Open-CSAM, a new tool for semi-automated analysis of myofiber cross-sectional area in regenerating adult skeletal muscle

Desgeorges, Thibaut; Liot, Sophie; Lyon, Solene; Bouvière, Jessica; Kemmel, Alix; Trignol, Aurélie; Rousseau, D.; Chapuis, Bruno; Gondin, Julien; Mounier, Rémi; Chazaud, Bénédicte; Juban, Gaëtan

doi:10.1186/s13395-018-0186-6

Cited by 59 publications

(61 citation statements)

References 11 publications

(14 reference statements)

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“…As reported by the authors, although this method works well for detection of the majority of myofibers within a tissue section, it requires substantial manual supplementation (correction) to achieve high accuracy (that is, the user must individually draw ROIs for missed fibers or delete ROIs for misidentified non-fibers). Furthermore, this macro is not appropriate for fiber-type analysis [38]. The second macro, which is unnamed, is heavily dependent on achieving high signal:noise membrane counterstaining, which the authors propose to accomplish by using anti-spectrin and anti-dystrophin antibodies in tandem during their immunofluorescent processing.…”

Section: Discussionmentioning

confidence: 99%

Myosoft: An automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software

et al. 2020

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Skeletal muscle is comprised of a heterogeneous population of muscle fibers which can be classified by their metabolic and contractile properties (fiber "types"). Fiber type is a primary determinant of muscle function along with fiber size (cross-sectional area). The fiber type composition of a muscle responds to physiological changes like exercise and aging and is often altered in disease states. Thus, analysis of fiber size and type in histological muscle preparations is a useful method for quantifying key indicators of muscle function and for measuring responses to a variety of stimuli or stressors. These analyses are nearubiquitous in the fields of muscle physiology and myopathy, but are most commonly performed manually, which is highly labor-and time-intensive. To offset this obstacle, we developed Myosoft, a novel method to automate morphometric and fiber type analysis in muscle sections stained with fluorescent antibodies. MethodsMuscle sections were stained for cell boundary (laminin) and myofiber type (myosin heavy chain isoforms). Myosoft, running in the open access software platform FIJI (ImageJ), was used to analyze myofiber size and type in transverse sections of entire gastrocnemius/soleus muscles. ResultsMyosoft provides an accurate analysis of hundreds to thousands of muscle fibers within 25 minutes, which is >10-times faster than manual analysis. We demonstrate that Myosoft is capable of handling high-content images even when image or staining quality is suboptimal, which is a marked improvement over currently available and comparable programs.

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Section: Discussionmentioning

confidence: 99%

Myosoft: An automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software

et al. 2020

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“…It may be appropriate for good research on muscle to work with a number greater than 400 bres [10]. In the current study, this number is reached using x200 magni cation with at least two elds for each type of coloration.…”

Section: Image Acquisitionmentioning

confidence: 96%

“…However, researchers were unable to capture the entire surface of a stained section, which considered the whole area of a muscle, into a single image, as a consequence some of them were forced to perform several images with low magni cation. Garton et al [10] and Wen et al [8] were used respectively, objectives of x20 and x40 to cover the entire surface of the muscle in order to join them after, into a single complete image using Photoshop. Moreover, there is considerable regional variability in bre size in some muscles; therefore, measuring or sampling only a few small areas will not necessarily provide representative measures [4].…”

Section: Introductionmentioning

confidence: 99%

“…Similar to acquisition, segmentation of histological muscle image into distinct bres in order to calculate their morphometric parameters is di cult, and simple thresholding or morphology technics have a big di culty to separate precisely tightly a xed bres [4,10,24]. To overcome these limitations, researchers use universal semi-automatic methods for image processing of different types of tissue (Fiji [25], Image Pro Plus « Media Cybernetics », Metamorph « Universel Imaging Corporation »), and specialized ones for processing histoenzymological images of muscle tissue (Racine [26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

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Comparative Study of Histological and Histochemical Image Processing in Muscle Fibre Sections of Broiler Chicken

Achouri¹,

Marrakchi

Belbedj

et al. 2020

Preprint

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Image processing of muscular fibre has significantly improved over the last decades, from light microscopy acquisition to virtual microscopy and from manual segmentation and fibre typing to automatic. The study aims to discuss main tools used in different histoenzymological image processing ‎phases of muscle fibre, which are consecutively, acquisition, segmentation and fibre typing and theirs ‎efficacy in morphometric parameters’ determination. Firstly, the acquisition, optical microscopic image with different magnifications ‎‎(x100, x200, x250 and x400) were compared with virtual slides digitized by Slide Scanner, in ‎muscle fibre sections, for cell number counting. Secondly, the segmentation, three software ‎‎(Fiji «Digitizing pen, Mouse», Image Pro Plus 10 -semi-automatic- and Cytoinformatics LLC -automatic-) were compared ‎for image segmentation quality and fibbers number determination. Thirdly, manual fibre typing with Fiji of segmented images using three software cited previously were performed to calculate the accuracy of morphometric parameter (CSA, perimeter and DMF). Results of acquisition showed that scanner slide have ‎a better resolution and detected a higher number of cells compared to optical microscopic with ‎different magnifications. For this latter, the processing can be performed only with an ‎acceptable resolution, where the number of cells is lesser, which requires unfortunately several ‎repetitions and exhausting work. Our findings regarding segmentation indicate that ‎Cytoinformatics LLC showed the best processing time and the highest quality followed by IP ‎and Fiji. For the last step, morphometric parameter calculation showed the best accuracy using Fiji followed by Cytoinformatics and finally by IP. ‎ The findings of this study suggest that Fiji (semi-automatic) showed the best quality/price ratio (open access software) for segmentation and fibre typing, but time consuming compared to ‎ Image Pro Plus 10 (semi-automatic) and Cytoinformatics LLC‎ (automatic) which are a paid service.

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“…Morphological Quantitative Analysis of muscle fibers were performed with ImageJ software 1.52a (http://rsb.info.nih.gov/ij/) using images of H&E stained cross-sections. Briefly, Open-CSAM, an ImageJ macro supporting quantitative analysis of muscle fibers, was built in ImageJ according to a recently published work by Thibaut et al [42]. H&E images were converted to grayscale in 8 bit with Photoshop software (Adobe Inc., San Jose, CA) before imported into Open-CSAM.…”

Section: Muscle Fibers Morphological Quantitative Analysismentioning

confidence: 99%

Loss of HtrA2/Omi protease activity induces mitonuclear imbalance and sarcopenia via differential regulation of mitochondrial biogenesis

Zhou

Yuan

Gao

et al. 2020

Preprint

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Background Cellular homeostasis requires tight coordination between nucleus and mitochondria, organelles that each possess their own genomes. Disrupted mitonuclear communication has been found to be implicated in many aging processes. However little is known about mitonuclear signaling regulator in sarcopenia which is a major contributor to the risk of poor health-related quality of life, disability and premature death in older people. HtrA2/Omi is a mitochondrial protease and play an important role in mitochondrial proteostasis. HtrA2 mnd2(-/-) mice harboring protease-deficient HtrA2/Omi Ser276Cys missense mutants exhibit premature aging phenotype. Additionally, HtrA2/Omi has been established as a signaling regulator in nervous system and tumors. We therefore asked whether HtrA2/Omi participates in mitonuclear signaling regulation in aging muscle.Methods Using motor functional, histological and molecular biological methods, we characterized the muscle phenotype of HtrA2 mnd2(-/-) mice. We employed bioinformatics analysis and identified HtrA2/Omi as a gene differentially associated with nDNA/mtDNA gene expression in sarcopenia. Further, we isolated the gastrocnemius muscle of HtrA2 mnd2(-/-) mice and determined expression of genes in UPR mt , mitohormesis, electron transport chain (ETC), and mitochondrial biogenesis.Results Here, we showed that HtrA2/Omi protease deficiency induced denervation-independent skeletal muscle degeneration. Despite of mitochondrial hypofunction, upregulation of UPR mt and mitohormesis related genes and elevated reactive oxygen species (ROS) production were not observed in HtrA2 mnd2(-/-) mice, contrary to previous assumptions that loss of protease activity of HtrA2/Omi would lead to mitochondrial dysfunction as a result of proteostasis disturbance and ROS burst. Instead, we showed that HtrA2/Omi protease deficiency results in different changes between the expression of nDNA and mtDNA encoded ETC subunits, which is in consistent with their transcription factors NRF-1/2 and coactivator PGC-1α, suggesting that HtrA2/Omi protease activity may differentially regulate mitonuclear signaling via mitochondrial biogenesis in sarcopenia. Besides, Akt1 but not GSK3β showed increased expression level in HtrA2 mnd2(-/-) muscles, indicating an involvement of Akt1 in PGC-1α regulation response to HtrA2/Omi protease deficiency.Conclusions HtrA2/Omi protease deficiency induces mitonuclear imbalance and sarcopenia via differential regulation of mitochondrial biogenesis. The novel mechanistic insights may be of importance in developing new therapeutic strategies for sarcopenia.

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Open-CSAM, a new tool for semi-automated analysis of myofiber cross-sectional area in regenerating adult skeletal muscle

Cited by 59 publications

References 11 publications

Myosoft: An automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software

Myosoft: An automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software

Comparative Study of Histological and Histochemical Image Processing in Muscle Fibre Sections of Broiler Chicken

Loss of HtrA2/Omi protease activity induces mitonuclear imbalance and sarcopenia via differential regulation of mitochondrial biogenesis

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