The sense of curiosity for spatial biology tools reminiscent of the advent of microarrays, next-generation sequencing, or single-cell analysis platforms. For good reason: the findings that are enabled by spatial biology promise to be even more revolutionary for our understanding of biological systems as they were brought about by major technological predecessors.
Spatial biology is now bringing together academic information that was previously difficult or even impossible to access. Eventually, by spatially resolving cells, biomarkers, and other elements of a biological system, we may finally know how their interactions affect drug response, immune responses, and the progression of infectious disease.
While spatial biology is promising, the recent advancement of technology solutions has left many scientists feeling confused or overwhelmed. With so many platforms and services to choose from and more coming to market on a regular basis it may be challenging to identify the best approach for a lab''s current needs as well as what it might require in the future.
Look at some of the earliest applications benefiting from spatial biology techniques and analyze several key issues to help scientists select the method that fits their experimental needs.
Although it seems obvious that the advantages of spatial biology will eventually be applied to all areas of biology, including use in clinical areas such as diagnostics, its development in these early years has focused on several key areas where it might make an immediate difference and have profound implications for human health.
Many early adopters of spatial biology came from the field of cancer research. Immuno-oncology studies provided a remarkable evidence to explain why some cancer patients were cured using immuno-oncology treatment, while others with similar cancers experienced little or no benefit.1-2 The ability to visualize the tumor microenvironment and clarify biology as closely as possible as it functions in vivo has been a major breakthrough for understanding cancer, and its ability to respond to the immune system as well as clinical interventions. The same approach has also revealed new insights
Although the use of spatial biology in cancer has increased the use of this technology elsewhere, other areas are seeing benefits from it. Among other things, scientists have developed spatial knowledge to characterize cell types in both mouse and human brain tissue, generating extensive molecular information.3-4 Spatial biology has also made inroads for infectious disease studies. In the COVID-19 epidemic, for example, researchers used this technique to gauge the molecular pathology of infection and the inflammatory response it triggers.5 Developing biology is another key
With so many spatial biology tools available, the best way to start the selection process is to identify the key requirements for your experimental needs. Once you have reviewed these factors, you will have all of the information you need to start examining vendors and selecting which systems are best suited for your lab.
Because spatial biology platforms employ different approaches to determine location, resolution varies quite a bit from one tool to another. In general, systems that use microscopy or optics to directly observe the tissue sample can produce significantly higher resolution. However, these techniques may be beneficial for your work, but these tools may also help with finding new areas. These methods may also be useful in determining whether or not to take a direct observation.
While sensitivity is critical in all areas of research, certain applications require excellent concentrations, such as the ability to detect as little as one transcript or protein in a cell. If identifying the rarest biomarkers is important for your research, be sure to look for platforms that meet this level of sensitivity. Generally, direct detection techniques, such as fluorescence in situ hybridization (SmFISH), excel in this area, while indirect detection often leads to reduced sensitivity.
Most spatial biology platforms today focus on one type of analyte, typically expressed genes or proteins. However, choosing between spatial transcriptomic tools or spatial proteomic tools is a matter of which analyte type is most appropriate for your research. However, it might be worthwhile to seek out platforms that are designed to be extended to other analytes over time.
In terms of the number of targets that can be analyzed and the number of samples that can be run at once, capacity has varies widely among spatial biology tools. For true discovery science where researchers must consider all proteins or all genes, a platform with the highest level of multiplexing is necessary. However, for most experiments, a longer list of platforms is needed. Consider the possibility to make several samples simultaneously.
Sample processing is quite different across spatial biology platforms. It is important to look for workflows that do not destroy the sample by clearing the tissue or as an unavoidable component of the analysis process if you are using precious samples or may need to re-analyze a particular sample.
Most biology experiments will have significant potential for spatial resolution, as next-generation sequencing data is widespread today. To benefit from your spatial biology project, you should look at how your research may evolve in the future several years and ensure that the platform you choose now can meet your potential goals. This is a valuable strategy to begin your spatial biology journey.
About the author
Jason T. Gammack, the CEO of Resolve Biosciences, a company that offers spatial transcriptomics with Molecular Cartography technology. He has spent more than 25 years in the life sciences industry, and has developed advanced technologies for research areas such as CRISPR gene editing, bioinformatics, and more.
References to the following statements
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2. Finotello F, Eduati F. Multi-omics modeling of the tumor microenvironment: paving the way for advanced immuno-oncology. Front Oncol. 2018;8:430. doi: 10.3389/fonc.2018.00430.
The potential for spatio-disturbing in neuroscience in the era of molecular cell typing. Science.2017;358(6359):64-69. doi:10.1126/science.aan6827.
Nilges B, Strauss S, Geipel A, and Reinecke F, respectively, for a quantitative spatial analysis of 67 genes to evaluate the effects of amyloid pathology in Alzheimers disease (AD). Poster presented at: Emerging Technologies in Single Cell Research (virtual edition); November 19-20, 2020; Leuven, Belgium. https://www.vibconferences.be/sites/default/files/2020-11/Single%20Cell%20Poster
5. Delorey TM, Ziegler CGK, Heimberg G, and others.COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets.Nature. 2021;595(7865):107-113. doi:10.1038/s41586-021-03570-8
DGama PP, Qiu T, Cosacak MI, Rayamajhi D, and others. Cell Rep. 2021;37(1):109775. doi: 10.1016/j.celrep.2021.109775.