Comparison of two 3D tracking paradigms for freely flying insects

In this paper, we discuss and compare state-of-the-art 3D tracking paradigms for flying insects such as Drosophila melanogaster. If two cameras are employed to estimate the trajectories of these identical appearing objects, calculating stereo and temporal correspondences leads to an NP-hard assignment problem. Currently, there are two different types of approaches discussed in the literature: probabilistic approaches and global correspondence selection approaches. Both have advantages and limitations in terms of accuracy and complexity. Here, we present algorithms for both paradigms. The probabilistic approach utilizes the Kalman filter for temporal tracking. The correspondence selection approach calculates the trajectories based on an overall cost function. Limitations of both approaches are addressed by integrating a third camera to verify consistency of the stereo pairings and to reduce the complexity of the global selection. Furthermore, a novel greedy optimization scheme is introduced for the correspondence selection approach. We compare both paradigms based on synthetic data with ground truth availability. Results show that the global selection is more accurate, while the previously proposed tracking-by-matching (probabilistic) approach is causal and feasible for longer tracking periods and very high target densities. We further demonstrate that our extended global selection scheme outperforms current correspondence selection approaches in tracking accuracy and tracking time

The curious case of NG2 cells: transient trend or game changer?

It has been 10 years since the seminal work of Dwight Bergles and collaborators demonstrated that NG2 (nerve/glial antigen 2)-expressing oligodendrocyte progenitor cells (NG2 cells) receive functional glutamatergic synapses from neurons (Bergles et al., 2000), contradicting the old dogma that only neurons possess the complex and specialized molecular machinery necessary to receive synapses. While this surprising discovery may have been initially shunned as a novelty item of undefined functional significance, the study of neuron-to-NG2 cell neurotransmission has since become a very active and exciting field of research. Many laboratories have now confirmed and extended the initial discovery, showing for example that NG2 cells can also receive inhibitory GABAergic synapses (Lin and Bergles, 2004) or that neuron-to-NG2 cell synaptic transmission is a rather ubiquitous phenomenon that has been observed in all brain areas explored so far, including white matter tracts (Kukley et al., 2007; Ziskin et al., 2007; Etxeberria et al., 2010). Thus, while still being in its infancy, this field of research has already brought many surprising and interesting discoveries, and has become part of a continuously growing effort in neuroscience to re-evaluate the long underestimated role of glial cells in brain function (Barres, 2008). However, this area of research is now reaching an important milestone and its long-term significance will be defined by its ability to uncover the still elusive function of NG2 cells and their synapses in the brain, rather than by its sensational but transient successes at upsetting the old order established by neuronal physiology. To participate in the effort to facilitate such a transition, here we propose a critical review of the latest findings in the field of NG2 cell physiology – discussing how they inform us on the possible function(s) of NG2 cells in the brain – and we present some personal views on new directions the field could benefit from in order to achieve lasting significance

Comparative analysis of somitogenesis related genes of the hairy/Enhancer of split class in Fugu and zebrafish

BACKGROUND: Members of a class of bHLH transcription factors, namely the hairy (h), Enhancer of split (E(spl)) and hairy-related with YRPW motif (hey) (h/E(spl)/hey) genes are involved in vertebrate somitogenesis and some of them show cycling expression. By sequence comparison, identified orthologues of cycling somitogenesis genes from higher vertebrates do not show an appropriate expression pattern in zebrafish. The zebrafish genomic sequence is not available yet but the genome of Fugu rubripes was recently published. To allow comparative analysis, the currently known Her proteins from zebrafish were used to screen the genomic sequence database of Fugu rubripes. RESULTS: 20 h/E(spl)/hey-related genes were identified in Fugu, which is twice the number of corresponding zebrafish genes known so far. A novel class of c-Hairy proteins was identified in the genomes of Fugu and Tetraodon. A screen of the human genome database with the Fugu proteins yielded 10 h/E(spl)/hey-related genes. By analysing the upstream sequences of the c-hairy class genes in zebrafish, Fugu and Tetraodon highly similar sequence stretches were identified that harbour Suppressor of hairless paired binding sites (SPS). This motif was also discovered in the upstream sequences of the her1 gene in the examined fish species. Here, the Su(h) sites are separated by longer intervening sequences. CONCLUSIONS: Our study indicates that not all her homologues in zebrafish have been isolated. Comparison to the human genome suggests a selective duplication of h/E(spl) genes in pufferfish or loss of members of these genes during evolution to the human lineage

A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns