Tracking all nuclei of an embryo in noisy and dense fluorescence microscopy data is a challenging task. We build upon a recent method for nuclei tracking that combines weakly-supervised learning from a small set of nuclei center point annotations with an integer linear program (ILP) for optimal cell lineage extraction. Our work specifically addresses the following challenging properties of C. elegans embryo recordings: (1) Many cell divisions as compared to benchmark recordings of other organisms, and (2) the presence of polar bodies that are easily mistaken as cell nuclei. To cope with (1), we devise and incorporate a learnt cell division detector. To cope with (2), we employ a learnt polar body detector. We further propose automated ILP weights tuning via a structured SVM, alleviating the need for tedious manual set-up of a respective grid search.

Summary HYlight is a genetically encoded fluorescent biosensor that ratiometrically monitors fructose 1,6-bisphosphate (FBP), a key glycolytic metabolite. Given the role of glucose in liver cancer metabolism, we expressed HYlight in human liver cancer cells and primary mouse hepatocytes. Through in vitro, in silico, and in cellulo experiments, we showed HYlight’s ability to monitor FBP changes linked to glycolysis, not gluconeogenesis. HYlight’s affinity for FBP was ∼1 μM and stable within physiological pH range. HYlight demonstrated weak binding to dihydroxyacetone phosphate, and its ratiometric response was influenced by both ionic strength and phosphate. Therefore, simulating cytosolic conditions in vitro was necessary to establish a reliable correlation between HYlight’s cellular responses and FBP concentrations. FBP concentrations were found to be in the lower micromolar range, far lower than previous millimolar estimates. Altogether, this biosensor approach offers real-time monitoring of FBP concentrations at single-cell resolution, making it an invaluable tool for the understanding of cancer metabolism.

We are interested in establishing the correspondence between neuron activity and body curvature during various movements of C. Elegans worms. Given long sequences of images, specifically recorded to glow when the neuron is active, it is required to track all identifiable neurons in each frame. The characteristics of the neuron data, e.g., the uninformative nature of neuron appearance and the sequential ordering of neurons, renders standard single and multi-object tracking methods either ineffective or unnecessary for our task. In this paper, we propose a multi-target tracking algorithm that correctly assigns each neuron to one of several candidate locations in the next frame preserving shape constraint. The results demonstrate how the proposed method can robustly track more neurons than several existing methods in long sequences of images.

Using a combination of metabolically labeled glycans, a bioorthogonal copper(I)-catalyzed azide-alkyne cycloaddition, and the controlled bleaching of fluorescent probes conjugated to azide- or alkyne-tagged glycans, a sufficiently low spatial density of dye-labeled glycans was achieved, enabling dynamic single-molecule tracking and super-resolution imaging of N-linked sialic acids and O-linked N-acetyl galactosamine (GalNAc) on the membrane of live cells. Analysis of the trajectories of these dye-labeled glycans in mammary cancer cells revealed constrained diffusion of both N- and O-linked glycans, which was interpreted as reflecting the mobility of the glycan rather than to be caused by transient immobilization owing to spatial inhomogeneities on the plasma membrane. Stochastic optical reconstruction microscopy (STORM) imaging revealed the structure of dynamic membrane nanotubes.

Summary: State-of-the-art light and electron microscopes are capable of acquiring large image datasets, but quantitatively evaluating the data often involves manually annotating structures of interest. This processis time-consuming and often a major bottleneck in the evaluation pipeline. To overcome this problem, we have introduced the Trainable Weka Segmentation (TWS), a machine learning tool that leveragesa limited number of manual annotations in order to train a classifier and segment the remaining dataautomatically. In addition, TWS can provide unsupervised segmentation learning schemes (clustering) and can be customized to employ user-designed image features or classifiers.

Availability and Implementation: TWS is distributed as open-source software as part of the Fiji image processing distribution of ImageJ at http://imagej.net/Trainable_Weka_Segmentation.

Contact: ignacio.arganda@ehu.eus.

Supplementary information: Supplementary data are available at Bioinformatics online.

Interleukin 15 (IL-15) is an essential cytokine for the survival and proliferation of natural killer (NK) cells. IL-15 activates signaling by the β and common γ (γ) chain heterodimer of the IL-2 receptor through -presentation by cells expressing IL-15 bound to the α chain of the IL-15 receptor (IL-15Rα). We show here that membrane-associated IL-15Rα-IL-15 complexes are transferred from presenting cells to NK cells through -endocytosis and contribute to the phosphorylation of ribosomal protein S6 and NK cell proliferation. NK cell interaction with soluble or surface-bound IL-15Rα-IL-15 complex resulted in Stat5 phosphorylation and NK cell survival at a concentration or density of the complex much lower than required to stimulate S6 phosphorylation. Despite this efficient response, Stat5 phosphorylation was reduced after inhibition of metalloprotease-induced IL-15Rα-IL-15 shedding from -presenting cells, whereas S6 phosphorylation was unaffected. Conversely, inhibition of -endocytosis by silencing of the small GTPase TC21 or expression of a dominant-negative TC21 reduced S6 phosphorylation but not Stat5 phosphorylation. Thus, -endocytosis of membrane-associated IL-15Rα-IL-15 provides a mode of regulating NK cells that is not afforded to IL-2 and is distinct from activation by soluble IL-15. These results may explain the strict IL-15 dependence of NK cells and illustrate how the cellular compartment in which receptor-ligand interaction occurs can influence functional outcome.

Transcription is a stochastic process occurring mostly in episodic bursts. Although the local chromatin environment is known to influence the bursting behavior on long timescales, the impact of transcription factors (TFs)-especially in rapidly inducible systems-is largely unknown. Using fluorescence in situ hybridization and computational models, we quantified the transcriptional activity of the proto-oncogene c-Fos with single mRNA accuracy at individual endogenous alleles. We showed that, during MAPK induction, the TF concentration modulates the burst frequency of c-Fos, whereas other bursting parameters remain mostly unchanged. By using synthetic TFs with TALE DNA-binding domains, we systematically altered different aspects of these bursts. Specifically, we linked the polymerase initiation frequency to the strength of the transactivation domain and the burst duration to the TF lifetime on the promoter. Our results show how TFs and promoter binding domains collectively act to regulate different bursting parameters, offering a vast, evolutionarily tunable regulatory range for individual genes.

Transcription factors that can convert adult cells of one type to another are usually discovered empirically by testing factors with a known developmental role in the target cell. Here we show that standard genomic methods (RNA-seq and ChIP-seq) can help identify these factors, as most are more strongly Polycomb repressed in the source cell and more highly expressed in the target cell. This criterion is an effective genome-wide screen that significantly enriches for factors that can transdifferentiate several mammalian cell types including neural stem cells, neurons, pancreatic islets, and hepatocytes. These results suggest that barriers between adult cell types, as depicted in Waddington’s "epigenetic landscape", consist in part of differentially Polycomb-repressed transcription factors. This genomic model of cell identity helps rationalize a growing number of transdifferentiation protocols and may help facilitate the engineering of cell identity for regenerative medicine.

Forty years of classical biochemical analysis have identified the molecular players involved in initiation of transcription by eukaryotic RNA polymerase II (Pol II) and largely assigned their functions. However, a dynamic picture of Pol II transcription initiation and an understanding of the mechanisms of its regulation have remained elusive due in part to inherent limitations of conventional ensemble biochemistry. Here we have begun to dissect promoter-specific transcription initiation directed by a reconstituted human Pol II system at single-molecule resolution using fluorescence video-microscopy. We detected several stochastic rounds of human Pol II transcription from individual DNA templates, observed attenuation of transcription by promoter mutations, observed enhancement of transcription by activator Sp1, and correlated the transcription signals with real-time interactions of holo-TFIID molecules at individual DNA templates. This integrated single-molecule methodology should be applicable to studying other complex biological processes.

Long-term memory depends on the control of activity-dependent neuronal gene expression, which is regulated by epigenetic modifications. The epigenetic modification of histones is orchestrated by the opposing activities of two classes of regulatory complexes: permissive co-activators and silencing co-repressors. Much work has focused on co-activator complexes, but little is known about the co-repressor complexes that suppress the expression of plasticity-related genes. Here, we define a critical role for the co-repressor SIN3A in memory and synaptic plasticity, showing that postnatal neuronal deletion of Sin3a enhances hippocampal long-term potentiation and long-term contextual fear memory. SIN3A regulates the expression of genes encoding proteins in the post-synaptic density. Loss of SIN3A increases expression of the synaptic scaffold Homer1, alters the mGluR1α- and mGluR5-dependence of long-term potentiation, and increases activation of extracellular signal regulated kinase (ERK) in the hippocampus after learning. Our studies define a critical role for co-repressors in modulating neural plasticity and memory consolidation and reveal that Homer1/mGluR signaling pathways may be central molecular mechanisms for memory enhancement.