFNγ

Mycobacterium indicus pranii (MIP) is approved for use as an adjuvant (Immuvac/Cadi‐05) in the treatment of leprosy. In addition, its efficacy is being investigated in clinical trials on patients with tuberculosis and different tumors. To evaluate and delineate the mechanisms by which autoclaved MIP enhances anti‐tumor responses, the growth of solid tumors consisting of Sp2/0 (myeloma) and EL4 (thymoma) cells was studied in BALB/c and C57BL/6 mice, respectively. Treatment of mice with a single intra‐dermal (i.d.) injection of MIP 3 days after Sp2/0 implantation greatly suppresses tumor growth. MIP treatment of tumor bearing mice lowers Interleukin (IL)6 but increases IL12p70 and IFNγ amounts in sera. Also, increase in CD8+ T cell mediated lysis of specific tumor targets and production of high amounts of IL2 and IFNγ by CD4+ T cells upon stimulation with specific tumor antigens in MIP treated mice is observed. Furthermore, MIP is also effective in reducing the growth of EL4 tumors; however, this efficacy is reduced in Ifnγ−/− mice. In fact, several MIP mediated anti‐tumor responses are greatly abrogated in Ifnγ−/− mice: increase in serum Interleukin (IL)12p70 amounts, induction of IL2 and lysis of EL4 targets by splenocytes upon stimulation with specific tumor antigens. Interestingly, tumor‐induced increase in serum IL12p70 and IFNγ and reduction in growth of Sp2/0 and EL4 tumors by MIP are not observed in nonobese diabetic severe combined immunodeficiency mice. Overall, our study clearly demonstrates the importance of a functional immune network, in particular endogenous CD4+ and CD8+ T cells and IFNγ, in mediating the anti‐tumor responses by MIP.

CTLA4-CD80/CD86 interactions on primary mouse CD4+ T cells integrate signal-strength information to modulate activation with Concanavalin A

The mechanisms by which concanavalin A (Con A), a lectin, activates T cells are poorly studied. A low dose of Con A is stimulatory for T cells, whereas a high dose of Con A results in suppression of proliferation and enhanced T cell death. The expression and functional roles of costimulatory receptors, CD28 and cytotoxic T‐lymphocyte antigen 4 (CTLA4), and their ligands, CD80 and CD86, on primary mouse CD4+ T cells after activation with different doses of Con A were studied. CTLA4‐CD80/CD86 interactions in this T:T cell activation model demonstrate distinct outcomes depending on the dose of Con A. CTLA4‐CD80/CD86 interactions inhibit CD4+ T cell cycling and survival after activation with a suppressive dose of Con A by increasing oxidative stress and decreasing levels of BclXL. The enhanced CD4+ T cell death with a suppressive dose of Con A is dependent on excess H2O2 and nitric oxide but is independent of Fas and caspase activity. It is surprising that the increased proliferation of CD4+ T cells with a suppressive dose of Con A on blocking CTLA4‐CD80/CD86 interactions is largely interleukin (IL)‐2‐independent but is cyclosporine A‐sensitive. On activation with a stimulatory dose of Con A, CTLA4‐CD80/CD86 interactions enhance T cell activation and survival by reducing the production of reactive oxygen species, increasing IL‐2 and BclXL levels. Here IL‐10 but not transforming growth factor‐β plays a functional role. In summary, CTLA4‐CD80/CD86 interactions on T cells integrate signal strength, based on the dose of Con A, to enhance or inhibit primary mouse CD4+ T cell cycling and survival.

Intracellular concentrations of Ca2+ modulate the strength of signal and alter the outcomes of cytotoxic T-lymphocyte antigen-4 (CD152)–CD80/CD86 interactions in CD4+ T lymphocytes

The costimulatory receptors CD28 and cytotoxic T‐lymphocyte antigen (CTLA)‐4 and their ligands, CD80 and CD86, are expressed on T lymphocytes; however, their functional roles during T cell–T cell interactions are not well known. The consequences of blocking CTLA‐4–CD80/CD86 interactions on purified mouse CD4+ T cells were studied in the context of the strength of signal (SOS). CD4+ T cells were activated with phorbol 12‐myristate 13‐acetate (PMA) and different concentrations of a Ca2+ ionophore, Ionomycin (I), or a sarcoplasmic Ca2+ ATPase inhibitor, Thapsigargin (TG). Increasing concentrations of I or TG increased the amount of interleukin (IL)‐2, reflecting the conversion of a low to a high SOS. During activation with PMA and low amounts of I, intracellular concentrations of calcium ([Ca2+]i) were greatly reduced upon CTLA‐4–CD80/CD86 blockade. Further experiments demonstrated that CTLA‐4–CD80/CD86 interactions reduced cell cycling upon activation with PMA and high amounts of I or TG (high SOS) but the opposite occurred with PMA and low amounts of I or TG (low SOS). These results were confirmed by surface T‐cell receptor (TCR)–CD3 signalling using a low SOS, for example soluble anti‐CD3, or a high SOS, for example plate‐bound anti‐CD3. Also, CTLA‐4–CD80/CD86 interactions enhanced the generation of reactive oxygen species (ROS). Studies with catalase revealed that H2O2 was required for IL‐2 production and cell cycle progression during activation with a low SOS. However, the high amounts of ROS produced during activation with a high SOS reduced cell cycle progression. Taken together, these results indicate that [Ca2+]i and ROS play important roles in the modulation of T‐cell responses by CTLA‐4–CD80/CD86 interactions.

Modulation of cell cycle progression by CTLA4-CD80/CD86 interactions on CD4+ T cells depends on strength of the CD3 signal : critical role for IL-2

Cytotoxic T‐lymphocyte antigen 4 (CTLA4) is a well‐studied T cell costimulatory receptor that is known to inhibit T cell activation. In this study, the relationship between strength of the first signal and costimulatory interactions on primary mouse CD4+ T cells was investigated. CTLA4‐CD80/CD86 interactions differentially modulate T cell cycling based on the mode of CD3 signal: Activation with plate‐bound (pb) anti‐CD3 generates a strong signal compared with a weak signal with soluble (sol) anti‐CD3, resulting in approximately sevenfold higher amounts of interleukin (IL)‐2 and an increase in cell cycling. Activation of T cells with sol anti‐CD3 (weak signal) together with CTLA4‐CD80/CD86 blockade lowers IL‐2 production and cell cycling, demonstrating an enhancing role for these interactions. Conversely, blockade of CTLA4‐CD80/CD86 interactions on T cells activated with pb anti‐CD3 (strong signal) increases proliferation, which is consistent with CTLA4 as a negative regulator. Also, coculture of T cells with Chinese hamster ovary cells expressing CD80 or CD86 demonstrates that the strength of the primary signal plays an important role. It is important that modulation of IL‐2 amounts leads to distinct alterations in the functional effects of CTLA4‐CD80/CD86 interactions. On increasing IL‐2 amounts, activation of T cells stimulated with sol anti‐CD3 (weak signal) and CTLA4‐CD80/CD86 blockade is greater compared with control. Concurrently, neutralization of IL‐2 greatly reduces activation of T cells stimulated with pb anti‐CD3 (strong signal) and CTLA4‐CD80/CD86 blockade compared with control. These results underscore the importance of strength of first signal, CTLA4‐CD80/CD86 interactions, and IL‐2 amounts in modulating primary CD4+ T cell responses.

Unbiased Identification of Blood-based Biomarkers for Pulmonary Tuberculosis by Modeling and Mining Molecular Interaction Networks

Efficient diagnosis of tuberculosis (TB) is met with multiple challenges, calling for a shift of focus from pathogen-centric diagnostics towards identification of host-based multi-marker signatures. Transcriptomics offer a list of differentially expressed genes, but cannot by itself identify the most influential contributors to the disease phenotype. Here, we describe a computational pipeline that adopts an unbiased approach to identify a biomarker signature. Data from RNA sequencing from whole blood samples of TB patients were integrated with a curated genome-wide molecular interaction network, from which we obtain a comprehensive perspective of variations that occur in the host due to TB. We then implement a sensitive network mining method to shortlist gene candidates that are most central to the disease alterations. We then apply a series of filters that include applicability to multiple publicly available datasets as well as additional validation on independent patient samples, and identify a signature comprising 10 genes — FCGR1A, HK3, RAB13, RBBP8, IFI44L, TIMM10, BCL6, SMARCD3, CYP4F3 and SLPI, that can discriminate between TB and healthy controls as well as distinguish TB from latent tuberculosis and HIV in most cases. The signature has the potential to serve as a diagnostic marker of TB.

The Major Players in Adaptive Immunity 1. Humoral Immunity

How do we remain healthy, for the most parts, in the midst of an environment teeming with opportunistic and infectious microbes, potential carcinogens and allergens? The fact is that our immune system, by and large, does a fine job in protecting us. It is therefore important to understand the organization of the immune network, which is broadly categorized into two groups: innate and adaptive. Cells involved in innate immunity are the first to come into contact with invading microbes, similar to the border security force, and respond rapidly but in a non-specific manner. On the other hand, the cells involved in adaptive immunity are slower to respond but act in a very specific manner. Though the primary response is slow, the secondary response is much faster and demonstrates memory. This article will focus on some important features and key players involved in the adaptive immune response. The first part deals with the humoral immune response mediated mainly by immunoglobulins produced by the B cells. The second part deals with T cells, the Major Histocompatibility Complex (MHC)-encoded molecules, and Recombination Activating Genes (RAG) responsible for generating diverse B-cell receptors (BCR) and T-cell receptors (TCR). With the advent of newer and smarter infectious agents, it is important to understand the working of the immune network as more research in this area may facilitate the development of better protective strategies.

T Cell Activation and Function: Role of Signal Strength

Optimal T cell function lies at the heart of an efficient adaptive response. T cell activation is a highly regulated process and it is important to ensure that activation occurs in the proper context to prevent the development of harmful conditions such as autoimmunity and excessive inflammatory responses. One of the important factors in this process is the strength of the primary activating signal which is delivered upon ligation of the T cell receptor (TCR) with the major histocompatibility complex (MHC) encoded class I or class II molecules bearing the antigenic peptide. The strength of signal (SOS), in turn, depends on several factors: the affinity/avidity of the TCR for the MHC–peptide complex, the time of engagement, antigen concentrations, costimulatory interactions, etc. This chapter reviews the effects of SOS on thymocyte selection and education, T cell costimulation, proliferation, survival, formation of T helper T H 1 and T H 2 subsets, responses to infectious agents etc. The role of the SOS in modulating diverse T cell responses is well appreciated. However, further studies are required to understand the mechanisms by which SOS signals are relayed from the TCR to downstream effectors to modulate T cell activation and responses.

Rapid burst of H2O2 by plant growth regulators increases intracellular Ca2+ amounts and modulates CD4+ T cell activation.

The identification of small molecules that affect T cell activation is an important area of research. Three molecules that regulate plant growth and differentiation, but not their structurally similar analogs, were identified to enhance primary mouse CD4(+) T cell activation in conjunction with soluble anti-CD3 stimulation: Indoleacetic acid (natural plant auxin), 1-Napthaleneacetic acid (synthetic plant auxin) and 2,4-Dichlorophenoxyacetic acid (synthetic plant auxin and herbicide). These effects are distinct in comparison to Curcumin, the well known phenolic immunomodulator, which lowers T cell activation. An investigation into the mechanisms of action of the three plant growth regulators revealed a rapid induction of reactive oxygen species (ROS), mainly comprising H(2)O(2). In addition, these three molecules synergize with soluble anti-CD3 signaling to enhance intracellular Ca(2+) concentrations [Ca(2+)](i), leading to greater T cell activation, e.g. induction of CD25 and IL-2. Enhanced production of TNFα and IFNγ by CD4(+) T cells is also observed upon plant growth regulator treatment with soluble anti-CD3. Interestingly, maximal IL-2 production and CD4(+) T cell cycle progression are observed upon activation with soluble anti-CD3 and phorbol 12-myristate 13-acetate (PMA), a phorbol ester. Additionally, stimulation with PMA and Ionomcyin (a Ca(2+) ionophore), which activates T cells by circumventing the TCR, and plant growth regulators also demonstrated the role of the strength of signal (SOS): T cell cycle progression is enhanced with gentle activation conditions but decreased with strong activation conditions. This study demonstrates the direct effects of three plant growth regulators on CD4(+) T cell activation and cycling.

Circulating HLA-DR+CD4+ effector memory T cells resistant to CCR5 and PD-L1 mediated suppression compromise regulatory T cell function in tuberculosis

Chronic T cell activation is a hallmark of pulmonary tuberculosis (PTB). The mechanisms underpinning this important phenomenon are however, poorly elucidated, though known to rely on control of T effector cells (Teff) by regulatory T cells (Treg). Our studies show that circulating natural Treg cells in adults with PTB preserve their suppressive potential but Teff cells from such subjects are resistant to Treg-mediated suppression. We found this to be due to expansion of an activated Teff subset identified by Human Leukocyte Antigen (HLA)-DR expression. Sensitivity to suppression was restored to control levels by depletion of this subset. Comparative transcriptome analysis of Teff cells that contain HLA-DR+ cells versus the fraction depleted of this population identified putative resistance mechanisms linked to IFNG, IL17A, IL22, PD-L1 and β-chemokines CCL3L3, CCL4 expression. Antibody blocking experiments confirmed HLA-DR+ Teff cells, but not the fraction depleted of HLA-DR+ effectors, to be resistant to Treg suppression mediated via CCR5 and PD-L1 associated pathways. In the presence of HLA-DR+ Teff cells, activation of NFκB downstream of CCR5 and PD-L1 was perturbed. In addition, HLA-DR+ Teff cells expressed significantly higher levels of Th1/Th17 cytokines that may regulate Treg function through a reciprocal counter-balancing relationship. Taken together, our study provides novel insight on how activated HLA-DR+CD4+ T cells may contribute to disease associated inflammation by compromising Treg-mediated suppression in PTB.