How to integrate Spatial Omics techniques in your lab/core facility

Session

Session 4 - New Technologies: Recent advances from Acquisition to Analysis

Authors

Sheida Hadji Rasouliha (1), Pascal Lorentz (2), Michael Abanto (2), Ewelina Bartoszek (2), Laurent Guerard (1), Sébastien Herbert (1), Oliver Biehlmaier (1)

Affiliations

1. Imaging Core Facility (IMCF), Biozentrum, University of Basel, Spitalstrasse 41, 4056 Basel
2. Nikon Center for Excellence, Departement Biomedizin, Universitätsspital Basel, Hebelstrasse 20, 4031 Basel

Keywords

spatial omics

multiplexing

core facility

Abstract text

Since being chosen as the 2020 method of the year, spatial biology techniques have seen an ever-increasing popularity in recent years. If you have not done so already, you may be considering implementing such technologies in your lab/core facility. Here, we discuss two approaches in facilities implementing spatial transcriptomics and spatial proteomics at the University of Basel. After in-depth research and comparison of different providers, we have successfully integrated the Vizgen MERSCOPE for spatial transcriptomics and the PhenoCycler (Akoya Biosciences), the 4i technology, and the Hyperion Imaging System (Standard BioTools) for spatial proteomics. We have documented some insights and challenges that facilities may face in this process.

It might be useful to consider the following questions to help you narrow down your options: 1) Are you interested in spatial proteomics, transcriptomics, or both? 2) Are you considering purchasing a commercially available solution, or developing it yourself? 3) Are you interested in a flexible and adaptable solution? The answers to these questions can help you narrow down your available options and find the best suitable method for your biological questions. 

The majority of the commercially available spatial biology systems consist of a standard wide-field microscope equipped with a microfluidic device, and require an in-depth and intensive analysis pipeline. Most of these systems provide a platform for simple analysis and visualization of the acquired data. However, the data analysis support they provide is limited. It is therefore crucial to allocate enough resources to perform tailored post-processing analysis and make sense of the spatial data. Many processing solutions are being developed and published in this rapidly evolving and complex field. Hence, finding and adapting the right pipeline for your specific needs is therefore likely to require strong experience in bio-image analysis and software development. 

Implementing Spatial Omics techniques presents several challenges. These include but are not limited to: the need for a dedicated lab space to conduct RNAse-free experiments, limited flexibility in adapting the acquisition pipeline, the significant cost associated with running a complete acquisition, the requirement for efficient storage solutions and means of data transfer, given that a single experiment can generate a substantial 3-6TB of raw data, and lastly user-friendly, efficient and robust image processing, supported by a high performance computing infrastructure.

In conclusion, offering spatial omics technologies at an imaging core facility presents both challenges and opportunities. It's important to note that there is no one-size-fits-all solution; flexibility and adaptability are key factors in navigating this dynamic field.