Quantifying organellar ultrastructure in cryo-electron tomography using a surface morphometrics pipeline

Abstract

Cellular cryo-electron tomography (cryo-ET) enables three-dimensional reconstructions of organelles in their native cellular environment at subnanometer resolution. However, quantifying ultrastructural features of pleomorphic organelles in three dimensions is challenging, as is defining the significance of observed changes induced by specific cellular perturbations. To address this challenge, we established a semiautomated workflow to segment organellar membranes and reconstruct their underlying surface geometry in cryo-ET. To complement this workflow, we developed an open-source suite of ultrastructural quantifications, integrated into a single pipeline called the surface morphometrics pipeline. This pipeline enables rapid modeling of complex membrane structures and allows detailed mapping of inter- and intramembrane spacing, curvedness, and orientation onto reconstructed membrane meshes, highlighting subtle organellar features that are challenging to detect in three dimensions and allowing for statistical comparison across many organelles. To demonstrate the advantages of this approach, we combine cryo-ET with cryo-fluorescence microscopy to correlate bulk mitochondrial network morphology (i.e., elongated versus fragmented) with membrane ultrastructure of individual mitochondria in the presence and absence of endoplasmic reticulum (ER) stress. Using our pipeline, we demonstrate ER stress promotes adaptive remodeling of ultrastructural features of mitochondria including spacing between the inner and outer membranes, local curvedness of the inner membrane, and spacing between mitochondrial cristae. We show that differences in membrane ultrastructure correlate to mitochondrial network morphologies, suggesting that these two remodeling events are coupled. Our pipeline offers opportunities for quantifying changes in membrane ultrastructure on a single-cell level using cryo-ET, opening new opportunities to define changes in ultrastructural features induced by diverse types of cellular perturbations.

In situ architecture of Opa1-dependent mitochondrial cristae remodeling

“…Perpendicular CJs can facilitate cristae stacking, which we noticed in a striking number of l-Opa1* cells. Stacking cristae have been previously observed both under conditions that induce metabolic and endoplasmic reticulum stress upon addition of thapsigargin (Barad et al, 2022 ) and in oma1 -/- cells (Anand et al, 2014 ). We speculate that cristae stacking may have features in common to an intermediate preceding fusion (Fig.…”

Mapping Stress-Responsive Signaling Pathways Induced by Mitochondrial Proteostasis Perturbations

“…18,19 ISR signaling has also been implicated in the regulation of many other aspects of mitochondrial biology including energy metabolism, lipid regulation, and organellar morphology. 18,[20][21][22][23][24] These results highlight a central role for the ISR in regulating mitochondria in response to stress.…”

“…18,19 ISR signaling has also been implicated in the regulation of many other aspects of mitochondrial biology including energy metabolism, lipid regulation, and organellar morphology. 18,[20][21][22][23][24] These results highlight a central role for the ISR in regulating mitochondria in response to stress.Recent work has revealed the molecular mechanism by which mitochondrial stress activates ISR signaling. In response to mitochondrial stress, the stress-sensing mitochondrial protein DELE1 accumulates in…”

MemBrain v2: an end-to-end tool for the analysis of membranes in cryo-electron tomography

“…As we progress, we aim to not only refine MemBrain-seg’s performance but also implement new functionalities that broaden its application, including the automated localization of membrane proteins (MemBrain-pick) and the statistical analysis of their organization (MemBrain-stats). The output segmentations from MemBrain-seg can also be fed into complementary software packages for the analysis of membrane curvature and morphometrics (Barad et al, 2023; Salfer et al, 2020).…”