Structural differences between the putative carbohydrate-recognition domains of human IL-1 alpha, IL-1 beta and IL-1 receptor antagonist obtained by in silico modeling

Unexpectedly High and Difficult-to-Explain Regenerative Capacity in an 82-Year-Old Patient with Insulin-Requiring Type 2 Diabetes and End-Stage Renal Disease

Background/Objectives: The case we present is part of a large study that we conducted on hemodialysis patients with type 2 diabetes mellitus (T2DM) and which set the following objectives: studying changes in the intestinal microbiota, innate and acquired immune response capacity, and tissue regeneration. Methods: (1) For the genetic study of the gut microbiota, special techniques that are not based on cultivation were used since most of the species in the intestinal flora are not cultivable. (2) The immunological study had two targets: innate immunity (inflammation) and adaptive immunity (we chose to address the cellular immune response because, unlike the humoral one, it is insufficiently studied in this category of associated pathologies). As markers for innate immunity (inflammation), the following were determined: IL-6, sIL-6R, IL-1β, TNFα, IL-10, and NGAL. TNFβ/LTα was determined as a marker for adaptive immunity (the cellular immune response). (3) The study of tissue regeneration capacity was performed using NT-3 (this is the first study to do so) and VEGFβ (another marker that is scarce in this category of patients) as markers. All the aforementioned compounds were determined from serum samples, utilizing Merck Millipore ELISA kits for IL-6, IL-1β, IL-10, NT-3, and VEGF β, and Elabscience ELISA kits for IL-6R, TNFα, TNFβ, and NGAL. Results: We were very surprised to find unexpected immunological changes and tissue regenerative capacity in one of the patients studied, an 82-year-old female patient diagnosed with insulin-dependent T2DM with multiple complications, including end-stage renal disease (ESRD). The patient showed a huge capacity for tissue regeneration, combined with amplification of immunological capacity, in comparison to patients in the same group (T2DM and ESRD) and to those in the control group (ESRD). Thus, extremely elevated serum concentrations of IL-1β, IL-6, IL-10, and TNF-β, as well as the tissue regeneration indicators NT-3 and VEGFβ, were obtained in comparison to all other members of the patient group. At the same time, serum levels of the soluble IL-6 receptor (sIL6-R) and TNFα were greatly reduced compared to the test group's mean. Conclusions: All the data obtained during our research were corroborated with those from the specialized literature and entitle us to support the hypothesis that the cause of these unexpected behaviors is the genetically conditioned overproduction (possibly acquired post-infection) of IL-6, along with its predominant anti-inflammatory and pro-regenerative signaling through the membrane-bound receptor IL-6R.

What Is IL-1 for? The Functions of Interleukin-1 Across Evolution

Interleukin-1 is a cytokine with potent inflammatory and immune-amplifying effects, mainly produced by macrophages during defensive reactions. In mammals, IL-1 is a superfamily of eleven structurally similar proteins, all involved in inflammation or its control, which mainly act through binding to specific receptors on the plasma membrane of target cells. IL-1 receptors are also a family of ten structurally similar transmembrane proteins that assemble in heterocomplexes. In addition to their innate immune/inflammatory effects, the physiological role of IL-1 family cytokines seems to be linked to the development of adaptive immunity in vertebrates. We will discuss why IL-1 developed in vertebrates and what is its physiological role, as a basis for understanding when and how it can be involved in the initiation and establishment of pathologies.

IL-1β promotes IL-9-producing Th cell differentiation in IL-2-limiting conditions through the inhibition of BCL6

IL-9-producing CD4⁺ T helper cells, termed Th9 cells, differentiate from naïve precursor cells in response to a combination of cytokine and cell surface receptor signals that are elevated in inflamed tissues. After differentiation, Th9 cells accumulate in these tissues where they exacerbate allergic and intestinal disease or enhance anti-parasite and anti-tumor immunity. Previous work indicates that the differentiation of Th9 cells requires the inflammatory cytokines IL-4 and TGF-β and is also dependent of the T cell growth factor IL-2. While the roles of IL-4 and TGF-β-mediated signaling are relatively well understood, how IL-2 signaling contributes to Th9 cell differentiation outside of directly inducing the Il9 locus remains less clear. We show here that murine Th9 cells that differentiate in IL-2-limiting conditions exhibit reduced IL-9 production, diminished NF-kB activation and a reduced NF-kB-associated transcriptional signature, suggesting that IL-2 signaling is required for optimal NF-kB activation in Th9 cells. Interestingly, both IL-9 production and the NF-kB transcriptional signature could be rescued by addition of the NF-kB-activating cytokine IL-1β to IL-2-limiting cultures. IL-1β was unique among NF-kB-activating factors in its ability to rescue Th9 differentiation as IL-2 deprived Th9 cells selectively induced IL-1R expression and IL-1β/IL-1R1 signaling enhanced the sensitivity of Th9 cells to limiting amounts of IL-2 by suppressing expression of the Th9 inhibitory factor BCL6. These data shed new light on the intertwined nature of IL-2 and NF-kB signaling pathways in differentiating Th cells and elucidate the potential mechanisms that promote Th9 inflammatory function in IL-2-limiting conditions.

The family of the interleukin-1 receptors

The extracellular forms of the IL-1 cytokines are active through binding to specific receptors on the surface of target cells. IL-1 ligands bind to the extracellular portion of their ligand-binding receptor chain. For signaling to take place, a non-binding accessory chain is recruited into a heterotrimeric complex. The intracellular approximation of the Toll-IL-1-receptor (TIR) domains of the 2 receptor chains is the event that initiates signaling. The family of IL-1 receptors (IL-1R) includes 10 structurally related members, and the distantly related soluble protein IL-18BP that acts as inhibitor of the cytokine IL-18. Over the years the receptors of the IL-1 family have been known with many different names, with significant confusion. Thus, we will use here a recently proposed unifying nomenclature. The family includes several ligand-binding chains (IL-1R1, IL-1R2, IL-1R4, IL-1R5, and IL-1R6), 2 types of accessory chains (IL-1R3, IL-1R7), molecules that act as inhibitors of signaling (IL-1R2, IL-1R8, IL-18BP), and 2 orphan receptors (IL-1R9, IL-1R10). In this review, we will examine how the receptors of the IL-1 family regulate the inflammatory and anti-inflammatory functions of the IL-1 cytokines and are, more at large, involved in modulating defensive and pathological innate immunity and inflammation. Regulation of the IL-1/IL-1R system in the brain will be also described, as an example of the peculiarities of organ-specific modulation of inflammation.

Environmental stimuli shape biofilm formation and the virulence of periodontal pathogens

Periodontitis is a common inflammatory disease affecting the tooth-supporting structures. It is initiated by bacteria growing as a biofilm at the gingival margin, and communication of the biofilms differs in health and disease. The bacterial composition of periodontitis-associated biofilms has been well documented and is under continual investigation. However, the roles of several host response and inflammation driven environmental stimuli on biofilm formation is not well understood. This review article addresses the effects of environmental factors such as pH, temperature, cytokines, hormones, and oxidative stress on periodontal biofilm formation and bacterial virulence.

Prediction of carbohydrate-binding proteins from sequences using support vector machines

Carbohydrate-binding proteins are proteins that can interact with sugar chains but do not modify them. They are involved in many physiological functions, and we have developed a method for predicting them from their amino acid sequences. Our method is based on support vector machines (SVMs). We first clarified the definition of carbohydrate-binding proteins and then constructed positive and negative datasets with which the SVMs were trained. By applying the leave-one-out test to these datasets, our method delivered 0.92 of the area under the receiver operating characteristic (ROC) curve. We also examined two amino acid grouping methods that enable effective learning of sequence patterns and evaluated the performance of these methods. When we applied our method in combination with the homology-based prediction method to the annotated human genome database, H-invDB, we found that the true positive rate of prediction was improved.