Pavel Tomancak

Fiji: an open-source platform for biological-image analysis

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

Globally optimal stitching of tiled 3D microscopic image acquisitions

Motivation: Modern anatomical and developmental studies often require high-resolution imaging of large specimens in three dimensions (3D). Confocal microscopy produces high-resolution 3D images, but is limited by a relatively small field of view compared with the size of large biological specimens. Therefore, motorized stages that move the sample are used to create a tiled scan of the whole specimen. The physical coordinates provided by the microscope stage are not precise enough to allow direct reconstruction (Stitching) of the whole image from individual image stacks. Results: To optimally stitch a large collection of 3D confocal images, we developed a method that, based on the Fourier Shift Theorem, computes all possible translations between pairs of 3D images, yielding the best overlap in terms of the cross-correlation measure and subsequently finds the globally optimal configuration of the whole group of 3D images. This method avoids the propagation of errors by consecutive registration steps. Additionally, to compensate the brightness differences between tiles, we apply a smooth, non-linear intensity transition between the overlapping images. Our stitching approach is fast, works on 2D and 3D images, and for small image sets does not require prior knowledge about the tile configuration. Availability: The implementation of this method is available as an ImageJ plugin distributed as a part of the Fiji project (Fiji is just ImageJ: http://pacific.mpi-cbg.de/). Contact: tomancak@mpi-cbg.de

Global analysis of mRNA localization reveals a prominent role in organizing cellular architecture and function.

Although subcellular mRNA trafficking has been demonstrated as a mechanism to control protein distribution, it is generally believed that most protein localization occurs subsequent to translation. To address this point, we developed and employed a high-resolution fluorescent in situ hybridization procedure to comprehensively evaluate mRNA localization dynamics during early Drosophila embryogenesis. Surprisingly, of the 3370 genes analyzed, 71% of those expressed encode subcellularly localized mRNAs. Dozens of new and striking localization patterns were observed, implying an equivalent variety of localization mechanisms. Tight correlations between mRNA distribution and subsequent protein localization and function, indicate major roles for mRNA localization in nucleating localized cellular machineries. A searchable web resource documenting mRNA expression and localization dynamics has been established and will serve as an invaluable tool for dissecting localization mechanisms and for predicting gene functions and interactions.

Exploiting transcription factor binding site clustering to identify cis-regulatory modules involved in pattern formation in the Drosophila genome

A major challenge in interpreting genome sequences is understanding how the genome encodes the information that specifies when and where a gene will be expressed. The first step in this process is the identification of regions of the genome that contain regulatory information. In higher eukaryotes, this cis-regulatory information is organized into modular units [cis-regulatory modules (CRMs)] of a few hundred base pairs. A common feature of these cis-regulatory modules is the presence of multiple binding sites for multiple transcription factors. Here, we evaluate the extent to which the tendency for transcription factor binding sites to be clustered can be used as the basis for the computational identification of cis-regulatory modules. By using published DNA binding specificity data for five transcription factors active in the early Drosophila embryo, we identified genomic regions containing unusually high concentrations of predicted binding sites for these factors. A significant fraction of these binding site clusters overlap known CRMs that are regulated by these factors. In addition, many of the remaining clusters are adjacent to genes expressed in a pattern characteristic of genes regulated by these factors. We tested one of the newly identified clusters, mapping upstream of the gap gene giant (gt), and show that it acts as an enhancer that recapitulates the posterior expression pattern of gt.

Systematic determination of patterns of gene expression during Drosophila embryogenesis

BackgroundCell-fate specification and tissue differentiation during development are largely achieved by the regulation of gene transcription.ResultsAs a first step to creating a comprehensive atlas of gene-expression patterns during Drosophila embryogenesis, we examined 2,179 genes by in situ hybridization to fixed Drosophila embryos. Of the genes assayed, 63.7% displayed dynamic expression patterns that were documented with 25,690 digital photomicrographs of individual embryos. The photomicrographs were annotated using controlled vocabularies for anatomical structures that are organized into a developmental hierarchy. We also generated a detailed time course of gene expression during embryogenesis using microarrays to provide an independent corroboration of the in situ hybridization results. All image, annotation and microarray data are stored in publicly available database. We found that the RNA transcripts of about 1% of genes show clear subcellular localization. Nearly all the annotated expression patterns are distinct. We present an approach for organizing the data by hierarchical clustering of annotation terms that allows us to group tissues that express similar sets of genes as well as genes displaying similar expression patterns.ConclusionsAnalyzing gene-expression patterns by in situ hybridization to whole-mount embryos provides an extremely rich dataset that can be used to identify genes involved in developmental processes that have been missed by traditional genetic analysis. Systematic analysis of rigorously annotated patterns of gene expression will complement and extend the types of analyses carried out using expression microarrays.

Global analysis of patterns of gene expression during Drosophila embryogenesis

BackgroundCell and tissue specific gene expression is a defining feature of embryonic development in multi-cellular organisms. However, the range of gene expression patterns, the extent of the correlation of expression with function, and the classes of genes whose spatial expression are tightly regulated have been unclear due to the lack of an unbiased, genome-wide survey of gene expression patterns.ResultsWe determined and documented embryonic expression patterns for 6,003 (44%) of the 13,659 protein-coding genes identified in the Drosophila melanogaster genome with over 70,000 images and controlled vocabulary annotations. Individual expression patterns are extraordinarily diverse, but by supplementing qualitative in situ hybridization data with quantitative microarray time-course data using a hybrid clustering strategy, we identify groups of genes with similar expression. Of 4,496 genes with detectable expression in the embryo, 2,549 (57%) fall into 10 clusters representing broad expression patterns. The remaining 1,947 (43%) genes fall into 29 clusters representing restricted expression, 20% patterned as early as blastoderm, with the majority restricted to differentiated cell types, such as epithelia, nervous system, or muscle. We investigate the relationship between expression clusters and known molecular and cellular-physiological functions.ConclusionNearly 60% of the genes with detectable expression exhibit broad patterns reflecting quantitative rather than qualitative differences between tissues. The other 40% show tissue-restricted expression; the expression patterns of over 1,500 of these genes are documented here for the first time. Within each of these categories, we identified clusters of genes associated with particular cellular and developmental functions.

TrakEM2 software for neural circuit reconstruction.

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.

Biological imaging software tools

Few technologies are more widespread in modern biological laboratories than imaging. Recent advances in optical technologies and instrumentation are providing hitherto unimagined capabilities. Almost all these advances have required the development of software to enable the acquisition, management, analysis and visualization of the imaging data. We review each computational step that biologists encounter when dealing with digital images, the inherent challenges and the overall status of available software for bioimage informatics, focusing on open-source options.

Gene expression divergence recapitulates the developmental hourglass model

The observation that animal morphology tends to be conserved during the embryonic phylotypic period (a period of maximal similarity between the species within each animal phylum) led to the proposition that embryogenesis diverges more extensively early and late than in the middle, known as the hourglass model. This pattern of conservation is thought to reflect a major constraint on the evolution of animal body plans. Despite a wealth of morphological data confirming that there is often remarkable divergence in the early and late embryos of species from the same phylum, it is not yet known to what extent gene expression evolution, which has a central role in the elaboration of different animal forms, underpins the morphological hourglass pattern. Here we address this question using species-specific microarrays designed from six sequenced Drosophila species separated by up to 40 million years. We quantify divergence at different times during embryogenesis, and show that expression is maximally conserved during the arthropod phylotypic period. By fitting different evolutionary models to each gene, we show that at each time point more than 80% of genes fit best to models incorporating stabilizing selection, and that for genes whose evolutionarily optimal expression level is the same across all species, selective constraint is maximized during the phylotypic period. The genes that conform most to the hourglass pattern are involved in key developmental processes. These results indicate that natural selection acts to conserve patterns of gene expression during mid-embryogenesis, and provide a genome-wide insight into the molecular basis of the hourglass pattern of developmental evolution.

An integrated micro- and macroarchitectural analysis of the Drosophila brain by computer-assisted serial section electron microscopy.

The analysis of microcircuitry (the connectivity at the level of individual neuronal processes and synapses), which is indispensable for our understanding of brain function, is based on serial transmission electron microscopy (TEM) or one of its modern variants. Due to technical limitations, most previous studies that used serial TEM recorded relatively small stacks of individual neurons. As a result, our knowledge of microcircuitry in any nervous system is very limited. We applied the software package TrakEM2 to reconstruct neuronal microcircuitry from TEM sections of a small brain, the early larval brain of Drosophila melanogaster. TrakEM2 enables us to embed the analysis of the TEM image volumes at the microcircuit level into a light microscopically derived neuro-anatomical framework, by registering confocal stacks containing sparsely labeled neural structures with the TEM image volume. We imaged two sets of serial TEM sections of the Drosophila first instar larval brain neuropile and one ventral nerve cord segment, and here report our first results pertaining to Drosophila brain microcircuitry. Terminal neurites fall into a small number of generic classes termed globular, varicose, axiform, and dendritiform. Globular and varicose neurites have large diameter segments that carry almost exclusively presynaptic sites. Dendritiform neurites are thin, highly branched processes that are almost exclusively postsynaptic. Due to the high branching density of dendritiform fibers and the fact that synapses are polyadic, neurites are highly interconnected even within small neuropile volumes. We describe the network motifs most frequently encountered in the Drosophila neuropile. Our study introduces an approach towards a comprehensive anatomical reconstruction of neuronal microcircuitry and delivers microcircuitry comparisons between vertebrate and insect neuropile.