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Method Article
Alexander Rodriguez-Palacios
Division of Gastroenterology and Liver Disease, Case Western Reserve University School of Medicine
Corresponding Author
License:
This work is licensed under a CC BY-NC 3.0 License. Read Full License
We recently described a unique phenotyping protocol based on stereomicroscopy (SM) to comprehensively characterize the intestinal mucosal topography in healthy and diseased mice (3D-SMAPgut). Such stereoscopic enterophenotyping approach has allowed the elucidation of novel pathophysiological mechanisms to explain three-dimensional (3D)-inflammatory structure patterns (stereoenterotypes) in the intestinal tract. Here we describe a step-wise protocol to assess the inflammatory reactivity of intestinal tissues using an improved cost-effective myeloperoxidase activity (96-well dianisidine) assay on SM-microdissected lesions harvested from intestinal specimens according to 3D-SM appearance. In addition, we emphasize the importance of controlling for gut flora effects by describing a laboratory protocol to harvest fecal and soiled bedding material from experimental mouse groups; the goal of this (‘inter-subject Pre-experimental Fecal flora Homogenization ‘IsPreFeH’) is to expose all investigational subjects to a composite of fecal material prior to experimentation as an alternative to cohousing which may not be always feasible with males and in all strains. Together, this methodology has enabled documenting the relevance of SM profiling of inflammatory 3D-structures in the gut while controlling for the cage effects of gut flora variability.
Keywords
stereomicroscopy, focal pathologies, inflammatory bowel disease, ulcerative colitis, mouse models, cobblestone lesions
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Authors declare no conflict of interests.
This is a list of supplementary files associated with this preprint. Click to download.
- supplement0.xlsx
*Supplementary Excel file 1* *MPO Excel calculator* This MPO-Excel file contains the equations necessary for the rapid reproducible determination of MPO activity. The reader needs to copy and paste the OD~450~ raw data from the plate reader in a table format, look at the curve values, and remove the data points that are outside of the steepest curve slope. MPO and other parameters will be automatically determined. Basic understanding of enzyme kinetics and linear regression and line fitting statistics is required.
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Method Article
Alexander Rodriguez-Palacios
Division of Gastroenterology and Liver Disease, Case Western Reserve University School of Medicine
Corresponding Author
Version History
CURRENT STATUS: Posted
Version 1
Posted 17 Jul, 2015
No community comments so far
Metrics
Comments: 0
HTML Views: ...
License:
This work is licensed under a CC BY-NC 3.0 License. Read Full License
We recently described a unique phenotyping protocol based on stereomicroscopy (SM) to comprehensively characterize the intestinal mucosal topography in healthy and diseased mice (3D-SMAPgut). Such stereoscopic enterophenotyping approach has allowed the elucidation of novel pathophysiological mechanisms to explain three-dimensional (3D)-inflammatory structure patterns (stereoenterotypes) in the intestinal tract. Here we describe a step-wise protocol to assess the inflammatory reactivity of intestinal tissues using an improved cost-effective myeloperoxidase activity (96-well dianisidine) assay on SM-microdissected lesions harvested from intestinal specimens according to 3D-SM appearance. In addition, we emphasize the importance of controlling for gut flora effects by describing a laboratory protocol to harvest fecal and soiled bedding material from experimental mouse groups; the goal of this (‘inter-subject Pre-experimental Fecal flora Homogenization ‘IsPreFeH’) is to expose all investigational subjects to a composite of fecal material prior to experimentation as an alternative to cohousing which may not be always feasible with males and in all strains. Together, this methodology has enabled documenting the relevance of SM profiling of inflammatory 3D-structures in the gut while controlling for the cage effects of gut flora variability.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
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