Advances, practice, and clinical perspectives in high-throughput sequencing

Distinctive genes and signaling pathways associated with type 2 diabetes-related periodontitis: Preliminary study

The biological mechanisms underlying the pathogenesis of type 2 diabetes (T2DM)-related periodontitis remain unclear. This cross-sectional study evaluated the distinctive transcriptomic changes between tissues with periodontal health and with periodontitis in patients with T2DM. In this cross-sectional study, whole transcriptome sequencing was performed on gingival biopsies from non-periodontitis and periodontitis tissues from non-diabetic and diabetic patients. A differentially expressed gene (DEG) analysis and Ingenuity Pathway Analysis (IPA) assessed the genes and signaling pathways associated with T2DM-related periodontitis. Immunohistochemistry was performed to validate selected DEGs possibly involved in T2DM-related periodontitis. Four hundred and twenty and one thousand five hundred and sixty-three DEGs (fold change ≥ 2) were uniquely identified in the diseased tissues of non-diabetic and diabetic patients, respectively. The IPA predicted the activation of Phagosome Formation, Cardiac β-adrenergic, tRNA Splicing, and PI3K/AKT pathways. The IPA also predicted the inhibition of Cholesterol Biosynthesis, Adrenomedullin, and Inositol Phosphate Compounds pathways in T2DM-related periodontitis. Validation of DEGs confirmed changes in protein expression of PTPN2, PTPN13, DHCR24, PIK3R2, CALCRL, IL1RN, IL-6R and ITGA4 in diseased tissues in diabetic subjects. Thus, these preliminary findings indicate that there are specific genes and functional pathways that may be involved in the pathogenesis of T2DM-related periodontitis.

Comparative analysis of subgingival microbiota in patients with mild, moderate, and severe chronic periodontitis

In this study, we explored the suspected pathogens of chronic periodontitis at different stages of occurrence and development. We collected 100 gingival crevicular fluid samples, 27, 27, and 26 from patients with mild, moderate, and severe chronic periodontitis, respectively, and 20 from healthy individuals. Pathogens were detected using a 16S rRNA metagenomic approach. Quantitative Insights in Microbial Ecology, Mothur, and other software were used to analyze the original data, draw relative abundance histograms and heat maps, and calculate flora abundance and diversity indexes. We identified 429 operational taxonomic units, covering 13 phyla, 20 classes, 32 orders, 66 families, and 123 genera from the four groups of samples. Each group showed microbial diversity, and the number of new species of bacterial flora in the gingival crevicular fluid samples gradually increased from the healthy to the severe chronic periodontitis group. There was a significant difference in the relative abundance of the core flora at the phylum, class, order, family, and genus classification levels. Our data indicated a certain correlation between the changes in the subgingival microbial structure and the occurrence and development of chronic periodontitis, which might be able to provide a reference for the diagnosis, treatment and prevention of chronic periodontitis.

Effects of Biocontrol Agents Application on Soil Bacterial Community and the Quality of Tobacco

In this study, to evaluate the effect of different biocontrol agents (BCAs) on the soil bacterial community, we investigated the effects of Bacillus amyloliquefaciens, synthetic bacterial community (Aspergillus niger:Bacillus subtilis:Bacillus licheniformis:Streptomyces microflavus = 3:3:3:1, SynCom), and BCAs combined with lime-nitrogen on soil bacterial community by utilizing 16S rRNA sequencing technology. The sequencing shows that BCAs application can improve the value of Shannon and Sobs index of bacterial community during tobacco rosette and vigorous growing period. With the growth of tobacco, the effect of BCAs on the composition and difference of soil bacterial community structure becomes more and more obvious. In terms of average relative richness, the top six phyla of soil bacterial community are Proteobacteria, Actinobacteria, Chloroflexi, Acidobacteria, Gemmatimonadetes, and Bacteroidetes. Bacillus amyloliquefaciens application can increase the relative richness of Proteobacteria and Bacteroidetes. And the combination between BCAs and lime-nitrogen can increase the relative richness of Gemmatimonadetes and Bacteroidetes. The SynCom also can increase the relative richness of Bacteroidetes, whereas it decreases the relative richness of Acidobacteria. Proteobacteria, Acidobacteria, Gemmatimonadetes, and Bacteroidetes showing an extremely significant correlation with pH and exchangeable magnesium (EMg). BCAs application can improve the tobacco yield, effective leaves, and reducing sugar content that also has extremely significant positive correlation with pH and EMg. In conclusion, the results of our field experiments clearly show that BCAs application can significantly affect the soil pH and EMg by changing most of the dominant soil bacterial species. The richness of Bacteroidetes can serve as an indicator of the changes in soil pH and EMg caused by BCAs application.

Molecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when

The increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical-chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80-85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore's law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.

Illumina-based sequencing analysis of pathogenic microorganisms in dental caries patients of different Chinese ethnic groups

Objective

To analyze the pathogenic community diversity of dental caries patients from Tu, Hui, Tibetan, and Han Chinese ethnic groups.

Methods

Forty saliva samples were collected from the following patients with dental caries: Tu from Huzhu County (n = 10), Hui from Ping’an County (n = 10), Han from Xining city (n = 10), and Tibetan from Yushu (n = 10). High-throughput sequencing of bacterial 16S rRNA genes (V3-V4) was performed using the Illumina MiSeq sequencing platform.

Results

Based on 97% similarity clustering, operational taxonomic units of Tu, Hui, Tibetan, and Han ethnic groups were 181, 210, 38, and 67, respectively. In Tu patients, 11 phyla, 19 classes, and 89 genera were identified, compared with 13 phyla, 21 classes, and 113 genera in Hui patients, two phyla, four classes, and 21 genera in Tibetan patients, five phyla, nine classes, and 34 genera in Han patients, and four phyla, five classes, and 12 genera from the control group. The main pathogens of dental caries included Veillonella, Aggregatibacter, Leptotrichia, Bacteroides, Granulicatella, Streptococcus, and Prevotella.

Conclusion

The pathogenic microorganisms of dental caries differ greatly among Tu, Hui, Tibetan, and Han ethnic groups. These findings provide a theoretical basis for the effective prevention and treatment of dental caries in different Chinese populations.

Detection approaches for multidrug resistance genes of leukemia

Leukemia is a clonal malignant hematopoietic stem cell disease. It is the sixth most lethal cancer and accounts for 4% of all cancers. The main form of treatment for leukemia is chemotherapy. While some cancer types with a higher incidence than leukemia, such as lung and gastric cancer, have shown a sharp decline in mortality rates in recent years, leukemia has not followed this trend. Drug resistance is often regarded as the main clinical obstacle to effective chemotherapy in patients diagnosed with leukemia. Many resistance mechanisms have now been identified, and multidrug resistance (MDR) is considered the most important and prevalent mechanism involved in the failure of chemotherapy in leukemia. In order to reverse MDR and improve leukemia prognosis, effective detection methods are needed to identify drug resistance genes at initial diagnosis. This article provides a comprehensive overview of published approaches for the detection of MDR in leukemia. Identification of relevant MDR genes and methods for early detection of these genes will be needed in order to treat leukemia more effectively.

ZBTB16 as a Downstream Target Gene of Osterix Regulates Osteoblastogenesis of Human Multipotent Mesenchymal Stromal Cells

Human multipotent mesenchymal stromal cells (hMSCs) possess the ability to differentiate into osteoblasts, and they can be utilized as a source for bone regenerative therapy. Osteoinductive pretreatment, which induces the osteoblastic differentiation of hMSCs in vitro, has been widely used for bone tissue engineering prior to cell transplantation. However, the molecular basis of osteoblastic differentiation induced by osteoinductive medium (OIM) is still unknown. Therefore, we used a next-generation sequencer to investigate the changes in gene expression during the osteoblastic differentiation of hMSCs. The hMSCs used in this study possessed both multipotency and self-renewal ability. Whole-transcriptome analysis revealed that the expression of zinc finger and BTB domain containing 16 (ZBTB16) was significantly increased during the osteoblastogenesis of hMSCs. ZBTB16 mRNA and protein expression was enhanced by culturing the hMSCs with OIM. Small interfering RNA (siRNA)-mediated gene silencing of ZBTB16 decreased the activity of alkaline phosphatase (ALP); the expression of osteogenic genes, such as osteocalcin (OCN) and bone sialoprotein (BSP), and the mineralized nodule formation induced by OIM. siRNA-mediated gene silencing of Osterix (Osx), which is known as an essential regulator of osteoblastic differentiation, markedly downregulated the expression of ZBTB16. In addition, chromatin immunoprecipitation (ChIP) assays showed that Osx associated with the ZBTB16 promoter region containing the GC-rich canonical Sp1 sequence, which is the specific Osx binding site. These findings suggest that ZBTB16 acts as a downstream transcriptional regulator of Osx and can be useful as a late marker of osteoblastic differentiation. J. Cell. Biochem. 117: 2423-2434, 2016. © 2016 Wiley Periodicals, Inc.

Synthetic lethality in lung cancer and translation to clinical therapies

Lung cancer is a heterogeneous disease consisting of multiple histological subtypes each driven by unique genetic alterations. Despite the development of targeted therapies that inhibit the oncogenic mutations driving a subset of lung cancer cases, there is a paucity of effective treatments for the majority of lung cancer patients and new strategies are urgently needed. In recent years, the concept of synthetic lethality has been established as an effective approach for discovering novel cancer-specific targets as well as a method to improve the efficacy of existing drugs which provide partial but insufficient benefits for patients. In this review, we discuss the concept of synthetic lethality, the various types of synthetic lethal interactions in the context of oncology and the approaches used to identify these interactions, including recent advances that have transformed the ability to discover novel synthetic lethal combinations on a global scale. Lastly, we describe the specific synthetic lethal interactions identified in lung cancer to date and explore the pharmacological challenges and considerations in translating these discoveries to the clinic.