Quantitative microscopy uncovers ploidy changes during mitosis in live Drosophila embryos and their effect on nuclear size.

Time-lapse microscopy is a powerful tool to investigate cellular and developmental dynamics. In Drosophila melanogaster, it can be used to study division cycles in embryogenesis. To obtain quantitative information from 3D time-lapse data and track proliferating nuclei from the syncytial stage until gastrulation, we developed an image analysis pipeline consisting of nuclear segmentation, tracking, annotation and quantification. Image analysis of maternal-haploid (mh) embryos revealed that a fraction of haploid syncytial nuclei fused to give rise to nuclei of higher ploidy (2n, 3n, 4n). Moreover, nuclear densities in mh embryos at the mid-blastula transition varied over threefold. By tracking synchronized nuclei of different karyotypes side-by-side, we show that DNA content determines nuclear growth rate and size in early interphase, while the nuclear to cytoplasmic ratio constrains nuclear growth during late interphase. mh encodes the Drosophila ortholog of human Spartan, a protein involved in DNA damage tolerance. To explore the link between mh and chromosome instability, we fluorescently tagged Mh protein to study its subcellular localization. We show Mh-mKO2 localizes to nuclear speckles that increase in numbers as nuclei expand in interphase. In summary, quantitative microscopy can provide new insights into well-studied genes and biological processes.

Live imaging of muscle histolysis in Drosophila metamorphosis.

BACKGROUND: The contribution of programmed cell death (PCD) to muscle wasting disorders remains a matter of debate. Drosophila melanogaster metamorphosis offers the opportunity to study muscle cell death in the context of development. Using live cell imaging of the abdomen, two groups of larval muscles can be observed, doomed muscles that undergo histolysis and persistent muscles that are remodelled and survive into adulthood. METHOD: To identify and characterize genes that control the decision between survival and cell death of muscles, we developed a method comprising in vivo imaging, targeted gene perturbation and time-lapse image analysis. Our approach enabled us to study the cytological and temporal aspects of abnormal cell death phenotypes. RESULTS: In a previous genetic screen for genes controlling muscle size and cell death in metamorphosis, we identified gene perturbations that induced cell death of persistent or inhibit histolysis of doomed larval muscles. RNA interference (RNAi) of the genes encoding the helicase Rm62 and the lysosomal Cathepsin-L homolog Cysteine proteinase 1 (Cp1) caused premature cell death of persistent muscle in early and mid-pupation, respectively. Silencing of the transcriptional co-repressor Atrophin inhibited histolysis of doomed muscles. Overexpression of dominant-negative Target of Rapamycin (TOR) delayed the histolysis of a subset of doomed and induced ablation of all persistent muscles. RNAi of AMPKα, which encodes a subunit of the AMPK protein complex that senses AMP and promotes ATP formation, led to loss of attachment and a spherical morphology. None of the perturbations affected the survival of newly formed adult muscles, suggesting that the method is useful to find genes that are crucial for the survival of metabolically challenged muscles, like those undergoing atrophy. The ablation of persistent muscles did not affect eclosion of adult flies. CONCLUSIONS: Live imaging is a versatile approach to uncover gene functions that are required for the survival of muscle undergoing remodelling, yet are dispensable for other adult muscles. Our approach promises to identify molecular mechanisms that can explain the resilience of muscles to PCD.

A model of muscle atrophy based on live microscopy of muscle remodelling in Drosophila metamorphosis.

Genes controlling muscle size and survival play important roles in muscle wasting diseases. In Drosophila melanogaster metamorphosis, larval abdominal muscles undergo two developmental fates. While a doomed population is eliminated by cell death, another persistent group is remodelled and survives into adulthood. To identify and characterize genes involved in the development of remodelled muscles, we devised a workflow consisting of in vivo imaging, targeted gene perturbation and quantitative image analysis. We show that inhibition of TOR signalling and activation of autophagy promote developmental muscle atrophy in early, while TOR and yorkie activation are required for muscle growth in late pupation. We discovered changes in the localization of myonuclei during remodelling that involve anti-polar migration leading to central clustering followed by polar migration resulting in localization along the midline. We demonstrate that the Cathepsin L orthologue Cp1 is required for myonuclear clustering in mid, while autophagy contributes to central positioning of nuclei in late metamorphosis. In conclusion, studying muscle remodelling in metamorphosis can provide new insights into the cell biology of muscle wasting.

Live imaging of muscles in Drosophila metamorphosis: Towards high-throughput gene identification and function analysis.

Time-lapse microscopy in developmental biology is an emerging tool for functional genomics. Phenotypic effects of gene perturbations can be studied non-invasively at multiple time points in chronological order. During metamorphosis of Drosophila melanogaster, time-lapse microscopy using fluorescent reporters allows visualization of alternative fates of larval muscles, which are a model for the study of genes related to muscle wasting. While doomed muscles enter hormone-induced programmed cell death, a smaller population of persistent muscles survives to adulthood and undergoes morphological remodeling that involves atrophy in early, and hypertrophy in late pupation. We developed a method that combines in vivo imaging, targeted gene perturbation and image analysis to identify and characterize genes involved in muscle development. Macrozoom microscopy helps to screen for interesting muscle phenotypes, while confocal microscopy in multiple locations over 4-5 days produces time-lapse images that are used to quantify changes in cell morphology. Performing a similar investigation using fixed pupal tissues would be too time-consuming and therefore impractical. We describe three applications of our pipeline. First, we show how quantitative microscopy can track and measure morphological changes of muscle throughout metamorphosis and analyze genes involved in atrophy. Second, our assay can help to identify genes that either promote or prevent histolysis of abdominal muscles. Third, we apply our approach to test new fluorescent proteins as live markers for muscle development. We describe mKO2 tagged Cysteine proteinase 1 (Cp1) and Troponin-I (TnI) as examples of proteins showing developmental changes in subcellular localization. Finally, we discuss strategies to improve throughput of our pipeline to permit genome-wide screens in the future.

Oral Administration and Selective Uptake of Polymeric Nanoparticles in Drosophila Larvae as an in Vivo Model.

In this article, Drosophila larvae are applied as an in vivo model to investigate the transport and uptake of polymeric nanoparticles in the larval digestive tract after oral administration. After feeding the larvae with food containing bare and chitosan-coated Poly(d,l-lactic-co-glycolic acid) (PLGA) nanoparticles encapsulated with BODIPY, time-lapse imaging of live larvae is used to monitor the movement of fluorescent nanoparticles in the anterior, middle, and posterior midgut of the digestive tract. Also, the dissection of the digestive tract enables the analysis of cellular uptake in the midgut. Bare PLGA nanoparticles travel through the whole midgut smoothly while chitosan-coated PLGA nanoparticles have a long retention time in the posterior midgut. We identify that this retention occurs in the posterior segment of the posterior midgut, and it is termed as the retention segment. During transport in the midgut, chitosan-coated nanoparticles pass through the near-neutral anterior midgut and become highly positively charged when entering into the highly acidic middle midgut. After traveling through the near-neutral anterior segment of the posterior midgut, chitosan-coated nanoparticles have a long retention time of ∼10 h in the retention segment, indicating that the chitosan coating greatly enhances mucoadhesive ability and promotes cellular uptake in this part of the midgut. The dynamic behavior of orally administered nanoparticles in Drosophila larvae is in agreement with studies in other animal models. A Drosophila larva has the potential to evolve into a low-cost drug screening model through real time imaging, which will accelerate the development of improved nanoparticle formulations for oral drug delivery.

FMAj: a tool for high content analysis of muscle dynamics in Drosophila metamorphosis.

BACKGROUND: During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates; one population is removed by cell death, while the other persistent subset undergoes morphological remodeling and survives to adulthood. Thanks to the ability to perform live imaging of muscle development in transparent pupae and the power of genetics, metamorphosis in Drosophila can be used as a model to study the regulation of skeletal muscle mass. However, time-lapse microscopy generates sizeable image data that require new tools for high throughput image analysis. RESULTS: We performed targeted gene perturbation in muscles and acquired 3D time-series images of muscles in metamorphosis using laser scanning confocal microscopy. To quantify the phenotypic effects of gene perturbations, we designed the Fly Muscle Analysis tool (FMAj) which is based on the ImageJ and MySQL frameworks for image processing and data storage, respectively. The image analysis pipeline of FMAj contains three modules. The first module assists in adding annotations to time-lapse datasets, such as genotypes, experimental parameters and temporal reference points, which are used to compare different datasets. The second module performs segmentation and feature extraction of muscle cells and nuclei. Users can provide annotations to the detected objects, such as muscle identities and anatomical information. The third module performs comparative quantitative analysis of muscle phenotypes. We applied our tool to the phenotypic characterization of two atrophy related genes that were silenced by RNA interference. Reduction of Drosophila Tor (Target of Rapamycin) expression resulted in enhanced atrophy compared to control, while inhibition of the autophagy factor Atg9 caused suppression of atrophy and enlarged muscle fibers of abnormal morphology. FMAj enabled us to monitor the progression of atrophic and hypertrophic phenotypes of individual muscles throughout metamorphosis. CONCLUSIONS: We designed a new tool to visualize and quantify morphological changes of muscles in time-lapse images of Drosophila metamorphosis. Our in vivo imaging experiments revealed that evolutionarily conserved genes involved in Tor signalling and autophagy, perform similar functions in regulating muscle mass in mammals and Drosophila. Extending our approach to a genome-wide scale has the potential to identify new genes involved in muscle size regulation.

TLM-Converter: reorganization of long time-lapse microscopy datasets for downstream image analysis.

Automated microscopy enables in vivo studies in developmental biology over long periods of time. Time-lapse recordings in three or more dimensions to study the dynamics of developmental processes can produce huge data sets that extend into the terabyte range. However, depending on the available computational resources and software design, downstream processing of very large image data sets can become highly inefficient, if not impossible. To address the lack of available open source and commercial software tools to efficiently reorganize time-lapse data on a desktop computer with limited system resources, we developed TLM-Converter. The software either fragments oversized files or concatenates multiple files representing single time frames and saves the output files in open standard formats. Our application is undemanding on system resources as it does not require the whole data set to be loaded into the system memory. We tested our tool on time-lapse data sets of live Drosophila specimens recorded by laser scanning confocal microscopy. Image data reorganization dramatically enhances the productivity of time-lapse data processing and allows the use of downstream image analysis software that is unable to handle large data sets of ≥2 GB. In addition, saving the outputs in open standard image file formats enables data sharing between independently developed software tools.

Cell cycle phase classification in 3D in vivo microscopy of Drosophila embryogenesis.

BACKGROUND: Cell divisions play critical roles in disease and development. The analysis of cell division phenotypes in high content image-based screening and time-lapse microscopy relies on automated nuclear segmentation and classification of cell cycle phases. Automated identification of the cell cycle phase helps biologists quantify the effect of genetic perturbations and drug treatments. Most existing studies have dealt with 2D images of cultured cells. Few, if any, studies have addressed the problem of cell cycle classification in 3D image stacks of intact tissues. RESULTS: We developed a workflow for the automated cell cycle phase classification in 3D time-series image datasets of live Drosophila embryos expressing the chromatin marker histone-GFP. Upon image acquisition by laser scanning confocal microscopy and 3D nuclear segmentation, we extracted 3D intensity, shape and texture features from interphase nuclei and mitotic chromosomes. We trained different classifiers, including support vector machines (SVM) and neural networks, to distinguish between 5 cell cycles phases (Interphase and 4 mitotic phases) and achieved over 90% accuracy. As the different phases occur at different frequencies (58% of samples correspond to interphase), we devised a strategy to improve the identification of classes with low representation. To investigate which features are required for accurate classification, we performed feature reduction and selection. We were able to reduce the feature set from 42 to 9 without affecting classifier performance. We observed a dramatic decrease of classification performance when the training and testing samples were derived from two different developmental stages, the nuclear divisions of the syncytial blastoderm and the cell divisions during gastrulation. Combining samples from both developmental stages produced a more robust and accurate classifier. CONCLUSIONS: Our study demonstrates that automated cell cycle phase classification, besides 2D images of cultured cells, can also be applied to 3D images of live tissues. We could reduce the initial 3D feature set from 42 to 9 without compromising performance. Robust classifiers of intact animals need to be trained with samples from different developmental stages and cell types. Cell cycle classification in live animals can be used for automated phenotyping and to improve the performance of automated cell tracking.