The Trace Element Selenium Is Important for Redox Signaling in Phorbol Ester-Differentiated THP-1 Macrophages

Physiological selenium (Se) levels counteract excessive inflammation, with selenoproteins shaping the immunoregulatory cytokine and lipid mediator profile. How exactly differentiation of monocytes into macrophages influences the expression of the selenoproteome in concert with the Se supply remains obscure. THP-1 monocytes were differentiated with phorbol 12-myristate 13-acetate (PMA) into macrophages and (i) the expression of selenoproteins, (ii) differentiation markers, (iii) the activity of NF-κB and NRF2, as well as (iv) lipid mediator profiles were analyzed. Se and differentiation affected the expression of selenoproteins in a heterogeneous manner. GPX4 expression was substantially decreased during differentiation, whereas GPX1 was not affected. Moreover, Se increased the expression of selenoproteins H and F, which was further enhanced by differentiation for selenoprotein F and diminished for selenoprotein H. Notably, LPS-induced expression of NF-κB target genes was facilitated by Se, as was the release of COX- and LOX-derived lipid mediators and substrates required for lipid mediator biosynthesis. This included TXB2, TXB3, 15-HETE, and 12-HEPE, as well as arachidonic acid (AA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). Our results indicate that Se enables macrophages to accurately adjust redox-dependent signaling and thereby modulate downstream lipid mediator profiles.

IL13Pred: A method for predicting immunoregulatory cytokine IL-13 inducing peptides for managing COVID-19 severity

Interleukin 13 (IL-13) is an immunoregulatory cytokine that is primarily released by activated T-helper 2 cells. It induces the pathogenesis of many allergic diseases, such as airway hyperresponsiveness, glycoprotein hypersecretion and goblet cell hyperplasia. IL-13 also inhibits tumor immunosurveillance, which leads to carcinogenesis. In recent studies, elevated IL-13 serum levels have been shown in severe COVID-19 patients. Thus it is important to predict IL-13 inducing peptides or regions in a protein for designing safe protein therapeutics particularly immunotherapeutic. This paper describes a method developed for predicting, designing and scanning IL-13 inducing peptides. The dataset used in this study contain experimentally validated 313 IL-13 inducing peptides and 2908 non-inducing homo-sapiens peptides extracted from the immune epitope database (IEDB). We have extracted 95 key features using SVC-L1 technique from the originally generated 9165 features using Pfeature. Further, these key features were ranked based on their prediction ability, and top 10 features were used for building machine learning prediction models. In this study, we have deployed various machine learning techniques to develop models for predicting IL-13 inducing peptides. These models were trained, test and evaluated using five-fold cross-validation techniques; best model were evaluated on independent dataset. Our best model based on XGBoost achieves a maximum AUC of 0.83 and 0.80 on the training and independent dataset, respectively. Our analysis indicate that certain SARS-COV2 variants are more prone to induce IL-13 in COVID-19 patients. A standalone package as well as a web server named ‘IL-13Pred’ has been developed for predicting IL-13 inducing peptides (https://webs.iiitd.edu.in/raghava/il13pred/).Key PointsInterleukin-13, an immunoregulatory cytokine plays an important role in increasing severity of COVID-19 and other diseases.IL-13Pred is a highly accurate in-silico method developed for predicting the IL-13 inducing peptides/ epitopes.IL-13 inducing peptides are reported in various SARS-CoV2 strains/variants proteins.This method can be used to detect IL-13 inducing peptides in vaccine candidates.User friendly web server and standalone software is freely available for IL-13PredAuthor’s BiographyShipra Jain is currently working as Ph.D. in Computational Biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Anjali Dhall is currently working as Ph.D. in Computational Biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Sumeet Patiyal is currently working as Ph.D. in Computational Biology from Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Gajendra P. S. Raghava is currently working as Professor and Head of Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.

Structure-based decoupling of the pro- and anti-inflammatory functions of interleukin-10

Interleukin-10 (IL-10) is an immunoregulatory cytokine with both anti-inflammatory and immunostimulatory properties and is frequently dysregulated in disease. We used a structure-based approach to deconvolute IL-10 pleiotropy by determining the structure of the IL-10 receptor (IL-10R) complex by cryo–electron microscopy at a resolution of 3.5 angstroms. The hexameric structure shows how IL-10 and IL-10Rα form a composite surface to engage the shared signaling receptor IL-10Rβ, enabling the design of partial agonists. IL-10 variants with a range of IL-10Rβ binding strengths uncovered substantial differences in response thresholds across immune cell populations, providing a means of manipulating IL-10 cell type selectivity. Some variants displayed myeloid-biased activity by suppressing macrophage activation without stimulating inflammatory CD8+ T cells, thereby uncoupling the major opposing functions of IL-10. These results provide a mechanistic blueprint for tuning the pleiotropic actions of IL-10.

There exists only one tumor necrosis factor

Tumor necrosis factor (TNF) is an important proinflammatory and immunoregulatory cytokine with several unique protective and homeostatic functions. Since TNF is a mediator of several pathologies and is a part of “cytokine storm”, its significance for clinical immunology is due to the fact that this cytokine is a target of commonly used anti-cytokine therapy in autoimmune and inflammatory diseases. In scientific literature and textbooks TNF is often goes as “TNFa”, implying the existence of at least TNFβ (indeed, such term was used for about 10 years in 80s and 90s to designate lymphotoxin). However, already 25 years ago such designation of lymphotoxin was cancelled “on scientific grounds”. Therefore, both in Russian and in English the term TNF should be used without “alpha”. Labels of the reagents related to TNFb that are offered by commercial companies are misleading.

Interleukin-19 as an Immunoregulatory Cytokine

IL-19 is a type of anti-inflammatory cytokine. Since the receptor for IL-19 is common to IL-20 and IL-24, it is important to clarify the role of each of the three cytokines. If three different cytokines bind to the same receptor, these three may have been produced to complement the other two. However, perhaps it is unlikely. Recently, the existence of a novel receptor for IL-19 was suggested. The distinction between the roles of the three cytokines still makes sense. On the other hand, because T cells do not produce IL-19, their role in acquired immunity is limited or indirect. It has been reported that IL-19 causes inflammation in some diseases but does not have an anti-inflammatory effect. In this review, we introduce the current role of IL-19 in each disease. In addition, we will describe the molecular mechanism of IL-19 and its development for the prevention of diseases. IL-19 was previously considered an anti-inflammatory cytokine, but we would like to propose it as an immunoregulatory cytokine.