A scalable and modular automated pipeline for stitching of large electron microscopy datasets
Abstract
Serial-section electronmicroscopy (ssEM) is themethod of choice for studyingmacroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so called connectomes. In order to use this data, consisting of up to 108 individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP (Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of the Render (27) services used in the volume assembly of the brain of adult Drosophilamelanogaster (30). It achieves high throughput by operating on themeta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP ismodular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous stitching of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex (28; 8) at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.
Data availability
The current manuscript describes is a software infrastructure resource that is being made publicly available. The manuscript is not a data generation manuscript. Nevertheless, one of the datasets used is already publicly available on https://www.microns-explorer.org/cortical-mm3#em-imagery with available imagery and segmentation (https://tinyurl.com/cortical-mm3).Moreover cloud-volume (https://github.com/seung-lab/cloud-volume) can be used to programmatically download EM imagery from either Amazon or Google with the cloud paths described below. The imagery was reconstructed in two portions, referred to internally by their nicknames 'minnie65' and 'minnie35' reflecting their relative portions of the total data. The two portions are aligned across an interruption in sectioning.minnie65:AWS Bucket: precomputed://https://bossdb-open-data.s3.amazonaws.com/iarpa_microns/minnie/minnie65/emGoogle Bucket: precomputed://https://storage.googleapis.com/iarpa_microns/minnie/minnie65/emminnie35:AWS Bucket: precomputed://https://bossdb-open-data.s3.amazonaws.com/iarpa_microns/minnie/minnie35/emGoogle Bucket: precomputed://https://storage.googleapis.com/iarpa_microns/minnie/minnie35/emWe have also made available in Dryad raw data of the remaining datasets https://doi.org/10.5061/dryad.qjq2bvqhr
-
ASAP-TEM-sampleDryad Digital Repository, doi:10.5061/dryad.qjq2bvqhr.
-
MICrONS multi-area datasethttps://doi.org/10.1101/2021.07.28.454025.
Article and author information
Author details
Funding
IARPA (D16PC00004)
- Gayathri Mahalingam
- Russel Torres
- Daniel Kapner
- Tim Fliss
- Shamishtaa Seshamani
- Rob Young
- Samuel Kinn
- JoAnn Buchanan
- Marc M Takeno
- Wenjing Yin
- Daniel J Bumbarger
- R Clay Reid
- Forrest Collman
- Nuno Macarico da Costa
The funders had no role in study design and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All procedures were carried out in accordance with Institutional Animal Care and Use Committee approval at the Allen Institute for Brain Science with protocol numbers 1503, 1801 and 1808
Human subjects: Human surgical specimen was obtained from local hospital in collaboration with local neurosurgeon. The sample collection was approved by the Western Institutional Review Board (Protocol # SNI 0405). Patient provided informed consent and experimental procedures were approved by hospital institute review boards before commencing the study.
Copyright
© 2022, Mahalingam et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,324
- views
-
- 370
- downloads
-
- 22
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Cell Biology
Prostaglandin E2 (PGE2) is an endogenous inhibitor of glucose-stimulated insulin secretion (GSIS) and plays an important role in pancreatic β-cell dysfunction in type 2 diabetes mellitus (T2DM). This study aimed to explore the underlying mechanism by which PGE2 inhibits GSIS. Our results showed that PGE2 inhibited Kv2.2 channels via increasing PKA activity in HEK293T cells overexpressed with Kv2.2 channels. Point mutation analysis demonstrated that S448 residue was responsible for the PKA-dependent modulation of Kv2.2. Furthermore, the inhibitory effect of PGE2 on Kv2.2 was blocked by EP2/4 receptor antagonists, while mimicked by EP2/4 receptor agonists. The immune fluorescence results showed that EP1–4 receptors are expressed in both mouse and human β-cells. In INS-1(832/13) β-cells, PGE2 inhibited voltage-gated potassium currents and electrical activity through EP2/4 receptors and Kv2.2 channels. Knockdown of Kcnb2 reduced the action potential firing frequency and alleviated the inhibition of PGE2 on GSIS in INS-1(832/13) β-cells. PGE2 impaired glucose tolerance in wild-type mice but did not alter glucose tolerance in Kcnb2 knockout mice. Knockout of Kcnb2 reduced electrical activity, GSIS and abrogated the inhibition of PGE2 on GSIS in mouse islets. In conclusion, we have demonstrated that PGE2 inhibits GSIS in pancreatic β-cells through the EP2/4-Kv2.2 signaling pathway. The findings highlight the significant role of Kv2.2 channels in the regulation of β-cell repetitive firing and insulin secretion, and contribute to the understanding of the molecular basis of β-cell dysfunction in diabetes.
-
- Cell Biology
The oviduct is the site of fertilization and preimplantation embryo development in mammals. Evidence suggests that gametes alter oviductal gene expression. To delineate the adaptive interactions between the oviduct and gamete/embryo, we performed a multi-omics characterization of oviductal tissues utilizing bulk RNA-sequencing (RNA-seq), single-cell RNA-sequencing (scRNA-seq), and proteomics collected from distal and proximal at various stages after mating in mice. We observed robust region-specific transcriptional signatures. Specifically, the presence of sperm induces genes involved in pro-inflammatory responses in the proximal region at 0.5 days post-coitus (dpc). Genes involved in inflammatory responses were produced specifically by secretory epithelial cells in the oviduct. At 1.5 and 2.5 dpc, genes involved in pyruvate and glycolysis were enriched in the proximal region, potentially providing metabolic support for developing embryos. Abundant proteins in the oviductal fluid were differentially observed between naturally fertilized and superovulated samples. RNA-seq data were used to identify transcription factors predicted to influence protein abundance in the proteomic data via a novel machine learning model based on transformers of integrating transcriptomics and proteomics data. The transformers identified influential transcription factors and correlated predictive protein expressions in alignment with the in vivo-derived data. Lastly, we found some differences between inflammatory responses in sperm-exposed mouse oviducts compared to hydrosalpinx Fallopian tubes from patients. In conclusion, our multi-omics characterization and subsequent in vivo confirmation of proteins/RNAs indicate that the oviduct is adaptive and responsive to the presence of sperm and embryos in a spatiotemporal manner.