A multicenter study to standardize reporting and analyses of fluorescence-activated cell-sorted murine intestinal epithelial cells

Abstract

Fluorescence-activated cell sorting (FACS) is an essential tool for studies requiring isolation of distinct intestinal epithelial cell populations. Inconsistent or lack of reporting of the critical parameters associated with FACS methodologies has complicated interpretation, comparison, and reproduction of important findings. To address this problem a comprehensive multicenter study was designed to develop guidelines that limit experimental and data reporting variability and provide a foundation for accurate comparison of data between studies. Common methodologies and data reporting protocols for tissue dissociation, cell yield, cell viability, FACS, and postsort purity were established. Seven centers tested the standardized methods by FACS-isolating a specific crypt-based epithelial population (EpCAM+/CD44+) from murine small intestine. Genetic biomarkers for stem/progenitor (Lgr5 and Atoh 1) and differentiated cell lineages (lysozyme, mucin2, chromogranin A, and sucrase isomaltase) were interrogated in target and control populations to assess intra- and intercenter variability. Wilcoxon's rank sum test on gene expression levels showed limited intracenter variability between biological replicates. Principal component analysis demonstrated significant intercenter reproducibility among four centers. Analysis of data collected by standardized cell isolation methods and data reporting requirements readily identified methodological problems, indicating that standard reporting parameters facilitate post hoc error identification. These results indicate that the complexity of FACS isolation of target intestinal epithelial populations can be highly reproducible between biological replicates and different institutions by adherence to common cell isolation methods and FACS gating strategies. This study can be considered a foundation for continued method development and a starting point for investigators that are developing cell isolation expertise to study physiology and pathophysiology of the intestinal epithelium.

Intestinal Enteroendocrine Lineage Cells Possess Homeostatic and Injury-Inducible Stem Cell Activity

“…Further, as representative +4/quiescent ISC populations, we compared cells expressing Bmi1 (Sangiorgi and Capecchi, 2008), mTert (Breault et al, 2008; Montgomery et al, 2011), Hopx (Takeda et al, 2011), Dclk1 (May et al, 2009) or a lower side population (SP) (von Furstenberg et al, 2014). We previously described an Intestinal Stem Cell Consortium (ISCC) initiative to standardize ISC FACS isolation from primary intestinal epithelium by EDTA-based epithelial isolation, depletion of non-epithelial contaminants and sequential scatter- and antibody-based gating (Magness et al, 2013). Within this common schema, we performed reporter- and non-reporter-based isolation of CBC-like and +4/quiescent-type ISCs.…”

“…For all bulk cell and single cell mRNA-seq analysis of different cell populations, a 10cm segment of proximal jejunum (designated as cm 2–12 past the gastroduodenal junction, following discard of the first 2 cm of duodenum) was dissected and used to obtain dissociated epithelial cells, as previously described (Magness et al, 2013). The intestinal segment was flushed with cold PBS and the tissue was opened longitudinally and rinsed extensively with cold PBS to remove debris.…”

HUIEC, Human intestinal epithelial cell line with differentiated properties: process of isolation and characterisation

“…Similar cells may be isolated from various sources, including human, and from the gut of other vertebrates and invertebrates [30][31][32]. In the literature, there are many descriptions of intestinal cells with a rich experimental portfolio [33,34].…”

Multiparametric Analysis of Screening Data: Growing Beyond the Single Dimension to Infinity and Beyond

“…Such gating strategies have, however, the disadvantage that if conducted manually, they can result in significant variability among users. 29 An additional source of variability can be normalization within and among different experiments, although tools to address these issues have been developed. 30,31 In high-content image-based screening, studies typically focus on one primary readout, such as a target protein signal, while using other readouts as filters to identify treatments that have resulted in overt toxicity.…”