Spatial Biology Technologies in the Lab of the Future – Technology Networks

Technology drives biological innovation. The continuous innovation of new technology over the past century has led to our continuously improved understanding of biological systems. In the future, research labs will continue to adopt new technologies that make it possible to perform previously impossible experiments: new instruments will make new experiments routine. Since biological systems are comprised of spatially organized cells, each making use of a particular combination of the genes available in its genomic repertoire, this will include technologies that can perform highly multiplexed biomarker analysis across whole tissues with single-cell resolution, giving us direct insight into biology.

Right now, it is common to measure just a few biomarkers at a time across biological tissues (e.g., immuno-fluorescence staining of a slice of brain tissue for a single protein), but most techniques that capture this spatial data do not have high enough bandwidth to capture more than just a few biomarkers such as RNAs or proteins. Yet, within the genome there are tens of thousands of unique genes. Measuring just one gene doesnt provide a clear indication of whats happening and distinguish the variety of cells present. On the other hand, experiments that perform highly multiplexed measurements tend to lose spatial context in doing so.

This deficiency can make it difficult to understand the biological complexities. Fortunately, an up-and-coming field called spatial biology promises to bridge the gap. Researchers in this field today are beginning to use technologies that simultaneously capture the arrangement of many proteins, RNA transcripts, or other biomolecules with single-cell resolution. The data can be used to spatially profile all the cells in a tissue, forming a cell atlas that can reveal novel biological mechanisms and act as a reference map for future work. While technologies today are not yet able to identify every molecule within a biological tissue, future advancements will continue to raise the ceiling of what is possible through spatial biology experiments.

With so much potential, single-cell spatial biology technologies are poised to become an integral aspect of life sciences labs in the future. By producing big, high-quality data, these technologies will provide scientists of the future with a new and more informed lens through which to interpret their research.

Lets consider two ways to approach understanding a complex biological system. Taking a macroscopic biological system as an analog, we could work towards understanding an ecosystem like the rainforest from the bottom up, one plant species at a time, carefully investigating how each plant grows and interacts with the surrounding environment. On the other hand, we could work from the top down by looking at the ecosystem as a whole and then honing into how the ecosystem is constructed from the constituent plant species. In the first approach, although you have thorough understanding of individual components of the system, it is difficult to piece together their complex interactions. In the second, its difficult to understand how each plant species then contributes to the overall ecosystem. Neither approach directly provides the full picture; instead, simultaneously capturing enough information about all organisms in the ecosystem to understand the function of each may yield more direct understanding.

Biological tissue functions like an ecosystem, with distinct cell types intricately interacting to form the whole. Therefore, to fully understand biological tissue, a comprehensive view using spatial biology to profile cells captures detailed molecular data about each individual cell and simultaneously captures information about every cell in the tissue. Cell types can vary across a staggering number of parameters. As with the jungle, scientists would benefit from analyzing many parameters simultaneously to not only identify the cell types but also gain a sense of how individual cells physiology is affected by their surroundings. This kind of data can be obtained through a technique called multiplexing, which allows scientists to capture information about many biological targets or parameters in a single experiment.

Many current spatial technologies incorporate multiplexing strategies, but those designed to detect RNA expression are leading the field by pushing the upper limit of how many unique RNA species can be detected at once. Right now, only the most advanced massively multiplexed techniques can capture hundreds of millions of data points for tens of thousands of biomolecules in a single experiment through a combination of molecular barcoding and combinatorial labeling. In the lab of the future, however, this level of multiplexing will become typical, allowing scientists to take a snapshot of a biological system and use that information to look for patterns, trends and markers to better identify molecular factors that are hallmarks of health and decline.

When it comes to biological systems, the localization and behavior of specific gene transcripts and proteins in individual cell types provides direct insight into how the whole cell and whole organism is functioning. Thats why new techniques to resolve details and reliably detect these molecules of interest are constantly being invented and improved across the world. In the coming years, advances in optics and imaging will give rise to a new generation of technologies that will provide a direct window into cell biology and the dynamics of larger biological systems.

While imaging at single-cell and subcellular resolution is not uncommon in todays laboratory, highly sensitive imaging technologies that can capture massively multiplexed data at single-cell resolution are extremely rare. One current technology that meets these criteria is MERFISH (Multiplexed Error-Resistant Fluorescence In Situ Hybridization), a quantitative technique that can spatially detect hundreds of millions of individual RNA transcripts from hundreds of genes across full tissues in a single instrument run including genes that are expressed at very low levels. While this technology is just beginning to find its way into todays genomics labs, the coming decades may see MERFISH technology becoming a leading tool for running single-cell spatial genomics studies. Additionally, single-cell technologies for detecting protein species and metabolic state will become more high-throughput and achieve higher resolution, rendering them capable of producing their own massively multiplexed data.

Once these technologies are available, labs of the future will likely be equipped with multiple instruments capable of capturing various types of highly multiplexed spatial data, offering a degree of clarity that will usher in a new era of life science research.

There is a growing appreciation for the fact that multidisciplinary research produces robust data. Scientists with diverse specialties, perspectives and approaches all bring something new and valuable to the table. In the lab of the future, instruments that produce massively multiplexed single-cell data will be accessible to researchers of numerous disciplines even those who dont have extensive experience running spatial experiments. Keeping pace with data generation, advancements in data science will make it easier to store and process the massive amount of information generated by these technologies. With ever increasing amounts of data, the role of the data scientist and computational biologist will become more important than ever. Their work towards generating novel ways to analyze massively multiplexed experiments and comparing results across multiple experiments and platforms analyzing RNA, protein and metabolic targets will be instrumental in moving the field forward.

Looking back, it took 13 years to first sequence the human genome; now, one group at Stanford has done the same in just over 5 hours. This was achieved through new technologies and new, advanced laboratory instrumentation. The field of spatial genomics is following the same trajectory. Considering spatial biologys growing role in research and medicine, technologies that can provide single-cell spatial information are poised to rise in prominence in life science labs in future decades.

To keep up, the lab of the future will adopt technologies that can capture more data at higher resolution in a way that is fast and accessible to researchers of varying skill sets. Data science will keep pace, enabling scientists to store and analyze big datasets with ease. By routinely being able to query high-resolution spatial information to shed light on unanswered questions and align results across disciplines, the lab of the future will transform the way scientists think about biology.

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Spatial Biology Technologies in the Lab of the Future - Technology Networks