The user interface of MuscleJ2 is organized into five panels: Sample Data, Data Acquisition, Data Analysis by Section, Data Analysis by Fiber, and Data Cartographies (Fig. 1), which will be described in more detail below. Before starting a run on an image set, the user must organize the acquired images into different folders so that the images in a given folder have the same properties (same type of muscle, same pathophysiological state, same staining, same data acquisition), as explained in the online User Guide.

Fig. 1

Interface of the MuscleJ2 plugin. Screenshots of the plugin dialog boxes. A The main dialog box MuscleJ2 is divided into five sections where the user must select from a drop-down menu or check boxes. The lowercase letters in red refer to dialog box 2, in which the channels and staining information must be indicated. B The Channel information dialog box is used to indicate the channel number for each requested analysis. Depending on the analyses selected in the MuscleJ2 dialog box, the design of this dialog box changes. In the upper panel, the lowercase letters in red refer to the section Data Analysis by Section (a, b, c); in the lower panel, they refer to the section Data Analysis by Fiber (d, e, f) and Data Cartographies (g)

Sample data panel

Under physiological conditions, CSA is homogeneous across fiber regions, making it possible to use this parameter to discriminate between what can and cannot be labeled as a fiber. This is not the case when skeletal muscle is damaged, as in myopathies or after injury, where fiber size can be very heterogeneous. We have taken this point into account and have introduced an option, named Pathophysiology, where the user can choose between Healthy and Damaged fiber populations (Fig. 1). In damaged muscles, the heterogeneity of fiber CSA is increased, and MuscleJ2 flexibly considers a wider range of CSA measurements. The contribution of the Damaged option (selected in the Pathophysiology tab) is illustrated in Fig. S1, where the mouse tibialis anterior was partially injured, resulting in significant variability in fiber CSA between injured and uninjured parts. When Healthy is selected, MuscleJ2 excludes the largest and smallest fibers. When the Damaged option is selected, the range of differences in fiber CSA is much wider, and all the fibers are taken into account. This option allows the users to adapt the algorithm according to their parameters of interest. Notably, even in fusiform muscles such as the tibialis anterior, not all myofibers are fully aligned with the longitudinal axis of the muscle, and some have a high pennation angle [2]. This has led to the presence of nontransversal but extremely elongated fibers within cross sections (in parts of rat muscles) holding a low circularity value, and these fibers were correctly excluded by MuscleJ2. There can also be variation in CSA values along the length of the muscle [3], which would require the analysis of multiple levels of cross sections for a better assessment of myofiber size variation.

In the Sample Data panel, the user can inform the plugin of the anatomical origin of the sections, i.e., from limb or diaphragm muscle (Fig. 1). This option was added because of the large difference between classical hind limb muscles and the diaphragm, the latter usually being cut in a folded state (Fig. S2). When the Diaphragm option is selected, MuscleJ2 does not fill in holes to account for the actual surface of the tissue. As this type of skeletal muscle is studied with particular interest in pathological states [4, 5], this option now offers the possibility of analyzing it with MuscleJ2.

It is now possible to analyze a section of skeletal muscle divided into several pieces in the image, whereas in the first version of MuscleJ, only the largest region was selected. This allows the analysis of different skeletal muscle subsections grouped on the same image, which is particularly useful for muscles with different chiefs, such as the quadriceps femoris or the gastrocnemius, which can be separated into several parts during the cryosection preparation.

Data acquisition panel

We have developed an algorithm applicable to images obtained from a wider range of more recent equipment, which is why the selection of the Acquisition system (Apotome/Wide field/…) and the File format is no longer necessary. MuscleJ2 can easily work on different image formats (such as.czi,.lif,.tiff …) supplied by the majority of gold standard image acquisition systems (Fig. S3). Importantly, image quality is a prerequisite for good analysis, and the acquisition system must be carefully selected before the batch experiments are performed.

In the Volume option, the user must inform MuscleJ2 if the images contain a single Z or a stack of Z. When the Z-stack option is selected, MuscleJ2 will automatically perform a maximum intensity projection prior to any analysis (Fig. S3). Although MuscleJ2 is designed to work on whole skeletal muscle sections, there is a Scanned Area option (Entire section/Crop) in case the muscle section is not whole. However, the user must be careful when using the Crop option and ensure that the crop contains a minimum of 25% of the image with a black background without tissue. This is essential for correct quantification.

The Artefact Detection option, which was previously in the MuscleJ macro, has been incorporated into this section (Fig. 1). It allows the user to eliminate from the analysis any slides where the detected muscle fibers represent less than the indicated percentage of the total muscle surface.

A new panel with features related to the whole skeletal muscle section

In this third panel, named Data Analysis by Section, we have introduced new functionalities that do not refer to individual fibers but to the total surface of the skeletal muscle (Fig. 1). All these analyses are performed on whole-slide image sections or on representative parts of the image manually cropped by users. For these analyses, the definition of ROI is not necessary, unlike other functionalities of the Data Analysis by Fiber panel, described below. Consequently, laminin staining is not mandatory, and artifact detection is not associated with these options. It is therefore the responsibility of the user to ensure that the muscle sections are correctly detected and do not contain holes or folds. However, staining for ECM or any fiber marker (except nuclear markers) is necessary for MuscleJ2 to delineate the section contours and estimate the total surface area. The corresponding channel must be implemented in the Section Shape in dialog box 2 (Fig. 1). This allows the quantifications of the different parameters to be related to the total surface of skeletal muscle.

In this panel, three new features have been developed:

ECM Area Detection (Fig. 2A) Fig. 2

New functionalities of the plugin. A Immunostaining of skeletal muscle with WGA showing the extracellular matrix (ECM) in green (SB = 600 µm) and respective quantification with MuscleJ2 in the "GlobalResults" file. B Immunostaining of skeletal muscle with laminin (gray) and CD31 showing the endothelial cells in red (SB = 600 µm) and quantification of vessels and capillaries with MuscleJ2. Tables present the results obtained after selecting the option Vascularization (section Data Analysis by Section) and Capillaries (section Data Analysis by Fibers). The gray table presents the results obtained in the "GlobalResults" file, and the green table presents some of the results obtained in the "CapillaryDetails" file (SB = 600 µm). C Immunostaining of skeletal muscle with laminin (gray), DAPI (blue), and F4/80 showing the macrophages in red and quantification of specific cells with MuscleJ2 (SB = 600 µm). The gray table presents the results obtained in the "GlobalResults" file, and the green table presents some of the results obtained in the "SpecificCells" file. Nucleus GC X and Y correspond to the coordinates of identified specific cells colabeled with DAPI. All areas are indicated in µm2

The ECM forms a network of macromolecules and smaller components that fill the extracellular space and can be divided into two parts: the basement membrane, which surrounds thin muscle fibers, and a more diffuse interstitial matrix. The basement membrane can be specifically detected using anti-laminin or anti-collagen IV antibodies, for example. Quantification of the ECM is particularly important in the context of myopathies and skeletal muscle regeneration studies, which require assessment of the area of fibrosis corresponding to modifications of the ECM, with accumulation of different components, such as collagen I (reviewed in Loreti et al. [6]). Similarly, wheat germ agglutinin (WGA), a carbohydrate-binding protein conjugated to various fluorochromes, can be used for the global visualization of muscle ECM and fiber boundaries [7]. This provides rapid fluorescence staining with few background noise events (Fig. 2A). Since WGA detects ECM by labeling sialic acid and N-acetylglucosamine residues contained in glycoproteins and glycolipids, it could also be linked to oligosaccharides contained in the cell membrane. Therefore, we do not recommend its utilization in conditions with large and multifocal myofiber necrosis areas and/or with immune infiltrates, such as the first few days after muscle injury (data not shown).

Because ECM staining is sufficient and is included in the algorithm to detect the muscle section, another channel for the Section Shape is not needed. We would like to emphasize that variations in ECM content can also be observed when tissue sections are obtained from different levels along the muscle length since internal tendons may or may not be present [8]. In the “GlobalResults” file for this analysis, two outputs are reported: the ECM area (in µm2) and the percentage of the total section area accounted for the ECM area (Fig. 2A).

Vascularization (Fig. 2B)

The second feature of the panel is the assessment of the Vascularization of the skeletal muscle. In the original version of MuscleJ, the number of vessels was quantified and reported to their associated fibers [1]. Such staining corresponds to capillaries. We now distinguish between total Vascularization, including all types of vessels without morphological criteria, and Capillaries (detailed below in the section Data Analysis by Fiber). This concerns all arteries or veins contained in the entire muscle section. This option measures the percentage of the total surface occupied by the vessels relative to the total section area of skeletal muscle. The number of vessels per mm2 is also provided in the result tables (Fig. 2B). Therefore, it is possible to perform an analysis of vascularization independently without using fiber morphology (which does not need to be labeled). As for the ECM, endothelial cell staining (for example, with CD31 antibody) is sufficient and is included in the algorithm to detect the muscle section; therefore, this channel can be used for the Section Shape.

Specific Cells (Fig. 2C)

Skeletal muscle tissue contains a variety of nonmyogenic cell types that are located between fibers and are not capillary or satellite cells, which are already tracked by MuscleJ. The third functionality is the characterization of these Specific Cells located anywhere in skeletal muscle. These may be, for example, resident stromal cells or infiltrating immune cells observed in pathological conditions or in injured tissues [9,10,11]. The name of the marker used to label-specific cells is entered manually as Cell Marker in the second dialog box (Channel Information) (Fig. 1F). This name will then be reported in the final table of results (Fig. 2C). This cell-specific marker can label an antigen as being located in the cytoplasm, membrane, or nucleus. A nuclear DNA label is also needed to ensure that the detected staining identifies a true cell and not artifacts such as cellular debris or a nonspecific signal. However, because nuclei of some cells may be imaged out of focus, the total number of specific cells, including those not counterstained with nuclear dye, is reported in the final “GlobalResults” file (Nb-Specific Cells and Nb-Specific Cells with nuclei) (Fig. 2C). In addition, MuscleJ2 provides information corresponding to the percentage of the area occupied by these cells (%Specific Cell Area), as well as the mean intensity of the signal in specific cells with nuclei (Intensity Mean) and their Area Mean (Fig. 2C).

Because each signal is different, MuscleJ2 provides the users with the raw data to allow them to set a personal threshold and filter their results based on their experience. In the final “SpecificDetails” file, the user can find the min and max Feret diameter, the coordinates (x, y) of the gravity center of the specific staining (only cells costained with DAPI), the nuclear center of gravity (x, y), and the intensity of the appropriate channel for each specific cell. As with all the other options, to allow viewing of the specific cells identified by MuscleJ2, their coordinates are saved in the ROI dedicated folder, and it is easy to return to any cell if needed. As an example, this new functionality was tested to detect F4/80-positive pan-macrophages (Fig. 2C) in a series of cross sections of regenerating muscle. Any validated antibody giving rise to a distinct signal in any cell in skeletal muscle can be used, offering a large panel of data analysis. In a set of images, it is possible to quantify several cellular markers, albeit one at a time, by running the batch of images for each specific marker. Since cells positive for multiple labels will share the same located nucleus, they could be quantified by mixing (using open-access software such as R) all the files “SpecificDetails” for each muscle section by the column nucleus gravity center (x, y).

All these novel functions are compatible with the other functions of the Data Analysis by Fiber panel.

New functionalities reported for muscle fibers

In this section, all the results are given per fiber, based on the laminin staining (or any equivalent staining to identify myofibers). We have already described the different ROIs in the original version of MuscleJ [1], and they are conserved in this new version of the plugin. However, to be more precise, we have changed ROIV (vessels) to ROICap (capillaries), as explained previously. Moreover, we added a new ROI corresponding to the cellular membrane region of the fiber (ROIMB) (Fig. 3A). This new specific ROIMB has been designed to quantify fluorescence staining in sarcolemmal or subsarcolemmal regions, such as the dystrophin-glycoproteins complex, where mutations in the genes encoding for its components can cause several muscular dystrophies.

Fig. 3

Measurement of Fiber Intensity by ROI. A Representation of the different ROIs in MuscleJ2. ROIF, ROI Fiber; ROICNF, ROI Centronucleated Fiber; ROISC, ROI Satellite Cell; ROICap, ROI Capillary; ROIMB, ROI Membrane. B Original image of skeletal muscle stained with dystrophin and corresponding cartographies representing the different ROIs obtained after MuscleJ2 analysis with the Fiber Intensity option. C For each fiber, the intensity of the staining and the percentage of positive pixels in each ROI are given. D Quantification of dystrophin staining in the different ROIs. The gray table presents the results obtained in the "GlobalResults" file, and the green table presents some of the results obtained in the "FiberDetails" file

We have also implemented new functionalities in this section.

Peri-myonuclei

Nuclei located inside myofibers are named “myonuclei” (Fig. 1). This novel functionality allows the quantification of the nuclei belonging exclusively to muscle fibers independently of the Centro-Myonuclei function. In healthy conditions, these nuclei exhibit a peripheral location. Since skeletal muscle is a highly adaptable tissue, their number may vary and needs to be quantified for each fiber. Myonuclei can be labeled in vivo using a transgenic mouse strain expressing histones coupled to GFP specifically in myofibers [12] or by using an antibody against the centrosomal protein PCM1 [13]. While PCM1 can also be expressed by proliferating myoblasts and macrophages in damaged muscle [14], MuscleJ2 can specifically detect myonuclei based on their location in the ROIMB (Fig. S4).

To be identified as peripheral myonuclei by MuscleJ2, nuclei must be colabeled with the myonuclei marker and a fluorescent DNA stain such as DAPI. This is different from Centro-Myonuclei detection, which uses ROICNF and does not require colabeling because the central location may be sufficient for classification as myonuclei.

This analysis could be particularly useful to study myonuclei modifications in response to exercise training, and its controversial persistence during detraining (reviewed in Rhamati et al. [15]), which could vary according to fiber type, could be associated with changes in nuclei [16] or could be regulated by epigenetic modifications that could be investigated in situ with fluorescent labeling [17].

Capillaries

The option named Capillaries replaces the option Vessels of the original version of MuscleJ. This allows the user to analyze the capillaries associated with the fibers independently of the total vascularization of the muscle, which can now be performed using the Vascularization option, as described above. Consequently, the new ROICap replaces the previous ROIV.

The “GlobalResults” file shows the number of fibers with capillaries and the total number of capillaries. The min and max Feret diameter, the gravity center coordinates (x, y), and the intensity of the appropriate channel for each capillary (Fig. 2B), as well as the parameter named Sharing Factor (SF), which represents the number of fibers around each capillary [17], are included in the “CapillaryDetails” file. In the “FibersDetails” file, the number of capillaries surrounding each fiber has been named capillary contacts to correspond to the commonly used terms [18, 19].

New fiber type IIX and changes in fiber typing

In the previous version of MuscleJ, fibers expressing type IIX myosin heavy chain (MyHC) were detected indirectly as corresponding to unstained fibers. In MuscleJ2, a channel can now be selected to directly identify this additional adult MyHC. This allows more accurate detection of type IIX fibers and hybrid myofibers expressing two or more isoforms [20]. This option is named Type IIX fibers (Fig. S5A). This allows, for example, investigation of hybrid myofiber transitions in disease or in response to exercise [20]. Specific labeling of fibers expressing MyHC IIX may be particularly useful for human muscle samples because the type IIB isoform is not expressed, and some antibodies may cross-react against other isoforms [21].

In addition, many changes were made in the fiber typing to improve this quantification (see “Methods”). The fiber-type analysis of the plugin has been optimized using a set of images from different users where type IIB or IIX fibers have, in most cases, a lower fluorescence intensity, probably due to lower reactivity of the IgM subclass of these primary antibodies [22]. We would like to point out that a fiber type could be variable along the same myofiber, as type IIA has been reported to be more abundant at the proximal extremity of the tibialis anterior in mice [3].

The thresholds are given in the “GlobalResults” file, as along with the associated fiber type defined by MuscleJ2 (Fig. S5B). However, if staining problems are encountered, it is possible not to use the automatic classification performed by MuscleJ2 and to go back to the “FiberDetails” files to reclassify the fibers manually based on a user-defined threshold.

Fiber intensity by ROI (Fig. 3 )

A myriad of fluorescent labels can be investigated in muscle fibers as part of skeletal muscle research. The Fiber Intensity by ROI is a feature that allows quantification of any staining in muscle fibers (Fig. 1). Staining intensity is measured simultaneously in different areas of interest, since some markers may be heterogeneously expressed within the myofiber or at or below the cell membrane (sarcolemma). The results provide the intensity of the labeling and the %intensity positivity in the different ROIs (Fig. 3A–B). In the “GlobalResults” file, the average intensity of all segmented fibers is given for each ROI (ROIx Intensity Mean), as well as the associated standard deviation (ROIx Intensity StdDev).

For example, in regenerating or pathologic states, developmental isoforms could be re-expressed as embryonic and perinatal MyHC [23]. The quantification of the number of newly regenerated fibers re-expressing embryonic MyHC (MYH3 -positive fibers) can now be detected using this new function. Another example is the quantification of the percentage of dystrophin positivity in the different fiber ROIs, particularly in the ROIMB (Fig. 3C). In the “GlobalResults” file, MuscleJ2 indicates the mean intensity of staining for all the fibers based on the staining/background ratio. However, the user can decide to use a different threshold based on the results by working directly on the “FiberDetails” file (Fig. 3D).

Multiple analysis in the cartography section

All analyses carried out by MuscleJ2 can be visualized on cartographies in the Data Cartographies panel (Fig. 1). In addition to the five cartographies initially developed in MuscleJ to visualize the results of the analysis of Fiber Morphology, Centro Myonuclei Fibers, Satellite Cells, Vessels, and Fiber Type, we have added the cartographies of peri-myonuclei, Fiber Intensity, Specific Cell Localization, and in situ ECM Signal (Fig. 4A). MuscleJ2 also offers the possibility of adding a legend and a scale bar at different positions of the image, determined by the user. In addition, it is now possible for the user to select the channel on which the cartography will be drawn (in the second dialog box: Image used for cartographies). Furthermore, for the option Fiber Intensity by ROI, different cartographies were added to represent the MuscleJ2 results in the different ROIs. Another new option in this panel, named Multi-Cartography Montage, allows users to obtain a photo montage of all selected options in the Data cartography panel (Fig. 4B).

Fig. 4

Novelty of the cartography section. A Representative images of the cartographies obtained for specific cells, ECM detection, and capillaries (SB = 600 µm). B Representation of the image obtained after selection of the multicartography option, in which different cartographies are assembled on the same image. In this example, the image was stained with dystrophin, and the results are represented in the different cartographies (SB = 300 µm)

Generation of metadata files

After each run, MuscleJ2 generates a text file containing a summary of the options and selected analyses (Fig. S6). This file allows the user to easily retrieve the metadata associated with the performed analysis and is in the result folder along with other files such as “GlobalResults” and “FiberDetails.” In the latter, the user can access the details of the requested Analysis by Fiber. The user can therefore use the "ROI" file to review the identified fibers of the section and possibly manually delete some major aberrant fiber detections. However, we do not recommend adding new fibers manually, as this will add an additional source of variability since the mode of quantification will be different from that performed automatically. The “GlobalResults” file averages all the fibers in the section. Compared to the original version of MuscleJ, it is no longer generated at the end of the run but is updated after each executed image to obtain the global results step by step, without losing data if the plugin unexpectedly stops before the end of the process.