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Pathogen Recognition and Innate Immunity

The discovery of Toll-like receptors (TLRs) as components that recognize conserved structures in pathogens has greatly advanced understanding of how the body senses pathogen invasion, triggers innate immune responses and primes antigen-specific adaptive immunity. Although TLRs are critical for host defense, it has become apparent that loss of negative regulation of TLR signaling, as well as recognition of self molecules by TLRs, are strongly associated with the pathogenesis of inflammatory and autoimmune diseases. Furthermore, it is now clear that the interaction between TLRs and recently identified cytosolic innate immune sensors is crucial for mounting effective immune responses. Here we describe the recent advances that have been made by research into the role of TLR biology in host defense and disease.

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The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors

Pattern Recognition Receptors and Inflammation

Type I interferons are central mediators for antiviral responses. Using high-throughput functional screening of interferon inducers, we have identified here a molecule we call interferon-beta promoter stimulator 1 (IPS-1). Overexpression of IPS-1 induced type I interferon and interferon-inducible genes through activation of IRF3, IRF7 and NF-kappaB transcription factors. TBK1 and IKKi protein kinases were required for the IPS-1-mediated interferon induction. IPS-1 contained an N-terminal CARD-like structure that mediated interaction with the CARD of RIG-I and Mda5, which are cytoplasmic RNA helicases that sense viral infection. 'Knockdown' of IPS-1 by small interfering RNA blocked interferon induction by virus infection. Thus, IPS-1 is an adaptor involved in RIG-I- and Mda5-mediated antiviral immune responses.

IPS-1, an adaptor triggering RIG-I- and Mda5-mediated type I interferon induction

Microbial infection initiates complex interactions between the pathogen and the host. Pathogens express several signature molecules, known as pathogen-associated molecular patterns (PAMPs), which are essential for survival and pathogenicity. PAMPs are sensed by evolutionarily conserved, germline-encoded host sensors known as pathogen recognition receptors (PRRs). Recognition of PAMPs by PRRs rapidly triggers an array of anti-microbial immune responses through the induction of various inflammatory cytokines, chemokines and type I interferons. These responses also initiate the development of pathogen-specific, long-lasting adaptive immunity through B and T lymphocytes. Several families of PRRs, including Toll-like receptors (TLRs), RIG-I-like receptors (RLRs), NOD-like receptors (NLRs), and DNA receptors (cytosolic sensors for DNA), are known to play a crucial role in host defense. In this review, we comprehensively review the recent progress in the field of PAMP recognition by PRRs and the signaling pathways activated by PRRs.

Pathogen Recognition by the Innate Immune System

Toll-like receptors and innate immunity

In many applications of classifier learning, training data suffers from label noise. Deep networks are learned using huge training data where the problem of noisy labels is particularly relevant. The current techniques proposed for learning deep networks under label noise focus on modifying the network architecture and on algorithms for estimating true labels from noisy labels. An alternate approach would be to look for loss functions that are inherently noise-tolerant. For binary classification there exist theoretical results on loss functions that are robust to label noise. In this paper, we provide some sufficient conditions on a loss function so that risk minimization under that loss function would be inherently tolerant to label noise for multiclass classification problems. These results generalize the existing results on noise-tolerant loss functions for binary classification. We study some of the widely used loss functions in deep networks and show that the loss function based on mean absolute value of error is inherently robust to label noise. Thus standard back propagation is enough to learn the true classifier even under label noise. Through experiments, we illustrate the robustness of risk minimization with such loss functions for learning neural networks.

Robust Loss Functions under Label Noise for Deep Neural Networks

Successful vaccines contain not only protective antigen(s) but also an adjuvant component that triggers innate immune activation and is necessary for their optimal immunogenicity. In the case of DNA vaccines, this consists of plasmid DNA; however, the adjuvant element(s) as well as its intra- and inter-cellular innate immune signalling pathway(s) leading to the encoded antigen-specific T- and B-cell responses remain unclear. Here we demonstrate in vivo that TANK-binding kinase 1 (TBK1), a non-canonical IkappaB kinase, mediates the adjuvant effect of DNA vaccines and is essential for its immunogenicity in mice. Plasmid-DNA-activated, TBK1-dependent signalling and the resultant type-I interferon receptor-mediated signalling was required for induction of antigen-specific B and T cells, which occurred even in the absence of innate immune signalling through a well known CpG DNA sensor-Toll-like receptor 9 (TLR9) or Z-DNA binding protein 1 (ZBP1, also known as DAI, which was recently reported as a potential B-form DNA sensor). Moreover, bone-marrow-transfer experiments revealed that TBK1-mediated signalling in haematopoietic cells was critical for the induction of antigen-specific B and CD4(+) T cells, whereas in non-haematopoietic cells TBK1 was required for CD8(+) T-cell induction. These data suggest that TBK1 is a key signalling molecule for DNA-vaccine-induced immunogenicity, by differentially controlling DNA-activated innate immune signalling through haematopoietic and non-haematopoietic cells.

Himanshu Kumar

Papers

IPS-1, an adaptor triggering RIG-I- and Mda5-mediated type I interferon induction

Pathogen Recognition by the Innate Immune System

Toll-like receptors and innate immunity

Robust Loss Functions under Label Noise for Deep Neural Networks

TANK-binding kinase-1 delineates innate and adaptive immune responses to DNA vaccines