Bioinformatics and Biology Insights最新文献

Several species of the Helicoverpa genus have been recognized as major agricultural pests from different regions of the world, among which Helicoverpa armigera species has been reported as the most destructive and cosmopolitan species in most regions of the world, including Iran. This pest is a polyphagous species and can cause damage to more than 120 plant species. Studying the internal microbiome of pests is very important in identifying species' weaknesses and natural enemies and potential biological control agents. For genomic characterization of the microbial community associated with H armigera, the whole genome of insect larvae collected from vegetable fields in the northwest of Iran was sequenced using next-generation sequencing Illumina platform. Finally, about 2 GB of raw data were obtained. Using the MetaPhlAn2 pipeline, it was predicted that 2 endosymbiont bacterial species including Buchnera aphidicola and Serratia symbiotica were associated with H armigera. Alignment of reference strains sequences related to both endosymbiotic bacteria with raw data and subsequently, assembly analyses resulted in 2 genomes with 657 623 bp length with GC content of 27.4% for B aphidicola and 1 595 135 bp length with GC content of 42.90% for S symbiotica. This research is the first report on the association of B aphidicola and S symbiotica as endosymbiotic bacteria with H armigera worldwide.

One of the most valuable traits in production and breeding is a sheep's prolificacy which is influenced by several genes, one of which is the osteopontin (OPN) gene. Thus, this study aimed to determine the effect of genetic variation within the OPN gene on Awassi ewe prolificacy. Genomic DNA was extracted from 123 single-progeny ewes and 109 twin ewes. Polymerase chain reaction (PCR) was used to amplify 4 sequence fragments (289, 275, 338, and 372 bp), representing exons 4, 5, 6, and 7 of the OPN gene. A 372 bp amplicon was identified with 3 different genotypes: TT, TC, and CC. Sequence analysis revealed a novel mutation in TC genotypes p.Q>R234. Statistical analysis revealed that the single nucleotide polymorphism (SNP) p.Q>R234 was associated with prolificacy. Ewes carrying the p.Q>R234 SNP had significantly (P ⩽ .01) lower litter sizes, twinning rates, and lambing rates, and more days to lambing than those with the TC and TT genotypes. The p.Q>R234 SNP was confirmed to be responsible for lower litter size through logistic regression analysis. From these results, we can conclude that the missense variant p.Q>R234 adversely affects the traits of interest and shows that the p.Q>R234 SNP negatively influences the prolificacy of Awassi sheep. Based on this study, it is evident that ewes in this population carrying the p.Q>R234 SNP have a lower litter size and are less prolific.

Multi-omic data mining has the potential to revolutionize synthetic biology especially in non-model organisms that have not been extensively studied. However, tangible engineering direction from computational analysis remains elusive due to the interpretability of large datasets and the difficulty in analysis for non-experts. New omics data are generated faster than our ability to use and analyse results effectively, resulting in strain development that proceeds through classic methods of trial-and-error without insight into complex cell dynamics. Here we introduce a user-friendly, interactive website hosting multi-omics data. Importantly, this new platform allows non-experts to explore questions in an industrially important chassis whose cellular dynamics are still largely unknown. The web platform contains a complete KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis derived from principal components analysis, an interactive bio-cluster heatmap analysis of genes, and the Halomonas TD1.0 genome-scale metabolic (GEM) model. As a case study of the effectiveness of this platform, we applied unsupervised machine learning to determine key differences between Halomonas bluephagenesis TD1.0 cultivated under varied conditions. Specifically, cell motility and flagella apparatus are identified to drive energy expenditure usage at different osmolarities, and predictions were verified experimentally using microscopy and fluorescence labelled flagella staining. As more omics projects are completed, this landing page will facilitate exploration and targeted engineering efforts of the robust, industrial chassis H bluephagenesis for researchers without extensive bioinformatics background.

Non-typhoidal Salmonella (NTS) infections occur globally with high morbidity and mortality. The public health challenge caused is exacerbated by increasing rate of antibiotic resistance and absence of NTS vaccine. In this study, we characterized the outer membrane protein C (OmpC) serovars isolated from different food animals and predicted antigenicity. ompC of 27 NTS serovars were amplified by polymerase chain reaction (PCR) and sequenced. Sequence data were analysed and B-cell epitope prediction was done by BepiPred tool. T-cell epitope prediction was done by determining peptide-binding affinities of major histocompatibility complex (MHC) classes I and II using NetMHC pan 2.8 and NetMHC-II pan 3.2, respectively. ompC sequence analysis revealed conserved region among ompCs of Salmonella Serovars. A total of 66.7% of ompCs were stable with instability index value < 40 and molecular weight that ranged from 27 745.47 to 32 714.32 kDa. All ompCs were thermostable and hydrophilic with the exception of S. Pomona (14p) isolate that had ompC with GRAVY value of 0.028 making it hydrophobic. Linear B-cell epitope prediction revealed ability of ompC to elicit humoral immunity. Multiple B-cell epitopes that were exposed and buried were observed on several positions on the ompC sequences. T-cell epitope prediction revealed epitopes with strong binding affinity to MHC-I and -II. Strong binding to human leukocyte antigen (HLA-A) ligands, including HLA-A03:1, HLA-A24:02 and HLA-A26:01 in the case of MHC-I were observed. While binding affinity to H-2 IAs, H-2 IAq and H-2 IAu (H-2 mouse molecules) were strongest in the case of MHC-II. ompCs of NTS serovars isolated from different food animal sources indicated ability to elicit humoral and cell-mediated immunity. Hence, ompCs of NTS serovars are potential candidate for production of NTS vaccines.

Human papillomavirus 16 (HPV16) is considered to be strongly correlated with the development of cervical cancer. Among the 8 HPV16 genes, the E6 constitutes a remarkable marker to follow the evolutionary history and spatial phylodynamics of HPV16 in the Mediterranean basin. Thus, this work aims to decipher the major evolutionary events and crosstalks in the Mediterranean basin with a focus on Tunisian strains regarding the E6 oncogene. In this study, we first extracted the available and annotated Mediterranean strains of HPV16 E6 gene sequences (n = 155) from the NCBI nucleotide database. These sequences were aligned, edited, and used for the downstream phylogenetic analyses. Finally, a Bayesian Markov Chain Monte Carlo approach was applied to reconstruct the evolutionary history of HPV16 migration. Our results showed that the HPV circulating in Tunisia derived from a Croatian ancestor around the year 1987. This starting point spreads to most European countries to reach northern Africa through the Moroccan gateway in 2004.

Eukaryotic non-coding regulatory features contribute significantly to cellular plasticity which on aberration leads to cellular malignancy. Enhancers are cis-regulatory elements that contribute to the development of resistance to endocrine therapy in estrogen receptor (ER)-positive breast cancer leading to poor clinical outcome. ER is vital for therapeutic targets in ER-positive breast cancer. Here, we review and report the different regulatory features present on ER with the objective to delineate potential mechanisms which may contribute to development of resistance. The UCSC Genome Browser, data mining, and bioinformatics tools were used to review enhancers, transcription factors (TFs), histone marks, long non-coding RNAs (lncRNAs), and variants residing in the non-coding region of the ER gene. We report 7 enhancers, 3 of which were rich in TF-binding sites and histone marks in a cell line-specific manner. Furthermore, some enhancers contain estrogen resistance variants and sites for lncRNA. Our review speculates putative models suggesting potential aberrations in gene regulation and expression if these regulatory landscapes and assemblies are altered. This review gives an interesting perspective in designing integrated in vitro studies including non-coding elements to study development of endocrine resistance in ER-positive breast cancer.

Background: Gram-negative bacterial infections are on the rise due to the high prevalence of multidrug-resistant bacteria, and efforts must be made to identify novel drug targets and then new antibiotics.

Methods: In the upstream part, we retrieved the genome sequences of 4 highly resistant Gram-negative bacteria (e.g., Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterobacter cloacae). The core proteins were assessed to find common, cytoplasmic, and essential proteins with no similarity to the human proteome. Novel drug targets were identified using DrugBank, and their sequence conservancy was evaluated. Protein Data Bank files and STRING interaction networks were assessed. Finally, the aminoacylation cavity of glycyl-tRNA synthetase (GlyQ) was virtually screened to identify novel inhibitors using AutoDock Vina and the StreptomeDB library. Ligands with high binding affinity were clustered, and then the pharmacokinetics properties of therapeutic agents were investigated.

Results: A total of 6 common proteins (e.g., RP-L28, RP-L30, RP-S20, RP-S21, Rnt, and GlyQ) were selected as novel and widespread drug targets against highly resistant Gram-negative superbugs based on different criteria. In the downstream analysis, virtual screening revealed that Rimocidin, Flavofungin, Chaxamycin, 11,11'-O-dimethyl-14'-deethyl-14'-methylelaiophylin, and Platensimycin were promising hit compounds against GlyQ protein. Finally, 11,11'-O-dimethyl-14'-deethyl-14'-methylelaiophylin was identified as the best potential inhibitor of GlyQ protein. This compound showed high absorption capacity in the human intestine.

Conclusion: The results of this study provide 6 common putative new drug targets against 4 highly resistant and Gram-negative bacteria. Moreover, we presented 5 different hit compounds against GlyQ protein as a novel therapeutic target. However, further in vitro and in vivo studies are needed to explore the bactericidal effects of proposed hit compounds against these superbugs.

Oxidative stress and inflammation have a role in the development of various diseases. Oxidative stress and inflammation are associated with many proteins, including Kelch ECH associating protein 1 (KEAP1) and inducible nitric oxide synthase (iNOS) proteins. The active compounds contained in Holothuria scabra have antioxidant and anti-inflammatory properties. This study aimed to evaluate the antioxidant and anti-inflammatory activity of sea cucumber's active compounds by targeting KEAP1 and iNOS proteins. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) scavenging activity of H. scabra extract were measured spectrophotometrically. The 3-dimensional (3D) structures of sea cucumber's active compounds and proteins were obtained from the PubChem and Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) databases. Molecular docking was performed using AutoDock Vina software. Molecular dynamics simulations were carried out using Yet Another Scientific Artificial Reality Application (YASARA) software with environmental parameters according to the cell's physiological conditions. The membrane permeability test was performed using the PerMM web server. The methanol extract of H. scabra had a weak antioxidant activity against DPPH and strong activity against NO radical. Scabraside and holothurinoside G had the most negative binding affinity values when interacting with the active site of KEAP1 and iNOS proteins. Molecular dynamics simulations also showed that both compounds were stable when interacting with KEAP1 and iNOS. However, scabraside and holothurinoside G were difficult to penetrate the cell plasma membrane, which is seen from the high energy transfer value in the lipid acyl chain region of phospholipids. Scabraside and holothurinoside G are predicted to act as antioxidants and anti-inflammations, but in their implementation to in vitro and in vivo study, it is necessary to have liposomes or nanoparticles, or other delivery methods to help these 2 compounds enter the cell.

Genomes may now be sequenced in a matter of weeks, leading to an influx of "hypothetical" proteins (HP) whose activities remain a mystery in GenBank. The information included inside these genes has quickly grown in prominence. Thus, we selected to look closely at the structure and function of an HP (AFF25514.1; 246 residues) from Pasteurella multocida (PM) subsp. multocida str. HN06. Possible insights into bacterial adaptation to new environments and metabolic changes might be gained by studying the functions of this protein. The PM HN06 2293 gene encodes an alkaline cytoplasmic protein with a molecular weight of 28352.60 Da, an isoelectric point (pI) of 9.18, and an overall average hydropathicity of around -0.565. One of its functional domains, tRNA (adenine (37)-N6)-methyltransferase TrmO, is a S-adenosylmethionine (SAM)-dependent methyltransferase (MTase), suggesting that it belongs to the Class VIII SAM-dependent MTase family. The tertiary structures represented by HHpred and I-TASSER models were found to be flawless. We predicted the model's active site using the Computed Atlas of Surface Topography of Proteins (CASTp) and FTSite servers, and then displayed it in 3 dimensional (3D) using PyMOL and BIOVIA Discovery Studio. Based on molecular docking (MD) results, we know that HP interacts with SAM and S-adenosylhomocysteine (SAH), 2 crucial metabolites in the tRNA methylation process, with binding affinities of 7.4 and 7.5 kcal/mol, respectively. Molecular dynamic simulations (MDS) of the docked complex, which included only modest structural adjustments, corroborated the strong binding affinity of SAM and SAH to the HP. Evidence for HP's possible role as an SAM-dependent MTase was therefore given by the findings of Multiple sequence alignment (MSA), MD, and molecular dynamic modeling. These in silico data suggest that the investigated HP might be used as a useful adjunct in the investigation of Pasteurella infections and the development of drugs to treat zoonotic pasteurellosis.

To analyze genome-wide super-enhancers (SEs) methylation signature of breast invasive carcinoma (BRCA) and its clinical value. Differential methylation sites (DMS) between BRCA and adjacent tissues from The Cancer Genome Atlas (TCGA) database were identified by using ChAMP package in R software. Super-enhancers were identified sing ROSE software. Overlap analysis was used to assess the potential DMS in SEs region. Feature selection was performed by Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm based on TCGA training cohort. Prognosis model validation was performed in TCGA training cohort, TCGA validation cohort, and gene expression omnibus (GEO) test cohort. The gene ontology and KEGG analysis revealed that SEs target genes were significantly enriched in cell-migration-associated processes and pathways. A total of 83 654 DMS were identified between BRCA and adjacent tissues. Around 2397 DMS in SEs region were identified by overlap study and used to feature selection. By using Cox regression and LASSO algorithm, 42 features were selected to develop a clinical prediction model (CPM). Both training (TCGA) and validation cohorts (TCGA and GEO) show that the CPM has ideal discrimination and calibration. The CPM based on DMS at SE regions has ideal discrimination and calibration, which combined with tumor node metastasis (TNM) stage could improve prognostication, and thus contribute to individualized medicine.