RESUMO
MOTIVATION: Time-lapse imaging in combination with fluorescence microscopy techniques enable the investigation of gene regulatory circuits and uncovered phenomena like culture heterogeneity. In this context, computational image processing for the analysis of single cell behaviour plays an increasing role in systems biology and mathematical modelling approaches. Consequently, we developed a software package with graphical user interface for the analysis of single bacterial cell behaviour. RESULTS: A new software called TLM-Tracker allows for the flexible and user-friendly interpretation for the segmentation, tracking and lineage analysis of microbial cells in time-lapse movies. AVAILABILITY: The software package, including manual, tutorial video and examples, is available as Matlab code or executable binaries at http://www.tlmtracker.tu-bs.de.
Assuntos
Processamento de Imagem Assistida por Computador/métodos , Microscopia de Fluorescência/métodos , Microscopia de Vídeo/métodos , Análise de Célula Única/métodos , Software , Imagem com Lapso de Tempo/métodos , Bacillus megaterium/citologia , Bacillus megaterium/metabolismo , Proteínas de Fluorescência Verde/biossíntese , Proteínas de Fluorescência Verde/química , Modelos Biológicos , Modelos TeóricosRESUMO
Pseudomonas aeruginosa is one of the most frequent agents of urinary tract infections especially in patients with indwelling urethral catheters. A total of 30 P. aeruginosa isolates from urinary tract infections was investigated for their genotypic and phenotypic characteristics. 'Single Nucleotide Polymorphism' chip typing experiments in combination with bioinformatical cluster analyses allowed genotypic grouping of the isolates. Some similarities to strains from lung infections but also to environmental strains were observed. Finally, several urinary tract-specific groups were identified indicating a strong heterogeneity of the urethral isolates. Pyoverdin, protease, and phospholipase A production in combination with quorum sensing activity and biofilm formation were common phenotypic characteristics of these strains. In contrast, swarming phenotypes, the production of pyocyanin, and the extracellular enzymes phospholipase C and elastase were rarely observed. Interestingly, strains isolated from catheter-associated infections showed significantly enhanced biofilm formation, decreased motility, and a slightly increased expression of virulence factors in relation to isolates from acute urinary tract infections.
Assuntos
Infecções por Pseudomonas/microbiologia , Pseudomonas aeruginosa/classificação , Pseudomonas aeruginosa/isolamento & purificação , Infecções Urinárias/microbiologia , Técnicas de Tipagem Bacteriana , Biofilmes/crescimento & desenvolvimento , Análise por Conglomerados , Enzimas/metabolismo , Genótipo , Humanos , Tipagem Molecular , Oligopeptídeos/metabolismo , Polimorfismo de Nucleotídeo Único , Pseudomonas aeruginosa/genética , Pseudomonas aeruginosa/fisiologia , Piocianina/metabolismo , Percepção de Quorum , Fatores de Virulência/metabolismoRESUMO
Streptococci are the causative agent of many human infectious diseases including bacterial pneumonia and meningitis. Here, we present Strepto-DB, a database for the comparative genome analysis of group A (GAS) and group B (GBS) streptococci. The known genomes of various GAS and GBS contain a large fraction of distributed genes that were found absent in other strains or serotypes of the same species. Strepto-DB identifies the homologous proteins deduced from the genomes of interest. It allows for the elucidation of the GAS and GBS core- and pan-genomes via genome-wide comparisons. Moreover, an intergenic region analysis tool provides alignments and predictions for transcription factor binding sites in the non-coding sequences. An interactive genome browser visualizes functional annotations. Strepto-DB (http://oger.tu-bs.de/strepto_db) was created by the use of OGeR, the Open Genome Resource for comparative analysis of prokaryotic genomes. OGeR is a newly developed open source database and tool platform for the web-based storage, distribution, visualization and comparison of prokaryotic genome data. The system automatically creates the dedicated relational database and web interface and imports an arbitrary number of genomes derived from standardized genome files. OGeR can be downloaded at http://oger.tu-bs.de.
Assuntos
Bases de Dados Genéticas , Genoma Bacteriano , Streptococcus/genética , Proteínas de Bactérias/genética , DNA Intergênico/química , Genômica , Streptococcus/classificaçãoRESUMO
PRODORIC is a database that provides annotated information on the regulation of gene expression in prokaryotes. It integrates a large compilation of gene regulatory data including transcription factor binding sites, promoter structures and gene expression patterns. The whole dataset is manually curated and relies on published results extracted from the scientific literature. The current extended version of PRODORIC contains gene regulatory data for several new microorganisms. Major improvements were realized in the design of the web interface and the accessibility of the stored information. The database was further improved by the implementation of various new tools for the elucidation of gene regulatory interactions. Thus, the PRODORIC platform represents a framework for the interactive exploration, prediction and evaluation of gene regulatory networks in prokaryotes. PRODORIC is accessible at http://www.prodoric.de.