Angiogenesis Analyzer for ImageJ - A comparative morphometric analysis of "Endothelial Tube Formation Assay" and "Fibrin Bead Assay".

Angiogenesis assays based on in vitro capillary-like growth of endothelial cells (EC) are widely used, either to evaluate the effect of anti- and pro-angiogenesis drugs of interest, or to test and compare the functional capacities of various types of EC and progenitor cells. Among the different methods applied to study angiogenesis, the most commonly used is the "Endothelial Tube Formation Assay" (ETFA). In suitable culture conditions, EC form two-dimensional (2D) branched structures that can lead to a meshed pseudo-capillary network. An alternative approach to ETFA is the "Fibrin Bead Assay" (FBA), based on the use of Cytodex 3 microspheres, which promote the growth of 3D capillary-like patterns from coated EC, suitable for high throughput in vitro angiogenesis studies. The analytical evaluation of these two widely used assays still remains challenging in terms of observation method and image analysis. We previously developed the "Angiogenesis Analyzer" for ImageJ (AA), a tool allowing analysis of ETFA-derived images, according to characteristics of the pseudo-capillary networks. In this work, we developed and implemented a new algorithm for AA able to recognize microspheres and to analyze the attached capillary-like structures from the FBA model. Such a method is presented for the first time in fully automated mode and using non-destructive image acquisition. We detailed these two algorithms and used the new AA version to compare both methods (i.e. ETFA and FBA) in their efficiency, accuracy and statistical relevance to model angiogenesis patterns of Human Umbilical Vein EC (HUVEC). Although the two methods do not assess the same biological step, our data suggest that they display specific and complementary information on the angiogenesis processes analysis.

NIH Image to ImageJ: 25 years of image analysis.

For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.

Sequence conservation and combinatorial complexity of Drosophila neural precursor cell enhancers.

BACKGROUND: The presence of highly conserved sequences within cis-regulatory regions can serve as a valuable starting point for elucidating the basis of enhancer function. This study focuses on regulation of gene expression during the early events of Drosophila neural development. We describe the use of EvoPrinter and cis-Decoder, a suite of interrelated phylogenetic footprinting and alignment programs, to characterize highly conserved sequences that are shared among co-regulating enhancers. RESULTS: Analysis of in vivo characterized enhancers that drive neural precursor gene expression has revealed that they contain clusters of highly conserved sequence blocks (CSBs) made up of shorter shared sequence elements which are present in different combinations and orientations within the different co-regulating enhancers; these elements contain either known consensus transcription factor binding sites or consist of novel sequences that have not been functionally characterized. The CSBs of co-regulated enhancers share a large number of sequence elements, suggesting that a diverse repertoire of transcription factors may interact in a highly combinatorial fashion to coordinately regulate gene expression. We have used information gained from our comparative analysis to discover an enhancer that directs expression of the nervy gene in neural precursor cells of the CNS and PNS. CONCLUSION: The combined use EvoPrinter and cis-Decoder has yielded important insights into the combinatorial appearance of fundamental sequence elements required for neural enhancer function. Each of the 30 enhancers examined conformed to a pattern of highly conserved blocks of sequences containing shared constituent elements. These data establish a basis for further analysis and understanding of neural enhancer function.

cis-Decoder discovers constellations of conserved DNA sequences shared among tissue-specific enhancers.

A systematic approach is described for analysis of evolutionarily conserved cis-regulatory DNA using cis-Decoder, a tool for discovery of conserved sequence elements that are shared between similarly regulated enhancers. Analysis of 2,086 conserved sequence blocks (CSBs), identified from 135 characterized enhancers, reveals most CSBs consist of shorter overlapping/adjacent elements that are either enhancer type-specific or common to enhancers with divergent regulatory behaviors. Our findings suggest that enhancers employ overlapping repertoires of highly conserved core elements.

EVOPRINTER, a multigenomic comparative tool for rapid identification of functionally important DNA.

Here, we describe a multigenomic DNA sequence-analysis tool, evoprinter, that facilitates the rapid identification of evolutionary conserved sequences within the context of a single species. The evoprinter output identifies multispecies-conserved DNA sequences as they exist in a reference DNA. This identification is accomplished by superimposing multiple reference DNA vs. test-genome pairwise blat (blast-like alignment tool) readouts of the reference DNA to identify conserved nucleotides that are shared by all orthologous DNAs. evoprinter analysis of well characterized genes reveals that most, if not all, of the conserved sequences are essential for gene function. For example, analysis of orthologous genes that are shared by many vertebrates identifies conserved DNA in both protein-encoding sequences and noncoding cis-regulatory regions, including enhancers and mRNA microRNA binding sites. In Drosophila, the combined mutational histories of five or more species affords near-base pair resolution of conserved transcription factor DNA-binding sites, and essential amino acids are revealed by the nucleotide flexibility of their codon-wobble position(s). Conserved small peptide-encoding genes, which had been undetected by conventional gene-prediction algorithms, are identified by the codon-wobble signatures of invariant amino acids. Also, evoprinter allows one to assess the degree of evolutionary divergence between orthologous DNAs by highlighting differences between a selected species and the other test species.