Drosophila Models Rediscovered with Super-Resolution Microscopy

With the advent of super-resolution microscopy, we gained a powerful toolbox to bridge the gap between the cellular- and molecular-level analysis of living organisms. Although nanoscopy is broadly applicable, classical model organisms, such as fruit flies, worms and mice, remained the leading subjects because combining the strength of sophisticated genetics, biochemistry and electrophysiology with the unparalleled resolution provided by super-resolution imaging appears as one of the most efficient approaches to understanding the basic cell biological questions and the molecular complexity of life. Here, we summarize the major nanoscopic techniques and illustrate how these approaches were used in Drosophila model systems to revisit a series of well-known cell biological phenomena. These investigations clearly demonstrate that instead of simply achieving an improvement in image quality, nanoscopy goes far beyond with its immense potential to discover novel structural and mechanistic aspects. With the examples of synaptic active zones, centrosomes and sarcomeres, we will explain the instrumental role of super-resolution imaging pioneered in Drosophila in understanding fundamental subcellular constituents

Machine learning framework to segment sarcomeric structures in SMLM data

Object detection is an image analysis task with a wide range of applications, which is difficult to accomplish with traditional programming. Recent breakthroughs in machine learning have made significant progress in this area. However, these algorithms are generally compatible with traditional pixelated images and cannot be directly applied for pointillist datasets generated by single molecule localization microscopy (SMLM) methods. Here, we have improved the averaging method developed for the analysis of SMLM images of sarcomere structures based on a machine learning object detection algorithm. The ordered structure of sarcomeres allows us to determine the location of the proteins more accurately by superimposing SMLM images of identically assembled proteins. However, the area segmentation process required for averaging can be extremely time-consuming and tedious. In this work, we have automated this process. The developed algorithm not only finds the regions of interest, but also classifies the localizations and identifies the true positive ones. For training, we used simulations to generate large amounts of labelled data. After tuning the neural network’s internal parameters, it could find the localizations associated with the structures we were looking for with high accuracy. We validated our results by comparing them with previous manual evaluations. It has also been proven that the simulations can generate data of sufficient quality for training. Our method is suitable for the identification of other types of structures in SMLM data

Quantitative dSTORM superresolution microscopy

Localization based superresolution technique provides the highest spatial resolution in optical microscopy. The final image is formed by the precise localization of individual fluorescent dyes, therefore the quantification of the collected data requires special protocols, algorithms and validation processes. The effects of labelling density and structured background on the final image quality were studied theoretically using the TestSTORM simulator. It was shown that system parameters affect the morphology of the final reconstructed image in different ways and the accuracy of the imaging can be determined. Although theoretical studies help in the optimization procedure, the quantification of experimental data raises additional issues, since the ground truth data is unknown. Localization precision, linker length, sample drift and labelling density are the major factors that make quantitative data analysis difficult. Two examples (geometrical evaluation of sarcomere structures and counting the γH2AX molecules in DNA damage induced repair foci) have been presented to demonstrate the efficiency of quantitative evaluation experimentally

The oxoglutarate dehydrogenase complex is involved in myofibril growth and Z-disc assembly in Drosophila

Myofibrils are long intracellular cables specific to muscles, composed mainly of actin and myosin filaments. The actin and myosin filaments are organized into repeated units called sarcomeres, which form the myofibrils. Muscle contraction is achieved by the simultaneous shortening of sarcomeres, which requires all sarcomeres to be the same size. Muscles have a variety of ways to ensure sarcomere homogeneity. We have previously shown that the controlled oligomerization of Zasp proteins sets the diameter of the myofibril. Here, we looked for Zasp-binding proteins at the Z-disc to identify additional proteins coordinating myofibril growth and assembly. We found that the E1 subunit of the oxoglutarate dehydrogenase complex localizes to both the Z-disc and the mitochondria, and is recruited to the Z-disc by Zasp52. The three subunits of the oxoglutarate dehydrogenase complex are required for myofibril formation. Using super-resolution microscopy, we revealed the overall organization of the complex at the Z-disc. Metabolomics identified an amino acid imbalance affecting protein synthesis as a possible cause of myofibril defects, which is supported by OGDH-dependent localization of ribosomes at the Z-disc

Machine learning framework to segment sarcomeric structures in SMLM data

Object detection is an image analysis task with a wide range of applications, which is difficult to accomplish with traditional programming. Recent breakthroughs in machine learning have made significant progress in this area. However, these algorithms are generally compatible with traditional pixelated images and cannot be directly applied for pointillist datasets generated by single molecule localization microscopy (SMLM) methods. Here, we have improved the averaging method developed for the analysis of SMLM images of sarcomere structures based on a machine learning object detection algorithm. The ordered structure of sarcomeres allows us to determine the location of the proteins more accurately by superimposing SMLM images of identically assembled proteins. However, the area segmentation process required for averaging can be extremely time-consuming and tedious. In this work, we have automated this process. The developed algorithm not only finds the regions of interest, but also classifies the localizations and identifies the true positive ones. For training, we used simulations to generate large amounts of labelled data. After tuning the neural network’s internal parameters, it could find the localizations associated with the structures we were looking for with high accuracy. We validated our results by comparing them with previous manual evaluations. It has also been proven that the simulations can generate data of sufficient quality for training. Our method is suitable for the identification of other types of structures in SMLM data

mmSTORM: Multimodal localization based super-resolution microscopy

Super-resolution localization microscopy provides a powerful tool to study biochemical mechanisms at single molecule level. Although the lateral position of the fluorescent dye molecules can be determined routinely with high precision, measurement of other modalities such as 3D and multicolor without the degradation of the original super-resolved image is still in the focus. In this paper a dual-objective multimodal single molecule localization microscopy (SMLM) technique has been developed, optimized and tested. The proposed optical arrangement can be implemented onto a conventional inverted microscope without serious system modification. The performance of the method was tested using fluorescence beads, F-actin filaments and sarcomere structures. It was shown that the proposed imaging method does not degrade the image quality of the original SMLM 2D image but could provide information on the axial position or emission spectra of the dye molecules

The oxoglutarate dehydrogenase complex is involved in myofibril growth and Z-disc assembly in Drosophila

Myofibrils are long intracellular cables specific to muscles, composed mainly of actin and myosin filaments. The actin and myosin filaments are organized into repeated units called sarcomeres, which form the myofibrils. Muscle contraction is achieved by the simultaneous shortening of sarcomeres, which requires all sarcomeres to be the same size. Muscles have a variety of ways to ensure sarcomere homogeneity. We have previously shown that the controlled oligomerization of Zasp proteins sets the diameter of the myofibril. Here, we looked for Zasp-binding proteins at the Z-disc to identify additional proteins coordinating myofibril growth and assembly. We found that the E1 subunit of the oxoglutarate dehydrogenase complex localizes to both the Z-disc and the mitochondria, and is recruited to the Z-disc by Zasp52. The three subunits of the oxoglutarate dehydrogenase complex are required for myofibril formation. Using super-resolution microscopy, we revealed the overall organization of the complex at the Z-disc. Metabolomics identified an amino acid imbalance affecting protein synthesis as a possible cause of myofibril defects, which is supported by OGDH-dependent localization of ribosomes at the Z-disc

DAAM is required for thin filament formation and Sarcomerogenesis during muscle development in Drosophila.

During muscle development, myosin and actin containing filaments assemble into the highly organized sarcomeric structure critical for muscle function. Although sarcomerogenesis clearly involves the de novo formation of actin filaments, this process remained poorly understood. Here we show that mouse and Drosophila members of the DAAM formin family are sarcomere-associated actin assembly factors enriched at the Z-disc and M-band. Analysis of dDAAM mutants revealed a pivotal role in myofibrillogenesis of larval somatic muscles, indirect flight muscles and the heart. We found that loss of dDAAM function results in multiple defects in sarcomere development including thin and thick filament disorganization, Z-disc and M-band formation, and a near complete absence of the myofibrillar lattice. Collectively, our data suggest that dDAAM is required for the initial assembly of thin filaments, and subsequently it promotes filament elongation by assembling short actin polymers that anneal to the pointed end of the growing filaments, and by antagonizing the capping protein Tropomodulin

Microtubule organization in presynaptic boutons relies on the formin DAAM

Regulation of the cytoskeleton is fundamental to the development and functioning of synaptic terminals, such as neuromuscular junctions. Nevertheless, despite identification of numerous proteins that regulate synaptic actin and microtubule dynamics, the mechanisms of cytoskeletal control during terminal arbor formation has remained largely elusive. Here, we show that DAAM, a member of the formin family of cytoskeleton organizing factors, is an important presynaptic regulator of neuromuscular junction development in Drosophila We demonstrate that the actin filament assembly activity of DAAM plays a negligible role in terminal formation; rather, DAAM is necessary for synaptic microtubule organization. Genetic interaction studies consistently link DAAM with the Wg/Ank2/Futsch module of microtubule regulation and bouton formation. Finally, we provide evidence that DAAM is tightly associated with the synaptic active zone scaffold, and electrophysiological data point to a role in the modulation of synaptic vesicle release. Based on these results, we propose that DAAM is an important cytoskeletal effector element of the Wg/Ank2 pathway involved in the determination of basic synaptic structures, and, additionally, DAAM may couple the active zone scaffold to the presynaptic cytoskeleton

DAAM is required for thin filament formation and Sarcomerogenesis during muscle development in Drosophila.

During muscle development, myosin and actin containing filaments assemble into the highly organized sarcomeric structure critical for muscle function. Although sarcomerogenesis clearly involves the de novo formation of actin filaments, this process remained poorly understood. Here we show that mouse and Drosophila members of the DAAM formin family are sarcomere-associated actin assembly factors enriched at the Z-disc and M-band. Analysis of dDAAM mutants revealed a pivotal role in myofibrillogenesis of larval somatic muscles, indirect flight muscles and the heart. We found that loss of dDAAM function results in multiple defects in sarcomere development including thin and thick filament disorganization, Z-disc and M-band formation, and a near complete absence of the myofibrillar lattice. Collectively, our data suggest that dDAAM is required for the initial assembly of thin filaments, and subsequently it promotes filament elongation by assembling short actin polymers that anneal to the pointed end of the growing filaments, and by antagonizing the capping protein Tropomodulin