estimation of total lipid volume from decellularized muscles by lipid extraction

Quantifizierung der Fettinfiltration der Skelettmuskulatur durch Dezellularisierung

The accumulation of adipocytes between myofibers within the skeletal muscle is a prominent feature of disparate conditions, from type 2 diabetes to sarcopenia to musculoskeletal injury1,2,3,4,5,6,7. Comprehensive assessment of this intramuscular adipose tissue (IMAT) is critical to understanding the pathogenesis of these conditions, as IMAT deposition is strongly correlated with insulin resistance3,8,9,10 and poor skeletal muscle function11,12,13,14,15. Although these associations have been noted for decades, the mechanisms associated with and the origin of IMAT still remain an area of intense investigation. This is partly because most studies assessing skeletal muscle fatty infiltration have been performed in humans, where mechanistic investigations are limited16,17. However, more recently, small animal models, including mice, have been utilized to help pinpoint cellular regulation of IMAT development and signaling18,19,20. This work aims to provide a new tool for use with small animal models for qualitatively visualizing and quantifying skeletal muscle fatty infiltration.
Clinically in human populations, fatty infiltration is assessed using noninvasive methods, including computed tomography (CT)6,21, magnetic resonance imaging (MRI)16,17,22,23, and ultrasound (US)17,24. These imaging techniques typically identify a defined region of interest (ROI) in a muscle and acquire image slices within that region, although comprehensive approaches have also been employed25,26,27. These image slices are subjected to qualitative grading6 and quantified via pixel thresholding28. Similar approaches have been utilized in animals previously29,30; however, they are costly and require access to small animal imaging systems. Spatial resolution via CT and MRI use also presents a major issue, as they are unable to delineate IMAT adipocytes from skeletal muscle fibers within a voxel and instead rely on subjective separation of primarily muscle regions and primarily IMAT regions31,32. As such, the inability to accurately identify fat or muscle tissue also presents inaccurate quantification of representative amounts of these tissues.
Due to these limitations, current techniques to assess skeletal muscle fatty infiltration in small animal models most commonly rely on histology as an inexpensive and accessible alternative33,34. Standard staining procedures, including hematoxylin and eosin (H&#38;E), oil red O (ORO), and immunostaining for adipocyte markers such as perilipin, allow for simple detection and visualization of adipocytes comprising fatty infiltration within the muscle. However, histology approaches are rarely comprehensive, and typically, IMAT qualitative or quantitative assessment is limited to a single section34. Lipid extraction has also been used to quantify total muscle lipids35; however, this technique fails to distinguish between intramyocellular lipid (IMCL) and intramuscular adipose tissue (IMAT) stores36. In summary, current methodologies to visualize and quantify fat in muscle remain limited either by financial costs or the specific detection of IMAT.
Here, we describe a detailed method for assessing skeletal muscle fatty infiltration both by qualitative visualization and multi-scale quantification. This methodology employs a simple decellularization technique that removes myocellular structures, including IMCL, but keeps the larger IMAT adipocyte-derived lipid droplets intact. Validation of the specificity of this technique has been published37, including using lipid extraction to show the depletion of IMCL with decellularization, &#181;CT to show the retention of IMAT patterning with decellularization, and histology to show the similar size distribution of IMAT lipid droplets compared with those identified with decellularization. Once decellularized, muscles can be stained with lipid-soluble dyes for qualitative visualization of the pattern and the extent of fatty infiltration and/or quantitative imaging of individual IMAT lipid droplets. Dyes can subsequently be extracted with isopropanol, and the optical density (OD) of the resulting solution can be used to estimate the IMAT lipid volume. The stringent validation of this technique has been published elsewhere37. This article provides a detailed protocol to use this methodology with mouse muscles and provides troubleshooting tips to support the adoption of this method in other applications, such as muscles from other species or other tissues.

Autor im Rampenlicht: Dezellularisierungsbasierte Quantifizierung der Fettinfiltration der Skelettmuskulatur  

Dezellularisierungsbasierte Quantifizierung der Fettinfiltration der Skelettmuskulatur

We are interested in crosstalk between contracting muscle and the adipocytes that form between muscle fibers in injury and disease called intramuscular adipose tissue, or IMAT. Genetic engineering in cells in mice is a powerful tool for mechanistically dissecting fat muscle crosstalk. Analysis of signaling via transcriptomics and proteomics identifies mediators, and then biomaterial based drug delivery can intervene in these pathways.One of the primary challenges is isolating and quantifying IMAT adipocytes. Especially in small animal models, the IMAT signal is washed out by whole muscle analysis like transcriptomics or lipidomics, and quantifying IMAT by noninvasive imaging suffers from similar washout, as most voxels contain a mixture of muscle and IMAT. We recently used this technique described in this article to demonstrate that IMAT directly impairs muscle contractility.With precise measures of IMAT deposition, we showed that it does not just replace contractile material, but impedes a contraction in the remaining lean muscle. This protocol addresses challenges with quantifying IMAT. The current standard to measure IMAT in small animals is single section histology, which is not comprehensive or non-invasive imaging, which is expensive and low resolution.We believe this has limited our understanding of IMAT muscle crosstalk. This technique provides a comprehensive and inexpensive method for assessing IMAT by qualitative visualization and multi-scale quantification. We hope this technique's simplicity will encourage more investigators to measure IMAT in their animal models.Also, this technique will provide a higher precision tool for the investigators interested in IMAT to uncover more subtle relationships between IMAT adipocytes and other cells.

Watch this Scientific Journal Video about Estimation of Total Lipid Volume from Decellularized Muscles by Lipid Extraction at JoVE.com

Estimation of Total Lipid Volume from Decellularized Muscles by Lipid Extraction  

Schätzung des Gesamtlipidvolumens aus dezellularisierten Muskeln durch Lipidextraktion

Beginnen Sie mit der Übertragung der dezellularisierten Skelettmuskeln, die mit ORO gefärbt wurden, auf 200 Mikroliter Isopropanol in den einzelnen Vertiefungen einer 96-Well-Platte. Rühren Sie die Lösung um, indem Sie auf die Platte klopfen. Und zerquetschen Sie den Muskel mechanisch mit einer Pipettenspitze unter einem Mikroskop, bis keine roten Kugeln mehr in der dezellularisierten Muskelsuspension zu sehen sind.Mischen Sie die Zellsuspension erneut in jeder Vertiefung, indem Sie sie auf und ab pipettieren, bevor Sie 75 Mikroliter in zwei saubere Vertiefungen der Platte überführen. Decken Sie die Platte ab und lesen Sie die Absorption der doppelten 75-Mikroliter-Vertiefungen mit einem Spektralphotometer oder einem Plattenlesegerät ab.

estimation-total-lipid-volume-from-decellularized-muscles-lipid

Research

JoVE Journal

Biology

Estimation of Total Lipid Volume from Decellularized Muscles by Lipid Extraction

259 Aufrufe.  Washington University in St. Louis. Beginnen Sie mit der Übertragung der dezellularisierten Skelettmuskeln, die mit ORO gefärbt wurden, auf 200 Mikroliter Isopropanol in den einzelnen Vertiefungen einer 96-Well-Platte. Rühren Sie die Lösung um, indem Sie auf die Platte klopfen. Und zerquetschen Sie den Muskel mechanisch mit einer Pipettenspitze unter einem Mikroskop, bis keine roten Kugeln mehr in der dezellularisierten Muskelsuspension zu sehen sind.Mischen Sie die Zellsuspension erneut in jeder Vertiefung, indem Si...

Serie: Estimation of Total Lipid Volume from Decellularized Muscles by Lipid Extraction  

Decellularization-Based Quantification of Skeletal Muscle Fatty Infiltration

Fatty infiltration is the accumulation of adipocytes between myofibers in skeletal muscle and is a prominent feature of many myopathies, metabolic disorders, and dystrophies. Clinically in human populations, fatty infiltration is assessed using noninvasive methods, including computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US). Although some studies have used CT or MRI to quantify fatty infiltration in mouse muscle, costs and insufficient spatial resolution remain challenging. Other small animal methods utilize histology to visualize individual adipocytes; however, this methodology suffers from sampling bias in heterogeneous pathology. This protocol describes the methodology to qualitatively view and quantitatively measure fatty infiltration comprehensively throughout intact mouse muscle and at the level of individual adipocytes using decellularization. The protocol is not limited to specific muscles or specific species and can be extended to human biopsy. Additionally, gross qualitative and quantitative assessments can be made with standard laboratory equipment for little cost, making this procedure more accessible across research laboratories.

The present study describes decellularization-based methodologies for visualizing and quantifying intramuscular adipose tissue (IMAT) deposition through intact muscle volume, as well as quantifying metrics of individual adipocytes that comprise IMAT.

Fatty infiltration is the accumulation of adipocytes between myofibers in skeletal muscle and is a prominent feature of many myopathies, metabolic ...

Forschung

Biologie

Decellularization of Skeletal Muscle 

To begin, inspect the muscles of interest dissected from the sacrificed mouse for the absence of bone chips or ragged edges and trim them away with sharp scissors if needed. Weigh the cleaned muscles using an analytical balance and record their weight. After placing the muscle in at least 0.1 milliliters of 1%SDS per milligram of weight, place the well plate on a rocking shaker set to 50 to 80 Hertz.Visually inspect the SDS solution periodically. When the solution becomes cloudy, remove the solution with a pipette without aspirating the muscles and replace it with an equal volume of fresh 1%SDS. When the solution remains clear for 24 hours, remove the final SDS solution from the decellularized muscles and replace it with an equal volume of PBS.Inspect the decellularized muscles under a stereo microscope and carefully remove any hair or debris stuck to the muscle using forceps. Carefully remove the PBS and replace it with an equal volume of 3.7%formaldehyde before returning the plate to the rocking shaker for 24 hours.

Dezellularisierung der Skelettmuskulatur 

Intramuscular Adipose Tissue (IMAT) Visualization with Oil Red O Staining

Prepare the ORO solution by dissolving 0.5 grams of ORO powder in 100 milliliters of isopropanol to generate a stock solution. Prepare the working solution for all muscles by combining the ORO stock solution and deionized water at a 60 to 40 ratio. Cover the working solution for 10 minutes to allow the particulate to settle.Filter it through a 40 micrometer mesh, followed by a 0.22 micrometer syringe filter. Next, remove the formaldehyde solution from the decellularized muscles in the well plate and wash the muscles three times with an equal volume of PBS. Then, replace the PBS with an equal volume of 60%isopropanol solution and incubate it on the rocking shaker for five minutes.Once done, replace the 60%isopropanol solution with ORO working solution before 10 minutes of incubation on the rocking shaker. Next, replace the ORO working solution with an equal volume of 1%SDS and inspect the SDS solution periodically. Once the solution becomes noticeably pink, replace the SDS solution with fresh 1%SDS.When the solution remains clear for 24 hours, replace the 1%SDS with PBS. Under a stereo microscope at four x magnification, remove any obvious debris or particulate stuck to the outside of the stained muscle. If the staining is satisfactory, showing the bright red spheres floating in a transparent matrix, acquire the staining images using a camera attached to the stereo microscope.Properly decellularized muscles were white and semi-transparent. When decellularized muscles were stained with ORO to visualized intramuscular adipose tissue, or IMAT, IMAT lipid droplets were apparent within the clear muscle structures as red spheres. Healthy mouse hind limb muscles showed a little natural IMAT evidenced by little to no red or positive lipid as compared to the hind limb muscles injected with cardio toxin or glycerol.Incomplete decellularization was identified immediately following initial SDS treatment or after the washout of the ORO staining as semi opaque light pink fibers. Incomplete ORO clearance was identified following ORO washout as a pink or red uniform background rather than distinct fiber lines.

Visualisierung von intramuskulärem Fettgewebe (IMAT) mit Ölrot-O-Färbung

Begin by transferring the decellularized skeletal muscles stained with ORO to 200 microliters of isopropanol in the individual wells of a 96 well plate. Agitate the solution by tapping the plate. And mechanically crush the muscle with a pipette tip under a microscope until no red spheres can be seen in the decellularized muscle suspension.Again, mix the cell suspension in each well by pipetting up and down before transferring 75 microliters to two clean wells of the plate. Cover the plate and read the absorbance of the duplicate 75 microliter wells using a spectrophotometer or a plate reader.

Quantification of Intramuscular Adipose Tissue (IMAT) Lipid Droplet Metrics Using Confocal Imaging

To begin the quantification of stained IMAT lipid droplet metrics, open Confocal Stacks in ImageJ. Open the Threshold User Interface by selecting Image, then Adjust, then Threshold. In the user interface, select Intermodes as the thresholding type and ensure Dark Background is selected.Then click on Apply to run a thresholding algorithm. Run the watershed algorithm to separate touching lipid droplets by selecting Process, then Binary, and Watershed. Select Yes in a dialog box to process all the images in the stack to add a thin black line dividing larger areas of solid white.To set the maximum and minimum particle sizes, open the original image and outline the smallest and largest lipid droplet in view using the Oval tool. Then add these shapes to the ROI Manager by typing T.Select Analyze, then Set Measurements. In the dialog box, select the settings, check Area only, and click OK.Then select Measure from the ROI Manager.Use the two area measures from this results window as the size range and analyze particles. To identify the region of interest, or ROIs, with the analyze particles algorithm. Select Analyze, then Analyze Particles.A dialog box opens to set the selection settings. To output the ROI Measurements, select Analyze, then Set Measurements, and select Area, Centroid, Fit Ellipse, and Stack Position. Click on OK.Then select Measure from the ROI Manager.The data in the results table can be selected and copied into Excel for further analysis. For a detailed assessment of individual lipid droplet metrics and distribution, the BODIPY fluorescently labeled lipid droplets were imaged via confocal microscopy. Thresholding and shape segmentation provided a good first pass for generating ROIs for each lipid droplet.However, manual edits were needed to correct the errors. Deep lipid droplets, which appeared dim on the image, can be added by hand using the Oval tool in ImageJ. A group of lipid droplets mistakenly identified as a single ROI can also be corrected by deleting and replacing the original ROI with multiple new ROIs.Where a single lipid droplet was identified as a unique ROI in multiple slices, the duplicate ROIs were consolidated into a single ROI.