Robust integrated intracellular organization of the human iPS cell: where, how much, and how variable

Abstract

SummaryDespite the intimate link between cell organization and function, the principles underlying intracellular organization and the relation between organization, gene expression and phenotype are not well understood. We address this by creating a benchmark for mean cell organization and the natural range of cell-to-cell variation. This benchmark can be used for comparison to other normal or abnormal cell states. To do this, we developed a reproducible microscope imaging pipeline to generate a high-quality dataset of 3D, high-resolution images of over 200,000 live cells from 25 isogenic human induced pluripotent stem cell (hiPSC) lines from the Allen Cell Collection. Each line contains one fluorescently tagged protein, created via endogenous CRISPR/Cas9 gene editing, representing a key cellular structure or organelle. We used these images to develop a new multi-part and generalizable analysis approach of the locations, amounts, and variation of these 25 cellular structures. Taking an integrated approach, we found that both the extent to which a structure’s individual location varied (“stereotypy”) and the extent to which the structure localized relative to all the other cellular structures (“concordance”) were robust to a wide range of cell shape variation, from flatter to taller, smaller to larger, or less to more polarized cells. We also found that these cellular structures varied greatly in how their volumes scaled with cell and nuclear size. These analyses create a data-driven set of quantitative rules for the locations, amounts, and variation of 25 cellular structures within the hiPSC as a normal baseline for cell organization.

Mapping Protein Numbers in Living Cells

“…Finally, we compared these results to four separate estimates using quantitative immunoblots. To determine the mean concentration per cell, we calculated the amount of protein per cell divided by the average cell volume (1,700 ± 45 μm 3 obtained from estimates using 125,000 segmented cells [19] yielding a value of 1.6 ± 0.1 μM or 960 ± 60 molecules/μm 3 ).…”

Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model

“…A recent exploration about the quality of published Method sections in scientific articles containing images obtained with advanced microscopes, found that the quality of reporting was poor, with some articles containing no information about how images were obtained, and many articles lacking important basic details (13). Nonetheless, there is ample evidence that the publication of full details about how each image was obtained is vital for rigor, reproducibility and maximal scientific and sharing value (14)(15)(16)(88)(89)(90). In this context, the 4DN-BINA-OME Microscopy Metadata specifications presented are intended to provide a major contribution towards the development of community-driven criteria for which information should be included in the Methods sections of scientific publications.…”

“…Light Microscopy images need to be accompanied by thorough documentation of the microscope hardware and imaging settings to ensure a correct interpretation of the results. A significant challenge with the reproducibility of microscopy results and their integration with other data types, such as chromatin folding maps generated by the 4DN consortium (1,2), lies in the lack of standardized reporting guidelines for microscopy experiments as well as instrument performance and calibration standards (13)(14)(15)88). Despite a growing consensus that such standards for light microscopy are desirable, previous efforts to develop shared microscopy data models and application programming interfaces (4,5,54) have not yet succeeded in the establishment of a universal set of norms.…”

“…The reproducibility crisis affecting the biological sciences is well-documented (12)(13)(14)(15)(16). In the field of light microscopy, it can only be addressed if all published images are accompanied by complete descriptions of experimental procedures, biological samples, microscope hardware specifications, image acquisition settings, image analysis parameters and metrics detailing instrument performance and calibration (4,9,13,(17)(18)(19)(20).…”

Micro-Meta App: an interactive software tool to facilitate the collection of microscopy metadata based on community-driven specifications

“…In addition to providing essential information about the provenance (i.e., origin, lineage) 7,8 of microscopy results, this would make it possible to faithfully interpret scientific claims, facilitate comparisons within and between experiments, foster reproducibility, and maximize the likelihood that data can be re-used by other scientists for further insight 5,6,9,10 . First and foremost, such information would serve to facilitate the compilation of accurate Methods sections for publications that utilize the quantitative power of microscopy experiments to answer scientific questions [11][12][13] . Furthermore, it would provide clear guidance to the manufacturers of microscopy instruments, hardware components, and processing software about what information the scientific community requires to ensure scientific rigor so that they can be automatically provided during acquisition and written in the headers of image files.…”