scholarly journals Towards the structure of the TIR-domain signalosome

2017 ◽  
Vol 43 ◽  
pp. 122-130 ◽  
Author(s):  
Surekha Nimma ◽  
Thomas Ve ◽  
Simon J. Williams ◽  
Bostjan Kobe
Keyword(s):  
2011 ◽  
Vol 48 (15-16) ◽  
pp. 2144-2150 ◽  
Author(s):  
Shun-ichiro Oda ◽  
Edward Franklin ◽  
Amir R. Khan
Keyword(s):  

2012 ◽  
Vol 33 (5) ◽  
pp. 341-346 ◽  
Author(s):  
V R Karody ◽  
M Le ◽  
S Nelson ◽  
K Meskin ◽  
S Klemm ◽  
...  

2011 ◽  
Vol 439 (1) ◽  
pp. 79-83 ◽  
Author(s):  
Girish K. Radhakrishnan ◽  
Jerome S. Harms ◽  
Gary A. Splitter

TIR (Toll/interleukin-1 receptor) domain-containing proteins play a crucial role in innate immunity in eukaryotes. Brucella is a highly infectious intracellular bacterium that encodes a TIR domain protein (TcpB) to subvert host innate immune responses to establish a beneficial niche for pathogenesis. TcpB inhibits NF-κB (nuclear factor κB) activation and pro-inflammatory cytokine secretions mediated by TLR (Toll-like receptor) 2 and TLR4. In the present study, we have demonstrated that TcpB modulates microtubule dynamics by acting as a stabilization factor. TcpB increased the rate of nucleation as well as the polymerization phases of microtubule formation in a similar manner to paclitaxel. TcpB could efficiently inhibit nocodazole- or cold-induced microtubule disassembly. Microtubule stabilization by TcpB is attributed to the BB-loop region of the TIR domain, and a point mutation affected the microtubule stabilization as well as the TLR-suppression properties of TcpB.


2012 ◽  
Vol 13 (8) ◽  
pp. 776-788 ◽  
Author(s):  
Ota Fekonja ◽  
Monika Avbelj ◽  
Roman Jerala
Keyword(s):  

Author(s):  
João Gonçalves ◽  
Helena Soares ◽  
Norman L. Eberhardt ◽  
Sarah C. R. Lummis ◽  
David R. Soto-Pantoja ◽  
...  

Author(s):  
João Gonçalves ◽  
Helena Soares ◽  
Norman L. Eberhardt ◽  
Sarah C. R. Lummis ◽  
David R. Soto-Pantoja ◽  
...  
Keyword(s):  

2018 ◽  
Author(s):  
Ailís O’Carroll ◽  
Brieuc Chauvin ◽  
James Brown ◽  
Ava Meagher ◽  
Joanne Coyle ◽  
...  

AbstractA novel concept has emerged whereby the higher-order self-assembly of proteins provides a simple and robust mechanism for signal amplification. This appears to be a universal signalling mechanism within the innate immune system, where the recognition of pathogens or danger-associated molecular patterns need to trigger a strong, binary response within cells. Previously, multiple structural studies have been limited to single domains, expressed and assembled at high protein concentrations. We therefore set out to develop new in vitro strategies to characterise the behaviour of full-length proteins at physiological levels. In this study we focus on the adaptor protein MyD88, which contains two domains with different self-assembly properties: a TIR domain that can polymerise similarly to the TIR domain of Mal, and a Death Domain that has been shown to oligomerise with helical symmetry in the Myddosome complex. To visualize the behaviour of full-length MyD88 without purification steps, we use single-molecule fluorescence coupled to eukaryotic cell-free protein expression. These experiments demonstrate that at low protein concentration, only full-length MyD88 forms prion-like polymers. We also demonstrate that the metastability of MyD88 polymerisation creates the perfect binary response required in innate signalling: the system is silenced at normal concentrations but upstream signalling creates a “seed” that triggers polymerisation and amplification of the response. These findings pushed us to re-interpret the role of polymerisation in MyD88-related diseases and we studied the impact of disease-associated point mutations L93P, R196C and L252P/L265P at the molecular level. We discovered that all mutations completely block the ability of MyD88 to polymerise. We also confirm that L252P, a gain-of-function mutation, allows the MyD88 mutant to form extremely stable oligomers, even when expressed at low nanomolar concentrations. Thus, our results are consistent with and greatly add to the findings on the Myddosomes digital ‘all-or-none’ responses and the behaviour of the oncogenic mutation of MyD88.


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10143
Author(s):  
Mohammed Alaidarous

Several bacterial pathogens produce Toll/interleukin-1 receptor (TIR) domain-containing protein homologs that are important for subverting the Toll-like receptor (TLR) signaling cascades in hosts. Consequently, promoting the persistence and survival of the bacterial pathogens. However, the exact molecular mechanisms elucidating the functional characteristics of these bacterial proteins are not clear. Physicochemical and homology modeling characterization studies have been conducted to predict the conditions suitable for the stability and purification of these proteins and to predict their structural properties. The outcomes of these studies have provided important preliminary data for the drug discovery pipeline projects. Here, using in silico physicochemical and homology modeling tools, we have reported the primary, secondary and tertiary structural characteristics of multiple N-terminal domains of selected bacterial TIR domain-containing proteins (Tcps). The results show variations between the primary amino acid sequences, secondary structural components and three-dimensional models of the proteins, suggesting the role of different molecular mechanisms in the functioning of these proteins in subverting the host immune system. This study could form the basis of future experimental studies advancing our understanding of the molecular basis of the inhibition of the host immune response by the bacterial Tcps.


2020 ◽  
Vol 34 (07) ◽  
pp. 11604-11611 ◽  
Author(s):  
Qiao Liu ◽  
Xin Li ◽  
Zhenyu He ◽  
Nana Fan ◽  
Di Yuan ◽  
...  

Existing deep Thermal InfraRed (TIR) trackers usually use the feature models of RGB trackers for representation. However, these feature models learned on RGB images are neither effective in representing TIR objects nor taking fine-grained TIR information into consideration. To this end, we develop a multi-task framework to learn the TIR-specific discriminative features and fine-grained correlation features for TIR tracking. Specifically, we first use an auxiliary classification network to guide the generation of TIR-specific discriminative features for distinguishing the TIR objects belonging to different classes. Second, we design a fine-grained aware module to capture more subtle information for distinguishing the TIR objects belonging to the same class. These two kinds of features complement each other and recognize TIR objects in the levels of inter-class and intra-class respectively. These two feature models are learned using a multi-task matching framework and are jointly optimized on the TIR tracking task. In addition, we develop a large-scale TIR training dataset to train the network for adapting the model to the TIR domain. Extensive experimental results on three benchmarks show that the proposed algorithm achieves a relative gain of 10% over the baseline and performs favorably against the state-of-the-art methods. Codes and the proposed TIR dataset are available at https://github.com/QiaoLiuHit/MMNet.


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