A MATLAB-based program for three-dimensional quantitative analysis of micronuclei reveals that neuroinflammation induces micronuclei formation in the brain

The micronucleus is known to be a biomarker for genomic instability, which is a hallmark of tumors and aging. Normally, micronuclei are produced by segregation errors and mechanical stresses arising from dividing or migrating cells, leading to activation of the innate immune response pathway. Although micronuclei often emerge in damaged tissues, the quantitative procedure for analyzing micronuclei accurately has been problematic. Here, we introduce a novel MATLAB-based program for quantifying micronuclei (CAMDi: calculating automatic micronuclei distinction) in vitro and in vivo. CAMDi is adaptable to various experimental imaging techniques and is useful for obtaining reproducible data. CAMDi enables us to measure the accurate size of micronuclei from the three-dimensional images. Using CAMDi, we revealed a novel link between the emergence of micronuclei and neuroinflammation. We found that inflammatory stimulation does not increase the number of micronuclei in primary neurons. On the other hand, the administration of lipopolysaccharide into mice slightly increases micronuclei formation in neurons of the hippocampus region. These findings demonstrate that neuronal micronuclei formations are induced by an inflammatory response in a non-cell-autonomous manner. We provide a novel tool, CAMDi, to quantify micronuclei and demonstrate that neuronal micronuclei are produced not only by the cell-autonomous process but also by the intercellular communication associated with neuroinflammation in vivo.

Recent Progress on Immunotherapy for Breast Cancer: Tumor Microenvironment, Nanotechnology and More

Immunotherapy is a major emerging treatment for breast cancer (BC). However, not all breast cancer patients derive benefit from immunotherapy. Predictive biomarkers of immunotherapy, such as tumor mutation burden and tumor-infiltrating lymphocytes, are promising to stratify the patients with BC and optimize the therapeutic effect. Various targets of the immune response pathway have also been explored to expand the modalities of immunotherapy. The use of nanotechnology for the imaging of predictive biomarkers and the combination with other therapeutic modalities presents a number of advantages for the immunotherapy of BC. In this review, we summary the emerging therapeutic modalities of immunotherapy, present prominent examples of immunotherapy in BC, and discuss the future opportunity of nanotechnology in the immunotherapy of BC.

Bacterial Lipopolysaccharide Induced Alterations of Genome-Wide DNA Methylation and Promoter Methylation of Lactation-Related Genes in Bovine Mammary Epithelial Cells

Bacterial lipopolysaccharide (LPS) could result in poor lactation performance in dairy cows. High methylation of DNA is associated with gene repression. However, it is unclear whether LPS could suppress the expression of lactation-related genes by inducing DNA methylation. Therefore, the objective of this study was to investigate the impact of LPS on genome-wide DNA methylation, using methylated DNA immunoprecipitation with high-throughput sequencing (MeDIP-seq) and on the promoter methylation of lactation-related genes using MassArray analysis in bovine mammary epithelial cells. The bovine mammary epithelial cell line MAC-T cells were treated for 48 h with LPS at different doses of 0, 1, 10, 100, and 1000 endotoxin units (EU)/mL (1 EU = 0.1 ng). The results showed that the genomic methylation levels and the number of methylated genes in the genome as well as the promoter methylation levels of milk genes increased when the LPS dose was raised from 0 to 10 EU/mL, but decreased after further increasing the LPS dose. The milk gene mRNA expression levels of the 10 EU/mL LPS treatment were significantly lower than these of untreated cells. The results also showed that the number of hypermethylated genes was greater than that of hypomethylated genes in lipid and amino acid metabolic pathways following 1 and 10 EU/mL LPS treatments as compared with control. By contrast, in the immune response pathway the number of hypomethylated genes increased with increasing LPS doses. The results indicate LPS at lower doses induced hypermethylation of the genome and promoters of lactation-related genes, affecting milk gene mRNA expression. However, LPS at higher doses induced hypomethylation of genes involved in the immune response pathway probably in favor of immune responses.

Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition

Accurate predictions of T-cell epitopes would be useful for designing vaccines, immunotherapies for cancer and autoimmune diseases, and improved protein therapies. The humoral immune response involves uptake of antigens by antigen presenting cells (APCs), APC processing and presentation of peptides on MHC class II (pMHCII), and T-cell receptor (TCR) recognition of pMHCII complexes. Most in silico methods predict only peptide-MHCII binding, resulting in significant over-prediction of CD4 T-cell epitopes. We present a method, ITCell, for prediction of T-cell epitopes within an input protein antigen sequence for given MHCII and TCR sequences. The method integrates information about three stages of the immune response pathway: antigen cleavage, MHCII presentation, and TCR recognition. First, antigen cleavage sites are predicted based on the cleavage profiles of cathepsins S, B, and H. Second, for each 12-mer peptide in the antigen sequence we predict whether it will bind to a given MHCII, based on the scores of modeled peptide-MHCII complexes. Third, we predict whether or not any of the top scoring peptide-MHCII complexes can bind to a given TCR, based on the scores of modeled ternary peptide-MHCII-TCR complexes and the distribution of predicted cleavage sites. Our benchmarks consist of epitope predictions generated by this algorithm, checked against 20 peptide-MHCII-TCR crystal structures, as well as epitope predictions for four peptide-MHCII-TCR complexes with known epitopes and TCR sequences but without crystal structures. ITCell successfully identified the correct epitopes as one of the 20 top scoring peptides for 22 of 24 benchmark cases. To validate the method using a clinically relevant application, we utilized five factor VIII-specific TCR sequences from hemophilia A subjects who developed an immune response to factor VIII replacement therapy. The known HLA-DR1-restricted factor VIII epitope was among the six top-scoring factor VIII peptides predicted by ITCall to bind HLA-DR1 and all five TCRs. Our integrative approach is more accurate than current single-stage epitope prediction algorithms applied to the same benchmarks. It is freely available as a web server (http://salilab.org/itcell).Author summaryKnowledge of T-cell epitopes is useful for designing vaccines, improving cancer immunotherapy, studying autoimmune diseases, and engineering protein replacement therapies. Unfortunately, experimental methods for identification of T-cell epitopes are slow, expensive, and not always applicable. Thus, a more accurate computational method for prediction of T-cell epitopes needs to be developed. While the T-cell response to extracellular antigens proceeds through multiple stages, current computational methods rely only on the prediction of peptide binding affinity to an MHCII receptor on antigen presenting cells, resulting in a relatively high number of false-positive predictions of T-cell epitopes within protein antigens. We developed an integrative approach to predict T-cell epitopes that computationally combines information from three stages of the humoral immune response pathway: antigen cleavage, MHCII presentation, and TCR recognition, resulting in an increased accuracy of epitope predictions. This method was applied to predict epitopes within blood coagulation factor VIII (FVIII) that were recognized by TCRs from hemophilia A subjects who developed an anti-FVIII antibody response. The correct epitope was predicted after modeling all possible 12-mer FVIII peptides bound in ternary complexes with the relevant MHCII (HLA-DR1) and each of five experimentally determined FVIII-specific TCR sequences.

Ablation of toll-like receptor 4 mitigates cardiac mitochondrial dysfunction in hyperhomocysteinemia

Hyperhomocysteinemia (HHcy) is a risk factor for adverse cardiovascular events; however, the mechanism for development of this disease is still unknown. Toll-like receptor 4 (TRL4) is a molecule involved in the immune response pathway and is quickly becoming a receptor of interest in the field of hypertension. In this study, we hypothesized that ablation of TLR4 mitigates cardiac mitochondrial dysfunction in a model of HHcy. Five strains of mice (C57BL/6J, CBS+/−, C3H, CBS+/−/C3H, and C3H/HeOuJ) 10–12 weeks old were utilized. We found that HHcy causes heart hypertrophy and promotes oxidative stress while mice with HHcy and inactivated TLR4 showed significant improvement in examined parameters. A dominance of endothelial cell mitochondrial fission over mitochondrial fusion in HHcy and oxidative stress was observed, which may explain the endothelial cell loss and dysfunction that contributes to inward cardiac remodeling.

The trained immunity phenomenon and mechanisms of action of non-specific immunomodifiers

The discovery of the trained immunity phenomenon, which explains adaptive characteristics of the components of the innate immunity, not only to modernizes our understanding of the fundamentals of anti-infectious defense, but also contributes to further progress in the development and more rational selection and use of immunomodulatory agents. Induction of memory within the innate immune response is the basis of long-lasting immunomodulating effects of some non-specific immunomodifiers, which either contain ligands for innate immunity receptors or modulate the immune response pathway mediated by these receptors. For the first time, the mechanisms of action of pidotimod (a synthetic dipeptide with immunomodulatory properties) have been re-examined in the light of the trained immunity phenomenon.