Genomics and Informatics最新文献

Importance of accurate molecular diagnosis and quantification of particular disease-related pathogenic microorganisms is highlighted as an introductory step to prevent and care for diseases. In this study, we designed a primer/probe set for quantitative real-time polymerase chain reaction (qRT-PCR) targeting rgpA gene, known as the specific virulence factor of periodontitis-related pathogenic bacteria 'Porphyromonas gingivalis', and evaluated its diagnostic efficiency by detecting and quantifying relative bacterial load of P. gingivalis within saliva samples collected from clinical subjects. As a result of qRT-PCR, we confirmed that relative bacterial load of P. gingivalis was detected and quantified within all samples of positive control and periodontitis groups. On the contrary, negative results were confirmed in both negative control and healthy groups. Additionally, as a result of comparison with next-generation sequencing (NGS)-based 16S metagenome profiling data, we confirmed relative bacterial load of P. gingivalis, which was not identified on bacterial classification table created through 16S microbiome analysis, in qRT-PCR results. It showed that an approach to quantifying specific microorganisms by applying qRT-PCR method could solve microbial misclassification issues at species level of an NGS-based 16S microbiome study. In this respect, we suggest that P. gingivalis-specific primer/probe set introduced in present study has efficient applicability in various oral healthcare industries, including periodontitis-related microbial molecular diagnosis field.

Mendelian randomization (MR) uses genetic variation as a natural experiment to investigate the causal effects of modifiable risk factors (exposures) on outcomes. Two-sample Mendelian randomization (2SMR) is widely used to measure causal effects between exposures and outcomes via genome-wide association studies. 2SMR can increase statistical power by utilizing summary statistics from large consortia such as the UK Biobank. However, the first-order term approximation of standard error is commonly used when applying 2SMR. This approximation can underestimate the variance of causal effects in MR, which can lead to an increased false-positive rate. An alternative is to use the second-order approximation of the standard error, which can considerably correct for the deviation of the first-order approximation. In this study, we simulated MR to show the degree to which the first-order approximation underestimates the variance. We show that depending on the specific situation, the first-order approximation can underestimate the variance almost by half when compared to the true variance, whereas the second-order approximation is robust and accurate.

Salivary gland carcinoma (SGC) is rare cancer, constituting 6% of neoplasms in the head and neck area. The most responsible genes and pathways involved in the pathology of this disorder have not been fully understood. We aimed to identify differentially expressed genes (DEGs), the most critical hub genes, transcription factors, signaling pathways, and biological processes (BPs) associated with the pathogenesis of primary SGC. The mRNA dataset GSE153283 in the Gene Expression Omnibus database was re-analyzed for determining DEGs in cancer tissue of patients with primary SGC compared to the adjacent normal tissue (adjusted p-value < 0.001; |Log2 fold change| > 1). A protein interaction map (PIM) was built, and the main modules within the network were identified and focused on the different pathways and BP analyses. The hub genes of PIM were discovered, and their associated gene regulatory network was built to determine the master regulators involved in the pathogenesis of primary SGC. A total of 137 genes were found to be differentially expressed in primary SGC. The most significant pathways and BPs that were deregulated in the primary disease condition were associated with the cell cycle and fibroblast proliferation procedures. TP53, EGF, FN1, NOTCH1, EZH2, COL1A1, SPP1, CDKN2A, WNT5A, PDGFRB, CCNB1, and H2AFX were demonstrated to be the most critical genes linked with the primary SGC. SPIB, FOXM1, and POLR2A significantly regulate all the hub genes. This study illustrated several hub genes and their master regulators that might be appropriate targets for the therapeutic aims of primary SGC.

Kawasaki disease (KD) is an acute pediatric vasculitis that affects genetically susceptible infants and children. To identify coding variants that influence susceptibility to KD, we conducted whole exome sequencing of 159 patients with KD and 902 controls, and performed a replication study in an independent 586 cases and 732 controls. We identified five rare coding variants in five genes (FCRLA, PTGER4, IL17F, CARD11, and SIGLEC10) associated with KD (odds ratio [OR], 1.18 to 4.41; p = 0.0027-0.031). We also performed association analysis in 26 KD patients with coronary artery aneurysms (CAAs; diameter > 5 mm) and 124 patients without CAAs (diameter < 3 mm), and identified another five rare coding variants in five genes (FGFR4, IL31RA, FNDC1, MMP8, and FOXN1), which may be associated with CAA (OR, 3.89 to 37.3; p = 0.0058-0.0261). These results provide insights into new candidate genes and genetic variants potentially involved in the development of KD and CAA.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encodes small envelope protein (E) that plays a major role in viral assembly, release, pathogenesis, and host inflammation. Previous studies demonstrated that pyrazine ring containing amiloride analogs inhibit this protein in different types of coronavirus including SARS-CoV-1 small envelope protein E (SARS-CoV-1 E). SARS-CoV-1 E has 93.42% sequence identity with SARS-CoV-2 E and shared a conserved domain NS3/small envelope protein (NS3_envE). Amiloride analog hexamethylene amiloride (HMA) can inhibit SARS-CoV-1 E. Therefore, we performed molecular docking and dynamics simulations to explore whether amiloride analogs are effective in inhibiting SARS-CoV-2 E. To do so, SARS-CoV-1 E and SARS-CoV-2 E proteins were taken as receptors while HMA and 3-amino-5-(azepan-1-yl)-N-(diaminomethylidene)-6-pyrimidin-5-ylpyrazine-2-carboxamide (3A5NP2C) were selected as ligands. Molecular docking simulation showed higher binding affinity scores of HMA and 3A5NP2C for SARS-CoV-2 E than SARS-CoV-1 E. Moreover, HMA and 3A5NP2C engaged more amino acids in SARS-CoV-2 E. Molecular dynamics simulation for 1 μs (1,000 ns) revealed that these ligands could alter the native structure of the proteins and their flexibility. Our study suggests that suitable amiloride analogs might yield a prospective drug against coronavirus disease 2019.

Kaposi's sarcoma-associated herpesvirus (KSHV) is one of the few human oncogenic viruses, which causes a variety of malignancies, including Kaposi's sarcoma, multicentric Castleman disease, and primary effusion lymphoma, particularly in human immunodeficiency virus patients. The currently available treatment options cannot always prevent the invasion and dissemination of this virus. In recent times, siRNA-based therapeutics are gaining prominence over conventional medications as siRNA can be designed to target almost any gene of interest. The ORF57 is a crucial regulatory protein for lytic gene expression of KSHV. Disruption of this gene translation will inevitably inhibit the replication of the virus in the host cell. Therefore, the ORF57 of KSHV could be a potential target for designing siRNA-based therapeutics. Considering both sequence preferences and target site accessibility, several online tools (i-SCORE Designer, Sfold web server) had been utilized to predict the siRNA guide strand against the ORF57. Subsequently, off-target filtration (BLAST), conservancy test (fuzznuc), and thermodynamics analysis (RNAcofold, RNAalifold, and RNA Structure web server) were also performed to select the most suitable siRNA sequences. Finally, two siRNAs were identified that passed all of the filtration phases and fulfilled the thermodynamic criteria. We hope that the siRNAs predicted in this study would be helpful for the development of new effective therapeutics against KSHV.

Campylobacter jejuni is one of the most prevalent organisms associated with foodborne illness across the globe causing campylobacteriosis and gastritis. Many proteins of C. jejuni are still unidentified. The purpose of this study was to determine the structure and function of a non-annotated hypothetical protein (HP) from C. jejuni. A number of properties like physiochemical characteristics, 3D structure, and functional annotation of the HP (accession No. CAG2129885.1) were predicted using various bioinformatics tools followed by further validation and quality assessment. Moreover, the protein-protein interactions and active site were obtained from the STRING and CASTp server, respectively. The hypothesized protein possesses various characteristics including an acidic pH, thermal stability, water solubility, and cytoplasmic distribution. While alpha-helix and random coil structures are the most prominent structural components of this protein, most of it is formed of helices and coils. Along with expected quality, the 3D model has been found to be novel. This study has identified the potential role of the HP in 2-methylcitric acid cycle and propionate catabolism. Furthermore, protein-protein interactions revealed several significant functional partners. The in-silico characterization of this protein will assist to understand its molecular mechanism of action better. The methodology of this study would also serve as the basis for additional research into proteomic and genomic data for functional potential identification.

Genome-wide association studies (GWASs) facilitated the discovery of countless disease-associated variants. However, GWASs have mostly been conducted in European ancestry samples. Recent studies have reported that these European-based association results may reduce disease prediction accuracy when applied in non-Europeans. Therefore, previously reported variants should be validated in non-European populations to establish reliable scientific evidence for precision medicine. In this study, we validated known associations with type 2 diabetes (T2D) and related metabolic traits in 125,850 samples from a Korean population genotyped by the Korea Biobank Array (KBA). At the end of December 2020, there were 8,823 variants associated with glycemic traits, lipids, liver enzymes, and T2D in the GWAS catalog. Considering the availability of imputed datasets in the KBA genome data, publicly available East-Asian T2D summary statistics, and the linkage disequilibrium among the variants (r2 < 0.2), 2,900 independent variants were selected for further analysis. Among these, 1,837 variants (63.3%) were statistically significant (p ≤ 0.05). Most of the non-replicated variants (n = 1,063) showed insufficient statistical power and decreased minor allele frequencies compared with the replicated variants. Moreover, most of known variants showed <10% genetic heritability. These results could provide valuable scientific evidence for future study designs, the current power of GWASs, and future applications in precision medicine in the Korean population.