Use of the iNo score to discriminate normal from altered nucleolar morphology, with applications in basic cell biology and potential in human disease diagnostics

Nat Protoc. 2018 Oct;13(10):2387-2406. doi: 10.1038/s41596-018-0044-3.

Abstract

Ribosome biogenesis is initiated in the nucleolus, a cell condensate essential to gene expression, whose morphology informs cancer pathologists on the health status of a cell. Here, we describe a protocol for assessing, both qualitatively and quantitatively, the involvement of trans-acting factors in the nucleolar structure. The protocol involves use of siRNAs to deplete cells of factors of interest, fluorescence imaging of nucleoli in an automated high-throughput platform, and use of dedicated software to determine an index of nucleolar disruption, the iNo score. This scoring system is unique in that it integrates the five most discriminant shape and textural features of the nucleolus into a parametric equation. Determining the iNo score enables both qualitative and quantitative factor classification with prediction of function (functional clustering), which to our knowledge is not achieved by competing approaches, as well as stratification of their effect (severity of defects) on nucleolar structure. The iNo score has the potential to be useful in basic cell biology (nucleolar structure-function relationships, mitosis, and senescence), developmental and/or organismal biology (aging), and clinical practice (cancer, viral infection, and reproduction). The entire protocol can be completed within 1 week.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Nucleolus / genetics
  • Cell Nucleolus / pathology*
  • Cell Nucleolus / ultrastructure*
  • Cellular Senescence
  • HeLa Cells
  • High-Throughput Screening Assays / methods
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Interphase
  • Mitosis
  • Neoplasms / diagnosis
  • Neoplasms / pathology
  • Nuclear Proteins / analysis
  • Nuclear Proteins / genetics
  • Optical Imaging / methods*
  • RNA Interference
  • RNA, Small Interfering / genetics
  • Software

Substances

  • Nuclear Proteins
  • RNA, Small Interfering