Auto-segmentation and time-dependent systematic analysis of mesoscale cellular structure in β-cells during insulin secretion

Author:

Li AngdiORCID,Zhang XiangyiORCID,Singla JitinORCID,White KateORCID,Loconte ValentinaORCID,Hu Chuanyang,Zhang Chuyu,Li ShuailinORCID,Li WeiminORCID,Francis John PaulORCID,Wang ChenxiORCID,Sali Andrej,Sun LipingORCID,He XumingORCID,Stevens Raymond C.ORCID

Abstract

The mesoscale description of the subcellular organization informs about cellular mechanisms in disease state. However, applications of soft X-ray tomography (SXT), an important approach for characterizing organelle organization, are limited by labor-intensive manual segmentation. Here we report a pipeline for automated segmentation and systematic analysis of SXT tomograms. Our approach combines semantic and first-applied instance segmentation to produce separate organelle masks with high Dice and Recall indexes, followed by analysis of organelle localization based on the radial distribution function. We demonstrated this technique by investigating the organization of INS-1E pancreatic β-cell organization under different treatments at multiple time points. Consistent with a previous analysis of a similar dataset, our results revealed the impact of glucose stimulation on the localization and molecular density of insulin vesicles and mitochondria. This pipeline can be extended to SXT tomograms of any cell type to shed light on the subcellular rearrangements under different drug treatments.

Funder

National Institutes of Health

DOE’s Office of Biological and Environmental Research

International Cooperation and Exchange Programme

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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