Superresolution Microscopy of Drosophila Indirect Flight Muscle Sarcomeres

Aligning with the 3Rs: alternative models for research into muscle development and inherited myopathies

Inherited and acquired muscle diseases are an important cause of morbidity and mortality in human medical and veterinary patients. Researchers use models to study skeletal muscle development and pathology, improve our understanding of disease pathogenesis and explore new treatment options. Experiments on laboratory animals, including murine and canine models, have led to huge advances in congenital myopathy and muscular dystrophy research that have translated into clinical treatment trials in human patients with these debilitating and often fatal conditions. Whilst animal experimentation has enabled many significant and impactful discoveries that otherwise may not have been possible, we have an ethical and moral, and in many countries also a legal, obligation to consider alternatives. This review discusses the models available as alternatives to mammals for muscle development, biology and disease research with a focus on inherited myopathies. Cell culture models can be used to replace animals for some applications: traditional monolayer cultures (for example, using the immortalised C2C12 cell line) are accessible, tractable and inexpensive but developmentally limited to immature myotube stages; more recently, developments in tissue engineering have led to three-dimensional cultures with improved differentiation capabilities. Advances in computer modelling and an improved understanding of pathogenetic mechanisms are likely to herald new models and opportunities for replacement. Where this is not possible, a 3Rs approach advocates partial replacement with the use of less sentient animals (including invertebrates (such as worms Caenorhabditis elegans and fruit flies Drosophila melanogaster) and embryonic stages of small vertebrates such as the zebrafish Danio rerio) alongside refinement of experimental design and improved research practices to reduce the numbers of animals used and the severity of their experience. An understanding of the advantages and disadvantages of potential models is essential for researchers to determine which can best facilitate answering a specific scientific question. Applying 3Rs principles to research not only improves animal welfare but generates high-quality, reproducible and reliable data with translational relevance to human and animal patients.

Triggered cagedSTORM microscopy

In standard SMLM methods, the photoswitching of single fluorescent molecules and the data acquisition processes are independent, which leads to the detection of single molecule blinking events on several consecutive frames. This mismatch results in several data points with reduced localization precision, and it also increases the possibilities of overlapping. Here we discuss how the synchronization of the fluorophores' ON state to the camera exposure time increases the average intensity of the captured point spread functions and hence improves the localization precision. Simulations and theoretical results show that such synchronization leads to fewer localizations with 15% higher sum signal on average, while reducing the probability of overlaps by 10%.

Peripheral thickening of the sarcomeres and pointed end elongation of the thin filaments are both promoted by SALS and its formin interaction partners

During striated muscle development the first periodically repeated units appear in the premyofibrils, consisting of immature sarcomeres that must undergo a substantial growth both in length and width, to reach their final size. Here we report that, beyond its well established role in sarcomere elongation, the Sarcomere length short (SALS) protein is involved in Z-disc formation and peripheral growth of the sarcomeres. Our protein localization data and loss-of-function studies in the Drosophila indirect flight muscle strongly suggest that radial growth of the sarcomeres is initiated at the Z-disc. As to thin filament elongation, we used a powerful nanoscopy approach to reveal that SALS is subject to a major conformational change during sarcomere development, which might be critical to stop pointed end elongation in the adult muscles. In addition, we demonstrate that the roles of SALS in sarcomere elongation and radial growth are both dependent on formin type of actin assembly factors. Unexpectedly, when SALS is present in excess amounts, it promotes the formation of actin aggregates highly resembling the ones described in nemaline myopathy patients. Collectively, these findings helped to shed light on the complex mechanisms of SALS during the coordinated elongation and thickening of the sarcomeres, and resulted in the discovery of a potential nemaline myopathy model, suitable for the identification of genetic and small molecule inhibitors.

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.

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.