Genome-wide methylation and expression analyses reveal the epigenetic landscape of immune-related diseases for tobacco smoking

Background Smoking is a major causal risk factor for lung cancer, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and is the main preventable cause of deaths in the world. The components of cigarette smoke are involved in immune and inflammatory processes, which may increase the prevalence of cigarette smoke-related diseases. However, the underlying molecular mechanisms linking smoking and diseases have not been well explored. This study was aimed to depict a global map of DNA methylation and gene expression changes induced by tobacco smoking and to explore the molecular mechanisms between smoking and human diseases through whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq). Results We performed WGBS on 72 samples (36 smokers and 36 nonsmokers) and RNA-seq on 75 samples (38 smokers and 37 nonsmokers), and cytokine immunoassay on plasma from 22 males (9 smokers and 13 nonsmokers) who were recruited from the city of Jincheng in China. By comparing the data of the two groups, we discovered a genome-wide methylation landscape of differentially methylated regions (DMRs) associated with smoking. Functional enrichment analyses revealed that both smoking-related hyper-DMR genes (DMGs) and hypo-DMGs were related to synapse-related pathways, whereas the hypo-DMGs were specifically related to cancer and addiction. The differentially expressed genes (DEGs) revealed by RNA-seq analysis were significantly enriched in the “immunosuppression” pathway. Correlation analysis of DMRs with their corresponding gene expression showed that genes affected by tobacco smoking were mostly related to immune system diseases. Finally, by comparing cytokine concentrations between smokers and nonsmokers, we found that vascular endothelial growth factor (VEGF) was significantly upregulated in smokers. Conclusions In sum, we found that smoking-induced DMRs have different distribution patterns in hypermethylated and hypomethylated areas between smokers and nonsmokers. We further identified and verified smoking-related DMGs and DEGs through multi-omics integration analysis of DNA methylome and transcriptome data. These findings provide us a comprehensive genomic map of the molecular changes induced by smoking which would enhance our understanding of the harms of smoking and its relationship with diseases.

Gender Variations in the Oral Microbiomes of Elderly Patients with Initial Periodontitis

Periodontitis is a globally prevalent disease that imposes a functional and aesthetic burden on patients. The oral microbiome influences human health. The aim of this study was at assessing gender variation in the subgingival bacterial microbiome of elderly patients with initial periodontitis and to determine the causes of this variation. Twelve males and twenty females (range 50–68 years old) with initial periodontitis provided subgingival plaque samples. 16S rRNA gene sequencing, QIIME-based data processing, and statistical analyses were carried out using several different analytical approaches to detect differences in the oral microbiome between the two groups. Males had higher Chao1 index, observed species, and phylogenetic diversity whole tree values than females. Analysis of β-diversity indicated that the samples were reasonably divided by the gender. The linear discriminant analysis effect size showed that the most representative biomarkers were the genus Haemophilus in males, whereas the dominant bacteria in females were Campylobacter. Kyoto Encyclopedia of Genes and Genomes analysis showed that predicting changes in the female oral microbiota may be related to the immune system and immune system diseases are the main factor in males. These data suggest that gender may be a differentiating factor in the microbial composition of subgingival plaques in elderly patients with initial periodontitis. These results could deepen our understanding of the role of gender in the oral microbiota present during initial periodontitis.

Microfluidics applications for high-throughput single cell sequencing

The inherent heterogeneity of individual cells in cell populations plays significant roles in disease development and progression, which is critical for disease diagnosis and treatment. Substantial evidences show that the majority of traditional gene profiling methods mask the difference of individual cells. Single cell sequencing can provide data to characterize the inherent heterogeneity of individual cells, and reveal complex and rare cell populations. Different microfluidic technologies have emerged for single cell researches and become the frontiers and hot topics over the past decade. In this review article, we introduce the processes of single cell sequencing, and review the principles of microfluidics for single cell analysis. Also, we discuss the common high-throughput single cell sequencing technologies along with their advantages and disadvantages. Lastly, microfluidics applications in single cell sequencing technology for the diagnosis of cancers and immune system diseases are briefly illustrated.

CRISPR Therapeutics: New Emerging Developments and Clinical Applications

CRISPR gene editing is a genetic engineering technique applied in clinical applications in which the genomes of living organisms may be modified. It is based on the principles of the CRISPR-Cas9 antiviral defense system. It is based on delivering the Cas9 nuclease complexed with a synthetic guide RNA into a living organism cell and that organisms’s genome can be “cut” and –“paste” at a desired location, allowing existing genes to be modified for desired outcome (i.e., CRISPR for Precision Medicine). CRISPR gene editing harnesses the natural defense mechanisms of some bacteria to cut human DNA strands. Then the DNA strand either heals itself or injects a new piece of DNA to mend the gap. Studies have been reported in Lung Cancer diagnosis and treatments. CRISPR-based engineering techniques have been developed for T Cells and Stem cells applications (i.e. Gene Corrections in Hematopoietic Stem Cells for the Treatment of Blood and Immune System Diseases). Even though earlier CRISPR methodologies were used for performing simple DNA edits, recent applications include the ability to delete genes or insert genes, and edit regulatory regions in a wide range of cell types. The role of CRISPR in human therapeutics is currently focused on utilizing CRISPR techniques to perform either in vivo editing of human cells–everything from the head, eye all the way to neurons and liver cells--or performing ex vivo therapies. The FDA’s new genomic CRISPR technology based products approval process begins with review and evaluation of preclinical studies in order to establish and characterize the proposed product’s safety profile. New genomic products must be shown to be safe and effective for the FDA approval process. The sponsor of the new genomic product must show that the product is safe and effective in human subjects.1

Clinical Trials Based on Mesenchymal Stromal Cells are Exponentially Increasing: Where are We in Recent Years?

Mesenchymal stromal cells (MSCs), present in the stromal component of several tissues, include multipotent stem cells, progenitors, and differentiated cells. MSCs have quickly attracted considerable attention in the clinical field for their regenerative properties and their ability to promote tissue homeostasis following injury. In recent years, MSCs mainly isolated from bone marrow, adipose tissue, and umbilical cord—have been utilized in hundreds of clinical trials for the treatment of various diseases. However, in addition to some successes, MSC-based therapies have experienced several failures. The number of new trials with MSCs is exponentially growing; still, complete results are only available for a limited number of trials. This dearth does not help prevent potentially inefficacious and unnecessary clinical trials. Results from unsuccessful studies may be useful in planning new therapeutic approaches to improve clinical outcomes. In order to bolster critical analysis of trial results, we reviewed the state of art of MSC clinical trials that have been published in the last six years. Most of the 416 published trials evaluated MSCs’ effectiveness in treating cardiovascular diseases, GvHD, and brain and neurological disorders, although some trials sought to treat immune system diseases and wounds and to restore tissue. We also report some unorthodox clinical trials that include unusual studies. Graphical abstract

Predicting the Specificity- Determining Positions of Receptor Tyrosine Kinase Axl

Owing to its clinical significance, modulation of functionally relevant amino acids in protein-protein complexes has attracted a great deal of attention. To this end, many approaches have been proposed to predict the partner-selecting amino acid positions in evolutionarily close complexes. These approaches can be grouped into sequence-based machine learning and structure-based energy-driven methods. In this work, we assessed these methods’ ability to map the specificity-determining positions of Axl, a receptor tyrosine kinase involved in cancer progression and immune system diseases. For sequence-based predictions, we used SDPpred, Multi-RELIEF, and Sequence Harmony. For structure-based predictions, we utilized HADDOCK refinement and molecular dynamics simulations. As a result, we observed that (i) sequence-based methods overpredict partner-selecting residues of Axl and that (ii) combining Multi-RELIEF with HADDOCK-based predictions provides the key Axl residues, covered by the extensive molecular dynamics simulations. Expanding on these results, we propose that a sequence-structure-based approach is necessary to determine specificity-determining positions of Axl, which can guide the development of therapeutic molecules to combat Axl misregulation.

Segmentation of epithelial human type 2 cell images for the indirect immune fluorescence based on modified quantum entropy

The autoimmune disorders such as rheumatoid, arthritis, and scleroderma are connective tissue diseases (CTD). Autoimmune diseases are generally diagnosed using the antinuclear antibody (ANA) blood test. This test uses indirect immune fluorescence (IIf) image analysis to detect the presence of liquid substance antibodies at intervals the blood, which is responsible for CTDs. Typically human alveolar epithelial cells type 2 (HEp2) are utilized as the substrate for the microscope slides. The various fluorescence antibody patterns on HEp-2 cells permits the differential designation-diagnosis. The segmentation of HEp-2 cells of IIf images is therefore a crucial step in the ANA test. However, not only this task is extremely challenging, but physicians also often have a considerable number of IIf images to examine.In this study, we propose a new methodology for HEp2 segmentation from IIf images by maximum modified quantum entropy. Besides, we have used a new criterion with a flexible representation of the quantum image(FRQI). The proposed methodology determines the optimum threshold based on the quantum entropy measure, by maximizing the measure of class separability for the obtained classes over all the gray levels. We tested the suggested algorithm over all images of the MIVIA HEp 2 image data set.To objectively assess the proposed methodology, segmentation accuracy (SA), Jaccard similarity (JS), the F1-measure,the Matthews correlation coefficient(MCC), and the peak signal-to-noise ratio (PSNR) were used to evaluate performance. We have compared the proposed methodology with quantum entropy, Kapur and Otsu algorithms, respectively.The results show that the proposed algorithm is better than quantum entropy and Kapur methods. In addition, it overcomes the limitations of the Otsu method concerning the images which has positive skew histogram.This study can contribute to create a computer-aided decision (CAD) framework for the diagnosis of immune system diseases

New Quinolinone O-GlcNAc Transferase Inhibitors Based on Fragment Growth

O-GlcNAcylation is an important post-translational and metabolic process in cells that must be carefully regulated. O-GlcNAc transferase (OGT) is ubiquitously present in cells and is the only enzyme that catalyzes the transfer of O-GlcNAc to proteins. OGT is a promising target in various pathologies such as cancer, immune system diseases, or nervous impairment. In our previous work we identified the 2-oxo-1,2-dihydroquinoline-4-carboxamide derivatives as promising compounds by a fragment-based drug design approach. Herein, we report the extension of this first series with several new fragments. As the most potent fragment, we identified 3b with an IC50 value of 116.0 μM. If compared with the most potent inhibitor of the first series, F20 (IC50 = 117.6 μM), we can conclude that the new fragments did not improve OGT inhibition remarkably. Therefore, F20 was used as the basis for the design of a series of compounds with the elongation toward the O-GlcNAc binding pocket as the free carboxylate allows easy conjugation. Compound 6b with an IC50 value of 144.5 μM showed the most potent OGT inhibition among the elongated compounds, but it loses inhibition potency when compared to the UDP mimetic F20. We therefore assume that the binding of the compounds in the O-GlcNAc binding pocket is likely not crucial for OGT inhibition. Furthermore, evaluation of the compounds with two different assays revealed that some inhibitors most likely interfere with the commercially available UDP-Glo™ glycosyltransferase assay, leading to false positive results. This observation calls for caution, when evaluating UDP mimetic as OGT inhibitors with the UDP-Glo™ glycosyltransferase assay, as misinterpretations can occur.

Functional variants in hematopoietic transcription factor footprints and their roles in the risk of immune system diseases

Genome-wide association studies (GWAS) have been performed to identify thousands of variants in the human genome as disease risk markers, but functional variants that actually affect gene regulation and their genomic features remain largely unknown. Here we performed a comprehensive survey of functional variants in the regulatory elements of the human genome. We integrated hematopoietic transcription factor (TF) footprints datasets generated by ENCODE project with multiple quantitative trait locus (QTL) datasets (eQTL, caQTL, bQTL, and hQTL) and investigated the associations of functional variants and immune system disease risk. We identified candidate regulatory variants highly linked with GWAS lead variants and found that they were strongly enriched in active enhancers in hematopoietic cells, emphasizing the clinical relevance of enhancers in disease risk. Moreover, we found some strong relationships between traits and hematopoietic cell types or TFs. We highlighted some credible regulatory variants and found that a variant, rs2291668, which potentially functions in the molecular pathogenesis of multiple sclerosis, is located within a TF footprint present in a protein-coding exon of the TNFSF14 gene, indicating that protein-coding exons as well as noncoding regions can possess clinically relevant regulatory elements. Collectively, our results shed light on the molecular pathogenesis of immune system diseases. The methods described in this study can readily be applied to the study of the risk factors of other diseases.