Petabyte-Scale Multi-Morphometry of Single Neurons for Whole Brains.

Shengdian Jiang,Liya Ding,Lijuan Liu,Yimin Wang,Giorgio A Ascoli,Hong-Wei Dong,Michael Hawrylycz,Hanchuan Peng,Zongcai Ruan,Hongkui Zeng

doi:10.1007/s12021-022-09569-4

Abstract

Recent advances in brain imaging allow producing large amounts of 3-D volumetric data from which morphometry data is reconstructed and measured. Fine detailed structural morphometry of individual neurons, including somata, dendrites, axons, and synaptic connectivity based on digitally reconstructed neurons, is essential for cataloging neuron types and their connectivity. To produce quality morphometry at large scale, it is highly desirable but extremely challenging to efficiently handle petabyte-scale high-resolution whole brain imaging database. Here, we developed a multi-level method to produce high quality somatic, dendritic, axonal, and potential synaptic morphometry, which was made possible by utilizing necessary petabyte hardware and software platform to optimize both the data and workflow management. Our method also boosts data sharing and remote collaborative validation. We highlight a petabyte application dataset involving 62 whole mouse brains, from which we identified 50,233 somata of individual neurons, profiled the dendrites of 11,322 neurons, reconstructed the full 3-D morphology of 1,050 neurons including their dendrites and full axons, and detected 1.9 million putative synaptic sites derived from axonal boutons. Analysis and simulation of these data indicate the promise of this approach for modern large-scale morphology applications.

Highlights

Reconstructing the complete 3-D shape or morphology of a neuron, including its dendrites and axons in their entirety, as well as finer structures such as the somata, dendritic spines, and axonal terminal boutons, is recognized as a crucial step to profile the myriad types of neurons in brains[1,2,3,4]
We applied MorphoHub to a petabyte application dataset involving 62 whole mouse brains, and identified 50,233 somata of individual neurons, profiled the dendrites of 11,322 neurons, reconstructed the full 3-D morphology of 1,050 neurons including their dendrites and full axons, and detected 1.9 million putative synaptic sites derived from axonal boutons
MorphoHub is able to streamline the workflow of imaging data management, visualization, reconstruction and annotation, and data sharing (Fig. 1b)

Summary

Introduction

Reconstructing the complete 3-D shape or morphology of a neuron, including its dendrites and axons in their entirety, as well as finer structures such as the somata, dendritic spines, and axonal terminal boutons, is recognized as a crucial step to profile the myriad types of neurons in brains[1,2,3,4]. This technique, which we refer to as Multi-Morphometry, has begun to generate intriguing information and hypotheses about brain circuits at the single-neuron / single-synapse level[5,6,7]. As each voxel is often stored as one or more bytes, the multimorphometry problem arises as a petabyte-computing challenge, and as a paramount task for current bioimage informatics applications and technologies[18,19,20,21]

Methods

Results

Discussion

Conclusion