The genome-scale metabolic network analysis <Emphasis Type="Italic">of Zymomonas mobilis</Emphasis> ZM4 explains physiological features and suggests ethanol and succinic acid production strategies

Background  

Zymomonas mobilis ZM4 is a Gram-negative bacterium that can efficiently produce ethanol from various carbon substrates, including glucose, fructose, and sucrose, via the Entner-Doudoroff pathway. However, systems metabolic engineering is required to further enhance its metabolic performance for industrial application. As an important step towards this goal, the genome-scale metabolic model of Z. mobilis is required to systematically analyze in silico the metabolic characteristics of this bacterium under a wide range of genotypic and environmental conditions.     

Graphical representation of ribosomal RNA probe accessibility data using ARB software package

Background  

Taxon specific hybridization probes in combination with a variety of commonly used hybridization formats nowadays are standard tools in microbial identification. A frequently applied technology, fluorescence in situ hybridization (FISH), besides single cell identification, allows the localization and functional studies of the microbial community composition. Careful in silico design and evaluation of potential oligonucleotide probe targets is therefore crucial for performing successful hybridization experiments.     

NERVE: New Enhanced Reverse Vaccinology Environment

Background  

Since a milestone work on Neisseria meningitidis B, Reverse Vaccinology has strongly enhanced the identification of vaccine candidates by replacing several experimental tasks using in silico prediction steps. These steps have allowed scientists to face the selection of antigens from the predicted proteome of pathogens, for which cell culture is difficult or impossible, saving time and money. However, this good example of bioinformatics-driven immunology can be further developed by improving in silico steps and implementing biologist-friendly tools.     

DNA watermarks: A proof of concept

Background  

DNA-based watermarks are helpful tools to identify the unauthorized use of genetically modified organisms (GMOs) protected by patents. In silico analyses showed that in coding regions synonymous codons can be used to insert encrypted information into the genome of living organisms by using the DNA-Crypt algorithm.     

Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum

Background  

In silico genome-scale metabolic models enable the analysis of the characteristics of metabolic systems of organisms. In this study, we reconstructed a genome-scale metabolic model of Corynebacterium glutamicum on the basis of genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA), and the results of FBA were validated using data from culture experiments performed at different oxygen uptake rates.     

SVRMHC prediction server for MHC-binding peptides

Background  

The binding between antigenic peptides (epitopes) and the MHC molecule is a key step in the cellular immune response. Accurate in silico prediction of epitope-MHC binding affinity can greatly expedite epitope screening by reducing costs and experimental effort.     

Experimental annotation of the human pathogen <Emphasis Type="Italic">Candida albicans</Emphasis> coding and noncoding transcribed regions using high-resolution tiling arrays

Background  

Compared to other model organisms and despite the clinical relevance of the pathogenic yeast Candida albicans, no comprehensive analysis has been done to provide experimental support of its in silico-based genome annotation.     

Coherent pipeline for biomarker discovery using mass spectrometry and bioinformatics

Background  

Robust biomarkers are needed to improve microbial identification and diagnostics. Proteomics methods based on mass spectrometry can be used for the discovery of novel biomarkers through their high sensitivity and specificity. However, there has been a lack of a coherent pipeline connecting biomarker discovery with established approaches for evaluation and validation. We propose such a pipeline that uses in silico methods for refined biomarker discovery and confirmation.     

Analysis of the features and source gene composition of the AluYg6 subfamily of human retrotransposons

Background  

Alu elements are a family of SINE retrotransposons in primates. They are classified into subfamilies according to specific diagnostic mutations from the general Alu consensus. It is now believed that there may be several retrotranspositionally-competent source genes within an Alu subfamily. To investigate the evolution of young Alu elements it is critical to have access to complete subfamilies, which, following the release of the final human genome assembly, can now be obtained using in silico methods.     

Ontology-oriented retrieval of putative microRNAs in Vitis vinifera via GrapeMiRNA: a web database of de novo predicted grape microRNAs

Background  

Two complete genome sequences are available for Vitis vinifera Pinot noir. Based on the sequence and gene predictions produced by the IASMA, we performed an in silico detection of putative microRNA genes and of their targets, and collected the most reliable microRNA predictions in a web database. The application is available at .     

ITS as an environmental DNA barcode for fungi: an <Emphasis Type="Italic">in silico</Emphasis> approach reveals potential PCR biases

Background  

During the last 15 years the internal transcribed spacer (ITS) of nuclear DNA has been used as a target for analyzing fungal diversity in environmental samples, and has recently been selected as the standard marker for fungal DNA barcoding. In this study we explored the potential amplification biases that various commonly utilized ITS primers might introduce during amplification of different parts of the ITS region in samples containing mixed templates ('environmental barcoding'). We performed in silico PCR analyses with commonly used primer combinations using various ITS datasets obtained from public databases as templates.     

Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram

Background  

With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells.     

Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates

Background  

The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the experimentally-derived data are sufficiently not complete for the reconstruction of signaling pathways. This problem can be solved by the network enrichment with predicted protein interactions. The previously published in silico method PAAS was applied for prediction of interactions between protein kinases and their substrates.     

Genomic features defining exonic variants that modulate splicing

Background  

Single point mutations at both synonymous and non-synonymous positions within exons can have severe effects on gene function through disruption of splicing. Predicting these mutations in silico purely from the genomic sequence is difficult due to an incomplete understanding of the multiple factors that may be responsible. In addition, little is known about which computational prediction approaches, such as those involving exonic splicing enhancers and exonic splicing silencers, are most informative.     

<Emphasis Type="Italic">In silico</Emphasis> panning for a non-competitive peptide inhibitor

Background  

Peptide ligands have tremendous therapeutic potential as efficacious drugs. Currently, more than 40 peptides are available in the market for a drug. However, since costly and time-consuming synthesis procedures represent a problem for high-throughput screening, novel procedures to reduce the time and labor involved in screening peptide ligands are required. We propose the novel approach of 'in silico panning' which consists of a two-stage screening, involving affinity selection by docking simulation and evolution of the peptide ligand using genetic algorithms (GAs). In silico panning was successfully applied to the selection of peptide inhibitor for water-soluble quinoprotein glucose dehydrogenase (PQQGDH).     

TIde: a software for the systematic scanning of drug targets in kinetic network models

Background  

During the stages of the development of a potent drug candidate compounds can fail for several reasons. One of them, the efficacy of a candidate, can be estimated in silico if an appropriate ordinary differential equation model of the affected pathway is available. With such a model at hand it is also possible to detect reactions having a large effect on a certain variable such as a substance concentration.     

Implications for domain fusion protein-protein interactions based on structural information

Background  

Several in silico methods exist that were developed to predict protein interactions from the copious amount of genomic and proteomic data. One of these methods is Domain Fusion, which has proven to be effective in predicting functional links between proteins.     

Genome-scale metabolic reconstruction and <Emphasis Type="Italic">in silico</Emphasis> analysis of methylotrophic yeast <Emphasis Type="Italic">Pichia pastoris</Emphasis> for strain improvement

Background  

Pichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism.