Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711

Background Metabolism including anabolism and catabolism is a prerequisite phenomenon for all living organisms. Anabolism refers to the synthesis of the entire compound needed by a species. Catabolism refers to the breakdown of molecules to obtain energy. Many metabolic pathways are undisclosed and many organism-specific enzymes involved in metabolism are misplaced. When predicting a specific metabolic pathway of a microorganism, the first and foremost steps is to explore available online databases. Among many online databases, KEGG and MetaCyc pathway databases were used to deduce trehalose metabolic network for bacteria Variovorax sp. PAMC28711. Trehalose, a disaccharide, is used by the microorganism as an alternative carbon source. Results While using KEGG and MetaCyc databases, we found that the KEGG pathway database had one missing enzyme (maltooligosyl-trehalose synthase, EC 5.4.99.15). The MetaCyc pathway database also had some enzymes. However, when we used RAST to annotate the entire genome of Variovorax sp. PAMC28711, we found that all enzymes that were missing in KEGG and MetaCyc databases were involved in the trehalose metabolic pathway. Conclusions Findings of this study shed light on bioinformatics tools and raise awareness among researchers about the importance of conducting detailed investigation before proceeding with any further work. While such comparison for databases such as KEGG and MetaCyc has been done before, it has never been done with a specific microbial pathway. Such studies are useful for future improvement of bioinformatics tools to reduce limitations.

A journey through the Corynebacterium pseudotuberculosis proteome promotes insights into its functional genome

Background Corynebacterium pseudotuberculosis is a Gram-positive facultative intracellular pathogen and the etiologic agent of illnesses like caseous lymphadenitis in small ruminants, mastitis in dairy cattle, ulcerative lymphangitis in equines, and oedematous skin disease in buffalos. With the growing advance in high-throughput technologies, genomic studies have been carried out to explore the molecular basis of its virulence and pathogenicity. However, data large-scale functional genomics studies are necessary to complement genomics data and better understating the molecular basis of a given organism. Here we summarize, MS-based proteomics techniques and bioinformatics tools incorporated in genomic functional studies of C. pseudotuberculosis to discover the different patterns of protein modulation under distinct environmental conditions, and antigenic and drugs targets. Methodology In this study we performed an extensive search in Web of Science of original and relevant articles related to methods, strategy, technology, approaches, and bioinformatics tools focused on the functional study of the genome of C. pseudotuberculosis at the protein level. Results Here, we highlight the use of proteomics for understating several aspects of the physiology and pathogenesis of C. pseudotuberculosis at the protein level. The implementation and use of protocols, strategies, and proteomics approach to characterize the different subcellular fractions of the proteome of this pathogen. In addition, we have discussed the immunoproteomics, immunoinformatics and genetic tools employed to identify targets for immunoassays, drugs, and vaccines against C. pseudotuberculosis infection. Conclusion In this review, we showed that the combination of proteomics and bioinformatics studies is a suitable strategy to elucidate the functional aspects of the C. pseudotuberculosis genome. Together, all information generated from these proteomics studies allowed expanding our knowledge about factors related to the pathophysiology of this pathogen.

An overview of databases and bioinformatics tools for plant antimicrobial peptides

: Antimicrobial peptides (AMPs) are small, ribosomally synthesized proteins found in nearly all forms of life. In plants, AMPs play a central role in plant defense due to their distinct physicochemical properties. Due to their broad-spectrum antimicrobial activity and rapid killing action, plant AMPs have become important candidates for the development of new drugs to control plant and animal pathogens that are resistant to multiple drugs. Further research is required to explore the potential uses of these natural compounds. Computational strategies have been increasingly used to understand key aspects of antimicrobial peptides. These strategies will help to minimize the time and cost of "wet-lab" experimentation. Researchers have developed various tools and databases to provide updated information on AMPs. However, despite the increased availability of antimicrobial peptide resources in biological databases, finding AMPs from plants can still be a difficult task. The number of plant AMP sequences in current databases is still small and yet often redundant. To facilitate further characterization of plant AMPs, we have summarized information on the location, distribution, and annotations of plant AMPs available in the most relevant databases for AMPs research. We also mapped and categorized the bioinformatics tools available in these databases. We expect that this will allow researchers to advance in the discovery and development of new plant AMPs with potent biological properties. We hope to provide insights to further expand the application of AMPs in the fields of biotechnology, pharmacy, and agriculture.

T-Cell Receptor Repertoire Analysis with Computational Tools—An Immunologist’s Perspective

Over the last few years, there has been a rapid expansion in the application of information technology to biological data. Particularly the field of immunology has seen great strides in recent years. The development of next-generation sequencing (NGS) and single-cell technologies also brought forth a revolution in the characterization of immune repertoires. T-cell receptor (TCR) repertoires carry comprehensive information on the history of an individual’s antigen exposure. They serve as correlates of host protection and tolerance, as well as biomarkers of immunological perturbation by natural infections, vaccines or immunotherapies. Their interrogation yields large amounts of data. This requires a suite of highly sophisticated bioinformatics tools to leverage the meaning and complexity of the large datasets. Many different tools and methods, specifically designed for various aspects of immunological research, have recently emerged. Thus, researchers are now confronted with the issue of having to choose the right kind of approach to analyze, visualize and ultimately solve their task at hand. In order to help immunologists to choose from the vastness of available tools for their data analysis, this review addresses and compares commonly used bioinformatics tools for TCR repertoire analysis and illustrates the advantages and limitations of these tools from an immunologist’s perspective.

Glioblastoma gene network reconstruction and ontology analysis by online bioinformatics tools

Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.

Advanced Bioinformatics Tools in the Pharmacokinetic Profiles of Natural and Synthetic Compounds with Anti-Diabetic Activity

Diabetes represents a major health problem, involving a severe imbalance of blood sugar levels, which can disturb the nerves, eyes, kidneys, and other organs. Diabes management involves several synthetic drugs focused on improving insulin sensitivity, increasing insulin production, and decreasing blood glucose levels, but with unclear molecular mechanisms and severe side effects. Natural chemicals extracted from several plants such as Gymnema sylvestre, Momordica charantia or Ophiopogon planiscapus Niger have aroused great interest for their anti-diabetes activity, but also their hypolipidemic and anti-obesity activity. Here, we focused on the anti-diabetic activity of a few natural and synthetic compounds, in correlation with their pharmacokinetic/pharmacodynamic profiles, especially with their blood-brain barrier (BBB) permeability. We reviewed studies that used bioinformatics methods such as predicted BBB, molecular docking, molecular dynamics and quantitative structure-activity relationship (QSAR) to elucidate the proper action mechanisms of antidiabetic compounds. Currently, it is evident that BBB damage plays a significant role in diabetes disorders, but the molecular mechanisms are not clear. Here, we presented the efficacy of natural (gymnemic acids, quercetin, resveratrol) and synthetic (TAK-242, propofol, or APX3330) compounds in reducing diabetes symptoms and improving BBB dysfunctions. Bioinformatics tools can be helpful in the quest for chemical compounds with effective anti-diabetic activity that can enhance the druggability of molecular targets and provide a deeper understanding of diabetes mechanisms.

Recent Trends in Cancer Genomics and Bioinformatics Tools Development

We overview recent research trends in cancer genomics, bioinformatics tools development and medical genetics, based on results discussed in papers collections “Medical Genetics, Genomics and Bioinformatics” (https://www [...]

Bioinformatics Applications to Reveal Molecular Mechanisms of Gene Expression Regulation in Model Organisms

Gene expression regulation at the transcriptome, genome, cell, and tissue levels is a complex phenomenon demanding the development of bioinformatics tools [...]